This paper proposes a wheel with a deployable leg that can change the apparent wheel radius to improve the runnability of a rover traversing a lunar surface covered with regolith. The driving force of the wheel was formulated according to terramechanics, and relations for the changing driving force with the different configurations were clarified. The simulated driving forces with the original wheel configuration and extended leg configuration were compared in a single-wheel experiment, and the results confirmed that the proposed extendable leg system exhibited a higher driving force than the original circular wheel. With this system, the rover can use the original wheel state for flat ground surfaces that do not require a high driving force and then switch to the proposed extendable leg system when a high driving force is required, such as escaping from local concave ground or climbing on steep slope. The proposed system is potentially applicable to efficiently traversing irregular surfaces not only on the Moon but also on other planets.

This research deals with hierarchical modular structure which is noted as the assembly method in view of the recent upsizing of space structures. The idea is dividing a large space structure into multiple modules and homogeneous automatic assembly functions are installed on each of a module. Hence the shape and function of the entire structure has diversity as they can be changed by the arrangement of modules, regardless of the size of the structure. The conventional researches of locomotion and docking / release mechanisms installed on each module and keeping such characteristics are limited to two-dimensional. In this research, we propose a mechanism using an electromagnet that can be assembled into any shape in three dimensions. The size and arrangement of the electromagnet are optimized to maximize its movement performance by using the Response Surface Method (RSM) for making response surface and applied downhill simplex method. On that basis, the demonstration experiment was actually carried out and the success rate was compared with the existing method to demonstrate the effectiveness of the proposed method.

© 2019, The Author(s). Breast cancer diagnosis has been mostly accomplished through imaging. These methods have great advantages in being able to detect the presence and location of breast cancer. However, it is difficult to distinguish between a benign and malignant tumor located in a deep position because both tumor types look similar. In this paper, tissue including the tumor from skin was vibrated using a compression cylinder, to analyze the frequency difference for distinguishing tissue type. Before distinguishing between a benign and malignant tumor, it is necessary to validate that the difference between normal tissue and tumor can be distinguished. The objective of the study is to validate the feasibility to emphasize the frequency differences in a 10.0 mm or greater deep tumors during vibration by pushing a cylinder towards the deep tumor. A phantom model and finite element analysis model were constructed to simulate the breast. In the experiment, air was injected into the phantom and the displacement was measured. The frequency response for distinction of tissue types was analyzed and it was found that the displacement difference rate was over 50% at a frequency of 130 Hz when the cylinder was pushed into the sample as opposed to when not pushed in. Changes in displacement were measured according to the distance between the tumor and vibration point using finite element analysis. When the measurement and vibration points were on the center of the tumor, the difference in the resonance point was at its largest (5.5 Hz). Results show that the position of a tumor could be easily and rapidly detected by vibrations from a cylinder pushed into the diagnostic site.

© 2019, The Author(s). Biomimetics present useful ideas for various product designs. However, most biomimetics only mimic the features of living organisms. It has not been clarified how a given shape is attained through natural selection. This paper presents the design factors that optimize the radula shape of Euhadra peliomphala. Clarifying the important design factors would help designers in solving several problems simultaneously in order to adapt to complicated and multi-functionalized design mechanisms. We measured the radula of Euhadra peliomphala by using a microscope and modeled the grinding/cutting force using the finite element analysis (FEA). We reproduced the natural selection using multi-objective genetic algorithm (MOGA). We compared the solutions when optimizing the radula shape using objective functions of each combination of stress, cutting force, abrasion, or volume. The results show that the solution obtained through two-objective optimization with stress and cutting force was the closest to the actual radula shape.

