ppxscal/embedding_network huggingface dataset:
Context-dependent Deactivation of the Amygdala during Pain
Authors: Predrag Petrovic, Katrina Carlsson, Karl Magnus Petersson, Per Hansson, Martin Ingvar
Venue: Journal of Cognitive Neuroscience (2004)

The amygdala has been implicated in fundamental functions for the survival of the organism, such as fear and pain. In accord with this, several studies have shown increased amygdala activity during fear conditioning and the processing of fear-relevant material in human subjects. In contrast, functional neuroimaging studies of pain have shown a decreased amygdala activity. It has previously been proposed that the observed deactivations of the amygdala in these studies indicate a cognitive strategy to adapt to a distressful but in the experimental setting unavoidable painful event. In this positron emission tomography study, we show that a simple contextual manipulation, immediately preceding a painful stimulation, that increases the anticipated duration of the painful event leads to a decrease in amygdala activity and modulates the autonomic response during the noxious stimulation. On a behavioral level, 7 of the 10 subjects reported that they used coping strategies more intensely in this context. We suggest that the altered activity in the amygdala may be part of a mechanism to attenuate pain-related stress responses in a context that is perceived as being more aversive. The study also showed an increased activity in the rostral part of anterior cingulate cortex in the same context in which the amygdala activity decreased, further supporting the idea that this part of the cingulate cortex is involved in the modulation of emotional and pain networks.
ASNA: An Intelligent Agent for Retrieving and Classifying News on the Basis of Emotion-Affinity
Authors: Shaikh Mostafa Al Masum, Md. Tawhidul Islam, Mitsuru Ishizuka
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

In this paper, we present a system Affect Sensitive News Agent (ASNA) developed as a news aggregator that fetches news employing several RSS news-feeds and auto-categorizes the news according to affect sensitivity. There are three main factors that distinguish our work from other similar ones. First, we have integrated the approach to sense affective information from news-texts by applying a cognitive theory of emotions known as the OCC model that none have ever considered for news classification. Second, instead of any machine learning algorithm, we used common-sense and current-affairs as our knowledgebase with a rule based approach to assess each line of text by assigning a numerical valence and finally, natural language processing (NLP) technologies are used to perform automated categorization of news stories on the basis of emotional affinity. Relying on these paradigms and content analysis technologies, we have developed a news-browser that can fetch the news from RSS news-feeds and categorizes the theme of the news according to eight emotion-types plus a neutral category for quicker and intuitive understanding.
OreDesk: A Tool for Retrieving Data History Based on User Operations
Authors: Ryo Ohsawa, Kazunori Takashio, Hideyuki Tokuda
Venue: Proceedings of the Eighth IEEE International Symposium on Multimedia (2006)

During day-to-day activities, a user refers to various data items on a PC, such as documents, images, and audio clips. However, when the number of items in the history increases, locating the data becomes more complicated. We propose a novel system called "OreDesk" to retrieve particular data items from the history. OreDesk calculates the "Active Index" and "Relation Index" values for each data item based on the user operations. Active Index indicates the interest of a user in the data. Relation Index indicates how closely one data item is related to another. By using these indices, data can be retrieved on the basis of the association of user experiences. OreDesk also provides users with facilities such as "Searching Tool for Related Data" and "Timeline Viewer". OreDesk is available at http://oredesk.net/ as a free software.
Using Attribute-Based Access Control to Enable Attribute-Based Messaging
Authors: Rakesh Bobba, Omid Fatemieh, Fariba Khan, Carl A. Gunter, Himanshu Khurana
Venue: Proceedings of the 22nd Annual Computer Security Applications Conference (2006)

Attribute Based Messaging (ABM) enables message senders to dynamically create a list of recipients based on their attributes as inferred from an enterprise database. Such targeted messaging can reduce unnecessary communications and enhance privacy, but faces challenges in access control. In this paper we explore an approach to ABM based on deriving access control information from the same attribute database exploited by the addressing scheme. We show how to address three key challenges. First, we demonstrate a manageable access control system based on attributes. Second we show how this can be used with existing messaging systems to provide a practical deployment strategy. Third, we show that such a system can be efficient enough to support ABM for mid-size enterprises. Our implementation can dispatch ABM messages approved by XACML review for an enterprise of at least 60,000 users with only seconds of latency.
A Framework for Desktop GRID Applications: CCADAJ
Authors: Iyad Alshabani, Richard Olejnik, Bernard Toursel, Marek Tudruj, Eryk Laskowski
Venue: Proceedings of the Proceedings of The Fifth International Symposium on Parallel and Distributed Computing (2006)

