Use of nuclear weapons: illusion of peace

Обґрунтовано необхідність дослідження використання ядерної зброї у всьому світі. Проаналізовані наслідки першого та останнього випадку застосування ядерної зброї у воєнних цілях в містах Японії Хіросімі та Нагасакі. Проведена оцінка подальшого випробовування ядерної зброї в ході її розробки.Обоснована необходимость исследования использования ядерного оружия во всем мире. Проанализированы последствия первого и последнего случая применения ядерного оружия в военных целях в городах Японии Хиросиме и Нагасаки. Проведена оценка дальнейшего испытания ядерного оружия в ходе ее разработки.The necessity of research of use of nuclear weapons throughout the whole world. The consequences of the first and the last case of using nuclear weapons for military purposes in the Japanese cities of Hiroshima and Nagasaki. The assessment of further testing nuclear weapons in the course of its development, as well as its use for the excavation of the artificial harbors, geological exploration of oil and gas exploration, testing, aimed at stimulating and facilitating the deposits of natural gas

Geometry Learning Through Batik Reconstruction

In this world, the shapes of objects, including Batik motifs in Indonesia, are regular and irregular. One of the regular Batik motifs is Surya Kawung Batik from Mojokerto. The purpose of this research is to observe the ability of the Electrical Engineering Department students in Maranatha Christian University to study and reconstruct the geometric shapes of Surya Kawung Batik. In the making of the Batik motifs, the research methods employed are survey, observation, exploration, testing, and improvement, while in the learning process, the method applied is descriptive qualitative, in which the researchers check the data credibility. Turtle graphics algorithm and mathematical calculations are used to form Batik geometric motifs. The result of this research shows an increase in the students' ability to learn the geometric shapes and to reconstruct digital Batik motifs which resemble the original Batik motifs and which can be stored using a smaller memory. If the memory for storing motifs is small, the required storage space will be more efficient.

Closed-loop optimization of fast-charging protocols for batteries with machine learning.

Simultaneously optimizing many design parameters in time-consuming experiments causes bottlenecks in a broad range of scientific and engineering disciplines1,2. One such example is process and control optimization for lithium-ion batteries during materials selection, cell manufacturing and operation. A typical objective is to maximize battery lifetime; however, conducting even a single experiment to evaluate lifetime can take months to years3-5. Furthermore, both large parameter spaces and high sampling variability3,6,7 necessitate a large number of experiments. Hence, the key challenge is to reduce both the number and the duration of the experiments required. Here we develop and demonstrate a machine learning methodology  to efficiently optimize a parameter space specifying the current and voltage profiles of six-step, ten-minute fast-charging protocols for maximizing battery cycle life, which can alleviate range anxiety for electric-vehicle users8,9. We combine two key elements to reduce the optimization cost: an early-prediction model5, which reduces the time per experiment by predicting the final cycle life using data from the first few cycles, and a Bayesian optimization algorithm10,11, which reduces the number of experiments by balancing exploration and exploitation to efficiently probe the parameter space of charging protocols. Using this methodology, we rapidly identify high-cycle-life charging protocols among 224 candidates in 16 days (compared with over 500 days using exhaustive search without early prediction), and subsequently validate the accuracy and efficiency of our optimization approach. Our closed-loop methodology automatically incorporates feedback from past experiments to inform future decisions and can be generalized to other applications in battery design and, more broadly, other scientific domains that involve time-intensive experiments and multi-dimensional design spaces

Energy-efficient and high-performance lock speculation hardware for embedded multicore systems

Embedded systems are becoming increasingly common in everyday life and like their general-purpose counterparts, they have shifted towards shared memory multicore architectures. However, they are much more resource constrained, and as they often run on batteries, energy efficiency becomes critically important. In such systems, achieving high concurrency is a key demand for delivering satisfactory performance at low energy cost. In order to achieve this high concurrency, consistency across the shared memory hierarchy must be accomplished in a cost-effective manner in terms of performance, energy, and implementation complexity. In this article, we propose Embedded-Spec, a hardware solution for supporting transparent lock speculation, without the requirement for special supporting instructions. Using this approach, we evaluate the energy consumption and performance of a suite of benchmarks, exploring a range of contention management and retry policies. We conclude that for resource-constrained platforms, lock speculation can provide real benefits in terms of improved concurrency and energy efficiency, as long as the underlying hardware support is carefully configured.This work is supported in part by NSF under Grants CCF-0903384, CCF-0903295, CNS-1319495, and CNS-1319095 as well the Semiconductor Research Corporation under grant number 1983.001. (CCF-0903384 - NSF; CCF-0903295 - NSF; CNS-1319495 - NSF; CNS-1319095 - NSF; 1983.001 - Semiconductor Research Corporation

DOES HEURISTIC BEHAVIOR LEAVE ANOMALIES IN THE CAPITAL MARKET?

Introduction/Main Objectives: This study aims to examine the role of heuristic behavior toward the formation of fundamental and technical anomalies in the capital market. This study also aims to examine the role of fundamental and technical anomalies on investment performance. Background Problems: Efficient Market Hypothesis (EMH) is not always able to explain all of the events or phenomena so that it still raises questions and produces research results that do not meet expectations, so in the end these phenomena are categorized as market anomalies. This study investigates whether heuristics have an effect on fundamental and technical anomalies and whether the anomalies have an effect on investment performance. Novelty: There is no research that uses hindsight variables incorporated into heuristics; therefore, this study confirms that the indicators used for hindsight measurements are appropriate for measuring what will be measured. Previous research did not involve hindsight in the heuristic category. Research Methods: Data management are done by using Structural Equation Modelling (SEM) with the help of the WarpPLS analysis tool. Mediation exploration testing was accomplished with variance accounted for (VAF). Findings/Results: The results of the study show that heuristics (availability, representativeness, and hindsight) are proven to be one of the factors that cause fundamental and technical anomalies in the capital market, except for availability heuristics. Conclusion: A large number of anomalies in the capital market do not stop investors from continuing to invest, so that at a certain level, investors are satisfied with their investments’ performance because they use heuristics in an efficient way