Search results for: generalised travelling salesman problem

Authors: Grace Rademacher

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Trauma” of the Kingdom of Hungary and the “Lost Cause” of the American Confederacy. Applying Nicole Maurantonio’s articulation of “confederate exceptionalism” and Svetlana Boym’s definition of “restorative nostalgia”, this article argues that, via memorialization and public discourse, both far right bodies flood their constituencies with narratives of nostalgia and martyrdom to sow existential anxieties about past and prophetic victimhood, all under the guise of protecting or restoring heritage. Linking this practice to gamification and conspiracy theorizing and following the work of Patrick Jagoda, this article identifies such industries of nostalgia as means by which the far right in both nations can partake in the “immanent and improvisational process of problem making.” Reified through monuments and references to the Trianon Trauma and the American confederacy, political actors “problem make” by alleging that they are victims of the West or the Left, subject to the cruel whims of liberalism and denial of historical legitimacy. In both nations, relying on their victimhood, pundits and politicians can appeal to white supremacists and distract citizens from legitimate active conflicts, such as wars or democratic rollbacks, redirecting them to fictional, mythical attacks on Hungarian or American society and civilization. This article will examine memorials and monuments as “lieux de memoire” and identify the purposeful similarities between the discourse of public figures and politicians such as María Schmidt, János Lázár, and Viktor Orbán, with that of Donald Trump and pundits such as Tucker Carlson.

Keywords: nationalism, political memory, white supremacy, trianon

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Authors: Qasim M. Kriri

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Few Saudi Arabia production companies face financial profit issues until this moment. This work presents a linear integer programming model that solves a production problem of a Saudi Food Company in Saudi Arabia. An optimal solution to the above-mentioned problem is a Linear Programming solution. In this regard, the main purpose of this project is to maximize profit. Linear Programming Technique has been used to derive the maximum profit from production of natural juice at Saudi Food Co. The operations of production of the company were formulated and optimal results are found out by using Lindo Software that employed Sensitivity Analysis and Parametric linear programming in order develop Linear Programming. In addition, the parameter values are increased, then the values of the objective function will be increased.

Keywords: parameter linear programming, objective function, sensitivity analysis, optimize profit

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Authors: Johan Esbach

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The entrepreneur has traditionally been defined through various historical lenses, emphasising individual traits, risk-taking, speculation, innovation and firm creation. However, these definitions often fail to address the dynamic nature of the modern entrepreneurial functions, which respond to unpredictable uncertainties and transition to routine management as certainty is achieved. This paper proposes a revised definition, positioning the entrepreneur as a dynamic function rather than a human construct, that emerges to address specific uncertainties in economic systems, but fades once uncertainty is resolved. By examining historical definitions and its limitations, including the works of Cantillon, Say, Schumpeter, and Knight, this paper identifies a gap in literature and develops a generalised definition for the entrepreneur. The revised definition challenges conventional thought by shifting focus from static attributes such as alertness, traits, firm creation, etc., to a dynamic role that includes reliability, adaptation, scalability, and adaptability. The methodology of this paper employs a mixed approach, combining theoretical analysis and case study examination to explore the dynamic nature of the entrepreneurial function in relation to uncertainty. The selection of case studies includes companies like Airbnb, Uber, Netflix, and Tesla, as these firms demonstrate a clear transition from entrepreneurial uncertainty to routine certainty. The data from the case studies is then analysed qualitatively, focusing on the patterns of entrepreneurial function across the selected companies. These results are then validated using quantitative analysis, derived from an independent survey. The primary finding of the paper will validate the entrepreneur as a dynamic function rather than a static, human-centric role. In considering the transition from uncertainty to certainty in companies like Airbnb, Uber, Netflix, and Tesla, the study shows that the entrepreneurial function emerges explicitly to address market, technological, or social uncertainties. Once these uncertainties are resolved and a certainty in the operating environment is established, the need for the entrepreneurial function ceases, giving way to routine management and business operations. The paper emphasises the need for a definitive model that responds to the temporal and contextualised nature of the entrepreneur. In adopting the revised definition, the entrepreneur is positioned to play a crucial role in the reduction of uncertainties within economic systems. Once the uncertainties are addressed, certainty is manifested in new combinations or new firms. Finally, the paper outlines policy implications for fostering environments that enables the entrepreneurial function and transition theory.

