Earticle

The secure access the lighting, Heating, ventilation, and air conditioning (HVAC), fire safety, and security control boxes of building facilities is the primary objective of future smart buildings. This paper proposes an authorized user access to the electrical, lighting, fire safety, and security control boxes in the smart building, by using color grid coded optical camera communication (OCC) with face recognition Technologies. The existing CCTV subsystem can be used as the face recognition security subsystem for the proposed approach. At the same time a smart device attached camera can used as an OCC receiver of color grid code for user access authentication data sent by the control boxes to proceed authorization. This proposed approach allows increasing an authorization control reliability and highly secured authentication on accessing building facility infrastructure. The result of color grid code sequence received by the unauthorized person and his face identification allows getting good results in security and gaining effectiveness of accessing building facility infrastructure. The proposed concept uses the encoded user access authentication information through control box monitor and the smart device application which detect and decode the color grid coded informations combinations and then send user through the smart building network to building management system for authentication verification in combination with the facial features that gives a high protection level. The proposed concept is implemented on testbed model and experiment results verified for the secured user authentication in real-time.

Recently, there was an increasing demand for an integrated access control system which is capable of user recognition, door control, and facility operations control for smart buildings automation. The market available door lock access control solutions need to be improved from the current level security of door locks operations where security is compromised when a password or digital keys are exposed to the strangers. At present, the access control system solution providers focusing on developing an automatic access control system using (RF) based technologies like bluetooth, WiFi, etc. All the existing automatic door access control technologies required an additional hardware interface and always vulnerable security threads. This paper proposes the user identification and authentication solution for automatic door lock control operations using camera based visible light communication (VLC) technology. This proposed approach use the cameras installed in building facility, user smart devices and IoT open source controller based LED light sensors installed in buildings infrastructure. The building facility installed IoT LED light sensors transmit the authorized user and facility information color grid code and the smart device camera decode the user informations and verify with stored user information then indicate the authentication status to the user and send authentication acknowledgement to facility door lock integrated camera to control the door lock operations. The camera based VLC receiver uses the artificial intelligence (AI) methods to decode VLC data to improve the VLC performance. This paper implements the testbed model using IoT open-source based LED light sensor with CCTV camera and user smartphone devices. The experiment results are verified with custom made convolutional neural network (CNN) based AI techniques for VLC deciding method on smart devices and PC based CCTV monitoring solutions. The archived experiment results confirm that proposed door access control solution is effective and robust for automatic door access control.

The objectives of this study were to compare unimanual, symmetrical and reciprocal movement of transportation. Nineteen participants with post-stroke hemiparesis were involved in this study. We used the Fitmeter accelerometer to measure the dependent variables: signal vector magnitude, peak acceleration and peak deceleration. With respect to the hand and arm, intensity of unimanual movement was higher than that of symmetrical movement, and reciprocal movement was greater than that of symmetrical movement. With regard to the trunk, intensity of unimanual movement was lower than that of symmetrical movement, and within bimanual movement, reciprocal movement was greater than that of symmetrical movement. In conclusion, reciprocal movement would facilitate upper extremity movement and decrease the compensatory movement of trunk more than would symmetrical movement.

This paper presents an effective single image haze removal using edge-preserving and adaptive transmission estimation to enhance the visibility of outdoor images vulnerable to weather and environmental conditions with computational complexity reduction. The conventional methods involve the time-consuming refinement process. The proposed transmission estimation however does not require the refinement, since it preserves the edges effectively, which selects one between the pixel-based dark channel and the patch-based dark channel in the vicinity of edges. Moreover, we propose an adaptive transmission estimation to improve the visual quality particularly in bright areas like sky. Experimental results with various hazy images represent that the proposed method is superior to the conventional methods in both subjective visual quality and computational complexity. The proposed method can be adopted to compose a haze removal module for realtime devices such as mobile devices, digital cameras, autonomous vehicles, and so on as well as PCs that have enough processing resources.

