Journal of Ambient Intelligence and Humanized Computing最新文献

Retraction Note: Impact of autoencoder based compact representation on emotion detection from audio. 注：基于自编码器的紧凑表示对音频情感检测的影响。

3区计算机科学

Journal of Ambient Intelligence and Humanized Computing Pub Date : 2026-01-01 Epub Date: 2026-03-11 DOI: 10.1007/s12652-026-05062-x

Nivedita Patel, Shireen Patel, Sapan H Mankad

引用次数: 0

Retraction Note: Artificial intelligence in disease diagnosis: a systematic literature review, synthesizing framework and future research agenda. 人工智能在疾病诊断中的应用：系统的文献综述、综合框架和未来研究议程。

3区计算机科学

Journal of Ambient Intelligence and Humanized Computing Pub Date : 2026-01-01 Epub Date: 2026-03-09 DOI: 10.1007/s12652-026-05063-w

Yogesh Kumar, Apeksha Koul, Ruchi Singla, Muhammad Fazal Ijaz

引用次数: 0

Retraction Note: Multiple attribute decision making based on Pythagorean fuzzy Aczel-Alsina average aggregation operators. 注：基于毕达哥拉斯模糊Aczel-Alsina平均聚合算子的多属性决策。

3区计算机科学

Journal of Ambient Intelligence and Humanized Computing Pub Date : 2026-01-01 Epub Date: 2026-01-30 DOI: 10.1007/s12652-026-05050-1

Tapan Senapati, Guiyun Chen, Radko Mesiar, Abhijit Saha

引用次数: 0

Predicting the unconfined compressive strength of stabilized soil using random forest coupled with meta-heuristic algorithms 利用随机森林和元启发式算法预测稳定土的无压抗压强度

3区计算机科学

Journal of Ambient Intelligence and Humanized Computing Pub Date : 2024-09-16 DOI: 10.1007/s12652-024-04857-0

Yan Li

引用次数: 0

Expressive sign language system for deaf kids with MPEG-4 approach of virtual human character 采用 MPEG-4 虚拟人物方法的聋哑儿童手语表达系统

3区计算机科学

Journal of Ambient Intelligence and Humanized Computing Pub Date : 2024-09-14 DOI: 10.1007/s12652-024-04842-7

Itimad Raheem Ali, Hoshang Kolivand

{"title":"Expressive sign language system for deaf kids with MPEG-4 approach of virtual human character","authors":"Itimad Raheem Ali, Hoshang Kolivand","doi":"10.1007/s12652-024-04842-7","DOIUrl":"https://doi.org/10.1007/s12652-024-04842-7","url":null,"abstract":"Children with language impairments during their significant developmental periods within ‎childhood are exposed to cognitive risk, social impairments, along with language. This is difficult ‎with children born deaf from hearing parents who own little or no experience of communicating ‎in sign language. This system presents the sign language in the context of British ‎Sign Language (BSL) for producing utterances through virtual characters. In capturing, Kinect ‎sensors use a motion capture sensor for motion actors. The connection uses sensors to read data, ‎connect to high-quality 3D scans, and then use these high-quality scans of the animated MPEG-4 ‎face and hand models. The main challenges of this system are the simultaneous capture of data ‎for the whole hand and the development of the MPEG-4 approach considering the animation ‎engines with descriptive sign language features. After synchronizing motion data from motion ‎capture results with Kinect, the combined hand character adjusts points, frames, and time with ‎virtual characters based on the motion of character actors. This study demonstrates the skills of ‎this sign language system instrumental in presenting an assessment by users, highlighting the ‎importance of the hand part in creating new accents and signs in BSL. We have validated this ‎system by testing the reliability and functionality of the virtual characters.‎.","PeriodicalId":14959,"journal":{"name":"Journal of Ambient Intelligence and Humanized Computing","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142257062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MEDCO: an efficient protocol for data compression in wireless body sensor network MEDCO：无线人体传感器网络中的高效数据压缩协议

3区计算机科学

Journal of Ambient Intelligence and Humanized Computing Pub Date : 2024-09-14 DOI: 10.1007/s12652-024-04858-z

Firas Salika, Hassan Harb, Chamseddine Zaki, Eric Saux

{"title":"MEDCO: an efficient protocol for data compression in wireless body sensor network","authors":"Firas Salika, Hassan Harb, Chamseddine Zaki, Eric Saux","doi":"10.1007/s12652-024-04858-z","DOIUrl":"https://doi.org/10.1007/s12652-024-04858-z","url":null,"abstract":"This paper introduces a new protocol named MEDCO for eMErgency Detection and COmpression, designed to minimize data transmission and optimize sensor energy usage in wireless body sensor networks. MEDCO operates in two stages. The first stage assesses the patient’s condition based on vital signs and compares it with the previous state to determine if the data should be transmitted to medical staff. Data is only sent if a change in the patient’s situation is detected. The second stage focuses on compressing the identified data using two algorithms: range and changed vital signs methods. The range method classifies patient readings into ranges based on the current health situation before compressing them. At the same time, the changed vital signs algorithm considers both current and previous situations during compression. Through simulations using actual patient data, we demonstrated the effectiveness of our protocol in reducing data transmission by 97% while maintaining a high level of accuracy in the transmitted information. The range method outperforms by achieving an additional data reduction of 34.6% compared to the selected protocol from state of the art, and the changed vital signs method achieves a reduction of 6.4%.","PeriodicalId":14959,"journal":{"name":"Journal of Ambient Intelligence and Humanized Computing","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142257064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A multi-objective gene selection for cancer diagnosis using particle swarm optimization and mutual information 利用粒子群优化和互信息进行癌症诊断的多目标基因选择

