Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey on Scene Text Recognition Using Tree Structure Model and Viterbi Algorithm

— Scene text recognition has inspired significant interest from the computer vision field in recent years. Recognizing such text is still problematic than the recognition of scanned documents. In this paper, we propose an efficient scene text recognition method integrating tree structure model and word recognition model. We use tree structure model to model each part of characters so as to detect and recognize characters simultaneously. For word recognition, the detection scores and language models are combined into the posterior probability of character sequence from the Bayes algorithm. The final word-recognition result is obtained from Viterbi algorithm by maximizing the character sequence posterior probability.
The role of endocrine disruptors in the present and future human endocrine evolution: The ed-exohormone-system

In this paper a theory on the possible transformation of endocrine disruptors (EDs) to real hormones, is introduced. The evidences, demonstrating the possibility of transformation, are reviewed. Lipid soluble vitamins (in fact, exo-hormones, e.g. vitamins A and D)), which once could have also acted as endocrine disruptors, were converted to physiologically active hormones during evolution, when they meet a claim. Our model yields to the prediction that a similar conversion will happen by phytoestrogens. These already have a role in human food consumption since thousand years having both beneficial and harmful effects. However, the conversion of other (e.g. industrial) disruptors (the number and amount of which are enormously growing) is also likely. The (non-mutational) epigenetic inheritance of faulty hormonal imprinting helps the stabilization of evolutionary changes. From this aspect the effect of EDs can also be useful, not only harmful, as it is believed up to now. The apparently harmful effects of endocrine disruptors (e.g. on male fertility) may also be beneficial in a certain respect, considering human overpopulation and its consequences. At present the whole human endocrine system is attacked by environmental and medical endocrine disruptors, causing the imbalance of the system, creating conditions of epigenetically inheriting changes. The goal of this paper to emphasize the possibility of evolutionary changes caused by the ubiquity of endocrine disruptors and to their importance in our present and future life.
Effects of Aging and Disease Progression on Behavioral Symptoms in Alzheimer’s Disease

In Japan, no medicine is permitted for behavioral and psychological symptoms of dementia (BPSD) in Alzheimer’s disease (AD). On the contrary, atypical antipsychotics are inhibited because mortality rate increases when these medicines are prescribed for elderly demented patients [1]. However, antipsychotics are prescribed for BPSD such as delusions, hallucinations, agitations or aggressions with permission of proxies of AD patients. Therefore in this article, we showed and reviewed our previous articles those reported the effects of aging and disease progress on BPSD [2,3] and we recommended the clinical implication of the pharmacotherapy for BPSD in AD.
PREDICTIVE VALUE OF VASCULAR ENDOTHELIAL GROWTH FACTOR IN WOMEN UNDERGOING INTRACYTOPLASMIC SPERM INJECTION WITH HIGH RISK FOR OVARIAN HYPERSTIMULATION SYNDROME

Background: Vascular endothelial growth factor (VEGF) is expressed and produced by granulosa-lutein cells and is released into the follicular fluid in response to human chorionic gonadotropin (hCG), increasing capillary permeability. In addition, plasma VEGF levels correlate with the clinical picture of ovarian hyperstimulation syndrome (OHSS). Objective: This study aimed to investigate the predictive value of serum VEGF at the day of hCG administration in women undergoing intracytoplasmic sperm injection (ICSI) cycle and in high risk of OHSS. Study design: Prospective cohort study. Subjects and Methods: This study was performed on eighty women with polycystic ovary syndrome with infertility and will undergoing ICSI cycle. All women were subjected to routine practice of long protocol for controlled ovarian stimulation (COS). The eighty subjects included in this study were classified into two groups based on ovarian response and E2 level before the day of hCG. Group A: Normal ovarian stimulation; thirty women with E2 less than 3000pg/ml before the day of hCG administration. Group B: Ovarian hyperstimulation (Coasting group); fifty women with E2 more than 3000pg/ml and count of large follicles more than 20 follicles in each ovary with diameter > 17mm before the day of World Journal of Pharmaceutical Research SJIF Impact Factor 7.523 Volume 6, Issue 5, 1615-1634. Research Article ISSN 2277– 7105 Article Received on 20 March 2017, Revised on 10 April 2017, Accepted on 30 April 2017 DOI: 10.20959/wjpr20176-9131 *Corresponding Author
Prevalence of Alcohol Use among Doctors, Nurses and Other Employees of A Teaching Hospital

