• Journal of the Korea Safety Management & Science
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• v.8 no.3
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• pp.115-123
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• 2006

The main focus of this study is to investigate the performance of a clark-scarf type multi-echelon serial supply chain operating with a base-stock policy and to optimize the inventory levels in the supply chains so as to minimize the systemwide total inventory cost, comprising holding and backorder costs as all the nodes in the supply chain. The source of supply of raw materials to the most upstream node, namely supplier, is assumed to have an infinite raw material availability. Retailer faces random customer demand, which is assumed to be stationary and normally distributed. If the demand exceeds on-hand inventory, the excess demand is backlogged. Using the echelon stock and demand quantile concepts and an efficient simulation technique, we derive near optimal inventory policy. Additionally we discuss the derived results through the extensive experiments for different supply chain settings.

• Journal of the Korea Safety Management & Science
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• v.9 no.2
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• pp.215-233
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• 2007

Even though the ad hoc Shewhart methods remain controversial due to various mathematical flaws, there is little disagreement among researchers and practitioners when a set of process data has a skewness distribution. In the context and language of process control, the error related to the process data shows that time to signal increases when a control parameter shifts to a skewness direction. In real-world industrial settings, however, quality practitioners often need to consider a skewness distribution. To address this situation, we developed an enhanced design method to utilize advantages of the traditional attribute control chart and to overcome its associated shortcomings. The proposed design method minimizes bias, i.e., an average time to signal for the shift of process from the target value (ATS) curve, as well as it applies a variable sampling interval (VSI) method to an attribute control chart for detecting a process shift efficiently. The results of the factorial experiment obtained by various parameter circumstances show that the VSI c control chart using nearly unbiased ATS design provides the smallest decreasing rate in ATS among other charts for all experimental cases.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.2
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• pp.79-86
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• 2019

For decades, in-memory data structures have been designed for DRAM-based main memory that provides symmetric read/write performances and has no limited write endurance. However, such data structures provide sub-optimal performance for NVM as it has different characteristics to DRAM. With this motivation, we rethink a conventional red-black tree in terms of its efficacy under NVM settings. The original red-black tree constantly rebalances sub-trees so as to export fast access time over dataset, but it inevitably increases the write traffic, adversely affecting the performance for NVM with a long write latency and limited endurance. To resolve this problem, we present a variant of the red-black tree called a hierarchical balanced binary search tree. The proposed structure maintains multiple keys in a single node so as to amortize the rebalancing cost. The performance study reveals that the proposed hierarchical binary search tree effectively reduces the write traffic by effectively reaping the high capacity of NVM.

• New & Renewable Energy
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• v.19 no.3
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• pp.13-21
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• 2023

Smart windows are capable of varying their visible light transmittance (VLT) in response to changing environmental conditions. The VLT variability of architectural windows is highly valuable because it enables indoor lighting and energy environments to align with external changes. However, challenges such as high installation costs and assurance of glass visibility have prompted the exploration of alternative solutions, including models incorporating partially applied smart windows., Prior research focused on useful daylight illuminance (UDI) analysis for south-facing office buildings, pointing out suitable areas for smart-window implementation to enhance lighting control. In this study, we broadened this scope by determining optimal smart-window application zones under changing building orientation. Furthermore, we studied the correlation between building orientation and smart-window deployment areas.

• Journal of Digestive Cancer Research
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• v.2 no.1
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• pp.15-20
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• 2014

Cancer, especially GI cancer itself and any associated treatments have profound effect on the patient's nutritional status. It is therefore very important to understand various nutritional issues in GI cancer patients for the cure and for increasing the compliance during the course of the treatment. Screening and identification of nutritional risk for the GI cancer patients is very essential and is plays a critical part of the treatment to help improve patient outcomes. Maintaining optimal nutritional status is an important goal in the management of individuals diagnosed, treated with cancer. Maintenance of adequate nutritional intake is important whether patients are undergoing active therapy, recovering from cancer therapy, or are in remission and striving to avoid cancer recurrence. The goals of nutrition therapy are to prevent or reverse nutrient deficiencies, preserve lean body mass, help patients better tolerate treatments and minimize nutrition-related side effects and complications, etc. Recent interest in clinical settings is also in maximizing quality of life of the patients which can also be modulated by appropriate nutrition.

