Technical Overview Research Articles

Detection of Brain Tumor using Medical Images: A Comparative Study of Machine Learning Algorithms – A Systematic Literature Review

Abstract: Background: Brain tumors are a significant global health concern impacting both adults and children. Tumors are characterized by abnormal or excessive growth resulting from uncontrolled cell division. Diagnosing brain tumors poses various challenges, including limited funding, a shortage of qualified professionals, and insufficient access to medical facilities in remote regions. Different learning techniques for detecting brain tumors have been developed due to their ease of use, cost-effectiveness, and non-invasive nature, in contrast to other invasive methods. Methods: This research conducts a systematic literature review to explore modern trends and concepts of machine learning in healthcare, aiming to identify effective techniques for brain tumor detection. It also compares and analyzes the most efficient machine learning methods currently in use, focusing on aspects such as machine learning algorithms, image augmentation, evaluation metrics, and the sizes of datasets employed. Results: The findings indicate that non-invasive methods, such as machine learning algorithms for brain tumor detection, are cost-effective and provide quick results. Conclusions: This systematic literature review offers a technical overview, demonstrating the efficiency and effectiveness of machine learning techniques in making brain tumor detection feasible. The study utilizes deep learning and machine learning methods to comprehensively analyse diagnosis, imaging, and clinical evaluations in medical fields related to brain tumor detection.

Technical Overview of Pyro-processing and Policy Considerations

Pyro-processing is an emerging technology crucial to the implementation of a closed nuclear fuel cycle. It is distinguished by its method of extracting and recycling actinides from fission products in spent nuclear fuels, utilizing high-temperature molten salt media. Despite its promise, the technology poses proliferation concerns that underscores the imperative for robust safeguards. While the safeguarding framework for aqueous reprocessing facilities that has been established over decades offers a foundational reference, the unique challenges posed by Pyro-processing necessitate a tailored approach. Amid these concerns, Pyro-processing is heralded as a viable strategy for nuclear waste management, with research increasingly focusing on its selectivity and efficacy within molten salt systems. This paper scrutinizes the proliferation risks inherent in Pyro-processing, delineates the requisite safeguards, and evaluates the feasibility of Pyro-processing, especially within the purview of the 123 Agreements between the United States and South Korea.

SPARC x-ray diagnostics: Technical and functional overview.

An overview is given of SPARC's three main x-ray diagnostics, with a focus on the functions they fulfill with respect to tokamak operation. The first is an in-vessel soft x-ray tomography diagnostic, aimed at providing early campaign information on plasma position, MHD activity, and impurity content. The second is an ex-vessel set of hard x-ray scintillators aimed at detecting the presence of runaway electrons, in particular during plasma startup phases. The third is a set of x-ray Bragg spectrometers, located outside of the tokamak hall, aimed at informing on the ion temperature as an indirect constraint to reduce uncertainties on the fusion power, on providing plasma rotation velocity estimates, and on observing impurity emission. Finally, more technical details are given on the beamlines at the end of which the spectrometers are located. It explains how their design allows us to ensure tritium containment and limit neutron radiation while providing a straight view into the plasma that can also be used for testing new innovative sensors.

Ultrasound-guided percutaneous liver biopsy: A review of what operators need to know.

Ultrasound-guided percutaneous liver biopsy (UG-PLB) is a commonly performed procedure for the diagnosis and monitoring of various liver diseases. The objective of this article is to present the most important information relating to UG-PLB from the perspective of interventional radiologists in a clear and concise fashion, referencing the most influential papers in current literature. This paper gives a brief overview of the history of the procedure and its conception, as well as the most common indications, contraindications, complications, and a technical overview of the most common techniques and equipment that are used by UG-PLB operators.

