Search results for: optimal location

Authors: Miguel A. Orellana, Sonia E. Ruiz, Juan Bojórquez

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Optimal load factors (dead, live and seismic) used for the design of buildings may be different, depending of the seismic ground motion characteristics to which they are subjected, which are closely related to the type of soil conditions where the structures are located. The influence of the type of soil on those load factors, is analyzed in the present study. A methodology that is useful for establishing optimal load factors that minimize the cost over the life cycle of the structure is employed; and as a restriction, it is established that the probability of structural failure must be less than or equal to a prescribed value. The life-cycle cost model used here includes different types of costs. The optimization methodology is applied to two groups of reinforced concrete buildings. One set (consisting on 4-, 7-, and 10-story buildings) is located on firm ground (with a dominant period Ts=0.5 s) and the other (consisting on 6-, 12-, and 16-story buildings) on soft soil (Ts=1.5 s) of Mexico City. Each group of buildings is designed using different combinations of load factors. The statistics of the maximums inter-story drifts (associated with the structural capacity) are found by means of incremental dynamic analyses. The buildings located on firm zone are analyzed under the action of 10 strong seismic records, and those on soft zone, under 13 strong ground motions. All the motions correspond to seismic subduction events with magnitudes M=6.9. Then, the structural damage and the expected total costs, corresponding to each group of buildings, are estimated. It is concluded that the optimal load factors combination is different for the design of buildings located on firm ground than that for buildings located on soft soil.

Keywords: life-cycle cost, optimal load factors, reinforced concrete buildings, total costs, type of soil

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Authors: Norm Josephy, Lucy Kimball, Victoria Steblovskaya

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Hedging of a portfolio of European options under proportional transaction costs is considered. Our discrete time financial market model extends the binomial market model with transaction costs to the case where the underlying stock price ratios are distributed over a bounded interval rather than over a two-point set. An optimal hedging strategy is chosen from a set of admissible non-self-financing hedging strategies. Our approach to optimal hedging of a portfolio of options is based on theoretical foundation that includes determination of a no-arbitrage option price interval as well as on properties of the non-self-financing strategies and their residuals. A computational algorithm for optimizing an investor relevant criterion over the set of admissible non-self-financing hedging strategies is developed. Applicability of our approach is demonstrated using both simulated data and real market data.

Keywords: extended binomial model, non-self-financing hedging, optimization, proportional transaction costs

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Authors: Reza Bahboodian

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One of the most important factors in the use of construction machinery is the fuel consumption cost of this equipment. The use of diesel engines in off-road vehicles is an important source of nitrogen oxides and particulate matter. Emissions of nitrogen oxides and particulate matter 10 in off-road vehicles (construction and mining) may be high. Due to the high cost of fuel, it is necessary to minimize fuel consumption. Factors affecting the fuel consumption of these cars are very diverse. Climate changes such as changes in pressure, temperature, humidity, fuel type selection, type of gearbox used in the car are effective in fuel consumption and pollution, and engine efficiency. In this paper, methods for reducing fuel consumption and pollutants by considering valid European and European standards are examined based on new methods such as hybridization, optimal gear change, adding hydrogen to diesel fuel, determining optimal working fluids, and using oxidation catalysts.

Keywords: improve fuel consumption, construction machinery, pollutant reduction, determining the optimal working cycle

Procedia PDF Downloads 127

Authors: Umarov Jamshid, Ju-Su Kim, Hak-Jun Lee, Man-Kyo Han, Ryum-Duck Oh

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Recently, it becomes convenient to identify the location information of cargos by using GPS and wireless communication technologies. The development of IoT technologies and tracking system allows us to confirm site situation on an ad hoc basis in all the industries and social environments. Moreover, it allows us to apply IT technologies to a manageable extent. However, there have been many limitations for using the system due to the difficulty of identifying location information in real time and also due to the simple features. To globalize the logistics related tracking system, it is required to conduct a study to resolve the aforementioned problem. On that account, this paper designed and developed the IoT and RTLS based intelligent multi tracking agent system for more secure, accurate and reliable transportation in relation to logistics.

