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Enhancing Missing Data Imputation for Migrants Data: A Neutrosophic Set-Based Machine Learning Approach

Neutrosophic Sets and Systems 2025年 81卷 479-502页

作者： Abdo, Doaa A. Salama, A.A. Abdelmegaly, Alaa A. Mahmoud, Hanan Khadari Mahdi Applied statistics and insurance department faculty of commerce Mansoura university Mansoura Egypt Dept. of Math and Computer Sci. Faculty of Science Port Said Univ. Egypt Higher Institute of Advanced Management Sciences and Computers Al-Buhayrah Egypt Depatrment of applied statistics at the Nile Higher Institute of commercial sciences and Computer Technology in Mansoura Egypt

This study tackles the problem of missing data in migrant datasets by introducing a new framework that combines machine learning techniques with neutrosophic sets. These sets, which can represent uncertainty and ambiguity, are well-suited for managing the complex nature of missing information in sensitive fields like migration research. We test the effectiveness of KNN, SVM, decision tree, random forest, and Ada Boost algorithms on a migrant dataset, comparing their results using different imputation methods (mean/mode, model-based imputer (simple tree), and random values). Our research showed that our proposed approach, which used neutrosophic sets, improved imputation accuracy and strengthened model reliability. Our results underscored the potential of neutrosophic set-based machine learning for addressing missing data issues across various fields. © 2025, University of New Mexico. All rights reserved.

关键词： Adversarial machine learning

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'Simple Mistakes' in College Algebra: an Analysis of Students' Perceptions of Their Errors Using Attribution Theory

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International Journal of Research in Undergraduate mathematics Education 2025年 1-28页

作者： Ryals, Megan Hill-Lindsay, Sloan Pilgrim, Mary E. Burks, Linda C. Center for Applied Mathematics University of Virginia 156 Engineer’s Way Charlottesville 22904 VA United States Department of Math and Statistics San Diego State University 5500 Campanile Dr San Diego 92182 CA United States Department of Mathematics and Computer Science Santa Clara University 500 El Camino Real Santa Clara 95053 CA United States

Analyzing their mistakes affords students opportunities for improved learning and success in problem solving disciplines, especially when students are able to identify reasons for their errors and modify their future study behavior. To help students make appropriate adjustments, instructors must understand the language students use to describe their own academic performance. This study explores what students mean when they say they made “simple mistakes.” Eight students participated in interviews where they reviewed errors from a recent exam, explaining why errors were simple or not simple. We analyzed the interview data using Causal Attribution Theory and discovered how students’ attributions of their errors influence their classification of their errors as simple or not simple. Results include descriptions of simple and not simple distinctions for three categories of students and evidence of similarities among students within each category regarding their self-efficacy and persistence through struggle. The analysis also reveals how students plan to adjust their study approach based on their classification of their errors. Across categories, students believe simple mistakes are preventable through repetitive practice or memorization, while not simple mistakes require help seeking, but students within different categories differ in how they use these strategies. The results show that that different students can use the same language to convey very different meanings for their own error categorizations and that there is need for instructors to probe these meanings before providing guidance. Our results also provide support for previous calls for interventions aimed at retraining students’ causal attribution styles towards controllable, unstable causes. © The Author(s) 2025.

关键词： Attribution theory College Algebra Motivation Student errors

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The Physics of Sensing and Decision-Making by Animal Groups

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Annual review of biophysics 2025年第1期54卷 329-351页

作者： Chase, Danielle L. Peleg, Orit BioFrontiers Institute University of Colorado Boulder Colorado USA email: Orit.Peleg@colorado.edu BioFrontiers Institute University of Colorado Boulder Colorado USA email: Danielle.Chase@colorado.edu Orit.Peleg@colorado.edu Department of Computer Science Department of Physics Department of Applied Math Department of Ecology and Evolutionary Biology University of Colorado Boulder CO United States Santa Fe Institute Santa Fe New Mexico USA

To ensure survival and reproduction, individual animals navigating the world must regularly sense their surroundings and use this information for important decision-making. The same is true for animals living in groups, where the roles of sensing, information propagation, and decision-making are distributed on the basis of individual knowledge, spatial position within the group, and more. This review highlights key examples of temporal and spatiotemporal dynamics in animal group decision-making, emphasizing strong connections between mathematical models and experimental observations. We start with models of temporal dynamics, such as reaching consensus and the time dynamics of excitation-inhibition networks. For spatiotemporal dynamics in sparse groups, we explore the propagation of information and synchronization of movement in animal groups with models of self-propelled particles, where interactions are typically parameterized by length and timescales. In dense groups, we examine crowding effects using a soft condensed matter approach, where interactions are parameterized by physical potentials and forces. While focusing on invertebrates, we also demonstrate the applicability of these results to a wide range of organisms, aiming to provide an overview of group behavior dynamics and identify new areas for exploration.

