Hasil untuk "Management information systems"

N. Gorla, T. Somers, Betty Wong

R. Allen, L. S. Pereira, T. Howell et al.

B. Becerik-Gerber, F. Jazizadeh, Nan Li et al.

J. Rowley

A. H. Sayed, A. Tarighat, N. Khajehnouri

P. Stone, M. Veloso

D. Stirling

J. Meredith, S. Mantel

S. Jarvenpaa, B. Ives

Shin-Ta Liu

E. Turban, D. Leidner, E. McLean et al.

R. Weng Zheng, J. Velez, N. Rodriguez et al.

ABSTRACT: The efficiency of automatic milking systems depends on the continuous flow of cows, which may be affected by specific cow conducts, including milking unit preference. Moreover, providing resources that favor the expression of natural cow behaviors during the milking process may result in improved animal welfare. The objective of this study was to analyze the selection behavior for automatic milking units, comparing preference consistency across the lactation of 3 genetic groups (Holstein [HO], Jersey [JE], and Holstein × Jersey [HJ]) in a multibreed organic dairy farm using a batch milking system. To expand the main objective, a secondary aim was to examine the relationship between milking unit selection behavior and premilking waiting time (WT). The study included data from 1,762,461 milking events in 1,355, 1,876, and 475 HO, JE, and HJ cows, respectively, from May 2023 to September 2024 in a commercial organic grass-fed dairy in Texas in the United States. Cows were moved to the waiting area of the milk center twice per day, where they could select their milking visits among 22 automatic milking units. Cow preferences were analyzed at 3 levels: automatic milking unit (n = 22), barn location (east, n = 11; west), and robotic arm configuration (left, n = 11; right). Milking visit information was collected from the management software to establish the frequency of specific milking unit usage per cow during the study period. Subsequently, the frequencies for selection of the top choice for 1, 3, and 5 automatic milking units, the top choice for barn location, and the top choice for robotic arm configuration were calculated for each cow. Preference consistency scores (PCS) were calculated as a ratio between the excess frequencies of the first choice over the base frequency of any option other than the first choice. The PCS calculations considered the frequency of access to each automatic milking unit, barn location, and robotic arm configuration in 30-d periods until 305 DIM. Premilking waiting times were calculated for each cow as the difference between the entry time into the waiting area of the milk center, indicated by a pedometer affixed in the rear leg of each cow, and the start of the corresponding milking, as indicated by the milking unit in use. Least squares means for PCS were calculated within parity category by genetic group for each 30-d period and compared using repeated-measures ANOVA. Subsequently, PCS and WT values were categorized into quartiles, and LSM for PCS and WT were calculated for each of the PCS by WT combinations within each parity category. As indicated by the chi-squared test of independence and the ANOVA, the frequency of selection for the top choice and the PCS were different from those expected by random selection of automatic milking unit, barn location, and robotic arm configuration, signifying different levels of selection behavior in the study cows. Overall, HO cows evidenced the greatest PCS values, indicating more consistent behaviors in milking unit preference. Additionally, the analysis of the association between PCS and WT indicated that greater PCS were associated with shorter WT. The resulting PCS suggest variable degrees of consistency in the selection behavior for automatic milking units in dairy cows. The selection behaviors identified in this study may have implications for cow welfare, as well as for improving cow traffic and system efficiency.

Tracy A. Jenkin, J. Webster, Lindsay McShane

Emmanuel Ahoa, Ayalew Kassahun, Cor Verdouw et al.

Traditional farming has evolved from standalone computing systems to smart farming, driven by advancements in digitalization. This has led to the proliferation of diverse information systems (IS), such as IoT and sensor systems, decision support systems, and farm management information systems (FMISs). These systems often operate in isolation, limiting their overall impact. The integration of IS into connected smart systems is widely addressed as a key driver to tackle these issues. However, it is a complex, multi-faceted issue that is not easily achievable. Previous studies have offered valuable insights, but they often focus on specific cases, such as individual IS and certain integration aspects, lacking a comprehensive overview of various integration dimensions. This systematic review of 74 scientific papers on IS integration addresses this gap by providing an overview of the digital technologies involved, integration levels and types, barriers hindering integration, and available approaches to overcoming these challenges. The findings indicate that integration primarily relies on a point-to-point approach, followed by cloud-based integration. Enterprise service bus, hub-and-spoke, and semantic web approaches are mentioned less frequently but are gaining interest. The study identifies and discusses 27 integration challenges into three main areas: organizational, technological, and data governance-related challenges. Technologies such as blockchain, data spaces, AI, edge computing and microservices, and service-oriented architecture methods are addressed as solutions for data governance and interoperability issues. The insights from the study can help enhance interoperability, leading to data-driven smart farming that increases food production, mitigates climate change, and optimizes resource usage.

