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The secure USB flash drive was developed to improve the security of the conventional USB flash drive, which is vulnerable to leakages of internally stored data caused by extortion, loss, etc. However, it has been continuously reported that the secure USB flash drive, which protects data through the adoption of a wide range of security technologies in wide-ranging ways, cannot assure data security because of implementation and environmental vulnerabilities, eavesdropping, unlock commands, and reverse engineering. As such, there is growing demand for a more powerful secure USB flash drive to solve these fundamental problems. Therefore, this paper presents a secure USB mechanism that prevents leakages of authentication data and does not compare authentication data for smart human care services, which have been a fundamental problem of existing flash drives. The proposed mechanism provides better security than the existing secure USB flash drive by satisfying the need for confidentiality, integrity, authentication, and access control and safely protecting data from impersonation, man-in-the-middle, replay, and eavesdropping attacks by malicious attackers. An assessment of its security using the formalized verification tool AVISPA has proved that it is safe. Therefore, it is considered that a safer, more secure USB flash drive can be manufactured using the mechanism proposed in this paper.

With data becoming a centerpiece of modern scientific discovery, data sharing by scientists is now a crucial element of scientific progress. This article aims to provide an in-depth examination of the practices and perceptions of data management, including data storage, data sharing, and data use and reuse by scientists around the world. The Usability and Assessment Working Group of DataONE, an NSF-funded environmental cyberinfrastructure project, distributed a survey to a multinational and multidisciplinary sample of scientific researchers in a two-waves approach in 2017-2018. We focused our analysis on examining the differences across age groups, sub-disciplines of science, and sectors of employment. Most respondents displayed what we describe as high and mediocre risk data practices by storing their data on their personal computer, departmental servers or USB drives. Respondents appeared to be satisfied with short-term storage solutions; however, only half of them are satisfied with available mechanisms for storing data beyond the life of the process. Data sharing and data reuse were viewed positively: over 85% of respondents admitted they would be willing to share their data with others and said they would use data collected by others if it could be easily accessed. A vast majority of respondents felt that the lack of access to data generated by other researchers or institutions was a major impediment to progress in science at large, yet only about a half thought that it restricted their own ability to answer scientific questions. Although attitudes towards data sharing and data use and reuse are mostly positive, practice does not always support data storage, sharing, and future reuse. Assistance through data managers or data librarians, readily available data repositories for both long-term and short-term storage, and educational programs for both awareness and to help engender good data practices are clearly needed.

Additive Manufacturing (AM) technology enables the production of personalized goods at reduced development costs, shorter lead times, lower energy consumption during manufacturing, and decreased material waste. AM will be consolidated as a leading technology in numerous sectors in the near future due to the maturity of the technology, the wide range of possibilities afforded by 3D printing, and the institutional push. One of the most important aspects of Industry 4.0 is 3D printing. It may be used to fabricate complicated parts and allows companies to cut inventory, develop on-demand items, create smaller localized manufacturing conditions, and even shorten supply chains. AM is expected to increase rapidly in the future because of its above stated remarkable “performance record.“ According to a report published the AM market is predicted to produce US$2 trillion worth of components and end products by year 2030. Hence integration of smart technology and production systems or indirectly one can say that AM is promoting Industry 4.0 and it plays a pivotal role in solving some of the 4th industrial revolution’s most important needs. AM is a future paradigm for futuristic production systems, and Industry 4.0 will leverage its potential to reach essential goals. AM will be found now days in a variety of industrial applications including aerospace and health care to consumer goods. This review article discusses about brief AM technology, history, its industrial applications, challenges, and future prospective. Finally, case studies using AM has been considered.

The universal serial bus (USB) has some advantages like high transmission speed, plug-and-play and hot swapping, and has become the most popular interface standard for peripheral connections. However, such features also make it easier for a malicious user to extract confidential files from computer systems via USB ports. Consequently, to control the potential security risks of USB interface, many workplace and commercial corporations have directly forbidden their employees from using USB devices. To provide a flexible way of using USB without compromising security, this study proposes a novel secure control protocol for USB storage devices. The device and the server are required to complete mutual authentication and establish a session key used to encrypt the transferred files. The details of each phase of the new protocol are given. Security analysis demonstrates that the proposed protocol conquers those security pitfalls existing in the available protocols and can resist various attacks. Performance discussion indicates that the new protocol is also efficient enough for practical applications.

