Miracle-dz/UniFAR-FTUs huggingface dataset:
Sentimental Analysis of Social Networks using MapReduce and Big Data Technologies

- Social networks have become important medium of communication in presents days. This communication is regularly evolving towards the goal of making it as human and real as possible. Social network sites are used to express thoughts, emotions and opinion. There is a need of a framework that can recognize emotions present in communication or emotions of the involved users in order to enrich user in social networks. The data is generated by social network sites is very huge in amount and it is generated regularly, So in our study we have proposed a Big Data architecture to identify emotions present in text data generated by Social networks. The proposed architecture comprises following phases. 1. Collection of data. 2. Model building for data management. 3. classification of text according to emotions from text using mode. We have used Apache mahout, Hadoop, NaiveBayes, OpenNLP, LMClassifier to create model, and classification of text. The traditional classifiers has restriction that these can work only for subset of large set of data which has to be taken for analysis and the size of data generated by social networks grows in exponentially. Hadoop is a framework that is used for distributed storage and parallel data processing. Our proposed architecture is able to create a combined clustering and classification of data that run on Hadoop to classify text data generated by social networks in to positive and negative classes. We tried to optimize the performance of Big data analysis and used map reduce paradigm in hadoop architecture. It is very useful in the distributed environment for huge number data and performs classification faster than standalone system.
Machine Learning b ased Oil Painting Authentication and Features Extraction

Summary After the amount of the available artwork in digital form is being increased, the need of finding simple and costless way to authenticate paintings is being more important. The process of artworks authentication is done using different analysis ways; manually by experts or automatically by computer processing. In this paper, oil paintings authentication system using digital image processing techniques and algorithms was proposed. Features were extracted from color and texture. Machine learning methods were used to classify the tested painting on original or forgery, based on rules from the mentioned extracted features. Five different tests and two datasets were used to evaluate the proposed system. The first dataset was used on previous work, and the second was built on this research. Color and texture features were extracted from both datasets. Two classifiers were used to study the effect of classification method on the accuracy of the authentication results. Results show an improvement on the classification accuracy using the proposed system compared with previous works.
Improving Cohesion Measurement for Object Oriented Systems in Java

High cohesion in classes is an essential property of Object Oriented (OO) software as it positively impacts understanding, reuse, and maintenance. Existing approaches to measure cohesion are largely based on using the structural information from the source code, such as attribute references in methods. The measure, named the Conceptual Cohesion of Classes (C3), for the cohesion of classes is based on the analysis of the unstructured information embedded in the source code, such as comments and identifiers. To retrieve the unstructured information from the source code Latent Semantic Indexing is used . C3, is inspired by the mechanisms used to measure textual coherence in cognitive psychology and computational linguistics. This measurement is used to construct models that predict software faults. This paper aims at developing a tool named “C-CUBE “to compute the conceptual cohesion of OO classes.
Results from a phase 2b, randomized, multicenter study of GVAX pancreas and CRS-207 compared to chemotherapy in adults with previously-treated metastatic pancreatic adenocarcinoma (ECLIPSE Study).

345Background: GVAX is composed of irradiated, allogeneic pancreatic cancer cells modified to express GM-CSF and induce broad tumor antigen responses. Low-dose cyclophosphamide (CY) is administered with GVAX to inhibit regulatory T cells. CRS-207 is live, attenuated, double-deleted Listeria monocytogenes(LADD) engineered to express mesothelin. CRS-207 boosts T cell responses against mesothelin and stimulates innate and adaptive immunity. In an earlier Phase 2 study in patients with mPDA, CY/GVAX + CRS-207 resulted in a significant improvement in overall survival (OS) compared to CY/GVAX alone. Methods: Patients with previously-treated mPDA were randomized 1:1:1 to receive 2 doses of CY/GVAX + 4 doses of CRS-207 (Arm A), 6 doses of CRS-207 alone (Arm B), or physician’s choice of single-agent chemotherapy (Arm C). Two cohorts were included based on number of prior lines of therapy; the primary cohort (PC) represented those with ≥ 2 prior lines. The primary objective was to compare OS between Arms A and C in.
Cone Photoreceptor Structure and Function in Adolescents and Young Adults with Type 1 Diabetes

