Academic literature on the topic 'Relaxed problem variants'
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Journal articles on the topic "Relaxed problem variants"
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Du, Yihong. "Critical point theorems with relaxed boundary condition and applications." Bulletin of the Australian Mathematical Society 47, no. 1 (February 1993): 101–18. http://dx.doi.org/10.1017/s0004972700012302.
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This paper is a sequel to a recent paper by the author in this journal. We prove some -variants of the min-max type critical point theorems with relaxed boundary condition and then apply the abstract results to a semilinear elliptic boundary value problem.
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Tran, Tony, Minh Do, Eleanor Rieffel, Jeremy Frank, Zhihui Wang, Bryan O'Gorman, Davide Venturelli, and J. Beck. "A Hybrid Quantum-Classical Approach to Solving Scheduling Problems." Proceedings of the International Symposium on Combinatorial Search 7, no. 1 (September 1, 2021): 98–106. http://dx.doi.org/10.1609/socs.v7i1.18390.
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An effective approach to solving complex problems is to decompose them and integrate dedicated solvers for those subproblems. We introduce a hybrid decomposition that incorporates: (1) a quantum annealer that samples from the configuration space of a relaxed problem to obtain strong candidate solutions, and (2) a classical processor that maintains a global search tree and enforces constraints on the relaxed components of the problem. Our framework is the first to use quantum annealing as part of a complete search. We consider variants of our approach with differing amounts of guidance from the quantum annealer. We empirically test our algorithm and compare the variants on problems from three scheduling domains: graph-coloring-type scheduling, simplified Mars Lander task scheduling, and airport runway scheduling. While we were only able to test on problems of small sizes, due to the limitation of currently available quantum annealing hardware, the empirical results show that results obtained from the quantum annealer can be used for more effective search node pruning and to improve node selection heuristics when compared to a standard classical approach.
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Gajjar, Kshitij, Agastya Vibhuti Jha, Manish Kumar, and Abhiruk Lahiri. "Reconfiguring Shortest Paths in Graphs." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 9 (June 28, 2022): 9758–66. http://dx.doi.org/10.1609/aaai.v36i9.21211.
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Reconfiguring two shortest paths in a graph means modifying one shortest path to the other by changing one vertex at a time, so that all the intermediate paths are also shortest paths. This problem has several natural applications, namely: (a) revamping road networks, (b) rerouting data packets in a synchronous multiprocessing setting, (c) the shipping container stowage problem, and (d) the train marshalling problem. When modelled as graph problems, (a) is the most general case while (b), (c) and (d) are restrictions to different graph classes. We show that (a) is intractable, even for relaxed variants of the problem. For (b), (c) and (d), we present efficient algorithms to solve the respective problems. We also generalise the problem to when at most k (for some k >= 2) contiguous vertices on a shortest path can be changed at a time.
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Yaffe, Tamir, Shawn Skyler, and Ariel Felner. "Suboptimally Solving the Watchman Route Problem on a Grid with Heuristic Search." Proceedings of the International Symposium on Combinatorial Search 12, no. 1 (July 21, 2021): 106–14. http://dx.doi.org/10.1609/socs.v12i1.18557.
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In the Watchman Route Problem (WRP) we are given a grid map with obstacles and the task is to (offline) find a (shortest) path through the grid such that all cells in the map can be visually seen by at least one cell on the path. WRP was recently formalized and optimally solved with heuristic search. In this paper we show how the previous optimal methods can be relaxed and modified to obtain suboptimal solvers that are much faster than the optimal solvers without sacrificing too much the quality of the solution. In particular, we present three methods that intelligently prune away large subtrees. We then derive bounded suboptimal solvers, suboptimal solvers without bounds and anytime variants of these. All these algorithms are backed up with experimental evidence that show their benefits compared to existing approaches.
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Singamsetty, Purusotham, and Jayanth Kumar Thenepalle. "An efficient genetic algorithm for solving open multiple travelling salesman problem with load balancing constraint." Decision Science Letters 10, no. 4 (2021): 525–34. http://dx.doi.org/10.5267/j.dsl.2021.5.003.
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The multiple travelling salesman problem (MTSP) is one of the widely studied combinatorial optimization problems with various theoretical and practical applications. However, most of the studies intended to deal with classical MTSP, very limited attention has been given to an open multiple travelling salesman problem and its variants. In this paper, an open multiple travelling salesman problem with load balancing constraint (OMTSPLB) is addressed. The OMTSPLB differs from the conventional MTSP, in which all the salesmen start from the central depot and need not come back to it after visiting the given number of cities by accomplishing the load balance constraint, which helps in fairly distributing the task among all salesmen. The problem aims to minimize the overall traversal distance/cost for operating open tours subject to the load balancing constraint. A zero-one integer linear programming (0-1 ILP) model and an efficient metaheuristic genetic algorithm (GA), is established for the OMTSPLB. Since no existing study on OMTSPLB, the proposed GA is tested on the relaxed version of the present model, comparative results are reported. The comparative results show that the proposed GA is competent over the existing algorithms. Furthermore, extensive experiments are carried out on OMTSPLB and the results show that proposed GA can find the global solution effectively.
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Walker, Thayne T., Nathan R. Sturtevant, and Ariel Felner. "Generalized and Sub-Optimal Bipartite Constraints for Conflict-Based Search." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (April 3, 2020): 7277–84. http://dx.doi.org/10.1609/aaai.v34i05.6219.
