Development Of Technology Research Articles

Automated Fingerprint Identification System

Abstract: AFIS is regarded as one of the greatest advancements in biometric systems as it enables fast and efficient identification of an individual by their distinct fingerprint designs. This system employs the use of digital imaging, finger-power techniques and other technologies in the storage and comparison of fingerprints. With AFIS, fingerprint images are all digitized making it easier to carry out crime investigations, border control and general identification of persons. The strength of AFIS systems is evidenced by the increased accuracy levels along with the capacity to accommodate numerous records and still allow for fast searches by fingerprinting matching to existing images for law enforcement on file. Some problems nevertheless persist which include the quality of fingerprints and environmental interferences, however machine learning and artificial intelligence improvements are still being incorporated into the systems to make them work even better. This paper investigates the system architecture and components, operational aspects, and prospects for development of the AFIS technology, which is essential in contemporary informational security

Research on the Correlation between Quantum Entanglement and Thinking Consciousness

The development of quantum technology has profoundly influenced research on consciousness. By analyzing the interaction of various microscopic particles in the universe, the article proposed that all things exhibit interconnected non-locality in both time and space, and that the interrelated connections of everything in the universe are based on quantum entanglement. Through analysis of the cellular and nervous system functions of organisms, as well as the influence of quantum science theories on consciousness and combined with research results in related fields, this paper presents the following viewpoints: first, life bodies exhibit quantum entanglement phenomena. Second, biological electricity phenomena are closely tied to consciousness. Third, both life bodies and non-life bodies are conscious, but different entities exhibit varying degrees of strong and weak consciousness. The strong and weak thinking consciousness influences the fluctuation of quantum and the size of quantum entanglement degree. Quantum fluctuations affect the consciousness of both life bodies and non-life bodies, and the entanglement quantum influences the degree of inductance between each other. Finally, the combination of quantum entanglement technology and thinking consciousness can realize the interconnection between human beings and the universe. Consciousness may affect the results measured in quantum mechanics when people observe. However, the macroscopic world mainly adopts the laws of classical physics to solve problems in life. Under certain conditions, the law of quantum physics and the law of classical physics can affect people’s lives together. No matter what angle we view the material world, it is real, and the universe is not illusory.

Comparative analysis of Environmental Impact of Each Building Material using Life Cycle assessment(LCA)_Focusing on Types of Construction Wood and Concrete

Objectives:The construction sector is a very important sector in achieving carbon neutrality. In modern society, construction has grown rapidly, and basic materials such as cement and concrete have contributed greatly to the development of construction. These materials emit a large amount of global warming substances during the raw material extraction and production process, causing serious environmental pollution. In order to establish a carbon reduction strategy to slow down global warming, we compared the environmental impacts of each building material and showed the current situation.Methods:The LCI DB for the construction materials used in the two-story wooden house (Building area 128.67m2, total floor area 235.73m2) located in the National Institute of Forest Science was extracted. Then, the data for LCA was processed and performed through the life cycle assessment methodology for the resources consumed from raw material collection, material production, and transportation stages. Then, based on the environmental performance labeling impact assessment method, a study was conducted on the environmental impact categories of the actual construction materials used and comparisons with other construction materials.Results and Discussion:When analyzing the environmental impact of concrete [25-21-120] and construction wood used in wooden house, the environmental impact was found to be 98.79% higher on average in the pre-manufacturing stage than in the manufacturing stage, and construction wood was confirmed to have a reduction effect of 62.21 kg CO2-eq per 1 m3 compared to concrete. Through the scenario, there was a carbon reduction effect of up to 36% when the entire area was replaced with wood. In addition, the environmental impact by major construction material was quantitatively quantified.Conclusion:When building a wooden house, reducing the amount of concrete equivalent to the amount of wood is expected to have a greenhouse gas reduction effect, so it is time to activate construction wood from the production process to the post-production stage to replace concrete. In addition, follow-up research on the development of construction technology with low environmental impact during construction should be continued. This study is expected to be used as a useful indicator for R&D and policies in the construction field in the future, as it quantitatively quantified the amount of CO2 reduction per m3 when replacing concrete with construction wood and numerically compared and analyzed six major environmental impact categories by major construction materials.

