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Добірка наукової літератури з теми "Multiple interval graphs"

Автор: Grafiati

Опубліковано: 21 грудня 2024

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Статті в журналах з теми "Multiple interval graphs"

Butman, Ayelet, Danny Hermelin, Moshe Lewenstein, and Dror Rawitz. "Optimization problems in multiple-interval graphs." ACM Transactions on Algorithms 6, no. 2 (March 2010): 1–18. http://dx.doi.org/10.1145/1721837.1721856.

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Ardévol Martínez, Virginia, Romeo Rizzi, Florian Sikora, and Stéphane Vialette. "Recognizing unit multiple interval graphs is hard." Discrete Applied Mathematics 360 (January 2025): 258–74. http://dx.doi.org/10.1016/j.dam.2024.09.011.

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Gyárfás, A. "On the chromatic number of multiple interval graphs and overlap graphs." Discrete Mathematics 55, no. 2 (July 1985): 161–66. http://dx.doi.org/10.1016/0012-365x(85)90044-5.

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Francis, Mathew C., Daniel Gonçalves, and Pascal Ochem. "The Maximum Clique Problem in Multiple Interval Graphs." Algorithmica 71, no. 4 (September 11, 2013): 812–36. http://dx.doi.org/10.1007/s00453-013-9828-6.

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Khabyah, Ali Al, Haseeb Ahmad, Ali Ahmad, and Ali N. A. Koam. "A uniform interval-valued intuitionistic fuzzy environment: topological descriptors and their application in neural networks." AIMS Mathematics 9, no. 10 (2024): 28792–812. http://dx.doi.org/10.3934/math.20241397.

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<p>The concept of being uniform strong interval-valued intuitionistic fuzzy (also termed as USIVIF) is an integration of two ideologies, which are called "uniformity" and "strong interval-valued intuitionistic fuzzy sets". Inspired by the study on uniform fuzzy topological indices, it is natural to introduce uniform IVIFTIs. Originally, topological indices were generalized for the fuzzy sets However, the utilization of the interval-valued intuitionistic fuzzy topological indices provides a finer approach, especially if there are multiple uncertainties based on intervals. Consequently, both theories imply that topological indices are not fixed and depend on certain situations or problems in the question. In this article, the generalized results for the uniform degree of the fuzzy sets associated with individual vertices/edges of strong interval-valued intuitionistic fuzzy graphs were presented and results for the total uniform degree of such graphs were also included. In addition, the nature of the implemented methods and models was discussed based on the cellular neural interval-valued intuitionistic fuzzy graphs of sets of membership and non-membership values.</p>

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Jiang, Minghui, and Yong Zhang. "Parameterized complexity in multiple-interval graphs: Domination, partition, separation, irredundancy." Theoretical Computer Science 461 (November 2012): 27–44. http://dx.doi.org/10.1016/j.tcs.2012.01.025.

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Bartlett, Sara M., John T. Rapp, and Marissa L. Henrickson. "Detecting False Positives in Multielement Designs." Behavior Modification 35, no. 6 (August 26, 2011): 531–52. http://dx.doi.org/10.1177/0145445511415396.

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The authors assessed the extent to which multielement designs produced false positives using continuous duration recording (CDR) and interval recording with 10-s and 1-min interval sizes. Specifically, they created 6,000 graphs with multielement designs that varied in the number of data paths, and the number of data points per data path, using a random number generator. In Experiment 1, the authors visually analyzed the graphs for the occurrence of false positives. Results indicated that graphs depicting only two sessions for each condition (e.g., a control condition plotted with multiple test conditions) produced the highest percentage of false positives for CDR and interval recording with 10-s and 1-min intervals. Conversely, graphs with four or five sessions for each condition produced the lowest percentage of false positives for each method. In Experiment 2, they applied two new rules, which were intended to decrease false positives, to each graph that depicted a false positive in Experiment 1. Results showed that application of new rules decreased false positives to less than 5% for all of the graphs except for those with two data paths and two data points per data path. Implications for brief assessments are discussed.

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Jiang, Minghui. "On the parameterized complexity of some optimization problems related to multiple-interval graphs." Theoretical Computer Science 411, no. 49 (November 2010): 4253–62. http://dx.doi.org/10.1016/j.tcs.2010.09.001.

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Li, Gen, Tri-Hai Nguyen, and Jason J. Jung. "Traffic Incident Detection Based on Dynamic Graph Embedding in Vehicular Edge Computing." Applied Sciences 11, no. 13 (June 24, 2021): 5861. http://dx.doi.org/10.3390/app11135861.

