Dynamic Frequency Scaling Regarding Memory for Energy Efficiency of Embedded Systems

Memory significantly affects the power consumption of embedded systems as well as performance. CPU frequency scaling for power management could fail in optimizing the energy efficiency without considering the memory access. In this paper, we analyze the power consumption and energy efficiency of an embedded system that supports dynamic scaling of frequency for both CPU and memory access. The power consumption of the CPU and the memory is modeled to show that the memory access rate affects the energy efficiency and the CPU frequency selection. Based on the power model, a method for frequency selection is presented to optimize the power efficiency which is measured using Energy-Delay Product (EDP). The proposed method is implemented and tested on a commercial smartphone to achieve about 3.3% - 7.6% enhancement comparing with the power management policy provided by the manufacturer in terms of EDP

On non-Abelian T-duality for non-semisimple groups

We revisit non-Abelian T-duality for non-semisimple groups, where it is well-known that a mixed gravitational-gauge anomaly leads to $\sigma$-models that are scale, but not Weyl-invariant. Taking into account the variation of a non-local anomalous term in the T-dual $\sigma$-model of Elitzer, Giveon, Rabinovici, Schwimmer \& Veneziano, we show that the equations of motion of generalized supergravity follow from the $\sigma$-model once the Killing vector $I$ is identified with the trace of the structure constants. As a result, non-Abelian T-duals with respect to non-semisimple groups are solutions to generalized supergravity. We illustrate our findings with Bianchi spacetimes.Comment: 20 pages; v2 show equations of motion of generalized supergravity follow from EGRSV sigma-mode

Assessment of weather events impacts on forage production trend of sorghum-sudangrass hybrid

This study aimed to assess the impact of weather events on the sorghum-sudangrass hybrid (Sorghum bicolor L.) cultivar production trend in the central inland region of Korea during the monsoon season, using time series analysis. The sorghum-sudangrass production data collected between 1988 and 2013 were compiled along with the production year’s weather data. The growing degree days (GDD), accumulated rainfall, and sunshine duration were used to assess their impacts on forage production (kg/ha) trend. Conversely, GDD and accumulated rainfall had positive and negative effects on the trend of forage production, respectively. Meanwhile, weather events such as heavy rainfall and typhoon were also collected based on weather warnings as weather events in the Korean monsoon season. The impact of weather events did not affect forage production, even with the increasing frequency and intensity of heavy rainfall. Therefore, the trend of forage production for the sorghum-sudangrass hybrid was forecasted to slightly increase until 2045. The predicted forage production in 2045 will be 14,926 ± 6,657 kg/ha. It is likely that the damage by heavy rainfall and typhoons can be reduced through more frequent harvest against short-term single damage and a deeper extension of the root system against soil erosion and lodging. Therefore, in an environment that is rapidly changing due to climate change and extreme/abnormal weather, the cultivation of the sorghum-sudangrass hybrid would be advantageous in securing stable and robust forage production. Through this study, we propose the cultivation of sorghum-sudangrass hybrid as one of the alternative summer forage options to achieve stable forage production during the dynamically changing monsoon, in spite of rather lower nutrient value than that of maize (Zea mays L.)

What is the Difference Between ABNORMAL CLIMATE and EXTREME CLIMATE that Cause Yield Damage to Silage Maize (Zea mays L.)?

This study aimed to compare the characteristics by estimating the impacts of abnormal climate and extreme climate on silage maize. In the maize-climate database, the variables were dry matter yield (DMY, kg/ha), mean temperature (MT, °C), lowest temperature (LT, °C), highest temperature (HT, °C), maximum precipitation (MP, mm/hr), accumulated precipitation (AP, mm), maximum wind speed (MW, m/s), mean wind speed (WS, m/s), sunshine duration (SD, hr). To define the abnormal climate, favorable condition was confirmed using the principal component analysis against a normal climate. In order to define the extreme climate, firstly, the median-interquartile method was used instead of the mean-standard deviation method. As a result, in mid-June, the characteristics of early monsoons without typhoons were confirmed as poor. In particular, MP in abnormal climate (20.54 mm/hr) was three times greater than that in normal climate (6.61 mm/hr). The damage in DMY caused by the abnormal climate in mid-June was estimated to be 1,155.9 kg/ha. For the extreme climate in mid-June, the low-extreme LT, high-extreme AP, and high-extreme MW were detected in the trends. However, the year records were different for each point. Thus, the damage in DMY was estimated based on high-extreme AP, as a representative scenario. As a result, the damage in DMY caused by the extreme climate in mid-June was estimated to be 927.2 kg/ha. Hence, the magnitude of yield damage to silage maize caused by extreme climate and abnormal climate, as well as characteristics of high precipitation, were similar

