Article
Computer Science, Artificial Intelligence
Musarrat Hussain, Fahad Ahmed Satti, Syed Imran Ali, Jamil Hussain, Taqdir Ali, Hun-Sung Kim, Kun-Ho Yoon, TaeChoong Chung, Sungyoung Lee
Summary: This paper presents research work in the field of healthcare to achieve a comprehensive framework using state-of-the-art machine learning techniques to extract knowledge from structured and unstructured data and integrate it with expert knowledge. The technique proposed shows higher accuracy compared to other methods, laying the foundation for an accurate and evolvable knowledge base that greatly enhances decision-making in the healthcare domain.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Chemistry, Physical
Wennan Xiong, Chen Zhu, Dongliang Guo, Chao Hou, Zhaoxi Yang, Zhangyu Xu, Lei Qiu, Hua Yang, Kan Li, YongAn Huang
Summary: Developing multifunctional flying perceptibility by mimicking the comprehensive capabilities of flying creatures, an intelligent flexible sensing skin with components similar to skin-like mechanosensing, neuron-like data transmission, immune system-like impact monitoring, and brain-like artificial intelligence has been shown to bring substantial improvements to aircraft performance. It also holds great potential for extending the capabilities of unmanned air vehicles and underwater vehicles.
Article
Multidisciplinary Sciences
Yupeng Mao, Yuzhang Wen, Bing Liu, Fengxin Sun, Yongsheng Zhu, Junxiao Wang, Rui Zhang, Zuojun Yu, Liang Chu, Aiguo Zhou
Summary: This paper introduces a wireless intelligent sensing system that includes wearable flexible triboelectric nanogenerator sensors and digital signal processing. The system conveniently promotes health and monitors sports skills for disabled people, and can be applied in the fields of human-computer interaction and wheelchair curling.
Article
Materials Science, Multidisciplinary
Yixin Wan, Juan Tao, Ming Dong, Li Zhang, Zhengchun Peng, Rongrong Bao, Caofeng Pan
Summary: A flexible intelligent sensing system has been designed to directly monitor the strain distribution of measured objects. The system utilizes PDMS and Ni-Au metal thin film to achieve high sensitivity, fast response time, and excellent mechanical stability. Combined with an ultra-thin flexible signal processing circuit, the system exhibits improved flexibility, sensitivity, and adaptability, providing real-time and precise 2D mapping of strain distribution.
ADVANCED MATERIALS TECHNOLOGIES
(2022)
Article
Computer Science, Information Systems
Jian Wang, Jia Liu, Guosheng Zhao
Summary: This study proposes a task allocation method based on link prediction in Mobile Crowd Sensing, which selects high-quality sensing users by mining deep link relationships between users and tasks, thus improving the quality of perception.
COMPUTER COMMUNICATIONS
(2022)
Article
Chemistry, Physical
Zhuzhu Shao, Xuan Zhang, Jingfeng Liu, Xingang Liu, Chuhong Zhang
Summary: This study constructs a fabric piezoelectric energy harvester (PEH) by introducing piezoelectric anisotropic BaTi2O5 nanorods (BT2-nr) into piezoelectric polyvinylidene fluoride (PVDF) nanofibers. The developed anisotropic PEH can sensitively identify the forces at different bending directions and is a feasible strategy for fabricating self-powered flexible PEHs with high electromechanical conversion efficiency and multifunctionality for wearable piezoelectric pressure sensors.
Article
Agriculture, Multidisciplinary
Leqin Qin, Junchang Zhang, Stankovski Stevan, Shaohua Xing, Xiaoshuan Zhang
Summary: An intelligent flexible manipulator system based on flexible tactile sensing (IFMSFTS) was developed to classify kiwifruit ripeness and minimize loss. The system uses a flexible tactile sensor coupled with a manipulator to perceive the firmness of kiwifruits and predict their ripeness. By employing principal component analysis (PCA) and K-Nearest neighbor (KNN) and support vector machine (SVM) classifiers, the classification accuracy of PCA-KNN is 97.5% and PCA-SVM is 96.24%. IFMSFTS can accurately classify ripeness, address fruit loss, and achieve sustainable and clean fruit production by sensing the firmness of kiwifruit and utilizing the mapping relationship between firmness and ripeness.
JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE
(2023)
Article
Green & Sustainable Science & Technology
Junchang Zhang, Xuepei Wang, Jie Xia, Shaohua Xing, Xiaoshuan Zhang
Summary: In the face of the challenges posed by the COVID-19 pandemic and global fruit sales trends, the development of an efficient and accurate ripeness grading system for avocados, FSIMS, addresses issues of inconsistent grading, low efficiency, and environmental vulnerability associated with traditional grading methods. By using flexible sensing units to determine avocado firmness, FSIMS achieves a 97.5% accuracy in grading, faster grading speed of 1.3 seconds per fruit, and high environmental robustness, effectively reducing waste in the market supply chain and promoting more sustainable and efficient avocado production.
JOURNAL OF CLEANER PRODUCTION
(2022)
Review
Materials Science, Multidisciplinary
Weitong Wu, Lili Wang, Guozhen Shen
Summary: The beat frequency, flow rate, and oxygen content of human pulsating blood are important health indicators. Noninvasive methods are used for early diagnosis of diseases and real-time monitoring of cardiovascular health. Blood oxygen saturation and pulse rate are key indices for assessing the cardiovascular system. This study summarizes the research outcomes of sensor devices used for blood oxygen and pulse rate signal monitoring and presents enlightening prospects for the future development of flexible PPG sensors.
JOURNAL OF MATERIALS CHEMISTRY C
(2022)
Article
Mining & Mineral Processing
Yonggang Zhang, Jun Tang, Yungming Cheng, Lei Huang, Fei Guo, Xiangjie Yin, Na Li
Summary: This paper proposes a dynamic way to predict landslide displacement based on the GRU neural network and CEEMDAN, and demonstrates its accuracy improvement over SVM in periodic displacement prediction through a case study. The dynamic predictive method significantly enhances accuracy by capturing the dynamic features of the inputs to optimize landslide displacement prediction.
INTERNATIONAL JOURNAL OF MINING SCIENCE AND TECHNOLOGY
(2022)
Article
Chemistry, Multidisciplinary
Yimeng Ni, Xuerui Zang, Jiajun Chen, Tianxue Zhu, Yue Yang, Jianying Huang, Weilong Cai, Yuekun Lai
Summary: Conductive hydrogels have attracted extensive attention due to their application in smart wearable electronics. However, achieving a balance between mechanical and electrical properties remains challenging. In this study, a simplified method for constructing hydrophobic association hydrogels with excellent mechanical and electrical properties is proposed. The developed conductive hydrogels demonstrate high tensile properties, linearity in the whole-strain-range, and a wide strain sensing range. Furthermore, an underwater communication device assembled with the conductive hydrogel successfully transmits signals and provides warnings of potential hazards.
ADVANCED FUNCTIONAL MATERIALS
(2023)
Article
Computer Science, Information Systems
Wenfeng Song, Xia Hou, Shuai Li, Chenglizhao Chen, Danyang Gao, Xian'e Wang, Yuzhe Sun, Jianxia Hou, Aimin Hao
Summary: This study proposes a novel approach to train medical students' diagnosis ability, called Virtual Standard Patient (VSP). By constructing an oral knowledge graph and designing personalized templates, VSP provides realistic and relevant disease clues, interacts accurately with dentists, and expresses symptom characteristics in a natural style. The results of user studies demonstrate that VSP satisfies the requirements of medical students' diagnosis practice in terms of naturalness, realism, and topic relevance.
