A Mobile System for the On-Site Assembly of Timber Frame Components: The Development of an Agile, Low-Cost Alternative to Offsite Prefabrication

Prefabricated timber component-based systems are the most prevalent industrialised system used to build housing. Along with many other countries, the UK has invested in different types of factory-based prefabrication systems as a means of increasing productivity and enhancing quality. In more recent decades, prefabrication has become part of a series of ‘modern methods of construction’ employed for, and aimed at, delivering sustainable and efficient construction. However, certain pragmatic issues remain. The industry is cyclical, and during periods of declining resources, skills and technical development can be lost. Additionally, factory-based prefabrication requires substantial initial investment and an appropriate local workforce. To help address these issues, this paper presents the concept of an alternative method of production and assembly that takes a different approach to traditional industrialised systems that involve large investments and fixed-location factories. The proposition presented in this paper is that it is possible to design and develop a small, low cost, portable micro-factory that can be taken to a temporary location or construction site, where it can then be used to construct prefabricated closed panels. We describe the development of a working prototype, effectively a micro-factory, along with its potential advantages over a fixed facility.

Versatile and Targeted Validation of Space-Borne XCO2, XCH4 and XCO Observations by Mobile Ground-Based Direct-Sun Spectrometers

Satellite measurements of the atmospheric concentrations of carbon dioxide (CO2), methane (CH4) and carbon monoxide (CO) require careful validation. In particular for the greenhouse gases CO2 and CH4, concentration gradients are minute challenging the ultimate goal to quantify and monitor anthropogenic emissions and natural surface-atmosphere fluxes. The upcoming European Copernicus Carbon Monitoring mission (CO2M) will focus on anthropogenic CO2 emissions, but it will also be able to measure CH4. There are other missions such as the Sentinel-5 Precursor and the Sentinel-5 series that target CO which helps attribute the CO2 and CH4 variations to specific processes. Here, we review the capabilities and use cases of a mobile ground-based sun-viewing spectrometer of the type EM27/SUN. We showcase the performance of the mobile system for measuring the column-average dry-air mole fractions of CO2 (XCO2), CH4 (XCH4) and CO (XCO) during a recent deployment (Feb./Mar. 2021) in the vicinity of Japan on research vessel Mirai which adds to our previous campaigns on ships and road vehicles. The mobile EM27/SUN has the potential to contribute to the validation of 1) continental-scale background gradients along major ship routes on the open ocean, 2) regional-scale gradients due to continental outflow across the coast line, 3) urban or other localized emissions as mobile part of a regional network and 4) emissions from point sources. Thus, operationalizing the mobile EM27/SUN along these use cases can be a valuable asset to the validation activities for CO2M, in particular, and for various upcoming satellite missions in general.

Continuous measurement of stress levels in naturalistic settings using heart rate variability: An experience-sampling study driving a machine learning approach

<p class="Abstract"><span id="page629R_mcid43" class="markedContent"><span dir="ltr">Developing automatic methods to measure psychological stress in everyday life has become an important research challenge. Here, we describe the design and implementation of a personalized mobile system for the detection of psychological stress episodes based on Heart-Rate Variability (HRV) indices. The system’s architecture consists of three main modules: a mobile acquisition module; an analysis-decision module; and a visualization-reporting module. Once the stress level is calculated by the mobile system, the visualization-reporting module of the mobile application displays the current stress level of the user. We carried out an experience-sampling study, involving 15 participants, monitored longitudinally, for a total of 561 ECG analyzed, to select the HRV features which best correlate with self-reported stress levels. Drawing on these results, a personalized classification system is able to automatically detect stress events from those HRV features, after a training phase in which the system learns from the subjective responses given by the user. Finally, the performance of the classification task was evaluated on the empirical dataset using the leave one out cross-validation process. Preliminary findings suggest that incorporating self-reported psychological data in the system’s knowledge base allows for a more accurate and personalized definition of the stress response measured by HRV indices.</span></span></p>

A Case Study of Quantizing Convolutional Neural Networks for Fast Disease Diagnosis on Portable Medical Devices

Recently, the amount of attention paid towards convolutional neural networks (CNN) in medical image analysis has rapidly increased since they can analyze and classify images faster and more accurately than human abilities. As a result, CNNs are becoming more popular and play a role as a supplementary assistant for healthcare professionals. Using the CNN on portable medical devices can enable a handy and accurate disease diagnosis. Unfortunately, however, the CNNs require high-performance computing resources as they involve a significant amount of computation to process big data. Thus, they are limited to being used on portable medical devices with limited computing resources. This paper discusses the network quantization techniques that reduce the size of CNN models and enable fast CNN inference with an energy-efficient CNN accelerator integrated into recent mobile processors. With extensive experiments, we show that the quantization technique reduces inference time by 97% on the mobile system integrating a CNN acceleration engine.

Study and Investigation on 5G Technology: A Systematic Review

In wireless communication, Fifth Generation (5G) Technology is a recent generation of mobile networks. In this paper, evaluations in the field of mobile communication technology are presented. In each evolution, multiple challenges were faced that were captured with the help of next-generation mobile networks. Among all the previously existing mobile networks, 5G provides a high-speed internet facility, anytime, anywhere, for everyone. 5G is slightly different due to its novel features such as interconnecting people, controlling devices, objects, and machines. 5G mobile system will bring diverse levels of performance and capability, which will serve as new user experiences and connect new enterprises. Therefore, it is essential to know where the enterprise can utilize the benefits of 5G. In this research article, it was observed that extensive research and analysis unfolds different aspects, namely, millimeter wave (mmWave), massive multiple-input and multiple-output (Massive-MIMO), small cell, mobile edge computing (MEC), beamforming, different antenna technology, etc. This article’s main aim is to highlight some of the most recent enhancements made towards the 5G mobile system and discuss its future research objectives.