Effect and Safety of Shihogyejitang for Drug Resistant Childhood Epilepsy

Objective. Herbal medicine has been widely used to treat drug resistant epilepsy. Shihogyejitang (SGT) has been commonly used to treat epilepsy. We investigated the effect and safety of SGT in children with drug resistant epilepsy. Design. We reviewed medical records of 54 patients with epilepsy, who failed to respond to at least two antiepileptic drugs and have been treated with SGT between April 2006 and June 2014 at the Department of Pediatric Neurology, I-Tomato Hospital, Korea. Effect was measured by the response rate, seizure-free rate, and retention rate at six months. We also checked adverse events, change in antiepileptic drugs use, and the variables related to the outcome. Results. Intent-to-treat analysis showed that, after six months, 44.4% showed a >50% seizure reduction, 24.1% including seizure-free, respectively, and 53.7% remained on SGT. Two adverse events were reported, mild skin rash and fever. Focal seizure type presented significantly more positive responses when compared with other seizure types at six months ( = 0.0284, Fisher's exact test). Conclusion. SGT is an effective treatment with excellent tolerability for drug resistant epilepsy patients. Our data provide evidence that SGT may be used as alternative treatment option when antiepileptic drug does not work in epilepsy children

Confirmation of causality of climatic and soil physical factors affecting the corn (Zea mays L.) yield for silage in the climate-soil-yield network

This study aimed to confirm the causality of climatic and soil physical factors on silage corn yield based on the climatesoil-yield network in Korea. The climatic variables were growing degree days, high temperature, low temperature, surface temperature, rainfall, relative humidity, wind speed, and sunshine duration before and after silking. The soil physical variables were the effective depth, slope and drainage class of the soil. The yield variables were total digestible nutrients, dry matter and fresh matter yields. The network was constructed using structural equations and neural network models. In the result of the network, three causalities were remarkable. First, all longitudinal climatic causality before and after the silking stages were significant. It implies that the effect of climate in the vegetative stage reaches to yield through themselves in the reproductive stage. Second, there was the causality between climatic and soil physical factors based on indirect effects. Thus, it is likely to lead to an offset between the direct and indirect effects of soil physical factors. Finally, the effects of drought and heavy rainfall were clear before and after silking stages, respectively. It indicates that stress can damage the corn yield for silage. Here, the damage caused by the drought could be recovered due to various indirect effects, while the damage caused by heavy rainfall was fatal because there was a lack of an indirect path to recover from. This study contributed to identifying how various climatic and soil physical factors can affect production in the network. Furthermore, the climate-soil-yield network for silage corn in this study will help extend the structure with various factors in future studies

Comparison of Causality of Temperature and Precipitation on Italian Ryegrass (Lolium Multiflorum Lam.) Yield between Cultivation Fields via Multi-Group Structural Equation Model Analysis in the Republic of Korea

This study aimed to compare the causality of climatic factors affecting the yield of Italian ryegrass (IRG) between upland fields and paddy fields, by multi-group structure equation modeling. The raw data (n = 728) on forage contains both yield, field type, and the plantation address were collected from the Rural Development Administration, Republic of Korea. The climatic factors were: growing days, temperature and precipitation-in autumn and next spring seasons-from the climate big data of the weather information system of Korean Meteorology Administration. In the result, the composition of climatic factors was similar, but the causality by the paths was different between upland fields and paddy fields. In particular, yield in the paddy fields was sensitive to autumn precipitation because of short growing days in the rice-rotation system. In the paddy fields, the precipitation effect in both autumn and the next spring indirectly affected the yield through temperature. The autumn temperature effect on yield in the paddy fields was 2.82 times greater than in the upland fields, between the two field types, the spring temperature effect was somewhat similar after wintering; thus, IRG cultivation in paddy fields should be limited to the south. However, there is greater suitability for IRG in the upland fields in the autumn, where the benefits of higher temperatures accumulate to offset effectively the short growing days. This study will assist in checking areas suitable for IRG cultivation as a winter forage crop in the Republic of Korea. In the future, the structure established in this study will be expanded by adding variables related to soil physical properties from soil information system and cultivation management from survey sheets

