ppxscal/embedding_network huggingface dataset:
An analog squaring technique based on asynchronous sigma-delta modulation
Authors: F. Colodra, A. Torralba, J. L. Mora, J. M. Martínez-Heredia
Venue: IEEE Transactions on Circuits and Systems II: Express Briefs (2009)

Accurate analog squarers are required for different signal processing functions, such as amplitude modulation, frequency shifting, signal power estimation, and neural and image processing. Transistor-level analog squarers suffer from limited accuracy, particularly in modern deep-submicrometer technology, where the squared law of the MOS transistor in the saturation region is no longer valid. Based on the asynchronous sigma-delta modulator (ASDM), a new circuit that provides the squared value of the input signal is proposed. For slowly varying input signals, the filtered output is a replica of the squared input signal. In this brief, the proposed analog squarer is studied, and the analytical results are validated by simulation in the time domain. The effect of analog imperfections on the accuracy of the squarer is also analyzed by showing that a high signal-to-noise-plus-distortion ratio can be obtained for typical values of the mismatch and up to frequencies near half the maximum frequency of the ASDM limit cycle.
Web-based assessment and examination system: from experiment to practice
Authors: Jerzy Rutkowski, Katarzyna Moscinska, Piotr Jantos
Venue: Proceedings of the 10th IASTED International Conference on Computers and Advanced Technology in Education (2007)

The Circuit Theory course at Silesian University of Technology, Gliwice, Poland has been recently converted into blended model and various forms of web-based formative and summative assessment have been implemented [1], [2]. In the paper the development of close-ended Computer Assisted exam has been presented. The new repository has been created based on the results of previous exams. The detailed statistical analysis of the exam results has been performed with respect to students' outcomes as well as particular questions performance. We present the results of students' survey on web-based assessment and the comments of the staff with respect to new idea of examination. The paper enlightens the numerous advantages of Computer Assisted exam and provides some tips for teachers, especially in case of technical university courses.
Space sense random access with collision mitigation in uplink WLANs
Authors: Chengkang Pan, Yueming Cai, Xiaofu Wu, Weiwei Yang, Youyun Xu
Venue: IEEE Communications Letters (2009)

Space sense random access (SSRA) with collision mitigation is proposed for TDD wireless local area networks (WLANs) with multiple antennas. Before transmitting a packet, the user performs space sense to detect the status of the channel. If the channel is idle, it then transmits a common training sequence for channel estimation. Multiple subslots are available for channel estimation and the user randomly selects one subslot to achieve the possible collision-free channel estimation. It is shown that SSRA removes the requirement of orthogonal training sequences while avoiding possible packet collision and further providing multipacket reception capability. Compared to the conventional slotted ALOHA scheme, SSRA can achieve much higher throughput, as verified by extensive simulation results.
Simple design of detector in the presence of frequency offset for IEEE 802.15.4 LR-WPANs
Authors: Daesik Park, Chester Sungchung Park, Kwyro Lee
Venue: IEEE Transactions on Circuits and Systems II: Express Briefs (2009)

A simple detector for orthogonal modulation that is robust to large frequency offsets is proposed. The complexity of the detector is significantly reduced by implementing the correlator using multiplexers instead of complex floating-point multiplications. The performance of this design is comparable to the optimal value obtained by double correlation in offset quadrature phase-shift keying (O-QPSK) and nearly reaches that of noncoherent maximum likelihood (NCOHML) detection with 10-ppm frequency offset in the additive white Gaussian noise (AWGN) channel. Therefore, the proposed design can be used in low-cost and low-power IEEE 802.15.4 low-rate wireless personal area network (LR-WPAN) applications.
An extended Markov blanket approach to proteomic biomarker detection from high-resolution mass spectrometry data
Authors: Jung Hun Oh, Prem Gurnani, John Schorge, Kevin P. Rosenblatt, Jean X. Gao
Venue: IEEE Transactions on Information Technology in Biomedicine (2009)

