Search results for: long-term financial performance

Authors: Joaquin Ticzon, Christian Demition, Jaime Honra

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Additive manufacturing (AM) or 3D printing has been one of the emerging trends present in various industries, particularly in prototyping. This review focuses on the impact of additive manufacturing on a motor vehicle's performance aiming to investigate potential advancements to further revolutionize the way parts are manufactured. One of the most common problems faced in the automotive industry is carbon footprint emissions from motor vehicles, which was stated to be remedied by lightweight; additively manufactured parts helped reduce these emissions due to weight reduction provided by additively manufactured parts. Composed of various techniques for AM as well as materials utilized during the manufacturing process, which differ in terms of the quality and performance it provides during its application on the final product. Given this, the generative design will not be discussed in such a detailed manner because the focus will revolve around the effects on the performance of a vehicle due to additively manufactured parts.

Keywords: additive manufacturing (AM), automotive, computer aided design (CAD), generative design

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Authors: Okoro Ikechukwu Ralph, Fuat Kara

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The discoveries of hydrocarbon reserves has clearly drifted offshore, and in deeper waters - areas where the industry still has limited knowledge; and that were hitherto, regarded as being out of reach. This shift presents significant and increased challenges in technology requirements needed to guarantee safety of personnel, environment and equipment; ensure high reliability of installed equipment; and provide high level of confidence in security of investment and company reputation. Nowhere are these challenges more apparent than on subsea well integrity and production performance. The past two decades has witnessed enormous rise in deep and ultra-deep water offshore field developments for the recovery of hydrocarbons. Subsea installed equipment at the seabed has been the technology of choice for these developments. This paper discusses the role of Subsea Control module (SCM) as a vital factor for deep-water well integrity and production performance. A case study for Deep-water well integrity and production performance is analysed.

Keywords: offshore reliability, production performance, subsea control module, well integrity

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Authors: Nishi Malhotra

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Art has developed as a mode of investment and saving. Art and culture of any nation is the source of foreign direct investment (FDI) generation and growth development. Several intermediaries and skill-building organizations thrive on at and culture for their earnings. Indian art market has grown to Rs. 2000 Crores. Art establishment houses access to privileged information is the main reason for arbitrariness and volatility in the market. The commercialization of art and development of the markets with refinement in the taste of the customers have led to the development of art as an investment avenue. Investors keen on investing in these products can do so, and earnings from art are taxable too, like any other capital asset. This research paper is aimed at exploring the role of art and culture as an investment avenue in India and reasons for increasing volatilities in the art market. Based on an extensive literature review and secondary research, a benchmarking study has been conducted to capture the growth of the art as an investment avenue. These studies indicate that during the financial crisis of 2008-10, the art emerged as an alternative investment avenue. The paper aims at discussing the financial engineering of various art funds and instruments. Based on secondary data available from Sotheby’s, Christies, Bonham, there is a positive correlation between strategic diversification and increasing return in the Art market. Similarly, digitization has led to disintermediation in the art markets and also helped to increase the market base. The data clearly enumerates the growing interest of the Indian investor towards art as an investment option. Much like any other broad asset class, art market too thrives on excess returns provided by diversification. Many financial intermediaries and art funds have emerged, to offer valuable investment planning advisory to a genuine investor. This paper clearly highlights the increasing returns of strategic diversification and its impact on reducing volatility in the art markets. Moreover, with coming up of e-auctions and websites, investors are able to analyse art more objectively. Digitization and commercialization of art have definitely helped in reducing volatility in world art markets.

