Miracle-dz/UniFAR-FTUs huggingface dataset:
The Legacy of Zellig Harris: Language and information into the 21st century. Volume 1: Philosophy of science, syntax and semantics

Zellig Harris had a profound influence in formal systems and applied mathematics, in demonstrations of the computability of language, and in informatics. Volume 2 begins with a commentary by André Lentin on Harris’s grounding in constructivist, intuitionist mathematics, drawing a parallel between Harris’s central insights and those of Gödel and others which were of like import in the foundations of mathematics. An international array of scholars describe further developments and relate this work to that of others. Fernando Pereira argues that Harrisian ‘linguistic information’ can effect a reunion of linguistics with information theory that has not been considered possible since Chomsky’s declaration of irrelevance in 1957. Chapters by Richard Oehrle and by Terence Langendoen develop two novel formal systems with intriguing properties. Chapters by Naomi Sager and Ngo Thanh Nhan, by Aravind Joshi, and by Stephen Johnson describe the history of work on the computability of language and project exciting prospects ahead. Karel van den Eynde and colleagues describe use of distributional methods, refined beyond those of Harris, to develop comprehensive computer dictionaries for several languages. The chapter by Benoît Habert and Pierre Zweigenbaum surveys the field of automatic acquisition of information categories, and that by Richard Kittredge surveys work on text generation. Richard Smaby shows how distributional analysis can even inform design of computer user interfaces. Current Issues in Linguistic Theory, 229 2002. Hb xx, 312 pp. 90 272 4737 4 EUR 99.00 / 1 58811 247 0 USD 89.00 The Legacy of Zellig Harris
Conceptual Blending of Harmonic Spaces for Creative Melodic Harmonisation

AbstractIn computational creativity, new concepts can be invented through conceptual blending of two independent conceptual spaces. In music, conceptual blending has been primarily used for analysing relations between musical and extra-musical elements in composed music rather than generating new music. This paper presents a probabilistic melodic harmonisation assistant that employs conceptual blending to combine learned, potentially diverse, harmonic idioms and generate new harmonic spaces that can be used to harmonise melodies given by the user. The key feature of this system is the application of creative conceptual blending to the most common chord transitions (pairs of consecutive chords) of two initial harmonic idioms. The proposed methodology integrates newly created blended chords and transitions in a compound probabilistic harmonic space, that preserves combined characteristics from both initial idioms along with those new chords and transitions within a unified setting. This methodology enables .
Testing the Informational Efficiency of OTC Optionson Emerging Market Currencies

This paper analyzes the informational efficiency of OTC currency options on the Czech koruna and the Polish zloty correcting for the volatility risk premium and errors-in-variable problems, using state-of-the-art techniques (Chernov 2001). It finds that these markets are more efficient than mature markets possibly because of higher relative participation of informed dedicated investors, which offset the effects of relative illiquidity and higher transaction costs in these countries. Moreover, implied volatilities generally anticipate the direction of volatility correctly, with a bias to overpredicting volatility increases reflecting one-sided markets.
Automated Data Extraction with Multiple Ontologies

Current search engines require an accurate yet fast automated extractor to extract relevant information from deep web for the users. Human users usually enter search queries and the search engines will then locate the desire information of interest by disambiguate the search query accordingly. The queries will then be passed on to multiple search engines for further processing. These search engines will then return the search results to the main search engine. However, data returned from these search engines are usually varied and presented in numerous formats and layouts. To extract them, we need automated extractor to filter out irrelevant information and locate the correct information. Current trends focused on using ontologies to automatically extract this information with high accuracy. To the best of our knowledge, no works have been made on using multiple ontologies (using many ontology techniques) to automatically extract information from deep webs. In this paper, we demonstrate that multiple ontologies technique can achieve higher accuracy when extracting data from the deep web. Our method outperforms existing state of the art systems and is able to robustly extract data from deep web.
Verificación en Alloy de modelos y metamodelos específicos del dominio

La verificación de modelos de sistemas de software es una actividad clave para mejorar la calidad del producto final. Numerosos lenguajes específicos del dominio han sido creados para favorecer la definición de modelos ajustados a un dominio o área particular. Sin embargo, la verificación de estos modelos, frecuentemente es dejada de lado como actividad complementaria al modelado. Esta línea de investigación, desarrollo e innovación se orienta a generalizar un mecanismo basado en Alloy, para la especificación y verificación de modelos y metamodelos específicos del dominio. Alloy es un lenguaje formal, soportado por una amigable herramienta de verificación y validación. Las características de Alloy pueden ser aprovechadas para establecer un enfoque que permita garantizar la calidad de los modelos de sistemas de software específicos.
Sentiment Analysis of Political Reviews in Punjabi Language

