ppxscal/embedding_network huggingface dataset:
Approximation Degrees in Decision Reduct-Based MRI Segmentation
Authors: Sebastian Widz, Dominik Slezak
Venue: Proceedings of the 2007 Frontiers in the Convergence of Bioscience and Information Technologies (2007)

Segmentation of Magnetic Resonance Images (MRI) is a process of assigning the tissue class labels to voxels. One of the main sources of segmentation error is the partial volume effect (PVE), which occurs most often with low resolution images. Indeed, for large voxels, the probability of a voxel containing multiple tissue classes increases. We have utilized a classification approach based on the attribute reduction, derived from the data mining paradigm of the theory of rough sets. An approximate reduct is an irreducible subset of features, which enables to classify decision concepts with a satisfactory degree of accuracy in the training data. The ensembles of the best found reducts trained for appropriate approximation degrees are applied to segmentation of previously unseen (parts of) images. One of the challenges is to adjust the approximation level during the training phase to obtain the best classification results for new cases. In this paper, it is proved experimentally that the choice of approximation level, consequently related to generality of classification rules induced by reducts, should correspond to expected quality of images. We show that when dealing with noisy images, or images with high PVE level, better results are obtained with higher degrees of approximation. Keywords: Rough Sets, Decision Reducts, Approximation Degrees, MRI Segmentation, Partial Volume Effect.
Zero skew clock routing in X-architecture based on an improved greedy matching algorithm
Authors: Weixiang Shen, Yici Cai, Xianlong Hong, Jiang Hu, Bing Lu
Venue: Integration, the VLSI Journal (2008)

As technology advances into nanometer territory, clock network layout plays an increasingly important role in determining circuit quality indicated by timing, power consumption, cost, power supply noise and tolerance to process variation. To alleviate the challenges to the existing routing algorithms due to the continuous increase of the problem size and the high-performance requirement, X-architecture has been proposed and applied to routing in that it can reduce wirelength and via counts, and thus improves the performance and routability compared with the conventional Manhattan routing. In this paper, we investigate zero skew clock routing using X-architecture based on an improved greedy matching algorithm (GMZSTX). The fitted Elmore delay model is employed to improve the accuracy over the Elmore delay model. The interactions among distance, delay balance and load balance are analyzed. Based on this analysis, an effective and efficient greedy matching scheme is suggested to reduce wire snaking and to get a more balanced clock tree. The proposed algorithm is simple and fast for practical applications. Experimental results on benchmark circuits show that our algorithm (GMZSTX) achieves a reduction of 8.15% in total wirelength, 30.19% in delay and 55.31% in CPU time on average compared with zero skew clock routing in the Manhattan plane (BB+DME-2, which means using the top-down balanced bipartition (BB) method [T.H. Chao, Y.C. Hsu, J.M. Ho, et al., Zero skew routing with minimum wirelength, IEEE Trans. Circuits Syst. II-Analog & Digital Signal Process 39 (11) (1992) 799-814] to generate the tree topology and using the Deferred-Merge Embedding (DME) algorithm [T.H. Chao, Y.C. Hsu, J.M. Ho, et al., Zero skew routing with minimum wirelength, IEEE Trans. Circuits Syst. II-Analog & Digital Signal Process 39 (11) (1992) 799-814] to embed the internal nodes), and reduces delay and CPU time by 17.44% and 62.21% on average over the BB+DME-4 method (which is similar to BB+DME-2, but routing in X-architecture). Our SPICE simulation further verifies the correctness of the resulting clock tree.
Boosting Haplotype Inference with Local Search
Authors: Inês Lynce, João Marques-Silva, Steve Prestwich
Venue: Constraints (2008)

