Super Fuzzy Matrices and Super Fuzzy Models for Social Scientists

This book introduces the concept of fuzzy super matrices and operations on them. This book will be highly useful to social scientists who wish to work with multi-expert models. Super fuzzy models using Fuzzy Cognitive Maps, Fuzzy Relational Maps, Bidirectional Associative Memories and Fuzzy Associative Memories are defined here. The authors introduce 13 multi-expert models using the notion of fuzzy supermatrices. These models are described with illustrative examples. This book has three chapters. In the first chaper, the basic concepts about super matrices and fuzzy super matrices are recalled. Chapter two introduces the notion of fuzzy super matrices adn their properties. The final chapter introduces many super fuzzy multi expert models.Comment: 280 page

Gait recognition and understanding based on hierarchical temporal memory using 3D gait semantic folding

Gait recognition and understanding systems have shown a wide-ranging application prospect. However, their use of unstructured data from image and video has affected their performance, e.g., they are easily influenced by multi-views, occlusion, clothes, and object carrying conditions. This paper addresses these problems using a realistic 3-dimensional (3D) human structural data and sequential pattern learning framework with top-down attention modulating mechanism based on Hierarchical Temporal Memory (HTM). First, an accurate 2-dimensional (2D) to 3D human body pose and shape semantic parameters estimation method is proposed, which exploits the advantages of an instance-level body parsing model and a virtual dressing method. Second, by using gait semantic folding, the estimated body parameters are encoded using a sparse 2D matrix to construct the structural gait semantic image. In order to achieve time-based gait recognition, an HTM Network is constructed to obtain the sequence-level gait sparse distribution representations (SL-GSDRs). A top-down attention mechanism is introduced to deal with various conditions including multi-views by refining the SL-GSDRs, according to prior knowledge. The proposed gait learning model not only aids gait recognition tasks to overcome the difficulties in real application scenarios but also provides the structured gait semantic images for visual cognition. Experimental analyses on CMU MoBo, CASIA B, TUM-IITKGP, and KY4D datasets show a significant performance gain in terms of accuracy and robustness

Psychological challenges for the analysis of style.

This article remains the copyright of Cambridge University Press. The definitive version of this article can be found at: http://dx.doi.org/10.1017/S089006040606015XAnalyses of styles in design have paid little attention to how people see style, and how designers use perceptions of style to guide designing. While formal and computational methods for analysing styles and generating designs provide impressively parsimonious accounts of what some styles are, they do not address many of the factors that influence how humans understand styles. The subtlety of human style judgements raises challenges for computational approaches to style. This paper differentiates between a range of distinct meanings of 'style', and explores how designers and ordinary people learn and apply perceptual similarity classes and style concepts in different situations to interpret and create designed artefacts. A range of psychological evidence indicates that style perception is dependent on knowledge, and involves the interaction of perceptual recognition of style features and explanatory inference processes that create a coherent understanding of an object as an exemplar of a style. This paper concludes by outlining how formal style analyses can be used in combination with psychological research to develop a fuller understanding of style perception and creative design

Assembly Line

An assembly line is a manufacturing process in which parts are added to a product in a sequential manner using optimally planned logistics to create a finished product in the fastest possible way. It is a flow-oriented production system where the productive units performing the operations, referred to as stations, are aligned in a serial manner. The present edited book is a collection of 12 chapters written by experts and well-known professionals of the field. The volume is organized in three parts according to the last research works in assembly line subject. The first part of the book is devoted to the assembly line balancing problem. It includes chapters dealing with different problems of ALBP. In the second part of the book some optimization problems in assembly line structure are considered. In many situations there are several contradictory goals that have to be satisfied simultaneously. The third part of the book deals with testing problems in assembly line. This section gives an overview on new trends, techniques and methodologies for testing the quality of a product at the end of the assembling line

Study on 3D modeling and pattern-making for upper garment（上衣の三次元モデルの構築およびパターンメーキングに関する研究）

信州大学(Shinshu university)博士（工学）ThesisZHANG JUN. Study on 3D modeling and pattern-making for upper garment（上衣の三次元モデルの構築およびパターンメーキングに関する研究）. 信州大学, 2017, 博士論文. 博士（工学）, 甲第663号, 平成29年03月20日授与.doctoral thesi

Parametric CAD modeling: An analysis of strategies for design reusability

CAD model quality in parametric design scenarios largely determines the level of flexibility and adaptability of a 3D model (how easy it is to alter the geometry) as well as its reusability (the ability to use existing geometry in other contexts and applications). In the context of mechanical CAD systems, the nature of the feature-based parametric modeling paradigm, which is based on parent-child interdependencies between features, allows a wide selection of approaches for creating a specific model. Despite the virtually unlimited range of possible strategies for modeling a part, only a small number of them can guarantee an appropriate internal structure which results in a truly reusable CAD model. In this paper, we present an analysis of formal CAD modeling strategies and best practices for history-based parametric design: Delphi's horizontal modeling, explicit reference modeling, and resilient modeling. Aspects considered in our study include the rationale to avoid the creation of unnecessary feature interdependencies, the sequence and selection criteria for those features, and the effects of parent/child relations on model alteration. We provide a comparative evaluation of these strategies in the form of a series of experiments using three industrial CAD models with different levels of complexity. We analyze the internal structure of the models and compare their robustness and flexibility when the geometry is modified. The results reveal significant advantages of formal modeling methodologies, particularly resilient techniques, over non-structured approaches as well as the unexpected problems of the horizontal strategy in numerous modeling situations. (C)2016 Elsevier Ltd. All rights reserved.Camba, JD.; Contero, M.; Company, P. (2016). Parametric CAD modeling: An analysis of strategies for design reusability. Computer-Aided Design. 74:18-31. doi:10.1016/j.cad.2016.01.003S18317

