Miracle-dz/UniFAR-FTUs huggingface dataset:
Polarity Classification Using Twitter Data

— Polarity Classification over Twitter offers different organizations a fast and effective way to monitor the feelings/emotions of general public towards their brand, business, politicians etc. A wide range of features for training polarity classifiers for Twitter datasets have been researched in recent years with varying results. In this paper, we introduce a novel approach for automatically classifying and adding semantics as additional features the polarity of Twitter messages. These messages are classified as positive or negative or neutral with respect to a query term. The paper focuses on addressing polarity classification for product features in product reviews by building semantic association between product features and polarity words. The results show that our method is encouraging.
Hybrid Diode Clamped Multi Level Inverter for Electric Vehicle Applications

This paper presents multilevel inverters as an application for all-electric vehicle (EV) and hybrid-electric vehicle (HEV) motor drives. A hybrid clamped multilevel inverter topology comprising active and passive clamping devices is presented in this paper. In this topology, the dc-link capacitor voltages can be balanced without additional circuitry or separated dc voltage sources, regardless of load characteristics. It can be used in real and reactive power conversion applications. The topology structure, operating principle and self-voltage balancing ability are analyzed. The PWM control method called higher and lower carrier cells alternative phase opposition PWM is employed. This method can effectively reduce the number of devices switching on or off within broad modulation index range, consequently reducing switching losses, and remarkably reduce the amplitude of lower harmonics. Keywords--Multilevel, DC voltage, EVS
Int. J. Biosci

The present work aimed to deepen knowledge on the properties of sorghum malt used for tchakpalo production in Benin. It focused on the physico-chemical characterization of white and red varieties of sorghum malt samples, compared to an imported Nigeria’s variety named Farafara, selected for its brewing properties. The malts were produced and the physico-chemical parameters of malted and unmalted grains were performed. The efficiency of crushing using maize or hammer mill was also investigated and compared. Results obtained indicated that the dry matter of white and red sorghum varieties samples were respectively 89.44±0.21% and 90.15±0.20%. The thousand kernel weights were respectively 34.66±0.33g and 31.79±0.35gand the germination rates were 97.66±1.2% and 75.33±1.5%. The protein content of Benin’s white and red varieties and imported variety ranged from 9.75±0.7 % to 12.21±0.1 % whereas ash content were ranged from 1.25± 0.02 to 1.4±0.04%. The phenolic compounds content of Benin and imported variety were 0.49±0.01, 1.77± 0.02 and 0.76g± 0.02/100gDM respectively while oxalate content of samples varied from 0.33± 0.01 to 1.39±0.06g/100g DM respectively. The crushing tests showed that the maize mill was not suitable for sorghum malt crushing. Based on the present study, sorghum varieties from Benin could present physico-chemical characteristics that predispose them for malting. However we recommend to producers constituting cooperative to acquire specialized mills which could enable them to get groat for good extraction during brewing. * Corresponding Author: Edwige Dahouenon-Ahoussi  edahoussi_95@yahoo.fr International Journal of Biosciences | IJB | ISSN: 2220-6655 (Print) 2222-5234 (Online) http://www.innspub. net Vol. 5, No. 1, p. 217-225, 2014
Importance and Functions of Bills of Quantities in the Construction Industry: A Content Analysis

Bills of Quantities (BQ) is one of systematic ways applied in the construction industry in which its primary function is to record items of works for tendering purposes and to create a fair agreement among the parties involved for contracting purposes. However, there are some issues pertaining to BQ functions such as BQ is a misunderstood facet in the construction industry today, BQ is only useful for tendering purposes, BQ’s benefit is not fully utilised by the construction team and most of them cannot relate BQ with everyday construction works and processes. Therefore, the purpose of this paper is to study on the importance of BQ and its functions in the construction industry. A content analysis was used to identify the importance and functions of BQ from reviewing articles and books. Findings from this paper are beneficial in providing knowledge to the education field and construction teams on the importance and functions of BQ in the construction industry.
Forensic Practice for Occupational Therapists—the Alberta Experience

AbstractOutlined is the expanding role of occupational therapists in the forensic system in Alberta, Canada. Examples of the services from institution to the community are given. The innovative use of fieldwork sites through faculty/forensic staff agreements has led to job opportunities and expanded occupational therapy service. The paper ends with recommendations for future expansion of occupational therapy service.
A NOVEL APPROACH ON EDGE COMPUTING AND ITS VISION AND CHALLENGES

The proliferation of Internet of Things (IoT) and the success of rich cloud services have pushed the horizon of a new computing paradigm, edge computing, which calls for processing the data at the edge of the network. Edge computing has the potential to address the concerns of response time requirement, battery life constraint, bandwidth cost saving, as well as data safety and privacy. In this paper, we introduce the definition of edge computing, we present several challenges and opportunities in the field of edge computing, and hope this paper will gain attention from the community and inspire more research in this direction.
Risk Management and Poverty Reduction through CBOs. Evidence from Hai District, Tanzania

