Search results for: simulated impact tests

Authors: Jiaying Gao, Thammananya Sakcharoen, Wilailuk Niyommaneerat

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Haikou is the capital of Hainan, a major tourism province in China with rich ecotourism resources. There is a need to strengthen tourism destination management in Haikou toward sustainable development as a tourism city. The purpose of this study was to investigate the relationship between tourism destination management and sustainable tourism in Haikou. Exploratory factor analysis was used to extract six dimensions of this study. Three dimensions (10 factors) of tourism destination management were analyzed in terms of economic development, social and cultural development, and conservation of ecosystem. Sustainability awareness, tourism development experience, and tourism public infrastructure in three dimensions (12 factors) of sustainable tourism. There were 426 questionnaire respondents, including 225 tourists, 172 residents, 12 tourism agency persons, 10 government persons, 3 self-employed, and 4 others. The Structural equation modeling (SEM) model was finally conducted to test the hypotheses empirically and explore the impact relationship. The study found a significant relationship between tourism destination management and sustainable tourism: social and cultural development had the greatest significant positive impact on the tourism development experience (0.788***). Social and cultural development also showed a significant positive impact and great impetus on tourism public infrastructure (0.561***). A negative effect relationship (-0.096***) emerged between ecosystem conversion and tourism development experience. It showed a positive relationship between economic development and social and cultural development of tourism destination management in promoting sustainable tourism. There are still some gaps for improvement, such as the need for sustainable ecological management to promote local sustainable tourism trends and enhance tourism experience development, which may require a long-term process of mitigation.

Keywords: Haikou (Hainan, China), influence relationship, sustainable tourism, tourism destination management

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Authors: Maxwell Henderson, Tristan Cook, Justin Chan Jin Le, Mark Hodson, YoungJung Chang, John Novak, Daniel Padilha, Nishan Kulatilaka, Ansu Bagchi, Sanjoy Ray, John Kelly

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We present a method of using adiabatic quantum optimization (AQO) to solve a mixed integer nonlinear programming (MINLP) problem instance. The MINLP problem is a general form of a set of NP-hard optimization problems that are critical to many business applications. It requires optimizing a set of discrete and continuous variables with nonlinear and potentially nonconvex constraints. Obtaining an exact, optimal solution for MINLP problem instances of non-trivial size using classical computation methods is currently intractable. Current leading algorithms leverage heuristic and divide-and-conquer methods to determine approximate solutions. Creating more accurate and efficient algorithms is an active area of research. Quantum computing (QC) has several theoretical benefits compared to classical computing, through which QC algorithms could obtain MINLP solutions that are superior to current algorithms. AQO is a particular form of QC that could offer more near-term benefits compared to other forms of QC, as hardware development is in a more mature state and devices are currently commercially available from D-Wave Systems Inc. It is also designed for optimization problems: it uses an effect called quantum tunneling to explore all lowest points of an energy landscape where classical approaches could become stuck in local minima. Our work used a novel algorithm formulated for AQO to solve a special type of MINLP problem. The research focused on determining: 1) if the problem is possible to solve using AQO, 2) if it can be solved by current hardware, 3) what the currently achievable performance is, 4) what the performance will be on projected future hardware, and 5) when AQO is likely to provide a benefit over classical computing methods. Two different methods, integer range and 1-hot encoding, were investigated for transforming the MINLP problem instance constraints into a mathematical structure that can be embedded directly onto the current D-Wave architecture. For testing and validation a D-Wave 2X device was used, as well as QxBranch’s QxLib software library, which includes a QC simulator based on simulated annealing. Our results indicate that it is mathematically possible to formulate the MINLP problem for AQO, but that currently available hardware is unable to solve problems of useful size. Classical general-purpose simulated annealing is currently able to solve larger problem sizes, but does not scale well and such methods would likely be outperformed in the future by improved AQO hardware with higher qubit connectivity and lower temperatures. If larger AQO devices are able to show improvements that trend in this direction, commercially viable solutions to the MINLP for particular applications could be implemented on hardware projected to be available in 5-10 years. Continued investigation into optimal AQO hardware architectures and novel methods for embedding MINLP problem constraints on to those architectures is needed to realize those commercial benefits.

Keywords: adiabatic quantum optimization, mixed integer nonlinear programming, quantum computing, NP-hard

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Authors: Srushti R. Joshi, Ujjwal Rakesh, Spoorthi Sripad

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The rapid advancement of remote sensing technologies has revolutionized plant health monitoring, offering valuable insights for precision agriculture and environmental management. This paper presents a comprehensive comparative analysis between the widely employed normalized difference vegetation index (NDVI) and state-of-the-art hyperspectral sensors in the context of plant health assessment. The study aims to elucidate the weigh ups of spectral resolution. Employing a diverse range of vegetative environments, the research utilizes simulated datasets to evaluate the performance of NDVI and hyperspectral sensors in detecting subtle variations indicative of plant stress, disease, and overall vitality. Through meticulous data analysis and statistical validation, this study highlights the superior performance of hyperspectral sensors across the parameters used.

