Article
Biotechnology & Applied Microbiology
Mohammad Hosseinifard, Tina Naghdi, Eden Morales-Narvaez, Hamed Golmohammadi
Summary: The rapid spread of the COVID-19 pandemic has highlighted the importance of diagnostics for life-saving decisions. Smart diagnostics enabled by industry 4.0 technologies, such as Internet of Things, play a crucial role in providing key data for pandemic treatment and prevention, and should be implemented sooner rather than later to avoid situations worse than the current one.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2021)
Article
Computer Science, Information Systems
Nadeem Javaid
Summary: This study explores an efficient integration of IoT devices based on context awareness in the agricultural sector. A four-layered framework with embedded automation techniques is proposed to obtain real-time context aware insights from the IoT ecosystem. The framework is evaluated using a strategic tool called TOWS matrix to measure the performance of automation techniques. This analysis identifies various opportunities to innovate the livelihood of agrarian society globally.
Article
Computer Science, Interdisciplinary Applications
Farhan A. Alenizi, Shirin Abbasi, Adil Hussein Mohammed, Amir Masoud Rahmani
Summary: This paper reviews 45 articles on the integration of AI and Industry 4.0, proposes a taxonomy, and identifies current challenges and open issues. The findings show that machine learning is the most common AI method in improving Industry 4.0, with Python being the most commonly used simulation tool.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Review
Chemistry, Analytical
Jitendra Bhatia, Kiran Italiya, Kuldeepsinh Jadeja, Malaram Kumhar, Uttam Chauhan, Sudeep Tanwar, Madhuri Bhavsar, Ravi Sharma, Daniela Lucia Manea, Marina Verdes, Maria Simona Raboaca
Summary: With the rapid growth in data and cloud processing, accessing data has become easier, but it poses technical and security challenges. Fog computing is a promising solution for handling security-critical and time-sensitive IoT big data. This paper explores research challenges and solutions for fog data analytics and IoT networks, and experimental analysis shows that fog computing outperforms cloud in terms of network utilization and latency. Future trends are also discussed.
Review
Biotechnology & Applied Microbiology
Hooi Ren Lim, Kuan Shiong Khoo, Wen Yi Chia, Kit Wayne Chew, Shih-Hsin Ho, Pau Loke Show
Summary: This review paper discusses the potential and process of applying IoT and AI technology in microalgae farming. Accurate monitoring of various parameters during the cultivation stage is crucial for ensuring biomass productivity. Integration of IoT can simplify the production process, while machine learning can be used for optimizing microalgae cultivation.
BIOTECHNOLOGY ADVANCES
(2022)
Review
Chemistry, Analytical
Carlos Poncinelli Filho, Elias Marques Jr, Victor Chang, Leonardo dos Santos, Flavia Bernardini, Paulo F. Pires, Luiz Ochi, Flavia C. Delicato
Summary: This paper investigates the challenges of running machine learning and deep learning algorithms on edge devices in a distributed manner. It focuses on how techniques are adapted or designed for execution on restricted devices, discussing techniques in caching, training, inference, and offloading processes, as well as exploring the benefits and drawbacks of these strategies.
Article
Computer Science, Information Systems
Mohammad Tabrez Quasim, Khair ul Nisa, Mohammad Zunnun Khan, Mohammad Shahid Husain, Shadab Alam, Mohammed Shuaib, Mohammad Meraj, Monir Abdullah
Summary: Energy theft is a significant problem in smart cities, and a proposed Energy Theft Prevention System (ETPS) that utilizes machine learning techniques has been proven to be more effective in detecting energy theft.
JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS
(2023)
Article
Computer Science, Hardware & Architecture
Priyanka Bothra, Raja Karmakar, Sanjukta Bhattacharya, Sayantani De
Summary: IoT and computing operate together to provide significant services in various sectors. However, IoT devices are vulnerable to cyber attacks, leading to security loopholes. Blockchain and AI have been integrated with IoT to design secure and intelligent models, enabling the utilization of their full capacities.
