• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.1037-1042
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• 2018

The neuromorphic technology has been researched for decades, which learns and processes the information by imitating the human brain. The hardware implementations of neuromorphic systems are configured with highly parallel processing structures and a number of simple computational units. It can achieve high processing speed, low power consumption, and low hardware complexity. Recently, the interests of the neuromorphic technology for low power and small embedded systems have been increasing rapidly. To implement low-complexity hardware, it is necessary to reduce input data dimension without accuracy loss. This paper proposed a low-complexity artificial intelligent engine which consists of parallel neuron engines and a feature extractor. A artificial intelligent engine has a number of neuron engines and its controller to process multimodal sensor data. We verified the performance of the proposed neuron engine including the designed artificial intelligent engines, the feature extractor, and a Micro Controller Unit(MCU).

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.6
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• pp.383-390
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• 2019

A helideck is one of the essential structures in offshore platforms for the transportation of goods and operating personnel between land and offshore sites. As such, it should be carefully designed and installed for the safety of the offshore platform. In this study, a structural design optimization method for a lightweight offshore helideck is developed based on a genetic algorithm and an attainable design set concept. A helideck consists of several types of structural members such as plates, girders, stiffeners, trusses, and support elements, and the dimensions of these members are typically pre-defined by manufacturers. Therefore, design sets are defined by collecting the standard section data for these members from the American Institute of Steel Construction (AISC), and integer section labels are assigned as design variables in the genetic algorithm. The objective is to minimize the total weight of the offshore helideck while satisfying the maximum allowable stress criterion under various loading conditions including self-weight, wind direction, landing position, and landing condition. In addition, the unity check process is also utilized for additional verification of structural safety against buckling failure of the helideck.

• Journal of the Korean Chemical Society
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• v.68 no.3
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• pp.151-159
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• 2024

Indian spices are well known for their numerous health benefits, flavour, taste, and colour. Recent Advancements in chemical technology have led to better extraction and identification of bioactive molecules (phytochemicals) from spices. The therapeutic effects of spices against diabetes, cardiac problems, and various cancers has been well established. The present in silico study aims to investigate the binding affinity of 29 phytochemicals from 11 Indian spices with two prominent proteins, BCL3 and CXCL10 involved in invasiveness and bone metastasis of breast cancer. The three-dimensional structures of 29 phytochemicals were extracted from PubChem database. Protein Data Bank was used to retrieve the 3D structures of BCL3 and CXCL10 proteins. The drug-likeness and other properties of compounds were analysed by ADME and Lipinski rule of five (RO5). All computational simulations were carried out using Autodock 4.0 on Windows platform. The proteins were set to be rigid and compounds were kept free to rotate. In-silico study demonstrated a strong complex formation (positive binding constants and negative binding energy ΔG) between all phytochemicals and target proteins. However, piperine and sesamolin demonstrated high binding constants with BCL3 (50.681 × 10³ mol^-1, 137.76 × 10³ mol^-1) and CXCL10 (98.71 × 10³ mol^-1, 861.7 × 10³ mol^-1), respectively. The potential of these two phytochemicals as a drug candidate was highlighted by their binding energy of -6.5 kcal mol^-1, -7.1 kcal mol^-1 with BCL3 and -6.9 kcal mol^-1, -8.2 kcal mol^-1 with CXCL10, respectively coupled with their favourable drug likeliness and pharmacokinetics properties. These findings underscore the potential of piperine and sesamolin as drug candidates for inhibiting invasiveness and regulating breast cancer metastasis. However, further validation through in vitro and in vivo studies is necessary to confirm the in silico results and evaluate their clinical potential.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.21-31
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• 2017

In this paper, the Zynq system-on-chip (SoC) platform is used to design an adaptive noise reduction and edge-detection system using partial reconfiguration. Filters are implemented in a partially reconfigurable (PR) region to provide high computational complexity in real-time, 1080p video processing. In addition, partial reconfiguration enables better utilization of hardware resources in the embedded system from autonomous replacement of filters in the same PR region. The proposed edge-detection system performs adaptive noise reduction if the noise density level in the incoming video sequences exceeds a given threshold value. Results of implementation show that the proposed system improves the accuracy of edge-detection results (14~20 times in Pratt's Figure of Merit) through self-reconfiguration of filter bitstreams triggered by noise density level in the video sequences. In addition, the ZyCAP controller implemented in this paper enables about 2.1 times faster reconfiguration when compared to a PCAP controller.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.411-419
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• 2019

