Scientific Programming
 Journal metrics
Acceptance rate27%
Submission to final decision66 days
Acceptance to publication33 days
CiteScore2.000
Journal Citation Indicator0.300
Impact Factor1.025

Article of the Year 2020

A Fortran-Keras Deep Learning Bridge for Scientific Computing

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 Journal profile

Scientific Programming provides a forum for research results in, and practical experience with, software engineering environments, tools, languages, and models of computation aimed specifically at supporting scientific and engineering computing.

 Editor spotlight

Chief Editor Professor Tramontana is based at the University of Catania and his research primarily concerns the areas of software engineering and distributed systems.

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We currently have a number of Special Issues open for submission. Special Issues highlight emerging areas of research within a field, or provide a venue for a deeper investigation into an existing research area.

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Research Article

The Prediction of Atherosclerosis Index Based on Photoplethysmograph

Current atherosclerosis (AS) assessment devices have a disadvantage for users to carry around. In response to this shortcoming, we propose to collect the wrist photoplethysmograph (PPG) signal and create models to predict the indicators of atherosclerosis (cardiovascular age and right brachial and ankle pulse wave velocity (baPWV)). This study uses the maximum correlation coefficient method for feature selection and establishes multiple models to predict cardiovascular age and the right baPWV. The study results show that the prediction of cardiovascular age using the backpropagation (BP) neural network model is the best. Its Pearson correlation coefficient (PCC) is 0.9501 (), and the model finds the best six physiological features as crest time (CT), crest time ratio (CTR), slop K, stiffness index (SI), reflection index (RI), and heart rate (HR). When predicting the right baPWV value on the right side, we propose a hybrid method MLR_BP, which has better experimental results than BP and MLR. The MLR_BP model improves the prediction accuracy, the predicted PCC value is 0.9204 (), and the model only needs two features, HR and cardiovascular age. This study further verified the results of related literature and proved the relationship between AS and related physiological parameters. The proposed method is applied to wearable devices and has an application value for diagnosing AS and preventing cardiovascular diseases.

Research Article

Research on Optimization Path of Intelligent Pension Industry Based on Intelligent Fusion Algorithm of Multisource Information

Accurate quantitative evaluation of the supervision effect of the smart pension industry can reduce the cost of social pension. The traditional methods cannot effectively classify the regulatory risk levels of the smart pension industry. Therefore, this paper proposes a multisource information intelligent fusion algorithm based on the intelligent pension industry optimization path research. Firstly, we establish the principal model of the supervision effect system of the intelligent elderly care industry optimization path and describe the risk level of the supervision effect from different levels. We build the intelligent service platform of the intelligent elderly care training, calculate the weight vector of the supervision risk of the optimization path at all levels, and determine the attribute type of the supervision effect at all levels. Finally, we calculate the maximum influence value of the supervision effect of the intelligent elderly care industry optimization path and use this value to complete the quantitative evaluation of its supervision effect. Simulation results show that the proposed method can evaluate the regulatory effect of smart pension industry and improve the precision of the regulatory effect of smart pension industry effectively.

Review Article

A Review of Keypoints’ Detection and Feature Description in Image Registration

For image registration, feature detection and description are critical steps that identify the keypoints and describe them for the subsequent matching to estimate the geometric transformation parameters between two images. Recently, there has been a large increase in the research methods of detection operators and description operators, from traditional methods to deep learning methods. To solve the problem, that is, which operator is suitable for specific application problems under different imaging conditions, the paper systematically reviewed commonly used descriptors and detectors from artificial methods to deep learning methods, and the corresponding principle, analysis, and comparative experiments are given as well. We introduce the handcrafted detectors including FAST, BRISK, ORB, SURF, SIFT, and KAZE and the handcrafted descriptors including BRISK, FREAK, BRIEF, SURF, ORB, SIFT, KAZE. At the same time, we review detectors based on deep learning technology including DetNet, TILDE, LIFT, multiscale detector, SuperPoint, and descriptors based on deep learning including pretrained descriptor, Siamese descriptor, LIFT, triplet network, and SuperPoint. Two group of comparison experiments are compared comprehensively and objectively on representative datasets. Finally, we concluded with insightful discussions and conclusions of descriptor and detector selection for specific application problem and hope this survey can be a reference for researchers and engineers in image registration and related fields.

