Miracle-dz/UniFAR-FTUs huggingface dataset:
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: Validation of clusters quality is a challenging task, especially when natures of cluster aredensed and arbitrary shaped. The internal and relative cluster validation indices are the most commonlypreferable approaches to validate correct formation clustering structure and clustering algorithms.Although many indices have been proposed, but literature survey revealed that, there is no work have been performed whichare used to validate clustering structure specially for densed, sparsed and arbitrary shaped clusters.This paper proposes suitability of validation indices from amongmost commonly used validation indices and thier mathematical background. Results obtained also act as a guidelines for selecting appropriatevalidation indices and validate clustering structure specially for densed, sparsed and arbitrary shaped clusters.
Parametric Variation with Doping Concentration in a FinFET using 3D TCAD

The parametric variations of FinFET in 22 nm due to doping concentrations are presented. In this paper different parameters of FinFET such as subthreshold slope, DIBL, threshold voltage, transconductance and Ioff are analysed using Synopsys Sentaurus 3D TCAD. From the results, it can be concluded that, optimized doping leads to better characteristics for the FinFET.
3D MR Images Denoising using Adaptive Blockwise Approached Non-Local Means (ABNLM) Filter for Spatially Varying Noise Levels

: The uniform noise distribution over the image is assumed in most of the filtering techniques. The resulting filtering technique becomes problematic when noise not uniformly distributed. Magnetic Resonance images with spatially varying noise levels were produced by Sensitivity-encoded, intensity inhomogeneity and surface coil based acquisition techniques. To adapt these spatial variations in noise levels, we propose a new Adaptive Blockwise approached NL-Means Filter where denoising capability of filter is adjusted based on the local image noise level. Image Noise levels are spontaneously acquired from the MR images using a proposed new adaptive technique. To reduce the computational burden of NLM Filter, an Adaptive Blockwise Non-Local Means Filter is proposed to speed up the denoising process. With adaptive soft wavelet coefficient mixing, a multiresolution framework is adapted to ABNLM filter for denoising of 3-Dimensional MR images. The proposed Multiresolution filter adapts the filtering parameters automatically based on image space-frequency resolution. The outcome of the stated multiresolution Adaptive Blockwise Non-Local Means Filter shows better performance in considering the non uniform noise when compared to Rician NL-means filters where the noise parameters has to be specified initially.
A Survey on Classification of Liver Diseases using Image Processing and Data Mining Techniques

-Human soft tissues are diagnosed by different imaging modalities such as Computed tomography CT, Ultrasound US, Magnetic resonance imaging MRI all these imaging modalities are applied depending on the nature of the disease. In the classification of liver related diseases each of these imaging modalities plays important role. Classifying a liver into normal liver and diseased liver (in diseased cirrhotic or fatty liver) depends completely on the texture of the liver. Texture is a combination of repeated patterns with regular or irregular frequency. Texture visualization is easier but very difficult to describe in words. Analyzing liver texture is also difficult. To classify liver into its respective diseases category it is very important to extract the Region of Interest ROI accurately by segmentation, but as liver structure has maximum disparity in intensity texture inside and along boundary which serves as a major problem in its segmentation and classification. There are different textural analysis techniques developed for liver classification over the years some of which work equally well for most of the imaging modalities. Here, an attempt is made to summarize the importance of textural analysis techniques devised for different imaging modalities.
Performance Analysis and Estimation of Naive Bayes Algorithm in Zone Routing Protocol

: In Mobile Ad-hoc Network zone routing protocol uses the analysis of Naive Bayes algorithm. While transmitting data with in the network the hybrid ZRP uses both proactive and reactive routing algorithm. Internet of things and wireless sensors networks has a bulk amount of data and technology which challenges in the view of energy resources, limitations and estimation and transmission. Trace analyzer and cooja simulator will find communication of routing nodes and creations of zones. Naive Bayes is a robust algorithm for the classification task and straight forward. This paper examines the Gaussian model, multi nominal and Bernoulli naive Bayes analysis cooja simulator .
in Computer

