Search results for: operation costs

Authors: Riyad Awad, Abdulmohsen Alghadeer, Meshari Otaibi

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Proper operation and maintenance (O&M) activities of high voltage equipment can lead to an increased asset lifecycle and maintain its integrity and reliability. Such a vital process is important to be proactively considered during equipment design and manufacturing phases by removing and eliminating any obstacles in the equipment which adversely affect the (O&M) activities. This paper presents a gap analysis pertaining to difficulties in performing operations and maintenance (O&M) high voltage electrical equipment, includes power transformers, switch gears, motor control center, disconnect switches and circuit breakers. The difficulties are gathered from field personnel, equipment design review comments, quality management system, and lessons learned database. The purpose of the gap analysis is to mitigate and prevent the (O&M) difficulties as early as possible in the design stage of the equipment lifecycle. The paper concludes with several recommendations and corrective actions for all identified gaps in order to reduce the cost (O&M) difficulties and improve the equipment lifecycle.

Keywords: operation and maintenance, high voltage equipment, equipment lifecycle, reduce the cost of maintenance

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Authors: E. V. Kuzmicheva

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An attention is concentrated on a service quality estimation of sport services. A typical mathematical model was developed at the base of the «general economic theory of mass service» accounting pedagogical requirements of fitness services. Also it took into account a dependence of the club member number versus on a value of square of sport facilities. Final recommendations were applied to the fitness club resulted in some improvement of the quality sport service, an increasing of the revenue from club members and profit of clubs.

Keywords: fitness club, efficiency of operation, facilities, service quality, mass service

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Authors: Hossein Havaeji, Tony Wong, Thien-My Dao

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1. Research Problems and Research Objectives: Blockchain Technology-enabled Supply Chain System (BT-enabled SCS) is the system using BT to drive SCS transparency, security, durability, and process integrity as SCS data is not always visible, available, or trusted. The costs of operating BT in the SCS are a common problem in several organizations. The costs must be estimated as they can impact existing cost control strategies. To account for system and deployment costs, it is necessary to overcome the following hurdle. The problem is that the costs of developing and running a BT in SCS are not yet clear in most cases. Many industries aiming to use BT have special attention to the importance of BT installation cost which has a direct impact on the total costs of SCS. Predicting BT installation cost in SCS may help managers decide whether BT is to be an economic advantage. The purpose of the research is to identify some main BT installation cost components in SCS needed for deeper cost analysis. We then identify and categorize the main groups of cost components in more detail to utilize them in the prediction process. The second objective is to determine the suitable Supervised Learning technique in order to predict the costs of developing and running BT in SCS in a particular case study. The last aim is to investigate how the running BT cost can be involved in the total cost of SCS. 2. Work Performed: Applied successfully in various fields, Supervised Learning is a method to set the data frame, treat the data, and train/practice the method sort. It is a learning model directed to make predictions of an outcome measurement based on a set of unforeseen input data. The following steps must be conducted to search for the objectives of our subject. The first step is to make a literature review to identify the different cost components of BT installation in SCS. Based on the literature review, we should choose some Supervised Learning methods which are suitable for BT installation cost prediction in SCS. According to the literature review, some Supervised Learning algorithms which provide us with a powerful tool to classify BT installation components and predict BT installation cost are the Support Vector Regression (SVR) algorithm, Back Propagation (BP) neural network, and Artificial Neural Network (ANN). Choosing a case study to feed data into the models comes into the third step. Finally, we will propose the best predictive performance to find the minimum BT installation costs in SCS. 3. Expected Results and Conclusion: This study tends to propose a cost prediction of BT installation in SCS with the help of Supervised Learning algorithms. At first attempt, we will select a case study in the field of BT-enabled SCS, and then use some Supervised Learning algorithms to predict BT installation cost in SCS. We continue to find the best predictive performance for developing and running BT in SCS. Finally, the paper will be presented at the conference.

Keywords: blockchain technology, blockchain technology-enabled supply chain system, installation cost, supervised learning

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Authors: Frantisek Bozek, Pavel Budinsky, Ignac Hoza, Alexandr Bozek, Magdalena Naplavova

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A cleaner production project was implemented in a bakery. The project is based on the substitution of the best available technique for an obsolete leaven production technology. The new technology enables production of durable, high-quality leavens. Moreover, 25% of flour as the original raw material can be replaced by pastry from the previous day production which has not been sold. That pastry was previously disposed in a waste incineration plant. Besides the environmental benefits resulting from less waste, lower consumption of energy, reduction of sewage waters quantity and floury dustiness there are also significant economic benefits. Payback period of investment was calculated with help of static method of financial analysis about 2.6 years, using dynamic method 3.5 years and an internal rate of return more than 29%. The supposed annual average profit after taxation in the second year of operation was incompliance with the real profit.

