Search results for: main controlling factors

Authors: Ibrahim A. Al-Sulaihi, Khalid S. Al-Gahtani, Abdullah M. Al-Sugair, Aref A. Abadel

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Achieving environmental sustainability is one of the important issues considered in many countries’ vision. Green/Sustainable building is widely used terminology for describing a friendly environmental construction. Applying sustainable practices has a significant importance in various fields, including construction field that consumes an enormous amount of resource and causes a considerable amount of waste. The need for sustainability is increased in the regions that suffering from the limitation of natural resource and extreme weather conditions such as Saudi Arabia. Since buildings designs are getting sophisticated, the need for tools, which support decision-making for sustainability issues, is increasing, especially in the design and preconstruction stages. In this context, Building Information Modeling (BIM) can aid in performing complex building performance analyses to ensure an optimized sustainable building design. Accordingly, this paper introduces a roadmap towards developing a systematic approach for presenting the sustainability of buildings using BIM. The approach includes set of main processes including; identifying the sustainability parameters that can be used for sustainability assessment in Saudi Arabia, developing sustainability assessment method that fits the special circumstances in the Kingdom, identifying the sustainability requirements and BIM functions that can be used for satisfying these requirements, and integrating these requirements with identified functions. As a result, the sustainability-BIM approach can be developed which helps designers in assessing the sustainability and exploring different design alternatives at the early stage of the construction project.

Keywords: Green buildings, sustainability, BIM, rating systems, environment, Saudi Arabia.

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Authors: Guarry Montrose, Ted Soubdhan

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In the fight against climate change, the energy consuming building sector must also be taken into account to solve this problem. In this case thermal insulation of buildings using bio-based materials is an interesting solution. Therefore, the thermal performance of some materials of this type has been studied. The advantages of these natural materials of plant origin are multiple, biodegradable, low economic cost, renewable and readily available. The use of biobased materials is widespread in the building sector in order to replace conventional insulation materials with natural materials. Vegetable fibers are very important because they have good thermal behaviour and good insulating properties. The aim of using bio-sourced materials is in line with the logic of energy control and environmental protection, the approach is to make the inhabitants of the houses comfortable and reduce their energy consumption (energy efficiency). In this research we will present the results of studies carried out on the thermal conductivity of banana leaves, latan leaves, vetivers fibers, palm kernel fibers, sargassum, coconut leaves, sawdust and bulk sugarcane leaves. The study on thermal conductivity was carried out in two ways, on the one hand using the flash method, and on the other hand a so-called hot box experiment was carried out. We will discuss and highlight a number of influential factors such as moisture and air pockets present in the samples on the thermophysical properties of these materials, in particular thermal conductivity. Finally, the result of a thermal performance test of banana leaves on a roof in Haiti will also be presented in this work.

Keywords: Buildings, insulating properties, natural materials of plant origin, thermal performance.

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Authors: M. Mohebbi, K. Shakeri

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In the real application of active control systems to mitigate the response of structures subjected to sever external excitations such as earthquake and wind induced vibrations, since the capacity of actuators is limited then the actuators saturate. Hence, in designing controllers for linear and nonlinear structures under sever earthquakes, the actuator saturation should be considered as a constraint. In this paper optimal design of active controllers for nonlinear structures by considering the actuator saturation has been studied. To this end a method has been proposed based on defining an optimization problem which considers the minimizing of the maximum displacement of the structure as objective when a limited capacity for actuator has been used as a constraint in optimization problem. To evaluate the effectiveness of the proposed method, a single degree of freedom (SDF) structure with a bilinear hysteretic behavior has been simulated under a white noise ground acceleration of different amplitudes. Active tendon control mechanism, comprised of pre-stressed tendons and an actuator, and extended nonlinear Newmark method based instantaneous optimal control algorithm have been used as active control mechanism and algorithm. To enhance the efficiency of the controllers, the weights corresponding to displacement, velocity, acceleration and control force in the performance index have been found by using the Distributed Genetic Algorithm (DGA). According to the results it has been concluded that the proposed method has been effective in considering the actuator saturation in designing optimal controllers for nonlinear frames. Also it has been shown that the actuator capacity and the average value of required control force are two important factors in designing nonlinear controllers for considering the actuator saturation.

Keywords: Active control, Actuator Saturation, Nonlinear, Optimization.

