Search results for: substantial budgetary allocation

Authors: Maria M. Giannakou, Athanasios K. Ziliaskopoulos

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Transmission pipelines carrying natural gas are often routed through populated cities, industrial and environmentally sensitive areas. While the need for these networks is unquestionable, there are serious concerns about the risk these lifeline networks pose to the people, to their habitat and to the critical infrastructures, especially in view of natural disasters such as earthquakes. This work presents an Integrated Pipeline Risk Management methodology (IPRM) for assessing the hazard associated with a natural gas pipeline failure due to natural or manmade disasters. IPRM aims to optimize the allocation of the available resources to countermeasures in order to minimize the impacts of pipeline failure to humans, the environment, the infrastructure and the economic activity. A proposed knapsack mathematical programming formulation is introduced that optimally selects the proper mitigation policies based on the estimated cost – benefit ratios. The proposed model is demonstrated with a small numerical example. The vulnerability analysis of these pipelines and the quantification of consequences from such failures can be useful for natural gas industries on deciding which mitigation measures to implement on the existing pipeline networks with the minimum cost in an acceptable level of hazard.

Keywords: cost benefit analysis, knapsack problem, natural gas distribution network, risk management, risk mitigation

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Authors: Kiran Kumar Gellaboina, Padmaja Kaja

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Agricultural Education and Research in India needs a transformation to serve the needs of the farmers and that of the nation. The fact that Agriculture and allied activities act as main source of livelihood for more than 70% population of rural India reinforces its importance in administrative and policy arena. As per Census 2011 of India it provides employment to approximately 56.6 % of labour. India has achieved significant growth in agriculture, milk, fish, oilseeds and fruits and vegetables owing to green, white, blue and yellow revolutions which have brought prosperity to farmers. Many factors are responsible for these achievement viz conducive government policies, receptivity of the farmers and also establishment of higher agricultural education institutions. The new breed of skilled human resources were instrumental in generating new technologies, and in its assessment, refinement and finally its dissemination to the farming community through extension methods. In order to sustain, diversify and realize the potential of agriculture sectors, it is necessary to develop skilled human resources. Agricultural human resource development is a continuous process undertaken by agricultural universities. The Department of Agricultural Research and Education (DARE) coordinates and promotes agricultural research & education in India. In India, agricultural universities were established on ‘land grant’ pattern of USA which helped incorporation of a number of diverse subjects in the courses as also provision of hands-on practical exposure to the student. The State Agricultural Universities (SAUs) established through the legislative acts of the respective states and with major financial support from them leading to administrative and policy controls. It has been observed that pace and quality of technology generation and human resource development in many of the SAUs has gone down. The reason for this slackening are inadequate state funding, reduced faculty strength, inadequate faculty development programmes, lack of modern infrastructure for education and research etc. Establishment of new state agricultural universities and new faculties/colleges without providing necessary financial and faculty support has aggrieved the problem. The present work highlights some of the key issues affecting agricultural education and research in India and the impact it would have on farm productivity and sustainability. Secondary data pertaining to budgetary spend on agricultural education and research will be analyzed. This paper will study the trends in public spending on agricultural education and research and the per capita income of farmers in India. This paper tries to suggest that agricultural education and research has a key role in equipping the human resources for enhanced agricultural productivity and sustainable use of natural resources. Further, a total re-orientation of agricultural education with emphasis on other agricultural related social sciences is needed for effective agricultural policy research.

Keywords: agriculture, challenges, education, research

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Authors: P. Strakos, M. Jaros, T. Karasek, T. Kozubek, P. Vavra, T. Jonszta

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In medical imaging, segmentation of different areas of human body like bones, organs, tissues, etc. is an important issue. Image segmentation allows isolating the object of interest for further processing that can lead for example to 3D model reconstruction of whole organs. Difficulty of this procedure varies from trivial for bones to quite difficult for organs like liver. The liver is being considered as one of the most difficult human body organ to segment. It is mainly for its complexity, shape versatility and proximity of other organs and tissues. Due to this facts usually substantial user effort has to be applied to obtain satisfactory results of the image segmentation. Process of image segmentation then deteriorates from automatic or semi-automatic to fairly manual one. In this paper, overview of selected available software applications that can handle semi-automatic image segmentation with further 3D volume reconstruction of human liver is presented. The applications are being evaluated based on the segmentation results of several consecutive DICOM images covering the abdominal area of the human body.

