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The Role of Information and Communications Technology (ICT) in Enhancing Service Sector Productivity in Palestine: An International Perspective
No full textThis article discusses the productivity of the Information and Communication Technology (ICT) sector using cross-sectional data from 793 service firms in Palestine. The authors have examined the impact of ICT growth on service sector productivity in Palestine using a set of indicators for ICT including internet usage, e-commerce, networks, websites, and use of “smart” phones. They find that using ICT (mainly Internet) in commerce (e-commerce) is one of the most important levers of labor productivity among service firms. Service firms that are less ICT-intensive are less productive than more ICT-intensive firms; moreover, the use of mobile phones for services other than send-and-receive calls, highly improves the labor productivity of service firms. Conversely, using a website and computer network does not positively affect the labor productivity. Regarding geographical differences in labor productivity, the analysis shows that firms in Jerusalem are characterized by higher productivity than firms in the West Bank, while firms in Gaza have a lower productivity compared to firms in the West Bank
Image Steganalysis in High-Dimensional Feature Spaces with Proximal Support Vector Machine
No full textThis article presents the linear Proximal Support Vector Machine (PSVM) to the image steganalysis, and further generates a very efficient method called PSVM-LSMR through implementing PSVM by the state-of-the-art optimization method Least Square Minimum-Residual (LSMR). Also, motivated by extreme learning machine (ELM), a nonlinear algorithm PSVM-ELM is proposed for the image steganalysis. It is shown by the experiments with the wide stego schemes and rich steganalysis feature sets in both the spatial and JPEG domains that the PSVM can achieve comparable performance with Fisher Linear Discriminant (FLD) and ridge regression, and its computational time is far more less than that of them on large feature sets. The PSVM-LSMR is comparable to Ridge Regression implemented by LSMR (RR-LSMR), and both of them require the least computational time among all the competitions when dealing with medium or large feature sets. The nonlinear PSVM-ELM performs comparably or even better than FLD and ridge regression for the spatial domain steganographic schemes, and its computational time is apparently less than that of them on large feature sets
Economic, Agronomic, and Environmental Benefits From the Adoption of Precision Agriculture Technologies: A Systematic Review
No full textPrecision agriculture (PA) as an integrated information- and production-based farming system is designed to delivery high-end technology solutions to increase farm production efficiency and profitability while minimizing environmental impacts on the ecosystems and the environment. PA technologies are technology innovations that incorporate recent advances in modern agriculture providing evidence for lower production costs, increased farming efficiency and reduced impacts. However, the adoption of the precision agriculture technologies has encountered difficulties such as additional application or management costs and investment on new equipment and trained employees. Some of these PA technologies were proven efficient, providing tangible benefits with lower costs and as a result they quickly gained scientific interest. To investigate further the economic, agronomic, and environmental benefits from the adoption of PA technologies a systematic review was conducted, based on the systematic search and evaluation of related eligible articles
Determinants of Digital Divide in Africa and Policy Implications
No full textThis article investigates the reasons most African households are not using the internet and discusses the policy implications for bridging the digital divide. The International Telecommunication Union (ITU) reports that at the end of 2014, only 7 percent of households in LDCs, most of whom are in Africa, had Internet access. This study analyses data from the ITU database and other sources to identify the determinants of the digital divide in Africa. Results show that peculiar challenges such as affordability and digital literacy do influence the percentage of African households who do not use the internet
A New Bi-Level Encoding and Decoding Scheme for Pixel Expansion Based Visual Cryptography
No full textMapping of image-based object textures to ASCII characters can be a new modification towards visual cryptography. Naor and Shamir proposed a new dimension of Information security as visual cryptography which is a secret sharing scheme among N number of participants with pixel expansion. Later on, many researchers extended the visual secret sharing scheme with no expansion of pixel regions in binary and color images. By stacking k shares the secret can be decoded using normal vision. In this paper the authors have proposed a modification towards visual cryptography by converting the message in the form of printable ASCII character-based numerical encoding patterns in a binary host image. The encoding of the message is represented as ASCII numeric and a texture of those numeric are arranged to form a binary host image. Then, N numbers of shares are built up but after stacking all the shares the decoding of the message is achieved by converting ASCII numeric to the secret