We propose a new component framework over a middleware platform for GRID computing: DG-ADAJ (Desktop GRID -- Adaptive Distributed Application in Java). Our platform allows to have a Single System Image (SSI) of the GRID platform. It gives a specialmechanism at middleware level which assures dynamic and automatic adaptation to variations of computation methods and execution platform. DG-ADAJ gives also specific mechanisms based on control components which helps a users to build component-based parallel/distributed applications. We use the CCA (Common Component Architecture) as a component architecture model for our framework. CCADAJ (CCA-ADAJ) is a layer above the DG-ADAJ environment, which helps user to build his parallel/distributed applications by assembling components in a transparent way and which exploits the parallelism of the environment.
Discovery of Collocation Episodes in Spatiotemporal Data
Authors: Huiping Cao, Nikos Mamoulis, David W. Cheung
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

Given a collection of trajectories of moving objects with different types (e.g., pumas, deers, vultures, etc.), we introduce the problem of discovering collocation episodes in them (e.g., if a puma is moving near a deer, then a vulture is also going to move close to the same deer with high probability within the next 3 minutes). Collocation episodes catch the inter-movement regularities among different types of objects. We formally define the problem of mining collocation episodes and propose two scaleable algorithms for its efficient solution. We empirically evaluate the performance of the proposed methods using synthetically generated data that emulate real-world object movements.
Research on \tau-Parameter Fuzzy Concept Lattice for Grid Resource
Authors: Zhenguo Shi, Zongtian Liu, Qiang Wu
Venue: Proceedings of the Second International Conference on Semantics, Knowledge, and Grid (2006)

It is a pivotal task how to organize and manage resources for Grid researchs and applications.This paper first proposes Grid resource management strategies by employing \tau-parameter fuzzy concept lattice and fuzzy concept trie and combines FCA theory with Grid resource management technology. The formal concept definitions of Grid and resource are given and \tau-parameter fuzzy concept lattice model of the Grid resources is proposed.The extent trie and intent trie of fuzzy concepts for the Grid resources are constructed and the algorithms are developed for trie creation and retrieval to resources and services by FCA method.Experiments and application examples show that our method of resource organization and management is feasible and effective.
The effectiveness of adaptive computer use for learning vocabulary
Authors: Joan Jamieson
Venue:  (2006)

Do language learners benefit from an adaptive computer application that can provide appropriate learning materials according to their learning styles? In the field of second language acquisition, it has been advocated that the match between learning styles and material presentations is necessary for successful language learning. Most commercial software for language learning, however, works the same for all users, and it is very rare to see an adaptive feature in computerized language learning materials. Moreover, there has been little research on the computer applications that employ learning styles for language learning, and it is not yet clear whether the adaptive use of computers according to learning styles is effective. In order to investigate this issue, a computer application embedded with two types of learning-style based materials for English vocabulary learning was created, and a total of 145 Japanese university students participated in the study. After being judged on their learning material preferences through questionnaires, half of the participants received computerized vocabulary instruction based on their learning preferences (a matched group), and the other half were assigned vocabulary instruction that was not suited for their learning preferences (a non-matched group). Both groups studied the same twelve academic words in the computer application, and were tested on their vocabulary achievement soon after the treatment and one week after the treatment. By comparing the results of the two groups, the effectiveness of computerized material adjustments according to learning styles was examined. Contrary to the initial expectation, the results showed no significant differences on vocabulary achievement between the matched and non-matched groups in both materials. Also, there were no significant differences on the learning behavior between the two groups. These results indicated that the learning-style based matching was not effective and did not create a better learning environment for the Japanese participants in the matched groups. However, it was found that both of the materials which included various learning-style elements were suitable for most of the participants, and facilitated their vocabulary retention rates regardless of their preferences. Based on these findings, implications for computerized teaching materials and suggestions for further research were considered.
Service domains for ambient services: concept and experimentation
Authors: Seng Wai Loke, Shonali Krishnaswamy, Thin Thin Naing
Venue: Mobile Networks and Applications (2005)

We investigate ambient services, which we define as services that are related to the surrounding physical environment of the user, are locally useful and can be considered a form of location-based services. We introduce the notion of service domain which refers to the geographical area of relevance and utility for ambient services. We also consider a stereotypical case where a user might be within multiple service domains at the same time (when the service domains containing the user overlap) and so, can utilize a collection of services comprising services selected from each of the service domains containing the user. A language of operators is given for defining such a collection of services in terms of constituent services from the overlapping service-domains. Moreover, we describe and evaluate a prototype system that shows how to compute the services for a user in multiple service domains. The result is a framework for reasoning about ambient services for filtering or proactively suggesting mobile services based on geographical boundaries.
Web-based multimedia collaboration system for medical images analysis and diagnosis
Authors: Yau Lin Chan, Yu S. Lim, David Dagan Feng
Venue: Selected papers from the 2002 Pan-Sydney workshop on Visualisation - Volume 22 (2003)

