JournalTOCs

Scientific Programming
Journal Prestige (SJR): 0.215

Citation Impact (citeScore): 1
Number of Followers: 12

This is an Open Access Journal

Open Access journal
ISSN (Print) 1058-9244 - ISSN (Online) 1875-919X
Published by Hindawi

[340 journals]

Grey Interest Chain Identification and Control Model for Government
Investment Engineering Projects Based on Node Identification
- Abstract: In the bidding process of government investment engineering projects, collusion between the government and bidders occurs repeatedly, which seriously affects the quality of engineering projects and the effectiveness of the government investment. Therefore, it is necessary to analyze and discuss the collusion between the government and bidders in government investment engineering projects, so as to provide a healthy and sustainable environment for the government investment engineering bidding market. There are two main types of collusion in engineering bidding: horizontal collusion and vertical collusion, and this paper focuses on the vertical collusion process in the engineering bidding process. A conceptual framework of the grey interest chain based on three stages of benefit creation, benefit distribution, and benefit realization was established, 15 major nodes in the grey interest chain were identified, and a grey interest chain control model was constructed, which further identified and classified the nodes into four levels: key nodes, important nodes, general nodes, and unimportant nodes. Finally, through the application of the model in the case, measures such as establishing a cracking mechanism for grey resource integration, increasing the supervision of grey interest chain, and strengthening post-bid audit are proposed. Measures such as including the preparation of bidding documents into the work assessment system and entrusting consulting units or third parties to prepare bidding documents are proposed to establish a crack mechanism for grey resource integration. In the benefit distribution stage, the penalties for the government and the bidders can be appropriately increased, the responsibilities of enterprises and project leaders can be implemented in the system on a reciprocal basis, and a perfect reputation mechanism information can be established. At the stage of benefit realization, the bidding system should be improved and post-bid audit should be strengthened to increase the difficulty of grey benefit realization. This paper will provide a reference for the prevention and governance of vertical collusion in bidding and tendering.
  PubDate: Tue, 14 Nov 2023 07:20:00 +000
Credit-Risk Prediction Model Using Hybrid Deep—Machine-Learning
Based Algorithms
- Abstract: Credit-risk prediction is one of the challenging tasks in the banking industry. In this study, a hybrid convolutional neural network—support vector machine/random forest/decision tree (CNN—SVM/RF/DT) model has been proposed for efficient credit-risk prediction. We proposed four classifiers to develop the model. A fully connected layer with soft-max trained using an end-to-end process makes up the first classifier and by deleting the final fully connected with soft-max layer, the other three classifiers—a SVM, RF, and DT classifier stacked after the flattening layer. Different parameter values were considered and fine-tuned throughout testing to select appropriate parameters. In accordance with the experimental findings, a fully connected CNN and a hybrid CNN with SVM, DT, and RF, respectively, achieved a prediction performance of 86.70%, 98.60%, 96.90%, and 95.50%. According to the results, our suggested hybrid method exceeds the fully connected CNN in its ability to predict credit risk.
  PubDate: Mon, 06 Nov 2023 07:50:00 +000
Network Traffic Anomaly Detection Model Based on Feature Reduction and
Bidirectional LSTM Neural Network Optimization
- Abstract: Aiming at the problems of large data dimension, more redundant data, and low accuracy in network traffic anomaly detection, a network traffic anomaly detection model (FR-APPSO BiLSTM) based on feature reduction and bidirectional long short-term memory (LSTM) neural network optimization is proposed. First, the feature dimensions are divided by hierarchical clustering according to the similarity distance between data features, and the features with high correlation are divided into the same feature subset. Second, an automatic encoder is used to reduce each feature subset, eliminating redundant information, and reducing the computational complexity of the detection data. Then, a particle swarm optimization algorithm based on adaptive updating of variables and dynamic adjustment of parameters (APPSO) is proposed, which is used to optimize the parameters of the bidirectional LSTM neural network (BiLSTM). Finally, the optimized BiLSTM is used as a classifier to model network traffic anomaly detection using the reduced feature data. Experiments based on NSL-KDD, UNSW-NB15, and CICIDS-2017 datasets show that the proposed FR-APPSO-BiLSTM model can effectively reduce data features, improve the accuracy of detection, and the performance of network traffic anomaly detection.
  PubDate: Fri, 03 Nov 2023 11:35:00 +000
Retracted: Research on Network Layer Recursive Reduction Model Compression
for Image Recognition
- PubDate: Wed, 01 Nov 2023 07:05:28 +000
