Implementation Of System Research Articles

Rancang Bangun Sistem Informasi Manajemen Penjualan Kopi Pada Coffee Shop Konamu Menggunakan Sistem Point Of Sale

The purpose of this research is to develop a coffee sales management information system at the KonamuCoffee Shop using a Point of Sale system to increase efficiency in sales management. The method used in thisstudy is the system development life cycle method, starting from system requirements analysis, system design,system implementation, to system testing. In the system requirements analysis stage, assistance is providedfor the problems faced by Konamu Coffee Shop in sales management. Furthermore, a system design is carriedout using the Point of Sale system to facilitate the transaction process and sales management. The result ofthis research is a coffee sales management information system that is integrated with the Point of Sale system.This system can assist Konamu Coffee Shop in managing sales transactions, as well as generating sales andfinancial reports. With this system, it is hoped that the Konamu Coffee Shop can increase efficiency inmanaging coffee sales.

Intelligent Decision Support System in Healthcare using Machine Learning Models

Background: The use of intelligent decision support systems (IDSS) is widespread in the healthcare industry, particularly for real-time data, client and family history datasets, and prevalent patient features. Objective: A massive chunk of various kinds of health data sets, including sensor information, medical evidence, and omic statistics, are produced by the modern techniques in this field and eventually transferred to a machine learning (ML) element for extracting data, categorization, as well as mining. Method: In recent times, many patents have been focused on healthcare monitoring; however, they do not adequately incorporate appropriate algorithms for data collection, analysis, and prediction. The data collected is used for predictive modelling, then additionally, machine learning techniques are assisting to compare acquired datasets mathematically for decision-making platforms that may learn to recognise the recent trend and anticipated future problems. Depending on the dataset type, ML-based techniques can assess the circumstances. Training datasets are crucial for correctly anticipating both current and emerging events as well as new challenges. Results: Since the importance of data acquisition determines how well learning models function, any deformed data of the types of dirty data, noisy data, unstructured data, and inadequate information results in inaccurate detection, estimate, and prediction. Conclusion: Additionally, in contrast to other approaches, the experimental findings demonstrate the usefulness of the proposed method as a widespread implementation of machine learning algorithms within healthcare systems.

Implementation and evaluation of a SARI surveillance system in a tertiary hospital in Scotland in 2021/2022

ObjectiveTo set up and evaluate a new surveillance system for severe acute respiratory infection (SARI) in Scotland. Study designCross-sectional study and evaluation of surveillance system. MethodsThe SARI case definition comprised patients aged 16 years or over with an acute respiratory illness presentation requiring testing for influenza and SARS-CoV-2 and hospital admission. Data were collected from SARI cases by research nurses in one tertiary teaching hospital using a bespoke data collection tool from November 2021 to May 2022. Descriptive analyses of SARI cases were carried out. The following attributes of the surveillance system were evaluated according to Centers for Disease Control and Prevention (CDC) guidelines: stability, data quality, timeliness, positive predictive value, representativeness, simplicity, acceptability and flexibility. ResultsThe final surveillance dataset comprised 1163 records, with cases peaking in ISO week 50 (week ending 19/12/2021). The system produced a stable stream of surveillance data, with the proportion of SARI records with sufficient information for effective surveillance increasing from 65.4% during the first month to 87.0% over time. Similarly, the proportion where data collection was completed promptly was low initially, but increased to 50%–65% during later periods. ConclusionSARI surveillance was successfully established in one hospital, but for a national system, additional sentinel hospital sites across Scotland, with flexibility to ensure consistently high data completeness and timeliness are needed. Data collection should be automated where possible, and demands on clinicians minimised. SARI surveillance should be embedded and resourced as part of a national respiratory surveillance strategy.

