ppxscal/embedding_network huggingface dataset:
Folksonomies meet ontologies in ARSMETEO: from social descriptions of artifacts to emotional concepts
Authors: Matteo Baldoni, Cristina Baroglio, András Horváth, Viviana Patti, Flavio Portis, Maurizio Avilia, Pierluigi Grillo
Venue: Proceeding of the 2008 conference on Formal Ontologies Meet Industry (2008)

This work focusses on bridging between folksonomies, which provide social but mainly flat and unstructured metadata on web resources, and semantic web ontologies, which instead design structured, machine-processable knowledge spaces. The main purpose is to capture emerging semantics in social tagging systems and to overcome the gap between Semantic Web and Web 2.0, by preserving the complementary advantages of social and ontology-driven methods for describing, categorizing and processing web content. As a way to bridge this gap, we propose a method for linking tags from a folksonomy to concepts of an existing ontology, adopting a statistic approach. We have applied the proposed method to the data collected through the art portal Arsmeteo, relating them to the concepts of an OWL ontology of emotions. Intuitively, by our method we try to capture the latent emotional semantics of the tags. Some of the artworks in Arsmeteo could be visited in real exhibitions. In order to capture the emotional potential of the tagging activity during the visit, we explored the possibility to enable tagging of artifacts in real spaces, by using Semacode technology.
Charisma perception from text and speech
Authors: Andrew Rosenberg, Julia Hirschberg
Venue: Speech Communication (2009)

Charisma, the ability to attract and retain followers without benefit of formal authority, is more difficult to define than to identify. While we each seem able to identify charismatic individuals - and non-charismatic individuals - it is not clear what it is about an individual that influences our judgment. This paper describes the results of experiments designed to discover potential correlates of such judgments, in what speakers say and the way that they say it. We present results of two parallel experiments in which subjective judgments of charisma in spoken and in transcribed American political speech were analyzed with respect to the acoustic and prosodic (where applicable) and lexico-syntactic characteristics of the speech being assessed. While we find that there is considerable disagreement among subjects on how the speakers of each token are ranked, we also find that subjects appear to share a functional definition of charisma, in terms of other personal characteristics we asked them to rank speakers by. We also find certain acoustic, prosodic, and lexico-syntactic characteristics that correlate significantly with perceptions of charisma. Finally, by comparing the responses to spoken vs. transcribed stimuli, we attempt to distinguish between the contributions of ''what is said'' and ''how it is said'' with respect to charisma judgments.
Estimating woody browse abundance from aerial imagery
Authors: S. M. Crimmins, A. R. Mynsberge, T. A. Warner
Venue: International Journal of Remote Sensing (2009)

In the deciduous forests of the eastern US, timber harvest programmes are often designed to increase the availability of woody browse for terrestrial wildlife. However, assessing the efficacy of timber harvest at increasingly available browse has traditionally required labour-intensive field-based measurements of woody plant growth and abundance. The objective of this study was to use readily available digital aerial imagery to estimate the amount of woody browse in regenerating clearcuts in central West Virginia. Aerial imagery from the National Agriculture Imagery Program and woody browse data collected from 11 regenerating clearcuts in the summer of 2007 were used in this analysis. Red, green and blue visible bands, as well as a simple texture metric, were used to create a multiple linear regression model to predict the amount of woody browse. The final model exhibited large correlation (R 2 = 0.94) and was statistically significant (F = 22.48, p = 0.0009), indicating that simple measures of image digital numbers and texture have potential utility in assisting forest and wildlife managers to assess habitat quality in forest regeneration areas.
Examination of digital modulations classification method based on spectrogram analysis on signals corrupted by different noises and interferences
Authors: Anna Kubankova
Venue: Proceedings of the 3rd WSEAS international symposium on Wavelets theory and applications in applied mathematics, signal processing & modern science (2009)

In this paper a new method of modulation classification based on spectrogram analysis is described. The classification method can discriminate between various digital signal modulations such as FSK, BPSK, MSK, QPSK and QAM-16. This classification method is examined on signals corrupted by Gaussian noise, phase noise and on signals after their transmission through multipath Rayleigh fading channel. The Matlab program is used for the analysis.
Efficient anomaly monitoring over moving object trajectory streams
Authors: Yingyi Bu, Lei Chen, Ada Wai-Chee Fu, Dawei Liu
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

