Miracle-dz/UniFAR-FTUs huggingface dataset:
INVESTIGATING THE CORRELATION BETWEEN THE STUDY SKILLS AND ACADEMIC PERFORMANCE IN MASTER STUDENTS AT ISLAMIC AZAD UNIVERSITY OF

MOHAMMADVAFAEENEZHAD, SAFIYEH TAHMASEBI LIMOONI * 1,2: Department of Knowledge and Information Science, Babol Branch, Islamic Azad University, Babol, Iran *Author for Correspondence: Sa.tahmasebi2@gmail.com ABSTRACT The aim of this study is to Determining the correlation between the study skills and academic performance in master students at Islamic Azad University of Sari.This research has analytical-survey type. The standardized Study Skills Inventory by Banville, Desrosiers and Janet-Walt (2000) is the research tool in this study. The reliability of inventory is equal to 0.76 based on Cronbach's alpha. The statistical population consists of 373 subjects (out of 9216) from the master students at Islamic Azad University of Sari during the academic year of 2014-15. The students' GPA is utilized to measure the academic performance. The data analysis is performed through the descriptive statistics (calculating the frequency, percentage of frequency, column chart, mean and standard deviation) and inferential statistical of Pearson correlation coefficient test, one-sample t-test and Kolomogrov-Smirnov test by SPSS 20 software. The results indicate that there is a significant positive correlation between the study skills (0.654) and dimensions of reading skills (0.493), noting (0.572), enhanced memory improvement (0.559), preparation for exam (0.568), increased focus (0.422) and time management (0.568) with academic performance in students (Sig<α= 0.01). There is a significant correlation between the study skills and academic performance in students at Islamic Azad University of Sari, so that the level of academic performance in Islamic Azad University students is increased by enhancing the study skills.
Multi-camera measurements of a three-dimensional shape using the likelihood set to the three-dimensional space

 Abstract — This paper describes three-dimensional shape measurements by a multi-camera system and the correction of the measured points. First, a geometrical model is constructed using the positional relationship of the calibrated multi-camera. Because the cameras are located linearly on a thin plate whose curvature is changed by an actuator, Zhang’s method is employed in the calibration. Second, a three-dimensional object is measured on an epipolar plane. DP (Dynamic Programming) matching is used to determine the corresponding points and SSD (Sum of Squared Difference) is used as the local area windows. Third, the correlation coefficient is employed to determine the likelihood of the three-dimensional points, which are then set to correct and modify the measured points. Consequently, the measurement results more closely resemble the shape of the measured object.
A MULTICHANNEL MAC PROTOCOL FOR WIRELESS SENSOR NETWORKS

: Wireless Sensor Networks consists of large number of small, low cost sensors deployed over an interested region communicating each other with the wireless medium and collecting data of interest. WSNs becomes a leading solution for many applications like target tracking, intrusion detection, industrial automation and so on. In these type of applications energy efficiency may be considered to be the most important concern while bandwidth utilization and maximizing throughput are of secondary importance. But recent applications like body area networks and structural health monitoring requires high amounts of data to be collected at faster rate. In this paper we are focusing on design, implementation and analysis of a scheduled-based multi-channel MAC protocol. These protocols designed with an objective of maximizing throughput of WSNs by coordinating the transmissions over multiple frequency channels. This protocol has advantage of interference and contention free parallel transmissions on different channels. The multichannel MAC protocol needs to operate effectively such that it is free of collisions during high trafﬁc. Each node has assigned a particular channel to transmit the data. Our approach outperforms some of the contention based single channel protocols, cluster based channel assignment in terms of energy and throughput for high data rate. As most of the multichannel MAC protocols have problem of excessive use of energy compared to single channel design. But our protocol is energy efficient than traditional single channel design. Our main focus is to improve the network throughput using scheduled-based multi-channel design scheme.
An Effective Security and Privacy in Big Data analytics Using Machine Learning

