ppxscal/embedding_network huggingface dataset:
Low cost system for detecting leakages along artificial dikes with wireless sensor networks
Authors: Jens Schulz, Frank Reichenbach, Jan Blumenthal, Dirk Timmermann
Venue: Proceedings of the workshop on Real-world wireless sensor networks (2008)

Recently, the number of floods has been increased worldwide enormously. Especially, the damage along flooded rivers cannot be significantly avoided with current techniques. That leads to a high demand for new approaches to detect leakages in the dike body early. Therefore, we present our work in progress on developing a "Leakage Detection System" (LDS). After this system has been installed alongside a dike, it operates autonomously and alarms the headquarter if the water level exceeds a critical threshold. This allows rescue workers to strengthen drenched regions preemptively. Real world experiments in a reconstructed dike environment demonstrate the feasibility of our system approach.
Feature Ranking Ensembles for Facial Action Unit Classification
Authors: Terry Windeatt, Kaushala Dias
Venue: Proceedings of the 3rd IAPR workshop on Artificial Neural Networks in Pattern Recognition (2008)

Recursive Feature Elimination RFE combined with feature-ranking is an effective technique for eliminating irrelevant features. In this paper, an ensemble of MLP base classifiers with feature-ranking based on the magnitude of MLP weights is proposed. This approach is compared experimentally with other popular feature-ranking methods, and with a Support Vector Classifier SVC. Experimental results on natural benchmark data and on a problem in facial action unit classification demonstrate that the MLP ensemble is relatively insensitive to the feature-ranking method, and simple ranking methods perform as well as more sophisticated schemes. The results are interpreted with the assistance of bias/variance of 0/1 loss function.
ARUBA: A Risk-Utility-Based Algorithm for Data Disclosure
Authors: Mohamed R. Fouad, Guy Lebanon, Elisa Bertino
Venue: Proceedings of the 5th VLDB workshop on Secure Data Management (2008)

Dealing with sensitive data has been the focus of much of recent research. On one hand data disclosure may incur some risk due to security breaches, but on the other hand data sharing has many advantages. For example, revealing customer transactions at a grocery store may be beneficial when studying purchasing patterns and market demand. However, a potential misuse of the revealed information may be harmful due to privacy violations. In this paper we study the tradeoff between data disclosure and data retention. Specifically, we address the problem of minimizing the risk of data disclosure while maintaining its utility above a certain acceptable threshold. We formulate the problem as a discrete optimization problem and leverage the special monotonicity characteristics for both risk and utility to construct an efficient algorithm to solve it. Such an algorithm determines the optimal transformations that need to be performed on the microdata before it gets released. These optimal transformations take into account both the risk associated with data disclosure and the benefit of it (referred to as utility). Through extensive experimental studies we compare the performance of our proposed algorithm with other date disclosure algorithms in the literature in terms of risk, utility, and time. We show that our proposed framework outperforms other techniques for sensitive data disclosure.
Hopfield Neural Network and Boltzmann Machine Applied to Hardware Resource Distribution on Chips
Authors: F. Javier Sánchez Jurado, Matilde Santos Peñas
Venue: Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks (2007)

On chip resource distribution is a problem that, due to its complexity, is susceptible to be solved by using artificial intelligence optimization procedures. In this paper, a Hopfield recurrent neural network and a Boltzmann machine are proposed for searching good solutions.The main challenge of this approach is proposing an energy function to be minimized so it mixes all the problem-related restrictions.Experimental data shows that we can get good enough solutions in a reasonable time using Hopfield nets or close to the global minimum solutions using Boltzmann machines.
A Query Index for Stream Data Using Interval Skip Lists Exploiting Locality
Authors: Jun-Ki Min
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

To accelerate the query performance, diverse continuous que- ry index schemes have been proposed for stream data processing systems. In general, a stream query contains the range condition. Thus, by using range conditions, the queries are indexed. In this paper, we propose an efficient range query index scheme QUISIS using a modified Interval Skip Lists to accelerate search time. QUISIS utilizes a locality where a value which will arrive in near future is similar to the current value.
The Conception and Development of Parallel Processors: A Personal Memoir
Authors: D. L. Slotnick
Venue: IEEE Annals of the History of Computing (1982)

The circumstances surrounding the conception and development of centrally controlled array processors are described in this article. The time period involved, from 1953 to 1975, brackets the Westinghouse SOLOMON systems, their precursors, and the University of Illinois ILLIAC IV. Some reflections on past and possible future interplay between university and government laboratories on the one hand and industry on the other are made at the conclusion.
PANTO: A Portable Natural Language Interface to Ontologies
Authors: Chong Wang, Miao Xiong, Qi Zhou, Yong Yu
Venue: Proceedings of the 4th European conference on The Semantic Web: Research and Applications (2007)