Keywords: normalized difference vegetation index, hyperspectral sensor, spectral resolution, infrared

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Authors: M. A. Hernández-Ceballos, M. Marín-Ferrer, G. Cinelli, L. De Felice, T. Tollefsen, E. Nweke, P. V. Tognoli, S. Vanzo, M. De Cort

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This study analyses the latitudinal impact of the spatial and temporal distribution on the cosmogenic isotope 7Be in surface air along Europe. The long-term database of the 6 sampling sites (Ivalo, Helsinki, Berlin, Freiburg, Sevilla and La Laguna), that regularly provide data to the Radioactivity Environmental Monitoring (REM) network managed by the Joint Research Centre (JRC) in Ispra, were used. The selection of the stations was performed attending to different factors, such as 1) heterogeneity in terms of latitude and altitude, and 2) long database coverage. The combination of these two parameters ensures a high degree of representativeness of the results. In the later, the temporal coverage varies between stations, being used in the present study sampling stations with a database more or less continuously from 1984 to 2011. The mean values of 7Be activity concentration presented a spatial distribution value ranging from 2.0 ± 0.9 mBq/m3 (Ivalo, north) to 4.8 ± 1.5 mBq/m3 (La Laguna, south). An increasing gradient with latitude was observed from the north to the south, 0.06 mBq/m3. However, there was no correlation with altitude, since all stations are sited within the atmospheric boundary layer. The analyses of the data indicated a dynamic range of 7Be activity for solar cycle and phase (maximum or minimum), having been observed different impact on stations according to their location. The results indicated a significant seasonal behavior, with the maximum concentrations occurring in the summer and minimum in the winter, although with differences in the values reached and in the month registered. Due to the large heterogeneity in the temporal pattern with which the individual radionuclide analyses were performed in each station, the 7Be monthly index was calculated to normalize the measurements and perform the direct comparison of monthly evolution among stations. Different intensity and evolution of the mean monthly index were observed. The knowledge of the spatial and temporal distribution of this natural radionuclide in the atmosphere is a key parameter for modeling studies of atmospheric processes, which are important phenomena to be taken into account in the case of a nuclear accident.

Keywords: Berilium-7, latitudinal impact in Europe, seasonal and monthly variability, solar cycle

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Authors: Malki Nadia Fatima Zahra, Kellal Chaimaa, Brahimi Houria

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Quality is one of the most important modern management patterns that organizations seek to achieve in all areas and sectors in order to meet the needs and desires of customers and to remain continuity, as they constitute a competitive advantage for the organization, and among the most prominent organizations that must be available on the quality factor are health organizations as they relate to the most valuable component of production It is a person and his health, and that any error in it threatens his life and may lead to death, so she must provide health services of high quality to achieve the highest degree of satisfaction for the patient. This research aims to study the quality of health services and the extent of their impact on patient satisfaction, and this is through an applied study that relied on measuring the level of quality of health services in the university hospital center of Algeria and the extent of their impact on patient satisfaction according to the dimensions of the quality of health services, and we reached a conclusion that the determinants of the quality of health services. It affects patient satisfaction, which necessitates developing health services according to patients' requirements and improving their quality to obtain patient satisfaction.

Keywords: health service, health quality, quality determinants, patient satisfaction

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Authors: Fatemeh Safdari, Amirnaser Shamkhali, Gholamabbas Parsafar

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Carbon nanostructures are of great importance in academic research and industry, which can be mentioned to chemical sensors, catalytic processes, pharmaceutical and environmental issues. Common point in all of these applications is the occurrence of adsorption of molecules on these structures. Important carbon nanostructures in this case are mainly nanotubes and graphene. To modify pure graphene, recently, many experimental and theoretical studies have carried out to investigate of metal adsorption on graphene. In this work, the adsorption of CO molecules on pure graphene and on metal adatom on graphene surface has been simulated based on density functional theory (DFT). All calculations were performed by PBE functional and Troullier-Martins pseudopotentials. Density of states (DOS) for graphene-CO, graphen and CO around the Fermi energy has been moved and very small mixing occured which implies the physisorption of CO on the bare graphen surface. While, the results have showed that CO adsorption on transition-metal adatom on graphene surface is chemisorption.

Keywords: adsorption, density functional theory, graphene, metal adatom

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Authors: Svetlana Gusarova

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The essential role in the recent development of world economy has led to the developing countries, notably to BRICS countries (Brazil, Russia, India, China, South Africa). Over the next 50 years the BRICS countries are expected to be the engines of global trade and economic growth. Trade cooperation of BRICS countries can enhance their economic development. BRICS countries were among Top 10 world exporters of office and telecom equipment, of textiles, of clothing, of iron and steel, of chemicals, of agricultural products, of automotive products, of fuel and mining products. China was one of the main trading partners of all BRICS countries, maintaining close relationship with all BRICS countries in the development of trade. Author analyzed trade complementarity of BRICS countries and revealed the high level of complementarity of their trade flows in connection with availability of specialization in different types of goods. The correlation and regression analysis of communication of Intra-BRICS merchandise turnover and their GDP (PPP) revealed very strong impact on the development of their economies.

Keywords: BRICS countries, trade cooperation, complementarity, regression analysis

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Authors: Marcin Baranski

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This article presents a vibration diagnostic method designed for permanent magnets (PM) traction motors. Those machines are commonly used in traction drives of electrical vehicles. Specific structural properties of machines excited by permanent magnets are used in this method - electromotive force (EMF) generated due to vibrations. This work presents: field-circuit model, results of static tests, results of calculations and simulations.

