Miracle-dz/UniFAR-FTUs huggingface dataset:
Online Oversampling Principle Component Analysis for Streaming Data Problems

— In a network unauthorized access to a computer is more prevalent that involves a choice of malicious activities. Hence it is essential for a system to be aware of normal system activities. Data mining is the process of summarizing information from various perspectives. Confessing of sensitive information poses another security risk when large amount of interrelated data is processed. This is where intrusion detection plays a vital role in identifying the suspect. Several data mining approaches for intrusion detection have been proposed as a countermeasure and anomaly detection is one such technique. However , most anomaly detection methods are typically implemented in batch mode, and thus cannot be easily extended to large scale problems without sacrificing computation and memory requirements. In this paper , the system propose an online oversampling principle component analysis (osPCA) algorithm is used to detect the presence of outliers from a large amount of data via an online updating technique. In terms of accuracy and efficiency, the osPCA is preferable for online large scale or streaming data problems.
An Improved binarization based algorithm using minutiae approach for Fingerprint Identification

 Abstract - T he long history of fingerprint, their extensive use in forensics and with need of automatic personal identification in recent years, fingerprints is receiving a lot of attention. There is misconception that fingerprint identification is a fully solved problem. However numerous fingerprint systems currently available which use minutiae based approach still do not meet performance requirement of several civilian applications. Performance of these systems degrades with deterioration in the quality of fingerprint image. In absence of an a priori enhancement step most of the binarization based techniques do not provide satisfactory results when applied to low quality images. Thus trying to eliminate these shortcomings we present an improved approach for fingerprint recognition providing accurate automatic personal identification. In this approach we use optical sensor which captures image of excellent quality with large capture area and superior reliability. The recognition algorithm first use histogram equalization technique to improve the global contrast of an image, then enhancement of the image is done by an efficient enhancement technique. We then use binarization based method to extract minutiae. False minutiae are removed using thresholding technique. The matching is based on determining the total number of matched minutiae based on Euclidian distances. This system is tested on two different databases. The experimental result shows that incorporating a fast enhancement technique and using an optical scanner increase the accuracy of the system for lower values of False accept rate.
Vehicle Detection Using Image Processing and Fuzzy Logic

Vehicles moving on road are of importance because problems like traffic congestion, economic waste, jamming on the underpasses and over-bridges (if the vehicle passing through is not of the permissible size) are associated with them. These problems can be dealt with; by using various morphological processes based image processing techniques to detect the vehicles. In this paper, the images of moving and still vehicles have been taken and an algorithm is used for vehicle detection which is based on image processing techniques and classification of vehicles in the form of natural description( in linguistic terms) based on fuzzy logic
Design, development and evaluation of ethosomal gel of fluconazole for topical fungal infection

In the present investigation efficiency of ethosomes as novel lipid carriers for topical delivery of fluconazole has been evaluated. Ethosomes were optimized by varying concentration of phospholipid and ethanol. Ethosomal formulation (F8) with soya phosphatidylcholine (3%) and ethanol 20% was optimized. On characterizationspherical, unilamellar vesicles with smooth surfacewere observed under transmission electron microscopy (TEM) in the range of 5 to 200 nm.Zeta potential of F8 formulation was found to be 4.16 mv. Drug entrapment efficiency of F8 formulation was found to be 90 %. The optimized formulation exhibited pH (8) and viscosity (73,200 cps). Physical evaluation of ethosomal gel was done.In vitro release of F8 formulation was carried out which showed 92 ± 0.79 % release over a period oF8 hours.Skin irritation study revealed no irritation from ethosomal gel.From the data obtained after plotting various models it was observed that the higuchi model was found to be best suited with R value of 0.9678. Stability studies performed at 40°C ± 1°C and 25oC ± 1oC for 3 months showed good storage stability. No phase separation was observed in the optimized ethosomal gel.Results suggested that ethosomes as efficient carriers for fluconazole topical delivery.
Antibacterial and Cytotoxicity Studies of