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With a large of time series dataset from the Internet of Things in Ambient Intelligence-enabled smart environments, many supervised learning-based anomaly detection methods have been investigated but ignored the correlation among the time series. To address this issue, we present a new idea for anomaly detection based on dynamic graph embedding, in which the dynamic graph comprises the multiple time series and their correlation in each time interval. We propose an entropy for measuring a graph’s information injunction with a correlation matrix to define similarity between graphs. A dynamic graph embedding model based on the graph similarity is proposed to cluster the graphs for anomaly detection. We implement the proposed model in vehicular edge computing for traffic incident detection. The experiments are carried out using traffic data produced by the Simulation of Urban Mobility framework. The experimental findings reveal that the proposed method achieves better results than the baselines by 14.5% and 18.1% on average with respect to F1-score and accuracy, respectively.

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Cardoza, Jacqueline E., Carina J. Gronlund, Justin Schott, Todd Ziegler, Brian Stone, and Marie S. O’Neill. "Heat-Related Illness Is Associated with Lack of Air Conditioning and Pre-Existing Health Problems in Detroit, Michigan, USA: A Community-Based Participatory Co-Analysis of Survey Data." International Journal of Environmental Research and Public Health 17, no. 16 (August 7, 2020): 5704. http://dx.doi.org/10.3390/ijerph17165704.

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The objective of the study was to investigate, using academic-community epidemiologic co-analysis, the odds of reported heat-related illness for people with (1) central air conditioning (AC) or window unit AC versus no AC, and (2) fair/poor vs. good/excellent reported health. From 2016 to 2017, 101 Detroit residents were surveyed once regarding extreme heat, housing and neighborhood features, and heat-related illness in the prior 5 years. Academic partners selected initial confounders and, after instruction on directed acyclic graphs, community partners proposed alternate directed acyclic graphs with additional confounders. Heat-related illness was regressed on AC type or health and co-selected confounders. The study found that heat-related illness was associated with no-AC (n = 96, odds ratio (OR) = 4.66, 95% confidence interval (CI) = 1.22, 17.72); living ≤5 years in present home (n = 57, OR = 10.39, 95% CI = 1.13, 95.88); and fair/poor vs. good/excellent health (n = 97, OR = 3.15, 95% CI = 1.33, 7.48). Co-analysis suggested multiple built-environment confounders. We conclude that Detroit residents with poorer health and no AC are at greater risk during extreme heat. Academic-community co-analysis using directed acyclic graphs enhances research on community-specific social and health vulnerabilities by identifying key confounders and future research directions for rigorous and impactful research.

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Дисертації з теми "Multiple interval graphs"

Ardevol, martinez Virginia. "Structural and algorithmic aspects of (multiple) interval graphs." Electronic Thesis or Diss., Université Paris sciences et lettres, 2024. http://www.theses.fr/2024UPSLD028.

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Les graphes d’intervalles multiples sont une généralisation bien connue des graphes d’intervalles, où chaque sommet d’un graphe est représenté par un d-intervalle (l’union de d intervalles) pour un certain nombre naturel d > 1, et il existe une arête entre deux sommets si et seulement si leurs d-intervalles correspondants se croisent. En particulier, un graphe de d-intervalles est unitaire si tous les intervalles de la représentation ont une longueur unitaire. Dans cette thèse, nous étudions les graphes de d-intervalles unitaires d’un point de vue structurel et algorithmique. Dans la première partie, nous essayons de généraliser la caractérisation de Roberts des graphes d’intervalles unitaires, qui affirme qu’un graphe est un graphe d’intervalles unitaire si et seulement s’il est un graphe d’intervalles et ne contient pas le graphe biparti complet K1,3 comme sous-graphe induit. Ensuite, nous passons à l’étude de la complexité de la reconnaissance des graphes d’intervalles multiples unitaires. Nous prouvons que, étant donné un graphe G, il est NP-difficile de déterminer si G est un graphe de d-intervalles unitaires, et nous étendons ensuite ce résultat de difficulté à d’autres sous-classes de graphes de d-intervalles unitaires. Dans la dernière partie de ce manuscrit, nous nous concentrons sur le problème de PIG-completion, qui étant donné un graphe d’intervalles G, demande de trouver le nombre minimum d’arêtes à ajouter à G pour qu’il devienne un graphe d’intervalles unitaire. Nous obtenons un algorithme polynomial lorsque G contient un sommet adjacent à tous les autres sommets du graphe, et un algorithme XP paramétré par une propriété structurelle du graphe
Multiple interval graphs are a well-known generalization of interval graphs, where each vertex of a graph is represented by a d-interval (the union of d intervals) for some natural number d > 1, and there exists an edge between two vertices if and only if their corresponding d-intervals intersect. In particular, a d-interval graph is unit if all the intervals on the representation have unit length. In this thesis, we study unit d-interval graphs from a structural and an algorithmic perspective. In the first part, we tryto generalize Roberts characterization of unit interval graphs, which states that a graph is unit interval if and only if it is interval and it does not contain the complete bipartite graph K1,3 as an induced subgraph. Then, we move on to studythe complexity of recognizing unit multiple interval graphs. We prove that given a graph G it is NP-hard to determine whether G is a unit d-interval graph, and then extend this hardness result to other subclasses of unit d-interval graphs. Inthe last part of this manuscript, we focus on the PIG-completion problem, where given an interval graph G, we are asked to find the minimum number of edges that we need to add to G so that it becomes a proper interval graph. We obtain apolynomial algorithm when G contains a vertex that is adjacent to every other vertex of the graph, and an XP algorithm parameterized by a structural property of the graph