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Authors: M. L. Arias, J. D’Adamo, M. N. Novosad, P. A. Raffo, H. P. Burbridge, G. O. Artana

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Shale oils are highly paraffinic and, consequently, can create wax deposits that foul pipelines during transportation. Several factors must be considered when designing pipelines or treatment programs that prevent wax deposition: including chemical species in crude oils, flowrates, pipes diameters and temperature. This paper describes the wax deposition study carried out within the framework of YPF Tecnolgía S.A. (Y-TEC) flow assurance projects, as part of the process to achieve a better understanding on wax deposition issues. Laboratory experiments were performed on a medium size, 1 inch diameter, wax deposition loop of 15 meters long equipped with a solid detector system, online microscope to visualize crystals, temperature, and pressure sensors along the loop pipe. A baseline test was performed with diesel with no added paraffin or additive content. Tests were undertaken with different temperatures of circulating and cooling fluid at different flow conditions. Then, a solution formed with a paraffin incorporated to the diesel was considered. Tests varying flowrate and cooling rate were again run. Viscosity, density, WAT (Wax Appearance Temperature) with DSC (Differential Scanning Calorimetry), pour point and cold finger measurements were carried out to determine physical properties of the working fluids. The results obtained in the loop were analyzed through momentum balance and heat transfer models. To determine possible paraffin deposition scenarios temperature and pressure loop output signals were studied. They were compared with WAT static laboratory methods.

Keywords: Paraffin deposition, wax, oil pipelines, experimental pipe loop.

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Authors: Hiroaki Nasu, Ryota Miyamoto, Yuta Kodera, Yasuyuki Nogami

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To promote Industry 4.0 and Society 5.0 and so on, it is important to connect and share data so that every member can trust it. Blockchain (BC) technology is currently attracting attention as the most advanced tool and has been used in the financial field and so on. However, the data collaboration using BC has not progressed sufficiently among companies on the supply chain of the manufacturing industry that handle sensitive data such as product quality, manufacturing conditions, etc. There are two main reasons why data utilization is not sufficiently advanced in the industrial supply chain. The first reason is that manufacturing information is top secret and a source for companies to generate profits. It is difficult to disclose data even between companies with transactions in the supply chain. Blockchain mechanism such as Bitcoin using Public Key Infrastructure (PKI) requires plaintext to be shared between companies in order to verify the identity of the company that sent the data. Another reason is that the merits (scenarios) of collaboration data between companies are not specifically specified in the industrial supply chain. For these problems, this paper proposes a Business to Business (B2B) collaboration system using homomorphic encryption and BC technique. Using the proposed system, each company on the supply chain can exchange confidential information on encrypted data and utilize the data for their own business. In addition, this paper considers a scenario focusing on quality data, which was difficult to collaborate because it is top-secret. In this scenario, we show an implementation scheme and a benefit of concrete data collaboration by proposing a comparison protocol that can grasp the change in quality while hiding the numerical value of quality data.

Keywords: Business to business data collaboration, industrial supply chain, blockchain, homomorphic encryption.

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Authors: Ahmed Barakat, Nourhan A. Saad, Mahmoud Hammad

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Tracking and monitoring agricultural products, cold chain activities, and transportation in real-time can effectively ensure both the quality and safety of agricultural products, as well as reduce overall logistics costs. Effective supply chain practices are one of the main requirements for enhancing agricultural business in Egypt. Cold chain is among the best practices for the storage and transportation of perishable goods and has potential within the agricultural sector in Egypt. This practice has the scope of reducing the wastage of food and increasing the profitability with a reduction in costs. Even though it has several implementation challenges for the farmers, traders, and people involved in the entire supply chain, it has highlighted better benefits for all and for the export of goods for the economic progression for Egypt. The aim of this paper is to explore cold supply chain practices for the agriculture sector in Egypt, to enhance the export performance of fresh goods. In this context, this study attempts to explore those aspects of the performance of cold supply chain practices that can enhance the functioning of the agriculture sector in Egypt from the perspective of export companies (traders) and farmers. Based on the empirical results obtained by data collection from the farmers and traders, the study argues that there is a significant association between cold supply chain practices and enhancement of the agriculture value chain. The paper thus highlights the contribution of the study with final conclusions and limitations with scope for future research.

Keywords: Agriculture sector, cold chain management, export companies, non-traded goods, supply chain management.

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Authors: Majid Saaly, Shahriar Tavousi Tafreshi, Mehdi Nazari Afshar

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Most reinforced concrete structures are designed only under heavy loads have large transverse reinforcement spacing values, and therefore suffer severe failure after intense ground movements. The main goal of this paper is to compare the shear- and axial failure of concrete bending frames available in Tehran using Incremental Dynamic Analysis (IDA) under near- and far-field records. For this purpose, IDA of 5, 10, and 15-story concrete structures were done under seven far-fault records and five near-faults records. The results show that in two-dimensional models of short-rise, mid-rise and high-rise reinforced concrete frames located on Type-3 soil, increasing the distance of the transverse reinforcement can increase the maximum inter-story drift ratio values up to 37%. According to the existing results on 5, 10, and 15-story reinforced concrete models located on Type-3 soil, records with characteristics such as fling-step and directivity create maximum drift values between floors more than far-fault earthquakes. The results indicated that in the case of seismic excitation modes under earthquake encompassing directivity or fling-step, the probability values of failure and failure possibility increasing rate values are much smaller than the corresponding values of far-fault earthquakes. However, in near-fault frame records, the probability of exceedance occurs at lower seismic intensities compared to far-fault records.

