Miracle-dz/UniFAR-FTUs huggingface dataset:
Sentiment Analysis for Opinion Mining Using Cross-Domain Classifier

: Now a day‟s sentiment analysis is important for various task and applications like market analysis, opinion mining, contextual advertising, etc. Domain generalization remains a challenge in sentiment analysis hence we proposed a methodologies to perform cross-domain sentiment analysis. In cross-domain sentiment analysis, classifier trained on one domain is used to classify other domain. We create a glossary using labeled data from source domain and unlabeled data from both source and target domain. This glossary is used to handle a feature mismatch problem
Sentiment Analysis on Hadoop with Hadoop Streaming

Ideas and opinions of peoples are influenced by the opinions of other peoples. Lot of research is going on analysis of reviews given by peoples. Sentiment analysis is the major computational technique to calculate or observe sentiments of people’s thoughts. Therefore, a method that assigns scores indicating positive and negative opinion about the product is proposed. It uses Hadoop Distributed File System (HDFS) to store data set and run on MapReduce architecture for performing sentiment analysis.
Accurate Spam Mail Detection using Bayesian Algorithm

— With the increasing popularity of a E-mail users, E-mail spam problem growing proportionally. Spam filtering with near duplicate matching scheme is widely discussed in recent years. It is based on a known spam database formed by user feedback which cannot fully catch the evolving nature of spam and also it requires much storage. In view of above drawbacks, we proposed an effective spam detection scheme based on Bayesian approach. First we use Bayesian filter based on single keyword sets and then we improve the scheme by using multiple keyword sets and satisfactory results obtained.
INVESTIGATION ON ANTIMICROBIAL ACTIVITY OF BIOSURFACTANT PRODUCED BY PSEUDOMONAS FLUORESCENS ISOLATED FROM MANGROVE ECOSYSTEM

The aim of this present study is to investigate the antimicrobial activity of rhamnolipid biosurfactant produced by Pseudomonas fluorescens MFS03 isolated from mangrove forest soil using groundnut oil cake as substrate. The biosurfactant was extracted with an equal amount of ethyl acetate and the concentrated extract was subjected to FT-IR analysis. The important adsorption bands at 3466.24, 2926.45, 1743.47, 1407.30 and 1162.26 cm-1indicate the chemical structure of rhamnolipid. The rhamnolipid biosurfactant was investigated for the potential antimicrobial activity by using disc-diffusion method against Gram positive bacteria (Bacillus subtilis, Listeria monocytogenes, Staphylococcus aureus, Methicillin resistance S. aureus) Gram negative bacteria (Escherichia coli, Salmonella typhimurium) and a yeast (Candida albicans). The biosurfactant showed distinct antibacterial activity towards tested bacteria and shows an antifungal activity against yeast. The biosurfactant with different concentration was performed for the evaluation of antimicrobial activity. Maximum antimicrobial activity of the biosurfactant (50μl) was observed in S. aureus (23 mm) and it was found that the biosurfactant activity was dependent on the concentration. So it could be used as a therapeutic agent in pharmaceutical application.
Analysis and Synthesis of Human Skin Feature Distribution

This paper investigates solutions to improvement of realistic rendering quality of CG (Computer Graphics) character face. In order to manipulate face skin feature distribution, based on bio-anatomic structure, skin surface is classiﬁed into 3 layers(Internal, Regular and Local layer) to control skin base color, surface cellular venation level and noise distribution like freckle, respectively. More-over, for the feature best re-targeting from real human to virtual character, a new face segmentation method is introduced by analyzing and overlaying the appropriate feature to the deserved area. By doing all above, a speciﬁc transformation from real human face skin data to virtual character is proposed which is meaningful for the synthesis of CG texture
Particle Swarm Optimization: Developments and Application Fields

--This paper presents a conceptual overview and a detailed explanation of the particle swarm optimization (PSO) algorithm, followed by an overview of the various published modifications to the standard PSO algorithm as well as its wide range of application fields. PSO is a powerful intelligent technique, a member of the recently growing swarm intelligent-based algorithms. Swarm intelligence is a new computational and behavioral metaphor for solving distributed problems, based on the principles underlying the behavior of natural systems consisting of many agents, such as ant colonies and bird flocks. It emphasizes distribution, direct or indirect interactions among relatively simple agents, flexibility, and robustness. Applications of swarm intelligence include optimization algorithms, communication networks, and robotics.
Implementation of Adaptive Wavelet Thresholding and Non-local Means for Medical Image Enhancement for Noise Reduction