© 2018 IEEE. Being ubiquitously used as anti-adhesive and wound-covering mechanisms, thin films have potential therapeutic uses as cell sheets to target inner organs while navigating narrow environments. A significant challenge to realize versatile films lies in achieving compact storage and efficient transport while ensuring coherency in curvature-bounded environments. In this paper, we propose a folding mechanism of a curved film by using a spiral approach, enabling efficient unfolding and flexible plasters with curved surfaces. Our experiments using gelatin-based films with curved surfaces shows the superior indwelling ability in terms of chromaticity level compared to the conventional planar films, as well as the efficient unfolding in the order of seconds. Our results presents the theoretical and experimental building blocks to realize a versatile class of films which are able to navigate narrow environments, and unfold efficiently and flexibly.

<p>In this study we propose the use of spiral folding to deploy automotive airbags, and propose the folding pattern considering creases, which has the potential benefits to diminish friction during storage and bring benefits to faster deployment. Our preliminary experiments show the feasibility to deploy airbags by using the spiral folding approach, and the reasonable consistency between the modeling and real-world deployment. Our results offer preliminary insights for further study on spiral folding mechanisms and safest deployment performance.</p>

<p>This paper presents a surgical robot mechanism optimization method considering of the working error and operator's muscle burden. The virtual surgical system was developed to simulate the visual and haptic feedback. The participants operated the VR surgical simulation system while the authors measured the working error and the participant's joint motion. The histogram was made of the data to show the distribution. The authors estimated the appropriate probabilistic distribution model using Akaike's Information Criterion (AIC) method. As a result, there were many cases most applicable to the Weibull model.</p>

© copyright Environment and Climate Change Canada. In this paper, we proposed a wheel equipped rover with deployable legs that can change the apparent wheel radius in order to improve the runnability of the rover which travels on the ground covered with lunar regolith. Furthermore, we formulated the driving force of the wheel based on Terramechanics and clarified the mechanism of the driving force change using our proposed rover wheel. In addition, the driving force was compared between the original wheel configuration and the leg expanded one in single wheel running experiments, and it was validated that the proposed leg expandable system exhibits higher driving force than the original circular wheel. With this system, in the case of a flat ground surface that does not require a high driving force, the vehicle should use the original wheel state, and when a high driving force is required such like the situation the vehicle need to escape the wheel from the local concaved ground, the proposed expandable leg system can be useful, and then the possibility of traveling on irregular surface efficiently not only on the moon but also on other planets was shown.

© 2019 Design Society. All rights reserved. In recent years, product complexity in terms of function and structure has been driven by technological development in complementary components. Designing unbiased product evaluation metrics being to grasp the complex relationships of product features, and able to capitalize on market needs has become a challenge in industrial practice. In this paper, we propose a hybrid framework in which evaluation models are generated by integrating Interpretive Structural Modeling (ISM), Hierarchical Clustering and Data Envelopment Analysis (DEA). Whereas ISM constructs hierarchical digraphs (skeletons), Hierarchical Clustering reduces dimensionality of pairwise comparisons (correlations) of design variables, and suggests possible evaluation configurations, and DEA computes weights to provide optimal evaluation metrics. Our computational experiments using more than twenty thousand vehicles from 1982 to 2013 confirmed the feasibility and usefulness of DEA with hierarchical concepts to generate the optimal vehicle evaluation metric, and to suggest configurations for vehicle design layouts.

© 2019 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved. This research formulates the two-dimensionally model of a membrane with crease line which is always added when the thin material is used for deployable space structure like a solar sail. Recent space development is tending to focus on installing a system on a ultra-light weight structure, so when the membrane is chosen as the base of space structure, the keeping accuracy of the membrane surface is the point of interest. This means how to reduce the wrinkle appeared on the membrane becomes the key point. However, the most research on modelling the membrane limit to the one dimension model, or if any, the plastic deformation is not considered. Here in this paper, the authors established the two-dimensionally membrane model considering the plasticity and clarified from analysis and experiment that wrinkles can be reduced by giving crease to a membrane. In the model assuming the actual antenna installed structure and with the actual load condition, the fact is obtained that a crease perpendicular to the loading direction should be applied to a position one fifth between the load application point and the wrinkle generated region. This position can be considered to be able to reduce wrinkle the most from the view point of amount of energy required to eliminate wrinkles.

