Search Results (23)

This article presents a comprehensive analysis of the potential for microgeneration of electrical energy from human physical activity and reviews current commercial and research solutions, including stationary bicycles, treadmills, rowing ergometers, strength equipment, and kinetic floor systems. The physiological foundations of human energy generation are examined, with attention to key factors such as age, gender, fitness level, maximum oxygen uptake, heart rate, and hydration. The study includes mathematical models of energy conversion from metabolic to electrical output, incorporating fatigue as a limiting factor in long-duration performance. Available energy storage technologies (e.g., lithium-ion batteries, supercapacitors, and flywheels) and intelligent energy management systems (EMS) for use in sports facilities and net-zero energy buildings are also reviewed. As part of the study, a conceptual design of a multifunctional training and diagnostic device is proposed to illustrate potential technological directions. This device integrates microgeneration with dynamic physiological monitoring and adaptive load control through power electronic conversion. The paper highlights both the opportunities and limitations of harvesting human-generated energy and outlines future directions for sustainable energy applications in fitness environments. A preliminary economic analysis is also included, showing that while the energy payback alone is limited, the device offers commercial potential when combined with diagnostic and smart fitness services and may contribute to broader building energy efficiency strategies through integration with intelligent energy systems. Full article

Background/Objective: Early mobilization (EM) of critically ill patients is a feasible and safe intervention that limits the implications of bed rest and improves lung function. However, its limited implementation suggests a gap between the research evidence and clinical practice. It is widely accepted that early mobilization faces a variety of barriers. This study aimed to investigate the perceptions of Greek physiotherapists on EM barriers and record their knowledge and practices. Methods: We conducted an electronic survey using the online platform “Microsoft Forms”, among critical care physiotherapists in 66 hospitals that had an Intensive Care Unit (ICU) department in Greece in 2024. We administered a questionnaire, developed based on valid and reliable international questionnaires, with the following domains: education and knowledge on early mobilization, practices, perception regarding EM, and perceived barriers to early mobilization. Results: A total of 126 Greek physical therapists participated. The majority of them worked in urban area hospitals and in a rotation schedule around all departments. Most physical therapists stated that early mobilization is a priority for the patient’s rehabilitation and an important factor in preventing the complications of bed rest. Yet, they do not use specific protocols. Most had knowledge of what EM involved and the international guidelines. The most common barriers reported were the hemodynamic instability and the incoherence with the ventilator. Dedicated physiotherapists singled out certain barriers like the presence of delirium and the lack of communication among ICU staff. Additionally, physiotherapists with more years of experience did not acknowledge tubes, connections, femoral lines and Body Mass Index (BMI) as barriers. Conclusions: Most Greek physiotherapists believe that early mobilization is crucial for the rehabilitation of critically ill patients. A significant percentage know the guidelines, yet they do not follow a specific protocol. Various barriers prevent its implementation, which depends on the patients, healthcare providers, and the overall process. Yet, It is recognized that practices and perceived barriers are influenced by experience and work schedule. Establishing clinical protocols is essential to facilitate the implementation of early mobilization and support patient rehabilitation. Future efforts should focus on designing strategies and EM protocols for physiotherapy in Greek ICUs. Also, we need to monitor changes in perceived barriers across other countries as focus on the matter via published studies and clinical seminars could lead to significant changes. Full article

Electronic monitoring systems (EMSs) have been widely used in global fishing vessels as an effective tool to obtain reliable information about catches and fishing operations in order to verify compliance with national and international regulations. Though EMS implementation in tuna vessels has not yet been made a mandatory requirement by tuna regional fisheries management organizations, many Chinese longliners have the system on board for traceability and safety purposes. Based on interviews with managers and skippers on Chinese tuna longliners, this paper firstly identifies the challenges in electronic monitoring management that have hindered fishermen’s confidence to implement EMS at a larger scale. Then this paper proposes a work plan to facilitate EMS implementation from the perspective of Chinese tuna longliners, in which the adoption of EM standards, specifications, and procedures, and identification of EM data fields are the top priorities. To fully address concerns raised by tuna longliners, a cloud computing platform for EMS data storage, transmission, and review could help to protect data safety and confidentiality. Artificial intelligence technology is recommended to increase cost-efficiency in data review procedures, in addition to compliance incentives and financial incentives from policy makers. Full article

