Miracle-dz/UniFAR-FTUs huggingface dataset:
Removal of Random Value Impulse Noise using Various Filters: A Review

— Digital image processing is significant in many areas. Noise detection and rectification in digital images is beneficial in many areas.In this paper we survey on efficient method for the removal of random valued impulse noise. Here applying a detection process and a filtering process. Detection process detects the noisy pixels by using the absolute difference and median filter for filtering. Removal of random valued impulse noise in digital images with edge preservation is one of the difficult tasks in digital image processing areas. For rectification of impulse noise as well as preserve edge implements a new filter that is Dual Threshold Median Filter (DTMF). The removal of impulse noise is applicable in two main stages, firstly, the rectification of the impulse noise on the basis of high and low value of pixels in a 3X3 window. The detection of impulse noise by using of median filter. In the filtering stage, the noiseless pixels remain constant in the low noise frequency, but in case of high noise frequency that is complex of identify the noisy pixel or edge of the image, this complexity is rectify by our new filter mechanism approach.
Int. J. Biosci

β-galactosidase production is carried out using lactose or lactose rich substrates like whey. Tamarind seed powder has not been reported as a substrate for production of this enzyme before. In this study, statistical optimization of medium components for production of β-galactosidase, using tamarind seed powder, by Aspergillus terreus was attempted. Screening for the effects of eleven medium components on enzyme activity was carried out by PlackettBurman design which showed that NH4(SO4)2, lactose and MgSO4 has significant (p<0.001) positive influence and pH, yeast extract, maltose and NaNO3 has significant negative influence. Optimal levels of positively influencing parameters were determined by ridge analysis and was found to be 2.97, 2.88 and 2.67 g/L of NH4(SO4)2, lactose and MgSO4 respectively. In the optimized medium, enzyme activity increased 2.8 folds in comparison with basal medium. Improved activity, being achieved by the use of a cheaper substrate, could reduce the cost of production of the enzyme. *Corresponding Author: Raghunath Rashmi  rashmikrishna1@yahoo.co.in International Journal of Biosciences (IJB) ISSN: 2220-6655 (Print) 2222-5234 (Online) Vol. 1, No. 6, p. 119-127, 2011 http://www.innspub. net
Impacts of gender and farmers’ level of education on access to agricultural extension services in Abuja, Nigeria

The study examined the impacts of gender and farmers’ level of education on access to agricultural extension services in Abuja. A purposive technique was adopted for sample selection while semistructured questionnaires were used for data collection. A sample of 80 rural male and female farmers who had post secondary, secondary, primary and no formal school education were used for the study. In each of the four educational categories, 10 male and 10 female farmers were selected. Two-way analysis of variance was used for data analysis and results indicated that irrespective of education, there was no significant difference (p > 0.05) in gender access to agricultural extension services. But, the mean response (3.03) indicated that female farmers had slightly more access to agricultural extension services than their male counterparts (2.98). Similarly, irrespective of gender, there was no significant (p > 0.05) effect of farmers’ level of education on access to agricultural extension services. Remarkably, farmers who had no formal school education had more access (3.40) to agricultural extension services than farmers who had at least primary school education. Furthermore, there was no significant (p > 0.05) interaction effect of gender and education on farmers’ access to agricultural extension services. Based on the findings, the paper concluded that gender and level of education were not major determinants of farmers’ access to agricultural extension services in the study area.
Role of Page ranking algorithm in Searching the Web: A Survey

: Web mining is awidely used research area today. Web pages that exist today, search engines assume an important role inthe current Internet.Finding relevant pages for any search topic, the number of results returned is often too big to be carefully explored. An application of Web mining can be seen in the case of search engines.Search engines typically linked to pages contains highest keyword value, which meant people could game the system by repeating the same phrase over and over to attract higher search page results. Most of the search engines are ranking their search results in response to users' queries to make their search navigation easier. The role of ranking algorithms is thus crucial: select the pages that are most likely be able to satisfy the user’s needs, and bring them in the top positions. In this paper, a survey of page ranking algorithms is discussed; we will cover the most popular algorithms usedtoday by the search engines: PageRank, N-stepPageRank, Weighted PageRank Algorithm, HITS etc.
Artificial Neural Network Approach with Back Propagations for Modelling SS-removal in GMF

— In this paper, removal efficiency of suspended solid SS from water was investigated in glasses media filter called GMF. Removal efficiency of SS is obtained by using laboratory glasses media filter "GMF" where this efficiency is used as target function in Artificial neural networks . The remain characteristics are used as input parameters for ANNs where these parameters include raw water quality, operation conditions and glasses media characteristics. The model result showed that optimal number of neurons is nine neurons. As a final observations, the study shows that Artificial neural networks with back propagation algorithm is a good tool that can be used in Prediction Removal efficiency of GMF whereas the results was indicated that the BP model has good convergence performance during training, and the predictions of outflow suspended solid removal efficiency coincided well with the measured values.
Recognition Of Traffic Symbols Using K-Means And Shape Analysis

