ppxscal/embedding_network huggingface dataset:
An advanced direct searching technique applied on compressed video content repositories
Authors: Fotis Andritsopoulos, Serafeim Papastefanos, Vassiliki Mpilili, Christos Theocharatos
Venue: Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts (2008)

The DIVAS system is a content based search engine for locating multimedia fragments in large video repositories mainly found across the Internet. DIVAS performs searching using only audiovisual characteristics, unlike other, metadata-based solutions. Metadata based search methods are used as complementary services to DIVAS, in order to help and refine the overall search procedure, instead of using it as the primary search method. Thus it achieves a totally automated indexing and search scheme. This paper is focused on techniques adopted by DIVAS for analyzing, indexing and searching video content directly on the compressed domain. Significant improvement on search time can be achieved when avoiding decompression of the content which is one of the most time consuming processes when dealing with video processing. The generic DIVAS architecture is also presented in this paper highlighting its modularity and providing to the researcher and the developer the ability to easily add new features and to improve the performance and the accuracy of results.
A Recognition Interface for Bridging the Semantic Desktop and the Physical World
Authors: Hiroshi Miyake, Koichi Kise, Andreas Dengel
Venue: Proceedings of the 31st annual German conference on Advances in Artificial Intelligence (2008)

The semantic desktop is an extension of the semantic web technologies to the field of desktops for the purpose of intelligent processing and share of data in the PC. Although most current technologies of the semantic desktop focus only on the virtual world in the PC, the field of user's activity is not limited to it; in a typical office environment, the user also interacts with various physical objects such as printed documents and office goods during the activity. The aim of this paper is to show some important concepts and a prototype of the interface necessary to extend the field of semantic desktop to the physical world. The key technologies for bridging the gap between virtual and physical worlds are fast and robust object recognition and document image retrieval.
An Evaluation of the Impact of Side Chain Positioning on the Accuracy of Discrete Models of Protein Structures
Authors: Miguel M. Bugalho, Arlindo L. Oliveira
Venue: Proceedings of the 3rd Brazilian symposium on Bioinformatics: Advances in Bioinformatics and Computational Biology (2008)

Discrete models are important to reduce the complexity of the protein folding problem. However, a compromise must be made between the model complexity and the accuracy of the model.Previous work by Park and Levitt has shown that the protein backbone can be modeled with good accuracy by four state discrete models. Nonetheless, for ab-initio protein folding, the side chains are important to determine if the structure is physically possible and well packed.We extend the work of Park and Levitt by taking into account the positioning of the side chain in the evaluation of the accuracy. We show that the problem becomes much harder and more dependent on the type of protein being modeled. In fact, the structure fitting method used in their work is no longer adequate to this extended version of the problem. We propose a new method to test the model accuracy.The presented results show that, for some proteins, the discrete models with side chains cannot achieve the accuracy of the backbone only discrete models. Nevertheless, for the majority of the proteins an RMSD of four angstrom or less is obtained, and, for many of those, we reach an accuracy near the two angstrom limit. These results prove that discrete models can be used in protein folding to obtain low resolution models. Since the side chains are already present in the models, the refinement of these solutions is simpler and more effective.
Implicit Training of Virtual Agents
Authors: Anton Bogdanovych, Marc Esteva, Simeon Simoff, Carles Sierra
Venue: Proceedings of the 7th international conference on Intelligent Virtual Agents (2007)

This paper provides a brief overview of an implicit training method used for teaching autonomous agents to represent humans in 3D Virtual Worlds without any explicit training efforts being required.
Dynamically populating large urban environments with ambient virtual humans
Authors: M. Haciomeroglu
Venue: Computer Animation and Virtual Worlds (2008)

Creating an interactive simulation of a large urban environment populated with virtual humans poses a number of interesting challenges, ranging from how to initialise the virtual humans in the correct locations to maintaining a real-time simulation. When considering a large environment it is beneficial to investigate automatic techniques that create and simulate virtual humans using the available computing resources effectively. In this paper, two contributions towards the population of a large environment are described. The first presents two methods that use an automatic analysis of the urban environment to determine the required population densities throughout the scene. These methods ensure that the virtual humans are distributed such that main high streets consistently exhibit a higher number of virtual humans than other areas. The methods presented here achieve above 90% correlation to the predicted population densities for the environment, which outperforms the state of the art. The second contribution concerns the optimisation of the two methods to facilitate their applicability to large environments. The methods presented are modified to insert virtual humans dynamically into the behaviour system when required. The approach limits the required computing resources whilst achieving above 75% correlation to the predicted population values. Copyright &copy; 2008 John Wiley Sons, Ltd.
GrooveWrite: A Multi-purpose Stylus-Based Text Entry Method
Authors: Khaldoun Al Faraj, Mustapha Mojahid, Nadine Vigouroux
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

