Search results for: optimal cropping pattern

Authors: Akram Khaleghei Ghosheh Balagh, Viliam Makis, Leila Jafari

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In this paper, we present a new maintenance model for a partially observable system subject to two failure modes, namely a catastrophic failure and a failure due to the system degradation. The system is subject to condition monitoring and the degradation process is described by a hidden Markov model. A cost-optimal Bayesian control policy is developed for maintaining the system. The control problem is formulated in the semi-Markov decision process framework. An effective computational algorithm is developed and illustrated by a numerical example.

Keywords: partially observable system, hidden Markov model, competing risks, multivariate Bayesian control

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Authors: Niklas Panten, Eberhard Abele

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This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.

Keywords: industrial smart grids, energy efficiency, deep reinforcement learning, optimal control

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Authors: Hui-Chuan Lu

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In a perfect secret-sharing scheme, a dealer distributes a secret among a set of participants in such a way that only qualified subsets of participants can recover the secret and the joint share of the participants in any unqualified subset is statistically independent of the secret. The access structure of the scheme refers to the collection of all qualified subsets. In a graph-based access structures, each vertex of a graph G represents a participant and each edge of G represents a minimal qualified subset. The average information ratio of a perfect secret-sharing scheme realizing a given access structure is the ratio of the average length of the shares given to the participants to the length of the secret. The infimum of the average information ratio of all possible perfect secret-sharing schemes realizing an access structure is called the optimal average information ratio of that access structure. We study the optimal average information ratio of the access structures based on bipartite graphs. Based on some previous results, we give a bound on the optimal average information ratio for all bipartite graphs of girth at least six. This bound is the best possible for some classes of bipartite graphs using our approach.

Keywords: secret-sharing scheme, average information ratio, star covering, deduction, core cluster

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Authors: T. Sattarpour, D. Nazarpour

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This paper investigates the effect of simultaneous placement of DGs and smart meters (SMs), on voltage profile improvement in active distribution networks (ADNs). A substantial center of attention has recently been on responsive loads initiated in power system problem studies such as distributed generations (DGs). Existence of responsive loads in active distribution networks (ADNs) would have undeniable effect on sizing and siting of DGs. For this reason, an optimal framework is proposed for sizing and siting of DGs and SMs in ADNs. SMs are taken into consideration for the sake of successful implementing of demand response programs (DRPs) such as direct load control (DLC) with end-side consumers. Looking for voltage profile improvement, the optimization procedure is solved by genetic algorithm (GA) and tested on IEEE 33-bus distribution test system. Different scenarios with variations in the number of DG units, individual or simultaneous placing of DGs and SMs, and adaptive power factor (APF) mode for DGs to support reactive power have been established. The obtained results confirm the significant effect of DRPs and APF mode in determining the optimal size and site of DGs to be connected in ADN resulting to the improvement of voltage profile as well.

Keywords: active distribution network (ADN), distributed generations (DGs), smart meters (SMs), demand response programs (DRPs), adaptive power factor (APF)

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Authors: Xinhuang Wu, Yousef Sardahi

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A hybrid and optimal multi-loop control structure combining linear and nonlinear control algorithms are introduced in this paper to regulate the position of a quadcopter unmanned aerial vehicle (UAV) driven by four brushless DC motors. To this end, a nonlinear mathematical model of the UAV is derived and then linearized around one of its operating points. Using the nonlinear version of the model, a sliding mode control is used to derive the control laws of the motor thrust forces required to drive the UAV to a certain position. The linear model is used to design two controllers, XG-controller and YG-controller, responsible for calculating the required roll and pitch to maneuver the vehicle to the desired X and Y position. Three attitude controllers are designed to calculate the desired angular rates of rotors, assuming that the Euler angles are minimal. After that, a many-objective optimization problem involving 20 design parameters and ten objective functions is formulated and solved by HypE (Hypervolume estimation algorithm), one of the widely used many-objective optimization algorithms approaches. Both stability and performance constraints are imposed on the optimization problem. The optimization results in terms of Pareto sets and fronts are obtained and show that some of the design objectives are competing. That is, when one objective goes down, the other goes up. Also, Numerical simulations conducted on the nonlinear UAV model show that the proposed optimization method is quite effective.