3区计算机科学

Journal of Ambient Intelligence and Humanized Computing Pub Date : 2024-09-12 DOI: 10.1007/s12652-024-04853-4

Azar Rafie, Parham Moradi

引用次数: 0

Partial policy hidden medical data access control method based on CP-ABE 基于 CP-ABE 的部分策略隐藏式医疗数据访问控制方法

3区计算机科学

Journal of Ambient Intelligence and Humanized Computing Pub Date : 2024-09-11 DOI: 10.1007/s12652-024-04843-6

Jing Huang, Detao Tang, Chenyu Jiang, Fulong Chen, Ji Zhang, Dong Xie, Taochun Wang, Chuanxin Zhao, Chao Wang, Jintao Li

引用次数: 0

Maximum dry density estimation of stabilized soil via machine learning techniques in individual and hybrid approaches 通过单独和混合方法中的机器学习技术估算稳定土的最大干密度

3区计算机科学

Journal of Ambient Intelligence and Humanized Computing Pub Date : 2024-09-11 DOI: 10.1007/s12652-024-04860-5

Lianping Zhao, Guan Dashu Guan

{"title":"Maximum dry density estimation of stabilized soil via machine learning techniques in individual and hybrid approaches","authors":"Lianping Zhao, Guan Dashu Guan","doi":"10.1007/s12652-024-04860-5","DOIUrl":"https://doi.org/10.1007/s12652-024-04860-5","url":null,"abstract":"In geotechnical engineering, the maximum dry density (MDD) stands as an important parameter, denoting the utmost mass of soil achievable per unit volume when compacted to its maximum dry state. Its significance extends to the design of various earthworks like embankments, foundations, and pavements, influencing the soil’s strength, stiffness, and stability. The MDD is contingent on diverse elements like soil type, grain size distribution, moisture content and compaction effort. Generally, heightened compaction effort correlates with an increased MDD, while elevated moisture content corresponds to a reduced MDD. Accurate prediction of the MDD under specific conditions is imperative to uphold the quality and safety standards of earthworks. This research aims to introduce Support Vector Regression (SVR) as a modeling technique for predicting the MDD of soil-stabilizer mixtures. To establish an accurate and comprehensive model that can correlate the stabilized soil’s MDD with attributes of natural soil, consisting linear shrinkage, particle size distribution, plasticity, as well as the type and number of stabilizing additives, three optimization algorithms, namely Artificial Rabbits Optimization (ARO), Manta Ray Foraging Optimization (MRFO), and Improved Manta-Ray Foraging Optimizer (IMRFO), were employed in addition to SVR. Considering the results of evaluative metrics, the SVAR model (combination of SVR and ARO) experienced the highest predictive performance, registering an impressive value of R2 in the training phase with 0.9948, as well as the lowest RMSE value of 19.1376.","PeriodicalId":14959,"journal":{"name":"Journal of Ambient Intelligence and Humanized Computing","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142227800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Kernel density-based radio map optimization using human trajectory for indoor localization 基于核密度的无线电地图优化，利用人体轨迹进行室内定位

3区计算机科学

Journal of Ambient Intelligence and Humanized Computing Pub Date : 2024-09-05 DOI: 10.1007/s12652-024-04850-7

Yun Fen Yong, Chee Keong Tan, Ian K. T. Tan, Su Wei Tan

{"title":"Kernel density-based radio map optimization using human trajectory for indoor localization","authors":"Yun Fen Yong, Chee Keong Tan, Ian K. T. Tan, Su Wei Tan","doi":"10.1007/s12652-024-04850-7","DOIUrl":"https://doi.org/10.1007/s12652-024-04850-7","url":null,"abstract":"Accurate indoor localization remains a significant challenge due to the complex nature of indoor environments. This paper proposes a novel method for constructing a radio map (RM) based on Kernel density estimation (KDE) and human trajectories (HT) to enhance indoor localization accuracy. The proposed method utilizes historical HT data in RM construction to capture the spatial variability and complexity of indoor environments, which is crucial for accurate localization. By employing KDE, kernel density maps are generated, identifying high-density regions where additional interpolated fingerprints are strategically placed to improve localization accuracy. In contrast to the conventional method of uniformly placing interpolated points (IPs), the proposed approach better models natural walking patterns and trajectories, thereby enhancing the uniqueness and accuracy of user position identification. Through extensive experiments with various HT patterns, the proposed KDE-RM optimization method consistently outperforms the conventional approach of evenly distributed IPs using Kriging and inverse distance weighting interpolation by up to 36.4%. This demonstrates the effectiveness and potential of the proposed method as a valuable tool for enhancing indoor localization.","PeriodicalId":14959,"journal":{"name":"Journal of Ambient Intelligence and Humanized Computing","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142202692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0