ppxscal/embedding_network huggingface dataset:
Entity discovery and assignment for opinion mining applications
Authors: Xiaowen Ding, Bing Liu, Lei Zhang
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

Opinion mining became an important topic of study in recent years due to its wide range of applications. There are also many companies offering opinion mining services. One problem that has not been studied so far is the assignment of entities that have been talked about in each sentence. Let us use forum discussions about products as an example to make the problem concrete. In a typical discussion post, the author may give opinions on multiple products and also compare them. The issue is how to detect what products have been talked about in each sentence. If the sentence contains the product names, they need to be identified. We call this problem entity discovery. If the product names are not explicitly mentioned in the sentence but are implied due to the use of pronouns and language conventions, we need to infer the products. We call this problem entity assignment. These problems are important because without knowing what products each sentence talks about the opinion mined from the sentence is of little use. In this paper, we study these problems and propose two effective methods to solve the problems. Entity discovery is based on pattern discovery and entity assignment is based on mining of comparative sentences. Experimental results using a large number of forum posts demonstrate the effectiveness of the technique. Our system has also been successfully tested in a commercial setting.
Comprehending annotations on object-oriented programs using fractional permissions
Authors: John Boyland, William Retert, Yang Zhao
Venue: International Workshop on Aliasing, Confinement and Ownership in Object-Oriented Programming (2009)

Fractional permissions are a general system for managing access to mutable state. We show how fractional permissions can give semantics to a regimen of annotations including "unique," "non-null," "read-only," ownership, and method effects. The unification supports new annotations: "unique-write" and "from". We also develop a model of object invariants in the presence of inheritance using "nesting," an extension of "adoption."
Combining digital access and parallel partition for quicksort and quickselect
Authors: Leonor Frias, Jordi Petit
Venue: Proceedings of the 2009 ICSE Workshop on Multicore Software Engineering (2009)

In this paper, we combine digital access to strings with parallel partition to enhance parallel quicksort and quickselect implementations. Previously, digital access had only been combined with sequential comparison-based algorithms and data structures. We present broadly our approach, not only algorithmically but from the design and implementation point of view. Finally, we give some experimental results that indicate its effectiveness in practice.
Mean and variance optimization of non---linear systems and worst---case analysis
Authors: P. Parpas, B. Rustem, V. Wieland, S. Žaković
Venue: Computational Optimization and Applications (2009)

In this paper, we consider expected value, variance and worst---case optimization of nonlinear models. We present algorithms for computing optimal expected value, and variance policies, based on iterative Taylor expansions. We establish convergence and consider the relative merits of policies based on expected value optimization and worst---case robustness. The latter is a minimax strategy and ensures optimal cover in view of the worst---case scenario(s) while the former is optimal expected performance in a stochastic setting. Both approaches are used with a small macroeconomic model to illustrate relative performance, robustness and trade-offs between the alternative policies.
RTKPS: A Key Pre-distribution Scheme Based on Rooted-Tree in Wireless Sensor and Actor Network
Authors: Zhicheng Dai, Zhi Li, Bingwen Wang, Qiang Tang
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

Key pre-distribution in wireless sensor and actor network (WSAN) is a challenging problem because the key pre-distribution schemes in wireless sensor network (WSN) are not well-suited for the unique features and requirements. In this paper, a new scheme of key pre-distribution in WSAN (RTKPS) is presented. To achieve the distributed and integrated secure communication scheme, the paper describes a construction of the key management tree among sink, actors, and sensors by making use of the sufficient energy capabilities, larger memory, better processing and communication capabilities of actor nodes. The analysis and simulation show that the proposed scheme can effectively save memory space and evidently improve security.
Digitizing Race: Visual Cultures of the Internet
Authors: Lisa Nakamura
Venue:  (2007)

