ppxscal/embedding_network huggingface dataset:
Mirror neuron system differentially activated by facial expressions and social hand gestures: A functional magnetic resonance imaging study
Authors: Kimberly J. Montgomery, James V. Haxby
Venue: Journal of Cognitive Neuroscience (2008)

Facial expressions and hand gestures are utilized in nonverbal communication to convey socially relevant information. One key process that mediates nonverbal communication is simulation. The mirror neuron system (MNS), which maps observed actions onto the motor representations used when producing those actions, likely plays a role in simulation. Previous neuroimaging experiments have identified a putative human MNS that includes the inferior parietal lobule (IPL) and the frontal operculum. Although understanding nonverbal communication presumably involves the MNS, it is unknown whether these two forms of nonverbal social communication have distinct representations within that system. Here we report the results of a functional magnetic resonance imaging experiment in which participants viewed, imitated, and produced facial expressions and social hand gestures. The observation and execution of facial expressions and social hand gestures activated the MNS, but the magnitude of response differed. Activation in the IPL was greater for social hand gestures, whereas activation in the frontal operculum was greater for viewing facial expressions. The locations of neural activity evoked by viewing facial expressions and social hand gestures in the frontal operculum were significantly different. These data argue that there are distinct representations of different types of social nonverbal communication in the MNS.
Computer Aided Diagnosis System to Detect Breast Cancer Pathological Lesions
Authors: Yosvany López, Andra Novoa, Miguel A. Guevara, Nicolás Quintana, Augusto Silva
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

Breast cancer is one of the most frequent forms of women's cancer over the world. Studies of the World Health Organization (WHO) reported 1,151,298 cases in 2002. A reliable Computer-Aided-Diagnosis (CAD) system for automated detection/classification of pathological lesions is very useful and helpful, providing a valuable "second opinion" to medical personnel. In this work, we describe a new CAD system to diagnose six mammography pathological lesions classes (calcifications, well-defined/circumscribed masses, spiculated masses, ill-defined masses, architectural distortions and asymmetries) as benign or malignant tissues. Two different Artificial Neural Networks models: Feedforward Backpropagation and Generalized Regression were tested statistically with a precision of 94.0% and 80.0% of true positives, respectively. This CAD system was validated successfully on the MiniMammographic Image Analysis Society (MiniMIAS) database, with a dataset formed by 100 images. The CAD system performance shows similar or better classification results compared with others available methods.
TiGenerator: Object-based training image generator
Authors: Amisha Maharaja
Venue: Computers Geosciences (2008)

A plug-in, TiGenerator, is written for the open source software SGeMS to generate 3D, categorical training images. It provides a graphical user interface to generate various parametric as well as non-parametric shapes using unconditional Boolean simulation with interaction between the objects. The code design allows new shapes and features to be added easily without altering the main algorithm.
Reflective Framework for Interactive Modeling and Simulation of Intelligent Systems
Authors: Vladimír Janouek, Elod Kironský
Venue: Proceedings of the 2008 19th International Conference on Systems Engineering (2008)

This paper presents a new implementation of a modeling and simulation framework based on the DEVS formalism. This framework uses rapid prototyping, interactivity and a reflective interface to provide a high degree of dynamism during the design of systems. It utilizes exploratory programming techniques as well as the flexibility of prototype based object oriented programming. We are focusing on the description of the core part of our framework, discussing its advantages compared with other frameworks. We present some examples of application, too.
Post Processing of Breast Phantom MRI-156 Images Using Snake Algorithm
Authors: Wan Eny Zarina W. Abd. Rahman, Arsmah Ibrahim, Zainab Abu Bakar, Rozi Mahmud, Md Saion Salikin, Mazani Manaf
Venue: Proceedings of the 2008 Fifth International Conference on Computer Graphics, Imaging and Visualisation (2008)

Mammography is a known method for the early detection of breast cancer. However, the mammograms which are in black and white and in the shade of grey have some limitations in portraying the abnormalities. Image segmentation is a very crucial process in detecting abnormalities in computed radiography mammographic images. Active contours which are known as 'snake' are dynamic algorithms which can be used to perform the image segmentation. In order to test the applicability of the snake algorithm in performing segmentation, the breast phantom MRI-156 images are used. Only the breast phantom images at the exposures of 25 kV, 28 kV and 35 kV with milliampere (mAs) of 0.5 are considered. It is found that when the image is divided into four equal regions, the detection of abnormalities in the image is more effective as compared to the image processed as a whole.
Evolving XSLT Stylesheets for Document Transformation
Authors: Pablo Garcia-Sanchez, Juan J. Merelo, Juan L. Laredo, Antonio Mora, Pedro A. Castillo
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

