System Administrators Research Articles

정책집행이론에 근거한 직업계고 학점제 진단 - 마이스터고 학점제 담당자 인식을 중심으로

Purpose: This study was conducted to analyze the level of policy awareness among vocational high school credit system policy implementers and derive improvement measures. Methods: This study utilized survey data on policy perceptions of the high school credit system from forty-four head teachers at Meister High Schools, supplemented by in-depth telephone interviews with five participants to explore the reasons behind the survey results. The data were analyzed using statistical methods such as descriptive statistics, t-tests, Borich needs assessment, and Importance Performance Analysis (IPA) with the help of SPSS 23.0 software. Results: The analysis of the perception of vocational high school credit system administrators revealed that in the policy goal factors, perception of the policy-making process emerged as the most urgently needed factor for improvement. In executing agency factors, perception of member capabilities emerged as the most urgently needed factor for improvement. In execution management factors, perception of performance goals emerged as the most urgently needed factor for improvement. In policy environment factors, perception of interest and support emerged as the most urgently needed factor for improvement. Conclusion: To enhance the effectiveness of the credit system in vocational high schools, it is necessary to improve the efficiency of tasks related to the credit system, implement a more flexible curriculum, and increase students' understanding and interest in the credit system policies.

A study of the relationship between professional autonomy and professional quality of life among operating room personnel: A cross-sectional study

BackgroundHealthcare personnel's professional autonomy and professional quality of life can influence the quality of care provided to patients. However, there is scarce and contradictory information available about the relationship between these two factors. The present study aims to investigate the relationship between professional autonomy and professional quality of life among operating room personnel. MethodsThis cross-sectional study was conducted in teaching hospitals in the south of Iran in 2023. The sample consisted of 464 operating room personnel who were selected by quota sampling. Data were collected using Dempster Professional Autonomy Scale and Stamm's Professional Quality of Life Scale. The collected data were analyzed in SPSS v. 24. Level of significance was set at 0.05. ResultsThe participants’ professional autonomy mean score was found to be average (92.6 ± 73.32). Among the subscales of professional quality of life, the participants’ highest and lowest mean scores were for compassion satisfaction (35.3 ± 3.75) and secondary traumatic stress (31.2 ± 9.94) respectively. Also, the researchers found a significant inverse correlation between professional autonomy on the one hand and the professional quality of life subscales of burnout (p = 0.017, r = -0.111) and secondary traumatic stress (p = 0.005, r = -0.131) on the other. Moreover, there was a significant correlation between the operating room personnel's employment status on the one hand and professional autonomy (p = 0.004, r = -0.133) and burnout (p = 0.034, r = -0.099) on the other. The results also showed a significant inverse correlation between the subscale of burnout on the one hand and the variables of age (p = 0.021, r = -0.107) and work experience (p = 0.027, r = -0.103) on the other. ConclusionIn view of the findings of the study, the healthcare system administrators are recommended to adopt effective policies and strategies to promote operating room personnel's professional autonomy and professional quality of life.

Implementation of Cyber Network’s Attacks Detection System with Deep Learning Designing Algorithms

The internet has become indispensable for modern communication, playing a vital role in the development of smart cities and communities. However, its effectiveness is contingent upon its security and resilience against interruptions. Intrusions, defined as unauthorized activities that compromise system integrity, pose a significant threat. These intrusions can be broadly categorized into host intrusions, which involve unauthorized access and manipulation of data within a system, and network intrusions, which target vulnerabilities within the network infrastructure. To mitigate these threats, system administrators rely on Network Intrusion Detection Systems (NIDS) to identify and respond to security breaches. However, designing an effective and adaptable NIDS capable of handling novel and evolving attack strategies presents a significant challenge. This paper proposes a deep learning-based approach for NIDS development, leveraging Self-Taught Learning (STL) and the NSL-KDD benchmark dataset for network intrusion detection. The proposed approach is evaluated using established metrics, including accuracy, F-measure, recall, and precision. Experimental results demonstrate the effectiveness of STL in the 5-class categorization, achieving an accuracy of 79.10% and an F-measure of 75.76%. This performance surpasses that of Softmax Regression (SMR), which attained 75.23% accuracy and a 72.14% F-measure. The paper concludes by comparing the proposed approach's performance with existing state-of-the-art methods.

