Search results for: Network reduction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4178

Search results for: Network reduction

758 The Tag Authentication Scheme using Self-Shrinking Generator on RFID System

Authors: HangRok Lee, DoWon Hong

Abstract:

Since communications between tag and reader in RFID system are by radio, anyone can access the tag and obtain its any information. And a tag always replies with the same ID so that it is hard to distinguish between a real and a fake tag. Thus, there are many security problems in today-s RFID System. Firstly, unauthorized reader can easily read the ID information of any Tag. Secondly, Adversary can easily cheat the legitimate reader using the collected Tag ID information, such as the any legitimate Tag. These security problems can be typically solved by encryption of messages transmitted between Tag and Reader and by authentication for Tag. In this paper, to solve these security problems on RFID system, we propose the Tag Authentication Scheme based on self shrinking generator (SSG). SSG Algorithm using in our scheme is proposed by W.Meier and O.Staffelbach in EUROCRYPT-94. This Algorithm is organized that only one LFSR and selection logic in order to generate random stream. Thus it is optimized to implement the hardware logic on devices with extremely limited resource, and the output generating from SSG at each time do role as random stream so that it is allow our to design the light-weight authentication scheme with security against some network attacks. Therefore, we propose the novel tag authentication scheme which use SSG to encrypt the Tag-ID transmitted from tag to reader and achieve authentication of tag.

Keywords: RFID system, RFID security, self shrinkinggeneratior, authentication, protocol.

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757 Regulation of Transfer of 137cs by Polymeric Sorbents for Grow Ecologically Sound Biomass

Authors: A. H. Tadevosyan, S. K. Mayrapetyan, N. B. Tavakalyan, K. I. Pyuskyulyan, A. H. Hovsepyan, S. N. Sergeeva

Abstract:

Soil contamination with radiocesium has a long-term radiological impact due to its long physical half-life (30.1 years for 137Cs and 2 years for 134Cs) and its high biological availability. 137Cs causes the largest concerns because of its deleterious effect on agriculture and stock farming, and, thus, human life for decades. One of the important aspects of the problem of contaminated soils remediation is understand of protective actions aimed at the reduction of biological migration of radionuclides in soil-plant system. The most effective way to bind radionuclides is the use of selective sorbents. The proposed research mainly aims to achieve control on transfer of 137Cs in a system growing media – plant due to counter ions variation in the polymeric sorbents. As research object Japanese basil - Perilla frutescens was chosen. Productivity of plants depending on the presence (control-without presence of polymer) and type of polymer material, as well as content of 137Cs in plant material has been determined. The character of different polymers influences on the 137Cs migration in growing media – plant system as well as accumulation in the plants has been cleared up.

Keywords: Radioceaseum, Japanese basil, polymer, soil-plant system.

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756 Effective Charge Coupling in Low Dimensional Doped Quantum Antiferromagnets

Authors: Suraka Bhattacharjee, Ranjan Chaudhury

Abstract:

The interaction between the charge degrees of freedom for itinerant antiferromagnets is investigated in terms of generalized charge stiffness constant corresponding to nearest neighbour t-J model and t1-t2-t3-J model. The low dimensional hole doped antiferromagnets are the well known systems that can be described by the t-J-like models. Accordingly, we have used these models to investigate the fermionic pairing possibilities and the coupling between the itinerant charge degrees of freedom. A detailed comparison between spin and charge couplings highlights that the charge and spin couplings show very similar behaviour in the over-doped region, whereas, they show completely different trends in the lower doping regimes. Moreover, a qualitative equivalence between generalized charge stiffness and effective Coulomb interaction is also established based on the comparisons with other theoretical and experimental results. Thus it is obvious that the enhanced possibility of fermionic pairing is inherent in the reduction of Coulomb repulsion with increase in doping concentration. However, the increased possibility can not give rise to pairing without the presence of any other pair producing mechanism outside the t-J model. Therefore, one can conclude that the t-J-like models themselves solely are not capable of producing conventional momentum-based superconducting pairing on their own.

Keywords: Generalized charge stiffness constant, charge coupling, effective Coulomb interaction, t-J-like models, momentum-space pairing.

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755 Malaria Parasite Detection Using Deep Learning Methods

Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

Abstract:

Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.

Keywords: Malaria, deep learning, DL, convolution neural network, CNN, thin blood smears.