This paper presents a new version of an evolutionary algorithm that creates XSLT programs from its intended input and output. XSLT is a general purpose, document-oriented functional language, generally used to transform XML documents (or, in general, solve any problem that can be coded as an XML document). Previously, a solution that solved the problem efficiently was proposed. In this paper, we improve on those results by testing different fitness functions, adding a new operator and changing the type of desired output document that can be obtained. The experiments show that the best results are obtained without considering the XSLT length and including this new operator.
Aspects regarding the use of SEC-DED codes to the cache level of a memory hierarchy
Authors: Ovidiu Novac, Mircea Vladutiu, Stefan Vari-Kakas, Francisc Ioan Hathazi, Mihaela Novac
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

In this paper we will apply a SEC-DED code to the cache level of a memory hierarchy. From the category of SEC-DED (Single Error Correction Double Error Detection) codes we select the Hsiao code. The Hsiao code is an odd-weight-column SEC-DED code. For correction of single-bit error we use a syndrome decoder, a syndrome generator and the check bits generator circuit.
A multisecret sharing scheme for color images based on cellular automata
Authors: G. Alvarez, L. Hernández Encinas, A. Martín del Rey
Venue: Information Sciences: an International Journal (2008)

In this work a new multisecret sharing scheme for secret color images among a set of users is proposed. The protocol allows that each participant in the scheme to share a secret color image with the rest of participants in such a way that all of them can recover all the secret color images only if the whole set of participants pools their shadows. The proposed scheme is based on the use of bidimensional reversible cellular automata with memory. The security of the scheme is studied and it is proved that the protocol is ideal and perfect and that it resists the most important statistical attacks.
Approximate convex decomposition and its applications
Authors: Nancy M. Amato
Venue:  (2006)

Geometric computations are essential in many real-world problems. One important issue in geometric computations is that the geometric models in these problems can be so large that computations on them have infeasible storage or computation time requirements. Decomposition is a technique commonly used to partition complex models into simpler components. Whereas decomposition into convex components results in pieces that are easy to process, such decompositions can be costly to construct and can result in representations with an unmanageable number of components. In this work, we have developed an approximate technique, called Approximate Convex Decomposition (ACD), which decomposes a given polygon or polyhedron into "approximately convex" pieces that may provide similar benefits as convex components, while the resulting decomposition is both significantly smaller (typically by orders of magnitude) and can be computed more efficiently. Indeed, for many applications, an ACD can represent the important structural features of the model more accurately by providing a mechanism for ignoring less significant features, such as wrinkles and surface texture. Our study of a wide range of applications shows that in addition to providing computational efficiency, ACD also provides natural multi-resolution or hierarchical representations. In this dissertation, we provide some examples of ACD's many potential applications, such as particle simulation, mesh generation, motion planning, and skeleton extraction.
Integrating KPCA and LS-SVM for Chaotic Time Series Forecasting Via Similarity Analysis
Authors: Jian Cheng, Jian-Sheng Qian, Xiang-Ting Wang, Li-Cheng Jiao
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

A novel approach is presented to reconstruct the phase space using kernel principal component analysis (KPCA) with similarity analysis and forecast chaotic time series based on a least squares support vector machines (LS-SVM) in the phase space. A three-stage architecture is proposed to improve its prediction accuracy and generalization performance for chaotic time series forecasting. In the first stage, KPCA is adopted to extract features and obtain kernel principal components. Then, in the second stage, the similarity is analyzed between every principal components and output variable, and some principal components are chosen to construct the phase space of chaotic time series according to their similarity degree to the model output. LS-SVM is employed in the third stage for forecasting the chaotic time series. The method was evaluated by coal mine gas concentration in experiment. The simulation shows that LS-SVM by phase space reconstruction using KPCA with similarity analysis performs much better than that without similarity analysis.
VLSI And System Performance Modeling
Authors: Sorin lacobovici, Chakchung Ng
Venue: IEEE Micro (1987)

Complex VLSI chips and systems call for performance evaluation techniques that are easy to understand, change, and maintain. High-level simulation environments answer this need.
Assessing Sentiment of Text by Semantic Dependency and Contextual Valence Analysis
Authors: Mostafa Al Shaikh, Helmut Prendinger, Ishizuka Mitsuru
Venue: Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction (2007)

Text is not only an important medium to describe facts and events, but also to effectively communicate information about the writer's (positive or negative) sentiment underlying an opinion, and an affect or emotion (e.g. happy, fearful, surprised etc.). We consider sentiment assessment and emotion sensing from text as two different problems, whereby sentiment assessment is a prior task to emotion sensing. This paper presents an approach to sentiment assessment, i.e. the recognition of negative or positive sense of a sentence. We perform semantic dependency analysis on the semantic verb frames of each sentence, and apply a set of rules to each dependency relation to calculate the contextual valence of the whole sentence. By employing a domain-independent, rule-based approach, our system is able to automatically identify sentence-level sentiment. Empirical results indicate that our system outperforms another state-of-the-art approach.
An Integrated IT System for Phenotypic and Genotypic Data Mining and Management
Authors: Angelo Nuzzo, Daniele Segagni, Giuseppe Milani, Cinzia Sala, Cristiana Larizza
Venue: Proceedings of the 11th conference on Artificial Intelligence in Medicine (2007)

