Miracle-dz/UniFAR-FTUs huggingface dataset:
International Journal of Soft Computing and Engineering

VANET is a vehicle communication platform in which the vehicles can communicate with other vehicles either directly or through infrastructure unit named as RSU (road side unit). The density of the network depends upon several factors and condition of roads. In urban cities, the densities of vehicles are high whereas in rural area, the density can vary. Therefore, vehicle to vehicle communication faces problems in while communicating through VANET and the developer needs to design an infrastructure that can resolve this problem. In this paper, we are presenting a comparative analysis of various routing techniques used in VANET. The main issue that find in VANET communication is the selection of an appropriate routing protocol. Therefore, to know about the advantages, disadvantages and application of four different routing algorithms named as position based, geo based, cluster based and topology based a comparative analysis has been performed.
Analysis on Comparing the Performance of Alpha Miner Algorithm on MYSQL and Oracle

— Process mining is a field that analyses the event log to discover, enhance and improve business processes and check performance between run time and design time business processes. The event logs are stored in databases. Many databases are available for handling and saving huge data like Oracle and MYSQL. However there are certain applications for which some databases do not implement. MYSQL has emerged for handling such applications. For this alpha miner algorithm is the most widely used technique. Our objective is to compare the performance of MYSQL and Oracle under process mining. We implement the alpha miner algorithm on row oriented database in database query languages. We present a performance benchmarking and comparison of α miner algorithm on row oriented databases to store massive event logs and analyse it in seconds to discover a process model.
“A REVIEW ON IMAGE RETRIEVAL USING HYPERGRAPH”

– Retrieving images similar to query image from a large image collection is a challenging task. Image consists of different regions. There are several methods in the literature which are useful to capture region level similarities between pair of images using graph. Each image can be represented by several visual concepts. Visual concept is the object or part of the image having some visual information. There are several images in the database which can be sharing the same visual concepts. Graphs are fails to capture the relationship between multiple vertices. Hypergraph is useful to represent group relationship between multiple vertices. Consider database images as a vertices and visual concept as a hyperedge of a hypergraph. All the images sharing same visual concept, form a hyperedge. Ranking methods on these hypergraph is design, to rank all the images in the database which are relevant to the query. Top k images are retrieved from these images which will handle query relevant image retrieval.
Graphical User Authentication Using Random Codes

- Now a days user authentication is one of the most important topic in information security . In this project, we propose a new graphical password scheme for authentication. Here user selects number of images as a password and while login user needs to enter the random codes generated below each image, which has been set as a password. The GUA (Graphical User Authentication) or simply Graphical based Password on the fact that humans tend to remember images better. This type of interface provides an easy to create and remember passwords for the users. This Scheme provides a way of making more user-friendly passwords. Here the security of the system is very high and every time user needs to enter different set of random codes for authentication i.e. every time new password gets generated for every login attempt. Dictionary attacks, Brute Force attack, shoulder surfing attack and spyware attack are infeasible on this password scheme.
Heart Disease Prediction System using Data Mining Techniques: A study

---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - Data Mining is the process of non-trivial extraction of implicit, previously unknown and potentially useful information from data. A pattern is interesting if it is valid for a given test data with some degree of certainty, novel, potentially useful and easily understood by humans. The huge amount of data generated for prediction of heart disease is too complex and voluminous to be processed and analyzed by traditional methods. Advanced Data Mining tools overcome this problem by discovering hidden patterns and useful information from complex and voluminous data. Researchers reviewed literature on prediction of heart disease using data mining techniques and reported that Neural Network technique overcome all other techniques with higher levels of accuracy[5][6]. Applying Data Mining techniques on healthcare data can help in predicting the likelihood of patients getting heart disease. This paper highlights the important role played by data mining tools in analyzing huge volumes of healthcare related data in prediction and diagnosis of disease.
Dissipation of imidacloprid on sweet orange fruits

