3D object detection from point cloud is an important aspect of environmental perception in intelligent systems such as autonomous driving systems and robot systems. However, efficient 3D feature extraction and accurate object localization is challenging for current algorithms. In this paper, we introduce a new single-shot refinement neural network for fast and accurate 3D object detection. Firstly, we simplify the 3D feature extraction network and use single-shot object detector to increase processing speed. Secondly, we exploit self-attention mechanism in main object detection branch to improve object feature representation. Thirdly, an object refinement branch is introduced to produce a finer regression of objects upon the primary estimation from the main detection branch. Both modifications lead to further improvements in performance without additional computational cost. Our approach is tested on KITTI 3D Car detection benchmark and achieves good results in the validation set. The running speed is around 40 frame per second.

Dynamic features are often used for structural damage diagnosis. Besides the features from the modal analysis, some other features describing the wave propagation in the structure are usually concerned, like the wave's intensity, speed, etc. In the data processing of experiment on the pre-stressed concrete (PC) box girders with artificial damages, the max-peak and max-peak-time, two of the basic features of time series will be investigated and analyzed in reconstruction combination matrices to investigate the global information of the update of structural status respectively, which are corresponding to the speed and intensity of the wave propagation separately. In all stages of vibration experiment, curve of distance/2-D correlation coefficient of the max-peak-time and max-peak matrices can have very clear tendencies to demonstrate the global damage happened in the PC box girder, which are better than some modal features in modal analysis using the same original data.

Feature Pyramid Network (FPN) builds a high-level semantic feature pyramid and detects objects of different scales in corresponding pyramid levels. Usually, features within the same pyramid levels have the same weight for subsequent object detection, which ignores the feature requirements of different scale objects. As we know, for most detection networks, it is hard to detect small objects and occluded objects because there is little information to exploit. To solve the above problems, we propose an Enhanced Feature Pyramid Object Detection Network (EFPN), which innovatively constructs an enhanced feature extraction subnet and adaptive parallel detection subnet. Enhanced feature extraction subnet introduces Feature Weight Module (FWM) to enhance pyramid features by weighting the fusion feature map. Adaptive parallel detection subnet introduces Adaptive Context Expansion (ACE) and Parallel Detection Branch (PDB). ACE aims to generate the features of adaptively enlarged object context region and original region. PDB predicts classification and regression results separately with the two features. Experiments showed that EFPN outperforms FPN in detection accuracy on Pascal VOC and KITTI datasets. Furthermore, the performance of EFPN meets the real-time requirements of autonomous driving systems.

In this research, the model of hierarchical structure from universe theory is imported into the general probability system which helps logically and subordinately describing, measuring, and evaluating the hierarchical probabilistic system. To clearly classify the hierarchy, “fayer” is proposed as the unit of hierarchy. Then, discussions on the relationship between hierarchy and system-of-systems and the risks caused by the hierarchy are proposed. This paper divides the problems of hierarchical probability mainly into two classes: the problems of surviving ratio and problems of passing ratio, and also, mixed problems of surviving ratio and passing ratio. Simultaneously, the surviving ratio is called as reliability. System reliability is one marked kind of hierarchical probability for the risk assessment of the hierarchical system. This paper introduces a new reliability system, P-out-of-1 system, which is derived from the K-out-of-N systems in hierarchy. The hierarchical reliability calculation of every fayer of the P-out-of-1 system is different from other fayers. Furthermore, the risk assessment of the hierarchical system for decision making of one maintenance manifests many differences by different descriptions in different fayers, even these descriptions concentrate on the same system.

In this paper, a novel, inexpensive and reliable stair climbing wheelchair mechanism is proposed. Large variation in inclination angle of a traditional wheelchair while moving on steps posses high risk to the rider's safety. A new active Slider-crank mechanism is used to minimize any variation in inclination angle of the wheelchair during climbing up or down on stairs. This, in-turn, reduces the risk of wheelchair toppling on steps. Kinematic model of the proposed wheelchair is developed and MATLAB simulations are performed to inspect the behavior of wheelchair on stairs. In addition, the mechanism is designed in such a way that the rider can sit towards the motion direction, which adds additional safety to the rider. It is envisaged that the novel step climbing wheelchair will enhance the mobility of the elderly people significantly.

Lane detection or road detection is one of the key features of autonomous driving. In computer vision area, it is still a very challenging target since there are various types of road scenarios which require a very high robustness of the algorithm. And considering the rather high speed of the vehicles, high efficiency is also a very important requirement for practicable application of autonomous driving. In this paper, we propose a deep convolution neural network based lane detection method, which consider the lane detection task as a pixel level segmentation of the lane markings. We also propose an automatic training data generating method, which can significantly reduce the effort of the training phase. Experiment proves that our method can achieve high accuracy for various road scenes in real-time.

For a system such as the concrete structure, flow can be the dynamic field to describe the motion, interactions, or both in dynamic or static (Eulerian description) states. Further, various kinds of flow propagate through it from the very start to the end of its lifecycle (Lagrangian description) accompanied by rains, winds, earthquakes, and so forth. Meanwhile, damage may occur inside the structure synchronously, developing from micro- to macro-scale damage, and eventually destroy the structure. This study was conducted to clarify the content of flow which has been implicitly used in the damage detection, and to propose a flow analysis framework based on the combination data space and the theory of dissipative structure theory specifically for nondestructive examination in structural damage detection, which can theoretically standardize the mechanism by which flow characteristics vary, the motion of the structure, or the swarm behavior of substructures in engineering. In this paper, a destructive experiment (static loading experiment) and a following nondestructive experiment (impact hammer experiment) were conducted. According to the experimental data analysis, the changing of flow characteristics shows high sensitivity and efficient precision to distinguish the damage exacerbations in a structure. According to different levels of interaction (intensity) with the structure, the information flow can be divided into two categories: Destructive flow and nondestructive flow. The method used in this research is named as a method of "flow analysis based on flow characteristics", i.e., "FC-based flow analysis".

The diesel engine is a typical multi-input multi-output system with strong couplings, actuator constraints, and fast dynamics. The control objective is to operate the engine to meet driver's speed demand and reduce exhaust emissions of nitrogen oxides during transient processes. Interactions between the actuators and nonlinear behavior of the system make the problem difficult to handle using classical control design methods. Therefore, we propose an offset-free model predictive control system in this paper. It is based on the combined design integrating the disturbance model and the state observer. Furthermore, the method of reduced-order design for H∞ problem is addressed. The proposed approach has low computation requirement and is suitable for implementation in the engine control unit on board. The application of this system in a continuous working process by using dSPACE MicroAutoBox verifies its feasibility and effectiveness for achieving precise reference tracking of engine speed and reducing emissions. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Lane detection or road detection is one of the key features of autonomous driving. By using deep convolutional neural network based semantic segmentation, we can build models with high accuracy and robustness. However, training a pixel-level semantic segmentation needs very fine-labeled training data, which requires large amount of labor. In this paper, we propose an automatic training data generating method, which can significantly reduce the effort of the training phase. Experiments prove that our method can generate high-quality training data for lane segmentation task.

