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2. Paper Perfect: Robert Lang and the Science of Origami
- Author
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Foer, Joshua
- Published
- 2014
3. Cooperative Multiobjective Decision Support for the Paper Industry
- Author
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Murthy, Sesh, Akkiraju, Rama, Goodwin, Richard, Keskinocak, Pinar, Rachlin, John, Wu, Frederick, Yeh, James, Fuhrer, Robert, Kumaran, Santhosh, Aggarwal, Alok, Sturzenbecker, Martin, Jayaraman, Ranga, and Daigle, Robert
- Published
- 1999
4. Special Issue Paper: Robust Solutions and Risk Measures for a Supply Chain Planning Problem under Uncertainty
- Author
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Poojari, C. A., Lucas, C., and Mitra, G.
- Published
- 2008
5. Special Issue: "2022 and 2023 Selected Papers from Algorithms' Editorial Board Members".
- Author
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Werner, Frank
- Subjects
EDITORIAL boards ,ALGORITHMS ,OPTIMIZATION algorithms ,DIFFERENTIAL evolution ,QUADRATIC assignment problem ,MACHINE learning ,TABU search algorithm - Abstract
This document is a special issue of the journal Algorithms, featuring selected papers from the journal's editorial board members from 2022 and 2023. The issue includes 16 research papers covering a range of topics such as game theory, fault detection in cellular networks, optimization algorithms, machine learning, cryptocurrency trading, and more. Each paper presents its own unique research findings and methodologies. The issue aims to showcase the diverse research interests and expertise of the journal's editorial board members. [Extracted from the article]
- Published
- 2024
- Full Text
- View/download PDF
6. A fully-automated paper ECG digitisation algorithm using deep learning.
- Author
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Wu, Huiyi, Patel, Kiran Haresh Kumar, Li, Xinyang, Zhang, Bowen, Galazis, Christoforos, Bajaj, Nikesh, Sau, Arunashis, Shi, Xili, Sun, Lin, Tao, Yanda, Al-Qaysi, Harith, Tarusan, Lawrence, Yasmin, Najira, Grewal, Natasha, Kapoor, Gaurika, Waks, Jonathan W., Kramer, Daniel B., Peters, Nicholas S., and Ng, Fu Siong
- Subjects
DEEP learning ,ELECTROCARDIOGRAPHY ,ELECTRONIC paper ,ATRIAL fibrillation ,ALGORITHMS ,HEART failure ,HEART rate monitors - Abstract
There is increasing focus on applying deep learning methods to electrocardiograms (ECGs), with recent studies showing that neural networks (NNs) can predict future heart failure or atrial fibrillation from the ECG alone. However, large numbers of ECGs are needed to train NNs, and many ECGs are currently only in paper format, which are not suitable for NN training. We developed a fully-automated online ECG digitisation tool to convert scanned paper ECGs into digital signals. Using automated horizontal and vertical anchor point detection, the algorithm automatically segments the ECG image into separate images for the 12 leads and a dynamical morphological algorithm is then applied to extract the signal of interest. We then validated the performance of the algorithm on 515 digital ECGs, of which 45 were printed, scanned and redigitised. The automated digitisation tool achieved 99.0% correlation between the digitised signals and the ground truth ECG (n = 515 standard 3-by-4 ECGs) after excluding ECGs with overlap of lead signals. Without exclusion, the performance of average correlation was from 90 to 97% across the leads on all 3-by-4 ECGs. There was a 97% correlation for 12-by-1 and 3-by-1 ECG formats after excluding ECGs with overlap of lead signals. Without exclusion, the average correlation of some leads in 12-by-1 ECGs was 60–70% and the average correlation of 3-by-1 ECGs achieved 80–90%. ECGs that were printed, scanned, and redigitised, our tool achieved 96% correlation with the original signals. We have developed and validated a fully-automated, user-friendly, online ECG digitisation tool. Unlike other available tools, this does not require any manual segmentation of ECG signals. Our tool can facilitate the rapid and automated digitisation of large repositories of paper ECGs to allow them to be used for deep learning projects. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
7. Servis povezan s prijelomom Hrvatskog društva za fizikalnu i rehabilitacijsku medicinu Hrvatskoga liječničkog zbora – dokument o stajalištu.
- Author
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Grazio, Simeon, Nikolić, Tatjana, Luke Vrbanić, Tea Schnurrer, Poljičanin, Ana, and Grubišić, Frane
- Abstract
Copyright of Lijecnicki Vjesnik is the property of Croatian Medical Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Published
- 2024
- Full Text
- View/download PDF
8. A Machine Learning Model to Predict Citation Counts of Scientific Papers in Otology Field.
- Author
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Alohali, Yousef A., Fayed, Mahmoud S., Mesallam, Tamer, Abdelsamad, Yassin, Almuhawas, Fida, and Hagr, Abdulrahman
- Subjects
DECISION trees ,SERIAL publications ,NATURAL language processing ,BIBLIOMETRICS ,MACHINE learning ,REGRESSION analysis ,RANDOM forest algorithms ,CITATION analysis ,DESCRIPTIVE statistics ,PREDICTION models ,ARTIFICIAL neural networks ,MEDICAL research ,MEDICAL specialties & specialists ,ALGORITHMS - Abstract
One of the most widely used measures of scientific impact is the number of citations. However, due to its heavy-tailed distribution, citations are fundamentally difficult to predict but can be improved. This study was aimed at investigating the factors and parts influencing the citation number of a scientific paper in the otology field. Therefore, this work proposes a new solution that utilizes machine learning and natural language processing to process English text and provides a paper citation as the predicted results. Different algorithms are implemented in this solution, such as linear regression, boosted decision tree, decision forest, and neural networks. The application of neural network regression revealed that papers' abstracts have more influence on the citation numbers of otological articles. This new solution has been developed in visual programming using Microsoft Azure machine learning at the back end and Programming Without Coding Technology at the front end. We recommend using machine learning models to improve the abstracts of research articles to get more citations. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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9. Computing Science: Pencil, Paper, and Pi
