ppxscal/embedding_network huggingface dataset:
Searching for information on occupational accidents
Authors: Philip J. Smith
Venue:  (2008)

Effective retrieval of the most relevant documents on the topic of interest from the Internet is difficult due to the large amount of information in all types of formats. Studies have been conducted on ways to improve information retrieval (IR). One approach to improve searches in large collections, such as the Web, is to take advantage of semantic representations in pre-existing relational databases that have been developed for explicit purposes besides supporting Internet searches in general. In an effort to enhance IR on the Internet, a prototype of a topic-oriented search agent, SAOA-1, was developed to use embedded semantics and domain-specific knowledge extracted from such a database. Activated when a set of retrieved keywords appears related to the topic of &ldquo;occupational accidents&rdquo;, SAOA-1 constructs an alternative search query and pruned lists of suggested refinements by applying the search engine knowledge and the domain-specific knowledge and semantics extracted from a relational database. Information seekers could then use the alternative search query or refine it further with a modified search query developed by SAOA-1 based on its semantic representation of the topic of occupational accidents to complete context-sensitive pruning of the semantic neighborhood. An empirical study was conducted to evaluate the usefulness of SAOA-1 in assisting information seekers to retrieve relevant documents. Sixty participants were randomly assigned to one of two treatments: with or without the assistance of SAOA-1, to perform Internet searches. Prior to performing searches, each participant had to decide upon a topic based on two given articles addressing hand injuries in the workplace. The participants then performed searches and, when satisfied with the results, evaluated the relevance of the first forty documents of their final search to their research topics on a 1-to-5 scale Likert scale. It was hypothesized that the treatment type could have an overall effect on expected rating. Based on the data collected, the average expecting rating was statistically significant (p < 0.001) with a slight improvement of 10% due to the treatment. From a practical perspective, however, the size of the effect was modest. The findings suggest that a topic-oriented search agent might be useful in assisting information seekers to retrieve more relevant documents but suggest important directions for further evaluating methods and settings for taking advantage of such semantically-based search techniques.
On the use of service oriented architectures for intelligent vehicle research and development
Authors: Mong Leng Sin, Mélanie Bouroche, Vinny Cahill
Venue: Proceedings of the 1st International Workshop on Context-Aware Middleware and Services: affiliated with the 4th International Conference on Communication System Software and Middleware (COMSWARE 2009) (2009)

Intelligent vehicles travelling on roads at high speed safely utilising sensors and communication can save time and protect lives. Influenced by the DARPA Grand Challenge and various other Intelligent Transportation System initiatives, new research results are being produced at an amazingly fast pace. The high rate of new technologies being introduced (e.g. hardware, control algorithms and behavioural sciences) presents an ever changing environment, placing the best software and system designs to the test. In this paper, we consider the use of a Service Oriented Architecture (SOA) as the basis of a system architecture for our research and developmental efforts in intelligent vehicles to allow us to exploit this evolving environment. We investigate whether this is a useful paradigm for this domain, and how it can be used. In particular, we introduce the abstractions of our intelligent vehicle design and show how this abstraction integrates with our previous work.
Performance Evaluation of Fast Startup Congestion Control Schemes
Authors: Michael Scharf
Venue: Proceedings of the 8th International IFIP-TC 6 Networking Conference (2009)

The Transmission Control Protocol (TCP) uses the Slow-Start mechanism at the beginning of a connection and after idle times. The Slow-Start delays the transport of data in particular if the round-trip time is large, which is undesirable for interactive applications. In order to speed up transfers, several alternatives have been proposed recently. This paper evaluates the performance and robustness of new fast startup congestion control schemes. We compare both end-to-end approaches as well as protocols that rely on additional feedback from the routers, using implementations in the Linux stack. Both testbed measurements and simulation studies quantify the potential performance improvement, the risk of packet loss, and the benefits of additional router support. Our results, which are also partly verified analytically, reveal that end-to-end fast startup mechanisms would not cause too much performance degradation if they are selectively used and carefully tuned. Additional router support would improve the fairness at the cost of a higher complexity.
The impact of non-technical factors on Software Architecture
Authors: Remo Ferrari, Nazim H. Madhavji, Mark Wilding
Venue: Proceedings of the 2009 ICSE Workshop on Leadership and Management in Software Architecture (2009)