PENGEMBANGAN USAHA PADA UMKM YU MIN BATIK & BUTIK DESA SIDOREJO KECAMATAN COMAL KABUPATEN PEMALANG

<table width="576" border="1" cellspacing="0" cellpadding="0"><tbody><tr><td width="402"><p>The Micro, Small and Medium Enterprises that are the object are the UMKM Yu Min Batik & Boutique owned by Mrs. Siti Aminah which is located in Sidorejo Village, Comal District, Pemalang Regency. This MSME operates in the field of clothing and modified batik cloth in Pemalang. The aim of implementing this activity is to develop business, good financial management and production performance. The business assistance provided includes marketing aspects. The efforts made by the accompanying team aim to promote Yu Min Batik & Boutique products through MSME activities such as bazaars and catalog content on online social media. This is due to increasingly sophisticated technological developments and seeing many entrepreneurs, especially MSMEs, promoting their businesses through online social media. The aim is to introduce and attract the interest of potential customers by understanding the individual characteristics of consumers so that the products sold will match their wishes.</p><p>The assistance method used is carrying out several programs such as making banners, making simple bookkeeping, Google maps, participating in MSME bazaar activities, making direction boards, making organizational structures, business profiles, and creating social media (Instagram). After analyzing and applying the program to Yu Min Batik products, it produced a positive impact on MSME owners. Such as introducing products through promotions on social media and placing banners, organizational structures, understanding simple bookkeeping, business profiles, and installing direction boards to fulfill product requirements to support promotions so that people have more confidence in the products they want to buy.<strong></strong></p></td></tr></tbody></table>

A critical Review on Advanced Membrane Bioreactors for Wastewater Treatment: Fouling Reduction and Energy Demand

Objectives:Rapid industrialization has highlighted the importance of addressing environmental issues and the increasing demand for water supply. As a result, innovative solutions to improve water circulation management in both public and industrial sectors have been proposed, one of which is the introduction of Membrane Bioreactor (MBR) technology. This study aims to understand the mechanisms and characteristics of membrane fouling in MBR processes and compare the associated energy consumption, with the goal of improving process efficiency and energy performance.Methods:In this study, various factors influencing the MBR process were considered to analyze the mechanisms and characteristics of membrane fouling. The impact of fouling on the process was assessed, and energy consumption was compared. Specifically, the power consumption of flat-sheet and hollow-fiber MBRs was analyzed, focusing on the proportion of energy used for microbial treatment and membrane cleaning. The Specific Energy Demand (SED) was calculated to evaluate the energy consumption efficiency of different fouling control methods in MBRs.Results and Discussion:In typical MBR processes, 68.0% (flat-sheet) and 53.0% (hollow-fiber) of the power consumption is attributed to air scouring for microbial treatment and membrane cleaning. Notably, 57.0% (flat-sheet) and 36.0% (hollow-fiber) of the power is consumed to supply air for detaching adhered foulants to maintain filtration performance. These results indicate that aeration is a major energy consumer in MBR processes. SED is a critical indicator for assessing the energy consumption of specific fouling control methods, with typical MBR processes having an SED of 0.2-0.3kWh/m3. In contrast, using a non-aerated membrane module with reciprocating inertial force for fouling control reduces SED to 0.005-0.01 kWh/m3, representing a 20-60 fold decrease in energy consumption, highlighting the need for energy reduction.Conclusion:This study provides insights into fouling reduction characteristics in MBR processes, suggesting a new paradigm for enhancing the economic feasibility of MBR technology. Applying non-aerated membrane modules to reduce energy consumption can significantly improve MBR efficiency, contributing to energy reduction and environmentally friendly technology development. Therefore, strategies to maximize energy efficiency and minimize environmental impact in MBR processes are essential.

Automation and innovation in home hemodialysis machines.

