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Nature-Inspired Level Set Segmentation Model for 3D-MRI Brain Tumor Detection

computers, Materials & Continua 2021年第7期68卷 961-981页

作者： Oday Ali Hassen Sarmad Omar Abter Ansam A.Abdulhussein Saad M.Darwish Yasmine M.Ibrahim Walaa Sheta Department of Computer Techniques Engineering Imam Al-Kadhum College(IKC)WasitIraq University of Information Technology and Communications Media Technology Engineering DepartmentIraq University of Information Technology and Communications Baghdad10081Iraq Department of Information Technology Institute of Graduate Studies and ResearchAlexandria University63 Horreya AvenueEl–ShatbyAlexandria21526Egypt Informatics Research Institute City of Scientific Research and Technology ApplicationsBorg EL Arab21934Egypt

Medical image segmentation has consistently been a significant topic of research and a prominent goal,particularly in computer *** tumor research plays a major role in medical imaging applications by providing a tremendous amount of anatomical and functional knowledge that enhances and allows easy diagnosis and disease therapy *** prevent or minimize manual segmentation error,automated tumor segmentation,and detection became the most demanding process for radiologists and physicians as the tumor often has complex *** methods for detection and segmentation presently exist,but all lack high *** paper’s key contribution focuses on evaluating machine learning techniques that are supposed to reduce the effect of frequently found issues in brain tumor ***,attention concentrated on the challenges related to level set *** study proposed in this paper uses the Population-based Artificial Bee Colony Clustering(P-ABCC)methodology to reliably collect initial contour points,which helps minimize the number of iterations and segmentation errors of the level-set *** proposed model measures cluster centroids(ABC populations)and uses a level-set approach to resolve contour differences as brain tumors vary as they have irregular form,structure,and *** suggested model comprises of three major steps:first,pre-processing to separate the brain from the head and improves contrast ***,P-ABCC is used to obtain tumor edges that are utilized as an initial MRI sequence *** level-set segmentation is then used to detect tumor regions from all volume slices with fewer *** suggest improved model efficiency compared to state-of-the-art methods for both datasets BRATS 2019 and BRATS *** BRATS 2019,dice progress was achieved for Entire Tumor(WT),Tumor Center(TC),and Improved Tumor(ET)by 0.03%,0.03%,and 0.01%*** BRATS 2017,an increase in precision for WT was reac

关键词： 3D-MRI tumor diagnosis bio-inspired clustering ABC optimization multimodal detection

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SKIN_ML: An Efficient Approach for Skin Cancer Detection Using Soft Computing Methods 3

SKIN_ML: An Efficient Approach for Skin Cancer Detection Usi...

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3rd International Mobile, Intelligent, and Ubiquitous Computing Conference, MIUCC 2023

作者： Abdelminaam, Diaa Salama Madbouly, Magda M. Farag, Mohamed S Gomaa, Ibrahim A Abd-Elghany Zeid, Magdy Abualigah, Laith Misr International University Faculty of Computer Science Cairo Egypt Benha University Faculty of Computers and Artificial Intelligence Benha Egypt Alexandria University Faculty of Computer and Data Science Alexandria Egypt Alobour High Institute for Computer and Informatics Computer Science Department Cairo Egypt Lebanese American University Department of Electrical and Computer Engineering Byblos13-5053 Lebanon Al-Ahliyya Amman University Hourani Center for Applied Scientific Research Amman19328 Jordan Middle East University Meu Research Unit Amman11831 Jordan School of Computer Sciences Universiti Sains Malaysia Pulau Pinang 11800 Malaysia

ISBN: (纸本)9798350306231

In today's environment, cancer is a fatal disease. Skin cancer has become a fairly common malignancy due to the spread of several forms of cancer. Skin cancer is divided into two types: melanoma and non-melanoma. Melanoma is one of the most fatal tumors on the planet, and it can spread to other parts of the body if not diagnosed early enough. Our proposed system uses Five alternative methods to predict a skin lesion's borders, texture, and color: a neural network and four standard machine learning classifiers. To enhance their performance, the outputs of these systems are merged using majority voting. Experiments have demonstrated that combining the five strategies yields the maximum level of accuracy. Pre-processing, Segmentation, Feature Extraction, and Classification are four critical phases in skin cancer identification. Skin lesion images were collected for this research from the International Skin Imaging Collaboration (ISIC), which contains over 3297 photos. The accuracy of the NN classifier is 91.9%, compared to 87.2% for the KNN classifier, 81.5% for the Naive Bayes classifier, 72.5% for the SVM classifier, and 68.3% for the DT classifier. © 2023 IEEE.