Keywords: image segmentation, semi-automatic, software, 3D volumetric reconstruction

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Authors: Ahmed S. Abdulrasool

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Recently sand wall started to gain more attention as the sand is easy to compact by using vibroflotation technique. An advantage of sand wall is the availability of different additives that can be mixed with sand to increase the stiffness of the sand wall and hence to increase its performance. In this paper, the bearing capacity of circular foundation surrounded by sand wall stabilized with lime is evaluated through laboratory testing. The studied parameters include different sand-lime walls depth (H/D) ratio (wall depth to foundation diameter) ranged between (0.0-3.0). Effect of lime percentages on the bearing capacity of skirted foundation models is investigated too. From the results, significant change is occurred in the behavior of shallow foundations due to confinement of the soil. It has been found that (H/D) ratio of 2 gives substantial improvement in bearing capacity, and beyond (H/D) ratio of 2, there is no significant improvement in bearing capacity. The results show that the optimum lime content is 11%, and the maximum increase in bearing capacity reaches approximately 52% at (H/D) ratio of 2.

Keywords: bearing capacity, circular foundation, clay soil, lime-sand wall

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Authors: Roza Rahbari

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After the Nigatta earthquake in Japan, in 1960, the liquefaction and its related hazards, moved to the thick of matter. Most of the research have been carried out on clean sands and silty sands so far, in order to study the effect of fine particles, confinement pressures, density and so on. However, because of this delusion that adhesiveness of clay prevents the liquefaction in sand, studies on clayey sands have not been taken seriously. However, several liquefactions happened in clayey sands in recent years, and lead to the necessity of more studies in this field. The studies which were carried out so far focused on high plastic clays. In this paper, the effect of low plasticity clays on the behavioral characteristics of sands is discussed. Thus, some triaxial tests were carried out on clean sands and clayey sands with different percentages of added clay. Specimens were compacted in various densities to study the effect of quantity of clay on various densities, too. Based on the findings, the amount of clay affects the behavior of sand greatly and leads to substantial changes in peak bearing capacity and steady state values.

Keywords: liquefaction, clay, sand, triaxial, monotonic, failure

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Authors: Anh Dao Vu, Bill Ryan

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The Vietnamese government struggles to grapple with the problem of rampant corruption, one of the most challenging difficulties the country faces. According to Transparency International’s Corruption Perceptions Index (CPI) 2014, Vietnam ranks 119 out of 175 countries. The CPI gives Vietnam a score of 31 on a scale from 0 to 100, where 0 indicates ‘highly corrupt’ and 100 represents ‘very clean’. Corruption eats into the national GDP of Vietnam, causing a loss of 3% to 4% of GDP per annum. In general, the Vietnamese people’s trust in their government to wage an effective fight against corruption, especially in the public sector, has been greatly eroded in recent years. Some substantial public demonstrations persuaded the government to implement strong anti-corruption measures. However, so far those measures have not been particularly successful. One of the main reasons for this shortcoming is that neither the Communist Party of Vietnam nor the government has demonstrated sufficiently strong ‘political will’ in fighting corruption. There remains a large gap between rhetoric and reality. This paper will examine the reasons why insufficient ‘political will’ is displayed in the ostensible fight against public sector corruption, and how certain anti-corruption strategies will both strengthen levels of political commitment to the fight against corruption while enhancing the effectiveness of that essential national endeavor.

Keywords: corruption, political will, Vietnam, anti-corruption

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Authors: Eldho Paul, Brijesh Paul

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This work proposes an auction mechanism based solution methodology for the optimum scheduling of trucks in a cross-docking centre. The cross-docking centre is an important element of lean supply chain. It reduces the amount of storage and transportation costs in the distribution system compared to an ordinary warehouse. Better scheduling of trucks in a cross-docking center is the best way to reduce storage and transportation costs. Auction mechanism is commonly used for allocation of limited resources in different real-life applications. Here, we try to schedule inbound trucks by integrating auction mechanism with the functioning of a cross-docking centre. A mathematical model is developed for the optimal scheduling of inbound trucks based on the auction methodology. The determination of exact solution for problems involving large number of trucks was found to be computationally difficult, and hence a genetic algorithm based heuristic methodology is proposed in this work. A comparative study of exact and heuristic solutions is done using five classes of data sets. It is observed from the study that the auction-based mechanism is capable of providing good solutions to scheduling problem in cross-docking centres.

