ppxscal/embedding_network huggingface dataset:
Projected cognition: capturing intent in descriptions of complex interaction
Authors: William Edmondson, Russell Beale
Venue: Proceedings of the 7th ACM conference on Designing interactive systems (2008)

In a study of activity and usage of comparatively complex configurations - where users have multiple screens and/or multiple computers - we have noticed that accounts of what is being observed and reported are tricky to unify within a coherent framework. In this paper we look in detail at one such setting, where a complex office configuration has the machines well spread out in a structure designed by an individual for themselves. The layout also permits pairs of users to work collaboratively and clear cases of co-operative working are observed. In order to describe this successfully, we have extended the distributed cognition approach to capture notions of intent. This Projected Cognition, as we have termed it, allows us to provide a richer description of intent, activity and context.
Improving the usability of web 2.0 applications
Authors: Chris J. Pilgrim
Venue: Proceedings of the nineteenth ACM conference on Hypertext and hypermedia (2008)

Web 2.0 is revolutionizing the way that users access content and interact with each other on the Web. Unfortunately, many developers are inspired by what is technologically possible possibly disregarding good design practice and fundamental theory. Very little research on Web 2.0 usability is reported in the literature. This paper reports progress on an investigation into the usability of Web 2.0 applications through an empirical study of the level of disorientation and cognitive overhead that users might experience. The outcomes of this project aim to provide an empirical basis for the development of design guidelines to improve Web 2.0 usability.
AMIDA: a sequence diagram extraction toolkit supporting automatic phase detection
Authors: Takashi Ishio, Yui Watanabe, Katsuro Inoue
Venue: Companion of the 30th international conference on Software engineering (2008)

Amida is a toolkit to record an execution trace of a Java program and visualize the trace as a sequence diagram. Amida supports our novel approach to efficiently detecting phases; the algorithm precisely divides a long execution trace into a series of smaller diagrams corresponding to features (or tasks to achieve a feature) without deep knowledge on a target system.
Proceedings of the 1st international workshop on Software development governance
Venue: International Conference on Software Engineering (2008)

It is our great pleasure to welcome you to the inaugural workshop on Software Development Governance -- SDG2008. Participating in this workshop ensures dealing with one of the contemporary issues in software development organizations that is better aligning of the projects to the organization goals thus reducing risk and increase value. This year the workshop concerns with the definition and concepts of software development governance as well as with ways to implement it. Among others, the goal of the workshop is to establish a research community in this field and identify new directions for future research and development. The workshop program includes two keynote presentations, six research papers, and guided activities that aim at summarizing insights and set the ground for collaborative research in the coming years.
Enhanced correlation search technique for clustering cancer gene expression data
Authors: B. Sathiyabhama, N. P. Gopalan
Venue: Proceedings of the 6th WSEAS International Conference on Signal, Speech and Image Processing (2006)

The advent of DNA Microarray technologies has revolutionized the experimental studies of gene expressions. In the post-genomics era, clustering analysis has become a valuable tool for in-silico analysis of gene expression profiles. Although a number of clustering methods have been proposed, they are confronted with difficulties in meeting the requirements of high quality, large memory, performance and automation. In this paper, a novel-clustering algorithm namely Heuristic based Enhanced Correlation Search Technique (HECST) has been proposed. The distinct characteristic of HECST is that it integrates the validation techniques into the clustering process so that it produces high quality clusters dynamically. This algorithm is implemented using memory efficient data structure namely sparse matrices to store the gene expression profile. Sparse matrices tremendously reduce the size of the memory, hence provides computational efficiency. The performance of the algorithm is evaluated against number of reasonable benchmarks (e.g Direct application of raw data) for cancer gene expression data sets. The empirical results proved that this new algorithm automatically produces the optimal clusters in a much faster way than the traditional clustering methods like K-means, CAST and E-CAST. Analysis of data produced by HECST tenders potential insight into gene function, molecular biological processes and regulatory mechanisms.
A satellite view of internal waves induced by the Indian Ocean tsunami
Authors: D. A. Santek, A. Winguth
Venue: International Journal of Remote Sensing (2007)