We demonstrated a successful fabrication of 4 ” Gallium Nitride (GaN)/Diamond High Electron Mobility Transistors (HEMTs) incorporated with Inner Slot Via Hole process. We made in manufacturing technology of 4” GaN/Diamond HEMT wafers in a compound semiconductor foundry since reported [1]. Wafer thickness uniformity and wafer flatness of starting GaN/Diamond wafers have improved greatly, which contributed to improved processing yield. By optimizing Laser drilling techniques, we successfully demonstrated a through-substrate-via process, which is last hurdle in GaN/Diamond manufacturing technology. To fully exploit Diamond’s superior thermal property for GaN HEMT devices, we include Aluminum Nitride (AlN) barrier in epitaxial layer structure, in addition to conventional Aluminum Gallium Nitride (AlGaN) barrier layer. The current collapse revealed very stable up to Vds = 90 V. The trapping behaviors were measured Emission Microscope (EMMI). The traps are located in interface between Silicon Nitride (SiN) passivation layer and GaN cap layer.

The fifth generation (5G) mobile communication has been commercialized and the 5G applications, such as the artificial intelligence (AI) and the internet of things (IoT), are deployed all over the world. The 5G new radio (NR) wireless networks are characterized by 100 times more traffic, 1000 times higher system capacity, and 1 ms latency. One of the promising 5G technologies is non-orthogonal multiple access (NOMA). In order for the NOMA performance to be improved, sometimes the additive signal-dependent Gaussian noise (ASDGN) channel model is required. However, the channel capacity calculation of such channels is so difficult, that only lower and upper bounds on the capacity of ASDGN channels have been presented. Such difficulties are due to the specific constraints on the dependency. Herein, we provide the capacity of ASDGN channels, by removing the constraints except the dependency. Then we obtain the ASDGN channel capacity, not lower and upper bounds, so that the clear impact of ASDGN can be clarified, compared to additive white Gaussian noise (AWGN). It is shown that the ASDGN channel capacity is greater than the AWGN channel capacity, for the high signal-to-noise ratio (SNR). We also apply the analytical results to the NOMA scheme to verify the superiority of ASDGN channels.

A Language model with neural networks commonly trained with likelihood loss. Such that the model can learn the sequence of human text. State-of-the-art results achieved in various language generation tasks, e.g., text summarization, dialogue response generation, and text generation, by utilizing the language model’s next token output probabilities. Monotonous and boring outputs are a well-known problem of this model, yet only a few solutions proposed to address this problem. Several decoding techniques proposed to suppress repetitive tokens. Unlikelihood training approached this problem by penalizing candidate tokens probabilities if the tokens already seen in previous steps. While the method successfully showed a less repetitive generated token, the method has a large memory consumption because of the training need a big vocabulary size. We effectively reduced memory footprint by encoding words as sequences of subword units. Finally, we report competitive results with token level unlikelihood training in several automatic evaluations compared to the previous work.

With the emergence of the words Personal Mobility (P.M.) or Smart Mobility (S.M.), which are terms for personal transportation, the activities of related technologies are increasing with the research. Personal transportation is basically used as a short distance transportation method using electrical energy. As personal mobility became more popular, the resulting products and studies are spreading throughout the country. Most of the electric scooters, which are personal vehicles, are mostly imported from China. This is due to the fact that the price competitiveness of major components of electric scooters is owned in China. At this point, the domestic research direction is considered to be desirable in terms of composition and design of the electric scooter body. In this study, the models of portable electric scooters according to the number of wheels mounted on portable electric scooters were presented and the prototypes were produced accordingly. The number of wheels applied to the electric scooter was 2 and 3 and 4; the contents and advantages and disadvantages of the proposed portable electric scooter models were reviewed.

The domestic sleep industry is rapidly increasing in market size as it is linked to sleep apnea in the longterm care insurance for the elderly and domestic IT technology. In addition, due to the aging society, the government's support policy is also increasing, and many domestic companies are focusing on the sleep industry. Therefore, this study intends to examine the development strategies of the domestic sleep industry due to the increased social interest and corporate activities. To this end, a survey of 108 domestic companies was conducted by means of a Frequency Analysis, revealing some problems, such as poor sleep companies, insufficient resources for technology development, and limitations in distribution channels. As a result, it was found that for the development of the domestic sleep industry, strategies to strengthen the ecosystem, such as softening strategies through the sleep technology culture, strengthening ecosystems such as revitalizing industrial connections, and reforming laws and regulations, are urgent.