Keywords: optimal control, many-objective optimization, sliding mode control, linear control, cascade controllers, UAV, drones

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Authors: Michael Ayomoh, Adriaan Roux, Oyindamola Omotuyi

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This paper presents an efficient robot navigation model in a multi-target domain amidst static and dynamic workspace obstacles. The problem is that of developing an optimal algorithm to minimize the total travel time of a robot as it visits all target points within its task domain amidst unknown workspace obstacles and finally return to its initial position. In solving this problem, a classical algorithm was first developed to compute the optimal number of paths to be travelled by the robot amidst the network of paths. The principle of shortest distance between robot and targets was used to compute the target point visitation order amidst workspace obstacles. Algorithm premised on the standard polar coordinate system was developed to determine the length of obstacles encountered by the robot hence giving room for a geometrical estimation of the total surface area occupied by the obstacle especially when classified as a relevant obstacle i.e. obstacle that lies in between a robot and its potential visitation point. A stochastic model was developed and used to estimate the likelihood of a dynamic obstacle bumping into the robot’s navigation path and finally, the navigation/obstacle avoidance algorithm was hinged on the hybrid virtual force field (HVFF) method. Significant modelling constraints herein include the choice of navigation path to selected target points, the possible presence of static obstacles along a desired navigation path and the likelihood of encountering a dynamic obstacle along the robot’s path and the chances of it remaining at this position as a static obstacle hence resulting in a case of re-routing after routing. The proposed algorithm demonstrated a high potential for optimal solution in terms of efficiency and effectiveness.

Keywords: multi-target, mobile robot, optimal path, static obstacles, dynamic obstacles

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Authors: Suwarno, M. Helmi Prakoso

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Mineral oil is commonly used for high voltage transformer insulation. The insulation quality of mineral oil is affecting the operation process of high voltage transformer. There are many contaminations which could decrease the insulation quality of mineral oil. One of them is water. This research talks about the effect of water content on dielectric properties, physic properties, and partial discharge pattern on mineral oil. Samples were varied with 10 varieties of water content value. And then all samples were tested to measure the dielectric properties, physic properties, and partial discharge pattern. The result of this research showed that an increment of water content value would decrease the insulation quality of mineral oil.

Keywords: dielectric properties, high voltage transformer, mineral oil, water content

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Authors: Patrick Ho

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Bloodstain Pattern Analysis (BPA) forensic evidence can be complex, requiring effective courtroom presentation to ensure clear and comprehensive understanding of the analyst’s findings. BPA witness statements can often involve reference to spatial information (such as location of rooms, objects, walls) which, when coupled with classified blood patterns, may illustrate the reconstructed movements of suspects and injured parties. However, it may be difficult to communicate this information through photography alone, despite this remaining the UK’s established method for presenting BPA evidence. Through an academic-police partnership between the University of Warwick and West Midlands Police (WMP), an integrated 3D scanning and HDR photography workflow for BPA was developed. Homicide scenes were laser scanned and, after processing, the 3D models were utilised in the BPA peer-review process. The same 3D models were made available for court but were not always utilised. This workflow has improved the ease of presentation for analysts and provided 3D scene models that assist with the investigation. However, the effects of incorporating 3D scene models in judicial processes may need to be studied before they are adopted more widely. 3D models from a simulated crime scene and West Midlands Police cases approved for conference disclosure are presented. We describe how the workflow was developed and integrated into established practices at WMP, including peer-review processes and witness statement delivery in court, and explain the impact the work has had on the Criminal Justice System in the West Midlands.

Keywords: bloodstain pattern analysis, forensic science, criminal justice, 3D scanning

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Authors: Vinko Lešić, Mario Vašak, Anita Martinčević, Marko Gulin, Antonio Starčić, Hrvoje Novak