Plants are important sources of medicinal products, they are recognized for their ability to produce a rich source of secondary metabolites and humans have long before now used many species to treat various kind of disease and ailment [1]. Barringtonia asiatica is a species of Barringtonia native to mangrove habitats on the tropical, it is a common plant in the Malaysian Mangroves and wetlands such as the Kuching wetlands Sarawak and Bako National Park,
Robust Method for Testing the Significance of Bivariate Correlation of Ordinal Data

The Tau’s statistics were introduced to solve the problems of tied data but its effect on shape of table cannot be ascertained. This study compares the non parametric approaches for testing the significance of bivariate correlation for ordinal data based on table shape (square and rectangular table). The bootstrap method was used to compare the magnitude of the correlation values and the associated standard error of the values of tau’s -b, c and Gamma over a square and rectangular table. The Gamma was found to be the most robust statistic for computing the correlation of ordinal data Keywords: Tau statistics, Gamma, ordinal correlation, Bivariate correlation
Root Biomodification Agents: A Closer Look

The ultimate goal of periodontal therapy has always been to achieve predictable regeneration of the periodontium at the diseased site. However the pathologic process of periodontitis results in a denuded and contaminated root surface with destruction of the attachment fibres. Conventional periodontal treatment procedures do not result in new connective tissue attachment or periodontal regeneration. The modification of this diseased root surface has thus been the means to achieve periodontal regeneration. Chemical root biomodification has been the most frequently attempted method to achieve this. A large variety of chemical root biomodification agents have been proposed from the conception of this mode of therapy. This review is a compilation of the various agents used for root biomodification, with a brief look at the historical background and a summary of literature on each of these agents.
The Determination of the Proximate Composition and Sensory, Chemical, Microbiological Quality of the Fish which are Sold by Retail in Sinop, Turkey

− In this study, the horse mackerel (Trachurus mediterraneus), whiting (Merlangius merlangus euxinus), red mullet (Mullus barbatus ponticus) and picarel (Spicara smaris) fish that are widely consumed in Turkey were bought from three fish markets (1, 2, 3). After being taken to the processing laboratories in the fisheries faculty in foam boxes with ice, the fish were analyzed in terms of sensory, chemical, physical (aw) and microbiological characteristics. For this purpose; skin, gill, color and texture analyses, chemical quality (TVBN, TBA) and proximate composition analysis (Raw protein, raw fat, raw ashes and moisture) were evaluated.
Health at Home System Design for Remote Patient Monitoring

This paper focuses on the design and development of the Health at Home (H@H) system for remote patient monitoring. The system is integrated with the windows PC for data acquisition. The implemented design contains Disease Detection Algorithm (DDA) for disease detection and metabolic parameter monitoring on health at home platform. Regular realtime monitoring in human beings is needed for early detection of abnormalities in metabolic parameters and prevention of disease occurrence. The general conditions of a person‘s body depend on many vital parameters which lead to consideration towards the system design. The system focuses on the monitoring of vital signs and work as early detection of disease. The proposed system consists of sensing devices and sensor processing using Arduino for remote monitoring of vital signs in human beings. KeywordsSensing Devices,Wireless Sensor Network,H@H, Arduino, DDA,Real-Time Monitoring. __________________________________________________*****_________________________________________________
OG3_OA_Arati EDIT