This study proposes an Artificial Intelligence-based Real-time Catch Analysis System (AI-RCAS) for sustainable fisheries management. The AI-RCAS, implemented on a Jetson board, consists of fish recognition using YOLOv10, tracking with a ByteTrack algorithm optimized for marine environments, and a counting module. Experiments in actual fishing environments showed significant improvements, with species recognition rates of 74–81%. The system supports the efficient operation of the total allowable catch (TAC) system through real-time analysis, addressing the limitations of the existing Electronic Monitoring (EM) systems. However, challenges remain, including object-tracking difficulties and performance issues in unstable marine environments. Future research should focus on optimizing the fishing process, improving video processing, and expanding the dataset for better generalization. Full article

Unintentional electromagnetic (EM) emissions often include information about the data processed by electronic devices. Intrusion based on an unintentional EM emission leaves no evidence of an attacker’s activity, while the data owner is unaware that it has been lost. EM attacks can be performed without physically damaging a device that operates regularly. The most typical intrusion activities involve sensitive data exfiltration using various methods that do not require the physical connection of devices to the computer network or communication channels. This research examines EM emissions from computer monitors, wireless keyboards and mice, printers, scanners, conductors, piezoelectric sensors (PES), and radio frequency identification (RFID) devices. The telecommunication electronics material protected from emanating spurious transmissions (TEMPEST) profiling as a performance engineering of the EM footprint is discussed. This study also presents different TEMPEST standards and highlights their importance concerning unintentional EM radiation. Full article

In recent years, with the development of pelagic fishing, the working environment and monitoring of crew (squid jigger) members have become increasingly important. However, traditional methods of pelagic human observers suffer from high costs, low coverage, poor timeliness, and susceptibility to subjective factors. In contrast, the Electronic Monitoring System (EMS) has advantages such as continuous operation under various weather conditions; more objective, transparent, and efficient data; and less interference with fishing operations. This paper shows how the 3DCNN model, LSTM+ResNet model, and TimeSformer model are applied to video-classification tasks, and for the first time, they are applied to an EMS. In addition, this paper tests and compares the application effects of the three models on video classification, and discusses the advantages and challenges of using them for video recognition. Through experiments, we obtained the accuracy and relevant indicators of video recognition using different models. The research results show that when NUM_FRAMES is set to 8, the LSTM+ResNet-50 model has the best performance, with an accuracy of 88.47%, an $F1$ score of 0.8881, and an $m_{ap}$ score of 0.8133. Analyzing the EMS for pelagic fishing can improve China’s performance level and management efficiency in pelagic fishing, and promote the development of the fishery knowledge service system and smart fishery engineering. Full article

The cyclin-dependent kinase 4/6 inhibitor (CDK4/6i) palbociclib is administered orally and cyclically, causing medication adherence challenges. We evaluated components of adherence to palbociclib, its relationship with pharmacokinetics (PK), and drug-induced neutropenia. Patients with metastatic breast cancer (MBC) receiving palbociclib, delivered in electronic monitors (EM), were randomized 1:1 to an intervention and a control group. The intervention was a 12-month interprofessional medication adherence program (IMAP) along with monthly motivational interviews by a pharmacist. Implementation adherence was compared between groups using generalized estimating equation models, in which covariates were included. Model-based palbociclib PK and neutrophil profiles were simulated under real-life implementation scenarios: (1) optimal, (2) 2 doses omitted and caught up at cycle end. At 6 months, implementation was slightly higher and more stable in the intervention (n = 19) than in the control (n = 19) group, 99.2% and 97.3% (Δ1.95%, 95% CI 1.1–2.9%), respectively. The impact of the intervention was larger in patients diagnosed with MBC for >2 years (Δ3.6%, 95% CI 2.1–5.4%), patients who received >4 cycles before inclusion (Δ3.1%, 95% CI 1.7–4.8%) and patients >65 (Δ2.3%, 95% CI 0.8–3.6%). Simulations showed that 25% of patients had neutropenia grade ≥3 during the next cycle in scenario 1 versus 30% in scenario 2. Education and monitoring of patient CDK4/6i cycle management and adherence along with therapeutic drug monitoring can help clinicians improve prescription and decrease toxicity. Full article

In this work, the evaluation of electromagnetic effect of Ultra High Frequency Radio Frequency Identification (UHF-RFID) passive tags used in the healthcare environment is presented. In order to evaluate exposure levels caused by EM field (865–868 MHz) of UHF-RFID readers, EM measurements in an anechoic chamber and in a real medical environment (Hospital Universitario de Canarias), as well as simulations by 3D Ray Launching algorithm, and of biophysical exposure effects in human models are presented. The results obtained show that the EM exposure is localized, in close vicinity of RFID reader and inversely proportional to its reading range. The EM exposure levels detected are sufficient to cause EM immunity effects in electronic devices (malfunctions in medical equipment or implants). Moreover, more than negligible direct effects in humans (exceeding relevant SAR values) were found only next to the reader, up to approximately 30% of the reading range. As a consequence, the EM risk could be firstly evaluated based on RFID parameters, but should include an in situ exposure assessment. It requires attention and additional studies, as increased applications of monitoring systems are observed in the healthcare sector—specifically when any system is located close to the workplace that is permanently occupied. Full article

