Search results for: Sangam text and trade

Authors: Shan Zhang, Peter Suechting

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Predicting trade patterns is critical to decision-making in public and private domains, especially in the current context of trade disputes among major economies. In the past, U.S. recycling has relied heavily on strong demand for recyclable materials overseas. However, starting in 2017, a series of new recycling policies (bans and higher inspection standards) was enacted by multiple countries that were the primary importers of recyclables from the U.S. prior to that point. As the global trade flow of recycling shifts, some new importers, mostly developing countries in South and Southeast Asia, have been overwhelmed by the sheer quantities of scrap materials they have received. As the leading exporter of recyclable materials, the U.S. now has a pressing need to build its recycling industry domestically. With respect to the global trade in scrap materials used for recycling, the interest in this paper is (1) predicting how the export of recyclable materials from the U.S. might vary over time, and (2) predicting how international trade flows for recyclables might change in the future. Focusing on three major recyclable materials with a history of trade, this study uses data-driven and machine learning (ML) algorithms---supervised (shrinkage and tree methods) and unsupervised (neural network method)---to decipher the international trade pattern of recycling. Forecasting the potential trade values of recyclables in the future could help importing countries, to which those materials will shift next, to prepare related trade policies. Such policies can assist policymakers in minimizing negative environmental externalities and in finding the optimal amount of recyclables needed by each country. Such forecasts can also help exporting countries, like the U.S understand the importance of healthy domestic recycling industry. The preliminary result suggests that gravity models---in addition to particular selection macroeconomic predictor variables--are appropriate predictors of the total export value of recyclables. With the inclusion of variables measuring aspects of the political conditions (trade tariffs and bans), predictions show that recyclable materials are shifting from more policy-restricted countries to less policy-restricted countries in international recycling trade. Those countries also tend to have high manufacturing activities as a percentage of their GDP.

Keywords: environmental economics, machine learning, recycling, international trade

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Authors: D. Zhigulskaya, V. Anisimov, A. Pikunov, K. Babanova, S. Zuev, A. Latyshkova, K. Сhernozatonskiy, A. Revazov

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Electrophysiology of information processing in reading is certainly a popular research topic. Natural reading, however, has been relatively poorly studied, despite having broad potential applications for learning and education. In the current study, we explore the relationship between text categories and spontaneous electroencephalogram (EEG) while reading. Thirty healthy volunteers (mean age 26,68 ± 1,84) participated in this study. 15 Russian-language texts were used as stimuli. The first text was used for practice and was excluded from the final analysis. The remaining 14 were opposite pairs of texts in one of 7 categories, the most important of which were: interesting/boring, fiction/non-fiction, free reading/reading with an instruction, reading a text/reading a pseudo text (consisting of strings of letters that formed meaningless words). Participants had to read the texts sequentially on an Apple iPad Pro. EEG was recorded from 12 electrodes simultaneously with eye movement data via ARKit Technology by Apple. EEG spectral amplitude was analyzed in Fz for theta-band (4-8 Hz) and in C3, C4, P3, and P4 for alpha-band (8-14 Hz) using the Friedman test. We found that reading an interesting text was accompanied by an increase in theta spectral amplitude in Fz compared to reading a boring text (3,87 µV ± 0,12 and 3,67 µV ± 0,11, respectively). When instructions are given for reading, we see less alpha activity than during free reading of the same text (3,34 µV ± 0,20 and 3,73 µV ± 0,28, respectively, for C4 as the most representative channel). The non-fiction text elicited less activity in the alpha band (C4: 3,60 µV ± 0,25) than the fiction text (C4: 3,66 µV ± 0,26). A significant difference in alpha spectral amplitude was also observed between the regular text (C4: 3,64 µV ± 0,29) and the pseudo text (C4: 3,38 µV ± 0,22). These results suggest that some brain activity we see on EEG is sensitive to particular features of the text. We propose that changes in theta and alpha bands during reading may serve as electrophysiological tools for assessing the reader’s cognitive state as well as his or her attitude to the text and the perceived information. These physiological markers have prospective practical value for developing technological solutions and biofeedback systems for reading in particular and for education in general.