Kusnadi Kusnadi, Muhammad Hatta, Goenawan Brotosaputro et al.

The integration of Information Technology (IT) has significantly transformed modern education, particularly classroom dynamics, by enhancing accessibility to information and enabling personalized learning experiences. This paper aims to explore both the positive impacts and challenges of IT adoption in the classroom, focusing on the importance of Computer Science in shaping effective teaching practices. The study analyzes tools like Learning Management Systems (LMS), simulation software, and data analysis platforms, which improve engagement between students and teachers but also highlight challenges such as the digital divide and less interactive learning. Understanding fundamental Computer Science concepts, including algorithms, programming, and networking, is key to developing innovative solutions that enhance classroom learning. The results show that while IT has revolutionized education by facilitating online learning and collaboration, it also presents challenges that must be addressed, such as access to resources and the need for more interactive learning experiences. To optimize IT’s impact, the paper recommends continuous teacher training, better integration of technology with curricula, and improved access to devices and internet connectivity, ensuring a more inclusive and innovative learning environment in the digital age.

Francisco M. Hidalgo-Sánchez, Ignacio Ruiz-Moreno, Jacinto Canivell et al.

Preventive conservation (PC) of built heritage has proved to be one of the most efficient and sustainable approaches to ensure its long-term preservation. Nevertheless, the management of all the areas involved in a PC project is complex, often resulting in poor interaction between them. This research proposes a GIS-based methodology for integrating data from different PC areas into a centralised digital model, establishing a Common Data Environment (CDE) to optimise PC strategies for heritage systems in complex contexts. Applying this method to the pavilions of the 1929 Ibero-American Exhibition in Seville (Spain), the study addresses five key PC areas: active follow-up, damage detection and assessment, risk analysis, maintenance, and dissemination and valorisation. The approach involved designing a robust relational database structure—using PostgreSQL—tailored for heritage management, defining several data standardisation criteria, and testing semi-automated procedures for generating multi-scale 2D and 3D GIS (LOD2 and LOD4) entities using remote sensing data sources. The proposed spatial database has been designed to function seamlessly with major GIS platforms (QGIS and ArcGIS Pro), demonstrating successful integration and interoperability for data management, analysis, and decision-making. Geographic web services derived from the database content were created and uploaded to a WebGIS platform. While limitations exist, this research demonstrates that simplified GIS models are sufficient for managing PC data across various working scales, offering a resource-efficient alternative compared to more demanding existing methods.

Sukhen Goswami, Md. Masum Billah, Md Sabbir Hossen et al.

Riverbank erosion, driven by natural processes and human activities, poses significant socio-environmental challenges in Bangladesh. This study investigated the geomorphic evolution and socioeconomic impacts of riverbank erosion along the Sandhya River in Babuganj Upazila, Barishal, Bangladesh. The primary aim was to assess how natural processes and human interventions, such as sand mining and infrastructure development, have altered the river morphology and affected local communities. Landsat imagery from 1980 to 2023, with a 10-year interval, was analyzed to assess key geomorphic indices—sinuosity, channel width, widening rate, and migration rate using remote sensing, geographic information systems (GIS), and field surveys. The results indicate significant geomorphic transformation, with sinuosity varying between 1.01 and 2.08, with a post-2000 increase in channel widening (up to 27 m/year) linked to intensified sand mining and brickfield expansion. Mid-channel bar formation, absent before 2000, reached 4.0 km2 by 2023, affecting flow patterns. The widening rate shifted from a maximum of 19 m/year (1980–2000, pre-sand mining) to 27 m/year (2000–2023, post-sand mining), with a peak near Doarika Bridge, which increased the vulnerability of the Barishal Airport area, averaging 3.65 m/year. Socioeconomic surveys (n = 154) reveal severe livelihood disruption: 65 % of lost land was agricultural, 73 % of affected households migrated to urban centers, and 45 % fell into debt. The most affected areas were Dehergati, Rahamatpur, Rakudia, and Kedarpur, emphasizing the need for capacity building. The study concludes that integrated geomorphic restoration and community resilience planning are urgently needed to address erosion-driven displacement and economic vulnerability in the region.

Emma Jenkins, Charlotte Ainscough, Marc George et al.

