ppxscal/embedding_network huggingface dataset:
Implementation of Defect Oriented Testing and ICCQ testing for industrial mixed-signal IC
Authors: Liquan Fang, Yang Zhong, Henk van de Donk
Venue: Proceedings of the 16th Asian Test Symposium (2007)

In the era of Zero Defects, ICCQ is one of the powerful non-specification based testing methods to achieve high test coverage and supreme product quality. Within this project, based on the fault simulation with Defect Oriented Test (DOT) technique, the current tests with the most efficient coverage improvements have been selected and implemented in the production testing flow.
Knowledge acquisition using rough sets when membership values are fuzzy sets
Authors: A. de Korvin, C. McKeegan, R. Kleyle
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (1998)

In this paper we model uncertainty using the so-called rough set approach in which upper and lower approximations of a set of objects are based on equivalence classes determined by attribute values. However, due to imprecision in the information, both the attributes and the resulting decisions are modeled as fuzzy sets. Furthermore, the membership of these fuzzy sets is also fuzzy, creating fuzzy sets of type II. From information of this type, we construct inference rules of unequal strength. The strength of any rule is determined by both its degree of truth and its degree of belief, each of which are obtained from the fuzzy memberships.
Fuzzy quality-team formation for value added auditing: A case study
Authors: Türkay Dereli, Adil Baykasoğlu, G. Sena Daş
Venue: Journal of Engineering and Technology Management (2007)

Value-added (quality) auditing is emerging as one of the most powerful tools for continuous quality improvement, with the introduction of the ISO 9001:2000 and ISO 19011 standards that focus team-based audits, proper auditor skills, process auditing, and effectiveness, etc. Formation of an effective quality audit team (QAT) based on the required auditor skills is therefore the initial stage of the value added auditing. QATs audit organizations at different locations with varying auditing requirements in order to evaluate an organization's own quality system (first party part audits according to IEC9001 Clause 8.2.2). The QAT consists of a lead auditor and one or more auditors that have the required skills in varying levels for the execution of an audit. For a successful audit, the formation of a QAT is vital since each audit team must at least fulfill the minimum requirements and skills needed for a specific audit. In this case study, a fuzzy mathematical-programming model and a solution algorithm based on ''simulated annealing'' is proposed for the formation of QATs. This is one of the first attempts in the literature to form this kind of teams analytically. Example problems are also solved in the paper to present the application of the proposed approach.
Crossover accelerates evolution in gas with a babel-like fitness landscape: Mathematical analyses
Authors: Hideaki Suzuki, Yoh Iwasa
Venue: Evolutionary Computation (1999)

The effectiveness of crossover in accelerating evolution in genetic algorithms (GAs) is studied with a haploid finite population of bit sequences. A Babel-like fitness landscape is assumed. There is a single bit sequence (schema) that is significantly more advantageous than all the others. We study the time until domination of the advantageous schema (Td). Evolution proceeds with appearance, spread, and domination of the advantageous schema. The most important process determining Td is the appearance (creation) of the advantageous schema. Crossover helps this creation process and enhances the rate of evolution. To study this effect, we first establish an analytical method to estimate Td with or without crossover. Then, we conduct a numerical analysis using the frequency vector representation of the population with the recurrence relations formulated after GA operations. Finally, we carry out direct computer simulations with simple GAs operating on a population of binary strings directly prepared in the computer memory to examine the performance of the two analytical methods. It is shown that Td is reduced greatly by crossover with a mildly high rate when the mutation rate is adjusted to a moderate value and that an advantageous schema has a fairly large order (the number of bits). From these observations, we can determine implementation criteria for GAs, which are useful when we applying GAs to engineering problems having a conspicuously discontinuous fitness landscape.
Review on Application of Data Mining in Product Design and Manufacturing
Authors: Keqin Wang, Shurong Tong, Benoit Eynard, Lionel Roucoules, Nada Matta
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04 (2007)

Implementation of data mining technology in some areas such as banking, finance, marketing, insurance, health care, etc. has given very good results. However, applications of data mining in product design and manufacturing are not as broad as expected and many challenges are still ahead. This work analyzes the reasons for the limitation of data mining application in manufacturing industry and focuses on reviewing the state-of-the-art of the applications of data mining in product design and manufacturing. Some points of views are also discussed and finally this paper is concluded.
Extracting Hand Vein Patterns from Low-Quality Images: A New Biometric Technique Using Low-Cost Devices
Authors: Shi Zhao, Yiding Wang, Yunhong Wang
Venue: Proceedings of the Fourth International Conference on Image and Graphics (2007)

