Function Virtualization Research Articles

Structure similarity virtual map generation network for optical and SAR image matching

Introduction: Optical and SAR image matching is one of the fields within multi-sensor imaging and fusion. It is crucial for various applications such as disaster response, environmental monitoring, and urban planning, as it enables comprehensive and accurate analysis by combining the visual information of optical images with the penetrating capability of SAR images. However, the differences in imaging mechanisms between optical and SAR images result in significant nonlinear radiation distortion. Especially for SAR images, which are affected by speckle noises, resulting in low resolution and blurry edge structures, making optical and SAR image matching difficult and challenging. The key to successful matching lies in reducing modal differences and extracting similarity information from the images.Method: In light of this, we propose a structure similarity virtual map generation network (SVGNet) to address the task of optical and SAR image matching. The core innovation of this paper is that we take inspiration from the concept of image generation, to handle the predicament of image matching between different modalities. Firstly, we introduce the Attention U-Net as a generator to decouple and characterize optical images. And then, SAR images are consistently converted into optical images with similar textures and structures. At the same time, using the structural similarity (SSIM) to constrain structural spatial information to improve the quality of generated images. Secondly, a conditional generative adversarial network is employed to further guide the image generation process. By combining synthesized SAR images and their corresponding optical images in a dual channel, we can enhance prior information. This combined data is then fed into the discriminator to determine whether the images are true or false, guiding the generator to optimize feature learning. Finally, we employ least squares loss (LSGAN) to stabilize the training of the generative adversarial network.Results and Discussion: Experiments have demonstrated that the SVGNet proposed in this paper is capable of effectively reducing modal differences, and it increases the matching success rate. Compared to direct image matching, using image generation ideas results in a matching accuracy improvement of more than twice.

Retracted: Design Analysis of Intelligent Enterprise Costing Platform Based on a Virtual Network Mapping Algorithm

Retracted: Design Analysis of Intelligent Enterprise Costing Platform Based on a Virtual Network Mapping Algorithm

Simulation of transportation of acute stroke patients in border regions

Determining the optimal transportation for each stroke patient is critically important to achieve the best possible outcomes. In border regions the next comprehensive stroke center may be just across an international border, but bureaucratic and financial hurdles may prevent a simple transfer to the next stroke center. We hypothesized that in regions close to international borders, patients may benefit from an "open border, closed transfer scenario", meaning that patients in whom a large vessel occlusion (LVO) is detected in the primary stroke center will benefit from a transfer to the nearest stroke center offering endovascular thrombectomy—even if this may be across a national border. We used the Swiss-German–French trinational region as an example for a region with several international borders within close proximity to one another, and compared two feasible scenarios; (a) a “closed borders, open transfer” scenario, where the patient is transported to any center in the same country, (b) an “open border, closed transfer” scenario, where patients are always transported to the nearby primary stroke center first and then to the nearest comprehensive stroke center in either the same or a neighboring country and (c) and “open borders, open transfer” scenario. The outcome of interest was the predicted probability of acute ischemic stroke patients to achieve a good outcome using a conditional probability model which predicts the likelihood of excellent outcome (modified Rankin scale score of 0–1 at 90 days post-stroke) for patients with suspected LVO. Results were modeled in a virtual map from which the ideal transport concept emerged. For an exemplary LVO stroke patient in Germany, the probability of a good outcome was higher in an open border, closed transfer scenario than with closed borders, open transfer (33.1 vs. 30.1%). Moreover, time to EVT would decrease from 232 min in the first scenario to 169 min in an open border, closed transfer scenario. The catchment area of the University Hospital Basel was almost double the size in an open border, closed transfer scenario compared to closed borders (1674 km2 vs. 2897 km2) and would receive transfers from 3 primary stroke centers in other countries (2 in Germany and 1 in France). Stroke patients showed a higher likelihood of good outcome in the “open border” scenarios without transfer restrictions to a specific healthcare system. This probably has implications for stroke treatment in all border regions where EVT eligible stroke patients may benefit from transport to the closest EVT capable center whenever possible, regardless of whether this hospital is located in the same or a neighboring country/jurisdiction.