关键词： Support vector machines

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Imitation Game for Adversarial Disillusion with Multimodal Generative Chain-of-Thought Role-Play

arXiv

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arXiv 2025年

作者： Chang, Ching-Chun Chen, Fan-Yun Gu, Shih-Hong Gao, Kai Wang, Hanrui Echizen, Isao Information and Society Research Division National Institute of Informatics Tokyo Japan Department of Information Engineering and Computer Science Feng Chia University Taichung Taiwan

As the cornerstone of artificial intelligence, machine perception confronts a fundamental threat posed by adversarial illusions. These adversarial attacks manifest in two primary forms: deductive illusion, where specific stimuli are crafted based on the victim model’s general decision logic, and inductive illusion, where the victim model’s general decision logic is shaped by specific stimuli. The former exploits the model’s decision boundaries to create a stimulus that, when applied, interferes with its decision-making process. The latter reinforces a conditioned reflex in the model, embedding a backdoor during its learning phase that, when triggered by a stimulus, causes aberrant behaviours. The multifaceted nature of adversarial illusions calls for a unified defence framework, addressing vulnerabilities across various forms of attack. In this study, we propose a disillusion paradigm based on the concept of an imitation game. At the heart of the imitation game lies a multimodal generative agent, steered by chain-of-thought reasoning, which observes, internalises and reconstructs the semantic essence of a sample, liberated from the classic pursuit of reversing the sample to its original state. As a proof of concept, we conduct experimental simulations using a multimodal generative dialogue agent and evaluates the methodology under a variety of attack scenarios. © 2025, CC BY.

关键词： Adversarial machine learning

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Metric Dimension and Geodetic Set Parameterized by Vertex Cover 42

Metric Dimension and Geodetic Set Parameterized by Vertex Co...

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42nd International Symposium on Theoretical Aspects of computer Science, STACS 2025

作者： Foucaud, Florent Galby, Esther Khazaliya, Liana Li, Shaohua Mc Inerney, Fionn Sharma, Roohani Tale, Prafullkumar Université Clermont Auvergne CNRS Mines Saint-Étienne Clermont Auvergne INP LIMOS Clermont-Ferrand63000 France Department of Computer Science and Engineering Chalmers University of Technology University of Gothenburg Sweden Technische Universität Wien Austria School of Computer Science and Engineering Central South University Changsha China Telefónica Scientific Research Barcelona Spain University of Bergen Norway Indian Institute of Science Education and Research Pune India

ISBN: (纸本)9783959773652

For a graph G, a subset S ⊆ V (G) is called a resolving set of G if, for any two vertices u, v ∈ V (G), there exists a vertex w ∈ S such that d(w, u) ≠ d(w, v). The Metric Dimension problem takes as input a graph G on n vertices and a positive integer k, and asks whether there exists a resolving set of size at most k. In another metric-based graph problem, Geodetic Set, the input is a graph G and an integer k, and the objective is to determine whether there exists a subset S ⊆ V (G) of size at most k such that, for any vertex u ∈ V (G), there are two vertices s1, s2 ∈ S such that u lies on a shortest path from s1 to s2. These two classical problems are known to be intractable with respect to the natural parameter, i.e., the solution size, as well as most structural parameters, including the feedback vertex set number and pathwidth. We observe that both problems admit an FPT algorithm running in 2O(vc2) · nO(1) time, and a kernelization algorithm that outputs a kernel with 2O(vc) vertices, where vc is the vertex cover number. We prove that unless the Exponential Time Hypothesis (ETH) fails, Metric Dimension and Geodetic Set, even on graphs of bounded diameter, do not admit an FPT algorithm running in 2o(vc2) · nO(1) time, nor a kernelization algorithm that does not increase the solution size and outputs a kernel with 2o(vc) vertices. We only know of one other problem in the literature that admits such a tight algorithmic lower bound with respect to vc. Similarly, the list of known problems with exponential lower bounds on the number of vertices in kernelized instances is very short. © Florent Foucaud, Esther Galby, Liana Khazaliya, Shaohua Li, Fionn Mc Inerney, Roohani Sharma, and Prafullkumar Tale.

