• Computers and Concrete
• /
• v.7 no.1
• /
• pp.53-62
• /
• 2010

Dredged silt from reservoirs in southern Taiwan was sintered to make lightweight aggregates (LWA), which were then used to produce high-performance lightweight aggregate concrete (HPLWC). The HPLWC was manufactured using different amounts of mixing water (140, 150, and 160 $kg/m^3$) and LWA of different particle densities (700, 1100, and 1500 $kg/m^3$) at different W/b ratios (0.28, 0.32, and 0.4). Results show that the lightweight aggregates of dredged silt taken in southern Taiwan perform better than the general lightweight aggregates. In addition, the HPLWC possessed high workability with a slump of 230-270 mm, and a slump flow of 450-610 mm, high compressive strength of over 40 MPa after 28 days of curing, good strength efficiency of cement exceeding $0.1MPa/kg/m^3$, low thermal conductivity of 0.4-0.8 $kcal/mh^{\circ}C$, shrinkage of less than $4.8{\times}10^{-4}$, and high electrical resistivity of above 40 $k{\Omega}-cm$. The above findings prove that HPLWC made from dredged silt can help enhance durability of concrete and provide and an ecological alternative use of dredged silt.

• Journal of Information Technology Services
• /
• v.8 no.1
• /
• pp.203-215
• /
• 2009

This paper illustrates the application of co-occurrence theory to generate lightweight ontologies semi-automatically. The proposed model includes three steps of a (Semi-) Automatic creation of Ontology; (they are conceptually named as) the Syntactic-based Ontology, the Semantic-based Ontology and the Ontology Refinement. Each of these three steps are designed to interactively work together, so as to generate Lightweight Ontologies. The Syntactic-based Ontology step includes generating Association words using co-occurrence in web documents. The Semantic-based Ontology step includes the Alignment large Association words with small Ontology, through the process of semantic relations by contextual terms. Finally, the Ontology Refinement step includes the domain expert to refine the lightweight Ontologies. We also conducted a case study to generate lightweight ontologies in specific domains(news domain). In this paper, we found two directions including (1) employment co-occurrence theory to generate Syntactic-based Ontology automatically and (2) Alignment large Association words with small Ontology to generate lightweight ontologies semi-automatically. So far as the design and the generation of big Ontology is concerned, the proposed research will offer useful implications to the researchers and practitioners so as to improve the research level to the commercial use.

• Structural Engineering and Mechanics
• /
• v.87 no.3
• /
• pp.221-229
• /
• 2023

Urbanization and industrialization have significantly increased the amount of solid waste produced in recent decades, posing considerable disposal problems and environmental burdens. The practice of waste utilization in concrete has gained popularity among construction practitioners and researchers for the efficient use of resources and the transition to the circular economy in construction. This study employed Lytag aggregate, an environmentally friendly pulverized fuel ash-based lightweight aggregate, as a substitute for natural coarse aggregate. At the same time, fly ash, an industrial by-product, was used as a partial substitute for cement. Concrete mix M20 was experimented with using fly ash and Lytag lightweight aggregate. The percentages of fly ash that make up the replacements were 5%, 10%, 15%, 20%, and 25%. The Compressive Strength (CS), Split Tensile Strength (STS), and deflection were discovered at these percentages after 56 days of testing. The concrete cube, cylinder, and beam specimens were examined in the explorations, as mentioned earlier. The results indicate that a 10% substitution of cement with fly ash and a replacement of coarse aggregate with Lytag lightweight aggregate produced concrete that performed well in terms of mechanical properties and deflection. The cementitious composites have varying characteristics as the environment changes. Therefore, understanding their mechanical properties are crucial for safety reasons. CS, STS, and deflection are the essential property of concrete. Machine learning (ML) approaches have been necessary to predict the CS of concrete. The Artificial Fish Swarm Optimization (AFSO), Particle Swarm Optimization (PSO), and Harmony Search (HS) algorithms were investigated for the prediction of outcomes. This work deftly explains the tremendous AFSO technique, which achieves the precise ideal values of the weights in the model to crown the mathematical modeling technique. This has been proved by the minimum, maximum, and sample median, and the first and third quartiles were used as the basis for a boxplot through the standardized method of showing the dataset. It graphically displays the quantitative value distribution of a field. The correlation matrix and confidence interval were represented graphically using the corrupt method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.8
• /
• pp.3224-3242
• /
• 2020

Internet of Things (IoT) networks composed of a large number of sensors and actuators generate a huge volume of data and control commands, which should be enforced by strong data reliability. The end-to-end data reliability of IoT networks is an essential industrial enabler. Blockchain technology can provide strong data reliability and integrity within IoT networks. We designed a lightweight end-to-end blockchain network that applies to common IoT applications. Its enhanced modular architecture and lightweight consensus mechanism guarantee its practical applicability for general IoT applications. In addition, the proposed blockchain network is highly software compatible because it adopts the Hyperledger development environment. Directly embedding the proposed blockchain middleware platform in small computing devices proves its practicability.

