Automation 5.0: The Key to Systems Intelligence and Industry 5.0

AUTOMATION has come a long way since the early days of mechanization,i.e.,the process of working exclusively by hand or using animals to work with machinery.The rise of steam engines and water wheels represented the first generation of industry,which is now called Industry Citation:L.Vlacic,H.Huang,M.Dotoli,Y.Wang,P.Ioanno,L.Fan,X.Wang,R.Carli,C.Lv,L.Li,X.Na,Q.-L.Han,and F.-Y.Wang,“Automation 5.0:The key to systems intelligence and Industry 5.0,”IEEE/CAA J.Autom.Sinica,vol.11,no.8,pp.1723-1727,Aug.2024.

Efficient and Secure IoT Based Smart Home Automation Using Multi-Model Learning and Blockchain Technology

The concept of smart houses has grown in prominence in recent years.Major challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the device itself.Current home automation systems try to address these issues but there is still an urgent need for a dependable and secure smart home solution that includes automatic decision-making systems and methodical features.This paper proposes a smart home system based on ensemble learning of random forest(RF)and convolutional neural networks(CNN)for programmed decision-making tasks,such as categorizing gadgets as“OFF”or“ON”based on their normal routine in homes.We have integrated emerging blockchain technology to provide secure,decentralized,and trustworthy authentication and recognition of IoT devices.Our system consists of a 5V relay circuit,various sensors,and a Raspberry Pi server and database for managing devices.We have also developed an Android app that communicates with the server interface through an HTTP web interface and an Apache server.The feasibility and efficacy of the proposed smart home automation system have been evaluated in both laboratory and real-time settings.It is essential to use inexpensive,scalable,and readily available components and technologies in smart home automation systems.Additionally,we must incorporate a comprehensive security and privacy-centric design that emphasizes risk assessments,such as cyberattacks,hardware security,and other cyber threats.The trial results support the proposed system and demonstrate its potential for use in everyday life.

Automatic modulation recognition of radio fuzes using a DR2D-based adaptive denoising method and textural feature extraction

The identification of intercepted radio fuze modulation types is a prerequisite for decision-making in interference systems.However,the electromagnetic environment of modern battlefields is complex,and the signal-to-noise ratio(SNR)of such environments is usually low,which makes it difficult to implement accurate recognition of radio fuzes.To solve the above problem,a radio fuze automatic modulation recognition(AMR)method for low-SNR environments is proposed.First,an adaptive denoising algorithm based on data rearrangement and the two-dimensional(2D)fast Fourier transform(FFT)(DR2D)is used to reduce the noise of the intercepted radio fuze intermediate frequency(IF)signal.Then,the textural features of the denoised IF signal rearranged data matrix are extracted from the statistical indicator vectors of gray-level cooccurrence matrices(GLCMs),and support vector machines(SVMs)are used for classification.The DR2D-based adaptive denoising algorithm achieves an average correlation coefficient of more than 0.76 for ten fuze types under SNRs of-10 d B and above,which is higher than that of other typical algorithms.The trained SVM classification model achieves an average recognition accuracy of more than 96%on seven modulation types and recognition accuracies of more than 94%on each modulation type under SNRs of-12 d B and above,which represents a good AMR performance of radio fuzes under low SNRs.

Enhancing Adaptability, Nutritional Quality in Tropical Tuber Crops: Source for Adaptive Food and Nutrition

