ppxscal/embedding_network huggingface dataset:
Instructional computer use by coe faculty in turkey: application of diffusion of innovations theory
Authors: Ann Thompson
Venue:  (2006)

The purpose of this quantitative research study was to explore instructional computer use by faculty members in the College of Education (COE) at an Anatolian university in Turkey. The faculty members in the study reported low levels of use and expertise in instructional computer technologies. Variables that were analyzed for their influence with regard to the faculty members' use of computers for instructional purposes included demographic characteristics, computer expertise, computer access, barriers to computer access, attitude toward computer use, support for computer use, and adopter categories based on innovativeness. Variables that were found to be significantly correlated with faculty members' level of computer use were computer ownership in the office, age, years of computer experience in general, computer expertise, computer access, barriers to computer access, attitude toward computer use, support for computer use, and adopter categories based on innovativeness. Group differences also were analyzed for the six computer-use factors based on the demographic characteristics and adopter categories. Associate professors; faculty members who owned a computer in the office or at home; those between the ages of 20 and 29; those with between 1 and 5 years and 6 and 10 years of teaching experience; those with between 16 and 20 years and over 20 years of computer experience; and those in the innovators, early adopters, and early majority categories reported higher uses of some or all of the computer use factors. Findings from this study were summarized and discussed with respect to Everett Rogers' (2003) diffusion of innovations theory. The faculty members reported positive attitudes toward instructional computer use relating to Rogers' first three attributes of innovations (relative advantage, compatibility, and simplicity of instructional computer use); the findings regarding the other two attributes (trialability and observability) were mixed. Finally, faculty members' low level of instructional computer use, the majority of the faculty members' self-placement in the last three adopter categories, and responses to the open-ended question regarding reasons for the adopter category that COE faculty members selected were consistent with Rogers' findings.
Investigating autonomic runtime management strategies for SAMR applications
Authors: Sumir Chandra, Manish Parashar, Jingmei Yang, Yeliang Zhang, Salim Hariri
Venue: International Journal of Parallel Programming (2005)

Dynamic structured adaptive mesh refinement (SAMR) techniques along with the emergence of the computational Grid offer the potential for realistic scientific and engineering simulations of complex physical phenomena. However, the inherent dynamic nature of SAMR applications coupled with the heterogeneity and dynamism of the underlying Grid environment present significant research challenges. This paper presents application/system sensitive reactive and proactive partitioning strategies that form a part of the GridARM autonomic runtime management framework. An evaluation using different SAMR kernels and system workloads is presented to demonstrate the improvement in overall application performance.
Structural evaluation of agent organizations
Authors: Davide Grossi, Frank Dignum, Virginia Dignum, Mehdi Dastani, Lambèr Royakkers
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

A multi-agent system can be analyzed and specified as an organization consisting of roles and their relations. The performance of an organization depends on many factors among which the topology of its organizational structure, i.e., the set of relations holding between its roles. This short paper provides the sketch of quantitative methods for addressing the issue of the analysis, evaluation, and comparison of organizational structures. To this aim, quantitative concepts from graph theory are applied which deliver numerical analyzes of organizational structures. Here, an illustrative number of these concepts is sketched and their connection to properties that are commonly indicated as critical for organizations (robustness, flexibility and efficiency) is shown.
SAGE storytellers: learning about identity, language and technology
Authors: Marina Umaschi
Venue: Proceedings of the 1996 international conference on Learning sciences (1996)

Storytelling is an ancient art that allows us to share experiences, thoughts and values. In the oral tradition, stories were told in a conversational way by the elders in order to give indirect advice and communicate morals. Each culture or community has its repertoire of inspirational stories or "literature of the spirit" (Campbell, 1988) that serves similar pedagogical functions as myths. They indirectly transmit how to live a human life and are not intended to perfectly match the addressed situation: time, characters, historical period and plot vary from the listener's situation. The power of this kind of storytelling lies in enabling the listeners to learn more about themselves by constructing personal meaning and interpretation. It is believed that in the very act of finding relevance the listener will find answers.
On some characteristics of computers of new generation
Authors: O. N. Granichin, S. S. Sysoev
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 3 (2003)

The paper deals with the problem of creating of computers of the new generation. Some abstract approach of constructing the hardware is considered and the basic scheme of functioning is proposed. The new generation is supposed to be the generation of computers with artificial intelligence features. In this paper term "intelligence" is understood as ability of system to adapt to the real world conditions by the effective choosing of the task to solve in current moment.
A preliminary performance comparison of five machine learning algorithms for practical IP traffic flow classification
Authors: Nigel Williams, Sebastian Zander, Grenville Armitage
Venue: ACM SIGCOMM Computer Communication Review (2006)

