| 1. |
- Bosona, Techane, et al.
(författare)
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The role of blockchain technology in promoting traceability systems in agri-food production and supply chains
- 2023
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Ingår i: Sensors. - 1424-8220 .- 1424-3210. ; 23
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Forskningsöversikt (refereegranskat)abstract
- Due to recurring food quality and safety issues, growing segments of consumers, especially in developed markets, and regulators in agri-food supply chains (AFSCs) require a fast and trustworthy system to retrieve necessary information on their food products. With the existing centralized traceability systems used in AFSCs, it is difficult to acquire full traceability information, and there are risks of information loss and data tampering. To address these challenges, research on the application of blockchain technology (BCT) for traceability systems in the agri-food sector is increasing, and startup companies have emerged in recent years. However, there have been only a limited number of reviews on the application of BCT in the agriculture sector, especially those that focus on the BCT-based traceability of agricultural goods. To bridge this knowledge gap, we reviewed 78 studies that integrated BCT into traceability systems in AFSCs and additional relevant papers, mapping out the main types of food traceability information. The findings indicated that the existing BCT-based traceability systems focus more on fruit and vegetables, meat, dairy, and milk. A BCT-based traceability system enables one to develop and implement a decentralized, immutable, transparent, and reliable system in which process automation facilitates the monitoring of real-time data and decision-making activities. We also mapped out the main traceability information, key information providers, and challenges and benefits of the BCT-based traceability systems in AFSCs. These helped to design, develop, and implement BCT-based traceability systems, which, in turn, will contribute to the transition to smart AFSC systems. This study comprehensively illustrated that implementing BCT-based traceability systems also has important, positive implications for improving AFSC management, e.g., reductions in food loss and food recall incidents and the achievement of the United Nations SDGs (1, 3, 5, 9, 12). This will contribute to existing knowledge and be useful for academicians, managers, and practitioners in AFSCs, as well as policymakers.
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| 2. |
- Mcmurray, S., et al.
(författare)
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A Study on ML-Based Software Defect Detection for Security Traceability in Smart Healthcare Applications
- 2023
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Ingår i: Sensors. - : MDPI. - 1424-8220 .- 1424-3210. ; 23:7
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Tidskriftsartikel (refereegranskat)abstract
- Software Defect Prediction (SDP) is an integral aspect of the Software Development Life-Cycle (SDLC). As the prevalence of software systems increases and becomes more integrated into our daily lives, so the complexity of these systems increases the risks of widespread defects. With reliance on these systems increasing, the ability to accurately identify a defective model using Machine Learning (ML) has been overlooked and less addressed. Thus, this article contributes an investigation of various ML techniques for SDP. An investigation, comparative analysis and recommendation of appropriate Feature Extraction (FE) techniques, Principal Component Analysis (PCA), Partial Least Squares Regression (PLS), Feature Selection (FS) techniques, Fisher score, Recursive Feature Elimination (RFE), and Elastic Net are presented. Validation of the following techniques, both separately and in combination with ML algorithms, is performed: Support Vector Machine (SVM), Logistic Regression (LR), Naïve Bayes (NB), K-Nearest Neighbour (KNN), Multilayer Perceptron (MLP), Decision Tree (DT), and ensemble learning methods Bootstrap Aggregation (Bagging), Adaptive Boosting (AdaBoost), Extreme Gradient Boosting (XGBoost), Random Forest(RF), and Generalized Stacking (Stacking). Extensive experimental setup was built and the results of the experiments revealed that FE and FS can both positively and negatively affect performance over the base model or Baseline. PLS, both separately and in combination with FS techniques, provides impressive, and the most consistent, improvements, while PCA, in combination with Elastic-Net, shows acceptable improvement.
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| 3. |
- Gautam, Sumit, et al.
