Search results for: fund allocation

Authors: Samee Ullah Khan, C. Ardil

Abstract:

Fine-grained data replication over the Internet allows duplication of frequently accessed data objects, as opposed to entire sites, to certain locations so as to improve the performance of largescale content distribution systems. In a distributed system, agents representing their sites try to maximize their own benefit since they are driven by different goals such as to minimize their communication costs, latency, etc. In this paper, we will use game theoretical techniques and in particular auctions to identify a bidding mechanism that encapsulates the selfishness of the agents, while having a controlling hand over them. In essence, the proposed game theory based mechanism is the study of what happens when independent agents act selfishly and how to control them to maximize the overall performance. A bidding mechanism asks how one can design systems so that agents- selfish behavior results in the desired system-wide goals. Experimental results reveal that this mechanism provides excellent solution quality, while maintaining fast execution time. The comparisons are recorded against some well known techniques such as greedy, branch and bound, game theoretical auctions and genetic algorithms.

Keywords: Internet, data content replication, static allocation, mechanism design, equilibrium.

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Authors: Samee Ullah Khan, C. Ardil

Abstract:

Fine-grained data replication over the Internet allows duplication of frequently accessed data objects, as opposed to entire sites, to certain locations so as to improve the performance of largescale content distribution systems. In a distributed system, agents representing their sites try to maximize their own benefit since they are driven by different goals such as to minimize their communication costs, latency, etc. In this paper, we will use game theoretical techniques and in particular auctions to identify a bidding mechanism that encapsulates the selfishness of the agents, while having a controlling hand over them. In essence, the proposed game theory based mechanism is the study of what happens when independent agents act selfishly and how to control them to maximize the overall performance. A bidding mechanism asks how one can design systems so that agents- selfish behavior results in the desired system-wide goals. Experimental results reveal that this mechanism provides excellent solution quality, while maintaining fast execution time. The comparisons are recorded against some well known techniques such as greedy, branch and bound, game theoretical auctions and genetic algorithms.

Keywords: Data replication, auctions, static allocation, pricing.

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Authors: A. R. Seifi

Abstract:

This work presents a new algorithm based on a combination of fuzzy (FUZ), Dynamic Programming (DP), and Genetic Algorithm (GA) approach for capacitor allocation in distribution feeders. The problem formulation considers two distinct objectives related to total cost of power loss and total cost of capacitors including the purchase and installation costs. The novel formulation is a multi-objective and non-differentiable optimization problem. The proposed method of this article uses fuzzy reasoning for sitting of capacitors in radial distribution feeders, DP for sizing and finally GA for finding the optimum shape of membership functions which are used in fuzzy reasoning stage. The proposed method has been implemented in a software package and its effectiveness has been verified through a 9-bus radial distribution feeder for the sake of conclusions supports. A comparison has been done among the proposed method of this paper and similar methods in other research works that shows the effectiveness of the proposed method of this paper for solving optimum capacitor planning problem.

Keywords: Capacitor planning, Fuzzy logic method, Genetic Algorithm, Dynamic programming, Radial Distribution feeder

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Authors: A. Pereira, S. Haffner, L. V. Gasperin

Abstract:

This paper presents two simplified models to determine nodal voltages in power distribution networks. These models allow estimating the impact of the installation of reactive power compensations equipments like fixed or switched capacitor banks. The procedure used to develop the models is similar to the procedure used to develop linear power flow models of transmission lines, which have been widely used in optimization problems of operation planning and system expansion. The steady state non-linear load flow equations are approximated by linear equations relating the voltage amplitude and currents. The approximations of the linear equations are based on the high relationship between line resistance and line reactance (ratio R/X), which is valid for power distribution networks. The performance and accuracy of the models are evaluated through comparisons with the exact results obtained from the solution of the load flow using two test networks: a hypothetical network with 23 nodes and a real network with 217 nodes.

Keywords: Distribution network models, distribution systems, optimization, power system planning.

