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Articoli di riviste sul tema "High (effective) dimension"

Autore: Grafiati

Pubblicato: 26 ottobre 2024

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1

Li, Yehua, e Tailen Hsing. "Deciding the dimension of effective dimension reduction space for functional and high-dimensional data". Annals of Statistics 38, n. 5 (ottobre 2010): 3028–62. http://dx.doi.org/10.1214/10-aos816.

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2

Wang, Xiaoqun, e Ian H. Sloan. "Why Are High-Dimensional Finance Problems Often of Low Effective Dimension?" SIAM Journal on Scientific Computing 27, n. 1 (gennaio 2005): 159–83. http://dx.doi.org/10.1137/s1064827503429429.

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3

Susanto, Susanto, Deris Stiawan, M. Agus Syamsul Arifin, Mohd Yazid Idris e Rahmat Budiarto. "Effective and efficient approach in IoT Botnet detection". SINERGI 28, n. 1 (9 dicembre 2023): 31. http://dx.doi.org/10.22441/sinergi.2024.1.004.

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Internet of Things (IoT) technology presents an advantage to daily life, but this advantage is not a guarantee of security. This is because cyber-attacks, such as botnets, remain a threat to the user. Detection systems are one of the alternatives to maintain the security of IoT network. A reliable detection system should effectively detect botnets with high accuracy levels and low positive rate. It should be efficient to perform detection quickly. However, data generated by IoT networks have high dimensions and high scalability, so they need to be minimized. In network security analysis process, high-dimension data pose challenges, such as the dimension curse correlation between different dimensions, which causes features that are hard to define, datasets that are mostly unordered, cluster combination, and exponential growth. In this study, we applied feature reduction using the Linear Discriminant Analysis (LDA) method to minimize features on the IoT network to detect botnet. The reduction process is carried out on the N-BaIoT dataset which has 115 features reduced to 2 features. Performing feature reduction with detection systems has become more effective and efficient. Experimental result showed that the application of LDA combined with machine learning on the classification Decision Tree method was able to detect with accuracy that reached 100% in 98.58s with only two features.

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Ghosh, Swagata, Rashidul Islam e Anirban Kundu. "Scattering unitarity with effective dimension-6 operators". Journal of Physics G: Nuclear and Particle Physics 45, n. 1 (5 dicembre 2017): 015003. http://dx.doi.org/10.1088/1361-6471/aa9873.

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5

RODULFO, E., e R. DELBOURGO. "ONE-LOOP EFFECTIVE MULTIGLUON LAGRANGIAN IN ARBITRARY DIMENSIONS". International Journal of Modern Physics A 14, n. 28 (10 novembre 1999): 4457–71. http://dx.doi.org/10.1142/s0217751x99002086.

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We exhibit the one-loop multigluon effective Lagrangian in any dimension for a field theory with a quasilocal background, using the background-field formalism. Specific results, including counterterms (up to 12 space–time dimensions), have been derived, applied to the Yang–Mills theory and found to be in agreement with other string-inspired approaches.

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6

Lin, K. N., e P. Mantero. "Hypergraphs with high projective dimension and 1-dimensional hypergraphs". International Journal of Algebra and Computation 27, n. 06 (settembre 2017): 591–617. http://dx.doi.org/10.1142/s0218196717500291.

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(Dual) hypergraphs have been used by Kimura, Rinaldo and Terai to characterize squarefree monomial ideals [Formula: see text] with [Formula: see text], i.e. whose projective dimension equals the minimal number of generators of [Formula: see text] minus 1. In this paper, we prove sufficient and necessary combinatorial conditions for [Formula: see text]. The second main result is an effective explicit procedure to compute the projective dimension of a large class of 1-dimensional hypergraphs [Formula: see text] (the ones in which every connected component contains at most one cycle). An algorithm to compute the projective dimension is also provided. Applications of these results are given; they include, for instance, computing the projective dimension of monomial ideals whose associated hypergraph has a spanning Ferrers graph.

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7

Wuzhou Dong, Jingyan Cui, Haitao He e Jiadong Ren. "Clustering over High-Dimensional Data Streams Based on Grid Density and Effective Dimension". International Journal of Advancements in Computing Technology 3, n. 8 (30 settembre 2011): 154–62. http://dx.doi.org/10.4156/ijact.vol3.issue8.18.

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8

Wang, Shuang-xi, Hong-wei Ge, Jian-ping Gou, Wei-hua Ou, He-feng Yin e Shu-zhi Su. "Fusion of effective dimension reduction and discriminative dictionary learning for high-dimensional classification". Computers and Electrical Engineering 99 (aprile 2022): 107684. http://dx.doi.org/10.1016/j.compeleceng.2022.107684.

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9

Kim, Heetae, e Chang-Soo Park. "Generalized N-Dimensional Effective Temperature for Cryogenic Systems in Accelerator Physics". Quantum Beam Science 8, n. 3 (27 agosto 2024): 21. http://dx.doi.org/10.3390/qubs8030021.

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Investigations into the properties of generalized effective temperature are conducted across arbitrary dimensions. Maxwell–Boltzmann distribution is displayed for one, two, and three dimensions, with effective temperatures expressed for each dimension. The energy density of blackbody radiation is examined as a function of dimensionality. Effective temperatures for non-uniform temperature distributions in one, two, three, and higher dimensions are presented, with generalizations extended to arbitrary dimensions. Furthermore, the application of generalized effective temperature is explored not only for linearly non-uniform temperature distributions but also for scenarios involving the volume fraction of two distinct temperature distributions. The effective temperature is determined for a cryogenic system supplied with both liquid nitrogen and liquid helium. This effective temperature is applied to the Coefficient of Performance (COP) in cryogenic systems and can also be applied to high-energy accelerator physics, including high-dimensional physics.

