Search results for: professional training level

Authors: Marija Lončar, Zorana Šuljug Vučica, Magdalena Nigoević

Abstract:

Diverse social, cultural and economic trends and changes in contemporary societies influence the ways masculinity is represented in a variety of media. Masculinity is constructed within media images as a dynamic process that changes slowly over time and is shaped by various social factors. In many societies, dominant masculinity is still associated with authority, heterosexuality, marriage, professional and financial success, ethnic dominance and physical strength. But contemporary media depict men in ways that suggest a change in the approach to media images. The number of media images of men, which promote men’s identity through their body, have increased. With the male body more scrutinized and commodified, it is necessary to highlight how the body is represented and which visual elements are crucial since the body has an important role in the construction of masculinities. The study includes content analysis of male body images in the advertisements of different men’s and women’s lifestyle magazines available in Croatia. The main aim was to explore how masculinities are currently being portrayed through body regarding age, physical appearance, fashion, touch and gaze. The findings are also discussed in relation to female images since women are central in many of the processes constructing masculinities and according to the recent conceptualization of masculinity. Although the construction of male images varies through body features, almost all of them convey the message that men’s identity could be managed through manipulation and by enhancing the appearance. Furthermore, they suggest that men should engage in “bodywork” through advertised products, activities and/or practices, in order to achieve their preferred social image.

Keywords: Body images, content analysis, lifestyle magazines, masculinity.

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Authors: Stella O. Olubodun, George E. Eriyamremu

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The study examined the effect of Bonny Light whole crude oil (WC) and its water soluble fraction (WSF) on the activities of antioxidant enzymes (catalase (CAT) and superoxide dismutase (SOD)) and crude mitochondria ATPases in the radicle of germinating bean (Vigna unguiculata). The percentage germination, level of lipid peroxidation, antioxidant enzyme and mitochondria Ca2+ and Mg2+ ATPase activities were measured in the radicle of bean after 7, 14 and 21 days post germination. Viable bean seeds were planted in soils contaminated with 10ml, 25ml and 50ml of whole crude oil (WC) and its water soluble fraction (WSF) to obtain 2, 5 and 10% v/w crude oil contamination. There was dose dependent reduction of the number of bean seeds that germinated in the contaminated soils compared with control (p<0.001). The activities of the antioxidant enzymes, as well as, adenosine triphosphatase enzymes, were also significantly (p<0.001) altered in the radicle of the plants grown in contaminated soil compared with the control. Generally, the level of lipid peroxidation was highest after 21 days post germination when compared with control. Stress to germinating bean caused by Bonny Light crude oil or its water soluble fraction resulted in adaptive changes in crude mitochondria ATPases in the radicle.

Keywords: Antioxidant enzymes, Bonny Light crude oil, Radicle, Mitochondria ATPases.

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Authors: Pranee Pathomchaiwat

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This research aims to study tourism data and behavior of foreign tourists visited Wat Phrachetuponwimolmangkalaram (Wat Po) Sample groups are tourists who visited inside the temple, during February, March, April and May 2013. Tools used in the research are questionnaires constructed by the researcher, and samples are dawn by Convenience sampling. There are 207 foreign tourists who are willing to be respondents. Statistics used are percentage, average mean and standard deviation. The results of the research reveal that: A. General Data of Respondents The foreign tourists who visited the temple are mostly female (57.5 %), most respondents are aged between 20-29 years (37.2%). Most respondents live in Europe (62.3%), most of them got the Bachelor’s degree (40.1%), British are mostly found (16.4%), respondents who are students are also found (23.2%), and Christian are mostly found (60.9%). B. Tourists’ Behavior While Visiting the Temple Compound. The result shows that the respondents came with family (46.4%), have never visited the temples (40.6%), and visited once (42 %). It is found that the foreign tourists’ inappropriate behavior are wearing revealing attires (58.9%), touching or getting closed to the monks (55.1%), and speaking loudly (46.9%) respectively. The respondents’ outstanding objectives are to visit inside the temple (57.5%), to pay respect to the Reclining Buddha Image in the Viharn (44.4%) and to worship the Buddha image in the Phra Ubosod (37.7%) respectively. C. The Respondents’ Self-evaluation of Performance It is found that over all tourists evaluated themselves in the highest level averaged 4.40. When focusing on each item, it is shown that they evaluated themselves in the highest level on obeying the temple staff averaged 4.57, and cleanness concern of the temple averaged 4.52, well-behaved performance during the temple visit averaged 4.47 respectively.