With the emergence of mobile computing devices such as Personal Digital Assistants (PDAs), a new challenge to design methods of interacting with them for people with disabilities has been created. In this paper, we propose GrooveWrite as a novel text entry system for handheld devices equipped with touch screen and stylus, targeted at people with situational and motor impairments. Based on traditional seven-segment layout, GrooveWrite interface is designed and implemented. The characters are entered by moving the stylus inside physical side-grooves, which are used as a stabilizer for stylus motion, and crossing the subset of segments that forms intended character. Character recognition neither considers the path of movement, nor recognition pattern, but only the subset of seven segments that is crossed. We examine our system theoretically using CLC model. This study shows that GrooveWrite text entry speed will be 24.78 words per minute.
Resolving Hidden Representations
Authors: Cheng-Yuan Liou, Wei-Chen Cheng
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

This paper presents a novel technique to separate the pattern representation in each hidden layer to facilitate many classification tasks. This technique requires that all patterns in the same class will have near representions and the patterns in different classes will have distant representions. This requirement is applied to any two data patterns to train a selected hidden layer of the MLP or the RNN. The MLP can be trained layer by layer feedforwardly to accomplish resolved representations. The trained MLP can serve as a kind of kernel functions for categorizing multiple classes.
Application of Undecimated Wavelet Transform to Surface Defect Detection of Hot Rolled Steel Plates
Authors: Xiu-yong Wu, Ke Xu, Jin-wu Xu
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

Characteristics of surface defects of hot rolled steel plates were analyzed, and an algorithm for detection of hot rolled steel plates was developed. Based on undecimated wavelet transform and mathematical morphology, the algorithm can solve the problem of false alarms by scales and water marks. Positions of defects were determined by modular maximum of inter-scale correlation of wavelet coefficient at first, and then the defects were classified with priori knowledge about characteristic of surface defects on hot rolled steel plates. Experimental results shows that the algorithm is not sensitive to disturbance of scales, water marks and uneven illumination, and the recognition rate of defects is up to 90.23%.
One-Time Password Access to Any Server without Changing the Server
Authors: Dinei Florêncio, Cormac Herley
Venue: Proceedings of the 11th international conference on Information Security (2008)

In this paper we describe a service that allows users one-time password access to any web account, without any change to the server, without changing anything on the client, and without storing user credentials in-the-cloud. The user pre-encrypts his password using an assigned set of keys and these encryptions are sent as one-time passwords to his cell phone or carried. To login he merely enters one of the encryptions as prompted, and the URRSA service decrypts before forwarding to the login server. Since credentials are not stored (the service merely decrypts and forwards) it has no need to authenticate users. Thus, while the user must trust the service, there are no additional passwords or secrets to remember. Since our system requires no server changes it can be used on a trust-appropriate basis: the user can login normally from trusted machines, but when roaming use one-time passwords. No installation of any software or alteration of any settings is required at the untrusted machine: the user merely requires access to a browser address bar.
A Message Oriented Middleware Solution Enabling Non-repudiation Evidence Generation for Reliable Web Services
Authors: Simon Parkin, David Ingham, Graham Morgan
Venue: Proceedings of the 4th international symposium on Service Availability (2007)

The paper describes an approach to providing reliable message passing together with mechanisms for enforcing non-repudiation for use by Web Services. In particular, we are concerned with message passing that occurs across organizational boundaries and evaluating the suitability of the Java Messaging Service in this approach.
Development of Online Inquiry Environments to Support Project-Based Learning of Robotics
Authors: Min Jou, Ming-Jenn Wu, Din-Wu Wu
Venue: Proceedings of the 1st world summit on The Knowledge Society: Emerging Technologies and Information Systems for the Knowledge Society (2008)

Robotics, an interdisciplinary engineering subject, has been a recurring theme in engineering education. Project-based learning provides opportunities for interdisciplinary learning. Thus, this research aims to develop interactive e-learning environments to support project-based learning of robotics and to enhance student participation, motivation, and learning effectiveness. This project developed inquiry modules to allow students to present their queries in natural Chinese language fashion and through engineering graphics. In addition, this study developed interactive learning platforms for robotic design including mechanism design, assembly and manipulation, manufacturing processes, and integration of mechatronics. Quantitative and qualitative methods such as questionnaires and interviews were used to evaluate the effects of the developed system. Findings showed that inquiry modules were able to facilitate investigation and planning activities on project developing stages. The results also showed that there were significant improvements in the participants' motivation and learning. Generally, the online interactive e-learning environment is beneficial to the participants and ought to be given the attention it deserves as an alternative to traditional classes.
From Cooperation to Cooperability
Authors: Walter Castelnovo
Venue: Proceedings of the 7th international conference on Electronic Government (2008)

