Miracle-dz/UniFAR-FTUs huggingface dataset:
EVALUATION OF STANDING LONG JUMPING FUNDAMENTAL SKILL DEVELOPMENTAL SEQUENCE IN CHILDREN

Fundamental Movement Skills (FMS) are skills that enable children to interact and explore their environment. The standing long jump has been included in numerous motor and physical fitness batteries with the primary purpose of determining jumping ability in relation to maximum distance. The purpose of this study was to investigate the developmental sequence of basic skills in children 2 to 6 years old standing long jump in Shiraz-Iran. Data was collected by video film from three angles, face, back and side. Pattern of pair's Long jump assessment by use stepwise Clark and Phillips (1985) scale and movement patterns general characteristics were analyzed. The Research was conducted on the sample of 151 preschool children (85 boys and 66 girls) aged 2-6 years from ShirazIran. Age and gender differences were calculated by the Univariate analysis of variance. The results of the analysis of variance showed no significant differences were found in the quality of the standing long jump performance between boys and girls and based on age groups.
Design, Modeling and Simulation of Axial Flux Permanent Magnet Synchronous Machine for Electric Vehicles

1Research Nuclear Center of Birine CRNB Box 180, Ain Oussera, ALGERIA 2Research Center in Renwable Energy, Bousmail, ALGERIA 3Electrical Department; University Amar Telidji of LAGHOUAT, ALGERIA ----------------------------------------------------------------------***--------------------------------------------------------------------Abstract Studies, most of the pollution from urban areas comes from vehicle emissions and the explosive growth in the number of vehicles. Therefore, finding a solution to reduce (or eliminate) pollution is a vital need. If in public transport (trains, buses and trams) there are non-polluting solutions (electric), for individual transport the electrification of vehicles is one of the solutions implemented by car manufacturers.
A REVIEW ON STEGANOGRAPHY TECHNIQUES USING CRYPTOGRAPHY

Cryptography and steganography are widely used methods to provide data security. The motivation behind cryptography and steganography are same. Both are utilized to secure essential data however in distinctive way. Cryptography only hides the content of message not the existence of message and Steganography hides the existence of message . This paper introduces various methods where cryptography and steganography are combined to encrypt the data as well as to hide the data in image. It provides two levels of security to the information being transmitted. This paper also concentrates on strength of combining cryptography and steganography methods.
Remote Control of Home Appliances with Smart Energy Efficient Model Using Android Application Based on Raspberry Pi Embedded Linux Board

- Smart phones and digitization are gathering attraction and one would like to control hi-tech appliances in home using this technology. It has almost become a requirement to control home appliances from remote location using smart technology. To make this possible a machine or a secondary brain is required to ‘Think’ and take actions control home appliances to do tasks as per the convenience of the user from long distances. A system is proposed for the users to control home electronic appliances with highly mobile platform and security. A set of devices will be controlled by internet with the help of Raspberry pi micro-controller [1]. A Raspberry pi micro-controller board accepts the user input from an android mobile application. The customized user friendly application has several buttons to control the appliances. A pi microcontroller will be located in a room and will be connected to all electronic devices in the home with the help of relays. The Raspberry pi can be controlled from any remote place with the help of Microsoft azure cloud service. Python GPIO library functions gives us a platform to interact with Raspberry pi’s General Purpose IO pins. The Raspberry pi then either allows or prevents the current through an electromagnetic relay connected to the intended switch and this result in turning the device ON or OFF. Thus globally accessible automation of electronic appliances can be controlled with the use of a Raspberry Pi controller board, an internet connection and relay switches in a user friendly way. An algorithm has been proposed in this paper to automatically optimize the energy consumption based on calculating total power consumption of the home appliances [1].
Recognition of X-rays bones: Challenges in the Past, Present and Future