- Author
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Hayes, Brian
- Published
- 2014
10. Cost Optimal Production-Scheduling Model Based on VNS-NSGA-II Hybrid Algorithm—Study on Tissue Paper Mill.
- Author
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Zhang, Huanhuan, Li, Jigeng, Hong, Mengna, Man, Yi, and He, Zhenglei
- Subjects
PAPER mills ,FLOW shop scheduling ,PRODUCTION scheduling ,INDUSTRIAL costs ,ALGORITHMS - Abstract
With the development of the customization concept, small-batch and multi-variety production will become one of the major production modes, especially for fast-moving consumer goods. However, this production mode has two issues: high production cost and the long manufacturing period. To address these issues, this study proposes a multi-objective optimization model for the flexible flow-shop to optimize the production scheduling, which would maximize the production efficiency by minimizing the production cost and makespan. The model is designed based on hybrid algorithms, which combine a fast non-dominated genetic algorithm (NSGA-II) and a variable neighborhood search algorithm (VNS). In this model, NSGA-II is the major algorithm to calculate the optimal solutions. VNS is to improve the quality of the solution obtained by NSGA-II. The model is verified by an example of a real-world typical FFS, a tissue papermaking mill. The results show that the scheduling model can reduce production costs by 4.2% and makespan by 6.8% compared with manual scheduling. The hybrid VNS-NSGA-II model also shows better performance than NSGA-II, both in production cost and makespan. Hybrid algorithms are a good solution for multi-objective optimization issues in flexible flow-shop production scheduling. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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- View/download PDF
11. S-integral points on elliptic curves - Notes on a paper of B. M. M. de Weger
- Author
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HERRMANN, Emanuel and PETHŐ, Attila
- Published
- 2001
12. A Paper-and-Pencil gcd Algorithm for Gaussian Integers
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Szabó, Sándor
- Published
- 2005
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13. Developments in the Design of Experiments, Correspondent Paper
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Atkinson, A. C.
- Published
- 1982
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14. Invited Papers
- Author
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Aldous, D. J., Arratia, R. A., Barbour, A. D., Bollobás, B., Diaconis, P., Donnelly, P. J., Erdős, P., Harper, L. H., Harris, B., Kolchin, V. F., Odlyzko, A. M., Pitman, J. W., Pittel, B. G., Shepp, L. A., Spencer, J., Takács, L., Vatutin, V. A., Vershik, A. M., Viskov, O. V., and Wilf, H. S.
- Published
- 1992
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- View/download PDF
15. Tools and algorithms for the construction and analysis of systems: a special issue on tool papers for TACAS 2021.
- Author
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Jensen, Peter Gjøl and Neele, Thomas
- Subjects
ALGORITHMS ,SOFTWARE verification ,INTEGRATED circuit verification ,SYSTEMS software ,CONFERENCES & conventions - Abstract
This special issue contains six revised and extended versions of tool papers that appeared in the proceedings of TACAS 2021, the 27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems. The issue is dedicated to the realization of algorithms in tools and the studies of the application of these tools for analysing hard- and software systems. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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16. Research on the Fusion of Hybrid Fuzzy Clustering Algorithm and Computer Automatic Test Paper Composition Algorithm.
- Author
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Kan, Baopeng
- Subjects
COMPUTERS ,COMPUTER algorithms ,FUZZY algorithms ,COMPUTER workstation clusters ,ALGORITHMS ,HIGHER education exams - Abstract
In order to improve the effect of intelligent automatic test paper composition, this paper combines the hybrid fuzzy clustering algorithm to study the computer automatic test paper composition algorithm. In this paper, a computer automatic test paper composition system based on hybrid fuzzy clustering algorithm is constructed. Moreover, the hybrid fuzzy clustering method used in this paper is used as the basic algorithm of the system, and the algorithm is improved according to the actual needs of intelligent paper composition. In addition, this paper uses an intelligent algorithm to input the relevant constraint parameters and combines the original parameters to select the most suitable test questions from the database and combine them into test papers. Finally, this paper constructs the system structure based on the requirements of intelligent test paper composition. The experimental research shows that the computer automatic test paper composition system based on the hybrid fuzzy clustering algorithm proposed in this paper has a good test paper composition function, which can effectively promote the progress of the intelligent examination mode in colleges and universities. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
17. Automated analysis of pen-on-paper spirals for tremor detection, quantification, and differentiation.
- Author
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Rajan, Roopa, Anandapadmanabhan, Reghu, Nageswaran, Sharmila, Radhakrishnan, Vineeth, Saini, Arti, Krishnan, Syam, Gupta, Anu, Vishnu, Venugopalan Y., Pandit, Awadh K., Singh, Rajesh Kumar, Radhakrishnan, Divya M, Singh, Mamta Bhushan, Bhatia, Rohit, Srivastava, Achal, Kishore, Asha, and Padma Srivastava, M. V.
- Subjects
STATISTICS ,RESEARCH ,CONFIDENCE intervals ,ANALYSIS of variance ,TASK performance ,HANDWRITING ,ACCELEROMETERS ,DYSTONIA ,MOVEMENT disorders ,TREMOR ,DRAWING ,DESCRIPTIVE statistics ,PARKINSON'S disease ,SENSITIVITY & specificity (Statistics) ,DATA analysis ,RECEIVER operating characteristic curves ,DATA analysis software ,ALGORITHMS - Abstract
OBJECTIVE: To develop an automated algorithm to detect, quantify, and differentiate between tremor using pen-on-paper spirals. METHODS: Patients with essential tremor (n = 25), dystonic tremor (n = 25), Parkinson’s disease (n = 25), and healthy volunteers (HV, n = 25) drew free-hand spirals. The algorithm derived the mean deviation (MD) and tremor variability from scanned images. MD and tremor variability were compared with 1) the Bain and Findley scale, 2) the Fahn–Tolosa–Marin tremor rating scale (FTM–TRS), and 3) the peak power and total power of the accelerometer spectra. Inter and intra loop widths were computed to differentiate between the tremor. RESULTS: MD was higher in the tremor group (48.9±26.3) than in HV (26.4±5.3; p < 0.001). The cut-off value of 30.3 had 80.9% sensitivity and 76.0% specificity for the detection of the tremor [area under the curve: 0.83; 95% confidence index (CI): 0.75, 0.91, p < 0.001]. MD correlated with the Bain and Findley ratings (rho = 0.491, p = 0 < 0.001), FTM–TRS part B (rho = 0.260, p = 0.032) and accelerometric measures of postural tremor (total power, rho = 0.366, p < 0.001; peak power, rho = 0.402, p < 0.001). Minimum Detectable Change was 19.9%. Inter loop width distinguished Parkinson’s disease spirals from dystonic tremor (p < 0.001, 95% CI: 54.6, 211.1), essential tremor (p = 0.003, 95% CI: 28.5, 184.9), or HV (p = 0.036, 95% CI: -160.4, -3.9). CONCLUSION: The automated analysis of pen-on-paper spirals generated robust variables to quantify the tremor and putative variables to distinguish them from each other. SIGNIFICANCE: This technique maybe useful for epidemiological surveys and follow-up studies on tremor. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
