Miracle-dz/UniFAR-FTUs huggingface dataset:
The Chemistry of Facebook: Using Social Networking to Create an Online Community for the Organic Chemistry

Web 2.0 technologies, and specifically social networking sites such as MySpace and Facebook, have a very strong influence on the lives of millions of students (Thompson 2007), leading many educators to wonder what role, if any, social networking could have in education (Joly 2007). The 2008 Horizon Report suggests that educators should develop strategies to utilize social networking for educational purposes (New Media Consortium and EDUCAUSE 2008).
[Paper] Using Gaussian Kernels to Remove Uneven Shading from a Document Image

Segmentation of document images into text or drawings is an important process, which is often related to binarization of a document image to perform character recognition and document analysis. This process is easier to do using a document image with a uniform background and illuminated under well-conditioned lighting. However, when a document image is very unevenly shaded, binarization becomes very difficult or even impossible. An effective method is to remove the shading prior to binarization. In this paper, we propose a novel method for estimating an unevenly shaded surface in an image obtained under poor illumination. A one-dimensional Gaussian kernel model is applied in both the horizontal and vertical directions to estimate the background surface, allowing uneven shading to be removed from the document image. Thereafter, the image can easily be binarized. Results of experiments conducted on many document images demonstrate that our method yields better results than other methods.
Tata bahasa baku bahasa Indonesia

Kedudukan sebuah buku tata bahasa yang lengkap bagi suatu bahas boleh di katakan kurang lebih sama dengan kedudukan sebuah undang undang dasar atau konstitusi bagi sebuah negara. Oleh sebab itu dalam buku ini akan di bahas tentang , ; membatasi keluwesan orang berbahasa dalam percakapan sehari - hari, pengunaan bahasa ujaran yang sembarangan cenrung menyimpang dari kaidah tata bahas yang benar. oleh sebab itu buku ini memuat pokok -pokok tata bahasa baku bahasa Indonesia yang digunakan oleh angota masyarakat.
Aspect-based Sentiment Analysis of Radiology Patient Experience Surveys: A Cohort Study

Institute of Healthcare Improvement considers experience of care as one of the Triple Aims. Radiology is among the highest volume departments in a health system. Despite being a cornerstone of quality, experience of care is poorly understood in Radiology. In radiology, Magnetic Resonance Imaging (MRI) is one of the most powerful and important medical imaging technologies for evaluate certain types of diseases. However, MRIs are among the most challenging imaging studies for patients due to long exams, loud noises during the exam, and the need to stay in a fixed position confined a narrow space for an extended time. Giving patients an opportunity to give feedback of their experiences after radiology visit can provide key patient-centered insights to elevate the experience of care for patients. The combination of simple, on-time electronic open-ended patient questionnaires and aspect-based sentiment analysis natural language processing (NLP) methods have enabled more accurate and prompt depictions of the patient experience, empowering operational and financial improvements in healthcare delivery. In this work, we create a labelled corpus of 146 post-MRI patient experience reviews by performing double-rated annotation, while iteratively developing annotation guidelines and resolving annotation inconsistencies. Sentiment-aspect pair segments were tagged by two expert annotators. Annotation guidelines, including the types of aspects and topics collected, were iteratively constructed to include the range and granularity of aspects for which patient had sentiment. Corpus analysis suggests waiting times, staff interactions and MRI discomfort were the primary sources of patient negative comment, but overall and staff-directed sentiment were positive. Subsequent work will extend the annotated corpus to a comprehensive gold standard dataset capable of distant supervision to supplement the corpus. Once sufficiently large, this corpus could be used to pretrain and train an aspect-based sentiment classification transformer model and deploy it as a real-time patient feedback engine to improve decision-making by health care providers and patient-centered care. (Abstract)
How “small” is “starting small” for learning hierarchical centre-embedded structures?

