ppxscal/embedding_network huggingface dataset:
Proposal for Teaching Manufacturing and Control Programming Using Autonomous Mobile Robots with an Arm
Authors: Shuji Kurebayashi, Hiroyuki Aoki, Toshiyuki Kamada, Susumu Kanemune, Yasushi Kuno
Venue: Proceedings of the 3rd international conference on Informatics in Secondary Schools - Evolution and Perspectives: Informatics Education - Supporting Computational Thinking (2008)

We propose a technology education curriculum for lower secondary school students using an autonomous mobile robot with an arm. The purpose of our curriculum is to teach the concept of systems that work with mechanics, electricity and computers. For this purpose, we have developed a control board and a computer language for an autonomous mobile robot with an arm. The benefit of this kind of robot is that students have to seriously think about the program for controlling the arm to lift and carry objects. This kind of serious thought is not necessary in programming simple mobile robots without arms[1]. In this paper, we will report a test conducted to evaluate our teaching materials and lessons in lower secondary school. As a result, our technology education curriculum satisfies requirements for students that have more incentives to learn the concept of systems.
Group discussion on magnetic-tape standards
Authors: Allen Shoup
Venue: Papers and discussions presented at the Dec. 8-10, 1953, eastern joint AIEE-IRE computer conference: information processing systems---reliability and requirements (1953)

About thirty-five persons attended an informal discussion regarding problems and points of interest pertaining to magnetic tape for use in the computer field. Several engineers explained some of their tape problems and the assembly in general very co-operatively offered helpful suggestions. There was considerable discussion regarding standardization of tape. It is impossible at this early date to set any standards, but various issues were submitted for consideration and these are being presented in this report. Everyone interested is invited to write the chairman regarding any of these subjects or any new items which they would like to discuss. After this information has been exchanged and collated, tentative standards will be formulated and distributed for comment. It is understood that although it will be some time before all the machines in the industry can become standardized, the present discussion may be of help to engineers starting new designs because they will be cognizant of the trend at this time. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Chicken Little and the Recorded Music Crisis
Authors: Michael Lesk
Venue: IEEE Security and Privacy (2003)

Music sales have declined in the past, and the recording industry has repeatedly blamed new technologies. But the new technologies haven't gone away; the solution has always been some kind of economic bargain, and we should again expect an economic bargain to deal with the problems caused by online music distribution.
A novel LS-SVMs hyper-parameter selection based on particle swarm optimization
Authors: X. C. Guo, J. H. Yang, C. G. Wu, C. Y. Wang, Y. C. Liang
Venue: Neurocomputing (2008)

The selection of hyper-parameters plays an important role to the performance of least-squares support vector machines (LS-SVMs). In this paper, a novel hyper-parameter selection method for LS-SVMs is presented based on the particle swarm optimization (PSO). The proposed method does not need any priori knowledge on the analytic property of the generalization performance measure and can be used to determine multiple hyper-parameters at the same time. The feasibility of this method is examined on benchmark data sets. Different kinds of kernel families are investigated by using the proposed method. Experimental results show that the best or quasi-best test performance could be obtained by using the scaling radial basis kernel function (SRBF) and RBF kernel functions, respectively.
Unsupervised and Semi-supervised Lagrangian Support Vector Machines
Authors: Kun Zhao, Ying-Jie Tian, Nai-Yang Deng
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

Support Vector Machines have been a dominant learning technique for almost ten years, moreover they have been applied to supervised learning problems. Recently two-class unsupervised and semi-supervised classification problems based on Bounded C-Support Vector Machines and Bounded ¿-Support Vector Machines are relaxed to semi-definite programming [4][11]. In this paper we will present another version to unsupervised and semi-supervised classification problems based on Lagrangian Support Vector Machines, which trained by convex relaxation of the training criterion: find a labelling that yield a maximum margin on the training data. But the problems have difficulty to compute, we will find their semi-definite relaxations that can approximate them well. Experimental results show that our new unsupervised and semi-supervised classification algorithms often obtain almost the same accurate results as the unsupervised and semi-supervised methods [4][11], while considerably faster than them.
Self-configuring Resource Discovery on a Hypercube Grid Overlay
Authors: Antonia Gallardo, Luis Díaz De Cerio, Kana Sanjeevan
Venue: Proceedings of the 14th international Euro-Par conference on Parallel Processing (2008)

