ppxscal/embedding_network huggingface dataset:
Region pointcut for AspectJ
Authors: Shumpei Akai, Shigeru Chiba, Muga Nishizawa
Venue: Proceedings of the 8th workshop on Aspects, components, and patterns for infrastructure software (2009)

This paper proposes a new pointcut called region pointcut, which has the ability to pick out regions as join points. This pointcut allows programmers to modularize synchronization, exception handling and parallelization. Although these are typical crosscutting concerns, the join point that we need to advise for such a concern is not a point but a region. The existing aspect-oriented programming language, including AspectJ, provide only the means to pick out points. We modified the AspectBench compiler and implemented region pointcuts as an extension to the AspectJ language.
Learning secondary mathematics with technology: Exploring the complex interrelationship between students' attitudes, engagement, gender and achievement
Authors: Anastasios (Tasos) Barkatsas, Katerina Kasimatis, Vasilis Gialamas
Venue: Computers Education (2009)

The aim of this study was to investigate the complex relationship between students' mathematics confidence, confidence with technology, attitude to learning mathematics with technology, affective engagement and behavioural engagement, achievement, gender and year level. The participants were secondary students from state co-educational schools in Metropolitan Athens, Greece. Gender differences as well as differences between year levels and the resulting clusters of students were investigated by using a MANOVA. It was found that boys expressed more positive views towards mathematics and more positive views towards the use of technology in mathematics, compared to girls. It was also found that high achievement in mathematics was associated with high levels of mathematics confidence, strongly positive levels of affective engagement and behavioural engagement, high confidence in using technology and a strongly positive attitude to learning mathematics with technology. Low levels of mathematics achievement was associated with low levels of mathematics confidence, strongly negative levels of affective engagement and behavioural engagement, low confidence in using technology, and a negative attitude to learning mathematics with technology.
Automatic Generation and Evolution of Model Transformations Using Ontology Engineering Space
Authors: Stephan Roser, Bernhard Bauer
Venue: Journal on Data Semantics XI (2008)

Model-driven software development facilitates faster and more flexible integration of information and communication systems. It divides system descriptions into models of different view points and abstraction levels. To effectively realize cross-organisational collaborations, it is an important prerequisite to exchange models between different modelling languages and tools. Knowledge is captured in model transformations, which are continuously adjusted to new modelling formats and tools. However, interoperability problems in modelling can hardly be overcome by solutions that essentially operate at syntactical level. This paper presents a novel approach using the capabilities of semantic technologies in order to improve cross-organisational modelling by automatic generation and evolution of model transformations.
Enhancing the Privacy of e-Learning Systems with Alias and Anonymity
Authors: Jianming Yong
Venue: Computer Supported Cooperative Work in Design IV: 11th International Conference, CSCWD 2007, Melbourne, Australia, April 26-28, 2007. Revised Selected Papers (2008)

The privacy of e-learning systems has become a big concern. This paper proposes a new approach, which can effectively protect the privacy of elearning users. We propose to use the alias and anonymity to implement the privacy preservation for e-learning systems. Through the approach, a unique alias represents the real e-learning user to communicate with each other or e-learning users use the anonymity to hide their information. This approach can be very simple and efficient to be implemented in the e-learning system by well designed meta-formats of digital identities of four types of e-learning users. The anonymity can be adopted by all e-learning users to keep their privacy.
Security Analysis of a Variant of Self-Shrinking Generator
Authors: Dong Hoon Lee, Je Hong Park, Jae Woo Han
Venue: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2008)

A variant of the self-shrinking generator (SSG) proposed at ICISC 2006, which we call SSG-XOR, was claimed to have better cryptographic properties than SSG in a practical setting. It was also claimed that SSG-XOR will be more secure than SSG. But we show that SSG-XOR has no advantage over SSG from the viewpoint of practical cryptanalysis, especially the guess-and-determine attack.
Preliminary comparison of ballistic electron emission spectroscopy measurements on InAs quantum dots in a GaAs/AlGaAs heterostructure grown by MBE and MOVPE
Authors: Jan Vaniš, Jiří Zelinka, Václav Malina, Mohamed Henini, Jiří Pangrác, Karel Melichar, Eduard Hulicius, Filip Šroubek, Jarmila Walachová
Venue: Microelectronics Journal (2009)

