ppxscal/embedding_network huggingface dataset:
Service Matching in Online Community for Mutual Assisted Living
Authors: Hong Sun, Vincenzo De Florio, Ning Gui, Chris Blondia
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

Elder people are becoming a predominant aspect of our societies. As such, solutions both efficacious and cost-effective need to be sought. Our previous study suggests that mutual assisted living community, where dwellers make contributions to the community. Thus community resources could be fully utilized and requested services would be provided in a prompt way. We used service oriented architecture (SOA) to orchestrate the available resources inside the community; and we organize the services into different forms such as formal ones (carried out by professionals, etc), informal ones (assisted by relatives, volunteers, .etc) and even as group activities. We expect such a community could help not only efficiently utilizing the social resources in maintaining the independent living of the elderly people, but also helping these people maintain their connections to the society and bring them entertainment, so that the quality of their living standard may be improved at the same time. This paper continues the track of the previous studies on building mutual assistance communities. Service matching algorithms are developed providing flexible choices on both requested services content and the organization forms of the services.
RACAI's Question Answering System at QA@CLEF2007
Authors: Dan Tufiş, Dan Ştefănescu, Radu Ion, Alexandru Ceauşu
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

We present a pattern-based question answering system for Romanian that participated in the Romanian monolingual task of the QA@CLEF 2007 track. We aim to prove that working with a good Boolean searching engine and using question type driven answer extraction heuristics and structural matching between the linkage representations of the question and candidate sentences, one can achieve acceptable results (30% overall accuracy).
Intrusion Detection Using Evolutionary Neural Networks
Authors: Emmanuel Michailidis, Sokratis K. Katsikas, Efstratios Georgopoulos
Venue: Proceedings of the 2008 Panhellenic Conference on Informatics (2008)

In this paper a network Intrusion Detection SystemUsing Evolutionary Neural Networks (ENN's) is proposed. Theanalysis engine of the IDS is modeled by the ENN and its abilityto predict attacks in a network environment is evaluated. TheENN is trained by a Particle Swarm Optimization (PSO)algorithm using labeled data from the KDD cup `99 competition.The results from the experiments are compared to the results bythe same competition and give positive results in the recognitionof DoS and Probe attacks
A Framework for Testing AIS Implementations
Authors: Tamás Horváth, Tibor Sulyán
Venue: Proceedings of the 19th IFIP TC6/WG6.1 international conference on Testing of Software and Communicating Systems: 7th International Workshop (2007)

Service availability has become one of the most crucial parameter of telecommunications infrastructure and other IT applications. Service Availability Forum (SAF) is a leading organization in publishing open specifications for Highly Available (HA) systems. Its Application Interface Specification (AIS) is a widely accepted standard for application developers. Conformance to the standard is one of the most important quality metrics of AIS implementations. However, implementers of the standard usually perform testing on proprietary test suites, which makes difficult to compare the quality of various AIS middleware. This paper presents a testing environment which can be used to perform both conformance and functional tests on AIS implementations. The results and experiences of testing a particular AIS middleware are also summarized. Finally we show how to integrate our testing environment to be part of a comprehensive TTCN-3 based AIS implementation testing framework.
Evaluating the trustworthiness of advice about seller agents in e-marketplaces: A personalized approach
Authors: Jie Zhang, Robin Cohen
Venue: Electronic Commerce Research and Applications (2008)

In this paper, we present a model for evaluating the trustworthiness of advice about seller agents in electronic marketplaces. In particular, we propose a novel personalized approach for effectively handling unfair ratings of sellers provided to buyer agents from other buyers (called advisors). Our approach offers flexibility for buyers to weight their value for private and public knowledge about advisors. A personalized approach is proposed as well for buyers to model the trustworthiness of sellers, based on the advice provided. Experimental results demonstrate that our approach can effectively model trustworthiness for both advisors and sellers, even when there are large numbers of unfair ratings.
An IA Based Approach for the Optimal Design of Traffic-Monitor Systems
Authors: Yi-Chih Hsieh, Yung-Cheng Lee, Ta-Cheng Chen
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

To improve the safety of drivers and walkers in a city, several traffic monitors are usually set on lanes. These traffic monitors can also improve the security of communities. In this paper, we integrate the so-called linear/circular consecutive-k-out-of-n:F systems into our proposed traffic-monitor system. The objective is to find the optimal design of monitors under limited budget for the system. The main purposes of this paper are : (1) to propose a new traffic-monitor system, (2) to present an immune algorithm (IA) for the optimal design of traffic monitors, and (3) to report numerical results of various parameters by the proposed algorithm. It is shown that the proposed immune algorithm performs well for all test problems.
Energy-Aware QoS Adjustment of Multimedia Tasks with Uncertain Execution Time
Authors: Wan Yeon Lee, Heejo Lee, Hyogon Kim
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