Providing a natural language interface to ontologies will not only offer ordinary users the convenience of acquiring needed information from ontologies, but also expand the influence of ontologies and the semantic web consequently. This paper presents PANTO, a Portable nAtural laNguage inTerface to Ontologies, which accepts generic natural language queries and outputs SPARQL queries. Based on a special consideration on nominal phrases, it adopts a triple-based data model to interpret the parse trees output by an off-the-shelf parser. Complex modifications in natural language queries such as negations, superlative and comparative are investigated. The experiments have shown that PANTO provides state-of-the-art results.
E-government and its application in the Republic of Croatia
Authors: Mario Spremic, Hrvoje Brzica
Venue: Proceedings of the 7th WSEAS International Conference on Applied Computer and Applied Computational Science (2008)

Information and communication technologies (ICTs) were recognized to have tremendous 'administrative' potential. For example, ICTs may help create a networked structure for interconnectivity (McClure, 2000), service delivery (Bekkers and Zouridis, 1999), efficiency and effectiveness (Heeks, 2001), interactivity (DiCaterino and Pardo, 1996), decentralization, transparency (Layne and Lee, 2001) and accountability (McGregor, 2001). Electronic government (e-government) cover all these functions and, generally speaking, refers to the intensive use of ICT in providing the citizens an improved access to information related to public administrations as well as in providing them superb service quality. E-government is defined as 'utilizing the Internet and the world-wide-web for delivering government information and services to citizens' (UN & ASPA, 2001). Jaeger (2003) added that, apart from Internet and web, it may also include other ICTs in providing superb governmental information services to the citizens (examples are database, networking, discussion support, automation, tracking, personal identification technologies). Means and Schneider (2000) define e-government as the relationships between governments, their customers and their suppliers by the use of electronic means. In this paper we give a brief review of e-government concept and its application in the Republic Croatia. E-government services and applications may positively affect the development of the Croatian emerging economy, as Croatia, even the EU candidate state, is still a country in transition. The review and discussion of current and future progressive e-government services and their impact on society and economy are given in the paper. The case studies results and analysis came up with the conclusion that efficient e-services my positively affect the transparency of various systems in Croatia such as justice, public procurement, health, etc.
Context-Aware Middleware for Resource Management in the Wireless Internet
Authors: Paolo Bellavista, Antonio Corradi, Rebecca Montanari, Cesare Stefanelli
Venue: IEEE Transactions on Software Engineering (2003)

The provisioning of Web services over the wireless Internet introduces novel challenging issues for service design and implementation: from user/terminal mobility during service execution, to wide heterogeneity of portable access devices and unpredictable modifications in accessible resources. In this scenario, there are frequent provision-time changes in the context, defined as the logical set of accessible resources depending on client location, access terminal capabilities, and system/service management policies. The development of context-dependent services requires novel middlewares with full context visibility. We propose a middleware for context-aware resource management, called CARMEN, capable of supporting the automatic reconfiguration of wireless Internet services in response to context changes without any intervention on the service logic. CARMEN determines the context on the basis of metadata, which include declarative management policies and profiles for user preferences, terminal capabilities, and resource characteristics. In addition, CARMEN exploits the mobile agent technology to implement mobile middleware components that follow the provision-time movement of clients to support locally their customized service access. The proposed middleware shows how metadata and mobile agents can favor component reusability and automatic service reconfiguration, by reducing the development/deployment complexity.
Traffic Signal Timing with Neural Dynamic Optimization
Authors: Jing Xu, Wen-Sheng Yu, Jian-Qiang Yi, Zhi-Shou Tu
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

With the discrete traffic model of an oversaturated intersection, the technique of neural dynamic optimization is used to approximate the optimal signal timing strategy which can lead the minimal delay time while considering the whole congestion period. Our approach can provide an approximation of the optimal timing split in each cycle, as well as the most reasonable number of cycles for specific oversaturated traffic inflows. Specifically, for the two-phase case, we are interested to find that the optimal timing strategy is a bang-bang like control instead of a strict bang-bang one as proposed in relative literature. Moreover, our approach is evaluated with a general four-phase case, and its optimal strategy appears also to be a bang-bang like control, which may illuminate the traffic signal timing in practice.
Early History and Perspectives of Automated Deduction
Authors: Wolfgang Bibel
Venue: Proceedings of the 30th annual German conference on Advances in Artificial Intelligence (2007)

