ppxscal/embedding_network huggingface dataset:
Application of Genetic Algorithms to Conceptual Design of Injection Mould
Authors: Guoyan Yu
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 04 (2007)

A decision support system for the conceptual design of injection mould is described. The system employs a genetic algorithm (GA) to search for variable design options, and it incorporates a high level understanding about structural design and its constraints. The design process is currently focused on getting structure scheme of injection mould, which including type of cooling system, guiding framework, ejector style, core-pulling device, die carrier, layout of cavity, and so on. The property feature parameter of injection mould function is chosen as input parameters. The system uses GA more than a search engine rather than as an optimization tool. In addition, for improving the GA's searching performance, technology of cased based reasoning (CBR) is used to create initial population in the system.
Performance Trees: Expressiveness and Quantitative Semantics
Authors: Tamas Suto, Jeremy T. Bradley, William J. Knottenbelt
Venue: Proceedings of the Fourth International Conference on Quantitative Evaluation of Systems (2007)

Performance Trees are a recently-proposed mechanism for the specification of performance properties and measures. They represent an attractive alternative to stochastic logics, since they support traditional stochastic model checking queries, while also allowing for the direct extraction of a wide range of quantitative measures. In this paper we illustrate differences in expressiveness between Performance Trees and Continuous Stochastic Logic (CSL), and present quantitative semantics showing the mathematical basis underlying Performance Tree operators. As a running example, we demonstrate performance query specification with Performance Trees on a stochastic Petri net model of a healthcare system.
Combining Gradient-Based With Evolutionary Online Learning: An Introduction to Learning Classifier Systems
Authors: Martin V. Butz
Venue: Proceedings of the 7th International Conference on Hybrid Intelligent Systems (2007)

Learning Classifier Systems (LCSs), introduced by John H. Holland in the 1970s, are rule-based evolutionary online learning systems that combine gradient-based rule evaluation with evolutionary-based rule structuring techniques. Since the introduction of the accuracy-based XCS classifier system by Stewart W. Wilson in 1995, LCSs showed to be flexible, online learning methods that are applicable to datamining, reinforcement learning, and function approximation problems. Comparisons showed that performance is competitive with state-of-the art machine learning algorithms, but the learning algorithms applied are usually more flexible and highly adaptive. Moreover, problem knowledge can be extracted easily. This tutorial provides a gentle introduction to LCSs and their general functioning. It then gives further details on the XCS classifier system and highlights various successful applications. In conclusion, promising future directions of LCS research and applications are discussed.
From IC to I see: amusing interactive platform to improve kids' cognition process
Authors: Tao Ma, Rong Yong, Yue Meng
Venue: Proceedings of the 2007 conference on Designing pleasurable products and interfaces (2007)

Kids' observation is a psychological behavior. It takes long to change their cognitive habit and get used to new ones. Our project aims to build an amusing interactive platform with electronic technology, which is easy for kids to control and can quickly improve their cognition process.
Special Feature An Overview of Data Compression Techniques
Authors: H. K. Reghbati
Venue: Computer (1981)

Reducing redundancy in data representation leads to decreased data storage requirements and lower costs for data communication.
IT diffusion in developing countries
Authors: Eric Shih, Kenneth L. Kraemer, Jason Dedrick
Venue: Communications of the ACM (2008)

Policymakers need to recognize that developing economies have different drivers for IT investment than their wealthier brethren.
A comparison of PCA, ICA and GA selected features for cloud field classification
Authors: C. J. García-Orellana, M. Macías-Macías, A. Serrano-Pérez, H. M. González-Velasco, R. Gallardo-Caballero
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (2002)

In this work a back propagation neural network is used for the segmentation of Meteosat images covering the Iberian Peninsula. The images are segmented in the classes land (L), sea (S), fog (F), low clouds (C_L), middle clouds (C_M), high clouds (C_H) and clouds with vertical growth (C_V). The classification is performed from an initial set of several statistical features based on the gray level co-occurrence matrix (GLCM) proposed by Welch [1]. This initial set of features is made up of 144 parameters and to reduce its dimensionality three methods for feature selection have been studied and compared. The first one includes genetic algorithms (GA), the second is based on principal component analysis (PCA) and the third uses independent component analysis (ICA). These methods are conceptually very different. While GA interacts with the neural network in the selection process, PCA and ICA only depend on the values of the initial set of features.
Text document clustering based on frequent word meaning sequences
Authors: Yanjun Li, Soon M. Chung, John D. Holt
Venue: Data Knowledge Engineering (2008)

