Application Of Technology Research Articles

Possibilities and prospects of artificial intelligence in the treatment of colorectal cancer (review)

AIM: to study modern approaches to the application of machine learning and deep learning technologies for the management of patients with colorectal cancer.MATERIALS AND METHODS: after screening 398 publications, 112 articles were selected and the full text of the works was studied. After studying the full texts of the articles, the works were selected, machine learning models in which showed an accuracy of more than 80%. The results of 41 original publications were used to write this review.RESULTS: several areas have been identified that are the most promising for the use of artificial intelligence technologies in the management of patients with colorectal cancer. They are predicting the response to neoadjuvant treatment, predicting the risks of metastasis and recurrence of the disease, predicting the toxicity of chemotherapy, assessing the risks of leakage of colorectal anastomoses. As the most promising factors that can be used to train models, researchers consider clinical parameters, the immune environment of the tumor, tumor RNA signatures, as well as visual pathomorphological characteristics. The models for predicting the risk of liver metastases in patients with stage T1 (AUC = 0.9631), as well as models aimed at assessing the risk of 30-day mortality during chemotherapy (AUC = 0.924), were characterized with the greatest accuracy. Most of the technologies discussed in this paper are software products trained on data sets of different quality and quantity, which are able to suggest a treatment scenario based on predictive models, and, in fact, can be used as a doctor’s assistant with very limited functionality.CONCLUSION: the current level of digital technologies in oncology and in the treatment of colorectal cancer does not allow us to talk about a strong AI capable of making decisions about the treatment of patients without medical supervision. Personalized treatment based on the microbiotic and mutation spectrum and, for example, personal pharmacokinetics, so far look fantastic, but certainly promising for future developments.

Application of Non-Fuel Power Generation Technology in Steel Industry

Through continuous equipment technology transformation and full utilization of Ma Steel's abundant gas, the boiler no longer relies on fuel oil for stable combustion during boiler startup, sliding parameter shutdown, and RB, thus achieving safe and stable operation of the boiler under any abnormal working conditions, and achieving good economic and social benefits.

Application of Acoustic Emission Technology for Bearing Condition Monitoring on Passenger Ropeway

Rolling bearings are important stressed components of driving wheels and detour wheels on passenger ropeway, and their failure may lead to accidents and casualties. After the ropeway is installed and put into operation, the rolling bearings in the wheels are difficult to disassemble. Once disassembled, the bearing may be damaged. Due to the installation position and the complex operation environment, the health status of the rolling bearings is a blind spot for ropeway inspection and detection. Acoustic emission detection technology is used to monitor the rolling bearings of passenger ropeways. After a large number of field tests, the acoustic emission monitoring program and signal analysis method of rolling bearing on ropeway were proposed. The parameter characteristics of acoustic emission signals obtained in bearing operating were analyzed from two aspects: the ropeway operating cycle and the bearing operating cycle. Spectrum analysis of typical signals was performed, and the spectrum characteristics of typical acoustic emission signals of rolling bearing during the operation of the ropeway were obtained. On-site tests results show that using acoustic emission technology to perform condition monitoring and fault diagnosis of low-speed rolling bearings on passenger ropeways has good application prospects.

Research on the Spatio-temporal Coupling Relationship between Agricultural Green Development Efficiency and Food Security System in China

Food security and agricultural green development are fundamental issues concerning the survival of mankind. To realize the coordinated development of them is of great significance to promote the green transformation of agriculture and ensure national food security. However, few studies have analyzed the coupling relationship between agricultural green development and food security. Therefore, this study complements the research on the coupling relationship between them. First, we use the agricultural panel data of 31 provinces in China from 2010 to 2021 to measure the agricultural green development efficiency and food security level by Super-SBM model and entropy weight method. Then, the coupling relationship and spatiotemporal evolution of the two are analyzed by coupling coordination degree model. The results show that, first of all, China's agricultural green development efficiency and food security level have improved overall, but there are regional differences. Secondly, the degree of coupling and coordination between the two is significantly improved, and most provinces develop from the break-in stage to the coordination stage, and the regional differences are relatively reduced. Finally, Beijing, Shanghai and other developed areas are mostly of the lagging food security type, Liaoning, Shandong and other major grain producing areas have reached a high degree of coordination, while Tibet, Qinghai and other western regions are still in the break-in stage. According to the development situation of different regions, corresponding suggestions are put forward. For regions with lagging food security type, the government should give full play to the application of science and technology in agriculture and promote green and low-carbon planting technologies. For regions with low coupling and coordination degree, the government should improve support policies and build a collaborative operation system, adjust planting structure to improve land utilization rate and food security level. Finally, the government should work together to build agricultural industrial parks and give full play to the leading role of competitive provinces to achieve common development.