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Authors: S. Shanthi, V. Muralibhaskaran

Abstract:

Mammography has been one of the most reliable methods for early detection of breast cancer. There are different lesions which are breast cancer characteristic such as microcalcifications, masses, architectural distortions and bilateral asymmetry. One of the major challenges of analysing digital mammogram is how to extract efficient features from it for accurate cancer classification. In this paper we proposed a hybrid feature extraction method to detect and classify all four signs of breast cancer. The proposed method is based on multiscale surrounding region dependence method, Gabor filters, multi fractal analysis, directional and morphological analysis. The extracted features are input to self adaptive resource allocation network (SRAN) classifier for classification. The validity of our approach is extensively demonstrated using the two benchmark data sets Mammographic Image Analysis Society (MIAS) and Digital Database for Screening Mammograph (DDSM) and the results have been proved to be progressive.

Keywords: Feature extraction, fractal analysis, Gabor filters, multiscale surrounding region dependence method, SRAN.

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Authors: N. H. Adenan, M. S. M. Noorani

Abstract:

River flow prediction is an essential to ensure proper management of water resources can be optimally distribute water to consumers. This study presents an analysis and prediction by using nonlinear prediction method involving monthly river flow data in Tanjung Tualang from 1976 to 2006. Nonlinear prediction method involves the reconstruction of phase space and local linear approximation approach. The phase space reconstruction involves the reconstruction of one-dimensional (the observed 287 months of data) in a multidimensional phase space to reveal the dynamics of the system. Revenue of phase space reconstruction is used to predict the next 72 months. A comparison of prediction performance based on correlation coefficient (CC) and root mean square error (RMSE) have been employed to compare prediction performance for nonlinear prediction method, ARIMA and SVM. Prediction performance comparisons show the prediction results using nonlinear prediction method is better than ARIMA and SVM. Therefore, the result of this study could be used to develop an efficient water management system to optimize the allocation water resources.

Keywords: River flow, nonlinear prediction method, phase space, local linear approximation.

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

Abstract:

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, thin layer chromatography.

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Authors: Chang, Chun-Lang, Liu, Chun-Kai

Abstract:

This study, for its research subjects, uses patients who had undergone total knee replacement surgery from the database of the National Health Insurance Administration. Through the review of literatures and the interviews with physicians, important factors are selected after careful screening. Then using Cross Entropy Method, Genetic Algorithm Logistic Regression, and Particle Swarm Optimization, the weight of each factor is calculated and obtained. In the meantime, Excel VBA and Case Based Reasoning are combined and adopted to evaluate the system. Results show no significant difference found through Genetic Algorithm Logistic Regression and Particle Swarm Optimization with over 97% accuracy in both methods. Both ROC areas are above 0.87. This study can provide critical reference to medical personnel as clinical assessment to effectively enhance medical care quality and efficiency, prevent unnecessary waste, and provide practical advantages to resource allocation to medical institutes.

Keywords: Total knee replacement, Case Based Reasoning, Cross Entropy Method, Genetic Algorithm Logistic Regression, Particle Swarm Optimization.

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Authors: Alireza Vafaei Sadr, Vida Abedi, Jiang Li, Ramin Zand

Abstract:

Missing data is a common challenge in medical research and can lead to biased or incomplete results. When the data bias leaks into models, it further exacerbates health disparities; biased algorithms can lead to misclassification and reduced resource allocation and monitoring as part of prevention strategies for certain minorities and vulnerable segments of patient populations, which in turn further reduce data footprint from the same population – thus, a vicious cycle. This study compares the performance of six imputation techniques grouped into Linear and Non-Linear models, on two different real-world electronic health records (EHRs) datasets, representing 17864 patient records. The mean absolute percentage error (MAPE) and root mean squared error (RMSE) are used as performance metrics, and the results show that the Linear models outperformed the Non-Linear models in terms of both metrics. These results suggest that sometimes Linear models might be an optimal choice for imputation in laboratory variables in terms of imputation efficiency and uncertainty of predicted values.

