ppxscal/embedding_network huggingface dataset:
Child watching support system with dynamic routing of motion pictures
Authors: Airi Kaneko, Shigeo Kaneda
Venue: Proceedings of the sixth conference on IASTED International Conference Web-Based Education - Volume 2 (2007)

We investigate a ubiquitous home network service that most resembles our everyday life. When looking at childcare support systems as important ubiquitous applications, proposals do research and development on nursery school. However, proposals rarely do considering inside homes. Therefore, we propose a child-care support system inside homes called DROP-CWS with peer-to-peer networks that don't use servers. We use a communication platform called "Jupiter" in which peer-to-peer protocols are incorporated. DROP-CWS observes a child playing inside the home by surveillance camera, allowing care providers to monitor from another room. Furthermore, care providers can select a camera for observation because we use multicast communication within a group that consists of one camera and two televisions. We did operation experiments in an environment with two rooms and used commercial cameras and televisions. Even though results showed successful delivery of motion pictures, the picture was projected on a television screen by a frame-by-frame advance. As future work, we will continue research and development of this system.
Neighborhood Limited Empirical Mode Decomposition and Application in Image Processing
Authors: Guanlei Xu, Xiaotong Wang, Xiaogang Xu
Venue: Proceedings of the Fourth International Conference on Image and Graphics (2007)

A novel decomposition approach called Neighborhood Limited Empirical Mode Decomposition (NLEMD) is presented. Unlike other EMD approaches, only local neighborhood data are used to estimate the local mean value in NLEMD. It is surprising that NLEMD has inherited all advantages from EMD proposed by Huang. Meanwhile, some inherent bugs in EMD have been avoided. In NLEMD, the signal can be decomposed into several basic components, while the minimum frequency existing in Intrinsic Mode Functions (IMFs) can be controlled in each decomposition step. The experiments show that NLEMD works well for the 1D signal and 2D signal. The decomposition results of images are distinct and precise, and no gray spots appear compared with ones from the existing algorithms. NLEMD is one novel multi-resolution approach, and every IMF has different time and frequency resolution . By extracting useful data from every IMF and fusing them, we can obtain better image visually. In this paper, NLEMD has succeeded in high dynamic range image compression, image fusion etc.
Bounded model checking for knowledge and real time
Authors: Alessio Lomuscio, Wojciech Penczek, Bożena Woźna
Venue: Artificial Intelligence (2007)

We present TECTLK, a logic to specify knowledge and real time in multi-agent systems. We show that the TECTLK model checking problem is decidable, and we present an algorithm for bounded model checking based on a discretisation method. We exemplify the use of the technique by means of the ''Railroad Crossing System'', a popular example in the multi-agent systems literature.
Application of the Rough Set to Image Median Denoising
Authors: Chen Bo, Geng Zexun, Yang Yang, Liu Xiaosong
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

Image denoising that is a kind of basal pretreatment can improve visual effect of original images. Rough set is a new mathematical tool to deal with problems on vagueness and uncertainty. It is regarded as a soft computation method. Being the same as fuzzy method, genetic algorithm, neural networks, it is an intellective information processing method. Rough set applies to gray image, and a new image median denoising algorithm based on rough set (RSMD) is proposed in this paper. Comparing experiments are done using classical median denoising (CMD) and the denoising algorithm presented in this paper. Experimental results show that the new algorithm denoising outperforms the classical median denoising.
Mining pathway signatures from microarray data and relevant biological knowledge
Authors: Eleftherios Panteris, Stephen Swift, Annette Payne, Xiaohui Liu
Venue: Journal of Biomedical Informatics (2007)

High-throughput technologies such as DNA microarray are in the process of revolutionising the way modern biological research is being done. Bioinformatics tools are becoming increasingly important to assist biomedical scientists in their quest in understanding complex biological processes. Gene expression analysis has attracted a large amount of attention over the last few years mostly in the form of algorithms, exploring cluster and regulatory relationships among genes of interest, and programs that try to display the multidimensional microarray data in appropriate formats so that they make biological sense. To reduce the dimensionality of microarray data and make the corresponding analysis more biologically relevant, in this paper we propose a biologically-led approach to biochemical pathway analysis using microarray data and relevant biological knowledge. The method selects a subset of genes for each pathway that describes the behaviour of the pathway at a given experimental condition, and transforms them into pathway signatures. The metabolic pathways of Escherichia coli are used as a case study.
Comparison of regression and artificial neural network models for surface roughness prediction with the cutting parameters in CNC turning
Authors: Muammer Nalbant, Hasan Gokkaya, Ihsan Toktas
Venue: Modelling and Simulation in Engineering (2007)