Design and implementation of an alcohol detection driver system

A technology called an alcohol detection driver system is used to stop drunk driving by identifying alcohol in a motorist's breath or blood. This technology correctly measures the amount of alcohol a driver has in their system using sensors and algorithms, and it stops the car from starting if the amount is more than the legal limit. The number of fatal accidents and traffic fatalities caused by drinking could be greatly decreased thanks to this technology. The main focus of this project is to carry out the experiment in lowering the number of alcohol-related incidents on the road. Alcohol detection devices come in a variety of forms right now, including ignition interlocks, passive alcohol sensors, and in-car breathalyzers. Although these systems have reduced the number of drunk driving accidents, there remain questions about their efficiency, dependability, and cost. According to the sensor's specs, the output voltage of the MQ-3 sensor reduces by 69% during the sensor's recovery period of 30 seconds at 69% of baseline resistance. To assess the long-term viability and efficiency of these systems in lowering alcohol-related accidents and enhancing traffic safety, more research is required.

Study on the Optimal Configuration of Battery Energy Storage System in Distribution Networks Considering Carbon Capture Units

Background: The implementation of Battery Energy Storage Systems (BESSs) and carbon capture units can effectively reduce the total carbon emissions of distribution networks. However, their widespread adoption has been hindered by the high investment costs associated with the BESSs and power generation costs of carbon capture units. Objective: The objective of this paper is to optimize the location and sizing of BESSs in distribution networks that comprise renewable power plants and coal-fired power units with carbon capture systems. The optimization process aims to minimize the grid’s impact from the configuration while maximizing economic cost savings and the benefits of reducing carbon emissions. Methods: A bi-layer optimization model is proposed to determine the configuration of BESSs. The upper layer of the model optimizes the size and operation strategy of the BESSs to minimize the configuration and power generation costs, using YALMIP and CPLEX optimization tools. Carbon emission reduction benefits are considered through deep peak-shaving and carbon tax. The lower layer of the model aims to optimizes the placement of the BESSs to minimize voltage fluctuation and network loss in the power grid. To achieve this, we improved the efficiency of the Nondominated Sorting Genetic Algorithm II (NSGA-II) to update the BESS’s placement. Results: The IEEE33-bus and IEEE118-bus systems were utilized for simulation and comparison in various scenarios. The findings demonstrate that the proposed configuration method can decrease the cost of investment and power generation. Furthermore, it reduces the degree of node voltage fluctuation and network loss in the distribution network. Conclusion: The study reveals that determining the optimal scale of BESSs can mitigate high energy consumption in carbon capture systems and improve the overall performance of power systems that integrate carbon capture technology and renewable power plants.

Decision Support System Software for Normal Pregnancy, in Maritime Medicine, Setting for Costal Situation, Recommended for Making A Decision Support System for Diving Fishermen

Background: The coastal situation in Indonesia with thousands of islands and its area, the use of Ultra Sono Graph (USG) as a tool for general practitioners will be useful to facilitate examinations, consult with experts, and make referrals easily and quickly. Objective: For ultrasound readings that require decisions, using the Decision Support System makes it easier and there are friends to discuss, indirectly with experts, even machines. Theoretical Basis: DSS is very important to clarify and speed up decision-making with the help of software and computers. Use Process: The ultrasound software will guide and direct the appropriate diagnosis so that decisions can be made or referred and handled quickly and precisely. DSS will be very useful in preventing accidents among diving fishermen, by using the P02 benchmark which is easy to use. Conclusion: The use of the Decision Support System for normal and abnormal pregnancy ultrasound is beneficial for coastal area support for early diagnosis and implementation of a referral system. By looking at examples of use like this, it is recommended to create a Decision Support System for Diving Fishermen.

Design and implementation of a polarization-encoding system for quantum key distribution

We present the design and implementation of a state-of-polarization (SOP) management technique and two efficient synchronizing methods for quantum key distribution (QKD) systems. This is achieved following a wavelength-division multiplexing approach, where the classical synchronization signal and the quantum states are propagated in the same optical fiber. The employed frame synchronization method is based on the monitoring of the quantum bit error ratio (QBER) of the quantum channel, thus avoiding additional hardware and high computational resources. We evaluate the operation of SOP generation method through the assessment of the individual response of the waveplates that comprise the employed electronic polarization controller. Finally, the performance was assessed by computing the overall QBER and the QBER contributions of each of the four polarization states associated with the different qubits. The measurements, obtained during six hours, show a slight variation of the QBER values associated with the individual contributions, reaching an overall QBER of 0.75%. This demonstrates the capability of the presented methods to operate, stably, with very low QBER values, making its application in practical QKD systems reliable.

