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Aziridine-capped poly(ethylene glycol) brush copolymer: Versatile cross-linkers for adhesives with tunable architecture
No full textComparative Techno-economic analysis of methanol production via carbon dioxide reforming of landfill gas using a highly active and stable Nickel-based catalyst
No full textThe economic viability of a methanol production process through carbon dioxide reforming of landfill gas using a newly developed nickel-based catalyst was assessed. The development of the catalyst and techno-economic analysis of the designed process were targeted. The nickel-based catalyst showed a highly active and stable performance even at an extremely high gas hourly space velocity of 1,620,000 mL g- 1h- 1. The high activity of the catalyst was due to the abundant nickel active sites (metallic nickel particles) on its surface. Coke formation was suppressed by the small particle size of nickel and relatively high oxygen storage capacity, resulting in a stable catalytic performance. In the process simulation, the methanol production system based on the nickelbased catalyst (new process) leveraged its smaller reformer size and more efficient heat utilization compared to those of a previously reported system based on a rhodium-based catalyst (base process) because of its higher gas hourly space velocity. The process simulation was conducted based on the gas hourly space velocity of 312,346 mL g- 1h- 1. The unit production costs of methanol were reduced from 184.0 ton-1 in the new process. In addition, profitability analysis based on the global market price of methanol demonstrated that the new process exhibited a positive net present value, indicating economic feasibility, whereas the base process was not viable in the worst-case scenario (lowest market price of methanol)
A Pharmacometric Model to Predict Chemotherapy-Induced Myelosuppression and Associated Risk Factors in Non-Small Cell Lung Cancer
Get PDFChemotherapy often induces severe neutropenia due to the myelosuppressive effect. While predictive pharmacokinetic (PK)/pharmacodynamic (PD) models of absolute neutrophil count (ANC) after anticancer drug administrations have been developed, their deployments to routine clinics have been limited due to the unavailability of PK data and sparseness of PD (or ANC) data. Here, we sought to develop a model describing temporal changes of ANC in non-small cell lung cancer patients receiving (i) combined chemotherapy of paclitaxel and cisplatin and (ii) granulocyte colony stimulating factor (G-CSF) treatment when needed, under such limited circumstances. Maturation of myelocytes into blood neutrophils was described by transit compartments with negative feedback. The K-PD model was employed for drug effects with drug concentration unavailable and the constant model for G-CSF effects. The fitted model exhibited reasonable goodness of fit and parameter estimates. Covariate analyses revealed that ANC decreased in those without diabetes mellitus and female patients. Using the final model obtained, an R Shiny web-based application was developed, which can visualize predicted ANC profiles and associated risk of severe neutropenia for a new patient. Our model and application can be used as a supportive tool to identify patients at the risk of grade 4 neutropenia early and suggest dose reduction
How to evaluate the wearability of electronic air filtration masks
No full textElectronic masks are wearable devices that can replace common disposable masks. Understanding user discomfort is important for proper electronic mask evaluation and design, but the method has not been standardized yet. This study presents evaluation methods that can qualitatively and quantitatively assess user discomfort caused by wearing an electronic mask. User interviews, surveys, and laboratory experiments were conducted. The pulling force of the ear bands and the contact pressure distribution of the face were selected as quantitative evaluation variables. The task was determined in consideration of various mask use environments through user observation. The final evaluation method was applied to the comparative evaluation of the two masks. It is the first attempt to evaluate the usability of the electronic mask, and this evaluation method could improve user convenience by using it for product development and improvement
Development of a Robot-Assisted Online Pain Communication System Using a Squeezable Tangible User Interface
No full textDescribing pain intensity constitutes an essential part of pain communication. A medical practitioner cannot depend on pain scales because of the criteria differences between the patient and caregiver. However, online pain communication is dependent on a patient???s description and an assessment on a pain scale. This paper proposes a robot-assisted pain communication system with a tangible user interface that enables non-numerical pain communication. The SQTT interface is proposed using design processes consisting of a novel squeezable input device and a twisting robot. The twisting expression of the robot represents the pain intensity, which is gauged from the squeezing power on the input device. Integrating input and output requires defining how the twisting motion of the robot is rendered from the squeezing input. An experiment was conducted to evaluate the four methods of rendering: raw, smoothing (moving average), dynamic smoothing, and updating peak. The result of a non-parametric one-way analysis of variance indicates a significant difference between the rendering methods. As a result, an appropriate rendering method is proposed based on the ranges: smoothing for mild pain, vibrating for moderate pain, and exaggerating for severe pain. In conclusion, the robot-assisted pain communication system can be implemented with intuitive interaction primitives for online context. This paper contributes a lesson in designing a robot-assisted online pain communication, which uses a new method of measuring deformation
