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Cartographic technique for determining areas of soil contamination by heavy metals

International Journal of Environmental Studies 2023年第2期80卷 451-463页

作者： Dmytruk, Yuriy Cherlinka, Vasyl Department of Ecology and General Biological Disciplines Podilskyi State University Kamianets-Podilskyi Ukraine Faculty of Science Institute of Geography Pavol Jozef Šafárik University Košice Slovakia R&D department EOS Data Analytics Mountain View CA United States

Soils are the interface of streams of matter and energy. In the modern world, they are constantly under man-made pressure, not least from pollution, so we need to monitor their status. If we know the points of impact, we can model the flows of solid particles and salts in solution, predict the trajectory of pollutants and, thereby, reduce the number of samples needed in a monitoring scheme. This is especially useful in areas of subdued relief where it is hard to see the zones of concentration. Sampling points may be selected according to accumulative surface curvature that separates shedding zones from the receiving zones where sampling should be concentrated. The cartographic model clearly indicates the zones of concentration and, so, minimises the chance of sampling the wrong places. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Heavy metals

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Enhancing Organizational Performance: Synergy of Cyber-Physical Systems, Cloud Services, and Crowdsensing

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International Journal of Crowd science 2025年第1期9卷 44-55页

作者： Al-Qerem, Ahmad Ali, Ali Mohd Nabot, Ahmad Jebreen, Issam Alauthman, Mohammad Alangari, Someah Aburub, Faisal Aldweesh, Amjad Computer Science Department Faculty of Information Technology Zarqa University Zarqa13110 Jordan Communications and Computer Engineering Department Faculty of Engineering Al-Ahliyya Amman University Amman19328 Jordan Department of Information Security University of Petra Amman11196 Jordan Department of Computer Science College of Science and Humanities Dawadmi Shaqra University Shaqra11911 Saudi Arabia Department of Business Intelligence and Data Analytics University of Petra Amman11196 Jordan College of Computing and Information Technology Shaqra University Shaqra11911 Saudi Arabia

In the contemporary business landscape, software has evolved into a strategic asset crucial for organizations seeking sustainable competitive advantage. The imperative of ensuring software quality becomes evident as low-quality software systems pose formidable challenges to organizational performance. This study delves into the profound impact of three key dimensions of information system quality on organizational performance—information quality (IQ), quality of service (QoS), and software quality (SQ). Anchored in the DeLone and McLean information system (IS) success model, a quantitative questionnaire was administered to 360 industry experts and academics. Rigorous data analysis, employing exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and structural equation modeling (SEM), revealed significant positive effects of all three quality dimensions on organizational performance. Among these dimensions, software quality emerged as the most influential, showcasing substantial total effects, closely followed by information and service qualities. The study underscores the tangible value derived from strategic investments in enhancing software, information, and service quality. Elevating these facets manifests as a catalyst for improved organizational performance, empowering decision-makers with accurate and timely information while enhancing user satisfaction with the system. This research contributes significantly to the IS success literature by empirically validating the synergistic relationship between information quality, service quality, software quality, and organizational outcomes. The systematic analysis offered in this study goes beyond theoretical validation, providing actionable insights for managers. The findings guide the prioritization of quality initiatives and resource allocation, enabling organizations to maximize competitive advantage. As a future research direction, investigating moderator influences and exploring alternate qualit

关键词： data quality

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Performance Improvement of Logistic Regression for Binary Classification by Gauss-Newton Method 22

Performance Improvement of Logistic Regression for Binary Cl...

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5th International Conference on Mathematics and Statistics, ICoMS 2022

作者： Jamhuri, Mohammad Mukhlash, Imam Irawan, Mohammad Isa Department of Mathematics Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Mathematics Faculty of Science and Technology UIN Maulana Malik Ibrahim Malang Indonesia

ISBN: (纸本)9781450396233

This paper proposes a new approach to optimizing cost function for binary logistic regression by the Gauss-Newton method. This method was applied to the backpropagation phase as a part of the training process to update the weighted coefficients. To show the performance of the approach, we used two data sets to train the logistic regression model for binary classification problems. Our experiment demonstrated that the proposed methods could perform better than gradient descent for both examples, as we expected. Furthermore, the performance of our approach is more advanced than the classical method, either in speed or accuracy. © 2022 ACM.