Keywords: EHR, Machine Learning, imputation, laboratory variables, algorithmic bias.

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Authors: Abegunde Linda, Adedeji Oluwatola, Tope-Ajayi Opeyemi

Abstract:

Maize constitutes a major agrarian production for use by the vast population but despite its economic importance; it has not been produced to meet the economic needs of the country. Achieving optimum yield in maize can meaningfully be supported by land suitability analysis in order to guarantee self-sufficiency for future production optimization. This study examines land suitability for maize production through the analysis of the physicochemical variations in soil properties and other land attributes over space using a Geographic Information System (GIS) framework. Physicochemical parameters of importance selected include slope, landuse, physical and chemical properties of the soil, and climatic variables. Landsat imagery was used to categorize the landuse, Shuttle Radar Topographic Mapping (SRTM) generated the slope and soil samples were analyzed for its physical and chemical components. Suitability was categorized into highly, moderately and marginally suitable based on Food and Agricultural Organisation (FAO) classification, using the Analytical Hierarchy Process (AHP) technique of GIS. This result can be used by small scale farmers for efficient decision making in the allocation of land for maize production.

Keywords: AHP, GIS, MCE, Suitability, Zea mays.

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Authors: G. Chandana Sushma, T. R. Jyothsna

Abstract:

This paper presents optimal Phasor Measurement Unit (PMU) Placement in network using a genetic algorithm approach as it is infeasible and require high installation cost to place PMUs at every bus in network. This paper proposes optimal PMU allocation considering observability and redundancy utilizing Genetic Algorithm (GA) approach. The nonlinear constraints of buses are modeled to give accurate results. Constraints associated with Zero Injection (ZI) buses and radial buses are modeled to optimize number of locations for PMU placement. GA is modeled with ZI bus constraints to minimize number of locations without losing complete observability. Redundancy of every bus in network is computed to show optimum redundancy of complete system network. The performance of method is measured by Bus Observability Index (BOI) and Complete System Observability Performance Index (CSOPI). MATLAB simulations are carried out on IEEE -14, -30 and -57 bus-systems and compared with other methods in literature survey to show the effectiveness of the proposed approach.

Keywords: Constraints, genetic algorithm, observability, phasor measurement units, redundancy, synchrophasors, zero injection bus.

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Authors: Sandesh Achar

Abstract:

Artificial intelligence (AI) 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 remains a fundamental challenge. This paper highlights different manifestations, roles, trends, and challenges related to AI-based cloud computing models. This work reviews and highlights 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, AI, cloud computing, deep learning, machine learning, ML, internet of things, IoT.

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Authors: N. H. Adenan, M. S. M. Noorani

Abstract:

River flow prediction is an essential tool to ensure proper management of water resources and the optimal distribution of water to consumers. This study presents an analysis and prediction by using nonlinear prediction method with monthly river flow data for Tanjung Tualang from 1976 to 2006. Nonlinear prediction method involves the reconstruction of phase space and local linear approximation approach. The reconstruction of phase space involves the reconstruction of one-dimension (the observed 287 months of data) in a multidimensional phase space to reveal the dynamics of the system. The revenue of phase space reconstruction is used to predict the next 72 months. A comparison of prediction performance based on correlation coefficient (CC) and root mean square error (RMSE) was employed to compare prediction performance for the nonlinear prediction method, ARIMA and SVM. Prediction performance comparisons show that the prediction results using the nonlinear prediction method are better than ARIMA and SVM. Therefore, the results of this study could be used to develop an efficient water management system to optimize the allocation of water resources.

Keywords: River flow, nonlinear prediction method, phase space, local linear approximation.

