ppxscal/embedding_network huggingface dataset:
Implementation of G.729 Codec Based on Mediastreamer Technology
Authors: Liting Hu, Xiangping Kong, Lianfen Huang, Hezhi Lin, Jianan Lin, Yan Yao, Xueyuan Jiang
Venue: Proceedings of the 2009 IEEE International Conference on Networking, Architecture, and Storage (2009)

Currently, the mediastreamer2 contains internal support for G.711u, G.711a, speex and gsm. However, it does not contain internal support for the popular G.729, which is known as the best audio codec ever. In this paper, we present the method of how to implement a G.729 codec filter on mediastreamer2. Then, we evaluate the performance of the G.729 filter in our platform. The experimental results show that our implementation of G.729 codec on mediastreamer2 is successful on the whole.
G-BLAST: BLAST Manager in an Heterogeneous Distributed Environment
Authors: Dong-Wook Kim, Tae-Sung Jung, Dae-Won Kim, Seong-Hyeuk Nam, Hyuk-Ryul Kwon, Sang-Haeng Choi, Hyung-Dae Koh, Han-Suk Choi, Hong-Seog Park
Venue: Proceedings of the 2009 Third IEEE International Symposium on Theoretical Aspects of Software Engineering (2009)

G-BLAST is an integrated software package for BLAST searches can be operating in heterogeneous distributed environment. G-BLAST means Grid-BLAST. G-BLAST provides two operating methods like NFS (Network File System) based and SDT (Socket Data Transfer) based in inter-connected network. SDT based method is simple to installation/operating because it provides more platform independence than NFS based method. To improve the performance of BLAST searches using exists computing resources, G-BLAST employed ‘database splicing’ and ‘query splicing’ methods. By default, G-BLAST querying into each client node for one query with one spliced database. But, if there are extra clients G-BLAST splice the query into sub-queries as extra client’s number. Each client should contain over one spliced database to join G-BLAST. The scheduler monitor the status and the databases of each client node, the query is executing in parallel with not working client nodes. BLAST results are stored into Java Beans data model using XML technique in the server node. By user request, the result can be exported in BLAST’s default output, XML format and tabular format. Also, BLAST results can be stored into database as given schema.
Rules Extraction from ANN Based on Clustering
Authors: Jie Ma, Dongwei Guo, Miao Liu, Yu Ma, Sha Chen
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

We propose a novel algorithm based on clustering to extract rules from artificial neural networks. After networks Beijing trained and pruned successfully, inner-rules are generated by discrete activation values of hidden units. Then, weights between input and hidden units are clustered to decrease the complexity of rules extraction. In clustering phase, the clustered number of weights can be adjusted dynamically according to activation values of their corresponding hidden units. The experimental results demonstrate that this algorithm is effective.
A Mechanism to Avoid Collusion Attacks Based on Code Passing in Mobile Agent Systems
Authors: Marc Jaimez, Oscar Esparza, Jose L. Muñoz, Juan J. Alins-Delgado, Jorge Mata-Díaz
Venue: Proceedings of the 3rd IFIP WG 11.2 International Workshop on Information Security Theory and Practice. Smart Devices, Pervasive Systems, and Ubiquitous Networks (2009)

Mobile agents are software entities consisting of code, data, state and itinerary that can migrate autonomously from host to host executing their code. Despite its benefits, security issues strongly restrict the use of code mobility. The protection of mobile agents against the attacks of malicious hosts is considered the most difficult security problem to solve in mobile agent systems. In particular, collusion attacks have been barely studied in the literature. This paper presents a mechanism that avoids collusion attacks based on code passing. Our proposal is based on a Multi-Code agent, which contains a different variant of the code for each host. A Trusted Third Party is responsible for providing the information to extract its own variant to the hosts, and for taking trusted timestamps that will be used to verify time coherence.
Complex Mobile Multiagent Systems
Authors: Barna László Iantovics, Bogdan Crainicu
Venue: Proceedings of the 2008 First International Conference on Complexity and Intelligence of the Artificial and Natural Complex Systems. Medical Applications of the Complex Systems. Biomedical Computing (2008)

Mobile agents as network computing technology has been applied to solve various parallel and distributed computing problems, including parallel processing, information search and network management. Protection of the mobile agents in the network and against the hosts is a difficult task. In this paper, we analyze the increased security solutions provided by a novel class of mobile agents called ICMA agents developed during our previous researches. An ICMA multiagent system is a complex system, composed from relatively simple agents who at the level of the system has a complex behavior. ICMA mobile agents have some advantages in the protection versus other mobile agents described in the literature. The self-protection mechanisms consist in distributing the problem solving knowledge, reducing the useless distributed problem solving knowledge in time and intelligent controlling of the distributed operating components. In this paper there are introduced the notions internal and external complexity of an agent-based complex system.
A Novel Promoter Prediction Method Inspiring by Biological Immune Principles
Authors: Ya-Jing Zhang
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01 (2009)

