Miracle-dz/UniFAR-FTUs huggingface dataset:
A Human Opinion Dynamics Based Trust Calculation And Communication In Delay Tolerant Network

- Data routing in a delay tolerant network is an area of concern in recent years and many researchers have proposed many techniques for routing. In delay tolerant sparse network number of nodes in the network is very fewer and probability of losing the data is very high. Many approaches have been proposed in recent past but most of them failed to perform significantly. An opinion dynamics based approach is proposed in this work which calculates the trust value of a node based on the opinion of other nodes in the network. An opinion is calculated on the basis of parameters like packet delivery delay, number of packets lost and residual energy. The result also shows the improvement in various performance parameters in the network.
KEY AGGREGATE SEARCHABLE ENCRYPTION WITH SECURE AND EFFICIENT DATA SHARING IN CLOUD

The proficiency of selectively allocating encrypted data with different users via public cloud storage may greatly affluence security disquiets over unintentional data leaks in the cloud. A crucial defy to scheming such encryption schemes lies in the efficient management of encryption keys. The preferred pliability of partaking any group of selected documents with any group of Users demands altered encryption keys to be used for different documents. However, this also suggests the necessity of securely distributing to users a large number of keys for both encryption and search, and those users will have to securely store the received keys, and submit an equally large number of keyword trapdoors to the cloud in order to perform search over the shared data. The practical problem, which is largely abandoned in the literature, by suggesting the novel concept of key aggregate searchable encryption (KASE) and instantiating the concept through a concrete KASE scheme, in which a data owner only needs to distribute a single key to a user for sharing a large number of documents, and the user only needs to submit a single trapdoor to the cloud for querying the shared documents. The security analysis and performance evaluation both confirm that proposed schemes are provably secure and practically efficient.
Int. J. Biosci

Phosphorous (P) is considered to be the macronutrient with the lowest availability for plants in the majority of tropical soils, and is thus a limiting factor for vegetal growth. The application of Phosphoric Rock (PR) has been widely studied in order to satisfy its requirement in crops, but the quantity of liberated P is too low to satisfy demand. A viable alternative for managing this problem is the use of rhizospheric microorganisms that solubilize P (PSM) in chemically unavailable forms. In the search for microorganisms that solubilize phosphates, studies report that Trichoderma spp. , in addition to their effects as pathogen biocontrollers, also exhibit phosphodissolvent capacities. The objective of this investigation was to evaluate in vitro strains of Trichoderma spp. isolated from rhizospheres of beans and corn with phosphate solubilizing abilities. Different strains of Trichoderma were isolated and selected from rhizospheric soil and rhizospheres. Three medium types were evaluated utilizing both solid and liquid media in order to determine their biometric characteristics, relative efficiency of solubilization of PR, bioacidulant capacity of the culture medium, and concentration of P in solution. In liquid media, these fungi were inoculated with and without PR, the quantity of soluble P was quantified, and the pH was taken. There were significant differences with respect to mycelial growth between solid media with and without the presence of PR, solubilization halos, and relative efficiency of solubilization in relation to incubation time. Liquid media with and without PR showed significant differences with respect to the quantity of soluble P. The pH of these media was inversely proportional to the quantity of soluble P, as the probable principle mechanism of dissolution of PR is the production of organic acids. * Corresponding Author: Dorcas Zúñiga-Silgado  dorcas.zuniga@colmayor.edu. co International Journal of Biosciences | IJB | ISSN: 2220-6655 (Print), 2222-5234 (Online) http://www.innspub. net Vol. 8, No. 4, p. 124-144, 2016
Automatic Detection and Localization of Tuberculosis in Chest X-Rays

