Relevant bibliographies by topics / General k-max search

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'General k-max search'

Author: Grafiati
Published: 8 June 2024
Last updated: 31 July 2025

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Journal articles on the topic "General k-max search"

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Xian, Aiyong, Kaiyuan Zhu, Daming Zhu, Lianrong Pu, and Hong Liu. "Approximating Max NAE-k-SAT by anonymous local search." Theoretical Computer Science 657 (January 2017): 54–63. http://dx.doi.org/10.1016/j.tcs.2016.05.040.

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Ahr, Dino, and Gerhard Reinelt. "A tabu search algorithm for the min–max k-Chinese postman problem." Computers & Operations Research 33, no. 12 (2006): 3403–22. http://dx.doi.org/10.1016/j.cor.2005.02.011.

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Ciftci, Esra, Emel Sesli Cetin, Ebru Us, Hüseyin Haydar Kutlu, and Buket Cicioglu Arıdogan. "Investigation of Carbapenem resistance mechanisms in Klebsiella pneumoniae by using phenotypic tests and a molecular assay." Journal of Infection in Developing Countries 13, no. 11 (2019): 992–1000. http://dx.doi.org/10.3855/jidc.10783.

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Introduction: The aim of this study was to investigate the presence of carbapenemase production and carbapenem resistance mechanisms in 47 carbapenem resistant Klebsiella pneumoniae isolates by phenotypic confirmatory tests and molecular assay.
 Methodology: Carbapenem resistance genes KPC, OXA-48 and NDM were investigated with the BD MAX CRE assay kit in the BD MAX real time PCR instrument. Modified Hodge test, MBL gradient strip test, D70C Carbapenemase Detection Set, Temocillin gradient strip test methods were used as phenotypic confirmatory tests. Clonal relationship between study iso
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Lan, Tianming, and Lei Guo. "Discovery of User Groups Densely Connecting Virtual and Physical Worlds in Event-Based Social Networks." International Journal of Information Technologies and Systems Approach 16, no. 2 (2023): 1–23. http://dx.doi.org/10.4018/ijitsa.327004.

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An essential task of the event-based social network (EBSN) platform is to recommend events to user groups. Usually, users are more willing to participate in events and interest groups with their friends, forming a particularly closely connected user group. However, such groups do not explicitly exist in EBSN. Therefore, studying how to discover groups composed of users who frequently participate in events and interest groups in EBSN has essential theoretical and practical significance. This article proposes the problem of discovering maximum k fully connected user groups. To address this issue
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Gupta, Ankita, Lakhwinder Kaur, and Gurmeet Kaur. "Drought stress detection technique for wheat crop using machine learning." PeerJ Computer Science 9 (May 19, 2023): e1268. http://dx.doi.org/10.7717/peerj-cs.1268.

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The workflow of this research is based on numerous hypotheses involving the usage of pre-processing methods, wheat canopy segmentation methods, and whether the existing models from the past research can be adapted to classify wheat crop water stress. Hence, to construct an automation model for water stress detection, it was found that pre-processing operations known as total variation with L1 data fidelity term (TV-L1) denoising with a Primal-Dual algorithm and min-max contrast stretching are most useful. For wheat canopy segmentation curve fit based K-means algorithm (Cfit-kmeans) was also va
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Hamann, Arne, and Sabine Wölk. "Performance analysis of a hybrid agent for quantum-accessible reinforcement learning." New Journal of Physics 24, no. 3 (2022): 033044. http://dx.doi.org/10.1088/1367-2630/ac5b56.

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Abstract In the last decade quantum machine learning has provided fascinating and fundamental improvements to supervised, unsupervised and reinforcement learning (RL). In RL, a so-called agent is challenged to solve a task given by some environment. The agent learns to solve the task by exploring the environment and exploiting the rewards it gets from the environment. For some classical task environments, an analogue quantum environment can be constructed which allows to find rewards quadratically faster by applying quantum algorithms. In this paper, we analytically analyze the behavior of a h
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Wang, Yanhao, Francesco Fabbri, Michael Mathioudakis, and Jia Li. "Fair Max–Min Diversity Maximization in Streaming and Sliding-Window Models." Entropy 25, no. 7 (2023): 1066. http://dx.doi.org/10.3390/e25071066.

