New Synonyms Extraction Model Based on a Novel Terms Weighting Scheme

The traditional statistical approach in synonyms extraction is time-consuming. It is necessary to develop a new method to improve the efficiency and accuracy. This research presents a new method in synonyms extraction called Noun Based Distinctive Verbs (NBDV) that replaces the traditional tf-idf weighting scheme with a new weighting scheme called the Orbit Weighing Scheme (OWS). The OWS links the nouns to their semantic space by examining the singular verbs in each context. The new method was compared with important models in the field such as the Skip-Gram, the Continuous Bag of Words, and the GloVe model. The NBDV model was manipulated over the Arabic and English languages and the results showed 47% Recall and 51% Precision in the dictionary-based evaluation and 57.5% Precision in the human experts’ evaluation. Comparing with the synonyms extraction based on tf.idf, the NBDV obtained 11% higher recall and 10% higher precision. Regarding the efficiency, we found that on average, the synonyms extraction of a single noun requires the process of 186 verbs and in 63% of the runs; the number of singular verbs was less than 200. It is concluded that the developed method is efficient and processes the single run in linear time.

Relating Smart Governance as a University Feature to Students' University Perceptions

Following the results of recent studies on the creative use of smart technologies in urban and university settings, there is a growing number of promising research areas under smart university as an umbrella term. Starting from the differentiation between six standard “smart” dimensions in the university, the paper focuses on one smart university feature in particular – it explores the level and the relation of smart governance to the attitudes towards university management, fellow students, and Perceived External Prestige (PEP) as antecedents of university affective commitment. The paper presents multivariate analysis results based on the feedback from over 400 students. Participants were first-year students from the second biggest university in Croatia. While the effect of smart governance on the positive attitude towards university management is found to be positive and significant, the effect of the perception of university management on students' university commitment is low and not significant in the given context.

The Use of E-government from the Perspective of Biggest Business Entities in Serbia

The development and use of information and communication technologies (ICTs), and in particular the Internet, have changed the way businesses operate in the last twenty years, providing a number of new opportunities for improving innovation and competitiveness. Today, modern ICT is considered to be the basis for the development of a knowledge society, in which the concept of e-government plays a special role. The main goal of this paper was to examine the perceptions of business users, in terms of perceived barriers and benefits achieved, from the use of electronic public administration services. The survey included 500 companies with the highest business income in Serbia. The data collected were analyzed using Pearson’s correlation coefficient, Mann Whitney’s test and Kruskal-Wallis test. The results of the research showed that the level of acceptance of electronic services is still lower than expected, given the volume of services offered. Also, this study pointed to the need to raise the level of awareness of businesses about e-government services, as well as the need to improve the quality of electronic services, in terms of complete digitization, alignment with enterprise requirements and regular updating of data.

ΔRLE

Lossless data compression algorithms can use statistical redundancy to represent data using a fewer number of bits in comparison to the original uncompressed data. Run-Length Encoding (RLE) is one of the simplest lossless compression algorithms in terms of understanding its principles and software implementation, as well as in terms of temporal and spatial complexity. If this principle is applied to individual bits of original uncompressed data without respecting the byte boundaries, this approach is referred to as bit-level Run-Length Encoding. Lightweight algorithm for lossless data compression proposed in this paper optimizes bit-level RLE data compression, uses special encoding of repeating data blocks, and, if necessary, combines it with delta data transformation or representation of data in its original form intending to increase compression efficiency compared to a conventional bit-level RLE approach. The advantage of the algorithm proposed in this paper is in its low time and memory consumption which are basic features of RLE, along with the simultaneous increase of compression ratio, compared to the classical bit-level RLE approach.

The Flexibility of Temporary Employment in Europe

Temporary employment is not influenced by the unemployment rate, but shows a positive relation with the social protection expenses of the companies. Poland is the country with the highest percentage of temporary workers (2013). The objective of this research is to study this flexibility, by obtaining empirical evidence in the European Union, using a quantitative research method. Research is still missing towards a better understanding of the relation between temporary employment and unemployment. The relevance of understanding of the effects of temporary employment in the European Labor Market. As future research, it is suggested that this study be replicated for the time span of 2006 to 2020. This research focuses on the geographical area studied, providing a better understanding of the relation between temporary employment and unemployment. This research is based on quantitative research using a European Union secondary database (Eurostat).

