Search results for: state machine

Authors: G. Çelik Gül, F. Kurtuluş

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Colemanite is the most common borate mineral, and the main source of the boron required by plants, human, and earth. Transition metals exhibit optical and physical properties such as; non-linear optical character, structural diversity, thermal stability, long cycle life and luminescent radiation. The doping of colemanite with a transition metal, bring it very interesting and attractive properties which make them applicable in industry. Iron doped calcium borate was synthesized by conventional solid state method at 1200 °C for 12 h with a systematic pathway. X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy/energy dispersive analyze (SEM/EDS) were used to characterize structural and morphological properties. Also, thermal properties were recorded by thermogravimetric-differential thermal analysis (TG/DTA). 

Keywords: colemanite, conventional synthesis, powder x-ray diffraction, borates

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Authors: Eleni Ioannou, Pascal Nucara, Keith Pullen

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The subject of this paper is the investigation of the best efficiency design of a compressor diffuser applied in new lightweight, ultra efficient micro-gas turbine engines for vehicles. The Computational Fluid Dynamics (CFD) results are obtained utilizing steady state simulations for a wedge and an ”oval” type pipe diffuser in an effort to identify the beneficial effects of the pipe diffuser design. The basic flow features are presented with particular focus on the optimization of the pipe diffuser leading to higher efficiencies for the compressor stage. The optimised pipe diffuser is designed to exploit the 3D freedom enabled by Selective Laser Melting, hence purposely involves an investigation of geometric characteristics that do not follow the traditional diffuser concept.

Keywords: CFD, centrifugal compressor, micro-gas turbine, pipe diffuser, SLM, wedge diffuser

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Authors: Kasidis Chomrat, Nopasit Chakpitak, Anukul Tamprasirt, Annop Thananchana

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Internet of Things devices or IoT and Edge Computing has become one of the biggest things happening in innovations and one of the most discussed of the potential to improve and disrupt traditional business and industry alike. With rises of new hang cliff challenges like COVID-19 pandemic that posed a danger to workforce and business process of the system. Along with drastically changing landscape in business that left ruined aftermath of global COVID-19 pandemic, looming with the threat of global energy crisis, global warming, more heating global politic that posed a threat to become new Cold War. How emerging technology like edge computing and usage of specialized design visual processing units will be great opportunities for business. The literature reviewed on how the internet of things and disruptive wave will affect business, which explains is how all these new events is an effect on the current business and how would the business need to be adapting to change in the market and world, and example test benchmarking for consumer marketed of newer devices like the internet of things devices equipped with new edge computing devices will be increase efficiency and reducing posing a risk from a current and looming crisis. Throughout the whole paper, we will explain the technologies that lead the present technologies and the current situation why these technologies will be innovations that change the traditional practice through brief introductions to the technologies such as cloud computing, edge computing, Internet of Things and how it will be leading into future.

Keywords: internet of things, edge computing, machine learning, pattern recognition, image classification

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Authors: Hassan Abubakar

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This paper will serve as a guide to good design and implementation of wireless networking for campus institutions in Nigeria. It can be implemented throughout the primary, secondary and tertiary institutions. This paper describe the some technical functions, standard configurations and layouts of the 802.11 wireless LAN(Local Area Network) that can be implemented across the campus network. The paper also touches upon the wireless infrastructure standards involved with enhanced services, such as voice over wireless and wireless guest hotspot. The paper also touch the benefits derived from implementing campus wireless network and share some lights on how to arrive at the success in increasing the performance of wireless and using the campus wireless to share resources like software applications, printer and documents.

Keywords: networking, standards, wireless local area network (WLAN), radio frequency (RF), campus

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Authors: Emilie Fort

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Two major pitfalls emerge at the intersection of gender and peacebuilding literature: the comprehension of women as a homogeneous category and a focus on women's participation in formal peace processes and state structures. However, women belong (and identify) to distinct ethnic, religious, or social groups, and the variety of their social location impacts their ability to mobilize, to participate in peace processes as well as the way they envision peace. This study is based on interviews conducted (remotely) with women activists from the post-Yugoslav area. It shows that women's economic empowerment and education are central issues that must be addressed for women political participation being effective. This has implications for peace projects –their priorities, scales of implementation, etc.– and the allocation of civil society’s funds.