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Diversity maximization is a fundamental problem with broad applications in data summarization, web search, and recommender systems. Given a set X of n elements, the problem asks for a subset S of k≪n elements with maximum diversity, as quantified by the dissimilarities among the elements in S. In this paper, we study diversity maximization with fairness constraints in streaming and sliding-window models. Specifically, we focus on the max–min diversity maximization problem, which selects a subset S that maximizes the minimum distance (dissimilarity) between any pair of distinct elements within
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Jayanthi, Neelampalli, Burra Babu, and Nandam Rao. "Outlier Detection Method based on Adaptive Clustering Method and Density Peak." International Journal of Intelligent Engineering and Systems 13, no. 6 (2020): 120–30. http://dx.doi.org/10.22266/ijies2020.1231.11.

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The outlier detection technique is widely used in the data analysis for the clustering of data. Many techniques have been applied in the outlier detection to increase the efficiency of the data analysis. The Local Projection based Outlier Detection (LPOD) method effectively identifies neighbouring values of data, but this has the drawback of random selection of the cluster centre that affects the overall clustering performance of the system. In this study, the Adaptive Clustering by Fast Search and Find of Density Peak (ACFSFDP) is proposed to select the clustering centre and density peak. Thi
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Gaspers, Serge, Eun Jung Kim, Sebastian Ordyniak, Saket Saurabh, and Stefan Szeider. "Don't Be Strict in Local Search!" Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 1 (2021): 486–92. http://dx.doi.org/10.1609/aaai.v26i1.8128.

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Local Search is one of the fundamental approaches to combinatorial optimization and it is used throughout AI. Several local search algorithms are based on searching the k-exchange neighborhood. This is the set of solutions that can be obtained from the current solution by exchanging at most k elements. As a rule of thumb, the larger k is, the better are the chances of finding an improved solution. However, for inputs of size n, a naive brute-force search of the k-exchange neighborhood requires n(O(k)) time, which is not practical even for very small values of k. Fellows et al. (IJCAI 2009) stu
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Pechnikov, Gennady, Alexander Blinkov, and Elena Parshina. "K. Marx on his own form and content in legal relations." Legal Science and Practice: Journal of Nizhny Novgorod Academy of the Ministry of Internal Affairs of Russia 2022, no. 4 (2022): 66–70. http://dx.doi.org/10.36511/2078-5356-2022-4-66-70.

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The article shows the importance of legal relations, based on the work of K. Marx “Debate on the order to steal a forest”, in which he clearly raised the question of the independence of legal relations, whether it be criminal law, or criminal procedure, or any other relationship... Any legal relationship has only its own form and content, inextricably dialectically interconnected. This is the true scientific nature of legal relations. Therefore, one legal relationship cannot be made the content of other relationships. For example, it is impossible to squeeze the Chinese procedural procedure in
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Dissertations / Theses on the topic "General k-max search"

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Schroeder, Pascal. "Performance guaranteeing algorithms for solving online decision problems in financial systems." Electronic Thesis or Diss., Université de Lorraine, 2019. http://www.theses.fr/2019LORR0143.

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Cette thèse contient quelques problèmes de décision financière en ligne et des solutions. Les problèmes sont formulés comme des problèmes en ligne (OP) et des algorithmes en ligne (OA) sont créés pour résoudre. Comme il peut y avoir plusieurs OAs pour le même OP, il doit y avoir un critère afin de pouvoir faire des indications au sujet de la qualité d’un OA. Dans cette thèse ces critères sont le ratio compétitif (c), la différence compétitive (cd) et la performance numérique. Un OA qui a un c ou cd plus bas qu’un autre est à préférer. Un OA qui possède le c le plus petit est appelé optimal. No
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Book chapters on the topic "General k-max search"

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Lopez, Kyra Mikaela M., and Ma Sheila A. Magboo. "A Clinical Decision Support Tool to Detect Invasive Ductal Carcinoma in Histopathological Images Using Support Vector Machines, Naïve-Bayes, and K-Nearest Neighbor Classifiers." In Machine Learning and Artificial Intelligence. IOS Press, 2020. http://dx.doi.org/10.3233/faia200765.

