bluuebunny/crossref_metadata_2025_split huggingface dataset:
Performance Evaluation of Efficient and Reliable Routing Protocol Algorithm
Authors: Sathyasri B. , Ganesh E.N. , Senthil Kumar P. , Rathna S. , Jaishree Bai R. , Nalini G. 
Published: November 2017

Abstract
Fixed-power wireless sensor networks are prevalent and cost-effective. However, they face mote failures, RF interference from environmental noise and energy constraints. Routing protocols for such networks must overcome these problems to achieve reliability, energy efficiency and scalability in message delivery. Achievement of these requirements, however, poses conflicting demands. In this work, we propose an efficient and reliable routing protocol (EAR) that achieves reliable and scalable performance with minimal compromise of energy efficiency. The routing design of EAR is based on four parameters expected path length and a weighted combination of distance traversed, energy levels and link transmission success history, to dynamically determine and maintain the best routes. Simulation experiments of EAR with four existing protocols demonstrate that a design based on a combination of routing parameters exhibits collectively better performance than protocols based on just hop-count and energy or those using flooding.
Cluster Head Election Mechanism-Based on Fuzzy Logic (Chef) with TDMA in WSN
Authors: Vijayalakshmi G. , Anto Bennet M. , Shenbagavalli P. , Vijayalakshmi M. , Saranya S. 
Published: November 2017

Abstract
Wireless sensor networks (WSN) are being used for huge range of applications where the traditional infrastructure based network is mostly infeasible. The most challenging aspect of WSN is that they are energy resource-constrained and that energy cannot be replenish. the wireless sensor network of power limited sensing devices called sensor deployed in a region to sense various types physical information from the environment, when these sensors sense and transmit data to other sensors present in the network, even the cluster head is elected according to check their residual energy considerable amount of energy will drain automatically to overcome this drawback by considering the protocol a fuzzy logic approach is used to elect the cluster head based on three descriptors-energy, centrality & distance and second CH is elected according to TDMA to overcome the data lost during energy drain occur in the CH .NS-2 simulation shows that proposed protocol provides higher energy efficiency. This paper proposes the mechanism or device is capable of utilizing its own system of control simply called as self-configurable clustering mechanism to detect the disordered CHs and replace them with other nodes. And results have been derived from simulator ns-2 to show the better performance.
An Intelligence Super Mart Billling System
Authors: Mekala S. , Thanagaraj M. , Chandranath M. , Vasanta Kumaran K.K. 
Published: November 2017

Abstract
Currently embedded systems be mainly based on microcontroller’s i.e. CPUs in the company of included reminiscence the same as well as tangential interface except ordinary microprocessors by means of external chips for memory and peripheral interface circuits are common, especially in technology may not only be useful for streamlining category and supply chains. Nowadays it is rare to see people getting keen in online shopping through e-commerce websites but still the shopping centers are popular. We come across many types of carts used for shopping in malls and shopping center. The major purpose of this effort is reducing delays in foremost supermarkets or shopping center via income of an electronic smart cart method which will introduce an cognitive approach to billing system during RFID technology. Zigbee is base scheduled an IEEE 802.15 ordinary. Zigbee devices a group of pass on data more than longer space by transient data through transitional devices to make more distances ones, create a interconnect network. Purchasing product during a RFID reader going on shopping cart, suggest while product information resolve be stored into EEPROM close to it and EEPROM data spirit send in the direction of central billing system throughout Zigbee module. The anticipated method will survive helpful for avoiding queues in shopping malls for billing. Hence the shopping becomes easy and enjoyable.
Computation of Field Programmable Cyclic Redundancy Checks Circuit Architecture
Authors: Anto Bennet M. , Ravali Lakshmi , Sughapriya T.R. , Jenitta J. , Vaishnavi K. , Alphonse Priyanka Paree 
Published: November 2017

