International Science Index

International Journal of Information and Communication Engineering

399
10011790
Interoperability Maturity Models for Consideration When Using School Management Systems in South Africa: A Scoping Review
Abstract:

The main purpose and focus of this paper are to determine the Interoperability Maturity Models to consider when using School Management Systems (SMS). The importance of this is to inform and help schools with knowing which Interoperability Maturity Model is best suited for their SMS. To address the purpose, this paper will apply a scoping review to ensure that all aspects are provided. The scoping review will include papers written from 2012-2019 and a comparison of the different types of Interoperability Maturity Models will be discussed in detail, which includes the background information, the levels of interoperability, and area for consideration in each Maturity Model. The literature was obtained from the following databases: IEEE Xplore and Scopus, the following search engines were used: Harzings, and Google Scholar. The topic of the paper was used as a search term for the literature and the term ‘Interoperability Maturity Models’ was used as a keyword. The data were analyzed in terms of the definition of Interoperability, Interoperability Maturity Models, and levels of interoperability. The results provide a table that shows the focus area of concern for each Maturity Model (based on the scoping review where only 24 papers were found to be best suited for the paper out of 740 publications initially identified in the field). This resulted in the most discussed Interoperability Maturity Model for consideration (Information Systems Interoperability Maturity Model (ISIMM) and Organizational Interoperability Maturity Model for C2 (OIM)).

Paper Detail
109
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398
10011645
Automata-Based String Analysis for Detecting Malware in Android Programs
Abstract:
We design and implement a precise model of string operations using finite state machine transformers and state transformers to approximate the values string variables can take throughout the execution of the program.We use our model to analyze Android program string variables. Our experimental results show that our string analysis is very efficient at detecting the contextual effect of string operations on the string variables. Our model proved to be very useful when it came to verifying statements about the string variables of the program.
Paper Detail
180
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397
10011664
Improving Taint Analysis of Android Applications Using Finite State Machines
Abstract:
We present a taint analysis that can automatically detect when string operations result in a string that is free of taints, where all the tainted patterns have been removed. This is an improvement on the conservative behavior of previous taint analyzers, where a string operation on a tainted string always leads to a tainted string unless the operation is manually marked as a sanitizer. The taint analysis is built on top of a string analysis that uses finite state automata to approximate the sets of values that string variables can take during the execution of a program. The proposed approach has been implemented as an extension of FlowDroid and experimental results show that the resulting taint analyzer is much more precise than the original FlowDroid.
Paper Detail
147
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396
10011544
Fast Approximate Bayesian Contextual Cold Start Learning (FAB-COST)
Abstract:
Cold-start is a notoriously difficult problem which can occur in recommendation systems, and arises when there is insufficient information to draw inferences for users or items. To address this challenge, a contextual bandit algorithm – the Fast Approximate Bayesian Contextual Cold Start Learning algorithm (FAB-COST) – is proposed, which is designed to provide improved accuracy compared to the traditionally used Laplace approximation in the logistic contextual bandit, while controlling both algorithmic complexity and computational cost. To this end, FAB-COST uses a combination of two moment projection variational methods: Expectation Propagation (EP), which performs well at the cold start, but becomes slow as the amount of data increases; and Assumed Density Filtering (ADF), which has slower growth of computational cost with data size but requires more data to obtain an acceptable level of accuracy. By switching from EP to ADF when the dataset becomes large, it is able to exploit their complementary strengths. The empirical justification for FAB-COST is presented, and systematically compared to other approaches on simulated data. In a benchmark against the Laplace approximation on real data consisting of over 670, 000 impressions from autotrader.co.uk, FAB-COST demonstrates at one point increase of over 16% in user clicks. On the basis of these results, it is argued that FAB-COST is likely to be an attractive approach to cold-start recommendation systems in a variety of contexts.
Paper Detail
138
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395
10011546
SNR Classification Using Multiple CNNs
Abstract:
Noise estimation is essential in today wireless systems for power control, adaptive modulation, interference suppression and quality of service. Deep learning (DL) has already been applied in the physical layer for modulation and signal classifications. Unacceptably low accuracy of less than 50% is found to undermine traditional application of DL classification for SNR prediction. In this paper, we use divide-and-conquer algorithm and classifier fusion method to simplify SNR classification and therefore enhances DL learning and prediction. Specifically, multiple CNNs are used for classification rather than a single CNN. Each CNN performs a binary classification of a single SNR with two labels: less than, greater than or equal. Together, multiple CNNs are combined to effectively classify over a range of SNR values from −20 ≤ SNR ≤ 32 dB.We use pre-trained CNNs to predict SNR over a wide range of joint channel parameters including multiple Doppler shifts (0, 60, 120 Hz), power-delay profiles, and signal-modulation types (QPSK,16QAM,64-QAM). The approach achieves individual SNR prediction accuracy of 92%, composite accuracy of 70% and prediction convergence one order of magnitude faster than that of traditional estimation.
Paper Detail
144
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394
10011562
Impact of Weather Conditions on Generalized Frequency Division Multiplexing over Gamma Gamma Channel
Abstract:

