Miracle-dz/UniFAR-FTUs huggingface dataset:
A Simulation of International Climate Regime Formation

The literature on pedagogical methods in international affairs includes a number of international politics simulations. We present the material for an in-class simulation exercise on international climate negotiations that attempts to help students understand the importance of theory as well as the substantive issues surrounding climate policy. Simulations have been proposed as a means of providing an engaging classroom experience and a more diverse learning experience. The exercises presented here focus on developing student research skills, analyzing data to present a realistic policy position and understanding the process of institutional regime formation. At the end of the simulation, students are asked to relate their own negotiation experiences back to the theoretical material discussed during the semester. An assessment was conducted of student expectations prior to the simulation exercise and compared with post-simulation experiences. Students reported the greatest positive difference between their expected learning outcome and actual experience with the simulation in terms of learning information about specific country assignments, overall enjoyment of the activity, and understanding the material covered in the course. The greatest negative difference between expectations and experience were reported for understanding international negotiations more generally and current international events. The article outlines the full content for an in-class simulation and its’ implementation as well as results from an evaluation of its use. The simulation provides students with a better understanding of the complexity of international negotiations over climate policy while outlining key theoretical concepts in international relations and comparative public policy.
A real-time ray-space acquisition system

This paper proposes novel Ray-Space acquisition systems that capture dynamic dense Ray-Space in video rate. Most of the previous works on Ray-Space acquisition system targeted “static” Ray-Space because of the difficulty of dealing with dynamic dense Ray-Space. In this paper, we investigate two types of real-time Ray-Space acquisition systems. One uses multiple video cameras. We developed a 16-camera setup and a capturing system using a PC cluster. Interpolation of Ray-Space is introduced to generate dense Ray-Space from sparsely placed video cameras. Another acquisition system captures a “real” dense Ray-Space without interpolation. Using a synchronized galvanometric mirror and a high-speed camera, we succeeded to capture more than 100 view images in 1/30 second. We developed a special hardware that receives digital high-speed camera signal and outputs an arbitrary viewpoint image based on Ray-Space method.
Introduction to VDM

Part 1 The VDM specification language: the software development process formal methods and the development process specifying data specifying functions specifying operations constructing a VDM specification solutions to part 1 questions. Part 2 Formal specification: sets specifications using sets composite object types maps sequences defining complex states solutions to part 2 questions. Part 3 Reifying abstract data types: stacks and queues case-study solutions to part 3 questions. Part 4 Correctness statements and proof rules: proving programs containing loops case study using data structures solutions to part 4 questions.
Data Security and Cryptography in Cloud Environment

Cloud is an intelligent computing delivery service. It provides unlimited service provisioning to users based on their demand. Services are processed by automated APIs(Application Programming Interface) without human interaction. Storage is one of the main services from the Cloud. Users could outsource their data to cloud. Cloud provides reliable storage. Data outsource to cloud are stored in different cloud datacenter located in different geographical location to maintain the reliable storage. Cloud has many challenges like scalability, resource allocation, virtualization, security, trust, service level agreement and etc. Among these challenges, security is the top level concern in cloud storage. Cloud storage has many security related issues. Traditionally, Security is addressed by cryptography techniques. This paper describes the data security challenges, importance of security and security mechanism for cloud storage. Different security mechanisms are addressed in this paper, among them confidentiality, integrity and authentication are important for data security in cloud. An efficient cryptography technique might protect the cloud environment from unauthorized usage.
Enabling end users to be more efficient during systems development

This article introduces a model of three maturity levels, which help managers to evaluate end user involvement during systems development. This model is based on research done in terms of how relationships between IT departments and end users are constructed. The value of the three levels lies therein that it gives the IT department the advantage of understanding and supporting the end user in a more effective way during systems development. Furthermore, it gives management on both the IT and business side the ability to establish training needs for end users and IT professionals of software project teams. End users on the other hand, who are aware of their level of maturity, could play a more efficient role during the systems development process.
MMI diversity based text summarization