Abstract
In this work we are going to simulate a field programmable cyclic redundancy check circuit architecture. The transmitted data or stored data must be free from error. The increased use of error correction techniques by digital communications designers has created a demand for tools to evaluate and exercise error correction coding approaches before they are committed to expensive ASICs or firmware. Cyclic redundancy check is an error detection method but it can be used only for a specific application. A field programmable circuit is one which enables a wide range of polynomial width and input port width to be used with in the same circuit. The parameters are reprogrammable and it is fully flexible. The circuit also consists of an embedded configuration controller that reduces the programming time and complexity. The hardware cost is reduced and the line speed is increased. The primary tool used is modelsim 6.1a.
A Multi-Keyword Ranked Search Scheme Over Encrypted Based on Hierarchical Clustering Index
Authors: Indhuja A. , Udaya shankar T.P. , Balajee Mastan Vali Shaik RM. , Sujatha P 
Published: November 2017

Abstract
A Secure and Dynamic Multi-keyword Ranked Search Scheme over Encrypted Cloud Data Due to the increasing popularity of cloud computing, more and more data owners are motivated to outsource their data to cloud servers for great convenience and reduced cost in data management. In this project, present a secure multi-keyword ranked search scheme over encrypted cloud data, which simultaneously supports dynamic update operations like deletion and insertion of documents. Specifically, the vector space model and the widely-used TFIDF model are combined in the index construction and query generation. The proposed hierarchical approach clusters the documents based on the minimum relevance threshold, and then partitions the resulting clusters into sub-clusters until the constraint on the maximum size of cluster is reached. In the search phase, this approach can reach a linear computational complexity against an exponential size increase of document collection. In order to verify the authenticity of search results, a structure called minimum hash sub-tree is designed in this paper. Due to the use of our special tree-based index structure, the proposed scheme can achieve sub-linear search time and deal with the deletion and insertion of documents flexibly. Extensive experiments are conducted to demonstrate the efficiency of the proposed scheme.
Data Mining with Big Data Revolution Hybrid
Authors: Elankavi R. , Kalaiprasath R. , Udayakumar R. 
Published: November 2017

Abstract
Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data are now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. This paper presents a HACE theorem that characterizes the features of the Big Data revolution, and proposes a Big Data processing model, from the data mining perspective. This data-driven model involves demand-driven aggregation of information sources, mining and analysis, user interest modeling, and security and privacy considerations. We analyze the challenging issues in the data-driven model and also in the Big Data revolution.
Porous Silicon Sensors- Elusive and Erudite
Authors: Saha H. 
Published: November 2017

Abstract
Porous Silicon Sensors have been fabricated and tested successfully over the last few years as humidity sensors, vapour sensors, gas sensors, piezoresistive pressure sensors and bio- sensors. In each case it has displayed remarkably sensitivity, relatively low temperature operation and ease of fabrication. Brief description of fabrication and properties of all these types of different sensors is reported in this paper. The barriers of porous silicon like contact, non- uniformity, instability etc. are also discussed.
Measuring Flow Parameters Of Particulate And Powdery Solids In Industrial Transportation Processes
Authors: Fuchs A. , Graz H. Zangl 
Published: November 2017

Abstract
This paper provides an overview of existing technologies to measure flow parameters, such as material velocity and material concentration, in industrial transportation processes of particulate and powdery solids with a focus on pneumatic conveying. Restrictions, advantages and drawbacks of state of the art measurement principles are discussed. We show that capacitance-based sensing with suitable electrode topology allows for non-invasive, low-cost determination of flow parameters. Two industrial applications for material transportation - by means of pneumatic conveying and of screw conveyors - are presented
Model Order Selection Criterion For Monitoring Haemoglobin Status In Dengue Patients Using Armax Model
Authors: Rahim H. Abdul , Ibrahim F. , Taib M. N. , Rahim R. Abdul , Sam Y.Mad 
Published: November 2017