Keywords: EEG, natural reading, reader's cognitive state, theta-rhythm, alpha-rhythm

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Authors: Felipe Bedoya Maya, Agustina Calatayud, Vileydy Gonzalez Mejia

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Encompassing inventory, warehousing, and transportation management, logistics is a crucial predictor of firm performance. This has been extensively proven by extant literature in business and operations management. Logistics is also a fundamental determinant of a country's ability to access international markets. Available studies in international and transport economics have shown that limited transport infrastructure and underperforming transport services can severely affect international competitiveness. However, the evidence lacks the overall impact of logistics performance-encompassing all inventory, warehousing, and transport components- on global trade. In order to fill this knowledge gap, the paper uses a gravitational trade model with 155 countries from all geographical regions between 2007 and 2018. Data on logistics performance is obtained from the World Bank's Logistics Performance Index (LPI). First, the relationship between logistics performance and a country’s total trade is estimated, followed by a breakdown by the economic sector. Then, the analysis is disaggregated according to the level of technological intensity of traded goods. Finally, after evaluating the intensive margin of trade, the relevance of logistics infrastructure and services for the extensive trade margin is assessed. Results suggest that: (i) improvements in both logistics infrastructure and services are associated with export growth; (ii) manufactured goods can significantly benefit from these improvements, especially when both exporting and importing countries increase their logistics performance; (iii) the quality of logistics infrastructure and services becomes more important as traded goods are technology-intensive; and (iv) improving the exporting country's logistics performance is essential in the intensive margin of trade while enhancing the importing country's logistics performance is more relevant in the extensive margin.

Keywords: gravity models, infrastructure, international trade, logistics

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Authors: Andriana Mkrtchyan, Vahe Khlghatyan

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The choice of a profession is one of the most important decisions people make throughout their life. With the development of modern science, technologies, and all the spheres existing in the modern world, more and more professions are being arisen that complicate even more the process of choosing. Hence, there is a need for a guiding platform to help people to choose a profession and the right career path based on their interests, skills, and personality. This review aims at analyzing existing methods of comparing PDF format documents and suggests that a 3-stage approach is implemented for the comparison, that is – 1. text extraction from PDF format documents, 2. comparison of the extracted text via NLP algorithms, 3. comparison representation using special shape and color psychology methodology.

Keywords: color psychology, data acquisition/extraction, data augmentation, disambiguation, natural language processing, outlier detection, semantic similarity, text-mining, user evaluation, visual search

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Authors: Mario Kubek, Herwig Unger

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Centroid terms are single words that semantically and topically characterise text documents and so may serve as their very compact representation in automatic text processing. In the present paper, centroids are used to measure the relevance of text documents with respect to a given search query. Thus, a new graphbased paradigm for searching texts in large corpora is proposed and evaluated against keyword-based methods. The first, promising experimental results demonstrate the usefulness of the centroid-based search procedure. It is shown that especially the routing of search queries in interactive and decentralised search systems can be greatly improved by applying this approach. A detailed discussion on further fields of its application completes this contribution.

Keywords: search algorithm, centroid, query, keyword, co-occurrence, categorisation

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Authors: Anwar Hussain, Muhammad Iqbal

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The changes in the prices of the agriculture commodities combined with changes in population and agriculture productivity affect farmers’ profitability and standard of living. This study intends to estimate various domestic terms of trade for agriculture sector and also to assess the volatility in the standard of living and profitability of farmers. The terms of trade has been estimated for Pakistan and its provinces using producer prices indices, consumer price indices, input prices indices and quantity indices using the data for the period 1990-91 to 2008-09. The domestic terms of trade of agriculture sector has been improved in terms of both approaches i.e. the ratio of producer prices indices to consumer prices indices and the real per capita income approach. However, the cross province estimates indicated that the terms of trade also improved for Khyber Pakhtunkhwa, Sindh and Punjab while Balochistan’s domestic terms of trade deteriorated drastically. In other words the standard of living of the farmers in Pakistan and its provinces except Balochistan improved. Using the input prices, the domestic terms of trade deteriorated for Pakistan as a whole and its provinces as well. This also explores that as a whole the profitability of the farmers reduced during the study period. The farmers pay more prices for inputs as compared to they receive for their produce. This further indicates that the poverty at the gross root level has been increased. Further, summing, the standard of living of the farmers improved but their profitability reduced, which indicates that the farmers do not completely rely on the farm income but also utilize some other sources of income for their livelihood. The study supports to give subsidies on farm inputs so as to improve the profitability of the farmers.

Keywords: agricultural terms of trade, farmers’ profitability, farmers’ standard of living, consumer and producer price indices, quantity indices

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Authors: Bency Jacob, S.B. Waykar

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Degradations in historical document images appear due to aging of the documents. It is very difficult to understand and retrieve text from badly degraded documents as there is variation between the document foreground and background. Thresholding of such document images either result in broken characters or detection of false texts. Numerous algorithms exist that can separate text and background efficiently in the textual regions of the document; but portions of background are mistaken as text in areas that hardly contain any text. This paper presents a way to overcome these problems by a robust binarization technique that recovers the text from a severely degraded document images and thereby increases the accuracy of optical character recognition systems. The proposed document recovery algorithm efficiently removes degradations from document images. Here we are using the ostus method ,local thresholding and global thresholding and after the binarization training and recognizing the characters in the degraded documents.