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754 A Study on Early Prediction of Fault Proneness in Software Modules using Genetic Algorithm

Authors: Parvinder S. Sandhu, Sunil Khullar, Satpreet Singh, Simranjit K. Bains, Manpreet Kaur, Gurvinder Singh

Abstract:

Fault-proneness of a software module is the probability that the module contains faults. To predict faultproneness of modules different techniques have been proposed which includes statistical methods, machine learning techniques, neural network techniques and clustering techniques. The aim of proposed study is to explore whether metrics available in the early lifecycle (i.e. requirement metrics), metrics available in the late lifecycle (i.e. code metrics) and metrics available in the early lifecycle (i.e. requirement metrics) combined with metrics available in the late lifecycle (i.e. code metrics) can be used to identify fault prone modules using Genetic Algorithm technique. This approach has been tested with real time defect C Programming language datasets of NASA software projects. The results show that the fusion of requirement and code metric is the best prediction model for detecting the faults as compared with commonly used code based model.

Keywords: Genetic Algorithm, Fault Proneness, Software Faultand Software Quality.

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753 A Real-Time Bayesian Decision-Support System for Predicting Suspect Vehicle’s Intended Target Using a Sparse Camera Network

Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

Abstract:

We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: Autonomous surveillance, Bayesian reasoning, decision-support, interventions, patterns-of-life, predictive analytics, predictive insights.

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752 Effect of L-Arginine on Neuromuscular Transmission of the Chick Biventer Cervicis Muscle

Authors: S. Asadzadeh Vostakolaei

Abstract:

In this study, the effect of L-arginine was examined at the neuromuscular junction of the chick biventer cervicis muscle. LArginine at 500 μg/ ml, decreased twitch response to electerical stimulation, and produced rightward shift of the dose- response curve for acetylcholine or carbachol. L-Arginine at 1000μg/ ml produced a strong shift to the right of the dose – response curve for acetylcholine or carbachol with a reduction in the efficacy. The inhibitory effect of L-arginine on the twitch response was blocked by caffeine (200μg/ ml). NO levels were also measured in the chick biventer cervicis muscle homogenates, using spectrophotometric method for the direct detection of NO, nitrite and nitrate. Total nitrite (nitrite + nitrate) was measured by a spectrophotometer at 540 nm after the conversion of nitrate to nitrite by copperized cadmium granules. NO levels were found to be significantly increased in concentrations 500 and 1000μg/ ml of L-arginine in comparison with the control group (p<0.001). These findings indicate a possible role of increased NO levels in the suppressive action of L-arginine on the twitch response. In addition, the results indicate that the post- junctional antagonistic action of L-arginine is probably the result of impaired sarcoplasmic reticulum (SR) Ca+2 releases.

Keywords: Chick, L-Arginine, Nitric Oxide, Skeletal muscle.

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751 WebAppShield: An Approach Exploiting Machine Learning to Detect SQLi Attacks in an Application Layer in Run-Time

Authors: Ahmed Abdulla Ashlam, Atta Badii, Frederic Stahl

Abstract:

In recent years, SQL injection attacks have been identified as being prevalent against web applications. They affect network security and user data, which leads to a considerable loss of money and data every year. This paper presents the use of classification algorithms in machine learning using a method to classify the login data filtering inputs into "SQLi" or "Non-SQLi,” thus increasing the reliability and accuracy of results in terms of deciding whether an operation is an attack or a valid operation. A method as a Web-App is developed for auto-generated data replication to provide a twin of the targeted data structure. Shielding against SQLi attacks (WebAppShield) that verifies all users and prevents attackers (SQLi attacks) from entering and or accessing the database, which the machine learning module predicts as "Non-SQLi", has been developed. A special login form has been developed with a special instance of the data validation; this verification process secures the web application from its early stages. The system has been tested and validated, and up to 99% of SQLi attacks have been prevented.

Keywords: SQL injection, attacks, web application, accuracy, database, WebAppShield.

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750 Reducing Greenhouse Gas Emissions by Recyclable Material Bank Project of Universities in Central Region of Thailand

Authors: Ronbanchob Apiratikul

Abstract:

This research studied recycled waste by the Recyclable Material Bank Project of 4 universities in the central region of Thailand for the evaluation of reducing greenhouse gas emissions compared with landfilling activity during July 2012 to June 2013. The results showed that the projects collected total amount of recyclable wastes of about 911,984.80 kilograms. Office paper had the largest amount among these recycled wastes (50.68% of total recycled waste). Groups of recycled waste can be prioritized from high to low according to their amount as paper, plastic, glass, mixed recyclables, and metal, respectively. The project reduced greenhouse gas emissions equivalent to about 2814.969 metric tons of carbon dioxide. The most significant recycled waste that affects the reduction of greenhouse gas emissions is office paper which is 70.16% of total reduced greenhouse gasses emission. According to amount of reduced greenhouse gasses emission, groups of recycled waste can be prioritized from high to low significances as paper, plastic, metals, mixed recyclables, and glass, respectively.