With this talk we want to pay tribute to the late Professor Gerd Veenker who deserves the historic credit of initiating the formation of the German AI community. We present a summary of his scientific contributions in the context of the early approaches to theorem proving and, against this background, we point out future perspectives of Automated Deduction.
Energy aware task scheduling on heterogeneous systems
Authors: Sanjeev Baskiyar
Venue:  (2007)

We consider the problem of scheduling directed a-cyclic task graphs (DAG) on heterogeneous distributed processor systems with the twin objectives of minimizing finish time and energy consumption. Previous scheduling heuristics have assigned DAGs to processors to minimize overall run-time of applications. But due to many new applications on embedded systems such as high performance DSP in image processing, multimedia, and wireless security, there is a strong need for scheduling algorithms which lower energy consumption and yet attain good finish times. In this research, we employ dynamic voltage scaling (DVS) within the scheduling heuristics to achieve the twin objectives. The processors used can run on different discrete operating voltages. Processors can scale down their voltages to slow down in order to reduce energy consumption whenever they idle due to task dependencies. Specifically, we combine Decisive Path Scheduling (DPS) and Heterogeneous N-predecessor Duplication (HNPD) with DVS. Using simulations, we show average energy consumption reductions of 40% over DPS and 28% over HNPD. The simulations used large number of randomly generated DAGs with various characteristics as well as DAGs of real world problems. Energy savings increased with increasing number of nodes or increasing Communication to Computation Ratios (CCR) whereas it decreased with increasing parallelism (out-degree) or increasing number of available processors. Increasing nodes, increase tasks dependencies and thus idle times. When CCR increases, processors are idle longer due to communication between tasks. Our algorithms used such idle times to achieve energy savings. An increase in out-degree resulted in smaller average energy savings. A larger out-degree allows more processors to run in parallel, reducing idle times.
An Overview of the Ciao Multiparadigm Language and Program Development Environment and Its Design Philosophy
Authors: Manuel V. Hermenegildo, Francisco Bueno, Manuel Carro, Pedro López, José F. Morales, German Puebla
Venue: Concurrency, Graphs and Models: Essays Dedicated to Ugo Montanari on the Occasion of His 65th Birthday (2008)

We describe some of the novel aspects and motivations behind the design and implementation of the Ciao multiparadigm programming system. An important aspect of Ciao is that it provides the programmer with a large number of useful features from different programming paradigms and styles, and that the use of each of these features can be turned on and off at will for each program module. Thus, a given module may be using e.g. higher order functions and constraints, while another module may be using objects, predicates, and concurrency. Furthermore, the language is designed to be extensible in a simple and modular way. Another important aspect of Ciao is its programming environment, which provides a powerful preprocessor (with an associated assertion language) capable of statically finding non-trivial bugs, verifying that programs comply with specifications, and performing many types of program optimizations. Such optimizations produce code that is highly competitive with other dynamic languages or, when the highest levels of optimization are used, even that of static languages, all while retaining the interactive development environment of a dynamic language. The environment also includes a powerful auto-documenter. The paper provides an informal overview of the language and program development environment. It aims at illustrating the design philosophy rather than at being exhaustive, which would be impossible in the format of a paper, pointing instead to the existing literature on the system.
Towards a Clinical Decision Support System for Pregnancies of Unknown Location
Authors: Ben Van Calster, Sabine Van Huffel, Dirk Timmerman, Emma Kirk, Tom Bourne, George Condous
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

This paper presents our activities towards the development of a clinical decision support (CDS) system for the early diagnosis of pregnancies of unknown location (PULs). PULs are pregnancies that are not visualized on ultrasound. Generally, they turn out to be failing, normal intra-uterine, or ectopic pregnancies. Using 856 PULs collected at a London hospital, we developed probabilistic multi-class models. At the moment, a large multi-center data set is being collected. Data are entered using stand-alone software, and are sent to the database server by ftp. These data will be used to prospectively test existing models, and to build new, hopefully more robust, models. The ultimate aim is to select one model for implementation in a CDS system that is easy to use in routine clinical practice.
SepRep: A Novel Reputation Evaluation Model in Peer-to-Peer Networks
Authors: Xiaowei Chen, Kaiyong Zhao, Xiaowen Chu
Venue: Proceedings of the 5th international conference on Autonomic and Trusted Computing (2008)

In a heterogeneous peer-to-peer network, different peers provide different qualities of service. It will be very helpful if a peer can identify which peers can provide better services than others. In this paper, we design a novel reputation model which enables any peer to calculate a reputation value for any other peer that reflects the quality of service provided by that peer, so as to differentiate peers providing good quality of service from those peers providing poor service. Furthermore, to overcome the problem of malicious recommenda-tions, we propose an auxiliary trust mechanism which calculates a trust value for each peer. Experimental results show that our reputation model achieves a fast convergence speed, and it is also robust against a large portion of malicious peers that provide fraud recommendations.
Model Synchronisation: Definitions for Round-Trip Engineering
Authors: Thomas Hettel, Michael Lawley, Kerry Raymond
Venue: Proceedings of the 1st international conference on Theory and Practice of Model Transformations (2008)

