• Radiative flow of Jeffrey fluid due to the curved stretching surface is discussed. • First order chemical reaction, heat generation and Ohmic heating are taken into account. • The resultant systems are computed successfully through optimal homotopy analysis method (OHAM). Non-Newtonian materials have tremendous applications in industries, pharmaceuticals, manufacturing, substance designing and natural procedures. These materials are utilized in surface coating, penetrating activities, printing, cooling of metallic plates, damping and braking devices and many others. In view of such innovative applications here we communicate Soret and Dufour impacts in Jeffrey liquid flow caused by curved stretching surface. Thermal conductivity and mass diffusivity are temperature and concentration dependent respectively. Convective conditions are utilized. Radiation, first order chemical reaction, heat generation and Ohmic heating in present attempt are taken into account. Adequate transformations lead to resulting nonlinear differential system. Such system is computed successfully through Optimal homotopy analysis method (OHAM). Skin friction coefficient and Nusselt and Sherwood numbers in addition to velocity, temperature and concentration are examined. Here skin friction and temperature against magnetic field are opposite when compared with velocity. Temperature through Dufour number and radiation has increasing impact. Concentration for variable mas diffusivity and solutal Biot number has opposite response. An increase in thermal transport rate through Eckert number is detected. Sherwood number for curvature and variable mass diffusivity has opposite response. Larger approximation of reaction variable leads to decay concentration.

• Radiative flow of Jeffrey fluid due to the curved stretching surface is discussed. • First order chemical reaction, heat generation and Ohmic heating are taken into account. • The resultant systems are computed successfully through optimal homotopy analysis method (OHAM). Non-Newtonian materials have tremendous applications in industries, pharmaceuticals, manufacturing, substance designing and natural procedures. These materials are utilized in surface coating, penetrating activities, printing, cooling of metallic plates, damping and braking devices and many others. In view of such innovative applications here we communicate Soret and Dufour impacts in Jeffrey liquid flow caused by curved stretching surface. Thermal conductivity and mass diffusivity are temperature and concentration dependent respectively. Convective conditions are utilized. Radiation, first order chemical reaction, heat generation and Ohmic heating in present attempt are taken into account. Adequate transformations lead to resulting nonlinear differential system. Such system is computed successfully through Optimal homotopy analysis method (OHAM). Skin friction coefficient and Nusselt and Sherwood numbers in addition to velocity, temperature and concentration are examined. Here skin friction and temperature against magnetic field are opposite when compared with velocity. Temperature through Dufour number and radiation has increasing impact. Concentration for variable mas diffusivity and solutal Biot number has opposite response. An increase in thermal transport rate through Eckert number is detected. Sherwood number for curvature and variable mass diffusivity has opposite response. Larger approximation of reaction variable leads to decay concentration.

This paper presents a novel methodology for designing the flight control system of a micro aerial vehicle (MAV); it allows the MAV to learn how to fly by itself, without the risk of damage. The proposed methodology uses a magnetic levitation–based safety-guaranteed flight test environment and deep reinforcement learning techniques to avoid the current problems in flight control system design procedures, such as the reality gap issue of simulations, and the safety issues inherent to real flight testing. The safety-guaranteed flight test environment was achieved using a developed magnetic suspension and balance system, which dynamically adjusts magnetic forces interacting with a magnetically levitated MAV. As a result, the MAV can perform in either a free-flight condition for reinforcement learning or can be constrained for safety. This learning environment was developed to permit safe reinforcement learning of MAV, since trial-and-error-based learning typically makes the MAV unstable. In this regard, the MAV can learn to fly by itself based on trial and error, by interacting with the emulated free-flight test environment. Notably, the entire learning process can be conducted without numerical models for both the MAV itself and the flight environment, and the safety of the MAV is guaranteed, even when attempting undesirable actions that might cause the model to become unstable. By avoiding the modeling errors typical of computational simulations and preventing the risk of damage in real flight tests, this approach could enhance the use of reinforcement learning in the development of advanced flight control systems.

