Journal of Ambient Intelligence and Humanized Computing最新文献

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

Neural network-based soil parameters predictive coordination algorithm for energy efficient wireless sensor network 基于神经网络的高能效无线传感器网络土壤参数预测协调算法

3区计算机科学

Journal of Ambient Intelligence and Humanized Computing Pub Date : 2024-09-04 DOI: 10.1007/s12652-024-04848-1

Dinesh Sharma, Geetam Singh Tomar

{"title":"Neural network-based soil parameters predictive coordination algorithm for energy efficient wireless sensor network","authors":"Dinesh Sharma, Geetam Singh Tomar","doi":"10.1007/s12652-024-04848-1","DOIUrl":"https://doi.org/10.1007/s12652-024-04848-1","url":null,"abstract":"The utilization of Wireless Sensor Networks (WSN) in the agricultural field represents a significant stride in the application of Information Technology. Recent advancements in technology have made it possible for sensor networks not only to provide real-time information about soil nutrient levels but also to assist in the automation of various agricultural processes. However, it’s crucial to acknowledge a substantial limitation associated with WSN, namely, energy consumption. Through the analysis of experimental data gathered from diverse soil types and employing sophisticated data analytics, it has been observed that the Nutrient Index exhibits a relatively stable pattern over time. Consequently, predictive neural network techniques can be employed to extract detailed insights from the primary inputs received from WSN. This approach eliminates the need for continuous operation of the WSN throughout the day, contributing to enhanced energy efficiency. To achieve this energy-efficient operation, the NR-MDEC protocol is implemented in conjunction with a coordination algorithm, resulting in a substantial improvement in overall efficiency.","PeriodicalId":14959,"journal":{"name":"Journal of Ambient Intelligence and Humanized Computing","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142202691","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

Analyzing the impact of conversation structure on predicting persuasive comments online 分析对话结构对预测网上劝说性评论的影响

3区计算机科学

Journal of Ambient Intelligence and Humanized Computing Pub Date : 2024-09-02 DOI: 10.1007/s12652-024-04841-8

Nicola Capuano, Marco Meyer, Francesco David Nota

{"title":"Analyzing the impact of conversation structure on predicting persuasive comments online","authors":"Nicola Capuano, Marco Meyer, Francesco David Nota","doi":"10.1007/s12652-024-04841-8","DOIUrl":"https://doi.org/10.1007/s12652-024-04841-8","url":null,"abstract":"The topic of persuasion in online conversations has social, political and security implications; as a consequence, the problem of predicting persuasive comments in online discussions is receiving increasing attention in the literature. Following recent advancements in graph neural networks, we analyze the impact of conversation structure in predicting persuasive comments in online discussions. We evaluate the performance of artificial intelligence models receiving as input graphs constructed on the top of online conversations sourced from the “Change My View” Reddit channel. We experiment with different graph architectures and compare the performance on graph neural networks, as structure-based models, and dense neural networks as baseline models. Experiments are conducted on two tasks: (1) persuasive comment detection, aiming to predict which comments are persuasive, and (2) influence prediction, aiming to predict which users are persuasive. The experimental results show that the role of the conversation structure in predicting persuasiveness is strongly dependent on its graph representation given as input to the graph neural network. In particular, a graph structure linking only comments belonging to the same speaker in the conversation achieves the best performance in both tasks. This structure outperforms both the baseline model, which does not consider any structural information, and structures linking different speakers’ comments with each other. Specifically, the F1 score of the best performing model is 0.58, which represents an improvement of 5.45% over the baseline model (F1 score of 0.55) and 7.41% over the model linking different speakers’ comments (F1 score of 0.54).","PeriodicalId":14959,"journal":{"name":"Journal of Ambient Intelligence and Humanized Computing","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142202564","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

Emas: an efficient MLWE-based authentication scheme for advanced metering infrastructure in smart grid environment Emas：基于 MLWE 的高效认证方案，适用于智能电网环境中的高级计量基础设施

3区计算机科学

Journal of Ambient Intelligence and Humanized Computing Pub Date : 2024-09-02 DOI: 10.1007/s12652-024-04852-5

Noureddine Chikouche, Fares Mezrag, Rafik Hamza

{"title":"Emas: an efficient MLWE-based authentication scheme for advanced metering infrastructure in smart grid environment","authors":"Noureddine Chikouche, Fares Mezrag, Rafik Hamza","doi":"10.1007/s12652-024-04852-5","DOIUrl":"https://doi.org/10.1007/s12652-024-04852-5","url":null,"abstract":"Advanced metering infrastructure (AMI) plays a critical role in the smart grid by integrating metering systems with communication capabilities, especially for the industrial internet of things. However, existing authentication protocols have proven ineffective against quantum computing attacks and are computationally intensive since AMI contains limited computing components, such as smart meters. In this paper, we present a novel, efficient module learning with errors-based authentication and key agreement system for AMI, which we call EMAS. As part of the security measures of EMAS, Kyber Post-Quantum Public Key Encryption, a one-time pad mechanism, and hash functions are used. A formal and informal analysis of the security features is presented, showing that the proposed system is secure and resistant to known attacks. The performance analysis of our proposed EMAS on a B-L475E-IOT01A node equipped with a ARM Cortex M4 microcontroller shows that EMAS is more efficient than existing relevant schemes. About the computation time, EMAS takes 15.693 ms. This result is lower than other existing relevant schemes.","PeriodicalId":14959,"journal":{"name":"Journal of Ambient Intelligence and Humanized Computing","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142202565","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