A very challenging problem in the genetics domain is to infer haplotypes from genotypes. This process is expected to identify genes affecting health, disease and response to drugs. One of the approaches to haplotype inference aims to minimise the number of different haplotypes used, and is known as haplotype inference by pure parsimony (HIPP). The HIPP problem is computationally difficult, being NP-hard. Recently, a SAT-based method (SHIPs) has been proposed to solve the HIPP problem. This method iteratively considers an increasing number of haplotypes, starting from an initial lower bound. Hence, one important aspect of SHIPs is the lower bounding procedure, which reduces the number of iterations of the basic algorithm, and also indirectly simplifies the resulting SAT model. This paper describes the use of local search to improve existing lower bounding procedures. The new lower bounding procedure is guaranteed to be as tight as the existing procedures. In practice the new procedure is in most cases considerably tighter, allowing significant improvement of performance on challenging problem instances.
(2 + ε)-Coloring of planar graphs with large odd-girth
Authors: William Klostermeyer, Cun Quan Zhang
Venue: Journal of Graph Theory (2000)

The odd-girth of a graph is the length of a shortest odd circuit. A conjecture by Pavol Hell about circular coloring is solved in this article by showing that there is a function 풻(&epsilon;) for each &epsilon; : 0 < &epsilon; < 1 such that, if the odd-girth of a planar graph G is at least 풻(&epsilon;), then G is (2 + &epsilon;)-colorable. Note that the function 풻(&epsilon;) is independent of the graph G and &epsilon; ➝ 0 if and only if 풻(&epsilon;) ➝ &infin;. A key lemma, called the folding lemma, is proved that provides a reduction method, which maintains the odd-girth of planar graphs. This lemma is expected to have applications in related problems. &copy; 2000 John Wiley Sons, Inc. J Graph Theory 33: 109119, 2000
Approximate colored range and point enclosure queries
Authors: Ying Kit Lai, Chung Keung Poon, Benyun Shi
Venue: Journal of Discrete Algorithms (2008)

In this paper, we formulate two classes of problems, the colored range query problems and the colored point enclosure query problems to model multi-dimensional range and point enclosure queries in the presence of categorical information. Many of these problems are difficult to solve using traditional data structural techniques. Based on a new framework of combining sketching techniques and traditional data structures, we obtain two sets of results in solving the problems approximately and efficiently. In addition, the framework can be employed to attack other related problems by finding the appropriate summary structures.
Effective Feature Space Reduction with Imbalanced Data for Semantic Concept Detection
Authors: Lin Lin, Guy Ravitz, Mei-Ling Shyu, Shu-Ching Chen
Venue: Proceedings of the 2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008) (2008)

Semantic understanding of multimedia content has become a very popular research topic in recent years. Semantic concept detection algorithms face many challenges such as the semantic gap and imbalance data, among others. In this paper, we propose a novel algorithm using multiple correspondence analysis (MCA) to discover the correlation between features and classes to reduce the feature space and to bridge the semantic gap. Moreover, the proposed algorithm is able to explore the correlation between items (i.e., feature-value pairs generated for each of the features) and classes which expands its ability to handle imbalance data sets. To evaluate the proposed algorithm, we compare its performance on semantic concept detection with several existing feature selection methods under various well-known classifiers using some of the concepts and benchmark data available from the TRECVID project. The results demonstrate that our proposed algorithm achieves promising performance, and it performs significantly better than those feature selection methods in the comparison for the imbalanced data sets.
Algorithm and Software Optimization of Variable Block Size Motion Estimation for H.264/AVC on a VLIW---SIMD DSP
Authors: Wonchul Lee, Hyojin Choi, Wonyong Sung
Venue: Journal of Signal Processing Systems (2008)

We implemented the H.264/AVC variable block size motion estimation (VBSME) using a very long instruction word (VLIW)---single instruction multiple data (SIMD) digital signal processor (DSP). The SAD_Reuse method which has a regular structure is chosen for VBSME not only to remove redundant sum of absolute difference (SAD) operations but also to utilize the instruction level parallelism (ILP) and data level parallelism (DLP) of the architecture. A fast mode decision algorithm is developed to reduce the number of `compare and update' operations and simplify the rate distortion optimization (RDO). The developed fast mode decision uses the difference of motion vectors and the maximum a posteriori (MAP) estimation of the rate-distortion costs. Several advanced software techniques that include software pipelining and packed-data processing are employed. Especially, memory access overhead reduction schemes including the multi-block processing and the inter-procedural scheduling are used for the software optimization. In order to reduce the `write buffer full' in the quarter pixel ME, a 4 bit quantization scheme is developed, which increases the number of arithmetic operations but decreases the stall cycles very much. The implemented variable block size ME for H.264/AVC requires an average of 9 M and 78 Mcycles per frame for QCIF and CIF size video sequences, respectively, in the TMS320C64x DSP architecture.
Coordination in multiagent reinforcement learning systems by virtual reinforcement signals
Authors: M. A. S. Kamal, Junichi Murata
Venue: International Journal of Knowledge-based and Intelligent Engineering Systems (2007)