Development of Telemedicine technologies are generating great impact in the field of health care services to overcome geographical displacement economically and efficiently. Previous researches about collaborative telemedicine have introduced many concepts to generate fundamental groundwork such as providing concrete image display, identical information sharing and distributed data management. The efficiency and effectiveness of telemedicine according to collaborative group work and consultation are needed to be considered for maximizing use of the system. We proposed the web based multimedia collaboration system for medical image analysis, diagnosis and report according to the concept of CSCW. The web based system can provide easy access to the user using Internet and also operating system independent. The efficiency of collaboration and consultation could be increased by providing video and audio data that user could aware the presence of other participants. The system network structure is server supported peer-to-peer system for efficient transmission of video and audio simultaneously. Proposed system can effectively provides a tool for collaboration and discussion about medical images.
Liveness Detection for Fingerprint Scanners Based on the Statistics of Wavelet Signal Processing
Authors: Bozhao Tan, Stephanie Schuckers
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

Fingerprint scanners can be spoofed by artificial fingers using moldable plastic, clay, Play-Doh, gelatin, silicone rubber materials, etc. Liveness detection is an anti-spoofing method which can detect physiological signs of life from fingerprints to ensure only live fingers can be captured for enrollment or authentication. In this paper, a new method based on the wavelet transform on the ridge signal extracted along the ridge mask is proposed which can detect the perspiration phenomenon using only a single image. Statistical features are extracted for multiresolution scales to discriminate between live and non-live fingers. Based on these features, we use a classification tree to generate the decision rules for the liveness classification. We test this method on the dataset which contains about 58 live, 80 spoof (50 made from Play-Doh and 30 made from gelatin), and 25 cadaver subjects for 3 different scanners. Also, we test this method on a second dataset which contains 33 live and 33 spoof (made from gelatin) subjects. The proposed liveness detection method is purely software based and application of this method can provide anti-spoofing protection for fingerprint scanners.
Neural Basis of the Retrieval of People's Names: Evidence from Brain-Damaged Patients and fMRI
Authors: Takashi Tsukiura, Toshikatsu Fujii, Reiko Fukatsu, Taisuke Otsuki, Jiro Okuda, Atsushi Umetsu, Kyoko Suzuki, Michio Tabuchi, Isao Yanagawa, Tatsuo Nagasaka, Ryuta Kawashima, Hiroshi Fukuda, Shoki Takahashi, Atsushi Yamadori
Venue: Journal of Cognitive Neuroscience (2002)

The aim of this study was to identify the neuroanatomical basis of the retrieval of people's names. Lesion data showed that patients with language-dominant temporal lobectomy had impairments in their ability to retrieve familiar and newly learned people's names, whereas patients with language-nondominant temporal lobectomy had difficulty retrieving newly learned people's names. Functional magnetic resonance imaging experiments revealed activations in the left temporal polar region during the retrieval of familiar and newly learned people's names, and in the right superior temporal and bilateral prefrontal cortices during the retrieval of newly learned information from face cues. These data provide new evidence that the left anterior temporal region is crucial for the retrieval of people's names irrespective of their familiarity and that the right superior temporal and bilateral prefrontal areas are crucial for the process of associating newly learned people's faces and names.
Designing Fuzzy Ensemble Classifiers by Evolutionary Multiobjective Optimization with an Entropy-Based Diversity Criterion
Authors: Yusuke Nojima, Hisao Ishibuchi
Venue: Proceedings of the Sixth International Conference on Hybrid Intelligent Systems (2006)

In this paper, we propose a multi-classifier coding scheme and an entropy-based diversity criterion in evolutionary multiobjective optimization algorithms for the design of fuzzy ensemble classifiers. In a multi-classifier coding scheme, an ensemble classifier is coded as an integer string. Each string is evaluated by using its accuracy and diversity. We use two accuracy criteria. One is the overall classification rate of the string as an ensemble classifier. The other is the average classification rate of component classifiers in the ensemble classifier. As a diversity criterion, we use the entropy of outputs from component classifiers in the ensemble classifier. We examine four formulations based on the above criteria through computational experiments on benchmark data sets in the UCI machine learning repository. The experimental results show the effectiveness of the multi-classifier coding scheme and the entropy-based diversity criterion.
2005 Special Issue: Emotion recognition through facial expression analysis based on a neurofuzzy network
Authors: Spiros V. Ioannou, Amaryllis T. Raouzaiou, Vasilis A. Tzouvaras, Theofilos P. Mailis, Kostas C. Karpouzis, Stefanos D. Kollias
Venue: Neural Networks (2005)