Keywords: ex-Yugoslavia, gender-based issues, peacebuilding, women activism

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Authors: Harche Rima, Laoufi Nadia Aicha

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The present work consists of studying the behavior of steel, copper, and aluminum vis-à-vis the corrosion in an aqueous medium in the presence of the antifreeze COOLELF MDX -26°C. For this, we have studied the influence of the temperature and the different concentrations of the antifreeze on the corrosion of these three metals, this will last for two months by the polarization method and weight loss. In the end, we investigated the samples with the optic microscope to know their surface state. The aim of this work is the protection of contraptions. The use of antifreeze in ordinary water has a high efficiency against steel corrosion, as demonstrated by electrochemical tests (potential monitoring as a function of time and tracing polarization curves). The inhibition rate is greater than 99% for different volume concentrations, ranging from 40% to 60%. The speeds are in turn low in the order of 10-4 mm/year. On the other hand, the addition of antifreeze to ordinary water increases the corrosion potential of steel by more than 400 mV.

Keywords: corrosion and prevention, steel, copper, aluminum, corrosion inhibitor, anti-cooling

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Authors: Bongs Lainjo

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Educational institutions and authorities that are mandated to run education systems in various countries need to implement a curriculum that considers the possibility and existence of elementary school dropouts. This research focuses on elementary school dropout rates and the ability to replicate various predictive models carried out globally on selected Elementary Schools. The study was carried out by comparing the classical case studies in Africa, North America, South America, Asia and Europe. Some of the reasons put forward for children dropping out include the notion of being successful in life without necessarily going through the education process. Such mentality is coupled with a tough curriculum that does not take care of all students. The system has completely led to poor school attendance - truancy which continuously leads to dropouts. In this study, the focus is on developing a model that can systematically be implemented by school administrations to prevent possible dropout scenarios. At the elementary level, especially the lower grades, a child's perception of education can be easily changed so that they focus on the better future that their parents desire. To deal effectively with the elementary school dropout problem, strategies that are put in place need to be studied and predictive models are installed in every educational system with a view to helping prevent an imminent school dropout just before it happens. In a competency-based curriculum that most advanced nations are trying to implement, the education systems have wholesome ideas of learning that reduce the rate of dropout.

Keywords: elementary school, predictive models, machine learning, risk factors, data mining, classifiers, dropout rates, education system, competency-based curriculum

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Authors: Monika Florczak-Wątor

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The main purpose of this paper is to determine the applicability of the constitutional social rights in the so-called horizontal relations, i.e. the relations between private entities. Nowadays the constitutional rights are more and more often violated by private entities and not only by the state. The private entities interfere with the privacy of individuals, limit their freedom of expression or disturb their peaceful gatherings. International corporations subordinate individuals in a way which may limit their constitutional rights. These new realities determine the new role of the constitution in protecting human rights. The paper will aim at answering two important questions. Firstly, are the private entities obliged to respect the constitutional social rights of other private entities and can they be liable for violation of these rights? Secondly, how the constitutional social rights can receive horizontal effect? Answers to these questions will have a significant meaning for the popularization of the practice of applying the Constitution among the citizens as well as for the courts which settle disputes between them.

Keywords: social rights, private relations, horizontality, constitutional rights

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Authors: Jae Hong Kim, Sang Cheol Um, Jong Kook Lee

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Strong and biocompatible wollastonite (CaSiO3) was fabricated by pressureless sintering at temperature range of 1250~ 1300 ℃ and phase transition of to β-wollastonite with an addition of MgSiO3. Starting pure α-wollastonite powder were prepared by solid state reaction, and MgSiO3 powder was added to α-wollastonite powder to induce the phase transition α to β-wollastonite over 1250℃. Sintered wollastonite samples at 1250℃ with 5 and 10 wt% MgSiO3 were α+β phase and β phase respectively, and showed higher densification rate than that of α or β-wollastonite, which are almost the same as the theoretical density. Hardness and Young’s modulus of sintered wollastonite were dependent on the apparent density and the amount of β-wollastonite. Young’s modulus (78GPa) of β-wollastonite added 10 wt% MgSiO3 was almost double time of sintered α-wollastonite. From the in-vitro test, biphasic (α+β) wollastonite with 5wt% MgSiO3 addition had good bioactivity in simulated body fluid solution.