Keywords: auction mechanism, cross-docking centre, genetic algorithm, scheduling of trucks

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Authors: Priyanka Bhatnagar, Malkeshkumar Patel, Joondong Kim, Joonpyo Hong

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Artificial skin and sensory memory platforms are produced using a flexible, transparent photovoltaic (TPV) device. The TPV device is composed of a metal oxide heterojunction (nZnO/p-NiO) and transmits visible light (> 50%) while producing substantial electric power (0.5 V and 200 μA cm-2 ). This TPV device is a transparent energy interface that can be used to detect signals and propagate information without an external energy supply. The TPV artificial skin offers a temperature detection range (0 C75 C) that is wider than that of natural skin (5 C48 °C) due to the temperature-sensitive pyrocurrent from the ZnO layer. Moreover, the TPV thermoreceptor offers sensory memory of extreme thermal stimuli. Much like natural skin, artificial skin uses the nociceptor mechanism to protect tissue from harmful damage via signal amplification (hyperalgesia) and early adaption (allodynia). This demonstrates the many features of TPV artificial skin, which can sense and transmit signals and memorize information under self-operation mode. This transparent photovoltaic skin can provide sustainable energy for use in human electronics.

Keywords: transparent, photovoltaics, thermal memory, artificial skin, thermoreceptor

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Authors: Alireza Taghdiri, Sara Ghanbarzade Ghomi

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Nowadays, steel structures are used for not only common buildings but also high-rise construction and wide span covering. The advanced methods of construction as well as the advanced structural connections have a great effect on architecture. However a better use of steel structural systems will be achieved with the deep understanding of steel structures specifications and their substantial advantages. On the other hand, the steel structures face to the different environmental factors such as air flow which cause erosion and corrosion. With the time passing, the amount of these steel mass damages and also the imposed stress will be increased. In other words, the position of erosion in steel structures related to existing stresses indicates that effective environmental conditions will gradually decrease the structural resistance of steel components and result in decreasing the durability of steel components. In this paper, the durability of different steel structural components is evaluated and on the basis of these stress, architectural strategies for designing the system and the components of steel structures is recognized in order to achieve an optimum life cycle.

Keywords: durability, bending stress, erosion in steel structure, life cycle

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Authors: Maria Casoria

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Throughout the last decade developing countries have been undergoing substantial reforms to promote the establishment of competition regimes, as consequence of the trade liberalization and the spread of a ‘competition awareness movement’ across the globe. The legislative trend affected the whole Asia. Notwithstanding the existence of extensive joint ventures, cartels and other collusive business relationships in this geographical area, almost all the countries have already passed or are committed to enforce specific laws in the field. The study dwells into legal solutions adopted in the five sub-regions in which the continent is commonly divided –i.e. Central, East, South, Southeast, and Western Asia- and, using a comparative methodology, shed lights on the main differences and similarities in place. The final outcome of the analysis is that, despite the undeniable divergences of approach, what links together the legislation in force in the region is the unveiled influence exercised by the European Union competition regulation. Consequently, in order to properly evaluate the deterrence of the rule of law in the sector concerned, it is fundamental to scrutinize the major role played by the EU and its policy for the evolution of pro-competitive practices in the continent.

Keywords: Asia, competition law, differences and similarities, European union, influences

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Authors: Pengfei Liu, Yiyi Xu

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There have been substantial incidents of wind turbine blade fractures and failures due to the lack of systematic blade strength design method incorporated with the aerodynamic forces and power generation efficiency. This research was to develop a methodology and procedure for the wind turbine rotor blade strength taking into account the strength, integration, and aerodynamic performance in terms of power generation efficiency. The wind turbine blade designed using this method and procedure will have a uniform strength across the span to save unnecessary thickness in many blade radial locations and yet to maintain the optimum power generation performance. A turbine rotor code, taking into account both aerodynamic and structural properties, was developed. An existing wind turbine blade was used as an example. For a condition of extreme wind speed of 100 km per hour, the design reduced about 19% of material usage while maintaining the optimum power regeneration efficiency.