Keywords: Recycling, garbage bank, waste management, recyclable wastes, greenhouse gasses.

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749 Optimizing Operation of Photovoltaic System Using Neural Network and Fuzzy Logic

Authors: N. Drir, L. Barazane, M. Loudini

Abstract:

It is well known that photovoltaic (PV) cells are an attractive source of energy. Abundant and ubiquitous, this source is one of the important renewable energy sources that have been increasing worldwide year by year. However, in the V-P characteristic curve of GPV, there is a maximum point called the maximum power point (MPP) which depends closely on the variation of atmospheric conditions and the rotation of the earth. In fact, such characteristics outputs are nonlinear and change with variations of temperature and irradiation, so we need a controller named maximum power point tracker MPPT to extract the maximum power at the terminals of photovoltaic generator. In this context, the authors propose here to study the modeling of a photovoltaic system and to find an appropriate method for optimizing the operation of the PV generator using two intelligent controllers respectively to track this point. The first one is based on artificial neural networks and the second on fuzzy logic. After the conception and the integration of each controller in the global process, the performances are examined and compared through a series of simulation. These two controller have prove by their results good tracking of the MPPT compare with the other method which are proposed up to now.

Keywords: Maximum power point tracking, neural networks, photovoltaic, P&O.

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748 Modeling and Simulation of Acoustic Link Using Mackenize Propagation Speed Equation

Authors: Christhu Raj M. R., Rajeev Sukumaran

Abstract:

Underwater acoustic networks have attracted great attention in the last few years because of its numerous applications. High data rate can be achieved by efficiently modeling the physical layer in the network protocol stack. In Acoustic medium, propagation speed of the acoustic waves is dependent on many parameters such as temperature, salinity, density, and depth. Acoustic propagation speed cannot be modeled using standard empirical formulas such as Urick and Thorp descriptions. In this paper, we have modeled the acoustic channel using real time data of temperature, salinity, and speed of Bay of Bengal (Indian Coastal Region). We have modeled the acoustic channel by using Mackenzie speed equation and real time data obtained from National Institute of Oceanography and Technology. It is found that acoustic propagation speed varies between 1503 m/s to 1544 m/s as temperature and depth differs. The simulation results show that temperature, salinity, depth plays major role in acoustic propagation and data rate increases with appropriate data sets substituted in the simulated model.

Keywords: Underwater Acoustics, Mackenzie Speed Equation, Temperature, Salinity.

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747 Efficacy of Polyfluoroalkyl Substances Filtration with Low-Cost Organic Fiber Filter

Authors: Gautham Das, Edward Morrone, Erik Treble, Clinton Binder

Abstract:

The purpose of this study was to evaluate the efficacy of a low-cost filter regarding per- and polyfluoroalkyl substances (PFAS). PFAS is a commonly used man-made chemical that can be found in a variety of household and industrial products with deleterious effects on humans. The filter consists of a combination of low-cost materials which could be locally procured. Water testing results for 4 different PFAS contaminants indicated that for Perfluorooctane sulfonic acid (PFOS), the Agency for Toxic Substances and Disease Registry (ATSDR) regulation is 7 ppt, the initial concentration was 15 ppt, and the final concentration was 3.9 ppt. For Perfluorononanoic acid (PFNA), the ATSDR regulation is 10.5 ppt, the initial concentration was 15 ppt, and the final concentration was 3.9 ppt. For Perfluorooctanoic acid (PFOA), the ATSDR regulation is 11 ppt, the initial concentration was 15 ppt, and the final concentration was 3.9 ppt. For Perfluorohexane sulfonic acid (PFHxS), the ATSDR regulation is 70 ppt, the initial concentration was 15 ppt, and the final concentration was 3.9 ppt. The results indicated a 74% reduction in PFAS concentration in filtered samples. Statistical data through regression analysis showed 0.9 validity of the sample data. Initial tests show the efficiency of the proposed filter described could be far greater if tested at a greater scale. It is highly recommended further testing to be conducted to validate the data for an innovative solution to a ubiquitous problem.

