ppxscal/embedding_network huggingface dataset:
Designing collaborative, constructionist and contextual applications for handheld devices
Authors: Bryan Patten, Inmaculada Arnedillo Sánchez, Brendan Tangney
Venue: Computers Education (2006)

This paper explores current applications for handheld devices and questions which of these make full use of the unique attributes of handheld devices in order to facilitate learning in a pedagogically sensible manner. In order to do so, the paper presents a functional framework which analyses handheld application in relation to their use as well as the pedagogical underpinning, if any, that informs their development. Our framework currently consists of seven distinct categories of application, which we term: administrative, referential, interactive, microworld, data collection, location aware and collaborative. We argue that three categories, namely data collection, location aware and collaborative, are particularly suited to learning with handheld devices when they are informed by collaborative, contextual and constructionist learning theories. Furthermore, we contend that applications of the type just outlined deserve further research since they are not attempting to replicate, or even augment, existing learning scenarios but rather they try to create new learning opportunities which would not be possible without (mobile) technology. Finally, the authors introduce a number of applications and learning scenarios that they have developed for handheld devices and explain their position within the framework.
Determining the presence of bias error using statistical methods
Authors: David M. Kwartowitz, Robert L. Galloway, Richard G. Shiavi
Venue: IEEE Transactions on Information Technology in Biomedicine (2009)

Current techniques in image-guided surgery rely on the use of localizers for the measurement of position in physical space. These measurements are prone to error due to intrinsic properties of the localizer used. The error and thus accuracy of a localizer can be determined using various techniques, many of which assume that the error is isotropic and free of bias. A bias error adds an orientation dependence to the error of measured points. Determination of the presence of a bias error is an important component in the characterization of a localizer's performance. Statistical analysis of localized points on a rigid phantom can be used to detect the presence of a bias error. In this paper, we will examine the use of statistical techniques in the characterization of a series of localizers and how that information is useful in determining localizer efficacy.
Sensitivity of multi-criteria decision making to linguistic quantifiers and aggregation means
Authors: David Ben-Arieh
Venue: Computers and Industrial Engineering (2005)

Developments in Multi-Criteria (MCDM) and Multi-Expert decision-making allow for using linguistic quantifiers such as 'all', 'most', 'at least half' and similar terms as quantifiers for the decision. Additionally, new methods of aggregating the various opinions have been developed, giving the decision maker an increasingly large variety of options. This paper presents the concept of linguistic quantifiers and presents a collection of quantifiers with their associated weight functions. This paper explores the effect that the type of linguistic quantifier and the aggregation method used have on the ranking of alternatives. This study utilizes eleven linguistic quantifiers and four aggregation means using four well-documented MCDM problems. The results show that the effect of the linguistic quantifiers varies and some quantifiers have more impact on ranking of the alternatives then others. Additionally, the sensitivity of the decision made to the aggregation method is found to be relatively small. The study finds that the weighted harmonic mean is the most sensitive aggregation function to the changes of linguistic quantifiers. The results of this research allow the decision maker to choose the linguistic quantifier and aggregation method based on subjective belief without impeding the resulting decision.
Design, analysis, and experimentation of chaotic permanent magnet dc motor drives for electric compaction
Authors: Zheng Wang, K. T. Chau
Venue: IEEE Transactions on Circuits and Systems II: Express Briefs (2009)

In this brief, a new electrically chaotic permanent magnet dc motor drive is designed, analyzed, and implemented for electric compaction. The key is to newly apply chaotic speed reference control to the torque controller of the motor drive, which, in turn, generates chaotic motion for the compactor. The proposed electric chaoization not only offers the advantages of lighter weight, smaller size, and higher controllability, compared with its mechanical counterpart, but also provides higher flexibility and better accuracy, compared with previous electric chaoizing approaches. By numerically comparing the compaction performance, i.e., the average compaction energy density, the proposed chaotic compactor is more effective than the conventional compactors using constant input voltage control and sinusoidal speed reference control. After prototyping, experimentation is performed to verify the validity of the proposed compactor.
Augmented and virtual reality based training in the field of logistics
Authors: Dennis Walch
Venue: Proceedings of the 10th IASTED International Conference on Computers and Advanced Technology in Education (2007)

