Search results for: web-based group decision support system.

Authors: N.B. Serova, N.A. Toporkova

Abstract:

The purpose of the research was to determine effectiveness of habilitation of preschool children with cerebral palsy in the process of pedagogical support of their families. The author presents the study of psychology-pedagogical problems of families with preschool children with cerebral palsy and the universal program of pedagogical support of families. In the conclusion, the author determines effectiveness of social adaptation of children with cerebral palsy and their families.

Keywords: habilitation, cerebral palsy, pedagogical support, social adaptation

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Authors: Karel Frajtak, Miroslav Bures, Ivan Jelinek

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Software testing is important stage of software development cycle. Current testing process involves tester and electronic documents with test case scenarios. In this paper we focus on new approach to testing process using automated test case generation and tester guidance through the system based on the model of the system. Test case generation and model-based testing is not possible without proper system model. We aim on providing better feedback from the testing process thus eliminating the unnecessary paper work.

Keywords: Model based testing, test automation, test generating, tester support.

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Authors: Justine Jun

Abstract:

This study aims to reveal migrant women English instructors' workplace learning experiences in Canadian post-secondary institutions in Ontario. Migrant women English instructors in higher education are an understudied group of teachers. This study employs a qualitative research paradigm. Mezirow’s Transformative Learning Theory is an essential lens for the researcher to explain, analyze, and interpret the research data. It is a collaborative research project. The researcher and participants cooperatively create photographic or other artwork data responding to the research questions. Photovoice and arts-informed data collection methodology are the main methods. Research participants engage in the study as co-researchers and inquire about their own workplace learning experiences, actively utilizing their critical self-reflective and dialogic skills. Co-researchers individually select the forms of artwork they prefer to engage with to represent their transformative workplace learning experiences about the Canadian workplace cultures that they underwent while working with colleagues and administrators in the workplace. Once the co-researchers generate their cultural artifacts as research data, they collaboratively interpret their artworks with the researcher and other volunteer co-researchers. Co-researchers jointly investigate the themes emerging from the artworks. They also interpret the meanings of their own and others’ workplace learning experiences embedded in the artworks through interactive one-on-one or group interviews. The following are the research questions that the migrant women English instructor participants examine and answer: (1) What have they learned about their workplace culture and how do they explain their learning experiences? (2) How transformative have their learning experiences been at work? (3) How have their colleagues and administrators influenced their transformative learning? (4) What kind of support have they received? What supports have been valuable to them and what changes would they like to see? (5) What have their learning experiences transformed? (6) What has this arts-informed research process transformed? The study findings implicate English language instructor support currently practiced in post-secondary English language programs in Ontario, Canada, especially for migrant women English instructors. This research is a doctoral empirical study in progress. This study has the urgency to address the research problem that few studies have investigated migrant English instructors’ professional learning and support issues in the workplace, precisely that of English instructors working with adult learners in Canada. While appropriate social and professional support for migrant English instructors is required throughout the country, the present workplace realities in Ontario's English language programs need to be heard soon. For that purpose, the conceptualization of this study is crucial. It makes the investigation of under-represented instructors’ under-researched social phenomena, workplace learning and support, viable and rigorous. This paper demonstrates the robust theorization of English instructors’ workplace experiences using Mezirow’s Transformative Learning Theory in the English language teacher education field. 

Keywords: English teacher education, professional learning, transformative learning theory, workplace learning.

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Authors: Ashkan Ebadi, Adam Krzyzak

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Recommender systems, also known as recommender engines, have become an important research area and are now being applied in various fields. In addition, the techniques behind the recommender systems have been improved over the time. In general, such systems help users to find their required products or services (e.g. books, music) through analyzing and aggregating other users’ activities and behavior, mainly in form of reviews, and making the best recommendations. The recommendations can facilitate user’s decision making process. Despite the wide literature on the topic, using multiple data sources of different types as the input has not been widely studied. Recommender systems can benefit from the high availability of digital data to collect the input data of different types which implicitly or explicitly help the system to improve its accuracy. Moreover, most of the existing research in this area is based on single rating measures in which a single rating is used to link users to items. This paper proposes a highly accurate hotel recommender system, implemented in various layers. Using multi-aspect rating system and benefitting from large-scale data of different types, the recommender system suggests hotels that are personalized and tailored for the given user. The system employs natural language processing and topic modelling techniques to assess the sentiment of the users’ reviews and extract implicit features. The entire recommender engine contains multiple sub-systems, namely users clustering, matrix factorization module, and hybrid recommender system. Each sub-system contributes to the final composite set of recommendations through covering a specific aspect of the problem. The accuracy of the proposed recommender system has been tested intensively where the results confirm the high performance of the system.

