Search results for: efficient inventory

Authors: S. M. Abbas, M. A. Hannan, S. A. Samad, A. Hussain

Abstract:

This paper presented a modified efficient inductive powering link based on ASK modulator and proposed efficient class- E power amplifier. The design presents the external part which is located outside the body to transfer power and data to the implanted devices such as implanted Microsystems to stimulate and monitoring the nerves and muscles. The system operated with low band frequency 10MHZ according to industrial- scientific – medical (ISM) band to avoid the tissue heating. For external part, the modulation index is 11.1% and the modulation rate 7.2% with data rate 1 Mbit/s assuming Tbit = 1us. The system has been designed using 0.35-μm fabricated CMOS technology. The mathematical model is given and the design is simulated using OrCAD P Spice 16.2 software tool and for real-time simulation, the electronic workbench MULISIM 11 has been used.

Keywords: Implanted devices, ASK techniques, Class-E power amplifier, Inductive powering and low-frequency ISM band.

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Authors: Marcelo Dias Carvalho, Leticia Ishikawa

Abstract:

Supply Chain Risk Management refers to a set of strategies used by companies to avoid supply chain disruption caused by damage at production facilities, natural disasters, capacity issues, inventory problems, incorrect forecasts, and delays. Many companies use the techniques of the Toyota Production System, which in a way goes against a better management of supply chain risks. This paper studies key events in some multinationals to analyze the trade-off between the best supply chain risk management techniques and management policies designed to create lean enterprises. The result of a good balance of these actions is the reduction of losses, increased customer trust in the company and better preparedness to face the general risks of a supply chain.

Keywords: Supply chain disruptions, supply chain management, supply chain resilience, just-in-time production, lean manufacturing.

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Authors: Ajay Verma, Nitin Seth

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In this era of competitiveness, there is a growing need for supply chains also to become competitive enough to handle pressures like varying customer’s expectations, low cost high quality products to be delivered at the minimum time and the most important is throat cutting competition at world wide scale. In the recent years, supply chain competitiveness has been, therefore, accepted as one of the most important philosophies in the supply chain literature and researchers have tried to identify variables of supply chain competitiveness. This paper highlights some of the concepts of supply chain competitiveness and tries to identify select variables on the basis of literature review. Further, the paper tries to highlight the importance of the identified variables in the achievement of supply chain competitiveness. The aim is to explore the concept and to motivate researchers to further investigate the unexplored areas of this important subject domain.

Keywords: Supply Chain Competitiveness, Demand Management, Integration, Inventory Management, Flexibility, Information Technology.

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Authors: Martha Liliana Reina Usuga, Wilson Adarme Jaimes, Oscar Eduardo Suarez

Abstract:

Coordinated supply chain represents major challenges for the different actors involved in it, because each agent responds to individual interests. The paper presents a framework with the reviewed literature regarding the system's decision structure and nature of demand. Later, it characterizes an agri food supply chain in the Central Region of Colombia, it responds to a decentralized distribution system and a stochastic demand. Finally, the paper recommends coordinating the chain based on shared information, and mechanisms for each agent, as VMI (vendor-managed inventory) strategy for farmer-buyer relationship, information system for farmers and contracts for transportation service providers.

Keywords: Agri-food supply chain, Coordination mechanisms, Decentralized distribution system, Supply chain coordination.

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Authors: Mustafa Jahanara

Abstract:

The purpose of the current study is to examine the relationships between hope, optimism and mental health (psychological well-being and psychological distress) among students. A total of 222 students (132 males and 90 females) at the University of Pune from India completed inventories Revision of the Life Orientation Test (LOT-R), the Trait Hope Scale (THS) and the Mental Health Inventory (MHI) that assessed their optimism, hope and psychological well-being and psychological distress. The results of the study showed that optimism and hope were significantly correlated with each other. Optimism is positively related to psychological well-being and optimism is negatively related to psychological distress. Also, hope was positively related to psychological well-being. However, the findings suggest that optimism and hope could influence on mental health.

