Hasil untuk "Management information systems"

Wei Hua

Against the backdrop of global urbanization and climate change, traditional disaster prevention and mitigation models struggle to address the increasingly complex risks to urban infrastructure. This paper reviews the applications of Global Positioning System (GPS), Geographic Information System (GIS), and Remote Sensing (RS)in urban disaster management. It illustrates how these technologies complement each other through point-based positioning, spatial analysis, and wide-area monitoring across the entire disaster lifecycle. Research indicates that GPS provides precise spatiotemporal reference points, GIS enables multi-source information integration and analysis, and RS facilitates dynamic monitoring. The deep integration of these technologies constructs an intelligent closed-loop management system covering risk early warning, emergency response, and post-disaster recovery. This system significantly enhances the proactivity, accuracy, and systematic capacity of disaster management, thereby promoting a shift from reactive to proactive prevention and control. This study provides both a theoretical foundation and practical pathways for building resilient cities and intelligent disaster prevention and mitigation systems.

R. M. Magdaong, Ma. R. C. O. Ang, Ma. R. C. O. Ang et al.

Air pollution poses significant environmental and public health risks, particularly in urban areas of low and middle-income countries like the Philippines. Regulatory air quality monitoring stations, while accurate, are expensive and limited in spatial coverage, highlighting the need for low-cost IoT-based sensor networks to provide broader and real-time air quality data. This study establishes a methodology using Geographic Information Systems (GIS) and a heuristic algorithm to determine locations for deploying low-cost IoT-based air quality sensors in urban environments, focusing on near-road areas in Quezon City. Using multi-criteria analysis, Street Aspect Ratio (SAR), traffic emissions, Global Horizontal Irradiance (GHI), and road proximity were combined to produce a suitability map; scores ranged from 0 to 6. The algorithm then selected sensor locations by combining suitability and population rasters while enforcing a minimum spacing between nodes. In a 40‑sensor test, the resulting networks covered approximately 1.27 - 1.35 million residents (23.0%–24.4% of the city’s population) across weighting schemes while maintaining balanced spatial dispersion. These results indicate that the method achieves substantial population coverage in high‑exposure corridors and aligns with public‑health priorities. The framework is reproducible for other cities to enhance near‑road air quality monitoring and management.

Hanif Noer Rofiq

The Indonesian auction, one of the sources of Indonesia's income for Non-Tax State Revenue (PNBP), faces challenges in accurately classifying auction objects, limiting revenue optimisation. This research aims to compare the performance of several transfer learning architectures on the Indonesian Auction Object Dataset, which includes categories such as Buildings, Cars, Motorbikes, and Salvage Materials. Seven pre-trained transfer learning models—MobileNetV2, NASNetMobile, EfficientNetV2B0, DenseNet121, Xception, InceptionV3, and ResNet50V2—were evaluated against a baseline model, focusing on validation accuracy, model size, and computational efficiency. MobileNetV2, NASNetMobile, DenseNet121, Xception, InceptionV3, and ResNet50V2 all achieved 100% validation accuracy, outperforming the baseline model's 96.5% accuracy. MobileNetV2 stands out for its efficiency, reaching 100% accuracy in just eight epochs with a compact model size of 11.1 MB. In contrast, EfficientNetV2B0 performed poorly on this dataset, achieving only 25% validation accuracy. These findings confirm that transfer learning architectures can significantly improve auction object classification accuracy while reducing the model size and training time, highlighting the benefit of transfer learning for optimising Indonesian auction systems.

Levent Çalli, Büşra Alma Çalli

The mainstream launch of generative AI video platforms represents a major change to the socio-technical system of digital media, raising critical questions about public perception and societal impact. While research has explored isolated technical or ethical facets, a holistic understanding of the user experience of AI-generated videos—as an interrelated set of perceptions, emotions, and behaviors—remains underdeveloped. This study addresses this gap by conceptualizing public discourse as a complex system of interconnected themes. We apply a mixed-methods approach that combines quantitative LDA topic modeling with qualitative interpretation to analyze 11,418 YouTube comments reacting to AI-generated videos. The study’s primary contribution is the development of a novel, three-tiered framework that models user experience. This framework organizes 15 empirically derived topics into three interdependent layers: (1) Socio-Technical Systems and Platforms (the enabling infrastructure), (2) AI-Generated Content and Esthetics (the direct user-artifact interaction), and (3) Societal and Ethical Implications (the emergent macro-level consequences). Interpreting this systemic structure through the lens of the ABC model of attitudes, our analysis reveals the distinct Affective (e.g., the “uncanny valley”), Behavioral (e.g., memetic participation), and Cognitive (e.g., epistemic anxiety) dimensions that constitute the major elements of user experience. This empirically grounded model provides a holistic map of public discourse, offering actionable insights for managing the complex interplay between technological innovation and societal adaptation within this evolving digital system.