High-resolution matrix-assisted laser desorption/ionization time-of-flight mass spectrometry has recently shown promise as a screening tool for detecting discriminatory peptide/protein patterns. The major computational obstacle in finding such patterns is the large number of mass/charge peaks (features, biomarkers, data points) in a spectrum. To tackle this problem, we have developed methods for data preprocessing and biomarker selection. The preprocessing consists of binning, baseline correction, and normalization. An algorithm, extended Markov blanket, is developed for biomarker detection, which combines redundant feature removal and discriminant feature selection. The biomarker selection couples with support vector machine to achieve sample prediction from high-resolution proteomic profiles. Our algorithm is applied to recurrent ovarian cancer study that contains platinum-sensitive and platinum-resistant samples after treatment. Experiments show that the proposed method performs better than other feature selection algorithms. In particular, our algorithm yields good performance in terms of both sensitivity and specificity as compared to other methods.
Positional error modeling for line simplification based on automatic shape similarity analysis in GIS
Authors: Chui Kwan Cheung, Wenzhong Shi
Venue: Computers Geosciences (2006)

Automatic generalization is a process for representing geographical objects with different degrees of detail on a digital map. The positional error for each geographical object is propagated through the process and a generalization error is also introduced by the generalization. Previous research has focused mainly on measuring the generalization error. This paper presents an analytical model for assessing the positional error in the generalized object by considering both error propagation from the original data and the generalization error. The analytical model provides a shape dissimilarity value that indicates the shape difference between the original data with a positional error and its simplified version. This model is able to objectively and automatically determine the applicability of the generalized data for further applications to geographical information system (GIS) problems. It can also deal with a large amount of data in GIS. Therefore, the analytical model presented, which provides a more comprehensive shape measure for assessing positional error in data derived from the generalization, is valuable in the development of automatic generalization.
Developing teachers' technology skills in a laptop initiative
Authors: Paul B. McKimmy, Peter Leong
Venue: Proceedings of the 10th IASTED International Conference on Computers and Advanced Technology in Education (2007)

The College of Education at the University of Hawai'i-Manoa, like many institutions, wrestles with the challenge of developing students' technology skills. Moreover, maintaining a hardware and software infrastructure that supports technology-integrated teaching is costly and difficult to maintain. Addressing both challenges, the College of Education implemented a one-to-one laptop program in 2005. By requiring continuous access to an Internet-connected laptop, the College hoped to improve student technology skills and to increase technology integration throughout its courses. The authors developed the Technology Skills Inventory to examine students' skill levels and skill development during this initiative. The Inventory consisted of 43 statements regarding students' abilities in performing tasks with a computer. The authors concluded that students who completed a teacher preparation program reported higher basic and personal/professional skills with computers, but were unable to draw conclusions about students' instructional application of technology skills.
Synchronization: an obstacle to identification of network topology
Authors: Liang Chen, Jun-An Lu, Chi K. Tse
Venue: IEEE Transactions on Circuits and Systems II: Express Briefs (2009)

Identification of network topology is an important issue for physics, biology, engineering, and other science disciplines. Under the application of an adaptive-feedback control algorithm, we explore a process through which the topology of an unknown dynamical network can be identified. Analytical results show that the key to guaranteeing successful topology identification is the existence of the condition that all coupling terms of the unknown network are linearly independent of the synchronization manifold between the drive (unknown) network and a response network. When complete synchronization is achieved in the unknown network, the linearly independent condition is no longer satisfied, making its topology unidentifiable. We also find that partial synchronization in the unknown network implies a part of topology being unidentifiable. The results can be extended to projection synchronization and some generalized synchronization. Furthermore, we show that when the network dynamical equation is stable, its topology can be identified subject to some limitations. Finally, a method of avoiding synchronization for a network is presented and verified by numerical simulations.
GIS-based NEXRAD Stage III precipitation database: automated approaches for data processing and visualization
Authors: Hongjie Xie, Xiaobing Zhou, Enrique R. Vivoni, Jan M. H. Hendrickx, Eric E. Small
Venue: Computers Geosciences (2005)