Keywords: Hope, optimism, psychological distress, psychological well-being.

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Authors: Besa Muslimi, Miriam A. M. Capretz, Jagath Samarabandu

Abstract:

Artificial neural networks (ANN) have the ability to model input-output relationships from processing raw data. This characteristic makes them invaluable in industry domains where such knowledge is scarce at best. In the recent decades, in order to overcome the black-box characteristic of ANNs, researchers have attempted to extract the knowledge embedded within ANNs in the form of rules that can be used in inference systems. This paper presents a new technique that is able to extract a small set of rules from a two-layer ANN. The extracted rules yield high classification accuracy when implemented within a fuzzy inference system. The technique targets industry domains that possess less complex problems for which no expert knowledge exists and for which a simpler solution is preferred to a complex one. The proposed technique is more efficient, simple, and applicable than most of the previously proposed techniques.

Keywords: fuzzy rule extraction, fuzzy systems, knowledgeacquisition, pattern recognition, artificial neural networks.

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Authors: Salah Al-Din I. Badran, Samad Ahmadi, Dylan Menzies, Ismail Shahin

Abstract:

This paper describes a new efficient blind source separation method; in this method we uses a non-uniform filter bank and a new structure with different sub-bands. This method provides a reduced permutation and increased convergence speed comparing to the full-band algorithm. Recently, some structures have been suggested to deal with two problems: reducing permutation and increasing the speed of convergence of the adaptive algorithm for correlated input signals. The permutation problem is avoided with the use of adaptive filters of orders less than the full-band adaptive filter, which operate at a sampling rate lower than the sampling rate of the input signal. The decomposed signals by analysis bank filter are less correlated in each sub-band than the input signal at full-band, and can promote better rates of convergence.

Keywords: Blind source separation (BSS), estimates, full-band, mixtures, Sub-band.

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Authors: Siyuan Jing, Kun She

Abstract:

Neighborhood Rough Sets (NRS) has been proven to be an efficient tool for heterogeneous attribute reduction. However, most of researches are focused on dealing with complete and noiseless data. Factually, most of the information systems are noisy, namely, filled with incomplete data and inconsistent data. In this paper, we introduce a generalized neighborhood rough sets model, called VPTNRS, to deal with the problem of heterogeneous attribute reduction in noisy system. We generalize classical NRS model with tolerance neighborhood relation and the probabilistic theory. Furthermore, we use the neighborhood dependency to evaluate the significance of a subset of heterogeneous attributes and construct a forward greedy algorithm for attribute reduction based on it. Experimental results show that the model is efficient to deal with noisy data.

Keywords: attribute reduction, incomplete data, inconsistent data, tolerance neighborhood relation, rough sets

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Authors: Jeon Chi-Ho, Lee Jae-Bin, Shim Chang-Su

Abstract:

National bridge inventory in Korea shows that the number of old prestressed concrete (PSC) bridgeover 30 years of service life is rapidly increasing. Recently tendon corrosion is one of the most critical issues in the maintenance of PSC bridges. In this paper, mechanical properties of corroded strands, which were removed from old bridges, were evaluated using tensile test. In the result, the equations to express the mechanical behavior of corroded strand were derived and compared to existing equation. For the decision of tendon replacement, it is necessary to evaluate the effect of corrosion level on strength and ductility of the structure. Considerations on analysis of PSC girders were introduced, and decision making on tendon replacement was also proposed.

Keywords: Prestressed concrete bridge, prestressing steel, corrosion, strength, ductility.