Hierarchical centre-embedded structures pose a large difficulty for language learners due to their complexity. A recent artificial grammar learning study (Lai & Poletiek, 2011) demonstrated a starting-small (SS) effect, i.e., staged-input and sufficient exposure to 0-level-of-embedding exemplars were the critical conditions in learning AnBn structures. The current study aims to test: (1) a more sophisticated type of SS (a gradually rather than discretely growing input), and (2) the frequency distribution of the input. The results indicate that SS optimally works under other conditional cues, such as a skewed frequency distribution with simple stimuli being more numerous than complex ones.
ScienceDirect Eleventh International Multi-Conference on Information Processing-2015 ( IMCIP-2015 ) Continuous Indian Sign Language Gesture Recognition and Sentence Formation

Hand gestures are a strong medium of communication for hearing impaired society. It is helpful for establishing interaction between human and computer. In this paper we proposed a continuous Indian Sign Language (ISL) gesture recognition system where both the hands are used for performing any gesture. Recognizing a sign language gestures from continuous gestures is a very challenging research issue. We solved this problem using gradient based key frame extraction method. These key frames are helpful for splitting continuous sign language gestures into sequence of signs as well as for removing uninformative frames. After splitting of gestures each sign has been treated as an isolated gesture. Then features of pre-processed gestures are extracted using Orientation Histogram (OH) with Principal Component Analysis (PCA) is applied for reducing dimension of features obtained after OH. Experiments are performed on our own continuous ISL dataset which is created using canon EOS camera in Robotics and Artificial Intelligence laboratory (IIIT-A). Probes are tested using various types of classifiers like Euclidean distance, Correlation, Manhattan distance, city block distance etc. Comparative analysis of our proposed scheme is performed with various types of distance classifiers. From this analysis we found that the results obtained from Correlation and Euclidean distance gives better accuracy then other classifiers. © 2015 The Authors. Published by Elsevier B.V. Peer-review under responsibility of organizing committee of the Eleventh International Multi-Conference on Information Processing-2015 (IMCIP-2015).
File servers, networking, and supercomputers

One of the major tasks of a supercomputer center is managing the massive amount of data generated by application codes. A data flow analysis of the San Diego Supercomputer Center is presented that illustrates the hierarchical data buffering/caching capacity requirements and the associated I/O throughput requirements needed to sustain file service and archival storage. Usage paradigms are examined for both tightly-coupled and loosely-coupled file servers linked to the supercomputer by high-speed networks.
Nutzerzentrierte Datenerhebung zur Aktivitätserkennung von alltäglichen Tätigkeiten durch mobile Geräte

Die Aktivitatserkennung mit einem Smartphone ist durch die Sensoren, die im Smartphone integriert sind, moglich. Dazu werden keine externen Sensoren benotigt. Um eine Aktivitat zu erkennen, mussen die Daten, die von den Sensoren geliefert werden, ausgewertet werden. Dafur werden Trainingsdaten, die wahrend einer Aktivitat aufgezeichnet werden, benotigt, die das Erkennen der Aktivitat erst moglich machen. Diese Arbeit beschaftigt sich mit der nutzerzentrierten Datenerhebung zur Aktivitatserkennung. Die benotigten Sensordaten werden mit Hilfe einer mobilen Android Anwendung von Personen gesammelt. Die mobile Android Anwendung wurde hierfur in Form eines Spiels entwickelt und verbreitet, sodass es von vielen Personen benutzt wird. Mit dieser Forschungsmethode soll erreicht werden, dass die Sensordaten fur die Aktivitatserkennung von vielen Personen erhoben werden konnen. Activity recognition with a smartphone is possible with the integrated sensors. So there is no need of external sensors. To recognize an activity, the data obtained from the sensors have to be analyzed. Therefore, training data which is recorded during an activity is needed. This work deals with user-centered data collection for activity recognition on mobile devices. The required sensor data are collected from people by using a mobile Android application. The mobile Android application is developed in the form of a game so that many persons use it. The aim is to collect many sensor data for activity recognition.
Het geluid als een innerlijke beweging in de overdracht van een ervaring in de film: een fenomenologische benadering

