Miracle-dz/UniFAR-FTUs huggingface dataset:
DBSCAN-BRNNDE: A Density-based Clustering Algorithm using Bichromatic Reverse nearest Neighbor Density Estimates

: In data mining, clustering algorithms is one of mostly used area for many applications. With the growth of the online applications, studies on cluster development were performed consequently as to reduce noise and sustain continuity of grouping results. Several clustering algorithms have been introduced, such as the evolutionary methods and spectral clustering, however none of the works has been were engaged to solving the density-based clustering problem. Recently new clustering algorithm, RNN-DBSCAN, is introduced which uses RNN counts as an estimate of observation density. But still the accuracy is challenging task, so Density-based Clustering Algorithm using Bichromatic Reverse Nearest Neighbor Density Estimates (DBSCAN-BRNNDE) clustering algorithm is introduced this work with two major steps: First, issues of computation complexity is decreased via the use of a single parameter (choice of Bichromatic k nearest neighbors), and second, an enhanced capability for managing huge variations in terms of cluster density (varied density). To measure the results of DBSCAN-BRNNDE, with respect to existing methods, many artificial datasets are used in this work. Results are evaluated in terms of Adjusted Rand Index (ARI) and Normalized Mutual Information (NMI) , it is implemented in MATLAB environment.
A Model for Document classification using Kernel Discriminant Analysis(KDA) and semantic analysis

In recent days, digital communication has become inevitable. The scope of this research is to provide a theoretical framework of automatically classification of question paper. It can be helpful to the library of any University to automate their archival process. A survey has been conducted to understand the existing systems in this research area. After doing the survey we observed that many authors have done significant work in document classification but little work has been done to automatically store the documents in particular folder. Therefore, there is a huge scope to develop working model of the framework suggested in this paper. Keywords: OCR, Kernel Discriminant Analysis (KDA), Semantic Analysis, document classification, binarization
Prevalence and Antibiotic Susceptibility of Methicillin Resistant Staphylococcus aureus Isolates in a Tertiary Care Centre

Introduction: Staphylococcus aureus produces a wide range of infections from soft skin infections to fatal septicemia. The prevalence of Methicillin resistant Staphylococcus aureus (MRSA) has increased drastically in Indian wards, of many which areresistant to antibiotic treatment. Aim: To study the prevalence rates and antibiogram pattern of MRSA from various clinical samples in a tertiary care Centre. Materials and Methods: A total of 434 various clinical samples received in Microbiology Laboratory, Tertiary care Centre, Chennai was included in study during the period from October 2016 to December 2016. A total 120 Staphylococcus aureus isolated, were identified by standard biochemical methods. Antibiotic susceptibility testing was performed by Kirby Bauer Disc Diffusion method. Methicillin resistance was detected by using cefoxitin (30μg) disc diffusion method as per CLSI guidelines 2016. Result: In our study120 (27.6%) of S.aureus was isolated from various clinical samples, out of which 23.3% were MRSA. MRSA was predominantlyisolated from pus samples. The resistance rate of MRSA isolates to antibiotics were 100% penicillin, 63% cotrimoxazole, 57.8% ciprofloxacin, 52.6% Erythromycin, 42.1% Clindamycin, 31.5% gentamycin and tetracycline, 21.05% amikacin, 3% Linezolid. All strains were sensitive to teicoplanin. Conclusion: Isolation of MRSA patients and carriers in the hospitals, regular surveillance, and monitoring of antibiotic susceptibility pattern of the hospital and community of that region regularly and formulation of antibiotic policy may help in reducing the treatment failures.
Survey on Self Evolving Antivirus Based on Neuro-Fuzzy Inference System

