Search results for: Cognitive Complexity Measure
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2113

Search results for: Cognitive Complexity Measure

1843 Dynamic TDMA Slot Reservation Protocol for QoS Provisioning in Cognitive Radio Ad Hoc Networks

Authors: S. M. Kamruzzaman

Abstract:

In this paper, we propose a dynamic TDMA slot reservation (DTSR) protocol for cognitive radio ad hoc networks. Quality of Service (QoS) guarantee plays a critically important role in such networks. We consider the problem of providing QoS guarantee to users as well as to maintain the most efficient use of scarce bandwidth resources. According to one hop neighboring information and the bandwidth requirement, our proposed protocol dynamically changes the frame length and the transmission schedule. A dynamic frame length expansion and shrinking scheme that controls the excessive increase of unassigned slots has been proposed. This method efficiently utilizes the channel bandwidth by assigning unused slots to new neighboring nodes and increasing the frame length when the number of slots in the frame is insufficient to support the neighboring nodes. It also shrinks the frame length when half of the slots in the frame of a node are empty. An efficient slot reservation protocol not only guarantees successful data transmissions without collisions but also enhance channel spatial reuse to maximize the system throughput. Our proposed scheme, which provides both QoS guarantee and efficient resource utilization, be employed to optimize the channel spatial reuse and maximize the system throughput. Extensive simulation results show that the proposed mechanism achieves desirable performance in multichannel multi-rate cognitive radio ad hoc networks.

Keywords: TDMA, cognitive radio, ad hoc networks, QoSguarantee, dynamic frame length.

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1842 Enhancing the Performance of H.264/AVC in Adaptive Group of Pictures Mode Using Octagon and Square Search Pattern

Authors: S. Sowmyayani, P. Arockia Jansi Rani

Abstract:

This paper integrates Octagon and Square Search pattern (OCTSS) motion estimation algorithm into H.264/AVC (Advanced Video Coding) video codec in Adaptive Group of Pictures (AGOP) mode. AGOP structure is computed based on scene change in the video sequence. Octagon and square search pattern block-based motion estimation method is implemented in inter-prediction process of H.264/AVC. Both these methods reduce bit rate and computational complexity while maintaining the quality of the video sequence respectively. Experiments are conducted for different types of video sequence. The results substantially proved that the bit rate, computation time and PSNR gain achieved by the proposed method is better than the existing H.264/AVC with fixed GOP and AGOP. With a marginal gain in quality of 0.28dB and average gain in bitrate of 132.87kbps, the proposed method reduces the average computation time by 27.31 minutes when compared to the existing state-of-art H.264/AVC video codec.

Keywords: Block Distortion Measure, Block Matching Algorithms, H.264/AVC, Motion estimation, Search patterns, Shot cut detection.

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1841 Analysis of Six Sigma in the Aerospace Industry

Authors: Masimuddin Mohd Khaled

Abstract:

This paper subsidizes to the discussion of Six Sigma in the Aerospace Industry. The main aim of this report is to study the literature review of Six Sigma emphasizing on the aerospace industry. The implementation of Six Sigma stages are studied and how the improvement cycle ‘Define, Measure, Analyze, Improve and Control cycle’ (DMAIC) and the design process is ‘Define, Measure, Analyze, Design and Verify cycle’ (DMADV) is used. The focus is also done by studying how the implementation of Six Sigma on an aerospace company has brought a positive effect to the company.

Keywords: Six Sigma, DMAIC, DMADV, aerospace.

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1840 Wear Measuring and Wear Modelling Based On Archard, ASTM, and Neural Network Models

Authors: A. Shebani, C. Pislaru

Abstract:

The wear measuring and wear modelling are fundamental issues in the industrial field, mainly correlated to the economy and safety. Therefore, there is a need to study the wear measurements and wear estimation. Pin-on-disc test is the most common test which is used to study the wear behaviour. In this paper, the pin-on-disc (AEROTECH UNIDEX 11) is used for the investigation of the effects of normal load and hardness of material on the wear under dry and sliding conditions. In the pin-on-disc rig, two specimens were used; one, a pin is made of steel with a tip, positioned perpendicular to the disc, where the disc is made of aluminium. The pin wear and disc wear were measured by using the following instruments: The Talysurf instrument, a digital microscope, and the alicona instrument. The Talysurf profilometer was used to measure the pin/disc wear scar depth, digital microscope was used to measure the diameter and width of wear scar, and the alicona was used to measure the pin wear and disc wear. After that, the Archard model, American Society for Testing and Materials model (ASTM), and neural network model were used for pin/disc wear modelling. Simulation results were implemented by using the Matlab program. This paper focuses on how the alicona can be used for wear measurements and how the neural network can be used for wear estimation.

