• Title/Summary/Keyword: Heterogeneous Container Types

Search Result 4, Processing Time 0.016 seconds

The effect of soil heterogeneity and container length on the growth of Populus euramericana in a greenhouse study

  • Rahman, Afroja;Meng, Loth;Han, Si Ho;Seo, Gi Chun;Jung, Mun Ho;Park, Byung Bae
    • Korean Journal of Agricultural Science
    • /
    • v.45 no.2
    • /
    • pp.143-153
    • /
    • 2018
  • Soil characteristics along with various container lengths have an important role in the early survival rate and growth of seedlings by influencing the seedling quality. This experiment was conducted to investigate the effect of container length and different soil mixtures on the growth of poplar in a greenhouse. Two types of soil, homogeneous vs. heterogeneous, were used along with two container lengths (30 vs. 60 cm). The heterogeneous soil was made by dividing 50% vermiculite from a mixture of 25% vermicompost and 25% nursery soil in volume. For the homogeneous soil, the above three soil types were mixed together. Populus euramericana clone cuttings were planted in late April, and then, the growth height, root collar diameter (RCD) and biomass were measured in August. The height of the poplar was not significantly affected by container length and soil type, but the RCD was significantly affected by soil type. Leaf and root biomass was higher at the long container than at the short container for both soil treatments, but stem biomass was lower at the heterogeneous soil than at the homogeneous soil treatment. Root to shoot biomass ratio was higher at the heterogeneous soil treatment than at the homogeneous soil treatment by 12%. In conclusion, heterogeneous soil along with a long container is suitable to increase the carbon allocation into the root.

A Dynamic Lot-Sizing and Outbound Dispatching Problem with Delivery Time Windows and Heterogeneous Container Types (납품시간창과 다종의 컨테이너를 고려한 동적 로트크기결정 및 아웃바운드 디스패칭 문제)

  • Seo, Wonchul;Lee, Woon-Seek
    • Journal of Korean Institute of Industrial Engineers
    • /
    • v.40 no.4
    • /
    • pp.435-441
    • /
    • 2014
  • This paper considers a single-product problem for inbound lot-sizing and outbound dispatching at a third-party warehouse, where the demand is dynamic over the discrete time horizon. Each demand must be delivered into the corresponding delivery time window which is the time interval characterized by the earliest and latest delivery dates of the demand. Ordered products are shipped by heterogeneous container types. Each container type has type-dependent carrying capacity and the unit freight cost depends on each container type. Total freight cost is proportional to the number of each container type used. Also it is assumed that related cost functions are concave and backlogging is not allowed. The objective of the paper is to simultaneously determine the optimal inbound lot-sizing and outbound dispatching plans that minimize total costs which include ordering, shipping, and inventory holding costs. The optimal solution properties are characterized for the problem and then a dynamic programming algorithm is presented to find the optimal solution.

An Engine for DRA in Container Orchestration Using Machine Learning

  • Gun-Woo Kim;Seo-Yeon Gu;Seok-Jae Moon;Byung-Joon Park
    • International journal of advanced smart convergence
    • /
    • v.12 no.4
    • /
    • pp.126-133
    • /
    • 2023
  • Recent advancements in cloud service virtualization technologies have witnessed a shift from a Virtual Machine-centric approach to a container-centric paradigm, offering advantages such as faster deployment and enhanced portability. Container orchestration has emerged as a key technology for efficient management and scheduling of these containers. However, with the increasing complexity and diversity of heterogeneous workloads and service types, resource scheduling has become a challenging task. Various research endeavors are underway to address the challenges posed by diverse workloads and services. Yet, a systematic approach to container orchestration for effective cloud management has not been clearly defined. This paper proposes the DRA-Engine (Dynamic Resource Allocation Engine) for resource scheduling in container orchestration. The proposed engine comprises the Request Load Procedure, Required Resource Measurement Procedure, and Resource Provision Decision Procedure. Through these components, the DRA-Engine dynamically allocates resources according to the application's requirements, presenting a solution to the challenges of resource scheduling in container orchestration.

Encapsulation of SEED Algorithm in HCCL for Selective Encryption of Android Sensor Data (안드로이드 센서 정보의 선택적 암호화를 지원하는 HCCL 기반 SEED 암호의 캡슐화 기능 연구)

  • Kim, Hyung Jong;Ahn, Jae Yoon
    • Journal of the Korea Society for Simulation
    • /
    • v.29 no.2
    • /
    • pp.73-81
    • /
    • 2020
  • HCCL stands for Heterogenous Container Class Library. HCCL is a library that allows heterogeneous types of data to be stored in a container as a single record and to be constructed as a list of the records to be stored in database. With HCCL, encryption/decryption can be done based on the unified data type. Recently, IoT sensor which is embedded in smartphone enables developers to provide various convenient services to users. However, it is also true that infringement of personal information may occur in the process of transmitting sensor information to API and users need to be prepared for this situation in some sense. In this study, we developed a data model that enhances existing security using SEED cryptographic algorithms while managing information of sensors based on HCCL. Due to the fact that the Android environment does not provide permission management function for sensors, this study decided whether or not to encrypt sensor information based on the user's choice so that the user can determine the creation and storage of safe data. For verification of this work, we have presented the performance evaluation by comparing with the situation of storing the sensor data in plaintext.