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10

Nie, Boxin, e Xiaojia Ran. "A Linear Discriminant Analysis model based on Sliced Inverse Regression lifting". Highlights in Science, Engineering and Technology 103 (26 giugno 2024): 424–32. http://dx.doi.org/10.54097/07bdff79.

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Linear Discriminant Analysis is a dimension-reduction tool for high-dimensional data in the classical field of machine learning. However, for the binary classification problem in the case of high-dimensional prediction, the dimension of the dimension reduction space of the Linear Discriminant Analysis model cannot be greater than the number of categories, that is, it can only be reduced to one dimension, which will greatly lose the effective information of the original prediction variable for the response variable. Based on this, this paper proposes an improved Linear Discriminant Analysis model based on sufficient dimensionality reduction auxiliary slice. On the one hand, by using the Sliced Inverse Regression method, the proposed method can construct auxiliary slice response variables without losing any effective information about the response variables; On the other hand, this method can increase the number of reduced dimensions of the reduced dimension space to any dimension not greater than the number of slices. The analysis results of simulated data and real data show that the proposed method is more accurate and robust than the classical Linear Discriminant Analysis model.

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11

CLARK, T. E., e S. T. LOVE. "THE EFFECTIVE POTENTIAL AND ADDITIONAL LARGE RADIUS COMPACTIFIED SPACE–TIME DIMENSIONS". International Journal of Modern Physics A 15, n. 31 (20 dicembre 2000): 4933–42. http://dx.doi.org/10.1142/s0217751x00002238.

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The consequences of large radius extra space–time compactified dimensions on the four-dimensional one-loop effective potential are investigated for a model which includes scalar self interactions and Yukawa coupling to fermions. The Kaluza–Klein tower of states associated with the extra compact dimensions shifts the location of the effective potential minimum and modifies its curvature. The dependence of these effects on the radius of the extra dimension is illustrated for various choices of coupling constants and masses. For large radii, the consequence of twisting the fermion boundary condition on the compactified dimensions is numerically found to produce but a negligible effect on the effective potential.

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12

Patel, Damodar, e Amit Kumar Saxena. "Feature Selection in High Dimension Datasets using Incremental Feature Clustering". Indian Journal Of Science And Technology 17, n. 32 (24 agosto 2024): 3318–26. http://dx.doi.org/10.17485/ijst/v17i32.2077.

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Objectives: To develop a machine learning-based model to select the most important features from a high-dimensional dataset to classify the patterns at high accuracy and reduce their dimensionality. Methods: The proposed feature selection method (FSIFC) forms and combines feature clusters incrementally and produces feature subsets each time. The method uses K-means clustering and Mutual Information (MI) to refine the feature selection process iteratively. Initially, two clusters of features are formed using K-means clustering (K=2) by taking features as the basis of clustering instead of taking the patterns (a traditional way). From these two clusters, the features with the highest MI value in each cluster are kept in a feature subset. Classification accuracies (CA) of the feature subset are calculated using three classifiers namely Support Vector Machines (SVM), Random Forest (RF), and k-nearest Neighbor (knn). The process is repeated by incrementing the value of K i.e. number of clusters; until a maximum user-defined value of K is reached. The best value of CA obtained from these trials is recorded and the corresponding feature set is finally accepted. Findings: The proposed method is demonstrated using ten datasets and the results are compared with the existing published results using three classifiers to determine the method's performance. The ten datasets are classified with average CAs of 92.72%, 93.13%, and 91.5%, using the SVM, RF, and K-NN classifiers respectively. The proposed method selects a maximum of thirty features from the datasets. In terms of selecting the most effective and the smallest feature sets, the proposed method outperforms eight other feature selection methods considering CAs. Novelty: The proposed model applies feature reduction using combined feature clustering and filter methods in an incremental way. This provides an improved selection of relevant features while removing those which are irrelevant at different trials. Keywords: Feature selection, High-dimensional datasets, K-means algorithm, Mutual information, Machine learning

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MOUNT, JOHN. "Fast Unimodular Counting". Combinatorics, Probability and Computing 9, n. 3 (maggio 2000): 277–85. http://dx.doi.org/10.1017/s0963548300004193.

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This paper describes methods for counting the number of nonnegative integer solutions of the system Ax = b when A is a nonnegative totally unimodular matrix and b an integral vector of fixed dimension. The complexity (under a unit cost arithmetic model) is strong in the sense that it depends only on the dimensions of A and not on the size of the entries of b. For the special case of ‘contingency tables’ the run-time is 2O(√dlogd) (where d is the dimension of the polytope). The method is complementary to Barvinok's in that our algorithm is effective on problems of high dimension with a fixed number of (non-sign) constraints, whereas Barvinok's algorithms are effective on problems of low dimension and an arbitrary number of constraints.

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14

SUZUKI, HIROSHI. "RENORMALON'S CONTRIBUTION TO EFFECTIVE COUPLINGS". Modern Physics Letters A 13, n. 31 (10 ottobre 1998): 2551–58. http://dx.doi.org/10.1142/s0217732398002710.

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When an asymptotically non-free theory possesses a mass parameter independent of the Λ parameter, the uv renormalon gives rise to nonperturbative contributions, to dimension-four operators and dimensionless couplings, thus has a "dual" effect of the instanton. We illustrate this phenomenon in O(N) symmetric massive λϕ4 model in the 1/N expansion. This effect of uv renormalon is briefly compared with nonperturbative corrections in the magnetic picture of the Seiberg–Witten theory.

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Rima Nurmalah, Muhibudin Wijaya Laksana e Hilma Mutiara Winata. "Pengaruh Inovasi Pada Aplikasi Access by KAI Terhadap Kualitas Pelayanan". PUBLIKA : Jurnal Ilmu Administrasi Publik 10, n. 1 (30 aprile 2024): 137–49. http://dx.doi.org/10.25299/jiap.2024.16859.

