Search results for: Quadratic Assignment Problem (QAP)

Authors: Erika Price, Lisa Johnson

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Cognitive and dispositional empathy is decreasing among students worldwide, particularly those at university. This paper looks at the effects of encouraging empathetic positioning in divisive topics by teaching listening skills and moral discovery to university students. Two groups of university students were given the assignment to interview individuals they disagreed with on social issues (e.g. abortion, gun control, legalization of drugs, involvement in Ukraine, etc.). One group completed the assignment with no other instruction. The second group completed the assignment after receiving instruction in active listening and Jonathan Haidt’s theory of moral foundations in politics. Results show that when students are given both active listening techniques and awareness of moral foundations, they are significantly more likely to have socially positive interactions with those they disagree with on issues as compared to those who listen passively to ideological opponents. As students interacted with those they disagreed with, they evidenced prosocial behaviors of acknowledgement, validation, and even commonalities with their opponents’ viewpoints, signifying a heartening trend of empathetic connection that is waning in students. The research suggests that empathy is a skill that can be nurtured by active listening but that it is more fully cultivated when paired with the concept of moral foundations underpinning political ideologies. These findings shed light on how to create more effective pedagogies for social and emotional learning, as well as inclusion.

Keywords: empathy, listening skills, moral discovery, pedagogy, prosocial behavior

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Authors: Ayoub Alsarhan, Ahmed Otoom, Yousef Kilani, Abdel-Rahman al-GHuwairi

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Wireless mesh networks (WMNs) have emerged recently to improve internet access and other networking services. WMNs provide network access to the clients and other networking functions such as routing, and packet forwarding. Spectrum scarcity is the main challenge that limits the performance of WMNs. Cognitive radio is proposed to solve spectrum scarcity problem. In this paper, we consider a cognitive wireless mesh network where unlicensed users (secondary users, SUs) can access free spectrum that is allocated to spectrum owners (primary users, PUs). Although considerable research has been conducted on spectrum allocation, spectrum assignment is still considered an important challenging problem. This problem can be solved using cognitive radio technology that allows SUs to intelligently locate free bands and access them without interfering with PUs. Our scheme considers several heuristics for spectrum allocation. These heuristics include: channel error rate, PUs activities, channel capacity and channel switching time. Performance evaluation of the proposed scheme shows that the scheme is able to allocate the unused spectrum for SUs efficiently.

Keywords: cognitive radio, dynamic spectrum access, spectrum management, spectrum sharing, wireless mesh networks

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Authors: Jing Yu, Hongyang Liu, Dong Hao

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On-Orbit Refueling is of great significance in extending space crafts' lifetime. The problem of minimum-fuel, time-fixed, Peer-to-Peer On-Orbit Refueling mission planning is addressed here with the particular aim of assigning fuel-insufficient satellites to the fuel-sufficient satellites and optimizing each rendezvous trajectory. Constraints including perturbation, communication link, sun illumination, hold points for different rendezvous phases, and sensor switching are considered. A planning model has established as well as a two-level solution method. The upper level deals with target assignment based on fuel equilibrium criterion, while the lower level solves constrained trajectory optimization using special maneuver strategies. Simulations show that the developed method could effectively resolve the Peer-to-Peer On-Orbit Refueling mission planning problem and deal with complex constraints.

Keywords: mission planning, orbital rendezvous, on-orbit refueling, space mission

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Authors: Amogh Katti, J. Sai Asritha, D. Nivedh, M. Kalyan Srinivas, B. Somnath Chakravarthi

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Today's modern education system uses Learning Management System (LMS) portals for the scoring and grading of student performances, to maintain student records, and teachers are instructed to accept assignments through online submissions of .pdf,.doc,.ppt, etc. There is a risk of data tampering in the traditional portals; we will apply the Blockchain model instead of this traditional model to avoid data tampering and also provide a decentralized mechanism for overall fairness. Blockchain technology is a better and also recommended model because of the following features: consensus mechanism, decentralized system, cryptographic encryption, smart contracts, Ethereum blockchain. The proposed system ensures data integrity and tamper-proof assignment submission and grading, which will be helpful for both students and also educators.