A nanopore DNA sequencer is used for real-time genomic surveillance of the Ebola virus epidemic in the field in Guinea; the authors demonstrate that it is possible to pack a genomic surveillance laboratory in a suitcase and transport it to the field for on-site virus sequencing, generating results within 24 hours of sample collection. Ebola virus genomics surveillance This paper reports the use of nanopore DNA sequencers (known as MinIONs) for real-time genomic surveillance of the Ebola virus epidemic, in the field in Guinea. The authors demonstrate that it is possible to pack a genomic surveillance laboratory in a suitcase and transport it to the field for on-site virus sequencing, generating results within 24 hours of sample collection. The Ebola virus disease epidemic in West Africa is the largest on record, responsible for over 28,599 cases and more than 11,299 deaths 1 . Genome sequencing in viral outbreaks is desirable to characterize the infectious agent and determine its evolutionary rate. Genome sequencing also allows the identification of signatures of host adaptation, identification and monitoring of diagnostic targets, and characterization of responses to vaccines and treatments. The Ebola virus (EBOV) genome substitution rate in the Makona strain has been estimated at between 0.87 × 10 −3 and 1.42 × 10 −3 mutations per site per year. This is equivalent to 16–27 mutations in each genome, meaning that sequences diverge rapidly enough to identify distinct sub-lineages during a prolonged epidemic 2 , 3 , 4 , 5 , 6 , 7 . Genome sequencing provides a high-resolution view of pathogen evolution and is increasingly sought after for outbreak surveillance. Sequence data may be used to guide control measures, but only if the results are generated quickly enough to inform interventions 8 . Genomic surveillance during the epidemic has been sporadic owing to a lack of local sequencing capacity coupled with practical difficulties transporting samples to remote sequencing facilities 9 . To address this problem, here we devise a genomic surveillance system that utilizes a novel nanopore DNA sequencing instrument. In April 2015 this system was transported in standard airline luggage to Guinea and used for real-time genomic surveillance of the ongoing epidemic. We present sequence data and analysis of 142 EBOV samples collected during the period March to October 2015. We were able to generate results less than 24 h after receiving an Ebola-positive sample, with the sequencing process taking as little as 15–60 min. We show that real-time genomic surveillance is possible in resource-limited settings and can be established rapidly to monitor outbreaks.

Computer Vision (CV) has become increasingly important for Single-Board Computers (SBCs) due to their widespread deployment in addressing real-world problems. Specifically, in the context of smart cities, there is an emerging trend of developing end-to-end video analytics solutions designed to address urban challenges such as traffic management, disaster response, and waste management. However, deploying CV solutions on SBCs presents several pressing challenges (e.g., limited computation power, inefficient energy management, and real-time processing needs) hindering their use at scale. Graphical Processing Units (GPUs) and software-level developments have emerged recently in addressing these challenges to enable the elevated performance of SBCs; however, it is still an active area of research. There is a gap in the literature for a comprehensive review of such recent and rapidly evolving advancements on both software and hardware fronts. The presented review provides a detailed overview of the existing GPU-accelerated edge-computing SBCs and software advancements including algorithm optimization techniques, packages, development frameworks, and hardware deployment specific packages. This review provides a subjective comparative analysis based on critical factors to help applied Artificial Intelligence (AI) researchers in demonstrating the existing state of the art and selecting the best suited combinations for their specific use-case. At the end, the paper also discusses potential limitations of the existing SBCs and highlights the future research directions in this domain.

IntroductionJUUL is an electronic cigarette (ECIG) with a compact form factor. It is prefilled with a liquid that is advertised to contain a high concentration of nicotine salt. JUUL commands 50% of the US ECIG market share, and its wide popularity with underage users has triggered unprecedented actions by the US FDA. Apart from its nicotine salt-containing liquid and compact form, a salient advertised design feature is a control circuit that limits the heating coil temperature, presumably reducing unwanted toxicants. In this study, several tobacco-flavoured JUUL devices were reverse engineered, and their aerosol emissions were studied.MethodsTotal nicotine and its partitioning (freebase and protonated), propylene glycol/vegetable glycerin (PG/VG) ratio, and carbonyls were quantified by gas chromatography (GC) and high performance liquid chromatography (HPLC). The temperature control functionality of JUUL was investigated using a temperature-controlled bath in which the coil was submerged.ResultsThe liquid nicotine concentration was found to be 69 mg/mL, and the liquid and aerosol PG/VG ratio was found to be 30/70. In 15 puffs, JUUL emitted 2.05 (0.08) mg of nicotine, overwhelmingly in the protonated form. Carbonyl yields were significantly lower than those reported for combustible cigarettes, but similar to other closed-system ECIG devices. The heating coil resistance was 1.6 (0.66) Ohm, while the maximum power delivered by the JUUL device was 8.1 W. The control circuit limited the peak operating temperature to approximately 215C.ConclusionsJUUL emits a high-nicotine concentration aerosol predominantly in the protonated form. JUUL’s nicotine-normalised formaldehyde and total aldehyde yields are lower than other previously studied ECIGs and combustible cigarettes.

