• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.85-92
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• 2022

In this article, we look at the application of BIM (Building Information Modeling) in sustainable infrastructures. In response to global warming, energy shortages, and environmental degradation, people are trying to build eco-friendly, low-carbon cities and promote eco-friendly homes. A "green" building is the entire life cycle of a building that includes maximizing the conservation of resources (energy, water, land, and materials), protecting the environment, reducing pollution, providing people with healthy, comfortable, and efficient use of space, and establishing harmony between nature and architecture. In the field of ecological and sustainable buildings, BIM modeling can be integrated into buildings with analog energy, air flow analysis, and solar building ecosystems. Using BIM technologies, you can reduce the amount of waste and improve the quality of construction. These technologies create "visualization" of digital building models through multidimensional digital design solutions that provide" modeling and analysis "of Scientific Collaboration Platforms for designers, architects, utility engineers, developers, and even end users. Moreover, BIM helps them use three-dimensional digital models in project design and construction and operational management.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.1093-1100
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• 2018

Fast progress in miniaturization and reducing power consumption of semiconductors for wearable devices makes it possible to develop extremely small wearable systems for various application services. This results recent wearable applications to be powered from extremely low-power energy harvesters based on solar, piezo, and TENG sources. In most cases, the harvesters generate power in non-linear manner. Therefore, we implemented and experimented the device platforms to utilize natural frequency of around 3Hz. We also designed two-stage power storages and high efficiency conversion platform to consider such non-linear power harvesting sources. The experiment showed power generation of about 4.67mW/min from these non-linear sources with provision of stable energy storages.

• Applied Chemistry for Engineering
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• v.33 no.2
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• pp.126-132
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• 2022

Alkaline fuel cells using liquid fuels such as hydrazine and ammonia are gaining great attention as a clean and renewable energy solution possibly owing to advantages such as excellent energy density, simple structure, compact size in fuel container, and ease of storage and transportation. However, common shortcomings including cathode flooding, fuel crossover, side yield reactions, and fuel security and toxicity are still challenging issues. Real time monitoring of fuel concentrations integrated into a fuel cell device can help improving fuel cell performance via predicting any loss of fuels used at a cathode for efficient energy production. There have been extensive research efforts made on developing real-time sensing platforms for hydrazine and ammonia. Among these, recent advancements in electrochemical sensors offering high sensitivity and selectivity, easy fabrication, and fast monitoring capability for analysis of hydrazine and ammonia concentrations will be introduced. In particular, research trend on the integration of metallic and metal oxide nanoparticles and also their hybrids with carbon-based nanomaterials into electrochemical sensing platforms for improvement in sensitivity and selectivity will be highlighted.

• The Journal of the Acoustical Society of Korea
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• v.36 no.5
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• pp.293-299
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• 2017

Small unmanned platforms maneuvering underwater are the key naval future forces, utilized as the asymmetric power in war. As a method of detecting and identifying such platforms, we introduce a property estimation technique based on an iterative numerical analysis. The property estimation technique can estimate not only the position of a target but also its physical properties. Moreover, it will have a potential in detecting and classifying still target or multiple targets. In this study, we have conducted the property estimation of an small underwater target using the data acquired from the lake experiment. As a result, it shows that the properties of a small platform may be roughly estimated from the in site data even using one channel.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.3
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• pp.89-100
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• 2023

Recently, on-device artificial intelligence (AI) solutions using mobile devices and embedded edge devices have emerged in various fields, such as computer vision, to address network traffic burdens, low-energy operations, and security problems. Although vision transformer deep learning models have outperformed conventional convolutional neural network (CNN) models in computer vision, they require more computations and parameters than CNN models. Thus, they are not directly applicable to embedded edge devices with limited hardware resources. Many researchers have proposed various model compression methods or lightweight architectures for vision transformers; however, there are only a few studies evaluating the effects of model compression techniques of vision transformers on performance. Regarding this problem, this paper presents a performance evaluation of vision transformers on embedded platforms. We investigated the behaviors of three vision transformers: DeiT, LeViT, and MobileViT. Each model performance was evaluated by accuracy and inference time on edge devices using the ImageNet dataset. We assessed the effects of the quantization method applied to the models on latency enhancement and accuracy degradation by profiling the proportion of response time occupied by major operations. In addition, we evaluated the performance of each model on GPU and EdgeTPU-based edge devices. In our experimental results, LeViT showed the best performance in CPU-based edge devices, and DeiT-small showed the highest performance improvement in GPU-based edge devices. In addition, only MobileViT models showed performance improvement on EdgeTPU. Summarizing the analysis results through profiling, the degree of performance improvement of each vision transformer model was highly dependent on the proportion of parts that could be optimized in the target edge device. In summary, to apply vision transformers to on-device AI solutions, either proper operation composition and optimizations specific to target edge devices must be considered.