Sentiment Analysis is to distinguish and group the assessments/feelings/opinions in composed content. Till date, English Language incorporates the majority of the examination work around there. In this paper, we talked about the different methodologies used to finish the opinion investigation and exploration work accomplished for Indian Languages like Hindi, Bengali and Telugu. An approach is proposed to determine the sentiment orientation i.e. polarity of the Punjabi reviews by scoring method. Sentiment analysis is needed to be performed in Punjabi language because of the increase in Punjabi data on the web. Separate positive and negative condensed results are created which is useful for the client in choice making. We contrasted the outcomes and right now existing methodologies. General Terms Sentiment Analysis, Punjabi,Political Reviews, Algorithms.
A Study on Anomaly Signal Detection and Management Model using Big Data

APT attack aimed at the interruption of information and communication facilities and important information leakage of companies. it performs an attack using zero-day vulnerabilities, social engineering base on collected information, such as IT infra, business environment, information of employee, for a long period of time. Fragmentary response to cyber threats such as malware signature detection methods can not respond to sophisticated cyber-attacks, such as APT attacks. In this paper, we propose a cyber intrusion detection model for countermeasure of APT attack by utilizing heterogeneous system log into big-data. And it also utilizes that merging pattern-based detection methods and abnormality detection method.
MovieTalk: 25 Years Old and Still Going Strong

Our initial plan was to focus on dialogue, seeking ways to make it more comprehensible for the students. We chose “The African Queen” as our first project. The two of us wrote simplified dialogue and recorded it on an audio cassette, paraphrasing the actors’ lines. Barb spoke the lines of Katharine Hepburn; I used my normal voice for Humphrey Bogart and altered my voice in various ways for the other male actors. We did this for the entire movie. The audio recording was carefully constructed so that it could be played in synchrony with the movie. As readers can imagine, this work took many hours. We field-tested our concept in two low-level oral skills classes. Our procedure was to show the movie in short segments, each played twice: first with the movie sound on, then with the movie silent and the simplified dialogue tape playing. During the repetition, we narrated the scenes whenever there was no dialogue. The students thought this was all a bit strange, but they seemed to like it, and their listening comprehension did improve noticeably. Although this field test was somewhat encouraging, we had already realized that the amount of labor required to prepare and use the dialogue tapes was prohibitive. Furthermore, by this time it had dawned on us that our narrations were providing vastly greater amounts of comprehensible input than the dialogue could give. Every language teacher knows how useful pictures can be in illustrating the meanings of new words. A movie contains thousands of pictures (frames) that illustrate many nouns, verbs, and adjectives. When we narrate a movie scene in clear, simple language, while pointing to various parts of the picture, we are providing
A.R. Luria’s cultural neuropsychology in the 21st century

Luria has long been one of the most influential authors in cognitive neurosciences, in particular in neuropsychology. New scientific advances and clinical observations have confirmed many of his proposals and hypotheses. In this paper one of his major ideas is analyzed: the influence of cultural factors on human cognition. The systemic-dynamic Lurian analysis of brain activity is based on Vygotsky's concept of higher mental functions, which are social in origin and complex and dynamic in their structure. Higher mental functions are based on a complex system of operations and means both external and internal. Living conditions and hence cultural characteristics have dramatically changed during the last half century with the development of new media and new virtual ways of communication. Review of contemporary developments supporting the appropriateness and usefulness of these concepts is presented. It is finally concluded that Luria is one of the major founders of contemporary neuropsychology not only from the clinical point of view, but also from the cultural perspective. His influence has continued undiminished during the 21st century.
A new data preprocessing method for 3D reconstruction of pavement

ABSTRACT Three-dimensional (3D) reconstruction of pavement surface based on the laser scanning can be used to extract the elevation information for evaluating the damage degree of the pavement. This technology is of great significance to road safety as well as the advances of smart transportation. The preprocessing procedures of the laser-scanned point cloud serve as the basis for accurate surface reconstruction, which includes outlier removal, smoothing and sampling. In view of the limitations of the existing preprocessing methods for pavement applications, this paper proposes a new preprocessing method. First, a local density-based outlier removal algorithm is used to solve the problem of poor adaptability or long computation time of the regular outlier removal algorithms. And then, a continuous algorithm based on the moving least squares method is used to smooth and sample the points, solving the problem of repeated degradation of the data. Finally, the field tests on three types of pavements are carried out to verify the feasibility of the proposed preprocessing method. The accuracy of the reconstructed surfaces of the pavements is improved by the new preprocessing method.
Information Dissemination in WSNs Applied to Physical Phenomena Tracking

