• 정보처리학회지
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• 제11권6호
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• pp.56-75
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• 2004

In this article we address some system characteristics and challenging issues in developing Context-aware Middleware for Ubiquitous Computing. The functionalities of a Context-aware Middleware includes gathering context data from hardware/software sensors, reasoning and inferring high-level context data, and disseminating/delivering appropriate context data to interested applications/services. The Middleware should facilitate the query, aggregation, and discovery for the contexts, as well as facilities to specify their privacy policy. Following a formal context model using ontology would enable syntactic and semantic interoperability, and knowledge sharing between different domains. Moddleware should also provide different kinds of context classification mechanical as pluggable modules, including rules written in different types of logic (first order logic, description logic, temporal/spatial logic, fuzzy logic, etc.) as well as machine-learning mechanical (supervised and unsupervised classifiers). Different mechanisms have different power, expressiveness and decidability properties, and system developers can choose the appropriate mechanism that best meets the reasoning requirements of each context. And finally, to promote the context-trigger actions in application level, it is important to provide a uniform and platform-independent interface for applications to express their need for different context data without knowing how that data is acquired. The action could involve adapting to the new environment, notifying the user, communicating with another device to exchange information, or performing any other task.

• International Journal of Quality Innovation
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• 제3권2호
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• pp.138-158
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• 2002

Nowadays, new product development (NPD) is one of the most crucial factors for business success. The manufacturing firms cannot afford the resources in the long development cycle and the costly redesigns. Good product planning is crucial to ensure the success of NPD, while the Quality Function deployment (QFD) is an effective tool to help the decision makers to determine appropriate product specifications in the product planning stage. Traditionally, in the QFD, the product specifications are determined by a rather subjective evaluation, which is based on the knowledge and experience of the decision makers. In this paper, the traditional QFD methodology is firstly reviewed. An improved Hybrid Quality Function Deployment (HQFD) [MSOfficel] then presented to tackle the shortcomings of traditional QFD methodologies in determining the engineering characteristics. A structured questionnaire to collect and analyze the customer requirements, a methodology to establish a QFD record base and effective case retrieval, and a model to more objectively determine the target values of engineering characteristics are also described.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권3호
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• pp.185-191
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• 2008

In this paper, experimental studies of a neural network (NN) control technique for non-model based position control of the x-y table robot are presented. Decentralized neural networks are used to control each axis of the x-y table robot separately. For an each neural network compensator, an inverse control technique is used. The neural network control technique called the reference compensation technique (RCT) is conceptually different from the existing neural controllers in that the NN controller compensates for uncertainties in the dynamical system by modifying desired trajectories. The back-propagation learning algorithm is developed in a real time DSP board for on-line learning. Practical real time position control experiments are conducted on the x-y table robot. Experimental results of using neural networks show more excellent position tracking than that of when PD controllers are used only.

• 유통과학연구
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• 제19권7호
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• pp.61-73
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• 2021

Purpose: This study offers suggestions to e-commerce companies for increasing shoppers' repurchase intention by considering the effect of distribution information in online shopping. It applies complexity theory to incorporate habitual information search behavior and shopper characteristics into the Stimulus-Organism-Response model and indicates how these complex factors work together in online shopping. Research design, data, and methodology: This study used an interview survey of 158 Vietnamese consumers with an experience of online shopping. A fuzzy-set Qualitative Comparative Analysis (fsQCA) was used to examine the relationship between antecedents and outcomes depending on complex conditions in the given contexts. Results: The results (1) indicate the importance of observing information search patterns and investigating their influence on online distribution, and (2) clarify what kind of configurations, under what conditions, predict a high or low outcome; this provides evidence and hints for the development of frameworks for future studies. Conclusions: The findings suggest that shoppers' unconscious, habitual behavior can work with conscious attitude factors, such as satisfaction, to increase their repurchase intention. Hence, e-commerce companies should consider how to present useful distribution information and create functions that allow shoppers to engage with a variety of information while increasing their repurchase intention on the site.

• 아태비즈니스연구
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• 제11권1호
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• pp.93-114
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• 2020

Purpose -The purpose of this study is to analyze how the accreditation system affect the selection of business strategies in social enterprises, which create social value rather than maximize profits. Design/methodology/approach - This study collected survey data from 40 accredited and 53 non-accredited social enterprises. This research employs a Fuzzy-set/qualitative comparative analysis to compare the combinations of factors that affect a social enterprise's performance Findings - The results show that for accredited enterprises organizational capabilities are significantly more important than networking capabilities, whereas for non-accredited enterprises internal communication, governance capacities and networking competencies are most important capabilities to improving their social performance. And also The accreditation systems for social enterprises would entice social enterprise away from business strategies based on with local society, which is differentiated with commonly accepted social enterprise model. Research implications or Originality - This research suggests that the accreditation system for social enterprises should be redesigned for enticing social enterprises in Korea to be more localized to meet local needs in terms of positive changes of local society.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권4호
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• pp.1276-1295
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• 2023

Sensor networks are now an essential aspect of wireless communication, especially with the introduction of new gadgets and protocols. Their ability to be deployed anywhere, especially where human presence is undesirable, makes them perfect choices for remote observation and control. Despite their vast range of applications from home to hostile territory monitoring, limited battery power remains a limiting factor in their efficacy. To analyze and transmit data, it requires intelligent use of available battery power. Several studies have established effective routing algorithms based on clustering. However, choosing optimal cluster heads and similarity measures for clustering significantly increases computing time and cost. This work proposes and implements a simple two-phase technique of route creation and maintenance to ensure route reliability by employing nature-inspired ant colony optimization followed by the fuzzy decision engine (FDE). Benchmark methods such as PSO, ACO and GWO are compared with the proposed HRCM's performance. The objective has been focused towards establishing the superiority of proposed work amongst existing optimization methods in a standalone configuration. An average of 15% improvement in energy consumption followed by 12% improvement in latency reduction is observed in proposed hybrid model over standalone optimization methods.