: Images are most widely used for radiological diagnosis in medical examinations. The presence of artifacts and noise in images causes the difficulty in medical diagnosis. The noises are generally occurred and corrupt an image during its acquisition or transmission. Image denoising is one of the popular methods with an aim of noise reduction to retain images quality. In this paper, Wavelet based noise reduction technique is proposed to improve image quality where thresholding and Non-local means algorithm are applied. The Noisy medical image is decomposed using DWT, where approximation part is filtered using Non-local means filter and detail parts are filtered by the thresholding. By using the level dependent, the wavelet coe ﬃ cients are calculated using optimal linear interpolation shrinkage function. Denoised image is acquired using inverse DWT. The value of the peak signal to noise ratio (PSNR) is used as the measure of image visual quality.
Detection of Cloning Forgery Images using SURF + DWT and PCA

: Over the last few years, there has been a growing body of work on tools for digital image forensics. These tools are capable of detecting tampering in images from any camera, without relying on watermarks or specialized hardware. Instead of watermarks, these tools assume that images possess certain regularities that are disturbed by tampering. So to evaluate the algorithms for image manipulation and to group they based upon their degree of manipulation. It is also important to consider image compression of image files in the area of work. An evaluation and comparison of the existing forgery detection techniques, and carry out the evaluation along with defining a new grouping structure for forgery detection techniques. There are cases when it is difficult to identify the edited region from the original image. Detection of forgery part of an image drives a need of an authenticity and to maintain integrity of an image. Here in work two techniques such DWT and PCA with SURF as detector is implemented to detect the forged part of an image from tampered image. Both algorithms have their own validation but PCA with Surf improves to be better in all respective. As in PCA SURF we can detect as well remove the forged object and it also takes less time to solve the detection problem than DWT SURF.
IMPLEMENTATION FOR ENHANCING SECURITY OF RFID CARD

Unauthorized money transaction is a very big problem. The main aim of the proposed system is to build a system that defends against unauthorized transaction in RFID. Although a variety of security solutions exist, many of them do not meet the constraints and requirements in terms of efficiency, security, and usability. In an attempt to address these drawbacks, the proposed system is used. In the proposed system on the server side a secure transaction verification scheme is designed which decides whether to make transaction successful or block the card. Many researchers proposed different techniques for unauthorized transaction but all of them required some auxiliary devices to carry with users. In the proposed work there is an interrogation session between reader and user with addition of extra security for secure transaction and according to the behaviour of the transaction theft can be determined.
Effect of Methanolic Extract of Smilax Wightii A.Dc. on Serum Protein Profile in Streptozotocin Induced Diabetic Rats

The present study was carried out to investigate the effects of methanolic extract of Smilax wightii (MESW) on the biochemical parameters (serumprotein, albumin, globulin, SGPT, SGOT and SALP levels) in diabetic induced rats. Diabetes was induced in Wistar albino rats by intraperitoneal (i.p) injection of streptozotocin (STZ) at a dose of 55 mg/kgb.wt . Forty eight hours after streptozotocin administration, blood samples were drawn from tail and glucose levels were determined to confirm diabetes. The rats were divided into 6 groups as follows; first group served as normal control which received normal saline, the second group served as diabetic control, received normal saline, the third, fourth, and fifth groups received graded dosage (100, 200 and 400mg/kg b. wt) of the plant extract and Glibenclamide (600m/kg b.wt) was used as the standard drug for the sixth group. The decrease in the levels of serum protein, albumin, and globulin in the diabetic rats were elevated to near normal levels by the extract treatment. The altered levels of serum SGPT, SGOT and ALP were normalized upon treatment with the plant extract. The results of the present study suggest that the plant extract can improve the protein metabolism and is beneficial in preventing diabetic complications.
A Feature Based Opinion Mining for Product Reviews using Naive Bayes and K-Nearest Neighbor Classifiers

— The explosive growth in the technology of web like social media, directs more number of people to express their sentiments, feedbacks or opinions towards the service, events, individuals, topics, products or social issues. Since the data get bigger extensively in everyday life, this makes so difficult for customers, manufactures as well as for end users of online websites to derive a conclusion on the accessibility of big data available as reviews. Opinion mining is referred to as a natural language processing technique that gives out the knowledge extraction of viewpoints or attitudes from the review texts. Feature-Based Opinion mining system aims to find the main aspects or features of a specified entity and the sentiment expressed on that entity by using natural language processing and AI techniques. Most of the studies have been conducted on aspect based opinion mining but not any of the particular works have justified to be adequate for assessing the critical or majorfactors. The major factors with respect to aspect based opinion mining are implicit or implied aspects, explicit or direct aspects and multiple aspect based. The Aspect based opinion mining by considering all these critical factors helps in analyzing the aspect of a particular entity and its sentiment more accurately. In this paper, an explicit aspect based opinion mining is carried out using naive bayes and K-nearest neighborclassifiers to generate more accurate opinions for product reviews. The end user can easily get opinions based on the particular aspect of the entity and the proposed work proves that the sentiment classification using naive bayes classifier provide with more accuracy than using K-nearest neighbor classifier.
ANALYZING THE PRIVACY PRESERVING USING BIG DATA TECHNIQUES

