Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancement of the Performance of the Medium Access Control (MAC) Protocol by using Modified New Approach

— Wireless networks are the widely used networks for communication now days. Hence it is very necessary to improve the performance of the Medium Access Control (MAC) layer by preventing the communication from collisions. In this work a new scheme is explained, for efficient channel access, which is based on the sequencing. The proposed method minimizes the number of collisions as well as the delays that occur during the backoff periods. When collision occurs in a MAC layer in the network, it may result in decreased throughput in the data transfer. In this way the bandwidth is wasted. Here an analytical study on MAC-layer issues is presented, which are very important when accessing a channel over wireless networks. The main function of Medium Access Control (MAC) is to share the channel efficiently between all nodes. The new approch is used in order to prevent collisions during multiple channel access in MAC Layer. This scheme uses fair distributed mechanisms for channel access. In this method, a counter is introduced at each node to maintain the discipline of the nodes. It is based on the concept of sequencing technique. As the routing protocol, AODV is used in this method and NS-2 is used for simulation environment. The proposed method minimizes the number of collisions in data transfer and increases the throughput along the network. The performance of the proposed method is evaluated under various conditions, and the obtained results are very promising. Also the proposed scheme shows that the energy requirements are minimum due to the limitation on the number of transmissions while reducing collisions in the MAC layer.
INTRA UTERINE INSEMINATION OUTCOME FOLLOWING THE DRILLING OF POLYCYSTIC OVARIAN SYNDROME OF INFERTILE WOMEN

Background: Polycystic ovarian syndrome (PCOS) is one of world wild problem, affecting women during their reproductive age. The PCO and PCOS in Iraqi women are found as the first common cause of infertility with negative response to medical treatment . One of the second line of treatment is Laparoscopic ovarian drilling (LOD) that used to induce ovulation in women with PCOS. Objective: The objective of the present study is to investigate the effect of PCO drilling on pregnancy rate following intrauterine insemination (IUI). Patients, materials and methods: Fifty couples were involved in current study during the period from September 2013 to July 2014. Laparoscopic ovarian drilling was done for the spouses after confirming diagnosis of PCOS by laparoscopy . The women were inseminated either through intrauterine insemination or natural intercourse into two groups depending on the results of husband semen analysis. Results: There was a significant (P<0.01) decrease in LH ,testosterone and prolactin hormones with elevation in progesterone level following the LOD operation compared to before the drilling of PCOS women. The pregnancy rate following IUI was 8% and after natural intercourse was 20%. and total pregnancy rate was 14%. Conclusions: This study concluded that LOD must be recommended as line treatment option for treatment resistance of PCOS women. The drilling is effective to turn back a normal levels of reproductive hormones and ovulation with successful pregnancy . Therefore LOD considered the ultimate clinical endpoints for studies on female infertility treatment. World Journal of Pharmaceutical Research SJIF Impact Factor 5.990 Volume 4, Issue 8, 300-308. Research Article ISSN 2277– 7105 Article Received on 12 June 2015, Revised on 03 July 2015, Accepted on 24 July 2015
Face Matching Using Geometrical Analysis of Different Face Parts

: This paper presents a robust face matching algorithm which will match two faces. We have used geometrical analysis of the different face parts for matching two faces. At first face regions will be detected from the both pictures. Then the position of different face parts (left eye, right eye, nose, and mouth) will be extracted from both faces. Then their positions will be analyzed and based o the analysis matching decision will be taken. Results of experiments with and without spectacles show that the proposed approach is not only robust but also quite efficient.
Scheme Critic-An Automated Opinion Mining System for Policy Making

Social has become mainstream and ubiquitous. Our day-to-day life has always been influenced by what people think and most of the conversations are being carried out online. At the same time, citizens are becoming more enthusiastically engaged in policy issues, more empowered, and more demanding in their relations with traditional ones. Researchers identify a hunger for and reliance upon peer advice and recommendations found online and this information hunger is strongly evident in the political sphere. In any policy making considering the opinion of the public is considered to be most crucial. Around the globe governments and policy makers are working on to improve their performance by creating systems which will facilitate them in understanding their performance. However, people have difficulty, owing to their mental and physical limitations, producing consistent results when the amount of such information to be processed is huge. Automated opinion mining systems are thus needed, as subjective biases and mental limitations can be overcome with an objective opinion analysis system. The everrising expectations from ordinary citizens provide a continuing force for policy makers to provide more services and with higher standards of quality. These pressures are also reason enough to find more cost effective ways of operating so that policy makers can do more with less. The system developed helps to tap into citizen generated content helping the policy makers more effectively engage with the citizens. It helps end users actively force social media for outreach, communication and engagement with the citizens and to identify the key initiatives required to enhance citizen delight by using the concepts of sentiment analysis. In this paper, we showcase-Scheme Critic -An aspect based opinion mining system which has been developed to help the policy makers in framing their policies by collecting opinions from twitter. It is used to measure the quality of the schemes, their outputs and to measure the outcomes and impacts resulting from these outputs. We demonstrate our system based on different schemes launched in India.
Supervised vehicular operation using WAN

