Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Learning for Social Sensing from Tweets

English. Distributional Semantic Models (DSM) that represent words as vectors of weights over a high dimensional feature space have proved very effective in representing semantic or syntactic word similarity. For certain tasks however it is important to represent contrasting aspects such as polarity, opposite senses or idiomatic use of words. We present a method for computing discriminative word embeddings can be used in sentiment classification or any other task where one needs to discriminate between contrasting semantic aspects. We present an experiment in the identification of reports on natural disasters in tweets by means of these embeddings. Italiano. I Distributional Semantic Model (DSM) rappresentano le parole come vettori di pesi in uno spazio di feature ad alte dimensioni, e si sono dimostrati molto efficaci nel rappresentare la similarità semantica o sintattica tra parole. Per certi compiti però è importante rappresentare aspetti contrastanti come la polarità, significati opposti o parole usate con significato idiomatico. Presentiamo un metodo per calcolare dei word embedding discriminativi che possono essere usati nella sentiment classification o per qualunque altro compito dove vi sia necessità di discriminare tra aspetti semantici contrastanti. Presentiamo un esperimento sull'identificazione di tweet relativi a calamità naturali utilizzando questi embedding.
Constrained Clustering: Advances in Algorithms, Theory, and Applications

Since the initial work on constrained clustering, there have been numerous advances in methods, applications, and our understanding of the theoretical properties of constraints and constrained clustering algorithms. Bringing these developments together, Constrained Clustering: Advances in Algorithms, Theory, and Applications presents an extensive collection of the latest innovations in clustering data analysis methods that use background knowledge encoded as constraints. Algorithms The first five chapters of this volume investigate advances in the use of instance-level, pairwise constraints for partitional and hierarchical clustering. The book then explores other types of constraints for clustering, including cluster size balancing, minimum cluster size,and cluster-level relational constraints. Theory It also describes variations of the traditional clustering under constraints problem as well as approximation algorithms with helpful performance guarantees. Applications The book ends by applying clustering with constraints to relational data, privacy-preserving data publishing, and video surveillance data. It discusses an interactive visual clustering approach, a distance metric learning approach, existential constraints, and automatically generated constraints. With contributions from industrial researchers and leading academic experts who pioneered the field, this volume delivers thorough coverage of the capabilities and limitations of constrained clustering methods as well as introduces new types of constraints and clustering algorithms.
The Metric Dilemma: Competence-Conscious Associative Classification

The classification performance of an associative classifier is strongly dependent on the statistic measure or metric that is used to quantify the strength of the association between features and classes (i.e., confidence, correlation etc.). Previous studies have shown that classifiers produced by different metrics may provide conflicting predictions, and that the best metric to use is data-dependent and rarely known while designing the classifier. This uncertainty concerning the optimal match between metrics and problems is a dilemma, and prevents associative classifiers to achieve their maximal performance. This dilemma is the focus of this paper. A possible solution to this dilemma is to learn the competence, expertise, or assertiveness of metrics. The basic idea is that each metric has a specific sub-domain for which it is most competent (i.e., it consistently produces more accurate classifiers than the ones produced by other metrics). Particularly, we investigate stacking-based metalearning methods, which use the training data to find the domain of competence of each metric. The meta-classifier describes the domains of competence (or areas of expertise) of each metric, enabling a more sensible use of these metrics so that competence-conscious classifiers can be produced (i.e., a metric is only used to produce classifiers for test instances that belong to its domain of competence). We conducted a systematic evaluation, using different datasets and evaluation measures, of classifiers produced by different metrics. The result is that, while no metric is always superior than all others, the selection of appropriate metrics according to their competence/expertise (i.e., competence-conscious associative classifiers) seems very effective, showing gains that range from 7% to 26% when compared to the baselines (SVMs and an existing ensemble method). This research was sponsored by UOL (www.uol.com.br) through its UOL Bolsa Pesquisa program (grant number 20080131200100), and partially supported by CNPq, Capes, Finep, Fapemig, and by the projects 5SVQ (CNPq grant number 551013/2005-2), INCTWeb (CNPq grant number 573871/2008-6), and InfoWeb (CNPq grant number 550874/2007-0).
DESIGN AND IMPLEMENTATION OF A PACKET SWITCHED ROUTING CHIP