Keywords: electrical vehicle, permanent magnet, traction drive, vibrations, electrical machine, eccentricity

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Authors: Reham K. El Sawah, N. S. M. El-Tayeb

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This study aims to produce a polymer matrix composite reinforced with Al₂O₃ nanoparticles in order to enhance the mechanical properties of PMMA. The composite was fabricated via Friction stir processing to ensure homogenous dispersion of Al₂O₃ nanoparticles in the polymer, and the processing was submerged to prevent the sputtering of nanoparticles. The surface quality, microstructure, impact energy and hardness of the prepared samples were investigated. Good surface quality and dispersion of nanoparticles were attained through employing sufficient processing conditions. The experimental results indicated that as the percentage of nanoparticles increased, the impact energy and hardness increased, reaching 2 kJ/m2 and 14.7 HV at a nanoparticle concentration of 25%, which means that the toughness and the hardness of the polymer-ceramic produced composite is higher than unprocessed PMMA by 66% and 33% respectively.

Keywords: friction stir processing, polymer matrix nanocomposite, mechanical properties, microstructure

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Authors: S. Sangaroon, W. Ratanatongchai, S. Khaweerat, R. Picha, J. Channuie

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The prompt gamma-ray neutron activation analysis system (PGNAA) has been constructed and installed at a 6 inch diameter neutron beam port of the Thai Research Reactor-1/ Modification 1 (TRR-1/M1) since 1989. It was designed for the reactor operating power at 1.2 MW. The purpose of the system is for an elemental and isotopic analytical. In 2016, the PGNAA facility will be developed to reduce the leakage and background of neutrons and gamma radiation at the sample and detector position. In this work, the designed condition of these facilities is carried out based on the Monte Carlo method using MCNP5 computer code. The conditions with different modification materials, thicknesses and structure of the PGNAA facility, including gamma collimator and radiation shields of the detector, are simulated, and then the optimal structure parameters with a significantly improved performance of the facility are obtained.

Keywords: MCNP simulation, PGNAA, Thai research reactor (TRR-1/M1), radiation shielding

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Authors: Nana Weng

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From 2008, Chinese Foreign Direct Investment flows to the European Union continued its rapid rise. Currently, the industrial structure adjustment in developing countries has also been placed on the international movement of factors of production. Now China economy is in an important period of transformation on industrial structure adjustment. Under the international transfer of industry background, the adjustment of industrial structure upgrading and sophistication are the key elements of a successful economic transformation. In order to achieve a virtuous cycle of foreign investment patterns and optimize the industrial structure of foreign direct investment as well, the research on the positive the role of the EU direct investment and how it impact China’s industrial structure optimization and upgrading is of great significance. In this paper, the author explained how the EU as an investment destination is different with the United States and ASEAN. Then, based on the theory of FDI and industrial structure and combining the four kinds of motives of China’s ODI in EU, this paper explained the impact mechanism which has influenced China domestic industrial structure primarily through the Transfer effect, Correlation effect and Competitive effect. On the premise that FDI activities do affect the home country’s domestic industrial structure, this paper made empirical analysis with industrial panel data. With the help of Gray Correlation Method and Limited Distributed Lags, this paper found that China/s ODI in the EU impacted the tertiary industry strongly and had a significant positive impact, particularly the manufacturing industry and the financial industry. This paper also pointed out that Chinese MNEs should realize several issues, such as pay more attention to high-tech industries so that they can make the best use of reverse technology spillover. When Chinese enterprises ‘go out,' they ought to keep in mind that domestic research and development capital contribution can make greater economic growth. Finally, based on theoretical and empirical analysis results, this paper presents the industry choice recommendations in the future of the EU direct investment, particularly through the development of the proper rational industrial policy and industrial development strategic to guide the industrial restructuring and upgrading.

Keywords: china ODI in european union, industrial structure optimization, impact mechanism, empirical analysis

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Authors: Fatima Naz, Ayesha Tariq

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In view of growing of the internet users for e-commerce and taking into account, the emergent impact of word of mouth phenomenon this research has different aims. The aims of this study were built following dissimilar discussion with teachers and colleagues enlightening that word of mouth information for online purchasing do not have the same effect for everybody. Then they were born following dissimilar researchers together with what was already done in previous researches and what was completed. As a result different aims were drawn; the initial aim of this research is to study the attention of the customers in the word of mouth to power their online purchasing activities. The next aim is to analyze the people influenced by the interest of word of mouth. The following aim is to examine the marketing behavior bearing in mind the internet progress and word of mouth, their consideration for word of mouth marketing. In the form of research questions the aims of the study are: 1) How community utilizes and multiplies word of mouth information about online purchasing experience? 2) How communities perceive the word of mouth marketing? 3) How marketers take the word of mouth phenomenon and how they handle it?

