• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.670-674
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• 2018

Social network service (SNS) related data including comments/text, images, videos, blogs, and user experiences contain a wealth of information which can be used to build recommendation systems for various clients' and provide insightful data/results to business analysts. Multimedia data, especially visual data like image and videos are the richest source of SNS data which can reflect particular region, and cultures values/interests, form a gigantic portion of the overall data. Mining such huge amounts of data for extracting actionable intelligence require efficient and smart data analysis methods. The purpose of this paper is to focus on this particular modality for devising ways to model, index, and retrieve data as and when desired.

• Transactions of Materials Processing
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• v.31 no.3
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• pp.136-142
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• 2022

The purpose of this study was to investigate the effects of sample thickness and support structure on the residual stress of Hastelloy X superalloy samples fabricated by laser powder bed fusion (LPBF), which is an additive manufacturing process. The residual stresses of LPBF samples with different thicknesses and support structures were measured using X-ray diffraction. The results revealed that as the thickness of sample increased from 2.5 mm to 20 mm, its tensile residual stress gradually decreased from 443.5 MPa to 182.2 MPa. Additionally, the residual stress in the bottom region of sample was higher than that in the top region, and the residual stress difference in the bottom and top regions became more pronounced as the sample thickness decreased. The residual stress of LPBF sample also varied depending on the structure of support. The residual stress of sample decreased with increasing contract area between the sample and the support, because the larger contract area led to smaller temperature gradient throughout the sample.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.171-184
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• 2022

The purpose of this paper is output oriented, in order to maximize the output level of sustainable development efficiency of foreign trade in western China with limited input. This paper adopts the relevant input-output indicators of sustainable foreign trade development of 11 provinces and cities in western China from 2016 to 2020, and uses DEA model to measure their technical efficiency, pure technical efficiency and scale efficiency. Malmquist index was used to calculate the total factor productivity change index of each province in western China from 2016 to 2020. We found that, on the whole, the average values of technical efficiency, pure technical efficiency and scale efficiency of provinces and cities in western China from 2016 to 2020 are greater than 0.8, indicating that the western region has high technical efficiency, relatively high management and institutional level and high existing scale level. Scale efficiency is lower than pure technical efficiency on the whole, indicating that the current sustainable development efficiency of foreign trade in western China is mainly limited by its scale level. The technological progress index is higher than the technological efficiency change index, indicating that the total factor productivity of the sustainable development of foreign trade in western China is mainly driven by technological progress and more influenced by external factors. We think the conclusion of this study can provide important reference information for the sustainable development of foreign trade of provinces and cities in western China.

• Smart Structures and Systems
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• v.32 no.1
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• pp.49-59
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• 2023

A bridge transportation network supplies products from various source nodes to destination nodes through bridge structures in a target region. However, recent frequent earthquakes have caused damage to bridge structures, resulting in extreme direct damage to the target area as well as indirect damage to other lifeline structures. Therefore, in this study, a surrogate model-based comprehensive framework to estimate the seismic resilience of bridge transportation networks is proposed. For this purpose, total system travel time (TSTT) is introduced for accurate performance indicator of the bridge transportation network, and an artificial neural network (ANN)-based surrogate model is constructed to reduce traffic analysis time for high-dimensional TSTT computation. The proposed framework includes procedures for constructing an ANN-based surrogate model to accelerate network performance computation, as well as conventional procedures such as direct Monte Carlo simulation (MCS) calculation and bridge restoration calculation. To demonstrate the proposed framework, Pohang bridge transportation network is reconstructed based on geographic information system (GIS) data, and an ANN model is constructed with the damage states of the transportation network and TSTT using the representative earthquake epicenter in the target area. For obtaining the seismic resilience curve of the Pohang region, five epicenters are considered, with earthquake magnitudes 6.0 to 8.0, and the direct and indirect damages of the bridge transportation network are evaluated. Thus, it is concluded that the proposed surrogate model-based framework can efficiently evaluate the seismic resilience of a high-dimensional bridge transportation network, and also it can be used for decision-making to minimize damage.

• Korean Journal of Agricultural Science
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• v.50 no.3
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• pp.399-406
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• 2023

In this study, we propose a ripe tomato bunch localization method based on convolutional neural networks, to be applied in robotic harvesting systems. Tomato images were obtained from a smart greenhouse at the Rural Development Administration (RDA). The sample images for training were extracted based on tomato maturity and resized to 128 × 128 pixels for use in the classification model. The model was constructed based on four-layer convolutional neural networks, and the classes were determined based on stage of maturity, using a Softmax classifier. The localization of the ripe tomato bunch region was indicated on a class activation map. The class activation map could show the approximate location of the tomato bunch but tends to present a local part or a large part of the ripe tomato bunch region, which could lead to poor performance. Therefore, we suggest a recursive method to improve the performance of the model. The classification results indicated that the accuracy, precision, recall, and F1-score were 0.98, 0.87, 0.98, and 0.92, respectively. The localization performance was 0.52, estimated by the Intersection over Union (IoU), and through input recursion, the IoU was improved by 13%. Based on the results, the proposed localization of the ripe tomato bunch area can be incorporated in robotic harvesting systems to establish the optimal harvesting paths.