18. Digitalized Control Algorithm of Bridgeless Totem-Pole PFC with a Simple Control Structure Based on the Phase Angle.
- Author
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Lee, Gi-Young, Park, Hae-Chan, Ji, Min-Woo, and Kim, Rae-Young
- Subjects
ELECTRIC current rectifiers ,ELECTRONIC paper ,PHASE-locked loops ,ALGORITHMS ,ANGLES ,VOLTAGE - Abstract
Compared to the conventional boost power factor correction (PFC) converter, a totem-pole bridgeless PFC has high efficiency because it does not have an input diode rectifier stage, but a current spike may occur when the polarity of the grid voltage changes. This paper proposes a digital control algorithm for bridgeless totem-pole PFC with a simple control structure based on the phase angle of grid voltage. The proposed algorithm has a PI-based double-loop control structure and performs DC-link voltage and input inductor current control. Rectifying switches operate based on the proposed rectification algorithm using phase angle information calculated through a single-phase phase-locked loop (PLL) to prevent current spikes. The feed-forward duty ratio value is calculated according to the polarity of the grid voltage and added to the double-loop controller to perform appropriate power factor control. The performance and feasibility of the proposed control algorithm are verified through a 3 kW hardware prototype. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
19. Optimization of Texture Rendering of 3D Building Model Based on Vertex Importance.
- Author
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Shen, Wenfei, Huo, Liang, Shen, Tao, Zhang, Miao, and Li, Yucai
- Subjects
TEXTURE mapping ,DATA modeling ,CURVATURE ,ALGORITHMS - Abstract
In 3D building models, a large number of texture maps with different sizes increase the number of model data loading and drawing batches, which greatly reduces the drawing efficiency of the model. Therefore, this paper proposes a texture set mapping method based on vertex importance. Firstly, based on the 2D space boxing algorithm, the texture maps are merged and a series of Mipmap texture maps are generated, and then the vertex curvature, texture variability and location information of each vertex are calculated, normalized, and weighted to get the importance of each vertex, and then finally, different Mipmap-level textures are remapped according to the importance of the vertices. The experiment proves that the algorithm in this paper can reduce the amount of texture data on the one hand, and avoid the rendering pressure brought by the still large amount of data after merging on the other hand, so as to improve the rendering efficiency of the model. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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- View/download PDF
20. Comments on a Paper by Romesh Saigal: "A Constrained Shortest Route Problem"
- Author
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Rosseel, Marc
- Published
- 1968
21. Comments on the Paper: 'Heuristic and Special Case Algorithms for Dispersion Problems' by S. S. Ravi, D. J. Rosenkrantz, and G. K. Tayi
- Author
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Tamir, Arie
- Published
- 1998
22. Development and Validation of an Algorithm for the Digitization of ECG Paper Images.
- Author
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Randazzo, Vincenzo, Puleo, Edoardo, Paviglianiti, Annunziata, Vallan, Alberto, and Pasero, Eros
- Subjects
DIGITIZATION ,DIGITAL images ,ELECTROCARDIOGRAPHY ,HEART rate monitors ,PEARSON correlation (Statistics) ,MEASUREMENT errors ,HEART beat ,ALGORITHMS - Abstract
The electrocardiogram (ECG) signal describes the heart's electrical activity, allowing it to detect several health conditions, including cardiac system abnormalities and dysfunctions. Nowadays, most patient medical records are still paper-based, especially those made in past decades. The importance of collecting digitized ECGs is twofold: firstly, all medical applications can be easily implemented with an engineering approach if the ECGs are treated as signals; secondly, paper ECGs can deteriorate over time, therefore a correct evaluation of the patient's clinical evolution is not always guaranteed. The goal of this paper is the realization of an automatic conversion algorithm from paper-based ECGs (images) to digital ECG signals. The algorithm involves a digitization process tested on an image set of 16 subjects, also with pathologies. The quantitative analysis of the digitization method is carried out by evaluating the repeatability and reproducibility of the algorithm. The digitization accuracy is evaluated both on the entire signal and on six ECG time parameters (R-R peak distance, QRS complex duration, QT interval, PQ interval, P-wave duration, and heart rate). Results demonstrate the algorithm efficiency has an average Pearson correlation coefficient of 0.94 and measurement errors of the ECG time parameters are always less than 1 mm. Due to the promising experimental results, the algorithm could be embedded into a graphical interface, becoming a measurement and collection tool for cardiologists. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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23. Scientific papers and artificial intelligence. Brave new world?