• 디자인학연구
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• 제20권3호
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• pp.203-214
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• 2007

본 논문은 이동(Navigation)지원을 목적으로 하는 정보기기 콘텐츠를 개발하기 위하여 보행자의 감성이 반영된 감성정보처리법을 퍼지이론에 기초하여 제안하였다. 먼저, 가상의 목적지로 설정한 상업공간의 감성평가를 실시하고, 시각적 특징과 감성적 특징 사이의 인과관계를 규명하여 내비게이션 지식베이스로 구축하는 방법을 제안하였다. 지식베이스는 감성적 특징 사이의 상관관계모델, 시각적 특징량과 감성적 특징량 사이의 인과관계모델, 그리고 시각적 특징량과 물리적 특징량 사이의 변환모델로 구축된다. 다음으로, 보행자의 목적지에 대한 감성적 취향과 내비게이션에 주어지는 시간적 제약조건에 따라 목적지 탐색을 4가지 유형으로 분류하고 각각의 유형에 적합한 목적지 탐색방법을 제시하였다. 마지막으로, 구축된 지식베이스와 감성검색 알고리즘을 이용하여 내비게이션 유형별로 목적지 탐색을 시뮬레이션 하여 보행자의 감성을 고려한 정보탐색방법으로서의 유효성을 검증하였다. 본 연구에서 제안한 감성정보처리법은 다양한 분야의 정보기기 콘텐츠를 개발함에 있어 사용자의 감성기능을 적용하는 방법론으로 활용될 수 있을 것으로 기대된다.

• 전기학회논문지
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• 제62권5호
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• pp.696-704
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• 2013

In this paper, we introduce the LED emotional lighting system realized with the aid of both intelligent algorithm and RGB LED combined with White LED. Generally, the illumination is known as a design factor to form the living place that affects human's emotion and action in the light- space as well as the purpose to light up the specific space. The LED emotional lighting system that can express emotional atmosphere as well as control the quantity of light is designed by using both RGB LED to form the emotional mood and W LED to get sufficient amount of light. RBFNNs is used as the intelligent algorithm and the network model designed with the aid of LED control parameters (viz. color coordinates (x and y) related to color temperature, and lux as inputs, RGBW current as output) plays an important role to build up the LED emotional lighting system for obtaining appropriate color space. Unlike conventional RBFNNs, Fuzzy C-Means(FCM) clustering method is used to obtain the fitness values of the receptive function, and the connection weights of the consequence part of networks are expressed by polynomial functions. Also, the parameters of RBFNN model are optimized by using PSO(Particle Swarm Optimization). The proposed LED emotional lighting can save the energy by using the LED light source and improve the ability to work as well as to learn by making an adequate mood under diverse surrounding conditions.

• Smart Structures and Systems
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• 제14권5호
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• pp.785-809
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• 2014

In this paper, an Adaptive nerou-based inference system (ANFIS) is being used for the prediction of shear strength of high strength concrete (HSC) beams without stirrups. The input parameters comprise of tensile reinforcement ratio, concrete compressive strength and shear span to depth ratio. Additionally, 122 experimental datasets were extracted from the literature review on the HSC beams with some comparable cross sectional dimensions and loading conditions. A comparative analysis has been carried out on the predicted shear strength of HSC beams without stirrups via the ANFIS method with those from the CEB-FIP Model Code (1990), AASHTO LRFD 1994 and CSA A23.3 - 94 codes of design. The shear strength prediction with ANFIS is discovered to be superior to CEB-FIP Model Code (1990), AASHTO LRFD 1994 and CSA A23.3 - 94. The predictions obtained from the ANFIS are harmonious with the test results not accounting for the shear span to depth ratio, tensile reinforcement ratio and concrete compressive strength; the data of the average, variance, correlation coefficient and coefficient of variation (CV) of the ratio between the shear strength predicted using the ANFIS method and the real shear strength are 0.995, 0.014, 0.969 and 11.97%, respectively. Taking a look at the CV index, the shear strength prediction shows better in nonlinear iterations such as the ANFIS for shear strength prediction of HSC beams without stirrups.

• Advances in Energy Research
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• 제5권2호
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• pp.107-128
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• 2017

Energy is a major component of almost all economic, production, and service activities, and rapid population growth, urbanization and industrialization have led to ever growing demand for energy. Limited energy resources and increasingly evident environmental effects of fossil fuel consumption has led to a growing awareness about the importance of further use of renewable energy sources in the countries energy portfolio. Renewable hydrogen production is a convenient method for storage of unstable renewable energy sources such as wind and solar energy for use in other place or time. In this study, suitability of 25 cities located in Iran's western region for renewable hydrogen production are evaluated by multi-criteria decision making techniques including TOPSIS, VIKOR, ELECTRE, SAW, Fuzzy TOPSIS, and also hybrid ranking techniques. The choice of suitable location for the centralized renewable hydrogen production is associated with various technical, economic, social, geographic, and political criteria. This paper describes the criteria affecting the hydrogen production potential in the study region. Determined criteria are weighted with Shannon entropy method, and Angstrom model and wind power model are used to estimate respectively the solar and wind energy production potential in each city and each month. Assuming the use of proton exchange membrane electrolyzer for hydrogen production, the renewable hydrogen production potential of each city is then estimated based on the obtained wind and solar energy generation potentials. The rankings obtained with MCDMs show that Kermanshah is the best option for renewable hydrogen production, and evaluation of renewable hydrogen production capacities show that Gilangharb has the highest capacity among the studied cities.