ppxscal/embedding_network huggingface dataset:
Analysis and Synthesis of the Current Situation in IT Security
Authors: Constantine A. Kalentis
Venue: Proceedings of the 2008 Panhellenic Conference on Informatics (2008)

The article presents a survey undertaken from medium - large scale organizations and focuses on specific concerns of the top level executives working for modern organizations in Greece and Cyprus. Through the survey we explore what decision makers think, when they consider security policies, methodologies and countermeasures. Through the process of analyzing the survey results, some very important aspects have come out. The research has been based on classic managerial research methods, in order to analyze and synthesize at a higher level, how the top managers face the challenge of the raising volume of threats and problems and organizational weaknesses.
A Parallel Hardware Architecture for Image Feature Detection
Authors: Vanderlei Bonato, Eduardo Marques, George A. Constantinides
Venue: Proceedings of the 4th international workshop on Reconfigurable Computing: Architectures, Tools and Applications (2008)

This paper presents a real time parallel hardware architecture for image feature detection based on the SIFT (Scale Invariant Feature Transform) algorithm. This architecture receives as input a pixel stream read directly from a CMOS image sensor and produces as output the detected features, where each one is identified by their coordinates, scale and octave. In addition, the proposed hardware also computes the orientation and gradient magnitude for every pixel of one image per octave, which is useful to generate the feature descriptors. This work also presents a suitable parameter set for hardware implementation of the SIFT algorithm and proposes specific hardware optimizations considered fundamental to embed whole system on a single chip, which implements in parallel 18 Gaussian filters, a modified CORDIC (COordinate Rotation DIgital Computer) algorithm version and a considerable number of fixed-point operations, such as those involved in a matrix inversion operation. As a result, the whole architecture is able to process up to 30 frames per second for images of 320×240 pixels independent of the number of features.
Towards a Model Independent Method for Explaining Classification for Individual Instances
Authors: Erik Štrumbelj, Igor Kononenko
Venue: Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery (2008)

Recently, a method for explaining the model's decision for an instance was introduced by Robnik-Šikonja and Kononenko. It is a rare example of a model-independent explanation method. In this paper we make a step towards formalization of the model-independent explanation methods by defining the criteria and a testing environment for such methods. We extensively test the aforementioned method and its variations. The results confirm some of the qualities of the original method as well as expose several of its shortcomings. We propose a new method, based on attribute interactions, that overcomes the shortcomings of the original method and serves as a theoretical framework for further work.
Handling Control Data Flow Graphs for a Tightly Coupled Reconfigurable Accelerator
Authors: Hamid Noori, Farhad Mehdipour, Morteza Saheb Zamani, Koji Inoue, Kazuaki Murakami
Venue: Proceedings of the 3rd international conference on Embedded Software and Systems (2007)

In an embedded system including a base processor integrated with a tightly coupled accelerator, extracting frequently executed portions of the code (hot portion) and executing their corresponding data flow graph (DFG) on the accelerator brings about more speedup. In this paper, we intend to present our motivations for handling control instructions in DFGs and extending them to Control DFGs (CDFGs). In addition, basic requirements for an accelerator with conditional execution support are proposed. Moreover, some algorithms are presented for temporal partitioning of CDFGs considering the target accelerator architectural specifications. To show the effectiveness of the proposed ideas, we applied them to the accelerator of an extensible processor called AMBER. Experimental results represent the effectiveness of covering control instructions and using CDFGs versus DFGs.
Mining Sequential Patterns with Negative Conclusions
Authors: Przemysław Kazienko
Venue: Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery (2008)

The new type of patterns: sequential patterns with the negative conclusions is proposed in the paper. They denote that a certain set of items does not occur after a regular frequent sequence. Some experimental results and the SPAWN algorithm for mining sequential patterns with the negative conclusions are also presented.
An Efficient Heterogeneous Wireless Access Based on Region and Time Partitioning in D-TDD OFDM Systems
Authors: Nak-Myeong Kim, Hee-Jeong Chung, Mee-Ran Kim, Hye-In Yu
Venue: Proceedings of the 5th international conference on Wired/Wireless Internet Communications (2007)

Under dynamic time division duplexing (D-TDD) architecture in OFDM cellular systems, the inter-BS and inter-MS interference is inevitable during the cross time slot (CTS) period, and this interference seriously degrades the wireless access system performance. To mitigate such interference, we propose a region and time partitioning D-TDD architecture for OFDM systems. Each time slot in the CTS period is split into several minislots, and then each cell is divided into as many regions as the number of minislots per time slot. We then assign each minislot only to the users in its corresponding region. On top of such architecture, which inherently separates interfering entities farther from each other, we design a robust time slot allocation scheme considering the channel status of each mobile station. By computer simulation, it has been verified that the proposed scheme outperforms conventional time slot allocation methods in both the outage probability and the bandwidth efficiency.
Engineering Tree Labeling Schemes: A Case Study on Least Common Ancestors
Authors: Saverio Caminiti, Irene Finocchi, Rossella Petreschi
Venue: Proceedings of the 16th annual European symposium on Algorithms (2008)