Keywords: GPS, tracking agent system, IoT, RTLS, Logistics

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Authors: Sunantha Teyarachakul

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We consider the worker-learning Newsvendor Model, under the case of lost-sales for unmet demand, with the research objective of proposing the cost-minimization order policy and lot size, scheduled to arrive at the beginning of the selling-period. In general, the New Vendor Model is used to find the optimal order quantity for the perishable items such as fashionable products or those with seasonal demand or short-life cycles. Technically, it is used when the product demand is stochastic and available for the single selling-season, and when there is only a one time opportunity for the vendor to purchase, with possibly of long ordering lead-times. Our work differs from the classical Newsvendor Model in that we incorporate the human factor (specifically worker learning) and its influence over the costs of processing units into the model. We describe this by using the well-known Wright’s Learning Curve. Most of the assumptions of the classical New Vendor Model are still maintained in our work, such as the constant per-unit cost of leftover and shortage, the zero initial inventory, as well as the continuous time. Our problem is challenging in the way that the best order quantity in the classical model, which is balancing the over-stocking and under-stocking costs, is no longer optimal. Specifically, when adding the cost-saving from worker learning to such expected total cost, the convexity of the cost function will likely not be maintained. This has called for a new way in determining the optimal order policy. In response to such challenges, we found a number of characteristics related to the expected cost function and its derivatives, which we then used in formulating the optimal ordering policy. Examples of such characteristics are; the optimal order quantity exists and is unique if the demand follows a Uniform Distribution; if the demand follows the Beta Distribution with some specific properties of its parameters, the second derivative of the expected cost function has at most two roots; and there exists the specific level of lot size that satisfies the first order condition. Our research results could be helpful for analysis of supply chain coordination and of the periodic review system for similar problems.

Keywords: inventory management, Newsvendor model, order policy, worker learning

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Authors: Arun Kumar R. K. Gothra, Hasan Alhakamy

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With increasing expectations and demands for warehousing and distribution, Warehouse Solution Incorporated in Victoria has been looking at ways to improve on its business processes to maintain the competitive edge. To maintain the provision of high quality service standards at competitive and affordable prices, improvements in the logistics management are necessary. One such avenue is to make efficient use of space available in the warehouse. This paper is based on a study of the collaboration of Warehouse Solution Inc with Dandenong Distribution Centre (DDC) to solve congestion problem and enhance efficiency of the whole warehouse activities.

Keywords: space optimization, optimal utilization, warehouse, DDC

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Authors: Eko Nursanty, Joesron Alie Syahbana, Atik Suprapti

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Tourist gaze is a set of experiences that experienced by a tourist in attempt to familiarize himself with the certain local tourism site’s condition. It is started from looking for information prior arriving at the location, then during the visit and gaining unique experience with the local inhabitant, and then experiencing the ingenuity of the location, finally to bring impression that keeps on attaching despite leaving from it. This research attempted to grab the message of tourist gaze in the process of structuring which is conducted in the global tourism in the cities in Indonesia, particularly Solo as the study case of the research. The method employed is the field observation of qualitative research. The expected result is to relate the tourist gaze theory with the development of ongoing global tourism.

Keywords: tourist gaze, tourism, city branding, Solo

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Authors: Amy Lebar, Kim L. Trenbath, Bennett Doherty, William Livingood

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Plug and process loads (PPLs) account for 47% of U.S. commercial building energy use. There is a huge potential to reduce whole building consumption by targeting PPLs for energy savings measures or implementing some form of plug load management (PLM). Despite this potential, there has yet to be a widely adopted commercial PLM technology. This paper describes the Automatic Type and Location Identification System (ATLIS), a PLM system framework with automatic and dynamic load detection (ADLD). ADLD gives PLM systems the ability to automatically identify devices as they are plugged into the outlets of a building. The ATLIS framework takes advantage of smart, connected devices to identify device locations in a building, meter and control their power, and communicate this information to a central database. ATLIS includes five primary capabilities: location identification, communication, control, energy metering and data storage. A laboratory proof of concept (PoC) demonstrated all but the data storage capabilities and these capabilities were validated using an office building scenario. The PoC can identify when a device is plugged into an outlet and the location of the device in the building. When a device is moved, the PoC’s dashboard and database are automatically updated with the new location. The PoC implements controls to devices from the system dashboard so that devices maintain correct schedules regardless of where they are plugged in within a building. ATLIS’s primary technology application is improved PLM, but other applications include asset management, energy audits, and interoperability for grid-interactive efficient buildings. A system like ATLIS could also be used to direct power to critical devices, such as ventilators, during a brownout or blackout. Such a framework is an opportunity to make PLM more widespread and reduce the amount of energy consumed by PPLs in current and future commercial buildings.

