Service Module Research Articles

Teaching ethics in a technology regulation module: exploring the pedagogical method

ABSTRACT Technology and regulation exert significant impacts on business decision-making; as such, technology law has become an indispensable part of business education. The ethical components embedded in technology regulation modules are designed to equip future business professionals with fundamental values and rules that both guide and facilitate their decision-making. However, owing to the interdisciplinary nature of such a module and because it is frequently offered as a service module, unique instructional challenges arise. This paper identifies problem-based learning (PBL) as the main suitable pedagogical method for teaching ethical content in such a module, supplemented by scenario-based learning (SBL), because they effectively contextualise the relevant module content, create an environment that simulates real-life scenarios where moral dilemmas reside, and contribute to the module learning outcome in fostering a sustainability competency in students. Through a theoretical discussion based on concrete examples (a bitcoin transaction’s ethical issues in the environmental, social and governance (ESG) context and ethical dilemmas related to abortion rights), this paper aims to guide future studies on how to deliver ethical content within a technology law module.

Radiation Aspect of Two Orbit Inclination Options of the Russian Orbital Service Station

The contribution to the effective dose from cosmic radiation of the Earth’s radiation belts, galactic cosmic rays, and solar proton events for astronauts located in the large-diameter working compartment of the service module of the ISS is considered. It is shown that for quasi-stationary sources of cosmic radiation, a change in the orbital inclination of 51.6° by 97.0° does not lead to significant variations in the average daily effective dose rate. When considering the contribution to the effective dose from solar-flare protons, the dose load on astronauts can increase by ten or more times.

Crow Sun Flower Optimization-Based Handover Modules in 5G Networks

Handover modifies the user equipment using mobility in which base station provides the best one. The repeated handovers may corrupt mobility reliability due to high signaling load and therefore, network capability enhancement is affected. Here, a network management system in a network is difficult one owing to the rising number of complexity issues and base stations. In this paper, Crow Sun Flower Optimization (CSFO)-based handover method is developed for enabling efficient handover in Fifth Generation (5G) network. This handover method mainly consists of four parts, such as User Preference (UP) section, Network Quality of Service (NQ) module, power section, and Decision System (DS) module. The Quality of service (QoS) is controlled by UP section and NQ module, whereas the power module is concentrated on power. Thus, the handover is decided based on three segments and DS module is used to enable the network. The DS module is effectively decided whether to offer handover in 5G network or not. Moreover, the decision is optimally selected based on an optimization technique, named as CSFO algorithm. The developed CSFO technique is newly designed by integrating Crow Search Algorithm (CSA) and Sun Flower Optimization (SFO) technique. Additionally, three performance indicators, including received power, throughput, and user-served ratio, are used to assess how well the created CSFO-based handover model performs. High received power, throughput, and user served ratio of [Formula: see text][Formula: see text]dBm, [Formula: see text][Formula: see text]kbps and 0.071, respectively, are achieved by the developed handover strategy.

Design of civil aviation security check passenger identification system based on residual convolution network

INTRODUCTION: A civil aviation security check passenger identification system based on residual convolution network is designed to improve the efficiency of airport passenger security check service. OBJECTIVES: The system uses the basic resource layer to provide communication and configuration services, collects the basic information of passengers, the images of passengers' faces and whole body, and the images of baggage security X-ray machine through the data layer, and stores the collected results in the unstructured database; METHODS: The image processing module of the business service layer calls the data in the database, and takes the STM32F103VBT6 microprocessor as the image processing control chip to complete the image data processing. The person, baggage, X-ray machine image and passenger basic information are associated through the person, baggage and X-ray machine information binding service module, and the association results are uploaded to the person and certificates integration unit of the client application layer. RESULTS: The face recognition module identifies the passenger identity through the residual convolution network with the attention mechanism, and realizes the ReID identification of passengers and baggage and the association of people and baggage through the transmission control unit. CONCLUSION: The experimental results show that the system can accurately identify the identity of civil aviation security passengers, and the identification efficiency of security passengers can reach more than 27 frames per second.

