Search results for: Asymmetric Traveling Salesman Problem

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: Kimberly McCabe

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The trafficking of women and children for abuse and exploitation is not a new problem under the umbrella of human trafficking; however, over the last decade, the problem has attracted increased attention from international governments and non-profits attempting to reduce victimization and provide services for survivors. Research on human trafficking suggests that the trafficking of human beings is, largely, a symptom of poverty. As the trafficking of human beings may be viewed as a response to the demand for people for various forms of exploitation, a product of poverty, and a consequence of the subordinate positions of women and children in society, it reaches beyond randomized victimization. Hence, human trafficking, and especially the trafficking of women and children, goes beyond the realm of poorness. Therefore, to begin to understand the reasons for the existence of human trafficking, one must identify and consider not only the immediate causes but also those underlying structural determinants that facilitate this form of victimization. Specifically, one must acknowledge the economic, social, and cultural factors that support human trafficking. This research attempts to study human trafficking at the country level by focusing on economic, social, and cultural characteristics. This study focuses on inequality and, in particular, gender inequality as related to legislative attempts to address human trafficking. Within the design of this project is the use of the US State Department’s tier classification system for Trafficking in Persons (TIP) and the USA CIA Fact Sheet of country characteristics for over 150 countries in an attempt to model legal outcomes as related to human trafficking. Results of this research demonstrate the significance of characteristics beyond poverty as related to country-level responses to human trafficking.

Keywords: child trafficking, gender inequality, human trafficking, inequality

Procedia PDF Downloads 241

Authors: G. Espinosa Garza, I. Loera, N. Antonyan

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In the last decades, teaching in particular engineering subjects is going through a significative problem. A quick evaluation of the entrepreneurial surroundings makes it more difficult for students to identify the course contents with real situations related with their future professions. Proposing teaching through challenges or problem-based projects, and real-life situations is turning into an important challenge for any university-level educator. The objective of this work is to present the educational experience and the investigation results taken through the Project Viability course, done by a group of professors and students from the Technologic of Monterrey. Currently, in Mexico, the orange peels are considered a dispose and they are not being utilized as an alternative to create subproducts. However, there is a great opportunity in its use as a raw material with the goal to originate the waste from the local citric firms or business. The project challenge consisted in the development of edible products from the orange peel with the intention to generate new healthy products. With this project, apart from the obtainment of the original results, the accomplishment consisted in creating a learning atmosphere, where students together with the professors were able to plan, evaluate, and implement the project related with the creative, innovative, and sustainable processes with the goal to apply it in the development of local solutions. In the present article, the pedagogic methodologies that allowed to carry out this project will be discussed.

Keywords: engineering subjects, learning project, orange peel, sustainable process

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Authors: M. Ahmadi, M. Kafil, H. Ebrahimi

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Nowadays, induction motors have a significant role in industries. Condition monitoring (CM) of this equipment has gained a remarkable importance during recent years due to huge production losses, substantial imposed costs and increases in vulnerability, risk, and uncertainty levels. Motor current signature analysis (MCSA) is one of the most important techniques in CM. This method can be used for rotor broken bars detection. Signal processing methods such as Fast Fourier transformation (FFT), Wavelet transformation and Empirical Mode Decomposition (EMD) are used for analyzing MCSA output data. In this study, these signal processing methods are used for broken bar problem detection of Mobarakeh steel company induction motors. Based on wavelet transformation method, an index for fault detection, CF, is introduced which is the variation of maximum to the mean of wavelet transformation coefficients. We find that, in the broken bar condition, the amount of CF factor is greater than the healthy condition. Based on EMD method, the energy of intrinsic mode functions (IMF) is calculated and finds that when motor bars become broken the energy of IMFs increases.

Keywords: broken bar, condition monitoring, diagnostics, empirical mode decomposition, fourier transform, wavelet transform

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Authors: Omar Bouhassoun, Cristian Garrido, César Hueso

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The radiation shielding design is an optimization problem with multiple -constrained- objective functions (radiation dose, weight, price, etc.) that depend on several parameters (material, thickness, position, etc.). The classical approach for shielding design consists of a brute force trial-and-error process subject to previous designer experience. Therefore, the result is an empirical solution but not optimal, which can degrade the overall performance of the shielding. In order to automate the shielding design procedure, the IDOM Shielding Optimization Tool (ISOT) has been developed. This software combines optimization algorithms with the capabilities to read/write input files, run calculations, as well as parse output files for different radiation transport codes. In the first stage, the software was established to adjust the input files for two well-known Monte Carlo codes (MCNP and Serpent) and optimize the result (weight, volume, price, dose rate) using multi-objective genetic algorithms. Nevertheless, its modular implementation easily allows the inclusion of more radiation transport codes and optimization algorithms. The work related to the development of ISOT and its verification on a simple 3D multi-layer shielding problem using both MCNP and Serpent will be presented. ISOT looks very promising for achieving an optimal solution to complex shielding problems.