The combination space concept had its origin in the theory of subspace and combinatorics. The combination space may be treated as the space reconstruction through combination, as well as the subspace one. Several new analytical methods are proposed based on combination principles applied to some operations. Under progressing structural damage, simple raw data cannot adequately characterize continuously changing processes and provide early prevention of considerable damage or loss of resistance to hazardous failure. Therefore, the data need to be further processed to find new criteria and factors of damage assessment. Three evaluation methods were experimentally established with the combination space. For the damage assessment and its early prevention, some factors are also proposed such that the combination space method can find the structural change earlier than the original data space. In the case of the the disparity between different conditions and the initial state, this method can contribute to the structure recovery, preventing its failure.

This paper presents a control design method for a nonlinear diesel engine system with strong couplings and actuator constraints. The performance goal is to track the reference of engine speed and reduce exhaust emission of nitrogen oxides (NOx) during transient process. Combustion uncertainties and nonlinear behavior of the system make the problem difficult to handle using classical control design methods. Instead, we propose the extended guaranteed cost control system. The models used for controller design are developed by the state-space format with parameter uncertainties. Exponential stability for the systems is studied. The control laws and observer gains are given from feasible solution of the augmented linear matrix inequality (LMI) to ensure that the cost function value is not more than a specified upper bound for all admissible uncertainties. The proposed approach has low computation requirement and is suitable for implementation in the on board. engine control unit The application of this system in a continuous working process by using dSPACE MicroAutoBox verified its feasibility and effectiveness. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

In this paper, a concept for development of cost effective and reliable stair climbing wheelchair is being proposed. Slider-crank mechanism is being used to compensate for any variation in inclination angle of the wheelchair during ascent or descent on stairs. Controlling wheelchair's inclination angle can reduce risk for the rider as it prevents the wheelchair from toppling. A prototype is being developed to validate proposed mechanism. Proposed mechanism allows rider to view in the direction of progress which adds additional safety to the rider.

In modern traffic systems, accurate video detection is a key challenge for traffic management. Aiming at the problem of public bus detection, this paper proposes a video detection method to well recognize the buses. Firstly, we employ the foreground detection method to find the moving vehicles. And then a training classifier which consists of the improved Adaboost algorithm and Haar-like features is proposed to filter undesired vehicles. Secondly, we use the Canny operator to locate bus characteristics, and further detect the bus with the modified HSV model. This design is tested on the Visual Stadio and OpenCV platform in which load the urban transport data as the samples. The test results show that our detection method has better robustness than both three-frame differential method and hybrid Gaussian method, and the accuracy of detection on the window positioning is more than 93 percent.

Daylight harvesting has great potential of energy saving by utilizing daylight in buildings, and the accuracy of daylight data is essential to realize daylight harvesting in lighting control systems. This paper proposes a modified RBFNN structure for daylight modeling and presents a Real-time Daylight Modeling (RTDM) method, which needs only a few illumination sensors for real-time modeling of daylight. The method uses real-time sensor data to regulate a pre-stored RBFNN (which represents the relationship between position and daylight illuminance in one scenario of daylight) to calculate real-time daylight illuminance inside the room. Simulations in a middle-sized office model show that: 1) RTDM can realize real-time daylight modeling with higher accuracy compared with existing modeling methods
2) lighting control system using RTDM can save considerable energy by daylight harvesting.

Road detection is an important research subject in autonomous driving. Both accuracy and efficiency are very important for road detection used in autonomous driving systems. However, these two properties are usually contradictory under certain calculation resources. In this paper, we make a good compromise between accuracy and efficiency by proposing a dual-stage detecting strategy, which consists of a fast Hough transform based road detection method and a reliable vanishing point based method. A dynamic region of interest (ROI) is proposed as a connector of the two stages. Experiments prove that our method can achieve good performance on both accuracy and efficiency.

In most existing centralized lighting control systems, the lighting control problem (LCP) is reformulated as a constrained minimization problem and solved by linear programming (LP). However, in realworld applications, LCP is actually discrete and non-linear, which means that more accurate algorithm may be applied to achieve improvements in energy saving. In this paper, particle swarm optimization (PSO) is successfully applied for office lighting control and a linear programming guided particle swarm optimization (LPPSO) algorithm is developed to achieve considerable energy saving while satisfying users' lighting preference. Simulations in DIALux office models (one with small number of lamps and one with large number of lamps) are made and analyzed using the proposed control algorithms. Comparison with other widely used methods including LP shows that LPPSO can always achieve higher energy saving than other lighting control methods.

Vanishing point estimation is an important issue for vision based road detection, especially in unstructured roads. However, most of the existing methods suffer from the long calculating time. This paper focuses on improving the efficiency of vanishing point estimation by using a heuristic voting method based on particle swarm optimization (PSO). Experiments prove that with our proposed method, the efficiency of vanishing point estimation is significantly improved with almost no loss in accuracy. Moreover, for sequenced images, this method is further improved and can get even better performance, by making full use of inter-frame information to optimize the performance of PSO.

<p>Pipeline has been widely used as important facilities for the transportation of various industrial raw materials, there will have leakage and broken parts in pipeline, generally, pipeline was set under the ground, it is difficult for human to detect and repair it; In this paper, it introduce a new type pipeline robot with small size, so it can be used in pipeline which has small diameter and running flexibility; At the same time, the robot has been installed with automatic operation system which based on infrared distance sensor, robot can make a judgment of pipeline condition and running automatically, it doesn't need any instructions from operator.</p>

<p>This paper describes a system of obstacle detection used by improved block matching by Guided image filtering based on in-vehicle stereo camera.This obstacle detection system can be used to finding car and person and other things on road aromatically.Thereby, it provide a method for autonomous driving which applicable to the Eco-drive automation.In addition,it can solve the problem of the traffic accident and energy crisis.In the paper,guided image filtering be used to the real-time obstacle detection system for getting the better result in fog application.This system can transform the data of obstacle to the car controller in real-time and the controller can do something to avoid the traffic accident.This paper also describes the experiment and the result in the driving school.</p>

In lighting control systems, accurate data of artificial light (lighting coefficients) are essential for the illumination control accuracy and energy saving efficiency. This research proposes a novel Lambertian-Radial Basis Function Neural Network (L-RBFNN) to realize modeling of both lighting coefficients and the illumination environment for an office. By adding a Lambertian neuron to represent the rough theoretical illuminance distribution of the lamp and modifying RBF neurons to regulate the distribution shape, L-RBFNN successfully solves the instability problem of conventional RBFNN and achieves higher modeling accuracy. Simulations of both single-light modeling and multiple-light modeling are made and compared with other methods such as Lambertian function, cubic spline interpolation and conventional RBFNN. The results prove that: 1) L-RBFNN is a successful modeling method for artificial light with imperceptible modeling error; 2) Compared with other existing methods, L-RBFNN can provide better performance with lower modeling error; 3) The number of training sensors can be reduced to be the same with the number of lamps, thus making the modeling method easier to apply in real-world lighting systems.

In most existing centralized lighting control systems, the lighting control problem (LCP) is reformulated as a constrained minimization problem and solved by linear programming (LP). However, in real-world applications, LCP is actually discrete and non-linear, which means that more accurate algorithm may be applied to achieve improvements in energy saving. In this paper, particle swarm optimization (PSO) is successfully applied for office lighting control and a linear programming guided particle swarm optimization (LPPSO) algorithm is developed to achieve considerable energy saving while satisfying users lighting preference. Simulations in DIALux office models (one with small number of lamps and one with large number of lamps) are made and analyzed using the proposed control algorithms. Comparison with other widely used methods including LP shows that LPPSO can always achieve higher energy saving than other lighting control methods.