• Journal of the Korean Crystal Growth and Crystal Technology
• /
• v.20 no.4
• /
• pp.185-191
• /
• 2010

To effectively utilize resources of reject ash and dredged soil, globular shape-formed artificial lightweight aggregate were manufactured in 8~10 mm size. Starting materials were changed various grading and composition, sintered at $1050{\sim}1250^{\circ}C$. The specific gravity, water absorptance of artificial lightweight aggregates were measured on the basis of the KS. In this study could make a prediction about application of bloating mechanism by ferrous materials and alkali/alkali-earth oxide at high temperature.

• Journal of Ocean Engineering and Technology
• /
• v.26 no.2
• /
• pp.39-47
• /
• 2012

The objective of this study was to develop a strength prediction model using a polynomial regression analysis based on the experimental results obtained from ninety samples. As the results of a correlation analysis between various mixing factors and unconfined compressive strength using SPSS (statistical package for the social sciences), the governing factors in the strength of lightweight soil were found to be the crumb rubber content, bottom ash content,and water-cement ratio. After selecting the governing factors affecting the strength through the correlation analysis, a strength prediction model, which consisted of the selected governing factors, was developed using the polynomial regression analysis. The strengths calculated from the proposed model were similar to those resulting from laboratory tests (R2=87.5%). Therefore, the proposed model can be used to predict the strength of lightweight mixtures with various mixing ratios without time-consuming experimental tests.

• Journal of Sensor Science and Technology
• /
• v.30 no.1
• /
• pp.15-19
• /
• 2021

Image processing is one of the major techniques that are used for computer vision. Nowadays, researchers are using machine learning and deep learning for the aforementioned task. In recent years, digit recognition tasks, i.e., automatic meter recognition approach using electric or water meters, have been studied several times. However, two major issues arise when we talk about previous studies: first, the use of the deep learning technique, which includes a large number of parameters that increase the computational cost and consume more power; and second, recent studies are limited to the detection of digits and not storing or providing detected digits to a database or mobile applications. This paper proposes a system that can detect the digital number of meter readings using a lightweight deep neural network (DNN) for low power consumption and send those digits to an Android mobile application in real-time to store them and make life easy. The proposed lightweight DNN is computationally inexpensive and exhibits accuracy similar to those of conventional DNNs.

• Journal of Electrochemical Science and Technology
• /
• v.14 no.2
• /
• pp.120-130
• /
• 2023

PEMFC has high potential for future development due to its high energy density, eco-friendliness, and high energy efficiency. When it becomes small, light and flexible, it can be competitive as an energy source for portable devices or flexible electronic devices. However, the use of hard and heavy materials for structural rigidity and uniform contact pressure transmission has become an obstacle to reducing the weight and flexibility of PEMFCs. This review intends to provide an example of the application of a new structure and material for lightweight and flexibility. As a lightweight PEMFC, a tubular design is presented and structural advantages through numerical modeling are explained. Manufacturing methods to realize the structural advantages and possibilities of tubular PEMFCs are discussed. In addition, the materials and manufacturing processes used to fabricate lightweight and flexible PEMFCs are described and factors affecting performance are analyzed. Strategies and structural improvements of light and flexible movements are discussed according to the component parts.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.4
• /
• pp.888-894
• /
• 2015

This paper describes an efficient hardware design of Lightweight Encryption Algorithm (LEA) developed by National Security Research Institute(NSRI). The LEA crypto-processor supports for master key of 128-bit. To achieve small-area and low-power implementation, an efficient hardware sharing is employed, which shares hardware resources for encryption and decryption in round transformation block and key scheduler. The designed LEA crypto-processor was verified by FPGA implementation. The LEA core synthesized with Xilinx ISE has 1,498 slice elements, and the estimated throughput is 216.24 Mbps with 135.15 MHz.

• Journal of Welding and Joining
• /
• v.33 no.3
• /
• pp.12-18
• /
• 2015

The ultimate goal of developing body is revealed the "lightweight" at latest EuroCarBody conference 2012 and the most core technology is joining process to make lightweight car body design. Accordingly, in this study, the car body assembly line for the assembly process applies to any introduction, particularly in the assembly of aluminum alloy and composite materials applied by the process for the introductory approached. Process were largely classified by welding (laser, arc, resistance, and friction stir welding), bonding (epoxy bonding) and mechanical fastening (FDS, SPR, Bolting and clinching). Applications for each process issues in the case and the applicable award was presented, based on the absolute strength of the test specimens and joining characteristics for comparative analysis were summarized. Finally, through this paper, we would tried to establish the characteristics of the joint for lightweight structure.