Keywords: education technology, learning management system, decentralized applications, blockchain

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Authors: M. Moharami Gargari, S. Javdani Zamani, A. Mohammadnejad, S. Abuali

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As maritime container transport is developing fast, the need arises for efficient operations at container terminals. One of the most important determinants of container handling efficiency is the productivity of quay cranes and internal transportation vehicles, which are responsible transporting of containers for unloading and loading operations for container vessels. For this reason, this paper presents an integrated mathematical model formulation for discrete berths with quay cranes and internal transportations vehicles. The problems have received increasing attention in the literature and the present paper deals with the integration of these interrelated problems. A new mixed integer linear formulation is developed for the Berth Allocation Problem (BAP), Quay Crane Assignment and Scheduling Problem (QCASP) and Internal Transportation Scheduling (ITS), which accounts for cranes and trucks positioning conditions.

Keywords: discrete berths, container terminal, truck scheduling, dynamic vessel arrival

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Authors: Alma Sobrevilla

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Using panel data from Mexico, this paper studies the determinants of women’s intrahousehold decision-making power using a generalised ordered logit model. Fixed effects estimations are also carried out to solve potential endogeneity coming from unobservable time-invariant factors. Finally, the paper analyses quadratic and community divergence effects of education on power. Results show heterogeneity in the effect of each of the determinants across different levels of decision-making power and suggest the presence of a significant quadratic effect of education. Having more education than the community average has a negative effect on power, supporting the notion that women tend to compensate their success outside the household with submissive attitudes at home.

Keywords: women, decision-making power, intrahousehold, Mexico

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Authors: Michael Johnson, Vincenzo Oliveri

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This work considers an interdisciplinary Problem-Based Learning (PBL) project developed by lecturers from the Aeronautical and Electronic and Computer Engineering departments at the University of Limerick. This “CANSAT” project utilises the CanSat can-sized satellite platform in order to allow students from aeronautical and electronic engineering to engage in a mixed format (online/face-to-face), interdisciplinary PBL assignment using a real-world platform and application. The project introduces students to the design, development, and construction of the CanSat system over the course of a single semester, enabling student(s) to apply their aeronautical and technical skills/capabilities to the realisation of a working CanSat system. In this case study, the CanSat kits are used to pivot the real-world, discipline-relevant PBL goal of designing, building, and testing the CanSat system with payload(s) from a traditional module-based setting to an online PBL setting. Feedback, impressions, benefits, and challenges identified through the semester are presented. Students found the project to be interesting and rewarding, with the interdisciplinary nature of the project appealing to them. Challenges and difficulties encountered are also addressed, with solutions developed between the students and facilitators to overcoming these discussed.

Keywords: problem-based learning, interdisciplinary, engineering, CanSATs

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Authors: Shahin Mirshekari, Mohammadreza Moradi, Hossein Jafari, Mehdi Jafari, Mohammad Ensaf

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This research employs Gaussian Process Regression (GPR) with an ensemble kernel, integrating Exponential Squared, Revised Matern, and Rational Quadratic kernels to analyze pharmaceutical sales data. Bayesian optimization was used to identify optimal kernel weights: 0.76 for Exponential Squared, 0.21 for Revised Matern, and 0.13 for Rational Quadratic. The ensemble kernel demonstrated superior performance in predictive accuracy, achieving an R² score near 1.0, and significantly lower values in MSE, MAE, and RMSE. These findings highlight the efficacy of ensemble kernels in GPR for predictive analytics in complex pharmaceutical sales datasets.

Keywords: Gaussian process regression, ensemble kernels, bayesian optimization, pharmaceutical sales analysis, time series forecasting, data analysis

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Authors: Jana Abu Ahmada, Zaineb Mohamed, Ilyasse Aksikas

