ppxscal/embedding_network huggingface dataset:
Affective Loop Experiences --- What Are They?
Authors: Kristina Höök
Venue: Proceedings of the 3rd international conference on Persuasive Technology (2008)

A research agenda for bodily persuasion through a design approach we name affective loops is outlined. Affective loop experiences draw upon physical, emotional interactions between user and system.
Modeling Fixed Priority Non-Preemptive Scheduling with Real-Time Calculus
Authors: Devesh B. Chokshi, Purandar Bhaduri
Venue: Proceedings of the 2008 14th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2008)

Modern real-time embedded systems are highly heterogeneous and distributed. As a result, compositional methods play an important role in the design and analysis of such complex systems. One such compositional analysis method is based on Real-Time Calculus. In this paper, we present an analysis of fixed priority non-preemptive scheduling with the Real-Time Calculus. Although fixed priority non-preemptive scheduling was modeled with the Real-Time Calculus previously, we show that the model gives overly pessimistic results. We also compare our analysis with the existing holistic scheduling analysis through an example of a system using a Controller Area Network (CAN) bus. The proposed method can be automated by incorporating it in the RTC Toolbox.
Discrimination between partial discharge pulses in voids using adaptive neuro-fuzzy inference system (ANFIS)
Authors: N. Kolev, N. Chalashkanov
Venue: Proceedings of the 9th WSEAS International Conference on Neural Networks (2008)

A novel method for partial discharge (PD) pattern classification is proposed based on adaptive neurofuzzy inference system (ANFIS). It is used for classification of partial discharges signals occurring in internal voids. Three different void shapes are considered in this work, namely flat void, square void and narrow void. The initial input feature vector, used for the classification is based on 15 statistical parameters. These parameters characterize fully the PD signals. The structure of the ANFIS classifier is thoroughly described. Afterwards, discriminant analysis is implemented to reduce the dimension of the feature vector. Therefore, the complexity of the ANFIS structure is reduced and classifier performance improved. Also, assessments of the classifiers are presented.
Adaptive Dialogue Management in the NIMITEK Prototype System
Authors: Milan Gnjatović, Dietmar Rösner
Venue: Proceedings of the 4th IEEE tutorial and research workshop on Perception and Interactive Technologies for Speech-Based Systems: Perception in Multimodal Dialogue Systems (2008)

The primary aim of this paper is to present the implementation of adaptive dialogue management in the NIMITEK prototype spoken dialogue system for supporting users while they solve problems in a graphics system (e.g., the Tower-of-Hanoi puzzle). The central idea is that the system dynamically refines a dialogue strategy according to the current state of the interaction. We analyze a recorded dialogue between the user and the prototype system that took place during the testing of the system. It illustrates several points of the implemented dialogue strategy: processing of user's commands, supporting the user, and multilingual working mode.
Rigorously Defining and Analyzing Medical Processes: An Experience Report
Authors: Stefan Christov, Bin Chen, George S. Avrunin, Lori A. Clarke, Leon J. Osterweil, David Brown, Lucinda Cassells, Wilson Mertens
Venue: Models in Software Engineering: Workshops and Symposia at MoDELS 2007, Nashville, TN, USA, September 30 - October 5, 2007, Reports and Revised Selected Papers (2008)

This paper describes our experiences in defining the processes associated with preparing and administrating chemotherapy and then using those process definitions as the basis for analyses aimed at finding and correcting defects. The work is a collaboration between medical professionals from a major regional cancer center and computer science researchers. The work uses the Little-JIL language to create precise process definitions, the Propel system to specify precise process requirements, and the FLAVERS system to verify that the process definitions adhere to the requirement specifications. The paper describes how these technologies were applied to successfully identify defects in the chemotherapy process. Although this work is still ongoing, early experiences suggest that this approach can help reduce medical errors and improve patient safety. The work has also helped us to learn about the desiderata for process definition and analysis technologies, both of which are expected to be broadly applicable to other domains.
Video Monitoring of Vulnerable People in Home Environment
Authors: Quoc-Cuong Pham, Yoann Dhome, Laetitia Gond, Patrick Sayd
Venue: Proceedings of the 6th international conference on Smart Homes and Health Telematics (2008)

