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As the physical size of a communication system for satellites or unmanned aerial vehicles demands to be reduced, a compact antenna with high directivity is proposed as a core element essential to the wireless device. Instead of using a horn or an array antenna, a unit planar antenna is combined with a surface-modulated lens to convert a low antenna gain to a high antenna gain. The lens is not a metal-patterned PCB but is dielectric, which is neither curved nor very wide. This palm-sized lens comprises pixels with different heights from the backside of PolyPhenylene Sulfide (PPS) as the dielectric base. The antenna gain from the unit antenna of 4.5 cm × 4.5 cm is enhanced by 10 dB with the help of a compact dielectric lens of 7.5 cm × 7.5 cm at 24.5 GHz as the frequency of interest. The antenna design is verified by far-field measurement as well as near-field observation, including sensing a metal object behind a blocking wall by using an RF test bench. Moreover, antenna performance is understood by making a comparison with conventional designs of antennas in terms of directivity and physical sizes. [ABSTRACT FROM AUTHOR]

In order to solve the problem of accurate and low-cost location of substation personnel in digital cities, a substation personnel location system based on wireless sensor cloud computing network is proposed. ZigBee wireless sensor cloud computing network is introduced into the substation to improve the direct location algorithm of substation personnel, and a fuzzy reasoning algorithm is proposed. The algorithm takes the signal strength received by each reference node and the relative distance between the reference nodes as input. After fuzzy, fuzzy reasoning and deblurring, the reliability of the received signal strength of each reference node is obtained, and then three reference nodes with high reliability are selected for trilateral positioning calculation. The experimental results show that the positioning error after improvement is more stable than that before improvement, and the maximum error before improvement is 1.4115m. Practice has proved that the algorithm can significantly improve the positioning accuracy of substation personnel without adding any hardware and using fewer nodes. [ABSTRACT FROM AUTHOR]

• This study analyzes Yasmin-related adverse events (AEs) using FAERS database data from 2004 to 2023. • Hepatobiliary, vascular, and psychiatric disorders were the top reported AEs for Yasmin users. • Novel adverse reactions like fear of disease and acute cor pulmonale identified with high signal strength. • Results emphasize the need for cautious prescribing and patient awareness of potential AEs with Yasmin. This study aimed to elucidate the scope and nature of adverse events (AEs) associated with Yasmin. Among the 17,035,572 AE reports collected from the Food and Drug Administration Adverse Event Reporting System (FAERS) database between January 2004 and September 2023, 25,949 reports involved Yasmin. The demographic details, clinical outcomes, and sources of reports were extracted, and four algorithms were used to evaluate adverse drug reactions. The majority of the AE reports involved females aged 18–45 years. Hospitalization was the most frequently reported serious outcome (46.84 %), with death occurring in 292 patients (1.82 %). The highest number of reports originated from the United States. Adverse reactions spanned across 24 system organ categories (SOCs), and hepatobiliary, vascular, and psychiatric disorders were the most frequently reported AEs. A total of 229 Preferred Terms (PTs) were identified for adverse reactions, with high signal strength observed for conditions such as post-cholecystectomy syndrome. In addition, fear of disease, which has not been previously identified as an AE related to Yasmin, was also identified as a high signal strength side effect. The findings of the present study underscore the importance of monitoring and identifying potential AEs in patients receiving Yasmin, including those not currently listed in the medication instructions. [ABSTRACT FROM AUTHOR]

In this study, we aim to implement an intelligent automatic notification system based on Bluetooth beacons and smartphones to prevent accidents caused by children being left in vehicles while commuting to school during summer or winter. This is a problem that is emerging as safety accidents occur owing to negligence in vehicles. Although teachers solutions, such as checking children’s attendance, safety accidents occur freq uently every year. Because the continuous occurrence of safety accidents, parents’ anxiety about accidents is increasing, and various accident prevention measures are being developed to solve this problem. However, these methods are difficult to implement as teachers have to manage a large number of children. To solve this problem, this study implements an intelligent automatic notification system based on Bluetooth beacons and smartphones. This notification system attaches a relatively low-power Bluetooth beacon to the child’s belongings to recognize boarding and disembarking using the teacher’s smartphone, and sends a message to the parent’s smartphone. [ABSTRACT FROM AUTHOR]