Keywords: binarization, denoising, global thresholding, local thresholding, thresholding

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Authors: Kayode A. Olaniyi, Tola. M. Osifeko, Adeola A. Ogunleye

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Text line segmentation is an important step in document image processing. It represents a labeling process that assigns the same label using distance metric probability to spatially aligned units. Text line detection techniques have successfully been implemented mainly in printed documents. However, processing of the handwritten texts especially unconstrained documents has remained a key problem. This is because the unconstrained hand-written text lines are often not uniformly skewed. The spaces between text lines may not be obvious, complicated by the nature of handwriting and, overlapping ascenders and/or descenders of some characters. Hence, text lines detection and segmentation represents a leading challenge in handwritten document image processing. Text line detection methods that rely on the traditional global projection profile of the text document cannot efficiently confront with the problem of variable skew angles between different text lines. Hence, the formulation of a horizontal line as a separator is often not efficient. This paper presents a technique to segment a handwritten document into distinct lines of text. The proposed algorithm starts, by partitioning the initial text image into columns, across its width into chunks of about 5% each. At each vertical strip of 5%, the histogram of horizontal runs is projected. We have worked with the assumption that text appearing in a single strip is almost parallel to each other. The algorithm developed provides a sliding window through the first vertical strip on the left side of the page. It runs through to identify the new minimum corresponding to a valley in the projection profile. Each valley would represent the starting point of the orientation line and the ending point is the minimum point on the projection profile of the next vertical strip. The derived text-lines traverse around any obstructing handwritten vertical strips of connected component by associating it to either the line above or below. A decision of associating such connected component is made by the probability obtained from a distance metric decision. The technique outperforms the global projection profile for text line segmentation and it is robust to handle skewed documents and those with lines running into each other.

Keywords: connected-component, projection-profile, segmentation, text-line

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Authors: Fabien Candau, Florian Lafferrere

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This article analyses how an emission policy for vessels (named California’s Ocean-Going Vessel Fuel Rule) was implemented in 2009 in California impacts trade and marine biodiversity. By studying the decrease in emission levels anticipated by the policy, we measure not only the consequences for port activities but also for one of the most important marine ecosystems of the California Coast: the Kelp forests. Using the Difference in Difference (DiD) approach at the Californian ports level, we find that this policy has led to a significant decrease in trade volume during this period. Therefore, we find a positive and significant effect of shipping policy on kelp canopy and biomass growth by controlling the specific climatic and environmental characteristics of California coastal areas.

Keywords: international trade, shipping, marine biodiversity, emission control area

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Authors: Abdelhadi Nadjer

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The structure of the text to the systemic school -(glossématique-Helmslev). At the beginning of the note we have a cursory look around the concepts of general linguistics The science that studies scientific study of human language based on the description and preview the facts away from the trend of education than we gave a detailed overview the founder of systemic school and most important customers and more methods and curriculum theory and analysis they extend to all humanities, practical action each offset by a theoretical and the procedure can be analyzed through the elements that pose as another method we talked to its links with other language schools where they are based on the sharp criticism of the language before and deflected into consideration for the field of language and its erection has outside or language network and its participation in the actions (non-linguistic) and after that we started our Valglosamatik analytical structure of the text is ejected text terminal or all of the words to was put for expression. This text Negotiable divided into types in turn are divided into classes and class should not be carrying a contradiction and be inclusive. It is on the same materials as described relationships that combine language and seeks to describe their relations and identified.

Keywords: text, language schools, linguistics, human language

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Authors: Tina Ternes, Florian Kleinau

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The study investigates the content and triggers of mind wandering (MW) in readers of fictional texts. It asks whether readers’ MW is productive (text-related) or unproductive (text-unrelated). Methodologically, it bridges the gap between narratological and data-driven approaches by utilizing a sentence-by-sentence self-paced reading paradigm combined with thought probes in the reading of an excerpt of A. L. Kennedy’s “Baby Blue”. Results show that the contents of MW can be linked to text properties. We validated the role of self-reference in MW and found prediction errors to be triggers of MW. Results also indicate that the content of MW often travels along the lines of the text at hand and can thus be viewed as productive and integral to interpretation.

