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Fulltext Real-time driver identification in IoV: A deep learning and cloud integration approach

Gheni HM, AbdulRahaim LA, Abdellatif A

Heliyon, 2024 Apr 15;10(7):e28109.
PMID: 38560228 DOI: 10.1016/j.heliyon.2024.e28109

The Internet of Vehicles (IoV) emerges as a pivotal extension of the Internet of Things (IoT), specifically geared towards transforming the automotive landscape. In this evolving ecosystem, the demand for a seamless end-to-end system becomes paramount for enhancing operational efficiency and safety. Hence, this study introduces an innovative method for real-time driver identification by integrating cloud computing with deep learning. Utilizing the integrated capabilities of Google Cloud, Thingsboard, and Apache Kafka, the developed solution tailored for IoV technology is adept at managing real-time data collection, processing, prediction, and visualization, with resilience against sensor data anomalies. Also, this research suggests an appropriate method for driver identification by utilizing a combination of Convolutional Neural Networks (CNN) and multi-head self-attention in the proposed approach. The proposed model is validated on two datasets: Security and collected. Moreover, the results show that the proposed model surpassed the previous works by achieving an accuracy and F1 score of 99.95%. Even when challenged with data anomalies, this model maintains a high accuracy of 96.2%. By achieving accurate driver identification results, the proposed end-to-end IoV system can aid in optimizing fleet management, vehicle security, personalized driving experiences, insurance, and risk assessment. This emphasizes its potential for road safety and managing transportation more effectively.
Fulltext Mono-Lateral External Fixation for Treatment of Femoral Osteomyelitis

Mohd Yusof N, Saleh AK, Abuomira IEAA, Attallah AA, Elshal EA, Khames AAA

Orthop Res Rev, 2022;14:437-443.
PMID: 36444242 DOI: 10.2147/ORR.S383863

BACKGROUND AND AIM: Maintenance of stability using external fixation devices is an important principle to ensure successful treatment of osteomyelitis (OM). In this study, we report our experience with femoral OM treated with acute compression and bone transport using the Orthofix limb reconstruction system (LRS).
PATIENTS AND METHODS: This prospective study included 30 consecutive patients with femoral OM. LRS insertion and corticotomy were done according to the standard technique. Radiographic evaluation was performed every 2 weeks during the distraction phase and every 2-4 weeks during the consolidation phase. The clinical outcome measurements included union time, limb length discrepancy, additional operative procedures, refracture and infection.
RESULTS: The present study included 30 patients with femoral OM. They comprised 27 males (90.0%) and 3 females (10.0%) with an age of 28.1 ± 15.6 years. All, except one, achieved union with a mean union time of 8.6 months (range 4-20 months). The mean union time for acute compression was 7.6 months (range 4-20 months) while for patients with bone transport it was 14.5 months (range 12-18 months). The mean limb length discrepancy was 1.8 cm (range 0-4 cm). At the end of the follow=up, two patients were not able to ambulate without support; one due to non-union and one due to paraplegia.
CONCLUSION: The present study identified treatment of femoral OM using LRS as a feasible and effective technique with good outcomes. Reported complications could be adequately managed in most cases.
Ilizarov External Fixator Versus Orthofix LRS in Management of Femoral Osteomyelitis: A Propensity Score Matched Analysis

Saleh AK, Yusof NM, Attallah AA, Elshal EA, Khames AAA, Ibrahim MNA, et al.

Indian J Orthop, 2024 Sep;58(9):1272-1277.
PMID: 39170658 DOI: 10.1007/s43465-024-01208-1