The tropical roots and tuber crops (R and T) consist of cassava, sweet potato, yams, elephant foot yam, taro, tannia and a couple of minor tuber crops. Tropical tuber crops are the third most important food crops after cereals and pulses. These crops play a crucial role in providing food and nutritional security to the rural masses in Africa, Latin America and parts of Asia. Cassava and sweet potato rank among the top 10 food crops produced in developing countries and contribute to about 6% of world’s dietary calories. In India, tropical tubers are grown mostly in states like Odisha, West Bengal, Andhra Pradesh, Kerala, Tamil Nadu, Bihar and North East covering 4.5% of the total area under vegetables with 5.7% of the total vegetable production. Low income farmers and most undernourished households in India depend on R and T crops. They value these crops for their high calorie and stable yields under conditions in which other crops may fail. Genetic diversity of major tropical tuber crops provides options for its diverse usage in “multicuisine”, “nutrition”, “feed”, health care” and renewable resources of processing firms. Water productivity is also higher, for example, to produce 1 kg of tubers, sweet potatoes require water (383 l), taro (606 l), yam (343 l), as compared to rice (1673 l), maize (1222 l), wheat (1827 l), etc. Tuber crops are one of most efficient producers of dry matter and edible energy. These crops have potential to reverse soil degradation. Cassava is already recognized as drought tolerant followed by yam. Tubers of taro, elephant foot yam and yams can be stored under zero energy conditions for 6 - 7 months unlike temperate potatoes in cold storage. The natural climatic resilience as well as inherent nutrition attributes, has been explored further. Such studies made these crops more robust to changing climate and as the source of nutrient enriched food bowls. Sweet potato variety Bhu Krishna is the first purple flesh variety in India containing (90 mg/100 g anthocyanin) coupled with starch 22% - 25%. Similarly, the orange flesh Bhu Sona containing beta carotene (14 mg/100 g) coupled with high starch 22% - 24% is the first variety having both high beta carotene and high starch. These varieties are tolerant to salinity and Bhu Krishna is resistant to weevil. Likewise, developed improved taro varieties resistant to biotic blight stress, tolerant to salinity and are enriched with micro nutrients. These improved varieties are used to breed the superior types further. All these climate resilient, nutritionally enriched varieties will have a greater impact on supplementing rainbow food for all. These can address the issues like “food insecurity”, “malnutrition”, diet related issue of mass consumers across the world. The analysis of innovations on enhancing adaptability, nutritional quality with a management matrix would help in strengthening future programme.

基于Automation Studio仿真软件的液压与气动技术人才培养实践

通过对《液压与气动技术》课程在教学过程中的问题盘点,总结出教学中存在的实验资源少、设备陈旧、成本高、利用率低等痛点,Automation Studio仿真软件具有强大的系统仿真与动画设计功能,有针对液压与气动及电气系统的功能模块,将Automation Studio仿真软件引入课堂教学可以很好的弥补上述问题,利用液压气动系统与电气系统的仿真功能,设计相应的实践教学课程内容,分别对课前、课中、课后三个环节的具体实施过程及要求进行详细阐述,通过对软件的教、学、用达到提升课程教学效果的目的。

On the Adaptability Range, Self-Selection, and Economic Nature of Biological Evolution

This article employs a combined approach of biology and economics to reveal that biological evolution has an economic nature, evolving towards improved energy efficiency. The orthodox Darwinian theory of evolution describes evolution as the random variation of organisms and their survival through natural selection. In fact, the natural environment itself is a constantly changing context, and the strategy to adapt to this change is to enhance behavioral capabilities, thereby expanding the range and dimensions of behavior. Therefore, the improvement of behavioral capabilities is an important aspect of evolution. The enhancement of behavioral capabilities expands the range of adaptation to the natural environment and increases the space for behavioral choices. Within this space of behavioral choices, some options are more effective and superior to others;thus, the ability to select is necessary to make the improved behavioral capabilities more beneficial to the organism itself. The birth and development of the brain serve the purpose of selection. By using the brain to make selections, at least the “better” behavior will be chosen between two alternatives. Once the better behavior yields better results, and the organism can associate these results with the corresponding behavior, it will persist in this behavior. The persistent repetition of a behavior over generations will form a habit. Habits passed down through generations constitute a new environment, causing the organism’s genes to activate or deactivate certain functions, ultimately leading to genetic changes that are beneficial to that habit. Since the brain’s selection represents the organism’s self-selection, it differs from random variation;it is also a rational selection, choosing behaviors that either obtain more energy or reduce energy consumption. Thus, this evolution possesses an economic nature.

Physio-ecological adaptability and service function in karst rocky desertification control of Premna puberula

Increased soil erosion as a consequence of karst rocky desertification(KRD)reduces soil quality and plant diversity.Premna puberula Pamp.is a perennial understory shrub that can adapt to the harsh environment of KRD and has potential value for KRD environmental restoration.We measure morphological and photosynthetic characteristics,nutrient accumulation,and soil physical and chemical properties of two-year-old P.puberula planted in KRD habitat and non-rocky desertification areas,and investigate how it adapts to this habitat.In KRD areas,P.puberula reduces aboveground water loss by decreasing leaf area,stomatal conductance,and transpiration rate,while increasing leaf thickness,root length and number,and increases belowground biomass to absorb more water and nutrients.In KRD areas,drought leads to decreased leaf water content,stomatal conductance,intercellular CO_(2) concentration,and chlorophyll content,and decreased photosynthetic rate.Soluble sugar and protein contents increase in KRD areas in response to water stress,but pectin and flavonoid contents decrease.Correlation analysis reveals that leaf area and thickness are important functional traits that affect leaf water content and photosynthesis.Totals of leaf carbon,nitrogen,and phosphorus,along with C:N,C:P,and N:P ratios,are coupled with leaf photosynthetic characteristics and root development.Redundancy analysis reveals that available K and P,and total P,K,and N in soil mainly influence the differences in plant functional traits,explaining 95.8%,95.5%,91.1%,85.8%,and 74%of variation,respectively.We hypothesize that P.puberula reduces aboveground productivity to maintain its water balance,and acquires more water and nutrients by increasing belowground biomass.It indicates that this species adapts to arid KRD environments.

