Miracle-dz/UniFAR-FTUs huggingface dataset:
Incorporating Network Embedding into Markov Random Field for Better Community Detection

Recent research on community detection focuses on learning representations of nodes using different network embedding methods, and then feeding them as normal features to clustering algorithms. However, we find that though one may have good results by direct clustering based on such network embedding features, there is ample room for improvement. More seriously, in many real networks, some statisticallysignificant nodes which play pivotal roles are often divided into incorrect communities using network embedding methods. This is because while some distance measures are used to capture the spatial relationship between nodes by embedding, the nodes after mapping to feature vectors are essentially not coupled any more, losing important structural information. To address this problem, we propose a general Markov Random Field (MRF) framework to incorporate coupling in network embedding which allows better detecting network communities. By smartly utilizing properties of MRF, the new framework not only preserves the advantages of network embedding (e.g. low complexity, high parallelizability and applicability for traditional machine learning), but also alleviates its core drawback of inadequate representations of dependencies via making up the missing coupling relationships. Experiments on real networks show that our new approach improves the accuracy of existing embedding methods (e.g. Node2Vec, DeepWalk and MNMF), and corrects most wrongly-divided statistically-significant nodes, which makes network embedding essentially suitable for real community detection applications. The new approach also outperforms other state-of-the-art conventional community detection methods.
ASSESSING ENERGY SECURITY IN THE CASPIAN REGION: THE GEOPOLITICAL IMPLICATIONS TO EUROPEAN ENERGY STRATEGY

Following the collapse of the Soviet Union, Western countries have signed several agreements regarding the use of hydrocarbon resources in the Caspian Basin, with the aim of diversifying their energy suppliers. However, recession in the world economy and persistently low oil prices have profoundly affected the economies of the Caspian states, whose gross domestic product and exports are dominated by oil and oil products. Strongly dependent on export revenues from oil and gas, the economic growth of these states has slowed since 2014. Although limited energy resources have stimulated an emphasis on security of supply, fundamentally understood as a continued and low-risk strategy of interruption of energy import flows, low oil prices have also maintained focus on the challenge of security of demand faced by energy-producing economies in terms of stable energy export revenues. However, geopolitical developments around the world, especially local armed conflicts, highlight the importance of secure routes, as they present a threat to energy transportation. Using an indicator-based approach and country-level data over the period 2000–2017, this paper assesses the security of demand for the oil and gas of three countries in the Caspian region: Azerbaijan, Kazakhstan, and Turkmenistan, over a 16-year period, capturing the geopolitical situation and contributing to a greater understanding of the impact of energy-transporting countries’ geopolitical situation on energy transportation to the European Union (EU). The results demonstrate that risk of energy security of demand is greater when political risk in energy-transporting countries is included within a measure of energy security of demand, i.e., risky external energy demand. The sharp decline in political stability and absence of violence or terrorism ratings in Ukraine and Turkey has increased the risk of security of energy demand in Azerbaijan, Kazakhstan, and Turkmenistan. The results highlight the importance of cooperation not only between the EU and the Caspian region, but also with energytransporting countries, such as Ukraine, Georgia, and Turkey. Alternatively, routes may be found that bypass countries with low levels of political stability, such as through the TransCaspian Pipeline.
Settling in: how newcomers use a public library

Purpose The purpose of this paper is to describe how recent immigrants and refugees to Canada (“newcomers”) use the facilities of a large, urban public library. As the library previously surveyed the general user population, the responses to the two surveys can be compared. Design/methodology/approach Questionnaires were administered as patrons were leaving Surrey Libraries Branches to adult public library members who self-identified as newcomers who arrived in Canada within the previous ten years. Findings The pattern of library use by newcomers differed from that of the general population. They visited more frequently and stayed longer. Newcomers were heavier users of library services and used a wider range of services. They used the library branch as a public place. The library provided them with a place to study, read or meet other people. Research limitations/implications The study was exploratory. The small sample size and the data collection process do not allow extrapolation to the underlying population. Practical implications Recent newcomers often have similar informational, psychological and social needs. Public libraries can play a role in assisting newcomers during their adjustment process. Originality/value Researchers worked closely with library management to develop questions based on decision usefulness. An earlier in-house study allowed comparisons to be made between branch use by newcomers and general library users. Canadian studies into government policy, along with immigrant and refugee studies, provide context for the survey results.
The Politics of Curriculum Making: Understanding the Possibilities for and Limitations to a "Teacher-Led" Curriculum in British Columbia. BCTF Research Report.

