Miracle-dz/UniFAR-FTUs huggingface dataset:
2010 Kraljevo Earthquake Recovery Process Metrics Derived from Recorded Reconstruction Data

Earthquake resilience starts with a sudden drop of performance when an earthquake strikes followed by a relatively long recovery phase. The dynamics and volume of investment directly affect the rate and level of recovery. In this paper, the recovery process of the city of Kraljevo, Serbia following the M5.4 November 3, 2010 Kraljevo earthquake is analyzed. The base for this analysis is recorded reconstruction data that includes building types, damage states, damage survey dates, repair methods, and repair design, permit, and completion dates. Tracking the rate of building re-occupation and the rate of investment in repairs during the recovery process made it possible to construct empirical housing resilience curves for a community of about 70,000 people. The recorded data also provides insights into the reasons for different recovery rates for different building types and damages states, as well as a basis to evaluate the housing recovery management process and identify the significant influence of the reconstruction funding volume and rate on the sequencing, design and construction of the post-earthquake repairs. A comparison between the housing recovery after the 2010 Kraljevo and the 2009 Yunnan earthquakes shows significant simulates, pointing to the need to further improve, optimize and standardize post-earthquake housing recovery strategies worldwide.
A Survey on Recognition of Offline Handwritten Words

Handwritten Word Recognition (HWR) is one of the attractive and challenging research areas in the field of pattern recognition. Pattern recognition is a type of machine learning it focus on recognizing the pattern and regularities in the data. HWR is challenging task as there is no constraint on human handwritten style, size, variation in angle and shape of the letters. As opposed to the character recognition in which each character in each word is recognized, in HWR each word is treated as individual entity and recognizes the word from the overall shape. HWR are used in document verification, forensic science, historical manuscript etc. This paper survey of the major works on offline handwritten word recognition with the various filters, classifiers along with their corresponding performance. Major works done in English, Arabic, Hindi and other scripts are addressed in this paper.
Are Foreign Investors Attracted to Politically Connected Firms

This research investigates whether 2014 Indonesia Presidential election, as an opportunity to examine political connection, could give any benefit/loss in terms of foreign investment – given the candidates were equally powerful. Based on the objective mentioned, this research analyzes the relationship between politically connected firms in Indonesia and their foreign share ownerships in one-year period (December 30, 2014 to December 31, 2014). This time bound is selected to represent the time before and after Jokowi-Prabowo 2014 presidential election. Politically connected firms in this research are divided into politically connected winning firms (Jokowi’s party) and politically connected losing firms (Prabowo’s party). In addition, this research also measures the effects of ownership structure, performance, size, and market value of the firms to foreign share ownership. Our findings show that politically winning firms have attracted foreign share ownership. However, it depends on the perspective of the investor (individual or institutional) and with whom the firm is connected. In 2014 Presidential election, where Jokowi was elected as the president, a firm where its board/shareholder is a parliament member of winning party impacts most on attracting foreign investment.
Seismic Wave Propagation for Complex Rheologies

Seismic waves are produced whenever a large amount of energy is released under the surface of the Earth, for example when earthquakes occur. Such waves are perturbed by the heterogeneities they find in their travel through the subsurface, from hypocenter to seismometer. In the last decades, the increase in computational power has made it possible to simulate the propagation of seismic waves in fully 3D heterogeneous media. However, the subsoil often displays very complicated geometrical structures which are difficult to nest by nowadays simulation methods. The ADER-DG (Arbitrary high-order DERivatives Discontinuous Galerkin) method provides the means to better represent subsoil geological structures using tetrahedral meshes. Such meshes can be easily deformed and adapted to very complicated geometries such as folded layers, faults and shallow basins. In this book the ADER-DG method is developed for problems of elastodynamics and further extended to accommodate anisotropic, viscoelastic and poroelastic rheologies. For all cases examples are provided to verify the fast convergence properties and to show the precision of the synthetic seismograms computed.
Self-Efficacy, Scientific Reasoning, and Learning Achievement in the STEM Project-Based Learning Literature