Tuberculosis is a major health threat in many regions of the world. Opportunistic infections in immune compromised HIV/AIDS patients and multi-drug-resistant bacterial strains have exacerbated the problem, while diagnosing tuberculosis still remains a challenge. When left undiagnosed and thus untreated, mortality rates of patients with tuberculosis are high. Standard diagnostics still rely on methods developed in the last century. They are slow and often unreliable. In an effort to reduce the burden of the disease, this thesis work presents an automated approach for detecting and localizing tuberculosis in conventional postero -anterior chest raadiographs. A set of features are extracted from the lung region, which enable the X-rays to be classified as normal or abnormal using a binary classifier. Then if the chest x-ray is classified as abnormal again a set of local features are extracted to localize the affected regions . Thus it become easy to diagnose and treat the disease. An accuracy of 90% is achieved by this method.
Investigation of different Face Recognition Databases under Uncontrolled Illumination Variation Method

: Confront acknowledgment framework is a PC application for naturally recognizing or confirming a man from a computerized picture or a video outline from a video source. Confront acknowledgment a framework has affected on numerous useful applications in view of the conditions. In this paper, investigation of two face databases is done with the assistance of a strong Face Recognition System under uncontrolled brightening variety. In this Face acknowledgment strategy comprises of three stages, brightening heartless preprocessing technique, Feature-extraction and score combination. In the preprocessing stage enlightenment delicate picture changed into brightening obtuse picture, and after that to joins different classifiers with corresponding components as opposed to enhancing the precision of a solitary classifier. Score combination figures a weighted entirety of scores, where the weight is a measure of the separating energy of the part classifier. The above strategy is connected into two diverse face databases named Yale and YaleB and results are contrasted and precision of every databases under various light condition.
RESEARCH IN COMPUTER APPLICATIONS AND ROBOTICS

: - Automatic Question Generation is the task of generating reasonable questions from an input with the help of various NLP techniques. This paper presents a review of automatic question generation for Indian languages. Automatic question generation is the field of Natural Language Processing (NLP). In context of English a lot of work has been done in the field of question generation with the help of various tools like Semantic Role Labeller, POS Tagger, Annotated corpora tools. But these tools are not yet available for Indian languages such as Punjabi and Hindi. For Indian languages rules are formed to create the questions automatically from a given text using Rule based approach. So, A Named Entity Recognition (NER) tool is needed to generate the questions automatically.
High Speed 16 Bit Digital Multiplier Architecture Using Urdhwa Tiryakbhyam and Compressors

: With the growing technology in field of Communication and VLSI a very high Speed processing power and low area is area is required. Multiplier unit is the central part of digital signal processor as well as general purpose processors that substantially decide the performance of the same. Due to this a high speed multiplier architecture become the need of the day. This paper introduce the 16 bit high speed digital multiplier architecture based on ancient Vedic mathematics. For further increasing the speed of multiplication, addition of partial products generated by multiplication has been implemented by 4:2 and 7:2 compressor. Upon comparison the compressor based Vedic multiplier is 1.5 times faster than normal Vedic multiplier and almost 2 times faster than conventional multiplier. The architecture has been implemented using Verilog language and the tool used for simulation is Xilinx ISE 14.2.
EFFICIENT HANDOVER ALGORITHM OVER LONGTERM EVOLUTION

3GPP is characterizing the long haul development (LTE) and long haul development progressed LTE Advanced)for picking up the 4G innovation status, with the end goal to keep up the future aggressiveness of 4G innovation. The advancement of remote systems is a nonstop marvel. This paper examines the enhancement ventures for HO components in long haul development (LTE) framework which is as a rule formally submitted as an applicant 4G framework. LTE arrange is relied upon to help versatility with paces of up to 500 km/h, when the HO will then turn out to be more successive and quick. The premise of the methodology is to lessen the quantity of superfluous HOs. qualities and shortcomings for every calculation are talked about, and ends are in this way made.
The Transition of Phrase based to Factored based Translation for Tamil language in SMT Systems

