Search results for: forklift allocation

Authors: Jaechun No

Abstract:

As the technology of NAND flash memory rapidly grows, SSD is becoming an excellent alternative for storage solutions, because of its high random I/O throughput and low power consumption. These SSD potentials have drawn great attention from IT enterprises that seek for better I/O performance. However, high SSD cost per capacity makes it less desirable to construct a large-scale storage subsystem solely composed of SSD devices. An alternative is to build a hybrid storage subsystem where both HDD and SSD devices are incorporated in an economic manner, while employing the strengths of both devices. This paper presents a hybrid file system, called hybridFS, that attempts to utilize the advantages of HDD and SSD devices, to provide a single, virtual address space by integrating both devices. HybridFS not only proposes an efficient implementation for the file management in the hybrid storage subsystem but also suggests an experimental framework for making use of the excellent features of existing file systems. Several performance evaluations were conducted to verify the effectiveness and suitability of hybridFS.

Keywords: hybrid file mapping, data layout, hybrid device integration, extent allocation

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Authors: Ferinar Moaidi, Mahdi Moaidi

Abstract:

Environmental issues and the ever-increasing in demand of electrical energy make it necessary to have distributed generation (DG) resources in the power system. In this research, in order to realize the goals of reducing losses and improving the voltage profile in a microgrid, the allocation and sizing of DGs have been used. The proposed Genetic Algorithm (GA) is described from the array of artificial intelligence methods for solving the problem. The algorithm is implemented on the IEEE 33 buses network. This study is presented in two scenarios, primarily to illustrate the effect of location and determination of DGs has been done to reduce losses and improve the voltage profile. On the other hand, decisions made with the one-level assumptions of load are not universally accepted for all levels of load. Therefore, in this study, load modelling is performed and the results are presented for multi-levels load state.

Keywords: distributed generation, genetic algorithm, microgrid, load modelling, loss reduction, voltage improvement

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Authors: Patrick Mbassegue, Mickael Gardoni

Abstract:

In a market environment centered more and more on services and the digital economy, knowledge management becomes a framework that can help organizations to create value and to improve their overall performance. Based on an optimal allocation of scarce resources, managers are interested in demonstrating the added value generated by knowledge management projects. One of the challenges faced by organizations is the difficulty in measuring impacts and concrete results of knowledge management initiatives. The present article concerns the measure of concrete results coming from knowledge management projects based on balance scorecard model. One of the goals is to underline what can be done based on this model but also to highlight the limits associated. The present article is structured in five parts; 1-knowledge management projects and organizational impacts; 2- a framework and a methodology to measure organizational impacts; 3- application illustrated in two case studies; 4- limits concerning the proposed framework; 5- the proposal of a new framework to measure organizational impacts.

Keywords: knowledge management, project, balance scorecard, impacts

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Authors: Salami Akeem Olanrewaju

Abstract:

The transportation models or problems are primarily concerned with the optimal (best possible) way in which a product produced at different factories or plants (called supply origins) can be transported to a number of warehouses or customers (called demand destinations). The objective in a transportation problem is to fully satisfy the destination requirements within the operating production capacity constraints at the minimum possible cost. The objective of this study is to determine ways of minimizing transport cost in order to maximum profit. Data were gathered from the records of the Distribution Department of 7-Up Bottling Company Plc. Ilorin, Kwara State, Nigeria. The data were analyzed using SPSS (Statistical Package for Social Sciences) while applying the three methods of solving a transportation problem. The three methods produced the same results; therefore, any of the method can be adopted by the company in transporting its final products to the wholesale dealers in order to minimize total production cost.