Keywords: dynamic function, uncertainty, revised definition, transition

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Authors: Gangadhara Rao K.

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In Andhra Pradesh traditionally, the flood problem had been confined to the flooding of smaller rivers. But the drainage problem in the coastal delta zones has worsened, multiplying the destructive potential of cyclones and increasing flood hazards. As a result of floods, the people living around these areas are forced to move out of their traditions in search of higher altitude places. This paper will be discussing about suitability of techniques used in Bangladesh in context of Godavari river basin in Andhra Pradesh. The study considers social, physical and environmental conditions of the region. The methods for achieving this objective includes the study of both cases from Bangladesh and Andhra Pradesh. Comparison with the existing techniques and suit to our requirements and context. If successful, we can adopt those techniques and this might help the people living in riverfront areas to stay safe during the floods without losing their traditional lands.

Keywords: amphibious, bouyancy, floating, architecture, flood resistent

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Authors: Nyla Anjum, Humaira Bano

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Disability, regardless of its type and nature limits one or two significant life activities. These limitations constitute risk factors for suicide. Rate and intensity of problem upsurges in critical age of adolescence. Researches in the field of mental health over look problem of suicide among persons with disability. Aim of the study was to investigate prevalence and risk factors for suicide among adolescents with disability. The study constitutes purposive sample of 106 elements of both gender with four major categories of disability: hearing impairment, physical impairment, visual impairment and intellectual disabilities. Face to face interview technique was opted for data collection. Other variable are: socio-economic status, social and family support, provision of services for persons with disability, education and employment opportunities. For data analysis independent sample t-test was applied to find out significant differences in gender and One Way Analysis of variance was run to find out differences among four types of disability. Major predictors of suicide were identified with multiple regression analysis. It is concluded that ideation, plans and attempts of suicide among adolescents with disability is a multifaceted and imperative concern in the area of mental health. Urgent research recommendations contains valid measurement of suicide rate and identification of more risk factors for suicide among persons with disability. Study will also guide towards prevention of this pressing problem and will bring message of happy and healthy life not only for persons with disability but also for their families. It will also help to reduce suicide rate in society.

Keywords: suicide, risk factors, adolescent, disability, mental health

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Authors: Quoc Khanh Dang, Thomas Bourdeaud’huy, Khaled Mesghouni, Armand Toguy´eni

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This paper studies a train routing and scheduling problem for busy railway stations. Our objective is to allow trains to be routed in dense areas that are reaching saturation. Unlike traditional methods that allocate all resources to setup a route for a train and until the route is freed, our work focuses on the use of resources as trains progress through the railway node. This technique allows a larger number of trains to be routed simultaneously in a railway node and thus reduces their current saturation. To deal with this problem, this study proposes an abstract model and a mixed-integer linear programming formulation to solve it. The applicability of our method is illustrated on a didactic example.

Keywords: busy railway stations, mixed-integer linear programming, offline railway station management, train platforming, train routing, train scheduling

Procedia PDF Downloads 253

Authors: Mounira Laabidi, Rafik Zayani, Ridha Bouallegue, Daniel Roviras

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The Filter Bank multicarrier with Offset Quadrature Amplitude Modulation (FBMC-OQAM) has been introduced to overcome the poor spectral characteristics and the waste in both bandwidth and energy caused by the use of the cyclic prefix. However, the FBMC-OQAM signals suffer from the high Peak to Average Power Ratio (PAPR) problem. Due to the overlapping structure of the FBMC-OQAM signals, directly applying the PAPR reduction schemes conceived for the OFDM one turns out to be ineffective. In this paper, we address the problem of PAPR reduction for FBMC-OQAM systems by suggesting a new scheme based on an improved version of Active Constellation Extension scheme (ACE) of OFDM. The proposed scheme, named Rolling Window ACE, takes into consideration the overlapping naturally emanating from the FBMC-OQAM signals.