Monsoon is a parallel processing dataflow computer that will require a high bandwidth interconnection network. A packet switched routing chip (PaRC) is described that will be used as the basis of this network. PaRC is a 4 by 4 routing switch which has been designed and fabricated as a CMOS gate array. PaRC will receive packets via one of its four input ports, store the packet in an on-chip buffer, and eventually transmit the packet via one of its four output ports. PaRC operates at 50 MHz, and each port has a bandwidth of 800 Mbits per second. Each input port operates asynchronously and has enough buffering to store four packets. The buffering and scheduling algorithms used in PaRC were designed to provide high utilization of the available bandwidth, while providing low latency for non-blocked packets. In addition, PaRC provides a mechanism whereby a processor can quickly receive an acknowledgment when a message it sent has been received. Although the design of PaRC has been driven by the needs of Monsoon, PaRC has been designed to be suitable for a wide variety of communication networks.
An Efficient Hierarchical Error Recovery Method for Hybrid Broadcast/Communication Networks

ABSTRACT This paper proposes a hierarchical error recovery method for the hybrid mobile broadcast/communication networks. The mobile broadcast network (e.g., DVB-T/H, T-DMB) transmits the base forward error correction (FEC) and the multimedia content at the same time for the error recovery. However, the occurrence of errors is different due to the receiving environment of the individual mobile broadcast network, and not all the base FECs can recover errors. The server retransmits the enhanced-FEC (E-FEC) to a terminal through the individual mobile communication network and a terminal can try to recover the packet with errors which the base FEC cannot recover. If there are more retransmitted source data to a user, the overhead of a user and the communication network will increase because the individual mobile communication is a subscription-based network. Therefore, this paper proposes a hierarchical error recovery method, and the E-FEC with higher channel coding rate than base FEC is generated and transmitted. The proposed method in this paper transmits only the redundancy data for the error recovery when errors occur, and reduces the resource by 50%–80% compared with the retransmission of the source. If the source bit rate is 800 kbps, for instance, the packet error ratio is 10%, and if a user watches a broadcast content for one hour, the amount of retransmitted data is 80 kbps × 3600 = 36 MBytes, but that of the proposed method in this paper is 7.2–18 MBytes.
Serum Asymmetric Dimethy L- Arginine Level and its Relation to Different Variables among Type 1 Diabetic Children

Patients with type 1 diabetes mellitus (DM) are very susceptible to vascular complications. Endothelial dysfunction is the earliest feature for the vascular complications of DM. Asymmetric N G , N G -dimethyl-l-arginine (ADMA) is a sensitive indicator for endothelial dysfunction and thus of vascular complications of DM. The aim of this study was to investigate the circulating ADMA level and its relation to metabolic parameters especially HbA1c in type 1 diabetic children. The current study was conducted on 30 children with type 1 DM (cases) of the outpatient endocrine Clinic in Cairo University Pediatric Hospital and 20 healthy children (controls) whose age and gender were similar to those of cases. Serum ADMA level was significantly increased in cases compared with that of controls. There was excellent positive correlation between ADMA levels and glycosylated heamoglobin (HbA1c) and diabetes duration among cases. In conclusion, increased circulating ADMA levels have been demonstrated in type 1 diabetic children who do not suffer from diabetic vascular complications. Monitoring ADMA levels in diabetic patients is of utmost importance to predict and then prevent the development of cardiovascular complications.
Simulating Life in Ancient Sites Using Mixed Reality Technology

More and more we can see several ancient sites simulated with 3D technologies. The presented case studies will illustrate the virtual reconstruction methodology and techniques we applied for the virtual restitution of historical sites such as Pompeii in Italy, using AR, or the Great Mosque of Hagia Sophia in Istanbul (using VR). But what is more interesting today is to mix some real scenery with virtual scenery. In the case of Pompeii, we have simulated life including humans, animals and plants together with the existing remaining building. This requires filming the natural decor and augmenting it at the right place with virtual humans. For doing that, we had also to analyze the costumes and the hairstyles, the behavior and the interaction between people living at that particular time. In our presentation, we will describe our real-time virtual human’s platform that allows us to see Pompeii augmented and to walk through the theater Aspendos in Turkey, seeing in the same time people that use to live there or be at these places. We will explain the methods used to simulate real-time clothes, hair and animation of the virtual humans. We also describe the rendering method that should consider the real light and the calculated light and visual case studies are shown.
Optimising hidden Markov models using discriminative output distributions