Keywords: art, investment avenue, diversification, digitization

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Authors: Abdulaziz Alkathiry

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Concussion is a common brain injury that affect physical and cognitive performance. While several studies indicated that adolescents are more likely to develop concussion, in the last decade concussion has been mainly explored in adults. Migraine has been identified as a common symptom reported after concussion and was tied with worse prognoses. Hence, we aimed to investigate the effect of migraine on functional performance and self-reported symptoms in children with concussion. This cross-sectional study involved 35 symptomatic children aged 9 – 17 years recruited within 1 year from their concussion injury at a tertiary balance center. Participants’ symptoms and functional performance were assessed using the post-concussion symptoms scale (PCSS) and the functional gait assessment (FGA) respectively. Concussed children with migraine showed significantly worse symptoms including fatigue, sleeping impairment, difficulty concentrating, and visual problems (P < 0.05). Functional performance didn’t show differences between concussed children with and without migraine. Although concussed children with and without migraine didn’t show any differences on functional performance, worse cognitive symptoms were found in concussed children with migraine. A customized treatment approach is indicated in the presence of migraine for the management of children with concussion. Keywords: Concussion; Migraine; Balance; Post-Concussion Symptoms Scale; Functional Gait Assessment

Keywords: concussion, migraine, post-concussion symptoms scale, functional gait assessment, balance

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Authors: Nidhin Dani Abraham, T. K. Sri Shilpa

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Asset liability management is an important aspect in banking business. Moreover, the today’s banking is based on BASEL III which strictly regulates on the counterparty default. This paper focuses on prediction and analysis of counter party default risk, which is a type of risk occurs when the customers fail to repay the amount back to the lender (bank or any financial institutions). This paper proposes an approach to reduce the counterparty risk occurring in the financial institutions using an appropriate data mining technique and thus predicts the occurrence of NPA. It also helps in asset building and restructuring quality. Liability management is very important to carry out banking business. To know and analyze the depth of liability of bank, a suitable technique is required. For that a data mining technique is being used to predict the dormant behaviour of various deposit bank customers. Various models are implemented and the results are analyzed of saving bank deposit customers. All these data are cleaned using data cleansing approach from the bank data warehouse.

Keywords: data mining, asset liability management, BASEL III, banking

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Authors: Amit Arora, P. M. V. Subbarao, R. S. Agarwal

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This study attempts to find promising locations of upwash delta winglets for an inline finned tube heat exchanger. Later, location of winglets that delivers highest improvement in thermal performance is identified. Numerical results clearly showed that optimally located upwash delta winglets not only improved the thermal performance of fin area in tube wake and tubes, but also improved overall thermal performance of heat exchanger.

Keywords: apparent friction factor, delta winglet, fin and tube heat exchanger, longitudinal vortices

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Authors: Malik Imtiaz Ahmad

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The prime sources of Islamic Law or Shariah are Quran and Sunnah and is applied to the personal and public affairs of Muslims. Islamic law is deemed to be divine and furnishes a complete code of conduct based upon universal values to build honesty, trust, righteousness, piety, charity, and social justice. The primary focus of this paper was to examine the development of Islamic jurisprudence (Fiqh) over time and its relevance to the field of Islamic finance. This encompassed a comprehensive analysis of the historical context, key legal principles, and their application in contemporary financial systems adhering to Islamic principles. This study aimed to elucidate the deep-rooted connection between Islamic law and finance, offering valuable insights for practitioners and policymakers in the Islamic finance sector. Understanding the historical context and legal underpinnings is crucial for ensuring the compliance and ethicality of modern financial systems adhering to Islamic principles. Fintech solutions are developing fields to accelerate the digitalization of Islamic finance products and services for the harmonization of global investors' mandate. Through this study, we focus on institutional governance that will improve Sharia compliance, efficiency, transparency in decision-making, and Islamic finance's contribution to humanity through the SDGs program. The research paper employed an extensive literature review, historical analysis, examination of legal principles, and case studies to trace the evolution of Islamic law and its contemporary application in Islamic finance, providing a concise yet comprehensive understanding of this intricate relationship. Through these research methodologies, the aim was to provide a comprehensive and insightful exploration of the historical evolution of Islamic law and its relevance to contemporary Islamic finance, thereby contributing to a deeper understanding of this unique and growing sector of the global financial industry.

Keywords: sharia, sequencing Islamic jurisprudence, Islamic congruent marketing, social development goals of Islamic finance

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Authors: Rit M., Girard R., Villot J., Thorel M.