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Authors: Yu-Cheng Chou, Po Ting Lin

Abstract:

The network of delivering commodities has been an important design problem in our daily lives and many transportation applications. The delivery performance is evaluated based on the system reliability of delivering commodities from a source node to a sink node in the network. The system reliability is thus maximized to find the optimal routing. However, the design problem is not simple because (1) each path segment has randomly distributed attributes; (2) there are multiple commodities that consume various path capacities; (3) the optimal routing must successfully complete the delivery process within the allowable time constraints. In this paper, we want to focus on the design optimization of the Multi-State Flow Network (MSFN) for multiple commodities. We propose an efficient approach to evaluate the system reliability in the MSFN with respect to randomly distributed path attributes and find the optimal routing subject to the allowable time constraints. The delivery rates, also known as delivery currents, of the path segments are evaluated and the minimal-current arcs are eliminated to reduce the complexity of the MSFN. Accordingly, the correct optimal routing is found and the worst-case reliability is evaluated. It has been shown that the reliability of the optimal routing is at least higher than worst-case measure. Two benchmark examples are utilized to demonstrate the proposed method. The comparisons between the original and the reduced networks show that the proposed method is very efficient.

Keywords: Multiple Commodities, Multi-State Flow Network (MSFN), Time Constraints, Worst-Case Reliability (WCR)

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Authors: Ahmad M. Awwad, Jehad Al-Sadi

Abstract:

The star network is one of the promising interconnection networks for future high speed parallel computers, it is expected to be one of the future-generation networks. The star network is both edge and vertex symmetry, it was shown to have many gorgeous topological proprieties also it is owns hierarchical structure framework. Although much of the research work has been done on this promising network in literature, it still suffers from having enough algorithms for load balancing problem. In this paper we try to work on this issue by investigating and proposing an efficient algorithm for load balancing problem for the star network. The proposed algorithm is called Star Clustered Dimension Exchange Method SCDEM to be implemented on the star network. The proposed algorithm is based on the Clustered Dimension Exchange Method (CDEM). The SCDEM algorithm is shown to be efficient in redistributing the load balancing as evenly as possible among all nodes of different factor networks.

Keywords: Interconnection networks, Load balancing, Star network.

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Authors: Haider A Ramadhan, Khalil Shihab

Abstract:

Clustering techniques have been used by many intelligent software agents to group similar access patterns of the Web users into high level themes which express users intentions and interests. However, such techniques have been mostly focusing on one salient feature of the Web document visited by the user, namely the extracted keywords. The major aim of these techniques is to come up with an optimal threshold for the number of keywords needed to produce more focused themes. In this paper we focus on both keyword and similarity thresholds to generate themes with concentrated themes, and hence build a more sound model of the user behavior. The purpose of this paper is two fold: use distance based clustering methods to recognize overall themes from the Proxy log file, and suggest an efficient cut off levels for the keyword and similarity thresholds which tend to produce more optimal clusters with better focus and efficient size.

Keywords: Data mining, knowledge discovery, clustering, dataanalysis, Web log analysis, theme based searching.

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Authors: Aline Zeitunlian, Ramzi A. Haraty

Abstract:

Caching was suggested as a solution for reducing bandwidth utilization and minimizing query latency in mobile environments. Over the years, different caching approaches have been proposed, some relying on the server to broadcast reports periodically informing of the updated data while others allowed the clients to request for the data whenever needed. Until recently a hybrid cache consistency scheme Scalable Asynchronous Cache Consistency Scheme SACCS was proposed, which combined the two different approaches benefits- and is proved to be more efficient and scalable. Nevertheless, caching has its limitations too, due to the limited cache size and the limited bandwidth, which makes the implementation of cache replacement strategy an important aspect for improving the cache consistency algorithms. In this thesis, we proposed a new cache replacement strategy, the Least Unified Value strategy (LUV) to replace the Least Recently Used (LRU) that SACCS was based on. This paper studies the advantages and the drawbacks of the new proposed strategy, comparing it with different categories of cache replacement strategies.