Keywords: Wear measuring, Wear modelling, Neural Network, Alicona.

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1839 Theoretical Exploration for the Impact of Accounting for Special Methods in Connectivity-Based Cohesion Measurement

Authors: Jehad Al Dallal

Abstract:

Class cohesion is a key object-oriented software quality attribute that is used to evaluate the degree of relatedness of class attributes and methods. Researchers have proposed several class cohesion measures. However, the effect of considering the special methods (i.e., constructors, destructors, and access and delegation methods) in cohesion calculation is not thoroughly theoretically studied for most of them. In this paper, we address this issue for three popular connectivity-based class cohesion measures. For each of the considered measures we theoretically study the impact of including or excluding special methods on the values that are obtained by applying the measure. This study is based on analyzing the definitions and formulas that are proposed for the measures. The results show that including/excluding special methods has a considerable effect on the obtained cohesion values and that this effect varies from one measure to another. For each of the three connectivity-based measures, the proposed theoretical study recommended excluding the special methods in cohesion measurement.

Keywords: Object-oriented class, software quality, class cohesion measure, class cohesion, special methods.

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1838 Unsupervised Image Segmentation Based on Fuzzy Connectedness with Sale Space Theory

Authors: Yuanjie Zheng, Jie Yang, Yue Zhou

Abstract:

In this paper, we propose an approach of unsupervised segmentation with fuzzy connectedness. Valid seeds are first specified by an unsupervised method based on scale space theory. A region is then extracted for each seed with a relative object extraction method of fuzzy connectedness. Afterwards, regions are merged according to the values between them of an introduced measure. Some theorems and propositions are also provided to show the reasonableness of the measure for doing mergence. Experiment results on a synthetic image, a color image and a large amount of MR images of our method are reported.

Keywords: Image segmentation, unsupervised imagesegmentation, fuzzy connectedness, scale space.

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1837 Simulating and Forecasting Qualitative Marcoeconomic Models Using Rule-Based Fuzzy Cognitive Maps

Authors: Spiros Mazarakis, George Matzavinos, Peter P. Groumpos

Abstract:

Economic models are complex dynamic systems with a lot of uncertainties and fuzzy data. Conventional modeling approaches using well known methods and techniques cannot provide realistic and satisfactory answers to today-s challenging economic problems. Qualitative modeling using fuzzy logic and intelligent system theories can be used to model macroeconomic models. Fuzzy Cognitive maps (FCM) is a new method been used to model the dynamic behavior of complex systems. For the first time FCMs and the Mamdani Model of Intelligent control is used to model macroeconomic models. This new model is referred as the Mamdani Rule-Based Fuzzy Cognitive Map (MBFCM) and provides the academic and research community with a new promising integrated advanced computational model. A new economic model is developed for a qualitative approach to Macroeconomic modeling. Fuzzy Controllers for such models are designed. Simulation results for an economic scenario are provided and extensively discussed

Keywords: Macroeconomic Models, Mamdani Rule Based- FCMs(MBFCMs), Qualitative and Dynamics System, Simulation.

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1836 Towards the Use of Software Product Metrics as an Indicator for Measuring Mobile Applications Power Consumption

Authors: Ching Kin Keong, Koh Tieng Wei, Abdul Azim Abd. Ghani, Khaironi Yatim Sharif

Abstract:

Maintaining factory default battery endurance rate over time in supporting huge amount of running applications on energy-restricted mobile devices has created a new challenge for mobile applications developer. While delivering customers’ unlimited expectations, developers are barely aware of efficient use of energy from the application itself. Thus, developers need a set of valid energy consumption indicators in assisting them to develop energy saving applications. In this paper, we present a few software product metrics that can be used as an indicator to measure energy consumption of Android-based mobile applications in the early of design stage. In particular, Trepn Profiler (Power profiling tool for Qualcomm processor) has used to collect the data of mobile application power consumption, and then analyzed for the 23 software metrics in this preliminary study. The results show that McCabe cyclomatic complexity, number of parameters, nested block depth, number of methods, weighted methods per class, number of classes, total lines of code and method lines have direct relationship with power consumption of mobile application.