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Innovation in the Access by KAI application aims to provide better services to the public. However, this innovation encounters several issues such as limited technological access by the public, policy non-inclusivity, and lack of effectiveness in socialization efforts. Therefore, this study aims to investigate the impact of innovation in the Access by KAI application on service quality. Additionally, it aims to determine the effective contribution of innovation dimensions in the Access by KAI application to service quality. This research utilizes an associative method with a quantitative approach. Data was collected through observation and questionnaire results, while data analysis employed robust M-estimation regression. The results indicate that the quality of public service innovation is very high, and the quality of m-service is high. Furthermore, public service innovation obtains significant variable coefficient values at a significant level (α=0.05). This is indicated by the p-value of the public service innovation variable being 0.000<0.05, showing the influence of public service innovation on m-service quality in the Access by KAI application. The effective contribution of each dimension of public service innovation to m-service quality is as follows: relative advantage dimension 0.48%, compatibility dimension 29.03%, complexity dimension 14.22%, testability dimension 9.83%, and observability dimension 8.39%.

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MIRZA, B., e M. ZAREI. "EFFECTIVE FIELD THEORY OF A LOCALLY NONCOMMUTATIVE SPACE–TIME AND EXTRA DIMENSIONS". International Journal of Modern Physics A 23, n. 16n17 (10 luglio 2008): 2613–33. http://dx.doi.org/10.1142/s0217751x08039529.

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We assume that the noncommutativity starts to be visible continuously from a scale ΛNC. According to this assumption, a two-loop effective action is derived for noncommutative ϕ4 and ϕ3 theories from a Wilsonian point of view. We show that these effective theories are free of UV/IR mixing phenomena. We also investigate the positivity constraint on coefficients of higher dimension operators present in the effective theory. This constraint makes the low energy theory to be UV completion of a full theory. Finally, we discuss noncommutativity and extra dimensions. In our effective theories formulated on noncommutative extra dimensions, if the campactification scale Λc is less than the scale ΛNC, the theory will not suffer from UV/IR mixing.

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Badakhshan Farahabadi, Fazel, Kianoush Fathi Vajargah e Rahman Farnoosh. "Dimension Reduction Big Data Using Recognition of Data Features Based on Copula Function and Principal Component Analysis". Advances in Mathematical Physics 2021 (11 luglio 2021): 1–8. http://dx.doi.org/10.1155/2021/9967368.

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Nowadays, data are generated in the world with high speed; therefore, recognizing features and dimensions reduction of data without losing useful information is of high importance. There are many ways to dimension reduction, including principal component analysis (PCA) method, which is by identifying effective dimensions in an acceptable level, reducing dimension of data. In the usual method of principal component analysis, data are usually normal, or we normalize data; then, the principal component analysis method is used. Many studies have been done on the principal component analysis method as a step of data preparation. In this paper, we propose a method that improves the principal component analysis method and makes data analysis easier and more efficient. Also, we first identify the relationships between the data by fitting the multivariate copula function to data and simulate new data using the estimated parameters; then, we reduce the dimensions of new data by principal component analysis method; the aim is to improve the performance of the principal component analysis method to find effective dimensions.

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Jana, Sudip, e S. Nandi. "New physics scale from Higgs observables with effective dimension-6 operators". Physics Letters B 783 (agosto 2018): 51–58. http://dx.doi.org/10.1016/j.physletb.2018.06.038.

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Silva, Marcos Eugênio da, e Thierry Barbe. "Quasi-Monte Carlo in finance: extending for problems of high effective dimension". Economia Aplicada 9, n. 4 (dicembre 2005): 577–94. http://dx.doi.org/10.1590/s1413-80502005000400004.

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ILTAN, E. O. "ANNIHILATION CROSS SECTIONS AND INTERACTION COUPLINGS OF THE DARK MATTER CANDIDATES IN THE WARPED AND FLAT EXTRA DIMENSIONS". Modern Physics Letters A 25, n. 14 (10 maggio 2010): 1187–97. http://dx.doi.org/10.1142/s0217732310032421.

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We consider a scenario with an additional scalar standard model singlet ϕS, living in a single extra dimension of the RS1 background. The zero mode of this scalar which is localized in the extra dimension is a dark matter candidate and the annihilation cross section is strongly sensitive to its localization parameter. As a second scenario, we assume that the standard model Higgs field is accessible to the fifth flat extra dimension. At first we take the additional standard model singlet scalar field as accessible to the sixth extra dimension and its zero mode is a possible dark matter candidate. Second, we consider that the new standard model singlet, the dark matter candidate, lives in four dimensions. In both choices the KK modes of the standard model Higgs field play an observable role for the large values of the compactification radius R and the effective coupling λS is of the order of 10-2–10-1 (10-6) far from (near to) the resonant annihilation.

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Cea, Paolo, e Luigi Tedesco. "Generalized Gaussian Effective Potential: Second-Order Thermal Corrections". Modern Physics Letters A 12, n. 15 (20 maggio 1997): 1077–85. http://dx.doi.org/10.1142/s0217732397001096.

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We discuss the finite temperature generalized Gaussian effective potential. We put out a very simple relation between the thermal corrections to the generalized Gaussian effective potential and those of the effective potential. We evaluate explicitly the second-order thermal corrections in the case of the self-interacting scalar field in one spatial dimension.

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Mikaeili, Alireza, Alireza Ghorbani, Vahid Babaei Agha Maleki – Poyan Ali, Abbas Zadeh e Mahmood Omrani. "Examining Effect of Organizational Structure Dimensions on the Knowledge management (Case Study: Payame Noor Universities of Semnan Province)". Environment Conservation Journal 16, SE (5 dicembre 2015): 347–55. http://dx.doi.org/10.36953/ecj.2015.se1640.