Models similar to Doddington's (1989, 1990) hidden Markov models (HMMs) that use phonetically sensitive discriminants are discussed. In this style of HMM, each state models a subspace of the overall acoustic vector; the subspace is chosen to increase discrimination between the in-class and potentially confusable out-of-class utterances. The theoretical basis is presented and various aspects of using these models are discussed, such as the method of gathering confusion statistics; obtaining the correct normalization for the subspace Gaussian distribution and the effects of this term; and the computational requirements for the method. A large number of experiments on a 104 talker British English E-set database were performed that illustrate the utility of the method on a difficult speech recognition task. The experiments give a best speaker-independent error rate 7.9%, and a best multiple speaker error rate of 3.8%. <<ETX>>
Rapid Identification by MALDITOFof Neisseria elongataSubspecies nitroreducens in anEndocarditis Case

Rapid Identification by MALDITOF of Neisseria elongata Subspecies nitroreducens in an Endocarditis Case Neisseria elongata subspecies nitroreducens is considered to be an important pathogen responsible for infective endocarditis, even if it is infrequently reported. We report the first case of endocarditis in Italy due to N. elongata subsp. nitroreducens.
A low‐cost, free‐software platform with hard real‐time performance for control engineering education

In this paper, we present a novel portable servomechanism control platform for educational purposes. The platform main features are: low cost, reliable and robust hardware, high‐speed USB interface, free open source software (FOSS), graphical interface modeling (via Scilab/XCos) and hard real‐time performance based on the Real‐Time Application Interface for Linux (RTAI). The platform is easy to interface with any computer and can be carried home by students, opening many new possibilities for practical assignments in control courses. We include application examples and student feedback regarding their experience during various workshops in which the system was demonstrated.
A Comparison of Word Embeddings and N-gram Models for DBpedia Type and Invalid Entity Detection

This article presents and evaluates a method for the detection of DBpedia types and entities that can be used for knowledge base completion and maintenance. This method compares entity embeddings with traditional N-gram models coupled with clustering and classification. We tackle two challenges: (a) the detection of entity types, which can be used to detect invalid DBpedia types and assign DBpedia types for type-less entities; and (b) the detection of invalid entities in the resource description of a DBpedia entity. Our results show that entity embeddings outperform n-gram models for type and entity detection and can contribute to the improvement of DBpedia’s quality, maintenance, and evolution.
A robot tool frame calibration method

We present a simple and effective calibration method for robot tool frame calibration.This method is based on the kinematic computation of a stacking robot,and recognizes the relative position of the tool frame to the end of the robot without the aid of extra measurement equipment.The method then recognizes the orientation of the robot tool frame based on the derived relative position.This method only employs the linear least square algorithm,so it is easy to be realized.We employ MATLAB and Virtual Robot Simulator to simulate the proposed method.Results show that the method is feasible and can be applied to practical environments to reduce the off-line time and improve the level of automation.
Data Intensive Technologies for Financial Regulatory Systems

We briefly review three U.S. regulatory initiatives in the context of data intensive technologies. We compare the conventional data warehouse approaches versus the newer approaches based on exploiting parallel computation, from data appliance to the open source “big data” approaches. Several existing financial applications are reviewed and implementation tradeoffs are discussed. The goal is to help regulators understand these technologies and to help technologists understand the new financial regulatory initiatives.
Effectiveness of Low Back Pain Manipulative Therapy in Combination with Physical Therapy as Compared to Standard Physical Therapy

Venegas-Ríos, Heidi L. , Effectiveness of Low Back Pain Manipulative Therapy in Combination with Physical Therapy as Compared to Standard Physical Therapy. Doctor in Public Health (Biostatistics), May 2009, 185 pp. 22 tables, 4 figures, references, 36 titles. Low back pain (LBP) can interfere with an individual’s ability to work, have a meaningful and active social life, and negatively affects overall quality of life. In recent years, new approaches have been considered as alternative treatments for LBP. Spinal manipulative therapy (SMT) is one of these new approaches to acute LBP treatment. Still, recent studies have found contradicting results in terms of the effectiveness of such alternative therapies. This study aimed to compare the effect of SMT in combination with standard physical therapy (SPT) versus SPT alone to treat chronic LBP. A randomized, controlled, parallel-group trial was undertaken in the Worker’s Compensation System, in Puerto Rico. A total of 66 subjects were enrolled in the study. The intervention consisted of adding two consecutive SMT two days apart followed by SPT for a total period of one month. The main outcome measures were functional impairment in activities of daily living, disability and perceived level of pain intensity and frequency. Results showed that both interventions were moderately effective in managing pain and disability in patients with chronic LBP who participate in the Worker’s Compensation Program, but that the addition of a SMT seemed to add minimal supplemental benefit to standard treatment. Future studies should consider including subjective and objective outcome measures in order to maximize information and understand the psychological, as well as, the physical effect LBP has on functional activities. It is also recommended to take into consideration diagnosed and undiagnosed depression among participants as it might have a negative effect on treatment outcomes. Finally, considering a moderate to severe level of impairment and disability at baseline might be important in order to avoid a floor effect and detect improvement with treatment. Including patients at various levels of disability and chronicity might help determine for which level of disability and/or level of pain chronicity this type of treatment is effective. EFFECTIVENESS OF LOW BACK PAIN MANIPULATIVE THERAPY IN COMBINATION WITH PHYSICAL THERAPY AS COMPARED TO STANDARD PHYSICAL THERAPY Heidi L. Venegas-Ríos, M.S.
Evaluation of Idempotency & Block Size of Data on the Performance of Normalized Compression Distance Algorithm

