Miracle-dz/UniFAR-FTUs huggingface dataset:
Face Recognition in Wireless Communication Using MOCHA Architecture on Jelastic Cloud

-- Face recognition applications are used in our daily lives, which is automatically identify an individual from captured images or videos and this application used for airport security, military, passport office, RTO office, law enforcement, government organization, research and development centre and border patrol. Face recognition algorithm analyse image, extract facial features and use these facial features to search a facial database to locate matching images. This paper describes our work with the design and implementation of face recognition in wireless devices using mobile-cloudlet-cloud architecture on jelastic cloud. Where we utilize a MOCHA framework and develop algorithm that minimize the overall response time for face recognition based on estimated communication latencies and processing powers of the cloud and demonstrate that high-powered cloudlets are technically feasible and provide benefits to mobile device face recognition applications, among others. We develop our own algorithm which compare the % matching faces with respect to given face name in database , it display % matching face with corresponding face n database id also. And perform load balancing in cloud so that millions request can be done at same time within less time period. We use tablets, netbooks, and smart phones as our main mobile device as a client and cloudlet and jelastic cloud as a server[1].
PHYTOCHEMICAL SCREENING AND ANTIOXIDANT POTENTIAL OF ANACARDIUM OCCIDENTALE, ACHYRANTHES ASPERA, AND AEGLE MARMELOS

Objective: Anacardium occidentale, Achyranthes aspera, and Aegle marmelos are the common plants found in North and South India. The present study identifies the active phytochemicals and antioxidant properties in various extracts derived from dried bark, whole aerial parts, and leaves of the above plants. Materials and Methods: Phytochemical screening included extracts of pet ether, hydroalcoholic, and aqueous. The antioxidant activity was determined by measuring total phenolic contents (TPC), 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging activity (RSA), and total flavonoid content (TFC). Results: The phytochemical screening of A. occidentale, A. aspera, and A. marmelos of dried bark, whole aerial parts, and leaves revealed the presence of flavonoids, phenols, tannins, and proteins. It also contains alkaloids and glycosides. Hydroalcoholic extract of A. occidentale, A. aspera, and A. marmelos showed highest TPC 0.125 mg/g, 0.256 mg/g, and 0.254 mg/g, respectively. TFCs 0.094 mg/g, 0.145 mg/g, and 0.121 mg/g and highest DPPH RSA with the half maximal inhibitory concentration of 125 μg/mL, 105.58 μg/mL, and 98.89 μg/mL compare to the standard ascorbic acid of 21.65 μg/mL. Conclusion: This study showed that the hydroalcoholic extract of A. occidentale, A. aspera, and A. marmelos is potential source of natural antioxidants.
Bioactive Evaluation and Antioxidant Potential of Three Native Fruits of the Pampa Biome: Yellow Araçá (Psidium Cattleyanum), Big River Cherry (Eugenia Involucrata ) and Jaboticaba (Plinia Cauliflora ). Perspectives for the Prevention of Damage in Biomolecules, Caused by Oxidative St

Studies show that the consumption of fruits and vegetables is related to the prevention of chronic diseases, probably due to the increase in the consumption of antioxidant compounds contained therein [1]. The main need of cells and tissues is to protect themselves against oxidative stress, being extremely important for the immune system, where the levels of the aggressive agents are controlled by the antioxidant defense system, which is composed of antioxidants and pro-antioxidants [1].
10. Dr.D.Nalini-Online (Back issue) (May 2016).cdr

During the course of maturation, oocytes undergo drastic morphological changes associated with the progression of the meiotic cell cycle, among which breakdown of the oocyte nuclear envelope (germinal vesicle breakdown, GVBD) occurring at the prophase/metaphase transi-tion is usually regarded as a hallmark of the progress of oocyte maturation. As the zebrafish is asynchronous, the ovary contains follicles present in different stages. The present study shows more number of oocytes at GV IV position GVBD) in control and lower concentrations of decis indicates normal progress in oocytes maturation. Less numberof oocytes in Germinal Vesicles IV position GVBD) in higher concentrations of decis indicates delay in oocytes maturation.
Impact Amplification for Distinguish User in viral marketing