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Authors: Ayman A. El-Saleh, Mahamod Ismail, Mohd. A. M. Ali, Ahmed N. H. Alnuaimy

Abstract:

The dynamic spectrum allocation solutions such as cognitive radio networks have been proposed as a key technology to exploit the frequency segments that are spectrally underutilized. Cognitive radio users work as secondary users who need to constantly and rapidly sense the presence of primary users or licensees to utilize their frequency bands if they are inactive. Short sensing cycles should be run by the secondary users to achieve higher throughput rates as well as to provide low level of interference to the primary users by immediately vacating their channels once they have been detected. In this paper, the throughput-sensing time relationship in local and cooperative spectrum sensing has been investigated under two distinct scenarios, namely, constant primary user protection (CPUP) and constant secondary user spectrum usability (CSUSU) scenarios. The simulation results show that the design of sensing slot duration is very critical and depends on the number of cooperating users under CPUP scenario whereas under CSUSU, cooperating more users has no effect if the sensing time used exceeds 5% of the total frame duration.

Keywords: Capacity, cognitive radio, optimization, spectrumsensing.

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Authors: Rishabh Garg

Abstract:

Blockchain technology can allow remote, untrusted parties in the banking and financial sector to reach consensus on the state of databases without the involvement of gatekeepers. Like a bookkeeper, it can manage all financial transactions including payments, settlements, fundraising, securities management, loans, credits and trade finance. It can outperform existing systems in terms of identity verification, asset transfers, peer-to-peer transfers, hedge funds, security and auditability. Blockchain-based decentralized finance (DeFi) is a new financial protocol. Being open and programmable, it enables various DeFi use-cases, including asset management, tokenization, tokenized derivatives, decentralized autonomous organizations, data analysis and valuation, payments, lending and borrowing, insurance, margin trading, prediction market, gambling and yield-farming, etc. In addition, it can ease financial transactions, cash-flow, use of programmable currency, no-loss lotteries, etc. This paper aims to assess the potential of decentralized finance by leveraging the blockchain-enabled Ethereum platform as an alternative to traditional finance. The study also aims to find out the impact of decentralized finance on prediction markets, quadratic funding and crowd-funding, together with the potential challenges and solutions associated with its implementation.

Keywords: Advance trading, crowd funding, exchange tokens, fund aggregation, margin trading, quadratic funding, smart contracts, streaming money, token derivatives.

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Authors: Nafe Moradkhani, Frederick Benaben, Benoit Montreuil, Ali Vatankhah Barenji, Dima Nazzal

Abstract:

In the context of the global pandemic, the practical management of the 2020 presidential election in the USA was a strong concern. To anticipate and prepare for this election accurately, one of the main challenges was to confront: (i) forecasts of voter turnout, (ii) capacities of the facilities and, (iii) potential configuration options of resources. The approach chosen to conduct this anticipative study consists of collecting data about forecasts and using simulation models to work simultaneously on resource allocation and facility configuration of polling places in Fulton County, Georgia’s largest county. This article presents the results of the simulations of such places facing pre-identified potential risks. These results are oriented towards the efficiency of these places according to different criteria (health, trust, comfort). Then a dynamic framework is introduced to describe risks as physical forces perturbing the efficiency of the observed system. Finally, the main benefits and contributions resulting from this simulation campaign are presented.

Keywords: performance, decision support, simulation, artificial intelligence, risk management, election, pandemics, information system

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Authors: Ghazi AL-Sukkar, Iyad Jafar, Khalid Darabkh, Raed Al-Zubi, Mohammed Hawa

Abstract:

Smart Grids employ wireless sensor networks for their control and monitoring. Sensors are characterized by limitations in the processing power, energy supply and memory spaces, which require a particular attention on the design of routing and data management algorithms. Since most routing algorithms for sensor networks, focus on finding energy efficient paths to prolong the lifetime of sensor networks, the power of sensors on efficient paths depletes quickly, and consequently sensor networks become incapable of monitoring events from some parts of their target areas. In consequence, the design of routing protocols should consider not only energy efficiency paths, but also energy efficient algorithms in general. In this paper we propose an energy efficient routing protocol for wireless sensor networks without the support of any location information system. The reliability and the efficiency of this protocol have been demonstrated by simulation studies where we compare them to the legacy protocols. Our simulation results show that these algorithms scale well with network size and density.