This paper presents a Video Monitoring System, which aims to achieve behavior analysis of elderly people. Real-time tracking and posture discrimination enable to detect emergency situation (by trigging an alarm in case of fall detection for example) and to analyze long term activity which enforces medical follow-up. These are key-issues to improve healthcare quality for rural population. Monitoring human activity in a home environment is a challenging task in computer vision. A multi-camera system is proposed to address the complexity of home environment. Person silhouette is extracted thanks to a robust background/foreground segmentation process. A multi-view particle filter is built to track the silhouette in the scene and discriminate the person posture. This posture is used to interpret basic activities and detect falls. A finer gesture reconstruction is finally exposed which will offer a more accurate activity determination and gait analysis for future system.
New Features in Math Accessibility with Infty Software
Authors: Katsuhito Yamaguchi, Toshihiko Komada, Fukashi Kawane, Masakazu Suzuki
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

The math OCR software, "InftyReader" can recognize properly printed math and scientific documents including many special symbols and technical notations such as math expressions. The recognition result can be converted to various accessible formats. The accessible math-document editor, "ChattyInfty" enables visually disabled people not only to read but also to author math documents with speech output. The current version of InftyReader can also recognize PDF files and achieves remarkable recognition rate for both of text and math parts. In the current version of ChattyInfty, user can customize various settings concerning speech output. A new function relevant to producing DAISY math books is also implemented.
Image Gradient Detection with Hough Transform
Authors: Seung-Joon Lee, Hyochang Ahn, Han-Jin Cho, Jun-Hwan Lee, Sang-Burm Rhee
Venue: Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology (2008)

In this paper, we propose gradient detection system of the vertical straight line using the Hough Transform after extracting from the color images. The input color images can be used to a method for detecting a gradient from only the luminance component of animage. In edge detection, traditional method of the mask of vertical edge detection can detect with the one direction of the image change but proposed method can detect bi-direction. Since the Hough Transform is required much time for processing, our method can be improved processing time through experimentally calculating valid pixel.
Appearance Models for Medical Volumes with Few Samples by Generalized 3D-PCA
Authors: Rui Xu, Yen-Wei Chen
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

Appearance models is important for the task of medical image analysis, such as segmentation. Principal component analysis (PCA) is an efficient method to build the appearance models; however the 3D medical volumes should be first unfolded to form the 1D long vectors before the PCA is used. For large medical volumes, such a unfolding preprocessing causes two problems. One is the huge burden of computing cost and the other is bad performance on generalization. A method named as generalized 3D-PCA is proposed to build the appearance models for medical volumes in this paper. In our method, the volumes are directly treated as the third order tensor in the building of the model without the unfolding preprocessing. The output of our method is three matrices whose columns are formed by the orthogonal bases in the three mode subspaces. With the help of these matrices, the bases in the third order tensor space can be constructed. According to these properties, our method is not suffered from the two problems of the PCA-based methods. Eighteen 256×256×26 MR brain volumes are used in the experiments of building appearance models. The leave-one-out testing shows that our method has good performance in building the appearance models for medical volumes even when few samples are used for training.
Reconstruction Algorithms with Images Inferred by Self-organizing Maps
Authors: Michiharu Maeda
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

For restoring a degraded image, reconstruction algorithms with images inferred by self-organizing maps are presented in this study. Multiple images inferred by self-organizing maps are prepared in the initial stage, which creates a map containing one unit for each pixel. Utilizing pixel values as input, image inference is conducted by self-organizing maps. An updating function with threshold according to the difference between input value and inferred value is introduced, so as not to respond to noisy input sensitively. The inference of an original image proceeds appropriately since any pixel is influenced by neighboring pixels corresponding to the neighboring setting. By using the inferred images, two approaches are presented. The first approach is that a pixel value of a restored image is a median value of inferred images for respective pixels. The second approach is that a pixel value is an average value of them. Experimental results are presented in order to show that our approach is effective in quality for image restoration.
Blended Learning: A Case Study for Japanese Language Studies
Authors: Kenneth K. Lee, Melody P. Chong
Venue: Proceedings of the 1st international conference on Hybrid Learning and Education (2008)

This article examines the link between e-learning and instructor-led teaching in a local university in Hong Kong. It employs a case study to examine the relation in a sample of undergraduate students studying Japanese language. More specifically, the study aims to pose a challenge to the existing and dominant instructor-led teaching method. The paper also provides implications for the design of course structure and content that will improve students' performance and motivation while enhancing the effectiveness of teaching and learning as a whole.
Ubi-Board: A Smart Information Diffusion System
Authors: Michel Banâtre, Mathieu Becus, Paul Couderc
Venue: Proceedings of the 8th international conference, NEW2AN and 1st Russian Conference on Smart Spaces, ruSMART on Next Generation Teletraffic and Wired/Wireless Advanced Networking (2008)

