ppxscal/embedding_network huggingface dataset:
E-commerce Security Risk Analysis and Management Strategies of Commercial Banks
Authors: Li Bo, Xu Congwei
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

With the rapid on-line business development of the commercial banks and the great changes of management circumstances and operating modes which make the traditional risk management confronted with challenges, the e-commerce risk management becomes an important issue of theory and practice. This paper outlines several kinds of e-commerce security risks of commercial banks, and analyzes in detail two kinds of risk analysis methods of the e-commerce security which measure and assess the e-commerce security risk. And then the risk management strategies of e-commerce security of the commercial banks are addressed. In the end, it is pointed out that the study of the risk analysis methods and the management strategies provides an available security framework for Chinese commercial banks to implement the e-commerce and manage the risk.
Tongue Image Segmentation Based on Fuzzy Rough Sets
Authors: Li Jiangping, Pan Baochang, Wei Yuke
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 03 (2009)

The paper studied a new theory of fuzzy rough sets, and presented a method to segment tongue image. It presented an algorithm of Fuzzy Rough Clustering Based on Grid by the theory. The algorithm extracts condensation points by the theory of fuzzy rough sets, and quarters the data space layer by layer, and softens the edge of the dense block by drawing condensation points in the borders. The algorithm has been put into use in tongue image segmentation of Traditional Chinese Medicine (TCM). The application result indicated: The algorithm avoided segmenting image excessively and speeded up segmentation velocity by fuzzy grid dividing.
Towards Guidelines for a Development Process for Component-Based Embedded Systems
Authors: Rikard Land, Jan Carlson, Stig Larsson, Ivica Crnković
Venue: Proceedings of the International Conference on Computational Science and Its Applications: Part II (2009)

Software is more and more built from pre-existing components. This is true also for the embedded software domain, and there is a need to consider how development processes need to be changed to best utilize the component-based paradigm, and how processes and technologies must be designed to support each other. To facilitate this change towards component-based embedded software, this paper presents a set of process guidelines, named the Progress Process Guidelines (PPG), which is based on the structure of CMMI. This paper presents the structure of the PPG, and presents and analyzes the PPG parts which most closely relate to system verification, which is typically an important and difficult activity for embedded software.
Vision Based Metal Spectral Analysis Using Multi-label Classification
Authors: Eranga Ukwatta, Jagath Samarabandu
Venue: Proceedings of the 2009 Canadian Conference on Computer and Robot Vision (2009)

Industrial equipments that employ element identification tend to be expensive as they utilize built-in spectroscopes and computers for post processing. In this paper we present an in situ fully automatic method for detecting constituent elements in a sample specimen using computer vision and machine learning techniques on Laser Induced Breakdown Spectroscopy (LIBS) spectra. This enables the development of a compact and portable spectrometer on a high resolution video camera.In the traditional classification problem, classes are mutually exclusive by definition. However, in spectral analysis a spectrum could contain emissions from multiple elements such that the disjointness of the labels is no longer valid. We cast the metal detection problem as a multi-label classification and enable detection of elemental composition of the specimen. Here, we apply both Support Vector Machine (SVM) and Artificial Neural Networks (ANN) to multiple metal classification and compare the performance with a simple template matching technique. Both machine learning approaches yield correct identification of metals to an accuracy of 99%. Our method is useful in instances where accurate elemental analysis is not required but rather a qualitative analysis. Experiments on the simulation data show that our method is suitable for LIBS metal detection.
Electronic Nose Ovarian Carcinoma Diagnosis Based on Machine Learning Algorithms
Authors: José Chilo, György Horvath, Thomas Lindblad, Roland Olsson
Venue: Proceedings of the 9th Industrial Conference on Advances in Data Mining. Applications and Theoretical Aspects (2009)

Ovarian carcinoma is one of the most deadly diseases, especially in the case of late diagnosis. This paper describes the result of a pilot study on an early detection method that could be inexpensive and simple based on data processing and machine learning algorithms in an electronic nose system. Experimental analysis using real ovarian carcinoma samples is presented in this study. The electronic nose used in this pilot test is very much the same as a nose used to detect and identify explosives. However, even if the apparatus used is the same, it is shown that the use of proper algorithms for analysis of the multi-sensor data from the electronic nose yielded surprisingly good results with more than 77% classification rate. These results are suggestive for further extensive experiments and development of the hardware as well as the software.
Much Ado about Zero
Authors: Stefan Schirra
Venue: Efficient Algorithms: Essays Dedicated to Kurt Mehlhorn on the Occasion of His 60th Birthday (2009)

