Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting Sentiments from Movie Reviews by Integrating Reviewers Own Prejudice

Presently, sentiment analysis algorithms are widely used to extract positive or negative feedback scores of various objects on the basis of the text/reviews. But, an individual may have a certain degree of biasness towards a certain product/company and hence may not objectively review the object. We try to combat this biasness problem by incorporating the positive and negative bias component in the existing sentiment score of the object. This paper proposes several algorithms for a new system of implementing individual bias in the corpus of data i.e. movie reviews in this case. Each review comment has an unadjusted sentiment score associated with it. This unadjusted score is refined to give an adjusted score using the positive and negative bias score. The bias score is calculated using certain parameters, the weightage of which has been determined by conducting a survey. We lay emphasis on the degree of biasness an individual has towards or against the review parameters for the movie reviews corpus namely actor, director and genre. We equip the system with the capability to handle various scenarios like positive inclination of the user, negative inclination of the user, presence of both positive and negative inclination of the user and neutral attitude of the user by implementing the formulae we developed.
Global Financial Crisis: Dynamics of Liquidity Risk in Emerging Asia

This study investigates the dynamic impact of global and regional liquidity along with volatility on the liquidity of emerging Asian equity markets. Further, we empirically disentangle the effects of volatility and liquidity. We find that the external liquidity factors have a higher impact on domestic liquidity as compared to volatility. The impact of global volatility shocks was witnessed only during the Global Financial Crisis. Global factors have a higher influence on developed markets such as Japan and Singapore, while regional factors have a higher influence on emerging markets. These results indicate that liquidity serves as the channel of regional integration in Asia. The findings of this study provide useful insights to cross-sections of stakeholders in the investment industry. JEL Classification: G15, F21, F36
A new model of binocular vision in image-based visual servoing robot control

In most eye-in-hand visual servoing systems,the depth information must be given,because the traditional image Jacobian matrix always needs one.In this paper,a new binocular stereo visual servo model that the depth information can be ignored is pro-posed.In the new model,three image coordinate variables are introduced and which counteract the depth coordinate variable,so it is not needed to measure or estimate the depth information about the target.The depth estimation problem is completely solved and the control performance of the servo system is improved in the new model.By using this model and considering the kinematics characteristics of the robot separately,a positioning controller of a robotic end effector has been designed.The effectiveness of the controller has been verified via simulation and put forward the improvement algorithm with wider practicability.Furthermore,the binocular vision control experiment has been done by means of the MOTOMAN UP6 robotic manipulator.The experimental result shows that the new model is effective and feasible in practical control project.
The Influence of Political Characteristics on the Relationship between Family Control and Firm Performance: A Meta-Analytical Approach

This multilevel meta-analytic study, based on 176 studies from 36 countries, examines the impact of political characteristics on the performance of family firms when comparing them to non-family firms (k=311, N=1,598,964). Our findings support the expectation that family firm characteristics are positively related to firm performance. We trace the variance between the studies to differences in certain political characteristics of the firms' countries of origin: government stability, regime stability, regime type and special periods of factionalism. In terms of government and regime stability, we find positive moderating effects on the focal relationship. We further show that periods of factionalism even reverse the superior performance of family firms. While the focal relationship becomes stronger in democracies, the relationship turns negative when looking at anocracies and becomes stronger and positive again considering autocracies. Finally, we reveal that government stability partly mediates the influence of the regime type. Therefore, government stability is a crucial condition for family firms to prosper in any political environment. Our study has several implications for the interplay between family firms and politics: First, the comparative advantage of family firms depends on specific political characteristics. Second, the ability of institutions to provide stability is more important for family firms than the actual institutional setting itself. Third, the impact of a political environment on economic success differs between family firms and nonfamily firms and therefore depends on the structure of the given economy.
Exploiting side information and scalability in compressed sensing and deep learning