Keywords: belief, power, inspiration, self-expression, positive attitude to online marketing, forwarding of contents, purchasing decision, standard marketing

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Authors: George B. Abaka-Wood, Massimiliano Zanin, Jonas Addai-Mensah, William Skinner

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The versatility of froth flotation has made it vital in the beneficiation of rare earth elements minerals from either high or low-grade ores. There has been a significant increase in the quantity of iron oxide silicate-rich tailings generated from the extraction of primary commodities such as copper and gold in Australia, which have been identified to contain very low-grade rare earth oxides (≤ 1%). There is a vast knowledge gap in the beneficiation of rare earth oxides from such tailings. The aim of this research is to investigate the feasibility of using fatty acids as collectors for the flotation recovery and upgrade of rare earth oxides from selected iron-oxide silicate-rich tailings. Two forms of fatty acid collectors (oleic acid and sodium oleate) were tested in this investigation. Flotation tests were carried out using a 1.2 L Denver D-12 cell. The effects of pulp pH, fatty acid dosage, particle size distribution (-150 +75 µm, -75 +38 µm and -38 µm) and conventional depressants (sodium silicate and starch) dosage on flotation recovery of rare earth oxides were investigated. A comparison of the flotation results indicated that sodium oleate was the more efficient fatty acid for rare earth oxides flotation at all the pulp pH investigated. The flotation performance was found to be particle size-dependent. Both sodium silicate and starch were unselective in decreasing the recovery of iron oxides and silicate minerals, respectively with the corresponding decrease in rare earth oxides recovery. Generally, iron oxides and silicate minerals formed the substantial fraction of the flotation concentrates obtained, both in the absence and presence of depressants, resulting in a generally low rare earth oxides upgrade, even though rare earth oxides recoveries were high. The flotation tests carried out on the tailings sample suggest the feasibility of rare earth oxides recovery using fatty acids, although particle size distribution and minerals liberation are key limiting factors in achieving selective rare earth oxides upgrade.

Keywords: depressants, flotation, oleic acid, sodium oleate

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Authors: Dimitris Varsamis, Christos Talagkozis, Alkiviadis Tsimpiris, Paris Mastorocostas

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The aim of this work is the parallel implementation of k-means in MATLAB, in order to reduce the execution time. Specifically, a new function in MATLAB for serial k-means algorithm is developed, which meets all the requirements for the conversion to a function in MATLAB with parallel computations. Additionally, two different variants for the definition of initial values are presented. In the sequel, the parallel approach is presented. Finally, the performance tests for the computation times respect to the numbers of features and classes are illustrated.

Keywords: K-means algorithm, clustering, parallel computations, Matlab

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Authors: Kianoosh Ahadi, Mustafa Ergil

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In this study, the event of vibrations caused by vortexes and the distribution of induced hydrodynamic forces due to vortexes on the sliding gate valves has been investigated. For this reason, a sliding valve with the help of computational fluid dynamics (CFD) software was simulated in two-dimensional )2D(, where the flow and turbulence equations were solved for three different valve openings (full, half, and 16.7 %) models. The variety of vortexes formed within the vicinity of the valve structure was investigated based on time where the trend of fluctuations and their occurrence regions have been detected. From the gathered solution dataset of the numerical simulations, the pressure coefficient (CP), the lift force coefficient (CL), the drag force coefficient (CD), and the momentum coefficient due to hydrodynamic forces (CM) were examined, and relevant figures were generated were from these results, the vortex-induced vibrations were analyzed.

Keywords: induced vibrations, computational fluid dynamics, sliding gate valves, vortexes

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Authors: Haggag H. Mohamed, Ghatass F. Zekry, Shalaby A. Elsayed

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Most sources of air pollution in Egypt are of anthropogenic origin. Alexandria Governorate is located at north of Egypt. The main contributing sectors of air pollution in Alexandria are industry, transportation and area source due to human activities. Alexandria includes more than 40% of the industrial activities in Egypt. Cement manufacture contributes a significant amount to the particulate pollution load. Alexandria Portland Cement Company (APCC) surrounding was selected to be the study area. APCC main kiln stack Total Suspended Particulate (TSP) continuous monitoring data was collected for assessment of dust emission control technology. Electro Static Precipitator (ESP) was fixed on the cement kiln since 2002. The collected data of TSP for first quarter of 2012 was compared to that one in first quarter of 2013 after installation of new bag house filter. In the present study, based on these monitoring data and metrological data a detailed air dispersion modeling investigation was carried out using the Industrial Source Complex Short Term model (ISC3-ST) to find out the impact of applying new bag house filter control technology on the neighborhood ambient air quality. The model results show a drastic reduction of the ambient TSP hourly average concentration from 44.94μg/m3 to 5.78μg/m3 which assures the huge positive impact on the ambient air quality by applying bag house filter technology on APCC cement kiln

Keywords: air pollution modeling, ambient air quality, baghouse filter, cement industry

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Authors: Mohammadamin Hashemi, Mohammadreza Kashizadeh

