Particle Track Classification Using Quantum Associative Memory (Final Technical Report)

Pattern matching algorithms have gained a lot of importance in computer science, primarily because they are used in various domains such as computational biology, video retrieval, intrusion detection systems, and fraud detection. Finding one or more patterns in a given text is known as pattern matching. Two important things that are used to judge how well exact pattern matching algorithms work are the total number of attempts and the character comparisons that are made during the matching process. The primary focus of our proposed method is reducing the size of both components wherever possible. Despite sprinting, hash-based pattern matching algorithms may have hash collisions. The Efficient Hashing Method (EHM) algorithm is improved in this research. Despite the EHM algorithm’s effectiveness, it takes a lot of time in the preprocessing phase, and some hash collisions are generated. A novel hashing method has been proposed, which has reduced the preprocessing time and hash collision of the EHM algorithm. We devised the Hashing Approach for Pattern Matching (HAPM) algorithm by taking the best parts of the EHM and Quick Search (QS) algorithms and adding a way to avoid hash collisions. The preprocessing step of this algorithm combines the bad character table from the QS algorithm, the hashing strategy from the EHM algorithm, and the collision-reducing mechanism. To analyze the performance of our HAPM algorithm, we have used three types of datasets: E. coli, DNA sequences, and protein sequences. We looked at six algorithms discussed in the literature and compared our proposed method. The Hash-q with Unique FNG (HqUF) algorithm was only compared with E. coli and DNA datasets because it creates unique bits for DNA sequences. Our proposed HAPM algorithm also overcomes the problems of the HqUF algorithm. The new method beats older ones regarding average runtime, number of attempts, and character comparisons for long and short text patterns, though it did worse on some short patterns.

This report will introduce novel resist materials including specific photo acid generator (PAG) to improve flare issue from the resist standpoint. We have developed a method to control the acid diffusion length from the PAG. It previously reported that acid diffusion length can be altered by the PAG anion size. In this report, we focused on the effect of the Tg of a resist film. The thermal flow rate of a resist film can suggest the approximate resist Tg. Therefore, we measured the thermal flow rate of the resist. And we found out passivity of acid diffusion control by changing PAG species and volume. Moreover, newly designed PAG tested was confirmed to have uniform distribution in the resist film with no PAG clustering at the resist surface at compared to our conventional PAG. This new positive tone resist formulation shows good performance under flare condition. In addition, we focused on the pattern density variation as one of the key parameters for flare value. Low pattern density indicated less flare value. It is considered that negative tone resist to have advantage for isolated line type features. Novel positive and negative tone type resists were compared side-by-side and discussed for its advantages at varying pattern densities.

Introduction: Breast densities are the non-fat (epithelial and stromal) breast tissue observable on screening mammograms. Known to be associated with a 4 to 6 fold increase in breast cancer risk, dense breast patterns complicate the reading of screening mammograms resulting in lowered sensitivity. Little is currently known about the prevalence and/or predictors of breast density in Hispanic/Latino women living in the Northeast, US. Objective: The goal of this prospective study is to identify risk factors for high risk breast density patterns among a large cohort of Hispanic/Latino women with ancestral ties primarily to the Eastern Caribbean (Puerto Rico and the Dominican Republic) as well as Central and South America. Because the hormonal milieu is somewhat different in Hispanic/Latinas compared with White women, and likely also differs from that of Hispanic/Latinas living in other parts of the US, we explored the role of reproductive and physiological factors in high risk breast density patterns. Methods: We analyzed breast density predictors in an established cohort of 1,600 Hispanic/Latino women recruited from primary care clinics in 4 cities with the largest enclaves of Hispanic/Latinos in Connecticut. Hour-long telephone interviews provided baseline data on biological, medical care, and sociodemographic factors. We retrieved radiology records on 1570 (98.7%) consenting women. For this analysis, we report predictors of breast density among the 1,040 (65.4%) women who received at least one screening mammogram during 2 to 4 years of follow-up. Breast density classification was based on radiologist assigned BI-RADS classification. Associations between predictors and high risk breast density patterns were examined using chi square tests. Multivariate analyses were conducted using logistic regression; odds ratios (OR) and 95% confidence intervals (CI) are reported. Results: Of the 1,040 women who received at least one screening mammogram during the follow-up period, 280 (27%) women were identified as having high risk dense breasts (extremely or heterogeneously dense, i.e., greater than 50% of the breast composed of fibroglandular densities), while 760 women (73%) were classified as having nondense breasts (fatty or scattered fibroglandular densities), suggesting a lower prevalence of high risk breast density patterns in this population. In multivariate analysis, breast density predictors were similar to those reported for the general population (mostly White) women, and are similar to known risk factors for breast cancer. However, we found that Hispanic/Latinas with diabetes to be at significantly reduced odds of high risk breast density patterns. There was also evidence that the relationship between age at menarche and density was modified by BMI, with early age at menarche a risk factor among normal and underweight women only. Conclusion: Our findings suggest that Hispanic/Latino women may differ in breast density prevalence relative to the general population. However, we observed a protective effect of diabetes and a potential interaction between age at menarche and BMI. This investigation enhances our understanding of breast density in a subset of the Hispanic/Latino population and provides the basis for further research. Citation Format: Jones BA, Claye E, Philpotts L, Hooley R, Silber A, Epstein L. Risk Factors for high risk breast density patterns in Hispanic/Latinas living in the Northeast, US [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P2-13-02.