There is a tremendous demand for increasingly efficient ways of both capturing and processing high-dimensional datasets of large size. When capturing such datasets, a promising recent trend has developed based on the recognition that, many high-dimensional datasets have low-dimensional structures. For example, the notion of sparsity is a requisite in the compressed sensing (CS) field, which allows for accurate signal reconstruction from subNyquist sampled measurements given certain conditions. When processing such datasets, the recently developed deep learning is a powerful tool, able to extract high-level and complex abstractions from massive amounts of data. CS has a wide range of applications that include imaging, radar and many more. Much effort has been put on developing more accurate and efficient reconstruction algorithms. In this thesis, first, we are interested in how to incorporate the side information into CS reconstruction when there is an initial estimation of the sparse signal available from other sources. Rigorous theoretical analysis was proposed for the first time in this field. Sufficient number of measurements is required for accurate CS reconstruction. We may have to wait for a long time to do the reconstruction until we receive enough measurements, which could incur undesired delays. Moreover, state-of-the-art CS reconstruction algorithms are still inefficient for signals of large size, e.g., images. Inspired by the multi-resolution or scalable reconstruction in multimedia transmission, such as JPEG 2000 and H.264/SVC, in the second part of this thesis, we analyzed scalable CS reconstruction problem and proposed to reconstruct a low-resolution signal if the number of measurements is too small. Deep learning or deep neural networks (DNNs) has evolved into the state-of-the-art technique for many artificial intelligence tasks including computer vision, speech recognition and natural language processing. However, DNNs generally involve many layers with millions of parameters, making them difficult to be deployed and updated on devices with limited resources such as mobile phones and other smart embedded systems. Moreover, if the DNN needs to be updated, usually via wireless communications, downloading the large amount of network parameters will cause excessive delay. In the final part of this thesis, we propose a scalable representation of the network parameters, so that different applications can select the most suitable bit rate of the network based on their own storage constraints.
Does distance matter? Examining the distance effect on tourists’ multi-attraction travel behaviors

ABSTRACT The purpose of this study was to examine the difference in the multi-attraction travel behavior patterns of short-haul and long-haul tourists in Incheon, South Korea. A network t-test analysis and normalized centrality analysis were employed to achieve the purpose. The finding confirmed significant differences between the multi-attraction travel patterns of short-haul and long-haul tourists. Geographic distance played an important role in determining the order of the top-ranking attractions within a multi-destssssination travel network. Since attractions with high centrality scores are comparatively more influential, they are important and competitive in attraction development and marketing. Implications for future studies were also suggested.
A Study on Differential Private Online Learning

Online learning algorithms are very attractive, in which iterations are applied efficiently instead of solving some optimization problems. In this paper, online learning with protecting privacy is considered. A perturbation term is added into the classical online algorithms to obtain the differential privacy property. Firstly the distribution for the perturbation term is deduced, and then an error analysis for the new algorithms is performed, which shows the convergence and learning rate. From the error analysis, a choice for the parameters for differential privacy can be found theoretically.
Zur Logik und Theorie der Makroorganisation der Verwaltung

Zusammenfassung Die Makroorganisation der Verwaltung, d.h. die Behordenzahl und die Behordenbeziehungen, wandelt sich standig, aber nur ein Bruchteil dieser Veranderungen wurde bisher auch einer verwaltungswissenschaftlichen Analyse unterzogen. Ublich war insofern die selektive Betrachtung einzelner makroorganisatorischer Phanomene, wie etwa die Zusammenlegung von Landratsamtern oder die Ausgrundung von verselbststandigten Bundesoberbehorden. Die dadurch jeweils entstehenden Perspektivverengungen versucht der vorliegende Artikel aufzubrechen, indem die grundsatzlichen, fallunabhangigen und ebenenubergreifenden Logiken der Makroorganisation der Verwaltung aufgedeckt werden. So sollen der theoretische Rahmen, der Forschungsstand und die Forschungsdesiderata in diesem Bereich benannt werden, um Perspektiven fur eine integrierende verwaltungswissenschaftliche Forschung in diesem Bereich zu erhalten. Schlagworte: Makroorganisation, Auserer Aufbau, Agencification, Dezentralisierung, Territorial- und Funktionalreformen ----- On the logic and theory of the macro-organization of public administration Abstract The macro-organization of public administration, i.e. the number of administrative units and the relationship between them, is constantly changing. However up to now, only a small percentage of these reforms has been subject to scientific scrutiny. Usually, a selective analysis of singular reform events is being conducted, for example the amalgamation of local administrations or the agencification of non-ministerial government departments. This article tries to overcome these limited views by uncovering the basic and fundamental logic of the macro-organization of public administration. Therefore, the theoretical framework, the state of research and the research gaps are identified to establish an integrated administrative science perspective on this research area. Keywords: macro-organization, public administration, administrative reforms, agencification, amalgamation, decentralization ----- Bibliographie: Richter, Philipp: Zur Logik und Theorie der Makroorganisation der Verwaltung, dms, 2-2016, S. 231-251. https://doi.org/10.3224/dms.v9i2. 26344
A Dynamic Panel Data Analysis for Relationship between Energy Consumption, Financial Development and Economic Growth

