A Low-Profile Antenna for On-Body and Off-Body Applications in the Lower and Upper ISM and WLAN Bands.

The article presents a Co-planar Waveguide (CPW) fed antenna of a low-profile, simple geometry, and compact size operating at the dual band for ISM and WLAN applications for 5G communication devices. The antenna has a small size of 30 mm × 18 mm × 0.79 mm and is realized using Rogers RT/Duroid 5880 substrate. The proposed dual-band antenna contains a CPW feedline along with the triangular patch. Later on, various stubs are loaded to obtain optimal results. The proposed antenna offers a dual band at 2.4 and 5.4 GHz while covering the impedance bandwidths of 2.25-2.8 GHz for ISM and 5.45-5.65 GHz for WLAN applications, respectively. The proposed antenna design is studied and analyzed using the Electromagnetic (EM) High-Frequency Structure Simulator (HFSSv9) tool, and a hardware prototype is fabricated to verify the simulated results. As the antenna is intended for on-body applications, therefore, Specific Absorption Rate (SAR) analysis is carried out to investigate the Electromagnetic effects of the antenna on the human body. Moreover, a comparison between the proposed dual-band antenna and other relevant works in the literature is presented. The results and comparison of the proposed work with other literary works validate that the proposed dual-band antenna is suitable for future 5G devices working in Industrial, Scientific, Medical (ISM), and Wireless Local Area Network (WLAN) bands.

Wireless Local Area Networks Threat Detection Using 1D-CNN.

Wireless Local Area Networks (WLANs) have revolutionized modern communication by providing a user-friendly and cost-efficient solution for Internet access and network resources. However, the increasing popularity of WLANs has also led to a rise in security threats, including jamming, flooding attacks, unfair radio channel access, user disconnection from access points, and injection attacks, among others. In this paper, we propose a machine learning algorithm to detect Layer 2 threats in WLANs through network traffic analysis. Our approach uses a deep neural network to identify malicious activity patterns. We detail the dataset used, including data preparation steps, such as preprocessing and division. We demonstrate the effectiveness of our solution through series of experiments and show that it outperforms other methods in terms of precision. The proposed algorithm can be successfully applied in Wireless Intrusion Detection Systems (WIDS) to enhance the security of WLANs and protect against potential attacks.

A Throughput Request Satisfaction Method for Concurrently Communicating Multiple Hosts in Wireless Local Area Network.

Nowadays, the IEEE 802.11 wireless local area network (WLAN) has been widely used for Internet access services around the world. Then, the unfairness or insufficiency in meeting the throughput request can appear among concurrently communicating hosts with the same access point (AP), which should be solved by sacrificing advantageous hosts. Previously, we studied the fairness control method by adopting packet transmission delay at the AP. However, it suffers from slow convergence and may not satisfy different throughput requests among hosts. In this paper, we propose a throughput request satisfaction method for providing fair or different throughput requests when multiple hosts are concurrently communicating with a single AP. To meet the throughput request, the method (1) measures the single and concurrent throughput for each host, (2) calculates the channel occupying time from them, (3) derives the target throughput to achieve the given throughput request, and (4) controls the traffic by applying traffic shaping at the AP. For evaluations, we implemented the proposal in the WLAN testbed system with one Raspberry Pi AP and up to five hosts, and conducted extensive experiments in five scenarios with different throughput requests. The results confirmed the effectiveness of our proposal.

WLAN RSS-Based Fingerprinting for Indoor Localization: A Machine Learning Inspired Bag-of-Features Approach.

Location-based services have permeated Smart academic institutions, enhancing the quality of higher education. Position information of people and objects can predict different potential requirements and provide relevant services to meet those needs. Indoor positioning system (IPS) research has attained robust location-based services in complex indoor structures. Unforeseeable propagation loss in complex indoor environments results in poor localization accuracy of the system. Various IPSs have been developed based on fingerprinting to precisely locate an object even in the presence of indoor artifacts such as multipath and unpredictable radio propagation losses. However, such methods are deleteriously affected by the vulnerability of fingerprint matching frameworks. In this paper, we propose a novel machine learning framework consisting of Bag-of-Features and followed by a k-nearest neighbor classifier to categorize the final features into their respective geographical coordinate data. BoF calculates the vocabulary set using k-mean clustering, where the frequency of the vocabulary in the raw fingerprint data represents the robust final features that improve localization accuracy. Experimental results from simulation-based indoor scenarios and real-time experiments demonstrate that the proposed framework outperforms previously developed models.