At 08:45 local time (02:45 GMT) on 26 December 2004, 1 h and 45 min after the Sumatra Earthquakes of magnitude 9.3, a devastating tsunami struck the east coast of Sri Lanka. Nearly 2 h and 30 min after the wave hit the coast, a weather satellite passed over Sri Lanka's coastal zone providing a rare glimpse of internal waves along the continental slope due to this tsunami. The satellite imagery indicates wave-like features from the tsunami being reflected, diffracted, and scattered off the steep continental slope and submarine canyons adjacent to Sri Lanka. The energetic wave and its modification to internal waves possibly eroded sediment from the sea floor and transported it to the sea surface. Solitary features generated by internal waves can explain the observed pattern. Future modelling approaches considering these nonlinear interactions would be required for a better understanding of the tsunami behaviour in the coastal zone, where its destructive effects are most prominent.
Multi-objective inventory planning using MOPSO and TOPSIS
Authors: Ching-Shih Tsou
Venue: Expert Systems with Applications: An International Journal (2008)

One of the main characteristics of today's business tends to vary often. Under such environment, many decisions should be carefully pondered over from relevant aspects which are usually conflicting. Hence, inventory planning problems, which address how much and when to order what customers need at the least relevant cost while maintaining a desirable service level expected by customers, could be recast into a multi-objective optimization problem (MOOP). In a MOOP there are normally infinite numbers of optimal solutions in the Pareto front due to the conflicts among objectives. Unfortunately, most multi-objective inventory models have been solved by aggregation methods through a linear combination of specific weights or only one objective was optimized and the others were turned into constraints. Therefore, the challenges decision makers face are not only modeling the problem in a multi-objective context, but also the effort dedicated to build the Pareto front of MOOPs. This paper first employs the multi-objective particle swarm optimization (MOPSO) algorithm to generate the non-dominated solutions of a reorder point and order size system. A ranking method called technique for order preference by similarity to ideal solution (TOPSIS) is then used to sort the non-dominated solutions by the preference of decision makers. That is, a two-stage multi-criteria decision framework which consists of MOPSO and TOPSIS is presented to find out a compromise solution for decision makers. By varying the weights of various criteria, including minimization of the annual expected total relevant cost, minimization of the annual expected frequency of stock-out occasions, and minimization of the annual expected number of stock-outs, managers can determine the order size and safety stock simultaneously which fits their preference under different situations.
On-line Stochastic Matching compensation for non-stationary noise
Authors: V. Barreaud, I. Illina, D. Fohr
Venue: Computer Speech and Language (2008)

This paper treats the problem of noise compensation in speech recognition when training and testing conditions do not match. We are interested in two types of non-stationary noise that may be present during test, namely slowly varying and abruptly varying noises. The context of our work is the Stochastic Matching framework. The Stochastic Matching compensation method transforms test data using an affine compensation function whose parameters are computed off-line. Stochastic Matching approaches are interesting since they make little assumptions about the nature and the level of the noise but they are best suited for the compensation of stationary noise. In this paper we propose an original contribution to the Stochastic Matching framework. It is based on an on-line frame-synchronous version of Stochastic Matching method to compensate for slowly varying noise. Our contribution extends this compensation algorithm in order to compensate for abruptly varying noise. The basic idea of the proposed methods is to perform the compensation and the recognition steps at the same time. The environment changes are identified using monitoring algorithms. The performance of our proposed methods is evaluated on two speech databases, one recorded in moving cars (VODIS), and another one obtained by corrupting VODIS with abruptly varying noise from NOISEX. The proposed approaches significantly outperform classical compensation methods (Off-line Stochastic Matching, Sequential Mean Cepstrum Removal, Parallel Model Combination, Spectral Subtraction). For instance, we obtain up to 32.6% word error rate reduction over S-MCR on database corrupted by a 10dB abruptly varying white noise.
Directions for Peer-to-Peer based mobile pervasive augmented reality gaming
Authors: Chao Huang, Aaron Harwood, Shanika Karunasekera
Venue: Proceedings of the 13th International Conference on Parallel and Distributed Systems - Volume 02 (2007)