Deep learning automation of radiographic patterns for hallux valgus diagnosis

Artificial intelligence(AI)and deep learning are becoming increasingly powerful tools in diagnostic and radiographic medicine.Deep learning has already been utilized for automated detection of pneumonia from chest radiographs,diabetic retinopathy,breast cancer,skin carcinoma classification,and metastatic lymphadenopathy detection,with diagnostic reliability akin to medical experts.In the World Journal of Orthopedics article,the authors apply an automated and AIassisted technique to determine the hallux valgus angle(HVA)for assessing HV foot deformity.With the U-net neural network,the authors constructed an algorithm for pattern recognition of HV foot deformity from anteroposterior highresolution radiographs.The performance of the deep learning algorithm was compared to expert clinician manual performance and assessed alongside clinician-clinician variability.The authors found that the AI tool was sufficient in assessing HVA and proposed the system as an instrument to augment clinical efficiency.Though further sophistication is needed to establish automated algorithms for more complicated foot pathologies,this work adds to the growing evidence supporting AI as a powerful diagnostic tool.

Intelligent Metal Detection and Disposal Automation Equipment Based on Geometric Optimization Driving Algorithm

In order to solve the problem of metal impurities mixed in the production line of wood pulp nonwoven raw materials,intelligent metal detection and disposal automation equipment is designed.Based on the principle of electromagnetic induction,the precise positioning of metal coordinates is realized by initial inspection and multi-directional re-inspection.Based on a geometry optimization driving algorithm,the cutting area is determined by locating the center of the circle that covers the maximum area.This approach aims to minimize the cutting area and maximize the use of materials.Additionally,the method strives to preserve as many fabrics at the edges as possible by employing the farthest edge covering circle algorithm.Based on a speed compensation algorithm,the flexible switching of upper and lower rolls is realized to ensure the maximum production efficiency.Compared with the metal detection device in the existing production line,the designed automation equipment has the advantages of higher detection sensitivity,more accurate metal coordinate positioning,smaller cutting material areas and higher production efficiency,which can make the production process more continuous,automated and intelligent.

基于Automation Studio的液压动力滑台控制系统仿真设计

动力滑台是组合机床实现进给运动的通用部件,其控制系统是实现组合机床自动化或半自动化的关键环节。在分析动力滑台工作过程及液压控制回路的基础上,基于Automation Studio进行了控制系统仿真设计,主要包括液压系统建模、PLC控制系统建模及软件设计,仿真结果满足各种控制要求。

Application and Adaptability of Ornamental Grasses in Road Flower Borders in Hefei, Anhui Province

In-depth research was conducted on the types,seasonal patterns,spatial levels,overwintering,summering,drought resistance,and disease and pest resistance of ornamental grasses in the road flower borders of Hefei,Anhui Province.Through field investigations,a total of 36 ornamental grasses were identified,with Liliaceae having the most species and the Lamiaceae the least.The results show that there are more warm season ornamental grasses,of 23 species;Acorus gramineus and Melinis minutiflora have poor overwintering ability;Arrhenatherum elatius,Festuca glauca,and Stipa tenuissima have poor summer tolerance;most ornamental grasses have strong drought resistance and resistance to pests and diseases.The comprehensive investigation shows that ornamental grasses have good application prospects and adaptability in the road flower borders in Hefei city.

Intelligent Decision-Making in Warehouse Management: How AI Automation Improves Inventory Tracking, Order Fulfillment, and Logistics Efficiency Compared to Drone Technology

This paper analyzes how artificial intelligence (AI) automation can improve warehouse management compared to emerging technologies like drone usage. Specifically, we evaluate AI’s impact on crucial warehouse functions—inventory tracking, order fulfillment, and logistics efficiency. Our findings indicate AI automation enables real-time inventory visibility, optimized picking routes, and dynamic delivery scheduling, which drones cannot match. AI better leverages data insights for intelligent decision-making across warehouse operations, supporting improved productivity and lower operating costs.