Keywords: renewable energy, wind turbine, turbine blade strength, aerodynamics-strength coupled optimization

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Authors: Matthias Nnadi

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Using samples of 250 large listed firms by market capitalization in China and Hong Kong, we conducted empirical test to determine the impact of regulatory environment on reporting quality following IFRS convergence using three financial reporting measures; earning management, timely loss recognition and value relevance. Our results indicate that accounting data are more value relevant for Hong Kong listed firms than the Chinese A-share firms. The empirical results for timely loss recognition further reveal that there is a larger coefficient estimate on bad news earnings, which suggests that Chines A-share firms are more likely to report losses in a timely manner. The results support the evidence that substantial convergence of IFRS can improve financial reporting quality in a regulated environment such as China. This further supports the expectation that IFRS are relevant to China and has positive effect on its accounting practice and quality.

Keywords: reporting, quality, earning, loss, relevance, financial, China, Hong Kong

Procedia PDF Downloads 441

Authors: E. U. Dampage, Ovindi D. Bandara, Vinushi S. Waraketiya, Samitha S. R. De Silva, Yasiru S. Gunarathne

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The knowledge of water inflow figures is paramount in decision making on the allocation for consumption for numerous purposes; irrigation, hydropower, domestic and industrial usage, and flood control. The understanding of how reservoir inflows are affected by different climatic and hydrological conditions is crucial to enable effective water management and downstream flood control. In this research, we propose a method using a Long Short Term Memory (LSTM) Artificial Neural Network (ANN) to assist the aforesaid decision-making process. The Kotmale reservoir, which is the uppermost reservoir in the Mahaweli reservoir complex in Sri Lanka, was used as the test bed for this research. The ANN uses the runoff in the Kotmale reservoir catchment area and the effect of Sea Surface Temperatures (SST) to make a forecast for seven days ahead. Three types of ANN are tested; Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), and LSTM. The extensive field trials and validation endeavors found that the LSTM ANN provides superior performance in the aspects of accuracy and latency.

Keywords: convolutional neural network, CNN, inflow, long short-term memory, LSTM, multi-layer perceptron, MLP, neural network

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Authors: Sanjay Kumar

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This paper reports the solvent effects on the electronic absorption and fluorescence emission spectra of 6-OH-4-CH3, 7-OH-4-CH3 and 7-OH-4-CF3 coumarin derivatives having -OH, -CH3 and -CF3 substituent at different positions in various solvents (Polar and Non-Polar). The first excited singlet state dipole moment and ground state dipole moment were calculated using Bakhshiev, Kawski-Chamma-Viallet and Reichardt-Dimroth equations and were compared for all the coumarin studied. In all cases the dipole moments were found to be higher in the excited singlet state than in the ground state indicating a substantial redistribution of Π-electron density in the excited state. The angle between the excited singlet state and ground state dipole moment is also calculated. The red shift of the absorption and fluorescence emission bands, observed for all the coumarin studied upon increasing the solvent polarity indicating that the electronic transitions were Π → Π* nature.

Keywords: coumarin, solvent effects, absorption spectra, emission spectra, excited singlet state dipole moment, ground state dipole moment, solvatochromism

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Authors: Ajayi Oluwasola Felix

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This paper examines how firm investments in technology-based employee monitoring impact both misconduct and productivity. We use unique and detailed theft and sales data from 392 restaurant locations from five firms that adopt a theft monitoring information technology (IT) product. We use difference-in-differences (DD) models with staggered adoption dates to estimate the treatment effect of IT monitoring on theft and productivity. We find significant treatment effects in reduced theft and improved productivity that appear to be primarily driven by changed worker behavior rather than worker turnover. We examine four mechanisms that may drive this productivity result: economic and cognitive multitasking, fairness-based motivation, and perceived increases of general oversight. The observed productivity results represent substantial financial benefits to both firms and the legitimate tip-based earnings of workers. Our results suggest that employee misconduct is not solely a function of individual differences in ethics or morality, but can also be influenced by managerial policies that can benefit both firms and employees.

Keywords: information technology, monitoring, misconduct, employee theft

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Authors: Gohar Rahman, Rabia Saad Ullah

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This research aims to examine the use of discourse markers within the dominion of political speeches, differentiating between genders. The analysis centers on twelve speakers, comprising six males and six females. Speeches selected include commencement, victory, state union addresses, campaigns, and presidential speeches. Halliday and Hasan's cohesion framework, specifically discourse markers, is utilized as a theoretical framework. Data is quantitatively analyzed using AntConc to identify marker frequency. The findings are presented through Excel's tables and graphs, suggesting differences in discourse marker preferences between genders. The findings suggest a divergence in the preferences for discourse markers between males and females. However, asserting that females utilize discourse markers more frequently due to the increased use of filler words, face threat mitigation, and polite speech would be an exaggeration. The disparity in frequency is not substantial, suggesting that males and females exhibit varying language inclinations to some degree.

