Search results for: Association rules mining

Authors: Malinwo Estone Ayikpa

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Electric power systems are likely to operate with minimum losses and voltage meeting international standards. This is made possible generally by control actions provide by automatic voltage regulators, capacitors and transformers with on-load tap changer (OLTC). With the development of photovoltaic (PV) systems technology, their integration on distribution networks has increased over the last years to the extent of replacing the above mentioned techniques. The conventional analysis and simulation tools used for electrical networks are no longer able to take into account control actions necessary for studying distributed PV generation impact. This paper presents an unbalanced optimal power flow (OPF) model that minimizes losses with association of active power generation and reactive power control of single-phase and three-phase PV systems. Reactive power can be generated or absorbed using the available capacity and the adjustable power factor of the inverter. The unbalance OPF is formulated by current balance equations and solved by primal-dual interior point method. Several simulation cases have been carried out varying the size and location of PV systems and the results show a detailed view of the impact of PV distributed generation on distribution systems.

Keywords: Distribution system, losses, photovoltaic generation, primal-dual interior point method, reactive power control.

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Authors: Mehmet Altınöz

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Organizational communication is an administrative function crucial especially for executives in the implementation of organizational and administrative functions. Executives spend a significant part of their time on communicative activities. Doing his or her daily routine, arranging meeting schedules, speaking on the telephone, reading or replying to business correspondence, or fulfilling the control functions within the organization, an executive typically engages in communication processes. Efficient communication is the principal device for the adequate implementation of administrative and organizational activities. For this purpose, management needs to specify the kind of communication system to be set up and the kind of communication devices to be used. Communication is vital for any organization. In conventional offices, communication takes place within the hierarchical pyramid called the organizational structure, and is known as formal or informal communication. Formal communication is the type that works in specified structures within the organizational rules and towards the organizational goals. Informal communication, on the other hand, is the unofficial type taking place among staff as face-to-face or telephone interaction. Communication in virtual as well as conventional offices is essential for obtaining the right information in administrative activities and decision-making. Virtual communication technologies increase the efficiency of communication especially in virtual teams. Group communication is strengthened through an inter-group central channel. Further, ease of information transmission makes it possible to reach the information at the source, allowing efficient and correct decisions. Virtual offices can present as a whole the elements of information which conventional offices produce in different environments. At present, virtual work has become a reality with its pros and cons, and will probably spread very rapidly in coming years, in line with the growth in information technologies.

Keywords: Organization, conventional office, virtual office, communication, communication model, communication functions, communication methods, vertical communication, linear communication, diagonal communication

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Authors: Aya Salama

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Digital Twin has emerged as a compelling research area, capturing the attention of scholars over the past decade. It finds applications across diverse fields, including smart manufacturing and healthcare, offering significant time and cost savings. Notably, it often intersects with other cutting-edge technologies such as Data Mining, Artificial Intelligence, and Machine Learning. However, the concept of a Human Digital Twin (HDT) is still in its infancy and requires further demonstration of its practicality. HDT takes the notion of Digital Twin a step further by extending it to living entities, notably humans, who are vastly different from inanimate physical objects. The primary objective of this research was to create an HDT capable of automating real-time human responses by simulating human behavior. To achieve this, the study delved into various areas, including clustering, supervised classification, topic extraction, and sentiment analysis. The paper successfully demonstrated the feasibility of HDT for generating personalized responses in social messaging applications. Notably, the proposed approach achieved an overall accuracy of 63%, a highly promising result that could pave the way for further exploration of the HDT concept. The methodology employed Random Forest for clustering the question database and matching new questions, while K-nearest neighbor was utilized for sentiment analysis.

Keywords: Human Digital twin, sentiment analysis, topic extraction, supervised machine learning, unsupervised machine learning, classification and clustering.

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Authors: Tamer ElSerafi

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In recent approaches to heritage conservation, the whole context of historic areas becomes as important as the single historic building. This makes the provision of infrastructure and network of mobility an effective element in the urban conservation. Sustainable urban conservation projects consider the high density of activities, the need for a good quality access system to the transit system, and the importance of the configuration of the mobility network by identifying the best way to connect the different districts of the urban area through a complex unique system that helps the synergic development to achieve a sustainable mobility system. A sustainable urban mobility is a key factor in maintaining the integrity between socio-cultural aspects and functional aspects. This paper illustrates the mobility aspects, mobility problems in historic districts, and the needs of the mobility systems in the first part. The second part is a practical analysis for different mobility plans. It is challenging to find innovative and creative conservation solutions fitting modern uses and needs without risking the loss of inherited built resources. Urban mobility management is becoming an essential and challenging issue in the urban conservation projects. Depending on literature review and practical analysis, this paper tries to define and clarify the guidelines for mobility management in historic districts as a key element in sustainability of urban conservation and development projects. Such rules and principles could control the conflict between the socio–cultural and economic activities, and the different needs for mobility in these districts in a sustainable way. The practical analysis includes a comparison between mobility plans which have been implemented in four different cities; Freiburg in Germany, Zurich in Switzerland and Bray Town in Ireland. This paper concludes with a matrix of guidelines that considers both principles of sustainability and livability factors in urban historic districts.