Towards a true conservation zero tillage system: “A proposed solution based on computer vision to herbicide resistance.”

The Zero Tillage (ZT) or Non-Tillage system constitutes an agricultural production approach designed for improved soil conservation, reduced fossil fuel usage, mitigation of waterway pollution, water and wind erosion, and addressing soil compaction, among other objectives. In this way, ZT promises more sustainable agriculture. However, current ZT production systems depend on herbicide applications for weed control. The use of herbicides with the same modes of action over many years has led to numerous resistant weed species, which end up threatening the success of the herbicide weed control and, consequently, the overall success of the ZT system. Being able to automatically detect and classify weed species directly under the sprayer during the chemical application is an alternative to control populations of weeds since it would allow selecting the herbicide and dose for those particular species. This study, conducted over 15 years in commercial fields utilizing Zero Tillage (ZT) management, examined various ground covers intrinsic to the ZT system originating from previous crops or residues post-harvest. ZT features a broad spectrum of contexts due to the complexity of different ground cover types, which challenge computer vision techniques. The assessment focused on the automatic detection and classification of among the most problematic monocotyledonous and dicotyledonous weed species in the province of Cordoba in Argentina, with the objective of enabling a more targeted and selective approach to their control. These are Amaranthus palmeri, Echinochloa crus-galli, Eleusine indica, Parietaria debilis and Conyza sumatrensis. Additionally, some species belong to the same botanical families with several morphological resemblances that defy vision algorithms. This work proceeded through a machine learning approach applied to computer vision features such as SIFT (scale-invariant feature transform), K-means (clustering), and Bag of Features over the Support Vector Machine for classification. The results showed an accuracy between 89 % and 98 % over the species, allowing a significant reduction of herbicide while applying the adequate active ingredient. Moreover, virtual binary maps from weed patches are devised to be implemented through ISOBUS protocol. Thus the current research contributes significantly to the issue of controlling populations of weeds in the ZT agriculture system.

Fully Digital Audio Haptic Maps for Individuals with Blindness

Tactile maps designed for individuals with blindness can greatly improve their mobility, safety and access to new locations. While 3D-printed maps have already been demonstrated to be a powerful tool for delivering spatial information, they might not always be available. Alternatively, a combination of audio and haptic information can be used to efficiently encode 2D maps. In this paper, we discuss the development and user-testing of a novel audio-haptic map creator application. Maps created using this application can provide people with blindness with a tool for understanding the navigational routes and layouts of spaces before physically visiting the site. Thirteen people with blindness tested various components of the virtual map application, such as audio, haptic feedback and navigation controls. Participants’ data and feedback were collected and analyzed to determine the effectiveness of the virtual maps as it relates to this user group’s readability and usability. The study showed that it was easy to use and that it efficiently delivered information about travel routes and landmarks that the participants could successfully understand.

Evaluating the Elasticity of Metastatic Cervical Lymph Nodes in Head and Neck Squamous Cell Carcinoma Patients Using DWI-based Virtual MR Elastography.

The assessment of metastatic cervical lymph nodes in head and neck squamous cell carcinoma patients is crucial; as such, many studies focusing on non-invasive imaging techniques to evaluate metastatic cervical lymph nodes have been performed. The aim of our study was to assess the usefulness of elasticity values on diffusion weighted imaging (DWI)-based virtual MR elastography in the evaluation of metastatic cervical lymph nodes from head and neck squamous cell carcinoma. Two head and neck radiologists measured the elasticity values of 16 metastatic cervical lymph nodes from head and neck squamous cell carcinoma and 13 benign cervical lymph nodes on DWI-based virtual MR elastography maps. Mean, minimum, maximum, and median elasticity values were evaluated for lymph nodes between the two groups and interobserver agreement in measuring the elasticity was also evaluated. The mean, maximum, and median elasticity values of metastatic cervical lymph nodes were significantly higher than those of benign cervical lymph nodes (P = 0.001, 0.01, and 0.002, respectively). Diagnostic accuracy, sensitivity, and specificity of the mean elasticity were 82.8%, 93.8%, and 69.2%, respectively. Interobserver agreement was excellent for the mean and median elasticity (intraclass correlation coefficients were 0.98 for both). Estimated elasticity values based on DWI-based virtual MR elastography show significant difference between benign and metastatic cervical lymph nodes from head and neck squamous cell carcinoma. While precise modulation of MR sequences and calibration parameters still needs to be established, elasticity values can be useful in differentiating between these lymph nodes.