Keywords: optimization, shielding, nuclear, genetic algorithm

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Authors: Thomas Turner

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Due to the Covid-19 pandemic alternative ways of delivering dental education were required. As a result, many institutions moved teaching online. The impact of this is poorly understood. Is online problem-based learning (PBL) and case-based learning (CBL) effective and is it suitable in the post-pandemic era? PBL and CBL are both types of interactive, group-based learning which are growing in popularity within many dental schools. PBL was first introduced in the 1960’s and can be defined as learning which occurs from collaborative work to resolve a problem. Whereas CBL encourages learning from clinical cases, encourages application of knowledge and helps prepare learners for clinical practice. To evaluate the use of online PBL and CBL. A literature search was conducted using the CINAHL, Embase, PubMed and Web of Science databases. Literature was also identified from reference lists. Studies were only included from dental education. Seven suitable studies were identified. One of the studies found a high learner and facilitator satisfaction rate with online CBL. Interestingly one study found learners preferred CBL over PBL within an online format. A study also found, that within the context of distance learning, learners preferred a hybrid curriculum including PBL over a traditional approach. A further study pointed to the limitations of PBL within an online format, such as reduced interaction, potentially hindering the development of communication skills and the increased time and technology support required. An audience response system was also developed for use within CBL and had a high satisfaction rate. Interestingly one study found achievement of learning outcomes was correlated with the number of student and staff inputs within an online format. Whereas another study found the quantity of learner interactions were important to group performance, however the quantity of facilitator interactions was not. This review identified generally favourable evidence for the benefits of online PBL and CBL. However, there is limited high quality evidence evaluating these teaching methods within dental education and there appears to be limited evidence comparing online and faceto-face versions of these sessions. The importance of the quantity of learner interactions is evident, however the importance of the quantity of facilitator interactions appears to be questionable. An element to this may be down to the quality of interactions, rather than just quantity. Limitations of online learning regarding technological issues and time required for a session are also highlighted, however as learners and facilitators get familiar with online formats, these may become less of an issue. It is also important learners are encouraged to interact and communicate during these sessions, to allow for the development of communication skills. Interestingly CBL appeared to be preferred to PBL in an online format. This may reflect the simpler nature of CBL, however further research is required to explore this finding. Online CBL and PBL appear promising, however further research is required before online formats of these sessions are widely adopted in the post-pandemic era.

Keywords: case-based learning, online, problem-based learning, remote, virtual

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Authors: Andrey V. Timofeev

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The practical efficient approach is suggested to estimate the high-speed objects instant bounds in C-OTDR monitoring systems. In case of super-dynamic objects (trains, cars) is difficult to obtain the adequate estimate of the instantaneous object localization because of estimation lag. In other words, reliable estimation coordinates of monitored object requires taking some time for data observation collection by means of C-OTDR system, and only if the required sample volume will be collected the final decision could be issued. But it is contrary to requirements of many real applications. For example, in rail traffic management systems we need to get data off the dynamic objects localization in real time. The way to solve this problem is to use the set of statistical independent parameters of C-OTDR signals for obtaining the most reliable solution in real time. The parameters of this type we can call as 'signaling parameters' (SP). There are several the SP’s which carry information about dynamic objects instant localization for each of C-OTDR channels. The problem is that some of these parameters are very sensitive to dynamics of seismoacoustic emission sources but are non-stable. On the other hand, in case the SP is very stable it becomes insensitive as a rule. This report contains describing the method for SP’s co-processing which is designed to get the most effective dynamic objects localization estimates in the C-OTDR monitoring system framework.

Keywords: C-OTDR-system, co-processing of signaling parameters, high-speed objects localization, multichannel monitoring systems

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Authors: Hongshan Guo

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Ground-source heat pumps provide stable and reliable heating and cooling when designed properly. The confounding effect of the borehole depth for a GSHP system, however, is rarely taken into account for any optimization: the determination of the borehole depth usually comes prior to the selection of corresponding system components and thereafter any optimization of the GSHP system. The depth of the borehole is important to any GSHP system because the shallower the borehole, the larger the fluctuation of temperature of the near-borehole soil temperature. This could lead to fluctuations of the coefficient of performance (COP) for the GSHP system in the long term when the heating/cooling demand is large. Yet the deeper the boreholes are drilled, the more the drilling cost and the operational expenses for the circulation. A controller that reads different building load profiles, optimizing for the smallest costs and temperature fluctuation at the borehole wall, eventually providing borehole depth as the output is developed. Due to the nature of the nonlinear dynamic nature of the GSHP system, it was found that between conventional optimal controller problem and model predictive control problem, the latter was found to be more feasible due to a possible history of both the trajectory during the iteration as well as the final output could be computed and compared against. Aside from a few scenarios of different weighting factors, the resulting system costs were verified with literature and reports and were found to be relatively accurate, while the temperature fluctuation at the borehole wall was also found to be within acceptable range. It was therefore determined that the MPC is adequate to optimize for the investment as well as the system performance for various outputs.

Keywords: geothermal borehole, MPC, dynamic modeling, simulation

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Authors: Bircan Demiral

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Cognitive radio (CR) is the promising technology that addresses the spectrum scarcity problem for future wireless communications. Orthogonal Frequency Division Multiplexing (OFDM) technology provides more power band ratios for cognitive radio networks (CRNs). While CR is a solution to the spectrum scarcity, it also brings up the capacity problem. In this paper, a novel power allocation algorithm that aims at maximizing the sum capacity in the OFDM based cognitive radio networks is proposed. Proposed allocation algorithm is based on the previously developed water-filling algorithm. To reduce the computational complexity calculating in water filling algorithm, proposed algorithm allocates the total power according to each subcarrier. The power allocated to the subcarriers increases sum capacity. To see this increase, Matlab program was used, and the proposed power allocation was compared with average power allocation, water filling and general power allocation algorithms. The water filling algorithm performed worse than the proposed algorithm while it performed better than the other two algorithms. The proposed algorithm is better than other algorithms in terms of capacity increase. In addition the effect of the change in the number of subcarriers on capacity was discussed. Simulation results show that the increase in the number of subcarrier increases the capacity.