Grid Resource Discovery Service is a fundamental problem that has been the focus of research in the recent past. We propose a scheme that presents essential characteristics for efficient, self-configuring and fault-tolerant resource discovery and is able to handle dynamic attributes, such as memory capacity. Our approach consists of an overlay network with a hypercube topology connecting the grid nodes and a scalable, fault-tolerant, self-configuring search algorithm. The algorithm improves the probability of reaching all working nodes in the system even in the presence of non-alive nodes (inaccessible, crashed or heavy loaded nodes). We analyze the static resilience of the approach presented, which is the measure of how well the algorithm can discover resources without having to update the routing tables.
Text analysis for ontology and terminology engineering
Authors: Nathalie Aussenac-Gilles, Dagobert Sörgel
Venue: Applied Ontology (2005)

After a recent breakthrough in the early 90's, text analysis is acknowledged as one of the promising ways to rapidly build better grounded semantic resources such as terminologies and ontologies. This domain has recently undergone significant evolutions with a massive reference to machine learning algorithms and information extraction techniques together with linguistic- and statistic-based natural language processing. This position paper promotes three main ideas: (i) that highly domain-specific or task-specific, even idiosyncratic ontologies, are very useful, especially when they are linked to broader consensual schemes and they can be built with reasonable effort; (ii) that corpus-based ontologies can capture the perspective of a domain; and (iii) that supervised ontology learning from text makes feasible the development of specialized ontologies adapted for specific uses. We propose the establishment of an inventory of tools for building ontologies from text, give a first classification of such tools, and present an initial review of some recent methods and tools.
On-Line Diagnosis of Faulty Insulators Based on Improved ART2 Neural Network
Authors: Hailong Zhang, Weimin Guan, Genzhi Guan
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

In this paper, an improved ART2 neural network is applied to on-line diagnosis of faulty insulators. Deterioration of insulator is a gradual phenomenon. Thus, the cluster centers tend to drift during the process of recognizing on-line monitor signals. The drifts of cluster centers cause wrong judgments. In order to solve this problem, an initial layer is settled in layer F2. The improved ART2 neural network divides layer F2 into upper-sublayer F22 and lower-sublayer F21. When insulators start working for the first time, the upper-sublayer F22 store initial states and typical-malfunction patterns. Furthermore, the improved ART2 structure of the network map, and detailed algorithm flowchart are also illustrated in this paper.
Security Contexts in Autonomic Systems
Authors: Kaiyu Wan, Vasu Alagar
Venue: Computational Intelligence and Security: International Conference, CIS 2006, Guangzhou, China, November 3-6, 2006, Revised Selected Papers (2007)

Autonomic Computing Systems (ACS) are expected to achieve the same level of self-regulation and pervasiveness as human autonomic systems. Because of the features of ACS, the traditional security model can not be applied to ACS any more. The goal of our research is to develop a context-based security model and architecture for ACS. Our focus is on self-protection feature of ACS. The self-protection feature is enforced through security contexts that we define. By taking security contexts into account, security policies can dynamic change in order to cope with new environment.
Implementing Product Line Engineering in Industry: Feedback from the Field to Research
Authors: Davide Falessi, Dirk Muthig
Venue: Proceedings of the 9th international conference on Product-Focused Software Process Improvement (2008)

Software product line engineering refers to methods (tools and techniques) for creating sets of similar software systems by taking advantage of their commonalities and predicted variabilities. After successfully installing product line engineering in practice, organizations typically experience a great improvement with respect to productivity or quality. Product line engineering is a proactive and strategic approach towards software reuse that requires the involvement of whole organizations to be successful. Implementing product line engineering in practice thus corresponds to identifying a strategy that transforms an existing organization into an organization that is fully centered around their product line(s), Although this transformation impacts nearly everything in an organization, it is often realized in an incremental way to manage risks and to ensure that production continues during the change process.
Steganalysis of QIM steganography using irregularity measure
Authors: Hafiz Malik
Venue: Proceedings of the 10th ACM workshop on Multimedia and security (2008)

This paper presents a nonparametric steganalysis technique to attack quantization index modulation (QIM) steganography and JSteg steganographic tool. The proposed scheme is based on the observation that message embedding using QIM introduces local irregularity (or randomness) in the cover-object. Presented steganalysis technique exploits rich spatial/temporal correlation in the multimedia-objects to estimate local irregularity in the test-object. The underlying density function based on local irregularity in the test-object is estimated in a systematic manner using a kernel density estimate (KDE) method. The Tsallis-divergence, a parametric divergence method, is used to quantify irregularity in the test-object. The Tsallis-divergence between the density function estimated from the test-object and its doubly-quantized version is used to distinguish between the cover and the stego. The impact of the choice of message embedding parameters such as quantization step-size, quality factor, etc. on the accuracy of the steganalysis detection for gray scale images is also evaluated. Simulation results presented for these message embedding parameters show that the proposed method can successfully distinguish between the quantized-cover and the QIM-stego with low false alarm rates. Detection performance of the proposed steganalysis scheme is also evaluated for JSteg steganographic tool.
Modeling parallel and reactive empathy in virtual agents: an inductive approach
Authors: Scott W. McQuiggan, Jennifer L. Robison, Robert Phillips, James C. Lester
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1 (2008)

