ppxscal/embedding_network huggingface dataset:
Exploiting Runtime Information in the IDE
Authors: David Röthlisberger, Orla Greevy, Oscar Nierstrasz
Venue: Proceedings of the 2008 The 16th IEEE International Conference on Program Comprehension (2008)

Developers rely on the mechanisms provided by their IDE to browse and navigate a large software system. These mechanisms are usually based purely on a system's static source code. The static perspective, however, is not enough to understand an object-oriented program's behavior, in particular if implemented in a dynamic language. We propose to enhance IDEs with a program's runtime information (e.g. message sends and type information) to support program comprehension through precise navigation and informative browsing. To precisely specify the type and amount of runtime data to gather about a system under development, dynamically and on demand, we adopt a technique known as partial behavioral reflection. We implemented navigation and browsing enhancements to an IDE that exploit this runtime information in a prototype called Hermion. We present preliminary validation of our experimental enhanced IDE by asking developers to assess its usefulness to understand an unfamiliar software system.
A Tool for Experimenting with Theories of Emotion in MultiAgent Systems
Authors: Maria R. Cravo, Énio M. Pereira
Venue: Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction (2007)

In order to synthetize affective states, computer systems use emotion theories from psychology, that provide guidelines for deciding what kind of emotion, and with what intensity, should be elicited in a given situation. According to most theories, the emotions of an agent depend on the subjective appraisal of situations. While they provide essential knowledge for the generation of synthetic emotions, these theories do not specify all aspects necessary for the design of computational systems that implement them. So, when designing computational agents that "experience" affective states, computer scientists have a long way to go, and many decisions to make, to produce the information necessary to theories of emotion. When all these difficulties are overcome, still a lot of experimenting is necessary to make adjustments to the formulas and algorithms used.
The Boundaries of Time
Authors: David Alan Grier
Venue: Computer (2007)

Much of the strategy to fix the Y2K Problem followed the standard cycle of quality engineering.
Using multimedia to teach inservice teachers: Impacts on learning, application, and retention
Authors: Caroline R. Pryor, Gary G. Bitter
Venue: Computers in Human Behavior (2008)

This study investigated teachers' ability to learn, apply in lesson plans, and retain knowledge of classroom discourse from a single module of a multimedia professional development program, used with 39 K-12 teachers enrolled in two graduate courses. Data collection and analysis included: (a) teacher development of - and panel review of - lesson plans integrating discourse, and (b) follow-up teacher interviews one year later. The study found: (a) the video modeling in the module was effective in helping teachers learn, and (b) discourse strategies were learned, applied, and retained. Implications for professional development with multimedia to teach classroom discourse include: (a) recursive use, (b) reflection, (c) multiple examples, (d) counter examples, and (e) prompts for observation.
Well Quasi-orders in Formal Language Theory
Authors: Flavio D'Alessandro, Stefano Varricchio
Venue: Proceedings of the 12th international conference on Developments in Language Theory (2008)

The concept of well quasi-order is a generalization of the classical notion of well order and plays a role in the studying of several problems of Mathematics and Theoretical Computer Science. This paper concerns some applications of well quasi-orders to Formal Language Theory. In particular, we present a survey of classical and recent results, based upon such structures, concerning context-free and regular languages. We also focus our attention to some application of well quasi-orders in the studying of languages obtained by using the operators of shuffle and iterated shuffle of finite languages.
Experiences using a hands-free interface
Authors: Cristina Manresa-Yee, Javier Varona, Francisco J. Perales, Francesca Negre, Joan Jordi Muntaner
Venue: Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility (2008)

Hands-free interfaces could be the best choice for Human-Computer Interaction (HCI) for people with physical disabilities that are not capable of using traditional input devices. Once a first prototype is developed in the laboratory taking into account design and usability requirements, real users is what finally categorize an interface as useful or not. Therefore, an evaluation of our interface with users with cerebral palsy and multiple sclerosis has been carried out during a project of 9 months long. This paper presents a vision-based user interface designed to achieve computer accessibility together with the validation and evaluation of its human computer interaction issues such as usability and accessibility.
Stability Analysis of a Class of Two-Neuron Networks with Time-Varying Delays
Authors: Ying Zhang, Chuangxia Huang, Yigang He
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

This paper formulates and studies a model of neural network under a time-varying environment. Without assuming the smoothness, monotonicity and boundedness of the activation functions, the existence and global exponential stability of an unique equilibrium are investigated. Ourap-proach is based on the Brouwer's fixed point theorem, Banach fixed point theorem, and Halanay-type inequality.
ID-Based Multiple Space Key Pre-distribution Scheme for Wireless Sensor Networks
Authors: Tran Thanh Dai, Choong Seon Hong
Venue: Proceedings of the 5th international conference on Wired/Wireless Internet Communications (2007)