This cross-sectional study assessed properties of cone photoreceptors in patients with type 1 diabetes, as potential biomarkers of sub-clinical retinopathy. Patients with no vascular signs of retinopathy (ages 12-25) exhibited abnormal neuroretinal structure and function of the cone photoreceptor layer as compared to age-similar controls. White flash electroretinogram a-waves, demonstrating Land M-cone function, were significantly less steep in patients than in controls (by 1.3 mV/ms, 95% CI: -0.3, -2.3, p=0.01). Red flash electroretinograms did not differ between groups. Adaptive optics retinal imaging was used to visualize Land M-cones in vivo. At 7.1 o eccentricity along the 45 o meridians, cone density was lower in patients than in controls. This difference was significant in the nasal hemiretina (168 cones/degree 2 , 95% CI: 62, 273, p=0.002), but not in the temporal hemiretina. To definitively assess the ability of a-wave slope and cone density to predict subsequent development of retinopathy, longitudinal analyses are
An Investigation on Face Detection Applications

Face detection in uncontrolled ambiance continues to be a challenge to traditional face detection methods due to the large difference in facial expressions. The task of alignment is particularly difficult when the face comes from an extremely unconditional environment. To overcome these problems, the present paper is a reliable and deeply considerable application that allows users to detect a face(s) in real-time and process them. Database of faces with bounding rectangles and facial landmark locations is collected, and simple discriminative classifiers are learned from each of them. Then methods for morphing, warping, swapping and averaging of faces are presented. As a result, faces can be very effectively detected, aligned/ oriented and used for the above methods. In addition, based on results this approach can detect faces and eyes in difficult conditions without explicitly simulating their variation. Evaluating the tests of the application, it can confidently said that this face detection method is accurate and effective and reaches the most modern level of performance. The same methodology can easily be generalized to other tasks, as well as the detection of a common object.
Occurrence, Ecotoxicology, and Treatment of Anticancer Agents as Water Contaminants

Pharmaceuticals and personal care products as pollutants (PPCPs) have been identified in the environment for decades. But until recently, these mainly manmade chemicals are first called as PPCPs, which comprise bioactive substances such as therapeutic drugs, diagnostic agents, fragrances, cosmetics, and sun screen products. The major concerns with the ecotoxicities of PPCPs come from prescription and over-the-counter medications due to their specific targets on living tissues. Antibiotics have long been studied for the development of antibiotic resistant bacteria in the environment [1]. Endocrine disrupting compounds are examples of PPCPs that influence the sexual behavior and reproduction of aquatic organisms [2].
ANTIDIARRHOEAL ACTIVITY OF Curcuma Neilgherrensis Wt

Turmeric is one of the wonderful product of Curcuma longa as major spice in Indian food used as antibiotic and other in medicinal formulations. And it is significant in using many traditional and auspicious occasions. The wild turmeric Curcuma neilgherrensis is also used by the local herbalists and ethnic group of seshachalam hill regions as spice ingredient in food preparations and used to cure many health disorders like skin diseases, wounds, ulcers, bone fractures, inflammations, arthritis, cold and cough, diarrhoea, worm infestations, chicken pox and small pox, menstrual disorders and diarrhoea. Rhizome and leaf were pharmacognostically evaluated for the presence of phytoconstituents, antibacterial and antifungal activities and anthelmintic studies, and proved its effective activity. Hence it is interested to evaluate against anti diarrhoeal activity of rhizome methanol and aqueous extracts and also its acute oral toxicity studies to prove as harmless drug on Albino wistar rats. Rhizome methanol extracts at 1000 mg/kg b.wt proved more effective to that of Atropine the standard drug with 70 % antidiarrhoeal activity and 60 % of fluid inhibition than the aqueous extracts may be due to the presence of tannins, terpinoids, glycosides, flavonoids and saponins. And it is proved as the safe drug upto 5000 mg/kg b.wt without any behavioural changes.
Central Electric Field and Threshold Voltage in Accumulation Mode Junctionless Cylindrical Gate MOSFET