: Over the years and as the result of technological developments, the importance of personal computers in our lives has grown significantly. This has resulted in a desire by some to develop malicious applications, whether lone teenagers or nation states, and distribute them across the Internet where they attack a range of computer systems. As a result, the importance of antivirus software has grown significantly and has resulted in an inexorable demand for a dependable antivirus system that can defend against this plethora of malicious viruses. Anti-virus programs are meant to discern computer viruses and protect computers from their actions. In order to guarantee effectiveness and a robust system, antivirus software must be continuously updated and is a perpetual process. This is no small undertaking when taken into consideration the fact that computers connected to the Internet are exposed to viruses from every direction and are delivered using any range of methods: Infected servers and files, USB drives, and more. With today’s world filled with information and data, it is very important for us to differentiate which information or data is benign and which is malignant. That is exactly what we aim to develop and implement in the form of our research Adaptive anti-virus using ANFIS architecture. An adaptive anti-virus system that will catch up to the speed at which the viruses update and evolve.
Prevention of Leaks and Strictures of Esophago-Organ Anastomosis in Esophagoplasty

1 Professor, Doctor of Medicine, Head of Surgery Department No 1, National Pirogov Memorial Medical University, Vinnytsia, Ukraine. 2 Doctor of Medicine, Associate Professor of Surgery Department, Medical Faculty No 2, National Pirogov Memorial Medical University, Vinnytsia, Ukraine. 3 Post-Graduate Student, Surgery Department No 1, National Pirogov Memorial Medical University, Vinnytsia, Ukraine. International Journal of Surgery and Research (IJSR) ISSN: 2379-156X
Knowledge Discovery in Social Networking for Future Filtering Purposes

Social media has become very popular and is able to generate oceans of data which is a goldmine to prospective researches in the real world. Discovering hidden patterns from such data can provide business intelligence. Mining such social media data and learning collective behavior can have very useful utilities in the real world. Many real world applications like advertising, marketing, sales do have their focus on social networking. Scalable learning of collective behavior is very important research area where as the social media data is very vast. Sustainable solution should promote scalability. Object heterogeneity is one of the challenging aspects that can be incorporated in mining tasks so as to gain actionable knowledge. Recently Tang et al. proposed a solution for this using edge-centric approach. In this paper we are influenced by that work and propose a scheme that can solve the problem of object heterogeneity based on the multi-mode network. With this solution the prediction capabilities of the proposed application will be more. We build an application to demonstrate the proof of concept. The application can predict collective behavior with scalable feature and will be useful in real world applications.
Comparison of Multi-Fractal Antenna with Star Shaped Fractal Antenna for Wireless Applications

This paper presents the comparison of two different fractal antennas. Both the antennas are designed by using FR4 glass epoxy substrate with relative permittivity of 4.4 and 1.6mm thickness. The different parameters such as return loss, VSWR, gain and bandwidth of existing antenna (multi-fractal antenna) are compared with designed antenna (star shaped fractal antenna) which shows that the designed antenna have more better results as compared with the existing antenna. The designed antenna was simulated by using HFSS V13 software and the antenna can be used for different wireless applications such as WLAN, satellite communication, long distance radar telecommunication etc.
DISTANCE BASED RANGE QUERIES

- Nowadays, a Location Based Services (LBS) are gaining more popularity. Spatial data mainly designed to focus on the location-enabled applications and geographic information system. Given a positive value r, a distance-based range query returns the objects that lie within the distance r of the query location. Distance based range queries are continuously change their locations in Euclidean space. In this paper, we continuously monitor the distance based range queries over static and dynamic data objects. Moreover the range query is compared with the kNN query. Our simulation results says that the range query will give the better results compared with kNN query.
Antibiotic Resistance Patterns of Enterococcus faecalis and E. faecium Isolated from Infected Wounds. Incidence of High –level Resistance to Vancomycin and Aminoglycosides