In this paper, we present the design and implementation of Ubi-Board, a context sensitive and multimodal information diffusion system. Typically, Ubi-Board consists of smart displays with the ability to sense the profile of nearby users, to adapt the information content so as it is understandable and accessible to the people, and to dynamically distribute the information to the appropriate devices, including users mobile devices when necessary.
Perception of Two-Stroke Apparent Motion and Real Motion
Authors: Qi Zhang, Ken Mogi
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

Motion perception is an important visual ability of human beings. We can perceive motions not only from real motion but also from apparent motion. Usually, the direction of a perceived apparent motion reflects the real spatial shift between the two successional images, but sometimes the perceived direction is distorted. Two-stroke apparent motion is one of such phenomena, which is induced by two pattern frames from a motion sequence and a blank ISI. We studied on two-stroke apparent motion and found that there were temporal limits to its perception. We measured the brain activity using fMRI when subjects observing the two-stroke apparent motion, real motion and still images. Our fMRI experimental results show that MT/V5 is activated for both the apparent motion and real motion perception, but more activities in the prefrontal/frontal and parietal cortex are observed for the apparent motion perception.
An FCA Perspective on n-Distributivity
Authors: Heiko Reppe
Venue: Proceedings of the 15th international conference on Conceptual Structures: Knowledge Architectures for Smart Applications (2007)

Distributive lattices belong to the best studied ordered structures. A. Huhn introduced a generalisation of this lattice property, called n-distributivity. We present two new methods to recognise the parameter n of this property for a given structure. For this purpose we use the arrow relations in a formal context and implications with proper premise. Additionally, we consider subsets of an order relation ≤ on a finite set P with an additional property. These subsets will be called left clearings of ≤. We show that the family of left clearings forms a complete dually l-distributive lattice, where l denotes the length of (P, ≤ ). Using these results, we determine that parameter n for Tamari lattices for the n-distributivity and dually n-distributivity.
An Application of Support Vector Machines for Induction Motor Fault Diagnosis with Using Genetic Algorithm
Authors: Ngoc-Tu Nguyen, Hong-Hee Lee
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

This paper introduces a technique for diagnosing mechanical faults of induction motors by using support vector machine (SVM) and genetic algorithm (GA). Features are extracted from the vibration time signals and selected by using GA with a distance evaluation fitness function. All SVM parameters are also obtained simultaneously by the same GA. The SVM is studied with two types of kernel functions, the radial basis function and the polynomial function. Four motor conditions are investigated with the chosen SVM classifiers. The classification results have high accuracy for the chosen feature set and SVM parameters.
Multimodal Retrieval by Text---Segment Biclustering
Authors: András Benczúr, István Bíró, Mátyás Brendel, Károly Csalogány, Bálint Daróczy, Dávid Siklósi
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

We describe our approach to the ImageCLEFphoto 2007 task. The novelty of our method consists of biclustering image segments and annotation words. Given the query words, it is possible to select the image segment clusters that have strongest cooccurrence with the corresponding word clusters. These image segment clusters act as the selected segments relevant to a query. We rank text hits by our own tf.idf-based information retrieval system and image similarities by using a 20-dimensional vector describing the visual content of an image segment. Relevant image segments were selected by the biclustering procedure. Images were segmented by graph-based segmentation. We used neither query expansion nor relevance feedback; queries were generated automatically from the title and the description words. The later were weighted by 0.1.
Shot Boundary Detection Using a Global Decision Tree in Ubiquitous Environment
Authors: Shin Seong-Yoon, Gao Cheng, Baek Seong-Eun, Sang-Joon Park, Shin Jung-Hoon, Rhee Yang-Won
Venue: Proceedings of the international conference on Computational Science and Its Applications, Part II (2008)

Role of video in Ubiquitous environment is growing. This paper presents a shot boundary detection method based on the global decision tree that allows for extraction of boundaries of high variations occurring due to camera breaks from frame difference values. For a start, difference values between frames are calculated through local X 2-histogram and normalization. Next, the distances between difference values are calculated through normalization. After the global threshold distance is computed based on the distances between the difference values calculated, a comparison between the distance value for two adjacent frames and the global threshold distance is performed to detect shot boundaries.
Challenges for Security Typed Web Scripting Languages Design
Authors: Doaa Hassan, Sherif El- Kassas, Ibrahim Ziedan
Venue: Proceedings of the 2008 The Fourth International Conference on Information Assurance and Security (2008)

This paper focuses on the different challenges to design a security typed web scripting language. It uses the type system approach on a simple imperative language that captures a subset of the security typed web language constructs to express the security properties that must be held in the language with respect to its formal semantics to prevent insecure information flow in web application system and hence the common web application security vulnerabilities.
On the Design Dilemma in Dining Cryptographer Networks
Authors: Jens O. Oberender, Hermann Meer
Venue: Proceedings of the 5th international conference on Trust, Privacy and Security in Digital Business (2008)

