Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Method For Discrimination Prevention Using Differentiated Virtual Passwords And Secret Little Functions

: In classification, discrimination is a type of treatment that includes denying the membership in one group opportunities that are available in another group. Discrimination based on age, religion, gender, caste, disability, employment, language, race and nationality. In this technique, direct and indirect discrimination is prevented using rule protection and rule generalization methods and BIRCH (Balanced Iterative Reducing and Clustering using Hierarchies) is used to perform hierarchical clustering for huge data-sets. To enhance privacy, we propose a virtual password concept to secure user‘s passwords in banking process. We applied user-determined randomized linear generation functions to secure user‘s passwords based on the fact that a server has more information than any adversary does. We are evaluating metrics for proposed methods that impact on information loss and data quality in data mining.
Load Balancing in Software Defined Networking: A Review

Software Defined Networking is an adaptable way of networking, which disconnects data forwarding plane and control-plane of system equipment’s and also solves issues in existing network infrastructure. More specifically, the control-plane of software defined network decides the advancing way of network flow with Centralized Control Manner (CCM). SDN (Software Defined Networking) is a strategy for making, planning and overseeing systems which intend to change this present unfortunate circumstance. It has been used in dissimilar areas, like a campus networks and data center systems. In this survey paper, we’ve reviewed the concept of (SDNs) Software Defined Networks, its architecture and applications. In the survey, it has been found that SDN load balancing has become more smart and efficient and reduces the statistic collection overhead and maintain better QoS (Quality of Service) data rates. In addition, we reviewed the direct routing based algorithms of Load Balancer and compare with Round Robin Strategy. Furthermore, we’ve reviewed and compared the existing work to get better idea about the concept of Load balancing.
Improving LEACH Protocol in Wireless Sensor Networks

With the growing utilization of Wireless Sensor Networks (WSN) in more and more areas, data transfer security becomes a important issue in research area. The secret key cryptography is not capable to offer security in WSN provided the nature of deployment area in the most applications This paper introduces a new version of LEACH protocol known as VLEACH which targets to decrease energy consumption throughout the wireless network. We measure both LEACH and V-LEACH by extensive simulations employing OMNET++ simulator which indicates that VLEACH performs better as compared to LEACH protocol .
Automatic Number Plate Recognition System using Template Matching and Euclidian Distance

— In the present world, the increase in the use of vehicles and automobiles are very useful for our day to day life. For the identification and classification of different vehicles according to the owner, vehicle type and region where the vehicle is used, we use the number plate. By the increase in the number of vehicles, the law enforcement and classification of vehicles are a great challenge to the authority. So the use of automatic number plate recognition system has a very important role in the current scenario. There are several types of research and methods are used to implement the recognition of numbers from the images such as optical character recognition (OCR) etc. But by using those methods there are several limitations for the identification of numbers and also classification of numbers with the characters which are in the same shape. Here we use a new method for the number plate recognition which done by the template matching by calculating the Euclidian distance between the current input and the template. We are also done some morphological operations on the input number plate image. By using this method, we got an 85% accuracy in the local images that we took in number plates having different dimensions and different background colours.
The Study of Cyanobacterial Flora from Lamazan Hot Springs of West Hormozgan , Iran

Cyanobacteria, known as blue-green algae, blue-green bacteria, cyanoprokaryots, and cyanophytes, are oxygenic photosynthetic prokaryotes Cyanobacteria show considerable morphological diversity. They are morphologically, physiologically and metabolically very diverse group and have been the thrust area for investigation since long. The blue-green algae are considered to be thermophilic when part or all of their optimal growth temperature range is above 40°C. Only a few species of eucaryotic protists or animals tolerate higher temperatures. Hot springs and their drain ways provide the most abundant aquatic habitats for thermophilic blue-green algae. Therefore, The present investigation involves study of mat forming cyanobacterial flora from Lamazan hot springs located in west part of Hormozgan province. This thermal spring are inhabited by characteristic thermophilic organisms including cyanophyta. Cyanophyta are among the few organisms that can occupy high temperature aquatic environments including hot springs. In alkaline and neutral hot springs and streams flowing from them cyanophyta can form thick colourful mats that exhibit banding patterns. Sampling was done based on temperature gradients; physicochemical analysis of the water was performed due to a dramatic effect on species distribution, Samples collected at different temperature ranges and were divided into two parts, One part was fixed in 4% formaldehyde to minimize quantitative and qualitative changes in phytoplankton and the other part were kept in a refrigerator for provide the pure isolates. Taxonomic determination was carried out by morphometric study of the isolates with light microscopy, based on Desikachary, Prescott, Whitford and Schumacher, John et al. and Wehr et al. by prepared semi-permanent slides. The vegetative and reproductive characters used in the taxonomic determination were: shape, colour and size of the cell, colony, thallus and trichome; as well as their width and length; shape, size and colour of vegetative cells. As result of this study, Total of 23 thermophilic cyanobacterial species representing 2 orders, 6 families and 10 genera were recorded.
Survey on Dynamic Query Forms for Database Queries

