Search results for: decision problem np-complete

Authors: Prawal Sinha, Peeyush Singh, Pravir Dutt

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Problems in elastohydrodynamic lubrication have attracted a lot of attention in the last few decades. Solving a two-dimensional problem has always been a big challenge. In this paper, a new discontinuous finite volume method (DVM) for two-dimensional point contact Elastohydrodynamic Lubrication (EHL) problem has been developed and analyzed. A complete algorithm has been presented for solving such a problem. The method presented is robust and easily parallelized in MPI architecture. GMRES technique is implemented to solve the matrix obtained after the formulation. A new approach is followed in which discontinuous piecewise polynomials are used for the trail functions. It is natural to assume that the advantages of using discontinuous functions in finite element methods should also apply to finite volume methods. The nature of the discontinuity of the trail function is such that the elements in the corresponding dual partition have the smallest support as compared with the Classical finite volume methods. Film thickness calculation is done using singular quadrature approach. Results obtained have been presented graphically and discussed. This method is well suited for solving EHL point contact problem and can probably be used as commercial software.

Keywords: elastohydrodynamic, lubrication, discontinuous finite volume method, GMRES technique

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Authors: Wang Yichen, Haruka Yamashita

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In recent years, in the field of sports, decision making such as member in the game and strategy of the game based on then analysis of the accumulated sports data are widely attempted. In fact, in the NBA basketball league where the world's highest level players gather, to win the games, teams analyze the data using various statistical techniques. However, it is difficult to analyze the game data for each play such as the ball tracking or motion of the players in the game, because the situation of the game changes rapidly, and the structure of the data should be complicated. Therefore, it is considered that the analysis method for real time game play data is proposed. In this research, we propose an analytical model for "determining the optimal lineup composition" using the real time play data, which is considered to be difficult for all coaches. In this study, because replacing the entire lineup is too complicated, and the actual question for the replacement of players is "whether or not the lineup should be changed", and “whether or not Small Ball lineup is adopted”. Therefore, we propose an analytical model for the optimal player selection problem based on Small Ball lineups. In basketball, we can accumulate scoring data for each play, which indicates a player's contribution to the game, and the scoring data can be considered as a time series data. In order to compare the importance of players in different situations and lineups, we combine RNN (Recurrent Neural Network) model, which can analyze time series data, and NN (Neural Network) model, which can analyze the situation on the field, to build the prediction model of score. This model is capable to identify the current optimal lineup for different situations. In this research, we collected all the data of accumulated data of NBA from 2019-2020. Then we apply the method to the actual basketball play data to verify the reliability of the proposed model.

Keywords: recurrent neural network, players lineup, basketball data, decision making model

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Authors: Olga Kokoulina

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Today, algorithms are assuming a leading role in various areas of decision-making. Prompted by a promise to provide increased economic efficiency and fuel solutions for pressing societal challenges, algorithmic decision-making is often celebrated as an impartial and constructive substitute for human adjudication. But in the face of this implied objectivity and efficiency, the application of algorithms is also marred with mounting concerns about embedded biases, discrimination, and exclusion. In Europe, vigorous debates on risks and adverse implications of algorithmic decision-making largely revolve around the potential of data protection laws to tackle some of the related issues. For example, one of the often-cited venues to mitigate the impact of potentially unfair decision-making practice is a so-called 'right to explanation'. In essence, the overall right is derived from the provisions of the General Data Protection Regulation (‘GDPR’) ensuring the right of data subjects to access and mandating the obligation of data controllers to provide the relevant information about the existence of automated decision-making and meaningful information about the logic involved. Taking corresponding rights and obligations in the context of the specific provision on automated decision-making in the GDPR, the debates mainly focus on efficacy and the exact scope of the 'right to explanation'. In essence, the underlying logic of the argued remedy lies in a transparency imperative. Allowing data subjects to acquire as much knowledge as possible about the decision-making process means empowering individuals to take control of their data and take action. In other words, forewarned is forearmed. The related discussions and debates are ongoing, comprehensive, and, often, heated. However, they are also frequently misguided and isolated: embracing the data protection law as ultimate and sole lenses are often not sufficient. Mandating the disclosure of technical specifications of employed algorithms in the name of transparency for and empowerment of data subjects potentially encroach on the interests and rights of IPR holders, i.e., business entities behind the algorithms. The study aims at pushing the boundaries of the transparency debate beyond the data protection regime. By systematically analysing legal requirements and current judicial practice, it assesses the limits of the transparency requirement and right to access posed by intellectual property law, namely by copyrights and trade secrets. It is asserted that trade secrets, in particular, present an often-insurmountable obstacle for realising the potential of the transparency requirement. In reaching that conclusion, the study explores the limits of protection afforded by the European Trade Secrets Directive and contrasts them with the scope of respective rights and obligations related to data access and portability enshrined in the GDPR. As shown, the far-reaching scope of the protection under trade secrecy is evidenced both through the assessment of its subject matter as well as through the exceptions from such protection. As a way forward, the study scrutinises several possible legislative solutions, such as flexible interpretation of the public interest exception in trade secrets as well as the introduction of the strict liability regime in case of non-transparent decision-making.