Keywords: Deportment, Traveler

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Authors: Anika Zafiah M. Rus, S. Shafizah

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This study was developed to compare the behavior and the ability of polymer foam composites towards sound absorption test of Shorea leprosula wood (SL) of acid hydrolysis treatment with particle size <355μm. Three different weight ratio of polyol to wood particle has been selected which are 10wt%, 15wt% and 20wt%. The acid hydrolysis treatment is to optimize the surface interaction of wood particle with polymer foam matrix. In addition, the acoustic characteristic of sound absorption coefficient (α) was determined. Further treatment is to expose the polymer composite in UV irradiation by using UV-Weatherometer. Polymer foam composite of untreated Shorea leprosula particle (SL-B) with respective percentage loading shows uniform pore structure as compared with treated wood particle (SL-A). As the filler percentage loading in polymer foam increases, the α value approaching 1 for both samples. Furthermore, SL-A shows better α value at 3500-4500 frequency absorption level (Hz), meanwhile α value for SL-B is maximum at 4000-5000 Hz. The frequencies absorption level for both SL-B and SL-A after UV exposure was increased with the increasing of exposure time from 0-1000 hours. It is therefore, concluded that the α for each sound absorbing material, with or without acid hydrolysis treatment of wood particles and it’s percentages loading in polymer matrix effect the sound absorption behavior.

Keywords: Polymer foam composite, sound absorption coefficient, UV-irradiation, wood.

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Authors: Noor Asma Husain, Mohd Shafry Mohd Rahim, Abdullah Bade

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Subdivision surfaces were applied to the entire meshes in order to produce smooth surfaces refinement from coarse mesh. Several schemes had been introduced in this area to provide a set of rules to converge smooth surfaces. However, to compute and render all the vertices are really inconvenient in terms of memory consumption and runtime during the subdivision process. It will lead to a heavy computational load especially at a higher level of subdivision. Adaptive subdivision is a method that subdivides only at certain areas of the meshes while the rest were maintained less polygons. Although adaptive subdivision occurs at the selected areas, the quality of produced surfaces which is their smoothness can be preserved similar as well as regular subdivision. Nevertheless, adaptive subdivision process burdened from two causes; calculations need to be done to define areas that are required to be subdivided and to remove cracks created from the subdivision depth difference between the selected and unselected areas. Unfortunately, the result of adaptive subdivision when it reaches to the higher level of subdivision, it still brings the problem with memory consumption. This research brings to iterative process of adaptive subdivision to improve the previous adaptive method that will reduce memory consumption applied on triangular mesh. The result of this iterative process was acceptable better in memory and appearance in order to produce fewer polygons while it preserves smooth surfaces.

Keywords: Subdivision surfaces, adaptive subdivision, selectioncriteria, handle cracks, smooth surface

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Authors: Okan Özgönenel

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This paper presents the development of a wavelet based algorithm, for distinguishing between magnetizing inrush currents and power system fault currents, which is quite adequate, reliable, fast and computationally efficient tool. The proposed technique consists of a preprocessing unit based on discrete wavelet transform (DWT) in combination with an artificial neural network (ANN) for detecting and classifying fault currents. The DWT acts as an extractor of distinctive features in the input signals at the relay location. This information is then fed into an ANN for classifying fault and magnetizing inrush conditions. A 220/55/55 V, 50Hz laboratory transformer connected to a 380 V power system were simulated using ATP-EMTP. The DWT was implemented by using Matlab and Coiflet mother wavelet was used to analyze primary currents and generate training data. The simulated results presented clearly show that the proposed technique can accurately discriminate between magnetizing inrush and fault currents in transformer protection.

Keywords: Artificial neural network, discrete wavelet transform, fault detection, magnetizing inrush current.

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Authors: Nicholas Milburn, Yu Liang, Dalei Wu

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Athlete performance scoring within the climbing domain presents interesting challenges as the sport does not have an objective way to assign skill. Assessing skill levels within any sport is valuable as it can be used to mark progress while training, and it can help an athlete choose appropriate climbs to attempt. Machine learning-based methods are popular for complex problems like this. The dataset available was composed of dynamic force data recorded during climbing; however, this dataset came with challenges such as data scarcity, imbalance, and it was temporally heterogeneous. Investigated solutions to these challenges include data augmentation, temporal normalization, conversion of time series to the spectral domain, and cross validation strategies. The investigated solutions to the classification problem included light weight machine classifiers KNN and SVM as well as the deep learning with CNN. The best performing model had an 80% accuracy. In conclusion, there seems to be enough information within climbing force data to accurately categorize climbers by skill.