IEEE TRANSACTIONS ON MULTIMEDIA
(2023)
Article
Chemistry, Multidisciplinary
Wenbo Liu, Youning Duo, Xingyu Chen, Bohan Chen, Tianzhao Bu, Lei Li, Jinxi Duan, Zonghao Zuo, Yun Wang, Bin Fang, Fuchun Sun, Kun Xu, Xilun Ding, Chi Zhang, Li Wen
Summary: This study presents an intelligent soft robotic system that can perceive, describe, and sort objects based on their physical properties. By utilizing a bimodal self-powered flexible sensor (BSFS) based on the triboelectric nanogenerator and giant magnetoelastic effect, the system is able to accurately describe objects using a convolutional neural network (CNN). The study lays a foundation for general artificial intelligence with the ability to interpret and interact with the physical world, as well as serving as an interface between artificial intelligence and soft robots.
ADVANCED FUNCTIONAL MATERIALS
(2023)
Article
Chemistry, Multidisciplinary
Wenbo Liu, Youning Duo, Xingyu Chen, Bohan Chen, Tianzhao Bu, Lei Li, Jinxi Duan, Zonghao Zuo, Yun Wang, Bin Fang, Fuchun Sun, Kun Xu, Xilun Ding, Chi Zhang, Li Wen
Summary: This study presents an intelligent soft robotic system that can perceive, describe, and sort objects based on their physical properties. By integrating bimodal self-powered flexible sensors (BSFS) into the soft fingers, the system achieves remarkable multimodal perception capabilities. Utilizing a convolutional neural network (CNN), the system accurately describes objects and achieves an accuracy rate of up to 97%.
ADVANCED FUNCTIONAL MATERIALS
(2023)
Article
Engineering, Electrical & Electronic
Chen Wang, Jun Wu, Xi Zheng, Bei Pei, Xuyun Zhang, Dongjin Yu, Junhua Tang
Summary: The paper proposes a Dynamic Naming approach to sense the Intelligent Transportation Systems network, which describes the status of changeable objects and organizes the routing table to improve efficiency in network sensing.
IEEE SENSORS JOURNAL
(2021)
Article
Chemistry, Multidisciplinary
Dragana Oros, Marko Pencic, Jovan Sulc, Maja Cavic, Stevan Stankovski, Gordana Ostojic, Olivera Ivanov
Summary: Intravenous (IV) infusion therapy is widely used in hospitals to directly administer medications into the bloodstream or for blood transfusions. The smart IV infusion dosing system presented in the paper allows real-time monitoring and alerting of IV therapy reception, facilitating timely bottle changes and potentially improving treatment outcomes.
APPLIED SCIENCES-BASEL
(2021)
Article
Green & Sustainable Science & Technology
Xuebing Bai, Zetian Fu, Nan Li, Stevan Stankovski, Xiaoshuan Zhang, Xinxing Li
Summary: This study proposed an effective risk assessment method for aquaculture to predict the bioaccumulation of pollutants in fish tissue based on water environment variables, aiming to safeguard China's food safety standards. The method can be extended to other aquaculture applications that require monitoring parameters to ensure quality and safety risk management.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Chemistry, Analytical
Radomir Prodanovic, Sohail Sarang, Dejan Rancic, Ivan Vulic, Goran M. Stojanovic, Stevan Stankovski, Gordana Ostojic, Igor Baranovski, Dusan Maksovic
Summary: This paper presents a trust model for monitoring humidity and moisture in agricultural and industrial environments, using digital signature and PKI to establish trust in sensor data source, and implementing timestamp technology to ensure data accuracy and integrity. Model validation shows significant improvement in WSN trust entity with increased power consumption and packet delay, as well as validating time for obtained timestamps.
Article
Green & Sustainable Science & Technology
Srdjan Tegeltija, Stefan Dejanovic, Huanhuan Feng, Stevan Stankovski, Gordana Ostojic, Denis Kucevic, Jelena Marjanovic
Summary: Organic production as a sustainable food production system aims to implement agroecological principles for health, environmental protection, and economic benefits. However, producers face administrative obstacles and consumers lack confidence in the control mechanisms, leading to the presence of counterfeit products in the market.
Article
Chemistry, Multidisciplinary
Ivan Vulic, Mirko Borisov, Radomir Prodanovic, Dejan Rancic, Vladimir M. Petrovic, Stevan Stankovski, Gordana Ostojic
Summary: The quality of DEMs is evaluated based on their spatial resolution and the type of terrain. This study analyzed LiDAR-based DEMs and compared them with radar recording method results. A model was developed to ensure the non-repudiation and protection of DEM data in security-sensitive systems, demonstrating the detection of even the smallest changes and proving data authenticity and the sender's non-repudiation.
