Miracle-dz/UniFAR-FTUs huggingface dataset:
Microblogging Reposting Mechanism： An Information Adoption Perspective

This study uses the Elaboration Likelihood Model(ELM)and social presence theory to examine the microblogging reposting mechanism.Subjective and objective data were collected from 216 respondents in a field experiment.The results indicate that information quality and source credibility of microblogging messages affect users’reposting intention by affecting their perceptions of the usefulness and enjoyment of the information.Perceived enjoyment has a greater impact on reposting intention than perceived usefulness.Furthermore,users are able to perceive social presence when interacting with microblogging messages.Social presence plays a full mediating role between information quality and perceived enjoyment,and a partial mediating role between information quality and perceived usefulness.
Distributed group support systems: Social dynamics and design dilemmas

A “distributed group support system”; includes decision support tools and structures embedded within a computer‐mediated communication system rather than installed in a “decision room. ”; It should support groups who are distributed in space but not time ("synchronous”; groups), as well as “asynchronous”; groups whose members participate at different times. Pilot studies conducted in preparation for a series of controlled experiments are reviewed in order to identify some of the problems of implementing such a system. Many of the means used by groups meeting in the same place at the same time to coordinate their activities are missing. Embedding decision support tools within a different communications medium and environment changes the way they “work. ”; Speculations are presented about software tools and structuring or facilitation procedures that might replace the “missing”; coordination channels.
Rainfall‐Runoff Modeling Based on Genetic Programming

The runoff formation process is believed to be highly nonlinear, time varying, spatially distributed, and not easily described by simple models. Considerable time and effort has been directed to model this process, and many hydrologic models have been built specifically for this purpose. All of them, however, require significant amounts of data for their respective calibration and validation. Using physical models raises issues of collecting the appropriate data with sufficient accuracy. In most cases, it is difficult to collect all the data necessary for such a model. By using data-driven models such as genetic programming (GP), one can attempt to model runoff on the basis of available hydrometeorological data. This work addresses the use of GP for creating rainfall-runoff (R-R) models both on the basis of data alone, as well as in combination with conceptual models (i.e taking advantage of knowledge about the problem domain). Keywords: genetic programming; symbolic regression; empirical equations; rainfall-runoff
Movie scene recognition with Convolutional Neural Networks

While the problem of scene recognition is not new, it is still a challenging problem on which a lot of work can be done to improve the recognition result. For a really long time methods of computer vision and machine learning cannot match human performance regarding tasks like recognition of objects and scene classification. It is especially true when it comes to movie scene recognition since movie frames tends to have objects or person in the foreground and the background is often blurred. But with the repaid development of computational ability of PCs especially in GPU computation, and new methods like Convolutional Neural Network together with large database with labels, now it is possible to outperform human recognition and classification. In this master thesis, a large deep Convolutional Neural Network is trained to classify movie scenes, general datasets are combined with movie specific datasets as both training dataset and validation dataset. The movie is pre-edited into movie segments using a scene switching detection algorithm and a subtitle analysis algorithm. The Network does not examine only movie frames but rather sequence of selected frames to build a stronger scene classifier.
Adaptive feedforward/feedback detection architectures for wideband CDMA

Detectors for high data rate wideband code-division multiple access (CDMA) networks must contend with both multiple access interference (MAI) and intersymbol interference (ISI). Our reverse link detector suppresses the MAI and ISI with a feedforward filter (FFF) which linearly processes the samples at the output of parallel chip matched filters (CMFs), and a feedback filter (FBF) which linearly processes detected symbols. We propose a fully-connected (FC) architecture whose synergy arises from sharing FFF and FBF contents among users to enable efficient multiuser recursive least-squares (RLS) adaptation towards the minimum mean-square error (MMSE) coefficients. Simulations validate the theoretical BER analysis and demonstrate that the FC detector trains in several hundred symbols, avoids severe error propagation, and supports 8 simultaneous 2 Mb/s QPSK users in an asynchronous CDMA system with a processing gain of 8, a delay spread of 1.25 /spl mu/s, an average SNR of 15 dB, with uncoded BERs less than 10/sup -4/ and 10/sup -3/ with 97% and 99.3% probabilities, respectively.
Using Electronic Messaging to Improve the Quality of Instruction.