Keywords: Classification, climbing, data imbalance, data scarcity, machine learning, time sequence.

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Authors: Kristina Davoian, Wolfram-M. Lippe

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Evolutionary Programming (EP) represents a methodology of Evolutionary Algorithms (EA) in which mutation is considered as a main reproduction operator. This paper presents a novel EP approach for Artificial Neural Networks (ANN) learning. The proposed strategy consists of two components: the self-adaptive, which contains phenotype information and the dynamic, which is described by genotype. Self-adaptation is achieved by the addition of a value, called the network weight, which depends on a total number of hidden layers and an average number of neurons in hidden layers. The dynamic component changes its value depending on the fitness of a chromosome, exposed to mutation. Thus, the mutation step size is controlled by two components, encapsulated in the algorithm, which adjust it according to the characteristics of a predefined ANN architecture and the fitness of a particular chromosome. The comparative analysis of the proposed approach and the classical EP (Gaussian mutation) showed, that that the significant acceleration of the evolution process is achieved by using both phenotype and genotype information in the mutation strategy.

Keywords: Artificial Neural Networks (ANN), Learning Theory, Evolutionary Programming (EP), Mutation, Self-Adaptation.

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Authors: Pashayev A., Askerov D., C. Ardil, Sadiqov R., Abdullayev P.

Abstract:

Groundlessness of application probability-statistic methods are especially shown at an early stage of the aviation GTE technical condition diagnosing, when the volume of the information has property of the fuzzy, limitations, uncertainty and efficiency of application of new technology Soft computing at these diagnosing stages by using the fuzzy logic and neural networks methods. It is made training with high accuracy of multiple linear and nonlinear models (the regression equations) received on the statistical fuzzy data basis. At the information sufficiency it is offered to use recurrent algorithm of aviation GTE technical condition identification on measurements of input and output parameters of the multiple linear and nonlinear generalized models at presence of noise measured (the new recursive least squares method (LSM)). As application of the given technique the estimation of the new operating aviation engine D30KU-154 technical condition at height H=10600 m was made.

Keywords: Identification of a technical condition, aviation gasturbine engine, fuzzy logic and neural networks.

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Authors: M.R. Mustafa, M.H. Isa, R.B. Rezaur

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Prediction of highly non linear behavior of suspended sediment flow in rivers has prime importance in the field of water resources engineering. In this study the predictive performance of two Artificial Neural Networks (ANNs) namely, the Radial Basis Function (RBF) Network and the Multi Layer Feed Forward (MLFF) Network have been compared. Time series data of daily suspended sediment discharge and water discharge at Pari River was used for training and testing the networks. A number of statistical parameters i.e. root mean square error (RMSE), mean absolute error (MAE), coefficient of efficiency (CE) and coefficient of determination (R2) were used for performance evaluation of the models. Both the models produced satisfactory results and showed a good agreement between the predicted and observed data. The RBF network model provided slightly better results than the MLFF network model in predicting suspended sediment discharge.

Keywords: ANN, discharge, modeling, prediction, suspendedsediment,

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Authors: Tzu-Hsin Liu

Abstract:

This study adopts a qualitative approach, which engages in the dialectical discussion on two levels of dyad opposite views. The first level of the dyad opposite views is the Western strategic perspective and the Eastern Tai-Chi thinking. The second level of the dyad opposite views is resource-based view and resource dependence theory. This study concludes the resource-oriented actions for competitive advantage as the metaphor of Tai-Chi consisted of yin and yang. This study argues that the focal firm should adopt bridging strategy during the core competence development period because its core competence development is likely to meet its competitor’s needs of exploring strategy during the competitor’s external resource development stage. In addition, the focal firm should adopt buffering strategy during the external resource development period to prevent its competitor’s the exploiting strategy from attack during the competitor’s core competence development stage. Consequently, this study takes a significant first step toward a novel contextualize understanding of resource development based on strategic perspective and Tai-Chi thinking providing more fully sustainable strategy for competitive advantage.

Keywords: Competitive advantage, resource-based view, resource dependence theory, strategic perspective, Tai-Chi thinking.