Keywords: Sustainable mobility, urban mobility, mobility management, historic districts.

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Authors: Annamária Käferné Rácz, Bence Jáger, Balázs Kövesdi, László Dunai

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Due to the numerous advantages of steel corrugated web girders, its application field is growing for bridges as well as for buildings. The global stability behavior of such girders is significantly larger than those of conventional I-girders with flat web, thus the application of the structural steel material can be significantly reduced. Design codes and specifications do not provide clear and complete rules or recommendations for the determination of the lateral torsional buckling (LTB) resistance of corrugated web girders. Therefore, the authors made a thorough investigation regarding the LTB resistance of the corrugated web girders. Finite element (FE) simulations have been performed to develop new design formulas for the determination of the LTB resistance of trapezoidally corrugated web girders. FE model is developed considering geometrical and material nonlinear analysis using equivalent geometric imperfections (GMNI analysis). The equivalent geometric imperfections involve the initial geometric imperfections and residual stresses coming from rolling, welding and flame cutting. Imperfection sensitivity analysis was performed to determine the necessary magnitudes regarding only the first eigenmodes shape imperfections. By the help of the validated FE model, an extended parametric study is carried out to investigate the LTB resistance for different trapezoidal corrugation profiles. First, the critical moment of a specific girder was calculated by FE model. The critical moments from the FE calculations are compared to the previous analytical calculation proposals. Then, nonlinear analysis was carried out to determine the ultimate resistance. Due to the numerical investigations, new proposals are developed for the determination of the LTB resistance of trapezoidally corrugated web girders through a modification factor on the design method related to the conventional flat web girders.

Keywords: Critical moment, FE modeling, lateral torsional buckling, trapezoidally corrugated web girders.

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Authors: Marcela Karmazínová, Jindrich Melcher, Lubomír Vítek, Petr Cikrle

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The paper deals with the diagnostics of steel roof structure of the winter sports halls built in 1970 year. The necessity of the diagnostics has been given by the requirement to the evaluation design of this structure, which has been caused by the new situation in the field of the loadings given by the validity of the European Standards in the Czech Republic from 2010 year. Due to these changes in the normative rules, in practice existing structures are gradually subjected to the evaluation design and depending on its results to the strengthening or reconstruction, respectively. Steel roof is composed of plane truss main girders, purlins and bracings and the roof structure is supported by two arch main girders with the span of L = 84 m. The in situ diagnostics of the roof structure was oriented to the following parts: (i) determination and evaluation of the actual material properties of used steel and (ii) verification of the actual dimensions of the structural members. For the solution the nondestructive methods have been used for in situ measurement. For the indicative determination of steel strengths the modified method based on the determination of Rockwell’s hardness has been used. For the verification of the member’s dimensions (thickness of hollow sections) the ultrasound method has been used. This paper presents the results obtained using these testing methods and their evaluation, from the viewpoint of the usage for the subsequent static assessment and design evaluation of the existing structure. For the comparison, the examples of the similar evaluations realized for steel structures of the stadiums in Olomouc and Jihlava cities are briefly illustrated, too.

Keywords: Diagnostics, existing steel structure, sport hall, steel strength, indirect non-destructive methods, Rockwel’s hardness, destructive methods, actual dimensions, ultrasound method.

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Authors: I. Boroňová, J. Bernasovská, J. Kmec, E. Petrejčíková

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Dilated cardiomyopathy (DCM) is a severe cardiovascular disorder characterized by progressive systolic dysfunction due to cardiac chamber dilatation and inefficient myocardial contractility often leading to chronic heart failure. Recently, a genome-wide association studies (GWASs) on DCM indicate that the ZBTB17 gene rs10927875 single nucleotide polymorphism is associated with DCM. The aim of the study was to identify the distribution of ZBTB17 gene rs10927875 polymorphism in 50 Slovak patients with DCM and 80 healthy control subjects using the Custom Taqman®SNP Genotyping assays. Risk factors detected at baseline in each group included age, sex, body mass index, smoking status, diabetes and blood pressure. The mean age of patients with DCM was 52.9±6.3 years; the mean age of individuals in control group was 50.3±8.9 years. The distribution of investigated genotypes of rs10927875 polymorphism within ZBTB17 gene in the cohort of Slovak patients with DCM was as follows: CC (38.8%), CT (55.1%), TT (6.1%), in controls: CC (43.8%), CT (51.2%), TT (5.0%). The risk allele T was more common among the patients with dilated cardiomyopathy than in normal controls (33.7% versus 30.6%). The differences in genotype or allele frequencies of ZBTB17 gene rs10927875 polymorphism were not statistically significant (p=0.6908; p=0.6098). The results of this study suggest that ZBTB17 gene rs10927875 polymorphism may be a risk factor for susceptibility to DCM in Slovak patients with DCM. Studies of numerous files and additional functional investigations are needed to fully understand the roles of genetic associations.