Keywords: Battery endurance, software metrics, mobile application, power consumption.

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1835 A Survey on Performance Tools for OpenMP

Authors: Mubarak S. Mohsen, Rosni Abdullah, Yong M. Teo

Abstract:

Advances in processors architecture, such as multicore, increase the size of complexity of parallel computer systems. With multi-core architecture there are different parallel languages that can be used to run parallel programs. One of these languages is OpenMP which embedded in C/Cµ or FORTRAN. Because of this new architecture and the complexity, it is very important to evaluate the performance of OpenMP constructs, kernels, and application program on multi-core systems. Performance is the activity of collecting the information about the execution characteristics of a program. Performance tools consists of at least three interfacing software layers, including instrumentation, measurement, and analysis. The instrumentation layer defines the measured performance events. The measurement layer determines what performance event is actually captured and how it is measured by the tool. The analysis layer processes the performance data and summarizes it into a form that can be displayed in performance tools. In this paper, a number of OpenMP performance tools are surveyed, explaining how each is used to collect, analyse, and display data collection.

Keywords: Parallel performance tools, OpenMP, multi-core.

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1834 Expert Based System Design for Integrated Waste Management

Authors: A. Buruzs, M. F. Hatwágner, A. Torma, L. T. Kóczy

Abstract:

Recently, an increasing number of researchers have been focusing on working out realistic solutions to sustainability problems. As sustainability issues gain higher importance for organisations, the management of such decisions becomes critical. Knowledge representation is a fundamental issue of complex knowledge based systems. Many types of sustainability problems would benefit from models based on experts’ knowledge. Cognitive maps have been used for analyzing and aiding decision making. A cognitive map can be made of almost any system or problem. A fuzzy cognitive map (FCM) can successfully represent knowledge and human experience, introducing concepts to represent the essential elements and the cause and effect relationships among the concepts to model the behaviour of any system. Integrated waste management systems (IWMS) are complex systems that can be decomposed to non-related and related subsystems and elements, where many factors have to be taken into consideration that may be complementary, contradictory, and competitive; these factors influence each other and determine the overall decision process of the system. The goal of the present paper is to construct an efficient IWMS which considers various factors. The authors’ intention is to propose an expert based system design approach for implementing expert decision support in the area of IWMSs and introduces an appropriate methodology for the development and analysis of group FCM. A framework for such a methodology consisting of the development and application phases is presented.

Keywords: Factors, fuzzy cognitive map, group decision, integrated waste management system.

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1833 Undecimated Wavelet Transform Based Contrast Enhancement

Authors: Numan Unaldi, Samil Temel, Süleyman Demirci

Abstract:

A novel undecimated wavelet transform based contrast enhancement algorithmis proposed to for both gray scale andcolor images. Contrast enhancement is realized by tuning the magnitude of approximation coefficients at each level with respect to the approximation coefficients of one higher level during the inverse transform phase in a center/surround  enhancement sense.The performance of the proposed algorithm is evaluated using a statistical visual contrast measure (VCM). Experimental results on the proposed algorithm show improvement in terms of the VCM.

Keywords: Image enhancement, local contrast enhancement, visual contrast measure.

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1832 Using Project MIND - Math Is Not Difficult Strategies to Help Children with Autism Improve Mathematics Skills

Authors: Hui Fang Huang Su, Leanne Lai, Pei-Fen Li, Mei-Hwei Ho, Yu-Wen Chiu

Abstract:

This study aimed to provide a practical, systematic, and comprehensive intervention for children with Autism Spectrum Disorder (ASD). A pilot study of quasi-experimental pre-post intervention with control group design was conducted to evaluate if the mathematical intervention (Project MIND - Math Is Not Difficult) increases the math comprehension of children with ASD Children with ASD in the primary grades (K-1, 2) participated in math interventions to enhance their math comprehension and cognitive ability. The Bracken basic concept scale was used to evaluate subjects’ language skills, cognitive development, and school readiness. The study found that our systemic interventions of Project MIND significantly improved the mathematical and cognitive abilities in children with autism. The results of this study may lead to a major change in effective and adequate health care services for children with ASD and their families. All statistical analyses were performed with the IBM SPSS Statistics Version 25 for Windows. The significant level was set at 0.05 P-value.

