Search results for: fund allocation

Authors: Oscar Javier Herrera Ochoa, Ivan Dario Romero Fonseca

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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

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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

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Authors: Keunock Lew, Seungryul Ma

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The paper analyzes risk and expected return of lenders who provide mortgage loans to households in the shared mortgage program of Korea. In 2013, the Korean government introduced the mortgage program to help low income householders to convert their renting into purchasing houses. The financial source for the mortgage program is the Urban Housing Fund set up by the Korean government. Through the program, low income households can borrow money from lenders to buy a house at a very low interest rate (e.g. 1 % per year) for a long time. The motivation of adopting this mortgage program by the Korean government is that the cost of renting houses has been rapidly increased especially in large urban areas during the past decade, which became financial difficulties to low income households who do not have their own houses. As the analysis methodology, the paper uses a spread sheet model for projecting cash flows of the mortgage product over the period of loan contract. It also employs Monte Carlo simulation method to analyze the risk and expected yield of the lenders with assumption that the future housing price and market rate of interest follow a stochastic process. The study results will give valuable implications to the Korean government and lenders who want to stabilize the mortgage program and innovate the related loan products.

Keywords: expected return, Monte Carlo simulation, risk, shared mortgage program

Procedia PDF Downloads 257

Authors: Wlodzimierz Ogryczak, Tomasz Sliwinski, Jaroslaw Hurkala, Mariusz Kaleta, Bartosz Kozlowski, Piotr Palka

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Implementation concepts of a decision support system for planning and management of mobile personnel tasks (sales representatives and others) are discussed. Large-scale periodic time-dependent vehicle routing and scheduling problems with complex constraints are solved for this purpose. Complex nonuniform constraints with respect to frequency, time windows, working time, etc. are taken into account with additional fast adaptive procedures for operational rescheduling of plans in the presence of various disturbances. Five individual solution quality indicators with respect to a single personnel person are considered. This paper deals with modeling issues corresponding to the problem and general solution concepts. The research was supported by the European Union through the European Regional Development Fund under the Operational Programme ‘Innovative Economy’ for the years 2007-2013; Priority 1 Research and development of modern technologies under the project POIG.01.03.01-14-076/12: 'Decision Support System for Large-Scale Periodic Vehicle Routing and Scheduling Problems with Complex Constraints.'

Keywords: mobile personnel management, multiple criteria, time dependent, time windows, vehicle routing and scheduling

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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

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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

Procedia PDF Downloads 136

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

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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: Viktorija Mano

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The objective of my research is to critique the International Monetary Fund (IMF) stance on foreign investment and the benefits for small, open economies of allowing the free movement of capital. In my research as a whole I will explore the extent to which this stance impacted upon and influenced the economic policies of Macedonia. This will involve providing a contextualized, critical account of the policy of the IMF focusing on a comparison of its policies during the early 2000s through policy documents, political discourse and enacted policies in Macedonia. The conditionality associated with these policies, such as the enforcement of austerity measures (including cutting public spending and reducing debt) and the privatization of public institutions has provoked strong reactions in countries which receive such loans. My main focus in my research is on exploring how the process of Financial Liberalization (FL) of the Macedonian economy affected capital flows in the form of foreign direct investments (FDI) in the private sector and how the recent Greek crisis of 2008 has impacted on this. In the case of Macedonia, the reality of FL was tested by the collapse of the Greek economy. However, this paper will highlight the main duties of the IMF and the goals of the FL process implemented in various countries.Additionally, I will undertake a rhetorical documentary analysis on the IMF reports regarding the process of FL in Macedonia since its independence until today.