Keywords: ACE, FBMC, OQAM, OFDM, PAPR, rolling-window

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Authors: Mayank Raj, V. G. Narendra

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Ever since the DARPA challenge on autonomous vehicles in 2005, there has been a lot of buzz about ‘Autonomous Vehicles’ amongst the major tech giants such as Google, Uber, and Tesla. Numerous approaches have been adopted to solve this problem, which can have a long-lasting impact on mankind. In this paper, we have used Deep Learning techniques and TensorFlow framework with the goal of building a neural network model to predict (speed, acceleration, steering angle, and brake) features needed for navigation of autonomous vehicles. The Deep Neural Network has been trained on images and sensor data obtained from the comma.ai dataset. A heatmap was used to check for correlation among the features, and finally, four important features were selected. This was a multivariate regression problem. The final model had five convolutional layers, followed by five dense layers. Finally, the calculated values were tested against the labeled data, where the mean squared error was used as a performance metric.

Keywords: autonomous vehicles, deep learning, computer vision, artificial intelligence

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Authors: Thien Van Ngo

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The engineering design process is a systematic approach to solving problems. It involves identifying a problem, brainstorming solutions, prototyping and testing solutions, and evaluating the results. The engineering design process can be used to teach students how to solve problems in a creative and innovative way. The research aim of this study was to investigate the effectiveness of using the engineering design process to enhance student learning outcomes in a physics course. A mixed research method was used in this study. The quantitative data were collected using a pretest-posttest control group design. The qualitative data were collected using semi-structured interviews. The sample was 150 first-year students in the Department of Mechanical Engineering Technology at Cao Thang Technical College in Vietnam in the 2022-2023 school year. The quantitative data were collected using a pretest-posttest control group design. The pretest was administered to both groups at the beginning of the study. The posttest was administered to both groups at the end of the study. The qualitative data were collected using semi-structured interviews with a sample of eight students in the experimental group. The interviews were conducted after the posttest. The quantitative data were analyzed using independent sample T-tests. The qualitative data were analyzed using thematic analysis. The quantitative data showed that students in the experimental group, who were taught using the engineering design process, had significantly higher post-test scores on physics problem-solving than students in the control group, who were taught using the conventional method. The qualitative data showed that students in the experimental group were more motivated and engaged in the learning process than students in the control group. Students in the experimental group also reported that they found the engineering design process to be a more effective way of learning physics. The findings of this study suggest that the engineering design process can be an effective way of enhancing student learning outcomes in physics courses. The engineering design process engages students in the learning process and helps them to develop problem-solving skills.

Keywords: engineering design process, problem-solving, learning outcome of physics, students’ physics competencies, deep learning

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a hybrid distributed algorithm has been suggested for multi-objective dynamic flexible job shop scheduling problem. The proposed algorithm is high level, in which several algorithms search the space on different machines simultaneously also it is a hybrid algorithm that takes advantages of the artificial intelligence, evolutionary and optimization methods. Distribution is done at different levels and new approaches are used for design of the algorithm. Apache spark and Hadoop frameworks have been used for the distribution of the algorithm. The Pareto optimality approach is used for solving the multi-objective benchmarks. The suggested algorithm that is able to solve large-size problems in short times has been compared with the successful algorithms of the literature. The results prove high speed and efficiency of the algorithm.

Keywords: distributed algorithms, apache-spark, Hadoop, flexible dynamic job shop scheduling, multi-objective optimization

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Authors: R. Nagarani

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An intrinsic property of software in a real-world environment is its need to evolve, which is usually accompanied by the increase of software complexity and deterioration of software quality, making software maintenance a tough problem. Refactoring is regarded as an effective way to address this problem. Many refactoring approaches at the method and class level have been proposed. But the extent of research on software refactoring at the package level is less. This work presents a novel approach to refactor the package structures of object oriented software using genetic algorithm based community detection. It uses software networks to represent classes and their dependencies. It uses a constrained community detection algorithm to obtain the optimized community structures in software networks, which also correspond to the optimized package structures. It finally provides a list of classes as refactoring candidates by comparing the optimized package structures with the real package structures.