Research and Progress of Inorganic Infrared Electrochromic Materials and Devices.

Electrochromic materials can dynamically change their optical properties (such as transmittance, absorbance, and reflectance under the action of an applied voltage, and their research and application in the visible band have been widely concerned. In recent years, with the continuous development of electrochromic technology, the related research has been gradually extended to the infrared region. This invited review aims to provide an overview of the current status of several inorganic infrared electrochromic materials, to provide some references for future research, and to promote the research and application of electrochromic technology in the infrared region. This review summarizes various research results in the field of infrared electrochromic, which includes a detailed literature review and patent search. Starting from the key performance parameters and device structure characteristics of infrared electrochromic devices (ECDs), the research and progress of several types of inorganic infrared electrochromic materials, including metal oxides, plasma nanocrystals, and carbon nanomaterials, are mainly presented, and feasible optimization directions are also discussed. We believe that the potential of these materials for civilian and military applications, for example, infrared electrochromic smart windows, infrared stealth/disguise, and thermal control of spacecraft, can be fully exploited by optimizing the materials and their devices to improve their performance.

The synergistic effect of vertical structural parameters of vertical-type two-dimensional hole gas diamond MOSFETs on improving the overall performance of devices based on TCAD simulation

Vertical-type two-dimensional hole gas (2DHG) diamond metal-oxide-semiconductor field effect transistors (MOSFETs), featuring vertical geometry and typically p-channel, are poised for application in future logic technology, high-voltage and high-power miniaturization complementary circuits. P-channel achieving high breakdown voltage and low on-resistance can be realized through the use of p− drift layer, while a trench structure is shown to be beneficial for increasing the drain current density of vertical-type devices. However, the cumulative impact of these key parameters on the performance of vertical-type diamond MOSFETs remains unclear. In this paper, we explore the physical mechanism that how the key parameters design affects on off-state, breakdown and output characteristics has been simulated using Silvaco TCAD tools. We propose a vertical-type trench-gate 2DHG diamond MOSFET that is favorable for general integration applications and exhibits equivalent performance to the double-gate vertical structure without relying on a high concentration of nitrogen doped layer. This demonstrates that our work offers a universal approach for optimizing the comprehensive device performance in vertical-type structures, accounting for the effects of multiple parameters across all wide bandgap material-based FETs.

An Exploration of Organoid Technology: Present Advancements, Applications, and Obstacles.

Organoids are in vitro models that exhibit a three-dimensional structure and effectively replicate the structural and physiological features of human organs. This work examines the potential applications of organoid technology, as well as the challenges and future directions associated with its implementation. The manuscript was put together by conducting a comprehensive literature review, which involved an in-depth evaluation of globally renowned scientific research databases. The field of organoids has generated significant attention due to its potential applications in tissue development and disease modelling, as well as its implications for personalised medicine, drug screening, and cell-based therapies. The utilisation of organoids has proven to be effective in the examination of various conditions, encompassing genetic disorders, cancer, neurodevelopmental disorders and infectious diseases. The exploration of the wider uses of organoids is still in its early phases. Research shall be conducted to integrate 3D organoid systems as alternatives for current models, potentially improving both fundamental and clinical studies in the future.