A Collaborative Detection Method of Wireless Mobile Network Intrusion Based on Cloud Computing

In order to improve the communication security of wireless mobile network, a collaborative intrusion detection method based on cloud computing is studied. The mobile terminal and the cloud computing platform are connected by the wireless mobile network. The cloud computing platform authentication server adopts a dual server and multifactor authentication scheme for mobile cloud computing to provide authentication services for mobile terminal users. The web server of the cloud computing platform uses the intrusion node detection protocol of the neighbor classification mechanism to provide a communication security protocol for users; Using the HMM algorithm, the intrusion detection module of the computing platform realizes the intrusion detection of wireless mobile network. Finally, using authentication service, security protocol, and intrusion detection module completes the cooperative detection of mobile network intrusion. The experimental results show that this method can realize the cooperative detection of wireless mobile network intrusion, and the detection accuracy is as high as 98%, which ensures the communication security of wireless mobile network.

Development Strategy of Intelligent Digital Library without Human Service in the Era of "Internet +".

Internet technology has a great impact on the application and development of libraries. In order to provide users with more convenient and efficient services, this paper puts forward the development strategy of unmanned intelligent digital libraries in the era of “Internet +.” Design by IntelliSense module, network transmission module, data storage and analysis module, and intelligent service module of no wisdom digital library service mode, IntelliSense module using RFID technology, close range wireless communication technology, and other Internet technologies to collect the wisdom of unmanned services of all kinds of information in the digital library; use network transmission module of the wireless LAN network, Internet technology such as RFID network to transmit information collected to store in a data storage and analysis module; and at the same time using k-means clustering algorithm in data mining techniques such as analysis of collected data, based on the analysis results provide users with intelligence services such as search, wisdom is recommended. The experimental results show that the developed strategy meets the expected functional requirements, can accurately perceive the location of data, and effectively realize the intelligent service function.

Online battery health diagnosis for electric vehicles based on DTW-XGBoost

With the rapid development of electric vehicles, electric vehicle battery health diagnosis has become a hot issue. In order to realize online battery health diagnosis, an online battery health diagnosis platform based on DTW-XGBoost was proposed. The feature extraction method of multi-source data fusion based on clustering was adopted. DTW clustering was used to perform data aggregation and feature extraction for real-time battery data during charging process, and XGBoost algorithm was used to establish SOH prediction model. Build an online battery health diagnosis platform including acquisition and control module, modeling and analysis module and application service module by using cloud platform to improve charging operation and maintenance management level.

Digital thread-based modeling of digital twin framework for the aircraft assembly system

Digital twins are proposed to manage the industrial production sites by mapping physical space entities to virtual spaces. Existing digital twin modeling methods are mainly realized through deploying several modules, including a physical module, a virtual module, a service module, a data module, and a connection module. However, the assembly environment of the aircraft assembly process is complex and challenging to manage. These methods do not provide the data flow and the intrinsic interaction between modules. As a consequence, a digital thread-based modeling digital twin (DTDT) framework with five modules is established in this paper, which takes advantage of both the digital twin and digital thread. Benefited by better data management, the DTDT framework would be conducive to the controllability and traceability of the manufacturing process and product quality. The key characteristics of products, process parameters, and equipment operation conditions, are stored in the database module. And then, the digital thread module will link the entity module and virtual module together by building the directed graph, in which interfaces are provided to the system services module for the process monitoring and processing quality prediction. Finally, the implementation of the DTDT framework is shown through a case of the drilling and riveting process in aircraft assembly. The comparative analysis confirms that this model can improve the efficiency of the aircraft assembly process.

Intelligent Community and Real Estate Management Based on Machine Learning.

When studying intelligent community and property management system, network service has an important impact on intelligent community construction and property management service. How to use machine learning and other technologies to improve the network service of intelligent community and integrate it into real estate property management is worthy of further research. This paper introduces the basic model of machine learning and proposes a network data prediction model based on time series. For the time dimension, an improved prediction algorithm model of machine learning is proposed. For mobile data allocation, from the perspective of ensuring the current and future continuity of the spectrum after spectrum allocation, this paper proposes a spectrum allocation algorithm based on the joint measurement of time domain and frequency domain. In addition, the VP-tree algorithm is used to construct the spatial vector relationship of the intelligent community. At the same time, in the time trend and periodicity of the mobile data in the intelligent community network, the attention mechanism is introduced to realize the distribution of mobile data and traffic prediction in the intelligent community by machine learning. This paper analyzes the requirements of the property management system, designs the property management information system including the field subsystem layer, data acquisition layer, and cloud service layer, introduces the property management module and customer service module in detail, and carries out the system test. The test results show that the system runs well. Finally, aiming at the problems existing in the property management industry, this paper puts forward the development strategy of property management.