- Author
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Nexøe, Jørgen
- Subjects
COMPUTERS ,MANUSCRIPTS ,ARTIFICIAL intelligence ,MACHINE learning ,DATA analysis ,MEDICAL literature ,MEDICAL research ,ALGORITHMS - Published
- 2023
- Full Text
- View/download PDF
24. Social and content aware One-Class recommendation of papers in scientific social networks.
- Author
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Wang, Gang, He, XiRan, and Ishuga, Carolyne Isigi
- Subjects
INFORMATION technology ,SOCIAL networks ,SPARSE graphs ,HYBRID computers (Computer architecture) ,HYBRID power systems - Abstract
With the rapid development of information technology, scientific social networks (SSNs) have become the fastest and most convenient way for researchers to communicate with each other. Many published papers are shared via SSNs every day, resulting in the problem of information overload. How to appropriately recommend personalized and highly valuable papers for researchers is becoming more urgent. However, when recommending papers in SSNs, only a small amount of positive instances are available, leaving a vast amount of unlabelled data, in which negative instances and potential unseen positive instances are mixed together, which naturally belongs to One-Class Collaborative Filtering (OCCF) problem. Therefore, considering the extreme data imbalance and data sparsity of this OCCF problem, a hybrid approach of Social and Content aware One-class Recommendation of Papers in SSNs, termed SCORP, is proposed in this study. Unlike previous approaches recommended to address the OCCF problem, social information, which has been proved playing a significant role in performing recommendations in many domains, is applied in both the profiling of content-based filtering and the collaborative filtering to achieve superior recommendations. To verify the effectiveness of the proposed SCORP approach, a real-life dataset from CiteULike was employed. The experimental results demonstrate that the proposed approach is superior to all of the compared approaches, thus providing a more effective method for recommending papers in SSNs. [ABSTRACT FROM AUTHOR]
- Published
- 2017
- Full Text
- View/download PDF
25. Utilizing tables, figures, charts and graphs to enhance the readability of a research paper.
- Author
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Divecha C. A., Tullu M. S., and Karande S.
- Subjects
GRAPHIC arts ,READABILITY (Literary style) ,SERIAL publications ,RESEARCH methodology ,COPYRIGHT ,MEDICAL research ,ALGORITHMS - Abstract
The authors offer observation on utilizing tables, figures, charts and graphs to help understand the research presented in a simple manner but also engage and sustain the reader's interest. Topics discussed include benefits provided by the use of tables/figures/charts/graphs, general methodology of design and submission, and copyright issues of using material from government publications/public domain.
- Published
- 2023
- Full Text
- View/download PDF
26. LA INTEL·LIGÈNCIA ARTIFICIAL EN LA DETECCIÓ DE LES PRÀCTIQUES DE BID RIGGING: EL PAPER CAPDAVANTER DE L'ACCO.
- Author
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Jiménez Cardona, Noemí
- Subjects
GOVERNMENT purchasing ,ARTIFICIAL intelligence ,ANTITRUST law ,SOFTWARE development tools ,CARTELS - Abstract
Copyright of Revista Catalana de Dret Públic is the property of Revista Catalana de Dret Public and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Published
- 2022
- Full Text
- View/download PDF
27. CAI versus Paper and Pencil — discrepancies in students' performance
- Author
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HATIVA, NIRA
- Published
- 1988
28. Digital marginalization, data marginalization, and algorithmic exclusions: a critical southern decolonial approach to datafication, algorithms, and digital citizenship from the Souths.
- Author
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Chaka, Chaka
- Subjects
CITIZENSHIP ,DECOLONIZATION ,ELECTRONIC paper ,ALGORITHMS ,COMMUNITIES ,CHIEF information officers - Abstract
This paper explores digital marginalization, data marginalization, and algorithmic exclusions in the Souths. To this effect, it argues that underrepresented users and communities continue to be marginalized and excluded by digital technologies, by big data, and by algorithms employed by organizations, corporations, institutions, and governments in various data jurisdictions. Situating data colonialism within the Souths, the paper contends that data ableism, data disablism, and data colonialism are at play when data collected, collated, captured, configured, and processed from underrepresented users and communities is utilized by mega entities for their own multiple purposes. It also maintains that data coloniality, as opposed to data colonialism, is impervious to legal and legislative interventions within data jurisdictions. Additionally, it discusses digital citizenship (DC) and its related emerging regimes. Moreover, the paper argues that digital exclusion transcends the simplistic haves versus the have nots dualism as it manifests itself in multiple layers and in multiple dimensions. Furthermore, it characterizes how algorithmic exclusions tend to perpetuate historical human biases despite the pervasive view that algorithms are autonomous, neutral, rational, objective, fair, unbiased, and non-human. Finally, the paper advances a critical southern decolonial (CSD) approach to datafication, algorithms, and digital citizenship by means of which data coloniality, algorithmic coloniality, and the coloniality embodied in DC have to be critiqued, challenged, and dismantled. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
29. Quantifying the impact of scholarly papers based on higher-order weighted citations.
- Author
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Bai, Xiaomei, Zhang, Fuli, Hou, Jie, Lee, Ivan, Kong, Xiangjie, Tolba, Amr, and Xia, Feng
- Subjects
CITATION analysis ,SCHOLARLY publishing ,BIBLIOMETRICS ,SIMULATION methods & models ,ALGORITHMS - Abstract
Quantifying the impact of a scholarly paper is of great significance, yet the effect of geographical distance of cited papers has not been explored. In this paper, we examine 30,596 papers published in Physical Review C, and identify the relationship between citations and geographical distances between author affiliations. Subsequently, a relative citation weight is applied to assess the impact of a scholarly paper. A higher-order weighted quantum PageRank algorithm is also developed to address the behavior of multiple step citation flow. Capturing the citation dynamics with higher-order dependencies reveals the actual impact of papers, including necessary self-citations that are sometimes excluded in prior studies. Quantum PageRank is utilized in this paper to help differentiating nodes whose PageRank values are identical. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
30. Using Paper Texture for Choosing a Suitable Algorithm for Scanned Document Image Binarization.
- Author
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Lins, Rafael Dueire, Bernardino, Rodrigo, Barboza, Ricardo da Silva, and De Oliveira, Raimundo Correa
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DOCUMENT imaging systems ,HISTORICAL source material ,TEXTURES ,ALGORITHMS - Abstract
The intrinsic features of documents, such as paper color, texture, aging, translucency, the kind of printing, typing or handwriting, etc., are important with regard to how to process and enhance their image. Image binarization is the process of producing a monochromatic image having its color version as input. It is a key step in the document processing pipeline. The recent Quality-Time Binarization Competitions for documents have shown that no binarization algorithm is good for any kind of document image. This paper uses a sample of the texture of the scanned historical documents as the main document feature to select which of the 63 widely used algorithms, using five different versions of the input images, totaling 315 document image-binarization schemes, provides a reasonable quality-time trade-off. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