Keywords: commercial buildings, grid-interactive efficient buildings (GEB), miscellaneous electric loads (MELs), plug loads, plug load management (PLM)

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Authors: Mahdi Goharrokhi, Rasool Shiri, Eiraj Naser

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A depropanizer column of a particular refinery was redesigned in this work. That is, minimum reflux ratio, minimum number of trays, feed tray location and the hydraulic characteristics of the tower were calculated and compared with the actual values of the existing tower. To Design review of the tower, fundamental equations were used to develop software which its results were compared with two commercial software results. In each case PR EOS was used. Based on the total energy consumption in reboiler and condenser, feed tray location was also determined using case study definition for tower.

Keywords: column, hydraulic design, pressure drop, energy consumption

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Authors: Khaled Ben Oualid Medani, Samir Sayah

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The Optimal Reactive Power Dispatch (ORPD) problem has been solved and analysed usually in the normal conditions. However, network collapses appear in contingency conditions. In this paper, ORPD under several contingencies is presented using the proposed method WOA. To ensure viability of the power system in contingency conditions, several critical cases are simulated in order to prevent and prepare the power system to face such situations. The results obtained are carried out in IEEE 30 bus test system for the solution of ORPD problem in which control of bus voltages, tap position of transformers and reactive power sources are involved. Moreover, another method, namely, Particle Swarm Optimization with Time Varying Acceleration Coefficient (PSO-TVAC) has been compared with the proposed technique. Simulation results indicate that the proposed WOA gives remarkable solution in terms of effectiveness in case of outages.

Keywords: optimal reactive power dispatch, power system analysis, real power loss minimization, contingency condition, metaheuristic technique, whale optimization algorithm

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Authors: Ho Yeon Park, Kyoung-Jae Kim

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Recently, user’s interests for location-based social network service increases according to the advances of social web and location-based technologies. It may be easy to recommend preferred items if we can use user’s preference, context and social network information simultaneously. In this study, we propose context-aware POI (point-of-interests) recommender systems using location-based network analysis and sentiment analysis which consider context, social network information and implicit user’s preference score. We propose a context-aware POI recommendation system consisting of three sub-modules and an integrated recommendation system of them. First, we will develop a recommendation module based on network analysis. This module combines social network analysis and cluster-indexing collaboration filtering. Next, this study develops a recommendation module using social singular value decomposition (SVD) and implicit SVD. In this research, we will develop a recommendation module that can recommend preference scores based on the frequency of POI visits of user in POI recommendation process by using social and implicit SVD which can reflect implicit feedback in collaborative filtering. We also develop a recommendation module using them that can estimate preference scores based on the recommendation. Finally, this study will propose a recommendation module using opinion mining and emotional analysis using data such as reviews of POIs extracted from location-based social networks. Finally, we will develop an integration algorithm that combines the results of the three recommendation modules proposed in this research. Experimental results show the usefulness of the proposed model in relation to the recommended performance.

Keywords: sentiment analysis, network analysis, recommender systems, point-of-interests, business analytics

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Authors: Rahman Dashti, Ehsan Gord

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In this paper, an improved impedance based fault location method is proposed. In this method, online fault locating is performed using voltage and current information at the beginning of the feeder. Determining precise fault location in a short time increases reliability and efficiency of the system. The proposed method utilizes information about main component of voltage and current at the beginning of the feeder and distributed generation unit (DGU) in order to precisely locate different faults in acceptable time. To evaluate precision and accuracy of the proposed method, a 13-node is simulated and tested using MATLAB.