In this review, we discuss the timeline of innovation and technologic development in home hemodialysis (HHD) in the United States and the legislative approvals that accompanied them. The most recently FDA-approved home hemodialysis devices provide features that include on-demand and batch dialysate generation, access disconnect for venous needle dislodgement, touchscreen interface with visual and auditory prompts and animations, drop-in sterilized cartridges with prestrung tubing, hot water disinfection of tubing allowing extended-use, dialysate flow rates as high as 500 ml/min, as well as remote treatment monitoring capabilities. Furthermore, wearable/portable dialysis devices are currently under development to simplify dialysis delivery to patients with end-stage kidney disease. Home hemodialysis devices providing longitudinal hemodialysis across different clinical settings, virtual reality headsets for more personalized training, automated patient support, as well as wearable device development and innovations give hope for a future where home hemodialysis is more accessible and seamless.

Exploring the mediating role of brand trust in the impact of digital marketing and online reviews on purchase decisions for beauty products: A case study on students in solo

The rapid development of information and communication technology has significantly altered the way consumers interact with brands. In the digital era, digital marketing has emerged as a primary strategy for companies to reach consumers and promote their products. The beauty industry, in particular, has undergone a major transformation, with digital marketing and online reviews playing crucial roles in influencing consumer purchasing decisions. This study focuses on exploring the mediating role of brand trust in the relationship between digital marketing, online reviews, and beauty product purchasing decisions among university students in Solo, Indonesia. The research aims to provide insights into how brand trust, as influenced by digital marketing and online reviews, impacts consumer behavior. The findings are expected to help beauty brands in enhancing their digital marketing strategies and improving brand trust among young consumers.

Telemedicine and telehealth

Regular hospital visits can be expensive due to travel costs, especially in rural areas. Fortunately, when telemedicine services are used through video conferencing or other virtual technologies, doctor visits can be reduced. Therefore, telemedicine saves the patient and the medical staff time and treatment costs. In addition, with its fast and efficient operations, it can simplify the workflow of hospitals and clinics. This innovative technology makes it easier to monitor discharged patients and manage their recovery. In conclusion, it is enough to say that telemedicine can create a win-win situation. The purpose of this article is to examine the main trends, treatment workflow characteristics, and barriers to the use of telemedicine in healthcare. As a new technology, telemedicine is preferred by large hospitals. With the development of Internet technology, digitization and information have been applied to telemedicine, but telemedicine still has many limitations due to many factors. This article summarizes the evolution of telemedicine. The development of telemedicine at home and abroad was discussed. The use of telemedicine was explored including the feasibility and limitations of commercialization and development. and provide a vision for the integration of these technologies into the medical field has resulted in the telephone, which is now available worldwide. This article presents telemedicine in three main areas, including current status, challenges and opportunities based on research and implementation. he integration of these technologies into the medical field has resulted in the telephone, which is now available worldwide. This article presents telemedicine in three main areas, including current status, challenges and opportunities based on research and implementation.

The use of artificial intelligence in the education of people with visual impairment

Over the past decades, technological advances have led to the development of assistive technologies in the field of education. Specifically, in special education, access for people with a disability may require adaptations to educational programs and technological applications to enhance their independence and participation in society. One of these innovative educational technologies is artificial intelligence. Research has shown that the effective application of artificial intelligence is an important aid in the education of students with special educational needs, such as those with visual impairments. This article presents a brief review of recent studies on the application of AI in the education of people with visual impairments and whether it can contribute to improving their quality of life and their equal access to all levels of education. It also provides a case study, the "PeopleLens" system, for an in-depth analysis of the use of AI as an assistive technology.