---------------------------------------------------------------------***--------------------------------------------------------------------Abstract To increase the profit of product in social network. We are going to use viral marketing platform. By using that, promoter can promote their product on social network. But there is one drawback of influence maximization is that, we cannot differ particular users from other users. To solve such problems we are going to proposed one proposed system called as “Influence maximization and maintenance” That proposed system show that, influence maximization problem as query processing which are going to distinguish that particular user from other users. For that, proposed system is used IMAX and Greedy algorithm. These algorithm used for approximation method. For experimental results, User can compare proposed system with existing system with respect to time required for uploading post on blog. So User can easily find out that proposed method results of time required w.r. t uploading post is faster and less than existing system
Comparative study for detection of group B Streptococci (GBS) by bacteriological culture and molecular methods

Group B Streptococci (GBS) is an important cause of invasive infection in newborn infants, in women around the time of childbirth and in older individuals with underlying chronic illnesses. Although GBS has the capacity to produce life threatening infection in susceptible hosts. One-Hundred eighty nine swabs were taken from the mucus of the vaginal ssues of pregnant women at 36-40 weeks of gesta on during October 2013 to February 2014 from Ibn-Al-Balady Hospital, Central Health Laboratory and Kamal-Al-Samaraie Hospital in Baghdad, Iraq. The isolates initially identified phenotypically by blood agar culture media and chromogenic culture media, further iden fica on performed by VITEK 2 system. Molecular methods was performed by using 16s rRNA gene based PCR. A comparative analysis were performed between the three phenotypic detection methods and molecular method were best tool for S. agalactiae detec on, where in which 46 isolates were iden fied while 37, 36 and 30 isolates were detected by VITEK 2 system, chromogenic agar and blood agar respec vely. VITEK Antibiotic Susceptibility Test for different antibiotics performed to all detected isolates, 45(23.8%) GBS were detected by 16S rRNA gene based PCR, The advantage of this method is that results can obtain within 1 day as compared to tradi onal microbiological tes ng. In addi on, 16S rRNA gene is accurate rapid tool for identification.
VOID FRACTION MEASUREMENT USING ELECTRICAL IMPEDANCE TECHNIQUES

An electrical impedance method for measuring void fraction in multi-phase flow is presented. Two and four concave electrodes configuration are used in the study. The electrodes are mounted on the outer circumference of a pipe and excited by the applied voltage. The existing open literature indicated that most research work on void fraction measurement using capacitance sensor techniques focuses mainly on two phase flow. Little or no attention had been given to three phase flow. Hence the objective of this study is to investigate the effect of sand particles on the overall performance of the capacitance sensor for measuring void fraction in air-water-sand phase flow. The considered flow patterns are the stratified flow and the annular flow. ANSYS multi-physics, a finite element based software was used to implements the problem. Results showed that the addition of about 20% sand particles in the flow path leads to over 40.90% reduction in capacitance value. Hence, the model is capable of detecting the addition of sand particles to the two phase flow.
Image Retrieval Using Attribute EnhancedSparse Code Words

Now a days the popularity of social networks like face book, twitter are mostly used by the people. Many of them use human face images to their profile. And also we can maintain large scale database for the image storage. To avoid the large database use two algorithms like attribute enhanced sparse codewords and attribute embedded inverted indexing and used in offline and online storage respectively. In large image database have problem regarding the image retrieval . By using this algorithm we can efficiently retrieve the images from the large image database. It will give the 80% perfect matched images.
MODELING AND CONTROL OF A FRONT END CONVERTER WITH LEAST DISTORTION AND IMPROVED POWER FACTOR