31. ITERATIVE ALGORITHMS FOR VARIATIONAL INCLUSIONS IN BANACH SPACES.
- Author
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ANSARI, QAMRUL HASAN, BALOOEE, JAVAD, and PETRUŞEL, ADRIAN
- Subjects
BANACH spaces ,LIPSCHITZ continuity ,PAPER arts ,DIFFERENTIAL inclusions ,ALGORITHMS - Abstract
The present paper is in two folds. In the first fold, we prove the Lipschitz continuity of the proximal mapping associated with a general strongly H-monotone mapping and compute an estimate of its Lipschitz constant under some mild assumptions imposed on the mapping H involved in the proximal mapping. We provide two examples to show that a maximal monotone mapping need not be a general H-monotone for a single-valued mapping H from a Banach space to its dual space. A class of multi-valued nonlinear variational inclusion problems is considered, and by using the notion of proximal mapping and Nadler's technique, an iterative algorithm with mixed errors is suggested to compute its solutions. Under some appropriate hypotheses imposed on the mappings and parameters involved in the multi-valued nonlinear variational inclusion problem, the strong convergence of the sequences generated by the proposed algorithm to a solution of the aforesaid problem is verified. The second fold of this paper investigates and analyzes the notion of Cn-monotone mappings defined and studied in [S.Z. Nazemi, A new class of monotone mappings and a new class of variational inclusions in Banach spaces, J. Optim. Theory Appl. 155(3)(2012) 785-795]. Several comments related to the results and algorithm appeared in the above mentioned paper are given. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
32. Guest editorial: AI for computational audition—sound and music processing.
- Author
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Li, Zijin, Wang, Wenwu, Zhang, Kejun, and Zhu, Mengyao
- Subjects
ARTIFICIAL intelligence ,INTERDISCIPLINARY research ,TRANSVERSAL lines ,ALGORITHMS - Abstract
Nowadays, the application of artificial intelligence (AI) algorithms and techniques is ubiquitous and transversal. Fields that take advantage of AI advances include sound and music processing. The advances in interdisciplinary research potentially yield new insights that may further advance the AI methods in this field. This special issue aims to report recent progress and spur new research lines in AI-driven sound and music processing, especially within interdisciplinary research scenarios. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
33. Millimeter-Wave Radar-Based Identity Recognition Algorithm Built on Multimodal Fusion.
- Author
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Guo, Jian, Wei, Jingpeng, Xiang, Yashan, and Han, Chong
- Subjects
FEATURE extraction ,HEART rate monitors ,ALGORITHMS ,SIGNAL-to-noise ratio - Abstract
Millimeter-wave radar-based identification technology has a wide range of applications in persistent identity verification, covering areas such as security production, healthcare, and personalized smart consumption systems. It has received extensive attention from the academic community due to its advantages of being non-invasive, environmentally insensitive and privacy-preserving. Existing identification algorithms mainly rely on a single signal, such as breathing or heartbeat. The reliability and accuracy of these algorithms are limited due to the high similarity of breathing patterns and the low signal-to-noise ratio of heartbeat signals. To address the above issues, this paper proposes an algorithm for multimodal fusion for identity recognition. This algorithm extracts and fuses features derived from phase signals, respiratory signals, and heartbeat signals for identity recognition purposes. The spatial features of signals with different modes are first extracted by the residual network (ResNet), after which these features are fused with a spatial-channel attention fusion module. On this basis, the temporal features are further extracted with a time series-based self-attention mechanism. Finally, the feature vectors of the user's vital sign modality are obtained to perform identity recognition. This method makes full use of the correlation and complementarity between different modal signals to improve the accuracy and reliability of identification. Simulation experiments show that the algorithm identity recognition proposed in this paper achieves an accuracy of 94.26% on a 20-subject self-test dataset, which is much higher than that of the traditional algorithm, which is about 85%. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
34. Special issue "Discrete optimization: Theory, algorithms and new applications".
- Author
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Werner, Frank
- Subjects
MATHEMATICAL optimization ,METAHEURISTIC algorithms ,ONLINE algorithms ,LINEAR matrix inequalities ,ALGORITHMS ,ROBUST stability analysis ,NONLINEAR integral equations - Abstract
This document is an editorial for a special issue of the journal AIMS Mathematics on the topic of discrete optimization. The issue includes 21 papers covering a range of subjects, including molecular trees, network systems, variational inequality problems, scheduling, image restoration, spectral clustering, integral equations, convex functions, graph products, optimization algorithms, air quality prediction, humanitarian planning, inertial methods, neural networks, transportation problems, emotion identification, fixed-point problems, structural engineering design, single machine scheduling, and ensemble learning. The papers present new theoretical results, algorithms, and applications in these areas. The guest editor expresses gratitude to the journal staff and reviewers and hopes that readers will find inspiration for their own research. [Extracted from the article]
- Published
- 2024
- Full Text
- View/download PDF
35. A BPNN Model-Based AdaBoost Algorithm for Estimating Inside Moisture of Oil–Paper Insulation of Power Transformer.
- Author
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Liu, Jiefeng, Ding, Zheshi, Fan, Xianhao, Geng, Chuhan, Song, Boshu, Wang, Qingyin, and Zhang, Yiyi
- Subjects
POWER transformers ,TRANSFORMER insulation ,MOISTURE ,ALGORITHMS ,MACHINE learning ,CLASSIFICATION algorithms - Abstract
The traditional method for transformer moisture diagnosis is to establish empirical equations between feature parameters extracted from frequency domain spectroscopy (FDS) and the transformer’s moisture content. However, the established empirical equation may not be applicable to a novel testing environment, resulting in an unreliable evaluation result. In this regard, it is acknowledged that FDS combined with machine learning is more suitable for estimating moisture content in a variety of test environments. Nonetheless, the accuracy of the estimation results obtained using the existing method is limited by the algorithm’s inability to generalize. To address this issue, we propose an AdaBoost algorithm-enhanced back-propagation neural network (BP_AdaBoost). This study creates a database by extracting feature parameters from the FDS that characterize the insulation states of the prepared samples. Then, using the BP_AdaBoost algorithm and the newly constructed database, the moisture estimation models are trained. Finally, the results of the estimation are discussed in terms of laboratory and field transformers. By comparing the proposed BP_AdaBoost algorithm to other intelligence algorithms, it is demonstrated that it not only performs better in generalization, but also maintains a high level of accuracy. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
36. Using Distance Transform Based Algorithms for Extracting Measures of the Fiber Network in Volume Images of Paper.
- Author
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Svensson, Stina and Aronsson, Mattias
- Subjects
FIBERS ,ALGORITHMS ,FOUNDATIONS of arithmetic ,CORDAGE ,PAPER - Abstract
Presents a study which showed how curve and surface representations of fiber network, fiber wall and fiber lumen can be computed using distance transform based algorithms. Motive for analyzing volume images of paper; Uses of the representations; Levels of detail in which the analysis of paper and paper fibers can be divided.
