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Recently, a large number of cryptocurrencies and block chains have been continuously released. However, these cryptocurrencies and block chains are open to users without authorized verification and testing procedures, causing various reliability problems. Existing cryptocurrencies and blockchain test methods build a blockchain Testnet for a certain period of time by the developer without external verification by a third party, and after repeatedly self-testing and self-operating processes, commercialization is in progress by switching to the Mainnet. This self-verification method does not guarantee objectivity and publicness, and high reliability of customers cannot be realized. This study proposes a cryptocurrency and blockchain test interface and test control system as a third-party open test method.

Since High Sierra, APFS has been used as the main file system. It is a well-established file system that has been used stably thus far. From the perspective of digital forensics, there are still many areas to be investigated. Apple File System Reference is provided to the apple developer site, but it is not satisfactory to fully analyze APFS. Researchers know more about the structure of APFS than before, but they have not yet fully analyzed its structure to a perfect level about it. In this paper, we develop APFS object identification tool for digital forensics. The most basic and essential object identification and analysis of the APFS filesystem will be conducted with the tool. The analysis in this study serves as the background for an analysis of the checkpoint operation principle and structure, including the more complex B-tree structure of APFS. There are several options for the developed tool, but the results of two use cases will be shown here. Based on the implemented tool, it is hoped that more functions will be added to make APFS a useful tool for faster and more accurate analyses.

“Know thyself” is one of the most famous ancient proverbs. We need to know ourselves to understand others and find true ourselves. Enneagram is one of the tools we can use to do it. It has drawn more and more attention from people by its effectiveness and spiritual depth. It has been widely promoted in both business management and spirituality contexts. It has many concepts to be understood. Holy ideas and virtues are understood to be restored to find our true self which is the purpose of using the Enneagram. Actually, holy ideas and virtues are similar with character qualities which comprise character. In this paper, holy ideas and virtues are matched with corresponding character qualities. To promote transformative process of character development through Enneagram, an app was designed. It has 2 levels. Level 1 is to find personality type and show corresponding character qualities of 9 personality types to users. Level 2 is to find subtypes and Enneagram Levels of Development for further purpose.

Since Tim Berners-Lee introduced the idea of the web to the world in the late 1980s, the way information is produced, accessed and used has been constantly changing. This was once again an era of upheaval after Apple's Steve Jobs introduced the smartphone to the world in the mid-2000s. Before the advent of smart devices, web browsing was mainly done using desktops. After the advent of this device, the era of solving almost all human needs with a small PC in the palm of your hand has arrived. The necessity of seamless connectivity between devices, which are constantly emerging and evolving, asks our attention more than ever. In this study, we will discuss a case of design and development of a national open access website, which is optimized for dynamic online user behaviors with diverse devices. Our goal is to provide one true web for people to use in their environment. Device makers need to provide products identical to the desktop environment as much as possible. Service providers should also provide services optimized for each device in hyper-connected environments. Providing a web, optimized for user’s online context, will eventually result in a sustainable user experience.

Interval caching is one of the representative caching strategies used in multimedia streaming systems. However, there has been no theoretical analysis on interval caching. In this paper, we present an optimality proof of the interval caching policy. Specifically, we propose a caching performance model for multimedia streaming systems and show the optimality of the interval caching policy based on this model.

With recent scientific advances and growing interest in AI technologies, AI-based chatbots have been viewed as a practical learning aid for English language development. The purpose of this study is to examine preservice teachers' perceptions on the potential benefits of employing AI chatbots in English instruction and its pedagogical aspects. 28 preservice teachers majoring in English education were asked to use Kuki chatbots for a week with a guidance of a researcher and then report on their perceptions of AI chatbots in terms of perceived usefulness after use, applicability, and educational benefits and drawbacks. Emerging codes and themes were identified and evaluated using Thematic Analysis(TA) based on qualitative data from surveys and interviews. The findings show that six emerging themes were identified, encompassing perspectives on teacher, learner, communication, linguistic, affective, and assessment. The overall findings of this study revealed that AI-based chatbots can play a significant role as learning tools for stimulating interactive communication in a target language. Most preservice primary teachers acknowledge that AI chatbots can be useful as teaching and learning aids for both teachers and students. Furthermore, when applying various learner data to chatbot technology, such as learner assessment and diagnosis, a guided approach is necessary to perform a conversation appropriate for the learner's level and characteristics. Finally, as chatbots have a variety of benefits in terms of affective aspects, they may improve EFL learners' confidence in speaking English and learning motivation.

In the paper, we propose a TSCH-based scheduling scheme for IEEE 802.15.4e, which is able to perform the scheduling of its own network by avoiding collision from interference network cluster (INC). Firstly, we model a bipartite graph structure for presenting the slot-frame (channel-slot assignment) of TSCH. Then, based on the bipartite graph edge weight, we utilize the Hungarian assignment algorithm to implement a scheduling scheme. We have employed two features (maximization and minimization) of the Hungarian-based assignment algorithm, which can perform the assignment in terms of minimizing the throughput of INC and maximizing the throughput of own network. Further, in this work, we called the scheme “dual-stage Hungarian-based assignment algorithm”. Furthermore, we also propose deep learning (DL) based deep neural network (DNN) scheme, where the data were generated by the dual-stage Hungarian-based assignment algorithm. The performance of the DNN scheme is evaluated by simulations. The simulation results prove that the proposed DNN scheme provides similar performance to the dual-stage Hungarian-based assignment algorithm while providing a low execution time.