PURPOSE: Treatment of osteomyelitis (OM) is challenging. Ilizarov bone transport is a commonly used technique for management of OM. The recently introduced limb reconstruction system (LRS) has been effectively used for management of OM. It was suggested to be easier in use and less invasive. The present retrospective study aimed to compare LRS and Ilizarov bone transport in management of femoral OM using a propensity score matched analysis.
METHODS: The present retrospective study included 80 consecutive patients with femoral OM. The studied patients were managed either using Ilizarov external fixator (n = 40) or Orthofix LRS (n = 40). The clinical outcome measurements included union time, limb length discrepancy, additional operative procedures, refracture and infection.
RESULTS: Patients in the LRS group were exposed to significantly higher frequency of bone transport (30.0 versus 15.0%) and lower frequency of acute compression and lengthening (10.0 versus 32.5%). Patients in Ilizarov group had significantly higher frequency of tobramycin pellets as compared to their counterparts. The studied groups were comparable regarding the operative complications including pin-tract infection, non-union at docking site and refracture. Patients in the Ilizarov had significantly shorter time to union (8.2 ± 3.2 versus 11.0 ± 5.6 months, p = 0.012). No statistically significant differences were found between the studied groups regarding the quality-of-life domains.
CONCLUSIONS: Use of Ilizarov external fixator and Orthofix LRS devices proved to be effective and reliable. Their influences on patients' quality appear to be comparable.
Fulltext Production of Aluminum AA6061 Hybrid Nanocomposite from Waste Metal Using Hot Extrusion Process: Strength Performance and Prediction by RSM and Random Forest

Msebawi MS, Leman Z, Shamsudin S, Tahir SM, Aiza Jaafar CN, Ariff AHM, et al.

Materials (Basel), 2021 Oct 15;14(20).
PMID: 34683694 DOI: 10.3390/ma14206102

To date, various studies have analysed the effects of reinforced ceramic on the properties of AA6061 recycled aluminum alloy chips, such as the tensile strength and fractography. However, a comprehensive analysis of the properties of hybrid composite with the addition of nano-silica oxide and nano-copper oxide reinforcements is still very limited. Therefore, this study aimed to optimise the factors comprising the preheating temperature (PHT), preheating time (PHti), and volume fraction (VF) of reinforcements then determine their impacts on the physical and mechanical properties of the recycled solid-state extruded composite aluminum chips. A total of 45 specimens were fabricated through the hot extrusion technique. The response surface methodology (RSM) was employed to study the optimisation at a PHT range of 450-550 °C with PHti of 1-3 h and VF of 1-3 vol% for both reinforcements (SiO2 and CuO). Moreover, a random forest (RF) model was developed to optimize the model based on a metaheuristic method to improve the model performance. Based on the experimental results the RF model achieve better results than response surface methodology (RSM). The functional quadratic regression is curvature and the tested variable shows stable close data of the mean 0 and α2. Based on the Pareto analysis, the PHT and VF were key variables that significantly affected the UTS, microhardness, and density of the product. The maximum properties were achieved at an optimum PHT, PHti, and VF of 541 °C, 2.25 h, 1 vol% SiO2 and 2.13 vol% CuO, respectively. Furthermore, the morphological results of the tensile fractured surface revealed the homogenous distribution of nano-reinforced CuO and SiO2 particles in the specimens' structure.
Dual therapy of cancer using optimal control supported by swarm intelligence

Tan PL, Kanesan J, Chuah JH, Badruddin IA, Abdellatif A, Kamangar S, et al.

Biomed Mater Eng, 2023 Dec 28.
PMID: 38189746 DOI: 10.3233/BME-230150

BACKGROUND: The scientific revolution in the treatment of many illnesses has been significantly aided by stem cells. This paper presents an optimal control on a mathematical model of chemotherapy and stem cell therapy for cancer treatment.
OBJECTIVE: To develop effective hybrid techniques that combine the optimal control theory (OCT) with the evolutionary algorithm and multi-objective swarm algorithm. The developed technique is aimed to reduce the number of cancerous cells while utilizing the minimum necessary chemotherapy medications and minimizing toxicity to protect patients' health.
METHODS: Two hybrid techniques are proposed in this paper. Both techniques combined OCT with the evolutionary algorithm and multi-objective swarm algorithm which included MOEA/D, MOPSO, SPEA II and PESA II. This study evaluates the performance of two hybrid techniques in terms of reducing cancer cells and drug concentrations, as well as computational time consumption.
RESULTS: In both techniques, MOEA/D emerges as the most effective algorithm due to its superior capability in minimizing tumour size and cancer drug concentration.
CONCLUSION: This study highlights the importance of integrating OCT and evolutionary algorithms as a robust approach for optimizing cancer chemotherapy treatment.