Keywords: Young Children, Autism, Mathematics, Curriculum, teaching and learning, children with special needs, Project MIND.

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1831 Probe Selection for Pathway-Specific Microarray Probe Design Minimizing Melting Temperature Variance

Authors: Fabian Horn, Reinhard Guthke

Abstract:

In molecular biology, microarray technology is widely and successfully utilized to efficiently measure gene activity. If working with less studied organisms, methods to design custom-made microarray probes are available. One design criterion is to select probes with minimal melting temperature variances thus ensuring similar hybridization properties. If the microarray application focuses on the investigation of metabolic pathways, it is not necessary to cover the whole genome. It is more efficient to cover each metabolic pathway with a limited number of genes. Firstly, an approach is presented which minimizes the overall melting temperature variance of selected probes for all genes of interest. Secondly, the approach is extended to include the additional constraints of covering all pathways with a limited number of genes while minimizing the overall variance. The new optimization problem is solved by a bottom-up programming approach which reduces the complexity to make it computationally feasible. The new method is exemplary applied for the selection of microarray probes in order to cover all fungal secondary metabolite gene clusters for Aspergillus terreus.

Keywords: bottom-up approach, gene clusters, melting temperature, metabolic pathway, microarray probe design, probe selection

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1830 The Emotions in Consumers’ Decision Making: Review of Empirical Studies

Authors: Mikel Alonso López

Abstract:

This paper explores, in depth, the idea that emotions are present in all consumer decision making processes, meaning that purchase decisions have never been purely cognitive or as they traditionally have been defined, rational. Human beings, in all kinds of decisions, has "always" used neural systems related to emotions along with neural systems related to cognition, regardless of the type of purchase or the product or service in question. Therefore, all purchase decisions are, at the same time, cognitive and emotional. This paper presents an analysis of the main contributions of researchers in this regard.

Keywords: Emotions, decision making, consumer behavior.

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1829 Measurement of Intellectual Capital in an Algerian Company

Authors: S. Brahmi, S. Aitouche, M. D. Mouss

Abstract:

Every modern company should measure the value of its intellectual capital and to report to complement the traditional annual balance sheets. The purpose of this work is to measure the intellectual capital in an Algerian company (or production system) using the Weightless Wealth Tool Kit (WWTK). The results of the measurement of intellectual capital are supplemented by traditional financial ratios. The measurement was applied to the National Company of Wells Services (ENSP) in Hassi Messaoud city, in the south of Algeria. We calculated the intellectual capital (intangible resources) of the ENSP to help the organization to better capitalize on its potential of workers and their know-how. The intangible value of the ENSP is evaluated at 16,936,173,345 DA in 2015.

Keywords: Financial valuation, intangible capital, intellectual capital, intellectual capital measurement.

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1828 Reliability Factors Based Fuzzy Logic Scheme for Spectrum Sensing

Authors: Tallataf Rasheed, Adnan Rashdi, Ahmad Naeem Akhtar

Abstract:

The accurate spectrum sensing is a fundamental requirement of dynamic spectrum access for deployment of Cognitive Radio Network (CRN). To acheive this requirement a Reliability factors based Fuzzy Logic (RFL) Scheme for Spectrum Sensing has been proposed in this paper. Cognitive Radio User (CRU) predicts the presence or absence of Primary User (PU) using energy detector and calculates the Reliability factors which are SNR of sensing node, threshold of energy detector and decision difference of each node with other nodes in a cooperative spectrum sensing environment. Then the decision of energy detector is combined with Reliability factors of sensing node using Fuzzy Logic. These Reliability Factors used in RFL Scheme describes the reliability of decision made by a CRU to improve the local spectrum sensing. This Fuzzy combining scheme provides the accuracy of decision made by sensornode. The simulation results have shown that the proposed technique provide better PU detection probability than existing Spectrum Sensing Techniques.

Keywords: Cognitive radio, spectrum sensing, energy detector, reliability factors, fuzzy logic.

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1827 A Review on Important Aspects of Information Retrieval

Authors: Yogesh Gupta, Ashish Saini, A.K. Saxena

Abstract:

Information retrieval has become an important field of study and research under computer science due to explosive growth of information available in the form of full text, hypertext, administrative text, directory, numeric or bibliographic text. The research work is going on various aspects of information retrieval systems so as to improve its efficiency and reliability. This paper presents a comprehensive study, which discusses not only emergence and evolution of information retrieval but also includes different information retrieval models and some important aspects such as document representation, similarity measure and query expansion.