© 2019, Springer Nature Switzerland AG. Path bundling consists in compounding multiple routes in a polygonal map to minimize connectivity in a network structure. Being closely related to the Steiner Tree Problem, yet with a different scope, path bundling aims at computing minimal trees while preserving network connectivity among origin-destination pairs to allow the joint transport of information, goods, and people. In this paper, we propose a method to tackle the path bundling problem in modular bipartite networks by using a two-layer optimization with a convex representation. Exhaustive computational experiments in diverse polygonal domains considering convex and non-convex geometry show the feasibility and the efficiency of the proposed approach, outperforming the state of the art in generating comparatively shorter trees, and improved scalability as a function of edges in bipartite networks.

© 2018 IEEE. Breast cancer diagnosis has been mostly accomplished by imaging technologies. These methods have the great advantages of detecting the presence and location of breast cancer. However, it's difficult to distinguish between a benign and malignant tumor in a deep position because both tumor types look similar. In this paper, we vibrated the tissue including tumor from skin with a compression cylinder to analyze the frequency difference for distinguishing the tissue type. Before distinguishing a benign and malignant tumor, it's necessary to validate to distinguish between normal tissue and tumor. The objective is to validate the feasibility of using a compression cylinder that emphasizes the differences in frequency between normal tissue and tumor. In two experiments, we measured the displacement on the surface of a breast phantom vibrated by an impulse hammer. We compared the frequency difference with and without a cylinder. We also studied the frequency changes in the relationship between tumor and cylinder position. We found a 5.0 Hz difference in compliance between normal tissue and the simulated tumor using a compression cylinder. The difference in frequency correlated negatively with distance from the simulated tumor to a compression cylinder. We concluded that a compression cylinder would enhance the frequency difference between normal tissue and a simulated tumor with appropriate configuration.

© 2018 IEEE. Laparoscopic surgery has the advantage of the minimally invasive for patients. However, the surgery is technically difficult for surgeon because high dexterity is required for suturing in the narrow patient's body. This paper presents a sealing method to locate the adhesive plaster at the incision instead of suturing. The objective is to optimize the plaster material and structure. We made the plaster with the thermally cross-linked gelatin film in a spiral fold because thermally cross-linked gelatin film has the high biocompatibility and tackiness, and a spiral fold has great storage efficiency. In 3 experiments, we measured expansion rate, expansion tension, peeling force, and sealing pressure in a variety of gelatin volume and concentration, and the films diameter. From these experimental results, we optimized the films using response surface method. As a result, the plaster is optimal at gelatin volume 10 mL, gelatin concentration 4 wt %, and films diameters 75 mm. We concluded that the optimized spiral folded adhesive plaster is sufficient in terms of the expansion, tackiness, and sealing properties.

This paper aims at computing minimal-length tree layouts given an n-star graph in a polygonal map. This problem is strongly related to the edge bundling problem, which consists of compounding the edges of an input graph to obtain topologically compact graph layouts being free of clutter and easy to visualize. Computational experiments using a diverse set of polygonal maps and number of edges in the input graph shows the feasibility, efficiency and robustness of our approach.

Graphs with self-loops enable to represent a large variety of interactions in natural and artificial systems, allowing not only inter-connectivity among heterogeneous entities but also the self-dependence of entities, e.g.The recursive and autonomous nature of dynamical systems. In this paper we present new bijective constructs which enable the numerical representation of graphs with self loops (or loopy graphs). In particular, we study the case of (1) undirected and (2) directed graphs with n nodes and m edges with self-loops. Our proposed approach realizes the succinct representations by using integer numbers in which rigorous computational experiments show the efficiency of our proposed algorithms: The complexity follows a quasi-linear behaviour as a function of the number of edges (which is independent of the number of nodes). Furthermore, as direct consequence of our constructs, we propose list structures having O(m) space complexity, which realize the linear space complexity depending only on the number of edges (the list is independent of n). We believe that our bijective algorithms are useful to tackle problems involving sampling of graphical models, network design as well as process planning by using number theory and sample-based learning.