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Transferring and understanding high volume of information and knowledge in organizations are affective internal and external factors. One of the effective internal factors on the knowledge management in organizational activities are divided, organized and coordinated. Organizations have created structures to coordinate factors of doing task and to control acts of members. In this research, structural Equation Method (SEM) is used for examining whether organizational structure dimensions have positive effect on knowledge management in Payame Noor organization in Lorestan province or not. Results of the research showed that there is direct and significant relationship between complexity dimension and knowledge management, formality dimension and knowledge management and centralization dimension and knowledge management. This means that the more complexity, formality and centralization dimensions, the more knowledge management effect in the organization.

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23

Fox, Shaul, Aharon Bizman e Anat Garti. "Is Distributional Appraisal More Effective than the Traditional Performance Appraisal Method?" European Journal of Psychological Assessment 21, n. 3 (gennaio 2005): 165–72. http://dx.doi.org/10.1027/1015-5759.21.3.165.

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Abstract. This study compared the distributional appraisal method (DAM) with the traditional appraisal method (TAM) on seven criteria reflecting appraisal effectiveness: Four interrater agreement measures, calculated by Cronbach's formulas, and three measures of differentiation: Ratee and dimension differentiation, and leniency. The study took place in a software company, where 45 participants, working in teams, rated all their team members on eight dimensions, both by DAM and TAM. DAM mean scores exhibited stronger agreement than TAM scores on two Cronbach's interrater agreement measures - stereotype accuracy and differential accuracy. High inverse correlations were found between measures of agreement and differentiation. The study demonstrates that DAM and TAM differ in their effectiveness and that criteria for rating effectiveness may be inversely related.

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OSAKA, MOTOHISA, e NOBUYASU ITO. "LOCAL BOX-COUNTING TO DETERMINE FRACTAL DIMENSION OF HIGH-ORDER CHAOS". International Journal of Modern Physics C 11, n. 08 (dicembre 2000): 1519–26. http://dx.doi.org/10.1142/s0129183100001474.

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To determine the attractor dimension of chaotic dynamics, the box-counting method has the difficulty in getting accurate estimates because the boxes are not weighted by their relative probabilities. We present a new method to minimize this difficulty. The local box-counting method can be quite effective in determining the attractor dimension of high-order chaos as well as low-order chaos.

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Soltani, Nahid, Parivash Jafari, Mehdi Bagheri e Nader Gholi Ghorchian. "A Model of Satisfaction Promotion for Students of Hormozgan University of Medical Sciences in Iran". Hormozgan Medical Journal 26, n. 1 (29 marzo 2022): 42–49. http://dx.doi.org/10.34172/hmj.2022.08.

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Background: Universities of medical sciences, as organizations that ensure the progress of society in the fields of health, treatment, and medical education, have been considered in many ways. The first important goal in these universities is student satisfaction and promotion strategies. Therefore, in this study we presented a model of satisfaction promotion among the students of Hormozgan University of Medical Sciences, Iran. Methods: The population of this applied quantitative research included students of Hormozgan University of Medical Sciences. A total of 380 people were selected by multi-stage cluster sampling. The data collection tool included a researcher-made questionnaire whose validity and reliability were confirmed. Decision making trial and evaluation laboratory (DEMATEL) method, importance-performance analysis (IPA), as well as MATLAB and Excel software were used for quantitative data analysis. Results: The results of IPA showed that the research dimension was of great importance for students and the performance of the university was appropriate in this dimension. Welfare and management dimensions were of little importance, but the performance of the university was high in these dimensions. The administrative component of this dimension was not very important and the university’s performance was not good in it. The support services dimension was very important for students’ satisfaction but the performance of the university was at a low level. As a result, support services had the highest priority for improvement and the welfare, managerial, educational, research and administrative dimensions were in the next ranks for improvement, respectively. The results of causal relationships between dimensions showed that the managerial dimension had the most interaction (impact and effectiveness), followed by research, welfare, education, supportive, and administrative dimensions. The management dimension was the most effective one. According to R-J values, educational and research dimensions were the most effective dimensions, respectively. Conclusion: The results of the present study showed that university policy-makers and administrators need to recognize the basic needs of students in various fields such as education, research, welfare, etc. before taking policy actions, decision-making, and future orientations.

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Tolley, Andrew J., Clifford P. Burgess, Doug Hoover e Yashar Aghababaie. "Bulk singularities and the effective cosmological constant for higher co-dimension branes". Journal of High Energy Physics 2006, n. 03 (29 marzo 2006): 091. http://dx.doi.org/10.1088/1126-6708/2006/03/091.

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González-Laguna, María Victoria, Raquel Fidalgo, Paula López e Gert Rijlaarsdam. "A Review of Effective Technology-Based Writing Interventions: A Componential Analysis". Sustainability 16, n. 9 (28 aprile 2024): 3703. http://dx.doi.org/10.3390/su16093703.

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Previous studies have shown the effectiveness of ICT-based writing instructional practices, but they do not show an in-depth analysis of their instructional elements, which could be key to explaining such effectiveness. This study aims to analyze the instructional design of effective ICT-based writing practices according to content and instructional dimensions. An empirical review was performed following the PRISMA statement guidelines with a sample of 22 studies. For the content dimension, learning objectives were coded in terms of target focus, subject-specific knowledge, and learning outcomes. For the instructional dimension, types of learning and instructional activities were coded, identifying their specific elements. Results showed that learning objectives were mostly focused on practice/internalization of high-level processes. Regarding learning activities, ICT was mainly used in practicing/applying, structuring, and observing/noting activities. Regarding instructional activities, application and demonstration principles appeared most frequently in the interventions, with application activities being most frequently performed by ICTs. Product-focused and corrective types of feedback, as well as static and procedural scaffolding types, were the most frequently performed using ICT. In conclusion, this study provides useful information on what writing activities can be performed using ICT and provide the basis for future studies analyzing to what extent these activities contribute to program effectiveness.