Keywords: Dilated cardiomyopathy, SNP polymorphism, ZBTB17 gene.

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Authors: Hyun-Koo Kim, Ju H. Park, Ho-Youl Jung

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This paper presents an effective traffic lights recognition method at the daytime. First, Potential Traffic Lights Detector (PTLD) use whole color source of YCbCr channel image and make each binary image of green and red traffic lights. After PTLD step, Shape Filter (SF) use to remove noise such as traffic sign, street tree, vehicle, and building. At this time, noise removal properties consist of information of blobs of binary image; length, area, area of boundary box, etc. Finally, after an intermediate association step witch goal is to define relevant candidates region from the previously detected traffic lights, Adaptive Multi-class Classifier (AMC) is executed. The classification method uses Haar-like feature and Adaboost algorithm. For simulation, we are implemented through Intel Core CPU with 2.80 GHz and 4 GB RAM and tested in the urban and rural roads. Through the test, we are compared with our method and standard object-recognition learning processes and proved that it reached up to 94 % of detection rate which is better than the results achieved with cascade classifiers. Computation time of our proposed method is 15 ms.

Keywords: Traffic Light Detection, Multi-class Classification, Driving Assistance System, Haar-like Feature, Color SegmentationMethod, Shape Filter

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Authors: S. Wongkoon, M. Jaroensutasinee, K. Jaroensutasinee, W. Preechaporn, S. Chumkiew

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This study investigated the number of Aedes larvae, the key breeding sites of Aedes sp., and the relationship between climatic factors and the incidence of DHF in Samui Islands. We conducted our questionnaire and larval surveys from randomly selected 105 households in Samui Islands in July-September 2006. Pearson-s correlation coefficient was used to explore the primary association between the DHF incidence and all climatic factors. Multiple stepwise regression technique was then used to fit the statistical model. The results showed that the positive indoor containers were small jars, cement tanks, and plastic tanks. The positive outdoor containers were small jars, cement tanks, plastic tanks, used cans, tires, plastic bottles, discarded objects, pot saucers, plant pots, and areca husks. All Ae. albopictus larval indices (i.e., CI, HI, and BI) were higher than Ae. aegypti larval indices in this area. These larval indices were higher than WHO standard. This indicated a high risk of DHF transmission at Samui Islands. The multiple stepwise regression model was y = –288.80 + 11.024xmean temp. The mean temperature was positively associated with the DHF incidence in this area.

Keywords: Dengue vectors, Aedes aegypti, Aedes albopictus, Container Index, House Index, Breteau Index, Aedes indices, Climatic factors, Temperature.

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Authors: Marjan Mahdavi-Roshan, Arsalan Salari, Mahboobeh Gholipour, Moona Naghshbandi

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Background and objectives: Before any nutritional intervention, it is necessary to have the prospect of eating habits of people with cardiovascular risk factors. In this study, we assessed the adherence of healthy diet based on Mediterranean dietary pattern and related factors in adults in the north of Iran. Methods: This study was conducted on 550 men and women with cardiovascular risk factors that referred to Heshmat hospital in Rasht, northern Iran. Information was collected by interview and reading medical history and measuring anthropometric indexes. The Mediterranean Diet Adherence Screener was used for assessing dietary adherence, this screener was modified according to religious beliefs and culture of Iran. Results: The mean age of participants was 58±0.38 years. The mean of body mass index was 27±0.01 kg/m², and the mean of waist circumference was 98±0.2 cm. The mean of dietary adherence was 5.76±0.07. 45% of participants had low adherence, and just 4% had suitable adherence. The mean of dietary adherence in men was significantly higher than women (p=0. 07). Participants in rural area and high educational participants insignificantly had an unsuitable dietary Adherence. There was no significant association between some cardiovascular disease risk factors and dietary adherence. Conclusion: Education to different group about dietary intake correction and using a Mediterranean dietary pattern that is similar to dietary intake in the north of Iran, for controlling cardiovascular disease is necessary.

Keywords: Dietary adherence, Mediterranean dietary pattern, cardiovascular disease, north of Iran.

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Authors: Vikas Tewari, Shivendra Tewari, K. R. Pardasani

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Calcium is a vital second messenger used in signal transduction. Calcium controls secretion, cell movement, muscular contraction, cell differentiation, ciliary beating and so on. Two theories have been used to simplify the system of reaction-diffusion equations of calcium into a single equation. One is excess buffer approximation (EBA) which assumes that mobile buffer is present in excess and cannot be saturated. The other is rapid buffer approximation (RBA), which assumes that calcium binding to buffer is rapid compared to calcium diffusion rate. In the present work, attempt has been made to develop a model for calcium diffusion under excess buffer approximation in neuron cells. This model incorporates the effect of [Na+] influx on [Ca2+] diffusion,variable calcium and sodium sources, sodium-calcium exchange protein, Sarcolemmal Calcium ATPase pump, sodium and calcium channels. The proposed mathematical model leads to a system of partial differential equations which have been solved numerically using Forward Time Centered Space (FTCS) approach. The numerical results have been used to study the relationships among different types of parameters such as buffer concentration, association rate, calcium permeability.

