Data Collection System Research Articles

The contribution of ports to shipping decarbonization: An analysis of port incentive programmes and the executive role of port state control

In policy design, the contribution of ports to shipping decarbonization has been underestimated. Port incentive programmes have not contributed significantly to shipping decarbonization, and in the implementation of energy regulations, the role of the port state control has been exclusively limited to document control. This study aims to analyse the role of ports in shipping decarbonization by conducting an online survey and interviewing experts. We examine two proposals: first, a global incentive scheme focused solely on CO2 reduction, supported by the GHG Fund of the future IMO carbon pricing mechanism, acting as a rebate mechanism, and second, a voyage-based data collection and verification system. Experts have strongly supported the first proposal. The second proposal is technically feasible, since some verification firms and pioneer shipping companies have already started this practice. It is economically also feasible at a minor cost. A differentiated bunker levy based on these proposals is recommended at the end, in which ports play a significant role.

Assessing Survey Data to Study Traffic Flow Characteristics: An in-depth analysis of King Fahad Road, Al-Ahsa, Saudi Arabia

Traffic volume studies are crucial for understanding vehicle quantity, movements, and classifications at specific sites. This study aims to establish a correlation between flow rate and density, providing in-sights into traffic flow characteristics such as density, velocity, and flow, essential for effective road design. The proposed method combines automated (mobile phones and cars) and manual counts on separate sheets, offering a compelling alternative to traditional traffic study methods. The collected da-ta can be utilized for various purposes including estimating fuel consumption, road pricing, road user cost, and planning road network improvements. Acquiring precise traffic data using cost-effective, low-tech solutions is vital for comprehending urban traffic dynamics. Evaluating collected data, which encompasses traffic parameters like flow, density, and speed, is crucial for informing urban road de-sign and planning. For instance, traffic flow indicates throughput, density reflects traffic conditions, and speed is essential for calculating travel times. This investigation focused on King Fahad Road in Al-Ahsa, Saudi Arabia, chosen among three alternative urban roads based on varying traffic condi-tions. Smartphones and cars were used to collect traffic data during weekday evening peak hours, ana-lyzing the interrelation between traffic flow, density, and vehicle speed. Manual traffic counts were conducted to determine measured density and speed, which were then used to estimate calculated den-sity. Additionally, a statistical t-test was performed to validate measured density against calculated den-sity at a 5% significance level. The data collection systems utilized in this research provide a cost-effective solution, considering capital, operational, and maintenance expenses, while remaining por-table and non-intrusive to road users during surveys. These characteristics make the system a practical choice for implementation in developing nations where resources are constrained, rendering costlier al-ternatives economically unfeasible.

Design and Implementation of a Two-Wheeled Vehicle Safe Driving Evaluation System.

The delivery market in Republic of Korea has experienced significant growth, leading to a surge in motorcycle-related accidents. However, there is a lack of comprehensive data collection systems for motorcycle safety management. This study focused on designing and implementing a foundational data collection system to monitor and evaluate motorcycle driving behavior. To achieve this, eleven risky behaviors were defined, identified using image-based, GIS-based, and inertial-sensor-based methods. A motorcycle-mounted sensing device was installed to assess driving, with drivers reviewing their patterns through an app and all data monitored via a web interface. The system was applied and tested using a testbed. This study is significant as it successfully conducted foundational data collection for motorcycle safety management and designed and implemented a system for monitoring and evaluation.

Rapid Online Data Collection and Reporting to Local Health Departments during the Pandemic: The COVID-19 Outbreak Public Evaluation (COPE) Initiative SARS-CoV-2 Case Surveys.

