Miracle-dz/UniFAR-FTUs huggingface dataset:
A SURVEY ON ONLINE GRAPH REGULARIZATION FOR USER PREFERENCE IN SOCIAL RECOMMENDATION

- Social recommendation system has pulled in a great deal of consideration as of late in the exploration groups of data recovery, machine learning and information mining. Conventional social recommendation algorithms are frequently in view of batch machine learning methods which experience the ill effects of a few basic restrictions, e.g., to a great degree costly model retraining cost at whatever point new user ratings arrive, not able to catch the change of user preferences after some time. Along these lines, it is imperative to make social recommendation system appropriate for true online applications where information regularly arrives consecutively and user preferences may change powerfully and quickly. The structure of online social recommendation from the perspective of online graph regularized user preference learning(OGRPL), which joins both collaborative user-item relationship and additionally item content features into a brought together preference Learning process.
DDoS Attack in “Cloud of Things” Environment, Software Defined Networking (SDN) and A Research on Defense Mechanisms against DDoS using SDN

-The Internet of Things presents the user with a novel means of communicating with the Web world through ubiquitous object-enabled networks. While IoT is exciting on its own, the real innovation will come from combining it with cloud computing. In the new era of Internet of Things integrated with cloud computing, Distributed Denial Service of Attacks (DDoS) is growing substantially. With the advancement of Software Defined Networking (SDN), defense mechanisms against DDoS attack has opened a new door to Cloud of Things environment. This paper discusses on how to make full use of SDN’s advantages to defeat DDoS attacks in cloud computing environments as well as cloud based IoT environment. The research results in this paper can be expanded to prepare a new architecture of SDN enabled secured Cloud of Things environment.
Improved Spectral Subtraction with Time Recursive Noise Estimation

: This Paper proposes a method for single channel speech enhancement with noise estimation algorithm in presence of additive back ground noise which overcomes the drawbacks of basic spectral subtraction. Since speech is non-Stationary signal, noise distribution is non-uniform i.e few frequency components are affected severely than others. So speech enhancementalgorithms requires an accurate noise estimation to remove the noise effectively. The proposed method uses noise estimation by First order recursive averaging algorithm based on a posteriori Signal -to-Noise-Ratio and its performance evaluated in terms of objective performance measures such as segmental SNR, Cepstrum distance, Log Likelihood Ratio and Perceptual Evaluation of Speech quality under eight different real-world noises at three ranges of input SNR. The performance of Proposed method was compared with Basic Spectral Subtraction method ,Spectral subtraction with Various noise estimation algorithms . The results shows that ,proposed method shows superior performance in all the cases considered.
A new conception of load balancing in cloud computing using Hybrid heuristic algorithm

This article introduces the last improvement in the field of hybrid heuristics designed to optimize the resources related to the allocation of user requests (tasks) in the cloud environment. We propose an efficient method for providing a load balancing in the cloud computing environment based on combining the global search abilities of Genetic Algorithm (GA) with different heuristics such as Tabu Search Algorithm, Simulated annealing Algorithm, ABC Algorithm, ACO Algorithm and PSO Algorithm. The experimental results showed that the proposed algorithm has high efficiency for reaching a load balancing in Cloud computing.
Comparison of the Virtual Biopsies of a Nodular Basal Cell Carcinoma and an Actinic Keratosis: Morphological, Cellular and Collagen Analyses

*Correspondence: Frederick H. Silver, Department of Pathology and Laboratory Medicine, Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; E-mail: silverfr@rutgers.edu Received Date: 11 Feb 2019 Accepted Date: 04 Mar 2019 Published Date: 08 Mar 2019 Citation: Silver FH, Shah RG, Richard M, Benedetto D. Comparison of the Virtual Biopsies of a Nodular Basal Cell Carcinoma and an Actinic Keratosis: Morphological, Cellular and Collagen Analyses. Clin Oncol. 2019; 4: 1588. Copyright © 2019 Frederick H. Silver. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Research Article Published: 08 Mar, 2019
Cellulitis in broiler chicken due to Escherichia coli: A case report

In present study, eight broiler carcasses were presented for postmortem examination. On necropsy examination the birds revealed typical perihepatitis, pericarditis lesions of E. coli infection. On gross examination out of these 8 birds, 3 birds revealed lesion of cellulitis characterized by thickening and reddish-brown discoloration of skin on head and neck region. Similar symptoms were also present in some illing birds in the flock. Broilers with cellulitis revealed fibrinous exudates in subcutaneous tissue. Microscopic examination of tissue confirmed hyperkeratosis, dermatitis, congestion and infiltration of histiocytes in dermis along with proliferation of fibrous tissue. On the basis of gross lesions and clinical symptoms the samples were collected for microbiological analysis. Isolates were E.coli on cultural examination which were further confirmed by Polymarase Chain Reaction.
Selective Harmonics Elimination Of Cascaded Multilevel Inverter Using Genetic Algorithm