Performance Analysis of Wireless Sensor Networks Using Damped Oscillation Functions for the Packet Transmission Probability

Wireless sensor networks are composed of many nodes distributed in a region of interest to monitor different environments and physical variables. In many cases, access to nodes is not easy or feasible. As such, the system lifetime is a primary design parameter to consider in the design of these networks. In this regard, for some applications, it is preferable to extend the system lifetime by actively reducing the number of packet transmissions and, thus, the number of reports. The system administrator can be aware of such reporting reduction to distinguish this final phase from a malfunction of the system or even an attack. Given this, we explore different mathematical functions that drastically reduce the number of packet transmissions when the residual energy in the system is low but still allow for an adequate number of transmissions. Indeed, in previous works, where the negative exponential distribution is used, the system reaches the point of zero transmissions extremely fast. Hence, we propose different dampening functions with different decreasing rates that present oscillations to allow for packet transmissions even at the end of the system lifetime. We compare the system performance under these mathematical functions, which, to the best of our knowledge, have never been used before, to find the most adequate transmission scheme for packet transmissions and system lifetime. We develop an analytical model based on a discrete-time Markov chain to show that a moderately decreasing function provides the best results. We also develop a discrete event simulator to validate the analytical results.

Centering equity, diversity, and inclusion in youth digital mental health: findings from a research, policy, and practice knowledge exchange workshop.

Youth mental health service organizations continue to rapidly broaden their use of virtual care and digital mental health interventions as well as leverage artificial intelligence and other technologies to inform care decisions. However, many of these digital services have failed to alleviate persistent mental health disparities among equity-seeking populations and in some instances have exacerbated them. Transdisciplinary and intersectional knowledge exchange is greatly needed to address structural barriers to digital mental health engagement, develop and evaluate interventions with historically underserved communities, and ultimately promote more accessible, useful, and equitable care. To that end, the Digital, Inclusive, Virtual, and Equitable Research Training in Mental Health Platform (DIVERT), the Maritime Strategy for Patient Oriented Research (SPOR) SUPPORT (Support for People and Patient-Oriented Research and Trials) Unit and IWK Mental Health Program invited researchers, policymakers, interprofessional mental health practitioners, trainees, computer scientists, health system administrators, community leaders and youth advocates to participate in a knowledge exchange workshop. The workshop aimed to (a) highlight local research and innovation in youth-focused digital mental health services; (b) learn more about current policy and practice issues in inclusive digital mental health for youth in Canada, (c) participate in generating action recommendations to address challenges to inclusive, diverse and equitable digital mental health services, and (d) to synthesize cross-sector feedback to inform future training curriculum, policy, strategic planning and to stimulate new lines of patient-oriented research. Eleven challenge themes emerged related to white-colonial normativity, lack of cultural humility, inaccessibility and affordability of participating in the digital world, lack of youth and community involvement, risks of too much digital time in youth's lives, and lack of scientific evidence derived from equity-deserving communities. Nine action recommendations focused on diversifying research and development funding, policy and standards, youth and community led promotion, long-term trust-building and collaboration, and needing to callout and advocate against unsafe digital services and processes. Key policy, training and practice implications are discussed.

Guidance for unbiased predictive information for healthcare decision-making and equity (GUIDE): considerations when race may be a prognostic factor.