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The linear quadratic control system of hyperbolic first order partial differential equations (PDEs) are presented. The aim of this research is to control chemical reactions. This is achieved by converting the PDEs system to ordinary differential equations (ODEs) using the method of characteristics to reduce the system to control it by using the integral reinforcement learning. The designed controller is applied to a catalytic cracking reactor. Background—Transport-Reaction systems cover a large chemical and bio-chemical processes. They are best described by nonlinear PDEs derived from mass and energy balances. As a main application to be considered in this work is the catalytic cracking reactor. Indeed, the cracking reactor is widely used to convert high-boiling, high-molecular weight hydrocarbon fractions of petroleum crude oils into more valuable gasoline, olefinic gases, and others. On the other hand, control of PDEs systems is an important and rich area of research. One of the main control techniques is feedback control. This type of control utilizes information coming from the system to correct its trajectories and drive it to a desired state. Moreover, feedback control rejects disturbances and reduces the variation effects on the plant parameters. Linear-quadratic control is a feedback control since the developed optimal input is expressed as feedback on the system state to exponentially stabilize and drive a linear plant to the steady-state while minimizing a cost criterion. The integral reinforcement learning policy iteration technique is a strong method that solves the linear quadratic regulator problem for continuous-time systems online in real time, using only partial information about the system dynamics (i.e. the drift dynamics A of the system need not be known), and without requiring measurements of the state derivative. This is, in effect, a direct (i.e. no system identification procedure is employed) adaptive control scheme for partially unknown linear systems that converges to the optimal control solution. Contribution—The goal of this research is to Develop a characteristics-based optimal controller for a class of hyperbolic PDEs and apply the developed controller to a catalytic cracking reactor model. In the first part, developing an algorithm to control a class of hyperbolic PDEs system will be investigated. The method of characteristics will be employed to convert the PDEs system into a system of ODEs. Then, the control problem will be solved along the characteristic curves. The reinforcement technique is implemented to find the state-feedback matrix. In the other half, applying the developed algorithm to the important application of a catalytic cracking reactor. The main objective is to use the inlet fraction of gas oil as a manipulated variable to drive the process state towards desired trajectories. The outcome of this challenging research would yield the potential to provide a significant technological innovation for the gas industries since the catalytic cracking reactor is one of the most important conversion processes in petroleum refineries.

Keywords: PDEs, reinforcement iteration, method of characteristics, riccati equation, cracking reactor

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Authors: Randall E. Osborne

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A four-step ‘humanities’ thought model has been used in an interdisciplinary course for almost two decades and has been proven to aid in student abilities to become more inclusive in their world view. Lack of tolerance for ambiguity can interfere with this progression so we developed an assignment that seems to have assisted students in developing more tolerance for ambiguity and, therefore, opened them up to make more progress on the critical thought model. A four-step critical thought model (built from a humanities education approach) is used in an interdisciplinary course on prejudice, discrimination, and hate in an effort to minimize egocentrism and promote sociocentrism in college students. A fundamental barrier to this progression is a lack of tolerance for ambiguity. The approach to the course is built on the assumption that Tolerance for Ambiguity (characterized by a dislike of uncertain, ambiguous or situations in which expected behaviors are uncertain, will like serve as a barrier (if tolerance is low) or facilitator (if tolerance is high) of active ‘engagement’ with assignments. Given that active engagement with course assignments would be necessary to promote an increase in critical thought and the degree of multicultural attitude change, tolerance for ambiguity inhibits critical thinking and, ultimately multicultural attitude change. As expected, those students showing the least amount of decrease (or even an increase) in intolerance across the semester, earned lower grades in the course than those students who showed a significant decrease in intolerance, t(1,19) = 4.659, p < .001. Students who demonstrated the most change in their Tolerance for Ambiguity (showed an increasing ability to tolerate ambiguity) earned the highest grades in the course. This is, especially, significant because faculty did not know student scores on this measure until after all assignments had been graded and course grades assigned. An assignment designed to assist students in making their assumption and inferences processes visible so they could be explored, was implemented with the goal of this exploration then promoting more tolerance for ambiguity, which, as already outlined, promotes critical thought. The assignment offers students two options and then requires them to explore what they have learned about inferences and/or assumptions This presentation outlines the assignment and demonstrates the humanities model, what students learn from particular assignments and how it fosters a change in Tolerance for Ambiguity which, serves as the foundational component of critical thinking.

Keywords: critical thinking, humanities education, sociocentrism, tolerance for ambiguity

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Authors: Cecile Edel, Sandrine Giscard D'Estaing, Elsa Labrune, Jacqueline Lornage, Mehdi Benchaib