This paper presents a novel method for on-line coordination in multiagent reinforcement learning systems. In this method a reinforcement-learning agent learns to select its action estimating system dynamics in terms of both the natural reward for task achievement and the virtual reward for cooperation. The virtual reward for cooperation is ascertained dynamically by a coordinating agent who estimates it from the change in degree of cooperation of all agents using a separate reinforcement learning. This technique provides adaptive coordination, requires less communication and ensures agents to be cooperative. The validity of virtual rewards for convergence in learning is verified, and the proposed method is tested on two different simulated domains to illustrate its significance. The empirical performance of the coordinated system compared to the uncoordinated system illustrates its advantages for multiagent systems.
Evolving blackbox quantum algorithms using genetic programming
Authors: Ralf Stadelhofer, Wolfgang Banzhaf, Dieter Suter
Venue: Artificial Intelligence for Engineering Design, Analysis and Manufacturing (2008)

Although it is known that quantum computers can solve certain computational problems exponentially faster than classical computers, only a small number of quantum algorithms have been developed so far. Designing such algorithms is complicated by the rather nonintuitive character of quantum physics. In this paper we present a genetic programming system that uses some new techniques to develop and improve quantum algorithms. We have used this system to develop two formerly unknown quantum algorithms. We also address a potential deficiency of the quantum decision tree model used to prove lower bounds on the query complexity of the parity problem.
A mathematical solution to power optimal pipeline design by utilizing soft edge flip-flops
Authors: Mohammad Ghasemazar, Behnam Amelifard, Massoud Pedram
Venue: Proceeding of the 13th international symposium on Low power electronics and design (2008)

This paper presents a novel technique to minimize the total power consumption of a synchronous linear pipeline circuit by exploiting extra slacks available in some stages of the pipeline. The key idea is to utilize soft-edge flip-flops to enable time borrowing between stages of a linear pipeline in order to provide the timing-critical stages with more time to complete their computations. Time borrowing, in conjunction with keeping the clock frequency unchanged, gives rise to a positive timing slack in each pipeline stage. The slack is subsequently utilized to minimize the circuit power consumption by reducing the supply voltage level. We formulate and solve the problem of optimally selecting the transparency window of the soft-edge flip-flops and choosing the minimum supply voltage level for the pipeline circuit as a quadratic program, thereby minimizing the power consumption of the linear pipeline circuit under a clock frequency constraint. Experimental results prove the efficacy of the problem formulation and solution technique.
Workshop on state-space exploration for automated testing (SSEAT 2008)
Authors: Darko Marinov, Wolfram Schulte
Venue: Proceedings of the 2008 international symposium on Software testing and analysis (2008)

SSEAT 2008 is a workshop that focuses on the recent research approaches to automated testing using state-space exploration techniques. The goal of the workshop is to bring together researchers from both industry and academia to informally discuss the latest successes and remaining challenges in this domain. One important aspect of the workshop is to discuss techniques that were tried but did not work well in certain contexts. Another important aspect is to try to identify a set of programs that can be used for comparing various tools and techniques. There will be no proceedings, but a brief summary of the workshop will appear at the workshop web page.
Efficient multiclass maximum margin clustering
Authors: Bin Zhao, Fei Wang, Changshui Zhang
Venue: Proceedings of the 25th international conference on Machine learning (2008)

