Hasil untuk "Management information systems"

L. Zadeh

A. Zhidebayeva, S. Syrlybekkyzy, L. Taizhanova et al.

The accelerating biodiversity crisis, driven by climate change and intensifying anthropogenic pressures, demands accurate, scalable, and dynamic tools to monitor ecosystem health and biological diversity. Remote sensing and geographic information systems have long been pivotal in observing environmental conditions and measuring biodiversity, nonetheless the fast-paced development of sensing technologies, analytical approaches, and computational power is greatly transforming their purpose in conservation science. This study provides a comprehensive synthesis of next-generation applications of remote sensing and geographic information systems in biodiversity and ecosystem monitoring. The study aimed to gather recent developments in the use of remote sensing and geographic information systems for biodiversity and ecosystem monitoring, thoroughly evaluate existing methods, recognize enduring challenges, and recommend innovative, technology-driven pathways for improving ecological assessments and conservation planning. A notable transition is taking place from standard land cover mapping towards assessing ecological functions, evaluating habitat quality, and detecting environmental changes in near real-time. Innovative technologies, including hyperspectral imaging, drone-based sensing, radar interferometry, three-dimensional laser scanning, and small satellite constellations, are combined with sophisticated computational methods, featuring machine learning, deep learning, spatiotemporal data fusion, and cloud-based geo-processing. These developments are transforming applications ranging from automated species distribution modelling and ecosystem service mapping to structural-functional landscape phenotyping, habitat connectivity assessment, and predictive early-warning systems for biodiversity loss. The merging of datasets with differing resolutions, timeframes, and sensors is promoting the establishment of broad ecological intelligence, which contributes to adaptive conservation strategies and evidence-based environmental governance. Despite these advances, several challenges remain, including algorithmic bias, the harmonization of heterogeneous datasets, limited direct biodiversity proxies, and disparities in access to emerging technologies. Ethical considerations along with the integration of community-driven monitoring frameworks, are essential for ensuring that technological advancements are in harmony with global sustainability goals. Anticipating the future, the integration of sophisticated sensing technologies, artificial intelligence, and cloud computing platforms presents remarkable opportunities to transform biodiversity monitoring and conservation planning. By enabling predictive, adaptive, and near real-time decision-making, these innovations are reshaping strategies for environmental management and the development of resilient socio-ecological systems in the context of rapid global change.

Thompson CC, Saracco B, Pruthi A et al.

Carol C Thompson,1 Benjamin Saracco,2,3 Anika Pruthi,3 Elizabeth Cerceo4 1Department of Educational Leadership, Administration, and Research, Rowan University, Glassboro, NJ, USA; 2Rowan University Libraries, Rowan University, Glassboro, NJ, USA; 3Cooper Medical School of Rowan University, Rowan University, Camden, NJ, USA; 4Department of Medicine, Cooper Medical School of Rowan University, Camden, NJ, USACorrespondence: Carol C Thompson, Department of Educational Leadership, Administration, and Research, Rowan University, Glassboro, NJ, 08086, USA, Email thompsonc@rowan.eduAbstract: Alpha-gal syndrome (AGS), a tick-borne allergy, is increasing as its vectors migrate throughout the US and the world. There were an estimated 450,000 cases in the US. AGS reactions to mammalian foods and medical products include delayed anaphylaxis, urticaria, gastrointestinal and cardiac symptoms often difficult to connect to the source. Despite its seriousness, provider knowledge is limited. This rapid review investigated published works on AGS from 2020 to 24; it also sought to determine the breadth of AGs publications across different fields and specialties. We identified 355 studies of AGS diagnosis and management from 2020 to 2024 via Cochrane Central, Medline via the PubMed interface, and Embase (additional grey literature via Web of Science and Google Scholar). Studies were assessed for quality and risk of bias using JBI critical appraisal tools. Two hundred and nineteen studies met the criteria. One hundred and sixty-eight (77%) were full studies; 51 (23%) were conference presentations. Studies remained largely confined to allergy and immunology literature, despite their implications for other organ systems. Although patients present with symptoms to emergency departments and dermatology clinics there is a paucity of literature in those fields and others; several studies document practitioners’ lack of knowledge. Inclusion of content within medical school curricula is needed to establish foundational knowledge on the topic. With the increase in patients presenting with AGS, and with the reach of AGS across multiple fields, physicians and other health care providers need to be able to diagnose and then manage AGS with their patients. This rapid review has documented the problem of silos in disseminating information about AGS widely through the medical field. The remedy for a lack of practitioner knowledge is education.Keywords: tick-borne, allergy, mammalian products, provider knowledge, immunology, red meat