• Journal of Digestive Cancer Research
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• v.6 no.2
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• pp.50-54
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• 2018

The incidence of gastric cancer has steadily declined and the overall mortality rate from gastric cancer has similarly decreased. However, compared to other malignancies, the quality of life and life expectancy remain relatively poor in patients with gastric cancer. For gastric cancers, surgical resection is the main treatment, but the optimal therapeutic strategy for locally advanced gastric cancer remains undefined. For many patients with gastric cancer, not only chemotherapy but also radiotherapy plays a crucial role in both the curative and palliative settings. In this article, we review the evidence for the different treatment paradigms with a particular focus on the role of radiotherapy.

• Journal of Digestive Cancer Research
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• v.2 no.2
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• pp.52-55
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• 2014

The incidence of colorectal cancer (CRC) has continuously increased and CRC is a major cause of cancer-related death. Systemic chemotherapy has resulted in a significant improvement in overall survival in metastatic CRC. The development of biologic agents for the treatment of CRC has additionally expanded the options for the treatment. Cetuximab is useful in KRAS wild type tumors in combination with chemotherapy for metastatic disease in both the first and second line settings. It is also used as monotherapy after failure of both irinotecan and oxaliplatin containing regimens. Panitumumab has similar indications, and is primarily used in patients intolerant to cetuximab due to hypersensitivity reactions. Bevacizumab is primarily used as first line and second line therapy in metastatic CRC. However, the optimal way and duration to combine these chemotherapeutic agents are not yet established.

• Advances in aircraft and spacecraft science
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• v.10 no.6
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• pp.545-554
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• 2023

The widespread introduction of unmanned aircrafts has led to the understanding of the need to organize a common information space for manned and unmanned aircrafts, which is reflected in the Russian Unmanned aircraft system Traffic Management (RUTM) project. The present article deals with the issues of spatial information database (DB) organization, which is the core of RUTM and provides storage of various data types (spatial, aeronautical, topographical, meteorological, vector, etc.) required for flight safety management. Based on the analysis of functional capabilities and types of work which it needs to ensure, the architecture of spatial information DB, including the base of source information, base of display settings, base of vector objects, base of tile packages and also a number of special software packages was proposed. The issues of organization of these DB, types and formats of data and ways of their display are considered in detail. Based on the analysis it was concluded that the optimal construction of the spatial DB for RUTM system requires a combination of different model variants and ways of organizing data structures.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.16-24
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• 2024

With an increase in the relevance of next-generation integrated networking environments, the need to effectively utilize advanced networking techniques also increases. Specifically, integrating Software-Defined Networking (SDN) with Multi-access Edge Computing (MEC) is critical for enhancing network flexibility and addressing challenges such as security vulnerabilities and complex network management. SDN enhances operational flexibility by separating the control and data planes, introducing management complexities. This paper proposes a reinforcement learning-based network path optimization strategy within SDN environments to maximize performance, minimize latency, and optimize resource usage in MEC settings. The proposed Enhanced Proximal Policy Optimization (PPO)-based scheme effectively selects optimal routing paths in dynamic conditions, reducing average delay times to about 60 ms and lowering energy consumption. As the proposed method outperforms conventional schemes, it poses significant practical applications.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.80-87
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• 2024

This paper focuses on improving accuracy in constrained computing settings by employing the ReLU (Rectified Linear Unit) activation function. The research conducted involves modifying parameters of the ReLU function and comparing performance in terms of accuracy and computational time. This paper specifically focuses on optimizing ReLU in the context of a Multilayer Perceptron (MLP) by determining the ideal values for features such as the dimensions of the linear layers and the learning rate (Ir). In order to optimize performance, the paper experiments with adjusting parameters like the size dimensions of linear layers and Ir values to induce the best performance outcomes. The experimental results show that using ReLU alone yielded the highest accuracy of 96.7% when the dimension sizes were 30 - 10 and the Ir value was 1. When combining ReLU with the Adam optimizer, the optimal model configuration had dimension sizes of 60 - 40 - 10, and an Ir value of 0.001, which resulted in the highest accuracy of 97.07%.