Only well-trained workers have the ability to deal with the requirements of flexible production and logistics systems and to ensure their operations' high efficiency. In future, new ways of practical in-house training are needed for transferring the required knowledge to the learner without negatively impacting the productivity of running processes. Hence within the research cooperation ForLog the focus lies on the development of new virtual training environments for operational workers in the field of production and logistics. The main goals are the reduction of training periods on the one hand as well as the preparation of workers for ramp-up situations of new products or facilities on the other. A new step in educating logistics workers will be achieved by evaluating the developed training environments, such as augmented reality- and virtual reality-based order picking.
MicroRNAs and cancer-the search begins!
Authors: Anastasis Oulas, Martin Reczko, Panayiota Poirazi
Venue: IEEE Transactions on Information Technology in Biomedicine (2009)

For almost three decades, cancer was thought to result from changes in the structure and/or expression of protein coding genes. The discovery of thousands of genes that produce noncoding RNA (ncRNA) transcripts in the past few years suggested that the molecular biology of cancer is much more complex. MicroRNAs (miRNAs), an important group of ncRNAs, have recently been associated with tumorigenesis by acting either as tumor suppressors or oncogenes. Experimental prediction of miRNA genes is a slow process, because of the difficulties of cloning ncRNAs. Complementary to experimental approaches, a number of computational tools trained to recognize features of the biogenesis of miRNAs have significantly aided in the prediction of new miRNA candidates. By narrowing down the search space, computational approaches provide valuable clues as to which are the dominant features that characterize these regulatory units and which genes are their most likely targets. Moreover, through the use of high-throughput expression profiling methods, many molecular signatures of miRNA deregulation in human tumors have emerged. In this review, we present an overview of existing computational methods for identifying miRNA genes and assessing their expression levels, and analyze the contribution of such tools toward illuminating the role of miRNAs in cancer.
Analysis of Aggregation Characteristics of Streaming Media Traffic
Authors: Xin Zhao, Xiaohui Zhang, Bin Wang
Venue: Proceedings of the 2009 International Conference on Multimedia Information Networking and Security - Volume 02 (2009)

The analysis of aggregation characteristics of streaming media traffic provides a scientific basis for the general plan of Next Generation Broadcasting network. Based on the method of simulation, the streaming media traffic characteristics, self-similarity and aggregation delay time are discussed with different load scales and source processing strategies. The result shows that delay time of the aggregation processing is improved, because of the source classification strategy. And with the increasing of the aggregation scale self-similarity of the traffic has been weakened.
Discrete-dopant-induced timing fluctuation and suppression in nanoscale CMOS circuit
Authors: Yiming Li, Chih-Hong Hwang, Tien-Yeh Li
Venue: IEEE Transactions on Circuits and Systems II: Express Briefs (2009)

As the dimensions of semiconductor devices continue to be reduced, device fluctuations have become critical to determining the accuracy of timing in circuits and systems. This brief studies the discrete-dopant-induced timing characteristic fluctuations in 16-nm-gate complementary metal-oxide-semiconductor (CMOS) circuits using a 3-D "atomistic" coupled device-circuit simulation. The accuracy of the simulation has been confirmed by using the experimentally calibrated transistor physical model. For a 16-nm-gate CMOS inverter, 3.5%, 2.4%, 18.3%, and 13.2% normalized. fluctuations in the rise time, fall time, high-to-low delay time" and low-to-high delay time, respectively, are found. Random dopants may cause significant timing fluctuations in the studied circuits. Suppression approaches that are based on the circuit and device design viewpoints are implemented to examine the associated characteristic fluctuations. The use of shunted transistors in the circuit provides similar suppression to the use of a device with doubled width. However, both approaches increase the chip area. To eliminate the need to increase the chip area, channel engineering approaches (vertical and lateral) are proposed, and their effectiveness in reducing the timing fluctuation is demonstrated.
A Novel Computer Virus Detection Method from Ideas of Immunology
Authors: Jie Zeng, Tao Li
Venue: Proceedings of the 2009 International Conference on Multimedia Information Networking and Security - Volume 01 (2009)