Abnormal State Detection Model Using Deep One-Class Classification in Nuclear Power Plant
No full textEarly warning for critical transitions using machine-based predictability
Get PDFDetecting critical transitions before they occur is challenging, especially for complex dynamical systems. While some early-warning indicators have been suggested to capture the phenomenon of slowing down in the system's response near critical transitions, their applicability to real systems is yet limited. In this paper, we propose the concept of predictability based on machine learning methods, which leads to an alternative early-warning indicator. The predictability metric takes a black-box approach and assesses the impact of uncertainties itself in identifying abrupt transitions in time series. We have applied the proposed metric to the time series generated from different systems, including an ecological model and an electric power system. We show that the predictability changes noticeably before critical transitions occur, while other general indicators such as variance and autocorrelation fail to make any notable signals
A Critical Review on the Introduction of the Continuity of Operations Plan(COOP) in Korean Local Governments
No full textDepartment of Urban and Environmental Engineering (Disaster Management Engineering)After the large disasters such 9/11, governments in the world realized that every organization should maintain its essential functions in the event of a disaster to avoid irreversible losses as much as possible. Continuity of Operation Plan(COOP) (Continuity of Operation Plan(COOP)) is a plan for maintaining the essential function of the organization in the event of a disaster in the public sector. Continuity of Operation Plan(COOP) can help continue the essential functions of the public organizations during emergency situations. The Korean government introduced the Continuity of Operation Plan(COOP) in public organizations. It became mandatory to introduce Continuity of Operation Plan(COOP) in public organizations including local governments in 2017. However, many public institutions experienced difficulties in introducing Continuity of Operation Plan(COOP). The research questions of this research are why it is difficult to introduce and how to respond these difficulties. Exploratory research was conducted in advance through interviews with experts in accordance with the characteristics of the research questions, and Continuity of Operation Plan(COOP) alternatives were prepared based on the responses of experts and the cases of the United States, the United Kingdom, and Japan. After that, an AHP analysis was conducted to find out preferred alternatives among conflicting alternatives from experts??? interviews and find out how effective the alternatives suggested in this research were.
As a result, the mismatch between other disaster preparation manuals and Continuity of Operation Plan(COOP), and the absence of standard Continuity of Operation Plan(COOP) plans for local governments are the main difficulties. In AHP analysis, we build the framework to know what the most preferable alternatives. As a result, simplifying Continuity of Operation Plan(COOP) and Building Standard Continuity of Operation Plan(COOP) plans by Central Government is the best option for the two problems.
And also, I???ve suggested there needs to be made a standard plan for local government???s Continuity of Operation Plan(COOP) at the central government???s stage. The suggested standard plan is based on a simplified Continuity of Operation Plan(COOP) to prevent conflict with existing disaster management manuals. This plan consisting scenario-based Risk Assessment(RA), work division-based Business Impact Analysis(BIA) and securing essential resources like manpower and alternative office and other resources which don???t deal with existing disaster manuals. In AHP analysis, this alternative has improved over current Continuity of Operation Plan(COOP) guidelines.clos
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No full textGraduate School of Artificial IntelligenceMusic creation is difficult because one must express one???s creativity while following strict rules. The advancement of deep learning technologies has diversified the methods to automate complex processes and express creativity in music composition. However, prior research has not paid much attention to exploring the audiences??? subjective satisfaction to improve music generation models. In this paper, we evaluate human satisfaction with the state-of-the-art automatic symbolic music generation models using deep learning. In doing so, we define a taxonomy for music generation models and suggest nine subjective evaluation metrics. Through an evaluation study, we obtained more than 700 evaluations from 100 participants, using the suggested metrics. Our evaluation study reveals that the token representation method and models??? characteristics affect subjective satisfaction. Through our qualitative analysis, we deepen our understanding of AI-generated music and suggested evaluation metrics. Lastly, we present lessons learned and discuss future research directions of deep learning models for music creation.clos