Edusat Satellite is the satellite dedicated forfulfillment the needs of education and its effective usage requiresa network comprising Hub, Teaching End (Studio) andReceiving Terminals. The present study is related with Edusatnetworkof Madhya Pradesh Bhoj (Open) University, whichincludes Hub dedicated for higher and distance education, Studioand 40 Satellite Interactive Terminals with Edusat-networkprovided by Indian Space Research Organization (ISRO). TheseSITs have been installed in urban, rural and tribal areas. Detailstudy of equipments of hub, studio and receiving terminals wastaken up. Target group was chosen and most easy and suitableway of virtual class was identified. Various factors affectingquality of audio/video were drawn from the study andcontent/presentation of video lectures were analysed. Recordedvideo lectures and live lectures were telecasted for 177 workingdays and observations related to BER (Bit Error Rate)correlating problems encountered during operation of terminals,audio-visual quality of lectures, skill and response of operatorswere made. We aimed at identifying the scope of enhancement inaudio-video quality of the material telecasted through Edusat.The study is based on the network which has been created mainlyfor the students of rural and tribal areas. On the basis ofobservations and BER data collected from hub, the present studymakes findings and suggests those possibilities which canenhance the audio-video quality of the telecast without any majorchange in satellite’s band width and hub, and with minimumincrease in cost and expenditure.

Edusat- Satellite dedicated for education --- SITSatellite Interactive terminals --- BER- Bit Error Rate --- RCSTReturn Channel Satellite Terminal --- LNB- Low Noise Block down converter --- GCU- (Gateway Cannel Unit) --- Gramsat- Satellite based project for villages --- TDCC- Training and Development Communication Channel.

Along with the increase in the advancement oftechnology in movie industry over internet, there is also anincrease in the movie piracy via internet which affects factors likeeconomy and repudiation of movie industry. Internet movie piracyis the most common means for pirates as well as downloader’s tobreak copyright laws by anonymous illegal uploads/downloads. Inthis paper we proposed an automated internet movie piracydetection mechanism based on audio fingerprint, whichimplements two famous algorithms, one is Mel-FrequencyCepstral Coefficients (MFCC) for feature extraction and the otheris Vector Quantization (VQ) for classification. Our trained systeminitially looks for the sites which offer illegitimate copies of moviesand if there is any suspicion based on a particular movie which issimilar to the database of copyrighted movies that are registeredwith our trained system, it simply compares the fingerprints thatare generated by implementing the above specified algorithms forboth the trained and suspected movies. We collected various audiosamples of different movies and we also extracted audio samplesof pirated movies via internet with and without noises and trainedand tested with our system. Finally, our system rendered efficientresults with few error rates. We collected 52 audio samples withoutnoise and 48 samples with noise and the resulted successclassification is 96% and 92% respectively.

Classification --- Code Book --- Movie Piracy --- MFCC --- VQ.

In this paper, an optimal fuzzy supervisorcontroller is developed to improve the performance of activesuspension system. Fuzzy logic is used to tune each parameter ofPID Controller and input membership function of fuzzycontroller optimized by Discrete Action ReinforcementLearning Automata (DARLA) technique. Through simulation inMATLAB, it is shown that the performance of active suspensionsystem has improved significantly compare to conventional PIDcontroller which is tuned by Zigler- Nichols method.

Active suspension system --- Discrete Action Reinforcement Learning Automata (DARLA) --- Fuzzy supervisor --- PID controller

Popularity and evolution of mobile devices like laptops, mobile phones and Personal Digital Assistants (P.D.A.), and the evolution of fast mobile networks in the last decade, have made it possible to increase the complexity of mobile applications and services provided to end-users. It is also a spectacular growth in multimedia communication especially via the World Wide Web. This paper explore some of the current technology of mobile devices, mobile networks and multimedia systems, and is based on the exploration outline some issues for design and development of mobile multimedia systems in 4G Mobile Communication System. Fourth-generation mobile communication systems will combine standardized streaming with a range of unique services to provide high-quality content (Multimedia) that meets the specific needs of the rapidly growing mobile market. By offering higher data-transmission rates up to 20 Mbps more than 3G for wide-area coverage and local-area coverage, 4G systems will be able to provide high quality streamed content to the rapidly growing mobile market.

4G --- Streaming --- Code Division Multiple Access C.D.M.A. --- Global System For Mobile (G.S.M.)