To develop and implement a pilot online data collection tool to help local health departments with their COVID-19 pandemic response efforts and inform health department actions. The COVID-19 Outbreak Public Evaluation (COPE) was an online survey and was distributed by participating sites to individuals who recently tested positive for SARS-CoV-2. Surveys recorded participant demographics and assessed recent infection risk behaviors (eg, mask use, air travel), vaccination status, sleep and exercise habits, social behaviors and beliefs, and physical and mental health. Seven health departments participated in the initiative, which took place during May 1 to September 30, 2022. Identical items were administered to demographically representative samples of adults nationally in the United States within a similar timeframe. A total of 38555 participants completed surveys. Responses from participants with recent SARS-CoV-2 infections were compared with respondents from the national surveys who did not have evidence or awareness of prior SARS-CoV-2 infections. To implement of a process that allows health departments to receive data from local cases and compare this information to national controls during the COVID-19 pandemic. Fifty-four biweekly reports were provided to public health departments between May and September 2022. Information and comparisons within the reports were updated in response to evolving public health priorities for the pandemic response. The initiative helped to guide public health response efforts during the COVID-19 pandemic. Moreover, the receptiveness by local health departments and participants provides evidence to support this data collection and reporting model as a component of the public health response to future emergencies. This project demonstrates the feasibility of a centralized, rapid, and adaptive data collection system for local health departments and provides evidence to advocate for data collection methods to help guide local health departments to respond in a timely and effective manner to future public health emergencies.

Perkembangan Hukum Tata Negara Indonesia dan Implikasinya dalam Dimensi Negara Hukum

The study is entitled The Development of The Indonesian State Law and Its Implications in The Dimension of The Rule of Law. This research begins with the formulation of Article 1 paragraph (3) of UUD 1945 which states that “The State of Indonesia is a state of law”. Described as a rule of law, Indonesia is responsible for always following the law as a means of achieving its goals. The law of the State that regulates the administration, government and institutions of the state is regarded as the foremost guard in achieving the ideals of a country. In its history, the Indonesian Civil Code has passed through many dynamics of all time and has arrived at the present time to dedicate its functions. However, the unavoidable development of the world makes the law including the Law of the State must always adapt to various developments. However, in its implementation the law of the state has always faced with various implications. For that, this study was written with the primary purpose of finding out how the Law of State Order has implicated its development in the modern era in the dimension of the rule of law. In completing his research, this paper uses the method of research of the juridic study with the data collection system of the study of the library.

A systematic benchmarking framework for future assessments of soil health: An example from Denmark

Based on current evidence and established critical thresholds for soil degradation indicators, it is concerning that over 60–70% of European soils are unhealthy due to unsustainable management and the impact of climate change. Despite European and national efforts to improve soil health, significant gaps remain. The proposal for a Soil Monitoring and Resilience Law, to be implemented by the European Union, seeks to establish a framework for soil monitoring and promote sustainable management practices to achieve healthy soils by 2050. This requires extensive data collection and soil monitoring systems to accurately estimate soil health across Europe, considering the diversity of soil types, climates, and land uses. To establish a framework for soil monitoring, we must understand the site-specific status of soil and the ranges of soil health indicators across specific pedoclimatic regions. In our study, we evaluated the soil status in agricultural areas in Denmark using soil health indicators and a site-specific benchmarking approach. We compiled nationally representative datasets, combining point and model-informed data of soil parameters such as organic carbon content, bulk density, pH, electrical conductivity, clay-to-soil organiccarbon ratio, water erosion, and nitrogen leaching. By categorizing Danish agricultural soils into monitoring units based on textural classes, landscape elements, and wetland types, we calculated benchmarks for these indicators, considering different cropping systems. Our approach provided detailed point-based results and a spatially explicit overview of the status of soil health indicators in Denmark. We identified areas where soil deviates from the benchmarks of different indicators. Such deviations might indicate soil functions operating outside the normal range, posing potential threats to soil health. This proposed framework could support the establishment of a baseline for assessing the directionality of future changes in soil health. Moreover, it is adaptable for implementation by other countries to support assessments of soil health.

A qualitative study of clinicians' impressions regarding the implementation of a clinical and research data collection system

AbstractBackgroundSystematically collecting data on clientele databases allows for describing the clientele's needs and addressing various clinical research questions. Conducted in a university psychology clinic, this initiative seeks to improve the overall quality of care provided by integrating evidence‐based practices. This study works to bridge the gap between clinical practice and research.AimsThis study aimed to describe the potential repercussions and clinicians' impressions regarding the implementation of this procedure.Research DesignAn inductive qualitative approach, inspired by Husserl's descriptive phenomenology, was used. To be consistent with this approach, data analysis followed Giorgi's five‐step scientific phenomenological method.Data Collection and AnalysisSemi‐structured individual interviews were conducted with 14 volunteer clinicians using an interview guide. The data were analysed to extract central themes using Giorgi's method, which involves collecting verbal data, reading the data, dividing it into units of meaning, organising the data using the language of the discipline and synthesising the results.ResultsFive central themes emerged: barriers to implementation, potential impacts on therapy, recommendations to enhance participation, perceived utility and an attitude of openness.DiscussionThe pilot project provides valuable insights into the feasibility and acceptability of systematic data collection in a clinical setting. Clinician consultation proves to be essential in the implementation process, highlighting the importance of addressing practical and philosophical obstacles.ConclusionUnderstanding clinicians' experiences can guide future implementations of similar systems and improve clinical practice by supporting the integration of systematic data collection. Enhanced communication and training on the data collection system are suggested.