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In a scenario of extensive residential housing renovation, stakeholders need models that support decision-making through a deep understanding of the existing building stock and accurate energy demand simulations. To address this need, we have modified an optimization model using open data that enables the study of renovation strategies at both territorial and national scales. This approach provides (1) a definition of a strategy to simplify decision trees from theoretical combinations, (2) input to decision makers on real-world renovation constraints, (3) more reliable identification of energy-saving measures (changes in technology or behaviour), and (4) discrepancies between currently planned and actually achieved strategies. The main contribution of the studies described in this document is the geographic scale: all residential buildings in the areas of interest were modeled and simulated using national data (geometries and attributes). These buildings were then renovated, when necessary, in accordance with the environmental objectives, taking into account the constraints applicable to each territory (number of renovations per year) or at the national level (renovation of thermal deficiencies (Energy Performance Certificates F&G)). This differs from traditional approaches that focus only on a few buildings or archetypes. This model can also be used to analyze the evolution of a building stock as a whole, as it can take into account both the construction of new buildings and their demolition or sale. Using specific case studies of French territories, this paper highlights a significant discrepancy between the strategies currently advocated by decision-makers and those proposed by our optimization model. This discrepancy is particularly evident in critical metrics such as the relationship between the number of renovations per year and achievable climate targets or the financial support currently available to households and the remaining costs. In addition, users are free to seek optimizations for their building stock across a range of different metrics (e.g., financial, energy, environmental, or life cycle analysis). These results are a clear call to re-evaluate existing renovation strategies and take a more nuanced and customized approach. As the climate crisis moves inexorably forward, harnessing the potential of advanced technologies and data-driven methodologies is imperative.

Keywords: residential housing renovation, MILP, energy demand simulations, data-driven methodology

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Authors: Qingli Lei

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This study investigates the impact of family socioeconomic status and parental involvement on the academic performance of elementary school students, specifically focusing on migrant students in China. The findings reveal that gender has a stronger influence on academic performance compared to local status and parental tutoring time. Female students tend to achieve higher scores than males. Parental education level does not significantly predict academic performance, while parent tutoring time does have a significant impact. Furthermore, there is a significant interaction between local status and parental education level, indicating that migrant students with lower-educated parents perform better than their local counterparts, while local children excel when their parents' education levels are higher. These results emphasize the importance of parental involvement, particularly for immigrant students, and highlight the need for interventions that enhance parental engagement in education to improve academic outcomes.

Keywords: academic performance, family socioeconomic status, migrant students, parental involvement

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Authors: Razika Ihaddadene, Nabila Ihaddadene

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This paper aims to highlight the importance of the application of the IEC 61724 standard in the study of the performance analysis of photovoltaic power plants on a monthly and annual scale. Likewise, the comparison of two photovoltaic power plants with two different climates was carried out in order to determine the effect of climatic parameters on the analysis of photovoltaic performances. All data from the Ain Skhouna and Adrar photovoltaic power plants for 2018 and the data from the Saida1 field for one month in 2019 were used. The results of the performance analysis according to the indicated standard show that the Saida PV power plant performs better than the Adrar PV power plant, which is due to the effect of increasing the ambient temperature. Increasing ambient temperature increases losses decreases system efficiency and performance ratio. It presents a key element in the proper functioning of PV plants.

Keywords: pv power plants, IEC 61724 norm, grid connected pv, algeria

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Authors: Mukesh Kumar, Onkar Singh, Naveen Kumar, Amar Deep

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The waste cooking oil is taken as feedstock for biodiesel production. For this research, waste cooking oil is collected from many hotels and restaurants, and then biodiesel is prepared for experimentation purpose. The prepared biodiesel is mixed with mineral diesel in the proportion of 10%, 20%, and 30% to perform tests on a diesel engine. The experimental analysis is carried out at different load conditions to analyze the impact of the blending ratio on the performance and emission parameters. When the blending proportion of biodiesel is increased, then the highest pressure reduces due to the fall in the calorific value of the blended mixture. Experimental analysis shows a promising decrease in nitrogen oxides (NOx). A mixture of 20% biodiesel and mineral diesel is the best negotiation, mixing ratio, and beyond that, a remarkable reduction in the outcome of the performance has been observed.