Keywords: bakery, best available technology, cleaner production, costs, economic benefit, efficiency, energy, environmental benefit, investment, savings

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Authors: Debi Konukcu Onal, Tarkan Cavusoglu

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In modern societies, the costs of public goods and services are shared through taxes paid by citizens. However, taxation has always been a frictional issue, as tax obligations are perceived to be a financial burden for taxpayers rather than being merit that fulfills the redistribution, regulation and stabilization functions of the welfare state. The tax compliance literature evolves into discussing why people still pay taxes in systems with low costs of legal enforcement. Related empirical and theoretical works show that a wide range of socially oriented behavioral factors can stimulate voluntary compliance and subversive effects as well. These behavioral motivations are argued to be driven by self-enforcing rules of informal institutions, either independently or through interactions with legal orders set by formal institutions. The main focus of this study is to investigate empirically whether institutional particularities have a significant role in explaining the cross-country differences in the tax noncompliance levels. A part of the controversy about the driving forces behind tax noncompliance may be attributed to the lack of empirical evidence. Thus, this study aims to fill this gap through regression estimates, which help to trace the link between institutional quality and noncompliance on a cross-country basis. Tax evasion estimates of Buehn and Schneider is used as the proxy measure for the tax noncompliance levels. Institutional quality is quantified by three different indicators (percentile ranks of Worldwide Governance Indicators, ratings of the International Country Risk Guide, and the country ratings of the Freedom in the World). Robust Least Squares and Threshold Regression estimates based on the sample of the Organization for Economic Co-operation and Development (OECD) countries imply that tax compliance increases with institutional quality. Moreover, a threshold-based asymmetry is detected in the effect of institutional quality on tax noncompliance. That is, the negative effects of tax burdens on compliance are found to be more pronounced in countries with institutional quality below a certain threshold. These findings are robust to all alternative indicators of institutional quality, supporting the significant interaction of societal values with the individual taxpayer decisions.

Keywords: institutional quality, OECD economies, tax compliance, tax evasion

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Authors: Hung-Chi Chang

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For an extended EPQ model with random yield, the existent study revealed that both the disaggregating and consolidating shipment policies for the imperfect quality items are independent of holding cost, and recommended a model with economic benefit by comparing the least total cost for each of the three models investigated. To better capture the real situation, we generalize the existent study to include different holding costs for perfect and imperfect quality items. Through analysis, we show that the above shipment policies are dependent on holding costs. Furthermore, we derive a simple decision rule solely based on the thresholds of problem parameters to select a superior model. The results are illustrated analytically and numerically.

Keywords: consolidating shipments, disaggregating shipments, EPQ, imperfect quality, inventory

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Authors: Chrysi K. Nikoloutsou, Gianna Th. Siapati

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The pandemic limitations have altered architectural education as the discourse shifted towards virtual studios and blended learning. In addition, lockdown conditions and remote working have affected habitation. Adaptability is now a key factor. The architectural studio needs to adjust to these new terms both in education and in inhabitation. This paper will investigate the operation of an architectural studio in relation to how one experiences their house due to the pandemic, based on a literature review and qualitative research methods (interviews & workshops with students). Zenetos’ prophetic ideas of ‘Electronic Urbanism’ and ‘tele-activities’ are now more present than ever.

Keywords: architectural education, pandemic, residential design, studio pedagogy

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Authors: Awa Diouf

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Since 2004, inputs specific to the agricultural sector have been exempt from VAT in Senegal. This paper measures, using the Naatal Mbay survey, the impact of this reform on agricultural productivity. The survey covers a sample of 3,122 rice, millet and maize farms for the 2016 crop year. The regressions show that tax incentives are ineffective in improving partial productivity of the land factor: the higher the share of the value of exemptions in the higher the production costs, the less productive the operation. The negative effect of the exemptions on productivity is accentuated for the most intensive agricultural area: the Senegal River Delta, and the most intensive crop: irrigated rice. This relationship could stem from a decrease in allocative efficiency: farmers have overinvested in the most accessible inputs. The loose budget constraint syndrome, therefore, explains this result: farmers who benefit more from exemptions reduce their managerial effort. The results suggest a removal of the VAT exemptions applied to finished products and agricultural inputs for a better efficiency of this tax, which typically taxes final consumption and should be neutral for the producer.