Most of the research and pedagogical literature in Software Architecture is on technical issues. Recently, however, there has been increasing interest on the importance of non-technical factors such as leadership, communication, inter-personal skills, work habits etc. in architecting. In this paper, we continue this line of research by conducting an empirical study examining the impact of non-technical factors in Software Architecture from the viewpoint of academia. We analysed non-technical problems encountered from 15 student architecting teams to determine the types of problems students have, and also their impact on the quality of the architecture. Furthermore, we analyzed the IEEE/ACM Software Engineering and Computer Science curriculums to determine any correspondence between these curriculums and the student's architecting performance. Based on this analysis, we make recommendations for the improved education of student software architects.
Sensitivity and specificity based multiobjective approach for feature selection: Application to cancer diagnosis
Authors: J. García-Nieto, E. Alba, L. Jourdan, E. Talbi
Venue: Information Processing Letters (2009)

The study of the sensitivity and the specificity of a classification test constitute a powerful kind of analysis since it provides specialists with very detailed information useful for cancer diagnosis. In this work, we propose the use of a multiobjective genetic algorithm for gene selection of Microarray datasets. This algorithm performs gene selection from the point of view of the sensitivity and the specificity, both used as quality indicators of the classification test applied to the previously selected genes. In this algorithm, the classification task is accomplished by Support Vector Machines; in addition a 10-Fold Cross-Validation is applied to the resulting subsets. The emerging behavior of all these techniques used together is noticeable, since this approach is able to offer, in an original and easy way, a wide range of accurate solutions to professionals in this area. The effectiveness of this approach is proved on public cancer datasets by working out new and promising results. A comparative analysis of our approach using two and three objectives, and with other existing algorithms, suggest that our proposal is highly appropriate for solving this problem.
Tackling high variability in video surveillance systems through a model transformation approach
Authors: Mathieu Acher, Philippe Lahire, Sabine Moisan, Jean-Paul Rigault
Venue: Proceedings of the 2009 ICSE Workshop on Modeling in Software Engineering (2009)

This work explores how model-driven engineering techniques can support the configuration of systems in domains presenting multiple variability factors. Video surveillance is a good candidate for which we have an extensive experience. Ultimately, we wish to automatically generate a software component assembly from an application specification, using model to model transformations. The challenge is to cope with variability both at the specification and at the implementation levels. Our approach advocates a clear separation of concerns. More precisely, we propose two feature models, one for task specification and the other for software components. The first model can be transformed into one or several valid component configurations through step-wise specialization. This paper outlines our approach, focusing on the two feature models and their relations. We particularly insist on variability and constraint modeling in order to achieve the mapping from domain variability to software variability through model transformations.
An evaporative approach to handle dynamics in diffusive aggregation schemes
Authors: Nicola Bicocchi, Marco Mamei, Franco Zambonelli
Venue: Proceedings of the 2009 workshop on Bio-inspired algorithms for distributed systems (2009)

Distributed computing in large-size dynamic networks often requires the availability at each and every node globally aggregated information about some overall properties of the network. In this context, since traditional broadcasting solutions become inadequate as the number of participating nodes increases, aggregation schemes inspired by the physical/biological phenomenon of diffusion have been recently proposed as a simple yet effective alternative to solve the problem. However, diffusive aggregation requires specific solutions to cope with the dynamics of the network and/or of the values being aggregated. While typical solutions are based on periodic restarts (epoch-based approaches), in this paper, we propose an original and more autonomic solution, relying on coupling diffusive aggregation schemes with the additional bio-inspired mechanism of evaporation. While a gossip-based diffusive communication scheme is used to aggregate values over a network, gradual evaporation of values can be exploited to account for network and value dynamics without requiring periodic restarts. A comparative performance evaluation shows that the evaporative approach is able to manage the dynamism of the values sensed over the network in an effective way and, in the most of the cases, it leads to more accurate aggregate estimations than epoch based techniques.
nAIT: A source analysis and instrumentation framework for nesC
Authors: Andrew R. Dalton, Jason O. Hallstrom
Venue: Journal of Systems and Software (2009)

Automated software engineering methods support the construction, maintenance, and analysis of both new and legacy systems. Their application is commonplace in desktop- and enterprise-class systems due to the productivity and reliability benefits they afford. The contribution of this article is to present an applied foundation for extending the use of such methods to the flourishing domain of wireless sensor networks. The objective is to enable developers to construct tools that aid in understanding both the static and dynamic properties of reactive, event-based systems. We present a static analysis and instrumentation toolkit for the nesC language, the defacto standard for sensor network development. We highlight the novel aspects of the toolkit, analyze its performance, and provide representative case-studies that illustrate its use.
Resource availability awareness and data utility: the foundation for a dss framework in a pervasive computing environment
Authors: Victoria Yoon
Venue:  (2008)