Abstract Total quality management requires rapid feedback on performance and an ability to remain close to the customer. Electronic messaging (EM) can provide this capability in traditional instructional settings. This study investigated whether electronic mail and computer conferencing improved course quality and teaching effectiveness for several business administration courses in management information systems. The results, supported by both qualitative and quantitative (survey) data, showed that electronic messaging enabled the instructor to be more accessible and responsive to the students. Additionally, the use of computer conferencing enabled the class to develop a greater level of cohesion. Overall, use of EM increased the perceived quality of the course and the effectiveness of the instructor.
Seasonal climate forecasting

The fascination of seasonal climate forecasting, of which El Niño forecasting is the prime example, comes from its multi‐faceted character. Not only does it pose interesting new challenges for the climate scientific community but also it is naturally linked to a great variety of socio‐economic applications. Seasonal climate forecasts are indeed becoming a most important element in some policy/decision making systems, especially within the context of climate change adaptation. Thus, seriously considering the management of risks posed by the variability of climate on the seasonal to interannual time scale is key to achieving the longer terms goals of climate change adaptation strategy. This review paper explores the main components needed to construct a seasonal forecasting system, from the physical basis of climate seasonal predictions, to the tools used for producing them, to the importance of assessing their skill, to their use in risk management decision‐making. Future challenges are also examined. Copyright © 2010 Royal Meteorological Society
Similarity and Compatibility in Fuzzy Set Theory – Assessment and Applications

AMITY SCHOOL OF ENGINEERING AND TECHNOLOGY Wed, 22 May 2019 03:39:00 GMT amity school of engineering & technology offers b.tech in different streams Peer Reviewed Journal IJERA.com Mon, 20 May 2019 16:35:00 GMT International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research . Join LiveJournal Fri, 24 May 2019 01:57:00 GMT Password requirements: 6 to 30 characters long; ASCII characters only (characters found on a standard US keyboard); must contain at least 4 different symbols;
CALL: past, present and future — a bibliometric approach

A bibliometric approach is used not only to sketch out the development of CALL during the last 25 years, but also to assess the contribution of educational technology to 21st century foreign-language teaching and learning. This study is based on the six instalments of the author’s International (and multilingual) Bibliography of Computer Assisted Language Learning and the 5,301 entries contained therein. The once text-based bibliography has been transformed into a searchable database. Since index terms to describe both the contents and the nature of individual publications have been attached to the bibliographic data, it is now possible to query whether the 25,000 descriptors cluster around certain topics and to depict developments chronologically. The statistical evaluation of a large corpus also avoids the pitfalls of selective interpretation. Recent controversies about the chronologisation of CALL events as well as the internal consistency of such time chunks are addressed. The data suggest that the online/offline divide occurs around 1993 and that the latest additions to the foreign language teacher’s tool box – from e-mails to voicechats – overcome the language acquisition/language learning barrier. New and student-oriented forms of dealing with foreign language learning come to the fore. This has induced some researchers to concentrate on events where conversation breaks down, because learners must then ask for modified input or negotiate the meanings of lexical items. Such a strategy promises success in instructed second-language acquisition. It is suggested, however, that the foreign language teacher’s intervention is a necessary complement to second-language developmental processes. Educational technology may allow the teacher to let nature run its course nowadays. But when nature is unsympathetic to the cause of foreign language learning the teacher must rein in the student’s language acquisition device to protect him or her from certain sanctions the target community holds in store for the unsuccessful learner.
Instructor Based Training versus Computer Based Training—A Comparative Study

This article describes two studies conducted to compare assembly performance and learning rate between computer based training and traditional training of skilled assembly operators. The studies were performed with pre-series production parts from a car cockpit and they were integrated as part of the overall training activities during a new vehicle product launch. The computer based training tool used was a desktop based commercial VR tool with focus on cognitive interactive procedural learning. Both studies indicate that computer based training can replace instructor based training for this level of assembly complexity and that it has a positive effect in preparing skilled operators.
Indexing and abstracting by association

This article discusses the possibility of exploiting the statistics of word co-occurrence in text for purposes of document retrieval. Co-occurrence is defined and related to the mental processes of authors and readers; several means of quantitative measurement of word co-occurrence are then scrutinized. It is shown that the most strongly co-occurring word pairs, which are therefore “associated” in a statistical sense, can be represented in the form of an “association map. ” The last half of the article presents two modes of use of association maps in literature searching.
The impact of object working memory on timing

