The article deals with the common translation problems and language confusion while teaching future interpreters from Ukrainian into English and vise versa in Ukrainian higher schools. The authors claim that higher educational establishments that train future translators form a deep knowledge of the main (technical or economic) specialty and professional competence of a professional translator, which allows future professionals to work effectively, quickly navigate in a dynamic environment, improve their professional level. High-quality professional training of translators requires constant updating, expansion and improvement of knowledge of foreign languages, and a certain field of activity, which puts before universities new tasks for the training of qualified personnel in the field of translation. The authors emphasize that there are some differences which exist in phonetics, vocabulary, grammar, spelling and punctuation and are difficult to be avoided even the non-professional English interpreter. It has been stated that the acquisition of a second language theoretically cannot be a process of mastering a new system of thinking, but it is only a matter of mastering a new code, which is projected on the code of the native language. In this situation, it is important to try to immerse yourself as deeply as possible in the English-speaking environment, creating artificial conditions in each lesson, to seek to organize conditions close to reality.
This study investigates the Trump election, an unpredicted outcome along with large policy differentiation between the two political leaders, caused significant reactions on the stock returns of indices of major five countries. Event study is used as a methodology to measure the abnormal returns of indices. Indices return data are collected for sixty days before and after the election event. Results showed negative abnormal returns on the day of election as well as prior to and after the Election Day. This study helps the investor to evaluate the effect of political event on indices returns and formulate the policies in accordance with political situation. Political environment may differ from country to country and further researches can be made by selecting indices of different countries to see the effect of election. This study verifies the considerable connection between political events and stock returns.
This article presents the results of an exploratory study on the use of business intelligence (BI) tools to help to take decisions about human resources management in Portuguese organizations. The purpose of this article is to analyse the effective use of BI tools in integrating reports, analytics, dashboards and metrics, which impacts on the decision making process of Human Resources Managers. The methodology approach to this research is quantitative based on the results of a survey to 43 Human Resources Managers and Technicians and the method of data analysis was the correlation coefficient and regression analysis performed by IBM SPSS software and also qualitative using focus group to identify the impacts of business intelligence on the human resources strategies from Portuguese companies. The findings of this study are that: Business Intelligence is positively associated with HRM decision taking and Business Intelligence will significantly predict HRM decision taking. The research also examines the process of the information gathered with BI tools from the Human Resources Information System on the decisions of the Human Resources Managers and that impacts the performance of the organizations. The study also gives indications about the practices and gaps, both in terms of human resources management and in processes related to business intelligence (BI) tools. It points out the different factors that must work together to facilitate effective decision-making. The article is structure as follows: literature review in relation to the use of the business intelligence concept and tools and the link between BI and Human Resources Management, methodology and the main findings and conclusions.
This study was undertaken to determine the some chemical parameters (moisture, fructose/glucose ratio, hydroxymethylfurfural value, volatile compounds) of honey samples obtained from Kars. 100 honey samples from eight districts of Kars were evaluated. The chemical characterizations were as follows: average moisture (15,5±1,11%), HMF (0,77 ppm ±0.9 ppm), F/G ratio (1,02±0,16). As a result of the gas chromatography–mass spectrometry (GC–MS) analyses, some volatile compounds in honey samples such as alcohols (1,15±1,84%), aldehydes (4,66±6,33%), aliphatic acids and their esters (1,86±4,5%), hydrocarbons (2,32±3,1%), flavonoids (4,34±1,63%), carboxylic acids and their esters (0,24±0,96%), ketones (6,05±6,35%), sugars (15,79±10,74%),vitamins (0,59±2,66%) were determined and quantitative variations of chemical components in different samples were reported.
Wireless Sensor Networks (WSNs) is composed of a huge number of sensor nodes that are densely deployed in a target environment. One of the major fundamental challenges in WSNs is the Topology Control (TC). TC algorithms try to reduction the average of nodes transition radius without reduction of the network connectivity. This paper has proposed a metaheuristic algorithm for TC based on the Vortex Search (VS) algorithm for WSNs termed VSTC. VSTC algorithm dynamically adjusts transition radius of nodes, so the proper transition radius can be determined using VS algorithm, so the position of each node is to calculate and represented in a binary format to enhance the coverage area and reduce the number of active nodes. Furthermore, the proposed algorithm is under a less average number of neighbors and the energy consumption compared with the present algorithms. In addition, the proposed algorithm is simulated with the A1 topology algorithm, A3 topology algorithm, and PSOTCS algorithm, the experimental results have been provided the highest in terms of the high residual energy by 34% and the number of active nodes was decreased by 18%.
In this paper, we propose hardware architectures for a modular reduction operation used in lattice-based cryptography. We modify the modular reduction algorithms for a set of generalized Mersenne primes. With the proposed architectures, we improve the modular reduction complexity. The proposed design speeds up the modular reduction almost $20\\%$ on the FPGA. To the best of our knowledge, the proposed design has the lowest arithmetic complexity.
Starches have a wide range of uses and their consumption has increased over the years, resulting in a growth in the agro-industries that produce them. Cassava is a very important plant for agri-business and one of the main products obtained from its roots is starch. Although cassava can be harvested throughout the year, its quality varies greatly through the seasons; this is because it is influenced by soil and climatic factors, as well as the genetic characteristics of the species. These influences result in seasonal oscillations in root classification based on the starch content available at the time of product delivery. Faced with this problem, the objective of this study was the collection and evaluation of documentary data for 3 years of product quality samples. This was done in order to observe the situation and propose tools that can minimize problems resulting from the quality of raw material received by starch producers throughout the year. It was observed that in the winter period there was an increase in root starch content, despite the differences between the months not being statistically significantly, they are financially representative of this agro-industry sector. At the end of the study, a proposal for a methodology for calculating payment per gram of starch is presented in order to minimize the problem.