— Several works suggest the use of wireless sensor networks to manage crisis situations. An example of such scenarios is forest fire fighting. In these situations, it is necessary to use efficient mechanisms for disseminating the environmental information captured by sensors. This paper analyzes the behavior of some representative broadcasting techniques when they are used to disseminate to the entire network the occurrence of multiple simultaneous events. The performance evaluation carried out shows that a moderate resource consumption in network devices can reduce the operation overhead.
Application of the BP Neural Network Based on PSO in Dynamic Gesture Recognition

In order to improve the training speed and identification accuracy of dynamic gesture,a method of gesture recognition based on the particle swarm optimization(PSO) BP neural network is put forward.First,a set of dynamic gestures is defined for Human-Machine Interaction(HMI). The engenvectors vectors of dynamic gestures are extracted as the input of the BP neural network on the basis of obtaining the trajectories of moving fingertips.An improved PSO algorithm is used to train the BP neural network and get the weights/thresholds of the network.Finally,the gestures based on machine vision are recognized through the trained BP neural network.The experimental results show that the proposed PSO algorithm can enhance the speed and precision of network training,and improve the accuracy of dynamic gesture recognition.
Does the IASB know the needs of SMEs? A comparative analysis between the IFRS for SMEs and full IFRS due processes

Our research contributes to the limited literature on lobbying in accounting standards for SMEs by analysing all comment letters in the due process for the IFRS for SMEs (from 2004 to 2012) and comparing them to all of the 97 IASB’s projects related to full IFRS during the same period of time. Results confirm that the participation of preparers is significantly lower in the international accounting standardisation process for SMEs. Although this reduced participation is compensated by a higher participation of auditors, results also reveal that auditors do not match the interests of preparers in the case of the IFRS for SMEs. In conclusion, the IASB finds a limitation of the Institutional Theory (Meyer and Rowan, 1977) in the case of the IFRS for SMEs, drawing attention to the need of IASB for conducting further analysis about the real preferences, not only of specific users of the SMEs’ financial information, but also of SMEs. We finally suggest the relevance of the analysis of the needs of SMEs in developing countries, in line with the pronouncements of UNCTAD (2003). Nuestra investigación contribuye a la reducida literatura sobre ‘lobbying’ en la NIIF para las PYMES al analizar todas las cartas de comentario en el ‘due process’ (entre 2004 y 2012) y compararlas con los 97 proyectos las NIIF completas relacionados con las NIIF completas durante el mismo período de tiempo. Los resultados confirman que la participación de los preparadores es significativamente menor en el proceso de normalización contable internacional para las PYMES. Si bien esta participación reducida se ve compensada por una mayor participación de los auditores, los resultados también revelan que los auditores no coinciden con los intereses de los preparadores en el caso de las NIIF para las PYMES. En conclusión, el IASB encuentra una limitación de la Teoría Institucional (Meyer y Rowan, 1977) en el caso de la NIIF para las PYMES, llamando la atención sobre la necesidad de que el IASB realice análisis adicionales sobre las necesidades reales, no solo de usuarios específicos de la información financiera emitida por las PYMES, sino también de las propias PYMES. Finalmente, sugerimos análisis adicionales de las necesidades de las PYMES en los países en desarrollo, en línea con los pronunciamientos de la UNCTAD (2003).
Issue Tracking Systems

Existuje mnoho aplikaci zaměřených na efektivni řizeni a sledovani životniho cyklu projektů, ukolů a požadavků v organizaci. Cilem prace je podat přehledný uvod do světa těchto aplikaci a představit v soucasnosti nejvyuživanějsi řeseni. Dale by cilem prace mělo být vyvinuti zasuvneho modulu (plug-inu) do vývojoveho prostředi NetBeans IDE, který by v něm usnadnil použiti systemu pro řizeni a spravu ukolů a požadavků v projektu JIRA.
Data access pattern protection in cloud storage

Cloud-based storage service has been popular nowadays. Due to the convenience and unprecedent cost-effectiveness, more and more individuals and organizations have utilized cloud storage servers to host their data. However, because of security and privacy concerns, not all data can be outsourced without reservation. The concerns are rooted from the users’ loss of data control from their hands to the cloud servers’ premise and the infeasibility for them to fully trust the cloud servers. The cloud servers can be compromised by hackers, and they themselves may not be fully trustable. As found by Islam et. al. [39], data encryption alone is not sufficient. The server is still able to infer private information from the user’s access pattern. Furthermore, it is possible for an attacker to use the access pattern information to construct the data query and infer the plaintext of the data. Therefore, Oblivious RAMs (ORAM) have been proposed to allow a user to access the exported data while preserving user’s data access pattern. In recent years, interests in ORAM research have increased, and many ORAM constructions have been proposed to improve the performance in terms of the communication cost between the user and the server, the storage costs at the server and the user, and the computational costs at the server and the user. However, the practicality of the existing ORAM constructions is still questionable: Firstly, in spite of the improvement in performance, the existing ORAM constructions still require either large bandwidth consumption or storage capacity. Secondly, these ORAM constructions all assume a single user mode, which has limited the application to more general, multiple user scenarios.
A Theory of Enterprise Risk Management