Keywords: narratology, mind wandering, reading fiction, meta cognition

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Authors: George-Anokwuru Chioma Chidinma Bernadette

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This paper investigated the effect of trade liberalization on domestic private investment in Nigeria from 1981 to 2020. To achieve this objective, secondary data on domestic private investment, trade openness, exchange rate and interest rate were sourced from the statistical bulletin of Nigeria’s apex bank. The Autoregressive Distributed Lag (ARDL) technique was used as the main analytical tool. The ARDL Bounds test revealed the existence of long run association among the variables. The results revealed that trade openness and exchange rate have positive and insignificant relationship with domestic private investment both in the long and short runs. At the same time, interest rate has negative relationship with domestic private investment both in the long and short runs. Therefore, it was concluded that there is no significant relationship between trade openness, exchange rate, interest rate and domestic private investment in Nigeria during the period of study. Based on the findings, the study recommended that government should formulate trade policies that will encourage the growth of domestic private investment in Nigeria. To achieve this, government should ensure consistency in trade policies and at the same time strengthen the existing policies to build investors’ confidence. Also, government should make available an investment-friendly environment, as well as monitor real sector operators to ensure that foreign exchange allocations are not diverted. Government should increase capital investment in education, housing, transportation, agriculture, health, power, road construction, national defense, among others that will help the various sectors of the economy to function very well thereby making the business environment friendly thereby enhancing the growth and development of the country.

Keywords: trade openness, domestic private investment, ARDL, exchange rate

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Authors: Rosa L. Figueroa, Christopher A. Flores, Qing Zeng-Treitler

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A regular expression consists of sequence characters which allow describing a text path. Usually, in clinical research, regular expressions are manually created by programmers together with domain experts. Lately, there have been several efforts to investigate how to generate them automatically. This article presents a text classification algorithm based on regexes. The algorithm named REX was designed, and then, implemented as a simplified method to create regexes to classify Spanish text automatically. In order to classify ambiguous cases, such as, when multiple labels are assigned to a testing example, REX includes an information gain method Two sets of data were used to evaluate the algorithm’s effectiveness in clinical text classification tasks. The results indicate that the regular expression based classifier proposed in this work performs statically better regarding accuracy and F-measure than Support Vector Machine and Naïve Bayes for both datasets.

Keywords: information gain, regular expressions, smith-waterman algorithm, text classification

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Authors: Andre C Jordaan

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The end of the Cold War and rivalry between super powers has changed the nature of military build-up in many countries. A call from international institutions like the United Nations, International Monetary Fund and the World Bank to reduce the levels of military expenditure was the order of the day. However, this bid to cut military expenditure has not been forthright. Recently, active armed conflicts occurred in at least 46 states in 2021 with 8 in the Americas, 9 in Asia and Oceania, 3 in Europe, 8 in the Middle East and North Africa and 18 in sub-Saharan Africa. Global military expenditure in 2022 was estimated to be US$2,2 trillion, representing 2.2 per cent of global gross domestic product. Particularly sharp rises in military spending have followed in African countries and the Middle East. Global military expenditure currently follows two divergent trends, either a declining trend in the West caused mainly by austerity, efforts to control budget deficits and the wrapping up of prolonged wars. However, some parts of the world shows an increasing trend on the back of security concerns, geopolitical ambitions and some internal political factors. Conflict related fatalities in sub-Saharan Africa alone increased by 19 per cent between 2020 and 2021. The interaction between military expenditure (read conflict) and international trade is generally the cause of much debate. Some argue that countries’ fear of losing trade opportunities causes political decision makers to refrain from engaging in conflict when important trading partners are involved. However, three main arguments are always present when discussing the relationship between military expenditure or conflicts and international trade: Free trade could promote peaceful cooperation, it could trigger tension between trading blocs and partners, and trade could have no effect because conflict is based on issues that are more important. Military expenditure remains an important element of the overall government expenditure in many African countries. On the other hand, numerous researchers perceive increased international trade to be one of the main factors promoting economic growth in these countries. The purpose of this paper is therefore to determine what effect, if any, exist between the level of military expenditure and international trade within a selection of 19 African countries. Applying an augmented gravity model to explore the relationship between military expenditure and international trade, evidence is found to confirm the existence of an inverse relationship between these two variables. It seems that the results are in line with the Liberal school of thought where trade is seen as an instrument of conflict prevention. Trade is therefore perceived as a symptom of peace and not a cause thereof. In general, conflict or rumors of conflict tend to reduce trade. If conflict did not impede trade, economic agents would be indifferent to risk. Many claim that trade brings peace, however, it seems that it is rather peace that brings trade. From the results, it appears that trade reduces the risk of conflict and that conflict reduces trade.

Keywords: African countries, conflict, international trade, military expenditure

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Authors: Biniam Tedros Kahsay, Yohannes Yebabe Tesfay