In this paper, inspired by the change of antibody concentration in biological immune system, we present a Novel Computer Virus Detection Method from Ideas of Immunology (NCVDMII). In NCVDMII, the concepts and formal definitions of antibody, antigen, nonself and detector are given. Then, NCVDMII get the specific antibody from the simulation of primary immune response and calculate the antibody number by using the secondary immune response. Finally, building upon the above processes, a probabilistic calculation method for computer virus alarm production, which is based on the correlation between the antibody concentration and the computer virus infection intensity, is proposed. Compared with Negative Selection Algorithm (NSA), Automatic Computer Immune System (ACIS) and Immunity-based System (IBS), the false alarm rate of NCVDMII is reduced by 17.5%, 5.0% and 2.8%, respectively.
Incremental privacy preservation for associative classification
Authors: Bowonsak Seisungsittisunti, Juggapong Natwichai
Venue: Proceeding of the ACM first international workshop on Privacy and anonymity for very large databases (2009)

Privacy preserving has become an essential process for any data mining task. Therefore, data transformation to ensure privacy preservation is needed. In this paper, we address a problem of privacy preserving on an incremental-data scenario in which the data need to be transformed are not static, but appended all the time. Our work is based on a well-known data privacy model, i.e. k-Anonymity. Meanwhile the data mining task to be applied to the given dataset is associative classification. As the problem of privacy preserving for data mining has proven as an NP-hard, we propose to study the characteristics of a proven heuristic algorithm in the incremental scenarios theoretically. Subsequently, we propose a few observations which lead to the techniques to reduce the computational complexity for the problem setting in which the outputs remains the same. In addition, we propose a simple algorithm, which is at most as efficient as the polynomial-time heuristic algorithm in the worst case, for the problem.
Computer-aided detection and diagnosis of breast cancer with mammography: recent advances
Authors: Jinshan Tang, Rangaraj M. Rangayyan, Jun Xu, Issam El Naqa, Yongyi Yang
Venue: IEEE Transactions on Information Technology in Biomedicine (2009)

Breast cancer is the second-most common and leading cause of cancer death among women. It has become a major health issue in the world over the past 50 years, and its incidence has increased in recent years. Early detection is an effective way to diagnose and manage breast cancer. Computer-aided detection or diagnosis (CAD) systems can play a key role in the early detection of breast cancer and can reduce the death rate among women with breast cancer. The purpose of this paper is to provide an overview of recent advances in the development of CAD systems and related techniques.We begin with a brief introduction to some basic concepts related to breast cancer detection and diagnosis.We then focus on key CAD techniques developed recently for breast cancer, including detection of calcifications, detection of masses, detection of architectural distortion, detection of bilateral asymmetry, image enhancement, and image retrieval.
First Arrival Seismic Tomography (FAST) vs. PStomo_eq applied to crooked line seismic data from the Siljan ring area
Authors: Johiris I. Rodríguez-Tablante, Christopher Juhlin, Björn Bergman
Venue: Computers Geosciences (2006)