We present an immune recognition algorithm for improving the performance of promoter regions prediction in this paper. We focus on generation of immune detectors by using negative selection operator and clone selection operator. Subsequently, the detectors are evolved. The results of testing on large genomic sequences by comparisons show that our algorithm is efficient with higher sensitivity and specificity in predicting promoter regions.
Empirical Findings on Critical Infrastructure Dependencies in Europe
Authors: Eric Luiijf, Albert Nieuwenhuijs, Marieke Klaver, Michel Eeten, Edite Cruz
Venue: Critical Information Infrastructure Security: Third International Workshop, CRITIS 2008, Rome, Italy, October13-15, 2008. Revised Papers (2009)

One type of threat consistently identified as a key challenge for Critical Infrastructure Protection (CIP) is that of cascading effects caused by dependencies and interdependencies across different critical infrastructures (CI) and their services. This paper draws on a hitherto untapped data source on infrastructure dependencies: a daily maintained database containing over 2375 serious incidents in different CI all over the world as reported by news media. In this paper we analyse this data to discover patterns in CI failures in Europe like cascades, dependencies, and interdependencies. Some analysis results indicate that less sectors than many dependency models suggest drive cascading outages and that cascading effects due to interdependencies are hardly reported.
Anchoring Design in Rural Customs of Doing and Saying
Authors: Nicola J. Bidwell
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I (2009)

An increasing range of initiatives aim to enable rural communities in developing regions to generate their own, non-text based, digital content to share local stories, information and concerns. Video, photos and audio offer new resources for practices that give communities' a sense of identity and continuity and that members acquire in relationships with each other, their environment and history via speech, gesture, song, music, drama, ritual, skills or crafts. However, these contexts pose challenges for designing interactions within frameworks that have a heritage of text and indirect orality and which emphasize particular communication dynamics and structures. We seek to create new design directions based on insights into local ways of `doing and saying' gained in interactions with people living under traditional law and custom in the Xhosa Kingdom of Pondoland, South Africa. This paper distils themes from an ethnography when the author lived according to local norms and constraints and cogenerated design activities, situated in the community's priorities, customary power relations and consensus-based practice. We reflect on communication in ordinary and extraordinary activities, and sociotechnical `experiments' from using social networking websites to storytelling with blogs. We describe how indexicality dynamically shares context and entwines a person's identity with physical setting; and, how practices, such as prolonged discussion, diachronic repetition and synchronous utterance, build rapport, collective memory and cohesion. We propose that these practices inspire ways that local social structures can impact on activities to design systems of organization for information sharing, with occasional reference to our observations of other rural peoples in north Mozambique and north Australia.
Developmental Computing
Authors: Przemyslaw Prusinkiewicz
Venue: Proceedings of the 8th International Conference on Unconventional Computation (2009)

Since their inception over forty years ago, L-systems have proven to be a useful conceptual and programming framework for modeling the development of plants at different levels of abstraction and different spatial scales. Formally, L-systems offer a means of defining cell complexes with changing topology and geometry. Associated with these complexes are self-configuring systems of equations that represent functional aspects of the models. The close coupling of topology, geometry and computation constitutes a computing paradigm inspired by nature, termed developmental computing. We analyze distinctive features of this paradigm within and outside the realm of biological models.
Ensemble forecasting for disease outbreak detection
Authors: Thomas H. Lotze, Galit Shmueli
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

We describe a method to improve detection of disease outbreaks in pre-diagnostic time series data. The method uses multiple forecasters and learns the linear combination to minimize the expected squared error of the next day's forecast. This combination adaptively changes over time. This adaptive ensemble combination is used to generate a disease alert score for each day, using a separate multiday combination method learned from examples of different disease outbreak patterns. These scores are used to generate an alert for the epidemiologist practitioner. Several variants are also proposed and compared. Results from the International Society for Disease Surveillance (ISDS) technical contest are given, evaluating this method on three syndromic series with representative outbreaks.
Integration of Heterogeneous Geospatial Data Based on Middleware Technology
Authors: Yun Ling, Fangfei Zhou, Xun Wang, Bailin Yang
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 02 (2009)

The diversity of the geospatial data format has led to the difficulties in data sharing. In this paper, three popular modes for integrating heterogeneous spatial data are analyzed. Aiming at their weak extensibility, a method of exchanging data format based on middleware technology is proposed. What’s more, this method can be extended freely. By establishing an internal format and using the independent interface designed in this paper, we can realize the exchange among different formats. Through this method, we can resolve the data-sharing problem cross several typical GIS platforms, and make the integration of heterogeneous data freely and conveniently.
A Novel JRRM Approach Working Together with DSA in the Heterogeneous Networks
Authors: Ding Zhe, Xu Yubin, Sha Xuejun, Cui Yang
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