In a model-centric software development environment, a multitude of different models are used to describe a software system on different abstraction layers and from different perspectives. Following the MDA vision, model transformation is used to support the gradual refinement from abstract models into more concrete models. However, target models do not stay untouched but may be changed due to maintenance work or evolution of the software. Therefore, in order to preserve a coherent description of the whole system, it is necessary to propagate certain changes to a target model back to the source model. However, as transformations in general are partial and not injective, they cannot be easily reversed to propagate changes. This paper presents a formal definition of round-trip engineering and the semantics of target changes in the context of partial and non-injective transformations.
Real-Time News Event Extraction for Global Crisis Monitoring
Authors: Hristo Tanev, Jakub Piskorski, Martin Atkinson
Venue: Proceedings of the 13th international conference on Natural Language and Information Systems: Applications of Natural Language to Information Systems (2008)

This paper presents a real-time news event extraction system developed by the Joint Research Centre of the European Commission. It is capable of accurately and efficiently extracting violent and disaster events from online news without using much linguistic sophistication. In particular, in our linguistically relatively lightweight approach to event extraction, clustered news have been heavily exploited at various stages of processing. The paper describes the system's architecture, news geo-tagging, automatic pattern learning, pattern specification language, information aggregation, the issues of integrating event information in a global crisis monitoring system and new experimental evaluation.
Experiments in Classification Clustering and Thesaurus Expansion for Domain Specific Cross-Language Retrieval
Authors: Ray R. Larson
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)

In this paper we will describe Berkeley's approach to the Domain Specific (DS) track for CLEF 2007. This year we are using forms of the Entry Vocabulary Indexes and Thesaurus expansion approaches used by Berkeley in 2005[7]. Despite the basic similarity of approach, we are using quite different implementations with different characteristics. We are not, however, using the tools for de-compounding for German. All of the runs submitted were performed using the Cheshire II system. This year Berkeley submitted a total of 24 runs, including one for each subtask of the DS track. These include 6 Monolingual runs for English, German, and Russian, 12 Bilingual runs (4 X2EN, 4 X2DE, and 4 X2RU), and 6 Multilingual runs (2 EN, 2 DE, and 2 RU).
Proprioceptive Motion Modeling for Monte Carlo Localization
Authors: Jan Hoffmann
Venue: RoboCup 2006: Robot Soccer World Cup X (2006)

This paper explores how robot localization can be improved and made more reactive by using an adaptive motion model based on proprioception. The motion model of mobile robots is commonly assumed to be constant or a function of the robot speed. We extend this model by explicitly modeling possible states of locomotion caused by interactions of the robot with its environment, such as collisions. The motion model thus behaves according to which state the robot is in. State transitions are based on proprioception, which in our case describes how well the robot's limbs are able to follow their respective motor commands. The extended, adaptive motion model yields a better, more reactive model of the current robot belief, which is shown in experiments. The improvement is due to the fact that the motion noise no longer has to subsume any possible outcome of actions including failure. In contrast, a clear distinction between failure and normal, desired operation is possible, which is reflected in the motion model.
Mobile components security
Authors: Benjamin Arazi
Venue: Proceedings of the 4th annual workshop on Cyber security and information intelligence research: developing strategies to meet the cyber security and information intelligence challenges ahead (2008)

Secure communications among mobile components, like wireless sensors and RFID tags, emerge as a fundamental branch of network security, needing message confidentiality, integrity and authentication. That is: protecting the content of transmitted information, assuring that it was not altered during transmission, and proving that it was sent by an approved identified source. Object integrity is another very relevant security application. Here, the purpose is to prove that an object, having storage and transmission facilities, is not cloned. We treat the hardware implementation of security measures in mobile components while considering two major issues: Resource constraints: Such components operate under highly constrained conditions, posing a demand for minimal logic hardware while providing for approved and recognized security level. Memory security: Wireless Sensors and RFID tags are deployed in hostile environments, enhancing a need for tamper-proof storage of their secret keys. The contribution of the paper is 3-fold: -- We present a novel approach to hardware minimization, serving message security while relying on approved security levels.- We show that memory security is not merely a physical problem, apparently independent of the served applications. This observation can be made general. -- Attention is devoted to recently announced logic gates fabrication techniques, and their relation to the devised approach, as well as their potential contribution to general security applications.