Keywords: Tourism, hotel recommender system, hybrid, implicit features.

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Authors: Shouzhen Zeng

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We present a new intuitionistic fuzzy aggregation operator called the intuitionistic fuzzy ordered weighted averaging-weighted average (IFOWAWA) operator. The main advantage of the IFOWAWA operator is that it unifies the OWA operator with the WA in the same formulation considering the degree of importance that each concept has in the aggregation. Moreover, it is able to deal with an uncertain environment that can be assessed with intuitionistic fuzzy numbers. We study some of its main properties and we see that it has a lot of particular cases such as the intuitionistic fuzzy weighted average (IFWA) and the intuitionistic fuzzy OWA (IFOWA) operator. Finally, we study the applicability of the new approach on a financial decision making problem concerning the selection of financial strategies.

Keywords: Intuitionistic fuzzy numbers, Weighted average, OWA operator, Financial decision making

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Authors: Seyedvahid Najafi, Viliam Makis

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In recent years, maintenance optimization has attracted special attention due to the growth of industrial systems complexity. Maintenance costs are high for many systems, and preventive maintenance is effective when it increases operations' reliability and safety at a reduced cost. The novelty of this research is to consider general repair in the modeling of multi-unit series systems and solve the maintenance problem for such systems using the semi-Markov decision process (SMDP) framework. We propose an opportunistic maintenance policy for a series system composed of two main units. Unit 1, which is more expensive than unit 2, is subjected to condition monitoring, and its deterioration is modeled using a gamma process. Unit 1 hazard rate is estimated by the proportional hazards model (PHM), and two hazard rate control limits are considered as the thresholds of maintenance interventions for unit 1. Maintenance is performed on unit 2, considering an age control limit. The objective is to find the optimal control limits and minimize the long-run expected average cost per unit time. The proposed algorithm is applied to a numerical example to compare the effectiveness of the proposed policy (policy Ⅰ) with policy Ⅱ, which is similar to policy Ⅰ, but instead of general repair, replacement is performed. Results show that policy Ⅰ leads to lower average cost compared with policy Ⅱ. 

Keywords: Condition-based maintenance, proportional hazards model, semi-Markov decision process, two-unit series systems.

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Authors: Wei Zhang, Su-Yan Tang, Yi-Fan Zhu, Wei-Ping Wang

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Support vector regression (SVR) has been regarded as a state-of-the-art method for approximation and regression. The importance of kernel function, which is so-called admissible support vector kernel (SV kernel) in SVR, has motivated many studies on its composition. The Gaussian kernel (RBF) is regarded as a “best" choice of SV kernel used by non-expert in SVR, whereas there is no evidence, except for its superior performance on some practical applications, to prove the statement. Its well-known that reproducing kernel (R.K) is also a SV kernel which possesses many important properties, e.g. positive definiteness, reproducing property and composing complex R.K by simpler ones. However, there are a limited number of R.Ks with explicit forms and consequently few quantitative comparison studies in practice. In this paper, two R.Ks, i.e. SV kernels, composed by the sum and product of a translation invariant kernel in a Sobolev space are proposed. An exploratory study on the performance of SVR based general R.K is presented through a systematic comparison to that of RBF using multiple criteria and synthetic problems. The results show that the R.K is an equivalent or even better SV kernel than RBF for the problems with more input variables (more than 5, especially more than 10) and higher nonlinearity.

Keywords: admissible support vector kernel, reproducing kernel, reproducing kernel Hilbert space, support vector regression.

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Authors: Anwar Kashgari

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COVID-19 has severe impacts on business all over the world. The great lockdown of many business owners requires a sage deal with this pandemic. This paper seeks to support business leaders with a standpoint about the COVID-19 situation and provides implications for the SMEs (Small and Medium Enterprises) and companies. The paper reflects the author's view about the impact of COVID-19 on business activities. We discussed the impact of COVID-19 upon three aspects, namely, startups, SMEs, and e-commerce. The KSA is taken as an example of the developing countries about which we present the current situation. Finally, recommendations to policy and decision-makers are given.