The need for vehicular supervision system is of the utmost need due to the sheer number of vehicles plying every day on our roads. With the rise in numbers of vehicles, there is also an increase in the need to prevent potentially fatal on-road incidents. Drowsiness and fatigue are large contributors to most on-road accidents. Prevention of such accidents can be achieved using a drowsiness detection system and drivers emotion recognition. Such a system employs recognition of facial expressions to identify emotions using a camera. The feed from the camera is processed to obtain instances of drowsiness or stress. Accordingly, tasks can be triggered such as slowing down or stopping the vehicle.
An Empirical Study on Power Optimization for Android based Mobile Devices

The current lifestyle of humans involves a wide range of electronic gadgets. The dependencies on mobile devices like laptops, smartphones, tablets and wearables for everyday activities have outburst and raised an urge to improve the battery life of such devices. The demand for thin and light weight devices restricts the battery size and capacity embodied to these devices. The advancements with respect to the mobile applications are way too quick compared to the innovations in the battery technology. All these factors impose the need for power optimization techniques. This paper gives overview of development of Android operating system, identifies the major power draining sinks of a generic mobile device and summarizes the various techniques the application developers should be aware of before developing mobile applications which utilize the available power wisely and provides best user experience. The techniques general for all the mobile devices irrespective of the operating system and the techniques specific to Android based devices are discussed briefly. The impact of the generic optimization techniques for the mobile device is discussed with the help of the data obtained by the experiments. This study comes handy for Android application developers. It also benefits other operating system developers to achieve software optimization for their mobile applications.
To Propose A Novel Technique to Isolate and Detect Virtual Side Channel Attack in Cloud Computing

— Cloud computing is one of the most important technology of networking which is widely used in these days. Cloud computing has some security issue also. There are several types of attacks which can be launch on cloud very easily and has many serious effects on the network. This paper discussed the proposed scheme to overcome the adversary effects of virtual side channel effects.
The Behavior of Beta in the 19 Century

This paper uses completely new data to study the variations in beta when it deviates from the constancy assumption presumed by the market model. The concentration of the literature on beta is based on post 1926 data. This makes the 19 century Brussels Stock Exchange (BSE) data a very good out-sample dataset to test beta variations. Various models proposed in the literature to capture the variations in beta were studied. Blume’s correlation techniques reveal that beta is not stable at the individual stocks level and that the stability can be fairly improved by portfolio formations. Using root mean square error (RMSE) criterion, it was shown that the market model betas are weak in predicting future betas. The predictability can be improved by adjusting betas with the Blume and Vasicek mean reversion techniques. Further results from this study reveal that few stocks have lead or lag relationship with the market index. Small sized stocks were detected to be more prone to outliers. In effect betas in the 19 century exhibits similar pattern as betas in the post 1926 era.
A Survey on Text Classification with Different Types of Classification Methods

: Text classification approach gaining more importance because of the accessibility of large number of electronic documents from a variety of resource. Text categorization (Also called Text Categorization) is the task of assigning predefined categories to documents. It is the method of finding interesting regularities in large textual, where interesting means non trivial, hidden, previously unknown and potentially useful. The goal of text mining is to enable users to extract information from textual resource and deals with operation such as retrieval, classification, clustering, data mining, natural language preprocessing and machine learning techniques together to classify different pattern. A major characteristic or difficulty of text categorization is high dimensionality of feature space. The reduction of dimensionality by selecting new attributes which is subset of old attributes is known as feature selection. Feature-selection methods are discussed in this paper for reducing the dimensionality of the dataset by removing features that are considered irrelevant for the classification. This paper surveys of text classification, several approaches of text classification, feature selection methods and applications of text classification.
VISUAL ASSESSMENT AND CLASSIFICATION OF SURFACE SOIL TYPES IN DRYLAND AND FADAMA AREAS OF KEBBI STATE, NIGERIA

The need for background information outlining the basic characteristics of surface soil types in the savannah areas is essential for environmental soil management. Visual assessment and classification of surface soil condition is a key to environmental soil management and development. In this study, Visual Soil Assessment (VSA) was used to assess and classify the surface soil condition of dryland and fadama sites of Kebbi State, Nigeria. The results show that the most common soil types, which have dominated great part of fadama and dryland agricultural sites in Kebbi State, are Alfisols, Aridisols, Calcisols, Histosols, Inceptisols, Mollisols and Vertisols. The study highlighted some of the basic characteristics of these soil types. The findings of the study provide an improved understanding of the basic meaning of surface soil condition for proper sustainable soil management of dryland and fadama soils in Kebbi State, Nigeria.
Health-related quality of life of women with nausea and vomiting in pregnancy attending a maternal clinic in Nigeria