Humans continuously assess one another's situational context, modify their own affective state, and then respond based on these outcomes through empathetic expression. Virtual agents should be capable of similarly empathizing with users in interactive environments. A key challenge posed by empathetic reasoning in virtual agents is determining whether to respond with parallel or reactive empathy. Parallel empathy refers to mere replication of another's affective state, whereas reactive empathy exhibits greater cognitive awareness and may lead to incongruent emotional responses (i.e., emotions different from the recipient's and perhaps intended to alter negative affect). Because empathy is not yet sufficiently well understood, it is unclear as to which type of empathy is most effective and under what circumstances they should be applied. Devising empirically informed models of empathy from observations of "empathy in action" may lead to virtual agents that can accurately respond in social situations. This paper proposes a unified inductive framework for modeling parallel and reactive empathy. First, in training sessions, a trainer guides a virtual agent through a series of problem-solving tasks in a learning environment and encounters empathetic characters. The proposed inductive architecture tracks situational data including actions, visited locations, intentions, and the trainer's physiological responses to generate models of empathy. Empathy models are used to drive runtime situation-appropriate empathetic behaviors by selecting suitable parallel or reactive empathetic expressions. An empirical evaluation of the approach in an interactive learning environment suggests that the induced empathy models can accurately assess social contexts and generate appropriate empathetic responses for virtual agent control.
Compiler transformations for automatic generation of vhdl from c for code acceleration on reconfigurable devices
Authors: Walid A. Najjar
Venue:  (2008)

Reconfigurable computers, where one or more FPGAs are attached to a conventional microprocessor, are promising platforms for code acceleration. Despite their advantages, programmability concerns and the lack of efficient design tools/compilers for FPGAs, are preventing the technology's widespread adoption. The traditional compiler technology is microprocessor-based-systems-specific and needs to be customized and augmented to address the programmability issues of reconfigurable platforms. The challenges are several due to the resources and performance-constraints for FPGAs being drastically different than those of microprocessors, and also that compiling for FPGAs requires laying the computation in space by a circuit rather than in time by a sequence of instructions. ROCCC is an optimizing C-to-VHDL compiler targeting specifically the reconfigurable computer platforms. ROCCC includes several high-level optimizations that parallelize and optimize the source code for minimized area and critical path length and, maximized throughput. This thesis presents ROCCC's high level transformations and their effect on the performance of the generated VHDL output. In this thesis explained are ROCCC's (1) several array access optimizations, which eliminate redundant memory accesses, (2) procedure-level optimizations that achieve circuit area reductions of up to 88% compared to circuit areas generated from unoptimized codes, (3) loop-level optimizations which help improve the throughput by increasing loop-level parallelism, and (4) application-specific transformations that map certain classes of applications uniquely and most efficiently to hardware. Through these transformations, ROCCC generates circuits with very large degrees of parallelism capable of very high computation rates.
Tutorial Introduction to Graph Transformation
Authors: Reiko Heckel
Venue: Proceedings of the 4th international conference on Graph Transformations (2008)

This tutorial is intended as a general introduction to graph transformation for participants to the conference or its satellite events who are not familiar with the mainstream approaches and concepts of the area. The tutorial will start with an informal introduction to the basic concepts of graph transformation, such as graphs, rules, transformations, discussing semantic choices such as the handling of dangling edges during rewriting, and extensions such as attributes, types, or inheritance.In the second part, the tutorial will give a survey of typical applications of graph transformation, for example as a specification language and semantic model for concurrent and distributed systems, as a model transformation language for defining syntax, semantics, and manipulation of visual models, etc.Finally, the tutorial will go into some details about the theory of (in particular) the algebraic approach to graph transformation, its formal foundations and relevant theory and tools. This shall enable the participants to better appreciate the conference and its satellite events.
Suppression of noise in the ECG signal using digital IIR filter
Authors: Mahesh S. Chavan, R. A. Agarwala, M. D. Uplane
Venue: Proceedings of the 8th WSEAS International Conference on Multimedia systems and signal processing (2008)

The electrocardiogram has considerable diagnostic significance, and application of ECG monitoring are diverse and in wide use. For diagnostic- quality ECG recordings, signal acquisition must be noise free. The signal acquisition is susceptible to the interference from other biological and environmental sources. This article presents the application of the digital IIR filter on the raw ECG signal. The filters utilized are Butterworth and elliptic notch and high pass filter. Complete design of the filters is depicted in the paper. At the end both the filter types are compared. It is found that the elliptic filter find suitable as compared to the Butterwoth with some limitations.
Learning transform invariant object recognition in the visual system with multiple stimuli present during training
Authors: S. M. Stringer, E. T. Rolls
Venue: Neural Networks (2008)