APPLIED SCIENCES-BASEL
(2022)
Article
Food Science & Technology
Zihan Yang, Jinchao Xu, Lin Yang, Xiaoshuan Zhang
Summary: This study analyzed the logistics process of Tibetan matsutake and optimized the dynamic monitoring and quality management systems in the cold chain using different preservation packaging. The research concluded that the matsutake were best preserved under modified atmosphere packaging. The optimized model could provide a more effective theoretical reference for dynamic monitoring and quality management.
Article
Chemistry, Analytical
Pengfei Liu, Luwei Zhang, You Li, Huanhuan Feng, Xiaoshuan Zhang, Mengjie Zhang
Summary: This study developed a flexible pressure sensor system using PDMS as the substrate and rGO as the sensitive layer to monitor the shell-closing strength (SCS) of live oysters. The time series model was used to predict the survival rate based on changes in SCS. The results show that SCS is a key physiological indicator of oyster survival, and dynamic monitoring using flexible pressure sensors can improve oyster survival rate.
Article
Chemistry, Analytical
Xiaoshuan Zhang, Yuliang Li, Tianyu Hong, Srdjan Tegeltija, Mladen Babic, Xiang Wang, Gordana Ostojic, Stevan Stankovski, Dragan Marinkovic
Summary: Post-ripening fruits need to be ripened using temperature control and gas regulation, with the proportion of ethylene being a key parameter. A sensor's response characteristic curve was obtained through ethylene monitoring, showing good response speed, stability, and repeatability. The optimal ripening parameters include color, hardness, adhesiveness, and chewiness, which are consistent with the sensor's response characteristics.
Article
Polymer Science
Ognjan Luzanin, Vera Guduric, Anne Bernhardt, Dejan Movrin, Ljiljana Damjanovic-Vasilic, Pal Terek, Gordana Ostojic, Stevan Stankovski
Summary: Due to affordability and parametric control, material extrusion is widely accepted in tissue engineering. An empirical model was used to control the level of in-process crystallinity of PLA scaffolds. High crystallinity scaffolds showed better cell response. The micro- and nanosurface topographic features of the scaffolds were the main contributor to the improved cell response.
Article
Green & Sustainable Science & Technology
Sergey Fominykh, Stevan Stankovski, Vladimir M. Markovic, Dusko Petrovic, Sead Osmanovic
Summary: The storage of CO2 is a significant global concern due to its impact on climate change. Carbon Capture and Storage (CCS) is a possible solution that involves removing excess CO2 from the atmosphere and securely storing it. This study focuses on horizontal saline aquifers and their ability to store CO2, analyzing the impact of CO2 permeability and aquifer porosity on horizontal migrations.
Article
Computer Science, Information Systems
Danijela Protic, Miomir Stankovic, Radomir Prodanovic, Ivan Vulic, Goran M. Stojanovic, Mitar Simic, Gordana Ostojic, Stevan Stankovski
Summary: Anomaly-based intrusion detection systems classify computer network behavior by identifying deviations from the statistical model of typical behavior. Feature selection and feature scaling are commonly used techniques to improve classifier performance.
Article
Computer Science, Information Systems
Sohail Sarang, Goran M. Stojanovic, Micheal Drieberg, Stevan Stankovski, Kishore Bingi, Varun Jeoti
Summary: The dynamic nature of energy harvesting rate in EH-WSNs raises new concerns and drives the development of energy aware solutions. A prediction-based adaptive duty cycle (PADC) MAC protocol, called PADC-MAC, has been proposed to improve network performance by incorporating current and future harvested energy information. The protocol utilizes a machine learning model, NAR neural network, to achieve accurate energy intake prediction. Simulation results show significant improvements in packet delay, energy consumption, and total energy consumption compared to state-of-the-art protocols.