Keywords: Excess buffer approximation, Na+ influx, sodium calcium exchange protein, sarcolemmal calcium atpase pump, forward time centred space.

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Authors: Mehrdad N. Khajavi , Golamhassan Paygane, Ali Hakima

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Vehicle which are turning or maneuvering at high speeds are susceptible to sliding and subsequently deviate from desired path. In this paper the dynamics governing the Yaw/Roll behavior of a vehicle has been simulated. Two different simulations have been used one for the real vehicle, for which a fuzzy controller is designed to increase its directional stability property. The other simulation is for a hypothetical vehicle with much higher tire cornering stiffness which is capable of developing the required lateral forces at the tire-ground patch contact to attain the desired lateral acceleration for the vehicle to follow the desired path without slippage. This simulation model is our reference model. The logic for keeping the vehicle on the desired track in the cornering or maneuvering state is to have some braking forces on the inner or outer tires based on the direction of vehicle deviation from the desired path. The inputs to our vehicle simulation model is steer angle δ and vehicle velocity V , and the outputs can be any kinematical parameters like yaw rate, yaw acceleration, side slip angle, rate of side slip angle and so on. The proposed fuzzy controller is a feed forward controller. This controller has two inputs which are steer angle δ and vehicle velocity V, and the output of the controller is the correcting moment M, which guides the vehicle back to the desired track. To develop the membership functions for the controller inputs and output and the fuzzy rules, the vehicle simulation has been run for 1000 times and the correcting moment have been determined by trial and error. Results of the vehicle simulation with fuzzy controller are very promising and show the vehicle performance is enhanced greatly over the vehicle without the controller. In fact the vehicle performance with the controller is very near the performance of the reference ideal model.

Keywords: Vehicle, Directional Stability, Fuzzy Logic Controller, ANFIS..

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Authors: Chan Eang Teng, Tang Mui Joo

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With the viral factor on social media, the sense of persuasion is generated by repetition and popularity. When users’ interest is captured, political awareness increases to spark political enthusiasm, but, the level of user’s political participation and political attitude of those active users is still questionable. An online survey on 250 youth and in-depth interview on two politicians are conducted to answer the main question in this paper. The result shows that Facebook significantly increases political awareness among youths. Social media may not be the major trigger to political activism among youths as most respondents opined that they would still vote without Facebook. Other factors could be political campaigning, political climate, age, peer pressure or others. Finding also shows that majority of respondents did not participate in online political debates or political groups. Many also wondered if the social media was the main power switch that triggers the political influx among young voters. The research finding is significant to understand how the new media, Facebook, has reshaped the political landscape in Malaysia, creating the Social Media Election that changed the rules of the political game. However, research finding does not support the ideal notion that the social media is the major trigger to youth’s political activism. This research outcome has exposed the flaws of the Social Media Election. It has revealed the less optimistic side of youth political activism. Unfortunately, results fall short of the idealistic belief that the social media have given rise to political activism among youths in the 13^th General Election in Malaysia. The research outcome also highlights an important lesson for the democratic discourse of Malaysia which is making informed and educated decisions takes more commitment, proactive and objective attitude.

Keywords: Social media, political participation, political activism, democracy, political communication.

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Authors: Fawad Hussain, Mohammad Basir Bin Saud, Mohd Azwardi Md Isa

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The aim of this study is to empirically investigate the mediating impact of export performance (EP) between technological advancement capabilities and business performance (BP) of Malaysian manufacturing micro, small and medium sized enterprises (MSME’s). Firm’s technological advancement resources are hypothesized as a platform to enhance both exports and BP of manufacturing MSMEs in Malaysia. This study is twofold, primary it has investigated that technological advancement capabilities helps to appreciates main performance measures noted in terms of EP and Secondly, it investigates that how efficiently and effectively technological advancement capabilities can contribute in overall Malaysian MSME’s BP. Smart PLS-3 statistical software is used to know the association between technological advancement capabilities, MSME’s EP and BP. In this study, the data was composed from Malaysian manufacturing MSME’s in east coast industrial zones known as the manufacturing hub of MSMEs. Seven hundred and fifty (750) questionnaires were distributed, but only 148 usable questionnaires are returned. The finding of this study indicated that technological advancement capabilities helps to strengthen the export in term of time and cost efficient and it plays a significant role in appreciating their BP. This study is helpful for small and medium enterprise owners who intend to expand their business overseas and though smart technological advancement resources they can achieve their business competitiveness and excellence both at local and international markets.

Keywords: Technological advancement capabilities, export performance, business performance, small and medium manufacturing enterprises, Malaysia.