Over successive stages, the visual system develops neurons that respond with view, size and position invariance to objects or faces. A number of computational models have been developed to explain how transform-invariant cells could develop in the visual system. However, a major limitation of computer modelling studies to date has been that the visual stimuli are typically presented one at a time to the network during training. In this paper, we investigate how vision models may self-organize when multiple stimuli are presented together within each visual image during training. We show that as the number of independent stimuli grows large enough, standard competitive neural networks can suddenly switch from learning representations of the multi-stimulus input patterns to representing the individual stimuli. Furthermore, the competitive networks can learn transform (e.g. position or view) invariant representations of the individual stimuli if the network is presented with input patterns containing multiple transforming stimuli during training. Finally, we extend these results to a multi-layer hierarchical network model (VisNet) of the ventral visual system. The network is trained on input images containing multiple rotating 3D objects. We show that the network is able to develop view-invariant representations of the individual objects.
Fault-Tolerant Compression Algorithms for Delay-Sensitive Sensor Networks with Unreliable Links
Authors: Alexandre Guitton, Niki Trigoni, Sven Helmer
Venue: Proceedings of the 4th IEEE international conference on Distributed Computing in Sensor Systems (2008)

We compare the performance of standard data compression techniques in the presence of communication failures. Their performance is inferior to sending data without compression when the packet loss rate of a link is above 10%. We have developed fault-tolerant compression algorithms for sensor networks that are robust against packet loss and achieve low delays in data decoding, thus being particularly suitable for time-critical applications. We show the advantage of our technique by providing results from our extensive experimental evaluation using real sensor datasets.
Finger Walking in Place (FWIP): A Traveling Technique in Virtual Environments
Authors: Ji-Sun Kim, Denis Gračanin, Krešimir Matković, Francis Quek
Venue: Proceedings of the 9th international symposium on Smart Graphics (2008)

In this paper we present a Finger Walking in Place (FWIP) interaction technique that allows a user to travel in a virtual world as her/his bare fingers slide on a multi-touch sensitive surface. Traveling is basically realized by translating and rotating the user's viewpoint in the virtual world. The user can translate and rotate a viewpoint by moving her/his fingers in place. Currently, our FWIP technique can be used to navigate in a plane but it can be extended to navigate in the third axis, so that the user can move to any direction in a 3D virtual world. Since our FWIP technique only uses bare fingers and a multi-touch device, finger motions are not precisely detected, especially compared with the use of data gloves or similar sensing devices. However, our experiments show that FWIP can be used as a novel traveling technique even without accurate motion detection. Our experiment tasks include finding and reaching the target(s) with FWIP, and the participants successfully completed the tasks. The experiments illustrate our efforts to make the FWIP technique robust as a scaled-down walking-in-place locomotion technique, so that it can be used as a reliable traveling technique.
Assuring Authenticity of Digital Mammograms by Image Watermarking
Authors: Anthony Maeder, Jason Dowling, Anthony Nguyen, Emma Brunton, Phuong Nguyen
Venue: Proceedings of the 9th international workshop on Digital Mammography (2008)

Wide availability of medical images in digital form introduces risk of changes to the image data, whether by deliberate or accidental means. Some level of protection is afforded by use of encapsulating software such as PACS and other image storage systems, and by making use of file format information (e.g. DICOM header fields). However a greater degree of assurance can be obtained by embedding a subtle hidden pattern within the actual image data, an approach termed image watermarking. The effect of adding the watermark must be below the perceptual threshold of a skilled observer, and must not measurably affect the performance of readers. This paper uses an approach developed specifically for medical image watermarking, and describes efforts to validate its effects on digital mammograms according to the above criteria. The operating region based on embedding strength values for two watermarking methods (DCT and DWT) in the vicinity of the perceptual threshold was characterized using two established perceptual quality metrics (PSNR and SVDP Sum). Subjective testing was then undertaken to compare these metric values with actual observer perception in a 2AFC experiment, and a clear perceptual threshold effect was found.
Grate Furnace Combustion: A Submodel for the Solid Fuel Layer
Authors: H. A. Kuijk, R. J. Bastiaans, J. A. Oijen, L. P. Goey
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

The reduction of NOx-formation in biomass fired grate furnaces requires the development of numerical models. To represent the variety in scales and physical processes playing a role in the conversion, newly developed submodels are required. Here, a submodel for the reverse combustion process in the solid fuel layer on the grate is described. The submodel is shown to give good predictions for the velocity of the combustion front as well as for the spatial profiles of porosity, oxygen mass fraction and temperature. These predictions are essential input for NOx-calculations.