Keywords: algorithms, public interest, trade secrets, transparency

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Authors: Nivedita Ghosh

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In his critique of Lefebvre’s view that ‘technological capacities’ are class-dependent, Francois Hetman argues that technology today is participatory, allowing the entry of individuals from different levels of social stratification. As a result, we are entering into an era of technology operators or ‘clerks’ who become the new decision-makers because of the knowledge they possess of the use of technologies. In response to Hetman’s thesis, this paper argues that knowledge of technology, while indeed providing a momentary space for decision-making, does not necessarily restructure social hierarchies. Through case studies presented from the world of Indian documentary filmmaking, this paper puts forth the view that Hetman’s clerks, despite being technologically advanced, do not break into the filmmaking hierarchical order. This remains true even for a situation where technical knowledge rests most with those in the lowest rungs of the filmmaking ladder. Instead, technological knowledge provides the space for other kinds of relationships to evolve, such as those of ‘trusting the technician’ or ‘admiration for the technician’s work’. Furthermore, what continues to define documentary filmmaking hierarchy is conceptualization capacities of the practitioners, which are influenced by a similarity in socio-cultural backgrounds and film school training accessible primarily to the filmmakers instead of the technicians. Accordingly, the paper concludes with the argument that more than ‘technological-capacities’, it is ‘conceptualization capacities’ which are class-dependent, especially when we study the field of documentary filmmaking.

Keywords: documentary filmmaking, India, technology, knowledge, hierarchy

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Authors: Assem El-Ansary

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This paper illustrates the event-oriented Behavioral Pattern Analysis (BPA) modeling approach using the Healthcare Multi-Agent System. The Event defined in BPA is a real-life conceptual entity that is unrelated to any implementation. The major contributions of this research are: The Behavioral Pattern Analysis (BPA) modeling methodology. The development of an interactive software tool (DECISION), which is based on a combination of the Analytic Hierarchy Process (AHP) and the ELECTRE Multi-Criteria Decision Making (MCDM) methods.

Keywords: analysis, modeling methodology, software modeling, event-oriented, behavioral pattern, use cases, Healthcare Multi-Agent System

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Authors: Abdallah Benaissa

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In this paper, we consider the problem of asymptotics of double oscillatory integrals in the case of critical points of the second kind, the order of contact between the boundary and a level curve of the phase being even, the situation when the order of contact is odd will be studied in other occasions. Complete asymptotic expansions will be derived and the coefficient of the leading term will be computed in terms of the original data of the problem. A multitude of people have studied this problem using a variety of methods, but only in a special case when the order of contact is minimal: the more cited papers are a paper of Jones and Kline and an other one of Chako. These integrals are encountered in many areas of science, especially in problems of diffraction of optics.

Keywords: asymptotic expansion, double oscillatory integral, critical point of the second kind, optics diffraction

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Authors: Uluhan Berk Ondul

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This article aims to shed light on the new stage of transitional justice in Argentina through examining the representations of the 2x1 decision of the Supreme Court and Santiago Maldonado’s Disappearance in the newspaper, La Nación. The two events hold the key to understanding Argentina’s journey since return to democracy as they are about the same crimes of the dictatorship, namely, the forced disappearance of civilians and the subsequent impunity that follows. In the case of a convicted torturer, The Supreme Court of Argentina ruled on 3rd of May 2017 that the days spent in preventive detention after two years should be counted double for the overall sentence. This court decision was met with severe resistance from the members of the parliament as well as the human rights movement. The second item on the list still continues and divides the country into two camps: (1) those who think that the police force has committed another act of forced disappearance in the case of activist Santiago Maldonado and (2) the others who blame the peronistas (the party and supporters of the ex-president Cristina Fernandez de Kirchner) of using this subject as a means to score political points. As a newspaper known for its proximity to the current administration, La Nación offers an insight to the direction of the country and also demonstrates how the neoliberal mindset works. The results of the study show that the transitional justice process in Argentina is far from being complete as the Promise of Nunca Más is still not a shared value but a political statement.

