ppxscal/embedding_network huggingface dataset:
Influence of gender, program of study and PC experience on unethical computer using behaviors of Turkish undergraduate students
Authors: Yavuz Akbulut, Ömer Uysal, Hatice Ferhan Odabasi, Abdullah Kuzu
Venue: Computers Education (2008)

This study administered the unethical computer using behavior scale (UECUBS) developed by [Namlu, A.G., & Odabasi, F. (2007). Unethical computer using behavior scale: A study of reliability and validity on Turkish university students. Computers and Education, 48, 205-215.] to investigate whether gender, program of study and PC experience have an impact on ethical judgments of undergraduate students regarding information and communication technologies (ICTs). The sample consisted of 559 undergraduates from the Education Faculty of the most populated state university in Turkey. The results of 5 (program of study)x2 (gender)x2 (PC experience) between-groups analysis of variance (ANOVA) indicated no significant differences among different programs of study and between high and low experienced PC users. The analysis showed significant differences between males and females. A significant interaction between the program of study and gender was found, which indicated that the difference between males and females did not follow a similar pattern across different programs of study. More specifically, females' ethical judgments were consistent across different fields while males' judgments varied according to the field of study.
High-fidelity geometric modeling for biomedical applications
Authors: Zeyun Yu, Michael J. Holst, J. Andrew McCammon
Venue: Finite Elements in Analysis and Design (2008)

We describe a combination of algorithms for high-fidelity geometric modeling and mesh generation. Although our methods and implementations are application-neutral, our primary target application is multiscale biomedical models that range in scales across the molecular, cellular, and organ levels. Our software toolchain implementing these algorithms is general in the sense that it can take as input a molecule in PDB/PQR forms, a 3D scalar volume, or a user-defined triangular surface mesh that may have very low quality. The main goal of our work presented is to generate high quality and smooth surface triangulations from the aforementioned inputs, and to reduce the mesh sizes by mesh coarsening. Tetrahedral meshes are also generated for finite element analysis in biomedical applications. Experiments on a number of bio-structures are demonstrated, showing that our approach possesses several desirable properties: feature-preservation, local adaptivity, high quality, and smoothness (for surface meshes). The availability of this software toolchain will give researchers in computational biomedicine and other modeling areas access to higher-fidelity geometric models.
An Efficient Method for Fast Delay and SI Calculation Using Current Source Models
Authors: Xin Wang, Ali Kasnavi, Harold Levy
Venue: Proceedings of the 9th international symposium on Quality Electronic Design (2008)

Current source models are the methods of choice for gate-level delay and SI calculation in Deep Sub Micron regime. To fully utilize the information provided by the current source models, numerical integration is often applied to solve stage-based transient simulation that calculates delay, slew, or noise bumps. However, this is computationally expensive. In this paper, we present a fast and robust algorithm for delay and signal integrity (SI) calculation using current source models. By applying diagonalization and Sherman-Morrison formula together with a one-step Newton-Raphson method, the transient simulation cost of a stage with a single driver can be reduced from O(kmn3) to O(kn) with a small runtime overhead, where k is the number of time step, m is the average number of Newton-Raphson steps, and n is the size of matrices of the Reduced Order Model(ROM) of the parasitic network. The proposed method works perfectly with the popular implicit integration methods such as the Trapezoidal and Backward Euler method.
Zero-Knowledge in the Applied Pi-calculus and Automated Verification of the Direct Anonymous Attestation Protocol
Authors: Michael Backes, Matteo Maffei, Dominique Unruh
Venue: Proceedings of the 2008 IEEE Symposium on Security and Privacy (2008)