Keywords: community detection, complex network, genetic algorithm, package, refactoring

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Authors: Petcharat Kerdonfag, Supunnee Thrakul

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School health services through regular screening of school students’ health status have been the main responsibility for community or school health nurses. The purposes of these retrospective study were to assess and compare health problems between government and private primary school students in the central region of Thailand. The data were collected from the school health records in October at the end of the first semester in the academic year 2018. Two thousand and fifty primary school health records from government and private primary schools were gathered to assess health problems regarding anthropometric measurements, physical examination/personal hygiene, and clinical findings for this study. Descriptive statistics and Chi-square were used to be analyzed. The results revealed that health problems of all the school students remained high magnitude. The five top ranks for prevalence rate of health problems were dental caries (36.6%), visual acuity problem (27.7%), over-nutrition (16.8%), head lice (12.8%), and under-nutrition (6.8%), respectively. However, when compared between government and private schools among five health problems; dental caries (55.0% vs 19.9%), visual acuity problem (23.1% vs 31.9%), over-nutrition (20.2% vs 13.8%), head lice (26.5% vs 0.3%), and under-nutrition (10.6% vs 3.4%) with Chi-square analysis, there were significantly different (p < .001). The problem of visual acuity seems to be more serious in private schools while other health problems tend to be more critical in government schools. The findings have suggested that parents who have children in the private primary schools should pay more attention to visual health defects whereas parents with children in the government school should pay more vigilance regards to hygiene and health behavior problems.

Keywords: community health nursing, school health service, health status, primary school children

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Authors: María Dolores Caro, Eugenio M. Fedriani, Ángel F. Tenorio

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When lorries transport dangerous goods, there exist some legal stipulations in the European Union for assuring the security of the rest of road users as well as of those goods being transported. At this respect, lorry drivers cannot park in usual parking areas, because they must use parking areas with special conditions, including permanent supervision of security personnel. Moreover, drivers are compelled to satisfy additional regulations about resting and driving times, which involve in the practical possibility of reaching the suitable parking areas under these time parameters. The “European Agreement concerning the International Carriage of Dangerous Goods by Road” (ADR) is the basic regulation on transportation of dangerous goods imposed under the recommendations of the United Nations Economic Commission for Europe. Indeed, nowadays there are no enough parking areas adapted for dangerous goods and no complete study have suggested the best locations to build new areas or to adapt others already existing to provide the areas being necessary so that lorry drivers can follow all the regulations. The goal of this paper is to show how many additional parking areas should be built in the Iberian Peninsula to allow that lorry drivers may park in such areas under their restrictions in resting and driving time. To do so, we have modeled the problem via graph theory and we have applied a new efficient algorithm which determines an optimal solution for the problem of locating new parking areas to complement those already existing in the ADR for the Iberian Peninsula. The solution can be considered minimal since the number of additional parking areas returned by the algorithm is minimal in quantity. Obviously, graph theory is a natural way to model and solve the problem here proposed because we have considered as nodes: the already-existing parking areas, the loading-and-unloading locations and the bifurcations of roads; while each edge between two nodes represents the existence of a road between both nodes (the distance between nodes is the edge's weight). Except for bifurcations, all the nodes correspond to parking areas already existing and, hence, the problem corresponds to determining the additional nodes in the graph such that there are less up to 100 km between two nodes representing parking areas. (maximal distance allowed by the European regulations).

Keywords: dangerous goods, parking areas, Iberian peninsula, graph-based modeling

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Authors: Alireza Mirrashid, Mohammad Khoshbin, Ali Atghaei, Hassan Shahbazi

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In various industries, smoke and fire are two of the most important threats in the workplace. One of the common methods for detecting smoke and fire is the use of infrared thermal and smoke sensors, which cannot be used in outdoor applications. Therefore, the use of vision-based methods seems necessary. The problem of smoke and fire detection is spatiotemporal and requires spatiotemporal solutions. This paper presents a method that uses spatial features along with temporal-based features to detect smoke and fire in the scene. It consists of three main parts; the task of each part is to reduce the error of the previous part so that the final model has a robust performance. This method also uses transformer modules to increase the accuracy of the model. The results of our model show the proper performance of the proposed approach in solving the problem of smoke and fire detection and can be used to increase workplace safety.

