Jiun-Lang Huang, Kun-Han Tsai, Yuping Liu et al. · 2013
Identifying speed-limiting paths is crucial for design stepping in which problematic paths are fixed or optimized so as to reach higher clock rates. Recently, using at-speed scan test patterns to identify speed-limiting paths has been reported to be a robust and effective solution. In this paper, we propose a systematic approach to find suspect path expressions (SPE) that explain the observed failing and passing bits during at-speed scan testing. These expressions contain comprehensive information, including (1) the pass/fail requirement on each involved path, and (2) the required AND/OR relationships among the involved paths. SPE's can be used to reduce the speed-limiting path suspect set or guide diagnostic pattern generation for further suspect reduction.
Cited by 0
Winston A. Haynes (389543), Roger Higdon (258190), Larissa Stanberry (389544) et al. · Figshare · 2015
<p>Maximally differentially expressed path identification by DEAP on the Notch signalling pathway. Pathway image is from PANTHER <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002967#pcbi.1002967-Thomas1" target="_blank">[11]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002967#pcbi.1002967-Huaiyu1" target="_blank">[46]</a>. The path shaded in purple was identified by DEAP as the most differentially expressed. Numerical values are log-expression ratios from the Interferon microarray study <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002967#pcbi.1002967-Khodarev1" target="_blank">[36]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002967#pcbi.1002967-Khodarev2" target="_blank">[37]</a>.</p>
Cited by 0Open access
Yajian Song, Fei Yan, Sheng Zheng · International Conference on Smart Transportation and City Engineering 2021 · 2021
As urban traffic congestion lengthens, the road network is likely to form a saturation cycle gradually. Solving the traffic congestion problem of the intersection group can effectively alleviate the overall congestion problem of the road network. The critical path is the entry point for the signal coordination controlling of the intersection group. In order to improve the existing critical path identification methods in which the number of intersections within a path is small and tend to fall into local critical path, this paper proposes a critical path identification method for intersection group considering path relevance. Firstly, the intersection group is abstracted as a road network undirected graph. Secondly, this paper improves the traditional ant colony algorithm including the state transfer probability criterion and the pheromone update mechanism. Finally, a case study is conducted for a local road network intersection group in the main urban area of Yiwu City. The result presents that the method proposed in this paper is significantly better than the breadth-first search algorithm in terms of the total number of paths identified and relevance degree values of critical paths. This method increases the convergence speed and can identify the global critical paths accurately.
Cited by 3
Norma L. Weinberg, Junebug Clark · The Journal of the Acoustical Society of America · 1980
For two long-range paths in the Atlantic, extensive data sets are available both for fixed source to fixed receiver multipath structures, and for sound velocity profiles along the paths. The sound velocity data have been used in range-dependent ray computations in an attempt to identify the observed multipaths. Data and computations are presented, along with the results of a special study of the sensitivity of computed multipath structure to range dependence in measured profiles.
Cited by 0
James F. Unruh, Paul D. Till, Ted J. Farwell · SAE technical papers on CD-ROM/SAE technical paper series · 2000
<div class="section abstract"><div class="htmlview paragraph">Excessive interior noise and vibration in propeller driven general aviation aircraft can result in poor pilot communications with ground control personnel and passengers, and, during extended flights, can lead to pilot and passenger fatigue. Noise source/path identification technology applicable to single engine propeller driven aircraft were employed to identify interior noise sources originating from structure-borne engine/propeller vibration, airborne propeller transmission, airborne engine exhaust noise, and engine case radiation. The approach taken was first to conduct a Principal Value Analysis (PVA) of an in-flight noise and vibration database acquired on a single engine aircraft to obtain a correlated data set as viewed by a fixed set of cabin microphones. A Conditioned Response Analysis (CRA), combining ground test noise source simulation frequency response function data with the in-flight PVA vectors, was then carried out to identify the relative contributions of each of the simulated sources to the cabin noise levels as measured by the fixed set of cabin microphones. Results of the analysis showed the aircraft interior noise to be generated from several airborne sources, including the propeller, exhaust, and engine case radiation. Structure-borne engine/propeller vibration was not found to be a significant contributor to interior noise. The major paths of noise propagation were identified to be the aircraft windshield and firewall.</div></div>
Cited by 3
Yuan Feng, Qiang Xu · 2010
This paper is concerned with finding timing-independent false paths that cannot be sensitized under any signal arrival time condition in integrated circuits. Existing techniques regard a path as a true path as long as a vector pair can be found to sensitize it. This is rather pessimistic since such a path might be activated only with illegal states in the circuit and hence it is actually functionally-unsensitizable. In this paper, we develop novel techniques to take the above issue into consideration when identifying false paths, which facilitates us to find much more false paths than conventional techniques. Experimental results on benchmark circuits demonstrate the effectiveness of the proposed methodology.