The main goal of education is to prepare students for future job opportunities and civic responsibilities, and this is one of the biggest challenges in the 21st century. Science, Technology, Engineering, and Mathematics (STEM) Project-Based Learning (PjBL) prepare students to master their new role as a global citizen with greater responsibilities. This systematic review analyzed 265 papers that are related to the STEM PjBL. The papers were collected from well-known databases such as Web of Science® and SCOPUS by using the quality assessment and relevant criteria. This study inspected the top 48 distinguished papers by covering three dimensions, Search result, Subject, and Research methodology. STEM and PjBL come together, due to the natural overlap between the fields of Science, Technology, Engineering, Mathematics and PjBL. The fully integrated STEM with PjBL can increase the effectiveness of teaching. Nonetheless, this inspection uncovered that previous research has not fully integrated STEM with PjBL. Thus, despite the wealth of existing research, there are still significant opportunities for future research on STEM PjBL in high schools to prepare students for 21st century challenges. Keywords: Enhanced teaching and learning, 21 st century skills, project-based learning STEM, systematic literature reviews Cite as: Jamali, S.M. , Md Zain, A.N. , Samsudin, M.A., & Ebrahim, N.A. (2017). Self-efficacy, scientific reasoning, and learning achievement in the STEM project-based learning literature. Journal of Nusantara Studies, 2 (2), 29-43. http://dx.doi. org/10.24200/jonus.vol2iss2pp29-43
Modelling Exchange Rate Volatility of Kenya’s Top Five Trade Partners Research Report in Mathematics,number 15, 2018

The world has become a global village and trade among countries has also become inevitable. Since most countries use their own domestic currencies, how much of one currency should be exchanged for another has slowly become a big issue. As a result of this exchange rate and exchange rate volatility has become a topic of interest among traders, Investors and other stakeholders. This research papers seeks to nd the best GARCH family of models that ts into the top ve Kenya’s trading partners currencies, which are USD, EUR, GBP, JPY and UGX and also checks whether there is co-integration in the trade volume data in USD which accounts for over 60 percent of Kenya’s imports and exports. The data used for both the exchange and trade volume span from January 2005 to December 2017. The results show that GARCH(1,2) ts KES/USD data and KES/GBP while GARCH(2,2) tted KES/EUR , KES /JPY and UGX/KES. The test for co-integration in the trade volume data showed that there is a co-integrating relationship in the trade volume data and hence conventional statistical analysis is unsuitable for this kind of data. Master Thesis in Mathematics at the University of Nairobi, Kenya. ISSN 2410-1397: Research Report in Mathematics ©Gichuhi George Gikunju, 2018 DISTRIBUTOR: School of Mathematics, University of Nairobi, Kenya
The Fulfillment of the Biblical Statement “Vanity of Vanities! All is Vanity” Through the Portrayal of Two Characters in Armah's the Beautyful Ones Are Not Yet Born

After the five basic needs, Man usually seeks power. This quest takes diverse forms namely financial, material, political and social to name just a few. Once it is got, the use may raise problems or difficulties that nobody mainly the holder has ever thought of. Here, it depends on how it is used. Power can be used properly by serving one's fellows. Whether used properly or not, Man's power ends on this earth. In this vein, in order to build a good reputation and or personality of oneself on this earth and after death, one has to use one's power in a good way. This research paper aims at bringing human beings to be aware of the fact that they must account for all their deeds one day or the other, and consequently must think several times before acting or even uttering a single word. If this is known, they must be as modest and honest as possible no matter their power and/or the fields where they operate in order to contribute to the promotion of their community and as such the development of their country. The study has highlighted the failure of Koomson who has misused his power in The Beautiful Ones Are Not Yet Born by Armah on the one hand and the rehabilitation of the man who has always been modest and honest on the other and each of them rewarded accordingly. Otherwise, it has proved that men have always accounted and will always account for their deeds and therefore ripe their fruits accordingly. It has also shown that Armah has been both a novelist and a teacher through the evolution of both characters under study. In order to efficiently explore the topic, I have used the theories of characterization and qualitative.
A New Text Clustering Method Based on KGA

Text clustering is one of the key research areas in data mining. K-medoids is a classical partitioning algorithm, which can better solve the isolated point problem, but it often converges to local optimization. In this paper, we put forward a new genetic algorithm called KGA algorithm by putting k-medoids into the genetic algorithm, then we form a local Optimal Solution with multiple initial species group, strategy for crossover within a species group and crossover among species groups, using the mutation threshold to control mutation. This algorithm will increase the diversity of species group and enhance the optimization capability of genetic algorithm, thus improve the accuracy of clustering and the capacity of acquiring isolated points.
Constructing and Evaluating a Churn Prediction Model using Classification of User Types in MMORPG

Massively Multiplayer Online Role Playing Games (MMORPG) have been the most enjoyed genre of games by users all over the world, because of the many enjoyable contents they provide. However, there still are some users leaving MMORPG, in spite of the various contents. Because the users, who are constantly engaged in a game, are directly connected to the profit of the game company, it is necessary to study churn prediction. In this study, we propose a churn prediction method based on the user types. Using actual MMORPG data, we define “Churn Users” and categorize users into 5 types by means of the clustering algorithm. The experiment shows that about 98.3% of the churn users are the “Light user type”. We then use user types as a feature and construct a churn prediction model with various machine learning algorithms. The churn prediction model shows a maximum accuracy of 85.7% and an F-measure of 72.3%.
Analysis of Growth