Vanishing point estimation is an important issue for vision based road detection, especially in unstructured roads. However, most of the existing methods suffer from the long calculating time. This paper focuses on improving the efficiency of vanishing point estimation by using a heuristic voting method based on particle swarm optimization (PSO). Experiments prove that with our proposed method, the efficiency of vanishing point estimation is significantly improved with almost no loss in accuracy. Moreover, for sequenced images, this method is further improved and can get even better performance, by making full use of inter-frame information to optimize the performance of PSO.

© 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. Recently, attention has been drawn by the local modeling techniques of an idea called "Just-In-Time (JIT) modeling". To apply "JIT modeling" to a large amount of database online, "Large-scale database-based Online modelling (LOM)" has been proposed. LOM is a technique that makes the retrieval of neighboring data more efficient by using stepwise method and quantization. This paper reports the improvement of LOM, a computerized sequential prediction method which uses a local regression model by PLS, on the shaft-furnace direct melting system (melting furnace). The gas temperature prediction of the furnace is done without delay.

Monitoring the health of bridges and diagnosing the damage is vital for government and related institutions in Japan because of frequent earthquakes and the oceanic climate. This paper develops a bridge structure health monitoring system (BSHM), which includes data acquisition and analysis. A two-stage structure damage detection algorithm based on post-nonlinear independent component analysis (ICA) and statistical pattern recognition is proposed to analyze the acquired data and evaluate the health of bridges. First, an improved post-nonlinear ICA algorithm is proposed for denoising, and a data-sample matching based data normalization scheme to reduce the effect of varying environmental and operational condition. Thereafter, fast Fourier transform (FFT) is used to detect the damage. Based on the first stage, a statistical pattern recognition damage detection algorithm, including a new damage sensitive index D-SPR, is proposed to determine the severity and location(s) of damage. In addition to the algorithm, this paper presents several simulations and experiments, including a detection experiment that applies artificial damage to a real bridge to show that our design choices are indeed effective. (c) 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Several data analysis algorithms exist for detecting damages in bridges; however, such algorithms only approximately locate the damaged areas. To increase the accuracy and sensitivity, a new nondestructive, standing-wave, bridge-testing system as well as algorithm is proposed. The proposed system sends 3.8-5.8 GHz modulated sweeping waves to an object, the input and reflected waves form a standing wave, which is used to check and evaluate the state of the object under examination. In comparison with other systems, the proposed system is compact and less expensive, and offers higher sensitivity, higher resolution, and higher accuracy. Simulations and experiments verified its effectiveness. (c) 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

It is important to quantify and prevent mental fatigue in order to forestall absence from work and death from overwork. In this study, we used "Large-scale Data-based Online Modeling (LOM)", one of the local modeling methods based on databases, to reproduce the characteristics of fatigue based on information derived from observation of biomedical signs. The subjects in our study were 10 male university students.After assuming a relaxed seated position for 10 minutes, they performed two repeated sessions of a mental arithmetic task for 30 minutes each session with a 30-minute break. Subjective symptoms of feelings of fatigue score were evaluated on a 10-point scale. We measured several biomedical signs and subjective symptoms of feelings of fatigue score. We propose that it is possible to estimate the degree of acute mental fatigue from biomedical signs using the LOM method. We propose a method for determining the reliability of estimating "degree of fatigue" by distance of neighboring data.

Driving assistant systems with cameras and sensors are expected as a solution of safe driving, congestion prevention and driving load reduction and vehicle to vehicle (V2V) communication systems that utilize wireless technology has been proposed as an auxiliary system of the existing systems. On the other hand, as long with the increasing of the aging rate of society, traffic accident of seniors become a serious problem to be solved. Smarty automatic driving system has been developed to realize a smarty platooning control system based on the automatic driving system for senior drivers. In this research, an embedded communication system is developed for small automatic electric vehicle, and an algorithm to avoid transmit collision is implemented in the developed system. Based on the vehicle to vehicle communication, a platooning control system including vehicle interruptions and separations is successfully designed. Some experiment results of several platooning patterns for small EV represent the effectiveness of the developed system.

Usually we evaluate a certain road detection method from two aspects, the detecting performance and the executing time. Normally there is a compromise between these two criteria. This paper is focused on how to provide a reliable and real-time road detection result for an autonomous vehicle. By using a vanishing point based high reliability detection method for the leading frame and Hough transformation based real-time method for the following frames, we solve the contradiction of the detecting performance and the executing time. In the vanishing point detection, we use Gabor filters to get the texture information of the road and use particle swarm optimization to increase the efficiency.

© 2015 The Society of Instrument and Control Engineers-SICE. In the city of Kitakyushu, a quarter more of people are older than 65 years old. Especially a large proportion of elderly people are living on their own. So how to let old people easily access the communal facilities like hospitals need be attended. Therefore, the bad connection between public transportation and home is need to be solved. Based on the survey result and road situation in Kitakyushu city, a new type small single-seat electrical vehicle (sEV) is studied to provide a solution for elder to easily access the public transportation. In this research, low cost and safe automatic driving electrical vehicle based on limited number of sensors is focused.

In this paper, by using the Android mobile terminal, we make a application of performing autonomous driving control small electric car as the target. Small EV car (COMS) is treated as experimental subjects. This application will help the Elderly, driving poor people, fast, accurate to park the car and call the car coming for users easily. Moreover, it is also considered that it becomes possible to inform the vehicle information for users.
For this study, itintroduce that how making the communication system with the car. Also using Map management tool "Mapinfo" for design the path for a small electric vehicle, for example the path to/from parking place. On top of that, we seek a control method to safely autonomous driving on the basis of the data around the vehicle. Also for other cars and pedestrians traveling the parking lot, we aim to correspond to the safety and smooth.

This paper represents an illumination modeling method for lighting control which can model the illumination distribution inside office buildings. The algorithm uses data from the illumination sensors to train Radial Basis Function Neural Networks (RBFNN) which can be used to calculate 1) the illuminance contribution from each luminaire to different positions in the office 2) the natural illuminance distribution inside the office. This method can be used to provide detailed illumination contribution from both artificial and natural light sources for lighting control algorithms by using small amount of sensors. Simulations with DIALux are made to prove the feasibility and accuracy of the modeling method.

© 2014 SICE. With the aging driver increasing, the smarty automatic driving system needs to be proposed. We analyze the smarty automatic driving system to propose a smarty platooning control system based on the automatic driving system for elderly person. Firstly, the small automatic electric vehicle and the control devices are explained. Then we introduce the Wireless communication method in our system. Based on the communication between the vehicles, we design related control method and the path recognize method for platooning control system using in urban road. At last we do some experiments to verify the effectiveness of our system.

This paper represents an illumination modeling method for lighting control which can model the illumination distribution inside office buildings. The algorithm uses data from the illumination sensors to train Radial Basis Function Neural Networks (RBFNN) which can be used to calculate 1) the illuminance contribution from each luminaire to different positions in the office 2) the natural illuminance distribution inside the office. This method can be used to provide detailed illumination contribution from both artificial and natural light sources for lighting control algorithms by using small amount of sensors. Simulations with DIALux are made to prove the feasibility and accuracy of the modeling method.