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Authors: Md. Emaj Uddin

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This study compares family communication patterns in association with family socio-cultural status, especially marriage and family pattern, and couples- socio-economic status between Muslim and Santal communities in rural Bangladesh. A total of 288 couples, 145 couples from the Muslim and 143 couples from the Santal were randomly selected through cluster sampling procedure from Kalna village situated in Tanore Upazila of Rajshahi district of Bangladesh, where both the communities dwell as neighbors. In order to collect data from the selected samples, interview method with semistructural questionnaire schedule was applied. The responses given by the respondents were analyzed by Pearson-s chi-squire test and bivariate correlation techniques. The results of Pearson-s chi-squire test revealed that family communication patterns (X2= 25. 90, df= 2, p<0.01, p>0.05) were significantly different between the Muslim and Santal communities. In addition, Spearman-s bivariate correlation coefficients suggested that among the exogenous factors, family type (rs=.135, p<0.05) and occupation of both husband (rs= .197, p<0.01) and wife (rs= .265, p<0.01) were significantly positive associations, and marital arrangement (rs= -.177, p<0.01), education of husband (rs= -.108, p<0.05) and wife (rs= -.142, p<0.01 & p<0.05), and family income (rs= -.164, p<0.01) were significantly negative relations with the family communication patterns followed between the two communities, although age difference between husband and wife, family head and residence patterns were not significant relations with ones.

Keywords: Bangladesh, Cross-Cultural Comparison, Family Communication Patterns, Family Socio-Cultural Status, Muslim, Santal.

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Authors: R. Suresh, Pavan Kumar Nimmagadda, Ming Zo Tan, Shane Hart, Sharp Ugwuocha

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Polycrystalline diamond compact (PDC) drill bits are extensively used in the oil and gas industry as well as the mining industry. Industry engineers continually improve upon PDC drill bit designs and hydraulic conditions. Optimized injection nozzles play a key role in improving the drilling performance and efficiency of these ever changing PDC drill bits. In the first part of this study, computational fluid dynamics (CFD) modelling is performed to investigate the hydrodynamic characteristics of drilling fluid flow around the PDC drill bit. An Open-source CFD software – OpenFOAM simulates the flow around the drill bit, based on the field input data. A specifically developed console application integrates the entire CFD process including, domain extraction, meshing, and solving governing equations and post-processing. The results from the OpenFOAM solver are then compared with that of the ANSYS Fluent software. The data from both software programs agree. The second part of the paper describes the parametric study of the PDC drill bit nozzle to determine the effect of parameters such as number of nozzles, nozzle velocity, nozzle radial position and orientations on the flow field characteristics and bit washing patterns. After analyzing a series of nozzle configurations, the best configuration is identified and recommendations are made for modifying the PDC bit design.

Keywords: ANSYS Fluent, computational fluid dynamics, nozzle configuration, OpenFOAM, PDC dill bit.

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Authors: Parvinder S. Sandhu, Sandeep Khimta, Kiranpreet Kaur

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The prediction of Software quality during development life cycle of software project helps the development organization to make efficient use of available resource to produce the product of highest quality. “Whether a module is faulty or not" approach can be used to predict quality of a software module. There are numbers of software quality prediction models described in the literature based upon genetic algorithms, artificial neural network and other data mining algorithms. One of the promising aspects for quality prediction is based on clustering techniques. Most quality prediction models that are based on clustering techniques make use of K-means, Mixture-of-Guassians, Self-Organizing Map, Neural Gas and fuzzy K-means algorithm for prediction. In all these techniques a predefined structure is required that is number of neurons or clusters should be known before we start clustering process. But in case of Growing Neural Gas there is no need of predetermining the quantity of neurons and the topology of the structure to be used and it starts with a minimal neurons structure that is incremented during training until it reaches a maximum number user defined limits for clusters. Hence, in this work we have used Growing Neural Gas as underlying cluster algorithm that produces the initial set of labeled cluster from training data set and thereafter this set of clusters is used to predict the quality of test data set of software modules. The best testing results shows 80% accuracy in evaluating the quality of software modules. Hence, the proposed technique can be used by programmers in evaluating the quality of modules during software development.

Keywords: Growing Neural Gas, data clustering, fault prediction.

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Authors: Asina Gülerarslan

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Today-s children, who are born into a more colorful, more creative, more abstract and more accessible communication environment than their ancestors as a result of dizzying advances in technology, have an interesting capacity to perceive and make sense of the world. Millennium children, who live in an environment where all kinds of efforts by marketing communication are more intensive than ever are, from their early childhood on, subject to all kinds of persuasive messages. As regards advertising communication, it outperforms all the other marketing communication efforts in creating little consumer individuals and, as a result of processing of codes and signs, plays a significant part in building a world of seeing, thinking and understanding for children. Children who are raised with metaphorical expressions such as tales and riddles also meet that fast and effective meaning communication in advertisements. Children-s perception of metaphors, which help grasp the “product and its promise" both verbally and visually and facilitate association between them is the subject of this study. Stimulating and activating imagination, metaphors have unique advantages in promoting the product and its promise especially in regard to print advertisements, which have certain limitations. This study deals comparatively with both literal and metaphoric versions of print advertisements belonging to various product groups and attempts to discover to what extent advertisements are liked, recalled, perceived and are persuasive. The sample group of the study, which was conducted in two elementary schools situated in areas that had different socioeconomic features, consisted of children aged 12.