Keywords: Directivity, fling-step, fragility curve, IDA, inter story drift ratio.v

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Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

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Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: Conditional Generative Adversarial Net, market and credit risk management, neural network, time series.

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Authors: Dongseok Cho, Mitchell Driedger, Sera Han, Noman Khan, Mohammed Elmorsy, Mohamad El-Hajj

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Since the approval of the COVID-19 vaccine in late 2020, vaccination rates have varied around the globe. Access to a vaccine supply, mandated vaccination policy, and vaccine hesitancy contribute to these rates. This study used COVID-19 vaccination data from Our World in Data and the Multilateral Leaders Task Force on COVID-19 to create two COVID-19 vaccination indices. The first index is the Vaccine Utilization Index (VUI), which measures how effectively each country has utilized its vaccine supply to doubly vaccinate its population. The second index is the Vaccination Acceleration Index (VAI), which evaluates how efficiently each country vaccinated their populations within their first 150 days. Pearson correlations were created between these indices and country indicators obtained from the World Bank. Results of these correlations identify countries with stronger Health indicators such as lower mortality rates, lower age-dependency ratios, and higher rates of immunization to other diseases display higher VUI and VAI scores than countries with lesser values. VAI scores are also positively correlated to Governance and Economic indicators, such as regulatory quality, control of corruption, and GDP per capita. As represented by the VUI, proper utilization of the COVID-19 vaccine supply by country is observed in countries that display excellence in health practices. A country’s motivation to accelerate its vaccination rates within the first 150 days of vaccinating, as represented by the VAI, was largely a product of the governing body’s effectiveness and economic status, as well as overall excellence in health practises.

Keywords: Data mining, Pearson Correlation, COVID-19, vaccination rates, hesitancy.

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Authors: Gülden Küçükakça, Şefika Dilek Güven, Rahşan Kolutek, Seçil Taylan

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Objective: Nursing students face with stress factors affecting academic performance and quality of life as from first moments of their educational life. Stress causes health problems in students such as physical, psycho-social, and behavioral disorders and might damage formation of professional identity by decreasing efficiency of education. In addition to determination of stress experienced by nursing students during their education, it was aimed to help review theoretical and clinical education settings for bringing stress of nursing students into positive level and to raise awareness of educators concerning their own professional behaviors. Methods: The study was conducted with 315 students studying at nursing department of Semra and Vefa Küçük Health High School, Nevşehir Hacı Bektaş Veli University in the academic year of 2015-2016 and agreed to participate in the study. “Personal Information Form” prepared by the researchers upon the literature review and “Nursing Education Stress Scale (NESS)” were used in this study. Data were assessed with analysis of variance and correlation analysis. Results: Mean NESS Scale score of the nursing students was estimated to be 66.46±16.08 points. Conclusions: As a result of this study, stress level experienced by nursing undergraduate students during their education was determined to be high. In accordance with this result, it can be recommended to determine sources of stress experienced by nursing undergraduate students during their education and to develop approaches to eliminate these stress sources.

Keywords: Stress, nursing education, nursing student, nursing education stress.

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Authors: F. C. Amadi, G. C. Enyi, G. Nasr

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Relative permeabilities are practical factors that are used to correct the single phase Darcy’s law for application to multiphase flow. For effective characterisation of large-scale multiphase flow in hydrocarbon recovery, relative permeability and capillary pressures are used. These parameters are acquired via special core flooding experiments. Special core analysis (SCAL) module of reservoir simulation is applied by engineers for the evaluation of these parameters. But, core flooding experiments in shale core sample are expensive and time consuming before various flow assumptions are achieved for instance Darcy’s law. This makes it imperative for the application of coreflooding simulations in which various analysis of relative permeabilities and capillary pressures of multiphase flow can be carried out efficiently and effectively at a relative pace. This paper presents a Sendra software simulation of core flooding to achieve to relative permeabilities and capillary pressures using different correlations. The approach used in this study was three steps. The first step, the basic petrophysical parameters of Marcellus shale sample such as porosity was determined using laboratory techniques. Secondly, core flooding was simulated for particular scenario of injection using different correlations. And thirdly the best fit correlations for the estimation of relative permeability and capillary pressure was obtained. This research approach saves cost and time and very reliable in the computation of relative permeability and capillary pressures at steady or unsteady state, drainage or imbibition processes in oil and gas industry when compared to other methods.

Keywords: Special core analysis (SCAL), relative permeability, capillary pressures, drainage, imbibition.

