Miracle-dz/UniFAR-FTUs huggingface dataset:
A Framework for Mining High Dimensional Data for Feature Subset Selection

--Features are representative characteristics of data sets. Identifying such fetures in a high dimensional dataset play an important role in real world applications. Data mining is best used to determine important features. Selecting important features from a subject of identified features can help in making expert decisions. However, efficient identification of such feature subset and selection is a challenging problem. Recently Song et al. proposed a solution that is capable of selecting subset of features with good quality. They used clustering approach before selecting representative features for final selection. Similar work is carried out in this paper which demonstrates the proof of concept. The proposed solution makes use of clustering for achieving the goal of the system. The empirical results reveal that the application is useful. The results are compared with many existing algorithms like C4.5, Naïve Bayes, IB1 and RIPPER.
Detection of Alternaria alternata isolated from grain by using specific primer.

This work was concentrated on Alternaria alternata because they are Different pathotypes common pathogens of different plants having a high toxigenic potential for which a special and sensitive detection method is required and are particularly difficult to distinguish with conventional methods often do not distinguish between the isolates of the same species Therefore DNA based method was applied to find if the isolates differ significantly from each other.
SVM BASED IMPROVEMENT IN KNN FOR TEXT CATEGORIZATION

-In today‟s library science, information and computer science, online text classification or text categorization is a huge complication. [1]With the enormous growth of online information and data, text categorization has become one of the crucial techniques for handling and standardizing text data. Various learning algorithms have been applied on text for categorization. On the basis of accuracy and efficiency KNN (K Nearest Neighbour) algorithm prove itself to be very efficient algorithm as compared to other learning algorithms. The framework of KNN with TF-IDF is studied and some changes need to be done for removing time complexity and improve accuracy so, proposed work is based on using SVM classifier which helps in splitting of training and testing data and take less time from the previous work with iKNN (improved KNN) algorithm which gives less time and more accuracy and overall improve text categorization.
Synthesis and Characterization of ZIF-8 Filler for Preparation of Mixed Matrix Membrane

Development of mixed matrix gas separation membranes by utilizing nano sized inorganic particle with polymer matrix is new approach for improving the separation properties of polymeric membranes. To overcome the several challenges of mixed matrix membrane (MMM) like dispersion, contact of fillers with polymer, percentage of filler loading, size and shape of crystal, stability of membrane in harsh conditions, selective separation of gases needs to find material in such a way that the permeability of polymer should match with the permeability of inorganic fillers. Zeolitic imidazolate framework (ZIFs) a subclass of metal organic framework is an emerging class of porous solid nano sized crystals comprised of imidazolate linkers and metal ions with structure similar to zeolite. It exhibit permanent porosity and high hydrothermal and chemical stability. Due to their molecular sieving effect, facile syn sis and compatible with the polymers, it reveals its importance during preparation of mixed matrix membrane. The main focus of this study was to synthesis ZIF-8 nano crystals in water and methanol at room temperature and characterization using xray diffraction (XRD) to ensure its size, surface area and crystalline porous nature. The review was taken on the methodology of preparation of mixed matrix membrane, its compatibility with polymer, significance and utilization for gas separation. Index Terms — Filler, Mixed Matrix Membrane (MMM), Polymer, Synthesis, Significance, Zeolitic Imidazolate Framework (ZIF-8). ——————————  ——————————
DELAY AWARE AODV FOR GREENY VANETS

— One of the important QOS parameter in highly dynamic VANETs is minimum delay. There has been a continuing innovation in the area of routing for the VANETs to find the optimal path between source and destination. Many protocols have been proposed and deployed to realize the benefits of intelligent transportation systems (ITS) in VANETS. But still the question arises is how best, the protocol finds optimal path besides the rapidly changing environment? However no single protocol excels for VANETs. Due to high mobility and lossy characteristics of wireless medium, it’s really a challenging question to find the optimal (shortest path) and at the same time, a lossless path which guarantees packet delivery. Guaranteeing packet delivery is the top most criteria in networks like VANETs. The importance of VANETS is better realized in the area of accident prevention and obviously, a safe driving. Link failures are frequent in VANETs and so the responses that arise from the protocol would degrade the performance, when the network size increases. So from our research study ,the issues that needs to be addressed for efficient routing are link failures , scalability, minimum delay and so a guaranteed transmission of real time data in accordance with the dynamic environments. In this paper, we propose a new algorithm to facilitate the reliable and efficient routing in VANET’s. The new algorithm enhances the well-known ad hoc on-demand distance vector (AODV) routing protocol to propose the location-based scalable routing protocol AODV-r. Simulation results demonstrate that AODV-r outperforms significantly the AODV routing protocol in terms of better delivery ratio and small end-to-end delay while maintaining a reasonable routing control overhead. We had also proposed a new metric called Extended ETX which enhances the original ETX.
Automatic Text Extraction in Video Based on the Combined Corner Metric and Laplacian Filtering Technique

