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Security Concerns with IoT-Based Health and Fitness Systems
Published in Ambikapathy, R. Shobana, Logavani, Dharmasa, Reinvention of Health Applications with IoT, 2022
Pushpendu Rakshit, Pramod Kumar Srivastava, Omkar Chavan
Security of IoT devices is critical. IoT sensors play a vital role in data collection, transfer, storage, and solutions. Built-in security codes in software allow sensors to function smoothly and secure the data in critical stages [11]. IoT sensors make use of secure boot to ensure that the device only executes codes produced by the original equipment manufacturer (OEM) or trusted party. An assigned public key helps to prevent malicious attacks from a third party and only allows OEM devices to execute software codes [12]. The firmware updates of devices help in server authentication before downloading or uploading and thereby add a layer of protection. For instance, an antivirus software on a desktop computer helps to protect the data on its hard drive. When we try to download an external file from through a web browser, the software first scans the file in boot scanner for any malicious threat. It then only downloads the file in encrypted form and decrypts it onto our hard drive. This end-to-end function is processed with the help of analytical sensors and detections available in software. Datagram transport layer security (DTLS) or transport layer security (TLS) helps to encrypt and transfer data in secured connection with the help of wireless protocols. Sensors secure the gateway while performing data collection or data analysis. For instance, the banking network contains data related to their clients and banking financial information.
Potential hydrometallurgical processes to recycle metals from discarded personal computer
Published in Geosystem Engineering, 2022
Om Shankar Dinkar, Rukshana Parween, Rekha Panda, Pankaj Kumar Choubey, Balram Ambade, Manis Kumar Jha
The PCs are one of the most widespread electrical and electronic equipment used in corporate/home for work, entertainment and communication placed at the top in waste electronic equipments (WEEs). Printed circuit boards (PCBs) inside a desktop computer is the wide sized motherboard, which is also known as the backbone of all types of electronic components. The PCBs of PCs are made up of 27.00 wt. % polymer, 28.00 wt. % ceramic, and 45.00 wt. % metals (Yamane et al., 2011) including some percentage of toxic metals too. If they are not recycled properly, then it can contaminate the air, soil and groundwater. And when PCBs are burned, dioxin and furan gases are emitted, which causes health and environmental hazards (Bi et al., 2010; Hadi et al., 2013; Owens et al., 2007). In addition to this, scrap PCBs contains all types of precious (Au, Ag, Pd, and Pt), base metals (Cu, Ni, Fe, and Fe) and rare earth metals, which can be recovered using recycling techniques (Guo et al., 2010; Park & Fray, 2009; Veit et al., 2005). The effective collection system and the efficient recycling technologies are still lacking (J. C. Lee et al., 2007). Only 17.4% of e-wastes were properly collected and recycled according to a global report (Forti et al., 2020).
Tree-Based Ensemble Machine Learning Techniques for Power System Static Security Assessment
Published in Electric Power Components and Systems, 2022
The IEEE 14-bus, 30-bus, 118-bus, and real 75-bus systems are analyzed in this section. A desktop computer runs all the programs with the central processing unit (CPU) of frequency 4 GHz and 8 GB of memory in MATLAB 2019a. The solution’s feasibility is validated by verifying the predictive values with the real values of the index. In test systems, all contingencies are considered except the one which results in the islanding of the system. Alarm limit and security limit of bus voltages are set at ±5% and ±7%, respectively. For line flows alarm limit is set to 80% of the security limit. Response and corresponding observations for exemplars are listed in Table 1.
Vehicle Interior Sound Classification Based on Local Quintet Magnitude Pattern and Iterative Neighborhood Component Analysis
Published in Applied Artificial Intelligence, 2022
Erhan Akbal, Turker Tuncer, Sengul Dogan
VISC8 database was collected from YouTube PoV drive videos, and interior sounds were stored as m4a format. MATLAB2018a programming environment was used to implement our model on these sounds. The proposed LQMP and INCA based VISC method was implemented on a desktop computer, and this computer has 16 GB main memory and intel i7 7700 microprocessor. The used operating system is Windows 10.1 ultimate.