A total of fifty seven isolates of Entercoccus faecalis (N=42) and E. faecium (N=15) from infected wounds were screened for their resistance against 17 antibiotics including vancomycin. E. faecalis isolates demonstrated absolute resistance (100%) against eight antibiotics: chloramphenicol, nalidixic acid, gentamicin, streptomycin, tetracyclin, erythromycin, penicillin G and lincomycin. While isolates of E. faecium revealed absolute resistance (100%) to only three antibiotics: chloramphenicol, nalidixic acid, and lincomycin, yet they exhibited 80% resistance against gentamicin and streptomycin. Higher percentage of resistance against vancomycin was shown by E. faecium (53.3%) as compared to Ent. faecalis (47.6%). E. faecalis and E. faecium isolates were involved in 5 and 2 antibiotic resistance patterns (ARPs) respectively. Of the two species; 24.5% isolates (N=11, 26.2% E. faecalis and N=3, 20% E. faecium ) were included in one ARP demonstrating resistance to all antibiotics under study. High-level resistance to glycopeptides (HLRG) vancomycin (64 μg/ml) was higher among isolates of E. faecium (50%) as compared to E. faecalis (30%). Whereas high-level resistance to aminoglycosides (HLRA): gentamicin (500 μg/ml) and streptomycin (>1000 μg/ml) was higher among E. faecalis against gentamicin (80% VS 62.5%) and almost similar incidence was reported by the two species against streptomycin (60% and 62.5% respectively). Emergence of varied ARPs and high-level resistance to vancomycin and aminoglycosides among E. faecalis and E. faecium isolates will reduce to a great extent the therapeutic options against enterococcal infections. Hence, we emphasizes on the importance of performing susceptibility testing on all clinically significant isolates.
Data-Collection using Clustering Approach in Wireless Sensor Network Design based on Heuristic Algorithms

— Data-gathering wireless sensor networks (WSNs) are operated unattended over long time horizons to collect data in several applications such as those in climate monitoring and a variety of ecological studies. Typically, sensors have limited energy (e.g., an on-board battery) and are subject to the elements in the terrain. In-network operations, which largely involve periodically changing network flow decisions to prolong the network lifetime, are managed remotely, and the collected data are retrieved by a user via internet. In this paper, we study an integrated topology control and routing problem in cluster-based WSNs. To prolong network lifetime via efficient use of the limited energy at the sensors, we adopt a hierarchical network structure with multiple sinks at which the data collected by the sensors are gathered through the cluster heads (CHs). We consider a Particle Swarm Optimization model to optimally determine the sink and CH locations as well as the data flow in the network. Our model effectively utilizes both the position and the energy-level aspects of the sensors while selecting the CHs and avoids the highest-energy sensors or the sensors that are well-positioned sensors with respect to sinks being selected as CHs repeatedly in successive periods
AMAZING ROLE OF SELENIUM IN BIOLOGICAL SYSTEM

Selenium is essential trace element, sulphur analogue with high chemical activity, component of some selenoproteins and enzymes: glutathione peroxidase and other peroxidases, blood and tissue proteins. As to their biological action mechanism selenium and its compounds are antioxidants. Selenium is active immunomodulator, much more potent anti-oxidant than vitamins E, C and A, beta-carotene, but much more toxic. It takes part in thyroxine conversion to triiodethyronine in thyroid hormone biosynthesis. As sperm antioxidant selenium protected its motility and fertility. Selenium is a serious factor of biological and antioxidant protection of vascular endothelium, of low-density lipoproteins, protection of DNA, chromosomes. As food component selenium is an exceptional agent of protection from atherosclerosis, coronary ischemic disease and cancer. Some hydrobionts, liver, kidney, meal, corn and garlic, onion, cabbage, broccoli are dietary products with high content of selenium. Selenium is an essential biological trace element. Adult daily intake of selenium should be approximately 100 μg per day. This compound has a two-sided effect depending on its concentration. A selenium-deficient diet is associated with various endemic diseases, including cardiomuscular malfunctions, osteoarthritis, cancer and viral infections that lead to premature death. These defects are prevented when dietary intake of selenium is adequate. The preventive biological effect of selenium is considered to be due to the antioxidant function of selenoproteins with a selenocysteine in the active site of the catalytic domain. Antioxidant selenoproteins maintain the intracellular redox status and, as a result, normal physiological processes in the cell. Conversely, an overdose of selenium generates oxygen radicals and leads to apoptotic cell death by inducing oxidation and cross-linking of protein thiol groups essential for cell survival. A lower redox state caused by selenium may be implicated in toxic diseases, such as alkali disease and blind staggers. Collectively, selenium seems to have both harmful and beneficial attributes. The aim of this review is to summarize the various biological functions of selenium and to illustrate its opposite roles as a pro-oxidant and an antioxidant.
Atomic Absorption Spectroscopy :A special emphasis on pharmaceutical and other applications