Lately there exist increasing demands for online abnormality monitoring over trajectory streams, which are obtained from moving object tracking devices. This problem is challenging due to the requirement of high speed data processing within limited space cost. In this paper, we present a novel framework for monitoring anomalies over continuous trajectory streams. First, we illustrate the importance of distance-based anomaly monitoring over moving object trajectories. Then, we utilize the local continuity characteristics of trajectories to build local clusters upon trajectory streams and monitor anomalies via efficient pruning strategies. Finally, we propose a piecewise metric index structure to reschedule the joining order of local clusters to further reduce the time cost. Our extensive experiments demonstrate the effectiveness and efficiency of our methods.
Regional telecommunication incident coordination: Sharing information for rapid response
Authors: Donna S. Canestraro, Theresa A. Pardo, Anna N. Raup-Kounovsky, Dennis Taratus
Venue: Information Polity (2009)

Governments around the world are increasingly turning to information sharing as a lead strategy for developing response capacity for problems in a wide range of program and policy areas. One form of information sharing is regional coordination, which links together organizations or groups within close proximity to one another to pursue similar interests, goals, or mandates. Regional coordination requires leveraging currently held resources in innovative and potentially more efficient ways, as well as the establishment of new business processes, communication flows, and a system of governance that satisfies the needs of all stakeholders. In addition, trust, collaboration, and timely cross-boundary information sharing all play a pivotal role in this new model. This paper presents the experiences of the New York State Department of Public Service as it explores the concept of regional telecommunications incident response in New York; although this case study presents only one example of regional coordination, it raises issues which may apply in other regional information-sharing initiatives.
Determination of the electronic parameters of nanostructure SnO2/p-Si diode
Authors: Yasemin Caglar, Mujdat Caglar, Saliha Ilican, Fahrettin Yakuphanoglu
Venue: Microelectronic Engineering (2009)

The current-voltage and capacitance-voltage characteristics of the nanostructure SnO"2/p-Si diode have been investigated. The optical band gap and microstructure properties of the SnO"2 film were analyzed by optical absorption method and scanning electron microscopy, respectively. The optical band of the film was found to be 3.58eV with a direct optical transition. The scanning electron microcopy results show that the SnO"2 film has the nanostructure. The ideality factor, barrier height and series resistance values of the nanostructure SnO"2/p-Si diode were found to be 2.1, 0.87eV and 36.35k@W, respectively. The barrier height obtained from C-V measurement is higher than obtained from I-V measurement and this discrepancy can be explained by introducing a spatial distribution of barrier heights due to barrier height inhomogeneities, which are available at the nanostructure SnO"2/p-Si interface. The interface state density of the diode was determined by conductance technique and was found to be 8.41x10^1^0eV^-^1cm^-^2. It is evaluated that the nanostructure of the SnO"2 film has an important effect on the ideality factor, barrier height and interface state density parameters of SnO"2/p-Si diode.
An ANFIS Based Fuzzy Synthesis Judgment for Transformer Fault Diagnosis
Authors: Hongsheng Su, Xiuhua Wang, Hao Chen
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

In conventional Fuzzy Synthesis Judgment (FSJ), the shape parameters of fuzzy membership functions are subjectively confirmed by man beforehand, and fuzzy relationship matrix is also established in advance, thus, the applicable object of fuzzy inference is a confirmed system beforehand. However, while the size of data set is larger, and the space distribution of the samples is more complicated, it is difficult to establish such a model to trace the characteristic change of input-output data. But Adaptive Neuro-Fuzzy Inference System (ANFIS) can resolve the above problem better. However, ANFIS is applied to realize FSJ, there two problems required to be improved. One is the innovation of the firing strength of a rule; the other is to change the learning of TSK linear parameters as the learning of fuzzy relationship matrix. In this paper the proposed ANFIS not only resolves the two problems, but also can be like FSJ to implement reasoning, and learn the shape parameters of fuzzy subjection function and fuzzy relation matrix from the given data set, automatically. In the end, transformer fault diagnosis results indicate that the proposed method is effective and ubiquitous, and is an ideal pattern classifier.
Graphs, Networks and Algorithms, 3rd edition
Authors: Dieter Jungnickel
Venue: Algorithms And Computation In Mathematics (2007)