This study develops a geographical information system (GIS) approach for automated processing of the Next Generation Weather Radar (NEXRAD) Stage III precipitation data. The automated processing system, implemented by using commercial GIS and a number of Perl scripts and C/C++ programs, allows for rapid data display, requires less storage capacity, and provides the analytical and data visualization tools inherent in GIS as compared to traditional methods. In this paper, we illustrate the development of automatic techniques to preprocess raw NEXRAD Stage III data, transform the data to a GIS format, select regions of interest, and retrieve statistical rainfall analysis over user-defined spatial and temporal scales. Computational expense is reduced significantly using the GIS-based automated techniques. For example, 1-year Stage III data processing (~9000 files) for the West Gulf River Forecast Center takes about 3 days of computation time instead of months of manual work. To illustrate the radar precipitation database and its visualization capabilities, we present three application examples: (1) GIS-based data visualization and integration, and ArcIMS-based web visualization and publication system, (2) a spatial-temporal analysis of monsoon rainfall patterns over the Rio Grande River Basin, and (3) the potential of GIS-based radar data for distributed watershed models. We conclude by discussing the potential applications of automated techniques for radar rainfall processing and its integration with GIS-based hydrologic information systems.
Improving face recognition via narrowband spectral range selection using Jeffrey divergence
Authors: Hong Chang, Yi Yao, Andreas Koschan, Besma Abidi, Mongi Abidi
Venue: IEEE Transactions on Information Forensics and Security (2009)

In order to achieve improved recognition performance in comparison with conventional broadband images, this paper addresses a new method that automatically specifies the optimal spectral range for multispectral face images according to given illuminations. The novelty of our method lies in the introduction of a distribution separation measure and the selection of the optimal spectral range by ranking these separation values. The selected spectral ranges are consistent with the physics analysis of the multispectral imaging process. The fused images from these chosen spectral ranges are verified to outperform the conventional broadband images by 3%-20%, based on a variety of experiments with indoor and outdoor illuminations using two well-recognized face-recognition engines. Our discovery can be practically used for a new customized sensor design associated with given illuminations for improved face-recognition performance over the conventional broadband images.
An algorithm for optimal resource allocation in cellular networks with elastic traffic
Authors: Marcin Wiczanowski, Holger Boche, Slawomir Stanczak
Venue: IEEE Transactions on Communications (2009)

In this letter we propose a power allocation iteration which optimizes the weighted aggregate performance of a single-hop network. We show that the proposed iteration is a competitive alternative to conventional gradient iterations in terms of convergence and computational effort.
New delay-dependent global exponential stability criterion for cellular-type neural networks with time-varying delays
Authors: Cheng-De Zheng, Huaguang Zhang, Zhanshan Wang
Venue: IEEE Transactions on Circuits and Systems II: Express Briefs (2009)

The problem ensuring the global exponential stability (GES) of a class of delayed cellular neural networks (CNNs) with time-varying delays is studied. Without assuming the boundedness of the activation functions, by applying the idea of the Lyapunov function, the linear matrix inequality (LMI) techniques, the free-weighting matrix method, and a novel equation, a new sufficient condition for the GES of CNNs with time-varying delays is obtained, which generalizes the previous results in the literature. The criterion is easy to be verified since it takes the form of an LMI. Three numerical examples are given to illustrate the effectiveness and less conservativeness of our proposed method.
A control chart pattern recognition system using a statistical correlation coefficient method
Authors: Jenn-Hwai Yang, Miin-Shen Yang
Venue: Computers and Industrial Engineering (2005)