Exploring the impact of HCI on smart buildings: A comprehensive literature review on user experience and sustainability

This paper provides insights into the application of human-computer interaction (HCI) principles in the field of smart building design, particularly their impact on improving occupant comfort, building energy efficiency, and the user interaction experience. The research context focuses on advances in HCI and the importance of smart buildings in enhancing quality of life and sustainability. The research theme focuses on how HCI principles can be utilized to improve the user interface design of smart buildings in order to promote more effective user-building system interactions. Through an extensive review of existing literature in the area of HCI and smart buildings, including recent research papers, case study reports, and technical overviews, this study concentrates on analyzing examples of HCI applications in smart lighting, temperature control systems, and energy management. Through this comprehensive literature review, this paper aims to illustrate how HCI principles can provide theoretical and practical guidance for the design of more humanized, interactive and environmentally friendly smart buildings, thereby providing insights and recommendations for future smart building design and research.

Air computing: A survey on a new generation computation paradigm

There is an ever-growing race between what novel applications demand from the infrastructure and what the continuous technological breakthroughs bring in. Especially after the proliferation of smart devices and diverse IoT requirements, we observe the dominance of cutting-edge applications with ever-increased user expectations in terms of mobility, pervasiveness, and real-time response. Over the years, to meet the requirements of those applications, cloud computing provides the necessary capacity for computation, while edge computing ensures low latency. However, these two essential solutions would be insufficient for next-generation applications since computational and communicational bottlenecks are inevitable due to the highly dynamic load. On the other hand, inadequate infrastructure considering rural areas and disaster sites makes the utilization of those solutions difficult. Therefore, a 3D networking structure using different air layers including Low Altitude Platforms, High Altitude Platforms, and Low Earth Orbits in a harmonized manner for both urban and rural areas should be applied to satisfy the requirements of the dynamic environment. In this perspective, we put forward a novel, next-generation paradigm called Air Computing that presents a dynamic, responsive, and high-resolution computation environment for all spectrum of applications. In this survey, we define the components of air computing, investigate its architecture in detail, and discuss its essential use cases and the advantages it brings for next-generation application scenarios. We provide a detailed and technical overview of the benefits and challenges of air computing as a novel paradigm and spot the important future research directions.

On the Making of IXPE

Drs. Weisskopf and Ramsey were the original Principal and Deputy Principal Investigators of the Imaging X-ray Polarimetry Explorer (IXPE). They outline the path to the development of IXPE and discuss the technical and programmatic history that led up to the mission, a partnership between the Italian Space Agency and NASA, and the first fully dedicated to imaging X-ray polarimetry in the 2–8 keV band. An admittedly biased, as seen through the eyes of the original and Deputy Principal Investigators, technical overview of the development of the historical and critical scientific instrumentation is provided. The outstanding, and often paradigm-shifting results are presented in the papers following this one.

State of the Art on Forensic Bridge Engineering in Chile. A Management and Technical Overview

Chile is a country highly affected by natural hazards, especially scour and seismic phenomena. Therefore, throughout the twentieth century and the beginning of the twenty-first, total or partial collapses of bridges have been evidenced, particularly those that occurred in the 1960 and 2010 earthquakes. From these experiences, the Chilean Highway Administration has promoted a series of management activities in order to reduce the number of collapsed structures. In this context, since 2019 the Ministry of Public Works of Chile (MOP) supported by the Chilean universities started a program to develop the subject of forensic engineering on bridges, in order to include the methodology in the technical codes and provide a standardization of protocols for the implementation of activities in the case of the collapse of structures. The aspects included in this methodology are: Determination of volatile and non-volatile information; Actions for intervention on the structure and protection of users; Gathering of technical information through the application of tests; Review of stress–strain states through Finite Element Method (FEM); Elaboration of hypotheses and review of them through a decision tree; and, finally, Conclusions and recommendations from a technical and contractual perspective. This paper presents a detailed description of the current forensic engineering methodology in Chile and its first application in the Cancura Bridge case study. In addition, a historical compilation of Chilean bridge collapses is presented, in each case identifying the typology of the structure, the causes of collapse and the main inspection techniques used. Finally, a statistical review is carried out analyzing aspects such as stages of the life cycle where collapse has occurred: design, construction or operation, and the incidence of natural hazards in these phenomena. From this analysis, the cases of Loncomilla, Cancura and Huasco bridges are highlighted. Since the collapse of these bridges occurred without the implementation of current methodology, the article concludes on the advantages and disadvantages of the methodology, providing a comparative analysis with the inspection activities in these structures.

