ppxscal/embedding_network huggingface dataset:
Detecting Intuitive Mentions of Diseases in Narrative Clinical Text
Authors: Stéphane M. Meystre
Venue: Proceedings of the 12th Conference on Artificial Intelligence in Medicine: Artificial Intelligence in Medicine (2009)

A significant portion of the clinical information content of narrative text documents in the medical record is only mentioned intuitively, but automated information extraction systems typically focus on explicitly mentioned concepts only. To extend the extraction of clinical information to intuitively mentioned diseases, we have developed a natural language processing application based on MMTx and on context analysis algorithms, enhanced with the detection of disease-specific concepts (e.g. medications used only for this disease), and values of some specific biomarkers. This application was developed for the i2b2 obesity challenge, a competition focused on the detection of patients with obesity or common comorbidities.
A Network Architecture to Easily Control Devices
Authors: Takahiro Hata, Michiharu Takemoto, Takashi Kambayashi, Kentaro Uchiyama, Mitsuo Teramoto
Venue: Proceedings of the 2009 Ninth Annual International Symposium on Applications and the Internet (2009)

Recently, many works on ubiquitous computing have been reported. Many of them assume a closed system such as a Smart Home. In this paper, we consider assumptions in ubiquitous computing environments and discuss requirements for those environments. In addition, we propose and discuss network architecture for reducing the spatial limitations when controlling devices. Moreover, we show the current implementation of our prototype system.
Evaluating Interface Variants on Personality Acquisition for Recommender Systems
Authors: Greg Dunn, Jurgen Wiersema, Jaap Ham, Lora Aroyo
Venue: Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH (2009)

Recommender systems help users find personally relevant media content in response to an overwhelming amount of this content available digitally. A prominent issue with recommender systems is recommending new content to new users; commonly referred to as the cold start problem. It has been argued that detailed user characteristics, like personality, could be used to mitigate cold start. To explore this solution, three alternative methods measuring users' personality were compared to investigate which would be most suitable for user information acquisition. Participants (N = 60) provided user ease of use and satisfaction ratings to evaluate three different interface variants believed to measure participants' personality characteristics. Results indicated that the NEO interface and the CFG interface were promising methods for measuring personality. Results are discussed in terms of potential benefits and broader implications for recommender systems.
An Algebraic Characterization of Semirings for Which the Support of Every Recognizable Series Is Recognizable
Authors: Daniel Kirsten
Venue: Proceedings of the 34th International Symposium on Mathematical Foundations of Computer Science 2009 (2009)

We show that for a semiring ${\mathbb K}$, the support of all recognizable series over ${\mathbb K}$ are recognizable if and only if in every finitely generated subsemiring of ${\mathbb K}$ there exists a finite congruence such that $0_{\mathbb K}$ is a singleton congruence class. 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
Recognition of User Intentions for Interface Agents with Variable Order Markov Models
Authors: Marcelo G. Armentano, Analía A. Amandi
Venue: Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH (2009)

A key aspect to study in the field of interface agents is the need to detect as soon as possible the user intentions. User intentions have an important role for an interface agent because they serve as a context to define the way in which the agents can collaborate with users. Intention recognition can be used to infer the user's intentions based on the observation of the tasks the user performs in a software application. In this work, we propose an approach to model the intentions the user can pursue in an application in a semi-automatic way, based on Variable-Order Markov models. We claim that with appropriate training from the user, an interface agent following our approach will be able both to detect the user intention and the most probable sequence of following tasks the user will perform to achieve his/her intention.
Energy Efficient and Progressive Strategy for Processing Skyline Queries on Air
Authors: Jongwoo Ha, Yoon Kwon, Jae-Ho Choi, Sangkeun Lee
Venue: Proceedings of the 20th International Conference on Database and Expert Systems Applications (2009)

Computing skyline and its variations is attracting a lot of attention in the database community, however, processing the queries in wireless broadcast environments is an uncovered problem despite of its unique benefits compared to the other environments. In this paper, we propose a strategy to process skyline queries for the possible expansion of current data broadcasting services. For the energy efficient processing of the skyline queries, the Sweep space-filling curve is utilized based on the existing DSI structure to generate broadcast program at a server side. The corresponding algorithms of processing skyline queries are also proposed for the mobile clients. Moreover, we extend the DSI structure based on a novel concept of Minimized Dominating Points (MDP) in order to provide a progressive algorithm of the queries. We evaluate our strategy by performing a simulation, and the experimental results demonstrate the energy efficiency of the proposed methods.
Recognizing daily activities with RFID-based sensors
Authors: Michael Buettner, Richa Prasad, Matthai Philipose, David Wetherall
Venue: Proceedings of the 11th international conference on Ubiquitous computing (2009)

