DIRECT INVERSION OF RAYLEIGH WAVE GROUP VELOCITY DISPERSION FOR 3D CRUSTAL SHEAR WAVE VELOCITY STRUCTURE IN THAILAND, MYANMAR, AND MALAYSIA by K. Saetang, W. Srisawat

“…This study presents a comprehensive investigation of the crustal structure in Thailand, Myanmar, and Malaysia using Rayleigh wave dispersion data from a dense network of 49 seismic stations. A direct inversion approach is employed to derive a high-resolution, 3D shear wave velocity model of the crust, circumventing the traditional intermediate step of constructing group velocity maps. …”
Get full text

CSK based on Priority Call Algorithm for Detection and Securing Platoon from Inside Attacks by Mohammed Al Sheıkhly, Sefer Kurnaz

“…The emergence of autonomous vehicles has bolstered the evolution of platooning as a trend in mobility and transportation. …”
Get full text

Microcosm of Ecologic Taxation in Russia by N. A. Zatsarnaya

“…The key part in microcosm being studied is assigned not to economic entities and administrative agents but to the network of interrelations, tools and control levers integrating them. …”
Get full text

Stateless Malware Packet Detection by Incorporating Naive Bayes with Known Malware Signatures by Ismahani Ismail, Sulaiman Mohd Nor, Muhammad Nadzir Marsono

“…Malware detection done at the network infrastructure level is still an open research problem ,considering the evolution of malwares and high detection accuracy needed to detect these threats. …”
Get full text

Enhancing corn industry sustainability through deep learning hybrid models for price volatility forecasting. by Chengjin Yang, Yanzhong Zhai, Zehua Liu

“…The model integrates a three-layer decomposition combined dual-filter time-series denoising method (TLDCF-TSD), a bidirectional time-convolutional enhancement network (BiTCEN), a bidirectional long- and short-term memory network (BiLSTM), and a frequency-enhanced channel attention mechanism (FECAM) to improve prediction accuracy and robustness. …”
Get full text

A hybrid CNN-LSTM model with adaptive instance normalization for one shot singing voice conversion by Assila Yousuf, David Solomon George

“…Deep learning-based singing voice conversion techniques, however, focus on disentangling singer-dependent and singer-independent features. While this approach can enhance the quality of synthesized singing voices, many voice conversion systems still grapple with the issue of singer-dependent feature leakage into content embeddings. …”
Get full text

Two-stage object detection in low-light environments using deep learning image enhancement by Ghaith Al-refai, Hisham Elmoaqet, Abdullah Al-Refai, Ahmad Alzu’bi, Tawfik Al-Hadhrami, Abedalrhman Alkhateeb

“…Three image enhancement algorithms—ZeroDCE++, Gladnet, and two-branch exposure-fusion network for low-light image enhancement (TBEFN)—were assessed in the first stage to enhance image quality. …”
Get full text

Traditional Chinese Medicine Prescription Generation Model Based on Search Enhancement by ZHAO Zijuan, REN Xueting, SONG Kai, QIANG Yan, ZHAO Juanjuan, ZHANG Junlong

“…[Findings] The validity of the model is verified by automatic evaluation and manual evaluation on the real medical case dataset. …”
Get full text

An Effective Strategy of Object Instance Segmentation in Sonar Images by Pengfei Shi, Huanru Sun, Qi He, Hanren Wang, Xinnan Fan, Yuanxue Xin

“…By integrating this with ResNet and transforming traditional convolutions into deformable convolutions, we further improve the ability of the network to extract features from sonar images. Additionally, we incorporate a bidirectional feature fusion module to enhance information fusion. …”
Get full text

Micro-Terrain Recognition Method of Transmission Lines Based on Improved UNet++ by Feng Yi, Chunchun Hu

“…Compared to the baseline network, the improved model enhances PA and IoU by 1.75% and 2.96%, respectively.…”
Get full text

Living in “Smart Cities and Green World” by Miranda HARIZAJ, Arjela NDREU

“…We are based on two features, "smart" and "green", which will include the electricity supply of the apartment and coverage of any of its indoor activities, street lighting, charging of electric cars and education on reducing pollution levels on nature.First of all, we will focus on presenting all the elements of this network, whose basis are photovoltaic modules, then we will introduce the creation of photovoltaic plants based on respective standards for their resistance to wind, with materials that do not pierce existing buildings and do not pollute the environment. …”
Get full text