Keywords: COVID-19, business networking, globalization, Saudi Arabia.

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Authors: Fei Ping Por, Soon Fook Fong

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The proposed Multimedia Pronunciation Learning Management System (MPLMS) in this study is a technology with profound potential for inducing improvement in pronunciation learning. The MPLMS optimizes the digitised phonetic symbols with the integration of text, sound and mouth movement video. The components are designed and developed in an online management system which turns the web to a dynamic user-centric collection of consistent and timely information for quality sustainable learning. The aim of this study is to design and develop the MPLMS which serves as an innovative tool to improve English pronunciation. This paper discusses the iterative methodology and the three-phase Alessi and Trollip model in the development of MPLMS. To align with the flexibility of the development of educational software, the iterative approach comprises plan, design, develop, evaluate and implement is followed. To ensure the instructional appropriateness of MPLMS, the instructional system design (ISD) model of Alessi and Trollip serves as a platform to guide the important instructional factors and process. It is expected that the results of future empirical research will support the efficacy of MPLMS and its place as the premier pronunciation learning system.

Keywords: Design, development, multimedia, pronunciation, learning management system

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Authors: P. Aragonés-Beltrán, F. Chaparro-González, J. P. Pastor Ferrando, M. García-Melón

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In this paper the Analytic Network Process (ANP) is applied to the selection of photovoltaic (PV) solar power projects. These projects follow a long management and execution process from plant site selection to plant start-up. As a consequence, there are many risks of time delays and even of project stoppage. In the case study presented in this paper a top manager of an important Spanish company that operates in the power market has to decide on the best PV project (from four alternative projects) to invest based on risk minimization. The manager identified 50 project execution delay and/or stoppage risks. The influences among elements of the network (groups of risks and alternatives) were identified and analyzed using the ANP multicriteria decision analysis method. After analyzing the results the main conclusion is that the network model can manage all the information of the real-world problem and thus it is a decision analysis model recommended by the authors. The strengths and weaknesses ANP as a multicriteria decision analysis tool are also described in the paper.

Keywords: Multicriteria decision analysis, Analytic Network Process, Photovoltaic solar power projects.

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Authors: Nooshin Salari, Viliam Makis, Jane Doe

Abstract:

This paper presents a maintenance policy for a system consisting of two units. Unit 1 is gradually deteriorating and is subject to soft failure. Unit 2 has a general lifetime distribution and is subject to hard failure. Condition of unit 1 of the system is monitored periodically and it is considered as failed when its deterioration level reaches or exceeds a critical level N. At the failure time of unit 2 system is considered as failed, and unit 2 will be correctively replaced by the next inspection epoch. Unit 1 or 2 are preventively replaced when deterioration level of unit 1 or age of unit 2 exceeds the related preventive maintenance (PM) levels. At the time of corrective or preventive replacement of unit 2, there is an opportunity to replace unit 1 if its deterioration level reaches the opportunistic maintenance (OM) level. If unit 2 fails in an inspection interval, system stops operating although unit 1 has not failed. A mathematical model is derived to find the preventive and opportunistic replacement levels for unit 1 and preventive replacement age for unit 2, that minimize the long run expected average cost per unit time. The problem is formulated and solved in the semi-Markov decision process (SMDP) framework. Numerical example is provided to illustrate the performance of the proposed model and the comparison of the proposed model with an optimal policy without opportunistic maintenance level for unit 1 is carried out.

Keywords: Condition-based maintenance, opportunistic maintenance, preventive maintenance, two-unit system.