— A social networking service is an online service, platform, or site that focuses on facilitating the building of social networks or social relations among people who, for example, share interests, activities, backgrounds, or real-life connections. A social network service consists of a representation of each user, his/her social links, and a variety of additional services. Most social network services are web-based and provide means for users to interact over the Internet, such as e-mail and instant messaging. Online community services are sometimes considered as a social network service, though in a broader sense, social network service usually means an individual-centered service whereas online community services are group-centered. Social networking sites allow users to share ideas, activities, events, and interests within their individual networks. The large-scale user-contributed content contains rich social media information such as tags, views, favorites, and comments, which are very useful for mining social influence. The social links such as views, favorites, and re tweets, indicate certain influence in the community. Since the content of interest is essentially topic-specific, the underlying social influence is topic-sensitive. Novel Topic-Sensitive Influencer Mining (TSIM) framework aims to mine topic-specific influential nodes in the networks and find topical influential users and images. The influence estimation is determined with a hyper graph learning approach. In the hyper graph, the vertices represent users and images, and the hyper edges are utilized to capture multitype relations including visual-textual content relations among images, and social links between users and images. The influence estimation is determined with a hyper graph learning approach. In the hyper graph, the vertices represent users and images, and the hyper edges are utilized to capture multitype relations including visual-textual content relations among images, and social links between users and images.
Effect of Physical Constraints on Load Frequency Control of Deregulated Hybrid Power System Integrated with DFIG Wind Turbine

Abstract -This paper presents a generalized model for load frequency control (LFC) design in a hybrid multi-area deregulated power system including physical constraints. Renewable energy source named doubly fed induction generator (DFIG) based wind energy source is integrated into the system that provides the modified emulating inertial control and reduces the deviations in frequency and tie-line power, following a transient load perturbation. In addition to this, the three basic physical constraints viz. generation rate constraints (GRC), speed governor dead band and communication or time delay have been imposed on the power system that affect the system’s security, reliability and integrity. To get the better performance of the various controllers in power system, their gains are optimized using integral square error (ISE) technique. Present simulation studies reveal that the system’s performance becomes better by the inclusion of DFIG based wind turbine. It is also shown that the dynamic performance of the system becomes poorer by adding physical constraints but it is a more realistic approach. KeywordsAutomatic Generation Control (AGC), LFC, Deregulated system, Bilateral contracts, Disco participation matrix (DPM), DFIG, GRC.
Designing a Hybrid Page Ranking Algorithm for Semantic Web Search Engine

-Web is the most important tool in now-a-days upon which people rely on to search their required information. In such a scenario it is the duty of service provider to provide proper, relevant and quality information to the internet where user can submit their query and find out the result. But it is a challenge for service provider to provide proper, relevant and quality information to the internet user by using the web page contents and hyperlink between the web pages. The next-generation Web architecture, represented by the Semantic Web, provides the layered architecture possibly allowing overcoming this limitation. Several search engines have been proposed, which allow increase in information retrieval accuracy by exploiting
Comparative Study of some Beta-Lactam Antibiotics Efficacy in Curing Resistant Escherichia coli Infection

Increased bacterial resistancy especially gram negative bacteria, impairs curing of some infections. On the other hand various studies showed that some antibiotics have efficacy in curing resistant bacterial infections. On account of that it was interesting to study efficacy of some beta lactam antibiotics (cephradine and ampicillin) and/or tenoxicam in curing wound infection caused by multiple antibiotic resistant (MAR) Escherichia coli (E.coli) and exploring other possible mechanisms irrespective of the antibacterial activity. This was performed by screening MAR strains of E.coli in vitro (agar dilution) and in vivo (bacterial infected rat wound and carrageenin acute inflammatory) models for assessing possible mechanisms of efficacy of tested antibiotics alone and in combination with standard nonsteroidal anti-inflammatory drug (tenoxicam), in curing resistant bacterial wound infection. This was evaluated by measuring immunological mediators and histopathological examination. This study revealed that in vivo cephradine and ampicillin alone or in combination with tenoxicam significantly improved healing of infected skin wounds with E.coli despite of resistancy in vitro, by improvement of immunological mediators involved in inflammatory reaction, oxidative stress and cytokines expression as response to bacterial infection. In vitro tenoxicam didn't have any antimicrobial activity alone nor in combination with tested antibiotics, but it was synergistically increasing efficacy of tested antibiotics when used in combination with it in vivo. Thus we concluded that immunomodulatory activity of cephradine and ampicillin through anti-inflammatory and antioxidant effects (beyond its antimicrobial activity) are the possible mechanisms by which these antibiotics have healed E.coli infections, despite its resistancy to those antibiotics. In addition to using these antibiotics in combination with tenoxicam synergistically increases their efficacy. K e y w o r d s Comparative, Efficacy,
Freundlich Adsorption Isotherm and Electrochemical Characterization of Cellulose acetate-Tween-20 supported liquid membrane