Enhancing Wi-Fi RSS-Based Indoor Positioning under Dynamic AP Availability: Leveraging Virtual Feature Maps and Contrastive Learning

Enhancing Wi-Fi RSS-Based Indoor Positioning under Dynamic AP Availability: Leveraging Virtual Feature Maps and Contrastive Learning

Development of A Metaverse-Based Teaching Material on Rainforest Ecosystem for Nigerian High School Biology

This study focused on the development of a metaverse-based rainforest ecosystem for high school students and tested its effectiveness in terms of students’ academic achievement and learning satisfaction. In this study, the metaverse platform ZEP is used to simulate a rainforest ecosystem. ZEP jointly developed by Supercat and Naver Z was formally launched in Korea on March 16, 2022. ZEP is a platform where users can integrate through avatars and integrates the metaverse’s virtual space map, video conferences, materials, movies and presentations displayed in object form. Ease of access, cost-effectiveness, interactivity, and user-friendliness are some of the strengths of the ZEP metaverse platform. The ZEP metaverse materials for high school biology were developed to serve as a hybrid world between the real and the virtual world. Data collection for the metaverse group was carried out using the pretest-posttest method, comparing it with two control groups—one using textbooks and the other using videos. The results indicate that the experimental group with metaverse technology is effective in improving students’ learning achievement and satisfaction. Therefore, it is proposed that the metaverse in education is valuable for teachers and learners because it could lead to student engagement and motivation in the classroom.

METODE CHEAPEST INSERTION HEURISTIC PADA SISTEM INFORMASI GEOGRAFIS TEMPAT WISATA DI KABUPATEN DELI SERDANG BERBASIS ANDROID

Geographic Information System (GIS) is a system created using information derived from processing a number of data, namely geographic data or data located on the earth's surface. Geographic Information Systems can be used in various fields, one of which is as a travel planning and tourist location. The lack of information conveyed on tourism in Deli Serdang Regency is one of the obstacles for people who want to travel. In this thesis, a Geographic Information System application for tourism in Deli Serdang Regency is developed which has detailed tourist information and the selection of the shortest travel route and alternative tours. To determine the shortest route and alternative travel, use the Cheapest Insertion Heuristic Algorithm. Then it is hoped that the community can be helped in planning tourist trips in Deli Serdang Regency. This application utilizes the google maps API as a virtual map provider which will later display tourist location points in Deli Serdang Regency. In addition, this application is also equipped with tourist list information along with tourist details that can be accessed by the public as a reference for traveling.

Computational-guided approach for identification of PI3K alpha inhibitor in the treatment of hepatocellular carcinoma by virtual screening and water map analysis

Hepatocellular carcinoma (HCC) is one of the most deadly disorders, with a relative survival rate of 36% in the last 5 years. After an extensive literature survey and pathophysiology analysis, PI3Kα was found to be a promising biological target as PIK3CA gene upregulation was observed in HCC, resulting in the loss of apoptosis of cells, which leads to uncontrollable growth and proliferation. Due to superior selectivity and promising therapeutic activity, the PI3K-targeted molecule library was selected, and the ligand preparation was executed. The study mainly focused on e-pharmacophore development, virtual screening and receptor–ligand docking analysis. Then, MMGBSA and ADME prediction analysis was performed with the top 10 molecules; for further analysis of ligand–receptor binding affinity at the catalytic binding site, induced fit docking was performed with the top two molecules. The analysis of quantum chemical stability descriptors, i.e., frontier molecular orbital analysis, was performed followed by molecular dynamics simulation of 100 ns to better understand the ligand-receptor binding. In this study, water map analysis played a significant role in the hit optimization and analysis of the thermodynamic properties of the receptor–ligand complex. The two hit molecules K894-1435 and K894-1045 represented superior docking scores, enhanced stability, and inhibitory action targeting Valine 851 amino acid residue at the catalytic binding site. Hence, the study has significance for the quest for selective PI3Kα inhibitors through the process of hit-to-lead optimization. Communicated by Ramaswamy H. Sarma