Keywords: agricultural productivity, agricultural taxation, Senegal, tax incentives

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Authors: Jovian Cheung, Thomas Kwok, Victor Wong

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Buildings are entwined with smart city developments. Building performance relies heavily on electrical and mechanical (E&M) systems and services accounting for about 40 percent of global energy use. By cohering the advancement of technology as well as energy and operation-efficient initiatives into the buildings, people are enabled to raise building performance and enhance the sustainability of the built environment in their daily lives. Digital transformation in the buildings is the profound development of the city to leverage the changes and opportunities of digital technologies To optimize the building performance, intelligent power quality and energy management system is developed for transforming data into actions. The system is formed by interfacing and integrating legacy metering and internet of things technologies in the building and applying big data techniques. It provides operation and energy profile and actionable insights of a building, which enables to optimize the building performance through raising people awareness on E&M services and energy consumption, predicting the operation of E&M systems, benchmarking the building performance, and prioritizing assets and energy management opportunities. The intelligent power quality and energy management system comprises four elements, namely the Integrated Building Performance Map, Building Performance Dashboard, Power Quality Analysis, and Energy Performance Analysis. It provides predictive operation sequence of E&M systems response to the built environment and building activities. The system collects the live operating conditions of E&M systems over time to identify abnormal system performance, predict failure trends and alert users before anticipating system failure. The actionable insights collected can also be used for system design enhancement in future. This paper will illustrate how intelligent power quality and energy management system provides operation and energy profile to optimize the building performance and actionable insights to revitalize an existing building into a smart building. The system is driving building performance optimization and supporting in developing Hong Kong into a suitable smart city to be admired.

Keywords: intelligent buildings, internet of things technologies, big data analytics, predictive operation and maintenance, building performance

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Authors: Amin Ebrahimi Ghadi, Morteza Moalagh

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This research is carried out to find how a perfect combination of IoT architecture (Internet of Things) and ERP system can strengthen environmental accounting to incorporate both economic and environmental information. IoT (e.g., sensors, software, and other technologies) can be used in the company’s value chain from raw material extraction through materials processing, manufacturing products, distribution, use, repair, maintenance, and disposal or recycling products (Cradle to Grave model). The desired ERP software then will have the capability to track both midpoint and endpoint environmental impacts on a green supply chain system for the whole life cycle of a product. All these enable environmental accounting to calculate, and real-time analyze the operation environmental impacts, control costs, prepare for environmental legislation and enhance the decision-making process. In this study, we have developed a model on how to use IoT devices in life cycle assessment (LCA) to gather emissions, energy consumption, hazards, and wastes information to be processed in different modules of ERP systems in an integrated way for using in environmental accounting to achieve sustainability.

Keywords: ERP, environmental accounting, green supply chain, IOT, life cycle assessment, sustainability

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Authors: Zerzouri Nora

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In this paper, author presented the generalities of a photovoltaic system study and simulation. Author inserted the DC-DC converter to raise the voltage level and improve the operation of the PV panel by continuing the operating point at maximum power by using the Perturb and Observe technique (P&O). The connection to the network is made by inserting a three-phase voltage inverter allowing synchronization with the network the inverter is controlled by a PWM control. The simulation results allow the author to visualize the operation of the different components of the system, as well as the behavior of the system during the variation of meteorological values.

Keywords: photovoltaic generator PV, boost converter, P&O MPPT, PWM inverter, three phase grid

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Authors: Mohammed Saeed Jawad

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Metaverse involves the convergence of three major technologies trends of AI, VR, and AR. Together these three technologies can provide an entirely new channel for delivering healthcare with great potential to lower costs and improve patient outcomes on a larger scale. Telepresence is the technology that allows people to be together even if they are physically apart. Medical doctors can be symbolic as interactive avatars developed to have smart conversations and medical recommendations for patients at the different stages of the treatment. Medical digital assets such as Medical IoT for real-time remote healthcare monitoring as well as the symbolic doctors’ avatars as well as the hospital and clinical physical constructions and layout can be immersed in extended realities 3D metaverse environments where doctors, nurses, and patients can interact and socialized with the related digital assets that facilitate the data analytics of the sensed and collected personal medical data with visualized interaction of the digital twin of the patient’s body as well as the medical doctors' smart conversation and consultation or even in a guided remote-surgery operation.

Keywords: personal healthcare, metaverse, telemedicine, telepresence, avatar, medical consultation, remote-surgery

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Authors: Dhaksha Vivekanandan

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DeFi is a network that avoids reliance on financial intermediaries through its peer-to-peer financial network. DeFi operates outside of government control; hence it is important for us to understand its impacts. This study employs a literature review to understand DeFi and its emergence, as well as its implications on transparency, social impact, and regulation. Further, 3 case studies are analysed within the context of these categories. DeFi’s provision of increased transparency poses environmental and storage costs and can lead to user privacy being endangered. DeFi allows for the provision of entrepreneurial incentives and protection against monetary censorship and capital control. Despite DeFi's transparency issues and volatility costs, it has huge potential to reduce poverty; however, regulation surrounding DeFi still requires further tightening by governments.