New Method for Solving Substation Expansion Planning Problem Using Fuzzy Clustering Algorithms by Zahra Moravej, Hossein Kiani Rad

“…The fast convergence, conformity of solution with engineering perspectives, consideration of real-world networks limitations as problem constraints and simplicity in applying to real networks are the other features of the proposed method.…”
Get full text

DBSQFusion: a multimodal image fusion method based on dual-channel attention by Shaodong Liu, Faming Shao, Xiaohui He, Jinhong Xue, Heng Zhang, Qing Liu

“…This method fully integrates the characteristics of different source images and processes them through specifically designed channels to maximize the retention of important information from the original images. Additionally, Feature Contrast Enhancement Fusion Network(FCEFN) is designed to exploit the differences between infrared and visible light features, enabling information complementarity by separating these distinct features. …”
Get full text

Hybrid deep learning model for accurate and efficient android malware detection using DBN-GRU. by Heena Kauser Sk, Maria Anu V

“…The model extracts static features (permissions, API calls, intent filters) and dynamic features (system calls, network activity, inter-process communication) from Android APKs, enabling a comprehensive analysis of application behavior.The proposed model was trained and tested on the Drebin dataset, which includes 129,013 applications (5,560 malware and 123,453 benign).Performance evaluation against NMLA-AMDCEF, MalVulDroid, and LinRegDroid demonstrated that DBN-GRU achieved 98.7% accuracy, 98.5% precision, 98.9% recall, and an AUC of 0.99, outperforming conventional models.In addition, it exhibits faster preprocessing, feature extraction, and malware classification times, making it suitable for real-time deployment.By bridging static and dynamic detection methodologies, the DBN-GRU enhances malware detection capabilities while reducing false positives and computational overhead.These findings confirm the applicability of the proposed model in real-world Android security applications, offering a scalable and high-performance malware detection solution.…”
Get full text

Attention-Module-Guided Time-Lapse Leakage Plume Imaging Driven by LeakInv-CUNet GPR Inversion Framework by Honghua Wang, Shan Wang, Fei Zhou, Yi Lei, Bin Zhang

“…This paper develops LeakInv-CUNet, a novel attention-guided GPR inversion framework, to enable refined imaging of leakage plumes and their temporal-spatial evolution. To enhance network training, extensive GPR datasets are generated by augmenting simulated data and experimentally measured data, accounting for variations in injection orientation, plume dynamics, and subsurface media properties. …”
Get full text

Research on Management Model Based on Deep Learning by Yuting Zhao

“…Improved DNN is used and modify weights that have an effect on the features extracted in advance to increase the accuracy and precisions are used. …”
Get full text

Optimizing Vital Signs in Patients With Traumatic Brain Injury: Reinforcement Learning Algorithm Development and Validation by Hongwei Zhang, Mengyuan Diao, Sheng Zhang, Peifeng Ni, Weidong Zhang, Chenxi Wu, Ying Zhu, Wei Hu

“…We used an RL algorithm called weighted dueling double deep Q-network with embedded human expertise to maximize cumulative returns and evaluated the model using a doubly robust off-policy evaluation method. …”
Get full text

Transfer Learning and Semisupervised Adversarial Detection and Classification of COVID-19 in CT Images by Ariyo Oluwasanmi, Muhammad Umar Aftab, Zhiguang Qin, Son Tung Ngo, Thang Van Doan, Son Ba Nguyen, Son Hoang Nguyen

“…In our proposed model, we explore the benefit of transfer learning as a means of resolving the problem of inadequate dataset and the importance of semisupervised generative adversarial network for the extraction of well-mapped features and generation of image data. …”
Get full text

Fast Recognition of Table Eggs from Different Farming Systems Using Physical Traits and Multi-layer Perceptron by MC Huang, Q Lin, H Cai, H Ni

“…The result demonstrates that the physical traits of eggs provide sufficient features for the Multi-layer Perceptron Neural Network classifier. …”
Get full text

Fusion of UAV-Acquired Visible Images and Multispectral Data by Applying Machine-Learning Methods in Crop Classification by Zuojun Zheng, Jianghao Yuan, Wei Yao, Paul Kwan, Hongxun Yao, Qingzhi Liu, Leifeng Guo

“…These features were combined with five machine learning models: random forest (RF), support vector machine (SVM), k-nearest neighbour (KNN) based, classification and regression tree (CART) and artificial neural network (ANN). …”
Get full text