Keywords: discourse markers, political discourse, gender, speeches, language

Procedia PDF Downloads 39

Authors: Yasser M. Saad, Amr A. El Hanafy, Saleh A. Alkarim, Hussein A. Almehdar, Elrashdy M. Redwan

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Camels are substantial providers of transport, milk, sport, meat, shelter, security and capital in many countries, particularly in Saudi Arabia. Inter simple sequence repeat technique was used to detect the genetic variations among some camel breeds (Majaheim, Safra, Wadah, and Hamara). Actual number of alleles, effective number of alleles, gene diversity, Shannon’s information index and polymorphic bands were calculated for each evaluated camel breed. Neighbor-joining tree that re-constructed for evaluated these camel breeds showed that, Hamara breed is distantly related from the other evaluated camels. In addition, the polymorphic sites, haplotypes and nucleotide diversity were identified for some camelidae cox1 gene sequences (obtained from NCBI). The distance value between C. bactrianus and C. dromedarius (0.072) was relatively low. Analysis of genetic diversity is an important way for conserving Camelus dromedarius genetic resources.

Keywords: camel, genetics, ISSR, neighbor-joining

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Authors: Zhenhua Wei, Gabriel Falzone, Bu Wang, Laurent Pilon, Gaurav Sant

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The production of ordinary Portland cement (OPC) is a CO₂ intensive process. Specifically, cement clinkering reactions require not only substantial energy in the form of heat, but also result in the release of CO₂, from limestone decarbonation and the combustion of fuel. To overcome this CO₂ intensive process, clinkering-free cementation is demonstrated by the carbonation of fly ash; i.e., a by-product of coal combustion. It is shown that in moist environments and at sub-boiling temperatures, calcium-rich fly ashes readily react with gas-phase CO₂ to provide cementation. After seven days of CO₂ exposure at 75°C, such formulations achieve a compressive strength on the order of 35 MPa and take-up 9% CO₂ (by mass of the solid). On the other hand, calcium-deficient fly ashes, due to their lack of alkalinity (i.e., abundance of mobile Ca or Mg), show little if any potential for CO₂ uptake and strength gain. The role of the CO₂ concentration and processing temperature are discussed and linked to the progress of reactions, and the development of microstructure. The outcomes demonstrate a means for enabling clinkering-free cementation while enabling beneficial utilization of CO₂ and fly ash; i.e., two abundant but underutilized industrial by-products.

Keywords: fly ash, carbonation, concrete, strength

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Authors: Manit Pollar

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Identifying the dengue epidemic periods early would be helpful to take necessary actions to prevent the dengue outbreaks. Providing an accurate prediction on dengue epidemic seasons will allow sufficient time to take the necessary decisions and actions to safeguard the situation for local authorities. This study aimed to develop a forecasting model on number of dengue incidences in Nakhon Si Thammarat Province, Southern Thailand using time series analysis. We develop Seasonal Autoregressive Moving Average (SARIMA) models on the monthly data collected between 2003-2011 and validated the models using data collected between January-September 2012. The result of this study revealed that the SARIMA(1,1,0)(1,2,1)12 model closely described the trends and seasons of dengue incidence and confirmed the existence of dengue fever cases in Nakhon Si Thammarat for the years between 2003-2011. The study showed that the one-step approach for predicting dengue incidences provided significantly more accurate predictions than the twelve-step approach. The model, even if based purely on statistical data analysis, can provide a useful basis for allocation of resources for disease prevention.

Keywords: SARIMA, time series model, dengue cases, Thailand

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Authors: Jun Wang, Ge Zhang

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Machine learning has been used in many areas today. It thrives at reviewing large volumes of data and identifying patterns and trends that might not be apparent to a human. Given the huge potential benefit and the amount of data available in the financial market, it is not surprising to see machine learning applied to various financial products. While future prices of financial securities are extremely difficult to forecast, we study them from a different angle. Instead of trying to forecast future prices, we apply machine learning algorithms to predict the direction of future price movement, in particular, whether a sector Exchange Traded Fund (ETF) would outperform or underperform the market in the next week or in the next month. We apply several machine learning algorithms for this prediction. The algorithms are Linear Discriminant Analysis (LDA), k-Nearest Neighbors (KNN), Decision Tree (DT), Gaussian Naive Bayes (GNB), and Neural Networks (NN). We show that these machine learning algorithms, most notably GNB and NN, have some predictive power in forecasting out-performance and under-performance out of sample. We also try to explore whether it is possible to utilize the predictions from these algorithms to outperform the buy-and-hold strategy of the S&P 500 index. The trading strategy to explore out-performance predictions does not perform very well, but the trading strategy to explore under-performance predictions can earn higher returns than simply holding the S&P 500 index out of sample.