— Machine translation is one of the major and the most active areas of Natural language processing. Machine translation (MT) is an automatic translation of one natural language into another using computer generated instructions. The utility and power of Statistical Machine Translation (SMT) seems destined to change our technological society in profound and fundamental ways. The current state-of-the-art approach to statistical machine translation,so-called phrase-based models is limited to linguistic information.For a highly agglutinative languages like Tamil developing a linguistic tools and machine translation system is a challenging task. Therefore, extending the phrase-based to factored based approach by tightly integrating additional annotation information at the word level which encompass not only of tokens but a vector of factor representating the levels of annotation. The additional linguistically features enabled in the toll will increase the accuracy of the SMT systems. This paper motivates the use of factored translation models for statistical machine translation systems for better reliable translation for highly morphological languages like Tamil.
Comparative Efficacy of Different Chinese Herbal Extracts in Broiler Production

The objective of current trail was to evaluate the effect of three Chinese herbal extracts (Lonicera japonica, Radix liquiritiae and Lysimachia davurica) supplementation in drinking water as alternative to antibiotics on performance and immune organs weight/index in growing broilers chicks. For this purpose, 150 day old broiler chicks were reared in floor pens and raised on commercial feed for 7 days for adaptation. After seven days, birds were distributed into five groups in such a way that each group contained 3 replicates and each replicate had 10 birds. All groups were fed commercial diet and offered water with or without additives. In control group drinking water was without any additives; In second group drinking water was supplemented with antibiotic (Flavomycin 10 ml/liter). The remaining three groups were supplemented with Lonicera japonica, Radix liquiritiae, and Codonopsis extract @ 20 ml/liter, 15 ml/liter, and 10 ml/liter in drinking water, respectively. Results indicated improved growth performance in broiler had supplementation of Chinese herbal extracts in drinking water as compared to control (P<0.05). A significant decrease in cholesterol and blood glucose was observed in those birds which had supplementation of Chinese herbs extracts in drinking water (P<0.05). Moreover, Chinese herbs extract in drinking water improved immune organ weight and immune indexes in broiler. It could be concluded that supplementation Chinese herbs extracts in drinking water had positive influence on growth performance, blood biochemistry and immune organs in broiler.
Moving Object Detection in Traffic Video using Optical Flow

- With the abrupt increase of motor vehicles, the advanced Intelligent Traffic Monitoring System is important in today's world. Automatic video segmentation plays an important role in the ITMS. Many algorithms have been proposed on automatic video segmentation. However, due to the large computation, many of them can-not be used for the real-time applications. Segmentation of moving objects in a scene is often desired in many applications for monitoring motion. In the project, we look at traffic videos. The approach used for object-oriented video segmentation is based on motion coherence.
MOUTH DISSOLVING FILMS : A REVIEW

The purpose of current review is to enlighten the present and future prospective on Mouth dissolving film drug delivery system. Now a days, we observe padietric and geriatric patients facing the problem of dysphasia due to administration of monolithic solid dosage form, which are also seen in the case of fast dissolving tablets. Hence mouth dissolving film is proved to be better alternative in such cases. This fast dissolving drug delivery system is suited for the drugs which undergo high first pass metabolism and is used for improving bioavailability. Mouth dissolving film consists of thin oral strip; which release active ingredients immediately after uptake into oral cavity. These films have potential to deliver a drug systematically through intragastric, sublingual or buccal route of administration and also has been used for local action. The present review provides an account of various formulation considerations, method of preparation, and quality control of mouth dissolving films.
EVALUATION OF TP53 GENE EXPRESSION IN FFPE OF BREAST CANCER PATIENTS