Providing security services for wireless sensor networks plays a vital role in secure network operation especially when sensor networks are deployed in hostile areas. In order to pave the way for these mechanisms, cryptographic keys must be agreed on by communicating nodes. Unfortunately, due to resource constraints, the key agreement problem in wireless sensor networks becomes quite intricate. To deal with this problem, many public-key unrelated proposals have been proposed so far. One prominent branch of these proposals is based on random key pre-distribution. Inspired by this trend, in this paper, we propose a new random key pre-distribution scheme that is comparable to Du et al.'s scheme [2] in terms of network resiliency and memory usage. On the other hand, our later analysis shows that our scheme outperforms Du et al.'s scheme in terms of computational and communication overhead.
Speech/Music Discrimination Based on Discrete Wavelet Transform
Authors: Stavros Ntalampiras, Nikos Fakotakis
Venue: Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications (2008)

In this paper we present an effective approach which addresses the issue of speech/music discrimination. Our architecture focuses on the matter from the scope of improving the performance of a speech recognition system by excluding the processing of information which is not speech. Multiresolution analysis is applied to the input signal while the most significant statistical features are calculated over a predefined texture size. These characteristics are then modeled using a state of the art technique for probability density function estimation, Gaussian mixture models (GMM). A classification scheme consisting of a conventional maximum likelihood decision methodology constitutes the next step of our implementation. Despite the fact that our system is based solely on wavelet signal processing, it demonstrated very good performance achieving 91.8% recognition rate.
A Characterisation of Lambda Definability with Sums Via T T -Closure Operators
Authors: Shin-Ya Katsumata
Venue: Proceedings of the 22nd international workshop on Computer Science Logic (2008)

We give a new characterisation of morphisms that are definable by the interpretation of the simply typed lambda calculus with sums in any bi-Cartesian closed category. The ¿ ¿-closure operator will be used to construct the category in which the collection of definable morphisms at sum types can be characterised as the coproducts of such collections at lower types.
Fluid Semantic Back-Channel Feedback in Dialogue: Challenges and Progress
Authors: Gudny Ragna Jonsdottir, Jonathan Gratch, Edward Fast, Kristinn R. Thórisson
Venue: Proceedings of the 7th international conference on Intelligent Virtual Agents (2007)

Participation in natural, real-time dialogue calls for behaviors supported by perception-action cycles from around 100 msec and up. Generating certain kinds of such behaviors, namely envelope feedback, has been possible since the early 90s. Real-time backchannel feedback related to the content of a dialogue has been more difficult to achieve. In this paper we describe our progress in allowing virtual humans to give rapid within-utterance content-specific feedback in real-time dialogue. We present results from human-subject studies of content feedback, where results show that content feedback to a particular phrase or word in human-human dialogue comes 560-2500 msec from the phrase's onset, 1 second on average. We also describe a system that produces such feedback with an autonomous agent in limited topic domains, present performance data of this agent in human-agent interactions experiments and discuss technical challenges in light of the observed human-subject data.
Extraction of Filled-In Items from Chinese Bank Check Using Support Vector Machines
Authors: Liangli Huang, Shutao Li, Liming Li
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

In this paper, a novel bank check filled-in-items extraction method based on support vector machines (SVM) is proposed. After preprocessing, the bank logos are cropped and recognized by SVMs. Then the bank type characters, in Chinese are cropped and classified with another SVM. After check type is recognized, real check is registered to the corresponding standard blank check. Finally the filled-in items in real check are extracted. The experimental results demonstrate the presented method is effective.
Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops
Venue: International Conference on Simulation Tools and Techniques for Commuications, Networks and Systems & Workshops (2008)

SIMUTools 2008 is the first international conference focusing on Simulation Tools and Techniques for Communications, Networks, and Systems. The conference will address all aspects of simulation modelling and analysis. Papers are sought on the topics of methodology, tools, applications, and practices. Particular emphasis will be given to papers that bridge multiple areas.
Context-aware multimedia services in a pervasive environment: the Daidalos approach
Authors: Kevin Doolin, Andreas Pashalidis, Andreas Kassler, Telma Mota
Venue: Proceedings of the 2008 Ambi-Sys workshop on Software Organisation and MonIToring of Ambient Systems (2008)