Keywords: cognitive radio network, OFDM, power allocation, water filling

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Authors: Digambar J. Darekar, Sharvari D. Darekar

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Childlessness is a universal problem. It particularly affects the mental health of childless couple. It leads to anxiety, frustration, nervousness, depression, loneliness, helplessness, hopelessness, etc. After reviewing the literature, it is found that mental health of married couples is negatively related to childlessness. To understand emotional and psychological problems of a childless couple, researcher surveyed and interviewed 50 childless couples with the help of medical practitioner and gynecologist. Personal adjustment and mental health inventory and marital adjustment inventory along with semi-structured interview questionnaire was used. On the basis of responses from the subject, distinction is made between the problems of male subjects and female subjects and common problem separately. The researcher found that childlessness leads to the conflict between in-laws, harassment, hopelessness, feeling of emptiness and vacuumed, frustration, lack of hope and desire for life, restlessness, loss of sleep, ideas of committing suicide, increased emotional distance and disturbed marital life. The childlessness leads to sorrow for women and anger for men. Men turns towards addiction and women tend to avoid social contact and face problems of social adjustments. Childless couples are sufferers of personal and marital adjustment problems which in turn affect their mental health adversely.

Keywords: childlessness, marital adjustments, mental health, social adjustment

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Authors: E. Montesinos-Pedro, L. G. Toscano-Flores, N. Domínguez-Ramírez

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Water scarcity is a worldwide issue, coupled with climate change is a relevant problem, that affect not only large cities, but also rural areas. The Municipality of Santiago Tilantongo belongs to the district of Nochixtlán Oaxaca, it’s built up from 14 communities, one of them San Martin de las Palmas. This community was founded in 1900, at that time the inhabitants were supplied with water through rivers of the region which were abundant (they used containers filled in the river for that purpose); However, over the years the level of the rivers began to drop and in 1994 specific wells were located to store water and at the same time make it drinkable, this whit support of the state of Oaxaca and the program Procampo. By the year 2000 the shortage of water in the supply sources was notorious, the community requested support from the Oaxaca State government to solve the problem. The government’s response consisted in the implementation of ferro-cement tanks (2005) and water wells (2010), both for rainwater collection, Hower, it was not enough. Now days the community has a population of 60 inhabitants who have resisted and adapted to water scarcity, not only with the programs implemented by the government, but they also have implemented important structural analysis strategies. The objective of this research is to know the adaptation strategies used by the community to analyze them and propose improvements for water conservation and mitigation of this scarcity.

Keywords: adaptation, climate change, mitigation, resiliencia

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Authors: Irina A. Gudkova, Yousra Demigha

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Scientific research is moving more and more towards the study of complex systems in several areas of economics, biology physics, and computer science. In this paper, we will work on complex systems in communication networks, Wireless Sensor Networks (WSN) that are considered as stochastic systems composed of interacting entities. The current advancements of the sensing in computing and communication systems is an investment ground for research in several tracks. A detailed presentation was made for the WSN, their use, modeling, different problems that can occur in their application and some solutions. The main goal of this work reintroduces the idea of mean field method since it is a powerful technique to solve this type of models especially systems that evolve according to a Continuous Time Markov Chain (CTMC). Modeling of a CTMC has been focused; we obtained a large system of interacting Continuous Time Markov Chain with population entities. The main idea was to work on one entity and replace the others with an average or effective interaction. In this context to make the solution easier, we consider a wireless sensor network as a multi-body problem and we reduce it to one body problem. The method was applied to a system of WSN modeled as a Markovian queue showing the results of the used technique.

Keywords: Continuous-Time Markov Chain, Hidden Markov Chain, mean field method, Wireless sensor networks

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Authors: S. Thanabanjerdsin, F. Srisuriyachai, J. Chewaroungroj

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Drilling horizontal well is one of the most cost-effective method to exploit reservoir by increasing exposure area between well and formation. Together with horizontal well technology, intelligent completion is often co-utilized to increases petroleum production by monitoring/control downhole production. Combination of both technological results in an opportunity to lower water cresting phenomenon, a detrimental problem that does not lower only oil recovery but also cause environmental problem due to water disposal. Flow of reservoir fluid is a result from difference between reservoir and wellbore pressure. In horizontal well, reservoir fluid around the heel location enters wellbore at higher rate compared to the toe location. As a consequence, Oil-Water Contact (OWC) at the heel side of moves upward relatively faster compared to the toe side. This causes the well to encounter an early water encroachment problem. Installation of Inflow Control Valve (ICV) in particular sections of horizontal well can involve several parameters such as number of ICV, water cut constrain of each valve, length of each section. This study is mainly focused on optimization of ICV configuration to minimize water production and at the same time, to enhance oil production. A reservoir model consisting of high aspect ratio of oil bearing zone to underneath aquifer is drilled with horizontal well and completed with variation of ICV segments. Optimization of the horizontal well configuration is firstly performed by varying number of ICV, segment length, and individual preset water cut for each segment. Simulation results show that installing ICV can increase oil recovery factor up to 5% of Original Oil In Place (OOIP) and can reduce of produced water depending on ICV segment length as well as ICV parameters. For equally partitioned-ICV segment, more number of segment results in better oil recovery. However, number of segment exceeding 10 may not give a significant additional recovery. In first production period, deformation of OWC strongly depends on number of segment along the well. Higher number of segment results in smoother deformation of OWC. After water breakthrough at heel location segment, the second production period begins. Deformation of OWC is principally dominated by ICV parameters. In certain situations that OWC is unstable such as high production rate, high viscosity fluid above aquifer and strong aquifer, second production period may give wide enough window to ICV parameter to take the roll.