Keywords: distribution network, fault section determination, distributed generation units, distribution protection equipment

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Authors: Folajinmi Oluwasina, Towolawi Adetayo, Kate Ssamula, Penninah Iutung, Daniel Reijer

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Objective: Routine HIV screening has been promoted as an essential component of efforts to reduce incidence, morbidity, and mortality. The objectives of this study were to identify the optimal annual volume needed to realize the public health goals of HIV screening in the AIDS Healthcare Foundation supported hospitals and establish an implementation process to realize that optimal annual volume. Methods: Starting in 2011 a program was established to routinize HIV screening within communities and government hospitals. In 2016 Five-years of HIV screening data were reviewed to identify the optimal annual proportions of age-eligible patients screened to realize the public health goals of reducing new diagnoses and ending late-stage diagnosis (tracked as concurrent HIV/AIDS diagnosis). Analysis demonstrated that rates of new diagnoses level off when 42% of age-eligible patients were screened, providing a baseline for routine screening efforts; and concurrent HIV/AIDS diagnoses reached statistical zero at screening rates of 70%. Annual facility based targets were re-structured to meet these new target volumes. Restructuring efforts focused on right-sizing HIV screening programs to align and transition programs to integrated HIV screening within standard medical care and treatment. Results: Over one million patients were screened for HIV during the five years; 16, 033 new HIV diagnoses and access to care and treatment made successfully for 82 % (13,206), and concurrent diagnosis rates went from 32.26% to 25.27%. While screening rates increased by 104.7% over the 5-years, volume analysis demonstrated that rates need to further increase by 62.52% to reach desired 20% baseline and more than double to reach optimal annual screening volume. In 2011 facility targets for HIV screening were increased to reflect volume analysis, and in that third year, 12 of the 19 facilities reached or exceeded new baseline targets. Conclusions and Recommendation: Quantifying targets against routine HIV screening goals identified optimal annual screening volume and allowed facilities to scale their program size and allocate resources accordingly. The program transitioned from utilizing non-evidence based annual volume increases to establishing annual targets based on optimal volume analysis. This has allowed efforts to be evaluated on the ability to realize quantified goals related to the public health value of HIV screening. Optimal volume analysis helps to determine the size of an HIV screening program. It is a public health tool, not a tool to determine if an individual patient should receive screening.

Keywords: HIV screening, optimal volume, HIV diagnosis, routine

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Authors: Ahmed Osama, Hassan A. Mahdy, Khalid A. Kandil, Mohamed Elhabiby

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Automatic Vehicle Location systems (AVL) have been used worldwide for more than twenty years and have showed great success in public transportation management and monitoring. Cairo public bus service suffers from several problems such as unscheduled stops, unscheduled route deviations, and inaccurate schedules, which have negative impacts on service reliability. This research aims to study those problems for a selected bus route in Cairo using a prototype AVL system. Experimental trips were run on the selected route; and the locations of unscheduled stops, regions of unscheduled deviations, along with other trip time and speed data were collected. Data was analyzed to demonstrate the reliability of passengers on the unscheduled stops compared to the scheduled ones. Trip time was also modeled to assess the unscheduled stops’ impact on trip time, and to check the accuracy of the applied scheduled trip time. Moreover, frequency and length of the unscheduled route deviations, as well as their impact on the bus stops, were illustrated. Solutions were proposed for the bus service deficiencies using the AVL system. Finally, recommendations were proposed for further research.

Keywords: automatic vehicle location, public transportation, unscheduled stops, unscheduled route deviations, inaccurate schedule

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Authors: Bandar A. Alkhayyal