Purpose: The call for supply chain transparency (SCT), especially the environmental, social and governance (ESG) aspect, is getting increasingly louder. Based on the signaling theory, our study investigates the operational benefit of supply chain transparency in terms of ESG (SCT-ESG). To further clarify the signaling process, the moderating roles of digitalization of the firm and signal strength are also examined. Design/methodology/approach: Longitudinal secondary data from multiple databases are matched and analyzed using ordinary least squares (OLS) regressions to validate the proposed hypotheses. Findings: Results suggest that with SCT-ESG, firms have a weakened disparity between production variance and demand variance, and the supply chain experiences a reduced bullwhip effect. Further, digitalization of the focal company and signal strength reinforce the negative effect of SCT-ESG on the bullwhip effect. Originality/value: The study integrates the SCT and ESG literature through SCT-ESG, extending benefits of ESG disclosure to the supply chain context. It extends the application of the signaling theory in OSCM by including contextual factors of digitalization and signal strength. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

An array antenna for millimeter-wave communication and an array antenna for millimeter-wave sensing are designed and put together into one structure. Because millimeter-wave signals become weaker fast with the increasing distance and any kind of error in the required functions of the antenna has to be minimized, pointing error from the target direction should be prevented. The device is a millimeter-wave sensing antenna with high directivity to check the straight link between the TX and RX sides of wireless communication. A 24 GHz 8-by-16 array antenna which generates stronger signals for sensing resolves the drawback of a 28 GHz 1-by-4 array antenna that is commonly seen in 5G wireless terminals. The sensing and communication antennas are integrated as a planar structure mountable on platforms, which is investigated with regard to forming wireless links over a distance of several meters with an input power of less than 0 dBm. Additionally, in the event of a reflecting surface disturbing the straight path and worsening the pointing error in RF signal transfer, the dual-capability of the combination is presented on the basis of intuitive electromagnetic experiments. [ABSTRACT FROM AUTHOR]

Localization of WSN sensor nodes gains significance in order to grasp the idea for dead node replacement and re-establishing the network from data loss. In this research, the node localization and the position estimation of the dead nodes during routing are more effectively identified by the Felis bee localization protocol. The node localization is significant for effective communication and data transfer throughout the network with high signal strength. The developed approach assists in identifying the dead nodes and replaces them with less localization error thus, the signal strength of the receiver side is maximum. By utilizing the information on the exact position of the anchor nodes, the unknown location of the dead nodes is estimated by the Felis bee localization protocol. The Felis bee localization protocol enhances the potential of node localization concerning the energy, localization error, and multi-objective function, and attains the minimum RMSE as 0.566 at the 25th round, maximum RSSI as −47.925 dBm as well as the Energy at round 25 as 0.6517 J and the Throughput as 0.2952bps over the simulation area of 10 × 100. Further the established localization reaches the minimum RMSE as 0.673, the maximum Energy as 0.5141 J, maximum throughput as 0.5682,and the maximum RSSI as −53.911 dBm, at the 50th round over simulation area 200 × 200 and surpasses other conventional localization techniques. [ABSTRACT FROM AUTHOR]

Industrial Internet of Things (IIoT) has become an indispensable element of smart industrial facilities, predicted to continue to grow at a rapid rate. Wireless technologies have become a standard part of today’s industrial facilities with applications including programming and control of electric drives, remote system and environment monitoring and fault diagnostics of industrial equipment. However, installation of physical connections can be time consuming and require substantial economic resources, especially when considering long-term maintenance costs. With that regard, IoT applications that use sensor technology, RFID technology, network communication, data mining and machine learning could prove to be quite efficient in solving the previously presented problem of localization. A new indoor localization algorithm has been introduced based on recurring neural networks (RNNs) for the positioning of indoor devices. Experiments were conducted in relatively complex surroundings of a faculty building. According to experimental results, the presented system surpasses the state-of-the-art algorithms and can achieve 98.6% localization accuracy of indoor devices.

