bluuebunny/crossref_metadata_2025_split huggingface dataset:
Définition ontologique du terme
Authors: Roche Christophe , Papadopoulou Maria 
Published: April 2021

Par « définition ontologique du terme », nous entendons une définition qui repose sur une représentation explicite du concept dénoté par le terme (la norme ISO 1087-1 définit le terme comme une « désignation verbale d’un concept général dans un domaine spécifique »). Cette démarche permet non seulement de prendre en compte les dimensions linguistique et conceptuelle qui composent toute terminologie, mais aussi de concilier les définitions des termes en langue et les spécifications formelles des concepts. Le résultat est un dictionnaire terminologique structuré selon l’ontologie du domaine (au sens de l’Ingénierie des Connaissances). Une telle approche, qui a un coût non négligeable, celui de la construction de l’ontologie, se justifie lorsqu’il existe un « flou » terminologique tel qu’il nuit à la communication et au partage des connaissances dans un domaine de spécialité. C’est le cas de la terminologie des vêtements de la Grèce antique.
The Implementation of Question Answer System Using Deep Learning
Authors: Et. al. Vaishali Fulmal, 
Published: April 2021

Question-answer systems are referred to as advanced systems that can be used to provide answers to the questions which are asked by the user. The typical problem in natural language processing is automatic question-answering. The question-answering is aiming at designing systems that can automatically answer a question, in the same way as a human can find answers to questions. Community question answering (CQA) services are becoming popular over the past few years. It allows the members of the community to post as well as answer the questions. It helps users to get information from a comprehensive set of questions that are well answered. In the proposed system, a deep learning-based model is used for the automatic answering of the user’s questions. First, the questions from the dataset are embedded. The deep neural network is trained to find the similarity between questions. The best answer for each question is found as the one with the highest similarity score. The purpose of the proposed system is to design a model that helps to get the answer of a question automatically. The proposed system uses a hierarchical clustering algorithm for clustering the questions.
A Modern Approach For Finding Minimization Cost In Transportation Problem
Authors: Et. al. G. Padma karthiyayini, 
Published: April 2021

In this paper, the proposed technique is new and simple for obtaining an initial basic feasible solution (IBFS) of a transportation problem (TP). The objective of this paper is to find how to minimize the transportation cost (TC) by using a new approach. The method is illustrated with some numerical examples using algorithm.
Role of Clean Technology in Sustainable Manufacturing
Authors: Agrawal Manoj Kumar 
Published: April 2021

Sustainable manufacturing is the backbone for the development of standard of living of the country along with its industrial growth. It is a process for meeting development needs while maintaining the stability, integrity and beauty of natural biotic systems such that societal consumption of natural resources is incommensurate with the rate which the nature can replenish itself. It can be more cost and time efficient, especially for small scale production and customized products. In order to have complete and efficient structure of sustainable manufacture it must produce green products by using clean technologies. The manufacturing industries which can integrate the aspect of clean technologies in their technical and financial decisions will hold an important role in winning the everlasting future race.
The main objective of this paper is to elaborate the concept and implementation of clean technologies in sustainable manufacturing which includes the process, models and impact assessment of green technologies.
The ideas presented in this paper will be quite useful for the researchers and industrialists who are interested in the field sustainable manufacturing.
On t-Neighbourhoods in Trigonometric Topological Spaces
Authors: Et. al. S. Malathi, 
Published: April 2021

In this paper we introduce a new type of neighbourhoods, namely, t-neighbourhoods in trigonometric topological spaces and study their basic properties. Also, we discuss the relationship between neighbourhoods and t-neighbourhoods. Further, we give the necessary condition for t-neighbourhoods in trigonometric topological spaces. .
National-Cultural Features of Verbal Associations
Authors: Et. al. Lutfullayeva Durdona Esanovna, 
Published: April 2021

The article discusses the role of associative thinking in the language of the external world, the associative relationship of language units, the issue of associative study of language units in Uzbek linguistics, the associative features of national-cultural units in the Uzbek language. The results of the associative experiment conducted in the Uzbek language were analyzed, and the national-cultural symbol of the language units and the reflection of this symbol in the associative units were commented on. The article also discusses issues such as the fact that the meaning of associations changes over the years, the scale of verbal associations varies among linguists, and the role of associations as a basic unit in text formation.
Question Classification for Efficient QA System
Authors: Et. al. K. P. Moholkar , 
Published: April 2021