Research Article

Design of Breakdown and Checklist for Continuous Renal Replacement Therapy

Objective. This study aimed to improve the quality of continuous renal replacement therapy (CRRT). Methods. A pool of candidate indicators was established using literature retrieval, panel discussion, and experience summary. The first round of consultation was performed with the selected 18 experts by the Delphi method. Then, the checklist was modified according to the experts’ opinions for the second round of consultation to prepare the final checklist. Results. The positivity coefficients of experts in the two rounds of consultation were 100% and 88.9%, respectively, with the authority coefficient of 0.88. The Kendall coordination coefficients of the primary and secondary indicators were 0.296 and 0.303, respectively (). Finally, the breakdown and checklist were prepared, which involved 16 primary indicators and 56 secondary indicators. Conclusion. The scientific and reasonable breakdown and checklist prepared based on a consultation can provide scientific guidance for nursing during CRRT, reduce the incidence of adverse events, and improve work efficiency and satisfaction of medical care.

Research Article

Care of Maintenance Hemodialysis Patients through Intelligent Algorithm-Based Low-Dose Digital Subtraction Angiography

Objective. The study aimed to explore the application value of artificial intelligence (AI)-based low-dose digital subtraction angiography (DSA) in the care of maintenance hemodialysis (MHD) patients. Methods. The characteristics of DSA imaging were analyzed, and the refinement efficiency of the AI algorithm was discussed, expected to assist clinicians in the care and treatment of patients. 100 MHD patients who were in the hospital were selected as the research subjects. They were randomly divided into the conventional DSA group (conventional group) and the AI algorithm-based DSA group (AI-based DSA group). The conventional group used conventional DSA images to guide the care of HM patients, and the AI-based DSA group used the AI algorithm to optimize DSA images. Results. It was found that the AI-based DSA group was better than the conventional DSA group in terms of image sharpness and shaded areas, and the image mean square error (MSE) loss value was smaller (). The patients were followed up for 3 months. In the AI-based DAS group, the blood flow of the drainage vein (DV), the blood flow of the proximal vein (PA), and the blood flow of the brachial artery (BA) were greater than those of the conventional group (). During the 3-month follow-up period, in the conventional group, thrombosis occurred in 4 patients, low-flow AVF occurred in 5 patients, high-flow AVF occurred in 3 patients, and heart failure occurred in 5 patients. In the AI-based DSA group, thrombosis occurred in 2 patients, low-flow AVF occurred in 2 cases, high-flow AVF occurred in 1 case, and heart failure occurred in 3 cases. There were no other cardiac complications in both groups. Conclusion. DSA images optimized by the AI algorithm are suitable for clinical diagnosis and have practical application value.

Research Article

Exploration on the Teaching Reform Measure for Machine Learning Course System of Artificial Intelligence Specialty

Due to the particularity of the artificial intelligence major and the machine learning courses learned, the traditional course teaching model is not suitable for artificial intelligence major machine learning courses. Based on this background, this article proposes a new system based on machine learning curriculum teaching reform. It mainly includes the reform of curriculum teaching mode, curriculum practice reform, and teaching process reform. In order to verify the effect of the proposed new model on the teaching quality of machine learning courses, this article also proposes an evaluation method based on intelligent technology. Firstly, the feasibility of evaluation based on intelligent technology is described. Secondly, it lists the application details of the existing teaching evaluation based on intelligent technology. Finally, a novel teaching quality evaluation system based on intelligent technology is proposed. The system collects student facial expression data and uses classification algorithms to make classification decisions on the data. The result of the decision can give feedback on the quality of classroom teaching. The comparison of experiments based on different intelligent technologies shows that the teaching quality evaluation system proposed in this article is feasible and effective.

Scientific Programming
 Journal metrics
Acceptance rate27%
Submission to final decision66 days
Acceptance to publication33 days
CiteScore2.000
Journal Citation Indicator0.300
Impact Factor1.025
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Article of the Year Award: Outstanding research contributions of 2020, as selected by our Chief Editors. Read the winning articles.