We explore a dense sensing approach that uses RFID sensor network technology to recognize human activities. In our setting, everyday objects are instrumented with UHF RFID tags called WISPs that are equipped with accelerometers. RFID readers detect when the objects are used by examining this sensor data, and daily activities are then inferred from the traces of object use via a Hidden Markov Model. In a study of 10 participants performing 14 activities in a model apartment, our approach yielded recognition rates with precision and recall both in the 90% range. This compares well to recognition with a more intrusive short-range RFID bracelet that detects objects in the proximity of the user; this approach saw roughly 95% precision and 60% recall in the same study. We conclude that RFID sensor networks are a promising approach for indoor activity monitoring.
Study on the Phosphorus Immobility of the Re-suspended Sediments
Authors: Dapeng Li, Yong Huang
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

The variation of EPC0s of the re-suspended sediments is studied and the relationship between the distribution of phosphorus forms and EPC0s of sediments is investigated. Results of this study show that sediment re-suspension could promote phosphorus migration from overlying water to the sediments. The EPC0 of the re-suspended sedimentsreduced evidently from 0.069mg•L-1 (the initial state) to 0.034mg•L-1, whereas the values of the sediments without re-suspension increased slightly from 0.069mg•L-1 (the initial state) to 0.071mg•L-1 (the control experiment) and 0.073 mg•L-1 (aerating to water), respectively. The EPC0s of the sediments had remarkable positive correlation with the concentrations of various phosphorus forms (BD-P+Al-P+NaOH-nrP) in those sediments except for the re-suspended sediments. It was suggested that the characteristics of BD-P, Al-P and NaOH-nrP formed under sediment re-suspension was different evidently from the initial state.
Personalised Web Experiences: Seamless Adaptivity across Web Service Composition and Web Content
Authors: Ian O'Keeffe, Vincent Wade
Venue: Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH (2009)

Users have become accustomed to a web that is more than an interactive hypermedia but is a complex mix of rich multimedia services and hypermedia content. Users are now contributors and active participants on the web. However, Pesonalisation technologies, such as Adaptive Hypermedia, have so far focused almost exclusively on adaptive content delivery resulting in their failure to become a high impact technologies. The absence of rich multimedia services in the current generation of Adaptive Hypermedia Systems means that they do not live up to the expectations of users. By providing personalised web experiences that combine both services and content in a seamless environment such systems could not only live up to the expectations of users but could exceed them. This paper presents a system that supports the adaptive selection and sequencing of both content and services in a unified manner. By applying techniques used in content based Adaptive Hypermedia to services with making use of the state of the art in service composition, this system delivers personalised web experiences that combine adaptively selected and sequenced content and services. The integration of appropriate content with services can improve the experience of the user as well as making the activity more efficient.
Realising Dead Path Elimination in BPMN
Authors: Matthias Weidlich, Alexander Grosskopf, Alistair Barros
Venue: Proceedings of the 2009 IEEE Conference on Commerce and Enterprise Computing (2009)

The Web Service Business Process Execution Language (BPEL) lacks any standard graphical notation. Various efforts have been undertaken to visualize BPEL using the Business Process Modelling Notation (BPMN). Although this is straightforward for the majority of concepts, it is tricky for the full BPEL standard, partly due to the insufficiently specified BPMN execution semantics. The upcoming BPMN~2.0 revision will provide this clear semantics. In this paper, we show how the dead path elimination (DPE) capabilities of BPEL can be expressed with this new semantics and discuss the limitations. We provide a generic formal definition of DPE and discuss resulting control flow requirements independent of specific process description languages.
The deep space network scheduling problem
Authors: Bradley J. Clement, Mark D. Johnston
Venue: Proceedings of the 17th conference on Innovative applications of artificial intelligence - Volume 3 (2005)

We describe the Deep Space Network's scheduling problem based on a user requirement language. The problem is difficult to encode by almost all existing planning and scheduling systems. We describe how it can be mapped into a system that supports metric resources, durative action, simple temporal network constraints, and task hierarchy among other language features. We also describe how we adapted a local search scheduler to generate schedules. However, we argue that the application will best serve the users if local search is combined with systematic search. We describe how an implemented systematic search can be effectively applied to rescheduling.
Current-controllable monostable multivibrator with retriggerable function
Authors: Yu-Kang Lo, Hung-Chun Chien
Venue: Microelectronics Journal (2009)