Enhancing Patient Outcomes Through Integrated Education and Navigation Programs at the Breast Cancer Comprehensive Center, National Cancer Institute, Cairo University.

Breast cancer remains a significant global health challenge, particularly in low- and middle-income countries where disparities in healthcare exacerbate the disease burden. The Breast Cancer Comprehensive Center at the National Cancer Institute, Cairo University, has implemented integrated patient navigation and education programs aimed at enhancing patient outcomes and healthcare quality.This study evaluated the effectiveness of these programs involving 2202 participants over 12 months. The methodology included systematic data collection, material preparation, and the application of tailored educational strategies to facilitate the patient's journey from diagnosis to treatment. The study utilized three-phased patient navigation assistance to provide comprehensive support.The programs significantly improved patient satisfaction, with over 90% of participants reporting high levels of contentment with the services received. Key improvements included enhanced understanding of breast cancer (including risk factors, symptoms, importance of seeking early care, and treatment options), reduction in patient anxiety, improved treatment adherence, and streamlined diagnostic and treatment processes. Notably, the use of audio-visual educational tools effectively bridged the literacy gap among patients.The integration of patient navigation and education systems at BCCC-NCI has proven to be a highly effective model for improving breast cancer care. This model not only enhances patient understanding and treatment compliance but also facilitates a more efficient healthcare process. The study underscores the potential for replicating this approach in similar healthcare settings globally, suggesting that such integrations can significantly improve cancer care outcomes.

Population-based incidence rates of 15 neuromuscular disorders: a nationwide capture-recapture study in the Netherlands

Most neuromuscular disorders are rare, but as a group they are not. Nevertheless, epidemiological data of specific neuromuscular disorders are scarce, especially on the incidence. We applied a capture-recapture approach to a nationwide hospital-based dataset and a patients association-based dataset to estimate the annual incidence rates for fifteen neuromuscular disorders in the Netherlands.The annual incidence rates per 100,000 population varied from 0.03/100,000 (95% CI 0.00 ‒ 0.06) for glycogenosis type 5 to 0.9/100,000 (95% confidence interval 0.7 ‒ 1.0) for myotonic dystrophy type 1. The summed annual incidence rate of these disorders was 4.1 per 100,000 per population. Nine of the provided incidence rates were previously unavailable, three rates were similar to the rates in the literature, and three rates were generally higher compared to previous findings but with overlapping confidence intervals.This study provides nationwide incidence rates for fifteen neuromuscular disorders predominantly diagnosed in adult life, nine which were previously unavailable. The capture-recapture approach provided estimates of the total number of individuals with neuromuscular disorders. To complete the gaps in the knowledge of disease frequencies, there is a need for estimates from an automated, obligatory data collection system of diagnosed and newly diagnosed patients with neuromuscular disorders.

Bridging the Gap : Aligning Teachers’ Pedagogical Beliefs with Learners’ Preferences of English Language Learning in The Adaptive Learning Era

This study aims to investigate the differing viewpoints of teachers and students regarding classroom participation, material delivery, teaching media, and assessment methods in the adaptive learning era. The study employs quantitative method, which involves the systematic collection and analysis of numerical data through statistical techniques. This study includes 10 teachers and 50 EFL undergraduate students from two universities in Indonesia, using a Likert scale questionnaire to collect data on various aspects of English language learning. The data were analysed using a t-test to find the mean, standards deviation, and p value of the responses in order to ascertained significant differences between the teachers and the students. The results reveal significant disparities between teachers' and students' perceptions across different dimensions of learning. While teachers prioritize delivery strategies and assessment methods, students focus more on delivery modes and traditional assessment types. However, both groups acknowledge the importance of autonomous learning and the effectiveness of diverse teaching media in enhancing engagement and motivation. The findings underscore the need for a balanced approach to learning that integrates both teacher preferences and student needs. Ultimately, understanding and addressing these discrepancies is essential for promoting meaningful and inclusive educational experiences in the adaptive learning era.