The reality of pervasive computing has nearly been realized, if it has not already. Pervasive computing environments promise ubiquitous connectivity, a plethora of information, and seamless computing support. Despite the advances in infrastructure to deliver on Weiser's original vision for pervasive computing environments, little attention has been specifically given to decision support systems that are expected to operate in these environments. Issues such as large amounts of highly variant data and decision resource availability can directly influence decision support systems and subsequently limit the efficacy of the support they provide. Moreover, these factors can have a direct effect on decision outcomes for deterministic structured and semi-structured problems. This research investigates the impact of data utility enhancement and availability awareness on decision making and decision support systems. A decision support system architecture that addresses the limitations caused by the large amounts of variant data and uneven conditioning of connectivity that are characteristic in pervasive computing environments is proposed and developed. By incorporating data utility enhancement, availability awareness, and an agent-based framework, the decision support system architecture seeks to extend the breadth of decision support systems research. This architecture, which we call the Pervasive Agent Decision Support System (PADSS), integrates intelligent agents, wavelets, and instant messaging as a comprehensive decision support solution to address data utility and resource availability related issues in pervasive computing environments. As such, this research study combines several experiments that include qualitative evaluation, empirical evaluation, mathematical modeling, and simulation in a design science context. The culmination of the research concludes with an implementation and evaluation of a pervasive computing DSS based on the presented DSS architecture.
Op-Glyph: a tool for exploring op art representation of height and vector field data
Authors: Francis T. Marchese
Venue: Proceedings of the working conference on Advanced visual interfaces (2002)

We report our experiences with application of the optical art techniques of Victor Vasarely and Bridget Riley to visualization of height field and vector field data. The bold use of color and simple form in Op Art engages the preattentive processing ability of the human visual system, facilitating a nearly instantaneous perception of image properties without the need for extended scrutiny of component parts. A software system called Op-Glyph was constructed to illustrate the Op Art method for data visualization, providing a user with extensive control over a visual representation's primitives, including shape, size, and color. Initial results suggest that this glyph-based approach to data visualization may be a viable alternative or complement to more complex representation schemes, particularly in situations where there are limited processing or graphical capabilities, such as with PDAs.
Artistic rendering of mountainous terrain
Authors: Margarita Bratkova, Peter Shirley, William B. Thompson
Venue: ACM Transactions on Graphics (TOG) (2009)

Panorama maps are aerial view paintings that depict complex, three-dimensional landscapes in a pleasing and understandable way. Painters and cartographers have developed techniques to create such artistic landscapes for centuries, but the process remains difficult and time-consuming. In this work, we derive principles and heuristics for panorama map creation of mountainous terrain from a perceptual and artistic analysis of two panorama maps of Yellowstone National Park. We then present methods to automatically produce landscape renderings in the visual style of the panorama map. Our algorithms rely on United States Geological Survey (USGS) terrain and classification data. Our surface textures are generated using perceptual metrics and artistic considerations, and use the structural information present in the terrain to guide the automatic placement of image space strokes for natural surfaces such as forests, cliffs, snow, and water.
Information Extraction and Machine Learning: Auto-Marking Short Free Text Responses to Science Questions
Authors: Jana Z. Sukkarieh, Stephen G. Pulman
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

Traditionally, automatic marking has been restricted to item types such as multiple choice that narrowly constrain how students may respond. More open ended items have generally been considered unsuitable for machine marking because of the difficulty of coping with the myriad ways in which credit-worthy answers may be expressed. Successful automatic marking of free text answers would seem to presuppose an advanced level of performance in automated natural language understanding. However, recent advances in computational linguistics techniques have opened up the possi-bility of being able to automate the marking of free text responses typed into a computer without having to create systems that fully understand the answers. This paper describes the use of information extraction and machine learning techniques in the marking of short, free text responses of up to around five lines.
Interactive Learning Neural Networks for Predicting Game Behavior
Authors: Qiaomei Sun, Guang Ren, Xiaowei Qi
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

Game theory is an interdisciplinary approach to the study of human behavior. Games describe a widely accepted framework for representing interactive decision-making. Artificial Neural Networks (ANNs) are universal approximators and have the ability of learning. Combining ANNs with game representation, we introduced a new architecture by which the learning abilities of ANNs are utilized to predict game behavior. Based on previous work, we investigated further the potential value of neural networks for modeling and predicting human interactive learning in repeated games. We conducted simulation studies based on the new model using experiments data which are provided by authors other than this paper. Through computer simulations and comparing with other models, we demonstrated that our model is superior in many respects to other models on ten experiments.
Improving bulk FinFET DC performance in comparison to SOI FinFET
Authors: Mirko Poljak, Vladimir Jovanović, Tomislav Suligoj
Venue: Microelectronic Engineering (2009)