Keywords: cost minimization, resources utilization, distribution system, allocation problem

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Authors: Tamar Trop

Abstract:

Bike sharing systems can be important elements of smart cities as they have the potential for impact on multiple levels. These systems can add a significant alternative to other modes of mass transit in cities that are continuously looking for measures to become more livable and maintain their attractiveness for citizens, businesses and tourism. Bike-sharing began in Europe in 1965, and a viable format emerged in the mid-2000s thanks to the introduction of information technology. The rate of growth in bike-sharing schemes and fleets has been very rapid since 2008 and has probably outstripped growth in every other form of urban transport. Today, public bike-sharing systems are available on five continents, including over 700 cities, operating more than 800,000 bicycles at approximately 40,000 docking stations. Since modern bike sharing systems have become prevalent only in the last decade, the existing literature analyzing these systems and their sustainability is relatively new. The purpose of the presented study is to assess the sustainability of these newly emerging transportation systems, by using the Envision™ rating system as a methodological framework and the Israeli 'Tel -O-Fun' – bike sharing project as a case study. The assessment was conducted by project team members. Envision™ is a new guidance and rating system used to assess and improve the sustainability of all types and sizes of infrastructure projects. This tool provides a holistic framework for evaluating and rating the community, environmental, and economic benefits of infrastructure projects over the course of their life cycle. This evaluation method has 60 sustainability criteria divided into five categories: Quality of life, leadership, resource allocation, natural world, and climate and risk. 'Tel -O-Fun' project was launched in Tel Aviv-Yafo on 2011 and today provides about 1,800 bikes for rent, at 180 rental stations across the city. The system is based on a complex computer terminal that is located in the docking stations. The highest-rated sustainable features that the project scored include: (a) Improving quality of life by: offering a low cost and efficient form of public transit, improving community mobility and access, enabling the flexibility of travel within a multimodal transportation system, saving commuters time and money, enhancing public health and reducing air and noise pollution; (b) improving resource allocation by: offering inexpensive and flexible last-mile connectivity, reducing space, materials and energy consumption, reducing wear and tear on public roads, and maximizing the utility of existing infrastructure, and (c) reducing of greenhouse gas emissions from transportation. Overall, 'Tel -O-Fun' project was highly scored as an environmentally sustainable and socially equitable infrastructure. The use of this practical framework for evaluation also yielded various interesting insights on the shortcoming of the system and the characteristics of good solutions. This can contribute to the improvement of the project and may assist planners and operators of bike sharing systems to develop a sustainable, efficient and reliable transportation infrastructure within smart cities.

Keywords: bike sharing, Envision™, sustainability rating system, sustainable infrastructure

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Authors: Roli Pradhan

Abstract:

All over the globe, the resources of the government are declining, and the funding requirements in education are on a constant rise. The governments are desperately increasing the budgetary allocation for higher education, the economic plans have been labeling investment in higher education to be immensely vital for development of the nation. Still the fact is that the government of the developing nations like India lacks the potential to fund the rising demands of this sector. In the face of declining government funding for higher education, there are the growing needs and justifiable pressure for direct beneficiaries to bear a reasonable part of the cost of higher education. The supply-demand gap in higher education in India is on the increase. This paper evaluates the Indian National Education Policy over the past three decades, furnishes the need of financing of education by private players. The paper also covers the aspects of incorporating the different forms of financing in education and also focuses on the regulations pertaining to quality maintenance in the education system. The paper also targets to suggest policy imperatives for the future education policy for India.

Keywords: national education policy, privatisation, private financing, government funding

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Authors: Agria Rhamdhan

Abstract:

WhatsApp as the most popular mobile messaging app has been used as evidence in many criminal cases. As the use of mobile messages generates large amounts of data, forensic investigation faces the challenge of large data problems. The hardest part of finding this important evidence is because current practice utilizes tools and technique that require manual analysis to check all messages. That way, analyze large sets of mobile messaging data will take a lot of time and effort. Our work offers methodologies based on forensic triage to reduce large data to manageable sets resulting easier to do detailed reviews, then show the results through interactive visualization to show important term, entities and relationship through intelligent ranking using Term Frequency-Inverse Document Frequency (TF-IDF) and Latent Dirichlet Allocation (LDA) Model. By implementing this methodology, investigators can improve investigation processing time and result's accuracy.