Keywords: FDI, financial liberalization, Greece, IMF, Macedonia

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Authors: Sandesh Achar

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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

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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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Authors: Seyedmirsajad Mokhtarimousavi, Danial Talebi, Hamidreza Asgari

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Gate Assignment Problem (GAP) is one of the most substantial issues in airport operation. In principle, GAP intends to maintain the maximum capacity of the airport through the best possible allocation of the resources (gates) in order to reach the optimum outcome. The problem involves a wide range of dependent and independent resources and their limitations, which add to the complexity of GAP from both theoretical and practical perspective. In this study, GAP was mathematically formulated as a three-objective problem. The preliminary goal of multi-objective formulation was to address a higher number of objectives that can be simultaneously optimized and therefore increase the practical efficiency of the final solution. The problem is solved by applying the second version of Non-dominated Sorting Genetic Algorithm (NSGA-II). Results showed that the proposed mathematical model could address most of major criteria in the decision-making process in airport management in terms of minimizing both airport/airline cost and passenger walking distance time. Moreover, the proposed approach could properly find acceptable possible answers.

Keywords: airport management, gate assignment problem, mathematical modeling, genetic algorithm, NSGA-II

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Authors: Taruna Katyal Arora, Geeta Kumari, Hari Shankar, Neelima Mishra

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Substandard and counterfeit antimalarials is a major problem in malaria endemic areas. The availability of counterfeit/ substandard medicines is not only decreasing the efficacy in patients, but it is also one of the contributing factors for developing antimalarial drug resistance. Owing to this, a pilot study was conducted to survey quality of drugs collected from different malaria endemic areas of India. Artesunate+Sulphadoxine-Pyrimethamine (AS+SP), Artemether-Lumefantrine (AL), Chloroquine (CQ) tablets were randomly picked from public health facilities in selected states of India. The quality of antimalarial drugs from these areas was assessed by using Global Pharma Health Fund Minilab test kit. This includes physical/visual inspection and disintegration test. Thin-layer chromatography (TLC) was carried out for semi-quantitative assessment of active pharmaceutical ingredients. A total of 45 brands, out of which 21 were for CQ, 14 for AL and 10 for AS+SP were tested from Uttar Pradesh (U.P.), Mizoram, Meghalaya and Gujrat states. One out of 45 samples showed variable disintegration and retension factor. The variable disintegration and retention factor which would have been due to substandard quality or other factors including storage. However, HPLC analysis confirms standard active pharmaceutical ingredient, but may be due to humid temperature and moisture in storage may account for the observed result.

Keywords: antimalarial medicines, counterfeit, substandard, TLC

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Authors: Berrachid Dounia, Bellihi Hassan