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Droughts pose a significant threat to sustainable water resource management, agriculture, and socioeconomic sectors, particularly in the field of climate change. This study investigates drought simulation using rainfall-runoff modelling in the Cuneo district, Italy, over the past 60-year period. The study leverages the TUW model, a lumped conceptual rainfall-runoff model with a semi-distributed operation capability. Similar in structure to the widely used Hydrologiska Byråns Vattenbalansavdelning (HBV) model, the TUW model operates on daily timesteps for input and output data specific to each catchment. It incorporates essential routines for snow accumulation and melting, soil moisture storage, and streamflow generation. Multiple catchments' discharge data within the Cuneo district form the basis for thorough model calibration employing the Kling-Gupta Efficiency (KGE) metric. A crucial metric for reliable drought analysis is one that can accurately represent low-flow events during drought periods. This ensures that the model provides a realistic picture of water availability during these critical times. Subsequent validation of monthly discharge simulations thoroughly evaluates overall model performance. Beyond model development, the investigation delves into drought analysis using the robust Standardized Runoff Index (SRI). This index allows for precise characterization of drought occurrences within the study area. A meticulous comparison of observed and simulated discharge data is conducted, with particular focus on low-flow events that characterize droughts. Additionally, the study explores the complex interplay between land characteristics (e.g., soil type, vegetation cover) and climate variables (e.g., precipitation, temperature) that influence the severity and duration of hydrological droughts. The study's findings demonstrate successful calibration of the TUW model across most catchments, achieving commendable model efficiency. Comparative analysis between simulated and observed discharge data reveals significant agreement, especially during critical low-flow periods. This agreement is further supported by the Pareto coefficient, a statistical measure of goodness-of-fit. The drought analysis provides critical insights into the duration, intensity, and severity of drought events within the Cuneo district. This newfound understanding of spatial and temporal drought dynamics offers valuable information for water resource management strategies and drought mitigation efforts. This research deepens our understanding of drought dynamics in the Cuneo region. Future research directions include refining hydrological modelling techniques and exploring future drought projections under various climate change scenarios.

Keywords: hydrologic extremes, hydrological drought, hydrological modelling, machine learning, rainfall-runoff modelling

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Authors: Houmame Benbouali, Aboubakr Gribi

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The risks, in general, exist in any project, one can hardly carry out a project without taking risks. The hydraulic works are rather complex projects in their design, realization and exploitation and are often subjected at the multiple risks being able to influence with their good performance and can have a negative impact on their environment. The present study was carried out to quote the impacts caused by purification plant STEP Chlef on the environment, it aims has studied the environmental impacts during construction and when designing this STEP, it is divided into two parts: The first part results from a research task bibliographer which contain three chapters (- cleansing of water-worn- general information on water worn-proceed of purification of waste water). The second part is an experimental part which is divided into four chapters (detailed state initial description of the station of purification-evaluation of the impacts of the project analyzes measurements and recommendations).

Keywords: treatment plant, waste water, waste water treatment, Chlef

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Authors: Riina I. Bray, Yifan Wang, Nikolas Argiropoulos, Stephanie Robins, John Molot, Kelly Tragash, Lynn M. Marshall, Margaret E. Sears, Marie-Andrée Pigeon, Michel Gaudet, Pierre Auger, Emily Bélanger, Rohini Peris

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Multiple chemical sensitivity (MCS) is a chronic medical condition characterized by intolerances to chemical substances. Since the arrival of the COVID-19 pandemic and associated health measures, people experiencing MCS (PEMCS) are at a heightened risk of environmental exposures associated with cleaners, disinfectants, and sanitizers. Little attention has been paid to the well-being of PEMCS in the context of the COVID-19 pandemic. Objective: This study assesses the lived experiences of Canadian adults with MCS in relation to their living environment, access to healthcare, and levels of perceived social support before and during the pandemic. Methods: A total of 119 PEMCS completed an online questionnaire. McNemar Chi-Squared and Wilcoxon Signed Rank tests were used to evaluate if there were statistically significant changes in participants’ perception of their living environment, access to healthcare, and levels of social support before and after March 11, 2020. Results: Both positive and negative outcomes were noted. Participants reported an increase in exposure to disinfectants/sanitizers that entered their living environment (p<.001). There was a reported decrease in access to a family doctor during the pandemic (p<0.001). Although PEMCS experienced increased social isolation (p<0.001), they also reported an increase in understanding from family (p<0.029) and a decrease in stigma for wearing personal protective equipment (p<0.001). Conclusion: PEMCS reported experiencing: increased exposure to disinfectants or sanitizers, a loss of social support, and barriers in accessing healthcare during the pandemic. However, COVID-19 provided an opportunity to normalize the living conditions of PEMCS, such as wearing masks and social isolation. These findings can guide decision-makers on the importance of implementing nontoxic alternatives for cleaning and disinfection, as well as improving accommodation measures for PEMCS.

Keywords: covid-19, multiple chemical sensitivity, MCS, quality of life, social isolation, physical environment, healthcare

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Authors: Teo Yen Nee, Tham Siew Yean, Andrew Kam Jia Yi

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There are growing concerns about the effect of increasing outward foreign direct investment (OFDI) from Malaysia. These concerns emerged when OFDI surpassed inward FDI for the first time in 2007 and in the subsequent years as well. From a theoretical point of view, the effect of OFDI on exports remains inconclusive depending on the types and/or motivations of investment. Therefore, the objective of this paper is to investigate the effect of Malaysia’s OFDI on manufacturing exports, using a reduced form exports model. The manufacturing data used in this study covered 24 manufacturing industries for the period 2003-2010. The manufacturing sector is the fourth largest sector invested by Malaysia’s OFDI abroad. However, this sector is chosen for this study because total manufacturing trade contributed significantly to Malaysia’s economy growth as reflected by its significant share in the country’s gross domestic product (138.7%) in 2013. Furthermore, Malaysia’s exports are dominated by manufacturing goods. Consequently, the drastic increase in OFDI added concerns about its impact on the country’s exports. Since OFDI activities are still relatively new in Malaysia, this study is exploratory in nature due to a lack of firm level data. Using industry level panel data, the value added of this paper is to meet the research gap by examining the effect of Malaysia’s outward FDI on manufacturing exports. Overall, the findings show that lagged inward FDI, technology development, and industry size are found to positive and significantly influence manufacturing exports as compared to other factors. The insignificant impact of OFDI on manufacturing exports suggests market seeking investment is the main form of OFDI from Malaysia and the destination markets are not served by exports before so that there are no new exports created or displacement of exports. While the results show that there is no need to worry about OFDI’s negative impact on exports, policies should be undertaken to encourage OFDI from Malaysia to create new exports for the country.