— In this paper, a genetic algorithm (GA) optimization technique is applied to cascaded multilevel inverter to determine optimum switching angles for eliminating some lower order harmonics also minimize the total harmonics distortion while maintaining the required fundamental voltage. This technique can he applied to multilevel inverters with any number of levels; as an example in this paper, a 15-level inverter is considered, and the optimum switching angles are calculated offline to eliminate 5th, 7th and 11th harmonics. Then, these angles are used in MATLAB similink to validate the results.
Expanded Tentacles of Cold Plasma Energy in Dentistry – Review

The atmospheric cold plasma is a non-thermal processing method. This technique becomes a subject of high interest for a wide variety of technological use, medical and dental treatment modalities. This review article on plasma therapy in dentistry is intended to provide with a summary of the current status of this emerging technology, its scope, and its broad interdisciplinary approach. States of matter are liquids, solids, and gases. But a fourth category of matter has been discovered called plasma that’s actually the most unusual and the most abundant. It has a plenty of uses in dentistry. It could become a new and painless way to prepare cavities for restoration with improved longevity. Also, it is capable of bacterial inactivation and non-inflammatory tissue modification, which makes it an attractive tool for the treatment of dental caries and for composite restorations. Plasma can also be used for tooth whitening. This review focuses on plasma basics, mean of production, mechanism of its effects upon dental tissues and its wide range dental applications. Lastly but not leastly the review confirmed that no harmful by-products are generated by this technology.
Biofilm formation by Streptococcus agalactiae is affected by pH changes in vitro

Background: The capacity of Streptococcus agalactiae to cause infections is related to their ability to produce biofilms which allow bacteria to adhere to tissues causing pathogenesis and promote their resistance to antibiotics resulting in prolonged infections. Therefore, the aim of current study was to study the ability of these bacteria to form biofilms and the effects of pH changes on this ability. Materials and Methods: A total of 25 confirmed isolates of Streptococcus agalactiae were collected in this study. The isolates were obtained by vaginal swaps from pregnant women who were complaining from abnormal vaginal discharge. Biofilm was detected by semiquantitative microtiter plate test (biofilm assay) using TSB supplemented with 1% glucose. Results: In this study, all strains of GBS were biofilm former and 52% of them were strong biofilm formers while 48% were moderate biofilms formers. Also, results showed that the ability of the studies isolates to form biofilms was weak at low pH and enhanced at high pH. Therefore, high pH plays a critical role in the pathogenesis of chronic vaginal bacterial infections.
A Tool for Privacy-Aware Online Personal Photo Sharing Using Deep Learning Technique

In recent years, online social networking has been considered as a sharing information platform and has occupied an essential part in many individual's lives and business growths. Consequently, there has been a marked increase in the collection and illegal exploitation of photos amassed online without owner consent, thus violating individual privacy rights such as contravention of online published photo laws which contribute to public social anxiety. To address these concerns, we propose a face recognition tool based on the Deep Learning Convolutional Neural Network (CNN) technique, which may be utilized within a social networking website as a gateway control for posting images. The goal of this paper is to preserve user privacy by preventing their images from being posted on social networking sites without prior consent. This tool will extract features from an input photo posted on a social network site and compare those attributes against the facial characteristics of photos in a prohibited dataset, which is comprised of users unwilling to share their photos. Depending on the result, the CNN-based tool could either allow sharing of the photo or prevent and alert the user attempting to post or share a given photo about his/her potential violation of end-user privacy provided the image belongs to a person on the banned list. Additionally, the CNN tool will provide an option for a user to add his/her photo to the banned list. The proposed tool includes two main elements which have been developed in Python with Jupyter Notebook. The first component is a deep learning model which is trained on LFW images dataset capable of achieving 91.89% matching accuracy. The second is the GUI of the tool which allows the user to input photos and use the trained model to predict whether this photo belongs to the person in banned list, thus preventing illicit sharing downstream. The integration between two elements has been tested and achieved 85% accuracy. Keywords: Deep Learning, Face Recognition (FR), Convolution Neural Networks (CNNs), Online Social Networks (OSNs), Online Photo Sharing.
Steganographic Method Image Security Based on Optimal Pixel Adjustment Process and Integer Wavelet Transform