Keywords: PFAS, PFOS, PFOA, PFHxS, low-cost filter.

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746 Predicting Global Solar Radiation Using Recurrent Neural Networks and Climatological Parameters

Authors: Rami El-Hajj Mohamad, Mahmoud Skafi, Ali Massoud Haidar

Abstract:

Several meteorological parameters were used for the  prediction of monthly average daily global solar radiation on  horizontal using recurrent neural networks (RNNs). Climatological  data and measures, mainly air temperature, humidity, sunshine  duration, and wind speed between 1995 and 2007 were used to design  and validate a feed forward and recurrent neural network based  prediction systems. In this paper we present our reference system  based on a feed-forward multilayer perceptron (MLP) as well as the  proposed approach based on an RNN model. The obtained results  were promising and comparable to those obtained by other existing  empirical and neural models. The experimental results showed the  advantage of RNNs over simple MLPs when we deal with time series  solar radiation predictions based on daily climatological data.

Keywords: Recurrent Neural Networks, Global Solar Radiation, Multi-layer perceptron, gradient, Root Mean Square Error.

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745 Design and Implementation of Secure Electronic Payment System (Client)

Authors: Pyae Pyae Hun

Abstract:

Secure electronic payment system is presented in this paper. This electronic payment system is to be secure for clients such as customers and shop owners. The security architecture of the system is designed by RC5 encryption / decryption algorithm. This eliminates the fraud that occurs today with stolen credit card numbers. The symmetric key cryptosystem RC5 can protect conventional transaction data such as account numbers, amount and other information. This process can be done electronically using RC5 encryption / decryption program written by Microsoft Visual Basic 6.0. There is no danger of any data sent within the system being intercepted, and replaced. The alternative is to use the existing network, and to encrypt all data transmissions. The system with encryption is acceptably secure, but that the level of encryption has to be stepped up, as computing power increases. Results In order to be secure the system the communication between modules is encrypted using symmetric key cryptosystem RC5. The system will use simple user name, password, user ID, user type and cipher authentication mechanism for identification, when the user first enters the system. It is the most common method of authentication in most computer system.

Keywords: A 128-bit block cipher, Microsoft visual basic 6.0, RC5 encryption /decryption algorithm and TCP/IP protocol.

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744 A Multiple-State Based Power Control for Multi-Radio Multi-Channel Wireless Mesh Networks

Authors: T. O. Olwal, K. Djouani, B. J. van Wyk, Y. Hamam, P. Siarry, N. Ntlatlapa

Abstract:

Multi-Radio Multi-Channel (MRMC) systems are key to power control problems in wireless mesh networks (WMNs). In this paper, we present asynchronous multiple-state based power control for MRMC WMNs. First, WMN is represented as a set of disjoint Unified Channel Graphs (UCGs). Second, each network interface card (NIC) or radio assigned to a unique UCG adjusts transmission power using predicted multiple interaction state variables (IV) across UCGs. Depending on the size of queue loads and intra- and inter-channel states, each NIC optimizes transmission power locally and asynchronously. A new power selection MRMC unification protocol (PMMUP) is proposed that coordinates interactions among radios. The efficacy of the proposed method is investigated through simulations.

Keywords: Asynchronous convergence, Multi-Radio Multi-Channel (MRMC), Power Selection Multi-Radio Multi-Channel Unification Protocol (PMMUP) and Wireless Mesh Networks(WMNs)

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743 A Web-Based Self-Learning Grammar for Spoken Language Understanding

Authors: S. M. Biondi, V. Catania, R. Di Natale, A. R. Intilisano, D. Panno

Abstract:

One of the major goals of Spoken Dialog Systems (SDS) is to understand what the user utters. In the SDS domain, the Spoken Language Understanding (SLU) Module classifies user utterances by means of a pre-definite conceptual knowledge. The SLU module is able to recognize only the meaning previously included in its knowledge base. Due the vastity of that knowledge, the information storing is a very expensive process. Updating and managing the knowledge base are time-consuming and error-prone processes because of the rapidly growing number of entities like proper nouns and domain-specific nouns. This paper proposes a solution to the problem of Name Entity Recognition (NER) applied to a SDS domain. The proposed solution attempts to automatically recognize the meaning associated with an utterance by using the PANKOW (Pattern based Annotation through Knowledge On the Web) method at runtime. The method being proposed extracts information from the Web to increase the SLU knowledge module and reduces the development effort. In particular, the Google Search Engine is used to extract information from the Facebook social network.