- Published
- 2003
- Full Text
- View/download PDF
37. Special Issue on papers from the 2019 Workshop on Models and Algorithms for Planning and Scheduling Problems.
- Author
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Khuller, Samir
- Subjects
SCHEDULING ,ALGORITHMS ,ONLINE algorithms - Abstract
The paper "Well-behaved Online Load Balancing Against Strategic Jobs" by Li, Li and Wu considers a truthful online load-balancing problem with the objective of the makespan minimization on related machines. The 2019 workshop on models and algorithms for planning and scheduling problems was held in Renesse (The Netherlands). [Extracted from the article]
- Published
- 2023
- Full Text
- View/download PDF
38. Smart Random Walk Distributed Secured Edge Algorithm Using Multi-Regression for Green Network.
- Author
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Saba, Tanzila, Haseeb, Khalid, Rehman, Amjad, Damaševičius, Robertas, and Bahaj, Saeed Ali
- Subjects
RANDOM walks ,ALGORITHMS ,ARTIFICIAL intelligence ,INTERNET of things ,ELECTRONIC paper ,INTERNET traffic - Abstract
Smart communication has significantly advanced with the integration of the Internet of Things (IoT). Many devices and online services are utilized in the network system to cope with data gathering and forwarding. Recently, many traffic-aware solutions have explored autonomous systems to attain the intelligent routing and flowing of internet traffic with the support of artificial intelligence. However, the inefficient usage of nodes' batteries and long-range communication degrades the connectivity time for the deployed sensors with the end devices. Moreover, trustworthy route identification is another significant research challenge for formulating a smart system. Therefore, this paper presents a smart Random walk Distributed Secured Edge algorithm (RDSE), using a multi-regression model for IoT networks, which aims to enhance the stability of the chosen IoT network with the support of an optimal system. In addition, by using secured computing, the proposed architecture increases the trustworthiness of smart devices with the least node complexity. The proposed algorithm differs from other works in terms of the following factors. Firstly, it uses the random walk to form the initial routes with certain probabilities, and later, by exploring a multi-variant function, it attains long-lasting communication with a high degree of network stability. This helps to improve the optimization criteria for the nodes' communication, and efficiently utilizes energy with the combination of mobile edges. Secondly, the trusted factors successfully identify the normal nodes even when the system is compromised. Therefore, the proposed algorithm reduces data risks and offers a more reliable and private system. In addition, the simulations-based testing reveals the significant performance of the proposed algorithm in comparison to the existing work. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
39. AI GODS, JEANS GODS, AND THRIFT GODS: RESPONDING TO RESPONSES TO THE BLESSED BY THE ALGORITHM PAPER (SINGLER 2020).
- Author
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Singler, Beth
- Subjects
GODS ,ARTIFICIAL intelligence ,ALGORITHMS ,THRIFT institutions - Published
- 2023
- Full Text
- View/download PDF
40. The contribution of cause-effect link to representing the core of scientific paper—The role of Semantic Link Network.
- Author
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Cao, Mengyun, Sun, Xiaoping, and Zhuge, Hai
- Subjects
COMPLEXITY (Philosophy) ,CAUSATION (Philosophy) ,SEMANTICS ,RESEARCH ,PHILOSOPHY - Abstract
The Semantic Link Network is a general semantic model for modeling the structure and the evolution of complex systems. Various semantic links play different roles in rendering the semantics of complex system. One of the basic semantic links represents cause-effect relation, which plays an important role in representation and understanding. This paper verifies the role of the Semantic Link Network in representing the core of text by investigating the contribution of cause-effect link to representing the core of scientific papers. Research carries out with the following steps: (1) Two propositions on the contribution of cause-effect link in rendering the core of paper are proposed and verified through a statistical survey, which shows that the sentences on cause-effect links cover about 65% of key words within each paper on average. (2) An algorithm based on syntactic patterns is designed for automatically extracting cause-effect link from scientific papers, which recalls about 70% of manually annotated cause-effect links on average, indicating that the result adapts to the scale of data sets. (3) The effects of cause-effect link on four schemes of incorporating cause-effect link into the existing instances of the Semantic Link Network for enhancing the summarization of scientific papers are investigated. The experiments show that the quality of the summaries is significantly improved, which verifies the role of semantic links. The significance of this research lies in two aspects: (1) it verifies that the Semantic Link Network connects the important concepts to render the core of text; and, (2) it provides an evidence for realizing content services such as summarization, recommendation and question answering based on the Semantic Link Network, and it can inspire relevant research on content computing. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
41. Application of Motion Capture Based on Digital Filtering Algorithm in Sports Dance Teaching.
- Author
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Rao, Fan
- Subjects
MOTION capture (Human mechanics) ,INTELLIGENT sensors ,ELECTRONIC paper ,ALGORITHMS ,MOTION detectors ,SYSTEMS design - Abstract
In order to improve the teaching effect of sports dance, this paper analyzes the traditional dance teaching motion capture, uses sensor motion perception algorithms to capture sports dance motion perception, and designs an intelligent sensor system that can be used for sports dance motion capture. Moreover, this paper combines the digital filter algorithm to design the hardware system structure of the sports dance motion capture system and builds a motion capture system for sports dance teaching based on the digital filter algorithm according to actual needs. In addition, this paper combines the simulation test to evaluate the performance of the system designed in this paper. The research results show that the motion capture system for sports dance teaching based on the digital filtering algorithm proposed in this paper can play an important role in sports dance teaching and effectively improve the efficiency of sports dance teaching. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
42. Building Crack Detection Based on Digital Image Processing Technology and Multiscale Feature Analysis Automatic Detection Algorithm.