Keywords: forensics, triage, visualization, WhatsApp

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Authors: Yuanjin Liu

Abstract:

Retirement withdrawal strategies are very important to minimize the probability of ruin in retirement. The ruin probability is modeled as a function of initial withdrawal age, gender, asset allocation, inflation rate, and initial withdrawal rate. The ruin probability is obtained based on the 2019 period life table for the Social Security, IRS Required Minimum Distribution (RMD) Worksheets, US historical bond and equity returns, and inflation rates using simulation. Several popular machine learning algorithms of the generalized additive model, random forest, support vector machine, extreme gradient boosting, and artificial neural network are built. The model validation and selection are based on the test errors using hyperparameter tuning and train-test split. The optimal model is recommended for retirees to monitor the ruin probability. The optimal withdrawal strategy can be obtained based on the optimal predictive model.

Keywords: ruin probability, retirement withdrawal strategies, predictive models, optimal model

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Authors: Fernando P. Silva, Valter J. S. Leite, Erivelton G. Nepomuceno

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In this paper, a nonlinear controller design for an omnidirectional mobile is presented. The robot controller consists of an inner-loop controller and an outer-loop controller, the first is designed using state feedback (robust allocation) and the second controller is designed based on Robust Multi Inversion (RMI) approach. The objective of RMI controller is rendering the robust inversion of the dynamic, when the model is affected by uncertainties. A model nonlinear MIMO of an omni-directional robot (small-league of Robocup) is used to simulate the RMI approach. The parameters of linear and nonlinear model are varied to cause modelling uncertainties among the model and the real model (real system) generating an error in inner-loop controller signal that must be compensated by RMI controller. The simulation test results show that the RMI is capable of compensating the uncertainties and keep the system stable and controlled under uncertainties.

Keywords: robust multi inversion, omni-directional robot, robocup, nonlinear control

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Authors: Kamalendu Pal

Abstract:

Supply chains are the spinal cord of trade and commerce. Their logistics use different transport corridors on regular basis for operational purpose. The international supply chain transport corridors include different infrastructure elements (e.g. weighbridge, package handling equipment, border clearance authorities, and so on) in supply chains. This paper presents the use of multi-agent systems (MAS) to model and simulate some aspects of transportation corridors, and in particular the area of weighbridge resource optimization for operational profit generation purpose. An underlying multi-agent model provides a means of modeling the relationships among stakeholders in order to enable coordination in a transport corridor environment. Simulations of the costs of container unloading, reloading, and waiting time for queuing up tracks have been carried out using data sets. Results of the simulation provide the potential guidance in making decisions about optimal service resource allocation in a trade corridor.

Keywords: multi-agent systems, simulation, supply chain, transport corridor, weighbridge

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Authors: Regita P. Permata, Ulfa S. Nuraini

Abstract:

Traveling Salesman Problem (TSP) is the most studied problem in combinatorial optimization. In simple language, TSP can be described as a problem of finding a minimum distance tour to a city, starting and ending in the same city, and exactly visiting another city. In product distribution, companies often get problems in determining the minimum distance that affects the time allocation. In this research, we aim to apply TSP heuristic methods to simulate nodes as city coordinates in product distribution. The heuristics used are sub tour reversal, nearest neighbor, farthest insertion, cheapest insertion, nearest insertion, and arbitrary insertion. We have done simulation nodes using Euclidean distances to compare the number of cities and processing time, thus we get optimum heuristic method. The results show that the optimum heuristic methods are farthest insertion and nearest insertion. These two methods can be recommended to solve product distribution problems in certain companies.

Keywords: Euclidean, heuristics, simulation, TSP

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Authors: Rama Seth, Luise Noring, Pratim Majumdar

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Based on an extensive literature review, this paper presents distinct approaches to value, quantify and trade ecosystem services, with particular emphasis on services provided by mangroves and wetlands. Building on diverse monetary and market-based systems for the improved allocation of natural resources, such trading and exchange-based methods can help tackle the degradation of ecosystem services in a more targeted and structured manner than achievable with stand-alone policy and administrative regulations. Using various threads of literature, the paper proposes a platform that serves as the skeletal foundation for developing an efficient global market for ecosystem services trading. The paper bridges a significant research and practice gap by recommending how to establish an equilibrium in the biosphere via trading mechanisms while also discovering other research gaps and future research potential in the domain of ecosystem valuation.