: This article proposes a novel steganography scheme based on Integer Wavelet Transform and Optimal Pixel Adjustment Process. The novel scheme embeds data in integer wavelet transform coefficients in an 8x8 block on the cover image. The Optimal Pixel Adjustment Process (OPAP) is applied after embedding the message. The frequency domain is employed to increase the robustness of the steganography method. The Integer wavelet transform (IWT) avoids the floating point precision problems of the wavelet filter. This research work uses IWT and OPAP to obtain an optimal mapping function to reduce the difference error between the cover and the stego-image which increases the hiding capacity with low distortions and Peak Signal to Noise Ratio (PSNR).
Cytogenetic and Biochemical effects of Metenix on Albino Male Mice

Background: Metenix (metolazone) is a new antihypertensive, it is effective in the treatment of patients with high blood pressure, heart failure and edema. The aim of the study is to evaluate the cytogenetic and biochemical effects of metenix. Materials and methods: Study sample (Male adult albino mice) was divided into two major groups;treated group and matched control. Treated group adminstred orally doses of (0.01, 0.02) and 0.04mg (kg) of metenix for 10 consecutive days.Control did not receive any treatment. All treated groups and control were sacrificed 24h after the last treatment the incidences of sperm head abnormalities and chromosomal aberrations in (bone marrow and spermatocytes, were determined in all treated groups. Results showed that (metenix) caused a significant increase in the frequencies of abnormal sperms and chromosomal aberrations in (somatic and germ cells, in all treated groups compared with control and these increases were dose dependent. The biochemical analysis (nucleic acids and total protein) were examined in the livers of treated animals. The results stowed that there was significant decrease in the nucleic acids and total protein content in the livers of treated animals compared with control; these decreases were dose dependent. The data obtained in this study suggested that (metenix) should be used under medical control due to its cytogenetic and biochemical toxic effects on male albino mice. [New York Science Journal 2010; 3(6):127-132]. (ISSN 1554 – 0200).
A DESIGN OF LOW POWE TRANSCONDUCTANCE OPE AMPLIFIER USING MULT WOLF OPTIMIZATION TE

In real world signal processing systems, the operational amplifier is the main block for detecting the analog signal. This paper presents a multi optimization technique for the optimal sizing of Transconduc amplifier. By using multi-CMOS folded cascode operational transconductance amplifier that operates at low voltage is designed for signal processing application. The MOGWO is a swarm intelligence based optimization algorithm has ability to explore the search space of an optimization problem. The objective functions and user defined specifications of proposed circuit can be modeled as optimization problem. The proposed method is a model based design optimization technique used to generate the transistor size and input bias current in an amplifier circuit. This paper mainly focuses on DC gain, unity gain bandwidth and slew rate of an amplifier without affecting other circuit performances. Finally, the optimally designed amplifier has 80.2 dB DC gain, 40 degree phase margin and 452 MHz unity gain bandwidth
THE ACOUSTO-ULTRASONIC TECHNIQUE: A REVIEW

This paper reviews the nature and underlying principle of the Acousto Ultrasonic approach. Acousto – Ultrasonic (AU) is a relatively new NDE approach that originates from the techniques of Acoustic Emission (AE) and conventional Ultrasonics. AU uses external ultrasonic inputs to resemble AE waves in the material without destructively disrupting the material microstructure. Thus, the AU technique is based on the concept of Stress Wave interaction with the microstructure for detecting and depicting the variations of mechanical properties. Unlike most NDE, Acousto Ultrasonic is less concerned with flaw detection than with the assessment of the collective effects of various flaws and material irregularity. Acousto Ultrasonic technique has been applied to the laminated fiber reinforced composites and filament wound fiber reinforced composites. It has been used to assess the significant strength and toughness reducing effects that can be worked by combinations of essentially minor flaws and diffuse flaw populations. Acousto Ultrasonic assesses integrated defect states and the resultant variations in properties such as tensile, shear, and flexural strengths and fracture resistance. Matrix cure state, porosity, fiber orientation, fiber volume fraction, fiber matrix bonding, and inter laminar bond quality are factors that underline acousto-ultrasonic evaluations. Compared with the AE Technique, AU Technique has the advantages that the component under examination does not have to be stressed. This result proved the AU Technique a truly non – destructive testing.
Authentication Techniques in Cloud and Mobile Cloud Computing