Keywords: Cache consistency, hybrid algorithm, and mobileenvironments

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Authors: Shun-Kai Yang, Kuo-Feng Ssu

Abstract:

Target tracking and localization are important applications in wireless sensor networks. In these applications, sensor nodes collectively monitor and track the movement of a target. They have limited energy supplied by batteries, so energy efficiency is essential for sensor networks. Most existing target tracking protocols need to wake up sensors periodically to perform tracking. Some unnecessary energy waste is thus introduced. In this paper, an energy efficient protocol for target localization is proposed. In order to preserve energy, the protocol fixes the number of sensors for target tracking, but it retains the quality of target localization in an acceptable level. By selecting a set of sensors for target localization, the other sensors can sleep rather than periodically wake up to track the target. Simulation results show that the proposed protocol saves a significant amount of energy and also prolongs the network lifetime.

Keywords: Coverage, energy efficiency, target localization, wireless sensor network.

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Authors: Anežka Hamranová, Blandína Šramová, Katarína Fichnová

Abstract:

We presented results of research aimed on findings influence of social - psychological training (realized with students of Constantine the Philosopher University- future teachers within their undergraduate preparation) on the choice of intrapersonal and interpersonal features. After social- psychological training using Interpersonal Check List (ICL) we found out shift of behavior to more adaptive forms in categories, which are characterized by extroversive friendly behavior, willingness to cooperation, conformity regard to social situation, responsible and regardful behavior. Using State-Trait Anxiety Inventory (STAI) we found out the cut down of state anxiety and of trait anxiety. The report was processed within grants KEGA 3/5269/07 and VEGA 1/3675/06.

Keywords: Intrapersonal and interpersonal features, social -psychological training, social competences.

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Authors: Dhinu Johnson, Gurdip Singh

Abstract:

Sensor network applications are often data centric and involve collecting data from a set of sensor nodes to be delivered to various consumers. Typically, nodes in a sensor network are resource-constrained, and hence the algorithms operating in these networks must be efficient. There may be several algorithms available implementing the same service, and efficient considerations may require a sensor application to choose the best suited algorithm. In this paper, we present a systematic evaluation of a set of algorithms implementing the data gathering service. We propose a modular infrastructure for implementing such algorithms in TOSSIM with separate configurable modules for various tasks such as interest propagation, data propagation, aggregation, and path maintenance. By appropriately configuring these modules, we propose a number of data gathering algorithms, each of which incorporates a different set of heuristics for optimizing performance. We have performed comprehensive experiments to evaluate the effectiveness of these heuristics, and we present results from our experimentation efforts.

Keywords: Data Centric Protocols, Shortest Paths, Sensor networks, Message passing systems.

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Authors: Toufic Abd El-Latif Sadek

Abstract:

The asphalt object represents the asphalted areas like roads, and the concrete object represents the concrete areas like concrete buildings. The efficient extraction of asphalt and concrete objects from one satellite thermal image occurred at a specific time, by preventing the gaps in times which give the close and same brightness values between asphalt and concrete, and among other objects. So that to achieve efficient extraction and then better analysis. Seven sample objects were used un this study, asphalt, concrete, metal, rock, dry soil, vegetation, and water. It has been found that, the best timing for capturing satellite thermal images to extract the two objects asphalt and concrete from one satellite thermal image, saving time and money, occurred at a specific time in different months. A table is deduced shows the optimal timing for capturing satellite thermal images to extract effectively these two objects.

Keywords: Asphalt, concrete, satellite thermal images, timing.

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Authors: Y. Harold Robinson, M. Rajaram

Abstract:

Designing cost-efficient, secure network protocols for Wireless Sensor Networks (WSNs) is a challenging problem because sensors are resource-limited wireless devices. Security services such as authentication and improved pairwise key establishment are critical to high efficient networks with sensor nodes. For sensor nodes to correspond securely with each other efficiently, usage of cryptographic techniques is necessary. In this paper, two key predistribution schemes that enable a mobile sink to establish a secure data-communication link, on the fly, with any sensor nodes. The intermediate nodes along the path to the sink are able to verify the authenticity and integrity of the incoming packets using a predicted value of the key generated by the sender’s essential power. The proposed schemes are based on the pairwise key with the mobile sink, our analytical results clearly show that our schemes perform better in terms of network resilience to node capture than existing schemes if used in wireless sensor networks with mobile sinks.