Most of existing text clustering algorithms use the vector space model, which treats documents as bags of words. Thus, word sequences in the documents are ignored, while the meaning of natural languages strongly depends on them. In this paper, we propose two new text clustering algorithms, named Clustering based on Frequent Word Sequences (CFWS) and Clustering based on Frequent Word Meaning Sequences (CFWMS). A word is the word form showing in the document, and a word meaning is the concept expressed by synonymous word forms. A word (meaning) sequence is frequent if it occurs in more than certain percentage of the documents in the text database. The frequent word (meaning) sequences can provide compact and valuable information about those text documents. For experiments, we used the Reuters-21578 text collection, CISI documents of the Classic data set [Classic data set, ftp://ftp.cs.cornell.edu/pub/smart/], and a corpus of the Text Retrieval Conference (TREC) [High Accuracy Retrieval from Documents (HARD) Track of Text Retrieval Conference, 2004]. Our experimental results show that CFWS and CFWMS have much better clustering accuracy than Bisecting k-means (BKM) [M. Steinbach, G. Karypis, V. Kumar, A Comparison of Document Clustering Techniques, KDD-2000 Workshop on Text Mining, 2000], a modified bisecting k-means using background knowledge (BBK) [A. Hotho, S. Staab, G. Stumme, Ontologies improve text document clustering, in: Proceedings of the 3rd IEEE International Conference on Data Mining, 2003, pp. 541-544] and Frequent Itemset-based Hierarchical Clustering (FIHC) [B.C.M. Fung, K. Wang, M. Ester, Hierarchical document clustering using frequent itemsets, in: Proceedings of SIAM International Conference on Data Mining, 2003] algorithms.
Validation of a remote monitoring system for the elderly: Application to mobility measurements
Authors: Marie Chan, Eric Campo, Evelyne Laval, Daniel Estève
Venue: Technology and Health Care (2002)

The aim of this paper is to introduce a smart tool for the assessment of the mobility of patient with motor disorders and to evaluate its performance through some initial experiments. These experiments are based on a system which is composed of sensors connected to a Personal Computer (PC) using data acquisition cards and a communication network. The PC includes a data acquisition and processing software. This system has been installed in a patient's housing (a bedroom and a washroom) in a long-stay setting. Pre-established travel and activity (going to bed, getting up, visiting the washroom&hellip;) patterns of patient in the housing including their duration have been defined by physicians for the experiments. A volunteer participated in the experiments and the results of his mobility obtained by the data processing software were compared with his real mobility. An agreement was found between the proposed assessment system and the experiments, thereby validating functioning of the whole system. Then, the system has been used to monitor a patient over a period of 39 nights. Again there is a good agreement between the characteristics derived from the system and the findings of the caring staff in charge of the patient's routine night monitoring. Data collected during 24 consecutive hours have been used to identify and characterise the patient's whole day mobility. This study paves the way for a new assessment system of the mobility of patient thus allowing the follow up of patients suffering from dementia and to study their significant mobility changes over time by introducing an indicator of mobility which can be used to assess their motor behavioural disorders.
Time Series Prediction Based on Support Vector Machines Experts and Genetic Algorithm
Authors: Weiwei Wang
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04 (2007)

A new time series prediction method based on support vector machines (SVMs) experts and genetic algorithm (GA) is proposed. The proposed method has a three-stage architecture. In the first stage, self-organizing feature map (SOM) is used as a clustering algorithm to partition the whole input space into several disjointed regions. Then, in the second stage, GA is adopted to determine the parameter combination of the SVMs expert corresponding to the partitioned region obtained above. In the last stage, the different SVMs experts in the different input-output spaces are constructed and used to predict time series. The simulation result shows that the multiple SVMs experts achieve significant improvement in the generalization performance in comparison with the single SVMs model. In addition, introducing GA to solve the parameter combination involved in SVMs expert avoids determining the parameters from experience. Key words: Support vector machines, Genetic algorithm, Mixture of experts, Self-organizing feature map
System Architecture for Distributed Data Management
Authors: R. Peebles
Venue: Computer (1978)

Successful implementation of most distributed processing systems hinges on solutions to the problems of data mangement, some of which arise directly from the nature of distributed architecture, while others carry over from centralized systems, acquiring new importance in their broadened environment. Numerous solutions have been proposed for the most important of these problems.
A Scheme of Parallel Processing for MIMD Systems
Authors: S. Jajodia
Venue: IEEE Transactions on Software Engineering (1983)

This paper presents a recognition procedure for parallel tasks in the user program written in a conventional programming language. To establish our program model, it describes the parallelism of the program in tenns of a process flow graph in which the relationships among processes are of predecessors and successors. And finally it presents a parallel processing scheme which realizes automatically the recognition of parallel tasks and schedules these tasks for parallel execution.
Algorithms ror Designing Fault-Detection Experiments ror Sequential Machines
Authors: D. E. Farmer
Venue: IEEE Transactions on Computers (1973)