Joint Radio Resource Management (JRRM) and Dynamic Spectrum Allocation (DSA) are both promising approaches in the heterogeneous networks to increase overall QoS and spectrum efficiency, which have already been taken into the framework of heterogeneous radio access networks of E2R. However, not much research has been done about how they could work together properly. In our opinion, JRRM should act according to the spectrum arrangement and planning of DSA among different RATs. This paper gives the load situation a new expression, through which JRRM would be informed of not only the load respected with the RAT considered but also the DSA’s planning about the spectrum and traffic distribution among RATs. JRRM could act in accordance with DSA. Simulative comparison demonstrates that the JRRM proposed in this paper performs better than the original JRRM when working together with DSA in heterogeneous scenarios.
Research on Information Technology Adoption of Agricultural Enterprises in China
Authors: Zheng Xiaoping, Wu Chunxia, Zhang Xiaoshuan
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

Agriculture constantly experiences advances in information technology. The paper discusses the adoption of information technolgy among agricultural enterprises, especially small-medium sized firms. The survey result shows that information technology has not widely used in Chinese agricultural enterprises, and the utilization level is low. Most of firms have adopted it in daily management, few of them in E-Commerce. Many agricultural enterprises have not been satisfied with the return of informatization investment. Lack of funds, professionals and misunderstanding are the main factors prohibiting the use of information technology. the Chinese agricultural enterprises should catch the key point to adopt information technology.
Varying the Office Work Posture between Standing, Half-Standing and Sitting Results in Less Discomfort
Authors: Peter Vink, Ineke Konijn, Ben Jongejan, Monique Berger
Venue: Proceedings of the International Conference on Ergonomics and Health Aspects of Work with Computers: Held as Part of HCI International 2009 (2009)

In this study 10 subjects worked two weeks in their rather new normal work station and two weeks in another work station. These VDU workers were trained and received a table making standing work possible. They also received a chair making half sitting possible. The effects on experienced variation in posture and discomfort were studied. It appeared that most of the time people work in the normal sitting situation (69% in the new and 90% in the old work station). Sometimes the half sitting and standing posture was used in the new situation. This new situation had a significant lower discomfort in the back, neck and shoulder region compared with the old situation.
A Process Based Unification of Process-Oriented Software Quality Approaches
Authors: Zádor Dániel Kelemen
Venue: Proceedings of the 2009 Fourth IEEE International Conference on Global Software Engineering (2009)

This paper describes the main steps of a research for defining a method for process based unification of multiple process-oriented software quality approaches.
Data Mining Techniques for the Identification of Genes with Expression Levels Related to Breast Cancer Prognosis
Authors: Gabriele Giarratana, Marco Pizzera, Marco Masseroli, Enzo Medico, Pier Luca Lanzi
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering (2009)

Providing clinical predictions for cancer patients by analyzing their genetic make-up is a difficult and very important issue. With the goal of identifying genes more correlated with the prognosis of breast cancer, we used data mining techniques to study the gene expression values of breast cancer patients with known clinical outcome. Focus of our work was the creation of a classification model to be used in the clinical practice to support therapy prescription. We randomly subdivided a gene expression dataset of 311 samples into a training set to learn the model and a test set to validate the model and assess its performance. We evaluated several learning algorithms in their not weighted and weighted form, which we defined to take into account the different clinical importance of false positive and false negative classifications. Based on our results, these last, especially when used in their combined form, appear to provide better results.
LAOVM: Lightweight Application-Oriented Virtual Machine for Thread Migration
Authors: Xiaofei Liao, Yifan Yue, Hai Jin, Haikun Liu
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

This paper describes the scheme of thread migration in a language virtual machine LAOVM – Lightweight Application-Oriented Virtual Machine. To maintain high portability and flexibility, thread migration is implemented at language level. To migrate process or thread in runtime in LAOVM, the following issues are addressed: (1) supporting kinds of applications implemented by different programming language; (2) enabling transparent process migration indifferent operating system; (3) implementing fine-grained mobility. Experimental results show that the downtime of thread migration is reasonably small, even the application runtime image is required for occupying massive memory blocks.
Category competition drives contrast maintenance within an exemplar-based production/perception loop
Authors: Andrew Wedel
Venue: Proceedings of the 7th Meeting of the ACL Special Interest Group in Computational Phonology: Current Themes in Computational Phonology and Morphology (2004)