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Jiang, Chung-Li. "Effective recursive algorithm for judging the positive-definiteness of matrices of high dimension". International Journal of Control 47, n. 2 (1 febbraio 1988): 657–60. http://dx.doi.org/10.1080/00207178808906040.

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Amit, S. N. K., S. Saito, S. Sasaki, Y. Kiyoki e Y. Aoki. "SEMANTIC SEGMENTATION AND DIFFERENCE EXTRACTION VIA TIME SERIES AERIAL VIDEO CAMERA AND ITS APPLICATION". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W3 (30 aprile 2015): 1119–22. http://dx.doi.org/10.5194/isprsarchives-xl-7-w3-1119-2015.

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Google earth with high-resolution imagery basically takes months to process new images before online updates. It is a time consuming and slow process especially for post-disaster application. The objective of this research is to develop a fast and effective method of updating maps by detecting local differences occurred over different time series; where only region with differences will be updated. In our system, aerial images from Massachusetts’s road and building open datasets, Saitama district datasets are used as input images. Semantic segmentation is then applied to input images. Semantic segmentation is a pixel-wise classification of images by implementing deep neural network technique. Deep neural network technique is implemented due to being not only efficient in learning highly discriminative image features such as road, buildings etc., but also partially robust to incomplete and poorly registered target maps. Then, aerial images which contain semantic information are stored as database in 5D world map is set as ground truth images. This system is developed to visualise multimedia data in 5 dimensions; 3 dimensions as spatial dimensions, 1 dimension as temporal dimension, and 1 dimension as degenerated dimensions of semantic and colour combination dimension. Next, ground truth images chosen from database in 5D world map and a new aerial image with same spatial information but different time series are compared via difference extraction method. The map will only update where local changes had occurred. Hence, map updating will be cheaper, faster and more effective especially post-disaster application, by leaving unchanged region and only update changed region.

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Wang, Junpeng, Xiaotong Liu e Han-Wei Shen. "High-dimensional data analysis with subspace comparison using matrix visualization". Information Visualization 18, n. 1 (14 ottobre 2017): 94–109. http://dx.doi.org/10.1177/1473871617733996.

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Due to the intricate relationship between different dimensions of high-dimensional data, subspace analysis is often conducted to decompose dimensions and give prominence to certain subsets of dimensions, i.e. subspaces. Exploring and comparing subspaces are important to reveal the underlying features of subspaces, as well as to portray the characteristics of individual dimensions. To date, most of the existing high-dimensional data exploration and analysis approaches rely on dimensionality reduction algorithms (e.g. principal component analysis and multi-dimensional scaling) to project high-dimensional data, or their subspaces, to two-dimensional space and employ scatterplots for visualization. However, the dimensionality reduction algorithms are sometimes difficult to fine-tune and scatterplots are not effective for comparative visualization, making subspace comparison hard to perform. In this article, we aggregate high-dimensional data or their subspaces by computing pair-wise distances between all data items and showing the distances with matrix visualizations to present the original high-dimensional data or subspaces. Our approach enables effective visual comparisons among subspaces, which allows users to further investigate the characteristics of individual dimensions by studying their behaviors in similar subspaces. Through subspace comparisons, we identify dominant, similar, and conforming dimensions in different subspace contexts of synthetic and real-world high-dimensional data sets. Additionally, we present a prototype that integrates parallel coordinates plot and matrix visualization for high-dimensional data exploration and incremental dimensionality analysis, which also allows users to further validate the dimension characterization results derived from the subspace comparisons.

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Wang, Hu. "Clustering statistical method of high dimensional sparse data based on fuzzy data". Journal of Physics: Conference Series 2791, n. 1 (1 luglio 2024): 012060. http://dx.doi.org/10.1088/1742-6596/2791/1/012060.

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Abstract Developing effective clustering and statistical methods for high-dimensional sparse data presents unique challenges compared to traditional low-dimensional data. To address this, a novel approach is proposed, leveraging fuzzy data principles to enhance the clustering and statistical performance of high-dimensional sparse datasets. The method builds upon the fuzzy C-means clustering algorithm, introducing key modifications for better suitability to high-dimensional sparse data. One crucial enhancement involves tackling the local optimization problem by optimizing the initial clustering center, significantly reducing clustering statistical time. Replacing the original Euclidean distance with cosine distance improves the clustering and statistical performance of high-dimensional sparse data. Experimental results have shown that this method has superior clustering statistical performance when the data dimensions are different. When the data dimension is low, and the blocking ratio is 10%, the clustering statistical effect is optimal. When the data dimension is high, and the blocking ratio is 40%, the clustering statistical effect is optimal. This method has higher hit rates and clustering statistical efficiency at different sparsity levels.

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Tsai, Pei-Hsuan, Chih-Jou Chen e Jia-Wei Tang. "Key Factors Influencing Talent Retention and Turnover in Convenience Stores: A Comparison of Managers’ and Employees’ Perspectives". SAGE Open 11, n. 4 (ottobre 2021): 215824402110672. http://dx.doi.org/10.1177/21582440211067240.

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This study identifies the main factors influencing turnover among convenience store employees from a managerial perspective and infers the changes necessary to reduce such high turnover rates. Employing the decision-making trial and evaluation laboratory (DEMATEL) methodology, it investigates the degree of mutual influence between evaluation indicators and constructs a network relation map for evaluation dimensions and criteria. This study also uses the DEMATEL-based analytic network process method to compute the influential weights of each dimension and criteria. According to the empirical results of the causality model, convenience store employees must first improve the relatedness dimension, and managers must first improve the existence dimension. These findings can help convenience store managers address talent retention and turnover problems, develop effective strategies to lower the high turnover rates at convenience stores, and offer solutions to new industry entrants to avoid potential problems that might lead to early exit.