: The databases used in today’s scientific research and web handle huge volumes of data. Such databases contain hundreds or even thousands of complex relations and attributes. The proposed system that implements dynamic query forms for non-relational data. The DQF captures a user’s preference and ranks query form components which assists the user in making decisions. Query form generation is an iterative process and initially requires user guidance in the form of feedback . The system automatically generates ranking list of form components, at each iteration and the desired form components are added by the user in Query forms. The ranking of form components depend on the captured user preference. The query results can be viewed at each iteration by the user after filling and submitting the query form. In order to measure the quality of the results generated by the Query form, a probabilistic model has been developed.
Detection of Optical nerve head by using Gabor and Mean filter

The fundus images is manually graded by the specialized clinicians which is very time consuming resource intensive process, so the motivation behind the work is to provide immediate detection and characterization of retinal feature before the specialist inspection. Optical nerve head provide an important anatomical landmark in analysis of retinal disease such as Glaucoma detection, measurement of vessel tortuosity and exudates region and for the screening programs for diabetic retinopathy of prematurity in fundus image of eyes. It is also important landmark to identify the other anatomical parts such as fovea, blood vessels (as it provides the starting point) and other task. The ONH is the entry point for the optical nerves and blood vessel supplying the retina so the center is the point of convergence of main blood vessels . It is present on the nasal side of fundus image . In normal eye it is the brightest, slightly oval disk measuring about 2mm in diameter. The approach used here is based on the detection of vascular tree as a source of reference to locate the ONH. Here after doing the basic preprocessing, in order to detect the vascular tree the resultant is fed to the gabor wavelet. Gabor functions are sinusoidally modulated Gaussian functions that provide optimal localization in both the frequency and space domains. The resultant is then applied to local mean filter of size 30X30. The pixel returning highest intensity value is considered as ONH. This method gave 100% result when applied to DRIVE database and 61.7% when applied to STARE database.
Human Factors Reliability Analysis Using Fuzzy Fault Tree

— In order to ensure effective prevention of harmful events, the risk assessment process cannot ignore the role of humans in the dynamics of accidental events and thus the seriousness of the consequences that may derive from them. Human reliability analysis (HRA) involves the use of qualitative and quantitative methods to assess the human contribution to risk. HRA techniques have been developed in order to provide human error probability values associated with operators’ tasks to be included within the broader context of system risk assessment, and are aimed at reducing the probability of accidental events. Fault tree analysis (FTA) is a graphical model that displays the various combinations of equipment failures and human errors that can result in the main system failure of interest. FTA is a risk analysis technique to assess likelihood (in a probabilistic context) of an event. The objective data available to estimate the likelihood is often missing, and even if available, is subject to incompleteness and imprecision or vagueness. Without addressing incompleteness and imprecision in the available data, FTA and subsequent risk analysis give a false impression of precision and correctness that undermines the overall credibility of the process. To solve this problem, qualitative justification in the context of failure possibilities can be used as alternative for quantitative justification. In this paper, we introduce the approach of fuzzy reliability as solution for fault tree analysis drawbacks. A new fuzzy fault tree method is proposed for the analysis of human reliability based on fuzzy sets and fuzzy operations t-norms, co-norms, defuuzzification, and fuzzy failure probability.
Mining of High Dimensional Data using Feature Selection

— Data mining techniques have been far and wide useful to extract knowledge from large databases. Data mining searches for associations and worldwide patterns that exist in large databases that are hidden among the high dimensional data. Feature selection involves selecting the most useful features from the given data set and reduces dimensionality. Graph clustering method is used for feature selection. Features which are most relevant to the target class and independent of other are selected from the cluster. The features selected from the cluster are given to the classifiers to increase the learning accuracy and achieve best feature subset. The feature selection can be competent and effectual using clustering approach considering time and quality of data respectively.
A Novel Multi Copy Routing Scheme for Delay Tolerant Networks

: A delay tolerant network (DTN) is a network designed to operate effectively over extreme distances such as those encountered in space communications or on an interplanetary scale. In such an environment, long latency -- sometimes measured in minutes, hours or days -- is inevitable. However, similar problems can also occur over more modest distances when interference is extreme or the network resources are severely overburdened. DTNs involves some of the same technologies as are used in a disruption-tolerant network b ut there are important distinctions. A DTN requires hardware that can store large amounts of data. Such media must be able to survive extended system restarts and power loss. This paper presents a multi-copy routing method for DTNs. For this we introduce a novel DTN routing protocol, called Self Adaptive Utility-based Routing Protocol (SAURP) that aims to overcome the shortcomings of the previously reported multi-copy schemes. Our main goal is to achieve a superb applicability to the DTN scenario with densely distributed hand-held devices. The main feature of SAURP method is the strong capability in adaptation to the fluctuation of network status, traffic patterns/characteristics, user encounter behaviors, and user resource availability, so as to improve network performance in terms of message delivery delay, message delivery ratio, and number of transmissions.
Performance Evaluation Analysis Of An Interference Alignment Based Precoding In Mimo-Ofdm System