Keywords: machine learning, ETF prediction, dynamic trading, asset allocation

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Authors: Mohamed Shaban, Adel Yahya

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The goal of this paper study is to schedule the power generation units to minimize fuel consumption cost based on a model that solves unit commitment problems. This can be done by utilizing forward dynamic programming method to determine the most economic scheduling of generating units. The model was applied to a power station, which consists of four generating units. The obtained results show that the applications of forward dynamic programming method offer a substantial reduction in fuel consumption cost. The fuel consumption cost has been reduced from $116,326 to $102,181 within a 24-hour period. This means saving about 12.16 % of fuel consumption cost. The study emphasizes the importance of applying modeling schedule programs to the operation of power generation units. As a consequence less consumption of fuel, less loss of power and less pollution

Keywords: unit commitment, forward dynamic, fuel cost, programming, generation scheduling, operation cost, power system, generating units

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Authors: Zainal Abu Zatim, Hafizah Omar Zaki

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Substantial research had been done on refining employee’s customer service performance. Thus, there were very limited empirical studies that are engage in an inter-organizational climate study in assessing employee’s customer service performance. With the current economic situation as well as emerging needs and requirements, all businesses either from public or private sector serving customers put greater attention on fulfilling those needs and requirements. In this state of affairs, the act of polishing its employees’ skills, knowledge, teamwork and passion is very important in ensuring better performance deliverance. A study conducted in one of the telecommunication service provider company in Malaysia had been done to test its inter-organizational climate study. The Internal Climate Study was done to benchmark opinions and perceptions of its employees. The study had provided baseline information about perceptions that exist in the internal environment and ways forward to improve customer service performance. The approach used is through the use of focus group and qualitative interview.

Keywords: employees, Customer Service Performance, inter-organizational climate study, public and private sector

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Authors: Sennanda Musa, Ahmed Mutunzi Kitunzi, Gerald Kasigwa, Ismail Kintu

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This paper is an analysis of the empirical relationship between project financing by Islamic Development Bank (IsDB) and the poverty trends in the context of countries benefiting from IsDB. Specifically, the study seeks to find out whether there is a statistically significant relationship between the project financing dollar amounts by IsDB (PF) and the GNI Per Capita, PPP of 57 countries for the years 2002 to 2021. The research is a longitudinal, desk-top triangulation of correlation, regression, hypothesis-testing employing the linear dynamic panel data GMM model as an estimator of the empirical relationships between the key variables of the study. The study results show that there is a significant positive relationship between the PF dollar amounts from the IsDB and the GNI Per Capita, PPP in these 57 countries. Therefore, countries that receive higher PF dollar amounts from the IsDB, generally have more GNI Per Capita, PPP (less poverty) than their counterparts. It is, therefore, recommendable for countries to formulate policies that facilitate Islamically financed projects to mitigate poverty. This paper develops policy discussions regarding allocation of political attention to the policy topics on poverty mitigation, and their relation to financing projects Islamically, thus generate information on policy choices regarding the Islamic financing alternative.