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The financial crisis made a barrier in front of small projects that are looking for funding, but in the other hand it has had at least an interesting side effect which is the rise of alternative and increasingly creative forms of financing. The traditional forms of financing has known a recession due to the new difficult situation of economical recession that all parts of the world have known. Having an innovating idea that has an effect on both sides, the economic one and social one is very beneficial for those who wants to get rid of the economical crisis. In this case, entrepreneurs who want to be successful are looking for the means of financing that are going to get their projects to the reality. The financing could be various, whether the entrepreneur can use his own resources, or go to the three “Fs”(Family, friends, and fools),look for Angel Investors, or try for the academic solution like universities and private incubators, but sometimes, entrepreneurs feels uncomfortable about those means and start looking to newer, less traditional forms of financing their projects. In the last few years, people have shown a great interest to the use of internet for many reasons (information, social networking, communication, entertainment, transaction, etc.). The use of internet facilitates relations between people and eases the maintenance of existing relationships ,it increases also the number of exchanges which leads to a “collective creativity”, moreover, internet gives an opportunity to create new tool for mobilizing civil society, which makes the participation in a project company much easier. The new atmosphere of business forces the project leaders to look for new solution of financing that cut out the financial intermediaries. Using platforms in order to finance projects is an alternative that is changing the traditional solutions of financing projects. New creative ways of lending money appears like Peer to Peer (person to person or P2P)lending. This digital directly intermediary got his origins from microcredit principles. Crowdfunding also, like P2P, involves getting individuals to pool their resources to finance a project without a typical financial intermediary. For Lambert and Schwienbacher "Crowdfunding involves an open call, essentially through the Internet, for the provision of financial resources either in the form of donations (without rewards) or in exchange for some form of reward and/or voting rights in order to support initiatives for specific purposes". The idea of this proposal for investors and entrepreneurs is to encourage small contributions from a large number of funders "the crowd" in order to raise money to fund projects. All those conditions made from crowdfunding a useful alternative to project leaders, and especially the ones who are carrying special ideas that need special funds. As mentioned before by Laflamme. S. et Lafortune. S. internet is a tool for mobilizing civil society. In our case, the crowdfunding is the tool that funds social entrepreneurship, in the case of not for profit organizations, it focuses his attention on social problems which could be resolved by mobilizing different resources, creating innovative initiatives, and building new social arrangements which call up the civil society. Social entrepreneurs are mostly the ones who goes onto crowdfunding web site, so they propose the amount which is expected to realize their project and then they receive the funds from crowd funders. Something the crowd funders expect something in return, like a product from the business (a sample from a product (case of a cooperative) or a CD (in the case of films or songs)), but not their money back. Thus, we cannot say that their lands are donations, because a donator did not expect anything back. However, in order to encourage "crowd-funders", rewards motivates people to get interested by projects and made some money from internet. The operation of crowd funding is making all parts satisfied investors, entrepreneurs and also crowdfunding sites owners. This paper aims to give a view of the mechanism of crowdfunding, by clarifying the techniques and its different categories, and social entrepreneurship as a sponsor of social development. Also, it aims to show how this alternative of financing could be beneficial for social entrepreneurs and how it is bringing a solution to fund social projects. The article concludes with a discussion of the contribution of crowdfunding in social entrepreneurship especially in the Moroccan context.

Keywords: crowd-funding, social entrepreneurship, projects funding, financing

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Authors: Wanqing You, Kai Qian, Ying Qian

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The concepts of Cloud Computing provide users with infrastructure, platform and software as service, which make those services more accessible for people via Internet. To better analysis the performance of Cloud Computing provisioning policies as well as resources allocation strategies, a toolkit named CloudSim proposed. With CloudSim, the Cloud Computing environment can be easily constructed by modelling and simulating cloud computing components, such as datacenter, host, and virtual machine. A good scheduling strategy is the key to achieve the load balancing among different machines as well as to improve the utilization of basic resources. Recently, the existing scheduling algorithms may work well in some presumptive cases in a single machine; however they are unable to make the best decision for the unforeseen future. In real world scenario, there would be numbers of tasks as well as several virtual machines working in parallel. Based on the concepts of multi-queue, this paper presents a new scheduling algorithm to schedule tasks with CloudSim by taking into account several parameters, the machines’ capacity, the priority of tasks and the history log.

Keywords: hierarchical queue, load balancing, CloudSim, information technology

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Authors: E. K. Soyele

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This study is on capacity building and motivation as determinants of productivity among library personnel in colleges of education in South West, Nigeria. This study made use of a descriptive research design of survey type. A total enumeration sampling technique was used for the selected sample. The research sample consisted of 40 library personnel. The instrument used for the study was a structured questionnaire divided into four parts. Statistics data analysis used were descriptive statistics with frequencies, percentages, and regression statistics analysis. Findings from this study revealed that capacity building and motivation have positive impact on library personnel productivity with their percentages greater than 50% acceptance level. A test of null hypotheses at P < 0.05 significant level was tested to see the significance between capacity building and productivity, which was positive at P < 0.05 significant level. This implies that capacity building and motivation significantly determine productivity among library personnel in selected college libraries in Nigeria. The study concluded that there is need for institutions to equip their library personnel via training programmes, in-service, digital training, ICT training, seminars, and conferences, etc. Incentives should be provided to motivate personnel for high productivity. The study, therefore, recommends that government, institutions and library management should fund college libraries adequately so as to enhance capacity building, staff commitment and training for further education