GNSS/INS-based positioning must be revised for forest mapping, especially inside the forest. This study deals with the issue of the processability of GNSS/INS-positioned MLS data collected in the forest environment. GNSS time-based point clustering processed the misaligned MLS point clouds collected from skid trails under a forest canopy. The points of a point cloud with two misaligned copies of the forest scene were manually clustered iteratively until two partial point clouds with the single forest scene were generated using a histogram of GNSS time. The histogram's optimal bin width was the maximum bin width used to create the two correct point clouds. The influence of GNSS outage durations, signal strength statistics, and point cloud parameters on the optimal bin width were then analyzed using correlation and regression analyses. The results showed no significant influence of GNSS outage duration or GNSS signal strength from the time range of scanning the two copies of the forest scene on the optimal width. The optimal bin width was strongly related to the point distribution in time, especially by the duration of the scanned plot's occlusion from reviewing when the maximum occlusion period influenced the optimal bin width the most (R2 = 0.913). Thus, occlusion of the sub-plot scanning of tree trunks and the terrain outside it improved the processability of the MLS data. Therefore, higher stem density of a forest stand is an advantage in mapping as it increases the duration of the occlusions for a point cloud after it is spatially tiled. [ABSTRACT FROM AUTHOR]

As a simple and inexpensive channel characteristic, received signal strength (RSS) finds extensive usage in localization applications. However, the quick changes in signal strength impact the localization precision. By averaging over access points (APs) with multiple frequencies and/or heights, this article suggests a novel approach to lowering RSS fluctuation. Initially focused on the plane-earth loss model, the study was later extended to include a multipath indoor propagation scenario that was simulated. We used ray-tracing software to model the indoor propagation situation. This research takes into account the results of three distinct methods for averaging RSS: height averaging, frequency averaging, and hybrid frequency and height (FH) averaging, which combines the two. We discovered that the Height-only strategy considerably decreased the RSS variation with distance for both settings we looked at. Using the frequency-only method even further reduced the variation. Using the Hybrid FH technique greatly enhances the results. Root mean square error values of 4.427 dB, 3.70 dB, and 3.5 dB, respectively, are provided for the averaging approaches and the ideal scenario in which no variance occurs. Another finding is that averaging with APs that have double the height or frequency will not improve the RSS distance variation. [ABSTRACT FROM AUTHOR]

The acoustic emission (AE) monitoring of failures, fractures and instabilities evolving within a snowpack may provide vital information about the avalanche formation preceding release processes. In this work, AE activity was collected continuously over five years from the snowpack built on avalanche starting zone in Great Himalaya, and the analyses are presented in the context of an avalanche release and two slab fracturing events detected successfully during this study period. For non-invasive detection of AE activity from snow, a specialised sensor-arrestor array was deployed over the avalanche slope. In our investigations, an abnormal AE activity was observed both during the slab fracturing as well as the avalanche occurrence periods. For AE-based direct assessment of snow instability, a method is proposed to estimate instability index (βin), based on AE count and amplitude values of a hit, and it is applied for analyses of avalanche formation preceding release and slab fracturing cases. The prominent AE attributes including βin-variations are also analysed at appropriate window scales for a smooth representation of the ongoing instability and failure processes underneath the slab. The AE spectral analyses of avalanche release and slab fracturing reveal the dominant frequencies around 45–47 kHz and 34–43 kHz, respectively. A progressively increasing behaviour was observed with an abrupt increase in the relevant AE parameters and also the βin-values, nearly 13 hours before the avalanche release, and it continued until the avalanche released which can be associated to the instability development prior to avalanche release. [ABSTRACT FROM AUTHOR]

Industrial Internet of Things (IIoT) has become an indispensable element of smart industrial facilities, predicted to continue to grow at a rapid rate. Wireless technologies have become a standard part of today’s industrial facilities with applications including programming and control of electric drives, remote system and environment monitoring and fault diagnostics of industrial equipment. However, installation of physical connections can be time consuming and require substantial economic resources, especially when considering long-term maintenance costs. With that regard, IoT applications that use sensor technology, RFID technology, network communication, data mining and machine learning could prove to be quite efficient in solving the previously presented problem of localization. A new indoor localization algorithm has been introduced based on recurring neural networks (RNNs) for the positioning of indoor devices. Experiments were conducted in relatively complex surroundings of a faculty building. According to experimental results, the presented system surpasses the state-of-the-art algorithms and can achieve 98.6% localization accuracy of indoor devices. [ABSTRACT FROM AUTHOR]