Owing to the nature of their career, medical practitioners and staff of hospitals in general have been held in high esteem as life preservers and role-models. Studies have pointed to the prevalence of alcohol use among medical practitioners and doctors in particular, detecting hazardous drinking among junior medical doctors at about 2% rate. The American Nurses Association (ANA) reports that approximately 10% of nurses are dependent on drugs and alcohol, making the incidence of alcohol abuse and addiction among nurses consistent with that of the U.S. population. This study examined the prevalence of alcohol use among medical and non-medical hospital staff of a Teaching Hospital in Nigeria. The prevalence of alcohol was estimated for 101 medical and 79 non-medical staff of the teaching hospital. Information was obtained using the Alcohol Use Disorder Identification Test (AUDIT) and a structured tool to collect sociodemographic information. Descriptive and Inferential statistics were employed in the data analyses. The prevalence of alcohol use among the hospital staff was 58.3% including 36.1% low risk drinkers, 20.5% high risk drinkers and 1.7% were hazardous drinkers. Non-medical staffs reported significantly higher level of alcohol intake than medical staff. Job designation and gender were found to have significant influence on the level of alcohol usage, while age and marital status were found not to significantly influence the level of alcohol usage of the hospital employees. Author concluded that the prevalence of alcohol use among the hospital staff was high. The Findings were discussed in line with the existing literature and the current socio-economic realities of the country. It was recommended, among others, that researchers should work hard to discover the precipitating and maintenance factors of alcohol consumption among hospital employees in Nigeria.
Integrity Auditing for Outsourced Dynamic Cloud Data with Group User Revocation

:- The imminent of the cloud computing makes storage outsourcing turns into a rising pattern, which advances the privacy for remote data auditing an intriguing issue that showed up in the literature. Recently a few researchers consider the issue of secure and productive public data respectability auditing for shared dynamic data. Be that as it may, these schemes are still not secure against the conspiracy of cloud storage server and revoked group users amid client denial reasonable cloud storage framework. In this paper, we make sense of the understanding attack in the presented system and give an adept public auditing scheme with secure group client repudiation in view of Asymmetric Group Key Agreement and group signature. Our Scheme supports effective dynamic user revocation with public auditing.
FPGA Design and Implementation of Secure Dual- Core Crypto Processor

This paper is devoted to the design and the physical security of a parallel dual-core flexible crypto processor for computing pairings over Barreto-Naehrig (BN) curves. The proposed design is specifically optimized for field-programmable gate-array (FPGA) platforms. The design explores the in-built features of an FPGA device for achieving an efficient crypto processor for computing 128- bit secure pairings. The work further pinpoints the vulnerability of those pairing computations against sidechannel attacks and demonstrates experimentally that power consumptions of such devices can be used to attack these ciphers. Finally, we suggest a suitable countermeasure to overcome the respective weaknesses.
Title: Guidelines for Inert Gas Washout Measurements for Multiple and Single Breath Tests:

Authors 1. Robinson, P.D. 1,2,3 2. Latzin, P.4 3. Verbanck, S.5 4. Hall, G.L. 6,7 5. Horsley, A.8 6. Gappa, M.9 7. Thamrin, C.2,4 8. Arets, H.G. M10 9. Aurora, P.3,11 10. Fuchs, S.9 11. King, G.G. 2,12 12. Lum, S.3 13. Macleod, K.13 14. Paiva, M.14 15. Pillow, J.15,16 16. Ranganathan, S.17,18 17. Ratjen, F.19 18. Singer, F.4 19. Sonnappa, S.3,11 20. Stocks. J3 21. Subbarao, P.19 22. Thompson, B.20 23. Gustafsson, P.M. 21,22
Synthesis of Biodiesel from Residual Animal Fats and Analysis of Properties