Clinical prediction models (CPMs) are tools that compute the risk of an outcome given a set of patient characteristics and are routinely used to inform patients, guide treatment decision-making, and resource allocation. Although much hope has been placed on CPMs to mitigate human biases, CPMs may potentially contribute to racial disparities in decision-making and resource allocation. While some policymakers, professional organizations, and scholars have called for eliminating race as a variable from CPMs, others raise concerns that excluding race may exacerbate healthcare disparities and this controversy remains unresolved. The Guidance for Unbiased predictive Information for healthcare Decision-making and Equity (GUIDE) provides expert guidelines for model developers and health system administrators on the transparent use of race in CPMs and mitigation of algorithmic bias across contexts developed through a 5-round, modified Delphi process from a diverse 14-person technical expert panel (TEP). Deliberations affirmed that race is a social construct and that the goals of prediction are distinct from those of causal inference, and emphasized: the importance of decisional context (e.g., shared decision-making versus healthcare rationing); the conflicting nature of different anti-discrimination principles (e.g., anticlassification versus antisubordination principles); and the importance of identifying and balancing trade-offs in achieving equity-related goals with race-aware versus race-unaware CPMs for conditions where racial identity is prognostically informative. The GUIDE, comprising 31 key items in the development and use of CPMs in healthcare, outlines foundational principles, distinguishes between bias and fairness, and offers guidance for examining subgroup invalidity and using race as a variable in CPMs. This GUIDE presents a living document that supports appraisal and reporting of bias in CPMs to support best practice in CPM development and use.

When Your Infrastructure Is a Buggy Program: Understanding Faults in Infrastructure as Code Ecosystems

Modern applications have become increasingly complex and their manual installation and configuration is no longer practical. Instead, IT organizations heavily rely on Infrastructure as Code (IaC) technologies, to automate the provisioning, configuration, and maintenance of computing infrastructures and systems. IaC systems typically offer declarative, domain-specific languages (DSLs) that allow system administrators and developers to write high-level programs that specify the desired state of their infrastructure in a reliable, predictable, and documented fashion. Just like traditional programs, IaC software is not immune to faults, with issues ranging from deployment failures to critical misconfigurations that often impact production systems used by millions of end users. Surprisingly, despite its crucial role in global infrastructure management, the tooling and techniques for ensuring IaC reliability still have room for improvement. In this work, we conduct a comprehensive analysis of 360 bugs identified in IaC software within prominent IaC ecosystems including Ansible, Puppet, and Chef. Our work is the first in-depth exploration of bug characteristics in these widely-used IaC environments. Through our analysis we aim to understand: (1) how these bugs manifest, (2) their underlying root causes, (3) their reproduction requirements in terms of system state (e.g., operating system versions) or input characteristics, and (4) how these bugs are fixed. Based on our findings, we evaluate the state-of-the-art techniques for IaC reliability, identify their limitations, and provide a set of recommendations for future research. We believe that our study helps researchers to (1) better understand the complexity and peculiarities of IaC software, and (2) develop advanced tooling for more reliable and robust system configurations.

Analysis of SR-IOV in Docker containers using RTT measurements

Cloud computing, a central pillar of modern IT infrastructure, faces constant challenges in provisioning and optimizing network performance, specifically regarding low-latency communication. This study investigates the impact of Single Root I/O Virtualization (SR-IOV) as a critical Quality of Service (QoS) enabler in virtualized environments. Data plane innovative technologies for virtual servers, especially SR-IOV technology, emerged as a promising solution adopted in data centers. When combined with Peripheral Component Interconnect (PCI) Passthrough in Docker environments, SR-IOV promises significant network performance gains. Our rigorous experimental methodology demonstrates that integrating SR-IOV reduces Round-Trip Time (RTT) latency by up to 15 times compared to the traditional Linux based Bridge configuration used in Docker, without significant additional costs. This research is particularly relevant for system administrators, data center professionals, and network traffic engineers, providing them valuable information into optimizing communication in cloud computing environments. By addressing this critical gap in knowledge, our study serves as a practical guide for the effective implementation these emerging technologies for network virtualization. In terms of practical applicability, the results raise valuable insights into the performance and implications of implementing SR-IOV and PCI Passthrough in a Docker environment. As a result, more informed decisions are tailored to the specific requirements of different usage scenarios.