This paper describes the application of an information technology infrastructure aimed at supporting translational bioinformatics studies which need the joint management of phenotypic and genotypic data. The system provides an integrated and easy to use software environment, based on data warehouse and data mining tools, to discover the most frequent complex phenotypes and search their penetrance and heritability by mapping them on the population pedigree. We first use a logical formalization to define phenotypes of interest in order to retrieve individuals having that phenotype from the electronic medical record. We then use an open-source Web-based data warehouse application for analyzing phenotypic data and presenting the results in a multidimensional format. Relationships between the selected individuals are automatically visualized by integrating in the system an ad-hoc developed pedigree visualization tool. Finally, the application of the system to support a genetic study of an isolated population, the Val Borbera project, is presented.
A coupled-cluster approach to polarizabilities: Computational aspects
Authors: B. K. Sahoo, B. P. Das, R. K. Chaudhuri, D. Mukherjee
Venue: Journal of Computational Methods in Sciences and Engineering (2007)

We present ab initio calculations of both the dipole and quadrupole polarizabilities within the framework of the relativistic coupled-cluster theory. We directly solve the first order perturbed equation arising from a general one-electron perturbation, thereby avoiding an explicit summation over intermediate states. This method can be applied to a wide range of problems including the high precision calculations of very small but finite parity non-conserving and CP violating amplitudes. We discuss in detail the computational methods used in the calculations and investigate the trends of electron correlation effects for the dipole and quadrupole polarizabilities.
The Greek Electronic Government Interoperability Framework: Standards and Infrastructures for One-Stop Service Provision
Authors: Yannis Charalabidis, Fenareti Lampathaki, Demetrios Sarantis, Aikaterini-Maria Sourouni, Spiros Mouzakitis, George Gionis, Sotirios Koussouris, Christos Ntanos, Christos Tsiakaliaris, Vasilis Tountopoulos, Dimitris Askounis
Venue: Proceedings of the 2008 Panhellenic Conference on Informatics (2008)

The need for centralized e-Government strategies and policies is a fertile ground for the development of e-Government Interoperability Frameworks (eGIFs). Integrated Information Systems and one-stop public services to citizens and businesses are heavily dependent on the resolution of the ever-expanding interoperability challenge and the satisfaction of public services' stakeholders. This can only be realistically addressed if the scope of eGIFs is widened, to include service composition and discovery, security standards, certification of public sites, as well as unified data models for achieving a common understanding of semantics at a syntax-independent level. The Greek eGIF presents a transition from paper-based specifications to a robust system that acts as a repository of systems, services, data schemas, certification tools and training material. This paper presents the objectives, the overall methodology and the architecture of the Greek eGIF, that meets today's demands for modelling, storing, managing and updating a vast number of eGovernment-related information.
Concurrent and Located Synchronizations in π-Calculus
Authors: Ivan Lanese
Venue: Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science (2007)

We present two novel semantics for ¿-calculus. The first allows one to observe on which channel a synchronization is performed, while the second allows concurrent actions, provided that they do not compete for resources. We present both a reduction and a labeled semantics, and show that they induce the same behavioral equivalence. As our main result we show that bisimilarity is a congruence for the concurrent semantics. This important property fails for the standard semantics.
Terminating Tableaux for Hybrid Logic with the Difference Modality and Converse
Authors: Mark Kaminski, Gert Smolka
Venue: Proceedings of the 4th international joint conference on Automated Reasoning (2008)

We present the first terminating tableau calculus for basic hybrid logic with the difference modality and converse modalities. The language under consideration is basic multi-modal logic extended with nominals, the satisfaction operator, converse, global and difference modalities. All of the constructs are handled natively.To obtain termination, we extend chain-based blocking for logics with converse by a complete treatment of difference.Completeness of our calculus is shown via a model existence theorem that refines previous constructions by distinguishing between modal and equational state equivalence.
Web-Based Anaphora Resolution for the QUASAR Question Answering System
Authors: Davide Buscaldi, Yassine Benajiba, Paolo Rosso, Emilio Sanchis
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

This paper describes the work done by the RFIA group at the Departamento de Sistemas Informáticos y Computación of the Universidad Politécnica of Valencia for the 2007 edition of the CLEF Question Answering task. We participated in the Spanish monolingual task only. A series of technical difficulties prevented us from completing all the tasks we subscribed. Our 2006 system was modified in order to comply with the 2007 guidelines, especially with regard to anaphora resolution, tackled with a web based anaphora resolution module.
Self-organized flocking with a mobile robot swarm
Authors: Ali E. Turgut, Hande Çelikkanat, Fatih Gökçe, Erol Şahin
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1 (2008)