Received Oct 29, 2017 Revised Feb 8, 2018 Accepted Feb 18, 2018 Transfer characteristics is presented using analytical potential distribution of accumulation-mode junctionless cylindrical surrounding-gate (JLCSG) MOSFET, and deviation of center electric field at threshold voltage is analyzed for channel length and oxide thickness. Threshold voltages presented in this paper is good agreement with results of other compared papers, and transfer characteristics is agreed with those of two-dimensional simulation. The most important factor to determine threshold voltage is center electric field at source because the greater part of electron flows through center axis of JLCSG MOSFET. As a result of analysis for center electric field at threshold voltage, center electric field is decreased with reduction of channel length due to drain induced barrier lowering. Center electric field is increased with decrease of oxide thickness, and deviation of center electric field for channel length is significantly occurred with decrease of oxide thickness. Keyword:
Enhancing the Performance of Iris Recognition System using Matching Score Fusion Technique

— As biometrics, iris always a preferred trait because of its uniqueness of pattern contain by each eye and lifetime stability. The random distribution of features in an iris image texture allows performing iris based person authentication with high confidence. But use of single iris image indicator often has to contend with noisy sensor data, physiological defects, and unacceptable error rates. So this paper proposed an iris recognition algorithm in which an image of left iris and right iris are use as an input. DCT can be employed to extract unique iris pattern and encode it into binary template. Then allows comparison between current and stored template using hamming distance. This process is applied on left iris and right iris separately and corresponding distance scores are generated for each eye. This score are then combined using weighted average fusion rule to generate final score. This score is compared with threshold to decide the person is genuine or imposter. Simulation studies are made to test the validity of the proposed algorithm. The results obtained ensure the superior performance of this algorithm. This ensures the presence only alive person and increases recognition rate by eliminating the possible spoofing attacks.
Clustering Techniques for Digital Image Segmentation

----------------------------------------------------------------ABSTRACT-------------------------------------------------------- An image analysis is a process to extract some useful and meaningful information from an image. Segmentation is one of the methods used for image analyses. Image segmentation has many techniques to extract information from an image. Clustering is a technique which is used for image segmentation. The main goal of clustering is to differentiate the objects in an image using similarity and dissimilarity between the regions. K-Nearest Neighbour is a classification method. K-mean is a clustering technique which is a simple and an iterative method. In this paper, details of both algorithms have been provided with the implementation results on an image dataset consisting of 4 images.
Unsupervised Classification in Land Cover Types ‎Using Remote Sensing and GIS Techniques

- Satellite images and the thematic maps extracted will provide higher-level of information in recognizing, monitoring and management of natural resources. It is very difficult to identify land cover classification manually from a satellite image. Therefore the need of remotely-sensed satellite images as sources of information for various investigations is required since they provide spatial and temporal information about the nature of the surface of the earth and feature therein. This paper examines image identification and classification using an unsupervised method with the use of Remote Sensing and GIS techniques. The objective of image classification is to identify and portray, as a unique gray level (or color), the features occurring in an image in terms of the object or type of land cover these features actually represent on the ground. Three classes identify in this study are the Soil, Vegetation and Water. Landsat 7 ETM+ Satellite imagery was used in identifying each class. This study also used parallelepiped method to determine the land cover through software ENVI 5 and ArcGIS 10.2. From the results, it showed that the three classes of land cover were properly demarcated and distinguished.
The Infrastructure of School Culture: Measuring Commitment, Discourse, Efficacy, and Sensemaking in Adequate Yearly Progress