Self-assembled InAs quantum dots (SAQDs) in GaAs/GaAlAs structures grown by molecular beam epitaxy (MBE) and metal-organic vapour phase epitaxy (MOVPE) of similar size was examined by ballistic electron emission spectroscopy. Ballistic current-voltage characteristics through the QD in the voltage range from 0.55 to 0.9V (range where the presence of resonance states of QD is expected) with its derivative (the derivation of the spectroscopic characteristics represents quantum levels in the QD) are given. Differences in the intensities and sharpnesses of the QD levels for MBE and MOVPE grown QDs are observed.
Social immersive media: pursuing best practices for multi-user interactive camera/projector exhibits
Authors: Scott S. Snibbe, Hayes S. Raffle
Venue: Proceedings of the 27th international conference on Human factors in computing systems (2009)

Based on ten years' experience developing interactive camera/projector systems for public science and culture exhibits, we define a distinct form of augmented reality focused on social interaction: social immersive media. Our work abandons GUI metaphors and builds on the language of cinema, casting users as actors within simulated narrative models. We articulate philosophical goals, design principles, and interaction techniques that create strong emotional responses and social engagement through visceral interaction. We describe approaches to clearly communicate cultural and scientific ideas through the medium. And we demonstrate how practitioners can design interactions that promote specific social behaviors in users.
Towards Virtual Epidemiology: An Agent-Based Approach to the Modeling of H5N1 Propagation and Persistence in North-Vietnam
Authors: Edouard Amouroux, Stéphanie Desvaux, Alexis Drogoul
Venue: Proceedings of the 11th Pacific Rim International Conference on Multi-Agents: Intelligent Agents and Multi-Agent Systems (2008)

In this paper we claim that a combination of an agent-based model and a SIG-based environmental model can act as a "virtual laboratory" for epidemiology. Following the needs expressed by epidemiologists studying micro-scale dynamics of avian influenza in Vietnam, and after a review of the epidemiological models proposed so far, we present our model, built on top of the GAMA platform, and explain how it can be adapted to the epidemiologists' requirements. One notable contribution of this work is to treat the environment, together with the social structure and the animals' behaviors, as a first-class citizen in the model, allowing epidemiologists to consider heterogeneous micro and macro factors in their exploration of the causes of the epidemic.
Physical design methodology for analog circuitsin a system-on-a-chip environment
Authors: Eric G. Soenen
Venue: Proceedings of the 2009 international symposium on Physical design (2009)

This talk reviews some of the issues that are unique to analog Integrated Circuit (IC) design. These issues become more acute as the process geometries shrink and the complexity of the IC increases. In so-called "Systems on a Chip" (SOCs), the analog circuitry is combined with large amounts of logic on the same die. The switching noise complicates the design of high-accuracy circuits.In addition, analog circuits need a certain amount of silicon area to work well. This area does not necessarily scale much as the process geometries get smaller. In order for the analog circuitry to remain cost-competitive, very careful optimization of the layout is critical. For all these reasons, new specialized design methodologies are needed. New tools are emerging, which are specifically aimed at optimizing the layout of the analog circuitry at the same time as the schematic, taking in account the environment. An overview of these tools is given.
Multi-level meshless methods based on direct multi-elliptic interpolation
Authors: C. Gáspár
Venue: Journal of Computational and Applied Mathematics (2009)