We devise an abstraction of zero-knowledge protocols that is accessible to a fully mechanized analysis. The abstraction is formalized within the applied pi-calculus using a novel equational theory that abstractly characterizes the cryptographic semantics of zero-knowledge proofs. We present an encoding from the equational theory into a convergent rewriting system that is suitable for the automated protocol verifier ProVerif. The encoding is sound and fully automated. We successfully used ProVerif to obtain the first mechanized analysis of (a simplified variant of) the Direct Anonymous Attestation (DAA) protocol. This required us to devise novel abstractions of sophisticated cryptographic security definitions based on interactive games. The analysis reported a novel attack on DAA that was overlooked in its existing cryptographic security proof. We propose a revised variant of DAA that we successfully prove secure using ProVerif.
GA, MR, FFNN, PNN and GMM based models for automatic text summarization
Authors: Mohamed Abdel Fattah, Fuji Ren
Venue: Computer Speech and Language (2009)

This work proposes an approach to address the problem of improving content selection in automatic text summarization by using some statistical tools. This approach is a trainable summarizer, which takes into account several features, including sentence position, positive keyword, negative keyword, sentence centrality, sentence resemblance to the title, sentence inclusion of name entity, sentence inclusion of numerical data, sentence relative length, Bushy path of the sentence and aggregated similarity for each sentence to generate summaries. First, we investigate the effect of each sentence feature on the summarization task. Then we use all features in combination to train genetic algorithm (GA) and mathematical regression (MR) models to obtain a suitable combination of feature weights. Moreover, we use all feature parameters to train feed forward neural network (FFNN), probabilistic neural network (PNN) and Gaussian mixture model (GMM) in order to construct a text summarizer for each model. Furthermore, we use trained models by one language to test summarization performance in the other language. The proposed approach performance is measured at several compression rates on a data corpus composed of 100 Arabic political articles and 100 English religious articles. The results of the proposed approach are promising, especially the GMM approach.
We're all stars now: reality television, web 2.0, and mediated identities
Authors: Michael A. Stefanone, Derek Lackaff, Devan Rosen
Venue: Proceedings of the nineteenth ACM conference on Hypertext and hypermedia (2008)

Social cognitive theory suggests a likely relationship between the rising popularity of both reality television and social networking sites. This research utilized a survey (N=456) of young adults to determine the extent to which reality television consumption explains user behavior in the context of social network sites. Results show a consistent relationship between reality television consumption on the length of time spent logged on to these sites, the size of user's networks, the proportion of friends not actually met face to face, and photo sharing frequency while controlling for age, gender and education. Other categories of television viewing like news, fiction, and educational programming were not related to user's online behavior.
Bent and hyper-bent functions over a field of 2l elements
Authors: A. S. Kuz'Min, V. T. Markov, A. A. Nechaev, V. A. Shishkin, A. B. Shishkov
Venue: Problems of Information Transmission (2008)

We study the parameters of bent and hyper-bent (HB) functions in n variables over a field $$ P = \mathbb{F}_q $$ with q = 2¿ elements, ¿ > 1. Any such function is identified with a function F: Q ¿ P, where $$ P . The latter has a reduced trace representation F = tr P Q (¿), where ¿(x) is a uniquely defined polynomial of a special type. It is shown that the most accurate generalization of results on parameters of bent functions from the case ¿ = 1 to the case ¿ > 1 is obtained if instead of the nonlinearity degree of a function one considers its binary nonlinearity index (in the case ¿ = 1 these parameters coincide). We construct a class of HB functions that generalize binary HB functions found in [1]; we indicate a set of parameters q and n for which there are no other HB functions. We introduce the notion of the period of a function and establish a relation between periods of (hyper-)bent functions and their frequency characteristics.
On perfect nonlinear functions (&#x03a0;)
Authors: Xiyong Zhang, Hua Guo
Venue: Applicable Algebra in Engineering, Communication and Computing (2008)