In deze dissertatie wordt de eigenheid van het geluid in de overdracht van een ervaring in film onderzocht vanuit de opvatting dat de waarneming van een film een actief gebeuren is. De toeschouwer/luisteraar richt zijn aandacht vanuit een beleefd en belichaamd luisteren en brengt hiermee zijn eigen coherentie van de film tot stand. De cineast kan door precieze keuzes een ervaring overdragen en de waarneming van een film sturen : door de keuzes van de geluiden die hij wel of niet laat horen, door de nuances in de geluiden zelf , door de opbouw van auditieve ruimtes, de compositie van geluiden en ten slotte door de mixage. Niet alleen een geluid toevoegen of wegnemen maar ook een kleine nuance in het geluid zelf, kan een grote impact hebben op de beleving en de waarneming van een film. Dit onderzoek wil juist dat aspect in het geluid van een film dat niet onmiddellijk wordt waargenomen, maar dat bepalend en motiverend kan zijn voor de filmwaarneming in haar geheel, bespreekbaar maken en zo een bijdrage leveren tot de filmtheorie en tot de artistieke filmpraktijk.
Speed and accuracy: large-scale machine learning algorithms and their applications

Over the past few years, considerable progress has been made in the area of machine learning. However, when these learning machines, including support vector machines (SVMs) and neural networks, are applied to massive sets of high-dimensional data, many challenging problems emerge, such as high computational cost and the way to adapt the structure of a learning system. Therefore, it is important to develop some new methods with computational efficiency and high accuracy such that learning algorithms can be applied more widely to areas such as data ruining, Optical Character Recognition (OCR) and bio-informatics. In this thesis, we mainly focus on three problems: methodologies to adapt the structure of a neural network learning system, speeding up SVM's training and facilitating test on huge data sets. For the first problem, a local learning framework is proposed to automatically construct the ensemble of neural networks, which are trained on local subsets so that the complexity and training time of the learning system can be reduced and its generalization performance can be enhanced. With respect to SVM's training on a very large data set with thousands of classes and high-dimensional input vectors, block diagonal matrices are used to approximate the original kernel matrix such that the original SVM optimization process can be divided into hundreds of sub-problems, which can be solved efficiently. Theoretically, the run-time complexity of the proposed algorithm linearly scales to the size of the data set, the dimension of input vectors and the number of classes. For the last problem, a fast iteration algorithm is proposed to approximate the reduced set vectors simultaneously based on the general kernel type so that the number of vectors in the decision function of each class can be reduced considerably and the testing speed is increased significantly. The main contributions of this thesis are to propose effective solutions to the above three problems. It is especially worth mentioning that the methods which are used to solve the last two problems are crucial in making support vector machines more competitive in tasks where both high accuracy and classification speed are required. The proposed SVM algorithm runs at a much higher training speed than the existing ones such as svm-light and libsvm when applied to a huge data set with thousands of classes. The total training time of SVM with the radial basis function kernel on Hanwang's handwritten Chinese database (2,144,489 training samples, 542,122 testing samples, 3755 classes and 392-dimensional input vectors) is 19 hours on P4. In addition, the proposed testing algorithm has also achieved a promising classification speed, 16,000 patterns per second, on MNIST database. Besides the efficient computation, the state-of-the-art generalization performances have also been achieved on several well-known public and commercial databases. Particularly, very low error rates of 0.38%, 0.5% and 1.0% have been reached on MNIST, Hanwang handwritten digit databases and ETL9B handwritten Chinese database.
Study of Cache Performance on GPGPU