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With 40% of total world energy consumption, building systems are developing into technically complex large energy consumers suitable for application of sophisticated power management approaches to largely increase the energy efficiency and even make them active energy market participants. Centralized control system of building heating and cooling managed by economically-optimal model predictive control shows promising results with estimated 30% of energy efficiency increase. The research is focused on implementation of such a method on a case study performed on two floors of our faculty building with corresponding sensors wireless data acquisition, remote heating/cooling units and central climate controller. Building walls are mathematically modeled with corresponding material types, surface shapes and sizes. Models are then exploited to predict thermal characteristics and changes in different building zones. Exterior influences such as environmental conditions and weather forecast, people behavior and comfort demands are all taken into account for deriving price-optimal climate control. Finally, a DC microgrid with photovoltaics, wind turbine, supercapacitor, batteries and fuel cell stacks is added to make the building a unit capable of active participation in a price-varying energy market. Computational burden of applying model predictive control on such a complex system is relaxed through a hierarchical decomposition of the microgrid and climate control, where the former is designed as higher hierarchical level with pre-calculated price-optimal power flows control, and latter is designed as lower level control responsible to ensure thermal comfort and exploit the optimal supply conditions enabled by microgrid energy flows management. Such an approach is expected to enable the inclusion of more complex building subsystems into consideration in order to further increase the energy efficiency.

Keywords: price-optimal building climate control, Microgrid power flow optimisation, hierarchical model predictive control, energy efficient buildings, energy market participation

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Authors: Maher Agi, Hardik Soni

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This paper presents a deterministic model for optimized control of the inventory of a perishable product subject to both physical deterioration and degradation of its freshness condition. The demand for the product depends on its current inventory level and freshness condition. Our model allows for any positive amount of end of cycle inventory. Some useful conditions that characterize the optimal solution of the model are derived and an algorithm is presented for finding the optimal values of the price, the inventory cycle, the end of cycle inventory level and the order quantity. Numerical examples are then given. Our work shows how the product freshness in conjunction with the inventory deterioration affects the inventory management decisions.

Keywords: inventory management, lot sizing, perishable products, deteriorating inventory, age-dependent demand, stock-dependent demand

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Authors: Azam Mohammadbagheri, Bahram Fathi

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DEA has become a very popular method of performance measure, but it still suffers from some shortcomings. One of these shortcomings is the issue of having multiple optimal solutions to weights for efficient DMUs. The cross efficiency evaluation as an extension of DEA is proposed to avoid this problem. Lam (2010) is also proposed a mixed-integer linear programming formulation based on linear discriminate analysis and super efficiency method (MILP model) to avoid having multiple optimal solutions to weights. In this study, we modified MILP model to determine more suitable weight sets and also evaluate the energy efficiency of MENA countries as an application of the proposed model.

Keywords: data envelopment analysis, discriminate analysis, cross efficiency, MILP model

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Authors: Tagore Sai Priya Nunna, Ankhi Banerjee

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The rapid growth of the tourism industry in India in the last few years after the economic crisis in 2009 has been one of the significant causes that led to the Land Use Land Cover change (LULC) of most tourism destinations. The tourist regions are subjected to significant increase in built-up due to increased construction activities for developing accommodation facilities further boosting tourism demand. This research attempts to analyse the changing LULC and the growth pattern of the built-up area within tourist destinations. Four popular tourist destinations, which promises various types of tourism activity and which are significantly dependent on tourism for economic growth, are selected for the study. The study uses remotely sensed data for analysis of land use change through supervised segmentation into five broad classes. Further, the landuse map is reclassified into binary classes to extract the built-up area. The growth patterns of the built-up are analysed in terms of size, shape, direction and form of growth, through a set of spatial metrics. Additionally, a detailed analysis of the existing development pattern corresponding to planned development zones was performed to identify unplanned growth spots in the study regions. The findings of the study provide insights into how tourism has contributed to significant changes in LULC around tourist sites. Also, the study highlights the growth pattern of built-up areas with respect to the type of tourism activity and geographical characteristics. The research attempts to address the need of integrating spatial metrics for the development of sustainable tourism plans as part of the goals of sustainable development.

Keywords: built-up, growth, patterns, tourism, sustainable

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Authors: S. Neelima, P. S. Subramanyam

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A distribution system is an interface between the bulk power system and the consumers. Among these systems, radial distributions system is popular because of low cost and simple design. In distribution systems, the voltages at buses reduces when moved away from the substation, also the losses are high. The reason for a decrease in voltage and high losses is the insufficient amount of reactive power, which can be provided by the shunt capacitors. But the placement of the capacitor with an appropriate size is always a challenge. Thus, the optimal capacitor placement problem is to determine the location and size of capacitors to be placed in distribution networks in an efficient way to reduce the power losses and improve the voltage profile of the system. For this purpose, in this paper, two stage methodologies are used. In the first stage, the load flow of pre-compensated distribution system is carried out using ‘dimension reducing distribution load flow algorithm (DRDLFA)’. On the basis of this load flow the potential locations of compensation are computed. In the second stage, Genetic Algorithm (GA) technique is used to determine the optimal location and size of the capacitors such that the cost of the energy loss and capacitor cost to be a minimum. The above method is tested on IEEE 9 and 34 bus system and compared with other methods in the literature.

