Search results for: short circuit test

Authors: Eyup Dogan

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The number of research articles analyzing the integration properties of energy variables has rapidly increased in the energy literature for about a decade. The stochastic behaviors of energy variables are worth knowing due to several reasons. For instance, national policies to conserve or promote energy consumption, which should be taken as shocks to energy consumption, will have transitory effects in energy consumption if energy consumption is found to be stationary in one country. Furthermore, it is also important to know the order of integration to employ an appropriate econometric model. Despite being an important subject for applied energy (economics) and having a huge volume of studies, several known limitations still exist with the existing literature. For example, many of the studies use aggregate energy consumption and national level data. In addition, a huge part of the literature is either multi-country studies or solely focusing on the U.S. This is the first study in the literature that considers a form of energy consumption by sectors at sub-national level. This research study aims at investigating unit root properties of electricity consumption for 12 regions of Turkey by four sectors in addition to total electricity consumption for the purpose of filling the mentioned limits in the literature. In this regard, we analyze stationarity properties of 60 cases . Because the use of multiple unit root tests make the results robust and consistent, we apply Dickey-Fuller unit root test based on Generalized Least Squares regression (DFGLS), Phillips-Perron unit root test (PP) and Zivot-Andrews unit root test with one endogenous structural break (ZA). The main finding of this study is that electricity consumption is trend stationary in 7 cases according to DFGLS and PP, whereas it is stationary process in 12 cases when we take into account the structural change by applying ZA. Thus, shocks to electricity consumption have transitory effects in those cases; namely, agriculture in region 1, region 4 and region 7, industrial in region 5, region 8, region 9, region 10 and region 11, business in region 4, region 7 and region 9, total electricity consumption in region 11. Regarding policy implications, policies to decrease or stimulate the use of electricity have a long-run impact on electricity consumption in 80% of cases in Turkey given that 48 cases are non-stationary process. On the other hand, the past behavior of electricity consumption can be used to predict the future behavior of that in 12 cases only.

Keywords: unit root, electricity consumption, sectoral data, subnational data

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Authors: Muhammad Shafiq, Huynh Trung Luong

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In this paper, we proposed a commitment based revenue sharing contract for a supply chain comprising one manufacturer and one retailer facing highly uncertain demand of a short life span fashionable product. In our model, the retailer reserves a commitment level with the manufacturer prior to the selling season. In response, the manufacturer allocates and produces a specific quantity which is the maximum available quantity for the retailer. The retailer is motivated to commit more by offering higher revenue sharing percentage for reserved capacity than non-reserved capacity. Due to asymmetric information, it is found that the manufacturer can optimize quantity allocation decision while the commitment level decision of the retailer may not be optimal.

Keywords: supply chain coordination, revenue sharing contract, commitment based revenue sharing, quantity allocation

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Authors: Dale Dzemydiene, Aurelija Burinskiene, Arunas Miliauskas, Kristina Ciziuniene

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Data flow and the purpose of reporting the data are different and dependent on business needs. Different parameters are reported and transferred regularly during freight delivery. This business practices form the dataset constructed for each time point and contain all required information for freight moving decisions. As a significant amount of these data is used for various purposes, an integrating methodological approach must be developed to respond to the indicated problem. The proposed methodology contains several steps: (1) collecting context data sets and data validation; (2) multi-objective analysis for optimizing freight transfer services. For data validation, the study involves Grubbs outliers analysis, particularly for data cleaning and the identification of statistical significance of data reporting event cases. The Grubbs test is often used as it measures one external value at a time exceeding the boundaries of standard normal distribution. In the study area, the test was not widely applied by authors, except when the Grubbs test for outlier detection was used to identify outsiders in fuel consumption data. In the study, the authors applied the method with a confidence level of 99%. For the multi-objective analysis, the authors would like to select the forms of construction of the genetic algorithms, which have more possibilities to extract the best solution. For freight delivery management, the schemas of genetic algorithms' structure are used as a more effective technique. Due to that, the adaptable genetic algorithm is applied for the description of choosing process of the effective transportation corridor. In this study, the multi-objective genetic algorithm methods are used to optimize the data evaluation and select the appropriate transport corridor. The authors suggest a methodology for the multi-objective analysis, which evaluates collected context data sets and uses this evaluation to determine a delivery corridor for freight transfer service in the multi-modal transportation network. In the multi-objective analysis, authors include safety components, the number of accidents a year, and freight delivery time in the multi-modal transportation network. The proposed methodology has practical value in the management of multi-modal transportation processes.

Keywords: multi-objective, analysis, data flow, freight delivery, methodology

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Authors: Djemai Bara, Mohamed Faouzi Mahboub, Djamila Bennaceur-Doumaz

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In this work, the role of the preformed plasma created on the front face of a target, irradiated by a high intensity short pulse laser, in the framework of ion acceleration process, modeled by Target Normal Sheath Acceleration (TNSA) mechanism, is studied. This plasma is composed of cold ions governed by fluid equations and non-thermal & trapped with densities represented by a "Cairns-Gurevich" equation. The self-similar solution of the equations shows that electronic trapping and the presence of non-thermal electrons in the pre-plasma are both responsible in ion acceleration as long as the proportion of energetic electrons is not too high. In the case where the majority of electrons are energetic, the electrons are accelerated directly by the ponderomotive force of the laser without the intermediate of an accelerating plasma wave.

