Miracle-dz/UniFAR-FTUs huggingface dataset:
A Noble Remote User Authentication Protocol Based on Smart Card Using Hash Function

-The security issues are always raised for remote authentication service. Smart card based authentication protocol is best suited for authenticate legitimate user. Developing secure authentication protocol is a strong challenge. There are many potential attacks that are targeted at authentication such as insider attack, offline password guessing attack, masquerade attack, server spoofing attack, and parallel session attack. Recently many previous proposed schemes are fail to resist these attacks. In this paper we introduce a remote authentication protocol that provides secure mutual authentication process and session key agreement. Our proposed protocol is providing better security to resist all possible attacks. In this protocol, we use low computing cost hash function and random nonce. We use random nonce to avoid complexity of time synchronization. The proposed protocol is efficient and practical. It is easy to adapt in low-weight devices like the subscriber identity module.
A REVIEW OF FRICTION STIR PROCESSING OF ALUMINIUM ALLOYS USING DIFFERENT TYPES OF REINFORCEMENTS

Friction Stir Processing (FSP) is a relatively new surface modification technique for alloys and composites. By using FSP the enhancement in the mechanical properties can be achieved. In this paper, the review of work with reinforcements (SiC, B4C, and Al2O3) on the aluminum alloy and the effect of the factors of the tool has been done and it has been seen that after employing the reinforcement the properties such as hardness, wear resistance, tensile strength of the reinforced alloy improved significantly.
Analysis of Mobile Phone Impact on Student Academic Performance in Tertiary Institution

— The usage of Internet enabled mobile phones is a 21st century experience which covers various operations. This research work examines phone usage and identified the effects internet enabled mobile phones have on the academic performance of students at the tertiary institutions using the Federal Polytechnic students of Ilaro, Ogun State in Nigeria as a case study. The research work was performed so as to understand and also find the correlation between academic performance of students and the usage of mobile phone during class hours which is general believed to be an avenue of distractions to students. The information from this work was carried out using structured questionnaires administered to 45 students to get their individual views. In addition 15 extensive interviews were done concurrently to have a grounded knowledge of the students with the data gathered during the course of this study. Our findings indicated that students are influenced negatively to a great extent by the mobile phone because attention is focused on chatting, music and others while their academic activities are neglected and left to suffer. Also, this study discovered that the use of mobile phone is uncontrollable among students which are the leading cause of poor academic performance among students.
A Study on Various Algorithms to Enhance Classification Accuracy in M-Learning

— This research paper aims to study about the accuracy of categorization by enhancing the preprocessing methods and competent use of evolutionary algorithms for classification. The real world datasets in general contain inconsistent, noisy and incomplete attributes which pose a challenge of preprocessing the datasets. This research paper focuses on extraction and categorization of opinions from the web-documents. As the opinions have many potential applications, mining on the reviews of the M-Learning users are contemplated.
Prediction of Chronic Kidney Disease Using Random Forest Machine Learning Algorithm

: The healthcare industry is producing massive amounts of data which need to be mine to discover hidden information for effective prediction, exploration, diagnosis and decision making. Machine learning techniques can help and provides medication to handle this circumstances. Moreover, Chronic Kidney Disease prediction is one of the most central problems in medical decision making because it is one of the leading cause of death. So, automated tool for early prediction of this disease will be useful to cure. In this study, the experiments were conducted for the prediction task of Chronic Kidney Disease obtained from UCI Machine Learning repository using the six machine learning algorithms, namely: Random Forest (RF) classifiers, Sequential Minimal Optimization (SMO), NaiveBayes, Radial Basis Function (RBF) and Multilayer Perceptron Classifier (MLPC) and SimpleLogistic (SLG). The feature selected is used for training and testing of each classifier individually with ten-fold cross validation. The results obtained show that the RF classifier outperforms other classifiers in terms of Area under the ROC curve (AUC), accuracy and MCC with values 1.0, 1.0 and 1.0 respectively.
Role of Dietary Fibers in the Management of Diabetes Induced Heart Disease in Male Rats