Keywords: capacity building, library personnel, motivation, productivity

Procedia PDF Downloads 179

Authors: Jeeban Amgain

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This paper investigates the impact of the size and composition of government expenditure and tax on GDP per capita growth in 36 Asian economies over the period of 1991-2012. The research employs the technique of panel regression; Fixed Effects and Generalized Method of Moments (GMM) as well as other statistical and descriptive approaches. The finding concludes that the size of government expenditure and tax revenue are generally low in this region. GDP per capita growth is strongly negative in response to Government expenditure, however, no significant relationship can be measured in case of size of taxation although it is positively correlated with economic growth. Panel regression of decomposed fiscal components also shows that the pattern of allocation of expenditure and taxation really matters on growth. Taxes on international trade and property have a significant positive impact on growth. In contrast, a major portion of expenditure, i.e. expenditure on general public services, health and education are found to have significant negative impact on growth, implying that government expenditures are not being productive in the Asian region for some reasons. Comparatively smaller and efficient government size would enhance the growth.

Keywords: government expenditure, tax, GDP per capita growth, composition

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Authors: Sangwon Han, Chengquan Jin

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Time-cost trade-off (TCTO) is one of the most significant part of construction project management. Despite the significance, current TCTO analysis, based on the Critical Path Method, does not consider resource constraint, and accordingly sometimes generates an impractical and/or infeasible schedule planning in terms of resource availability. Therefore, resource constraint needs to be considered when doing TCTO analysis. In this research, genetic algorithms (GA) based optimization model is created in order to find the optimal schedule. This model is utilized to compare four distinct scenarios (i.e., 1) initial CPM, 2) TCTO without considering resource constraint, 3) resource allocation after TCTO, and 4) TCTO with considering resource constraint) in terms of duration, cost, and resource utilization. The comparison results identify that ‘TCTO with considering resource constraint’ generates the optimal schedule with the respect of duration, cost, and resource. This verifies the need for consideration of resource constraint when doing TCTO analysis. It is expected that the proposed model will produce more feasible and optimal schedule.

Keywords: time-cost trade-off, genetic algorithms, critical path, resource availability

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Authors: Mohammadali Abedini Sanigy, Jiangang Fei

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In this paper, a mathematical optimization model was developed to maximize the profit in a vegetable production planning problem. It serves as a decision support system that assists farmers in land allocation to crops and harvest scheduling decisions. The developed model can handle different rotation rules in two consecutive cycles of production, which is a common practice in organic production system. Moreover, different production methods of the same crop were considered in the model formulation. The main strength of the model is that it is not restricted to predetermined production periods, which makes the planning more flexible. The model is classified as a mixed integer programming (MIP) model and formulated in PYOMO -a Python package to formulate optimization models- and solved via Gurobi and CPLEX optimizer packages. The model was tested with secondary data from 'Australian vegetable growing farms', and the results were obtained and discussed with the computational test runs. The results show that the model can successfully provide reliable solutions for real size problems.

Keywords: crop rotation, harvesting, mathematical model formulation, vegetable production

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Authors: Kirstie Smith

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This paper elucidates the value of neighborhood perception as it contributes to the advancement of well-being for individuals and families within a neighborhood. Through in-depth interviews with city residents, this paper examines the degree to which key stakeholders’ (residents) evaluate their neighborhood and perception of resources and identify, access, and utilize local assets existing in the community. Additionally, the research objective included conducting a community inventory that qualified the community assets and resources of lower-income neighborhoods of a medium-sized industrial city. Analysis of the community’s assets was compared with the interview results to allow for a better understanding of the community’s condition. Community mapping revealed the key informants’ reflections of assets were somewhat validated. In each neighborhood, there were more assets mapped than reported in the interviews. Another chief supposition drawn from this study was the identification of key development partners and social networks that offer the potential to facilitate locally-driven community development. Overall, the participants provided invaluable local knowledge of the perception of neighborhood assets, the well-being of residents, the condition of the community, and suggestions for responding to the challenges of the entire community in order to mobilize the present assets and networks.