Keywords: β-wollastonite, high density, MgSiO3, phase transition

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Authors: P. Vosynek, T. Návrat, M. Peč, J. Pořízka, P. Diviš

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Changes of mechanical properties and response behavior of bones is an important external sign of medical problems like osteoporosis, bone remodeling after fracture or surgery, osteointegration, or bone tissue loss of astronauts in space. Measuring of mechanical behavior of bones in physiological and osteoporotic states, quantified by different degrees of protein (collagen) and mineral loss, is thus an important topic in biomechanical research. This contribution deals with the relation between mechanical properties of the turkey long bone–tibia in physiological, demineralized, and deproteinized state. Three methods for comparison were used: densitometry, three point bending and harmonic response analysis. The results help to find correlations between the methods and estimate their possible application in medical practice.

Keywords: bone properties, long bone, osteoporosis, response behavior

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Authors: Hwan-Jun Choi, Sung-Bok Choi, Hyoung-Kyu Song

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Recently, among the MIMO-OFDM detection techniques, a lot of papers suggested V-BLAST scheme which can achieve high data rate. Therefore, the signal detection of MIMOOFDM system is important issue. In this paper, efficient iterative VBLAST detection technique is proposed in wireless communication system. The proposed scheme adjusts the number of candidate symbol and iterative scheme based on channel state. According to the simulation result, the proposed scheme has better BER performance than conventional schemes and similar BER performance of the QRD-M with iterative scheme. Moreover complexity of proposed scheme has 50.6 % less than complexity of QRD-M detection with iterative scheme. Therefore the proposed detection scheme can be efficiently used in wireless communication.

Keywords: MIMO-OFDM, V-BLAST, QR-decomposition, QRDM, DFE, iterative scheme, channel condition

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Authors: Ilaria Lucrezia Amerise

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Electricity markets throughout the world have undergone substantial changes. Accurate, reliable, clear and comprehensible modeling and forecasting of different variables (loads and prices in the first instance) have achieved increasing importance. In this paper, we describe the actual state of the art focusing on reg-SARMA methods, which have proven to be flexible enough to accommodate the electricity price/load behavior satisfactory. More specifically, we will discuss: 1) The dichotomy between point and interval forecasts; 2) The difficult choice between stochastic (e.g. climatic variation) and non-deterministic predictors (e.g. calendar variables); 3) The confrontation between modelling a single aggregate time series or creating separated and potentially different models of sub-series. The noteworthy point that we would like to make it emerge is that prices and loads require different approaches that appear irreconcilable even though must be made reconcilable for the interests and activities of energy companies.

Keywords: interval forecasts, time series, electricity prices, reg-SARIMA methods

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Authors: Carol Okigbo

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Mathematical problem solving has long been accorded an important place in mathematics curricula at every education level in both advanced and emerging economies. Its classroom approaches have varied, such as teaching for problem-solving, teaching about problem-solving, and teaching mathematics through problem-solving. It requires engaging in tasks for which the solution methods are not eminent, making sense of problems and persevering in solving them by exhibiting processes, strategies, appropriate attitude, and adequate exposure. Teachers play important roles in helping students acquire competency in problem-solving; thus, they are expected to be good problem-solvers and have proper conceptions of problem-solving. Studies show that teachers’ conceptions influence their decisions about what to teach and how to teach. Therefore, how teachers view their roles in teaching problem-solving will depend on their pedagogical conceptions of problem-solving. If teaching problem-solving is a major component of secondary school mathematics instruction, as recommended by researchers and mathematics educators, then it is necessary to establish teachers’ conceptions, what they do, and how they approach problem-solving. This study is designed to determine secondary school teachers’ conceptions regarding mathematical problem solving, its current situation, how teachers’ conceptions relate to their demographics, as well as the interaction patterns in the mathematics classroom. There have been many studies of mathematics problem solving, some of which addressed teachers’ conceptions using single-method approaches, thereby presenting only limited views of this important phenomenon. To address the problem more holistically, this study adopted an integrated mixed methods approach which involved a quantitative survey, qualitative analysis of open-ended responses, and ethnographic observations of teachers in class. Data for the analysis came from a random sample of 327 secondary school mathematics teachers in two Nigerian states - Anambra State and Enugu State who completed a 45-item questionnaire. Ten of the items elicited demographic information, 11 items were open-ended questions, and 25 items were Likert-type questions. Of the 327 teachers who responded to the questionnaires, 37 were randomly selected and observed in their classes. Data analysis using ANOVA, t-tests, chi-square tests, and open coding showed that the teachers had different conceptions about problem-solving, which fall into three main themes: practice on exercises and word application problems, a process of solving mathematical problems, and a way of teaching mathematics. Teachers reported that no period is set aside for problem-solving; typically, teachers solve problems on the board, teach problem-solving strategies, and allow students time to struggle with problems on their own. The result shows a significant difference between male and female teachers’ conception of problems solving, a significant relationship among teachers’ conceptions and academic qualifications, and teachers who have spent ten years or more teaching mathematics were significantly different from the group with seven to nine years of experience in terms of their conceptions of problem-solving.