Image processing tool is a key role in medical uses, by extracting anatomical features the contouring of the regions from medical images. The discovery of bone sketch from X-ray images has recently introduced a new dimension in the literature as it proves to be an important step of radiological imaging analysis. X-ray images are segmented to study bone skeleton where the image is split into several parts, to examine the fracture of bones, and to plan for treatment before surgery. This report's, purpose is to survey digital image splitting methods. In image segmentation, research analysis is important for categories and it is important to provide an overview of assistive segmentation techniques with highlighting advantage and disadvantage.
REVIEW OF FLASH ANALOGUE TO DIGITAL CONVERTER

This research presents the review of Analog to Digital Convertor (ADC). For ADC there are mainly four different methods, Flash ADC, Pipelined ADC, Successive Approximation ADC, and Sigma Delta ADC. The Flash ADC is the Fast ADC. For Designing the ADC, the parameters important are Static and Dynamic. In static parameters Differential Non Linearity Error (DNLE), Integral Non Linearity Error (INLE) and in dynamic parameters Signal to Noise Ratio (SNR ), Effective Number of Bits ( EONB ), Spurious-Free Dynamic Range (SFDR), Dynamic Range (DR). The design issues which consist first CMOS inverter used in CDC architecture, MUX based Decoder and DAC.
An Enhanced Apriori Algorithm Using Hybrid Data Layout Based on Hadoop for Big Data Processing

Summary Frequent itemset mining is one of the data mining methodes implemeted to find frequent patterns, utilized in prediction, association rule mining, classification, etc. Apriori algorithm is an iterative method , that is used to discover frequent itemsets from transactional dataset. It scans entire dataset in every iteration to come up with the large frequent itemsets of various cardinality, which sounds efficient for small data but not useful for big data. To resolve the problem of treatment dataset in every iteration, we present an algorithm called Hybrid Frequent Itemset Mining on Hadoop ( HFIMH ) which uses the vertical layout of dataset to solve the problem of treatment the dataset in every iteration. Vertical dataset conveys information to discover support of every itemsets, and the idea of set intersection is utilized to compute it. We compare the execution of HFIMH with another Hadoop based implementation of Apriori algorithm for different datasets. Experimental results demonstrate that our approach is better.
Development, Characterization and Evaluation of TinidazoleNanosuspension for Treatment of Amoebiasis

Amoebiasis is an infectious disease of gastrointestinal tract caused by the protozoan, Entamoeba histolytica. This disease is widely distributed worldwide and is endemic in most parts of India and other developing countries. The protozoa multiply rapidly in their hosts. Since effective vaccines are as yet unavailable, chemotherapy is the major strategy to treat infected individuals and reduce transmission. Nitroimmidazoles, like Tinidazole (TNZ) form an important class of drugs, which are active against both intestinal and systemic forms of amoebiasis. Most of these drugs have high dose and metallic to bitter taste which result in poor patient compliance. In the present study, nanosuspension was developed by nanoprecipitation method for oral delivery using Tinidazole as model drugs with improved its dissolution rate and hence bioavailability. With improved bioavailability it may be possible to reduce the dose requirement, which would be especially advantageous for paediatric patients. Ex-vivo absorption studies performed using the rat intestinal model showed an enhanced absorption from the nanosuspension as compared to micronized drug.
SURVEY ON CLASSIFICATION ALGORITHMS FOR DATAMINING: (COMPARISON AND EVALUATION)

Data-Mining Classification is amachine learning technique used for portioning the data into different classes according to some constrains. It can deal with a wide variety of data so that large amount of data can be involved in processing. Several major kinds of classification methods that can be used such as decision tree induction, case-based reasoning, genetic algorithm, fuzzy logic techniques, C4.5, k-nearest neighbor classifier, Naive Bayes, SVM, and AdaBoost. In this paper a comparison among three classification’s algorithms will be studied, these are (K-Nearest Neighbor classifier, Decision tree and Bayesian network) algorithms. The objective of this survey is to providean inclusive evaluationof different classification algorithms that are being generally used.
Semantic Feature Reduction in Text Document Clustering with Natural Language Processing