Abstract
This paper describes the development of linear autoregressive moving average with exogenous input (ARMAX) models to monitor the progression of dengue infection based on hemoglobin status. Three differents ARMAX model order selection criteria namely Final Prediction Error (FPE), Akaike’s Information Criteria (AIC) and Lipschitz number have been evaluated and analyzed. The results showed that Lipschitz number has better accuracy compared to FPE and AIC. Finally based on Lipschitz number, appropriate model orders have been selected to monitor the progression of dengue patients based on hemoglobin status. Further work is to apply this appropriate model orders to nonlinear Autoregressive (NARMAX) model.
Guidance-Based On-Line Motion Planning For Autonomous Highway Overtaking
Authors: Ghumman Usman , Kunwar Faraz , Benhabib Beno 
Published: November 2017

Abstract
In the context of intelligent transportation, this paper presents a novel on-line trajectorygeneration method for autonomous lane changing. The proposed scheme is guidance based, realtime applicable, and ensures safety and passenger ride comfort. Based on the principles of Rendezvous Guidance, the passing vehicle is guided in real-time to match the position and velocity of a shadow target (i.e., rendezvous with) during the overtaking manoeuvre. The shadow target’s position and velocity are generated based on real-time sensory information gathered about the slower vehicle ahead of the passing vehicle as well as other vehicles which may be travelling in the passing lane. Namely, the guidance principle is also used to prevent any potential collision with these obstacle vehicles. The proposed method can be used as a fully autonomous system or simply as a driver-assistance tool. Extensive simulations and experiments, some of which are presented herein, clearly demonstrate the tangible efficiency of the proposed method.
A Robot Succeeds in 100% Mirror Image Cognition
Authors: Takeno Junichi 
Published: November 2017

Abstract
Humans are capable of identifying their own image when reflected in a mirror. This mechanism is a mystery that has never been solved. I created a program that achieved such awareness on a robot and conducted three experiments. The first was an experiment on a self robot that imitates its own self-image reflected in a mirror. The second experiment had a robot imitating another robot of the same type which was made to perform the same behavior. The last was an experiment using two robots of the same type and the same functions to imitate each other. In these experiments, the program calculated the coincidence rate of behavior between the self robot and the other robot. I found that compared with the case in which the robot performed a behavior according to its own judgment, the coincidence rate was always higher in the case of the mirror image. At this time, when the target moved according to its own judgment in the second experiment, this can be considered as a part of the self, similar to the use of “human hands and feet.” From this result, the mirror image can be judged to “exist closer to the self than a part of the self” and can in fact be considered a “self.” I thought that the result of these experiments indicated that mirror image cognition of the robot succeeded completely and that this would be the “first example toward explaining physically the mirror image cognition capability of humans.” This paper details logical and physical explanations for achieving the results, and in addition, presents several considerations and prospects derived from the experiment results.
Single Sh-Saw Sensor as a Distributed Sensor Array for Liquids Recognition
Authors: Kryshtal R.G. , Medved A.V. 
Published: November 2017

Abstract
Basic possibility to use single-channel shear-horizontal surface acoustic waves sensor constructed as a delay line on multilayered structure with 36 YX LiTaO3 substrate for liquids recognition has been proposed. The changes under analytes influence of the sensor pulse responses obtained by transformation to time domain of one of the S-parameters measured in frequency domain have been used as sensor responses. Examples of responses to some liquid analytes have been demonstrated for a sensor based on LiTaO3 – SiO2 – molecularly imprinted polymer layered structure. Qualitative explanation of the result is given by treating such a sensor as a distributed sensor array.
Performance Analysis of Patient Specific Elman-Chaotic Optimization Model for Fuzzy Based Epilepsy Risk Level Classification from Eeg Signals
Authors: HariKumar R. , Vijayakumar T. 
Published: November 2017