In many countries of the European Union the system of Local Government is highly fragmented and characterized by the prevalence of small municipalities. By allowing the sharing of resources within an aggregation of municipalities, inter-municipal cooperation could be a solution for some of the problems related to administrative fragmentation. In the paper, after considering the conditions that make the sharing of different types of resources feasible, the concept of cooperability will be introduced in order to describe the non technical aspects of interoperability. Finally, it will be shown how an aggregation of cooperable Local Government organizations can carry out a process of virtual integration among the partners that can help reduce the fragmentation of the system of Local Government without resorting to a forced merger of municipalities.
A Case-Based Framework for Collaborative Semantic Search in Knowledge Sifter
Authors: Larry Kerschberg, Hanjo Jeong, Yong Uk Song, Wooju Kim
Venue: Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development (2007)

This paper addresses the role of case-based reasoning in semantic search, and in particular, as it applies to Knowledge Sifter, an agent-based ontology-driven search system based on Web services. The Knowledge Sifter architecture is extended to include a case-based methodology for collaborative semantic search, including case creation, indexing and retrieval services. A collaborative filtering methodology is presented that uses stored cases as a way to improve user query specification, refinement and processing.
The History of FORTRAN I, II and III
Authors: John Backus
Venue: IEEE Annals of the History of Computing (1979)

This article discusses attitudes about "automatic programming," the economics of programming, and existing programming systems, all in the early 1950s. It describes the formation of the FORTRAN group, its knowledge of existing systems, its plans for FORTRAN, and the development of the language in 1954. It describes the development of the optimizing compiler for FORTRAN I, of various language manuals, and of FORTRAN II and III. It concludes with remarks about later developments and the impact of FORTRAN and its successors on programming today.
Recommending Software Artifacts from Repository Transactions
Authors: Joern David
Venue: Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence (2008)

The central problem addressed by this interdisciplinary paper is to predict related software artifacts that are usually changed together by a developer. The working focus of programmers is revealed by means of their interactions with a software repository that receives a set of cohesive artifact changes within one commit transaction. This implicit knowledge of interdependent changes can be exploited in order to recommend likely further changes, given a set of already changed artifacts. We suggest a hybrid approach based on Latent Semantic Indexing (LSI) and machine learning methods to recommend software development artifacts, that is predicting a sequence of configuration items that were committed together. As opposed to related approaches to repository mining that are mostly based on symbolic methods like Association Rule Mining (ARM), our connectionist method is able to generalize onto unseen artifacts. Text analysis methods are employed to consider their textual attributes. We applied our technique to three publicly available datasets from the PROMISE Repository of Software Engineering Databases. The evaluation showed that the connectionist LSI-approach achieves a significantly higher recommendation accuracy than existing methods based on ARM. Even when generalizing onto unseen artifacts, our approach still provides an accuracy of up to 72.7% on the given datasets.
Computational Models of Neural Representations in the Human Brain
Authors: Tom M. Mitchell
Venue: Proceedings of the 19th international conference on Algorithmic Learning Theory (2008)

For many centuries scientists have wondered how the human brain represents thoughts in terms of the underlying biology of neural activity. Philosophers, linguists, cognitive scientists and others have proposed theories, for example suggesting that the brain organizes conceptual information in hierarchies of concepts, or that it instead represents different concepts in different local regions of the cortex.
Tile-Based Modeling and Rendering
Authors: Maki Terai, Jun Fujiki, Reiji Tsuruno, Kiyoshi Tomimatsu
Venue: Proceedings of the 8th international symposium on Smart Graphics (2007)

Generally, 2D computer graphics are suitable for depicting 2D structures. However, computer games generally depict 3D structures using 2D computer graphics. We are interested in such expression. As the overhead view has no 3D geometry data, a mechanism 3D geometry data from the overhead view is proposed. In addition, a tile-based technique for seamless conversion of a two-dimensional graphical expression into a three-dimensional geometric shape is proposed. In the proposed approach, an overhead 2D view defined by tiles on a canvas is converted into groups of 3D forms automatically and distorted according to an arbitrary viewing angle.The derivation and algorithm of the scheme are presented, and example applications are shown.
Handling out of domain topics by a conversational character
Authors: Manish Mehta, Andrea Corradini
Venue: Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts (2008)