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Introduction: The use of incubator equipped with time-lapse technology in Artificial Reproductive Technology (ART) allows a continuous surveillance. With morphocinetic parameters, algorithms are available to predict the potential outcome of an embryo. However, the different proposed time-lapse algorithms do not take account the missing data, and then some embryos could not be classified. The aim of this work is to construct a predictive model even in the case of missing data. Materials and methods: Patients: A retrospective study was performed, in biology laboratory of reproduction at the hospital ‘Femme Mère Enfant’ (Lyon, France) between 1 May 2013 and 30 April 2015. Embryos (n= 557) obtained from couples (n=108) were cultured in a time-lapse incubator (Embryoscope®, Vitrolife, Goteborg, Sweden). Time-lapse incubator: The morphocinetic parameters obtained during the three first days of embryo life were used to build the predictive model. Predictive model: A quadratic regression was performed between the number of cells and time. N = a. T² + b. T + c. N: number of cells at T time (T in hours). The regression coefficients were calculated with Excel software (Microsoft, Redmond, WA, USA), a program with Visual Basic for Application (VBA) (Microsoft) was written for this purpose. The quadratic equation was used to find a value that allows to predict the blastocyst formation: the synthetize value. The area under the curve (AUC) obtained from the ROC curve was used to appreciate the performance of the regression coefficients and the synthetize value. A cut-off value has been calculated for each regression coefficient and for the synthetize value to obtain two groups where the difference of blastocyst formation rate according to the cut-off values was maximal. The data were analyzed with SPSS (IBM, Il, Chicago, USA). Results: Among the 557 embryos, 79.7% had reached the blastocyst stage. The synthetize value corresponds to the value calculated with time value equal to 99, the highest AUC was then obtained. The AUC for regression coefficient ‘a’ was 0.648 (p < 0.001), 0.363 (p < 0.001) for the regression coefficient ‘b’, 0.633 (p < 0.001) for the regression coefficient ‘c’, and 0.659 (p < 0.001) for the synthetize value. The results are presented as follow: blastocyst formation rate under cut-off value versus blastocyst rate formation above cut-off value. For the regression coefficient ‘a’ the optimum cut-off value was -1.14.10-3 (61.3% versus 84.3%, p < 0.001), 0.26 for the regression coefficient ‘b’ (83.9% versus 63.1%, p < 0.001), -4.4 for the regression coefficient ‘c’ (62.2% versus 83.1%, p < 0.001) and 8.89 for the synthetize value (58.6% versus 85.0%, p < 0.001). Conclusion: This quadratic regression allows to predict the outcome of an embryo even in case of missing data. Three regression coefficients and a synthetize value could represent the identity card of an embryo. ‘a’ regression coefficient represents the acceleration of cells division, ‘b’ regression coefficient represents the speed of cell division. We could hypothesize that ‘c’ regression coefficient could represent the intrinsic potential of an embryo. This intrinsic potential could be dependent from oocyte originating the embryo. These hypotheses should be confirmed by studies analyzing relationship between regression coefficients and ART parameters.

Keywords: ART procedure, blastocyst formation, time-lapse incubator, quadratic model

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Authors: T. Godwin

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A call-taxi system is a type of taxi service where a taxi could be requested through a phone call or mobile app. A schematic functioning of a call-taxi system is modeled using Petri net, which provides the necessary conditions for a taxi to be assigned by a dispatcher to pick a customer as well as the conditions for the taxi to be released by the customer. A Petri net is a graphical modeling tool used to understand sequences, concurrences, and confluences of activities in the working of discrete event systems. It uses tokens on a directed bipartite multi-graph to simulate the activities of a system. The Petri net model is translated into a simulation model and a call-taxi system is simulated. The simulation model helps in evaluating the operation of a call-taxi system based on the fleet size as well as the operating policies for call-taxi assignment and empty call-taxi repositioning. The developed Petri net based simulation model can be used to decide the fleet size as well as the call-taxi assignment policies for a call-taxi system.

Keywords: call-taxi, discrete event system, petri net, simulation modeling

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Authors: Abraham Castellanos, Christophe Durville, Sophie Echenim

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In this article, a portfolio optimization problem is performed in a Solvency II context: it illustrates how advanced optimization techniques can help to tackle complex operational pain points around the monitoring, control, and stability of Solvency Capital Requirement (SCR). The market SCR of a portfolio is calculated as a combination of SCR sub-modules. These sub-modules are the results of stress-tests on interest rate, equity, property, credit and FX factors, as well as concentration on counter-parties. The market SCR is non convex and non differentiable, which does not make it a natural optimization criteria candidate. In the SCR formulation, correlations between sub-modules are fixed, whereas risk-driven portfolio allocation is usually driven by the dynamics of the actual correlations. Implementing a portfolio construction approach that is efficient on both a regulatory and economic standpoint is not straightforward. Moreover, the challenge for insurance portfolio managers is not only to achieve a minimal SCR to reduce non-invested capital but also to ensure stability of the SCR. Some optimizations have already been performed in the literature, simplifying the standard formula into a quadratic function. But to our knowledge, it is the first time that the standard formula of the market SCR is used in an optimization problem. Two solvers are combined: a bundle algorithm for convex non- differentiable problems, and a BFGS (Broyden-Fletcher-Goldfarb- Shanno)-SQP (Sequential Quadratic Programming) algorithm, to cope with non-convex cases. A market SCR minimization is then performed with historical data. This approach results in significant reduction of the capital requirement, compared to a classical Markowitz approach based on the historical volatility. A comparative analysis of different optimization models (equi-risk-contribution portfolio, minimizing volatility portfolio and minimizing value-at-risk portfolio) is performed and the impact of these strategies on risk measures including market SCR and its sub-modules is evaluated. A lack of diversification of market SCR is observed, specially for equities. This was expected since the market SCR strongly penalizes this type of financial instrument. It was shown that this direct effect of the regulation can be attenuated by implementing constraints in the optimization process or minimizing the market SCR together with the historical volatility, proving the interest of having a portfolio construction approach that can incorporate such features. The present results are further explained by the Market SCR modelling.