Keywords: gross-national-income, IsDB-project-financing, public policy, poverty

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Authors: Ursula Das, Manavjit Singh Dhindsa, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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Wildland fires, also known as forest fires or wildfires, are exhibiting an alarming surge in frequency in recent times, further adding to its perennial global concern. Forest fires often lead to devastating consequences ranging from loss of healthy forest foliage and wildlife to substantial economic losses and the tragic loss of human lives. Despite the existence of substantial literature on the detection of active forest fires, numerous potential research avenues in forest fire management, such as preventative measures and ancillary effects of forest fires, remain largely underexplored. This paper undertakes a systematic review of these underexplored areas in forest fire research, meticulously categorizing them into distinct phases, namely pre-fire, during-fire, and post-fire stages. The pre-fire phase encompasses the assessment of fire risk, analysis of fuel properties, and other activities aimed at preventing or reducing the risk of forest fires. The during-fire phase includes activities aimed at reducing the impact of active forest fires, such as the detection and localization of active fires, optimization of wildfire suppression methods, and prediction of the behavior of active fires. The post-fire phase involves analyzing the impact of forest fires on various aspects, such as the extent of damage in forest areas, post-fire regeneration of forests, impact on wildlife, economic losses, and health impacts from byproducts produced during burning. A comprehensive understanding of the three stages is imperative for effective forest fire management and mitigation of the impact of forest fires on both ecological systems and human well-being. Artificial intelligence and machine learning (AI/ML) methods have garnered much attention in the cyber-physical systems domain in recent times leading to their adoption in decision-making in diverse applications including disaster management. This paper explores the current state of AI/ML applications for managing the activities in the aforementioned phases of forest fire. While conventional machine learning and deep learning methods have been extensively explored for the prevention, detection, and management of forest fires, a systematic classification of these methods into distinct AI research domains is conspicuously absent. This paper gives a comprehensive overview of the state of forest fire research across more recent and prominent AI/ML disciplines, including big data, classical machine learning, computer vision, explainable AI, generative AI, natural language processing, optimization algorithms, and time series forecasting. By providing a detailed overview of the potential areas of research and identifying the diverse ways AI/ML can be employed in forest fire research, this paper aims to serve as a roadmap for future investigations in this domain.

Keywords: artificial intelligence, computer vision, deep learning, during-fire activities, forest fire management, machine learning, pre-fire activities, post-fire activities

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Authors: Patricia P. M. C. Lourenco, Javier Bringué Sala, Anaisa D. A. de Sena

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Almost everyone in Dramaland knows the names of big Korean stars that grace their computer screens on a roll through social media and video streaming platforms that enable awareness of Korean dramas and lifestyle at a click. A surface culture instilled with notions of belonging has redefined the meaning of friendship and challenged deep inner values. Not everyone, however, knows Chinese Dramas or their stars, which is a consequence of Dramaland's focus on Korean dramas and promoting the Korean experience. Despite a parity in terms of production quality, star power, scripts and compelling visual settings, Chinese Dramas have been playing catch up to their famous counterparts. While they might have a strong competitive soft power for international drama fans, the soft power of Korean dramas is imbued with substantial societal values that they want to share with others. Those values are portrayed in an artistic way that connects with audiences who experience loneliness in the non-virtual world contrary to the way Chinese Dramas are perceived.

Keywords: Chinese dramas, fandom, Korean dramas, participatory culture, value perception, soft power, surface culture

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Authors: Aditi Viswanathan, Shree Ranjani, Aruna Govada

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With data sizes constantly expanding, and with classical machine learning algorithms that analyze such data requiring larger and larger amounts of computation time and storage space, the need to distribute computation and memory requirements among several computers has become apparent. Although substantial work has been done in developing distributed binary SVM algorithms and multi-class SVM algorithms individually, the field of multi-class distributed SVMs remains largely unexplored. This research seeks to develop an algorithm that implements the Support Vector Machine over a multi-class data set and is efficient in a distributed environment. For this, we recursively choose the best binary split of a set of classes using a greedy technique. Much like the divide and conquer approach. Our algorithm has shown better computation time during the testing phase than the traditional sequential SVM methods (One vs. One, One vs. Rest) and out-performs them as the size of the data set grows. This approach also classifies the data with higher accuracy than the traditional multi-class algorithms.

Keywords: distributed algorithm, MapReduce, multi-class, support vector machine

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Authors: Dhananjoy Dutta

Abstract:

Field studies in lower Gangetic plains of India reveal that over-abstraction of groundwater for irrigation to paddy leads to a substantial depletion of groundwater over the decades, resulting in negative effects on lowering of the water table, drying up of surface water sources and aquifer pollution with leached-out arsenic. The aggravating arsenic toxicity in drinking water is manifested in health problems and ‘arsenicosis’ of people. A social conflict arises between farmers, who intend to grow paddy for livelihoods, and the groundwater authority, which enacts the ‘Regulation Laws’ by putting a check on the excessive installation of private tube wells for irrigation. Hence, considering the challenges of resource sustainability, health issues and food security, the study calls for a paradigm shift in policy from further groundwater development to sustainable water resources management and evaluates some strategies integrating supply and demand side management for mitigating the problems.