Keywords: attention, fire detection, smoke detection, spatio-temporal

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Authors: Xu Jie

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As a key network security method, cryptographic services must fully cope with problems such as the wide variety of cryptographic algorithms, high concurrency requirements, random job crossovers, and instantaneous surges in workloads. Its complexity and dynamics also make it difficult for traditional static security policies to cope with the ever-changing situation. Cyber Threats and Environment. Traditional resource scheduling algorithms are inadequate when facing complex decision-making problems in dynamic environments. A network cryptographic resource allocation algorithm based on reinforcement learning is proposed, aiming to optimize task energy consumption, migration cost, and fitness of differentiated services (including user, data, and task security) by modeling the multi-job collaborative cryptographic service scheduling problem as a multi-objective optimized job flow scheduling problem and using a multi-agent reinforcement learning method, efficient scheduling and optimal configuration of cryptographic service resources are achieved. By introducing reinforcement learning, resource allocation strategies can be adjusted in real-time in a dynamic environment, improving resource utilization and achieving load balancing. Experimental results show that this algorithm has significant advantages in path planning length, system delay and network load balancing and effectively solves the problem of complex resource scheduling in cryptographic services.

Keywords: cloud computing, cryptography on-demand service, reinforcement learning, workflow scheduling

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Authors: Sung Ham, Chanho Song, Jiabin Wu

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Employees are commonly incentivized on both quantity and quality performance and much of the extant literature focuses on demonstrating that multitasking incentives lead to tradeoffs. Alternatively, we consider potential solutions to the tradeoff problem from both a theoretical and an experimental perspective. Across two field experiments from a call center, we find that tradeoffs can be mitigated when incentives are jointly enhanced across tasks, where previous research has suggested that incentives be reduced instead of enhanced. In addition, we also propose and test, in a laboratory setting, the implications of revising the metric used to assess quality. Our results indicate that metrics can be adjusted to align quality and quantity more efficiently. Thus, this alignment has the potential to thwart the classic tradeoff problem. Finally, we validate our findings with an economic experiment that verifies that effort is largely consistent with our theoretical predictions.

Keywords: incentives, multitasking, field experiment, experimental economics

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Authors: Bita Payami-Shabestari, Dariush Eslami

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The purpose of this paper is to develop a multi-product economic production quantity model under vendor management inventory policy and restrictions including limited warehouse space, budget, and number of orders, average shortage time and maximum permissible shortage. Since the “costs” cannot be predicted with certainty, it is assumed that data behave under uncertain environment. The problem is first formulated into the framework of a bi-objective of multi-product economic production quantity model. Then, the problem is solved with three multi-objective decision-making (MODM) methods. Then following this, three methods had been compared on information on the optimal value of the two objective functions and the central processing unit (CPU) time with the statistical analysis method and the multi-attribute decision-making (MADM). The results are compared with statistical analysis method and the MADM. The results of the study demonstrate that augmented-constraint in terms of optimal value of the two objective functions and the CPU time perform better than global criteria, and goal programming. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The contribution of this research is the use of random costs data in developing a multi-product economic production quantity model under vendor management inventory policy with several constraints.

Keywords: economic production quantity, random cost, supply chain management, vendor-managed inventory

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Authors: Ahmed Hammed, Wady Naanaa

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In this paper, we propose a general approach to deal with the problem of a convolutive mixture of images. We use a direct blind source separation method by adding only one non-statistical justified constraint describing the relationships between different mixing matrix at the aim to make its resolution easy. This method can be applied, provided that this constraint is known, to degraded document affected by the overlapping of text-patterns and images. This is due to chemical and physical reactions of the materials (paper, inks,...) occurring during the documents aging, and other unpredictable causes such as humidity, microorganism infestation, human handling, etc. We will demonstrate that this problem corresponds to a convolutive mixture of images. Subsequently, we will show how the validation of our method through numerical examples. We can so obtain clear images from unreadable ones which can be caused by pages superposition, a phenomenon similar to that we find every often in archival documents.

Keywords: blind source separation, convoluted mixture, degraded documents, text-patterns overlapping

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Authors: Ashwini Umale

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Trajectory planning and optimization is a fundamental problem in articulated robotics. It is often viewed as a two phase problem of initial feasible path planning around obstacles and subsequent optimization of a trajectory satisfying dynamical constraints. An optimized trajectory of multi-axis robot is important and directly influences the Performance of the executing task. Optimal is defined to be the minimum time to transition from the current speed to the set speed. In optimization of trajectory through virtual environment explores the most suitable way to represent robot motion from virtual environment to real environment. This paper aims to review the research of trajectory optimization in virtual environment using simulation software Robcad. Improvements are to be expected in trajectory optimization to generate smooth and collision free trajectories with minimization of overall robot cycle time.

