Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementation of Emotion Recognition By Real Image Expression usingWeb Camera With The Help of Matlab Tool

: The human face assumes a tremendous part for programmed acknowledgment of feeling in the field of recognizable proof of human feeling and the connection amongst human and PC for some genuine application like driver state observation, customized learning, wellbeing checking and so on. Most announced facial feeling acknowledgment frameworks, in any case, are not completely thought to be subject-autonomous dynamic highlights, so they are not sufficiently vigorous for genuine acknowledgment assignments with subject (human face) variety, head development and brightening change. In this article we have endeavored to outline a computerized structure for feeling location utilizing outward appearance. For human-PC cooperation outward appearance makes a stage for non-verbal correspondence. The feelings are adequately variable happenings that are evoked because of actuating power. So, in actuality, application, discovery of feeling is exceptionally testing undertaking. Outward appearance acknowledgment framework requires to defeat the human face having various changeability, for example, shading, introduction, demeanor, stance and surface so on. In our structure we have taken edge from live gushing and prepared it utilizing Grabor highlight extraction and neural system. To distinguish the feeling facial traits extraction by foremost segment investigation is utilized and a clusterization of various outward appearance with individual feelings. At long last to decide outward appearances independently, the handled element vector is directed through the officially learned example classifiers. Outward appearances offer essential information concerning feelings of somebody. Understanding outward appearances precisely is one in all the troublesome assignments for social connections. Programmed feeling identification abuse outward appearances acknowledgment is as of now a principle space of enthusiasm among changed fields like registering, drug, and science. HCI examination groups also utilize machine-controlled facial highlights acknowledgment framework for higher outcomes. changed element extraction systems are produced for acknowledgment of articulations from static pictures in addition as ongoing recordings. This paper gives an audit of investigation work dispensed and uncovered inside the field of facial highlights acknowledgment and changed methods utilized for facial highlights acknowledgment.
Data Mining Techniques and Research Challenges and Issues

--Data mining is considered to deal with huge amounts of data which are kept in the database, to locate required information and facts. Data mining is the exploration and analysis of large quantities of data in order to discover valid, novel, potentially useful, and ultimately understandable patterns in data. Non trivial extraction of implicit, previously unknown and potentially useful information from data Exploration & analysis, by automatic or semi-automatic means, of large quantities of data in order to discover meaningful patterns. In this paper, we discuss the data mining techniques and functionalities with application. Also discuss the research challenges in science and engineering, from the data mining perspective, with a focus on the data mining issues.
Shadow Elimination and Vehicles Classification approaches in Traffic Video Surveillance Context and Log Conversion

-Object detection in the field of computer vision stands to be a crucial and critical task for object and scene recognition, employment of object recognition is vast in field of surveillance and artificial intelligence. An inner–outer outline profile (IOOPL) algorithm is employed to detect the three levels of object boundaries to enhance the satellite imagery segmentation with the help of shadow elevations. This method can be adapted to an experimental model of traffic surveillance video monitoring. In Intelligent Transportation System (ITS) it is very important to recognize the type of a detected object in order to track reliably and estimate traffic parameters correctly . This work addresses the major difficulty faced in the vehicle image segmentation due to the misconception of assuming object shadows as part of object itself. The proposed methodology will be utilized for vehicle detection and segmentation by eliminating its shadow counterpart
Efficacy of yoga to improve balance and reduce fall in community dwelling elders who are at risk of fall

Identification of older adults who are at a risk for falling is a vital medical concern. Falls are common events in the lives of older people and can result in a range of adverse outcomes, from minor bruises to fractures, disability, dependence and death. With age, balance abilities decline and become harder to control, which results in an increased risk of falling, even in the absence of specific neurological or musculoskeletal problems. TUG a simple screening test for measuring the probability for fall among elders and Modified fall efficacy scale for determination of measuring fear of falling. Yoga, with its gentle movements, can address known fall risk factors (poor balance, impaired mobility, reduced strength and flexibility) and focus on increased awareness and proprioception, resulting in decreased fear of fall and improved balance in older adults. Therefore, the purpose of this study is to investigate the effect of yoga to improve balance and reduce fall in community dwelling elders at risk of fall. 100 subject were taken with consent and 6weeks protocol Yoga was given. Yoga Asanas were uttkatasana, tadasana, vrukshasana, trikonasana, virbhadrasana (position 1 & 2). First 3 week Yoga exercises were performed with support of walls and chair. (in the modified form). In the next 3 weeks yoga exercises were progressed by performing without support and increasing the hold time of asanas. Results obtain were that the functional mobility (TUG), and fear of falling (MFES) showed more improvement. Therefore Yoga is effective to improve balance and reduce risk of fall.
EVALUATE ANTIFERTILITY EFFECTS OF TECOMELLA UNDULATA TO DEVELOP AN ORAL MALE CONTRACEPTIVE