The study is on the investigation of the roles of CBOs in risk management and poverty reduction in Hai District. It is a case study research employing a total of 353 respondents as sample size. Data were collected through the use of different tools including observation, interview and documentary review. Most data collected were statistical thus analysed through SPSS
Gradual Shot Boundary Detection using SVM Optimization Technique and HOG Feature

 Abstract: Rapid growth in the field of data capturing and storage along with the increase in the availability of multimedia content in the web, has resulted in many large personal and public digital video databases. The Shot Boundary Detection (SBD) is the very first step in the research arear of video application. The objective of the SBD is to address the issues in Video Content Analysis (VCA), namely, Video Segmentation. From the analysis it is identified it is difficult for the human being to analyze the contents manually. Therefore, many methods is needed to automate the process of videos. Gradual Transition detection is based on the Support Vector Machine (SVM). To improve the result of this shot boundary detection, SVM with Histogram of Gradient (HOG) is used. HOG feature is calculated for further shot detection. Finally gradual shots are detected based on the above methods. Here the performance is evaluated by the parameters called precision and recall value.
A Study of Effective Sentiment Analysis Process for Opinion Mining

: Internet has become a platform for online learning, exchanging ideas and sharing opinions. Due to the sheer volume of opinion rich web resources such as discussion forum, review sites, blogs and news corporate available in digital form, much of the current research is focusing on the area of sentiment analysis. Social networking sites are rapidly gaining popularity as they allow people to share and express their views about topics, have discussion with different communities, or post messages across the world. There has been lot of work in the field of sentiment analysis of social networking data. This study focuses mainly on sentiment analysis of data which is helpful to analyze the information in the wordnet where opinions are highly unstructured, heterogeneous and are either positive or negative, or neutral in some cases. In this paper, we provide a study for opinion mining like Feature extraction is a crucial step for opinion mining which been used to collect the useful information from user reviews and one that takes as input these features, assigns ranks to them and decides the ﬁnal classiﬁcation of the review as positive, neutral, or negative. The algorithm we propose to identify the features is called the Improved High Adjective Count (IHAC). This will be done by Artificial Bee Colony (ABC) optimization algorithm. The main idea behind the algorithm is the nouns for which reviewers express a lot of opinions are most likely to be the important and distinguishing than those for which users don’t express such opinions. After processing all reviews the algorithm will score for each noun. The ranking will be used to filter to find which scores above a threshold, and the second proposed algorithm is Max opinion score algorithm which ranks the extracted features using opinion scores assigned from previous method. Till now, there are few different problems predominating in this research community, namely, sentiment classification, feature based classification and handling negations. This paper presents a study covering the techniques and methods in sentiment analysis and challenges appear in the field.
ENERGY EFFICIENT COMMUNICATION FOR WIRELESS SENSOR NETWORKS

MEMS (Micro Electro Mechanical Systems) technology is enabling the development of low-cost, autonomous wireless sensor nodes with energy consumption of various components. In wireless sensor network, the deployments of small sensor nodes are usually inaccessible to the user, and thus replacement of the energy source is not feasible as per battery powered. Hence, energy efficiency is a key design issue that improves the life span of the network. A homogeneous sensor network consists of identical sensor nodes, while a heterogeneous sensor network consists of two or more types of sensor nodes (organized into hierarchical clusters). We proposed several network layer protocols to improve the effective lifetime of a network with a limited energy supply. We classified sensor network as per clustering. The simulation results of energy consumption prove that the performance of the heterogeneous sensor networks and the homogeneous sensor networks.
Validation of “ Prosocial Tendencies Measure ” in Iranian University Students

The aim of the present study was to examine the validity of Prosocial Tendency Measure (PTM) in Iranian students. This scale measures 6 types of prosocial tendencies including altruistic, anonymous, dire, emotional, compliant and public prosocial tendencies (Carlo and Randal, 2002). We used 182 undergraduate students in order to study the validity of the scale by confirmatory factor analysis method, internal consistency and relationships to other measures. Also 34 students were used for test retest reliability procedure. We studied the relationships of the measure s’ subscales to additional items, empathy, religiosity and social desirability. The results showed that this measure has acceptable fitness on Carlo and Randall (2002) model. Also the subscales of this measure had acceptable internal consistency and reliability after test retest. The subscales of compliant, emotional, anonymous and altruism had positive and significant relationships with empathy but there was negative relationship between public to empathy. The subscales of compliant and anonymous had positive and significant relationships with religiosity. Social desirability had negative and significant correlation to public. But social desirability had also positive and significant relationships to anonymous and altruism. There was not any significant difference between girls and boys in any of six PTM subscales.
STUDIES ON GENETIC VARIABILITY OF TASAR ECORACES AS REVEALED THROUGH MICROSATELLITE MARKERS