Retracted: Ice and Snow Sports Education Based on 5G Cloud Computing to
Improve the Social Adaptability of Southern University Students
- PubDate: Wed, 01 Nov 2023 07:05:27 +000
Retracted: Research on Distance Teaching System of English Course Based on
Wireless Network Technology
- PubDate: Wed, 01 Nov 2023 07:05:25 +000
SKT-MOT and DyTracker: A Multiobject Tracking Dataset and a Dynamic
Tracker for Speed Skating Video
- Abstract: Speed skating serves as a significant application domain for multiobject tracking (MOT), presenting unique challenges such as frequent occlusion, highly similar appearances, and motion blur. To address these challenges, this paper constructs an MOT dataset called SKT-MOT for speed skating and analyzes the shortcomings of existing datasets and methods. Accordingly, we propose a dynamic MOT method called DyTracker. The method builds upon the DeepSORT baseline and enhances three key modules. At the global level, we design the track dynamic management (TDM) algorithm. In the motion branch, a novel metric is proposed to evaluate occlusion and Kalman filter dynamic update (KFDU) is implemented. In the appearance branch, we account for the difference in human posture and propose the feature dynamic selection and updating (FDSU) strategy. This makes our DyTracker flexible and efficient to achieve a multiobject tracking accuracy (MOTA) of 93.70% and identification F1 (IDF1) score of 92.39% on SKT-MOT, which is a significant advantage over existing SOTA methods. To validate the generalization of our proposed module, two dynamic update modules are inserted into other methods and validated on the public dataset MOT17, and the accuracy is generally improved by 0.2%–0.6%.
  PubDate: Wed, 18 Oct 2023 12:05:00 +000
Retracted: Application and Value of Dynamic Volume CT Multiparameter
Imaging in the Diagnosis of Traumatic High-Flow Penile Abnormal Erection
- PubDate: Wed, 18 Oct 2023 07:05:52 +000
Retracted: Digital Image Art Style Transfer Algorithm and Simulation Based
on Deep Learning Model
- PubDate: Wed, 18 Oct 2023 07:05:51 +000
Retracted: Ultrasound Image-Guided Pudendal Nerve Block on Analgesic
Effect of Perineotomy under Optimized Fast Super Resolution Reconstructed
Convolutional Neural Network Algorithm
- PubDate: Wed, 18 Oct 2023 07:05:49 +000
Retracted: Diagnosis of Bronchial and Pulmonary Fungal Infection Using
Gradient Weighted Denoising Algorithm-Based CT Images
- PubDate: Wed, 18 Oct 2023 07:05:48 +000
Retracted: DenseNet-Based Classification of MRI Images for Detecting the
Difference before and after Treating Liver Cancer
- PubDate: Wed, 18 Oct 2023 07:05:46 +000
Retracted: Industrial Design Capability Evaluation System under Cloud
Service Model
- PubDate: Wed, 18 Oct 2023 07:05:45 +000
Retracted: Computed Tomography Imaging Based on Edge Detection Algorithm
in Diagnosis and Rehabilitation Nursing of Stroke Patients with Motor
Dysfunction
- PubDate: Wed, 18 Oct 2023 07:05:44 +000
Retracted: Image Processing Method Based on FGCA and Artificial Neural
Network
- PubDate: Wed, 11 Oct 2023 07:06:14 +000
Retracted: Research on English Education Auxiliary Teaching System Based
on MOOC
- PubDate: Wed, 04 Oct 2023 07:06:09 +000
Retracted: TCM Physical Health Management Training and Nursing Effect
Evaluation Based on Digital Twin
- PubDate: Wed, 04 Oct 2023 07:06:08 +000
Retracted: Research on the Use of Neural Network for the Prediction of
College Students’ Mental Health
- PubDate: Wed, 04 Oct 2023 07:06:06 +000
Retracted: An English Teaching Resource Recommendation System Based on
Network Behavior Analysis
- PubDate: Wed, 04 Oct 2023 07:06:05 +000
Retracted: Preliminary Study on the Evaluation of Multimodal Effects of
Type 2 Diabetic Nephropathy
- PubDate: Wed, 04 Oct 2023 07:06:03 +000
Retracted: Deep Learning-Based Identification of Spinal Metastasis in Lung
Cancer Using Spectral CT Images
- PubDate: Wed, 04 Oct 2023 07:06:02 +000
Retracted: Study on Aesthetic Teaching Methods in Ethnic Music Teaching in
Universities in the Context of Intelligent Internet of Things
- PubDate: Wed, 04 Oct 2023 07:06:00 +000
Retracted: K-Means Clustering Algorithm-Based Detection of Carotid
Atherosclerotic Plaque Using Contrast-Enhanced Ultrasound Images
- PubDate: Wed, 04 Oct 2023 07:05:59 +000
Retracted: Analysis on the Application of Mobile Information System in the
5G Era in the Transformation of Ethnic PE Teaching in Colleges and
Universities
- PubDate: Wed, 04 Oct 2023 07:05:57 +000
Retracted: Analysis of Tai Chi Ideological and Political Course in
University Based on Big Data and Graph Neural Networks
- PubDate: Wed, 27 Sep 2023 07:05:17 +000
Retracted: Enlightenment of Physical Education Teaching Experiment Based
on Cloud Computing to the Current Physical Education Reform
- PubDate: Wed, 27 Sep 2023 07:05:16 +000
Retracted: Application of Three-Dimensional Image Reconstruction
Technology in Neurogenic Intestinal Nursing Tasks
- PubDate: Wed, 27 Sep 2023 07:05:14 +000
Retracted: Deep Learning Analysis of English Education Blended Teaching in
Virtual Reality Environment
- PubDate: Wed, 27 Sep 2023 07:05:13 +000
Retracted: Dynamic Early-Warning Model of College Students’
Psychological Crisis Based on Characteristic Attribute
- PubDate: Wed, 27 Sep 2023 07:05:11 +000
Retracted: Construction of a Six-Pronge Intelligent Physical Education
Classroom Model in Colleges and Universities
- PubDate: Wed, 27 Sep 2023 07:05:10 +000