Keywords: DeFi, transparency, regulation, social impact

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Authors: K. Bourouni, M. Chacha, T. Jaber, A. Tchantchane

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In Multi-Effect Distillation (MED) desalination evaporators, the scale deposit outside the tubes presents a barrier to heat transfers reducing the global heat transfer coefficient and causing a decrease in water production; hence a loss of efficiency and an increase in operating and maintenance costs. Scale removal (by acid cleaning) is the main maintenance operation and constitutes the major reason for periodic plant shutdowns. A better understanding of scale deposition mechanisms will lead to an accurate determination of the variation of scale thickness around the tubes and an improved accuracy of the overall heat transfer coefficient calculation. In this paper, a coupled heat transfer-calcium carbonate scale deposition model on a horizontal tube bundle is presented. The developed tool is used to determine precisely the heat transfer area leading to a significant cost reduction for a given water production capacity. Simulations are carried to investigate the influence of different parameters such as water salinity, temperature, etc. on the heat transfer.

Keywords: multi-effect-evaporator, scale deposition, water desalination, heat transfer coefficient

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Authors: Samaniego Campoverde José Enrique, Rosero Muñoz Jorge Enrique, Luzcando Narea Lorena Elizabeth

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This paper presents a practical and theoretical model for the operation of the Tesla coil using digital signal processing. The research is based on the analysis of ten scientific papers exploring the development and operation of the Tesla coil. Starting from the Testa coil, several modifications were carried out on the Tesla coil, with the aim of amplifying the digital signal by making use of digital signal processing. To achieve this, an amplifier with a transistor and digital filters provided by MATLAB software were used, which were chosen according to the characteristics of the signals in question.

Keywords: tesla coil, digital signal process, equalizer, graphical environment

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Authors: Alpesh Adeshara, Rajendrasinh Jadeja, Praghnesh Bhatt

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Implementation of advanced technologies requires sophisticated instruments that deal with the operation, control, restoration and protection of rapidly growing power system network under normal and abnormal conditions. Presently, the applications of Phasor Measurement Unit (PMU) are widely found in real time operation, monitoring, controlling and analysis of power system network as it eliminates the various limitations of Supervisory Control and Data Acquisition System (SCADA) conventionally used in power system. The use of PMU data is very rapidly increasing its importance for online and offline analysis. Wide Area Measurement System (WAMS) is developed as new technology by use of multiple PMUs in power system. The present paper proposes a model of MATLAB based PMU using Discrete Fourier Transform (DFT) algorithm and evaluation of its operation under different contingencies. In this paper, PMU based two bus system having WAMS network is presented as a case study.

Keywords: GPS global positioning system, PMU phasor measurement system, WAMS wide area monitoring system, DFT, PDC

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Authors: Eduardo Rodrigues, Gisela Mendes, José M. Torres, José E. Sousa

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In the sequence of the liberalisation of the electricity sector a progressive engagement of consumers has been considered and targeted by sector regulatory policies. With the objective of promoting market competition while protecting consumers interests, by transferring some of the upstream benefits to the end users while reaching a fair distribution of system costs, different market models to value consumers’ demand flexibility at the energy community level are envisioned. Local Energy and Flexibility Markets (LEFM) involve stakeholders interested in providing or procure local flexibility for community, services and markets’ value. Under the scope of DOMINOES, a European research project supported by Horizon 2020, the local market concept developed is expected to: • Enable consumers/prosumers empowerment, by allowing them to value their demand flexibility and Distributed Energy Resources (DER); • Value local liquid flexibility to support innovative distribution grid management, e.g., local balancing and congestion management, voltage control and grid restoration; • Ease the wholesale market uptake of DER, namely small-scale flexible loads aggregation as Virtual Power Plants (VPPs), facilitating Demand Response (DR) service provision; • Optimise the management and local sharing of Renewable Energy Sources (RES) in Medium Voltage (MV) and Low Voltage (LV) grids, trough energy transactions within an energy community; • Enhance the development of energy markets through innovative business models, compatible with ongoing policy developments, that promote the easy access of retailers and other service providers to the local markets, allowing them to take advantage of communities’ flexibility to optimise their portfolio and subsequently their participation in external markets. The general concept proposed foresees a flow of market actions, technical validations, subsequent deliveries of energy and/or flexibility and balance settlements. Since the market operation should be dynamic and capable of addressing different requests, either prioritising balancing and prosumer services or system’s operation, direct procurement of flexibility within the local market must also be considered. This paper aims to highlight the research on the definition of suitable DR models to be used by the Distribution System Operator (DSO), in case of technical needs, and by the retailer, mainly for portfolio optimisation and solve unbalances. The models to be proposed and implemented within relevant smart distribution grid and microgrid validation environments, are focused on day-ahead and intraday operation scenarios, for predictive management and near-real-time control respectively under the DSO’s perspective. At local level, the DSO will be able to procure flexibility in advance to tackle different grid constrains (e.g., demand peaks, forecasted voltage and current problems and maintenance works), or during the operating day-to-day, to answer unpredictable constraints (e.g., outages, frequency deviations and voltage problems). Due to the inherent risks of their active market participation retailers may resort to DR models to manage their portfolio, by optimising their market actions and solve unbalances. The interaction among the market actors involved in the DR activation and in flexibility exchange is explained by a set of sequence diagrams for the DR modes of use from the DSO and the energy provider perspectives. • DR for DSO’s predictive management – before the operating day; • DR for DSO’s real-time control – during the operating day; • DR for retailer’s day-ahead operation; • DR for retailer’s intraday operation.

