34 research outputs found
Systematic Approaches for Telemedicine and Data Coordination for COVID-19 in Baja California, Mexico
Conference proceedings info:
ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologies
Raleigh, HI, United States, March 24-26, 2023
Pages 529-542We provide a model for systematic implementation of telemedicine within a large evaluation center for COVID-19 in the area of Baja California, Mexico. Our model is based on human-centric design factors and cross disciplinary collaborations for scalable data-driven enablement of smartphone, cellular, and video Teleconsul-tation technologies to link hospitals, clinics, and emergency medical services for point-of-care assessments of COVID testing, and for subsequent treatment and quar-antine decisions. A multidisciplinary team was rapidly created, in cooperation with different institutions, including: the Autonomous University of Baja California, the Ministry of Health, the Command, Communication and Computer Control Center
of the Ministry of the State of Baja California (C4), Colleges of Medicine, and the College of Psychologists. Our objective is to provide information to the public and to evaluate COVID-19 in real time and to track, regional, municipal, and state-wide data in real time that informs supply chains and resource allocation with the anticipation of a surge in COVID-19 cases. RESUMEN Proporcionamos un modelo para la implementación sistemática de la telemedicina dentro de un gran centro de evaluación de COVID-19 en el área de Baja California, México. Nuestro modelo se basa en factores de diseño centrados en el ser humano y colaboraciones interdisciplinarias para la habilitación escalable basada en datos de tecnologías de teleconsulta de teléfonos inteligentes, celulares y video para vincular hospitales, clínicas y servicios médicos de emergencia para evaluaciones de COVID en el punto de atención. pruebas, y para el tratamiento posterior y decisiones de cuarentena. Rápidamente se creó un equipo multidisciplinario, en cooperación con diferentes instituciones, entre ellas: la Universidad Autónoma de Baja California, la Secretaría de Salud, el Centro de Comando, Comunicaciones y Control Informático.
de la Secretaría del Estado de Baja California (C4), Facultades de Medicina y Colegio de Psicólogos. Nuestro objetivo es proporcionar información al público y evaluar COVID-19 en tiempo real y rastrear datos regionales, municipales y estatales en tiempo real que informan las cadenas de suministro y la asignación de recursos con la anticipación de un aumento de COVID-19. 19 casos.ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologieshttps://doi.org/10.1007/978-981-99-3236-
Symmetry-Adapted Machine Learning for Information Security
Symmetry-adapted machine learning has shown encouraging ability to mitigate the security risks in information and communication technology (ICT) systems. It is a subset of artificial intelligence (AI) that relies on the principles of processing future events by learning past events or historical data. The autonomous nature of symmetry-adapted machine learning supports effective data processing and analysis for security detection in ICT systems without the interference of human authorities. Many industries are developing machine-learning-adapted solutions to support security for smart hardware, distributed computing, and the cloud. In our Special Issue book, we focus on the deployment of symmetry-adapted machine learning for information security in various application areas. This security approach can support effective methods to handle the dynamic nature of security attacks by extraction and analysis of data to identify hidden patterns of data. The main topics of this Issue include malware classification, an intrusion detection system, image watermarking, color image watermarking, battlefield target aggregation behavior recognition model, IP camera, Internet of Things (IoT) security, service function chain, indoor positioning system, and crypto-analysis
Standardization Roadmap for Unmanned Aircraft Systems, Version 2.0
This Standardization Roadmap for Unmanned Aircraft Systems, Version 2.0 (“roadmap”) is an update to version 1.0 of this document published in December 2018. It identifies existing standards and standards in development, assesses gaps, and makes recommendations for priority areas where there is a perceived need for additional standardization and/or pre-standardization R&D.
The roadmap has examined 78 issue areas, identified a total of 71 open gaps and corresponding recommendations across the topical areas of airworthiness; flight operations (both general concerns and application-specific ones including critical infrastructure inspections, commercial services, and public safety operations); and personnel training, qualifications, and certification. Of that total, 47 gaps/recommendations have been identified as high priority, 21 as medium priority, and 3 as low priority. A “gap” means no published standard or specification exists that covers the particular issue in question. In 53 cases, additional R&D is needed.