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Книги з теми "Multiple interval graphs"

United States. Government Accountability Office. Homeland security: Opportunities exist to enhance collaboration at 24/7 operations centers staffed by multiple DHS agencies : report to congressional requesters. Washington, D.C: U.S. States Government Accountability Office, 2006.

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Nguyen, Kim-Phuong, and Chris D. Glover. Obesity. Edited by Erin S. Williams, Olutoyin A. Olutoye, Catherine P. Seipel, and Titilopemi A. O. Aina. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190678333.003.0043.

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Childhood obesity has become a major public health concern. Obesity affects perioperative anesthetic management from airway management and drug selection to postoperative monitoring requirements. This chapter explains the perioperative implications of childhood obesity and addresses multiple considerations in the formulation of an anesthetic plan for the obese child. The chapter examines the anesthetic implications of obesity and its effects on various body systems, discusses the principles of perioperative management of obese children, and grants a working knowledge of pharmacokinetics of common anesthetic drugs in obese children and dosage implications. A case study of an obese 13-year-old boy with late-onset Blount disease who presents for proximal tibial osteotomy with internal fixation is presented to illustrate the concepts in the chapter.

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Частини книг з теми "Multiple interval graphs"

Jiang, Minghui, and Yong Zhang. "Parameterized Complexity in Multiple-Interval Graphs: Domination." In Parameterized and Exact Computation, 27–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28050-4_3.

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Jiang, Minghui, and Yong Zhang. "Parameterized Complexity in Multiple-Interval Graphs: Partition, Separation, Irredundancy." In Lecture Notes in Computer Science, 62–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22685-4_6.

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Francis, Mathew C., Daniel Gonçalves, and Pascal Ochem. "The Maximum Clique Problem in Multiple Interval Graphs (Extended Abstract)." In Graph-Theoretic Concepts in Computer Science, 57–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34611-8_9.

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Jiang, Minghui. "On the Parameterized Complexity of Some Optimization Problems Related to Multiple-Interval Graphs." In Combinatorial Pattern Matching, 125–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13509-5_12.

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Zheng, Yan, Bin Xu, Jingyu Liu, Yating Shen, Kongkea Phan, and Benjamin C. Bostick. "Arsenic in Hydro-geo-biospheres of the Mekong River Watershed: Implications for Human Health." In Water Resources in the Lancang-Mekong River Basin: Impact of Climate Change and Human Interventions, 121–202. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-0759-1_4.

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AbstractThis chapter assesses human health risks of inorganic arsenic (As) from drinking well water and consumption of rice irrigated by high-As groundwater in the Mekong River Delta. Geogenic inorganic As (iAs) occurring at elevated levels in groundwater has been detected in more than 70 countries. Among mostly rural residents relying on groundwater for drinking, this exposure has resulted in negative health consequences including visible skin lesions, multiple internal organ cancers, numerous invisible non-cancer health effects such as cardiovascular diseases, and premature deaths. In the Mekong River Delta (MRD, defined by elevation <10 m above sea level in this book), As issues in groundwater have been documented as early as 1999 in Cambodia, with literature reporting its occurrence in Vietnam since 2005. Since the early 2000s, efforts have been made to test for As in about 100,000 wells from Cambodia, Laos, Vietnam and Thailand. Here, a combined dataset with a total of 94,768 unique As tests was analyzed to illustrate the spatial patterns and to assess the health risks of drinking well water As in Cambodia and in southern Vietnam. Although knowledge is far more limited, an attempt was also made to examine the potential health risks associated with iAs exposure from rice, a major staple for the MRD. Here, irrigation using highly As enriched groundwater for rice cultivation has expanded this environmental health problem from the hydrosphere (water) to the geosphere (soil) and, in turn, the biosphere (rice, and ultimately humans). Of 41,928 tests in Cambodia, 35.8% exceeded 10 μg/L, the WHO guideline value for drinking water As, while 21.5% exceeded 50 μg/L, the Cambodian drinking water standard. Of 52,858 tests in Vietnam, the exceedance rate for 10 μg/L, which is also the Vietnamese drinking water standard, is 10.0%. High As wells, regardless of whether it is relative to 10 or 50 μg/L, are located in proximity to the main course of the Mekong-Bassac Rivers, especially within a 5 km distance. The vast majority (>98%) of high-As wells are located in low-lying areas, i.e. <25 m elevation in Cambodia and <10 m elevation in Vietnam. High-As wells occur frequently at shallow depths (<70 m) across the MRD but also at deeper depths (300–500 m) in Vietnam. Due to the clustering of high As wells along the Mekong-Bassac Rivers, extreme human health tolls are identified in 11 districts of Cambodia and 3 districts of Vietnam with a population attributable fraction exceeding 0.1, meaning that >1 in every 10 adult deaths is solely due to drinking water As exposure. The annual excess deaths attributable to arsenic exposure alone is 1204 in Cambodia and 1486 in Vietnam, or 1 in every 27 adult deaths and 1 in every 78 adult deaths, respectively. In addition to uncertainties in bioavailability and toxicity of iAs in rice grains, soil and rice As data, especially rice As speciation data needed for risk assessment, are still limited in the MRD.