A new biometric technique using hand-dorsa vein patterns attracted attention these years. In this technique, extracting vein structures is a key procedure. For conventional algorithm, it is necessary to use high-quality images, which demand high-priced collection devices. That is because vein pattern images usually have low contrast, high-quality images are proper for segment. In our research, an extracting method for low-quality image is presented. The proposed method makes using low-cost devices possible. The results show that we could extract the vein networks as successfully as using high-quality images. In this paper, the principle of vein imaging is discussed, a new method to acquire vein images, which could enhance the contrast, is proposed, and the algorithm of extracting the vein pattern from low quality images is put forward. Our innovations are designing a new method to obtain good contrast vein images and proposing a novel denoising algorithm.
Toward a hybrid data mining model for customer retention
Authors: Bong-Horng Chu, Ming-Shian Tsai, Cheng-Seen Ho
Venue: Knowledge-Based Systems (2007)

The prevention of subscriber churn through customer retention is a core issue of Customer Relationship Management (CRM). By minimizing customer churn a company maximizes its profit. This paper proposes a hybridized architecture to deal with customer retention problems. It does so not only through predicting churn probability but also by proposing retention policies. The architecture works in two modes: learning and usage. In the learning mode, the churn model learner seeks potential associations from the subscriber database. This historical information is used to form a churn model. This mode also calls for a policy model constructor to use the attributes identified in the churn model to divide all 'churners' into distinct groups. The policy model constructor is also responsible for developing a policy model for each churner group. In the usage mode, a churn predictor uses the churn model to predict the churn probability of a given subscriber. When the churn model finds that the subscriber has a high churn probability the policy model is used to suggest specific retention policies. This study's experiments show that the churn model has an evaluation accuracy of approximately eighty-five percent. This suggests that policy model construction represents an interesting and important technique in investigating the characteristics of churner groups. Furthermore, this study indicates that understanding the relationships between churns is essential in creating effective retention policy models for dealing with 'churners'.
An Embedded Low Power/Cost 16-Bit Data/Instruction Microprocessor Compatible with ARM7 Software Tools
Authors: Fu-Ching Yang, Ing-Jer Huang
Venue: Proceedings of the 2007 Asia and South Pacific Design Automation Conference (2007)

A 16-bit THUMB instruction set microprocessor is proposed for low cost/power in short-precision computing. It achieves 40% gate count, 51% power consumption and 160% clock frequency comparing to ARM7, even the performance is 67% better in narrow width memory at the same clock frequency. The ARM7 software is also compatible.
NetPhosYeast
Authors: Christian R. Ingrell, Martin L. Miller, Ole N. Jensen, Nikolaj Blom
Venue: Bioinformatics (2007)

Summary: We here present a neural network-based method for the prediction of protein phosphorylation sites in yeast—an important model organism for basic research. Existing protein phosphorylation site predictors are primarily based on mammalian data and show reduced sensitivity on yeast phosphorylation sites compared to those in humans, suggesting the need for an yeast-specific phosphorylation site predictor. NetPhosYeast achieves a correlation coefficient close to 0.75 with a sensitivity of 0.84 and specificity of 0.90 and outperforms existing predictors in the identification of phosphorylation sites in yeast. Availability: The NetPhosYeast prediction service is available as a public web server at http://www.cbs.dtu.dk/services/NetPhosYeast/ Contact: nikob@cbs.dtu.dk
Infrastructure for a clinical-decision-intelligence system
Authors: Xueyun Sharon Wang, Leonard Nayda, Richard Dettinger
Venue: IBM Systems Journal (2007)

Clinical decision intelligence (CDI) is an emerging area in health care, covering a broad range of subjects, from clinical data integration and data analysis to knowledge management and application development. The goal of CDI systems is to improve health-care quality and reduce costs through the discovery, management, and application of clinical intelligence from heterogeneous and rapidly expanding data sources. These sources include data from clinical practice, nursing, health-care management, health-care administration, and medical research. In this paper, we discuss the functional requirements and reference architecture for CDI systems and their clinical applications. This architecture includes an integrated framework for managing the entire CDI process, a standardized enterprise ontology management system, and a clinical knowledge representation platform. The CDI approach has the potential to transform the health-care management process through the integration of business intelligence, business rule management, and business process management in a clinical setting, and to help health-care organizations move closer to an on demand model.
Document Images Retrieval Based on Multiple Features Combination
Authors: G. Meng, N. Zheng, Y. Song, Y. Zhang
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01 (2007)

Retrieving the relevant document images from a great number of digitized pages with different kinds of artificial variations and documents quality deteriorations caused by scanning and printing is a meaningful and challenging problem. We attempt to deal with this problem by combining up multiple different kinds of document features in a hybrid way. Firstly, two new kinds of document image features based on the projection histograms and crossings number histograms of an image are proposed. Secondly, the proposed two features, together with density distribution feature and local binary pattern feature, are combined in a multistage structure to develop a novel document image retrieval system. Experimental results show that the proposed novel system is very efficient and robust for retrieving different kinds of document images, even if some of them are severely degraded.
Energy-Efficient Monitoring of Mobile Objects with Uncertainty-Aware Tolerances
Authors: Tobias Farrell, Reynold Cheng, Kurt Rothermel
Venue: Proceedings of the 11th International Database Engineering and Applications Symposium (2007)

