• Journal of Powder Materials
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• v.25 no.3
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• pp.263-272
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• 2018

Recent developments in the field of energy harvesting technology that convert ambient energy resources into electricity enable the use of self-powered energy systems in wearable and portable electronic devices without the need for additional external power sources. In particular, piezoelectric-effect-based flexible energy harvesters have drawn much attention because they can guarantee power generation from ubiquitous mechanical and vibrational movements. In response to demand for sustainable, permanent, and remote use of real-life personal electronics, many research groups have investigated flexible piezoelectric energy harvesters (f-PEHs) that employ nanoscaled piezoelectric materials such as nanowires, nanoparticles, nanofibers, and nanotubes. In those attempts, they have proven the feasibility of energy harvesting from tiny periodic mechanical deformations and energy utilization of f-PEH in commercial electronic devices. This review paper provides a brief overview of f-PEH devices based on piezoelectric nanomaterials and summarizes the development history, output performance, and applications.

• Journal of information and communication convergence engineering
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• v.14 no.2
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• pp.97-105
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• 2016

With the increasing demand for interoperability among existing learning resource systems in order to enable the sharing of learning resources, such resources need to be annotated with ontologies that use different metadata standards. These different ontologies must be reconciled through ontology mediation, so as to cope with information heterogeneity problems, such as semantic and structural conflicts. In this paper, we propose an ontology-mapping technique using Semantic Web Rule Language (SWRL) to generate semantic mapping rules that integrate learning resources from different systems and that cope with semantic and structural conflicts. Reasoning rules are defined to support a semantic search for heterogeneous learning resources, which are deduced by rule-based inference. Experimental results demonstrate that the proposed approach enables the integration of learning resources originating from multiple sources and helps users to search across heterogeneous learning resource systems.

• Journal of Korean Society of Transportation
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• v.12 no.4
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• pp.99-118
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• 1994

This study is designed to evaluate the effectiveness of TDM as a peak-period trip reduction strategy. This effort uses as a case study, the implementation of Regulation XV (REGXV) in Southern California, the most ambitious and far reaching employer-based ridesharing program implemented to date. This study explores the program effectiveness in terms of three aspects ; employee travel behavior changes after implementating Regulation XV, TDM programs offered by employers subjects to Regulation XV, and causal relationship between employee travel behavior changes and employer-based TDM programs. The study finds that Regualtion XV has a small, but statistically significant positive impact on AVR change. Popular incentives used by employers are less costly and easy to implement rather than to be effective. The increase in AVR is associated with increases of carpools promoted by strong incentives such as monetary subsides. A large number of indirect incentive programs are not effective. The study concludes that employers need to invest heavily on strong incentives, rather than on proposing diverse incentives, to comply with REGXV.

• The Korean Journal of Financial Studies
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• v.3 no.2
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• pp.267-279
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• 1996

The prediction of future demand is a vital task in managing business operations. To this end, traditional approaches often focused on statistical techniques such as exponential smoothing and moving average. The need for better accuracy has led to nonlinear techniques such as neural networks and case based reasoning. In addition, experimental design techniques such as orthogonal arrays may be used to assist in the formulation of an effective methodology. This paper investigates a multistrategy approach involving neural nets, case based reasoning, and orthogonal arrays. Neural nets and case based reasoning are employed both separately and in combination, while orthoarrays are used to determine the best architecture for each approach. The comparative evaluation is performed in the context of an application relating to the prediction of Treasury notes.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.1
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• pp.48-54
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• 2011

As personal or compact devices with image acquisition functionality are becoming easily available for common users, the voluminous images that need to be managed by image related services or systems demand efficient and effective methods in the perspective of image identification. The objective of image identification is to associate an image with a unique identifier. Moreover, whenever an image identifier needs to be regenerated, the newly generated identifier should be consistent. In this paper, we propose three image identifier generation methods utilizing image features: linear component, luminance area, and combination of both features. The linear component based method exploits the information of distribution of partial lines over an image, while the luminance area based method utilizes the partition of an image into a number of small areas according to the same luminance degree. The third method is proposed in order to take advantage of both former methods. In this paper, we also demonstrate the experimental evaluations for uniqueness and similarity analysis that have shown favorable results.