Pervasive Augmented Reality Gaming and Mobile P2P are both attracting significant focus and much progress has occurred recently. Augmented reality games extend reality with virtual elements to enhance game experience and mobile P2P networks provide autonomous, self-organizing, scalable and robust communication platforms. We review the technological challenges in both mobile P2P computing and AR domains by investigating some existing related works. Then we propose possible directions of the mobile AR collaborative gaming over p2p networks and show its advantages over other AR gaming and discuss the feasibility and future requirements regarding the support for this type of game.
A Factorization-Based Approach for Articulated Nonrigid Shape, Motion and Kinematic Chain Recovery From Video
Authors: Jingyu Yan, Marc Pollefeys
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2008)

Recovering articulated shape and motion, especially human body motion, from video is a challenging problem with a wide range of applications in medical study, sport analysis and animation, etc. Previous work on articulated motion recovery generally requires prior knowledge of the kinematic chain and usually does not concern the recovery of the articulated shape. The non-rigidity of some articulated part, e.g. human body motion with nonrigid facial motion, is completely ignored. We propose a factorization-based approach to recover the shape, motion and kinematic chain of an articulated object with nonrigid parts altogether directly from video sequences under a unified framework. The proposed approach is based on our modeling of the articulated non-rigid motion as a set of intersecting motion subspaces. A motion subspace is the linear subspace of the trajectories of an object. It can model a rigid or non-rigid motion. The intersection of two motion subspaces of linked parts models the motion of an articulated joint or axis. Our approach consists of algorithms for motion segmentation, kinematic chain building, and shape recovery. It handles outliers and can be automated. We test our approach through synthetic and real experiments and demonstrate how to recover articulated structure with non-rigid parts via a single-view camera without prior knowledge of its kinematic chain.
Nondissipative Marbling
Authors: Jiayi Xu, Xiaoyang Mao, Xiaogang Jin
Venue: IEEE Computer Graphics and Applications (2008)

A real-time marbling system for creating marbling textures interactively uses a modern GPU. The approach models the marbling texture design process as a 2D fluid-dynamics problem and forms textures as a result of the color advection in the 2D flow fields.
Autonomous geometric precision error estimation in low-level computer vision tasks
Authors: Andrés Corrada-Emmanuel, Howard Schultz
Venue: Proceedings of the 25th international conference on Machine learning (2008)

Errors in map-making tasks using computer vision are sparse. We demonstrate this by considering the construction of digital elevation models that employ stereo matching algorithms to triangulate real-world points. This sparsity, coupled with a geometric theory of errors recently developed by the authors, allows for autonomous agents to calculate their own precision independently of ground truth. We connect these developments with recent advances in the mathematics of sparse signal reconstruction or compressed sensing. The theory presented here extends the autonomy of 3-D model reconstructions discovered in the 1990s to their errors.
A comparative study on Peer-to-Peer failure rate estimation
Authors: Lei Ni, Aaron Harwood
Venue: Proceedings of the 13th International Conference on Parallel and Distributed Systems - Volume 02 (2007)