Dissipation pattern of imidacloprid residues in fruits of sweet orange and elimination of its residue through washing were studied at North region, Hisar, Haryana, India during Kharif season year 2014-15. Residues were determined by highperformance liquid chromatography (HPLC). The average initial deposits of imidacloprid on the sweet orange rind was found to be 1.12 and 2.33 mg kgand in thecase of pulp it was 0.13 and 0.32mg kgfrom treatment at the recommended and double the recommended dose, respectively. The residues dissipated with time regularly in both the cases showing 70% dissipation in case of rind and showing 97% dissipation in case of pulp. The residues show 79.53 % reduction on 0 (2h after spray) day due to washing in single dose and 84.62% in case of double dose.
Validation of the Lot Quality Assurance Sampling Method Using House-to-House Polio Campaign and Routine Immunization Data in Butaleja District, Uganda

The Lot Quality Assurance Sampling (LQAS) method has been growingly used in evaluating public health interventions in decentralized settings. We assessed the validity of LQAS method against results of data generated from highly monitored house-to-house polio vaccination of supplemental immunization activities; and that of data generated from routine immunization and supplementation. This study was conducted in Butaleja district, Uganda. It was a descriptive cross-sectional study that was executed in 2011. We collected community-based data by interviewing 228 mothers of children of various age categories each to assess for coverage of oral polio vaccine, routine vaccination and supplementation using the LQAS method. We also reviewed records of vaccination with oral polio vaccine during the supplemental immunization activities of 2010 and 2011 and collected data on routine immunization and supplementation from the child registers and tally sheets from health facilities. We compared the point estimates for the latter two against 95% CIs for the weighted coverage of the same antigens and supplements for LQAS survey. We found out that point estimates for house-to-house polio vaccination were within the 95% CI for weighted coverage of LQAS survey indicators for all the four rounds. Coverage for 7 of the 9 indicators of routine immunization lay within the 95% CI of weighted coverage of the same indicators generated from LQAS survey. We computed non-adjusted and wide-CI-adjusted global accuracy-levels of 84.6% and 81.8% respectively for LQAS. We concluded that LQAS method can generate accurate information for decision making at districts when all quality standards are adhered to. Managers of health services can reliably adopt this sampling method to assess district performance; and compare differential performance across service indicators and supervision areas in order to enhance evidence-based prioritization and resource allocation in decentralized settings.
Mechanism of Arsenic Tolerance in Klebsiella pneumoniae (HQ857583)

Arsenic is a well-known toxic chemical and listed as a known carcinogen by the Environmental Protection Agency (EPA) and the World Health Organization (WHO, 2001). It is the 20 abundant element in the earth s crust but is widely distributed in the environment being released from both natural sources, e.g. by volcanic action, during weathering of rocks and mining as well as from anthropogenic ones, such as pesticides (e.g. calcium arsenate dimethylarsonate, disodium methylarsenate), production of paints and dyes, application of dusts from burning of fossil fuels, semiconductor industry, processing of pressure-treated wood [e.g. chromated copper arsenate (CCA)], coal combustion, high-temperature combustion and smelting of metals (Cullen and Reimer, 1989). In nature, the most common oxidation states for soluble arsenic exist as pentavalent arsenate [As(V)] and trivalent arsenite [As(III)] (Bhattacharjee and Rosen, 2007).
Development of a psychologically-based treatment for chronic pain in Singapore : patient and healthcare professional inputs, theoretical model and a feasibility trial

2 TABLE OF CONTENTS . 4 LIST OF FIGURES . 9 LIST OF TABLES . 10 ACKNOWLEDGEMENT . 11 ABBREVIATIONS . 13 CHAPTER 1: GENERAL INTRODUCTION . 15 1.1 Thesis Overview . 17 1.2 Summary of Chapters . 18 CHAPTER 2: THE PROBLEM OF CHRONIC PAIN: AN OVERVIEW . 20 2.1 Chapter Overview . 20 2.2 Definition of Chronic Pain. 21 2.3 Prevalence of Chronic Pain. 21 2.4 Economic and Healthcare Burden of Chronic Pain . 21 2.5 Impact on Work and Productivity . 22 2.6 Efficacy of Medical Treatments . 23 2.7 Evolving Views of Chronic Pain . 32 2.8 Conclusion . 38 CHAPTER 3: THE DEVELOPMENT OF PSYCHOLOGICAL TREATMENTS FOR CHRONIC PAIN . 39 3.1 Chapter Overview . 39 3.2 The Early Years . 40 3.3 The Operant Approach . 42 3.4 Cognitive-Behavioural Models . 45 3.5 Fear-avoidance Model . 51
Role of Image Segmentation in Digital Image Processing For Information Processing