The technique called as Generalized frequency division multiplexing (GFDM) used in the free space optical channel can be a good option for implementation free space optical communication systems. This technique has several strengths e.g. good spectral efficiency, low peak-to-average power ratio (PAPR), adaptability and low co-channel interference. In this paper, the impact of weather conditions such as haze, rain and fog on GFDM over the gamma-gamma channel model is discussed. A Trade off between link distance and system performance under intense weather conditions is also analysed. The symbol error probability (SEP) of GFDM over the gamma-gamma turbulence channel is derived and verified with the computer simulations.

Paper Detail
172
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393
10011425
Discussing Embedded versus Central Machine Learning in Wireless Sensor Networks
Abstract:

Machine learning (ML) can be implemented in Wireless Sensor Networks (WSNs) as a central solution or distributed solution where the ML is embedded in the nodes. Embedding improves privacy and may reduce prediction delay. In addition, the number of transmissions is reduced. However, quality factors such as prediction accuracy, fault detection efficiency and coordinated control of the overall system suffer. Here, we discuss and highlight the trade-offs that should be considered when choosing between embedding and centralized ML, especially for multihop networks. In addition, we present estimations that demonstrate the energy trade-offs between embedded and centralized ML. Although the total network energy consumption is lower with central prediction, it makes the network more prone for partitioning due to the high forwarding load on the one-hop nodes. Moreover, the continuous improvements in the number of operations per joule for embedded devices will move the energy balance toward embedded prediction.

Paper Detail
283
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392
10011456
AniMoveMineR: Animal Behavior Exploratory Analysis Using Association Rules Mining
Abstract:
Environmental changes and major natural disasters are most prevalent in the world due to the damage that humanity has caused to nature and these damages directly affect the lives of animals. Thus, the study of animal behavior and their interactions with the environment can provide knowledge that guides researchers and public agencies in preservation and conservation actions. Exploratory analysis of animal movement can determine the patterns of animal behavior and with technological advances the ability of animals to be tracked and, consequently, behavioral studies have been expanded. There is a lot of research on animal movement and behavior, but we note that a proposal that combines resources and allows for exploratory analysis of animal movement and provide statistical measures on individual animal behavior and its interaction with the environment is missing. The contribution of this paper is to present the framework AniMoveMineR, a unified solution that aggregates trajectory analysis and data mining techniques to explore animal movement data and provide a first step in responding questions about the animal individual behavior and their interactions with other animals over time and space. We evaluated the framework through the use of monitored jaguar data in the city of Miranda Pantanal, Brazil, in order to verify if the use of AniMoveMineR allows to identify the interaction level between these jaguars. The results were positive and provided indications about the individual behavior of jaguars and about which jaguars have the highest or lowest correlation.
Paper Detail
230
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391
10011348
Assessment of the Administration and Services of Public Access Computers in Academic Libraries in Kaduna State, Nigeria
Abstract:

This study is posed to explore the practice of Public Access Computers (PACs) in academic libraries in Kaduna State, Nigeria. The study aimed to determine the computers and other tools available, their services and challenges of the practices. Three questions were framed to identify number of public computers and tools available, their services and problems faced during the practice. The study used qualitative research design along with semi-constructed interview and observation as tools for data collection. Descriptive analysis was employed to analyze the data. The sample size of the study comprises 52 librarian and IT staff from the seven academic institutions in Kaduna State. The findings revealed that, PACs were provided for access to the Internet, digital resources, library catalogue and training services. The study further explored that, despite the limit number of the computers, users were not allowed to enjoy many services. The study recommends that libraries in Kaduna state should provide more public computers to be able to cover the population of their users; libraries should allow users to use the computers without limitations and restrictions.

Paper Detail
192
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390
10011361
The Use of Mobile Phones by Refugees to Create Social Connectedness: A Literature Review
Abstract:

Mobile phones are one of the main tools for promoting the wellbeing of people and supporting the integration of communities on the margins such as refugees. Information and Communication Technology has the potential to contribute towards reducing isolation, loneliness, and to assist in improving interpersonal relations and fostering acculturation processes. Therefore, the use of mobile phones by refugees might contribute to their social connectedness. This paper aims to demonstrate how existing literature has shown how the use of mobile phones by refugees should engender social connectedness amongst the refugees. Data for the study are drawn from existing literature; we searched a number of electronic databases for papers published between 2010 and 2019. The main findings of the study relate to the use of mobile phones by refugees to (i) create a sense of belonging, (ii) maintain relationships, and (iii) advance the acculturation process. The analysis highlighted a gap in the research over refugees and social connectedness. In particular, further studies should consider evaluating the differences between those who have a refugee permit, those who are waiting for the refugee permit, and those whose request was denied.

Paper Detail
151
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389
10011321
Digital Transformation as the Subject of the Knowledge Model of the Discursive Space
Authors:
Abstract:

Due to the development of the current civilization, one must create suitable models of its pervasive massive phenomena. Such a phenomenon is the digital transformation, which has a substantial number of disciplined, methodical interpretations forming the diversified reflection. This reflection could be understood pragmatically as the current temporal, a local differential state of knowledge. The model of the discursive space is proposed as a model for the analysis and description of this knowledge. Discursive space is understood as an autonomous multidimensional space where separate discourses traverse specific trajectories of what can be presented in multidimensional parallel coordinate system. Discursive space built on the world of facts preserves the complex character of that world. Digital transformation as a discursive space has a relativistic character that means that at the same time, it is created by the dynamic discourses and these discourses are molded by the shape of this space.

Paper Detail
197
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388
10011322
DocPro: A Framework for Processing Semantic and Layout Information in Business Documents
Abstract:

With the recent advance of the deep neural network, we observe new applications of NLP (natural language processing) and CV (computer vision) powered by deep neural networks for processing business documents. However, creating a real-world document processing system needs to integrate several NLP and CV tasks, rather than treating them separately. There is a need to have a unified approach for processing documents containing textual and graphical elements with rich formats, diverse layout arrangement, and distinct semantics. In this paper, a framework that fulfills this unified approach is presented. The framework includes a representation model definition for holding the information generated by various tasks and specifications defining the coordination between these tasks. The framework is a blueprint for building a system that can process documents with rich formats, styles, and multiple types of elements. The flexible and lightweight design of the framework can help build a system for diverse business scenarios, such as contract monitoring and reviewing.