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

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

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

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Authors: Pashayev A., Askerov D., C. Ardil, Sadiqov R., Abdullayev P.

Abstract:

Groundlessness of application probability-statistic methods are especially shown at an early stage of the aviation GTE technical condition diagnosing, when the volume of the information has property of the fuzzy, limitations, uncertainty and efficiency of application of new technology Soft computing at these diagnosing stages by using the fuzzy logic and neural networks methods. It is made training with high accuracy of multiple linear and nonlinear models (the regression equations) received on the statistical fuzzy data basis. At the information sufficiency it is offered to use recurrent algorithm of aviation GTE technical condition identification on measurements of input and output parameters of the multiple linear and nonlinear generalized models at presence of noise measured (the new recursive least squares method (LSM)). As application of the given technique the estimation of the new operating aviation engine D30KU-154 technical condition at height H=10600 m was made.

Keywords: Identification of a technical condition, aviation gasturbine engine, fuzzy logic and neural networks.

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Authors: Miika Toivanen, Jouko Lampinen

Abstract:

This paper presents an online method that learns the corresponding points of an object from un-annotated grayscale images containing instances of the object. In the first image being processed, an ensemble of node points is automatically selected which is matched in the subsequent images. A Bayesian posterior distribution for the locations of the nodes in the images is formed. The likelihood is formed from Gabor responses and the prior assumes the mean shape of the node ensemble to be similar in a translation and scale free space. An association model is applied for separating the object nodes and background nodes. The posterior distribution is sampled with Sequential Monte Carlo method. The matched object nodes are inferred to be the corresponding points of the object instances. The results show that our system matches the object nodes as accurately as other methods that train the model with annotated training images.

Keywords: Bayesian modeling, Gabor filters, Online learning, Sequential Monte Carlo.

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Authors: Ramandeep S. Sidhu, Sunil Khullar, Parvinder S. Sandhu, R. P. S. Bedi, Kiranbir Kaur

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In this paper, subtractive clustering based fuzzy inference system approach is used for early detection of faults in the function oriented software systems. This approach has been tested with real time defect datasets of NASA software projects named as PC1 and CM1. Both the code based model and joined model (combination of the requirement and code based metrics) of the datasets are used for training and testing of the proposed approach. The performance of the models is recorded in terms of Accuracy, MAE and RMSE values. The performance of the proposed approach is better in case of Joined Model. As evidenced from the results obtained it can be concluded that Clustering and fuzzy logic together provide a simple yet powerful means to model the earlier detection of faults in the function oriented software systems.

Keywords: Subtractive clustering, fuzzy inference system, fault proneness.

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Authors: E. F. Aransiola, M.O. Daramola, E. O. Iwalewa, A. M. Seluwa, O. O. Olufowobi

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Diabetes is a chronic metabolic disorder that affects the quality of life in terms of physical health, social and psychological well-being. In spite of the enormous progress in the treatment of diabetes using existing commercial drugs, such as, insulin and oral hypoglycemic agents, the quest and search for new drugs is imperative due to several limitations of the commercial drugs. In addition, the existing diabetic drugs are expensive and unaffordable by the rural populace in the developing countries. The present study demonstrates the anti-diabetic property of aqueous extract of Bryophyllum pinnatum (BP) leaves using diabetic rats (albino rats) as models. At the same time, the anti-diabetic effect of the aqueous extract was compared to that of a sample containing a mixture of the extract and a commercial diabetic medicine, glibenclamide. A specified dosage of aqueous extract of Bryophyllum pinnatum (BP) leaves was administered on the experimental diabetic rats, and their BGL was measured and recorded. The results showed a significant drop in the BGL of the diabetic rats to a value close to normal blood glucose level within 120 minutes when only aqueous extract from BP leaves was used. When a sample containing a mixture of the aqueous extract and glibenclamide was administered, a further drop in BGL was observed. Therefore, the results reveal that aqueous extract of Bryophyllum pinnatum leaves have significant anti-diabetic properties, and that the performance of the existing drugs (glibenclamide) could be enhanced with the use of the aqueous extract.

Keywords: Anti-diabetics, Bryophyllum pinnatum, Blood glucose level, albino rats.