Although tremendous progress has made in the past years to eliminate the inter-block interference (IBI) but still it is considered as area of concern in orthogonal frequency division multiplexing system. We proposed interference alignment based channel independent precoding in MIMO OFDM system. We showed that when the number of receive antennas ( n r ) is not more than the number of transmit antennas ( n t ), our proposed precoding is more bandwidth efficient than the conventional zero-padded or CP added MIMO systems, such as, ZP-only, CP-OFDM and SC-FDE system and When the number of receive antennas is more than the number of transmit antennas, it was shown that the IBI in an MIMO OFDM system can be completely eliminated without any CP or zero-padding or precoding, when the OFDM block size is not too small. In this paper, we consider only CP based block transmission system.
Causality of Audit Expectation Gap and Corporate Performance in Nigeria

This study examined the relationship between Audit Expectation Gap and firms’ performance in Nigeria which arises as a result of the several differences between the auditors’ role as defined by law and the perceived role of the Auditor by the users of audited financial statement of companies. Cross sectional field survey of the quasi-experimental research design was used in this study because the survey relied on a sample of elements from the population of interest. Secondary data was also used to corroborate the primary data. Diagnostic analysis, augmented Dickey-Fuller analysis, regression analysis and granger causality analysis were used to test the implications the independent variables have on the dependent variables. The results showed that the variation in earnings per share and return on capital employed was attributable to the variation in detection of error and fraud and opinion of auditors in the audited financial statement and that the independent variables granger cause the dependent variables. The study concludes that EPS is significantly influenced by prevention of error and fraud in audited financial statements. Therefore the study recommends, among others, that the Audit profession should accept additional or modified responsibilities demanded by the users of audited Accounts in order to further improve EPS and audit-cost-benefit value. Also necessary is the use of engagement letter as an appendix to Audited Accounts to explain and create awareness to the users of Annual Accounts of what the CAMA, 1990 requires the duties of auditors to be and what the auditors believes his legal duties entail . Keywords: Audit, Expectation Gap, Corporate Performance, Causality, Nigeria
Development of Mushroom Expert System Based on SVM Classifier and Naive Bayes Classifier

criterion through the analysis of data. Support vector machine (SVM) is the machine learning algorithm used for creating the classification model from training data. In this paper, Support Vector Machine and Naïve Bayes algorithms are used for classification of mushrooms. Mushroom Expert System is developed for classification of mushrooms and to predict the class of mushrooms on submission of characteristics of the mushrooms. Programmed interviews are conducted with domain experts to build the knowledge base for the mushroom expert system. Performances of both algorithms are evaluated on mushroom data in fold cross-validation. This system is a web based application for online users and developed with JSP as front end and MySQL as backend.
A comparative study of sequential pattern mining algorithms

The concept of sequence Data Mining was first introduced by Rakesh Agrawal and Ramakrishnan Srikanth in the year 1995. Sequential pattern mining are used in broad applications. It is used to uncover all sequential pattern which satisfy the user specified constraint, from the given sequence database. However, it is also a difficult to generate and examine a number of intermediate sub-sequences. Sequential pattern mining is the method of finding interesting sequential patterns among the large database. The application can be used in various domain like natural disaster, sales record analysis, marketing strategy, shopping sequences, medical treatment and DNA sequences etc. This paper presents the traditional sequential pattern mining algorithms. The sequential pattern mining algorithms are classified into four classes: First, on the basis of Apriori-based algorithm, Second on Breadth First search-strategy, third on Depth First search-strategy and fourth, on Sequential closed-pattern algorithm. The surveys of all these algorithms are made on the basis on of various research perspectives. First algorithms are categorized using various approaches to solve the mining problem and then algorithms are compared each one with another by their various provided features and performance point of view.
Entropy based Intrusion Detection System in Hybrid Cloud

The principle objective of Denial-of-Service (DoS) assaults is to restrain or much more terrible keep genuine clients from getting to organize assets, administrations, and data. To defeat the deformities of the DOS assault we fundamental plan an IDS. An Intrusion revelation structure (IDS) is a device or software application that screens a framework or systems for harmful activity or course of action encroachment. In this paper, we propose another element choice technique on recognizing a portion of the potential traits of a DoS assault dependent on processed load for every one of the qualities utilizing entropy estimation and recursive component end. We apply one of the proficient classifier choice tree calculation for assessing highlight decrease technique. Choice Tree is the basic methods connected to interruption discovery framework and keep the assaults from the interlopers. The NSL-KDD informational collection is the refined variant of the KDD cup99 informational collection. Numerous sorts of examination have been completed by numerous specialists on the NSL-KDD dataset utilizing diverse strategies and apparatuses with a general target to build up a compelling interruption identification framework
Gold Nanoparticles: Applications in Photo-Thermal Therapy (PTT)