Natural Language Processing (NLP), a subfield of Artificial Intelligence (AI), supports the machine to understand and manipulate the human languages in different sectors. Subsequently, the Question and answering scheme using Machine learning is a challengeable task. For an efficient QA system, understanding the category of a question plays a pivot role in extracting suitable answer. Computers can answer questions requiring single, verifiable answers but fail to answer subjective question demanding deeper understanding of question. Subjective questions can take different forms entailing deeper, multidimensional understanding of context. Identifying the intent of the question helps to extract expected answer from a given passage. Pretrained language models (LMs) have demonstrated excellent results on many language tasks. The paper proposes model of deep learning architecture in hierarchical pattern to learn the semantic of question and extracting appropriate answer. The proposed method converts the given context to fine grained embedding to capture semantic and positional representation, identifies user intent and employs a encoder model to concentrate on answer span. The proposed methods show a remarkable improvement over existing system
Analysis and Visualisation of Research Trends in Carbon Nano Tubes: A General Review
Authors: Kumar Raman 
Published: April 2021

Carbon nanotubes are made up of carbon atoms, with each carbon atom covalently bonded to three other carbon atoms. The bibliometric analysis had been conducted to understand the active authors, organizations, journals, and countries involved in the research domain of “Carbon Nanotubes”. All published articles related to “Carbon Nanotubes” from “Scopus”, were analyzed using the VOS viewer to develop analysis tables and visualization maps.This article had set the objective to consolidate the scientific literature regarding the “Carbon Nanotubes”and also to find out the trends related to the same.The most active journals in this research domain were Journal of Computational and Theoretical Nano Science; Journal of Physical Society of Japan and Journal of Power Sourceswith the highest publications, citations, and co-authorship links. The most active countries were India and Japan. The leading organizations were the Chinese Academy of Sciences, China, and the Islamic Azad University of Iran.The most active authors who had made valuable contributions related to Nanomaterial were Li X, Ajiki H, and Ando T.
Wireless Sensor Network routing for Life Time Maximization Using ANFIS Based Decision with Low Power Consumption
Authors: Et. al. N. Srinivas Rao, 
Published: April 2021

Wireless sensor networks (WSNs) allocate thousands of cheap micro-sensor nodes to a hundreds to more than thousands of nodes in the reserved areas. In the WSN, sensor nodes control storage resources, calculating energy of nodes, power resources of nodes, and additional resources information on a sensor network. These micro-sensor nodes are key components of the Internet of Things (). WSNs are pre-arranged in clusters or groups to protect the ability for efficient data communication. Strong routing methods are required to maintain long network life and achieve high power usage. In this work, the new energy efficient ANFIS-based routing system for WSN enabled to improve network performance. The proposed ANFIS-based routing involves a novel distributed clustering mechanism that activates the local configuration of local node energy equally across all sensors. A new technique for replacing clusters and rotating nodes with a centroid-based cluster head (CH) to distribute loads. The simulation results show that the proposed program will surpass conventional methods with 78% improvement over the lifetime of the network and 26% improvement in performance.
A Secure Methodology to Detect and Prevent Ddos and Sql Injection Attacks
Authors: Et. al. Leelavathy S, 
Published: April 2021

As most of the applications host on cloud, Security is a major concern for the data owners. The cloud environment has to be secure and protect data owner data from cloud attacks. In this project work, we study about securing firewall against client side attacks namely Denial of firewall and SQL injection attacks. Denial of firewall is nothing but overloading the firewall by bursting n number of requests through vulnerable scripts. SQL injection attack is defined as bypassing the security protocols by malicious scripts. Thus we proposed to design and develop a web application to detect and prevent denial of firewall and SQL injection attacks.
The denial of firewall attack can be performed using Java environment based servers and prevention can be performed using Digital Signature Algorithm (DSA) in which filter based approach and software puzzle based approach are performed to detect the malicious script based requests. Once the Deep Packet Inspection (DPI): filter based approach and software puzzle based approach are find satisfactory only the request would be processed. If the request is find malicious automatically the requested IP address would be blocked. Various type of SQL injection attacks namely SQL login bypass, Blind injection, SQL sleep attack, Data fetching attack are analysed and performed. The SQL injection attack can be prevented using PREPARE statements. This statements are created to make the SQL queries more efficient and render security benefits. This statement provides effective prevention mechanism against SQL injection attacks. Thus our proposed solution, provides high security against firewall attacks namely denial of firewall and SQL injection securing the data owner files and preventing compromising of firewall
Comparative study of Existing Models for Online Social Network
Authors: Attri Vikas 
Published: April 2021