We The 4th industrial revolution, the core characteristics of super-intelligence, hyper-connective, and ultrareality, has been actualized. New technologies such as artificial intelligence, big data, the Internet of Things, and high-tech video have begun to be applied to media and advertising. With the introduction of new technologies in the advertising field, innovative changes in advertising types, advertising effects, advertising methods, and advertising contents are expected. Accordingly, We intends to design a future advertising roadmap development by predicting how future advertising will change and develop through future technologies in the 4th industrial revolution era. To design the roadmap, this study analyzes changes in advertising technology, consumer, and media as changes in the advertising environment in the 4th industrial revolution era, and identifies the core changing trends, advertising factors in future advertising through the Delphi Survey on experts in advertising and future fields. We identifies how the future advertising technology, types, media, effects, and fields are developed by the changes of future advertising environments, including technology, consumers, and media in the 4th industrial revolution era. Hence it is expected to help the advertising industry and experts to prepare for future changes.

IoT devices frequently require input resources to communicate with various sensors or IoT platforms. IoT device wastes a lot of time as idle time or waiting time to check the data of the input resource and use the input resource. In addition, IoT devices use various input resources. We compares and analyzes input idle time and input waiting time generated from hardware serial input resource, software serial input resource, digital port input resource, and analog port input resource using Arduino widely used as IoT device. In order to design the IoT device framework, it is necessary to understand the characteristics of input resources and to design them to minimize unnecessary input idle time and input waiting time. The analog input wait time has a much larger input wait time than the digital input wait time, so it must be designed to receive analog information periodically at the appropriate timing. The characteristics of the input resources analyzed in this way help to design an efficient IoT device.

A microstrip feedline based open ended folded-slot antenna is proposed for ultra-wideband (UWB) applications. The prototype of the proposed antenna is fabricated on the FR4 dielectric substrate. The proposed antenna has a wide n-shaped slot that is useful for designing circuit components on the same printed circuit board (PCB) as that of the radio frequency (RF) modules. The proposed antenna use two kinds of slots as radiators, and each slots have different characteristics because of the different type of ends of the slot. The wideband characteristic can be obtained by resonances of each slot which are occurred at different frequencies. The measured impedance bandwidth (S11≤ -10 dB) is 2.9–11.56 GHz, and the antenna peak gain is 2–4 dBi over the UWB range. The antenna has a stable omni-directional radiation pattern and only a small groupdelay variation across the UWB passband. In addition, we present a modified design with band-notched characteristics of a 5 GHz wireless local area network (WLAN) frequency band.

Recently, with the growth of mixed reality industrial infrastructure, relevant convergence research has been proposed. For real-time mixed reality services such as remote video conferencing, the research on real-time acquisition-process-transfer methods is required. This paper aims to implement an AR remote rendering method of volumetric 3D video data. We have proposed and implemented two modules; one, the parsing module of the volumetric 3D video to a game engine, and two, the server rendering module. The result of the experiment showed that the volumetric 3D video sequence data of about 15 MB was compressed by 6-7%. The remote module was streamed at 27 fps at a 1200 by 1200 resolution. The results of this paper are expected to be applied to an AR cloud service.

There is a strong connection between the diet rich in antioxidants and the decreased incidence of inflammatory bowel disease and cancerous diseases. Diets that are rich in anti-oxidants particularly include fruits and vegetables containing the high amounts of vitamin A-E, carotenoids, and minerals. The supercritical heat-treated radish extracts of the research result had an inhibitory effect on the development of aberrant crypt foci (ACF), namely, preneoplastic lesions having a potential to become cancer cells and reduced the number of the aberrant crypt foci (ACF) consisting of four or more aberrant crypts (AC) having high risk to become tumors by about half. The supercritical heat-treated radish extracts can reduce the incidence of preneoplastic lesions having a high risk of developing cancer by about 28 %. DSS-treated mice developed symptoms similar to those of human UC, such as severe bloody diarrhea and weight loss. Supercritical heat-treated radish extracts, as well as sulfasalazine, suppressed colonic length and mucosal inflammatory infiltration. In addition, supercritical heat-treated radish extracts treatment significantly reduced the expression of pro-inflammatory signaling molecules through suppression both mitogen-activated protein kinases (MAPK) and nuclear factorkappa B (NF-kB) signaling pathways, and prevented the apoptosis of colon. Moreover, supercritical heattreated radish extracts administration significantly led to the up-regulation of anti-oxidant enzyme including SOD and Catalase.