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The main idea of conflict-based search (CBS), a popular, state-of-the-art algorithm for multi-agent pathfinding is to resolve conflicts between agents by systematically adding constraints to agents. Recently, CBS has been adapted for new domains and variants, including non-unit costs and continuous time settings. These adaptations require new types of constraints. This paper introduces a new automatic constraint generation technique called bipartite reduction (BR). BR converts the constraint generation step of CBS to a surrogate bipartite graph problem. The properties of BR guarantee completeness and optimality for CBS. Also, BR's properties may be relaxed to obtain suboptimal solutions. Empirical results show that BR yields significant speedups in 2k connected grids over the previous state-of-the-art for both optimal and suboptimal search.
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Ivankovic, Franc, Patrik Haslum, Sylvie Thiebaux, Vikas Shivashankar, and Dana Nau. "Optimal Planning with Global Numerical State Constraints." Proceedings of the International Conference on Automated Planning and Scheduling 24 (May 10, 2014): 145–53. http://dx.doi.org/10.1609/icaps.v24i1.13648.
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Automating the operations of infrastructure networks such as energy grids and oil pipelines requires a range of planning and optimisation technologies. However, current planners face significant challenges in responding to this need. Notably, they are unable to model and reason about the global numerical state constraints necessary to capture flows and similar physical phenomena occurring in these networks. A single discrete control action can affect the flow throughout the network in a way that may depend on the entire network topology. Determining whether preconditions, goals and invariant conditions are satisfied requires solving a system of numerical constraints after each action application. This paper extends domain-independent optimal planning to this kind of reasoning. We present extensions of the formalism, relaxed plans, and heuristics, as well as new search variants and experimental results on two problem domains.
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Wang, Lingya, and Dean S. Oliver. "Efficient Optimization of Well-Drilling Sequence with Learned Heuristics." SPE Journal 24, no. 05 (August 26, 2019): 2111–34. http://dx.doi.org/10.2118/195640-pa.
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Summary When preparing a field–development plan, the forecast value of the development can be sensitive to the order in which the wells are drilled. Determining the optimal drilling sequence generally requires many simulation runs. In this paper, we formulate the sequential decision problem of a drilling schedule as one of finding a path in a decision tree that is most likely to generate the highest net present value (NPV). A nonparametric online–learning methodology is developed to efficiently compute the sequence of drilling wells that is optimal or near optimal. The main ideas behind the approach are that heuristics from relaxed problems can be used to estimate the maximum value of complete drilling sequences constrained to previous wells, and that multiple online–learning techniques can be used to improve the accuracy of the estimated values. The performance of various heuristic methods is studied in a model for which uncertainty in properties is neglected. The initial heuristic used in this work generates a higher estimated NPV than the actual maximum NPV. Although such a heuristic is guaranteed to find the true optimal drilling order when used in the A* informed-search algorithm method, the cost of the search can be prohibitive unless the initial heuristic is highly accurate. For the variants of heuristic search methods with weighting parameters, the results show that it might not be possible to identify parameters that can be used to find a solution quickly without sacrificing the accuracy of the estimated NPV in this drilling–sequence problem. In contrast, the online learned heuristics derived from observations from previous drilling steps are shown to outperform the other variants of heuristic methods in terms of running time, accuracy of the estimated value, and solution quality. Multilearned heuristic search (MLHS) with space reduction (MLHS–SR) is an efficient and fast method to find a solution with high value. Continuing the search with space restoration is guaranteed to improve the solution quality or find the same solution as the MLHS without any space reduction.
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Mendoza, Victoria May P., Renier Mendoza, Jongmin Lee, and Eunok Jung. "Adjusting non-pharmaceutical interventions based on hospital bed capacity using a multi-operator differential evolution." AIMS Mathematics 7, no. 11 (2022): 19922–53. http://dx.doi.org/10.3934/math.20221091.
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<abstract><p>Without vaccines and medicine, non-pharmaceutical interventions (NPIs) such as social distancing, have been the main strategy in controlling the spread of COVID-19. Strict social distancing policies may lead to heavy economic losses, while relaxed social distancing policies can threaten public health systems. We formulate optimization problems that minimize the stringency of NPIs during the prevaccination and vaccination phases and guarantee that cases requiring hospitalization will not exceed the number of available hospital beds. The approach utilizes an SEIQR model that separates mild from severe cases and includes a parameter $ \mu $ that quantifies NPIs. Payoff constraints ensure that daily cases are decreasing at the end of the prevaccination phase and cases are minimal at the end of the vaccination phase. Using a penalty method, the constrained minimization is transformed into a non-convex, multi-modal unconstrained optimization problem. We solve this problem using the improved multi-operator differential evolution, which fared well when compared with other optimization algorithms. We apply the framework to determine optimal social distancing strategies in the Republic of Korea given different amounts and types of antiviral drugs. The model considers variants, booster shots, and waning of immunity. The optimal $ \mu $ values show that fast administration of vaccines is as important as using highly effective vaccines. The initial number of infections and daily imported cases should be kept minimum especially if the bed capacity is low. In Korea, a gradual easing of NPIs without exceeding the bed capacity is possible if there are at least seven million antiviral drugs and the effectiveness of the drug in reducing severity is at least 86%. Model parameters can be adapted to a specific region or country, or other infectious diseases. The framework can be used as a decision support tool in planning economic policies, especially in countries with limited healthcare resources.</p></abstract>
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Pagel, Kymberleigh A., Rick Kim, Kyle Moad, Ben Busby, Lily Zheng, Collin Tokheim, Michael Ryan, and Rachel Karchin. "Integrated Informatics Analysis of Cancer-Related Variants." JCO Clinical Cancer Informatics, no. 4 (September 2020): 310–17. http://dx.doi.org/10.1200/cci.19.00132.