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Eritrea is a country in the East of Africa. The country is a neighbor of Djibouti, Ethiopia, and Sudan and is bordered by the Red Sea. The country declared its independence from Ethiopia in 1993. Thus, Eritrea has a lot of commonalities with the Northern Part of Ethiopia's tradition, religion, and languages. Many economists suggested that Eritrea is in a very strategic position for world trade roots and has an impact on geopolitics. This study focused on identifying the most important factor in boosting the Eritrean Economy. The paper collected big secondary data from the World Bank, International Trade and Tariff Data (WTO), East African Community (EAC), Ethiopian Statistical Agency (ESA), and the National Statistics Office (Eritrea). Economists consider economic and population growth in determining trade belts in East Africa. One of the most important Trade Belt that will potentially boost the Eritrean economy is the root of Eritrea (Massawa)->Eritea, (Asmara)->Tigray, (Humora)->Tigray, (Dansha)-> Gondar-> Gojjam-> Benshangual Gumuz => {Oromia, South Sudan}->Uganda. The estimate showed that this is one of the biggest trade roots in East Africa and has a participation of more than 150 million people. We employed various econometric analyses to predict the GDP of Eritrea, considering the future trade belts in East Africa. The result showed that the economy of Eritrea from the Trade Belt will have an elasticity estimate of 65.87% of the GDP of Ethiopia, 3.32% of the GDP of South Sudan, and 0.09% of the GDP of Uganda. The result showed that the existence of war has an elasticity of -93% to the GDP of the country. Thus, if Eritrea wants to strengthen its economy from the East African Trade Belt, the country needs to permanently avoid war in the region. Essentially, the country needs to establish a collaborative platform with the Northern part of Ethiopia (Tigray). Thus, establishing a mutual relationship with Tigray will boost the Eritrean economy. In that regard, Eritrean scholars and policymakers need to work on establishing the East African Trade Belt to boost their economy.

Keywords: Eritrea, east Africa trade belt, GDP, cointegration analysis, critical path analysis

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Authors: Syed Basit Ali Shah Bukhari, Yan Qiang, Saad Abdul Rauf, Syed Saqlaina Bukhari

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Text Classification is the methodology to classify any given text into the respective category from a given set of categories. It is highly important and vital to use proper set of pre-processing , feature selection and classification techniques to achieve this purpose. In this paper we have used different ensemble techniques along with variance in feature selection parameters to see the change in overall accuracy of the result and also on some other individual class based features which include precision value of each individual category of the text. After subjecting our data through pre-processing and feature selection techniques , different individual classifiers were tested first and after that classifiers were combined to form ensembles to increase their accuracy. Later we also studied the impact of decreasing the classification categories on over all accuracy of data. Text classification is highly used in sentiment analysis on social media sites such as twitter for realizing people’s opinions about any cause or it is also used to analyze customer’s reviews about certain products or services. Opinion mining is a vital task in data mining and text categorization is a back-bone to opinion mining.

Keywords: Natural Language Processing, Ensemble Classifier, Bagging Classifier, AdaBoost

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Authors: Lisa Listiana

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ASEAN leader agreed to accelerate ASEAN Economic Community (AEC) implementation by 2015. The AEC Blueprint has set up obligations for its members to follow which include the establishment of (a) free trade in goods, according to ASEAN Free Trade Area: AFTA, (b) free trade in services, according to ASEAN Framework Agreement on Services: AFAS, (c) free trade in investment, according to ASEAN Comprehensive Investment Agreement: ACIA, (d) free capital flow, and (e) free flow of skilled labors. Consequently, these obligations bring both challenges and opportunities for its members. As accountant is included in the coverage of 8 skilled labors, the readiness of accounting profession to embrace AEC 2015 is pivotal. If Indonesian accountants do not accelerate their learning effort, the knowledge gap between Indonesian accountants and their international colleagues will only be worsened. This paper aims to analyze the current progress of AEC preparation and its challenges and opportunities for Indonesian accountants, and also to propose recommendation as necessary.

Keywords: AEC, ASEAN, readiness, Indonesian accountants

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Authors: Tamar Lazariashvili

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There are a number of factors that determine the growth and development of the country's economy; however, trade and economic relations with other countries are the most important of all these factors. The paper analyzes the trade and economic relations between Georgia and Germany, identifies the impediments caused by the Covid pandemic, and substantiates the need for further economic cooperation between the countries. Research objectives. The objective of the research is to develop recommendations and reveal the prospects of further cooperation between Georgia and Germany based on identifying the problems in the field of trade and economy in the post-crisis situation. The research object is Georgian German economic relations. Germany is Georgia's largest trading partner in the European Union. Georgia and Germany actively cooperate within the framework of international organizations as well. The paper analyzes the multilateral and intensive economic relations between Germany and Georgia; evaluates the investments of German companies in Georgia and the activities of Georgian companies in Germany. Research methods. The paper uses general and specific research methods; in particular, analysis, synthesis, induction, deduction, comparison, statistical (selection, grouping, observation, trend), and other research methods.SWOT analysis is used to determine development opportunities between countries. As a result of the research economic ranking of Georgia and Germany are determined according to the above criteria, the causes of the impediments due to the pandemic are studied; the main problems in the field of trade and economy are identified. The paper provides conclusions on the problems in the trade relations between Georgia and Germany and suggests recommendations regarding the prospects for improving these relations.