Yield Prediction Modeling for Sorghum–Sudangrass Hybrid Based on Climatic, Soil, and Cultivar Data in the Republic of Korea

The objective of this study was to construct a sorghum–sudangrass hybrid (SSH) yield prediction model based on climatic, soil, and cultivar information in the southern area of the Korean Peninsula. Besides, the effects of climatic factors on SSH yield were investigated simultaneously. The SSH dataset (n = 105), including Dry Matter Yield (DMY, kg/ha), Seeding-Harvest Accumulated Temperature (SHaAT, °C), Seeding–Harvest Accumulated Precipitation (SHAP, mm), Seeding–Harvest Sunshine Duration (SHSD, h), Soil Suitability Score (SSS), and cultivar maturity information, was developed for model construction. Subsequently, using general linear modeling method, the SSH yield prediction model was constructed as follows: DMY = 6.5SHaAT – 4.9SHAP + 13.8SHSD – 54.4SSS – 1036.4 + Maturity. The impacts of the accumulated thermal climatic variables and accumulated precipitation during crop growth on the variance of SSH yield in this region were confirmed. The summer-concentrated precipitation in the southern area of the Korean Peninsula exceeded the proper range of SSH water requirement and led to stresses to its yield production. Furthermore, to improve the data quality for high fitness model construction, the standard schedule for forage crop cultivation experiment in this region was recommended to be developed, especially under the data requirement in the context of the big data era

Effect and Safety of Shihogyejitang for Drug Resistant Childhood Epilepsy

Objective. Herbal medicine has been widely used to treat drug resistant epilepsy. Shihogyejitang (SGT) has been commonly used to treat epilepsy. We investigated the effect and safety of SGT in children with drug resistant epilepsy. Design. We reviewed medical records of 54 patients with epilepsy, who failed to respond to at least two antiepileptic drugs and have been treated with SGT between April 2006 and June 2014 at the Department of Pediatric Neurology, I-Tomato Hospital, Korea. Effect was measured by the response rate, seizure-free rate, and retention rate at six months. We also checked adverse events, change in antiepileptic drugs use, and the variables related to the outcome. Results. Intent-to-treat analysis showed that, after six months, 44.4% showed a >50% seizure reduction, 24.1% including seizure-free, respectively, and 53.7% remained on SGT. Two adverse events were reported, mild skin rash and fever. Focal seizure type presented significantly more positive responses when compared with other seizure types at six months (p=0.0284, Fisher’s exact test). Conclusion. SGT is an effective treatment with excellent tolerability for drug resistant epilepsy patients. Our data provide evidence that SGT may be used as alternative treatment option when antiepileptic drug does not work in epilepsy children

Effect of Heavy Rainfall Events on the Dry Matter Yield Trend of Whole Crop Maize (<i>Zea mays</i> L.)

The objective of this study was to detect the historical dry matter yield (DMY) trend and to evaluate the effects of heavy rainfall events on the observed DMY trend of whole crop maize (WCM, Zea mays L.) using time-series analysis in Suwon, Republic of Korea. The climatic variables corresponding to the seeding to harvesting period, including the growing degree days, mean temperature, etc., of WCM along with the DMY data (n = 543) during 1982&#8211;2011, were used in the analysis. The DMY trend was detected using Autoregressive Integrated Moving Average with the explanatory variables (ARIMAX) form of time-series trend analysis. The optimal DMY model was found to be ARIMAX (1, 1, 1), indicating that the DMY trend follows the mean DMY of the preceding one year and the residual of the preceding one year with an integration level of 1. Furthermore, the SHGDD and SHHR were determined to be the main variables responsible for the observed trend in the DMY of WCM. During heavy rainfall events, the DMY was found to be decreasing by 4745.27 kg/ha (p &lt; 0.01). Our analysis also revealed that both the intensity and frequency of heavy rainfall events have been increasing since 2005. The forecasted DMY indicates the potential decrease, which is expected to be 11,607 kg/ha by 2045. This study provided us evidence for the correlation between the DMY and heavy rainfall events that opens the way to provide solutions for challenges that summer forage crops face in the Republic of Korea