In the nineties, neoliberalism simultaneously provided the context for the Internets rapid uptake in the United States and discouraged public conversations about racial politics. At the same time many scholars lauded the widespread use of text-driven interfaces as a solution to the problem of racial intolerance. Todays online world is witnessing text-driven interfaces such as e-mail and instant messaging giving way to far more visually intensive and commercially driven media forms that not only reveal but showcase peoples racial, ethnic, and gender identity. Lisa Nakamura, a leading scholar in the examination of race in digital media, uses case studies of popular yet rarely examined uses of the Internet such as pregnancy Web sites, instant messaging, and online petitions and quizzes to look at the emergence of race-, ethnic-, and gender-identified visual cultures. While popular media such as Hollywood cinema continue to depict nonwhite nonmales as passive audiences or consumers of digital media rather than as producers, Nakamura argues the contrarywith examples ranging from Jennifer Lopez music videos; films including the Matrix trilogy, Gattaca, and Minority Report; and online joke sitesthat users of color and women use the Internet to vigorously articulate their own types of virtual community, avatar bodies, and racial politics. Lisa Nakamura is associate professor of speech communication and Asian American studies at the University of Illinois, Urbana-Champaign. She is the author of Cybertypes: Race, Ethnicity, and Identity on the Internet and coeditor, with Beth Kolko and Gilbert Rodman, of Race in Cyberspace.
MunchCrunch: a game to learn healthy-eating heuristics
Authors: Anna Mansour, Mugdha Barve, Sushama Bhat, Ellen Yi-Luen Do
Venue: Proceedings of the 8th International Conference on Interaction Design and Children (2009)

Children and adolescents are at an age where they are beginning to gain autonomy over choosing the foods they eat, yet may not have adequate support or information to make informed choices. This paper describes the design of a heuristic-based health game called MunchCrunch to help this age group learn more about healthy and unhealthy foods to develop balanced eating habits.
The Problem of Tacit Knowledge --Is It Possible to Externalize Tacit Knowledge?
Authors: Ilkka Virtanen
Venue: Proceeding of the 2009 conference on Information Modelling and Knowledge Bases XX (2009)

Various authors in the field of knowledge management have adopted the view that individuals' tacit knowledge should be externalized and shared in organizations. According to Polanyi's original theory of tacit knowing, an explicit expression of tacit knowledge is, however, considered very difficult, even impossible. We studied this contradiction by analyzing Polanyi's theory of tacit knowing in order to consider the correctness of the idea of externalization of tacit knowledge. Despite the fact that tacit knowing is an essential basis for all knowledge, we claim that tacit knowledge cannot be externalized in a way it is presented in the knowledge management literature.
A dynamic holding strategy in public transit systems with real-time information
Authors: Bin Yu, Zhongzhen Yang
Venue: Applied Intelligence (2009)

Holding strategies are among the most commonly used operation control strategies in transit systems. In this paper, a dynamic holding strategy is developed, which consists of two major steps: (1) judging whether an early bus should be held, and (2) optimizing the holding times of the held bus. A model based on support vector machine (SVM), which contains four input variables (time-of-day, segment, the latest speed on the next segment, and the bus speed on the current segment) for forecasting the early bus departure times from the next stop is also developed. Then, in order to determine the optimal holding times, a model aiming to minimize the user costs is constructed and a genetic algorithm is used to optimize the holding times. Finally, the dynamic holding strategy proposed in this study is illustrated with the microscopic simulation model Paramics and some conclusions are drawn.
What did they do? understanding clickstreams with the WebQuilt visualization system
Authors: Sarah J. Waterson, Jason I. Hong, Tim Sohn, James A. Landay, Jeffrey Heer, Tara Matthews
Venue: Proceedings of the working conference on Advanced visual interfaces (2002)

This paper describes the visual analysis tool WebQuilt, a web usability logging and visualization system that helps web design teams record and analyze usability tests. The logging portion of WebQuilt unobtrusively gathers clickstream data as users complete specified tasks. This data is then aggregated and presented as an interactive graph, where nodes of the graph are images of the web pages visited, and arrows are the transitions between pages. To aid analysis of the gathered usability test data, the WebQuilt visualization provides filtering capabilities and semantic zooming, allowing the designer to understand the test results at the gestalt view of the entire graph, and then drill down to sub-paths and single pages. The visualization highlights important usability issues, such as pages where users spent a lot of time, pages where users get off track during the task, navigation patterns, and exit pages, all within the context of a specific task. WebQuilt is designed to conduct remote usability testing on a variety of Internet-enabled devices and provide a way to identify potential usability problems when the tester cannot be present to observe and record user actions.
Comparative reliability analysis for TMR «2 out of 3»; fault tolerance systems
Authors: George Popov, Tasho Tashev
Venue: Proceedings of the international conference on Computational and information science 2009 (2009)

Microprocessor systems with high reliability are used for control responsible processes in transport, industry, military work, security systems and other areas. The targets of this paper are dependable structures with continuous reservation. It is suggested mathematical models and comparative analysis with aim to establish the conditions and parameters at which corresponded structure haves higher reliability.
Tag-Based Cooperation in Peer-to-Peer Networks with Newscast
Authors: Andrea Marcozzi, David Hales, Gian Paolo Jesi, Stefano Arteconi, Ozalp Babaoglu
Venue: Proceeding of the 2005 conference on Self-Organization and Autonomic Informatics (I) (2005)