Keywords: alternative sources, diesel engine, emissions, performance

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Authors: Abdolmajid Mosleh, Afzal Ghasimi

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The purpose of this research is to investigate and identify effective factors that can improve the quality of personal performance in industrial companies. In the present study, it was assumed that the hidden variables of talent management could be explained by an important part of the variance in improving the quality of employee performance. This research is targeted in terms of applied research. The statistical population of the research is SAIPA automobile company with a number (N=10291); the sample of 380 people was selected based on the Cochran formula in a random sampling method among employed people. The measurement tool in this research was a questionnaire of 33 items with a control questionnaire that included two talent management departments (talent identification and talent exploitation) and improvements in staff performance (enhancement of technical and specialized capabilities, managerial capability, organizational interaction, and communication). The reliability of the internal consistency method was confirmed by the Cronbach's alpha coefficient and the two half-ways. In order to determine the validity of the questionnaire structure, confirmatory factor analysis was used. Based on the results of the data analysis, the effect of talent management on improving the quality of staff performance was confirmed. Based on the results of inferential statistics and structural equations of the proposed model, it had high fitness.

Keywords: employee performance, talent management, performance improvement, SAIPA automobile manufacturing company

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In multi-echelon supply chain networks, optimal supplier selection significantly depends on the accuracy of suppliers’ performance prediction. Different methods of multi criteria decision making such as ANN, GA, Fuzzy, AHP, etc have been previously used to predict the supplier performance but the “black-box” characteristic of these methods is yet a major concern to be resolved. Therefore, the primary objective in this paper is to implement an artificial intelligence-based gene expression programming (GEP) model to compare the prediction accuracy with that of ANN. A full factorial design with %95 confidence interval is initially applied to determine the appropriate set of criteria for supplier performance evaluation. A test-train approach is then utilized for the ANN and GEP exclusively. The training results are used to find the optimal network architecture and the testing data will determine the prediction accuracy of each method based on measures of root mean square error (RMSE) and correlation coefficient (R2). The results of a case study conducted in Supplying Automotive Parts Co. (SAPCO) with more than 100 local and foreign supply chain members revealed that, in comparison with ANN, gene expression programming has a significant preference in predicting supplier performance by referring to the respective RMSE and R-squared values. Moreover, using GEP, a mathematical function was also derived to solve the issue of ANN black-box structure in modeling the performance prediction.

Keywords: Supplier Performance Prediction, ANN, GEP, Automotive, SAPCO

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Authors: Asia Ashfaq, Muhammad Saud

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The present study aims to highlight the socio-economic aspect of international migration by analyzing the effect of remittances sent by adult male children on the well-being of left behind parents. Well-being of left behind parents was operationalized through two indicators as financial security and health-care facilities. For this purpose, quantitative research design was employed and a survey was conducted in three cities i.e. Gujrat, Jhelum and Mirpur. The data was collected from 94 respondents chosen--purposively--on the basis of certain characteristics including demographic profile of the respondents and their male children who must be living abroad. The findings of the study revealed that parents were getting money from their sons regularly. Parents were getting financial assistance from their children for managing their household expenditures, visiting good hospitals and the specialist doctors in case of illness. Lastly, the study concluded that the economic aspect of migration of male children has a significant impact on the health status of left behind parents with the value of correlation (r) =0.241 and level of significance as 0.019. The research study also gives some suggestions and provides future directions for research.

Keywords: international migration, left behind parents, Pakistan, remittances, well-being

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Authors: Nurul Nadrah

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As a result of the COVID-19 pandemic, a movement control order was implemented, leading to the adoption of online learning as a substitute for conventional classroom instruction. Thus, this study aims to determine the differences in skill performance between online learning and conventional methods among nursing students. We employed a quasi-experimental design with purposive sampling, involving a total of 59 nursing students, and used online learning as the intervention. As a result, the study found there was a significant difference in student skill performance between online learning and conventional methods. As a conclusion, in times of hardship, it is necessary to implement alternative pedagogical approaches, especially in critical fields like nursing, to ensure the uninterrupted progression of educational programs. This study suggests that online learning can be effectively employed as a means of imparting knowledge to nursing students during their training.