Abstract
This paper aims to analyze the optimization of Epilepsy risk levels from EEG signals using Fuzzy based Elman-Chaotic Optimization. The EEG (Electroencephalogram) signals of twenty patients are collected from Sri Ramakrishna Hospitals at Coimbatore. The raw EEG signals are sampled and various parameters like energy, energy, variance, peaks, sharp and spike waves, duration, events and covariance. The fuzzy techniques are applied as a first level classifier to classify the risk levels of epilepsy by converting the EEG signal parameters in to code patterns by fuzzy systems. Elman-Chaotic optimization is identified as post classifiers on the classified data to obtain the optimized risk level that characterizes the patient’s epilepsy risk level. This classification provides a better way of treating the epileptic patients. This project aims to safeguard a patient’s life when critical situation occurs. Future scope is to design an embedded system which collects the raw EEG signals from the brain and directly gives the level of epilepsy. It will make the neural surgeons to give appropriate remedial measures.
Sensors for Monitoring Components, Systems and Processes
Authors: Jayakumar T. , Rao C. Babu , Philip John , Mukhopadhyay C.K. , Jayapandian J. , Pandian C. 
Published: November 2017

Abstract
The application of sensors encompasses many sectors of industry. In this paper, we outline different sensors – Raman distributed temperature sensor, sensor based on nano ferrofluids and MEMS based ultrasonic sensors. The development and application of these sensors for monitoring performance of systems and processes are discussed. Further, we also discuss the application of acoustic emission and infrared thermal imaging for process monitoring.
Robust Fusion Algorithms for Linear Dynamic System with Uncertainty
Authors: Beak Inhea , Lee Seokhyoung , Shin Vladimir 
Published: November 2017

Abstract
In this paper, two robust fusion algorithms for a linear system with observation uncertainty are proposed. The first algorithm is based on the classical median function and the second one uses relative distances between local estimates and their median value. In the view of estimation accuracy, the proposed fusion algorithms can be robust against uncertainty measurements since median can avoid extremely big or small values. This fact is verified from comparative analysis using numerical examples.
Experimental Study on Vibration Control of Shape Memory Alloy Actuated Flexible Beam
Authors: Dhanalakshmi K. , Avinash Aditya , Umapathy M. , Marimuthu M. 
Published: November 2017

Abstract
This paper describes the development of an experimental platform which analyzes and controls the vibration of a Shape Memory Alloy (SMA) actuated and piezo sensed flexible beam. The vibration is controlled using the interactive force of a pair of almost identical SMA wires connected in an antagonistic manner, arranged in parallel to and on both sides of the cantilever beam structure. Data acquisition and control are implemented using a PCI data acquisition card and LabVIEW. Standard P, PI, ON-OFF controllers have been used to control the first mode of vibration of the flexible beam. Experimental results are used to demonstrate the effectiveness of the controllers designed and usefulness of the proposed test platform by exciting the structure at resonance.
The Effect of Catalytic Metal Contact on Methane Sensing Performance of Nanoporous ZnO -Si Heterojunction
Authors: Mishra G. P. , Sengupta A. , Maji S. , Sarkar S. K. , Bhattacharyya P. 
Published: November 2017

Abstract
A sol-gel derived ZnO-p-Si heterojunction structure were fabricated and investigated as a potential methane sensor. Three configurations with different contacts (Pd-Ag contact both on ZnO and Si / Pd-Ag on ZnO side and Au on Si / and Au on both sides of the junction) were fabricated in order to study the impact of the catalytic contact on the methane sensing properties. Structural characterization with high resolution FESEM and EDX study revealed the synthesis of highly crystalline ZnO thin film with particle size ~40nm. The catalytic contact metal used was also of nanoporous nature as was revealed from FESEM were as the noncatalyic metal showed flake like texture. The heterojunctions were investigated at different operating temperatures (50°C-300°C) and at different operating voltages (1-5V) for varying concentrations of methane (0.1%, 0.5% and 1.0%). It was observed that the device with Pd-Ag (70%) contacts on both sides offered shorter response time (~28sec) and much higher response magnitude (~63%) compared to the sensor with Au contact both sides (response time ~47 sec and response magnitude ~ 19%). It is further revealed that the sensor performance with catalytic contact only to ZnO (and Au to Si) is almost the same as that of sensor having catalytic contact on both sides, emphasizing the fact that using catalytic contact to the sensing layer only modulates the sensor characteristics. The diode parameters like ideality factor, saturation current and the change in barrier height (upon exposure to methane) were also calculated for getting the insight of the sensing mechanism and were found to be in well agreement with the experimental results.
Hepa Filter Material Load Detection Using a Microwave Cavity Sensor
Authors: Mason A. , Wylie S. , Thomas A. , Keele H. , Shaw A. , Al-Shamma’a A.I. 
Published: November 2017