Keywords: community mapping, family, resource allocation, social networks

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Authors: Soheila Sadeghi

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Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

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Authors: Juliza Hidayati, Sukardi, Ani Suryani, Sugiharto, Anas M. Fauzi

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The idea of making North Sumatera as a barometer of national oil palm industry requires efforts commodities and agro-industry development of oil palm. One effort that can be done is by successful execution plantation revitalization. The plantation Revitalization is an effort to accelerate the development of smallholder plantations, through expansion and replanting by help of palm Estate Company as business partner and bank financed plantation revitalization fund. Business partner agreement obliged and bound to make at least the same smallholder plantation productivity with business partners, so that the refund rate to banks become larger and prosperous people as a plantation owner. Generally low productivity of smallholder plantations under normal potential caused a lot of old and damaged plants with plant material at random. The purpose of revitalizing oil palm plantations is which are to increase their competitiveness through increased farm productivity. The research aims to identify potential criteria in influencing plantation productivity improvement priorities to be observed and followed up in order to improve the competitiveness of destinations and make North Sumatera barometer of national palm oil can be achieved. Research conducted with Analytical Network Process (ANP), to find the effect of dependency relationships between factors or criteria with the knowledge of the experts in order to produce an objective opinion and relevant depict the actual situation.

Keywords: palm barometer, acceleration of plantation development, productivity, revitalization

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Authors: Jeh-Nan Pan, Chung-I Li

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Measurement system analysis (MSA) plays an important role in helping organizations to improve their product quality. Generally speaking, the gauge repeatability and reproducibility (GRR) study is performed according to the MSA handbook stated in QS9000 standards. Usually, GRR study for assessing the adequacy of gauge variation needs to be conducted prior to the process capability analysis. Traditional MSA only considers a single quality characteristic. With the advent of modern technology, industrial products have become very sophisticated with more than one quality characteristic. Thus, it becomes necessary to perform multivariate GRR analysis for a measurement system when collecting data with multiple responses. In this paper, we take the correlation coefficients among tolerances into account to revise the multivariate precision-to-tolerance (P/T) ratio as proposed by Majeske (2008). We then compare the performance of our revised P/T ratio with that of the existing ratios. The simulation results show that our revised P/T ratio outperforms others in terms of robustness and proximity to the actual value. Moreover, the optimal allocation of several parameters such as the number of quality characteristics (v), sample size of parts (p), number of operators (o) and replicate measurements (r) is discussed using the confidence interval of the revised P/T ratio. Finally, a standard operating procedure (S.O.P.) to perform the GRR study for multivariate measurement systems is proposed based on the research results. Hopefully, it can be served as a useful reference for quality practitioners when conducting such study in industries. Measurement system analysis (MSA) plays an important role in helping organizations to improve their product quality. Generally speaking, the gauge repeatability and reproducibility (GRR) study is performed according to the MSA handbook stated in QS9000 standards. Usually, GRR study for assessing the adequacy of gauge variation needs to be conducted prior to the process capability analysis. Traditional MSA only considers a single quality characteristic. With the advent of modern technology, industrial products have become very sophisticated with more than one quality characteristic. Thus, it becomes necessary to perform multivariate GRR analysis for a measurement system when collecting data with multiple responses. In this paper, we take the correlation coefficients among tolerances into account to revise the multivariate precision-to-tolerance (P/T) ratio as proposed by Majeske (2008). We then compare the performance of our revised P/T ratio with that of the existing ratios. The simulation results show that our revised P/T ratio outperforms others in terms of robustness and proximity to the actual value. Moreover, the optimal allocation of several parameters such as the number of quality characteristics (v), sample size of parts (p), number of operators (o) and replicate measurements (r) is discussed using the confidence interval of the revised P/T ratio. Finally, a standard operating procedure (S.O.P.) to perform the GRR study for multivariate measurement systems is proposed based on the research results. Hopefully, it can be served as a useful reference for quality practitioners when conducting such study in industries.

