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Record W1968098382 · doi:10.1002/dac.1386

Ubiquitous computing for communications and broadcasting

2012· article· en· W1968098382 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Communication Systems · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Network Optimization
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsComputer scienceUbiquitous computingBroadcasting (networking)Presentation (obstetrics)Focus (optics)Wireless sensor networkQuality (philosophy)Data scienceMultimediaTelecommunicationsHuman–computer interactionComputer securityComputer network

Abstract

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Ubiquitous computing (Ubi-Com) aims to cover the topics of seamless, secure, and intuitive access for distributed processing of various ubiquitous computing applications. Because the technology is evolving into the direction of wireless and the fast processing speed is also getting more attention, there have been many efforts to support the ubiquitous computing through distributed and parallel processing over the scattered networks. Specially, Ubiquitous Communication and Broadcasting are the core technologies for Ubi-Com. This special issue provides an international forum for the presentation and showcase of recent advances on various aspects of Ubiquitous Communication and Broadcasting (UCB). It will reflect the state-of-the-art of the computational methods, involving theory, algorithm, numerical simulation, error and uncertainty analysis and/or novel applications of new processing techniques in engineering, science, and other disciplines related to the UCB. The published papers are expected to focus on novel approaches for the UCB and to present high quality results for tackling problems arising from the ever-growing UCB. This special issue will serve as a landmark source for education, information, and reference to students, professionals, and researchers interested in updating their knowledge about or active in UCB models and services. We have received many manuscripts. Only seven manuscripts of high quality were finally selected for this special issue. Each manuscript selected was blindly reviewed by at least three reviewers consisting of guest editors and external reviewers. We present a brief overview of each manuscript in the following. The first paper entitled ‘A sliding window-based false-negative approach for ubiquitous data stream analysis’ by Younghee Kim et al. propose a method for a false-negative approach based on the Chernoff bound for efficient analysis of the data stream. Hence, we consider the problem of approximating frequency counts for space-efficient computation over data stream sliding windows. We show that a false-negative approach allowing a controlled number of frequent itemsets to be missing from the output is a more promising solution for mining frequent itemsets from a ubiquitous data stream. These are simple to implement, and have provable quality, space, and time guarantees. The experimental results have shown that the proposed algorithms achieve a high accuracy of at least 99% and require a small execution time. The second paper entitled ‘A new query-by-humming system based on the score level fusion of two classifiers’ by Gi Pyo Nam et al. propose a new method of query-by-humming (QBH) based on the score level fusion of two classifiers. This research is novel in the following three ways as compared with previous works. First, the features of the humming data are extracted by using musical note estimation based on the spectro-temporal autocorrelation. The extracted features are normalized by using the mean-shifting, median filtering, average filtering, and min–max scaling methods. Second, a pitch-based dynamic time warping method is used as the first classifier. The linear scaling method is used with the quantized binary (QB) code of the pitch data as the second classifier. Third, through the combination of these two classifiers based on the score level by the MIN rule, the performance of QBH is much enhanced. Experimental results with the 2006 MIREX QBSH and 2009 MIR-QBSH corpus databases showed that the performance of the proposed fusion method was best compared with single classifier and other fusion methods. Another paper in this special issue, entitled ‘Efficient uplink scheduling policy for variable bit rate traffic in IEEE 802.16 BWA systems’ by Yeong-Sheng Chen et al. propose an uplink scheduling algorithm for variable bit rate (VBR) traffic transmission for IEEE 802.16 BWA systems. In the proposed algorithm, the base station (BS) assigns uplink bandwidth to the video user by considering the traffic state transitions. The uplink bandwidth is equally divided into several intervals where each interval represents a traffic state. Only when the traffic state is changed is the bandwidth request process incurred. Also, by using two reserved bits in the generic medium access control header of IEEE 802.16 BWA systems as piggyback bits, the information about traffic state transition can be sent to the BS without extra overhead. Simulations conducted with QualNet 4.0 show that the bandwidth waste ratio of our proposed algorithm is less than that of the conventional algorithms. That is, the proposed algorithm outperforms the conventional algorithms for VBR traffic transmission in IEEE 802.16 BWA systems in terms of bandwidth utilization. The fourth paper entitled ‘Color recognition with compact color features’ by Sun-Mi Park et al. propose a method of reducing the feature vector dimension by a factor of 170 based on combining two techniques: (i) projecting a color histogram generated in 3D color space into 2D color planes and (ii) converting the color histograms to class histograms using a naive Bayesian classifier. The resulting feature vectors are then classified using a support vector machine method and template matching method to recognize the object colors. With both classification methods, a better recognition rate is achieved than when using the original large feature vectors. The fifth paper entitled ‘Integrating multimedia streaming from heterogeneous sources to JavaME mobile devices’ M. Delgado Calvo-Flores et al. integrates environmental multimedia resources (IP cameras, Webcams, Aibo cameras, and microphones) to be played in real time over virtual machines, in particular, using JavaME devices. They also present the techniques for generating multimedia streaming from the virtual machines accessing the cameras and microphones of mobile devices. The next paper entitled ‘An early collision warning algorithm for vehicles based on V2V communication’ by Chung-Ming Huang et al. proposes an algorithm named Early Collision Warning Algorithm (ECWA). In ECWA, vehicles broadcast relationship information (RI) to neighboring vehicles periodically. Each vehicle calculates whether potential collisions may happen or not upon receiving RI messages. After calculation, ECWA sends warning messages to drivers if the collision will occur. ECWA allows drivers to set the warning level and warning distance by themselves. In our simulation, not only vehicles' collisions at an intersection were simulated but also the GPS error range was considered in our design. The results show that ECWA has good performance and can always alert drivers suitably if the GPS error range was small. Even though the GPS error range is large, ECWA also can enhance the hit rate of warning messages. The last paper entitled ‘A service-oriented taxonomical spectrum, cloudy challenges and opportunities of cloud computing’ by Bhaskar Prasad Rimal et al. proposes a service-oriented taxonomical spectrum of cloud computing, which is more focused on the service engineering perspective of cloud. Their argument behind cloud engineering is a layered structural approach ‘as a Service’ such as security as a service, fault tolerance as a service, and architecture as a service. The main contribution of this paper is to identify a wide spectrum of taxonomy, aiming at a better understanding of functional and architectural components that could benefit from cloudification. Each subtaxonomy is described (architecture, core services, security, fault tolerance, management services etc.) in detail. In addition, a comparative study of several cloud systems is presented based on taxonomy. Moreover, the paper also identifies many challenges and opportunities that exist on the landscape of enterprise cloud. Finally, our special thanks go to Prof. Mohammad S. Obaidat who is Editor-in-Chief of the International Journal of Communication Systems journal and the editorial staff for their valuable support throughout the preparation and publication of this special issue. We would like to thank all authors for their contributions to this special issue. We also extend our thanks to the external reviewers for their excellent help in reviewing the manuscripts.

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Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.905
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.302
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it