Perfect nonlinear functions are of importance in cryptography. By using Galois ring, relative trace and investigating the character values of corresponding relative difference sets, we present a construction of perfect nonlinear functions from $${\mathbb{Z}_4^{2m}}$$ to $${\mathbb{Z}_4^{m'}}$$, where m&#x2032; is a divisor of 2m, and a construction of perfect nonlinear functions from $${\mathbb{Z}_{p^2}^{n}}$$ to $${\mathbb{Z}_{p^2}^m}$$ where 2m is possibly larger than the largest divisor of n. Meanwhile we prove that there exists a perfect nonlinear function from $${\mathbb{Z}_{2p}^2}$$ to $${\mathbb{Z}_{2p}}$$ if and only if p&#x00a0;=&#x00a0;2, and there doesn&#x2019;t exist a perfect nonlinear function from $${\mathbb{Z}_{2^kl}^{2n}}$$ to $${\mathbb{Z}_{2^kl}^m}$$ if m&#x00a0;>&#x00a0;n and l(l is odd) is self-conjugate modulo 2 k (k&#x00a0;&#x2265;&#x00a0;1).
Cache Design for Low Power and High Yield
Authors: Baker Mohammad, Martin Saint-Laurent, Paul Bassett, Jacob Abraham
Venue: Proceedings of the 9th international symposium on Quality Electronic Design (2008)

A novel circuit approach to increase SRAM Static Noise Margin (SNM) and enable lower operating voltage is described. Increasing process variability for new technologies coupled with increased reliability effects like Negative Bias Temperature Instability (NBTI) all contribute to raising the minimum voltage required for stable SRAM. Our strategy is to improve the noise margin of the 6T SRAM cell by reducing the effect of parametric variation of the cell, especially in the low voltage operation mode. This is done using a novel circuit that selectively reduces the voltage swing on the world line and reduces the memory supply voltage during write operation. The proposed design increases the SRAM Static Noise Margin (SNM) and write margin using a single voltage supply and with minimum impact to chip area, complexity, and timing. The technique supports both on-chip corner identification to adapt the SRAM behavior to silicon, and software controllability to tradeoff yield, power, and performance.
Off-the-path flow handling mechanism forhigh-speed and programmable traffic management
Authors: Hideyuki Shimonishi, Takashi Yoshikawa, Atsushi Iwata
Venue: Proceedings of the ACM workshop on Programmable routers for extensible services of tomorrow (2008)

In this paper, we propose a high-speed and programmable traffic management mechanism to enable easy and timely innovations. A control framework introduced by 4D, Tesseract, or OpenFlow, separates control functions from the switch nodes to a control server so that a variety of network control policies can be implemented outside of the switches. Within this framework, we propose a mechanism to enable flexible flow-based traffic management so that a variety of innovative traffic management schemes can be realized. Per-flow traffic management, however, requires packet-by-packet state updates, which can spoil this control framework. The proposed mechanism consists of a control server that monitors traffic conditions using sampled packets sent from the switches and calculates per-flow packet discarding rate, and switches that discard incoming packets according to the discarding rate. Packet sampling and discarding do not require packet-by-packet state handling at the switches and thus allows controls from a control server. We also propose a mechanism to compress the discarding information using a time series of bloom filters, so that frequent control updates are allowed. We tested the mechanism with per-flow WFQ emulation and the simulation results showed very good per-flow fairness. Furthermore, we found that the flow table is compressed 600 times smaller and that the processing cost at the server and the switches is small enough for use with 10 Gbps links.
Speech feature analysis using step-weighted linear discriminant analysis
Authors: Jiang Hai, Er Meng Joo
Venue: Proceedings of the 2nd WSEAS International Conference on Electronics, Control and Signal Processing (2003)

In the speech feature extraction procedure, the relative simple strategy to promote the discriminant of feature vectors is to plus their deltas. Followed the dimension of the feature vector will increase remarkably. Therefore, how to effectively decrease the feature space dimension is key to the performance of calculation. In this paper, a step-weighted linear discriminant dimensionality reduction technique is proposed. Dimensionality reduction using the linear discriminant analysis (LDA) is commonly based on optimization of certain separability criteria in the output space. The resulting optimization problem using LDA is linear, but these separability criteria are not related to the classification accuracy in the output space directly. As a result, even the best weighting function among the input-space results in poor classification of data in the output-space. Through the step-weighted linear discriminant dimensionality reduction technique, we can adjust the weight function of between-class scatter matrix based on the output-space when one dimension is reduced. We describe this method and present an application to a speaker-independent isolated digit recognition task.
Comparisons of weakly compressible and truly incompressible algorithms for the SPH mesh free particle method
Authors: E. -S. Lee, C. Moulinec, R. Xu, D. Violeau, D. Laurence, P. Stansby
Venue: Journal of Computational Physics (2008)