When seismic profiles deviate significantly from straight lines, the results from 2D traveltime inversion programs will be in error due to the inherent 3D component present in the data. Thus, it is necessary to use a program that can handle the 3D aspects of the acquisition geometry. This study compares the performance and results from two computer programs for 3D seismic tomography. These algorithms are the package for First Arrival Seismic Tomography (FAST) and a Local Earthquake tomography program, PStomo_eq. Although both codes invert for the velocity field using the conjugate gradient solver LSQR, the common smoothness constraint is handled differently. In addition, the programs do not incorporate the same options for user-specified constraints. These differences in implementation are clearly observed in the inverted velocity fields obtained in this study. Both FAST and PStomo_eq are applied to synthetic and real data sets with crooked line geometry. First arrival traveltimes from seismic data acquired in the Siljan ring impact area are used for the real data set test. The results show that FAST gives smoother models than PStomo_eq. On the real data set PStomo_eq showed a better correlation to the information at hand. Different criteria exist for what is desirable in a model; thus, the choice of which program to use will mostly depend on the particular goals of the study.
Pseudo-fuzzy discrete-event simulation for on-line production control
Authors: Michele Dassisti, Luigi M. Galantucci
Venue: Computers and Industrial Engineering (2005)

In this paper we propose an alternative use of commercial object-oriented discrete-event simulators. We attempt to bridge the intrinsic inaccuracy of simulators in modelling real systems affected by fuzziness. The strategy adopted, called pseudo-fuzzy discrete event simulation, models fuzziness through a set of several classic simulation runs to trace an output fuzzy performance function. The idea behind the approach proposed is to use the simulator as a fuzzy operator, which embeds some stochastic functions. A benchmark industrial setting has been used to build a reference simulation model and perform evaluations of the simulation strategy proposed for a specific working case.
Hadoop high availability through metadata replication
Authors: Feng Wang, Jie Qiu, Jie Yang, Bo Dong, Xinhui Li, Ying Li
Venue: Proceeding of the first international workshop on Cloud data management (2009)

Hadoop is widely adopted to support data intensive distributed applications. Many of them are mission critical and require inherent high availability of Hadoop. Unfortunately, Hadoop has no high availability support yet, and it is not trivial to enhance Hadoop. Based on thorough investigation of Hadoop, this paper proposes a metadata replication based solution to enable Hadoop high availability by removing single point of failure in Hadoop. The solution involves three major phases: in initialization phase, each standby/slave node is registered to active/primary node and its initial metadata (such as version file and file system image) are caught up with those of active/primary node; in replication phase, the runtime metadata (such as outstanding operations and lease states) for failover in future are replicated; in failover phase, standby/new elected primary node takes over all communications. The solution presents several unique features for Hadoop, such as runtime configurable synchronization mode. The experiments demonstrate the feasibility and efficiency of our solution.
A local nonlinear model for the approximation and identification of a class of systems
Authors: Heinz Koeppl
Venue: IEEE Transactions on Circuits and Systems II: Express Briefs (2009)

The special form of the Laplace-domain Volterra kernels for linear-analytic systems is exploited to obtain an approximate model that obeys an appealingly simple feedforward block structure. It comprises a composition of the linearization and the multivariate nonlinear function of the original system. The model does not involve a truncation in the power series expansion nor in the memory depths and offers an economic parameterization. It is shown to be linearly identifiable in one step if a priori information about the linearized dynamics is provided. We present simulation results for a simple nonlinear circuit showing the validity of the model.
A Security Framework for JXTA-Overlay
Authors: Joan Arnedo-Moreno, Keita Matsuo, Leonard Barolli, Fatos Xhafa
Venue: Proceedings of the 2009 International Conference on Network-Based Information Systems (2009)

At present time, the maturity of P2P research field has pushed through new problems such us those related with security. For that reason, security starts to become one of the key issues when evaluating a P2P system and it is important to provide security mechanisms to P2P systems. The JXTA-Overlay project is an effort to use JXTA technology to provide a generic set of functionalities that can be used by developers to deploy P2P applications. However, since its design focused on issues such as scalability or overall performance, it did not take security into account. This work proposes a security framework specifically suited to JXTA-Overlay's idiosyncrasies.
Collaborative environments for the learning of design: a model and a case study in Domotics
Authors: Crescencio Bravo, Miguel. Á. Redondo, Manuel Ortega, M. Felisa Verdejo
Venue: Computers Education (2006)