The present study was conducted to evaluate the effect of oat or wheat bran (as a source of dietary fibers) on the heart disease associated with streptozotocin (STZ)-induced diabetes in male rats. As a result of induction of diabetes, the level of serum glucose and lipids (total lipids, triglycerides, total cholesterol, LDL-C, vLDL-C), as well as activity of lactic dehydrogenase (LDH) and creatinine kinase (CK) were increased, while HDL-C level was decreased. This goes in parallel with a significant reduction in the level of serum insulin and T-homocystein (tHcy). Furthermore, a reduction of total protein and glycogen content in the heart of diabetic rats were recorded. In addition, the diabetic rats exhibited marked trend for increased malondialaldehde and protein carbonyl levels, accompanied with decreased glutathione content in the heart tissue, which together with the other reported abnormalities predict development of heart disease as a result of diabetes. In contrast, feeding diabetic rats on diets supplemented with 7% oat or wheat bran was found to be effective in the management of diabetes-induced changes with the greatest effect being achieved with oat bran administration. Thus, it can be concluded that diet high in plant fibers, particularly oat bran is useful in reducing the development of heart disease associated with diabetes. [A. M. El-Wakf, H. A. Hassan, M. M. El-komy and M. M. Amr. Role of Dietary Fibers in the Management of Diabetes Induced Heart Disease in Male Rats. Journal of American Science 2011;7(4):638-649]. (ISSN: 1545-1003). http://www.americanscience. org.
QUANTUM BASED PSO TECHNIQUE FOR IMAGE SEGMENTATION

: Many techniques have been in use for image segmentation some of which use histograms, some of them used spatial while some used fuzzy but none of them worked well under noisy environment. Otsu method is one the thresholding technique which converts the gray scale images into binary image. Thereafter 2d Otsu was adopted which was proven to be more effective than simple Otsu method. 2D Otsu was implemented using histogram to reduce the computation complexity. Further to improve computational efficiency many evolutionary algorithms were proposed of which particle swarm optimization with its simplicity and computationally efficient as it required very few parameters compared to other algorithms like Differential Evolution in which mutation crossover are also taken into consideration. But the particle swarm optimization (PSO) did not do well for problems which were discrete and lead to found in a loop of local optima when dealt with problems in multi-modal. Thus a new technique was adopted named quantum particle swarm optimization (QPSO) which worked on discrete problems very well. Many hybridized QPSO have been proposed like Cooperative QPSO, Cooperative Gaussian QPSO etc. and has been applied for image segmentation. Cultural QPSO has also been proposed which used Cultural algorithms but has not been applied in the field of image segmentation. Thus to obtain a simple and highly reliable and efficient results during image segmentation this algorithm has been applied. It also results in good convergence rate which when compared with PSO, QPSO, CQPSO, CGQPSO. All the findings and results have been done on matrix laboratory (MATLAB). The images that are segmented using QPSO are simple images like temple, ant, leaf. The results that are obtained are satisfactory and are stable with low population and iterations thus the application of the proposed work can be done in the area of medical where deep and enhanced knowledge of images of internal human body organs like brain, lungs are required.
A Review of ZeroAccess peer-to-peer Botnet

— Today ZeroAccess is one of the widespread threats over the internet. The total number of infected systems is in the tens of millions with the number of lively infection. ZeroAccess is a Peer-to-peer botnet that affects Microsoft windows operating systems. It is used to download other malware on an infected machine from a Botnet and works as a platform. ZeroAccess is mostly implicated in bitcoin mining and click fraud, while outstanding hidden on a system using rootkit techniques. In this survey, we will explain the Evolution of ZeroAccess Botnet, the life cycle of ZeroAccess Botnet and concludes what are the challenges in ZeroAccess botnet.
Application of Unified Network Management in LAN for Load Shedding

The differentiated services (DiffServ) model has been proposed as a scalable traffic management mechanism to ensure Internet QoS without using per-flow resource reservation and per flow signaling, but it sacrifices the ability to accurately configure the network devices and efficiently utilize the network resources. In this thesis, the DiffServ model is augmented with traffic engineering tools, per-flow call admission control (CAC), dynamic resource sharing schemes to improve resource utilization efficiency. Specifically, an advanced two-tier resource management (ATTRM) model is proposed for efficient resource allocation over DiffServ networks, which manages network resources based on the “first plan, then take care” principle. By proper boundary service level agreement (SLA) arrangement and path-oriented internal resource mapping, the Internet service provider (ISP) can optimally plan the network resources to achieve the maximum long-term network revenue. To efficiently utilize the well-planned network, novel effective bandwidth techniques are developed for packet-and call-level QoS control in DiffServ networks.
Molecular Analysis of G1691A Mutation in Factor 5 Leiden and its relation with mtDNA common deletion in Human Recurrent Pregnancy Loss