Review
Chemistry, Physical
Yuankai Zhou, Maoliang Shen, Xin Cui, Yicheng Shao, Lijie Li, Yan Zhang
Summary: The sensor based on the triboelectric nanogenerator has excellent material compatibility, low cost, and high flexibility, making it a unique candidate technology for artificial intelligence. Triboelectric nanogenerators effectively provide the critical infrastructure for the new generation of sensing systems that collect information through a large number of self-powered sensors. The application of triboelectric nanogenerators in intelligent sports, security, touch control, and document management systems has attracted increasing attention in the field of artificial intelligence.
Article
Computer Science, Information Systems
Francesco Piccialli, Fabio Giampaolo, Edoardo Prezioso, Danilo Crisci, Salvatore Cuomo
Summary: Smart parking is a critical component of a smart city, utilizing IoT sensors and mobile applications to reduce air pollution and traffic noise, optimize parking search times and traffic flow, thereby improving urban traffic efficiency.
ACM TRANSACTIONS ON INTERNET TECHNOLOGY
(2021)
Article
Computer Science, Information Systems
Ankit Verma, Gaurav Agarwal, Amit Kumar Gupta
Summary: In the modern healthcare system, the Internet of Things (IoT) and data mining methods with cloud computing play an important role in predicting and diagnosing various diseases. This research proposes a predictive method using the cloud and IoT-based database to forecast diseases accurately, and introduces a novel Generalized Fuzzy Intelligence-based Ant Lion Optimization (GFIbALO) classifier along with a regression rule.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2022)
Review
Computer Science, Information Systems
Atefeh Hemmati, Amir Masoud Rahmani
Summary: The Internet of Autonomous Things (IoAT) is a new concept that enables autonomous devices to connect and share information without human intervention. It includes robotics, autonomous vehicles, drones, and smart home devices. Recent progress in deep learning and artificial intelligence (AI) is the foundation for all IoAT applications. Transportation is the most prominent application domain for IoAT.
INTERNET OF THINGS
(2022)
Article
Chemistry, Analytical
Puchuan Tan, Yuan Xi, Shengyu Chao, Dongjie Jiang, Zhuo Liu, Yubo Fan, Zhou Li
Summary: Hypertension is a significant global health issue, and traditional blood pressure measurement methods may lead to misdiagnosis. This article presents an artificial intelligence-enhanced blood pressure monitoring wristband that can continuously monitor blood pressure and predict blood pressure readings.
Review
Computer Science, Information Systems
Abdul Matin, Md Rafiqul Islam, Xianzhi Wang, Huan Huo, Guandong Xu
Summary: The integration of IoT and AI, known as AIoT, has become a focus in the manufacturing industry for its potential to digitize and drive sustainability. AIoT solutions provide benefits such as improved efficiency, reduced waste, and increased safety measures. Adoption of these solutions has increased and academic researchers and industry practitioners are developing advanced AIoT-based techniques for sustainable manufacturing. This paper aims to provide an overview of AIoT-based industry technology, survey existing research, discuss current challenges, and explore research prospects in the field.
INTERNET OF THINGS
(2023)
Article
Computer Science, Hardware & Architecture
Nagender Kumar Suryadevara
Summary: The paper discusses how ML algorithms are applied in the resource-constrained IoT fog computing framework, and how ML classifiers are utilized to reduce latency and energy consumption by using ambient sensors in the IoT theme.
SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS
(2021)
Article
Engineering, Multidisciplinary
Mehmet Cagatay Akbolat, Kali Babu Katnam, Constantinos Soutis, Prasad Potluri, Stephan Sprenger, James Taylor
Summary: This study investigates the influence of hybrid toughening on carbon fiber/epoxy laminates, and finds that hybrid toughening significantly enhances fracture energy and R-curve behavior by intrinsic and extrinsic toughening mechanisms. Fractography analysis shows that hybrid toughening can constrain crack propagation and absorb more energy.
COMPOSITES PART B-ENGINEERING
(2022)
Article
Automation & Control Systems
Xiaoli Tang, Yuandong Xu, Xiuquan Sun, Yanfen Liu, Yu Jia, Fengshou Gu, Andrew D. Ball
Summary: Helical gearboxes are crucial for power transmission in industrial applications, but they are prone to various faults due to long-term and heavy-duty operations. Conventional measurements for gearbox fault diagnosis include lubricant analysis, vibration, airborne acoustics, thermal images, and electrical signals. However, relying on a single measurement domain may lead to unreliable diagnosis, especially in harsh environments. This article proposes a Compressive Sensing-based Dual-Channel Convolutional Neural Network method that utilizes non-contact measurements (thermal images and acoustic signals) to accurately diagnose gearbox faults.