As a key sensor, radar plays an important role in obtaining war information. However, radar will be affected by the deteriorating electromagnetic environment on the battlefield. Therefore, it is necessary to carry out electromagnetic interference effect experiments to improve the anti-interference ability. In the electromagnetic interference experiment of the radar TR component, the signal output from the signal generator passes through the power amplifier, the transmitting antenna and the receiving antenna, and then is applied to the TR component. In the experiment, to obtain a certain size of interference signal acting on the TR component, it is often necessary to manually adjust the output signal strength of the signal generator repeatedly through human experience. The experimental process is complicated, and the experimental error is large. Therefore, it will make the experiment more convenient and accurate to achieve the desired interference signal size on the TR component by accurately predicting the output signal strength value of the signal generator, which has important practical significance. This paper proposes an IGWO-SVR based signal generator output signal strength prediction model, which includes Improved Grey Wolf Optimizer (IGWO) and Support Vector Regression (SVR) algorithms. IGWO is a new swarm optimization algorithm proposed in this paper. By improving the convergence factor a and the final position of $\omega $ wolf, IGWO solves the problems that the traditional GWO algorithm easily falls into local optimum and the convergence speed is slow. IGWO is used to optimize two hyperparameters of SVR (penalty coefficient C and kernel parameter $\gamma $ ). SVR is used to predict the output signal strength value of the signal generator. To prove the validity of the IGWO-SVR, comparison experiments are made between the IGWO-SVR and 20 other models. The real data obtained from the experiments of electromagnetic interference effect by irradiation method are selected as the experimental data. Mean Absolute Error (MAE), Mean Squared Error (MSE), and Fitting Degree R Squared $(R^{2})$ are used to evaluate the overall performance of the models. Through comparative experiments, the MAE of the IGWO-SVR model is 1.1481, MSE is 2.6679, $R^{2}$ is 0.9430, and its performance in various evaluation indexes is better than other models.

As the physical size of a communication system for satellites or unmanned aerial vehicles demands to be reduced, a compact antenna with high directivity is proposed as a core element essential to the wireless device. Instead of using a horn or an array antenna, a unit planar antenna is combined with a surface-modulated lens to convert a low antenna gain to a high antenna gain. The lens is not a metal-patterned PCB but is dielectric, which is neither curved nor very wide. This palm-sized lens comprises pixels with different heights from the backside of PolyPhenylene Sulfide (PPS) as the dielectric base. The antenna gain from the unit antenna of 4.5 cm × 4.5 cm is enhanced by 10 dB with the help of a compact dielectric lens of 7.5 cm × 7.5 cm at 24.5 GHz as the frequency of interest. The antenna design is verified by far-field measurement as well as near-field observation, including sensing a metal object behind a blocking wall by using an RF test bench. Moreover, antenna performance is understood by making a comparison with conventional designs of antennas in terms of directivity and physical sizes.

On a regional or worldwide scale, satellite-based navigation systems can offer three-dimensional Position, Velocity, and Timing (PVT) services to an indefinite number of users. BeiDou-2 is China's regional navigation satellite system that encompasses the Asia-Pacific region. BeiDou-2's space section comprises GEO, MEO, and IGSO satellites, making it unique among the navigation systems. This research focuses on key aspects, including satellite visibility and signal strength, as a function of the elevation angle across the low latitude region (Indian region). In addition, the results were compared with those obtained using the GPS. The data is acquired from a GNSS receiver located at the Hyderabad station (latitude:17°24′28″, longitude:78°31′04″). The results show that BeiDou-2 satellites have better visibility than GPS satellites at all elevation angles. However, visibility is low at high elevations; therefore, multiple systems are required to obtain user information. As the elevation angle increases, the carrier-to-noise density ratio (C/No) also increases. Additionally, the standard deviation (STD) was calculated and compared to that of the GPS. Despite the average signal strength of GPS satellites remaining high throughout the elevation range, the STD of BeiDou-2 satellites was found to be low. These results indicate that further work is needed to improve the interoperability of multiple navigation systems and to provide more accurate location information to Indian users. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

IoT networks on large ships are known to face challenges, such as severe signal attenuation due to the complex steel bulkhead structure inside the ship. However, reliable connectivity is still required to monitor critical facilities such as engine rooms. This study presents an evaluation study of an IoT network using the IEEE 802.15.4 DSME MAC protocol for reliable data collection within a ship. We investigate the impact of ship-specific characteristics on signal propagation and analyze the feasibility of utilizing the DSME MAC protocol. We also compare the viability of 2.4 GHz and sub-1 GHz communication within a ship. In addition, we strategically select router locations and evaluate the stability and time sensitivity of the constructed network. The experimental results demonstrate the feasibility and reliability of the proposed multi-hop wireless network for seamless data transmission onboard ships. [ABSTRACT FROM AUTHOR]

