6G Network Architecture Using FSO-PDM/PV-OCDMA System with Weather Performance Analysis

This paper presents a novel 160 Gbps free space optics (FSO) communication system for 6G applications. Polarization division multiplexing (PDM) is integrated with an optical code division multiple access (OCDMA) technique to form a PDM-OCDMA hybrid. There are two polarization states: one is X-polarization generated from adjusting the azimuthal angle of a light source at 0° while the other is Y-polarization which is generated by adjusting the azimuthal angle of a light source at 90°. Each polarization state is used for the transmission of four independent users. Each channel is assigned by permutation vector (PV) codes and carries 20 Gbps data. Four different weather conditions are considered for evaluating the performance of our proposed model. These weather conditions are clear air (CA), foggy conditions (low fog (LF), medium fog (MF), and heavy fog (HF)), dust storms (low dust storm (LD), moderate dust storm (MD), heavy dust storm (HD)), and snowfall (wet snow (WS) and dry snow (DS)). Bit error rate (BER), Q-factors, maximum propagation range, channel capacity, and eye diagrams are used for evaluating the performance of the proposed model. Simulation results assure successful transmission of 160 Gbps overall capacity for eight channels. The longest FSO range is 7 km which occurred under CA while the minimum is achieved under HD, which is 0.112 km due to large attenuation caused by HD. Within fog conditions, the maximum propagation distances are 1.525 km in LF, 1.05 km in MF, and 0.85 km in HF. Likewise, under WS and DS, the proposed system can support transmission distances of 1.15 km and 0.28 km, respectively. All these transmission distances are achieved at BER less than 10−5

Crops leaf diseases recognition: a framework of optimum deep learning features

Manual diagnosis of crops diseases is not an easy process; thus, a computerized method is widely used. From a couple of years, advancements in the domain of machine learning, such as deep learning, have shown substantial success. However, they still faced some challenges such as similarity in disease symptoms and irrelevant features extraction. In this article, we proposed a new deep learning architecture with optimization algorithm for cucumber and potato leaf diseases recognition. The proposed architecture consists of five steps. In the first step, data augmentation is performed to increase the numbers of training samples. In the second step, pre-trained DarkNet19 deep model is opted and fine-tuned that later utilized for the training of fine-tuned model through transfer learning. Deep features are extracted from the global pooling layer in the next step that is refined using Improved Cuckoo search algorithm. The best selected features are finally classified using machine learning classifiers such as SVM, and named a few more for final classification results. The proposed architecture is tested using publicly available datasets–Cucumber National Dataset and Plant Village. The proposed architecture achieved an accuracy of 100.0%, 92.9%, and 99.2%, respectively. A comparison with recent techniques is also performed, revealing that the proposed method achieved improved accuracy while consuming less computational time

Metasurface-Inspired Flexible Wearable MIMO Antenna Array for Wireless Body Area Network Applications and Biomedical Telemetry Devices

This article presents a sub-6GHz ISM-band flexible wearable MIMO antenna array for wireless body area networks (WBANs) and biomedical telemetry devices. The array is based on metasurface inspired technology. The antenna array consists of 2×2 matrix of triangular-shaped radiation elements that were realized on 0.8 mm thick Rogers RT/duroid 5880 substrate. Radiation characteristics of the array are enhanced by isolating the surface current interaction between the individual radiators in the array. This is achieved by inserting an electromagnetic bandgap (EBG) decoupling structure between the radiating elements. The radiating elements were transformed into a metasurface by etching sub-wavelength slots inside them. The periodic arrangement of slots acts like resonant scatterers that manipulate the electromagnetic response of the surface. Results confirm that by employing the decoupling structure and sub-wavelength slots the isolation between the radiators is significantly improved (>34.8 dB). Moreover, there is an improvement in the array’s fractional bandwidth, gain and the radiation efficiency. The optimized array design for operation over 5.0-6.6 GHz has an average gain and efficiency of 10 dBi and 83%, respectively. Results show that the array’s performance is not greatly affected by a certain amount of bending. In fact, the antenna maintains a gain between 8.65-10.5 dBi and the efficiency between 77-83%. The proposed MIMO antenna array is relatively compact, can be easily fabricated on one side of a dielectric material, allows easy integration with RF circuitry, is robust, and maintains its characteristics with some bending. These features make it suitable for various wearable applications and biomedical telemetry devices

Pilot implementation of elder-friendly care practices in acute care setting: a mixed methods study