This paper studies self-organized flocking in a swarm of mobile robots. We present Kobot, a mobile robot platform developed specifically for swarm robotic studies, briefly describing its sensing and communication abilities. In particular, we describe a scalable method that allows the robots to sense the orientations of their neighbors using a digital compass and wireless communication. Then we propose a behavior for a swarm of robots that creates self-organized flocking by using heading alignment and proximal control. The flocking behavior is observed to operate in three phases: alignment, advance, and avoidance. We evaluate four variants of this behavior by setting its parameters to extreme values and analyze the performance of flocking using a number of metrics, such as order and entropy. Our results show that, the flocking behavior obtained under appropriate parameter values, is quite robust and generates successful self-organized flocking in constraint environments.
Estimation of the Current Density in a Dynamic Heart Model and Visualization of Its Propagation
Authors: Liansheng Wang, Pheng Ann Heng, Wong Tien Tsin
Venue: Proceedings of the 4th international workshop on Medical Imaging and Augmented Reality (2008)

The inverse approach from MR images to electrical propagation is very novel, but difficult due to complicated processes from electrical excitation to heart contraction. A novel strategy is presented to recover cardiac electrical excitation pattern from medical image sequences and ECG data. We used MRI images to estimate the current density and visualize it on the surface of the heart model. The ECG data also be used to achieve the time synchronization when the propagation of the current density. Experiments are conducted on a set of real time MRI images, also with the real ECG data, and we get favorable results.
Mass Interpersonal Persuasion: An Early View of a New Phenomenon
Authors: B. J. Fogg
Venue: Proceedings of the 3rd international conference on Persuasive Technology (2008)

In 2007 a new form of persuasion emerged: mass interpersonal persuasion (MIP). The advances in online social networks now allow individuals to change attitudes and behaviors on a mass scale. MIP has six components: persuasive experience, automated structure, social distribution, rapid cycle, huge social graph, and measured impact. Before the launch of Facebook Platform, these six components had never come together in one system. As tools for creating MIP become available to ordinary people, individuals and small groups can better reach and persuade masses. This new phenomenon will change the future of persuasion.
A Novel Multi-objective Evolutionary Algorithm
Authors: Bojin Zheng, Ting Hu
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

Evolutionary Algorithms are recognized to be efficient to deal with Multi-objective Optimization Problems(MOPs) which are difficult to be solved with traditional methods. Here a new Multi-objective Optimization Evolutionary Algorithm named DGPS which is compound with Geometrical Pareto Selection Method (GPS), Weighted Sum Method (WSM) and Dynamical Evolutionary Algorithm (DEA) is proposed. Some famous benchmark functions are carried out to test this algorithm's performance and the numerical experiments show that this algorithm runs much faster than SPEA2, NSGAII, HPMOEA and can obtain finer approximate Pareto fronts which include thousands of well-distributed points.
Large-Scale Datasets Visualization on Networks Using Dynamic Pipeline Decomposition and Mapping
Authors: Chun Hu, Jinwen Tian
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

Datasets of tens of gigabytes are becoming common in computational and experimental science. Providing remote visualization of these large datasets with adequate levels of quality and interactivity is an extremely challenging task, particularly for scientists who collaborate in widely distributed locations and their primary access to visualization resources is a desktop computer. This paper describes a remote visualization system for large-scale terrain rendering, which adaptively decomposes and maps the terrain visualization pipeline such as filtering, refinement, rendering, and display onto a wide-area network. The prototype system was implemented on China next-generation Internet backbone. Scientists dispersed in three cities could visualize 3D flight simulation at about 30 frames per second; furthermore, the need for data replication to local desktops was eliminated.
Checking Correctness of Transactional Behaviors
Authors: Vincenzo Ciancia, Gian Luigi Ferrari, Roberto Guanciale, Daniele Strollo
Venue: Proceedings of the 28th IFIP WG 6.1 international conference on Formal Techniques for Networked and Distributed Systems (2008)

The Signal Calculus is an asynchronous process calculus featuring multicast communication. It relies on explicit modeling of the communication structure of the network (communication flows), and on handling sessions, even multi-party. The calculus is strongly motivated by the practical needs of Service-Oriented Computing, and there exists a Java implementation, called JSCL, with a graphical modeling framework. To the aim of adding to SC (and JSCL) a verification environment, in this work we introduce the abstract semantics of SC, based on bisimulation. We show an example exploiting bisimilarity to prove the correctness of an SC model with respects to a transactional isolation requirement.