End-to-end technologies as a tool for developing sociocultural competence among inophones in the process of linguistic and cultural adaptation in the space of “urban text”

Introduction. One of the main processes associated with the stay of an inophone student who came to study a foreign language in a foreign country is linguistic adaptation in a new cultural and geographical space. The result of successful adaptation is the formation of sociocultural competence among the student, awareness of regional identity. From the point of view of the methodology for teaching the Russian language as a foreign language, it seems significant to search for the most effective technologies, methods and techniques that would allow immersing the inophone in the natural environment. End-to-end technologies used in urban space to obtain multidirectional information for native speakers and foreigners meet this methodological task. Authentic texts of chatbots, interactive maps become didactic material for the formation of key competencies of an inophone student.Materials and Methods. The scientific basis of the study is scientific works related to the methodology of teaching the Russian language as a foreign language, the problems of linguistic and cultural adaptation and the use of end-to-end technologies in linguistic education. The research materials are authentic (natural) texts of the digital urban environment: online maps, chat bots, audio guides, which contribute to a more effective linguistic and cultural adaptation of inphones to "alien" space. Based on the methods of analysis and generalization, a theoretical understanding of the experience of working with foreign students at the Nizhny Novgorod State Pedagogical University named after K. Minin. The key concepts used in the work are "digital pedagogy," "end-to-end technologies," "urban text," "regional identity." "sociocultural competence," "linguostranological adaptation."Results. The use of end-to-end technologies in the practice of teaching Russian as a foreign language is currently an effective way to develop communicative competence. Urban space provides an opportunity for direct immersion in the environment of the language being studied. In teaching practice, online cards are actively used, according to which, on the one hand, tasks can be compiled aimed at developing skills in any type of speech activity (reading, speaking, listening, writing), on the other hand, they can become the basis for project activities students. Another online tool for developing communication skills in a foreign language is chatbots. A chatbot makes it possible to learn a foreign language and maintain communication skills at a pace convenient for the student, while eliminating the fear of making mistakes, because there is interaction with artificial intelligence. The AudioGuideNN chatbot allows a student of Russian as a foreign language to enter the urban space, get acquainted with the city and learn the language at the same time.Discussion and Conclusions. Modern end-to-end technologies are effective tools for teaching a foreign language, including Russian as a foreign language. Virtual maps, audio guides, chat bots allow you to relieve the cultural shock of the urban space from a native speaker of a foreign language who is in a new environment for him, create conditions for the linguistic and cultural adaptation of a foreign speaker, and also contribute to the study of the Russian language due to direct immersion in the urban – Russian-language – text.

Path Planning of Logistic Robot Using Method of Vector Marks Tree Generation

The authors of this article analyzed the problem of logistic robotics. This paper presents a method for robot navigation in a known environment. The method consists of two steps. The first step is to model the system, assign vector marks to the prominent edges of the virtual environment map, and direct the robot to reach these marks. The second step is to enable the robot to execute a specific task based on the given paths and deal with the local obstacles avoidance independently. The identification of the prominent point, the computation of the vector mark, and optimal path calculation are performed on the computer model using colored Petri nets in the software ‘Centaurus CPN’. The proposed approach was extended to simulate the work of a logistic robot, which has to take boxes and deliver them to certain places in storages. The experimental investigation has shown that the simulated mobile robots with the proposed navigation system were efficiently moving along the planned path. The analysis of the vector tree reveals that it takes 0.389 s to compute and graphically represent it. The occupation of certain places in storages is visualized and shown in experimental graphics.