Keywords: Cairns-Gurevich Equation, ion acceleration, plasma expansion, pre-plasma

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Authors: Reinhard Neck, Guido Schäfer

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In this paper, we explore the macroeconomic effects of the European Single Market on Austria by simulating the McKibbin-Sachs Global Model. Global interdependence and the impact of long-run effects on short-run adjustments are taken into account. We study the sensitivity of the results with respect to different assumptions concerning monetary and fiscal policies for the countries and regions of the world economy. The consequences of different assumptions about budgetary policies in Austria are also investigated. The simulation results are contrasted with ex-post evaluations of the actual impact of Austria’s membership in the Single Market. As a result, it can be concluded that the Austrian participation in the European Single Market entails considerable long-run gains for the Austrian economy with nearly no adverse side-effects on any macroeconomic target variable.

Keywords: macroeconomics, European Union, simulation, sensitivity analysis

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Authors: Cathy Basterfield

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Issue: To engage in one’s own health care, health professionals need to be aware of an individual’s specific skills and abilities for best communication. One of the most discussed is health literacy. One of the assumed skills and abilities for adults is an individuals’ health literacy. Background: A review of publicly available health content appears to assume all adult readers will have a broad and full capacity to read at a high level of literacy, often at a post-school education level. Health information writers and clinicians need to recognise one critical area for why there may be little or no change in a person’s behaviour, or no-shows to appointments. Perhaps unintentionally, they are miscommunicating with the majority of the adult population. Health information contains many literacy domains. It usually includes technical medical terms or jargon. Many fact sheets and other information require scientific literacy with or without specific numerical literacy. It may include graphs, percentages, timing, distance, or weights. Each additional word or concept in these domains decreases the readers' ability to meaningfully read, understand and know what to do with the information. An attempt to begin to read the heading where long or unfamiliar words are used will reduce the readers' motivation to attempt to read. Critically people who have low literacy are overwhelmed when pages are covered with lots of words. People attending a health environment may be unwell or anxious about a diagnosis. These make it harder to read, understand and know what to do with the information. But access to health information must consider an even wider range of adults, including those with poor school attainment, migrants, and refugees. It is also homeless people, people with mental health illnesses, or people who are ageing. People with low literacy also may include people with lifelong disabilities, people with acquired disabilities, people who read English as a second (or third) language, people who are Deaf, or people who are vision impaired. Outcome: This paper will discuss Easy English, which is developed for adults. It uses the audiences’ everyday words, short sentences, short words, and no jargon. It uses concrete language and concrete, specific images to support the text. It has been developed in Australia since the mid-2000s. This paper will showcase various projects in the health domain which use Easy English to improve the understanding and functional use of written information for the large numbers of adults in our communities who do not have the health literacy to manage a range of day to day reading tasks. See examples from consent forms, fact sheets and choice options, instructions, and other functional documents, where Easy English has been developed. This paper will ask individuals to reflect on their own work practice and consider what written information must be available in Easy English. It does not matter how cutting-edge a new treatment is; when adults can not read or understand what it is about and the positive and negative outcomes, they are less likely to be engaged in their own health journey.

Keywords: health literacy, inclusion, Easy English, communication

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Authors: Ming Gao, Matthew Tingchi Liu, Hoi Ngan Loi

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Live streaming refers to the video contents generated by broadcasters and shared with viewers in real-time by uploading them to short-video platforms. In recent years, individual KOL broadcasters have successfully made use of live streams to sell a large amount of goods to the consumers. For example, Wei Ya, the Number 1 broadcaster in Taobao Live, sold products worth RMB 2.7 billion (USD 0.38 billion) in 2018. Regarding the success of live streaming commerce (LSC) in China, this study explores the elements of the booming LSC industry and attempts to explain the reasons behind its prosperity. A systematic review of industry reports and academic papers was conducted to summarize the latest findings in this field. And the results of this investigation showed that a live streaming eco-system has been established by the LSC players, namely, the platform, the broadcaster, the product supplier, and the viewer. In this eco-system, all players have complementary advantages and needs, and their close cooperation leads to a win-win situation. For instance, platforms and broadcasters have abundant internet traffic, which needs to be monetized, while product suppliers have mature supply chains and the need of promoting the products. In addition, viewers are attached to the LSC platforms to get product information, bargains, and entertainment. This study highlights the importance of the mass-personal hybrid communication nature of live streaming because its interpersonal communication feature increases consumers’ positive experiences, while its mass media broadcasting feature facilitates product promotion. Another innovative point of this study lies in its inclusion of the special characteristic of Chinese Internet culture - entertainment. The entertaining genres of the live streams created by broadcasters serve as down-to-earth approaches to reach their audiences easily. Further, the nature of video, i.e., the dynamic and salient stimulus, is emphasized in this study. Since video is more engaging, it can attract viewers in a quick and easy way. Meanwhile, the abundant, interesting, high-quality, and free short videos have added “stickiness” to platforms by retaining users and prolonging their staying time on the platforms. In addition, broadcasters’ important characters, such as physical attractiveness, humor, sex appeal, kindness, communication skills, and interactivity, are also identified as important factors that influence consumers’ engagement and purchase intention. In conclusion, all players have their own proper places in this live streaming eco-system, in which they work seamlessly to give full play to their respective advantages, with each player taking what it needs and offering what it has. This has contributed to the success of live streaming commerce in China.