This paper presents a novel current-controllable monostable multivibrator, which is composed of three operational transconductance amplifiers (OTAs), two grounded resistors, and one grounded capacitor. The pulse width and height of the output signal can be adjusted through the bias currents of OTAs and external resistors. In addition, this new monostable circuit features a retriggerable function that can efficiently overcome the problem of the recovery time. The proposed retriggerable monostable multivibrator including the parasitics and slew rate (SR) effect is analyzed in detail. A prototype circuit is built to conduct tests. Experimental results are shown to confirm the theoretical analysis. The presented current-controllable monostable circuits displays good linearities of current-to-pulse width and current-to-pulse height. Also the temperature stabilities are acceptable.
Interval-valued Fuzzy Subsemigroups and Subgroups Associated by Interval-valued Fuzzy Graphs
Authors: Ju Hongmei, Wang Lianhua
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01 (2009)

The aim of this paper is to introduce the notion of interval-valued fuzzy graphs. We also show how to associate an interval-valued fuzzy sub(semi)group with an interval-valued fuzzy graph in a natural way.
Parameter-Free Hierarchical Co-clustering by n-Ary Splits
Authors: Dino Ienco, Ruggero G. Pensa, Rosa Meo
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I (2009)

Clustering high-dimensional data is challenging. Classic metrics fail in identifying real similarities between objects. Moreover, the huge number of features makes the cluster interpretation hard. To tackle these problems, several co-clustering approaches have been proposed which try to compute a partition of objects and a partition of features simultaneously. Unfortunately, these approaches identify only a predefined number of flat co-clusters. Instead, it is useful if the clusters are arranged in a hierarchical fashion because the hierarchy provides insides on the clusters. In this paper we propose a novel hierarchical co-clustering, which builds two coupled hierarchies, one on the objects and one on features thus providing insights on both them. Our approach does not require a pre-specified number of clusters, and produces compact hierarchies because it makes n ¿ary splits, where n is automatically determined. We validate our approach on several high-dimensional datasets with state of the art competitors.
Immunity for Closed Sets
Authors: Douglas Cenzer, Rebecca Weber, Guohua Wu
Venue: Proceedings of the 5th Conference on Computability in Europe: Mathematical Theory and Computational Practice (2009)

The notion of immune sets is extended to closed sets and $\Pi^0_1$ classes in particular. We construct a $\Pi^0_1$ class with no computable member which is not immune. We show that for any computably inseparable sets A and B, the class S(A,B) of separating sets for A and B is immune. We show that every perfect thin $\Pi^0_1$ class is immune. We define the stronger notion of prompt immunity and construct an example of a $\Pi^0_1$ class of positive measure which is promptly immune. We show that the immune degrees in the Medvedev lattice of closed sets forms a filter. We show that for any $\Pi^0_1$ class P with no computable element, there is a $\Pi^0_1$ class Q which is not immune and has no computable element, and which is Medvedev reducible to P. We show that any random closed set is immune.
An incremental learning algorithm for Lagrangian support vector machines
Authors: Hua Duan, Xiaojian Shao, Weizhen Hou, Guoping He, Qingtian Zeng
Venue: Pattern Recognition Letters (2009)

Incremental learning has attracted more and more attention recently, both in theory and application. In this paper, the incremental learning algorithms for Lagrangian support vector machine (LSVM) are proposed. LSVM is an improvement to the standard linear SVM for classifications, which leads to the minimization of an unconstrained differentiable convex programming. The solution to this programming is obtained by an iteration scheme with a simple linear convergence. The inversion of the matrix in the solving algorithm is converted to the order of the original input space's dimensionality plus one at the beginning of the algorithm. The algorithm uses the Sherman-Morrison-Woodbury identity to reduce the computation time. The incremental learning algorithms for LSVM presented in this paper include two cases that are namely online and batch incremental learning. Because the inversion of the matrix after increment is solved based on the previous computed information, it is unnecessary to repeat the computing process. Experimental results show that the algorithms are superior to others.
Inverse System Decoupling Control for Induction Motor Based on Neural Network On-Line Learning
Authors: Wei Ni, Yu Zhang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

The induction motor is a MIMO, nonlinear and high coupling system. The reversibility of the induction motor is testified. Consequently, a pseudo-linear system is completed by constructing a neural network inverse (NNI) system and combining it with the motor system. The inverse can transform the MIMO nonlinear system into two SISO linear subsystems (i.e., rotor speed and flux subsystems). In order to approach the inversion exactly in operation of the motor, the control method online learning based on NNI system is proposed, in which connection value can be amended continuously on-line to make the NN adapt to the changes of environment to strengthen its robustness. Simulation and experiment results have shown that NN can be adjusted in the control process. The good applicability of NN along with the strong stability and robustness of the system can be achieved by using the proposed method.
Parcellation of the Auditory Cortex into Landmark---Related Regions of Interest
Authors: Karin Engel, Klaus Tönnies, André Brechmann
Venue: Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns (2009)