Daniela Pöhn, Heiner Lüken

Security situational awareness refers to identifying, mitigating, and preventing digital cyber threats by gathering information to understand the current situation. With awareness, the basis for decisions is present, particularly in complex situations. However, while logging can track the successful login into a system, it typically cannot determine if the login was performed by the user assigned to the account. An account takeover, for example, by a successful phishing attack, can be used as an entry into an organization's network. All identities within an organization are managed in an identity management system. Thereby, these systems are an interesting goal for malicious actors. Even within identity management systems, it is difficult to differentiate legitimate from malicious actions. We propose a security situational awareness approach specifically to identity management. We focus on protocol-specifics and identity-related sources in a general concept before providing the example of the protocol OAuth with a proof-of-concept implementation.

Rosita Moradi, Mohammad Yazdi, Aida Haghighi et al.

The circular economy (CE) is reasoned to organize complex systems supporting sustainable resilience by distinguishing between waste materials and economic growth. This is crucial to the electronic waste (e-waste) industry of developed countries, and e-waste operation management has become their top priority because e-waste contains toxic materials and valuable sources of elements. In the UK, although London Metropolitan city boasts an ambitious sustainable resilience target underlying the context of CE, practical implementation has yet to be feasible, with few investigations detailing if and how the existing target implications enable industrial and social-ecological sectors to continue their performance functionalities in the face of undesired disruptions. In this paper, a dynamic Bayesian Network (dynamic BN) approach is developed to address a range of potential risks. The existing London e-waste operation management is considered as an application of study for sustainable resilience development. Through the utilization of dynamic BN, a comprehensive analysis yields a Resilience Index (RI) of 0.5424, coupled with a StdDev of 0.01350. These metrics offer a profound insight into the intricate workings of a sustainable system and its capacity to swiftly rebound from unexpected shocks and disturbances. This newfound understanding equips policymakers with the knowledge needed to navigate the complexities of sustainable e-waste management effectively. The implications drawn from these in-depth analyses furnish policymakers with invaluable information, enabling them to make judicious decisions that advance the cause of sustainable e-waste management. The findings underscore that the absorptive capacity of a sustainable and resilient e-waste operation management system stands as the foremost defense mechanism against unforeseen challenges. Furthermore, it becomes evident that two pivotal factors, namely “diversifying the supply chain” and “enhancing supply chain transparency,” play pivotal roles in augmenting the sustainability and resilience of e-waste operation management within the context of London's ambitious sustainability targets. These factors are instrumental in steering the trajectory of e-waste management towards a more sustainable and resilient future, aligning with London's aspirations for a greener and more eco-conscious future.

Alessandra Cucurnia

The paper documents some of the results of the research program Smart Yard: Industry 4.0 Production Process aimed at reducing inefficiencies in construction site procedures by developing new management methods supported by digitisation processes that can memorise and monitor computational data and guide them towards specific purposes of production processes optimisation. In particular, the aim of the study is to propose evolved, highly efficient and innovative organisational and information management models that enable more reliable control of processes in the construction sector, mitigating unavoidable uncertainties while pursuing a more rational use of resources. The products developed to support the programme include two newly designed pieces of equipment with advanced functions, which can be configured as examples of site management systems such as a “smart factory” in the logic of Industry 4.0, illustrated below. One is a high-performance charging system for power banks to be used with portable power tools, while the other concerns a work standing desk that employs wireless communication protocols to dialogue with other devices at the construction site.