Keywords: Children, metaphor, perception, print advertisements, recall.

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Authors: E. Dolatdar, S. Soleymani, B. Mozafari

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Power loss reduction is one of the main targets in power industry and so in this paper, the problem of finding the optimal configuration of a radial distribution system for loss reduction is considered. Optimal reconfiguration involves the selection of the best set of branches to be opened ,one each from each loop, for reducing resistive line losses , and reliving overloads on feeders by shifting the load to adjacent feeders. However ,since there are many candidate switching combinations in the system ,the feeder reconfiguration is a complicated problem. In this paper a new approach is proposed based on a simple optimum loss calculation by determining optimal trees of the given network. From graph theory a distribution network can be represented with a graph that consists a set of nodes and branches. In fact this problem can be viewed as a problem of determining an optimal tree of the graph which simultaneously ensure radial structure of each candidate topology .In this method the refined genetic algorithm is also set up and some improvements of algorithm are made on chromosome coding. In this paper an implementation of the algorithm presented by [7] is applied by modifying in load flow program and a comparison of this method with the proposed method is employed. In [7] an algorithm is proposed that the choice of the switches to be opened is based on simple heuristic rules. This algorithm reduce the number of load flow runs and also reduce the switching combinations to a fewer number and gives the optimum solution. To demonstrate the validity of these methods computer simulations with PSAT and MATLAB programs are carried out on 33-bus test system. The results show that the performance of the proposed method is better than [7] method and also other methods.

Keywords: Distribution System, Reconfiguration, Loss Reduction , Graph Theory , Optimization , Genetic Algorithm

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Authors: Thea Freese

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Environmental legislation to protect North and Baltic Sea areas from harmful vessel-source emissions has received increased political attention in recent years. Legislative measures are expected to show positive effects on the health of the marine environment and society. At the same time, compliance might increase the costs to industry and have effects on freight rates and volumes shipped with potential negative repercussions on the environment. Building on an exploratory sequential mixed methods approach, this research project will study the economic effects of maritime environmental legislation in two phases. In Phase I, exploratory in-depth interviews were conducted with 12 experts from various stakeholder groups aiming at identifying variables influencing the relationship between environmental legislation, freight rates and volumes shipped. Influencing factors like compliance, enforcement and modal shift were identified and studied. Phase II will comprise of a quantitative study conducted with the aim of verifying the theory build in Phase I and quantifying economic effects of rules on shipping pollution. Research in this field might inform policy-makers about determinants of behaviour of ship operators in the face of the law and might further the development of a comprehensive legal system for marine environmental protection. At the present stage of research, first tentative results from the qualitative phase may be examined and open research questions to be addressed in the quantitative phase as well as possible research designs for phase II may be discussed. Input from other researchers will be highly valuable at this point.

Keywords: Clean shipping operations, compliance, maritime environmental legislation, maritime law and economics, mixed methods research, North and Baltic Sea area.

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Authors: S. K. Balashanmugam, Padmavati Manchikanti, S. R. Subramanian

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The question of legal liability over injury arising out of the import and the introduction of GM food emerges as a crucial issue confronting to promote GM food and its derivatives. There is a greater possibility of commercialized GM food from the exporting country to enter importing country where status of approval shall not be same. This necessitates the importance of fixing a liability mechanism to discuss the damage, if any, occurs at the level of transboundary movement or at the market. There was a widespread consensus to develop the Cartagena Protocol on Biosafety and to give for a dedicated regime on liability and redress in the form of Nagoya Kuala Lumpur Supplementary Protocol on the Liability and Redress (‘N-KL Protocol’) at the international context. The national legal frameworks based on this protocol are not adequately established in the prevailing food legislations of the developing countries. The developing economy like India is willing to import GM food and its derivatives after the successful commercialization of Bt Cotton in 2002. As a party to the N-KL Protocol, it is indispensable for India to formulate a legal framework and to discuss safety, liability, and regulatory issues surrounding GM foods in conformity to the provisions of the Protocol. The liability mechanism is also important in the case where the risk assessment and risk management is still in implementing stage. Moreover, the country is facing GM infiltration issues with its neighbors Bangladesh. As a precautionary approach, there is a need to formulate rules and procedure of legal liability to discuss any kind of damage occurs at transboundary trade. In this context, the proposed work will attempt to analyze the liability regime in the existing Food Safety and Standards Act, 2006 from the applicability and domestic compliance and to suggest legal and policy options for regulatory authorities.

Keywords: Commercialisation, food safety, FSSAI, genetically modified foods, India, liability.