关键词： active matter collective behavior decision-making dynamical systems sensing soft matter

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A novel pythonic paradigm for image encryption using axis-aligned bounding boxes

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Scientific Reports 2025年第1期15卷 1-27页

作者： Banga, Abdulbasid Abbas, Akifa Ali, Danish Innab, Nisreen Alluhaidan, Ala Saleh Iqbal, Nadeem Diab, Hossam College of Computing and Informatics (CCI) Saudi Electronic University Riyadh 11673 Saudi Arabia School of Computing Bath Spa University Academic Center Ras Ul Khaima United Arab Emirates Department of Computer Science and Information Systems College of Applied Sciences AlMaarefa University Riyadh 13713 Saudi Arabia Department of Information Systems College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Riyadh 11671 Saudi Arabia Department of Computer Science & IT The University of Lahore Lahore 54000 Pakistan Math and Computer Science Department Faculty of Science Menoufia University Menoufia Shibin El Kom 32511 Egypt Computer Science Department Applied College Taibah University Madinah 41477 Saudi Arabia

In the digital age, images permeate every facet of our lives, often carrying critical information for organizations, institutions, and even nation-states. Ensuring their security against unauthorized access is paramount. This research introduces a novel image encryption algorithm designed to safeguard the integrity and confidentiality of sensitive gray-scale digital images. The algorithm leverages the theory of axis-aligned bounding boxes, translating the input image into a 3D representation. Within this 3D space, two identically sized boxes are generated and assessed for overlap. If the boxes do not overlap, the pixels within them are swapped. This pixel-swapping process, guided by random numbers generated from a 5D multi-wing hyper-chaotic map, is repeated numerous times to infuse confusion into the image. To further enhance security, diffusion effects are introduced by performing an XoR operation between the confused image and random numbers provided by the piece-wise linear chaotic map. This study employs private key cryptography and utilizes four gray-scale images to validate the feasibility and effectiveness of the proposed method. Simulation has been carried out in the Pythonic ecosystem. So, the algorithms presented in this study are designed to closely resemble Python code. Comprehensive validation metrics attest to the robustness of the cipher, achieving an information entropy of 7.99985 and a computational speed of 0.3987 seconds. These results underscore the potential of this encryption approach for practical, real-world applications. These applications span military, diplomacy & government, commerce, showbiz, industry, and social life etc. © The Author(s) 2025.

关键词： Chaotic map Non-linearity Random numbers S-Box Smart cities Wireless communication security

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Parsoffensive: Persian Offensive Comments Dataset

Parsoffensive: Persian Offensive Comments Dataset

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International Conference on Web Research (ICWR)

作者： Ali Nazarizadeh Minoo Sayyadpour Omid Ebrahimkhani Amirmasoud Iravani Golnaz Ghannadan Shirazi Mojgan Behravan Department of Computer Engineering Central Tehran Branch Islamic Azad University Tehran Iran Dept. Math and Computer Science Kharazmi University Tehran Iran Department of English Translation Studies Faculty of Persian Literature and Foreign Languages Allameh Tabataba'i University Tehran Iran Department of Linguistics Faculty of Letters and Humanities Ferdowsi University of Mashhad Mashhad Iran Department of Engineering Faculty of Computer Engineering Alzahra University Tehran Iran Department of IT& Technology IU International University of Applied science Tehran Iran

ISBN: (数字)9798331508913

ISBN: (纸本)9798331508920

Offensive language detection is essential for maintaining respectful and inclusive online environments. By implementing detection systems, platforms aim to protect users from harmful content, curb the spread of hate speech, and promote positive interactions within digital communities. Leveraging natural language processing (NLP) techniques, this area has become a key focus in computational linguistics research and development. To address this challenge, we created the ParsOffensive dataset, consisting of approximately 8,433 Persian comments labeled as Offensive or Neutral. These comments were sourced from Instagram and labeled by two linguists. Machine learning models were trained on this dataset, with the ParsBert model achieving 90% accuracy in detecting offensive speech in Persian.

关键词： Accuracy Social networking (online) Computational modeling Prevention and mitigation Hate speech Text categorization Natural language processing Web sites Multimedia communication Research and development

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Accelerating Traditional Object Detection Methods on Sophisticated Embedded Systems 4th

Accelerating Traditional Object Detection Methods on Sophis...

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4th International Conference on Intelligent Systems and Pattern Recognition, ISPR 2024

作者： Sehairi, Kamal Bouhafs, Abdelkader Boucherit, Ibtissam Mama Bouwmans, Thierry Chouireb, Fatima Department of Physics Laboratory of Applied Sciences and Didactics École Normale Supérieure de Laghouat Laghouat Algeria Department of Electronics Telecommunication Signals and Systems Laboratory University Amar Telidji of Laghouat Laghouat Algeria Department of Computer Science Lab. Mathématiques Image et Applications Université de La Rochelle La Rochelle France

