500 research outputs found
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Discursive Construction of News Values in the Headline: A Case Study of BBC News Reports on Zimbabwe Crisis
No full textThe paper makes a discursive analysis of the news value construction in the headlines of new media news. The data chosen is 59 news headlines on coverage of Zimbabwe Crisis released in the apps of BBC from November 6th to November 18th 2017. The data indicates a chronological variance of the news values in the headlines. Specifically, eliteness and negativity are values constantly occurring in the headlines throughout the crisis report. The value of positivity appears only at the final stage of the news coverage. The value of timeliness emerges at the final four days of the news coverage. The value of suspense appears at the middle stage of the event. The value of proximity is employed when the detention just occurred. In terms of the linguistic realization of those news values, the study finds that the frequent use of some words contributed to the realization of news values. This study is important in that it reveals how language resources are used by newsmakers to construct news value in the headlines and how news values are realized in the context of communication
A Universal Image Forensics of Smoothing Filtering
No full textDigital image smoothing filtering operations, including the average filtering, Gaussian filtering and median filtering are always used to beautify the forged images. The detection of these smoothing operations is important in the image forensics field. In this article, the authors propose a universal detection algorithm which can simultaneously detect the average filtering, Gaussian low-pass filtering and median filtering. Firstly, the high-frequency residuals are used as being the feature extraction domain, and then the feature extraction is established on the local binary pattern (LBP) and the autoregressive model (AR). For the LBP model, the authors exploit that both of the relationships between the central pixel and its neighboring pixels and the relationships among the neighboring pixels are differentiated for the original images and smoothing filtered images. A method is further developed to reduce the high dimensionality of LBP-based features. Experimental results show that the proposed detector is effective in the smoothing forensics, and achieves better performance than the previous works, especially on the JPEG images
Clustering Approach Using Artificial Bee Colony Algorithm for Healthcare Waste Disposal Facility Location Problem
No full textIn this study, an Artificial Bee Colony (ABC) based clustering algorithm is proposed for solving continuous multiple facility location problems. Unlike the original version applied to multivariate data clustering, the ABC based clustering here solves the two-dimensional clustering. On the other hand, the multiple facility location problem the proposed clustering algorithm deals with is aimed to find site locations for healthcare wastes. After applying ABC based clustering algorithm on test data, a real-world facility location problem is solved for identifying healthcare waste disposal facility locations for Istanbul Municipality. Geographical coordinates and healthcare waste amounts of Istanbul hospitals are used to decide the locations of sterilization facilities to be established for reducing the medical waste generated. ABC based clustering is performed for different number of clusters predefined by Istanbul Metropolitan Municipality, and the total cost—the amount of healthcare waste produced by a hospital, multiplied by its distance to the sterilization facility—is calculated to decide the number of facilities to be opened. Benchmark results with four algorithms for test data and with two algorithms for real world problem reveal the superior performance of the proposed methodology
Conditioned Slicing of Interprocedural Programs
No full textProgram slicing is a technique to decompose programs depending on control flow and data flow amongst several lines of code in a program. Conditioned slicing is a generalization of static slicing and dynamic slicing. A variable, the desired program point, and a condition of interest form a slicing criterion for conditioned slicing. This paper proposes an approach to calculate conditioned slices for programs containing multiple procedures. The approach is termed Node-Marking Conditioned Slicing (NMCS) algorithm. In this approach, first and foremost step is to build an intermediate symbolization of a given program code and the next step is to develop an algorithm for finding out conditioned slices. The dependence graph, termed System Dependence Graph (SDG), is used to symbolize intermediate presentation. After constructing SDG, the NMCS algorithm chooses nodes that satisfy a given condition by the process of marking and unmarking. The algorithm also finds out conditioned slices for every variable at every statement during the process. NMCS algorithm employs a stack to save call context of a method. Few edges in SDG are labeled to identify the statement that calls a method. The proposed algorithm is implemented, and its performance is tested with several case study projects
Exploiting Routing Strategy of DTN for Message Forwarding in Information Hiding Applications