Keywords: Spoken Dialog System, Spoken Language Understanding, Web Semantic, Name Entity Recognition.

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742 Available Transmission Transfer Efficiency (ATTE) as an Index Measurement for Power Transmission Grid Performance

Authors: Ahmad Abubakar Sadiq, Mark N. Nwohu, Jacob Tsado, Ahmad A. Ashraf, Agbachi E. Okenna, Enesi E. Yahaya, Ambafi James Garba

Abstract:

Transmission system performance analysis is vital to proper planning and operations of power systems in the presence of deregulation. Key performance indicators (KPIs) are often used as measure of degree of performance. This paper gives a novel method to determine the transmission efficiency by evaluating the ratio of real power losses incurred from a specified transfer direction. Available Transmission Transfer Efficiency (ATTE) expresses the percentage of real power received resulting from inter-area available power transfer. The Tie line (Rated system path) performance is seen to differ from system wide (Network response) performance and ATTE values obtained are transfer direction specific. The required sending end quantities with specified receiving end ATC and the receiving end power circle diagram are obtained for the tie line analysis. The amount of real power loss load relative to the available transfer capability gives a measure of the transmission grid efficiency.

Keywords: Available transfer capability, efficiency performance, real power, transmission system.

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741 Soil Moisture Control System: A Product Development Approach

Authors: Swapneel U. Naphade, Dushyant A. Patil, Satyabodh M. Kulkarni

Abstract:

In this work, we propose the concept and geometrical design of a soil moisture control system (SMCS) module by following the product development approach to develop an inexpensive, easy to use and quick to install product targeted towards agriculture practitioners. The module delivers water to the agricultural land efficiently by sensing the soil moisture and activating the delivery valve. We start with identifying the general needs of the potential customer. Then, based on customer needs we establish product specifications and identify important measuring quantities to evaluate our product. Keeping in mind the specifications, we develop various conceptual solutions of the product and select the best solution through concept screening and selection matrices. Then, we develop the product architecture by integrating the systems into the final product. In the end, the geometric design is done using human factors engineering concepts like heuristic analysis, task analysis, and human error reduction analysis. The result of human factors analysis reveals the remedies which should be applied while designing the geometry and software components of the product. We find that to design the best grip in terms of comfort and applied force, for a power-type grip, a grip-diameter of 35 mm is the most ideal.

Keywords: Agriculture, human factors, product design, soil moisture control.

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740 Effect of Hydrogen-Diesel Dual Fuel Combustion on the Performance and Emission Characteristics of a Four Stroke-Single Cylinder Diesel Engine

Authors: Madhujit Deb, G. R. K. Sastry, R. S. Panua, Rahul Banerjee, P. K. Bose

Abstract:

The present work attempts to investigate the combustion, performance and emission characteristics of an existing single-cylinder four-stroke compression-ignition engine operated in dual-fuel mode with hydrogen as an alternative fuel. Environmental concerns and limited amount of petroleum fuels have caused interests in the development of alternative fuels like hydrogen for internal combustion (IC) engines. In this experimental investigation, a diesel engine is made to run using hydrogen in dual fuel mode with diesel, where hydrogen is introduced into the intake manifold using an LPGCNG injector and pilot diesel is injected using diesel injectors. A Timed Manifold Injection (TMI) system has been developed to vary the injection strategies. The optimized timing for the injection of hydrogen was 10^0 CA after top dead center (ATDC). From the study it was observed that with increasing hydrogen rate, enhancement in brake thermal efficiency (BTHE) of the engine has been observed with reduction in brake specific energy consumption (BSEC). Furthermore, Soot contents decrease with an increase in indicated specific NOx emissions with the enhancement of hydrogen flow rate.

Keywords: Diesel engine, Hydrogen, BTHE, BSEC, Soot, NOx.