L. M. Wedding, S. J. Pittman, C. A. Lepczyk et al.

Abstract Marine spatial planning (MSP) has emerged as a tool to enable marine ecosystem-based management that seeks to balance human demands for ocean space with environmental protection. However, there is a history of thinking about our ocean systems as spaces, not places. As a result, most MSPs have been implemented without consideration of place. The relationship between people and the rest of nature is at the core of the UN SDGs (Sustainable Development Goals). Due to significant knowledge gaps in sociocultural connections, people and their place-based perspectives and needs are often overlooked in the MSP process. New approaches are required to equip societies with information to inform sustainable ocean planning relevant to environmental change and the local sociocultural context. We encourage the inclusion of a distinct place-based characteristic in MSP and argue that bringing in the concepts of space and place from the discipline of geography can enable a broader view of the seascape in MSP. Here, we provide five core considerations of place-based MSP that include: (1) sense of place; (2) social-ecological systems; (3) ocean and human health; (4) multiple ways of knowing; and (5) social knowledge. We review available methods and suggest a multi-evidence-based approach that can highlight dynamic eco-cultural connections between people and the biophysical patterns and processes of interlinked landscapes and seascapes. Moving towards place-based MSP can help to solve three important issues in the current context of global socio-environmental transformations. First, these key concepts are relevant for interdisciplinary science, as solving problems raised by MSP requires more than superimposing spatial layers of scientific knowledge. Second, marine planning and management is less efficient if policies are not integrated and if issues are addressed by each individual sector rather than in a holistic manner. Third, a place-based approach accounts for individual and collective values and may open new ways to solve governance issues. A shift from understanding and managing ocean spaces to including ocean places can support progress towards sustainable and equitable MSP goals.

Drazen Orescanin, Tomislav Hlupic, Boris Vrdoljak

Privacy is a fundamental human right according to the Universal Declaration of Human Rights of the United Nations. Adoption of the General Data Protection Regulation (GDPR) in European Union in 2018 was turning point in management of personal data, specifically personal identifiable information (PII). Although there were many previous privacy laws in existence before, GDPR has brought privacy topic in the regulatory spotlight. Two most important novelties are seven basic principles related to processing of personal data and huge fines defined for violation of the regulation. Many other countries have followed the EU with the adoption of similar legislation. Personal data management processes in companies, especially in analytical systems and Data Lakes, must comply with the regulatory requirements. In Data Lakes, there are no standard architectures or solutions for the need to discover personal identifiable information, match data about the same person from different sources, or remove expired personal data. It is necessary to upgrade the existing Data Lake architectures and metadata models to support these functionalities. The goal is to study the current Data Lake architecture and metadata models and to propose enhancements to improve the collection, discovery, storage, processing, and removal of personal identifiable information. In this paper, a new metadata model that supports the handling of personal identifiable information in a Data Lake is proposed.

Keenan J. A. Down, Pedro A. M. Mediano

The Shannon entropy of a random variable $X$ has much behaviour analogous to a signed measure. Previous work has concretized this connection by defining a signed measure $μ$ on an abstract information space $\tilde{X}$, which is taken to represent the information that $X$ contains. This construction is sufficient to derive many measure-theoretical counterparts to information quantities such as the mutual information $I(X; Y) = μ(\tilde{X} \cap \tilde{Y})$, the joint entropy $H(X,Y) = μ(\tilde{X} \cup \tilde{Y})$, and the conditional entropy $H(X|Y) = μ(\tilde{X}\, \setminus \, \tilde{Y})$. We demonstrate that there exists a much finer decomposition with intuitive properties which we call the logarithmic decomposition (LD). We show that this signed measure space has the useful property that its logarithmic atoms are easily characterised with negative or positive entropy, while also being coherent with Yeung's $I$-measure. We present the usability of our approach by re-examining the Gács-Körner common information from this new geometric perspective and characterising it in terms of our logarithmic atoms. We then highlight that our geometric refinement can account for an entire class of information quantities, which we call logarithmically decomposable quantities.

