ppxscal/embedding_network huggingface dataset:
Design and manufacturing of cranioplasty implants by 3-axis cnc milling
Authors: L. C. Hieu, E. Bohez, J. Vander Sloten, P. Oris, H. N. Phien, E. Vatcharaporn, P. H. Binh
Venue: Technology and Health Care (2002)

Although various techniques and materials have been used for making cranioplasty implants, personalized cranioplasty implants are high in cost because of expensive materials and production technology, long design and manufacturing time, and intensive labor use. This research was a part of our research project in ASEAN countries to investigate feasible technical solutions of minimizing the implant cost based on available production technologies in the region. The use of 3-axis CNC (Computer Numerical Control) milling techniques for making molds to fabricate PMMA implants was successfully investigated. With the development of a design support program bridging between Computer Aided Design (CAD) and Medical Image Processing (MIP) system, the time for geometrical modeling of implants and molds was reduced to half a day. The machining time to complete a mold was about 5 to 6 hours; and it took maximal 2 hours to fabricate an implant with self-curing PMMA and 3 and half hours for fabricating an implant with heat-curing PMMA. The cost of implants is acceptable for the ASEAN region.
A Fast Carrier Synchronization Algorithm for Burst-Mode MPSK
Authors: Lianfen Huang, Mingsheng Luo, Xiangxu Dong
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 05 (2007)

On the basis of carrier synchronization algorithms in traditional continuous communications, a fast carrier synchronization algorithm for burst-mode MPSK, based on the Mth power loop-like with feedforward and open-loop structure, was put forward in this paper. Moreover, we proposed two improved approaches to the deficiencies of this algorithm and analyzed, simulated the performance of these algorithms. The simulation results demonstrate that the algorithm with backward-estimation and compensation has the best performance among the three, and outperforms other normal approaches to carrier synchronization in bit error rate (BER) when the carrier frequency-offset is relatively small. Finally, the algorithm with backward-estimation and compensation is applied to practical communications systems and has achieved superior performance.
The scheme of things: exact and inexact numbers
Authors: William Clinger
Venue: ACM SIGPLAN Lisp Pointers (1988)

Numbers are one of the greatest achievements of humanity. They are the product of many thousands of years of effort by the best minds of history---and prehistory. That effort continues, for our concept of numbers is, and will remain, unfinished.
Exploiting Constraint Solving History to Construct Interaction Test Suites
Authors: Myra B. Cohen, Matthew B. Dwyer, Jiangfan Shi
Venue: Proceedings of the Testing: Academic and Industrial Conference Practice and Research Techniques - MUTATION (2007)

Researchers have explored the application of combinatorial interaction testing (CIT) methods to construct samples to drive systematic testing of software system configurations. Applying CIT to highly-configurable software systems is complicated by the fact that, in many such systems, there are constraints between specific configuration parameters that render certain combinations invalid. In recent work, automated constraint solving methods have been combined with search-based CIT methods to address this problem with promising results. In this paper, we observe that the pattern of computation in greedy CIT algorithms leads to sequences of constraint solving problems that are closely related to one another. We propose two techniques for exploiting the history of constraint solving: (1) using incremental algorithms that are present within available constraint solvers and (2) mining constraint solver data structures to extract information that can be used to reduce the CIT search space. We evaluate the cost-effectiveness of these reductions on four real-world highly-configurable software systems and on a population of synthetic examples that share the characteristics of those four systems. In combination our techniques reduce the cost of CIT in the presence of constraints to that of traditional unconstrained CIT methods without sacrificing the quality of solutions.
A Job Scheduling Optimization Model based on Time Difference in Service Grid Environments
Authors: Jianxun Liu, Chunjie Zhou, Jinjun Chen, Hongwen Liu, Yiping Wen
Venue: Proceedings of the Sixth International Conference on Grid and Cooperative Computing (2007)

Service grid can provide us an environment to distribute tasks to executors around the world. Since there exist time zone difference and different working calendar systems for independent organizations, there will be some organizations are on-duty while others are off work at a specified time point. Therefore, the time factors can play an important role for job optimization scheduling in service grid. Aiming at utilizing the time difference, this paper proposed and constructed a mathematical model to solve the problem of completion time optimization of task scheduling in these environments. A case study is analyzed and it is shown that the whole execution time of the tasks can be shortened a lot while compared with the local execution scheduling model.
A Robust Method for Detecting Regression Change Points
Authors: Li-Li Wei, Chong-Zhao Han
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01 (2007)

