Article
Computer Science, Interdisciplinary Applications
Yanyan Ouyang, Jiamin Liu, Tiejun Tong, Wangli Xu
Summary: This article introduces the Wilcoxon signed-rank test and the Wilcoxon-Mann-Whitney test as commonly used methods for non-normally distributed data. For high-dimensional data, a new rank-based nonparametric test is proposed, and its advantages are demonstrated through simulation studies and practical data application.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2022)
Article
Computer Science, Artificial Intelligence
Issam El Khadiri, Youssef El Merabet, Ahmad S. Tarawneh, Yassine Ruichek, Dmitry Chetverikov, Raja Touahni, Ahmad B. Hassanat
Summary: This paper introduces a novel image feature descriptor called PGMO-MSTP for texture and material classification, which improves performance by combining LTP and LGS concepts, and demonstrates superior performance in experiments.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2021)
Article
Mathematics, Interdisciplinary Applications
Vigya, Saurav Raj, Chandan Kumar Shiva, Basetti Vedik, Sheila Mahapatra, V. Mukherjee
Summary: In solving complex optimization problems, it is important to fulfill multiple objectives while considering various conditions and limitations. Traditional methods face challenges such as slow convergence and being stuck in local optima. To overcome these issues, the proposed C-CHOA-SC algorithm combines CHOA and SCA, incorporating chaos for effective exploration and exploitation of the search space. This hybrid approach offers enhanced performance and better solutions for multi-objective optimization problems. The algorithm is evaluated through analysis on benchmark problems, performance metrics, and non-parametric tests, showing significant improvement and outperforming other methods.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Environmental Sciences
Supratim Guha, Reet Kamal Tiwari
Summary: This study examines the temporal changes in glacier response in the Sikkim region through analyzing area changes, retreat, and surface elevation changes. The results indicate significant changes in glacier area, retreat rate, and surface elevation over the past few decades.
GEOCARTO INTERNATIONAL
(2022)
Article
Green & Sustainable Science & Technology
Ali Reza Noori, S. K. Singh
Summary: Increased demand and declining quality of groundwater resources in metropolitan areas require long-term conservation. This study developed the spatial distribution of groundwater quality parameters in the Kabul basin and assessed their seasonal significance. Concentrations of magnesium, sodium, chloride, fluoride, iron, and manganese varied significantly between dry and wet seasons, with some exceeding the World Health Organization's recommendations. The variations in water quality metrics are influenced by recharge volume, hydraulic conductivity, and geological formation. The findings provide valuable insights for sustainable water resource management by local authorities.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2023)
Article
Computer Science, Software Engineering
Sylwester Czmil, Jacek Kluska, Anna Czmil
Summary: This paper introduces a tool for comparing classification algorithm performance, evaluating classification performance, reproducibility, and statistical reliability. The tool simplifies the classifier evaluation process and provides code examples, output results, and an overview of the module's capabilities.
Article
Engineering, Multidisciplinary
Zahid Rasheed, Hongying Zhang, Muhammad Arslan, Babar Zaman, Syed Masroor Anwar, Muhammad Abid, Saddam Akber Abbasi
Summary: The study presents an advanced NP TEWMA Wilcoxon signed-rank based on RSS, referred to as TEWMA - SRRSS control chart, to detect shifts in the process location parameter. Monte Carlo simulation is used to compare the performance of the proposed TEWMA - SRRSS control chart with other existing control charts. Findings indicate that the proposed TEWMA - SRRSS control chart is more effective in identifying shifts in the process location, especially for small shifts. A real-life application is also demonstrated for practical implementation of the TEWMA - SRRSS control chart.
MATHEMATICAL PROBLEMS IN ENGINEERING
(2021)
Article
Statistics & Probability
Dimitrios Bagkavos, Prakash N. Patil
Summary: This note extends the applicability of the Wilcoxon signed rank test to data from asymmetric densities, discussing in detail the operational characteristics and asymptotic properties of the process. A real data example is used to highlight the benefits gained in practice.
STATISTICS & PROBABILITY LETTERS
(2021)
Article
Mathematics
Sajad Ahmad Rather, Sujit Das
Summary: Image segmentation is a crucial step in image processing with significant application potential in medical image analysis, data mining, and pattern recognition. This study employs the Levy flight and Chaos theory-based Gravitational Search Algorithm (LCGSA) for the segmentation of COVID-19 chest CT scan images. Experimental results demonstrate the efficient performance of LCGSA in terms of computational time and image quality metrics.
Article
Computer Science, Interdisciplinary Applications
Masato Kitani, Hidetoshi Murakami
Summary: This study introduces a new statistical method for addressing the one-sample testing problem, demonstrating its suitability through numerical results compared to traditional methods. Additionally, asymptotic power under the alternative hypothesis is derived and the unbiasedness and biasedness of the test are investigated.
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
(2022)
Article
Neurosciences
Xuan Li, Yunqiao Wu, Mengting Wei, Yiyun Guo, Zhenhua Yu, Haixian Wang, Zhanli Li, Hui Fan
Summary: The proposed PLWT index introduces a novel way to characterize functional connectivity based on phase lag with a weighting procedure, reducing the influence of volume conduction and noise. It automatically identifies important connections without relying on thresholds, showing robustness to volume conduction and noise in both simulated and real EEG datasets. The brain functional networks derived from PLWT exhibit a reasonable scale-free characteristic and high TRT reliability.
COGNITIVE NEURODYNAMICS
(2021)
Article
Mathematics
Chengfeng Zheng, Mohd Shareduwan Mohd Kasihmuddin, Mohd Asyraf Mansor, Ju Chen, Yueling Guo
Summary: The paper investigates the sine and cosine algorithm and its performance factors, proposes a hybrid sine and cosine algorithm, and combines it with the fuzzy k-nearest neighbor method for numerical simulations. The results show that the hybrid SCA FKNN achieves high accuracy in classification and prediction across multiple datasets, surpassing other algorithms.