Keywords: broadcasters, communication, entertainment, live streaming commerce, viewers

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Authors: Haifeng Zhou, Tsungyang Liow, Xiaoguang Tu, Eujin Lim, Chao Li, Junfeng Song, Xianshu Luo, Ying Huang, Lianxi Jia, Lianwee Luo, Qing Fang, Mingbin Yu, Guoqiang Lo

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With the development of technology, countries gradually allocated more and more frequency spectrums for civilization and commercial usage, especially those high radio frequency bands indicating high information capacity. The field effect becomes more and more prominent in microwave components as frequency increases, which invalidates the transmission line theory and complicate the design of microwave components. Here a modeling approach based on numerical search algorithm is proposed to design various building blocks for microwave circuits to avoid complicated impedance matching and equivalent electrical circuit approximation. Concretely, a microwave component is discretized to a set of segments along the microwave propagation path. Each of the segment is initialized with random dimensions, which constructs a multiple-dimension parameter space. Then numerical searching algorithms (e.g. Pattern search algorithm) are used to find out the ideal geometrical parameters. The optimal parameter set is achieved by evaluating the fitness of S parameters after a number of iterations. We had adopted this approach in our current projects and designed many microwave components including sharp bends, T-branches, Y-branches, microstrip-to-stripline converters and etc. For example, a stripline 90° bend was designed in 2.54 mm x 2.54 mm space for dual-band operation (Ka band and Ku band) with < 0.18 dB insertion loss and < -55 dB reflection. We expect that this approach can enrich the tool kits for microwave designers.

Keywords: microwave component, microstrip and stripline, bend, power division, the numerical search algorithm.

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Authors: Hossein Nikandam Kermanshah, Babak Samavatian, Akbar Hemmati Sabet, Mohammad Ahmadpanah

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This is a quasi-experimental study that has been conducted in order to compare the effectiveness of social skills training and stress management training on self-esteem and aggression in first grade high school students. Forty-five people were selected from research community and were put randomly in there groups of social skills training, stress management training and control ones. Collecting data tools in this study was devise, self-esteem and AGQ aggression questionnaire. Self-esteem and aggression questionnaires has been conducted as the pre-test and post-test. Social skills training and stress management groups participated in eight 1.5 hour session in a week. But control group did not receive any therapy. For descriptive analysis of data, statistical indicators like mean, standard deviation were used, and in inferential statistics level multi variable covariance analysis have been used. The finding result show that group training social skills and stress management is significantly effective on the self-esteem and aggression, there is a meaningful difference between training social skills and stress management on self-esteem that the preference is with group social skills training, in the difference between group social skills training and stress management on aggression, the preference is with group stress management.

Keywords: social skill training, stress management training, self-esteem aggression, psychological sciences

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Authors: Vinay C. Doranalu, Amba Shetty

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In recent days due to climate change, there is a large variation in spatial distribution of daily rainfall within a small region. Rainfall is one of the main end climatic variables which affect spatio-temporal patterns of water availability. The real task postured by the change in climate is identification, estimation and understanding the uncertainty of rainfall. This study intended to analyze the spatial variations and temporal trends of daily precipitation using high resolution (0.25º x 0.25º) gridded data of Indian Meteorological Department (IMD). For the study, 38 grid points were selected in the study area and analyzed for daily precipitation time series (113 years) over the period 1901-2013. Grid points were divided into two zones based on the elevation and situated location of grid points: Low Land (exposed to sea and low elevated area/ coastal region) and High Land (Interior from sea and high elevated area/western Ghats). Time series were applied to examine the spatial analysis and temporal trends in each grid points by non-parametric Mann-Kendall test and Theil-Sen estimator to perceive the nature of trend and magnitude of slope in trend of rainfall. Pettit-Mann-Whitney test is applied to detect the most probable change point in trends of the time period. Results have revealed remarkable monotonic trend in each grid for daily precipitation of the time series. In general, by the regional cluster analysis found that increasing precipitation trend in shoreline region and decreasing trend in Western Ghats from recent years. Spatial distribution of rainfall can be partly explained by heterogeneity in temporal trends of rainfall by change point analysis. The Mann-Kendall test shows significant variation as weaker rainfall towards the rainfall distribution over eastern parts of the Western Ghats region of Karnataka.