Keywords: trajectory optimization, forward kinematics and reverse kinematics, dynamic constraints, robcad simulation software

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Authors: P. Priyanka, S. Shruthi, N. Guruprasad

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Health is a common theme in most cultures. In fact all communities have their concepts of health, as part of their culture. Health continues to be a neglected entity. Planning of Human diet should be done very careful by selecting the food items or groups of food items also the composition involved. Low price and good taste of foods are regarded as two major factors for optimal human nutrition. Linear programming techniques have been extensively used for human diet formulation for quiet good number of years. Through the process, we mainly apply “The Simplex Method” which is a very useful statistical tool based on the theorem of Elementary Row Operation from Linear Algebra and also incorporate some other necessary rules set by the Simplex Method to help solve the problem. The study done by us is an attempt to develop a programming model for optimal planning and best use of nutrient ingredients.

Keywords: diet formulation, linear programming, nutrient ingredients, optimization, simplex method

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Authors: Michał Jaśkiewicz

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The relation between walkability, place adherence, social relations and quality of life was explored in a Polish context. A considerable number of studies have suggested that environmental factors may influence the quality of life through indirect pathways. The list of possible psychological mediators includes social relations and identity-related variables. Based on the results of Study 1, local identity is a significant mediator in the relationship between neighbourhood walkability and quality of life. It was assumed that pedestrian-oriented neighbourhoods enable residents to interact and that these spontaneous interactions can help to strengthen a sense of local identity, thus influencing the quality of life. We, therefore, conducted further studies, testing the relationship experimentally in studies 2a and 2b. Participants were exposed to (2a) photos of walkable/non-walkable neighbourhoods or (2b) descriptions of high/low-walkable neighbourhoods. They were then asked to assess the walkability of the neighbourhoods and to evaluate their potential social relations and quality of life in these places. In both studies, social relations with neighbours turned out to be a significant mediator between walkability and quality of life. In Study 3, we implemented the measure of overlapping individual and communal identity (fusion with the neighbourhood) and willingness to collective action as mediators. Living in a walkable neighbourhood was associated with identity fusion with that neighbourhood. Participants who felt more fused expressed greater willingness to engage in collective action with other neighbours. Finally, this willingness was positively related to the quality of life in the city. In Study 4, we used commuting time (an aspect of walkability related to the time that people spend travelling to work) as the independent variable. The results showed that a shorter average daily commuting time was linked to more frequent social interactions in the neighbourhood. Individuals who assessed their social interactions as more frequent expressed a stronger city identification, which was in turn related to quality of life. To sum up, our research replicated and extended previous findings on the association between walkability and well-being measures. We introduced potential mediators of this relationship: social interactions in the neighbourhood and identity-related variables.

Keywords: walkability, quality of life, social relations, analysis of mediation

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Authors: Essam Al Daoud

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Genome rearrangement is an important area in computational biology and bioinformatics. The basic problem in genome rearrangements is to compute the edit distance, i.e., the minimum number of operations needed to transform one genome into another. Unfortunately, unsigned genome rearrangement problem is NP-hard. In this study an improved ant colony optimization algorithm to approximate the edit distance is proposed. The main idea is to convert the unsigned permutation to signed permutation and evaluate the ants by using Kaplan algorithm. Two new operations are added to the standard ant colony algorithm: Replacing the worst ants by re-sampling the ants from a new probability distribution and applying the crossover operations on the best ants. The proposed algorithm is tested and compared with the improved breakpoint reversal sort algorithm by using three datasets. The results indicate that the proposed algorithm achieves better accuracy ratio than the previous methods.

Keywords: ant colony algorithm, edit distance, genome breakpoint, genome rearrangement, reversal sort

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Authors: Aymen Gammoudi, Hamza Labbaci, Nizar Messai, Yacine Sam

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Web Service Composition (Mash-up) has been considered as a new approach used to offer the user a set of Web Services responding to his request. These approaches can return a set of similar Mash-ups in a given context that makes users unable to select the perfect one. Recent approaches focus on computing the skyline over a set of Quality of Service (QoS) attributes. However, these approaches are not sufficient in a dynamic web service environment where the delivered QoS by a Web service is inherently uncertain. In this paper, we treat the problem of computing the skyline over a set of similar Mash-ups under certain dimension values. We generate dimensions for each Mash-up using aggregation operations applied to the QoS attributes. We then tackle the problem of computing the skyline under uncertain dimensions. We present each dimension value of mash-up using a frame of discernment and introduce the d-dominance using the Evidence Theory. Finally, we propose our experimental results that show both the effectiveness of the introduced skyline extensions and the efficiency of the proposed approaches.