This paper proposes Front End Conversion (FEC) using Pulse Width Modulated Voltage Source Converter (PWMVSC) with a suitable input filter as a viable solution to improve the input spectral quality which confines the harmonic parameters within acceptable standards and regulations. The input current is nearly sinusoidal with least harmonic distortion and input power factor is adjustable though normally kept at unity. The active converter provides consistently stable dc voltage and has regeneration capability. Better attenuation to switching frequency ripple is obtained with higher value of input line reactor but it increases the size, cost and losses. In this study, the synchronous reference frame control strategy is adopted and conventional proportional-integral (PI) controllers are used for controlling currents and dc bus voltage. The synchronous reference frame strategy eliminates cross coupling between the d and q phases and allows separate control of real and reactive power. Successful simulation is also carried out with designed values.
Efficient Queuing Mechanism for QoS provisioning in Wireless IP Networks

-This paper presents the mechanism used in Class based queuing for enhancing the QoS in Wireless IP networks. Multiclass traffic increases the complexity in handling the data rate. Mobility of the user provides yet another challenge to this issue. This paper presents the design considerations while developing a wireless scheduling algorithm. Most of the algorithms used in real time are compensation based providing fairness between the same traffic classes. Wireless errors generally occur in bursts, because of the inability of signal propagation in a cellular network, as well as the inertia of users’ movement in time intervals comparable to the time needed for processing of an individual IP packet. By using the compensation based algorithms, both issues: the location-dependence of wireless bit errors and the multiclass environment are discussed.
An Efficient Algorithm for the Exemplar Based Image Inpainting

Image inpainting is the process of filling the missing portion of an image or removing an object from a image. In this paper we introduce a literature review of some latest exemplar based image inpainting techniques. The working of each method for inpainting is explained in brief. An overview of image inpainting is also given at the beginning. We have also proposed a novel exemplar based image inpainting method. The proposed image inpainting method will be capable of removing the complete object from an image or a part of the object & it will produce high quality results.
Opinion Analysis: A Multistage Approach

— The task of opinion mining has attracted interest during the last years. This is mainly due to the vast availability and value of opinions on-line and the easy access of data through conventional or intelligent crawlers. In order to utilize this information, algorithms make extensive use of word sets with known polarity. We consider the above issues by proposing an approach for a multistage model for analysis of opinions using sentiment orientation with conjunction and iteration at multilevel.
Biometric Online Signature Verification with added Security of unique ID

: Biometrics refers to metrics related to human characteristics. In this paper we discuss the Biometric Online Signature Verification with added security of unique ID using coordinates methods. Various Biometric techniques are now available which is helpful in personal identification. Among all those verification system signature verification is one of the important biometric system. Here we capture the signature by a special device such as touch screen. In this system we implement the signature verification using advance RISC processor. Here each signature is protected with a separate UID.
BRAIN COMPUTER INTERFACE IMPLEMENTATION USING CLUSTERING TECHNIQUES

Brain Computer Interface (BCI) generally utilizes non-invasive EEG signals in order to detect intended movement. Normally all EEG electrode receive brain activity on scalp surface which is superimposition of different brain activity. As the number of channel is high we need to reduce it in order to properly detect movement related activity. In this work we have utilized different clustering algorithms to reduce insignificant channels. We have extracted features using statistical methods Principal Component Analysis (PCA). And the classification is done using unsupervised learning algorithm in order to improve generalization capability. The proposed approach reduces false positive rate and it also shows different person have different activity region.
Protoplasts Isolation From Leaf Explants Of Solanum Surattense Burm . F . A Medicinally Important Plant

A simple protoplast isolation protocol that was designed to recover totipotent plant protoplasts with relative ease has been described· The key elements of the protocol are, tissue digestion at slightly elevated temperatures and use of protoplast releasing enzymes that are stable and efficient at higher temperatures· Besides enzymes, the protoplast isolation cocktail consisted of an Osmoticum (Mannitol or MgSO4), and a Protectant (CaCl2 2H2O), all dissolved in distilled water. The protocol has ensured reproducibility, higher yields and is gentle on protoplasts as the protoplasts obtained were amenable to cell wall regeneration and cell division· Plant regeneration was demonstrated for Solanum surattense Burm.f from protoplasts isolated by this method· Wall regeneration and cell division were obtained in other species. The merits of the protocol are, simple and easy-to-handle procedure, non-requirement of preconditioning of donor plant and explants, incubation without agitation, satisfactory yields, culturability of the protoplasts isolated and applicability of the protocol to a large number of species including mucilage-containing plants
Efficiency of Telecommunication Companies in ASEAN: Corporate Mergers and Acquisitions