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Tatoulis, James, and Brian F. Buxton. "Composite grafts." In State of the Art Surgical Coronary Revascularization, edited by Joseph F. Sabik, Stuart J. Head, and Vipin Zamvar, 327–32. Oxford University Press, 2021. http://dx.doi.org/10.1093/med/9780198758785.003.0056.

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Composite grafts should be within the repertoire of every coronary surgeon. Validated in the early 1990s, they are used to accomplish multiple or total arterial revascularization, which achieves the best coronary revascularization results, either with two internal thoracic arteries or by a combination of an internal thoracic artery and a radial artery.

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F. àWengen, Daniel. "Internal and External Nasal Valve Widening and Stabilization by Titanium Breathe-Implant." In New Advances in Rhinoplasty [Working Title]. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.108984.

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Nasal airway obstruction is a very common reason for reduced quality of life. For decades, nose surgeons have applied multiple techniques with little or partial success. Since 2003, the Titanium Breathe-Implant widens and stabilizes the internal nasal valve with a long-term success rate of 90% approval by the patients. Since 2017, the Titanium Batten Grafts widen and stabilize the external nasal valves. Combination of these grafts is possible. Quality of life improves, snoring is reduced, and acceptance of possible CPAP masks are proofs of the patient’s widened nasal airway. Surgical techniques of open and closed rhinoplasty techniques are presented.

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Bolboacă, Sorana D., and Lorentz Jäntschi. "Characteristic Polynomial in Assessment of Carbon-Nano Structures." In Sustainable Nanosystems Development, Properties, and Applications, 122–47. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-0492-4.ch004.

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Six dodecahedrane assemblies as multiple of five and respectively six structures were constructed and investigated from the topological point of view. The investigation was conducted using characteristic polynomials, graph invariant encoding important properties of the graph of the chemical structure. The assemblies of 5, 6, 15 and 25 dodecahedranes proved to have the center in the same plane while the assemblies of 12 and 24 dodecahedranes degenerated from the planar central form to a chair conformation. Generally, the number of real roots of characteristic polynomials is equal to the number of atoms in the assembly. The obtained roots of the characteristic polynomial were split into intervals and the frequency apparition spectra were simulated. The obtained spectra were used to investigate the behavior of investigated assembly.

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Falk, Volkmar, and Sebastian Holinski. "Minimally invasive direct coronary artery bypass." In State of the Art Surgical Coronary Revascularization, edited by Joseph F. Sabik, Stuart J. Head, and Vipin Zamvar, 349–52. Oxford University Press, 2021. http://dx.doi.org/10.1093/med/9780198758785.003.0060.

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There are different minimal invasive approaches of coronary bypass surgery. Avoiding sternotomy and gaining access to the heart via an alternative route is one strategy. Another is to avoid cardiopulmonary bypass. Combining these two measures defines the classical minimally invasive direct coronary artery bypass (MIDCAB) procedure. While multiple grafts can be placed through a limited mini-thoracotomy on the beating heart, the classic MIDCAB procedure is usually limited to grafting of the left internal thoracic artery to the left anterior descending artery.

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Wong, Andrew K. C., Yang Wang, and Gary C. L. Li. "Pattern Discovery as Event Association." In Machine Learning, 1924–32. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-60960-818-7.ch804.