This paper deals with the synthesis of biodiesel from residual goat tallow at laboratory scale, determination of free fatty acid profile, lowering the level of free fatty acid content fordecrement of the viscosityto meet the standards for usage in diesel engines. The obtained product is also tested for different rheological, thermodynamic and physical properties such as Viscosity with respect to temperature, Shear Stress with respect to temperature, Calorific value, Flash point, Fire point, PH value, density etc. These results are then compared with existing standards for petroleum diesel. Further a comparisonof the cost of the produced biodiesel with petroleum diesel has also been provided.
IMPLEMENTATION OF SPEAKER RECOGNITION SYSTEM ON FPGA USING LOGICORE IP

In any biometric systems, the response time is proven to be critical. In the past decades, speaker recognition software systems have been running on a general microprocessor having a sequential operation which tend to be slow. As a result, FPGA implemented systems gained preference because of the dedicated hardware. This paper presents a Speaker Recognition system implemented on Spartan 6 using Xilinx LogiCORE. MFCC is used to extract the features and Minimum Euclidian Distance Classifier has been used at the decision logic. It has proven that this implementation is simpler compared to generic methods. The device utilization is optimum.
A Comparative Study of Sentiment Analysis Techniques

Data Analytics is the process of examining large and varied data sets in order to draw conclusions about the information they contain, increasingly with the aid of specialized systems and software. It is widely used in many industries and organization to make a better Business decision. Sentiment analysis or emotion extraction or opinion mining plays a significant role in the decision making process. It is a very popular field of research in text mining. The idea is to find the polarity of the text and classify it into various groups as-positive, negative or neutral. To perform sentiment analysis, one has to perform various tasks like subjectivity detection, sentiment classification, aspect term extraction, feature extraction etc. This paper presents the survey of the main approaches used for sentiment analysis classification.
Recent Advances to Monitor Early Revascularization for Assessment of Postsurgical Healing: A case report

Endodontic infections with periapical lesions are usually diagnosed conventional radiological findings. Ultrasound with color doppler has potentials to examine physiological conditions and investigate suspected pathology and mask the limitations of conventional radiography. It can differentiate between cystic and non cystic lesion as well as monitor the healing of periapical lesions Hence this present case report have focused on effectiveness of ultrasound, color doppler imaging and radiography to monitor periapical healing post endodontic surgery.
Modified Hybrid PWM Technique For Neutral Point Stabilization of Five Level Diode Clamped Inverter

An intrinsic problem with diode clamped multi-level inverter is fluctuations or simply called unbalance of voltage at neutral point. This voltage fluctuations can cause uneven voltage sharing among the switching devices. Sometimes may cause failure and increases harmonic component in the output waveform. This problem is normally mitigated by closed loop control of neutral point voltage. There are many mitigation methods well established in literature to balance the neutral point voltage using conventional SPWM and space vector PWM techniques. But these techniques has drawbacks like low frequency ripples at the neutral point and high switching losses. So This project deals with the new control technique for balancing the neutral point voltage i.e. With the combination of both SPWM and SVPWM techniques to the fullest for achieving efficient voltage balance at the neutral point by providing quality output for 5 level diode-clamped multi level inverter for any type of load. MATLAB-SIMULINK will be used to develop this technique.
Composition of Feature Relevancy Based Biomarker Gene Selection in Gene Expression Dataset

