Search results for: Framework interface classes
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2409

Search results for: Framework interface classes

519 Photo Mosaic Smartphone Application in Client-Server Based Large-Scale Image Databases

Authors: Sang-Hun Lee, Bum-Soo Kim, Yang-Sae Moon, Jinho Kim

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In this paper we present a photo mosaic smartphone application in client-server based large-scale image databases. Photo mosaic is not a new concept, but there are very few smartphone applications especially for a huge number of images in the client-server environment. To support large-scale image databases, we first propose an overall framework working as a client-server model. We then present a concept of image-PAA features to efficiently handle a huge number of images and discuss its lower bounding property. We also present a best-match algorithm that exploits the lower bounding property of image-PAA. We finally implement an efficient Android-based application and demonstrate its feasibility.

Keywords: smartphone applications; photo mosaic; similarity search; data mining; large-scale image databases.

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518 Indonesian Store Loyalty Factors for Modern Retailing Market

Authors: Lina Salim

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Modern retailers such as hypermarket/supermarket need to be more customer-oriented in order to survive in today-s competitive business world. As a result, the investigation of determinant factors of store loyalty becomes important issue for modern retailing players. This study suggests that consumers- store loyalty in the modern retailing market (hypermarkets and supermarkets) is influenced by environmental factors (such as store image, store personnel). Using a model of stimulus-organismresponse (S-O-R), this research examines S-R relationship of store loyalty. S-O-R framework is derived from the existence literature and tested empirically based on Indonesian consumers- experience. The stimuli for this study are store image, store personnel, satisfaction and culture factors. Affect, or the consumers- liking to modern retailing stores, mediates the chosen environmental factors on consumer-s store loyalty. The findings showed that store image, store satisfaction and culture have significant positive relationship to store loyalty via affect.

Keywords: Affect, Culture, Store Image, Store Loyalty, StorePersonnel, Store Satisfaction

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517 Hybridized Technique to Analyze Workstress Related Data via the StressCafé

Authors: Anusua Ghosh, Andrew Nafalski, Jeffery Tweedale, Maureen Dollard

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This paper presents anapproach of hybridizing two or more artificial intelligence (AI) techniques which arebeing used to fuzzify the workstress level ranking and categorize the rating accordingly. The use of two or more techniques (hybrid approach) has been considered in this case, as combining different techniques may lead to neutralizing each other-s weaknesses generating a superior hybrid solution. Recent researches have shown that there is a need for a more valid and reliable tools, for assessing work stress. Thus artificial intelligence techniques have been applied in this instance to provide a solution to a psychological application. An overview about the novel and autonomous interactive model for analysing work-stress that has been developedusing multi-agent systems is also presented in this paper. The establishment of the intelligent multi-agent decision analyser (IMADA) using hybridized technique of neural networks and fuzzy logic within the multi-agent based framework is also described.

Keywords: Fuzzy logic, intelligent agent, multi-agent systems, neural network, workplace stress.

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516 Self-Supervised Pretraining on Paired Sequences of fMRI Data for Transfer Learning to Brain Decoding Tasks

Authors: Sean Paulsen, Michael Casey

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In this work, we present a self-supervised pretraining framework for transformers on functional Magnetic Resonance Imaging (fMRI) data. First, we pretrain our architecture on two self-supervised tasks simultaneously to teach the model a general understanding of the temporal and spatial dynamics of human auditory cortex during music listening. Our pretraining results are the first to suggest a synergistic effect of multitask training on fMRI data. Second, we finetune the pretrained models and train additional fresh models on a supervised fMRI classification task. We observe significantly improved accuracy on held-out runs with the finetuned models, which demonstrates the ability of our pretraining tasks to facilitate transfer learning. This work contributes to the growing body of literature on transformer architectures for pretraining and transfer learning with fMRI data, and serves as a proof of concept for our pretraining tasks and multitask pretraining on fMRI data.

Keywords: Transfer learning, fMRI, self-supervised, brain decoding, transformer, multitask training.