Keywords: horizontal well, water cresting, inflow control valve, reservoir simulation

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Authors: Tarek Soliman Mostafa Soliman Al-Nana'i

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There are non-steady voiced augments in the Semitic languages, and in the morphological and structural augmentation, two sounds were augments in all Semitic languages at the level of the spoken language and two letters at the level of the written language, which are the hamza and the ta’. This research studies only the second of them; Therefore, we defined it as “The Voiceless Dental- alveolar common augment” (VDACA) to distinguish it from the glottal sound “Hamza”, first, middle, or last, in a noun or in a verb, in Arabic and its equivalent in the Semitic languages. What is meant by “VDACA” is the ta’ that is in addition to the root of the word at the morphological level: the word “voiceless” takes out the voiced sounds that we studied before, and the “dental- alveolar common augment” takes out the laryngeal sound of them, which is the “Hamza”: and the word “common” brings out the uncommon voiceless sounds, which are sīn, shīn, and hā’. The study is limited to the ta' alone among the Arabic sounds, and this title faced a problem in identifying it with the ta'. Because the designation of the ta is not the same in most Semitic languages. Hebrew, for example, has “tav” and is pronounced with the voiced fa (v), which is not in Arabic. It is called different names in other Semitic languages, such as “taw” or “tAu” in old Syriac. And so on. This goes hand in hand with the insistence on distance from the written level and the reference to the phonetic aspect in this study that is closely and closely linked to the morphological level. Therefore, the study is “morphophonemic”. What is meant by Semitic languages in this study are the following: Akkadian, Ugaritic, Hebrew, Syriac, Mandaean, Ge'ez, and Amharic. The problem of the study is the agreement or difference between these languages in the position of that augment, first, middle, or last. And in determining the distinguishing characteristics of each language from the other. As for the study methodology, it is determined by the comparative approach in Semitic languages, which is based on the descriptive approach for each language. The study is divided into an introduction, four sections, and a conclusion: Introduction: It included the subject of the study, its importance, motives, problem, methodology, and division. The first section: VDACA as a non-common phoneme. The second: VDACA as a common phoneme. The third: VDACA as a functional morpheme. The fourth section: Commentary and conclusion with the most important results. The positions of VDACA in Arabic and other Semitic languages, and in nouns and verbs, were limited to first, middle, and last. The research identified the individual addition, which is common with other augments, and the research proved that this augmentation is constant in all Semitic languages, but there are characteristics that distinguish each language from the other.

Keywords: voiceless -, dental- alveolar, augment, Arabic - semitic languages

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Authors: Jaechoul Shin, Juhwan Hwang

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In case of applying the BIM method to the civil engineering in the area of free formed structure, we can expect comparatively high rate of construction productivity as it is in the building engineering area. In this research, we developed quantity calculation error applying it to earthwork and bridge construction (e.g. PSC-I type segmental girder bridge amd integrated bridge of steel I-girders and inverted-Tee bent cap), NATM (New Austrian Tunneling Method) tunnel construction, retaining wall construction, culvert construction and implemented BIM based 3D modeling quantity survey. we confirmed high reliability of the BIM-based method in structure work in which errors occurred in range between -6% ~ +5%. Especially, understanding of the problem and improvement of the existing 2D-CAD based of quantity calculation through rock type quantity calculation error in range of -14% ~ +13% of earthwork quantity calculation. It is benefit and applicability of BIM method in civil engineering. In addition, routine method for quantity of earthwork has the same error tolerance negligible for that of structure work. But, rock type's quantity calculated as the error appears significantly to the reliability of 2D-based volume calculation shows that the problem could be. Through the estimating quantity of earthwork based 3D-BIM, proposed method has better reliability than routine method. BIM, as well as the design, construction, maintenance levels of information when you consider the benefits of integration, the introduction of BIM design in civil engineering and the possibility of applying for the effectiveness was confirmed.

Keywords: BIM, 3D modeling, 3D-BIM, quantity of earthwork

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Authors: Alper Akin, Ibrahim Aydogdu

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This study presents a hybrid metaheuristic algorithm to obtain optimum designs for steel space buildings. The optimum design problem of three-dimensional steel frames is mathematically formulated according to provisions of LRFD-AISC (Load and Resistance factor design of American Institute of Steel Construction). Design constraints such as the strength requirements of structural members, the displacement limitations, the inter-story drift and the other structural constraints are derived from LRFD-AISC specification. In this study, a hybrid algorithm by using teaching-learning based optimization (TLBO) and harmony search (HS) algorithms is employed to solve the stated optimum design problem. These algorithms are two of the recent additions to metaheuristic techniques of numerical optimization and have been an efficient tool for solving discrete programming problems. Using these two algorithms in collaboration creates a more powerful tool and mitigates each other’s weaknesses. To demonstrate the powerful performance of presented hybrid algorithm, the optimum design of a large scale steel building is presented and the results are compared to the previously obtained results available in the literature.