Surface roughness, an indicator of surface quality, is one of the most specified customer requirements in machining of parts. In this study, the experimental results corresponding to the effects of different insert nose radii of cutting tools (0.4, 0.8, 1.2 mm), various depth of cuts (0.75, 1.25, 1.75, 2.25, 2.75 mm), and different feedrates (100, 130, 160, 190, 220 mm/min) on the surface quality of the AISI 1030 steel workpieces have been investigated using multiple regression analysis and artificial neural networks (ANN). Regression analysis and neural network-based models used for the prediction of surface roughness were compared for various cutting conditions in turning. The data set obtained from the measurements of surface roughness was employed to and tests the neural network model. The trained neural network models were used in predicting surface roughness for cutting conditions. A comparison of neural network models with regression model was carried out. Coefficient of determination was 0.98 in multiple regression model. The scaled conjugate gradient (SCG) model with 9 neurons in hidden layer has produced absolute fraction of variance (R2) values of 0.999 for the training data, and 0.998 for the test data. Predictive neural network model showed better predictions than various regression models for surface roughness. However, both methods can be used for the prediction of surface roughness in turning.
Automatic Retrieval of Optimal Texture from Aerial Video for Photo-realistic 3D Visualization of Street Environment
Authors: Jun Wu, Guoqing Zhou, FengLi Ding, Zhigang Liu
Venue: Proceedings of the Fourth International Conference on Image and Graphics (2007)

This paper presents an approach of automatic retrieval of optimal texture from aerial video for photo-realistic 3D visualization of street environment. First, problems of using aerial video as texture source are summarized and based on that, a set of criterions for the determination of optimal texture are proposed; After that, texture ortho-rectification method based on 3D building model is developed to eliminate texture distortion due to inherent perspective projection; Next, the Normalized Cross-correlation (NCC) operation is applied to ortho-rectified texture sub-windows to select a pair of texture with least occlusion as two candidates of optimal texture; Finally, optimal texture is determined from two candidates based on the estimation of area of each Texture View Triangle (TVT), which is the right-angled triangle consisting of camera project position, geometry center of building wall and its normal vector. 170 buildings with 1015 walls, located in the 1.7 km long test area Ginzav Street, Tokyo, Japapen, are processed to obtain optimal texture from three strip of aerial video captured by helicopter. The experimental results demonstrated that the proposed approach increase 8 times more efficiency and effectiveness than manual operation for urban texture reconstruction.
A Novel SVM Decision Tree and its application to Face Detection
Authors: Jian-qing Sun, Gong-gui Wang, Qiong Hu, Shou-yi Li
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

In order to speed up support vector classification, a novel algorithm by the names of SVM Decision Tree is proposed in this paper. In the decision tree, several linear SVM are constructed which can achieve the highest detection rate on the negative samples, the negative samples which can be correctly classified by the hyperplane are removed from the original samples, and train one nonlinear SVM using the rest samples. In the test step, the root of tree is used as the first classification. We apply this algorithm to face detection, experiment results show that the speed up factor is large and with no loss in generalization performance.
Automatic Detection of Instruments in Laparoscopic Images: A First Step Towards High-level Command of Robotic Endoscopic Holders
Authors: Sandrine Voros, Jean-Alexandre Long, Philippe Cinquin
Venue: International Journal of Robotics Research (2007)

The tracking of surgical instruments o fers interesting possibilities for the development of high-level commands for robotic camera holders in laparoscopic surgery. We have developed a new method to detect instruments in laparoscopic images which uses information on the 3D position of the insertion point of an instrument into the abdominal cavity. This information strongly constrains the search for the instrument in each endoscopic image. Hence, the instrument can be detected in near real-time using shape considerations. Early results on laparoscopic images show that the method is rapid and robust in the presence of partial occlusion and smoke. Our first experiment on a cadaver validates our approach and shows encouraging results.
Integrated placement and skew optimization for rotary clocking
Authors: Ganesh Venkataraman, Jiang Hu, Frank Liu
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2007)

The clock distribution network is a key component of any synchronous VLSI design. High power dissipation and pressure volume temperature-induced variations in clock skew have started playing an increasingly important role in limiting the performance of the clock network. Rotary clocking is a novel technique which employs unterminated rings formed by differential transmission lines to save power and reduce skew variability. Despite its appealing advantages, rotary clocking requires flip-flop locations to match predesigned clock skew on rotary clock rings. This requirement poses a difficult chicken-and-egg problem which prevents its wide application. In this paper, we propose an integrated placement and skew scheduling methodology to break this hurdle, making rotary clocking compatible with practical design flows. A network flow based flip-flop assignment algorithm and a cost-driven skew optimization algorithm are developed. We also present an integer linear programming formulation that minimizes maximum capacitance loaded at any of the rotary rings, thereby maximizing the operating frequency. Experimental results on benchmark circuits show that our method can reduce the tapping cost (measured as the total length of the wire segments connecting the rotary rings to the clock sinks) for rotary clocking by 33%-53%.
Geographically Weighted Visualization: Interactive Graphics for Scale-Varying Exploratory Analysis
Authors: Jason Dykes, Chris Brunsdon
Venue: IEEE Transactions on Visualization and Computer Graphics (2007)