The traffic symbol recognition system plays an important role in recognition of traffic symbol.The proposed traffic symbol recognition system is based on color image segmentation with the integration of shape analysis. The presented system is robust, which is able to recognize traffic symbols with any color and any of the existing shapes (e.g., circular, rectangular, triangular, pentagonal, and octagonal) and is invariant to transformation (e.g., translation, scale and occlusion). The proposed system uses two different methods Peri2Area and boundary touching point for analyzing different shapes of the traffic symbol and the correlation coefficient pattern matching for the recognition of the traffic symbols. There are three main stages in the proposed algorithm: 1) segmentation by clustering the pixels based on the color features to find the regions of interest (ROIs); 2) traffic-sign detection by using two novel shape classiffication criteria, i.e., the relationship between area and perimeter and the boundary touching point 3) recognition of the traffic symbol using correlation coefficient to match the unknown symbols with the known reference traffic symbols stored in the database. The proposed framework provides a novel way to detect a traffic symbol by integrating image features with the geometric shape information. Experimental results on real-life images show a high success rate and a very low false hit rate. KeywordsClustering, boundary Point Touching (BPT), correlation coefficient, segmentation
An Embedding Model for Mining Human Trajectory Data with Image Sharing

--Location based services are used in positioning enabled devices through Social Media. It is increasing demand in physical world. It gives a many ways to track the record of human mobility, it includes user generated contents and check-in services. Mostly location based social networks have become the digital mirror to human mobility in physical world, which lends an opportunity to understand people’s behavior. A multiple status trajectory Embedding Model used to discover contexts in a systematic way which contains user-level, user-trajectory, user-location and temporal contexts. All this contextual Information provides better understanding between different contexts. This is all done for some selected datasets and has employed for trajectory data which has been already gathered in the database. In research area there is a trend on extraction of trajectory data in data mining and it handle demand of trajectory information. Data clustering is one of the best methods to group the same community data. This paper solves the automatic updation of data which is stored in geo-based applications and improves efficiency.
EVALUATION OF ANTIANXIETY EFFECTS OF DEGLYCYRRHINATED LICORICE ON ALBINO RATS

Context: Glycyrrhiza glabra has antidepressant, anti-stress and antianxiolytic potential. It can be hypothesized that Deglycyrrhinated licorice (DGL) to be effective in anxiety too. Aims: To evaluate the anti-anxiety effects of Deglycyrrhinated licorice (DGL) in albino rats and compare the antianxiety activity of DGL against standard drug diazepam (2-3 mg/kg), using animal models Elevated plus maze (EPM) Light and dark arena (LDA) apparatus Settings and Design: Animals were divided into four groups, each consisting six rats. DGL extract, Diazepam and Saline was given to the test groups and after 45 min, animals were exposed to EPM and light–dark test for normal duration (5 min), sufficient to assess the anxiety levels in rodents. Statistical analysis used: One-way ANOVA. Results: In EPM and Light & dark study DGL 1 group showed antianxiety effect compared to control group, but antianxiety effect is inferior to diazepam group and DGL 2 group possessed very mild insignificant antianxiety effect, which is inferior to both diazepam group and DGL 1 group. Conclusions: Deglycyrrhinated licorice possesses antianxiety effect but inferior to Diazepam and therefore can be used as add on therapy.
Economic Load Dispatch Problem with Valve – Point Effect Using a Binary Bat Algorithm

This paper proposes application of BAT algorithm for solving economic load dispatch problem. BAT algorithmic rule is predicated on the localization characteristics of micro bats. The proposed approach has been examined and tested with the numerical results of economic load dispatch problems with three and five generating units with valve point loading without considering prohibited operating zones and ramp rate limits. The results of the projected BAT formula are compared with that of other techniques such as lambda iteration, GA, PSO, APSO, EP, ABC and basic principle. For each case, the projected algorithmic program outperforms the answer reported for the existing algorithms. Additionally, the promising results show the hardness, quick convergence and potency of the projected technique.
SURVEY ON NEW TRENDS IN FINGER PRINT IDENTIFICATION TECHNOLOGY

: Biometrics innovation, which utilizes physical or behavioural qualities to distinguish users, has come to pull in expanded consideration as a method for dependable individual confirmation that makes a difference set up the character of a genuine client. Among different modalities of biometrics, fingerprints are known not the longest history of genuine use in law authorization applications with demonstrated execution. This paper studies the best in class in unique finger impression distinguishing proof innovation. The present pattern of unique mark detecting and recognizable proof calculations are introduced first in point of interest keeping in mind the end goal to show how unique mark based frameworks function and at that point a few subjects with respect to unique mark distinguishing proof are talked about.
An Improved Security Threat Model for Big Data Life Cycle