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Modern supply chains are typically linear, transforming virgin raw materials into products for end consumers, who then discard them after use to landfills or incinerators. Nowadays, there are major efforts underway to create a circular economy to reduce non-renewable resource use and waste. One important aspect of these efforts is the development of Green Supply Chain (GSC) systems which enables a reverse flow of used products from consumers back to manufacturers, where they can be refurbished or remanufactured, to both economic and environmental benefit. This paper develops novel multi-objective optimization models to inform GSC system design at multiple levels: (1) strategic planning of facility location and transportation logistics; (2) tactical planning of optimal pricing; and (3) policy planning to account for potential valuation of GSC emissions. First, physical linear programming was applied to evaluate GSC facility placement by determining the quantities of end-of-life products for transport from candidate collection centers to remanufacturing facilities while satisfying cost and capacity criteria. Second, disassembly and remanufacturing processes have received little attention in industrial engineering and process cost modeling literature. The increasing scale of remanufacturing operations, worth nearly $50 billion annually in the United States alone, have made GSC pricing an important subject of research. A non-linear physical programming model for optimization of pricing policy for remanufactured products that maximizes total profit and minimizes product recovery costs were examined and solved. Finally, a deterministic equilibrium model was used to determine the effects of internalizing a cost of GSC greenhouse gas (GHG) emissions into optimization models. Changes in optimal facility use, transportation logistics, and pricing/profit margins were all investigated against a variable cost of carbon, using case study system created based on actual data from sites in the Boston area. As carbon costs increase, the optimal GSC system undergoes several distinct shifts in topology as it seeks new cost-minimal configurations. A comprehensive study of quantitative evaluation and performance of the model has been done using orthogonal arrays. Results were compared to top-down estimates from economic input-output life cycle assessment (EIO-LCA) models, to contrast remanufacturing GHG emission quantities with those from original equipment manufacturing operations. Introducing a carbon cost of $40/t CO2e increases modeled remanufacturing costs by 2.7% but also increases original equipment costs by 2.3%. The assembled work advances the theoretical modeling of optimal GSC systems and presents a rare case study of remanufactured appliances.

Keywords: circular economy, extended producer responsibility, greenhouse gas emissions, industrial ecology, low carbon logistics, green supply chains

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Authors: A. Abbou, V. Makis, N. Salari

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We study the condition-based maintenance (CBM) problem of a system subject to stochastic deterioration. The system is composed of three units (or modules): (i) Module 1 deterioration follows a Markov process with two operational states and one failure state. The operational states are partially observable through periodic condition monitoring. (ii) Module 2 deterioration follows a Gamma process with a known failure threshold. The deterioration level of this module is fully observable through periodic inspections. (iii) Only the operating age information is available of Module 3. The lifetime of this module has a general distribution. A CBM policy prescribes when to initiate a maintenance intervention and which modules to repair during intervention. Our objective is to determine the optimal CBM policy minimizing the long-run expected average cost of operating the system. This is achieved by formulating a Markov decision process (MDP) and developing the value iteration algorithm for solving the MDP. We provide numerical examples illustrating the cost-effectiveness of the optimal CBM policy through a comparison with heuristic policies commonly found in the literature.

Keywords: reliability, maintenance optimization, Markov decision process, heuristics

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Authors: S. Dey, T. Mukhopadhyay, S. Adhikari

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This paper presents an exhaustive comparative investigation on sampling techniques of polynomial regression model based stochastic natural frequency of composite plates. Both individual and combined variations of input parameters are considered to map the computational time and accuracy of each modelling techniques. The finite element formulation of composites is capable to deal with both correlated and uncorrelated random input variables such as fibre parameters and material properties. The results obtained by Polynomial regression (PR) using different sampling techniques are compared. Depending on the suitability of sampling techniques such as 2k Factorial designs, Central composite design, A-Optimal design, I-Optimal, D-Optimal, Taguchi’s orthogonal array design, Box-Behnken design, Latin hypercube sampling, sobol sequence are illustrated. Statistical analysis of the first three natural frequencies is presented to compare the results and its performance.

Keywords: composite plate, natural frequency, polynomial regression model, sampling technique, uncertainty quantification

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Authors: Krishnanunni S.

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The COVID-19 Pandemic has had an impact on every part of our lives, and the film industry is no exception. The restrictions the pandemic has brought made filmmakers confine their films to limited spaces. In India, Malayalam cinema was the first to incorporate the pandemic into its stories and started producing films within existing constraints. The purpose of this study was to study how the limited location storytelling concept influenced Malayalam independent and lockdown films. To answer this question, the three of the most popular films that we shot during the pandemic: The Great Indian Kitchen, Joji and Joyful Mystery, were dissected through text analysis and in-depth interviews were conducted with the makers of The Great Indian Kitchen and Joyful Mystery. The study revealed that the pandemic had had an influence on the way filmmakers visualize their stories and shoot them, especially while working within the restrictions of the pandemic. It was also observed that working with limited locations was the only way for filmmakers to make films during the times of pandemic. But rather than a hindrance to their work, filmmakers saw it as a new possibility to create in times of confinement. The findings of this study expanded the work of previous researchers about films shot in limited locations and the significant changes the pandemic has brought to the film industry.