Keywords: Argentina, Fallo 2x1, impunity, Santiago Maldonado, transitional justice

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Authors: Krambia-Kapardis Maria, Neophytidou Christina

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Lobbying is an inherent aspect within the democratic regimes across the globe. Although it can provide decision-makers with valuable knowledge and grant access to stakeholders in the decision-making process, it can also lead to undue influence and unfair competition at the expense of the public interest if it not transparent. Given the multi-level governance structure of the EU, it is no surprise that the EU policy-making arena has become a place-to-be for lobbyists. However, in order to ensure that influence is legitimate and not biased of any business interests, lobbying must be effectively regulated. A comparison with the US and Canadian lobbying regulatory framework and utilising some good practices from EU countries it is apparent that lobbying is the Achilles’ heel to transparency in the EU. It is evident that EU institutions suffer from ineffective regulations and could in fact benefit from a more robust, mandatory and better implemented system of lobbying regulation.

Keywords: EU, lobbying regulation, transparency, democratic regimes

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Authors: Grace Omowunmi Soyebi

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A computerized medical record system is a collection of medical information about a person that is stored on a computer. One principal problem of most hospitals in rural areas is using the file management system for keeping records. A lot of time is wasted when a patient visits the hospital, probably in an emergency, and the nurse or attendant has to search through voluminous files before the patient's file can be retrieved, this may cause an unexpected to happen to the patient. This Data Mining application is to be designed using a Structured System Analysis and design method which will help in a well-articulated analysis of the existing file management system, feasibility study, and proper documentation of the Design and Implementation of a Computerized medical record system. This Computerized system will replace the file management system and help to quickly retrieve a patient's record with increased data security, access clinical records for decision-making, and reduce the time range at which a patient gets attended to.

Keywords: programming, computing, data, innovation

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Authors: Assem El-Ansary

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This paper illustrates the event-oriented Behavioral Pattern Analysis (BPA) modeling approach in developing an Intelligent Agent Reservation System (IARS). The Event defined in BPA is a real-life conceptual entity that is unrelated to any implementation. The major contributions of this research are developing the Behavioral Pattern Analysis (BPA) modeling methodology, and developing an interactive software tool (DECISION) which is based on a combination of the Analytic Hierarchy Process (AHP) and the ELECTRE Multi-Criteria Decision Making (MCDM) methods.

Keywords: analysis, intelligent agent, reservation system, modeling methodology, software modeling, event-oriented, behavioral pattern, use cases

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Authors: Ashok Kalagura

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This paper presents a data-mining model for fault-zone identification of flexible AC transmission systems (FACTS)-based transmission line including a thyristor-controlled series compensator (TCSC) and unified power-flow controller (UPFC), using ensemble decision trees. Given the randomness in the ensemble of decision trees stacked inside the random forests model, it provides an effective decision on the fault-zone identification. Half-cycle post-fault current and voltage samples from the fault inception are used as an input vector against target output ‘1’ for the fault after TCSC/UPFC and ‘1’ for the fault before TCSC/UPFC for fault-zone identification. The algorithm is tested on simulated fault data with wide variations in operating parameters of the power system network, including noisy environment providing a reliability measure of 99% with faster response time (3/4th cycle from fault inception). The results of the presented approach using the RF model indicate the reliable identification of the fault zone in FACTS-based transmission lines.

Keywords: distance relaying, fault-zone identification, random forests, RFs, support vector machine, SVM, thyristor-controlled series compensator, TCSC, unified power-flow controller, UPFC

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Authors: Maria Valeria De Bonis, Gianpaolo Ruocco

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Nowadays, computational modeling is paving new design and verification ways in a number of industrial sectors. The technology is ripe to challenge some case in the Bioengineering and Medicine frameworks: for example, looking at the strategical and ethical importance of oncology research, efforts should be made to yield new and powerful resources to tumor knowledge and understanding. With these driving motivations, we approach this gigantic problem by using some standard engineering tools such as the mathematics behind the biomass transfer. We present here some bacterial colonization studies in complex structures. As strong analogies hold with some tumor proliferation, we extend our study to a benchmark case of solid tumor. By means of a commercial software, we model biomass and energy evolution in arbitrary media. The approach will be useful to cast virtualization cases of cancer growth in human organs, while augmented reality tools will be used to yield for a realistic aid to informed decision in treatment and surgery.