Extracting and validating emotional cues through analysis of users' facial expressions is of high importance for improving the level of interaction in man machine communication systems. Extraction of appropriate facial features and consequent recognition of the user's emotional state that can be robust to facial expression variations among different users is the topic of this paper. Facial animation parameters (FAPs) defined according to the ISO MPEG-4 standard are extracted by a robust facial analysis system, accompanied by appropriate confidence measures of the estimation accuracy. A novel neurofuzzy system is then created, based on rules that have been defined through analysis of FAP variations both at the discrete emotional space, as well as in the 2D continuous activation-evaluation one. The neurofuzzy system allows for further learning and adaptation to specific users' facial expression characteristics, measured though FAP estimation in real life application of the system, using analysis by clustering of the obtained FAP values. Experimental studies with emotionally expressive datasets, generated in the EC IST ERMIS project indicate the good performance and potential of the developed technologies.
Ranking Pages by Topology and Popularity within Web Sites
Authors: José Borges, Mark Levene
Venue: World Wide Web (2006)

We compare two link analysis ranking methods of web pages in a site. The first, called Site Rank, is an adaptation of PageRank to the granularity of a web site and the second, called Popularity Rank, is based on the frequencies of user clicks on the outlinks in a page that are captured by navigation sessions of users through the web site. We ran experiments on artificially created web sites of different sizes and on two real data sets, employing the relative entropy to compare the distributions of the two ranking methods. For the real data sets we also employ a nonparametric measure, called Spearman's footrule, which we use to compare the top-ten web pages ranked by the two methods. Our main result is that the distributions of the Popularity Rank and Site Rank are surprisingly close to each other, implying that the topology of a web site is very instrumental in guiding users through the site. Thus, in practice, the Site Rank provides a reasonable first order approximation of the aggregate behaviour of users within a web site given by the Popularity Rank.
An Efficient Hybrid Fuzzy Clustering Method
Authors: Mehdi Mohseni, Behrouz Minaei
Venue: Proceedings of the First International Workshop on Semantic Media Adaptation and Personalization (2006)

It is known that fuzzy algorithms will stop minimizing the objective function whenever reaches to a local minimum. It is known also that they are biased with the initial values of input parameters. In this work we address the minimizing problem of the objective function in the field of fuzzy clustering and introduce a method which is based on the Majorization idea and the KNN algorithm. It speeds up the search for the minimum, passes the local minimum, and also tries to set the initial values into sound values. We use a modified version of the KNN in such a way that the initial values for the parameters can be settled. There are two approaches for dealing with local minima. The algorithm has been put into study by applying it into three known datasets. The results show that the performance of the proposed method is promising.
Policies for Caching OLAP Queries in Internet Proxies
Authors: Thanasis Loukopoulos Ishfaq Ahmad
Venue: IEEE Transactions on Parallel and Distributed Systems (2006)

The Internet now offers more than just simple information to the users. Decision makers can now issue analytical, as opposed to transactional, queries that involve massive data (such as, aggregations of millions of rows in a relational database) in order to identify useful trends and patterns. Such queries are often referred to as On-Line-Analytical Processing (OLAP). Typically, pages carrying query results do not exhibit temporal locality and, therefore, are not considered for caching at Internet proxies. In OLAP processing, this is a major problem as the cost of these queries is significantly larger than that of the transactional queries. This paper proposes a technique to reduce the response time for OLAP queries originating from geographically distributed private LANs and issued through the Web toward a central data warehouse (DW) of an enterprise. An active caching scheme is introduced that enables the LAN proxies to cache some parts of the data, together with the semantics of the DW, in order to process queries and construct the resulting pages. OLAP queries arriving at the proxy are either satisfied locally or from the DW, depending on the relative access costs. We formulate a cost model for characterizing the respective latencies, taking into consideration the combined effects of both common Web access and query processing. We propose a cache admittance and replacement algorithm that operates on a hybrid Web-OLAP input, outperforming both pure-Web and pure-OLAP caching schemes.
Scientific Workflows: More e-Science Mileage from Cyberinfrastructure
Authors: Bertram Ludascher, Shawn Bowers, Timothy McPhillips, Norbert Podhorszki
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

We view scientific workflows as the domain scientist's way to harness cyberinfrastructure for e-Science. Domain scientists are often interested in "end-to-end" frameworks which include data acquisition, transformation, analysis, visualization, and other steps. While there is no lack of technologies and standards to choose from, a simple, unified framework combining data modeling and processoriented modeling and design of scientific workflows has yet to emerge. Towards this end, we introduce a number of concepts such as models of computation and provenance, actor-oriented modeling, adapters, hybrid types, and higher-order components, and then outline a particular composition of some of these concepts, yielding a promising new synthesis for describing scientific workflows, i.e., Collection-Oriented Modeling and Design (COMAD).