Dongmahn Seo

Bio: Dongmahn Seo is an academic researcher from Catholic University of Daegu. The author has contributed to research in topics: Server & Quality of service. The author has an hindex of 8, co-authored 50 publications receiving 252 citations. Previous affiliations of Dongmahn Seo include Catholic University of Korea & The Catholic University of America.

Smart parking system for Internet of Things

Abstract: In this paper, we propose a smart parking system detecting and finding the parked location of a consumer's vehicle. Using ultrasonic and magnetic sensor, the proposed system detects vehicles in indoor and outdoor parking fields, accurately. Wireless sensor motes support a vehicle location service in parking lots using BLE.

Activation of NF-kappaB by HDAC inhibitor apicidin through Sp1-dependent de novo protein synthesis: its implication for resistance to apoptosis.

Abstract: Histone deacetylase (HDAC) inhibitors are promising anti-cancer drugs, but these exert differential responses depending on the cell types. Here, we demonstrate a new mechanism for activation of nuclear factor-kappaB (NF-kappaB) by HDAC inhibitor apicidin and the role of NF-kappaB signaling pathway for mediating differential cellular responses, especially, apoptosis. Treatment of HeLa cells with apicidin increases transcriptional activity of NF-kappaB and its target gene IL-8 and cIAP-1 induction, which involves the activation of IKK-IkappaBalpha signaling pathway through Sp1-dependent de novo protein synthesis. In parallel, apicidin treatment leads to histone hyperacetylation in the IL-8 promoter region independent of NF-kappaB signaling pathway, which is not sufficient for full transcription of IL-8 gene. This NF-kappaB activation contributes to resistance of HeLa cells to apoptotic potential of apicidin. Collectively, our results suggest that activation of NF-kappaB signaling cascade functions as a critical modulator to determine cell fate on apoptosis in response to HDAC inhibitors.

Detecting a pothole using deep convolutional neural network models for an adaptive shock observing in a vehicle driving

Abstract: A pothole is a one of the greatest threat to vehicle drives. It causes an accident by sudden steering of the vehicle wheel, forcing an enormous stress on a vehicle tire or making a hard turning in a vehicle by late detection. It is crucial to find where a pothole is on the pavement. As the number of pavement increases, detecting a pothole becomes a great challenge in a modern society. Several methods suggest detecting potholes using sensors. However, these methods require an installation on the vehicle in order to collect data of the pavement. Meanwhile, other methods are using smartphone sensors to reduce a cost of deployment and get an advantage of sensitive sensors without a complex installation on the vehicle. For this reason, a method using a smartphone camera with the artificial neural network becomes a way in detecting a pothole on a pavement. In this paper, we investigate the performance in detecting potholes with an image classification method based on the deep convolutional neural network models.

Detecting faulty solar panels based on thermal image processing

Abstract: Recently, the solar power generation has attracted much attention and market is growing. Although it is more common than in the past, there is not enough specialist for maintenance of the solar panel. Because solar panels are exposed to the outdoor environment, frequent failures can occur. So, we propose a solar panel detection system using the drones, the thermal cameras, and the RGB cameras. We used the characteristics of the fault of solar panel in the thermal camera, and detected the position of the photovoltaic panel and the array using the RGB camera.

Image processing-based pothole detecting system for driving environment

Abstract: The pothole is one of the significant factors for the motorist. It can cause a car accident, the decrease of car lifetime and a decrease of the motorist concentration. There are three kinds of the pothole detecting methods, such as using a 3-axis acceleration sensor, a camera sensor and, a laser sensor. All of three have the cons and pros. Our proposed system is based on an image processing method with the camera sensor. Detecting the potholes based on the potholes characteristic. The characteristics of the potholes are the dark region, the round shape and the rugged texture.

