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A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Rajeswari, P.
- Parameter Extraction of Planar Transmission Line Structure By ADI-FDTD Method
Abstract Views :132 |
PDF Views:2
Authors
Affiliations
1 Electronics and Communication Engineering Department, Velammal College of Engineering and Technology, Madurai, TamilNadu, IN
2 Velammal College of Engineering and Technology, Madurai, TamilNadu, IN
3 Electronics and Communication Engineering Department, Thiagarajar College of Engineering, Madurai, TamilNadu, IN
1 Electronics and Communication Engineering Department, Velammal College of Engineering and Technology, Madurai, TamilNadu, IN
2 Velammal College of Engineering and Technology, Madurai, TamilNadu, IN
3 Electronics and Communication Engineering Department, Thiagarajar College of Engineering, Madurai, TamilNadu, IN
Source
Wireless Communication, Vol 1, No 7 (2009), Pagination: 329-338Abstract
As very large scale integration (VLSI) technology shrinks to Deep Sub Micron (DSM) geometries, interconnect is becoming a limiting factor in determining circuit performance. High speed interconnect suffers from signal integrity effects like crosstalk, and propagation delay thereby degrading the entire system operation. In order to reduce the adverse signal integrity effects, if is necessary for the interconnect to have accurate physical dimensions. The interconnection and packaging related issues are main factors that determine the number of circuits that can be integrated in a chip as well as the chip performance. In this paper, it is proposed to simulate high speed interconnect structure using Alternate Direction Implicit Finite-Difference Time-Domain Method (ADI-FDTD) method.
Keywords
High Speed Interconnects, Microstripline, Signal Integrity, ADI-FDTD Method.
- Application of Echo State Neural Network in Identification of Microcalcification in Breast
Abstract Views :141 |
PDF Views:3
Authors
Affiliations
1 Mother Teresa Women’s University, Kodaikanal, IN
2 Institute of Technology, Haramaya University, ET
1 Mother Teresa Women’s University, Kodaikanal, IN
2 Institute of Technology, Haramaya University, ET
Source
Digital Image Processing, Vol 8, No 2 (2016), Pagination: 45-50Abstract
This paper presents a combination of wavelet with echo state neural network in identifying the microcalcification (MC) in a mammogram image. Mammogram image is decomposed using Daubauchi wavelet to 5 levels. Statistical features are extracted from the wavelet coefficients. Training of the ESNN/BPA is done using the features as inputs to the network along with a labeling of presence or non-presence of MC. The classification performance of ESNN is compared with back propagation algorithm.
Keywords
Microcalcification, Wavelet, Neural Network, Echo State Neural Network, Backpropagation Algorithm.- Analysis of High Speed VLSI Interconnects for Signal Integrity in Nanometer Range
Abstract Views :165 |
PDF Views:2
Authors
Affiliations
1 Department of ECE, Velammal College of Engineering and Technology, IN
2 Department of ECE, Mepco Schlenk Engineering College, IN
3 Velammal College of Engineering and Technology, IN
4 Department of ECE, Thiagarajar College of Engineering, IN
1 Department of ECE, Velammal College of Engineering and Technology, IN
2 Department of ECE, Mepco Schlenk Engineering College, IN
3 Velammal College of Engineering and Technology, IN
4 Department of ECE, Thiagarajar College of Engineering, IN
Source
Digital Signal Processing, Vol 2, No 7 (2010), Pagination: 65-69Abstract
The role of interconnects in integrated circuit performances has considerably increased with the technology scale down. Hence interconnect signal integrity becomes much more important, due to the smaller feature sizes and wire pitches. Devices with faster rise and fall times (typically tens of picoseconds) make global interconnects such as clock nets, bus signals, power/ground grids, more vulnerable to signal integrity (SI) degradations. Meanwhile, nanometer process technologies have increased manufacturing and lithography-based distortions of wires, dielectrics, and devices. Starting with the 130nm generation, the interconnect delay began to surpass the intrinsic gate delay. Since most of the delay comes from the IC's interconnect, the tool flow needs accurate interconnect delay information as early as possible and should allow continuous optimization in different stages to correctly reflect the real interconnect delay. The power consumption, performance, signals and power integrity are all affected by the chip interconnect. In addition, minimizing the signal integrity effects such as crosstalk, reflections loss, attenuation, insertion loss, etc., is also a major challenge in the nanometer design. Hence the signal integrity analysis of high-speed electronic designs at nanometer range requires a specific design methodology. In this paper, a single pass SI-aware design methodology is adopted; whose design flow involves three steps. First, the parameters (such as scattering, RLC, Transmission line and near field distributions), which characterize the transmission line structures as interconnect are extracted. Then the frequency range over which the different interconnect structures having minimum losses are found based on the extracted parameters. Next, the nanometer structure selected based on a standard design criterion, is analyzed for various signal integrity effects. Finally, suitable mitigation techniques are adopted so as to eliminate the SI effects.Keywords
Signal Integrity, Transmission Line Structures, SI Effects, Parameter Extraction.- Intelligent Voting Machine with a Finger Print Sensor and GSM Modem