In lieu of performing laboratory testing, Eaton Corporation and Oak Ridge National Laboratories (ORNL) conducted an additional field test in March 2007 at ORNL facilities. The results of this test summarized in the report entitled 'DE-FC26-04NT42071, Final Technical Report' submitted to the Department of Energy on June 27, 2007.

EPMA: Efficient pattern matching algorithm for DNA sequences

Intrusion Detection System has become the important part of the computer and network security because it can effectively compensate for the lack of network security measures. However, the intrusion detection technology relies heavily on pattern matching algorithms, as the choice of pattern matching algorithms directly affect the detection rate, so it is more important. First the paper is detailed analysis the characteristics of the four kinds of single pattern matching which based on prefix search, and then it tests by the number of different pattern strings. The experimental results show that the KMP algorithm can improve effectively the speed of pattern matching. So the application of KMP algorithm can improve the efficiency of intrusion detection.

This study intended for the assessment of the stiffness, tensile and bursting properties of 3D printed auxetic sinusoidal patterns of different density and thickness deposited on the nylon fabric by means of fused deposition modeling (FDM) with the use of thermoplastic polyurethane (TPU) filament. Morphology, weight variation, flex stiffness, tensile property, Poisson’s ratio and bursting strength were analyzed for the characteristic evaluation of produced composite. The prototypes of two auxetic pattern repeat of 47 mm×43 mm and 20 mm×20 mm were developed named as low density (LD) and high density (HD) respectively. Both patterns were repeatedly combined to produce bigger size patterns and 3D printed with various thicknesses. Weight variation is found proportional to the density and thickness of 3D printed auxetic sinusoidal. Maximum up to 552 % weight increase was recorded for LD pattern and for HD 857 %. Flex stiffness increased with the rise of density and thickness of 3d printed auxetic sinusoidal pattern. Maximum flex stiffness for HD was 7.21 cm-g and for LD 4.73 cm-g. Warp direction is stiffest comparing with diagonal and weft in all cases. In case of tensile strength, a great extent of elongation was noticed due to the presence of auxetic sinusoidal 3D pattern and TPU filament. Maximum, more than 500 % elongation was showed by HD diagonal direction. HD patters exhibited more strength and toughness than LD patterns. In addition, warp direction is strongest and diagonal direction is weakest whereas the weft stays in between. Both LD-1.0 and HD-1.0 3D printed pattern showed negative Poisson’s ratio and the value was between -1.0 to 0. The enhanced bursting strength is found in HD patterns up to 1514 kPa comparing up to 1449 for LD. Thus, this study confirmed the excellent stiffness, tensile and bursting properties of HD 3D printed auxetic sinusoidal pattern/nylon composite over LD.

Pattern matching is essential to a wide range of applications such as network intrusion detection, virus scanning, etc. Pattern matching algorithms normally rely on state machines to detect predefined patterns. Recently, parallel pattern matching engines, based on ASICs, FPGAs or network processors, perform matching with multiple state machines. The state migration in the matching procedure incurs intensive memory accesses. Thus, it is critical to minimize the storage of state machines such that they can be fit in on-chip or other fast memory modules to achieve high-speed pattern matching. This paper proposes novel optimization techniques, namely state re-labeling and memory partition, to reduce state machine storage. The paper also presents architectural designs based on the optimization strategy. We evaluate our design using realistic pattern sets, and the results show state machine memory reduction up to 80.1%.

