Online Novelty Detection System: One-Class Classification of Systemic Operation

Presented is an Online Novelty Detection System (ONDS) that uses Gaussian Mixture Models (GMMs) and one-class classification techniques to identify novel information from multivariate times-series data. Multiple data preprocessing methods are explored and features vectors formed from frequency components obtained by the Fast Fourier Transform (FFT) and Welch\u27s method of estimating Power Spectral Density (PSD). The number of features are reduced by using bandpower schemes and Principal Component Analysis (PCA). The Expectation Maximization (EM) algorithm is used to learn parameters for GMMs on feature vectors collected from only normal operational conditions. One-class classification is achieved by thresholding likelihood values relative to statistical limits. The ONDS is applied to two different applications from different application domains. The first application uses the ONDS to evaluate systemic health of Radio Frequency (RF) power generators. Four different models of RF power generators and over 400 unique units are tested, and the average robust true positive rate of 94.76% is achieved and the best specificity reported as 86.56%. The second application uses the ONDS to identify novel events from equine motion data and assess equine distress. The ONDS correctly identifies target behaviors as novel events with 97.5% accuracy. Algorithm implementation for both methods is evaluated within embedded systems and demonstrates execution times appropriate for online use

Novel Detection and Analysis using Deep Variational Autoencoders

This paper presents a Novel Identification System which uses generative modeling techniques and Gaussian Mixture Models (GMMs) to identify the main process variables involved in a novel event from multivariate data. Features are generated and subsequently dimensionally reduced by using a Variational Autoencoder (VAE) supplemented by a denoising criterion and a β disentangling method. The GMM parameters are learned using the Expectation Maximization(EM) algorithm on features collected from only normal operating conditions. A one-class classification is achieved by thresholding the likelihoods by a statistically derived value. The Novel Identification method is verified as a detection method on existing Radio Frequency (RF) Generators and standard classification datasets. The RF dataset contains 2 different models of generators with almost 100 unique units tested. Novel Detection on these generators achieved an average testing true positive rate of 97.31% with an overall target class accuracy of 98.16%. A second application has the network evaluate process variables of the RF generators when a novel event is detected. This is achieved by using the VAE decoding layers to map the GMM parameters back to a space equivalent to the original input, resulting in a way to directly estimate the process variables fitness

Investigation of the Heating Processes and Temperature Field of the Frequency-controlled Asynchronous Engine Based on Mathematical Models

The study of the temperature field of the engine for non-stationary modes is done. A numerical simulation of a non-stationary thermal process using dynamic EHD, the characteristic of the rate of rise of temperatures is done. An increase in the temperature of individual parts in the idle interval, when the power of heat release is significantly reduced, is established, and the reverse of the heat flow through the air gap is established. It is shown that the EHD method, in contrast to the FEM, is self-sufficient, which determines its practical value. In various parts of the speed control range in the implementation of various laws of regulation. At the same time, the main electrical, magnetic and additional losses associated with the fundamental voltage harmonics (FVH), and mechanical losses, as well as additional electrical and magnetic losses associated with the higher voltage harmonics, change. When using serial asynchronous engines as frequency-controlled. Permissible under the conditions of heating power is significantly reduced by the power of serial engines. Depending on the synchronous speed, the reduction is from 10 % to 20 %. Given the additional overheating due to higher voltage harmonics, as well as the deterioration of the cooling conditions when adjusting the rotational speed "down" from the nominal, it seems very relevant