Introduction: The fragmented landscape of emergency medical guidelines across individual Trusts has resulted in inefficiencies in accessibility, maintenance and real-time applicability. Clinicians often struggle to locate relevant, up-to-date information quickly in critical situations, leading to potential delays in patient care and clinical decision-making. The absence of a centralised, user-friendly resource contributes to inefficiencies and risks to patient safety.1,2To address this, we developed the Medical Emergency Document Library (MEDL), a regional repository of standardised, one-page, evidence-based guidelines adaptable to local populations. This initiative aims to streamline emergency care, enhance decision-making and improve patient outcomes.1 Materials and methods: A preliminary assessment of existing Trust guidelines revealed a lack of standardisation, limited accessibility and outdated protocols. To resolve these issues, we created a library of one-page protocols covering various medical emergencies (Fig 1). The guidelines were designed for brevity, clarity and adherence to evidence-based practices. They were made available on mobile devices and hospital intranets, and linked to Electronic Health Record (EHR) systems to ensure seamless accessibility.Pilot testing was conducted within a single hospital, requiring the establishment of a local governance framework to expedite guideline approvals and of a steering committee to navigate operational challenges. Recognising the benefits of regional guideline standardisation, such as reducing health inequalities and minimising workload, while allowing for local adaptability, we expanded the MEDL to another Trust. By creating a collaborative regional MEDL committee, we shared resources and experience to scale the initiative. This approach enabled organisations to prioritise individual guidelines, allowed resident doctors to drive local quality improvement projects and fostered a sense of ownership among clinicians. Results and discussion: The implementation of MEDL has demonstrated significant clinical and operational benefits. Across two participating Trusts, over 80 MEDL guidelines were created, with more than 22,000 documented uses within 1 year, reflecting high demand for accessible emergency guidelines.Before MEDL implementation, emergency management varied widely, contributing to inconsistencies in patient care. By standardising protocols, MEDL has reduced variability in decision-making, enhanced efficiency and minimised delays in patient management. Senior clinicians and frontline staff have recognised the benefits, leading to the expansion of the initiative to include paediatric emergency guidelines (PEDLs) and regional guidelines, including hypertensive emergencies and maternal medicine.The integration of MEDL into an app-based platform has been particularly impactful. Over 80% of users accessed the guidelines via mobile devices, highlighting strong preference for digital accessibility. User feedback indicated high satisfaction, with clinicians strongly recommending MEDL to their peers as a critical tool for emergency management. Conclusion: The MEDL initiative has successfully addressed challenges in emergency guideline accessibility, standardisation and usability. By fostering regional collaboration and enabling a scalable model, MEDL has improved consistency in emergency medical care, leading to enhanced clinical efficiency and patient safety. Future expansion aims to integrate MEDL into additional Trusts and specialties, ensuring wider access to standardised, high-quality emergency care protocols. This initiative serves as a model for broader NHS-wide implementation, driving sustainable improvements in emergency medicine and patient outcomes.

Chao Ma, Haiyu Zhao, Kaiqi Zhang et al.

With the rapid development of supply chain finance, effectively managing risks while safeguarding participant data privacy has become a critical area of research. However, existing traditional risk control models predominantly rely on centralized data processing, which leads to the phenomenon of ”data silos,” hindering the flow and sharing of information. Furthermore, the significant privacy risks associated with centralized processing restrict collaboration among financial institutions, exacerbating the challenges of risk management. In this context, this study proposes a federated risk control method for supply chain finance based on personalized differential privacy optimization. This approach introduces a personalized differential privacy mechanism, enabling different institutions to collaboratively optimize model parameters without directly exchanging sensitive data. This methodology not only effectively safeguards data privacy but also enhances the overall performance of risk control, facilitating multi-party collaboration. Experimental results indicate that, compared to traditional centralized risk control models and other privacy protection methods, the proposed solution demonstrates favorable outcomes in terms of predictive accuracy and model performance while adhering to data privacy protection requirements. This research lays a theoretical foundation for the future development of safer and more efficient cross-institutional risk control systems and provides new insights and technical support for innovative risk management in the field of supply chain finance.

Jian Chen, Zhihan Lv, H. Song

Abstract With the continuous development of information technology, enterprises, universities and governments are constantly stepping up the construction of electronic personnel information management system. The information of hundreds of thousands or even millions of people’s information are collected and stored into the system. So much information provides the cornerstone for the development of big data, if such data is tampered with or leaked, it will cause irreparable serious damage. However, in recent years, electronic archives have exposed a series of problems such as information leakage, information tampering, and information loss, which has made the reform of personnel information management more and more urgent. The unique characteristics of the blockchain, such as non-tampering and traceability make it have great application potential in personnel information management, and can effectively solve many problems of traditional file management. However, the blockchain is limited by its own shortcomings such as small storage space and slow synchronization time, and cannot be directly applied to the big data field. This paper proposes a personnel management system based on blockchain, we analyzed the defects of the blockchain and proposed an improved method, constructs a novel data storage model of on-chain and out-of-chain that can effectively solve the problem of data redundancy and insufficient storage space. Based on this, we developed a prototype system with query, add, modify, and track personnel information, verified the feasibility of applying blockchain to personnel information management, explore the possibility of combining blockchain with big data.