© 2017 IEEE. Route bundling implies compounding multiple routes in a way that anchoring points at intermediate locations minimize a global distance metric. The result of route bundling is a tree-like structure where the roots of the tree (anchoring points) serve as coordinating locus for the joint transport of information, goods, and people. Route bundling is a relevant conceptual construct in a number of path planning scenarios where the resources and means of transport are scarce/expensive, or where the environments are inherently hard to navigate due to limited space. In this paper we propose a method for searching optimal route bundles based on a self-adaptive class of differential evolution using a convex representation. Computational experiments in scenarios with and without convex obstacles show the feasibility and efficiency of our approach.

Computing hierarchical routing networks in polygonal maps is significant to realize the efficient coordination of agents, robots and systems in general
and the fact of considering obstacles in the map, makes the computation of efficient networks a relevant need for cluttered environments. In this paper, we present an approach to compute the minimal-length hierarchical topologies in polygonal maps by Differential Evolution and Route Bundling Concepts. Our computational experiments in scenarios considering convex and non-convex configuration of polygonal maps show the feasibility of the proposed approach.

© Springer International Publishing AG, part of Springer Nature 2018. Huge lava tubes with an approximate diameter of 65–225 m were found on the surfaces of Moon and Mars in the late 2000’s. It has been argued that the interiors of the caves are spacious, and are suitable to build artificial bases with habitable features such as constant temperature, as well as protection from both meteorites and harmful radiation. In line of the above, a number of studies which regard the soft landing mechanisms on the bottom of the lava tubes have been proposed. In this paper, aiming to extend the ability to explore arbitrary surface caves, we propose a mechanism which is able to reach the ceiling of lava tubes. The basic concept of our proposed mechanism consists of a rover connected to an oscillating sample-gatherer, wherein the rover is able to adjust the length of the rope parametrically to increase the deflection angle by considering periodic changes in the pivot, and thus to ease the collection of samples by hitting against the ceiling of the cave. Relevant simulations confirmed our theoretical observations which predict the increase of deflection angle by periodically winding and rewinding the rope according to pivotal variations. We believe the our proposed approach brings the building blocks to enable finer control of exploration mechanisms of lava tubes and narrow environments.

In this paper we aim at tackling the problem of searching for novel and high-performing product designs. Generally speaking, the conventional schemes usually optimize a (multi) objective function on a dynamic model/simulation, then perform a number of representative real-world experiments to validate and test the accuracy of the some product performance metric. However, in a number of scenarios involving complex product configuration, e.g. optimum vehicle design and large-scale spacecraft layout design, the conventional schemes using simulations and experiments are restrictive, inaccurate and expensive.
In this paper, in order to guide/complement the conventional schemes, we propose a new approach to search for novel and high-performing product designs by optimizing not only a proposed novelty metric, but also a performance function which is learned from historical data. Rigorous computational experiments using more than twenty thousand vehicle models over the last thirty years and a relevant set of well-known gradient-free optimization algorithms shows the feasibility and usefulness to obtain novel and high performing vehicle layouts under tight and relaxed search scenarios.
The promising results of the proposed method opens new possibilities to build unique and high performing systems in a wider set of design engineering problems. (C) 2017 Elsevier B.V. All rights reserved.

The differentiation and the integration of products are the essential procedures for product innovation. To understand the product innovation, the approaches using S-curve theory, which explain the evolution of a technological system, have been effective. However, the S-curve theory has the disadvantage that the validity of the analysis depends greatly on the number of data. In this paper, we propose a novel method for measuring and predicting the technological innovation and the product evolution based on the S-curve and wavelet transform to solve the problem. In order to confirm the effectiveness of the proposed method, we will conduct a case study using patents of air purifiers. Furthermore, we will define and support the differentiation and the integration of the mechanical structure using the proposed method. Our analysis shows that the differentiation and the integration of the mechanical structure occur as a life cycle extension after the main technologies enter the declining phase. Therefore, the incidental technologies should be introduced at the beginning of the declining phase of the main technologies.