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Authors: Mustafa M. Donma

Abstract:

Metabolic syndrome (MetS) is characterized by a series of biochemical, physiological and anthropometric indicators and is a life-threatening health problem due to its close association with chronic diseases such as obesity, diabetes mellitus, hypertension, cancer and cardiovascular diseases. The syndrome deserves great interest both in adults and children. Particularly, children with morbid obesity have a great tendency to develop the disease. The diagnostic decision is not so easy and may not be complete particularly in the pediatric population. Therefore, preventive measures should be considered at this stage. The aim of the study was to develop a MetS index capable of predicting MetS, while children are at the morbid obesity stage. This study was performed on morbid obese (MO) children, which were divided into two groups. MO children, who do not possess MetS criteria comprised the first group (n = 44). The second group was composed of children with MetS diagnosis (n = 42). Anthropometric measurements including weight, height, waist circumference (WC), hip C, head C, neck C, biochemical tests including fasting blood glucose (FBG), insulin (INS), triglycerides (TRG), high density lipoprotein cholesterol (HDL-C) and blood pressure measurements (systolic (SBP) and diastolic (DBP)) were performed. Body fat percentage (BFP) values were determined by TANITA’s Bioelectrical Impedance Analysis technology. Body mass index and MetS indices were calculated. Descriptive statistics including median values, t-test, Mann Whitney U test, correlation-regression analysis were performed within the scope of data evaluation using the statistical package program, SPSS. Statistically significant mean differences were determined by a p value smaller than 0.05. Median values for MetSI and ADMI in MO (MetS-) and MO (MetS+) groups were calculated as 25.9 and 36.5 and 74.0 and 106.1, respectively. Corresponding mean ± SD values for BFPs were 35.9 ± 7.1 and 38.2 ± 7.7 in groups. Correlation analysis of these two indices with corresponding general BFP values exhibited significant association with ADMI, close to significance with MetSI in MO group. Any significant correlation was found with neither of the indices in MetS group. In conclusion, important associations observed with MetS indices in MO group were quite meaningful. The presence of these associations in MO group was important for showing the tendency towards the development of MetS in MO (MetS-) participants. The other index, ADMI, was more helpful for predictive purpose.

Keywords: Body fat percentage, child obesity, metabolic syndrome index, morbid obesity.

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Authors: Xun Ge, Jingju Qian

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To investigate some relations between higher mathe¬matics scores in Chinese graduate student entrance examination and calculus (resp. linear algebra, probability statistics) scores in subject's completion examination of Chinese university, we select 20 students as a sample, take higher mathematics score as a decision attribute and take calculus score, linear algebra score, probability statistics score as condition attributes. In this paper, we are based on rough-set theory (Rough-set theory is a logic-mathematical method proposed by Z. Pawlak. In recent years, this theory has been widely implemented in the many fields of natural science and societal science.) to investigate importance of condition attributes with respective to decision attribute and strength of condition attributes supporting decision attribute. Results of this investigation will be helpful for university students to raise higher mathematics scores in Chinese graduate student entrance examination.

Keywords: Rough set, higher mathematics scores, decision attribute, condition attribute.

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Authors: S. N. F. Mohd Fauzi, N. Yusof, N. Zainul Abidin

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When the Malaysian government announced the implementation of the Build-Then-Sell (BTS) system in 2007, the proponents of the BTS have argued that the implementation of this new system may provide houses with low defects. However, there has been no empirical data to support their argument. Therefore, this study is conducted to measure the level of housing defects in the BTS housing delivery system. A survey was conducted to the occupiers in six BTS residential areas. The BTS residential areas have been identified through the media and because of the small number of population, all households in the BTS residential areas were required to participate in the study to enable the researcher to collect the data concerning defects. Questionnaire had been employed as the data collection instrument and was distributed to the respondents of this study. The result has shown that the level of defects in the BTS houses is low, as the rate of defects for all elements are slight. Such low level of defects has apparently only affected the aesthetic value of the houses.

Keywords: Build-Then-Sell houses, housing defects, residentialareas, occupiers

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Authors: Nevine M. Labib, Michael N. Malek

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Data Mining aims at discovering knowledge out of data and presenting it in a form that is easily comprehensible to humans. One of the useful applications in Egypt is the Cancer management, especially the management of Acute Lymphoblastic Leukemia or ALL, which is the most common type of cancer in children. This paper discusses the process of designing a prototype that can help in the management of childhood ALL, which has a great significance in the health care field. Besides, it has a social impact on decreasing the rate of infection in children in Egypt. It also provides valubale information about the distribution and segmentation of ALL in Egypt, which may be linked to the possible risk factors. Undirected Knowledge Discovery is used since, in the case of this research project, there is no target field as the data provided is mainly subjective. This is done in order to quantify the subjective variables. Therefore, the computer will be asked to identify significant patterns in the provided medical data about ALL. This may be achieved through collecting the data necessary for the system, determimng the data mining technique to be used for the system, and choosing the most suitable implementation tool for the domain. The research makes use of a data mining tool, Clementine, so as to apply Decision Trees technique. We feed it with data extracted from real-life cases taken from specialized Cancer Institutes. Relevant medical cases details such as patient medical history and diagnosis are analyzed, classified, and clustered in order to improve the disease management.