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PURPOSE The modern researcher is confronted with hundreds of published methods to interpret genetic variants. There are databases of genes and variants, phenotype-genotype relationships, algorithms that score and rank genes, and in silico variant effect prediction tools. Because variant prioritization is a multifactorial problem, a welcome development in the field has been the emergence of decision support frameworks, which make it easier to integrate multiple resources in an interactive environment. Current decision support frameworks are typically limited by closed proprietary architectures, access to a restricted set of tools, lack of customizability, Web dependencies that expose protected data, or limited scalability. METHODS We present the Open Custom Ranked Analysis of Variants Toolkit 1 (OpenCRAVAT) a new open-source, scalable decision support system for variant and gene prioritization. We have designed the resource catalog to be open and modular to maximize community and developer involvement, and as a result, the catalog is being actively developed and growing every month. Resources made available via the store are well suited for analysis of cancer, as well as Mendelian and complex diseases. RESULTS OpenCRAVAT offers both command-line utility and dynamic graphical user interface, allowing users to install with a single command, easily download tools from an extensive resource catalog, create customized pipelines, and explore results in a richly detailed viewing environment. We present several case studies to illustrate the design of custom workflows to prioritize genes and variants. CONCLUSION OpenCRAVAT is distinguished from similar tools by its capabilities to access and integrate an unprecedented amount of diverse data resources and computational prediction methods, which span germline, somatic, common, rare, coding, and noncoding variants.
Dissertations / Theses on the topic "Relaxed problem variants"
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Lin, Shian-liang, and 林憲良. "A Survey on the Algorithms of the Edit Distance Problem and Related Variants." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/xwc588.
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碩士國立中山大學
資訊工程學系研究所
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Abstract The edit distance problem has been studied for several decades. Given sequences (strings) A and B with length m and n, respectively, m ≤ n, the edit distance problem is to find the minimum cost of operations required to transform A to B. According to different models of cost functions, operations and input sequences, the problem has several variants. The edit distance on run-length encoding sequences and cyclic sequences are the variants on the input aspect. The block edit problem is a variant on the operation aspect. The edit distance considering consecutive insertions and deletions is another variant on the cost function. Besides, the genome rearrangement problem can also be viewed as a variant, whose operations include inversions, reversals and transpositions. In this thesis, we survey some algorithms for the edit distance problem, its variants and the genome rearrangement problem. We also perform some experiments to illustrate the execution efficiency of various algorithms. Keywords: Edit Distance, Block Edit, Genome Rearrangement, Longest Common Subsequence, Dynamic Programing, Similarity
Books on the topic "Relaxed problem variants"
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Kuz'mina, Tat'yana. Self-awareness and personal adaptive potential in normal and impaired development. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1086621.
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The monograph presents the generalized results of the author's scientific activity related to the diagnosis and phenomenological description of the state of self-consciousness and the Self-concept of persons with developmental disorders, in particular with mild mental retardation. The variants of self-awareness diagnostics and a comprehensive assessment of the personal adaptive potential of subjects of different ages with intellectual disabilities are presented and methodologically justified. The presented methods allow us to form an individual adaptive profile based on a quantitative assessment of qualitative indicators of adaptability/maladaptivity. The content aspects of the formation of the antisocial potential of a person with mild mental retardation, in particular, the problems of suggestibility, indoctrination and the participation of persons with intellectual disabilities in criminal communities, are separately identified.
It will be useful for students, postgraduates, researchers and practitioners in the field of pedagogy, psychology, law.
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Pye, David. Practical Nitriding and Ferritic Nitrocarburizing. ASM International, 2003. http://dx.doi.org/10.31399/asm.tb.pnfn.9781627083508.
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Practical Nitriding and Ferritic Nitrocarburizing addresses many questions that arise when using nitriding and nitrocarburizing processes to case harden engineered components. It describes the basic chemistry of each process and its effect on the metallurgy and microstructure of different grades of iron and steel. It explains how the processes and their variants are implemented and how to set up, monitor, and control process equipment to meet specific design objectives. It discusses the factors that must be considered when selecting materials and determining parameters related to surface hardness, case depth, compound zone thickness, corrosion and wear resistance, distortion, and other such variables. It also explains how materials should be prepared and handled before and after processing, how to examine and evaluate results, and how to diagnose and fix problems. For information on the print version, ISBN 978-0-87170-791-8, follow this link.
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Taljanovic, Mihra S., Imran M. Omar, Kevin B. Hoover, and Tyson S. Chadaz, eds. Musculoskeletal Imaging Volume 1. Oxford University Press, 2019. http://dx.doi.org/10.1093/med/9780190938161.001.0001.
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This volume meets the needs of radiology residents to become adept at interpreting musculoskeletal (MSK) imaging studies. It does so by presenting core knowledge and fundamentals that must be learned to accurately and effectively interpret MSK studies by the trainee and non-specialist. The goal is to impart to residents, as well as to refresh for practitioners, essential facts in a concise and readable format so the reader becomes conversant with all imaging modalities used and the essentials of interpretation and technique. Other resources are at too high a level for the resident in training or contain far more information than a resident can easily assimilate during a rotation. The book is part of the Rotations in Radiology series for residents, which defines and encapsulates core knowledge for areas within Radiology, offering a guided, structured approach to imaging diagnosis. It contains sections on 10 key topics in MSK radiology: trauma; arthritis; tumors and tumor-like conditions; metabolic, hematopoietic, endocrine, and deposition diseases; infectious diseases; arthrography; internal derangements of the joints; congenital diseases; and ultrasound. Each section begins with an overview chapter, orienting the reader to the specific concerns and issues related to imaging that anatomic region or category of problem. Each clinical problem or diagnosis is concisely covered to provide a targeted discussion and highlight salient points. For each topic, concise chunks of text will review: definition; clinical features; anatomy and physiology; how to appraoch the image; what not to miss; differential diagnosis; common variants if pertinent; clinical issues; key points; high yield references.