A coding and decoding scheme for energy-basedtarget localization in wireless sensor networks (WSNs) ispresented in this paper. This scheme can improve targetlocalziation performance when WSNs are deployed in noisyenvironments. Simulation results showed that the energy-basedtarget localization method using this coding and decoding schemecould produce better localization performance than theenergy-based target localziation method which did not use thisscheme. Moreover, the root mean square (RMS) errors given bythe proposed method were close to the Cramer-Rao lower bound(CRLB).

Cramer-Rao lower bound --- maximum likelihood estimation --- quantization --- Wireless sensor networks.

The effect of fading and interference effects can be combated with equalizer for a MIMO system. MIMO systems exploit the multipath propagation in rich scattering environment using multiple transmit and receive antennas to increase the capacity of a link. The matrix channel plays a pivotal role in the throughput of a MIMO link since the modulation, data rate, power allocation and antenna weights are dependent on the channel gain. In this case independent, identically distributed (i.i.d.) Rayleigh fading MIMO channel with m-transmit and n-receive antennas has been taken, the diversity order is almost same i.e. m x n for ZF, MRC and MMSE-filtering-based decoding. The error probability analysis also yields a design criterion for optimizing transmitt power allocations. This paper analyses the performance of MMSE, ZF equalizer and MRC based receiver for MIMO wireless channel .The BER characteristics for the various transmitting and receiving antennas simulated in MATLAB tool box and many advantages and disadvantages the system is described. The simulation is carried out in signal processing lab, which shows that the MRC equalizer based receiver is a good choice for removing some ISI and minimizes the total noise power. The results show that the BER decreases as the m x n antenna configurations is increased.

Equalizer --- Bit error rate --- Signal to noise ratio (Eb/N0) --- transmitting antenna --- receiving antenna

Classification in data mining has gained a lot of importance in literature and it has a great deal of application areas from medicine to astronomy, from banking to text classification.. It can be described as supervised learning algorithm as it assigns class labels to data objects based on the relationship between the data items with a pre-defined class label. The classification techniques are help to learn a model from a set of training data and to classify a test data well into one of the classes. This research is related to the study of the existing classification algorithm and their comparative in terms of speed, accuracy, scalability and other issues which in turn would help other researchers in studying the existing algorithms as well as developing innovative algorithms for applications or requirements which are not available.

classification --- decision tree --- nearest neighbour --- neural network --- SVM --- Supervised learning

This work provides the construction of Genetic Algorithm based Neural Network for parameter estimation of Fast Breeder Test Reactor (FBTR) Subsystem. The parameter estimated here is temperature of Intermediate Heat Exchanger of Fast Breeder Test Reactor. Genetic Algorithm based Neural Network is a global search algorithm having less probability of being trapped in local minimum problem as compared to Standard Back Propagation algorithm which is a local search algorithm. The various development stages of Genetic Algorithm based Neural Network such as the preparation of the training set, weight extraction from the genetic population, training of the neural network and validation phase etc have been described in detail.

Genetic Algorithm based Neural Network --- Fast Breeder Test Reactor --- Intermediate Heat Exchanger --- Multi layer Perceptron

Effective implementation of KnowledgeManagement is considered as an increasingly important toolfacilitating organisations to gain a competitive advantage.Educational Institutes are not far behind, they have also realisedthat Knowledge is now a driving force for organisational changeand innovation, which are a survival tool in today’s dynamicenvironment. As a result, Educational Institutions are exercisingradical changes and are at varying stages of planning andimplementing knowledge-based strategies in effort to improvetheir competitiveness, productivity, organisational effectivenessand better service to the nation by producing skilled leaders fortomorrow. However, KM initiatives are both expensive and riskypropositions. Financial resources put a constraint on what can beexpended on knowledge activities. This necessitates a re-look atknowledge management initiatives in Educational Institutions,which can be considered to be knowledge intensive organisation.This paper presents a framework which can be adopted forbuilding a Knowledge Management platform in HigherEducation Institutions. It lists the steps to implement a KMsolution/portal and discusses the sub parts of the portal, whichcan cater to the needs of the stakeholders of an AcademicInstitution. It also discusses the factors influencing the success ofknowledge management initiatives in a Higher EducationInstitution, which help them to distinguish themselves in theacademic market place.

Higher Education Institutions (HEI) --- Knowledge Management (KM) --- Portal.