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Authors: Perminderjit Singh, Sukhvir Singh

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Total Quality Management (TQM) refers to management methods used to enhance quality and productivity in business organizations. Total Quality Management (TQM) has become a frequently used term in discussions concerning quality. Total Quality management has brought rise in demands on the organizations policy and the customers have gained more importance in the organizations focus. TQM is considered as an important management tool, which helps the organizations to satisfy their customers. In present research critical success factors includes management commitment, customer satisfaction, continuous improvement, work culture and environment, supplier quality management, training and development, employee satisfaction and product/process design are studied. A questionnaire is developed to implement these critical success factors in implementation of total quality management in Indian industry. Questionnaires filled by consulting different industrial organizations. Data collected from questionnaires is analyzed by descriptive and importance indexes. 

Keywords: Total quality management, critical success factor, employee satisfaction.

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Authors: Thossaporn Thossansin

Abstract:

This paper presents the development of a mobile application for students at the Faculty of Information Technology, Rangsit University (RSU), Thailand. RSU upgrades an enrollment process by improving its information systems. Students can download the RSU APP easily in order to access the RSU substantial information. The reason of having a mobile application is to help students to access the system regardless of time and place. The objectives of this paper include: 1. To develop an application on iOS platform for those students at the Faculty of Information Technology, Rangsit University, Thailand. 2. To obtain the students’ perception towards the new mobile app. The target group is those from the freshman year till the senior year of the faculty of Information Technology, Rangsit University. The new mobile application, called as RSU APP, is developed by the department of Information Technology, Rangsit University. It contains useful features and various functionalities particularly on those that can give support to students. The core contents of the app consist of RSU’s announcement, calendar, events, activities, and ebook. The mobile app is developed on the iOS platform. The user satisfaction is analyzed from the interview data from 81 interviewees as well as a Google application like a Google form which 122 interviewees are involved. The result shows that users are satisfied with the application as they score it the most satisfaction level at 4.67 SD 0.52. The score for the question if users can learn and use the application quickly is high which is 4.82 SD 0.71. On the other hand, the lowest satisfaction rating is in the app’s form, apps lists, with the satisfaction level as 4.01 SD 0.45.

Keywords: Mobile application, development of mobile application, framework of mobile development, software development for mobile devices.

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Authors: S. Cobos-Guzman

Abstract:

This paper presents the results of a mechatronic design based on a 4-wheel omnidirectional mobile robot that can be used in indoor logistic applications. The low-level control has been selected using two open-source hardware (Raspberry Pi 3 Model B+ and Arduino Mega 2560) that control four industrial motors, four ultrasound sensors, four optical encoders, a vision system of two cameras, and a Hokuyo URG-04LX-UG01 laser scanner. Moreover, the system is powered with a lithium battery that can supply 24 V DC and a maximum current-hour of 20Ah.The Robot Operating System (ROS) has been implemented in the Raspberry Pi and the performance is evaluated with the selection of the sensors and hardware selected. The mechatronic system is evaluated and proposed safe modes of power distribution for controlling all the electronic devices based on different tests. Therefore, based on different performance results, some recommendations are indicated for using the Raspberry Pi and Arduino in terms of power, communication, and distribution of control for different devices. According to these recommendations, the selection of sensors is distributed in both real-time controllers (Arduino and Raspberry Pi). On the other hand, the drivers of the cameras have been implemented in Linux and a python program has been implemented to access the cameras. These cameras will be used for implementing a deep learning algorithm to recognize people and objects. In this way, the level of intelligence can be increased in combination with the maps that can be obtained from the laser scanner.

Keywords: Autonomous, indoor robot, mechatronic, omnidirectional robot.

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Authors: Sareh Rajabi, Salwa Bheiry

Abstract:

In general, Covid-19 created many financial and non-financial damages to the economy and community. Level and severity of covid-19 as pandemic case varies over the region and due to different types of the projects. Covid-19 virus emerged as one of the most imperative risk management factors word-wide recently. Therefore, as part of portfolio management assessment, it is essential to evaluate severity of such risk on the project and program in portfolio management level to avoid any risky portfolio. Covid-19 appeared very effectively in South America, part of Europe and Middle East. Such pandemic infection affected the whole universe, due to lock down, interruption in supply chain management, health and safety requirements, transportations and commercial impacts. Therefore, this research proposes Analytical Hierarchy Process (AHP) to analyze and assess such pandemic case like Covid-19 and its impacts on the construction projects. The AHP technique uses four sub-criteria: Health and safety, commercial risk, completion risk and contractual risk to evaluate the project and program. The result will provide the decision makers with information which project has higher or lower risk in case of Covid-19 and pandemic scenario. Therefore, the decision makers can have most feasible solution based on effective weighted criteria for project selection within their portfolio to match with the organization’s strategies.