Keywords: limited location storytelling, pandemic, pandemic restrictions, lockdown cinema, pandemic films, Malayalam cinema, OTT revolution, cinema, films

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Authors: Jae Moon Lee

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In general, algorithms to find continuous k-nearest neighbors have been researched on the location based services, monitoring periodically the moving objects such as vehicles and mobile phone. Those researches assume the environment that the number of query points is much less than that of moving objects and the query points are not moved but fixed. In gaming environments, this problem is when computing the next movement considering the neighbors such as flocking, crowd and robot simulations. In this case, every moving object becomes a query point so that the number of query point is same to that of moving objects and the query points are also moving. In this paper, we analyze the performance of the existing algorithms focused on location based services how they operate under gaming environments.

Keywords: flocking behavior, heterogeneous agents, similarity, simulation

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Authors: Cinzia Cruder, Deborah Falla, Francesca Mangili, Laura Azzimonti, Liliana Araujo, Aaron Williamon, Marco Barbero

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Background and aims: According to the existing literature, musicians are at risk to experience a range of musculoskeletal painful conditions. Recently, digital technology has been developed to investigate pain location and pain extent. The aim of this study was to describe pain location and pain extent in musicians using a digital method for pain drawing analysis. Additionally, the association between pain drawing (PD) variables and clinical features in musicians with pain were explored. Materials and Methods: One hundred fifty-eight musicians (90 women and 68 men; age 22.4±3.6 years) were recruited from Swiss and UK conservatoires. Participants were asked to complete a survey including both background musical information and clinical features, the Quick Dash (QD) questionnaire and the digital PDs. Results: Of the 158 participants, 126 musicians (79.7%) reported having pain, with more prevalence in the areas of the neck and shoulders, the lower back and the right arm. The mean of pain extent was 3.1% ±6.5. The mean of QD was larger for musicians showing the presence of pain than for those without pain. Additionally, the results indicated a positive correlation between QD score and pain extent, and there were significant correlations between age and pain intensity, as well as between pain extent and pain intensity. Conclusions: The high prevalence of pain among musicians has been confirmed using a digital PD. In addition, positive correlations between pain extent and upper limb disability has been demonstrated. Our findings highlight the need for effective prevention and treatment strategies for musicians.

Keywords: pain location, pain extent, musicians, pain drawings

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Authors: Jin Ho Kim, Yujeong Shin, Seong-Jin Cho, Dong-Jin Kim, U-Syn Ha

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Due to the development of the information industry and technologies, cellular phones have must not only function to communicate, but also have functions such as the Internet, e-banking, entertainment, etc. These phones are called smartphones. The performance of smartphones has improved, because of the various functions of smartphones, and the capacity of the battery has been increased gradually. Recently, linear generators have been embedded in smartphones in order to recharge the smartphone's battery. In this study, optimization is performed and an array change of permanent magnets is examined in order to increase efficiency. We propose an optimal design using design of experiments (DOE) to maximize the generated induced voltage. The thickness of the poleshoe and permanent magnet (PM), the height of the poleshoe and PM, and the thickness of the coil are determined to be design variables. We made 25 sampling points using an orthogonal array according to four design variables. We performed electromagnetic finite element analysis to predict the generated induced voltage using the commercial electromagnetic analysis software ANSYS Maxwell. Then, we made an approximate model using the Kriging algorithm, and derived optimal values of the design variables using an evolutionary algorithm. The commercial optimization software PIAnO (Process Integration, Automation, and Optimization) was used with these algorithms. The result of the optimization shows that the generated induced voltage is improved.

