ppxscal/embedding_network huggingface dataset:
Activity Recognition Based on Semi-supervised Learning
Authors: Donghai Guan, Weiwei Yuan, Young-Koo Lee, Andrey Gavrilov, Sungyoung Lee
Venue: Proceedings of the 13th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2007)

Activity recognition is a hot topic in context-aware computing. In activity recognition, machine learning techniques have been widely applied to learn the activity models from labeled activity samples. Since labeling samples requires human's efforts, most existing research in activity recognition focus on refining learning techniques to utilize the costly labeled samples as effectively as possible. However, few of them consider using the costless unlabeled samples to boost learning performance. In this work, we propose a novel semi-supervised learning algorithm named En-Co-training to make use of the unlabeled samples. Our algorithm extends the cotraining paradigm by using ensemble method. Experimental results show that En-Co-training is able to utilize the available unlabeled samples to enhance the performance of activity learning with a limited number of labeled samples.
Using a process modeling language for the design and implementation of process-driven applications
Authors: Davide Rossi, Elisa Turrini
Venue: Proceedings of the International Conference on Software Engineering Advances (2007)

Process driven software architectures are establishing themselves as prominent examples of distributed software infrastructures. Workflow Management Systems, web service orchestration platforms, Business Process Management support systems are relevant instances of process driven software architectures all of which, as the name suggests, are characterized as having a process perspective. In this paper we show that a (well designed) process modeling language and its execution engine can address the process perspective in different architectures and be (re)used among different application domains resulting in useful tools for the design and the implementation of process-driven applications. This can be achieved by maximizing the suitability of such a language via high expressive power and good separation of concerns. We also show sample process driven architectures, addressing different application domains, that are built with it.
R68-18 Random Pulse Machines
Authors: B. R. Gaines
Venue: IEEE Transactions on Computers (1968)

In conventional digital computation, continuous quantities are quantized and represented by binary words in which the number of bits determines the precision of representation. In stochastic computation, as described in this paper, continuous quantities are represented as a sequence of one-bit binary words (i. e., as a pulse stream or sequence of logic levels) in which the probability of an ON logic level is a measure of the quantity. Since probability is a continuous variable in the range O=p=1, this removes the effects of quantization. However, a probability cannot be measured precisely, only estimated subject to random variance, and hence there is an effective random noise in the output of the computer.
Management and preservation of research data with iRODS
Authors: Mark Hedges, Adil Hasan, Tobias Blanke
Venue: Proceedings of the ACM first workshop on CyberInfrastructure: information management in eScience (2007)

This paper presents first steps towards implementing a data layer to support a semi-automated preservation management system for research data in the arts and humanities. We suggest to use e-Science technology and grid middleware to implement a virtualised storage system for research data. We will outline how iRODS (Rule-Oriented Data management System)can be used within an architecture to implement complex,automated,scalable digital preservation strategies.
On the parameterized complexity of d-dimensional point set pattern matching
Authors: Sergio Cabello, Panos Giannopoulos, Christian Knauer
Venue: Information Processing Letters (2008)

Deciding whether two n-point sets A,B@?R^d are congruent is a fundamental problem in geometric pattern matching. When the dimension d is unbounded, the problem is equivalent to graph isomorphism and is conjectured to be in FPT. When |A|=m
Echo Algorithms: Depth Parallel Operations on General Graphs
Authors: E. J. H. Chang
Venue: IEEE Transactions on Software Engineering (1982)

This paper describes a method for the detection of properties of general graphs in an environment in which each node can be considered an autonomous processor, interacting with its neighbors by passing messages.
Embedded Hardware/Software Design and Cosimulation using User Mode Linux and SystemC
Authors: Yung-Tai Hsu, Yuan-Jin Wen, Sheng-De Wang
Venue: Proceedings of the 2007 International Conference on Parallel Processing Workshops (2007)

The paper represents a software framework that can be used to assist the system level design of multiprocessor embedded systems. The proposed solution basically relies on the interaction between the user mode Linux virtual machine, which is used to abstract the model of the real programmable processor where the embedded software should run, and the hardware device simulated by SystemC. We can view the hardware device as a coprocessor to the CPU. In this way, designers will be able to program and validate embedded software as well as the device driver in the early stages of the design flow. Two experiments will be carried out to show that the proposed framework is capable to model a system containing software and hardware. The results show that the synchronization overhead in the proposed framework is acceptable. In Experiment 1, the transmission speed of the packets processed by the simulated switch is examined, while in Experiment 2, we analyze the jpeg compression operation and show that the proposed framework can successfully model a hardware and software system with the consideration of an operating system and the driver for the hardware coprocessor.
Multidimensional Binary Search Trees in Database Applications
Authors: J. L. Bentley
Venue: IEEE Transactions on Software Engineering (1979)