Keywords: Information Retrieval, query expansion, similarity measure, query expansion, vector space model.

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1826 Dual-Task – Immersion in the Interactions of Simultaneously Performed Tasks

Authors: M. Liebherr, P. Schubert, S. Kersten, C. Dietz, L. Franz, C. T. Haas

Abstract:

With a long history, dual-task has become one of the most intriguing research fields regarding human brain functioning and cognition. However, findings considering effects of taskinterrelations are limited (especially, in combined motor and cognitive tasks). Therefore, we aimed at developing a measurement system in order to analyse interrelation effects of cognitive and motor tasks. On the one hand, the present study demonstrates the applicability of the measurement system and on the other hand first results regarding a systematisation of different task combinations are shown. Future investigations should combine imagine technologies and this developed measurement system.

Keywords: Dual-task, interference, cognition, measurement.

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1825 Efficient Frontier - Comparing Different Volatility Estimators

Authors: Tea Poklepović, Zdravka Aljinović, Mario Matković

Abstract:

Modern Portfolio Theory (MPT) according to Markowitz states that investors form mean-variance efficient portfolios which maximizes their utility. Markowitz proposed the standard deviation as a simple measure for portfolio risk and the lower semi-variance as the only risk measure of interest to rational investors. This paper uses a third volatility estimator based on intraday data and compares three efficient frontiers on the Croatian Stock Market. The results show that range-based volatility estimator outperforms both mean-variance and lower semi-variance model.

Keywords: Variance, lower semi-variance, range-based volatility.

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1824 Identifying Factors for Evaluating Livability Potential within a Metropolis: A Case of Kolkata

Authors: Arpan Paul, Joy Sen

Abstract:

Livability is a holistic concept whose factors include many complex characteristics and levels of interrelationships among them. It has been considered as people’s need for public amenities and is recognized as a major element to create social welfare. The concept and principles of livability are essential for recognizing the significance of community well-being. The attributes and dimensions of livability are also important aspects to measure the overall quality of environment. Livability potential is mainly considered as the capacity to develop into the overall well-being of an urban area in future. The intent of the present study is to identify the prime factors to evaluate livability potential within a metropolis. For ground level case study, the paper has selected Kolkata Metropolitan Area (KMA) as it has wide physical, social, and economic variations within it. The initial part of the study deals with detailed literature review on livability and its significance of evaluating its potential within a metropolis. The next segment is dedicated for identifying the primary factors which would evaluate livability potential within a metropolis. In pursuit of identifying primary factors, which have a direct impact on urban livability, this study delineates the metropolitan area into various clusters, having their distinct livability potential. As a final outcome of the study, variations of livability potential of those selected clusters are highlighted to explain the complexity of the metropolitan development.

Keywords: Livability potential, metropolis, Kolkata Metropolitan Area (KMA), well-being.

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1823 Cognitive Virtual Exploration for Optimization Model Reduction

Authors: Livier Serna, Xavier Fischer, Fouad Bennis

Abstract:

In this paper, a decision aid method for preoptimization is presented. The method is called “negotiation", and it is based on the identification, formulation, modeling and use of indicators defined as “negotiation indicators". These negotiation indicators are used to explore the solution space by means of a classbased approach. The classes are subdomains for the negotiation indicators domain. They represent equivalent cognitive solutions in terms of the negotiation indictors being used. By this method, we reduced the size of the solution space and the criteria, thus aiding the optimization methods. We present an example to show the method.

Keywords: Optimization Model Reduction, Pre-Optimization, Negotiation Process, Class-Making, Cognition Based VirtualExploration.

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1822 A Proposed Framework for Visualization to Teach Computer Science

Authors: Muhammed Yousoof, Mohd Sapiyan, Khaja Kamaluddin

Abstract:

Computer programming is considered a very difficult course by many computer science students. The reasons for the difficulties include cognitive load involved in programming, different learning styles of students, instructional methodology and the choice of the programming languages. To reduce the difficulties the following have been tried: pair programming, program visualization, different learning styles etc. However, these efforts have produced limited success. This paper reviews the problem and proposes a framework to help students overcome the difficulties involved.

Keywords: Cognitive Load, Instructional Models, LearningStyles, Program Visualization.