Keywords: smartphone, linear generator, design of experiment, approximate model, optimal design

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Authors: Abul B. M. M. K. Islam, Nuria Lopez-Bigas, Elizaveta V. Benevolenskaya

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RBP2 has shown to be important for cell differentiation control through epigenetic mechanism. The main aim of the present study is genome-wide location analysis of human RBP2 isoforms that differ in a histone-binding domain by ChIPseq. It is conceivable that the larger isoform (LI) of RBP2, which contains a specific H3K4me3 interacting domain, differs from the smaller isoform (SI) in genomic location, may account for the observed diversity in RBP2 function. To distinguish the two RBP2 isoforms, we used the fact that the SI lacks the C-terminal PHD domain and hence used the antibodies detecting both RBP2 isoforms (AI) through a common central domain, and the antibodies detecting only LI but not SI, through a C-terminal PHD domain. Overall our analysis suggests that RBP2 occupies about 77 nucleotides and binds GC rich motifs of active genes, does not bind to centromere, telomere, or enhancer regions, and binding sites are conserved compare to random. A striking difference between the only-SI and only-LI is that a large number of only-SI peaks are located in CpG islands and close to TSS compared to only-LI peaks. Enrichment analysis of the related genes indicates that several oncogenic pathways and metabolic pathways/processes are significantly enriched among only-SI/AI targets, but not LI/only-LI peak’s targets.

Keywords: bioinformatics, cancer, ChIP-seq, KDM5A

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Authors: S. Sambath, P. Palanivel

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Research conducted in the last few decades has proven that an inclusion of Distributed Genaration (DG) into distribution systems considerably lowers the level of power losses and the power quality improved. Moreover, the choice of DG is even more attractive since it provides not only benefits in power loss minimisation, but also a wide range of other advantages including environment, economic, power qualities and technical issues. This paper is an intent to quantify and analyse the impact of distributed generation (DG) in Tamil Nadu, India to examine what the benefits of decentralized generation would be for meeting rural loads. We used load flow analysis to simulate and quantify the loss reduction and power quality enhancement by having decentralized generation available line conditions for actual rural feeders in Tamil Nadu, India. Reactive and voltage profile was considered. This helps utilities to better plan their system in rural areas to meet dispersed loads, while optimizing the renewable and decentralised generation sources.

Keywords: distributed generation, distribution system, load flow analysis, optimal location, power quality

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Authors: Yiqiong Yuan, Jun Sun, Dongmei Zhou, Jianan Sun

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In this paper, we presented a Multi-Objective Random Drift Particle Swarm Optimization algorithm (MORDPSO-CD) based on RDPSO and crowding distance sorting to improve the convergence and distribution with less computation cost. MORDPSO-CD makes the most of RDPSO to approach the true Pareto optimal solutions fast. We adopt the crowding distance sorting technique to update and maintain the archived optimal solutions. Introducing the crowding distance technique into MORDPSO can make the leader particles find the true Pareto solution ultimately. The simulation results reveal that the proposed algorithm has better convergence and distribution

Keywords: multi-objective optimization, random drift particle swarm optimization, crowding distance sorting, pareto optimal solution

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Authors: Bingxi Huang, Yiqing Li, Marek Morzynski, Bernd R. Noack

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We propose a Kriging-based global optimization method for active flow control with multiple actuation parameters. This method is designed to converge quickly and avoid getting trapped into local minima. We follow the model-free explorative gradient method (EGM) to alternate between explorative and exploitive steps. This facilitates a convergence similar to a gradient-based method and the parallel exploration of potentially better minima. In contrast to EGM, both kinds of steps are performed with Kriging surrogate model from the available data. The explorative step maximizes the expected improvement, i.e., favors regions of large uncertainty. The exploitive step identifies the best location of the cost function from the Kriging surrogate model for a subsequent weight-biased linear-gradient descent search method. To verify the effectiveness and robustness of the improved Kriging-based optimization method, we have examined several comparative test problems of varying dimensions with limited evaluation budgets. The results show that the proposed algorithm significantly outperforms some model-free optimization algorithms like genetic algorithm and differential evolution algorithm with a quicker convergence for a given budget. We have also performed direct numerical simulations of the fluidic pinball (N. Deng et al. 2020 J. Fluid Mech.) on three circular cylinders in equilateral-triangular arrangement immersed in an incoming flow at Re=100. The optimal cylinder rotations lead to 44.0% net drag power saving with 85.8% drag reduction and 41.8% actuation power. The optimal results for active flow control based on this configuration have achieved boat-tailing mechanism by employing Coanda forcing and wake stabilization by delaying separation and minimizing the wake region.