Keywords: bacteria, simulation, tumor, precision medicine

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Authors: Thiago R. Pereira

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The philosophical hermeneutics is able to change the Brazilian Judiciary because of the understanding of the characteristics of the human being. It is impossible for humans, to be invested in the function of being a judge, making absolutely neutral decisions, but the philosophical hermeneutics can assist the judge making impartial decisions, based on the federal constitution. The normative legal positivism imagined a neutral judge, a judge able to try without any preconceived ideas, without allowing his/her background to influence him/her. When a judge arbitrates based on legal rules, the problem is smaller, but when there are no clear legal rules, and the judge must try based on principles, the risk of the decision is based on what they believe in. Solipsistically, this issue gains a huge dimension. Today, the Brazilian judiciary is independent, but there must be a greater knowledge of philosophy and the philosophy of law, partially because the bigger problem is the unpredictability of decisions made by the judiciary. Actually, when a lawsuit is filed, the result of this judgment is absolutely unpredictable. It is almost a gamble. There must be the slightest legal certainty and predictability of judicial decisions, so that people, with similar cases, may not receive opposite sentences. The relativism, since classical antiquity, believes in the possibility of multiple answers. Since the Greeks in in the sixth century before Christ, through the Germans in the eighteenth century, and even today, it has been established the constitution as the great law, the Groundnorm, and thus, the relativism of life can be greatly reduced when a hermeneut uses the Constitution as North interpretational, where all interpretation must act as the hermeneutic constitutional filter. For a current philosophy of law, that inside a legal system with a Federal Constitution, there is a single correct answer to a specific case. The challenge is how to find this right answer. The only answer to this question will be that we should use the constitutional principles. But in many cases, a collision between principles will take place, and to resolve this issue, the judge or the hermeneut will choose a solipsism way, using what they personally believe to be the right one. For obvious reasons, that conduct is not safe. Thus, a theory of decision is necessary to seek justice, and the hermeneutic philosophy and the linguistic turn will be necessary for one to find the right answer. In order to help this difficult mission, it will be necessary to use philosophical hermeneutics in order to find the right answer, which is the constitutionally most appropriate response. The constitutionally appropriate response will not always be the answer that individuals agree to, but we must put aside our preferences and defend the answer that the Constitution gives us. Therefore, the hermeneutics applied to Law, in search constitutionally appropriate response, should be the safest way to avoid judicial individual decisions. The aim of this paper is to present the science of law starting from the linguistic turn, the philosophical hermeneutics, moving away from legal positivism. The methodology used in this paper is qualitative, academic and theoretical, philosophical hermeneutics with the mission to conduct research proposing a new way of thinking about the science of law. The research sought to demonstrate the difficulty of the Brazilian courts to depart from the secular influence of legal positivism. Moreover, the research sought to demonstrate the need to think science of law within a contemporary perspective, where the linguistic turn, philosophical hermeneutics, will be the surest way to conduct the science of law in the present century.

Keywords: hermeneutic, right answer, solipsism, Brazilian judiciary

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Authors: Lichung Jen, Yi Chun Liu, Kuan-Wei Lee

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Fruitful data has been accumulated in database nowadays and is commonly used as support for decision-making. In the healthcare industry, hospital, for instance, ordering pharmacy inventory is one of the key decision. With large drug inventory, the current cost increases and its expiration dates might lead to future issue, such as drug disposal and recycle. In contrast, underestimating demand of the pharmacy inventory, particularly standing drugs, affects the medical treatment and possibly hospital reputation. Prescription behaviour of hospital physicians is one of the critical factor influencing this decision, particularly irregular prescription behaviour. If a drug’s usage amount in the month is irregular and less than the regular usage, it may cause the trend of subsequent stockpiling. On the contrary, if a drug has been prescribed often than expected, it may result in insufficient inventory. We proposed a hierarchical Bayesian mixture model with two components to identify physicians’ regular/irregular prescription patterns with probabilities. Heterogeneity of hospital is considered in our proposed hierarchical Bayes model. The result suggested that modeling the prescription patterns of physician is beneficial for estimating the order quantity of medication and pharmacy inventory management of the hospital. Managerial implication and future research are discussed.

Keywords: hierarchical Bayesian model, poission mixture model, medicines prescription behavior, irregular behavior

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Authors: Kalandi Charan Pradhan

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In this study, we investigate does weather variation determine temporary labour migration using 210 sample households from six Semi-Arid Tropic (SAT) villages for the period of 2005-2014 in India. The study has made an attempt to examine how households use temporary labour migration as a coping mechanism to minimise the risk rather than maximize the utility of the households. The study employs panel Logit regression model to predict the probability of household having at least one temporary labour migrant. As per as econometrics result, it is found that along with demographic and socioeconomic factors; weather variation plays an important role to determine the decision of migration at household level. In order to capture the weather variation, the study uses mean crop yield deviation over the study periods. Based on the random effect logit regression result, the study found that there is a concave relationship between weather variation and decision of temporary labour migration. This argument supports the theory of New Economics of Labour Migration (NELM), which highlights the decision of labour migration not only maximise the households’ utility but it helps to minimise the risks.