Data Fusion and IoT for Smart Ubiquitous Environments: A Survey

Abstract: The Internet of Things (IoT) is set to become one of the key technological developments of our times provided we are able to realize its full potential. The number of objects connected to IoT is expected to reach 50 billion by 2020 due to the massive influx of diverse objects emerging progressively. IoT, hence, is expected to be a major producer of big data. Sharing and collaboration of data and other resources would be the key for enabling sustainable ubiquitous environments, such as smart cities and societies. A timely fusion and analysis of big data, acquired from IoT and other sources, to enable highly efficient, reliable, and accurate decision making and management of ubiquitous environments would be a grand future challenge. Computational intelligence would play a key role in this challenge. A number of surveys exist on data fusion. However, these are mainly focused on specific application areas or classifications. The aim of this paper is to review literature on data fusion for IoT with a particular focus on mathematical methods (including probabilistic methods, artificial intelligence, and theory of belief) and specific IoT environments (distributed, heterogeneous, nonlinear, and object tracking environments). The opportunities and challenges for each of the mathematical methods and environments are given. Future developments, including emerging areas that would intrinsically benefit from data fusion and IoT, autonomous vehicles, deep learning for data fusion, and smart cities, are discussed.

The Cytoplasmic Deacetylase HDAC6 Is Required for Efficient Oncogenic Tumorigenesis

Abstract: Histone deacetylase inhibitors (HDACI) are promising antitumor agents. Although transcriptional deregulation is thought to be the main mechanism underlying their therapeutic effects, the exact mechanism and targets by which HDACIs achieve their antitumor effects remain poorly understood. It is not known whether any of the HDAC members support robust tumor growth. In this report, we show that HDAC6, a cytoplasmic-localized and cytoskeleton-associated deacetylase, is required for efficient oncogenic transformation and tumor formation. We found that HDAC6 expression is induced upon oncogenic Ras transformation. Fibroblasts deficient in HDAC6 are more resistant to both oncogenic Ras and ErbB2-dependent transformation, indicating a critical role for HDAC6 in oncogene-induced transformation. Supporting this hypothesis, inactivation of HDAC6 in several cancer cell lines reduces anchorage-independent growth and the ability to form tumors in mice. The loss of anchorage-independent growth is associated with increased anoikis and defects in AKT and extracellular signal-regulated kinase activation upon loss of adhesion. Lastly, HDAC6-null mice are more resistant to chemical carcinogen-induced skin tumors. Our results provide the first experimental evidence that a specific HDAC member is required for efficient oncogenic transformation and indicate that HDAC6 is an important component underlying the antitumor effects of HDACIs.

DNA damage-dependent NF-κB activation: NEMO turns nuclear signaling inside out.

Abstract: The dimeric transcription factor nuclear factor κB (NF-κB) functions broadly in coordinating cellular responses during inflammation and immune reactions, and its importance in the pathogenesis of cancer is increasingly recognized. Many of the signal transduction pathways that trigger activation of cytoplasmic NF-κB in response to a broad array of immune and inflammatory stimuli have been elaborated in great detail. NF-κB can also be activated by DNA damage, though relatively less is known about the signal transduction mechanisms that link DNA damage in the nucleus with activation of NF-κB in the cytoplasm. Here, we focus on the conserved signaling pathway that has emerged that promotes NF-κB activation following DNA damage. Post-translational modification of NF-κB essential modulator (NEMO) plays a central role in linking the cellular DNA damage response to NF-κB via the ataxia telangiectasia mutated (ATM) kinase. Accumulating evidence suggests that DNA damage-dependent NF-κB activation may play significant biological roles, particularly during lymphocyte differentiation and progression of human malignancies.

Subcellular-resolution delivery of a cytokine through precisely manipulated nanowires

Abstract: Precise delivery of molecular doses of biologically active chemicals to a pre-specified single cell among many, or a specific subcellular location, is still a largely unmet challenge hampering our understanding of cell biology. Overcoming this could allow unprecedented levels of cell manipulation and targeted intervention. Here, we show that gold nanowires conjugated with a cytokine such as tumour-necrosis factor-alpha can be transported along any prescribed trajectory or orientation using electrophoretic and dielectrophoretic forces to a specific location with subcellular resolution. The nanowire, 6 microm long and 300 nm in diameter, delivered the cytokine and activated canonical nuclear factor-kappaB signalling in a single cell. Combined computational modelling and experimentation indicated that cell stimulation was highly localized to the nanowire vicinity. This targeted delivery method has profound implications for controlling signalling events on the single cell level.