Background: To determine the socio-demographic and obstetric causes of uterine rupture, the case fatality rate and association of these factors with maternal mortality among patients of uterine rupture. Methods: A retrospective study between January 2010 to December 2011. Result: During the study period, 18637 deliveries were conducted and 69 cases of uterine rupture were admitted giving the incidence of 0.37% of deliveries. Of the 69 women 53.5% had spontaneous uterine rupture. Among these the most frequent factor (40.5%) was mismanaged labour leading to prolonged & then obstructed labour. The case fatality rate was 10.1%. Factors like age, parity, status of antenatal care, site of rupture & presence of shock did not show any statistically significant association with maternal mortality from uterine rupture. Conclusion: A more vigilant approach to prevent prolonged and obstructed labour in delivery units around SCB medical college is required to reduce the incidence of this condition. Strengthening emergency obstetric care at all level of health care delivery system can help in anticipation, early diagnosis and resuscitation to reach the referral centre safely, thereby reducing the case fatality rate of uterine rupture.
MMukatash GN, Zaid R. Al-Zobe (2016) Implant-Supported Fixed Dentures Versus Implant-assisted Over-Dentures: A Prospective Follow up Study of the ability of Prosthetic Rehabilitation in the Mandible to Achieve Patient

Background: Clinical experiences showed that most patients prefer the fixed prosthetic replacement of their missing teeth over the removable modalities, therefore this study was conducted to compare implants survival rate, prosthetic rehabilitation results and patient satisfaction in two groups of patients using lower conventional complete dentures which were replaced by either implant supported fixed dentures or implant assisted over-dentures. Patients and methods: Fifty patients with edentulous mandible were studied. An approval of the different treatment conditions and types for replacement of their lower missing teeth was obtained from all studied patients and the study protocol was approved by the ethical committee of the royal medical services armed forces in Jordan. An implant-supported fixed dentures (ISFDs) were made to half of them, and implant assisted over-denture (IODs) to the other. The implant fixtures were selected with the same length and diameter and inserted by the same clinician. All the delivery of the prosthesis was done after 6 weeks period of the insertion time. The radio-graphical examination and patients’ satisfaction were performed after 6 months, 1 year and 3 years. Results: The survival rate of all implants used for rehabilitation was (100 %). The mean crestal bone resorption was 1.1 (SD = 0.7) after 3 years examination period in patients using ISFDs and 1.5mm (SD = 0.7) in patients using IODs. Unsurprisingly, patient’s satisfaction with ISFDs was higher than that with IODs. Conclusion: Both the treatment modalities are efficient prosthetic option for mandibular rehabilitation of edentulous mandible. Although many patients still prefer the fixed option, both modalities improved patient satisfaction and oral health quality of life.
Analysis Techniques for Data-Driven Hint Generation for Code-Writing Intelligent Tutoring Systems

Introductory programming is an essential part of the curriculum in any engineering discipline in universities. However, for many beginning students, it is very difficult to learn. In particular, these students often get stuck and frustrated when attempting to solve programming exercises. One way to assist beginning programmers to overcome difficulties in learning to program is to use intelligent tutoring systems (ITSs) for programming, which can provide students with personalized hints of students’ solving process in programming exercises. Our goal in this paper is to review and classify analysis techniques that are requested to generate data-driven hints in ITSs for programming. The paper also proposes several research directions.
Comparative Study of Block Chain and Artificial Intelligence Metrics to Provide Security and Privacy for the Growth of Organizations

: Artificial intelligence and block chain are the two major technologies that lead the innovation and change almost every industry from automotive to healthcare. Both are among the key drivers behind innovation today and introducing radical shifts in every aspect of our life and predicted to contribute trillions of US dollars to the global economy. AI, as defined by Marvin Minsky and John McCarthy—the fathers of the field—is any task performed by a program or a machine that seems to require intelligence. AI systems often exhibit the following behaviors associated with human intelligence: reasoning, planning, learning and problem solving, as well as social intelligence and creativity. The recent resurgence in AI is fueled by breakthroughs in machine learning, especially within the field of deep learning. It has also been driven by the explosion in available data, making the training of machine learning algorithms more effective. A blockchain is a open ledger, mutual and agreed on by all users in a distributed network . to do business it presents a new model and describes how big data analytics, blockchain, and artificial intelligence strength us to rethink present business models and develop organization’s that will be ready for human–machine interactions[2]. Blockchain will help AI's decisions be more transparent, explainable, and trustworthy. As all data on blockchain is publicly available, AI is the key to providing users with confidentiality and privacy.
IN VITRO & IN VIVO ANTIOXIDANT AND HEPATOPROTECTIVE POTENTIAL OF CARALLUMA ADSCENDENS VAR. ATTENUATA AGAINST ETHANOL TOXICITY