- Big data is a huge amount of data created by individuals related to their medical, internet activity, social networking sites, energy usage communication patterns etc. From these sources, data is being collected and processed by various survey organizations, national statistical agencies, medical centres, and other companies etc. There are many security challenges which occur during data transactions, such as un-authentication, phishing, Vishing, data mining based attacks, etc. From a security point of view the biggest challenge for big data is the protection of user’s privacy. Yazan et.al, have presented big data lifecycle threat model. This paper does a critical review of the work. An Improved Security Threat Model for Big Data Life Cycle has been proposed as a main contribution of the paper. A new phase i.e. data creation phase has been added to the life cycle and it is claimed that the phase is very important one with respect to security and privacy. To justify the claim theoretical and statistical evidences have been provided.
A survey: Sentiment Analysis of Online Review

Sentiment Analysis is a new and emerging field of research which deals with information extraction and knowledge discovery from text using Natural Language Processing (NLP) and Data Mining (DM) technique, which help to track the mood of public about specific products and social or political event. Sentiments of individuals are extremely useful for people and company owner for making several decisions. It is intended to survey on sentiment analysis architecture, sentiment analysis type, level and task. This survey deals with machine learning methods that utilized for mining sentiment analysis and Opinion Mining. Keywords— Sentiment Analysis, Opinion Mining, Machine Learning Method, Sentiment Classification, Feature Extraction, Subjectivity Classification
A Review on Energy Efficient Computation Offloading Frameworks for Mobile Cloud Computing

Mobile Cloud Computing is an evolving technology that integrates the concept of cloud computing into the mobile environment. Smartphones are boon in the world of technology but they have certain limitations (e.g. battery life, network bandwidth, storage, energy) when running complex applications which require large computations. Using Cloud Computing in mobile phones, these limitations can be addressed. Certain frameworks have been proposed over the years that can address the issues in mobile cloud computing. These frameworks allow the computation to be offloaded in the cloud environment resulting improvementin the battery life, bandwidth, memory capacity and energy consumption in the smartphones. This paper provides the extensive surveyon the various energy efficient frameworks available to offload the computation from the mobile to the cloud environment.
Negative Binomial and Generalized Poisson Regressions in Dengue Hemorrhagic Fever Data at Central Java 2012

Poisson regression model, also known as Generalized Linear Model (GLM) was one of the most popular techniques for the analysis of count data. One important assumption for the Poisson regression model was the mean of the distribution must be equal to the variance. Inequality mean and variance led to serious underestimation of standard error and misleading inference for the regression parameters. This problems led an overdispersion. This paper proposed the Negative Binomial and Generalized Poisson regression models as alternative for handling overdispersion. The result shown that based on the test for the dispersion parameter and the goodness-of-fit measure for the total number of Dengue Hemorrhagic Fever morbility Data at Central Java 2012, the Generalized Poisson regression model performed better than the other regression models.
CONTROLLER BASED MODEL FOR ACTIVE AND REACTIVE POWER IN PV SYSTEMS DURING UNBALANCED GRID VOLTAGE

1 M.Tech scholar, EEE Department, Radharamam Engineering College, Bhopal 2 H.O. D, EEE Department, Radharamam Engineering College, Bhopal. ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract Now a day the population is increasing day by day, at the same way the industries are also increasing. So the demand for power is also increasing. As the conventional sources of energy are depleting and the cost of energy is rising day by day. In order to minimize the cost and to generate the power the alternative sources of energy are non conventional energy sources. The generated maximum power is delivered to the grid through an inverter. The output power of PV units is not constant during a day; it varies with changes in atmospheric conditions so robustness is essential.
PAPR Reduction with Amplitude Clipping & Filtering, SLM & PTS Techniques for MIMO-OFDM System: A Brief Review

— Nowadays MIMO-OFDM has become a popular technique for 4G wireless communications . OFDM technique combined with multiple antennas at transmitter and receiver point to high data rate, low complexity and diversity. One of the major drawbacks in the MIMO-OFDM is high peak-to-average power ratio (PAPR). Clipping & Filtering, Selective Mapping (SLM), Partial Transmit Sequence (PTS) are some of the techniques which minimizes the PAPR. In this review paper, different techniques of PAPR reduction have been studied.
Accessing Confidential Data in Public Clouds