Advanced Imaging Techniques for Cardiovascular Research

Objectives: In this thesis we addressed some of those difficulties by exploring new applications of a 68Galabeled radiotracer (68Ga-DOTA). 68Ga can be obtained from a 68Ge/68Ga generator and has a half-life of 68 minutes, which makes it a convenient candidate for its widespread clinical use. We proposed and validated the use of 68Ga-DOTA as a radiotracer for assessment of myocardial blood flow (MBF), myocardial viability and pulmonary blood flow (PBF). Additionally, we introduced a new methodology to perform a PET scan in which this tracer could be coinjected simultaneously with some other radiotracers such as 18FDG (multi-tracer PET). Lastly, we developed an automatic detector able to perform blood spectroscopy analysis, which offered the possibility to perform multi-tracer PET with minimal human intervention. Methods To test the capability of 68Ga-DOTA to measure MBF, viability and PBF, different groups of Large White pigs underwent PET/CT scans using 68Ga-DOTA as the injected radiotracer. For PBF studies, a group of healthy pigs (n = 4) were scanned under rest conditions. For MBF studies, a group of 8 pigs were scanned under rest and pharmacologically-induced stress in order to perform rest/stress tests, as it is done for humans in clinical routine. Additionally, a group of 5 pigs were scanned 7 days after the induction of a myocardial infarction (MI) to assess viability and MBF in a MI model. MBF, extracellular volume fraction (ECV, for viability assessment) and PBF maps were obtained after fitting the dynamic PET images to the corresponding pharmacokinetic model followed by 68Ga-DOTA in each tissue under study. Global and regional perfusion maps for the myocardial tissue (MBF) and lungs (PBF) were obtained. For validation purposes, the “goldstandard” technique used in tissue perfusion quantification (fluorescent-labeled microspheres (MS)) was simultaneosly performed along with the PET/CT scans. The blood sampling spectroscopic methodology was evaluated and calibrated in vitro using different 68Ga/18F mixtures. Then, it was tested in pigs (n = 3) injected with 68Ga-DOTA and 18FDG in the same acquisition. The activity concentration of each radiotracer in myocardial tissue was subsequently measured ex vivo. The automatic blood sampling detector was built from scratch and characterized using a catheter filled with different 68Ga/18F mixtures. Finally, it was additionally evaluated in vivo in n = 3 pigs under conditions resembling to those encountered in clinical routine. Results Regarding MBF quantification and validation with 68Ga-DOTA-PET, a strong correlation (r = 0.91) between MBF measured with PET and MS was obtained (slope = 0.96 ± 0.10, y-intercept = 0.11 ± 0.19 ml·min−1·g−1). For the myocardial infarction model, MBF values obtained with 68Ga-DOTA-PET in the infarcted area (LAD, left anterior descendant) were significantly reduced in comparison to remote ones LCX (left circumflex artery, p < 0.0001) and RCA (right coronary artery, p < 0.0001). In addition, 68Ga-DOTA-PET detected a significant ECV increase in the infarcted area (p < 0.0001). The correlation evaluation between 68Ga-DOTA-PET and MS as a PBF radiotracer also showed a good and significant correlation (r = 0.74, p < 0.0001). The gamma spectroscopic analysis on blood samples proposed for multi-tracer PET imaging was also succesfully validated, showing a correlation of r = 0.95 (p < 0.0001) for 18FDG concentration in myocardium measured with multi-tracer PET and by ex vivo validation. The blood sampling detector was able to measure the arterial input function in pigs in an experimental setup under realistic conditions. Discussion and conclusions 68Ga-DOTA-PET allowed accurate non-invasive assessment of MBF and ECV in pigs with myocardial infarction and under rest-stress conditions. This technique could provide wide access to quantitative measurement of both MBF and ECV with PET imaging. 68Ga-DOTA-PET was also demonstrated to be a potential inexpensive method for measuring PBF in clinical settings. As for multi-tracer PET imaging, the proposed methodology allowed explicit measurement of separate arterial input functions, offering very similar results to those obtained as a reference from the ex vivo analysis of the tissue under evaluation. Finally, a novel blood sampling device was developed and characterized, showing performance parameters similar to other devices in the literature. Noteworthy, this detector has the additional and unique feature of allowing us to perform multi-tracer PET by means of a gamma spectroscopic analysis of the blood flowing between its detection blocks. All the results summarized in this abstract may contribute to spread the use of PET in clinical routine, either by the clinical use of 68Ga-DOTA as an inexpensive but accurate radiotracer for MBF, PBF or viability assessment, or by the implementation of multi-tracer PET, which could lead to cost reduction of PET examinations by shortening the scanning time and eliminating misalignment inaccuracies. This multi-tracer PET methodology could also be safely implemented using our proposed automated device that permits to perform the gamma spectroscopic analysis on blood samples with minimal human intervention