Zero separation bounds provide a lower bound on the absolute value of an arithmetic expression, unless the value is zero. Such separation bounds are used for verified identification of zero in sign computations with real algebraic numbers, especially with number types that record the computation history of a numerical value using expression dags. We summarize results on separation bounds and their use for adaptive sign computation with real algebraic numbers based on expression dags.
Blue versus Red: Towards a Model of Distributed Security Attacks
Authors: Neal Fultz, Jens Grossklags
Venue: Financial Cryptography and Data Security: 13th International Conference, FC 2009, Accra Beach, Barbados, February 23-26, 2009. Revised Selected Papers (2009)

We develop a two-sided multiplayer model of security in which attackers aim to deny service and defenders strategize to secure their assets. Attackers benefit from the successful compromise of target systems, however, may suffer penalties for increased attack activities. Defenders weigh the force of an attack against the cost of security. We consider security decision-making in tightly and loosely coupled networks and allow defense expenditures in protection and self-insurance technologies.
Integrating multiple learning components through Markov logic
Authors: Thomas G. Dietterich, Xinlong Bao
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 2 (2008)

This paper addresses the question of how statistical learning algorithms can be integrated into a larger AI system both from a practical engineering perspective and from the perspective of correct representation, learning, and reasoning. Our goal is to create an integrated intelligent system that can combine observed facts, hand-written rules, learned rules, and learned classifiers to perform joint learning and reasoning. Our solution, which has been implemented in the CALO system, integrates multiple learning components with a Markov Logic inference engine, so that the components can benefit from each other's predictions. We introduce two designs of the learning and reasoning layer in CALO: the MPE Architecture and the Marginal Probability Architecture. The architectures, interfaces, and algorithms employed in our two designs are described, followed by experimental evaluations of the performance of the two designs. We show that by integrating multiple learning components through Markov Logic, the performance of the system can be improved and that the Marginal Probability Architecture performs better than the MPE Architecture.
Integrity-Checking Framework: An In-situ Testing and Validation Framework for Wireless Sensor and Actuator Networks
Authors: S. Pennington, T. Bauge, B. Murray
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

Wireless sensor and actuator network applications require several levels of testing during their development.Although software algorithms can be tested through simulations and syntax checking, it is difficult to predict or test for problems that may occur once the wireless sensor and actuator has been deployed. The requirement for testing is not however limited to the development phase. During the lifecycle of the system, faults, upgrades, retasking, etc. lead to further needs for system validation. In this paper we review the state-of-the-art techniques for testing wireless sensor and actuator applications and propose the Integrity-Checking Framework. The framework provides in-situ full lifecycle testing and validation of wireless sensor and actuator applications by performing an “Integrity Check”, during which the sensor inputs and actuator responses are emulated within the physical wireless sensor and actuator. This enables application-level testing by feeding controlled information to the sensor inputs, while data processing, communication, aggregation and decision making continue as normal across the physical wireless sensor and actuator.
Rapid Classification of Surface Reflectance from Image Velocities
Authors: Katja Doerschner, Dan Kersten, Paul Schrater
Venue: Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns (2009)

We propose a method for rapidly classifying surface reflectance directly from the output of spatio-temporal filters applied to an image sequence of rotating objects. Using image data from only a single frame, we compute histograms of image velocities and classify these as being generated by a specular or a diffusely reflecting object. Exploiting characteristics of material-specific image velocities we show that our classification approach can predict the reflectance of novel 3D objects, as well as human perception.
Proceedings of the European Computing Conference: Volume 2, 1st edition
Authors: Nikos Mastorakis, Valeri Mladenov, Vassiliki T. Kontargyri
Venue:  (2009)

The European Computing Conference offers a unique forum for establishing new collaborations within present or upcoming research projects, exchanging useful ideas, presenting recent research results, participating in discussions and establishing new academic collaborations, linking university with the industry. Engineers and Scientists working on various areas of Systems Theory, Applied Mathematics, Simulation, Numerical and Computational Methods and Parallel Computing present the latest findings, advances, and current trends on a wide range of topics. This proceedings volume will be of interest to students, researchers, and practicing engineers.
A clinical decision support system for cancer diseases
Authors: André Cid Ferrizzi, Toni Jardini, Leandro Rincon Costa, Jucimara Colombo, Edmundo Carvalho Mauad, Lígia Maria Kerr, Geraldo Santiago Hidalgo, Paula Rahal, Carlos Roberto Valêncio
Venue: Proceedings of the 2008 Euro American Conference on Telematics and Information Systems (2008)

