Search results for: Real Coded Genetic Algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5451

Search results for: Real Coded Genetic Algorithm

831 Improving Packet Latency of Video Sensor Networks

Authors: Arijit Ghosh, Tony Givargis

Abstract:

Video sensor networks operate on stringent requirements of latency. Packets have a deadline within which they have to be delivered. Violation of the deadline causes a packet to be treated as lost and the loss of packets ultimately affects the quality of the application. Network latency is typically a function of many interacting components. In this paper, we propose ways of reducing the forwarding latency of a packet at intermediate nodes. The forwarding latency is caused by a combination of processing delay and queueing delay. The former is incurred in order to determine the next hop in dynamic routing. We show that unless link failures in a very specific and unlikely pattern, a vast majority of these lookups are redundant. To counter this we propose source routing as the routing strategy. However, source routing suffers from issues related to scalability and being impervious to network dynamics. We propose solutions to counter these and show that source routing is definitely a viable option in practical sized video networks. We also propose a fast and fair packet scheduling algorithm that reduces queueing delay at the nodes. We support our claims through extensive simulation on realistic topologies with practical traffic loads and failure patterns.

Keywords: Sensor networks, Packet latency, Network design, Networkperformance.

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830 Using ANSYS to Realize a Semi-Analytical Method for Predicting Temperature Profile in Injection/Production Well

Authors: N. Tarom, M.M. Hossain

Abstract:

Determination of wellbore problems during a production/injection process might be evaluated thorough temperature log analysis. Other applications of this kind of log analysis may also include evaluation of fluid distribution analysis along the wellbore and identification of anomalies encountered during production/injection process. While the accuracy of such prediction is paramount, the common method of determination of a wellbore temperature log includes use of steady-state energy balance equations, which hardly describe the real conditions as observed in typical oil and gas flowing wells during production operation; and thus increase level of uncertainties. In this study, a practical method has been proposed through development of a simplified semianalytical model to apply for predicting temperature profile along the wellbore. The developed model includes an overall heat transfer coefficient accounting all modes of heat transferring mechanism, which has been focused on the prediction of a temperature profile as a function of depth for the injection/production wells. The model has been validated with the results obtained from numerical simulation.

Keywords: Energy balance equation, reservoir and well performance, temperature log, overall heat transfer coefficient.

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829 Variation of Spot Price and Profits of Andhra Pradesh State Grid in Deregulated Environment

Authors: Chava Sunil Kumar, P.S. Subrahmanyan, J. Amarnath

Abstract:

In this paper variation of spot price and total profits of the generating companies- through wholesale electricity trading are discussed with and without Central Generating Stations (CGS) share and seasonal variations are also considered. It demonstrates how proper analysis of generators- efficiencies and capabilities, types of generators owned, fuel costs, transmission losses and settling price variation using the solutions of Optimal Power Flow (OPF), can allow companies to maximize overall revenue. It illustrates how solutions of OPF can be used to maximize companies- revenue under different scenarios. And is also extended to computation of Available Transfer Capability (ATC) is very important to the transmission system security and market forecasting. From these results it is observed that how crucial it is for companies to plan their daily operations and is certainly useful in an online environment of deregulated power system. In this paper above tasks are demonstrated on 124 bus real-life Indian utility power system of Andhra Pradesh State Grid and results have been presented and analyzed.

Keywords: OPF, ATC, Electricity Market, Bid, Spot Price

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828 Micromechanics of Stress Transfer across the Interface Fiber-Matrix Bonding

Authors: Fatiha Teklal, Bachir Kacimi, Arezki Djebbar

Abstract:

The study and application of composite materials are a truly interdisciplinary endeavor that has been enriched by contributions from chemistry, physics, materials science, mechanics and manufacturing engineering. The understanding of the interface (or interphase) in composites is the central point of this interdisciplinary effort. From the early development of composite materials of various nature, the optimization of the interface has been of major importance. Even more important, the ideas linking the properties of composites to the interface structure are still emerging. In our study, we need a direct characterization of the interface; the micromechanical tests we are addressing seem to meet this objective and we chose to use two complementary tests simultaneously. The microindentation test that can be applied to real composites and the drop test, preferred to the pull-out because of the theoretical possibility of studying systems with high adhesion (which is a priori the case with our systems). These two tests are complementary because of the principle of the model specimen used for both the first "compression indentation" and the second whose fiber is subjected to tensile stress called the drop test. Comparing the results obtained by the two methods can therefore be rewarding.