While achievement test results lead to after-the-fact AYP results, this research delves into measures behind and beyond test scores, the matter-of-fact workplace norms of schools. Elementary teachers completed items in the VISTAA survey as analysis revealed five constructs of school culture: commitment to student learning, commitment to collegiality, discourse, efficacy, and sensemaking. As a single aggregate factor, defined standard deviation gains in the school culture composite increased the likelihood of attaining AYP by 81%. The results also show positive associations for individual predictors concerning the infrastructure of school culture with the outcome of AYP.
Speech Based Access for Agricultural Commodity Prices in Tamil

Machine-Human interaction plays an important role for many users in order to access the information. The interactions could be in the combination of text, speech, facial expressions etc., or separately. The objective of the proposed work is to develop a speech based agricultural commodity prices accessing system in which recognition of user queries is implemented using i-vector approach. In the proposed work, i-vector based approach is adopted for speech recognition. The recognition tasks can be conducted for both speaker dependent and speaker independent case. The experimental results show that the Equal Error rate (EER) obtained for the proposed system is improved and the performance of the system is improved when increasing the number of Gaussian mixture components and also number of i-vector components.
Frequency Reconfigurable Metamaterial Inspired High Gain Antenna

In this paper, we present a design of frequency reconfigurable metamaterial inspired high gain antenna. In this we use an equilateral triangular shaped split ring resonator (ETSRR) with rotated rings. The rings are virtually rotated with the help of Microelectro-mechanical system (MEMS) switches. The ETSRR structure exhibits negative refractive index material (NRIM) property and at the same time ETSRR structure behaves like high gain antenna. When the inner ring of ETSRR is rotated the antenna resonant frequency shits from 8.07 GHz to 8.05 GHz; while by rotation of outer ring the antenna resonant frequency shifts from 8.07 GHz to 8.04 GHz or to 8.08 GHz. Thus we get frequency reconfigurability.
Cooperative QOS Control Scheme Based on Power Allocation and Scheduling of WDM-OWC Network

In the past two decades, transfer of data can be possible with the combination of radio frequency and optical wireless communication (OWC) system. An alternative to radio frequency and fiber optic communication system is an OWC. Optical wireless Communication network have high data rate, license free spectrum, high immune to electromagnetic interference, low power and cost of optical components used. In this paper we have designed a WDM-OWC system for a range of 800 Km. Different simulation module like power allocation and scheduling have been performed on WDM-OWC. With Power allocation in which Q-factor and output power increases, whereas BER decreases other module is scheduling of OWC and it is found that 100 GHz of frequency spacing at a wavelength of 1550 nm is the best efficient in terms of Q-factor and BER.
Human Action Recognition using Support Vector Machine and K-Nearest Neighbor

 Abstract — Recognizing human actions from video sequences is termed as Human Action Recognition. It has many important applications like video surveillance, patient monitoring, human computer interaction, dance choreography analysis, analysis of sports events and entertainment environments. In this paper the work of the enhancement of human action recognition of the videos with the help of a Hybrid technique has been demonstrated. It proceeds in a step-wise approach. Firstly the train feature database is created to store the features. The testing of videos is then done on basis of support vector machine and K-nearest neighbor classifiers. The K-NN classifier here works by taking up Euclidean distances between the test and train features. Also Region of Interest is extracted by highlighting the boundary box to recognize the action and specific action labels are applied in the videos and the Non-ROI is enhanced using the median filter. The results obtained are quite significant and are analyzed on the public benchmark Weizmann dataset, which contains examples of bending, running, walking, skipping, and hand-waving of two types with both one and two hands, with nine actors performing these actions.
A Survey on congestion control with TCP network

- Congestion Control performs a completely important role in Computer Networks, Modern Telecommunication, Internet and each wired and wireless communications are being meant for excessive-velocity conversation of huge quantities of records. Due to lack of right Congestion control mechanism the congestion collapse of such networks would emerge as especially complex. A network with Streamed media traffic is a challenge for Congestion manages because of sensitivity. In this paper, a survey on diverse mechanisms of congestion control and avoidance has been completed.
Big Data with reference to IoT: Architecture, Opportunities and Challenges