Keywords: change point analysis, coastal region India, gridded rainfall data, non-parametric

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Authors: Malik Abdul Jabbar Zen, Wiwik Misaco Yuniarti, Azisya Amalia Karimasari, Novita Priandini

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Zoonos is as an infectiontransmitted froma nimals to human sand vice versa currently having increased in the last 20 years. The experts/scientists predict that zoonosis will be a threat to the community in the future since it leads on 70% emerging infectious diseases (EID) and the high mortality of 50%-90%. The zoonosis’ spread from animal to human is caused by contaminated food known as foodborne disease. One World One Health, as the conceptual prevention toward zoonosis, requires the crossed disciplines cooperation to accelerate and streamlinethe handling ofanimal-based disease. E-Vet Smart Rapid System is an integrated innovation in the veterinary expertise application is able to facilitate the prevention, treatment, and educationagainst pandemic diseases and zoonosis. This system is constructed by Decision Support System (DSS) method provides a database of knowledge that is expected to facilitate the identification of disease rapidly, precisely, and accurately as well as to identify the deduction. The testingis conducted through a black box test case and questionnaire (N=30) by validity and reliability approach. Based on the black box test case reveals that E-Vet Rapid System is able to deliver the results in accordance with system design, and questionnaire shows that this system is valid (r > 0.361) and has a reliability (α > 0.3610).

Keywords: diagnosis, disease, expert systems, livestock, zoonosis

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Authors: Bowei Yuan, Shi Li, Liuyang Song, Huaqing Wang, Lingli Cui

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Convolutional neural networks (CNN) have received extensive attention in the field of fault diagnosis. Many fault diagnosis methods use CNN for fault type identification. However, when the amount of raw data collected by sensors is massive, the neural network needs to perform a time-consuming classification task. In this paper, a mechanical fault diagnosis method based on vibration signal down-sampling and the improved one-dimensional convolutional neural network is proposed. Through the robust principal component analysis, the low-rank feature matrix of a large amount of raw data can be separated, and then down-sampling is realized to reduce the subsequent calculation amount. In the improved one-dimensional CNN, a smaller convolution kernel is used to reduce the number of parameters and computational complexity, and regularization is introduced before the fully connected layer to prevent overfitting. In addition, the multi-connected layers can better generalize classification results without cumbersome parameter adjustments. The effectiveness of the method is verified by monitoring the signal of the centrifugal pump test bench, and the average test accuracy is above 98%. When compared with the traditional deep belief network (DBN) and support vector machine (SVM) methods, this method has better performance.

Keywords: fault diagnosis, vibration signal down-sampling, 1D-CNN

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Authors: C. Hall, J. Ramos, V. Ramasamy

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Hydrocarbon-based fuel vehicles are a major contributor to air pollution due to harmful emissions produced, leading to a demand for cleaner fuel types. A leader in this pursuit is hydrogen, with its application in vehicles producing zero harmful emissions and the only by-product being water. To compete with the performance of conventional vehicles, hydrogen gas must be stored on-board of vehicles in cylinders at high pressures (35–70 MPa) and have a short refueling duration (approximately 3 mins). However, the fast-filling of hydrogen cylinders causes a significant rise in temperature due to the combination of the negative Joule-Thompson effect and the compression of the gas. This can lead to structural failure and therefore, a maximum allowable internal temperature of 85°C has been imposed by the International Standards Organization. The technological solution to tackle the issue of rapid temperature rise during the refueling process is to decrease the temperature of the gas entering the cylinder. Pre-cooling of the gas uses a heat exchanger and requires energy for its operation. Thus, it is imperative to determine the least amount of energy input that is required to lower the gas temperature for cost savings. A validated universal thermodynamic model is used to identify an energy-efficient pre-cooling strategy. The model requires negligible computational time and is applied to previously validated experimental cases to optimize pre-cooling requirements. The pre-cooling characteristics include the location within the refueling timeline and its duration. A constant pressure-ramp rate is imposed to eliminate the effects of rapid changes in mass flow rate. A pre-cooled gas temperature of -40°C is applied, which is the lowest allowable temperature. The heat exchanger is assumed to be ideal with no energy losses. The refueling of the cylinders is modeled with the pre-cooling split in ten percent time intervals. Furthermore, varying burst durations are applied in both the early and late stages of the refueling procedure. The model shows that pre-cooling in the later stages of the refuelling process is more energy-efficient than early pre-cooling. In addition, the efficiency of pre-cooling towards the end of the refueling process is independent of the pressure profile at the inlet. This leads to the hypothesis that pre-cooled gas should be applied as late as possible in the refueling timeline and at very low temperatures. The model had shown a 31% reduction in energy demand whilst achieving the same final gas temperature for a refueling scenario when pre-cooling was applied towards the end of the process. The identification of the most energy-efficient refueling approaches whilst adhering to the safety guidelines is imperative to reducing the operating cost of hydrogen refueling stations. Heat exchangers are energy-intensive and thus, reducing the energy requirement would lead to cost reduction. This investigation shows that pre-cooling should be applied as late as possible and for short durations.

Keywords: cylinder, hydrogen, pre-cooling, refueling, thermodynamic model

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Authors: Kilari Nikhil, Ankur Tibrewal, Srinivas Kruthiventi S. S.