Keywords: web services, uncertain QoS, mash-ups, uncertain dimensions, skyline, evidence theory, d-dominance

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Authors: Ons Triki, Fathi Abid

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The basic objective of this paper is twofold. It resides in designing a model for a contingent convertible lease contract that can ensure the financial stability of a company and recover the losses of the parties to the lease in the event of default. It also aims to compare the convertible lease contract on inefficiencies resulting from the debt-overhang problem and asset substitution with other financing policies. From this perspective, this paper highlights the interaction between investments and financing policies in a dynamic model with existing assets and a growth option where the investment cost is financed by a contingent convertible lease and equity. We explore the impact of the contingent convertible lease on the capital structure. We also check the reliability and effectiveness of the use of the convertible lease contract as a means of financing. Findings show that the rental convertible contract with a sufficiently high conversion ratio has less severe inefficiencies arising from risk-shifting and debt overhang than those entailed by risky debt and pure-equity financing. The problem of underinvestment pointed out by Mauer and Ott (2000) and the problem of overinvestment mentioned by Hackbarth and Mauer (2012) may be reduced under contingent convertible lease financing. Our findings predict that the firm value under contingent convertible lease financing increases globally with asset volatility instead of decreasing with business risk. The study reveals that convertible leasing contracts can stand for a reliable solution to ensure the lessee and quickly recover the counterparties of the lease upon default.

Keywords: contingent convertible lease, growth option, debt overhang, risk-shifting, capital structure

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Authors: Ayala Kobo-Greenhut, Amos Notea, Izhar Ben-Shlomo

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In R&D projects, there is no doubt about the need to change a current concept to an alternative one over time (i.e., concept leaping). Concept leaping is required since with most R&D projects uncertainty is present as they take place in dynamic environments. Despite the importance of concept leaping when needed, R&D teams may fail to do so (i.e., frozen concept). This research suggests a possible reason why frozen concept happens in the framework of quality engineering and control engineering. We suggest that frozen concept occurs since concept determines the derived plan and its implementation may be considered as equivalent to a closed-loop process, and is subject to the problem of not recognizing gaps as failures. We suggest that although implementing quality practices into an R&D project’s routine has many advantages, it intensifies the frozen concept problem since working according to quality practices relates to exploitation of learning behavior, while leaping to a new concept relates to exploring learning behavior.

Keywords: closed loop, control engineering, design, leaping, frozen concept, quality engineering, quality practices

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Authors: Jorge A. Ruiz-Vanoye, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, Daniel Vélez-Díaz, Edith Olaco García

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In this paper, we present the use of the discriminant analysis to select evolutionary algorithms that better solve instances of the vehicle routing problem with time windows. We use indicators as independent variables to obtain the classification criteria, and the best algorithm from the generic genetic algorithm (GA), random search (RS), steady-state genetic algorithm (SSGA), and sexual genetic algorithm (SXGA) as the dependent variable for the classification. The discriminant classification was trained with classic instances of the vehicle routing problem with time windows obtained from the Solomon benchmark. We obtained a classification of the discriminant analysis of 66.7%.

Keywords: Intelligent Transportation Systems, data-mining techniques, evolutionary algorithms, discriminant analysis, machine learning

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Authors: Unchalee Inkampa, Tuanjai Somboonwiwat

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Painting process of automobiles and automobile parts, which is a continuous process based on EDP (Electrode position paint, EDP). Through EDP, all work pieces will be continuously sent to the painting process. Work process can be divided into 2 groups based on the running time: Painting Room 1 and Painting Room 2. This leads to continuous operation. The problem that arises is waiting for workloads onto Painting Room. The grading process EDP to Painting Room is a major problem. Therefore, this paper aim to develop production sequencing method by applying EDP to painting process. It also applied fixed rate launching for painting room and earliest due date (EDD) for EDP process and swap pairwise interchange for waiting time to a minimum of machine. The result found that the developed method could improve painting reduced waiting time, on time delivery, meeting customers wants and improved productivity of painting unit.