Keywords: Data Mining, Decision Trees, Knowledge Discovery, Leukemia.

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Authors: Jisun Mo, Paola Boarin

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The impact of common buildings on climate and environment has prompted people to get involved in the green building standards aimed at implementing rating tools or certifications. Thus, green building rating systems were introduced to the construction industry, and the demand for certified green buildings has increased gradually and succeeded considerably in enhancing people’s environmental awareness. However, the existing certification process has been unsatisfactory in attracting stakeholders and/or professionals who are actively engaged in adopting a rating system. It is because they have faced recurring barriers regarding limited information in understanding the rating process, time-consuming procedures and higher costs, which have a direct influence on pursuing green building rating systems. To promote the achievement of green building certifications within the building industry more successfully, this paper aims at designing a Pre-Assessment Tool (PAT) framework that can help stakeholders and/or professionals engaged in the construction industry to clarify their basic knowledge, timeframe and extra costs needed to activate a green building certification. First, taking the first steps towards the rating tool seems to be complicated because of upfront commitment to understanding the overall rating procedure is required. This conceptual PAT framework can increase basic knowledge of the rating tool and the certification process, mainly in terms of all resources or information of each credit requirements. Second, the assessment process of rating tools is generally known as a “lengthy and time-consuming system”, contributing to unenthusiastic reactions concerning green building projects. The proposed framework can predict the timeframe needed to identify how long it will take for a green project to process each credit requirement and the documentation required from the beginning of the certification process to final approval. Finally, most people often have the initial perception that pursuing green building certification costs more than constructing a non-green building, which makes it more difficult to execute rating tools. To overcome this issue, this PAT will help users to estimate the extra expenses such as certification fees and third-party contributions based on the track of the amount of time it takes to implement the rating tool throughout all the related stages. Also, it can prevent unexpected or hidden costs occurring in the process of assessment. Therefore, this proposed PAT framework can be recommended as an effective method to support the decision-making of inexperienced users and play an important role in promoting green building certification.

Keywords: Barriers, certification process, green building rating systems, pre-assessment tool.

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Authors: Pavol Molnar, Martin Dolinsky

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Paper deals with environmental metrics and assessment systems devoted to Small and Medium Sized Enterprises. Authors are presenting proposed assessment model which has an ability to discover current environmental strengths and weaknesses of Small and Middle Sized Enterprise. Suggested model has also an ambition to become a Sustainability Decision Tool. Model is able to identify "best environmental devision" in the company, and to quantify how this decision contributed into overall environmental improvement. Authors understand environmental improvements as environmental innovations (product, process and organizational). Suggested model is based on its own concept; however, authors are also utilizing already existing environmental assessment tools.

Keywords: Corporate Social Responsibility, (e)IMPACT model, Environmental metrics, , Small and Middle Sized Enterprises

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Authors: Robin C. Ladwig

Abstract:

The future of work becomes less predictable which requires increasing adaptability of organizations to social and work changes. Society is transforming regarding gender identity in the sense that more people come forward to identify as trans and gender diverse (TGD). Organizations are ill-equipped to provide a safe and encouraging work environment by lacking inclusive organizational structures. The qualitative multi-method research about TGD inclusivity in the workplace explores the enablers and barriers for TGD individuals to satisfactorily engage in the work environment and organizational culture. Furthermore, these TGD insights are analyzed based on organizational implications and awareness from a leadership and management perspective. The semi-structured online interviews with TGD individuals and the photo-elicit open-ended questionnaire addressed to leadership and management in diversity, career development, and human resources have been analyzed with a critical grounded theory approach. Findings demonstrated the significance of TGD voices, the support of leadership and management, as well as the synergy between voices and leadership. Hence, it indicates practical implications such as the revision of exclusive language used in policies, data collection, or communication and reconsideration of organizational decision-making by leaders to include TGD voices.