Keywords: Portfolio management, risk management, COVID-19, analytical hierarchy process technique.

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Authors: Snežana T. Tanasković, Sonja M. Gvozdenac, Branka D. Popović, Vesna M. Đurović, Matthias Erb

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Western corn rootworm – WCR (Diabrotica virgifera sp.virgifera, Coleoptera, Chrysomelidae) is economically the most important pest of maize worldwide. WCR natural population is already very abundant on Serbian fields, and keeps increasing each year. Tolerance is recognized by larger root size and bigger root regrowth. Severe larval injuries cause lack of compensatory regrowth and lead to reduction of plant growth and yield. The aim of this research was to evaluate tolerance of commercial Serbian maize hybrid NS 640, under natural WCR infestation and under conditions of artificial infestation, and to obtain the information about its tolerance to WCR larval feeding in two consecutive years. Field experiments were conducted in 2015 and 2016, in Bečej (Vojvodina province, Serbia). In experimental field, 96 plants were selected, marked and arranged in 48 pairs. Each pair represented two plants. The first plant was artificially infested with 4 mL WCR egg suspension in agar (550 eggs plant^-1) in the root zone (D plant). The second plant represented control plant (C plant) with injection of 4 mL distilled water in root zone. The experimental field was inspected weekly. A hybrid tolerance was assessed based on root injury level and root mass. Root injury was rated using the Node-Injury Scale 1-6, during the last field inspection (September – October). Comparing the root injuries on D and C plants in 2015, more severe damages were recorded on D plants (12 plants - rate 5 and 17 plants - rate 6) compared to C plants (2 plants - rate 5 and 8 plants - rate 6). Also, the highest number of plants with healthy roots (rate 1), was registered in the control (25 plants), while only 4 D plants were rated as injury level 1. In 2016, root injuries caused by WCR larvae on D and C plants did not differ significantly. The reason is the difference in climatic conditions between the years. The 2015 was extremely dry and more suitable for WCR larval development and movement in the soil, compared to 2016. Thus, more severe damages appeared on artificially infested plants (D plants). Root mass was in strong correlation with the level of root injury, but did not differ significantly between D and C plants, in both years.

Keywords: D. v. virgifera, maize, root injury, tolerance.

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Authors: A. Karasek

Abstract:

Rapid growth of Information Technologies (IT) has had huge influence on enterprises, and it has contributed to its promotion and increasingly extensive use in enterprises. Information Technologies have to a large extent determined the processes taking place in an enterprise; what is more, IT development has brought the need to adopt a brand new approach to human resources management in an enterprise. The use of IT in human resource management (HRM) is of high importance due to the growing role of information and information technologies. The aim of this paper is to evaluate the use of information technologies in human resources management in enterprises. These practices will be presented in the following areas: recruitment and selection, development and training, employee assessment, motivation, talent management, personnel service. Results of conducted survey show diversity of solutions applied in particular areas of human resource management. In the future, further development in this area should be expected, as well as integration of individual HRM areas, growing mobile-enabled HR processes and their transfer into the cloud. Presented IT solutions applied in HRM are highly innovative, which is of great significance due to their possible implementation in other enterprises.

Keywords: E-HR, human resources management, HRM practices, HRMS, information technologies.

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Authors: Nattapong Techarattanased

Abstract:

The purposes of this research are to make comparisons in respect of the behaviors on the use of the services of metered taxi classified by the demographic factor and to study the influence of the recognition on service quality having the effect on usage behaviors of metered taxi services of consumers in Bangkok Metropolitan Areas. The samples used in this research were 400 metered taxi service users in Bangkok Metropolitan Areas and questionnaire was used as the tool for collecting the data. Analysis statistics are mean and multiple regression analysis. Results of the research revealed that the consumers recognize the overall quality of services in each aspect include tangible aspects of the service, responses to customers, assurance on the confidence, understanding and knowing of customers which is rated at the moderate level except the aspect of the assurance on the confidence and trustworthiness which are rated at a high level. For the result of hypothetical test, it is found that the quality in providing the services on the aspect of the assurance given to the customers has the effect on the usage behaviors of metered taxi services and the aspect of the frequency on the use of the services per month which in this connection. Such variable can forecast at one point nine percent (1.9%). In addition, quality in providing the services and the aspect of the responses to customers have the effect on the behaviors on the use of metered taxi services on the aspect of the expenses on the use of services per month which in this connection, such variable can forecast at two point one percent (2.1%).