The identification of network applications through observation of associated packet traffic flows is vital to the areas of network management and surveillance. Currently popular methods such as port number and payload-based identification exhibit a number of shortfalls. An alternative is to use machine learning (ML) techniques and identify network applications based on per-flow statistics, derived from payload-independent features such as packet length and inter-arrival time distributions. The performance impact of feature set reduction, using Consistency-based and Correlation-based feature selection, is demonstrated on Naïve Bayes, C4.5, Bayesian Network and Naïve Bayes Tree algorithms. We then show that it is useful to differentiate algorithms based on computational performance rather than classification accuracy alone, as although classification accuracy between the algorithms is similar, computational performance can differ significantly.
Accountability protocols: Formalized and verified
Authors: Giampaolo Bella, Lawrence C. Paulson
Venue: ACM Transactions on Information and System Security (TISSEC) (2006)

Classical security protocols aim to achieve authentication and confidentiality under the assumption that the peers behave honestly. Some recent protocols are required to achieve their goals even if the peer misbehaves. Accountability is a protocol design strategy that may help. It delivers to peers sufficient evidence of each other's participation in the protocol. Accountability underlies the nonrepudiation protocol of Zhou and Gollmann and the certified email protocol of Abadi et al. This paper provides a comparative, formal analysis of the two protocols, and confirms that they reach their goals under realistic conditions. The treatment, which is conducted with mechanized support from the proof assistant Isabelle, requires various extensions to the existing analysis method. A byproduct is an account of the concept of higher-level protocol.
A Genetic Neuro-Model Reference Adaptive Controller for Petroleum Wells Drilling Operations
Authors: Tiago C. Fonseca, Jose Ricardo P. Mendes, Adriane B. S. Serapiao, Ivan R. Guilherme
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

Motivated by rising drilling operation costs, the oil industry has shown a trend towards real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated to parameters modeling. One of the drill-bit performance evaluators, the Rate of Penetration (ROP), has been used in the literature as a drilling control parameter. However, the relationships between the operational variables affecting the ROP are complex and not easily modeled. This work presents a neuro-genetic adaptive controller to treat this problem. It is based on the Auto-Regressive with Extra Input Signals model, or ARX model, to accomplish the system identification and on a Genetic Algorithm (GA) to provide a robust control for the ROP.Results of simulations run over a real offshore oil field data, consisted of seven wells drilled with equal diameter bits, are provided.
Supporting design studio learning: an investigation into design communication in computer-supported collaboration
Authors: Thomas Kvan, Wan Hung Yip, Alonso Vera
Venue: Proceedings of the 1999 conference on Computer support for collaborative learning (1999)

Earlier studies suggest that benefits may be found in chat line communication rather than high bandwidth video-conferencing conditions when considering collaborative design learning. This paper draws together studies that look at this conjecture and concludes that chat line collaboration reduces fixation in problem space exploration. This encourages the participants to explore design opportunities in a different way than graphical or video based communication.
Video Classification Using Normalized Information Distance
Authors: K. Kaabneh, A. Abdullah, Z. Al-Halalemah
Venue: Proceedings of the conference on Geometric Modeling and Imaging: New Trends (2006)

There has been a vast collection of multimedia resources on the net. This has opened an opening for researchers to explore and advance the science in the field of research in storing, handling, and retrieving digital videos. Video classification and segmentation are fundamental steps for efficient accessing; retrieving, browsing and compressing large amount of video data. The basic operation video analysis is to design a system that can accurately and automatically segments video material into shots and scenes. This paper presents a detailed video segmentation technique based on pervious researches which lacks performance and since some of the videos is stored in a compressed form using the Normalized Information Distance (NID) which approximates the value of a theoretical distance between objects using the Kolmogrov Complexity Theory. This technique produced a better result in reference to performance, high recall of 95.5% and a precision of 89.7%.
Image Retrieval Using Multimodal Keywords
Authors: Rajeev Agrawal, William Grosky, Farshad Fotouhi
Venue: Proceedings of the Eighth IEEE International Symposium on Multimedia (2006)