Introduction At present, population explosion is one of the social problems since uncontrolled growth declined natural resources and cause threatens to sustainable development. Many methods of contraceptives have been designed for women, while need to paid satisfactorily attention for men in this issue (Soni et al., 2015) and secondary thing is the synthetic contraceptives use for fertility control create several harmful effects such as weight gain, hypertension, increased possibility of cancer and hormonal imbalance (Shafik, 1994) Thus demand to replace these synthetic agents by safe and effective agents based on plants. In Ayurveda medicine system, these plant based drugs are more use because of these low toxic natures and long standing experience of exposure (Chaudhary et al., 2011).
Sentence Alignment for English Urdu Language Pair

 Abstract:Sentence aligned parallel text is an important resource in statistical machine translation; therefore, Sentence alignment is a crucial part of machine translation.The sentence alignment task comprises of recognizing the correspondence between words sentences and paragraphs of the source and target languages. Different researchers proposed several sentence alignment algorithms for aligning sentences of the source and target language. In this paper, we have explored sentence alignment algorithms based on character length , word length and lexical matching and carry out performance analysis of Gale and Church Algorithm on English and low resource language Urdu .
FRAMINGHAM RISK SCORE IN ESTIMATING CARDIOVASCULAR DISEASE RISK FACTORS IN PEOPLE OF ASIAN INDIAN ORIGIN: A STUDY ON RURAL ADULT POPULATION IN WEST BENGAL, INDIA

Aims: This study was aimed to investigate the efficacy of Framingham risk score (FRS) in estimating cardiovascular disease (CVD) risk in a rural adult population in West Bengal, India. Methods: This crosssectional study was carried out among 1007 participants (645 males and 362 females) aged 20 to 80 years in a rural adult population in West Bengal, India. Anthropometric measures and blood pressure were collected using standard techniques. Metabolic profiles and insulin was also estimated and HOMA-IR was calculated subsequently. Results: The higher mean was observed for age, height, waist circumference, waist-hip ratio, total cholesterol, triglycerides, low and very low density lipoprotein cholesterol, fasting blood glucose, systolic and diastolic blood pressure and mean arterial pressure with increasing FRS category. On the contrary, lower mean was found for weight, hip circumference, waist-height ratio, body mass index, percentage body fat, sum of four skinfolds, high density lipoprotein cholesterol, insulin and insulin resistance. Significant age group difference was found in respect to FRS category. No remarkable difference was noticed in the prevalence of metabolic syndrome with increasing FRS. Conclusion: More comprehensive risk prediction algorithm is required to better comprehend the CVD and its’ risk factors in this population.
A Dendrogeomorphological Study of the Local Effect of Climate Change

The climatic and environmental conditions of Patagonia changed substantially after 1850 and after the mid-1970s decade. The impact of these changes is being observed in the new configuration of rivers and their riverine vegetation. The objective of this work is to integrate dendrogeomorphological techniques to the mapping and modeling of the recent distribution of vegetation of the riverine landscape, as an indicator of the local effect of climate change.The hydrological regime and the evolution of riparian vegetation at the confluence of the Cuyin Manzano and Traful Rivers were synchronized using the data obtained from 34 samples of plots of 6x6 meters. The plots were adjusted to the pixel resolution of two SPOT 7 satellite images (flood and dryness), concentric to an area of 18x18 meters, in order to validate a supervised classification of vegetation, belonging to different fluvial geoforms. In the plots with woody vegetation two trees corresponding to one or two age classes characteristic of the stands were drilled. The results indicate that, in agreement with global and Patagonia climate change estimates, there is a slight tendency of change in the flood and drought regime, with decreases in mean annual minimum flows and a period of drought in the last six years. The most outstanding result of our study indicates that the change of the hydrological regime implies a slight European Scientific Journal June 2017 /SPECIAL/ edition ISSN: 1857 – 7881 (Print) e ISSN 18577431 177 reduction of the average minimum flows, without this entailing a modification of the regime of flood pulses that in some cases are very extreme. This situation has a marked incidence in the fact that the woody vegetation colonizes new substrates and emerged landforms, while it is affected by frequent and intense flood events, with a change of the compositions and distribution of the vegetation.
A Roadmap to an Enhanced Graph Based Datamining Approach for Multi-Relational Data mining