Keywords: nursing education, online learning, skill performance, conventional learning method

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Authors: Ahmadreza Jabalameli, Mohammad Ebrahimpour Borujeni

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This study aims to evaluate the effectiveness of intensive short-term dynamic psychotherapy (ISTDP) on ambiguity tolerance, emotional intelligence and stress coping strategies in financial market traders. The methodology of this study was quasi-experimental, pre-test and post-test with control group. The statistical population of this study includes all students at Jabalameli Information Technology Academy in 2022. Among them, 30 people were selected by voluntary sampling through interviews, and were randomly divided into two experimental and control groups of 51 people. And the components were measured according to McLain Ambiguity Tolerance Questionnaire, Bar-On Emotional Intelligence and Lazarus Stress Coping Strategies. The data were obtained by SPSS software and were analyzed by using multivariate analysis of covariance. The results indicate that intensive short-term dynamic psychotherapy influences the emotional intelligence as well as the ambiguity tolerance of traders.

Keywords: ISTDP, ambiguity tolerance, trading, emotional intelligence, stress

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Authors: Eudjen Cinc

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Work with a human voice, especially with a child s voice and cultivating the sound of the choir, presents an area of crucial importance for a conductor. We use the term conductor because it needs to be understood that regardless of whether we have in front of us an amateur or a professional choir, whether they are singers with a wealth of experience or children who are still developing and educating their inner ear so that in the future they could contribute to the development of choir music, the person who stands in front of the group and works with them, needs to have the characteristics of a conductor. Voice formation is a long-term process, without which there is no success in both solo and collective music performance.

Keywords: music group, conductor, collective, performance

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Authors: Taylan Kabbani, Ekrem Duman

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The design of adaptive systems that take advantage of financial markets while reducing the risk can bring more stagnant wealth into the global market. However, most efforts made to generate successful deals in trading financial assets rely on Supervised Learning (SL), which suffered from various limitations. Deep Reinforcement Learning (DRL) offers to solve these drawbacks of SL approaches by combining the financial assets price "prediction" step and the "allocation" step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. In this paper, a continuous action space approach is adopted to give the trading agent the ability to gradually adjust the portfolio's positions with each time step (dynamically re-allocate investments), resulting in better agent-environment interaction and faster convergence of the learning process. In addition, the approach supports the managing of a portfolio with several assets instead of a single one. This work represents a novel DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem, or what is referred to as The Agent Environment as Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. More specifically, we design an environment that simulates the real-world trading process by augmenting the state representation with ten different technical indicators and sentiment analysis of news articles for each stock. We then solve the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which can learn policies in high-dimensional and continuous action spaces like those typically found in the stock market environment. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of deep reinforcement learning in financial markets over other types of machine learning such as supervised learning and proves its credibility and advantages of strategic decision-making.

Keywords: the stock market, deep reinforcement learning, MDP, twin delayed deep deterministic policy gradient, sentiment analysis, technical indicators, autonomous agent

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Authors: Jing Zhang

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Sustainable development in the new energy vehicles field is the requirement of the net zero aim. Green bonds are accepted as a practical financial tool to boost the transformation of relevant enterprises. The paper analyzes the interactions among governments, enterprises of new energy vehicles, and financial institutions by an evolutionary game theory model and offers advice to stakeholders in China. The decision-making subjects of green behavior are affected by experiences, interests, perception ability, and risk preference, so it is difficult for them to be completely rational. Based on the bounded rationality hypothesis, this paper applies prospect theory in the evolutionary game analysis framework and analyses the costs of government regulation of enterprises adopting green bonds. The influence of the perceived value of revenue prospect and the probability and risk transfer coefficient of the government's active regulation on the decision-making agent's strategy is verified by numerical simulation. Finally, according to the research conclusions, policy suggestions are given to promote green bonds.