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Conventional speaker identification systems often fall short of capturing the diverse variations present in speech data due to fixed-scale architectures. In this research, we propose a CNN-based architecture, USENet, designed to overcome these limitations. Leveraging two key techniques, our approach achieves superior performance on the VoxCeleb 1 Dataset without any pre-training. Firstly, we adopt a U-net-inspired design to extract features at multiple scales, empowering our model to capture speech characteristics effectively. Secondly, we introduce the squeeze and excitation block to enhance spatial feature learning. The proposed architecture showcases significant advancements in speaker identification, outperforming existing methods, and holds promise for future research in this domain.

Keywords: multi-scale feature extraction, squeeze and excitation, VoxCeleb1 speaker identification, mel-spectrograms, USENet

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Authors: Faruk Elaldi

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There are lots of concrete columns and beams around in our living cities. Those columns are mostly open to aggressive environmental conditions and earthquakes. Mostly, they are deteriorated by sand, wind, humidity and other external applications at times. After a while, these beams and columns need to be repaired. Within the scope of this study, for reinforcement of concrete columns, samples were designed and fabricated to be strengthened with carbon fiber reinforced composite materials and conventional concrete encapsulation and followed by, and they were put into the axial compression test to determine load-carrying performance before column failure. In the first stage of this study, concrete column design and mold designs were completed for a certain load-carrying capacity. Later, the columns were exposed to environmental deterioration in order to reduce load-carrying capacity. To reinforce these damaged columns, two methods were applied, “concrete encapsulation” and the other one “wrapping with carbon fiber /epoxy” material. In the second stage of the study, the reinforced columns were applied to the axial compression test and the results obtained were analyzed. Cost and load-carrying performance comparisons were made and it was found that even though the carbon fiber/epoxy reinforced method is more expensive, this method enhances higher load-carrying capacity and reduces the reinforcement processing period.

Keywords: column reinforcement, composite, earth quake, carbon fiber reinforced

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Authors: S. Jakšić, B. Žmuk

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The paper investigates the key factors of export dynamics for a set of Central and Southeast European (CSEE) countries in the context of current economic and financial crisis. In order to model the export dynamics a Global Vector Auto Regressive (GVAR) model is defined. As opposed to models which model each country separately, the GVAR combines all country models in a global model which enables obtaining important information on spill-over effects in the context of globalization and rising international linkages. The results of the study indicate that for most of the CSEE countries, exports are mainly driven by domestic shocks, both in the short run and in the long run. This study is the first application of the GVAR model to studying the export dynamics in the CSEE countries and therefore the results of the study present an important empirical contribution.

Keywords: export, GFEVD, global VAR, international trade, weak exogeneity

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Authors: Noora Al-Shanfari, M. Mazharul Islam

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The cumulative incidence function (CIF) is a fundamental approach for analyzing survival data in the presence of competing risks, which estimates the marginal probability for each competing event. Parametric modeling of CIF has the advantage of fitting various shapes of CIF and estimates the impact of covariates with maximum efficiency. To calculate the total CIF's covariate influence using a parametric model., it is essential to parametrize the baseline of the CIF. As the CIF is an improper function by nature, it is necessary to utilize an improper distribution when applying parametric models. The Gompertz distribution, which is an improper distribution, is limited in its applicability as it only accounts for monotone hazard shapes. The generalized Gompertz distribution, however, can adapt to a wider range of hazard shapes, including unimodal, bathtub, and monotonic increasing or decreasing hazard shapes. In this paper, the generalized Gompertz distribution is used to parametrize the baseline of the CIF, and the parameters of the proposed model are estimated using the maximum likelihood approach. The proposed model is compared with the existing Gompertz model using the Akaike information criterion. Appropriate statistical test procedures and model-fitting criteria will be used to test the adequacy of the model. Both models are applied to the ‘colon’ dataset, which is available in the “biostat3” package in R.

Keywords: competing risks, cumulative incidence function, improper distribution, parametric modeling, survival analysis

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Authors: Eric S. Lee, Connie Bygrave, Jordan Mahar, Naina Garg, Suzanne Cottreau

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Marking exams is universally detested by lecturers. Final exams in many higher education courses often last 3.0 hrs. Do exams really need to be so long? Can we justifiably reduce the number of questions on them? Surprisingly few have researched these questions, arguably because of the complexity and difficulty of using traditional methods. To answer these questions empirically, we used a new approach based on three key elements: Use of an unusual variation of a true experimental design, equivalence hypothesis testing, and an expanded set of six psychometric criteria to be met by any shortened exam if it is to replace a current 3.0-hr exam (reliability, validity, justifiability, number of exam questions, correspondence, and equivalence). We compared student performance on each official 3.0-hr exam with that on five shortened exams having proportionately fewer questions (2.5, 2.0, 1.5, 1.0, and 0.5 hours) in a series of four experiments conducted in two classes in each of two finance courses (224 students in total). We found strong evidence that, in these courses, shortening of final exams to 2.0 hrs was warranted on all six psychometric criteria. Shortening these exams by one hour should result in a substantial one-third reduction in lecturer time and effort spent marking, lower student stress, and more time for students to prepare for other exams. Our approach provides a relatively simple, easy-to-use methodology that lecturers can use to examine the effect of shortening their own exams.