No full textDelay tolerant networks (DTNs) represent a class of intermittently connected networks. In such networks, messages are hard to track since they are transmitted by opportunistic encounters between mobile nodes. This feature makes DTN an appropriate masking channel for information hiding systems. However, the DTN often has poor communication quality, given that it suffers from frequent disruptions. In order to improve the communication quality of DTN and meet the needs of information hiding system, an efficient routing strategy is proposed in this article. On the other hand, in information hiding systems, a relatively long Time-To-Live (TTL) of messages will increase the risk of the message being exposed. To achieve a balance between delivery ratio and concealment, the sensitivity of message TTL is analyzed and a suitable value of lifetime is given. Finally, the simulation results show that the proposed algorithm can improve the effectiveness of message transmission, and the DTN can be used as masking channel to realize information hiding system
MCDM for Candidate Selection in E-Voting
No full textE-voting is one of the most important components of e-democracy and forms the basis of a democratic governance system. Voting results always lead to a broad debate in terms of candidate selection and whether the candidate elected to a position is suitable for that position. At present, the selection of qualified personnel and their appointment to responsible positions in public administration is one of the topical issues. In this article is proposed an MCDM for selection of candidates in e-voting. Criteria for the candidates' selection are determined and the relation of each candidate to other candidates is assessed using a binary matrix. Candidate rating is calculated according to all criteria. A numerical experiment is provided for candidate evaluation on the base of the selected criteria and ranked according to the importance of the criteria. The proposed model allows selecting a candidate with competencies based on the criteria set out in the e-voting process and making more effective decisions
Clustering E-Shoppers on the Basis of Shopping Values and Web Characteristics
No full textThis article describes how the exponential growth of e-commerce in India and the presence of many national and multinational e-retailers has set the trend for the major overhaul of the online industry. Most of the e-retailers have failed to differentiate themselves from the competitors. This has resulted in their failure to attract and retain the right set of consumers for their respective businesses. The present paper is aimed at identifying and developing the typology of online shoppers based on importance given by them to shopping values and web portal features. The data collected was analysed using factor, cluster and correspondence analyses. The article identifies four types of online shoppers – ‘Information Seekers,' ‘Utility Seekers,' ‘Value Seekers' and ‘Core Shoppers.' Each of these four segments display significant differences and this information can be strategically used by web retailers in targeting their markets effectively
Conceptual Model of Information Technology Management for Smart Cities: SmarTICity
No full textThis article presents a proposal of conceptual model for public administrations that allows analyzing the level of IT management capacity as an enabler of smart cities from a multidimensional and dynamic approach taking into account technological, institutional and innovation aspects. The model includes five domains (e-government strategy, Public Innovation, Data Management, IT Services and Infrastructure) that are described in terms of key domain areas, objectives and questions. The model was conceptually validated with four IT offices in Colombia and a pilot test was developed in the Atlantic department. A profile of information technology management capabilities was obtained from public data of the Ministry of ICT in Colombia
The Impact of Technostress Components on the Employees Satisfaction and Perceived Performance: The Case of Qatar
No full textThe present study investigates the effects of technostress creators and inhibitors on job satisfaction, organizational commitment and perceived performance. A research model derived from the Transaction-Based Model of Stress and Coping Theory was developed and tested using a web-based survey questionnaire. The variables considered are technostress creators, technostress inhibitors, job satisfaction, organizational commitment, and perceived performance. A Structural Equation Model using a convenience sample from Qatar population was used to test the model. The results show that organizational commitment has a significant positive effect on perceived performance. Job satisfaction has a significant positive effect on organizational commitment. Technostress creators have a significant negative effect on job satisfaction. Technostress inhibitors have a significant positive effect on job satisfaction. Implications for managers and researchers are reported
Estimating Morphological Features of Plant Growth Using Machine Vision
No full textMotivated by the fact that human visionary intelligence plays a vital role in guiding many of the agriculture practices, this article represents an effective use of machine vision technology for estimating plant morphological features to ascertain its growth and health conditions. An alternative to traditional, manual and time-consuming testing methods of plant growth parameters, a novel online plant vision system is proposed and developed on the platform of virtual instrumentation. Deployed in real time, the system acquires plant images using digital camera and communicates the raw image to host PC on Wi-Fi network. The dedicated application software with plant user interface, effective image processing and analysis algorithms, loads the plant images, extracts and estimates certain morphological features of the plant such as plant height, leaf area, detection of flower onset and fall foliage. The system was tested and validated under real-time conditions using different plants and leaves. Further, the performance of the system was statistically analysed to show promising results