The search for interesting information in a huge data collection is a tough job frustrating the seekers for that information. The automatic text summarization has come to facilitate such searching process. The selection of distinct ideas “diversity” from the original document can produce an appropriate summary. Incorporating of multiple means can help to find the diversity in the text. In this paper, we propose approach for text summarization, in which three evidences are employed (clustering, binary tree and diversity based method) to help in finding the document distinct ideas. The emphasis of our approach is on controlling the redundancy in the summarized text. The role of clustering is very important, where some clustering algorithms perform better than others. Therefore we conducted an experiment for comparing two clustering algorithms (K-means and complete linkage clustering algorithms) based on the performance of our method, the results shown that k-means performs better than complete linkage. In general, the experimental results shown that our method performs well for text summarization comparing with the benchmark methods used in this study
Gamificación en la educación, una aplicación práctica con la plataforma Kahoot

espanolEn los ultimos anos, los video-juegos estan tomando un nuevo y enriquecedor enfoque como es el de su uso en aplicaciones no ludicas como potenciadoras de la concentracion, el esfuerzo o la motivacion de las personas. En este trabajo nos vamos a centrar en una de sus aplicaciones, en la educacion. La denominada gamificacion se populariza en el ano 2010 y se refiere a la incorporacion de aspectos sociales o premios de los juegos en red. Para ello vamos a emplear y hacer una demostracion de una de las plataformas de aprendizaje basadas en el juego, se trata de Kahoot. Aprender jugando es posible gracias a plataformas como esta, que permite a los estudiantes aprender de forma divertida e interactiva, introducir, repasar o reforzar conocimientos, dar energia y entusiasmo en un entorno ameno o evaluar el conocimiento de los alumnos, todo ello a traves del juego en red con una aplicacion facil, intuitiva y gratuita. EnglishIn recent years, video games are taking a new and enriching approach such as their use in non-play applications as enhancer of concentration, effort or motivation of people. In this paper we will focus on one of its applications, education. Gamification is popularized in the year 2010 and it refers to the incorporation of social aspects or prizes in the network games.To do this we will employ and demonstrate one of the learning platforms based on the game, this is Kahoot. Learning to play is made possible by platforms like this, which allow students to learn in a fun and interactive way, introduce, review or reinforce knowledge, give energy and enthusiasm in a pleasant environment or evaluate students' knowledge, all through network game with an easy, intuitive and free application.
MMSE Beamforming for SC-FDMA Transmission over MIMO ISI Channels

We consider transmit beamforming for single-carrier frequency-division multiple access (SC-FDMA) transmission over frequency-selective multiple-input multiple-output (MIMO) channels. The beamforming filters are optimized for minimization of the sum of the mean-squared errors (MSEs) of the transmitted data streams after MIMO minimum mean-squared error linear equalization (MMSE-LE), and for minimization of the product of the MSEs after MIMO MMSE decision-feedback equalization (MMSE-DFE), respectively. We prove that for SC-FDMA transmission in both cases eigenbeamforming, diagonalizing the overall channel, together with a nonuniform power distribution is the optimum beamforming strategy. The optimum power allocation derived for MMSE-LE is similar in spirit to classical results for the optimum continuous-time transmit filter for linear modulation formats obtained by Berger/Tufts and Yang/Roy, whereas for MMSE-DFE the capacity achieving waterfilling strategy well known from conventional single-carrier transmission schemes is obtained. Moreover, we present a modification of the beamformer design to mitigate an increase of the peak-to-average power ratio (PAPR) which is in general associated with beamforming. Simulation results demonstrate the high performance of the proposed beamforming algorithms.
Materialized view design and maintenance in a financial data warehouse system