СОВЕРШЕНСТВОВАНИЕ СПОСОБА ПОЛУЧЕНИЯ УСНИНОВОЙ КИСЛОТЫ ИЗ РАСТИТЕЛЬНОГО СЫРЬЯ ИСЛАНДСКОГО МХА

Relevance. Contemporary pharmaceutical industry requires constant search and development of new technologies for the production of pharmacological products. At the same time, the processing of plants, which contain substances with a therapeutic effect, is a promising direction. Their use in terms of economic and therapeutic effectiveness is sometimes very beneficial. It has been proven that lichen plants contain substances that have a therapeutic effect. Organisms of the genus Cladonia, which synthesize usnic acid, among them have a special significance and application. The extraction of usnic acid from lichen biomass is carried out using various organic solvents. At the same time, it is preferable to use techniques with the lowest cost with a high quantitative yield of extractives. In addition, extracts containing bioactive substances should exhibit significant biological activity. The aim is improving the technology of extraction of usnic acid from the vegetable raw materials of Cladonia rangiferina Hoff by determining the optimal components for its extraction. Materials and methods. The material for the study is raw material of Yagel (Deer Moss)/Cladonia rangiferina Hoff. The extractive properties of the most commonly used solvents (purified water, ethyl alcohol 40, 70 and 95%) were studied, among which the most effective was identified. The content of extractive substances was determined by the gravimetric analysis method. The results of the study. According to the results of a series of experiments to study extractive capabilities, of all solvents, the maximum extractive ability of extractive substances from Cladonia rangiferina Hoff was noted for 95% ethyl alcohol (7.38%). Ethyl alcohol 70% was produced with a high extraction capacity, however, it turned out to be less effective. The conclusion was made about these methods can be used to detect biologically active substances obtained from the raw materials of Cladonia rangiferina Hoff. The obtained developments create prerequisites for the development of regulatory documentation on the procedure and position of the relevant standard or a temporary pharmacopoeia article.

Development of a demulsifier and technological process study for the preparation of highly viscous heavy oils for refinement

One of the challenges in the petroleum industry is the production of highly viscous heavy oils, often accompanied by undesirable emulsion formation with very high aggregate stability. To prepare the crude oils for refinement, the oils must be destroyed. The destruction of aqueous emulsions containing highly viscous heavy oils is an intricate task owing to the comparatively small disparity in water and oil densities, as well as the high viscosity of the dispersive medium and its high content of mechanical impurities. The problem of the destruction of petroleum emulsions arises desperately during the desalination and dehydration of crude oils with a high content of emulsifiers (resins, asphalts, paraffin, etc.) The creation of a highly efficient demulsifier and the development of an optimal technological process for the preparation of highly emulsifying oils that are distinguished by the composition and quantity of emulsifiers of West Siberian oils, which are widely refined in Russia, are the ways to resolve this challenging and timely issue. This study focuses on the viscous heavy oil of the Verbliouje deposit in the Astrakhan region. It also explains the creation of an effective demulsifier for the destruction of petroleum emulsions characterized by a very high emulsifying power and the fundamental principles of the development of deep dehydration technology and desalination of such high-viscosity heavy oils.

The Role of Sentiment Analysis in Machine Translation- A Review on the Example of ChatGPT

In today’s globalization, machine translation technology has become an indispensable bridge for cross-lingual communication. The integration of sentiment analysis makes machine translation not only able to convey information, but also able to accurately express and understand the emotional color of the original text, which is of great significance in the fields of cross-cultural communication, customer service, and social media interaction. This study overviews the development of machine translation technology, from early rule-based models to modern statistical models to Transformer-based neural network models, with a special focus on the integrated application of ChatGPT in sentiment analysis and machine translation. First, this study introduces the background and research significance of machine translation, and discusses the role of sentiment analysis in improving translation quality and user satisfaction. Subsequently, the historical development of machine translation technology is reviewed in detail, and the basic concepts and methodologies of sentiment analysis and its applications in different fields are elaborated. On this basis, this study analyzes in depth the technical architecture, language model and interaction capability of ChatGPT, as well as its specific application and performance in sentiment analysis. Further, this study explores the importance of sentiment analysis in machine translation, including sentiment recognition, translation strategies for sentiment expression, and the impact of sentiment analysis on improving translation quality and cultural adaptability. Meanwhile, the advantages and limitations of ChatGPT in sentiment analysis are assessed, and future research directions are proposed, including technology convergence, construction of datasets and evaluation criteria, and ethical and bias issues. Finally, this study summarizes the practical application value of sentiment analysis in machine translation and looks forward to the potential areas of future research, aiming to provide reference and inspiration for the further development of machine translation and sentiment analysis.