This paper presents a cutting plane algorithm for multiclass maximum margin clustering (MMC). The proposed algorithm constructs a nested sequence of successively tighter relaxations of the original MMC problem, and each optimization problem in this sequence could be efficiently solved using the constrained concave-convex procedure (CCCP). Experimental evaluations on several real world datasets show that our algorithm converges much faster than existing MMC methods with guaranteed accuracy, and can thus handle much larger datasets efficiently.
Reproduction of global impression of landscape images by improved texture reconstruction methods
Authors: Toshihiro Bando, Tomohiro Oshima
Venue: Machine Graphics Vision International Journal (2006)

In order to reproduce the atmosphere or the global impression of the landscape images we have created model patterns by reconstructing the texture of the whole images. We have first segmented full-color landscape images into patches of same color after converting them into 216-color images, and then analyzed the size and the center of gravity of each color patch. We have created five improved reconstructed model patterns from the data in the color patches. Some of the reconstructed texture patterns are similar in the global appearance to the original landscape images, although the details of the original images have been completely destroyed, to the extent that it is difficult to understand what these images represent at all. Each of the reconstructed patterns has been evaluated in order to find good methods for reproducing the atmosphere of the landscape. The patterns reconstructed using the proposed methods, which take into consideration the shape and position of the original color patches, demonstrate very high quality. The results suggest that the reconstructed global texture of the whole image creates an atmosphere or a global impression of the landscape images.
Fuzzy diagnosis of turbomachines
Authors: Meijun Yang, Qiang Shen
Venue: International Journal of Knowledge-based and Intelligent Engineering Systems (2008)

This paper presents a fuzzy knowledge-based system for turbomachinery diagnosis. Given symptoms associated with a vibration problem, the system can identify and rank possible causes by performing incremental forward chaining. The diagnostic system incorporates an attribute weighting component to reflect the relative significance of conditional attributes, thereby allowing the system to produce more accurate diagnoses. The ability of this system to identify causes of typical vibration problems in rotating machinery is supported with tests on real cases.
Fabrication of miniaturized Schottky emitter by wire electrical discharge machining (WEDM)
Authors: A. K. Dokania, M. Pelle, P. Kruit
Venue: Microelectronic Engineering (2008)

The Schottky emitter is extensively used in scanning electron beam lithography machines because of its high brightness and stable current. For its use in parallel electron beam lithography to increase the throughput, we are investigating the possibility of creating an array of miniaturized Schottky emitters. This paper discusses a novel method of fabricating a miniaturized Schottky emitter of 1mm diameter by wire-electro discharge machining (WEDM). Various WEDM process parameters were optimized for better reproducibility and surface finish of the fabricated emitter. The fabricated samples match well with the intended input design, with no visible stress or bending. Joule heating in vacuum shows good operational feasibility and temperature stability. After heating, the tip becomes as sharp as conventional Schottky emitters. The miniaturized emitter operates at a relatively low power.
A simple diagnostic method for memory testing
Authors: Keon-Jik Lee, Byeong-Jik Lee, Seong-Woon Kim
Venue: Proceedings of the 2nd WSEAS International Conference on Electronics, Control and Signal Processing (2003)

We present the efficient and simple diagnostic method for memory integrity test. This paper gives an introduction how to construct memory tests and test flows. A typical memory test steps through the memory array and tests all cells. It ensures that addresses works and all cells can store and retrieve '0' and '1' information. Step by step a basic test is developed choosing a pattern. Starting with this basic pattern, modifications for characterization, diagnostic are discussed. These variations are then used to construct a test sequence to ensure functionality according to the data sheet specification. The proposed algorithms facilitate the simple and efficient diagnosis of semiconductor memories.
Excel Modeling in the Fundamentals of Corporate Finance Book and CD-ROM, 2 edition
Authors: Craig W. Holden
Venue:  (2007)

It teaches the reader how to build financial modelsnot templateswith step-by-step instructions in Excel. Progressing from simple examples to practical, real-world applications, this book covers the time value of money, valuation, capital budgeting, financial planning, and options and corporate finance. For financial planners and analysts.
Session mobility of SIP over multiple devices
Authors: Min-Xiou Chen, Fu-Ju Wang
Venue: Proceedings of the 4th International Conference on Testbeds and research infrastructures for the development of networks & communities (2008)