The tropical tasar silkworm Antheraea mylitta D. , a wild sericigenous and polyphagous insect. is cultivated in the dense, humid, tropical forests of eastern, central and southern India. Its primary food plants are Terminalia Arjuna, Terminalia tomentosa and Shorea robusta. The present studies of genetic relations is based on phylogeny of tasar ecoraces using SSR markers, which further provides molecular evidence of the fact that climatic factors, the changes at DNA level and its wide range of distribution in varied geographic conditions would lead to genetic divergence ultimately leading to the formation of new ecorace.
A Survey on Secure Data Sharing Methods in Public Cloud Computing

— The objective of the study is to conduct a survey about secure data sharing in public clouds. Due to the high popularity of cloud computing, many organizations use the public cloud for secure data sharing and large-scale data storage. But the privacy and security of sharing data have become two major issues. In public cloud, the user transfers his data to public cloud server and PCS is responsible for the overall control of the data. The semi trusted nature of PCS is another important problem. Thus we take these issues into account and collect different methods that give better solution to these problems.
Using Topic Hierarchies with Matrix Factorization Techniques to Improve Context-Aware Recommendation Systems

— Recommender system can efficiently alleviate the information overload problem, but it has been trapped in the recommendation accuracy. Recommender systems are designed to assist individuals to identify items of interest in a set of options. A context-aware recommender system makes recommendations by incorporating available contextual information into the recommendation process. One of the major challenges in context-aware recommender systems research is the lack of automatic methods to obtain contextual information for these systems. This paper proposed the use of topic hierarchies with matrix factorization techniques. Three different types of topic hierarchies are constructed by using the LUPI-based Incremental Hierarchical Clustering method: a topic hierarchy using only a traditional bag-of-words, a second topic hierarchy using a bag-of-words of named entities and a third topic hierarchy using both information. More factors including contextual information, user ratings and item feature are all taken into consideration. By using topic hierarchies better recommendations can be provided and improve the accuracy.
Investigation of Reverse Phase HPLC Method for Determination of Nimodipinein Pharmaceutical Dosage Form using Nanoparticles Modified with Cetyltrimethylammonium Bromide

A rapid and sensitive high-performance liquid chromatogaphic method was developed for the estimation of nimodipine in pharmaceutical dosage forms. Nimodipine was chromatographed on a reverse phase C18 column in a mobile phase consisting of acetonitrile and water in the ratio of 58:42 (v/v). The mobile phase was pumped at a flow rate of 1 ml/min and the eluents were monitored at 241 nm. A pre-concentration of nimodipine was applied using Nanoparticles Modified with Cetyltrimethylammonium Bromide. The calibration curve was linear in the range of 0.1-40 μg/mL. The intra and inter-day variation was found to be less than 1% showing high precision of the assay method. The mean recovery of the from the solution containing 10 μg/mL was 99.95 ± 0.86% indicating high accuracy of the proposed HPLC method. Due to its simplicity, rapidness, high precision and the proposed HPLC method may be used for determining nimodipine in bulk drug samples and pharmaceutical dosage forms.
Study on Hand Gesture Recognition

— To access any information user has to repeat keyboard and mouse actions which results in waste of time and it is inconvenient to use. So hand gesture recognition has received attention in the recent years. Using hand gesture we can easily interact with any device robustly. In this paper we have surveyed methods of hand gesture recognition like coloured glove, vision based depth camera etc. This paper focuses advantages and disadvantages of all these methods
Image Retrieval System Past and Future, A Survey

: Image retrieval is a one of the most promising domain of digital image processing. From last 2 decades image retrieval is the most popular area for researchers. They present millions of papers based on image retrieval techniques. This paper presents a comprehensive survey of some techniques that are used in image retrieval systems especially content-based image retrieval, text based image retrieval system and medical image retrieval systems. These techniques are Genetic Algorithm, Greedy Approach, Particle Swarm Optimization, neutral networks etc. Paper also Furthermore, based on the state-of-the-art technology available now this paper puts a light on some issues facing in image retrievals systems and future promising research directio ns are suggested.
ENHANCED V-BLAST FOR MIMO-OFDM SYSTEMS WITH NOVEL IDD