A data warehouse is a repository of integrated information from distributed, autonomous and possibly heterogeneous sources. One of the problems related with a data warehouse is how to keep views in the data warehouse up-to-date, given the various geographical and operational constraints of the underlying source databases. Two main techniques are used to address this view maintenance problem viz., the auxiliary view technique and the summary-delta table method. We discuss an implementation which makes use of both techniques in a single system: a Financial Data Warehouse System (FDWS), as a hybrid approach to view maintenance. Such an approach applies the two techniques as complements to each other and takes into account the special characteristics of the data warehouse concerned.
Hearts, Minds and Screens: Taming the Future

Dr. Gilly Salmon provides a focus on the future of distance learning and interpets opportunities and realities for researchers, organizations, teachers and students. She sees content as king in the transmission model of teaching (Contenteous). Learning objects and dynamic information technologies enable us to customize e-learning (Instantia). Mobile learning devices facilitate anywhere-anytime learning (Nomadict), and learning communities and interaction extend access beyond the bounds of time and space (Cafelattia). Exploring each of these scenarios give us a better foundation for designing learning experiences and adapting them to specific learning needs of the individual student, teacher, and organization.
Loaded cylindrical metallic cavities modeling using neural networks

The feasibility of using neural networks for resonant frequencies determination in loaded cylindrical metallic cavities is presented. The load in the form of a homogeneous dielectric slab with losses, which is located on the bottom of the cavity, is considered. The use of the classical multilayer perceptron (MLP) network is illustrated through the example of TM/sub 113/ modes determination in a microwave cavity with circular cross-section. An original approach for decreasing the neural network training set is used.
Soft computing tools to detect and characterize anomalous network behavior

As part of a funded effort in network security, soft computing is used to create a system capable of detecting and characterizing anomalous network behavior. Soft computing is composed of evolutionary computational tools combined with artificial neural networks and/or fuzzy logic. Actual network traffic is used as opposed to simulated data. The benefits here are that the attacks are real and the use of the tool is in a "production" environment as opposed to being a product of purely simulated theoretical speculation.
Supervised Learning under Covarita Shift

教師付き学習は,入力と出力の組から成る訓練標本 を用いて,将来与えられるテスト入力に対する出力を 予測する問題である. この時,訓練標本とテスト標本 が同じ規則に従って生成されるというのが大前提であ る 25, 38, . しかし,現実的な場面ではこの前提が満たされない ことも多い. 例えば非定常なシステムでは,標本の生 成規則が時々刻々と変化する. このような場合,昔に 採取した訓練標本は破棄して,比較的最近に集めた標 本のみを使う忘却型の学習アルゴリズムがよく用いら れる . 標本生成のメカニズムが徐々に変化する場 合は,このような方法によりテスト出力を効果的に予 測することができる. 一方,標本の生成規則が訓練時とテスト時で大きく 変化する場合,忘却型のアルゴリズムではうまく対応 できない. もちろん,訓練標本とテスト標本が全く異 なる規則により生成された場合は,訓練標本からテス ト標本に関する情報が全く抽出できない. 従って,意 味のある議論をするためには,訓練時とテスト時の標 本に何らかの共通点が必要である.
Neo-hetergeneous Programming and Parallelized Optimization of a Human Genome Re-sequencing Analysis Software Pipeline on TH-2 Supercomputer