(författare)
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Hybrid Active-and-Passive Relaying Model for 6G-IoT Greencom Networks with SWIPT
- 2021
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Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 21:18
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Tidskriftsartikel (refereegranskat)abstract
- In order to support a massive number of resource-constrained Internet-of-Things (IoT) devices and machine-type devices, it is crucial to design a future beyond 5G/6G wireless networks in an energy-efficient manner while incorporating suitable network coverage expansion methodologies. To this end, this paper proposes a novel two-hop hybrid active-and-passive relaying scheme to facilitate simultaneous wireless information and power transfer (SWIPT) considering both time-switching (TS) and power-splitting (PS) receiver architectures, while dynamically modelling the involved dual-hop time-period (TP) metric. An optimization problem is formulated to jointly optimize the throughput, harvested energy, and transmit power of a SWIPT-enabled system with the proposed hybrid scheme. In this regard, we provide two distinct ways to obtain suitable solutions based on the Lagrange dual technique and Dinkelbach method assisted convex programming, respectively, where both the approaches yield an appreciable solution within polynomial computational time. The experimental results are obtained by directly solving the primal problem using a non-linear optimizer. Our numerical results in terms of weighted utility function show the superior performance of the proposed hybrid scheme over passive repeater-only and active relay-only schemes, while also depicting their individual performance benefits over the corresponding benchmark SWIPT systems with the fixed-TP.
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| 4. |
- Kristoffersson, Annica, 1980-, et al.
(författare)
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A Systematic Review on the Use of Wearable Body Sensors for Health Monitoring : A Qualitative Synthesis
- 2020
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Ingår i: Sensors. - Basel, Switzerland : MDPI AG. - 1424-8220. ; 20:5
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Forskningsöversikt (refereegranskat)abstract
- The use of wearable body sensors for health monitoring is a quickly growing field with the potential of offering a reliable means for clinical and remote health management. This includes both real-time monitoring and health trend monitoring with the aim to detect/predict health deterioration and also to act as a prevention tool. The aim of this systematic review was to provide a qualitative synthesis of studies using wearable body sensors for health monitoring. The synthesis and analysis have pointed out a number of shortcomings in prior research. Major shortcomings are demonstrated by the majority of the studies adopting an observational research design, too small sample sizes, poorly presented, and/or non-representative participant demographics (i.e., age, gender, patient/healthy). These aspects need to be considered in future research work.
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| 5. |
- Kristoffersson, Annica, 1980-, et al.
(författare)
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Performance and Characteristics of Wearable Sensor Systems Discriminating and Classifying Older Adults According to Fall Risk: A Systematic Review
- 2021
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Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 21:17
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Forskningsöversikt (refereegranskat)abstract
- Sensor-based fall risk assessment (SFRA) utilizes wearable sensors for monitoring individuals’ motions in fall risk assessment tasks. Previous SFRA reviews recommend methodological improvements to better support the use of SFRA in clinical practice. This systematic review aimed to investigate the existing evidence of SFRA (discriminative capability, classification performance) and methodological factors (study design, samples, sensor features, and model validation) contributing to the risk of bias. The review was conducted according to recommended guidelines and 33 of 389 screened records were eligible for inclusion. Evidence of SFRA was identified: several sensor features and three classification models differed significantly between groups with different fall risk (mostly fallers/non-fallers). Moreover, classification performance corresponding the AUCs of at least 0.74 and/or accuracies of at least 84% were obtained from sensor features in six studies and from classification models in seven studies. Specificity was at least as high as sensitivity among studies reporting both values. Insufficient use of prospective design, small sample size, low in-sample inclusion of participants with elevated fall risk, high amounts and low degree of consensus in used features, and limited use of recommended model validation methods were identified in the included studies. Hence, future SFRA research should further reduce risk of bias by continuously improving methodology.
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| 6. |
- Xu, Ye, et al.