Recently big data has become a hot research topic. The rising amounts of big data also increase the chance of violate the privacy of individuals. Since big data need high computational power and large storage, distributed systems are used. As multiple parties are concerned in these systems, the risk of privacy violation is improved. There have been a number of privacy-preserving methods developed for privacy protection at different stages (e.g., data generation, data storage, and data processing) of a big data life cycle. The goal of this paper is to provide a comprehensive overview of the privacy preservation methods in big data and present the challenge for existing mechanisms. In this paper, we illustrate the infrastructure of big data and the big data life cycle. Furthermore, we discuss the research challenges of the privacy preservation in big data. This paper also presents recent techniques of privacy preserving in big data like hiding a needle in a haystack, identity based anonymization, differential privacy and privacy-preserving big data publishing of big data streams and future research directions related to big data.
Case of Spontaneous Live Unilateral Tubal Twin Ectopic Gestation Maheshgir International Journal of Case Reports & Short Reviews

Ectopic pregnancy is a common medical problem and it pose a serious diagnostic and therapeutic challenge in the obstetrics as the presenting symptoms and signs vary widely between patients. Unilateral twin tubal pregnancy is quite rare with a reported incidence of 1:200 ectopic pregnancies. It was ﬁ rst described in 1891 by De Ott . I present a case of successful management of spontaneous live right tubal ectopic pregnancy with no history of assisted reproductive techninique fertilization or pelvic inﬂ ammatory disease . Twin ectopic pregnancy, even though rare, must be looked for on ultrasound scanning with increasing incidence of pelvic inﬂ ammatory disease because of the potential mortality and morbidity associated with this condition.
Two-Year Success and Early Failure of Osseointegration of 3049 Dental Implants in Dubai Health Authority

Introduction Background: Replacing missing teeth using dental implants is a predictable treatment modality for completely and partially edentulous patients. Despite the high success and survival rates associated with dental implants, early implant failure (before loading) can occur and represents the majority of reported failure. The aim of the present study was to identify the factors associated with early failure of dental implants in patients of Dubai Health Authority (DHA), Dubai, United Arab Emirates.
Offline and computer‐based eLearning interventions for medical students' education

This is the protocol for a review and there is no abstract. The objectives are as follows: The primary objective of this review is to assess the effects of offline, computer-based eLearning compared with ‘traditional’ learning and other types of eLearning interventions for medical students’ knowledge as well as changes in skills and attitude towards the intervention. Additionally, as secondary objectives, this review will assess the economic impact (cost-benefit, cost-utility or cost-effectiveness), unintended adverse effects, and medical students’ satisfaction with using offline and computer-based educational interventions.
A Hybrid Approach Based on Fourier-Mellin Transform for Copy-Move Forgery Detection Using Sift

: Copy move forgery in which an object is copied from one place and pasted on another place within the same image has become most common in the field of image processing. Various Copy-move Image forgery detection schemes are used to solve these problems. In this paper, a hybrid scheme is used to detect the copy-move object or region of an image. This hybrid scheme is basically a combination of keypoint based method and block based method. The proposed algorithm is tested on a number of digital images. The experimental results prove the FMSIFT algorithm is a novel approach in its accuracy.
Advances and Alternatives in Human Anatomy Teaching: What Next?

For this purpose, we need an ancient tool, which dates back to 500 BC, by the Greeks although some authors mention the beginning of its use by the Egyptians -, the cadaveric dissection. The earliest known records of dissection, as the act of cutting bodies to study anatomy, dates back to the third century BC, in Alexandria. Hippocrates of Kos was the first to write about Human Anatomy in the fifth century BC [1].
LOCATION BASED REMINDER SYSTEM USING MOBILE GPS SYSTEM

Privacy and security is most important part while using the location based services. The aim to develop location based reminder system is provide an interactive user friendly environment to user's as well as privacy about their saved location and current location. Location based service, provide many facilities to smart mobile phone users. They can navigate map, set location while driving and many more. With the using of “Location Based Reminder System” the user can set their task or reminder for particular location. With the help of this, no need to worry about the particular task at particular location. When the user is near about the location, it will automatically remind for saved task. Location Based Remind System consumes the low data, because in this project the user’s data saved in local system
PERFORMANCE COMPARISON BETWEEN OFDMA AND SC-FDMA USING RAYLEING FADING CHANNEL