Keywords: Interface, micromechanics, pull-out, composite, fiber, matrix.

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827 Approximating Maximum Speed on Road from Curvature Information of Bezier Curve

Authors: M. Y. Misro, A. Ramli, J. M. Ali

Abstract:

Bezier curves have useful properties for path generation problem, for instance, it can generate the reference trajectory for vehicles to satisfy the path constraints. Both algorithms join cubic Bezier curve segment smoothly to generate the path. Some of the useful properties of Bezier are curvature. In mathematics, curvature is the amount by which a geometric object deviates from being flat, or straight in the case of a line. Another extrinsic example of curvature is a circle, where the curvature is equal to the reciprocal of its radius at any point on the circle. The smaller the radius, the higher the curvature thus the vehicle needs to bend sharply. In this study, we use Bezier curve to fit highway-like curve. We use different approach to find the best approximation for the curve so that it will resembles highway-like curve. We compute curvature value by analytical differentiation of the Bezier Curve. We will then compute the maximum speed for driving using the curvature information obtained. Our research works on some assumptions; first, the Bezier curve estimates the real shape of the curve which can be verified visually. Even though, fitting process of Bezier curve does not interpolate exactly on the curve of interest, we believe that the estimation of speed are acceptable. We verified our result with the manual calculation of the curvature from the map.

Keywords: Speed estimation, path constraints, reference trajectory, Bezier curve.

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826 Dynamic Metrics for Polymorphism in Object Oriented Systems

Authors: Parvinder Singh Sandhu, Gurdev Singh

Abstract:

Metrics is the process by which numbers or symbols are assigned to attributes of entities in the real world in such a way as to describe them according to clearly defined rules. Software metrics are instruments or ways to measuring all the aspect of software product. These metrics are used throughout a software project to assist in estimation, quality control, productivity assessment, and project control. Object oriented software metrics focus on measurements that are applied to the class and other characteristics. These measurements convey the software engineer to the behavior of the software and how changes can be made that will reduce complexity and improve the continuing capability of the software. Object oriented software metric can be classified in two types static and dynamic. Static metrics are concerned with all the aspects of measuring by static analysis of software and dynamic metrics are concerned with all the measuring aspect of the software at run time. Major work done before, was focusing on static metric. Also some work has been done in the field of dynamic nature of the software measurements. But research in this area is demanding for more work. In this paper we give a set of dynamic metrics specifically for polymorphism in object oriented system.

Keywords: Metrics, Software, Quality, Object oriented system, Polymorphism.

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825 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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824 A Unique Solution for Designing Low-Cost, Heterogeneous Sensor Networks Using a Middleware Integration Platform

Authors: Jarrod Trevathan, Trina Myers

Abstract:

Proprietary sensor network systems are typically expensive, rigid and difficult to incorporate technologies from other vendors. When using competing and incompatible technologies, a non-proprietary system is complex to create because it requires significant technical expertise and effort, which can be more expensive than a proprietary product. This paper presents the Sensor Abstraction Layer (SAL) that provides middleware architectures with a consistent and uniform view of heterogeneous sensor networks, regardless of the technologies involved. SAL abstracts and hides the hardware disparities and specificities related to accessing, controlling, probing and piloting heterogeneous sensors. SAL is a single software library containing a stable hardware-independent interface with consistent access and control functions to remotely manage the network. The end-user has near-real-time access to the collected data via the network, which results in a cost-effective, flexible and simplified system suitable for novice users. SAL has been used for successfully implementing several low-cost sensor network systems.

Keywords: Sensor networks, hardware abstraction, middleware integration platform, sensor web enablement.