This paper presents a control chart pattern recognition system using a statistical correlation coefficient method. Pattern recognition techniques have been widely applied to identify unnatural patterns in control charts. Most of them are capable of recognizing a single unnatural pattern for different abnormal types. However, before an unnatural pattern occurs, a change point from normal to abnormal may appear at any point in control charts for most practical cases. Moreover, concurrent patterns where two unnatural patterns simultaneously exist may also occur in a control chart pattern recognition system. Our statistical correlation coefficient approach is a simple mechanism for recognizing these unnatural control chart patterns with good performance. This approach is also an effective method for the control chart pattern recognition without a tedious training process.
A hybrid learning-based model for on-line detection and analysis of control chart patterns
Authors: Ruey-Shiang Guh
Venue: Computers and Industrial Engineering (2005)

Unnatural control chart patterns (CCPs) are associated with a particular set of assignable causes for process variation. Therefore, effectively recognizing CCPs can substantially narrow down the set of possible causes to be examined, and accelerate the diagnostic search. In recent years, neural networks (NNs) have been successfully used to the CCP recognition task. The emphasis has been on the CCP detection rather than more detailed quantification of information of the CCP. Additionally, a common problem in existing NN-based CCP recognition methods is that of discriminating between various types of CCP that share similar features in a real-time recognition scheme. This work presents a hybrid learning-based model, which integrates NN and DT learning techniques, to detect and discriminate typical unnatural CCPs, while identifying the major parameter (such as the shift displacement or trend slope) and starting point of the CCP detected. The performance of the model was evaluated by simulation, and numerical and graphical results that demonstrate that the proposed model performs effectively and efficiently in on-line CCP recognition task are provided. Although this work considers the specific application of a real-time CCP recognition model for the individuals (X) chart, the proposed learning-based methodology can be applied to other control charts (such as the X-bar chart).
Group-synchronized polling algorithm in WDM-EPON
Authors: Hye Kyung Lee, Hyunseung Choo, Tae-Jin Lee, Min Young Chung
Venue: IEEE Communications Letters (2009)

Wavelength Division Multiplexing-Ethernet Passive Optical Network (WDM-EPON) technology yields evolutionary advantages which enable next generation broadband access networks to overcome the bandwidth limit of EPON. To effectively share uplink resources of Inter-Optical Network Units (ONUs) in WDM-EPON, we propose a Group-Synchronized Polling Algorithm (GSPA). In GSPA, ONUs are partitioned into g (> 2) groups and each group fully uses one among m (≥ 2) uplink wavelengths during a predetermined time TRef. Since the starting times of groups are inter-weaved with different wavelengths to enable groups to transmit frames to an Optical Line Terminator (OLT), the GSPA can perform Dynamic Bandwidth Allocation (DBA) in parallel without wasting uplink resources. Comprehensive simulation results show that GSPA yields better performance compared with both the existing Offline and On-The-Fly algorithms.
Unsupervised binning of environmental genomic fragments based on an error robust selection of l-mers
Authors: Bin Yang, Yu Peng, Henry C.M. Leung, S. M. Yiu, J. C. Chen, Francis Y.L. Chin
Venue: Proceeding of the third international workshop on Data and text mining in bioinformatics (2009)

With the rapid development of genome sequencing techniques, the traditional research methods of microorganisms based on the isolation and cultivation are gradually replaced by metagenomics, also known as environmental genomics. The first step, which is still a major bottleneck, of metagenomic is the taxonomic characterization of the DNA fragments (reads) resulting from sequencing a sample of mixed species. This step is usually referred as "binning". Existing binning methods belong to supervised or semi-supervised approaches which rely heavily on the reference genomes of known microorganisms and phylogenetic marker genes. Due to the limited availability of reference genomes and the bias and unstable of marker genes, these methods may not be applicable in all cases. In this paper, we present an unsupervised binning method based on the distribution of a careful selected set of l-mers (substrings of length l in reads). From our experiments, we show that our approach can accurately bin DNA fragments with various length and relative species abundance ratio without any reference and training datasets. Another highlight of our approach is error robustness. The binning accuracy only decreases less than 1% while the sequencing error rate increases from 0% to 5% which is much lower than the typical sequencing error rate of entire existing commercial sequencing platform which is less than 2%. The source code of our software tool, the reference genomes of the species for generating the test datasets and the corresponding test datasets are available at http://i.cs.hku.hk/~alse/MetaCluster/.
A novel orthogonal space-time-frequency block code for OFDM systems
Authors: Keonkook Lee, Youngok Kim, Joonhyuk Kang
Venue: IEEE Communications Letters (2009)