关键词： Geodesy

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ML_Alzheimer: Alzheimer Disease Prediction Using Machine Learning 3

ML_Alzheimer: Alzheimer Disease Prediction Using Machine Lea...

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3rd International Mobile, Intelligent, and Ubiquitous Computing Conference, MIUCC 2023

ISBN: (纸本)9798350306231

Alzheimer's disease is a fatal brain disorder that impacts predominantly the elderly. The early identification of Alzheimer's illness requires the use of efficient automated methods. For the categorization of Alzheimer's disease, researchers have proposed several distinct methods. To create more effective learning strategies, however, a deeper comprehension of Alzheimer's research is necessary. The condition is diagnosed but not until a later stage. As a consequence, the disease's progression or its symptoms' onset can be slowed if detected earlier. This article uses two datasets and machine learning techniques to predict Alzheimer's disease based on psychological characteristics such as age, gender, number of visits, and Mini-Mental State Examination (MMSE). We ultimately focused on the masculine gender and characteristics. The following results (accuracy) were discovered: SVM: 84%, KNN: 79%, and Random forest: 86%. Neural network: 86%;Naive Bayes: 83%. © 2023 IEEE.

关键词： Support vector machines

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Application of Neural Network in the Prediction Models of Machine Learning Based Design

Application of Neural Network in the Prediction Models of Ma...

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2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2022

作者： Gehlot, Anita Ansari, Bushra Khatoon Arora, Deepika Anandaram, Harishchander Singh, Bhagwant Arias-Gonzáles, José Luis Uttaranchal University Uttaranchal Institute of Technology India Institute of Engineering and Technology AKTU Department of Civil Engineering Lucknow India Lloyd Institute of Engineering & Technology Computer Science & Engineering Centre for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Tamil Nadu Coimbatore India SS Informatics Cluster School of Computer Science Uttarakhand Dehradun248007 India Pontificia Universidad Católica Del Peru Peru

ISBN: (数字)9781665474139

ISBN: (纸本)9781665474139

This research examines way to pass, among the most dynamic and quickly-evolving technology fields in the telecommunication sector. Data may be sent between two locations wirelessly without the usage of digital downloads like wires and cables. Business telecom companies have advanced as a consequence and joined the big data age. Among the most potential machine learning methods for interpreting this deluge of information is computer science, which is employed in a range of business and scholarly research situations. This paper gives a broad overview of technology advancements and big data analytics, as well as possible uses for them in succeeding cellular networks. Apply sophisticated analytics to determine what mobile users' demands are, and then utilise that information to raise the effectiveness of "social wireless channels of communication."The huge, integrated, information machine educational approach it offers, which consists of extracting the features, simulation models, and forecasting enhancements, is particularly noteworthy. The key benefit of the proposed methodology is the logic of robust mathematical methods, issue conceptualization within the context of cellular networks, and reliance on a vast amount of data that represents both the bandwidth as well as other stringent user needs. and the ability to create a procedure. In a communication network, data is normally sent from the transmitter to the receiver across a distance. Using communication systems, the transmitter may be positioned somewhere within a few metres. We will examine existing strategies, their advantages and disadvantages, and potential developments in underwater sensors right now. We had discovered a fresh method of investigation. © 2022 IEEE.