Paper Detail
253
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387
10011193
A Design of Beam-Steerable Antenna Array for Use in Future Mobile Handsets
Abstract:

A design of beam-steerable antenna array for the future cellular communication (5G) is presented. The proposed design contains eight elements of compact end-fire antennas arranged on the top edge of smartphone printed circuit board (PCB). Configuration of the antenna element consists of the conductive patterns on the top and bottom copper foil layers and a substrate layer with a via-hole. The simulated results including input-impedance and also fundamental radiation properties have been presented and discussed. The impedance bandwidth (S11 ≤ -10 dB) of the antenna spans from 17.5 to 21 GHz (more than 3 GHz bandwidth) with a resonance at 19 GHz. The antenna exhibits end-fire (directional) radiation beams with wide-angle scanning property and could be used for the future 5G beam-forming. Furthermore, the characteristics of the array design in the vicinity of user-hand are studied.

Paper Detail
293
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386
10011199
Dual-Polarized Multi-Antenna System for Massive MIMO Cellular Communications
Abstract:

In this paper, a multiple-input/multiple-output (MIMO) antenna design with polarization and radiation pattern diversity is presented for future smartphones. The configuration of the design consists of four double-fed circular-ring antenna elements located at different edges of the printed circuit board (PCB) with an FR-4 substrate and overall dimension of 75×150 mm2. The antenna elements are fed by 50-Ohm microstrip-lines and provide polarization and radiation pattern diversity function due to the orthogonal placement of their feed lines. A good impedance bandwidth (S11 ≤ -10 dB) of 3.4-3.8 GHz has been obtained for the smartphone antenna array. However, for S11 ≤ -6 dB, this value is 3.25-3.95 GHz. More than 3 dB realized gain and 80% total efficiency are achieved for the single-element radiator. The presented design not only provides the required radiation coverage but also generates the polarization diversity characteristic.

Paper Detail
370
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385
10011179
Remote Monitoring and Control System of Potentiostat Based on the Internet of Things
Abstract:

Constant potometer is an important component of pipeline anti-corrosion systems in the chemical industry. Based on Internet of Things (IoT) technology, Programmable Logic Controller (PLC) technology and database technology, this paper developed a set of a constant potometer remote monitoring management system. The remote monitoring and remote adjustment of the working status of the constant potometer are realized. The system has real-time data display, historical data query, alarm push management, user permission management, and supporting Web access and mobile client application (APP) access. The actual engineering project test results show the stability of the system, which can be widely used in cathodic protection systems.

Paper Detail
316
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384
10011069
60 GHz Multi-Sector Antenna Array with Switchable Radiation-Beams for Small Cell 5G Networks
Abstract:

A compact design of multi-sector patch antenna array for 60 GHz applications is presented and discussed in details. The proposed design combines five 1x8 linear patch antenna arrays, referred to as sectors, in a multi-sector configuration. The coaxial-fed radiation elements of the multi-sector array are designed on 0.2 mm Rogers RT5880 dielectrics. The array operates in the frequency range of 58-62 GHz and provides switchable directional/omnidirectional radiation beams with high gain and high directivity characteristics. The designed multi-sector array exhibits good performances and could be used in the fifth generation (5G) cellular networks.

Paper Detail
419
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383
10011001
The Current Status of Middle Class Internet Use in China: An Analysis Based on the Chinese General Social Survey 2015 Data and Semi-Structured Investigation
Abstract:

In today's China, the well-educated middle class, with stable jobs and above-average income, are the driving force behind its Internet society. Through the analysis of data from the 2015 Chinese General Social Survey and 50 interviewees, this study investigates the current situation of this group’s specific internet usage. The findings of this study demonstrate that daily life among the members of this socioeconomic group is closely tied to the Internet. For Chinese middle class, the Internet is used to socialize and entertain self and others. It is also used to search for and share information as well as to build their identities. The empirical results of this study will provide a reference, supported by factual data, for enterprises seeking to target the Chinese middle class through online marketing efforts.