General-purpose graphics processing units (GPGPUs) provide tremendous computational and processing power. Despite the latency hiding mechanism, a GPU architecture requires high memory bandwidth and lower latency between computational units and the memory system. For this reason, the current GPU architecture has private L1 caches in each core and a shared L2 cache to increase performance by reducing memory latency. But in some cases, this CPU-like cache design is not suitable for GPGPUs. In this paper, we analyze detailed cache performance related to GPGPU application characteristics, and suggest technical alternatives for the GPGPU architecture as future work.
Le poppérisme en science économique : entre incomplétude et connivence

Cet article propose un regard a nouveaux frais sur le rationalisme critique de Popper, posture epistemologique largement adoptee par la science economique. En effet, l’epreuve de refutabilite popperienne meconnait les faits de limitation interne auxquels font face tant le savoir economique que le formalisme mathematique qui lui est attache. Reconnaitre et signifier ces faits de limitation seraient un autre gage de scientificite, complementaire au critere popperien.
Sistemas inteligentes para la detección y filtrado de correo spam: una revisión

Este articulo presenta una revision general de los modelos de deteccion y filtrado de correo spam existentes en la actualidad. En concreto, se realiza una subdivision de las tecnicas existentes en dos grandes tipos: modelos basados en la colaboracion de usuarios y modelos basados en el analisis de contenido. Se presentan las caracteristicas especificas del problema y se analizan los corpus publicos disponibles, asi como las tecnicas habituales empleadas en su preprocesamiento. Ademas, se realiza una revision de los distintos sistemas implementados destacando las caracteristicas distintivas de cada uno de ellos. El trabajo finaliza con la exposicion de las conclusiones mas destacables acerca del estado del arte actual.
Loi de position

La loi de position tire sa force de son imprecision, de son refus d’examiner avec rigueur les faits du passe et de son recours au futur pour ignorer les cas les plus recalcitrants. Spence (1988) se porte neanmoins a sa rescousse dans ce numero. Son argumentation, cependant, est minee par de nombreuses generalisations hâtives, pour ne pas dire fausses. Il concede a mes remarques anterieures (Morin 1986) que la longueur pourrait avoir eu une influence, mais deforme souvent mes propos. En particulier, il m’attribue a tord la these que « la qualite des voyelles contemporaines [du francais] se rattacherait […] a leur longueur en francais moyen »— une these qui est clairement farfelue et qu’il n’a aucun mal a discrediter.
Building large knowledge-based systems

In this age of modern era, the use of internet must be maximized. Yeah, internet will help us very much not only for important thing but also for daily activities. Many people now, from any level can use internet. The sources of internet connection can also be enjoyed in many places. As one of the benefits is to get the on-line building large knowledge based systems book, as the world window, as many people suggest.
Ontological Services Using Crowdsourcing

This paper develops a service for ontology evolution based on crowdsourcing. The approach is demonstrated using OntoAssist, a specially designed semantic search service that is capable of capturing and disambiguating user’s search intent as well as automatically enabling ontology evolution. Successful and consistent ontology evolution often requires large amount of input data to specify new terms or changes in relationships. These inputs typically come mainly from domain experts or ontology professionals, which makes it hard to keep up with the change of open, dynamic World Wide Web environment. By integrating OntoAssist with an existing search engine, we show that users’ search intent can be disambiguated and aggregated to help to evolve underlying ontology. The disambiguation feature helps the users to find desirable search results. OntoAssist has been implemented and tested by Turkers from Amazon Mechanical Turk in a live demonstration site. Promising results and analysis are reported.
The problem of negatives in input-output analysis: a review of the solutions

The main models to construct technical coefficients are the industry technology model and the commodity technology model. The former yields nonnegative coefficients and the latter fulfills nice theoretical properties, such as price invariance. Although the models are very different, this paper presents a flexible formula that encompasses both of them. Various solutions to the problem of negatives of the commodity technology model-including replacements by industry technology based coefficients-are reviewed in our framework.
DFT/FFT and Convolution Algorithms: Theory and Implementation