Keywords: financial risk, numerical optimization, portfolio management, solvency capital requirement

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Authors: S. Aditya, K. T. Nideesh, N. Guruprasad

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Being a subclass of linear programing problem, the Transportation Problem is a classic Operations Research problem where the objective is to determine the schedule for transporting goods from source to destination in a way that minimizes the shipping cost while satisfying supply and demand constraints. In this paper, we are representing the transportation problem for various warehouses along with various dealers situated in Bangalore city to reduce the transportation cost incurred by them as of now. The problem is solved by obtaining the Initial Basic feasible Solution through various methods and further proceeding to obtain optimal cost.

Keywords: NW method, optimum utilization, transportation problem, Vogel’s approximation method

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Authors: Sumit Banerjee, Chandan Kumar Chanda

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The paper presents allocation of active power losses and energy losses to consumers connected to radial distribution networks in a deregulated environment for loads of composite types. A detailed comparison among four algorithms, namely quadratic loss allocation, proportional loss allocation, pro rata loss allocation and exact loss allocation methods are presented. Quadratic and proportional loss allocations are based on identifying the active and reactive components of current in each branch and the losses are allocated to each consumer, pro rata loss allocation method is based on the load demand of each consumer and exact loss allocation method is based on the actual contribution of active power loss by each consumer. The effectiveness of the proposed comparison among four algorithms for composite load is demonstrated through an example.

Keywords: composite type, deregulation, loss allocation, radial distribution networks

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Authors: Prema Basargekar

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Facilitating the subject ‘Entrepreneurship Education’ in higher education, such as management studies, can be exhilarating as well as challenging. It is a multi-disciplinary and ever-evolving subject. Capturing entrepreneurship as a phenomenon in a holistic manner is a daunting task as it requires covering various dimensions such as new ideas generation, entrepreneurial traits, business opportunities scanning, the role of policymakers, value creation, etc., to name a few. Implicit entrepreneurship theory and effectuation are two different theories that focus on engaging the participants to create content by using their own experiences, perceptions, and belief systems. It helps in understanding the phenomenon holistically. The assumption here is that all of us are part of the entrepreneurial ecosystem, and effective learning can come through active engagement and peer learning by all the participants together. The present study is an attempt to use these theories in the class assignment given to the students at the beginning of the course to build the course content and understand entrepreneurship as a phenomenon in a better way through peer learning. The assignment was given to three batches of MBA post-graduate students doing the program in one of the private business schools in India. The subject of ‘Entrepreneurship Management’ is facilitated in the third trimester of the first year. At the beginning of the course, the students were given the assignment to submit a brief write-up/ collage/picture/poem or in any other format about “What entrepreneurship means to you?” They were asked to give their candid opinions about entrepreneurship as a phenomenon as they perceive it. Nearly 156 students doing post-graduate MBA submitted the assignment. These assignments were further used to find answers to two research questions. – 1) Are students able to use divergent and innovative forms to express their opinions, such as poetry, illustrations, videos, etc.? 2) What are various dimensions of entrepreneurship which are emerging to understand the phenomenon in a better way? The study uses the Brawn and Clark framework of reflective thematic analysis for qualitative analysis. The study finds that students responded to this assignment enthusiastically and expressed their thoughts in multiple ways, such as poetry, illustration, personal narrative, videos, etc. The content analysis revealed that there could be seven dimensions to looking at entrepreneurship as a phenomenon. They are 1) entrepreneurial traits, 2) entrepreneurship as a journey, 3) value creation by entrepreneurs in terms of economic and social value, 4) entrepreneurial role models, 5) new business ideas and innovations, 6) personal entrepreneurial experiences and aspirations, and 7) entrepreneurial ecosystem. The study concludes that an implicit approach to facilitate entrepreneurship education helps in understanding it as a live phenomenon. It also encourages students to apply divergent and convergent thinking. It also helps in triggering new business ideas or stimulating the entrepreneurial aspirations of the students. The significance of the study lies in the application of implicit theories in the classroom to make higher education more engaging and effective.