Background Breast cancer is a malignant tumor arising from the terminal duct lobular unit of the breast tissues. It is most prevalent malignancy in women and its incidence is increasing globally and the lifetime risk of develo ping breast cancer between 5-10%. Tumor suppressor geneTP53 is essenti al for preventing inappropriate cell proliferation a d maintaining genome stability and integrity following genotoxic stress. TP53 gene is the most commonly mutated gene in cancer and approximately 20% of breast cancer. Thus, gene expr ession was investigated. Patients and Methods One hundred formalin fixed paraffin embedded (FFPE) tissues samples of malignant breast tumor as well as 100 FFPE samples of normal breast tissues samples obtai ned from same patients were investigated. The block s f breast cancer patients were collected from Al Sadder Medical City , Najaf, Iraq. Ages of patients were expressed as M ean ± S.D 48.4 ± 10.90 year with a minimum to maximum of 20 -75 year s. Nucleic acid (RNA) isolated and evaluated by picodr op spectrophotometer for the expression of TP53 gene b y qRT-PCR. cDNA was prepared using the High Capacit y RNA-tocDNA (ABI). For real-time quantitative PCR (RTQ-PCR ), 100 ng cDNA was added to SYBR Green Master Mixtu re (Applied Biosystems) and run in Corbett Real-time P CR System. Results The current study involved investigated of TP53 gen e xpression in FFPE tissues of breast cancer tissu es. TP53 gene expression was indicated to be 44 fold (P<0.00 1) relative to housekeeing gene (18S rRNA). Conclusions TP53 gene is a major tumor suppressor that is alter ed by mutations in 50% of human cancers and functio ally inactivated in other 50%.
Genetic Neural Approach for Heart Disease Prediction

Data mining techniques are used to explore, analyze and extract data using complex algorithms in order to discover unknown patterns in the process of knowledge discovery. Heart disease is a major life threatening disease that cause to death and it has a serious long term disability. The time taken to recover from heart disease depends on patient’s severity. Heart disease diagnosis is complex task which requires much experience and knowledge. Nowadays, health care industry contain huge amount of health care data, which contain hidden information. Advanced data mining techniques along with computer generated information are used for appropriate results. Neural Network is widely used tool for predicting heart diseases diagnosis. A Heart Disease Prediction System is developed using Neural Network and Genetic Algorithm. This system calculates the number of hidden nodes for neural network which train the network with proper selection of neural network architecture and uses the global optimization of genetic algorithm for initialization of neural network. For prediction, the system uses 12 parameters such as sex, age, blood cholesterol etc. From the result, it is found that genetic neural approach predicts the heart disease upto 98% accuracy.
Cerebellar syndrome and cognitive dysfunction with characteristic MRI findings in fragile X-associated tremor ataxia syndrome: A Case Report

An adult male patient came to our observation for a brain magnetic resonance imaging (MRI) study because of progressive symptoms characterized by ataxia, tremor, rigidity and cognitive dysfunction. The neuropsychological tests confirmed an IQ reduction and cognitive impairment. The MRI study showed symmetric T1 decreased and T2 increased signal intensity in cerebellar white matter (wm) lateral, superior, and inferior to the cerebellar dentate nuclei. Moreover, hyperintense T2 focal areas of both deep wm cerebral hemisphere and T2 hyperintensity of the splenium of the corpus callosum were documented. The progressive neurological symptoms of our adult male patient and the MRI study features suggested a degenerative disease, due to fragile X premutation. Genetic tests confirmed the diagnostic hypothesis of fragile X-associated tremor ataxia syndrome (FXTAS). *Correspondence to: Alberto Negro, PhD at University of Campania Luigi Vanvitelli, Neuroradiology Service PO CTO, Viale Colli Aminei, 21, 80131 Naples, Italy, Tel: +328 2858849; E-mail: Alberto.Negro@hotmail.it
A NOVEL ALGORITHM FOR MINING HIGH UTILITY ITEMSETS

— Data mining is an activity fretful with examining of huge volumes of data to extract some useful information or knowledge and interesting patterns or relationships which in turn leads to better understanding of the essential processes. An emerging topic in the field of data mining is Utility Mining. The main objective of Utility Mining is to identify the itemsets with high utilities, by considering profit, quantity, cost or other user preferences. Mining High Utility itemsets from a transaction database is to find itemsets that have utility above a user-specified threshold. In this paper We also propose a new algorithm for high utility item set mining. The new algorithm outperforms previous algorithms in terms of execution time.
Iris Segmentation Along with Noise Detection using Hough Transform

