Miracle-dz/UniFAR-FTUs huggingface dataset:
THE PREVALENCE OF ANXIETY AND DEPRESSION AMONG MOTHERS OF CHILDREN WITH AUTISM SPECTRUM DISORDERS AND ATTENTION DEFICIT HYPERACTIVITY DISORDER IN MADINA, SAUDI ARABIA

Background: Of child with autism, parents especially mothers pose a substantial role in the care and support and compared with other parents they go throw many considerable challenges to handle with their child illness. Studies on parents of a newly diagnosed autistic child have proved that parents have raised levels of posttraumatic stress disorder and depression. [14,15] Parents mostly liable to anxiety wish can be attributed to demands of dealing with their autistic child. [16,17,18,19,20,21,22] Aims & Objective: To explore the prevalence of anxiety and depression among mothers of children with Autism spectrum disorders and attention deficit hyperactivity disorder in Madinah Saudi Arabia. Material and Methods: For mothers’ diagnostic assessment, we used questionnaire based on Taylor scale for anxiety and Beck scale for depression. All mothers of children with Autism spectrum disorders and attention deficit hyperactivity disorder in Madinah and were obtaining medical care in Al Amal Complex for Mental Health were invited to participate in study. Results: The result of this study show that from 50 mother of children with Autism spectrum disorders and Attention Deficit Hyperactivity Disorder in Madinah The prevalence of mothers who have both anxiety and depression was 18 %. The prevalence of mothers with alone depression was 20%. The prevalence of mothers with alone anxiety was 8 %. Conclusion: Autism and ADHD can affect the mother mental health which should be considered when treating the child. We have to check the mother mental health give them proper treatment if needed, and if there is a need for cognitive behavioral therapy. World Journal of Pharmaceutical Research SJIF Imp ct Factor 7.523 Volume 7, Issue 03, 1365-1372. Research Article ISSN 2277–7105 Article Received on 19 Dec. 2017, Revised on 08 Jan. 2018, Accepted on 29 Jan. 2018 DOI: 10.20959/wjpr20183-10859 *Corresponding Author Raghad Abdulelah Alsayed Saudi Arabia.
Review Paper on Sentiments Analyzer by Using a Supervised Joint Topic Modeling Approach

: In this work, we focus on modeling user-generated feedback and overall rating pairs, and aim to identify semantic aspects and aspect-level sentiments from user feedback data as well as to predict overall sentiments of user feedbacks. We propose a novel probabilistic supervised joint aspect and sentiment model (SJASM) to deal with the problems. SJASM represents each user feedback document in the form of opinion pairs, and can simultaneously model aspect terms and corresponding opinion words of the user feedback for hidden aspect and sentiment detection. It also leverages sentimental overall ratings, which often comes with online user feedbacks, as supervision data, and can infer the semantic aspects and aspect-level sentiments that are not only meaningful but also predictive of overall sentiments of user feedbacks. Moreover, we also develop efficient inference method for parameter estimation of SJASM based on collapsed Gibbs sampling. We evaluate SJASM extensively on real-world user feedback data, and experimental results demonstrate that the proposed model outperforms seven well-established baseline methods for sentiment analysis tasks. Generally, sentiments and opinions can be analyzed at different levels of granularity. We call the sentiment expressed in a whole piece of text, e.g., review document or sentence, overall sentiment. The task of analyzing overall sentiments of texts is typically formulated as classification problem, e.g., classifying a review document into positive or negative sentiment. Then, a variety of machine learning methods trained using different types of indicators (features) have been employed for overall sentiment analysis. However, analyzing the overall sentiment expressed in a whole piece of text alone (e.g., review document), does not discover what specifically people like or dislike in the text. In reality, the fine-grained sentiments may very well tip the balance in purchase decisions. For example, savvy consumers nowadays are no longer satisfied with just overall sentiment/rating given to a product in a review; they
Current Methodologies and Advances in Bio-ethanol Production