Dynamic Rendering-Aware VR Service Module Placement Strategy in MEC Networks

Combining multiaccess edge computing (MEC) technology and wireless virtual reality (VR) game is a promising computing paradigm. Offloading the rendering tasks to the edge node can make up for the lack of computing resources of mobile devices. However, the current offloading works ignored that when rendering is enabled at the MEC server, the rendering operation depends heavily on the environment deployed on this MEC serve. In this paper, we propose a dynamically rendering-aware service module placement scheme for wireless VR games over the MEC networks. In this scheme, the rendering tasks of VR games are offloaded to the MEC server and closely coupled with service module placement. At the same time, to further optimize the end-to-end latency of VR video delivery, the routing delay of the rendered VR video stream and the costs of the service module migration are jointly considered with the proposed placement scheme. The goal of this scheme is to minimize the sum of the network costs over a long time under satisfying the delay constraint of each player. We model our strategy as a high-order, nonconvex, and time-varying function. To solve this problem, we transform the placement problem into the min-cut problem by constructing a series of auxiliary graphs. Then, we propose a two-stage iterative algorithm based on convex optimization and graphs theory to solve our object function. Finally, extensive simulation results show that our proposed algorithm can ensure low end-to-end latency for players and low network costs over the other baseline algorithms.

Editorial

<p class="Text">Management of tourism destinations and suppliers is a big challenge. So many modules need to be coordinated, such as command and dispatching module, business management module, electronic monitoring module, security module, traffic management module, resource management module, tourist service module, and marketing promotion module. So many supporting elements need to be ensured to work well such as infrastructure and data. So many opinions from different groups need to be harmonized, such as tourists, market, enterprise and government.</p><p class="Text">In this issue, studies about management in smart tourism were collected. These cases include related research about China and Latin America. They used to be published in Chinese or Spanish. It our honor to have their authorization to translate and republish on <em>Smart Tourism</em>. Detailed suggestions and innovations are provided here. Management of special situations are also contained.</p><p class="Text"> </p><p class="Text" align="right">Editorial board member</p><p align="right">Dr. Eldar Magomedovich Eldarov</p>

Design of Smart and Secured Healthcare Service Using Deep Learning with Modified SHA-256 Algorithm.

Background: The modern era of human society has seen the rise of a different variety of diseases. The mortality rate, therefore, increases without adequate care which consequently causes wealth loss. It has become a priority of humans to take care of health and wealth in a genuine way. Methods: In this article, the authors endeavored to design a hospital management system with secured data processing. The proposed approach consists of three different phases. In the first phase, a smart healthcare system is proposed for providing an effective health service, especially to patients with a brain tumor. An application is developed that is compatible with Android and Microsoft-based operating systems. Through this application, a patient can enter the system either in person or from a remote place. As a result, the patient data are secured with the hospital and the patient only. It consists of patient registration, diagnosis, pathology, admission, and an insurance service module. Secondly, deep-learning-based tumor detection from brain MRI and EEG signals is proposed. Lastly, a modified SHA-256 encryption algorithm is proposed for secured medical insurance data processing which will help detect the fraud happening in healthcare insurance services. Standard SHA-256 is an algorithm which is secured for short data. In this case, the security issue is enhanced with a long data encryption scheme. The algorithm is modified for the generation of a long key and its combination. This can be applicable for insurance data, and medical data for secured financial and disease-related data. Results: The deep-learning models provide highly accurate results that help in deciding whether the patient will be admitted or not. The details of the patient entered at the designed portal are encrypted in the form of a 256-bit hash value for secured data management.