Multi-relational data mining (MRDM) is a subfield of data mining which focuses on knowledge discovery from relational databases comprising multiple tables. The approaches to MRDM are categorized into five groups. They are greedy search based approach, inductive logic programming (ILP) based approach, inductive database based approach, mathematical graph theory based approach and kernel function based approach. Representation is a fundamental as well as a critical aspect in the process of discovery. These five approaches are grouped into two forms of representation, namely the graph-based representation (GBR) and the logic-based representation (LBR). In this paper, some major studies in each category are described, and representative methods among the studies are sketched. The comparison of Graph-based and logic-based multi-relational data mining according to the factors such as Structural Complexity, Semantic Complexity, Background Knowledge intended to condense the hypothesis space, and Background Knowledge intended to augment the hypothesis space is described and based on the comparison results the necessity of enhancing the Graph-based representation is enforced.
A Novel Multi-hop Threshold based Relay Selection Scheme

Relay selection in co-operative networks plays a vital role in increasing the efficiency of networks. If the selected relay is not the best relay then the end-to-end co-operative network will be in failure. In this proposed relay selection scheme, threshold-based relay selection is applied in the first-hop the source-to-relay link. From the destination, the best relay will be selected based on Output Threshold Multiple Relay Selection (OT-MRS) scheme [8]. If the relay selected by the source and destinations are different then multi-relay transmission will take place between the relays. In this paper closed form SER formulations of the system are derived. Keywords— Co-operative networks; Relay selection; Outage probability; Interference; Co-operative relaying
Mobile Keylogger Detection By Using Machine Learning Technique

- Keylogger, a highly specialized tool designed to record every keystroke made on the machine to giving the attacker the ability to steal large amounts of sensitive information silently. The primary objective of this project is to detect keylogger applications and prevent data loss and sensitive information leakage. In This project aims to identify the set of permissions and storage level owned by each of the applications and hence differentiate applications with proper permissions and keylogger applications that can abuse permissions . This technique of detecting keyloggers is completely Black-box its based on behavioral characteristics common to all keyloggers and it does not rely on the internal structure of the keylogger. The paper intends to develop a machine learning-based keylogger detection system on mobile phones to detect malware applications
Analysis of EEG Signals for Epilepsy and Seizure by decomposition with Wavelet Transform

293  Abstract— The Electroencephalogram (EEG) is a complex signal that indicates the electrical activity of brain. EEG is a signal that represents that effect of the superimposition of diverse processes in the brain. Epilepsy is a common brain disorder. Out of hundred one person is suffering from this problem. Here we study a novel scheme for detecting epileptic seizure from EEG data recorded for healthy subjects and Epileptic patients. EEG is obtained by International 10-20 electrodes system. Wavelet transform is used for feature extraction. Wavelet Transform (WT) provides a flexible way of time-frequency representation of a signal.
GREEN CONCRETE AND ITS DEMAND ON THE SUSTAINABLE CONSTRUCTION INDUSTRY

Concrete is one of the most important components of construction materials. The world is converting into concrete jungles at a very fast rate, which is involving high consumption of energy and other resources, thus leading to adverse environmental impact. Consequently there is need to carry out sustainable growth in the field of concrete industry. Such sustainable development can be attained by use of environmentally friendly green concrete leading to decrease in greenhouse gas emissions. Green cement concrete is produced by using recycled waste materials such as activated fly ash and recycled concrete aggregates. Other concrete alternatives can be equally used to significantly increase the sustainability and durability. Secondly, one must plan for structural designs involving environmentally friendly maintenance strategies which will need less of energy and resources. Although green concrete seems to be providing lot of benefits, still one needs to consider the potential barriers on its way. They are increase in cost of recycling and reusing along with use of additional energies and resources for the same and the fear of failure of the green concrete as it is made from reused products. One can conclude that overcoming the above demerits would help to use green cement concrete with a potentially new environmental friendly
Prioritizing Test Suites Using Clustering Approach in Software Testing

- Prioritizing test cases enables test suites to be scheduled in a manner that optimize the objective of reducing effort to test exhaustively. Of various techniques/methods available, a need is felt to further improve existing schemes. In this paper, we propose clustering based prioritization and support our effort with average percentage of fault detection (APFD) measure. We target the significant test suites to get priority. Our method can considerably help realization of overall clustering approach.
A Review of Literature on Delta Closed Patterns and Noninduced Patterns from Sequences

—Discovering patterns from sequence data has significant impact in many aspects of science and society. In the real world, usually a large set of patterns could be discovered yet many of them are redundant, thus degrading the output quality. To improve the output quality by removing two types of redundant patterns. First, the notion of delta tolerance closed itemset is employed to remove redundant patterns that are not delta closed. Second, the concept of statistically induced patterns is proposed to capture redundant patterns which seem to be statistically significant yet their significance is induced by their strong significant subpatterns. This approach produce a relatively small set of patterns which reveal interesting information in the sequences.
International Journal of Scientific Research in Computer Science, Engineering and Information Technology