Keywords: OFDI, manufacturing industries, exports, Malaysia

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Authors: Soufiane Benoumhani, Nadia Saifi, Boubekeur Dokkar, Mohamed Cherif Benzid

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This work presents the design and simulation of electric equipment for a hybrid solar vehicle. The new drive train of this vehicle is a parallel hybrid system which means a vehicle driven by a great percentage of an internal combustion engine with 49.35 kW as maximal power and electric motor only as assistance when is needed. This assistance is carried out on the rear axle by a single electric motor of 7.22 kW as nominal power. The motor is driven by 12 batteries connecting in series, which are charged by three PV panels (300 W) installed on the roof and hood of the vehicle. The individual components are modeled and simulated by using the Matlab Simulink environment. The whole system is examined under different load conditions. The reduction of CO₂ emission is obtained by reducing fuel consumption. With the use of this hybrid system, fuel consumption can be reduced from 6.74 kg/h to 5.56 kg/h when the electric motor works at 100 % of its power. The net benefit of the system reaches 1.18 kg/h as fuel reduction at high values of power and torque.

Keywords: light car, hybrid system, PV panel, electric motor

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Authors: Dušica Kovačević

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This study explores the influence of destructive groups on the mental health and social integration of high school students in Loznica, Serbia. Despite increasing concerns, there is a significant lack of research on the impact of these groups on adolescents in this region. This qualitative study aims to fill this gap by examining the prevalence of destructive groups, their psychological effects on students, and their broader social implications. Data were collected through surveys and in-depth interviews with high school students, educators, and mental health professionals. The study focuses on key mental health indicators, such as anxiety, depression, and identity formation, alongside social factors, including peer relationships and community engagement. Additionally, it defines coping mechanisms and supporting strategies employed by students affected by these groups. The findings reveal substantial psychological and social challenges faced by students exposed to destructive groups, including increased levels of anxiety and depression, disrupted identity development, and impaired social integration. Insights into the personal experiences of these students provide a detailed understanding of the groups’ impact, underscoring the need for targeted interventions. This research offers evidence-based recommendations for educators, mental health practitioners, and policymakers. It emphasizes the importance of developing effective educational programs and support services to enhance the well-being of high school advocates for proactive measures to protect adolescent mental health and promote healthy social values within educational and community settings.

Keywords: adolescents, mental health, destructive groups, social integration, qualitative study, high school students, Serbia

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Authors: Sara atibi, Azzeddine Atibi, Salim Ahmed, Khadija El Kababi

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Given the crucial impact of entrepreneurship on socio-economic development, nations are making various efforts to support and encourage it. Entrepreneurship education has proven to be a vital lever in stimulating business creation. This research is part of this dynamic, which is increasingly attracting the attention of educational policymakers. Indeed, entrepreneurship education provides students with the skills, knowledge, and motivation needed to succeed in various entrepreneurial contexts. it objective is to demonstrate the impact of entrepreneurship education on the development of entrepreneurial intention among students at Al Akhawayn University and to determine whether introducing this discipline at the secondary school level can strengthen this intention, with the aim of proposing measures to foster entrepreneurship. To achieve this objective, it conducted a literature review on entrepreneurship, entrepreneurial intention, and entrepreneurship education to draw from existing experiences in the field. it then carried out an exploratory study through a qualitative survey. it collected real data via an online questionnaire hosted on Google Drive. This questionnaire was tested on a sample of 100 students, adjusted, and validated by three university professors who are experts in the field, and then administered to the students of Al Akhawayn University. The results of our survey among students at Al Akhawayn University clearly show that the development of entrepreneurial intention increases among students who have taken entrepreneurship courses or participated in seminars, thus promoting business creation and entrepreneurship. A minority of these students still choose to work in the private or public sector; however, the majority express a strong desire to become entrepreneurs. We also noted that some students believe entrepreneurship depends solely on entrepreneurial training, while others think it relies on a combination of training, resources, and personal will.

Keywords: entrepreneurship education, entrepreneurial intention, business creation, al akhawayn university, secondary school curriculum

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Authors: Chin-Shan Lu, Yi-Pei Liu

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This study examines the factors influencing the adoption of MASS in Taiwan's shipping industry. Digital technology and unmanned vehicle advancements have enhanced efficiency and reduced environmental impact in the shipping industry. The IMO has set regulations to promote low-carbon emissions and autonomous ship technology. Using the TOE framework and DOI theory, a research model was constructed, and data from 132 Taiwanese shipping companies were collected via a questionnaire survey. A structural equation modeling (SEM) was conducted to examine the relationships between variables. Results show that technological and environmental factors significantly influence operators' attitudes toward MASS, while organizational factors impact their willingness to adopt. Enhancing technological support, internal resource allocation, top management support, and cost management are crucial for promoting adoption. This study identifies key factors and provides recommendations for adopting autonomous ships in Taiwan's shipping industry.