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515 Robust Image Transmission Over Time-varying Channels using Hierarchical Joint Source Channel Coding

Authors: Hatem. Elmeddeb, Noureddine, Hamdi, Ammar. Bouallègue

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In this paper, a joint source-channel coding (JSCC) scheme for time-varying channels is presented. The proposed scheme uses hierarchical framework for both source encoder and transmission via QAM modulation. Hierarchical joint source channel codes with hierarchical QAM constellations are designed to track the channel variations which yields to a higher throughput by adapting certain parameters of the receiver to the channel variation. We consider the problem of still image transmission over time-varying channels with channel state information (CSI) available at 1) receiver only and 2) both transmitter and receiver being informed about the state of the channel. We describe an algorithm that optimizes hierarchical source codebooks by minimizing the distortion due to source quantizer and channel impairments. Simulation results, based on image representation, show that, the proposed hierarchical system outperforms the conventional schemes based on a single-modulator and channel optimized source coding.

Keywords: Channel-optimized VQ (COVQ), joint optimization, QAM, hierarchical systems.

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514 Holomorphic Prioritization of Sets within Decagram of Strategic Decision Making of POSM Using Operational Research (OR): Analytic Hierarchy Process (AHP) Analysis

Authors: Elias O. Tembe, Hussain A. Al-Salamin

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There is decagram of strategic decisions of operations and production/service management (POSM) within operational research (OR) which must collate, namely: design, inventory, quality, location, process and capacity, layout, scheduling, maintain ace, and supply chain. This paper presents an architectural configuration conceptual framework of a decagram of sets decisions in a form of mathematical complete graph and abelian graph. Mathematically, a complete graph is undirected (UDG), and directed (DG) a relationship where every pair of vertices is connected, collated, confluent, and holomorphic. There has not been any study conducted which, however, prioritizes the holomorphic sets which of POMS within OR field of study. The study utilizes OR structured technique known as The Analytic Hierarchy Process (AHP) analysis for organizing, sorting and prioritizing(ranking) the sets within the decagram of POMS according to their attribution (propensity), and provides an analysis how the prioritization has real-world application within the 21st century.

Keywords: AHP analysis, Decagram, Decagon, Holomorphic.

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513 Determination of the Content of Teachers’ Presentism through a Web-Based Delphi Method

Authors: Tsai-Hsiu Lin

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Presentism is one of the orientations of teachers’ teaching culture. However, there are few researchers to explore it in Taiwan. The objective of this study is to establish an expert-based determination of the content of teachers’ presentism in Taiwan. The author reviewed the works of Jackson, Lortie, and Hargreaves and employed Hargreaves’ three forms of teachers’ presentism as a framework to design the questionnaire of this study. The questionnaire of teachers’ presentism comprised of 42 statements. A three-round web-based Delphi survey was proposed to 14 participants (two teacher educators, two educational administrators, three school principals, and seven schoolteachers), 13 participants (92.86%) completed the three-rounds of the study. The participants were invited to indicate the importance of each statement. The Delphi study used means and standard deviation to present information concerning the collective judgments of respondents. Finally, the author obtained consensual results for 67% (28/42). However, the outcome of this study could be the result of identifying a series of general statements rather than an in-depth exposition of the topic.

Keywords: Delphi Technique, teachers’ presentism, sociology of teaching, teaching culture.

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512 Real-Time Vision-based Korean Finger Spelling Recognition System

Authors: Anjin Park, Sungju Yun, Jungwhan Kim, Seungk Min, Keechul Jung

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Finger spelling is an art of communicating by signs made with fingers, and has been introduced into sign language to serve as a bridge between the sign language and the verbal language. Previous approaches to finger spelling recognition are classified into two categories: glove-based and vision-based approaches. The glove-based approach is simpler and more accurate recognizing work of hand posture than vision-based, yet the interfaces require the user to wear a cumbersome and carry a load of cables that connected the device to a computer. In contrast, the vision-based approaches provide an attractive alternative to the cumbersome interface, and promise more natural and unobtrusive human-computer interaction. The vision-based approaches generally consist of two steps: hand extraction and recognition, and two steps are processed independently. This paper proposes real-time vision-based Korean finger spelling recognition system by integrating hand extraction into recognition. First, we tentatively detect a hand region using CAMShift algorithm. Then fill factor and aspect ratio estimated by width and height estimated by CAMShift are used to choose candidate from database, which can reduce the number of matching in recognition step. To recognize the finger spelling, we use DTW(dynamic time warping) based on modified chain codes, to be robust to scale and orientation variations. In this procedure, since accurate hand regions, without holes and noises, should be extracted to improve the precision, we use graph cuts algorithm that globally minimize the energy function elegantly expressed by Markov random fields (MRFs). In the experiments, the computational times are less than 130ms, and the times are not related to the number of templates of finger spellings in database, as candidate templates are selected in extraction step.