Normalized compression distance (NCD) is a similarity distance metric algorithm which is used for the purpose of analyzing the type of file fragments. The performance of NCD depends upon underlying compression algorithm to be used. We have studied three compressors bzip2, gzip and ppmd, the compression ratio of ppmd is better than bzip2 and the compression ratio of bzip2 is better than gzip, but which one out of these three is better than one another in the viewpoint of idempotency is evaluated by us. Then we have applied NCD along with k nearest neighbour as a classification algorithm to a randomly selected public corpus data with different block sizes (512 byte, 1024 bytes, 1536 bytes, 2048 bytes). The performance of two compressors bzip2 and gzip is also compared for the NCD algorithm in the perspective of idempotency. Objectives: In this study we have investigated the In this study we have investigated the combine effect of both of the parameters namely compression ratio versus idempotency and varying block size of data on the performance of NCD. The objective is to figure out that in order to have a better performance of NCD either a compressor for NCD should be selected on the basis of better compression ratio of compressors or better idempotency of compressors. The whole purpose of using different block sizes was to evaluate either the performance of NCD will improve or not by varying the block size of data to be used for making the datasets. Methods: Experiments are performed to test the hypotheses and evaluate the effect of compression ratio versus idempotency and block size of data on the performance of NCD. Results: The results obtained after the analysis of null hypotheses of main experiment are retained, which showed that there is no statistically significant difference on the performance of NCD when varying block size of data is used and also there is no statistically significant difference on the NCD’s performance when a compressor is selected for NCD on the basis of better compression ratio or better idempotency. Conclusions: As the results obtained from the experiments are unable to reject the null hypotheses of main experiment so no conclusion could be drawn of the effect of the independent variables on the dependent variable i.e. there is no statistically significant effect of compression ratio versus idempotency and varying block size of data on performance of the NCD.
Scalable Vector Graphics SVG 1.0 Specification

This specification defines the features and syntax for Scalable Vector Graphics (SVG) Version 1.1, a modularized language for describing two-dimensional vector and mixed vector/raster graphics in XML. Status of this document This section describes the status of this document at the time of its publication. Other documents may supersede this document. The latest status of this document series is maintained at the W3C. This document is the 15 November 2002 Proposed Recommendation of the SVG 1.1 specification. SVG 1.1 serves two purposes: to provide a modularization of SVG based on SVG 1.0 and to include the errata found so far in SVG 1.0. The SVG Working Group believes SVG 1.1 has been widely reviewed by the community, developers and other W3C groups. The list of changes made in this version of the document is available. W3C Advisory Committee representatives are invited to send formal review comments to the W3C Team until 20 December 2002 at w3t-svg@w3.org. After the review the Director will announce the document's disposition. This announcement should not be expected sooner than 21 days after the end of the review. Public comments are also welcome. Please send them to www-svg@w3.org: the public email list for issues related to vector graphics on the Web. This list is archived and senders must agree to have their message publicly archived from their first posting. To subscribe send an email to www-svg-request@w3.org with the word subscribe in the subject line. The W3C SVG Working Group have released a test suite for SVG 1.1 along with an implementation report. The latest information regarding patent disclosures related to this document is available on the Web. As of this publication, the SVG Working Group are not aware of any royaltybearing patents they believe to be essential to SVG. This document has been produced by the W3C SVG Working Group as part of the Graphics Activity within the W3C Document Formats Domain. The goals of the W3C SVG Working Group are discussed in the W3C SVG Charter (W3C Members only). The W3C SVG Working Group has maintained a public Web page, http://www.w3.org/Graphics/SVG/, which contains further background information. The authors of this document are the SVG Working Group participants. Publication of this document does not imply endorsement by the W3C membership. A list of current W3C Recommendations and other technical documents can be found at http://www.w3.org/TR/. W3C publications may be updated, replaced, or obsoleted by other documents at any time.