Cellulose acetate (CA) and Tween-20(T-20) are interacted and resulted as a supported liquid membrane system. The membrane potential was measured with uni-uni valent electrolyte, NaCl solutions using saturated calomel electrodes (SCEs). The effective fixed charge density of the membrane was determined by TMS method. Other important electrochemical parameters were calculated. Membrane adsorb-ability showed Freundlich type adsorption. Membrane water uptake with respect to time is observed. Membrane permselectivity (the ability of the membrane to discriminate between the anions (Cl-) and cations (Na+)) is estimated using effective fixed charge density of the membrane. The transport number which quantifies the fraction of the charge carried by certain ion is estimated by membrane potential values. Tween-20 surfactant is most frequently used for membrane surface modification. Electrochemical parameters are estimated under both conditions, i.e. without and with Tween-20 to investigate the effect on the membrane behavior.53% composite membrane of CA/T-20 is obtained as a liquid membrane.
DARCAH: Distributed Approach to Rendezvous Channel Setup in Cognitive Radio Ad Hoc Networks

In this paper, we propose a solution to the problem on how cognitive radios can find each other. The easiest and common practice to address this problem is to have a dedicated control channel on which the nodes can rendezvous with each other. However, a dedicated Common Control Channel (CCC) has severe drawbacks. As a solution to this drawback, we propose a rendezvous channel (RC) setup scheme called Distributed Approach to Rendezvous Channel Setup in Cognitive Radio Ad Hoc Networks (DARCAH) in which, one of the free channels is chosen as RC rather than having dedicated CCC. Besides, instead of deploying a dedicated central entity, one of the nodes from the Secondary Users (SUs) is in charge of transmitting the RC. Extensive MATLAB simulations were performed to study the effectiveness of DARCAH.
Genetic Diversity and Phylogenetic Relationship between Indigenous Cattle Breeds

Zebu breeds of cattle from southern part of India are well known for their adaptability to extreme climatic conditions, draught efficiency, disease resistance and poor nutritional environment. Selection of appropriate populations for conservation of such genetic resources is needed in view of preventing rapid erosion of animal genetic resources. Estimation of genetic diversity is essential to decide the priority of the population to be conserved. DNAbased molecular markers with high level of polymorphism have been used to evaluate genetic variation of breeds in breeding programmes and conservation. Micro satellites are the potential markers to study genetic variation, gene flow, genetic distance and genetic identity of indigenous cattle breeds.
Sideband Suppression of Time Modulated Linear Array using Fit Simulation Method

A time modulated linear antenna array consisting of 16 elements very thin wired dipole antennas is simulated using the CST Microwave Studio. The proposed technique utilizes on-off RF switches and operated at 3GHz central frequency and time switched at 1MHz pulse repetition frequency. Particle Swarm Optimization based technique is used to obtain the optimum time pulses applied to individual element to reduce the side band radiation while constraining the radiation pattern at central frequency below a fixed sidelobe level (SLL) for a given first null beam width (FNBW). Simulated results are in good agreement with those obtained using analytical approaches. Reduction of radiated power at sideband frequencies increases the gain of the proposed array.
Error Rate Performance Analysis of OFDM System over Nakagami-n and Nakagami-q Distributions

The Orthogonal Frequency Division Multiplexing (OFDM) is a multicarrier modulation technique becomes very popular because of its advance used in VLSI. Today it is used in many wireless standards such as WLAN, DAB and ETSI Hiperlan/2.In wireless communication system multi path propagation impairments can be reduce the error rate performance of the system. In this paper, the error rate performance of the OFDM system over Nakagami-n and Nakagami-q fading channels has been investigated. Further these results have been used to evaluate the threshold value of fading figure n and q based on error rate and SNR.
Association between Primary Health Care Access and Acute CareUtilization for Hypertension: A Systematic Review

Background: Ambulatory Care Sensitive Conditions (ACSC) are chronic conditions for which hospitalizations can potentially be avoided through timely and effective primary health care; one of these is hypertension. However, the association between primary health care access and ACSC hospitalizations is not consistent in the literature. We conducted a systematic review to assess the association between primary health care access and hospitalizations or emergency department visits using hypertension as the ACSC of interest. Methods: We searched two electronic databases (Medline and Embase) from inception to September 2017 to identify all observational studies evaluating the association between primary health care access and acute care utilization (hospitalizations or emergency department visits) for patients diagnosed with hypertension. Results were synthesized narratively. Study quality was assessed using components of the Newcastle Ottawa Scale and the Downs and Black Checklist. Results: Our search strategy yielded 5,123 abstracts; 3 met all inclusion criteria. Two studies found a positive association between primary health care access (the number of primary care visits or general practitioner density) and hospitalization rates for hypertension, while the other study found increases in general practitioner density resulted in a reduction in hospitalization rates for hypertension. Study metrics and quality varied substantially across the selected studies. No studies adjusted for system-level factors or severity of hypertension. Conclusions: There is limited and inconclusive evidence on the relationship between access to primary health care and acute care utilization for hypertension. Further research, including adjustment for disease severity and key confounders is required to elucidate this relationship.
A Privacy-Preserving QoS Prediction Framework for Web Service Recommendation