In order to make the best use of available energy budget, we propose a QoS adjustment method which maximizes the total QoS-provisioning of multimedia tasks with uncertain execution time. This method utilizes the probability distribution of task's execution time to determine an instant QoS level. Our experiments show that the proposed method gives 52% more QoS-provisioning than the conventional method using a constant QoS level derived from the worst-case time.
Perceptually Adaptive Rendering of Immersive Virtual Environments
Authors: Kimberly Weaver, Derrick Parkhurst
Venue: Proceedings of the 8th international symposium on Smart Graphics (2007)

When rendering immersive virtual environments, it is necessary to limit the geometric complexity of the scene in order to retain interactive frame rates. Both reduced frame rendering rates and reduced geometric complexity have been shown to have a negative impact on task performance. We present a perceptually adaptive rendering system which optimizes rendering performance in immersive virtual environments. Our system currently uses three discrete levels of detail for each model, which are created prior to run time. We use head position and orientation in the 3D environment to determine the appropriate geometric level of detail (LOD) of the objects in the scene. Based upon the thresholds used to trigger a change between two LODs, interactivity can be significantly improved without overtly distracting the user.
A Protocol for Making an Agreement in a Peer-to-Peer (P2P) Society
Authors: Ailixier Aikebaier, Tomoya Enokido, Makoto Takizawa
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (2008)

There are many discussions on agreement protocols of multiple peer processes where every peer just aims at agreeing on one value out of values shown by the peers. In human societies, agreement procedures are so flexible that persons can change their opinions and can use not only all-condition but also various types of agreement conditions in a meeting. In this paper, we discuss a flexible agreement protocol of multiple peer processes (peers) by taking account the human behaviour in social agreement procedures. Each peer first takes a value v1 and notifies the other peers of the value v1. A peer in turn receives values from other peers.Unless a set of the values from all the peers satisfy an agreement condition, the peer can take another value v2. In order to model the social human behaviour, we already discuss E- and P-precedent relations on values of a peer. The relations show that a peer can take a value v2 after taking v1 and prefers v1 to v2, respectively. If a peer autonomously takes values based on its precedent relations, the processes might not make an agreement even if there exist a satisfiable tuple of values. In order to efficiently make an agreement, peers are required to be coordinated. In this paper, we introduce methods for coordination of multiple peer processes, forward, backward, and null.
Condition Prediction of Hydroelectric Generating Unit Based on Immune Optimized RBFNN
Authors: Zhong Liu, Shuyun Zou, Shuangquan Liu, Fenghua Jin, Xuxiang Lu
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

Establishing the condition prediction model of characteristic parameters is one of the key parts in the implementation of condition based maintenance (CBM) of the hydroelectric generating unit (HGU). The performance of radial basis function neural network (RBFNN) in prediction mainly depends on the determination of the number and locations of data centers at the hidden layer. A novel approach inspired from the immune optimization principles is proposed in this paper and used to determine and optimize the structure at the hidden layer. The immune optimized RBFNN has been applied to the vibration condition prediction of the hydroturbine guiding bearing. The prediction results are compared with those by some other intelligent algorithms and the actual values, which shows the effectiveness and the preciseness of the proposed immune optimized RBFNN.
Exploring LDA-Based Document Model for Geographic Information Retrieval
Authors: Zhisheng Li, Chong Wang, Xing Xie, Xufa Wang, Wei-Ying Ma
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

Latent Dirichlet Allocation (LDA) model, a formal generative model, has been used to improve ad-hoc information retrieval recently. However, its feasibility and effectiveness for geographic information retrieval has not been explored. This paper proposes an LDA-based document model to improve geographic information retrieval by inheriting the LDA model with text retrieval model. The proposed model has been evaluated on GeoCLEF2007 collection. This is a part of the experiments of Columbus Project of Microsoft Research Asia (MSRA) in GeoCLEF2007 (a cross-language geographical retrieval track which is part of Cross Language Evaluation Forum). This is the second time we participate in this event. Since the queries in GeoCLEF2007 are similar to those in GeoCLEF2006, we leverage most of the methods that we used in GeoCLEF2006, including MSRAWhitelist, MSRAExpansion, MSRALocation and MSRAText approaches. The difference is that MSRAManual approach is not included this time, and we use MSRALDA instead. The results show that the application of LDA model in GeoCLEF monolingual English task performs stably but needs to be further explored.
A Polynomial-Time Checkable Sufficient Condition for Deadlock-Freedom of Component-Based Systems
Authors: Mila Majster-Cederbaum, Moritz Martens, Christoph Minnameier
Venue: Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science (2007)