Keywords: environment, economics, mangroves, wetlands, markets, ESG, global capital, climate investments, valuation, ecosystem services

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Authors: Samira Alvandi

Abstract:

In the context of the circular economy, production planning aims to eliminate waste and emissions and maximize resource efficiency. Historically production planning is challenged through arrays of uncertainty and complexity arising from the interdependence and variability of products, processes, and systems. Manufacturers worldwide are facing new challenges in tackling various environmental issues such as climate change, resource depletion, and land degradation. In managing the inherited complexity and uncertainty and yet maintaining profitability, the manufacturing sector is in need of a holistic framework that supports energy efficiency and carbon emission reduction schemes. The proposed framework addresses the current challenges and integrates simulation modeling with optimization for finding optimal machine-job allocation to maximize throughput and total energy consumption while minimizing lead time. The aluminium refinery facility in western Sydney, Australia, is used as an exemplar to validate the proposed framework.

Keywords: smart production planning, simulation-optimisation, energy aware capacity planning, energy intensive industries

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Authors: Cagri Memis, Muzaffer Kapanoglu

Abstract:

The school bus routing problem (SBRP) is a variant of the Vehicle Routing Problem (VRP) classified as a location-allocation-routing problem. In this study, the SBRP is decomposed into two sub-problems: (1) bus route generation and (2) bus stop selection to solve large instances of the SBRP in reasonable computational times. To solve the first sub-problem, we propose a genetic algorithm to generate bus routes. Once the routes have been fixed, a sub-problem remains of allocating students to stops considering the capacity of the buses and the walkability constraints of the students. While the exact method solves small-scale problems, treating large-scale problems with the exact method becomes complex due to computational problems, a deficiency that the genetic algorithm can overcome. Results obtained from the proposed approach on 150 instances up to 250 stops show that the matheuristic algorithm provides better solutions in reasonable computational times with respect to benchmark algorithms.

Keywords: genetic algorithm, matheuristic, school bus routing problem, vehicle routing problem

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Authors: Evelyn Fabian

Abstract:

The focus of this discussion centres on the emerging issues in Early Childhood Care and development in Nigeria. Early childhood care is the bedrock of Nigeria’s educational system. However, there are critical issues that had not been addressed and it is frustrating the entire educational process. Thus, this paper will show the inter-connectedness between these issues such as poor funding, trained skillful teachers that would supervise the learning process of the kids, unconducive learning environment and lack of relevant facilities. For a clear grasp of these issues, the researcher visited 36 early childhood centres distributed across the 36 spates of Nigeria. The findings which were expressed in simple percentages revealed a near total absence or government neglect of these critical areas. The findings equally showed a misplaced priority in the government allocation of funds to early child care education and development. The study concludes that this mismatch in the training of these categories of pupils, government should expedite action in addressing these emerging issues in early childhood care and development in Nigeria.

Keywords: early childhood, ECCE, education, emerging issues

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Authors: Oualid Walid Ben Ali

Abstract:

Big Data has become one of the buzzwords today. The recent explosion of digital data has led the organization, either private or public, to a new era towards a more efficient decision making. At some point, business decided to use that concept in order to learn what make their clients tick with phrases like ‘sales funnel’ analysis, ‘actionable insights’, and ‘positive business impact’. So, it stands to reason that Big Data was viewed through green (read: money) colored lenses. Somewhere along the line, however someone realized that collecting and processing data doesn’t have to be for business purpose only, but also could be used for other purposes to assist law enforcement or to improve policing or in road safety. This paper presents briefly, how Big Data have been used in the fields of policing order to improve the decision making process in the daily operation of the police. As example, we present a big-data driven system which is sued to accurately dispatch the patrol cars in a geographic environment. The system is also used to allocate, in real-time, the nearest patrol car to the location of an incident. This system has been implemented and applied in the Emirate of Abu Dhabi in the UAE.