Keywords: exam length, psychometric criteria, synthetic experimental designs, test length

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Authors: Fatima Babar, Majid I. Khan, Malik Najmus Saqib, Muhammad Tahir

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This article provides range based improvements over a well-known single-hop range free localization scheme, Approximate Point in Triangulation (APIT) by proposing an energy efficient Barycentric coordinate based Point-In-Triangulation (PIT) test along with PIT based trilateration. These improvements result in energy efficiency, reduced localization error and improved localization coverage compared to APIT and its variants. Moreover, we propose to embed Received signal strength indication (RSSI) based distance estimation in DV-Hop which is a multi-hop localization scheme. The proposed localization algorithm achieves energy efficiency and reduced localization error compared to DV-Hop and its available improvements. Furthermore, a hybrid multi-hop localization scheme is also proposed that utilize Barycentric coordinate based PIT test and both range based (Received signal strength indicator) and range free (hop count) techniques for distance estimation. Our experimental results provide evidence that proposed hybrid multi-hop localization scheme results in two to five times reduction in the localization error compare to DV-Hop and its variants, at reduced energy requirements.

Keywords: Localization, Trilateration, Triangulation, Wireless Sensor Networks

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Authors: Mark Archei O. Javier

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The Fourth Industrial Revolution (FIR) is a major industrial era characterized by the fusion of technologies that is blurring the lines between the physical, digital, and biological spheres. Since this era teaches us how to thrive in the fast-paced developing world, it is important to be able to adapt. With this, there is a need to make learning and teaching in the bioscience laboratory more challenging and engaging. The goal of the research is to find out if using in silico and in vitro laboratory activities compared to the conventional conduct laboratory activities would have positive impacts on the academic performance of the learners. The potential contribution of the research is that it would improve the teachers’ methods in delivering the content to the students when it comes to topics that need laboratory activities. This study will develop a method by which teachers can provide learning materials to the students. A one-tailed t-Test for independent samples was used to determine the significant difference in the pre- and post-test scores of students. The tests of hypotheses were done at a 0.05 level of significance. Based on the results of the study, the gain scores of the experimental group are greater than the gain scores of the control group. This implies that using in silico and in vitro labs for the experimental group is more effective than the conventional method of doing laboratory activities.

Keywords: academic performance, general biology, in silico laboratory, in vivo laboratory, virtual laboratory

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Authors: M. S. Lu, Y. P. Tsai, H. Shu, K. F. Chen, L. L. Lai

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This study used sodium hypochlorite/sodium dodecyl sulfate method to successfully extract polyhydroxyalkanoates (PHA) from the wasted sludge of a husbandry industry wastewater treatment plant. We investigated the optimum operational conditions of three key factors with respect to effectively extract PHAs from husbandry industry wastewater sludge, including the sodium hypochlorite concentration, liquid-solid ratio, and reaction time. The experimental results showed the optimum operational conditions for polyhydroxyalkanoate recovery as follows: (1) being digested by the sodium hypochlorite/sodium dodecyl sulfate solution with 15% (v/v) of hypochlorite concentration, (2) being operated at the condition of 1.25 mLmg-1 of liquid-solid ratio, and (3) being reacted for more than 60 min. Under these conditions, the content of the recovered PHAs was about 53.2±0.66 mgPHAs/gVSS, and the purity of the recovered PHAs was about 78.5±6.91 wt%. The recovered PHAs were further used to produce biodegradable plastics for decomposition test buried in soils. The decomposition test showed 66.5% of the biodegradable plastics produced in the study remained after being buried in soils for 49 days. The cost for extracting PHAs is about 10.3 US$/kgPHAs and is lower than those produced by pure culture methods (12-15 US$/kgPHAs).

Keywords: biodegradable plastic, biopolymers, polyhydroxyalkanoates (PHAs), waste sludge

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Authors: El Asnaoui Khalid, Chawki Youness, Aksasse Brahim, Ouanan Mohammed

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In these recent decades, the important and fast growth in the development and demand of multimedia products is contributing to an insufficient in the bandwidth of device and network storage memory. Consequently, the theory of data compression becomes more significant for reducing the data redundancy in order to save more transfer and storage of data. In this context, this paper addresses the problem of the lossless and the near-lossless compression of images. This proposed method is based on Block SVD Power Method that overcomes the disadvantages of Matlab's SVD function. The experimental results show that the proposed algorithm has a better compression performance compared with the existing compression algorithms that use the Matlab's SVD function. In addition, the proposed approach is simple and can provide different degrees of error resilience, which gives, in a short execution time, a better image compression.