A Systematic Review of Wi-Fi and Machine Learning Integration with Topic Modeling Techniques.

Wireless networks have drastically influenced our lifestyle, changing our workplaces and society. Among the variety of wireless technology, Wi-Fi surely plays a leading role, especially in local area networks. The spread of mobiles and tablets, and more recently, the advent of Internet of Things, have resulted in a multitude of Wi-Fi-enabled devices continuously sending data to the Internet and between each other. At the same time, Machine Learning has proven to be one of the most effective and versatile tools for the analysis of fast streaming data. This systematic review aims at studying the interaction between these technologies and how it has developed throughout their lifetimes. We used Scopus, Web of Science, and IEEE Xplore databases to retrieve paper abstracts and leveraged a topic modeling technique, namely, BERTopic, to analyze the resulting document corpus. After these steps, we inspected the obtained clusters and computed statistics to characterize and interpret the topics they refer to. Our results include both the applications of Wi-Fi sensing and the variety of Machine Learning algorithms used to tackle them. We also report how the Wi-Fi advances have affected sensing applications and the choice of the most suitable Machine Learning models.

Low Profile Monopole Meander Line Antenna for WLAN Applications.

An antenna assumes a significant role in expanding the levels of communication to meet the demands of contemporary technologically based industry and private data services. In this paper, a printed compact meander line patch antenna array for wireless local-area network (WLAN) applications in the frequency span of 2.3685-2.4643 GHz is presented. The impedance matching of the antenna is generated by applying a partial rectangular-shaped ground plane backside of the meander line antenna. The proposed antenna evolved on the Rogers RT5880 substrate with a dielectric permittivity of 2.2, and the height of the substrate was 1.575 mm to accomplish the lowest possible return loss. The proposed antenna was developed to achieve particular outcomes, for example, voltage standing wave ratio (VSWR) 1.32, reflection coefficient 20 dB with a bandwidth of 94.2 MHz, a gain of 2.8 dBi, and an efficacy measurement of 97%. This antenna is appropriate for WLAN applications that utilize a 2.4 GHz resonance frequency. The overall dimensions of the antenna are 15 mm × 90.86 mm.

Reliability Analysis of the Proactive Transmission of Replicated Frames Mechanism over Time-Sensitive Networking.

The Time-Sensitive Networking (TSN) Task Group has standardised different mechanisms to provide Ethernet with hard real-time guarantees and reliability in layer 2 of the network architecture. Specifically, TSN proposes using space redundancy to increase the reliability of Ethernet networks, but using space redundancy to tolerate temporary faults is not a cost-effective solution. For this reason, we propose to use time redundancy to tolerate temporary faults in the links of TSN-based networks. Specifically, in previous works we proposed the Proactive Transmission of Replicated Frames (PTRF) mechanism to tolerate temporary faults in the links. Now, in this work we present a series of models of TSN and PTRF developed using PRISM, a probabilistic model checker that can be used to evaluate the reliability of systems. After that, we carry out a parametric sensitivity analysis of the reliability achievable by TSN and PTRF and we show that we can increase the reliability of TSN-based networks using PTRF to tolerate temporary faults in the links of TSN networks. This is the first work that presents a quantitative analysis of the reliability of TSN networks.

A Wearable Button Antenna Sensor for Dual-Mode Wireless Information and Power Transfer.

A novel wearable button antenna sensor is proposed for the concept of simultaneous wireless information and power transfer (SWIPT). This integrates two working modes for the transfer of power and information, respectively, and optimizes transfer efficiency. An omni-directional radiation pattern is achieved in the 3.5 GHz World Interoperability for Microwave Access (WiMAX) band to support on-body wireless communications, while a circularly polarized broadside radiation pattern is obtained in the 5 GHz wireless local area networks (WLAN) band to harvest power. The measured -10 dB return loss bandwidths are 4.0% (3.47-3.61 GHz) in the lower band, and 25.0% (4.51-5.80 GHz) in the higher band, respectively. An artificial magnetic conductor (AMC) structure with wideband characteristics is applied to obtain a low-profile design and to increase the stability of the antenna sensor. A high radiation efficiency of over 80% in the whole working band is observed. The specific absorption rate (SAR) of the proposed antenna sensor is below 0.509 W/kg at 3.55 GHz, and below 0.0532 W/kg at 5.5 GHz, respectively, which is much lower than the European standard threshold of 2 W/kg. All these characteristics make the designed antenna sensor suitable for on-body information transmission and off-body energy harvesting. The antenna sensor has been prototyped. Simulations and measurements agree well, proving the validity of the new concept.

