Miracle-dz/UniFAR-FTUs huggingface dataset:
Neural network based sensor array signal processing

An autoassociative memory using neural networks is proposed for sensor failure detection and correction. A classical approach to sensor failure detection and correction relies upon complex models of physical systems, however, a neural network approach can be used to represent systems through training for which mathematical models can not be formulated. In such cases, a neural network autoassociative memory can be used to predict sensor outputs. Differences between measured sensor outputs and sensor outputs estimated by the autoassociative memory, can be used to identify faulty sensors. Median filtering or other signal processing schemes may then be used to correct faulty sensor outputs. This technique can be used to process data from MEMS (micro electromechanical systems) or other sensor arrays.
Person re-identification in UAV videos using relevance feedback

In this paper we present an approach to recognize individual persons in aerial video data. We start from a baseline approach that matches a number of color and texture image features in order to find possible matches to a query person track. This approach is improved by incorporating operator feedback in three ways. First, features are being weighted based on their degree of agreement (correlation) to the operator feedback. Second, a classifier is trained based on the operator feedback. This classifier learns to distinguish the query person from others. Third, we use feedback from past queries to further restrict the search space and improve feature selection as well as provide additional classifier training data. Finally we also investigate active learning strategies to select those results that the operator should label in order to gain the highest possible improvement of accuracy in the next iteration. We evaluate our approach on a publicly available dataset and demonstrate improvements over the baseline as well as over a previous work.
The Anatomy of a Plagiarism Initiative: One Library's Campus Collaboration

ABSTRACT Plagiarism in media and print continues to be a major issue for professors, librarians, and students. Through initiatives and outreach from the B. Davis Memorial Library at the C. W. Post Campus of Long Island University, plagiarism Web sites have been created and workshops and programs continually provided for faculty and students to detect, discourage, and prevent plagiarism. Faculty members are presented with techniques and tips that range from designing assignments to detecting and ultimately stemming the tide of plagiarism, and students are apprised of plagiarism and the myriad ways of avoiding it. However, collaborations between librarians and the academic community are vital in arresting and curtailing this pervasive problem.
Simple recurrent network for Chinese word prediction

This paper presents preliminary investigations concerning the use of simple recurrent network (SRN) in Chinese word prediction. We explore the architecture introduced by Elman (1990) for predicting successive elements of a sequence. This model is based on a multilayer architecture and contains special units, called context units which provide the short-term memory (STM) in the system. Based on this model, We constructed a modular SRN to predict Chinese word at two levels. The first level network predicts the major category of the next word, then the next possible word is predicted at the second level network. Also, the specific encoding schemes was described in the paper. Experiments show that the method is promising.
Reducing Threats to Validity by Design in a Nonrandomized Experiment of a School-Wide Prevention Model

This paper reviews literature on the rationale, challenges, and recommendations for choosing a nonequivalent comparison (NEC) group design when evaluating intervention effects. After reviewing frequently addressed threats to validity, the paper describes recommendations for strengthening the research design and how the recommendations were implemented in a current study. Next, tests were performed in order to investigate whether the added design components had contributed to increased internal validity by creating comparable cluster groups at baseline. In order to estimate the external validity or the potential generalizability of results, the statistical power of the study was calculated up front and representativeness of the participating schools in relation to other schools in Norway was examined. Baseline comparisons indicated that the addition of several design elements, such as the random invitation of multiple, stratified, and active comparison groups, may have reduced significant validity threats stemming from selection bias. The need for more accurate and reliable effect estimates in school-based evaluation research is discussed.
Database Modeling and Design: Logical Design

Database systems and database design technology have undergone significant evolution in recent years. The relational data model and relational database systems dominate business applications; in turn, they are extended by other technologies like data warehousing, OLAP, and data mining. How do you model and design your database application in consideration of new technology or new business needs? In the extensively revised fifth edition, you'll get clear explanations, lots of terrific examples and an illustrative case, and the really practical advice you have come to count on--with design rules that are applicable to any SQL-based system. But you'll also get plenty to help you grow from a new database designer to an experienced designer developing industrial-sized systems. In-depth detail and plenty of real-world, practical examples throughout Loaded with design rules and illustrative case studies that are applicable to any SQL, UML, or XML-based system Immediately useful to anyone tasked with the creation of data models for the integration of large-scale enterprise data.
Evaluation of in-network adaptation of scalable high efficiency video coding (SHVC) in mobile environments