Keywords: gauge repeatability and reproducibility, multivariate measurement system analysis, precision-to-tolerance ratio, Gauge repeatability

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Authors: Samuel Reisman

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Background: Comparative rankings are increasingly used to evaluate health care systems. These rankings combine discrete attribute rankings into a composite overall ranking. Health care equity is a component of overall rankings, but excelling in other categories can counterbalance low inequity grades. Highly ranked inequitable health care would commend systems that disregard human rights. We simulated the ranking of a maximally inequitable health care system using a published, influential ranking methodology. Methods: We used The Commonwealth Fund’s ranking of eleven health care systems to simulate the rank of a maximally inequitable system. Eighty performance indicators were simulated, assuming maximal ineptitude in equity benchmarks. Maximal rankings in all non-equity subcategories were assumed. Subsequent stepwise simulations lowered all non-equity rank positions by one. Results: The maximally non-equitable health care system ranked first overall. Three subsequent stepwise simulations, lowering non-equity rankings by one, each resulted in an overall ranking within the top three. Discussion: Our results demonstrate that grossly inequitable health care systems can rank highly in comparative health care system rankings. These findings challenge the validity of ranking methodologies that subsume equity under broader benchmarks. We advocate limiting maximum overall rankings of health care systems to their individual equity rankings. Such limits are logical given the insignificance of health care system improvements to those lacking adequate health care.

Keywords: global health, health equity, healthcare systems, international health

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Authors: Xin-Hua Zhao

Abstract:

In recent years, the growth rate of social responsibility reports disclosed by Chinese corporations has grown rapidly. The economic effects of the growing corporate social responsibility reports have become a hot topic. The article takes the chemical listed engineering corporations that disclose social responsibility reports in China as a sample, and based on the information asymmetry theory, examines the economic effect generated by corporate social responsibility disclosure with the method of ordinary least squares. The research is conducted from the perspective of analysts’ earnings forecasts and studies the impact of corporate social responsibility information disclosure on improving the accuracy of analysts' earnings forecasts. The results show that there is a statistically significant negative correlation between corporate social responsibility disclosure index and analysts’ earnings forecast error. The conclusions confirm that enterprises can reduce the asymmetry of social and environmental information by disclosing social responsibility reports, and thus improve the accuracy of analysts’ earnings forecasts. It can promote the effective allocation of resources in the market.

Keywords: analysts' earnings forecasts, corporate social responsibility disclosure, economic effect, information asymmetry

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Authors: Pawas Suren

Abstract:

The conflict between livelihood and forest protection has been a perpetual phenomenon in India. In the era of climate change, the problem is expected to aggravate the declining trend of dense forest in the country, creating impediments in the climate change adaptation by the forest dependent communities. In order to access the complexity of the problem, Hazarinagh and Chatra districts of Jharkhand were selected as a case study. To identify norms practiced by the communities to manage community forestry, the ethnographic study was designed to understand the values, traditions, and cultures of forest dependent communities, most of whom were tribal. It was observed that internalization of efficient forest norms is reflected in the pride and honor of such behavior while violators are sanctioned through guilt and shame. The study analyzes the effect of norms being practiced in the management and ecology of community forestry as common property resource. The light of the findings led towards the gaps in the prevalent forest laws to address efficient allocation of property rights. The conclusion embarks on reconsidering accepted factors of forest degradation in India.