This paper aims to deepen our understanding of the opportunities for, as well as challenges to, teacher-led curriculum change. Drawing on interviews with teachers who served on Provincial Curriculum Development Teams, the paper explores how teachers have navigated the curriculum development process in four key moments: (1) framing the work (2) curricular knowledge (3) the question of implementation (4) politics and expertise
Stock Market Development and Economic Performance of West-African Countries: A Dynamic Panel Data Analysis

The nexus between development of stock market and the performance of economic activities have been a critical issue around the globe. The issue as to whether a well-developed stock market influences the performance of economic activities and the relevant of developmental policy strategies have been a concern for the developing economies especially the West Africa economies. Literatures have shown that most of the West Africa economies were faced with sharp swings and wide fluctuations in the stock market indices, which had negative effect on the performance of economic activities of these economies. This study examined the effect of stock market development on the economic performance among West Africa economies. The study employed secondary data subjected to panel regression method of analysis within the period of seven years across selected West-Africa countries. Findings revealed that stock market development indicators; ratio of market capitalization to gross domestic product, All Share Index, and Stock Turnover have positive effect on economic performance while corruption perception index have negative effect on economic performance, all at 5% level of significance. The study concludes that stock market development indicators and corruption index affect economic performance in West Africa. Therefore, the study recommends that the stock market regulatory authorities should initiate strategic policies that would boost market liquidity and encourage easy access of companies to the market and also be more Received 23 July 2019 Revised 10 August 2019 Accepted 27 August 2019 Corresponding author: k.fakunmoju@gmail.com Abdullahi I. B. , Fakunmoju S. K. Journal of Management, Economics, and Industrial Organization, Vol.3 No.3, 2019, pp.12-26. 13 proactive in surveillance role in order to check unethical practices which undermine stock market integrity, erode investors’ confidence and patronage. JEL Code: G1, O4, C1.
Stereo Matching Based Estimation of Depth Map from Stereo Image Pair

Stereo vision is a technique of depth perception, in which the information about the depth is inferred from the two (or more) images captured from different perspectives of a scene. These images is known as stereo image pair. Practical applications where stereo vision technology plays a role may include autonomous vehicle guidance, aerial photogrammetry, robotics vision, object tracking and industrial automation. Many automated vision systems could benefit substantially from depth maps. A depth map is a grayscale image that contains depth information for each pixel in an image. Traditionally depth maps were extracted using stereo camera approach. Depth estimation from stereo involves finding disparities along the same scanline, also called as epipolar lines. Such a search process typically requires a prior adjustment of the images known as rectification step to ensure that epipolar lines are well aligned. Still, the approaches for estimation of depth map suffer from either limited reliability and robustness when tested on stereo image pair or large time of computation. A novel approach for depth estimation that integrates the image filtering into a stereo matching framework is introduced. Experiment helps verifying the sustenance of high quality in depth maps, while reducing the average percent of bad pixels to 3.58%.
Simplifying Encoder-Decoder-Based Neural Machine Translation Systems to Translate between Related Languages

Neural machine translation is one of the most advanced approaches to machine translation and one that is recently obtaining good enough results to make use of it in real-life scenarios. The currently widely used architecture is what is known as sequence-to-sequence architecture with attention mechanism, which uses an encoder to create a vector representation of the input sentence in source language, a decoder to output a sentence in target language and an attention mechanism to help the decoder produce more accurate outputs. The simplification of state-of-the-art sequence-to-sequence neural machine translation with attention is explored in this work for the translation between related languages. First, some of the state-of-the-art features present in the baseline system are presented and described. The main hypothesis of this work is the possibility of removing these features without worsening the translation quality too much and simplifying the network’s structure at the same time when translating between related languages. The main part of this work is the substitution of state-of-the-art attention mechanisms, used to help the decoder know which part of the source sentence is more relevant for the part of the target sentence being outputted, by a simplified attention mechanism which mostly pays attention to the word in the source sentence in the same position as the current target word. The simplification is carried out by removing beam search (a technique used to explore a wider range of possible outputs instead of limiting the output to the highest probability of being the correct output), substituting the bidirectional encoder by a unidirectional encoder and creating a new “local attention” mechanism in replacement for the current more complex state-of-the-art attention mechanism. Once the simplifications have been discussed and implemented, their impact on translation quality for related languages (Spanish and Catalan in the case of this work) is tested and compared to determine their suitability. From the results obtained, as expected, the removal of beam search and the substitution of the bidirectional encoder by a unidirectional encoder does not have a great impact on translation quality, resulting in a decrease of 6%-23% in BLEU score depending on the attention mechanism being used. On top of this, the introduction of the newly-developed “local attention” mechanism improves translation quality by 176% and 218% in BLEU score when compared to an attention-less i system, about 22%-27% less than the state-of-the-art attention mechanism used in the baseline system. All of this resulting in the great simplification in the network, reducing the number of trainable parameters from 12.195. 945 to 9.816. 485 (19.5%) and the training time from 22h 53m to 12h 15m.
National Culture and Women Managers: Evidence From Microfinance Institutions Around the World