Background: In general, miscarriage is one of the most common complications of pregnancy and it is the pregnancy loss before 20 weeks of gestation or birth weight below500 grams. Recurrent Pregnancy Loss is defined as two or more spontaneous miscarriages. Genetic disorders such as mutations can be involved in miscarriage. Considering the importance of this issue, in this study, G1691A mutation of coagulation factor 5 and common deletion mutation in the mitochondrial genome(4977-bp deletion in mtDNA) were investigated as factors which can influence miscarriage, especially recurrent miscarriage. Materials and Methods: For this study 41 patients with the history of miscarriage and 48 healthy women with successful delivery were selected and completed the questionnaires which included questions such as miscarriage history, age, blood type and then Blood samples were taken. After extraction of DNA from each sample, the studied mutations were determined using PCR method. At the end, analysis of the results and assessment of other important and effective factors in them was done using Epi Info software and using chi square (X) test. Results: Among the patients ,there were 29.25% patients with one miscarriage, 65.85% patients with two miscarriages and 4.9% patients with three miscarriages. There was no homozygous genotype in the study of G1691A mutations in both groups, and prevalence of heterozygotes was 17% among patients and 4.17% among controls. On the other hand, frequency of 4977-bp deletion in mtDNA in patients group and control group was 68.29% and 14.58%, respectively. Analysis showed that frequency of G1691A mutations and common deletion mutation in mtDNA in patients group were higher than controls and were statistically significant . Although the opportunity to have miscarriage in GA genotype and carriers of common deletion is more than control, but there is not any correlation between these two mutations and their inheritability and also they have not affected each other. Therefore, we can use the above mutations as a molecular marker for early detection and timely treatment in patient’s likelihood of miscarriage.
Influence of Dental Education on Oral Health Attitude and Behavior of 1st Year Dental Students through Interns

Objective: The aim of the present study was to assess the influence of dental education on oral health attitude and behavior of the dental students. Methods: This cross sectional study was conducted among dental students using Hiroshima University Dental Behavioral Inventory (HU-DBI) questionnaire written in English and validated through a pilot survey including 20 questions with agree/disagree responses along with information pertaining to level of education. The data was analyzed using the Statistical Package for Social Science (SPSS) version 16.0 software. Results: The total number of participants was 384 comprising of 314 (81.8%) girls and 70 (18.2%) boys. It was found that girls had higher scores of attitude regarding oral health as compared to boys. Regarding educational status, the level of attitude and behavior improved significantly with advancing years of education (p = 0.000). Conclusion: The study revealed positive changes in oral health attitude and behavior among participants and its relation to education, But still more preventive behavior among the students is required.
Evolution of Internet of Things (IoT)

: IoT collaborates of three major domains of technology namely i.e Cloud, IOT (Internet of Things) and Data Mining. The title ‘IOT’ itself is indicative of the fact that this project imparts intelligence to the ‘things’ in IOT which is a concept that envisions all objects around us as a part of the internet resulting in ubiquitous computing. This proposition is attained by proposing a cloud based system wherein smart sensors are embedded on the devices which will continuously monitor their operational status and detecting any fault or failure in the device functioning, it will immediately find an appropriate solution by applying Naive Bayes data mining algorithm on the database inclusive of similar previous instances of malfunctioning and by that resolving the issue without any human intervention.
Diabetic Retinopathy Screening using Machine Learning for Hierarchical Classification

Diabetic Retinopathy is a consequence of prolonged unaddressed diabetes. It is currently diagnosed by the subjective clinical examination and manual grading of the fundus images by the ophthalmologists. This disease is progressive in nature. Hence early detection and treatment go a long way in helping the patients fight the dire consequences of the disease. Given the fact that number of ophthalmologists is very less as compared to the patients, a cost-effective, computer assisted, automated retina analysis system is highly desirable for the rural health care. This paper proposes an automatic Diabetic Retinopathy detection system based on the presence of bright lesions on the retina which is one of the symptoms of Diabetic Retinopathy. Initially the optic disc is removed from the fundus image as its brightness is similar to that of the bright lesions. Exudates are extracted and its various features are obtained. Later, feature based hierarchical classification is performed for detection of different stages of the disease. This method is based on the same logical steps as followed by the ophthalmologists and hence assures more accurate classification results. Two methodologies, Random Forest algorithm and Artificial Neural Network are explored and accuracy, sensitivity and specificity are evaluated at each stage of classification. The former outperformed the latter. The accuracy obtained using Random Forest are 100%, 85.71% and 87.5% and Artificial Neural network are 100%,78.5% and 66.67% for Stage 1, Stage 2 and Stage 3 respectively.
THE IN VIVO ASSESSMENT OF NEUROTOXICITY IN ALBINO WISTAR RATS FED ON LATHYRUS SATIVUS