Keywords: Data-centric storage, Dynamic Address Allocation, Sensor networks, Smart Grid Communications.

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Authors: Po-Hsiang Chiu, Torre Wenaus

Abstract:

In the current Grid environment, efficient workload management presents a significant challenge, for which there are exorbitant de facto standards encompassing resource discovery, brokerage, and data transfer, among others. In addition, the real-time resource status, essential for an optimal resource allocation strategy, is often not readily accessible. To address these issues and provide a cleaner abstraction of the Grid with the potential of generalizing into arbitrary resource-sharing environment, this paper proposes a new Condor-based pilot mechanism applied in the PanDA architecture, PanDA-PF WMS, with the goal of providing a more generic yet efficient resource allocating strategy. In this architecture, the PanDA server primarily acts as a repository of user jobs, responding to pilot requests from distributed, remote resources. Scheduling decisions are subsequently made according to the real-time resource information reported by pilots. Pilot Factory is a Condor-inspired solution for a scalable pilot dissemination and effectively functions as a resource provisioning mechanism through which the user-job server, PanDA, reaches out to the candidate resources only on demand.

Keywords: Condor, glidein, PanDA, Pilot, Pilot Factory.

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Authors: Bright O. Osu, Edikan E. Akpanibah, Chidinma Olunkwa

Abstract:

In this paper, mean-variance optimization of portfolios with the return of premium clauses in a defined contribution (DC) pension plan with multiple contributors under constant elasticity of variance (CEV) model is studied. The return clauses which permit death members to claim their accumulated wealth are considered, the remaining wealth is not equally distributed by the remaining members as in literature. We assume that before investment, the surplus which includes funds of members who died after retirement adds to the total wealth. Next, we consider investments in a risk-free asset and a risky asset to meet up the expected returns of the remaining members and obtain an optimized problem with the help of extended Hamilton Jacobi Bellman equation. We obtained the optimal investment strategies for the two assets and the efficient frontier of the members by using a stochastic optimal control technique. Furthermore, we studied the effect of the various parameters of the optimal investment strategies and the effect of the risk-averse level on the efficient frontier. We observed that the optimal investment strategy is the same as in literature, secondly, we observed that the surplus decreases the proportion of the wealth invested in the risky asset.

Keywords: DC pension fund, Hamilton Jacobi Bellman equation, optimal investment strategies, stochastic optimal control technique, return of premiums clauses, mean-variance utility.

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Authors: Andrea Paltrinieri, Alberto Dreassi, Stefano Miani, Alex Sclip

Abstract:

The financial crises caused a collapse in prices of most asset classes, raising the attention on alternative investments such as sukuk, a smaller, fast growing but often misunderstood market. We study diversification benefits of sukuk, their correlation with other asset classes and the effects of their inclusion in investment portfolios of institutional and retail investors, through a comprehensive comparison of their risk/return profiles during and after the financial crisis. We find a beneficial performance adjusted for the specific volatility together with a lower correlation especially during the financial crisis. The distribution of sukuk returns is positively skewed and leptokurtic, with a risk/return profile similarly to high yield bonds. Overall, our results suggest that sukuk present diversification opportunities, a significant volatility-adjusted performance and lower correlations especially during the financial crisis. Our findings are relevant for a number of institutional investors. Long term investors, such as life insurers would benefit from sukuk’s protective features during financial crisis yet keeping return and growth opportunities, whereas banks would gain due to their role of placers, advisors, market makers or underwriters.

Keywords: Asset allocation, asset performance, sukuk, zero beta asset.