Keywords: image compression, SVD, block SVD power method, lossless compression, near lossless

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Authors: Mananya Meenakorn

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This research aims to investigate: (1) Relationship between the quality of working life and organizational commitment of municipal employee in Samut Sakhon Province. (2) To compare the quality of working life and the organizational commitment of municipal employee in Samut Sakhon Province by the gender, age, education, official experience, position, division, and income. This study is a quantitative research; data was collected by questionnaires distributed to the municipal employee in Samut Sakhon province for 241 sample by stratified random sampling. Data was analyzed by descriptive statistic including percentage, mean, standard deviation and inferential statistic including t-test, F-test and Pearson correlation for hypothesis testing. Finding showed that the quality of working life and the organizational commitment of municipal Employee in Samut Sakhon province in terms of compensation and fair has a positive correlation (r = 0.673) and the comparison of the quality of working life and organizational commitment of municipal employees in Samut Sakhon province by gender. We found that the overall difference was statistically significant at the 0.05 level and we also found stability and progress in career path and the characteristics are beneficial to society has a difference was statistically significant at the 0.01 level, and the participation and social acceptance has a difference was statistically significant at the 0.05 level.

Keywords: quality of working life, organizational commitment, municipal employee, Samut Sakhon province

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Authors: K. M. Etmimi, A. A. Sghayer, A. M. Gsiea, A. M. Abutruma

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Relatively few chemical species can be incorporated into diamond during CVD growth, and until recently the uptake of oxygen was thought to be low perhaps as a consequence of a short surface residence time. Within the literature, there is speculation regarding spectroscopic evidence for O in diamond, but no direct evidence. For example, the N3 and OK1 EPR centres have been tentatively assigned models made up from complexes of substitutional N and substitutional oxygen. In this study, we report density-functional calculations regarding the stability, electronic structures, geometry and hyperfine interaction of substitutional oxygen in diamond and show that the C2v, S=1 configuration very slightly lower in energy than the other configurations (C3v, Td, and C2v with S=0). The electronic structure of O in diamond generally gives rise to two defect-related energy states in the band gap one a non-degenerate a1 state lying near the middle of the energy gap and the other a threefold-degenerate t2 state located close to the conduction band edges. The anti-bonding a1 and t2 states will be occupied by one to three electrons for O+, O and O− respectively.

Keywords: DFT, oxygen, diamond, hyperfine

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Authors: Raphael Tuor, Denis Lalanne

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The ATM research community is missing suitable tools to design, test, and validate new UI prototypes. Important stakes underline the implementation of both DSS and XAI methods into current systems. ML-based DSS are gaining in relevance as ATFM becomes increasingly complex. However, these systems only prove useful if a human can understand them, and thus new XAI methods are needed. The human-machine dyad should work as a team and should understand each other. We present xSky, a configurable benchmark tool that allows us to compare different versions of an ATC interface in conflict detection tasks. Our main contributions to the ATC research community are (1) a conflict detection task simulator (xSky) that allows to test the applicability of visual prototypes on scenarios of varying difficulty and outputting relevant operational metrics (2) a theoretical approach to the explanations of AI-driven trajectory predictions. xSky addresses several issues that were identified within available research tools. Researchers can configure the dimensions affecting scenario difficulty with a simple CSV file. Both the content and appearance of the XAI elements can be customized in a few steps. As a proof-of-concept, we implemented an XAI prototype inspired by the maritime field.

Keywords: air traffic control, air traffic simulation, conflict detection, explainable artificial intelligence, explainability, human-automation collaboration, human factors, information visualization, interpretability, trajectory prediction

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Authors: Asiful H. Seikh, Jabair A. Mohammed, Ubair A. Samad, Mohammad A. Alam, Saeed M. Al-Zahrani, El-Sayed M. Sherif

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Three coating formulations were fabricated by incorporating different percentages of MIO (micaceous iron oxide ) (1, 2, and wt%) with ball-milled nanocrystalline Al (2 wt%) particles, which was optimized earlier. These coatings were characterized by means of different methods, namely, SEM, TGA, pendulum hardness, scratch test, and nano-indentation. The EIS measurements were carried out to report the effect of adding MIO powder in fabricated coatings on their corrosion behavior in 3.5 wt% NaCl solutions. In order to report the effect of immersion time on the corrosion and degradation of the prepared coatings, the EIS data were also acquired after various exposure periods of time, i.e., 1 h, 7 d, 14 d, 21 d, and 30 d in the test chloride solution. It has been found that the obtained EIS data for the fabricated coatings proved that the presence of 2% MIO provided the highest corrosion resistance amongst all coatings and that effect was recorded after all immersion periods of time. But, the MIO-incorporated coatings have less corrosion resistance than Al based epoxy coatings. It was also shown that with prolonged immersion, the resistance to corrosion declined after 7d, then with a longer period of immersion, i.e. 14 d, 21 d, and 30 d increases the resistance to corrosion by forming oxide products on the coatings surface. The results obtained from both mechanical and electrochemical testing confirmed that the fabricated coating with 2 wt% Al exhibited better hardness and higher resistance to corrosion as compared to coatings with 1 wt% Al and 3 wt% Al.