This paper describes a novel clustering routing and coverage algorithm, referred as Brief Artificial Fish-School Optimization Clustering Routing and Coverage (BAFSOCRC), for a wireless sensor network. Based on the detailed analysis of the cluster head selection algorithm and the deficiencies of LEACH algorithm, I propose an algorithm based on Brief Artificial Fish-School Optimization (BAFSO). The key point of the clustering routing algorithm is applying BAFSO algorithm. This algorithm can be divided into two parts: The clustering routing algorithm of WSN based on BAFSO (BAFSOCR) and the coverage of WSN based on BAFSO (BAFSOC). In the BAFSOCR, it can achieve the balance of the network energy consumption, improve the energy efficiency and prolong life cycle of the whole network. In the BAFSOC, it can achieve the distribution optimization in a higher speed with a lower cost, and increase the efficiency of the algorithm.

Currently, problem of battery life is restricting the development of almost all of the wireless sensor networks, especially in structural health monitoring. This paper proposes and proves the possibility of a continuous battery life solution for wireless sensor networks using wireless power transfer. Different from current mainstream methods using resonance coils, this research is using 950MHz electric waves for power transfer. Experiment results shows that this power transfer system is able to support sensor modules operation at 10m distance under current structure monitoring plan. Also, this system is able to recharge batteries at 16m distance maximum.

The fuel efficiency and emission reductions are the two consistent drivers for diesel engine development. Although many control devices mounted in diesel engine and in addition to the development of individual emission control methods, optimization techniques are required to utilize these methods in finding optimal engine operating conditions efficiently. This research was focused on the minimization of nitrogen oxides (NOx) emission and soot emission, as well as improving brake specific fuel consumption (BSFC) and power in a single cylinder diesel engine, which can be modeled as a multi-objective optimization problem. Many approaches have been applied to multi-objective optimization problems. In recent years, particle swarm optimization (PSO) method has been successfully applied to different areas since its advent. It has been demonstrated that PSO is an effective method for optimization problem. © 2012 IEEE.

The purpose of the automotive driving system is to understand the surroundings of the vehicle, evaluate potential risks, and help the driver to behave correctly, safely and efficiently. And for the purpose, we need the precondition that can accurately and precisely estimate the vehicle state. One key challenge is to design a data fusion method to fuse information from multiple sensors used in the automotive driving system. This paper introduces the automotive driving system with Robocar and also presents the method of adaptive particle filter to fuse different data from different sensors to estimate the vehicle state even in noise environment. We are trying to fuse data from different sensors in a probabilistic way. A particle filter with joint observation model will be adopted to fuse different observations according to accuracy and reliability of the corresponding sensor.

This article is aimed to introduce a new hybrid time offset synchronization (sync) scheme for Wireless Sensor Network (WSN) for Bridge Health Diagnosis System (BHDS), which is wildly used as a main monitoring method in japan for collection of vibration information to diagnose the health condition of the bridge affected by the frequent nature disasters around whole country. It is publicly known that the collection and communication of such a large-scale distributed WSN requires a strict time sync scheme with little average sync error as well as max error, while taking energy-awareness and sync latency into consideration. In some cases, the traditional sync scheme such like TPSN or RBS fail to fulfill the needs. Therefore a hybrid scheme between the TPSN and direct-adjustment ensuring the sync accuracy without consuming more power has been studied in this paper. Generally speaking, the partial TPSN time offset scheme studied in this paper is a scheme to choose No. k of the children nodes to sync according to TPSN protocol and calculate the time offset for rest of nodes by using the data from both kind of nodes (the No. k's and the rest's). The mathematical model has been introduced and the simulator also has been developed to calculate the optimized k. By choosing different k, different average error and power consumption will occur hence to fulfill the different needs for BHDS. At last, the idea has been evaluated and experimented to make sure that it can, especially in BHDS, meet the needs for WSN.

Due to the oceanic climate and frequent earthquakes in Japan, bridge health diagnosis is a problem of greater complexity. In bridge diagnosis system, we develop a wireless sensor network to sample and gather the vibration data of bridge. Time synchronization is a crucial component for the wireless sensor network (WSN), because large populations of sensor nodes will collaborate in order to complete the measuring data at the same time, data gathering, data fusion and localization. In the wireless sensor network with large scale of energy limited nodes, multi-hop time synchronization is necessarily applied. To solve above mentioned problem, some protocols such as RBS, TSPN FTPS etc. are proposed. However most of the algorithms mainly focus on the precision of synchronization. In fact energy efficiency is also a challenge in a resource-limited WSN. In this paper an improved time synchronization scheme is proposed with the purpose of reducing energy consumption and lengthening whole WSN' life. Performance analyses, simulations and realization in node hardware of WSN are also presented. © 2012 The Institute of Electrical Engineers of Japan.

This paper describes the automatic driving control system for elderly person using low cost sensors. Firstly, the small automatic electric vehicle and the control devices are explained. Next, the path tracking method is explained. And in order to realize path tracking, GPS and IMU are used to calculate the current position and orientation separately in real time for steering angle control. By the fusion method of Ultrasonic sensors, CCD stereo camera, GPS and IMU, the automatic driving system and the obstacle avoiding system is realized.
Some test runs of automatic driving system of a small vehicle was done to verify the fusion and control methods in the outdoor experiments.

This paper introduced a wireless power transfer system controlled by a microchip board. Recently, wireless sensor network for structure health monitoring has been developed. However, battery consumption became an important problem, especially in structure health monitoring system, since maintenance costs huge human resources. Therefore, a wireless power transfer system is developed to supply sensor networks. This system works at 950MHz band, and the transmission rate is about -8dBm (about 140 mu W) at 10m's distance. After boost converter, power efficiency became 33%, which means there is less than 50 mu W can be stored into batteries. Moreover, a microchip board is used in this system to control and coordinate the whole transmission system, including the wireless modules. Comparing with power consumption of current microchip, 50 mu W is not enough. Therefore, power consumption control method is developed in this system.

Bridges are essential links in any surface transportation network. A damage to an important bridge may result in enduring economic loss due to partial or complete closure of the route in addition to the cost of repair or replacement. Also, survival of bridges are of utmost importance in the aftermath of a devastating earthquake in order to facilitate rescue operations. Therefore, it has become customary to carry out a critical assessment of safety and integrity of bridges in regular intervals as well as immediately after disastrous events such as an earthquake. The prevalent practice of bridge inspection requires checking of each and every component, which is experience-based, highly time consuming and an expensive process, often enforcing disruption in traffic flow. As a result, the wireless sensor-based inspection methodology is gaining popularity in recent times. This paper a presents a study to show the efficiency of a multi-hopped wireless sensor network (WSN) for remote health monitoring of bridge. Various vibration-based and feature-based output-only damage detection techniques are applied to show their efficacy in terms of determining the location and severity of damages using the data collected from the bridge under damaged and undamaged conditions. © 2012 IFAC.

Recently, attention has been drawn by the local modeling techniques of a idea called "Just-In-Time (JIT) modeling". To apply "JIT modeling" to a large amount of database online, "Large-scale database-based Online modeling (LOM)" has been proposed LOM is such a technique that makes the retrieval of neighboring data more efficient by using stepwise method and quantization. This paper reports the application of LOM, a computerized sequential prediction method which uses a local regression model, on the shaft-furnace direct melting system (melting furnace) to systematically support and enhance the operation procedure compared to conventional methods of relying only human skills and experiences. © 2012 IFAC.