This study aims to assess the effects of atmospheric temperature, relative humidity, and atmospheric pressure on the signal strength of Maloney FM Radio, 95.9 MHz, Keffi, Nasarawa State. It is essential to measure the signal strength of the new radio station in relation with some parameters of weather to provide effective service delivery to the critical sectors and the entire populace. The research was conducted using the data of atmospheric temperature, atmospheric pressure, relative humidity, and the strength of the Maloney radio signal acquired from 6.00 a.m. to 6.00 p.m. daily at a 30 min interval, from January 2023 to June 2023, in Karshi, Abuja, a neighbouring town to Nasarawa state where the radio station is located. The data analysis involving cointegration and descriptive statistics of the effects of atmospheric variables on the radio signal strength was implemented using Eviews and Microsoft Excel Software. The results showed daily and monthly variations of the radio signal strength as well as the atmospheric temperature, atmospheric pressure and relative humidity. The variation is such that the lowest monthly signal strength was in June, probably due to higher rainfall in the area in June being the last month in this work (Jan.–Jun.) compared to other months which are dry season (January–March) or when the rain was just starting (April–May), in the study area. It was observed that atmospheric temperature and pressure negatively correlate with signal strength while relative humidity positively correlates with received signal strength in all the six months under study. The cointegration analysis also showed a long-term relationship between the radio signal strength and the atmospheric components, as the probability on the first row on the tables of both Trace Test and Maximum Eigenvalue methods were 0.0016 and 0.0008, which are less than the 5% (0.05) set critical value. In the same way, the critical value results on the same first row in both methods are smaller than the Trace statistics values. This implies that there is a long-term relationship between the atmospheric variables and the Maloney FM radio signal strength. These results will help mitigate the attenuation effect, and attendant signal loss of the radio station's signal strength. By proxy, the results will support the operations and regulations of spectrum management in the design of satellite communications and satellite microwave band specifications in Nigeria. In addition, the pre-determination of the radio station location will depend on this study's result analyses, considering that the effects of atmospheric temperature, pressure, and humidity conditions are inevitable. Governments, policymakers, stakeholders, and other relevant authorities should ensure the domestication of the study by providing the necessary research materials and facilities for wider studies. As regards the Maloney FM radio station, Keffi, studied in this work, there is no similar or related work done on it before now, hence, providing the detailed relationship between the signal strength of the radio station and some weather variables will go a long way in the improvement of the quality of signal transmission from Maloney radio station. The results when provided to the station, will enable the management to also evaluate if their set target of the station such as the radio horizon, radio signal coverage, and the link budget have been met.

An array antenna for millimeter-wave communication and an array antenna for millimeter-wave sensing are designed and put together into one structure. Because millimeter-wave signals become weaker fast with the increasing distance and any kind of error in the required functions of the antenna has to be minimized, pointing error from the target direction should be prevented. The device is a millimeter-wave sensing antenna with high directivity to check the straight link between the TX and RX sides of wireless communication. A 24 GHz 8-by-16 array antenna which generates stronger signals for sensing resolves the drawback of a 28 GHz 1-by-4 array antenna that is commonly seen in 5G wireless terminals. The sensing and communication antennas are integrated as a planar structure mountable on platforms, which is investigated with regard to forming wireless links over a distance of several meters with an input power of less than 0 dBm. Additionally, in the event of a reflecting surface disturbing the straight path and worsening the pointing error in RF signal transfer, the dual-capability of the combination is presented on the basis of intuitive electromagnetic experiments.

GNSS/INS-based positioning must be revised for forest mapping, especially inside the forest. This study deals with the issue of the processability of GNSS/INS-positioned MLS data collected in the forest environment. GNSS time-based point clustering processed the misaligned MLS point clouds collected from skid trails under a forest canopy. The points of a point cloud with two misaligned copies of the forest scene were manually clustered iteratively until two partial point clouds with the single forest scene were generated using a histogram of GNSS time. The histogram’s optimal bin width was the maximum bin width used to create the two correct point clouds. The influence of GNSS outage durations, signal strength statistics, and point cloud parameters on the optimal bin width were then analyzed using correlation and regression analyses. The results showed no significant influence of GNSS outage duration or GNSS signal strength from the time range of scanning the two copies of the forest scene on the optimal width. The optimal bin width was strongly related to the point distribution in time, especially by the duration of the scanned plot’s occlusion from reviewing when the maximum occlusion period influenced the optimal bin width the most (R2 = 0.913). Thus, occlusion of the sub-plot scanning of tree trunks and the terrain outside it improved the processability of the MLS data. Therefore, higher stem density of a forest stand is an advantage in mapping as it increases the duration of the occlusions for a point cloud after it is spatially tiled.