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Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

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Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies  the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: Retail stores, Faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition.

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Authors: Reza Meimandi Parizi, Abdul Azim Abdul Ghani

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The ever-growing usage of aspect-oriented development methodology in the field of software engineering requires tool support for both research environments and industry. So far, tool support for many activities in aspect-oriented software development has been proposed, to automate and facilitate their development. For instance, the AJaTS provides a transformation system to support aspect-oriented development and refactoring. In particular, it is well established that the abstract interpretation of programs, in any paradigm, pursued in static analysis is best served by a high-level programs representation, such as Control Flow Graph (CFG). This is why such analysis can more easily locate common programmatic idioms for which helpful transformation are already known as well as, association between the input program and intermediate representation can be more closely maintained. However, although the current researches define the good concepts and foundations, to some extent, for control flow analysis of aspectoriented programs but they do not provide a concrete tool that can solely construct the CFG of these programs. Furthermore, most of these works focus on addressing the other issues regarding Aspect- Oriented Software Development (AOSD) such as testing or data flow analysis rather than CFG itself. Therefore, this study is dedicated to build an aspect-oriented control flow graph construction tool called AJcFgraph Builder. The given tool can be applied in many software engineering tasks in the context of AOSD such as, software testing, software metrics, and so forth.

Keywords: Aspect-Oriented Software Development, AspectJ, Control Flow Graph, Data Flow Analysis

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Authors: Yusuf Garba Baba

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The construction industry and housing subsector are fraught with risks that have the potential of negatively impacting on the achievement of project objectives. The success or otherwise of most construction projects depends to large extent on how well these risks have been managed. The recent paradigm shift by the subsector to use of formal risk management approach in contrast to hitherto developed rules of thumb means that risks must not only be identified but also properly assessed and responded to in a systematic manner. The study focused on identifying risks associated with housing development projects and prioritisation assessment of the identified risks in order to provide basis for informed decision. The study used a three-step identification framework: review of literature for similar projects, expert consultation and questionnaire based survey to identify potential risk factors. Delphi survey method was employed in carrying out the relative prioritization assessment of the risks factors using computer-based Analytical Hierarchical Process (AHP) software. The results show that 19 out of the 50 risks significantly impact on housing development projects. The study concludes that although significant numbers of risk factors have been identified as having relevance and impacting to housing construction projects, economic risk group and, in particular, ‘changes in demand for houses’ is prioritised by most developers as posing a threat to the achievement of their housing development objectives. Unless these risks are carefully managed, their effects will continue to impede success in these projects. The study recommends the adoption and use of the combination of multi-technique identification framework and AHP prioritization assessment methodology as a suitable model for the assessment of risks in housing development projects.

Keywords: Risk identification, risk assessment, analytical hierarchical process, multi-criteria decision.

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Authors: P. Ashok, G. M. Kadhar Nawaz

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Rough set theory is used to handle uncertainty and incomplete information by applying two accurate sets, Lower approximation and Upper approximation. In this paper, the rough clustering algorithms are improved by adopting the Similarity, Dissimilarity–Similarity and Entropy based initial centroids selection method on three different clustering algorithms namely Entropy based Rough K-Means (ERKM), Similarity based Rough K-Means (SRKM) and Dissimilarity-Similarity based Rough K-Means (DSRKM) were developed and executed by yeast dataset. The rough clustering algorithms are validated by cluster validity indexes namely Rand and Adjusted Rand indexes. An experimental result shows that the ERKM clustering algorithm perform effectively and delivers better results than other clustering methods. Outlier detection is an important task in data mining and very much different from the rest of the objects in the clusters. Entropy based Rough Outlier Factor (EROF) method is seemly to detect outlier effectively for yeast dataset. In rough K-Means method, by tuning the epsilon (ᶓ) value from 0.8 to 1.08 can detect outliers on boundary region and the RKM algorithm delivers better results, when choosing the value of epsilon (ᶓ) in the specified range. An experimental result shows that the EROF method on clustering algorithm performed very well and suitable for detecting outlier effectively for all datasets. Further, experimental readings show that the ERKM clustering method outperformed the other methods.

Keywords: Clustering, Entropy, Outlier, Rough K-Means, validity index.

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Authors: Ali Ghaffari, Mansour Nikkhah Bahrami, Hesam Parsa

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In this paper a comprehensive model of a fossil fueled power plant (FFPP) is developed in order to evaluate the performance of a newly designed turbine follower controller. Considering the drawbacks of previous works, an overall model is developed to minimize the error between each subsystem model output and the experimental data obtained at the actual power plant. The developed model is organized in two main subsystems namely; Boiler and Turbine. Considering each FFPP subsystem characteristics, different modeling approaches are developed. For economizer, evaporator, superheater and reheater, first order models are determined based on principles of mass and energy conservation. Simulations verify the accuracy of the developed models. Due to the nonlinear characteristics of attemperator, a new model, based on a genetic-fuzzy systems utilizing Pittsburgh approach is developed showing a promising performance vis-à-vis those derived with other methods like ANFIS. The optimization constraints are handled utilizing penalty functions. The effect of increasing the number of rules and membership functions on the performance of the proposed model is also studied and evaluated. The turbine model is developed based on the equation of adiabatic expansion. Parameters of all evaluated models are tuned by means of evolutionary algorithms. Based on the developed model a fuzzy PI controller is developed. It is then successfully implemented in the turbine follower control strategy of the plant. In this control strategy instead of keeping control parameters constant, they are adjusted on-line with regard to the error and the error rate. It is shown that the response of the system improves significantly. It is also shown that fuel consumption decreases considerably.