: Caralluma adscendens var. attenuata is a succulent plant grows in tropical areas. It has been reported for the presence of phenolics, flavanoids, tannins etc., which are responsible for antioxidant activity and hepatoprotection. Several biological activities like anti diabetic, anti-inflammatory and anti-ulcerogenic were also reported. The present study was aimed to evaluate invitro antioxidant property as the prime step to carryout invivo antioxidant and hepatoprotective activity of methanolic stem extract of this plant. In vitro antioxidant activity was evaluated by determination of total phenolics, flavonoids content, reductive ability and free radical scavenging activity assays. In vivo studies were performed against ethanol induced liver toxicity in rats using Silymarin as standard. In this study serum catalase, superoxide dismutase, reduced glutathione levels were quantified. The results obtained by this study revealed that the concentration of the liver protecting enzymes was not affected by ethanol when animals were coadministerd with plant extract. Rats which were pretreated with methanolic extract of Caralluma adscendens var. attenuata inhibited the stimulated serum levels of serum glutamate pyruvate transaminase (SGPT), serum glutamate oxaloacetate transaminase (SGOT), alkaline phosphatase (ALP) and total bilirubin when compared with silymarin. The research findings reveal that Caralluma adscendens var. Attenuata has significant antioxidant and hepatoprotective activities.
Predictive Migration for Application High Availability

Customer applications and workloads are increasingly become complex today as business environments they serve are very dynamic, competitive and require IT systems and applications that are highly flexible to serve the changing needs of businesses. One such need is high availability of applications and services customer uses, to keep the continuity of business. Clustering of machines is one of the approaches used to achieve high availability. Traditional high availability clustering solutions involve restarting of business critical applications on the standby machines in the cluster when the primary machine goes down. The services rendered by the application would not be available causing the service downtime proportional to the complexity of the application.
Performance Analysis of Data Processing Tasks in Mobile Phone Sensing System Using Cloud

: Mobile phone sensing is an emerging area of interest for researchers as smart phones are becoming the core communication device in people's everyday lives. Sensor enables mobile phones or smart phones are attractive sensing application in different domains such as environment monitoring, industrial automation, healthcare, etc Taking advantage of data gathering of mobile phone sensing system (MPSS) as well as the data storage and processing ability of cloud computing (CC) to integrate MPSS-CC. This paper focuses on the processing of the sensory data in MPSS-CC integration architecture and transmitting desirable sensory data to the mobile users in a fast, reliable and secure manner. In this paper, we perform the data processing tasks on the sensory data for reducing the traffic load and bandwidth requirements of sensory data transmission. In addition, the architecture of MPSS-CC is capable of monitoring and predicting the sensory data traffic and also enabling mobile user to securely obtain their desired sensory data faster.
Survey Paper on Giving Privacy to Sensitive Labels

: Sensitive Label and data handling are important issues for social network users. Ideally, access control enforcement should not depend on the social networking provider but should be under the control of the user. We propose a privacy protection scheme that not only prevents the disclosure of identity of users but also the disclosure of selected features in users’ proﬁles also, a graph model where each vertex in the graph is associated with a sensitive label. It makes all requests for private data from third party applications (TPAs) explicit and enables a user to exert ﬁne-grained control over what proﬁle data can be accessed by them. Users can share their access control conﬁgurations for TPAs with their friends who can reuse and rate such conﬁgurations. The social networks are modeled as graphs in which users are nodes and features are labels. Labels are denoted either as sensitive or as non-sensitive.
Integrating Domain Familiarity and Reinforcement Learning For Artificial Neural Network