The multidimensional binary search tree (abbreviated k-d tree) is a data structure for storing multikey records. This structure has been used to solve a number of "geometric" problems in statistics and data analysis. The purposes of this paper are to cast k-d trees in a database framework, to collect the results on k-d trees that have appeared since the structure was introduced, and to show how the basic data structure can be modified to facilitate implementation in large (and very large) databases.
Automatic Detection of Document Script and Orientation
Authors: S. J. Lu, C.-L. Tan
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01 (2007)

This paper presents an identification technique that au- tomatically detects the underlying script and orientation of scanned document images. In the proposed technique, document script and orientation are identified by using the stroke density and distribution, which convert each docu- ment image into a document vector. For each script at each orientation, a number of reference document vectors are first constructed. Script and orientation of the query document are then determined according to the similar- ity between the query document vector and multiple pre- constructed reference document vectors by using the K- nearest neighbor algorithm. Experiments show that the pro- posed technique is tolerant to the document skew and able to detect orientations of documents of different scripts.
A Machine Learning Approach Classification of Deep Web Sources
Authors: Hexiang Xu, Chenghong Zhang, Xiulan Hao, Yunfa Hu
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04 (2007)

The classification of deep Web Sources is an important area in large-scale deep Web integration, which is still at an early stage. Many deep Web sources are structured by providing structured query interfaces and results. Classifying such structured sources into domains is one of the critical steps toward the integration of heterogeneous Web sources. To date, in terms of the Classification, existing works mainly focus on classifying texts or Web documents, and there is little in the deep Web. In this paper, we present a deep Web model and machine learning based classifying model. The experimental results show that we can achieve a good performance with a small scale training samples for each domain, and as the number of training samples increases, the performance keeps stabilization.
Proving Termination by Divergence.
Authors: Domagoj Babic, Alan J. Hu, Zvonimir Rakamaric, Byron Cook
Venue: Proceedings of the Fifth IEEE International Conference on Software Engineering and Formal Methods (2007)

We describe a simple and efficient algorithm for proving the termination of a class of loops with nonlinear assignments to variables. The method is based on divergence testing for each variable in the cone-of-influence of the loop's termination condition. The analysis allows us to automatically prove the termination of loops that cannot be handled using previous techniques. The paper closes with experimental results using short examples drawn from industrial code.
Modeling of supersonic plasma flow in the scrape-off layer
Authors: O. Marchuk, M. Z. Tokar
Venue: Journal of Computational Physics (2007)

The substantial drop of the plasma temperature along magnetic field lines with increasing plasma density is one of the main features in tokamak divertors. As a result the temperature gradient at the divertor plates becomes very steep and the boundary condition normally applied for the parallel Mach number M at the target, M"t=1, cannot be satisfied. In this case the value of M"t based on the general form of the Bohm criterion, M"t>=1, has to be determined from the continuity of plasma parameters. In the present paper a new approach to resolve the Mach number at the target for such a situation is proposed. This method avoids the singularity problem that arises by treating the particle balance and parallel motion equations in a differential form. Instead, the integral representation of the equations is formulated for an arbitrary form of particle and momentum sources. The approach can also take into account transport perpendicular to the magnetic field lines. The proposed method is demonstrated on the example of a one-dimensional stationary model for the scrape-off layer (SOL) plasma and includes the continuity-, parallel momentum- and heat transfer equations. The recycled neutrals are described in the diffusion approximation. In the case of low density the normal condition M"t=1 is satisfied and the results are in agreement with the two-point model. At high enough plasma density solutions with the supersonic flow at the divertor plates, M"t>1, are found. These states correspond to a partially detached plasma with a temperature of a few eV.
Research on a Novel Planning Algorithm Based on Constraints Propagating
Authors: Weijin Jiang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 04 (2007)

This paper presents a distrusted multi-agent planning algorithm based on constraints propagating. In our algorithm, conflicts are detected and resolved through a special type of negotiation among agents, i.e. consistency checking for constraints. The algorithm is sound under deterministic circumstance. In our algorithm, agents only exchange information about actions, casual links and constraints related to conflicts. It is of less communication, higher security than that exchanging the whole plan.
Border Detection in Digital Images: An Approach by Fuzzy Numbers
Authors: Ines A. Gasparotto Boaventura, Adilson Gonzaga
Venue: Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications (2007)