Flexible Wearable Composite Antennas for Global Wireless Communication Systems.

Although wearable antennas have made great progress in recent years, how to design high-performance antennas suitable for most wireless communication systems has always been the direction of RF workers. In this paper, a new approach for the design and manufacture of a compact, low-profile, broadband, omni-directional and conformal antenna is presented, including the use of a customized flexible dielectric substrate with high permittivity and low loss tangent to realize the compact sensing antenna. Poly-di-methyl-siloxane (PDMS) is doped a certain proportion of aluminum trioxide (Al2O3) and Poly-tetra-fluoro-ethylene (PTFE) to investigate the effect of dielectric constant and loss tangent. Through a large number of comparative experiments, data on different doping ratios show that the new doped materials are flexible enough to increase dielectric constant, reduce loss tangent and significantly improve the load resistance capacity. The antenna is configured with a multisection microstrip stepped impedance resonator structure (SIR) to expand the bandwidth. The measured reflection return loss (S11) showed an operating frequency band from 0.99 to 9.41 GHz, with a band ratio of 146%. The antenna covers two important frequency bands, 1.71-2.484 GHz (personal communication system and wireless body area network (WBAN) systems) and 5.15-5.825 GHz (wireless local area network-WLAN)]. It also passed the SAR test for human safety. Therefore, the proposed antenna offers a good chance for full coverage of WLAN and large-scale development of wearable products. It also has potential applications in communication systems, wireless energy acquisition systems and other wireless systems.

Time-Sensitive Networking in IEEE 802.11be: On the Way to Low-Latency WiFi 7.

A short time after the official launch of WiFi 6, IEEE 802.11 working groups along with the WiFi Alliance are already designing its successor in the wireless local area network (WLAN) ecosystem: WiFi 7. With the IEEE 802.11be amendment as one of its main constituent parts, future WiFi 7 aims to include time-sensitive networking (TSN) capabilities to support low latency and ultra-reliability in license-exempt spectrum bands, enabling many new Internet of Things scenarios. This article first introduces the key features of IEEE 802.11be, which are then used as the basis to discuss how TSN functionalities could be implemented in WiFi 7. Finally, the benefits and requirements of the most representative Internet of Things low-latency use cases for WiFi 7 are reviewed: multimedia, healthcare, industrial, and transport.

[Research on Visualized Traceability Supervision System of Medical Equipment Based on Wireless Local Area Network Real-time Positioning System].

Aiming at the shortcomings of traditional medical device tracking and supervision mode, such as delayed feedback of medical device positioning information, poor visual tracking effect of medical device, and missing early warning of medical device working state supervision, a medical device visual tracking and supervision system based on wireless Local Area Network (LAN) real-time positioning system is developed. Introduction of wireless LAN real-time positioning system, using standard coding algorithm generating device object ID tags, with the only attribute based on RFID read-write terminal complete physical mapping of medical equipment and material ID label, we realize a real-time positioning and traceability of medical equipment, with the help of active warning algorithm based on depth of learning medical equipment working state supervision for early warning, with the help of indoor map generation and trajectory playback medical equipment to realize visualization back regulation. Choose equipment of hospital of Linyi Central Hospital for performance evaluation of the carrier, the evaluation model of engineering practice and clinical statistical analysis, the results show that the system has a complete real-time positioning, visible trace, abnormal warning function. In medical equipment real-time positioning information visual tracing feedback, abnormal state warning etc, medical equipment has obvious advantages.

LAN: A Materials Notation for Two-Dimensional Layered Assemblies.

Two-dimensional (2D) layered materials offer intriguing possibilities for novel physics and applications. Before any attempt at exploring the materials space in a systematic fashion, or combining insights from theory, computation, and experiment, a formal description of information about an assembly of arbitrary composition is required. Here, we introduce a domain-generic notation that is used to describe the space of 2D layered materials from monolayers to twisted assemblies of arbitrary composition, existent or not yet fabricated. The notation corresponds to a theoretical materials concept of stepwise assembly of layered structures using a sequence of rotation, vertical stacking, and other operations on individual 2D layers. Its scope is demonstrated with a number of example structures using common single-layer materials as building blocks. This work overall aims to contribute to the systematic codification, capture, and transfer of materials knowledge in the area of 2D layered materials.