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Taljanovic, Mihra S., Imran M. Omar, Kevin B. Hoover, and Tyson S. Chadaz, eds. Musculoskeletal Imaging Volume 2. Oxford University Press, 2019. http://dx.doi.org/10.1093/med/9780190938178.001.0001.
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This volume meets the needs of radiology residents to become adept at interpreting musculoskeletal (MSK) imaging studies. It does so by presenting core knowledge and fundamentals that must be learned to accurately and effectively interpret MSK studies by the trainee and non-specialist. The goal is to impart to residents, as well as to refresh for practitioners, essential facts in a concise and readable format so the reader becomes conversant with all imaging modalities used and the essentials of interpretation and technique. Other resources are at too high a level for the resident in training or contain far more information than a resident can easily assimilate during a rotation. The book is part of the Rotations in Radiology series for residents, which defines and encapsulates core knowledge for areas within Radiology, offering a guided, structured approach to imaging diagnosis. It contains sections on 10 key topics in MSK radiology: trauma; arthritis; tumors and tumor-like conditions; metabolic, hematopoietic, endocrine, and deposition diseases; infectious diseases; arthrography; internal derangements of the joints; congenital diseases; and ultrasound. Each section begins with an overview chapter, orienting the reader to the specific concerns and issues related to imaging that anatomic region or category of problem. Each clinical problem or diagnosis is concisely covered to provide a targeted discussion and highlight salient points. For each topic, concise chunks of text will review: definition; clinical features; anatomy and physiology; how to appraoch the image; what not to miss; differential diagnosis; common variants if pertinent; clinical issues; key points; high yield references.
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Rose, Cramer Sacha. Vaccine Nationalism in the age of COVID-19. Technische Universität Dresden, 2021. http://dx.doi.org/10.25368/2022.413.
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It is no secret that the world has a COVID-19 vaccine problem. The majority of vaccination doses have been administered in Europe and North America, whilst many poorer counties have vaccinated less than 1% of their entire population. In light of the new variants presenting health risks, countries such as South Africa and India have proposed that the World Trade Organisation temporarily waive intellectual property rights for COVID-19 vaccines to help increase the production of vaccines. The world’s economic powerhouses such as U.S., Britain and the European Union vetoed the idea, submitting that intellectual property rights are important for ensuring continued innovation. They are of the opinion that waiving such rights would not result in increased production. The question therefore stands if these are only two options: either patents remain unchanged, or patents are disregarded. An alternative, and perhaps a middle ground is that of compulsory licensing. Although a seemingly good option, it presents its own problems. For instance, patents are territorial and grant the patent holder a monopoly for a limited time of 20 years. However, based on public needs – including health emergencies, a government can allow others to make the product, usually with a fair royalty, or fee, paid to the patent owner. However, this ends at the border. Article 31 of the WTO’s Agreement on Trade-Related Aspects of Intellectual Property Law, or TRIPS, limit compulsory licenses primarily to domestic production and use. This is also limited to companies within the territory, producing products primarily for export. This of course would make the whole point of such compulsory licenses redundant, since the countries producing such vaccines are not the countries that do not have access to them. The other problem with the COVID-19 vaccine is that the technologies used in producing such vaccines are complex and involve numerous patents, trade secrets and know-how. A compulsory licensing system would need to address not just patents but also the related intellectual property in question. To successfully expand vaccine production, countries need a moderately smooth structure to allow a country such as India, to grant a single, blanket license allowing companies to produce vaccines develop by the U.S. or European companies for export to all countries that lack their own manufacturing capacity. The proposed WTO waiver of intellectual property rights seeks to address the need of improved vaccine production, but it may be little too far stressed. Compulsory licensing would smooth the way for the expansion of vaccine manufacturing whilst at the same time still compensating the right holders.
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Casey, Patricia. History of the concept of adjustment disorders (DRAFT). Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198786214.003.0001.
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Adjustment disorder (AD) was introduced by ICD-9 in 1978 and by DSM-III in 1980. Until recently it was neglected in research and in clinical practice. It has withstood the early controversies suggesting that it was a manufactured condition to facilitate the reimbursement of clinicians for treating mild conditions which otherwise would not be covered by insurance. Others argue that it medicalized problems of living. More recent controversies concern its status as a subthreshold disorder, disbarring it from being diagnosed when the threshold for other disorders is reached. Its status has been enhanced by its new positioning in DSM-5 in the Trauma and Stressor-Related Disorders category, similar to ICD-10. However, ICD-11 is proposing making AD a full-threshold disorder with specific criteria for diagnosis, unlike DSM-5. This radical proposal will put ICD-11 and DSM-5 at variance with each other and will require a reappraisal of the research, to date, on AD.
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Crowley, Lara M. Manuscript Matters. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198821861.001.0001.