The purpose of this paper is to introduce a new approach for edge detection in gray shaded images. The proposed ap- proach is based on the fuzzy number theory . The idea is to deal with the uncertainties concerning the gray shades mak- ing up the image, and thus calculate the appropriateness of the pixels in relation to an homogeneous region around them. The pixels not belonging to the region are then clas- sified as border pixels. The results have shown that the technique is simple, com- putationally efficient and with good results when compared with both the traditional border detectors and the fuzzy edge detectors.
Prognostic Bayesian networks
Authors: Marion Verduijn, Peter M. J. Rosseel, Niels Peek, Evert de Jonge, Bas A. J. M. de Mol
Venue: Journal of Biomedical Informatics (2007)

A prognostic Bayesian network (PBN) is new type of prognostic model that implements a dynamic, process-oriented view on prognosis. In a companion article, the rationale of the PBN is described, and a dedicated learning procedure is presented. This article presents an application hereof in the domain of cardiac surgery. A PBN is induced from clinical data of cardiac surgical patients using the proposed learning procedure; hospital mortality is used as outcome variable. The predictive performance of the PBN is evaluated on an independent test set, and results were compared to the performance of a network that was induced using a standard algorithm where candidate networks are selected using the minimal description length principle. The PBN is embedded in the prognostic system ProCarSur; a prototype of this system is presented. This application shows PBNs as a useful prognostic tool in medical processes. In addition, the article shows the added value of the PBN learning procedure.
Integrating Functionality and Appearance with the Electronic Work Logical Structure
Authors: Miguel A. Martinez-Prieto, Pablo de la Fuente, Jesus Vegas, Joaquin Adiego
Venue: Proceedings of the 2007 Latin American Web Conference (2007)

Considering that the use of e-books has an important impact in educational environments, we work for getting a competitive and reliable entity for publishing classic literature in the Spanish environment by means of a digital library which helps us to distribute, in an organized way, these electronic documents in Internet. Although currently this content is classical literature in different editions, we want to get a flexible entity which allows us to publish other types of texts that can be demanded by future curriculum. Taking into account these requirements, we define, from the e-book features, the concept of electronic work as an entity focused in the logical structure which represents the original structure of the book. This structure plays a main role, because it is used to integrate the functionality and the appearance necessary for interaction services provided by electronic works. These services are built through Aqueducts, a specific processing model driven by XML data.
Informational report on an international workshop on the use of the computer in the teaching of secondary school subjects
Authors: Alfred Bork
Venue: ACM SIGCUE Outlook (1974)

GNOSIS is a system which makes it very simple for a teacher to produce a computerized lesson. The teacher compiles a lesson containing texts and questions and expected answers to the questions. The teacher can check the student results and adjust the lesson according to the student's achievements, e.g., by prescribing remedial sections for students with difficulties. The teacher can also react in special ways to different expected and unexpected false answers to questions, e.g., by appropriate hints followed by a repetition of the wrongly answered question. Unexpected false answers are saved when a student takes a lesson, and later sent to the teacher to help him improve the lesson. GNOSIS is written in ALGOL for the DEC-system 10 computer, but is probably not too difficult to transfer to another computer which has an ALGOL or preferably a SIMULA compiler.
An Algebra for a General Entity-Relationship Model
Authors: C. Parent
Venue: IEEE Transactions on Software Engineering (1985)

Although many data manipulation languages (DML's) have been proposed for the entity-relationship (ER) model, there is no agreement on what are the basic manipulations that any ER DML must offer. Moreover, there is no DML which fully supports all the capabilities of a general ER model with n-ary relationships, relationships with attributes, optional, complex, and multivalued attributes. This paper consequently proposes a definition of a set of algebraic operators to be applied on a general ER database. The algebra is said to be complete through equivalence with the usual definition of completeness for relational data manipulation languages. This work is intended to provide a sound basis for the definition of complete entity-relationship DML's, an essential feature to make the ER model fully operational.
Covering indexes for XML queries: bisimulation - simulation = negation
Authors: Prakash Ramanan
Venue: Proceedings of the 29th international conference on Very large data bases - Volume 29 (2003)