Keywords: co-creation of content, divergent thinking, entrepreneurship education, implicit theory

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Authors: Shaban Guma, Naim Bajcinca

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We propose an event-triggered algorithm for the solution of a distributed optimization problem by means of the projected subgradient method. Thereby, we invoke an OFDMA resource allocation scheme by applying an event-triggered sensitivity analysis at the access point. The optimal resource assignment of the subcarriers to the involved wireless nodes is carried out by considering the sensitivity analysis of the overall objective function as defined by the control of vehicle clusters with respect to the information exchange between the nodes.

Keywords: consensus, cross-layer, distributed, event-triggered, multi-vehicle, protocol, resource, OFDMA, wireless

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Authors: Pontsho E. Tseke, Phatu W. Mashela

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Cucurbitacin-containing phytonematicides had been consistent in suppressing root-knot (Meloidogyne species) when used in dried crude form, with limited evidence whether the efficacy could be affected when fresh fruits were used during fermentation. The objective of this study was to determine the influence of Nemafric-BL phytonematicide prepared using fermented crude extracts of fresh fruit from wild watermelon (Cucumis africanus) on the growth of tomato (Solanum lycopersicum) plants and suppression of Meloidogyne species. Seedlings of tomato cultivar ‘Floradade’ were inoculated with 3 000 eggs and second-stage juveniles (J2) of M. incognita race 2 in pot trials, with treatments comprising 0, 2, 4, 8, 16, 32 and 64 % Nemafric-BL phytonematicide. At 56 days after inoculation, the phytonematicide reduced eggs and J2 in roots by 84-97%, J2 in soil by 49-96% and total nematodes by 70-97%. Plant variables and concentrations of Nemafric-BL phytonematicide exhibited positive quadratic relations, with 74-98% associations. In conclusion, fresh fruit of C. africanus could be used for the preparation of Nemafric-BL phytonematicide, particularly in cases where the dry infrastructure is not available.

Keywords: Cucurbitacin B, density-dependent growth, effective microorganisms, quadratic relations

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Authors: Junjie Peng, Jinbao Chen, Shuai Kong, Danxu Liu

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On the basis of traditional resource allocation strategies, the usage of resources on physical servers in cloud data center is great uncertain. It will cause waste of resources if the assignment of tasks is not enough. On the contrary, it will cause overload if the assignment of tasks is too much. This is especially obvious when the applications are the same type because of its resource preferences. Considering CPU intensive application is one of the most common types of application in the cloud, we studied the optimization strategy for CPU intensive applications on the same server. We used resource preferences to analyze the case that multiple CPU intensive applications run simultaneously, and put forward a model which can predict the execution time for CPU intensive applications which run simultaneously. Based on the prediction model, we proposed the method to select the appropriate number of applications for a machine. Experiments show that the model can predict the execution time accurately for CPU intensive applications. To improve the execution efficiency of applications, we propose a scheduling model based on priority for CPU intensive applications. Extensive experiments verify the validity of the scheduling model.

Keywords: cloud computing, CPU intensive applications, resource optimization, strategy

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Authors: Keng Keh Lim, Zaleha Ismail, Yudariah Mohammad Yusof

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This paper aims to find out how students using convergent and divergent thinking in creative problem solving to solve mathematical problems creatively. Eight engineering undergraduates in a local university took part in this study. They were divided into two groups. They solved the mathematical problems with the use of creative problem solving skills. Their solutions were collected and analyzed to reveal all the processes of problem solving, namely: problem definition, ideas generation, ideas evaluation, ideas judgment, and solution implementation. The result showed that the students were able to solve the mathematical problem with the use of creative problem solving skills.

Keywords: convergent thinking, divergent thinking, creative problem solving, creativity

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Authors: G. Sirbiladze, B. Ghvaberidze, B. Matsaberidze

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A fuzzy vehicle routing problem is considered in the possibilistic environment. A new criterion, maximization of expectation of reliability for movement on closed routes is constructed. The objective of the research is to implement a two-stage scheme for solution of this problem. Based on the algorithm of preferences on the first stage, the sample of so-called “promising” routes will be selected. On the second stage, for the selected promising routes new bi-criteria problem will be solved - minimization of total traveled distance and maximization of reliability of routes. The problem will be stated as a fuzzy-partitioning problem. Two possible solutions of this scheme are considered.