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A basic task of machine learning and data mining is to automatically uncover <b>patterns</b> that reflect regularities in a data set. When dealing with a large database, especially when domain knowledge is not available or very weak, this can be a challenging task. The purpose of <b>pattern discovery</b> is to find non-random relations among events from data sets. For example, the “exclusive OR” (XOR) problem concerns 3 binary variables, A, B and C=A<img src="http://resources.igi-global.com/Marketing/Preface_Figures/x_symbol.png">B, i.e. C is true when either A or B, but not both, is true. Suppose not knowing that it is the XOR problem, we would like to check whether or not the occurrence of the compound event [A=T, B=T, C=F] is just a random happening. If we could estimate its frequency of occurrences under the random assumption, then we know that it is not random if the observed frequency deviates significantly from that assumption. We refer to such a compound event as an event association pattern, or simply a <b>pattern</b>, if its frequency of occurrences significantly deviates from the default random assumption in the statistical sense. For instance, suppose that an XOR database contains 1000 samples and each primary event (e.g. [A=T]) occurs 500 times. The expected frequency of occurrences of the compound event [A=T, B=T, C=F] under the independence assumption is 0.5×0.5×0.5×1000 = 125. Suppose that its observed frequency is 250, we would like to see whether or not the difference between the observed and expected frequencies (i.e. 250 – 125) is significant enough to indicate that the compound event is not a random happening.<div><br></div><div>In statistics, to test the correlation between random variables, <b>contingency table</b> with chi-squared statistic (Mills, 1955) is widely used. Instead of investigating variable correlations, pattern discovery shifts the traditional correlation analysis in statistics at the variable level to association analysis at the event level, offering an effective method to detect statistical association among events.</div><div><br></div><div>In the early 90’s, this approach was established for second order event associations (Chan & Wong, 1990). A higher order <b>pattern discovery</b> algorithm was devised in the mid 90’s for discrete-valued data sets (Wong & Yang, 1997). In our methods, patterns inherent in data are defined as statistically significant associations of two or more primary events of different attributes if they pass a statistical test for deviation significance based on <b>residual analysis</b>. The discovered high order patterns can then be used for classification (Wang & Wong, 2003). With continuous data, events are defined as Borel sets and the pattern discovery process is formulated as an optimization problem which recursively partitions the sample space for the best set of significant events (patterns) in the form of high dimension intervals from which probability density can be estimated by Gaussian kernel fit (Chau & Wong, 1999). Classification can then be achieved using Bayesian classifiers. For data with a mixture of discrete and continuous data (Wong & Yang, 2003), the latter is categorized based on a global optimization discretization algorithm (Liu, Wong & Yang, 2004). As demonstrated in numerous real-world and commercial applications (Yang, 2002), pattern discovery is an ideal tool to uncover subtle and useful patterns in a database. </div><div><br></div><div>In pattern discovery, three open problems are addressed. The first concerns learning where noise and uncertainty are present. In our method, noise is taken as inconsistent samples against statistically significant patterns. Missing attribute values are also considered as noise. Using a standard statistical <b>hypothesis testing</b> to confirm statistical patterns from the candidates, this method is a less ad hoc approach to discover patterns than most of its contemporaries. The second problem concerns the detection of polythetic patterns without relying on exhaustive search. Efficient systems for detecting monothetic patterns between two attributes exist (e.g. Chan & Wong, 1990). However, for detecting polythetic patterns, an exhaustive search is required (Han, 2001). In many problem domains, polythetic assessments of feature combinations (or higher order relationship detection) are imperative for robust learning. Our method resolves this problem by directly constructing polythetic concepts while screening out non-informative pattern candidates, using statisticsbased heuristics in the discovery process. The third problem concerns the representation of the detected patterns. Traditionally, if-then rules and graphs, including networks and trees, are the most popular ones. However, they have shortcomings when dealing with multilevel and multiple order patterns due to the non-exhaustive and unpredictable hierarchical nature of the inherent patterns. We adopt <b>attributed hypergraph</b> (AHG) (Wang & Wong, 1996) as the representation of the detected patterns. It is a data structure general enough to encode information at many levels of abstraction, yet simple enough to quantify the information content of its organized structure. It is able to encode both the qualitative and the quantitative characteristics and relations inherent in the data set.<br></div>

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Тези доповідей конференцій з теми "Multiple interval graphs"

Yanushkevich, Z., A. Mogucheva, M. Tikhonova, A. Belyakov, and R. Kaibyshev. "Mechanical Properties and Microstructures of an S304H-Type Steel Subjected to Hot Working." In AM-EPRI 2010, edited by D. Gandy, J. Shingledecker, and R. Viswanathan, 986–94. ASM International, 2010. http://dx.doi.org/10.31399/asm.cp.am-epri-2010p0986.