Keywords: CAMShift, DTW, Graph Cuts, MRF.

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511 Advancing the Hi-Tech Ecosystem in the Periphery: The Case of the Sea of Galilee Region

Authors: Yael Dubinsky, Orit Hazzan

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There is a constant need for hi-tech innovation to be decentralized to peripheral regions. This work describes how we applied Design Science Research (DSR) principles to define what we refer to as the Sea of Galilee (SoG) method. The goal of the SoG method is to harness existing and new technological initiatives in peripheral regions to create a socio-technological network that can initiate and maintain hi-tech activities. The SoG method consists of a set of principles, a stakeholder network, and actual hi-tech business initiatives, including their infrastructure and practices. The three cycles of DSR, the Relevance, Design, and Rigor cycles, lay out a research framework to sharpen the requirements, collect data from case studies, and iteratively refine the SoG method based on the existing knowledge base. We propose that the SoG method can be deployed by regional authorities that wish to be considered as smart regions (an extension of the notion of smart cities).

Keywords: Design Science Research, socio-technological initiatives, Sea of Galilee method, periphery stakeholder network, hi-tech initiatives.

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510 Social Network Management Enhances Customer Relationship

Authors: Srisawas Siriporn, Rotchanakitumnuai Siriluck

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The study aims to develop a framework of social network management to enhance customer relationship. Social network management of this research is derived from social network site management, individual and organization social network usage motivation. The survey was conducted with organization employees who have used social network to interact with customers. The results reveal that content, link, privacy and security, page design and interactivity are the major issues of social network site management. Content, link, privacy and security, individual and organization motivation have major impacts on encouraging business knowledge sharing among employees. Moreover, Page design and interactivity, content, organization motivation and knowledge sharing can improve customer relationships.

Keywords: Social network management, social network site, motivation, knowledge sharing, customer relationship

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509 The Link between Money Market and Economic Growth in Nigeria: Vector Error Correction Model Approach

Authors: Ehigiamusoe, Uyi Kizito

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The paper examines the impact of money market on economic growth in Nigeria using data for the period 1980-2012. Econometrics techniques such as Ordinary Least Squares Method, Johanson’s Co-integration Test and Vector Error Correction Model were used to examine both the long-run and short-run relationship. Evidence from the study suggest that though a long-run relationship exists between money market and economic growth, but the present state of the Nigerian money market is significantly and negatively related to economic growth. The link between the money market and the real sector of the economy remains very weak. This implies that the market is not yet developed enough to produce the needed growth that will propel the Nigerian economy because of several challenges. It was therefore recommended that government should create the appropriate macroeconomic policies, legal framework and sustain the present reforms with a view to developing the market so as to promote productive activities, investments, and ultimately economic growth.

Keywords: Economic Growth, Investments, Money Market, Money Market Challenges, Money Market Instruments.

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508 A Relational Case-Based Reasoning Framework for Project Delivery System Selection

Authors: Yang Cui, Yong Qiang Chen

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An appropriate project delivery system (PDS) is crucial to the success of a construction projects. Case-based Reasoning (CBR) is a useful support for PDS selection. However, the traditional CBR approach represents cases as attribute-value vectors without taking relations among attributes into consideration, and could not calculate the similarity when the structures of cases are not strictly same. Therefore, this paper solves this problem by adopting the Relational Case-based Reasoning (RCBR) approach for PDS selection, considering both the structural similarity and feature similarity. To develop the feature terms of the construction projects, the criteria and factors governing PDS selection process are first identified. Then feature terms for the construction projects are developed. Finally, the mechanism of similarity calculation and a case study indicate how RCBR works for PDS selection. The adoption of RCBR in PDS selection expands the scope of application of traditional CBR method and improves the accuracy of the PDS selection system.

Keywords: Relational Cased-based Reasoning, Case-based Reasoning, Project delivery system, Selection.