The purpose of this work is to investigate the cointegration and Granger causal relationship between economic growth and total energy consumption as well as the relationship between economic growth and financial development in the MENA region by using a panel data analysis the period over 2000-2018. Different from limited existing provincial studies on the MENA region, an advanced panel econometric methodologies such as dynamic Panel data techniques consider the question of the energy use-economic growth-financial development nexus. Our results suggest that energy consumption exerts a positive and significant impact on economic growth. Furthermore a positive relationship between financial development and economic growth was detected. Thereby it is important to examine the causal effects of both the total energy use and the financial system before local governments make specific energy and economic policies.
Relación riesgo-rendimiento en las acciones del sector industrial de la BMV en los actuales cambios geopolíticos. | Risk-return relationship in the shares of the industrial sector of the BMV in the current geopolitical changes

La teoria financiera asume una correlacion positiva en la relacion riesgo-rendimiento. En 2017 EUA modifica su interaccion con el mundo en todos los ambitos y se evalua la participacion del sector industrial de Mexico-EUA-Canada. En esta investigacion se analiza la relacion riesgo-rendimiento de los precios de las acciones del sector industrial de la Bolsa Mexicana de Valores durante 2006-2016 versus el 2017 considerado ano de cambios geopoliticos, se estudio 14,300 correlaciones semanales de relacion riesgo-rendimiento. Se encontro que existen companias con correlacion negativa de relacion riesgo-rendimiento y los resultados del analisis estadistico de varianza (ANOVA) demostraron que solo en algunos meses del 2017 se modifico la relacion riesgo-rendimiento y que cada subsector del sector industrial mantiene diferentes valores de riesgo-rendimiento. Abstract Given that during the year 2017 the United States (USA) modified its interaction with the world, it is considered relevant and relevant to the participation of the industrial sector of Mexico-US-Canada. This article is based on an investigation carried out by the authors in which 14,300 weekly risk-return correlations will be analyzed, in order to determine their relationship with the prices of the industrial sector shares of the Mexican Stock Exchange. The results of said statistical analysis of variance (ANOVA) showed that only in some months of 2017 the risk-performance ratio was modified and that each sub-sector of the industrial sector with different values. Likewise, if the financial theory assumes a positive relationship in the risk-return relationship, it has been detected that there are relationships with negative correlation.
Foreign aid, the mining sector and democratic ownership: The case of Canadian assistance to Peru

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. © 2019 The Authors Development Policy Review published by John Wiley & Sons Ltd on behalf of Overseas Development Institute Professor, School of Political Studies, University of Ottawa
Identificación de influyentes en twitter a través del análisis textual y la elaboración de grafos

Las redes sociales digitales se han vuelto imprescindibles en la participacion social y politica creando espacios que se contraponen a los ya tradicionales medios de comunicacion. En este articulo se presentan los resultados de la investigacion realizada a partir de la extraccion de un gran volumen de datos del caso UBER en Mexico. La investigacion sobre el fenomeno #UberSeQueda aborda distintos aspectos en el que la transparencia y la democratizacion de la informacion son el resultado del uso de Twitter. En este articulo se aplica un proceso computacional para extraer actores influyentes a partir de los mensajes enviados. La metodologia utilizada se base en estudios que analizan las redes complejas explorando la interdisciplinariedad entre la Computacion y las Humanidades para detectar actores influyentes. Se concluye, a partir del uso de grafos, que la preponderancia de los actores involucrados en un movimiento social basado en las redes sociales cambia constantemente en cortos lapsos de tiempo y que es necesaria la combinacion de metodos que involucren tanto el perfil del usuario como el contexto actual. Palabra(s) Clave(s): analisis de redes sociales, grafos, actores influyentes, interdisciplina.
Monetary Policy Transmission to Consumer Financial Stress and Durable Consumption