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Abstract The effect of multiple hot rolling in the temperature interval of 700-1000°C (1290-1830°F) on microstructures and tensile behavior of an S304H-type austenitic stainless steel was studied. The structural changes during hot working are characterized by the elongation of original grains towards the rolling axis and the development of new fine grains. The fraction of fine grains and the average grain size increase with increasing the rolling temperature. The multiple hot rolling results in significant strengthening. The offset yield strength approaches 1080 MPa in the sample processed at 700°C (1290°F), while that of 390 MPa is obtained after rolling at 1000°C (1830°F). On the other hand, the tensile strength at elevated temperatures of 600-700°C (1110-1290°F) decreases with a decrease in the rolling temperature. The relationship between the deformation structures and the tensile behavior is considered in some detail.

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Mousas, Christos, and Paul Newbury. "Real-time motion editing for reaching tasks using multiple internal graphs." In 2012 17th International Conference on Computer Games: AI, Animation, Mobile, Interactive Multimedia, Educational & Serious Games (CGAMES). IEEE, 2012. http://dx.doi.org/10.1109/cgames.2012.6314551.

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Ganter, M. A., and P. A. Skoglund. "Feature Extraction for Casting Core Development." In ASME 1991 Design Technical Conferences. American Society of Mechanical Engineers, 1991. http://dx.doi.org/10.1115/detc1991-0074.

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Abstract Feature extraction techniques are presented for the generation of casting core patterns from a boundary representation (B-Rep) solid model. Techniques are presented which would allow for automatic extraction of three classes of core features (internal voids, single and multi-surface holes, and boundary perturbations). The task of extracting casting cores from solid models involves recognizing a collection of entities (i.e. slots, bosses, undercut surfaces, local and global concavities, etc.) from the set of lower level entities (i.e. the B-Rep structure). To this end, a combination of solid modeling B-Rep and graph structures and their associated methods will be used for casting core development. Appropriate local features are identified and extracted from the original object, and are grouped into one or more new object(s) (termed a core-object). If the core-object is multiply connected (i.e. composed of multiple objects), it is graph separated into global feature objects. Each of these global feature objects represents a core in the final pattern. Lastly, the geometry of the original part is augmented to add core prints where core geometries were extracted. The core print, as currently developed, combines the extracted core geometry and its convex hull.

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Zhang, Chenrui, and Yuxin Peng. "Better and Faster: Knowledge Transfer from Multiple Self-supervised Learning Tasks via Graph Distillation for Video Classification." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/158.

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Video representation learning is a vital problem for classification task. Recently, a promising unsupervised paradigm termed self-supervised learning has emerged, which explores inherent supervisory signals implied in massive data for feature learning via solving auxiliary tasks. However, existing methods in this regard suffer from two limitations when extended to video classification. First, they focus only on a single task, whereas ignoring complementarity among different task-specific features and thus resulting in suboptimal video representation. Second, high computational and memory cost hinders their application in real-world scenarios. In this paper, we propose a graph-based distillation framework to address these problems: (1) We propose logits graph and representation graph to transfer knowledge from multiple self-supervised tasks, where the former distills classifier-level knowledge by solving a multi-distribution joint matching problem, and the latter distills internal feature knowledge from pairwise ensembled representations with tackling the challenge of heterogeneity among different features; (2) The proposal that adopts a teacher-student framework can reduce the redundancy of knowledge learned from teachers dramatically, leading to a lighter student model that solves classification task more efficiently. Experimental results on 3 video datasets validate that our proposal not only helps learn better video representation but also compress model for faster inference.

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Chen, Gaode, Xinghua Zhang, Yanyan Zhao, Cong Xue, and Ji Xiang. "Exploring Periodicity and Interactivity in Multi-Interest Framework for Sequential Recommendation." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/197.

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Sequential recommendation systems alleviate the problem of information overload, and have attracted increasing attention in the literature. Most prior works usually obtain an overall representation based on the user’s behavior sequence, which can not sufficiently reflect the multiple interests of the user. To this end, we propose a novel method called PIMI to mitigate this issue. PIMI can model the user’s multi-interest representation effectively by considering both the periodicity and interactivity in the item sequence. Specifically, we design a periodicity-aware module to utilize the time interval information between user’s behaviors. Meanwhile, an ingenious graph is proposed to enhance the interactivity between items in user’s behavior sequence, which can capture both global and local item features. Finally, a multi-interest extraction module is applied to describe user’s multiple interests based on the obtained item representation. Extensive experiments on two real-world datasets Amazon and Taobao show that PIMI outperforms state-of-the-art methods consistently.

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Shang, Junyuan, Tengfei Ma, Cao Xiao, and Jimeng Sun. "Pre-training of Graph Augmented Transformers for Medication Recommendation." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/825.