• Journal of Multimedia Information System
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• v.3 no.3
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• pp.63-68
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• 2016

Environmental downtime produces a significant cost to organizations and makes them unable to do business because what happens in the data center affects everyone. In addition, the amount of electrical energy consumed by data centers increases with the amount of computing power installed. Installation of physical Information Technology and facilities related to environmental concerns, such as monitoring temperature, humidity, power, flood, smoke, air flow, and room entry, is the most proactive way to reduce the unnecessary costs of expensive hardware replacement or unplanned downtime and decrease energy consumed by servers. In this paper, we present remote system for monitoring datacenter implementing using open-source hardware platforms; Arduino, Raspberry Pi, and the Gobetwino. The sensed data displayed through Arduino are transferred using Gobetwino to the nearest host server such as temperature, humidity and distance every time an object hitting another object or a person coming in entrance. The raspberry Pi records the sensed data at the remote location. The objective of collecting temperature and humidity data allows monitoring of the server's health and getting alerts if things start to go wrong. When the temperature hits $50^{\circ}C$, the supervisor at remote headquarters would get a SMS, and then they would take appropriate actions to reduce electrical costs and preserve functionality of servers in data centers.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.103.1-103.1
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• 2014

Due to their excellent optical and electrochemical properties, conjugated polymers have attracted much attention over the last two decades and employed to opto-electrical devices. In particular, conjugated polymers possess many attractive features that make them suitable for a variety of sensing task. For example, their delocalized electronic structures can be strongly modified by varying the surrounding environment, which significantly affected molecular energy level. In other word, conjugated polymers can detect and transduce the environmental information into a fluorescence signal. Conjugated polymers also display amplified quenching compared to small molecule counterparts. This amplified fluorescence quenching is attributed to the delocalization and migration of the excitons along the conjugated polymer backbones. Long backbones of conjugated polymer provide the transporting path for electron as a conduit, allowing that excitons migrate rapidly into quencher site along the backbone. This is often referred to as the molecular wire effect or antenna effect. Moreover, structures of conjugated polymers can be easily tailored to adjust solubility, absorption/emission properties, and regulation of electron/energy transfer. Based on this versatility, conjugated polymers have been utilized to many novel sensory platforms as a promising material. In this tutorial, I will highlight a variety of fluorescence sensors base on conjugated polymer and explain their sensory mechanism together with selected examples from reference literatures.

• The Journal of the Acoustical Society of Korea
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• v.32 no.2
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• pp.147-156
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• 2013

In this paper, a new speech endpoint detection method in noisy environments for moving robot platforms is proposed. In the conventional method, the endpoint of speech is obtained by applying an edge detection filter that finds abrupt changes in the feature domain. However, since the feature of the frame energy is unstable in such noisy environments, it is difficult to accurately find the endpoint of speech. Therefore, a novel feature extraction method based on the twice-iterated fast fourier transform (TIFFT) and statistical models of speech is proposed. The proposed feature extraction method was applied to an edge detection filter for effective detection of the endpoint of speech. Representative experiments claim that there was a substantial improvement over the conventional method.

• Journal of the Korea Society of Computer and Information
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• v.23 no.10
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• pp.1-9
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• 2018

Modern graphics processing units (GPUs) have become one of the most attractive platforms in exploiting high thread level parallelism with the support of new programming tools such as CUDA and OpenCL. Recent GPUs has applied cache hierarchy to support irregular memory access patterns; however, L1 data cache (L1D) exhibits poor efficiency in the GPU. This paper shows that the L1D does not always positively affect the applications in terms of performance and energy efficiency for the GPU. The performance of the GPU is even harmed by using the L1D for lots of applications. Our proposed technique exploits the characteristics of the currently-executed applications to predict the performance impact of the L1D on the GPU and then decides whether to continuously use the cache for the application or not. Our experimental results show that the proposed technique improves the GPU performance by 9.4% and saves up to 52.1% of the power consumption in the L1D.

• Journal of Life Science
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• v.21 no.1
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• pp.159-164
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• 2011

Microbial whole-cell biosensors can be excellent analytical tools for monitoring environmental pollutants. They are constructed by fusing reporter genes (e.g., lux, gfp or lacZ) to inducible regulatory genes which are responsive to the relevant pollutants, such as aromatic hydrocarbons and heavy metals. A large spectrum of microbial biosensors has been developed using recombinant DNA technology and applied in fields as diverse as environmental monitoring, medicine, food processing, agriculture, and defense. Furthermore, their sensitivity and target range could be improved by modification of regulatory genes. Recently, microbial biosensor cells have been immobilized on chips, optic fibers, and other platforms of high-throughput cell arrays. This paper reviews recent advances and future trends of genetically modified microbial biosensors used for monitoring of specific environmental pollutants.