© Copyright 2017 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved. Path bundling, a class of path planning problem, consists of compounding multiple routes to minimize a global distance metric. Naturally, a tree-like structure is obtained as a result wherein roots play the role of coordinating the joint transport of information, goods, and people. In this paper we tackle the path bundling problem in bipartite networks by using gradient-free optimization and a convex representation. Then, by using 7,500 computational experiments in diverse scenarios with and without obstacles, implying 7.5 billion shortest path computations, show the feasibility and efficiency of the mesh adaptive search.

Directed graphs encode meaningful dependencies among objects ubiquitously. This paper introduces new and simple representations for labeled directed graphs with the properties of being succinct (space is information-theoretically optimal); in which we avoid exploiting a-priori knowledge on digraph regularity such as triangularity, separability, planarity, symmetry and sparsity. Our results have direct implications to model directed graphs by using single integer numbers effectively, which is significant to enable canonical (generation of graph instances is unique) and efficient (coding and decoding take polynomial time) encodings for learning and optimization algorithms. To the best of our knowledge, the proposed representations are the first known in the literature.

Being a significant construct in a wide range of combinatorial problems, the k-subset sum problem (k-SSP) computes k-element subsets, out of an n-element set, satisfying a user-defined aggregation value. In this paper, we formulate the k-subset sum problem as a search (optimization) problem over the space of integers associated with combination elements. And by using rigorous computational experiments using the search space over more than 10(14) integer numbers, we show that our approach is effective and efficient: it is feasible to find any combination with a user-defined sum within 10(4) function evaluations by using a gradient-free optimization algorithm. Our scheme opens the door to further advance the understanding of combinatorial problems by improved/tailored gradient-free optimization algorithms based on enumerative encoding. Also, our approach realizes the practical building block for combinatorial problems in planning and operations research using k-SSP concepts.

The search for novel and high-performing product designs is a ubiquitous problem in science and engineering: aided by advances in optimization methods the conventional approaches usually optimize a (multi) objective function using simulations followed by experiments. However, in some scenarios such as vehicle layout design, simulations and experiments are restrictive, inaccurate and expensive. In this paper, we propose an alternative approach to search for novel and high-performing product designs by optimizing not only a proposed novelty metric, but also a performance function learned from historical data. Computational experiments using more than twenty thousand vehicle models over the last thirty years shows the usefulness and promising results for a wider set of design engineering problems.

Modularity is vital to engineer complex products and machines. We assert that modularity can emerge in the context of desirable structures constrained to life cycle factors; and propose a method to evaluate machine modularity in the context of life cycle optimization. Experiments using explorit, a new and well suited global optimization algorithm, on fve relevant and divergent machine models show that it is possible to obtain tractable modules within the context of life cycle factors.

Graphs denote useful dependencies among objects ubiquitously. This paper introduces new and simple bijections to the integer grid to enable the succinct, canonical and efficient representations of labeled graphs; whereas previous work has focused on regularities in structure such as triangularity, separability, planarity, symmetry and sparsity. By succinct we imply that space is information-theoretically optimal, by canonical we imply that generation of instances is unique, and by efficient we imply that coding and decoding take polynomial time.
Our results have direct implications to handle labeled graphs by using single numbers efficiently, which is significant to enable the canonical graph encodings in learning and optimization algorithms. Our bijections are the first known in the literature.

How to build optimal vehicular powertrains? We study this question and propose an algorithm inspired by a domain-general design process. The basic idea is to interplay co-biasingly between the local approximations of discrete design and the global refinements of continuous parameters. The proposed method was evaluated to design powertrains of four types of vehicles: Series Hybrid Electric Vehicle(SHEV), Parallel Hybrid Electric Vehicle(PHEV), Fuel Cell(FC) and Electric Vehicle(EV). Simulation results show noticeable improvements on mileage per gas emissions over different study cases. To our knowledge, this is the first study aiming at designing vehicle powertrains considering the holistic point of view. © Springer-Verlag 2013.