— This paper presents the result of an experimental study of document clustering by applying bisecting k-means with Natural language Processing and by applying standard k-means algorithm. In particular we compare the two main approaches to document clustering Bisecting k-means with Natural Language Processing and k-means. Bisecting k-means is better quality clustering approach but by applying combination of NLP and Bisecting k-means we get the better clustering results. In constract k-means have time complexity which is linear in the number of documents but produce inferior clusters. We proposed an explanation for these results that is based on analysis of above clustering algorithm on text document.
Software Defined Internet of Things (IoT) in 5G Millimeter Wave (mmWave) Communication System

This research paper discusses software defined secure Internet of Things (IoT) data transmission in 5G millimeter wave (mmWave) communication system. The proposed software defined system dynamically interleaves the data before transmission in in 5G mmWave communication system. Software defined secure 5G mmWave communication system randomly transmits the dynamically interleaved data and the interleaved parameters to the desired IoT device. The IoT receiver performs dynamic de-interleaving of the received data using the received interleaved parameters.
VLSI Architecture of Turbo Codes-IP Secure With PUF for Dedicated Short Range Communication (DSRC) Systems

-The Dedicated Short Range Communication (DSRC) is an emerging technique to push the Intelligent Transportation System (ITS) into our daily life. To establish proper communication with information security, turbo encoded algorithm is introduced. Turbo encoded algorithm implemented in DSRC system with secure IP core. In this paper, turbo encoded-IP secure with Physical Unclonable Function (PUF) is proposed for a process DSRC system efficiently and enhances the signal reliability. PUFs can enable low-cost authentication of individual ICs and generate volatile secret keys for transceiver operations. This approach requires the authentication mechanism to be implemented in hardware incurring an area overhead
Prediction Analysis Techniques of Data Mining: A Review

Data mining within the databases is called a technique from which the extraction of necessary information can be done from the raw information. With the help of the prediction analysis technique provided by the data mining the future scenarios regarding to the current information can be predicted. The prediction analysis is the combination of clustering and classification. In order to provide prediction analysis there are several techniques presented through many researchers. In this review paper, various techniques proposed by various authors are analyzed to understand latest trends in the prediction analysis. The prediction analysis techniques have two steps which are feature extraction and classification. The various classification techniques are reviewed in terms of certain parameters and compared in terms of their outcomes.
Intrusion Detection and Prevention Systems (IDPS) and Security Issues

Summary Technical solutions, introduced by policies and implantations are essential requirements of an information security program. Advanced technologies such as intrusion detection and prevention system (IDPS) and analysis tools have become prominent in the network environment while they involve with organizations to enhance the security of their information assets. Scanning and analyzing tools to pinpoint vulnerabilities, holes in security components, unsecured aspects of the network and deploying of IDPS technology have highlighted.
International Journal of Soft Computing and Engineering

This paper investigates how to reduce error and increase speed of Back propagation ANN by certain defined Capacity factor. For the years from 1965 to 1980 the use of a variety of ANNs for problem solving was relented significantly because of limitations in one layer networks that weren’t good enough for enhancements of a specific issue, although there were low expectancies for even simple tasks and mathematical operations. Multi-layer networks have a serious covenant to improve this privation by more effective error reduction for example by least squares error method and a better learning factor like the one that is considered in MLP which is modified, enhanced version of Perception network that has provided a better chance of using these networks for intelligent signal processing. But the purpose of this paper is not showing capabilities of these networks alone but to consider error reduction while the weighting equations both satisfy ordinary task of algorithm and at the same time reduces presumptions of errors by a predetermined Capacitance factor that is not very anomalous to other bunch of clustering pedagogy styles anent the other types of ANNs. Unlike a single layer network with many limitations in learning, approximating and estimating a mapping function, multi-layer networks are well prepared for estimation of any uniformly continues subordination with tunable accuracy. Hidden layer in many applications does the job of enhancement, but sometimes poly-layer methods are used for this error reduction separately by some factor definitions (and new hidden parts that paper adds to gets error reduced) that paper tries to measure for exact improvements which were envisaged in design process. And as a result understand how to use Capacity factor for BPANN algorithm, and error reduction in general that holds convergence, speed improvement and error smoothing at the same time.
A Novel Approach for Face Recognition Using PCA and Artificial Neural Network