A short overview on the direct multi-elliptic interpolation and the related meshless methods for solving partial differential equations is given. A new technique is proposed which produces a biharmonic interpolation along the boundary and solves the original problem inside the domain. An error estimation is also derived. To implement the method, quadtree-based multi-level methods are used. The approach avoids the use of large, dense and ill-conditioned matrices and significantly reduces the computational cost.
Serialization sets: a dynamic dependence-based parallel execution model
Authors: Matthew D. Allen, Srinath Sridharan, Gurindar S. Sohi
Venue: Proceedings of the 14th ACM SIGPLAN symposium on Principles and practice of parallel programming (2009)

This paper proposes a new parallel execution model where programmers augment a sequential program with pieces of code called serializers that dynamically map computational operations into serialization sets of dependent operations. A runtime system executes operations in the same serialization set in program order, and may concurrently execute operations in different sets. Because serialization sets establish a logical ordering on all operations, the resulting parallel execution is predictable and deterministic. We describe the API and design of Prometheus, a C++ library that implements the serialization set abstraction through compile-time template instantiation and a runtime support library. We evaluate a set of parallel programs running on the x86_64 and SPARC-V9 instruction sets and study their performance on multicore, symmetric multiprocessor, and ccNUMA parallel machines. By contrast with conventional parallel execution models, we find that Prometheus programs are significantly easier to write, test, and debug, and their parallel execution achieves comparable performance.
Novel Architecture of Feedforward Second-Order Multibit ΔΣAD Modulator
Authors: Hao San, Hajime Konagaya, Feng Xu, Atsushi Motozawa, Haruo Kobayashi, Kazumasa Ando, Hiroshi Yoshida, Chieto Murayama, Kanichi Miyazawa
Venue: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2008)

This paper proposes novel feedforward architecture of the second-order multibit ΔΣAD modulator with single DAC-feedback topology. The ΔΣAD modulator realizes high resolution by oversampling and noise shaping techniques. However, its SNDR (Signal to Noise and Distortion Ratio) is limited by the dynamic range of the input signal and non-idealities of circuit building blocks, particularly by the harmonic distortion in amplifier circuits. A full feedforward ΔΣAD modulator structure has the signal transfer function of unity under ideal circumstances, which means that the signal swings through the loop filter become smaller compared with a feedbacked ΔΣAD modulator. Therefore, the harmonic distortion generated inside the loop filter can be significantly reduced in the feedforward structure because the effect of non-idealities in amplifiers can be suppressed when signal swing is small. Moreover, the reduction of the internal signal swings also relaxes output swing requirements for amplifiers with low supply voltage. However, in conventional feedforward ΔΣAD modulator, an analog adder is needed before quantizer, and especially in a multibit modulator, an additional amplifier is necessary to realize the summation of feedforward signals, which leads to extra chip area and power dissipation. In this paper, we propose a novel architecture of a feedforward ΔΣAD modulator which realizes the summation of feedforward signals without additional amplifier. The proposed architecture is functionally equivalent to the conventional one but with smaller chip area and lower power dissipation. We conducted MATLAB and SPICE simulations to validate the proposed architecture and modulator circuits.
Learning to predict information needs: context-aware display as a cognitive aid and an assessment tool
Authors: Bradley C. Love, Matt Jones, Marc T. Tomlinson, Michael Howe
Venue: Proceedings of the 27th international conference on Human factors in computing systems (2009)

We discuss the problem of assessing and aiding user performance in dynamic tasks that require rapid selection among multiple information sources. Motivated by research in human sequential learning, we develop a system that learns by observation to predict the information a user desires in different contexts. The model decides when the display should be updated, which is akin to the problem of scene segmentation, and then selects the situationally relevant information display. The model reduces the cognitive burden of selecting situation-relevant displays. We evaluate the system in a tank video game environment and find that the system boosts user performance. The fit of the model to user data provides a quantitative assessment of user behavior, which is useful in assessing individual differences and the progression from novice- to expert-level proficiency. We discuss the relative benefits of adopting a learning approach to predicting information preferences and possible avenues to reduce the negative consequences of automation.
Interpreting PET Scans by Structured Patient Data: A Data Mining Case Study in Dementia Research
Authors: Andreas Hapfelmeier, Jana Schmidt, Marianne Mueller, Stefan Kramer, Robert Perneczky, Alexander Kurz, Alexander Drzezga
Venue: Proceedings of the 2008 Eighth IEEE International Conference on Data Mining (2008)