 Abstract — this paper presents the iris localization using Hough transformation. The performance of iris recognition systems highly depends on the segmentation process. Segmentation is used for the localization of the correct iris region in an eye and it should be done accurately and correctly to remove the eyelids, eyelashes noises present in iris region. In this paper we are using Hough Transform segmentation method for Iris Recognition. Generally eyelids and eyelashes are noise factors in the iris image. To increase the accuracy of the system we must have to remove these factors from the iris image. Linear Hough transformation can be used to detect the eyelids. Before applying Hough transformation on the images for identify the circles and lines we have used the canny edge detection to improve the performance of the iris recognition system.
Formulation and evaluation of extended release trilayered matrix tablets of rasagiline mesylate by geomatrix

The main objective of the present study was to prepare controlled release (CR) matrix trilayer tablet of rasagiline mesylate to achieve zero-order drug release for controlled plasma concentration. Twenty seven formulations (F1-F27) for middle layer were prepared by direct compression method using 3 3 response surface method (3 variables and 3 levels of polymers) by using design of experiment software with polymers like different HPMC grades. The barrier layers was formulated employing hydrophobic swellable polymer Polyox WSR 303, xanthan gum and EC. The procedure adopted to make the compacts was via direct compressions. The tablets were also evaluated for physicochemical characteristics and release kinetics and it was satisfactory. The developed drug delivery systems showed prolonged drug release rates over a period of 24 h. The release profile of the optimized formulation (HF17) was described by the zero-order and Higuchi model. These results also demonstrated the suitability of rasagiline mesylate three-layered tablet formulation of to provide controlled release for prolonged period of time and improved linearity for rasagiline mesylate in comparison to marketed product in the management of Parkinson’s disease.
DE AND PSO BASED HYBRID OPTIMIZED WATERMARKING SYSTEM FOR COPYRIGHT PROTECTION AND AUTHENTICATION

Digital contents are simply broaden over through the continually growing communication media like Internet. Image watermarking has become a significant tool for intellectual copyright protection and authentication. In this paper a novel hybrid optimized watermarking system is designed with help of Discrete Wavelet Transform, DE and PSO which tender the solution to the issues such as Copyright Protection and authentication. The coefficients are selected in Discrete Wavelet Transform with help of DE and PSO to embed the DCT transformed selected high energy coefficients watermark bits in the host image. The image quality index metric (IQIM) is used to measure the image quality distortion. The experimental results are assessed with respect to IQIM, PSNR and BCR and offered to exhibit the capability of the proposed system .
OF SUDANESE MEDICINAL PLANTS TESTED FOR THEIR ANTIPARSITICAL ACTIVITY

Background: Review articles, especially in medicinal plants’ research, are very important in saving time, materials and efforts, to reach the ultimate goal for application of the findings. This study is considered as the most comprehensive review in this field since it covered about 53 studies during the period 1986-2016. Objectives: The study is designed to define the current status of Sudanese medicinal plants' research seeking for antiparasitical activity, in order to define the gaps in this field and provide basic data for setting future strategic plans in medicinal plants’ research in Sudan. Methods: The current review was done by collecting data on medicinal plants native to Sudan, which have been reported to possess potential antiparasitical activity. This was carried out by reviewing various research papers, review papers, short communications, MSc and PhD theses and published books, during the period 1986-2016. The sources of data were initially gathered from the major scientific databases such as science web of Knowledge, Science Direct, Pubmed and Google. Results: The study revealed that, at least 49 plant species belonging to 29 families were screened and tested for their antiparasitical activity in Sudan during the mentioned period. The family Fabaceae was the most screened family with 10 species. The species Acacia nilotica (L.) Del. received the greatest attention by researchers and has been tested in six different studies. At least 24 species of parasites belonging to 16 genera were investigated in search for antiparasitical activity. The species Plasmodium falciparum received the greatest attention by Sudanese researchers and has been investigated in 25 different studies out of the 53 studies reviewed. Conclusions: Parasitic diseases represent a major health problem in Sudan. The search for medicinal plants with antiparasitical activity is badly needed to help overcome this problem. The current study will highlight the most promising plants and define the gaps for completing the research in this highly important field.