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Shokri, Alireza Rangriz, Tayfun Babadagli e Alireza Jafari. "A Critical Analysis of the Relationship Between Statistical- and Fractal-Fracture-Network Characteristics and Effective Fracture-Network Permeability". SPE Reservoir Evaluation & Engineering 19, n. 03 (13 giugno 2016): 494–510. http://dx.doi.org/10.2118/181743-pa.

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Summary Estimation of effective fracture-network permeability (EFNP) is an essential part of modeling transport processes in naturally fractured reservoirs. A practical way of doing this is to use correlations that consider the statistical and physical characteristics of the networks. Thus, selection of the proper parameters to be characterized and/or measured that are highly correlative to the network permeability is critical. In this study, we analyzed fractal-based correlations previously developed by Jafari and Babadagli (2011a, 2011b) to clarify the physical relationship among network properties and the correlation parameters. It was shown that the connectivity index is a more-powerful parameter to rely on in permeability estimation, especially at percolation ranges far from the threshold. Also, it was of high interest to inspect the effect of physical parameters of a fracture network on different fractal dimensions as well as their positive/negative correlation with permeability to make a distinction between the mathematical and physical contributions of variables. We explained the earlier observation of Jafari and Babadagli (2009) regarding the method to determine fractal dimensions and their observed differences, which were found to be related to the computational scheme. That is why the box-counting fractal dimension gives the highest correlation compared with other fractal dimensions, especially the sandbox fractal dimension. The conditions of a strong correlation among different fractal dimensions and the scale-dependency of correlations in natural and synthetic patterns were also addressed.

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DAVIS, SIMON. "BOUNDARY EFFECTS IN STRING THEORY AND THE EFFECTIVE STRING COUPLING". Modern Physics Letters A 23, n. 23 (30 luglio 2008): 1921–27. http://dx.doi.org/10.1142/s0217732308027266.

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The effect of the ideal boundaries of infinite-genus surfaces and Dirichlet boundaries on the value of the string coupling is evaluated. It is demonstrated that the value coincides with the unified gauge coupling and it is not altered by the inclusion of curved four-dimensional spacetimes in the path integral for quantum gravity or boundaries with fractional dimension and nonzero harmonic measure.

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35

Chakrabortty, Joydeep, Shakeel Ur Rahaman e Kaanapuli Ramkumar. "One-loop effective action up to dimension eight: Integrating out heavy fermion(s)". Nuclear Physics B 1000 (marzo 2024): 116488. http://dx.doi.org/10.1016/j.nuclphysb.2024.116488.

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36

Tan, Yunliang, Dongmei Huang e Ze Zhang. "Rock Mechanical Property Influenced by Inhomogeneity". Advances in Materials Science and Engineering 2012 (2012): 1–9. http://dx.doi.org/10.1155/2012/418729.

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In order to identify the microstructure inhomogeneity influence on rock mechanical property, SEM scanning test and fractal dimension estimation were adopted. The investigations showed that the self-similarity of rock microstructure markedly changes with the scanned microscale. Different rocks behave in different fractal dimension variation patterns with the scanned magnification, so it is conditional to adopt fractal dimension to describe rock material. Grey diabase and black diabase have high suitability; red sandstone has low suitability. The suitability of fractal-dimension-describing method for rocks depends on both investigating scale and rock type. The homogeneities of grey diabase, black diabase, grey sandstone, and red sandstone are 7.8, 5.7, 4.4, and 3.4, separately; their average fractal dimensions of microstructure are 2.06, 2.03, 1.72, and 1.40 correspondingly, so the homogeneity is well consistent with fractal dimension. For rock material, the stronger brittleness is, the less profile fractal dimension is. In a sense, brittleness is an image of rock inhomogeneity in macroscale, while profile fractal dimension is an image of rock inhomogeneity in microscale. To combine the test of brittleness with the estimation of fractal dimension with condition will be an effective approach for understanding rock failure mechanism, patterns, and behaviours.

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KAR, SUPRIYA K., S. PRATIK KHASTGIR e ALOK KUMAR. "AN ALGORITHM TO GENERATE CLASSICAL SOLUTIONS OF STRING EFFECTIVE ACTION". Modern Physics Letters A 07, n. 17 (7 giugno 1992): 1545–51. http://dx.doi.org/10.1142/s021773239200121x.

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It is shown explicitly that a number of solutions for the background field equations of the string effective action in space-time dimension D can be generated from any known lower dimensional solution when background fields have only time dependence. An application of the result to the two-dimensional charged black hole is presented. The case of background with more general coordinate dependence is also discussed.

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38

Desnawati, Fera, Amali Putra, Gusnedi e Hidayati. "CONSEPTUAL MODEL APPLICATION OF KNOWLEDGE DIMENSION COMPLEXITY AND COGNITIVE PROCESS LEVEL IN STATIC FLUID MATERIALS IN HIGH SCHOOL PHYSICS LEARNING". PILLAR OF PHYSICS EDUCATION 15, n. 2 (25 luglio 2022): 161. http://dx.doi.org/10.24036/12127171074.

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Abstract (sommario):

The 2013 curriculum requires the implementation of learning activities by referring to the Bloom classification revised by Anderson and Krathwohl (2001), which combines knowledge dimensions and cognitive process levels. However, the complexity of the knowledge dimension and the realization of the cognitive processing level in static fluid materials have not been optimally realized. This research aims to establish a conceptual model of the complexity of the knowledge dimension and cognitive process level of static fluid materials in high school physics learning. The type of research is R&D research using the ADDIE development method, which is reduced to the development stage. The subjects were 3 lecturers from FMIPA UNP in the Department of Physics and 3 physics teachers from Merangin Regency State High School, including SMAN 3, 6, and 17 Merangin. The object is learning tools (RPP, teaching materials, and evaluation instruments) oriented to knowledge dimension and cognitive process level in static fluid materials in high school physics learning. The expert group's research and application results on the knowledge dimension complexity and cognitive process hierarchical conceptual model composed of teaching plans, teaching materials, and evaluation tools were 0.71, and the practitioner group was 0.87. The average result of the degree of learning device verification value is 0.79, so it can be classified as effective and practical to test the effectiveness and practicality of this field.