In the smoothed particle hydrodynamics (SPH) discretisation method for the Navier-Stokes equations the most widespread method to solve for pressure and mass conservation is the weakly compressible assumption (WCSPH). This includes hydraulics applications and leads to some drawbacks such as severe artificial pressure fluctuations and a limitation to very small time steps related to the WCSPH Mach number and explicit method. This paper presents comparisons of a semi-implicit and truly incompressible SPH (ISPH) algorithm with the classical WCSPH method, showing how some of the problems encountered in WCSPH have been resolved by using ISPH to simulate incompressible flows. Mathematical models are presented before describing SPH formalism. Several standard boundary conditions are introduced and special attention is given to tracking the surface particles. The lid-driven cavity flow (Re=400 and 1000) is performed as a benchmarking test. A bluff body test case (a square cylinder in a closed channel, Re"d=20 and 100 based on the cylinder diameter) shows that pressure fields extracted from WCSPH are very unreliable whereas ISPH predict pressures and forces in closer agreement with classical finite volume CFD methods. Dam-breaking cases, with dry or wet beds downstream, are then presented to highlight free-surface flow and rapid dynamics effects. The WCSPH and ISPH results are generally verified with reference data from experiment and/or another numerical method. All the comparisons show improvement with ISPH and good agreement in general.
Shared Sub-Path Protection Algorithm with Recovery Time Constraint in WDM Networks
Authors: Lei Guo, Xingwei Wang, Jin Cao, Lemin Li, Ting Yang, Fei Yang
Venue: Proceedings of the Fourth International Conference on Networking and Services (2008)

This paper proposes a new heuristic algorithm called Traffic recovery time Constrained Shared Sub-Path Protection (TC_SSPP) to provide survivability in WDM networks with Shared-Risk-Link-Group (SRLG). By properly setting the delay parameter of each link and running the Delay Constrained Shortest Path Algorithm (DCSPA) to compute the backup sub-paths, TC_SSPP can effectively guarantee the traffic recovery time for connection requests. Simulation results show that TC_SSPP outperforms the traditional algorithms.
Hierarchical second-order sliding-mode observer for linear time invariant systems with unknown inputs
Authors: F. J. Bejarano, A. Poznyak, L. Fridman
Venue: International Journal of Systems Science (2007)

The problem of observability for systems with unknown inputs is revised. The sufficient and necessary conditions are used for the design of an observer for linear systems with bounded unknown inputs. To realize the observation of the state, a second-order sliding-mode observer is suggested to be applied. Such an observer provides a robust estimate of the state vector in a finite time, without filtration. The design is based on the concept of the hierarchical output injection maintaining zero value for output tracking error at each level of the hierarchy. The equivalent control is used to identify the unknown inputs. A numerical example illustrates the effectiveness of the suggested technique.
Selecting an IT Control Framework
Authors: Steven Schlarman
Venue: The EDP Audit, Control, and Security Newsletter (2007)

Companies have now weathered several years of scrutiny under regulatory requirements with the inception of HIPAA, Sarbanes Oxley, and other industry regulations. To meet these compliance challenges, many companies have looked to different frameworks to help build controls structures within the organization. For IT organizations, this has required a shift in mindset to adopt a "controls oriented" approach while keeping up with the technology needs of the business. A key to the adoption of any framework has been ensuring the approach is applicable to your business.
Vection change exacerbates simulator sickness in virtual environments
Authors: Frederick Bonato Andrea Bubka, Stephen Palmisano, Danielle Phillip Giselle Moreno
Venue: Presence: Teleoperators and Virtual Environments (2008)