CC-DTW: An Accurate Indoor Fingerprinting Localization Using Calibrated Channel State Information and Modified Dynamic Time Warping.

Indoor wireless local area network (WLAN) based positioning technologies have boomed recently because of the huge demands of indoor location-based services (ILBS) and the wide deployment of commercial Wi-Fi devices. Channel state information (CSI) extracted from Wi-Fi signals could be calibrated and utilized as a fine-grained positioning feature for indoor fingerprinting localization. One of the main factors that would restrict the positioning accuracy of fingerprinting systems is the spatial resolution of fingerprints (SRF). This paper mainly focuses on the improvement of SRF for indoor CSI-based positioning and a calibrated CSI feature (CCF) with high SRF is established based on the preprocess of both measured amplitude and phase. In addition, a similarity calculation metric for the proposed CCF is designed based on modified dynamic time warping (MDTW). An indoor fingerprinting method based on CCF and MDTW, named CC-DTW, is then proposed to improve the positioning accuracy in indoors. Experiments are conducted in two indoor office testbeds, and the performances of the proposed CC-DTW, one time-reversal (TR) based approach and one Euclidean distance (ED) based approach are evaluated and discussed. The results show that the SRF of CC-DTW outperforms the TR-based one and the ED-based one in both two testbeds in terms of the receiver operating characteristic (ROC) curve metric, and the area under curve (AUC) metric.

Clinical significance of antibodies to antigens in the Raph, John Milton Hagen, I, Globoside, Gill, Rh-associated glycoprotein, FORS, JR, LAN, Vel, CD59, and Augustine blood group systems.

CONCLUSIONS: This article reviews information on the clinical significance of antibodies to antigens in the Raph, John Milton Hagen, I, Globoside, Gill, Rh-associated glycoprotein, FORS, JR, LAN, Vel, CD59, and Augustine blood group systems. Antibodies to many of the antigens in these groups are rarely encountered because of the high prevalence of the associated antigens in most populations. For many of these antibodies, the clinical significance-that is, the potential to cause reduced survival of transfused antigen-positive red blood cells or a transfusion reaction (e.g., anti-P, anti-Jra, and anti-Lan), and/or hemolytic disease of the fetus and newborn (e.g., anti-RHAG4 and anti-Vel)-has been documented. For other antibodies, their prevalence is so rare that information on the clinical significance of their antibodies is not available (e.g., anti-FORS1).

Clinic staff attitudes towards the use of mHealth technology to conduct perinatal depression screenings: a qualitative study.

BACKGROUND: The use of mHealth technology is an innovative approach for screening low-income mothers for depression. Past studies show that the use of technology removes barriers such as literacy issues, language challenges, concerns about privacy and lack of transportation and can also increase reliability. However, little is known about staff attitudes and perceptions towards using mHealth technology for screening low-income women for depression in clinics. METHODS: Four focus groups were conducted with staff members in a supplemental nutrition program for women, infants and children located in a public health clinic. A semi-structured focus group interview guide was used to examine staff perceptions related to depression screening with tablet technology. All interviews were audio recorded and transcribed verbatim. Thematic analysis was used to analyse all focus group data. RESULTS: Three major benefits and two major barriers were found. The benefits of using technology for perinatal depression screenings were reduction of literacy and language barriers, reduction of redundancy and errors and increased privacy for clients. The barriers were increased network issues and responsibility for technology, which included fear of the devices being lost, stolen or broken. IMPLICATIONS: Before implementing mHealth tablet technology for depression screening in a public health clinic, it is important to address the concerns of staff members to make the transition more effective. This study provides timely information on staff-perceived benefits and barriers when implementing mHealth technology in a public health setting.

PRIMAL: Page Rank-Based Indoor Mapping and Localization Using Gene-Sequenced Unlabeled WLAN Received Signal Strength.