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HASEGAWA, Takuma, Yasuharu TANAKA e Makoto NISHIGAKI. "AN EVALUATION METHOD ON EFFECTIVE POROSITY AND FLOW DIMENSION BY HIGH VISCOSITY FLUID INJECTION". Doboku Gakkai Ronbunshuu C 63, n. 1 (2007): 163–73. http://dx.doi.org/10.2208/jscejc.63.163.

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40

Hasgall, Alon E., e Snunith Shoham. "Effective use of digital applications promotes professional self-efficacy". VINE 45, n. 2 (11 maggio 2015): 279–91. http://dx.doi.org/10.1108/vine-06-2014-0038.

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Purpose – This paper aims to investigate the relationship between the use of digital applications (DAs) in the daily life of organizational workers, and the workers’ professional self-efficacy. Design/methodology/approach – A hypothesis was tested that the digital literacy of organizational workers is positively correlated with their professional self-efficacy. To test the hypothesis, 300 Israeli organizational workers filled online questionnaires that assessed their daily pattern of DA usage (both during and after working hours) and their self-perceived professional efficacy. A linear regression analysis was performed to identify correlations between the frequency (one dimension) and effectiveness (three dimensions) of DA usage and the workers’ self-perceived professional efficacy (three dimensions). Findings – The three dimensions of the DA usage effectiveness (diversity of the DA used, diversity of the means and ease of access to the DA) were significantly and positively correlated with all three dimensions of professional self-efficacy (functional autonomy, work effectiveness and personal knowledge sharing). In contrast, the frequency of DA usage was not correlated with any of the three dimensions of professional self-efficacy. Practical implications – High digital literacy allows rapid and effective retrieval of specific networked content and an accessible means of multimedia communication. According to the ecological model of organizational knowledge management, knowledge develops through diverse interactions between workers and through their ability to retrieve and share knowledge. The findings of this study support this model and indicate that high digital literacy, manifested through easy access and diverse use of DA, increases professional self-efficacy and knowledge sharing and, thereby, the stability of the organization. Managers should thus encourage workers’ digital literacy by allowing convenient access to a wide range of DA, both during and after working hours, to increase the organizational ability to adapt to complex and rapidly changing environments. Originality/value – DA are innovative tools that were only recently developed. This is the first study to characterize the relationship between the use of DA in daily life and the vocational behavior of organizational workers.

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41

Bern, Zvi, Julio Parra-Martinez e Eric Sawyer. "Structure of two-loop SMEFT anomalous dimensions via on-shell methods". Journal of High Energy Physics 2020, n. 10 (ottobre 2020). http://dx.doi.org/10.1007/jhep10(2020)211.

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Abstract We describe on-shell methods for computing one- and two-loop anomalous dimensions in the context of effective field theories containing higher-dimension operators. We also summarize methods for computing one-loop amplitudes, which are used as inputs to the computation of two-loop anomalous dimensions, and we explain how the structure of rational terms and judicious renormalization scheme choices can lead to additional vanishing terms in the anomalous dimension matrix at two loops. We describe the two-loop implications for the Standard Model Effective Field Theory (SMEFT). As a by-product of this analysis we verify a variety of one-loop SMEFT anomalous dimensions computed by Alonso, Jenkins, Manohar and Trott.

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42

Catani, Stefano, Daniel de Florian, Simone Devoto, Massimiliano Grazzini e Javier Mazzitelli. "Soft-gluon effective coupling: perturbative results and the large-nF limit to all orders". Journal of High Energy Physics 2023, n. 11 (29 novembre 2023). http://dx.doi.org/10.1007/jhep11(2023)217.

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Abstract We consider extensions of the soft-gluon effective coupling that generalize the Catani-Marchesini-Webber (CMW) coupling in the context of soft-gluon resummation beyond the next-to-leading logarithmic accuracy. Starting from the probability density of correlated soft emission in d dimensions we introduce a class of soft couplings relevant for resummed QCD calculations of hard-scattering observables. We show that at the conformal point, where the d-dimensional QCD β function vanishes, all these effective couplings are equal and they are also equal to the cusp anomalous dimension. We present explicit results in d dimensions for the soft-emission probability density and the soft couplings at the second-order in the QCD coupling αS. In d = 4 dimensions we obtain the explicit relation between the soft couplings at $$ \mathcal{O} $$ O ($$ {\alpha}_{\textrm{S}}^3 $$ α S 3 ). Finally, we study the structure of the soft coupling in the large-nF limit and we present explicit expressions to all orders in perturbation theory. We also check that, at the conformal point, our large-nF results agree with the known result of the cusp anomalous dimension.

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43

Huang, Xiaoyang, e Andrew Lucas. "Hydrodynamic effective field theories with discrete rotational symmetry". Journal of High Energy Physics 2022, n. 3 (marzo 2022). http://dx.doi.org/10.1007/jhep03(2022)082.

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Abstract We develop a hydrodynamic effective field theory on the Schwinger-Keldysh contour for fluids with charge, energy, and momentum conservation, but only discrete rotational symmetry. The consequences of anisotropy on thermodynamics and first-order dissipative hydrodynamics are detailed in some simple examples in two spatial dimensions, but our construction extends to any spatial dimension and any rotation group (discrete or continuous). We find many possible terms in the equations of motion which are compatible with the existence of an entropy current, but not with the ability to couple the fluid to background gauge fields and vielbein.

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Miró, Joan Elias, James Ingoldby e Marc Riembau. "EFT anomalous dimensions from the S-matrix". Journal of High Energy Physics 2020, n. 9 (settembre 2020). http://dx.doi.org/10.1007/jhep09(2020)163.