: Big amounts of data have been produced, as the miniaturization of Internet of things (IoT) devices increases. However, such data are not useful without analytic power. Several big data, IoT, and analytics solutions have empowered people to obtain valuable insight into large data generated by IoT devices. This paper investigates the contemporary research efforts directed toward big IoT data analytics. The relationship between big data analytics and IoT is explained. We identify the opportunities resulting from the convergence of big data, analytics, and IoT as well as discuss the role of big data analytics in IoT applications. Furthermore, big IoT data analytic types, methods, and technologies for big data mining, challenges, and opportunities are discussed. Several notable use cases are also presented. Several opportunities brought by data analytics in IoT paradigm are then discussed.
Effect of Perturb & Observe Algorithm and Incremental Conductance Algorithm on the Performance of Cuk Converters for Photovoltaic Application

This study presents a new kind of maximum power point tracking algorithm based on perturb and observe algorithm and incremental conductance algorithm compare. A generalized photovoltaic array simulation model in MATLAB/Simulink environment is developed and presented. This paper presents in details comparative study between two most popular algorithms technique which is incremental conductance algorithm and perturb & observe algorithm. Considering the effect of solar irradiance and temperature changes, the output current and voltage of PV modules are simulated and optimized using this model. Cuk converter use for comparative study. Few comparisons such as efficiency, voltage, current and power output for each different combination has been recorded in this paper. Cuk converters are considered as possible dc–dc converters that can be cascaded. MATLAB simulations are used to compare the efficiency of each topology as well as evaluating the benefits of increasing cost and complexity. The cuk converters are shown to be the most efficient topologies for a given cost, with the cuk best suited for long strings. The proposed model is designed with a user-friendly icon and a dialog box like Simulink block libraries.
Study of the Vascular Endothelial Growth Factor Gene Expression and Serum Placental Growth Factor Levels in Egyptian Women with Preeclampsia

Introduction: Preeclampsia (PE) is one of the major causes of feto-maternal morbidity and mortality, it is diagnosed by development of hypertension and proteinuria after 20 weeks of gestation. This study was conducted to determine whether altered levels of vascular endothelial growth factor (VEGF) andPLGF level may play a role in the pathogenesis of preeclampsia.Methods: We performed a cross section study in 50 preeclampticwomen: 25women with mild PE, 25 patients with severe PE. While 24 normotensive pregnant women matched for age as a control group. Placental mRNA expression of VEGF was measured by real time PCR (RTPCR). Maternal serum levels of PLGF was measured by ELISA.Results: Themean VFGF expression was statistically higher in cases of severe PE than Mild PE, both were higher than control group (p<0.0005). On the other hand the mean PLGF levels wasstatistically significantly higher in control group as compared to either of the two PE groups (p< 0.0005) and there is no statistically significantly difference between sPE and mPE groups. Conclusion: The increase of VEGF gene Expression in placenta tissue and decrease of PLGF level in maternal serum predict the risk of preeclampsia.
SURVEY OF SENTIMENT ANALYSIS

In recent days, Sentiment Analysis is studied and analyzed by divergence, and collaboration ways to model a framework. In this regard, a lot of attempts have customized scopes and purposes. Sentiment Analysis gains momentum due to numerous applications are revealed in the real world. Researchers across the globe applied ranges of methods over periods of time that slowly but steadily betterment the extraction procedure of sentiment and its associated evaluations. Few interesting survey papers are found that cited latest papers. Substantial advancement is incurred thereafter with both new approaches, and evaluation techniques that have cutting-edge scopes. In this work, more than forty research papers are studied. Among those, five novel and utmost reputed research works are classified according to their approaches, results, and data set. Summarization, Tables, and diagram are used to illustrate pros and cons of different approaches in the survey work. Finally, the findings of the survey are specified.