- Author
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Liu, Chenguang
- Subjects
DIGITAL image processing ,SMART structures ,ENGINEERING personnel ,ELECTRONIC paper ,ALGORITHMS ,CRACKING of concrete - Abstract
At present, the monitoring of concrete cracks is still mainly carried out by engineering personnel using simple mechanical monitoring instruments. The human inspection will undoubtedly be interfered by the individual's psychological, physical, and external conditions, and there may also be unobjective emotions, so it is impossible to ensure that the quality of the detection is up to standard and accurate. This paper combines digital image processing technology and multiscale feature analysis automatic detection algorithm to construct an intelligent building structure crack detection system. Moreover, this paper proposes an enrichment scheme for the unknown partially entangled states of building microparticles and utilizes the entanglement exchange process based on the Raman interaction of two building microparticles. The experimental results show that the automatic detection method of building cracks based on digital image processing technology and multiscale feature analysis has a good effect. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
43. A Review on Federated Learning and Machine Learning Approaches: Categorization, Application Areas, and Blockchain Technology.
- Author
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Ogundokun, Roseline Oluwaseun, Misra, Sanjay, Maskeliunas, Rytis, and Damasevicius, Robertas
- Subjects
BLOCKCHAINS ,ARTIFICIAL intelligence ,MACHINE learning ,CONFERENCE papers ,ALGORITHMS ,SCIENCE publishing - Abstract
Federated learning (FL) is a scheme in which several consumers work collectively to unravel machine learning (ML) problems, with a dominant collector synchronizing the procedure. This decision correspondingly enables the training data to be distributed, guaranteeing that the individual device's data are secluded. The paper systematically reviewed the available literature using the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guiding principle. The study presents a systematic review of appliable ML approaches for FL, reviews the categorization of FL, discusses the FL application areas, presents the relationship between FL and Blockchain Technology (BT), and discusses some existing literature that has used FL and ML approaches. The study also examined applicable machine learning models for federated learning. The inclusion measures were (i) published between 2017 and 2021, (ii) written in English, (iii) published in a peer-reviewed scientific journal, and (iv) Preprint published papers. Unpublished studies, thesis and dissertation studies, (ii) conference papers, (iii) not in English, and (iv) did not use artificial intelligence models and blockchain technology were all removed from the review. In total, 84 eligible papers were finally examined in this study. Finally, in recent years, the amount of research on ML using FL has increased. Accuracy equivalent to standard feature-based techniques has been attained, and ensembles of many algorithms may yield even better results. We discovered that the best results were obtained from the hybrid design of an ML ensemble employing expert features. However, some additional difficulties and issues need to be overcome, such as efficiency, complexity, and smaller datasets. In addition, novel FL applications should be investigated from the standpoint of the datasets and methodologies. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
44. Research on the 3D Virtual Product Network Display Algorithm Based on Digital Drive.
- Author
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Zhang, Qian, Guo, Xiaoying, Liang, Hui, and Sun, Maojun
- Subjects
VIRTUAL networks ,HOUGH transforms ,ALGORITHMS ,ELECTRONIC paper ,IMAGE analysis ,THREE-dimensional display systems - Abstract
In order to improve the effect of 3D virtual product network display, this paper combines digital drive technology to analyze the virtual simulation algorithm and proposes a digital drive-based Hough transform clustering virtual image processing algorithm. Through the knowledge of clustering and generalized Hough transform, generalized Hough transform is applied to clustering. Moreover, this paper uses cluster analysis to determine the image characteristics of three-dimensional virtual products. In addition, this article combines the methods proposed in this article to construct a three-dimensional virtual product network display system. The research shows that the digital-driven 3D virtual product network display algorithm model proposed in this paper has a good 3D virtual display effect. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
45. Digital Mining Algorithm of English Translation Course Information Based on Digital Twin Technology.
- Author
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Juan Yang
- Subjects
MINES & mineral resources ,ELECTRONIC paper ,PATTERNS (Mathematics) ,ALGORITHMS ,TRANSLATING & interpreting - Abstract
Cross-language communication puts forward higher requirements for information mining in English translation course. Aiming at the problem that the frequent patterns in the current digital mining algorithms produce a large number of patterns and rules, with a long execution time, this paper proposes a digital mining algorithm for English translation course information based on digital twin technology. According to the results of word segmentation and tagging, the feature words of English translation text are extracted, and the cross-language mapping of text is established by using digital twin technology. The estimated probability of text translation is maximized by corresponding relationship. The text information is transformed into text vector, the semantic similarity of text is calculated, and the degree of translation matching is judged. Based on this data dimension, the frequent sequence is constructed by transforming suffix sequence into prefix sequence, and the digital mining algorithm is designed. The results of example analysis show that the execution time of digital mining algorithm based on digital twin technology is significantly shorter than that based on Apriori and Map Reduce, and the mining accuracy rate reached more than 80%, which has good performance in processing massive data. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
46. The Folded Paper Size Illusion: Evidence of Inability to Perceptually Integrate More Than One Geometrical Dimension.
- Author
-
Carbon, Claus-Christian
- Subjects
PAPER sizing ,PERCEPTUAL illusions ,SENSORIMOTOR integration ,COGNITION ,ALGORITHMS ,PSYCHOPHYSICS - Abstract
The folded paper-size illusion is as easy to demonstrate as it is powerful in generating insights into perceptual processing: First take two A4 sheets of paper, one original sized, another halved by folding, then compare them in terms of area size by centering the halved sheet on the center of the original one! We perceive the larger sheet as far less than double (i.e., 100%) the size of the small one, typically only being about two thirds larger--this illusion is preserved by rotating the inner sheet and even by aligning it to one or two sides, but is dissolved by aligning both sheets to three sides, here documented by 88 participants' data. A potential explanation might be the general incapability of accurately comparing more than one geometrical dimension at once--in everyday life, we solve this perceptual-cognitive bottleneck by reducing the complexity of such a task via aligning parts with same lengths. [ABSTRACT FROM AUTHOR]