In location-based services, continuous queries are often employed to monitor the locations of mobile objects that are determined by sensing devices like GPS receivers. Due to limited battery resources, it is important for these objects to acquire and report location data only if necessary. We study how these energy-consuming operations can be reduced with a controlled impact on query accuracy of continuous range queries (CRQs). Specifically, we develop uncertainty-aware tolerances, which are user-defined error bounds that provide correctness guarantees, with consideration of different sources of data uncertainty: sensing uncertainty, sampling uncertainty, and communication delay. Novel algorithms are developed to control carefully when an object should acquire and update a location, while satisfying these tolerances. Extensive simulations validate the effectiveness of our methods.
Some mathematical aspects of the Kelvin equation
Authors: S. Siboni, C. Della Volpe
Venue: Computers Mathematics with Applications (2008)

The complete form of the Kelvin equation, which describes the effect of the interface curvature on the equilibrium vapour pressure in the presence of the relative liquid, is considered. Regularity and general trend of solutions are investigated. A rigorous power-series expansion of the physically meaningful solution is derived by Lagrange's expansion. Our discussion also covers the question of convergence (rate and uniformity) of the appropriate algorithm for numerical estimates. Some mathematical by-products are finally presented.
Conditional Interpretation of Operation Codes
Authors: C. C. Foster, R. Gonter
Venue: IEEE Transactions on Computers (1971)

A method, called conditional interpretation, is proposed which will allow small computers to have as large a set of instructions as may be desired without using a large number of bits to hold the operation code. The method is based on the redundancy of machine language instruction sequences. Most machine language instructions have a limited number of "reasonable" successors. For example "load accumulator" hardly ever follows "enter accumulator." It turns out that if each instruction is allowed seven successors plus an "escape instruction," only about one out of every five instructions needs to be an "escape" to get to one of the less usual successors. Seventy-five percent of the time the desired "next instruction" is among the seven permitted successors. Since each instruction has its own, possibly unique, set of successors, the interpretation of the stored op-code is conditional upon the state of the machine.
Harvesting credentials in trust negotiation as an honest-but-curious adversary
Authors: Lars E. Olson, Michael J. Rosulek, Marianne Winslett
Venue: Proceedings of the 2007 ACM workshop on Privacy in electronic society (2007)

Need-to-know is a fundamental security concept: a party should not learn information that is irrelevant to its mission. In this paper we show that during a trust negotiation in which parties show their credentials to one another, an adversary can systematically harvest information about all of a victim's credentials that the attacker is entitled to see, regardless of their relevance to the negotiation. We present examples of need-to-know attacks with the trust negotiation approaches proposed Yu, Winslett, and Seamons; by Bonatti and Samarati; and by Winsborough and Li. Finally, we propose possible countermeasures against need-to-know attacks, and discuss their advantages and disadvantages.
Implementing viable remote laboratories using server virtualisation
Authors: V. L. Lasky, S. J. Murray
Venue: Proceedings of the sixth conference on IASTED International Conference Web-Based Education - Volume 2 (2007)

Remote laboratories are gaining prominence in university education, especially in respect of their ability to support distance education by allowing students to carry out experiments without being near the actual equipment and also by providing secure, equitable sharing of limited laboratory resources. For some types of laboratory experiments, remote laboratories have not in the past been viable to build due to infrastructure and maintenance costs. Large-scale remote laboratories may require a proportionally large number of servers to provide remote control, monitoring and management of the various experiments. Server Virtualisation software allows individual physical servers to host multiple virtual machines that can run multiple operating systems concurrently. In 2005, the Faculty of Engineering at UTS designed a remote Programmable Logic Controller (PLC) laboratory for Mechanical and Mechatronic engineering students based around the use of the popular Server Virtualisation software package, VMwareTM. This paper details the various benefits of Server Virtualisation that have been realised through the implementation of the Remote PLC laboratory and benefits for remote laboratories in general.
The Strategies of Initial Diversity and Dynamic Mutation Rate for Gene Expression Programming
Authors: Lei Duan, Changjie Tang, Jun Zhu, Jie Zuo, Yintian Liu, Jiang Wu, Li Dai
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 04 (2007)