Abstract Views :133 |
PDF Views:2
Authors
Affiliations
1 Department of Electronics and Communication, Dr. N. G. P. Institute of Technology, Coimbatore, IN
1 Department of Electronics and Communication, Dr. N. G. P. Institute of Technology, Coimbatore, IN
Source
Biometrics and Bioinformatics, Vol 5, No 8 (2013), Pagination: 291-294Abstract
In the present voting system the voter should show the voter identity card or some other photo identity cards for verification at the time of voting which raise confusions. This innovation is to overcome the problems which arise during verification process and to give an authentication to the voter. The system consists of finger print sensor and a GSM modem. Finger print sensor is used for recognition. Since no human in the universe have the same finger print, this also works for the identical twins. . A finger print sensor is an electronic device used to capture the digital image of finger print pattern, then it is compared with the existing database with the help of microcontroller and the details are displayed through the LCD display. A buzzer is provided to indicate the confirmation of verification. This Intelligent Voting Machine also gives protection from forgery like false fingerprint by sending a confirmation message to the voter’s mobile phone. This is done by a GSM modem which connected with the PC. Once the vote has been casted by the voter, the mobile number of the voter is traced and an acknowledgement is sent to the voter’s mobile.Keywords
Voting Machine, Finger Print Sensor, GSM Modem.- An EDTM Based Intrusion Prevention System
Abstract Views :250 |
PDF Views:2
Authors
Affiliations
1 Department of ECE, Hindustan College of Engineering and Technology, Coimbatore, IN
1 Department of ECE, Hindustan College of Engineering and Technology, Coimbatore, IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 8, No 5 (2016), Pagination: 186-190Abstract
Due to the wireless and resource-constraint nature of a sensor network makes it an ideal medium for malicious attackers to intrude the system during packet transmission. Thus, providing security is extremely important for the safe application of WSNs. In order to prevent the nodes from various attacks we propose an intrusion prevention system based on trust modeling and evaluation in EDTM. The proposed method will prevent the nodes from various attacks based on trust modeling and evaluation in EDTM. The EDTM can evaluate trustworthiness of sensor nodes more precisely and prevent the security breaches more effectively. According to the number of packets received by sensor nodes, direct trust and recommendation trust are selectively calculated. Then, communication trust, energy trust and data trust are considered during the calculation of direct trust. Furthermore, trust reliability and familiarity are defined to improve the accuracy of recommendation trust. A multi-hop network which means that the sensor nodes can only directly communication with the neighbor nodes within their communication range the packets exchanged between any two non-neighbor nodes are forwarded by other nodes. The forwarding node not only can just "pass" the packets from source nodes to destination nodes but also can process the information based on their own judgments. The simulation results are provided to compare that proposed model is efficient to use than NBBTE model.Keywords
Wireless Sensor Networks, Network Security, Efficient Distributed Trust Model.- Methodology of Echo State Neural Network To Diagnose Human Depression
Abstract Views :161 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Science, A. M. Jain College, Chennai - 600 114, Tamil Nadu, IN
2 Institute of Technology, Haramaya University, ET
3 Department of ECE, Institute of Technology, Haramaya University, ET
1 Department of Computer Science, A. M. Jain College, Chennai - 600 114, Tamil Nadu, IN
2 Institute of Technology, Haramaya University, ET
3 Department of ECE, Institute of Technology, Haramaya University, ET
Source
Indian Journal of Science and Technology, Vol 8, No 29 (2015), Pagination:Abstract
Depression is common in working personality due to high tension in the working environment. Symptoms can affect dayto- day life and can become very worrying. With true depression, there is a low mood and other symptoms each day for more than two weeks. Symptoms can also become rigorous enough to interfere with normal day-to-day activities. This paper suggests an Artificial Neural Network (ANN) algorithm approach for quicker learning of psychological depression data. Performance of neural network methods for estimating depression state with Echo State Neural Network (ESNN) is presented. Tentative data were collected from the patients with 21 input variables. One target output is used for training the ESNN. The training and testing patterns are made using the data as per Hamilton Rating Scale.The input patterns are pre-processed and presented to the input layer of ANN. The proposed method proves to be a capable system for diagnosis of depression.Keywords
Depression Data, ESNN, Hamilton Rating ScaleFull Text
- Implementation Of Single Data Rate Module In ONFI
Abstract Views :130 |
PDF Views:6
Authors
Source
International Journal of Innovative Research and Development, Vol 2, No 5 (2013), Pagination:Abstract
Huge amount of Data is generated by Different Modules by different Processes ,as a requirement of operation data or information has to sent from one module to another module which are usually dissimilar ,this can be achieved with a help of interface between two modules .