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Authors: J. Bernasovska, I. Boronova, J. Poracova, M. Mydlarova Blascakova, V. Szabadosova, P. Ruzbarsky, E. Petrejcikova, I. Bernasovsky

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The paper presents the results of the molecular genetics analysis in sports research, with special emphasis to use genetic information in diagnosing of motoric predispositions in Roma boys from East Slovakia. The ability and move are the basic characteristics of all living organisms. The phenotypes are influenced by a combination of genetic and environmental factors. Genetic tests differ in principle from the traditional motoric tests, because the DNA of an individual does not change during life. The aim of the presented study was to examine motion abilities and to determine the frequency of ACTN3 (R577X) gene in Roma children. Genotype data were obtained from 138 Roma and 155 Slovak boys from 7 to 15 years old. Children were investigated on physical performance level in association with their genotype. Biological material for genetic analyses comprised samples of buccal swabs. Genotypes were determined using Real Time High resolution melting PCR method (Rotor-Gene 6000 Corbett and Light Cycler 480 Roche). The software allows creating reports of any analysis, where information of the specific analysis, normalized and differential graphs and many information of the samples are shown. Roma children of analyzed group legged to non-Romany children at the same age in all the compared tests. The % distribution of R and X alleles in Roma children was different from controls. The frequency of XX genotype was 9.26%, RX 46.33% and RR was 44.41%. The frequency of XX genotype was 9.26% which is comparable to a frequency of an Indian population. Data were analyzed with the ANOVA test.

Keywords: ACTN3 gene, R577X polymorphism, Roma children, Slovakia, sports performance.

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Authors: G. Gokceli, O. Eksik, E. Ozkan Zayim, N. Karatepe

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Alternative electrode materials for optoelectronic devices have been widely investigated in recent years. Since indium tin oxide (ITO) is the most preferred transparent conductive electrode, producing ITO films by simple and cost-effective solution-based techniques with enhanced optical and electrical properties has great importance. In this study, single- and multi-walled carbon nanotubes (SWCNT and MWCNT) incorporated into the ITO structure to increase electrical conductivity, mechanical strength, and chemical stability. Carbon nanotubes (CNTs) were firstly functionalized by acid treatment (HNO₃:H₂SO₄), and the thermal resistance of CNTs after functionalization was determined by thermogravimetric analysis (TGA). Thin films were then prepared by spin coating technique and characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), four-point probe measurement system and UV-Vis spectrophotometer. The effects of process parameters were compared for ITO, MWCNT-ITO, and SWCNT-ITO films. Two factors including CNT concentration and annealing temperature were considered. The UV-Vis measurements demonstrated that the transmittance of ITO films was 83.58% at 550 nm, which was decreased depending on the concentration of CNT dopant. On the other hand, both CNT dopants provided an enhancement in the crystalline structure and electrical conductivity. Due to compatible diameter and better dispersibility of SWCNTs in the ITO solution, the best result in terms of electrical conductivity was obtained by SWCNT-ITO films with the 0.1 g/L SWCNT dopant concentration and heat-treatment at 550 °C for 1 hour.

Keywords: CNT incorporation, ITO electrode, spin coating, thin film.

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Authors: N. H. Harun, A. S. Abdul Nasir, M. Y. Mashor, R. Hassan

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Leukaemia is a blood cancer disease that contributes to the increment of mortality rate in Malaysia each year. There are two main categories for leukaemia, which are acute and chronic leukaemia. The production and development of acute leukaemia cells occurs rapidly and uncontrollable. Therefore, if the identification of acute leukaemia cells could be done fast and effectively, proper treatment and medicine could be delivered. Due to the requirement of prompt and accurate diagnosis of leukaemia, the current study has proposed unsupervised pixel segmentation based on clustering algorithm in order to obtain a fully segmented abnormal white blood cell (blast) in acute leukaemia image. In order to obtain the segmented blast, the current study proposed three clustering algorithms which are k-means, fuzzy c-means and moving k-means algorithms have been applied on the saturation component image. Then, median filter and seeded region growing area extraction algorithms have been applied, to smooth the region of segmented blast and to remove the large unwanted regions from the image, respectively. Comparisons among the three clustering algorithms are made in order to measure the performance of each clustering algorithm on segmenting the blast area. Based on the good sensitivity value that has been obtained, the results indicate that moving kmeans clustering algorithm has successfully produced the fully segmented blast region in acute leukaemia image. Hence, indicating that the resultant images could be helpful to haematologists for further analysis of acute leukaemia.

Keywords: Acute Leukaemia Images, Clustering Algorithms, Image Segmentation, Moving k-Means.

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Authors: Jailan Mohamed El Demerdash

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Millennials are a distinctive and dominant consumer group whose behavior, preferences and purchase decisions are broadly explored but not fully understood yet. Making up the largest market segment in the world, and in Egypt, they have the power to reinvent the hospitality industry and contribute to forming prospective demand for green hotels by showing willingness to adopting their environmental-friendly practices. The current study aims to enhance better understanding of Millennials' perception about sustainable initiatives and to increase the prediction power of their intentions regarding green hotel practices in Egypt. In doing so, the study is exploring the relation among different factors; Millennials' environmental awareness, their acceptance of green practices and their willingness to pay more for them. Millennials' profile, their preferences and environmental decision-making process are brought under light to stimulate actions of hospitality decision-makers and hoteliers. Bearing in mind that responsible consumerism is depending on understanding the different influences on consumption. The study questionnaire was composed of four sections and it was distributed to random Egyptian travelers' blogs and Facebook groups, with approximately 8000 members. Analysis of variance test (ANOVA) was used to examine the study variables. The findings indicated that Millennials' environmental awareness will not be a significant factor in their acceptance of hotel green practices, as well as, their willingness to pay more for them. However, Millennials' acceptance of the level of hotel green practices will have an impact on their willingness to pay more. Millennials were found to have a noticeable level of environmental awareness but lack commitment to tolerating hotel green practices and their associated high prices.