Keywords: Future of work, occupational identity, organizational decision-making, trans and gender diverse identity.

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Authors: Siti Azrina B. A. Aziz, Siti Hafizah A. Hamid

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New approaches to analyze and visualize data stream in real-time basis is important in making a prompt decision by the decision maker. Financial market trading and surveillance, large-scale emergency response and crowd control are some example scenarios that require real-time analytic and data visualization. This situation has led to the development of techniques and tools that support humans in analyzing the source data. With the emergence of Big Data and social media, new techniques and tools are required in order to process the streaming data. Today, ranges of tools which implement some of these functionalities are available. In this paper, we present chronological evolution evaluation of technologies for supporting of real-time analytic and visualization of the data stream. Based on the past research papers published from 2002 to 2014, we gathered the general information, main techniques, challenges and open issues. The techniques for streaming text visualization are identified based on Text Visualization Browser in chronological order. This paper aims to review the evolution of streaming text visualization techniques and tools, as well as to discuss the problems and challenges for each of identified tools.

Keywords: Information visualization, visual analytics, text mining, visual text analytics tools, big data visualization.

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Authors: José M. Merigó, Montserrat Casanovas

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We study different types of aggregation operators and the decision making process with minimization of regret. We analyze the original work developed by Savage and the recent work developed by Yager that generalizes the MMR method creating a parameterized family of minimal regret methods by using the ordered weighted averaging (OWA) operator. We suggest a new method that uses different types of geometric operators such as the weighted geometric mean or the ordered weighted geometric operator (OWG) to generalize the MMR method obtaining a new parameterized family of minimal regret methods. The main result obtained in this method is that it allows to aggregate negative numbers in the OWG operator. Finally, we give an illustrative example.

Keywords: Decision making, Regret, Aggregation operators, OWA operator, OWG operator.

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Authors: Preetam Kumar

Abstract:

The number of users supported in a DS-CDMA cellular system is typically less than spreading factor (N), and the system is said to be underloaded. Overloading is a technique to accommodate more number of users than the spreading factor N. In O/O overloading scheme, the first set is assigned to the N synchronous users and the second set is assigned to the additional synchronous users. An iterative multistage soft decision interference cancellation (SDIC) receiver is used to remove high level of interference between the two sets. Performance is evaluated in terms of the maximum number acceptable users so that the system performance is degraded slightly compared to the single user performance at a specified BER. In this paper, the capacity of CDMA based O/O overloading scheme is evaluated with SDIC receiver. It is observed that O/O scheme using orthogonal Gold codes provides 25% channel overloading (N=64) for synchronous DS-CDMA system on an AWGN channel in the uplink at a BER of 1e-5.For a Rayleigh faded channel, the critical capacity is 40% at a BER of 5e-5 assuming synchronous users. But in practical systems, perfect chip timing is very difficult to maintain in the uplink.. We have shown that the overloading performance reduces to 11% for a timing synchronization error of 0.02Tc for a BER of 1e-5.

Keywords: DS-CDMA, Interference Cancellation, MultiuserDetection, Orthogonal codes, Overloading.

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Authors: К. R. Aida–Zade, C. Ardil, S. S. Rustamov

Abstract:

Statement of the automatic speech recognition problem, the assignment of speech recognition and the application fields are shown in the paper. At the same time as Azerbaijan speech, the establishment principles of speech recognition system and the problems arising in the system are investigated. The computing algorithms of speech features, being the main part of speech recognition system, are analyzed. From this point of view, the determination algorithms of Mel Frequency Cepstral Coefficients (MFCC) and Linear Predictive Coding (LPC) coefficients expressing the basic speech features are developed. Combined use of cepstrals of MFCC and LPC in speech recognition system is suggested to improve the reliability of speech recognition system. To this end, the recognition system is divided into MFCC and LPC-based recognition subsystems. The training and recognition processes are realized in both subsystems separately, and recognition system gets the decision being the same results of each subsystems. This results in decrease of error rate during recognition. The training and recognition processes are realized by artificial neural networks in the automatic speech recognition system. The neural networks are trained by the conjugate gradient method. In the paper the problems observed by the number of speech features at training the neural networks of MFCC and LPC-based speech recognition subsystems are investigated. The variety of results of neural networks trained from different initial points in training process is analyzed. Methodology of combined use of neural networks trained from different initial points in speech recognition system is suggested to improve the reliability of recognition system and increase the recognition quality, and obtained practical results are shown.