Traditionally, acquiring companies have an expectation of synergy in the coming years as a result of mergers and acquisitions (M&As). Instead of using traditional financial ratios from accounting statements such as return on assets in terms of measuring performance, this study intends to provide a broad view of the effects of M&As and asset utilization on technical efficiency. In light of the foregoing, this study was done by taking into account the consequences of multiple M&As undertaken by the telecommunication companies in the Association of Southeast Asian Nations (ASEAN)region using year-by-year projections. The study employed the Data Envelopment Analysis (DEA) approach which calculates the technical efficiency using the total asset of companies during the period between 2000 until 2011. Subsequently, regression analysis was employed to examine the factors that influenced the efficiency of the companies. The empirical findings indicate that there exists a significant relationship, of negative value, between sequence of M&A and technical efficiency (TE). The findings also indicated that the relationship between size and TE are significant and negative. This paper also discussed the importance of having a merger control under Competition Law and suggested that there is a need for improvement of merger control regulations to sustain the relative efficiency of companies.
ANALYSIS OF IMAGE SEGMENTATION TECHNIQUES FOR TEXTURE FEATURE EXTRACTION

The pixels of an image are grouped into several regions for segmentation. In segmentation technique the texture feature parameter is an image analysis technique in the field of Computer vision. In the Segmentation field, there are many techniques are used to segment the images . The proposed approach is to analyze and compare the gray level texture feature techniques, number of clusters, Fuzzy C means
Feature Extraction Technique for Robust and Fast Visual Tracking: A Typical Review

: Visual tracking is a fundamental task in many computer vision applications and it remains a huge challenge, although numerous approaches have been proposed. Feature extraction is one of the major research fields in video processing. Feature Extraction is a method of capturing visual content of images for indexing and retrieval. It is a crucial step for multimedia processing. In this paper, we focus our review on different feature extraction technique. In particular, we first analyze the state-of-the-art feature descriptors which are used to represent the appearance of tracked objects. The image descriptors include texture, color, and shape of the object inside an image. Several feature-extraction techniques viz., Average RGB, Color Moments, Co-occurrence, Local Color Histogram, Global Color Histogram and Geometric Moment have been typically reviewed in this paper. The effectiveness of the fusion of global and local features in automatic image annotation and content based image retrieval system.
Study on exploring the potential of Nymphoides peltatum as animal feed growing in Dal lake of Kashmir Himalaya

The present study was conducted to investigate the biochemical attributes of Nymphoides peltatum an aquatic plant at three study sites viz., site I (Ashai Bagh, near residential area); site II (Telbal) and site III (Nehru Park) of Dal Lake, Kashmir. The sampling was done on monthly basis and the entire study period was divided into two phases i.e., the active growth phase (summerJuly and August) and the senescence phase (September, October, early November and late November). The biochemical assessment (chlorophyll, amino acids, sugar content, total protein content and starch) of selected macrophyte at three sites revealed that the concentration of chlorophyll-a varied between (3.10 to 5.42μg mL at site-I); (0.08 to 2.38 μg mL at site-II) and (0.14 to 2.48 μg mL at site-III); chlorophyll-b varied between (0.003 to 1.40 μg mL 1 at site-I); (0.001 to 1.10 μg mL at site-II) and (0.002 to 1.12 μg mL at site-III); total chlorophyll concentration varied between (3.33 to 5.6 μg mLat site-I); (1.00 to 2.12 μg mL at site-II) and (1.18 to 2.67 μg mLat site-III). Similarly, the results of proteins follow the same trend decreasing from peak growth phase to senescence phase with (0.88 to 1.14 mg mL at site-I); (0.048 to 1.08 mg mL at site-II) and (0.053 to 1.124 mg mL at siteIII). The concentration of starch also follows the same trend highest in peak growth phase and lowest in senescence phase. The results revealed that the biosynthesis of various biomolecules accelerated during the active growth phase at Site-I (July) while as, low range of biomolecules was observed at site-II in the senescence phase (November). The finding of the present study suggests that the macrophyte can be used as a potential source of food and fodder for bovine animals and as fertilizers for agriculture fields and flowering gardens.
Sentimental Analysis using Deep Learning Techniques