The Technology Evolution and Future Trend of Smart Blackboard

As an important tool for educational digitization, the function of the smart blackboard has gradually evolved from a single teaching information-sharing tool to a smart system for knowledge expression, sharing and generation. Smart blackboard technology has been experienced from chalk + blackboard to projection equipment + blackboard, to interactive electronic whiteboard, and then to today's integrated touch, high-definition display and artificial intelligence technology. The evolution process of the smart blackboard is characterized by interactivity, effectiveness and intelligence. At present, the smart blackboard has become a collection of many advanced technologies. It is gradually integrated into modern technologies such as artificial intelligence, cloud computing, big data analysis and the Internet of Things, making remote collaboration and intelligent classroom management possible. It has become a smart system for big data collection, mining and analysis, evaluation and feedback, and teaching decision-making. Looking forward to the future, the smart blackboard will pay more attention to user experience design, provide an immersive learning experience through Augmented Reality and Virtual Reality technology, and optimize personalized teaching content in combination with machine learning, to lay a foundation for building an intelligent and personalized teaching environment.

Fatal and non-fatal civilian injuries sustained during law enforcement-reported encounters in California, 2016–2021

BackgroundIn 2015, California passed AB 71 to create a state-wide Use of Force Incident Reporting Database (URSUS) to tabulate law enforcement-reported encounters that resulted in serious bodily injury, death or...

Current type 2 diabetes guidelines: Individualized treatment and how to make the most of metformin.

Evidence-based guidelines provide the premise for the delivery of quality care to preserve health and prevent disabilities and premature death. The systematic gathering of observational, mechanistic and experimental data contributes to the hierarchy of evidence used to guide clinical practice. In the field of diabetes, metformin was discovered more than 100 years ago, and with 60 years of clinical use, it has stood the test of time regarding its value in the prevention and management of type 2 diabetes. Although some guidelines have challenged the role of metformin as the first-line glucose-lowering drug, it is important to point out that the cardiovascular-renal protective effects of sodium-glucose co-transporter-2 inhibitors and glucagon-like peptide-1 receptor agonists were gathered from patients with type 2 diabetes, the majority of whom were treated with metformin. Most national, regional and international guidelines recommend metformin as a foundation therapy with emphasis on avoidance of therapeutic inertia and early attainment of multiple treatment goals. Moreover, real-world evidence has confirmed the glucose-lowering and cardiovascular-renal benefits of metformin accompanied by an extremely low risk of lactic acidosis. In patients with type 2 diabetes and advanced chronic kidney disease (estimated glomerular filtration rate 15-30 mL/min/1.73m2), metformin discontinuation was associated with an increased risk of cardiovascular-renal events compared with metformin persistence. Meanwhile, it is understood that microbiota, nutrients and metformin can interact through the gut-brain-kidney axis to modulate homeostasis of bioactive molecules, systemic inflammation and energy metabolism. While these biological changes contribute to the multisystem effects of metformin, they may also explain the gastrointestinal side effects and vitamin B12 deficiency associated with metformin intolerance. By understanding the interactions between metformin, foods and microbiota, healthcare professionals are in a better position to optimize the use of metformin and mitigate potential side effects. The United Kingdom Prospective Diabetes Study and the Da Qing Diabetes Prevention Program commenced 40 years ago provided the first evidence that type 2 diabetes is preventable and treatable. To drive real-world impact fromthis evidence, payors, practitioners and planners need to co-design and implement an integrated, data-driven, metformin-based programme to detect people with undiagnosed diabetes and prediabetes (intermediate hyperglycaemia), notably impaired glucose tolerance, for early intervention. The systematic data collection will create real-world evidence to bring out the best of metformin and make healthcare sustainable, affordable and accessible.