A Home Automation Control System Based on LabVIEW

The objective of this project is to explore the possibility of using X-10 and LabVIEW to control the device in the house. Based on the serial port communication of LabVIEW, the X-10 module can be programmed by using the X-10 commands. Through the power line, all the devices connected to the socket will be controlled. Without replacing the existing wire, it must be an easy control system for the user who has no experience in electronics or communication engineering. Actually, this is a quite practical X-10 home automation system.

Robotic Process Automation with New Future Trends

The invention concept of Robotic Process Automation (RPA) has emerged as a transformative technology that has revolved the local business processes by programming repetitive task and efficiency adjusting the operations. This research had focused on developing the RPA environment and its future features in order to elaborate on the projected policies based on its comprehensive experiences. The current and previous situations of industry are looking for IT solutions to fully scale their company Improve business flexibility, improve customer satisfaction, improve productivity, accuracy and reduce costs, quick scalability in RPA has currently appeared as an advance technology with exceptional performance. It emphasizes future trends and foresees the evolution of RPA by integrating artificial intelligence, learning of machine and cognitive automation into RPA frameworks. Moreover, it has analyzed the technical constraints, including the scalability, security issues and interoperability, while investigating regulatory and ethical considerations that are so important to the ethical utilization of RPA. By providing a comprehensive analysis of RPA with new future trends in this study, researcher’s ambitions to provide valuable insights the benefits of it on industrial performances from the gap observed so as to guide the strategic decision and future implementation of the RPA.

Optimizing Two-Phase Flow Heat Transfer:DCS Hybrid Modeling and Automation in Coal-Fired Power Plant Boilers

In response to escalating challenges in energy conservation and emission reduction,this study delves into the complexities of heat transfer in two-phase flows and adjustments to combustion processes within coal-fired boilers.Utilizing a fusion of hybrid modeling and automation technologies,we develop soft measurement models for key combustion parameters,such as the net calorific value of coal,flue gas oxygen content,and fly ash carbon content,within theDistributedControl System(DCS).Validated with performance test data,thesemodels exhibit controlled root mean square error(RMSE)and maximum absolute error(MAXE)values,both within the range of 0.203.Integrated into their respective automatic control systems,thesemodels optimize two-phase flow heat transfer,finetune combustion conditions,and mitigate incomplete combustion.Furthermore,this paper conducts an in-depth exploration of the generationmechanismof nitrogen oxides(NOx)and low oxygen emission reduction technology in coal-fired boilers,demonstrating a substantial reduction in furnace exit NOx generation by 30%to 40%and the power supply coal consumption decreased by 1.62 g/(kW h).The research outcomes highlight the model’s rapid responsiveness,enabling prompt reflection of transient variations in various economic indicator parameters.This provides a more effective means for real-time monitoring of crucial variables in coal-fired boilers and facilitates timely combustion adjustments,underscoring notable achievements in boiler combustion.The research not only provides valuable and practical insights into the intricacies of two-phase flow heat transfer and heat exchange but also establishes a pioneering methodology for tackling industry challenges.

Design and Implementation of Enterprise Office Automation System Based on Web Service Framework & Data Mining Techniques