Paper Detail
306
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382
10011009
SVID: Structured Vulnerability Intelligence for Building Deliberated Vulnerable Environment
Abstract:

The diversity and complexity of modern IT systems make it almost impossible for internal teams to find vulnerabilities in all software before the software is officially released. The emergence of threat intelligence and vulnerability reporting policy has greatly reduced the burden on software vendors and organizations to find vulnerabilities. However, to prove the existence of the reported vulnerability, it is necessary but difficult for security incident response team to build a deliberated vulnerable environment from the vulnerability report with limited and incomplete information. This paper presents a structured, standardized, machine-oriented vulnerability intelligence format, that can be used to automate the orchestration of Deliberated Vulnerable Environment (DVE). This paper highlights the important role of software configuration and proof of vulnerable specifications in vulnerability intelligence, and proposes a triad model, which is called DIR (Dependency Configuration, Installation Configuration, Runtime Configuration), to define software configuration. Finally, this paper has also implemented a prototype system to demonstrate that the orchestration of DVE can be automated with the intelligence.

Paper Detail
266
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381
10011016
Motivational Antecedents that Influenced a Higher Education Institution in the Philippines to Adopt Enterprise Architecture
Abstract:

Technology is a recent prodigy in people’s everyday life that has taken off. It infiltrated almost every aspect of one’s lives, changing how people work, how people learn and how people perceive things. Academic Institutions, just like other organizations, have deeply modified its strategies to integrate technology into the institutional vision and corporate strategy that has never been greater. Information and Communications Technology (ICT) continues to be recognized as a major factor in organizations realizing its aims and objectives. Consequently, ICT has an important role in the mobilization of an academic institution’s strategy to support the delivery of operational, strategic or transformational objectives. This ICT strategy should align the institution with the radical changes of the ICT world through the use of Enterprise Architecture (EA). Hence, EA’s objective is to optimize the islands of legacy processes to be integrated that is receptive to change and supportive of the delivery of the strategy. In this paper, the focus is to explore the motivational antecedents during the adoption of EA in a Higher Education Institution in the Philippines for its ICT strategic plan. The seven antecedents (viewpoint, stakeholders, human traits, vision, revolutionary innovation, techniques and change components) provide understanding into EA adoption and the antecedents that influences the process of EA adoption.

Paper Detail
465
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380
10010827
Analysis of Cooperative Hybrid ARQ with Adaptive Modulation and Coding on a Correlated Fading Channel Environment
Authors:
Abstract:
In this study, a cross-layer design which combines adaptive modulation and coding (AMC) and hybrid automatic repeat request (HARQ) techniques for a cooperative wireless network is investigated analytically. Previous analyses of such systems in the literature are confined to the case where the fading channel is independent at each retransmission, which can be unrealistic unless the channel is varying very fast. On the other hand, temporal channel correlation can have a significant impact on the performance of HARQ systems. In this study, utilizing a Markov channel model which accounts for the temporal correlation, the performance of non-cooperative and cooperative networks are investigated in terms of packet loss rate and throughput metrics for Chase combining HARQ strategy.
Paper Detail
226
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379
10010615
Optimizing the Probabilistic Neural Network Training Algorithm for Multi-Class Identification
Abstract:

In this work, a training algorithm for probabilistic neural networks (PNN) is presented. The algorithm addresses one of the major drawbacks of PNN, which is the size of the hidden layer in the network. By using a cross-validation training algorithm, the number of hidden neurons is shrunk to a smaller number consisting of the most representative samples of the training set. This is done without affecting the overall architecture of the network. Performance of the network is compared against performance of standard PNN for different databases from the UCI database repository. Results show an important gain in network size and performance.

Paper Detail
625
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378
10010639
Make Up Flash: Web Application for the Improvement of Physical Appearance in Images Based on Recognition Methods
Abstract:

This paper presents a web application for the improvement of images through recognition. The web application is based on the analysis of picture-based recognition methods that allow an improvement on the physical appearance of people posting in social networks. The basis relies on the study of tools that can correct or improve some features of the face, with the help of a wide collection of user images taken as reference to build a facial profile. Automatic facial profiling can be achieved with a deeper study of the Object Detection Library. It was possible to improve the initial images with the help of MATLAB and its filtering functions. The user can have a direct interaction with the program and manually adjust his preferences.