We introduce a series of geographically weighted (GW) interactive graphics, or geowigs, and use them to explore spatial relationships at a range of scales. We visually encode information about geographic and statistical proximity and variation in novel ways through gw-choropleth maps, multivariate gw-boxplots, gw-shading and scalograms. The new graphic types reveal information about GW statistics at several scales concurrently. We impement these views in prototype software containing dynamic links and GW interactions that encourage exploration and refine them to consider directional geographies. An informal evaluation uses interactive GW techniques to consider Guerry's dataset of 'moral statistics', casting doubt on correlations originally proposed through visual analysis, revealing new local anomalies and suggesting multivariate geographic relationships. Few attempts at visually synthesising geography with multivariate statistical values at multiple scales have been reported. The geowigs proposed here provide informative representations of multivariate local variation, particularly when combined with interactions that coordinate views and result in gw-shading. We argue that they are widely applicable to area and point-based geographic data and provide a set of methods to support visual analysis using GW statistics through which the effects of geography can be explored at multiple scales.
Fault Line Detection in Small Current Grounding Systems Based on RBF Network
Authors: Yundong Song, Shun Yuan, Yanjie Wang, Chunfang Zhao
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 02 (2007)

It is a long-standing issue on fault line detection of single-phase grounding fault in the small current grounding systems. If only one fault line detection method is used, fault information will be analyzed partially, which is not enough for fault line detection; and there are different fit conditions for every method. So the single method can not ensure that the reliability of the fault line detection. In this paper, the effective domains of fault line detection through some methods were obtained by Rough Set theory, and the radial basis function (RBF) neural network was designed and trained, then the results of the methods based on RBF Network were got. Fusing those detection results, a better fault line detection result was advanced. Simulation results by EMTP show that the fault line detection method is efficient with high value of studying and wide application future.
Brief paper: Analysis of networked control systems with drops and variable delays
Authors: Matías García-Rivera, Antonio Barreiro
Venue: Automatica (Journal of IFAC) (2007)

Motivated by the insertion of a communication network in the feedback control loop, this paper focuses on how network-induced data dropouts and variable delays affect the stability of a linear plant with state feedback control. Sufficient conditions for Lyapunov stability are derived in the case of uncertainty due to drops and delays. The verification problem of the sufficient conditions can be directly cast as an LMI feasibility problem. We illustrate the methodology by an example in the cases of drops, delays and drops with delays.
Critical-Path based Low-Energy Scheduling Algorithms for Body Area Network Systems
Authors: Yanhong Liu, Bharadwaj Veeravalli, Sivakumar Viswanathan
Venue: Proceedings of the 13th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2007)

In this paper, we propose novel low-energy scheduling algorithms with low computational complexities for the heterogeneous Body Area Network (BAN) systems, considering task graphs with deadlines (timing constraints) and precedence relationships to satisfy. Our proposed novel scheme, referred to as "critical-path information track-andupdate", analyses the critical-paths, identifies the slack and distributes it over tasks such that the overall energy consumption is minimised. Our dynamic scheduling algorithm utilises the results from the static scheduling algorithm and attempts to aggressively reduce the energy consumption. Simulations for the task graph for a typical BAN application show that our static and dynamic scheduling algorithms deliver 25% and 15% more energy savings respectively compared to typical slack reclamation based scheduling algorithms.
A Query Expansion Method Based on Semantic Element
Authors: Li Li
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

Query Expansion technology can reduce word mismatch between query and related documents, improve retrieval precision through adding similar or related terms to original query. In the algorithm proposed in this paper, terms or phrases which have closely related sense are added to the original query and express users' query intention more precisely. This algorithm costs O(L) time which is independent of the SER-Base, and this is very practical for highly real-time search engine.
B73-4 High Level Languages International Computer State of the Art Report
Authors: P. J. Plauger
Venue: IEEE Transactions on Computers (1973)

According to the inside back cover, this volume is number 7 in a series of 16 state of the art reports put out by Infotech. I have not looked at any of the others. Its 500 typewritten pages document a nameless, dateless, placeless conference attended by many of the leading contributors to the current state of the art of high-level languages. Twelve Presentations and six Invited Papers comprise 60 percent of the content; the rest is derived material in the form of a Foreword and Analysis plus a gathering of indexes of various sorts.
Extending the fast multipole method for charges inside a dielectric sphere in an ionic solvent: High-order image approximations for reaction fields
Authors: Shaozhong Deng, Wei Cai
Venue: Journal of Computational Physics (2007)