Development of a decision support system for client acceptance in independent audit process

Intelligent Information Technology (IIT) applications are crucial in the audit process, enhancing quality, effectiveness, and efficiency. The client acceptance process (CAP), one of the critical audit steps, involves subjective evaluations where business managers' claims intersect with independent audit firm managers' expectations. This subjective nature introduces the potential for errors or misjudgments, impacting audit time and costs. In this paper, therefore, we propose a decision support system considering both auditors' subjective judgments and financial data variations for accepting or rejecting a client enterprise. The decision support system consisting of the Fuzzy Analytic Hierarchy Process (AHP), the logistic regression model, and the fuzzy inference system comprises four phases. In the first phase, a logistic regression model is developed using financial ratios to determine the client's probability of being in a close monitoring market (CMM) which represents publicly traded firms that are struggling to meet specific financial indicators or that are exposed to certain risks. In the second phase, the evaluation criteria used by the audit firm to measure the market reputation of the client enterprise are defined, and the weights of the evaluation criteria are obtained by using Fuzzy AHP. In the third phase, the Client Acceptance Score (CAS) representing market reputation of the client is calculated by incorporating the results of a reputation survey and applying the weights assigned to the evaluation criteria obtained in the second phase. Finally, client acceptance risk level (CARL) is obtained by using a fuzzy inference system and a rule-based defined by auditors. The CMM probability value and CAS score obtained in previous phases are used as input values of the fuzzy inference system. The CARL score guides the audit firm in deciding whether to engage with the client. To illustrate the applicability of the proposed model, a case study has been given in the paper.

The Concept of Electronic Pensioner in Some Countries Versus Romania

We aim to introduce the concept of e-pensioner (EP) with the intention of having this term used as a document within the European Union’s strategy on Artificial Intelligence (AI) for the period 2023-2027 and after implemented into the legislation of member countries. The relationship between older generations and emerging forms of digitalization and artificial intelligence is the focal point, aiming to provide an easily approachable dimension for pensioners. This article presents an analytical framework and approaches for integrating pensioners into the digital era. Following the exposition of theoretical foundations, the article delineates the use of pensioner cards in select countries worldwide. The intersection of pensioners with the digital era proves to be a fertile entry point for examining regulatory ordinances in the digital realm. A novel digital form, the AI-based digital portal, involves a technique of facial authentication for pensioners to send digital life certificates. Two key factors are named across all examined countries. The primary driver of digital transformation is propelled by the desire to enhance the efficiency and efficacy of public administration, which becomes particularly crucial as populations age, leading to increased demand for social services and competition for limited resources in the developed public sector. The innovative application of technology presents opportunities for streamlining processes, enhancing productivity, and reducing costs while concurrently improving service quality. The use of artificial intelligence (AI) in the management and administration of public pension funds stands for a natural progression of technology in the public domain. In an environment characterized by complexity and volatility, AI can provide a level of analysis and prediction that exceeds human ability. Presently, there exists a wide array of AI-powered tools for object detection, natural language processing, understanding and inference, optical character recognition, predictive analytics, anomaly detection, noise elimination, model forecasting, recommendation systems, and monitoring and observability.

The Curriculum in NDT Training Have to Include Basics Information Technology to Accomplish Reliability of Automated NDT Result's

Automation in Non-Destructive Testing (NDT) is a reality of modern manufacturing and quality assurance. Information technology applications are simultaneously developed and applied to different fields of NDT methods. The future of doing reliability checks using automated system is inevitable. The results are important to make a variety of decisions regarding the quality of a product and/or service, hence affecting safety and reliability. Depending on artificial intelligence and quantum device development, various NDT training schemes have to adopt a new curriculum to address the issue of the basic knowledge of information technology and automation in NDT. NDT operators are basically dependent on the end results of software, in which the software developer uses a set of algorithms. These are obtained in three categories; 1) Real time database; 2) Synthetic database and 3) Hybrid or combination of them. The developers should know how the NDT systems run and NDT operators in the other hand know the mechanism of the program, so that appropriate action can be taken, in case there is a missed detection, or a detected indication is not very much detrimental to the reliability of the part (Over sizing or wrongly evaluated). For example, a set of algorithms are used to create the focal laws in a phased array ultrasonic test software in space of 1˚ beam steering. Each has a limit of maximum up to 2nd Critical angle. Operators try to copy the same algorithm and set up to 89˚ refraction angle, which will just create creep wave with unreliable results to detect effective size the reflector. Programming knowledge of the operator can effectively eliminate this type of unreliability. In various Schemes of NDT Syllabus which are in common place to employ and train plus certify operators does not have it; actually, the operators do the scope of work which does includes application of Artificial Intelligence (AI) and Software. With the development of Q coupler (Quantum Computing) system, it is obvious to adopt the upcoming technology into the application of NDT industry. Training needs to update the curriculum accordingly. The current topic has intended to focus on the training gap and to address related kind of unreliability.