Keywords: Millennials, environment, awareness, green practices, paying more, Egypt.

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Authors: Khaled Hamdan, Abid Amorri, Fatima Hamdan

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Involving students in English language learning process and achieving an adequate English language proficiency in the target language can be a great challenge for both teachers and students. This can prove even a far greater challenge to engage students with special needs (Dyslexia) if they have physical impairment and inadequate mastery of basic communicative language competence/proficiency in the target language. From this perspective, technology like robots can probably be used to enhance learning process for the special needs students who have extensive communication needs, who face continuous struggle to interact with their peers and teachers and meet academic requirements. Robots, precisely NAO, can probably provide them with the perfect opportunity to practice social and communication skills, and meet their English academic requirements. This research paper aims to identify to what extent robots can be used to improve students’ social interaction and communication skills and to understand the potential for robotics-based education in motivating and engaging UAEU dyslexic students to meet university requirements. To reach this end, the paper will explore several factors that come into play – Motion Level-involving cognitive activities, Interaction Level-involving language processing, Behavior Level -establishing a close relationship with the robot and Appraisal Level- focusing on dyslexia students’ achievement in the target language.

Keywords: Dyslexia, robot technology, motion, interaction, behavior and appraisal levels, social and communication skills.

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Authors: Armaghan Eslami, Nasrin Arshadi

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Scarce resources are the inseparable part of organization life. This fact that only small number of the employees can have these resources such as promotion, raise, and recognition can cause competition among employees, which create competitive climate. As well as any other competition, small number wins the reward, and a great number loses, one of the possible emotional reactions to this loss is negative emotions like malicious envy. In this case, the envious person may try to harm the envied person by reducing the prosocial behavior. Prosocial behavior is a behavior that aimed to benefit others. The main propose of this action is to maintain and increase well-being and well-fare of others. Therefore, one of the easiest ways for harming envied one is to suppress prosocial behavior. Prosocial behavior has positive and important implication for organizational efficiency. Our results supported our model and suggested that competitive climate has a significant effect on increasing workplace envy and on the other hand envy has significant negative impact on prosocial behavior. Our result also indicated that envy is the mediator in the relation between competitive climate and prosocial behavior. Organizational competitive climate can cause employees respond envy with negative emotion and hostile and damaging behavior toward envied person. Competition can lead employees to look out for proof of their self-worthiness; and, furthermore, they measure their self-worth, value and respect by the superiority that they gain in competitions. As a result, loss in competitions can harm employee’s self-definition and they try to protect themselves by devaluating envied other and being ‘less friendly’ to them. Some employees may find it inappropriate to engage in the harming behavior, but they may believe there is nothing against withholding the prosocial behavior.

Keywords: Competitive climate, mediator, prosocial behavior, workplace envy.

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Authors: Ntloana Hlabishi Peter

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The availability of public transportation modes and qualitative infrastructure is a burning issue that affects urban sustainability. Public transportation is indispensable in providing adequate transportation means to people at an affordable price, and it promotes public transport reliance. Burgersfort town has a critical condition on the urban public transportation infrastructure which affects the bus and taxi public transport modes and the existing infrastructure. The municipality is regarded as one of the mining towns in Limpopo Province considering the availability of mining activities and proposal on establishment of a Special Economic Zone (SEZ). The study aim is to assess the efficacy of current public transportation infrastructure and to propose relevant recommendations that will unlock the possibility of future supportable public transportation systems. The Key Informant Interview (KII) was used to acquire data on the views from commuters and stakeholders involved. There KII incorporated three relevant questions in relation to services rendered in public transportation. Relevant literature relating to public transportation modes and infrastructure revealed the imperatives of public transportation infrastructure, and relevant legislation was reviewed concerning public transport infrastructure. The finding revealed poor conditions on the public transportation ranks and also inadequate parking space for public transportation modes. The study reveals that 100% of people interviewed were not satisfied with the condition of public transportation infrastructure and 100% are not satisfied with the services offered by public transportation sectors. The findings revealed that the municipality is the main player who can upgrade the existing conditions of public transportation. The study recommended that an intermodal transportation facility must be established to resolve the emerging challenges.

Keywords: Public transportation, modes, infrastructure, urban sustainability.