Paper Detail
265
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377
10010440
Students’ Perceptions of Communication Design in Media: Case Study of Portuguese and Spanish Communication Students
Abstract:

The proliferation of mobile devices in society enables the media to disseminate information and knowledge more rapidly. Higher education students access these contents and share them with each other, in the most diverse platforms, allowing the ubiquity in access to information. This article presents the results and respective quantitative analysis of a survey applied to communication students of two higher education institutions: one in Portugal and another in Spain. The results show that, in this sample, higher education students regularly access news content believing traditional news sources to be more credible. Regarding online sources, it was verified that the access was mostly to free news contents. This study intends to promote the knowledge about the changes that occur in the relationship of higher education students with the media, characterizing how news consumption is processed by these students, considering the resulting effects of the digital media evolution. It is intended to present not only the news sources they use, but also to know some of their habits and relationship with the news media.

Paper Detail
432
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376
10010351
Context Aware Anomaly Behavior Analysis for Smart Home Systems
Abstract:

The Internet of Things (IoT) will lead to the development of advanced Smart Home services that are pervasive, cost-effective, and can be accessed by home occupants from anywhere and at any time. However, advanced smart home applications will introduce grand security challenges due to the increase in the attack surface. Current approaches do not handle cybersecurity from a holistic point of view; hence, a systematic cybersecurity mechanism needs to be adopted when designing smart home applications. In this paper, we present a generic intrusion detection methodology to detect and mitigate the anomaly behaviors happened in Smart Home Systems (SHS). By utilizing our Smart Home Context Data Structure, the heterogeneous information and services acquired from SHS are mapped in context attributes which can describe the context of smart home operation precisely and accurately. Runtime models for describing usage patterns of home assets are developed based on characterization functions. A threat-aware action management methodology, used to efficiently mitigate anomaly behaviors, is proposed at the end. Our preliminary experimental results show that our methodology can be used to detect and mitigate known and unknown threats, as well as to protect SHS premises and services.

Paper Detail
709
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375
10010352
The Paralinguistic Function of Emojis in Twitter Communication
Abstract:

In response to the dearth of information about emoji use for different purposes in different settings, this paper investigates the paralinguistic function of emojis within Twitter communication in the United States. To conduct this investigation, the Twitter feeds from 16 population centers spread throughout the United States were collected from the Twitter public API. One hundred tweets were collected from each population center, totaling to 1,600 tweets. Tweets containing emojis were next extracted using the “emot” Python package; these were then analyzed via the IBM Watson API Natural Language Understanding module to identify the topics discussed. A manual content analysis was then conducted to ascertain the paralinguistic and emotional features of the emojis used in these tweets. We present our characterization of emoji usage in Twitter and discuss implications for the design of Twitter and other text-based communication tools.

Paper Detail
1018
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374
10010374
Specific Emitter Identification Based on Refined Composite Multiscale Dispersion Entropy
Abstract:
The wireless communication network is developing rapidly, thus the wireless security becomes more and more important. Specific emitter identification (SEI) is an vital part of wireless communication security as a technique to identify the unique transmitters. In this paper, a SEI method based on multiscale dispersion entropy (MDE) and refined composite multiscale dispersion entropy (RCMDE) is proposed. The algorithms of MDE and RCMDE are used to extract features for identification of five wireless devices and cross-validation support vector machine (CV-SVM) is used as the classifier. The experimental results show that the total identification accuracy is 99.3%, even at low signal-to-noise ratio(SNR) of 5dB, which proves that MDE and RCMDE can describe the communication signal series well. In addition, compared with other methods, the proposed method is effective and provides better accuracy and stability for SEI.
Paper Detail
289
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373
10010399
Labview-Based System for Fiber Links Events Detection
Abstract:

With the rapid development of modern communication, diagnosing the fiber-optic quality and faults in real-time is widely focused. In this paper, a Labview-based system is proposed for fiber-optic faults detection. The wavelet threshold denoising method combined with Empirical Mode Decomposition (EMD) is applied to denoise the optical time domain reflectometer (OTDR) signal. Then the method based on Gabor representation is used to detect events. Experimental measurements show that signal to noise ratio (SNR) of the OTDR signal is improved by 1.34dB on average, compared with using the wavelet threshold denosing method. The proposed system has a high score in event detection capability and accuracy. The maximum detectable fiber length of the proposed Labview-based system can be 65km.

Paper Detail
355
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372
10009823
Monitoring Co-Creation: A Survey of Lithuanian Urban Communities
Abstract:

In this paper, we conduct a systematic survey of urban communities in Lithuania to evaluate their potential to co-create collective intelligence or “civic intelligence” applying Digital Co-creation Index methodology that includes different socio-technological indicators. Civic intelligence is a form of collective intelligence that refers to the group’s capacity to perceive societal problems and to address them effectively. The research focuses on evaluation of diverse organizational designs that increase efficient collective performance. The current scientific project advanced the state of the art by evaluating the basic preconditions in the urban communities through which the collective intelligence is being co-created under the systemic manner. The research subject is the “bottom up” digital enabled urban platforms, initiated by Lithuanian public organizations, civic movements or business entities. The web-based monitoring results obtained by applying a social indices calculation methodology and Pearson correlation analysis provided the information about the potential and limits of the urban communities and what possible changes need to be implemented to overcome the limitations.

Paper Detail
402
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371
10009435
Lexical Based Method for Opinion Detection on Tripadvisor Collection
Abstract:
The massive development of online social networks allows users to post and share their opinions on various topics. With this huge volume of opinion, it is interesting to extract and interpret these information for different domains, e.g., product and service benchmarking, politic, system of recommendation. This is why opinion detection is one of the most important research tasks. It consists on differentiating between opinion data and factual data. The difficulty of this task is to determine an approach which returns opinionated document. Generally, there are two approaches used for opinion detection i.e. Lexical based approaches and Machine Learning based approaches. In Lexical based approaches, a dictionary of sentimental words is used, words are associated with weights. The opinion score of document is derived by the occurrence of words from this dictionary. In Machine learning approaches, usually a classifier is trained using a set of annotated document containing sentiment, and features such as n-grams of words, part-of-speech tags, and logical forms. Majority of these works are based on documents text to determine opinion score but dont take into account if these texts are really correct. Thus, it is interesting to exploit other information to improve opinion detection. In our work, we will develop a new way to consider the opinion score. We introduce the notion of trust score. We determine opinionated documents but also if these opinions are really trustable information in relation with topics. For that we use lexical SentiWordNet to calculate opinion and trust scores, we compute different features about users like (numbers of their comments, numbers of their useful comments, Average useful review). After that, we combine opinion score and trust score to obtain a final score. We applied our method to detect trust opinions in TRIPADVISOR collection. Our experimental results report that the combination between opinion score and trust score improves opinion detection.
Paper Detail
381
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370
10009052
Optimized Approach for Secure Data Sharing in Distributed Database
Abstract:

In the current age of technology, information is the most precious asset of a company. Today, companies have a large amount of data. As the data become larger, access to data for some particular information is becoming slower day by day. Faster data processing to shape it in the form of information is the biggest issue. The major problems in distributed databases are the efficiency of data distribution and response time of data distribution. The security of data distribution is also a big issue. For these problems, we proposed a strategy that can maximize the efficiency of data distribution and also increase its response time. This technique gives better results for secure data distribution from multiple heterogeneous sources. The newly proposed technique facilitates the companies for secure data sharing efficiently and quickly.

Paper Detail
435
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