One important concept in financial risk management is the diversification process of capital allocation. This paper proposes an evolutionary approach for the optimal diversification when making asset allocation using variable-size genetic relation algorithm (vs-GRA), whose main role is to model and evolve structures toward effective and diversified portfolios through its graph structure. Simulations using heterogeneous and globally located asset classes in the United States, Europe, and Asia show that the proposed scheme offers competitive economic advantages. (C) 2012 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

As global financial innovation opens innumerable risks and opportunities, a global view of the asset allocation brings advantages in risk diversification for investments. We propose a novel framework for asset selection under global diversification principles using genetic network programming. Simulations using the stocks, bonds and currencies from relevant financial markets in USA, Europe and Asia show that the proposed framework is effective and offers competitive advantages against the conventional methods in finance and computational fields. (C) 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

One important question in investment is how to build adaptive asset allocation strategies, i.e. portfolios which adjust to the changing conditions of the economic environments. This paper proposes an evolutionary approach for the adaptive asset allocation by using Guided Genetic Relation Algorithm(GRA-g), whose main role is to model and evolve the optimal adaptive portfolio structures. Simulations using asset classes in USA show that the proposed scheme offers competitive economic advantages. This paper suggests that the use of evolutionary computing techniques is an excellent tool to aid the asset allocation, whose advantages imply the usefulness to manage the exposure to risk. ? 2011 SICE.

Stock selection involves the continuous quest for the margin of safety, or a favorable difference between the stock price and its intrinsic value. Although this variable might not be quantified with exact precision, it may be approximated through the underlying relationships in financial markets and the real economy. We propose Genetic Network Programming with changing structures(GNP-cs), a novel evolutionary based algorithm to approximate these relationships through graph networks, and build asset selection models to identify the prospective stocks in the context of changing environments. GNP-cs uses functionally distributed systems to monitor the change of the economic environment and execute the strategy for stock selection adaptively. The comparison shows that the proposed scheme outperforms the standard stock selection styles using the stocks listed in the Russell 3000 Index. This paper suggests that the use of evolutionary computing techniques is an excellent tool to tackle the stock selection problem, whose advantages imply the usefulness to manage the risk and safeguard investments. © 2011 Authors.

Financial innovation is continuously testing the asset selection models, which are the key both for building robust portfolios and for managing diversified risk. This paper describes a novel evolutionary based scheme for the asset selection using Robust Genetic Network Programming(r-GNP). The distinctive feature of r-GNP lies in its generalization ability when building the optimal asset selection model, in which several training environments are used throughout the evolutionary approach to avoid the over-fitting problem to the training data. Simulation using stocks, bonds and currencies in developed financial markets show competitive advantages over conventional asset selection schemes.

Asset selection is a challenging task in the complex global financial system, whose nature has highlighted the need to rethink conventional practices. The attractive and non-toxic assets must be kept on the eye so that our financial systems sustain building blocks in our economic systems. This paper presents an asset selection framework using Genetic Network Programming(GNP). GNP handles evolvable graph structures that prevent the size expansion for dynamic and complex environments, which in turn make it suitable for dealing with decision processes effectively under uncertainty such as partially observable Markov decision processes. Simulations using stocks, bonds and currencies from relevant financial markets in USA, Europe and Asia show the competitive advantages of the proposed method against relevant selection strategies in the finance literature.

Global financial development have opened innumerable risks and opportunities for investments. A global view of the portfolio allocation through diversification brings advantages for the risk allocation in investments. In this paper, an asset allocation framework under the return, risk and liquidity considerations is proposed for short term investment using Genetic Relation Algorithm. Simulations using the stocks, bonds and currencies from relevant financial markets in USA, Europe and Asia show that the proposed framework is effective and robust. The efficacy of the proposed method is compared against the relevant constructs in finance and computational fields.