Nowadays we are not able to consider and imagine anything without taking into account what is called Artificial Intelligence. Even broadcasting media technologies could not be thought of outside this newly emerging technology of A.I.. Since the last part of 20th century, this technology seemingly is accelerating it's development thanks to an unbelievably enormous computational capacity of data information treatments. In conjunction with the firmly established worldwide platform companies like GAFA(Google, Amazon, Facebook, Apple), the key cutting edge technologies dubbed NBIC(Nanotech, Biotech, Information Technology, Cognitive science) converge to change the map of the current civilization by affecting the human relationship with the world and hence modifying what is essential in humans. Under the sign of the converging technologies, the relatively recently coined concepts such as 'trans(post)humanism' are emerging in the academic sphere in the North American and Major European regions. Even though the so-called trans(post)human movements are prevailing in the major technological spots, we have to say that these terms do not yet reach an unanimous acceptation among many experts coming from diverse fields. Indeed trans(post)humanism as a sort of obscure term has been a largely controversial trend. Because there have been many different opinions depending on scientific, philosophical, medical, engineering scholars like Peter Sloterdijk, K. N. Hayles, Neil Badington, Raymond Kurzweil, Hans Moravec, Laurent Alexandre, Gilbert Hottois just to name a few. However, considering the highly dazzling development of artificial intelligence technology basically functioning in conjunction with the cybernetic communication system firstly conceived by Nobert Wiener, MIT mathematician, we can not avoid questioning what A. I. signifies and how it will affect the current media communication environment.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.45-52
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• 2014

The Ubiquitous-City (U-City) is a smart or intelligent city to satisfy human beings' desire to enjoy IT services with any device, anytime, anywhere. It is a future city model based on Internet of everything or things (IoE or IoT). It includes a lot of video cameras which are networked together. The networked video cameras support a lot of U-City services as one of the main input data together with sensors. They generate huge amount of video information, real big data for the U-City all the time. It is usually required that the U-City manipulates the big data in real-time. And it is not easy at all. Also, many times, it is required that the accumulated video data are analyzed to detect an event or find a figure among them. It requires a lot of computational power and usually takes a lot of time. Currently we can find researches which try to reduce the processing time of the big video data. Cloud computing can be a good solution to address this matter. There are many cloud computing methodologies which can be used to address the matter. MapReduce is an interesting and attractive methodology for it. It has many advantages and is getting popularity in many areas. Video cameras evolve day by day so that the resolution improves sharply. It leads to the exponential growth of the produced data by the networked video cameras. We are coping with real big data when we have to deal with video image data which are produced by the good quality video cameras. A video surveillance system was not useful until we find the cloud computing. But it is now being widely spread in U-Cities since we find some useful methodologies. Video data are unstructured data thus it is not easy to find a good research result of analyzing the data with MapReduce. This paper presents an analyzing system for the video surveillance system, which is a cloud-computing based video data management system. It is easy to deploy, flexible and reliable. It consists of the video manager, the video monitors, the storage for the video images, the storage client and streaming IN component. The "video monitor" for the video images consists of "video translater" and "protocol manager". The "storage" contains MapReduce analyzer. All components were designed according to the functional requirement of video surveillance system. The "streaming IN" component receives the video data from the networked video cameras and delivers them to the "storage client". It also manages the bottleneck of the network to smooth the data stream. The "storage client" receives the video data from the "streaming IN" component and stores them to the storage. It also helps other components to access the storage. The "video monitor" component transfers the video data by smoothly streaming and manages the protocol. The "video translator" sub-component enables users to manage the resolution, the codec and the frame rate of the video image. The "protocol" sub-component manages the Real Time Streaming Protocol (RTSP) and Real Time Messaging Protocol (RTMP). We use Hadoop Distributed File System(HDFS) for the storage of cloud computing. Hadoop stores the data in HDFS and provides the platform that can process data with simple MapReduce programming model. We suggest our own methodology to analyze the video images using MapReduce in this paper. That is, the workflow of video analysis is presented and detailed explanation is given in this paper. The performance evaluation was experiment and we found that our proposed system worked well. The performance evaluation results are presented in this paper with analysis. With our cluster system, we used compressed $1920{\times}1080(FHD)$ resolution video data, H.264 codec and HDFS as video storage. We measured the processing time according to the number of frame per mapper. Tracing the optimal splitting size of input data and the processing time according to the number of node, we found the linearity of the system performance.