Keywords: Consumer behavior, metered taxi, satisfaction, service quality.

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Authors: Lewis E. Hibell, Honghai Liu, David J. Brown

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This paper presents the use of a newly created network structure known as a Self-Delaying Dynamic Network (SDN) to create a high resolution image from a set of time stepped input frames. These SDNs are non-recurrent temporal neural networks which can process time sampled data. SDNs can store input data for a lifecycle and feature dynamic logic based connections between layers. Several low resolution images and one high resolution image of a scene were presented to the SDN during training by a Genetic Algorithm. The SDN was trained to process the input frames in order to recreate the high resolution image. The trained SDN was then used to enhance a number of unseen noisy image sets. The quality of high resolution images produced by the SDN is compared to that of high resolution images generated using Bi-Cubic interpolation. The SDN produced images are superior in several ways to the images produced using Bi-Cubic interpolation.

Keywords: Image Enhancement, Neural Networks, Multi-Frame.

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Authors: Abdulkadir Abu Lawal

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For the dearth of reliable cardinal numerical data, the linked phenomena in productivity indices such as operational costs and company turnovers, etc. could not be investigated. This would not give us insight to the root of productivity problems at unique sites. So, ordinal ranking by professionals who were most directly involved with construction sites was applied for Kendall’s concordance. Responses gathered from independent architects, builders/engineers, and quantity surveyors were herein analyzed. They were responses based on factors that affect sites productivity, and these factors were categorized as head office factors, resource management effectiveness factors, motivational factors, and training/skill development factors. It was found that productivity is low and has to be improved in order to facilitate Nigerian efforts in bridging its infrastructure deficit. The significance of this work is underlined with the Kendall’s coefficient of concordance of 0.78, while remedial measures must be emphasized to stimulate better productivity. Further detailed study can be undertaken by using Fuzzy logic analysis on wider Delphi survey.

Keywords: Factors, Kendall’s coefficient of concordance, magnitude of agreement, percentage magnitude of dichotomy, ranking variables.

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Authors: M. Javanmard

Abstract:

This study was aimed at analyzing the effects of packaging (MAP) and preservation conditions on the packaged fresh walnut kernel quality. The central composite plan was used for evaluating the effect of oxygen (0–10%), carbon dioxide (0-10%), and temperature (4-26 °C) on qualitative characteristics of walnut kernels. Also, the response level technique was used to find the optimal conditions for interactive effects of factors, as well as estimating the best conditions of process using least amount of testing. Measured qualitative parameters were: peroxide index, color, decreased weight, mould and yeast counting test, and sensory evaluation. The results showed that the defined model for peroxide index, color, weight loss, and sensory evaluation is significant (p < 0.001), so that increase of temperature causes the peroxide value, color variation, and weight loss to increase and it reduces the overall acceptability of walnut kernels. An increase in oxygen percentage caused the color variation level and peroxide value to increase and resulted in lower overall acceptability of the walnuts. An increase in CO₂ percentage caused the peroxide value to decrease, but did not significantly affect other indices (p ≥ 0.05). Mould and yeast were not found in any samples. Optimal packaging conditions to achieve maximum quality of walnuts include: 1.46% oxygen, 10% carbon dioxide, and temperature of 4 °C.

Keywords: Shelled walnut, MAP, quality, storage temperature.

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Authors: Yudia Mailani Putri, Martalena Purba, B. J. Istiti Kandarina

Abstract:

Background: Obesity has been recognized as a global health problem. Individuals classified as overweight and obese are increasing at an alarming rate. This condition is associated with psychological and physiological problems. as a person reaches adulthood, somatic growth ceases. At this stage, the human body has developed fully, to a stable state. As the capital of Riau Province in Indonesia, Pekanbaru is dominated by Malay ethnic population habitually consuming cholesterol-rich fatty foods as a daily menu, a trigger to the onset of obesity resulting in high prevalence of degenerative diseases. Research objectives: The aim of this study is elaborating the relationship between high-fat consumption pattern, stress level, physical activity and the incidence of obesity in adult women in Pekanbaru city. Research Methods: Among the combined research methods applied in this study, the first stage is quantitative observational, analytical cross-sectional research design with adult women aged 20-40 living in Pekanbaru city. The sample consists of 200 women with BMI≥25. Sample data is processed with univariate, bivariate (correlation and simple linear regression) and multivariate (multiple linear regression) analysis. The second phase is qualitative descriptive study purposive sampling by in-depth interviews. six participants withdrew from the study. Results: According to the results of the bivariate analysis, there are relationships between the incidence of obesity and the pattern of high fat foods consumption (energy intake (p≤0.000; r = 0.536), protein intake (p≤0.000; r=0.307), fat intake (p≤0.000; r=0.416), carbohydrate intake (p≤0.000; r=0.430), frequency of fatty food consumption (p≤0.000; r=0.506) and frequency of viscera foods consumption (p≤0.000; r=0.535). There is a relationship between physical activity and incidence of obesity (p≤0.000; r=-0.631). However, there is no relationship between the level of stress (p=0.741; r=0.019-) and the incidence of obesity. Physical activity is a predominant factor in the incidence of obesity in adult women in Pekanbaru city. Conclusion: There are relationships between high-fat food consumption pattern, physical activity and the incidence of obesity in Pekanbaru city whereas physical activity is a predominant factor in the occurrence of obesity, supported by the unchangeable pattern of high-fat foods consumption.

Keywords: Obesity, adult, high in fat, stress, physical activity, consumption pattern.

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Authors: Nitin Singh, Meng Ling, Talha Ahmed, Tianxia Zhao, Reinier van de Pol

Abstract:

We propose the use of Reinforcement Learning (RL) as a viable alternative for optimizing supply chain management, particularly in scenarios with stochasticity in product demands. RL’s adaptability to changing conditions and its demonstrated success in diverse fields of sequential decision-making make it a promising candidate for addressing supply chain problems. We investigate the impact of demand fluctuations in a multi-product supply chain system and develop RL agents with learned generalizable policies. We provide experimentation details for training RL agents and a statistical analysis of the results. We study generalization ability of RL agents for different demand uncertainty scenarios and observe superior performance compared to the agents trained with fixed demand curves. The proposed methodology has the potential to lead to cost reduction and increased profit for companies dealing with frequent inventory movement between supply and demand nodes.

Keywords: Inventory Management, Reinforcement Learning, Supply Chain Optimization, Uncertainty.

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Authors: Gabriel Jinga, Madalina Dumitru

Abstract:

The objective of this paper is to present the process of change in management accounting in Romania, a former communist country from Eastern Europe. In order to explain this process, we used the contingency and institutional theories. We focused on the following directions: the presentation of the scientific context and motivation of this research and the case study. We presented the state of the art in the process of change in the management accounting from the international and national perspective. We also described the evolution of management accounting in Romania in the context of economic and political changes. An important moment was the fall of communism in 1989. This represents a starting point for a new economic environment and for new management accounting. Accordingly, we developed a case study which presented this evolution. The conclusion of our research was that the changes in the management accounting system of the company analysed occurred in the same time with the institutionalisation of some elements (e.g. degree of competition, training and competencies in management accounting). The management accounting system was modelled by the contingencies specific to this company (e.g. environment, industry, strategy).

Keywords: Management accounting, change, Romania, contingency and institutional theory.

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Authors: Neil Morgan

Abstract:

The notion of Threshold Concepts has offered a fertile new perspective on the transformative effects of mastery of particular concepts on student understanding of subject matter and their developing identities as inductees into disciplinary discourse communities. Only by successfully traversing essential knowledge thresholds can neophytes achieve the more sophisticated understandings of subject matter possessed by mature members of a discipline. This paper uses thematic analysis of disciplinary guiding principles to identify nine candidate Threshold Concepts that appear to underpin effective TESOL practice. The relationship between these candidate TESOL Threshold Concepts, TESOL principles, and TESOL instructional techniques appears to be amenable to a schematic representation based on superordinate categories of TESOL practitioner concern and, as such, offers an alternative to the view of Threshold Concepts as a privileged subset of disciplinary core concepts. The paper concludes by exploring the potential of a Threshold Concepts framework to productively inform TESOL initial teacher education (ITE) and in-service education and training (INSET).

Keywords: TESOL, threshold concepts, TESOL principles, TESOL ITE/INSET, community of practice.

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