Two-phase flow regime identification using multi-method feature extraction and explainable kernel Fisher discriminant analysis

PurposeIdentifying the flow regime is a prerequisite for accurately modeling two-phase flow. This paper aims to introduce a comprehensive data-driven workflow for flow regime identification.Design/methodology/approachA numerical two-phase flow model was validated against experimental data and was used to generate dynamic pressure signals for three different flow regimes. First, four distinct methods were used for feature extraction: discrete wavelet transform (DWT), empirical mode decomposition, power spectral density and the time series analysis method. Kernel Fisher discriminant analysis (KFDA) was used to simultaneously perform dimensionality reduction and machine learning (ML) classification for each set of features. Finally, the Shapley additive explanations (SHAP) method was applied to make the workflow explainable.FindingsThe results highlighted that the DWT + KFDA method exhibited the highest testing and training accuracy at 95.2% and 88.8%, respectively. Results also include a virtual flow regime map to facilitate the visualization of features in two dimension. Finally, SHAP analysis showed that minimum and maximum values extracted at the fourth and second signal decomposition levels of DWT are the best flow-distinguishing features.Practical implicationsThis workflow can be applied to opaque pipes fitted with pressure sensors to achieve flow assurance and automatic monitoring of two-phase flow occurring in many process industries.Originality/valueThis paper presents a novel flow regime identification method by fusing dynamic pressure measurements with ML techniques. The authors’ novel DWT + KFDA method demonstrates superior performance for flow regime identification with explainability.

3D Specimen Scanning and Mapping in Musculoskeletal Oncology: A Feasibility Study.

Surgical resection is the primary treatment for bone and soft tissue tumors. Negative margin status is a key factor in prognosis. Given the three-dimensional (3D) anatomic complexity of musculoskeletal tumor specimens, communication of margin results between surgeons and pathologists is challenging. We sought to perform ex vivo 3D scanning of musculoskeletal oncology specimens to enhance communication between surgeons and pathologists. Immediately after surgical resection, 3D scanning of the fresh specimen is performed prior to frozen section analysis. During pathologic grossing, whether frozen or permanent, margin sampling sites are annotated on the virtual 3D model using computer-aided design (CAD) software. 3D scanning was performed in seven cases (six soft tissue, one bone), with specimen mapping on six cases. Intraoperative 3D scanning and mapping was performed in one case in which the location of margin sampling was shown virtually in real-time to the operating surgeon to help achieve a negative margin. In six cases, the 3D model was used to communicate final permanent section analysis. Soft tissue, cartilage, and bone (including lytic lesions within bone) showed acceptable resolution. Virtual 3D scanning and specimen mapping is feasible and may allow for enhanced documentation and communication. This protocol provides useful information for anatomically complex musculoskeletal tumor specimens. Future studies will evaluate the effect of the protocol on positive margin rates, likelihood that a re-resection contains additional malignancy, and exploration of targeted adjuvant radiation protocols using a patient-specific 3D specimen map.