Tree Pattern Queries (TPQ), Branching Path Queries (BPQ), and Core XPath (CXPath) are subclasses of the XML query language XPath, TPQ ⊂ BPQ ⊂ CX Path ⊂ X Path. Let TPQ = TPQ+ ⊂ BPQ+ ⊂ CX Path+ ⊂ X Path+ denote the corresponding subclasses, consisting of queries that do not involve the boolean negation operator not in their predicates. Simulation and bisimulation are two different binary relations on graph vertices that have previously been studied in connection with some of these classes. For instance, TPQ queries can be minimized using simulation. Most relevantly, for an XML document, its bisimulation quotient is the smallest index that covers (i.e., can be used to answer) all BPQ queries. Our results are as follows: • A CXPath+ query can be evaluated on an XML document by computing the simulation of the query tree by the document graph. • For an XML document, its simulation quotient is the smallest covering index for BPQ+. This, together with the previously-known result stated above, leads to the following: For BPQ covering indexes of XML documents, Bisimulation - Simulation = Negation. • For an XML document, its simulation quotient, with the idref edges ignored throughout, is the smallest covering index for TPQ. For any XML document, its simulation quotient is never larger than its bisimulation quotient; in some instances, it is exponentially smaller. Our last two results show that disallowing negation in the queries could substantially reduce the size of the smallest covering index.
Mixed reality for enhancing business communications using virtual worlds
Authors: Muthukkumar S. Kadavasal, Krishna K. Dhara, Xiaotao Wu, Venkatesh Krishnaswamy
Venue: Proceedings of the 2007 ACM symposium on Virtual reality software and technology (2007)

Online virtual worlds are attracting businesses that intend to offer new enterprise class services. Often, these services in virtual worlds are closely linked with the real enterprise resources. For a successful deployment of these services, a mixed reality model with communications that extend the virtual worlds to enterprise resources is required. In this paper, we take a look at this new class of collaborative applications by using a customer service application as an example. We discuss various issues in offering such a service, lay out the requirements, propose an architecture for mixed reality communications, and present our prototype implementation. We believe that this example service can introduce a mixed reality based communication paradigm that is applicable to a wide range of other business or enterprise services.
Guest Editors' Introduction: Semantic-Web-Based Knowledge Management
Authors: John Davies, Miltiadis Lytras, Amit P. Sheth
Venue: IEEE Internet Computing (2007)

The Semantic Web promises to make Web-accessible data more amenable to machine processing. This special issue presents several proposals for the Semantic Web's strategic role in supporting more effective knowledge management at several levels.
Diagnosing misconfiguration with dynamic detection of configuration invariants
Authors: Dong Zhou
Venue: Proceedings of the 3rd workshop on on Hot Topics in System Dependability (2007)

In software engineering, an invariant is a set of properties describing the value of a program variable. Dynamic invariant detection has been used to debug software errors. In this position paper, we propose to dynamically construct invariants for configuration settings, and to detect violations to configuration invariants for misconfiguration diagnosis. We also propose to use task-based suspect ranking to identify suspicious configuration changes made by less trustable programs to improve the diagnosis process. We describe our design of a misconfiguration diagnosis system based on dynamic configuration invariant detection and suspect ranking with task-related information.
Program Optimization Using Invariants
Authors: S. Katz
Venue: IEEE Transactions on Software Engineering (1978)

Optimizing a computer program is defined as improving the execution time without disturbing the correctness. We show how to use invariants from a proof of correctness in order to change the statement in and around the program's loops. This approach is shown to systematize existing optimization methods, and to sometimes allow stronger optimizations than are possible under the standard transformation approach.
Analyzing and Improving of Neural Networks used in Stereo Calibration
Authors: Yingjie Xing, Jing Sun, Zhentong Chen
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

In this paper, CCD cameras are calibrated implicitly using BP neural network by means of its ability to fit the complicated nonlinear mapping relation. Dense sample data is acquired by using high precisely numerical control platform, and the variances error (PVE) is adopted during training the neural network. The error percentages obtained from our set-up are limitedly better than those obtained through Mean Square Error (MSE). The system is generalization enough for most machine-vision applications and the calibrated system can reach acceptable precision of 3D measurement standard. It is expected that, with this approach, we can maintain the major advantage of linear methods and obtain improved accuracy without any complicated mathematical modeling process thank to nonlinear learning capability of neural networks. The value p needs to be decided by experiments, and the reconstruction images will be distorted if the value is more than 6.
Towards a Security Metrics Taxonomy for the Information and Communication Technology Industry
Authors: Reijo Savola
Venue: Proceedings of the International Conference on Software Engineering Advances (2007)

To obtain evidence of the security of different products or organizations, systematic approaches to measuring security are needed. We introduce a high abstraction level taxonomy to support the development of feasible security metrics, along with a survey of the emerging security metrics from the academic, governmental and industrial perspectives. With our taxonomy, we strive to bridge the gap between information security management and ICT products, and services security engineering. We believe that if common metrics approaches between different security disciplines can be found, this will advance our holistic understanding and capabilities, both in security management and engineering. Our taxonomy is based on comparing earlier taxonomy approaches and analyzing types of security metrics. Based on the survey, a discussion of future research directions is given in order to prompt advances in the field.