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Medication recommendation is an important healthcare application. It is commonly formulated as a temporal prediction task. Hence, most existing works only utilize longitudinal electronic health records (EHRs) from a small number of patients with multiple visits ignoring a large number of patients with a single visit (selection bias). Moreover, important hierarchical knowledge such as diagnosis hierarchy is not leveraged in the representation learning process. Despite the success of deep learning techniques in computational phenotyping, most previous approaches have two limitations: task-oriented representation and ignoring hierarchies of medical codes. To address these challenges, we propose G-BERT, a new model to combine the power of Graph Neural Networks (GNNs) and BERT (Bidirectional Encoder Representations from Transformers) for medical code representation and medication recommendation. We use GNNs to represent the internal hierarchical structures of medical codes. Then we integrate the GNN representation into a transformer-based visit encoder and pre-train it on EHR data from patients only with a single visit. The pre-trained visit encoder and representation are then fine-tuned for downstream predictive tasks on longitudinal EHRs from patients with multiple visits. G-BERT is the first to bring the language model pre-training schema into the healthcare domain and it achieved state-of-the-art performance on the medication recommendation task.

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Seong, Bo-Ok, Jimin Ahn, Myeongjun Son, and Hyeongok Lee. "Three-degree graph and design of an optimal routing algorithm." In 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1001466.

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Learning, as well as the importance of a high-performance computer is significantly emerging. In parallel computing, we denote the concept of interconnection between the single memory and multiple processors as multi-processor. In a similar context, multi-computing signifies the connection of memory-loaded processors through the communication link. The relationship between the performance of multi-computing and the processor’s linkage structure is extremely proximate. Let the connection structure of the processor be an interconnection network. The interconnection network can be modeled through a classical graph consisting of node and edge. In this regard, a multi-computing processor is expressed as a node, communication link as an edge. When categorizing the suggested interconnection network through the criteria of the number of nodes, it can be classified as follows: Mesh class type consisted of the n×k nodes (Torus, Toroidal mesh, Diagonal mesh, Honeycomb mesh), Hypercube class type with 2^n nodes (Hypercube, Folded hypercube, Twisted cube, de Breijin), and Star graph class type (Star graph, Bubblesort star, Alternating group, Macro-star, Transposition) with n! nodes. The mesh type structure is a planar graph that is widely being utilized in the domains such as VLSI circuit design and base station installing (covering) problems in a mobile communication network. Mesh class types are comparatively easier to design and could potentially be implemented in algorithmic domains in a practical manner. Therefore, it is considered as a classical measure that is extensively preferred when designing a parallel computing network system. This study suggests the novel mesh structure De3 with the degree of three and designs an optimal routing algorithm as well as a parallel route algorithm (병렬경로알고리즘) based on the diameter analysis. The address of the node in the De3 graph is expressed with n-bit binary digits, and the edge is noted with the operator %. We built the interval function (구간 함수) that computes the locational property of the corresponding nodes to derive an optimal routing path from node u to node v among the De3 graph structure. We represent the optimal routing algorithm based on the interval function, calculating and validating the diameter of the De3 graph. Furthermore, we propose the algorithm that establishes the node disjoint parallel path which addresses a non-overlap path from node u to v. The outcome of this study proposes a novel interconnection network structure that is applicable in the routing algorithm optimization by limiting the communication links to three while the number of nodes These results implicate the viable operation among the high-performance edge computing system in a cost-efficient and effective manner.

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Biradar, Sachin, Jyoti Shankar Jha, Sushil Mishra, and Asim Tewari. "Fatigue Crack Growth Retardation in Titanium Alloy." In ASME 2017 Gas Turbine India Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/gtindia2017-4893.

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The gas turbine components undergo fatigue load spectrum of variable amplitude loading. In this study, fatigue crack growth rate after multiple cycles of tensile overload has been investigated in Ti-2.77Sn-0.48Cu-1.15Fe-6.61V alloy. The overload at the crack tip produces the plastic zone at the vicinity, which retards the crack growth. Crack growth retardation effect has been studied at 15% and 25% overload percentages to observe its retardation effect. The multiple overloads applied after fixed interval of cycles produces a plastic region around the crack. After reloading the specimen further with constant loading, the crack growth rate is retarded thus causing increase in the fatigue life, which is observed in the graph of crack length vs number of cycles. The microstructure study has been carried out using Scanning Electron Microscope (SEM) and Electron Back Scatter Diffraction (EBSD), which gives qualitative information of strain to characterize the fatigue crack growth. The slope of crack length vs number of cycles before and after tensile peak overload was compared to evaluate the retardation effect at varying overload percentages.

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Tang, Wei, Dominic Giuliano, Oscar Martinez, Maxim Gussev, Andrzej Nycz, Ke An, Luke Meyer, et al. "Mechanical Responses of 316L Stainless Steel Printed by Wire Arc Additive Manufacturing With Different Thermal Histories." In ASME 2023 Pressure Vessels & Piping Conference. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/pvp2023-106680.