Keywords: big data, big data analytics, patrol car allocation, dispatching, GIS, intelligent, Abu Dhabi, police, UAE

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Authors: Marwa Sahnoun, Chokri Abdennadher

Abstract:

This article comes, very timely, to look at the effectiveness of active labor market policies (ALMP) in improving labor market outcomes. Using panel data estimates for 19 European countries during the period 2000-2012, this article showed the role of institutional factors, especially the role of employment policies implementation based on three variables: the allocation of resources for the implementation of policies, continuity and timing in the implementation of policies to capture their effectiveness on the labor market. Empirical results shows favor effect of training, employment incentives, sheltered employment and rehabilitation and direct job creation on the entire population employment growth. Results shows also that start-up incentives seems to be more effective in increasing employment than other types of policies. Importantly, two aspects are important in terms of implementation: public expenditure on program administration, e.g. (PES) watches the most favorable aspect and the continuity of policies implemented.

Keywords: active labor market policies, implementation, public expenditure on program administration, start-up incentives, training

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Authors: Stephen Wheat

Abstract:

Institutional mobile application governance and distribution processes are essential to mobile app innovation. The absence of effective processes poses a significant barrier to the development and adoption of mobile apps for use within a research enterprise and also impedes the translational science of applying research apps in clinical and engineering settings. To accelerate mobile app innovation and adoption, Emory University and Emory Healthcare implemented a three-pronged strategy including. I) Mobile app review and distribution policies and processes. II) Mobile app management infrastructure and mobile app foundation components. III) A strategic sourcing strategy based on preferred mobile app development firms. The results have been an increase from five to 56 mobile apps in the pipeline over three years; increased engagement from technology transfer, legal counsel, compliance, and information security; articulation of a coordinated mobile app strategy; and allocation of more institutional resources toward specific mobile technology and mobile application goals.

Keywords: mobile app management, governance, distribution, information security

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Authors: Mohammad H. Almomani

Abstract:

In this paper, we argue the effect of the initial sample size, and the increment in simulation samples on the performance of a sequential approach that used in selecting the top m designs when the number of alternative designs is very large. The sequential approach consists of two stages. In the first stage the ordinal optimization is used to select a subset that overlaps with the set of actual best k% designs with high probability. Then in the second stage the optimal computing budget is used to select the top m designs from the selected subset. We apply the selection approach on a generic example under some parameter settings, with a different choice of initial sample size and the increment in simulation samples, to explore the impacts on the performance of this approach. The results show that the choice of initial sample size and the increment in simulation samples does affect the performance of a selection approach.

Keywords: Large Scale Problems, Optimal Computing Budget Allocation, ordinal optimization, simulation optimization

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Authors: Jeonghwan Jeon

Abstract:

As the science and technology (S&T) has been rapidly advanced, the national government attempts to reflect changes in the S&T for promoting public R&D activities and economic development. Amongst others, due to the rapid advances and changes of S&T, it becomes important to analyze the trends of S&T policies for formulating the new policy and investigating promising S&T fields. Thus, this paper aims to trace the national S&T policies during this decade for analyzing the change of major S&T fields in the case of South Korea. As one of the organization for S&T policy in South Korea, the National Science and Technology Council (NSTC) has been established to coordinate inter-ministerial policies and programs and to determine all of the national and public S&T policy of South Korea. In this regard, the items on national S&T policy determined by the NSTC are useful for understanding the needs for major S&T fields and adapting to the rapid change of S&T. To this end, we first gathered the data on 512 items on the S&T agenda from 1999 to 2013. Based on these items, the trend of S&T policies is monitored and the major S&T fields are derived. Differences of policy purposes between S&T fields are identified to provide guideline for policy making such as budget allocation or investment promotion as well.

Keywords: national science and technology, policy, trends, S&T field

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

Abstract:

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

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

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Authors: Adeolu O. Dairo

Abstract:

Getting the consumer marketing strategy right is a crucial and complex task for firms with a large customer base such as mobile operators in a competitive mobile market. While empirical studies have made efforts to identify key constructs, no geospatial model has been developed to comprehensively assess the viability and interdependency of ground realities regarding the customer, competition, channel and the network quality of mobile operators. With this research, a geo-analytic framework is proposed for strategy formulation and allocation for mobile operators. Firstly, a fuzzy analytic network using a self-organizing feature map clustering technique based on inputs from managers and literature, which depicts the interrelationships amongst ground realities is developed. The model is tested with a mobile operator in the Nigeria mobile market. As a result, a customer-centric geospatial and visualization solution is developed. This provides a consolidated and integrated insight that serves as a transparent, logical and practical guide for strategic, tactical and operational decision making.