The robustness of Peer-to-Peer systems is challenged by its highly dynamic nature. Frequent peer failure and departure events introduce uncertainty for which is considered exceptional in traditional distributed systems. The difficulty of monitoring such large scale networks is further exacerbated because it has to be done in a completely decentralized way for both scalability and reliability concerns. Some methods for estimating peer failure rate have been applied in Peer-to-Peer systems, however their comparative performance has not yet been reported in the literature. We simulate three different failure rate estimation methods and compare their accuracy and response time with respect to sample size, stabilization interval and neighbour set size. We conclude that the Maximum Likelihood Method introduced is better than the Failure Frequency based Methods commonly used in current Peer-to-Peer systems.
SENHOD: scarce-resources wireless sensor network for healthcare in oil derricks
Authors: Pablo Pancardo, Juan C. Dueñas
Venue: Proceedings of the 2nd WSEAS International Conference on Computer Engineering and Applications (2008)

We present our experience with designing, developing, and deploying of a Scarce-resource Wireless Sensor Network (SWSN) for monitoring temperature and humidity high above oil derricks (drilling tower) in PEMEX (Parastatal Mexican Petroleum Company) drilling facilities. SENHOD system (scarce-resources wireless SEnsor Network for Healthcare in Oil Derricks) represents an information tool to reduce derrickmens' health risk due to high temperature and humidity exposure during a working day. For our deployment we meet the design requirements, in accordance to the scenario and its necessities. SENHOD has suitable operation characteristics configurable by users, such as: operation modes, physical parameter selection, sensing rate, and awake-sleep nodes.
Integrated Access Permission: Secure and Simple Policy Description by Integration of File Access Vector Permission
Authors: Takuto Yamaguchi, Yuichi Nakamura, Toshihiro Tabata
Venue: Proceedings of the 2008 International Conference on Information Security and Assurance (isa 2008) (2008)

In pervasive computing, embedded systems have a possibility to be attacked by crackers, including 0-day attack, as well as enterprise systems. In particular, in a case where a cracker gets a root privilege, damages are significant. To resolve this problem, Security-Enhanced Linux (SELinux) is useful. However, SELinux has a problem that is significant complexity for configuration because of too fine-grained access control. As a method for resolving this problem, SELinux Policy Editor (SEEdit) has been developed; this is a tool that simplifies the SELinux configuration. SEEdit uses the Simplified Policy Description Language (SPDL) as a policy description language. In the SPDL, we define new access permissions that integrate Access Vector Permissions (AVPs) employed in SELinux to provide access permissions in a security policy. Thus, we propose a set of access permissions named Integrated Access Permissions (IAPs), which enables the achievement of a good balance between reducing the workload of the configurations and guaranteeing security in SELinux. In addition, we evaluate our IAPs and show them almost secure.
Cellular automata: critical densities on forest fire dispersion
Authors: Siriporn Supratid, Ramakoti Sadananda
Venue: Proceedings of the 4th WSEAS International Conference on Applied Informatics and Communications (2004)

Cellular automata offer excellent modeling paradigms for the study of global behavior from local interactions. Instead of focusing on a physical model of forest fires, this paper considers possible models of artificial ones with the point of view of global parameters given local interactions rules. A set of possible rules for fire ignition, is assumed for the purpose of local interactions. These examine the empirical results and enquire if there are critical densities for various kinds of initial configurations and rules of interactions. It is found that there exists the association between λ 99, the parameter developed in this study, and the rules set. This leads to the certain relationship among an initial density of a dynamic state of a forest, a global phenomenon, and a local interactions.
Early detection of nutrient and biotic stress in Phaseolus vulgaris
Authors: L. Chaerle, D. Hagenbeek, X. Vanrobaeys, D. Van Der Straeten
Venue: International Journal of Remote Sensing (2007)