There is a rapid growth in the domain of opinion mining as well as sentiment analysis which targets to discover the text or opinions present on the disparate social media platforms via machine-learning (ML) with polarity calculations, sentiment analysis or subjectivity analysis. Sentimental analysis (SA) indicates the text organization which is employed to categorize the expressed feelings or mindset in diverse manners like favorable, thumbs up, positive, unfavorable, thumbs down, negative, etc. SA is a demanding and notable task that comprises i) natural-language processing (NLP), ii) web mining and iii) ML. Also, to tackle this challenge, the SA is merged with deep learning (DL) techniques since DL models are efficient because of their automatic learning ability. This paper emphasizes recent studies regarding the execution of DL models like i) deep neural networks (DNN), ii) deep-belief network (DBN), iii) convolutional neural networks (CNN) together with, iv) recurrent neural network (RNN) model. Those DL models aid in resolving different issues of SA like a) sentiment classification, b) the classification methods of i) rule-based classifiers (RBC), ii) KNN and iii) SVM classification methods. Lastly, the classification methods’ performance is contrasted in respect of accuracy.
Augmented reality using artificial neural networks –a review

The present paper reviews the areas where Augmented Reality (AR) has been used in Artificial Neural Networks (ANN) (Artificial Neural Networks). The focus on systems based on AR is largely on enhancing technologies in diverse application areas such as; defense, robotics, medical, manufacturing, education, entertainment, assisted driving, maintenance and mobile assistance. However, AR is now finding much usage in ANN. The research considered a review based methodology wherein most studies conducted in the past on AR and ANN were reviewed. AR with ANN has profound applications in various sectors and has been developed in an extended way but still has some distance to go afore industries, the military and the common public will receive it as a accustomed user interface. AR would modernize the way people animate and the way industries endeavor by effective utilization. There is an incredible potential in fields such as construction, art, architecture, repair and manufacturing with mediated reality and well-organized visualization through AR.
Dynamic Vehicle Tracking and Detection For Self Driving Using FCM Algorithm

-This paper describes about vehicle tracking and detection for un-manned vehicle using FCM algorithm. In order to achieve this Artificial Intelligence is used to recognize and track a path which an intelligent car can follow. The drawback of the using Beam-Model based algorithm is that they cannot detect and track dynamic vehicle that are occluded by other objects and cannot move in a proper direction when an obstacle occurs in the middle. To solve this problem a novel detection and tracking algorithm for the ALV is proposed. Frame rate up-conversion increases temporal sampling rate in progressive video. MPEM enables automatic detection of objects and allows non-grid motion. Second order feature extraction is done using Hough Transform. Pose search and detection using deep network with lane space estimation is done to provide an improvised result.
Classification of ECG Waveforms for Abnormalities Detection using DWT and Back Propagation Algorithm

— ECG signal analysis for abnormalities detection using discrete wavelet transform and Back Propagation Neural Network is addressed in this paper. Proposed technique used to detect the abnormal ECG Sample and classify it into two different classes (normal and abnormal). We have employed MIT-BIH arrhythmia database and chosen 45 files of one minute recording where 25 files are considered as normal class and 20 files of abnormal class out of total 48 files. The features are break up in to two classes that are DWT based features and morphological feature of ECG signal which is an input to the classifier. Back Propagation Neural Network (BPNN) are employed to classify the ECG signal and the stem performance is measured on the basis of percentage accuracy. For the normal class sample 96% of accuracy is reached whereas 100% accuracy is achieved for normal class sample. The overall system accuracy obtained is 97.8 % using (BPNN) classifier.