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507 An MADM Framework toward Hierarchical Production Planning in Hybrid MTS/MTO Environments

Authors: H. Rafiei, M. Rabbani

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This paper proposes a new decision making structure to determine the appropriate product delivery strategy for different products in a manufacturing system among make-to-stock, make-toorder, and hybrid strategy. Given product delivery strategies for all products in the manufacturing system, the position of the Order Penetrating Point (OPP) can be located regarding the delivery strategies among which location of OPP in hybrid strategy is a cumbersome task. In this regard, we employ analytic network process, because there are varieties of interrelated driving factors involved in choosing the right location. Moreover, the proposed structure is augmented with fuzzy sets theory in order to cope with the uncertainty of judgments. Finally, applicability of the proposed structure is proven in practice through a real industrial case company. The numerical results demonstrate the efficiency of the proposed decision making structure in order partitioning and OPP location.

Keywords: Hybrid make-to-stock/make-to-order, Multi-attribute decision making, Order partitioning, Order penetration point.

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506 Enhanced Quality of Zeolite LSX: Studying Effect of Crystallized Containers

Authors: Jitlada Chumee

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Low silica type X (LSX) Zeolite is one of useful material in many manufacturing due to the advantage properties including high surface area, stability, microporous crystalline aluminosilicates and positive ion in an extra–framework. The LSX was used rice husk silica source which obtained by leaching with hydrochloric acid and calcination at 500C. To improve the synthesis method, the LSX was crystallizated in Teflon–lined autoclave will expedite deceasing of the amorphous particles. The mixed gel with composition of 5.5 Na2O : 1.65 K2O : Al2O3 : 2.2 SiO2 : 122 H2O was crystallized in different container (Polypropylene bottom and Teflon–lined autoclave). The obtained powder was characterized by X–ray diffraction (XRD), X–ray fluorescence spectrometry, N2 adsorption-desorption analysis BET surface area Scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy to justify the quality of zeolite. The results showed the crystallized zeolite in Teflon lined autoclave has 102.8 nm of crystal size, 286 m2/g of surface area and fewer amounts of round amorphous particles when compared with the crystallized zeolite in Polypropylene.

Keywords: LSX Zeolite, rice husk and crystallized container.

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505 Overcrowding and Adequate Housing: The Potential of Adaptability

Authors: Inês Ramalhete, Hugo Farias, Rui da Silva Pinto

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Adequate housing has been a widely discussed theme in academic circles related to low-cost housing, whereas its physical features are easy to deal with, overcrowding (related to social, cultural and economic aspects) is still ambiguous, particularly regarding the set of indicators that can accurately reflect and measure it. This paper develops research on low-cost housing models for developing countries and what is the best method to embed overcrowding as an important parameter for adaptability. A critical review of international overcrowding indicators and their application in two developing countries, Cape Verde and Angola, is presented. The several rationales and the constraints for an accurate assessment of overcrowding are considered, namely baseline data (statistics), which can induce misjudgments, as well as social and cultural factors (such as personal choices of residents). This paper proposes a way to tackle overcrowding through housing adaptability, considering factors such as physical flexibility, functional ambiguity, and incremental expansion schemes. Moreover, a case-study is presented to establish a framework for the theoretical application of the proposed approach.

Keywords: Adaptive housing, low-cost housing, overcrowding.

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504 FCNN-MR: A Parallel Instance Selection Method Based on Fast Condensed Nearest Neighbor Rule

Authors: Lu Si, Jie Yu, Shasha Li, Jun Ma, Lei Luo, Qingbo Wu, Yongqi Ma, Zhengji Liu

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Instance selection (IS) technique is used to reduce the data size to improve the performance of data mining methods. Recently, to process very large data set, several proposed methods divide the training set into some disjoint subsets and apply IS algorithms independently to each subset. In this paper, we analyze the limitation of these methods and give our viewpoint about how to divide and conquer in IS procedure. Then, based on fast condensed nearest neighbor (FCNN) rule, we propose a large data sets instance selection method with MapReduce framework. Besides ensuring the prediction accuracy and reduction rate, it has two desirable properties: First, it reduces the work load in the aggregation node; Second and most important, it produces the same result with the sequential version, which other parallel methods cannot achieve. We evaluate the performance of FCNN-MR on one small data set and two large data sets. The experimental results show that it is effective and practical.

Keywords: Instance selection, data reduction, MapReduce, kNN.