Keywords: Wireless Sensor Networks, predistribution scheme, cryptographic techniques.

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Authors: Mohammed A. Khidhir, K. Praveen Kumar, Marwa Al-Aseer

Abstract:

This is a genetic comparison study of Arabian Oryx (Oryx leucoryx) population at two different locations (A &B) based on nuclear microsatellite DNA markers. Arabian Oryx is listed as vulnerable and endanger by the World Conservation Union (IUCN). Thirty microsatellite markers from bovine family were applied to investigate the genetic diversity of the Arabian Oryx and to set up a molecular inventory. Among 30 microsatellite markers used, 13 markers were moderately polymorphic. Arabian Oryx at location A has shown better gene diversity over location B. However, mean number of alleles were less than location B. Data of within population inbreeding coefficient indicates inbreeding at both locations (A&B). Based on the analysis of polymorphic microsatellite markers, the study revealed that Arabian Oryx need a genetically designed breeding program.

Keywords: Arabian oryx, Microsatellites

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Authors: Yao-Hong Tsai

Abstract:

This paper presents an efficient fusion algorithm for iris images to generate stable feature for recognition in unconstrained environment. Recently, iris recognition systems are focused on real scenarios in our daily life without the subject’s cooperation. Under large variation in the environment, the objective of this paper is to combine information from multiple images of the same iris. The result of image fusion is a new image which is more stable for further iris recognition than each original noise iris image. A wavelet-based approach for multi-resolution image fusion is applied in the fusion process. The detection of the iris image is based on Adaboost algorithm and then local binary pattern (LBP) histogram is then applied to texture classification with the weighting scheme. Experiment showed that the generated features from the proposed fusion algorithm can improve the performance for verification system through iris recognition.

Keywords: Image fusion, iris recognition, local binary pattern, wavelet.

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Authors: Jürgen Roßmann, Gerrit Alves

Abstract:

In today-s world, the efficient utilization of wood resources comes more and more to the mind of forest owners. It is a very complex challenge to ensure an efficient harvest of the wood resources. This is one of the scopes the project “Virtual Forest II" addresses. Its core is a database with data about forests containing approximately 260 million trees located in North Rhine-Westphalia (NRW). Based on this data, tree growth simulations and wood mobilization simulations can be conducted. This paper focuses on the latter. It describes a discrete-event-simulation with an attached 3-D real time visualization which simulates timber harvest using trees from the database with different crop resources. This simulation can be displayed in 3-D to show the progress of the wood crop. All the data gathered during the simulation is presented as a detailed summary afterwards. This summary includes cost-benefit calculations and can be compared to those of previous runs to optimize the financial outcome of the timber harvest by exchanging crop resources or modifying their parameters.

Keywords: Timber harvest, simulation, 3-D, optimization.

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Authors: Hongjoong Sin, Jangsoo Lee, Sungju Lee, Seunghwan Yoo, Sanghyuck Lee, Jaesik Lee, Yongjun Lee, Sungchun Kim

Abstract:

Wireless sensor networks are consisted of hundreds or thousands of small sensors that have limited resources. Energy-efficient techniques are the main issue of wireless sensor networks. This paper proposes an energy efficient agent-based framework in wireless sensor networks. We adopt biologically inspired approaches for wireless sensor networks. Agent operates automatically with their behavior policies as a gene. Agent aggregates other agents to reduce communication and gives high priority to nodes that have enough energy to communicate. Agent behavior policies are optimized by genetic operation at the base station. Simulation results show that our proposed framework increases the lifetime of each node. Each agent selects a next-hop node with neighbor information and behavior policies. Our proposed framework provides self-healing, self-configuration, self-optimization properties to sensor nodes.

Keywords: Agent, Energy Efficiency, Genetic algorithm, Wireless Sensor Networks.