Competency Standardization for Indonesian Tourism Human Resources: Implementation in Education, Training and Competency Certification

The increasing trend of Indonesia's tourism competitiveness has placed it as one of the priority industrial sectors in Indonesia. However, this achievement is not in line with increasing the competitiveness of human resources (HR). The national work competency standardization system (SKKN), which the Indonesian Government has implemented since 2012, has not been effective, and human resources' competitiveness has even shown a negative trend. It is feared that this situation will hamper the growth rate of Indonesia's tourism competitiveness in the future. The purpose of this study is to critically analyze the application of the SKKNI system, which is focused on education, training, and competency certification of Indonesian tourism human resources, to uncover the inhibiting factors for its implementation. This education, training, and competency certification are the main components in the performance of the SKKNI system in Indonesia. The research was carried out by reviewing the relevant literature, analyzing the processes and elements in applying the SKKNI system. Research data is secondary data collected from data sources of Government and non-government institutions and scientific and non-scientific literature available on official government websites and the internet. The research results are then triangulated to get a comprehensive picture and understanding of the application of the SKKNI system. The results showed that the implementation of the SKKN system was effective in increasing the capacity of Indonesian tourism human resources but has a tiny growth Quantitatively. The main obstacle is limited trainer, assessor, facilities, and educational, training, and certification institutions to produce trained and certified human resources of tourism.

The Impact of Unified Medical Insurance System Implementation (Nphies) on Healthcare Service Quality: Applied Research Case Study in Arrawdha General Hospital Dammam, Saudi Arabi

Ensuring high-quality healthcare services is crucial for the well-being of individuals and the overall development of societies. In Saudi Arabia, healthcare reform efforts under Vision 2030 emphasize the importance of enhancing healthcare service quality. One key aspect of these reforms is implementing the unified medical insurance system, NPHIES. This system aims to improve access to healthcare and enhance the quality of services provided. However, there is a lack of research examining the specific impact of NPHIES on healthcare service quality, particularly in hospitals like Arrawdha General Hospital in Dammam. This study aims to investigate the impact of NPHIES implementation on healthcare service quality at Arrawdha General Hospital in Dammam, Saudi Arabia. By examining the relationship between NPHIES and healthcare service quality, the study seeks to provide valuable insights that can inform healthcare policies and practices in the region. The study has adopted a quantitative approach, collecting data through a questionnaire administered to physicians and administrators at Arrawdha General Hospital. Statistical analysis (descriptive statistics, t-tests, ANOVA, and Pearson’s correlation coefficient) have been used to analyze the data. Statistical analysis showed no significant differences in NPHIES implementation or healthcare service quality based on demographics suggesting a consistent perception across different demographic groups. The study also identified a statistically significant positive effect of NPHIES on healthcare service quality, emphasizing its role in improving healthcare services. Future research should examine the impact of the Unified Medical Insurance System (NPHIES) implementation on elderly patient satisfaction and health outcomes in Saudi Arabia.

From Boardrooms to Classrooms: How Interorganizational Networks Influence Education Policy Adoption

This paper examines how relationships among government and “outside” organizations influenced policy implementation of new dropout prediction data systems. Using comparative historical and network analyses of three cities, I suggest the concept of interorganizational coupling—highlighting how the dependence and (in)formal collaborations among local school improvement organizations affected implementation speed, variation, and constraint. In Chicago, the loosely coupled system influenced slow and varied implementation, sustained by interpersonal relations and challenged by unclear division of labor. In Philadelphia, the tightly coupled system shaped swift and uniform changes, constrained by questions of sustainability. In New York, the tightening system led to fast yet variable transformations, limited by competition among organizations. Broadly, the article contributes to studies of education policies, interorganizational networks, and school improvement.