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739 Optimization of Process Parameters of Pressure Die Casting using Taguchi Methodology

Authors: Satish Kumar, Arun Kumar Gupta, Pankaj Chandna

Abstract:

The present work analyses different parameters of pressure die casting to minimize the casting defects. Pressure diecasting is usually applied for casting of aluminium alloys. Good surface finish with required tolerances and dimensional accuracy can be achieved by optimization of controllable process parameters such as solidification time, molten temperature, filling time, injection pressure and plunger velocity. Moreover, by selection of optimum process parameters the pressure die casting defects such as porosity, insufficient spread of molten material, flash etc. are also minimized. Therefore, a pressure die casting component, carburetor housing of aluminium alloy (Al2Si2O5) has been considered. The effects of selected process parameters on casting defects and subsequent setting of parameters with the levels have been accomplished by Taguchi-s parameter design approach. The experiments have been performed as per the combination of levels of different process parameters suggested by L18 orthogonal array. Analyses of variance have been performed for mean and signal-to-noise ratio to estimate the percent contribution of different process parameters. Confidence interval has also been estimated for 95% consistency level and three conformational experiments have been performed to validate the optimum level of different parameters. Overall 2.352% reduction in defects has been observed with the help of suggested optimum process parameters.

Keywords: Aluminium Casting, Pressure Die Casting, Taguchi Methodology, Design of Experiments

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738 Relocation of the Air Quality Monitoring Stations Network for Aburrá Valley Based on Local Climatic Zones

Authors: Carmen E. Zapata, José F. Jiménez, Mauricio Ramiréz, Natalia A. Cano

Abstract:

The majority of the urban areas in Latin America face the challenges associated with city planning and development problems, attributed to human, technical, and economical factors; therefore, we cannot ignore the issues related to climate change because the city modifies the natural landscape in a significant way transforming the radiation balance and heat content in the urbanized areas. These modifications provoke changes in the temperature distribution known as “the heat island effect”. According to this phenomenon, we have the need to conceive the urban planning based on climatological patterns that will assure its sustainable functioning, including the particularities of the climate variability. In the present study, it is identified the Local Climate Zones (LCZ) in the Metropolitan Area of the Aburrá Valley (Colombia) with the objective of relocate the air quality monitoring stations as a partial solution to the problem of how to measure representative air quality levels in a city for a local scale, but with instruments that measure in the microscale.

Keywords: Air quality, monitoring, local climatic zones, valley, monitoring stations.

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737 An Environmentally Friendly Approach towards the Conservation of Vernacular Architecture

Authors: M. Philokyprou, A. Michael

Abstract:

Contemporary theories of sustainability, concerning the natural and built environment, have recently introduced an environmental attitude towards the architectural design that, in turn, affects the practice of conservation and reuse of the existing building stock. This paper presents an environmentally friendly approach towards the conservation of vernacular architecture and it is based on the results of a research program which involved the investigation of sustainable design elements of traditional buildings in Cyprus. The research in question showed that Cypriot vernacular architecture gave more emphasis on cooling rather than heating strategies. Another notable finding of the investigation was the great importance given to courtyards as they enhance considerably, and in various ways, the microclimatic conditions of the immediate environment with favorable results throughout the year. Moreover, it was shown that the reduction in temperature fluctuation observed in the closed and semi-open spaces, compared to the respective temperature fluctuation of the external environment -due to the thermal inertia of the building envelope- helps towards the achievement of more comfortable living conditions within traditional dwellings. This paper concludes with a proposal of a sustainable approach towards the conservation of the existing environment and the introduction of new environmental criteria for the conservation of traditional buildings, beyond the aesthetic, morphological and structural ones that are generally applied.

Keywords: Bioclimatic, conservation, environmental, traditional dwellings, vernacular architecture.

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736 Effect of Relative Permeability on Well Testing Behavior of Naturally Fractured Lean Gas Condensate Reservoirs

Authors: G.H. Montazeri, Z. Dastkhan, H. Aliabadi

Abstract:

Gas condensate Reservoirs show complicated thermodynamic behavior when their pressure reduces to under dew point pressure. Condensate blockage around the producing well cause significant reduction of production rate as well bottom-hole pressure drops below saturation pressure. The main objective of this work was to examine the well test analysis of naturally fractured lean gas condensate reservoir and investigate the effect of condensate formed around the well-bore on behavior of single phase pseudo pressure and its derivative curves. In this work a naturally fractured lean gas condensate reservoir is simulated with compositional simulator. Different sensitivity analysis done on Corry parameters and result of simulator is feed to analytical well testing software. For consideration of these phenomena eighteen compositional models with Capillary number effect are constructed. Matrix relative permeability obeys Corry relative permeability and relative permeability in fracture is linear. Well testing behavior of these models are studied and interpreted. Results show different sensitivity analysis on relative permeability of matrix does not have strong effect on well testing behavior even most part of the matrix around the well is occupied with condensate.

