{"title":"IEEE Transactions on Broadcasting Information for Readers and Authors","authors":"","doi":"10.1109/TBC.2025.3603346","DOIUrl":"https://doi.org/10.1109/TBC.2025.3603346","url":null,"abstract":"","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 3","pages":"C3-C4"},"PeriodicalIF":4.8,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11152557","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Novel Approach to Construct 1-D Discrete Complex Variable Chaotic Systems and Its Application","authors":"Xiangguang Sun, Jun Zheng, Yulai Xie, Peisong He","doi":"10.1109/tii.2025.3600762","DOIUrl":"https://doi.org/10.1109/tii.2025.3600762","url":null,"abstract":"","PeriodicalId":13301,"journal":{"name":"IEEE Transactions on Industrial Informatics","volume":"35 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145003060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Rate Adaptation and Power Control for IoT Networks With Ambient Energy Harvesting: A Deep Reinforcement Learning Approach","authors":"Abdulaziz Alorainy, Nour Kouzayha, Hesham ElSawy, Mohamed-Slim Alouini, Tareq Y. Al-Naffouri","doi":"10.1109/jiot.2025.3606793","DOIUrl":"https://doi.org/10.1109/jiot.2025.3606793","url":null,"abstract":"","PeriodicalId":54347,"journal":{"name":"IEEE Internet of Things Journal","volume":"8 1","pages":""},"PeriodicalIF":10.6,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145003062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"TASE-Net: A Novel Robust Deep-Learning Network for Open-Set Few-Shot UAV Recognition","authors":"Xiao Yan, Bo Wang, Hsiao-Chun Wu, Guannan Liu, Qian Wang, Xinyue Qiao","doi":"10.1109/jiot.2025.3602385","DOIUrl":"https://doi.org/10.1109/jiot.2025.3602385","url":null,"abstract":"","PeriodicalId":54347,"journal":{"name":"IEEE Internet of Things Journal","volume":"33 1","pages":""},"PeriodicalIF":10.6,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145003064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
MohammadHossein Alishahi, Ming Zeng, Paul Fortier, Omer Waqar, Muhammad Hanif, Dinh Thai Hoang, Diep N. Nguyen, Quoc-Viet Pham
{"title":"Efficient STAR-RIS Mode for Energy Minimization in WPT-FL Networks with NOMA","authors":"MohammadHossein Alishahi, Ming Zeng, Paul Fortier, Omer Waqar, Muhammad Hanif, Dinh Thai Hoang, Diep N. Nguyen, Quoc-Viet Pham","doi":"10.1109/tcomm.2025.3606641","DOIUrl":"https://doi.org/10.1109/tcomm.2025.3606641","url":null,"abstract":"","PeriodicalId":13041,"journal":{"name":"IEEE Transactions on Communications","volume":"304 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145003128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sushil Kumar, Soumya P. Dash, Debasish Ghose, George C. Alexandropoulos
{"title":"RIS-Assisted MIMO CV-QKD at THz Frequencies: Channel Estimation and Secret Key Rate Analysis","authors":"Sushil Kumar, Soumya P. Dash, Debasish Ghose, George C. Alexandropoulos","doi":"10.1109/tcomm.2025.3606653","DOIUrl":"https://doi.org/10.1109/tcomm.2025.3606653","url":null,"abstract":"","PeriodicalId":13041,"journal":{"name":"IEEE Transactions on Communications","volume":"103 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145003133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Enhancing multi-level cross-modal interaction with false negative-aware contrastive learning for text-video retrieval","authors":"Eungyeop Kim, Changhee Lee","doi":"10.1007/s10489-025-06821-7","DOIUrl":"10.1007/s10489-025-06821-7","url":null,"abstract":"<div><p>Text-video retrieval (TVR) has become a crucial branch in multi-modal understanding tasks. Enhanced by CLIP, a well-known contrastive learning framework that connects text and image, TVR has made substantial progress, particularly in developing cross-grained methods that account for both coarse and fine granularity in text and video. Nonetheless, previous cross-grained approaches have overlooked two crucial aspects. First, they utilize text-agnostic video summaries by simply averaging frame-level embeddings, potentially failing to capture crucial frame-level information that is semantically relevant to the corresponding text. Second, these approaches employ contrastive learning that neglects the impact of false negatives containing semantically relevant information. To address the aforementioned aspects, we introduce a novel framework for TVR, referred to as <i>X-MLNet</i>, focusing on capturing multi-level cross-modal interactions across video and text. This is done by first incorporating cross-attention modules at various levels of granularity, ranging from fine-grained (i.e., frame/word-level) representations to coarse-grained (i.e., video/sentence-level) representations. Then, we apply a contrastive learning framework that utilizes a similarity score computed based on the multi-level cross-modal interactions, excluding potential false negatives based on intra-modal connectivity among samples. Our experiments on five real-world benchmark datasets, including MSRVTT, MSVD, LSMDC, ActivityNet, and DiDeMo, demonstrate state-of-the-art performance in both text-to-video and video-to-text retrieval tasks. Our code is available at https://github.com/celestialxevermore/X-VLNet.</p></div>","PeriodicalId":8041,"journal":{"name":"Applied Intelligence","volume":"55 14","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144990538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}