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1821 Compromise Ratio Method for Decision Making under Fuzzy Environment using Fuzzy Distance Measure

Authors: Debashree Guha, Debjani Chakraborty

Abstract:

The aim of this paper is to adopt a compromise ratio (CR) methodology for fuzzy multi-attribute single-expert decision making proble. In this paper, the rating of each alternative has been described by linguistic terms, which can be expressed as triangular fuzzy numbers. The compromise ratio method for fuzzy multi-attribute single expert decision making has been considered here by taking the ranking index based on the concept that the chosen alternative should be as close as possible to the ideal solution and as far away as possible from the negative-ideal solution simultaneously. From logical point of view, the distance between two triangular fuzzy numbers also is a fuzzy number, not a crisp value. Therefore a fuzzy distance measure, which is itself a fuzzy number, has been used here to calculate the difference between two triangular fuzzy numbers. Now in this paper, with the help of this fuzzy distance measure, it has been shown that the compromise ratio is a fuzzy number and this eases the problem of the decision maker to take the decision. The computation principle and the procedure of the compromise ratio method have been described in detail in this paper. A comparative analysis of the compromise ratio method previously proposed [1] and the newly adopted method have been illustrated with two numerical examples.

Keywords: Compromise ratio method, Fuzzy multi-attributesingle-expert decision making, Fuzzy number, Linguistic variable

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1820 Sidelobe Reduction in Cognitive Radio Systems Using Hybrid Technique

Authors: Atif Elahi, Ijaz Mansoor Qureshi, Mehreen Atif, Noor Gul

Abstract:

Orthogonal frequency division multiplexing (OFDM) is one of the best candidates for dynamic spectrum access due to its flexibility of spectrum shaping. However, the high sidelobes of the OFDM signal that result in high out-of-band radiation, introduce significant interference to the users operating in its vicinity. This problem becomes more critical in cognitive radio (CR) system that enables the secondary users (SUs) users to access the spectrum holes not used by the primary users (PUs) at that time. In this paper, we present a generalized OFDM framework that has a capability of describing any sidelobe suppression techniques, despite of whether one or a number of techniques are used. Based on that framework, we propose cancellation carrier (CC) technique in conjunction with the generalized sidelobe canceller (GSC) to reduce the out-of-band radiation in the region where the licensed users are operating. Simulation results show that the proposed technique can reduce the out-of-band radiation better when compared with the existing techniques found in the literature.

Keywords: Cognitive radio, cancellation carriers, generalized sidelobe canceller, out-of-band radiation, orthogonal frequency division multiplexing.

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1819 Quick Similarity Measurement of Binary Images via Probabilistic Pixel Mapping

Authors: Adnan A. Y. Mustafa

Abstract:

In this paper we present a quick technique to measure the similarity between binary images. The technique is based on a probabilistic mapping approach and is fast because only a minute percentage of the image pixels need to be compared to measure the similarity, and not the whole image. We exploit the power of the Probabilistic Matching Model for Binary Images (PMMBI) to arrive at an estimate of the similarity. We show that the estimate is a good approximation of the actual value, and the quality of the estimate can be improved further with increased image mappings. Furthermore, the technique is image size invariant; the similarity between big images can be measured as fast as that for small images. Examples of trials conducted on real images are presented.

Keywords: Big images, binary images, similarity, matching.

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1818 The Effect of Socio-Affective Variables in the Relationship between Organizational Trust and Employee Turnover Intention

Authors: Paula A. Cruise, Carvell McLeary

Abstract:

Employee turnover leads to lowered productivity, decreased morale and work quality, and psychological effects associated with employee separation and replacement. Yet, it remains unknown why talented employees willingly withdraw from organizations. This uncertainty is worsened as studies; a) priorities organizational over individual predictors resulting in restriction in range in turnover measurement; b) focus on actual rather than intended turnover thereby limiting conceptual understanding of the turnover construct and its relationship with other variables and; c) produce inconsistent findings across cultures, contexts and industries despite a clear need for a unified perspective. The current study addressed these gaps by adopting the theory of planned behavior (TPB) framework to examine socio-cognitive factors in organizational trust and individual turnover intentions among bankers and energy employees in Jamaica. In a comparative study of n=369 [nbank= 264; male=57 (22.73%); nenergy =105; male =45 (42.86)], it was hypothesized that organizational trust was a predictor of employee turnover intention, and the effect of individual, group, cognitive and socio-affective variables varied across industry. Findings from structural equation modelling confirmed the hypothesis, with a model of both cognitive and socio-affective variables being a better fit [CMIN (χ2) = 800.067, df = 364, p ≤ .000; CFI = 0.950; RMSEA = 0.057 with 90% C.I. (0.052 - 0.062); PCLOSE = 0.016; PNFI = 0.818 in predicting turnover intention. The findings are discussed in relation to socio-cognitive components of trust models and predicting negative employee behaviors across cultures and industries.