The growing velocity of biological big data is way beyond Moore's Law of compute power growth. The amount of genomic data has been explosively accumulating, which calls for an enormous amount of computing power, while current computation methods cannot scale out with the data explosion. In this paper, we try to utilize huge computing resources to solve thebig dataproblems of genome processing on TH-2 supercomputer. TH-2supercomputer adopts neo-heterogeneous architecture and owns 16,000 compute nodes: 32000 Intel Xeon CPUs + 48000 Xeon Phi MICs. The heterogeneity, scalability, and parallel efficiency pose great challenges forthe deployment of the genomeanalysis software pipeline on TH-2. Runtime profiling shows that SOAP3-dp and SOAPsnp are the most time-consuming parts up to 70% of total runtime in the whole pipeline, which need parallelized optimization deeply and large-scale deployment. To address this issue, we first designa series of new parallel algorithms for SOAP3-dp and SOAPsnp, respectively, to eliminatethe spatial-temporal redundancy. Then we propose a CPU/MIC collaboratedparallel computing method in one node to fully fill the CPU/MIC time slots. We also propose a series ofscalable parallel algorithms and large scaleprogramming methods to reduce the amount of communications between different nodes. Moreover, we deploy and evaluate our works on the TH-2 supercomputer in different scales. At the most large scale, the whole process takes 8.37 hours using 8192 nodes to finish the analysis of a 300TB dataset of whole genome sequences from 2,000 human beings, which can take as long as 8 months on a commodity server. The speedup is about 700x.
Explanation of the mechanism by which CAD assistance improves diagnostic performance when reading CT images

The purpose of our research is to make clear the mechanism that a reader (physician or radiological technologist) effectively identify abnormal findings in CT images of lung cancer screening by using with CAD system. A method guessing the 2X2 decision matrix between reader / CAD and reader / reader with CAD was investigated. We suppose the next scene to be it. At first, a reader judges whether abnormal findings per one patient per one CT image are present (1) or absent (0) without CAD results. The second, a reader judges whether abnormal findings are present (1) or absent (0) with CAD results. We expresses the correlation between diagnoses by a reader and CAD system for abnormal cases and for normal cases by following formula using phi correlation coefficient:φ=(cd-ab)/√(a+c)(b+d)(b+c)(a+d). a,b,c,d: 2X2 decision matrix parameters. If TPR1=(a+c)/n, TPR2=(b+c)/n and TPR3=(a+b+c)/n for abnormal cases, TPR3=TPR1+TPR2 - TPR1×TRR2 - φ√TPR1(1-TPR1)TPR2(1-TPR2). Therefore, a=n (TPR3 - TPR1), b=n (TPR3 - TPR2), c=n (TPR1 + TPR2 -TPR3), d=n (1.0 - TPR3). This theory was applied for the experimental data. The 41 students interpreted the same CT images [no training]. A second interpretation was performed after they had been instructed on how to interpret CT images [training], and third was assisted by a virtual CAD [training + CAD]. The mechanism that makes up for a good point of a reader and a CAD with CAD in interpreting CT images was theoretically and experimentally investigated. We concluded that a method guessing the decision matrix (2X2) between a reader and a CAD decided the "presence" or "absence" of abnormal findings explain the improvement mechanism of diagnostic performance with CAD system.
Morphology in auditory lexical processing: Sensitivity to fine phonetic detail and insensitivity to suffix reduction

This dissertation investigates two seemingly contradictory properties of the speech perception system. On the one hand, listeners are extremely sensitive to the fine phonetic details in the speech signal. These subtle acoustic cues can reduce the temporal ambiguity between words that show initial segmental overlap, and can guide lexical activation. On the other hand, comprehension does not seem to be hampered at all by the drastic reductions that typically occur in casual speech. Complete segments, and sometimes even complete syllables, may be missing, but comprehension is seemingly unaffected. This thesis aims at elucidating how words are represented and accessed in the mental lexicon, by investigating these contradictory phenomena for the domain of morphology This dissertation investigates two seemingly contradictory properties of the speech perception system. On the one hand, listeners are extremely sensitive to the fine phonetic details in the speech signal. These subtle acoustic cues can reduce the temporal ambiguity between words that show initial segmental overlap, and can guide lexical activation. On the other hand, comprehension does not seem to be hampered at all by the drastic reductions that typically occur in casual speech. Complete segments, and sometimes even complete syllables, may be missing, but comprehension is seemingly unaffected. This thesis aims at elucidating how words are represented and accessed in the mental lexicon, by investigating these contradictory phenomena for the domain of morphology This dissertation investigates two seemingly contradictory properties of the speech perception system. On the one hand, listeners are extremely sensitive to the fine phonetic details in the speech signal. These subtle acoustic cues can reduce the temporal ambiguity between words that show initial segmental overlap, and can guide lexical activation. On the other hand, comprehension does not seem to be hampered at all by the drastic reductions that typically occur in casual speech. Complete segments, and sometimes even complete syllables, may be missing, but comprehension is seemingly unaffected. This thesis aims at elucidating how words are represented and accessed in the mental lexicon, by investigating these contradictory phenomena for the domain of morphology
Digital Signal Processing Using MATLAB