关键词： Cost functions

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A Comprehensive Analysis of Neutrosophic Bonferroni Mean Operator

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Neutrosophic Sets and Systems 2024年 64卷 54-76页

作者： Kanchana, A. Nagarajan, D. Broumi, S. Prastyo, Dedy Dwi Department of Mathematics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai602 105 India Department of Mathematics Rajalakshmi Institute of Technology Tamil Nadu Chennai India Laboratory of Information Processing Faculty of Science Ben M’Sik University Hassan II B.P 7955 Sidi Othman Casablanca Morocco Department of Statistics Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Surabaya60111 Indonesia

The Neutrosophic Bonferroni operator is a novel operator that we provide in this paper. Then the arithmetic operations for Neutrosophic Bonferroni operator is developed which tells the existence of Neutrosophic Bonferroni operator. Then its properties were discussed with special cases. To group decision-making issues with several attributes, arithmetic ranking operations and the Neutrosophic approach are used. The result is compared with the existing methodology. The suggested approach will more accurately give the decision maker the ideal attribute than the existing system does. Neutrophic multicriteria is a method of decision-making that makes use of ambiguity to integrate various criteria or factors—often with imprecise or ambiguous data—to reach a result. The neutrosophic multicriteria analysis enables the assessment of subjective and qualitative factors, which can assist in resolving conflicting goals and preferences. In Neutrosophic Multi-Attribute Group Decision Making (NMAGDM) problems, all the data supplied by the decision makers (DMs) is expressed in single-value Neutrosophic triangular and trapezoidal numbers, which are studied in this work and can improve the flexibility and precision of capturing uncertainty and aggregating preferences. Studying this operator is crucial because it can be utilised to resolve multi-attribute. © (2023), (University of New Mexico). All Rights Reserved.

关键词： Decision making

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N-Doped rGO-Like Carbon Prepared from Coconut Shell:Structure and Specific Capacitance

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Journal of Renewable Materials 2023年第4期11卷 1823-1833页

作者： Imam Khambali Budhi Priyanto Retno Asih Malik Anjelh Baqiya Muhammad Mahyiddin Ramli Nurul Huda Osman Sarayut Tunmee Hideki Nakajima Triwikantoro Mochamad Zainuri Darminto Department of Physics Faculty of Science and Data AnalyticsInstitut Teknologi Sepuluh NopemberSurabaya60111Indonesia Department of Electrical Engineering Faculty of EngineeringUniversity of Muhammadiyah MalangMalang65144Indonesia Geopolymer&Green Technology Centre of Excellence Universiti Malaysia PerlisArauPerlis02600Malaysia Applied Electromagnetic Laboratory 1 Department of PhysicsFaculty of ScienceUniversiti Putra MalaysiaSelangor43400Malaysia Synchrotron Light Research Institute(SLRI) Nakhon Ratchasima3000Thailand

An rGO−like carbon compound has been synthesized from biomass,i.e.,old coconut shell,by a carbonization process followed by heating at 400°C for 5 *** nitrogen doping was achieved by adding the urea(CH4N2O)and stirring at 70°C for 14 *** morphology and structure of the rGO-like carbon were investigated by electron microscopies and Raman *** presence of C-N functional groups was analyzed by Fourier transform infrared and synchrotron X-ray photoemission spectroscopy,while the particle and the specific capacitance were measured by particle sizer and cyclic *** highest specific capacitance of 72.78 F/g is achieved by the sample with 20%urea,having the smallest particles size and the largest surface *** corresponding sample has shown to be constituted by the appropriate amount of C–N pyrrolic and pyridinic defects.