Keywords: vehicle routing problem, fuzzy partitioning problem, multiple-criteria optimization, possibility theory

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Authors: Terence Soule, Tami Al Ghamdi

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To study how the partial knowledge transfer may affect the Genetic Algorithm (GA) performance, we model the Transfer Learning (TL) process using GA as the model solver. The objective of the TL is to transfer the knowledge from one problem to another related problem. This process imitates how humans think in their daily life. In this paper, we proposed to study a case where the knowledge transferred from the S problem has less information than what the T problem needs. We sampled the transferred population using different strategies of TL. The results showed transfer part of the knowledge is helpful and speeds the GA process of finding a solution to the problem.

Keywords: transfer learning, partial transfer, evolutionary computation, genetic algorithm

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Authors: Kaushalendra K. Khadanga, Lee Hee Hyol

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Passenger comfort has been paramount in the design of suspension systems of high speed cars. To analyze the effect of vibration on vehicle ride quality, a vertical model of a six degree of freedom railway passenger vehicle, with front and rear suspension, is built. It includes car body flexible effects and vertical rigid modes. A second order linear shaping filter is constructed to model Gaussian white noise into random rail excitation. The temporal correlation between the front and rear wheels is given by a second order Pade approximation. The complete track and the vehicle model are then designed. An active secondary suspension system based on a Linear Quadratic Gaussian (LQG) optimal control method is designed. The results show that the LQG control method reduces the vertical acceleration, pitching acceleration and vertical bending vibration of the car body as compared to the passive system.

Keywords: active suspension, bending vibration, railway vehicle, vibration control

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Authors: BenedictI Ita, Etido P. Inyang

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In this work, the resolutions of the N-dimensional Schrödinger equation with the screened modified Kratzerplus inversely quadratic Yukawa potential (SMKIQYP) have been obtained with the Greene-Aldrich approximation scheme using the Nikiforov-Uvarov method. The eigenvalues and the normalized eigenfunctions are obtained. We then apply the energy spectrum to study four (HCl, N₂, NO, and CO) diatomic molecules. The results show that the energy spectra of these diatomic molecules increase as quantum numbers increase. The energy equation was also used to calculate the partition function and other thermodynamic properties. We predicted the partition function of CO and NO. To check the accuracy of our work, the special case (Modified Kratzer and screened Modified Kratzer potentials) of the collective potential energy eigenvalues agrees excellently with the existing literature.

Keywords: Schrödinger equation, Nikiforov-Uvarov method, modified screened Kratzer, inversely quadratic Yukawa potential, diatomic molecules

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Authors: Diana Fajardo, Sebastián Ortiz, Oscar Herrera, Angélica Santis

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Currently, in Colombia is arising a problem related to collecting used lubricant oils which are generated by the increment of the vehicle fleet. This situation does not allow a proper disposal of this type of waste, which in turn results in a negative impact on the environment. Therefore, through the comparative analysis of various heuristics, the best solution to the VRP (Vehicle Routing Problem) was selected by comparing costs and times for the collection of used lubricant oils in the city of Pereira, Colombia; since there is no presence of management companies engaged in the direct administration of the collection of this pollutant. To achieve this aim, six proposals of through methods of solution of two phases were discussed. First, the assignment of the group of generator points of the residue was made (previously identified). Proposals one and four of through methods are based on the closeness of points. The proposals two and five are using the scanning method and the proposals three and six are considering the restriction of the capacity of collection vehicle. Subsequently, the routes were developed - in the first three proposals by the Clarke and Wright's savings algorithm and in the following proposals by the Traveling Salesman optimization mathematical model. After applying techniques, a comparative analysis of the results was performed and it was determined which of the proposals presented the most optimal values in terms of the distance, cost and travel time.

Keywords: Heuristics, optimization Model, savings algorithm, used vehicular oil, V.R.P.

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Authors: Kenza Aida Amara, Bachir Djebbar

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We treat the two-dimensional bin packing problem which involves packing a given set of rectangles into a minimum number of larger identical rectangles called bins. This combinatorial problem is NP-hard. We propose a pretreatment for the oriented version of the problem that allows the valorization of the lost areas in the bins and the reduction of the size problem. A heuristic method based on the strategy first-fit adapted to this problem is presented. We present an approach of resolution by bee colony optimization. Computational results express a comparison of the number of bins used with and without pretreatment.