Advanced imaging techniques for cardiovascular research

According to the World Health Organization, cardiovascular diseases (CVDs) are the first cause of death globally. CVDs are a cluster of disorders that involve heart and blood vessels. Among them, coronary artery disease (CAD) is the most important disease in terms of mortality, causing more than 50% of the annual deaths. Over the last decades, many recognized international organisms, such as the World Health Organization and the American College of Cardiology have done great efforts to reduce the mortality and morbidity of CAD. In this line, accurate diagnosis and cost-effective management of CAD have revealed to be of utmost importance. Several imaging techniques are currently used in the clinical practice to provide a diagnosis and clinical assessment of the disease. Among them, Positron Emission Tomography (PET) is considered to be the “gold standard” for non invasive assessment of myocardial perfusion and viability, the two most relevant physiological parameters used to diagnose and manage patients with known or suspected CAD..

IoT Applications Computing

The evolution of emerging and innovative technologies based on Industry 4.0 concepts are transforming society and industry into a fully digitized and networked globe. Sensing, communications, and computing embedded with ambient intelligence are at the heart of the Internet of Things (IoT), the Industrial Internet of Things (IIoT), and Industry 4.0 technologies with expanding applications in manufacturing, transportation, health, building automation, agriculture, and the environment. It is expected that the emerging technology clusters of ambient intelligence computing will not only transform modern industry but also advance societal health and wellness, as well as and make the environment more sustainable. This book uses an interdisciplinary approach to explain the complex issue of scientific and technological innovations largely based on intelligent computing

Biomedical Engineering

Biomedical engineering is currently relatively wide scientific area which has been constantly bringing innovations with an objective to support and improve all areas of medicine such as therapy, diagnostics and rehabilitation. It holds a strong position also in natural and biological sciences. In the terms of application, biomedical engineering is present at almost all technical universities where some of them are targeted for the research and development in this area. The presented book brings chosen outputs and results of research and development tasks, often supported by important world or European framework programs or grant agencies. The knowledge and findings from the area of biomaterials, bioelectronics, bioinformatics, biomedical devices and tools or computer support in the processes of diagnostics and therapy are defined in a way that they bring both basic information to a reader and also specific outputs with a possible further use in research and development

磁気特性を制御したフェライトナノ粒子の磁気ハイパーサーミアおよびバイオテクノロジー応用

早大学位記番号:新7334早稲田大

Synthesis and preclinical evaluation of peptide receptor-targeted diagnostic and therapeutic radiopharmaceuticals for prostate cancer