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Manuscript Matters illuminates responses to some of John Donne’s most elusive texts by his contemporary audiences. Since examples of seventeenth-century literary criticism prove somewhat rare and frequently ambiguous, this book emphasizes a critical framework rarely used for exhibiting early readers’ exegeses of literary texts: the complete manuscripts containing them. Many literary manuscripts that include poems by Donne and his contemporaries were compiled during their lifetimes, often by members of their circles. For this reason, and because various early modern poems and prose works satirize topical events and prominent figures in highly coded language, attempting to understand early literary interpretations proves challenging but highly valuable. Compilers, scribes, owners, and other readers—men and women who shared in Donne’s political, religious, and social contexts—offer clues to their literary responses within a range of features related to the construction and subsequent use of the manuscripts. This study’s findings call us to investigate more extensively and systematically how certain early manuscripts were constructed through analysis of such features as scripts, titles, sequence of contents, ascriptions, and variant diction. While such studies can throw light on many early modern texts, exploring artifacts containing Donne’s works proves particularly useful because more of his poetry circulated in manuscript than did that of any other early modern poet. Manuscript Matters engages Donne’s satiric, lyric, and religious poetry, as well as his prose paradoxes and problems—refocusing modern interpretation through an early modern lens.
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Suprun, Sergey P., Anatoly P. Suprun, and Victor F. Petrenko. Schrödinger's Cat Smile. BENTHAM SCIENCE PUBLISHERS, 2022. http://dx.doi.org/10.2174/97898150496641220201.
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The book presents a multidisciplinary analysis of the context of quantum physics experiments and the function of the human mind that makes it possible to demonstrate that an object-based model of reality formed at the level of the unconscious is the basis of our worldview. The consciousness experiences a time flow because of the specific features of perception in the form of a model with a sequential fixation of events. Together with the need to relate objects in terms of the model, this generates a space-time representation of the world around us. Acceptance of a mental character of our construct of reality allows for resolution of the problems in quantum physics and its paradoxes, thereby opening the way to an insight into reality. The presented material is organized in a specific order to facilitate the reader`s understanding. First, the fact that if there are no objects in the area of quantum mechanics, then they belong to the corresponding model rather than the reality is proved by case studies of the most discussed and relevant paradoxes of quantum physics. The authors consider a topological variant in constructing an object-based space that describes the physical properties of an object that are the most verified in science and describable with mathematical relations. The functionality of the proposed construct is tested by deriving the laws of conservation of energy and momentum in a relativistic form. The book is oriented towards experts in physics and psychology, advanced students, and readers interested in state-of-the-art science and the philosophy connected to it.
Book chapters on the topic "Relaxed problem variants"
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Frazho, A. E., S. ter Horst, and M. A. Kaashoek. "A Time-variant Norm Constrained Interpolation Problem Arising from Relaxed Commutant Lifting." In Operator Algebras, Operator Theory and Applications, 139–66. Basel: Birkhäuser Basel, 2009. http://dx.doi.org/10.1007/978-3-0346-0174-0_6.
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Ben-Haim, Yakov. "Nonlinear Problems in Selectively Sensitive Identification of Structures." In Safety Evaluation Based on Identification Approaches Related to Time-Variant and Nonlinear Structures, 204–21. Wiesbaden: Vieweg+Teubner Verlag, 1993. http://dx.doi.org/10.1007/978-3-322-89467-0_12.
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Dumas, Éric, David Lannes, and Jérémie Szeftel. "Variants of the Focusing NLS Equation: Derivation, Justification, and Open Problems Related to Filamentation." In Laser Filamentation, 19–75. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-23084-9_2.
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Fingerhut, Abe, Hayato Kurihara, and William Tzu-Liang Chen. "Vascular Problems Related to Colectomy: Habitual and Variant Anatomy, Prevention, and Tactical Aspects." In Prophylactic Surgery, 193–200. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66853-2_18.
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Tran, Hoang-Dung, Neelanjana Pal, Patrick Musau, Diego Manzanas Lopez, Nathaniel Hamilton, Xiaodong Yang, Stanley Bak, and Taylor T. Johnson. "Robustness Verification of Semantic Segmentation Neural Networks Using Relaxed Reachability." In Computer Aided Verification, 263–86. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81685-8_12.
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AbstractThis paper introduces robustness verification for semantic segmentation neural networks (in short, semantic segmentation networks [SSNs]), building on and extending recent approaches for robustness verification of image classification neural networks. Despite recent progress in developing verification methods for specifications such as local adversarial robustness in deep neural networks (DNNs) in terms of scalability, precision, and applicability to different network architectures, layers, and activation functions, robustness verification of semantic segmentation has not yet been considered. We address this limitation by developing and applying new robustness analysis methods for several segmentation neural network architectures, specifically by addressing reachability analysis of up-sampling layers, such as transposed convolution and dilated convolution. We consider several definitions of robustness for segmentation, such as the percentage of pixels in the output that can be proven robust under different adversarial perturbations, and a robust variant of intersection-over-union (IoU), the typical performance evaluation measure for segmentation tasks. Our approach is based on a new relaxed reachability method, allowing users to select the percentage of a number of linear programming problems (LPs) to solve when constructing the reachable set, through a relaxation factor percentage. The approach is implemented within NNV, then applied and evaluated on segmentation datasets, such as a multi-digit variant of MNIST known as M2NIST. Thorough experiments show that by using transposed convolution for up-sampling and average-pooling for down-sampling, combined with minimizing the number of ReLU layers in the SSNs, we can obtain SSNs with not only high accuracy (IoU), but also that are more robust to adversarial attacks and amenable to verification. Additionally, using our new relaxed reachability method, we can significantly reduce the verification time for neural networks whose ReLU layers dominate the total analysis time, even in classification tasks.
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Hogben, Leslie. "Nordhaus-Gaddum problems for Colin de Verdière type parameters, variants of tree-width, and related parameters." In Recent Trends in Combinatorics, 275–94. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-24298-9_12.
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Perrot, Nancy, Amal Benhamiche, Yannick Carlinet, and Eric Gourdin. "Future Networks." In Research Anthology on Developing and Optimizing 5G Networks and the Impact on Society, 677–706. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7708-0.ch028.