Keywords: demand response, energy communities, flexible demand, local energy and flexibility markets

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Authors: Margerita Topalli

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In this paper, we analyze the impact of corruption (business environment, informal payments and state capture), crime and tax time, on the enterprise's performance during economic transition in the Central and Eastern Europe and the role of privatization as a moderator. We examine this effect by comparing the performance of the privatized enterprises and the state-owned-enterprises, while controlling for various forms of selection bias. The present study is based on firm-level panel data collected by the BEEPS for 27 transition countries over 2002, 2005, 2007, and 2011. In addition to firm characteristics, BEEPS collects valuable survey information on different forms of corruption, crime, tax time and firm ownership. We estimate the impact of corruption, crime, tax time on the different performance measures (sales, productivity, employment, labor costs and material costs) of the enterprise, whereby we control for firm ownership, with a special focus on the role of the privatization as a moderator. It argues that in general terms, the privatization has positive effects on the performance of enterprises during transition, but these effects are significantly different, depending on the examined performance measure (sales, productivity, employment, labor costs and material costs). When the privatization is effective, the privatized enterprises show a considerable performance improvements, particularly in terms of revenue growth and productivity growth. It also argues that the effects of privatization are different depending on the types of owner (outsider or insider) to whom it gives control. The results show that privatization to insider owners has no significant performance effect.

Keywords: effects of privatization, enterprise performance, state capture, corruption, firm ownership, economic transition, Central and Eastern Europe

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Authors: Dmytro Symak

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Drying is a complex technologic, thermal and energy process. Energy cost of drying processes in many cases is the most costly stage of production, and can be over 50% of total costs. As we know, in Ukraine over 85% of Portland cement is produced moist, and the finished product energy costs make up to almost 60%. During the wet cement production, energy costs make up over 5500 kJ / kg of clinker, while during the dry only 3100 kJ / kg, that is, switching to a dry Portland cement will allow result into double cutting energy costs. Therefore, to study raw materials drying process in the manufacture of Portland cement is very actual task. The fine ferrous materials drying (small pyrites, red mud, clay Kyoko) is recommended to do by filtration method, that is one of the most intense. The essence of filtration method drying lies in heat agent filtering through a stationary layer of wet material, which is located on the perforated partition, in the "layer-dispersed material - perforated partition." For the optimum drying purposes, it is necessary to establish the dependence of pressure loss in the layer of dispersed material, and the values of heat and mass transfer, depending on the speed of the gas flow filtering. In our research, the experimentally determined pressure loss in the layer of dispersed material was generalized based on dimensionless complexes in the form and coefficients of heat exchange. We also determined the relation between the coefficients of mass and heat transfer. As a result of theoretic and experimental investigations, it was possible to develop a methodology for calculating the optimal parameters for the thermal agent and the main parameters for the filtration drying installation. The comparison of calculated by known operating expenses methods for the process of small pyrites drying in a rotating drum and filtration method shows to save up to 618 kWh per 1,000 kg of dry material and 700 kWh during filtration drying clay.

Keywords: drying, cement, heat and mass transfer, filtration method

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Authors: B. F. Nteumagne, E. Pindza, E. Mare

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We apply Lie symmetries analysis to price and hedge options in the fractional Brownian framework. The reputation of Lie groups is well spread in the area of Mathematical sciences and lately, in Finance. In the presence of transactions costs and under fractional Brownian motions, analytical solutions become difficult to obtain. Lie symmetries analysis allows us to simplify the problem and obtain new analytical solution. In this paper, we investigate the use of symmetries to reduce the partial differential equation obtained and obtain the analytical solution. We then proposed a hedging procedure and calibration technique for these types of options, and test the model on real market data. We show the robustness of our methodology by its application to the pricing of digital options.