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Authors: U. Datta

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The main objective of this study is to find a suitable approach to monitor the land infrastructure growth over a period of time using multispectral satellite images. Bi-temporal change detection method is unable to indicate the continuous change occurring over a long period of time. To achieve this objective, the approach used here estimates a statistical model from series of multispectral image data over a long period of time, assuming there is no considerable change during that time period and then compare it with the multispectral image data obtained at a later time. The change is estimated pixel-wise. Statistical composite hypothesis technique is used for estimating pixel based change detection in a defined region. The generalized likelihood ratio test (GLRT) is used to detect the changed pixel from probabilistic estimated model of the corresponding pixel. The changed pixel is detected assuming that the images have been co-registered prior to estimation. To minimize error due to co-registration, 8-neighborhood pixels around the pixel under test are also considered. The multispectral images from Sentinel-2 and Landsat-8 from 2015 to 2018 are used for this purpose. There are different challenges in this method. First and foremost challenge is to get quite a large number of datasets for multivariate distribution modelling. A large number of images are always discarded due to cloud coverage. Due to imperfect modelling there will be high probability of false alarm. Overall conclusion that can be drawn from this work is that the probabilistic method described in this paper has given some promising results, which need to be pursued further.

Keywords: Co-registration, GLRT, infrastructure growth, multispectral, multitemporal, pixel-based change detection.

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Authors: Krisna Damayanti, Lilis Ardini

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Many issues about the relationship between auditors in auditing practices with its stakeholders often heard. It appears in perspectives of bringing out the variety of phenomena affecting from the audit practice of greed and not appreciating from the independency of the audit profession and professional code of ethics. It becomes a logical consequence in practicing of capitalism in accounting. The main purpose of this article would like to uncover the existing auditing practices in Indonesia, especially in Java that associated with a strong influence of Javanese culture with reluctant /”shy", politely, "legowo (gratefully accepted)", "ngemong" (friendly), "not mentholo" (lenient), "tepo seliro" (tolerance), "ngajeni" (respectful), "acquiescent" and also reveals its relationships with Non Javanese culture in facing the conflict of interest in practical of auditing world. The method used by interpretive approach that emphasizes the role of language, interpret and understand and see social reality as something other than a label, name or concept. Global practices in auditing of each country have particular cultures that affect the standard set by those regulatory standards results the adaptation of IAS. The majority of parties in Indonesia is dominated by Javanese racial regulators, so Java culture is embedded in every audit practices and those conditions in Java leads auditors in having similar behaviour, sometimes interfere with standard Java code of conduct must be executed by an auditor. Auditors who live in Java have the characters of Javanese culture that is hard to avoid in the audit practice. However, practically, the auditors still are relevant in their profession.

Keywords: Auditors, java, character, profession, code of ethics, client.

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Authors: M. Yilmaz, I. Yilmaz, M. Uysal

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The Earth system generates different phenomena that are observable at the surface of the Earth such as mass deformations and displacements leading to plate tectonics, earthquakes, and volcanism. The dynamic processes associated with the interior, surface, and atmosphere of the Earth affect the three pillars of geodesy: shape of the Earth, its gravity field, and its rotation. Geodesy establishes a characteristic structure in order to define, monitor, and predict of the whole Earth system. The traditional and new instruments, observables, and techniques in geodesy are related to the gravity field. Therefore, the geodesy monitors the gravity field and its temporal variability in order to transform the geodetic observations made on the physical surface of the Earth into the geometrical surface in which positions are mathematically defined. In this paper, the main components of the gravity field modeling, (Free-air and Bouguer) gravity anomalies are calculated via recent global models (EGM2008, EIGEN6C4, and GECO) over a selected study area. The model-based gravity anomalies are compared with the corresponding terrestrial gravity data in terms of standard deviation (SD) and root mean square error (RMSE) for determining the best fit global model in the study area at a regional scale in Turkey. The least SD (13.63 mGal) and RMSE (15.71 mGal) were obtained by EGM2008 for the Free-air gravity anomaly residuals. For the Bouguer gravity anomaly residuals, EIGEN6C4 provides the least SD (8.05 mGal) and RMSE (8.12 mGal). The results indicated that EIGEN6C4 can be a useful tool for modeling the gravity field of the Earth over the study area.

Keywords: Free-air gravity anomaly, Bouguer gravity anomaly, global model, land gravity.