Cancer gene selection plays a prominent work in the area of Bioinformatics. Gene selection methods aim to retain relevant genes and remove redundant genes. This proposed technique deals on gene selection techniques based on information theory. By investigating the information theory based on composition of feature relevancy, we consider that a excellent gene technique method could boost novel classification of the cancer gene data while reducing gene redundancy. Therefore, a modified gene selection technique called Composition of Feature Relevancy (CFR) is carried out. To assess CFR, the experiments are carrying out on five real-world cancer gene expression data sets and three best classifiers (KNN, Support Vector Machine and Random forest). The modified gene selection technique gives best outcome when competing to other recent technique in terms of accuracy and sensitivity in classification.
The Effect of Life satisfaction and Role Centrality on Job Satisfaction- Turnover Intention Relationship

The aim of the present study was to investigate how life satisfaction and role centrality were operating in the relationship between job satisfaction and turnover intention in order to understand why employees may leave even if the work is designed to satisfy all what they want. The hypotheses were tested with a sample of 353 nurses from three hospitals by using structural equation modeling for the direct effects and multiple regressions for the moderation. The results indicate that 52 percent of the nurses often think about quitting the current job, 40 percent of them think about looking for another job next year, and 37 percent will actively look for a new job in the next year. The results of the hypotheses indicate that all the direct effect between job satisfaction, life satisfaction and turnover intention are significant. All the moderation hypotheses by using role centrality as a moderator are not supported. Nevertheless, the result of the exploratory analysis suggested that role centrality could be best conceptualized as the main effect directly influencing life satisfaction. Job satisfaction and role centrality may have an indirect relationship with turnover intention through life satisfaction. Implications for future r esearch a nd m en t or i n g practice a re discussed. [Charif Amara, Management Department, University of Jijel, Algeria. The Effect of Life satisfaction and Role Centrality on Job SatisfactionTurnover Intention Relationship. Researcher 2014;6(2):87-98]. (ISSN: 1553-9865). http://www.sciencepub. net/researcher. 13
Brand Management Practices, Corporate Image, Customer Characteristics and Satisfaction among University Students in Kenya

The objective of the study was to determine the influence of brand management practices, corporate image, and customer characteristics on customer satisfaction among university students in Kenya. The study was founded on three theories namely: Customer based brand equity model, expectation confirmation theory and consumer utility theory. The study adopted descriptive research design, the target population comprised of students from all 70 universities registered and accredited to operate in Kenya, with a population of 443,783 students enrolled for various undergraduate degree programmes from which a sample of 384 students was drawnstudent’s characteristics in public and private universities tend to differ significantly. The study used a multistage sampling procedure that involved two stages. The first stage was sampling 30% of the universities in each category using a simple random sampling method. The second stage used systematic random sampling, selecting every 5th student entering the main gate of the main campus of the selected university. Purposeful sampling was applied strategically to ensure equitable distribution of respondents based on gender, the program enrolled and the year of study. This helped reduce biasness and ensured fair representation. Data was analyzed using descriptive statistical analysis, correlation analysis and regression analysis. The study revealed there was a joint effect of brand management practices, customer characteristics and corporate image on customer satisfaction in university students in Kenya with R 2=0.308; p-value= 0.000. Brand management practices were found to influence customer satisfaction more in the private individual owned and private institutional owned than in public universities, with R square of 0.149, 0.312 and 0.423 respectively. Similarly, corporate image was found to have a stronger moderation effect on the relationship between brand management practices and customer satisfaction in private institutional owned universities as compared to the private individual owned and public universities, with R 2 of 0.671, 0.440 and 0.213 respectively. The study recommends that policy can be developed that encourages inculcating brand management practices within universities in Kenya. Policy can be developed to encourage measurement and reporting of performance along brand management practices as used in this study
A Review on Class Imbalance Problem: Analysis and Potential Solutions

The Imbalanced class problem is a recent challenge in data mining. A dataset is said to be imbalance when their classification categories are not properly mentioned, and the class which has fewer instances as compare to other classes is of more interest from the point of view of the learning task. Here we study about the various factors that influence the datasets and leads to imbalance the dataset like as Features selection, classification of imbalance datasets. Here in this paper, we also discussed about the various sampling methods utilize for dataset balancing and for getting measurable performance
A Tumor Segmentation using Improved K-mean Clustering with Morphological Algorithm