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This chapter gives an insight into some challenging combinatorial optimization problems that have to be tackled to deliver efficient and appropriate decision algorithms to manage future networks. The first part of the chapter is dedicated to variants of routing optimization problems in future IP networks, and the second part is dedicated to two optimization problems related to network virtualization and 5G network slicing, the virtual network embedding problem and the service function chaining problem. Each of these optimization problems is described along with the main challenges to overcome, and a recent and extensive related state of the art is given, so as to highlight the most recent and promising approaches to solve them.
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Mokrzycka, Krystyna. "Tożsamość konstytucyjna – monolit czy krajobraz inności?" In Interdyscyplinarny wymiar tożsamości konstytucyjnej, 13–30. Ksiegarnia Akademicka Publishing, 2022. http://dx.doi.org/10.12797/9788381387149.01.
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CONSTITUTIONAL IDENTITY - A MONOLITH OR A PANORAMA OF DIFFERENCES? Although the notion of constitutional identity still lacks a unified definition, attempts can be made to delineate a framework of features by which it could be characterized. One of the fundamental problems that arise in this process is the question of the possible multiplicity of constitutional identities. While it may be viewed as a monistic entity, reducible to the most general and abstract set of postulates, such a definition would give rise to further problems, primarily that of an excessively generalised approach to constitutional identity, which does not make it possible to clearly distinguish it from other concepts in the social sciences, and does not fully reflect its nature. Therefore, an alternative approach should be considered, related to the possibility of a multiple character of constitutional identity (allowing for its several variants and making this multiplicity one of its postulated features) or even the existence not of several variants of identity with the same axiological core, but several equal, typologically distinctive variants of constitutional identity derived from the same set of values. The purpose of this paper is to outline the framework of each of the above discussed answers to the problem of the multiplicity of constitutional identities, and to present the issues related to its uniform definition in an extremely pluralist, polarized society.
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"Two-Echelon Location-Routing and Vehicle Routing Problems in City Logistics." In Logistics and Transport Modeling in Urban Goods Movement, 55–87. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8292-2.ch003.
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This chapter presents the main notions of two-echelon vehicle routing (2E-VRP) in relation to city logistics. After introducing vehicle routing and the main single-echelon problems and variants, the two-echelon version is presented and two different models proposed: one based on commodity flow and the other on vehicle flow modelling). Several instances are solved with those models and the results are compared and discussed. That comparison illustrates the difficulty of using this type of models to obtain results to that problem, and motivates the need of developing suitable algorithms. For that reason, an overview of heuristic methods to solve two-echelon vehicle routing problems is made, as well as an introduction of other related problems which are similar and interesting, relating in all cases the presented methods and problems to city logistics needs and goals.
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Reyes, Laura Cruz, Claudia Gómez Santillán, Marcela Quiroz, Adriana Alvim, Patricia Melin, Jorge Ruiz Vanoye, and Vanesa Landero Najera. "Heuristic Algorithms." In Logistics Management and Optimization through Hybrid Artificial Intelligence Systems, 238–67. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-0297-7.ch009.
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This chapter approaches the Truck Loading Problem, which is formulated as a rich problem with the classic one dimensional Bin Packing Problem (BPP) and five variants. The literature review reveals that related work deals with three variants at the most. Besides, few efforts have been done to combine the Bin Packing Problem with the Vehicle Routing Problem. For the solution of this new Rich BPP a heuristic-deterministic algorithm, named DiPro, is proposed. It works together with a metaheuristic algorithm to plan routes, schedules and loads. The objective of the integrated problem, called RoSLoP, consists of optimizing the delivery process of bottled products in a real application. The experiments show the performance of three version of the Transportation System. The best version achieves a total demand satisfaction, an average saving of three vehicles and a reduction of the computational time from 3 hrs to two minutes regarding their manual solution. For the large scale the authors have develop a competitive genetic algorithm for BPP. As future work, it is intended integrate the approximation algorithm to the transportation system.
Conference papers on the topic "Relaxed problem variants"
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Wang, Rong, Jitao Lu, Yihang Lu, Feiping Nie, and Xuelong Li. "Discrete Multiple Kernel k-means." 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.2021/428.
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The multiple kernel k-means (MKKM) and its variants utilize complementary information from different kernels, achieving better performance than kernel k-means (KKM). However, the optimization procedures of previous works all comprise two stages, learning the continuous relaxed label matrix and obtaining the discrete one by extra discretization procedures. Such a two-stage strategy gives rise to a mismatched problem and severe information loss. To address this problem, we elaborate a novel Discrete Multiple Kernel k-means (DMKKM) model solved by an optimization algorithm that directly obtains the cluster indicator matrix without subsequent discretization procedures. Moreover, DMKKM can strictly measure the correlations among kernels, which is capable of enhancing kernel fusion by reducing redundancy and improving diversity. What’s more, DMKKM is parameter-free avoiding intractable hyperparameter tuning, which makes it feasible in practical applications. Extensive experiments illustrated the effectiveness and superiority of the proposed model.
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Khajavirad, Aida, and Jeremy J. Michalek. "A Single-Stage Gradient-Based Approach for Solving the Joint Product Family Platform Selection and Design Problem Using Decomposition." In ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/detc2007-35611.