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823 Impact of Safety and Quality Considerations of Housing Clients on the Construction Firms’ Intention to Adopt Quality Function Deployment: A Case of Construction Sector

Authors: Saif Ul Haq

Abstract:

The current study intends to examine the safety and quality considerations of clients of housing projects and their impact on the adoption of Quality Function Deployment (QFD) by the construction firm. Mixed method research technique has been used to collect and analyze the data wherein a survey was conducted to collect the data from 220 clients of housing projects in Saudi Arabia. Then, the telephonic and Skype interviews were conducted to collect data of 15 professionals working in the top ten real estate companies of Saudi Arabia. Data were analyzed by using partial least square (PLS) and thematic analysis techniques. Findings reveal that today’s customer prioritizes the safety and quality requirements of their houses and as a result, construction firms adopt QFD to address the needs of customers. The findings are of great importance for the clients of housing projects as well as for the construction firms as they could apply QFD in housing projects to address the safety and quality concerns of their clients.

Keywords: Construction industry, quality considerations, quality function deployment, safety considerations.

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822 Augmented Reality in Advertising and Brand Communication: An Experimental Study

Authors: O. Mauroner, L. Le, S. Best

Abstract:

Digital technologies offer many opportunities in the design and implementation of brand communication and advertising. Augmented reality (AR) is an innovative technology in marketing communication that focuses on the fact that virtual interaction with a product ad offers additional value to consumers. AR enables consumers to obtain (almost) real product experiences by the way of virtual information even before the purchase of a certain product. Aim of AR applications in relation with advertising is in-depth examination of product characteristics to enhance product knowledge as well as brand knowledge. Interactive design of advertising provides observers with an intense examination of a specific advertising message and therefore leads to better brand knowledge. The elaboration likelihood model and the central route to persuasion strongly support this argumentation. Nevertheless, AR in brand communication is still in an initial stage and therefore scientific findings about the impact of AR on information processing and brand attitude are rare. The aim of this paper is to empirically investigate the potential of AR applications in combination with traditional print advertising. To that effect an experimental design with different levels of interactivity is built to measure the impact of interactivity of an ad on different variables o advertising effectiveness.

Keywords: Advertising effectiveness, augmented reality, brand communication, brand recall, interactivity.

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821 Pipelines Monitoring System Using Bio-mimetic Robots

Authors: Seung You Na, Daejung Shin, Jin Young Kim, Seong-Joon Baek, Bae-Ho Lee

Abstract:

Recently there has been a growing interest in the field of bio-mimetic robots that resemble the behaviors of an insect or an aquatic animal, among many others. One of various bio-mimetic robot applications is to explore pipelines, spotting any troubled areas or malfunctions and reporting its data. Moreover, the robot is able to prepare for and react to any abnormal routes in the pipeline. Special types of mobile robots are necessary for the pipeline monitoring tasks. In order to move effectively along a pipeline, the robot-s movement will resemble that of insects or crawling animals. When situated in massive pipelines with complex routes, the robot places fixed sensors in several important spots in order to complete its monitoring. This monitoring task is to prevent a major system failure by preemptively recognizing any minor or partial malfunctions. Areas uncovered by fixed sensors are usually impossible to provide real-time observation and examination, and thus are dependent on periodical offline monitoring. This paper proposes a monitoring system that is able to monitor the entire area of pipelines–with and without fixed sensors–by using the bio-mimetic robot.

Keywords: Bio-mimetic robots, Plant pipes monitoring, Mobile and active monitoring.

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820 Enhancing the Performance of H.264/AVC in Adaptive Group of Pictures Mode Using Octagon and Square Search Pattern

Authors: S. Sowmyayani, P. Arockia Jansi Rani

Abstract:

This paper integrates Octagon and Square Search pattern (OCTSS) motion estimation algorithm into H.264/AVC (Advanced Video Coding) video codec in Adaptive Group of Pictures (AGOP) mode. AGOP structure is computed based on scene change in the video sequence. Octagon and square search pattern block-based motion estimation method is implemented in inter-prediction process of H.264/AVC. Both these methods reduce bit rate and computational complexity while maintaining the quality of the video sequence respectively. Experiments are conducted for different types of video sequence. The results substantially proved that the bit rate, computation time and PSNR gain achieved by the proposed method is better than the existing H.264/AVC with fixed GOP and AGOP. With a marginal gain in quality of 0.28dB and average gain in bitrate of 132.87kbps, the proposed method reduces the average computation time by 27.31 minutes when compared to the existing state-of-art H.264/AVC video codec.