Keywords: conceptions, education, mathematics, problem solving, teacher

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Authors: Hawre Hasan Hama, Choman Mahmood H. Rashid

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The four-year armed conflict between the Kurdistan Democratic Party (KDP) and the Patriotic Union of Kurdistan (PUK) ended in September 1998 under the terms of the Washington Agreement. Since then, there has been a quarter-century of durable peace between the two combatant parties, though they have often been at odds politically. Based on interviews with Kurdish political leaders from both parties, this paper argues that sharing or dividing power across all four dimensions of state power — political, military, territorial, and economic — has played a vital role ensuring the durability of the peace settlement. The paper traces the KDP-PUK power sharing system through three stages: the transition stage (1998-2006), the “golden” period (2006-2013), the “weakening” period (2013 to present).

Keywords: peace settlement, enduring peace, power-sharing and power dividing, Iraqi Kurdistan.

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Authors: Usamah Al-Ali

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We explore the effect of expanding space on the exoticity of the matter supporting a traversable Lorentzian wormhole of zero radial tide whose line element is given by ds2 = dt^2 − a^2(t)[ dr^2/(1 − kr2 −b(r)/r)+ r2dΩ^2 in the context of General Relativity. This task is achieved by deriving the Einstein field equations for anisotropic matter field corresponding to the considered cosmological wormhole metric and performing a classification of their solutions on the basis of a variable equations of state (EoS) of the form p = ω(r)ρ. Explicit forms of the shape function b(r) and the scale factor a(t) arising in the classification are utilized to construct the corresponding energy-momentum tensor where the energy conditions for each case is investigated. While the violation of energy conditions is inevitable in case of static wormholes, the classification we performed leads to interesting solutions in which this violation is either reduced or eliminated.

Keywords: general relativity, Einstein field equations, energy conditions, cosmological wormhole

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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: Hugo Sampaio Libero, Max de Castro Magalhaes

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The perception of sound radiated from a building floor is greatly influenced by the rooms in which it is immersed and by the position of both listener and source. The main question that remains unanswered is related to the influence of the source position on the sound power radiated by a complex wall-floor system in buildings. This research is concerned with the investigation of vibration transmission across walls and floors in buildings. It is primarily based on the determination of vibration reduction index via experimental tests. Knowledge of this parameter may help in predicting noise and vibration propagation in building components. First, the physical mechanisms involving vibration transmission across structural junctions are described. An experimental setup is performed to aid this investigation. The experimental tests have shown that the vibration generation in the walls and floors is directed related to their size and boundary conditions. It is also shown that the vibration source position can affect the overall vibration spectrum significantly. Second, the characteristics of the noise spectra inside the rooms due to an impact source (tapping machine) are also presented. Conclusions are drawn for the general trend of vibration and noise spectrum of the structural components and rooms, respectively. In summary, the aim of this paper is to investigate the vibro-acoustical behavior of building floors and walls under floor impact excitation. The impact excitation was at distinct positions on the slab. The analysis has highlighted the main physical characteristics of the vibration transmission mechanism.