The overexpression of certain peptide receptors on cancers cells can be exploited for the development of radiopharmaceuticals that are selectively delivered to cancer cells for diagnostic imaging or therapeutic purposes. Parts of this dissertation explore the development and preclinical evaluation of a radiolabeled antagonist peptide conjugate (RM2 = DOTA-4-amino-1-carboxymethyl-piperidine-D-Phe-Gln-Trp-Ala-Val-Gly-His-Sta-Leu-NH2) that targets the bombesin receptor (BB2r) overexpressed in human prostate cancer. Two radionuclides, [203]Pb and [212]Pb, were selected due to their uniqueness as a chemically identical theranostic matched pair. Lead--203 (t1/2 = 51.9 hours) decays by electron capture to stable [203]Tl, with the emission of [278] keV gamma rays (81% intensity) suitable for single-photon emission computed tomography (SPECT) imaging. On the other hand, [212]Pb (t1/2 = 10.6 hours) decays by beta emission into [212]Bi (t1/2 = 60.6 minutes), which subsequently decays into stable [208]Pb through a branched decay chain consisting of one alpha particle and one beta particle emission in each decay pathway. Hence, [212]Pb is of interest as an in vivo generator of [212]Bi for targeted alpha therapy. The fundamental chemistry and radiochemistry involved in the synthesis, purification and characterization of both [203Pb]Pb-RM2 and [212Pb]Pb-RM2 is described. Additionally, in vivo preclinical evaluation of the radiolabeled peptide conjugates was performed in male mouse models inoculated with PC3 human prostate cancer cells. The last portion of the work described in this dissertation focuses on 105Rh as a potential therapeutic radionuclide. Rhodium-105 (t1/2 = 35.4 hours) is a moderate energy beta-emitting radionuclide [ [beta] avg = 152 keV], with low energy gamma emissions [319 keV (19%) and 306 keV (5%)]. The production of 105Rh from recycled 104Ru metal target via the 104Ru (p, n) 105Ru -> 105Rh reaction was reported. In addition, a microwave-assisted procedure for the synthesis of Rh(III) complexes without the addition of refluxing ethanol or SnCl2 as reducing agents is described.Includes bibliographical references