Digital Image processing is a technique using computer algorithms to perform specific operations on an image, in order to get an enhanced image or to extract some useful information from it. Image segmentation, an important phase in image processing, is the division of an image into regions or categories, which correspond to different objects or parts of objects. This step is typically used to identify objects or other relevant information in digital images. There are generic methods available for image segmentation, but each method has to be applied in a particular context combining the domain information of that particular domain
A Survey on Image Steganography & its Techniques in Spatial & Frequency Domain

— Steganography is an intelligent art of communicating in a way which hides the endurance of the communication. The image steganography technique takes the asset of confined power of visual system of human being. The art of hiding information such that it averts ferreting out of hidden messages is getting very popular nowadays, which is referred as Steganography. The word Steganography has been educed from the two Greek words - Steganos , which mean covered or secret and Graphy mean writing or drawing. There have been many techniques for hiding information or messages in images in such a manner that the modifications made to the image are perceptually undetected. This paper proposes the evaluation of a few techniques of the Image Steganography in spatial domain and frequency domain. The Image Steganography techniques in spatial domain that would be discussed are Least-Significant-Bit (LSB), LSB Replacement, LSB Matching, and Bit Plane Complexity Segmentation Steganography and frequency domain techniques to be conferred in this paper are Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT), Discrete Fourier Transform (DFT) and Singular Valued Decomposition (SVD). Steganography technique is intended to be compared with the Watermarking Technique.
Genetic diversity and structure of two populations of Ambystoma altamirani and A. rivulare of the trans-Mexican volcanic belt.

The most important factor leading to amphibian population declines and extinctions is habitat degradation and destruction. To help prevent further extinctions, studies are needed to make appropriate conservation decisions in small and fragmented populations. The studied mole salamanders are micro-endemic, and their habitat is found in the most ecologically disturbed region in Mexico: The Trans-Mexican Volcanic Belt. The goal of this study was to provide data from the population genetics of two micro-endemic mole salamanders that can be used as a basis for future research and conservation planning of these species and other amphibian species of this region of Mexico. We analysed the genetic diversity and structure, effective population size, the presence of bottlenecks and inbreeding coefficient of 152 individuals from two Ambystoma species. For A. altamirani, two locations were sampled, as well as for A. rivualre; 38 tissues were collected from each locality. We found medium to high levels of genetic diversity expressed as heterozygosity in the populations. However, all the populations presented few alleles per locus and genotypes. Each sampled locality represents a population with a significant level of genetic structure. The effective population size is small but similar to that of the studies from other mole salamanders with restricted distributions or with recently fragmented habitats. Despite the high levels of genetic diversity found, the populations are going through bottleneck processes and their habitats are fragmenting and degrading. Therefore, this study is important to propose better management plans and conservation efforts for these species.
Utilization of Kangaroo Mother Care (KMC) and Influencing Factors Among Mothers and Care Takers of Preterm/Low Birth Weight Babies in Yirgalem Town, Southern, Ethiopia