Keywords: vibration transmission, vibration reduction index, impact excitation, experimental tests

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Authors: Juan S. Mantilla, Peter Thomson

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Seismic events may result in discomfort on occupants of the buildings, structural damage or even buildings collapse. Traditional design aims to reduce dynamic response of structures by increasing stiffness, thus increasing the construction costs and the design forces. Structural control systems arise as an alternative to reduce these dynamic responses. A commonly used control systems in buildings are the passive friction dampers, which adds energy dissipation through damping mechanisms induced by sliding friction between their surfaces. Passive friction dampers are usually implemented on the diagonal of braced buildings, but such devices have the disadvantage that are optimal for a range of sliding force and out of that range its efficiency decreases. The above implies that each passive friction damper is designed, built and commercialized for a specific sliding/clamping force, in which the damper shift from a locked state to a slip state, where dissipates energy through friction. The risk of having a variation in the efficiency of the device according to the sliding force is that the dynamic properties of the building can change as result of many factor, even damage caused by a seismic event. In this case the expected forces in the building can change and thus considerably reduce the efficiency of the damper (that is designed for a specific sliding force). It is also evident than when a seismic event occurs the forces in each floor varies in the time what means that the damper's efficiency is not the best at all times. Semi-Active Friction devices adapt its sliding force trying to maintain its motion in the slipping phase as much as possible, because of this, the effectiveness of the device depends on the control strategy used. This paper deals with the development and performance evaluation of a low cost Semiactive Variable Friction Damper (SAVFD) in reduced scale to reduce vibrations of structures subject to earthquakes. The SAVFD consist in a (1) hydraulic brake adapted to (2) a servomotor which is controlled with an (3) Arduino board and acquires accelerations or displacement from (4) sensors in the immediately upper and lower floors and a (5) power supply that can be a pair of common batteries. A test structure, based on a Benchmark structure for structural control, was design and constructed. The SAVFD and the structure are experimentally characterized. A numerical model of the structure and the SAVFD is developed based on the dynamic characterization. Decentralized control algorithms were modeled and later tested experimentally using shaking table test using earthquake and frequency chirp signals. The controlled structure with the SAVFD achieved reductions greater than 80% in relative displacements and accelerations in comparison to the uncontrolled structure.

Keywords: earthquake response, friction damper, semiactive control, shaking table

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Authors: Mohd Zuhair, Ram Babu Roy

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This paper presents an overview of the accessibility, design, and functioning of health insurance plans launched by state governments in India. In recent years, the governments of several states in India have come forward to provide health insurance coverage for the low-income group and rural population to reduce the out of pocket expenditure (OPE) on healthcare. Different health insurance schemes have different structures and offerings which differ in the different demographic factors. This study will portray a comparative analysis of the various health insurance schemes by analyzing different offerings and finance generation of the schemes. The comparative analysis will explain the lesson to be learned from these schemes and extend the existing knowledge of the health insurance in India. This would help in recognizing tension between various drivers and identifying issues pertaining to the sustainability of health insurance schemes in India.

Keywords: health insurance, out of pocket expenditure, universal healthcare, sustainability

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Authors: Tariq Mansoor, Lubos Hes, Vladimir Bajzik

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Socks comfort has great significance in our daily life. This significance even increased when we have undergone a work of low or high activity. It causes the sweating of our body with different rates. In this study, plain socks with differential fibre composition were wetted to saturated level. Then after successive intervals of conditioning, these socks are characterized by thermal resistance in dry and wet states. Theoretical thermal resistance is predicted by using combined filling coefficients and thermal conductivity of wet polymers instead of dry polymer (fibre) in different models. By this modification, different mathematical models could predict thermal resistance at different moisture levels. Furthermore, predicted thermal resistance by different models has reasonable correlation range between (0.84 -0.98) with experimental results in both dry (lab conditions moisture) and wet states. "This work is supported by Technical University of Liberec under SGC-2019. Project number is 21314".