High Efficiency Video Coding (HEVC), the latest video compression standard (also known as H.265), can deliver video streams of comparable quality to the current H.264 Advanced Video Coding (H.264/AVC) standard with a 50% reduction in bandwidth. Research into SHVC, the scalable extension to the HEVC standard, is still in its infancy. One important area for investigation is whether, given the greater compression ratio of HEVC (and SHVC), the loss of packets containing video content will have a greater impact on the quality of delivered video than is the case with H.264/AVC or its scalable extension H.264/SVC. In this work we empirically evaluate the layer-based, in-network adaptation of video streams encoded using SHVC in situations where dynamically changing bandwidths and datagram loss ratios require the real-time adaptation of video streams. Through the use of extensive experimentation, we establish a comprehensive set of benchmarks for SHVC-based highdefinition video streaming in loss prone network environments such as those commonly found in mobile networks. Among other results, we highlight that packet losses of only 1% can lead to a substantial reduction in PSNR of over 3dB and error propagation in over 130 pictures following the one in which the loss occurred. This work would be one of the earliest studies in this cutting-edge area that reports benchmark evaluation results for the effects of datagram loss on SHVC picture quality and offers empirical and analytical insights into SHVC adaptation to lossy, mobile networking conditions.
A Low-Cost Pedestrian Detection System with a Single Optical Camera

This paper presents a low-cost solution for pedestrian detection using a single optical video camera on a moving vehicle. Since only one optical camera can collect just a little original information, our system scan two sequential frames to get both appearance and motion information. We use zoom image and slide window techniques to select the objective region, apply a cascaded classifier combined with statistical learning and SVM to recognize human body, adopt zoom-scale to estimate the distance from a pedestrian and develop a distance transform algorithm to forecast his/her orientation. This system is suitable for detecting pedestrians in the range of 0.3-20 meters in the city traffic with the speed under 50 km/h. The test with videos of real city traffic indicates that our system has got acceptable detecting rate and processing speed
Internet group management protocol

• Changed tests 1.4a, 2.1a-b, 2.5a-b, 3.1a-b, and 3.5a-b to use SSM address range (232.0.0.0/8) for source-specific queries. • Corrected typos in tests 1.3b, 2.3b, and 3.3b. • Some devices may not support or may ignore IGMPv3 Member Reports for groups that are not in the SSM address range. Added this to possible problems for all tests that do not use the SSM address range. ACKNOWLEDGMENTS The University of New Hampshire would like to acknowledge the efforts of the following individuals in the development of this test suite. INTRODUCTION Overview The University of New Hampshire's InterOperability Laboratory (IOL) is an institution designed to improve the interoperability of standards based products by providing an environment where a product can be tested against other implementations of a standard. This suite of tests has been developed to help implementers evaluate the functioning of their Internet Group Management Protocol version 3 (IGMPv3) implementations. The tests do not determine if a product conforms to the specifications, nor are they purely interoperability tests. Rather, they provide a method to isolate problems within a device. Successful completion of all tests contained in this suite does not guarantee that the tested device will operate with other IGMPv3 devices. However, these tests provide a reasonable level of confidence that the Router Under Test will function well in most multi-vendor IGMPv3 environments. When several entities of the same type are present in a test configuration, a number is appended to the acronym to yield a label for each entity. For example, if there were three testing routers in the test configuration, they would be labeled TR1, TR2 and TR3. Timers and Default Values: IGMPv3 defines several timers and default values. For the purpose of testing, all configurable timers and values are set to their defaults, unless otherwise noted in the test description. These defaults are given here for reference, taken or calculated from RFC3376: Robustness Variable: 2 Query Interval: 125 seconds Query Response Interval: 100 tenths of a second (10 seconds) TEST ORGANIZATION This document organizes tests by group based on related test methodology or goals. Each group begins with a brief set of comments pertaining to all tests within that group. This is followed by a series of description blocks; each block describes a single test. The format of the description block is as follows: Test Label: The test label and title comprise the first line of the test …
Riding the wave of BYOD: developing a framework for creative pedagogies