Mobile Adhoc Network (MANET) are resource constrained. Energy is one of the most important resources in such networks. Therefore, optimal use of energy is necessary. In this project, we present a novel energy-efficient routing protocol for MANETs. We propose a Scattered Based Energy-aware Fuzzy Logic based routing algorithm (SBFL) that simultaneously addresses energy efficiency and energy balancing. Our design captures network status through appropriate energy metrics and maps them into corresponding cost values for the shortest path calculation. We seek fuzzy logic approach for the mapping to incorporate human logic. We compare the network lifetime performance of SBFL with other popular solutions including GA and ACO. Rigorous simulation results depict the energy efficiency, throughput, and prolonged lifetime of the nodes under the influence of the proposed protocol. Future scope of this work is outlined.
QUALITY IMPROVEMENT OF CIVIL ENGGINERING PRODUCTS USING HELPFUL REVIEWS FROM SOCIAL MEDIA

The social media sites are a source of content of customer experiences based on Product usage (the best and the worst) with details covering preferences, expectations and a variety of candid product feedbacks resulting in User Generated Content (UGC). This vast user generated content of product reviews and comments which when utilized can provide meaningful insights and information to improve product quality across industries and a competitive advantage in the product market segment. This study aims to explain the importance and the effective source of meaningful reviews from social sites which help product quality improvements. This research is based on secondary data that shows the relationship available between helpful review comments and product quality management aspects. The findings from the existing literature review concludes that user generated content from social sites appeal and when innovative technological solutions applied help product quality improvement effectively.
Variability and Association Grain Weight with Grain size (and shape) and grain quality, and stepwise Regression analysis on thousand grain weight in Iranian Durum Wheat Landraces

Grain weight and quality in durum wheat, greatly influence by grain morphology and grain protein content (GPC). In order to detection of phenotypic diversity level and relations between thousand grain weight (TGW), grain size (and shape) and grain quality, a collection of 79 durum wheat landraces from different geographic regions of Iran was used across two years (2013-15). A high-throughput method was used to capture grain size and shape. The high level of variation was observed with significant differences (P <0.001) among genotypes for all traits. A moderate to high broad sense heritability was found for all traits and ranged between 0.70 and 0.93 for grain yield and width, respectively. Grain weight significantly correlated with grain morphology (with exception of aspect ratio (AR) and roundness) and GPC. It can be a result of durum wheat landraces with high grain yield and high grain protein. By taking TGW as dependent variable a six variables regression model, including grain volume, factor from density (FFD), width, length, perimeter and GPC with explain more than 99.25% of TGW variation, was recognize as the best model. Based on path analysis, FFD exhibited maximum positive direct effect on grain weight followed by perimeter. Grain length, width and volume had similar positive direct effects. However, GPC has negative direct effect on grain weight. According to cluster analysis, landraces separated into 6 clusters, and cluster V and IV had the maximum and minimum average for the most traits, respectively. This study provides useful information on the relations between TGW, grain size (and shape) and grain quality in durum wheat, that may help to improve grain weight in breeding programs.
333-337 Padma Ambalam

Two human lactobacilli strains L. rhamnosus 231 (Lr 231) and L. rhamnosus V92 (Lr V92) exhibits potential probiotic properties. In the present study we evaluated safety of these strains by using (i) in vitro test; non haemolytic and antibiotic sensitivity (ii) in vivo trials using mouse model by an orally feeding 1x10 cfu of Lr 231 and Lr V92 to Swiss albino mice for 2 weeks. During the experimental period, probiotic strains did not produce any adverse effect on the general health status, feed intake and body weight. No viable Lr 231 or Lr V92 cells were recovered from blood or tissue (liver and spleen) of mice. No treatment-associated illness or death was observed. Microscopic observation of liver and spleen sections did not show any sign of inflammation, degeneration or necrosis. The potential probiotic strains Lr 231 and Lr V92 possess no hemolytic activity, antibiotic sensitivity pattern was evaluated and are non-toxic to mice and appear to be safe for human use.
MaxNet-A New Congestion Control Architecture

— In this paper, we will introduce a new model of performing congestion control on a source-flow controlled best-effort network. We will now explore the structural constraints of the Internet congestion signalling model and develop a new architecture for signalling congestion on an Internet-like network that we call MaxNet. MaxNet differs from Internet because source rates are controlled only by the most severely bottlenecked link on the end-to-end source to destination path. MaxNet redefines how congestion signalling is performed and results in unique fairness and scaling properties. MaxNet is in keeping with the very successful Internet philosophy of having a simple network infrastructure. Providing a minimalist service model and having the stateless waist in the protocol hourglass allows the Internet to scale with both the size of the network and heterogeneous applications and technologies.