Scarcity of non-renewable energy sources has paved need for sustainable and renewable biofuels from biomass. Of all natural resources used for production of biofuel, lignocellulosic biomass (producing second generation biofuel) are most attractive as they are highly abundant and easily available throughout the year. Various measures for maximal and efficient utilization of these lignocellulosic biomass for production of biofuels (bioethanol, biodiesel and biogas) have been taken including pretreatment, saccharification and fermentation process. In the present chapter we have consolidated relevant applications for bioethanol production, which includes a brief overview of the current status and biochemical route towards bioethanol production. Various approaches like tailoring of hydrolytic enzymes to increase the specific activity of particular enzymatic reaction and contributions by prominent scientists for effective utilization of celluloses and hemicelluloses for bioethanol production have been discussed. We have also highlighted the comparison on utilization of simple sugars (hexoses and pentoses) by bacteria and fungi and described the recent advanced techniques utilized for the production of ethanol.
Evaluate the Performance of Video Transmission Using H.264 (SVC) Over Long Term Evolution (LTE)

- In recent years, the mobile Internet has increased dramatically with the development of 3G and 4G technologies. Especially the usage of mobile broadband internet on the devices like cellular mobiles, Tablets and Laptops has skyrocketed. Among the multimedia applications video streaming is the most popular mobile application. But, making these services available to users in a cost effective way without compromising quality is a big challenge. The development of Long Term Evolution (LTE) technology in the mobile world made this task achievable. The features of LTE technology provide effective services in multimedia applications with high data rates and low latency. The aim of this paper is to evaluate the quality of service (QoS) performance over LTE.
IMPLEMENT ATION OF MODIFIED SELECTIVE MEDIAN FILTER IN FPGATOWARDS THE DETECTION OF BREAST CANCER

In medical image processing, noise removal is the challenging task. Removal of noise using the existing methods like Median Filter (MF), Center Weighted Median Filter (CWMF), Rank Condition Rank Selection Filter (RCRSF) and SMF Selective Median Filter (SMF) provides satisfactory results. In this paper, we have made improvements in SMF by providing the adaptive thresholding concept and called as Modified Selective Median Filter (MSMF). Mean square error (MSE) and mean absolute error (MAE) has been calculated and the performance are compared. The performance of MSMF is better than the other methods and it is also implemented in field programmable gate array (FPGA). We found this method works good for the noise removal in mammograms for the detection of breast cancer. Furthermore, the method has been tested for the sample image mdb218 taken from mammographic image analysis society (MIAS) and the results found were good.
MULTIFEATURE EXTRACTION BASED PALMPRINT IDENTIFICATION WITH FEATURE NORMALIZATION

: Palmprint based recognition is accepted nowadays as it provide features like minutiae features, principal lines, orientation field and creases. Verification or the identification of an individual is based on these features. Palmprint recognition is characterized by its uniqueness, reliability and stability. Palmprint recognition has been used for civil applications, access control applications and law enforcement. The main contribution of paper includes extraction of multiple features like principal line, minutiae, orientation field. After that applying the features normalization method on extracted features which reduces the feature vector length and matching time. These normalized features are further used for identification of user by matching the features. For feature normalization, PCA based Gaussianization technique is used. After normalization of the features time required to match the features will be reduce. An error rate of user identification will also reduce. Database used is of high resolution (i.e. 500 dpi) images of TUMPALMLAB to increase the security as it provides more information. Identification rate of the system is 98.20% and Equal Error Rate 0.1%.
CAVITATION RADIO FREQUENCY VERSUS MESOTHERAPY ON ABDOMINAL ADIPOSITY

Abdominal obesity, also known as beer belly, beer gut, pot belly or clinically as central obesity, is when excessive abdominal fat around the stomach and abdomen has built up to the extent that it is likely to have a negative impact on health. There is a strong correlation between central obesity and cardiovascular disease. (1) Abdominal obesity is not confined only to the elderly and obese subjects. (2) Abdominal obesity has been linked to Alzheimer's Disease as well as other metabolic and vascular diseases. (3)
Recent development and challenges in processing of ceramics reinforced Al matrix composite through stir casting process: A Review