Interaction systems are a formal model for component-based systems. Combining components via connectors to form more complex systems may give rise to deadlock situations. Deciding the existence of deadlocks is NP-hard as it involves global state analysis. We present here a parametrized polynomial-time algorithm that is able to confirm deadlock-freedom for a certain class of interaction systems. The discussion includes characteristic examples and displays the role of the parameter of the algorithm.
When loading working memory reduces distraction: Behavioral and electrophysiological evidence from an auditory-visual distraction paradigm
Authors: Iria SanMiguel, María-José Corral, Carles Escera
Venue: Journal of Cognitive Neuroscience (2008)

The sensitivity of involuntary attention to top-down modulation was tested using an auditory-visual distraction task and a working memory (WM) load manipulation in subjects performing a simple visual classification task while ignoring contingent auditory stimulation. The sounds were repetitive standard tones (80%) and environmental novel sounds (20%). Distraction caused by the novel sounds was compared across a 1-back WM condition and a no-memory control condition, both involving the comparison of two digits. Event-related brain potentials (ERPs) to the sounds were recorded, and the N1/MMN (mismatch negativity), novelty-P3, and RON components were identified in the novel minus standard difference waveforms. Distraction was reduced in the WM condition, both behaviorally and as indexed by an attenuation of the late phase of the novelty-P3. The transient/change detection mechanism indexed by MMN was not affected by the WM manipulation. Sustained, slow frontal and parietal waveforms related to WM processes were found on the standard ERPs. The present results indicate that distraction caused by irrelevant novel sounds is reduced when a WM component is involved in the task, and that this modulation by WM load takes place at a late stage of the orienting response, all in all confirming that involuntary attention is under the control of top-down mechanisms. Moreover, as these results contradict predictions of the load theory of selective attention and cognitive control, it is suggested that the WM load effects on distraction depend on the nature of the distractor-target relationships.
SensorMaker: A Wireless Sensor Network Simulator for Scalable and Fine-Grained Instrumentation
Authors: Sangho Yi, Hong Min, Yookun Cho, Jiman Hong
Venue: Proceeding sof the international conference on Computational Science and Its Applications, Part I (2008)

Nowadays, wireless sensor networks have drawn great attention as a new and important research area. These sensor networks typically consist of hundreds or even thousands of sensor nodes deployed in a geographical region to sense events. Therefore, using actual sensor networks in case of developing a new scheme or experimenting functionalities may consume too much time and cost. In this paper, we present a SensorMaker, which is a simulator for wireless sensor networks. It supports scalable and fine-grained instrumentation of the entire sensor networks. We also present the actual simulation results of the various existing routing and clustering algorithms, and network management schemes.
Key Issues in Expansion of Mobile Data Communications in China
Authors: Sunanda Sangwan, Chong Guan, Louis-Francois Pau
Venue: Proceedings of the 2008 7th International Conference on Mobile Business (2008)

China's mobile communications market presents unique market challenges. Market is experiencing a high subscriber growth rate and its implications for business and end-users and investigation into the current status of this market will improve our understanding on how adoption of mobile communications is evolving at the end-user level. In this paper we use a descriptive method to analyze key issues relating to market characteristics of mobile communications with an objective to better comprehend the dynamics of this largest mobile subscribers market. Using secondary data we identify mobile industry and end-user related trends to infer our conclusions for the industry. We find that mobile diffusion is extensive but adoption is polarized (rural and urban) and stratified (based on VAS usage). Usage patterns also reveal low ARPU and thus limited revenue streams for business. Growth of mobile communications is also dependent on growth of other sectors namely banking and logistics, and data services development.
Optimizing Feature Sets for Structured Data
Authors: Ulrich Rückert, Stefan Kramer
Venue: Proceedings of the 18th European conference on Machine Learning (2007)

Choosing a suitable feature representation for structured data is a non-trivial task due to the vast number of potential candidates. Ideally, one would like to pick a small, but informative set of structural features, each providing complementary information about the instances. We frame the search for a suitable feature set as a combinatorial optimization problem. For this purpose, we define a scoring function that favors features that are as dissimilar as possible to all other features. The score is used in a stochastic local search (SLS) procedure to maximize the diversity of a feature set. In experiments on small molecule data, we investigate the effectiveness of a forward selection approach with two different linear classification schemes.
A New Algorithm for Finding the Shortest Path Tree Using Competitive Pulse Coupled Neural Network
Authors: Dongming Zhou, Rencan Nie, Dongfeng Zhao
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