- The Conservation of privacy largely relies on technological limitations on the ability to extract, analyze, and correlate potentially sensitive data sets. However, advances in Big Data analytics provide tools to extract and utilize this data, making violations of privacy easier. As a result, along with implementing Big Data tools, it is necessary to create safeguards to prevent abuse In addition to privacy; data used for analytics may include regulated information or intellectual property. Moreover, current efforts aimed at improving and extending Map Reduce to address identified challenges are presented. Accordingly, by identifying issues and challenges Map Reduce faces when handling Big Data, this study encourages future Big Data research System architects must ensure that the data is protected and used only according to regulations. The scope of this document is on how Big Data can improve information security best practices. Identifying the best practices in Big Data privacy and increasing awareness of the threat to private information Machine learning as a data science to uncover patterns and hidden insights is not entirely a new concept. It has been in play with the use of neural networks starting in the 1980’s. The question therefore is, “Why is there a big buzz around machine learning today? ” The answer deception in the fact that development in technology and science has enabled game-changing differences in how machine learning algorithms have evolved and being applied. For example, traditionally, human-generated rule sets were the most prevalent approach in fraud management and still continue to be in practice today. But the required leap in computing power and accessibility of big data over the last five years has disrupted how data is being used to identify and prevent fraud. In the Big Data community, Map Reduce has been seen as one of the key enabling approaches for meeting continuously increasing demands on computing resources imposed by massive data sets. The reason for this is the high capacity of the Map Reduce model which allows for extremely equivalent and disseminated execution over a large number of computing nodes. This paper identifies Map Reduce issues and challenges in handling Big Data with the objective of providing an overview of the field, facilitating better planning and management of Big Data projects, and finding opportunities for future research in this field. The identified challenges are grouped into four main types corresponding to Big Data tasks types: online processing, data storage, security and privacy Machine learning uses artificially intelligent computer systems to separately learn, predict, act and explain without being clearly programmed. Simply put, machine learning eliminates the use of preprogrammed rule sets no matter how complex.
PERCENTAGE OF CITIZENS WHO MAKE SELF-HEALING MEDICATION

The development of Herbal Medicines in various countries of the World has been a discussion of researchers. Indonesia is one of the countries that uses and produces herbal medicine, which is believed to have enormous natural resources to support the development of this plant-based medicine. Consumer Trust becomes an interesting phenomenon to be examined more deeply, because the use of herbal medicine [traditional] is still less by modern medicine [chemical] when consumers buy for their own treatment. Several studies in various contexts show that Perceived Value has an impact on Consumer Trust. Nevertheless whether in the context of herbal medicine consumer perceptions of the value of herbal medicinal products will affect the trust of taking the herbal medicine. This study uses the design of Structural Equational Modeling analysis, and involving 357 respondents. In this article was revealed the influence of dimensions of Perceived Value to Consumer Trust of Herbal Medicines with Emotional Value, Functional Value, and Price Value Significantly Positive effect Consumer Trust, only one dimension has no significant effect that is Social Value.
IMPROVED APPROACH FOR PREDICTING THE BUG TRIAGE USING DATA REDUCTION METHODS

- Most of the software companies need to deal with vast number of software bugs day to day. This paper can be viewed as an application of instance selection and feature selection in bug repositories. The aim is to address the problem of data reduction for bug triage, and to reduce the scale and improve the quality of bug data. This can be achieved by combining instance selection with feature selection to simultaneously reduce data scale on the bug dimension and the word dimension. Data reduction can be addressed by combining instance selection and feature selection approaches.The reduced data set contains lesser bug data with fewer bug reports and fewer words than the original bug data and provide similar information over the original bug data and build a binary classifier to predict the order of applying instance selection and feature selection. Determine the order of applying instance selection and feature selection, to extract attributes from historical bug data sets and build a predictive model for a new bug data set. Empirically investigate the performance of data reduction on bug reports of two large open source projects, namely Eclipse and Mozilla.
C based Complex Event Processing Technique using ADS algorithm