Una observación hacia los procesos asistidos por computadora en la producción de prendas de vestir. Comparación y análisis de software CAD/CAM en Bangladesh

This research paper inquires about different attributes of Computer-aided processes in garments production. This perspective Research was done by our courageous team from 2021 to 2022. It reveals adequate information on the Garments industry's Intension and criteria for choosing CAD/CAM software. For the sake of this Research, we visited more than 600 industries to gather raw data; Every Industry tried to attend this Research from a different region of Bangladesh willingly. After collecting all raw data from the garments industry. The data of the Garments industry was coordinated by Excel program. Consequently, the data was analyzed and implemented statistically to identify the Garments Industry attribute for satisfaction with CAD/CAM software. This process also detects many challenges and defines and advises a proper solution to the problems that the Garments industry is facing in the current situation. This research paper demonstrates adequate information about the Garment's criteria and demand in purchasing garments Computer-aided software.Este trabajo de investigación indaga sobre los diferentes atributos de los procesos asistidos por computadora en la producción de prendas de vestir. Esta investigación de perspectiva fue realizada por nuestro valiente equipo de 2021 a 2022. Revela información adecuada sobre la intención de la industria de la confección y los criterios para elegir el software CAD/CAM. Por el bien de esta investigación, visitamos más de 600 industrias para recopilar datos sin procesar; Cada industria trató de asistir a esta investigación desde una región diferente de Bangladesh de buena gana. Después de recopilar todos los datos sin procesar de la industria de la confección. Los datos de la industria de Vestuario fueron coordinados por el programa Excel. En consecuencia, los datos se analizaron e implementaron estadísticamente para identificar el atributo de la industria de la confección para la satisfacción con el software CAD/CAM. Este proceso también detecta muchos desafíos y define y aconseja una solución adecuada a los problemas que enfrenta la industria de la confección en la situación actual. Este trabajo de investigación demuestra información adecuada sobre los criterios de la prenda y la demanda en la compra de prendas Software asistido por computadora

Embedding the personal: the construction of a 'fashion autobiography' as a museum exhibition, informed by innovative practice at ModeMuseum, Antwerp

My intention is to contribute to the field of exhibition-making a repertoire of presentation modes, previously not analysed or documented, that can be applied to the display of fashion in the museum and which will extend those techniques currently available to the exhibition-maker to create meaningful and stimulating exhibition environments. Part 1 contextualises my investigation, through discussion of the exhibition as source material, the methods employed to execute the research and analysis of relevant literature. Part 1 concludes with an introduction to ModeMuseum, Antwerp, which is the primary location for my research. Part 2 details the identification, description and definition of a repertoire of presentation modes, classified and distinguished as innovative through comparative analysis of over 100 exhibitions visited for this research, alongside investigation of the exhibition formats and structures that support deployment of the modes. Part 3 relates the application of the presentation modes to the construction of a 'fashion autobiography‘ in the form of a proposal for a hypothetical exhibition, through examination of the processes utilised to develop the exhibition narrative and detailed account of the proposal in its final realisation. In conclusion, I will critically reflect on the research executed, underlining the interrelationship of the theoretical and practice-based activities. Finally, I will detail opportunities taken to disseminate this research, and indicate possible directions for continued investigation

Parametric design for human body modeling by wireframe-assisted deep learning

Statistical learning of human body shape can be used for reconstructing or estimating body shapes from incomplete data, semantic parametric design, modifying images and videos, or simulation. A digital human body is normally represented in a high-dimensional space, and the number of vertices in a mesh is far larger than the number of human bodies in public available databases, which results in a model learned by Principle Component Analysis (PCA) can hardly reflect the true variety in human body shapes. While deep learning has been most successful on data with an underlying Euclidean or grid-like structure, the geometric nature of human body is non-Euclidean, it will be very challenging to perform deep learning techniques directly on such non-Euclidean domain. This paper presents a deep neural network (DNN) based hierarchical method for statistical learning of human body by using feature wireframe as one of the layers to separate the whole problem into smaller and more solvable sub-problems. The feature wireframe is a collection of feature curves which are semantically defined on the mesh of human body, and it is consistent to all human bodies. A set of patches can then be generated by clustering the whole mesh surface to separated ones that interpolate the feature wireframe. Since the surface is separated into patches, PCA only needs to be conducted on each patch but not on the whole surface. The spatial relationships between the semantic parameter, the wireframe and the patches are learned by DNN and linear regression respectively. An application of semantic parametric design is used to demonstrate the capability of the method, where the semantic parameters are linked to the feature wireframe instead of the mesh directly. Under this hierarchy, the feature wireframe acts like an agent between semantic parameters and the mesh, and also contains semantic meaning by itself. The proposed method of learning human body statistically with the help of feature wireframe is scalable and has a better quality