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503 Diversity and Public Decision Making

Authors: Karin Hansson, Göran Cars, Mats Danielson, Love Ekenberg, Aron Larsson

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Within the realm of e-government, the development has moved towards testing new means for democratic decisionmaking, like e-panels, electronic discussion forums, and polls. Although such new developments seem promising, they are not problem-free, and the outcomes are seldom used in the subsequent formal political procedures. Nevertheless, process models offer promising potential when it comes to structuring and supporting transparency of decision processes in order to facilitate the integration of the public into decision-making procedures in a reasonable and manageable way. Based on real-life cases of urban planning processes in Sweden, we present an outline for an integrated framework for public decision making to: a) provide tools for citizens to organize discussion and create opinions; b) enable governments, authorities, and institutions to better analyse these opinions; and c) enable governments to account for this information in planning and societal decision making by employing a process model for structured public decision making.

Keywords: Negotiation games, Agenda setting, Multi-criteria decision analysis, Elicitation method.

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502 Architecture of Speech-based Registration System

Authors: Mayank Kumar, D B Mahesh Kumar, Ashwin S Kumar, N K Srinath

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In this era of technology, fueled by the pervasive usage of the internet, security is a prime concern. The number of new attacks by the so-called “bots", which are automated programs, is increasing at an alarming rate. They are most likely to attack online registration systems. Technology, called “CAPTCHA" (Completely Automated Public Turing test to tell Computers and Humans Apart) do exist, which can differentiate between automated programs and humans and prevent replay attacks. Traditionally CAPTCHA-s have been implemented with the challenge involved in recognizing textual images and reproducing the same. We propose an approach where the visual challenge has to be read out from which randomly selected keywords are used to verify the correctness of spoken text and in turn detect the presence of human. This is supplemented with a speaker recognition system which can identify the speaker also. Thus, this framework fulfills both the objectives – it can determine whether the user is a human or not and if it is a human, it can verify its identity.

Keywords: CAPTCHA, automatic speech recognition, keyword spotting.

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501 A Study on Use of User Demand Evaluation in Interactive Interface – Using Virtual Fitting-Room as an Example

Authors: Chang, Wei-Chen

Abstract:

The purpose of this study is to research on thoughts transmitted from virtual fitting-room and to deduce discussion in an auxiliary narrative way. The research structure is based on 3D virtual fitting-room as the research subject. Initially, we will discuss the principles of narrate study, User Demand and so on by using a narrative design pattern to transmit their objective indications of “people-situation-reason-object", etc, and then to analyze the virtual fitting-room examples that are able to provide a new thinking for designers who engaged in clothing related industry – which comes in “story telling" and “user-centered design" forms. Clothing designs are not just to cover up the body to keep warm but to draw closer to people-s demand physiologically and psychologically through interactive designs so as to achieve cognition between people and environment. In the “outside" goal of clothing-s functional designs, we use tribal group-s behavior characteristics to “transform" the existing personal cultural stories, and “reform" them to design appropriate interactive products. Synthesizing the above matters, apart from being able to regard “narrate" as a kind of functional thinking process, we are also able to regard it as a kind of choice, arrangement and an activity of story expression, allowing interactive design-s spirit, product characteristics and experience ideas be transmitted to target tribal group in a visual image performance method. It is a far more confident and innovative attempt, and meanwhile, able to achieve entertainment, joyful and so forth fundamental interactive transmissions. Therefore, this study takes “user-centered design" thinking as a basis to establish a set of clothing designs with interactive experience patterns and to assist designers to examine the five sensual feeling of interactive demands in order to initiate a new value in textile industry.

Keywords: Virtual Fitting-room, Interactive Design, User Demand Evaluation, Intelligent Systems.

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500 Multidimensional and Data Mining Analysis for Property Investment Risk Analysis

Authors: Nur Atiqah Rochin Demong, Jie Lu, Farookh Khadeer Hussain

Abstract:

Property investment in the real estate industry has a high risk due to the uncertainty factors that will affect the decisions made and high cost. Analytic hierarchy process has existed for some time in which referred to an expert-s opinion to measure the uncertainty of the risk factors for the risk analysis. Therefore, different level of experts- experiences will create different opinion and lead to the conflict among the experts in the field. The objective of this paper is to propose a new technique to measure the uncertainty of the risk factors based on multidimensional data model and data mining techniques as deterministic approach. The propose technique consist of a basic framework which includes four modules: user, technology, end-user access tools and applications. The property investment risk analysis defines as a micro level analysis as the features of the property will be considered in the analysis in this paper.