Moving innovation in teaching and learning beyond isolated short-term projects is one of the holy grails of educational technology research, which is littered with the debris of a constant stream of comparative studies demonstrating no significant difference between innovative technologies and traditional pedagogical approaches. Meanwhile, the approaching giant wave of the bring your own device (BYOD) movement threatens to overwhelm education practitioners and researchers preoccupied with replicating current practice on mobile devices. A review of the literature indicates that there are yet few well-developed theoretical frameworks for supporting creative pedagogies via BYOD. In this paper, we overview the development of a framework for creative pedagogies that harness the unique affordances of BYOD. This framework has been used across multiple educational contexts and scale from short workshops through to full courses and international collaborative projects. Our key design principles for supporting creative pedagogies via BYOD include modelling collaborative practice via establishing teacher communities of practice to learn about the affordances of mobile devices in relation to new modes of student learning, collaborative curriculum redesign in response to shifts in conceptions of teaching and learning, and collaborating with ICT Services for infrastructure development across the campus. Keywords: Mobile Learning; augmented reality; creative pedagogies; communities of practice; social media (Published: 28 August 2014) Citation: Research in Learning Technology 2014, 22 : 24637 - http://dx.doi. org/10.3402/rlt.v22. 24637
Exploiting unsupervised techniques to predict EFL learner errors

Wrd Lem Tag Phr SynEDRMI < 0 0.167 0.161 0.070 0.042 0.046LL ≤ −7.88 0.136 0.125 0.070 0.042 0.046MI < 0 or LL ≤ −7.88 0.167 0.161 0.070 0.042 0.046MI < 0 and LL ≤ −7.88 0.136 0.125 0.070 0.042 0.046FARMI < 0 0.080 0.078 0.046 0.030 0.034LL ≤ −7.88 0.063 0.055 0.046 0.030 0.034MI < 0 or LL ≤ −7.88 0.080 0.078 0.046 0.030 0.034MI < 0 and LL ≤ −7.88 0.063 0.055 0.046 0.030 0.034
A Survey of Cloud Computing Architecture and Applications in Health

The growth of data produced by the medical and clinical community requires the introduction of advanced techniques and resources in terms of computational and storage capabilities. The different problems and needs that afflict the information technologies for health support conduce to adoption of new infrastructure and application based on cloud computing. The different problems concerning to one side to the managerial, administrative and management aspects, to the other side concern who works as a physician or researcher, that needs the infrastructure to process, store, manage patient data, analysis, diagnosis, and so on. Today, cloud computing represents an important alternative to ensure high performance data processing and easy management of the complex tools in different area and in health. Cloud computing can solve many of these problems providing several advantages in terms of resource management and computational capabilities. In this paper a survey concerning the current models of health that are switching to solutions based on cloud computing, is proposed. Different applications and services are explored and concluded that the use of cloud computing and in particular of hybrid cloud solution can represent a significant opportunity to increase the development of the health sector in all its aspects.
Exchange - rate adjustment in a multicurrency monetary system

A multination monetary system like the European Monetary System (EMS) is intended to concentrate trade and employment within the block of member na tions by stabilising internal exchange rates. Each member nation accepts a defined responsibility for intervention by its central bank to maintain exchange rates within a specified band. Since intermember exchange rates are affected by changes in the ex change rates of individual member currencies with respect to major currencies outside the block, monetary systems like the EMS use a formula to allo cate responsibility among the member nations for counteracting such exogenous disturbances of inter- block exchange rates. Though the rules for assigning responsibility for intervention are clearly stated, their consequences to the member nations are not. For this reason, a simulation model of the EMS was built. (It could, of course, be adapted to represent any similar sys tem.) This paper describes the results of a simula tion study of the EMS based on this model. The study was undertaken to increase understanding of the impact on EMS members of the external economic environment, of changes in the number of members of the EMS, and of changes in their relative trading importance. Simulation was used because the EMS is too complex for conventional mathematical analysis.
The simple model of large scale co-ordinate measuring system and its error analysis

Coordinate measuring system which based on the theory of binocular stereo vision is widely used in many areas, whereas their effective measuring ranges are usually not larger than ten meters. In modern times the surveillance of large scale is used more and more in the civil and military area with the development of camera and computer technology. So based on this requirement this paper developed a new measuring model for this binocular stereo vision measuring system which is proper used in outdoor surveillance to get the 3D coordinate of the moving object. When the distance between two cameras is hundreds meters, the installation and camera calibration are quiet simple and convenient without expensive calibration apparatus and an elaborate setup or a planar pattern shown at a few different orientations or complicated camera imaging model and the parameters of math model are easy to get. After building the model of measuring system error analysis is performed to show influence of every parameter on the measuring system error. Both computer simulation and real data have been used to test the validity of our new simple measuring system model.
Educational Effectiveness and the Computer Conferencing Interface.