In the present paper, a theoretical investigation on energy conservation and their effect on green house gases will be discussed. The result shows the reduction of thermal (roof) load if the space between roof and false ceiling is ventilated by outside air, a certain portion of the roof load may be carried away by this air due to convective heat transfer between roof and air. Reduction in thermal load leads to reductions in the amount of environmental loads. The saving is determined between 9am to 6 pm. The other parameters are air velocities of 1.25, 1.75 and2.25 m/s; roof length in the direction flow as 10, 20 and 30m; inclination of roof at 00,300 and 450 at a location of 290 latitude.

roof heat load --- environmental loads.

Digital watermarking techniques have beenproposed for handling applications like Copy protection, Contentauthentication of digital images. Any tiny change to the contentis not acceptable in images especially when they are used to storesecret information in the form of an invisible digital watermark.To address this present paper proposes a simple block basedcontent checksum watermarking (BCCW) method for imageauthentication and tamper localization. The proposed BCCW is ahierarchical and block based method. In BCCW the image isdivided into sub blocks of size 4×4. Then a hierarchicalrelationship is established by dividing each 4×4 as a set of four2×2 blocks. A Checksum of 8 bits is computed from pixels of 4×4block and the checksum is placed intelligently on the selected 2×2block pixels. In the proposed BCCW if any block or even a pixelis tampered then the block checksum does not match with theextracted bit sequence. The main advantage of the BCCWscheme is, it can identify effectively in which blocks thetampering has occurred. The experimental results show that thequality of the embedded image is very high, and the positions ofthe tampered parts are located correctly. The proposed BCCWmethod is compared with several other methods.

Block Based --- Content Checksum --- Image Authentication

The access control models like DAC, MAC, RBAC,TBAC, TMAC, DomBAC, etc. mainly model security policies forinformation systems having a centralized governance. Moreover,they only specify permissions and prohibitions, sometimesobligations. Besides that, they generally do not allow theestablishment of activated, dynamic and adapted rules. However,such rules are highly useful in a cloud environment where ITgovernance is shared, used or managed by different entities. Inthis paper, we propose a new model for specifying such securitypolicies. This model called Trust Organization Based AccessControl (TOrBAC) which relies on the use of a recursive formulafor calculating a confidence index. We also formalize our workusing a language based on first order logic and we apply it to acloud computing (CC) related use case.

Cloud computing --- Access model control --- security

Mining data streams for knowledge discovery hasbeen used in many applications like web click stream mining,network traffic monitoring, network intrusion detection, anddynamic tracing of financial transactions. In this paper, byanalyzing characteristics of date stream, we propose an efficientalgorithm weighted frequent pattern (WFP) mining that discoversmore knowledge compared to traditional frequent pattern mining.The existing algorithms cannot apply for stream of data becausethose algorithms require multiple database scans. This techniqueuses a single database scan for mining stream of data. Ourtechnique is efficient for web applications for mining web recordsand also discovers valuable knowledge compared to othertechniques.

Data stream --- weight --- weighted frequent pattern mining

Trait theory is a major approach to the study ofhuman personality. Personality is the branch of psychologywhich is concerned with providing a systematic account of theways by which we can differentiate one-another. Individualsdiffer from one another in a variety of ways: their anatomicaland physiognomic characteristics, their personal appearance,grooming, manner of dress, their social backgrounds, roles andother demographic characteristics, their effect on others or socialstimulus value and their temporary states, moods, attitudes andactivities at any given moment in time.. In this paper we havedesigned a system that takes text input and returns the author’strait accordingly. Since human tendencies are largely dependenton environmental and situational consistencies, we haveconsidered five different traits in our identification. These areHigh Extrovert, Low Extrovert, High Introvert, Low Introvertand Ambivert. Our algorithm refines the author’s text undereight different properties. The text undergoes POS tagger whereeach word is assigned a tag. After analyzing the tag we generateFeature Vector matrix (FVM), we use this FVM for our analysisas well as for the classification. We have applied our proposedalgorithm on different 280 files. These files are also annotated byhuman. We compare the result got from human annotation andproposed algorithm and we found that the accuracy of ouralgorithm is 84.26%.

FVM --- POS --- SVM --- Trait Theory.