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This study aims to describe a model that will apply image processing and traditional machine learning techniques specifically Support Vector Machines, Naïve-Bayes, and k-Nearest Neighbors to identify whether or not a given breast histopathological image has Invasive Ductal Carcinoma (IDC). The dataset consisted of 54,811 breast cancer image patches of size 50px x 50px, consisting of 39,148 IDC negative and 15,663 IDC positive. Feature extraction was accomplished using Oriented FAST and Rotated BRIEF (ORB) descriptors. Feature scaling was performed using Min-Max Normalization while K-Means Clus
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Jabari, Farkhondeh, Heresh Seyedia, Sajad Najafi Ravadanegh, and Behnam Mohammadi Ivatloo. "Stochastic Contingency Analysis Based on Voltage Stability Assessment in Islanded Power System Considering Load Uncertainty Using MCS and k-PEM." In Advances in Computer and Electrical Engineering. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9911-3.ch002.

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Increased electricity demands and economic operation of large power systems in a deregulated environment with a limited investment in transmission expansion planning causes interconnected power grids to be operated closer to their stability limits. Meanwhile, the loads uncertainty will affect the static and dynamic stabilities. Therefore, if there is no emergency corrective control in time, occurrence of wide area contingency may lead to the catastrophic cascading outages. Studies show that many wide area blackouts which led to massive economic losses may have been prevented by a fast feasible
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Conference papers on the topic "General k-max search"

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Tönshoff, Jan, Berke Kisin, Jakob Lindner, and Martin Grohe. "One Model, Any CSP: Graph Neural Networks as Fast Global Search Heuristics for Constraint Satisfaction." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/476.

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We propose a universal Graph Neural Network architecture which can be trained as an end-2-end search heuristic for any Constraint Satisfaction Problem (CSP). Our architecture can be trained unsupervised with policy gradient descent to generate problem specific heuristics for any CSP in a purely data driven manner. The approach is based on a novel graph representation for CSPs that is both generic and compact and enables us to process every possible CSP instance with one GNN, regardless of constraint arity, relations or domain size. Unlike previous RL-based methods, we operate on a global searc
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Neagu, Laurentiumarian, Teodormihai Cotet, Mihai Dascalu, Stefan Trausanmatu, Laura Badescu, and Eugen Simion. "SEMANTIC AUTHOR RECOMMENDATIONS BASED ON THEIR BIOGRAPHY FROM THE GENERAL ROMANIAN DICTIONARY OF LITERATURE." In eLSE 2019. Carol I National Defence University Publishing House, 2019. http://dx.doi.org/10.12753/2066-026x-19-022.

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The Romanian Language Dictionary is a centralized text repository which contains detailed biographies of all Romanian authors and can be used to perform various subsequent analyses. The aim of this paper is to introduce a novel method to recommend authors based on their biography from the Romanian Language Dictionary. Starting from multiple PDF input files made available by the "G. C?linescu" Institute of Literary History and Theory, we extracted relevant information on Romanian authors which was indexed into Elasticsearch, a non-relational database optimized for full-text indexing and search.
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Seena, Abu. "Determinant Search Method for the Large Structural Systems With Small Bandwidth." In ASME 2021 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/imece2021-71761.