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Abstract In this paper, 316L stainless steel walls were printed using single-bead pass and multiple-bead pass wire arc additive manufacturing (WAAM), which represent the internal basket wall and external wall of a spent nuclear fuel (SNF) canister, respectively. Scanning electron microscopy (SEM) microstructure characterization and tensile tests at room temperature (21 °C) and elevated temperature (250 °C, the maximum temperature at the center of a SNF canister.) were performed on specimens extracted along the length and height directions of the printed walls. Results showed that grain morphology, grain angles, and retained ferrite are different between the two printed walls, which received different heat input in WAAM. The single-bead pass printed wall exhibited higher yield strength than the multiple-bead pass printed wall because of more retained ferrite and larger portion of random-high angle boundaries (RHAB) grains.

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Fischer, L. S., and S. B. Herschbein. "Focused Ion Beam Assisted Circuit Debug of a Video Graphics Chip." In ISTFA 1996. ASM International, 1996. http://dx.doi.org/10.31399/asm.cp.istfa1996p0037.

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Abstract Microchip circuit simulation modeling cannot always duplicate all of the independent variables found in a system level application. Sometimes, monitoring the logic states at multiple internal nodes when operating in the native environment is the only way of debugging a subtle design error. In this situation, Focused Ion Beam (FIB) technology was used to provide microprobe access points to deeply buried nets, allowing levels of real-time mapping not available by any other method. Data extraction was accomplished by probing the socketed chip on a rigidly mounted AT bus video card. The driver was a fully disassembled personal computer running a graphics intensive program. The close collaboration between failure analyst, applications engineering and the chip designers made this a truly unique experience.

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Звіти організацій з теми "Multiple interval graphs"

Green, Alastair, and Hannes Voigt, eds. Introduction to Graph Schema design. Linked Data Benchmark Council, October 2019. http://dx.doi.org/10.54285/ldbc.epwq6741.

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This presentation was prepared to summarize a design for Graph Schema for an internal audience in Neo4j reflecting multiple strands of work including WG3 standards contributions and the Cypher for Apache Spark project

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Brown, Yolanda, Twonia Goyer, and Maragaret Harvey. Heart Failure 30-Day Readmission Frequency, Rates, and HF Classification. University of Tennessee Health Science Center, December 2020. http://dx.doi.org/10.21007/con.dnp.2020.0002.

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30 Day Hospital Readmission Rates, Frequencies, and Heart Failure Classification for Patients with Heart Failure Background Congestive heart failure (CHF) is the leading cause of mortality, morbidity, and disability worldwide among patients. Both the incidence and the prevalence of heart failure are age dependent and are relatively common in individuals 40 years of age and older. CHF is one of the leading causes of inpatient hospitalization readmission in the United States, with readmission rates remaining above the 20% goal within 30 days. The Center for Medicare and Medicaid Services imposes a 3% reimbursement penalty for excessive readmissions including those who are readmitted within 30 days from prior hospitalization for heart failure. Hospitals risk losing millions of dollars due to poor performance. A reduction in CHF readmission rates not only improves healthcare system expenditures, but also patients’ mortality, morbidity, and quality of life. Purpose The purpose of this DNP project is to determine the 30-day hospital readmission rates, frequencies, and heart failure classification for patients with heart failure. Specific aims include comparing computed annual re-admission rates with national average, determine the number of multiple 30-day re-admissions, provide descriptive data for demographic variables, and correlate age and heart failure classification with the number of multiple re-admissions. Methods A retrospective chart review was used to collect hospital admission and study data. The setting occurred in an urban hospital in Memphis, TN. The study was reviewed by the UTHSC Internal Review Board and deemed exempt. The electronic medical records were queried from July 1, 2019 through December 31, 2019 for heart failure ICD-10 codes beginning with the prefix 150 and a report was generated. Data was cleaned such that each patient admitted had only one heart failure ICD-10 code. The total number of heart failure admissions was computed and compared to national average. Using age ranges 40-80, the number of patients re-admitted withing 30 days was computed and descriptive and inferential statistics were computed using Microsoft Excel and R. Results A total of 3524 patients were admitted for heart failure within the six-month time frame. Of those, 297 were re-admitted within 30 days for heart failure exacerbation (8.39%). An annual estimate was computed (16.86%), well below the national average (21%). Of those re-admitted within 30 days, 50 were re-admitted on multiple occasions sequentially, ranging from 2-8 re-admissions. The median age was 60 and 60% male. Due to the skewed distribution (most re-admitted twice), nonparametric statistics were used for correlation. While graphic display of charts suggested a trend for most multiple re-admissions due to diastolic dysfunction and least number due to systolic heart failure, there was no statistically significant correlation between age and number or multiple re-admissions (Spearman rank, p = 0.6208) or number of multiple re-admissions and heart failure classification (Kruskal Wallis, p =0.2553).

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