Keywords: georgia-germany, trade and economic relations, economic ranking, perspective directions

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Authors: Sakapas Saengchai, Pichamon Chansuchai

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Research Thai- Myanmar Border Trade Promotion Policy, Mae Sai District, Chiang Rai Province The objectives of this study were to study the policy of promoting Thai- Myanmar border trade in Mae Sai district, Chiang Rai province. And suitable models for the development of border trade in Mae Sai. Chiang Rai province This research uses qualitative methodology. The method of collecting data from research papers. Participatory Observation In-depth interviews in which the information is important, the governor of Chiang Rai. Chiang Rai Customs Service Executive Office of Mae Sai Immigration Bureau Maesai Chamber of Commerce and Private Entrepreneurs By specific sampling Data analysis uses content analysis. The study indicated that Border Trade Promotion Policy The direction taken by the government to focus on developing 1. Security is further reducing crime. Smuggling and human trafficking Including the preparation to protect people from terrorism and natural disasters. And cooperation with Burma on border security. 2. The development of wealth is the promotion of investment. The transport links, logistics value chain. Products and services across the Thai-Myanmar border. Improve the regulations and laws to promote fair trade. Convenient and fast 3. Sustainable development is the ability to generate income, quality of life of people in the Thai border to increase continuously. By using balanced natural resources, production and consumption are environmentally friendly. Which featured the participation of all sectors of the public and private sectors in the region to drive the development of the border with Thailand. Chiang Rai province To be more competitive .

Keywords: Border, Trade, Policy, Promote

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Authors: Nor Diana Ahmad, Eric Atwell, Brandon Bennett

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Text processing techniques for English have been developed for several decades. But for the Malay language, text processing methods are still far behind. Moreover, there are limited resources, tools for computational linguistic analysis available for the Malay language. Therefore, this research presents the use of natural language processing (NLP) in processing Malay translated Qur’an text. As the result, a new language resource for Malay translated Qur’an was created. This resource will help other researchers to build the necessary processing tools for the Malay language. This research also develops a simple question-answer prototype to demonstrate the use of the Malay Qur’an resource for text processing. This prototype has been developed using Python. The prototype pre-processes the Malay Qur’an and an input query using a stemming algorithm and then searches for occurrences of the query word stem. The result produced shows improved matching likelihood between user query and its answer. A POS-tagging algorithm has also been produced. The stemming and tagging algorithms can be used as tools for research related to other Malay texts and can be used to support applications such as information retrieval, question answering systems, ontology-based search and other text analysis tasks.

Keywords: language resource, Malay translated Qur'an, natural language processing (NLP), text processing

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Authors: Victor N. Anisimov, Lyubov A. Boyko, Yazgul R. Almukhametova, Natalia V. Galkina, Alexander V. Latanov

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Modern commercials presented on billboards, TV and on the Internet contain a lot of information about the product or service in text form. However, this information cannot always be perceived and understood by consumers. Typical sociological focus group studies often cannot reveal important features of the interpretation and understanding information that has been read in text messages. In addition, there is no reliable method to determine the degree of understanding of the information contained in a text. Only the fact of viewing a text does not mean that consumer has perceived and understood the meaning of this text. At the same time, the tools based on marketing analysis allow only to indirectly estimate the process of reading and understanding a text. Therefore, the aim of this work is to develop a valid method of recording objective indicators in real time for assessing the fact of reading and the degree of text comprehension. Psychophysiological parameters recorded during text reading can form the basis for this objective method. We studied the relationship between multimodal psychophysiological parameters and the process of text comprehension during reading using the method of correlation analysis. We used eye-tracking technology to record eye movements parameters to estimate visual attention, electroencephalography (EEG) to assess cognitive load and polygraphic indicators (skin-galvanic reaction, SGR) that reflect the emotional state of the respondent during text reading. We revealed reliable interrelations between perceiving the information and the dynamics of psychophysiological parameters during reading the text in commercials. Eye movement parameters reflected the difficulties arising in respondents during perceiving ambiguous parts of text. EEG dynamics in rate of alpha band were related with cumulative effect of cognitive load. SGR dynamics were related with emotional state of the respondent and with the meaning of text and type of commercial. EEG and polygraph parameters together also reflected the mental difficulties of respondents in understanding text and showed significant differences in cases of low and high text comprehension. We also revealed differences in psychophysiological parameters for different type of commercials (static vs. video, financial vs. cinema vs. pharmaceutics vs. mobile communication, etc.). Conclusions: Our methodology allows to perform multimodal evaluation of text perusal and the quality of text reading in commercials. In general, our results indicate the possibility of designing an integral model to estimate the comprehension of reading the commercial text in percent scale based on all noticed markers.