From reviews of the previous editions .... The book is a first class textbook and seems to be indispensable for everybody who has to teach combinatorial optimization. It is very helpful for students, teachers, and researchers in this area. The author finds a striking synthesis of nice and interesting mathematical results and practical applications. ... the author pays much attention to the inclusion of well-chosen exercises. The reader does not remain helpless; solutions or at least hints are given in the appendix. Except for some small basic mathematical and algorithmic knowledge the book is self-contained. ... (K. Engel, Mathematical Reviews (2002) The substantial development effort of this text, involving multiple editions and trailing in the context of various workshops, university courses and seminar series, clearly shows through in this new edition with its clear writing, good organisation, comprehensive coverage of essential theory, and well-chosen applications. The proofs of important results and the representation of key algorithms in a Pascal-like notation allow this book to be used in a high-level undergraduate or low-level graduate course on graph theory, combinatorial optimization or computer science algorithms. The well-worked solutions to exercises are a real bonus for self study by students. The book is highly recommended. (P.B. Gibbons, Zentralblatt fr Mathematik 1061, 2005) The third edition of this standard textbook contains additional material: two new application sections (on graphical codes and their decoding) and about two dozen further exercises (with solutions, as throughout the text). Moreover, recent developments have been discussed and referenced, in particular for the travelling salesman problem. The presentation has been improved in many places (for instance, in the chapters on shortest paths and on colorings), and a number of proofs have been reorganized, making them more precise or more transparent.
Parallelism in Current and Future Processors --- Challenges and Support for Designing Optimal Algorithms
Authors: Heinz Bast
Venue: Proceedings of the 8th International Symposium on Experimental Algorithms (2009)

Both explicit usable and implicit transparent parallelism is nothing really new in processor technology but has been restricted to high-end computer systems accessible to only a few developers. In recent years, however, parallelism on all levels has found its way into even the cheapest desktop and notebook system and thus every algorithm being developed today should reflect this change to optimally exploit theses additional resources.This session will outline the parallelism offered by current Intel processors and some new parallel enhancements of future architectures including the many-core approach implemented by Larrabee and the coming improvements for data-parallel (SIMD, SSE) execution. Some of these enhancements will introduce new challenges to the algorithm designer and developer. This includes the massive number of available hardware-threads, the increased size of vector operations, and non-uniform memory access. Intel actively looks for new parallel programming models to tackle these challenges including CT, Software Transactional Memory and Concurrent Collections for C++. While these models might make it into future program development environments, there are multiple developer tools for parallel program development as mature products available today --- including compilers, libraries, thread checker/debugger, performance analysis tools using hardware performance counters etc. The talk will outline how some of these tools as offered by Intel and how they can facilitate the complete development cycle for parallel program development. 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
Boosting with structural sparsity
Authors: John Duchi, Yoram Singer
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

We derive generalizations of AdaBoost and related gradient-based coordinate descent methods that incorporate sparsity-promoting penalties for the norm of the predictor that is being learned. The end result is a family of coordinate descent algorithms that integrate forward feature induction and back-pruning through regularization and give an automatic stopping criterion for feature induction. We study penalties based on the l1, l2, and l&infin; norms of the predictor and introduce mixed-norm penalties that build upon the initial penalties. The mixed-norm regularizers facilitate structural sparsity in parameter space, which is a useful property in multiclass prediction and other related tasks. We report empirical results that demonstrate the power of our approach in building accurate and structurally sparse models.
Dynamic Selection of a Video Content Adaptation Strategy from a Pareto Front
Authors: Anastasis A. Sofokleous, Marios C. Angelides
Venue: The Computer Journal (2009)

Genetic Algorithms may be used together with Pareto Optimality in the process of selection of a suitable video content adaptation strategy, the former to return best or fittest solutions that have evolved over many generations and the latter to evaluate and rank each generation's solutions against a set of objectives without the need to assign weights to each one. The outcome of this is a Pareto front of optimal strategies, all of which would satisfy the objectives. The distribution of optimal strategies on a Pareto front, however, suggests that there may be a ‘best-fit’ optimal strategy. This article refines the process of selection of an optimal strategy by taking into account this distribution alongside user preferences, video content characteristics and usage history. In order to make the refined process dynamic, it pursues its implementation using Self-Organising Neural Networks.
Effective static deadlock detection
Authors: Mayur Naik, Chang-Seo Park, Koushik Sen, David Gay
Venue: Proceedings of the 2009 IEEE 31st International Conference on Software Engineering (2009)

We present an effective static deadlock detection algorithm for Java. Our algorithm uses a novel combination of static analyses each of which approximates a different necessary condition for a deadlock. We have implemented the algorithm and report upon our experience applying it to a suite of multi-threaded Java programs. While neither sound nor complete, our approach is effective in practice, finding all known deadlocks as well as discovering previously unknown ones in our benchmarks with few false alarms.
Automatic generation method of relation matrix for ISM
Authors: Nobuaki Kanazawa, Toshiaki Sasahira, Shigeo Kaneda, Hirohide Haga
Venue: Proceeding of the 2006 conference on Knowledge-Based Software Engineering: Proceedings of the Seventh Joint Conference on Knowledge-Based Software Engineering (2006)