Nano-technology has entered the field of medicine in recent decades and many of the nanomaterials developed have already had a high impact on health care. Among nanomaterials, gold nanoparticles (GNPs) are receiving significant attention because their unique physical, chemical, and biological properties are quite different from the bulk of their counterparts. In this article, after a brief historical overview, the applications of Nano-gold and the methods of its preparation are reviewed, this review particularly deals the use of GNPs in photo thermal therapy. © 2018 ijrei.com. All rights reserved
QUERY OPTIMIZATION USING INDEX JOINS FOR PERFORMANCE GAIN IN HIVE

— The Index joins are crucial for efficiency and scalability when processing the queries over big data. Hive being a batch oriented big data management engine that is well suited for data analysis application and for OLAP. For every “selective” query whose output sizes are small fraction from the contributing data, there the brute-force suffers from poor performance because of redundant disk I/O operations or lead to initiations of extra map operations. Here in this paper an attempt is made and propose index join technique to speed up the query process and integrate it in Hive by mapping our design to the conceptual optimization flow. To evaluate the performance, we create and evaluate test queries on datasets generated using TPC-H benchmark. The results indicate significant performance gain over relatively large data sets and/or high selective queries having a two-way join and a single join condition.
Deficient Human Aspects in Current Multimedia Indexing and Retrieval (MIR) of Large Social Networks Databases

An inside look at the contents of social networks databases shows a significant diversion from traditional database contents and functionality. There is also enormous evidences that Social networks are changing the way multimedia content is shared on the web, by allowing users to upload their photos, videos, and audio content, produced by any means of digital recorders such as mobile/smart-phones, and web/digital cameras. In this article, an overview of multimedia indexing and searching algorithms, following the data growth curve is presented in detail. This paper concludes with the social aspects and new, interesting views on multimedia retrieval in the large social media databases. Keywords : multimedia, indexing, social media, algorithms social networks, databases, retrieval
Closing gaps for performing a risk assessment on Listeria monocytogenes in ready‐to‐eat (RTE) foods: activity 3, the comparison of isolates from different compartments along the food chain, and from humans using whole genome sequencing (WGS) analysis

We would like to thank all the persons and institutes that have provided the project with isolates and accompanying information. Without them, this project would not have been possible. Lin Cathrine T. Brandal, Norwegian Institute of Public Health, Norway Julio Vazquez Moreno and Raquel Abad Torreblanca, Instituto de Salud Carlos III, Spain Marc Lecuit, Institut Pasteur, France Alexandre Leclercq, Institut Pasteur, France Iva Hristova, National Center of Infectious and Parasitic Diseases, Bulgaria Marija Trkov, National Laboratory of Health, Environment and Food, Slovenia Cecilia Jernberg, Public Health Agency of Sweden, Sweden Ariane Pietzka, Austrian Agency for Health and Food Safety, Austria Eelco Franz and Ingrid Friesema, RIVM, The Netherlands Carlo Spanu, University of Sassari Sardinia Ifip, French Institute for Pig and Pork Industry, Maisons-Alfort, France All the NRLs for providing the isolates from the EU baseline study Special thanks to Sylvain Brisse and Alexandra Moura, Institut Pasteur, France, for providing cgMLST data. The authors would also like to thank the EFSA staff members: Maria Teresa da Silva Felicio, Beatriz Guerra, Ernesto Liebana and Valentina Rizzi as well as the members of the Working Group on Listeria monocytogenes contamination of ready-to-eat foods: Kostas Koutsoumanis, Roland Lindqvist, Moez Sanaa, Panagiotis Skandamis, Niko Speybroek, Johanna Takkinen and Martin Wagner for the support, revisions and suggestions during the development of the present procurement activity and report.
Anti-diabetic effect of methanolic leaf extract of Pongamia pinnata on streptozotocin induced diabetic rats

Selvaraju Kavipriya, Narayanaswamy Tamilselvan, Thirunavukkarasu Thirumalai, Gangaipillai Arumugam Department of Biochemistry, Adhiparasakthi college of Arts and Science, Kalavai, Tamilnadu, India Division of Biomolecules and Genetic Division, VIT University, Vellore, Tamilnadu, India P.G and Research, Department of Zoology, Voorhees College, Vellore-632001, Tamilnadu, India Journal of Coastal Life Medicine 2013; 1(2): 113-117