Advances and Challenges in Meta-Learning: A Technical Review.

Meta-learning empowers learning systems with the ability to acquire knowledge from multiple tasks, enabling faster adaptation and generalization to new tasks. This review provides a comprehensive technical overview of meta-learning, emphasizing its importance in real-world applications where data may be scarce or expensive to obtain. The article covers the state-of-the-art meta-learning approaches and explores the relationship between meta-learning and multi-task learning, transfer learning, domain adaptation and generalization, self-supervised learning, personalized federated learning, and continual learning. By highlighting the synergies between these topics and the field of meta-learning, the article demonstrates how advancements in one area can benefit the field as a whole, while avoiding unnecessary duplication of efforts. Additionally, the article delves into advanced meta-learning topics such as learning from complex multi-modal task distributions, unsupervised meta-learning, learning to efficiently adapt to data distribution shifts, and continual meta-learning. Lastly, the article highlights open problems and challenges for future research in the field. By synthesizing the latest research developments, this article provides a thorough understanding of meta-learning and its potential impact on various machine learning applications. We believe that this technical overview will contribute to the advancement of meta-learning and its practical implications in addressing real-world problems.

Canadian Senate Reform: Lessons from Its First Decade, 1867–78

During the 19th century and through the 20th century, the role of the parliamentary upper house (especially, but not exclusively, within the Westminster system of government) changed in subtle, yet dramatic, ways. Among those changes was increasing deference to elected lower houses of parliament, a reduction in partisanship in its actions and legislative goals, the development and pursuit of greater specialization of interest and function, appeals to the public interest beyond the electoral mandate, and greater practical attention to technical overview and improvement of legislation and policy, especially through the engagement of the committee process. This article argues that the role of the current Senate of Canada is a result of that historical transformation and was evident as early as the first decade of its existence (consistent with an institutional evolution that continues through the 21st century) and should be strongly considered in relation to current and future proposals for its reform.

The Decision to Discipline the Employee with Some References to Its Communication through Online Means of Communication. Elements of Comparative Law

Domestically, the field of labour discipline is a complex one, both in terms of legislation and case law. In order to provide a better understanding of how these regulations are implemented in practice, this article reviews some theoretical and practical issues concerning the validity of the decision to discipline an employee, with a focus on the doctrinal and jurisprudential problems identified with regard to the time limit within which the employer may issue the disciplinary decision, the content of the disciplinary decision, the individualisation of the disciplinary sanction in relation to the conclusions of the Disciplinary Committee, and the communication of disciplinary decisions by online means. In addition, in order to provide a clearer technical and legislative overview of the regulations on the issuing of a sanctioning decision, the regulations of other countries are also relevant to this objective, and comparative law elements will be closely examined. Thus, the legal systems of France, Cyprus, the United Kingdom and Georgia are considered.

Technical overview of the main types, designs, and materials of brake pads for mobile agricultural machinery

Brake pads are a critical element of any machine, as they directly affect the safety of its use. Accordingly, the quality of brake pads, their resistance, and durability are key aspects that must be considered when developing braking systems for mobile agricultural machinery. The purpose of this study was to review scientific sources related to the study of the tribological properties of brake pads, their operating modes, and friction materials included in brake linings. The main parameters affecting the efficiency of brake pads were analysed and the main criteria for selecting materials for brake pads of mobile agricultural machinery were defined, namely, wear resistance, temperature resistance, and corrosion resistance. Accordingly, the materials used in the production of brake pads for such equipment must be capable of operating under any conditions, have high thermal conductivity, help reduce the wear rate, have a stable friction coefficient, and be environmentally friendly. The study focused on an overview of the types and design of brake pads, their systematisation by various features (by purpose; by design features; by friction material composition; by the presence of wear sensors) and composition (semi-metallic, non-asbestos organic, and ceramic). The study described modern components of friction materials for brake linings and found that they are usually composites formed by hot pressing coarse powders, which include many different components: a binder (thermosetting phenolic resins, often with rubber added), structural materials (metal, carbon, glass, and/or Kevlar fibres), fillers (mica and vermiculite), and friction additives (graphite and various metal sulphides). The study also assessed the main characteristics of friction material components used in the manufacture of brake linings. The findings of this study can provide researchers and scientists with useful information on the types and design of brake pads and the main materials used in the manufacture of brake linings and be useful for further practical development of braking mechanisms