Unlike the standard cross-country growth regressions that focus on the long run average growth and hence mask episodes of high and low growth that most of these countries experience, this paper follows the recent literature and examine growth episodes in SSA countries. This new approach applied enable us identify years of growth accelerations and episodes which were sustained over the medium and long-term. More specifically, utilizing the Penn World Data Tables (version 6.2), the study follows the diagnostic or two-pronged strategy of Rodrik (2005a and 2005b), which focuses on the particular constraints that prevent a given country from growing faster. In the latter part, we analyze the impact of growth on income poverty and inequality in selected countries drawing on available household survey data published by the World Bank in its Global Poverty Monitoring Database.To establish correlation between growth episodes(all accelerations and sustained ones) and policy variables, institutional variables and geographic factors, we estimate alternative limited dependant variable models. The results show that variables affect these two growth episodes differently.
SISTEM REKOMENDASI ARTIKEL BERITA MENGGUNAKAN METODE KNEAREST NEIGHBOR BERBASIS WEBSITE

Based on data from the Ministry of Communication and Informatics (KOMINFO) in 2014 the number of internet users in Indonesia reached 88.3 million people. The figure puts Indonesia in the 6th position of internet users worldwide. It shows people have been using the internet in everyday life. The number of visitors on news websites can be utilized by managers and developers of a news site to attract visitors and access longer. Because based on statistics, webiste is often visited in Indonesia based alexa site is a search engine like google or yahoo and also social media like facebook. While the news site is Detik.com which ranks 9th. One way is to build a system of article recommender recommendations on a relevant website for users or visitors to obtain information. The goal of this recommendation system is also the owner of the website, so that website traffic and visitor statistics can go up so it can profit from managing the website. the accuracy of the error value in making the news recommendation system using K-nearest Neigbor method is 14%.
Mejora del acceso a Infoleg mediante técnicas de procesamiento automático del lenguaje

Resumen En este art́ıculo presentamos una aproximación para la detección Automática de Entidades en textos legales, y su aplicación al corpus InfoLeg. La aproximación se basa en diversas técnicas de Extracción de Información, entre ellas Aprendizaje Automático a partir de ejemplos y reglas creadas manualmente. Presentamos un análisis de los diferentes tipos de entidades que se encuentran en los textos, sus realizaciones lingǘısticas y sus dificultades para el análisis automático. El diseño de la solución se basa en las dificultades propias de estas entidades. En la fase actual de desarrollo de la aproximación hemos anotado manualmente una porción del corpus y hemos desarrollado reglas para anotar casos sencillos automáticamente. Hemos entrenado y evaluado una aproximación basada en aprendizaje automático para casos sencillos, con resultados muy prometedores.
Verwendung von Krankenhausabrechnungsdaten für die Versorgungsforschung in Deutschland

In Germany, the introduction of a reimbursement system for inpatient services based on Diagnosis Related Groups (DRG) provided the availability of comprehensive medical information in hospital administrative data. As this system includes all patients and all payers the national DRG data represent a complete registry of inpatient episodes in German acute care hospitals. The German national DRG database is available for research purposes. As these data illustrate hospital care under real-world conditions without additional data collection efforts their availability provides new opportunities for health services research in Germany. However, significance and reliability of analyses based on administrative hospital data crucially depend on accurate operationalization of the research question considering the available data fields and the context of data collection. Within the present cumulative dissertation the characteristics of the German DRG data are described. Examples for health services research based on these data are given by three published papers. By analyzing hospital care for stroke patients the first paper demonstrates how DRG data can be used to illustrate burden and quality of care. The second paper gives an example for the evaluation of changes within the health care system by analyzing the impact of financing of stroke units on the provision of this service by hospitals and changes in in-hospital mortality of stroke patients after stroke unit implementation. The third paper aimed to assess the development of data quality over time by studying trends in secondary diagnosis coding and the consequent implications for research based on administrative hospital data. These papers demonstrate that the nationwide German DRG data are an important data source and provide numerous opportunities for health services research in Germany. Since these data are available for several years they can be used to study temporal trends, e.g. regarding the spread of new treatment options. Moreover, analyses of these data help to indicate potential for health care improvement. The strength of the German DRG data is their completeness. Thus, analyses of these data are population-based. Due to uniform regulations for coding patterns of hospital care can be reliably illustrated. However, similar to other data sources used for health services research the German DRG data have specific characteristics and limitations, which have to be considered within the study design, as well as within the interpretation and discussion of study results.
Alberta School Principals' Use of Professional Portfolios in Teacher Hiring.