We examine the effects of monetary policy on household self-assessed financial stress and durable consumption using panel data from eighteen annual waves of the British Household Panel Survey. For identification, we exploit random variation in household exposure to interest rates generated by the random timing of household interview dates with respect to policy rate changes. After accounting for household and month-year-of-interview fixed effects, we uncover significant heterogeneities in the way monetary policy affects household groups that differ in housing and saving status. In particular, an increase in the interest rate induces financial stress among mortgagors and renters, while it lessens financial stress of savers. We find symmetric effects on durable consumption, mainly driven by mortgagors with high debt burden or limited access to liquidity and younger renters who are prospective home buyers.
Agricultural and rural transformations in Asian development

Over the past sixty years, most Asian countries have undergone relatively rapid agricultural transformations that helped jumpstart broader economic development. However, the changes have differed markedly in nature and speed across countries of the region.In much of East and Southeast Asia, the Green Revolution brought a quantum leap in yields of staple crops. Agricultural productivity growth facilitated labour exit and savings transfers, which helped jumpstart industrial growth and urbanization, which in turn induced deeper agrarian change and food system transformations.In South Asia, these transformative changes have lagged in part because of structural hurdles to agrarian change signalled by Gunnar Myrdal in his seminal book Asian Drama of 1968. More recently, South Asian economies also managed to overcome most of those obstacles, inducing accelerated growth of both agriculture and non-agricultural sectors.Vast challenges of still widespread poverty and food insecurity in this part of Asia remain. These challenges remain in a context of relatively advanced urbanization, strongly changed dietary patterns and agri-food systems, and pressing environmental constraints.Consequently, as this paper argues, moving forward, the role and nature of agricultural transformations and structural change in forging economic growth and poverty reduction in still disadvantaged regions of Asia will need to be different as well.
Privacy Preserving Independent Component Analysis (The 8th Workshop on Stochastic Numerics)

Privacy Preserving Data Mining is the methodology used to discover knowledge of distributed databases with providing guarantees concerning the non-disclosure of the data. We will propose the Privacy Preserving Independent Component Analysis (PPICA) in order to conduct ICA in a privacy preserving manner. The proposed method can compute a separating matrix in order to re-construct sources from all databases without disclosing the data of each database to others. Although the issue in PPICA is the signiﬁcant communication traﬃc, the proposed method overcome this and has property equivalent to low communication traﬃc. We assume that the database is horizontally partitioned, whereby each database has the same attributes in common for diﬀerent samples.
Automatic detection of learner-style for adaptive eLearning

The advent of modern wireless technologies has seen a shift in focus towards the design and development of educational systems for deployment through mobile devices. The use of mobile phones, tablets and Personal Digital Assistants (PDAs) is steadily growing across the educational sector as a whole. Mobile learning (mLearning) systems developed for deployment on such devices hold great significance for the future of education. However, mLearning systems must be built around the particular learner’s needs based on both their motivation to learn and subsequent learning outcomes. This thesis investigates how biometric technologies, in particular accelerometer and eye-tracking technologies, could effectively be employed within the development of mobile learning systems to facilitate the needs of individual learners. The creation of personalised learning environments must enable the achievement of improved learning outcomes for users, particularly at an individual level. Therefore consideration is given to individual learning-style differences within the electronic learning (eLearning) space. The overall area of eLearning is considered and areas such as biometric technology and educational psychology are explored for the development of personalised educational systems. This thesis explains the basis of the author’s hypotheses and presents the results of several studies carried out throughout the PhD research period. These results show that both accelerometer and eye-tracking technologies can be employed as an Human Computer Interaction (HCI) method in the detection of student learning-styles to facilitate the provision of automatically adapted eLearning spaces. Finally the author provides recommendations for developers in the creation of adaptive mobile learning systems through the employment of biometric technology as a user interaction tool within mLearning applications. Further research paths are identified and a roadmap for future of research in this area is defined.