Authenticating the user based on behavior basedbiometrics is more reliable than the more traditional means ofpassword authentication .Since Biometric identification is uniqueand slow intrusive .Biometric systems provide the solution toensure that the rendered services are accessed only by alegitimate user and no one else. Biometric systems identify usersbased on behavioral or physiological characteristics. Theadvantages of such systems over traditional authenticationmethods, such as passwords and IDs, are well known; hence,biometric systems are gradually gaining ground in terms ofusage. As security is the main concern in using cloud computingfused biometric authentication technique which can be used assingle sign on so that the services can be more secure andreliable ,and that biometric authentication is provided as aservice by a cloud provider.

Biometrics --- cloud --- authentication --- Single Sign On --- fused

The multi-layer advanced high-performance bus (ML-AHB) matrix proposed by ARM is an excellent architecture for applying embedded systems with low power. However, there is one clock cycle delay for each master in the ML-AHB Bus Matrix of the advanced microcontroller bus architecture (AMBA) design kit (ADK) whenever a master starts new transactions or changes the slave layers. The total area and power consumption of the ML-AHB Bus Matrix of an ADK is increases due to the heavy input stages. Due to heavy input stage the cost of arbitration scheme becomes high. The computation time of each master is predictable, but it is not easy to foresee the data transfer time since the on-chip bus is usually shared by several masters. Previous works solved this issue by minimizing the latencies of several latency-critical masters, but a side effect of these methods is that they can increase the latencies of other masters; hence, they may violate the given timing constraints. It is better to apply improved Bus Matrix to some applications that do not require the time division multiple accesses to the slaves. This paper adapts improved ML-AHB Bus Matrix to multimedia applications such as a video phone, MPEG-4, and H.264 codec and presents flexible arbiter based on the Dynamic Arbitration scheme for the ML-AHB bus matrix. The arbiter supports three priority policies-fixed priority, round-robin, and dynamic priority-and three approaches to data multiplexing-transfer, transaction, and desired transfer length. Experimental results show that, although the area of the proposed Dynamic Arbitration scheme is 9%–25% larger than those of other arbitration schemes, the arbiter scheme improves the throughput by 14%–62% compared with other schemes.

Multilayer AHB (ML-AHB) bus matrix --- on-chip bus --- Dynamic arbitration scheme --- slave side arbitration --- system-on-a-chip (SoC).

The learning algorithms have great application inknowledge discovery. Learning algorithm offers new beneficiaryways in for real-world applications. Genetic Programming (GP)have some advantages due to which it become suitable forclassification in data mining for Knowledge Discovery(KDD)This paper focuses on the classification by using the GeneticProgramming. There are various types of the traditionalclassification techniques like Naïve Bayesian, ID3, C4.5, CART,kNN, k-mean, SVM etc. The proposed algorithm is implementedon the Diabetes data set and excremental results are comparedwith traditional approach

Classification --- DM --- GP --- KDD

In this paper a new method has been developed tocontrol the operation of a DC motor remotely. It becomes verymuch advantageous if a DC motor is controlled using a cellphone.In order to do that the proposed method uses a complexprogrammable logic device (CPLD). The control input of CPLD isgiven by Dual Tone Multi-Frequency Signaling (DTMF) decoder.The decoder is connected with a cellphone. It becomes very muchbeneficial as range of controlling becomes very much wider i.eequivalent to coverage area of the service provider. It is knownthat CPLD provides quick implementation and fast hardwareverification. It gives facilities of reconfiguring the designconstruct unlimited number of times. The function of CPLD is toprocess the data coming from the output of DTMF decoder and tocreate proper duty cycle PWM output, which will control the speedof DC Motor. Hardware is implemented using CPLD trainer kit(model: UNI-BSX-M1) and software is written using VHSIChardware description language (VHDL) as a pattern tool.

DC motor --- CPLD --- VHDL --- PWM --- DTMF.

Max-min algorithm is based on comprehensivestudy of the impact of RASA algorithm in scheduling tasks and theatom concept of Max-min strategy. An Improved unique versionof Max-min algorithm is proposed to outperform scheduling mapat least similar to RASA map in total complete time for submittedjobs. Improved Max-min is based on the expected execution timeinstead of complete time as a selection basis. We employ Petri netswhich are well suited for modeling the concurrent behavior ofdistributed systems. Experimental results show availability of loadbalance in small cloud computing environment and total smallmakespan in large-scale distributed system; cloud computing. Inturn scheduling tasks within cloud computing using ImprovedMax-min demonstrates achieving schedules with comparablelower makespan rather than RASA and original Max-min.