As with the earlier version of this document, the hope is that the roadmap will be broadly adopted by the standards community and that it will facilitate a more coherent and coordinated approach to the future development of standards for UAS. To that end, it is envisioned that the roadmap will continue to be promoted in the coming year. It is also envisioned that a mechanism may be established to assess progress on its implementation
Knowledge Capturing in Design Briefing Process for Requirement Elicitation and Validation
Knowledge capturing and reusing are major processes of knowledge management that deal with the elicitation of valuable knowledge via some techniques and methods for use in actual and further studies, projects, services, or products. The construction industry, as well, adopts and uses some of these concepts to improve various construction processes and stages. From pre-design to building delivery knowledge management principles and briefing frameworks have been implemented across project stakeholders: client, design teams, construction teams, consultants, and facility management teams. At pre-design and design stages, understanding the client’s needs and users’ knowledge are crucial for identifying and articulating the expected requirements and objectives. Due to underperforming results and missed goals and objectives, many projects finish with highly dissatisfied clients and loss of contracts for some organizations. Knowledge capturing has beneficial effects via its principles and methods on requirement elicitation and validation at the briefing stage between user, client and designer. This paper presents the importance and usage of knowledge capturing and reusing in briefing process at pre-design and design stages especially the involvement of client and user, and explores the techniques and technologies that are usable in briefing process for requirement elicitation
Survivable Virtual Network Embedding in Transport Networks
Network Virtualization (NV) is perceived as an enabling technology for the future Internet and the 5th Generation (5G) of mobile networks. It is becoming increasingly difficult to keep up with emerging applications’ Quality of Service (QoS) requirements in an ossified Internet. NV addresses the current Internet’s ossification problem by allowing the co-existence of multiple Virtual Networks (VNs), each customized to a specific purpose on the shared Internet. NV also facilitates a new business model, namely, Network-as-a-Service (NaaS), which provides a separation between applications and services, and the networks supporting them. 5G mobile network operators have adopted the NaaS model to partition their physical network resources into multiple VNs (also called network slices) and lease them to service providers. Service providers use the leased VNs to offer customized services satisfying specific QoS requirements without any investment in deploying and managing a physical network infrastructure.
The benefits of NV come at additional resource management challenges. A fundamental problem in NV is to efficiently map the virtual nodes and virtual links of a VN to physical nodes and paths, respectively, known as the Virtual Network Embedding (VNE) problem. A VNE that can survive physical resource failures is known as the survivable VNE (SVNE) problem, and has received significant attention recently. In this thesis, we address variants of the SVNE problem with different bandwidth and reliability requirements for transport networks. Specifically, the thesis includes four main contributions. First, a connectivity-aware VNE approach that ensures VN connectivity without bandwidth guarantee in the face of multiple link failures. Second, a joint spare capacity allocation and VNE scheme that provides bandwidth guarantee against link failures by augmenting VNs with necessary spare capacity. Third, a generalized recovery mechanism to re-embed the VNs that are impacted by a physical node failure. Fourth, a reliable VNE scheme with dedicated protection that allows tuning of available bandwidth of a VN during a physical link failure. We show the effectiveness of the proposed SVNE schemes through extensive simulations. We believe that the thesis can set the stage for further research specially in the area of automated failure management for next generation networks
An Investigation on Benefit-Cost Analysis of Greenhouse Structures in Antalya
Significant population increase across the world, loss of cultivable land and increasing demand for food put pressure on agriculture. To meet the demand, greenhouses are built, which are, light structures with transparent cladding material in order to provide controlled microclimatic environment proper for plant production. Conceptually, greenhouses are similar with manufacturing buildings where a controlled environment for manufacturing and production have been provided and proper spaces for standardized production processes have been enabled. Parallel with the trends in the world, particularly in southern regions, greenhouse structures have been increasingly constructed and operated in Turkey. A significant number of greenhouses are located at Antalya. The satellite images demonstrated that for over last three decades, there has been a continuous invasion of greenhouses on all cultivable land. There are various researches and attempts for the improvement of greenhouse design and for increasing food production by decreasing required energy consumption. However, the majority of greenhouses in Turkey are very rudimentary structures where capital required for investment is low, but maintenance requirements are high when compared with new generation greenhouse structures. In this research paper, life-long capital requirements for construction and operation of greenhouse buildings in Antalya has been investigated by using benefit-cost analysis study