One of the goals of medical research in the area of dementia is to correlate images of the brain with other variables, for instance, demographic information or outcomes of clinical tests. The usual approach is to select a subset of patients based on such variables and analyze the images associated with those patients. In this paper, we apply data mining techniques to take the opposite approach: We start with the images and explain the differences and commonalities in terms of the other variables. In the first step, we cluster PET scans of patients to form groups sharing similar features in brain metabolism. To the best of our knowledge, it is the first time ever that clustering is applied to whole PET scans. In the second step, we explain the clusters by relating them to non-image variables. To do so, we employ RSD, an algorithm for relational subgroup discovery, with the cluster membership of patients as target variable. Our results enable interesting interpretations of differences in brain metabolism in terms of demographic and clinical variables. The approach was implemented and tested on an exceptionally large pre-existing data collection of patients with different types of dementia. It comprises 10 GB of image data from 454 PET scans, and 42 variables from psychological and demographical data organized in 11 relations of a relational database. We believe that explaining medical images in terms of other variables (patient records, demographic information, etc.) is a challenging new and rewarding area for data mining research.
A Practical Approach to Classify Evolving Data Streams: Training with Limited Amount of Labeled Data
Authors: Mohammad M. Masud, Jing Gao, Latifur Khan, Jiawei Han, Bhavani Thuraisingham
Venue: Proceedings of the 2008 Eighth IEEE International Conference on Data Mining (2008)

Recent approaches in classifying evolving data streams are based on supervised learning algorithms, which can be trained with labeled data only. Manual labeling of data is both costly and time consuming. Therefore, in a real streaming environment, where huge volumes of data appear at a high speed, labeled data may be very scarce. Thus, only a limited amount of training data may be available for building the classification models, leading to poorly trained classifiers. We apply a novel technique to overcome this problem by building a classification model from a training set having both unlabeled and a small amount of labeled instances. This model is built as micro-clusters using semisupervised clustering technique and classification is performed with κ-nearest neighbor algorithm. An ensemble of these models is used to classify the unlabeled data. Empirical evaluation on both synthetic data and real botnet traffic reveals that our approach, using only a small amount of labeled data for training, outperforms state-of-the-art stream classification algorithms that use twenty times more labeled data than our approach.
Sketch-on-Map: Spatial Queries for Retrieving Human Locomotion Patterns from Continuously Archived GPS Data
Authors: Gamhewage C. Silva, Toshihiko Yamasaki, Kiyoharu Aizawa
Venue: Proceedings of the 15th International Multimedia Modeling Conference on Advances in Multimedia Modeling (2009)

We propose a system for retrieving human locomotion patterns from tracking data captured within a large geographical area, over a long period of time. A GPS receiver continuously captures data regarding the location of the person carrying it. A constrained agglomerative hierarchical clustering algorithm segments these data according to the person's navigational behavior. Sketches made on a map displayed on a computer screen are used for specifying queries regarding locomotion patterns. Two basic sketch primitives, selected based on a user study, are combined to form five different types of queries. We implement algorithms to analyze a sketch made by a user, identify the query, and retrieve results from the collection of data. A graphical user interface combines the user interaction strategy and algorithms, and allows hierarchical querying and visualization of intermediate results. The sketch-based user interaction strategy facilitates querying for locomotion patterns in an intuitive and unambiguous manner.
A cross-language focused crawling algorithm based on multiple relevance prediction strategies
Authors: Zhumin Chen, Jun Ma, Jingsheng Lei, Bo Yuan, Li Lian, Ling Song
Venue: Computers Mathematics with Applications (2009)