As a sequel to our previous paper on extending the Fast Multipole Method (FMM) for charges inside a dielectric sphere [J. Comput. Phys. 223 (2007) 846-864], this paper further extends the FMM to the electrostatic calculation for charges inside a dielectric sphere immersed in an ionic solvent, a scenery with more relevance in biological applications. The key findings include two fourth-order multiple discrete image approximations in terms of u=@la to the reaction field induced by the ionic solvent, provided that u=@la
Context-Aware Learning Privacy Disclosure Policy from Interaction History
Authors: Qingsheng Zhang, Yong Qi, Jizhong Zhao, Di Hou, Tianhai Zhao, Jihong Zhang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 05 (2007)

Context-aware applications use personal information to provide appropriate services for people. This personal information is often involved in personal privacy. In order to balance the personal privacy concerns against enjoying context-aware services, we propose a conceptual framework and privacy role to control access personal information. Privacy disclosure policy can be learned from people's interaction history about personal information disclosure using rough set theory. According to deducing from the privacy disclosure policy and context information, a context-aware application is assigned to an adequate privacy role. A case analysis and the initial performance evaluation show that the proposed method is effective.
COBALT
Authors: Jason S. Papadopoulos, Richa Agarwala
Venue: Bioinformatics (2007)

Motivation: A tool that simultaneously aligns multiple protein sequences, automatically utilizes information about protein domains, and has a good compromise between speed and accuracy will have practical advantages over current tools. Results: We describe COBALT, a constraint based alignment tool that implements a general framework for multiple alignment of protein sequences. COBALT finds a collection of pairwise constraints derived from database searches, sequence similarity and user input, combines these pairwise constraints, and then incorporates them into a progressive multiple alignment. We show that using constraints derived from the conserved domain database (CDD) and PROSITE protein-motif database improves COBALT's alignment quality. We also show that COBALT has reasonable runtime performance and alignment accuracy comparable to or exceeding that of other tools for a broad range of problems. Availability: COBALT is included in the NCBI C++ toolkit. A Linux executable for COBALT, and CDD and PROSITE data used is available at: ftp://ftp.ncbi.nlm.nih.gov/pub/agarwala/cobalt Contact: richa@helix.nih.gov
Iterative Arrays ror Radix Conversion
Authors: J. -D. Nicoud
Venue: IEEE Transactions on Computers (1971)

the general study of the conversion of a number from the radix p to the radix q number system leads to four different algorithms for integers, and to four similar ones for fractions. Most transform algorithms can be implemented by iterative arrays of cells characterized by simple equations. Such arrays are very attractive with present-time large-scale integration technology.
Activity-based Access Control Model to Hospital Information
Authors: Le Xuan Hung, Sungyoung Lee, Young-Koo Lee, Heejo Lee
Venue: Proceedings of the 13th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2007)

Hospital work is characterized by the need to manage multiple activities simultaneously, constant local mobility, frequently interruptions, and intense collaboration and communication. Hospital employees must handle a large amount of data that is often tied to specific work activities. This calls for a proper access control model. In this paper, we propose a novel approach, Activity-based access Control Model (ACM). Unlike conventional approaches which exploit user identity/role information, ACM leverages user's activities to determine the access permissions for that user. In ACM, a user is assigned to perform a number of actions if s/he poses a set of satisfactory attributes. Access permissions to hospital information are granted according to user's actions. By doing this, ACM contributes a number of advantages over conventional models: (1) facilitates user's work; (2) reduces complexity and cost of access management. Though the design of ACM first aims to support clinical works in hospitals, it can be applied in other activity-centered environments.
WiMAX for Emergency Services: An Empirical Evaluation
Authors: Pedro Neves, Paulo Simoes, Alvaro Gomes, Luis Mario, Susana Sargento, Francisco Fontes, Edmundo Monteiro, Thomas Bohnert
Venue: Proceedings of the The 2007 International Conference on Next Generation Mobile Applications, Services and Technologies (2007)

WiMAX, as a Broadband Wireless Access technology for Metropolitan Area Networks, supporting fixed and mobile terminals, is very promising for Next Generation Networks. Emergency Services can also strongly benefit from WiMAX features, allowing the exploitation of novel application scenarios and business models. This paper presents a set of scenarios, such as Environmental Monitoring, Telemedicine and Fire Prevention, defined and implemented in several European testbeds, interconnected by the European research network GEANT 2, in the framework of the WEIRD project1. In particular, we focus our attention on the scenario implemented in the Portuguese testbed Fire Preventionproviding a detailed description about the testbed planning, implementation and evaluation.