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Authors: Takashi Kaburagi, Masashi Takenaka, Yosuke Kurihara, Takashi Matsumoto

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Major depressive disorder (MDD) is one of the most common mental illnesses today. It is believed to be caused by a combination of several factors, including stress. Stress can be quantitatively evaluated using the State-Trait Anxiety Inventory (STAI), one of the best indices to evaluate anxiety. Although STAI scores are widely used in applications ranging from clinical diagnosis to basic research, the scores are calculated based on a self-reported questionnaire. An objective evaluation is required because the subject may intentionally change his/her answers if multiple tests are carried out. In this article, we present a modified index called the “multi-channel Laterality Index at Rest (mc-LIR)” by recording the brain activity from a wider area of the frontal lobe using multi-channel functional near-infrared spectroscopy (fNIRS). The presented index aims to measure multiple positions near the F_pz defined by the international 10-20 system positioning. Using 24 subjects, the dependencies on the number of measuring points used to calculate the mc-LIR and its correlation coefficients with the STAI scores are reported. Furthermore, a simple linear regression was performed to estimate the STAI scores from mc-LIR. The cross-validation error is also reported. The experimental results show that using multiple positions near the Fpz will improve the correlation coefficients and estimation than those using only two positions.

Keywords: Stress, functional near-infrared spectroscopy, frontal lobe, state-trait anxiety inventory score.

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Authors: Paula A. Cruise, Carvell McLeary

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

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

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Authors: Ziad Abdeldayem, Jakub Markiewicz, Kunal Kansara, Laura Edwards

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Airborne Laser Scanning (ALS) is one of the main technologies for generating high-resolution digital terrain models (DTMs). DTMs are crucial to several applications, such as topographic mapping, flood zone delineation, geographic information systems (GIS), hydrological modelling, spatial analysis, etc. Laser scanning system generates irregularly spaced three-dimensional cloud of points. Raw ALS data are mainly ground points (that represent the bare earth) and non-ground points (that represent buildings, trees, cars, etc.). Removing all the non-ground points from the raw data is referred to as filtering. Filtering heavily forested areas is considered a difficult and challenging task as the canopy stops laser pulses from reaching the terrain surface. This research presents an approach for removing non-ground points from raw ALS data in densely forested areas. Smoothing splines are exploited to interpolate and fit the noisy ALS data. The presented filter utilizes a weight function to allocate weights for each point of the data. Furthermore, unlike most of the methods, the presented filtering algorithm is designed to be automatic. Three different forested areas in the United Kingdom are used to assess the performance of the algorithm. The results show that the generated DTMs from the filtered data are accurate (when compared against reference terrain data) and the performance of the method is stable for all the heavily forested data samples. The average root mean square error (RMSE) value is 0.35 m.

Keywords: Airborne laser scanning, digital terrain models, filtering, forested areas.

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Authors: Ana Gabriela Diaz, Luis Fermín Córdova, Jr., Roberto Lamazares

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The island of Cuba, the largest of the Greater Antilles, is located in the tropical North Atlantic. It is annually affected by numerous weather events, which have caused severe damage to our coastal areas. In the same way that many other coastlines around the world, the beautiful beaches of the Hicacos Peninsula also suffer from erosion. This leads to a structural regression of the coastline. If measures are not taken, the hotels will be exposed to the advance of the sea, and it will be a serious problem for the economy. With the aim of studying the intensity of this type of activity, specialists of group of coastal and marine engineering from CIH, in the framework of the research conducted within the project MEGACOSTAS 2, provide their research to simulate extreme events and assess their impact in coastal areas, mainly regarding the definition of flood volumes and morphodynamic changes in sandy beaches. The main objective of this work is the evaluation of the process of Varadero beach erosion (the coastal sector has an important impact in the country's economy) on the Hicacos Peninsula for different paths of hurricanes. The mathematical model XBeach, which was integrated into the Coastal engineering system introduced by the project of MEGACOSTA 2 to determine the area and the more critical profiles for the path of hurricanes under study, was applied. The results of this project have shown that Center area is the greatest dynamic area in the simulation of the three paths of hurricanes under study, showing high erosion volumes and the greatest average length of regression of the coastline, from 15- 22 m.

Keywords: Beach, erosion, mathematical model, coastal areas.

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Authors: Othman Maklouf, Abdurazag Ghila, Ahmed Abdulla, Ameer Yousef

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Land vehicle navigation system technology is a subject of great interest today. Global Positioning System (GPS) is a common choice for positioning in such systems. However, GPS alone is incapable of providing continuous and reliable positioning, because of its inherent dependency on external electromagnetic signals. Inertial Navigation is the implementation of inertial sensors to determine the position and orientation of a vehicle. As such, inertial navigation has unbounded error growth since the error accumulates at each step. Thus in order to contain these errors some form of external aiding is required. The availability of low cost Micro-Electro-Mechanical-System (MEMS) inertial sensors is now making it feasible to develop Inertial Navigation System (INS) using an inertial measurement unit (IMU), in conjunction with GPS to fulfill the demands of such systems. Typically IMU’s are very expensive systems; however this INS will use “low cost” components. Unfortunately with low cost also comes low performance and is the main reason for the inclusion of GPS and Kalman filtering into the system. The aim of this paper is to develop a GPS/MEMS INS integrated system, which is able to provide a navigation solution with accuracy levels appropriate for land vehicle navigation. The primary piece of equipment used was a MEMS-based Crista IMU (from Cloud Cap Technology Inc.) and a Garmin GPS 18 PC (which is both a receiver and antenna). The integration of GPS with INS can be implemented using a Kalman filter in loosely coupled mode. In this integration mode the INS error states, together with any navigation state (position, velocity, and attitude) and other unknown parameters of interest, are estimated using GPS measurements. All important equations regarding navigation are presented along with discussion.