关键词： N-doped rGO−like carbon coconut shell specific capacitance

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Synchronous Parallel Heuristics for Solving the Joint Order Batching and Picker Routing Problem 13

Synchronous Parallel Heuristics for Solving the Joint Order ...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Tran, Son Thai Almeida, Rui Jorge Defryn, Christof Van Nieuwenhuyse, Inneke School of Business and Economics Maastricth University Dept. of Quantitative Economics Maastricht Netherlands School of Business and Economics Maastricth University Dept. of Data Analytics and Digitization Maastricht Netherlands University of Antwerp Faculty of Business and Economics Dept. of Engineering Management Antwerp Belgium FlandersMake@UHasselt Data Science Institute Hasselt University Faculty of Sciences Hasselt Belgium

ISBN: (纸本)9798350308365

The joint order batching and picker routing problem is an important problem for improving warehouse efficiency. The goal is to minimize the total distance travel of picking customer orders. It is NP-hard, indicating that exact solutions are intractable for large instances. Many solution methods provided in the current literature use local search to solve the problem sequentially, often including a complex searching procedure for the order batching problem (OBP) followed by a simple heuristic for the picker routing problem (PRP). In this paper, we propose three heuristics that jointly solves the OBP and the PRP: two of these are combinations of variable neighborhood search, simulated annealing, and tabu search, while the third one uses guided local search. We discuss how the search procedure of the proposed algorithms can be parallelized, and benchmark them against state-of-the-art heuristics using well-studied instances. The results show a reduction of 3.06% to 7.63% in the geometric mean of the total travel distance across 64 instances. Increasing the number of threads in parallelization leads to diminishing returns in reducing running time and has no statistical effect on travel distance. In contrast, increasing the chunk size results in a linear increase in running time for all proposed algorithms, and improves the travel distance obtained when the batch size is 75 items. © 2024 IEEE.

关键词： Simulated annealing

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Partial optimality in the linear ordering problem 24

Partial optimality in the linear ordering problem

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Proceedings of the 41st International Conference on Machine Learning

作者： David Stein Bjoern Andres Faculty of Computer Science TU Dresden Germany Faculty of Computer Science TU Dresden Germany and Center for Scalable Data Analytics and AI Dresden/Leipzig

The linear ordering problem consists in finding a linear order < on a finite set A so as to minimize the sum of costs associated with pairs of elements a, b for which a < b. The problem is NP-hard and APX-hard. We introduce algorithms for solving the problem partially by deciding efficiently for some pairs (a, b) whether a < b is in an optimal solution. To do so, we construct maps from the feasible set of orders to itself and establish efficiently testable conditions on the cost function of the problem for which these maps are improving. We examine the effectiveness and efficiency of these conditions and algorithms empirically, on two data sets.

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A Hybrid Evaluation Index Approach in Optimizing Single Tuition Fee Cluster Validity 6

A Hybrid Evaluation Index Approach in Optimizing Single Tuit...

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6th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2022

作者： Yustanti, Wiyli Iriawan, Nur Irhamah Universitas Negeri Surabaya Faculty of Engineering Department of Informatics Surabaya Indonesia Institut Teknologi Sepuluh Nopember Faculty of Science and Data Analytics Department of Statistics Surabaya Indonesia

ISBN: (纸本)9798350399615

The grouping of the socio-economic level of new students at the time of registration at public universities is a problem faced by all state universities. Identifying the right group will have an impact on the students and the university. The quality of the results of a valid grouping will give a sense of fairness to the parents of students in paying tuition fees. On the other hand, the university also expects that the results of a valid grouping will contribute to optimal revenue. This study aims to evaluate the cluster structure of a single tuition fee at the State University of Surabaya. The existing cluster structure is compared with the results of grouping using nine clustering methods, namely K-Mean, Hierarchical, BIRCH, DBSCAN, Mini Batch K-Mean, Mean Shift, OPTICS, Spectral Clustering, and Mixture Gaussian. The proposed evaluation method is a combination of three evaluation concepts, namely internal validity (Silhouette-Index), external validity (Rand Index), and the percentage conformity value to the expected income factor (Revenue-Index). These three indicators are then calculated as the average value for each clustering method as Hybrid-Index. The highest Hybrid-Index is shown by the Mini Batch K-Mean algorithm, with an average value of 0.6420, so the Mini Batch K-Mean algorithm can be recommended as a method for grouping single tuition fees. © 2022 IEEE.

