ppxscal/embedding_network huggingface dataset:
Design of crack detection system software for IC package using blob analysis and neural network
Authors: Rosdiyana Samad, Mohd Rizal Arshad, Zahurin Samad
Venue: Proceedings of the 9th WSEAS International Conference on Systems (2005)

In this research, three methods for the detection of crack defects on integrated circuit (IC) packages are proposed. These methods use blob analysis technique in image processing stage, and use multi-layered perceptron (MLP) neural network to classify the IC package. This paper presents the various filters and operations employed in blob analysis. The simulation results have shown, that a two-layer back-propagation neural network, which has a log-sigmoid transfer function in the hidden and output layer, could be trained to classify the IC package image. An early stopping technique was used in this study to provide benefits to the network performance in terms of a decrease in over-fitting. It was found that the optimal number of hidden neurons for the network 1,2 and 3 were 12, 12 and 10. The first method produced an accuracy of 74.82% with 87.72 ms processing time, while the second method utilizing the same classifier, achieved 86.17% accuracy with 119.45 ms processing time. The third method achieved 96.1% accuracy with 188.44 ms processing speed. The results obtained in this study indicated that the third method proceed better performance with higher accuracy and processing speed below 200 ms.
Clustering of High-Dimensional Gene Expression Data with Feature Filtering Methods and Diffusion Maps
Authors: Rui Xu, Steven Damelin, Boaz Nadler, Donald C. Wunsch II
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 01 (2008)

The importance of gene expression data in cancer diagnosis and treatment by now has been widely recognized by cancer researchers in recent years. However, one of the major challenges in the computational analysis of such data is the curse of dimensionality, due to the overwhelming number of measures of gene expression levels versus the small number of samples. Here, we use a two-step method to reduce the dimension of gene expression data. At first, we extract a subset of genes based on the statistical characteristics of their corresponding gene expression measurements. For further dimensionality reduction, we then apply diffusion maps, which interpret the eigenfunctions of Markov matrices as a system of coordinates on the original data set in order to obtain efficient representation of data geometric descriptions, to the reduced data. A neural network clustering theory, Fuzzy ART, is applied to the resulting data to generate clusters of cancer samples. Experimental results on the small round blue-cell tumor (SRBCT) data set, compared with other widely-used clustering algorithms, demonstrate the effectiveness of our proposed method in addressing multidimensional gene expression data.
Measuring concept relatedness using language models
Authors: Dolf Trieschnigg, Edgar Meij, Maarten de Rijke, Wessel Kraaij
Venue: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (2008)

Over the years, the notion of concept relatedness has attracted considerable attention. A variety of approaches, based on ontology structure, information content, association, or context have been proposed to indicate the relatedness of abstract ideas. We propose a method based on the cross entropy reduction between language models of concepts which are estimated based on document-concept assignments. The approach shows improved or competitive results compared to state-of-the-art methods on two test sets in the biomedical domain.
Research on WEB Cache Prediction Recommend Mechanism Based on Usage Pattern
Authors: Jianhui Lin, Tianshu Huang, Chao Yang
Venue: Proceedings of the First International Workshop on Knowledge Discovery and Data Mining (2008)

Cache prefetching technique can improve the hit ratio and expedite users visiting speed. After analyzed the recommend system in E-Business, this paper studied the characteristics how user visit web page and proposed a web prefetching recommender system based on usage pattern. This system cluster user behavior through an improved ant colony algorithm, then usage pattern can be abstracted from these classes through sequence mining. These sequence patterns are applied to forecast the coming behavior of users thus improve the hit ratio of system. Experiment result proves the validity of the system.
Using virtualization technology to teach operating system concepts: tutorial presentation
Authors: Sharon Weber
Venue: Journal of Computing Sciences in Colleges (2008)

The system software landscape is quickly changing as the adoption of virtualization software accelerates. The use of virtualization software allows hardware resources, particularly servers, to be effectively managed as a computing pool, leading to a reduction in the amount of computing resources necessary to support an organization. The purpose of this tutorial is to show how basic operating system concepts (CPU, memory, and file systems) can be illustrated using examples from the area of virtualization. For example, one important function of the memory management system of a traditional operating system is to translate virtual addresses in a program into physical addresses that map directly into the computing system's physical memory. In a virtualized system such as VMware's server product [1], address translation requires an additional step. In such a system, the guest operating system cannot actually map addresses to the underlying memory hardware, even though the operating system has the illusion of controlling the physical memory and performs address translation as if it were running directly on the hardware. The underlying virtualization layer translates physical addresses from the guest operating system into machine addresses, which are the actual memory addresses in the hardware. Additional mechanisms such as shadow page tables are used to insure that performance in this two step translation does not suffer. The tutorial will cover the above mentioned topics in detail appropriate to an undergraduate introductory course in operating system concepts.
UM-RTCOM: An analyzable component model for real-time distributed systems
Authors: M. Díaz, D. Garrido, L. Llopis, F. Rus, J. M. Troya
Venue: Journal of Systems and Software (2008)