Keywords: Lean gas, fractured condensate reservoir, capillary number, well testing analysis, relative permeability.

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735 Modified Plastic-Damage Model for Fiber Reinforced Polymer-Confined Repaired Concrete Columns

Authors: I. A Tijani, Y. F Wu, C.W. Lim

Abstract:

Concrete Damaged Plasticity Model (CDPM) is capable of modeling the stress-strain behavior of confined concrete. Nevertheless, the accuracy of the model largely depends on its parameters. To date, most research works mainly focus on the identification and modification of the parameters for fiber reinforced polymer (FRP) confined concrete prior to damage. And, it has been established that the FRP-strengthened concrete behaves differently to FRP-repaired concrete. This paper presents a modified plastic damage model within the context of the CDPM in ABAQUS for modelling of a uniformly FRP-confined repaired concrete under monotonic loading. The proposed model includes infliction damage, elastic stiffness, yield criterion and strain hardening rule. The distinct feature of damaged concrete is elastic stiffness reduction; this is included in the model. Meanwhile, the test results were obtained from a physical testing of repaired concrete. The dilation model is expressed as a function of the lateral stiffness of the FRP-jacket. The finite element predictions are shown to be in close agreement with the obtained test results of the repaired concrete. It was observed from the study that with necessary modifications, finite element method is capable of modeling FRP-repaired concrete structures.

Keywords: Concrete, FRP, damage, repairing, plasticity, and finite element method.

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734 Optimisation of a Dragonfly-Inspired Flapping Wing-Actuation System

Authors: Jia-Ming Kok, Javaan Chahl

Abstract:

An optimisation method using both global and local optimisation is implemented to determine the flapping profile which will produce the most lift for an experimental wing-actuation system. The optimisation method is tested using a numerical quasi-steady analysis. Results of an optimised flapping profile show a 20% increase in lift generated as compared to flapping profiles obtained by high speed cinematography of a Sympetrum frequens dragonfly. Initial optimisation procedures showed 3166 objective function evaluations. The global optimisation parameters - initial sample size and stage one sample size, were altered to reduce the number of function evaluations. Altering the stage one sample size had no significant effect. It was found that reducing the initial sample size to 400 would allow a reduction in computational effort to approximately 1500 function evaluations without compromising the global solvers ability to locate potential minima. To further reduce the optimisation effort required, we increase the local solver’s convergence tolerance criterion. An increase in the tolerance from 0.02N to 0.05N decreased the number of function evaluations by another 20%. However, this potentially reduces the maximum obtainable lift by up to 0.025N.

Keywords: Flapping wing, Optimisation, Quasi-steady model.

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733 Effects of Cerium Oxide Nanoparticle Addition in Diesel and Diesel-Biodiesel Blends on the Performance Characteristics of a CI Engine

Authors: Abbas Alli Taghipoor Bafghi, Hosein Bakhoda, Fateme Khodaei Chegeni

Abstract:

An experimental investigation is carried out to establish the performance characteristics of a compression ignition engine while using cerium oxide nanoparticles as additive in neat diesel and diesel-biodiesel blends. In the first phase of the experiments, stability of neat diesel and diesel-biodiesel fuel blends with the addition of cerium oxide nanoparticles is analyzed. After series of experiments, it is found that the blends subjected to high speed blending followed by ultrasonic bath stabilization improves the stability. In the second phase, performance characteristics are studied using the stable fuel blends in a single cylinder four stroke engine coupled with an electrical dynamometer and a data acquisition system. The cerium oxide acts as an oxygen donating catalyst and provides oxygen for combustion. The activation energy of cerium oxide acts to burn off carbon deposits within the engine cylinder at the wall temperature and prevents the deposition of non-polar compounds on the cylinder wall results reduction in HC emissions. The tests revealed that cerium oxide nanoparticles can be used as additive in diesel and diesel-biodiesel blends to improve complete combustion of the fuel significantly.

Keywords: Diesel engine, cerium oxide, diesel-biodiesel blends, nanoparticles.