Keywords: Block Distortion Measure, Block Matching Algorithms, H.264/AVC, Motion estimation, Search patterns, Shot cut detection.

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819 Flocculation on the Treatment of Olive Oil Mill Wastewater: Pretreatment

Authors: G. Hodaifa, J. A. Páez, C. Agabo, E. Ramos, J. C. Gutiérrez, A. Rosal

Abstract:

Currently, continuous two-phase decanter process used for olive oil production is the more internationally widespread. The wastewaters generated from this industry (OMW) are a real environmental problem because of its high organic load. Among proposed treatments for these wastewaters, advanced oxidation technologies (Fenton, ozone, photoFenton, etc.) are the most favourable. The direct application of these processes is somewhat expensive. Therefore, the application of a previous stage based on a flocculation-sedimentation operation is of high importance. In this research five commercial flocculants (three cationic, and two anionic) have been used to achieve the separation of phases (liquid clarifiedsludge). For each flocculant, different concentrations (0-1000 mg/L) have been studied. In these experiments, sludge volume formed and the final water quality were determined. The final removal percentages of total phenols (11.3-25.1%), COD (5.6-20.4%), total carbon (2.3-26.5%), total organic carbon (1.50-23.8%), total nitrogen (1.45-24.8%), and turbidity (27.9-61.4%) were determined. The variation on electric conductivity reduction percentage (1-8%) was also determined. Finally, the best flocculants with highest removal percentages have been determined (QG2001 and Flocudex CS49).

Keywords: Flocculants, flocculation, olive oil mill wastewater, water quality.

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818 Illumination Invariant Face Recognition using Supervised and Unsupervised Learning Algorithms

Authors: Shashank N. Mathur, Anil K. Ahlawat, Virendra P. Vishwakarma

Abstract:

In this paper, a comparative study of application of supervised and unsupervised learning algorithms on illumination invariant face recognition has been carried out. The supervised learning has been carried out with the help of using a bi-layered artificial neural network having one input, two hidden and one output layer. The gradient descent with momentum and adaptive learning rate back propagation learning algorithm has been used to implement the supervised learning in a way that both the inputs and corresponding outputs are provided at the time of training the network, thus here is an inherent clustering and optimized learning of weights which provide us with efficient results.. The unsupervised learning has been implemented with the help of a modified Counterpropagation network. The Counterpropagation network involves the process of clustering followed by application of Outstar rule to obtain the recognized face. The face recognition system has been developed for recognizing faces which have varying illumination intensities, where the database images vary in lighting with respect to angle of illumination with horizontal and vertical planes. The supervised and unsupervised learning algorithms have been implemented and have been tested exhaustively, with and without application of histogram equalization to get efficient results.

Keywords: Artificial Neural Networks, back propagation, Counterpropagation networks, face recognition, learning algorithms.

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817 Gender Based Variability Time Series Complexity Analysis

Authors: Ramesh K. Sunkaria, Puneeta Marwaha

Abstract:

Non linear methods of heart rate variability (HRV) analysis are becoming more popular. It has been observed that complexity measures quantify the regularity and uncertainty of cardiovascular RR-interval time series. In the present work, SampEn has been evaluated in healthy normal sinus rhythm (NSR) male and female subjects for different data lengths and tolerance level r. It is demonstrated that SampEn is small for higher values of tolerance r. Also SampEn value of healthy female group is higher than that of healthy male group for short data length and with increase in data length both groups overlap each other and it is difficult to distinguish them. The SampEn gives inaccurate results by assigning higher value to female group, because male subject have more complex HRV pattern than that of female subjects. Therefore, this traditional algorithm exhibits higher complexity for healthy female subjects than for healthy male subjects, which is misleading observation. This may be due to the fact that SampEn do not account for multiple time scales inherent in the physiologic time series and the hidden spatial and temporal fluctuations remains unexplored.

Keywords: Heart rate variability, normal sinus rhythm group, RR interval time series, sample entropy.