Distributed System --- Job Dispatching Algorithms and Cloud Computing. Petri net --- Load Balance --- Quality of Service --- Meta Task Scheduling --- Max-min Algorithm --- Min-min Algorithm

Mobile IPv6 (MIPv6) and Hierarchical MobileIPv6 (HMIPv6) both are the mobility management solutionproposed by the Internet Engineering Task Force (IETF) tosupport IP Mobility. There are various types of parameters whichhave been proposed and used to describe the system performancein the form of mobility of MIPv6 and HMIPv6. In this paper acomparative study has been described in which the performanceof MIPv6 and HMIPv6 with Intelligent Mobility Support (IMS)scheme in terms of cost has been demonstrated using ananalytical model. Numerical results demonstrate the performanceof MIPv6 and HMIPv6 when certain parameters are changed.

Access Route --- Fast Mobile IPv6 --- Hierarchical Mobile IPv6 --- Mobile IPv6 --- Mobility Anchor Point.

Autonomous agents and multi agent systems (oragents) and data mining and knowledge discovery (or datamining) are two of the most active areas in informationtechnology. Ongoing research has revealed a number of intrinsicchallenges and problems facing each area, which can't beaddressed solely within the confines of the respective discipline. Aprofound insight of bringing these two communities together hasunveiled a tremendous potential for new opportunities and widerapplications through the synergy of agents and data mining. Withincreasing interest in this synergy, agent mining is emerging as anew research field studying the interaction and integration ofagents and data mining. In this paper, we give an overallperspective of the driving forces, theoretical underpinnings, mainresearch issues, and application domains of this field, whileaddressing the state-of-the-art of agent mining research anddevelopment. Our review is divided into three key research topics:agent-driven data mining, data mining-driven agents, and jointissues in the synergy of agents and data mining. This new andpromising field exhibits a great potential for groundbreaking workfrom foundational, technological and practical perspectives.

multi-agent systems --- distributed data mining --- clustering --- privacy --- agent- based ddm.

The rapid advancement in Information andCommunications Technologies (ICTs) has given rise to newapplications that were impossible just few years ago. Agriculture isan important sector with the majority of the rural population indeveloping countries depending on it. The sector faces majorchallenges of enhancing production in a situation of dwindlingnatural resources necessary for production. ICT plays animportant role in challenging and uplifting the livelihoods of therural populace using an agro computer-based information system.This paper proposes an Agro-Information System that enables afarmer to have relevant information about a crop, such as thevarieties and other requirements like soil type, temperature, typeand quantity of fertilizer, time of planting, time of maturity,planting distance, diseases, pest, pest and Disease controlmeasures, rainfall, sunshine, etc. of that crop. The level ofapplication of this information determines the volume andefficiency of the crop yield. An AIS software is designed andimplemented which helps the farmer achieve the afore-mentionedobjectives.

Agriculture --- Crop yield --- ICT --- Crop requirements --- Agro Information System (AIS).

Web applications consist of several different andinteracting technologies. These interactions between differenttechnologies can cause vast security problems. As organizationsare taking their businesses online they make their systemsaccessible to the world. They might have a firewall in place andpossibly even their web server is running an up-to-date version ofits software but that is not enough to protect their resources.The research areas of this paper outline the major publiclyreported security vulnerability in recent year’s strong growth ofthe web applications. Unvalidated Input, Broken Access Control,Broken Authentication and Sessions Management, InsecureConfiguration Management, Improper Error Handling,Parameter Modification, Cookie Modification and DirectoryTraversal have been the most dominant class of webvulnerabilities. Further, the research includes methods fordetecting the vulnerabilities and then providing securitymechanism to protect web application from those vulnerabilities.The result shows the security mechanisms against the attacksand vulnerabilities. Securing the websites against thesevulnerabilities is very difficult and challenging task as day to daynew techniques for attacks are invented, so the study of varioustypes of vulnerabilities, detecting the attacks and providingsolution for these vulnerabilities is essential part in internetworld.

Security --- Vulnerability detection and Web applications.

Cloud computing provides dynamically scalable and virtualized resources as a service over the network at a nominal initial investment. Data-center works as backbone in cloud computing there a large number of servers are networked to host computing & storage needs of the users. We study and seek to improve the confidentiality of application data stored on third-party computing clouds. Scalable database services allow data query only by primary key rather than supporting secondary-key or join queries. We propose to identify and encrypt all functionally encrypt able data, sensitive data that can be encrypted without limiting the functionality of the application on the cloud. Many data intensive applications produce enormous amounts of data which travel on cloud network. As the cloud users grow, cloud architecture should accommodate movement of voluminous data to avoid data congestion in the network. Many other applications such as payment and online auction services cannot afford any data inconsistency. Cloud computing model provides benefits for private enterprise environments where a significant physical infrastructure already exists. Private cloud management platforms have been emerging in the last several years providing new opportunities for efficient management of internal infrastructures leading to high utilization.