Cited by 3
Jing Zeng, Magdy S. Abadir, J. Bhadra et al. · 2002
Static timing analysis sets the industry standard in the design methodology to gage the speed of high performance microprocessors. Unfortunately, not all the paths identified using such analysis can be sensitized. This leads to a pessimistic estimation of processor speed, and the engineering efforts spent optimizing such paths can not improve the performance of the chip. In the past, we demonstrated initial results of how ATPG technique can be used to eliminate false paths efficiently. Due to the gap between the physical design on which the static timing analysis of the chip is based and the test view on which the ATPG technique is applied to eliminate false paths, in many cases only sections of some of the paths in the full-chip were analyzed in our initial results. In this paper, we fully analyze all the timing paths using the ATPG technique overcoming the gap between the testing and timing analysis techniques. We applied our method on the second G4 PowerPC/sup TM/.
Cited by 1
K. Arun, R. Rejimoan · Lecture notes in networks and systems · 2017
Cited by 1
Nina Fei, Youlong Yang · Wuhan University Journal of Natural Sciences · 2019
Finding causality merely from observed data is a fundamental problem in science. The most basic form of this causal problem is to determine whether X leads to Y or Y leads to X in the case of joint observation of two variables X, Y. In statistics, path analysis is used to describe the direct dependence between a set of variables. But in fact, we usually do not know the causal order between variables. However, ignoring the direction of the causal path will prevent researchers from analyzing or using causal models. In this study, we propose a method for estimating causality based on observed data. First, observed variables are cleaned and valid variables are retained. Then, a direct linear non-Gaussian acyclic graph models (DirectLiNGAM) estimates the causal order K between variables. The third step is to estimate the adjacency matrix B of the causal relationship based on K. Next, since B is not convenient for model interpretation, we use adaptive lasso to prune the causal path and variables. Further, a causal path graph and a recursive model are established. Finally, we test and debug the recursive model, obtain a causal model with good fit, and estimate the direct, indirect and total effects between causal variables. This paper overcomes the randomness assigning causal order to variables. This study is different from the researcher’s understanding of his own model by generating some form of simulation data. The simplest and relatively unsmooth statistical learning method used in this study has obvious advantages in the field of interpretable machine learning.
Cited by 3
G.P. Eatwell, C.M. Dorling · 1990
The first step in seeking solutions to radiated noise problems is to look at the source of the noise. If this cannot be altered or controlled, the next step is to look at the transmission paths by which the noise reaches the region where a reduction in sound level is required. In some applications it may be enough to reduce the noise transmission along the most important path. However, since all the paths are excited by a common source, the contributions from the different paths interfere coherently in the region where reduction is required. Noise components transmitted via separate paths may cancel each other, in which case reducing the transmission along one path will increase the overall noise rather than reducing it. To design active and passive systems to reduce noise, it is essential to know both the magnitude of the transmission along each path and the way in which the different paths interfere.
Cited by 0
Ateeq-Ur-Rehman Shaheen, Fawnizu Azmadi Hussin, Nor Hisham Hamid · 2016
In order to achieve the less test generation complexity, design-for-testability (DFT) techniques are used which causes untestable paths to be testable. These testable path delays have no effect on circuit performance are called false paths. It has been contended that such false paths should not be detected for test generation to keep off the unnecessary decrease in production. This paper proposes an algorithm framework to deal with these false paths through identification for DFT test. Proposed framework uses an integrated functional RTL circuit, called assignment decision diagram (ADD) which target at structural-level. Identification is done by sensitizing, observability and propagation rules for unified functional RTL circuits. Proposed framework overcomes the limitation of several existing RTL based approaches, such as the need for explicit separation between controller and data path. The effectiveness of the framework algorithm is shown through lemma proof.
Cited by 1
Kyriakos Christou, Maria K. Michael, Stelios Neophytou · 2010
It has been previously shown that in order to guarantee the temporal correctness of a circuit, only the primitive path delay fault set needs to be tested. However, as in the case of the traditional and simpler path delay fault model, the number of possible faults can be exponential to the circuit size and, therefore, it is only practical to consider the set of critical faults. This work defines critical primitive path delay faults and presents an exact algorithm to identify them, using zero-suppressed binary decision diagrams and newly introduced operators necessary for handling multiple path delay faults. We report the number of critical primitive path delay faults for various criticality thresholds under the bounded delay model. The results indicate that only a small, but still necessary, number of multiple (primitive) faults, which escape testing under the singly testable fault criterion, must be considered in order to guarantee the timing correctness of the circuit.