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816 Adversarial Disentanglement Using Latent Classifier for Pose-Independent Representation

Authors: Hamed Alqahtani, Manolya Kavakli-Thorne

Abstract:

The large pose discrepancy is one of the critical challenges in face recognition during video surveillance. Due to the entanglement of pose attributes with identity information, the conventional approaches for pose-independent representation lack in providing quality results in recognizing largely posed faces. In this paper, we propose a practical approach to disentangle the pose attribute from the identity information followed by synthesis of a face using a classifier network in latent space. The proposed approach employs a modified generative adversarial network framework consisting of an encoder-decoder structure embedded with a classifier in manifold space for carrying out factorization on the latent encoding. It can be further generalized to other face and non-face attributes for real-life video frames containing faces with significant attribute variations. Experimental results and comparison with state of the art in the field prove that the learned representation of the proposed approach synthesizes more compelling perceptual images through a combination of adversarial and classification losses.

Keywords: Video surveillance, disentanglement, face detection.

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815 Preparation and Investigation of Photocatalytic Properties of ZnO Nanocrystals: Effect of Operational Parameters and Kinetic Study

Authors: N. Daneshvar, S. Aber, M. S. Seyed Dorraji, A. R. Khataee, M. H. Rasoulifard

Abstract:

ZnO nanocrystals with mean diameter size 14 nm have been prepared by precipitation method, and examined as photocatalyst for the UV-induced degradation of insecticide diazinon as deputy of organic pollutant in aqueous solution. The effects of various parameters, such as illumination time, the amount of photocatalyst, initial pH values and initial concentration of insecticide on the photocatalytic degradation diazinon were investigated to find desired conditions. In this case, the desired parameters were also tested for the treatment of real water containing the insecticide. Photodegradation efficiency of diazinon was compared between commercial and prepared ZnO nanocrystals. The results indicated that UV/ZnO process applying prepared nanocrystalline ZnO offered electrical energy efficiency and quantum yield better than commercial ZnO. The present study, on the base of Langmuir-Hinshelwood mechanism, illustrated a pseudo first-order kinetic model with rate constant of surface reaction equal to 0.209 mg l-1 min-1 and adsorption equilibrium constant of 0.124 l mg-1.

Keywords: Zinc oxide nanopowder, Electricity consumption, Quantum yield, Nanoparticles, Photodegradation, Kinetic model, Insecticide.

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814 Hybrid Control Mode Based On Multi-Sensor Information by Fuzzy Approach for Navigation Task of Autonomous Mobile Robot

Authors: Jonqlan Lin, C. Y. Tasi, K. H. Lin

Abstract:

This paper addresses the issue of the autonomous mobile robot (AMR) navigation task based on the hybrid control modes. The novel hybrid control mode, based on multi-sensors information by using the fuzzy approach, has been presented in this research. The system operates in real time, is robust, enables the robot to operate with imprecise knowledge, and takes into account the physical limitations of the environment in which the robot moves, obtaining satisfactory responses for a large number of different situations. An experiment is simulated and carried out with a pioneer mobile robot. From the experimental results, the effectiveness and usefulness of the proposed AMR obstacle avoidance and navigation scheme are confirmed. The experimental results show the feasibility, and the control system has improved the navigation accuracy. The implementation of the controller is robust, has a low execution time, and allows an easy design and tuning of the fuzzy knowledge base.

Keywords: Autonomous mobile robot, obstacle avoidance, MEMS, hybrid control mode, navigation control.

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813 Iraqi Short Term Electrical Load Forecasting Based On Interval Type-2 Fuzzy Logic

Authors: Firas M. Tuaimah, Huda M. Abdul Abbas

Abstract:

Accurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy can drop due to the presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. Interval Type 2 Fuzzy Logic System (IT2 FLS), with additional degrees of freedom, gives an excellent tool for handling uncertainties and it improved the prediction accuracy. The training data used in this study covers the period from January 1, 2012 to February 1, 2012 for winter season and the period from July 1, 2012 to August 1, 2012 for summer season. The actual load forecasting period starts from January 22, till 28, 2012 for winter model and from July 22 till 28, 2012 for summer model. The real data for Iraqi power system which belongs to the Ministry of Electricity.