Elena Tenti, Giuseppe Basile, Claudia Giorgetti et al.

The evolution of decentralized clinical trials, driven by advanced digital technologies, is transforming traditional clinical research. It introduces innovative methods for informed consent, remote patient monitoring, and data analysis, enhancing study efficiency, validity, and participation while reducing patient burden. Some clinical procedures can be conducted remotely, increasing trial accessibility and reducing population selection biases, particularly for cardiovascular patients. However, this also presents complex regulatory and ethical challenges. The article explores how digital platforms and emerging technologies like block chain, AI, and advanced cryptography can promote traceability, security, and transparency throughout the trial process, ensuring participant identification and documentation of each procedural step. Clear, legally compliant informed consent, often managed through electronic systems, both for research participation and data management in line with GDPR, is essential. Ethical considerations include ensuring participants understand trial information, with adaptations such as simplified language, visual aids, and multilingual support. The transnational nature of decentralized trials highlights the need for coordinated regulatory standards to overcome jurisdictional barriers and reinforce accountability. This framework promotes trust, shared responsibility, and the protection of participants rights while upholding high ethical standards in scientific research.

Saihu Lu, Yuhan Liu, Guangqiang He et al.

Cough is a key symptom reflecting respiratory health, with its frequency and pattern providing valuable insights into disease progression and clinical management. Objective and reliable cough detection systems are therefore of broad significance for healthcare and remote monitoring. However, existing algorithms often struggle to jointly model spatial and temporal information, limiting their robustness in real-world applications. To address this issue, we propose a cough recognition framework based on frequency-modulated continuous-wave (FMCW) radar, integrating a deep convolutional neural network (CNN) with a Self-Attention mechanism. The CNN extracts spatial features from range-Doppler maps, while Self-Attention captures temporal dependencies, and effective data augmentation strategies enhance generalization by simulating position variations and masking local dependencies. To rigorously evaluate practicality, we collected a large-scale radar dataset covering diverse positions, orientations, and activities. Experimental results demonstrate that, under subject-independent five-fold cross-validation, the proposed model achieved a mean F1-score of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>0.974</mn><mo>±</mo><mn>0.016</mn></mrow></semantics></math></inline-formula> and an accuracy of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>99.05</mn><mo>±</mo><mn>0.55</mn></mrow></semantics></math></inline-formula> %, further supported by high precision of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>98.77</mn><mo>±</mo><mn>1.05</mn></mrow></semantics></math></inline-formula> %, recall of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>96.07</mn><mo>±</mo><mn>2.16</mn></mrow></semantics></math></inline-formula> %, and specificity of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>99.73</mn><mo>±</mo><mn>0.23</mn></mrow></semantics></math></inline-formula> %. These results confirm that our method is not only robust in realistic scenarios but also provides a practical pathway toward continuous, non-invasive, and privacy-preserving respiratory health monitoring in both clinical and telehealth applications.

Guillaume Lim Fat, Kristina M Kokorelias, Erica Foronda et al.

Background: In healthcare systems prioritizing care of older adults, resource limitations and escalating demand often impede access to outpatient specialized geriatric services. Objectives: This study, theoretically guided by the Consolidated Framework for Implementation Research (CFIR), aimed to explore barriers and facilitators in implementing a centralized “Geri-Hub.” The Geri-Hub is a centralized intake system established within 2 hospital systems to coordinate outpatient and community-based services for older adults, aiming to connect them with the most appropriate care in a timely manner. Methods: Qualitative insights were gathered from healthcare professionals at 2 academic institutions in the process of consolidating services. Through open-ended surveys and semi-structured interviews, we solicited feedback on referral management, waiting times, and overall work experiences. Results: Thirteen frequently referring providers and a cohort of 9 geriatricians, along with 4 administrators, contributed to the study. Geriatricians emphasized streamlined referrals, flexible scheduling for urgent cases, and a target wait time of 3 months. Administrators stressed standardized referral procedures, defined roles, and accessible referral information. Discussion: The findings underscored the need for straightforward referral processes, enhanced communication on referral statuses, and reduced wait times. Optimizing these processes could potentially mitigate resource utilization issues and improve patient outcomes in healthcare systems. This research highlights the critical role of timely access to geriatric services during transformative phases in healthcare delivery.