The user’s perception that the confidentiality of their data is endangered by internal and external attacks is limiting the diffusion of public cloud database services. In this context, the use of cryptography is complicated by high computational costs and restrictions on supported SQL operations over encrypted data. In this paper, we propose an architecture that takes advantage of adaptive encryption mechanisms to guarantee at runtime the best level of data confidentiality for any type of SQL operation. We demonstrate through a large set of experiments that these encryption schemes represent a feasible solution for achieving data confidentiality in public cloud databases, even from a performance point of view.
MATLAB AND SIMULINK LABORATORY – A BASIS FOR LEARNING REAL CONTROL APPLICATIONS

A laboratory for teaching computer programming and engineering concepts related to control applications was recently established in the Department of Electrical Engineering and Electronics at the Ariel University Center of Samaria. The new laboratory provides hands-on experience in the design of control systems used in different fields of engineering. The lab offers an excellent introduction to programming concepts and research concepts that are often troublesome for the undergraduates. This paper describes the general approach and practical application of MATLAB and Simulink in the frame of a laboratory for teaching control. The main aim of the laboratory is to help students gain a deep understanding of typical problems in control applications. Students prepare codes in MATLAB and Simulink, based on knowledge acquired in a preliminary course on the theory of control. These codes are further used to investigate and design various control systems. In this way, control lab assignments with models of various physical processes are performed. Key words: control laboratory, control systems, MATLAB and Simulink, programming.
International Journal of Soft Computing and Engineering

An understanding towards the overlapping syndromes is essential to cope up the liver disease with the paradigm shift which is underway. Autoimmune hepatitis (AIH), primary biliary cirrhosis (PBC) and primary sclerosing cholangitis (PSC) all belong to the family of autoimmune liver diseases. This can result in a transient phenotypic overlap or a combined syndrome with characteristics of both diseases. It demonstrates mixed clinical presentations of immune-mediated liver injury. Due to overlapping features of AIH, some patients connote such phenotype that leads to a dubious diagnosis of any disease. In some cases, this type of diagnosis system causes the patient’s death in the absence of well-validated diagnostic criteria. Some improvements in diagnosis instrumentation and automation that has become to capture experience of any veteran person, is needed. Simulation of such diagnosis experience is extremely important as it leads to knowledge discovery. In this paper, we gave a soft computing model based disease diagnosis system for overlapping syndrome of liver disease. It helped the in physician’s decision process that comes after long experience in new
A REVIEW ON VARIOUS TEXT MINING TECHNIQUES AND ALGORITHMS

Text mining is the method of extracting meaningful information or knowledge or patterns from the available text documents from various sources. The pattern discovery from the text and document organization of document is a well-known problem in data mining. At present world, the amount of stored information has been enormously increasing day by day which is generally in the unstructured form and cannot be used for any processing to extract useful information, so different techniques such as classification, clustering and information extraction are available under the category of text mining. In order to find an efficient and effective technique for text categorization, various techniques of text categorization is recently developed. Some of them are supervised and some of them unsupervised manner of document arrangement. In this paper, focus is text mining process, different method of text categorization, cluster analysis for text documents, the basic differences between relative terminologies on the basis of process, model and the algorithms used, a comparison between text mining techniques on the basis of algorithms, models and tools used. In addition of that a new text mining technique is proposed for future implementation
A Study on the Nutritional Value of Three Plant Species Alhagi (Alhagi persarum), Psyllium (Plantago psyllium), and Artemisia (Artemisia Biennis Wild)

This research has been conducted following the aim of studying the nutritional value of three dominant plant species in Sistan region including Alhagi (Alhagi persarum), Psyllium (Plantago psyllium), and Artemisia (Artemisia Biennis Wild) and the sampling has been done at the vegetative stage. These samples, then, were milled under dry shade conditions and the chemical components of the samples which include: dry matter, organic matter, ash, crud protein, crud fat, cell wall, and ADF were measured in the laboratory. These samples, then, were milled under dry shade conditions and the chemical components of the samples which include: dry matter, organic matter, ash, crud protein, crud fat, cell wall, and ADF were measured in the laboratory. Organic Matter Digestibility (OMD) and Metabolizable Energy (ME) were calculated using the gas production method. The results showed that between these samples, in terms of their chemical components, there is a significant difference (P<0.05). The highest amounts of crud protein and ADF were that of the Artemisia (11.46) and Psyllium (39.98) respectively. The results concluded from the produced amounts of gas (mg) at different incubation hours indicated that the highest and lowest amounts of produced gas were that of Artemisia (67.19) and Psyllium (55.34) respectively. Low cp might be the cause of Psyllium having the lowest amounts of both OMD and ME. Regarding the degradability and effective degradability parameters at different incubation hours, a significant difference was observed (P<0.05). KeywordsForage plants, Gas production, Dry matter degradability, Sistan