Article
Biochemical Research Methods
Eric Frauenhofer, Carleigh Cimmerer, Jihnhee Yu, Zeki Y. Al-Saigh, Joonyeong Kim
Summary: The study used inverse gas chromatography to investigate the sorption and diffusion of hydrocarbons into polydimethylsiloxane (PDMS) in the headspace-solid phase microextraction (HS-SPME) sampling process. The results showed that the molar enthalpy of sorption was the main driving force for the hydrocarbon sorption into the PDMS SPME fibers, with the molar enthalpies of sorption becoming more exothermic as the molecular size of the hydrocarbon increased. Interaction parameters and diffusion coefficients suggested that n-heptane and n-octane diffused into the PDMS matrix and localized to form clusters, while n-nonane and aromatic probes had limited diffusivities due to their large molecular size and lack of structural flexibility.
JOURNAL OF CHROMATOGRAPHY A
(2021)
Article
Engineering, Geological
Selcuk Demir, Emrehan Kutlug Sahin
Summary: This research investigates and compares the performance of three tree-based ML methods (CCF, RotFor, and RF) for predicting soil liquefaction potential. The results show that these methods are robust to training sample size variations, with CCF and RotFor performing slightly better than RF.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2022)
Article
Engineering, Multidisciplinary
Ibrahim M. Almanjahie, Zahid Rasheed, Majid Khan, Syed Masroor Anwar, Ammara Nawaz Cheema
Summary: Nonparametric control charts are introduced for situations where quality characteristics do not follow a specific distribution. Ranked-set sampling is preferred over simple random sampling, and a nonparametric homogeneously weighted moving average based on the Wilcoxon signed-rank test with ranked set sampling (NPHWMA(RSS)) control chart is proposed. Monte Carlo simulations are used to evaluate the performance of this chart, which outperforms other control charts. An example is provided to demonstrate the practical implementation of the proposed scheme.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2023)
Article
Computer Science, Hardware & Architecture
Mohammad Masdari, Saeid Barshande, Suat Ozdemir
JOURNAL OF SUPERCOMPUTING
(2019)
Article
Computer Science, Interdisciplinary Applications
Saeid Barshandeh, Maryam Haghzadeh
Summary: The convergence speed of ASO is enhanced by incorporating chaotic maps and Levy flight random walk, and the hybridization with the tree-seed algorithm (TSA) improves the exploration and exploitation capabilities, achieving a proper balance between them.
ENGINEERING WITH COMPUTERS
(2021)
Article
Computer Science, Artificial Intelligence
Mohammad Masdari, Saeid Barshandeh
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
(2020)
Article
Engineering, Electrical & Electronic
Ali Shahidinejad, Saeid Barshandeh
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS
(2020)
Article
Computer Science, Artificial Intelligence
Abdollahzadeh Benyamin, Soleimanian Gharehchopogh Farhad, Barshandeh Saeid
Summary: The paper introduces a novel discrete version of the Farmland Fertility Algorithm, utilizing various mechanisms and operators to tackle the TSP problem, demonstrating its effectiveness and superiority through simulation results.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Benyamin Abdollahzadeh, Saeid Barshandeh, Hatef Javadi, Nicola Epicoco
Summary: This paper introduces an enhanced binary SMA for solving the 0-1 knapsack problem at different scales. By using multiple transfer functions and bitwise and Gaussian mutation operators, along with penalty function and repair algorithm to handle infeasible solutions, the superiority of the proposed method is demonstrated.
ENGINEERING WITH COMPUTERS
(2022)
Article
Computer Science, Artificial Intelligence
Saeid Barshandeh, Mohammad Masdari, Gaurav Dhiman, Vahid Hosseini, Krishna K. Singh
Summary: The Internet of Things is a ubiquitous network that processes, collects, and analyzes data produced by IoT objects to monitor and organize the world. Accurate localization of IoT objects is essential, with DV-Hop algorithm being a widely used method accompanied by various techniques to increase accuracy.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Saeid Barshandeh, Reza Dana, Parinaz Eskandarian
Summary: This paper presents a novel Learning-Automata (LA)-based hybrid optimization algorithm for global optimization problems. The algorithm modifies the artificial Jellyfish search algorithm and Marine Predator Algorithm to reduce computational complexity while retaining their strengths. The LA mechanism is used to intelligently select the most optimal action for updating particles. Experimental results demonstrate the superiority of the proposed LA-based hybrid algorithm in solving benchmark functions and data clustering problems.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Engineering, Multidisciplinary
Farhad Soleimanian Gharehchopogh, Mohammad H. Nadimi-Shahraki, Saeid Barshandeh, Benyamin Abdollahzadeh, Hoda Zamani
Summary: This paper proposes the CQFFA algorithm by incorporating chaotic maps into the FFA algorithm, improving its convergence speed and exploration ability for solving optimization problems. Experimental results demonstrate that the CQFFA algorithm outperforms other competitor algorithms in widely-used test functions and real-world engineering problems.
JOURNAL OF BIONIC ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Saeid Barshandeh, Shima Koulaeizadeh, Mohammad Masdari, Benyamin AbdollahZadeh, Mahsa Ghasembaglou
Summary: This paper proposes a new positioning system to locate objects in 3D IoTs. The system combines the modified Slime Mold Algorithm with the Equilibrium Optimizer and integrates learning and neighborhood search strategies to enhance search efficiency. Experimental results demonstrate the superior accuracy and performance of the proposed algorithm in 3D IoTs.
APPLIED SOFT COMPUTING
(2023)