Keywords: temporary migration, socioeconomic factors, weather variation, crop yield, logit estimation

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Authors: Peng Liu, Chyng Wen Tee, Xiaofei Xu

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This paper integrates machine learning forecasting techniques into the multi-period portfolio optimization framework, enabling dynamic asset allocation based on multiple future periods. We explore both theoretical foundations and practical applications, employing diverse machine learning models for return forecasting. This comprehensive guide demonstrates the superiority of multi-period optimization over single-period approaches, particularly in risk mitigation through strategic rebalancing and enhanced market trend forecasting. Our goal is to promote wider adoption of multi-period optimization, providing insights that can significantly enhance the decision-making capabilities of practitioners and researchers alike.

Keywords: multi-period portfolio optimization, look-ahead constrained optimization, machine learning, sequential decision making

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Authors: Alireza Alizadeh, Hossein Ghadimi, Oveis Abedinia, Noradin Ghadimi

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A Particle Swarm Optimization with Time Varying Acceleration Coefficients (PSO-TVAC) is proposed to determine optimal economic load dispatch (ELD) problem in this paper. The proposed methodology easily takes care of solving non-convex economic load dispatch problems along with different constraints like transmission losses, dynamic operation constraints and prohibited operating zones. The proposed approach has been implemented on the 3-machines 6-bus, IEEE 5-machines 14-bus, IEEE 6-machines 30-bus systems and 13 thermal units power system. The proposed technique is compared to solve the ELD problem with hybrid approach by using the valve-point effect. The comparison results prove the capability of the proposed method giving significant improvements in the generation cost for the economic load dispatch problem.

Keywords: PSO-TVAC, economic load dispatch, non-convex cost function, prohibited operating zone, transmission losses

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Authors: Zahid Ullah, Atlas Khan

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The rapid growth of data in various domains has created a pressing need for effective methods to transform this data into meaningful knowledge. In this era of big data, mathematical and statistical innovations play a crucial role in unlocking insights and facilitating informed decision-making in data analytics. This abstract aims to explore the transformative potential of these innovations and their impact on converting raw data into actionable knowledge. Drawing upon a comprehensive review of existing literature, this research investigates the cutting-edge mathematical and statistical techniques that enable the conversion of data into knowledge. By evaluating their underlying principles, strengths, and limitations, we aim to identify the most promising innovations in data analytics. To demonstrate the practical applications of these innovations, real-world datasets will be utilized through case studies or simulations. This empirical approach will showcase how mathematical and statistical innovations can extract patterns, trends, and insights from complex data, enabling evidence-based decision-making across diverse domains. Furthermore, a comparative analysis will be conducted to assess the performance, scalability, interpretability, and adaptability of different innovations. By benchmarking against established techniques, we aim to validate the effectiveness and superiority of the proposed mathematical and statistical innovations in data analytics. Ethical considerations surrounding data analytics, such as privacy, security, bias, and fairness, will be addressed throughout the research. Guidelines and best practices will be developed to ensure the responsible and ethical use of mathematical and statistical innovations in data analytics. The expected contributions of this research include advancements in mathematical and statistical sciences, improved data analysis techniques, enhanced decision-making processes, and practical implications for industries and policymakers. The outcomes will guide the adoption and implementation of mathematical and statistical innovations, empowering stakeholders to transform data into actionable knowledge and drive meaningful outcomes.

Keywords: data analytics, mathematical innovations, knowledge extraction, decision-making

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Authors: Verónica Díaz Quezada

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The importance given to the development of the problem solving skill and the requirement to solve problems framed in mathematical or real life contexts, in practice, they are not evidence in relation to the teaching of proportional variations. This qualitative and descriptive study aims to (1) to improve problem solving ability of high school students in Chile, (ii) to elaborate and describe a didactic intervention strategy based on learning situations in proportional variations, focused on solving types of routine problems of various contexts and non-routine problems. For this purpose, participant observation was conducted, test of mathematics problems and an opinion questionnaire to thirty-six high school students. Through the results, the highest academic performance is evidenced in the routine problems of purely mathematical context, realistic, fantasy context, and non-routine problems, except in the routine problems of real context and compound proportionality problems. The results highlight the need to consider in the curriculum different types of problems in the teaching of mathematics that relate the discipline to everyday life situations

Keywords: algebra, high school, proportion variations, nonroutine problem solving, routine problem solving

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Authors: Lara Dutil-Fafard, Caroline Rhéaume, Patrick Archambault, Daniel Lafond, Neal W. Pollock