— Text in the videos and images provides very major information about the content of the videos, the video text extraction provide a major role in semantic analysis of the video, video indexing and video retrieval which is an important role in video database. We propose an efficient method for detecting, localizing and extracting the text appearing in the videos with noisy and complex background. The text region appearing in the video or an image has certain features that distinguishes it from the rest of the background, we make use of corner metric and Laplacian filtering techniques to detect the text appearing in video independent of each other and combine the results for an efficient detection and localization. Then the binarization of the localized text is done by the seed pixel determination of the text. the experimental results shows the efficiency of the proposed system.
Factors Influencing Teachers Take-up of Continuing Professional Development: the Perspectives of Basic School Citizenship Education and Social Studies Teachers of Sissala West District, Ghana.

This study focused on the factors that influence take-up of CPD activities by Basic School Social Studies teachers and the relationship between teacher characteristics and teacher participation in CPD. The used of the mixed-method approach which involved two phases of quantitative and qualitative data. A total of 185 respondents were purposively sampled. Data on factors that support CPD take-up as well as the relationship between teacher characteristics and teacher participation were gathered using questionnaire and semi-structured interview. Qualitative responses were coded, categorized and analyzed into themes. Quantitative data were analyzed using frequencies and percentages. Most teachers felt that consultation, good content and organisation as well as delivery were the key factors which contributed to the success of CPD activities in the district. It could be concluded from the findings of this study that linear relationship existed between the variables (teacher qualification, teacher experience) and participation in CPDs. Keywords: Staff development, professional development, continuing professional development, participation of teachers.
An Efficient Materialized View Selection Approach for Query Processing in Database Management

: Quick response time and accuracy are important factors in the success of any database. In large databases particularly in distributed database, query response time plays an important role as timely access to information and it is the basic requirement of successful business application. A data warehouse uses multiple materialized views to efficiently process a given set of queries. The materialization of all views is not possible because of the space constraint and maintenance cost constraint. Materialized views selection is one of the crucial decisions in designing a data warehouse for optimal efficiency. Selecting a suitable set of views that minimizes the total cost associated with the materialized views is the key component in data warehousing. Materialized views are found useful for fast query processing. This paper gives the results of proposed tree based materialized view selection algorithm for query processing. In distributed environment where database is distributed over the nodes on which query should get executed & also plays an important role. This paper also proposes node selection method for fast materialized view selection in distributed environment. It is found that the proposed methodology performs well as compare to other materialized view selection strategies.
Optimal Allocation of TCSC Using Heuristic Optimization Technique

With the massive increase in the population and, as a result of the expansion of the power grid, new problems such as loss power in network retaliation were created. So studies on this issue began. These studies led to the emergence of FACTs devices. The Flexible AC transmission System (FACTS) devices, such as, thyristor controlled series compensators (TCSC) may be used to enhance system performance by controlling the power flows in the network. Optimal location and setting of this devices are considered complicated and multi-objective problems. It is important to limit the number of TCSCs and to locate optimally these devices in the power system because of their considerable costs. In this paper, efficient heuristic optimization technique, is employed to find the optimal location and setting of a thyristor controlled series capacitor (TCSC) device in a modified system. To demonstrate the effectiveness of the proposed approach, IEEE 30-bus test system has been studied.
Routing Optimization with Load Balancing: an Energy Efficient Approach

---------------------------------------------------------------------- ABSTRACT ----------------------------------------------------------- The area of Wireless Sensor Network (WSN) is covered with considerable range of problems, where majority of research attempts were carried out to enhance the network lifetime of WSN. But very few of the studies have proved successful. This manuscript discusses about a structure for optimizing routing and load balancing that uses standard radio and energy model to perform energy optimization by introducing a novel routing agent. The routing agent is built within aggregator node and base station to perform self motivated reconfiguration in case of energy depletion. Compared with standard LEACH algorithm, the proposed technique has better energy efficiency within optimal data aggregation duration.
Comparison of Segmentation based on Threshold and K-Means Method

In MRI brain images segmentation, extraction and detection of tumor infected area from the basic brain image properties are the primary, tedious and time taking process. The accuracy of separation the tumor area is based on the experience of clinical experts or radiologists. So, we need computer aided technology to overcome those limitations. In this study, we do automatic methods to reduce the complexity and improve the performance of MRI bran image segmentation. We have investigated many algorithms are available in medical imaging research area such as K-means clustering, Threshold technique, FCMeans, Watershed and Hierarchical Clustering (WHC) and so on. The proposed method compares Threshold technique and K-means clustering technique. The experimental results of proposed techniques have been evaluated and validated for performance and quality analysis on magnetic resonance brain images, based on segmented area, min and major axis and process time for the segmentation. The experimental results achieved more accuracy, less running time and high resolution.
Interpositional Arthroplasty Technique for Hallux Rigidus Using Amniotic Membrane and Regenerative Tissue Matrix