† Use of Composites are increasing day by day because they offers advantages such as low weight, corrosion resistance, high fatigue strength, faster assembly, etc. MMCs posses significantly improved properties including high specific strength, specific modulus, damping capacity and good wear resistance compared to the unreinforced alloys. It is durable and highly efficient for automobile or aircraft. It exhibits higher competence for machining complex shapes with greater accuracy. Homogenous Continuous reinforcements can result in dramatic improvements in MMCs properties, consist of lightweight metal alloys, but cost remains high. Cost reduction can be achieved by cheaper reinforcements, simpler fabrication methods. It is possible to tailor their properties as per the requirement of various industrial applications by suitable combinations of matrix, reinforcement and fabrication method. This paper presents an up-to-date review of progress and benefits of different routes for fabrication and machining of composites. The purpose of this review to provide a reliable scientific basis for the researchers planning to synthesize particulate reinforcement, Wettability, porosity MMC in the stir casting.
Design of Mobility Implementation into an ATM Networks

:- The world of telecommunication is rapidly changing. The capabilities of wireless networks are improving at a steady pace. This paper presents a design for implementing mobility into an Asynchronous Transfer Mode (ATM) network. The vision is ATM based wireless telecommunication network that is capable of supporting a variety of today’s application with roam to grow for advanced application of the future. One of the major design issues in the Wireless ATM is the support of inter-switch handoff. This objective of this paper is to study the various rerouting schemes and the path optimization schemes required to perform the inter-switch handoff. We discuss here the various issues involved in the mobility in the ATM and then we study the various rerouting schemes that can be used for the handoff in an ATM Wireless Network.
Data Access Privilege With Attribute-Based Encryption and Users Revocation

—Cloud Computing Providers tremendous advantages, like flexibility, low cost on usage, on demand accessibility. But various privacy problems are related to the privacy, because data are stored on cloud server. To solve the problem related to the data privacy various schemes are proposed based on the attribute based encryption techniques, still more attention is on privacy of the data content and the access control of the data and less attention is on the privilege control and the privacy of user’s identity. In these papers presents Anony Control scheme which address data privacy as well as users identity privacy also presents Anony Control-F for fully preventing the identity problems. In proposed scheme we add user revocation in users to enable activating and deactivating users to enhance efficiency of system and adding more feasibility. Revoked users are maintained in the revoke user list, will decide which user should may in cloud storage server to access data or which will remove. The data access privilege will be depending upon misbehavior of user in cloud server.
Pyloric Stenosis as Cause of a Venous Hypertensive Syndrome Mimicing True Shaken Baby Syndrome

The SBS hypothesis arose out of attempts to explain the origin of a series of clinical features recognized as forming a syndrome. This syndrome produced intracranial haemorrhages without evidence of external injury to the head. It appeared that the only way such injuries could be produced was by rotational inertia, such as might occur during manual shaking of the infant. Another feature of this syndrome was some prior dysphagia. It had been noticed that:“The infant may have a history of poor feeding, vomiting, lethargy, and/or irritability occurring for days or weeks prior to the time of initial health care contact”. This was construed as a provoking factor that could cause some emotionally vulnerable carers to shake the infant. The syndrome became known as Shaken Baby Syndrome [1]. The concept of SBS has subsequently been modified, renamed, broadened etc but this initial definition, closest to the unexplained syndrome originally recognized, is referred to in this article as True Shaken Baby Syndrome.
Cure-Rate Survival Models in Clinical Trials