Keywords: Short term load forecasting, prediction interval, type 2 fuzzy logic systems.

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812 Agent/Group/Role Organizational Model to Simulate an Industrial Control System

Authors: Noureddine Seddari, Mohamed Belaoued, Salah Bougueroua

Abstract:

The modeling of complex systems is generally based on the decomposition of their components into sub-systems easier to handle. This division has to be made in a methodical way. In this paper, we introduce an industrial control system modeling and simulation based on the Multi-Agent System (MAS) methodology AALAADIN and more particularly the underlying conceptual model Agent/Group/Role (AGR). Indeed, in this division using AGR model, the overall system is decomposed into sub-systems in order to improve the understanding of regulation and control systems, and to simplify the implementation of the obtained agents and their groups, which are implemented using the Multi-Agents Development KIT (MAD-KIT) platform. This approach appears to us to be the most appropriate for modeling of this type of systems because, due to the use of MAS, it is possible to model real systems in which very complex behaviors emerge from relatively simple and local interactions between many different individuals, therefore a MAS is well adapted to describe a system from the standpoint of the activity of its components, that is to say when the behavior of the individuals is complex (difficult to describe with equations). The main aim of this approach is the take advantage of the performance, the scalability and the robustness that are intuitively provided by MAS.

Keywords: Complex systems, modeling and simulation, industrial control system, MAS, AALAADIN, AGR, MAD-KIT.

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811 Implementation of an Innovative Simplified Sliding Mode Observer-Based Robust Fault Detection in a Drum Boiler System

Authors: L. Khoshnevisan, H. R. Momeni, A. Ashraf-Modarres

Abstract:

One of the robust fault detection filter (RFDF) designing method is based on sliding-mode theory. The main purpose of our study is to introduce an innovative simplified reference residual model generator to formulate the RFDF as a sliding-mode observer without any manipulation package or transformation matrix, through which the generated residual signals can be evaluated. So the proposed design is more explicit and requires less design parameters in comparison with approaches requiring changing coordinates. To the best author's knowledge, this is the first time that the sliding mode technique is applied to detect actuator and sensor faults in a real boiler. The designing procedure is proposed in a drum boiler in Synvendska Kraft AB Plant in Malmo, Sweden as a multivariable and strongly coupled system. It is demonstrated that both sensor and actuator faults can robustly be detected. Also sensor faults can be diagnosed and isolated through this method.

Keywords: Boiler, fault detection, robustness, simplified sliding-mode observer.

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810 Influence of Radio Frequency Identification Technology in Logistic, Inventory Control and Supply Chain Optimization

Authors: H. Amoozad-khalili, R. Tavakkoli-Moghaddam, N.Shahab-Dehkordi

Abstract:

The main aim of Supply Chain Management (SCM) is to produce, distribute, logistics and deliver goods and equipment in right location, right time, right amount to satisfy costumers, with minimum time and cost waste. So implementing techniques that reduce project time and cost, and improve productivity and performance is very important. Emerging technologies such as the Radio Frequency Identification (RFID) are now making it possible to automate supply chains in a real time manner and making them more efficient than the simple supply chain of the past for tracing and monitoring goods and products and capturing data on movements of goods and other events. This paper considers concepts, components and RFID technology characteristics by concentration of warehouse and inventories management. Additionally, utilization of RFID in the role of improving information management in supply chain is discussed. Finally, the facts of installation and this technology-s results in direction with warehouse and inventory management and business development will be presented.

Keywords: Logistics, Supply Chain Management, RFIDTechnology, Inventory Control.

