Boundary Setting for Ecosystem Services by Factor Analysis: A Case Study in Seocheon, South Korea

Ecosystem service assessment maps are an important form of data, showing the flow and characteristics of ecosystem services. However, there has been a lack of research on the spatial boundaries of synergetic and trade-off relationships among different types of ecosystem services based on the microscopic characteristics of ecosystem maps. Therefore, the boundaries of ecosystems were identified in this study using factor analysis of indicators in ecosystem service maps. Ecosystems were mapped for each indicator in each cell, and then factor analysis was used to combine all indicators into one map. Analysis of Seocheon in central South Korea shows the boundaries of two ecosystem types: a mountainous region with abundant underground water and carbon stocks that lack rice paddies, and flatlands with high crop production and a lack of scenic views. The spatial types of ecosystems in which synergy and trade-offs occur were identified by indicator, and these can be used as evidentiary material for spatial planning in order to maximize the function of each ecosystem service

OF@TEIN: An OpenFlow-enabled SDN Testbed over International SmartX Rack Sites

In this paper, we will discuss our on-going effort for OF@TEIN SDN(Software-Defined Networking) testbed, which currently spans over Korea and fiveSouth-East Asian (SEA) collaborators with internationally deployed OpenFlowenabledSmartX Racks

Finding Shortest Vector Using Quantum NV Sieve on Grover

Quantum computers, especially those with over 10,000 qubits, pose a potential threat to current public key cryptography systems like RSA and ECC due to Shor\u27s algorithms. Grover\u27s search algorithm is another quantum algorithm that could significantly impact current cryptography, offering a quantum advantage in searching unsorted data. Therefore, with the advancement of quantum computers, it is crucial to analyze potential quantum threats. While many works focus on Grover’s attacks in symmetric key cryptography, there has been no research on the practical implementation of the quantum approach for lattice-based cryptography. Currently, only theoretical analyses involve the application of Grover\u27s search to various Sieve algorithms. In this work, for the first time, we present a quantum NV Sieve implementation to solve SVP, posing a threat to lattice-based cryptography. Additionally, we implement the extended version of the quantum NV Sieve (i.e., the dimension and rank of the lattice vector). Our extended implementation could be instrumental in extending the upper limit of SVP (currently, determining the upper limit of SVP is a vital factor). Lastly, we estimate the quantum resources required for each specific implementation and the application of Grover\u27s search. In conclusion, our research lays the groundwork for the quantum NV Sieve to challenge lattice-based cryptography. In the future, we aim to conduct various experiments concerning the extended implementation and Grover\u27s search

A Next-Generation Cryogenic Processor Architecture

Cryogenic computing can achieve high performance and power efficiency by dramatically reducing the device's leakage power and wire resistance at low temperatures. Recent advances in cryogenic computing focus on developing cryogenic-optimal cache and memory devices to overcome memory capacity, latency, and power walls. However, little research has been conducted to develop a cryogenic-optimal core architecture even with its high potentials in performance, power, and area efficiency. In this article, we first develop CryoCore-Model, a cryogenic processor modeling framework that can accurately estimate the maximum clock frequency of processor models running at 77 K. Next, driven by the modeling tool, we design CryoCore, a 77 K-optimal core microarchitecture to maximize the core's performance and area efficiency while minimizing the cooling cost. The proposed cryogenic processor architecture, in this article, achieves the large performance improvement and power reduction and, thus, contributes to the future of high-performance and power-efficient computer systems.N

Cryogenic Computer Architecture Modeling with Memory-Side Case Studies

Modern computer architectures suffer from lack of architectural innovations, mainly due to the power wall and the memory wall. That is, architectural innovations become infeasible because they can prohibitively increase power consumption and their performance impacts are eventually bounded by slow memory accesses. To address the challenges, making computer systems run at ultra-low temperatures (or cryogenic computer systems) has emerged as a highly promising solution as both power consumption and wire resistivity are expected to significantly reduce at ultra-low temperatures. However, cryogenic computers have not been yet realized as computer architects do not fully understand the behaviors of existing computer systems and their cost effectiveness at such ultra-low temperatures. In this paper, we first develop CryoRAM, a validated computer architecture simulation tool to incorporate cryogenic memory devices. For this work, we focus on 77K temperature (easily achieved by applying low-cost liquid nitrogen), at which modern CMOS devices still reliably operate. We also focus on reducing the temperature of memory devices only as a pilot study prior to building a full cryogenic computer. Next, driven by the modeling tool, we propose our temperature-aware memory device and architecture designs to improve the DRAM access speed by 3.8 times or reduce the power consumption to 9.2%. Finally, we provide three promising case studies using cryogenic memories to significantly improve (1) server performance (up to 2.5 times), (2) server power (down to 6% on average), and (3) datacenter's power cost (by 8.4%). We will release our modeling and simulation tools deliberately implemented on top of only open-source simulators combined, even though some experiments were conducted under industry-confidential environments.N

Screening of Plant Extracts for Nemastatic Activity

against Rhabditis sp. by 96-well microplate bioassay. The plant extracts with a concentration of 5,000 μg/ml were mixed with aqueous nematode solution containing about 20 Rhabditis sp. and their activity was examined daily for 7 days. Out of 2,714 plant extracts examined in this test, 2,362 (87.0%) showed no negative influence on the nematode activity, while 187 (6.9%) inhibited nematode activity about 50%, 95 (3.5%) inhibited nematode activity over 90%, and 70 (2.6%) rather enhanced nematode activity. Among those showing over 50% nemastatic activity, 25 extracts were randomly selected for further screening with Rhabditis sp. and with juveniles of Meloidogyne incognita. The screening revealed that 11 extracts (44%) were consistently

Driving Forces in Archetypical Land-Use Changes in a Mountainous Watershed in East Asia

Identifying patterns and drivers of regional land use changes is crucial for supporting land management and planning. Doing so for mountain ecosystems in East Asia, such as the So-yang River Basin in South Korea, has until now been a challenge because of extreme social and ecological complexities. Applying the techniques of geographic information systems (GIS) and statistical modeling via multinomial logistic regression (MNL), we attempted to examine various hypothesized drivers of land use changes, over the period 1980 to 2000. The hypothesized drivers included variables of topography, accessibility, spatial zoning policies and neighboring land use. Before the inferential statistic analyses, we identified the optimal neighborhood extents for each land use type. The two archetypical sub-periods, i.e., 1980–1990 with agricultural expansions and 1990–2000 with reforestation, have similar causal drivers, such as topographic factors, which are related to characteristics of mountainous areas, neighborhood land use, and spatial zoning policies, of land use changes. Since the statistical models robustly capture the mutual effects of biophysical heterogeneity, neighborhood characteristics and spatial zoning regulation on long-term land use changes, they are valuable for developing coupled models of social-ecological systems to simulate land use and dependent ecosystem services, and to support sustainable land management