In this letter, we propose an orthogonal space-time-frequency block code for orthogonal frequency division multiplexing (STFBC-OFDM) systems, newly designed to be robust against both time- and frequency-selective fading. The performance of the proposed system is analyzed in spatially uncorrelated time-varying multipath Rayleigh-fading channels. The analytic results, which closely match the numerical results, show that the proposed system outperforms STBC-OFDM in time-varying channels and SFBC-OFDM in frequency-selective fading channels.
Generalization of the ZZW embedding construction for steganography
Authors: Weiming Zhang, Xin Wang
Venue: IEEE Transactions on Information Forensics and Security (2009)

We generalize the Zhang, Zhang, and Wang (ZZW) construction to produce larger code families for steganography from existing codes, which can cover the range of relative payloads more densely. We also prove that the expanded code family keeps the similar asymptotic property as the code family produced by the ZZW construction, that is, the codes follow the theoretic upper bound on embedding efficiency as relative payload tends to zero.
Cross-training in a cellular manufacturing environment
Authors: Jannes Slomp, Jos A. C. Bokhorst, Eric Molleman
Venue: Computers and Industrial Engineering (2005)

This study addresses the need for cross-training in a cellular manufacturing environment. It is demonstrated that an effective cross-training situation results if workers and machines are connected, directly or indirectly, by task assignment decisions. The connections between workers and machines (i.e. the qualifications of workers) form 'chains' that can be used to reallocate work from heavily loaded workers to less loaded workers. This provides the possibility of a balanced workload situation among workers, something that is desirable from a social as well as an economic viewpoint. Based on this insight, we have developed an integer programming (IP) model that can be used to select workers to be cross-trained for particular machines. The model may help in trade-offs between training costs and the workload balance among workers in a manufacturing cell. The workload balance indicates the usefulness of labor flexibility in a particular situation. A numerical example is presented to illustrate various elements and features of the model. It also provides further insight into the role of 'chaining' workers and machines. The industrial applicability of the model and directions for future research are also indicated.
The issues of project-based learning management model for secondary students: a case study of information technology course
Authors: Kalayanee Jitgarun, Niramis Painprasert, Anuvat Tongsakul
Venue: Proceedings of the 10th IASTED International Conference on Computers and Advanced Technology in Education (2007)

The purposes of this research were to develop and to compare achievement and satisfaction of students in level 4 (Muttayom Suksa 4--6) between Project-Based Learning Management (PBLM) model and conventional learning on Information Technology course. Sampling groups consisted of students who were studying in level 4 (Muttayom Suksa 4--6) from Uttaraditdarunee School in Uttaradit Province and Mattayom-Watnhongjok School in Bangkok Metropolitan area. Then, the students from each school were divided into two groups: an experimental group and a control group. The research tools used in the study were composed of pretest and posttest, a learning management plan, progress assessment, and a questionnaire on students' learning satisfaction. Statistics utilized for data analysis were mean (X), Standard Deviation (S.D.), t-test and Analysis of Covariance (ANCOVA). The results of overall study were that when the mean scores of the students' learning achievement between the PBLM model (X = 46.80, S.D. = 3.78) and the conventional learning (X = 46.05, S.D. = 4.66) were compared by using t-test, it was found that there was a significant difference at .05 level. When ANCOVA utilized and pre-test used as a covariance, it was found that teaching models had a direct effect on students' learning achievement only at Mattayom-Watnhongjok School at 61.20 percent. Then, when the mean of students' satisfaction were compared, it was found that students' satisfaction on the PBLM model (X = 3.81, S.D. = 0.88) and the conventional learning (X = 3.69, S.D. = 0.88) was at a good level. However, the mean of students' satisfaction on the PBLM model was higher than the mean of conventional learning.