In this paper, computation of very high frequency (VHF) signal strength for point to area network was carried out using machine learning modeling techniques. Seven different machine learning models were adopted: Decision Tree, Random Forest, AdaBoost, k-Nearest Neighbor, Support Vector Machine, Artificial Neural Network and Linear Regression. A total of 120 data points was used in computing the signal strength. 72 data points (60%) was used to train the model, while the remaining 48 data points (40%) were used as test data to determine the accuracy of the computation for all the models. From the results, it was observed that the accuracy of the computations was greatly influenced by the amount of training data that was used. Also, from the results, in highest order of accuracy, AdaBoost was adjudged the best model. This was followed by the Artificial Neural Network model. Generally, the error margin of computation obtained for these two models were low, hence indicating that the models can be effectively relied on for computation of signal strength in the study area.

The evolution of wireless networks towards high mobility has led to the concept of connecting vehicles. Wireless link quality is a vital attribute of a dynamic vehicular environment and a backbone for successful communication among vehicles. The vehicles are expected to be equipped with a number of sensors and measurement devices, making a lot of data available for research. To solve the challenges in the context of the connectivity of vehicles, data-driven approaches are recently applied to estimate the dynamic attributes of vehicular networks. In this paper, a deep learning model based on an artificial neural network technique is proposed to predict wireless link quality in vehicular networks. The proposed algorithm uses the essential features, including the current location of a vehicle, to estimate the quality of a wireless link. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is a future-generation networking environment in which distributed smart objects can communicate directly and create a connection between different types of heterogeneous networks. Knowing the accurate localization of IoT-based devices is one of the most challenging issues in expanding the IoT network performance. This paper was done to propose a new fuzzy type2-based scheme to enhance the position accurateness of sensors deployed in the Internet of Things environments. Our proposed scheme is based on the weighted centralized localization strategy, in which the location of unknown nodes calculates using the fuzzy type-2 system. The flow measurement via the wireless channel to calculate the separation distance between the sensor/anchor nodes is employed as the fuzzy system input. Also, the fuzzy membership functions to better adaptivity of our scheme with lossy IoT environments via learning automata algorithm are tuned. Then, in the proposed method, the fuzzy type-2 calculations are restricted by comparing the received signal strength with a predefined threshold value to extend the network lifetime. The effectiveness of the proposed scheme has been proven through extensive simulation. Based on the simulation results, our scheme, on average, reduced the localization error by 35.9% and 9.5% decreased the energy consumption by 13% and 7.2%, and reduced the convergence rate by 33.1% and 12.37 % compared to the HSPPSO and IMRL methods, respectively. [ABSTRACT FROM AUTHOR]

Testing the mobile network signal strength is essential for evaluating actual user experience. This procedure is done by measurement campaign, where a person or a group of people walk or drive through the target area holding a measuring equipment. However, this is not suitable to do in hard-to-reach areas. In order to minimize human involvement and to reduce resources, labour, and time consumed, an alternative approach for physical assessment of cellular coverage and quality evaluating is needed. In this work, we used a drone to measure mobile network signal strength to generate a two-dimensional coverage map for difficult-to-reach areas. A machine learning algorithm is used to estimate the signal strength in other locations within the area to generate a dense 2D coverage map. The measurements were done on Sultan Qaboos University Campus, Muscat, Oman. Our finding shows that a drone equipped with a low-cost signal strength measuring device and an artificial neural network (ANN) algorithm are able to generate an accurate dense map of mobile signal strength in a flexible and cost-effective manner. The ANN was capable of predicting the signal strength at the ground from measurement at higher altitudes with an accuracy of 97%.