Optimization challenges of resources in it outsourcing companies in uncertain market conditions

The introduction of computer networks can significantly speed up the execution of information processes, as well as increase the efficiency of distribution and use of hardware, software and information resources. In a network, different computers perform different functions. Computers that give other computers access to their resources and manage the distribution of network resources are called servers. Those computers that use the servers' resources are known as clients. The article is devoted to the study of the important issue of the selection and use of tools for the order of server administration, which manage and maintain the server infrastructure in the environment of the network of computer clubs in order to determine the classification of system server administration tools, which are necessary for effective management of servers in computer networks. Carrying out various tasks requires making decisions about choosing server administration tools from the many available or developing new ones for managing and maintaining the server infrastructure, which leads the company to achieve business goals. Difficulties with the choice of effective tools for solving tasks lie in the competence of network administrators. This issue is especially important when it comes to training system administrators. That is, it is necessary to achieve certain educational goals, after achieving which the network administrator will be able to: describe the functions of the administration center, describe the rules for the effective use of package tools for system administration, determine the procedure for dispatching servers; use a variety of remote server administration tools to manage servers; apply cross-platform administration tools, apply tools for automating the performance of individual administration tasks, etc. To solve the problem, a list of typical groups has been defined: 1) administration of user groups; 2) administration of security measures; 3) administration of local and global networks; 4) monitoring of events and resources; 5) data archiving and recovery. Classes of tools for automating system administration tasks are offered: tool packages for system administration; cross-platform administration tools; tools for individual administration tasks. Considerable attention in the course is given to the analysis of the classes of system administration tools, since knowledge of system administration tools is necessary to troubleshoot, test, communicate, and fix the systems needed to continue operation. With the right tools, the job becomes less tedious as many tasks can be accomplished with these system administration tools. Overall, the article provides valuable information for system administrators looking for ways to improve their system administration skills and knowledge and may be useful for companies looking for ways to optimize their server infrastructure.

An expert system of recommendations for combating cyber threats using CVSS metrics and game theory

This study is focused on the creation of an expert system for generating recommendations on cyber security. The developed expert system uses a game-theoretic model as a inference engine to transform expert knowledge into recommendations for end-users, who may be chief IT security officers (CISOs), system administrators, or cyber security engineers. Expert knowledge is presented in the form of an estimate of the base group of CVSS metrics - Common Vulnerability Score System, for each type of attack and adjusted values of CVSS in the case that the counterattack strategy is applied. Given a set of attacks and a base of expert attack knowledge, the system generates a game matrix of zero-sum game with a cybercriminal and a cyberdefense expert as players. The inference engine of the expert system is a game-theoretic model responsible for solving the game using the Brown-Robinson iterative method and generating cyber protection recommendations. An experiment was conducted on the convergence of the BrownRobinson algorithm on the 2022 vulnerability dataset from the Cybersecurity and Infrastructure Security Agency database, as a result of which it was determined that the convergence of the algorithm for solving the matrix game is achieved at a number of iterations of 1000. As a result of the work, expert system was designed and implemented along with the Web interface, which provides input by experts of CVSS level assessments of collected threats, threats countermeasures and output of recommendations for combating cyber threats

CPanel Server Hosting Security Against Malware and DDoS Attacks on the Open Journal System Platform

Purpose: This research analyzes the security of cPanel in protecting Open Journal Systems (O.J.S.) from DDoS attacks and malware infections. Since contemporary threats to this environment are continuously evolving, this investigation seeks to offer empirical findings and applicable suggestions for platform managers of academic publishing platforms. Methods: The method applies the scope of the literature study and tests system-specific security using cpanel features to test Imunify360, SSL Manager, IP Blocker, Site Quality Monitoring, Awstats, and Jetbackup. This is then followed by observing the server logs on cPanel, where any suspicious activities or signs of attacks can be identified. It contributes to the detection of attack patterns and weaknesses in a system. Result: This indicates several default settings within cPanel were found to be vulnerable and could allow exploitation for DDoS purposes. Tools available in cPanel helped eliminate malware and strengthen defense against DDoS attacks. This is verified by the AWStats check, which means a quicker and more secure access time from the server. Novelty: This study combines many security features and tools from cPanel to implement a complete manner of detecting and improving its security. This method will not only help find out what the weak points are but also provide actionable solutions that can be employed to secure your application. The research results offer a practical guide for system administrators to enhance cPanel security configurations. This includes applying amended security settings and using more tools to safely sweep O.J.S. from online threats.