Nontemporal information processing involving short-term memory requirements disturbs time estimation. Previous studies mostly used letters or digits, which are maintained in working memory by phonological loops. Since verbal and nonverbal information are processed by separate working-memory subsystems, how do nonverbal, object-based memory tasks affect time estimation? We manipulated visual object memory load using the magic cube materials. Participants were divided into three groups, who completed a reaction-time task (control task), a memory-recognition task interposed by an attempt to produce a 2500-ms time interval (active processing), and a memory-recognition task following time interval production (passive retention). The produced time increased with increasing memory-object size under both the active processing and passive retention conditions; mean produced time interval did not significantly differ between the two experimental conditions. By comparing the reaction times and error rates of a relevant task, we excluded any speed–accuracy tradeoff during timing. This result suggests that when the working-memory information to be processed includes objects requiring attention for retention, the production of time intervals is also affected by memory item maintenance.
ACO-Based Routing Algorithm for Cognitive Radio Networks

Cognitive Radio Networks (CRNs) are an outstanding solution to improve efficiency of spectrum usage. Secondary users in cognitive networks may select from a set of available channels to use provided that the occupancy does not affect the prioritized licensed users. However, CRNs produce unique routing challenges due to the high fluctuation in the available spectrum as well as diverse quality-of-service (QoS) requirements. In CRNs, distributed multihop architecture and time varying spectrum availability are some of the key factors in design of routing algorithms. In this paper, we develop an ant-colony-optimization- (ACO-) based on-demand cognitive routing algorithm (ACO-OCR), jointly consider path and spectrum scheduling, and take advantage of the availability of multiple channels, to improve the delivery latency and packet loss rate. Then, an analytical framework based on M/G/1 queuing theory is introduced to illustrate the relay node queuing model. The performances of ACO-OCR have been evaluated by means of numerical simulations, and the experimental results confirm its effectiveness. Simulation results show that ACO-OCR outperforms other routing approaches in end-to-end path latency and package loss rate.
Processor-Sharing Models for Integrated-Services Networks

• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
How much camera separation should be used for the capture and presentation of 3D stereoscopic imagery on binocular HMDs?

Designers, researchers, and users of binocular stereoscopic head- or helmet-mounted displays (HMDs) face the tricky issue of what imagery to present in their particular displays, and how to do so effectively. Stereoscopic imagery must often be created in-house with a 3D graphics program or from within a 3D virtual environment, or stereoscopic photos/videos must be carefully captured, perhaps for relaying to an operator in a teleoperative system. In such situations, the question arises as to what camera separation (real or virtual) is appropriate or desirable for end-users and operators. We review some of the relevant literature regarding the question of stereo pair camera separation using deskmounted or larger scale stereoscopic displays, and employ our findings to potential HMD applications, including command & control, teleoperation, information and scientific visualization, and entertainment.
New Strategy for the Synthesis of Oligodeoxynucleotides Bearing Adducts at Exocyclic Amino Sites of Purine Nucleosides

Report a novel postoligomerization strategy that provides complete regiochemical and stereochemical control of adduction. In this method the natural polarity of reaction, i.e., with the heterocyclic base as the nucleophilic species and the adducting moiety as electrophile, is reversed. Thus, an amino derivative of the mutagen is used to displace halogen from the appropriate halo-substituted heterocyclic species. The key to the present method is that the displacement reaction is carried out while the oligomer is still attached to the solide support
Internet tools in teaching quantitative economics: why gaps between potential and reality?

The use of Internet tools in economic pedagogy is growing. This paper attempts to investigate the impact of Internet tools, as a supplement to traditional teaching methods, on teaching and learning and attempts to answer the question why there are gaps between potential and reality of using Internet tools in economics education, based on our experience of integrating e‐learning into courses at Lancaster University. Responses to student questionnaires suggest that the practical features of e‐learning which are most successful at enhancing the learning experience are: the noticeboard, discussion space, multiple‐choice questions and freedom of expression anonymously. Moreover, the degree of the impact of these e‐learning features is affected by network access, residence off campus and student gender. In spite of the enormous potential of the Internet tools in higher education, it is found that much of it is not fully realized due to the problems encountered by lecturers/tutors and students and technical difficulties. It is important to note the many challenges associated with e‐learning which are yet to be debated and resolved.
Mathematical Aspects of the Implementation of Particle Filters on FPGA