Design plays a central role in a range of subjects at different educational levels. Students have to acquire the knowledge necessary for the execution of tasks that enable them to construct an artefact or model that can be tested by simulation and that satisfies some requirements and verifies some constraints. They achieve this by means of a design process. In some design domains there is a lack of teaching tools from a learner-centred perspective. Moreover, when these domains are complex, the design problems that the students have to solve during their learning process require the design activity to be carried out in group. In response to this situation, we have developed a design model and a collaborative learning method. Using this conceptual framework, we have built a collaborative environment for the learning of domotical design by means of complex problem solving, with an emphasis on synchronous collaboration for work distribution, discussion, design in shared surfaces and simulation. This environment has already been evaluated and used in real teaching experiences.
Trellis precoding for MIMO broadcast signaling
Authors: Aaron Callard, Amir Khandani, Aladdin Saleh
Venue: IEEE Transactions on Communications (2009)

Channel Inversion, and its Minimum Mean Square Error (MMSE) variation, are low complexity methods for Space Division Multiple Access (SDMA) in Multiple Input Multiple Output Broadcast Channel (MIMO-BC). As the channel matrix deviates from orthogonal, these methods result in a waste of transmit power. This paper proposes a trellis precoding method (across time and space) to improve the power efficiency. Adopting a 4-state trellis shaping method from [1], the complexity of the proposed method, which is entirely at the transmitter side, is equivalent to the search in a trellis with 4N states where N is the number of transmit antennas. Numerical results are presented showing that the achievable gains, which depend on the channel realization, can be significantly higher than the traditional shaping gain which is limited to 1.53dB.
A cost/benefit model for investments in inventory and preventive maintenance in an imperfect production system
Authors: Hsu-Hua Lee
Venue: Computers and Industrial Engineering (2005)

In this research, a cost/benefit model is developed for supporting investment strategies about inventory and preventive maintenance in an imperfect production system. The effect of such investments on the return is expressed as a function of measurable variables. Using this model, the decision maker can decide whether investments in inventory and preventive maintenance are necessary and how much to invest. This investment model is developed for an imperfect production system with imperfect product quality and supplied quantity. Investments in inventory and preventive maintenance increase service level for the customer and reduce the proportion of defective products, and hence affect stockout and backlog of supplied products and the delivery time to the customer. This model includes in its scope investment in inventory and preventive maintenance, manufacturing cost, inventory cost, backlog cost, stockout cost, and delay cost. This model can be used to evaluate the effects of investments on the financial cost/benefit and other relevant critical performance measures. This model can be solved by an iterative process using the Sequential Quadratic Programming Method. The optimal investment in inventory with respect to the service level and the optimal investment in preventive maintenance with respect to the proportion of defective items can be obtained first, and then other relevant costs can also be obtained.
Limited Contention Scheme (LCS) to Reduce Collision in LR-WPAN
Authors: Su-Hwan Ko, Jung-Kyu lee
Venue: Proceedings of the 2009 Fifth International Joint Conference on INC, IMS and IDC (2009)

Data collision in LR-WPAN(Low Rate Wireless Personal Area Network) causes retransmission of which energy consumption may reduce life of the entire network. Furthermore LR-WPAN is very sensitive to collision as it has relatively fewer frequencies of back-off retries. LCS(Limited Contention Scheme) suggested in this study is a way to transmit data by certain groups of the total nodes so that it can reduce possibilities of data collision and retransmission by decreasing the number of competing nodes. As a result LCS can increase a throughput and the life of the entire network. As using LCS in designing LR-WPAN in the future can extend battery life, LCS can be useful in any application that requires low energy consumption.