Keywords: sequencing, mixed model lines, painting process, electrode position paint

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Authors: Rihab Ben Lamine, Raoudha Ben Jemaa, Ikram Amous Ben Amor

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This paper proposes a graph planning technique for semantic adaptable Web Services composition. First, we use an ontology based context model for extending Web Services descriptions with information about the most suitable context for its use. Then, we transform the composition problem into a semantic context aware graph planning problem to build the optimal service composition based on user's context. The construction of the planning graph is based on semantic context aware Web Service discovery that allows for each step to add most suitable Web Services in terms of semantic compatibility between the services parameters and their context similarity with the user's context. In the backward search step, semantic and contextual similarity scores are used to find best composed Web Services list. Finally, in the ranking step, a score is calculated for each best solution and a set of ranked solutions is returned to the user.

Keywords: semantic web service, web service composition, adaptation, context, graph planning

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Authors: Jinlai Bian, Zailin Yang, Guanxixi Jiang, Xinzhu Li

Abstract:

The problem of elastic wave propagation in inhomogeneous medium has always been a classic problem. Due to the frequent occurrence of earthquakes, many economic losses and casualties have been caused, therefore, to prevent earthquake damage to people and reduce damage, this paper studies the dynamic response around the circular inclusion in the whole space with inhomogeneous modulus, the inhomogeneity of the medium is reflected in the shear modulus of the medium with the spatial position, and the density is constant, this method can be used to solve the problem of the underground buried pipeline. Stress concentration phenomena are common in aerospace and earthquake engineering, and the dynamic stress concentration factor (DSCF) is one of the main factors leading to material damage, one of the important applications of the theory of elastic dynamics is to determine the stress concentration in the body with discontinuities such as cracks, holes, and inclusions. At present, the methods include wave function expansion method, integral transformation method, integral equation method and so on. Based on the complex function method, the Helmholtz equation with variable coefficients is standardized by using conformal transformation method and wave function expansion method, the displacement and stress fields in the whole space with circular inclusions are solved in the complex coordinate system, the unknown coefficients are solved by using boundary conditions, by comparing with the existing results, the correctness of this method is verified, based on the superiority of the complex variable function theory to the conformal transformation, this method can be extended to study the inclusion problem of arbitrary shapes. By solving the dynamic stress concentration factor around the inclusions, the influence of the inhomogeneous parameters of the medium and the wavenumber ratio of the inclusions to the matrix on the dynamic stress concentration factor is analyzed. The research results can provide some reference value for the evaluation of nondestructive testing (NDT), oil exploration, seismic monitoring, and soil-structure interaction.

Keywords: circular inclusions, complex variable function, dynamic stress concentration factor (DSCF), inhomogeneous medium

Procedia PDF Downloads 135

Authors: Richa Grover, Rahul Grover, V. Balaji Rao, Kavish Kejriwal

Abstract:

Selection of suppliers is a crucial problem in the supply chain management. On top of that, sustainable supplier selection is the biggest challenge for the organizations. Environment protection and social problems have been of concern to society in recent years, and the traditional supplier selection does not consider about this factor; therefore, this research work focuses on introducing sustainable criteria into the structure of supplier selection criteria. Sustainable Supply Chain Management (SSCM) is the management and administration of material, information, and money flows, as well as coordination among business along the supply chain. All three dimensions - economic, environmental, and social - of sustainable development needs to be taken care of. Purpose of this research is to maximize supply chain profitability, maximize social wellbeing of supply chain and minimize environmental impacts. Problem statement is selection of suppliers in a sustainable supply chain network by ranking the suppliers against sustainable criteria identified. The aim of this research is twofold: To find out what are the sustainable parameters that can be applied to the supply chain, and to determine how these parameters can effectively be used in supplier selection. Multicriteria decision making tools will be used to rank both criteria and suppliers. AHP Analysis will be used to find out ratings for the criteria identified. It is a technique used for efficient decision making. TOPSIS will be used to find out rating for suppliers and then ranking them. TOPSIS is a MCDM problem solving method which is based on the principle that the chosen option should have the maximum distance from the negative ideal solution (NIS) and the minimum distance from the ideal solution.

Keywords: sustainable supply chain management, sustainable criteria, MCDM tools, AHP analysis, TOPSIS method

Procedia PDF Downloads 325