关键词： Information management

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Pose Estimation of Spacecraft Using Dual Transformers and Efficient Bayesian Hyperparameter Optimization

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International Journal of Advanced computer Science and Applications 2025年第4期16卷 629-644页

作者： Raja, N. Kannaiya Ramesh, Janjhyam Venkata Naga El-Ebiary, Yousef A. Baker Muniyandy, Elangovan Reddy, N. Konda Kumar, Vanipenta Ravi Devarasetty, Prasad School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh Bhopal466114 India Department of CSE Graphic Era Hill University Dehradun248002 India Department of CSE Graphic Era Deemed To Be University Uttarakhand Dehradun248002 India Faculty of Informatics and Computing UniSZA University Malaysia Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai602 105 India Applied Science Research Center Applied Science Private University Amman Jordan Department of Engineering Mathematics K L University Greenfields Guntur Dist Andhra Pradesh Vaddeswaram522302 India Department of Mathematics Annamacharya University New Boyanapalli Rajampet India Department of Computer Science and Engineering DVR & Dr HS MIC College of Technology Andhra Pradesh Kanchikacherla India

Spacecraft pose estimation is an essential contribution to facilitating central space mission activities like autonomous navigation, rendezvous, docking, and on-orbit servicing. Nonetheless, methods like Convolutional Neural Networks (CNNs), Simultaneous Localization and Mapping (SLAM), and Particle Filtering suffer significant drawbacks when implemented in space. Such techniques tend to have high computational complexity, low domain generalization capacity for varied or unknown conditions (domain generalization problem), and accuracy loss with noise from the space environment causes such as fluctuating lighting, sensor limitations, and background interference. In order to overcome these challenges, this study suggests a new solution through the combination of a Dual-Channel Transformer Network with Bayesian Optimization methods. The innovation is at the center with the utilization of EfficientNet, augmented with squeeze-and-excitation attention modules, to extract feature-rich representations without sacrificing computational efficiency. The dual-channel architecture dissects satellite pose estimation into two dedicated streams—translational data prediction and orientation estimation via quaternion-based activation functions for rotational precision. Activation maps are transformed into transformer-compatible sequences via 1×1 convolutions, allowing successful learning in the transformer's encoder-decoder system. To maximize model performance, Bayesian Optimization with Gaussian Process Regression and the Upper Confidence Bound (UCB) acquisition function makes the optimal hyperparameter selection with fewer queries, conserving time and resources. This entire framework, used here in Python and verified with the SLAB Satellite Pose Estimation Challenge dataset, had an outstanding Mean IOU of 0.9610, reflecting higher accuracy compared to standard models. In total, this research sets a new standard for spacecraft pose estimation, by marrying the versatility of deep le

关键词： Convolutional neural networks

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Bounded Indistinguishability for Simple Sources 13

Bounded Indistinguishability for Simple Sources

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13th Innovations in Theoretical computer Science Conference, ITCS 2022

作者： Bogdanov, Andrej Dinesh, Krishnamoorthy Filmus, Yuval Ishai, Yuval Kaplan, Avi Srinivasan, Akshayaram Department of Computer Science and Engineering Institute of Theoretical Computer Science and Communications The Chinese University of Hong Kong Hong Kong Institute of Theoretical Computer Science and Communications The Chinese University of Hong Kong Hong Kong The Henry and Marylin Taub Faculty of Computer Science Technion Haifa Israel School of Technology and Computer Science Tata Institute of Fundamental Research Mumbai India

ISBN: (纸本)9783959772174

A pair of sources X, Y over {0, 1}n are k-indistinguishable if their projections to any k coordinates are identically distributed. Can some AC0 function distinguish between two such sources when k is big, say k = n0.1? Braverman's theorem (Commun. ACM 2011) implies a negative answer when X is uniform, whereas Bogdanov et al. (Crypto 2016) observe that this is not the case in general. We initiate a systematic study of this question for natural classes of low-complexity sources, including ones that arise in cryptographic applications, obtaining positive results, negative results, and barriers. In particular: - There exist Ω(√n)-indistinguishable X, Y, samplable by degree-O(log n) polynomial maps (over F2) and by poly(n)-size decision trees, that are Ω(1)-distinguishable by OR. - There exists a function f such that all f(d, ϵ)-indistinguishable X, Y that are samplable by degree-d polynomial maps are ϵ-indistinguishable by OR for all sufficiently large n. Moreover, f(1, ϵ) = ⌈log(1/ϵ)⌉ + 1 and f(2, ϵ) = O(log10(1/ϵ)). - Extending (weaker versions of) the above negative results to AC0 distinguishers would require settling a conjecture of Servedio and Viola (ECCC 2012). Concretely, if every pair of n0.9indistinguishable X, Y that are samplable by linear maps is ϵ-indistinguishable by AC0 circuits, then the binary inner product function can have at most an ϵ-correlation with AC0 ◦ ⨁ circuits. Finally, we motivate the question and our results by presenting applications of positive results to low-complexity secret sharing and applications of negative results to leakage-resilient cryptography. © Andrej Bogdanov, Krishnamoorthy Dinesh, Yuval Filmus, Yuval Ishai, Avi Kaplan, and Akshayaram Srinivasan;licensed under Creative Commons License CC-BY 4.0