We address the problem of labeling the nodes of a tree such that one can determine the identifier of the least common ancestor of any two nodes by looking only at their labels. This problem has application in routing and in distributed computing in peer-to-peer networks. A labeling scheme using ¿(log2 n)-bit labels has been previously presented by Peleg. By engineering this scheme, we obtain a variety of data structures with the same asymptotic performances. We conduct a thorough experimental evaluation of all these data structures. Our results clearly show which variants achieve the best performances in terms of space usage, construction time, and query time.
Tight Bounds for Connecting Sites Across Barriers
Authors: David Krumme, Eynat Rafalin, Diane L. Souvaine, Csaba D. T&#x00f3;th
Venue: Discrete Computational Geometry (2008)

Given m points (sites) and n obstacles (barriers) in the plane, we address the problem of finding a straight line minimum cost spanning tree on the sites, where the cost is proportional to the number of intersections (crossings) between tree edges and barriers. If the barriers are infinite lines, it is known that there is a spanning tree such that every barrier is crossed by $O(\sqrt{m}\,)$tree edges, and this bound is asymptotically optimal. Asano et&#x00a0;al. showed that if the barriers are pairwise disjoint line segments, then there is a spanning tree such that every barrier crosses at most 4 tree edges and so the total cost is at most&#x00a0;4n. Lower bound constructions are known with&#x00a0;3 crossings per barrier and 2n total cost. We obtain tight bounds on the minimum cost of spanning trees in the special case where the barriers are interior disjoint line segments that form a convex subdivision of the plane and there is a point in every cell of the subdivision. In particular, we show that there is a spanning tree such that every barrier crosses at most 2 tree edges, and there is a spanning tree of total cost 5n/3. Both bounds are the best possible.
Reliable and Scalable State Management Using Migration of State Information in Web Services
Authors: Jongbae Moon, Hyungil Park, Myungho Kim
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

The WS-Resource framework (WSRF) was proposed as a reengineering and evolution of OGSI to be compatible with the current Web services conventions and specifications. Although WSRF separates state management from the stateless web service and provides a mechanism for state management, it still has some limitations. The tight-coupling between web services and their resource factories restricts the scalability. When the repository of stateful resources fails, stateful web services can not work. In this paper, we propose a new state management framework which is called State Management Web Service Framework (SMWSF) and implemented on Microsoft .NET framework. SMWSF provides reliability, flexibility, scalability, and security. SMWSF provides migration of state information and the service requestor can control the location of the repository of stateful resource. We also implemented a prototype system and conducted comparison experiments to evaluate performance.
Coordination Without Negotiation in Teams of Heterogeneous Robots
Authors: Michael Isik, Freek Stulp, Gerd Mayer, Hans Utz
Venue: RoboCup 2006: Robot Soccer World Cup X (2006)

A key feature of human cooperation is that we can coordinate well without communication or negotiation. We achieve this by anticipating the intentions and actions of others, and adapting our own actions to them accordingly. In contrast, most multi-robot systems rely on extensive communication to exchange their intentions.This paper describes the joint approach of our two research groups to enable a heterogeneous team of robots to coordinate implicitly, without negotiation. We apply implicit coordination to a typical coordination task from robotic soccer: regaining ball possession. We discuss the benefits and drawbacks of implicit coordination, and evaluate it by conducting several experiments with our robotic soccer teams.
Automated Multi-Camera Surveillance: Algorithms and Practice, 1 edition
Authors: Omar Javed, Mubarak Shah
Venue:  (2008)

The deployment of surveillance systems has captured the interest of both the research and the industrial worlds in recent years. The aim of this effort is to increase security and safety in several application domains such as national security, home and bank safety, traffic monitoring and navigation, tourism, and military applications. The video surveillance systems currently in use share one feature: A human operator must monitor them at all times, thus limiting the number of cameras and the area under surveillance and increasing cost. A more advantageous system would have continuous active warning capabilities, able to alert security officials during or even before the happening of a crime. Existing automated surveillance systems can be classified into categories according to: The environment they are primarily designed to observe; The number of sensors that the automated surveillance system can handle; The mobility of sensor. The primary concern of this book is surveillance in an outdoor urban setting, where it is not possible for a single camera to observe the complete area of interest. Multiple cameras are required to observe such large environments. This book discusses and proposes techniques for development of an automated multi-camera surveillance system for outdoor environments, while identifying the important issues that a system needs to cope with in realistic surveillance scenarios. The goal of the research presented in this book is to build systems that can deal effectively with these realistic surveillance needs.
Empirical Analysis of Reliability Estimates for Individual Regression Predictions
Authors: Zoran Bosnić, Igor Kononenko
Venue: Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery (2008)