Research design and production of ambient atmosphere monitoring control system internet of things technology application

In this paper, presents solutions to application internet of things (IoT) technology in the field of high-tech agriculture, livestock in Vietnam is currently a new problem. The system includes an application on a smartphone; access the parameters via the web, on the computer. The product has a monitoring function: the ambient atmosphere indicators of the pig farm (temperature, humidity, CO<sub>2</sub>, NH<sub>3</sub>, H<sub>2</sub>S gas, and Biogas pressure), on the website 24/24 hour and control automatic control monitoring system. This is a problem of researching, designing and manufacturing products to automatically control the quality of the ambient atmosphere to improve productivity and quality of pig raising in practice at Bach Khoa Production, Trade and Service Joint Stock Company Bach Phuong (Address: Vinh Hao Commune, Vu Ban District, Nam Dinh Province, Vietnam).

Human Action Recognition System Using LRCN

Abstract: The importance of human action recognition is significant across various domains, driving advancements in safety, healthcare, sports analytics, and interactive technologies. Leveraging machine learning techniques like Long Recurrent Convolutional Neural Networks (LRCN) trained on datasets such as UCF50, our project focuses on action prediction from YouTube videos. This technology plays a pivotal role in enhancingsafety and security by enabling the detection of anomalies and suspicious behaviours in surveillance systems. In healthcare, it supports remote patient monitoring, rehabilitation assessment, and personalized care plans based on observed actions. Addi- tionally, in sports analytics and entertainment, human action recognition informs performance evaluation, content creation, and immersive experiences. Our integration of a pre-trained LRCN model into a Flask web application signifies the tangible impact of machine learning on human action recognition, with ongoing efforts to optimize functionality through input validation, error handling, user feedback, security measures, and performance enhancements, illustrating the practical application and societal benefits of this innovative technology

Design and Implementation of Autonomous Vehicle Using Computer Vision

Abstract: In transportation sector there are many technological foundations, applications, and challenges in present days. Autonomous vehicles, equipped with artificial intelligence and machine learning, can perceive their environment, make decisions, and execute actions without constant human intervention. They have transformative potential across various sectors, including manufacturing, healthcare, transportation, agriculture, and space exploration. Autonomous vehicles can streamline processes, enhance efficiency, improve safety, and assist in surgical procedures and patient monitoring. However, challenges such as safety, ethical considerations, job displacement, and regulatory frameworks must be addressed for their widespread adoption.

Technological advancements in drilling: A comparative analysis of onshore and offshore applications

This paper examines the technological advancements in onshore and offshore drilling operations, emphasizing their significance, challenges, and environmental considerations. Technological innovations, including automation, data analytics, and real-time monitoring, have transformed drilling practices, enhancing efficiency, safety, and environmental sustainability. By comparing onshore and offshore applications, the paper evaluates the effectiveness of these advancements in addressing the unique challenges of each environment. Key areas of focus include efficiency improvements, safety enhancements, environmental impacts, and regulatory compliance. Through case studies and analysis, the study aims to provide valuable insights into the current state of onshore and offshore drilling operations and identify opportunities for innovation and improvement. Ultimately, the findings contribute to advancing sustainable practices, mitigating environmental risks, and fostering responsible resource extraction in the oil and gas industry. This comparative study delves into the dynamic landscape of technological advancements within onshore and offshore drilling operations. It explores the evolving role of automation, data analytics, and real-time monitoring in revolutionizing drilling practices, offering insights into their implications for efficiency, safety, and environmental stewardship. By juxtaposing the unique challenges and operational requirements of onshore and offshore environments, the study underscores the importance of a nuanced understanding of technological applications. Through rigorous analysis and case studies, it illuminates the interplay between advancements and environmental considerations, shedding light on opportunities for innovation and sustainable development. The study's comprehensive scope encompasses efficiency gains, safety protocols, environmental impact mitigation, and regulatory compliance, providing a holistic view of the transformative potential of technology in the drilling industry. Ultimately, the study serves as a catalyst for informed decision-making, fostering dialogue, and driving forward-looking strategies for the future of onshore and offshore drilling operations.