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809 Palmprint Recognition by Wavelet Transform with Competitive Index and PCA

Authors: Deepti Tamrakar, Pritee Khanna

Abstract:

This manuscript presents, palmprint recognition by combining different texture extraction approaches with high accuracy. The Region of Interest (ROI) is decomposed into different frequencytime sub-bands by wavelet transform up-to two levels and only the approximate image of two levels is selected, which is known as Approximate Image ROI (AIROI). This AIROI has information of principal lines of the palm. The Competitive Index is used as the features of the palmprint, in which six Gabor filters of different orientations convolve with the palmprint image to extract the orientation information from the image. The winner-take-all strategy is used to select dominant orientation for each pixel, which is known as Competitive Index. Further, PCA is applied to select highly uncorrelated Competitive Index features, to reduce the dimensions of the feature vector, and to project the features on Eigen space. The similarity of two palmprints is measured by the Euclidean distance metrics. The algorithm is tested on Hong Kong PolyU palmprint database. Different AIROI of different wavelet filter families are also tested with the Competitive Index and PCA. AIROI of db7 wavelet filter achievs Equal Error Rate (EER) of 0.0152% and Genuine Acceptance Rate (GAR) of 99.67% on the palm database of Hong Kong PolyU.

Keywords: DWT, EER, Euclidean Distance, Gabor filter, PCA, ROI.

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808 Effect of the Internet on Social Capital

Authors: Safaee Safiollah , Javadi Alimohammad, Javadi Maryam

Abstract:

Internet access is a vital part of the modern world and an important tool in the education of our children. It is present in schools, homes and even shopping malls. Mastering the use of the internet is likely to be an important skill for those entering the job markets of the future. An internet user can be anyone he or she wants to be in an online chat room, or play thrilling and challenging games against other players from all corners of the globe. It seems at present time (or near future) for many people relationships in the real world may be neglected as those in the virtual world increase in importance. Internet is provided a fast mode of transportation caused freedom from family bonds and mixing with different cultures and new communities. This research is an attempt to study effect of Internet on Social capital. For this purpose a survey technique on the sample size amounted 168 students of Payame Noor University of Kermanshah city in country of Iran were considered. Degree of social capital is moderate. With the help of the Multi-variable Regression, variables of Iranian message attractive, Interest to internet with effect of positive and variable Creating a cordial atmosphere with negative effect be significant.

Keywords: Internet, Social Capital, social participation Social trust

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807 MLOps Scaling Machine Learning Lifecycle in an Industrial Setting

Authors: Yizhen Zhao, Adam S. Z. Belloum, Gonc¸alo Maia da Costa, Zhiming Zhao

Abstract:

Machine learning has evolved from an area of academic research to a real-world applied field. This change comes with challenges, gaps and differences exist between common practices in academic environments and the ones in production environments. Following continuous integration, development and delivery practices in software engineering, similar trends have happened in machine learning (ML) systems, called MLOps. In this paper we propose a framework that helps to streamline and introduce best practices that facilitate the ML lifecycle in an industrial setting. This framework can be used as a template that can be customized to implement various machine learning experiments. The proposed framework is modular and can be recomposed to be adapted to various use cases (e.g. data versioning, remote training on Cloud). The framework inherits practices from DevOps and introduces other practices that are unique to the machine learning system (e.g.data versioning). Our MLOps practices automate the entire machine learning lifecycle, bridge the gap between development and operation.

Keywords: Cloud computing, continuous development, data versioning, DevOps, industrial setting, MLOps, machine learning.

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806 Fuzzy EOQ Models for Deteriorating Items with Stock Dependent Demand and Non-Linear Holding Costs

Authors: G. C. Mahata, A. Goswami

Abstract:

This paper deals with infinite time horizon fuzzy Economic Order Quantity (EOQ) models for deteriorating items with  stock dependent demand rate and nonlinear holding costs by taking deterioration rate θ0 as a triangular fuzzy number  (θ0 −δ 1, θ0, θ0 +δ 2), where 1 2 0 0 <δ ,δ <θ are fixed real numbers. The traditional parameters such as unit cost and ordering  cost have been kept constant but holding cost is considered to vary. Two possibilities of variations in the holding cost function namely, a non-linear function of the length of time for which the item is held in stock and a non-linear function of the amount of on-hand inventory have been used in the models. The approximate optimal solution for the fuzzy cost functions in both these cases have been obtained and the effect of non-linearity in holding costs is studied with the help of a numerical example.

Keywords: Inventory Model, Deterioration, Holding Cost, Fuzzy Total Cost, Extension Principle.