24‐1: Visible Difference Predictors: A Class of Perception‐Based Metrics

The Visible Difference Predictors are a class of data driven, white box, efficiently implemented image or video difference metrics. They model important aspects of perception like spatial and temporal vision, foveation, and more, and are calibrated on datasets relevant for display and graphics applications. In this paper, we present a historic retrospective of VDPs, and a high‐level technical overview and comparison to other metrics in the literature. Finally, we put forward a practical guide for selecting the appropriate metric for a given engineering problem and discuss how metrics can be effectively combined with subjective testing for high‐confidence assessments.

P52. Chondrolaryngoplasty: A Technical Overview and Measure of Outcomes Over A 5-year Period at a Metropolitan Medical Center

P52. Chondrolaryngoplasty: A Technical Overview and Measure of Outcomes Over A 5-year Period at a Metropolitan Medical Center

Using multi-way correspondence analysis to examine the Nobel Prize data in STEM related disciplines

There are two purposes of this paper. The first, and primary, purpose is to examine the association between the Country of nationality, the Discipline, and Time period of Nobel Prize laureates in the Science, Technology, Engineering, and Mathematics (STEM) related disciplines. This is done by performing a multi-way correspondence analysis (MWCA). The second purpose is to provide a technical, bibliographic and practical overview of MWCA. Our investigation of the variables shows that there is a statistically significant three-way association between them, as well as between only one pair of the variables: Country and Time period. The row-tube biplot provides a visual description of this association.

Large language models could change the future of behavioral healthcare: a proposal for responsible development and evaluation

Large language models (LLMs) such as Open AI’s GPT-4 (which power ChatGPT) and Google’s Gemini, built on artificial intelligence, hold immense potential to support, augment, or even eventually automate psychotherapy. Enthusiasm about such applications is mounting in the field as well as industry. These developments promise to address insufficient mental healthcare system capacity and scale individual access to personalized treatments. However, clinical psychology is an uncommonly high stakes application domain for AI systems, as responsible and evidence-based therapy requires nuanced expertise. This paper provides a roadmap for the ambitious yet responsible application of clinical LLMs in psychotherapy. First, a technical overview of clinical LLMs is presented. Second, the stages of integration of LLMs into psychotherapy are discussed while highlighting parallels to the development of autonomous vehicle technology. Third, potential applications of LLMs in clinical care, training, and research are discussed, highlighting areas of risk given the complex nature of psychotherapy. Fourth, recommendations for the responsible development and evaluation of clinical LLMs are provided, which include centering clinical science, involving robust interdisciplinary collaboration, and attending to issues like assessment, risk detection, transparency, and bias. Lastly, a vision is outlined for how LLMs might enable a new generation of studies of evidence-based interventions at scale, and how these studies may challenge assumptions about psychotherapy.

Hydrogen energy storage integrated grid: A bibliometric analysis for sustainable energy production