Advances in therapy have made cure a possibility for some cancers. For example, multiple myeloma (MM) is generally considered an incurable disease [14], but recent research suggests that some MM patients could be cured. Investigators at the University of Arkansas for Medical Sciences (UAMS) have developed an approach called total therapy (TT) that has recently been shown to cure up to 30% of MM patients [13]. The most common regression model for survival data, the proportional hazards (PH) model [12], is often not appropriate for heterogeneous patient populations including both cured and uncured patients because the PH assumptions fails [37]. In this situation, alternative models are needed, and a number of cure regression models have been proposed for this type of data. Cure models can be useful for applications where patients are not technically “cured,” but rather there is a proportion of patients who will not fail during the follow-up of the study. These patients can be referred to as long-term survivors rather than cured. Cure models often can more adequately describe survival trends when CONTENTS
Current trends in reducing microbial adhesion to acrylic denture base resins

The adhesion of microorganisms and the formation of dental plaque on acrylic denture surfaces are the primary causes of several oral diseases such as radicular decay and oral stomatitis. [1] Acrylic polymethyl methacrylate resins (PMMA) was one of the first materials used for provisional crown and bridge restorations. To form the polymer, PMMA prepolymerized fine particles are mixed with a liquid monomer resulting in chains of polymer. PMMA provisional materials are susceptible to bacterial adhesion and colonization when compared to materials used for final restorations due to the increased surface roughness and possible inferior fit provided by the temporary restoration. [2] This is especially true when these temporary restorations are unexpectedly worn for long periods of time.
Kaluza-Klein Cosmological Models with Barotropic Fluid Distribution

Submit Manuscript | http://medcraveonline.com CMB radiation is one of the fluids preferred while another is a perfect fluid represent by the matter content of the Universe [5]. Recently, many researchers investigated different aspects of FRW cosmological models and Kaluza-Klein cosmological models [610] in the context of f(R,T) theory of gravity. Higher dimensional plane symmetric cosmological models studied by Mete et al. [11] and Amirhashchi et al. [12] also conferred interrelating two-fluid viscous dark energy models in a non-flat Universe. In particular, Samantha & Debata [13] have considered two-fluid cosmological models in Kaluza-Klein space-time.
Robust & Efficient Power Management Technique For MIMO Network Interfaces

— In this paper we proposes a new methodology called as “Antenna Management” , which provides a high degree of efficient use of power and power management in high speed wireless networks and high data rate mobile wireless systems. This technique is particularly very usefully in the case of MIMO network interfaces, which contains a number of components and as well as RF chains. The objective of this project is to efficiently manage the available power among the large number of antennas in MIMO systems, and also satisfies all the requirements of MIMO like bit error rate, data rate, minimize energy per bit etc.In this paper we provide a systematic procedure to validate the energy efficiency and benefits of proposed method i.e. Antenna Management. Finally using this paper we provide a great solution for Power requirements by efficiently and effectively managing the all active antennas in MIMO systems.
A New Parallel Partition Prime Multiple Algorithm for Data Mining

- One of the important problems in data mining is discovering association rules from databases. Each transaction contains a set of items. Discovering the frequent itemsets require a lot of computation power, memory and input/output values, which can only be provided by parallel computer. In this paper, we proposed a new Parallel Partition Prime Multiple Algorithm for association rule mining. Proposed algorithm addresses the shortcoming of previously proposed Parallel Buddy Prima Algorithm. The proposed algorithm divides transaction database equally according to their assignment of variable for each processor. The decision of assignment of next transaction to the processor depends on the value of count variable of itemset per transaction. It reduces the time and data complexity.
Putative Role of Micro-RNAs in Female Reproductive Tract