In this paper, we propose a technique to retrieve the images using the 'search by similarity' method with the help of multimodal keywords. Multimodal keywords consist of low-level MPEG-7 color descriptors and textual keywords. The visual keywords and textual keywords are combined together and the image collection is represented as a matrix, which is similar in representation to a term-document matrix. Using LSI (latent semantic indexing), we demonstrate that the visual keywords, when combined with textual keywords can improve the retrieval results to a great degree.
Methodology for UML Modeling and Formal Verification of Real-Time Systems
Authors: Nawal Addouche, Christian Antoine, Jacky Montmain
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

In the paper, we present a methodology developed in order to verify probabilistic timed properties related to dependability of real-time systems. The methodology is made of three essential steps. The first one is a UML profile called DAMRTS (Dependability Analysis Models for Real-Time Systems) designed using GME tool. The aim is to model a real-time system with qualitative and quantitative information related to its quality of service. In this profile, UML statecharts are used to represent the system behavior. An extension is introduced with probabilities, real-time requirements and nondeterministic choices. The second one proposes a translation from extended UML statecharts to probabilistic timed automata. In this step, synchronization by events is used in probabilistic timed automata to describe the concurrency in UML statecharts. The last one is about the probabilistic model checking. This requires specification of dependability properties with a suitable temporal logic.
A Novel Algorithm for Scrambling Digital Image Based on Cat Chaotic Mapping
Authors: Liehuang Zhu, Wenzhuo Li, Lejian Liao, Hong Li
Venue: Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia (2006)

This paper proposes a new algorithm for scrambling digital image based on the cat chaotic mapping. We disorder the pixel coordinates of the digital image through using a cat chaotic mapping, and then perform exclusive OR operation between certain pixel value of the digital image and a chaotic value. The experiment results have shown that the new diffusion technique proposed in this paper is very effective to uniform the statistical characteristics of the encrypted graph, and the efficiency of this method is very high.
An Evaluation of Query Languages for Context-Aware Computing
Authors: Pari Delir Haghighi, Arkady Zaslavsky, Shonali Krishnaswamy
Venue: Proceedings of the 17th International Conference on Database and Expert Systems Applications (2006)

Context-awareness highly depends on easy and prompt access to the right information and this needs overcoming challenges of query expression and processing of context information. One of the main considerations in querying context is selecting and applying an appropriate and expressive query language for defining user's context needs. This paper presents an overview of current languages used for querying context and investigates their strengths and limitations in expressing different aspects of context.
Conserving total synaptic weight ensures one-trial sequence learning of place fields in the hippocampus
Authors: Zhihua Wu, Yoko Yamaguchi
Venue: Neural Networks (2006)

The hippocampus plays a critical role in the rapid acquisition of information from a novel experience. Recent theoretical studies on the rat hippocampus have shown the possibility of behavioral sequence learning in a single traversal experience by theta phase coding. Specifically, previous work using computer simulations demonstrated that the extent of overlap among individual events of sequence and rat running velocity should be quantitatively incorporated into the learning rule to ensure one-trial sequence learning. These extents of overlap- and running velocity-dependent properties in the learning rule are called the input-dependent regulation of the learning rule. However, the biological meaning of such learning properties remains poorly understood. In this study, we quantitatively derive these learning properties with mathematical analyses. We further find that the input-dependent regulation of the learning rule allows maintenance of total synaptic weight over a given neuron during one-trial learning. Our results predict that a homeostatic plasticity mechanism should exist for conserving total synaptic weight on a rapid timescale.
In the News
Authors: Danna Voth, Jan Krikke
Venue: IEEE Intelligent Systems (2006)

The first news story, "AI and Privacy on the Web," looks at how computer scientists are dealing withissues of protecting personal information on the Web. The second news story, "Phonetic-Sequence AlgorithmCould Reduce Drug Name Confusion," reports on ALINE, an algorithm for aligning phonetic sequences. ALINE ispart of a US Food and Drug Administration program to decrease deaths and injuries due to confusion betweendrug names.
Kernel-based Recognition of Human Actions Using Spatiotemporal Salient Points
Authors: A. Oikonomopoulos, I. Patras, M. Pantic
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

This paper addresses the problem of human action recognition by introducing a sparse representation of image sequences as a collection of spatiotemporal events that are localized at points that are salient both in space and time. We detect the spatiotemporal salient points by measuring the variations in the information content of pixel neighborhoods not only in space but also in time. We derive a suitable distance measure between the representations, which is based on the Chamfer distance, and we optimize this measure with respect to a number of temporal and scaling parameters. In this way we achieve invariance against scaling, while at the same time, we eliminate the temporal differences between the representations. We use Relevance Vector Machines (RVM) in order to address the classification problem. We propose new kernels for use by the RVM, which are specifically tailored to the proposed spatiotemporal salient point representation. The basis of these kernels is the optimized Chamfer distance of the previous step. We present results on real image sequences from a small database depicting people performing 19 aerobic exercises.
Improving Traffic Locality in BitTorrent via Biased Neighbor Selection
Authors: Ruchir Bindal, Pei Cao, William Chan, Jan Medved, George Suwala, Tony Bates, Amy Zhang
Venue: Proceedings of the 26th IEEE International Conference on Distributed Computing Systems (2006)