Assessing the Applicability of Solar Thermal Technologies for Industrial Tea Drying

Most process heat being used for various industrial applications is supplied from fossil fuels. Coal, gas, and wood fuel are the most used heat resources which usually power steam boilers for production of heat used in a wide range of industrial processes. Since economic growth is largely linked to industrial production, it implies that, a shift towards use of clean energy technologies in industries is crucial to meet the rising demand of process heat while, cutting down carbon emissions to mitigate climate change. Solar thermal systems have over the past years shown potential as a practical alternative to fossil fuels for production of heat for several applications including, water and space heating, industrial process heating and electricity generation in thermal power plants. This study seeks to assess the feasibility of employing solar thermal technologies for drying purposes at Tingamira-Tanganda Tea estate in Zimbabwe. Systems advisor model (SAM) was applied to simulate performance of linear Fresnel (LF) and parabolic trough (PT) solar thermal technologies for industrial tea drying. Information on daily heat demand, required process temperatures and current heat sources was obtained to inform the design process of the proposed solar thermal systems. LF system exhibited better techno-economic performance. It requires a smaller collector area (360 m2) with a lower initial capital cost which is about 8% cheaper. Moreover, it produces higher annual energy at lower levelized cost of heat for solar multiples higher than 1. Carbon footprint of the factory would be reduced by about 114 tonnes CO2 annually. Sensible thermal energy storage technology can be considered for back up heat and heat recovery.

The emerging application of ultrasound technology in pediatric bone fractures: Clinical application, related issues and development prospect

AbstractUltrasonography has begun to be applied to the examination of fractures in recent years owing to its safety, noninvasiveness, portability, and high sensitivity. The subcutaneous soft tissue of children is thinner than that of adults, children's bones have a high level of elasticity and a low level of brittleness, and the pediatric fractures heal quickly and produce more callus, therefore ultrasonography is a more suitable examination in pediatric bone fractures. In this paper, we intend to review the mechanism, performance, and examination effect of ultrasound examination in bone fractures, analyze the advantages and disadvantages between ultrasound imaging and X‐ray imaging, and further propose an outlook for the application of ultrasound technology in pediatric bone fractures.

Enhancing CO2 Injection Efficiency: Rock-Breaking Characteristics of Particle Jet Impact in Bottom Hole

Storing CO2 in oil and gas reservoirs offers a dual benefit: it reduces atmospheric CO2 concentration while simultaneously enhancing oil displacement efficiency and increasing crude oil production. This is achieved by injecting CO2 into producing oil and gas wells. Employing particle jet technology at the bottom of CO2 injection wells significantly expands the bottom hole diameter, thereby improving CO2 injection efficiency and storage safety. To further investigate the rock-breaking characteristics and efficiency, a finite element model for particle jet rock breaking is established by utilizing the smoothed particle hydrodynamics (SPH) method. Specifically, this new model considers the high temperature and confining pressure conditions present at the bottom hole. The dynamic response and fracturing effects of rock subjected to a particle jet are also revealed. The results indicate that particle jet impact rebound significantly influences the size of the impact crater, with the maximum first principal stress primarily concentrated on the crater’s surface. The impact creates a “v”-shaped crater on the rock surface, with both depth and volume increasing proportionally to jet inlet velocity and particle diameter. However, beyond a key particle concentration of 3%, the increase in depth and volume becomes less pronounced. Confining pressure is found to hinder particle impact rock-breaking efficiency, while high temperatures contribute to larger impact depths and breaking volumes. This research can provide theoretical support and parameter guidance for the practical application of particle impact technology in enhancing CO2 injection efficiency at the bottom hole.