Atomic absorption spectroscopy (AAS) has emerged as a powerful analytical technique in estimating various atoms by the measurement of light energy of specific wavelength. This employs usually three different analytical techniques such as atomic emission, atomic absorption and atomic fluorescence. The AAS can measure even trace concentrations of various elements with higher degree of sensitivity and precision. Therefore, AAS possesses considerable position in the modern analytical laboratories. The present review highlights the various components of atomic absorption spectrophotometer, different types of AAS and applications of atomic absorption spectroscopy in various fields such as pharmaceuticals, food, biological, geological, metallurgical, environmental, forensic and marine applications.
Reusing Vehicular Control Networks as Test Access Mechanism for Automotive Semiconductor Chips

Today, air and road vehicles accommodate several electronic control units (ECUs) to ensure safety, reliability and comfort. Such ECUs are connected through vehicular control networks (VCNs). Typically, integrated circuits are tested for structural defects, which could occur during fabrication. However, the adverse environment in vehicles may develop defects within a chip, which may lead to catastrophe. The work in hand presents test access mechanism for in-vehicle ICs through VCNs and the on-chip test circuitry; moreover, the proposed test access mechanism complies with the VCNs’ protocols. In this paper, two well-known VCNs are considered, i.e., controller area network (CAN) and FlexRay.
Personality Traits as Predictors of General Health among High school Female Students in Bandar Abbas

The current research has been performed due to evaluation of tie personality traits and general health. 205 students have been selected through multi stage random sampling. In order to collect data, NEO personality inventory (1985) and Goldberg & Hiller (1972) general health questionnaire have been applied. Research data were analyzed by Pearson’s correlation and Regression analysis. The results have indicated that there is a positive and significant relationship between personality traits of extraversion, openness (flexibility), agreeableness, conscientiousness and general health of students and there is a negative relationship (p < 0.05) between Neuroticism and general health of students. Neuroticism predicts 0.452 % of variance of general health.
GRAPHOLOGY (TO COPY ANY DOCUMENTS IN USER’S HANDWRITING): A REVIEW

— Graphology or Handwriting analysis is a scientific method of identifying, evaluating and understanding of anyone personality through the strokes and pattern revealed by handwriting. Handwriting reveals the true personality including emotional outlay, honesty, fears and defenses and etc. Handwriting stroke reflects the written trace of each individual's baseline, slant, pressure, letter, size, letter spacing, word spacing, margin, rhythm and Style. The image split into two areas: the handwriting based on three features and application form of letters digit area. In this research performance evaluation is done by calculating mean square error using Back Propagation Neural Network (BPNN). Human behaviour is analyzed on the basis of signature by using neural network. This paper survey efforts to establish a method which reduces human efforts on pen and paper work. Some of based on computational theories—as well as software tools to assists document examiners.
A Comparison of Symmetrical and Asymmetrical Three -Phase Cascaded H -Bridge Multile vel I nverter Using Novel Control Technique for DTC I nduction Moto r Driv es