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Authors: Hamed Najafi, Ghasem Nikjou

Abstract:

Nowadays, there is an increasing attention to the resources scarcity issues. Because of failure in present patterns in the field of the allocation of exhaustible resources between generations and the challenges related to economic justice supply, it is supposed, to present a pattern from the Islamic perspective in this essay. By using content analysis of religious texts, we conclude that governments should remove the gap which is exists between the per capita income of the poor and their minimum consumption (necessary consumption). In order to preserve the exhaustible resources for poor people) not for all), between all generations, government should invest exhaustible resources on endless resources according to Hartwick’s criteria and should spend these benefits for poor people. But, if benefits did not cover the gap between minimum consumption and per capita income of poor levels in one generation, in this case, the government is responsible for covering this gap through the direct consumption of exhaustible resources. For an exact answer to this question, ‘how much of exhaustible resources should expense to maintain justice between generations?’ The theoretical and mathematical modeling has been used and proper function has been provided. The consumption pattern is presented for economic policy makers in Muslim countries, and non-Muslim even, it can be useful.

Keywords: Exhaustible resources, Islamic justice, intergenerational justice, distribution of resources, Hartwick Criteria.

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Authors: Syed Iftekhar Ali, M. S. Islam

Abstract:

In this paper we present an energy efficient match-line (ML) sensing scheme for high-speed ternary content-addressable memory (TCAM). The proposed scheme isolates the sensing unit of the sense amplifier from the large and variable ML capacitance. It employs feedback in the sense amplifier to successfully detect a match while keeping the ML voltage swing low. This reduced voltage swing results in large energy saving. Simulation performed using 130nm 1.2V CMOS logic shows at least 30% total energy saving in our scheme compared to popular current race (CR) scheme for similar search speed. In terms of speed, dynamic energy, peak power consumption and transistor count our scheme also shows better performance than mismatch-dependant (MD) power allocation technique which also employs feedback in the sense amplifier. Additionally, the implementation of our scheme is simpler than CR or MD scheme because of absence of analog control voltage and programmable delay circuit as have been used in those schemes.

Keywords: content-addressable memory, energy consumption, feedback, peak power, sensing scheme, sense amplifier, ternary.

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Authors: Wang Shuen-Tai, Lin Yu-Ching, Chang Hsi-Ya

Abstract:

Cloud computing is the innovative and leading information technology model for enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort. In this paper, we aim at the development of workflow management system for cloud computing platforms based on our previous research on the dynamic allocation of the cloud computing resources and its workflow process. We took advantage of the HTML5 technology and developed web-based workflow interface. In order to enable the combination of many tasks running on the cloud platform in sequence, we designed a mechanism and developed an execution engine for workflow management on clouds. We also established a prediction model which was integrated with job queuing system to estimate the waiting time and cost of the individual tasks on different computing nodes, therefore helping users achieve maximum performance at lowest payment. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for cloud computing platform. This development also helps boost user productivity by promoting a flexible workflow interface that lets users design and control their tasks' flow from anywhere.

Keywords: Web-based, workflow, HTML5, Cloud Computing, Queuing System.

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Authors: Edikan E. Akpanibah Obinichi C. Mandah Imoleayo S. Asiwaju

Abstract:

In this paper, we studied the effect of supplementary premium on the optimal portfolio policy in a defined contribution (DC) pension scheme with refund of premium clauses. This refund clause allows death members’ next of kin to withdraw their relative’s accumulated wealth during the accumulation period. The supplementary premium is to help sustain the scheme and is assumed to be stochastic. We considered cases when the remaining wealth is equally distributed and when it is not equally distributed among the remaining members. Next, we considered investments in cash and equity to help increase the remaining accumulated funds to meet up with the retirement needs of the remaining members and composed the problem as a continuous time mean-variance stochastic optimal control problem using the actuarial symbol and established an optimization problem from the extended Hamilton Jacobi Bellman equations. The optimal portfolio policy, the corresponding optimal fund size for the two assets and also the efficient frontier of the pension members for the two cases was obtained. Furthermore, the numerical simulations of the optimal portfolio policies with time were presented and the effect of the supplementary premium on the optimal portfolio policy was discussed and observed that the supplementary premium decreases the optimal portfolio policy of the risky asset (equity). Secondly we observed a disparity between the optimal policies for the two cases.

