ANALISIS KEBIJAKAN JEPANG DALAM PEMBATASAN EKSPOR BAHAN KIMIA TERHADAP KOREA SELATAN TAHUN 2019

This research investigates Japan's policy of restricting chemical exports to South Korea in 2019. The chemicals restricted by Japan include fluorinated polyamide, photoresist, and hydrogen fluoride. Chemicals originating from Japan are crucial materials for South Korea's technology industry. This research is explanatory, aiming to explain why Japan imposed restrictions on chemical exports to South Korea in 2019. The study utilizes foreign policy theory with an adaptive model according to James Nathan Rosenau. This theory elucidates Japan's national interests when implementing the policy of restricting chemical exports to South Korea in 2019 and how domestic and foreign actors were involved in influencing the policies. The relationship between Japan and South Korea has been ongoing since 1910, where historical issues between Japan and South Korea have persisted for a long time. The research findings indicate that historical issues are one of the factors in the formulation of Japan's policy to limit chemical exports to South Korea in 2019. Additionally, Japan restricted chemical exports to South Korea to maintain their national security

Bottom-Up and Top-Down Reasoning with Hierarchical Rectified Gaussians

Convolutional neural nets (CNNs) have demonstrated remarkable performance in recent history. Such approaches tend to work in a unidirectional bottom-up feed-forward fashion. However, practical experience and biological evidence tells us that feedback plays a crucial role, particularly for detailed spatial understanding tasks. This work explores bidirectional architectures that also reason with top-down feedback: neural units are influenced by both lower and higher-level units. We do so by treating units as rectified latent variables in a quadratic energy function, which can be seen as a hierarchical Rectified Gaussian model (RGs). We show that RGs can be optimized with a quadratic program (QP), that can in turn be optimized with a recurrent neural network (with rectified linear units). This allows RGs to be trained with GPU-optimized gradient descent. From a theoretical perspective, RGs help establish a connection between CNNs and hierarchical probabilistic models. From a practical perspective, RGs are well suited for detailed spatial tasks that can benefit from top-down reasoning. We illustrate them on the challenging task of keypoint localization under occlusions, where local bottom-up evidence may be misleading. We demonstrate state-of-the-art results on challenging benchmarks.Comment: To appear in CVPR 201

Managing engagement behaviors in a network of customers and stakeholders: evidence from the nursing home sector

Firms striving for long-term profitability need to build stronger customer-firm relationships by getting their customers more engaged with the firm. One path to this end is introducing practices to manage different forms of customer engagement behaviors (CEBs). To develop more effective and efficient CEB management practices, this research proposes and empirically tests a theoretical model on managerial and psychological processes to encourage CEBs that are embedded in a broader network of customers and stakeholders. Based on qualitative and quantitative studies in nursing homes, we demonstrate that organizational support and overall service quality toward significant others influence some forms of CEBs—more particularly feedback and positive word of mouth (WOM) behaviors—through customer affect toward the organization. It is interesting to note that customer affect toward the organization encouragesWOMbehaviors, while it discourages feedback behaviors. Conversely, managerial processes that increase customer role readiness—such as organizational socialization and support from other customers—were found to have a positive impact on all forms of CEBs. This research helps managers of nursing homes and other services with a broad network of customers and stakeholders to improve existing CEB management practices and develop new CEB management practices that are beneficial for the firm and its stakeholders