With the problem of environmental pollution and energy depletion in recent years, a control technology which improves the performance of automobile engine has been demanded. This paper presents a method for construction of response surface model and a control parameter optimization method for automobile diesel engine in order to develop a model-based control system and the early development technique based on the model. The proposed method for construction of response surface model is able to efficiently-develop the response surface model that describes the multiple control parameters in relation to the characteristic value such as fuel consumption and emission. The proposed control parameter optimization method is able to quickly and efficiently calculate optimal control parameters to optimize evaluation item such as fuel consumption and emission based on the model.

With the problem of environmental pollution and energy depletion in recent years, a control technology which improves the performance of automobile engine has been demanded. This paper presents a method for construction of response surface model and a control parameter optimization method for automobile diesel engine in order to develop a model-based control system and the early development technique based on the model. The proposed method for construction of response surface model is able to efficiently-develop the response surface model that describes the multiple control parameters in relation to the characteristic value such as fuel consumption and emission. The proposed control parameter optimization method is able to quickly and efficiently calculate optimal control parameters to optimize evaluation item such as fuel consumption and emission based on the model.

In order to reduce the amount of wasted energy in office lighting and provide a major contribution to lowering overall energy consumption, we are developing a new energy saving system for office lighting by using adjustable lamp, Wireless Sensor Network (WSN) and Particle Swarm Optimization (PSO). The illumination sensors collect and send the data to the control module. After the PSO (Particle Swarm Optimization) process, the module finally sets the power of the lamps according to the PSO result. In this paper we extent a prototype system which consists of one WSN control module, four fluorescent lamps with dimming capacity and three illumination sensors to a system which consists of one control module, sixteen lamps and up to sixteen sensors. We also make improvements on the PSO algorithm for more complicated situations. After real experiments in a middle-sized meeting room, it was proved that the system can successfully control the lights, and save considerable energy. © 2011 SICE.

This paper describes the development of a High Speed Calculation Diesel Combustion Model that predicts combustion-related behaviors of diesel engines from passenger cars. Its output is dependent on the engine's operating parameters and on input from on-board pressure and temperature sensors. The model was found to be capable of predicting the engine's in-cylinder pressure, rate of heat release, and NOx emissions with a high degree of accuracy under a wide range of operating conditions at a reasonable computational cost. The construction of this model represents an important preliminary step towards the development of an integrated Model Based Control system for controlling combustion in diesel engines used in passenger cars. © Copyright 2011 Society of Automotive Engineers of Japan, Inc. and SAE International.

Model based control design is an important method for optimizing engine operating conditions so as to simultaneously improve engines' thermal efficiency and emission profiles. Modeling of intake system that includes an intake throttle valve, an EGR valve and a variable geometry turbocharger was constructed based on conservation laws combined with maps. Calculated results were examined the predictive accuracy of fresh charge mass flow, EGR rate and boost pressure. © Copyright 2011 Society of Automotive Engineers of Japan, Inc. and SAE International.

With the problem of environmental pollution and energy depletion in recent years, a control technology which improves the performance of automobile engine has been demanded. This paper presents a method for construction of response surface model and a control parameter optimization method for automobile diesel enginein order to develop a model-based control system and the early development technique based on the model. The proposed method for construction of response surface model is able to efficiently-develop the response surface model that describes the multiple control parameters in relation to the characteristic value such as fuel consumption and emission. The proposed control parameter optimization method is able to quickly and efficiently calculate optimal control parameters to optimize evaluation item such as fuel consumption and emission based on the model.

Model based control is an important technology to optimize engine operating conditions for improvements in thermal efficiency and emissions simultaneously. Modeling of intake system that includes an intake throttle valve, an EGR valve and a variable geometry turbocharger was constructed based on conservation laws combined with maps. Calculated results were examined the predictive accuracy of fresh charge mass flow, EGR ratio and boost pressure.

The purpose of this study is to develop a wireless networked lighting system for office buildings, which can reduce the energy consumption while meeting users' lighting preferences. By using particle swarm optimization, the system is able to optimize the dimming ratio of luminaires according to the real time natural illumination and occupancy condition. In this paper we make a prototype system and test the feasibility and efficiency of the system. The prototype consists of one wireless control module, three illumination sensors and four fluorescent lamps with dimming capacity. The illumination sensors collect and send the data to the control module. After the process of PSO (Particle Swarm Optimization), the module finally sets the power of the lamps according to the PSO result. After real experiments in a certain designed office, it was proved that the system can successfully control the illuminations, and can save considerable energy.© 2011 The Institute of Electrical Engineers of Japan.

Platooning technology is becoming a future task which suggests as a way of reducing carbon dioxide emissions and realizing safe driving at a high speed velocity. This paper describes a few control methods for vehicle-platooning. The conventional control method improved fuel consumption by shortening the distance between vehicles. By contrast, the method we proposed improves it by controlling the velocity at the time of acceleration gently. The velocity is controlled by generating the desired value of inter-vehicular distance cones ponding to the leading vehicle velocity. Another method which is planned to realize a highly efficient arterial traffic distribution system includes reducing aerodynamic drag by minimizing the distance between vehicles to allow drafting. In this paper, the two degrees-of-freedom control system is applied for it. These proposed met hods were evaluated by simulation and some experiments.

Recently many drain pipes used for transportation of water and gas at the plants have become old. These pipes have many defects caused by corrosion and cracking and they cause serious accidents because of leakage, fire and blasts. Therefore, to forestall these accidents, we believe it is important to do drain pipe inspections and maintenance using drain pipe inspection robots.
'Rotating probe' and 'Image processing' are used for the method of inspecting pipe in this research. Then, the development of the Pipe Inspection Robot measures the irregularity and the form of the defect in pipe. Therefore, this robot using the rotating probe of this touch sensor is profitable.

Recently, attention has been drawn to the local modeling techniques of a new idea called "Just-In-Time (JIT) modeling". To apply "JIT modeling" to a large amount of database online, "Large-scale database-based Online Modeling (LOM)" has been proposed. LOM is a technique that makes the retrieval of neighboring data more efficient by using both "stepwise selection" and quantization. In order to predict the long-term state of the plant without using future data of manipulated variables, an Extended Sequential Prediction method of LOM (ESP-LOM) has been proposed. In this paper, the LOM and the ESP-LOM are introduced. © 2011 The Institute of Electrical Engineers of Japan.

In Japan, Bridge is an important part of public transportation infrastructures. As a result, the monitoring of bridge health is accordingly vital important for the government and related institutions. In bridge diagnoses system, we develop a wireless sensor network to measure and gather the vibration data of bridge. The problem is: in past field bridge diagnosis experiment, node failure and data packets loss always occurred in the WSN. Furthermore, when we deploy all the nodes of WSN to bridge in the first time, it is always difficult to set the location of nodes in order to ensure the quality of link is extremely reliable. In order to solve above mentioned problem we propose a distributed data aggregation active monitoring method and a distributed localized decision monitoring method. Based on the two methods we build a self-health monitoring system for WSN: DLDMS (Distributed Localized Decision Monitoring System). We apply this system to the field experiments at Kitakyushu city in Japan and successfully obtain the health status of WSN. © 2011 IEEE.