• Journal of Appropriate Technology
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• v.6 no.2
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• pp.136-145
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• 2020

Agriculture is the backbone of the economy of most developing countries. In these countries, agriculture or farming is mostly done manually with little integration of machinery, intelligent systems and data monitoring. Irrigation is an essential process that directly influences crop production. The fluctuating amount of rainfall per year has led to the adoption of irrigation systems in most farms. The absence of smart sensors, monitoring methods and control, has led to low harvests and draining water sources. In this research paper, we introduce a 433 MHz Radio Frequency and 2G based Smart Irrigation Meter System and a water prepayment system for rural areas of Tanzania with no reliable internet coverage. Specifically, Ngurudoto area in Arusha region where it will be used as a case study for data collection. The proposed system is hybrid, comprising of both weather data (evapotranspiration) and soil moisture data. The architecture of the system has on-site weather measurement controllers, soil moisture sensors buried on the ground, water flow sensors, a solenoid valve, and a prepayment system. To achieve high precision in linear and nonlinear regression and to improve classification and prediction, this work cascades a Dynamic Regression Algorithm and Naïve Bayes algorithm.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.2
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• pp.13-19
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• 2017

This paper analyzed MODIS data from 2006 to 2013 to determine relationship between meteorological changes and vegetation index. The experimental area was divided into the northern, central and southern regions according to the regional characteristics, and the smoothed MODIS LAI and NDVI were obtained using Timesat. In the case of precipitation, MODIS NDVI had correlation coefficients of 0.66, 0.44 and 0.35 in the northern, central and southern regions and the correlation was the highest in the northern region. In the case of temperature, MODIS LAI had correlation coefficients of 0.66, 0.64 and 0.68, and MODIS NDVI had 0.89, 0.89 and 0.80. The correlation of MODIS NDVI was higher and showed similar positive correlation regardless of region. In addition, The accuracy between Timesat plant seasonal start and actual plant seasonal start in MODIS NDVI was higher than MODIS LAI. The average error in MODIS LAI was 19 days in the central region and 20 days in the southern region. And the average error in MODIS NDVI was 6 days in the central region and 8 days in the southern region.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.2
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• pp.97-105
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• 2016

Microcontrollers (MCUs) for endpoint smart sensor devices of internet-of-thing (IoT) are being implemented as system-on-chip (SoC) with on-chip instruction flash memory, in which user firmware is embedded. MCUs directly fetch binary code-based instructions through bit-line sense amplifier (S/A) integrated with on-chip flash memory. The S/A compares bit cell current with reference current to identify which data are programmed. The S/A in reading '0' (erased) cell data consumes a large sink current, which is greater than off-current for '1' (programmed) cell data. The main motivation of our approach is to reduce the number of accesses of erased cells by binary code level transformation. This paper proposes a built-in write/read path architecture using binary code inversion method based on hot-spot region detection of instruction code access to reduce sensing current in S/A. From the profiling result of instruction access patterns, hot-spot region of an original compiled binary code is conditionally inverted with the proposed bit-inversion techniques. The de-inversion hardware only consumes small logic current instead of analog sink current in S/A and it is integrated with the conventional S/A to restore original binary instructions. The proposed techniques are applied to the fully-custom designed MCU with ARM Cortex-M0$^{TM}$ using 0.18um Magnachip Flash-embedded CMOS process and the benefits in terms of power consumption reduction are evaluated for Dhrystone$^{TM}$ benchmark. The profiling environment of instruction code executions is implemented by extending commercial ARM KEIL$^{TM}$ MDK (MCU Development Kit) with our custom-designed access analyzer.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.9-14
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• 2019

In modern society drones are actively utilized in the fields of security, defense, agriculture, communication and so on. Smart technology and artificial intelligence software have been developed with convergence, and the field of use is expected to expand further. On the point of the excellent performance of drones one of the essential technologies is the wireless communication that make the ground facility receive the video streaming obtained by the drones in the air. In the research the concept of communication region is proposed to cover the both the low altitude region for Wi-Fi communication and the high altitude region for LTE communication for the sake of video transmission. Also the hybrid communication structure is designed along the proposed concept and the proposed system is implemented as a communication system in the small size which can be mounted in a small size of drone. It is confirmed that the proposed system contains the effectiveness by showing the ability to successfully transmit HD video streaming in the range of 500 meters and the transfer time between two different communication systems is measured in 200msec by the experiments.

• Smart Structures and Systems
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• v.15 no.1
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• pp.99-117
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• 2015

The Stonecutters Bridge (SCB) in Hong Kong is the third-longest cable-stayed bridge in the world with a main span stretching 1,018 m between two 298 m high single-leg tapering composite towers. A Wind and Structural Health Monitoring System (WASHMS) is being implemented on SCB by the Highways Department of The Hong Kong SAR Government, and the SCB-WASHMS is composed of more than 1,300 sensors in 15 types. In order to establish a linkage between structural health monitoring and maintenance management, a Structural Health Rating System (SHRS) with relevant rating tools and indices is devised. On the basis of a 3D space frame finite element model (FEM) of SCB and model updating, this paper presents the development of an SHR-oriented 3D multi-scale FEM for the purpose of load-resistance analysis and damage evaluation in structural element level, including modeling, refinement and validation of the multi-scale FEM. The refined 3D structural segments at deck and towers are established in critical segment positions corresponding to maximum cable forces. The components in the critical segment region are modeled as a full 3D FEM and fitted into the 3D space frame FEM. The boundary conditions between beam and shell elements are performed conforming to equivalent stiffness, effective mass and compatibility of deformation. The 3D multi-scale FEM is verified by the in-situ measured dynamic characteristics and static response. A good agreement between the FEM and measurement results indicates that the 3D multi-scale FEM is precise and efficient for WASHMS and SHRS of SCB. In addition, stress distribution and concentration of the critical segments in the 3D multi-scale FEM under temperature loads, static wind loads and equivalent seismic loads are investigated. Stress concentration elements under equivalent seismic loads exist in the anchor zone in steel/concrete beam and the anchor plate edge in steel anchor box of the towers.