Keywords: Speech recognition, cepstral analysis, Voice activation detection algorithm, Mel Frequency Cepstral Coefficients, features of speech, Cepstral Mean Subtraction, neural networks, Linear Predictive Coding.

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Authors: C. Ardil

Abstract:

Multiple criteria decision making analysis (MCDMA) methods are applied to many real - life problems in different fields of engineering science and technology. The "preference analysis for reference ideal solution (PARIS)" method is proposed for an efficient MCDMA evaluation of decision problems. The multiple criteria aircraft evaluation approach is based on the integrated the mean weight, entropy weight, PARIS, and TOPSIS method, which eliminates the subjective importance weight assignment process. The evaluation criteria were identified from an extensive literature review of aircraft selection process. The aim of this study is to propose an efficient methodology for handling the aircraft selection process in which the proposed method solves effectively the MCDMA problem. A numerical example is presented to demonstrate the applicability and validity of the proposed MCDMA approach. 

Keywords: aircraft selection, aircraft, multiple criteria decision making, multiple criteria decision making analysis, mean weight, entropy weight, MCDMA, PARIS, TOPSIS, VIKOR, ELECTRE, PROMETHEE

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Authors: Xiaoyun Zhao, Rami Darwish, Anna Pernestål

Abstract:

Automated vehicles (AVs) have the potential to enhance road capacity, improving road safety and traffic efficiency. Research and development on AVs have been going on for many years. However, when the complicated traffic rules and real situations interacted, AVs fail to make decisions on contradicting situations, and are not able to have control in all conditions due to highly dynamic driving scenarios. This limits AVs’ usage and restricts the full potential benefits that they can bring. Furthermore, regulations, infrastructure development, and public acceptance cannot keep up at the same pace as technology breakthroughs. Facing these challenges, this paper proposes automated vehicle traffic control tower (AVTCT) acting as a safe, efficient and integrated solution for AV control. It introduces a concept of AVTCT for control, management, decision-making, communication and interaction with various aspects in transportation. With the prototype demonstrations and simulations, AVTCT has the potential to overcome the control challenges with AVs and can facilitate AV reaching their full potential. Possible functionalities, benefits as well as challenges of AVTCT are discussed, which set the foundation for the conceptual model, simulation and real application of AVTCT.

Keywords: Automated vehicle, connectivity and automation, intelligent transport system, traffic control, traffic safety.

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Authors: Liping Li, Ke Li, Changchun Liu, Chengyu Liu, Yuanyang Li

Abstract:

A five-class density histogram with an index named cumulative density was proposed to analyze the short-term HRV. 150 subjects participated in the test, falling into three groups with equal numbers -- the healthy young group (Young), the healthy old group (Old), and the group of patients with congestive heart failure (CHF). Results of multiple comparisons showed a significant differences of the cumulative density in the three groups, with values 0.0238 for Young, 0.0406 for Old and 0.0732 for CHF (p<0.001). After 7 days and 14 days, 46 subjects from the Young and Old groups were retested twice following the same test protocol. Results showed good-to-excellent interclass correlations (ICC=0.783, 95% confidence interval 0.676-0.864). The Bland-Altman plots were used to reexamine the test-retest reliability. In conclusion, the method proposed could be a valid and reliable method to the short-term HRV assessment.

Keywords: Autonomic nervous system, congestive heart failure, heart rate variability, histogram.

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Authors: C. Ardil

Abstract:

In this paper, a new MCDMA approach, the permanent analytics process is proposed to assess the immovable valuation criteria and their significance in the placement of the healthcare facility. Five decision factors are considered for the value and selection of immovables. In the multiple factor selection problems, the priority vector of the criteria used to compare several immovables is first determined using the permanent analytics method, a mathematical model for the multiple criteria decisionmaking process. Then, to demonstrate the viability and efficacy of the suggested approach, twenty potential candidate locations were evaluated using the hospital site selection problem's decision criteria. The ranking accuracy of estimation was evaluated using composite programming, which took into account both the permanent analytics process and the weighted multiplicative model. 