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732 Reliability Factors Based Fuzzy Logic Scheme for Spectrum Sensing

Authors: Tallataf Rasheed, Adnan Rashdi, Ahmad Naeem Akhtar

Abstract:

The accurate spectrum sensing is a fundamental requirement of dynamic spectrum access for deployment of Cognitive Radio Network (CRN). To acheive this requirement a Reliability factors based Fuzzy Logic (RFL) Scheme for Spectrum Sensing has been proposed in this paper. Cognitive Radio User (CRU) predicts the presence or absence of Primary User (PU) using energy detector and calculates the Reliability factors which are SNR of sensing node, threshold of energy detector and decision difference of each node with other nodes in a cooperative spectrum sensing environment. Then the decision of energy detector is combined with Reliability factors of sensing node using Fuzzy Logic. These Reliability Factors used in RFL Scheme describes the reliability of decision made by a CRU to improve the local spectrum sensing. This Fuzzy combining scheme provides the accuracy of decision made by sensornode. The simulation results have shown that the proposed technique provide better PU detection probability than existing Spectrum Sensing Techniques.

Keywords: Cognitive radio, spectrum sensing, energy detector, reliability factors, fuzzy logic.

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731 DAMQ-Based Approach for Efficiently Using the Buffer Spaces of a NoC Router

Authors: Mohammad Ali Jabraeil Jamali, Ahmad khademzadeh

Abstract:

In this paper we present high performance dynamically allocated multi-queue (DAMQ) buffer schemes for fault tolerance systems on chip applications that require an interconnection network. Two virtual channels shared the same buffer space. Fault tolerant mechanisms for interconnection networks are becoming a critical design issue for large massively parallel computers. It is also important to high performance SoCs as the system complexity keeps increasing rapidly. On the message switching layer, we make improvement to boost system performance when there are faults involved in the components communication. The proposed scheme is when a node or a physical channel is deemed as faulty, the previous hop node will terminate the buffer occupancy of messages destined to the failed link. The buffer usage decisions are made at switching layer without interactions with higher abstract layer, thus buffer space will be released to messages destined to other healthy nodes quickly. Therefore, the buffer space will be efficiently used in case fault occurs at some nodes.

Keywords: DAMQ, NoC, fault tolerant, odd-even routingalgorithm, buffer space.

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730 Nuclear Power Generation and CO2 Abatement Scenarios in Taiwan

Authors: Chang-Bin Huang, Fu-Kuang Ko

Abstract:

Taiwan was the first country in Asia to announce “Nuclear-Free Homeland" in 2002. In 2008, the new government released the Sustainable Energy Policy Guidelines to lower the nationwide CO2 emissions some time between 2016 and 2020 back to the level of year 2008, further abatement of CO2 emissions is planed in year 2025 when CO2 emissions will decrease to the level of year 2000. Besides, under consideration of the issues of energy, environment and economics (3E), the new government declared that the nuclear power is a carbon-less energy option. This study analyses the effects of nuclear power generation for CO2 abatement scenarios in Taiwan. The MARKAL-MACRO energy model was adopted to evaluate economic impacts and energy deployment due to life extension of existing nuclear power plants and build new nuclear power units in CO2 abatement scenarios. The results show that CO2 abatement effort is expensive. On the other hand, nuclear power is a cost-effective choice. The GDP loss rate in the case of building new nuclear power plants is around two thirds of the Nuclear-Free Homeland case. Nuclear power generation has the capacity to provide large-scale CO2 free electricity. Therefore, the results show that nuclear power is not only an option for Taiwan, but also a requisite for Taiwan-s CO2 reduction strategy.

Keywords: Energy model, CO2 abatement, nuclear power, economic impacts.

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729 Biometric Technology in Securing the Internet Using Large Neural Network Technology

Authors: B. Akhmetov, A. Doszhanova, A. Ivanov, T. Kartbayev, A. Malygin

Abstract:

The article examines the methods of protection of citizens' personal data on the Internet using biometric identity authentication technology. It`s celebrated their potential danger due to the threat of loss of base biometric templates. To eliminate the threat of compromised biometric templates is proposed to use neural networks large and extra-large sizes, which will on the one hand securely (Highly reliable) to authenticate a person by his biometrics, and on the other hand make biometrics a person is not available for observation and understanding. This article also describes in detail the transformation of personal biometric data access code. It`s formed the requirements for biometrics converter code for his work with the images of "Insider," "Stranger", all the "Strangers". It`s analyzed the effect of the dimension of neural networks on the quality of converters mystery of biometrics in access code.

Keywords: Biometric security technologies, Conversion of personal biometric data access code, Electronic signature, Large neural networks, quality of converters "Biometrics - the code", the Egovernment.

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