Keywords: reading, commercials, eye movements, EEG, polygraphic indicators

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Authors: Muhammad Khaliqi, Amzul Rifin, Andriyono Kilat Adhi

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The non-tariff policy could make Indonesian shrimp exports decrease in the international market. This research was aimed to analyze factors affecting Indonesia's exports of shrimp and the impact of SPS and TBT policy on Indonesian shrimp. Factors affecting the exports of Indonesian shrimp were estimated using gravity model. The results showed the GDP of exporters and exchange rate, have a negative influence against the export of Indonesia’s shrimp exports. The GDP of the importers and trade cost have a positive influence against the export of shrimp Indonesia while the SPS policy and TBT don’t affect Indonesia's exports of shrimp in the international market.

Keywords: gravity model, international trade, non-tariff measure, sanitary and phytosanitary, shrimp, technical barriers to trade

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Authors: Zayar Phyo, Ei Chaw Htoon

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In a New-LSB based Steganography method, the Fisher-Yates algorithm is used to permute an existing array randomly. However, that algorithm performance became slower and occurred memory overflow problem while processing the large dimension of images. Therefore, the Text-Based Shuffling algorithm aimed to select only necessary pixels as hiding characters at the specific position of an image according to the length of the input text. In this paper, the enhanced text-based shuffling algorithm is presented with the powered of GPU to improve more excellent performance. The proposed algorithm employs the OpenCL Aparapi framework, along with XORShift Kernel including the Pseudo-Random Number Generator (PRNG) Kernel. PRNG is applied to produce random numbers inside the kernel of OpenCL. The experiment of the proposed algorithm is carried out by practicing GPU that it can perform faster-processing speed and better efficiency without getting the disruption of unnecessary operating system tasks.

Keywords: LSB based steganography, Fisher-Yates algorithm, text-based shuffling algorithm, OpenCL, XORShiftKernel

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Authors: Sidi Yang, Haiyi Zhang

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Twitter is a microblogging platform, where millions of users daily share their attitudes, views, and opinions. Using a probabilistic Latent Dirichlet Allocation (LDA) topic model to discern the most popular topics in the Twitter data is an effective way to analyze a large set of tweets to find a set of topics in a computationally efficient manner. Sentiment analysis provides an effective method to show the emotions and sentiments found in each tweet and an efficient way to summarize the results in a manner that is clearly understood. The primary goal of this paper is to explore text mining, extract and analyze useful information from unstructured text using two approaches: LDA topic modelling and sentiment analysis by examining Twitter plain text data in English. These two methods allow people to dig data more effectively and efficiently. LDA topic model and sentiment analysis can also be applied to provide insight views in business and scientific fields.

Keywords: text mining, Twitter, topic model, sentiment analysis

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Authors: Beier Zhu, Rui Zhang, Qi Song

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Text contained within fixed-layout documents can be of great semantic value and so requires a high localization accuracy, such as ID cards, invoices, cheques, and passports. Recently, algorithms based on deep convolutional networks achieve high performance on text detection tasks. However, for text localization in fixed-layout documents, such algorithms detect word bounding boxes individually, which ignores the layout information. This paper presents a novel architecture built on convolutional neural networks (CNNs). A global text localization network and a regional bounding-box regression network are introduced to tackle the problem in a coarse-to-fine manner. The text localization network simultaneously locates word bounding points, which takes the layout information into account. The bounding-box regression network inputs the features pooled from arbitrarily sized RoIs and refine the localizations. These two networks share their convolutional features and are trained jointly. A typical type of fixed-layout documents: ID cards, is selected to evaluate the effectiveness of the proposed system. These networks are trained on data cropped from nature scene images, and synthetic data produced by a synthetic text generation engine. Experiments show that our approach locates high accuracy word bounding boxes and achieves state-of-the-art performance.

Keywords: bounding box regression, convolutional networks, fixed-layout documents, text localization

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Authors: Priti Bajpai, Mohammed Shibil

Abstract:

This paper utilizes a comparative case study design to examine a regional onion market. The particular case of onion markets is used to understand perishable product supply chains. The site for the study is Dubai, United Arab Emirates. Results from a six-month field study are outlined. In particular, the findings suggest that firms should examine adding additional destinations to their supply chain. Further, we argue that utilizing Dubai as a supply chain hub is in certain cases counterproductive. Implications for food supply chains and regional trade are discussed.

Keywords: supply chains, food markets, onion trade, field study

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Authors: Rabi Mouhcine, Amrouch Mustapha, Mahani Zouhir, Mammass Driss

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In this paper, we present a system for offline recognition cursive Arabic handwritten text based on Hidden Markov Models (HMMs). The system is analytical without explicit segmentation used embedded training to perform and enhance the character models. Extraction features preceded by baseline estimation are statistical and geometric to integrate both the peculiarities of the text and the pixel distribution characteristics in the word image. These features are modelled using hidden Markov models and trained by embedded training. The experiments on images of the benchmark IFN/ENIT database show that the proposed system improves recognition.