Miniaturization trends in high-frequency electronics have led to accommodation challenges in the integration of the corresponding components. Size reduction thereof has become a practical necessity. At the same time, the increasing performance demands imposed on electronic systems remain in conflict with component miniaturization. On the practical side, the challenges related to handling design constraints are aggravated by the high cost of system evaluation, normally requiring full-wave electromagnetic (EM) analysis. Some of these issues can be alleviated by implicit constraint handling using the penalty function approach. Yet, its performance depends on the arrangement of the penalty factors, necessitating a costly trial-and-error procedure to identify their optimum setup. A workaround is offered by the recently proposed algorithms with automatic adaptation of the penalty factors using different adjustment schemes. However, these intricate strategies require a continuous problem-dependent adaptation of the penalty function throughout the entire optimization process. Alternative methodologies have been proposed by taking an explicit approach to handle the inequality constraints, along with correction-based control over equality conditions, the combination of which proves to be demonstrably competitive for some miniaturization tasks. Nevertheless, optimization-based miniaturization, whether using implicit or explicit constraint handling, remains a computationally expensive task. A reliable way of reducing the aforementioned costs is the incorporation of multi-resolution EM fidelity models into the miniaturization procedure. Therein, the principal operation is based on the simultaneous monitoring of factors such as quality of the constraint satisfaction, as well as algorithm convergence status. This paper provides an overview of the abovementioned size-reduction algorithms, in which theoretical considerations are illustrated using a number of antenna and microwave circuit case studies. Full article

The latest innovations in the field of electronics and telecommunications have revolutionised and brought new dimensions to human activities. As well as in other sectors, we observe that a wide range of electronic means have also shown their utility in criminal justice. Undergoing continuous development, these means ensure efficient monitoring of subjects and contribute to higher efficiency of judiciary systems, and provide “more humane” conditions compared with traditional incarceration for offenders when they execute criminal penalties. In this context, this study discussed the main challenges faced by Romania in implementing electronic monitoring (EM) devices in court proceedings and in the execution of criminal penalties. These have been researched from different perspectives, including those related to the current legal framework, opportunities provided by today’s developments in electronics, and in terms of financial public resources allocated for such purposes. Our study is among the few articles published on this topic and it brings to light both the advantages of introducing the Electronic Monitoring Information System (EMIS) in Romania, as well as the limitations, and overviews the international experience in this area by assessing the measures that have been taken so far worldwide to implement EMIS effectively. The final part of the paper presents the study conclusions, its limitations, and future lines of research. Full article

The use of fiber-reinforced composite materials has widely spread in various sectors, including aerospace, defense, and civil industry. The assessment of these heterogeneous material systems is important for safer and risk-free applications and has contributed to the need for self-sensing composites. This work is focused on the development of piezoresistive composites, the prediction of their performance and structural health monitoring (SHM). Additionally, this work unpacks the complexity of carbon nanotubes (CNTs) micro-fabrication and the development of piezoresistive and electromagnetic (EM) waves detection electrodes. Scanning electron microscopy (SEM) was used to characterize the CNTs structure and morphologies. The manufactured CNTs were incorporated in epoxy systems to fabricate glass fiber reinforced polymer (GFRP)-CNTs smart composites with piezoresistive properties. The detection of micro-damage onset and its progression was carried out in mode I, to evaluate the sensitivity of the smart composites to damage development. The change in electrical conductivity of the nanotubes-reinforced composite systems due to localized mechanical strains enabled crack propagation detection. The relationship between crack propagation, fracture toughness, and electrical resistivity of the smart composite was analyzed. Full article