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805 Cell Phone: A Vital Clue

Authors: Meenakshi Mahajan, Arun Sharma, Navendu Sharma

Abstract:

Increasing use of cell phone as a medium of human interaction is playing a vital role in solving riddles of crime as well. A young girl went missing from her home late in the evening in the month of August, 2008 when her enraged relatives and villagers physically assaulted and chased her fiancée who often frequented her home. Two years later, her mother lodged a complaint against the relatives and the villagers alleging that after abduction her daughter was either sold or killed as she had failed to trace her. On investigation, a rusted cell phone with partial visible IMEI number, clothes, bangles, human skeleton etc. recovered from abandoned well in the month of May, 2011 were examined in the lab. All hopes pinned on identity of cell phone, for only linking evidence to fix the scene of occurrence supported by call detail record (CDR) and to dispel doubts about mode of sudden disappearance or death as DNA technology did not help in establishing identity of the deceased. The conventional scientific methods were used without success and international mobile equipment identification number of the cell phone could be generated by using statistical analysis followed by online verification. 

Keywords: Call detail record, Luhn algorithm, stereomicroscope.

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804 Operating System Based Virtualization Models in Cloud Computing

Authors: Dev Ras Pandey, Bharat Mishra, S. K. Tripathi

Abstract:

Cloud computing is ready to transform the structure of businesses and learning through supplying the real-time applications and provide an immediate help for small to medium sized businesses. The ability to run a hypervisor inside a virtual machine is important feature of virtualization and it is called nested virtualization. In today’s growing field of information technology, many of the virtualization models are available, that provide a convenient approach to implement, but decision for a single model selection is difficult. This paper explains the applications of operating system based virtualization in cloud computing with an appropriate/suitable model with their different specifications and user’s requirements. In the present paper, most popular models are selected, and the selection was based on container and hypervisor based virtualization. Selected models were compared with a wide range of user’s requirements as number of CPUs, memory size, nested virtualization supports, live migration and commercial supports, etc. and we identified a most suitable model of virtualization.

Keywords: Virtualization, OS based virtualization, container and hypervisor based virtualization.

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803 2D Spherical Spaces for Face Relighting under Harsh Illumination

Authors: Amr Almaddah, Sadi Vural, Yasushi Mae, Kenichi Ohara, Tatsuo Arai

Abstract:

In this paper, we propose a robust face relighting technique by using spherical space properties. The proposed method is done for reducing the illumination effects on face recognition. Given a single 2D face image, we relight the face object by extracting the nine spherical harmonic bases and the face spherical illumination coefficients. First, an internal training illumination database is generated by computing face albedo and face normal from 2D images under different lighting conditions. Based on the generated database, we analyze the target face pixels and compare them with the training bootstrap by using pre-generated tiles. In this work, practical real time processing speed and small image size were considered when designing the framework. In contrast to other works, our technique requires no 3D face models for the training process and takes a single 2D image as an input. Experimental results on publicly available databases show that the proposed technique works well under severe lighting conditions with significant improvements on the face recognition rates.

Keywords: Face synthesis and recognition, Face illumination recovery, 2D spherical spaces, Vision for graphics.

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802 The Application of FSI Techniques in Modeling of Realist Pulmonary Systems

Authors: Abdurrahim Bolukbasi, Hassan Athari, Dogan Ciloglu

Abstract:

The modeling lung respiratory system that has complex anatomy and biophysics presents several challenges including tissue-driven flow patterns and wall motion. Also, the pulmonary lung system because of that they stretch and recoil with each breath, has not static walls and structures. The direct relationship between air flow and tissue motion in the lung structures naturally prefers an FSI simulation technique. Therefore, in order to toward the realistic simulation of pulmonary breathing mechanics the development of a coupled FSI computational model is an important step. A simple but physiologically relevant three-dimensional deep long geometry is designed and fluid-structure interaction (FSI) coupling technique is utilized for simulating the deformation of the lung parenchyma tissue that produces airflow fields. The real understanding of respiratory tissue system as a complex phenomenon have been investigated with respect to respiratory patterns, fluid dynamics and tissue viscoelasticity and tidal breathing period. 

Keywords: Lung deformation and mechanics, tissue mechanics, viscoelasticity, fluid-structure interactions, ANSYS.

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