Keywords: fractional brownian model, symmetry, transaction cost, option pricing

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Authors: Fatemeh Yazdanmehr, Iulian Nistor

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The scope of the current study is the evaluation of the electric field effect on electrostatic desalting mathematical modeling with laboratory data. This research study was focused on developing a model for an existing operation desalting unit of one of the Iranian heavy oil field with a 75 MBPD production capacity. The high temperature of inlet oil to dehydration unit reduces the oil recovery, so the mathematical modeling of desalter operation parameters is very significant. The existing production unit operating data has been used for the accuracy of the mathematical desalting plant model. The inlet oil temperature to desalter was decreased from 110 to 80°C, and the desalted electrical field was increased from 0.75 to 2.5 Kv/cm. The model result shows that the desalter parameter changes meet the water-oil specification and also the oil production and consequently annual income is increased. In addition to that, changing desalter operation conditions reduces environmental footprint because of flare gas reduction. Following to specify the accuracy of selected electrostatic desalter electrical field, laboratory data has been used. Experimental data are used to ensure the effect of electrical field change on desalter. Therefore, the lab test is done on a crude oil sample. The results include the dehydration efficiency in the presence of a demulsifier and under electrical field (0.75 Kv) conditions at various temperatures. Comparing lab experimental and electrostatic desalter mathematical model results shows 1-3 percent acceptable error which confirms the validity of desalter specification and operation conditions changes.

Keywords: desalter, electrical field, demulsification, mathematical modeling, water-oil separation

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Authors: Musoke Ivan, Birungi Racheal

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The construction trend is characterized by increased use of modern methods yet traditional methods are cheaper in terms of costs, in addition to the benefits it offers to the construction sector, like providing more jobs that could have been worked with the intensive machines. The purpose of this research was to assess the influence of using Traditional methods of construction (TMC) on the costs and quality of building structures and determine the different ways. Traditional methods of construction (TMC) can be applicable and integrated into the construction trend, and propose ways how this can be a success. The study adopted a quantitative method approach targeting various construction professionals like Architects, Quantity surveyors, Engineers, and Construction Managers. Questionnaires and analyses of literature were used to obtain research data and findings. Simple random sampling was used to select 40 construction professionals to which questionnaires were administered. The data was then analyzed using Microsoft Excel. The findings of the research indicate that Traditional methods of construction (TMCs) in Uganda are cheaper in terms of costs, but the quality is still low. This is attributed to a lack of skilled labour and efficient supervision while undertaking tasks leading to low quality. The study identifies strategies that would improve Traditional methods of construction (TMC), which include the employment of skilled manpower and effective supervision. It also identifies the need by stakeholders like the government, clients, and professionals to appreciate Traditional methods of construction (TMCs) and allow for a levelled ground for Traditional Methods of Construction and Modern methods of construction (MMCs).

Keywords: traditional methods of construction, integration, cost, quality

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Authors: E. Feizi Ashtiani, S. Jamshidi, M.H Niksokhan, A. Feizi Ashtiani

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Waste load allocation (WLA) policies may use multi-objective optimization methods to find the most appropriate and sustainable solutions. These usually intend to simultaneously minimize two criteria, total abatement costs (TC) and environmental violations (EV). If other criteria, such as inequity, need for minimization as well, it requires introducing more binary optimizations through different scenarios. In order to reduce the calculation steps, this study presents value index as an innovative decision making approach. Since the value index contains both the environmental violation and treatment costs, it can be maximized simultaneously with the equity index. It implies that the definition of different scenarios for environmental violations is no longer required. Furthermore, the solution is not necessarily the point with minimized total costs or environmental violations. This idea is testified for Haraz River, in north of Iran. Here, the dissolved oxygen (DO) level of river is simulated by Streeter-Phelps equation in MATLAB software. The WLA is determined for fish farms using multi-objective particle swarm optimization (MOPSO) in two scenarios. At first, the trade-off curves of TC-EV and TC-Inequity are plotted separately as the conventional approach. In the second, the Value-Equity curve is derived. The comparative results show that the solutions are in a similar range of inequity with lower total costs. This is due to the freedom of environmental violation attained in value index. As a result, the conventional approach can well be replaced by the value index particularly for problems optimizing these objectives. This reduces the process to achieve the best solutions and may find better classification for scenario definition. It is also concluded that decision makers are better to focus on value index and weighting its contents to find the most sustainable alternatives based on their requirements.