(författare)
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System Implementation Trade-Offs for Low-Speed Rotational Variable Reluctance Energy Harvesters
- 2021
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Ingår i: Sensors. - Basel, Switzerland : MDPI. - 1424-8220. ; 21:18
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Tidskriftsartikel (refereegranskat)abstract
- Low-power energy harvesting has been demonstrated as a feasible alternative for the power supply of next-generation smart sensors and IoT end devices. In many cases, the output of kinetic energy harvesters is an alternating current (AC) requiring rectification in order to supply the electronic load. The rectifier design and selection can have a considerable influence on the energy harvesting system performance in terms of extracted output power and conversion losses. This paper presents a quantitative comparison of three passive rectifiers in a low-power, low-voltage electromagnetic energy harvesting sub-system, namely the full-wave bridge rectifier (FWR), the voltage doubler (VD), and the negative voltage converter rectifier (NVC). Based on a variable reluctance energy harvesting system, we investigate each of the rectifiers with respect to their performance and their effect on the overall energy extraction. We conduct experiments under the conditions of a low-speed rotational energy harvesting application with rotational speeds of 5rpm–20rpm, and verify the experiments in an end-to-end energy harvesting evaluation. Two performance metrics—power conversion efficiency (PCE) and power extraction efficiency (PEE)—are obtained from the measurements to evaluate the performance of the system implementation adopting each of the rectifiers. The results show that the FWR with PEEs of 20 % at 5 rpm to 40 % at 20 rpm has a low performance in comparison to the VD (40–60 %) and NVC (20–70 %) rectifiers. The VD-based interface circuit demonstrates the best performance under low rotational speeds, whereas the NVC outperforms the VD at higher speeds (>18 rpm). Finally, the end-to-end system evaluation is conducted with a self-powered rpm sensing system, which demonstrates an improved performance with the VD rectifier implementation reaching the system’s maximum sampling rate (40 Hz) at a rotational speed of approximately 15.5 rpm.
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| 7. |
- Gautam, Sumit, et al.
(författare)
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Boosting Quantum Battery-Based IoT Gadgets via RF-Enabled Energy Harvesting
- 2022
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Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 22:14
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Tidskriftsartikel (refereegranskat)abstract
- The search for a highly portable and efficient supply of energy to run small-scale wireless gadgets has captivated the human race for the past few years. As a part of this quest, the idea of realizing a Quantum battery (QB) seems promising. Like any other practically tractable system, the design of QBs also involve several critical challenges. The main problem in this context is to ensure a lossless environment pertaining to the closed-system design of the QB, which is extremely difficult to realize in practice. Herein, we model and optimize various aspects of a Radio-Frequency (RF) Energy Harvesting (EH)-assisted, QB-enabled Internet-of-Things (IoT) system. Several RF-EH modules (in the form of micro- or nano-meter-sized integrated circuits (ICs)) are placed in parallel at the IoT receiver device, and the overall correspondingly harvested energy helps the involved Quantum sources achieve the so-called quasi-stable state. Concretely, the Quantum sources absorb the energy of photons that are emitted by a photon-emitting device controlled by a micro-controller, which also manages the overall harvested energy from the RF-EH ICs. To investigate the considered framework, we first minimize the total transmit power under the constraints on overall harvested energy and the number of RF-EH ICs at the QB-enabled wireless IoT device. Next, we optimize the number of RF-EH ICs, subject to the constraints on total transmit power and overall harvested energy. Correspondingly, we obtain suitable analytical solutions to the above-mentioned problems, respectively, and also cross-validate them using a non-linear program solver. The effectiveness of the proposed technique is reported in the form of numerical results, which are both theoretical and simulations based, by taking a range of operating system parameters into account.
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| 8. |
- Sjölander, Andreas, Ph.D, 1983-, et al.
(författare)
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Towards Automated Inspections of Tunnels: A Review of Optical Inspections and Autonomous Assessment of Concrete Tunnel Linings
- 2023
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Ingår i: Sensors. - : MDPI. - 1424-8220. ; 23:6, s. 3189-3189
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Tidskriftsartikel (refereegranskat)abstract
- In recent decades, many cities have become densely populated due to increased urbanization, and the transportation infrastructure system has been heavily used. The downtime of important parts of the infrastructure, such as tunnels and bridges, seriously affects the transportation system’s efficiency. For this reason, a safe and reliable infrastructure network is necessary for the economic growth and functionality of cities. At the same time, the infrastructure is ageing in many countries, and continuous inspection and maintenance are necessary. Nowadays, detailed inspections of large infrastructure are almost exclusively performed by inspectors on site, which is both time-consuming and subject to human errors. However, the recent technological advancements in computer vision, artificial intelligence (AI), and robotics have opened up the possibilities of automated inspections. Today, semiautomatic systems such as drones and other mobile mapping systems are available to collect data and reconstruct 3D digital models of infrastructure. This significantly decreases the downtime of the infrastructure, but both damage detection and assessments of the structural condition are still manually performed, with a high impact on the efficiency and accuracy of the procedure. Ongoing research has shown that deep-learning methods, especially convolutional neural networks (CNNs) combined with other image processing techniques, can automatically detect cracks on concrete surfaces and measure their metrics (e.g., length and width). However, these techniques are still under investigation. Additionally, to use these data for automatically assessing the structure, a clear link between the metrics of the cracks and the structural condition must be established. This paper presents a review of the damage of tunnel concrete lining that is detectable with optical instruments. Thereafter, state-of-the-art autonomous tunnel inspection methods are presented with a focus on innovative mobile mapping systems for optimizing data collection. Finally, the paper presents an in-depth review of how the risk associated with cracks is assessed today in concrete tunnel lining.