Putri Nabillah, Inggih Permana, M. Afdal et al.

This study evaluates the performance of various algorithms in determining eligible recipients for the Kartu Indonesia Sehat program. The Random Forest algorithm demonstrated the highest accuracy, precision, and recall, with values of 72.08%, 72.41%, and 99.64%, respectively. The emphasis on recall helps minimize errors in identifying eligible recipients. Additionally, the C4.5 algorithm reduced the total number of variables from 33 to 8, highlighting its computational efficiency. The findings provide valuable insights for the Social Affairs Office of Dumai City in making informed decisions regarding KIS eligibility. The results underscore the effectiveness of using algorithmic approaches to enhance the accuracy and efficiency of aid distribution processes.

Veronika Nowak, Johanna Ullrich, Edgar Weippl

Cybersecurity is still considered a purely technological challenge; however, despite all technological progress, this challenge remains unsolved as emphasized by many high-impact attacks against public administration and industry worldwide. We postulate that the mere focus on technology fogs the bigger picture, since people generate, operate, and interact with all technological systems, thus making them socio-technical systems. Hence, in this commentary we argue for a change of perspective towards a holistic, interdisciplinary view on our technological infrastructure. By example of the European power grid inarguably a critical infrastructure not only for daily life but also for the continuity of our polity we show that through interpretation as a socio-technical system, systematic and interdisciplinary studies would allow to reveal how its (cyber)security is not only a technological matter. An interdisciplinary approach combining STEM disciplines and Social Sciences would additionally advance the understanding of stakeholders and their goals and mindsets as well as the manifold dependencies between technology and human actors. While interdisciplinary endeavours appear to be generally supported by funding agencies, reviewers, universities, and researchers, they rarely occur in practice. We discuss why this is the case and present ideas on how to facilitate more interdisciplinary research.

Ahmed Azab, Jaehyun Park, Noha A. Mostafa

Smart service systems have been dealing with various wicked social and cultural problems by providing diverse solutions for society. Cargo transportation is one of the most challenging issues in logistics; in this paper, we explore multiple stakeholders’ information environments surrounding containerized cargo transportation by a design thinking approach. Throughout the analysis, the latent problems are summarized in the following two manners: (1) miscommunication with inefficient information flow among multiple stakeholders; and (2) a lack of resource management coordination among service providers. With these two identified problems, the objective of this work is to develop a prototype information and communication technology-based service application for both trucking companies and customers. This work makes two contributions. First, it methodologically proposes a customer-centered design approach for logistics management by adopting a design thinking approach. Second, it suggests a practical ICT-based solution for the mentioned problems.

S. Hemavathi and R. Manjula

Information of interactions between waves and aquatic vegetation is becoming increasingly important, in particular, due to the trend of plant-induced wave attenuation towards sustainable coastal management systems. This study aims to understand monotypic vegetation-wave interactions through three-level, four factors, response surface methodology (RSM) using laboratory wave flume under controlled conditions. Cymodocea Serrulata is one of the prevalent monotypic seagrass species found in the Gulf of Mannar, Tamilnadu, South India. It was physically simulated using synthetic plant imitations to create a relationship between wave attenuation (E%) and four direct control factors, i.e., water depth (h), wave period (T), plant density (N) and bed roughness factor (f) using an empiric model. The model developed was tested using the analysis of variance technique (ANOVA) and evaluated for the main and interaction effects of the studied parameters. The findings showed that both individually and in combination, all of the parameters considered were significantly effective on E%. All model-based findings were compared with a new collection of experimental data and validation tests were performed. The comparison of experimental results with model predictions was at a good agreement with a high coefficient of determination (R2) of 0.98 (with p-value < 0.05).

Xu Lingxiang, Chen Jiawei, Ding Guohui et al.