There are problems in the limitations of conventional inverters, especially in high -voltage and high-power applications. Recently multilevel inverters are becoming increasingly popular for high -power applications due to their improved harmonic profile and increased power ratings. Several studies have been reported on multilevel inverters topologies, control techniques, and applications. However, there are few studies that actually discuss or evaluate the performance of induction motor drives associated with three-phase multilevel inverter. This paper presents a comparison study of symmetrical and asymmetrical for a cascaded H-bridge multilevel using flexible control technique and also direct torque control (DTC) for induction motor drive. In this case, symmetrical and asymmetrical arrangements of five-level, seven-level, nine-level and eleven H-bridge inverters are compared using flexible control technique vector space in order to find an optimum arrangement with lower switching losses and optimized output voltage quality. So, as to decrease the THD value (total harmonic distortion) the number of levels is increased. The experiments show that an asymmetrical configuration provides nearly sinusoidal voltages with very low distortion, using less switching devices. Moreover, torque ripples are greatly reduced by increasing number of levels we can bring step waveform to nearly sinusoidal waveform by decreasing the THD value. Thus ripples are reduced and efficiency is increased.
Human Movement Tacking using Centroid Weighted Kalman Filter

— Video surveillance system supports object classification and object tracking. Object tracking is considered as one of the most important task in video surveillance system. Two key steps in these systems are: detection and frame by frame tracking of object. This paper proposes an illumination-sensitive background modelling approach to detect moving objects. The binary mask of moving objects can be generated by the proposed thresholding function. In the visual object tracking, the Kalman filter produce errors and decreasing estimation precision. In order to enhance the stability, Centroid Weighted Kalman Filter (CWKF) is proposed. The algorithm uses illumination sensitive background subtraction method to detect moving target region, and centroid weighted method to optimize the predictive state value, finally updates observation data according to the corrected state value. This tracking experiment shows that this algorithm can detect effectively moving objects and at the same time it can quickly and accurately track moving objects with good robustness.
Collaborative Filtering Based Recommendation System Augmented with SVM Classifier

A recommendation system is a system that recommends a user or users, the items, possibly, of their interest. There are wide examples of recommendation systems like the recommendation of books on Amazon, or recommendation of movies on some web-portal. A large class of recommended ads that a user sees on some web page comes from the cookie information saved on the user machine. The recommendation system discussed in this paper is the one which is based on the user interest, to the extent accurately as might be possible, based on the profile of the user and the overall rating of the item. Recommendation systems are classified by the mechanism which is used to calculate the affinity between the user and the item. Content based recommendation system recommends the items based on the properties of the similar items. On the other hand, collaborative filtering based system predicts the user interests based on properties of items and users having similar interest. In this paper, colleborative filtering is implemented in conjunction with Support Vector Machine (SVM) based classifier to classify the users having similat interests to model more accurately the user likes and dislikes as compared to collaborative filtering alone. The model proposed in this paper is based on the generic SVM classifier and thus applicable to a large class of items as compared to specific domain-based content filtering. The proposed model is implemented on Netflix movie data and the simulations results are compared with those of benchmark techniques.
Ethno Medicines of Kolli Hills at Namakkal District in Tamilnadu and its significance in Indian Systems of Medicine

1 Ethno Medicines of Kolli Hills at Namakkal District in Tamilnadu and its significance in Indian Systems of Medicine G.Arunachalam, M.Karunanithi N.Subramanian, V.Ravichandran and S.Selvamuthukumar PGP College of Pharmaceutical Science and Research Institute, NH -7, Namakkal Karur Main Road, Namakkal – 637297, Tamilnadu, India. Department of CARISM, SASTRA University, Thanjavur 613402, Tamilnadu, India. Bharathidasan Institute of Technology, Anna University Tiruchrappalli, Tiruchirappalli 620 024, Tamilnadu, India Vels College of Pharmacy, Chennai600 035, Tamilnadu, India Department of Pharmacy, Annamalai University, Annamalai Nagar608002, Tamilnadu, India.