Evolution of the performance monitoring techniques for solar arrays of the service module Zvezda within the ISS Russian segment over the course of its orbital flight

The paper discusses issues involved in mission control of the International Space Station (ISS), in particular, specific aspects of monitoring and evaluating the status of Power Supply Systems (PSS) and solar arrays (SA) as their components. Power budget simulations use as their initial computational parameter the current SA performance, which is determined on the basis of a special performance evaluation mode. The obtained data make it possible to take into account the spaceflight factors resulting in performance degradation. Besides that, when using the SA performance evaluation mode as a method for periodically checking the SA status, the more accurate determination of the actual SA performance involves taking into account the shadowing of the photovoltaic cells, the effect of the light reflected off the Earth surface, and current generation resulting from illumination of both the front and the back surfaces of the SA. The paper presents the results of space experiment Albedo carried out onboard the Russian Segment (RS) of the ISS, which included development of techniques for taking into account the above factors when simulating the PSS power budget for the Service Module (SM) Zvezda. Developed as a result of carrying out the space experiment was a procedure for determining SA performance and simulating the power input from the ISS RS SM SA taking into account the Earth albedo; recommendations were made for the orbital spacecraft PSS control modes taking into account the possibility of power generation from the Earth outgoing light flux. Based on the results of testing the developed computational schemes for evaluating the SA performance and simulations of incoming power that take into account the Earth albedo, substantiated values were obtained for the proposed reference parameter for evaluating the ISS RS SM SA. The developed procedure provides the most accurate performance evaluation for both front and back surfaces of the SA. Computational schemes for predicting incoming power proposed within the framework of the procedure make it possible to give highly accurate predictions of incoming power using precise simulations of light flux coming from Earth, as well as to determine the contribution of variable components into the SA performance determined during a periodic SA performance estimate.

Research on Computer Intelligent Proofreading System for English Translation Based on Deep Learning

English, as a global language, is widely used in daily life, which leads to higher requirements for people’s language proficiency. Grammar, as an essential part of English, plays a significant role in language acquisition. Although the needs for English learning have become greater, the resources of English teaching are quite limited. Under this circumstance, it is imperative to apply information technology to alleviate the burden of lacking sufficient educational resources. The intelligent grammar correction system is in special needs. In this study therefore, the deep learning-based CNN and RNN bidirectional propagation model were utilized to construct a feedback filtering function, screen the suggested text, and select the high-quality suggested text for the retraining of the error correction model. The proofreading optimization algorithm and feedback filtering algorithm were used in practice to implement each functional module. The core function service module was designed with a cluster deployment scheme with high system performance and response speed to ensure system stability and availability. Experimental results demonstrate that the correct rate gradually increased with increasing the number of tests and finally stabilized at about 86%. The overall average correcting rate obtained from the present model was verified to be superior to that from the GRU model and the MGB model.

Performance Analysis of a Solar-Powered Multi-Purpose Supply Container

In this article, the performance of a solar-powered multi-purpose supply container used as a service module for first-aid, showering, freezing, refrigeration and water generation purposes in areas of social emergency is analyzed. The average daily energy production of the solar panel is compared to the average daily energy demands of the above-mentioned types of service modules. The comparison refers to five different locations based on the Köppen–Geiger classification of climatic zones with the data for energy demand being taken from another publication. It is shown that in locations up to mid-latitudes, the supply container is not only able to power all types of modules all year round but also to provide up to 15 m3 of desalinated water per day for drinking, domestic use and irrigation purposes. This proves and quantifies the possibility of combining basic supply with efficient transport and self-sufficiency by using suitably equipped shipping containers. Thus, flexible solutions are provided to some of the most challenging problems humans will face in the future, such as natural disasters, water scarcity, starvation and homelessness.

Construction of Water Conservancy and Energy Engineering Structure Platform Based on Cloud Computing

In view of the current water conservancy engineering system in solving the problem of water conservancy spatial information sharing and repeated investment in the construction of GIS systems by various water conservancy business departments, the research on the construction of water conservancy engineering structure platform based on cloud computing is proposed. We discussed the key technologies to realize the platform: pooled services, elastic cloud services, and spatial information services. The aggregation pooling service mainly uses the pooling mechanism and improves the responsiveness of platform services by creating object instances in advance. Based on the Cloud API provided by the cloud computing platform (such as creating a virtual machine, starting a virtual machine at runtime, and obtaining the real-time status of a virtual machine) and the REST Admin API provided by the water conservancy basic service module, using cloud computing technology ideas, we designed and implemented elastic cloud service technology. Enable the water conservancy spatial information service platform to be deployed in the cloud computing environment, support cloud architecture, and provide flexible computing capabilities, because the three types of services have different requirements for CPU and network utilization, the weight coefficient can be assigned to them. The CPU slice map service is 0.1, the spatial query service is 0.3, and the spatial analysis processing service is 0.6. The network bandwidth slice map service is 0.5, the spatial query service is 0.3, and the spatial analysis processing service is 0.2. Reduce the waste of infrastructure resources; meet the concurrent access needs of a large number of users. Spatial information service aggregation is one of the core service capabilities of the platform; it can effectively aggregate multisource spatial information, generate new services, and provide new information.