A Concept of Mobile Support System for the Young Onset Dementia in Taiwan

Owing to the increasing population of young onset dementia all over the world. We designed a 6”-display Android mobile system for evaluating the potential patient of Dementia. A pilot test at experienced nursing members showed that they had strong willing of launching this design in their daily practical events.

Verification of a Mobile Psychoacoustic Test System

Many hearing difficulties can be explained as a loss of audibility, a problem easily detected and treated using standard audiological procedures. Yet, hearing can be much poorer (or more impaired) than audibility predicts because of deficits in the suprathreshold mechanisms that encode the rapidly changing, spectral, temporal, and binaural aspects of the sound. The ability to evaluate these mechanisms requires well-defined stimuli and strict adherence to rigorous psychometric principles. This project reports on the comparison between a laboratory-based and a mobile system’s results for psychoacoustic assessment in adult listeners with normal hearing. A description of both systems employed is provided. Psychoacoustic tests include frequency discrimination, amplitude modulation detection, binaural encoding, and temporal gap detection. Results reported by the mobile system were not significantly different from those collected with the laboratory-based system for most of the tests and were consistent with those reported in the literature. The mobile system has the potential to be a feasible option for the assessment of suprathreshold auditory encoding abilities.

High efficiency class-D RF amplifiers and mobile NMR systems

<p>This thesis details the development of a hand held mobile NMR system. The new system addressed the drawbacks on most of the existing NMR systems of being physically large and heavy with poor power inefficiency. In order to achieve the goal of producing a compact and power efficient NMR system, several high efficiency Class D RF amplifiers were developed which showed efficiencies of over 80%. The single cycle controlled PWM amplifier working at 2 MHz was a novel design and no other PWM Class D amplifiers has been reported to operate at high frequency with output power greater than 100 W. Development of the 20 MHz amplifier with 100 W constant amplitude output showed that the Class D amplifiers are suitable for NMR applications even at high frequency and further development of this amplifier to work at 17 MHz with amplitude modulation was successful. It paved the way for the development of a full mobile system with the newly available 17 MHz Mini-MOUSE sensor. The fully integrated mobile system was developed using SoC FPGA technologies. The use of a 400 Msps DDS device for RF pulse generation results in a broadband system. A duplexer was developed to enable sensor tuning and matching with the receiver amplifiers on the duplexer output stage provided 72 dB gain. The web based control program running on an iPad has shown great portability and it allows the system to be operated outdoors, even in remote areas. Experiments on industrial applications has shown successful T2eff measurements on polymer composites and rubber samples and showed the potential for such a system to be used in industrial applications. The fully integrated system prototype fits in a case measuring 140x120x100 mm (LxWxH) and weighs 800 grams and fulfil all the requirements for a mobile NMR system.</p>

High efficiency class-D RF amplifiers and mobile NMR systems

<p>This thesis details the development of a hand held mobile NMR system. The new system addressed the drawbacks on most of the existing NMR systems of being physically large and heavy with poor power inefficiency. In order to achieve the goal of producing a compact and power efficient NMR system, several high efficiency Class D RF amplifiers were developed which showed efficiencies of over 80%. The single cycle controlled PWM amplifier working at 2 MHz was a novel design and no other PWM Class D amplifiers has been reported to operate at high frequency with output power greater than 100 W. Development of the 20 MHz amplifier with 100 W constant amplitude output showed that the Class D amplifiers are suitable for NMR applications even at high frequency and further development of this amplifier to work at 17 MHz with amplitude modulation was successful. It paved the way for the development of a full mobile system with the newly available 17 MHz Mini-MOUSE sensor. The fully integrated mobile system was developed using SoC FPGA technologies. The use of a 400 Msps DDS device for RF pulse generation results in a broadband system. A duplexer was developed to enable sensor tuning and matching with the receiver amplifiers on the duplexer output stage provided 72 dB gain. The web based control program running on an iPad has shown great portability and it allows the system to be operated outdoors, even in remote areas. Experiments on industrial applications has shown successful T2eff measurements on polymer composites and rubber samples and showed the potential for such a system to be used in industrial applications. The fully integrated system prototype fits in a case measuring 140x120x100 mm (LxWxH) and weighs 800 grams and fulfil all the requirements for a mobile NMR system.</p>

Intelligent system for assessing the harmfulness of food products based on the processing of textual and graphic information

The paper substantiates the need to assess the harm of food for consumers with chronic diseases or allergies, which is important to prevent possible deterioration of the disease or eliminate acute allergic reactions of the human body to harmful ingredients present in the product. It is proved that currently there is no convenient intelligent system that could recognize the composition of products on the Ukrainian market, provide product characteristics and assess the harmfulness of the product. It is proposed to use food labels and packaging as primary sources of food information that is available to the consumer. It is shown that the printed information on the packages is presented in text-graphic form. The development of a mobile system as a software solution for the detection and analysis of textual and graphical information on the composition of products based on the use of artificial intelligence methods is proposed and substantiated. The block diagram of the intelligent mobile system for detection and analysis of food composition has been developed. The MSER algorithm is used to select text regions on the input image matrix in the presented algorithmic software. The solution to the problem of character recognition was based on the use of convolutional neural network MobileNet-V2, which is currently the best option in the classification of images by mobile applications that do not have a server part, and therefore large computing resources. Alignment of text on the image was carried out using the method of finding a rectangle with the smallest area Developed algorithms for grouping words. A decision support algorithm has been proposed to assess the harmfulness of products. The developed system allows personalized selection of food for each individual user, ie, the assessment of the composition of products is calculated taking into account the state of health of use, existing threats, diseases, restrictions or allergies