Female reproductive tract is composed of ovarium, oviduct, cervix and uterus. Development and function of reproductive tract is dispensable for maintenance and achievement of reproduction. Reproductive tract responses to cyclic changes and ovarium hormones which provide optimum conditions for gamete movement and development. While the potential influence of pituitary and gonadal hormones on reproductive function is clearly understood, the molecular mechanism regulating reproductive tract remains elusive. Although, post-transcriptional gene regulation has critical role in cell differentiation and proliferation, little information is available in post-transcriptional gene regulation in reproductive tract. Post-transcriptional gene regulation includes splicing, processing, transport and translation of mRNA. In addition, role of RNA binding proteins and recently discovered miRNAs were also implicated in reproductive tract.
Virtual Backbone Scheduling For Balancing Energy Efficiency In Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are key for various applications that involve long-term to monitor physical or environmental conditions such as temperature, sound, vibration, pressure, motion or pollutants and to cooperatively pass their data through the network to a main location. In these applications, sensor nodes use batteries as the sole energy source. Therefore, energy efficiency becomes critical. To meet this challenge, this paper proposes, a novel sleep-scheduling technique called Virtual Backbone Scheduling (VBS). In contrast to earlier MAC protocols designed for general-purpose networks.VBS is designed for WSNs has redundant sensor nodes. VBS forms multiple overlapped backbones which work alternatively to prolong the network lifetime. In VBS, traffic is only forwarded by backbone sensor nodes, and the rest of the sensor nodes turn off their radios to save energy. Keywords—Wireless sensor networks (WSNs), backbone scheduling, sleep scheduling, virtual backbone, energy-delay tradeoff,
Recent and the Latest Developments in Rapid and Efficient Detection of Salmonella in Food and Water

Salmonella is a leading cause of foodborne diseases. Gastroenteritis caused by nontyphoid Salmonella is still a major infectious disease in the world. About 95% of Salmonella infections are caused by ingestion of contaminated food and water. Rapid, sensitive, and efficient detection and identification of Salmonella from foods and water are critical for minimizing the spread of outbreaks caused by this pathogen. These methods can be applied to track the food source of contamination or by early diagnosis of the infections in a clinical setting. Culture-based methods for detection of Salmonella are laborious and time-consuming, typically taking 5-7 days to obtain a pure culture and serovar identification. In the past few decades, molecular-based technologies have greatly shortened the time for detection and identification of bacterial pathogens from food and water, and drastically increased the specificity and sensitivity of the assays. In this review, we report an update on the development of rapid and efficient methods for the detection and identification of Salmonella in food and water, focusing on the approaches for concentration of Salmonella cells and viable cell detection, as well as the advantages and drawbacks of these methods.
MOBILE BANKING AND TECHNOLOGY ADOPTION: PERSPECTIVE OF CHANDIGARH YOUTH

The study aims at adapting the technological acceptance model (TAM)for the use of mobile banking service by the youth of Chandigarh. Four dimensions were focused upon, namely perceived ease of use, perceived usefulness, attitude and awareness and behavioral intention to use. In light of this, the study extends these essential dimensions and factors in order to expand in line with the banking business especially in using mobile banking services. The development of the two hypotheses was based on the dimension of study as well as on the related literature. A questionnaire consisting of (16) questions covering the dimension and hypotheses of the study was designed in order to collect the required data for examining hypotheses and reaching conclusions. The standardized questionnaire used in this study wasdistributed to a sample of (114) youth of Panjab University, Chandigarh. The hypotheses were tested using baron and Kenny model.It was found that all the variables used in this study has given the relationshipbetween the dimensions of conceptual model. The statistical analysis showed positive (strongest) correlation between all these dimensions between perceived ease of use and behavioral intention to use mediated by awareness and attitude with a value of coefficient correlation.As for the dimension, a stronger correlation was found between perceived usefulness and behavioral intention to use mediated by awareness and attitude with a value of coefficient correlation.
Detecting Distributed Denial of Service Attacks Using Hidden Markov Models

Distributed Denial of Service (DDoS) attacks considered the most critical attack for cyber security and serious security threat to Internet services in recent years. These attacks have evolved to be increasingly sophisticated, complex, and difficult to mitigate and detect. In this paper, we propose a new approach using HMM to detect DDoS attacks. The performance of the proposed approach is generally better and achieve higher detection rate and lower false positive rate comparing with two other machine-learning algorithms Naive Bayes and Neural Network. Training and testing applied on a DDoS data set with reduced feature. Using the reduced feature set after applying the Feature Pruning algorithm that we implemented obtains a significant improvement in detection performance and reduction model training and testing time.