There is a clear trend towards making multimedia applications context-aware so as to customize them by taking into account any collection of information which may be relevant, such as e.g. user location. However, current multimedia services are dominated by IMS, which is seen as a service platform that uses the SIP protocol to access all services that the Internet can provide. In this paper, we describe the Daidalos approach on making IMS based multi-media services context-aware. We also demonstrate, how generic sensor networks can be integrated into the context management system of our platform thus enabling sensor network detected events to influence behavior of context-aware multimedia applications.
Representing and Parsing Sketched Symbols Using Adjacency Grammars and a Grid-Directed Parser
Authors: Joan Mas, Joaquim A. Jorge, Gemma Sanchez, Josep Llados
Venue: Graphics Recognition. Recent Advances and New Opportunities: 7th International Workshop, GREC 2007, Curitiba, Brazil, September 20-21, 2007. Selected Papers (2008)

While much work has been done in Structural and Syntactical Pattern Recognition applied to drawings, most approaches are non-interactive. However, the recent emergence of viable pen-computers makes it desirable to handle pen-input such as sketches and drawings interactively. This paper presents a syntax-directed approach to parse sketches based on Relational Adjacency Grammars, which describe spatial and topological relations among parts of a sketch. Our approach uses a 2D grid to avoid re-scanning all the previous input whenever new strokes entered into the system, thus speeding up parsing considerably. To evaluate the performance of our approach we have tested the system using non-trivial inputs analyzed with two different grammars, one to design user interfaces and the other to describe floor-plans. The results clearly show the effectiveness of our approach and demonstrate good scalability to larger drawings.
Computer usage by young individuals with down syndrome: an exploratory study
Authors: J. Feng, J. Lazar, L. Kumin, A. Ozok
Venue: Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility (2008)

In this paper, we discuss the results of an online survey that investigates how children and young adults with Down syndrome use computers and computer-related devices. The survey responses cover 561 individuals with Down syndrome between the age of four to 21. The survey results suggest that the majority of the children and young adults with Down syndrome can use the mouse to interact with computers, which requires spatial, cognitive, and fine motor skills that were previously believed to be quite challenging for individuals with Down syndrome. The results show great difficulty in text entry using keyboards. Young individuals with Down syndrome are using a variety of computer applications and computer related devices, and computers and computer-related devices play important roles in the life of individuals with Down syndrome. There appears to be great potential in computer-related education and training to broaden existing career opportunities for individuals with Down syndrome, and there needs to be further research on this topic.
Measuring and Analyzing Emerging Properties for Autonomic Collaboration Service Adaptation
Authors: Christoph Dorn, Hong-Linh Truong, Schahram Dustdar
Venue: Proceedings of the 5th international conference on Autonomic and Trusted Computing (2008)

Dynamic collaboration environments in which team member utilize different pervasive collaboration services for their collaborative work pose many challenges for service adaptation. Given a team, the underlying collaboration services must fulfil the team's goal. Thus, it is not enough to adapt collaboration services to the context of an individual. One needs to understand the behavior of the team and the collaboration services in order to adapt these services. Though many research efforts aim at understanding team behavior at the human level, there is no such a framework that focuses on adapting collaboration services for teamwork.In this paper, we introduce a set of novel metrics that characterizes emergent behavior of teams. We present a team analysis and adaptation framework (TAAF) which monitors diverse collaboration services, analyzes and provides relevant metrics for understanding dynamic teams and for continuous team and service adaptation. This paper also discusses how TAAF can be used to support self-management of collaboration services for collaborative teams.
Wavelet Enhanced Analytical and Evolutionary Approaches to Time Series Forecasting
Authors: Bartosz Kozlowski
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

This paper provides two methodologies for forecasting time series. One of them is based on the Wavelet Analysis and the other one on the Genetic Programming. Two examples from finance domain are used to illustrate how given methodologies perform in real-life applications. Additionally application to specific classes of time series, seasonal, is discussed.
Nonlinear Feature Selection by Relevance Feature Vector Machine
Authors: Haibin Cheng, Haifeng Chen, Guofei Jiang, Kenji Yoshihira
Venue: Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition (2007)

Support vector machine (SVM) has received much attention in feature selection recently because of its ability to incorporate kernels to discover nonlinear dependencies between features. However it is known that the number of support vectors required in SVM typically grows linearly with the size of the training data set. Such a limitation of SVM becomes more critical when we need to select a small subset of relevant features from a very large number of candidates. To solve this issue, this paper proposes a novel algorithm, called the `relevance feature vector machine'(RFVM), for nonlinear feature selection. The RFVM algorithm utilizes a highly sparse learning algorithm, the relevance vector machine (RVM), and incorporates kernels to extract important features with both linear and nonlinear relationships. As a result, our proposed approach can reduce many false alarms, e.g. including irrelevant features, while still maintain good selection performance. We compare the performances between RFVM and other state of the art nonlinear feature selection algorithms in our experiments. The results confirm our conclusions.
RAM: Randomized Approximate Graph Mining
Authors: Shijie Zhang, Jiong Yang
Venue: Proceedings of the 20th international conference on Scientific and Statistical Database Management (2008)