To meet the increasing demands on the mobile radio systems and data traffic, a successor of UMTS, which runs on an evolution of the existing infrastructure used by over 80 percent of mobile subscribers globally, has been worked on by 3GPP, called Long Term Evolution (LTE). This will permit more powerful and better spectral efficiency of the transmission. The major parts of LTE are Single Carrier Frequency Division Multiple Access (SC-FDMA) & Orthogonal Division Multiple Access (OFDMA). OFDMA is used as multiple access method and it’s providing immunity of multi-path and frequency selective fading. SC-FDMA is introduced recently and it became handy candidate for uplink multiple access scheme in LTE system. In our paper, we analyzed the performance of SCFDMA and OFDMA for BPSK Modulation scheme on the basis of BER by simulating the model of SCFDMA & OFDMA in MATLAB. We used Additive White Gaussian Noise (AWGN) channel and introduced frequency flat fading in the channel by using Rayleigh fading model to evaluate the performance in presence of noise and fading. Though the total channel is a frequency selective channel, the channel experienced by each subcarrier in an OFDM system is a flat fading channel with each subcarrier experiencing independent Rayleigh fading .
Web Search Query Result Optimization based on Memetic Algorithms: A Comparative Study

In recent years, the importance and volume of online biological databases, grows tremendously, which makes searching and manipulating data quite challenging.The present study was conducted to minimize the retrieval time of precise data from remote and voluminous databases using metasearch methods. The search query results were optimized by the proposed adaptive cellular Memetic Algorithms (ACMA) implemented over heterogeneous entomological databases. The performance of the algorithm was analyzed by comparing with Genetic Algorithms and with popular search engines like Yahoo, Bing and Ask. The results revealed that ACMA enhanced in efficiency for about thirty-seven times better than the Genetic Algorithms. Despite the growth of data, the performance of the algorithm improves in retrieval time, however making no compromise with its quality.The outcome of the present research could be useful for extending the idea for other similar research areas, and applications like life-science databases with slight modifications.
INTESTINAL MICROBIOTA INFLUENCES TYPE1 DIABETES

Increasing diabetes incidence in the last decades drew the attention of researchers that there are other reasons besides genetic susceptibility. There are several factors that influence the occurrence of type 1 diabetes (T1D) encomposing genetic and environmental components. This review will throw light on the important aspects of T1D development in context with the intestinal microbiota. Gut microbiota provides an immunological barrier to the gut from the invasion of pathogenic microorganisms. Gut microbiota dysbiosis mediates T1D through stimulation of inflammatory cells that induce β-cell destruction. Research in this field is important to find out new protective substances in ameliorating TID.
Dynamic Grouping of Semantically Similar User Search Histories

--Users over Internet make queries continuously for various kinds of information. Such information might be about various tasks and that is done through existing search engines. When queries are made by users continuously, over a period of time, the queries are plenty. The existing search engines organize such queries only in chronological order. However, when the quires are grouped together based on the relevancy that might be very useful to users as they can reuse queries with ease. Hwang et al. studied this problem recently and proposed mechanisms that help in grouping or organizing user search histories in useful fashion. This organization of user search histories can have various real time utilities such as result ranking, query alternations, query suggestions, sessionization and collaborative search. In this paper we implement algorithms that are used to group user search histories. We built a web based prototype that demonstrates the proof of concept. The empirical results are encouraging.
EFFICIENT TRUST ESTABLISHMENT FOR SECURE COMMUNICATION IN DELAY TOLERANT NETWORKS USING ATTRIBUTE BASED ENCRYPTION

: Conventional ad hoc routing protocols are not capable of work in irregularly connected networks since end-to-end paths may not exist in such networks. Hence, routing methods that can survive disruptions need to be designed. A store-and-forward approach has been proposed for delivering messages in delay tolerant networks. Delay-tolerant network (DTN) technologies are becoming successful solutions that permit wireless devices in military environments to communicate with each other and access the secret information or command reliably by exploiting external storage nodes. In this paper, we propose a protected data recovery scheme using CP-ABE for decentralized DTNs where multiple key authorities manage their attributes independently. We express how to apply the proposed mechanism to securely and efficiently administer the confidential data distributed in the disruption-tolerant military network.
BCI Based Analysis Of Hand Movement Trajectories For Rehabilitate Patients

For many years people have speculated that electroencephalographic activity or other electrophysiological measures of brain function might provide a new non-muscular channel for sending messages and commands to the external world – a brain–computer interface (BCI). This paper investigates the application of a non-invasive Electroencephalography (EEG)-based BCI to identify brain signal features in regard to actual hand movement trajectories. An experiment was performed to collect EEG data from subjects while they performed right hand movement at two different speeds, namely fast and slow, in four different directions. The informative features from the data were obtained using the Wavelet-Common Spatial Pattern (W-CSP) algorithm that provided high temporal-spatial-spectral resolution. The immediate goal is to provide these users, who may be completely paralyzed, or ‘locked in’, with basic communication capabilities so that they can express their wishes to caregivers or even operate word processing programs. The classified result is provided by the SVM classifier. The spatial patterns of the WCSP features obtained showed activations in parietal and motor areas of the brain. The results achieved promises to provide a more refined control in BCI by including control of movement speed.