---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - Web service recommendation has become a hot topic even in basic research in IT. The most popular technique is the collaborative filtering (CF) on the basis of a quality of service value. With the increasing presence and adoption of web services over the World Wide Web, the quality of service (QoS) is becoming more important to the description Non-functional characteristics of Web services. Several approaches for the selection of Web services and recommendation via collaborative filtering were studied; here we are going to investigate these techniques with the pros and cons of Techniques. Also based on these comments, we will propose a new technique for predicting the Web service selection based on known quality of service values and unknown we explain in our future work.
An Overview on Multimedia Data Mining and Its Relevance Today

Over the past few decades, data quarrying or mining has been an effective approach for extracting concealed knowledge from huge collections of regulated digital data stored in databases. Multimedia data mining (MULTIMEDIA DATAMINING) refers to the analysis of large amounts of multimedia information in order to find patterns or statistical relationships. Rapid changes in information technology have drastically changed the functions and activities of multimedia. It includes audio, video, speech, text, web, image and combinations of several types are becoming increasingly available and are almost unstructured or semi structured data by nature, which makes it difficult for human beings to extract the information without powerful tools. This paper sight sees survey of the current state of multimedia data mining and knowledge discovery, data mining efforts aimed at multimedia data, current approaches and well known techniques for mining multimedia data.
Synthesis of Biologically Active 3-Hydroxy-3-Phenyl-1-(5-Chloro-2-Methyl) Phenyltriazene and Application in the Spectrophotometric Study of Iron Complex

Accepted on 17 th December 2015 _____________________________________________________________________________ ABSTRACT In the present study synthesis, characterization and activity prediction of 3-hydroxy-3-phenyl-1-(5-chloro2-methyl) phenyltriazene has been done. The spectrophotometric behaviour of complex of Fe (III) with 3hydroxy-3-phenyl-1-(5-chloro-2-methyl) phenyltriazene was also studied. It was observed that 3-hydroxy3-phenyl-1-(5-chloro-2-methyl) phenyltriazene forms 1:3 complex with Fe (III) between pH 2.8-3.8.
A Study of Events Logs from Elevated Volume of Logistics Information in Spatio-Temporal Data Mining

In logistics, software aids for transportation planning and scheduling are often based in approximations and abstractions that do not take into account real-world data. The aim of this work is to provide an analysis and methodology, based on real-world data, on how to obtain probability density functions for prediction of activity duration. Such information can be used in planning algorithms, like vehicle routing problem, capable of dealing with stochastic time-windows. Given a large spatio-temporal database of events, where each event consists of the fields event ID, time, location, and event type, the aim is to extract valuable information about activities duration. The process is not straightforward since the log is human-influenced creating uncertainty related with the time at which the events are logged. In order to overcome this, a novel framework is proposed: it uses the spatiotemporal trajectories to identify regions-of-interest based on speed, and builds an ROI activity time-line using the activities extracted from event logs. The framework’s ability to estimate activities durations was tested in three different environments: the Amsterdam Airport Schiphol, the Port of Rotterdam and a single vehicle scenario. Experimental results validate the usefulness of the approach at finding probability density functions for prediction of activity durations at specific locations.
Evaluating Data Compression and Image Steganography Techniques for Optimized Embedding

We investigate the performance of state of the art data compression techniques and steganography methods for digital images proposed in the literature. Data compression and hiding methods are tested against a number of well-known steganographic methods for digital images that operate in spatial domains. Our experiments are performed and results are analyzed on large data set of digital colored images captured by our own canon camera and images available on the websites. Images are categorized on the basis of size, texture and types that include only jpeg, bmp and png types to determine their impending impact on steganographic methods. Text data to be embedded is classified and selected of varying capacities and domains to determine best suited data compression mechanisms and steganographic techniques. Our results designate the selection of compression and embedding techniques with respect to types of data .
Isolated Word Speech Recognition Using Vector Quantization (VQ)

The results o f a case study carried out while developing an automatic speaker recognition system are presented in this paper. The Vector Quantization (VQ) approach is used for mapping vectors from a large vector space to a finite number of regions in that space. Each region is called a cluster and can be represented by its center called a codeword. The collection of all code words is called a codebook. After the enrolment session, the acoustic vectors extracted from input speech of a speaker provide a set of training vectors. LBG algorithm formulated by Linde, Buzo and Gray is used for clustering a set of L training vectors into a set of M codebook vectors. For comparison purpose, the distance between each test codeword and each codeword in the master codebook is computed. The difference is used to make recognition decision.