关键词： Decision trees

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An Exploratory Investigation into Sustaining Cybersecurity Protection Through the Implementation of SETA 4

An Exploratory Investigation into Sustaining Cybersecurity P...

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4th International Conference on Emerging Trends in Networks and computer Communications, ETNCC 2024

作者： Abdullah Huda, Mahfuzul Brayyich, Mohammed Haroon, Noor Hanoon Khan, Abdul Azeem Verma, Rajan University Institute of Computing Chandigarh University Punjab India College of Computing and Informatics Saudi Electronic University Riyadh Saudi Arabia College of Technical Engineering National University of Science & Technology Dhi Qar Iraq Technical Engineering College Al-Ayen University Department of Computer Technical Engineering Thi-Qar Iraq Negara Brunei Darussalam Faculty of Islamic Technology Brunei Lovely Professional University Division of Research and Development Phagwara144411 India KKR & KSR Institute of Technology & Sciences Andhra Pradesh Guntur India

ISBN: (纸本)9798350353266

Most modern businesses run their competitive operations online. Cybersecurity is crucial to commercial operations. No cybersecurity defensive solution is universal. Standard security strategy involves using hardware and software to counter known security threats that may become stronger over time. Attackers and security professionals fight constantly. A security approach based primarily on tools is untenable. However, some firms skip employee awareness training, resulting in biased cybersecurity breach decisions. This study objectively analyzes key factors that help enterprises and organizations deploy Security Education, Training, and Awareness (SETA) to find ways to maintain such protection. A dataset of UK corporate cybersecurity breach surveys is used to perform performance testing on eight supervised learning models. The entire research uses the model's built characteristics that are excellent at recognizing SETA-adopting enterprises and organizations. The trial shows that awareness is vital when organizations use SETA. Many firms don't know how to safeguard employees from cybersecurity risks when they use online products and services, such as external web services. © 2024 IEEE.

关键词： Personnel training

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Critical Factors of Immersive Learning in Higher Education: A Systematic Literature Review 10

Critical Factors of Immersive Learning in Higher Education: ...

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10th International Conference on ICT for Smart Society, ICISS 2023

作者： Sunardi Meyliana Ramadhan, Arief Rosmansyah, Yusep Bina Nusantara University BINUS Graduate Program Doctor of Computer Science Computer Science Department Jakarta Indonesia School of Information System Bina Nusantara University Information System Departement Jakarta Indonesia School of Computing Telkom University Bandung Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia

ISBN: (纸本)9798350339543

Immersive learning has gained significant attention with the rising trend of spatial computing, particularly in the after-pandemic era. Numerous research has explored the potential of immersive learning in higher education, primarily on the educational sector. However, prior research has frequently focused too narrowly on the effects of technology and neglected to address the crucial element influencing successful immersive learning in higher education. This study seeks to pinpoint the crucial element contributing to the development of immersive learning experiences. The methodology uses a systematic literature review (SLR) from 2018 up to 2023 to investigate the critical factors of immersive Learning in Higher Education. From the 728 papers initially retrieved, 274 were considered potential candidates, and ultimately, 86 articles were selected based on their relevance to the research question. The results reveal that the critical factors include learning design, technology, immersion, engagement, interactivity, and usability. academic interests will benefit from this SLR's consequences as institutions create models for designing suitable immersive learning, especially within the context of higher education. © 2023 IEEE.

关键词： E-learning

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