Jieao Zhu, Zhongzhichao Wan, Linglong Dai et al.

Traditional massive multiple-input multiple-output (MIMO) information theory adopt non-physically consistent assumptions, including white-noised, scalar-quantity, far-field, discretized, and monochromatic EM fields, which mismatch the nature of the underlying electromagnetic (EM) fields supporting the physical layer of wireless communication systems. To incorporate EM laws into designing procedures of the physical layer, we first propose the novel concept of EM physical layer, whose backbone theory is called EM information theory (EIT). In this article, we systematically investigate the basic ideas and main results of EIT. First, we review the fundamental analytical tools of classical information theory and EM theory. Then, we introduce the modeling and analysis methodologies of EIT, including continuous field modeling, degrees of freedom, and mutual information analyses. Several EIT-inspired applications are discussed to illustrate how EIT guides the design of practical wireless systems. Finally, we point out the open problems of EIT, where further research efforts are required for EIT to construct a unified interdisciplinary theory.

Walaiporn Patcharanarumol, Viroj Tangcharoensathien, Aniqa Islam Marshall et al.

Participatory and responsive governance in universal health coverage (UHC) systems synergistically ensure the needs of citizens are protected and met. In Thailand, UHC constitutes of three public insurance schemes: Civil Servant Medical Benefit Scheme, Social Health Insurance and Universal Coverage Scheme. Each scheme is governed through individual laws. This study aimed to identify, analyse and compare the legislative provisions related to participatory and responsive governance within the three public health insurance schemes and draw lessons that can be useful for other low-income and middle-income countries in their legislative process for UHC. The legislative provisions in each policy document were analysed using a conceptual framework derived from key literature. The results found that overall the UHC legislative provisions promote citizen representation and involvement in UHC governance, implementation and management, support citizens’ ability to voice concerns and improve UHC, protect citizens’ access to information as well as ensure access to and provision of quality care. Participatory governance is legislated in 33 sections, of which 23 are in the Universal Coverage Scheme, 4 in the Social Health Insurance and none in the Civil Servant Medical Benefit Scheme. Responsive governance is legislated in 24 sections, of which 18 are in the Universal Coverage Scheme, 2 in the Social Health Insurance and 4 in the Civil Servant Medical Benefit Scheme. Therefore, while several legislative provisions on both participatory and responsive governance exist in the Thai UHC, not all schemes equally bolster citizen participation and government responsiveness. In addition, as legislations are merely enabling factors, adequate implementation capacity and commitment to the legislative provisions are equally important.

Benzar Glen Grepon

Computer-based information systems for case management are still at an early stage of adoption in many trial courts in the Philippines. In most cases, information system implemented is the case docket using the official record book on which cases are written and inventory of cases and reports are generated. This is a standalone system that often face data processing, data security and case management challenges. However, there are examples of Information systems in overcoming these pitfalls and producing innovative solutions that surpass data management practices in in many trial courts in the country. One such case is the Regional Trial Court Branch 23 of Cagayan de Oro City in Northern Mindanao, Philippines. A project named Web-based Case Docket Information System (WCDIS) has been designed and developed for the court branch. This system uses a framework known as System Development Life Cycle (SDLC) which is a guide for the design and development. This paper also discusses the key system functionalities and the implementation methodology, including both the benefits and shortcomings of this approach, with the goal of applying lessons learned for future installations. Foremost among the successes of this project is its ability to increase efficiency and reliability in completing court transactions.