The Interface plays an important role in transferring a data between the host (Memory controller) and the device (Memory Unit). Different Devices have Different Interfaces and for NAND Flash ONFI is standard interface which helps in transferring the data between the host (Controller) and the device (Card) in a most accurate way and at higher speed than compared to any other interfaces. ONFI provides three most efficient way of data transferring methods i.e., Single Data rate (SDR),NV-Double Data Rate (NV-DDR), NV-Double Data Rate -2 (NV-DDR2).
Keywords
NAND FLASH, ONFI, SDR, STATE MACHINESFull Text
- Assessment of Combination of Biocontrol Strains on the Fusaric Acid and other Toxins Secreted from Fusarium oxysporum by HPLC-MS/MS Method and Differential Expression Profiling in Arachis hypogaea L
Abstract Views :221 |
PDF Views:0
Authors
Affiliations
1 Department of Botany, University of Delhi, Delhi - 110007, IN
1 Department of Botany, University of Delhi, Delhi - 110007, IN
Source
Toxicology International (Formerly Indian Journal of Toxicology), Vol 26, No 3&4 (2019), Pagination: 89–97Abstract
The ability of Fusarium oxysporum (Schlecht Emend. Snyder and Hansen) in Arachis hypogaea L to produce mycotoxins i.e. Fusaric Acid (FA), Deoxynivalenol (DON), Nivalenol (NIV), Zearalenone, (ZEN), Aflatoxin B1, B2, G1 and G2 in Arachis hypogaea L. leaves in vivo was evaluated in relation to combination of three biocontrol agents, Trichoderma viride + Pseudomonas fluorescens, Trichoderma harzianum + Pseudomonas fluorescens, Trichoderma viride + Trichoderma harzianum. Among the toxins tested, only FA was identified in plants infected with Fusarium oxysporum by LC-MS/MS and quantified using HPLC (4 μg/Kg) Fusaric acid, Deoxynivalenol, Nivalenol, Zearalenone, Aflatoxin B1, B2, G1 and G2 toxins were not detected in plants treated with the combinations of biocontrol agents. The results demonstrate that this procedure is suitable for simultaneous determination of mycotoxins in Fusarium oxysporum of groundnut and the toxin (FA) identified which contributes to the pathogenicity of the fungus during infection. Further differential expression of genes of three leaf samples of control, infected with Fusarium oxysporum and treated leaf sample using combinations of biocontrol agents (Trichoderma viride + Pseudomonas fluorescens ) depicted 5559 genes in control specific, 4316 genes as infected specific and 4264 genes are treated specific. In treated samples 1265 up and 850 down regulation genes were depicted where as in infected sample 605 up and 509 down regulatory genes were depicted. Gene oncology and pathways were found from Uniprot data base. These findings provide new insights into the genetic and biochemical processes required for FA production of Fusarium oxysporum infecting Arachis hypogaea L.Keywords
Arachis Hypogaea L, Fusarium Oxysporum, HPLC-MS/MS Method, RNA Transcriptome Sequencing.References
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