Peer-to-peer (P2P) applications such as BitTorrent ignore traffic costs at ISPs and generate a large amount of cross-ISP traffic. As a result, ISPs often throttle BitTorrent traffic to control the cost. In this paper, we examine a new approach to enhance BitTorrent traffic locality, biased neighbor selection, in which a peer chooses the majority, but not all, of its neighbors from peers within the same ISP. Using simulations, we show that biased neighbor selection maintains the nearly optimal performance of Bit- Torrent in a variety of environments, and fundamentally reduces the cross-ISP traffic by eliminating the traffic's linear growth with the number of peers. Key to its performance is the rarest first piece replication algorithm used by Bit- Torrent clients. Compared with existing locality-enhancing approaches such as bandwidth limiting, gateway peers, and caching, biased neighbor selection requires no dedicated servers and scales to a large number of BitTorrent networks.
Mechanisms Underlying Spatial Representation Revealed through Studies of Hemispatial Neglect
Authors: Marlene Behrmann, Thea Ghiselli-crippa, John A. Sweeney, Ilaria Di Matteo, Robert Kass
Venue: Journal of Cognitive Neuroscience (2002)

The representations that mediate the coding of spatial position were examined by comparing the behavior of patients with left hemispatial neglect with that of nonneurological control subjects. To determine the spatial coordinate system(s) used to define "left" and "right," eye movements were measured for targets that appeared at 5&deg;, 10&deg;, and 15&deg; to the relative left or right defined with respect to the midline of the eyes, head, or midsaggital plane of the trunk. In the baseline condition, in which the various egocentric midlines were all aligned with the environmental midline, patients were disproportionately slower at initiating saccades to left than right targets, relative to the controls. When either the trunk or the head was rotated and the midline aligned with the most peripheral position while the eyes remained aligned with the midline of the environment, the results did not differ from the baseline condition. However, when the eyes were rotated and the midline aligned with the peripheral position, saccadic reaction time (SRT) differed significantly from the baseline, especially when the eyes were rotated to the right. These findings suggest that target position is coded relative to the current position of gaze (oculocentrically) and that this eye-centered coding is modulated by orbital position (eye-in-head signal). The findings dovetail well with results from existing neurophysiological studies and shed further light on the spatial representations mediated by the human parietal cortex.
Inferring Socio-Affective Factors and Cooperation Capacity in Computer Assisted Collaborative Teaching/Learning Environments
Authors: Cicero Costa Quarto, Sofiane Labidi, Patricia Augustin Jaques
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

Nowadays, socio-affective factors such as cooperation, motivation, socio-cognitive affinities, pro-activity, interaction and others, tend to be widely exploited in teacher/student and in between pupils relationship, so that the results of the building of knowledge be reached in a collaborative fashion. This is because these factors would play an encouraging role towards collaboration, acting positively in building human relationships within a socio-cultural panorama. Therefore, this work will show the importance of considering socio-affective factors in collaborative learning environments focusing on the relevant socio-affective factor that we designate as Collaboration Capacity, describing its manual and computed aided inference mechanisms. The rest of the relevant socio-affective factors quoted in this work, will be described and inferred along the course of the dissertation concluding research.
A new approach in the analysis and modeling of disk access patterns
Authors: M. E. Gomez
Venue: Proceedings of the 2000 IEEE International Symposium on Performance Analysis of Systems and Software (2000)

While in previous work we have demonstrated that disk arrival patterns are consistent with self-similarity and have provided a physical explanation for the self-similar phenomenon in disk arrival patterns, the authors now deal with the analysis and modeling of disk access patterns. We provide visual and mathematical evidence showing that the same bursty behavior observed in the time series can also be observed in the spatial series formed by the starting address of the accessed blocks. Moreover, we demonstrate that the clustering of accesses in areas of the disk has self-similar characteristics. Next, we demonstrate that the observed behavior can be explained using the same self-similar property used in the analysis of arrival patterns and applying the same physical explanation.