Keywords: Uncertainty factors, data mining, multidimensional data model, risk analysis.

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499 Investigating Determinants of Medical User Expectations from Hospital Information System

Authors: G. Gürsel, K. H. Gülkesen, N. Zayim, A. Arifoğlu, O. Saka

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User satisfaction is one of the most used success indicators in the research of information system (IS). Literature shows user expectations have great influence on user satisfaction. Both expectation and satisfaction of users are important for Hospital Information Systems (HIS). Education, IS experience, age, attitude towards change, business title, sex and working unit of the hospital, are examined as the potential determinant of the medical users’ expectations. Data about medical user expectations are collected by the “Expectation Questionnaire” developed for this study. Expectation data are used for calculating the Expectation Meeting Ratio (EMR) with the evaluation framework also developed for this study. The internal consistencies of the answers to the questionnaire are measured by Cronbach´s Alpha coefficient. The multivariate analysis of medical user’s EMRs of HIS is performed by forward stepwise binary logistic regression analysis. Education and business title is appeared to be the determinants of expectations from HIS.

Keywords: Evaluation, Fuzzy Logic, Hospital Information System, User Expectation.

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498 Robot Exploration and Navigation in Unseen Environments Using Deep Reinforcement Learning

Authors: Romisaa Ali

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This paper presents a comparison between twin-delayed Deep Deterministic Policy Gradient (TD3) and Soft Actor-Critic (SAC) reinforcement learning algorithms in the context of training robust navigation policies for Jackal robots. By leveraging an open-source framework and custom motion control environments, the study evaluates the performance, robustness, and transferability of the trained policies across a range of scenarios. The primary focus of the experiments is to assess the training process, the adaptability of the algorithms, and the robot’s ability to navigate in previously unseen environments. Moreover, the paper examines the influence of varying environment complexities on the learning process and the generalization capabilities of the resulting policies. The results of this study aim to inform and guide the development of more efficient and practical reinforcement learning-based navigation policies for Jackal robots in real-world scenarios.

Keywords: Jackal robot environments, reinforcement learning, TD3, SAC, robust navigation, transferability, Custom Environment.

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497 A Unified Robust Algorithm for Detection of Human and Non-human Object in Intelligent Safety Application

Authors: M A Hannan, A. Hussain, S. A. Samad, K. A. Ishak, A. Mohamed

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This paper presents a general trainable framework for fast and robust upright human face and non-human object detection and verification in static images. To enhance the performance of the detection process, the technique we develop is based on the combination of fast neural network (FNN) and classical neural network (CNN). In FNN, a useful correlation is exploited to sustain high level of detection accuracy between input image and the weight of the hidden neurons. This is to enable the use of Fourier transform that significantly speed up the time detection. The combination of CNN is responsible to verify the face region. A bootstrap algorithm is used to collect non human object, which adds the false detection to the training process of the human and non-human object. Experimental results on test images with both simple and complex background demonstrate that the proposed method has obtained high detection rate and low false positive rate in detecting both human face and non-human object.

Keywords: Algorithm, detection of human and non-human object, FNN, CNN, Image training.

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496 Video-Based Face Recognition Based On State-Space Model

Authors: Cheng-Chieh Chiang, Yi-Chia Chan, Greg C. Lee

Abstract:

This paper proposes a video-based framework for face recognition to identify which faces appear in a video sequence. Our basic idea is like a tracking task - to track a selection of person candidates over time according to the observing visual features of face images in video frames. Hence, we employ the state-space model to formulate video-based face recognition by dividing this problem into two parts: the likelihood and the transition measures. The likelihood measure is to recognize whose face is currently being observed in video frames, for which two-dimensional linear discriminant analysis is employed. The transition measure estimates the probability of changing from an incorrect recognition at the previous stage to the correct person at the current stage. Moreover, extra nodes associated with head nodes are incorporated into our proposed state-space model. The experimental results are also provided to demonstrate the robustness and efficiency of our proposed approach.