SUMMARY Computer conferencing can be a medium for educationally valuable communication, especially for students on distance learning courses. Difficulties which prevent students gaining the full benefits of conferencing are described, many of which are due to the human interface provided by conferencing software on text terminals. A graphical interface has been developed which avoids many of the difficulties. This software runs on local computers under Microsoft Windows and handles connection and subsequent communication with the conferencing software running on a remote host computer. Students can use it on‐line, or off‐line with a local copy of a conference which is automatically updated on connection. The interface is integrated with other applications used by students.
Learning musical structure and style with neural networks

The investigation of neural information structures in music is a rather new, exciting research area bringing together different disciplines such as computer science, musicology, mathematics, and cognitive science. One of its objectives is to develop neural network models that are able to learn from musical compositions the structural elements that characterize a composer's personal style. This has been a starting point for research activities at our institute in recent years. We have the impression that artificial neural networks, when carefully developed, can be sensitive, powerful, and innovative tools for capturing the specificity of a certain composer's style.
Comparison Study of GA and PSO with their Applications to Multi-Objective Power Unit Coordinate Control Problem

Power unit coordinate control problem is a typical non-linear, constrained optimization problem with high computational complexity, in which the optimal solution is balanced between unit load demand and pressure set point. This problem is traditionally solved by fixed nonlinear mapping method, while more and more attention is payed on solving this issue with modern heuristic algorithms, like GA, PSO, etc. This paper presents a comparison study between two typical modern heuristic algorithms with their applications to a 3-objective power unit coordinate control problem. The merits and drawbacks of each algorithm is analyzed via simulation experiments.
The potential for scientific collaboration in virtual ecosystems

This article explores the potential benefits of creating virtual ecosystems from real‐world data. These ecosystems are intended to be realistic virtual representations of environments that may be costly or difficult to access in person. They can be constructed as 3D worlds rendered from stereo video data, augmented with scientific data, and then deployed online for use. The application of virtual ecosystems stretches from interdisciplinary scientific research that may not occur otherwise to providing science students with an environment to conduct studies and virtual field trips in that they would otherwise not have access to.
A multicarrier QAM modulator

A multicarrier quadrature amplitude modulation (QAM) modulator has been developed and implemented with programmable logic devices. The multicarrier QAM modulator contains four CORDIC-based QAM modulators. A conventional QAM modulator needs two multipliers, one adder, and sine/cosine ROM's. The designed CORDIC-based QAM modulator has about the same logic complexity as the two multipliers and the adder with the same word sizes. Each QAM modulator accepts 13-bit in-phase and quadrature data streams, interpolates them by 16, and upconverts the baseband signal to a selected center frequency. The frequencies of the four carriers can be independently adjusted. The proposed multicarrier QAM modulator does not use an analog I/Q modulator, and therefore, the difficulties of adjusting the dc offset, phasing, and the amplitude levels between the in-phase and quadrature-phase signal paths are avoided. The multicarrier QAM modulator is designed to fulfil the spectrum and error vector magnitude (EVM) specifications of the wideband code-division multiple-access (WCDMA) system. The simulated EVM is 1.06% root mean square (rms), well below the specified 12.5% rms for WCDMA. The measured ratio of the integrated first/second/third adjacent channel power (4.096-MHz bandwidth) to the integrated channel power (4.096-MHz bandwidth) is -68.16/-68.24/-66.17 dB versus the specified -45/-55/-55 dB.
Unsupervised acoustic model adaptation algorithm using MLLR in a noisy environment

This paper proposes an unsupervised noisy environment adaptation algorithm based on the HMM acoustic model, using MLLR and a multispeaker database. An arbitrary single sentence uttered by the target speaker, together with living room noise, is used as the input, and the data with superposed noise for environment adaptation are generated from the speech database. By the above procedure, a large amount of adaptation data can be acquired without burdening the speaker. Specifically, the adaptation procedure is composed of the following three stages. (1) Speaker identification by GMM is used to select speakers with short acoustic distances from the input speaker from the database. (2) Utterances read out by the selected speakers are extracted from the database, and living room noise is superposed. (3) Using the constructed speech with superimposed noise as adaptation samples, adaptation by MLLR is performed. Then, by combining the method with unsupervised speaker adaptation based on sufficient statistics and the speaker distance, and HMM synthesis, a highly precise unsupervised integrated adaptation system is constructed. The system is evaluated through large-vocabulary continuous speech recognition, and it is shown that the adaptation model by the proposed method can realize the same or better recognition accuracy than the environment matched model, and realize performance close to supervised MLLR using several tens of samples. In a noisy environment with an SNR of 20 dB, the proposed adaptation system improved the recognition rate from 48.3% to 70.5% in the monophone model, and from 60.1% to 79.9% in the PTM model. © 2005 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 89(3): 48–58, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20227