The efficient framework and algorithm for provisioning evolving VDC in federated data centers
Data center has been working as a cost-efficient infrastructure to store a large amount of data and host service applications. With the virtualization technology, a resource request submitted to data center can be abstracted as a virtual data center (VDC) request which consist of virtual machines (VMs) connected through virtual switches, routers and links with guaranteed bandwidth. As one of the challenges, VDC embedding/provisioning focuses on mapping VDC components onto physical nodes and links in data center. In this paper we study the problem of provisioning/embedding for evolving/dynamic VDC request across federated data centers, such that the total operation cost is minimized. We use the VM migration to reconfigure evolving/dynamic VDC for reducing the total operation cost, as well to consolidate the VDCs on as few servers as possible for reducing the number of active servers and thus lowering energy consumption. We design an efficient framework and algorithm for solving the studied NP-Hard problem. Finally, we evaluate and compare the performance of our proposed approach through extensive simulation experiments. The simulation results show that the proposed approach performs better in terms of lowering total operation cost and energy consumption than existing solution does
Modeling the contribution of ecological agriculture for climate change mitigation in cote d'Ivoire
The use of crop models is motivated by the prediction of crop production under climate
change and for the evaluation of climate risk adaptation strategies. Therefore, in the present
study the performance of DSSAT 4.6 was evaluated in a cropping system involving integrated
soil fertility management options that are being promoted as ways of adapting agricultural
systems to improve both crop yield and carbon sequestration on highly degraded soils
encountered throughout middle Côte d’Ivoire. Experimental data encompassed two seasons
in the Guinea savanna zone. Residues from the preceding vegetation were left to dry on plots
like mulch on an experimental design that comprised the following treatments: (i) herbaceous
savanna-maize, (ii)10 year-old of the shrub Chromolaena odorata fallow-maize (iii) 1 or 2
year-old Lalab pupureus stand-rotation, (iv) the legume L. pupureus -maize rotation; (v) continuous
maize crop fertilized with urea; (vi) continuous maize crop fertilized with triple superphosphate;
(vii) continuous maize crop, fertilized with both urea and triple superphosphate
(TSP); (viii) continuous maize cultivation. The model’s sensitivity analysis was run to figure
out how uncertainty of stable organic carbon (SOM3) can generate variation in the prediction
of soil organic carbon (SOC) dynamics during the monitoring period of two years, within
the first soil layer and to estimate the most suitable value. The observed variations were of
0.05 % in total SOC within the short-term and acceptable dynamics of changes were obtained
for 0.80% of SOM3. The DSSAT model was calibrated using data from the 2007-2008
season and validated against independent data sets of yield of 2008-2009 to 2011-2012
cropping seasons. After the default values for SOM3 used in the model was substituted by the
estimated one from sensitivity analysis, the model predicted average maize yields of 1 454
kg ha-1 across the sites versus an observed average value of 1 736 kg ha-1, R2 of 0.72
and RMSE of 597 kg ha-1. The impact of fallow residues and cropping sequence on maize
yield was simulated and compared to conventional fertilizer and control data using historical
climate scenarios over 12 years. Improving soil fertility through conservation agriculture cannot
maintain grain yield in the same way as conventional urea inputs, although there is better
yield stability against high climate variability according to our results
Low-latency and Resource-efficient Service Function Chaining Orchestration in Network Function Virtualization
© 2014 IEEE. Recently, network function virtualization (NFV) has been proposed to solve the dilemma faced by traditional networks and to improve network performance through hardware and software decoupling. The deployment of the service function chain (SFC) is a key technology that affects the performance of virtual network function (VNF). The key issue in the deployment of SFCs is proposing effective algorithms to achieve efficient use of resources. In this article, we propose an SFC deployment optimization (SFCDO) algorithm based on a breadth-first search (BFS). The algorithm first uses a BFS-based algorithm to find the shortest path between the source node and the destination node. Then, based on the shortest path, the path with the fewest hops is preferentially chosen to implement the SFC deployment. Finally, we compare the performances with the greedy and simulated annealing (G-SA) algorithm. The experiment results show that the proposed algorithm is optimized in terms of end-to-end delay and bandwidth resource consumption. In addition, we also consider the load rate of the nodes to achieve network load balancing