The main object of this paper is to design and realize a real-time autonomous driving system for intelligent vehicles by using the map information. By appointing the destination, the intelligent vehicle selects the optimal route in real-time, and reaches the specific destination without ordering the course of the travel. In addition, a simulation study which contains a number of map instances was made to confirm the algorithm. Finally, the performance and accuracy of the proposed system was verified by real-time experiment result. © 2011 IEEE.

This paper introduces a multi-hopped wireless sensor network for remote bridge health monitoring, including system architecture, transmission protocol, data acquiring and processing. This system based on detecting the three-dimension vibration or acceleration data of the bridge, which data is caused by external impacts such as a car or a truck. Comparing with traditional monitoring systems, this bridge health monitoring system has advantages in human-free, long-life, and real-time responses. Additionally, to compare data of a damaged bridge and a healthy one, an experiment of making artificial damage to a bridge is carried out with consent of related departments. Moreover, this system can be applied in any form of bridges. In the future, it is even expected to be applied in other kind of buildings more than bridges. © 2011 The Institute of Electrical Engineers of Japan.

Recently, attention has been drawn by the local modeling techniques of a new idea called "Just-In-Time (JIT) modeling" or "Lazy Learning". To apply "JIT modeling" to a large amount of database online, "Large-scale database-based Online Modeling (LOM)" has been proposed. LOM is such a technique that makes the retrieval of "neighboring" data more efficient by using "stepwise selection" and quantization. This paper reports an Extended Sequential Prediction (ESP) method of LOM with the local regression model. The ESP method is able to predict process variables over a long period by modeling the operator and the plant based on LOM, the approach is to repeat a process that predicts the process variables of the next step by using the predicted variables of the previous step. The method is applied to a dynamic industrial furnace with several deeply-intertwined physical phenomena; practical effectiveness of the method is verified. As a result, the method has predicted the process variables with satisfactory accuracy. © 2010 SICE.

A method for the analysis of fatigue parameters has been rarely researched in VDT operation. Up to now, fatigue was evaluated by changing of biological information. If signals regarding fatigue are detected, fatigue can be measured. The purpose of this study was an experiment and analysis method to extract parameters related to fatigue from the biological information during VDT operation using Independent Component Analysis (ICA). The experiment had I I subjects, and examined light-load and heavyload VDT operation. Measurement items were amount of work, number of mistakes, subjective symptoms, surface skin temperature (forehead and apex nasi), heart rate, skin blood flow of forearm, and respiratory rate. In the heavyload operation group, number of mistakes and subjective symptom score were increased. Two-factor ANOVA was used for analysis. The result of number of mistakes was confirmed for the heavy load. After the moving averages of waveform were calculated, we extracted independent components by using ICA. The results of ICA suggest that the independent components increase according to accumulation of fatigue. Thus, the independent components would be a possible parameter of fatigue. However, further experiments should continue in order to obtain conclusive findings of our research. (C) 2010 Wiley Periodicals, Inc. Electron Comm Jpn, 93(9): 47-57, 2010; Published online in Wiley Online Library (wileyonlinelibrai-y.com). DOI 10.1002/ecj.10033

In order to cope with energy crisis, and emission pollution, an engine with lower pollution burden is appreciated. In this research, diesel engine optimization objectives are formulized on the basis of experiment data. The reduction of brake specific fuel consumption (BSFC), exhaust gas emission, and soot using particle swarm optimization (PSO) and multi-objective particle swarm optimization (MOPSO) is proposed. Optimal results of PSO are obtained and validated by engine test bench. In this paper, MOPSO with three optimization objectives are presented and simulated, these optimal results of MOPSO would also be tested in experiment in the future.

In order to reduce the amount of wasted energy in office lighting and provide a major contribution to lowering overall energy consumption, we are developing a new energy saving system for office lighting by using adjustable lamp, ZigBee Wireless Sensor Network (WSN) and Particle Swarm Optimization (PSO). In this paper we make a prototype system which consists of one ZigBee control module, four fluorescent lamps with dimming capacity and three illumination sensors. The illumination sensors collect and send the data to the control module. After the PSO (Particle Swarm Optimization) process, the module finally sets the power of the lamps according to the PSO result. After real experiments in both sunny day and cloudy dayin a small-size office, it was proved that the system can successfully control the lights, and save considerable energy.

In this paper, an optimal driving control system based on model predictive control (MPC) is developed for the purpose of processing more surrounding information which is essential for improving the current intelligent driving assistance and further dealing with traffic issues caused by automobiles. The proposed system provides a method of calculating a desirable driving path based on surrounding traffic environments. The performance of this system is evaluated through simulations which are carried out with introduction of surrounding information such as traffic jams, traffic signal changes, and fuel consumption. Simulation results reveal that the proposed system as a driving assist system has a potential of finding optimal driving paths for drivers.

Platooning technology is becoming a future task which suggests as way of reducing carbon dioxide emissions and realizing safe driving at a high velocity. This paper presents a unique optimal control method of velocity and distance for platooning using model predictive control. The vehicle-platoon&apos;s distance model which is based on the road condition and weather condition is used in this rigorous approach of deriving the control input. A combination of Continuation and Generalized Minimum Residual Methods is used to optimize the sequence of vehicle control commands which is required in the prediction horizon aiming at minimizing the relative velocity and keeping safe distance of the vehicle-platoon while the vehicle-platoon is on a high velocity driving.

Pipe lines of any material need to be inspected after a certain number of years. Therefore, it is necessary to develop a flexible pipe inspection robot using a wireless communication system. In this research, a wireless communication system is tested, and it is verified that the system can transmit image information steadily at a high speed. On the basis of this wireless communication system, a new pipe inspection robot for drain pipes is developed. With this new system, the movement of the robot can be controlled, defects or other problems inside a pipe can be inspected, and an image of the inside of the pipe can also be transmitted in real time. © 2009 International Symposium on Artificial Life and Robotics (ISAROB).

In order to apply an engine intake air system model to engine control, it is necessary to calculate the intake air system model quickly and accurately under constraints of computational performance. Therefore, a study has been made on a method for calculating the intake air system model implemented by an analog LSI at short times. However, the problem is to include the model error in the intake air system model based on the analog LSI of present state. This paper reports a compensation of the intake air system model with error by Extended Kalman Filter (EKF).A basic model that reproduces model errors of analog LSI model is built, and a compensator based on EKF is designed. As a result, it is confirmed that the compensator reduces the model errors by half. Moreover, this paper reports the numeric solution in order to reduce the hunting phenomenon of the engine intake air system model. © 2009 SICE.

As a basis of an intelligent driving assist system, an on-line calculation method calculating a desirable driving path based on information and prediction of surrounding traffic environment is developed. The problem is how to use information of traffic jam and signal. This paper reports an automobile optimal driving control system using information of traffic jam and signal based on the model prediction control to support drivers. Moreover, physical models for information of traffic jam and signal are constructed. © 2009 SICE.

This paper focuses on maintaining a bridge s safety by developing a daily management system. And the purpose of this study is the development of the health monitoring system. It supports the maintenance by using sensor network and Independent Component Analysis (ICA) when there are some troubles in a bridge. The result of this study brings out the vibration behavior of the overall structure in a bridge. This vibration is caused by the external force such as wind pressure, and running vehicle. The character frequency was extracted from the analysis result using ICA and Spectral Analysis.The actual sensor network system has been developed and the performance was demonstrated. ©ISAROB 2008.