Change-points detection is one of the important problems in data analysis. Traditional investigations on the detection of change-points considering little infection of noise always ignore the robust of the methods. In this paper, a highly robust regression-class mixture decomposition method is proposed for finding change-points in a large data set. By using this method, the problem of detecting change-point can be converted to determine the breakpoint of different regression classes. We can mine all of the regression classes first, and then determine the estimation of change-points by anglicizing the two joined regression-classes. So the change-points can be found with little prior information. The analysis of experiments shows that our method can detect change-points in a data set with a large proportion of noisy, which demonstrate that this method is very robust and effective in change points detection.
Fuzzy Concept Lattice Based Classifier
Authors: Wen Zhou, Zongtian Liu, Yan Zhao, Yu Zheng, Dong Xu, Wei Liu, Ying Zhu
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01 (2007)

The large collection of formal concepts can be a hedge of the application of FCA. Development of methods which help to overcome the problem of the huge size of concept lattice is thus an important task. This paper proposes clustering-based reduction algorithm for reducing the size of fuzzy concept lattices. At the end, experiment results show that the compression rate of the concept lattice and classifier is remarkable, while it preserves the accuracy of classification of concept lattice.
The health record banking imperative: a conceptual model
Authors: Jonathan D. Gold Marion J. Ball
Venue: IBM Systems Journal (2007)

No unified, functioning system currently exists for the exchange of comprehensive health-care information across the wide spectrum of health-care networks. Regional health information organizations (RHIOs) and a national health information network (NHIN) have been proposed as vital building blocks in providing such a system, but these face many challenges, including delineation and implementation of accepted standards for health-care data, accurate patient identification and record matching, and the definition of incentives for accelerated deployment of health information technology. In response to these challenges, we present in this paper an alternative option, the Health Record Banking (HRB) system. Emulating commercial banking, this approach uses health-record banks to serve the need for immediately accessible and secure data for diverse stakeholders. It provides a means for financial independence for these banks and a mechanism for fostering medical research. We conclude with 10 critical issues associated with the development and implementation of an HRB system, which require public discussion.
Active Services Model and its Supporting Platform in Grid Environment
Authors: Ming Zhong, Yaoxue Zhang, Cunhao Fang, Pengwei Tian
Venue: Proceedings of the Sixth International Conference on Grid and Cooperative Computing (2007)

Grid is a new paradigm of Internet computing and is developing rapidly. Web service technologies have improved the interoperability of grid protocols and services, as well as providing a unified functional extension mechanism. But current research has not definitely solved the problem of system construction based on Web services in grid environment, especially on the method of dynamically assembling existing resource to realize user-oriented services. This paper introduces an Active Services model and its supporting platform in grid computing environment, which focuses on relieving the disorder condition in service creating, publishing and deploying and providing a new method to provide user-oriented Active Services in grid computing environment. Active Services are proposed to actively collect, organize, classify and manage the published services to create services resource view for users on application level, and dynamically assemble and execute those services to meet the user demands. The paper also presents the implementation of Compositive suppOrting and Management Platform (COMP), with an applied case of customized multimedia player generated on it.
Quality of service in stateful information filters
Authors: Peter M. Fischer, Donald Kossmann
Venue: Proceedings of the 3rd workshop on Data management for sensor networks: in conjunction with VLDB 2006 (2006)

Information Filters play an important role in processing streams of events, both for filtering as well as routing events based on their content. Stateful information filters like AGILE [15], Cayuga [13] and SASE [24] have gained a significant amount of attention recently. Such filters not only consider the data of a single event, but also additional state such as a sequence of previous events or a context state. Applications for Wireless Sensors and RFID data are particularly prominent examples for the need for stateful information filtering, with use cases like event correlation or sensor data affecting the routing of other events. While quality of service has been researched fairly thoroughly for networking systems and general data stream management systems, no comprehensive work exists for information filters. The goal of this work is to present QoS criteria for stateful information filters and to examine how QoS control methods established in other areas can be applied to information filters.
An introduction to nonlinear analysis of fuzzy control systems
Authors: David F. Jenkins, Kevin M. Passino
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (1999)