본 연구는 Q방법론의 핵심 절차인 의미통합체(concourse)와 Q표본(Q-set) 구축 과정에 대한 표준화된 가이드라인을 제시한다. Q방법론은 인간의 주관성 탐색에 유용한 방법론이지만, 의미통합체와 Q표본 구축 과정이 연구자 개인의 판단에 의존하거나 구체성이 부족하다는 한계가 지속적으로 지적되어 왔다. 특히 국내 연구는 이러한 방법론적 논의가 미흡한 실정이었다.<br/> 이에 본 연구는 국내외 선행연구 검토를 바탕으로, 의미통합체와 Q표본 구축 과정을 체계적 수집, 구조화 및 분류, 체계적 추출, 사전 검토 및 검증의 4단계로 구분하고 각 단계별 구체적 절차와 기준을 명시하였다. 이로써 연구의 재현성과 객관성을 확보하고자 하였다.<br/> 본 연구의 의의는 다음과 같다. 첫째, 기존 연구에서 모호했던 의미통합체 및 Q표본 선정 기준을 명확히 제시하여 Q방법론 연구의 타당성과 신뢰성을 제고했다. 둘째, 연구자의 주관적 판단을 최소화하고 객관적이고 과학적인 절차를 강조함으로써, 후속 연구자들이 보다 엄밀한 방법론을 적용할 수 있는 기반을 마련했다.<br/> 다만, 본 연구는 이론적 검토에 초점을 두었으며, 제안된 절차의 실증적 효용성을 검증하지 못했다는 한계를 지닌다. 향후 연구에서는 다양한 사례 연구를 통해 본 절차의 효과성과 한계를 실증적으로 검토할 필요가 있다. 본 연구는 Q방법론의 학술적 정합성과 실용적 활용도를 높이는 데 기여할 것으로 기대된다.

Motivation: Vessel size index (VSI) MRI of the rodent brain is measured at various in-plane resolutions, but the resolution dependence of VSI has not yet been explored. Goal(s): Here, we investigated the differences in rat brain VSI at mostly measured in-plane resolutions of 125&amp;mu;m2 and 250&amp;mu;m2. Approach: Resolution-dependent differences in VSI across brain regions were investigated in in-vivo rat experiments via a steady-state susceptibility contrast method by injection of monocrystalline iron oxide nanoparticles and validated through Monte Carlo simulations. Results: In the white matter and hippocampus regions, the VSI was measured to be 12% larger as the resolution was lowered from 125&amp;mu;m2 to 250&amp;mu;m2. Impact: Because the resolution dependence of VSI quantification varies across brain regions depending on the vascular configuration within MRI voxels, caution is required when comparing and analyzing brain VSI MRI obtained at different resolutions.

Janghoon Han, Dongkyu Lee, Joongbo Shin, Hyunkyung Bae, Jeesoo Bang, Seonghwan Kim, Stanley Jungkyu Choi, Honglak Lee. Proceedings of the 6th Workshop on NLP for Conversational AI (NLP4ConvAI 2024). 2024.

The increasing demand for programming language education and growing class sizes require immediate and personalized feedback. However, traditional code review methods have limitations in providing this level of feedback. As the capabilities of Large Language Models (LLMs) like GPT for generating accurate solutions and timely code reviews are verified, this research proposes a system that employs GPT-4 to offer learner-friendly code reviews and minimize the risk of AI-assist cheating. To provide learner-friendly code reviews, a dataset was collected from an online judge system, and this dataset was utilized to develop and enhance the system's prompts. In addition, to minimize AI-assist cheating, the system flow was designed to provide code reviews only for code submitted by a learner, and a feature that highlights code lines to fix was added. After the initial system was deployed on the web, software education experts conducted usability test. Based on the results, improvement strategies were developed to improve code review and code correctness check module, thereby enhancing the system. The improved system underwent evaluation by software education experts based on four criteria: strict code correctness checks, response time, lower API call costs, and the quality of code reviews. The results demonstrated a performance to accurately identify error types, shorten response times, lower API call costs, and maintain high-quality code reviews without major issues. Feedback from participants affirmed the tool's suitability for teaching programming to primary and secondary school students. Given these benefits, the system is anticipated to be a efficient learning tool in programming language learning for educational settings.

We present a 14nm FinFET embedded MRAM (eMRAM) technology for non-volatile RAM (nvRAM) applications, featuring endurance of 1E12 cycles, 100ns write speed, 150°C retention for 10 years, and macro density of 18Mb/mm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>. With SRAM interface, this macro provides write speed 24 times faster than flash-type eMRAM and ~50% area saving compared to SRAM. Compared to 28nm nvRAM-type eMRAM, we have improved retention temperature from 89°C to 150°C at the same endurance characteristics, which is suitable for automotive-grade products.