Hallux rigidus is a painful osteoarthritic condition of the first metatarsophalangeal joint. It is the most prevalent arthritic condition of the foot, affecting up to 1 in 40 adults over 50 years of age. Mild cases of hallux rigidus are frequently treated with cheilectomy, whereas severe cases are often treated with arthrodesis. Interposition arthroplasty is a joint-sparing alternative to fusion that has been used effectively in moderate to severe cases of hallux rigidus. This paper discusses a novel modification of interpositional arthroplasty technique using amniotic membrane graft and regenerative tissue matrix to successfully treat patients who have failed cheilectomy. Levels of Evidence: Diagnostic Level 4. See Instructions for Authors for a complete description of levels of evidence.
MATRIX BASED EFFICIENT ECC TECHNIQUE FOR TEXT ENCRYPTION

-We propose a novel mapping method based on invertible matrix and random sequence for converting alphanumeric characters of the plaintext message onto the (x; y) coordinates of Elliptic Curve defined over the prime eld GF(p). The mapped points are further encrypted with Elgamal Cryptosystem. Finally we illustrate the implementation of our cryptosystem based into an elliptic curve characterized by the equation y2 = x3 - x + 19 (mod 71). The cryptosystem provides sufficient security against cryptanalysis at low computational overhead, a brute force attack to break the cryptosystem is almost infeasible.
A framework for conceptualizing patient loyalty to healthcare organizations

This paper develops a framework with which to conceptualize loyalty to healthcare organizations in terms of relationship marketing, patient satisfaction, provider switching, and retention programs. This conceptual framework can be viewed from the perspective of hospitals and clinics using structural equation modeling with a partial least squares approach (Smart PLS 2.0). Respondents received healthcare services, funded by the government and a university health insurance plan, from both types of organizations. The concept of loyalty differed slightly depended on whether data from the hospital and the clinic were analyzed together or separately. Indeed, hospitals and clinics differ with regard to several factors that can affect loyalty.
Scheduling Algorithms for MapReduce Framework

- Google proposed MapReduce as a simple and flexible parallel programming model, for large-scale distributed data processing. MapReduce framework allows users to quickly develop big-data applications and process big-data effectively. However, unexpected malfunction may be found in cloud environment because a distributed system consists of several hardware, and this malfunction often causes delay of overall processing. In MapReduce framework, the underlying runtime system automatically parallelizes the computation through large-scale nodes of machines, handles machine failures, and schedules inter-machine communication to make use of the network and disks efficiently. Scheduling is one of the important factors in MapRduce. In order to achieve good performance a MapReduce scheduler must avoid unnecessary data transmission. Hence different scheduling algorithms for MapReduce are necessary to provide good performance. how to schedule the service resources to achieve the lowest cost becomes more and more important. In this paper, we describe the overview of fifteen different scheduling algorithms for MapReduce in Hadoop and their scheduling issues and problems. At the end, Advantages and disadvantages of these algorithms are identified.
Strategies for Network Intrusion Detection using Machine Learning Algorithms

: Spying identification is an emerging field of software development and research and networking with increasing Internet use in daily life. There have been many issues with classical IDS systems, along with other low network attack identification, high false alarm rate, and inadequate analytical capacity. The primary potential of research on the subject then is to establish a model for intrusion detection with increased performance and decreased preparation time. Machine learning is an efficient tool for analyzing any abnormal events taking place in the network activity flow. This paper proposes a mixture of two methodologies to determine any abnormal conduct in internet traffic. This paper recommends to use the principal component analysis (PCA) and Rough-set Support Vector Machine (SVM) as the hybrid intrusion detection models.
Molecular Variability of Celosia argentea Using Amplified Fragment Length Polymorphism (AFLP) Marker