The evolution of competing lexical categories is simulated within a model in which lexical outputs are organized as sequences of articulatory gestures. When exemplar-based categories compete for assignment and storage of incoming exemplars in a production/storage loop, contrast between categories spontaneously emerges and remains stable, driven by the differences in storage consistency between more contrastive and less contrastive variants. Further, when lexical outputs are biased toward use of previously produced gestures, the set of exemplars in the lexicon evolve to be derived from a small set of contrastive units used in combination, despite the absence of direct selection for contrast at the sub-lexical level.
Critical Paths in the Partial Order Unfolding of a Stochastic Petri Net
Authors: Anne Bouillard, Stefan Haar, Sidney Rosario
Venue: Proceedings of the 7th International Conference on Formal Modeling and Analysis of Timed Systems (2009)

In concurrent real-time processes, the speed of individual components has a double impact: on the one hand, the overall latency of a compound process is affected by the latency of its components. But, if the composition has race conditions, the very outcome of the process will also depend on the latency of component processes. Using stochastic Petri nets, we investigate the probability of a transition occurrence being critical for the entire process, i.e. such that a small increase or decrease of the duration of the occurrence entails an increase or decrease of the total duration of the process. The first stage of the analysis focuses on occurrence nets, as obtained by partial order unfoldings, to determine criticality of events; we then lift to workflow nets to investigate criticality of transitions inside a workflow.
A Potential-Based Node Selection Strategy for Influence Maximization in a Social Network
Authors: Yitong Wang, Xiaojun Feng
Venue: Proceedings of the 5th International Conference on Advanced Data Mining and Applications (2009)

Social network often serves as a medium for the diffusion of ideas or innovations. The problem of influence maximization which was posed by Domingos and Richardson is stated as: if we can try to convince a subset of individuals to adopt a new product and the goal is to trigger a large cascade of further adoptions, which set of individuals should we target in order to achieve a maximized influence? In this work, we proposed a potential-based node selection strategy to solve this problem. Our work is based on the observation that local most-influential node-selection adopted in many works, which is very costly, does not always lead to better result. In particular, we investigate on how to set two parameters(¿ v and b uv ) appropriately. We conduct thorough experiments to evaluate effectiveness and efficiency of the proposed algorithm. Experimental results demonstrate that our approximation algorithm significantly outperforms local-optimal greedy strategy.
Region Analysis for Race Detection
Authors: Helmut Seidl, Vesal Vojdani
Venue: Proceedings of the 16th International Symposium on Static Analysis (2009)

Automatic race detection of C programs requires fast, yet sufficiently precise analysis of dynamic memory. Therefore, we present a region-based pointer analysis which seeks to identify disjoint regions of dynamically allocated objects to ensure that write accesses to the same region are always protected by the same mutexes. Our approach has been implemented within the interprocedural analyzer of concurrent C programs GobLint and we have successfully applied it on code from the Linux kernel, such as the access vector cache. This code relies on a synchronized hash table where an array of doubly linked lists is protected by an array of locks.
Towards the Automatic Classification of Reading Disorders in Continuous Text Passages
Authors: Andreas Maier, Tobias Bocklet, Florian Hönig, Stefanie Horndasch, Elmar Nöth
Venue: Proceedings of the 12th International Conference on Text, Speech and Dialogue (2009)

In this paper, we present an automatic classification approach to identify reading disorders in children. This identification is based on a standardized test. In the original setup the test is performed by a human supervisor who measures the reading duration and notes down all reading errors of the child at the same time. In this manner we recorded tests of 38 children who were suspected to have reading disorders. The data was confronted to an automatic system which employs speech recognition and prosodic analysis to identify the reading errors. In a subsequent classification experiment -- based on the speech recognizer's output, the duration of the test, and prosodic features -- 94.7 % of the children could be classified correctly.
Minimum Free Energy Principle for Constraint-Based Learning Bayesian Networks
Authors: Takashi Isozaki, Maomi Ueno
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I (2009)

Constraint-based search methods, which are a major approach to learning Bayesian networks, are expected to be effective in causal discovery tasks. However, such methods often suffer from impracticality of classical hypothesis testing for conditional independence when the sample size is insufficiently large. We propose a new conditional independence (CI) testing method that is effective for small samples. Our method uses the minimum free energy principle, which originates from thermodynamics, with the "Data Temperature" assumption recently proposed for relating probabilistic fluctuation to virtual thermal fluctuation. We define free energy using Kullback---Leibler divergence in a manner corresponding to an information-geometric perspective. This CI method incorporates the maximum entropy principle and converges to classical hypothesis tests in asymptotic regions. We provide a simulation study, the results of which show that our method improves the learning performance of the well known PC algorithm in some respects.