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Improving resources for medical autonomy of astronauts in prolonged space missions, such as a Mars mission, requires not only technology development, but also decision-making support systems. The Advanced Crew Medical System - Medical Condition Requirements study, funded by the Canadian Space Agency, aimed to create knowledge content and a scenario-based query capability to support medical autonomy of astronauts. The key objective of this study was to create a prototype tool for identifying medical infrastructure requirements in terms of medical knowledge, skills and materials. A multicriteria decision-making method was used to prioritize the highest risk medical events anticipated in a long-term space mission. Starting with those medical conditions, event sequence diagrams (ESDs) were created in the form of decision trees where the entry point is the diagnosis and the end points are the predicted outcomes (full recovery, partial recovery, or death/severe incapacitation). The ESD formalism was adapted to characterize and compare possible outcomes of medical conditions as a function of available medical knowledge, skills, and supplies in a given mission scenario. An extensive literature review was performed and summarized in a medical condition database. A PostgreSQL relational database was created to allow query-based evaluation of health outcome metrics with different medical infrastructure scenarios. Critical decision points, skill and medical supply requirements, and probable health outcomes were compared across chosen scenarios. The three medical conditions with the highest risk rank were acute coronary syndrome, sepsis, and stroke. Our efforts demonstrate the utility of this approach and provide insight into the effort required to develop appropriate content for the range of medical conditions that may arise.

Keywords: decision support system, event-sequence diagram, exploration mission, medical autonomy, scenario-based queries, space medicine

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Authors: M. B. Tavakoli, R. Reiazi, M. M. Mohammadi, K. Jabbari

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From 2003, AD4/ACE experiment in CERN tried to investigate different aspects of antiproton as a new modality in particle therapy. Because of lack of reliable absolute dose measurements attempts to find out the radiobiological characteristics of antiproton have not reached to a reasonable result yet. From the other side, application of Geant4 in medical approaches is increased followed by Geant4-DNA project which focuses on using this code to predict radiation effects in the cellular scale. This way we can exploit Geant4-DNA results for antiproton. Unfortunately, previous studies showed there are serious problem in simulating an antiproton beam using Geant4. Since most of the problem was in the Bragg peak region which antiproton annihilates there, in this work we tried to understand if the problem came from the way in which Geant4 handles annihilation products especially pion particles. This way, we can predict the source of the dose discrepancies between Geant4 simulations and dose measurements done in CERN.

Keywords: Geant4, antiproton, annihilation, pion plus, pion minus

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Authors: Eun-Jun Yoon

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Deniable authentication protocol is a new security authentication mechanism which can enable a receiver to identify the true source of a given message, but not to prove the identity of the sender to a third party. In 2013, Kar proposed a secure ID-based deniable authentication protocol whose security is based on computational infeasibility of solving Elliptic Curve Diffie-Hellman Problem (ECDHP). Kar claimed that the proposed protocol achieves properties of deniable authentication, mutual authentication, and message confidentiality. However, this paper points out that Kar's protocol still suffers from sender spoofing attack and message modification attack unlike its claims.

Keywords: deniable authentication, elliptic curve cryptography, Diffie-Hellman problem, cryptanalysis

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Authors: S. Aizikovich, L. Krenev, Y. Tokovyy, Y. C. Wang

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An approximate analytical-numerical solution to the axisymmetric problem on thermo-mechanical indentation of a flat cylindrical punch into an arbitrarily non-homogeneous elastic half-space is constructed by making use of the bilateral asymptotic method. The key point of this method lies in evaluation of the ker¬nels in the obtained integral equations by making use of a numerical technique. Once the structure of the kernel is defined, it then is approximated by an analytical expression of special kind so that the solution of the integral equation can be achieved analytically. This fact allows for construction of the solution in an analytical form, which is convenient for analysis of the mechanical effects concerned with arbitrarily presumed non-homogeneity of the material.

Keywords: contact problem, circular punch, arbitrarily-nonhomogeneous halfspace

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Authors: Safieh Javadinejad

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In order to make well-informed decisions respecting long-term system planning, resource managers and policy creators necessitate to comprehend the interconnections among energy and water utilization and manufacture—and also the energy-water nexus. Planning and assessment issues contain the enhancement of strategies for declining the water and energy system’s vulnerabilities to climate alteration with also emissions of decreasing greenhouse gas. In order to deliver beneficial decision support for climate adjustment policy and planning, understanding the regionally-specific features of the energy-water nexus, and the history-future of the water and energy source systems serving is essential. It will be helpful for decision makers understand the nature of current water-energy system conditions and capacity for adaptation plans for future. This research shows an integrated hydrology/energy modeling platform which is able to extend water-energy examines based on a detailed illustration of local circumstances. The modeling links the Water Evaluation and Planning (WEAP) and the Long Range Energy Alternatives Planning (LEAP) system to create full picture of water-energy processes. This will allow water managers and policy-decision makers to simply understand links between energy system improvements and hydrological processing and realize how future climate change will effect on water-energy systems. The Zayandeh Rud river basin in Iran is selected as a case study to show the results and application of the analysis. This region is known as an area with large integration of both the electric power and water sectors. The linkages between water, energy and climate change and possible adaptation strategies are described along with early insights from applications of the integration modeling system.