Validity and Reliability of an Evaluation Instrument for English Curriculum System in Chinese Vocational Higher Education Institutions

The English curriculum is the basic part of the curriculum system of vocational higher education institutions (VHEIs) in China, and it is the public compulsory curriculum that students of all majors must study. It not only cultivates students' ability to learn and apply English but also lays an English foundation for students' future further learning and lifelong development. The purpose of this study is to validate the evaluation instrument for English curriculum system. This is a quantitative research and the questionnaire has adapted from previous scholars. A stratified random sampling technique has been employed to select 350 English lecturers from a total of 864 English lecturers at 20 vocational HEIs in Shandong Province, China. The results showed: ⅰ) Each dimension Clonbach alpha coefficient and McDonald’s omega (Composite reliability) are more than 0.70. ⅱ) For the convergent validity, each item factor loading > 0.5, each dimension AVE >0.5. ⅲ) For the discriminant validity, the square root of the AVE of the five dimensions is greater than the corresponding correlation coefficients between the two dimensions. ⅳ) Measurement model meet the fit indices, that CMIN χ2=411.228, with degrees of freedom (df) 314, CMIN/df=1.310 (1-3), CFI=0.979 (>0.9), GFI=0.916 (>0.9), NFI=0.916 (>0.9), and RMSEA=0.031(<0.08). The results prove that this English curriculum implementation instrument has good validity and reliability. The instrument can measure the level of English curriculum systems in VHEIs in Shandong Province, China. The research findings showed there were five dimensions in the evaluation of English curriculum system. The research can be used as the basis for evaluation curriculum system for other researchers and education administrators.

Identifying anticipated challenges when implementing group care: Context-analyses across seven countries to develop an anticipated challenges framework

ProblemDespite increasing interest in Group Care worldwide, implementation is challenging. BackgroundGroup Care is an evidence-based perinatal care model including three core components: health assessment, interactive learning, and community building. It has several advantages for service users and providers compared to individual perinatal care. AimWe aimed to identify anticipated challenges when implementing Group Care, and to develop a supporting tool based on these challenges. MethodsContext analyses through Rapid Qualitative Inquiries were conducted in 26 sites in seven countries to gain insight into the anticipated challenges when implementing Group Care. Data triangulation and investigator triangulation were applied. The context analyses generated 330 semi-structured interviews with service users and other stakeholders, 10 focus group discussions, and 56 review meetings with the research teams. FindingsWe identified six surface structure anticipated challenges categories (content, materials, facilitators, timing, location, group composition), and five deep structure anticipated challenges categories (health assessment, scheduling Group Care into regular care, enrolment, (possible) partner organisations, financials) occurring in all participating sites, leading to the development of the Anticipated Challenges Framework. ConclusionCompleting the Anticipated Challenges Framework raises awareness of anticipated challenges if sustainable Group Care implementation is to succeed and encourages the initiation of a concrete action plan to tackle these challenges. Application of the framework may offer important insights to health systems administrators and other key stakeholders before implementing Group Care. In the medium- and long-term, insights gained may lead to greater possibilities for sustainability and to the most cost-effective approaches for implementing Group Care.

Patient reported measures of continuity of care and health outcomes: a systematic review

BackgroundThere is a considerable amount of research showing an association between continuity of care and improved health outcomes. However, the methods used in most studies examine only the pattern of interactions between patients and clinicians through administrative measures of continuity. The patient experience of continuity can also be measured by using patient reported experience measures. Unlike administrative measures, these can allow elements of continuity such as the presence of information or how joined up care is between providers to be measured. Patient experienced continuity is a marker of healthcare quality in its own right. However, it is unclear if, like administrative measures, patient reported continuity is also linked to positive health outcomes.MethodsCohort and interventional studies that examined the relationship between patient reported continuity of care and a health outcome were eligible for inclusion. Medline, EMBASE, CINAHL and the Cochrane Library were searched in April 2021. Citation searching of published continuity measures was also performed. QUIP and Cochrane risk of bias tools were used to assess study quality. A box-score method was used for study synthesis.ResultsNineteen studies were eligible for inclusion. 15 studies measured continuity using a validated, multifactorial questionnaire or the continuity/co-ordination subscale of another instrument. Two studies placed patients into discrete groups of continuity based on pre-defined questions, one used a bespoke questionnaire, one calculated an administrative measure of continuity using patient reported data. Outcome measures examined were quality of life (n = 11), self-reported health status (n = 8), emergency department use or hospitalisation (n = 7), indicators of function or wellbeing (n = 6), mortality (n = 4) and physiological measures (n = 2). Analysis was limited by the relatively small number of hetrogenous studies. The majority of studies showed a link between at least one measure of continuity and one health outcome.ConclusionWhilst there is emerging evidence of a link between patient reported continuity and several outcomes, the evidence is not as strong as that for administrative measures of continuity. This may be because administrative measures record something different to patient reported measures, or that studies using patient reported measures are smaller and less able to detect smaller effects. Future research should use larger sample sizes to clarify if a link does exist and what the potential mechanisms underlying such a link could be. When measuring continuity, researchers and health system administrators should carefully consider what type of continuity measure is most appropriate.