From the Publisher: This readable handbook provides complete coverage of both the theory and implementation of modern signal processing algorithms for computing the Discrete Fourier transform. Reviews continuous and discrete-time transform analysis of signals and properties of DFT, several ways to compute the DFT at a few frequencies, and the three main approaches to an FFT. Practical, tested FORTRAN and assembly language programs are included with enough theory to adapt them to particular applications. Compares and evaluates various algorithms.
Is what you see what you get? representations, metaphors and tools in mathematics didactics

This paper is exploratory in character. The aim is to investigate ways in which it is possible to use the theoretical concepts of representations, tools and metaphors to try to understand what learners of mathematics ‘see’ during classroom interactions (in their widest sense) and what they might get from such interactions. Through an analysis of a brief classroom episode, the suggestion is made that what learners see may not be the same as what they get. From each of several theoretical perspectives utilised in this paper, what learners ‘get’ appears to be something extra. According to our analysis, this something ‘extra’ is likely to depend on the form of technology being used and the representations and metaphors that are available to both teacher and learner.
Evaluating movement patterns of rats-the measurement theoretical point of view

Behavior (movement patterns) of animals has been used for a long time in medical sciences as an indicator of the "system state" i.e. of the influence of a particular treatment upon the animal's condition. Until recently the evaluation of such behavior was done visually, by the experimenter, without any possibility of on objective measurement procedure. The introduction of the passive marker based motion analysis in controlled laboratory conditions led to the reproducible generation of observables, that can be relatively easily quantified and processed. The selection of an adequate model and the appropriate signal processing constitutes the major problem. The models must describe the rat behavior in two levels. The quantitative (low level) model is used to describe the physical movement. In the paper we present the measurement setup, the low-level model and the conclusions regarding movement patterns drawn from several long-term measurements. The qualitative (high level) model can be established with the involvement of medical experts.
Always On: Language in an Online and Mobile World

PREFACE 1. Email to Your Brain: Language in an Online and Mobile World 2. Language Online: The Basics 3. Controlling the Volume: Everyone a Language Czar 4. Are Instant Messages Speech? The World of IM 5. My Best Day: Managing Buddies and Friends 6. Having Your Say: Blogs and Beyond 7. Going Mobile: Cell Phones in Context 8. Whatever: Is the Internet Destroying Language? 9. Greshams Ghost: Challenges to Written Culture 10. The People We Become: Costs of Being Always On
The Processes of Life: An Introduction to Molecular Biology

A brief and accessible introduction to molecular biology for students and professionals who want to understand this rapidly expanding field.Recent research in molecular biology has produced a remarkably detailed understanding of how living things operate. Becoming conversant with the intricacies of molecular biology and its extensive technical vocabulary can be a challenge, though, as introductory materials often seem more like a barrier than an invitation to the study of life. This text offers a concise and accessible introduction to molecular biology, requiring no previous background in science, aimed at students and professionals in fields ranging from engineering to journalism? anyone who wants to get a foothold in this rapidly expanding field. It will be particularly useful for computer scientists exploring computational biology. A reader who has mastered the information in The Processes of Life is ready to move on to more complex material in almost any area of contemporary biology.
Don’t Fidget with Widgets, Draw!

In their quest to produce tools for the production of uniform graphical user interfaces, almost all designers of toolkits for the X window system have overlooked an important capability. The best way to improve many programs is not to replace text interfaces based on command line flags with graphical buttons, but to provide programs with a simple way to draw pictures. This report describes a graphics server, ezd, that sits between an application program and the X server and allows both existing and new programs easy access to structured graphics. Programs may draw, edit, and sense user events in terms of application-defined graphical objects. When run on workstations with 10 MIPS or faster processors, interactive response is excellent, indicating that ezd’s simple structured graphics drawing model can be widely applied. The enthusiastic response of ezd’s initial users and the variety of uses to which they have put it to suggest that there is a tremendous pent-up urge to draw with programs and that ezd has lowered the barriers to doing so.