Background: Kangaroo mother care (KMC) is a universally available method of care particularly, for premature babies for maintaining their body temperature. However, its prevalence is very low in Ethiopia. Thus, this study was intended to assess utilization of kangaroo mother care (KMC) and factors influencing among mothers and care takers of preterm /low birth weight babies in Yirgalem town, southern, Ethiopia Materials and Method: A community based cross sectional study was conducted from of February to March, 2017 among 215 mothers of preterm/low birth weight (LBW) infants in Yirgalem town. Mothers of preterm/LBW infant of age less than 36 months were included in study. Data was collected by using interviewer administered questionnaire that is adapted from relevant literatures and standardized accordingly. Data analyses ere accomplished using SPSS version 20. Logistic regression analyses were used to identify the association of different variables. Results: A total of 215 mothers with their preterm infants ranged 1-36 months of age voluntarily participated, with response rate of 100%. A hundred ninety (88.4%) of the mothers had normal vaginal delivery, and 11.6% had cesarean section. Among all study subjects 90(41.9%) practice KMC. Of these, 31(14.4%) started KMC immediately after birth as the infant had been stabilized, and 59(27.4%) practice it after 24 hours. However, only sixty of the infants showed improvement after they used continuous KMC at home compared to those infants that did not use KMC. It was found that some variables were statistically associated with the utilization of KMC. Respondents who gave birth spontaneously were 4.3 times more likely to practice KMC than those had caesarean section delivery [(AOR 4.341) 95%CI(1.435, 13.130)] and mothers who delivered at governmental hospital were 20.4 times more likely to practice KMC than those who gave birth at home [(AOR (20.458) 95%CI(2.644, 158.299))]. Conclusion: In this study only very low mothers initiated KMC immediately after birth and were practiced continuously KMC at home. Thus, it is recommended to promote KMC at home and develop studies on acceptability and applicability of the KMC and affecting factors that prevent the use of KMC at home method in Ethiopian context.
Long Short-Term Memory Recurrent Neural Network based Mobility Prediction in MANET

A Mobile Ad hoc NETwork (MANET) is formed by a gathering of wireless nodes without any infrastructure and the wireless nodes are not static but dynamic in nature. The mobile nodes can be connected together dynamically to route data packets from other mobile node present in the network. The mobility of the nodes is a significant feature in the MANET. The nodes follow one of the different mobility patterns which affect the connectivity among the other nodes. The dynamic changes in the connectivity decides the performance of the routing protocol and hence the performance of the overall network. When considering these characteristics of the MANET it becomes essential to predict the mobility of the nodes in both service-oriented and as well as application-oriented aspects of the dynamic networking. At the network level the mobility prediction is useful in pre-configuring services, provisioning of QoS and reservation of net-work resources and whereas in application level the end user can be provisioned with route guidance, information on network traffic and broadcasting important information to users. The mobility prediction will lead to the estimation of the stability of the routing paths and the distances between the neighboring nodes. This helps to improve the overall performance of the network by reducing the frequent link failures and increasing packet delivery ratio. In this paper, a novel mobility prediction method is developed using the historical time and positioning data. Auto Regressive Integrated Moving Average (ARIMA) and Long Short Term Memory (LSTM) with Recurrent Neural Network (RNN) are utilized for mobility prediction based on the sequence of time series data
Role of Total Quality Management (TQM) as a Tool for Performance Measurement in Small and Medium-sized Enterprise (SME’S) in Ghana

In the phase of globalization and internationalization, businesses and organizations around the globe have launched Total Quality Management (TQM) programs in an endeavor to gain or remain competitive in this dynamic business environment. Herein, this paper focuses on the role of total quality management (TQM), as a management tool effect on SME’s in Ghana as far as performance measurement is concerned. The researchers used both purposive sampling and accidental techniques for a sample size of four hundred and fifty (450) respondents. SPSS Statistics version 20.0 was utilized to analyze the data. Correlation and regression was executed to ascertain the significant level of the variables chosen for the study. Inferences from the analysis proved that all the independent variables had a positive correlation with the dependent variable, hence the statistical findings of our hypothesis were supported. It is therefore recommended that in order to improve performance of SME’s, management should do their best to address the concerns of the few customers to maximize the level of customer satisfaction and the Government of Ghana Original Research Article Kwamega et al.; BJEMT, 10(3): 1-10, 2015; Article no.BJEMT. 20806 2 through the Ghana standard board and Ministry of Trade and industry must institute a national quality award where quality criteria will be set for firms.
SOME RISK FACTORS AFFECTING THE PREVALENCE OF BALANTIDIUM COLI IN CATTLE AND THEIR BREEDERS IN BABYLON, IRAQ