A method for the analysis of fatigue parameters has been rarely researched in VDT operation. Up to now, fatigue was evaluated by changing of biological information. If signals regarding fatigue are detected, fatigue can be measured. The purpose of this study proposed experiment and analysis method to extract parameters related to fatigue from the biological information during VDT operation using the Independent Component Analysis (ICA). An experiment had 11 subjects. As for the experiment were light loaded VDT operation and heavy loaded VDT operation. A measurement item were amount of work, a mistake number, subjective symptom, surface skin temperature (forehead and apex nasi), heart rate, skin blood flow of forearm and respiratory rate. In the heavy loaded operation group, mistake number and subjective symptom score were increased to compare with the other. And Two-factor ANOVA was used for analysis. The result of mistake number was confirmed that heavy loaded. After the moving averages of waveshape were calculated, it was made to extract independent components by using the ICA. The results of the ICA suggest that the independent components increase according to accumulation of fatigue. Thus, the independent components would be a possible parameter of fatigue. However, further experiments should continue in order to obtain the conclusive finding of our research.

The aim of this paper is the development of a bridge diagnosis system for daily bridge maintenance. The system includes the technology of wireless sensor network, signal processing, and structure analysis of a bridge. We collect the vibration data caused by external force such as wind pressure, running vehicles and etc through wireless sensor network and then use independent component analysis (ICA) and spectral analysis to analyze the data for extracting character frequency. The diagnosis technology is developed to understand the phenomena like deterioration and corrosion of a bridge through the measurement result. So the diagnosis system can evaluate the health condition of a bridge and conduct a comprehensive deliberation on repair and reinforcement work. We apply this diagnosis system to field experiments at Kokura, Kitakyushu city in Japan and successfully extract the character frequency of a bridge. © 2008 SICE.

This paper presents an introduction of engine control education system. The education system is composed of PC hardware, high-speed arithmetic processing board, ECU, and engine test bench. This system can realize following functions: familiarize people with gasoline engine properties, do engine control simulation, design engine control system, and realize engine real-time simulation. In this paper, we designed basic engine control system and got simulation results, developed real-time simulation system, and realized real-time simulation by adjusting PID parameters. Further more, we can design new control system by improving the basic ones. When we connect engine control model to engine test bench and ECU, this system can realize virtual engine real-time simulation. © 2008 SICE.

As an aging society is a tendency in the future, the production of disposable diaper has been increased year by year. It is believed that the problem of the disposal of diapers will be becoming a great problem in the future. For waste reduction, a new disposal technique for the used disposable diapers by the pair conditions of microorganisms, cryptomeria chips and ALGA is purposed. In this paper, we showed that microorganisms living with the cryptomeria chips have effect on the decomposition of the disposable diapers. A disposal process model of disposable diapers is built according to the results of experiments. © 2006 IEEE.

In this research, we studied the wireless radio communication system which can transfer stable and at high speed. And we developed some prototype robot systems and made some tests. In this system, we could make control the moving robot and inspect the defects from inside of steel pipe or ceramic pipe. We could transfer the image information of inside pipe with the defect in real time.

With the advent of throw-away products, the final disposal of such products has become a problem to which considerable attention need be given. For example, the investigation in Japan in 2004 shows the fact that the quantity of production of the diaper increases from 3000 million in 2003 to 3,700 million in 2008[1]. Therefore, in this paper, a new treatment technique for decomposing disposable diapers by microorganisms with cryptomeria chips is proposed. In addition, because a small size disposal system with a temperature controller is expected, the disposal processes of disposable diapers are modeled. The simulations with difference temperature conditions are performed using the models. And then, the relationship between temperature and decomposition rate become clear. © ICROS.

A method for the analysis of fatigue parameters has been rarely researched in VDT operation. Up to now, fatigue was evaluated by changing of biological information. If signals regarding fatigue are detected, fatigue can be measured. This study proposes an experiment and analysis method to extract parameters related to fatigue from the biological information during VDT operation using the Independent Component Analysis (ICA). An experiment had 11 subjects. As for the experiment were light loaded VDT operation and heavy loaded VDT operation. A measurement item were amount of work, a mistake number, subjective symptom surface skin temperature (forehead and apex nasi), heart rate, skin blood flow of forearm and respiratory rate. In the heavy loaded operation group, mistake number and subjective symptom score were increased to compare with the other. And Two-factor ANOVA was used for analysis. The result of mistake number was confirmed that heavy loaded. After the moving averages of waveshapes were calculated, it was made to extract independent components by using the ICA. The results of the ICA suggest that the independent components increase according to accumulation of fatigue. Thus, the independent components would be a possible parameter of fatigue.

This paper reports a sequential prediction system of "Large scale database-based Online Modeling (LOM)". The sequential prediction system predicts time-series process variables repeating processing that predicts process variables of next step by using the predicted process variables of previous step and prepared manipulated variables. Furthermore, the system is applied to the industrial reactor; Practical effectiveness of the system is verified. As the result, the system has predicted the process variables with satisfactory accuracy. The practical effectiveness has been confirmed.

In this paper, we build the intake manifold model of an engine with a turbo charger and develop a high speed calculation algorithm for model-based predictive control in real time. The model is built according to the analysis of its thermodynamic and hydrodynamic characteristics and the sampled experiment data. The model equations are presented as a set of differential equations with condition selection (bifurcation) on the right hand side. The switching surface is divided into two parts, sliding and crossing. The sliding mode on the switching surface is analyzed in detail, and a calculation algorithm is proposed to remove illegal crossing caused by the numerical errors on this surface. Also, the control formula and the condition guiding the bifurcation between these two parts are demonstrated. Using this method, we can solve this model over the entire region of input throttle angles, the stability is greatly increased, and the calculation time is greatly reduced for real time control systems.

In this paper we propose a method of simulation and verification for a class of hybrid system. This kind of dynamic system integrates discrete and continuous parts according to the external control commands and internal evolution rules. In this case the system has character of chatting (oscillation or bifurcation) between the intersections of different regions. The switching surface is divided into two parts of sliding and crossing. The sliding mode on the switching surface is analyzed in detail; the conditions guiding the bifurcation between these two parts and the control formula to crossing or sliding are demonstrated. Furthermore the calculation algorithm is proposed to remove illegal crossing caused by the errors on this surface. Finally, we illustrate a successful application of solving an intake manifold model of an automobile engine with turbo charger for real time predictive control, in which the stability is improved greatly and the trajectory oscillation is reduced.

This paper reports a Java-based operation support system integrated with a "Large scale database Online Modeling (LOM)" and a blast furnace simulator. The system predicts blast furnace operation by combining the partial unsteady simulator of the physical modeling method and LOM of the local modeling method and supports the operation. To construct the system, the Java-based partial unsteady blast furnace simulator is developed.

A method for analysis of fatigue signal was rarely researched in VDT input work. Then to search the fatigue signal, experiments on the work load of the VDT input work are performed under a constant environment. The fatigue signal in vital reaction is obtained.