Gene Expression Programming (GEP) is a genotype/phenotype system that evolves candidate solutions encoded in linear chromosomes of fixed length. Its characteristics make GEP surpass other evolutionary algorithms. However, the original GEP algorithm generates the initial population in a simple way and uses a constant mutation rate determined empirically. Two effective strategies are proposed to overcome these limitations. The contributions of this paper include: (1) developing an algorithm to extract the Open Reading Frame of a gene without parsing the Expression Tree, (2) defining the consanguineous relation between chromosomes, (3) proposing an algorithm to diversify the initial population based on the consanguineous relation, and (4) proposing a novel adaptive mutation rate strategy for each chromosome in evolution. Furthermore, a performance evaluation using both synthetic and real-life data demonstrates that the proposed strategies are effective. The result shows that the correlation coefficient between observed values and predicted values can be increased by as high as 0.1856, and the classification problem can be solved in less running time.
Feature selection and classification model construction on type 2 diabetic patients' data
Authors: Yue Huang, Paul McCullagh, Norman Black, Roy Harper
Venue: Artificial Intelligence in Medicine (2007)

Objective: Diabetes affects between 2% and 4% of the global population (up to 10% in the over 65 age group), and its avoidance and effective treatment are undoubtedly crucial public health and health economics issues in the 21st century. The aim of this research was to identify significant factors influencing diabetes control, by applying feature selection to a working patient management system to assist with ranking, classification and knowledge discovery. The classification models can be used to determine individuals in the population with poor diabetes control status based on physiological and examination factors. Methods: The diabetic patients' information was collected by Ulster Community and Hospitals Trust (UCHT) from year 2000 to 2004 as part of clinical management. In order to discover key predictors and latent knowledge, data mining techniques were applied. To improve computational efficiency, a feature selection technique, feature selection via supervised model construction (FSSMC), an optimisation of ReliefF, was used to rank the important attributes affecting diabetic control. After selecting suitable features, three complementary classification techniques (Naive Bayes, IB1 and C4.5) were applied to the data to predict how well the patients' condition was controlled. Results: FSSMC identified patients' 'age', 'diagnosis duration', the need for 'insulin treatment', 'random blood glucose' measurement and 'diet treatment' as the most important factors influencing blood glucose control. Using the reduced features, a best predictive accuracy of 95% and sensitivity of 98% was achieved. The influence of factors, such as 'type of care' delivered, the use of 'home monitoring', and the importance of 'smoking' on outcome can contribute to domain knowledge in diabetes control. Conclusion: In the care of patients with diabetes, the more important factors identified: patients' 'age', 'diagnosis duration' and 'family history', are beyond the control of physicians. Treatment methods such as 'insulin', 'diet' and 'tablets' (a variety of oral medicines) may be controlled. However lifestyle indicators such as 'body mass index' and 'smoking status' are also important and may be controlled by the patient. This further underlines the need for public health education to aid awareness and prevention. More subtle data interactions need to be better understood and data mining can contribute to the clinical evidence base. The research confirms and to a lesser extent challenges current thinking. Whilst fully appreciating the requirement for clinical verification and interpretation, this work supports the use of data mining as an exploratory tool, particularly as the domain is suffering from a data explosion due to enhanced monitoring and the (potential) storage of this data in the electronic health record. FSSMC has proved a useful feature estimator for large data sets, where processing efficiency is an important factor.
Packet Switching Interconnection Networks for Modular Systems
Authors: D. M. Dias
Venue: Computer (1981)

Adding buffers to a packet switching network can increase throughput in certain system architectures. A word of warning don't make them too large.
Economic recognition of innovation
Authors: Balkrishna C. Rao
Venue: Ubiquity (2007)

Globalization has benefited the economies of member countries of the Organization for Economic Cooperation and Development (OECD) by helping their businesses stay profitable through cost-effective outsourcing of mostly garden-variety tasks and some knowledge-based activities. With time, the latter will account for the lion's share of work outsourced and emerging export houses will also tend to cater more to their own domestic markets because of their expanding infrastructure and growing manpower possessing advanced skills. This will result in a leveled playing field coaxing developed countries to adopt widespread innovations to maintain their high perch in the economic pecking order. Such large-scale creativity can be managed better if it could be gauged with an appropriate measure. This work propounds a new economic measure called the Gross Domestic Innovation (GDI) to quantify innovations in OECD countries. It will supplement universal measures such as the Gross Domestic Product (GDP), productivity and numbers concerning employment. Apart from the methodology for its estimation, the impact of GDI on the various facets of a vibrant economy is discussed and inter alia, the role of GDI in fighting inflation and alleviating the negative influences of globalization is stressed. Also, a tentative analysis on the economies of U.S., Japan, Germany and China is presented to illustrate the concept.
The Need for Heroes
Authors: S. H. Unger
Venue: Computer (1972)

In a play about Galileo, Bertold Brecht has one of his characters comment bitterly after Galileo's recantation that "unhappy is a land that breeds no heroes." The reply by Galileo is "unhappy is a land that needs heroes."