&lt;p&gt;Lunar cave is appropriate to making the moon base because the cave has high tightness, constant temperature, and safety from meteorite and radiation. The sampling in lunar cave is necessary to understand inside so there are many approaches studied. However, there is few studies about the approach method of sampling from the ceiling of vertical hole. This paper presents a sample acquisition method from the ceiling of vertical hole. The master unit throw the handset from the outside of the vertical hole, control the handset vibration by just pulling the wire, and get the sample by colliding the handset with the ceiling. We validated to control the handset with parametric excitation theory from the experiment. As a result, the average error rate of the maximum deflection angle was 30.9%, and the average error rate of the time to reach the maximum deflection angle was 1.88%. We concluded that the winding timing of the wire is mostly consistent with the theoretical value.&lt;/p&gt;

&lt;p&gt;In this paper, in order to develop a structure capable of coping with trend in large scale and the diversification of the space structure in recent years. We will propose a moving mechanism using electromagnets and permanent magnets. We make a real machine as a self-construction system that automatically joins and assembles to the target shape after dividing a large space structure into some modules and conveying them to outer space over several times. We confirmed the reliability of moving mechanism for modular space structure proposed in this paper by giving a success rate of movement completion through an experiment.&lt;/p&gt;

Path planning with safety considerations regards the minimization of the (variation) of curvature along the curved path. We present for the first time the application of log-aesthetic curves in path planning. Our results show the feasibility and the computational efficiency compared to the conventional methods.

Route bundling consists of compounding multiple paths into a single route by finding optimal anchoring points at intermediate joints, which serve as coordinating locus for joint transport of goods/people. Route bundling is a significant construct in a number of planning scenarios where transport resource is scarce. We present the problem of route bundling and propose a new method for finding such compounded routes. Computational experiments in scenarios with/without obstacles show the feasibility and efficiency of our approach.

&lt;p&gt;前腕義手を懸垂する上腕カフにおいて，マジックテープやバックル式ベルト等が締止構造として用いられている．しかしながら操作が煩雑であり，ベルトの一部を引張って締め付けるため圧力分布が不均一になり，褥瘡となる可能性がある．この問題に対して，半径方向に全体的に締め付けることによる圧力分散の改善を考えた．巨視的なポアソン比が負の構造をリング状にすることにより，軸方向への圧縮という単純な動作によって，半径方向への全体的な締め付けが可能となり，圧力分散の改善が期待できる．本研究においては，上腕カフへの適用を想定し，最適化設計したポアソン比が負のコンプライアントメカニズムによる締止構造の，従来の締止構造に対する圧力分散の優位性を検証した．最適化の初期形状として，寒野氏が提案した二種類の構造を基に，リング構造に円筒軸方向に強制変位を加え，構造中央部の半径方向変位を最大化する寸法最適化を行った．リング構造の収縮実験を行い，レーザ変位計で構造中央部の半径方向変位を測定し，最適化結果と実験値の整合性を確認した．次に，円柱の上腕モデルに対して締め付けた時の内圧を圧力センサにより測定し，圧力分散について変動係数を用いて従来の締止方式と比較した．これにより，周方向の圧力分散に関して，コンプライアントメカニズムによる締止構造によって優位性が得られることを確認した．&lt;/p&gt;

Continuing our work on aesthetic curves and surfaces, in this report we present novel results on the comparison between the log-aesthetic surfaces obtained by the conventional energy methods and out proposed method.

Directed graphs are useful to encode oriented dependencies among entities. We propose a new method that enables the representation of directed graphs via numbers; enabling the succinct, canonical and efficient encoding schemes. We present examples in graph encoding and its applicability to real world networks.

Developing affordable and robust human-machine interfaces is key to improve the quality of life of handicapped and amputee users in developing countries. While most of the available technologies are robust, the cost is inaccessible to large portions of the population with low-income. In this paper, we propose a compact, robust and cost-effective interface for arm pose sensing and control of external devices based on the low-cost accelerometer, gyroscope and Xbee technologies. Experiments using a prototype showed the promising results to detect and classify the robust poses.