Keywords: green bonds, new energy vehicles, sustainable development, evolutionary Game Theory model

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Authors: Tugrul Oktay, Mehmet Konar, Mohamed Abdallah Mohamed, Murat Aydin, Firat Sal, Murat Onay, Mustafa Soylak

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In this paper, it is aimed to improve autonomous flight performance of a load-carrying (payload: 3 kg and total: 6kg) unmanned aerial vehicle (UAV) through active wing and horizontal tail active morphing and also integrated autopilot system parameters (i.e. P, I, D gains) and UAV parameters (i.e. extension ratios of wing and horizontal tail during flight) design. For this purpose, a loadcarrying UAV (i.e. ZANKA-II) is manufactured in Erciyes University, College of Aviation, Model Aircraft Laboratory is benefited. Optimum values of UAV parameters and autopilot parameters are obtained using a stochastic optimization method. Using this approach autonomous flight performance of UAV is substantially improved and also in some adverse weather conditions an opportunity for safe flight is satisfied. Active morphing and integrated design approach gives confidence, high performance and easy-utility request of UAV users.

Keywords: unmanned aerial vehicles, morphing, autopilots, autonomous performance

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Authors: Onur Arugaslan, Ajay Samant, Devrim Yaman

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Financial advisors and investors seek new assets which could potentially increase portfolio returns and decrease portfolio risk. Cryptocurrencies represent a relatively new asset class which could serve in both these roles. There has been very little research done in the area of the risk/return tradeoff in a portfolio consisting of fixed income assets, stocks, and cryptocurrency. The objective of this study is a rigorous examination of this issue. The data used in the study are the monthly returns on 4-week US Treasury Bills, S&P Investment Grade Corporate Bond Index, Bitcoin and the S&P 500 Stock Index. The methodology used in the study is the application Modern Portfolio Theory to evaluate the risk-adjusted returns of portfolios with varying combinations of these assets, using Sharpe, Treynor and Jensen Indexes, as well as the Sortino and Modigliani measures. The results of the study would include the ranking of various investment portfolios based on their risk/return characteristics. The conclusions of the study would include objective empirical inference for investors who are interested in including cryptocurrency in their asset portfolios but are unsure of the risk/return implications.

Keywords: financial economics, portfolio diversification, fixed income securities, cryptocurrency, stock indexes

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Authors: P. Chaipanya, R. Keawchai, W. Sombatsanongkhun, S. Jantaramporn

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To manage the demand of wireless communication that has been dramatically increased, switched beam antenna in smart antenna system is focused. Implementation of switched beam antennas at mobile terminals such as notebook or mobile handset is a preferable choice to increase the performance of the wireless communication systems. This paper proposes the low complexity switched beam antenna using single element of antenna which is suitable to implement at mobile terminal. Main beam direction is switched by changing the positions of short circuit on the radiating patch. There are four cases of switching that provide four different directions of main beam. Moreover, the performance in terms of Signal to Interference Ratio when utilizing the proposed antenna is compared with the one using omni-directional antenna to confirm the performance improvable.

Keywords: switched beam, shorted circuit, single element, signal to interference ratio

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Authors: Yusuf Ziya Ayık, Ferhat Kahveci

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Currently, database management systems have various tools such as backup and maintenance, and also provide statistical information such as resource usage and security. In terms of query performance, this paper covers query optimization, views, indexed tables, pre-computation materialized view, query performance analysis in which query plan alternatives can be created and the least costly one selected to optimize a query. Indexes and views can be created for related table columns. The literature review of this study showed that, in the course of time, despite the growing capabilities of the database management system, only database administrators are aware of the need for dealing with archival and transactional data types differently. These data may be constantly changing data used in everyday life, and also may be from the completed questionnaire whose data input was completed. For both types of data, the database uses its capabilities; but as shown in the findings section, instead of repeating similar heavy calculations which are carrying out same results with the same query over a survey results, using materialized view results can be in a more simple way. In this study, this performance difference was observed quantitatively considering the cost of the query.