In machine learning, the reliability estimates for individual predictions provide more information about individual prediction error than the average accuracy of predictive model (e.g. relative mean squared error). Such reliability estimates may represent a decisive information in the risk-sensitive applications of machine learning (e.g. medicine, engineering, business), where they enable the users to distinguish between better and worse predictions. In this paper, we compare the sensitivity-based reliability estimates, developed in our previous work, with four other approaches, proposed or inspired by the ideas from the related work. The results, obtained using 5 regression models, indicate the potentials for the usage of the sensitivity-based and the local modeling approach, especially with the regression trees.
Hardware Implementation of Moment Functions in a CMOS Retina: Application to Pattern Recognition
Authors: Olivier Aubreton, Lew Fock Lew Yan Voon, Matthieu Nongaillard, Guy Cathebras, Cédric Lemaitre, Bernard Lamalle
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I (2007)

We present in this paper a method for implementing moment functions in a CMOS retina for object localization, and pattern recognition and classification applications. The method is based on the use of binary patterns and it allows the computation of different moment functions such as geometric and Zernike moments of any orders by an adequate choice of the binary patterns. The advantages of the method over other methods described in the literature are that it is particularly suitable for the design of a programmable retina circuit where moment functions of different orders are obtained by simply loading the correct binary patterns into the memory devices implemented on the circuit. The moment values computed by the method are approximate values, but we have verified that in spite of the errors the approximate values are significant enough to be applied to classical shape localization and shape representation and description applications.
On Race Vulnerabilities in Web Applications
Authors: Roberto Paleari, Davide Marrone, Danilo Bruschi, Mattia Monga
Venue: Proceedings of the 5th international conference on Detection of Intrusions and Malware, and Vulnerability Assessment (2008)

A web programmer often conceives its application as a sequential entity, thus neglecting the parallel nature of the underlying execution environment. In this environment, multiple instances of the same sequential code can be concurrently executed. From such unexpected parallel execution of intended sequential code, some unforeseen interactions could arise that may alter the original semantic of the application as it was intended by the programmer. Such interactions are usually known as race conditions.In this paper, we discuss the impact of race condition vulnerabilities on web-based applications. In particular, we focus on those race conditions that could arise because of the interaction between a web application and an underlying relational database. We introduce a dynamic detection method that, during our experiments, led to the identification of several race condition vulnerabilities even in mature open-source projects.
Accessing the Distributed Learner Profile in the Semantic Web
Authors: Mourad Ouziri
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part I (2008)

Adaptive e-learning systems need to get complete learner profile to make efficient personalization. However, learner profile is dispersed over multiple heterogeneous e-learning systems. Unfortunately, these e-learning systems are heterogeneous what makes difficult to get complete learner profile. By using semantic web technology, namely Topic Maps, we show how we perform integration of heterogeneous fragments of learner profile to get more complete one. However, this technology does not consider constraints and is not able to make reasoning. So we use, together with Topic Maps, Description Logics to represent constraints and make reasoning over integrated data.
Weighted Order Statistic Filters for Pattern Detection
Authors: Slawomir Skoneczny, Dominik Cieslik
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

In this paper we propose a method of using Weighted Order Statistic (WOS) filters for the task of pattern detection. Usually WOS filters are applied to noise removal. An efficient algorithm for pattern detection is described in details with emphasis put on the problem of a proper choice of filter windows. Also practical results of different pattern detection cases are presented.
Systematic Performance Analysis of SART as Applied to Digital Breast Tomosynthesis
Authors: Dominique Sompel, Michael Brady
Venue: Proceedings of the 9th international workshop on Digital Mammography (2008)

Breast tomosynthesis reconstructions require a wide range of design choices to be made in order to yield consistently good results. Since algebraic reconstruction, specifically the SART algorithm, has given excellent results in CT and is being actively considered for commercial use in tomosynthesis, we in this study systematically vary a number of key imaging parameters and assess the performance of the SART algorithm under these variations. The phantoms used are basic ellipsoids in 2D (yielding analytical projections), and an MR-derived breast phantom in 3D.
A hybrid noise canceling structure with secondary path estimation
Authors: Andres Romero, Mariko Nakano-Miyatake, Hector Perez-Meana
Venue: Proceedings of the 7th WSEAS International Conference on Applied Computer and Applied Computational Science (2008)