Keywords: waste load allocation (WLA), value index, multi objective particle swarm optimization (MOPSO), Haraz River, equity

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Authors: Zhao Tianxu, Cui Shumei

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This paper proposes a novel multiphase motor structure. The armature winding consists of several independent multiphase windings that have different rating rotate speed and power. Compared to conventional motor, the novel motor structure has more operation mode and fault tolerance mode, which makes it adapt to high-reliability requirement situation such as electric vehicle, aircraft and ship. Performance of novel motor structure varies with winding match. In order to find optimum control strategy, motor torque character, efficiency performance and fault tolerance ability under different operation mode are analyzed in this paper, and torque distribution strategy for efficiency optimization is proposed. Simulation analyze is taken and the result shows that proposed structure has the same efficiency on heavy load and higher efficiency on light load operation points, which expands high efficiency area of motor and cruise range of vehicle. The proposed structure can improve motor highest speed.

Keywords: multiphase motor, armature winding match, torque distribution strategy, efficiency

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Authors: Eyhab El-Kharashi, Maher El-Dessouki

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The paper is dedicated to precise assessment of the induction motor output energy during the unbalanced operation. Since many years ago and until now the voltage complex unbalance factor (CVUF) is used only to assess the output energy of the induction motor while this output energy for asymmetry supply voltage does not depend on the value of unbalanced voltage only but also on the machine parameters. The paper illustrates the variation of the two unbalance factors, complex voltage unbalance factor (CVUF) and impedance unbalance factor (IUF), with positive sequence voltage component, reveals that degree and manner of unbalance in supply voltage. From this point of view the paper delineates the current unbalance factor (CUF) to exactly reflect the output energy during unbalanced operation. The paper proceeds to illustrate the importance of using this factor in the multi-machine system to precise prediction of the output energy during the unbalanced operation. The use of the proposed unbalance factor (CUF) avoids the accumulation of the error due to more than one machine in the system which is expected if only the complex voltage unbalance factor (CVUF) is used.

Keywords: induction motor, electromagnetic torque, voltage unbalance, energy conversion

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Authors: Lundqvist M., Alwin J., Levin L-A.

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Background: Assistance dogs are dogs trained to assist persons with functional impairment or chronic diseases. The assistance dog concept includes different types: guide dogs, hearing dogs, and service dogs. The service dog can further be divided into subgroups of physical services dogs, diabetes alert dogs, and seizure alert dogs. To examine the long-term effects of health care interventions, both in terms of resource use and health outcomes, cost-effectiveness analyses can be conducted. This analysis can provide important input to decision-makers when setting priorities. Little is known when it comes to the cost-effectiveness of assistance dogs. The study aimed to assess the cost-effectiveness of certified service or hearing dogs in comparison to regular companion dogs. Methods: The main data source for the analysis was the “service and hearing dog project”. It was a longitudinal interventional study with a pre-post design that incorporated fifty-five owners and their dogs. Data on all relevant costs affected by the use of a service dog such as; municipal services, health care costs, costs of sick leave, and costs of informal care were collected. Health-related quality of life was measured with the standardized instrument EQ-5D-3L. A decision-analytic Markov model was constructed to conduct the cost-effectiveness analysis. Outcomes were estimated over a 10-year time horizon. The incremental cost-effectiveness ratio expressed as cost per gained quality-adjusted life year was the primary outcome. The analysis employed a societal perspective. Results: The result of the cost-effectiveness analysis showed that compared to a regular companion dog, a certified dog is cost-effective with both lower total costs [-32,000 USD] and more quality-adjusted life-years [0.17]. Also, we will present subgroup results analyzing the cost-effectiveness of physicals service dogs and diabetes alert dogs. Conclusions: The study shows that a certified dog is cost-effective in comparison with a regular companion dog for individuals with functional impairments or chronic diseases. Analyses of uncertainty imply that further studies are needed.

Keywords: service dogs, hearing dogs, health economics, Markov model, quality-adjusted, life years

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Authors: Lai Junzhe, Wang Lihao, Burra Venkata Durga Kumar

Abstract:

In recent years, due to today's global technological advances, big data and artificial intelligence technologies have been widely used in various industries and fields, playing an important role in reducing costs and increasing efficiency. Among them, artificial intelligence has derived another branch in its own continuous progress and the continuous development of computer personnel, namely distributed artificial intelligence computing systems. Distributed AI is a method for solving complex learning, decision-making, and planning problems, characterized by the ability to take advantage of large-scale computation and the spatial distribution of resources, and accordingly, it can handle problems with large data sets. Nowadays, distributed AI is widely used in military, medical, and human daily life and brings great convenience and efficient operation to life. In this paper, we will discuss three areas of distributed AI computing systems in vision processing, blockchain, and smart home to introduce the performance of distributed systems and the role of AI in distributed systems.