This paper is proposed, an efficient complex event-processing framework, designed to process a large number of sequential events on field-programmable gate arrays (FPGAs). Unlike conventional structured query language based approaches, our approach features logic automation constructed with a new C-based event language that supports regular expressions on the basis of C functions, so that a wide variety of event-processing applications can be efficiently mapped to FPGAs. Evaluations on an FPGA-based network interface card show that we can achieve 12.3 times better event-processing performance than does a CPU software in a financial trading application. Advanced Encryption Standard algorithm was introduced to resist classical methods of cryptanalysis (i
Review On Leaf Disease Detection Using Image Processing Techniques

- This paper holds a survey on leaf disease detection using various image processing technique. Digital image processing is fast, reliable and accurate technique for detection of diseases also various algorithms can be used for identification and classification of leaf diseases in plant. This paper presents techniques used by different author to identify disease such as clustering method, color base image analysis method, classifier and artificial neural network for classification of diseases. The main focus of our work is on the analysis of different leaf disease detection techniques and also provides an overview of different image processing techniques.
Performance of Particle Swarm Optimization for Sensor Networks: A Survey

— The Quality of Service provided by any network is affected by some specific factors. An efficient network achieves its goal by solving all the challenges and satisfies the factors. Many researchers develop several approaches, protocols, techniques, algorithms and methods to improve the performance of network. In this paper, we have conducted a survey to understand the problems of sensor network. The Swarm Optimization Algorithm is reviewed to solve these problems. We analyze that the particle swarm optimization is a capable algorithm to optimize each and every NP hard problems and develops an efficient network.
A Two Dimensional Video Based Face Recognition Using Artificial Neural Network

Human faces carry huge and essential information which plays an important role in face detection and recognition. Automatic recognition has various applications in diverse fields. To recognize a face in real time is a challenging problem because pose variation is a major issue. This paper presents a new robust technique for face recognition. A two-dimensional discrete cosine transform which uses an image-based approach towards artificial is used for feature extraction. The unwanted information is discarded and only the relevant data is extracted. A neural network is used to train the database and also for recognition. Two video sequences of a person are captured from a webcam mounted on a computer monitor. Out of which one is for training phase and one is dedicated to testing phase. The video sequences are taken under same illumination condition but with change in facial expression and pose variation. Experimental results carried out prove that the combination of 2dimensional-DCT and artificial neural network tool used for face recognition improves the recognition rate significantly.
The Effect of Agro Industry, Infrastructure, and Natural Resources to Farmers Income in Shallots Agribusiness Based Agropolitan Area at Banggai Regency of Central Sulawesi Province

The research aims to find out the effect of agro industry, natural resources and infrastructure directly and indirectly to the farmers income in shallots agribusiness based agropolitan area. Data analysis method used was descriptive statistics analysis and path analysis. The research results reveal that the direct effect of natural resources to the farmer’s income with path analysis value is 0.604, coefficient regression 0.909. If the natural resources owned by the adjustability of good land, has a carrying capacity of land and maintained continuously and sustainably in shallots agribusiness based agropolitan area of Banggai Regency with other variables considered fixed, then, natural resources directly affects of 0.909 to the increasing of farmer’s income. The direct effect of infrastructure on the increasing of farmer’s income in the area of shallots agribusiness based agropolitan is 1.420, coefficient regression 2.101. The availability of infrastructure facilities on the agriculture field such as agriculture machinery equipment, farm road, market availability, transportation, people harbor, airport and telecommunication in the area of agropolitan of Banggai Regency greatly affect with 2.101 to the increasing of shallots farmer’s income. The direct effect of agro industry to the farmer’s income in agropolitan area of Banggai Regency with path analysis value is 2.771, coefficient regression of 3.853. The increasing of agro industry productivity using tools and machines in the production process, increasing the marketing of agricultural products, increasing the quality of agro-products, increasing employment by 3.853 highly affect to the farmer’s income. The indirect effect of natural resources on the agro industry development in increasing the income is mediation coefficient value (the indirect effect) of 3.675. It explains that the indirect effect of natural resources to the farmer’s income and entrepreneurs through agro industry development are significant. The indirect effect of natural resources to infrastructure in increasing farmers' income is mediation coefficient value (the indirect effect) of 3.675. It is clear that the indirect effect of natural resources to the income of farmers and entrepreneurs through infrastructure improvement are significant. Keywords: Agro industry, Infrastructure, Natural Resources, Income, Shallots Agribusiness
Modified One-Against-All Algorithm Based on Support Vector Machine