Designing optimal ZigBee networks is key for efficient low-cost communication of multi-agent sensors and mechatronics systems. In this paper, we report a novel approach to optimize ZigBee networks using the optimization of bundled routes. To the best of our knowledge, this is the first approach reported in the literature to find optimal ZigBee network topologies.

自動車等の意匠設計に使用する新しいパラダイムの曲線，曲面表現式として，美的B-spline曲線，曲面を提案する．前報までに，対数型美的曲線の汎用目的関数として，曲率半径の指数乗の曲率グラフでの直線からのずれを最小化する式を提案し，空間曲線や曲面について境界条件からの対話的生成と，測定データの当てはめに対して最適解を求めた．本報では，曲面の曲率について考察し，曲面の当てはめ法とその結果を示す．さらに，複合曲線・曲面についての定式化を行い実験結果を示す．

We introduce Homeostatic Learning Networks, a simple and effective algorithm for problems involving optimal control in unknown systems. The basic idea of the proposed method is to introduce homeostasis into the behaviour of nodes and connections of a robot controller in order to allow the more diverse and sophisticated building blocks and control rules for unknown environments.

自動車等の意匠設計に使用する新しいパラダイムの曲線，曲面表現式として，美的B-spline曲線，曲面の定式化を行う．対数型美的曲線，曲面の表現式の汎用目的関数として，曲率グラフまたは曲率半径グラフの直線からのずれを最小化することを考え，境界条件からの対話的生成と，測定データ等の当てはめに対して最適解を求める．本報では，定式化を行い曲線に対する実験結果を示す．

自動車等の意匠設計に使用する新しいパラダイムの曲線，曲面表現式として，美的B-spline曲線，曲面を提案する．第1報では，対数型美的曲線の表現式の汎用目的関数として，曲率半径の指数乗の曲率グラフにおいて直線からのずれを最小化する式を提案し，平面曲線について境界条件からの対話的生成と，測定データ等の当てはめに対して最適解を求めた．本報では，空間曲線と曲面についての定式化を行い，空間曲線と境界条件からの曲面生成に対する実験結果を示す．

Modularity is vital to engineer complex products and machines. We assert that modularity can emerge from searching desirable machine structures constrained to life cycle costs in manufacturing, maintenance, and disassemblability. Compared to the conventional methods, computational experiments that maximize machine performance and minimize life cycle costs yield machine structures that are modular and tractable.

Designing wire harnesses is computationally complex. We use a generative approach to design the conceptual models of generic wire harnesses. Our approach is more compact and efficient compared to the conventional methods.

Due to rise of environmental awareness in recent years, engineering designers are required to consider not only product performance but also whole product lifecycle in order to reduce environmental burdens of their products. Especially, a product in End-of-Life (EoL) phase has great impact to environment. Because of this, design for disassembly (DfD) has attracted great attention to promote product recyclability and reusability. This paper applies modular design, originally a technique intended to short the lead time and improve assimilability, to DfD to reduce disassembly process. Although a lot of works about modular design has done, since existing methods configure modules based on similarities of components&#039; lifecycle characteristics without consideration of hierarchy of a product function structure, there is a possibility of obtaining functionality and geometrically infeasible modules. This paper proposes the method optimizing product modular structure according to hierarchy of a product functional structure to get feasible modules from the perspectives of function and geometry. The optimization is conducted by Hierarchical Genetic Algorithm (HGA) which can describe hierarchical structure of mechanical system exactly. The proposed method is applied to a design of the inkjet printer to demonstrate its effectiveness.

Diversification in finance is the process of spreading investments in heterogeneous asset classes. We provide a novel approach for evolving the diversification process by variable size Genetic Relation Algorithm(vs-GRA). Simulations using assets in USA, Europe and Asia indicate that the proposed approach offers competitive advantages for the global asset allocation problem.