Cited by 13
Haysam Selim, Justin Zhan · Journal Of Big Data · 2016
The use of Big Data in today’s world has become a necessity due to the massive number of technologies developed recently that keeps on providing us with data such as sensors, surveillance system and even smart phones and smart wearable devices they all tend to produce a lot of information that need to be analyzed and studied in details to provide us with some insight to what these data represent. In this paper we focus on the application of the techniques of data reduction based on data nodes in large networks datasets by computing data similarity computation, maximum similarity clique (MSC) and then finding the shortest path in a quick manner due to the data reduction in the graph. As the number of vertices and edges tend to increase on large networks the aim of this article is to make the reduction of the network that will cause an impact on calculating the shortest path for a faster analysis in a shortest time.
Cited by 31Open access
Mohamed Abuella, M. Amine Atoui, Sławomir Nowaczyk et al. · IEEE Access · 2024
This paper addresses the challenge of identifying the paths for vessels with operating routes of repetitive paths, partially repetitive paths, and new paths. We propose a spatial clustering approach for labeling the vessel paths by using only position information. We develop a path clustering framework employing two methods: a distance-based path modeling and a likelihood estimation method. The former enhances the accuracy of path clustering through the integration of unsupervised machine learning techniques, while the latter focuses on likelihood-based path modeling and introduces segmentation for a more detailed analysis. The result findings highlight the superior performance and efficiency of the developed approach, as both methods for clustering vessel paths into five clusters achieve a perfect F1-score. The approach aims to offer valuable insights for route planning, ultimately contributing to improving safety and efficiency in maritime transportation.
Cited by 5Open access
Shreyas Vijay Parnerkar · Minds at UW (University of Wisconsin) · 2010
A Project Report submitted to the University of Wisconsin -- Department of Electrical and Computer Engineering in partial fulfillment of the requirements for the degree of Master of Science Graduate Program in Electrical and Computer Engineering.
Cited by 0Open access
Zhen Li, Ping Deng, Rui Luo et al. · 2023
Aiming at the problem of mobile localization in nonline-of-sight (NLOS) environments, in this paper a new mobile location method based on scattering path identification is proposed. First of all, an improved single scattering path identification algorithm which is used to identify whether two scattering paths is from the same scatterer based on line-of-possible-mobile-device (LPMD) line is proposed, then the scattering paths from the same scatterer at different BSs are grouped and the scatterer is located by these paths and BSs, at last, the located scatterers are utilized as virtual base stations to take part in the localization of mobile. Simulation results show that the proposed method can effectively improve the localization accuracy of mobile station, which is close to the accuracy acquired in line-of-sight (LOS) environments.
Cited by 4
Wen Ching Wu, Chung Len Lee, J.E. Chen · 2002
This paper presents a theoretical analysis to identify robust untestable path delay faults. It first classifies the path reconvergence of fanouts into seven cases and deduces the necessary conditions to robustly test path delay faults for each case. It then proposes a procedure, based on the deduced conditions, to identify the robust untestable path delay faults. The procedure was applied to ISCAS 85' circuits and it was found that the robust untestable faults occupy a high percentage of the total path delay faults. In addition, it also presents a method to estimate the number of robust untestable path delay faults for a circuit.
Cited by 1
Elisabete Ferreira, J. Pinho-da-Cruz, A. Andrade‐Campos · HAL (Le Centre pour la Communication Scientifique Directe) · 2013
International audience
Cited by 0Open access
SHAHIDI, SEYED HOUTAN · OSF Preprints (OSF Preprints) · 2022
The authors aimes to review all longitudinal studies in children and adolescents on the association between physical performance factors or progression of such performance on success as future elite athletes.
Cited by 0Open access
Yuanyuan Zhang, Cunli Song, Xuesong Zhang · Journal of Computer-Aided Design & Computer Graphics · 2025
In order to solve the problem of insufficient attention to non-salient distinguishable features and insufficient expression of extracted key features of pedestrians in current Re-ID methods, a feature extraction network based on a dual-path attention mechanism is proposed (Dual-Path Attention Network), which consists of a dual-path attention backbone network. It is composed of an enhanced attention feature fusion module. Among them, the dual-path attention network allows the model to focus on effective feature areas with different salience levels, which can be used to mine significant and potentially non-salient distinguishable features respectively, emphasizing the importance of potential key features.The enhanced attention feature fusion module is used to complete feature information complementation, and counterfactual intervention is used to enhance the quality and effectiveness of the learned attention feature map, so as to make the final feature representation more discriminative. Extensive experiments were conducted on Market1501, DukeMTMC-reID and MSMT17 data sets, and the results showed that the mAP values reached 89.3%, 80.0%, 58.4% respectively; the Rank-1 values reached 95.7%, 89.8%, 80.7% respectively, which fully proved the superiority of this method.
Cited by 0Open access