A major challenge in cloud and mobile cloud computing is to ensure security and privacy of user’s personal information (e.g., financial data, health record, location information) from malicious attacks. It is important for a cloud service provider (CSP) to establish trust and gain confidence by providing proper security and privacy to the clients. Authentication is important for establishing accountability and authorization of the users while allocating cloud resources. Researchers have proposed several techniques, such as token-based, image and biometric based, to make the authentication process more efficient, secure and user friendly. In this paper, we discuss different authentication techniques proposed for both cloud and mobile cloud computing environments. We categorize the algorithms based on its input, i.e. the credentials required for validating users. However, we emphasize that the classification is not precise, as it is difficult to classify the authentication algorithms relying on more than one user credentials (multi-factor authentication). To understand the complexity and delay of an authentication process, we focus on the number of entities involved in an authentication process and the number of handshakes taking place between them. We also compare the authentication algorithms on the basis of design principles and popular security attacks.
Analysis on Visual Cryptography for Color Image with Error Diffusion

-This paper proposes an analysis on the concept of visual cryptography which is applicable on color images. This analysis includes review on color visual cryptography which involves visual information pixel (VIP) synchronization and error diffusion for color visual cryptography. VIP carries visual information of original image and VIP synchronization helps to keep the same position of pixels throughout the color channels. Error diffusion generates shares which are clear and visible to human eyes and it improves the visibility of shares.
Randomize Dissemination Path for Secure Data Transmission in Mobile Ad-Hoc Network

 Abstract— Mobile ad hoc network (MANET) is an autonomous system of mobile nodes. The nodes are free to move arbitrarily. Due to lack of a centralized secure infrastructure, the communication is prone to security attacks and the nodes can be easily compromised. Security has become one of the major issues for data communication over wired and wireless networks so various security-enhanced measures have been proposed to improve the security of data transmission over public networks. The objective of proposed work is to improve routing security we propose a proactive mechanism as Randomized routing that explores the existence of multiple routes and forces packets to take alternate paths randomly from its neighbors that is a Randomize delivery path for secure data transmission. We maintain neighboring nodes of each node by sending hello packets. Then we find out delivery path from neighboring nodes by random operation excluding previous hop which is maintained as history node. Protocol RDSDV is implemented to randomize delivery paths and compared the proactive routing protocols DSDV and RDSDV for different number of nodes. The performance of these protocols is measured under a Particular scenario on the basis of three metrics as Packet delivery ratio, e2e delay and jitter.
An Approach to Bodo Document Clustering

: Searching a document from the huge collection all over the internet is becoming a challenge. Like other languages Bodo language also providing content to the electronic world. Bodo is widely used in the North Eastern states of India. As text documents are increasing exponentially across the web, grouping similar documents for versatile applications suffers from challenges in dealing with problems of high dimensionality, scalability, accuracy and meaningful cluster label. Clustering of documents has many effective points in information retrieval and data mining field. However, in this presentation a practical approach for clustering of Bodo documents are implemented in order to find suitable clustering technique specifically for this purpose.
A Rotation-free Isogeometric Analysis for Composite Sandwich Thin Plates

In this paper, a rotation-free isogeometric formulation for static analysis of composite sandwich plates is presented. The idea relies on a combination of isogeometric analysis with a classical laminate plate theory (CLPT). Isogeometric analysis (IGA) based on non-uniform rational B-spline(NURBS) basic function was recently proposed to preserve exact geometries and to enhance very significantly the accuracy of the traditional finite elements. B-splines basis functions (or NURBS) is used to represent for both geometric and field variable approximat ions, which provide a flexib le way to make refinement and degree elevation. They enable us to achieve easily the s moothness with arbitrary continuity order compared with the traditional FEM. CLPT ignores the transvers e shear deformation so it is only applied for thin plates. In our formulation, only deflection variab les (without rotational degrees of freedom (dof)) are used for each control point. Essential displacements and rotations boundary conditions can be satisfied strongly by assigning control variable values on the boundary and these adjacent to the boundary, respectively. Several numerical examples are illustrated to demonstrate the performance of the present method in comparison with other published methods.
RECOGNITION OF SURGICALLY ALTERED FACE IMAGES

- Plastic surgery procedures provide a procuring way to enhance the facial appearance by correcting efficient and feature anomalies and treating facial skin to get a younger look. The effects of change in illumination direction, plastic surgery procedures induce intra face (face image versions of the same person) dissimilarity, which are obstruction to robust face recognition. The most challenging task for face recognition in these application scenarios is the development of robust face recognition systems. In this research, we have designed a multiple granular algorithm to match face images of a person before and after his plastic surgery. A total of 40 face granules are extracted from each of the images and the granules are compared. Based on the comparison of the two images a decision is made.