From the Publisher: This supplement to any standard DSP text is one of the first books to successfully integrate the use of MATLAB® in the study of DSP concepts. In this book, MATLAB® is used as a computing tool to explore traditional DSP topics, and solve problems to gain insight. This greatly expands the range and complexity of problems that students can effectively study in the course. Since DSP applications are primarily algorithms implemented on a DSP processor or software, a fair amount of programming is required. Using interactive software such as MATLAB® makes it possible to place more emphasis on learning new and difficult concepts than on programming algorithms. Interesting practical examples are discussed and useful problems are explored. This updated printing revises the scripts in the book, available functions, and m-files (available for downloading from the Brooks/Cole Bookware Companion Resource Series Center Web site) to MATLAB® V5 (created with 5.3).
A new modified centroid classifier approach for automatic text classification

To enhance the automatic text classification task, this paper proposes a novel approach for treating the problem of inductive bias incurred by the centroid classifier assumption. This approach is a trainable classifier, which takes into account tfidf as a text feature. The main goal of the proposed approach is to take advantage of the most similar training errors in the classification model for successively updating that model based on a certain threshold. The proposed approach is practical and flexible to implement. The complete performance of the proposed approach is measured at several threshold values on the Reuters‐21578 text categorization collection. Experimental results show that the proposed approach can improve the performance of the centroid classifier better than traditional approaches (traditional centroid classifier, support vector machines, decision trees, Bayes nets, and N Bayes) by 1, 1.2, 4.1, 7.5, and 11%, respectively. © 2013 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
Colocações especializadas em alemão e português na área de Cardiologia

This study describes the methodology used in the identification of specialized phraseologies in German and Portuguese with aims at helping translators. To achieve this goal, we adopted Textual Terminology and Corpus Linguistics conceptions – among other areas – and offered a methodology of work. This paper focused on specialized collocations that are built by the combination of noun compounds and verbs or deverbatives. Using a corpus of Cardiology – in German and Portuguese – we developed a methodology that enables the identification of this type of combination in German as well as the localization of the corresponding equivalent in Portuguese. During our research, we tested statistical methods using calculations such as mutual information and T-score. We also tested contrastive methods based on inter- and intralinguistic contrasts of contexts. The contrastive method presented more satisfactory results. From the corpus wordlist, we selected 11 noun compounds as a starting point for our study and then found 97 groups of specialized collocations with their corresponding phraseological equivalents. One example of specialized collocation with equivalent can be seen in the pair Wiederherstellung von Sinusrhythmus and restauracao do ritmo sinusal . In this study, we realized that the use of statistical methods should be carefully analyzed because it may not consider important information, especially when the objective is to help translators.
Prediction of plasma simulation data with the Gaussian process method

The simulation of plasma-wall interactions of fusion plasmas is extremely costly in computer power and time - the running time for a single parameter setting is easily in the order of weeks or months. We propose to exploit the already gathered results in order to predict the outcome for parametric studies within the high dimensional parameter space. For this we utilize Gaussian processes within the Bayesian framework and perform validation with one and two dimensional test cases from which we learn how to assess the outcome. Finally, the newly implemented method is applied to simulated data from the scrape-off layer of a fusion plasma. Uncertainties of the predictions are provided which point the way to parameter settings of further (expensive) simulations.