Loom: A Modular Open-Source Approach to Rapidly Produce Sensor, Actuator, Datalogger Systems

In the face of rising population, erratic climate, resource depletion, and increased exposure to natural hazards, environmental monitoring is increasingly important. Satellite data form most of our observations of Earth. On-the-ground observations based on in situ sensor systems are crucial for these remote measurements to be dependable. Providing open-source options to rapidly prototype environmental datalogging systems allows quick advancement of research and monitoring programs. This paper introduces Loom, a development environment for low-power Arduino-programmable microcontrollers. Loom accommodates a range of integrated components including sensors, various datalogging formats, internet connectivity (including Wi-Fi and 4G Long Term Evolution (LTE)), radio telemetry, timing mechanisms, debugging information, and power conservation functions. Additionally, Loom includes unique applications for science, technology, engineering, and mathematics (STEM) education. By establishing modular, reconfigurable, and extensible functionality across components, Loom reduces development time for prototyping new systems. Bug fixes and optimizations achieved in one project benefit all projects that use Loom, enhancing efficiency. Although not a one-size-fits-all solution, this approach has empowered a small group of developers to support larger multidisciplinary teams designing diverse environmental sensing applications for water, soil, atmosphere, agriculture, environmental hazards, scientific monitoring, and education. This paper not only outlines the system design but also discusses alternative approaches explored and key decision points in Loom’s development.

Practices to Improve the Sustainability of Australian Cold Storage Facilities

With the ever-increasing threat of climate change and global warming, ways to make energy intensive buildings, such as cold storage warehouses essential for food preservation, more sustainable need to be found. Some refrigerated warehouse owners may be unaware or unsure of the benefits obtainable from implementing sustainable practices and technologies. To search for innovations that could inform the owners and managers of cold storage warehouses about how to enhance their sustainability, convergent interviewing of subject matter experts was conducted. The resulting practices and processes were organized into a hierarchy that ranged from essential to best practices that can be implemented to improve the sustainability of refrigerated warehouses. Examples of these practices and technologies include ideal refrigeration systems, racking methods, and insulation types. To encourage the use of sustainable practices and technologies, more reporting on successful or unsuccessful applications of practices and technologies needs to be communicated. Applying change diagnostic tools such as convergent interviewing enables a practical and industry focused set of outcomes to be determined that can help drive change towards more sustainable cold storage warehouses in Australia.

Advancing LED technology: the FDCSP element’s breakthrough in mini and micro-LED packaging and backlight module enhancement

In this research, we introduce an advanced methodology for the calculation of bulk light sources tailored for free-form surface design, focusing on the principle of energy conservation. This method is especially relevant for the evolving needs of micro-LED packaging, highlighting its potential in this burgeoning field. Our work includes the development of an algorithm for creating freeform-designed chip-scale package (FDCSP) components. These components seamlessly integrate LEDs and lenses, underscoring our commitment to advancing free-form surface design in chip-level packaging. By adhering to the principle of energy conservation, our approach facilitates a meticulous comparison of simulation outcomes with predefined target functions. This enables the iterative correction of discrepancies, employing layering techniques to refine the design until the simulated results closely align with our goals, as demonstrated by an appropriate difference curve. The practical application of these simulations leads to the innovative design of FDCSP devices. Notably, these devices are not just suitable for traditional applications in backlight modules but are explicitly optimized for the emerging sector of micro-LED packaging. Our successful demonstration of these FDCSP devices within backlight modules represents a significant achievement. It underscores the effectiveness of our design strategy and its expansive potential to transform micro-LED packaging solutions. This research not only contributes to the theoretical understanding of energy conservation in lighting design but also paves the way for groundbreaking applications in micro-LED and backlight module technologies.