IMPLEMENTATION OF INFORMATION TECHNOLOGIES IN INSTITUTIONS OF VOCATIONAL EDUCATION

The article covers the theoretical, methodical and practical aspects of the implementation of information technologies in vocational education and training. The purpose of the article is to find factors for improving the educational process, management, methods and information work via the introduction of information/information and communication technologies in institutions of vocational and technical education. The following methods were used in the research process: theoretical and substantive analysis of primary sources and advanced pedagogical experience, analysis, generalization and systematization of scientific approaches in the use of information and communication technologies in the educational process of vocational education institutions, as well as methods of modelling and designing the “Teacher’s Road Map”. It has been established that information/information and communication technologies in vocational education are an important area of activity of an educational institution and a tool for increasing the teacher’s productivity. It has been found out that the pedagogical terms contributing to the effectiveness of the use of information technologies in vocational education institutions are a high level of information culture of teachers and students; implementation of innovative technologies including information and communication pedagogical ones based on subject-subject interaction; ensuring the reflection of the subjects of the educational process, their capability of adequate self-assessment of their personality. A virtual road map for the teacher has been developed as an electronic public resource (for example, a website). The map shows all mandatory points and routes that a teacher should take during educational activities in a vocational education institution. The main directions in the teacher’s virtual road map which are consistent with the similar ones of the teacher’s activity in a real educational situation are defined. The virtual road map covers educational and methodical work, has a hyperlink to the plan of methodical work of the cycle commission for the year, a hyperlink to methodical manuals or guides on the organization work in a vocational education institution; provides teachers with system suggestions and hyperlinks to electronic educational resources; a hyperlink to cloud storage for downloading documents for advanced training courses or internships; certificates, diplomas regarding participation in scientific and methodical events and self-education; a hyperlink to the cloud storage for uploading planning documents and methodological developments for review and approval. The virtual road map is differentiated by subject area which allows for providing meaningful instructions to occupational safety teachers, road safety teachers, industrial training masters, and teachers of special disciplines. The result of the research is the development of a meaningful module “Digital technologies in education: cloud services, online platforms for the creation of an educational environment by the teacher and the improvement of the qualifications of the pedagogical staff of the vocational educational institution.” It has been concluded that due to the testing of the information educational environment model at the Kostyantyniv Higher Vocational School, the approaches to the internal management of the institution, the organization of methodical, educational and study work, the forms and methods of teaching the profession, the culture of designing theoretical and industrial training lessons, the system assessment of educational achievements of students, and ways of involving parents in the educational process at the institution have been enhanced.

Virtual Network Embedding Over Multi-Band Elastic Optical Network Based on Cross-Matching Mechanism and Hypergraph Theory

The commercialization of 5G and the explosive emergence of new applications stimulate the exponential growth of network traffic and diversification of services. It is promising to integrate multi-band elastic optical network (MBEON) and network virtualization for large volume traffic transmission and highly diverse services. However, performing virtual network embedding (VNE) for network virtualization over MBEON faces the challenge of severe inter-channel stimulated Raman scattering (ISRS) effect, which complicates the underlying physical layer effect in the substrate network. In this paper, we investigate the ISRS-aware VNE over MBEON, where a cross-matching mechanism is proposed for virtual node mapping (VNM) and a hypergraph is introduced for parallel virtual link mapping (VLM). A lightpath-level integer linear programming model is first formulated. To integrate the cost and availability of VLM, which significantly affect the performance of the VNE under the ISRS effect, into the VNM process, the “virtual node-substrate node” mapping pairs are specifically evaluated through the cross-matching mechanism. Moreover, to tackle the couplings among multiple lightpaths induced by the wide spectrum ISRS effect, hypergraphs are used to model the ISRS effect-aware quality of transmission (QoT) constraints among multiple lightpaths. A hypergraph maximal weight independent set heuristic is presented for lightpath selection, which guarantees the obedience of basic constraints and generates near-optimal solutions. Experimental results show that the proposed methods decrease blocking ratio by more than 30% compared with the benchmarks with similar computational complexity.

Multisensor fusion-based digital twin for localized quality prediction in robotic laser-directed energy deposition

Early detection of defects, such as keyhole pores and cracks is crucial in laser-directed energy deposition (L-DED) additive manufacturing (AM) to prevent build failures. However, the complex melt pool behaviour cannot be adequately captured by conventional single-modal process monitoring approaches. This study introduces a multisensor fusion-based digital twin (MFDT) for localized quality prediction in the robotic L-DED process. The data used in multisensor fusion includes features extracted from a coaxial melt pool vision camera, a microphone, and an off-axis short wavelength infrared thermal camera. The key novelty of this work is a spatiotemporal data fusion method that synchronizes multisensor features with the real-time robot motion data to achieve localized quality prediction. Optical microscope (OM) images of the printed part are used to locate defect-free and defective regions (i.e., cracks and keyhole pores), which serve as ground truth labels for training supervised machine learning (ML) models for quality prediction. The trained ML model is then used to generate a virtual quality map that registers quality prediction outcomes within the 3D volume of the printed part, thus eliminating the need of physical inspections by destructive methods. Experiments show that the virtual quality map closely matches the actual quality observed by OM. Compared to traditional single-sensor-based quality prediction, the MFDT has achieved a significantly higher quality prediction accuracy (96%), a higher ROC-AUC score (99%), and a lower false alarm rate (4.4%). As a result, the MFDT is a more reliable method for defect prediction. The proposed MFDT also lays the groundwork for our future development of a self-adaptive hybrid processing strategy that combines machining with AM for defect removal and quality improvement.