The Internet of Things (IoT) has had a tremendous impact on the evolution and adoption of information and communication technology. In the modern world, data are generated by individuals and collected automatically by physical objects that are fitted with electronics, sensors, and network connectivity. IoT sensor networks have become integral aspects of environmental monitoring systems. However, data collected from IoT sensor devices are usually incomplete due to various reasons such as sensor failures, drifts, network faults and various other operational issues. The presence of incomplete or missing values can substantially affect the calibration of on-field environmental sensors. The aim of this study is to identify efficient missing data imputation techniques that will ensure accurate calibration of sensors. To achieve this, we propose an efficient and robust imputation technique based on k-means clustering that is capable of selecting the best imputation technique for missing data imputation. We then evaluate the accuracy of our proposed technique against other techniques and test their effect on various calibration processes for data collected from on-field low-cost environmental sensors in urban air pollution monitoring stations. To test the efficiency of the imputation techniques, we simulated missing data rates at 10–40% and also considered missing values occurring over consecutive periods of time (1 day, 1 week and 1 month). Overall, our proposed BFMVI model recorded the best imputation accuracy (0.011758 RMSE for 10% missing data and 0.169418 RMSE at 40% missing data) compared to the other techniques (kNearest-Neighbour (kNN), Regression Imputation (RI), Expectation Maximization (EM) and MissForest techniques) when evaluated using different performance indicators. Moreover, the results show a trade-off between imputation accuracy and computational complexity with benchmark techniques showing a low computational complexity at the expense of accuracy when compared with our proposed technique. Full article

Vaginal bleeding and abdominal pain are symptoms indicative of a threat to pregnancy that prompt women to seek assistance from health care professionals. The purpose of the study was to present the characteristics of Emergency Medical Services (EMS) team interventions in cases of suspected miscarriage. The study involved a retrospective analysis of EMS team interventions in cases of suspected miscarriage carried out between January 2018 and December 2019 in Poland. Data obtained from Poland’s National Monitoring Center of Emergency Medical Services included emergency medical procedure records and EMS team dispatch records in electronic format. The mean patient age was 30.53 years. Most were primiparous (48.90%) and up to the 13th gestational week (76.65%). The most commonly reported symptom was vaginal bleeding (80.71%). EMS teams were most commonly dispatched in the winter (27.03%), between 7 A.M. and 6:59 P.M. (51.87%), in urban areas (69.23%), with urgency code 2 (55.60%), and in most cases, they transferred the patient to a hospital (97.53%). The present study addresses very important issues concerning the characteristics of Polish suspected miscarriage cases handled by different EMS team types, in different locations (urban vs. rural areas), and concerning patients in a different obstetric situation (gestational week, gravidity, parity). Our findings suggest a need for further studies in this field and for gestational health promotion activities to be implemented, specifically including actions to reduce the risk of vaginal bleeding during pregnancy. Full article

Intelligent electronic devices (IEDs) along with advanced information and communication technology (ICT)-based networks are emerging in the legacy power grid to obtain real-time system states and provide the energy management system (EMS) with wide-area monitoring and advanced control capabilities. Cyber attackers can inject malicious data into the EMS to mislead the state estimation process and disrupt operations or initiate blackouts. A machine learning algorithm (MLA)-based approach is presented in this paper to detect false data injection attacks (FDIAs) in an IED-based EMS. In addition, stealthy construction of FDIAs and their impact on the detection rate of MLAs are analyzed. Furthermore, the impacts of natural disturbances such as faults on the system are considered, and the research work is extended to distinguish between cyber attacks and faults by using state-of-the-art MLAs. In this paper, state-of-the-art MLAs such as Random Forest, OneR, Naive Bayes, SVM, and AdaBoost are used as detection classifiers, and performance parameters such as detection rate, false positive rate, precision, recall, and f-measure are analyzed for different case scenarios on the IEEE benchmark 14-bus system. The experimental results are validated using real-time load flow data from the New York Independent System Operator (NYISO). Full article

Across the world, millions of people are incarcerated every year, while hundreds of thousands of them are released back into their home communities. Despite several alternatives within the criminal justice system, incarceration is still considered as the most natural method of correction. This can lead to different types of unsustainable pathways within a society. Despite the growing importance and increasing use of digital technologies, there are relatively few scientific studies related to the implementation of digital technologies in corrections. Therefore, the present paper aims to assess the sustainable policy measures based on the implementation of digital technologies in corrections, namely electronic monitoring (EM). The originality of our paper is supported by unique primary data gathered during the first national survey on the assessment of sustainability measures of EM in Slovakia. Our research reveals that EM implementation contributes to individual and institutional resilience in a socio-economic context; the requirements for a conditional release of serious offenders with mandatory EM seem to have created sustainable conditions for the use of this form of the EM “back door” scheme. EM programs are aimed at suppressing crime through increased accountability and monitoring, which leads to their sustainability. Maintaining social and family ties, reducing risk of imprisonment and undesirable new ties, and keeping working habits are the main sustainable policy measures of EM that support better social inclusion of offenders. Assessment of the sustainable policy measures based on the implementation of digital technologies in corrections, namely electronic monitoring (EM) uncovered in the present paper, creates space for further research and policy implications. Data protection, automated data processing and artificial intelligence in the implementation of digital technologies in corrections are important topics that deserve much more attention in research. Full article