Effective Strategies for Human Resource Development in the Digital Era

The rapid development of digital technology has brought significant changes in various aspects of life, including the field of human resource management (HR). This article aims to identify and analyze effective strategies that can be applied in human resource development in the digital era. In this context, HR development strategies do not only focus on improving technical skills, but also on developing soft skills which are essential for adaptation in a dynamic work environment. This research uses a qualitative approach with a comprehensive literature study method, reviewing various academic and practical sources. relevant to the topic. The main findings of this study show that the integration of technology in the training and development process, the formation of a work culture that supports innovation, and the implementation of a digital-based performance management system are some of the key effective strategies. Apart from that, the importance of visionary and adaptive leadership has also been identified as a determining factor for success in HR development in the digital era. This article provides insight for HR practitioners and managers to formulate HR development policies and programs that are relevant to the demands of the times. In addition, this research also makes a theoretical contribution by offering a conceptual framework for holistic and sustainable human resource development in the digital era.

Developing a System on the Dynamics and Implications of Parental and School Tracking of Children's Activities and Academic Progress

This paper explores the dynamics and effects of the school and parent tracking system at École Secondaire Islamique de Gisenyi. The study addresses the problem of monitoring students' academic performance and attendance by examining the extent to which parents and the school utilize tracking mechanisms. Motivations, benefits, and challenges associated with parental and school tracking practices are explored, considering factors like privacy concerns, parental involvement, and student autonomy. The research objectives focus on understanding how the implementation of a tracking system can enhance student success and the overall educational experience through collaborative efforts between parents and the school. By investigating the impact of parental tracking, the study aims to strengthen the bond between parents and the school, fostering a more supportive and engaged learning environment. The methodology involves qualitative data collection methods, including interviews and observations, to provide a comprehensive understanding of the dynamics and effects of the tracking system. The expected results are based on the assumption that the implementation of a tracking system at École Secondaire Islamique de Gisenyi will positively impact student progress, parental involvement, and overall school dynamics. The study's findings aim to contribute to the broader discourse on educational monitoring practices, inform policy recommendations, and empower stakeholders to make informed decisions regarding student tracking in Rwandan secondary schools. In conclusion, this research sheds light on the dynamics and effects of the school and parent tracking system at École Secondaire Islamique de Gisenyi. The anticipated positive outcomes of implementing a robust and user-friendly tracking system include enhancing student success and fostering collaboration between parents and school staff. Keywords: parental tracking, school tracking, data collection, tracking practices.

Energy loss and efficiency investigations of a dual clutch transmission based on adaptive experiment and analytical simulation

Energy transfer improvement and energy consumption reduction are getting more crucial in the automotive sector. As one of the essential elements directly influencing energy transfer in the powertrain system, transmission losses have been widely analyzed with both simulation and experimental approaches. For a better characterization of individual losses, this paper investigates and compares most of the available analytical models for further system implementation. Regarding laboratory experiments, an adaptive sampling strategy is presented and analyzed for various operating conditions. Compared to the traditional factorial design, the applied Gaussian Process Regression (GPR) delivers both estimations and their predictive variances in the entire experiment process. Besides, new measurement candidates can be determined with the prior information from GPR model. The analytical simulation and adaptive measurement are employed to investigate a seven-speed transmission. With both approaches, a detailed discussion about total transmission losses and individual loss mechanisms are performed under various operating conditions.