Component-based development is a key technology in the development of software for modern real-time systems. However, standard component models and tools are not suitable for this type of system, since they do not explicitly address real time, memory or cost constraints. This paper presents a new predictable component model for real-time systems (UM-RTCOM) together with a set of tools to support it. The environment allows new components to be developed which can then be assembled to build complete applications, including hardware interaction. The model includes support for real-time analysis at the component and application level. The analysis is achieved by combining component meta-information in the form of an abstract behaviour model and a method to measure worst-case execution times in the final platform. Additionally, we propose an implementation model based on RT-CORBA where the developer uses the UM-RTCOM components and a set of tools to map these elements to elements of the desired platform. In order to apply our proposals, we have used the model and tools in real applications specifically in the context of nuclear power plant simulators.
WAITER: A Wearable Personal Healthcare and Emergency Aid System
Authors: Wanhong Wu, Jiannong Cao, Yuan Zheng, Yong-Ping Zheng
Venue: Proceedings of the 2008 Sixth Annual IEEE International Conference on Pervasive Computing and Communications (2008)

The emerging pervasive computing is regarded as a promising solution to the systems of personal healthcare and emergency aid, which can monitor personal health status in a real-time manner and automatically issue the alert for medical aids in case of emergency. However, the implementation of such a system is not trivial due to the issues, including 1) the system operations without complicated caregiver aid to reduce cost of human resource, 2) vital sensor deployment for user comfort, 3) on-site vital data process and storage for energy saving in data transmission, and 4) timely communication with healthcare centre for reporting users’ health status and seeking urgent medical aids. In this paper, we propose a novel wearable personal healthcare and emergency aid system, namely WAITER. Our system does not require specific caregiver aid. WAITER just employs the tiny wearable sensors to continuously collect user’s vital signals and Bluetooth device to transmit the sensory data to a mobile phone, which can perform on-site vital data storage and process. After local data process, the mobile phone can use its GSM module to periodically report users’ health status to the healthcare centre and issue alert for medical aids once detecting emergency. We believe that WAITER can satisfy the requirements of real personal healthcare and emergency aid system.
Run-time integration of reconfigurable video processing systems
Authors: Pete Sedcole, Peter Y. K. Cheung, George A. Constantinides, Wayne Luk
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2007)

Embedded systems in field-programmable gate arrays (FPGAs) can be customized and adaptive if assembled from modular components at run time. This paper examines realizing run-time system assembly by extension of platform-based design. Two major challenges are addressed in this paper. First, the design of a reconfigurable platform architecture suitable for run-time system assembly is described. Different systems are constructed by integrating the platform architecture with different modular components, which employ the communication infrastructure supplied by the platform in order to interact. Second, where on-chip communications channels use shared media, we propose techniques for modeling the intermodule communication behavior based on statistical time-division multiplexing. The proposed techniques enable system designers to guarantee that logical communication requirements between the adjunct modules can be satisfied by the infrastructure. An in-depth analysis is presented and then verified with cycle-accurate simulations for an example reconfigurable platform for real-time video applications.
Identification of a free boundary in Norton-Hoff flows with thermal effects
Authors: J. Ferchichi, J. P. Zolésio
Venue: Journal of Computational and Applied Mathematics (2008)

This work deals with a free boundary identification problem in a steady viscoplastic flow. We provide a novel identification model based on a non-linear optimization. The fluid motion is governed by the incompressible Norton-Hoff model coupled with the heat equation. The viscosity of the fluid is modeled by the non-linear Arrhenius law. Our point of view is to treat the problem as a shape sensitivity of a cost functional formulated on the free boundary and governed by the normal component of the velocity of the flow. We analyze the mathematical statement of the forward problem. The equations related to the free boundary are simplified. Various properties of this optimization are proved. Since the state of Norton-Hoff model is not regular enough we introduce a parameter penalization. The shape gradient of the considered cost functional is given in the strong sense up to the parameter of penalization. We supply the expression of the shape gradient in a weak sense.
Classifying Software Changes: Clean or Buggy?
Authors: Sunghun Kim, E. James Whitehead,  Jr., Yi Zhang
Venue: IEEE Transactions on Software Engineering (2008)