Participatory E-Planning With Civic Crowdfunding: Donor Background, Involvement, and Social Capital Outcomes
No full textCivic crowdfunding, or recruiting participants and collecting financial donations online for local development projects with public benefits, is an increasingly popular method for participatory e-Planning at the neighborhood scale. However, little is known about the donors' backgrounds, project involvement, or social capital outcomes. This article reports on a survey of 154 donors to ten such projects that finds that they are geographically diverse, are older and whiter than the project tracts, report some volunteering activities, and experience modest changes to social capital outcomes. The article discusses implications of the findings, such as how practitioners can ensure inclusion of diverse people and encourages participation among donors, and what future research is needed
A Multi-Objective Approach for Materialized View Selection
No full textIn today's world, business transactional data has become the critical part of all business-related decisions. For this purpose, complex analytical queries have been run on transactional data to get the relevant information, from therein, for decision making. These complex queries consume a lot of time to execute as data is spread across multiple disparate locations. Materializing views in the data warehouse can be used to speed up processing of these complex analytical queries. Materializing all possible views is infeasible due to storage space constraint and view maintenance cost. Hence, a subset of relevant views needs to be selected for materialization that reduces the response time of analytical queries. Optimal selection of subset of views is shown to be an NP-Complete problem. In this article, a non-Pareto based genetic algorithm, is proposed, that selects Top-K views for materialization from a multidimensional lattice. An experiments-based comparison of the proposed algorithm with the most fundamental view selection algorithm, HRUA, shows that the former performs comparatively better than the latter. Thus, materializing views selected by using the proposed algorithm would improve the query response time of analytical queries and thereby facilitate in decision making
PSK Method for Solving Mixed and Type-4 Intuitionistic Fuzzy Solid Transportation Problems
No full textIn this article, the author categorises the solid transportation problem (STP) under uncertain environments. He formulates the mixed and fully intuitionistic fuzzy solid transportation problems (FIFSTPs) and utilizes the triangular intuitionistic fuzzy number (TIFN) to deal with uncertainty and hesitation. The PSK (P. Senthil Kumar) method for finding an intuitionistic fuzzy optimal solution for fully intuitionistic fuzzy transportation problem (FIFTP) is extended to solve the mixed and type-4 IFSTP and the optimal objective value of mixed and type-4 IFSTP is obtained in terms of triangular intuitionistic fuzzy number (TIFN). The main advantage of this method is that the optimal solution of mixed and type-4 IFSTP is obtained without using the basic feasible solution and the method of testing optimality. Moreover, the proposed method is computationally very simple and easy to understand. Finally, the procedure for the proposed method is illustrated with the help of numerical examples which is followed by graphical representation of the finding
The Strengths, Weaknesses, Opportunities, and Threats Analysis of Big Data Analytics in Healthcare
No full textImproving the performance and reducing the cost of healthcare have been a great concern and a huge challenge for healthcare organizations and governments at every level in the US. Measures taken have included laws, regulations, policies, and initiatives that aim to improve quality of care, reduce costs of care, and increase access to care. Central to these measures is the meaningful and effective use of Big Data analytics. To reap the benefits of big data analytics and align expectations with results, researchers, practitioners, and policymakers must have a clear understanding of the unique circumstances of healthcare including the strengths, weaknesses, opportunities, and threats (SWOT) associated with the use of this emerging technology. Through descriptive SWOT analysis, this article helps healthcare stakeholders gain awareness of both success factors and issues, pitfalls, and barriers in the adoption of big data analytics in healthcare
User-Independent Detection for Freezing of Gait in Parkinson's Disease Using Random Forest Classification
No full textFreezing of gait (FOG) is a gait impairment which occurs in Parkinson's disease (PD) patients. As PD progresses, the patient is unable to perform locomotion normally. This increases the risk of falls and adversely affects the patient's quality of life. In this article, a user-independent method has been proposed to detect FOG events in PD patients. The proposed method is divided into three phases. Phase-1 extracts the statistical features from a FOG dataset. Phase-2 divides the data into two clusters based on FOG events. Phase-3 selects significant factors, using a randomized block design with replication. A Random Forest model is built using a combination of significant factors obtained from the design of experiments. The proposed method classifies FOG events with an average sensitivity up to 94.33% and specificity up to 92.77%. This model can be integrated along with non-pharmaceutical treatments to generate sensory-motor feedback at the onset of a FOG event