Yubo Luo, Shahriar Nirjon

We propose SmartON, a batteryless system that learns to wake up proactively at the right moment in order to detect events of interest. It does so by adapting the duty cycle to match the distribution of event arrival times under the constraints of harvested energy. While existing energy harvesting systems either wake up periodically at a fixed rate to sense and process the data, or wake up only in accordance with the availability of the energy source, SmartON employs a three-phase learning framework to learn the energy harvesting pattern as well as the pattern of events at run-time, and uses that knowledge to wake itself up when events are most likely to occur. The three-phase learning framework enables rapid adaptation to environmental changes in both short and long terms. Being able to remain asleep more often than a CTID (charging-then-immediate-discharging) wake-up system and adapt to the event pattern, SmartON is able to reduce energy waste, increase energy efficiency, and capture more events. To realize SmartON we have developed a dedicated hardware platform whose power management module activates capacitors on-the-fly to dynamically increase its storage capacitance. We conduct both simulation-driven and real-system experiments to demonstrate that SmartON captures 1X--7X more events and is 8X--17X more energy-efficient than a CTID system.

Minghan Li, Diana Nicoleta Popa, Johan Chagnon et al.

On a wide range of natural language processing and information retrieval tasks, transformer-based models, particularly pre-trained language models like BERT, have demonstrated tremendous effectiveness. Due to the quadratic complexity of the self-attention mechanism, however, such models have difficulties processing long documents. Recent works dealing with this issue include truncating long documents, in which case one loses potential relevant information, segmenting them into several passages, which may lead to miss some information and high computational complexity when the number of passages is large, or modifying the self-attention mechanism to make it sparser as in sparse-attention models, at the risk again of missing some information. We follow here a slightly different approach in which one first selects key blocks of a long document by local query-block pre-ranking, and then few blocks are aggregated to form a short document that can be processed by a model such as BERT. Experiments conducted on standard Information Retrieval datasets demonstrate the effectiveness of the proposed approach.

Joseph Breeden, Kunal Garg, Dimitra Panagou

This paper presents conditions for ensuring forward invariance of safe sets under sampled-data system dynamics with piecewise-constant controllers and fixed time-steps. First, we introduce two different metrics to compare the conservativeness of sufficient conditions on forward invariance under piecewise-constant controllers. Then, we propose three approaches for guaranteeing forward invariance, two motivated by continuous-time barrier functions, and one motivated by discrete-time barrier functions. All proposed conditions are control affine, and thus can be incorporated into quadratic programs for control synthesis. We show that the proposed conditions are less conservative than those in earlier studies, and show via simulation how this enables the use of barrier functions that are impossible to implement with the desired time-step using existing methods.

S. Narasimha Swamy, Solomon Raju Kota

Internet of Things (IoT) is an integration of the Sensor, Embedded, Computing, and Communication technologies. The purpose of the IoT is to provide seamless services to anything, anytime at any place. IoT technologies play a crucial role everywhere, which brings the fourth revolution of disruptive technologies after the internet and Information and Communication Technology (ICT). The Research & Development community has predicted that the impact of IoT will be more than the internet and ICT on society, which improves the well-being of society and industries. Addressing the predominant system-level design aspects like energy efficiency, robustness, scalability, interoperability, and security issues result in the use of a potential IoT system. This paper presents the current state of art of the functional pillars of IoT and its emerging applications to motivate academicians and researches to develop real-time, energy-efficient, scalable, reliable, and secure IoT applications. This paper summarizes the architecture of IoT, with the contemporary status of IoT architectures. Highlights of the IoT system-level issues to develop more advanced real-time IoT applications have been discussed. Millions of devices exchange information using different communication standards, and interoperability between them is a significant issue. This paper provides the current status of the communication standards and application layer protocols used in IoT with the detailed analysis. The computing paradigms like Cloud, Cloudlet, Fog, and Edge computing facilitate IoT with various services like data offloading, resource and device management, etc. In this paper, an exhaustive analysis of Edge Computing in IoT with different edge computing architectures and existing status are deliberated. The widespread adoption of IoT in society has resulted in privacy and security issues. This paper emphasizes on analyzing the security challenges, privacy and security threats, conventional mitigation techniques, and further scope for IoT security. The features like fewer memory footprints, scheduling, real-time task execution, fewer interrupt, and thread switching latency of Real-Time Operating Systems (RTOS) enables the development of time critical IoT applications. Also, this review offers the analysis of the RTOS's suitable for IoT with the current status and networking stack. Finally, open research issues in IoT system development are discussed.