— This paper presents a modification of Support Vector Machine (SVM) One-Against-All Algorithm for multi-class classification task. SVM is originally a model for the binary-class classification. To allow for multi-class classification, different combinations of various binary sub-classifiers are used. The main objective of this paper is to compare and modify the One-Against-All method of multi-class classification based on support vector machine. This paper discusses One-Against-All SVM algorithm which is able to improve the classification accuracy without imposing high computational cost. Two versions of One-Against-All SVM algorithms are tested on Iris and Lenses data sets. It shows that the proposed algorithm for multi-class problem produce good results.
HAND GESTURE RECOGNITION SYSTEM FOR DUMB PEOPLE

Few years ago, there is no way to communicate between the dumb people in a normal speed. And also the normal people never try to communicate between dumb persons. But now a days so many facility are available for understanding to communicate a dumb person using machine translator, hidden grove method etc. But drawback of this method is that is requiring more power supply and this type of machine translator is very costly. To overcome this drawback, In this paper use the static hand gesture recognition system using digital image processing.
Effect of Epoxy Chain Extender on the Properties of Polylactic Acid

Modification of polylactic acid (PLA) by chain extension is a method used to improve its melt strength and heat resistance. In this study, the chemical structure, viscosity average molecular weight, thermal properties, melt viscosity, mechanical properties and Vicat softening temperature of PLA before and after the modification were measured by Fourier-transform infrared spectroscopy (FTIR), a viscometer (Mv), differential scanning calorimetry (DSC), a melt index instrument (MI), a rotary rheometer, a universal material testing machine, and a Vicat softening temperature tester, respectively, to characterize the effect of chemically modifying PLA with KL-E4370. The experimental results showed that the epoxy group contained in KL-E4370 reacted with the carboxyl group of PLA. In addition, the modified PLA showed increased molecular weight, enhanced melt strength, decreased melt fluidity, a significantly decreased melt index, significantly increased complex viscosity and modulus, enhanced impact and tensile strengths, and an increased Vicat softening temperature. When the content of KL-E4370 was 0.1%, the viscosity average molar mass increased from 2.88×103 g/mol (that of neat PLA) to 4.02×103 g/mol, the crystallinity increased from 17.0% (that of neat PLA) to 32.5%, the melt index decreased from 6.0 g/10 min (that of neat PLA) to 2.2 g/10 min, the Vicat softening temperature increased from 67.9 °C (that of neat PLA) to 160.1 °C, and the heat resistance of PLA was improved significantly.
PHYTOCHEMICAL SCREENING OF SOME SELECTED BANANA PEELS OF MUSA ACUMINATA SPECIE

The study investigates the phytochemicals present in peels of selected banana species (Musa accuminata cv cavendish banana, Musa accuminata cv red skin banana, Musa accuminata cv white skin banana). The banana fruits used were bought at Apata market, Ibadan, and later peeled. The peels were air dried and subjected to extraction process using methanol maceration. The phytochemicals screened were tannin, flavnoid, saponin, oxalate, T. phenols, steroids, and terpenoid. The results showed that all phytochemicals screened were present in the peels at appropriate levels recorded (Oxalate ranges between 4.33 – 1.16, tannin between 5.00 – 5.75, flavonoid between 6.94 – 8.75, steroid between 0.1 – 0.185, terpenoid ranges between 0.21 – 0.28, T. phenol range between 53.35 – 82.20 and saponin between 0.075 – 0.25).
Antioxidant and antimicrobial activities of methanol leaf extract of Chellakumar * Corresponding