— Face recognition is a biometric tool for verification and authentication a facial recognition based verification system can further be deemed a computer application for automatically verifying or identifying a person in a digital image. Analytic (local features based) and holistic (global features based) are the two common approaches employed for face recognition approaches with acceptable success rates. In this paper, we present a hybrid features based face recognition Technique . It combines the local and global approaches to produce a high success rate face recognition system. Experiments are carried out on the SDUMLA-HMT face database. Principal component analysis is used to compute global features while the local feature are computed configuring the central moment and Eigen vectors and the standard deviation of the nose, eyes and mouth segments of the human face as the decision support entities of Artificial neural network.
Echocardiographic Assessment of Right Ventricular Function in Normotensive Non Diabetic Hemodialysis Patients

Background: Heart is affected structurally and functionally in end-stage renal disease (ESRD). However, the data available about adverse effects of ESRD on right ventricle (RV) is scarce. We aimed to evaluate echocardiographic parameters of RV in normotensive, nondiabetic patients with ESRD undergoing hemodialysis (HD). Methods The study was conducted on 75 individuals classified into two groups: 50 patients with end stage renal disease on regular hemodialysis for more than one year (group one) nad 25 persons of normal individuals as control group (group two). All patients and control were subjected to full medical history, full clinical examination and laboratory investigations including Serum creatinine, complete blood count (CBC), C-reactive protein (CRP), fasting blood glucose levels, lipid profile (triglycerides and cholesterol), Serum calcium (CA), phosphorus (PO4), and intact parathyroid hormone (IPTH). Also M-mode and two dimensional images, pulsed and continuous wave Doppler, and tissue Doppler measurements were acquired from all subjects. Echocardiographic evaluation was performed in the days between HD dates of the patients. Results: RV fractional area change, tricuspid annular plane systolic excursion, tricuspid E velocity, E/A ratio, tricuspid annular Evelocity, and E/A ratio were lower in patients than controls (p < 0.001, p = 0.003, p = 0.007, p = 0.005, p < 0.001, and p = 0.034, respectively). However, RV diastolic area, E/E ratio, and mean and systolic pulmonary artery pressure were higher in patients than controls (p < 0.001, p = 0.007, p = 0.005, p < 0.001, p = 0.006, respectively). Conclusions: RV systolic and diastolic functions of normotensive, nondiabetic HD patients are deteriorated as compared to healthy controls. [Ahmed A. Saad, Sami H. Nouh, Magdy E. Mohamed, Nabil F. Hassan, and Ibrahim A. Mohammed. Echocardiographic Assessment of Right Ventricular Function in Normotensive Non Diabetic Hemodialysis Patients. N Y Sci J 2017;10(7):15-20]. ISSN 1554-0200 (print); ISSN 2375-723X (online). http://www.sciencepub. net/newyork. 3. doi:10.7537/marsnys100717.03.
DOES GENDER MATTER ON MOBILE GOVERNMENT (M-GOVERNMENT) SERVICES ACCEPTANCE? AN EXPLORATORY STUDY

In the smart cities era, mobile government (m-government) projects became faster and more advanced due to the high penetration of smart phones among citizens. Several studies identified factors influence citizens’ acceptance of m-government. However, gender was not considered in those studies, so this paper attempts to investigate and conceptualize the major factors that influence adoption of m-government and gender as a moderating variable. This paper highlighted the major influence factors namely (perceive ease of use, perceive usefulness, social influence, and awareness) and conceptualize them in a unique model where the gender is moderating or controlling the relationship toward citizens’ adoption of m-government.The proposedframeworkhighlighted the main factors to understand the citizens’ perception of m-government from gender point of view. This may result more efficient and cost effective efforts and operations as well as resource allocation. Furthermore, it is significant especially fordeveloping countries, which may facilitate to faster andsuccessful implementation. In summary, this study attemptsto provide benefits for both practice and research.
Evaluating diagnostic significance of magnifying narrow band imaging endoscopy in various gastric lesions