The second main cause of death in Brazil is cancer, and according to statistics disclosed by National Cancer Institute from Brazil (INCA) 466,730 new cases of cancer are forecast for 2008. The analysis of tumour tissues of various types and patients' clinical data, genetic profiles, characteristics of diseases and epidemiological data may lead to more precise diagnoses, providing more effective treatments. In this work we present a clinical decision support system for cancer diseases, which manages a relational database containing information relating to the tumour tissue and their location in freezers, patients and medical forms. Furthermore, it is also discussed some problems encountered, as database integration and the adoption of a standard to describe topography and morphology. It is also discussed the dynamic report generation functionality, that shows data in table and graph format, according to the user's configuration.
A Survey of Cloud Platforms and Their Future
Authors: Milad Pastaki Rad, Ali Sajedi Badashian, Gelare Meydanipour, Morteza Ashurzad Delcheh, Mahdi Alipour, Hamidreza Afzali
Venue: Proceedings of the International Conference on Computational Science and Its Applications: Part I (2009)

It is predicted that most computing and data storage will be done by cloud computing in the future. Tendency to use cloud services and changes in IT world to become service-based will be inevitable in future. This leading change toward cloud computing will be a great movement in IT dependent industries. One of the main parts of this variation is the usage of cloud platforms. This method will affect software engineering events in software production process. Cloud platform let developers write programs which can both run in cloud space and use available services provided in cloud space. In this paper, a survey on cloud platforms, their arrangements, foundation and infrastructure services and their main capabilities used in some leading software companies is presented.
Adaptive tutorial dialogue systems using deep NLP techniques
Authors: Myroslava O. Dzikovska, Charles B. Callaway, Elaine Farrow, Manuel Marques-Pita, Colin Matheson, Johanna D. Moore
Venue: Proceedings of Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations on XX (2007)

We present tutorial dialogue systems in two different domains that demonstrate the use of dialogue management and deep natural language processing techniques. Generation techniques are used to produce natural sounding feedback adapted to student performance and the dialogue history, and context is used to interpret tentative answers phrased as questions.
A Multi-functional Visualization System for Motion Captured Human Body Based on Virtual Reality Technology
Authors: Qichang He, Lifeng Zhang, Xiumin Fan, Yong Hu
Venue: Proceedings of the 2nd International Conference on Digital Human Modeling: Held as Part of HCI International 2009 (2009)

This study is to develop a multi-functional visualization system (KINE) for motion captured Human Body based on Virtual Reality (VR) technology, which reconstruct the skeleton rigid model motion in the 3D virtual environment. The KINE is based on VR general application development platform named VRFlier, which provide an innovative human-machine interaction. This paper focuses on the methods of human rigid modeling and motion reconstruction. The human rigid modeling is based on Rigid Body Assumption (RBA) theory and using Virtual Marker (VM) to position the arthrosis of linked body segment. The motion reconstruction is implemented through coordination transformation of Local Coordination System (LCS) defined by VM. KINE is applied in the research project "Mechanical Virtual Human of China", the results show that this software tool can help conveniently analyze the data collected by motion captured system.
Topology Control Target Tracking-Oriented
Authors: Dongmei Yan, JinKuan Wang, Li Liu, Bin Wang, Peng Xu
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

One of the most important constraints on wireless sensor network is the low power consumption. Therefore, topology of wireless sensor network must focus on power conservation. It is possible to extend the lifetime of a network by controlling its topology through clustering. Topology control target tracking-oriented based on overlapping clustering in wireless sensor network is proposed in this paper. When a target move to the sensing filed, cluster heads invite their neighboring sensors to form a cluster, the sensor information is passed on to cluster heads, where, in turn, transmit information to the base station. Utilizing cluster technology can make good use of each sensor nodes’ limited energy and perform tasks coordinately.
New Solutions of VoIP on Multi-hop Wireless Network
Authors: Shi Yuhe, Xu Jie
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