We propose a definition for frequent approximate patterns in order to model important subgraphs in a graph database with incomplete or inaccurate information. By our definition, frequent approximate patterns possess three main properties: possible absence of exact match, maximal representation, and the Apriori Property. Since approximation increases the number of frequent patterns, we present a novel randomized algorithm (called RAM) using feature retrieval. A large number of real and synthetic data sets are used to demonstrate the effectiveness and efficiency of the frequent approximate graph pattern model and the RAM algorithm.
On the gradual evolution of complexity and the sudden emergence of complex features
Authors: Charles Ofria, Wei Huang, Eric Torng
Venue: Artificial Life (2008)

Evolutionary theory explains the origin of complex organismal features through a combination of reusing and extending information from less-complex traits, and by needing to exploit only one of many unlikely pathways to a viable solution. While the appearance of a new trait may seem sudden, we show that the underlying information associated with each trait evolves gradually. We study this process using digital organisms, self-replicating computer programs that mutate and evolve novel traits, including complex logic operations. When a new complex trait first appears, its proper function immediately requires the coordinated operation of many genomic positions. As the information associated with a trait increases, the probability of its simultaneous introduction drops exponentially, so it is nearly impossible for a significantly complex trait to appear without reusing existing information. We show that the total information stored in the genome increases only marginally when a trait first appears. Furthermore, most of the information associated with a new trait is either correlated with existing traits or co-opted from traits that were lost in conjunction with the appearance of the new trait. Thus, while total genomic information increases incrementally, traits that require much more information can still arise during the evolutionary process.
The Use of LSI Modules in Computer Structures: Trends and Limitations
Authors: D. P. Siewiorek
Venue: Computer (1978)

Advances in LSI technology are beginning to outstrip architectural innovations and their implementation, calling for greater software productivity and development of better design aids.
Tactile Perceptual Dimensions: A Study with Light-Weight Wool Fabrics
Authors: Alexandra Fernandes, Pedro B. Albuquerque
Venue: Proceedings of the 6th international conference on Haptics: Perception, Devices and Scenarios (2008)

The aim of this study was to identify the tactile dimensions in the discrimination of light-weight wool fabrics. The participants judged the overall similarity between 21 light-weight wool fabrics using free sorting tasks. The fabrics were evaluated using active touch with limited exploratory procedure. Multidimensional scaling (MDS) was used to generate the perceptual space, revealing one dimension of tactile perception. Finally, through regression analysis we were able to interpret this dimension, using verbal attributes and physical properties of the fabrics. We discuss the relevance of the stimuli properties and the associations between verbal attributes and between physical properties, on the evaluation of the fabrics, considering its theoretical implications.
Machine learning for physical layer link adaptation in multiple-antenna wireless networks
Authors: Robert C. Daniels, Ketan Mandke, Steven W. Peters, Scott M. Nettles, Robert W. Heath,  Jr.
Venue: Proceedings of the third ACM international workshop on Wireless network testbeds, experimental evaluation and characterization (2008)

Prototyping and experimentation are key to understanding the operation of wireless systems in practice. In this extended abstract we present an implementation of physical layer link adaptation, or data rate selection, through machine learning on Hydra: an IEEE 802.11n draft standard multihop wireless networking prototype. This implementation highlights both the utility of learning-based link adaptation in practical networks as well as the flexibility of Hydra.
Online or offline? exploring working memory constraints in spatial updating
Authors: Anthony Michael Harrison
Venue:  (2007)

All spatial representation theories rely upon two spatial updating processes in order to maintain spatially consistent self-to-object relationships: movement-driven, automatic online updating and offline, conscious mental transformations of perspective. Theoretical differentiation based on offline updating is difficult given the equivalent predictions for many of the spatial tasks commonly used (i.e. egocentric pointing). However, representational theories do diverge with respect to the predicted working memory constraints of online updating. In experiment one participants studied groups of 4, 6, 8 targets, engaged in a 180&deg; rotation on half the trials and completed a series of judgments of relative direction and egocentric pointing. Set size effects for both tasks were limited to latencies alone, suggesting offline updating. Experiment two had participants study smaller (3 target) configurations and make egocentric pointing responses. On half the trials, participants engaged in either a verbal or spatial 1-back task during both retention and rotation periods. No effect of dual-task load or type were found for egocentric pointing. Both latencies and errors were significantly greater for the post-rotation pointing suggesting offline updating. The lack of evidence for online updating is surprising and contrary to previous findings that it is an obligatory automatic process (e.g. Farrell Thomson, 1998). Multiple models were developed within ACT-R/S (Harrison Schunn, 2003) illustrating the sufficiency of offline updating to account for the current findings. The challenges of detecting online updating and investigating its working memory constraints are discussed in the light of these results and simulations.