Adrien Le Franc, Pierre Carpentier, Jean-Philippe Chancelier et al.

Inserting renewable energy in the electric grid in a decentralized manneris a key challenge of the energy transition. However, at local scale, both production and demand display erratic behavior, which makes it delicate to match them. It is the goal of Energy Management Systems (EMS) to achieve such balance at least cost. We present EMSx, a numerical benchmark for testing control algorithms for the management of electric microgrids equipped with a photovoltaic unit and an energy storage system. EMSx is made of three key components: the EMSx dataset, provided by Schneider Electric, contains a diverse pool of realistic microgrids with a rich collection of historical observations and forecasts; the EMSx mathematical framework is an explicit description of the assessment of electric microgrid control techniques and algorithms; the EMSx software EMSx.jl is a package, implemented in the Julia language, which enables to easily implement a microgrid controller and to test it. All components of the benchmark are publicly available, so that other researchers willing to test controllers on EMSx may reproduce experiments easily. Eventually, we showcase the results of standard microgrid control methods, including Model Predictive Control, Open Loop Feedback Control and Stochastic Dynamic Programming.

Nindian Puspa Dewi, Indah Listiowarni

Games are media that can be used in the learning process to stimulate students in teaching and learning activities in the classroom. The game used is a game that has been adapted to the needs of learning in the classroom called game based learning or educational games. English subjects are difficult to learn by elementary students at SDN Bujur Barat II, so the use of learning media is needed to attract students' interest in learning the subject. In this study, an educational game was made based on the SD English curriculum consisting of writing, reading, listening, and speaking, which was built using the Ionic programming language and the PHP Framework.

Linara Adilova, Julia Rosenzweig, Michael Kamp

An approach to distributed machine learning is to train models on local datasets and aggregate these models into a single, stronger model. A popular instance of this form of parallelization is federated learning, where the nodes periodically send their local models to a coordinator that aggregates them and redistributes the aggregation back to continue training with it. The most frequently used form of aggregation is averaging the model parameters, e.g., the weights of a neural network. However, due to the non-convexity of the loss surface of neural networks, averaging can lead to detrimental effects and it remains an open question under which conditions averaging is beneficial. In this paper, we study this problem from the perspective of information theory: We measure the mutual information between representation and inputs as well as representation and labels in local models and compare it to the respective information contained in the representation of the averaged model. Our empirical results confirm previous observations about the practical usefulness of averaging for neural networks, even if local dataset distributions vary strongly. Furthermore, we obtain more insights about the impact of the aggregation frequency on the information flow and thus on the success of distributed learning. These insights will be helpful both in improving the current synchronization process and in further understanding the effects of model aggregation.

Hsuan-Yin Lin, Siddhartha Kumar, Eirik Rosnes et al.

Private information retrieval (PIR) protocols make it possible to retrieve a file from a database without disclosing any information about the identity of the file being retrieved. These protocols have been rigorously explored from an information-theoretic perspective in recent years. While existing protocols strictly impose that no information is leaked on the file's identity, this work initiates the study of the tradeoffs that can be achieved by relaxing the requirement of perfect privacy. In case the user is willing to leak some information on the identity of the retrieved file, we study how the PIR rate, as well as the upload cost and access complexity, can be improved. For the particular case of replicated servers, we propose two weakly-private information retrieval schemes based on two recent PIR protocols and a family of schemes based on partitioning. Lastly, we compare the performance of the proposed schemes.