Purpose The purpose of this paper is to develop a theory of enterprise risk management (ERM). Design/methodology/approach The method is to develop a theory for ERM based on identifying the general risk management problems that it is supposed to solve and to apply the principle of deduction based on these premises. Findings ERM consists of risk governance, which is a set of mechanisms that deals with the agency problem of risk management and risk aggregation, which is a set of mechanisms that deals with the information problem of risk management. Research limitations/implications The theory, by identifying the central role of the Board of Directors, encourages further research into the capabilities and incentives of directors as determinants of ERM adoption. It also encourages research into how ERM adoption depends on proxies for agency problems of risk management, such as a decentralized company structure. Practical implications The theory encourages Boards of Directors to focus on understanding where the under and over management of risk are likely to be greatest, as opposed to the current practice of mapping a large number of risk factors. Originality/value The theory complements existing theory on corporate risk management, which revolves around the role of external frictions, by focusing on internal frictions in the firm that prevent effective risk management. It is the first work to delineate ERM vis-a-vis existing risk theory.
Supplier Selection Model using Game Theoretical Approach

-The purchasing function has gained importance in supplier selection of procurement. As the evaluation of the supplier depends on various non-price attributes, formulating the strategy is very important. Every supplier tries to play tactical game in order to win the contract under uncertain situations. In our paper we propose a model through case study to select best supplier using game theoretical approach by applying simplex algorithm.
A holistic approach towards Information and Communication Technology (ICT) for addressing education challenges in Asia and the Pacific

Abstract Information and Communication Technology (ICT) offers opportunities for governments to address key education challenges of quality, equity, and efficiency. While governments and educational institutions in developed countries may have taken up these opportunities, many developing countries in Asia and the Pacific region have often missed them out. This may be due to countries’ socioeconomic settings, approaches towards design and implementation of the ICT in education plan, and investment on research and development of ICT in education. This paper explores the current challenges of education in Asia and the Pacific and explains how these challenges may be overcome by the strategic use of ICTs when a holistic approach towards ICT in education is adopted.
Unpacking Stickiness: Categorizing User Inputs and Knowledge for Innovation

Firms are increasingly involving their customers in their innovation processes. Customers co-develop products, provide feedback, and provide specific problemand solution-based customer knowledge. This phenomenon has been extensively studied in the user innovation literature from a user-centric perspective. Less attention is paid to examining the micro-foundations of how firms use user knowledge to generate innovative outcomes. We offer a starting point to addressing this issue, by categorizing user inputs grounded on the knowledge characteristics of embedded user knowledge and innovation dimensions of the outcomes. Categorizing user inputs can provide a clearer indication of the user knowledge that firms can access, transfer, and utilize throughout the user innovation process. We systematically review the user innovation literature and apply a knowledge management and micro-foundations perspectives to propose four categories of user inputs with varying knowledge characteristics. The review enables the identification of a range of practices and issues for transferring user knowledge that forms the micro-foundations of user innovation phenomenon.
Opinion Detection in Thai Political News Columns Based on Subjectivity Analysis

News columns are opinionated contents in newspapers such as editorials where columnists usually express their opinion and taking side explicitly with issues in the society. While this is normal in democratic society, in some places where journalism is often lack of, this bias could encourage rifts and polarity, especially in delicate issues such as politics. With such concern in mind, in this paper, we propose an opinion mining framework for detecting opinions in Thai political news columns. Our goal is to construct an information filtering model for monitoring highly-opinionated news content. Findings provided in this paper included our primarily result and discussion about difficulties found in applying opinion mining in Thai, as well as our analysis. In our work, contents from Thai news columns, annotated at sentence level by human experts, are used as training dataset to build a model in which various classifiers and feature selection techniques have been experimented. The best result is achieved by Multinomial Naive Bayes with prior-knowledge based feature selection. The Precision, Recall, and F-Measure are equal to 0.809, 0.804, and 0.803 respectively.
Interest Rate Determination in Lebanon

This paper seeks to understand how interest rates are formed in Lebanon, by focusing on the pass-through from benchmark rates, prevailing liquidity conditions, and the main characteristics of the Lebanese economy, notably its open capital account, fixed exchange rate, high government borrowing requirement, large public debt, and high degree of deposit dollarization. We find that international interest rates are an important element in the determination of interest rates in Lebanon. In particular, the pass-through of global benchmark rates to interest rates on sovereign bonds is about 70 percent. The less-than-complete pass-through could be attributed to a home-bias effect reflecting a relatively stable and dedicated investor base. The study also shows that interest rates in Lebanon are affected by liquidity conditions as well as perceived sovereign risk.