Keywords: Defined contribution pension scheme, extended Hamilton Jacobi Bellman equations, optimal portfolio policies, refund of premium clauses, supplementary premium.

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Authors: Shrikrishan Yadav, Akhilesh Saini, Krishna Chandra Roy

Abstract:

The electromagnetic spectrum is a natural resource and hence well-organized usage of the limited natural resources is the necessities for better communication. The present static frequency allocation schemes cannot accommodate demands of the rapidly increasing number of higher data rate services. Therefore, dynamic usage of the spectrum must be distinguished from the static usage to increase the availability of frequency spectrum. Cognitive radio is not a single piece of apparatus but it is a technology that can incorporate components spread across a network. It offers great promise for improving system efficiency, spectrum utilization, more effective applications, reduction in interference and reduced complexity of usage for users. Cognitive radio is aware of its environmental, internal state, and location, and autonomously adjusts its operations to achieve designed objectives. It first senses its spectral environment over a wide frequency band, and then adapts the parameters to maximize spectrum efficiency with high performance. This paper only focuses on the analysis of Bit-Error-Rate in cognitive radio by using Particle Swarm Optimization Algorithm. It is theoretically as well as practically analyzed and interpreted in the sense of advantages and drawbacks and how BER affects the efficiency and performance of the communication system.

Keywords: BER, Cognitive Radio, Environmental Parameters, PSO, Radio spectrum, Transmission Parameters

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Authors: C. Sathiyakumar, K. Duraiswamy

Abstract:

In MANET, mobile nodes communicate with each other using the wireless channel where transmission takes place with significant interference. The wireless medium used in MANET is a shared resource used by all the nodes available in MANET. Packet reserving is one important resource management scheme which controls the allocation of bandwidth among multiple flows through node cooperation in MANET. This paper proposes packet reserving and clogging control via Routing Aware Packet Reserving (RAPR) framework in MANET. It mainly focuses the end-to-end routing condition with maximal throughput. RAPR is complimentary system where the packet reserving utilizes local routing information available in each node. Path setup in RAPR estimates the security level of the system, and symbolizes the end-to-end routing by controlling the clogging. RAPR reaches the packet to the destination with high probability ratio and minimal delay count. The standard performance measures such as network security level, communication overhead, end-to-end throughput, resource utilization efficiency and delay measure are considered in this work. The results reveals that the proposed packet reservation and clogging control via Routing Aware Packet Reserving (RAPR) framework performs well for the above said performance measures compare to the existing methods.

Keywords: Packet reserving, Clogging control, Packet reservation in MANET, RAPR.

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Authors: Priyanka Paliwal, N.P. Patidar

Abstract:

Distributed Power generation has gained a lot of attention in recent times due to constraints associated with conventional power generation and new advancements in DG technologies .The need to operate the power system economically and with optimum levels of reliability has further led to an increase in interest in Distributed Generation. However it is important to place Distributed Generator on an optimum location so that the purpose of loss minimization and voltage regulation is dully served on the feeder. This paper investigates the impact of DG units installation on electric losses, reliability and voltage profile of distribution networks. In this paper, our aim would be to find optimal distributed generation allocation for loss reduction subjected to constraint of voltage regulation in distribution network. The system is further analyzed for increased levels of Reliability. Distributed Generator offers the additional advantage of increase in reliability levels as suggested by the improvements in various reliability indices such as SAIDI, CAIDI and AENS. Comparative studies are performed and related results are addressed. An analytical technique is used in order to find the optimal location of Distributed Generator. The suggested technique is programmed under MATLAB software. The results clearly indicate that DG can reduce the electrical line loss while simultaneously improving the reliability of the system.