Keywords: optimum structural design, hybrid techniques, teaching-learning based optimization, harmony search algorithm, minimum weight, steel space frame

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Authors: Katerina Koliou, Scott Parr, Evangelos Kaisar

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The surface transportation of freight is particularly vulnerable to storm and hurricane disasters, while at the same time, it is the primary transportation mode for delivering medical supplies, fuel, water, and other essential goods. To better plan for commercial vehicles during an evacuation, it is necessary to understand how these vehicles travel during an evacuation and determine if this travel is different from the general public. The research investigation used Florida's statewide continuous-count station traffic volumes, where then compared between years, to identify locations where traffic was moving differently during the evacuation. The data was then used to identify days on which traffic was significantly different between years. While the literature on auto-based evacuations is extensive, the consideration of freight travel is lacking. To better plan for commercial vehicles during an evacuation, it is necessary to understand how these vehicles travel during an evacuation and determine if this travel is different from the general public. The goal of this research was to investigate the movement of vehicles by classification, with an emphasis on freight during two major evacuation events: hurricanes Irma (2017) and Michael (2018). The methodology of the research was divided into three phases: data collection and management, spatial analysis, and temporal comparisons. Data collection and management obtained continuous-co station data from the state of Florida for both 2017 and 2018 by vehicle classification. The data was then processed into a manageable format. The second phase used geographic information systems (GIS) to display where and when traffic varied across the state. The third and final phase was a quantitative investigation into which vehicle classifications were statistically different and on which dates statewide. This phase used a two-sample, two-tailed t-test to compare sensor volume by classification on similar days between years. Overall, increases in freight movement between years prevented a more precise paired analysis. This research sought to identify where and when different classes of vehicles were traveling leading up to hurricane landfall and post-storm reentry. Of the more significant findings, the research results showed that commercial-use vehicles may have underutilized rest areas during the evacuation, or perhaps these rest areas were closed. This may suggest that truckers are driving longer distances and possibly longer hours before hurricanes. Another significant finding of this research was that changes in traffic patterns for commercial-use vehicles occurred earlier and lasted longer than changes for personal-use vehicles. This finding suggests that commercial vehicles are perhaps evacuating in a fashion different from personal use vehicles. This paper may serve as the foundation for future research into commercial travel during evacuations and explore additional factors that may influence freight movements during evacuations.

Keywords: evacuation, freight, travel time, evacuation

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Authors: Reza Alikhani

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This research focuses on the establishment of horizontal cooperation among companies to enhance their operational efficiency and competitiveness. The study proposes an approach to horizontal collaboration, called coalition configuration, which involves partnering companies sharing distribution centers in a network design problem. The paper investigates which coalition should be formed in each distribution center to minimize the total cost of the network. Moreover, potential uncertainties, such as operational and disruption risks, are considered during the collaborative design phase. To address this problem, a two-stage robust optimization model for collaborative distribution network design under surging demand and facility disruptions is presented, along with a column-and-constraint generation algorithm to obtain exact solutions tailored to the proposed formulation. Extensive numerical experiments are conducted to analyze solutions obtained by the model in various scenarios, including decisions ranging from fully centralized to fully decentralized settings, collaborative versus non-collaborative approaches, and different amounts of uncertainty budgets. The results show that the coalition formation mechanism proposes some solutions that are competitive with the savings of the grand coalition. The research also highlights that collaboration increases network flexibility and resilience while reducing costs associated with demand and capacity uncertainties.

Keywords: logistics, warehouse sharing, robust facility location, collaboration for resilience

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Authors: Loai AbdAllah, Mahmoud Kaiyal

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Missing values in real-world datasets are a common problem. Many algorithms were developed to deal with this problem, most of them replace the missing values with a fixed value that was computed based on the observed values. In our work, we used a distance function based on Bhattacharyya distance to measure the distance between objects with missing values. Bhattacharyya distance, which measures the similarity of two probability distributions. The proposed distance distinguishes between known and unknown values. Where the distance between two known values is the Mahalanobis distance. When, on the other hand, one of them is missing the distance is computed based on the distribution of the known values, for the coordinate that contains the missing value. This method was integrated with Wikaya, a digital health company developing a platform that helps to improve prevention of chronic diseases such as diabetes and cancer. In order for Wikaya’s recommendation system to work distance between users need to be measured. Since there are missing values in the collected data, there is a need to develop a distance function distances between incomplete users profiles. To evaluate the accuracy of the proposed distance function in reflecting the actual similarity between different objects, when some of them contain missing values, we integrated it within the framework of k nearest neighbors (kNN) classifier, since its computation is based only on the similarity between objects. To validate this, we ran the algorithm over diabetes and breast cancer datasets, standard benchmark datasets from the UCI repository. Our experiments show that kNN classifier using our proposed distance function outperforms the kNN using other existing methods.