Article
Automation & Control Systems
Teruyoshi Kanno, Hiroki Kurita, Fumio Narita
Summary: Cellulose nanofiber (CNF) was incorporated into a SiC slurry via robocasting method to strengthen the SiC green bodies. The addition of CNF increased the flexural strength of SiC green bodies due to the increased number of hydrogen-bonding sites. However, annealing at 250 degrees C caused a decrease in flexural strength due to bonding sites via trapped water on CNF. Moreover, the addition of CNF did not affect the relative densities, microstructures, and crystalline phases of the sintered SiC body, showing its suitability for robocasting.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Chemistry, Analytical
Youxi Hu, Chao Liu, Ming Zhang, Yu Jia, Yuchun Xu
Summary: Remanufacturing extends the life cycle and increases the residual value of end-of-life products. Disassembly is crucial in retrieving valuable components from these products, and disassembly lines are introduced to improve efficiency. However, existing research on disassembly line balancing problem (DLBP) focuses on straight lines and single-objective optimization methods, lacking representation of the actual disassembly environment. This paper introduces a stochastic parallel complete DLBP and proposes a simulated annealing-based hyper-heuristic algorithm (HH) for multi-objective optimization, demonstrating its feasibility and superiority through computational experiments.
Article
Engineering, Electrical & Electronic
Daiki Neyama, Siti Masturah Binti Fakhruddin, Kumi Y. Inoue, Hiroki Kurita, Shion Osana, Naoto Miyamoto, Tsuyoki Tayama, Daiki Chiba, Masahito Watanabe, Hitoshi Shiku, Fumio Narita
Summary: This study investigates the dynamic characteristics of batteryless magnetostrictive alloys for energy harvesting to detect human coronavirus 229E (HCoV-229E). A light and thin magnetostrictive Fe-Co/Ni clad plate with rectification, DC voltage storage capacitor, and wireless information transmission circuits was developed. A novel CD13 biorecognition layer was immobilized on the clad plate surface, allowing successful detection of HCoV-229E.
SENSORS AND ACTUATORS A-PHYSICAL
(2023)
Article
Engineering, Electrical & Electronic
An Li, Keiju Goto, Yuusuke Kobayashi, Yushin Hara, Yu Jia, Yu Shi, Constantinos Soutis, Hiroki Kurita, Fumio Narita, Keisuke Otsuka, Kanjuro Makihara
Summary: In this work, a switching control energy harvesting method using magnetostrictive materials is proposed, which enables large-scale kinetic to electrical energy conversion. The method combines a magnetostrictive material, an electric circuit, and an electronic switch. Numerical simulations were conducted to optimize the parameters, and experimental measurements validated the harvesting performance using a 3.75 m vibrated cantilever truss structure. The proposed method achieved an electrical energy of approximately 45μJ in 20.0 s, which is seven times more than that of the conventional passive method.
SENSORS AND ACTUATORS A-PHYSICAL
(2023)
Article
Chemistry, Physical
Renzhi Li, Yangyang Feng, R. Hugh Gong, Constantinos Soutis
Summary: A fully biodegradable straw formed by stereocomplexation of poly (lactic acid) (SC-PLA) is reported, which outperforms its counterparts on the market due to the unique strong interaction and high density of link chains between stereocomplex crystallites. SC-PLA straws offer the advantages of simple processing and relatively low cost, making them a superior substitute for plastic ones. The proposed SC-PLA straws lose less than 5% of their flexural strength when wet, while commercially available PLLA straws lose almost 60%.
Article
Polymer Science
Hatim Alotaibi, Chamil Abeykoon, Constantinos Soutis, Masoud Jabbari
Summary: This paper presents a numerical framework for modelling and simulating convection-diffusion-reaction flows in liquid composite moulding (LCM). The model incorporates cure kinetics and rheological characteristics of thermoset resin impregnation. The simulations show its ability to provide information on flow-front, viscosity development, degree of cure, and rate of reaction at once. The model has been validated with a comparative analysis, showing good agreement with previous research findings.