In this paper we present algorithms for designing fault-detection experiments for sequential machines with special emphasis on the case in which the machine does not possess a distinguishing sequence. The length of an experiment is reduced through: 1) identifying each state with its own unique input/output set rather than using a common set for all states; 2) utilizing overlapping of the required input/output sequences so that a portion of the experiment serves more than one purpose; and 3) verifying the reference condition in which the machine is placed at many points in the experiment by as short a locating sequence as possible. Important distinctions are made between locating sequences of the type introduced in previous work and those defined and used here.
Interactive Pattern Recognition: A System and Data Structure
Authors: R. F. H. Farag
Venue: IEEE Transactions on Software Engineering (1977)

In this paper a general-purpose interactive pattern recognition system is built using limited resources. The system utilizes Ribak's [5] relationship matrix (R-matrix) as a data structure and a PDP-9 minicomputer as hardware. The software developed for the interactive system along with the implemented idea of "vague" relations gives the human operator flexibility and aid in interactive file creation. Files created to describe complex patterns can be formed by merging simpler subfiles of different portions of that pattem. In addition to merging files (union operation), common elements between files can be detected using an intersection operation. User-defined routines are readily interfaced to the interactive system, thus increasing the system flexibility and giving the human operator a tailor-made effect.
Towards a taxonomy for information security metrics
Authors: Reijo M. Savola
Venue: Proceedings of the 2007 ACM workshop on Quality of protection (2007)

Systematic approaches to measuring security are needed in order to obtain evidence of the security performance of products or an organization. In this study we survey the emerging security metrics approaches from the academic, governmental and industrial perspectives and aim to bridge the gap between information security management and Information and Communication Technology (ICT) product security practices. If common metrics approaches between different security disciplines can be found, this will advance our holistic understanding and capabilities, both in management and engineering practices.
Streaming technology as an enabler of top quality web-based education
Authors: Alexander Uskov, Vladimir Uskov
Venue: Proceedings of the sixth conference on IASTED International Conference Web-Based Education - Volume 2 (2007)

Various types of recent research projects and surveys confirm a tremendous growth of streaming multimedia technology utilization worldwide due to its great potential for the top quality Web-based education (WBE) and Web-based training (WBT). Broadband Internet with 150 - 1,000 Kbps bandwidth serves as an ideal channel to deliver rich multimedia learning content using streaming technology. This paper describes the results of 5-year long design, development, and pilot utilization of the InterLabs Web-lecturing system (InterLabs). The results, outcomes and findings of this research, design and development project clearly show that streaming technology will be in great demand in Web-based education in upcoming 5 years.
On scene interpretation with description logics
Authors: Bernd Neumann, Ralf Möller
Venue: Image and Vision Computing (2008)

We examine the possible use of description logics (DLs) as a knowledge representation and reasoning system for high-level scene interpretation. It is shown that so-called aggregates composed of multiple parts and constrained primarily by temporal and spatial relations can be used to represent high-level concepts such as object configurations, occurrences, events, and episodes that are required in an application context. Scene interpretation is modelled as a stepwise process which exploits the taxonomical and compositional relations between aggregate concepts while incorporating visual evidence and contextual information. It is shown that aggregates can be represented by concept expressions of a description logic which provides a concrete-domain extension for quantitative temporal and spatial constraints. The analysis reveals that different kinds of representation constructs have to be carefully selected in order to provide for the required expressivity while retaining decidability in general as well as practical support from description logic system implementations in particular. Reasoning services of the DL system can be used as building blocks for the interpretation process, but additional information is required to generate preferred interpretations. A probabilistic model is sketched which can be integrated with the knowledge-based framework.
Fuzzy Boolean Networks Learning Behaviour
Authors: Jose Alberto Tome, Joao Paulo Carvalho
Venue: Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications (2007)

In this paper one studies the Learning behaviour of an entire Rule Base in Fuzzy Boolean Networks. It is analyzed the influence of a set of factors such as number of inputs per neuron, granularity of antecedent spaces and number of teaching experiments on learning effectiveness without cross influence between rules and on interpolation capabilities of the network. Both one dimensional problems and two dimensional problems are tested and results interpreted using theoretical results also presented.
Evolution of optical core networks
Authors: D. Johnson, T. Gilfedder
Venue: BT Technology Journal (2007)