Keywords: cost of query, database management systems, materialized view, query performance

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Authors: Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang

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2016 has become the year of the Artificial Intelligence explosion. AI technologies are getting more and more matured that most world well-known tech giants are making large investment to increase the capabilities in AI. Machine learning is the science of getting computers to act without being explicitly programmed, and deep learning is a subset of machine learning that uses deep neural network to train a machine to learn  features directly from data. Deep learning realizes many machine learning applications which expand the field of AI. At the present time, deep learning frameworks have been widely deployed on servers for deep learning applications in both academia and industry. In training deep neural networks, there are many standard processes or algorithms, but the performance of different frameworks might be different. In this paper we evaluate the running performance of two state-of-the-art distributed deep learning frameworks that are running training calculation in parallel over multi GPU and multi nodes in our cloud environment. We evaluate the training performance of the frameworks with ResNet-50 convolutional neural network, and we analyze what factors that result in the performance among both distributed frameworks as well. Through the experimental analysis, we identify the overheads which could be further optimized. The main contribution is that the evaluation results provide further optimization directions in both performance tuning and algorithmic design.

Keywords: artificial intelligence, machine learning, deep learning, convolutional neural networks

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Authors: Pascal François Faye, Baye Mor Sall, Bineta Dembele, Jeanne Ana Awa Faye

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In agriculture, estimating crop yields is key to improving productivity and decision-making processes such as financial market forecasting and addressing food security issues. The main objective of this paper is to have tools to predict and improve the accuracy of crop yield forecasts using machine learning (ML) algorithms such as CART , KNN and SVM . We developed a mobile app and a web app that uses these algorithms for practical use by farmers. The tests show that our system (collection and deployment architecture, web application and mobile application) is operational and validates empirical knowledge on agro-climatic parameters in addition to proactive decision-making support. The experimental results obtained on the agricultural data, the performance of the ML algorithms are compared using cross-validation in order to identify the most effective ones following the agricultural data. The proposed applications demonstrate that the proposed approach is effective in predicting crop yields and provides timely and accurate responses to farmers for decision support.

Keywords: prediction, machine learning, artificial intelligence, digital agriculture

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Authors: Mohamed El-Khateeb

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Encompassing inventory, warehousing, and transportation management, logistics is a crucial predictor of firm performance. This has been extensively proven by extant literature in business and operations management. Logistics is also a fundamental determinant of a country's ability to access international markets. Available studies in international and transport economics have shown that limited transport infrastructure and underperforming transport services can severely affect international competitiveness. However, the evidence lacks the overall impact of logistics performance-encompassing all inventory, warehousing, and transport components- on global trade. In order to fill this knowledge gap, the paper uses a gravitational trade model with 155 countries from all geographical regions between 2007 and 2018. Data on logistics performance is obtained from the World Bank's Logistics Performance Index (LPI). First, the relationship between logistics performance and a country’s total trade is estimated, followed by a breakdown by the economic sector. Then, the analysis is disaggregated according to the level of technological intensity of traded goods. Finally, after evaluating the intensive margin of trade, the relevance of logistics infrastructure and services for the extensive trade margin is assessed. Results suggest that: (i) improvements in both logistics infrastructure and services are associated with export growth; (ii) manufactured goods can significantly benefit from these improvements, especially when both exporting and importing countries increase their logistics performance; (iii) the quality of logistics infrastructure and services becomes more important as traded goods are technology-intensive; and (iv) improving the exporting country's logistics performance is essential in the intensive margin of trade while enhancing the importing country's logistics performance is more relevant in the extensive margin.

Keywords: low-cost, recycling, reuse, solid waste, wastewater treatment

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Authors: N. Hiranmai, M. L. S. Deva Kumar

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In this project, it is planned to carry out an experimental investigation on 4- stroke Direct Injection Diesel Engine, which is a single-cylinder, four-stroke, water-cooled, and constant speed engine capable of developing a power output of 3.7 kW at 1500 rpm, run with diesel fuel and also with different proportions of Safflower oil methyl esters, with a piston having five number of grooves on its crown to create turbulence. Various performance parameters, such as brake power, specific fuel consumption, and thermal efficiency, are calculated. At all the load conditions, the performance of the engine is obtained better for blend B40 (40% Safflower oil + 60% of Diesel). At different load conditions, Brake thermal Efficiency (ηbth) is comparatively more for all blends than that for Diesel. At different load conditions, ηith is less for blend B40.