The competitive pulse coupled neural network (CPCNN) model is proposed based on the pulse coupled neural network (PCNN), the properties of pulse wave propagation of the CPCNN are analyzed for the solution of network shortest routing. The setting terms of the neuron parameters for the pulse wave propagation along the routing of the shortest path tree (SPT) of network routing graph are educed. The simulation results show that the proposed method is better than Dijkstra algorithm when the network routing graph holds many nodes. With the nodes number of the network increasing, the number of iterations of our algorithm will basically hold the line. The method shows better computational performance and dominance.
Elbows Higher! Performing, Observing and Correcting Exercises by a Virtual Trainer
Authors: Zsófia Ruttkay, Herwin Welbergen
Venue: Proceedings of the 8th international conference on Intelligent Virtual Agents (2008)

In the framework of our Reactive Virtual Trainer (RVT) project, we are developing an Intelligent Virtual Agent (IVA) capable to act similarly to a real trainer. Besides presenting the physical exercises to be performed, she keeps an eye on the user. She provides feedback whenever appropriate, to introduce and structure the exercises, to make sure that the exercises are performed correctly, and also to motivate the user. In this paper we talk about the corpora we collected, serving a basis to model repetitive exercises on high level. Then we discuss in detail how the actual performance of the user is compared to what he should be doing, what strategy is used to provide feedback, and how it is generated. We provide preliminary feedback from users and outline further work.
Relevant Timed Schedules / Clock Valuations for Constructing Time Petri Net Reachability Graphs
Authors: Hanifa Boucheneb, Kamel Barkaoui
Venue: Proceedings of the 6th international conference on Formal Modeling and Analysis of Timed Systems (2008)

We consider here time Petri nets (the TPN model) and two of its state space abstractions: the state class graph (SCG) and the zone based graph (ZBG). We show that only some time points of the clock/firing domains of abstract states are relevant to construct a TPN reachability graph. Moreover, for the state class graph method, the graph computed using relevant time points is smaller than the SCG.
A Topic-Specific Web Crawler with Concept Similarity Context Graph Based on FCA
Authors: Yuekui Yang, Yajun Du, Jingyu Sun, Yufeng Hai
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

With Internet growing exponentially, topic-specific web crawler is becoming more and more popular in the web data mining. How to order the unvisited URLs was studied deeply, we present the notion of concept similarity context graph, and propose a novel approach to topic-specific web crawler, which calculates the unvisited URLs' prediction score by concepts' similarity in Formal Concept Analysis (FCA), while improving the retrieval precision and recall ratio. We firstly build a concept lattice using the visited pages, extract the core concepts which reflect the user's query topic from the concept lattice, and then construct our concept similarity context graph based on the semantic similarities between the core concepts and other concepts.
An Interactive Graphical Environment for Code Optimization
Authors: Jie Tao, Thomas Dressler, Wolfgang Karl
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

Applications usually do not show a satisfied initial performance and require optimization. This kind of optimization often covers a complete process, starting with gathering performance data, followed by performance visualization and analysis, up to bottleneck finding and code modification. In this paper we introduce DECO (Development Environment for Code Optimization), an interactive graphical interface that enables the user to conduct this whole process within a single environment.
Image Level Fusion Method for Multimodal 2D + 3D Face Recognition
Authors: Gede Putra Kusuma, Chin-Seng Chua
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

Most of the existing multimodal 2D + 3D face recognition approaches do not account for the dependency between 2D and 3D representations of a face. This dependency reduces the benefit of fusion at the late-stage feature or metric level. On the other hand, it is advantageous to fuse at the early stage. We propose an image-level fusion method that explores the dependency between modalities for face recognition. Facial cues from 2D and 3D images are fused into more independent and discriminating data by finding fusion axes that pass through the most uncorrelated information in the images. Experimental results based on our face database of 1280 2D + 3D facial samples from 80 adults show that our image-level fusion approach outperforms the pixel- and metric-level fusion approaches.
A centralized arbitration scheme to avoid collisions of RFID readers
Authors: Won Sang Ryu, Si Young Ahn, Sung Woo Bae, Jung Kyu Yang, Yun Ho Kim, Hyoung Hwan Roh, Jun Hyung Kim, Jun Seok Park, Yeong Rak Seong, Ha Ryoung Oh
Venue: Proceedings of the WSEAS International Conference on Applied Computing Conference (2008)

Recently, the UHF-band RFID (Radio Frequency IDentification) technology that has been spotlighted. A RFID system is comprised of readers and tags. In the RFID environment that multiple readers exist, the mutual interference causes collision problems. This paper proposes the centralized arbitration scheme for avoiding the collision problems between multiple readers. By the centralized arbitration scheme, readers that want to communicate with tags are allotted to operate at different times. This paper presents the algorithm, modeling and simulation, of the centralized arbitration scheme.