While the design methodology for fuzzy controllers has proven itself in certain commercial and industrial applications, there is a significant need to perform mathematical analysis of fuzzy control systems prior to implementation&colon; (i) to verify and certify their behavior so that, for example, instabilities can be avoided for applications demanding highly reliable operation such as aircraft and nuclear reactor control, and (ii) to provide insight to the expert on how to modify the fuzzy controller to guarantee that performance specifications are met (e.g., to guarantee a specified rise-time or the absence of steady state tracking error). In this paper we provide a survey of, and an introduction to the area of nonlinear analysis of fuzzy control systems. We begin by overviewing several approaches to stability analysis including Lyapunov's Direct and Indirect Methods, and the Circle Criterion. We provide examples to illustrate how to design stable fuzzy control systems and test for stability, including an application of Lyapunov's direct method to Takagi-Sugeno fuzzy systems. Next, we introduce the idea of analyzing the steady state tracking error of a class of fuzzy control systems and provide examples of how to predict and reduce steady state error. Finally, we provide an introduction to the use of the describing function technique for the prediction of the existence, frequency, amplitude, and stability of limit cycles. We provide examples of limit cycle analysis and show how to design fuzzy controllers to avoid limit cycles. While our primary objective is to provide a control-theoretic introduction to, and survey of approaches to nonlinear analysis of fuzzy control systems where we utilize several existing results and provide useful tutorial examples, in the process we actually make contributions by providing, for example, the first results that show how to analyze steady state tracking error for fuzzy control systems.
A Model Combined Fuzzy Optimum Theory with Analytical Hierarchy Process for Engineering Design
Authors: Chi Zhang, Xumei Song, Wei Li
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04 (2007)

Engineering scheme optimization is of particular importance in the concept design process, which involves multiple objectives with uncertainty. Also, the objective set, used to evaluate and select the satisfying alternative, consists of many qualitative and quantitative factors. So it is a problem of semi-structured multi-objective decision making (SEMODM). This paper develops a framework and methodology for evaluation of engineering alternatives, where a fuzzy optimum model (FOM) is proposed to integrate the influence of each objective in the criteria set, and the analytical hierarchy process (AHP) is adopted to calculate the weight vector, which can mimic the decision maker's experience and preference based on comple-mentary pair wise comparisons. A case study is given to show the efficiency and robustness of the new framework and methodology.
Load-Balanced Routing in Wireless Networks: State Information Accuracy Using OLSR
Authors: Thomas Kunz, Rana Alhalimi
Venue: Proceedings of the Third IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (2007)

To support QoS routing, accurate state should be available and manageable. But due to bandwidth constraints, communication costs, high loss rate and the dynamic topology of wireless networks, obtaining and keeping up-to-date state information is a very complex task. A commonly used QoS metric is router queue length, used as a load metric in a number of load-balancing routing protocols. In this paper, we explore how to accurately propagate information about a router's queue length in a network that runs the Optimized Link State Routing (OLSR) protocol. We report the quantification of state information accuracy under different traffic rates. The results show that state information is inaccurate, especially under high traffic rates. Tuning the OLSR protocol parameters has no noticeable impact on inaccuracy levels. Based on our initial analysis, we propose two additional techniques to collect queue length information as an attempt to reduce inaccuracies. We compare the different techniques against the basic OLSR, no additional improvements were observed. The results raise questions as to how load-balanced routing should be done in the face of non-negligible inaccuracies in the load metric.
Improving Evolutionary Testing in the Presence of Function-Assigned Flags
Authors: Stefan Wappler, Andre Baresel, Joachim Wegener
Venue: Proceedings of the Testing: Academic and Industrial Conference Practice and Research Techniques - MUTATION (2007)

Evolutionary structural testing, an approach to automat- ically generating relevant unit test cases, encounters dif- ficulties when the tested software contains boolean vari- ables. This issue, known as the flag problem, has been stud- ied by many researchers. However, previous work does not address the issue of function-assigned flags which consti- tutes a special type of the flag problem that often occurs in the context of object-orientation. This paper elaborates on a new approach to the flag problem that can also handle function-assigned flags while being applicable to the con- ventional flag problem, as well. It relies on a code transfor- mation that leads to an improved fitness landscape which provides better guidance to the evolutionary search. We present four case studies including a fitness landscape anal- ysis and empirical results. The results show that the sug- gested code transformation improves evolutionary struc- tural testing in the presence of function-assigned flags.
The Symbolics Genera Programming Environment
Authors: J. H. Walker
Venue: IEEE Software (1987)

This Lisp-based system helps designers get from prototype to product faster. The key is an open architecture and highly integrated development tools.
A self-adjusting clock tree architecture to cope with temperature variations
Authors: Jieyi Long, Ja Chun Ku, Seda Ogrenci Memik, Yehea Ismail
Venue: Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design (2007)