NETWORK SECURITY ISSUES AND SECURITY ATTACK CLASSIFICATION FOR 5G

Fifth-generation technology [5G] services commercialized in 2019 have not only provided voice and data communication but also undergone significant structural changes in mobile networks to accommodate Internet-of-things devices, sensitive to latency and reliability, by adopting the latest ICT technologies, such as software-defined networking/network function virtualization, multi-access edge computing, and network slicing. However, this technological evolution poses new security chal- lenges, such as creation of new access paths, owing to its complex inter-operation structures, security downgrading, and limitations in security visibility. To address these issues, research on 5G security threats and security architecture has been actively underway at international standards organizations, communication carriers, and universities. However, security researchers find it difficult to conduct studies on 5G security technology design and application methods owing to the relatively unknown nature of the mobile carrier network. Therefore, in this paper, we analyzed five new security issues for each 5G section, relative to 5G technical advantages, by reviewing previous studies. In addition, we classified cyber attacks against nine network protocols primarily used in the 5G core network. The result of this study is expected to be used as basic data for modeling 5G security threats. Keywords: 5G security, Internet of things, 5G security technology, Cyber attacks, 5G threats

Applications of the Digital Mapping System (DMS) and the Influence on Climate Change

Recent years have seen a rapid change in climate, which has led to an increase in the number of severe weather-related disasters. The management, on the other hand, has not provided a solution that is adequate to the question of how to avert similar calamities. Because planners, designers, and those in charge of making decisions lack essential meteorological expertise and data, there is currently insufficient consideration given to the influence that DMS will have on the climate. As a direct result of increasing urbanisation, the rate at which climate change is occurring is accelerating, which means that the significance of this problem is growing. The city virtual map system has the potential to serve as a convergence point for virtual and climate systems, which will make it easier to find solutions to problems. The significance of DMS is analysed, and data-driven recommendations are offered based on the obtained meteorological data and after taking into consideration the effects of climate, population, and greening. This article starts with a brief overview of how the city's climate has changed recently. Next, the purpose of the urban climate map is explained, followed by a list of relevant pros and cons based on the relevant characteristics and a discussion of how DMS could be used in real-world situations.

Digital Twin-Based Vibration Monitoring of Plant Factory Transplanting Machine

In response to the problem of bowl seedling detachment caused by the shaking of the transplanting machine in plant factories, this paper proposes a physical entity monitoring method for the digital twin (DT) plant factory transplanting system. The method is used to analyze the vibration signals of the transplanting machine under different operating conditions and explore the optimal working conditions. Firstly, a demand analysis for the physical entity of the DT plant factory transplanting system is conducted, focusing on practical applications. Then, an optimal deployment plan is designed based on the axiomatic design (AD) theory. Subsequently, a comparative analysis of the operating conditions of the plant factory transplanting equipment is carried out using data-driven approaches. Finally, the optimal working condition parameters are determined by comparing the modal vibration power spectral density of the transplanting equipment under different operating conditions. The results show that the maximum amplitude occurs in the Z-axis, with a magnitude of 2.1 m/s2. By comparing the cloud maps, it is evident that the vibration trends in the Z-axis and X-axis above the transplanting robotic arm are more pronounced compared to the Y-axis. This indicates that under the operating condition of transplanting 3000 plants per hour, a high transplanting efficiency can be maintained, and the vibration signals in the XYZ-axis above the transplanting robotic arm are relatively smooth, making them suitable for transplanting operations. This study combines digital twin technology to analyze the vibration signals of the plant factory transplanting machine under different operating conditions and explore the optimal working conditions. Compared to traditional monitoring platforms, this method facilitates the real-time visualization of different operating conditions of the transplanting machine in a virtual mapping, providing a more intuitive reflection of the equipment operation status.