IoT and Sensor Networks in Industry and Society

The exponential progress of Information and Communication Technology (ICT) is one of the main elements that fueled the acceleration of the globalization pace. Internet of Things (IoT), Artificial Intelligence (AI) and big data analytics are some of the key players of the digital transformation that is affecting every aspect of human's daily life, from environmental monitoring to healthcare systems, from production processes to social interactions. In less than 20 years, people's everyday life has been revolutionized, and concepts such as Smart Home, Smart Grid and Smart City have become familiar also to non-technical users. The integration of embedded systems, ubiquitous Internet access, and Machine-to-Machine (M2M) communications have paved the way for paradigms such as IoT and Cyber Physical Systems (CPS) to be also introduced in high-requirement environments such as those related to industrial processes, under the forms of Industrial Internet of Things (IIoT or I2oT) and Cyber-Physical Production Systems (CPPS). As a consequence, in 2011 the German High-Tech Strategy 2020 Action Plan for Germany first envisioned the concept of Industry 4.0, which is rapidly reshaping traditional industrial processes. The term refers to the promise to be the fourth industrial revolution. Indeed, the first industrial revolution was triggered by water and steam power. Electricity and assembly lines enabled mass production in the second industrial revolution. In the third industrial revolution, the introduction of control automation and Programmable Logic Controllers (PLCs) gave a boost to factory production. As opposed to the previous revolutions, Industry 4.0 takes advantage of Internet access, M2M communications, and deep learning not only to improve production efficiency but also to enable the so-called mass customization, i.e. the mass production of personalized products by means of modularized product design and flexible processes. Less than five years later, in January 2016, the Japanese 5th Science and Technology Basic Plan took a further step by introducing the concept of Super Smart Society or Society 5.0. According to this vision, in the upcoming future, scientific and technological innovation will guide our society into the next social revolution after the hunter-gatherer, agrarian, industrial, and information eras, which respectively represented the previous social revolutions. Society 5.0 is a human-centered society that fosters the simultaneous achievement of economic, environmental and social objectives, to ensure a high quality of life to all citizens. This information-enabled revolution aims to tackle today’s major challenges such as an ageing population, social inequalities, depopulation and constraints related to energy and the environment. Accordingly, the citizens will be experiencing impressive transformations into every aspect of their daily lives. This book offers an insight into the key technologies that are going to shape the future of industry and society. It is subdivided into five parts: the I Part presents a horizontal view of the main enabling technologies, whereas the II-V Parts offer a vertical perspective on four different environments. The I Part, dedicated to IoT and Sensor Network architectures, encompasses three Chapters. In Chapter 1, Peruzzi and Pozzebon analyse the literature on the subject of energy harvesting solutions for IoT monitoring systems and architectures based on Low-Power Wireless Area Networks (LPWAN). The Chapter does not limit the discussion to Long Range Wise Area Network (LoRaWAN), SigFox and Narrowband-IoT (NB-IoT) communication protocols, but it also includes other relevant solutions such as DASH7 and Long Term Evolution MAchine Type Communication (LTE-M). In Chapter 2, Hussein et al. discuss the development of an Internet of Things message protocol that supports multi-topic messaging. The Chapter further presents the implementation of a platform, which integrates the proposed communication protocol, based on Real Time Operating System. In Chapter 3, Li et al. investigate the heterogeneous task scheduling problem for data-intensive scenarios, to reduce the global task execution time, and consequently reducing data centers' energy consumption. The proposed approach aims to maximize the efficiency by comparing the cost between remote task execution and data migration. The II Part is dedicated to Industry 4.0, and includes two Chapters. In Chapter 4, Grecuccio et al. propose a solution to integrate IoT devices by leveraging a blockchain-enabled gateway based on Ethereum, so that they do not need to rely on centralized intermediaries and third-party services. As it is better explained in the paper, where the performance is evaluated in a food-chain traceability application, this solution is particularly beneficial in Industry 4.0 domains. Chapter 5, by De Fazio et al., addresses the issue of safety in workplaces by presenting a smart garment that integrates several low-power sensors to monitor environmental and biophysical parameters. This enables the detection of dangerous situations, so as to prevent or at least reduce the consequences of workers accidents. The III Part is made of two Chapters based on the topic of Smart Buildings. In Chapter 6, Petroșanu et al. review the literature about recent developments in the smart building sector, related to the use of supervised and unsupervised machine learning models of sensory data. The Chapter poses particular attention on enhanced sensing, energy efficiency, and optimal building management. In Chapter 7, Oh examines how much the education of prosumers about their energy consumption habits affects power consumption reduction and encourages energy conservation, sustainable living, and behavioral change, in residential environments. In this Chapter, energy consumption monitoring is made possible thanks to the use of smart plugs. Smart Transport is the subject of the IV Part, including three Chapters. In Chapter 8, Roveri et al. propose an approach that leverages the small world theory to control swarms of vehicles connected through Vehicle-to-Vehicle (V2V) communication protocols. Indeed, considering a queue dominated by short-range car-following dynamics, the Chapter demonstrates that safety and security are increased by the introduction of a few selected random long-range communications. In Chapter 9, Nitti et al. present a real time system to observe and analyze public transport passengers' mobility by tracking them throughout their journey on public transport vehicles. The system is based on the detection of the active Wi-Fi interfaces, through the analysis of Wi-Fi probe requests. In Chapter 10, Miler et al. discuss the development of a tool for the analysis and comparison of efficiency indicated by the integrated IT systems in the operational activities undertaken by Road Transport Enterprises (RTEs). The authors of this Chapter further provide a holistic evaluation of efficiency of telematics systems in RTE operational management. The book ends with the two Chapters of the V Part on Smart Environmental Monitoring. In Chapter 11, He et al. propose a Sea Surface Temperature Prediction (SSTP) model based on time-series similarity measure, multiple pattern learning and parameter optimization. In this strategy, the optimal parameters are determined by means of an improved Particle Swarm Optimization method. In Chapter 12, Tsipis et al. present a low-cost, WSN-based IoT system that seamlessly embeds a three-layered cloud/fog computing architecture, suitable for facilitating smart agricultural applications, especially those related to wildfire monitoring. We wish to thank all the authors that contributed to this book for their efforts. We express our gratitude to all reviewers for the volunteering support and precious feedback during the review process. We hope that this book provides valuable information and spurs meaningful discussion among researchers, engineers, businesspeople, and other experts about the role of new technologies into industry and society