Sistem Pengelolaan Data Karyawan Secara Online di PT. DARMA HENWA, Tbk-ACP

The employee data collection system is an important part of employee management in the company. The information system required for the storage and management of employee information by PT Darma Henwa Tbk-ACP, a mining company in Asam-asam. In addition, this study also wants to find out the use of data collection information systems for employees at PT Darma Henwa Tbk-ACP and how this can affect operational efficiency and personnel management

A collaborative WSN‐IoT‐Animal for large‐scale data collection

AbstractIn recent years, large‐scale data collection systems have developed rapidly in many fields, including agriculture, transport and many others. The internet of things (IoT), whose main platform is wireless sensor networks (WSNs), is behind this development. Comprising thousands of sensors of different kinds, their main purpose is to collect and transmit data. Several data collection techniques have been proposed, including static, mobile and hybrid approaches. The challenges faced by these techniques are considerable, and include energy conservation, planning and trajectory optimisation during data collection, most importantly, the challenges related to the communication between the static sensors generally distributed in a more or less large geographical space and the mobile data collection system (UAV, vehicle, robot etc.). Not to mention the cost, which remains enormous for the agricultural sectors. A hybrid WSN‐IoT‐Animal that is self‐configured to improve data acquisition over large agricultural areas is presented. The main objective and originality of the heterogeneous semi‐modern scheme proposed here oscillating between traditional agriculture and precision agriculture is the use of animals as data collection tools. The main contribution here is the design of a simple and efficient model of data collection that is easily accessible by farmers by adapting the available resources. This model describes and adopts a sensor deployment method based on the notion of the hypergraph, which provides adequate coverage and ensures communication between the mobile sink and a subset of peripheral sensors chosen in alternation. Simulation results verify the effectiveness of the proposed protocol in terms of network lifetime compared to other works. In addition, the amount of data received by the mobile sink demonstrates the importance of this approach in terms of connectivity for large‐scale data collection.

Association between early pregnancy maternal blood pressure and risk of congenital heart disease in offspring

Objective: To analyze the association between maternal blood pressure and congenital heart disease (CHD) in offspring. Methods: From February 2018 to December 2020, pregnant women who participated in the China birth cohort study in Beijing Obstetrics and Gynecology Hospital, Shenzhen Maternal and Child Healthcare Hospital and Chengdu Women's and Children's Central Hospital were enrolled in this study. The baseline and follow-up information were collected using an electronic data collection system. Stepwise logistic regression model was used to analyze the association between maternal blood pressure including systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP) and pulse pressure difference (PP) in the first trimester of pregnancy and the risk of CHD in the offspring. A restrictive cubic spline curve was used to draw the dose-response curve between maternal blood pressure and CHD. Results: A total of 55 552 participants were included in this study. Of them, 31 038, 15 375 and 9 139 pregnant women were enrolled in Beijing Obstetrics and Gynecology Hospital, Shenzhen Maternal & Child Healthcare Hospital and Chendu Women's and Children's Central Hospital, respecitively. The age of pregnant women was (31.3±4.0) and the incidence of CHD in the offspring was 0.78% (435/55 552). Multivariable logistic regression model analysis showed that the increase of SBP (OR=1.01, 95%CI: 1.00-1.02), DBP (OR=1.01, 95%CI: 1.00-1.03) and MAP (OR=1.02, 95%CI: 1.00-1.03) in the first trimester were significantly associated with the risk of CHD in the offspring. The restrictive cubic spline analysis showed a positive linear association of SBP (Ptotal<0.001; Pnon-liear=0.315), DBP (Ptotal<0.001; Pnon-liear=0.928) and MAP (Ptotal<0.001; Pnon-liear=0.929) with the risk of CHD in the offspring. Conclusion: Maternal SBP, DBP and MAP in the first trimester of pregnancy were positively associated with the risk of CHD in the offspring.

Unpacking Conflict Process on the Korean Peninsula with Political and Seasonal Distribution

Under what conditions does a North Korean threat escalate to the actual use of force? To address this question, we delve into the underlying causal mechanism that shapes the entire conflict process on the Korean Peninsula. Dismissing the presumption that repeated disputes are independent of one another and that factors exhibit a monotonic effect across conflict stages, we direct our focus towards the comprehensive conflict process encompassing North Korea's provocation onset and escalation. Our approach involves the systematic collection of monthly data, which we analyze using appropriate statistical models to account for the selection effect. The empirical investigation not only corroborates our theoretical proposition but also uncovers several key factors that exhibit a non‐monotonic effect across various stages of conflict. The results indicate that North Korea's domestic factors and those within South Korea influence the onset of conflict, while the escalation stage is shaped by factors within the United States. Furthermore, our findings highlight the effect of seasonality, indicating an increased frequency of conflict onset and escalation during the summer season.