Keywords: missing values, incomplete data, distance, incomplete diabetes data

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Authors: Habtamu Garoma Debela, Gemechis File Duressa

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In this work, our primary interest is to provide ε-uniformly convergent numerical techniques for solving singularly perturbed semilinear boundary value problems with non-local boundary condition. These singular perturbation problems are described by differential equations in which the highest-order derivative is multiplied by an arbitrarily small parameter ε (say) known as singular perturbation parameter. This leads to the existence of boundary layers, which are basically narrow regions in the neighborhood of the boundary of the domain, where the gradient of the solution becomes steep as the perturbation parameter tends to zero. Due to the appearance of the layer phenomena, it is a challenging task to provide ε-uniform numerical methods. The term 'ε-uniform' refers to identify those numerical methods in which the approximate solution converges to the corresponding exact solution (measured to the supremum norm) independently with respect to the perturbation parameter ε. Thus, the purpose of this work is to develop, analyze, and improve the ε-uniform numerical methods for solving singularly perturbed problems. These methods are based on nonstandard fitted finite difference method. The basic idea behind the fitted operator, finite difference method, is to replace the denominator functions of the classical derivatives with positive functions derived in such a way that they capture some notable properties of the governing differential equation. A uniformly convergent numerical method is constructed via nonstandard fitted operator numerical method and numerical integration methods to solve the problem. The non-local boundary condition is treated using numerical integration techniques. Additionally, Richardson extrapolation technique, which improves the first-order accuracy of the standard scheme to second-order convergence, is applied for singularly perturbed convection-diffusion problems using the proposed numerical method. Maximum absolute errors and rates of convergence for different values of perturbation parameter and mesh sizes are tabulated for the numerical example considered. The method is shown to be ε-uniformly convergent. Finally, extensive numerical experiments are conducted which support all of our theoretical findings. A concise conclusion is provided at the end of this work.

Keywords: nonlocal boundary condition, nonstandard fitted operator, semilinear problem, singular perturbation, uniformly convergent

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Authors: Manana Lobzhanidze

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Introduction: The paper will argue that labor migration is the most important problem Georgia faces today. The structure of labor migration by age and gender of Georgia is analyzed. The main driving factors of circular labor migration during the last ten years are identified. While studying migration, it is necessary to discuss the interconnection of economic, social, and demographic features, also taking into consideration the policy of state regulations in terms of education and professional training. Methodology: Different research methods are applied in the presented paper: statistical, such as selection, grouping, observation, trend, and qualitative research methods, namely; analysis, synthesis, induction, deduction, comparison ones. Main Findings: Labour migrants are filling the labor market as a low salary worker. The main positive feedback of migration from developing countries is poverty eradication, but this process is accompanied by problems, such as 'Brain Drain'. The country loses an important part of its intellectual potential, and it is invested by households or state itself. Conclusions: Labor migration is characterized to be temporary, but socio-economic problems of the country often push the labor migration in the direction of longterm and illegal migration. Countries with developed economies try to stricter migration policy and fight illegal migration with different methods; circular migration helps solve this problem. Conclusions and recommendations are included about circular labor migration consequences in Georgia and its influence on the reduction of unemployment level.

Keywords: migration, circular labor migration, labor migration employment, unemployment

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Authors: Weiju Zhou, Alex Hopkins, Ruoling Chen

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Background: China has increased the gap in income between richer and poorer over the past 40 years, and the number of deaths from people with angina has been rising. It is unclear whether socioeconomic status (SES) is associated with increased mortality in older people with angina. Methods: Data from a cohort study of 2,380 participants aged ≥ 65 years, who were randomly recruited from 5-province urban communities were examined in China. The cohort members were interviewed to record socio-demographic and risk factors and document doctor-diagnosed angina at baseline and were followed them up in 3-10 years, including monitoring vital status. Multivariate Cox regression models were employed to examine all-cause mortality in relation to low SES. Results: The cohort follow-up identified 373 deaths occurred; 41 deaths in 208 angina patients. Compared to participants without angina (n=2,172), patients with angina had increased mortality (multivariate adjusted hazard ratio (HR) was 1.41, 95% CI 1.01-1.97). Within angina patients, the risk of mortality increased with low satisfactory income (2.51, 1.08-5.85) and having financial problem (4.00, 1.07-15.00), but significantly with levels of education and occupation. In non-angina participants, none of these four SES indicators were associated with mortality. There was a significant interaction effect between angina and low satisfactory income on mortality. Conclusions: In China, having low income and financial problem increase mortality in older people with angina. Strategies to improve economic circumstances in older people could help reduce inequality in angina survival.

Keywords: angina, mortality, older people, socio-economic status

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Authors: Alvaro Javier Ortega

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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

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Authors: Jiao Sun, Li Pan, Shijun Liu

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Recommender systems have been widely used in contemporary industry, and plenty of work has been done in this field to help users to identify items of interest. Collaborative Filtering (CF, for short) algorithm is an important technology in recommender systems. However, less work has been done in automobile recommendation system with the sharp increase of the amount of automobiles. What’s more, the computational speed is a major weakness for collaborative filtering technology. Therefore, using MapReduce framework to optimize the CF algorithm is a vital solution to this performance problem. In this paper, we present a recommendation of the users’ comment on industrial automobiles with various properties based on real world industrial datasets of user-automobile comment data collection, and provide recommendation for automobile providers and help them predict users’ comment on automobiles with new-coming property. Firstly, we solve the sparseness of matrix using previous construction of score matrix. Secondly, we solve the data normalization problem by removing dimensional effects from the raw data of automobiles, where different dimensions of automobile properties bring great error to the calculation of CF. Finally, we use the MapReduce framework to optimize the CF algorithm, and the computational speed has been improved times. UV decomposition used in this paper is an often used matrix factorization technology in CF algorithm, without calculating the interpolation weight of neighbors, which will be more convenient in industry.