Models of quality costs by A. Feigenbaum, J. Juran, F. Crosby in the concept of the development of quality economics

Aim. Consider the specifics and features of quality cost models by A. Feigenbaum, J. Juran, F. Crosby in the context of increasing the efficiency of cost management.Objectives. Describe Joseph M. Juran's model (Juran's Spiral); classify quality costs by J. Juran — A. Feigenbaum; describe the classification of costs by F. Crosby.Methods. This work uses general scientific research methods: deduction, induction, generalization, comparative analysis, synthesis (unification), study and theoretical analysis.Results. In the modern economy, product quality plays a critical role, influencing the competitiveness and stability of the country's economic system, which makes quality management not just a formality, but a strategic necessity. Active implementation and development of quality systems is considered by enterprises as a means to improve reputation, increase market share and strengthen customer loyalty, and such systems help reduce costs by preventing defects and optimizing processes.Conclusions. An analysis of quality cost models was carried out as one of the key methods in increasing the economic efficiency of the organization. In modern quality management practice, special attention is paid not only to the identification and assessment of quality costs, but also to their role in the process of making managerial and technical decisions. This is especially true when planning the production activities of an enterprise. Quality cost analysis is becoming an important tool to help management formulate economically sound decisions.

Decommissioned open-pit mines are potential geothermal sources of heating or cooling for nearby population centres

In the shift to cleaner technologies, coal thermal power plants and mines will be decommissioned earlier than planned. These open-pit coal mines show potential as a geothermal source/sink for space heating and cooling, yet this post-closure use option remains unexplored. Here, we assess the techno-economic feasibility of providing heating and cooling using a decommissioned mine pit as a source or sink of heat for nearby population centres. Mixed integer quadratically constrained programming is employed for operational optimisation. The results show that thermal provisioning, considering centralised and decentralised arrangements, is economically competitive under specific scenarios regarding commodities prices, thermal demands and pit source temperature. Notably, a higher pit temperature reduces the overall thermal provisioning costs for residential thermal demands. Improvements in the economics due to transmission pipeline insulation are limited. While an expected decline in the system lifecycle costs occurs for decreasing electricity prices, the results highlight that the relative economic competitiveness of the thermal systems is tied to the individual alternatives’ performance at the same commodities prices. Overall, this paper identifies general conditions for techno-economic competitiveness for the implementation of shallow geothermal systems in the context of mine closure.

The Relevance of Creating an Integral Pedagogical System of Career Guidance Work with Students of Different Levels of Education

Introduction. The article reveals the issues of organizing career guidance and mentoring activities at a university through a description of holistic career guidance work with students of different levels of education in the “school – university” system; areas of career guidance work are considered; passive and active methods used in the implementation of career guidance activities are described. Methodology. The methodological basis of the study was based on the principles of the system-activity approach and the competence approach. To achieve the research goal, theoretical (analysis, synthesis, generalization and systematization of scientific publications data) and empirical (observation, survey) methods were used. Results. The authors have revealed an integrated pedagogical system of career guidance work with students of different levels of education, described the main directions of career guidance through the implementation of activities implemented at the university with school-age students and students, characterized the advantages of implementing an integrated pedagogical system of career guidance work with students. Conclusions. An integrated pedagogical system of career guidance is an important condition for the functioning of a university in a competitive environment. The innovative component of the presented holistic pedagogical system of career guidance work consists in the implementation of a continuous system of career guidance (“school – university”, “student – entrant – student – young specialist”), as well as in conducting career guidance and educational activities with students of different levels of education.

Design and Implementation of an IOT-based Smart Home Automation System in Real World Scenario

INTRODUCTION: Automation developments have significantly increased general convenience in modern technology. Our study focuses on developing and deploying an Internet of Things (IoT)–enabled smart home automation system that maximizes energy efficiency and improves convenience in residential settings. Our technology provides homes with an intelligent environment by smoothly combining several sensors, actuators, and communication protocols. We explore the challenges of creating a reliable and useful smart home systemthat works well in everyday situations. We investigate the difficulties, architectural issues, communication protocols, and security features specific to these systems.OBJECTIVES: This project aims to use a database server and Wi-Fi module to develop an effective and reasonably priced smart home automation system. It improves accessibility and convenience by enabling smartphone voice control of household appliances.METHODS: This project was developed using various implementation techniques, including wireless home automation via GSM technology, speech recognition-based systems, Blynk, and the Internet of Things. These techniques added up to a reliable and effective smart home system.RESULTS: Although it improved user routines, the IoT-based smart home system had latency problems. Interoperability issues are still present. Improvements were guided by user input. Using Blynk, our software manages loads remotely. CONCLUSION: A home automation system that is inexpensive and locally supplied can effectively operate household appliances. It is adaptable, scalable, and a component of future smart homes. IoT applications in real life revolutionize convenience and efficiency in living environments.