Today, Online Social Networks becomes the first choice for businesses to broadcast their campaigns for branding, publicity, strategies, advertising, marketing, social influence and so many other areas. Social Network is a platform for communicating with social actors and Social Media is used by companies for broadcasting information. Online Social Network used by businesses for number of purposes but the primary concern is build new social connections that helps to target most audiences for successful campaign purposes. In OSNs sites the social objects are represented by nodes and the term edge used for connection between nodes under the graph theory. Today Social Network sites have becomes most exploded as compared to traditional sites because of impact of so many influence models over traditional models.Some of popular websites of OSN such as MySpace, Facebook, Flickr, YouTube, Google Video, Orkut, LinkedIn, Live Journal and BlogSpot have great impact on customer when targeting the sales marketing funnel for businesses. Adjacent users sometimes called engaged users tend to have more trust level as compared to random pairs users on the social media sites. Already have so much research that helps to calculate the trust factor using influence modeling. So influence models play a vital role to predict the behavior of the customer that helps to fulfill the goal of the business. The key contribution of this work is study of online social networking models.
Threshold Modeling of Basic Statistical Methods for Effective Motion Detection in Video Surveillance
Authors: Et. al. Surender Singh, 
Published: April 2021

This paper empirical investigates two basic statistical methods namely Adaptive Median and Adaptive Mean for motion detection in video surveillance for the optimization of parameters namely threshold and the refresh rate of background frame used in these methods. Experimentation shows that the optimum choice of parameters majorly affects the quality of motion detection. The performance of methods for different parameters is measured using precision, recall and f1-score. PR curves are also drawn which are based on precision and recall values to show the effect of different parameters. Test data includes six data sets from different scenarios of ‘CDNet2012’. Experimental results verify that for every method there are fixed values of parameters with slight variations which gives better result of object motion. These parameter values can be used or adapted for future experimentation on these methods with respect to each scenario.
Outsourcing Provider Selection Model in Public Sector
Authors: Et.al Glory Urekwere Orlu 
Published: April 2021

In recent times, decision outsourcing IT activities in the public sector is fast evolving in the world at large. This fact has been considered as a high level of strategic measure used in different industries particularly in the public sector where internal IT expertise is found wanting in the area of implementing IT activities to improve the performance growth of the public sector. Although outsourcing IT activities are beneficial to IT Practitioners, Decision-makers, and heads of departments, but the fact remains that choosing the right IT Provider is still a challenge that is inevitable to be avoided as they continue to make the mistake of choosing the wrong IT Provider during outsourcing provider selection. This study considered mainly the approach undertaken towards achieving the key objective of this paper which is the development of the proposed model that can support IT practitioners in outsourcing selection practices. However, this paper considered an appropriate technique that can be implemented in an uncertain and complex situation. Having reviewed thoroughly five existing techniques used in the prior researchers’ work, in-depth understanding on this justified that, fuzzy logic and its particular tools used Fuzzy Inference Systems (FIS) was found to be considered efficient and suitable for outsourcing selection practices in an uncertain and complex situation. Also, a pilot study and empirical study were conducted to ascertain the validity of the instruments (questionnaire data). The pilot study consists of 33 respondents while the empirical study consists of 133 respondents. Finally, the reliability test was carried out to determine the validity and reliability of the six influential factors selected, thereafter the proposed model was developed. The application of the developed Decision Outsourcing Selection Model (DOSM) will aid the IT Practitioners in their decision outsourcing Selection practices.
An Optimized DiscretizationApproach using k-Means Bat Algorithm
Authors: Et.al Rozlini Mohamed 
Published: April 2021

This study has proposed arelatively new discretization approach using k-means and Bat algorithm in preparation phase of classification problem. In essence, bat algorithm is applied to find the best search space solution. Eventually, the best search space solution is utilized to produce cluster centroid. The cluster centroid is very useful to determine appropriate breakpoint for discretization. The proposed discretization approach is applied in the experiments with continuous datasets. Decision Tree, k-Nearest Neighbours and Naïve Bayes classifiers are used in the experiments. The proposed discretization approach is evaluated against other existing approaches: K-Means algorithm, hybrid K-Means with Particle Swarm Optimization (PSO) and hybrid K-Means with Whale Optimization Algorithm (WOA).The classification performance is evaluated in terms of accuracy, recall, f-measure and receiver operating characteristic curve (ROC). To test the performance of the proposed algorithm, nine benchmark continuous datasets are used. The proposed algorithm show the better results compare to other approaches. The proposed algorithm performs better in discretization to solve classification problems.
Fuzzy-Based Trust Model to Evaluate Customer Trust towards Online SNSs Sellers
Authors: Et.al Ramona Ramli 
Published: April 2021