Keywords: 2DLDA, face recognition, state-space model, likelihood measure, transition measure.

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495 Towards Incorporating Context Awareness into Business Process Management

Authors: Xiaohui Zhao, Shahan Mafuz

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Context-aware technologies provide system applications with the awareness of environmental conditions, customer behaviours, object movements, etc. Further, with such capability system applications can be smart to intelligently adapt their responses to the changing conditions. In regard to business operations, this promises businesses that their business processes can run more intelligently, adaptively and flexibly, and thereby either improve customer experience, enhance reliability of service delivery, or lower operational cost, to make the business more competitive and sustainable. Aiming at realising such context-aware business process management, this paper firstly explores its potential benefit, and then identifies some gaps between the current business process management support and the expected. In addition, some preliminary solutions are also discussed in regard to context definition, rule-based process execution, run-time process evolution, etc. A framework is also presented to give a conceptual architecture of context-aware business process management system to guide system implementation.

Keywords: Business process adaptation, business process evolution, business process modelling, and context awareness.

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494 Uncertainty Analysis of a Hardware in Loop Setup for Testing Products Related to Building Technology

Authors: Balasundaram Prasaant, Ploix Stephane, Delinchant Benoit, Muresan Cristian

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Hardware in Loop (HIL) testing is done to test and validate a particular product especially in building technology. When it comes to building technology, it is more important to test the products for their efficiency. The test rig in the HIL simulator may contribute to some uncertainties on measured efficiency. The uncertainties include physical uncertainties and scenario-based uncertainties. In this paper, a simple uncertainty analysis framework for an HIL setup is shown considering only the physical uncertainties. The entire modeling of the HIL setup is done in Dymola. The uncertain sources are considered based on available knowledge of the components and also on expert knowledge. For the propagation of uncertainty, Monte Carlo Simulation is used since it is the most reliable and easy to use. In this article it is shown how an HIL setup can be modeled and how uncertainty propagation can be performed on it. Such an approach is not common in building energy analysis.

Keywords: Energy in Buildings, Hardware in Loop, Modelica (Dymola), Monte Carlo Simulation, Uncertainty Propagation.

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493 A Framework of Monte Carlo Simulation for Examining the Uncertainty-Investment Relationship

Authors: George Yungchih Wang

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This paper argues that increased uncertainty, in certain situations, may actually encourage investment. Since earlier studies mostly base their arguments on the assumption of geometric Brownian motion, the study extends the assumption to alternative stochastic processes, such as mixed diffusion-jump, mean-reverting process, and jump amplitude process. A general approach of Monte Carlo simulation is developed to derive optimal investment trigger for the situation that the closed-form solution could not be readily obtained under the assumption of alternative process. The main finding is that the overall effect of uncertainty on investment is interpreted by the probability of investing, and the relationship appears to be an invested U-shaped curve between uncertainty and investment. The implication is that uncertainty does not always discourage investment even under several sources of uncertainty. Furthermore, high-risk projects are not always dominated by low-risk projects because the high-risk projects may have a positive realization effect on encouraging investment.

Keywords: real options, geometric Brownian motion, mixeddiffusion-jump process, mean- reverting process, jump amplitudeprocess

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492 Discrepant Views of Social Competence and Links with Social Phobia

Authors: Pamela-Zoe Topalli, Niina Junttila, Päivi M. Niemi, Klaus Ranta

Abstract:

Adolescents’ biased perceptions about their social competence (SC), whether negatively or positively, serve to influence their socioemotional adjustment such as early feelings of social phobia (nowadays referred to as Social Anxiety Disorder-SAD). Despite the importance of biased self-perceptions in adolescents’ psychosocial adjustment, the extent to which discrepancies between self- and others’ evaluations of one’s SC are linked to social phobic symptoms remains unclear in the literature. This study examined the perceptual discrepancy profiles between self- and peers’ as well as between self- and teachers’ evaluations of adolescents’ SC and the interrelations of these profiles with self-reported social phobic symptoms. The participants were 390 3rd graders (15 years old) of Finnish lower secondary school (50.8% boys, 49.2% girls). In contrast with variable-centered approaches that have mainly been used by previous studies when focusing on this subject, this study used latent profile analysis (LPA), a person-centered approach which can provide information regarding risk profiles by capturing the heterogeneity within a population and classifying individuals into groups. LPA revealed the following five classes of discrepancy profiles: i) extremely negatively biased perceptions of SC, ii) negatively biased perceptions of SC, iii) quite realistic perceptions of SC, iv) positively biased perceptions of SC, and v) extremely positively biased perceptions of SC. Adolescents with extremely negatively biased perceptions and negatively biased perceptions of their own SC reported the highest number of social phobic symptoms. Adolescents with quite realistic, positively biased and extremely positively biased perceptions reported the lowest number of socio-phobic symptoms. The results point out the negatively and the extremely negatively biased perceptions as possible contributors to social phobic symptoms. Moreover, the association of quite realistic perceptions with low number of social phobic symptoms indicates its potential protective power against social phobia. Finally, positively and extremely positively biased perceptions of SC are negatively associated with social phobic symptoms in this study. However, the profile of extremely positively biased perceptions might be linked as well with the existence of externalizing problems such as antisocial behavior (e.g. disruptive impulsivity). The current findings highlight the importance of considering discrepancies between self- and others’ perceptions of one’s SC in clinical and research efforts. Interventions designed to prevent or moderate social phobic symptoms need to take into account individual needs rather than aiming for uniform treatment. Implications and future directions are discussed.

Keywords: Adolescence, latent profile analysis, perceptual discrepancies, social competence, social phobia.

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491 Theoretical Literature Review on Lack of Cardiorespiratory Fitness and Its Effects on Children

Authors: E. Abdi

Abstract:

The purpose of this theoretical literature review is to study the relevant academic literature on lack of cardiorespiratory fitness and its effects on children. The total of thirty eight relevant documents were identified and considered for this review which nineteen of those were original research articles published in peer reviewed journals. The other nineteen articles were statistical documents. This literature review is structured to examine 5 effects in deficiency of cardiorespiratory fitness in school aged children (A) Relative Age Effect (RAE), (B) Obesity, (C) Inadequate fitness level (D) Unhealthy life style, and (E) Academics. The categories provide a theoretical framework for future studies where results are driven from the literature review. The study discusses that regular physical fitness assists children and adolescents to develop healthy physical activity behaviors which can be sustained throughout adult life. Conclusion suggests that advocacy for increasing physical activity and decreasing sedentary behaviors at school and home are necessary.

Keywords: Cardiorespiratory, endurance, physical activity, physical fitness.

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490 Efficacy of Selected Mobility Exercises and Participation in Special Games on Psychomotor Abilities, Functional Abilities and Game Performance among Intellectually Disabled Children of Under 14 Age

Authors: J. Samuel Jesudoss

Abstract:

The purpose of the study was to find out the efficacy of selected mobility exercises and participation in special games on psychomotor abilities, functional abilities and skill performance among intellectually disabled children of age group under 14. Thirty male students who were studying in Balar Kalvi Nilayam and YMCA College Special School, Chennai, acted as subjects for the study. They were only mild and moderate in intellectual disability. These students did not undergo any special training or coaching programme apart from their regular routine physical activity classes as a part of the curriculum in the school. They were attached at random, based on age in which 30 belonged to under 14 age group, which was divided into three equal group of ten for each experimental treatment. 10 students (Treatment group I) underwent calisthenics and special games participation, 10 students (Treatment group II) underwent aquatics and special games participation, 10 students (Treatment group III) underwent yoga and special games participation. The subjects were tested on selected criterion variables prior (pre test) and after twelve weeks of training (post test). The pre and post test data collected from three groups on functional abilities(self care, learning, capacity for independent living), psychomotor variables(static balance, eye hand coordination, simple reaction time test) and skill performance (bocce skill, badminton skill, table tennis skill) were statistically examined for significant difference, by applying the analysis ANACOVA. Whenever an 'F' ratio for adjusted test was found to be significant for adjusted post test means, Scheffe-s test was followed as a post-hoc test to determine which of the paired mean differences was significant. The result of the study showed that among under 14 age groups there was a significant improvement on selected criterion variables such as, Balance, Coordination, self-care and learning and also in Bocce, Badminton & Table Tennis skill performance, due to mobility exercises and participation in special games. However there were no significant differences among the groups.

Keywords: Functional ability, intellectually disabled, Mobility exercises, Psychomotor ability.

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