Keywords: geospatial, geo-analytics, self-organizing map, customer-centric

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Authors: Oscar Javier Herrera Ochoa, Ivan Dario Romero Fonseca

Abstract:

This paper presents a design of a model for planning the distribution logistics operation. The significance of this work relies on the applicability of this fact to the analysis of small and medium enterprises (SMEs) of dry freight in Bogotá. Two stages constitute this implementation: the first one is the place where optimal planning is achieved through a hybrid model developed with mixed integer programming, which considers the transhipment operation based on a combined load allocation model as a classic transshipment model; the second one is the specific routing of that operation through the heuristics of Clark and Wright. As a result, an integral model is obtained to carry out the step by step planning of the distribution of dry freight for SMEs in Bogotá. In this manner, optimum assignments are established by utilizing transshipment centers with that purpose of determining the specific routing based on the shortest distance traveled.

Keywords: transshipment model, mixed integer programming, saving algorithm, dry freight transportation

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Authors: Jeonghwan Jeon

Abstract:

As the science and technology(S&T) has been rapidly advanced, the national government attempts to reflect changes in the S&T for promoting public R&D activities and economic development. Amongst others, due to the rapid advances and changes of S&T, it becomes important to monitor the trends of S&T policies for formulating the new policy and investigating promising S&T fields. Thus, this paper aims to trace the national S&T policies during this decade for monitoring the change of major S&T fields in the case of South Korea. As one of the organization for S&T policy in South Korea, the National Science and Technology Council (NSTC) has been established to coordinate inter-ministerial policies and programs and to determine all of the national and public S&T policy of South Korea. In this regard, the items on national S&T policy determined by the NSTC are useful for understanding the needs for major S&T fields and adapting to the rapid change of S&T. To this end, we first gathered the data on 512 items on the S&T agenda from 1999 to 2013. Based on these items, the trend of S&T policies is monitored and the major S&T fields are derived. Differences of policy purposes between S&T fields are identified to provide guideline for policy making such as budget allocation or investment promotion as well.

Keywords: science and technology policy, trends, S&T field, monitoring

Procedia PDF Downloads 289

Authors: Ebrahim Fataei, Seyed Ali Hosseini, Zahra Arabi, Habib farhadi, Mehdi Aalipour Erdi, Seiied Taghi Seiied Safavian

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Solid waste production is an integral part of human life and management of waste require full scientific approach and essential planning. The allocation of most management cost to collection and transportation and also the necessity of operational efficiency in this system, by limiting time consumption, and on the other hand optimum collection system and transportation is the base of waste design and management. This study was done to optimize the exits collection and transportation system of solid waste in Meshkinshahr city. So based on the analyzed data of municipal solid waste components in seven zones of Meshkinshahr city, and GIS software, applied to design storage place based on origin recycling and a route to collect and transport. It was attempted to represent an appropriate model to store, collect and transport municipal solid waste. The result shows that GIS can be applied to locate the waste container and determine a waste collection direction in an appropriate way.

Keywords: municipal solid waste management, transportation, optimizing, GIS, Iran

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Authors: Shuen-Tai Wang, Yu-Ching Lin

Abstract:

With more and more workflow systems adopting cloud as their execution environment, it presents various challenges that need to be addressed in order to be utilized efficiently. This paper introduces a method for resource provisioning based on our previous research of dynamic allocation and its pipeline processes. We present an abstraction for workload scheduling in which independent tasks get scheduled among various available processors of distributed computing for optimization. We also propose an integrated web-based workflow designer by taking advantage of the HTML5 technology and chaining together multiple tools. In order to make the combination of multiple pipelines executing on the cloud in parallel, we develop a script translator and an execution engine for workflow management in the cloud. All information is known in advance by the workflow engine and tasks are allocated according to the prior knowledge in the repository. This proposed effort has the potential to provide support for process definition, workflow enactment and monitoring of workflow processes. Users would benefit from the web-based system that allows creation and execution of pipelines without scripting knowledge.