Plant phenomics is under rapid development in recent years, a research field that is progressing towards integration, scalability, multi-perspectivity and high-throughput analysis. Through combining remote sensing, Internet of Things (IoT), robotics, computer vision, and artificial intelligence techniques such as machine learning and deep learning, relevant research methodologies, biological applications and theoretical foundation of this research domain have been advancing speedily in recent years. This article first introduces the current trends of plant phenomics and its related progress in China and worldwide. Then, it focuses on discussing the characteristics of indoor phenotyping and phenotypic traits that are suitable for indoor experiments, including yield, quality, and stress related traits such as drought, cold and heat resistance, salt stress, heavy metals, and pests. By connecting key phenotypic traits with important biological questions in yield production, crop quality and Stress-related tolerance, we associated indoor phenotyping hardware with relevant biological applications and their plant model systems, for which a range of indoor phenotyping devices and platforms are listed and categorized according to their throughput, sensor integration, platform size, and applications. Additionally, this article introduces existing data management solutions and analysis software packages that are representative for phenotypic analysis. For example, ISA-Tab and MIAPPE ontology standards for capturing metadata in plant phenotyping experiments, PHIS and CropSight for managing complicated datasets, and Python or MATLAB programming languages for automated image analysis based on libraries such as OpenCV, Scikit-Image, MATLAB Image Processing Toolbox. Finally, due to the importance of extracting meaningful information from big phenotyping datasets, this article pays extra attention to the future development of plant phenomics in China, with suggestions and recommendations for the integration of multi-scale phenotyping data to increase confidence in research outcomes, the cultivation of cross-disciplinary researchers to lead the next-generation plant research, as well as the collaboration between academia and industry to enable world-leading research activities in the near future.

Rory Joseph Quinn, Geraldine Gray, Dr

Increasingly educational providers are being challenged to use their data stores to improve teaching and learning outcomes for their students. A common source of such data is learning management systems which enable providers to manage a virtual platform or space where learning materials and activities can be provided for students to engage with. This study investigated whether data from the learning management system Moodle can be used to predict academic performance of students in a blended learning further education setting. This was achieved by constructing measures of student activity from Moodle logs of further education courses. These were used to predict alphabetic student grade and whether a student would pass or fail the course. A key focus was classifiers that could predict likelihood of failure from data available early in the term. The results showed that classifiers built on all course data predicted student grade moderately well (accuracy= 60.5%, kappa = 0.43) and whether a student would pass or fail very well (accuracy= 92.2%, kappa=0.79). However, classifiers built on the first six weeks of data did not predict failing students well. Classifiers trained on the first ten weeks of data improved significantly on a no-information rate (p<0.008) though more than half of failing students were still misclassified. The evidence indicates that measures of Moodle activity on further education courses could be useful as part of on an early-warning system at ten weeks.

Halyna Nahorniak

The article is devoted to the study of the content of staffing as a component of the intellectual capital of the enterprises of the domestic engineering industry, and the toolkit for its improvement is proposed. The development of a modern enterprise is ensured by the social interaction of its employees and the interaction of the enterprise with the environment is established. The exchange of subjective values of the workers allows to realize the labor potential of the enterprise to a large extent. In itself, the process of forming the intellectual capital of an enterprise represents organizational and managerial innovations, which are determined by the needs of innovation development in the production and technological sphere. The exchange of knowledge and skills of individuals in the process of interaction is one of the most important factors in the development of the national innovation system. A prerequisite for the modernization of the Ukrainian economy is to increase the effectiveness of innovation activities, which is largely determined by the ability of economic actors to use and generate new knowledge derived from the intellectual results obtained by productive relations with the external environment, which is interpreted as staffing, which is necessary component of intellectual capital. The assessment of this component of intellectual capital is an essential tool for efficient management of its quality in the interests of innovative development of machine-building enterprises and provides feedback in human-oriented management of innovation activities. In this regard, the development of tools for improving staffing as a component of intellectual capital is an urgent task that is of considerable scientific and practical importance. The content of the concept of "human resources provision as a component of intellectual capital" is specified, the author's interpretation of the concept of "staffing as an integral part of the intellectual capital of machine-building enterprises" is given. The issue of management of human resources provision as a component of intellectual capital of domestic enterprises of mechanical engineering is disclosed. There are a number of problems that directly influence the growth of intellectual capital in Ukraine's machine-building industry. The toolkit for the development of the machine-building industry is presented at the expense of improvement of human resources provision as a component of intellectual capital. A model of intellectual capital is defined which can be interpreted using three main components: human capital (contains such component as staffing); organizational capital (corporate information systems, databases, hardware and software, organizational structures, patents, know-how, licenses, trademarks, corporate culture); consumer capital (the capital of relations, representing the causal mechanism of interaction of the company with consumers, suppliers, competitors, as well as the socio-economic potential of its brands, brands, image and reputation). It is noted that in a generalized way, the structure of personnel supply represents four interacting components: moral values (moral and cultural levels); creative abilities (including creativity); education (knowledge gained during the learning process); professionalism (work experience taking into account the performed work tasks).