The optic flow patterns generated by virtual reality (VR) systems typically produce visually induced experiences of self-motion (vection). While this vection can enhance presence in VR, it is often accompanied by a variant of motion sickness called simulator sickness (SS). However, not all vection experiences are the same. In terms of perceived heading and/or speed, visually simulated self-motion can be either steady or changing. It was hypothesized that changing vection would lead to more SS. Participants viewed an optic flow pattern that either steadily expanded or alternately expanded and contracted. In one experiment, SS was measured pretreatment and after 5 min of viewing using the Simulator Sickness Questionnaire. In a second experiment employing the same stimuli, vection onset and magnitude were measured using a computer-interfaced slide indicator. The steadily expanding flow pattern, compared to the expanding and contracting pattern, led to: 1) significantly less SS, 2) lower subscores for nausea, oculomotor, and disorientation symptoms, 3) more overall vection magnitude, and 4) less changing vection. Collectively, these results suggest that changing vection exacerbates SS.
Cruise control using model predictive control with constraints
Authors: T. Coen, J. Anthonis, J. De Baerdemaeker
Venue: Computers and Electronics in Agriculture (2008)

Model Predictive Control (MPC) originated in process industry, but in recent years it has been used in many applications beyond this sector. MPC implies solving a quadratic optimisation problem with constraints online. For a practical prototype implementation, it is often necessary to implement the optimisation method yourself. First, the application is presented; then an overview of the most important optimisation methodologies is given. A modified Active Set Method (ASM) is derived. The advantage of this method is its straightforward implementation and good timing behaviour. This method is compared to a commercially implemented Interior Point Method (IPM) on a numerical example and on a real-life implementation.
On replacing cryptographic keys in hierarchical key management systems
Authors: Anne V. D. M. Kayem_ca, Selim G. Akl Patrick Martin
Venue: Journal of Computer Security (2008)

Shared data access maximizes resource utilization on the Internet but raises the issue of data security. We consider a method of shared data access control whereby the data is sub-divided into categories and each encrypted with a unique cryptographic key that is distributed to the user group requiring access. Key management can be simplified by classifying every user into exactly one of a number of disjoint groups that are partially ordered such that lower level keys are mathematically derivable from higher level keys, but not the reverse. The drawback in this approach is that changes in group membership imply updating both the affected group key and those that are derivable from it. Moreover, the data encrypted with the affected keys must be re-encrypted with the new keys to preserve data security. In the worst case, when the affected group is at the highest level of the hierarchy, the entire hierarchy is affected. This paper presents an algorithm that minimizes the cost of key replacement (rekeying) by associating a timestamp to each key. The timestamp and key are used to compute a verification signature that is used to authenticate users before data access is granted. Thus, whenever group membership changes, instead of rekeying and re-encrypting the affected data, only the timestamp is updated and a new verification signature computed. The new scheme is analyzed using both a time complexity and experimental analysis.
Memory karaoke: using a location-aware mobile reminiscence tool to support aging in place
Authors: Karen P. Tang, Jason I. Hong, Ian E. Smith, Annie Ha, Lalatendu Satpathy
Venue: Proceedings of the 9th international conference on Human computer interaction with mobile devices and services (2007)

Episodic memory exercises such as reminiscing and storytelling have been shown to provide therapeutic benefits for older adults by prolonging their ability to lead an independent lifestyle. In this paper, we describe a mobile reminiscence tool called Memory Karaoke, which facilitates episodic memory exercise through contextualized storytelling of meaningful experiences by using contextual cues such as location, time, and photos. We present results from two studies we conducted with Memory Karaoke to explore which contextual cues contribute to best exercising a person's episodic memory. Our findings suggest that while viewing photos do exercise episodic memory to some extent, additional contextual cues (e.g. location and time) can solicit a greater amount of episodic memory exercise. This suggests that Memory Karaoke's selective capture process and its ability to contextualize memories while users retell stories are two effective features which help it to support episodic memory use. These results, together with positive qualitative feedback, provide promising evidence for Memory Karaoke as a viable mobile alternative for helping older adults to exercise their episodic memory and, in turn, assist them in successfully "aging in place".