This paper explores the development of a real time intelligent surveillance system using the technology of pattern recognition based on independent component analysis (ICA) and a novel matching method as a reaction to perceptions of insecurity in sensitive spaces. An array of motion images of people are caught by micro digital cameras on board and transferred through wireless network to FPGA board. The feature points of the shot image and the image in database are extracted out using ICA algorithm in embedded PowerPC. The most similar images are picked up from the image database, which is classified to different clusters, and the potential insecurity level of invaders is detected. Furthermore the respective locations are connected by wireless network. The system of hardware and software co-design is implemented on Xilinx FPGA with the performance of high efficiency, low power consumption and easy integration with other devices.

In this paper, we explore a novel method for building a virtual vehicle system, integrating pure software simulation and Hardware In Loop (HIL) simulation, which is constructed based on a distributed network of Controller Area Network (CAN) and TCP/IP. Firstly, the dynamic vehicle model is developed in the platform of software simulation, used to design and verify the response of ABS control logic. Secondly, in the HIL simulation the model equations are converted to a stand-alone program of C++ on main computer and integrated with ABS controller, real vehicle devices and components, generate a real vehicle environment based on CAN bus to verify the control performance of ABS in real time. Database, graphic and data processing systems are integrated by cross-platform programming technology on assistant computer connected by ethernet. The analysis and validation of developed control logic for ABS can be performed successfully on this platform. Copyright © 2006 Inderscience Enterprises Ltd.

As an aging society is a tendency in the future, the production of disposable diaper has been increased year by year. It is believed that the problem of the disposal of diapers will be becoming a great problem in the future. For waste reduction, a new disposal technique for the used disposable diapers by the pair conditions of microorganisms, cryptomeria chips and ALGA is purposed. In this paper, we showed that cryptomeria chips have effect microorganisms living with the the decomposition of the disposable diapers. A disposal process model of disposable diapers is built according to the results of experiments.

The intake manifold model of turbo charge engine is constructed and a high speed calculation algorithm is developed for model based predictive control in real time. The model is built from the analysis of its thermodynamic and hydrodynamic characters and the sampled experiment data which are expressed by a set of differential equations with switching (bifurcation) on the right hand side. The switching surface is divided into two parts: sliding and crossing. We analyze the reasons of error existing on the surface, and develop well-defined control semantics for managing behavior discontinuities in the case of state transition. The calculation algorithm can seamlessly integrate the continuous behavior generation and the discrete mode switching. Using this method we can solve this model under the entire region of input throttle angles. Furthermore, the stability is greatly improved and the calculation time is greatly reduced for the real time control system.

In the society with high environmental consciousness, development of new treatment techniques in used disposable diapers, which are currently mostly disposed by incineration, is needed. In this paper, a new treatment technique for decomposing disposable diapers by microorganisms with cryptomeria chips is proposed. In addition, a small size disposal system has ability to process steady like a garbage disposal unit is expected to develop. For that reason, the disposal process of disposable diapers is modeled, and the parameters of constructed process model are defined according to the results of experiment. Then a simulation with the parameters is performed used SIMULINK and MATLAB.

In this paper, development of LOM with general versatility (Generalized LOM) and its speed enhancement technology are described. An existing LOM is rebuilt by using versatile database and Java to realize the "Generalized LOM". The Generalized LOM doesn't depend on the software platform and it is convenient to use the network and the visualization. Furthermore, the speed of the Generalized LOM is enhanced. The processing time is shortened without reducing the prediction accuracy.

This paper focuses on maintaining a bridge's safety by developing a daily management system. And the purpose of this study is the development of the health monitoring system. It supports the maintenance by Independent Component Analysis (ICA) when there are some troubles in a bridge. The result of this study brings out the vibration behavior of the overall structure in a bridge. This vibration is caused by the external force such as heavy weight impact, wind pressure, and running vehicle. The character frequency was extracted from the analysis result using ICA and Spectral Analysis. When the vibration behavior caused by external force is very small in the bridge, ICA can detect the vibration response from the analysis result. Therefore, it is proved that the potential of detection was high by ICA.

In the field of pig ironmaking process, operation malfunction is caused by both enlarging a blast furnace and increasing use of low quality ore. Thus, operation support systems predicting a blast furnace performance are demanded. This paper reports a Java-based operation support system integrated with a "Large-scale database-based Online Modeling (LOM)" and a blast furnace simulator. The system predicts blast furnace performance by combining the partial unsteady simulator of the physical modeling method and the LOM of the local modeling method and supports the operation. To construct the system, the Java-based partial unsteady simulator is developed and the existing LOM is rebuilt by using versatile database and Java to realize the generalized LOM with general versatility. These systems are integrated by using Java.

Accurately estimating or measuring intake manifold absolute pressure plays an important role in automobile engine control. In order to achieve the real-time estimation of the absolute pressure, the high accuracy and high speed processing ability is commonly required for the automobile engine control system. However, the conventional numerical methods cannot satisfy the requirement of the strict time needed by high speed automobile engine. Therefore, in this paper, an analog LSI method is proposed to estimate this pressure in real time. Furthermore, a novel behavioral macromodel is given for further analog LSI design. Compared with conventional numerical method, the proposed method is highly advantageous in speed to simulate the automobile engine intake system.

In the field of pig ironmaking process, operation malfunction is caused by both enlarging a blast furnace and increasing use of low quality ore. Thus, operation support systems predicting a blast furnace performance are demanded. This paper reports application of a partial unsteady simulator and a "Large-scale database-based Online Modeling (LOM)"for blast furnace operation support. First, the partial unsteady simulator constructed by using steady model as fundamental model is described. Second, a generalized LOM rebuilt by the existing LOM system is introduced. Third, a Java-based operation support system is described. The system is realized by combining the simulator of the physical modeling method and the LOM of the local modeling method. The system predicts dynamic molten pig-iron temperature in blast furnace. To predict the dynamic molten pig-iron temperature, a basic tank model of metal and slag is incorporated into. the simulator. Functions representing effect of pulverized coal injection are incorporated into the unsteady model.

This paper introduces Java-based blast furnace simulator and describes visualization system. The Java-based blast furnace simulator is constructed by integrating existing partial simulators. The visualization system provides integrated visualization information of real measured data and simulation result in order to support blast furnace operation. Furthermore, guidance method based on the simulation result which changes the manipulated variable in tuyere of blast furnace is described. © 2005 SICE.

This paper introduces Java-based blast furnace simulator and describes visualization system. The Java-based blast furnace simulator is constructed by integrating existing partial simulators. The visualization system provides integrated visualization information of real measured data and simulation result in order to support blast furnace operation. Furthermore, guidance method based on the simulation result which changes the manipulated variable in tuyere of blast furnace is described. © 2005 SICE.

Recently, the controlled object is complicated, and the improvement in performance enhancement (high precision and speedup) and safety of the control system is required, and the demand which simulates the whole system heightens. In this research, the method of unifying two or more partial simulators for one simulator was proposed. By applying this method to the partial simulators for Rabit model (the burden distribution computation model) and Bright model (the internal model) on the blast furnace, the blast furnace integration simulator was constructed. JNI(Java Native Interface) is used in order to integrate the simulator described in the different language, and RMI(Remote Method Invocation) is used in order to integrate the simulator which runs in the different environment (the multi- platform).These detail methods and the blast furnace integrated simulator are reported. ©2004 IEEE.