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A core challenge in product family optimization is to develop a single-stage approach that can optimally select the set of variables to be shared in the platform(s) while simultaneously designing the platform(s) and variants within an algorithm that is efficient and scalable. However, solving the joint product family platform selection and design problem involves significant complexity and computational cost, so most prior methods have narrowed the scope by treating the platform as fixed or have relied on stochastic algorithms or heuristic two-stage approaches that may sacrifice optimality. In this paper, we propose a single-stage approach for optimizing the joint problem using gradient-based methods. The combinatorial platform-selection variables are relaxed to the continuous space by applying the commonality index and consistency relaxation function introduced in a companion paper. In order to improve scalability properties, we exploit the structure of the product family problem and decompose the joint product family optimization problem into a two-level optimization problem using analytical target cascading so that the system-level problem determines the optimal platform configuration while each subsystem optimizes a single product in the family. Finally, we demonstrate the approach through optimization of a family of ten bathroom scales; Results indicate encouraging success with scalability and computational expense.
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Khajavirad, Aida, and Jeremy J. Michalek. "An Extension of the Commonality Index for Product Family Optimization." In ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/detc2007-35605.
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One critical aim of product family design is to offer distinct variants that attract a variety of market segments while maximizing the number of common parts to reduce manufacturing cost. Several indices have been developed for measuring the degree of commonality in existing product lines to compare product families or assess improvement of a redesign. In the product family optimization literature, commonality metrics are used to define the multi-objective tradeoff between commonality and individual variant performance. These metrics for optimization differ from indices in the first group: While the optimization metrics provide desirable computational properties, they generally lack the desirable properties of indices intended to act as appropriate proxies for the benefits of commonality, such as reduced tooling and supply chain costs. In this paper, we propose a method for computing the commonality index introduced by Martin and Ishii using the available input data for any product family without predefined configuration. The proposed method for computing the commonality index, which was originally defined for binary formulations (common / not common), is relaxed to the continuous space in order to solve the discrete problem with a series of continuous relaxations, and the effect of relaxation on the metric behavior is investigated. Several relaxation formulations are examined, and a new function with desirable properties is introduced and compared with prior formulations. The new properties of the proposed metric enable development of an efficient and robust single-stage gradient-based optimization of the joint product family platform selection and design problem, which is examined in a companion paper.
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Biłozor, Andrzej, and Małgorzata Renigier-Biłozor. "Methodology of the Polyoptimization for Spatial Processes." In Environmental Engineering. VGTU Technika, 2017. http://dx.doi.org/10.3846/enviro.2017.100.
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Optimization is a complex activity that aims to find the best solution for a given activity, considering all existing limitations. The best variant possible in the set of acceptable variants is sought-out. In particular, in urban areas, optimization of land use function as the beginning of a decision-making process requires performing a great number of tasks, which minimize the risk of spatial conflicts, set at the stage of studies and analyses. Polyoptimization is optimization with a vector objective function. The aim of polyoptimization is to find the best solution, concurrently applying several criteria which, due to their limitations, are conflicting as a general rule. It leads to finding compromise solutions (polyoptimum variants in the set of acceptable variants). In the paper the following ideas will be presented – the idea of spatial processes polyoptimization, the methods for determining the collection and selection of compromise solutions, the methodology for determining polioptimum states of the space use, the possibility of using polyoptimization methods that are regarded as supporting decision-making tools in the planning and management of space with the use of GIS tools. The Authors will show the benefits of using the polyoptimization. The methods of formulating and solving problems which are related to selection of optimum way use of land will be delivered.
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Farhadi, Alireza, and MohammadTaghi Hajiaghayi. "On the Complexity of Chore Division." 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.2018/31.
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We study the proportional chore division problem where a protocol wants to divide an undesirable object, called chore, among n different players. This problem is the dual variant of the cake cutting problem in which we want to allocate a desirable object. In this paper, we show that chore division and cake cutting problems are closely related to each other and provide a tight lower bound for proportional chore division.
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Glotzer, Dylan, and Vladas Pipiras. "Statistical Perspectives on Some Problems Arising in Naval Engineering." In SNAME 30th American Towing Tank Conference. SNAME, 2017. http://dx.doi.org/10.5957/attc-2017-0047.
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This paper reviews several statistical problems arising in Naval Engineering that the authors were involved with professionally or at NSWCCD over the past several years. The considered problems relate to statistical uncertainty, characterizing rare events, and ocean modeling, and naturally involve a stochastic component which needs to be accounted for through statistical methods. In statistical uncertainty, for example, one problem consists of constructing confidence intervals for measured quantities of interest (e.g. the variance of a ship motion) when temporal dependence in a signal needs to be taken into account. In characterizing rare events (e.g. ship capsizing or broaching to), a common problem is to estimate their frequency, which can be carried out under the umbrella of the statistical Extreme Value Theory. In ocean modeling, spatiotemporal statistical modeling of significant wave height has attracted much attention, especially in the context of modern treatments of “big data.” The focus throughout this work is on the theoretical underpinnings of these statistical problems, related work in the Statistics literature, and some open future directions.
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Nakagawa, Kei, Shuhei Noma, and Masaya Abe. "RM-CVaR: Regularized Multiple β-CVaR Portfolio." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/629.
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The problem of finding the optimal portfolio for investors is called the portfolio optimization problem. Such problem mainly concerns the expectation and variability of return (i.e., mean and variance). Although the variance would be the most fundamental risk measure to be minimized, it has several drawbacks. Conditional Value-at-Risk (CVaR) is a relatively new risk measure that addresses some of the shortcomings of well-known variance-related risk measures, and because of its computational efficiencies, it has gained popularity. CVaR is defined as the expected value of the loss that occurs beyond a certain probability level (β). However, portfolio optimization problems that use CVaR as a risk measure are formulated with a single β and may output significantly different portfolios depending on how the β is selected. We confirm even small changes in β can result in huge changes in the whole portfolio structure. In order to improve this problem, we propose RM-CVaR: Regularized Multiple β-CVaR Portfolio. We perform experiments on well-known benchmarks to evaluate the proposed portfolio. Compared with various portfolios, RM-CVaR demonstrates a superior performance of having both higher risk-adjusted returns and lower maximum drawdown.