A cross section study was carried out to determine the prevalence of Balantidium coli infection in cattle and their breeders and to evaluate the risk factors including the gender, age and region. A total of 200 cattle fecal samples and 100 breeder fecal samples were collected foe different ages and sexes in Babylon. All samples were collected during the period from January to June -2016. The results showed that the prevalence of Balantidium coli were 22.00% and 12.00% in cattle and their breeders respectively. The differences between infection rates due to sex and age were not significant. However, females cattle were lower at risk (OR=0.67; 95% CI0.34-1.32) as compared with male cattle but with no significant effect (P=0.25). Also the age showed that cattle at age 1-<3 were lower at risk (OR=0.47; 95%CI 0.16-1.30) but with no significant effect (P=0.14). Based on the results of this research, it can be concluded that cattle are highly susceptible to balantidiasis irrespective of gender and age.
Habitat Wise Variation in Periphytic Microalgal Assemblages in the Vazhachal forest division of Chalakkudy River basin

The microalgal community as primary producers has to play a significant role in the biotic and abiotic interactions of any aquatic ecosystem. Any change in the habitat can alter the normal algal functions, thus inducing major changes in its community structure. Whenever a community is exposed to different habitat, variation in responses can occur because of the difference in the potential of the individuals to acclimatize. The habitats also impart changes on the organism and selection can occur favouring resistant genotypes within a population, and selection among species can result in changes in the community structure (Forbes and Forbes, 1994). The ability of periphytic microalgae to grow and prosper in a habitat is the outcome of a series of complex interactions between hydrological, climatic and nutrient factors (Biggs, 1996). The variability of the periphytic organisms in the ISSN: 2319-7706 Volume 3 Number 6 (2014) pp. 649-658 http://www.ijcmas. com
Can Pre-Transplant Quality of Life Scores Predict Post-Transplant Mortality in Adolescents with Cystic Fibrosis?

of a thesis at the University of Miami. Thesis supervised by Professor Alexandra Quittner. No. of pages in text. (36) Introduction: Cystic fibrosis (CF) is the most common indication for pediatric lung transplantation and ranks number three for adults. However, using the current criteria for selection and timing of a transplant, the survival benefit of this procedure in pediatric patients is controversial (Liou & Cahill, 2008). Modification of the current selection criteria has the potential to reduce mortality rates both for those on the waitlist and those who receive a transplant. Use of the Cystic Fibrosis Questionnaire-Revised (CFQ-R; Quittner et al., 2012), a well-validated, disease-specific quality of life measure may improve pre-transplant decision-making and thus, reduce mortality. Methods: This multi-center study evaluated whether specific domains on the CFQ-R (i.e., Physical Functioning, Respiratory Symptoms) and parent proxy reports on the CFQR (i.e., Health Perceptions, Vitality, Role/School Functioning) predicted mortality 4 years post-transplant for the Transplant group (n=28) and 2 years post-evaluation for the Waitlist group (n=35). These analyses controlled for physical predictors (i.e., age, CFrelated Diabetes (CFRD), FEV1 % predicted), to assess whether the CFQ-R added additional and unique variance. Cox Regressions were used to measure the overall impact of the CFQ-R scales and Receiver Operating Characteristic (ROC) curves were used to assess the sensitivity and specificity of optimal cut-points of significant CFQ-R domains.
An NLP Based Plagiarism Detection Approach for Short Sentences

 Abstract: The notable issue in the fields of plagiarism detection is, to assess the semantic similarity between obfuscated sentences, and it becomes more completed in case of short sentences (only 4-8 words). An innovative approach, typed dependencies relationship (TDR), based on Natural Language processing is presented for detecting plagiarism on short sentences. In this study proposed approach performed on previous datasets of short sentences and compared results with 3 state-of-art methods. The investigation shows that the proposed calculation has exceptional execution in taking care of sentences with complex linguistic structure.