Keywords: recognition, handwriting, Arabic text, HMMs, embedded training

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Authors: Bilge Afşar, Zeynep Karaçor, Burcu Guvenek

Abstract:

The aim of this study is to examine and analyze the effect of macroeconomic policies on foreign trade. In the study, the effect of the macroeconomic policies applied in Turkey after 2001 on foreign trade was scrutinized carrying out a survey study in the sample of the province Konya. In the survey study, the survey was administered to a total of 209 exporter firms, which are the members of Konya Chamber of Commerce. While 51 of the firms, to which the survey was administered, exported below $ 100,000, 158 of them are the firms exporting above $ 100,000. Survey was realized in the way of face to face interview with the firms in the rate of 79%. 47% of the institutions forming the mass were reached. In forming survey questionnaire, in general, 5-point Likert scale was used. In order to assess the study results, SPSS 15 package program was utilized. In the survey, foreign trade activities of the firms in Konya were analyzed; and the problems they face, while performing foreign trade, and those needing to be carried out for increasing foreign trade volume of Konya were revealed by determining how and at what degree they were affected from the macroeconomic policies applied. Thus, foreign trade structure and state of the province Konya were attempted to be analyzed. In the survey study, it emerges that although the problems Konya faces in foreign trade overlap with the problems across Turkey, the province Konya seems to be affected relatively less from the last crisis with its equity capital in either trade or other areas. Until the year 2008, while Konya is in a position of the province continuously increasing its export, also with the effect of global crisis, in 2009, a fall was seen in the amount of export. The results emerging in the survey study also confirm this case. In parallel with demand inadequacy and recession all over the world, firms experience trouble. However, again according to our survey result, foreign market weight of firms shifted from EU countries to Russia, East Bloc, and Middle East countries. This prevented Konya from negative affecting from EU crisis at maximum level. That is, Russian and Middle East market express significance for Konya. That market is diversified, and being relatively rid of dependence to EU is extremely important in terms of Konya export.

Keywords: economy, foreign trade, economic crise, macro economic politicies

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Authors: Ngo the Bach

Abstract:

Vietnam is one of not many Asian countries that have a long-standing and famous tradition of pottery production. Vietnam is also one of three countries including China, Vietnam, and Japan developed strongly the export of ceramics to other countries. In recent decades, the studies of Vietnamese and foreign scholars on Vietnamese trade ceramics as well as Vietnamese foreign trade was initially recorded. The aim of this article is to introduce an overview of the findings situation and research results; the development of Vietnam ceramics and the Vietnamese history of maritime trade with Asian ceramics from the 14th century to the 17th century. Given that, the author systematized materials; carried out the synthetic and analysis for research results of Vietnamese and foreign researchers until now on Vietnamese export ceramics on the basis of the historical sources, archaeological findings discovered from relics in the tombs, relics of residence, relics of trading port inland, and the ancient shipwreck sank in the Asian countries.

Keywords: Vietnamese ceramics, trading, maritime, international

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Authors: Syed Toqueer Akhter, Muhammad Muzaffar Abbas

Abstract:

Conflicts in Pakistan are a result of a configuration of factors, which are directly related to the system of the state, the unstable regional setting, and the geo-strategic location of Pakistan at large. This paper examines the impact of regional conflict onto the socio-political sustainability of Pakistan. The magnitude of the spillover from a conflicted region is similar in size of the equivalent increase in domestic conflict. Pakistan has gone at war three times with India; the border with India is named as the tensest borderlines of the world. Disagreements with India and lack of dispute settlement mechanisms have negatively effected the peace in the region, influx of illegal weapons and refugees from Afghanistan as an outcome of 9/11 incidence, have exasperated the criticality of levels of internal conflict in Pakistan. Our empirical findings are based on the data collected on regional conflict levels, regional trade, global trade, comparative defence capabilities of the region in contrast to Pakistan and the government regime (Autocratic, Democratic) over 1972-2007. It has been proposed in this paper that the intent of domestic conflict is associated with the conflict in the region, regional trade, global trade and the government regime of Pakistan. The estimated model (OLS) implies that domestic conflict is effected positively and significantly with long term impact of conflict in the region. Also, if defence capabilities of the region are better than that of Pakistan it effects domestic conflict positively and significantly. Conflict in neighbouring countries are found as a source of domestic conflict in Pakistan, whereas the regional trade as well as type of government regimes in Pakistan lowered the intensity of domestic conflict significantly, while globalized trade imply risk of domestic conflict to be reduced but not significantly.

Keywords: conflict, regional trade, socio-politcal instability

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