Keywords: dimension reducing distribution load flow algorithm, DRDLFA, genetic algorithm, electrical distribution network, optimal capacitors placement, voltage profile improvement, loss reduction

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Authors: Stelvin Sebastian, Andriya Annie Tom, Joyalanna Babu, Merin Joshy

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Introduction: The worldwide increase in the use of antibiotics in poultry and livestock industry to treat and prevent bacterial diseases and as growth promoters in feeds has led to the problem of development of antibiotic resistance both in animals and human population. Aim: To study the pattern of antibiotic use and prevalence of multidrug-resistant Escherichia coli in poultry chickens in selected farms in Muvattupuzha and to compare the spread of multidrug-resistant bacteria from poultry environment to UTI patients. Methodology: Two farms from each of 6 localities in Muvattupuzha were selected. A questionnaire on the pattern of antibiotic use and various farming practices were surveyed from farms. From each farm, 60samples of fresh fecal matter, litter from inside, litter from the outside shed, agricultural soil and control soil were collected, and antimicrobial susceptibility testing of E. coli was done. Antibiogram of UTI patients was collected from the secondary care hospital included in the study, and those were compared with resistance patterns of poultry samples. Results: From survey response antibiotics such as ofloxacin, enrofloxacin, levofloxacin, ciprofloxacin, colistin, ceftriaxone, neomycin, cephalexin, and oxytetracycline were used for treatment and prevention of infections in poultry. 31of 48 samples (51.66%) showed E. coli growth. 7 of 15 antibiotics (46.6%) showed resistance. Ampicillin, amoxicillin, meropenem, tetracycline showed 100% resistance to all samples. Statistical analysis confirmed similar resistance pattern in the poultry environment and UTI patients for antibiotics such as ampicillin, amoxicillin, amikacin, and ofloxacin. Conclusion: E. coli were resistant not only to extended-spectrum beta-lactams but also to carbapenems, which may be disseminated to the environment where litter was used as manure. This may due to irrational use of antibiotics in chicken or from their use in poultry feed as growth promoters. The study concludes the presence of multidrug-resistant E.coli in poultry and its spread to environment and humans, which may cause potentially serious implications for human health.

Keywords: multidrug resistance, escherichia coli, urinary tract infection, poultry

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Authors: Akinsola Oluwatosin, Udofia Samuel, Odofin Mayowa

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The study is aimed at assessing the Geographic Information System (GIS)-based spatial analysis of Survival Pattern and Treatment Outcomes of Multi-Drug Resistant Tuberculosis (MDR-TB) cases for Lagos, Nigeria, with an objective to inform priority areas for public health planning and resource allocation. Multi-drug resistant tuberculosis (MDR-TB) develops due to problems such as irregular drug supply, poor drug quality, inappropriate prescription, and poor adherence to treatment. The shapefile(s) for this study were already georeferenced to Minna datum. The patient’s information was acquired on MS Excel and later converted to . CSV file for easy processing to ArcMap from various hospitals. To superimpose the patient’s information the spatial data, the addresses was geocoded to generate the longitude and latitude of the patients. The database was used for the SQL query to the various pattern of the treatment. To show the pattern of disease spread, spatial autocorrelation analysis was used. The result was displayed in a graphical format showing the areas of dispersing, random and clustered of patients in the study area. Hot and cold spot analysis was analyzed to show high-density areas. The distance between these patients and the closest health facility was examined using the buffer analysis. The result shows that 22% of the points were successfully matched, while 15% were tied. However, the result table shows that a greater percentage of it was unmatched; this is evident in the fact that most of the streets within the State are unnamed, and then again, most of the patients are likely to supply the wrong addresses. MDR-TB patients of all age groups are concentrated within Lagos-Mainland, Shomolu, Mushin, Surulere, Oshodi-Isolo, and Ifelodun LGAs. MDR-TB patients between the age group of 30-47 years had the highest number and were identified to be about 184 in number. The outcome of patients on ART treatment revealed that a high number of patients (300) were not ART treatment while a paltry 45 patients were on ART treatment. The result shows the Z-score of the distribution is greater than 1 (>2.58), which means that the distribution is highly clustered at a significance level of 0.01.