We investigate the effect of national culture on women manager appointments. We argue that culture influences women manager appointments through their effects on managerial decision-making. Using firm-level data on 2,456 microfinance institutions (MFIs) across 61 countries, we document that fewer women managers are appointed in societies high on individualism and uncertainty avoidance. On the contrary, high power distance societies are positively associated with the appointment of women managers. We demonstrate that a greater number of women nonmanagers reduces (increases) the appointment of women managers in high individualistic (uncertainty avoidance) cultures. Our findings challenge the “one-size-fit-all” approach adopted by policy makers around the world to increase women manager appointments. Our results are robust to endogeneity.
Social Entrepreneurship Policy: Evidences from the Italian Reform

Social entrepreneurship (third sector) is an increasingly important global economic phenomenon that is squarely under the academic lens. Social entrepreneurship represents an interesting opportunity for policy makers to explore new frontiers of economic growth and implement innovation in a potentially growing services sector with possible job opportunities coming from new job creation in the upcoming decades. Based on evidence from Italy, this paper considers the broader picture of this phenomenon. Addressing the need to better understand the drivers of social entrepreneurship policy, we propose a model for interpreting the impact of the recent Italian reform of the third sector at various levels of the ecosystem, which favors innovation, technology adaptation, and greater employability. The presented results contribute to laying the foundation for the further development of a theory of entrepreneurship policy.
Intelligent Consumer Flow and Experience Analysis System Based on Cognitive Intelligence: Smart Eye System

With the saturation of the market and the competition in e-commerce, the focus of the offline new retail has gradually shifted from commodities to consumers. Although there have been some developments in the offline retail industry in terms of consumer analysis in recent years, such as consumer flow statistics based on the non-visual sensors and consumer experience based on the questionnaire, it is still difficult to meet the growing demand due to the limitations of traditional technologies. To deal with the problem, Smart Eye System (SES) is proposed to analyze the characteristics and evaluate the experience of consumers by Cognitive Intelligence (CI). As a new attempt, face recognition, emotion recognition and ambient information are combined to provide more detailed and accurate analysis of consumers, including the statistics, characteristics and experience of consumer flow. As the first batch of products that combine CI with commercial applications, SES brings not only more accurate analysis and broader perspectives to the offline retail industry, but also a frontier experiment that commercializes CI.
Russia, the Former Soviet Republics, and Europe Since 1989

Nearly three decades after the fall of the Berlin Wall, early hopes for the integration of the post-Soviet states into a “Europe whole and free” seem to have been decisively dashed. Europe itself is in the midst of a multifaceted crisis that threatens the considerable gains of the postwar liberal European experiment. This book provides a panoramic view of the process of “Europeanization” in Russia and all fourteen of the other former Soviet republics since 1989, in a study that is both theoretically grounded (with five chapters that discuss the historical and contemporary meanings of “Europe” in its cultural-civilizational, political, and security guises) and empirically rich (with case studies that examine the question of Europeanization in Russia and each of the other fourteen ex-Soviet republics). It argues that deeply rooted ideas about Europe’s cultural-civilizational primacy and about who “belongs” in Europe, and who doesn’t—and who might be able to “become European” someday, and who definitely cannot—to influence both internal politics in contemporary Europe and the processes of Europeanization in Russia and the former Soviet Union. From the “European dreams” of people in Ukraine and Georgia, who continue to see Europe as a beacon of liberal values, democratic institutions, and economic prosperity, to Russia’s efforts to weaken the postwar European order by presenting an alternative, more ethnonationalist, realist, and revanchist view of “Europe,” it demonstrates the necessity and utility of viewing contemporary Eurasian politics as a struggle over the meaning and practices of “Europeanness. ”
Forecasting the wind power generation using Box–Jenkins and hybrid artificial intelligence

Purpose The purpose of this paper is to forecast wind power generation in an area through different methods, and then, recommend the most suitable one using some performance criteria. Design/methodology/approach The Box–Jenkins modeling and the Neural network modeling approaches are applied to perform forecasting for the last 12 months. Findings The results indicated that among the tested artificial neural network (ANN) model and its improved model, artificial neural network-genetic algorithm (ANN-GA) with RMSE of 0.4213 and R2 of 0.9212 gains the best performance in prediction of wind power generation values. Finally, a comparison between ANN-GA and ARIMA method confirmed a far superior power generation prediction performance for ARIMA with RMSE of 0.3443 and R2 of 0.9480. Originality/value Performance of the ARIMA method is evaluated in comparison to several types of ANN models including ANN, and its improved model using GA as ANN-GA and particle swarm optimization (PSO) as ANN-PSO.
Fatigue Driving Detection Based on Machine Learning and Image Processing Technology