This article proposes an automatic generation method of a relation matrix for Interpretive Structural Modelling (ISM). In ISM, keywords related to the problem are selected. Then the relation between two arbitrary keyword pairs is examined. When there is a relation between these two keywords, a non-zero value such as 1 is assigned to this relation. After examining the relations of all pairs of keywords, an n×n relation matrix is generated where n stands for the number of keywords. Then a reachable matrix is calculated from the relation matrix. By using the reachable matrix, the hierarchy structure of the problem is constructed. Building a relation matrix requires much time and labour. This article proposes an automatic generation method of relation matrix based on the co-occurrence probability of keywords in primary materials. As the proposed method is fully automatic, less labour is necessary than in the original ISM method. This method is evaluated by using newspaper articles.
Managing operations in multiagent virtual organizations
Authors: Shelley Zhang, Ping Xuan, Bhumit Patel
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

In this paper we present our method and experimental results for handling virtual organization (VO) task management operations. First, we present a combinatorial auction approach to the initial commitment decision problem, which determines how a team task (i.e. VO task) can be allocated to a team of agents forming a virtual organization, while taking into consideration that the agents may be of different nature and they have other (their own) tasks in addition to the VO tasks. Then we present our solution to the crisis management problem, which determines at run time what to do when an agent decides to abandon a previously committed task in order to pursue a newly arrived, better task. We have built a testbed for evaluation of the strategies and used a building construction domain problem to show the effectiveness of our approach.
Understanding Pair-Programming from a Socio-Cultural Perspective
Authors: Weiqin Chen, Marius Nordbø
Venue: Proceeding of the 2007 conference on Supporting Learning Flow through Integrative Technologies (2007)

Pair-programming, as one of the 12 practices in extreme programming, has been used more and more often in educational settings. Although some studies have been conducted and pair-programming was found in these studies more effective for students to learn programming, very few studies have focused on the interactions within the pair during the pair-programming process. The study reported in this paper seeks to better understand the learner's activities by taking a closer look at the interactions between the pair from a socio-cultural perspective.
Active learning of greedy algorithms by means of interactive experimentation
Authors: J. Ángel Velázquez-Iturbide, Antonio Pérez-Carrasco
Venue: Proceedings of the 14th annual ACM SIGCSE conference on Innovation and technology in computer science education (2009)

Greedy algorithms are one of the most common algorithm design techniques. Despite their apparent simplicity, their design is a demanding task. As a consequence, they are usually taught and learnt in a passive way. In this paper, we make a new proposal aimed at active learning of greedy algorithms. The paper contains two main contributions. First, we introduce a novel approach to their active learning, based on experimentation with and evaluation of alternative greedy strategies for a given problem. Second, we present a family of interactive assistants designed to support this approach. The assistants were evaluated for their usability in real lab situations, having obtained high scores from students as well as useful information to enhance them.
Legal metadata interchange framework to match CEN metalex
Authors: Monica Palmirani, Luca Cervone, Fabio Vitali
Venue: Proceedings of the 12th International Conference on Artificial Intelligence and Law (2009)

This paper presents a legal metadata interchange framework for adding semantics on top of the CEN Metalex standard. Indeed for exploiting its potentialities CEN Metalex needs to be enriched with a legal document ontology and moreover to an intermediate layer called LMIF for managing in automatic way the mapping between different local metadata on the general structural layer.
On some Problems with Modelling of Exceptions in UML
Authors: Radosław Klimek, Paweł Skrzyński, Michał Turek
Venue: Proceeding of the 2005 conference on Software Engineering: Evolution and Emerging Technologies (2005)

During the last couple of years UML has been becoming more popular and has been rapidly accepted as the standard modelling language for specifying software and system architectures. Despite this popularity using UML 1.x caused some trouble and developers face some limitations due to the fact that software industry has evolved considerably during last seven years and software system become more and more complex. One of the most important issues in modem software systems is exception handling. Exception handling mechanism enables to make software systems robust and reliable [6]. However mechanism provided even by the 2.0 version of UML, in authors opinion, seems to be insufficient and is far from well-known implementation practise. UML does not put proper emphasis on exceptions handling the aim of the paper is to present the possibilities of excep-tions modelling in UML using statechart diagrams. These approach seems to be the most natural way to model the mechanism. Alternative methods, which should be taken into consideration in future research, are discussed at the end of the paper. UML dialect used is proposed by Telelogic so does the tool Tau G2.
Arabic morphological tagging, diacritization, and lemmatization using lexeme models and feature ranking
Authors: Ryan Roth, Owen Rambow, Nizar Habash, Mona Diab, Cynthia Rudin
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

We investigate the tasks of general morphological tagging, diacritization, and lemmatization for Arabic. We show that for all tasks we consider, both modeling the lexeme explicitly, and retuning the weights of individual classifiers for the specific task, improve the performance.