Lathyrus sativus, rather profoundly known as grass pea, is a legume commonly grown for human consumption and livestock feed in Asia and East Africa. It is of prime importance in drought-stricken and famine affected areas and is thus thought of as an insurance crop as it produces reliable yields when all other crops fail. The seeds of grass pea contain a neurotoxin that causes a neurodegenerative disease when consumed as a primary period on a daily basis. The present study is a strong attempt to evaluate the various traditional processing methods on the composition of grass pea and select the efficient processing method, which makes the food more safe that can prevent lathyrism and protein energy malnutrition. As a result considering the importance of grass pea and the unparallel contribution of improved varieties in the productivity of the crop, the present study was pursued for the In vivo assessment of neurotoxicity using acute oral toxicity tests on Albino Wistar rats using the Rota rod apparatus method and the Incline screen test method. Further, the relationship between the various food processing techniques employed and the neurotoxicological assessments was possible.
TARGET TRACKING SYSTEM IN UNDERSEA WIRELESS SENSOR NETWORK WITH LANDMARK AMBIGUITY

: Iterative algorithm is implemented by means of multi-sink data transmission in underwater vehicle is possible here. It prevents from collision and also improves their throughput performance by working dynamically. This will minimize the bit error rate and gives an improved accurate solution. Target tracking is a method of following an object into number of frames of a video and to find its relative motion with respective to other objects. Using this technique, tracking capability of the system can be increased. The underwater sensor network became more and more popular for monitoring vast area of oceans using tracking systems. The UWSNs provide continuous monitoring for various applications like disaster prevention, pollution monitoring, submarine detection, etc. In this paper various target tracking techniques for object detection were surveyed.
Dietary Intake and Food Preferences of Autistic Children Versus Children with Typical Development: A Comparative Cross-Sectional Study

Consumption of macroand micronutrients and food group servings by children aged 4–13 with autism spectrum disorders (ASDs; n = 103) and typical development (TDs; n = 188) were compared using 3-day diet records. More than 50 percent of ASD children did not meet the RDA levels of adequacy for daily intake of energy, carbohydrate, and fiber. Similarly, TD children (more than 50%) also did not meet the 100 percent RDA requirement for intake of energy and fiber. No significant difference in level of adequacy for protein was observed between ASD and TD groups (p = 0.106). However, a significant difference was recorded for the other macronutrients for age group (4 13) between ASD and TD children. With the exception of vitamin D (p < 0.001), no significant differences were observed in the daily intake of vitamins between ASD and TD children (p > 0.05). No significant difference was found in the intake of iron between the two groups (p = 0.517), whereas the difference in calcium consumption was highly significant (p = 0.010). TD children’s calcium intake tended to be much higher than that of ASD children. In summary, a large portion of the sample of children with ASD and TD did not meet the nutritional recommendation for macronutrients, micronutrients, and minerals.
A Study on Different Approaches for Image Restoration

: One of the major problem while capturing the image is the improper image extraction because of bad light or the camera problem. Because of this, some of the important features or the object visibility over the image is not retrieved effectively. In this present work, a study of different problems associated with image processing along with relative solutions. The paper has discussed some common approaches to repair the images. In this paper window based analysis is analyzed based on neighbor pixels so that effective image generation will be performed.
Multi Authority Access Control in Public Cloud Storage System

Data access control is an efficient scheme to grant information security within the cloud but as a result of information outsourcing over the cloud servers which are untrusted, the data access management has become a troublesome issue in the public cloud. Attribute-based cryptographic (ABE) technique is taken into account as a most trustworthy cryptographical conducting tool to make sure data owner’s direct control on their info in public cloud storage. The previous ABE schemes involve just one authority to require care of the whole attribute set, which could bring a single-point hindrance on every security and performance. Paper planned an efficient revocable decentralized manner CP-ABE information access management technique for multi-authority systems, wherever there exist multiple authorities and every authority is prepared to issue attributes independent to each other.