Keywords: collaborative filtering, recommendation, data normalization, mapreduce

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Authors: S. R. Santhanam

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A gifted child is one who gives evidence of creativity, good memory, rapid learning. In mathematics, a teacher often comes across some gifted children and they exhibit the following characteristics: unusual alertness, enjoying solving problems, getting bored on repetitions, self-taught, going beyond what teacher taught, ask probing questions, connecting unconnected concepts, vivid imagination, readiness for research work, perseverance of a topic. There are two main areas of research carried out on them: 1)identifying gifted children, 2) interacting and channelizing them. A lack of appropriate recognition will lead the gifted child demotivated. One of the main findings is if proper attention and nourishment are not given then it leads a gifted child to become depressed, underachieving, fail to reach their full potential and sometimes develop negative attitude towards school and study. After identifying them, a mathematics teacher has to develop them into a fall fledged achiever. The responsibility of the teacher is enormous. The teacher has to be resourceful and patient. But interacting with them one finds a lot of surprises and awesomeness. The elementary algebraic identities like (a+b)(a-b)=a²-b², expansion of like (a+b)²(a-b)² and others are taught to students, of age group 13-15 in India. An average child will be satisfied with a single proof and immediate application of these identities. But a gifted child expects more from the teacher and at one stage after a little training will surpass the teacher also. In this short paper, the author shares his experience regarding teaching algebraic identities to gifted children. The following problem was given to a set of 10 gifted children of the specified age group: If a natural number ‘n’ to expressed as the sum of the two squares, will 2n also be expressed as the sum of two squares? An investigation has been done on what multiples of n satisfying the criterion. The attempts of the gifted children were consolidated and conclusion was drawn. A second problem was given to them as: can two natural numbers be found such that the difference of their square is 3? After a successful solution, more situations were analysed. As a third question, the finding of the sign of an algebraic expression in three variables was analysed. As an example: if a,b,c are real and unequal what will be sign of a²+4b²+9c²-4ab-12bc-6ca? Apart from an expression as a perfect square what other methods can be employed to prove an algebraic expression as positive negative or non negative has been analysed. Expressions like 4x²+2y²+13y²-2xy-4yz-6zx were given, and the children were asked to find the sign of the expression for all real values of x,y and z. In all investigations, only basic algebraic identities were used. As a next probe, a divisibility problem was initiated. When a,b,c are natural numbers such that a+b+c is at least 6, and if a+b+c is divisible by 6 then will 6 divide a³+b³+c³. The gifted children solved it in two different ways.

Keywords: algebraic identities, gifted children, Indian scenario, research

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Authors: Paolo Fantozzi, Luigi Laura, Umberto Nanni

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The problem of Entity relation discovery in structured data, a well covered topic in literature, consists in searching within unstructured sources (typically, text) in order to find connections among entities. These can be a whole dictionary, or a specific collection of named items. In many cases machine learning and/or text mining techniques are used for this goal. These approaches might be unfeasible in computationally challenging problems, such as processing massive data streams. A faster approach consists in collecting the cooccurrences of any two words (entities) in order to create a graph of relations - a cooccurrence graph. Indeed each cooccurrence highlights some grade of semantic correlation between the words because it is more common to have related words close each other than having them in the opposite sides of the text. Some authors have used sliding windows for such problem: they count all the occurrences within a sliding windows running over the whole text. In this paper we generalise such technique, coming up to a Weighted-Distance Sliding Window, where each occurrence of two named items within the window is accounted with a weight depending on the distance between items: a closer distance implies a stronger evidence of a relationship. We develop an experiment in order to support this intuition, by applying this technique to a data set consisting in the text of the Bible, split into verses.

Keywords: cooccurrence graph, entity relation graph, unstructured text, weighted distance

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Authors: Sagri Sharma

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Analysis of diseases integrating multi-factors increases the complexity of the problem and therefore, development of frameworks for the analysis of diseases is an issue that is currently a topic of intense research. Due to the inter-dependence of the various parameters, the use of traditional methodologies has not been very effective. Consequently, newer methodologies are being sought to deal with the problem. Supervised Learning Algorithms are commonly used for performing the prediction on previously unseen data. These algorithms are commonly used for applications in fields ranging from image analysis to protein structure and function prediction and they get trained using a known dataset to come up with a predictor model that generates reasonable predictions for the response to new data. Gene expression profiles generated by DNA analysis experiments can be quite complex since these experiments can involve hypotheses involving entire genomes. The application of well-known machine learning algorithm - Support Vector Machine - to analyze the expression levels of thousands of genes simultaneously in a timely, automated and cost effective way is thus used. The objectives to undertake the presented work are development of a methodology to identify genes relevant to Hepatocellular Carcinoma (HCC) from gene expression dataset utilizing supervised learning algorithms and statistical evaluations along with development of a predictive framework that can perform classification tasks on new, unseen data.