Keywords: Context-specific organizational trust, cross-cultural psychology, theory of planned behavior, employee turnover intention.

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1817 Prediction Modeling of Alzheimer’s Disease and Its Prodromal Stages from Multimodal Data with Missing Values

Authors: M. Aghili, S. Tabarestani, C. Freytes, M. Shojaie, M. Cabrerizo, A. Barreto, N. Rishe, R. E. Curiel, D. Loewenstein, R. Duara, M. Adjouadi

Abstract:

A major challenge in medical studies, especially those that are longitudinal, is the problem of missing measurements which hinders the effective application of many machine learning algorithms. Furthermore, recent Alzheimer's Disease studies have focused on the delineation of Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI) from cognitively normal controls (CN) which is essential for developing effective and early treatment methods. To address the aforementioned challenges, this paper explores the potential of using the eXtreme Gradient Boosting (XGBoost) algorithm in handling missing values in multiclass classification. We seek a generalized classification scheme where all prodromal stages of the disease are considered simultaneously in the classification and decision-making processes. Given the large number of subjects (1631) included in this study and in the presence of almost 28% missing values, we investigated the performance of XGBoost on the classification of the four classes of AD, NC, EMCI, and LMCI. Using 10-fold cross validation technique, XGBoost is shown to outperform other state-of-the-art classification algorithms by 3% in terms of accuracy and F-score. Our model achieved an accuracy of 80.52%, a precision of 80.62% and recall of 80.51%, supporting the more natural and promising multiclass classification.

Keywords: eXtreme Gradient Boosting, missing data, Alzheimer disease, early mild cognitive impairment, late mild cognitive impairment, multiclass classification, ADNI, support vector machine, random forest.

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1816 A New Similarity Measure on Intuitionistic Fuzzy Sets

Authors: Binyamin Yusoff, Imran Taib, Lazim Abdullah, Abd Fatah Wahab

Abstract:

Intuitionistic fuzzy sets as proposed by Atanassov, have gained much attention from past and latter researchers for applications in various fields. Similarity measures between intuitionistic fuzzy sets were developed afterwards. However, it does not cater the conflicting behavior of each element evaluated. We therefore made some modification to the similarity measure of IFS by considering conflicting concept to the model. In this paper, we concentrate on Zhang and Fu-s similarity measures for IFSs and some examples are given to validate these similarity measures. A simple modification to Zhang and Fu-s similarity measures of IFSs was proposed to find the best result according to the use of degree of indeterminacy. Finally, we mark up with the application to real decision making problems.

Keywords: Intuitionistic fuzzy sets, similarity measures, multicriteriadecision making.

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1815 Distributed Relay Selection and Channel Choice in Cognitive Radio Network

Authors: Hao He, Shaoqian Li

Abstract:

In this paper, we study the cooperative communications where multiple cognitive radio (CR) transmit-receive pairs competitive maximize their own throughputs. In CR networks, the influences of primary users and the spectrum availability are usually different among CR users. Due to the existence of multiple relay nodes and the different spectrum availability, each CR transmit-receive pair should not only select the relay node but also choose the appropriate channel. For this distributed problem, we propose a game theoretic framework to formulate this problem and we apply a regret-matching learning algorithm which is leading to correlated equilibrium. We further formulate a modified regret-matching learning algorithm which is fully distributed and only use the local information of each CR transmit-receive pair. This modified algorithm is more practical and suitable for the cooperative communications in CR network. Simulation results show the algorithm convergence and the modified learning algorithm can achieve comparable performance to the original regretmatching learning algorithm.

Keywords: cognitive radio, cooperative communication, relay selection, channel choice, regret-matching learning, correlated equilibrium.

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1814 Optimizing the Capacity of a Convolutional Neural Network for Image Segmentation and Pattern Recognition

Authors: Yalong Jiang, Zheru Chi

Abstract:

In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, capsule network, capacity optimization, character recognition, data augmentation; semantic segmentation.

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