The implementation of FinFET structure in bulk silicon wafers is very attractive due to low-cost technology and compatibility with standard bulk CMOS in comparison with silicon-on-insulator (SOI) FinFET. SOI and bulk FinFET were analyzed by a three-dimensional numerical device simulator. We have shown that bulk FinFET with source/drain-to-body (S/D) junctions shallower than gate-bottom has equal or better subthreshold performance than SOI FinFET. By reducing S/D junction depth, fin width scaling for suppression of short-channel-effects (SCEs) can be relaxed. On-state performance has also been examined and drain current difference between the SOI and bulk FinFET at higher body doping levels has been explained by investigating enhanced conduction in silicon-oxide interface corners. By keeping the body doping low and junctions shallower than the gate-bottom, bulk FinFET characteristics can be improved with no increase in process complexity and cost.
Artificial General Intelligence via Finite Covering with Learning
Authors: Yong K. Hwang, Samuel B. Hwang, David B. Hwang
Venue: Proceeding of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference (2008)

This position paper claims that the combination of solutions to a finite collection of problem instances and an expansion capability of those solutions to similar problems is enough to achieve the artificial general intelligence comparable to the human intelligence. Learning takes place during expansion of existing solutions using various methods such as trial and error, generalization, case-based reasoning, etc. This paper also looks into the amount of innate problem solving capability an artificial agent must have and the difficulty of the tasks the agent is expected to solve. To illustrate our claim examples in robotics are used where tasks are physical movements of the agent and objects in its environment.
Detecting sliding areas in three-dimensional Filippov systems using an integration-free method
Authors: Iván Arango, John Alexander Taborda
Venue: Proceedings of the 2nd conference on European computing conference (2008)

In this paper, we detect sliding areas in three-dimensional (3D) Filippov systems using an integration-free method denominated Singular Point Tracking (SPT). Many physical applications in engineering can be modelled as Filippov systems. Sliding dynamics due to nonsmooth phenomena as friction, hysteresis or switching are inherent to Filippov systems. The analysis of sliding dynamics has many mathematical and numerical difficulties. Several well-known numerical problems can be avoid using integration-free methods. In this paper, we extend the SPT method to 3D Filippov systems. In comparison with the 2D case, the evaluation of the vector fields on the discontinuity boundary (DB) should be reformulated and new dynamics on DB should be characterized.
Speaker diarization using autoassociative neural networks
Authors: S. Jothilakshmi, V. Ramalingam, S. Palanivel
Venue: Engineering Applications of Artificial Intelligence (2009)

This paper addresses a new approach to speaker diarization using autoassociative neural networks (AANN). The speaker diarization task consists of segmenting a conversation into homogeneous segments which are then clustered into speaker classes. The proposed method uses AANN models to capture the speaker specific information from mel frequency cepstral coefficients (MFCC). The distribution capturing ability of the AANN model is utilized for segmenting the conversation and grouping each segment into one of the speaker classes. The algorithm has been tested on different databases, and the results are compared with the existing algorithms. The experimental results show that the proposed approach competes with the standard speaker diarization methods reported in the literature and it is an alternative method to the existing speaker diarization methods.
A Core Ontology of Knowledge Acquisition
Authors: José Iria
Venue: Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications (2009)

Semantic descriptions of knowledge acquisition (KA) tools and resources enable machine reasoning about KA systems and can be used to automate the discovery and composition of KA services, thereby increasing interoperability among systems and reducing system design and maintenance costs. Whilst there are a few general-purpose ontologies available that could be combined for describing knowledge acquisition, albeit at an inadequate abstraction level, there is as yet no KA ontology based on Semantic Web technologies available. In this paper, we present OAK, a well-founded, modular, extensible and multimedia-aware ontology of knowledge acquisition which extends existing foundational and core Semantic Web ontologies. We start by using a KA tool development scenario to illustrate the complexity of the problem, and identify a number of requirements for OAK. After we present the ontology in detail, we evaluate it with respect to the identified requirements.
Data Interoperability Community of Interest Handbook
Authors: Michael M. Gorman
Venue:  (2007)

The Data Interoperability Community of Interest Handbook provides the: * Rationale for Shared Data Environments across the Enterprise * The Unbeatable Business Case * Blueprint for Collaborative Data Sharing * Why Communities of Interest are Ideal Organizational Structures * How Communities of Interest are Best Engineered * Step-by-Step Strategies to Build Common Data Architectures * Methodology & Plan to Create Focused Organizations * Strategies for Meetings, Decision Making, and Voting * And Much, Much More! 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