Hydrogen energy storage and grid integration are emerging as key technologies for efficient energy generation and decarbonization, addressing the unpredictability of renewable sources like wind and solar. Hydrogen serves as a flexible energy carrier, enabling storage and conversion back to energy, and supporting various applications. Since there is a lack of bibliometric investigation in the grid-connected hydrogen energy storage system, this review conducted the bibliometric analysis and analyzed the role of hydrogen in enhancing grid-connected systems' sustainability and flexibility, based on data from the Scopus database. The principal search terms that have been used to identify the publications are “Hydrogen AND Storage AND ("Grid-connected" OR "On-grid" OR “Grid-tied” OR “Integrated grid” OR “Grid integration”)” and several keywords have also been utilized in the filter including “Hydrogen Storage”, “Hydrogen”, “Hydrogen Production” and “Grid-connected”. The chosen documents type is only comprised of ‘Article’ and ‘Review’. By conducting an analysis of publication trends, citation patterns, co-authorship, and keyword usage, significant and informative observations regarding the development of grid-connected hydrogen storage system research from 2013 to 2023 (up until November) were unveiled. Notably, 86.55% of the articles focused on simulation study, while the rest are focusing in experimental work, reviews, and technical overview of integrated-grid hydrogen storage system. China is establishing itself as prominent participant, while International Journal of Hydrogen Energy is recognized as a notable medium for distributing research on the integrated-grid hydrogen storage system. Compressed hydrogen tank emerges as a prominent type of storage because of its less energy requirement to increase the density of hydrogen that allow more efficient transportation for hydrogen. The review also underlines numerous factors, issues, challenges, and difficulties that next-generation hydrogen energy storage production should overcome with regards to system sustainability.

Richard Raspet's contributions to our understanding of low-frequency wind noise

Richard Raspet's research in wind noise spanned three decades and took the acoustics community from a rudimentary understanding of how low-frequency wind noise is generated in pressure sensors to a firm theoretical understanding derived from first principles in fluid dynamics. This talk will present a technical overview of his work starting with early quantitative studies, progressing through the development of the theoretical framework for wind noise studies, and finishing with a summary of research including wind noise at the ground surface, wind noise under tree canopies, wind fences, and wind induced seismic noise.

Human Activity Recognition Using Inertial Sensors in a Smartphone: Technical Background(Review)

Human Activity Recognition (HAR) stands at the intersection of machine learning, deep learning, and sensor technology, primarily focusing on leveraging inertial sensors in smartphones and wearable devices. This paper presents a comprehensive technical overview of HAR, examining the amalgamation of machine learning and deep learning systems while considering the data inputs from mobile and wearable inertial sensors. The review encompasses a broad spectrum of methodologies applied to HAR, ranging from classical machine learning algorithms to cutting-edge deep learning architectures. Emphasis is placed on the nuanced challenges and opportunities posed using inertial sensors in smartphones and wearables. This includes discussions on data preprocessing strategies, feature extraction methods, and model architectures, accounting for the unique characteristics of sensor data, such as noise, variability, and power consumption. The paper explores recent advancements, scrutinizing state-of-the-art approaches, innovative model architectures, and emerging trends in HAR. Through a comparative evaluation of various machine learning and deep learning techniques, the review aims to guide researchers and practitioners in selecting the most appropriate methods for HAR applications across diverse scenarios. In conclusion, this paper serves as an inclusive guide to the technical landscape of HAR, incorporating insights from both mobile and wearable inertial sensors. By synthesizing existing knowledge and addressing future research directions, it aims to propel advancements in developing robust and efficient systems for recognizing human activities, accommodating the evolving landscape of sensor technologies in mobile and wearable devices.

Reducing the Environmental Impact of Large Battery Systems with Conductive Electric Road Systems—A Technical Overview

A radical transformation of the transport industry is required in order to achieve a fossil-fuel-free vehicle fleet and reach the greenhouse gas emissions goals. Electrification plays a crucial role in this radical process. An electric road system (ERS) is a road that supplies power to electric vehicles as they drive on it, offering numerous advantages. These include an extended driving range, decreased reliance on batteries, and increased flexibility and convenience for drivers, eliminating the need to stop for recharging. This paper highlights the transformative potential of ERS in revolutionizing the land transport sector. Through thorough testing with a conductive ERS demonstrator, the viability of the presented technology is validated. Essential aspects like power transfer, efficiency, safety, and environmental impact showcase ERS’s adaptability and scalability across diverse vehicle types. This study recommends widespread ERS support for battery electric vehicles, emphasizing the route toward a sustainable future.