This work examines how reflections from various reflective surfaces affect the reception of RF electromagnetic waves and how the latter impacts wireless power transmission. The frequency range used was 469.5 MHz to 773.5 MHz, and three reflective materials of almost 20% variation in the reflection coefficient were tested with a Yagi–Uda antenna at the receiving end. Additionally, the orientation of the antenna was changed in terms of elevation and azimuthal angles. The results were then assessed, and a conclusion was drawn. [ABSTRACT FROM AUTHOR]

This work introduced a novel approach for the movie recommender system using a machine learning approach. This work introduces a clustering-based approach to introduce a recommender system (RS). The conventional clustering approaches suffer from the clustering error issue, which leads to degraded performance. Hence, to overcome this issue, we developed an expectation-maximization-based clustering approach. However, due to imbalanced data, the performance of RS is degraded due to multicollinearity issues. Hence, we Incorporate PCA (Principal Component Analysis) based dimensionality reduction model to improve the performance. Finally, we aim to reduce the error; thus, a Genetic Algorithm (GA) is included to achieve the optimal clusters and assign the suitable recommendation. The experimental study is carried out on publically available movie datasets performance of the proposed approach is measured in terms of MSE (Mean Squared Error) and Root Mean Squared Error (RMSE). The comparative study shows that the proposed approach achieves better performance when compared with a state-of-art movie recommendation system. [ABSTRACT FROM AUTHOR]

This paper presents a novel wireless power transmission system through reflecting walls for enhancing received signal strength. The study has been conducted with the objective to achieve a novel system for energy harvesting and subsequent wireless power transmission for mobile phone charging applications. The work is carried out at the well-known RF frequency range from 469.5 MHz to 773.5 MHz. We have employed three different antennas for the proposed system. Multiple changes in antenna orientations have also been accounted for including azimuthal variations. The results show substantial enhancement in the received signal strength (RSS) due to the use of these reflecting walls.

This paper presents a novel wireless power transmission system through reflecting walls for enhancing received signal strength. The study has been conducted with an objective to achieve a novel system for the energy harvesting and subsequent wireless power transmission for mobile phone charging applications. The work is carried out at the well-known RF frequency range from 469.5 MHz to 773.5 MHz. We have employed three different antennas for the proposed system. Multiple changes in antenna orientations have also been accounted for including azimuthal variations. The results show substantial enhancement in the received signal strength (RSS) due to use of these reflecting walls. [ABSTRACT FROM AUTHOR]

Abstract Background Optical coherence tomography (OCT) is used worldwide by clinicians to evaluate macular and retinal nerve fiber layer (RNFL) characteristics. It is frequently utilized to assess disease severity, progression and efficacy of treatment, and therefore must be reliable and reproducible. Objective To examine the influence of signal strength on macular thickness parameters, macular volume measurement and RNFL thickness measured by spectral-domain optical coherence tomography (SD-OCT). Methods Macular thickness parameters, macular volume measurement and RNFL thickness were measured by the Spectralis® OCT (Heidelberg Engineering, Heidelberg, Germany). In each eye, the focusing knob was adjusted to obtain 4 images with different signal strengths – Low (below 15), Moderate (15-20), Good (20-25) and Excellent (above 25). The relationship between signal strength and measured data was assessed using the mixed model procedure. Results A total of 71 eyes of 41 healthy subjects were included. Central macular thickness, macular volume and mean RNFL thickness increased with decreasing signal strength. Specifically, eyes with excellent signal strength showed significantly thinner central macular thickness (p = 0.023), macular volume (p = 0.047), and mean RNFL thickness (p = 0.0139). Conclusions Higher signal strength is associated with lower macular thickness, macular volume and RNFL thickness measurements. The mean differences between excellent and low-quality measurements were small implicating that SD-OCT is a reliable imaging tool even at low quality scans. It is imperative that the physician compares the signal strength of all scans, as minute differences may alter results.

IoT networks on large ships are known to face challenges, such as severe signal attenuation due to the complex steel bulkhead structure inside the ship. However, reliable connectivity is still required to monitor critical facilities such as engine rooms. This study presents an evaluation study of an IoT network using the IEEE 802.15.4 DSME MAC protocol for reliable data collection within a ship. We investigate the impact of ship-specific characteristics on signal propagation and analyze the feasibility of utilizing the DSME MAC protocol. We also compare the viability of 2.4 GHz and sub-1 GHz communication within a ship. In addition, we strategically select router locations and evaluate the stability and time sensitivity of the constructed network. The experimental results demonstrate the feasibility and reliability of the proposed multi-hop wireless network for seamless data transmission onboard ships.