Electronic Control Units (ECUs) have been increasingly used in modern vehicles to control the operations of the vehicle, improve driving comfort, and safety. For the operation of the vehicle, these ECUs communicate using a Controller Area Network (CAN) protocol that has many security vulnerabilities. According to the report of Upstream 2022, more than 900 automotive cybersecurity incidents were reported in 2021 only. In addition to developing a more secure CAN protocol, intrusion detection can provide a path to mitigate cyberattacks on the vehicle. This paper proposes a machine learning-based intrusion detection system (IDS) using a Support Vector Machine (SVM), Decision Tree (DT), and K-Nearest Neighbor (KNN) and investigates the effectiveness of the IDS using multiple real-world datasets. The novelty of our developed IDS is that it has been trained and tested on multiple vehicular datasets (Kia Soul and a Chevrolet Spark) to detect and classify intrusion. Our IDS has achieved accuracy up to 99.9% with a high true positive and a low false negative rate. Finally, the comparison of our performance evaluation outcomes demonstrates that the proposed IDS outperforms the existing works in terms of its liability and efficiency to detect cyber-attacks with a minimal error rate.

The paper presents a highly efficient, low cost, ultra-wideband, microstrip monopole antenna for microwave imaging and wireless communications applications. A new structure (z-shape, ultra-wideband (UWB) monopole) is designed, which consists of stepped meander lines to achieve super-wide bandwidth and high efficiency. Three steps are used to design the proposed structure for the purpose to achieve high efficiency and wide bandwidth. The antenna bandwidth is enhanced by varying the length of meander line slots, optimization of the feeding line and with the miniaturization of the ground width. The simulated and measured frequency bands are 2.7–22.5 GHz and 2.8–22.7 GHz (156% fractional bandwidth), respectively. The dimensions of the antenna are 38 mm × 35 mm × 1.57 mm, and its corresponding electrical size is 2.41 λg × 2.22 λg × 0.09 λg, where guided wavelength λg is at the center frequency (12.75 GHz). This antenna achieved a high bandwidth ratio (8.33:1). The realized gain is varying from 1.6–6.4 dBi, while that of efficiency is 70% to 93% for the whole band. Radiation patterns are measured at four operating frequencies. It has an acceptable group delay, fidelity factor, and phase variation results that satisfy the limit of ultra-wideband in the form of the time domain.

The demand for wearable and point-of-care devices has led to an increase in electrochemical sensor development to measure an ever-increasing array of biological molecules. In order to move from the benchtop to truly portable devices, the development of new biosensors requires miniaturized instrumentation capable of making highly sensitive amperometric measurements. To meet this demand, we have developed KickStat, a miniaturized potentiostat that combines the small size of the integrated Texas Instruments LMP91000 potentiostat chip (Texas Instruments, Dallas, TX, USA) with the processing power of the ARM Cortex-M0+ SAMD21 microcontroller (Microchip Technology, Chandler, AZ, USA) on a custom-designed 21.6 mm by 20.3 mm circuit board. By incorporating onboard signal processing via the SAMD21, we achieve 1 mV voltage increment resolution and an instrumental limit of detection of 4.5 nA in a coin-sized form factor. This elegant engineering solution allows for high-resolution electrochemical analysis without requiring extensive circuitry. We measured the faradaic current of an anti-cocaine aptamer using cyclic voltammetry and square wave voltammetry and demonstrated that KickStat’s response was within 0.6% of a high-end benchtop potentiostat. To further support others in electrochemical biosensors development, we have made KickStat’s design and firmware available in an online GitHub repository.