Keywords: Hospital Facility Location Selection, Permanent Analytics Process, Multiple Criteria Decision Making (MCDM)

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Authors: Yun-na Wu, Zhen Wang

Abstract:

Due to the economic downturn and the deterioration of the living environment, the development of residential buildings as high energy consuming building is gradually changing from “extensive” to green building in China. So, the evaluation system of green building is continuously improved, but the current evaluation work has the following problems: (1) There are differences in the cost of the actual investment and the purchasing power of residents, also construction target of green residential building is single and lacks multi-objective performance development. (2) Green building evaluation lacks regional characteristics and cannot reflect the different regional residents demand. (3) In the process of determining the criteria weight, the experts’ judgment matrix is difficult to meet the requirement of consistency. Therefore, to solve those problems, questionnaires which are about the green residential building for Ningxia area are distributed, and the results of questionnaires can feedback the purchasing power of residents and the acceptance of the green building cost. Secondly, combined with the geographical features of Ningxia minority areas, the evaluation criteria system of green residential building is constructed. Finally, using the improved group AHP method and the grey clustering method, the criteria weight is determined, and a real case is evaluated, which is located in Xing Qing district, Ningxia. A conclusion can be obtained that the professional evaluation for this project and good social recognition is basically the same.

Keywords: Evaluation, green residential building, grey clustering method, group AHP.

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Authors: Hossein Ali Akbarpour, Fatemeh Dadkhah

Abstract:

This paper considers a multi criteria cell formation problem in Cellular Manufacturing System (CMS). Minimizing the number of voids and exceptional elements in cells simultaneously are two proposed objective functions. This problem is an Np-hard problem according to the literature, and therefore, we can-t find the optimal solution by an exact method. In this paper we developed two ant algorithms, Ant Colony Optimization (ACO) and Max-Min Ant System (MMAS), based on Data Envelopment Analysis (DEA). Both of them try to find the efficient solutions based on efficiency concept in DEA. Each artificial ant is considered as a Decision Making Unit (DMU). For each DMU we considered two inputs, the values of objective functions, and one output, the value of one for all of them. In order to evaluate performance of proposed methods we provided an experimental design with some empirical problem in three different sizes, small, medium and large. We defined three different criteria that show which algorithm has the best performance.

Keywords: Ant algorithm, Cellular manufacturing system, Data envelopment analysis, Efficiency

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Authors: F. Habib, A. Shokoohi

Abstract:

Urban problems are problems of organized complexity. Thus, many models and scientific methods to resolve urban problems are failed. This study is concerned with proposing of a fuzzy system driven approach for classification and solving urban problems. The proposed study investigated mainly the selection of the inputs and outputs of urban systems for classification of urban problems. In this research, five categories of urban problems, respect to fuzzy system approach had been recognized: control, polytely, optimizing, open and decision making problems. Grounded Theory techniques were then applied to analyze the data and develop new solving method for each category. The findings indicate that the fuzzy system methods are powerful processes and analytic tools for helping planners to resolve urban complex problems. These tools can be successful where as others have failed because both incorporate or address uncertainty and risk; complexity and systems interacting with other systems.

Keywords: Classification, complexity, Fuzzy theory, urban problems.

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Authors: U. Bottigli, R.Chiarucci, B. Golosio, G.L. Masala, P. Oliva, S.Stumbo, D.Cascio, F. Fauci, M. Glorioso, M. Iacomi, R. Magro, G. Raso

Abstract:

Purpose of this work is to develop an automatic classification system that could be useful for radiologists in the breast cancer investigation. The software has been designed in the framework of the MAGIC-5 collaboration. In an automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based generally on morphological lesion differences. A study in the space features representation is made and some classifiers are tested to distinguish the pathological regions from the healthy ones. The results provided in terms of sensitivity and specificity will be presented through the ROC (Receiver Operating Characteristic) curves. In particular the best performances are obtained with the Neural Networks in comparison with the K-Nearest Neighbours and the Support Vector Machine: The Radial Basis Function supply the best results with 0.89 ± 0.01 of area under ROC curve but similar results are obtained with the Probabilistic Neural Network and a Multi Layer Perceptron.

Keywords: Neural Networks, K-Nearest Neighbours, Support Vector Machine, Computer Aided Detection

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