Recent work has proposed how socially inspired mechanisms, based on “tags” and developed within social science simulations, might be applied in peer-to-peer overlay networks to maintain high cooperation between peers even when they act selfishly. The proposed mechanism involves a dynamic re-wiring algorithm called “SLAC”. The algorithm assumes a random sampling service over the entire population of nodes but does not implement this itself. In this paper we re-implement SLAC on an open source peer-to-peer simulation testbed called “PEERSIM”. For the random sampling service we utilize an existing protocol called “NEWSCAST”. We present the results of some experiments we performed in which peers play the Prisoner's Dilemma game with their neighbours. Our results demonstrate that SLAC augmented with NEWSCAST produces high levels of cooperation. This increases our confidence that previous results from SLAC are generally applicable and valid and also that SLAC could have applications in real implemented systems. Finally we discuss the open issues that need to be addressed for SLAC to progress to a valuable deployable protocol.
Minimizing a nonlinear function under a fuzzy max-t-norm relational equation constraint
Authors: Jun-Lin Lin, Yan-Kuen Wu, Pei-Chann Chang
Venue: Expert Systems with Applications: An International Journal (2009)

This work studies a nonlinear optimization problem subject to fuzzy relational equations with max-t-norm composition. Since the feasible domain of fuzzy relational equations with more than one minimal solution is non-convex, traditional nonlinear programming methods usually cannot solve them efficiently. This work proposes a genetic algorithm to solve this problem. This algorithm first locates the feasible domain through the maximum solution and the minimal solutions of the fuzzy relational equations, to significantly reduce the search space. The algorithm then executes all genetic operations inside this feasible domain, and thus avoids the need to check the feasibility of each solution generated. Moreover, it uses a local search operation to fine-tune each mutated solution. Experimental results indicate that the proposed algorithm can accelerate the searching speed and find the optimal solution.
Large margin training for hidden Markov models with partially observed states
Authors: Trinh-Minh-Tri Do, Thierry Artières
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

Large margin learning of Continuous Density HMMs with a partially labeled dataset has been extensively studied in the speech and handwriting recognition fields. Yet due to the non-convexity of the optimization problem, previous works usually rely on severe approximations so that it is still an open problem. We propose a new learning algorithm that relies on non-convex optimization and bundle methods and allows tackling the original optimization problem as is. It is proved to converge to a solution with accuracy &epsilon; with a rate O (1/&epsilon;). We provide experimental results gained on speech and handwriting recognition that demonstrate the potential of the method.
EnTracked: energy-efficient robust position tracking for mobile devices
Authors: Mikkel Baun Kjærgaard, Jakob Langdal, Torben Godsk, Thomas Toftkjær
Venue: Proceedings of the 7th international conference on Mobile systems, applications, and services (2009)

An important feature of a modern mobile device is that it can position itself. Not only for use on the device but also for remote applications that require tracking of the device. To be useful, such position tracking has to be energy-efficient to avoid having a major impact on the battery life of the mobile device. Furthermore, tracking has to robustly deliver position updates when faced with changing conditions such as delays due to positioning and communication, and changing positioning accuracy. This work proposes EnTracked - a system that, based on the estimation and prediction of system conditions and mobility, schedules position updates to both minimize energy consumption and optimize robustness. The realized system tracks pedestrian targets equipped with GPS-enabled devices. The system is configurable to realize different trade-offs between energy consumption and robustness. We provide extensive experimental results by profiling how devices consume power, by emulation on collected data and by validation in several real-world deployments. Results from this profiling show how a device consumes power while tracking its position. Results from the emulation indicate that the system can estimate and predict system conditions and mobility. Furthermore they provide evidence for that the system can lower the energy consumption considerably and remain robust when faced with changing system conditions. By validation in several real-world deployments we provide evidence that the real system works as predicted by the emulation.
Ethical awareness of computer use among undergraduate students
Authors: Maslin Masrom, Zuraini Ismail, Ramlah Hussein
Venue: ACM SIGCAS Computers and Society (2009)