This paper proposes a hybrid active noise canceling (ANC) system to reduce the distortion produced by the acoustic feedback present in most feed-forward ANC systems. Proposed ANC system provides a solution of two important problems present in ANC systems the acoustic feedback and the secondary path estimation. The acoustic feedback is reduced by using two adaptive ANC, one with a feed-forward and the other one feedback configuration, respectively. For secondary path modeling modification of the on line methods proposed by Bao, Erickson and Zhang are used. Computer simulation results show that the combination of the Feedback and Feed-forward stages provides a fairly good acoustic feedback cancellation, while the secondary path estimation method performs fairly well, specially using the Zhang method, providing a fairly good noise cancellation performance.
Tracking control for nonholonomic mobile robots: Integrating the analog neural network into the backstepping technique
Authors: Jun Ye
Venue: Neurocomputing (2008)

This paper proposes an improved learning algorithm of analog compound orthogonal networks and a novel tracking control approach for nonholonomic mobile robots by integrating the neural network into the backstepping technique. The adaptive control is derived from continuously tuning parameters using the analog neural network in the backstepping control law. The proposed control approach for the mobile robot has the properties to quickly drive the position error to zero and to indicate better smooth movement in the tracking control process. These features are due to continuous online learning and adaptive capability of analog neural networks. Simulation results demonstrate that the proposed control approach is effective and has better control performance.
On Characteristic Constants of Theories Defined by Kolmogorov Complexity
Authors: Shingo Ibuka, Makoto Kikuchi, Hirotaka Kikyo
Venue: Proceedings of the 15th international workshop on Logic, Language, Information and Computation (2008)

Chaitin discovered that for each formal system T, there exists a constant c such that no sentence of the form K(x) > c is provable in T, where K(x) is the Kolmogorov complexity of x. We call the minimum such c the Chaitin characteristic constant of T, or c T . There have been discussions about whether it represents the information content or strength of T. Raatikainen tried to reveal the true source of c T , stating that it is determined by the smallest index of Turing machine which does not halt but we cannot prove this fact in T. We call the index the Raatikainen characteristic constant of T, denoted by r T . We show that r T does not necessarily coincide with c T ; for two arithmetical theories T, T¿ with a ¿ 1-sentence provable in T¿ but not in T, there is an enumeration of the Turing machines such that r T < r T¿ and c T = c T¿ .
OntoAlbum: An Ontology Based Digital Photo Management System
Authors: Yan-Mei Chai, Xiao-Yan Zhu, Jing-Ping Jia
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

This paper presents a prototype system that helps users manage and search collections of their digital photos. Existing systems and methods suffer from some shortcomings. For example, the visual similarity based search has poor precision and lacks for semantic information, while the text-based retrieval is only lexically motivated and those lexicons are not organized well. In one word, systems that really support intelligent retrieval are rare. In order to overcome these shortcomings, an ontology based approach is proposed for photo management, which is conceptual motivated. The approach is implemented in the OntoAlbum system. When a photo is imported into the database, the system automatically creates an instance of it. Then the user annotates the photo with concepts of ontology. Finally, by clicking on an instance of concepts in the ontology, the user can find all the photos related to the instance through ontology inference. Ontology provides a formal, explicit and conceptual annotation as well as an effective inference query. It makes intelligent retrieval possible in the photo management system. Experiments on the OntoAlbum system show that the proposed approach is very effective and promising.
Protection Techniques of Secret Information in Non-tamper Proof Devices of Smart Home Network
Authors: Abedelaziz Mohaisen, Youngjae Maeng, Joenil Kang, Daehun Nyang, Kyunghee Lee, Dowon Hong, Jongwook Han
Venue: Proceedings of the 5th international conference on Ubiquitous Intelligence and Computing (2008)

The problem of revealing secret information in home network becomes critical when a physical capture of single device or more happen where the attacker can statically analyze the entire device's memory. While the trusted platform module that assumes a tamper proof chip in each device is not a choice, we investigate other software-based solutions. This paper introduces several mechanisms and schemes in varying scenarios for secret information protection in non-tamper proof devices of the smart home environment. The mechanisms provided herein utilize the existence of several algorithms and techniques and building blocks that do not require an extra hardware while they are computation efficient on the typical home network devices. To demonstrate the value of contributions, an extensive analysis for different scenarios including security and cost estimations are provided.
Learning Structurally Analogous Tasks
Authors: Paul W. Munro
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

A method for training overlapping feedforward networks on analogous tasks is extended and analyzed. The learning dynamics of simultaneous (interlaced) training of similar tasks interact at the shared connections of the networks. The influence of one task on the other can be studied by examining the output of one network in response to a stimulus to the other network. Using backpropagation to train networks with shared hidden layers, a "crosstraining" mechanism for specifying corresponding components between structurally similar environments is introduced. Analysis of the resulting mappings reveals the potential for analogical inference.