Creating a professional portfolio is a requirement for most pre-service teachers in Alberta. Little is known, however, about principals’ use of applicant portfolios in hiring. In response, researchers conducted an online survey of principals throughout the province. Findings indicate a preference for traditional job application items (e.g., a resume, reference letters, and letter of introduction) and teacher competence indicators (e.g., teacher mentor and school administrator assessments, student assessment methods, and a classroom management plan). Examining attitudes and hiring practices provides direction for creating portfolios that attend to the actual needs and interests of principals in the province, thereby enhancing the employment prospects of new teachers.
Onderzoek in het onderwijs van de Hogeschool van Amsterdam : op weg naar diversiteit in een uniform model

Onderzoek maakt een steeds prominenter onderdeel uit van het hoger beroepsonderwijs. Dit geldt ook voor de Hogeschool van Amsterdam. Op basis van een bevinding van de visitatiecommissie Onderzoek werkt de Hogeschool van Amsterdam aan een model om de onderdelen van onderzoek in de curricula te kunnen benoemen en onderling te kunnen vergelijken. Dit artikel beschrijft het pad dat gevolgd is om tot een voorlopig model te komen. Ook geeft het een beschrijving van dit model voor ‘inhoud en niveau’ van onderzoek.
Federal and State Advances to Support Grandfamilies

GrAND Voices have been front and center at the nation’s Capitol inspiring law makers to enact reform during an uncertain time. Activity has been frenetic in Washington, with a new Administration, repeated efforts to repeal the Affordable Care Act and several natural disasters demanding attention. Despite distracted law makers, several committed members of Congress have forged ahead on reforms specifically for grandfamilies, thanks in significant part to a new initiative of Generations United and Casey Family Programs, called GrAND Voices. GrAND Voices are caregiver advocates from around the country who elevate their voices, bringing their personal experience raising relatives, in addition to those they work with, to the attention of lawmakers. GrAND Voices were an integral part of the 5 national GrandRally in Washington, D.C., and have inspired new legislation. They have helped elevate the need for supports and services to grandfamilies in light of the opioid crisis and the increased numbers of children they are raising. The crisis has provided an urgent platform for pursuing reforms such as providing preventative services to grandfamilies and implementing the Model Family Foster Home Licensing Standards. Improved foster care data collection and a 2016 federal court case also have implications for those grandfamilies who have child welfare involvement. On the state level, many jurisdictions continue to try to make inroads for grandfamilies by implementing policy changes, such as new guardianship assistance programs. Grandfamilies support is moving in the right direction, albeit slowly.
Paving the Way for Efficient Content Delivery in Mobile Networks

Paving the Way for Efficient Content Delivery in Mobile Networks Chun Pong Lau The flexibility of future mobile networks exploiting modern technologies such as cloud-optimized radio access and software-defined networks opens a gateway to deploying dynamic strategies for live and on-demand content delivery. Traditional live broadcasting systems are spectral inefficient. It takes up a lot more radio spectrum than that of mobile networks, to cover the same size of an area. Furthermore, content caching at base stations reduces network traffic in core networks. However, numerous duplicated copies of contents are still transmitted in the unicast fashion in radio access networks. It consumes valuable radio spectrum and unnecessary energy. Finally, due to the present of numerous mobile receivers with a wide diversity of wireless channels in a base station coverage area, it is a challenge to select a proper modulation scheme for video broadcasting to optimize the quality of services for users. In this thesis, the challenges and the problems in the current strategies for content delivery are addressed. A holistic novel solution is proposed that considers user preferences, user mobility, device-to-device communication, physical-layer resource allocation, and video quality prediction. First, a system-level scheduling framework is introduced to increase the spectral efficiency on broadcasting live contents onto mobile networks. It considers the audience preferences for allocating radio resources spatially and temporally. Second, to reduce the redundant transmissions in radio access networks, a content distribution system that exploits user mobility is proposed that utilizes the urban-scale user mobility and broadcasting nature of wireless communication for delay-tolerant large size 5 content. Third, to further reduce the energy consumption in network infrastructure, a content distribution system that relies on both user mobility, and device-to-device communication is proposed. It leverages the mobile users as content carriers to offload the heavy mobile traffic from network-level onto device-level. Fourth, to mitigate the multi-user channel diversity problem, a cross-layer approach is deployed to increase the video quality for users especially for those who have a low signal-to-noise ratio signal. Finally, data mining techniques are employed to predict video qualities of wireless transmissions over mobile networks. The holistic solution has been empirically developed and evaluated. It achieves high spectral and energy efficiency and mitigates the video quality degradation in mobile networks.