All the world now is depending on networks to share information between the users, where different data types are transferred wirelessly from network to network. Using wireless LANs are important to connect the users and share the data, these Wireless LANs have different types of obstacles that affect the data sharing or the wireless signal, such as, compatibility wireless protocol types, range coverage, walls penetration, moving devices, different routing protocols, data transferred types, weak signal, and many more. In this paper a practical analysis will be made to the latest IEEE 802.11ax wireless protocol to be compared with two types of Wi-Fi booster’s networks, Mesh and Extender Wi-Fi, while transferring 4k video size data rate, inside a room and on different rooms for wall penetration analysis, while measuring the throughput, delay, and signal strength metrics. The main importance of this paper is to give a more practical understanding and avoid the main problems of using the wireless protocol 802.11ax in different network types.

This study reported the investigation of the Radio Frequency (RF) signal propagation of Global System for Mobile Communications (GSM) coverage in Emmanuel Alayande College of Education (EACOED), Oyo, Oyo State, Nigeria. The study aims at amplifying the quality of service and augment end users' sensitivity of the wireless services operation. The drive test method is adopted with estimation of coverage level and received signal strength. The Network Cell Info Lite application installed in three INFINIX GSM mobile phones was employed to take the measurement of the signal strength received from the transmitting stations of different mobile networks. The results of the study revealed that MTN has the maximum signal strength with a mean value of - 68.33 dBm, directly followed by Globacom (-80.41 dBm) and Airtel with -83.13 dBm. The Airtel signal has a conspicuously invariable poor performance with coverage level of 41.66 %. Conversely, the MTN and Globacom signal reception are observed to surpass the Airtel network within the college premises with 83.33 % and 60.41 % coverage level respectively. This implies that the signal quality for MTN and Globacom networks were comparatively disseminated within the college with inconsequential fluctuations in quality while Airtel signal is subsided and weaken. The poor performance in some areas was due to the presence of physical impediments and far distances location of base station antennas in the promulgation locations. This study therefore suggested that Airtel and Globacom Base Transceiver Stations (BTS) should be positioned within the college to improve good network reportage level.

Wireless sensor network (WSN) is applicable in all IoT applications, thus it has many advancements. However, it has many drawbacks like localization, link failure, and so on. In addition, the reduction of received signal strength (RSS) often causes path loss, while transferring the data when the path is lost then it drops the packets. To address this problem, the current research aimed to develop a novel grey wolf ant lion recurrent (GWALR) localization model in WSN to find the location of each unknown node. Moreover, the fitness function of GWALR is utilized to track the location of each node. The key focus of this proposed model is to find the location of unknown nodes and to improve the RSS by reducing the localization error. In addition, the model that attained high RSS measure has better data broadcasting rate. Finally, the performance of the proposed approach is compared with existing works and attained better accuracy and reduced error rate. Thus the outcome of the proposed model proved the efficiency of the proposed work by gaining maximum throughput ratio as 7000bps, data broadcasting rate as 99%, accuracy 99.8% and reduced error rate as 1.4%. [ABSTRACT FROM AUTHOR]

This study reported the investigation of the Radio Frequency (RF) signal propagation of Global System for Mobile Communications (GSM) coverage in Emmanuel Alayande College of Education (EACOED), Oyo, Oyo State, Nigeria. The study aims at amplifying the quality of service and augment end users' sensitivity of the wireless services operation. The drive test method is adopted with estimation of coverage level and received signal strength. The Network Cell Info Lite application installed in three INFINIX GSM mobile phones was employed to take the measurement of the signal strength received from the transmitting stations of different mobile networks. The results of the study revealed that MTN has the maximum signal strength with a mean value of - 68.33 dBm, directly followed by Globacom (-80.41 dBm) and Airtel with -83.13 dBm. The Airtel signal has a conspicuously invariable poor performance with coverage level of 41.66 %. Conversely, the MTN and Globacom signal reception are observed to surpass the Airtel network within the college premises with 83.33 % and 60.41 % coverage level respectively. This implies that the signal quality for MTN and Globacom networks were comparatively disseminated within the college with inconsequential fluctuations in quality while Airtel signal is subsided and weaken. The poor performance in some areas was due to the presence of physical impediments and far distances location of base station antennas in the promulgation locations. This study therefore suggested that Airtel and Globacom Base Transceiver Stations (BTS) should be positioned within the college to improve good network reportage level. [ABSTRACT FROM AUTHOR]