Abstract
This paper presents a novel microwave cavity sensor application for the detection of HEPA filter particulate loading. The sensor resonates at 3.435GHz and 8.570GHz when empty, where the TM010 and TM020 modes dominate respectively. Experimental results show that the resonant frequency of the sensor shifts significantly when filters of different particulate loadings are presented to it. This is a significant finding, and means that the sensor could present an effective solution for determining the loading of periodic use HEPA filters (e.g. those used in personal respirators), which are often disposed of unnecessarily.
A Cooperative Object Tracking System with Fuzzy-Based Adaptive Camera Selection
Authors: Morioka Kazuyuki , Kovacs Szilveszter , Lee Joo-Ho , Korondi Peter 
Published: November 2017

Abstract
The intelligent environments, built upon many distributed sensors, are promising technology for ubiquitous interaction between robots and human beings. Especially, it is important to track target objects and get the positional information of them in such environments. This paper focuses on adapting camera selection for target tracking in multi-camera system. In this paper, a fuzzy automaton based camera selection method is introduced. In the proposed method, the camera selection decision is driven by fuzzy automaton based on the previously selected camera (previous camera state) and the tracking level of the object in each available camera. Simulations for evaluation of the proposed method and comparison with the previous method are presented. The results show that the proposed method is efficient for adaptive camera selection in multi-camera environment and helps easy construction of multi-camera placement. An actual multi-camera system with the proposed camera selection method was developed for checking tracking performance in the real environment. Experiments in the constructed system show that the proposed method suits well the camera selection task for tracking a moving object in the real intelligent environment.
Analysis of Tactile Slippage Control Algorithm for Robotic Hand Performing Grasp-Move-Twist Motions
Authors: Yussof Hanafiah , Wada Jiro , Ohka Masahiro 
Published: November 2017

Abstract
This paper presents an analysis result of grasp-move-and-twist motions of robotic hands equipped with optical three-axis tactile sensor to evaluate performance of a new control algorithm based on tactile slippage sensation. The optical three-axis tactile sensor is capable of defining normal and shear forces simultaneously. The proposed algorithm consists of robot arm and hand controls based on parameters of normal and shear force, and slippage detection. To improve performance during grasp, move and twist motions, we present analysis of slippage direction and classify the control algorithm in two phases: grasp-move-release and grasp-twist. We present detailed explanation of the control algorithm based on the existing robot arm control system. The experiment is conducted using a bottle cap, and the analysis results show that the slippage control parameters enhanced performance of grasp control in simultaneous robot tasks. Experimental results revealed good performance of the proposed control algorithm to accomplish the proposed grasp-move-and-twist motions.
Self-Organizing Urban Traffic Control Architecture With Swarm-Self Organizing Map in Jakarta: Signal Control System and Simulator
Authors: Jatmiko W. , Azurat A. , Herry  , Wibowo A. , Marihot H. , Wicaksana M. , Takagawa I. , Sekiyama K. , Fukuda T. 
Published: November 2017

Abstract
Urban traffic control is the main factor that contributes to traffic jam. Approach in distributed Urban traffic control has been developed in several research, but the coordinating controller factor is basically a quite complicated task to tackle, because between intersection have dependency, so required a method of distributed control system capable for synchronizing between intersections. In this paper we present architecture of decentralized self-organizing traffic control with swarm-self organizing map in real situation even on non-structure intersections like in Jakarta (Indonesia). Based on the proposed architecture we have been implemented Traffic Signal Control System for controlling traffic lights in which the coordination between the intersections is implemented using distributed swarm self-organizing map. Traffic Signal Control System were tested in a simulated real-road scenario of Jakarta. By means of the computer simulation, the application of distributed swarm signal self-organizing control is proved effective in urban traffic.