Soojin Park, Sungyong Park, Young B. Park

With the emergence of various forms of smart devices and new paradigms such as the Internet of Things (IoT) concept, the IT (Information Technology) service areas are expanding explosively compared to the provision of services by single systems. A new system operation concept that has emerged in accordance with such technical trends is the IT ecosystem. The IT ecosystem can be considered a special type of system of systems in which multiple systems with various degrees of autonomy achieve common goals while adapting to the given environment. The single systems that participate in the IT ecosystem adapt autonomously to the current situation based on collected data from sensors. Furthermore, to maintain the services supported by the whole IT ecosystem sustainably, the configuration of single systems that participate in the IT ecosystem also changes appropriately in accordance with the changed situation. In order to support the IT ecosystem, this paper proposes an architecture framework that supports dynamic configuration changes to achieve the goal of the whole IT ecosystem, while ensuring the autonomy of single systems through the collection of data from sensors so as to recognize the situational context of individual participating systems. For the feasibility evaluation of the proposed framework, a simulated example of an IT ecosystem for unmanned forest management was constructed, and the quantitative evaluation results are discussed in terms of the extent to which the proposed architecture framework can continuously provide sustainable services in response to diverse environmental context changes.

Carolina Ramalho Brito, João Paulo Miranda de Castro, Kelly Oliveira Barros et al.

O presente artigo pautou-se na realização de um inventário arbóreo com a incorporação dos Sistemas de Informações Geográficas. A área de estudo corresponde ao campus Santa Apolónia, Instituto Politécnico de Bragança (IPB), em Bragança, Portugal. Além do inventário foram realizadas recomendações e também a espacialização dos indivíduos levantados e, em caráter individual, das espécies de maior ocorrência. A utilização dos Sistemas de Informações Geográficas foi uma ferramenta fundamental de suporte para o inventário urbano realizado. Com as características levantadas e a espacialização realizada pôde-se perceber a necessidade de elaboração de um plano de arborização para a área do campus em estudo. Desta forma, medidas relacionadas ao manejo das espécies podem ser aplicadas de maneira eficiente.<br>This article aimed to realize a forest inventory with the incorporation of Geographic Information Systems. The study was carried out at the Santa Apolonia campus, Polytechnic Institute of Bragança, Bragança (IPB), Portugal. In addition of the inventory, it was realized recommendations and the spatial distribution of the individuals surveyed, and individually, the most common species. The use of Geographic Information Systems was a key tool to support the urban inventory accomplished. From the characteristics and spatial distribution can be realized the need to prepare an arborization plan for the area in the campus in study. Thus, measures related to the management of the species can be efficiently applied.

A. Rector, W. Solomon, W. Nowlan et al.

D. Robey

Qing Hu, C. Saunders, M. Gebelt

Judith Mavodza, Patrick Ngulube

<strong>Background:</strong> This article underscores the fact that society is becoming more and more knowledge-based, and that the organisations that can identify, value, create and evolve their knowledge assets are likely to be more successful than those that do not. Knowledge management (KM) is about enhancing the use of organisational knowledge through sound practices of KM and organisational learning. KM practices encompass the capture and/or acquisition of knowledge, its retention and organisation, its dissemination and re-use, and lastly responsiveness to the new knowledge.<p><strong>Objective:</strong> The focus of this study was on KM principles and practices that may be in place in the Metropolitan College of New York (MCNY). The argument is that KM and its survival principles and tools may help the College to improve performance. However, there is uncertainty about whether the use of KM principles and tools can partly solve the College’s approach to improving the quality of education it provides.</p><p><strong>Methods:</strong> A mixed methods research methodology encompassing a questionnaire, observation, interviews, and use of institutional documents was used in the investigation.</p><p><strong>Results:</strong> The findings of the study indicate that KM concepts were not universally understood at MCNY.</p><p><strong>Conclusion:</strong> There is a need to create a knowledge inventory at MCNY. This may help the College to develop appropriate institution-wide policies and practices for proper and well organised methods of integrating work processes, collaborating and sharing (including the efficient use of social media), and developing an enabling institutional culture.</p>