Keywords: direct numerical simulations, flow control, kriging, stochastic optimization, wake stabilization

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Authors: Mohamed Hafid, Marcel Lacroix

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This study presents a simple inverse heat transfer procedure for predicting the wall erosion and the time-varying thickness of the protective bank that covers the inside surface of the refractory brick wall of a melting furnace. The direct problem is solved by using the Finite-Volume model. The melting/solidification process is modeled using the enthalpy method. The inverse procedure rests on the Levenberg-Marquardt method combined with the Broyden method. The effect of the location of the temperature sensors and of the measurement noise on the inverse predictions is investigated. Recommendations are made concerning the location of the temperature sensor.

Keywords: melting furnace, inverse heat transfer, enthalpy method, levenberg–marquardt method

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Authors: Palash Dey, Sudip Talukdar

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In this work, a cross-breed approach is presented for obtaining both the amount of the damage intensity and location of damage existing in thin-walled members. This cross-breed approach is developed based on response surface methodology (RSM) and genetic algorithm (GA). Theoretical finite element (FE) model of cracked angle section thin walled curved beam has been linked to the developed approach to carry out trial experiments to generate response surface functions (RSFs) of free, forced and heterogeneous dynamic response data. Subsequently, the error between the computed response surface functions and measured dynamic response data has been minimized using GA to find out the optimum damage parameters (amount of the damage intensity and location). A single crack of varying location and depth has been considered in this study. The presented approach has been found to reveal good accuracy in prediction of crack parameters and possess great potential in crack detection as it requires only the current response of a cracked beam.

Keywords: damage parameters, finite element, genetic algorithm, response surface methodology, thin walled curved beam

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Authors: Getachew Tilahun, Oluwole Makinde, David Malonza

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We propose and analyze a non-linear mathematical model for the transmission dynamics of pneumonia disease in a population of varying size. The deterministic compartmental model is studied using stability theory of differential equations. The effective reproduction number is obtained and also the local and global asymptotically stability conditions for the disease free and as well as for the endemic equilibria are established. The model exhibit a backward bifurcation and the sensitivity indices of the basic reproduction number to the key parameters are determined. Using Pontryagin’s maximum principle, the optimal control problem is formulated with three control strategies; namely disease prevention through education, treatment and screening. The cost effectiveness analysis of the adopted control strategies revealed that the combination of prevention and treatment is the most cost effective intervention strategies to combat the pneumonia pandemic. Numerical simulation is performed and pertinent results are displayed graphically.

Keywords: cost effectiveness analysis, optimal control, pneumonia dynamics, stability analysis, numerical simulation

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Authors: Imad Zeyad Ramadan

Abstract:

In this paper a genetic algorithm was developed to construct the optimal portfolio based on the Treynor method. The GA maximizes the Treynor ratio under budget constraint to select the best allocation of the budget for the companies in the portfolio. The results show that the GA was able to construct a conservative portfolio which includes companies from the three sectors. This indicates that the GA reduced the risk on the investor as it choose some companies with positive risks (goes with the market) and some with negative risks (goes against the market).

Keywords: oOptimization, genetic algorithm, portfolio selection, Treynor method

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Authors: Changhwan Choi, Yongwan Park

Abstract:

In this paper, we propose a method that allows faster and more accurate detection of traffic lights by a vision sensor during driving, DGPS is used to obtain physical location of a traffic light, extract from the image information of the vision sensor only the traffic light area at this location and ascertain if the sign is in operation and determine its form. This method can solve the problem in existing research where low visibility at night or reflection under bright light makes it difficult to recognize the form of traffic light, thus making driving unstable. We compared our success rate of traffic light recognition in day and night road environments. Compared to previous researches, it showed similar performance during the day but 50% improvement at night.

Keywords: traffic light, intelligent vehicle, night, detection, DGPS

Procedia PDF Downloads 299