Keywords: Attemperator, Evolutionary algorithms, Fossil fuelled power plant (FFPP), Fuzzy set theory, Gain scheduling

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Authors: Khadiga Kahwa, Aniza Ismail

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Depression, anxiety, and stress are associated with decreased role functioning, productivity, and quality of life. International students are more prone to psychological distress as they face many stressors while studying abroad. The objectives of the study were to determine the prevalence and associated factors of depression, anxiety, and stress among international students, their help-seeking behavior, and their awareness of the available on-campus mental support services. A cross-sectional study with a purposive sampling method was performed on 280 international students at Universiti Kebangsaan Malaysia (UKM) between the age of 18 and 35 years. The Depression Anxiety Stress Scale-21 (DASS-21) questionnaire was used anonymously to assess the mental health of students. Socio-demographic, help-seeking behavior, and awareness data were obtained. Independent sample t-test, one-way ANOVA test, and multiple linear regression were used to explore associated factors. The overall prevalence of depression, anxiety, and stress among international students were 58.9%, 71.8%, and 53.9%, respectively. Age was significantly associated with depression and anxiety. Ethnicity showed a significant association with depression and stress. No other factors were found to be significantly associated with psychological distress. Only 9.6% of the international students had sought help from on-campus mental support services. Students who were aware of the presence of such services were only 21.4% of the participants. In conclusion, this study addressed the gap in the literature on the mental health of international students and provided data that could be used in intervention programs to improve the mental health of the increasing number of international students in Malaysia.

Keywords: Anxiety, depression, stress, help-seeking behavior, students.

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Authors: Rajvir Kaur, Jeewani Anupama Ginige

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With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: Artificial neural networks, breast cancer, cancer dataset, classifiers, cervical cancer, F-score, logistic regression, machine learning, precision, recall, support vector machine.

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Authors: Carine Cridelich, Pablo Juesas Cano, Emmanuel Ramasso, Noureddine Zerhouni, Bernd Weiler

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Safety is one of the most important considerations when buying a new car. While active safety aims at avoiding accidents, passive safety systems such as airbags and seat belts protect the occupant in case of an accident. In addition to legal regulations, organizations like Euro NCAP provide consumers with an independent assessment of the safety performance of cars and drive the development of safety systems in automobile industry. Those ratings are mainly based on injury assessment reference values derived from physical parameters measured in dummies during a car crash test. The components and sub-systems of a safety system are designed to achieve the required restraint performance. Sled tests and other types of tests are then carried out by car makers and their suppliers to confirm the protection level of the safety system. A Knowledge Discovery in Databases (KDD) process is proposed in order to minimize the number of tests. The KDD process is based on the data emerging from sled tests according to Euro NCAP specifications. About 30 parameters of the passive safety systems from different data sources (crash data, dummy protocol) are first analysed together with experts opinions. A procedure is proposed to manage missing data and validated on real data sets. Finally, a procedure is developed to estimate a set of rough initial parameters of the passive system before testing aiming at reducing the number of tests.

Keywords: KDD process, passive safety systems, sled test, dummy injury assessment reference values, frontal impact

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Authors: Celso L. Fernando, Toshio Yoshii, Takahiro Tsubota

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Understanding the causes of a road accident and predicting their occurrence is key to prevent deaths and serious injuries from road accident events. Traditional statistical methods such as the Poisson and the Logistics regressions have been used to find the association of the traffic environmental factors with the accident occurred; recently, an artificial neural network, ANN, a computational technique that learns from historical data to make a more accurate prediction, has emerged. Although the ability to make accurate predictions, the ANN has difficulty dealing with highly unbalanced attribute patterns distribution in the training dataset; in such circumstances, the ANN treats the minority group as noise. However, in the real world data, the minority group is often the group of interest; e.g., in the road traffic accident data, the events of the accident are the group of interest. This study proposes a combination of the k-means with the ANN to improve the predictive ability of the neural network model by alleviating the effect of the unbalanced distribution of the attribute patterns in the training dataset. The results show that the proposed method improves the ability of the neural network to make a prediction on a highly unbalanced distributed attribute patterns dataset; however, on an even distributed attribute patterns dataset, the proposed method performs almost like a standard neural network. 

Keywords: Accident risks estimation, artificial neural network, deep learning, K-mean, road safety.

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