Tumor detection is an important work in the medical image processing. In the last decade researcher are focused on tumor detection in early age of development. In this research paper proposed a new improved method to deals with the implementation of simple algorithm for detection of range and shape of different types of tumor images. Tumor is an uncontrolled growth of tissues in any part of the body. Many techniques have been developed for the detection of tumor using the abnormal lesion size and shape. However this method of detection resists the accurate determination of stage and size of tumor. To avoid such type of problems, this research uses computer aided method for segmentation (detection) of tumor based on the combination of two algorithms K-means algorithm for with five cluster method and morphological operation for proper area detection. In addition, it also reduces the time for analysis. The detection of the malignant tumor is somewhat difficult to mass tumor. The developing platform for the detection is MATLAB. Because it is easy to develop and execute. At the end, we are providing systems that detect the tumor and its shape and area. The final outcome of proposed method calculate the area of tumor and also the complexity level of tumor image.
End to End Delay Improvement Using Multipath Routing in MANET

Congestion and the loss of energy is the most common problem in the Ad hoc network. A considerable amount of energy is consumed in wireless interfaces. On the other hand the actual available bandwidth varies due to change in contention affected by node mobility. Many of routing protocols use the shortest path route from source to destination with minimum hop count as optimal route selection. But minimum end to end delay may not always achieved through shortest path because of high collision rate and flows at the intermediate nodes. In this paper we propose an improvement of end to end delay using multipath routing which determines the best path selection out of the N-available shortest paths by considering congestion and energy constrains at each of the intermediate nodes. Contention window along with buffer size at MAC layer affects successfully transmission of packets. Performance results show that increase in the PDR, throughput and decrease of overhead and latency when compared to AODV. The proposed method improves the performance of network. Keywords- MANET, IEEE 802.11, MAC layer, Contention window, Performance
Survey on Secure and Efficient AODV Routing Protocol Using Trust Mechanism

— In Ad-hoc networking its devices found network for the communication and it is self-governing of a central infrastructure, no central ability and self-organization. Organization the devices in the ad-hoc network can move randomly gives rise to various kind of problems, such as routing and security. Its work on trust based secure routing protocol and it will more secure AODV routing protocol. Purpose of this work is to reduce the path breakage due to the smaller amount battery power by dynamically replacing the nodes with very less power by the nodes having enough amount of power. Only power aware routing is lacking for MANET, thus we introduce, and trust based routing along with power. Apart from considering battery power of nodes, the proposed system considers the location of the node. The relay nodes are chosen towards the destination to reduce packet drops. In this algorithm has also been developed to reduce the packet dropping attack in MANET which has been simulated on Network simulator-2 (NS-2) and demonstrated an increase in packet delivery ratio, throughput while decrease in average end-to-end delay as compared the basic AODV protocol.
Ranking Product Aspects Based on Consumer Reviews

:- The Internet has become an excellent source for gathering consumer’s opinions or reviews. For product numerous consumer reviews of product are available on internet . Consumer reviews or opinions are useful for both firms & users as they contain rich & valuable knowledge about product. The business firm needs different reviews of customers for development of product. The user can make wise purchasing decision by looking at customer reviews. There are reviews on various aspects of the products. The reviews are numerous, diverse and not precise leading to difficulties in information gathering and knowledge acquisition. A product may have hundreds of aspects. Some of the aspects are important than the others. Therefore we are developing the system to mine those aspects and rank them which will help for better product development. This proposed method is named as “A product aspect ranking framework”. Among reviews of consumer for particular product, it first identifies aspects in the reviews by a shallow dependency parser and then analyzes consumer opinions on these aspects via a sentiment classifier. Then a probabilistic aspect ranking algorithm is used, which effectively exploits the aspect frequency as well as the influence of consumer’s opinions given to each aspect over their overall opinions on the product in a unified probabilistic model.