The need for efficient intrusion detection systems increases every day to protect network traffic against emerging attacks. Unfortunately, increasing network speeds and number of signatures makes it harder for the existing signature-based intrusion detection systems to keep up. This makes those systems the weak link and the bottleneck which decreases the overall network performance. Researchers found that 30%–60% of the overall processing time of signature-based intrusion detection systems is spent on pattern matching operations [1]. In this paper, we present a novel and fast software-based pattern matching algorithm to reduce the number of times to perform pattern matching. This new algorithm introduces an exclusion-inclusion filter programmed only with signatures prefixes. It filters out the clean traffic without requiring pattern matching and weeds out suspicious packets to be searched using a specially modified Wu-Manber pattern matching algorithm. The exclusion-inclusion filter is a modified Bloom filter that produces a list of probable matching signatures for each suspect packet. The remaining few suspicious packets are searched only for the probable matches. Compared to the Wu-Manber algorithm used in intrusion detection systems, the experimental results indicate a speed up of 3.4 times on average, 5.5 times for regular traffic, and 1.6 times for worst case traffic. The memory overhead added by the algorithm was limited to 0.11%.

Pattern matching with wildcards is very important in many fields such as information retrieval and bioinformatics. Suffix trees are used in pattern matching with variable length wildcards. But the construction of a suffix tree needs significant time and space overload. This paper presents a new pattern matching algorithm, PST, based on multiple suffix trees. The PST algorithm uses a cutting process to divide a string S into several parts firstly, and then establishes a suffix tree for each part of S respectively. If multiple patterns are to be retrieved, the suffix trees should be adjusted according to the cutting points: prefix sequence deletion and suffix sequence addition; prefix sequence addition and suffix sequence deletion. Theoretical analysis and experiments show that the PST algorithm can decrease the time and space overload than other peers.

Discontinuous and Pattern Matching algorithm to measure deformation having discontinuities

Journal Article A Digest and Pattern Matching-Based Intrusion Detection Engine Get access Zhongqiang Chen, Zhongqiang Chen * 1Yahoo! Inc., Santa Clara, CA 95054, USA *Corresponding author: zqchen@yahoo-inc.com Search for other works by this author on: Oxford Academic Google Scholar Yuan Zhang, Yuan Zhang 2Department of Mathematics, Florida State University, Tallahassee, FL 32306, USA Search for other works by this author on: Oxford Academic Google Scholar Zhongrong Chen, Zhongrong Chen 3ProMetrics Inc., King of Prussia, PA 19406, USA Search for other works by this author on: Oxford Academic Google Scholar Alex Delis Alex Delis 4Department of Informatics and Telecommunications, University of Athens, Athens, 15784, Greece Search for other works by this author on: Oxford Academic Google Scholar The Computer Journal, Volume 52, Issue 6, August 2009, Pages 699–723, https://doi.org/10.1093/comjnl/bxp026 Published: 15 April 2009 Article history Received: 05 October 2008 Revision received: 14 March 2009 Published: 15 April 2009

We develop the static and dynamic semantics of PiDuce, a process calculus with XML values, schemas, and pattern matching. PiDuce values include channel names, therefore the structure of values may not reveal anything about their schemas. This is problematic in the pattern matching algorithm because it requires to verify whether a schema of a channel is a subschema of a pattern. Such a verification has exponential cost, in general. In order to reduce the computational complexity of the pattern matching, channel schemas are constrained to occur in tail positions of sequences and to be labelled-determined.

We propose a document-searching architecture based on high-speed hardware pattern matching to increase the throughput of an information retrieval system. We also propose a new parallel VLSI pattern-matching algorithm called the Data Parallel Pattern Matching (DPPM) algorithm, which serially broadcasts and compares the pattern to a block of data in parallel. The DPPM algorithm utilizes the high degree of integration of VLSI technology to attain very high-speed processing through parallelism. Performance of the DPPM has been evaluated both analytically and by simulation. Based on the simulation statistics and timing analysis on the hardware design, a search rate of multiple gigabytes per second is achievable using 2-μm CMOS technology. The potential performance of the proposed document-searching architecture is also analyzed using the simulation statistics of the DPPM algorithm.

With the remarkable increase in the number of nucleotide and acid sequences, it is necessary to study pattern matching in querying sequence patterns in the biological sequence database. To further raise the performance of the pattern matching algorithm, an improved BM algorithm (called BMBR) is presented. It bases on the method of BM algorithm and combines with the shift function of BR algorithm, thus reaches the best shift distance and improves the performance. The best and worst cases in time complexities of the proposed algorithm are also discussed. The experimental results show that the algorithm is faster than other compared algorithms for small alphabets and long patterns, and thus the proposed algorithm is quite suitable for pattern matching in biological sequences.