关键词： clustering clustering validity hybrid evaluation rand index silhouette index

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Leveraging Machine Learning to Assess Factors Influencing Undernourishment in Nigeria 1st

Leveraging Machine Learning to Assess Factors Influencing Un...

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1st International Conference on Intelligent Systems, Blockchain, and Communication Technologies, ISBCom 2024

作者： Mobark, Nada Elfiky, Noha Ahmedin, Ahmed Ibrahim, Ameera Abdel-Aziz, M. Hamad, Safwat Faculty of Computers and Information South Valley University Qena83523 Egypt Business Analytics and Data Science Department School of Economics and Business Administration Saint Mary’s College of California MoragaCA94575 United States Department of Artificial Intelligence Engineering Faculty of Computer Science and Engineering King Salman International University South Sinai46511 Egypt

ISBN: (纸本)9783031823763

Notwithstanding economic progress, Nigeria continues to countenance significant food security issues. This study investigates the root causes of this problem and attempts to develop predictive models to address hunger in Nigeria. The research covering data from 2000 to 2022, sourced primarily from the World Bank and other institutions. The trend analysis, along with the linear model, indicates that investment in farming is crucial for reducing undernourishment. Additionally, there is a strong relationship between agricultural expenditure, exports, access to electricity, and unemployment in relation to undernourishment. In this paper, a linear model, correlation analysis, ARIMA, and trend analysis are utilized to demonstrate how undernourishment, representing hunger and food insecurity, is influenced by other factors. As a result, it is recommended to maintain the unemployment rate between 3.5% and 3.7%, while ensuring that exceeds 5% of government spending is recommended. In other words, to combat hunger in Nigeria, it is important to focus on investing in agriculture, creating jobs, and improving infrastructure. This aligns with our findings and with another research around the world. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： ARIMA Nigeria predictive model Undernourishment

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Image Fusion Using Wavelet Transformation and XGboost Algorithm

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Computers, Materials & Continua 2024年第4期79卷 801-817页

作者： Shahid Naseem Tariq Mahmood Amjad Rehman Khan Umer Farooq Samra Nawazish Faten S.Alamri Tanzila Saba Department of Information Sciences Division of S&TUniversity of EducationLahore54770Pakistan Artificial Intelligence and Data Analytics(AIDA)Lab CCIS Prince Sultan UniversityRiyadh11586Saudi Arabia Faculty of Information Sciences University of EducationVehari CampusVehari61100Pakistan Department of Computer Science University of Engineering and TechnologyTaxila47050Pakistan Department of Mathematical Sciences College of SciencePrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Recently,there have been several uses for digital image *** fusion has become a prominent application in the domain of imaging *** create one final image that provesmore informative and helpful compared to the original input images,image fusion merges two or more initial images of the same *** fusion aims to produce,enhance,and transform significant elements of the source images into combined images for the sake of human visual *** fusion is commonly employed for feature extraction in smart robots,clinical imaging,audiovisual camera integration,manufacturing process monitoring,electronic circuit design,advanced device diagnostics,and intelligent assembly line robots,with image quality varying depending on *** research paper presents various methods for merging images in spatial and frequency domains,including a blend of stable and curvelet transformations,everageMax-Min,weighted principal component analysis(PCA),HIS(Hue,Intensity,Saturation),wavelet transform,discrete cosine transform(DCT),dual-tree Complex Wavelet Transform(CWT),and multiple wavelet *** fusion methods integrate data from several source images of an identical target,thereby enhancing information in an extremely efficient *** precisely,in imaging techniques,the depth of field constraint precludes images from focusing on every object,leading to the exclusion of certain *** tackle thess challanges,a very efficient multi-focus wavelet decomposition and recompositionmethod is *** use of these wavelet decomposition and recomposition techniques enables this method to make use of existing optimized wavelet code and filter *** simulated outcomes provide evidence that the suggested approach initially extracts particular characteristics from images in order to accurately reflect the level of clarity portrayed in the original *** study enhances the performance of the eXtreme Gradient Boosting(XGBoos

关键词： Image fusion max-min average CWT XGBoost DCT inclusive innovations spatial and frequency domain

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