Purpose: This study evaluated the health related quality of life of women with nausea and vomiting of pregnancy attending a maternal clinic in Nigeria Methods: A cross-sectional study was conducted on women with nausea and vomiting of pregnancy(NVP) attending ante-natal clinic at a secondary health facility. The NVP-specific quality of life questionnaire developed for women within 12 weeks of pregnancy was used in this study with some modifications. A total number of 119 women made up the study sample. Data was analyzed using SPSS version 20.Mean scores were presented with standard deviations and domain scores were compared using the mean transformed scores. Results: One hundred and nineteen pregnant women who had NVP at the time of the study participated in the study. The mean total quality of life score was 112.16±33.3 and 53.7% had an average quality of life. Domains on Limitation had a mean transformed score of 27.90 while domain on Fatigue had a mean transformed score of 50.94 depicting better and worse quality of life respectively.Conclusion: The findings showed that women in this locality were able to carry out their normal daily activity irrespective of the impact of nausea and vomiting on them.Members of the healthcare team should however work at improving the quality of life of women with NVP in this locality.
3D Object Extraction from 2D Object

- The gesture recognition is to be studied vigorously, for the communication between human and computer in an interactive computing environment. Lots of studies have proposed the efficient methods about the recognition algorithm using 2D camera captured images. There is a limitation to these methods are exist, such as the extracted features cannot represent fully the object in the real world.
Significance of Emotional Intelligence in the Indian Retail Industry: A Review Study

Introduction of modern retailing in the form of multi-complexes that offers shopping, food and entertainment under one roof along with growing awareness and brand consciousness among people across different socioeconomic classes in India has led to a rapid growth in the Indian retail industry. Since, salespersons in the retail business are the only link a company has with their customers, the performance of salespersons largely affects the long-term relationship of a company with its customers. Some individuals are better in recognizing and regulating emotions in themselves and others. This set of abilities is termed as emotional intelligence. Emotional intelligence is the ability to perceive emotion, integrate emotion to facilitate thought, understand emotions and to regulate emotions to promote personal growth (Mayer & Salovey, 1997). Emotional intelligence can be used as a human-resource development instrument, as improvements in emotional intelligence enhance salesperson’s interpersonal and communication skills which help them in providing quality services and improving their relationship with the customers. In this competitive scenario where Indian companies have to compete with multinational brands, they can have an edge over their competitors if they are having customer-responsive and emotionally intelligent workforce. Thus, the present paper discusses how enhancing emotional intelligence can lead to higher performance of sales professionals in Indian retail industry, thereby flourishing and strengthening the industry. Significance of Emotional Intelligence in the Indian Retail Industry: A Review Study Paper ID IJIFR/ V2/ E5/ 056 Page No. 1518-1528 Subject Area Commerce
Automated Approach for Detecting Tuberculosis using Chest Radiographs

Tuberculosis is one of the major health problems in many parts of the world. Due to multi-drug-resistant bacterial strains have increased the problem, tuberculosis still remains a challenge. Mortality rates of patients with tuberculosis are high when left undiagnosed and untreated. Standard diagnostics depends on methods developed in the last century which are slow and unreliable. In an effort to reduce the complexity of the disease, this paper presents our automated approach for detecting tuberculosis using chest radiographs. At ﬁrst we extract the lung region using a graph cut segmentation method. From this extracted lung region, we compute a set of texture and shape features, which enable the X-rays to be classiﬁed as normal or abnormal using a binary classiﬁer.
Patient of Foot Ulcer Diabetes Identification Based on Smartphone

: Our System a novel wound image analysis System implemented solely on Gmail Smartphone. Now-a-day‟s many people face to Foot ulcer. The Aim is to identify foot ulcer by Smartphone. The camera on the Smartphone with the assistance of an image that captured the wound image using Smartphone, it is easy to capture wound image at that time patient are active participants in their own care. After that by using mean shift Algorithm Smartphone performs wound segmentation. Doctor can easily analyse the problem through image & Segmentation. According to patients with diabetes these technique is easy to use Smartphone device for self-management of foot ulcer. The outline of foot ulcer & accurate wound area are detected by the image segmentation. The processing algorithm of mean Shift Algorithm & K-mean Algorithm both are Accurate & well suited for the available hardware & computational resource that can be provided by the candidate through image capture & image processing.
Evaluation of thyroid dysfunction as a candidate surrogate marker for efficacy of sunitinib in patients (pts) with advanced renal cell cancer (RCC)