Abstract Background Frail older patients are at risk of experiencing a decline in physical and cognitive function unrelated to the reason for admission. The Elder-Friendly Care (EFC) program was designed to improve the care, experiences, and outcomes of frail older adults. The project supported 8 Early Adoption Sites (EAS) in a large Canadian healthcare organization by providing multiple strategies, educational opportunities, and resources. The purpose of this study was to assess the usefulness of EFC educational materials and resources, staff practice changes and perceptions in pilot sites, and readiness for scale and spread. Methods The study was conducted from May 2017 to June 2018 using a mixed-methods approach incorporating the Kirkpatrick Model of Training/Evaluation. A total of 76 Direct Care Staff participated in the staff survey, which assessed their awareness of, satisfaction with, and utilization of EFC principles, resources, and practices. Additionally, 12 interviews were conducted with staff who were directly involved in site implementation of EFC. Results Most survey participants were aware (86%, n = 63) of the EFC program, and 85% (n = 41) indicated they or their site/unit had implemented EFC. Out of these 41 participants, the most common practice changes identified were: incorporating alternatives to restraint (81%, n = 33), decreased use of pharmacological restraint (78%, n = 32), and patient and family care planning (76%, n = 31). Participants that attended all 3 EFC Learning Workshops (LWs) were significantly more likely to recommend the EFC Toolkit to others (87% versus 40%; χ2 = 8.82, p < 0.01) compared to participants attending less than 3 EFC LWs. Interview participants indicated that the program was well structured and flexible as sites/units could adopt changes that suited their individual sites, needs, contexts, and challenges. Conclusions The educational materials and resources used for the EFC project are useful and appreciated by the Direct Care Staff. Further, participants perceive the EFC intervention as effective in creating positive practice change and useful in reducing hospital-related complications for older patients. Future implementation will investigate the impact of EFC on system-level outcomes in acute care

Response score-based protein structure analysis for cancer prediction aided by the Internet of Things

Abstract Medical diagnosis through prediction and analysis is par excellence in integrating modern technologies such as the Internet of Things (IoT). With the aid of such technologies, clinical assessments are eased with protracted computing. Specifically, cancer research through structure prediction and analysis is improved through human and machine interventions sustaining precision improvements. This article, therefore, introduces a Protein Structure Prediction Technique based on Three-Dimensional Sequence. This sequence is modeled using amino acids and their folds observed during the pre-initial cancer stages. The observed sequences and the inflammatory response score of the structure are used to predict the impact of cancer. In this process, ensemble learning is used to identify sequence and folding responses to improve inflammations. This score is correlated with the clinical data for structures and their folds independently for determining the structure changes. Such changes through different sequences are handled using repeated ensemble learning for matching and unmatching response scores. The introduced idea integrated with deep ensemble learning and IoT combination, notably employing stacking method for enhanced cancer prediction precision and interdisciplinary collaboration. The proposed technique improves prediction precision, data correlation, and change detection by 11.83%, 8.48%, and 13.23%, respectively. This technique reduces correlation time and complexity by 10.43% and 12.33%, respectively

Medication adherence support of an in-home electronic medication dispensing system for individuals living with chronic conditions: a pilot randomized controlled trial

Abstract Background Medication adherence is challenging for older adults due to factors such as the number of medications, dosing schedule, and the duration of drug therapy. The objective of this study was to examine the effectiveness of an in-home electronic medication dispensing system (MDS) on improving medication adherence and health perception in older adults with chronic conditions. Methods A pilot Randomized Controlled Trial (RCT) was conducted using a two-arm parallel assignment model. The intervention group used an MDS as their medication management method. The control group continued to use their current methods of medication management. Block randomization was used to assign participants into the intervention or control group. The inclusion criteria included 1) English speaking 2) age 50 and over 3) diagnosed with one or more chronic condition(s) 4) currently taking five or more oral medications 5) City of Calgary resident. Participants were recruited from a primary care clinic in Alberta, Canada. The study was open-label where knowledge about group assigned to participants after randomization was not withheld. Medication adherence was captured over a continuous, six-month period and analyzed using Intention-to-Treat (ITT) analysis. Results A total of 91 participants were assessed for eligibility and 50 were randomized into the two groups. The number of participants analyzed for ITT was 23 and 25 in the intervention and control group, respectively. Most of the demographic characteristics were comparable in the two groups except the mean age of the intervention group, which was higher compared to the control group (63.96 ± 7.86 versus 59.52 ± 5.93, p-value = 0.03). The average recorded adherence over 26 weeks was significantly higher in the intervention group than the control group (98.35% ± 2.15% versus 91.17% ± 9.76%, p < 0.01). The self-rated medication adherence in the intervention group also showed a significant increase from baseline to 6-month (Z=-2.65, p < 0.01). The control group showed a non-significant increase (Z=-1.79, p = 0.07). Conclusion The MDS can be an effective, long-term solution to medication non-adherence in older adults experiencing chronic conditions and taking multiple medications. The technology induces better consistency and improvement in medication taking behaviour than simple, non-technological intervention. Trial registration Registered with ClinicalTrials.gov on April 09, 2020 with identifier NCT04339296

Design and Fabrication of Compact, Multiband, High Gain, High Isolation, Metamaterial-Based MIMO Antennas for Wireless Communication Systems

We proposed a novel approach based on a complementary split-ring resonator metamaterial in a two-port MIMO antenna, giving high gain, multiband results with miniature size. We have also analyzed a circular disk metasurface design. The designs are also defected using ground structure by reducing the width of the ground plane to 8 mm and etching all other parts of the ground plane. The electric length of the proposed design is 0.5&lambda; &times; 0.35&lambda; &times; 0.02&lambda;. The design results are also investigated for a different variation of complementary split-ring resonator ring sizes. The inner and outer ring diameters are varied to find the optimized solution for enhanced output performance parameters. Good isolation is also achieved for both bands. The gain and directivity results are also presented. The results are compared for isolation, gain, structure size, and the number of ports. The compact, multiband, high gain and high isolation design can apply to WiMAX, WLAN, and satellite communication applications