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Sevostyanov, Petr A., Tatyana A. Samoilova, and Maria L. Markova. "The method of adaptive random search for training the neural network." In INTERNATIONAL SCIENTIFIC-TECHNICAL SYMPOSIUM (ISTS) «IMPROVING ENERGY AND RESOURCE-EFFICIENT AND ENVIRONMENTAL SAFETY OF PROCESSES AND DEVICES IN CHEMICAL AND RELATED INDUSTRIES». The Kosygin State University of Russia, 2021. http://dx.doi.org/10.37816/eeste-2021-2-78-82.
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The issues of neural network training are considered. The authors have proposed and tested on problems of pattern recognition a global optimization algorithm, which is one of the variants of adaptive random search.
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"Dravet syndrome and Dravet-like phenotype: a systematic review of the SCN1A and PCDH19 variants." In XIII Congresso Paulista de Neurologia. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1516-3180.229.
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Background: Dravet syndrome (DS) is a rare and severe epileptic syndrome of childhood with a prevalence around 1/40,000 people worldwide. Approximately 80% of patients with DS present SCN1A pathogenic variants, which encodes an alpha subunit of a neural voltage- dependent sodium channel. SCN1A variants were also related to DS. There is a correlation between PCDH19 pathogenic variants, encodes the protocadherin 19, and a similar disease to DS known as DS-like phenotype. Objectives: To clarify the differences between DS and DS-like phenotype according to the SCN1A and PCDH19 variants. Methodology: A review from March/2019 to November/2020 was conducted in PubMed and VHL databases, following PRISMA criteria. Results: 19 studies were included and a significant proportion of patients with DS carrying SCN1A was greater than patients with DS-like phenotype harboring PCDH19 variants (76.6% vs. 23.4%). Considering SCN1A and PCDH19, 47 variants were pathogenic and 12 of uncertain significance; 25% were deletions and 75% were single- nucleotide variants. Autism was predominantly observed in patients with DS-like carrying PCDH19 variants compared to SCN1A variants carriers (62.5% vs. 37.5%, p=0.044). In addition, it was noticed a significant predisposition to hyperthermia during seizures in patients with variants in the PCDH19 (p=0.003). There was no significance differences between both groups and cognitive deficit, ataxia, behavior problems, and motor deficit. Conclusions: The study is the first to point out differences between the DS and DS-like phenotype according to the SCN1A and PCDH19 variants.
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Gobbi, Massimiliano. "Optimal and Robust Design of Ground Vehicle Systems." In ASME 8th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2006. http://dx.doi.org/10.1115/esda2006-95471.
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A new approach for the design of vehicle subsystems is addressed in the paper. The new approach is based not only on the theory of multi-objective optimisation but also on robust design. The method is characterised both by the optimisation of the objective functions (corresponding to system performance indices) and by the reduction (or minimisation) of the sensitivity (variance) of the performance indices to stochastic perturbations. Such variances are computed (very quickly) by means of an original procedure based on the global approximation of the objective functions. Additionally, with respect to the mentioned features, the new approach is based on both a special study to explore all of the feasible design solutions, and on a global sensitivity procedure to analyse (in a stochastic context) the influence of each design variable on each objective function. Pareto-optimal design solutions for different levels of “robustness” can be computed in a very short time. The optimisation method has been tested on a relatively simple problem and applied with successful results to a complex design problem related to vehicle design.
Reports on the topic "Relaxed problem variants"
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Woodson, William, Shimon Mayak, and Haim Rabinowitch. Physiological and Molecular Characterization of the Response to Ethylene during Senescence of Carnation Genotypic Variants. United States Department of Agriculture, July 1995. http://dx.doi.org/10.32747/1995.7613011.bard.
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The senescence of carnation (Dianthus caryophyllus L.) flowers is associated with increased production of the phytohormone ethylene, which in turn serves to initiate and regulate the processes involved in programmed petal death. We investigated the regulation of ethylene production and petal senescence in carnation. Several carnation genotypes were identified that exhibited extended vase-life in comparison to flowers from typical commercial cultivars. The capacity of these genotypes to produce ethylene during postharvest vase-life and to respond to exogenous ethylene was investigated. Several genotypes, represented by 'Sandrosa' and 87-37G produced little ethylene durig their postharvest vase-life and as a result failed to exhibit the symptoms (in-rolling and wilting) typical of flowers producing elevated levels of ethylene. These genotypes were further separated by their capacity to respond to exogenous ethylene by both increased ethylene synthesis and premature petal senescence. In one case a genotype (799) was identified that was not capable of responding to exogenous ethylene by either increased ethylene production or premature petal senescence. The regulation of ethylene production during petal senescence was investigated both at the enzyme and gene levels. A full length cDNA was identified for the petal senescence-related ACC synthase gene. Utilizing this, and other ethylene biosynthetic pathway cDNA probes, an increase in both ACC synthase and ACC oxidase mRNAs were detected following ethylene treatment. An increase in ACC oxidase mRNA and enzyme activity was detected within 2-3 h following ethylene treatment, indicating the expression of this gene is an early response to ethylene. An investigation into the expression of novel proteins during petal senescence revealed a number of polypeptides increased in abundance and possibly play a role in the regulation or biochemical processes of senescence. One polypeptide of 70 kDa was identified as being encoded by the previously characterized gene SR12 and possibly represents a b-galactosidase involved in the remobilization of carbohydrates during senescence.