This study investigates the ethical awareness of computer use among undergraduate computer science students at two public Malaysian universities. One hundred and fifty-nine students were asked to evaluate the code of ethics pertaining to computer ethics. A comparison of undergraduate computer science students between two public universities was done to determine the level of ethical awareness of computer use. Independent Samples t-tests for differences were performed across four distinct groups: university, gender, age, and duration of computer use. The results of the tests conducted indicate that the ethical awareness of computer use of the students differ most significantly on the basis of the university itself. There were minimal differences across gender, age and duration of computer use. This suggests that computer ethics awareness training is needed for university users. The results are discussed and the implications for studies in an educational context are outlined.
Latent Palmprint Matching
Authors: Anil K. Jain, Jianjiang Feng
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2009)

The evidential value of palmprints in forensics is clear as about 30% of the latents recovered from crime scenes are from palms. While palmprint-based personal authentication systems have been developed, they mostly deal with low resolution (about 100 ppi) palmprints and only perform full-to-full matching. We propose a latent-to-full palmprint matching system that is needed in forensics. Our system deals with palmprints captured at 500 ppi and uses minutiae as features. Latent palmprint matching is a challenging problem because latents lifted at crime scenes are of poor quality, cover small area of palms and have complex background. Other difficulties include the presence of many creases and a large number of minutiae in palmprints. A robust algorithm to estimate ridge direction and frequency in palmprints is developed. This facilitates minutiae extraction even in poor quality palmprints. A fixed-length minutia descriptor, MinutiaCode, is utilized to capture distinctive information around each minutia and an alignment-based matching algorithm is used to match palmprints. Two sets of partial palmprints (150 live-scan partial palmprints and 100 latents) are matched to a background database of 10,200 full palmprints to test the proposed system. Rank-1 recognition rates of 78.7% and 69%, respectively, were achieved for live-scan palmprints and latents.
Automatic discovery of workflow models
Authors: Clarence Ellis
Venue:  (2008)

Workflow systems are model-driven collaborative software systems designed to (semi-) automate the coordination of resources, activities, and people within an organization. A workflow system can be a tremendous aid to an organization because it attempts to ensure that the right agent (software, or human) gets the right resource at the right time during the execution of a workflow. But, how does a workflow system know the particular workflows, agents, and resources of a particular organization? The answer is business process analysis (BPA) and workflow modeling. The result of BPA and workflow modeling is a workflow model that captures the workflows, agents, and resources of an organization in a rigorous and formal language that can be interpreted by computer software. However, for most organizations, BPA and workflow modeling are time-consuming, error-prone, and expensive tasks that usually result in workflow models that are inaccurate and incomplete. To mitigate some of the problems traditionally associated with BPA and workflow modeling, many forward-thinking organizations are beginning to record, manually or automatically, the data associated with the executions of their workflows in workflow execution logs that can be analyzed during BPA and workflow modeling. These logs, however, are becoming too large to be analyzed manually. This thesis is concerned with workflow discovery, the task of automatically constructing workflow models from workflow execution logs. Specifically, we develop a framework for workflow discovery. This framework considers workflow to be multidimensional and admit observation from multiple perspectives. Using this framework, we&rsquo;ve developed algorithms to discover workflow models from the behavioral and informational perspectives of workflow.
Nasal Region Contribution in 3D Face Biometrics Using Shape Analysis Framework
Authors: Hassen Drira, Boulbaba Ben Amor, Mohamed Daoudi, Anuj Srivastava
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

The main goal of this paper is to illustrate a geometric analysis of 3D facial shapes in presence of varying facial expressions using the nose region. This approach consists of the following two main steps: (i) Each nasal surface is automatically denoised and preprocessed to result in an indexed collection of nasal curves. During this step one detects the tip of the nose and defines a surface distance function with that tip as the reference point. The level curves of this distance function are the desired nasal curves. (ii) Comparisons between noses are based on optimal deformations from one to another. This, in turn, is based on optimal deformations of the corresponding nasal curves across surfaces under an elastic metric. The experimental results, generated using a subset of FRGC v2 dataset, demonstrate the success of the proposed framework in recognizing people under different facial expressions. The recognition rates obtained here exceed those for a baseline ICP algorithm on the same dataset.
Real-time correction of closed-captions
Authors: P. Cardinal, G. Boulianne, M. Comeau, M. Boisvert
Venue: Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions (2007)

Live closed-captions for deaf and hard of hearing audiences are currently produced by stenographers, or by voice writers using speech recognition. Both techniques can produce captions with errors. We are currently developing a correction module that allows a user to intercept the real-time caption stream and correct it before it is broadcast. We report results of preliminary experiments on correction rate and actual user performance using a prototype correction module connected to the output of a speech recognition captioning system.