Keywords: tuberculosis, patients, treatment, GIS, MDR-TB

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Authors: Zheni S. Stefanova, Kandethody M. Ramachandran

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With the increasing dependency on our computer devices, we face the necessity of adequate, efficient and effective mechanisms, for protecting our network. There are two main problems that Intrusion Detection Systems (IDS) attempt to solve. 1) To detect the attack, by analyzing the incoming traffic and inspect the network (intrusion detection). 2) To produce a prompt response when the attack occurs (intrusion prevention). It is critical creating an Intrusion detection model that will detect a breach in the system on time and also challenging making it provide an automatic and with an acceptable delay response at every single stage of the monitoring process. We cannot afford to adopt security measures with a high exploiting computational power, and we are not able to accept a mechanism that will react with a delay. In this paper, we will propose an intrusion response mechanism that is based on artificial intelligence, and more precisely, reinforcement learning techniques (RLT). The RLT will help us to create a decision agent, who will control the process of interacting with the undetermined environment. The goal is to find an optimal policy, which will represent the intrusion response, therefore, to solve the Reinforcement learning problem, using a Q-learning approach. Our agent will produce an optimal immediate response, in the process of evaluating the network traffic.This Q-learning approach will establish the balance between exploration and exploitation and provide a unique, self-learning and strategic artificial intelligence response mechanism for IDS.

Keywords: cyber security, intrusion prevention, optimal policy, Q-learning

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Authors: M. Amara, M. Tahar Abbes, A. Dokkiche, M. Benbrike

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Shear stresses generate frictional forces thus lead to the reduction of engine performance due to the power losses. This friction can also cause damage to the piston material. Thus, the choice of an optimal material for the piston is necessary to improve the elastohydrodynamical contacts of the piston. In this study, to achieve this objective, an elastohydrodynamical lubrication model that satisfies the best tribological behavior of the piston with the optimum choice of material is developed. Several aluminum alloys composed of different components are studied in this simulation. An application is made on the piston 60 x 120 mm Diesel engine type F8L413 currently mounted on Deutz trucks TB230 by using different aluminum alloys where alloys based on aluminum-silicon have better tribological performance.

Keywords: EHD lubricated contacts, friction, properties of materials, tribological performance

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Authors: Jing Zhao, Yoshiharu Ishikawa, Chuan Xiao, Kento Sugiura

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In order to analyze large-scale scientific data, research on data exploration and visualization has gained popularity. In this paper, we focus on the exploration and visualization of scientific simulation data, and define a spatial V-Optimal histogram for data summarization. We propose histogram construction algorithms based on a general binary hierarchical partitioning as well as a more specific one, the l-grid partitioning. For effective data summarization and efficient data visualization in scientific data analysis, we propose an optimal algorithm as well as a heuristic algorithm for histogram construction. To verify the effectiveness and efficiency of the proposed methods, we conduct experiments on the massive evacuation simulation data.

Keywords: simulation data, data summarization, spatial histograms, exploration, visualization

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Authors: Satish Kumar Dewangan, Santosh Kumar Senapati

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The present work focuses on the investigation of the effect of non-Newtonian behavior on the oil-water stratified flow in a horizontal channel using ANSYS Fluent. Coupled level set and volume of fluid (CLSVOF) has been used to capture the evolving interface assuming unsteady, coaxial flow with constant fluid properties. The diametric variation of oil volume fraction, mixture velocity, total pressure and pressure gradient has been studied. Non-Newtonian behavior of oil has been represented by the power law model in order to investigate the effect of flow behavior index. Stratified flow pattern tends to assume dispersed flow pattern with the change in the behavior of oil to non-Newtonian. The pressure gradient is found to be very much sensitive to the flow behavior index. The findings could be useful in designing the transportation pipe line in petroleum industries.

Keywords: oil-water stratified flow, horizontal channel, CLSVOF, non–Newtonian behaviour.