Keywords: climate change, common property resource, community forestry, norms

Procedia PDF Downloads 325

Authors: Kasman, Darmawansyah, Alimin Maidin, Amran Razak

Abstract:

Background: In decentralization, advocacy is needed to increase the health budget in Parepare District. One of the advocacy methods recommended by the World Bank is the economic loss approach. Methods: This research is observational in the field of health economics that contributes directly to the magnitude of the economic loss of the community and the government and provides advocacy to the executive and legislative to see the harm it causes. Results: The research results show the amount of direct cost, which consists of household expenditure for transport Rp.295,865,500. Indirect Cost of YLD of Rp.14.688.000, and YLL of Rp.28.986.336.00, so the amount of DALY is Rp.43.674.336.000. The total economic loss of Rp.43.970.201.500. These huge economic losses can be prevented by increasing the allocation of health budgets for promotive and preventive efforts and expanding the coverage of health insurance for the community. Conclusion: There is a need to advocate the executive and legislative about the importance of guarantee on public health financing by conducting studies in terms of economic losses so that all strategic alliances believe that health is an investment.

Keywords: advocacy, economic lost, health insurance, economic losses

Procedia PDF Downloads 91

Authors: Marziyeh Bahrami, Hamed Pahlevan Hsseini, Behnam Ghamami, Arman Alvanpour, Hamed Ezzati, Amir Salar Sadeghi

Abstract:

One of the ways to increase the efficiency of services in the system of agents and, of course, in the world of cloud computing, is to use virtualization techniques. The aim of this research is to create changes in cloud computing services that will reduce as much as possible the energy consumption related to the migration of virtual machines and, in some way, the energy related to the allocation of resources and reduce the amount of pollution. So far, several methods have been proposed to increase the efficiency of cloud computing services in order to save energy in the cloud environment. The method presented in this article tries to prevent energy consumption by data centers and the subsequent production of carbon and biological pollutants as much as possible by increasing the efficiency of cloud computing services. The results show that the proposed algorithm, using the improvement in virtualization techniques and with the help of a genetic algorithm, improves the efficiency of cloud services in the matter of migrating virtual machines and finally saves consumption. becomes energy.

Keywords: consumption reduction, cloud computing, genetic algorithm, live migration, virtual Machine

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Authors: Anurag Jain, Rajneesh Kumar

Abstract:

Cloud computing is the outcome of rapid growth of internet. Due to elastic nature of cloud computing and unpredictable behavior of user, load balancing is the major issue in cloud computing paradigm. An efficient load balancing technique can improve the performance in terms of efficient resource utilization and higher customer satisfaction. Load balancing can be implemented through task scheduling, resource allocation and task migration. Various parameters to analyze the performance of load balancing approach are response time, cost, data processing time and throughput. This paper demonstrates a two level load balancer approach by combining join idle queue and join shortest queue approach. Authors have used cloud analyst simulator to test proposed two level load balancer approach. The results are analyzed and compared with the existing algorithms and as observed, proposed work is one step ahead of existing techniques.

Keywords: cloud analyst, cloud computing, join idle queue, join shortest queue, load balancing, task scheduling

Procedia PDF Downloads 407

Authors: Kidist Mesfin Nguse

Abstract:

Ethiopia is the second most densely populated nation in Africa, and about 121 million people as the 2022 Ethiopia population live report recorded. In recent years, the Ethiopian government (GOE) has been gradually growing its road network. With 138,127 kilometers (85,825 miles) of all-weather roads as of the end of 2018–19, Ethiopia possessed just 39% of the nation's necessary road network and lacked a well-organized system. The Ethiopian urban population report recorded that about 21% of the population lives in urban areas, and the high population, coupled with growth in various infrastructures, has led to the migration of the workforce from rural areas to cities across the country. In main roads, the heterogeneous traffic flow with various operational features makes it more unfavorable, causing frequent congestion in the stretch of road. The Level of Service (LOS), a qualitative measure of traffic, is categorized based on the operating conditions in the traffic stream. Determining the capacity and LOS for this city is very crucial as this affects the planning and design of traffic systems and their operation, and the allocation of route selection for infrastructure building projects to provide for a considerably good level of service.

Keywords: capacity, level of service, traffic volume, free flow speed

Procedia PDF Downloads 27