Surveillance of Antimicrobial Resistance in the ECOWAS Region: Setting the Scene for Critical Interventions Needed.

Antimicrobial resistance poses a significant challenge to public health globally, leading to increased morbidity and mortality. AMR surveillance involves the systematic collection, analysis, and interpretation of data on the occurrence and distribution of AMR in humans, animals, and the environment for action. The West African Health Organization, part of the Economic Community of West African States (ECOWAS), is committed to addressing AMR in the region. This paper examines the status of AMR surveillance in ECOWAS countries using available WHO data from the TrACSS survey and GLASS enrollments. The analysis reveals that while progress has been made, significant challenges remain. Twelve of the fifteen ECOWAS countries are enrolled in GLASS, and ten have developed national action plans (NAPs) for AMR. However, there is a need to ensure all countries fully implement their NAPs, continue reporting to GLASS, and use the data for evidence-based actions and decision making. Surveillance systems for AMR and antimicrobial consumption/use vary across countries with some demonstrating limited capacity. All countries, except Cabo Verde, reported having a reference laboratory for AMR testing. Strengthening laboratory capabilities, data management and use, and multisectoral coordination are crucial for effective AMR surveillance and response. Based on the findings and the regional context, it is essential to prioritize capacity building, data utilization, and the adoption of standardized guidelines for AMR surveillance. Collaboration among ECOWAS countries, the WAHO, and international partners is essential to address AMR comprehensively. Ensuring a consistent supply of essential antimicrobial medications and reagents is vital.

An Intelligent Manufacturing Management System for Enhancing Production in Small-Scale Industries

Industry 4.0 integrates the intelligent networking of machines and processes through advanced information and communication technologies (ICTs). Despite advancements, small mechanical manufacturing enterprises face significant challenges transitioning to ICT-supported Industry 4.0 models due to a lack of technical expertise and infrastructure. These enterprises commonly encounter variable production volumes, differing priorities in customer orders, and diverse production capacities across low-, medium-, and high-level outputs. Frequent issues with machine health, glitches, and major breakdowns further complicate optimizing production scheduling. This paper presents a novel production management approach that harnesses bio-inspired methods alongside Internet of Things (IoT) technology to address these challenges. This comprehensive approach integrates the real-time monitoring and intelligent production order distribution, leveraging advanced LoRa wireless communication technology. The system ensures efficient and concurrent data acquisition from multiple sensors, facilitating accurate and prompt capture, transmission, and storage of machine status data. The experimental results demonstrate significant improvements in data collection time and system responsiveness, enabling the timely detection and resolution of machine failures. Additionally, an enhanced genetic algorithm dynamically allocates tasks based on machine status, effectively reducing production completion time and machine idle time. Case studies in a screw manufacturing facility validate the practical applicability and effectiveness of the proposed system. The seamless integration of the scheduling algorithm with the real-time monitoring subsystem ensures a coordinated and efficient production process, ultimately enhancing productivity and resource utilization. The proposed system’s robustness and efficiency highlight its potential to revolutionize production management in small-scale manufacturing settings.

Web-Based E-Budgeting Design

Every year, the faculties and units at KH. A. Wahab Hasbullah University submit budget proposals to the Planning Department. Some common issues include low budget absorption and suboptimal reporting. Reporting also faces difficulties as everything is done manually. In an effort to address the aforementioned problems, a system needs to be developed to facilitate communication and coordination among various parties in budget creation, ensuring the formulation of a realistic and achievable budget. Thus, the E-Budgeting system is established to tackle these budget submission challenges. The research methodology involves several stages, including data collection methods (literature review, field study) and system development methods (design phase, coding phase, and testing phase). The goal of this research is to design a budget submission and preparation system at KH. A. Wahab Hasbullah University in Tambakberas Jombang that can expedite the budget disbursement process. The final outcome of this research is the creation of a web-based E-BUDGETING application providing budget processing information accessible to the academic community at KH. A. Wahab Hasbullah University.