In a Dining Cryptographers network, the anonymity level raises with the number of participating users. This paper studies strategic behavior based on game theory. Strategic user behavior can cause sudden changes to the number of system participants and, in consequence, degrade anonymity. This is caused by system parameters that influence strategic behavior. Additionally, conflicting goals of participants result in dilemma games. Properties of message coding, e.g. collision robustness and disrupter identification, change the game outcome by preventing dilemmas and, therefore, enhance anonymity. Properties of anonymity metrics are proposed that allow for strategic user behavior.
A Bayesian Multilevel Modeling Approach for Data Query in Wireless Sensor Networks
Authors: Honggang Wang, Hua Fang, Kimberly Andrew Espy, Dongming Peng, Hamid Sharif
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

In power-limited Wireless Sensor Network (WSN), it is important to reduce the communication load in order to achieve energy savings. This paper applies a novel statistic method to estimate the parameters based on the real-time data measured by local sensors. Instead of transmitting large real-time data, we proposed to transmit the small amount of dynamic parameters by exploiting both temporal and spatial correlation within and between sensor clusters. The temporal correlation is built on the level-1 Bayesian model at each sensor to predict local readings. Each local sensor transmits their local parameters learned from historical measurement data to their cluster heads which account for the spatial correlation and summarize the regional parameters based on level-2 Bayesian model. Finally, the cluster heads transmit the regional parameters to the sink node. By utilizing this statistical method, the sink node can predict the sensor measurements within a specified period without directly communicating with local sensors. We show that this approach can dramatically reduce the amount of communication load in data query applications and achieve significant energy savings.
Planar Features for Visual SLAM
Authors: Tobias Pietzsch
Venue: Proceedings of the 31st annual German conference on Advances in Artificial Intelligence (2008)

Among the recent trends in real-time visual SLAM, there has been a move towards the construction of structure-rich maps. By using landmarks more descriptive than point features, such as line or surface segments, larger parts of the scene can be represented in a compact form. This minimises redundancy and might allow applications such as object detection and path planning. In this paper, we propose a probabilistic map representation for planar surface segments. They are measured directly using the image intensities of individual pixels in the camera images. Preliminary experiments indicate that the motion of a camera can be tracked more accurately than with traditional point features, even when using only a single planar feature. 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
Successful CIOs: Pushing the IT Business Value Envelope
Authors: John D. Hwang, Simon Liu
Venue: IT Professional (2004)

Any IT system should add value to the business.Frameworks help you determine whether your IT investments make sense.
Identifiability: A Fundamental Problem of Student Modeling
Authors: Joseph E. Beck, Kai-Min Chang
Venue: Proceedings of the 11th international conference on User Modeling (2007)

In this paper we show how model identifiabilityis an issue for student modeling: observed student performance corresponds to an infinite family of possible model parameter estimates, all of which make identical predictions about student performance. However, these parameter estimates make different claims, some of which are clearly incorrect, about the student's unobservable internal knowledge. We propose methods for evaluating these models to find ones that are more plausible. Specifically, we present an approach using Dirichlet priors to bias model search that results in a statistically reliable improvement in predictive accuracy (AUC of 0.620 ± 0.002 vs. 0.614 ± 0.002). Furthermore, the parameters associated with this model provide more plausible estimates of student learning, and better track with known properties of students' background knowledge. The main conclusion is that prior beliefs are necessary to bias the student modeling search, and even large quantities of performance data alone are insufficient to properly estimate the model.
Monitoring Aggregate k-NN Objects in Road Networks
Authors: Lu Qin, Jeffrey Xu Yu, Bolin Ding, Yoshiharu Ishikawa
Venue: Proceedings of the 20th international conference on Scientific and Statistical Database Management (2008)

In recent years, there is an increasing need to monitor k nearest neighbor (k-NN) in a road network. There are existing solutions on either monitoring k-NN objects from a single query point over a road network, or computing the snapshot k-NN objects over a road network to minimize an aggregate distance function with respect to multiple query points. In this paper, we study a new problem that is to monitor k-NN objects over a road network from multiple query points to minimize an aggregate distance function with respect to the multiple query points. We call it a continuous aggregate k-NN (CANN) query. We propose a new approach that can significantly reduce the cost of computing network distances when monitoring aggregate k-NN objects on road networks. We conducted extensive experimental studies and confirmed the efficiency of our algorithms.