• Journal of Conservation Science
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• v.37 no.1
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• pp.25-33
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• 2021

To extend the application of digital technology to the replication of artifacts, meticulous details of the process and the diversity of three-dimensional (3D) printing output materials need to be supplemented. Thus, in this study, a bronze mirror with Hwangbichangcheon inscription was digitalized by 3D scanning, converted into a voxel model, and virtual conservation treatment was performed using a haptic device. Furthermore, the digital mold of the bronze mirror completed by Boolean modeling was printed using a 3D sand-printer. Such contactless replication based on digital technology reflects the stability, precision, expressivity, collectivity, durability, and economic feasibility of artifacts. Its application can be further extended to cultural products as well as such areas as education, exhibition, and research. It is expected to be in high demand for metal artifacts that require casting. If empirical studies through experimental research on casting are supplemented in the future, it could extend the application of digital technology-based contactless replication methods.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.9-18
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• 2021

Blockchain and its infrastructure technology have expanded rapidly in the last decade and are in high demand, but there is a lack of comprehensive studies on those platforms. Blockchain is a new technology based on the distributed digital ledger system. Decentralized trust is one of the key factors behind the blockchain-based system. Transparency of such a system is better than a conventional centralized ledger system. By using a blockchain-based transaction system, any business organization can harness key benefits like data integrity, confidentiality, and anonymity without involving any third party in control of the transactions. Since the blockchain is used in numerous applications and the horizon is expanding at an unprecedented pace. So, there is a need for an introducing and reviewing of blockchain platforms. In this paper, we have reported a review on existing contemporary blockchain platforms. In particular, From the existing studies, we have identified eighty blockchain platforms and the majority of them have a lack of technical details. To provide the researchers a comprehensive introducing on blockchain platforms to perform a broad guideline for future research and investment in the blockchain domain.

• Journal of KIBIM
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• v.12 no.4
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• pp.52-60
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• 2022

Recently, the demand for connection between various heterogeneous dataset and BIM as a construction data model hub is increasing. In the past, in order to connect model between BIM and heterogeneous dataset, related dataset was stored in the RDBMS, and the service was provided by programming a method to link with the BIM object. This approach causes problems such as the need to modify the database schema and business logic, and the migration of existing data when requirements change. This problem adversely affects the scalability, reusability, and maintainability of model information. This study proposes an ontology BIM-based knowledge service framework considering the connectivity and scalability between BIM and heterogeneous dataset. Through the proposed framework, ontology BIM mapping, semantic information query method for linking between knowledge-expressing dataset and BIM are presented. In addition, to identify the effectiveness of the proposed method, the prototype is developed. Also, the effectiveness and considerations of the ontology BIM-based knowledge service framework are derived.

• Health Policy and Management
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• v.33 no.2
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• pp.115-117
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• 2023

The issue of increasing the number of physicians is emerging. Because the physician workforce is a critical component of the health care system, and substantial costs are involved in training personnel, a cautious approach is required. The demand to increase the number of physicians is based on the contention that there are difficulties in accessing essential health services and the need to prepare for future demands such as fostering physician-scientists. However, simply increasing the number of physicians is not an appropriate approach to address these demands, especially considering that the effects of such an increase will appear 10 years later. Moreover, it is concerned that the current argument for increasing the physician workforce is intertwined with political interests. When considering the impact on the health care system, decisions regarding the expansion of the physician workforce should be based on evidence. Additionally, rather than temporarily responding to social issues, it is expected that a governance system will be established to continuously discuss and decide on fostering medical personnel.

• Journal of Electrochemical Science and Technology
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• v.15 no.1
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• pp.14-31
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• 2024

The text highlights the growing need for eco-friendly energy storage and the potential of metal-organic frameworks (MOFs) to address this demand. Despite their promise, challenges in MOF-based energy storage include stability, reproducible synthesis, cost-effectiveness, and scalability. Recent progress in supercapacitor materials, particularly over the last decade, has aimed to overcome these challenges. The review focuses on the morphological characteristics and synthesis methods of MOFs used in supercapacitors to achieve improved electrochemical performance. Various types of MOFs, including monometallic, binary, and tri-metallic compositions, as well as derivatives like hybrid nanostructures, sulfides, phosphides, and carbon composites, are explored for their energy storage potential. The review emphasizes the quest for superior electrochemical performance and stability with MOF-based materials. By analyzing recent research, the review underscores the potential of MOF-based supercapacitors to meet the increasing demands for high power and energy density solutions in the field of energy storage.