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Authors: A. S. Salimzhanova, J. C. Sardinas, O. A. Yanovskaya

Abstract:

The objective of this research work is to discuss the concept of “green growth” in the Republic of Kazakhstan introduced by its government in the “National Sustainable Development Strategy” with the objective of transition to a resource-efficient, “green economy.” We believe that emerging economies like Kazakhstan can pursue a cleaner and more efficient development path by introducing an environmental tax system based on resource consumption rather than only income and labor. The key issues discussed in this article are the eco-efficiency, which refers to closing the gap between economic and ecological efficiencies, and the structural change of the economy toward “green growth.” We also strongly believe that studying the experience of East Asian countries on “green reform” including eco-innovation and “green solutions” in business is essential to the case of Kazakhstan. All of these will raise the status of Kazakhstan to the level of one of the thirty developed countries over the next decades.

Keywords: Economic strategy, green growth, green solutions, natural resource management, environmental tax system.

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Authors: Sandesh Achar

Abstract:

The cloud computing industry has set new goals for better service delivery and deployment, so anyone can access services such as computation, application, and storage anytime. Cloud computing promises new possibilities for approaching sustainable solutions to deploy and advance their services in this distributed environment. This work explores energy-efficient approaches and how cloud-based architecture can reduce energy consumption levels amongst enterprises leveraging cloud computing services. Adopting cloud-based networking, database, and server machines provide a comprehensive means of achieving the potential gains in energy efficiency that cloud computing offers. In energy-efficient cloud computing, virtualization is one aspect that can integrate several technologies to achieve consolidation and better resource utilization. Moreover, the Green Cloud Architecture for cloud data centers is discussed in terms of cost, performance, and energy consumption, and appropriate solutions for various application areas are provided.

Keywords: Greener Cloud, cloud computing, energy efficiency, energy consumption, metadata tags, Green Cloud Advisor.

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Authors: D. Kliaugaitė, J. K, Staniškis

Abstract:

In this study tree types of multilayer gas barrier plastic packaging films were compared using life cycle assessment as a tool for resource efficient and environmentally low-impact materials selection. The first type of multilayer packaging film (PET-AlOx/LDPE) consists of polyethylene terephthalate with barrier layer AlOx (PET-AlOx) and low density polyethylene (LDPE). The second type of polymer film (PET/PE-EVOH-PE) is made of polyethylene terephthalate (PET) and co-extrusion film PE-EVOH-PE as barrier layer. And the third one type of multilayer packaging film (PET-PVOH/LDPE) is formed from polyethylene terephthalate with barrier layer PVOH (PET-PVOH) and low density polyethylene (LDPE).

All of analyzed packaging has significant impact to resource depletion, because of raw materials extraction and energy use and production of different kind of plastics. Nevertheless the impact generated during life cycle of functional unit of II type of packaging (PET/PE-EVOH-PE) was about 25% lower than impact generated by I type (PET-AlOx/LDPE) and III type (PET-PVOH/LDPE) of packaging.

Result revealed that the contribution of different gas barrier type to the overall environmental problem of packaging is not significant. The impact are mostly generated by using energy and materials during raw material extraction and production of different plastic materials as plastic polymers material as PE, LDPE and PET, but not gas barrier materials as AlOx, PVOH and EVOH.

The LCA results could be useful in different decision-making processes, for selecting resource efficient and environmentally low-impact materials.

Keywords: Polymer packaging, life cycle assessment, resource efficiency.

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Authors: D.Gnanadurai, V.Sadasivam

Abstract:

This frame work describes a computationally more efficient and adaptive threshold estimation method for image denoising in the wavelet domain based on Generalized Gaussian Distribution (GGD) modeling of subband coefficients. In this proposed method, the choice of the threshold estimation is carried out by analysing the statistical parameters of the wavelet subband coefficients like standard deviation, arithmetic mean and geometrical mean. The noisy image is first decomposed into many levels to obtain different frequency bands. Then soft thresholding method is used to remove the noisy coefficients, by fixing the optimum thresholding value by the proposed method. Experimental results on several test images by using this method show that this method yields significantly superior image quality and better Peak Signal to Noise Ratio (PSNR). Here, to prove the efficiency of this method in image denoising, we have compared this with various denoising methods like wiener filter, Average filter, VisuShrink and BayesShrink.