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Authors: Srijitra Khanpakdee, Teera Butburee, Jung-Ho Yun, Miaoqiang Lyu, Supphasin Thaweesak, Piangjai Peerakiatkhajohn

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The synthesis of titanium dioxide (TiO₂) nanorods (NRs) on fluorine-doped tin oxide (FTO) glass via hydrothermal methods was investigated to determine the optimal reaction time for enhanced photocatalytic and optical performance. Reaction times of 4, 6, and 8 hours were studied. Characterization through SEM, UV-vis, XRD, FTIR, Raman spectroscopy and photoelectrochemical (PEC) techniques revealed significant differences in the properties of the TiO₂ NRs based on the reaction duration. XRD and Raman spectroscopy analysis confirmed the formation of the rutile phase of TiO₂. As photoanodes in PEC cells, TiO₂ NRs synthesized for 4 hours exhibited the best photocatalytic activity, with the highest photocurrent density and superior charge transport properties, attributed to their densely packed vertical structure. Longer reaction times resulted in less optimal morphological and photoelectrochemical characteristics. The bandgap of the TiO₂ NRs remained consistent around 3.06 eV, with only slight variations observed. This study highlights the critical role of reaction time in hydrothermal synthesis, identifying 4 hours as the optimal duration for producing TiO₂ NRs with superior photoelectrochemical performance. These findings provide valuable insights for optimizing TiO₂-based materials for solar energy conversion and renewable energy applications.

Keywords: titanium dioxide, nanorods, hydrothermal, photocatalytic, photoelectrochemical

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Authors: S. Gherbi, F. Bouchareb

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This paper deals with the novel intelligent bio-inspired control strategies, it presents a novel approach based on an optimal fuzzy immune PID parameters tuning, it is a combination of a PID controller, inspired by the human immune mechanism with fuzzy logic. Such controller offers more possibilities to deal with the delayed systems control difficulties due to the delay term. Indeed, we use an optimization approach to tune the four parameters of the controller in addition to the fuzzy function; the obtained controller is implemented in a modified Smith predictor structure, which is well known that it is the most efficient to the control of delayed systems. The application of the presented approach to control a three tank delay system shows good performances and proves the efficiency of the method.

Keywords: delayed systems, fuzzy immune PID, optimization, Smith predictor

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Authors: G. V. Siva Krishna Rao, B. Srinivasa Rao

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Electrical energy is vital in every aspect of day-to-day life. Keen interest is taken on all possible sources of energy from which it can be generated and this led to the encouragement of generating electrical power using renewable energy resources such as solar, tidal waves and wind energy. Due to the increasing interest on renewable sources in recent times, the studies on integration of distributed generation to the power grid have rapidly increased. Distributed Generation (DG) is a promising solution to many power system problems such as voltage regulation, power loss and reduction in operational cost, etc. To reduce production cost, it is important to minimize the losses by determining the location and size of local generators to be placed in the radial distribution systems. In this paper, reduction of production cost by optimal size of DG unit operated at optimal power factor is dealt. The optimal size of the DG unit is calculated analytically using approximate reasoning suitable nodes and DG placement to minimize production cost with minimum loss is determined by fuzzy technique. Total Cost of Power generation is compared with and without DG unit for 1 year duration. The suggested method is programmed under MATLAB software and is tested on IEEE 33 bus system and the results are presented.

Keywords: distributed generation, operational cost, exact loss formula, optimum size, optimum location

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Authors: Tayyaba Hussain, Sobia Jangsher, Saqib Ali, Saqib Ejaz

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Unmanned Aerial vehicles (UAV’s) have gained great popularity due to their remoteness, ease of deployment and high maneuverability in different applications like real-time surveillance, image capturing, weather atmospheric studies, disaster site monitoring and mapping. These applications can involve a real-time communication with the ground station. However, altitude and mobility possess a few challenges for the communication. UAV’s at high altitude usually require more transmit power. One possible solution can be with the use of multi hops (UAV’s acting as relays) and exploiting the mobility pattern of the UAV’s. In this paper, we studied a relay (UAV’s acting as relays) selection for a reliable transmission to a destination UAV. We exploit the mobility information of the UAV’s to propose a Mobility-Aware Relay Selection (MARS) algorithm with the objective of giving improved data rates. The results are compared with Non Mobility-Aware relay selection scheme and optimal values. Numerical results show that our proposed MARS algorithm gives 6% better achievable data rates for the mobile UAV’s as compared with Non MobilityAware relay selection scheme. On average a decrease of 20.2% in data rate is achieved with MARS as compared with SDP solver in Yalmip.