- Knowledge integration and learning are two key issues in designing knowledge-based intelligent systems. This talk will present a family of self-organizing neural networks, collectively known as fusion Adaptive Resonance Theory (fusion ART), for building knowledge-based intelligent systems with real-time learning capabilities. By extending the original Adaptive Resonance Theory (ART) models consisting of a single pattern field into a multi-channel architecture, fusion ART unifies a number of important neural network designs developed over the past decades. Based on a universal set of neural encoding and adaptation principles, fusion AT supports a myriad of learning paradigms, notably unsupervised learning, supervised learning, and reinforcement learning. TD-FALCON is a self-organizing neural network that incorporates Temporal Difference (TD) methods for reinforcement learning. Despite the advantages of fast and stable learning, TD-FALCON still relies on an iterative process to evaluate each available action in a decision cycle. To remove this deficiency, this paper presents a direct code access procedure whereby TD-FALCON conducts instantaneous searches for cognitive nodes that match with the current states and at the same time provide maximal reward values. Our comparative experiments show that TD-FALCON with direct code access produces comparable performance with the original TD-FALCON while improving significantly in computation efficiency and network complexity.
COMPARATIVE STUDY BETWEEN CONVENTIONAL AND MOLECULAR ASSAYS FOR DETECTION SHIGA TOXIN-PRODUCING ESCHERICHIA COLI IN CHILDREN WITH BLOODY DIARRHEA IN KERBALA CITY

Bloody diarrhea is a serious public-health problem in children especially in developing countries; it appears in approximately twenty to thirty percent of all diarrhea cases and has a higher level of mortality and morbidity. At every age and stage of life the intestinal bacterial infections are a significant cause. The epidemiology and handling of this condition are varies in the developing world, where infectious agents became predominate. This study was proceed during the period from October 2017 to December 2017 to isolate Shiga toxin-producing Escherichia coli (STEC) and characterize them by biochemical reactions and confirmatory diagnosis of Escherichia coli (Stx1), (Stx2) genes using conventional monoplex and multiplex polymerase chain reaction (PCR) technique. A total of 80 bloody diarrhea stool samples were achieved from hospitalized children (40 females and 40 males) under 6 years old whose suffered from acute gastroenteritis and hemorrhagic colitis with bloody diarrhea in Kerbala Pediatric Teaching Hospital in Karbala City. The overall prevalence of Shiga toxinproducing Escherichia coli (STEC) in stool samples were 16 80 / (20%) and 31 80 / (38.75%) by PCR and conventional bacterial cultivation techniques, respectively, distributed in a total of 11 80 / (13.75%) females and 5 80 / (6.25%) males by PCR, and 22 80 / (27.5%) females and 9 80 / (11.25%) males by cultivation techniques, with a significant variation (P≤0.05) between the two bacterial detection as says. The present study was accelerated due to endemic clinical bloody diarrhea in children for reducing the required period for laboratory diagnosis and to increase the accuracy for the detection of the specific bacterial causative agents of bloody diarrhea in children.
A General Framework of Reversible Data Hiding with Controlled Contrast Enhancement

: This paper proposes a two-step general framework for reversible data hiding (RDH) schemes with controllable contrast enhancement. The first step aims at preserving visual perception as much as possible on the basis of achieving high embedding capacity (EC), while the second step is used for increasing image contrast. In the second step, some peak-pairs are utilized so that the histogram of pixel values is modified to perform histogram equalization (HE), which would lead to the image contrast enhancement. However, for HE, the utilization of some peak-pairs easily leads to over-enhanced image contrast when a large number of bits are embedded. Therefore, in our proposed framework, contrast over-enhancement is avoided by controlling the degree of contrast enhancement. Since the second step can only provide a small amount of data due to controlled contrast enhancement, the first one helps to achieve a large amount of data without degrading visual quality. Any RDH method which can achieve high EC while preserve good visual quality, can be selected for the first step. In fact, Gao et al.’s method is a special case of our proposed framework. In addition, two simple and commonly-used RDH methods are also introduced to further demonstrate the generalization of our framework.