Optical networks have developed rapidly over the last ten years and show every sign of continuing to grow and adapt to the new challenges of supporting more traffic, more reliably and flexibly, at lower cost. We briefly review the developments of the last ten years and then discuss current thinking on how core optical networks will develop into the future, exploring the similarities and differences with the previous generation of technologies. We have attempted to provide a `low-jargon' paper with links to more detailed studies where appropriate.
Enterprise Architecture: A Framework Supporting System Quality Analysis
Authors: Per Narman, Pontus Johnson, Lars Nordstrom
Venue: Proceedings of the 11th IEEE International Enterprise Distributed Object Computing Conference (2007)

Enterprise Architecture is a model-based approach to business-oriented IT management. To promote good IT decision making, an enterprise architecture framework needs to explicate what kind of analyses it supports. Since creating enterprise architecture models is expensive and without intrinsic value, it is desirable to only create enterprise architecture models based on metamodels that support well-defined analyses. This paper suggests a metamodel derived specifically with a set of theory-based system quality analyses in mind. The ISO 9126-based theory behind the system quality analysis is introduced in the shape of an extended influence diagram. Finally, an example illustrates that our theory-based metamodel does support system quality analysis.
XML Auto-Transformation System for Ubiquitous Port using RFID Technology
Authors: Jaehong Ahn, Kyeongrim Ahn, Kyoungrog Yi, Jinwook Chung
Venue: Proceedings of the 5th ACIS International Conference on Software Engineering Research, Management & Applications (2007)

Ubiquitous business means to improve the business service and to create new business model under the environment which computing object is applied to real life and we can freely connect to network. As the related technology develops, the need of u-Business is rising in e-Business. Business formalities which are electronically processed through EDI or bar code, such as stock management, terminal gate management, container management, changes to the formalities using RFID. These formalities receive the sent input data through RDIF chip and antenna from RFID middleware, and transfer that data to server. In this paper, we propose the XML agent that transfers the input data to server and transfers the sent data from server to RFID middleware. The basic data form used at the proposed system is XML and the proposed system supports the converting functionality. The Converting functionality is to translate the received text to XML or XML to text. To provide the converting functionality, it is possible to migrate with various RFID antennas and middleware regardless of vendor. It also is able to migrate with the various information models as providing interface with server.
Sensing danger: Innate immunology for intrusion detection
Authors: Uwe Aickelin, Julie Greensmith
Venue: Information Security Tech. Report (2007)

The immune system provides an ideal metaphor for anomaly detection in general and computer securities in particular. Based on this idea, artificial immune systems have been used for a number of years for intrusion detection, unfortunately so far with little success. However, these previous systems were largely based on immunological theory from the 1970s and 1980s and over the last decade our understanding of immunological processes has vastly improved. In this paper we present two new immune-inspired algorithms based on the latest immunological discoveries, such as the behaviour of Dendritic Cells. The resultant algorithms are applied to real-world intrusion problems and show encouraging results. Overall, we believe that there is a bright future for these next-generation artificial immune algorithms.
Very efficient mining of distance-based outliers
Authors: Fabrizio Angiulli, Fabio Fassetti
Venue: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management (2007)

In this work a novel algorithm, named DOLPHIN, for detecting distance-based outliers is presented. The proposed algorithm performs only two sequential scans of the dataset. It needs to store into main memory a portion of the dataset, to efficiently search for neighbors and early prune inliers. The strategy pursued by the algorithm allows to keep this portion very small. Both theoretical justification and empirical evidence that the size of the stored data amounts only to a few percent of the dataset are provided. Another important feature of DOLPHIN is that the memory-resident data are indexed by using a suitable proximity search approach. This allows to search for nearest neighbors looking only at a small subset of the main memory stored data. Temporal and spatial cost analysis show that the novel algorithm achieves both near linear CPU and I/O cost. DOLPHIN has been compared with state of the art methods, showing that it outperforms existing ones.
A Component Based Interoperability Solution over Existing Grid Middleware
Authors: Weiyuan Huang, Yongwei Wu, Jia Liu, Guangwen Yang, Weimin Zheng
Venue: Proceedings of the Sixth International Conference on Grid and Cooperative Computing (2007)

The purpose of grid technology is to integrate various heterogeneous resources together to provide huge computation and storage capacity for users transparently. However, current grids have only created large information islands - Grids based on different middleware cannot interoperate with each other. Although many efforts have been made to address the problem of interoperability, existing solutions only focused on making several specific Grid middleware interact with each other. This paper proposed a universal solution based on Grid Component Model (GCM) make interoperability of all existing middleware and even for new coming ones. Experiments based on a bioinformatics grid have been made, and the result shows that our implementation is practical for simple programs and can gain performance improvement for complicated ones too.