Session Initiation Protocol (SIP) has been widely applied to telephony service. SIP is also adopted as the signal communication protocol of VoIP and 3GPP, so the development of SIP receiving much concern. Currently the research of SIP can be divided into four issues, including terminal mobility, session mobility, personal mobility, and service mobility. In this paper, we address the issue of session mobility. We want to solve the problem allowing a user to transfer, split, and retrieve a session over multiple devices by using SIP. In order to provide the service, three new agents have been introduced based on the definition of user agent proposed in RFC 3261. There are session manager, session user, and free node. Based on these agents, we propose a complete mechanism, to transfer and retrieve a session over multiple devices. According to our mechanism, the user will facility transfers, splits, and retrieves a session over multiple devices. Finally, we implement the mechanism by modifying the open source project of "Sip-Communicator".
Telepresence after death
Authors: Matthew Lombard Melissa E. Markaridian Selverian
Venue: Presence: Teleoperators and Virtual Environments (2008)

This paper examines some of the increasingly sophisticated attempts by humans to evoke the presence of themselves or others after death and considers these efforts in the context of telepresence theory and research. Potential future research and ethical implications are also addressed.
Mercury BLASTP: Accelerating Protein Sequence Alignment
Authors: Arpith Jacob, Joseph Lancaster, Jeremy Buhler, Brandon Harris, Roger D. Chamberlain
Venue: ACM Transactions on Reconfigurable Technology and Systems (TRETS) (2008)

Large-scale protein sequence comparison is an important but compute-intensive task in molecular biology. BLASTP is the most popular tool for comparative analysis of protein sequences. In recent years, an exponential increase in the size of protein sequence databases has required either exponentially more running time or a cluster of machines to keep pace. To address this problem, we have designed and built a high-performance FPGA-accelerated version of BLASTP, Mercury BLASTP. In this article, we describe the architecture of the portions of the application that are accelerated in the FPGA, and we also describe the integration of these FPGA-accelerated portions with the existing BLASTP software. We have implemented Mercury BLASTP on a commodity workstation with two Xilinx Virtex-II 6000 FPGAs. We show that the new design runs 11--15 times faster than software BLASTP on a modern CPU while delivering close to 99% identical results.
A fast planar partition algorithm. I
Authors: K. Mulmuley
Venue: Proceedings of the 29th Annual Symposium on Foundations of Computer Science (1988)

A fast randomized algorithm is given for finding a partition of the plane induced by a given set of linear segments. The algorithm is ideally suited for a practical use because it is extremely simple and robust, as well as optimal; its expected running time is O(m+n log n) where n is the number of input segments and m is the number of points of intersection. The storage requirement is O(m+n). Though the algorithm itself is simple, the global evolution of the partition is complex, which makes the analysis of the algorithm theoretically interesting in its own right.
The influence of temperature and precipitation climate regimes on vegetation dynamics in the US Great Plains: a satellite bioclimatology case study
Authors: S. -Y. Tan
Venue: International Journal of Remote Sensing (2007)

Advanced Very High Resolution Radiometer (AVHRR)-derived Normalized Difference Vegetation Index (NDVI) data are widely used in global-change research, yet relationships between the NDVI and ecoclimatological variables are not fully understood. This study attempts to model climate-driven vegetation dynamics through the integration of satellite-derived NDVI data with climate data collected from ground-based meteorological stations in the US Great Plains. Monthly maximum value composites of NDVI data (8-km resolution) and monthly temperature and precipitation records from 305 stations were collected from 1982 to 2001. Analyses involving deseasonalized datasets supported temperature as the dominant climate regime, demonstrating a higher average NDVI-temperature correlation (r = 0.73) than the NDVI-precipitation relationship (r = 0.38). Cluster analysis was used to develop a climate regionalization scheme based primarily on temperature, and NDVI characteristics of each subregion were compared. In the context of global climate change, findings from this study emphasize the influence of temperature and precipitation variability over vegetation cover in the Great Plains region.