Keywords: thermal resistance, mathematical model, plain socks, moisture loss rate

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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: Mohsen Maraoui

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In the aim of natural language processing applications improvement, such as information retrieval, machine translation, lexical disambiguation, we focus on statistical approach to semantic indexing for multilingual text documents based on conceptual network formalism. We propose to use this formalism as an indexing language to represent the descriptive concepts and their weighting. These concepts represent the content of the document. Our contribution is based on two steps. In the first step, we propose the extraction of index terms using the multilingual lexical resource Euro WordNet (EWN). In the second step, we pass from the representation of index terms to the representation of index concepts through conceptual network formalism. This network is generated using the EWN resource and pass by a classification step based on association rules model (in attempt to discover the non-taxonomic relations or contextual relations between the concepts of a document). These relations are latent relations buried in the text and carried by the semantic context of the co-occurrence of concepts in the document. Our proposed indexing approach can be applied to text documents in various languages because it is based on a linguistic method adapted to the language through a multilingual thesaurus. Next, we apply the same statistical process regardless of the language in order to extract the significant concepts and their associated weights. We prove that the proposed indexing approach provides encouraging results.

Keywords: concept extraction, conceptual network formalism, fuzzy association rules, multilingual thesaurus, semantic indexing

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Authors: Engi E. I. Sarhan, Usama M. Rashad, Ibrahim M. I. Hamoda, Mohammed K. Mohamed

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Background: This study aimed to know the effect of nitrogen-based cryotherapy on the spasticity of calf muscle in stroke patients. Patients were selected from the outpatient clinic of Neurology, Al-Mansoura general hospital, Al-Mansoura University. Subjects and methods: Thirty Stroke Patients of both sexes ranged from 45 to 60 years old were divided randomly into two equal groups, a study group (A) received a nitrogen-based cryotherapy, a selective physical therapy program and ankle foot orthosis (AFO), while as patients in control group (B) received the same program and AFO only. The treatment duration was three times per week for four weeks for both groups. We assessed spasticity of calf muscle before and after treatment subjectively using modified Ashworth scale (MAS) and objectively via measuring H / M ratio on electromyography machine. We also assessed ankle dorsiflexion ROM objectively using two dimensions motion analysis (2D). Results: After treatment, there was a highly significant improvement in the study group compared to the control group regarding the score of MAS, no significant difference in the study group compared to the control group regarding the readings of H / M ratio, highly significant improvement in the study group compared to the control group regarding the 2D motion analysis findings. Conclusion: This modality considers effective in reducing spasticity in the calf muscle and improving ankle dorsiflexion of the affected limb.

Keywords: ankle foot orthosis, nitrogen-based cryotherapy, stroke, spasticity

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Authors: Zheng Baichuan, Li Shenghui, Li Bingqian, Zhang Ning, Chen Kai

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Entity alignment (EA) tasks in knowledge graphs often play a pivotal role in the integration of knowledge graphs, where structural differences often exist between the source and target graphs, such as the presence or absence of attribute information and the types of attribute information (text, timestamps, images, etc.). However, most current research efforts are focused on improving alignment accuracy, often along with an increased reliance on specific structures -a dependency that inevitably diminishes their practical value and causes difficulties when facing knowledge graph alignment tasks with varying structures. Therefore, we propose a universal knowledge graph alignment approach that only utilizes the common basic structures shared by knowledge graphs. We have demonstrated through experiments that our method achieves state-of-the-art performance in fair comparisons.

Keywords: knowledge graph, entity alignment, transformer, deep learning

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Authors: Divya Juneja, Sukhjeet Kaur Matharu

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Purpose: The paper is aimed at identifying the challenging factors experienced by the women entrepreneurs in India in operating their enterprises amidst the challenges posed by the COVID-19 pandemic. Methodology: The sample for the study comprised 396 women entrepreneurs from different regions of India. A purposive sampling technique was adopted for data collection. Data was collected through a self-administered questionnaire. Analysis was performed using the SPSS package for quantitative data analysis. Findings: The results of the study state that entrepreneurial characteristics, resourcefulness, networking, adaptability, and continuity have a positive influence on the resiliency of women entrepreneurs when faced with a crisis situation. Practical Implications: The findings of the study have some important implications for women entrepreneurs, organizations, government, and other institutions extending support to entrepreneurs.

Keywords: women entrepreneurs, analysis, data analysis, positive influence, resiliency

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Authors: D. K. Soni

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A study of engineering properties of stones, i.e. compressive strength, tensile strength, modulus of elasticity, density, hardness were carried out to explore the possibility of optimum utilization of stone. The laboratory test results on equally dimensioned discs of the stone show a considerable variation in computed split tensile strength with varied rates of deformation. Hence, the effect of strain rate on the tensile strength of a sand stone and lime stone under wet and dry conditions has been studied experimentally using the split tensile strength test technique. It has been observed that the tensile strength of these stone is very much dependent on the rate of deformation particularly in a dry state. On saturation the value of split tensile strength reduced considerably depending upon the structure of rock and amount of water absorption.