5126 Background: Sunitinib is a multi-target tyrosine kinase inhibitor with anti-angiogenic and anti-proliferative activity mediated by signal blockade of VEGFR1/2, KIT, PDGFR α/β, and FLT-3. Sunitinib has recently been approved for the treatment of RCC. Several studies have identified biochemical thyroid function test (TFT) abnormalities in approximately 2/3 of pts under sunitinib treatment. The possible association of the incidence of sunitinib-induced thyroid dysfunction and progression-free (PFS) and overall survival (OS) has not been analyzed yet. Methods: Thyroid function was evaluated prospectively in pts with advanced RCC on days l and 28 of each treatment cycle. Sunitinib was given at a daily oral dose of 50 mg 4 weeks on, 2 weeks off. For the statistical analysis the Kaplan-Meier method was used to construct curves for PFS and OS. The log-rank test was used to compare between pts with and without biochemical thyroid abnormalities. The analysis has been performed with SAS (version 9.1). The alpha.
ANALYSIS EFFICIENY OF GRAPH COMPUTATION BASED ON PARTITIONING TECHNIQUES

Graph computation system performance is generally affected by the quality of graph partition. The balance factor and small edge cut ratio is used to measure the quality of graph partition. A balance graph partition with small edge cut ratio is generally preferred since it cut down the expensive network communication cost. Even so, according to the study of the Giraph, the execution over well partitioned graph strength is even two times worse than simple random partitions. This system only optimize for simple partition strategies and cannot efficiently handle the increasing workload of local message processing when high quality graph partition with the encryption process is used. In this paper, we provide a new processor and dynamic concurrency control models. The new message processor at the same time processes local and remote message in a unified way, the dynamic model adaptively adjust the concurrency of the processor based on the online statics.
Identifying Factors Likely to Influence the Use of Diagnostic Imaging Guidelines for Adult Spine Disorders Among North American Chiropractors

57 Introduction. 59 Methods . 60 Data analysis and management . 63 Results . 64 Discussion . 67 Conclusion . 74 References . 87 Chapter Three Impact of guideline dissemination strategies . 95 Abstract . 97. 97 Introduction. 98 Methods . 99 Data analysis and management . 102 Results . 104 Discussion . 105 Conclusions . 108 References . 116
A COMPARATIVE STUDY OF EFFECTIVENESS OF ONLINE LEARNING AND TRADITIONAL FACE TO FACE LEARNING AT SECONDARY LEVEL By

Technology is revolutionizing education today. The present study was undertaken to compare the effectiveness of online learning and traditional face to face learning at secondary school level.The sample of the study included total 80 students of class IX randomly selected from of D.A. V. Senior Secondary School of Yamuna Nagar on the basis of locality, parental occupational background and parental income. Two group pretest posttest research design was used to conduct this study. Results from the analysis of data reveled that students having rural background of both groups were not differ significantly in pre-test and it was also found that students having rural Abstract
TITLE: Energy Efficient and Collision Aware Routing Algorithm for Wireless Sensor Networks

A wireless sensor network (WSN) is a acquiring of sensor nodes that dynamically self-organize themselves into a wireless network without the utilization of any pre-existing infrastructure. Energy Efficient is a critical feature of wireless sensor networks, because sensor nodes run on batteries that are generally difficult to recharge once deployed. Clustering the sensor nodes using Energy Efficient Distributed Clustering algorithm to achieve these goal. In this work, an Energy Efficient Distributed algorithm based on Ant Colony Optimization Algorithm (EEDC-ACO) with Sleep Scheduling Multiple Target Tracking Algorithm to maximize the network lifetime. SSMTT algorithm, schedule the sensor node that will make them awake from sleep mode to active mode when needed. It improves the energy efficiency of sensor node as well as prolongs the network lifetime. In this proposed approach will provide optimal solutions in terms of efficient energy utilization and enhanced network lifetime.
Counterfactual Thinking and Gender Difference Effect on Voting Decision

General elections globally have been characterized by large or low turnout of voters. Numerous reasons has been suggested as plausible explanations of voting decision during elections. We adopted a 2x2 factorial design to test the effects of counterfactual thinking and gender differences in the voting decision of Nigerian voters during the 2019 general election. One hundred and twenty (60 male, 60 female) National Diploma 1 students of a Federal Polytechnic (age range = 19-27, mean age = 22.37, SD =2.85) participated in the study. Counterfactual thinking was varied into downward and upward counterfactual conditions, while gender was categorized into male and female electorates. The counterfactual voting thought, and the reasons to vote questionnaire were the stimulus materials used to assess counterfactual thinking and voting decision respectively. Analysis of variance (ANOVA) result revealed significant main effects for counterfactuals and gender on voting decision. The interaction of counterfactual thinking and gender had nosignificant effect on voting decision, (p>.05). The implications and limitations of these findings were discussed and suggestions were made for future studies