Keywords: mobility aware, relay selection, time division multiple acess, unmanned aerial vehicle

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Authors: Mahmoud Samkan

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Dispersed Generation (DG) is a promising solution to many power system problems such as voltage regulation and power loss. This paper proposes a heuristic two-step method to optimize the location and size of DG for reducing active power losses and, therefore, improve the voltage profile in radial distribution networks. In addition to a DG placed at the system load gravity center, this method consists in assigning a DG to each lateral of the network. After having determined the central DG placement, the location and size of each lateral DG are predetermined in the first step. The results are then refined in the second step. This method is tested for 33-bus system for 100% DG penetration. The results obtained are compared with those of other methods found in the literature.

Keywords: optimal location, optimal size, dispersed generation (DG), radial distribution networks, reducing losses

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Authors: Alina Fedossova, Jose Jorge Sierra Molina

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SIP problems are part of non-classical optimization. There are problems in which the number of variables is finite, and the number of constraints is infinite. These are semi-infinite programming problems. Most algorithms for semi-infinite programming problems reduce the semi-infinite problem to a finite one and solve it by classical methods of linear or nonlinear programming. Typically, any of the constraints or the objective function is nonlinear, so the problem often involves nonlinear programming. An investment portfolio is a set of instruments used to reach the specific purposes of investors. The risk of the entire portfolio may be less than the risks of individual investment of portfolio. For example, we could make an investment of M euros in N shares for a specified period. Let yi> 0, the return on money invested in stock i for each dollar since the end of the period (i = 1, ..., N). The logical goal here is to determine the amount xi to be invested in stock i, i = 1, ..., N, such that we maximize the period at the end of ytx value, where x = (x1, ..., xn) and y = (y1, ..., yn). For us the optimal portfolio means the best portfolio in the ratio "risk-return" to the investor portfolio that meets your goals and risk ways. Therefore, investment goals and risk appetite are the factors that influence the choice of appropriate portfolio of assets. The investment returns are uncertain. Thus we have a semi-infinite programming problem. We solve a semi-infinite optimization problem of portfolio selection using the outer approximations methods. This approach can be considered as a developed Eaves-Zangwill method applying the multi-start technique in all of the iterations for the search of relevant constraints' parameters. The stochastic outer approximations method, successfully applied previously for robotics problems, Chebyshev approximation problems, air pollution and others, is based on the optimal criteria of quasi-optimal functions. As a result we obtain mathematical model and the optimal investment portfolio when yields are not clear from the beginning. Finally, we apply this algorithm to a specific case of a Colombian bank.

Keywords: outer approximation methods, portfolio problem, semi-infinite programming, numerial solution

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Authors: Eung-Seok Park, Tae-Chul Jeong, Hyun-Jong Park, Hyun-Woo Jun, Dong-Woo Kang, Ju Lee

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This presents a methodology to determine detail design directions of an 150kW-class IPMSM (interior permanent magnet synchronous motor) and its detail design. The basic design of the stator and rotor was conducted. After dividing the designed models into the best cases and the worst cases based on rotor shape parameters, Sensitivity analysis and 3D Voltage-Inductance Map (3D EL-Map) parameters were analyzed. Then, the design direction for the final model was predicted. Based on the prediction, the final model was extracted with Trend analysis. Lastly, the final model was validated with experiments.