Abstract Particle filters are a type of Bayesian filters commonly used for system state estimation such as tracking and localization applications. Tracking and localization are important tasks for autonomous robots, and particle filters are particularly well suited to deal with such tasks, as demonstrated by many RoboCup-Teams. However the computational complexity of particle filters lead to a high load of the Central Processing Unit (CPU) resulting in a high clock and a high energy usage. This limits the use of particle filters in small autonomous robots or intelligent embedded sensor for traffic surveillance. The algorithm is well suited for parallel execution, on customized hardware architectures. Such architectures can be realized using Field Programmable Gate Arrays (FPGA). The parallel execution leads to a significant reduction of clock and therefore of energy, making embedded high performance particle filters possible, relieving the CPU from a computational expensive task while providing high performance tracking capabilities. For reasons of logical cell usage the use of fixed point representations of the numbers involved in the computation of the algorithm is used. This poses a bigger problem than one might expect, as the original theory of the particle filter is based on continuous representations, and the algorithm won't work without modifications to counter the effects resulting from the limited precision of the fixed point number representation. A fixed point based particle filter for tracking of an object in six dimensions, 2D-translation, rotation, and translation and rotation speed has been implemented on a FPGA and the feasibility of some treatment approaches has been shown.
Integrating a corpus of classroom discourse in language teacher education: the case of discourse markers

While language teacher education programmes and language syllabi in secondary education encourage the use of the target language in the classroom, resources to support teachers in this endeavour, such as books with useful phrases, do not state that the examples they provide are corpus-based, i.e. drawn from actual language use rather than invented phrases. This paper investigates whether consultation of a corpus of classroom discourse can be of benefit in language teacher education. The paper describes a project involving the creation of corpora of classroom discourse in French and Spanish, and the use of these corpora with student teachers. After setting the research in the context of corpora and classroom interaction, it examines issues such as the content of the corpora, the type of consultation (direct or mediated by the teacher), and the student teachers’ evaluation of the activity. Special attention is paid to one particular aspect of classroom interaction, discourse markers.
An application of ensemble/multi model approach for wind power production forecasting

Abstract. The wind power forecasts of the 3 days ahead period are becoming always more useful and important in reducing the problem of grid integration and energy price trading due to the increasing wind power penetration. Therefore it's clear that the accuracy of this forecast is one of the most important requirements for a successful application. The wind power forecast applied in this study is based on meteorological models that provide the 3 days ahead wind data. A Model Output Statistic correction is then performed to reduce systematic error caused, for instance, by a wrong representation of surface roughness or topography in the meteorological models. For this purpose a training of a Neural Network (NN) to link directly the forecasted meteorological data and the power data has been performed. One wind farm has been examined located in a mountain area in the south of Italy (Sicily). First we compare the performances of a prediction based on meteorological data coming from a single model with those obtained by the combination of models (RAMS, ECMWF deterministic, LAMI). It is shown that the multi models approach reduces the day-ahead normalized RMSE forecast error (normalized by nominal power) of at least 1% compared to the singles models approach. Finally we have focused on the possibility of using the ensemble model system (EPS by ECMWF) to estimate the hourly, three days ahead, power forecast accuracy. Contingency diagram between RMSE of the deterministic power forecast and the ensemble members spread of wind forecast have been produced. From this first analysis it seems that ensemble spread could be used as an indicator of the forecast's accuracy at least for the first three days ahead period.
Simulation of Piecewise-Linear One-Dimensional Chaotic Maps by Verilog-A

ABSTRACT Piecewise-linear one-dimensional (PL1D) chaotic maps have simple mathematical descriptions, while their behaviour is rich and complex. This nature is ideal for the development of integrated circuit (IC) designs and applications. Moreover, one needs to determine the conditions from which PL1D maps can become chaotic. With this in mind, this article introduces the high-level behavioural simulation of PL1D chaotic maps by Verilog-A descriptions, from which one can find the values guaranteeing the conditions to maintain chaotic behaviour, and then one can synthesize the block descriptions to the transistor level of abstraction, e.g. linking simulation program with integrated circuits emphasis (SPICE) simulations. In this manner, we highlight that this can be the first step in a top-down IC design flow for the successful implementation of integrated PL1D chaotic maps.
Virtual reality hemianopic scotomas induce eccentric fixation scanpath strategies to optimize high-level vision in healthy subjects

Normal Subjects (Ss) show a stairstep/overshoot saccadic strategy similar to hemianopic patients either when confronted with a virtual reality model of an artificial hemianopia using eye position feedback (H3-VRM), or when achieving eccentric fixation using 2ndVFB. Here gaze position is displayed simultaneously with the target and the subject learns either to superpose target and eye position feedback, or to position the gaze feedback target up to 9 deg off the target (eccentric fixation) which helps to keep the "blind side" in sight. Using this technique normal Ss confronted with H3-VRM as well as hemianopic patients minimize their deficit very fast and efficiently-faster than without 2ndVFB training.