Deep Learning and Human-machine Integration in Smart Prosthetic Control: Process and Perspectives

With the rapid development of science and technology and the maturity of deep learning technology, intelligent prosthetic limb control has made significant progress in human-machine integration. While traditional prosthetic technology has seen improvements in form and function, it still faces challenges in user experience and physiological adaptability. Deep learning, with its powerful pattern recognition and decision-making capabilities, offers new possibilities to address these issues. This paper reviews the current status and future development of the application of deep learning in intelligent prosthetic limb control, emphasizing its close relationship with the concept of human-machine integration. Intelligent prosthetic control involves not only mechanical engineering and bioengineering, but also interdisciplinary integration of the fields of neural engineering, electrical engineering, motion control and computer science. This paper reviews the limitations in traditional prosthetic technology, such as accuracy and user adaptability, introduces the successful cases and latest research results of deep learning in the medical field, and explores the potential of deep reinforcement learning in optimizing complex movements and adapting to different environments. Finally, the future direction of deep learning technology in smart prosthetic limb control is envisioned, and research challenges and recommendations are presented in the hope of providing theoretical support for the innovative development of smart prosthetic limb technology and improving the quality of life of people with disabilities.

Innovative Application of Optoelectronic Control Engineering for Safety Assurance of Surgical Robots

As an emerging technology, optoelectronic control engineering has demonstrated a wide range of application potential in surgical robot safety and security. Through a literature review, this paper provides an in-depth discussion on the innovative applications of optoelectronics technology in enhancing the positioning accuracy, environment sensing, supple control and remote operation of surgical robots. At the same time, this paper summarizes the current research hotspots and future research directions, with a view to providing a reference for promoting the technological progress in this field. The current research focuses on improving the operating precision of surgical robots, enhancing the environment sensing ability and the application of force feedback system, while the future research will mainly focus on interdisciplinary cooperation and new technology development.

Research of Optical Fiber Sensing Technology in Bridge Detection

Fiber optic sensing technology is a new type of detection technology that realizes information transmission through total reflection of light and photoelectric conversion. It has been used in the fields of medicine, military, communication, transportation, industrial control, scientific research, etc., especially in the field of bridges for decades.This paper summarizes the research status of optical fiber sensing technology and optical fiber in bridge detection, and reviews the application of optical fiber in bridge detection. First, this paper introduce the optical fiber technology, its working principle and application advantages. Secondly, the feasibility of optical fiber sensing technology in bridge detection is demonstrated through concrete application cases. It includes the detection of bridge structure and the detection of bridge material structure. Through the optical fiber sensing technology, this paper can detect the hidden dangers of the bridge in a timely and non-destructive manner Finally, this paper prospect the future development of optical fiber technology in the field of bridge detection.

Applications of Graphene Materials in Optoelectronic Devices

Graphene is a groundbreaking material at the forefront of material science and nanotechnology area. Graphene exhibit special qualities, including great mechanical strength, strong electrical conductivity and thermal conductivity. Consequently, the optical property of graphene is focused in this work. The excellent optical properties of graphene make it a good candidate material for optoelectronic devices. In recent years, a great deal of research has been conducted on the use of graphene for optoelectronic devices. Therefore, conducting research in this field is of great significance. In this work, researches are analyzed and studied to gain new insights into this area. In addition, a summary of the prevalent synthesis methods utilized for the production of graphene is provided, accompanied by a detailed examination of the merits and demerits associated with each technique. Finally, the applications of graphene materials in optoelectronic devices are discussed in depth to further understand the development status of graphene materials. This work seeks to generate new ideas and directions for the future development of optoelectronic technology.