Keywords: PMSM, optimal design, rotor design, voltage-inductance map

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Authors: Raman Kumar Singh

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Urbanization and economic growth are considered to be the most striking features of the past century. There is currently a radical demographic shift in progress worldwide, wherein people are moving from rural to urban areas at an increasing rate. The UN-Habitat report 2005 indicates that in 2025, 61 per cent of the 5 billion world population will reside in the urban areas with about 85 per cent of the development process taking place in the urban hinterlands widely referred to as ‘peri-urban’, ‘suburbs’, ‘urban fringe’, ‘city edge’, ‘metropolitan shadow’, or ‘urban sprawl’. In this context the study is broadly concerned with understanding the development of the industrial hub in the Gurgaon and its impact on the immediate neighbourhood. However studies have revealed that with the increase of industrial development the growth pattern changes rapidly, not only the growth of the urban area but the overall economy shifts from more agrarian to non-agrarian, with the change in the occupational pattern of the people. The process is mainly known as tertiarization, where a number of tertiary activities increase in comparison to primary or secondary. The change in the occupational pattern creates a pull factor on its immediate neighbourhood, which triggers the in- migrations from the rural areas as people come in the core urban area in search of the better job opportunities and increased standards of living. But this gives way to the unplanned growth of the urban fringe and the villages which tend to accommodate the migrants and in turn the pressure on the socio-economic infrastructure increases. Therefore, it becomes increasing necessary for the government institution and policy level intervention to provide an overall socio-economic growth along with rapid industrial growth.

Keywords: policy intervention, urban morphology, urban industrial hub, livelihood transformation

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Authors: K. Y. Tseng, C. Y. Wu

Abstract:

This paper employs a heuristic algorithm to solve engineering problems including truss structure optimization and optimal chiller loading (OCL) problems. Two different type algorithms, real-valued differential evolution (DE) and modified binary differential evolution (MBDE), are successfully integrated and then can obtain better performance in solving engineering problems. In order to demonstrate the performance of the proposed algorithm, this study adopts each one testing case of truss structure optimization and OCL problems to compare the results of other heuristic optimization methods. The result indicates that the proposed algorithm can obtain similar or better solution in comparing with previous studies.

Keywords: differential evolution, Truss structure optimization, optimal chiller loading, modified binary differential evolution

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Authors: Sujay Bisht

Abstract:

The purpose of the study was to assess and examines the pattern of injury among the field hockey players at different field position during practice & game. It was hypothesized that the backfield might have the height rate of injury, followed by midfield. Methods: university level and national level male field hockey (N=60) are selected as a subject and requested to respond an anon questionnaire. Personal characteristics of each and individual players were also collected like (age, height, weight); field hockey professional information (level of play, year of experience, playing surface); players injury history (site, types, cause etc). The rates of injury per athlete per year were also calculated. Result: Around half of the injury occurred were to the lower limbs (49%) followed by head and face (30%), upper limbs (19%) and torso region (2%). Injuries included concussion, wounds, broken nose, ligament sprain, dislocation, fracture, and muscles strain and knee injury. The ligament sprain is the highest rate (40%) among the other types of injuries. After investigation and evaluation backfield players had the highest rate of risk of injury (1.10 injury/athletes-year) followed by midfield players (0.70 injury/athlete-year), forward players (0.45 injury/athlete-year) & goalkeeper was (0.37 injury/athlete-year). Conclusion: Due to the different field position the pattern & rate of injury were different. After evaluation, lower limbs had the highest rate of injury followed by head and face, upper limbs and torso respectively. It also revealed that not only there is a difference in the rate of injury between playing the position, but also in the types of injury sustain at a different position.

Keywords: trauma, sprain, strain, astroturf, acute injury

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Authors: Alvaro Javier Ortega

Abstract:

A large number of companies face the challenge of matching highly-skilled professionals to high-end positions by human resource deployment professionals. However, when the professional list and tasks to be matched are larger than a few dozens, this process result is far from optimal and takes a long time to be made. Therefore, an automated assignment algorithm for this workforce management problem is needed. The majority of companies are divided into several sectors or departments, where trained employees with different experience levels deal with a large number of tasks daily. Also, the execution order of all tasks is of mater consequence, due to some of these tasks just can be run it if the result of another task is provided. Thus, a wrong execution order leads to large waiting times between consecutive tasks. The desired goal is, therefore, creating accurate matches and a near-optimal execution order that maximizes the number of tasks performed and minimizes the idle time of the expensive skilled employees. The problem described before can be model as a mixed-integer non-linear programming (MINLP) as it will be shown in detail through this paper. A large number of MINLP algorithms have been proposed in the literature. Here, genetic algorithm solutions are considered and a comparison between two different mutation approaches is presented. The simulated results considering different complexity levels of assignment decisions show the appropriateness of the proposed model.

Keywords: employees, genetic algorithm, industry management, workforce

Procedia PDF Downloads 154