Development of a POS System with Computer Vision for Automated Retail Checkout

A Point-of-Sale (POS) is a computerized system of hardware and software utilized by businesses to complete sales transactions. In conventional POS setups, cashiers manually scan individual product barcodes, before processing the totals. This manual procedure is laborious and often leads to long queues and waiting times, especially during peak hours, ultimately affecting customer experience and retention. This work seeks to automate the product scanning procedure with a computer vision approach, thereby expediting the sales process. An efficient YOLOv4 object detection model was trained on a custom dataset of common products found in Malaysian retail stores. 550 images were initially acquired and split 80:20 into training and validation groups; further augmentation tripled the size of the training group to 1,320 images. Training was conducted for 10,000 epochs, at 0.0013 learning rate. During training, the model achieved 99.19% mAP, 87.42% average IoU, and a 0.40 average loss. Subsequently, the model was deployed on a low-power single-board computer running a transaction notification program. To evaluate its performance, 10 instances of shopping carts with random product combinations were processed using the system. The system autonomously identified and quantified all products through its video feed, generating itemized bills in real-time. Fixed with a 0.9 confidence threshold, the system yielded a 98% average accuracy across all object classes. On average, transactions, from product detection to delivering the itemized bill to the system administrator, were processed in just 14 seconds. This POS system holds potential for integration with unmanned stores, offering a seamless shopping experience.

Optimized Decentralized Reward Distribution(1)

In DeFi (Decentralized Finance) applications, and in dApps (Decentralized Application) generally, it is common to periodically pay interest to users as an incentive, or periodically collect a penalty from them as a deterrent. If we view the penalty as a negative reward, both the interest and penalty problems come down to the problem of distributing rewards. Reward distribution is quite accomplishable in financial management where general computers are used, but on a blockchain, where computational resources are inherently expensive and the amount of computation per transaction is absolutely limited with a predefined, uniform quota, not only do the system administrators have to pay heavy gas fees if they handle rewards of many users one by one, but the transaction may also be terminated on the way. The computational quota makes it impossible to guarantee processing an unknown number of users. We propose novel algorithms that solve Simple Interest, Simple Burn, Compound Interest, and Compound Burn tasks, which are typical components of DeFi applications. If we put numerical errors aside, these algorithms realize accurate distribution of rewards to an unknown number of users with no approximation, while adhering to the computational quota per transaction. For those who might already be using similar algorithms, we prove the algorithms rigorously so that they can be transparently presented to users. We also introduce reusable concepts and notations in decentralized reasoning, and demonstrate how they can be efficiently used. We demonstrate, through simulated tests spanning over 128 simulated years, that the numerical errors do not grow to a dangerous level.

Optimalisasi Monitoring Traffic Komunikasi Data dan Penggunaan Resource Network Equipment Dalam Jaringan Lokal di IBI-K 1957

Monitoring a network and its device resources is very necessary in a data communications network, because based on the monitoring results, we can find out how much network resources are used, especially firewall and server devices. The monitoring carried out previously used an application that was accessed via remote desktop, where the application could only monitor data communication traffic used by users on the network. The use of remote desktops is very vulnerable from a network security perspective because it is often the target of exploration by cybercriminals or so-called black hackers. For this reason, monitoring of network devices is optimized using an open-source based application that can visualize the results of monitoring these devices on a web basis. By implementing this application, it can be concluded that it is able to fulfill the need for monitoring the use of resources and data communication traffic in the network so that if there is something unusual it can be immediately addressed by a System Administrator.