The effective provision of real-time, packet-based voice conversations over multi-hop wireless networks faces several stringent constraints not found in conventional packet-based networks. The wireless links in an ad hoc network are highly error prone and may go down frequently because of node mobility, interference, channel fading, and the lack of infrastructure, it is very difficult and challenging to implement voice transmission over multi-hop wireless networks. In this research, to maximize the performance of multi-hop wireless networks during voice transmission we choose some parameters and methodological approaches e.g. Since voice applications consume more energy than typical applications, we designed the ad hoc and adaptive control model to simulate our scheme.
Modeling letter-to-phoneme conversion as a phrase based statistical machine translation problem with minimum error rate training
Authors: Taraka Rama, Anil Kumar Singh, Sudheer Kolachina
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Student Research Workshop and Doctoral Consortium (2009)

Letter-to-phoneme conversion plays an important role in several applications. It can be a difficult task because the mapping from letters to phonemes can be many-to-many. We present a language independent letter-to-phoneme conversion approach which is based on the popular phrase based Statistical Machine Translation techniques. The results of our experiments clearly demonstrate that such techniques can be used effectively for letter-to-phoneme conversion. Our results show an overall improvement of 5.8% over the baseline and are comparable to the state of the art. We also propose a measure to estimate the difficulty level of L2P task for a language.
Providing Objective Feedback on Skill Assessment in a Dental Surgical Training Simulator
Authors: Phattanapon Rhienmora, Peter Haddawy, Siriwan Suebnukarn, Matthew N. Dailey
Venue: Proceedings of the 12th Conference on Artificial Intelligence in Medicine: Artificial Intelligence in Medicine (2009)

Dental students devote several years to the acquisition of sufficient psychomotor skills to prepare them for entry-level dental practice. Traditional methods of dental surgical skills training and assessment are being challenged by the complications such as the lack of real-world cases, unavailability of expert supervision and the subjective manner of surgical skills assessment. To overcome these challenges, we developed a dental training system that provides a VR environment with a haptic device for dental students to practice tooth preparation procedures. The system monitors important features of the procedure, objectively assesses the quality of the performed procedure using hidden Markov models, and provides objective feedback on the user's performance for each stage in the procedure. Important features for characterizing the quality of the procedure were identified based on interviews with experienced dentists. We evaluated the accuracy of the skill assessment with data collected from novice dental students as well as experienced dentists. We also evaluated the quality of the system's feedback by asking a dental expert for comments. The experimental results show high accuracy in classifying users into novice and expert, and the evaluation indicated a high acceptance rate for the generated feedback.
Advanced Biosignal Processing, xvi, 374 pgs. edition
Authors: Amine Nait-Ali
Venue:  (2009)

Through 17 chapters, this book presents the principle of many advanced biosignal processing techniques. After an important chapter introducing the main biosignal properties as well as the most recent acquisition techniques, it highlights five specific parts which build the body of this book. Each part concerns one of the most intensively used biosignals in the clinical routine, namely the Electrocardiogram (ECG), the Elektroenzephalogram (EEG), the Electromyogram (EMG) and the Evoked Potential (EP). In addition, each part gathers a certain number of chapters related to analysis, detection, classification, source separation and feature extraction. These aspects are explored by means of various advanced signal processing approaches, namely wavelets, Empirical Modal Decomposition, Neural networks, Markov models, Metaheuristics as well as hybrid approaches including wavelet networks, and neuro-fuzzy networks. The last part, concerns the Multimodal Biosignal processing, in which we present two different chapters related to the biomedical compression and the data fusion. Instead organising the chapters by approaches, the present book has been voluntarily structured according to signal categories (ECG, EEG, EMG, EP). This helps the reader, interested in a specific field, to assimilate easily the techniques dedicated to a given class of biosignals. Furthermore, most of signals used for illustration purpose in this book can be downloaded from the Medical Database for the Evaluation of Image and Signal Processing Algorithm. These materials assist considerably the user in evaluating the performances of their developed algorithms. This book is suited for final year graduate students, engineers and researchers in biomedical engineering and practicing engineers in biomedical science and medical physics. 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 Model of Personality and Emotional Traits
Authors: Margaret Mcrorie, Ian Sneddon, Etienne Sevin, Elisabetta Bevacqua, Catherine Pelachaud
Venue: Proceedings of the 9th International Conference on Intelligent Virtual Agents (2009)

How do we construct credible personalities? The current SAL (Sensitive Artificial Listeners) characters were constructed intuitively and can be unconvincing. In addressing these issues, this paper considers a theory of personality and associated emotional traits, and discusses how behaviours associated with personality types in people may be adapted to develop characteristics of virtual agents. Our objective is to ensure that behavioural perceptions of a virtual agent credibly reflect the agent's `actual' personality as prescribed.