Keywords: MASS, technology-organization-environment, diffusion of innovations theory, shipping industry

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Authors: Abhinav Kumar Rajverma, Arun Kumar Misra, Abhijeet Chandra

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Family involvement in business is universal across countries, with varying characteristics. Firms of developed economies have diffused ownership structure; however, that of emerging markets have concentrated ownership structure, having resemblance with that of family firms. Optimization of dividend payout and leverage are very crucial for firm’s valuation. This paper studies dividend paying behavior of National Stock Exchange listed Indian firms from financial year 2007 to 2016. The final sample consists of 422 firms and of these more than 49% (207) are family firms. Results reveal that family firms pay lower dividend and are more leveraged compared to non-family firms. This unique data set helps to understand dividend behavior and capital structure of sample firms over a long-time period and across varying family ownership concentration. Using panel regression models, this paper examines factors affecting dividend payout and capital structure and establishes a link between the two using Two-stage Least Squares regression model. Profitability shows a positive impact on dividend and negative impact on leverage, confirming signaling and pecking order theory. Further, findings support bankruptcy theory as firm size has a positive relation with dividend and leverage and volatility shows a negative relation with both dividend and leverage. Findings are also consistent with agency theory, family ownership concentration has negative relation with both dividend payments and leverage. Further, the impact of family ownership control confirms the similar finding. The study further reveals that firms with high family ownership concentration (family control) do have an impact on determining the level of private benefits. Institutional ownership is not significant for dividend payments. However, it shows significant negative relation with leverage for both family and non-family firms. Dividend payout and leverage show mixed association with each other. This paper provides evidence of how varying level of family ownership concentration and ownership control influences the dividend policy and capital structure of firms in an emerging market like India and it can have significant contribution towards understanding and formulating corporate dividend policy decisions and capital structure for emerging economies, where majority of firms exhibit behavior of family firm.

Keywords: dividend, family firms, leverage, ownership structure

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Authors: Ian O'Loughlin

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Memory networks aim to integrate some of the recent successes in machine learning with a dynamic memory base that can be updated and deployed in artificial reasoning tasks. These models involve training networks to identify, update, and operate over stored elements in a large memory array in order, for example, to ably perform question and answer tasks parsing real-world and simulated discourses. This family of approaches still faces numerous challenges: the performance of these network models in simulated domains remains considerably better than in open, real-world domains, wide-context cues remain elusive in parsing words and sentences, and even moderately complex sentence structures remain problematic. This innovation, employing an array of stored and updatable ‘memory’ elements over which the system operates as it parses text input and develops responses to questions, is a compelling one for at least two reasons: first, it addresses one of the difficulties that standard machine learning techniques face, by providing a way to store a large bank of facts, offering a way forward for the kinds of long-term reasoning that, for example, recurrent neural networks trained on a corpus have difficulty performing. Second, the addition of a stored long-term memory component in artificial reasoning seems psychologically plausible; human reasoning appears replete with invocations of long-term memory, and the stored but dynamic elements in the arrays of memory networks are deeply reminiscent of the way that human memory is readily and often characterized. However, this apparent psychological plausibility is belied by a recent turn in the study of human memory in cognitive science. In recent years, the very notion that there is a stored element which enables remembering, however dynamic or reconstructive it may be, has come under deep suspicion. In the wake of constructive memory studies, amnesia and impairment studies, and studies of implicit memory—as well as following considerations from the cognitive neuroscience of memory and conceptual analyses from the philosophy of mind and cognitive science—researchers are now rejecting storage and retrieval, even in principle, and instead seeking and developing models of human memory wherein plasticity and dynamics are the rule rather than the exception. In these models, storage is entirely avoided by modeling memory using a recurrent neural network designed to fit a preconceived energy function that attains zero values only for desired memory patterns, so that these patterns are the sole stable equilibrium points in the attractor network. So although the array of long-term memory elements in memory networks seem psychologically appropriate for reasoning systems, they may actually be incurring difficulties that are theoretically analogous to those that older, storage-based models of human memory have demonstrated. The kind of emergent stability found in the attractor network models more closely fits our best understanding of human long-term memory than do the memory network arrays, despite appearances to the contrary.

Keywords: artificial reasoning, human memory, machine learning, neural networks

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Authors: M. Pienaar, J. W. Odendaal, J. C. Smit, J. Joubert