Keywords: climate impacts, hydrology, water systems, adaptation planning, electricity, integrated modeling

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Authors: Saif Ullah, Guan Zailin, Xu Xianhao, He Zongdong, Wang Baoxi

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Assembly line balancing problem is aimed to divide the tasks among the stations in assembly lines and optimize some objectives. In assembly lines the workload on stations is different from each other due to different tasks times and the difference in workloads between stations can cause blockage or starvation in some stations in assembly lines. Buffers are used to store the semi-finished parts between the stations and can help to smooth the assembly production. The assembly line balancing and buffer sizing problem can affect the throughput of the assembly lines. Assembly line balancing and buffer sizing problems have been studied separately in literature and due to their collective contribution in throughput rate of assembly lines, balancing and buffer sizing problem are desired to study simultaneously and therefore they are considered concurrently in current research. Current research is aimed to maximize throughput, minimize total size of buffers in assembly line and minimize workload variations in assembly line simultaneously. A multi objective optimization objective is designed which can give better Pareto solutions from the Pareto front and a simple example problem is solved for assembly line balancing and buffer sizing simultaneously. Current research is significant for assembly line balancing research and it can be significant to introduce optimization approaches which can optimize current multi objective problem in future.

Keywords: assembly line balancing, buffer sizing, Pareto solutions

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Authors: Danilo López, Johana Hernández, Edwin Rivas

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The use of the Multilayer Perceptron Neural Networks (MLPNN) technique is presented to estimate the future state of use of a licensed channel by primary users (PUs); this will be useful at the spectral decision stage in cognitive radio networks (CRN) to determine approximately in which time instants of future may secondary users (SUs) opportunistically use the spectral bandwidth to send data through the primary wireless network. To validate the results, sequences of occupancy data of channel were generated by simulation. The results show that the prediction percentage is greater than 60% in some of the tests carried out.

Keywords: cognitive radio, neural network, prediction, primary user

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Authors: Taisir Eldos, Aws Kanan, Waleed Nazih, Ahmad Khatatbih

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Chemical Reaction Optimization (CRO) is an optimization metaheuristic inspired by the nature of chemical reactions as a natural process of transforming the substances from unstable to stable states. Starting with some unstable molecules with excessive energy, a sequence of interactions takes the set to a state of minimum energy. Researchers reported successful application of the algorithm in solving some engineering problems, like the quadratic assignment problem, with superior performance when compared with other optimization algorithms. We adapted this optimization algorithm to the Printed Circuit Board Drilling Problem (PCBDP) towards reducing the drilling time and hence improving the PCB manufacturing throughput. Although the PCBDP can be viewed as instance of the popular Traveling Salesman Problem (TSP), it has some characteristics that would require special attention to the transactions that explore the solution landscape. Experimental test results using the standard CROToolBox are not promising for practically sized problems, while it could find optimal solutions for artificial problems and small benchmarks as a proof of concept.

Keywords: evolutionary algorithms, chemical reaction optimization, traveling salesman, board drilling

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Authors: J. Niyitegeka, G. Nshimirimana, A. Silverstein, J. Odhiambo, Y. Lin, T. Nkurunziza, R. Riviello, S. Rulisa, P. Banguti, H. Magge, M. Macharia, J. P. Dushime, R. Habimana, B. Hedt-Gauthier

Abstract:

In low-resource settings, women needing an emergency cesarean section experiences various delays in both reaching and receiving care that is often linked to poor neonatal outcomes. In this study, we quantified different measures of delays and assessed the association between these delays and neonatal outcomes at three rural district hospitals in Rwanda. This retrospective study included 441 neonates and their mothers who underwent emergency cesarean sections in 2015 at Butaro, Kirehe and Rwinkwavu District Hospitals. Four possible delays were measured: Time from start of labor to district hospital admission, travel time from a health center to the district hospital, time from admission to surgical incision, and time from the decision for the emergency cesarean section to surgical incision. Neonatal outcomes were categorized as unfavorable (APGAR < 7 or death) and favorable (APGAR ≥ 7). We assessed the relationship between each type of delay and neonatal outcomes using multivariate logistic regression. In our study, 38.7% (108 out of 279) of neonates’ mothers labored for 12 to 24 hours before hospital admission and 44.7% (159 of 356) of mothers were transferred from health centers that required 30 to 60 minutes of travel time to reach the district hospital. 48.1% (178 of 370) of caesarean sections started within five hours after admission and 85.2% (288 of 338) started more than thirty minutes after the decision for the emergency cesarean section was made. Neonatal outcomes were significantly worse among mothers with more than 90 minutes of travel time from the health center to the district hospital compared to health centers attached to the hospital (OR = 5.12, p = 0.02). Neonatal outcomes were also significantly different depending on decision to incision intervals; neonates with cesarean deliveries starting more than thirty minutes after decision had better outcomes than those started immediately (OR = 0.32, p = 0.04). Interventions that decrease barriers to access to maternal health care services can improve neonatal outcome after emergency cesarean section. Triaging could explain the inverse relationship between time from decision to incision and neonatal outcome; this must be studied more in the future.

Keywords: Africa, emergency obstetric care, rural health delivery, maternal and child health

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Authors: Ariane Plaisance, Holly O. Witteman, Patrick Michel Archambault

Abstract:

Upon admission to an intensive care unit (ICU), all patients should discuss their wishes concerning life-sustaining interventions (e.g., cardiopulmonary resuscitation (CPR)). Without such discussions, interventions that prolong life at the cost of decreasing its quality may be used without appropriate guidance from patients. We employed user-centered design to adapt an existing decision aid (DA) about CPR to create a novel wiki-based DA adapted to the context of a single ICU and tailored to individual patient’s risk factors. During Phase 1, we conducted three weeks of ethnography of the decision-making context in our ICU to identify clinician and patient needs for a decision aid. During this time, we observed five dyads of intensivists and patients discussing their wishes concerning life-sustaining interventions. We also conducted semi-structured interviews with the attending intensivists in this ICU. During Phase 2, we conducted three rounds of rapid prototyping involving 15 patients and 11 other allied health professionals. We recorded discussions between intensivists and patients and used a standardized observation grid to collect patients’ comments and sociodemographic data. We applied content analysis to field notes, verbatim transcripts and the completed observation grids. Each round of observations and rapid prototyping iteratively informed the design of the next prototype. We also used the programming architecture of a wiki platform to embed the GO-FAR prediction rule programming code that we linked to a risk graphics software to better illustrate outcome risks calculated. During Phase I, we identified the need to add a section in our DA concerning invasive mechanical ventilation in addition to CPR because both life-sustaining interventions were often discussed together by physicians. During Phase II, we produced a context-adapted decision aid about CPR and mechanical ventilation that includes a values clarification section, questions about the patient’s functional autonomy prior to admission to the ICU and the functional decline that they would judge acceptable upon hospital discharge, risks and benefits of CPR and invasive mechanical ventilation, population-level statistics about CPR, a synthesis section to help patients come to a final decision and an online calculator based on the GO-FAR prediction rule. Even though the three rounds of rapid prototyping led to simplifying the information in our DA, 60% (n= 3/5) of the patients involved in the last cycle still did not understand the purpose of the DA. We also identified gaps in the discussion and documentation of patients’ preferences concerning life-sustaining interventions (e.g.,. CPR, invasive mechanical ventilation). The final version of our DA and our online wiki-based GO-FAR risk calculator using the IconArray.com risk graphics software are available online at www.wikidecision.org and are ready to be adapted to other contexts. Our results inform producers of decision aids on the use of wikis and user-centered design to develop DAs that are better adapted to users’ needs. Further work is needed on the creation of a video version of our DA. Physicians will also need the training to use our DA and to develop shared decision-making skills about goals of care.

Keywords: ethnography, intensive care units, life-sustaining therapies, user-centered design

Procedia PDF Downloads 337

Authors: Birome Holo Ba, Christian Prins, Caroline Prodhon

Abstract:

Optimization is an important aspect of logistics management. It can reduce significantly logistics costs and also be a good tool for decision support. In this paper, we address a planning problem specific to biomass supply chain. We propose a new mixed integer linear programming (MILP) model dealing with different feed stock production operations such as harvesting, packing, storage, pre-processing and transportation, with the objective of minimizing the total logistic cost of the system on a regional basis. It determines the optimal number of harvesting machine, the fleet size of trucks for transportation and the amount of each type of biomass harvested, stored and pre-processed in each period to satisfy demands of refineries in each period. We illustrate the effectiveness of the proposal model with a numerical example, a case study in Aube (France department), which gives preliminary and interesting, results on a small test case.

Keywords: biomass logistics, supply chain, modelling, optimization, bioenergy, biofuels

Procedia PDF Downloads 499