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Abstract In a solution to large eigenvalue problems, the number of required eigenvalues and corresponding vectors is usually much smaller than the order of matrices. For small bandwidth problems, the determinant search method is very efficient and the oldest. Its from a family of nonlinear Eigen solution techniques also referred to as frequency scanning methods. By using the shift technique, it can also calculate the largest eigenvalues. This calculation process involves three steps: polynomial iteration, inverse iteration, and polynomial deflation. The polynomial iteration determines the eige
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Hu, Zijian, Fengjun Bai, Huajie Wang, et al. "Deep Learning Approaches in Tight Gas Field Pay Zone Classification." In SPE Argentina Exploration and Production of Unconventional Resources Symposium. SPE, 2023. http://dx.doi.org/10.2118/212394-ms.

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Abstract Log interpretation is critical in locating pay zones and evaluating their potential. Conventional log interpretation is done manually. In our work, deep learning methods are utilized to deal with preliminary pay zone classification. In this way, human expertise can be liberated from trivial and repetitive tasks during logging interpretation. In a fluvial depositional environment, the sand distribution varies both vertically and horizontally. Thus, a large dataset covering a large area may lead to a too "averaged" model. In our work, we select a relatively small dataset (e.g., seven we
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Zhu, Pengli, Linlin Wang, and ChengQi Xue. "Dynamic Alarm Information Presentation Strategy under the Influence of Dynamic Elements in Smart Factory." In 2025 Intelligent Human Systems Integration. AHFE International, 2025. https://doi.org/10.54941/ahfe1005811.

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This study aims to propose a dynamic design strategy to assist operators in swiftly identifying alarm-indicating controls within dynamic background environments. Through comparative data analysis of alarm signals in behavioral experiments, the research identifies the most suitable combination of alarm information for the current smart factory interface, thereby laying the groundwork for improving alarm presentation methods on monitoring interfaces. With the advent of the Industry 4.0 era, the digitalization process is driving contemporary industrial manufacturing towards unmanned and intellige
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Ahmadov, Jamal. "Utilizing Data-Driven Models to Predict Brittleness in Tuscaloosa Marine Shale: A Machine Learning Approach." In SPE Annual Technical Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/208628-stu.

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Abstract The Tuscaloosa Marine Shale (TMS) formation is a clay- and liquid-rich emerging shale play across central Louisiana and southwest Mississippi with recoverable resources of 1.5 billion barrels of oil and 4.6 trillion cubic feet of gas. The formation poses numerous challenges due to its high average clay content (50 wt%) and rapidly changing mineralogy, making the selection of fracturing candidates a difficult task. While brittleness plays an important role in screening potential intervals for hydraulic fracturing, typical brittleness estimation methods require the use of geomechanical
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Barreto Fernandes, Francisco António, and Bernabé Hernandis Ortuño. "Usability and User-Centered Design - User Evaluation Experience in Self-Checkout Technologies." In Systems & Design 2017. Universitat Politècnica València, 2017. http://dx.doi.org/10.4995/sd2017.2017.6634.

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The increasing advance of the new technologies applied in the retail market, make it common to sell products without the personal contact between seller and buyer, being the registration and payment of the products made in electronic equipment of self-checkout. The large-scale use of these devices forces the consumer to participate in the service process, which was previously done through interaction with the company's employees. The user of the self-checkout system thus performs all the steps of the purchase, from weighing the products, registering them and making the payment. This is seen as
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Andov, Stojan, Violeta Cvetkoska, and Tea Mijac. "Unveiling Global Road Accident Patterns - Insights, Analytics, and Implications for Safer Driving Practices." In Economic and Business Trends Shaping the Future. Ss Cyril and Methodius University, Faculty of Economics-Skopje, 2023. http://dx.doi.org/10.47063/ebtsf.2023.0031.

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Every day, we are confronted with alarming news of serious injuries and fatalities resulting from car accidents. In the past decade, these incidents have been on the rise, posing a significant concern for individuals and societies worldwide. The impact of these accidents is particularly devastating when innocent lives, including children, are affected by the long-lasting consequences. While driver behavior remains a major contributing factor to road accidents, there are also other indirect reasons such as infrastructure issues and weather conditions. Addressing this global problem is of utmost
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