The Apollo ATCA design for the CMS track finder and the pixel readout at the HL-LHC

The challenging conditions of the High-Luminosity LHC require tailored hardware designs for the trigger and data acquisition systems. The Apollo platform features a “Service Module” with a powerful system-on-module computer that provides standard ATCA communications and application-specific “Command Modules” with large FPGAs and high speed optical fiber links. The CMS version of Apollo will be used for the track finder and the pixel readout. It features up to two large FPGAs and more than 100 optical links with speeds up to 25 Gb/s. We study carefully the design and performance of the board by using customized firmware to test power consumption, heat dissipation, and optical link integrity. This paper presents the results of these performance tests, design updates, and future plans.

Pengembangan Gamifikasi Pada Modul E - Learning Service Excellence Untuk Karyawan Frontliner

This paper is to develop teaching materials in the form of developing gamification teaching materials in the service excellence module that will be used for frontliner employees. The purpose of this research is to design the development of gamification teaching materials in the service excellence module that can be used for frontliner employees. The research results from the results of designing and testing gamification teaching materials for the service excellence module for frontlinner mall employees on a limited scale, that the feasibility of the content of the material and the feasibility of presenting gamification obtained an average score of 80%. Validation of the content of the Service Excellence module using gamification obtained an average score of 81%, and validation of the feasibility of presenting the Service Excellence module using gamification obtained an average score of 78%, so the survey results from the trial show that the teaching materials in the E-learning Service module Excellence carried out using gamification is suitable for use in training activities

Modul digital layanan klasikal melalui platform zedemy untuk meminimalisir perilaku cyberbullying

The use of devices that should be intended to support learning activities, it turns out that students can try various access to social media which can unwittingly increase cyberbullying. The classical services of School Counselor are also required to be adaptive to technology. However, the classic School Counselor service module is less attractive and rigid. The purpose of this study is to develop an integrated module with social media that is used as a classic Guidance and Counseling teacher service in Banjar Regency, South Kalimantan through the zedemy platform, which is expected to minimize cyberbullying. Research design using Research and Development (R&D) ADDIE model. Collecting data using Focus Group Discussion, and Likert scale questionnaire. The instrument used is the instrument of material, media and user feasibility. Data analysis was carried out descriptively to determine the characteristics of the distribution of respondents, then the Kendall's W concordance test was carried out to determine consistency and assessment.Expert tests are carried out by material experts, media experts and users. Based on the research, the material and media expert's assessment showed very good criteria, no revision needed. User ratings by Counselor School also showed very good criteria, no need for revision. So it can be concluded that the classical service digital module through the zedemy platform has met the criteria for being suitable for use as a classical service medium to minimize cyberbullying.

Prospective Primary Teachers’ Didactic-Mathematical Knowledge in a Service-Learning Project for Inclusion

An analysis of the didactic-mathematical knowledge put into play by a sample of 30 prospective primary teachers during their participation in a Service-Learning program focused on mathematical stimulation as a measure of attention to adolescents at risk of social exclusion is presented. The program aimed to respond to current training demands by promoting the development of mathematics-specific professional competencies, as well as social skills to interact with students, and to positively influence the prospective teachers’ affection towards mathematics and its teaching. It was developed during three academic years in two phases: the learning module was oriented to the presentation of the mathematical stimulus program and the didactical analysis of the STEAM activities knocking it into shape; in the service module, the participants implemented the activities in an educational center with students at risk of social exclusion. The analysis was carried out from the video recordings of the sessions, the future teachers’ written reports with the analysis of the activities, questionnaires on the didactic-mathematical knowledge and a satisfaction test. The results show difficulties on the part of the future teachers to analyze some of the activities of the program, which seems to have its origin in their poor command of the common knowledge of the mathematical content, which also limits them when it comes to managing the activities in the way expected for the stimulus program. All in all, participation in the program was positively assessed by them in relation to its usefulness for their training. The potential benefit of Service-Learning programs such as the one addressed here in the face of a positive impact on the affections towards mathematics is concluded, as a necessary step for a more effective acquisition of didactic-mathematical knowledge and skills in the initial training.