Keywords: Wavelet Transform, Gaussian Noise, ImageDenoising, Filter Banks and Thresholding.

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Authors: Je Young Lee, Hee Sung Kim, Kwang Ho Choi, Joonhoo Lim, Sebum Chun, Hyung Keun Lee

Abstract:

This study is purposed to develop an efficient fault detection method for Global Navigation Satellite Systems (GNSS) applications based on adaptive noise covariance estimation. Due to the dependence on radio frequency signals, GNSS measurements are dominated by systematic errors in receiver’s operating environment. In the proposed method, the pseudorange and carrier-phase measurement noise covariances are obtained at time propagations and measurement updates in process of Carrier-Smoothed Code (CSC) filtering, respectively. The test statistics for fault detection are generated by the estimated measurement noise covariances. To evaluate the fault detection capability, intentional faults were added to the filed-collected measurements. The experiment result shows that the proposed method is efficient in detecting unhealthy measurements and improves GNSS positioning accuracy against fault occurrences.

Keywords: Adaptive estimation, fault detection, GNSS, residual.

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Authors: Amin Akhnoukh

Abstract:

The National Bridge Inventory (NBI) includes more than 600,000 bridges within the United States of America. Prestressed concrete girder bridges represent one of the most widely used bridge systems. The majority of these girder bridges were constructed using 0.5 and 0.6 inch diameter strands. The main impediments to using larger strand diameters are: 1) lack of prestress bed capacities, 2) lack of structural knowledge regarding the transfer and development length of larger strands, and 3) the possibility of developing wider end zone cracks upon strand release. This paper presents a study about using 0.7 inch strands in girder fabrication. Transfer and development length were evaluated, and girders were fabricated using 0.7 inch strands at different spacings. Results showed that 0.7 inch strands can be used at 2.0 inch spacing without violating the AASHTO LRFD Specifications, while attaining superior performance in shear and flexure.

Keywords: 0.7 inch strands, prestress, I-girders, bridges

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Authors: Haniye Dehestani, Yadollah Ordokhani

Abstract:

In this work, we present an efficient approach for solving variable-order time-fractional partial differential equations, which are based on Legendre and Laguerre polynomials. First, we introduced the pseudo-operational matrices of integer and variable fractional order of integration by use of some properties of Riemann-Liouville fractional integral. Then, applied together with collocation method and Legendre-Laguerre functions for solving variable-order time-fractional partial differential equations. Also, an estimation of the error is presented. At last, we investigate numerical examples which arise in physics to demonstrate the accuracy of the present method. In comparison results obtained by the present method with the exact solution and the other methods reveals that the method is very effective.

Keywords: Collocation method, fractional partial differential equations, Legendre-Laguerre functions, pseudo-operational matrix of integration.

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Authors: F. Gökgöz, M. E. Atmaca

Abstract:

Electricity plays an indispensable role in human life and the economy. It is a unique product or service that must be balanced instantaneously, as electricity is not stored, generation and consumption should be proportional. Effective and efficient use of electricity is very important not only for society, but also for the environment. A competitive electricity market is one of the best ways to provide a suitable platform for effective and efficient use of electricity. On the other hand, it carries some risks that should be carefully managed by the market players. Risk management is an essential part in market players’ decision making. In this paper, risk management through diversification is applied with the help of Markowitz’s Mean-variance, Down-side and Semi-variance methods for a case study. Performance of optimal electricity sale solutions are measured and evaluated via Sharpe-Ratio, and the optimal portfolio solutions are improved. Two years of historical weekdays’ price data of the Turkish Day Ahead Market are used to demonstrate the approach.

Keywords: Electricity market, portfolio optimization, risk management in electricity market, Sharpe ratio.

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