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Simulations are commonly used to predict the bistatic radar cross section (RCS) of military targets since characterization measurements can be expensive and time consuming. It is thus important to accurately predict the bistatic RCS of targets. Computational electromagnetic (CEM) methods can be used for bistatic RCS prediction. CEM methods are divided into full-wave and asymptotic methods. Full-wave methods are numerical approximations to the exact solution of Maxwell’s equations. These methods are very accurate but are computationally very intensive and time consuming. Asymptotic techniques make simplifying assumptions in solving Maxwell's equations and are thus less accurate but require less computational resources and time. Asymptotic techniques can thus be very valuable for the prediction of bistatic RCS of electrically large targets, due to the decreased computational requirements. This study extends previous work by validating the accuracy of asymptotic techniques to predict bistatic RCS through comparison with full-wave simulations as well as measurements. Validation is done with canonical structures as well as complex realistic aircraft models instead of only looking at a complex slicy structure. The slicy structure is a combination of canonical structures, including cylinders, corner reflectors and cubes. Validation is done over large bistatic angles and at different polarizations. Bistatic RCS measurements were conducted in a compact range, at the University of Pretoria, South Africa. The measurements were performed at different polarizations from 2 GHz to 6 GHz. Fixed bistatic angles of β = 30.8°, 45° and 90° were used. The measurements were calibrated with an active calibration target. The EM simulation tool FEKO was used to generate simulated results. The full-wave multi-level fast multipole method (MLFMM) simulated results together with the measured data were used as reference for validation. The accuracy of physical optics (PO) and geometrical optics (GO) was investigated. Differences relating to amplitude, lobing structure and null positions were observed between the asymptotic, full-wave and measured data. PO and GO were more accurate at angles close to the specular scattering directions and the accuracy seemed to decrease as the bistatic angle increased. At large bistatic angles PO did not perform well due to the shadow regions not being treated appropriately. PO also did not perform well for canonical structures where multi-bounce was the main scattering mechanism. PO and GO do not account for diffraction but these inaccuracies tended to decrease as the electrical size of objects increased. It was evident that both asymptotic techniques do not properly account for bistatic structural shadowing. Specular scattering was calculated accurately even if targets did not meet the electrically large criteria. It was evident that the bistatic RCS prediction performance of PO and GO depends on incident angle, frequency, target shape and observation angle. The improved computational efficiency of the asymptotic solvers yields a major advantage over full-wave solvers and measurements; however, there is still much room for improvement of the accuracy of these asymptotic techniques.

Keywords: asymptotic techniques, bistatic RCS, geometrical optics, physical optics

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Authors: G. N. Srinivas, K. Raju

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This paper presents Markov processes for determining the reliability indices of distribution system. The continuous Markov modeling is applied to a complex radial distribution system and electrical equivalent circuits are developed for the modeling. In general PSPICE is being used for electrical and electronic circuits and various applications of power system like fault analysis, transient analysis etc. In this paper, the SPICE modeling equivalent circuits which are developed are applied in a novel way to Distribution System reliability analysis. These circuits are simulated using PSPICE software to obtain the state probabilities, the basic and performance indices. Thus the basic indices and the performance indices obtained by this method are compared with those obtained by FMEA technique. The application of the concepts presented in this paper are illustrated and analyzed for IEEE-Roy Billinton Test System (RBTS).

Keywords: distribution system, Markov Model, reliability indices, spice simulation

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Authors: W. V. W. H. Wickramaarachchi, S. Walpalage, S. M. Egodage

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Thermoplastic elastomer (TPE) is a multifunctional polymeric material which possesses a combination of excellent properties of parent materials. Basically, TPE has a rubber phase and a thermoplastic phase which gives processability as thermoplastics. When the rubber phase is partially or fully crosslinked in the thermoplastic matrix, TPE is called as thermoplastic elastomer vulcanizate (TPV). If the rubber phase is non-crosslinked, it is called as thermoplastic elastomer olefin (TPO). Nowadays TPEs are introduced into the commercial market with different products. However, the application of TPE as a roofing material is limited. Out of the commercially available roofing products from different materials, only single ply roofing membranes and plastic roofing sheets are produced from rubbers and plastics. Natural rubber (NR) and high density polyethylene (HDPE) are used in various industrial applications individually with some drawbacks. Therefore, this study was focused to develop both TPO and TPV blends from NR and HDPE at different compositions and then to identify the best blend composition to use as a roofing material. A series of blends by varying NR loading from 10 wt% to 50 wt%, at 10 wt% intervals, were prepared using a twin screw extruder. Dicumyl peroxide was used as a crosslinker for TPV. The standard properties for a roofing material like tensile properties tear strength, hardness, impact strength, water absorption, swell/gel analysis and thermal characteristics of the blends were investigated. Change of tensile strength after exposing to UV radiation was also studied. Tensile strength, hardness, tear strength, melting temperature and gel content of TPVs show higher values compared to TPOs at every loading studied, while water absorption and swelling index show lower values, suggesting TPVs are more suitable than TPOs for roofing applications. Most of the optimum properties were shown at 10/90 (NR/HDPE) composition. However, high impact strength and gel content were shown at 20/80 (NR/HDPE) composition. Impact strength, as being an energy absorbing property, is the most important for a roofing material in order to resist impact loads. Therefore, 20/80 (NR/HDPE) is identified as the best blend composition. UV resistance and other properties required for a roofing material could be achieved by incorporating suitable additives to TPVs.

Keywords: thermoplastic elastomer, natural rubber, high density polyethylene, roofing material

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Authors: Suvimon Wajeetongratana, Prateep Wajeetongratana

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The purpose of this research will study the organizational behavior including self-efficacy, hope, optimism, and resiliency that affect to the work motivation in the Dusit workplace and the sample consisted of the production workers in a private company in Dusit area for four hundred workers with approximately 10,000 employees and in this study will provide the multiple regression analysis was used to analyze the questionnaire survey data. The results of the analysis indicate the latent core confidence factor derived from the four components of self-efficacy, hope, optimism, and resiliency provided a significant positive impact on performance. The impact of the integrated latent core confidence factor was, in fact, more effective than derived from any one individual component, as well as any core trait-like self-evaluations such as self-esteem, general efficacy, internal locus of control, and emotional stability.

Keywords: firm performance effectiveness, organizational behavior, work motivation, Dusit workplace

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