Keywords: artificial intelligence, biomarker, gene expression datasets, hepatocellular carcinoma, machine learning, supervised learning algorithms, support vector machine

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Authors: Sultan Çağırıcı, Arsida Bajrami, Beyza Aslan, Hacı Ali Erdoğan, Nejla Sözer Topçular, Dilek Bozkurt, Vildan Yayla

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Objective: Corticobasal syndrome (CBS) is phenotypically characterized by asymmetric rigidity, apraxia, alien-limb phenomenon, cortical sensory loss, dystonia and myoclonus. The underlying pathologies consists of corticobasal degeneration (CBD), progressive supra nuclear palsy, Alzheimer's, Creutzfeldt-Jakob and frontotemporal degeneration. CBD is a degenerative disease with clinical symptoms related to the prominent involvement of cerebral cortex and basal ganglia. CBD is a pathological diagnosis and antemortem clinical diagnosis may change many times. In this paper, we described the clinical features and discussed a cases diagnosed with symmetric CBS because of its rarity. Case: Seventy-five-year-old woman presented with a three years history of difficulty in speaking and reading. Involuntary hand jerks and slowness of movement also had began in the last six months. In the neurological examination the patient was alert but not fully oriented. The speech was non-fluent, word finding difficulties were present. Bilateral limited upgaze, bradimimia, bilateral positive cogwheel' rigidity but prominent in the right side, postural tremor and negative myoclonus during action on the left side were detected. Receptive language was normal but expressive language and repetition were impaired. Acalculia, alexia, agraphia and apraxia were also present. CSF findings were unremarkable except for elevated protein level (75 mg/dL). MRI revealed bilateral symmetric cortical atrophy prominent in the frontoparietal region. PET showed hypometabolism in the left caudate nucleus. Conclusion: The increase of data related to neurodegenerative disorders associated with dementia, movement disorders and other findings results in an expanded range of diagnosis and transitions between clinical diagnosis. When considered the age of onset, clinical symptoms, imaging findings and prognosis of this patient, clinical diagnosis was CBS and pathologic diagnosis as probable CBD. Imaging of CBD usually consist of typical asymmetry between hemispheres. Still few cases with clinical appearance of CBD may show symmetrical cortical cerebral atrophy. It is presented this case who was diagnosed with CBD although we found symmetrical cortical cerebral atrophy in MRI.

Keywords: symmetric cortical atrophy, corticobasal degeneration, corticobasal syndrome

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Authors: Ellen Van Den Oord, Julien Marie Jan Ferdinand Van Campen

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This article introduces a computationally efficient method for stacking sequence blending of composite structures. The computational efficiency makes the presented method especially interesting for composite structures with a large number of design regions. Optimization of composite structures with an unequal load distribution may lead to locally optimized thicknesses and ply orientations that are incompatible with one another. Blending constraints can be enforced to achieve structural continuity. In literature, many methods can be found to implement structural continuity by means of stacking sequence blending in one way or another. The complexity of the problem makes the blending of a structure with a large number of adjacent design regions, and thus stacking sequences, prohibitive. In this work the local stacking sequence optimization is preconditioned using a method found in the literature that couples the mechanical behavior of the laminate, in the form of lamination parameters, to blending constraints, yielding near-optimal easy-to-blend designs. The preconditioned design is then fed to the scheme using cellular automata that have been developed by the authors. The method is applied to the benchmark 18-panel horseshoe blending problem to demonstrate its performance. The computational efficiency of the proposed method makes it especially suited for composite structures with a large number of design regions.

Keywords: composite, blending, optimization, lamination parameters

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Authors: F. Mutelet, L. Cesari

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Development of safer and environmentally friendly processes and products is needed to achieve sustainable production and consumption patterns. Ionic liquids, which are of great interest to the chemical and related industries because of their attractive properties as solvents, should be considered. Ionic liquids are comprised of an asymmetric, bulky organic cation and a weakly coordinating organic or inorganic anion. A large number of possible combinations allows for the ability to ‘fine tune’ the solvent properties for a specific purpose. Physical and chemical properties of ionic liquids are not only influenced by the nature of the cation and the nature of cation substituents but also by the polarity and the size of the anion. These features infer to ionic liquids numerous applications, in organic synthesis, separation processes, and electrochemistry. Separation processes required a good knowledge of the behavior of organic compounds with ionic liquids. Gas chromatography is a useful tool to estimate the interactions between organic compounds and ionic liquids. Indeed, retention data may be used to determine infinite dilution thermodynamic properties of volatile organic compounds in ionic liquids. Among others, the activity coefficient at infinite dilution is a direct measure of solute-ionic liquid interaction. In this work, infinite dilution thermodynamic properties of volatile organic compounds in specific bis(trifluoromethylsulfonyl)imide based ionic liquids measured by gas chromatography is presented. It was found that apolar compounds are not miscible in this family of ionic liquids. As expected, the solubility of organic compounds is related to their polarity and hydrogen-bond. Through activity coefficients data, the performance of these ionic liquids was evaluated for different separation processes (benzene/heptane, thiophene/heptane and pyridine/heptane). Results indicate that ionic liquids may be used for the extraction of polar compounds (aromatics, alcohols, pyridine, thiophene, tetrahydrofuran) from aliphatic media. For example, 1-benzylpyridinium bis(trifluoromethylsulfonyl) imide and 1-cyclohexylmethyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide are more efficient for the extraction of aromatics or pyridine from aliphatics than classical solvents. Ionic liquids with long alkyl chain length present important capacity values but their selectivity values are low. In conclusion, we have demonstrated that specific bis(trifluoromethylsulfonyl)imide based ILs containing polar chain grafted on the cation (for example benzyl or cyclohexyl) increases considerably their performance in separation processes.

Keywords: interaction organic solvent-ionic liquid, gas chromatography, solvation model, COSMO-RS

Procedia PDF Downloads 109