Received: 02 Jul 2017 Accepted: 17 Nov 2017 Published: 28 dec 2017 A b s t r a c t The present scavenging activities, antioxidant properties and antimicrobial activities of the methanol leaf extract of extract of standard procedures. The antioxidant activities were carried out by DPPH free radical scavenging assay, OH Fe antimicrobial activity was carried out by well diffusion method. The methanol leaf extract of tamilnadensis activities which were found to increase with the increasing concentration of the extract. The study revealed the presence of major phytochemicals such as phenols and flavonoids at the concentration of 211.0 mg/g at 100 μg and 52.91 mg study revealed that the methanol leaf extract of significant antioxidant and antimicrobial activities.
Blind Signal Processing Algorithmsbased based on Recursive Gradient Estimation

Blind algorithms based on the Euclidean distance (ED) between the output distribution function and a set of Dirac delta functions have a heavy computational burden of due to some double summation operations for the sample size and symbol points. In this paper, a recursive approach to the estimation of the ED and its gradient is proposed to reduce the computational complexity for efficient implementation of the algorithm. The ED of the algorithm is comprised of information potentials (IPs), and the IPs at the next iteration can be calculated recursively based on the currently obtained IPs. Utilizing the recursively estimated IPs, the next step gradient for the weight update of the algorithm can be estimated recursively with the present gradient. With this recursive approach, the computational complexity of gradient calculation has only . The simulation results show that the proposed gradient estimation method holds significantly reduced computational complexity keeping the same performance as the block processing method
Overview of the use of probiotics in aquaculture

Probiotics, which have been widely used in livestock rearing, have recently been applied to aquaculture. Probiotics are defined as live cells or a substrate that provides benefits through stimulation of growth, improved digestion, and improved immune response. Probiotics can also improve water quality. This review summarizes the current understanding of the use of probiotics in aquaculture, including the definition and mechanism of probiotics, and describes their application, and prospects and difficulties associated with their use in aquaculture. This review includes general knowledge of probiotics from previous studies and evaluates the efficacy of probiotics in aquaculture. © 2013 Universal Research Publications. All rights reserved
A Survey on Plant Disease Identification

Plant disease is a wreckage of the normal state of a plant. It interrupts or modifies its vital function. Plant disease causes, loss of crops that may result in hunger and starvation especially in less developed countries. Automatic detection of plant disease helps in monitoring the crop and automatically detects the symptoms of the disease as soon as they appear on plant leaves. Most plant diseases are caused by fungi, bacteria and viruses. Image processing techniques are used to detect various plant diseases. This includes several steps viz. input images, image preprocessing, and extraction of features and classify them on the different basis. It uses many classification techniques such as K Nearest Neighbor classifier, k-means Classifier, Neural Networks, Support Vector Machine, Artificial neural network, and Fuzzy logic. Selecting a best classification method is cumbersome because the efficiency of result can vary based on input data. This paper focuses on different image processing techniques along with different classification techniques used for plant leaf disease classification.
LEAKAGE POWER REDUCTION IN DEEP SUB MICRON SRAM DESIGN - A REVIEW

Present day electronic industry faces the major problem of standby leakage current, as the processor speed increases, there is requirement of high speed cache memory. SRAM being mainly used for cache memory design, several low power techniques are being used for SRAM cell design. Full CMOS 6T SRAM cell is the most preferred choice for digital circuits. This paper reviews various leakage power techniques used in 6T SRAM cell and their comparative study.