Background: Narrow-band imaging (NBI) is a novel endoscopic technique that may enhance the accuracy of diagnosis by using narrow-bandwidth filters in a red-green-blue (R/G/B) sequential illumination system. In the current study we try to evaluate the diagnostic significance of magnifying narrow band imaging endoscopy in various gastric lesions, this may provide an early diagnosis of malignant and premalignant changes of the mucosa with enhanced selection of appropriate treatment, as gastric malignancy is one of the most common malignant tumors, and is the second commonest cause of cancer deaths worldwide. Methods: The current study included 101 patients whose upper gastrointestinal endoscopy showed different gastric lesions not in active bleeding and those patients were reevaluated by using magnifying narrow band imaging technique. Biopsies were taken from these target lesions for histopathological examinations. The presence of gastric carcinoma and high grade intraepithelial neoplasia in the biopsy samples was considered as a positive pathological result, which is used to assess the accuracy of endoscopic diagnosis. Results: There were differences in the accuracy, sensitivity, specificity, PPV and NPV of the magnifying narrow band imaging (ME-NBI) endoscopy in detecting presence of dysplasia or neoplasia in different gastric lesions. With overall sensitivity 63.6% which is superior to that of conventional white light imaging (C-WLI) endoscopy (36.3%). Conclusion: Magnifying NBI is more sensitive than conventional white light endoscopy in detection of high grade dysplasia and early gastric cancer in different gastric lesions. But, still MENBI endoscopy is not sufficient to replace conventional histopathology. [Yahia Al-Shazly, Mohammed Abd El Moghny Mostafa, Nanees Ahmed Adel Abd Elmageed, George Safwat Riad and Eman Abdel-Salam Ibrahim. Evaluating diagnostic significance of magnifying narrow band imaging endoscopy in various gastric lesions. J Am Sci 2013;9(12):115-123]. (ISSN: 1545-1003). http://www.jofamericanscience. org. 17
Maximize Crop Water Productivity of Garlic by Modified Fertilizer Management Under Drip Irrigation

Semiarid regions forced to maximize utilization from available of water unit, which is a significant factor that affecting not only the agricultural productivity but also extended reclamation projects. Field experiment was conducted in two successive seasons in the Production and Research Station of National Research Centre, Nubaria, Behera Governorate, Egypt, to study the effect of surface and subsurface drip irrigation methods on garlic yield under different organic manure source. Results showed that the highest and lowest values of the soil bulk density and soil hydraulic conductivity were recorded at sub-surface drip irrigation and NPK and ChM and FYM ChM and FYM under surface drip irrigation system relative to NPK treatments and FYM enriched by 50 % NPK. Organic manure used enriched by 50 % NPK or in specific ratio between both lead to increase all the garlic growth characters. FYM enriched by 50% NPK has the best performance to improve garlic yield with exceed consume of NPK fertilizer from side and from the other one reduced soil pollution by mineral fertilizers and the impact of FYM enriched by 50 % under surface drip irrigation by 19 % comparing with NPK treated plot. Surface drip irrigation has a pronounced effect on garlic yield than sub-surfac drip. Garlic yield increased by 18.7 % above sub-surface one. Garlic yield was positively correlated (5% level) with bulb diameter and clove length. Surface drip irrigation has superior effect on the garlic water crop productivity and the increase was highly after of FYM application enriched by 50 % NPK fertilizer than others. Obtained results data mentioned that the vital role of continuous application of the organic manure in maximizing not only the garlic yield and the other studied growth characters that help in maximizing yield but also improve studied soil hydrophysical properties under investigated irrigation methods.