The rapid growth of Social Networking Sites (SNSs) as business platforms for individual or small sellers recognised trust as the main important role in determining the successful execution of their business operation.Current trust modelfocused in business sellers by considering website as one of the trust factors. However, these model are not applicable for SNSs environment. Based on the identified factors affecting trust in SNSs environment, this paper proposeda fuzzy-based trust model to evaluate customers‘ trust based on their perception and experiences.The evaluation model was then tested to validate its efficiency in evaluating trust level.
Towards Clasification Exploration in Spatial Crowdsourcing Domain: A Systematic Literature Review
Authors: Et.al Shirley Salimun 
Published: April 2021

Today, spatial crowdsourcing concept has been widely applied in various fields. The increasing ofmobile user and adoption of social network has catalyst spatial crowdsourcing growth. It has madevarious types of data to be easily collected and transmitted from different geographical location.However, the massive amounts of task in spatial area bring challenges for the online system tomanage especially when the task is heterogeneous, and the interactions are dynamic. Such scenario
has alerted the researchers to understand different types of information in order to make taskassignment reliable and efficient.This study investigates current state of task assignment for spatialcrowdsourcing. It basically, aims to identify several issues like trend in publication and crowdcomputing areas that studies task assignment in crowdsourcing. We used Systematic LiteratureReview (SLR) method for analysing the trends and significance of task classification for betterdynamic crowd-computing.
Test Suite Reduction and Prioritization Framework in Regression Testing
Authors: Et.al Samaila Musa 
Published: April 2021

Most of the test cases minimization reduced test cases during regression testing to generate new test suite to cover the same software requirements.The objective of this paper is to present new framework that integrate the idea of minimization and prioritization.Hence, reduction and prioritization able to reduce test cases based on the statements covered by the previous test cases to avoid redundancy.Beginning from the reduction of the test cases, followed by weighted prioritizationaccording to their usefulness.The framework was tested using sample test suite and the results obtained shown increases on the average percentage of faults detection (APFD). Future plan is to test on the larger size of test suite.
Chaotic Identification of Hourly and Daily Water Level Time Series Data in Different Areas of Elevation at Pahang River
Authors: Et.al Adib Mashuri 
Published: April 2021

This study focused on chaotic analysis of water level data in different elevations located in the highland and lowland areas. This research was conducted considering the uncertain water level caused by the river flow from highland to lowland areas. The analysis was conducted using the data collected from the four area stations along Pahang River on different time scales which were hourly and daily time series data. The resulted findings were relevant to be used by the local authorities in water resource management in these areas. Two methods were used for the analysis process which included Cao method and phase space plot. Both methods are based on phase space reconstruction that is referring to reconstruction of one dimensional data (water level data) to d-dimensional phase space in order to determine the dynamics of the system. The combination of parameters and d is required in phase space reconstruction. Results showed that (i) the combination of phase space reconstruction’s parameters gave a higher value of parameters by using hourly time scale compared to daily time scale for different elevation; (ii) different elevation gave impact on the values of phase space reconstructions’ parameters; (iii) chaotic dynamics existed using Cao method and phase space plot for different elevation and time scale. Hence, water level data with different time scale from different elevation in Pahang River can be used in the development of prediction model based on chaos approach.
Does Customer Knowledge on Islamic Financial Planning is Crucial for Islamic Credit Cards Users?
Authors: Et.al Azwan Abdullah 
Published: April 2021

Credit cards is one of the popular products of the Islamic bank. Despite being a popular product, the demand for Islamic credit cards was very low correlated to the conventional credit cards despite its unique offering features to customers. The appointment of a trusted Islamic Banking product is one of the steps to be considered in Islamic financial planning. The knowledge of Islamic financial planning plays a significant role in customer decision making regarding patronage. When making a purchase, it is important that customers completely understand products or services offered to ensure it followed the Shari’ah guidelines. Therefore, this study aims to investigate the factor of customer knowledge on Islamic financial planning that can influence customer satisfaction towards Islamic credit cards. The questionnaires were distributed by employing the convenient sampling technique and Statistical Package for Social Scientist (SPSS) is used to analyze the data that will be gathered. The result shows that the customer knowledge of Islamic financial planning has a significant relationship towards customer satisfaction of Islamic credit card.