The advancement of science and technology has introduced the concept of big data, which has significantly transformed the business management environment of enterprises. Currently, most administrative tasks in companies heavily rely on human resources, with skilled management staff using their expertise to oversee business operations. However, this approach is susceptible to human subjective biases. The method assists managers in formulating efficient strategies for implementing management measures and enhancing the effectiveness of production, sales, financial, and people organization structure management. This ultimately leads to a more evidence-based approach to corporate management. This technique expands the utilization of Web services from a strategy focused on integrating services to a comprehensive framework for Service-Oriented Computing (SOC). The primary focus is implementing WS-session to manage sessions in general Web services applications, defining a bidirectional entire duplex interface for communication in Web services, and developing the Web Services Initiation Protocol, presenting WIP, a thorough multimedia and voice communication framework constructed using Web services and Service-Oriented Architecture (SOA). The office automation management system, created utilizing ASP.net and SQL Server technology, encompasses the evaluation of viability, analysis of needs, and system design. Office automation refers to using equipment with computing capabilities to carry out various office tasks and utilize associated tools and applications. Office automation uses computer-based systems to collect, organize, and modify visual and auditory information to enhance business energy efficiency and time management. Office automation refers to auto-mating essential tasks employees perform, including identification, automatic appointment reminders, and automatic power management for personal computers. The employee image is obtained through the utilization of the Java media framework. Attendance data for all employees are collected and methodically examined. The database enables the retrieval of these records monthly or weekly. An office automation system offers organizations enhanced features for managing office information, significantly improving office efficiency and quality. Moreover, it improves office administration and decision-making procedures by automating and strengthening the scientific elements of office functions. The ongoing progress of organizational information technology has led to a strong focus on sharing information resources in scientific research initiatives. Conventional firms exhibit intricate company processes, inadequate managerial efficacy, and unnecessarily elevated operational expenses, resulting in diminished competitiveness. Thus, using an ERP management system is the optimal decision for organizations to restore their crucial competitive advantage. This technology enhances their operational methods, streamlines their operations, and enhances transparency in their operational approaches. The system comprises six modules: buy plan, purchase order, purchase contract, purchase document inquiry, purchase to order, and purchase return. These modules effectively meet the operational needs of enterprises.

Change in self-image pressure level before and after autologous fat breast augmentation and its effect on social adaptability

BACKGROUND There is an increasingly strong demand for appearance and physical beauty in social life,marriage,and other aspects with the development of society and the improvement of material living standards.An increasing number of people have improved their appearance and physical shape through aesthetic plastic surgery.The female breast plays a significant role in physical beauty,and droopy or atrophied breasts can frequently lead to psychological inferiority and lack of confidence in women.This,in turn,can affect their mental health and quality of life.AIM To analyze preoperative and postoperative self-image pressure-level changes of autologous fat breast augmentation patients and their impact on social adaptability.METHODS We selected 160 patients who underwent autologous fat breast augmentation at the First Affiliated Hospital of Xinxiang Medical University from January 2020 to December 2022 using random sampling method.The general information,selfimage pressure level,and social adaptability of the patients were investigated using a basic information survey,body image self-assessment scale,and social adaptability scale.The self-image pressure-level changes and their effects on the social adaptability of patients before and after autologous fat breast augmentation were analyzed.RESULTS We collected 142 valid questionnaires.The single-factor analysis results showed no statistically significant difference in the self-image pressure level and social adaptability score of patients with different ages,marital status,and monthly income.However,there were significant differences in social adaptability among patients with different education levels and employment statuses.The correlation analysis results revealed a significant correlation between the self-image pressure level and social adaptability score before and after surgery.Multiple factors analysis results showed that the degree of concern caused by appearance in selfimage pressure,the degree of possible behavioral intervention,the related distress caused by body image,and the influence of body image on social life influenced the social adaptability of autologous fat breast augmentation patients.CONCLUSION The self-image pressure on autologous fat breast augmentation patients is inversely proportional to their social adaptability.

Instrument Automation Control System Faults and Maintenance

This article explores the topic of fault diagnosis and maintenance strategies for instrument automation control systems,analyzing them through specific cases.The aim of this research is to improve the stability and reliability of the system by conducting a thorough investigation of faults and maintenance in instrument automation control systems.By doing so,this research hopes to provide a strong guarantee for the smooth progress of industrial production.

Research on Electrical Automation Control Design Based on PLC Technology

As science and technology continue to progress forward,electrical automation engineering is also developing,of which programmable logic controller(PLC)technology is widely being used.Through the integration of PLC technology and traditional electrical automation technology,good development of modern science and technology is promoted while traditional automation is preserved.The development of electrical engineering can greatly improve the strength of science,technology,and economy in our country.Based on PLC technology,this paper analyzes the design of electrical automation control.

Teaching Mode Reform of the Electrical Automation Control Course

Under the background of the new era,higher requirements are put forward for colleges and universities to carry out teaching reform.Teachers of electrical automation control courses should update their teaching ideas regularly,innovate teaching methods,and take novel and effective measures to carry out related work.Because electrical automation control courses tend to be technology-oriented,teachers can help students consolidate basic knowledge.They should also focus on developing practical skills so students can easily adapt to future job positions.However,there are many problems in the actual teaching process,which hampers the improvement of the teaching quality to a certain extent.In view of this,this paper presents an in-depth exploration based on theories and practical experiences.It starts with an analysis of the current teaching status of electrical automation control courses in colleges and universities,followed by suggestions to improve them based on their characteristics and students’needs.