Ensuring resilience against environmental variations is becoming one of the great challenges of chip design. In this paper, we propose a self adjusting clock tree architecture, SACTA, to improve chip performance and reliability in the presence of on-chip temperature variations. SACTA performs temperature dependent dynamic clock skew scheduling to prevent timing violations in a pipelined circuit. We present an automatic temperature adjustable skew buffer design, which enables the adaptive feature of SACTA. Furthermore, we propose an efficient and general optimization framework to determine the configuration of these special delay elements. Experimental results show that a pipeline supported by SACTA is able to prevent thermal induced timing violations within a significantly larger range of operating temperatures (enhancing the violation-free range by as much as 45&deg;C).
Hybrid Mathematical Symbol Recognition Using Support Vector Machines
Authors: B. Keshari, S. Watt
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02 (2007)

Recognition of mathematical symbols is a challenging task, with a large set with many similar symbols. We present a support vector machine based hybrid recognition system that uses both online and offline information for classifica- tion. Probabilistic outputs from the two support vector ma- chine based multi-class classifiers running in parallel are combined by taking a weighted sum. Results from the exper- iments show that giving slightly higher weight to the on-line information produces better results. The overall error rate of the hybrid system is lower than that of both the online and offline recognition systems when used in isolation.
Time series compressibility and privacy
Authors: Spiros Papadimitriou, Feifei Li, George Kollios, Philip S. Yu
Venue: Proceedings of the 33rd international conference on Very large data bases (2007)

In this paper we study the trade-offs between time series compressibility and partial information hiding and their fundamental implications on how we should introduce uncertainty about individual values by perturbing them. More specifically, if the perturbation does not have the same compressibility properties as the original data, then it can be detected and filtered out, reducing uncertainty. Thus, by making the perturbation "similar" to the original data, we can both preserve the structure of the data better, while simultaneously making breaches harder. However, as data become more compressible, a fraction of the uncertainty can be removed if true values are leaked, revealing how they were perturbed. We formalize these notions, study the above trade-offs on real data and develop practical schemes which strike a good balance and can also be extended for on-the-fly data hiding in a streaming environment.
Genomic mining for complex disease traits with "random chemistry"
Authors: Margaret J. Eppstein, Joshua L. Payne, Bill C. White, Jason H. Moore
Venue: Genetic Programming and Evolvable Machines (2007)

Our rapidly growing knowledge regarding genetic variation in the human genome offers great potential for understanding the genetic etiology of disease. This, in turn, could revolutionize detection, treatment, and in some cases prevention of disease. While genes for most of the rare monogenic diseases have already been discovered, most common diseases are complex traits, resulting from multiple gene---gene and gene-environment interactions. Detecting epistatic genetic interactions that predispose for disease is an important, but computationally daunting, task currently facing bioinformaticists. Here, we propose a new evolutionary approach that attempts to hill-climb from large sets of candidate epistatic genetic features to smaller sets, inspired by Kauffman's "random chemistry" approach to detecting small auto-catalytic sets of molecules from within large sets. Although the algorithm is conceptually straightforward, its success hinges upon the creation of a fitness function able to discriminate large sets that contain subsets of interacting genetic features from those that don't. Here, we employ an approximate and noisy fitness function based on the ReliefF data mining algorithm. We establish proof-of-concept using synthetic data sets, where individual features have no marginal effects. We show that the resulting algorithm can successfully detect epistatic pairs from up to 1,000 candidate single nucleotide polymorphisms in time that is linear in the size of the initial set, although success rate degrades as heritability declines. Research continues into seeking a more accurate fitness approximator for large sets and other algorithmic improvements that will enable us to extend the approach to larger data sets and to lower heritabilities.
Time-efficient spam e-mail filtering using n-gram models
Authors: Ali Çıltık, Tunga Güngör
Venue: Pattern Recognition Letters (2008)

In this paper, we propose spam e-mail filtering methods having high accuracies and low time complexities. The methods are based on the n-gram approach and a heuristics which is referred to as the first n-words heuristics. We develop two models, a class general model and an e-mail specific model, and test the methods under these models. The models are then combined in such a way that the latter one is activated for the cases the first model falls short. Though the approach proposed and the methods developed are general and can be applied to any language, we mainly apply them to Turkish, which is an agglutinative language, and examine some properties of the language. Extensive tests were performed and success rates about 98% for Turkish and 99% for English were obtained. It has been shown that the time complexities can be reduced significantly without sacrificing performance.