Keywords: AENS, CAIDI, Distributed Generation, lossreduction, Reliability, SAIDI

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Authors: Chuan-Ching Sue, Shi-Zhou Chen, Ting-Yu Huang

Abstract:

Dynamic bandwidth allocation in EPONs can be generally separated into inter-ONU scheduling and intra-ONU scheduling. In our previous work, the active intra-ONU scheduling (AS) utilizes multiple queue reports (QRs) in each report message to cooperate with the inter-ONU scheduling and makes the granted bandwidth fully utilized without leaving unused slot remainder (USR). This scheme successfully solves the USR problem originating from the inseparability of Ethernet frame. However, without proper setting of threshold value in AS, the number of QRs constrained by the IEEE 802.3ah standard is not enough, especially in the unbalanced traffic environment. This limitation may be solved by enlarging the threshold value. The large threshold implies the large gap between the adjacent QRs, thus resulting in the large difference between the best granted bandwidth and the real granted bandwidth. In this paper, we integrate AS with a cooperative prediction mechanism and distribute multiple QRs to reduce the penalty brought by the prediction error. Furthermore, to improve the QoS and save the usage of queue reports, the highest priority (EF) traffic which comes during the waiting time is granted automatically by OLT and is not considered in the requested bandwidth of ONU. The simulation results show that the proposed scheme has better performance metrics in terms of bandwidth utilization and average delay for different classes of packets.

Keywords: EPON, Inter-ONU and Intra-ONU scheduling, Prediction, Unused slot remainder

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Authors: Umar Ubandawaki

Abstract:

Political participation involves voluntary and deliberate efforts by the members of a political system to determine the kinds of political institution and individuals that will govern them and equally influence the mobilization and allocation of the available societal resources. Over the years, youths in Nigeria participate actively in political party rallies and voting to elect their leaders and representatives in governance. This paper examines categories and nature of participation in politics as well as factors that drive youths into politics in Sokoto State. A survey conducted, through focus group discussions, interviews and questionnaire, in the six sampled Local Government of Sokoto State identifies three category of political participation; namely, active, moderate and apathetic participation. The findings reveal that 63.57% of respondents are apathetic to politics in the State and unemployed youth constitutes 34.74% of the entire responses. The paper establishes that lack of attainment of need (63.22%) is one of the reasons that make youths engage into participatory activities that encourage political thuggery and manipulation of electoral outcomes. The paper recommends that youths should be engaged into positive rational participatory activities that ensure inclusiveness and promotion of good governance in Nigeria. It is hoped that this will enlighten youths and policy implementers on the constructive strategies in controlling youths’ negative participation in politics in Nigeria.

Keywords: Democracy, Governance, Inclusiveness, Participation and Politics.

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Authors: Kuyucu Helvacioglu Asli Deniz, Tektas Arzu

Abstract:

European Union candidate status provides a strong motivation for decision-making in the candidate countries in shaping the regional development policy where there is an envisioned transfer of power from center to the periphery. The process of Europeanization anticipates the candidate countries configure their regional institutional templates in the context of the requirements of the European Union policies and introduces new instruments of incentive framework of enlargement to be employed in regional development schemes. It is observed that the contribution of the local actors to the decision making in the design of the allocation architectures enhances the efficiency of the funds and increases the positive effects of the projects funded under the regional development objectives. This study aims at exploring the performances of the three regional development grant schemes in Turkey, established and allocated under the pre-accession process with a special emphasis given to the roles of the national and local actors in decision-making for regional development. Efficiency analyses have been conducted using the DEA methodology which has proved to be a superior method in comparative efficiency and benchmarking measurements. The findings of this study as parallel to similar international studies, provides that the participation of the local actors to the decision-making in funding contributes both to the quality and the efficiency of the projects funded under the EU schemes.

Keywords: Efficiency, European Union Funds, RegionalDevelopment, Turkey

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