Keywords: bee colony optimization, bin packing, heuristic algorithm, pretreatment

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Authors: Sukhveer Singh, Sandeep Singh

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A bi-objective fuzzy transportation problem with the objectives to minimize the total fuzzy cost and fuzzy time of transportation without according priorities to them is considered. To the best of our knowledge, there is no method in the literature to find efficient solutions of the bi-objective transportation problem under uncertainty. In this paper, a bi-objective transportation problem in an uncertain environment has been formulated. An algorithm has been proposed to find efficient solutions of the bi-objective transportation problem under uncertainty. The proposed algorithm avoids the degeneracy and gives the optimal solution faster than other existing algorithms for the given uncertain transportation problem.

Keywords: uncertain transportation problem, efficient solution, ranking function, fuzzy transportation problem

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Authors: Gloria Patricia Manurung

Abstract:

Jakarta Bus Rapid Transit (BRT) system which was established in 2009 to reduce private vehicle usage and ease the rush hour gridlock throughout the Jakarta Greater area, has failed to achieve its purpose. With gradually increasing the number of private vehicles ownership and reduced road space by the BRT lane construction, private vehicle users intuitively invade the exclusive lane of BRT, creating local traffic along the BRT network. Invaded BRT lanes costs become the same with the road network, making BRT which is supposed to be the main public transportation in the city becoming unreliable. Efforts to guard critical lanes with preventing the invasion by allocating traffic agents at several intersections have been expended, lead to the improving congestion level along the lane. Given a set of number of traffic agents, this study uses an analytical approach to finding the best deployment strategy of traffic agent on a simplified Jakarta road network in minimizing the BRT link cost which is expected to lead to the improvement of BRT system time reliability. User-equilibrium model of traffic assignment is used to reproduce the origin-destination demand flow on the network and the optimum solution conventionally can be obtained with brute force algorithm. This method’s main constraint is that traffic assignment simulation time escalates exponentially with the increase of set of agent’s number and network size. Our proposed metaheuristic and heuristic algorithms perform linear simulation time increase and result in minimized BRT cost approaching to brute force algorithm optimization. Further analysis of the overall network link cost should be performed to see the impact of traffic agent deployment to the network system.

Keywords: traffic assignment, user equilibrium, greedy algorithm, optimization

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Authors: Chusak Thanawattano, Roongroj Bhidayasiri

Abstract:

This paper proposes a novel feature set utilized for classifying the Parkinson tremor and essential tremor. Ten ET and ten PD subjects are asked to perform kinetic, postural and resting tests. The empirical mode decomposition (EMD) is used to decompose collected tremor signal to a set of intrinsic mode functions (IMF). The IMFs are used for reconstructing representative signals. The feature set is composed of peak frequencies of IMFs and reconstructed signals. Hypothesize that the dominant frequency components of subjects with PD and ET change in different directions for different tests, difference of peak frequencies of IMFs and reconstructed signals of pairwise based tests (kinetic-resting, kinetic-postural and postural-resting) are considered as potential features. Sets of features are used to train and test by classifier including the quadratic discriminant classifier (QLC) and the support vector machine (SVM). The best accuracy, the best sensitivity and the best specificity are 90%, 87.5%, and 92.86%, respectively.

Keywords: tremor, Parkinson, essential tremor, empirical mode decomposition, quadratic discriminant, support vector machine, peak frequency, auto-regressive, spectrum estimation

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Authors: K. E. Ch. Vidyasagar, M. Moghavvemi, T. S. S. T. Prabhat

Abstract:

Epilepsy is a global problem, and with seizures eluding even the smartest of diagnoses a requirement for automatic detection of the same using electroencephalogram (EEG) would have a huge impact in diagnosis of the disorder. Among a multitude of methods for automatic epilepsy detection, one should find the best method out, based on accuracy, for classification. This paper reasons out, and rationalizes, the best methods for classification. Accuracy is based on the classifier, and thus this paper discusses classifiers like quadratic discriminant analysis (QDA), classification and regression tree (CART), support vector machine (SVM), naive Bayes classifier (NBC), linear discriminant analysis (LDA), K-nearest neighbor (KNN) and artificial neural networks (ANN). Results show that ANN is the most accurate of all the above stated classifiers with 97.7% accuracy, 97.25% specificity and 98.28% sensitivity in its merit. This is followed closely by SVM with 1% variation in result. These results would certainly help researchers choose the best classifier for detection of epilepsy.

Keywords: classification, seizure, KNN, SVM, LDA, ANN, epilepsy

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