We review a system that performs accurate computation of body temperature elevation and sweating by combining electromagnetic and thermal analysis with weather forecast data toward the risk assessment and management. We validate our computational code by comparing with different exposure scenarios, and then extend to estimate allowable time of firefighters as a computational example. We also review our newly-designed system for public enlightenment toward reducing heat stroke patients. Finally, we apply the system to estimate the number of patients of heat stroke in summer.
In recent years, the rates of heat-related morbidity and mortality have begun to increase with the increase in global warming; in this context, it is noteworthy that the number of patients transported by ambulance in heat-related cases in Japan reached 95,137 in 2018. The estimation of heat-related morbidity forms a key factor in proposing and implementing suitable intervention strategies and ambulance availability and arrangements. Heat-related morbidity is known to be fairly correlated to metrics related to ambient conditions, thus necessitating the exploration of new metrics to more accurately estimate morbidity. In this study, we use an integrated computational technique relating to thermodynamics and thermoregulation to estimate daily peak core temperature elevation and daily water loss, which are linked to heat-related illnesses, from weather data of three different prefectures in Japan (Tokyo, Osaka, and Aichi). The correlations of the computed core temperature elevation and water loss as well as conventional ambient conditions are investigated in terms of number of patients suffering from heat-related illnesses transported by ambulance from 2013 to 2018. The estimated water loss per the proposed computation yields better correlation with the number of patients transported by ambulance. In particular, the weight-sum daily water loss for two to three successive days is found to be an important metric for predicting the number of patients transported by ambulance. For the same ambient conditions, morbidity is found to decrease to 0.4 owing to heat adaption at the end of summer (60 days) as compared with that at the end of the rainy season. Thus, the weighted sum of water loss and daily average ambient temperature for successive days can be used as better metrics than conventional weather data for the application of intervention strategies and planning of ambulance arrangements for heat-related morbidity.
In this work, we report a novel approach using thermal annealing to recover the degradation of cell characteristics due to program/erase (P/E) cycling in 3D flash memory. To achieve an effective recovery, the threshold voltage (Vth) of the cell during thermal annealing should be close to the neutral Vth level, at which defects in the tunnel dielectric layer (TNL) generated by P/E cycling are electrically empty. Optimized annealing temperatures and times, specifically 3 hours (h) at 200 °C or 7 h at 150 °C, effectively recover the degradation of the cell characteristics caused by 10k P/E cycling. Furthermore, the recovery effect of annealing is valid even after repeating 10k P/E cycling and recovery annealing at least 5 times. Optimized recovery annealing can achieve reuse of 3D flash memory that have reached their end-of-life (EOL), contributing to sustainability by reducing CO2 emissions during product manufacturing.
XML is a de-fact standard format on the Web. In general, schemas of XML documents are continuously updated according to changes in real world. If a schema is updated, then query expressions have to be transformed so that they are \valid under the updated schema, since the expressions are no longer valid under the updated schema due to the schema update. However, this is not an easy task since many of recent schemas are large and complex and thus it is becoming difficult to know how to update the query expressions correctly. In this paper, we propose an algorithm for transforming XPath expressions according to schema evolution. For an XPath expression p and a schema S , our algorithm treats both p and S as tree automata T A p and T A S,
This paper deals with a new design problem of adaptive gain robust model-following/tracking controllers for a class of systems with matched and unmatched uncertainties via piecewise Lyapunov functions. In the proposed design approach, compensation inputs for matched and mismatched uncertainties for the system are introduced and the proposed adaptive gain model-following/tracking robust controller can achieve that the tracking error decreases asymptotically to zero in spite of uncertainties. In this paper, on the basis of the concept of piecewise Lyapunov functions, we show linear matrix inequality-based sufficient conditions for the existence of the proposed controller. Finally, a numerical example is given to demonstrate the effectiveness of the proposed method.
In the Knowledge Graph Reasoning Challenge, the plot of a mystery novel is converted into a knowledge graph. Building the graph requires the work of choosing the parts to put into the knowledge graph. This research aims to automate this task. Specifically, BERT, a Natural Language Processing model, is used to classify with either summary or non-summary, with the results proposed as the parts to put into the knowledge graph. We established a binary classification model and verified its accuracy. Its was found to have an F-value of 0.59. Given the likelihood of improving the accuracy, it is thought that organizing the dataset could have a significant impact. This is to be pursued as a next step.
Power consumption and thermal throttling of the 3D flash memory have become a prevalent issue owing to the requirement for higher performance in SSDs. One of the main causes is the on-die charge pump circuit, which has a low conversion efficiency and induces high heat generation. The heat generation becomes a critical issue due to the high-density mounting of components, especially in mobile products. In this work, we fabricated a 3D flash memory with an in-package boost converter to replace the on-die charge pump circuit. The boost converter consists of three types of discrete components: a DC-DC converter, an inductor, and capacitors. Using the in package boost converter, we show that the power consumption can be reduced by up to 39% while the temperature rise can be reduced by 50%. Furthermore, when the number of word line (WL) layers reaches 1000, a significantly large power reduction up to 43% can be achieved, resulting in 9% smaller power consumption compared to the conventional 1xx layers. The proposed in-package boost converter is an effective scheme to suppress the power consumption and heat generation and can realize the development of a thermal throttling-less SSD.