Cloud computing --- Green computing --- Data confidentiality --- Program analysis --- Dynamic resource allocation --- Scalability --- Performance --- ACID --- SAAS (Software as a Service).

In this paper, different types of impulse noiseremoval techniques are presented. Because of adaptive nature ofmask size depending on the noise quantity in the image, adaptivemedian filter works better in removing the salt and pepper noise.To show the performance of Adaptive Median filter, median filter,Lee filter, Frost and Kuan filters and DWT and Duqal treeComplex Wavelet Transform are considered. Adaptive medianfilter is compared with other filters and also the transformations.The superiority of Adaptive Median filter in removing the HighlyCorrupted with impulse noise in images are presented. Graphs aredrawn between the input PSNR and output PSNR for impulsenoise removal techniques.

Dual-Tree CWT --- Adaptive median Filter --- DWT

Image fusion is defined as the process of combining two or more different images into a new single image retaining the important features from each image with extended information content. To overcome the spectral distortions in the fused image, many multiresolution based approaches have been proposed. They include different pyramid transforms and discrete scalar wavelet transforms. The multiwavelet transform (MWT) produces a non-redundant image representation, which provides better spatial and spectral localization of image formation. This paper has derived an efficient block based feature level multiwavelet transform with neural network (BFMN) model for image fusion. The proposed (BFMN) model integrates MWT with neural network, which is one of the feature extraction or detection machine learning applications. In the proposed BFMN model, the two fusion techniques, multiwavelet transform (MWT) and neural network (NN) are discussed for fusing the IRS-1D images using LISS III scanner about the locations Hyderabad, Vishakhapatnam, Mahaboobnagar and Patancheru in Andhra Pradesh, India. Also QuickBird image data and Landsat 7 image data are used to perform experiments on the proposed BFMN model. The features under study are contrast visibility, spatial frequency, energy of gradient, variance and edge information. Feed forward back propagation neural network is trained and tested for classification since the learning capability of neural network makes it feasible to customize the image fusion process. The trained neural network is then used to fuse the pair of source images. The proposed BFMN model is compared with other techniques to assess the quality of the fused image. Experimental results clearly prove that the proposed BFMN model is an efficient and feasible algorithm for image fusion.

Image Fusion --- Multiwavelet Transform --- GHM multiwavelet --- Mutual information --- Performance Analysis.

In this paper high quality single crystal of n-type CDSE is grown from the vapor phase by the piper polich method. X-ray laue photographs from different directions are taken. DC galvanomagnetic properties are measured and analyzed in the temperature range 75 to 450 K in an undoped single crystal of n-type CDSE, which was optimally annealed in high purity molten CD at 850 0C for a period of ~ 400 h. α- the polaron coupling constant is estimated from the measured Hall mobility (μH) data at low and intermediate temperature by identifying a temperature region, wherein only the polar optical phonon scattering operates in the conduction band. The deformation potential Eb in the conduction band of CDSE is obtained from the measured μH data in the temperature region wherein the deformation potential also operates effectively. It is shown that a change in the microscopic mobility through photo excitation indicate a change in scattering.

CDSE --- Methodology

We present a CMOS compatible n-type gate-all-around (GAA) silicon nanowire (NW) MOSFETs with excellent electrostatic scaling. This paper investigates the sensitivity of gate-all-around (GAA) nanowire (NW) to process variations in silicon film thickness and material i.e. Si and Ge with multigate devices using analytical solutions of Poisson's equation verified with device simulation Our study indicates that the GAA nanowire (NW) has the smallest threshold voltage (Vth) dispersion caused by process variations in silicon film thickness. Specifically, the GAA NW shows better immunity to channel thickness variation than multigate devices because of its inherently superior surrounding gate structure. To explore the optimum design space for (GAA) silicon nanowire (NW) MOSFETs were performed with three variable device parameters: channel width, material, and silicon film thickness. The efficiency of the GAA gate structures is shown to be dependent of these parameters.

GAA gate FETs --- MOS devices