ISBN: (纸本)9783031821523

Identifying and locating objects in images and videos, including elements like traffic signs, vehicles, buildings, and people, constitutes a fundamental and demanding task in computer vision, known as object detection. Due to the higher computing complexity of this technique and the large amount of data carried by the video signal, it is nearly impossible for ordinary general-purpose processors GPPs or CPUs to run these techniques in real-time, especially for embedded systems applications. Therefore, special hardware that can acquire, control, or execute in parallel is required. These specialized hardware systems include Digital Signal Processors DSPs, Field Programmable Gate Arrays FPGAs, Visual Processing Units VPUs, Tensor Processing Units TPUs, Neural Processing Units NPUs or Graphics Processing Units GPUs. This work presents the benefits of accelerating traditional object detection methods on a high-end embedded system, the Jetson Nano Developer Kit. This single computer board is equipped with the Tegra K1 System on Chip SoC, which is composed of a quad-core ARM A15 and 192 cores of Kepler-embedded GPU. Computing acceleration was ensured via the use of the CUDA OpenCV library for both the Histogram of Oriented Gradients HOG and the Haar Cascade Classifier. For VGA resolution, results reveal that the GPU implementation on this embedded system is 1.4× faster than the CPU for the HOG method and 2× for the Haar Cascade Classifier method. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： System-on-chip

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A fast randomized LOGSPACE algorithm for graph connectivity

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THEORETICAL computer science 1996年第2期169卷 147-160页

作者： Feige, U Department of Applied Math and Computer Science The Weizmann Institute Rehovot 76100 Israel

We study the relationship between undirected graph reachability and graph connectivity, in the context of randomized LOGSPACE algorithms. Aleluinas et al. [2] show that graph reachability (checking whether there is a path connecting vertices L and F) can be decided in logarithmic space and polynomial time, by starting a random walk at L, and checking whether F is hit within some time limit. The randomized algorithm has one-sided error (with small probability, it fails to determine that L and F are connected). The reachability algorithm may be used in order to decide (with one-sided error) whether a graph is connected, by running it n - 1 times, each time with a different target vertex F. This increases the running time by a factor of n. In this paper we give an alternative randomized LOGSPACE algorithm for graph connectivity. Its running time varies between O(n(2)) steps and O(n(3)) steps, depending on the structure of the input graph. This matches the fastest known RLOGSPACE algorithm for reachability, up to a constant factor. Our algorithm has two-sided error.

关键词： Computation theory

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A TIGHT LOWER-BOUND ON THE COVER TIME FOR RANDOM-WALKS ON GRAPHS

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RANDOM STRUCTURES & ALGORITHMS 1995年第4期6卷 433-438页

作者： FEIGE, U Department of Applied Math and Computer Science The Weizmann Institute Rehovot Israel

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Qudit Dynamical Decoupling on a Superconducting Quantum Processor

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Physical Review Letters 2025年第5期134卷 050601-050601页

作者： Vinay Tripathi Noah Goss Arian Vezvaee Long B. Nguyen Irfan Siddiqi Daniel A. Lidar Department of Physics and Astronomy University of Southern California Los Angeles California 90089 USA Center for Quantum Information Science and Technology University of Southern California Los Angeles California 90089 USA Quantum Nanoelectronics Laboratory Department of Physics University of California at Berkeley Berkeley California 94720 USA Applied Math and Computational Research Division Lawrence Berkeley National Lab Berkeley California 94720 USA Department of Electrical and Computer Engineering University of Southern California Los Angeles California 90089 USA Department of Chemistry University of Southern California Los Angeles California 90089 USA

Multilevel qudit systems are increasingly being explored as alternatives to traditional qubit systems due to their denser information storage and processing potential. However, qudits are more susceptible to decoherence than qubits due to increased loss channels, noise sensitivity, and crosstalk. To address these challenges, we develop protocols for dynamical decoupling (DD) of qudit systems based on the Heisenberg-Weyl group. We implement and experimentally verify these DD protocols on a superconducting transmon processor that supports qudit operation based on qutrits (d=3) and ququarts (d=4). Specifically, we demonstrate single-qudit DD sequences to decouple qutrits and ququarts from system-bath-induced decoherence. We also introduce two-qudit DD sequences designed to suppress the detrimental cross-Kerr couplings between coupled qudits. This allows us to demonstrate a significant improvement in the fidelity of time-evolved qutrit Bell states. Our results highlight the utility of leveraging DD to enable scalable qudit-based quantum computing.

关键词： Qubits

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Randomized graph products, chromatic numbers, and the Lovasz theta-function

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COMBINATORICA 1997年第1期17卷 79-90页

作者： Feige, U Department of Applied Math. and Computer Science The Weizmann Institute Rehovot Israel

For a graph G, let alpha(G) denote the size of the largest independent set in G, and let theta(G) denote the Lovasz theta-function on G. We prove that for some c > 0, there exists an infinite family of graphs such that theta(G) > alpha(G)n/2(c root log n), where n denotes the number of vertices in a graph. This disproves a known conjecture regarding the theta function. As part of our proof, we analyse the behavior of the chromatic number in graphs under a randomized version of graph products. This analysis extends earlier work of Linial and Vazirani, and of Berman and Schnitger, and may be of independent interest.

关键词： mathematics Subject Classification (1991) 05 C 15 90 C 35

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