We propose a method for the automated delineation of cortical regions of interest as a basis for the anatomo---functional parcellation of the human auditory cortex using neuroimaging. Our algorithm uses the properties of the cortical surface, and employs a recent hierarchical part---based pattern recognition strategy for a semantically correct labelling of the temporal lobe. The anatomical landmarks are finally combined to obtain an accurate separation and parametrisation of two auditory cortical regions. Experimental results show the good performance of the approach that was automated using simplified atlas information. 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
A Proposed Movie Recommendation Method Using Emotional Word Selection
Authors: Mina Song, Hyun Namgoong, Hong-Gee Kim, Juhyun Eune
Venue: Proceedings of the 3d International Conference on Online Communities and Social Computing: Held as Part of HCI International 2009 (2009)

Many online movie sites or music sites offering recommendation services employ a collaborative filtering technique archived by analyzing customers' satisfaction rating, evaluation, search history, download records etc. This approach, however, has difficulty with reflecting individuals' perosonalities and their own taste for the recommendation. Exploiting such emotional data to a film recommendation remains a challenge in the present. To solve this, we propose an emotion words selection method usable for the collaborative filtering. Through the proposed emotion-based collaborative filtering method, a recommendation system can exploit individuals' emotional differences on the movie items for the recommendation process. This approach was proven by gathering users' emotion words selection and satisfaction rating data on several films, and comparing them with MBTI (Myers-Briggs Type Indicator) that is a representative psychometric test for measuring psychological preferences and personalities. This study assumes that individual's movie taste is much related to the personalities classifiable by MBTI types, because movie taste and evaluation on a movie is influenced by individual's subjective matters. The results of this study show that emotion words based collaborative filtering method is appropriate for extracting users' MBTI types. Thus, if a recommendation service offers users films based on their MBTI types, the users can be recommended more customized films.
Application of Time-Cost-Quality Tradeoff Optimization Model Based on Improved PSO Algorithm to Construction Project
Authors: Qin Yang
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 02 (2009)

Time, cost and quality are important factors to construction project management. Tradeoff optimization among them is significant for the overall benefits of construction projects. In this paper, a model of multi-attribute utility function is established to study the tradeoff among time, cost and quality based on inter-related linear programming functions. In order to get the optimal decision result, an effective algorithm based on the improved particle swarm optimization algorithm and critical path method(CPM) are used according to the characteristic of optimization problem. At last, a case study on heavy repair of instrument control system for hot blast stove is given to verify the feasibility and practicability of the model.
RACON: a routing protocol for mobile cognitive radio networks
Authors: A. Cagatay Talay, D. Turgay Altilar
Venue: Proceedings of the 2009 ACM workshop on Cognitive radio networks (2009)

Advancement of Cognitive Radio technology can remedy the problems encountered from bandwidth and spectrum access limitations. In Cognitive Radio Ad Hoc Networks routing is one of the most important issues to be addressed and desires deep investigation. Previously proposed routing protocols assume the presence of a connected path from the source to the destination. In some scenarios, due to the characteristics of ad hoc networks and the features of the used cognitive radios, this assumption is likely to be invalid. In this study, a novel routing algorithm for future multi-hop Cognitive Radio Networks is proposed. The main motivation is to maximize data rates and minimize data delivery latency for a set of user communication sessions to deliver messages for the case where there is no connected path from the source to the destination or when network is partitioned at the time a message is originated. Experimental evaluations are performed in the ns2 simulator. It has been shown that the proposed approach provides better adaptability to the environment and maximizes throughput in a number of realistic scenarios and outperforms recently proposed routing protocols for Cognitive Radio networks.
A reconfigurable stochastic tagger for languages with complex tag structure
Authors: Lstrokukasz Dębowski
Venue: Proceedings of the 2003 EACL Workshop on Morphological Processing of Slavic Languages (2003)

We present a case study of a complex stochastic disambiguator of alternatives of morphosyntactic tags which allows for using incomplete disambiguation, shorthand tag notation, external tagset definition and external definition of multivalued context features. The tagger bases on Naive Bayes modeling and allows for using almost as general context features as in classical trigram taggers as well as more specific ones. Its preliminary results for Polish still do not meet our expectations. Possible sources of the tagger's failures can be: inhomogeneity of the training corpus in preparation, lack of the automatic search of probability models, too general conditional independence assumptions in defining the class of interpretable models.