Keywords: four-stroke engine, diesel, safflower oil, engine performance, emissions.

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Authors: Uwalomwa Uwuigbe, Olubukola Ranti Uwuigbe, Jinadu Olugbenga, Otekunrin Adegbola

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Corporate reporting has evolved over the years resulting from criticisms of the precedent by shareholders, stakeholders and other relevant financial institutions. Integrated reporting has become a globalized corporate reporting style, with its adoption around the world occurring rapidly to bring about an improvement in the quality of corporate reporting. While some countries have swiftly clinched into reporting in an integrated manner, others have not. In addition, there are ample research that has been conducted on the benefits of adopting integrated reporting, however, the same is not true in developing economies like Nigeria. Hence, this study basically examined the factors determining the adoption of integrated reporting in Nigeria. One hundred (100) copies of questionnaire was administered to financial managers of 20 selected listed companies in the Nigeria stock exchange market. The data obtained was analysed using the Spearman Rank Order Correlation via the Statistical Package for Social Science. This study observed that there is a significant relationship between the social pressures of isomorphic changes and integrated reporting adoption in Nigeria. The study recommends the need for an enforcement mechanism to be put in place while considering the adoption of integrated reporting in Nigeria, enforcement mechanisms should put into consideration the investors demand, the level of economic development, and the degree of corporate social responsibility.

Keywords: corporate social responsibility, isomorphic, integrated reporting, Nigeria, sustainability

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Authors: N. K. Chougule, G. V. Parishwad

Abstract:

The pin fin heat sink is a novel heat transfer device to transfer large amount of heat through with very small temperature differences and it also possesses large uniform cooling characteristics. Pin fins are widely used as elements that provide increased cooling for electronic devices. Increasing demands regarding the performance of such devices can be observed due to the increasing heat production density of electronic components. For this reason, extensive work is being carried out to select and optimize pin fin elements for increased heat transfer. In this paper, the effects of design parameters and the optimum design parameters for a Pin-Fin heat sink (PFHS) under multi-jet impingement case with thermal performance characteristics have been investigated by using Taguchi methodology based on the L9 orthogonal arrays. Various design parameters, such as pin-fin array size, gap between nozzle exit to impingement target surface (Z/d) and air velocity are explored by numerical experiment. The average convective heat transfer coefficient is considered as the thermal performance characteristics. The analysis of variance (ANOVA) is applied to find the effect of each design parameter on the thermal performance characteristics. Then the results of confirmation test with the optimal level constitution of design parameters have obviously shown that this logic approach can effective in optimizing the PFHS with the thermal performance characteristics. The analysis of the Taguchi method reveals that, all the parameters mentioned above have equal contributions in the performance of heat sink efficiency. Experimental results are provided to validate the suitability of the proposed approach.

Keywords: Pin Fin Heat Sink (PFHS), Taguchi method, CFD, thermal performance

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Authors: K. Thawichai, R. Pornthep

Abstract:

The purpose of this study was to compare the effects of a four week training period of combined plyometric and resistance training or resistance training alone on muscle strength and sprint performance in wheelchair racing athletes. The participants were sixteen healthy male wheelchair racing athletes of the Thai national team. All participants were randomly assignments into two groups in the plyometric and resistance training group (n = 8) performed plyometric exercises followed by resistance training, whereas the resistance training group (n = 8) performed static stretching and the same resistance training program. At baseline and after training all participants were tested on 1-RM bench press for muscle strength and 100-m cycling sprint performance. The results of this study show that the plyometric and resistance training group made significantly greater improvements in overall muscle strength and sprint performance than the resistance training group following training. In conclusion, these findings suggest that the addition of a four week plyometric and resistance training program more beneficial than resistance training alone on muscle strength and sprint performance in wheelchair racing athletes.

Keywords: plyometric, resistance training, strength, sprint, wheelchair athletes

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