Focused crawling is increasingly seen as a solution to address the scalability limitations of existing general-purpose search engines, by traversing the Web to only gather pages that are relevant to a specific topic. How to predict the relevance of the unvisited pages pointed to by candidate URLs in the crawling frontier to a given topic is a key issue in the design of focused crawlers. In this paper, we propose a novel approach based on multiple relevance prediction strategies to address this problem. For cross-language crawling, we first introduce a hierarchical taxonomy to describe topics in both English and Chinese. We then present a formal description of the relevance predicting process and discuss four strategies that make use of page contents, anchor texts, URL addresses and link types of Web pages, respectively, to evaluate the relevance more accurately, in which we propose a particular strategy using Chinese URL addresses to estimate the relevance of cross-language Web pages. Finally, we get a new focused crawling algorithm (FCMRPS, Focused Crawling based on Multiple Relevance Prediction Strategies) based on the combination of these strategies and Shark-Search, which is a classic focused crawling algorithm. Experiments show that the FCMRPS is more effective than the traditional algorithms, namely Breadth-First, Best-First and Shark-Search, in terms of precision and sum of information.
Dynamic Texture Detection Based on Motion Analysis
Authors: Sándor Fazekas, Tomer Amiaz, Dmitry Chetverikov, Nahum Kiryati
Venue: International Journal of Computer Vision (2009)

Motion estimation is usually based on the brightness constancy assumption. This assumption holds well for rigid objects with a Lambertian surface, but it is less appropriate for fluid and gaseous materials. For these materials an alternative assumption is required. This work examines three possible alternatives: gradient constancy, color constancy and brightness conservation (under this assumption the brightness of an object can diffuse to its neighborhood). Brightness conservation and color constancy are found to be adequate models. We propose a method for detecting regions of dynamic texture in image sequences. Accurate segmentation into regions of static and dynamic texture is achieved using a level set scheme. The level set function separates each image into regions that obey brightness constancy and regions that obey the alternative assumption. We show that the method can be simplified to obtain a less robust but fast algorithm, capable of real-time performance. Experimental results demonstrate accurate segmentation by the full level set scheme, as well as by the simplified method. The experiments included challenging image sequences, in which color or geometry cues by themselves would be insufficient.
On the Capacity of Weibull Fading MIMO Channels under Different Adaptive Transmission Techniques
Authors: Hailin Xiao, Shan Ouyang
Venue: Proceedings of the 2009 WRI International Conference on Communications and Mobile Computing - Volume 01 (2009)

Space-time block codes (STBCs) are known to orthogonalize the multiple-input multiple-out (MIMO) wireless channels. In this paper, we study the capacity of STBCs over Weibull MIMO channels under three adaptive transmission techniques: optimal power and rate adaptation (orpa), optimal rate adaptation with constant transmit power (ora) and channel inversion with fixed rate. In particular, we obtain closed-form expressions for channel capacity of orthogonalized Weibull MIMO channels under these adaptive transmission techniques. This capacity provides an upper bound on spectral efficiency using these techniques and avoids Monte-Carlo simulations. Moreover, we also examine the effects of the fading severity on the concerned quantities. The figures show that our theoretical results of channel capacity line up exactly with the simulations.
Resilience through technology adoption: merging the old and the new in Iraq
Authors: Gloria J. Mark, Ban Al-Ani, Bryan Semaan
Venue: Proceedings of the 27th international conference on Human factors in computing systems (2009)

Citizen response to disaster has begun to receive attention in the CHI community but little attention has so far been given to how citizens use technology to adapt when their country is at war. We report on an ethnographic interview study of how technology was adopted and used by citizens to be resilient during wartime. We interviewed 45 Iraqi citizens experiencing the current Iraq war. Based on our data we identified properties of resilience: reconfiguring social networks, self-organization, redundancy, proactive practices, and repairing trust in information. Technology supported people in being resilient by enabling them to control identity, to collaborate in travel, to create an organizational memory, and to provide alternative sources of news and information. As people adopted and used technology to be resilient we found a merging of old and new cultural practices. We discuss these systemic changes and describe implications for how technology can support people in being resilient in disrupted environments.