Keywords: sedimentary rocks, split tensile test, deformation rate, saturation rate, sand stone, lime stone

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Authors: Evangelos Koumparoudis

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The definition of death is a deep philosophical question, and no single meaning can be ascribed to it. This essay focuses on the ontological, epistemological, and ethical aspects of death and dying in view of technological progress in information technology and biomedicine. It starts with the ad hoc 1968 Harvard committee that proposed that the criterion for the definition of death be irreversible coma and then refers to the debate over the whole brain death formula, emphasizing the integrated function of the organism and higher brain formula, taking consciousness and personality as essential human characteristics. It follows with the contribution of information technology in personalized and precision medicine and anti-aging measures aimed at life prolongation. It also touches on the possibility of the creation of human-machine hybrids and how this raises ontological and ethical issues that concern the “cyborgization” of human beings and the conception of the organism and personhood based on a post/transhumanist essence, and, furthermore, if sentient AI capable of autonomous decision-making that might even surpass human intelligence (singularity, superintelligence) deserves moral or legal personhood. Finally, there is the question as to whether death and dying should be redefined at a transcendent level, which is reinforced by already-existing technologies of “virtual after-” life and the possibility of uploading human minds. In the last section, I refer to the current (and future) applications of nanomedicine in diagnostics, therapeutics, implants, and tissue engineering as well as the aspiration to “immortality” by cryonics. The definition of death is reformulated since age and disease elimination may be realized, and the criterion of irreversibility may be challenged.

Keywords: death, posthumanism, infomedicine, nanomedicine, cryonics

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Authors: Ilzira A. Minigalieva

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Assessment of cumulative health risks associated with the widely observed combined exposures to two or more metals and their compounds on the organism in industrial or general environment, as well as respective regulatory and technical risk management decision-making have presumably the theoretical and experimental toxicology of mixtures as their reliable scientific basis. Analysis of relevant literature and our own experience proves, however, that there is no full match between these different practices. Moreover, some of the contradictions between them are of a fundamental nature. This unsatisfactory state of things may be explained not only by unavoidable simplifications characteristic of the methodologies of risk assessment and permissible exposure standards setting but also by the extreme intrinsic complexity of the combined toxicity theory, the most essential issues of which are considered and briefly discussed in this paper.

Keywords: toxic metals, nanoparticles, typology of combined toxicity, mathematical modeling, health risk assessment and management

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Authors: Wheyming Song, Hung-Hsiang Lin, Scott Lian

Abstract:

In this research, we investigate the optimal dispatching rule for machines and manpower allocation in the solar ingot-wafer systems. The performance of the method is measured by the sales profit for each dollar paid to the operators in a one week at steady-state. The decision variables are identification-number of machines and operators when each job is required to be served in each process. We propose a rule which is a function of operator’s ability, corresponding salary, and standing location while in the factory. The rule is named ‘Multi-nominal distribution dispatch rule’. The proposed rule performs better than many traditional rules including generic algorithm and particle swarm optimization. Simulation results show that the proposed Multi-nominal distribution dispatch rule improvement on the sales profit dramatically.

Keywords: dispatching, solar ingot, simulation, flexsim

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Authors: Rahma Abed, Sahbi Bahroun, Ezzeddine Zagrouba

Abstract:

Due to the huge amount of data in videos, extracting the relevant frames became a necessity and an essential step prior to performing face recognition. In this context, we propose a method for extracting keyframes from videos based on face quality and deep learning for a face recognition task. This method has two steps. We start by generating face quality scores for each face image based on the use of three face feature extractors, including Gabor, LBP, and HOG. The second step consists in training a Deep Convolutional Neural Network in a supervised manner in order to select the frames that have the best face quality. The obtained results show the effectiveness of the proposed method compared to the methods of the state of the art.

Keywords: keyframe extraction, face quality assessment, face in video recognition, convolution neural network

Procedia PDF Downloads 207