Keywords: epoxy coatings, nanomaterials, corrosion resistance, EIS, nanoindentation

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Authors: Silvia Platania, Martina Morando, Giuseppe Santisi

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Introduction: In the last thirty years, there is constant talk of sustainable consumption and a "transition" of consumer lifestyles towards greater awareness of consumer choices (United Nation, 1992). The 2019 coronavirus (COVID-19) epidemic that has hit the world population since 2020 has had significant consequences in all areas of people's lives; individuals have been forced to change their behaviors, to redefine their owngoals, priorities, practices, and lifestyles, to rebuild themselves in the new situation dictated by the pandemic. Method(Participants and procedure ): The data were collected through an online survey; moreover, we used convenience sampling from the general population. The participants were 669 Italians consumers (Female= 514, 76.8%; Male=155, 23.2%) that choice sustainability brands, aged between 18 and 65 years (Mₐ𝓰ₑ = 35.45; Standard Deviation, SD = 9.51).(Measure ): The following measures were used: The Muncy–Vitell Consumer Ethics Scale; Attitude Toward Business Scale; Perceived Consumer Effectiveness Scale; Consumers Perception on Sustainable Brand Attitudes. Results: Preliminary analyses were conducted to test our model. Pearson's bivariate correlation between variables shows that all variables of our model correlate significantly and positively, PCE with CPSBA (r = .56, p <.001). Furthermore, a CFA, according to Harman's single-factor test, was used to diagnose the extent to which common-method variance was a problem. A comparison between the hypothesised model and a model with one factor (with all items loading on a unique factor) revealed that the former provided a better fit for the data in all the CFA fit measures [χ² [6, n = 669] = 7.228, p = 0.024, χ² / df = 1.20, RMSEA = 0.07 (CI = 0.051-0.067), CFI = 0.95, GFI = 0.95, SRMR = 0.04, AIC = 66.501; BIC = 132,150). Next, amulti mediation was conducted to test our hypotheses. The results show that there is a direct effect of PCE on ethical consumption behavior (β = .38) and on ATB (β = .23); furthermore, there is a direct effect on the CPSBA outcome (β = .34). In addition, there is a mediating effect by ATB (C.I. =. 022-.119, 95% interval confidence) and by CES (C.I. =. 136-.328, 95% interval confidence). Conclusion: The spread of the COVID-19 pandemic has affected consumer consumption styles and has led to an increase in online shopping and purchases of sustainable products. Several theoretical and practical considerations emerge from the results of the study.

Keywords: decision making, sustainability, pandemic, multimediation model

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Authors: Zhiyong Shan, Preethi Santhanam, Vinod Namboodiri, Rajiv Bagai

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In recent years, the emerging network worms and attacks have distributive characteristics, which can spread globally in a very short time. Security management crossing networks to co-defense network-wide attacks and improve the efficiency of security administration is urgently needed. We propose a hierarchical distributed network security management system (HD-NSMS), which can integrate security management across multiple networks. First, we describe the system in macrostructure and microstructure; then discuss three key problems when building HD-NSMS: device model, alert mechanism, and emergency response mechanism; lastly, we describe the implementation of HD-NSMS. The paper is valuable for implementing NSMS in that it derives from a practical network security management system (NSMS).

Keywords: network security management, device organization, emergency response, cross-network

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Authors: Songul Cinaroglu

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Background: Random Forest is an efficient, multi-class machine learning method using for classification, regression and other tasks. This method is operating by constructing each tree using different bootstrap sample of the data. Determining the number of trees in random forests is an open question in the literature for studies about improving classification performance of random forests. Aim: The aim of this study is to analyze whether there is an optimal number of trees in Random Forests and how performance of Random Forests differ according to increase in number of trees using sample health data sets in R programme. Method: In this study we analyzed the performance of Random Forests as the number of trees grows and doubling the number of trees at every iteration using “random forest” package in R programme. For determining minimum and optimal number of trees we performed Mc Nemar test and Area Under ROC Curve respectively. Results: At the end of the analysis it was found that as the number of trees grows, it does not always means that the performance of the forest is better than forests which have fever trees. In other words larger number of trees only increases computational costs but not increases performance results. Conclusion: Despite general practice in using random forests is to generate large number of trees for having high performance results, this study shows that increasing number of trees doesn’t always improves performance. Future studies can compare different kinds of data sets and different performance measures to test whether Random Forest performance results change as number of trees increase or not.

Keywords: classification methods, decision trees, number of trees, random forest

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Authors: Anwar Hasan Abdullah Othman, Ahamed Kameel, Hasanuddeen Abdul Aziz

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In this study, an attempt has been made to investigate the relationship specifically the causal relation between fund unit prices of Islamic equity unit trust fund which measure by fund NAV and the selected macro-economic variables of Malaysian economy by using VECM causality test and Granger causality test. Monthly data has been used from Jan, 2006 to Dec, 2012 for all the variables. The findings of the study showed that industrial production index, political election and financial crisis are the only variables having unidirectional causal relationship with fund unit price. However, the global oil prices is having bidirectional causality with fund NAV. Thus, it is concluded that the equity unit trust fund industry in Malaysia is an inefficient market with respect to the industrial production index, global oil prices, political election and financial crisis. However, the market is approaching towards informational efficiency at least with respect to four macroeconomic variables, treasury bill rate, money supply, foreign exchange rate and corruption index.

Keywords: fund unit price, unit trust industry, Malaysia, macroeconomic variables, causality

Procedia PDF Downloads 471