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Abstract We use the on-shell S-matrix and form factors to compute anomalous dimensions of higher dimension operators in the Standard Model Effective Field Theory. We find that in many instances, these computations are made simple by using the on-shell method. We first compute contributions to anomalous dimensions of operators at dimension-six that arise at one-loop. Then we calculate two-loop anomalous dimensions for which the corresponding one-loop contribution is absent, using this powerful method.

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Qian, Hong, e Yang Yu. "Solving High-Dimensional Multi-Objective Optimization Problems with Low Effective Dimensions". Proceedings of the AAAI Conference on Artificial Intelligence 31, n. 1 (12 febbraio 2017). http://dx.doi.org/10.1609/aaai.v31i1.10664.

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Abstract (sommario):

Multi-objective (MO) optimization problems require simultaneously optimizing two or more objective functions. An MO algorithm needs to find solutions that reach different optimal balances of the objective functions, i.e., optimal Pareto front, therefore, high dimensionality of the solution space can hurt MO optimization much severer than single-objective optimization, which was little addressed in previous studies. This paper proposes a general, theoretically-grounded yet simple approach ReMO, which can scale current derivative-free MO algorithms to the high-dimensional non-convex MO functions with low effective dimensions, using random embedding. We prove the conditions under which an MO function has a low effective dimension, and for such functions, we prove that ReMO possesses the desirable properties of optimal Pareto front preservation, time complexity reduction, and rotation perturbation invariance. Experimental results indicate that ReMO is effective for optimizing the high-dimensional MO functions with low effective dimensions, and is even effective for the high-dimensional MO functions where all dimensions are effective but most only have a small and bounded effect on the function value.

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46

Matsumoto, Minoru, e Yu Nakayama. "Dilaton invading from infinitesimal extra dimension". Modern Physics Letters A, 25 maggio 2022. http://dx.doi.org/10.1142/s0217732322500808.

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We show that the Wess–Zumino action for the spontaneously broken Weyl (or conformal) symmetry, a.k.a dilaton effective action, in even [Formula: see text] dimensions can be obtained from the Kaluza–Klein dimensional reduction of the Lovelock action in [Formula: see text] dimensions by taking the [Formula: see text] limit, where the dilaton is identified with the metric in the extra dimension. The construction gives an explicit form of the dilaton effective action in any even dimensions.

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47

Trott, Timothy. "Causality, unitarity and symmetry in effective field theory". Journal of High Energy Physics 2021, n. 7 (luglio 2021). http://dx.doi.org/10.1007/jhep07(2021)143.

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Abstract (sommario):

Abstract Sum rules in effective field theories, predicated upon causality, place restrictions on scattering amplitudes mediated by effective contact interactions. Through unitarity of the S-matrix, these imply that the size of higher dimensional corrections to transition amplitudes between different states is bounded by the strength of their contributions to elastic forward scattering processes. This places fundamental limits on the extent to which hypothetical symmetries can be broken by effective interactions. All analysis is for dimension 8 operators in the forward limit. Included is a thorough derivation of all positivity bounds for a chiral fermion in SU(2) and SU(3) global symmetry representations resembling those of the Standard Model, general bounds on flavour violation, new bounds for interactions between particles of different spin, inclusion of loops of dimension 6 operators and illustration of the resulting strengthening of positivity bounds over tree-level expectations, a catalogue of supersymmetric effective interactions up to mass dimension 8 and 4 legs and the demonstration that supersymmetry unifies the positivity theorems as well as the new bounds.

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Murphy, Christopher W. "Low-Energy Effective Field Theory below the Electroweak Scale: dimension-8 operators". Journal of High Energy Physics 2021, n. 4 (aprile 2021). http://dx.doi.org/10.1007/jhep04(2021)101.

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Abstract (sommario):

Abstract We construct a complete basis of dimension-8 operators in the Low-Energy Effective Field Theory below the Electroweak Scale (LEFT). We find there are 35058 dimension-8 operators in the LEFT for two generations of up-type quarks and three generations of down-type quarks, charged leptons, and left-handed neutrinos. The existence of this operator basis is a necessary prerequisite for matching to the Standard Model Effective Field Theory at the dimension-8 level.

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Li, Hao-Lin, Zhe Ren, Ming-Lei Xiao, Jiang-Hao Yu e Yu-Hui Zheng. "Low energy effective field theory operator basis at d ≤ 9". Journal of High Energy Physics 2021, n. 6 (giugno 2021). http://dx.doi.org/10.1007/jhep06(2021)138.

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Abstract (sommario):

Abstract We obtain the complete operator bases at mass dimensions 5, 6, 7, 8, 9 for the low energy effective field theory (LEFT), which parametrize various physics effects between the QCD scale and the electroweak scale. The independence of the operator basis regarding the equation of motion, integration by parts and flavor relations, is guaranteed by our algorithm [1, 2], whose validity for the LEFT with massive fermions involved is proved by a generalization of the amplitude-operator correspondence. At dimension 8 and 9, we list the 35058 (756) and 704584 (3686) operators for three (one) generations of fermions categorized by their baryon and lepton number violations (∆B, ∆L), as these operators are of most phenomenological relevance.

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50

Murphy, Christopher W. "Dimension-8 operators in the Standard Model Effective Field Theory". Journal of High Energy Physics 2020, n. 10 (ottobre 2020). http://dx.doi.org/10.1007/jhep10(2020)174.

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Abstract (sommario):

Abstract We present a complete basis of dimension-8 operators in the Standard Model Effective Field Theory. Attention is paid to operators that vanish in the absence of flavor structure. The 44,807 operators are encoded in 1,031 Lagrangian terms. We also briefly discuss a few aspects of phenomenology involving dimension-8 operators, including light-by-light scattering and electroweak precision data.

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