This paper introduces a new technique for finding latent software bugs called change classification. Change classification uses a machine learning classifier to determine whether a new software change is more similar to prior buggy changes, or clean changes. In this manner, change classification predicts the existence of bugs in software changes. The classifier is trained using features (in the machine learning sense) extracted from the revision history of a software project, as stored in its software configuration management repository. The trained classifier can classify changes as buggy or clean with 78% accuracy and 65% buggy change recall (on average). Change classification has several desirable qualities: (1) the prediction granularity is small (a change to a single file), (2) predictions do not require semantic information about the source code, (3) the technique works for a broad array of project types and programming languages, and (4) predictions can be made immediately upon completion of a change. Contributions of the paper include a description of the change classification approach, techniques for extracting features from source code and change histories, a characterization of the performance of change classification across 12 open source projects, and evaluation of the predictive power of different groups of features.
Development and Evaluation of a Collaborative Virtual Environment Supporting Self Feedbacks of Electroencephalogram
Authors: Akihiro Miyata, Shota Yamamoto, Masaki Hayashi, Takefumi Hayashi, Hiroshi Shigeno, Kenichi Okada
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications (2008)

Currently, there are many occasions to communicate with each other in the collaborative virtual environment. However, it is more difficult to keep high-motivation for participating in communication in such virtual environment than in face-to-face environment. It is considered that the reasons are 1) the difficulty of understanding how their own motivations are and 2) the boring expression due to the fixed view point. To address this issue, we display electroencephalogram information to a virtual space by forward-backward model – zoom in/out of whole virtual space. According to the results of experiment, our system successfully provides an environment in which people can keep high-motivations for participating in communication.
Generating a Tailored Middleware for Wireless Sensor Network Applications
Authors: Christian Buckl, Stephan Sommer, Andreas Scholz, Alois Knoll, Alfons Kemper
Venue: Proceedings of the 2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008) (2008)

Wireless sensor networks are characterized by resource constraints. Therefore, today's sensor networks are implemented from scratch emphasizing code efficiency. This development strategy leads to relatively complex code and bad code reusability in further projects. To improve reusability and development efficiency, it is state-of-the-art in the development of standard information systems to divide applications into at least two parts, the application-logic, providing all the functions to solve a given problem and a reusable distributed middleware providing a container for the application. After developing the middleware once, the developer of further projects need to focus only on the application-logic. Thereby, the development times can be reduced considerably. However, a generic middleware layer replacing code implemented from scratch is not practicable in sensor networks due to resource constraints. Within this paper, we will present a model-driven approach in combination with a template-based code generator to get the best of both development strategies. This approach enables us to generate a tailored middleware for our application including interface-stubs for the application-logic. In contrast to other component-based approaches, the templates can be adopted easily to fulfill specific platform needs. We will demonstrate the practicability of this approach by implementing the control of a model railway.
Collaborative Learning in a Mobile Technology Supported Environment: A Case Study on Analyzing the Interactions
Authors: Siu Cheung Kong
Venue: Proceedings of the Fifth IEEE International Conference on Wireless, Mobile, and Ubiquitous Technology in Education (2008)

This paper reports a case study on the trial use of a cognitive tool (CT) called the “Graphical Partitioning Model (GPM)” for the learning of mathematical fractions in a mobile technology supported environment. The interactions between a dyad of Primary 5 students and the GPM were analyzed. The results show that the interactions between the students and the GPM have the potential to foster deep learning of subject knowledge and there is a possibility to integrate the mobile version CT with collaborative learning strategies such as reciprocal tutoring.
Toward multi-level modeling of robotic sensor networks: a case study in acoustic event monitoring
Authors: Christopher M. Cianci, Thomas Lochmatter, Jim Pugh, Alcherio Martinoli
Venue: Proceedings of the 1st international conference on Robot communication and coordination (2007)

Modeling and simulation can be powerful tools for analyzing multi-agent systems, such as networked robotic systems and sensor networks. In this paper, it is shown concretely how instances of both these elements fit into a general methodology for multi-level modeling, providing insight into system dynamics. Use of the resulting general framework is illustrated through application to a specific sample case study involving a robotic wireless sensor network engaged in an acoustic detection task. We then compare and contrast the resulting family of models, highlighting explicitly the trade-off between realism and simplicity.
Feasibility of Imaging Photoplethysmography
Authors: Jia Zheng, Sijung Hu, Vassilios Chouliaras, Ron Summers
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 02 (2008)

Contact and spot measurement have limited the application of photoplethysmography (PPG), thus an imaging PPG system comprising a digital CMOS camera and three wavelength light-emitting diodes (LEDs) is developed to detect the blood perfusion in tissue. With the means of the imaging PPG system, the ideally contactless monitoring with larger field of view and the different depth of tissue by applying multi-wavelength illumination can be achieved to understand the blood perfusion change. Corresponding to the individual wavelength LED illumination, the PPG signals can be derived in the both transmission and reflection modes, respectively. The outcome explicitly reveals the imaging PPG is able to detect blood perfusion in a illuminated tissue and indicates the vascular distribution and the blood cell response to individual wavelength LED. The functionality investigation leads to the engineering model for 3-D visualized blood perfusion of tissue and the development of imaging PPG tomography.
Query answering techniques on uncertain and probabilistic data: tutorial summary
Authors: Jian Pei, Ming Hua, Yufei Tao, Xuemin Lin
Venue: Proceedings of the 2008 ACM SIGMOD international conference on Management of data (2008)