Optimization Analysis of Low-Noise Amplifier

This paper mainly analyzes the important component of a wireless receiver – low-noise amplifiers (LNA). Low-noise amplifiers can reduce the effect of noise on the received signal and amplify signals. For the better development of wireless communication technology, remote control, and other related fields, it is necessary to optimize the design of low-noise amplifiers, so that low-noise operational amplifiers can finally obtain high gain, low noise figure, and other advantages. This paper analyzes the optimization design of LNA in the field of Global Navigation Satellite Systems (GNSS). This paper analyzes a low-noise amplifier design with the operation of concurrent dual-band for GNSS receivers with a single channel. The optimized design of a low-noise amplifier in this field uses a low-cost 0.18µm CMOS tube and adds load capacitances and a feedforward path to reduce the noise figure (NF) of the system. Noise figures in 1.2 GHz and 1.57 GHz bands are reduced by about 0.9 dB. In addition, the high gain, high linearity, and other excellent properties are shown in 1.2 GHz and 1.57GHz. In the application of 5G/6G network technology, the optimized design of Gallium Arsenide (GaAs) PHEMT technology with a gate length of 0.3µmm and inductively degraded common source topology phase structure is adopted. From this optimization, the noise figure is optimized to 1.3-1.4, and the gain of the system is 20-22 dB. At the same time, good linearity is also shown. Then, the prospects of semiconductor materials such as Gallium Nitride (GaN) and Indium Phosphide (InP), which have the advantages of high electron mobility and low-cost design, in optimizing low noise operational amplifiers. To a certain extent, the in-depth study of the optimal design of LNA can improve the technical level of wireless communication, aerospace, and other fields.

A Review of Deep Learning Based Object Detection Algorithms

With the rapid development of artificial intelligence technology, the traditional manual feature-based object detection method has been gradually replaced by deep learning-based object detection technology. Object detection is the basis and prerequisite for many computer vision tasks aimed at recognizing targets in an image and determining their class and location. The purpose of object detection algorithm research based on deep learning is to improve the detection accuracy and detection speed of the detection algorithm, so that the object detection algorithm can be more safe and convenient applied to People's Daily production and life. This article reviews the evolution of object detection algorithms, focusing on two-stage, one-stage and object detection algorithms based on the transformer architecture. In addition, the performance, advantages and disadvantages of different algorithms are compared, and the development trend of object detection algorithms based on deep learning is summarized in the end.

Systematic Analysis on The Development and Potential Use of Novel Semiconductors

Silicon-based transistors and integrated circuits, crucial for modern technology, are facing limitations due to scaling constraints. As transistors shrink, their performance is capped, affecting advanced technologies like AI, IoT, and 5G. Gallium nitride (GaN), with a melting point 200°C higher than silicon, presents a promising alternative due to its superior high-power and high-frequency performance. This essay reviews silicon’s semiconductor limitations and highlights the advancements in silicon carbide and Gan. The basic theories, such as electron mobility, energy level and covalent bond, are analyzed, and it is found that GaN is better than Sic and Si, but the three examples of semiconductors have different development fields in different fields. It compares the benefits of traditional silicon with these novel semiconductors, focusing on high-frequency and high-temperature performance. The essay also discusses current development, issues, and future predictions in semiconductor technology. Exploring new materials like GaN and silicon carbide addresses the technical challenges of silicon and enhances device performance, broadening technological possibilities.

Application of Artificial Intelligence Technology in New Energy Vehicles

Due to environmental pollution caused by excessive exploitation of world resources, countries are now advocating for green travel, which has led to the rapid development of the new energy vehicle industry. Compared to traditional cars, the safety, maneuverability, and convenience of new energy vehicles have made the application of artificial intelligence technology increasingly widespread in this field. Therefore, this article provides a systematic review and analysis of the application of artificial intelligence technology in new energy vehicles. Firstly, the article outlined the main application scenarios of artificial intelligence in the field of new energy vehicles, including autonomous driving, energy management optimization, vehicle intelligent interconnection, and predictive maintenance. On this basis, this paper analyzed the role of artificial intelligence technology in improving the performance, safety, and reliability of new energy vehicles, as well as the technological challenges and development trends it faces. For example, issues such as data privacy protection and real-time performance need to be further addressed. In the future, artificial intelligence and new energy vehicles will further integrate, making important contributions to achieving intelligent, green, and safe future travel.