Orthogonal frequency division multiplexing (OFDM) systems divide the entire channel into many narrow parallel sub-channels, increasing the symbol duration and reducing the inter-symbol interference (ISI) caused by the multipath. Multiple-input multiple-output (MIMO) systems make use of multiple antennas at the transmitter and receiver can exhibit a substantially higher spectral efficiency and improve the system capacity significantly. Therefore, the combination of MIMO and OFDM, which is called MIMO-OFDM, has emerged as a major candidate for the fourth-generation communications. First, in this paper, we introduce an enhanced vertical Bell Labs layered space–time (V-BLAST) receiver which takes the decision errors into account. Second, we propose a novel iterative detection and decoding (IDD) scheme for coded layered space–time architectures in MIMO-OFDM systems. For the iterative process, a low complexity demapper is developed by making use of both non-linear interference cancellation and linear minimum mean-square error filtering and a low complexity algorithm for LLR calculation also developed. Simulation results demonstrate that the proposed method achieves the optimal turbo-MIMO approach, while providing considerable reduction in latency and also considerable reduction in computational complexity
Validation of Predictive Construction Workers Safety Behavior Model

— Safety Manager’s leadership style has a great impact on workers’ safety behaviors on construction sites. Effective leadership styles have been associated with benefits such as increased operational efficiency; reduction in insurance cost and workers retention and satisfaction. The aim of this paper is to validate the proposed construction workers safety behavior model. Model validation is associated with the process of assessing the ability of the model to do what it set out to achieve. The validation process tries to ensure that the model represents the characteristics of the general population and not peculiar to the samples used in its estimation. Certain criteria were set for the study in order to validate the predictive model obtained from the analysis conducted with the SPSS 20. Ten (10) construction safety practitioners (experts) were identified within the study area. External validation approach was adopted for the study. This type of approach where experts verify the tentative results of the research generate more confidence in the validity of the findings. The majority of the responded were in favor of the model indicating that the model is a positive contribution to the subject of construction workers safety behavior. It can be concluded from the opinion of the experts that the model is of an acceptable standard and can be a viable tool for decision making. The clients, contractors and the stakeholders can used the model to make appropriate decision, take suitable measures and devote the necessary resources required for accident prevention. Also the contractors seeking to improve safety and health at their workplace could use this model to make informed and objective decision towards accident prevention on construction site.
Incremental-Parallel Data Stream Classification in Apache Spark Environment

With notorious domain of big data age, the challenging task on data stream classification is high velocity conceptual infinite stream and perspective statistical properties of data which differs periodically. In this paper, we propose an Incremental Parallel Random Forest (IPRF) algorithm for data streams in spark cloud computing environment. The algorithm incrementally estimates the accuracy for classifying the data streams, which priors to parallelization process in order to reduce the training time and prediction process using random sampling and filtering approach, that improves the dynamic-data allocation and task-scheduling mechanism in a cloud environment. From the perspective of dynamic-data allocation, dynamically changes the data in a data stream environment, to reduce the communication cost, volume data using vertically data-partitioning, data-multiplexing method. From the perspective of task scheduling, an incremental-parallel technique is carried out in the training process of Random Forest and a task directed acyclic graph depends upon resilient distributed data objects as static, redundant, and least data object appending to re-organize the mapping relationship between successor task and slaves. The details and the results of evaluating the proposed mechanism using benchmark datasets are presented in this paper.
Effect of Packagings on shelf life and post- harvest quality of fruits different cultivars of Bael [Aegle marmelos (L.) Correa] under ambient conditions

Bael [Aegle marmelos (L.) Correa] is one of the important fruits of India and having tremendous therapeutic and commercial potentialities. A wide range of variations in morphological and physicochemical was observed in bael fruit cultivars. The packaging and storage environment greatly affect the post-harvest storage life and quality of fruits. Effect of packagings on shelf life and quality attributes of bael fruits cv. NB-4, NB-5, NB-7 and NB-9 were studies. Bael fruits were harvested at physiological mature stage, wrapped in news paper, polythene bags and dipped fruits in Niprofresh wax (20%). The packed fruits and control (without packaging) were stored under ambient conditions i.e. 27-32°C and 5265% RH and analyzed for various physico-chemical parameters after every 10 days interval. News paper wrapping proved to be most effective on NB-9 then NB-4 in extending the storage life of bael fruits up to thirty days and maintained superior quality as indicated by lower physiological loss in weight (23.46%), decay loss (1.03%), total soluble solids, total sugars, acidity, and higher ascorbic acid (31.80 mg/100g) and organoleptic score.
Sentiment Analysis on Post

The tweets are nothing but the Short-text messages. They are created and shared on the large scale. The tweets are very informative in the original form. But tweets are very large in numbers that it became impossible to read each and every tweets. There can be millions of tweets. The tweets are posted randomly. To identify the tweets are related to which topic is also plays a vital role, and to detect the current event from them is also a very critical task. In this paper, the framework known as Somber is used. Sentiment analysis aim to get the underlying viewpoint of text which could be tweets. The aim of this project is to offer better sentiment text analysis strategy which recognize the polarity of text message including positive, negative, and neutral using senti wordnet. The contribution of this paper is use POS(parts of speech) tagger to examine specific prior polarity of text. An important subtask in sentiment analysis is polarity analysis but major issues is detecting corret polarity.