Prerequisites for optimal, high crop yield are disease-free growth and an equilibrated supply of nutrients. Early signatures of stress-altered physiology, before appearance of symptoms in the visible spectrum, allow timely treatment. Early detection of stress development was carried out on phaseolus vulgaris bean infected with the agriculturally important grey mould pathogen and under conditions of magnesium deficiency, limiting photosynthesis. During stress development, bean plants were monitored by time-lapse imaging with thermal, video and chlorophyll fluorescence cameras, mounted on a gantry robot system. For early detection of grey mould infection, chlorophyll fluorescence imaging proved to be the most sensitive. This technique detected magnesium deficiency at least three days before visual symptoms appeared. Further development of non-contact technology for plant health monitoring will help to achieve optimal productivity in greenhouse and field cultures. Associated establishment of a stress catalogue based on early symptoms will allow swift diagnosis.
DCA Using Suffix Arrays
Authors: Martin Fiala, Jan Holub
Venue: Proceedings of the Data Compression Conference (2008)

The paper deals with an implementation of Data Compression using Antidictionaries. Suffix array is used instead of suffix trie. A dynamic version is implemented as well.
The Group-Lasso for generalized linear models: uniqueness of solutions and efficient algorithms
Authors: Volker Roth, Bernd Fischer
Venue: Proceedings of the 25th international conference on Machine learning (2008)

The Group-Lasso method for finding important explanatory factors suffers from the potential non-uniqueness of solutions and also from high computational costs. We formulate conditions for the uniqueness of Group-Lasso solutions which lead to an easily implementable test procedure that allows us to identify all potentially active groups. These results are used to derive an efficient algorithm that can deal with input dimensions in the millions and can approximate the solution path efficiently. The derived methods are applied to large-scale learning problems where they exhibit excellent performance and where the testing procedure helps to avoid misinterpretations of the solutions.
Incorporating blogs, social bookmarks, and podcasts into unit teaching
Authors: Nauman Saeed, Yun Yang
Venue: Proceedings of the tenth conference on Australasian computing education - Volume 78 (2008)

The use of emerging e-learning technologies to build lifelong learning solutions is on the rise in academic settings. However there is a need to further explore these technologies in educational contexts and find novel ways of combining them in unit design. This paper presents our experience of incorporating a combination of blogs, social bookmarks, and podcasts in teaching a Web programming unit. An iterative action research methodology has been adopted to carry out the study. The study outcomes are encouraging in terms of usage and acceptance of incorporated technologies. They fulfil the basic objectives of the study and highlight the key areas of improvement for follow up studies.
Brief paper: Markovian jump delayed Hopfield networks with multiplicative noise
Authors: Adrian-Mihail Stoica, Isaac Yaesh
Venue: Automatica (Journal of IFAC) (2008)

A non-symmetric version of Hopfield networks subject to state-multiplicative noise, pure time delay and Markov jumps is considered. Such networks arise in the context of visuo-motor control loops and may, therefore, be used to mimic their complex behavior. In this paper, we adopt the Lur'e-Postnikov systems approach to analyze the stochastic stability and the L"2 gain of generalized Hopfield networks including these effects.
A novel early DBA mechanism with prediction-based fair excessive bandwidth allocation scheme in EPON
Authors: I-Shyan Hwang, Zen-Der Shyu, Liang-Yu Ke, Chun-Che Chang
Venue: Computer Communications (2008)

In this paper, we propose a novel Early dynamic bandwidth allocation (E-DBA) mechanism incorporated with a prediction-based fair excessive bandwidth allocation (PFEBA) scheme in Ethernet passive optical networks (EPONs). The E-DBA mechanism can reduce the idle period in the traditional DBA mechanism. On the other hand, the PFEBA scheme can provide more accurate prediction to ensure the fairness of each ONU and improve the overall system performance. The proposed model makes prediction for different traffic classes according to the variation in traffic for each ONU in the EPON. The PFEBA scheme includes the unstable degree list, predictions made using linear estimation credit and the fair excessive bandwidth allocation scheme. The simulation results show that the proposed E-DBA mechanism with PFEBA scheme can improve the system performance of well-known DBA algorithms in terms of wasted bandwidth, wasted bandwidth improved percentage, downlink data available bandwidth, throughput, average end-to-end delay and average queue length, especially under high traffic load.