Numerous tourist-related data produced on the Internet contain not only simple tourist information but also diverse ideas and opinions from users. In order to derive meaningful information about tourist sites from such big data, the social network analysis of tourist keywords can identify the frequency of keywords and the relationship between keywords. Thus, it is possible to make recommendations more suitable for users by utilizing the clear recommendation criteria of tourist attractions and the relationship between tourist attractions. In this paper, a recommendation system was designed based on tourist site information through big data social network analysis. Based on user personality information, the types of tourism suitable for users are classified through deep learning and the network analysis among tourist keywords is conducted to identify the relationship between tourist attractions belonging to the type of tourism. Tour information for related tourist attractions shown on SNS and blogs will be recommended through tagging.

Studies are being conducted regarding falling recognition using sensors on smartphones to recognize falling in human daily life. These studies use a number of sensors, mostly acceleration sensors, gyro sensors, motion sensors, etc. Falling recognition system processes the values of sensor data by using a falling recognition algorithm and classifies behavior based on thresholds. If the threshold is ambiguous, the accuracy will be reduced. To solve this problem, Deep learning was introduced in the behavioral recognition system. Deep learning is a kind of machine learning technique that computers process and categorize input data rather than processing it by man-made algorithms. Thus, in this paper, we propose a falling recognition application system using deep learning based on smartphones. The proposed system is powered by apps on smartphones. It also consists of three layers and uses DataBase as a Service (DBaaS) to handle big data and address data heterogeneity. The proposed system uses deep learning to recognize the user's behavior, it can expect higher accuracy compared to the system in the general rule base.

This paper presents an environment for rule-based English-Korean machine translation system, which supports the translation domain adaptation and the continuous translation quality improvement. For the purposes, corpus is essential, from which necessary information for translation will be acquired. The environment consists of a corpus construction part and a translation knowledge extraction part. The corpus construction part crawls news articles from some newspaper sites. The extraction part builds the translation knowledge such as newly-created words, compound words, collocation information, distributional word representations, and so on. For the translation domain adaption, the corpus for the domain should be built and the translation knowledge should be constructed from the corpus. For the continuous improvement, corpus needs to be continuously expanded and the translation knowledge should be enhanced from the expanded corpus. The proposed web-based environment is expected to facilitate the tasks of domain adaptation and translation system improvement.

The purpose of this study is to analyze the structural relationship among advertising attribute, advertising attitude, product attitude and purchase intention in YouTube advertising. The survey subjects to achieve the purpose of this study were selected the group of 300 students who have been watching YouTube VOD once more and are attending in three universities that are located in Seoul, Gyeonggi and Chungnam. Data processing was done with SPSS 23 for frequency analysis, Cronbach's α analysis. Also, AMOS 18 was used for confirmatory factor analysis and structural equation model analysis. information, irrtation and individuality affect viewers' advertisement attitude, their product attitude and purchasing intent, among advertisement attributes of e-sports items perceived by viewers of YouTube's e-sports videos with the insertion of advertisements that cannot be skipped in the middle of the video.Therefore, the similarity between the video and the advertised product or brand should be taken into account when producing advertisements inserted in the YouTube video, and a more positive advertising effect can be achieved when advertisement can be carried out reflecting the characteristics of the target viewers.

A database called Home Location Register(HLR) plays a major role in location management in mobile cellular networks. The objectives of this paper are to identify the problems of the current HLR system through rigorous analysis, to suggest solutions to them. The current HLR backup method is a process of simply writing the changed memory SLD block to disk, which has a problem in maintaining database consistency. Since information change and backup are performed separately by separate processes, there is a risk of information inconsistency when an error restart occurs. To solve this problem, a transaction concept was introduced for subscriber-related operation functions and a recovery method through logging and checkpointing was introduced. The subscriber related functions of tasks terminated normally by the suggested process are recovered with consistency even after system restarts. Performance is also not affected seriously because disk tasks for log occur with only subscriber related functions.