Linear System Identification-Oriented Optimal Tampering Attack Strategy and Implementation Based on Information Entropy with Multiple Binary Observations

With the rapid development of computer technology, communication technology, and control technology, cyber-physical systems (CPSs) have been widely used and developed. However, there are massive information interactions in CPSs, which lead to an increase in the amount of data transmitted over the network. The data communication, once attacked by the network, will seriously affect the security and stability of the system. In this paper, for the data tampering attack existing in the linear system with multiple binary observations, in the case where the estimation algorithm of the defender is unknown, the optimization index is constructed based on information entropy from the attacker’s point of view, and the problem is modeled. For the problem of the multi-parameter optimization with energy constraints, this paper uses particle swarm optimization (PSO) to obtain the optimal data tampering attack solution set, and gives the estimation method of unknown parameters in the case of unknown parameters. To implement the real-time improvement of online implementation, the BP neural network is designed. Finally, the validity of the conclusions is verified through numerical simulation. This means that the attacker can construct effective metrics based on information entropy without the knowledge of the defense’s discrimination algorithm. In addition, the optimal attack strategy implementation based on PSO and BP is also effective.

A novel formulation of low voltage distribution network equivalents for reliability analysis

Reliability analysis of large power networks requires accurate aggregate models of low voltage (LV) networks to allow for reasonable calculation complexity and to prevent long computational times. However, commonly used lumped load models neglect the differences in spatial distribution of demand, type of phase-connection of served customers and implemented protection system components (e.g., single-pole vs three-pole). This paper proposes a novel use of state enumeration (SE) and Monte Carlo simulation (MCS) techniques to formulate more accurate LV network reliability equivalents. The combined SE and MCS method is illustrated using a generic suburban LV test network, which is realistically represented by a reduced number of system states. This approach allows for a much faster and more accurate reliability assessments, where further reduction of system states results in a single-component equivalent reliability model with the same unavailability as the original LV network. Both mean values and probability distributions of standard reliability indices are calculated, where errors associated with the use of single-line models, as opposed to more detailed three-phase models, are quantified.

Current Status of Cold Injuries in the South Korean Military Over the Past 5 Years: Analysis and Assessment Based on the 2023-2024 Surveillance System.

This study aimed to examine the prevalence of cold injuries and review the cold injury monitoring system in the South Korean military. This study conducted a retrospective and cross-sectional analysis using data from the Defense Medical Statistic Information System (DMSIS) on cold injuries among military personnel from 2018 to 2023. It incorporated findings from the Korean Armed Forces Medical Command's cold injury surveillance system and analyzed cases from the Armed Forces Capital Hospital, covering all branches of the military by status and rank. An analysis of cold injury in the South Korean military over the past 5 years revealed varying numbers of cases treated, from 799 in 2018-2019 to 467 in 2022-2023. According to the surveillance system in 2023-2024, the Army experienced the majority of these cases, with 94.5% of the total. The incidence per 1,000 personnel was the highest in the Army at 0.98 compared to the Air Force and Navy/Marine Corps. Rank-based analysis indicated the most affected were private first-class soldiers. Frostbite was the most frequent condition, alongside chilblains, hypothermia, and immersion injuries, with no marked difference in the type of illness across branches. The study underscores the need for focused prevention and treatment, particularly in the Army. By analyzing data from a newly implemented surveillance system, it revealed a higher incidence of frostbite and chilblains among lower ranks. The findings highlight the importance of targeted educational measures and enhanced response strategies to protect personnel against cold injuries.