The molecular variability of ten genotypes of Celosia argentea seeds collected from National Institute of Horticultural Research (NIHORT) and National Centre for Genetic Resources and Biotechnology (NACGRAB) germplasms were evaluated using the Amplified Fragment Length Polymorphism (AFLP) marker. The polymorphism of C. argentea was detected within the population using primer mix of AFLP EcoRI + MseI adaptors type in three primer combinations. Powermarker software V3.25 was statistically used to analyse the fragments from extracted DNA region. The highest concentrations of genomic DNA of 13.30 μL and volume of 2 217.59 μL for total genomic DNA were recorded for NG/TO/MAY/09/015 and NG/MA/MAY/09/015 genotypes respectively. Variations were observed in the number of fragments amplified by each of the three AFLP primers combinations. The polymorphic information content (PIC) of the amplified fragment of the genomic DNA was diverse at 89.1% for DNA size of 100 base pairs, while the percentage gene diversity was 90%. The primer sequence combination of AAC + CAG produced the highest number of bands, amplified fragments, and number of polymorphic bands of 400, 40, and 156.000 respectively. A dendrogram constructed revealed three cluster groups, in which clusters 1 and 3 were delineated into 4 genotypes each, while cluster 2 had the least with two genotypes. This study revealed variability among the genome of C. argentea using AFLP marker. This could promote improvement and conservation of C. argentea germplasm for broaden genetic basis of breeding program.
Short term effect of 28-homobrassinolide on serum, liver and kidney marker enzymes and other biochemical parameters o f male albino rats

K. Srikumar Ph.D., FABMS 1. Dept. of Biochemistry & Molecular Biology, School of Life Sciences, Pondicherry University, Kalapet, Puducherry-605014, India. Tel: +91-413-2654422 Email: kotteazeth_srikumar@excite.com Abstract Brassinosterols (BS) are ubiquitous pluripotent gro wth regulator present in plants. They exist in isoforms of epi an d homobrassinolides (HB). BS act as potent stimulato rs of root and shoot elongation, cell division, DNA and RNA polyme rase activity, ethylene production and of stress tolerance to temp erature, water scarcity and salinity in plants. It is also used to increase the yield of crop and to protect the plants against pesticides. Consumption of plant material as diet and used as growth regulator in animals, and application of BS in agriculture would increases it s availability to the host tissues. In the present study, the effect of 2 8-HB, an isomer of brassinosterol on serum, liver and kidney marker en zymes, lipid peroxidation, tissue histology and the blood parame ters of rat were investigated. The rats were given the compound by i ntradermal mode at the concentration of 75μg, 150μg and 300μg as single dose and the effects were observed after 4 hr to study t he immediate response of the animal. The treatment of rats with 28-HB, caused different ffects on the serum, liver and kidney parameters of this study. In conclusion, the present study showed that 28-HB affects the structure and function of rat tissues in a dose dep endent manner.
A REVIEW ON THE RECENT DEVELOPMENT IN ENHANCING THE THERMAL CONDUCTIVITY IN NANOFLUIDS

Nanofluid, the synergy of base fluid and nanoparticles, has exhibited many compulsive properties, and the unique attributes offer an unmatched potential for future applications. This review aims to compile the recent developments in enhancing the thermal conductivity (k) of nanofluids. Most of the papers reviewed here reported an enhancement by focusing on volume concentration. The nanofluid exhibits wideranging applications in numerous domains including electronics, biomedical and mechanical fields. And lastly, this review guides to directions for future research and developments of contention issues.
Implementation of High Speed and Energy-Efficient Carry Skip Adder using Verilog HDL

This paper presents a high speed carry skip adder (CSKA) structure yet brings down energy utilization contrasted with the existing one. The proficiency is improved that of the existing CSKA (Conv-CSKA) structure with updating the adder by applying the concatenation and incrementation plan. The AND-OR-Invert (AOI) and moreover OR-AND-Invert (OAI) logic gates are utilized for the skip logic as a replace to the multiplexer logic. The structure is acknowledged in both uniform (FSS) where at long last the speed and energy parameters of the adder are updated. At long last, a hybrid variable latency expansion of the proposed structure with an Brent-Kung parallel prefix adder, which brings down the power utilization without extensively affecting the speed, is presented. The proposed structures are evaluated by comparing their speed, power and energy parameters with those of different adders design by Verilog HDL and Simulated by Modelsim 6.4 c and Synthesized by Xilinx Design Suite 13.2 and proposed system implemented in FPGA Spartan 6 XC6SLX4 TQG-144 with a speed grade of -3.
A Study Of Structure From Motion Photogrammetry For Generating 3D Model From 2D Images

: With the advancement in technology and the rapidly increasing usage of internet applications for online shopping, there is an increase in the need and expectation of the online consumers.The online commerce that are used now for shopping mostly provide a 2D view of the products . Therefore buyers have only partial view of the product they intend to purchase. Therefore We aim to develop a 3D grocery review application that would provide a 3D object view of the products online using reconstruction.3D modeling is a process of mapping an object into the real-world coordinates in 3 dimensions representing the height, width and also the depth. Traditional and recent technology for building 3D models from images include photogrammetry, structure from motion and other 3D scanning approaches such as laser, lidar, etc have been discussed in this study. Photogrammetry is a process of extracting features from images that measurement of an image(distance,height etc) and then structure from motion , to build a 3D model from those images.Later,using three.js generated model will be displayed . THREE.JS is a WEB API for 3d modelling.