Keywords: GPS, IMU, Kalman Filter.

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Authors: A. Badoud, M. Khemliche, S. Latreche

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The main objective developed in this paper is to find a graphic technique for modeling, simulation and diagnosis of the industrial systems. This importance is much apparent when it is about a complex system such as the nuclear reactor with pressurized water of several form with various several non-linearity and time scales. In this case the analytical approach is heavy and does not give a fast idea on the evolution of the system. The tool Bond Graph enabled us to transform the analytical model into graphic model and the software of simulation SYMBOLS 2000 specific to the Bond Graphs made it possible to validate and have the results given by the technical specifications. We introduce the analysis of the problem involved in the faults localization and identification in the complex industrial processes. We propose a method of fault detection applied to the diagnosis and to determine the gravity of a detected fault. We show the possibilities of application of the new diagnosis approaches to the complex system control. The industrial systems became increasingly complex with the faults diagnosis procedures in the physical systems prove to become very complex as soon as the systems considered are not elementary any more. Indeed, in front of this complexity, we chose to make recourse to Fault Detection and Isolation method (FDI) by the analysis of the problem of its control and to conceive a reliable system of diagnosis making it possible to apprehend the complex dynamic systems spatially distributed applied to the standard pressurized water nuclear reactor.

Keywords: Bond Graph, Modeling, Simulation, Monitoring, Analytical Redundancy Relations, Pressurized Water Reactor, Directed Graph.

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: Deep learning, artificial neural networks, energy price forecasting, Turkey.

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Authors: Omid A. Zargar

Abstract:

Vibration analysis of most critical equipment is considered as one of the most challenging activities in preventive maintenance. Utilities are heart of the process in big industrial plants like petrochemical zones. Vibration analysis methods and condition monitoring systems of these kinds of equipments are developed too much in recent years. On the other hand, there are too much operation factors like inlet and outlet pressures and temperatures that should be monitored. In this paper, some of the most effective concepts and techniques related to gas turbine vibration analysis are discussed. In addition, a gas turbine SIEMENS 162MW - V94.2 vibration case history related to Iran power industry in Fars province is explained. Vibration monitoring system and machinery technical specification are introduced. Besides, absolute and relative vibration trends, turbine and compressor orbits, Fast Fourier transform (FFT) in absolute vibrations, vibration modal analysis, turbine and compressor start up and shut down conditions, bode diagrams for relative vibrations, Nyquist diagrams and waterfall or three-dimensional FFT diagrams in startup and trip conditions are discussed with relative graphs. Furthermore, Split Resonance in gas turbines is discussed in details. Moreover, some updated vibration monitoring system, blade manufacturing technique and modern damping mechanism are discussed in this paper.

Keywords: Gas turbine, turbine compressor, vibration data collector, utility, condition monitoring, non-contact probe, Relative Vibration, Absolute Vibration, Split Resonance, Time Wave Form (TWF), Fast Fourier transform (FFT).

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Authors: Chan Eang Teng, Tang Mui Joo

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In the beginning of the prevalence of social media, it would be an obvious trend that the young adult age group has the highest population among the users on social media. However, apart from the age group of the users are becoming younger and younger, the elderly group has become a new force on social media, and this age group has increased rapidly. On top of that, the influence of social media towards the elderly is becoming more significant and it is even trending among them. This is because basic computer knowledge is not instilled into their life when they were young. This age group tends to be engrossed more than the young as this is something new for them, and they have the mindset that it is a new platform to approach things, and they tend to be more engrossed when they start getting in touch with the social media. Generally, most of the social media has been accepted and accessed by teenagers and young adult, but it is reasonable to believe that the social media is not really accepted among the elderly. Surprisingly, the elderlies are more addicted to the social media than the teenagers. Therefore, this study is to determine and understand the relationship between the elderly and social media, and how they employ social media in their lives. An online survey on 200 elderly aged 45-80 and an interview with a media expert are conducted to answer the main questions in the research paper. Uses and Gratification Approach is employed in theoretical framework. Finding revealed that majority of the respondents use social media to connect with family, friends, and for leisure purposes. The finding concluded that the elderly use social media differently according to their needs and wants which is in par with the highlight of Uses and Gratification theory. Considering the significantly large role social media plays in our culture and daily life today, the finding will shed some light on the effect of social media on the elderly or senior citizens who are usually relegated into a minority group in today’s age where the internet and social media are of great importance to our society and humanity in general. This may also serve to be useful in understanding behavioral patterns and preference in terms of social media usage among the elderly.

Keywords: Elderly, Facebook, Malaysia, social media.

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