Article
Polymer Science
Lovisa Rova, Hiroki Kurita, Shinji Kudo, Sho Hatayama, Teruyoshi Kanno, Alia Gallet-Pandelle, Fumio Narita
Summary: Little is known about the changes in strength of biodegradable polymers during decomposition. This study focused on the tensile properties of polybutylene succinate (PBS) and basalt-fiber (BF)-reinforced PBS (PBS-BF) composite sheets during degradation in bacterial solutions. The results showed that the elongation at break of PBS specimens decreased significantly after 7 days, while the PBS-BF composite specimens had barely any change in ultimate tensile strength (UTS) after immersion in bacteria-free medium for 7 and 56 days. However, when immersed in bacterial solution, the UTS of PBS-BF composite specimens showed a tendency to decrease after 7 days, and after 56 days, it decreased to about half of its initial value, indicating decomposition throughout the material due to infiltration of the bacterial solution into structurally weak areas.
Article
Engineering, Manufacturing
Yaonan Yu, Yu Shi, Hiroki Kurita, Yu Jia, Zhenjin Wang, Fumio Narita
Summary: This study developed a carbon fiber-reinforced polymer combined with a sodium potassium niobate nanoparticle-filled epoxy plate, which exhibited enhanced mechanical properties and served as a force sensor for damage detection. The voltage signals generated by this composite accurately reflected crack growth in a bending test, providing real-time crack state and fracture prediction.
COMPOSITES PART A-APPLIED SCIENCE AND MANUFACTURING
(2023)
Article
Materials Science, Composites
Tao Wen, Fumio Narita, Hiroki Kurita, Yu Jia, Yu Shi
Summary: This paper presents a feasibility study on quantifying damage size using the integral differential method. The study successfully validates the quantification method using piezoelectric transducers and composite panels, combined with thermography imaging technology for measuring damage geometrical dimensions. The study derived a quantification formula through numerical analysis, which showed a linear relation between the damage index and size governed by power and logarithmic functions.
COMPOSITES SCIENCE AND TECHNOLOGY
(2023)
Article
Materials Science, Composites
Tomoki Miyashita, Kenichi Katabira, Hiroki Kurita, Takeru Nakaki, Fumio Narita
Summary: This study investigated the crack self-sensing capability of GFRP composites with magnetostrictive Fe-Co fibers under mixed-mode bending. The self-sensing capability of crack propagation was discussed by measuring the magnetic flux density induced by the inverse magnetostrictive effect using Hall probes. The GFRP composites with Fe-Co fibers fabricated in this study are a promising monitoring technology for non-contact sensing.
COMPOSITES SCIENCE AND TECHNOLOGY
(2023)
Article
Chemistry, Physical
Hiroki Kurita, Siti Masturah Binti Fakhruddin, Kumi Y. Inoue, Takeru Nakaki, Shotaro Kuroda, Zhenjin Wang, Wakako Araki, Hitoshi Shiku, Fumio Narita
Summary: In this study, cobalt ferrite (CoFe2O4) was spattered onto a Fe-Co alloy plate, resulting in higher energy-harvesting and mass sensor performances compared to the Fe-Co/Ni clad plate. The CoFe2O4-spattered Fe-Co alloy plate successfully transmitted the electrical signal and the output voltage was significantly changed by the adhesion of microgram silica particles. The CoFe2O4-spattered Fe-Co alloy plate has considerable value as a self-powered mass sensor, which is significant for the development of battery-free virus sensors.
JOURNAL OF ALLOYS AND COMPOUNDS
(2023)
Review
Chemistry, Analytical
Tianzhuo Zhan, Mao Xu, Zhi Cao, Chong Zheng, Hiroki Kurita, Fumio Narita, Yen-Ju Wu, Yibin Xu, Haidong Wang, Mengjie Song, Wei Wang, Yanguang Zhou, Xuqing Liu, Yu Shi, Yu Jia, Sujun Guan, Tatsuro Hanajiri, Toru Maekawa, Akitoshi Okino, Takanobu Watanabe
Summary: Wide-bandgap gallium nitride (GaN)-based semiconductors offer advantages in high-power and high-frequency operations, but self-heating effects (SHE) cause performance degradation. Reducing thermal boundary resistance (TBR) is necessary for better heat dissipation.