- Published
- 2016
- Full Text
- View/download PDF
47. Digital Art Design Effectiveness Model System Based on K-Medoids Algorithm.
- Author
-
Luo, Xin
- Subjects
COMPUTER art ,DIGITAL communications ,DIGITAL technology ,ABSTRACT art ,ELECTRONIC paper ,COMPUTER networks ,ALGORITHMS - Abstract
With the development of the times, figurative expressions no longer meet the creative needs of artists and the aesthetic demands of the people. In order to express art in a more profound way, the perfect use of abstract graphics plays a crucial role in the success of the work. In recent years, there has been a surge in the creation of digital art, but there is relatively little theoretical literature on the combination of abstract graphics as a visual language and digital art. In addition, research on the theoretical aspects of digital art design is also relatively weak, so it is essential to analyse the formal aesthetics and innovative applications. In fact, digital art design has a very important role to play in promoting the development of creative cultural industries. In other words, the healthy development of digital art design can influence the future prospects of a country's creative and cultural industries. Digital art design is an integrated and complex production process and labour outcome. In addition to its human, aesthetic, and social value, digital art also has an economic value. Digital art is a new art form that combines digital technology and artistic aesthetics. As such, digital art is characterised by high technology, diverse forms, popularised art, and the advantages of high communication, interactivity, and influence, which can provide more assistance for the innovation and application of abstract graphics. Digital art is multifaceted and has an artistic expression that cannot be matched by other forms of technology. Abstract graphics, driven by digital art, are full of novelty and interest and can greatly enrich people's emotions and senses. Abstract graphics bring the experience of digital art to its fullest potential. The combination of digital art and abstract graphics offers more innovation and possibilities for the development of art and will bring great prosperity to art communication. With the widespread use of computer and network technology, the Internet has developed rapidly. In this context, digital art, as art created in a digital way and concept, has gained widespread attention. As a result, how to integrate existing computer resources in the new environment to build a model of digital art design effectiveness will cause a direct influence on the quality of digital art design with digital content innovation as the core. At the same time, as digital art becomes more and more popular, the demand for digital talents becomes very urgent. As a result, the cultivation of high-quality digital talents has become a major concern for society. Therefore, in order to explore the success of digital art design and the cultivation of digital art talents, and to better serve the innovation of digital art, this paper proposes a digital art effectiveness model based on the K-medoids algorithm. This model can provide a deeper and more comprehensive understanding of digital art and abstract graphics and provide theoretical support for professional design creation. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
48. SOFTWARE DEFECT PREDICTION APPROACHES REVISITED.
- Author
-
Shebl, Khaled S., Afify, Yasmine M., and Badr, Nagwa
- Subjects
SEMANTICS ,DATABASES ,ALGORITHMS ,COMPUTER software testing ,MACHINE learning - Abstract
A crucial field in software development and testing is Software Defect Prediction (SDP) because the quality, dependability, efficiency, and cost of the software are all improved by forecasting software defects at an earlier stage. Many existing models predict defects to facilitate software testing process for testers. A comprehensive review of these models from different perspectives is crucial to help new researchers enter this field and learn about its latest developments. Algorithms, method types, datasets, and tools were the only perspectives discussed in the current literature. A comprehensive study that takes into account a wide spectrum of viewpoints hasn't yet been published. Examining the development and advancement of SDP-related studies is the goal of this literature review. It provides a comprehensive and updated state-of-the-art that satisfies all stated criteria. Out of 591 papers retrieved from 6 reputable databases, 73 papers were eligible for analysis. This review addresses relevant research questions regarding techniques & method types, data details, tools, code syntax, semantics, structural and domain information. Motivation to conduct this comprehensive review is to equip the readers with the necessary information and keep them informed about the software defect prediction domain. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
49. A collaborative approach for research paper recommender system.
- Author
-
Haruna, Khalid, Akmar Ismail, Maizatul, Damiasih, Damiasih, Sutopo, Joko, and Herawan, Tutut
- Subjects
CITATION analysis ,SCIENCE & state ,SOCIAL network analysis ,SOCIAL networks ,COMPUTER networks - Abstract
Research paper recommenders emerged over the last decade to ease finding publications relating to researchers’ area of interest. The challenge was not just to provide researchers with very rich publications at any time, any place and in any form but to also offer the right publication to the right researcher in the right way. Several approaches exist in handling paper recommender systems. However, these approaches assumed the availability of the whole contents of the recommending papers to be freely accessible, which is not always true due to factors such as copyright restrictions. This paper presents a collaborative approach for research paper recommender system. By leveraging the advantages of collaborative filtering approach, we utilize the publicly available contextual metadata to infer the hidden associations that exist between research papers in order to personalize recommendations. The novelty of our proposed approach is that it provides personalized recommendations regardless of the research field and regardless of the user’s expertise. Using a publicly available dataset, our proposed approach has recorded a significant improvement over other baseline methods in measuring both the overall performance and the ability to return relevant and useful publications at the top of the recommendation list. [ABSTRACT FROM AUTHOR]
- Published
- 2017
- Full Text
- View/download PDF
50. Construction of Personalized Learning Platform Based on Collaborative Filtering Algorithm.
- Author
-
Zhang, Qian
- Subjects
ARTIFICIAL intelligence ,DATABASE design ,ALGORITHMS ,RECOMMENDER systems ,ELECTRONIC paper - Abstract
On the network service platform for vocational education, there are currently over 10,000 online courses. Learners face a challenge in selecting interesting courses from the vast resources available. Learners' urgent need for personalized learning is becoming more apparent as educational informatization progresses. Personalized recommendation (PR) technology can aid personalized learning and increase learners' learning efficiency significantly. This paper constructs a smart classroom model based on AI (artificial intelligence) by studying the connotation and characteristics of smart classroom in light of the current research status and trend of smart classroom at home and abroad. The merits of the recommendation system are determined by the recommendation algorithm used by PR system. This paper primarily focuses on developing a personalized learning platform based on the CF (collaborative filtering) algorithm, as well as conducting system requirements analysis, database design, functional module design, implementation, and testing on this foundation. Experiments are carried out to see if the optimized PR algorithm in the network learning platform is effective. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
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