Due to the wide deployment of wireless local area networks (WLAN), received signal strength (RSS)-based indoor WLAN localization has attracted considerable attention in both academia and industry. In this paper, we propose a novel page rank-based indoor mapping and localization (PRIMAL) by using the gene-sequenced unlabeled WLAN RSS for simultaneous localization and mapping (SLAM). Specifically, first of all, based on the observation of the motion patterns of the people in the target environment, we use the Allen logic to construct the mobility graph to characterize the connectivity among different areas of interest. Second, the concept of gene sequencing is utilized to assemble the sporadically-collected RSS sequences into a signal graph based on the transition relations among different RSS sequences. Third, we apply the graph drawing approach to exhibit both the mobility graph and signal graph in a more readable manner. Finally, the page rank (PR) algorithm is proposed to construct the mapping from the signal graph into the mobility graph. The experimental results show that the proposed approach achieves satisfactory localization accuracy and meanwhile avoids the intensive time and labor cost involved in the conventional location fingerprinting-based indoor WLAN localization.

The Enhanced Workflow and Efficiency of the Wireless Local Area Network (WLAN)-Based Direct Digital Radiography (DDR) Portable Radiography.

With the implementation of the PACS in the hospital, there is an increasing demand from the clinicians for immediate access and display of radiological images. Recently, our hospital has installed the first wireless local area network (WLAN)-based direct digital radiography (DDR) portable radiography system. The DDR portable radiography system allows wireless retrieval of modality worklist and wireless transmission of portable X-ray image on the console to the Picture Archiving and Communication System (PACS), via WLAN connection of wireless fidelity (Wi-Fi). The aim of this study was to analyze the workflow and performance between the WLAN-based DDR portable radiography system and the old practice using conventional portable X-ray machine with computed radiography (CR) system. A total of 190 portable chest X-ray examinations were evaluated and timed, using the conventional portable X-ray machine with CR from March to April of 2012 and using the new DDR portable radiography system on December of 2012 (n = 97 for old system and n = 93 for DDR portable system). The time interval of image becoming available to the PACS using the WLAN-based DDR portable radiography system was significantly shorter than that of the old practice using the conventional portable X-ray machine with CR (6.8 ± 2.6 min for DDR portable system; 23 ± 10.2 min for old system; p < 0.0001), with the efficiency improved by 70 %. The implementation of the WLAN-based DDR portable radiography system can enhance the workflow of portable radiography by reduction of procedural steps.

[Current status and issues of regional clinic network for hip fractures in the elderly].

I investigated presence of taking medicine and a taking medicine continuation rate to evaluate how to use the regional post-referral treatment plan about the osteoporosis treatment for the secondary hip fractures prevention. I evaluated the present conditions of the regional post-referral treatment plan that I considered from acute care hospital points of view. The osteoporosis treatment that continued and expanse of the osteoporosis liaison service are necessary to quit the chain of the osteoporotic fracture. It is necessary to improve a taking medicine continuation rate.

Multidimensional optimization of signal space distance parameters in WLAN positioning.

Accurate indoor localization of mobile users is one of the challenging problems of the last decade. Besides delivering high speed Internet, Wireless Local Area Network (WLAN) can be used as an effective indoor positioning system, being competitive both in terms of accuracy and cost. Among the localization algorithms, nearest neighbor fingerprinting algorithms based on Received Signal Strength (RSS) parameter have been extensively studied as an inexpensive solution for delivering indoor Location Based Services (LBS). In this paper, we propose the optimization of the signal space distance parameters in order to improve precision of WLAN indoor positioning, based on nearest neighbor fingerprinting algorithms. Experiments in a real WLAN environment indicate that proposed optimization leads to substantial improvements of the localization accuracy. Our approach is conceptually simple, is easy to implement, and does not require any additional hardware.

Beamforming transmission in IEEE 802.11ac under time-varying channels.

The IEEE 802.11ac wireless local area network (WLAN) standard has adopted beamforming (BF) schemes to improve spectral efficiency and throughput with multiple antennas. To design the transmit beam, a channel sounding process to feedback channel state information (CSI) is required. Due to sounding overhead, throughput increases with the amount of transmit data under static channels. Under practical channel conditions with mobility, however, the mismatch between the transmit beam and the channel at transmission time causes performance loss when transmission duration after channel sounding is too long. When the fading rate, payload size, and operating signal-to-noise ratio are given, the optimal transmission duration (i.e., packet length) can be determined to maximize throughput. The relationship between packet length and throughput is also investigated for single-user and multiuser BF modes.