Keywords: workflow systems, resources provisioning, workload scheduling, web-based, workflow engine

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Authors: Mohsen Mazidi, Ali Abbaspour, Mahmud Fotuhi-Firuzabad, Mohamamd Rastegar

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To tackle the air pollution issues, Plug-in Hybrid Electric Vehicles (PHEVs) are proposed as an appropriate solution. Charging a large amount of PHEV batteries, if not controlled, would have negative impacts on the distribution system. The control process of charging of these vehicles can be centralized in parking lots that may provide a chance for better coordination than the individual charging in houses. In this paper, an optimization-based approach is proposed to determine the optimum PHEV parking capacities in candidate nodes of the distribution system. In so doing, a profile for charging and discharging of PHEVs is developed in order to flatten the network load profile. Then, this profile is used in solving an optimization problem to minimize the distribution system losses. The outputs of the proposed method are the proper place for PHEV parking lots and optimum capacity for each parking. The application of the proposed method on the IEEE-34 node test feeder verifies the effectiveness of the method.

Keywords: loss, plug-in hybrid electric vehicle (PHEV), PHEV parking lot, V2G

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Authors: Guillaume Craveur

Abstract:

The work presented here shows a study on several parameters identified as influencing dwell times for trains. Three kinds of rolling stocks are studied for this project and the parameters presented are the number of passengers, the allocation of passengers, their priorities, the platform station height, the door width and the train design. In order to make this study, a lot of records have been done in several stations in Paris (France). Then, in order to study these parameters, numerical simulations are completed. The goal is to quantify the impact of each parameter on the dwelling times. For example, this study highlights the impact of platform height and the presence of steps between the platform and the train. Three types of station platforms are concerned by this study : ‘optimum’ station platform which is 920 mm high, standard station platform which is 550 mm high, and high station platform which is 1150 mm high and different kinds of steps exist in order to fill these gaps. To conclude, this study shows the impact of these parameters on dwell times and their impact in function of the size of population.

Keywords: dwell times, numerical tools, rolling stock, platforms

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Authors: Sandesh Achar

Abstract:

Artificial intelligence is being increasingly incorporated into many applications across various sectors such as health, education, security, and agriculture. Recently, there has been rapid development in cloud computing technology, resulting in AI’s implementation into cloud computing to enhance and optimize the technology service rendered. The deployment of AI in cloud-based applications has brought about autonomous computing, whereby systems achieve stated results without human intervention. Despite the amount of research into autonomous computing, work incorporating AI/ML into cloud computing to enhance its performance and resource allocation remain a fundamental challenge. This paper highlights different manifestations, roles, trends, and challenges related to AI-based cloud computing models. This work reviews and highlights excellent investigations and progress in the domain. Future directions are suggested for leveraging AI/ML in next-generation computing for emerging computing paradigms such as cloud environments. Adopting AI-based algorithms and techniques to increase operational efficiency, cost savings, automation, reducing energy consumption and solving complex cloud computing issues are the major findings outlined in this paper.

Keywords: artificial intelligence, cloud computing, deep learning, machine learning, internet of things

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Authors: Xin Jie Li

Abstract:

Due to population agglomeration, huge scale, and complex activities, megacities have become risk centers. To resist the risks brought by development uncertainty, the construction of resilient cities has become a common strategic choice for megacities. As a key link in promoting the modernization of the national governance system and governance capacity, optimizing the layout of national land space that focuses on ecology, production, and life and improving the rationality of spatial resource allocation are conducive to fundamentally promoting the resilience construction of megacities. Therefore, based on the perspective of territorial space governance, this article explores the potential risks faced by the territorial space of megacities and proposes possible paths for the resilience construction of megacities from four aspects: promoting the construction of a resilience system throughout the entire life cycle, constructing a disaster prevention and control system with ecological resilience, creating an industrial spatial pattern with production resilience, and enhancing community resilience to anchor the front line of risk response in megacities.

Keywords: mega cities, potential risks, resilient city construction, territorial and spatial governance

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