Unlike traditional task-oriented dialog systems, one of the goals of conversational applications is to keep the user engaged and interested for as long as possible. This paper describes a technique that we implemented for dealing with the problem of out-of-domain topics and successfully integrated in a fully functional conversational system. In our approach, we exploit a simple and freely available coarsegrained ontology, namely Google's directory' structure, in order to automatically categorize unknown words and combines it with the existing ontological properties and dialog acts to create an automated semantic representation. We also resort to available web-based question and answering (QA) systems to generate answers to user's questions that are outside the domains covered by the application. Further, we make a first attempt at categorizing the retrieved information to generate appropriate non-verbal behaviors synced up with spoken utterances. The evaluation of the complete system shows promising results for the future and suggests that we are on the right track in terms of our approach for a better handling of out-of-domain topics.
Close Encounters with Boolean Functions of Three Different Kinds
Authors: Matthew G. Parker
Venue: Proceedings of the 2nd international Castle meeting on Coding Theory and Applications (2008)

Complex arrays with good aperiodic properties are characterised and it is shown how the joining of dimensions can generate sequences which retain the aperiodic properties of the parent array. For the case of 2 ×2 ×...×2 arrays we define two new notions of aperiodicity by exploiting a unitary matrix represention. In particular, we apply unitary rotations by members of a size-3 cyclic subgroup of the local Clifford group to the aperiodic description. It is shown how the three notions of aperiodicity relate naturally to the autocorrelations described by the action of the Heisenberg-Weyl group. Finally, after providing some cryptographic motivation for two of the three aperiodic descriptions, we devise new constructions for complementary pairs of Boolean functions of three different kinds, and give explicit examples for each.
Fast Background Subtraction Using Improved GMM and Graph Cut
Authors: Zhen Tang, Zhenjiang Miao
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

Background Subtraction is widely used to detect moving object from static background. In order to get good performance for practical application systems, the background subtraction method should not be too time and space consuming, and the accuracy is also required. Gaussian Mixture Model is a robust background subtraction method and has been widely used since it is proposed. Graph cut is a new algorithm developed to solve energy minimization problem and can be used to extract foreground object by constructing some appropriate energy functions. In this paper, an improved Gaussian Mixture Model is proposed to save time and space. And a new energy function is constructed for the graph cut. Space sampling is used to further accelerate the processing speed, so that it can be used in real-time applications. Shadow eliminating and noise removing method are also used to further improve the performance of the system. The experiment results demonstrate the efficiency of our method.
Multi-stage FCM-Based Intensity Inhomogeneity Correction for MR Brain Image Segmentation
Authors: László Szilágyi, Sándor M. Szilágyi, László Dávid, Zoltán Benyó
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

Intensity inhomogeneity or intensity non-uniformity (INU) is an undesired phenomenon that represents the main obstacle for MR image segmentation and registration methods. Various techniques have been proposed to eliminate or compensate the INU, most of which are embedded into clustering algorithms, and they generally have difficulties when INU reaches high amplitudes. This paper proposes a multiple stage fuzzy c-means (FCM) based algorithm for the estimation and compensation of INU, by modeling it as a slowly varying additive or multiplicative noise, supported by a pre-filtering technique for Gaussian and impulse noise elimination. The slowly varying behavior of the bias or gain field is assured by a smoothing filter that performs a context dependent averaging, based on a morphological criterion. The experiments using 2-D synthetic phantoms and real MR images show, that the proposed method provides accurate segmentation. The resulting segmentation and fuzzy membership values can serve as excellent support for 3-D registration and segmentation techniques.
Sequential Proximity-Based Clustering for Telecommunication Network Alarm Correlation
Authors: Yan Liu, Jing Zhang, Xin Meng, John Strassner
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

Alarm correlation for fault management in large telecommunication networks demands scalable and reliable algorithms. In this paper, we propose a clustering based alarm correlation approach using sequential proximity between alarms. We define two novel distance metrics appropriate for measuring similarity between alarm sequences obtained from interval-based division: 1) the two-digit binary metric that values the occurrences of two alarms in neighboring intervals to tolerate the false separation of alarms due to interval-based alarm sequence division, and 2) the sequential ordering-based distance metric that considers the time of arrival for different alarms within the same interval. We validate both metrics by applying them with hierarchical clustering using real-world cellular network alarm data. The efficacy of the proposed sequential proximity based alarm clustering is demonstrated through a comparative study with existing similarity metrics.