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| 9. |
- Abafogi, Abdurhaman Teyib, et al.
(författare)
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3D-Printed Modular Microfluidic Device Enabling Preconcentrating Bacteria and Purifying Bacterial DNA in Blood for Improving the Sensitivity of Molecular Diagnostics
- 2020
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Ingår i: Sensors. - : MDPI. - 1424-8220. ; 20:4
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Tidskriftsartikel (refereegranskat)abstract
- Molecular diagnostics for sepsis is still a challenge due to the presence of compounds that interfere with gene amplification and bacteria at concentrations lower than the limit of detection (LOD). Here, we report on the development of a 3D printed modular microfluidic device (3Dpm mu FD) that preconcentrates bacteria of interest in whole blood and purifies their genomic DNA (gDNA). It is composed of a W-shaped microchannel and a conical microchamber. Bacteria of interest are magnetically captured from blood in the device with antibody conjugated magnetic nanoparticles (Ab-MNPs) at 5 mL/min in the W-shaped microchannel, while purified gDNA of the preconcentrated bacteria is obtained with magnetic silica beads (MSBs) at 2 mL/min in the conical microchamber. The conical microchamber was designed to be connected to the microchannel after the capturing process using a 3D-printed rotary valve to minimize the exposure of the MSBs to interfering compounds in blood. The pretreatment process of spiked blood (2.5 mL) can be effectively completed within about 50 min. With the 3Dpm mu FD, the LOD for the target microorganism Escherichia coli O157:H7 measured by both polymerase chain reaction (PCR) with electrophoresis and quantitative PCR was 10 colony forming unit (CFU) per mL of whole blood. The results suggest that our method lowers the LOD of molecular diagnostics for pathogens in blood by providing bacterial gDNA at high purity and concentration.
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| 10. |
- Abbas, Zaheer, et al.
(författare)
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In Situ Growth of CuWO4 Nanospheres over Graphene Oxide for Photoelectrochemical (PEC) Immunosensing of Clinical Biomarker
- 2020
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Ingår i: Sensors. - : MDPI. - 1424-8220. ; 20:1
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Tidskriftsartikel (refereegranskat)abstract
- Procalcitonin (PCT) protein has recently been identified as a clinical marker for bacterial infections based on its better sepsis sensitivity. Thus, an increased level of PCT could be linked with disease diagnosis and therapeutics. In this study, we describe the construction of the photoelectrochemical (PEC) PCT immunosensing platform based on it situ grown photo-active CuWO4 nanospheres over reduced graphene oxide layers (CuWO4@rGO). The in situ growth strategy enabled the formation of small nanospheres (diameter of 200 nm), primarily composed of tiny self-assembled CuWO4 nanoparticles (2-5 nm). The synergic coupling of CuWO4 with rGO layers constructed an excellent photo-active heterojunction for photoelectrochemical (PEC) sensing. The platform was then considered for electrocatalytic (EC) mechanism-based detection of PCT, where inhibition of the photocatalytic oxidation signal of ascorbic acid (AA), subsequent to the antibody-antigen interaction, was recorded as the primary signal response. This inhibition detection approach enabled sensitive detection of PCT in a concentration range of 10 pgmL(-1) to 50 ng.mL(-1) with signal sensitivity achievable up to 0.15 pgmL(-1). The proposed PEC hybrid (CuWO4@rGO) could further be engineered to detect other clinically important species.
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