Dissimilarity Clustering Algorithm for Designing the PID-like Fuzzy Controllers

Fuzzy logic controller is one of the most prominent research fields to improve efficiency for process industries, which usually stick to the conventional proportional-integral-derivative (PID) control. The paper proposes an improved version of the three-term PID-like fuzzy logic controller by removing the necessity of having user-defined parameters in place for the algorithm to work. The resulting non-parametric three-term dissimilarity-based clustering fuzzy logic controller algorithm was shown to be very efficient and fast. The performance study was conducted by simulation on armature-controlled and field-controller DC motors, for linguistic type and Takagi-Sugeno-Kang (TSK) models. Comparison of the created algorithm with fuzzy c-means algorithm resulted in improved accuracy, increased speed and enhanced robustness, with an especially high increase for the TSK type model.

Re-examination and expanding the EUCS Model on Cloud-based ERP system

The end-user computing satisfaction model (EUCS) has been widely used in previous studies, and Enterprise Resource Planning. Therefore, Enterprise Resource Planning (ERP) System, need to be developed in accordance with cloud computing that dominate current information technology devices. This study was carried out to test the expansion of the EUCS model in a cloud-based ERP system. Therefore, the purpose of this research is to re-examine the validity and reliability of the computer application satisfaction model and its relationship with user performance in cloud-based ERP system. The overall satisfaction variable is added as a mediation between the satisfaction model and user performance. Data was collected through snowball sampling with a questionnaire distributed to the cloud-based ERP users. Additionally, data processing was conducted using the Second-order concept in structural equation modeling with the Partial Least Square approach. Since data processing using WarpPLS confirmed the validity and reliability of the model and all relationships between variables, this research contributes theoretically to the study of end-user satisfaction from information technology applications. Its final section describes the limitations and opportunities for future research.

Queueing Systems with Random Volume Customers and their Performance Characteristics

In the paper, we consider non-classical queueing systems with non-homogeneous customers. The non-homogeneity we treat in the following sense: in systems under consideration, we characterize each customer by random capacity (volume) that can have an influence on his service time. We analyze a stochastic process having the sense of the total volume of all customers present in the system at given time instant. Such analysis for different queueing systems with unlimited or limited total volume can be used in designing of nodes of computer and communication networks while determining their buffer space capacity. We discuss basic problems of the theory of these systems and their performance characteristics. We also present some examples and results for systems with random volume customers

Real-time Web Search Framework for Performing Efficient Retrieval of Data

With the rapidly growing amount of information on the internet, real-time system is one of the key strategies to cope with the information overload and to help users in finding highly relevant information. Real-time events and domain-specific information are important knowledge base references on the Web that frequently accessed by millions of users. Real-time system is a vital to product and a technique must resolve the context of challenges to be more reliable, e.g. short data life-cycles, heterogeneous user interests, strict time constraints, and context-dependent article relevance. Since real-time data have only a short time to live, real-time models have to be continuously adapted, ensuring that real-time data are always up-to-date. The focal point of this manuscript is for designing a real-time web search approach that aggregates several web search algorithms at query time to tune search results for relevancy. We learn a context-aware delegation algorithm that allows choosing the best real-time algorithms for each query request. The evaluation showed that the proposed approach outperforms the traditional models, in which it allows us to adapt the specific properties of the considered real-time resources. In the experiments, we found that it is highly relevant for most recently searched queries, consistent in its performance, and resilient to the drawbacks faced by other algorithms

Trends in the Enterprise Resource Planning Market Landscape

This article provides a brief discussion of ERPs, including how they can be defined, their component parts, and the evolution of technologies since the 1940s. The article then offers a general overview of the current ERP vendor market landscape based on academic journals and industry reports. The article’s methodological approach is a review of both academic literature and industry expert reports, which the author performed to trace trends within the landscape. Results of the analysis demonstrate that the rapidly evolving market landscape dates back at least six decades, and there are many large, longstanding ERP vendors. Yet, opportunities like cloud computing may result in niche products in existing industry players or through start-ups. Nonetheless, technologies such as blockchain are emerging. It remains to be seen how they will impact the ERP market.