Keywords: distributed system, artificial intelligence, blockchain, IoT, visual information processing, smart home

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Authors: Mauricio Becerra Fernández, Olga Rosana Romero Quiroga, Elsa Cristina González La Rotta

Abstract:

The logistics facilities design and construction is one of the strategic decisions that critically affects the performance of the company, from the economic perspective and relationship with customers. The case study company is the Colombian logistic sector leader, with over 60 years of experience, with sales of about one hundred twenty million dollars at the end of 2014. The preliminary design for the warehouse layout and operation includes a customer that provides approximately 17% of the profits of the company, considering the possibility of moving two forklifts in the warehouse halls. Some changes were not consider in previous stages of design, operations required forklift with different characteristics, whose size, do not allow the circulation of more than a forklift at a time. Therefore, it is necessary to assess the impact of this restriction on the warehouse operation, so decision makers implement actions to achieve efficient operation. The problem is addressed by recognizing logistics processes, which develop in a warehouse, collection of processes information behavior, the simulation of the current situation using ProModel software, model validation, making adjustments required, experiments design, conclusions and recommendations for the company.

Keywords: design, discrete events simulation, forklift allocation, logistics facilities, warehouse

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Authors: Kazuaki Shiraishi, Narumitsu Asai, Tsukasa Kitahara, Sosuke Mieno, Takaharu Kameoka

Abstract:

The purpose of this research is to facilitate productivity advances in agriculture. To accomplish this, we developed an automatic three-dimensional (3D) recording system for growth of field crops that consists of a number of inexpensive modules: a very low-cost stereo camera, a couple of ZigBee wireless modules, a Raspberry Pi single-board computer, and a third generation (3G) wireless communication module. Our system uses an inexpensive Web stereo camera in order to keep total costs low. However, inexpensive video cameras record low-resolution images that are very noisy. Accordingly, in order to resolve these problems, we adopted a deep learning method. Based on the results of extended period of time operation test conducted without the use of an external power supply, we found that by using Super-Resolution Convolutional Neural Network method, our system could achieve a balance between the competing goals of low-cost and superior performance. Our experimental results showed the effectiveness of our system.

Keywords: 3D plant data, automatic recording, stereo camera, deep learning, image processing

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Authors: Teemu Saressalo

Abstract:

This article examines the evolution of the Israel Defence Forces’ information operation activities during an eight-year timespan from the 2006 war with Hezbollah to more recent operations such as Pillar of Defence and Protective Edge. To this end, the case study will show a change in the Israel Defence Forces’ activities in the information domain. In the 2006 war with Hezbollah in Lebanon, Israel inflicted enormous damage on the Lebanese infrastructure, leaving more than 1,200 people dead and 4,400 injured. Casualties among Hezbollah, Israel’s main adversary, were estimated to range from 250 to 700 fighters. Damage to the Lebanese infrastructure was estimated at over USD 2.5bn, with almost 2,000 houses and buildings damaged and destroyed. Even this amount of destruction did not force Hezbollah to yield and while both sides were claiming victory in the war, Israel paid a heavier price in political backlashes and loss of reputation, mainly due to failures in the media and the way in which the war was portrayed and perceived in Israel and abroad. Much of this can be credited to Hezbollah’s efficient use of the media, and Israel’s failure to do so. Israel managed the next conflict it was engaged in completely differently – it had learnt its lessons and built up new ways to counter its adversary’s propaganda and media operations. In Operation Cast Lead at the turn of 2009, Hamas, Israel’s adversary and Gaza’s dominating faction, was not able to utilize the media in the same way that Hezbollah had. By creating a virtual and physical barrier around the Gaza Strip, Israel almost totally denied its adversary access to the worldwide media, and by restricting the movement of journalists in the area, Israel could let its voice be heard above all. The operation Cast Lead began with a deception operation, which caught Hamas totally off guard. The 21-day campaign left the Gaza Strip devastated, but did not cause as much protest in Israel during the operation as the 2006 war did, mainly due to almost total Israeli dominance in the information dimension. The most important outcome from the Israeli perspective was the fact that Operation Cast Lead was assessed to be a success and the operation enjoyed domestic support along with support from many western nations, which had condemned Israeli actions in the 2006 war. Later conflicts have shown the same tendency towards virtually total dominance in the information domain, which has had an impact on target audiences across the world. Thus, it is clear that well-planned and conducted information operations are able to shape public opinion and influence decision-makers, although Israel might have been outpaced by its rivals.

Keywords: Hamas, Hezbollah, information operations, Israel Defence Forces

Procedia PDF Downloads 211