Keywords: groundwater, irrigation, paddy farming, water table depletion, arsenic pollution, gangetic plains

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Authors: Vivek Hokam, Vishrut Landge

Abstract:

An ideal maintenance program for an industrial road network is one that would maintain all sections at a sufficiently high level of functional and structural conditions. However, due to various constraints such as budget, manpower and equipment, it is not possible to carry out maintenance on all the needy industrial road sections within a given planning period. A rational and systematic priority scheme needs to be employed to select and schedule industrial road sections for maintenance. Priority analysis is a multi-criteria process that determines the best ranking list of sections for maintenance based on several factors. In priority setting, difficult decisions are required to be made for selection of sections for maintenance. It is more important to repair a section with poor functional conditions which includes uncomfortable ride etc. or poor structural conditions i.e. sections those are in danger of becoming structurally unsound. It would seem therefore that any rational priority setting approach must consider the relative importance of functional and structural condition of the section. The maintenance priority index and pavement performance models tend to focus mainly on the pavement condition, traffic criteria etc. There is a need to develop the model which is suitably used with respect to limited budget provisions for maintenance of pavement. Linear programming is one of the most popular and widely used quantitative techniques. A linear programming model provides an efficient method for determining an optimal decision chosen from a large number of possible decisions. The optimum decision is one that meets a specified objective of management, subject to various constraints and restrictions. The objective is mainly minimization of maintenance cost of roads in industrial area. In order to determine the objective function for analysis of distress model it is necessary to fix the realistic data into a formulation. Each type of repair is to be quantified in a number of stretches by considering 1000 m as one stretch. A stretch considered under study is having 3750 m length. The quantity has to be put into an objective function for maximizing the number of repairs in a stretch related to quantity. The distress observed in this stretch are potholes, surface cracks, rutting and ravelling. The distress data is measured manually by observing each distress level on a stretch of 1000 m. The maintenance and rehabilitation measured that are followed currently are based on subjective judgments. Hence, there is a need to adopt a scientific approach in order to effectively use the limited resources. It is also necessary to determine the pavement performance and deterioration prediction relationship with more accurate and economic benefits of road networks with respect to vehicle operating cost. The infrastructure of road network should have best results expected from available funds. In this paper objective function for distress model is determined by linear programming and deterioration model considering overloading is discussed.

Keywords: budget, maintenance, deterioration, priority

Procedia PDF Downloads 179

Authors: V. S. S. Kumar, B. Vikram

Abstract:

The development of effective decision support tools that adopted in the construction industry is vital in the world we live in today, since it can lead to substantial cost reduction and efficient resource consumption. Solving the time-cost trade off problems and its related variants is at the heart of scientific research for optimizing construction planning problems. In general, the classical optimization techniques have difficulties in dealing with TCT problems. One of the main reasons of their failure is that they can easily be entrapped in local minima. This paper presents an investigation on the application of meta-heuristic techniques to two particular variants of the time-cost trade of analysis, the time-cost trade off problem (TCT), and time-cost trade off optimization problem (TCO). In first problem, the total project cost should be minimized, and in the second problem, the total project cost and total project duration should be minimized simultaneously. Finally it is expected that, the optimization models developed in this paper will contribute significantly for efficient planning and management of construction project.

Keywords: fuzzy sets, uncertainty, optimization, time cost trade off problems

Procedia PDF Downloads 334

Authors: Nafe Moradkhani, Frederick Benaben, Benoit Montreuil, Ali Vatankhah Barenji, Dima Nazzal

Abstract:

In the context of the global pandemic, the practical management of the 2020 presidential election in the USA was a strong concern. To anticipate and prepare for this election accurately, one of the main challenges was to confront (i) forecasts of voter turnout, (ii) capacities of the facilities and, (iii) potential configuration options of resources. The approach chosen to conduct this anticipative study consists of collecting data about forecasts and using simulation models to work simultaneously on resource allocation and facility configuration of polling places in Fulton County, Georgia’s largest county. A polling place is a dedicated facility where voters cast their ballots in elections using different devices. This article presents the results of the simulations of such places facing pre-identified potential risks. These results are oriented towards the efficiency of these places according to different criteria (health, trust, comfort). Then a dynamic framework is introduced to describe risks as physical forces perturbing the efficiency of the observed system. Finally, the main benefits and contributions resulting from this simulation campaign are presented.

Keywords: performance, decision support, simulation, artificial intelligence, risk management, election, pandemics, information system

Procedia PDF Downloads 128