The Premier Medical Education Model: Improving Preceptor Recruitment in Underserved Areas.

Building on research highlighting the success of tribal, rural, and underserved clerkships to increase students' intention to practice family medicine in these areas, we explored the perspectives of prospective precepting physicians and administrators to develop an optimal structure to facilitate recruitment of external preceptors. We conducted semistructured interviews with family physicians (N=14) and health system administrators (N=14) working in tribal, rural, and underserved areas. Discussions were recorded, transcribed verbatim, and coded independently by two researchers. Applying rapid assessment qualitative research methods, we used a framework method to identify emergent themes that were applied to improve the recruitment of external preceptors. Physicians identified key facilitating factors and barriers to serving as a preceptor, which paralleled those common within the existing literature. However, administrators were motivated to serve as a precepting site to increase the potential of recruiting future physicians. We developed the Premier Medical Education Hub model to align these different but compatible interests with the goal to increase preceptor participation. In this model, each host site dedicates staff and adopts standardized procedures to manage rotations, hosts at least five students annually, provides housing, has procedures to facilitate electronic health record access, and offers student immersion experiences. As practice ownership shifts from physician-owned to health system ownership, administrators become the gatekeepers for prospective preceptors. Our findings demonstrate that integrating the compatible interests between physicians and administrators allows for the creation of a synergistic model that facilitates preceptor recruitment.

RESOURCES’ IDENTIFICATION IN EDUCATION SYSTEMS

The use of computers and internet for sharing information has proved to be reliable and cost-effective. Therefore, use of ICT in education systems is likely continue increasing in contributing to the efficiency of educational record keeping. However, it is necessary to secure computer equipment and information systems. Consequently, proactive measures to ensure security of data in education system is extremely important. This means education systems administrators, education policy makers and stakeholders need to have standard safety measures. The core governing principle for good standing information security posture in modern organization is confidentiality, integrity and availability (CIA). First, confidentiality is make data available or disclosed to authorize users only. Second, integrity is to preserve the accuracy and completeness of data both at rest and on-transit. Third, availability is to make information in education systems timely and reliably accessible to authenticated and authorized users. These security goals relies on adequate identification system. Identification is the key that verifies the authenticity of users and evaluate if a user is authorize to access the system. This paper provide identification technologies for both human and material resources in education systems. Since education data are stored in database, identification is a fundamental aspect of database system to create, retrieve, update and delete a record. Ultimately, identification of database record lays a solid foundation for CIA realization in information security

Design and implementation of a mobile medical and continuing care system based on wireless sensor networks

The Android system has good compatibility, freedom, rich hardware resources and a good development environment. At the same time, it can also work with Google services to obtain external support. Android is an open source operating system platform, which is similar to the iOS platform. In contrast, developers have more room for development, making the Android platform more people use. This article aims to develop a mobile medical system based on the Android operating system that integrates search engines, maps, and hospital HIS systems. The users are mainly patients, doctors and system administrators. Patients can register online and use mobile healthcare to pay online. They can also upload various physical indicators to record their daily health status. The establishment of health files is convenient for doctors to make health assessments and provide patients with medical consultation and medical health protection. Patients can also realize hospital navigation, intra-hospital navigation, and view various hospital inspection reports through the APP. The design of mobile medical service system is to design user behavior in the system based on the concept of service design. Therefore, in the process of system design, it is necessary to comprehensively consider service design principles and related factors, and propose behavior design principles that conform to service design theory. This study uses a mutual continuation care platform to implement seamless care for patients. Patients and medical staff can realize the continuation of the relationship and the continuity of information, and the patients can receive comprehensive guidance in a timely and effective manner. It can provide a reference basis for improving the continuity management and information management of patients in China, and provide reference value for the standardization and standardization of patients' continuation of nursing care standards and procedures.