Fatigue driving is a major cause of traffic accidents. If fatigue driving can be detected and stopped in time, perhaps traffic accidents will be reduced. This paper proposes a fatigue driving detection algorithm using machine learning and image processing technology. The algorithm is designed to run on the vehicle’s smart terminal. In the algorithm, terminal has to analyze the status of driver’s eyes, nose and mouth using machine learning and image processing technology. When catch typical behaviors such as blink, yawn and nod, terminal will record the time and calculate the frequencies of these behaviors. If one of the frequencies is greater than the threshold, terminal will trigger the alert and take measures to make driver no longer fatigue driving. The algorithm works fine in the experiment. The experimental accuracy of the algorithm is 94%.
Peran Kiai Sebagai Inisiator dan Elitist Charismatic dalam Membentuk Akuntabilitas Nahdlatul Ulama

Abstract: Nahdlatul Ulama (NU) is a religious organization that has a representative from traditional ulama with the ideology of ahlus sunnah waljamaah. Along with its development, NU still holds a culture that is derived from its predecessors (Kiai) in managing the organization, both in the organizational structure and in terms of organizing community-based non-profit organizations that have a principle of accountability. For this reason, the purpose of this research is to analyze and describe the reality of the role of the Kiai in forming NU’s accountability. The research perspective used is the interpretive paradigm with qualitative research methods through a multiple case study approach. The results of the study revealed that the role of the Kiai as an initiator in establishing accountability was shown by the provision of ideas in accordance to the needs of NU residents in particular, and the Indonesian State in general. This role can be categorized as the Elitist-charismatic values — which is the value system of pride of the charismatic leader which results in the fanaticism of the members of the organization. Since the charismatic nature of the kiai is temporary, these values are transitional. NU's accountability process is called "Typical Accountability of Lillahita'ala and Ikhlas in the style of NU". The purpose of the accountability of Lillahita’ala and Ikhlas is the principle of honesty and sincerity in preparing financial statements . Abstrak: NU merupakan organisasi agama yang yang memiliki reprensentatif dari ulama tradisional dengan ideologi ahlus sunnah waljamaah. Seiring perkembangannya, ternyata NU masih memegang budaya yang diturunkan dari para pendahulunya (Kiai) dalam mengelola organisasinya, baik dalam struktur organisasi maupun dalam hal penyelenggaraan organisasi nirlaba berbasis masyarakat yang berprinsip akuntabilitas. Melihat hal tersebut, maka tujuan dalam penelitian ini adalah menganalisis dan mendeskripsikan secara mendalam tentang realitas peran Kiai dalam membentuk Akuntabilitas NU. Prespektif penelitian yang dipakai adalah paradigma interpretif dengan metode penelitian kualitatif melalui pendekatan studi kasus kolektif (collective or multiple case study). Hasil penelitian diketahui bahwa Peran Kiai sebagai inisiator dalam membentuk Akuntabilitas ditunjukkan adanya pemberian gagasan sesuai dengan kebutuhan warga NU pada khususnya dan Negara Indonesia pada umumnya. Peran Kiai yang sedemikian besar tersebut dikategorikan dalam nilai tipe elitist charismatic values, yang merupakan sistem nilai kebanggaan diri dari pimpinan yang kharismatik yang menghasilkan fanatisme para anggota organisasi. Mengingat sifat kharismatik dari kiai bersifat temporer, maka nilai-nilai ini bersifat transisional. Proses akuntabilitas NU ini disebut “Akuntabilitas Khas Lillahita’ala dan Ikhlas ala NU”. Maksud dari akuntabilitas Lillahita’ala dan Ikhlas ini adalah adanya prinsip kejujuran dan keikhlasan dalam menyusun laporan keuangan.
Research Impact on Drone by means of Scientometric Analysis

The Scientometric analysis done on “Drone” is based on the literatures indexed in SCOPUS from 1999 to 2018. The data reveals that 2902 records were published with a total of 2746 Local Citation Score and 16494 Global Citation Score. The Regression test has been conducted to test the hypothesis in an intention to check the deviation among the research publications. The year wise, language wise growth of literature and the type of documents involved in process of publications were assessed. The Bradford’s Bibliometric law was applied to identify the core journals. Top ten countries, ten journals and top five authors were retrieved along with the hindices. Through the research, it is suggested that the Ministry of Human Resource Development to allocate more funds to enhance the research on “Drone”, as this un-manned vehicle can reach the place where human being hesitate to enter, to unhide many more facts for the smooth and safe life of the living beings in this world. -------