Uncertain data are inherent in some important applications, such as environmental surveillance, market analysis, and quantitative economics research. Due to the importance of those applications and the rapidly increasing amount of uncertain data collected and accumulated, analyzing large collections of uncertain data has become an important task and has attracted more and more interest from the database community. Recently, uncertain data management has become an emerging hot area in database research and development. In this tutorial, we systematically review some representative studies on answering various queries on uncertain and probabilistic data.
On the relation of refactorings and software defect prediction
Authors: Jacek Ratzinger, Thomas Sigmund, Harald C. Gall
Venue: Proceedings of the 2008 international working conference on Mining software repositories (2008)

This paper analyzes the influence of evolution activities such as refactoring on software defects. In a case study of five open source projects we used attributes of software evolution to predict defects in time periods of six months. We use versioning and issue tracking systems to extract 110 data mining features, which are separated into refactoring and non-refactoring related features. These features are used as input into classification algorithms that create prediction models for software defects. We found out that refactoring related features as well as non-refactoring related features lead to high quality prediction models. Additionally, we discovered that refactorings and defects have an inverse correlation: The number of software defects decreases, if the number of refactorings increased in the preceding time period. As a result, refactoring should be a significant part of both bug fixes and other evolutionary changes to reduce software defects.
Improved bi-layer lift-off process for MEMS applications
Authors: Jinxing Liang, Fusao Kohsaka, Takahiro Matsuo, Xuefeng Li, Toshitsugu Ueda
Venue: Microelectronic Engineering (2008)

Conventional lift-off process is designed for defining very fine pattern or removing metals hard to etch and the process is limited to surface microfabrication due to the requirement on directional deposition. We improved the process for the step coverage requirement in 3-D MEMS. A novel bi-layer (top image resist Shipley S1808 and bottom lift-off resist Microchem LOR) lift-off process was built up for patterning 3-D devices. Resists were coated and patterned with an overhang profile on a substrate before the substrate was etched. The key feature of the new lift-off process is to create a resist undercut profile, which is deep enough to reduce step coverage and durable to aggressive substrate etchant. The two-step development method was effective for patterning 3-D microdevices with high aspect ratio trench or through-holes. The development time of the resist profile was optimized. Fine pattern of 2@mm/5@mm (line/space) was achieved on quartz microstructure with high aspect ratio (2.7) trench.
On rank-constrained Hermitian nonnegative-definite least squares solutions to the matrix equation AXAH=B
Authors: Musheng Wei, Qian Wang
Venue: International Journal of Computer Mathematics (2007)

In the literature, rank-constrained Hermitian nonnegative-definite solutions to the matrix equation AXAH=B have been investigated, under the conditions that B is Hermitian and nonnegative-definite, and the matrix equation is consistent. In this paper, we discuss rank-constrained Hermitian nonnegative-definite least squares solutions to this matrix equation, in which the above conditions may not hold. We derive the rank range and expression of these least squares solutions. Therefore, the results obtained in this paper generalize those in the literature.
Detour-saturated graphs
Authors: Lowell W. Beineke, J. E. Dunbar, M. Frick
Venue: Journal of Graph Theory (2005)

A graph is said to be detour-saturated if the addition of any edge results in an increased greatest path length. In this paper, we add to the relatively small amount that is known about detour-saturated graphs. Our main result is a determination of all connected detour-saturated graphs with exactly one cycle. (The family of detour-saturated trees was found by K&aacute;szonyi and Tuza 7.) We also show that the smallest detour-saturated graph of girth 5 is the graph obtainable from the Petersen graph by splitting one of its vertices into three, each of degree 1. &copy; 2005 Wiley Periodicals, Inc. J Graph Theory
Building the WorldWide Telescope
Authors: Curtis Wong
Venue: ACM SIGMOD Record (2008)

This paper is talks about the critical role that Jim Gray played in the creation of the WorldWide Telescope software. Contrary to what you might think it wasn't his database brilliance that made it happen, it was his generosity in sharing credit, inspiring, nurturing and connecting people, in this case that made it possible for the pieces to come into place and make it happen. Without Jim Gray's work with Alex Szalay on Sky Server and their ongoing support and encouragement, the software that is named in their honor would not exist today.