The advent of location-based social networks (LBSNs), and the pervasive use of smartphones have allowed individuals to easily inform their status through locational information. This led to a new trend in social media: to upload geotagged photos that illustrate the location of the images and then share them with others. In this circumstance, the current study aims to examine the use of geotags on Instagram. Further, the motivations for using geotags as well as the relationship among the motivation, satisfaction, and location information sharing behavior are analyzed. The online survey was conducted on 411 respondents of Hong Kong who are active Instagram users. Based on uses and gratification theory and goal theory, the users’ motivations and goals for utilizing geotags were divided into mainly two categories; task-involved and self-involved goals. Then, four different motivations (contribution, memory aid, showing off, and reputation gaining) were further examined. The result indicated that contribution, memory aid, and reputation gaining were the goals and motivation for the users to utilize geotags on Instagram, having a positive impact on satisfaction. However, a positive relationship between showing off and geotag satisfaction was not supported. Among four different factors, memory aid was found to have the strongest influence on geotagging satisfaction. The result of testing the relationship between geotag satisfaction and further location information sharing behavior also turned out to have a positive relationship. The implications and limitations of findings are also discussed in the study.

In this paper, to improve further the bit-error rate (BER) performance of the stronger channel user in non-uniform source non-orthogonal multiple access (NOMA) with symmetric superposition coding (SSC), we propose a smart bit-to-symbol (BTS) mapping of SSC. First, the analytical expression for the total allocated power of the proposed BTS mapping scheme is derived, and then we show that the BER of the proposed BTS mapping scheme improves further, compared to that of the existing BTS mapping scheme. Moreover, based on the simulations, the signal-to-noise (SNR) gain of the proposed BTS mapping scheme over the existing BTS mapping scheme is calculated. In result, the proposed BTS mapping could be a candidate scheme for non-uniform source SSC NOMA with the SNR gain.

Recently, consumers who prefer contactless consumption are increasing due to pandemic trends such as Corona 19. This is the driving force for developing the last mile-based logistics ecosystem centered on the online e-commerce market. Lastmile led to the continued development of the logistics industry, but increased the amount of cargo in urban area, and caused social problems such as overcrowding of logistics. The courier service in the logistics base area utilizes the process of visiting the delivery site directly because the courier must precede the loading work of the cargo in the truck for the delivery of the ordered product. Currently, it’s carried out as automated logistics equipment such as conveyor belt in unloading or classification stage, but the automation system isn’t applied, so the work efficiency is decreasing and the intensity of the courier worker's labor is increased. In particular, small-scale courier workers belonging to the sub-terminal unload at night at underdeveloped facilities outside the city center. Therefore, the productivity of the work is lowered and the risk of safety accidents is exposed, so robot-based loading technology is needed. In this paper, we have derived the top-level concept and requirements of robot-based loading system to increase the flexibility of logistics processing and to ensure the safety of courier drivers. We defined algorithms and motion concepts to increase the cargo loading efficiency of logistics sub-terminals through the requirements of end effector technology, which is important among concepts.Finally, the control technique was proposed to determine and position the load for design input development of the automatic conveyor system.

A TPR-tree is a well-known indexing structure that is developed to answer queries about the current or future time locations of moving objects. For the purpose of space efficiency, the TPR-tree employs the notion of VBR (velocity bounding rectangle) so that a regional rectangle presents varying positions of a group of moving objects. Since the rectangle computed from a VBR always encloses the possible maximum range of an indexed object group, a search process only has to follow VBR-based rectangles overlapped with a given query range, while searching toward candidate leaf nodes. Although the TPR-tree index shows up its space efficiency, it easily suffers from the problem of dead space that results from fast and constant expansions of VBR-based rectangles. Against this, the TPR-tree index is enforced to update leaf nodes for reducing dead spaces within them. Such an update-prone feature of the TPR-tree becomes more problematic when the tree is saved in flash storage. This is because flash storage has very expensive update costs. To solve this problem, we propose a new Bloom filter based caching scheme that is useful for reducing updates in a flash TPR-tree. Since the proposed scheme can efficiently control the frequency of updates on a leaf node, it can offer good performance for indexing moving objects in modern flash storage.

The platform for displaying cars has been changing with the times. From the popularity of paper media to the rise of computer graphics, the improvement of technology has brought more space and possibilities to the automotive industry. Yiming Zhong proposed the workflow of car configurator through Unreal Engine 4 to implement the basic functions of configuration in 2021, according to Yiming Zhong's final presentation, there is still room to improve the realism of graphics and functionality of the car configurator. Therefore, in this paper we propose to upgrade the car shaders and lighting environments according to the real-world physics and add multi-scenes switching function to car configurator. However the multi-scenes switching function also brings a large amount of data, which leads to the problem of display lag. At the end of the paper, we use the level of details(LOD) process to reduce the amount of data for real-time computing in Unreal Engine 4 and the increase of frames per second(FPS) values verifies the feasibility of our optimization solution.

In this paper, we propose a highly secure watermarking technique in which the watermark is multi-encrypted using the R, G, and B component pixels of color image, and then the multi-encrypted watermark is hidden in the LSB of the color image pixel. According to the technique proposed in this paper, the quality of the stego-image created by hiding the multi-encrypted watermark in the LSB of the color image is so excellent that the difference from the cover image cannot be recognized. Also, it is possible to extract the original watermark from the stego-image without loss. If the watermark is hidden in the image using the proposed technique, the security of the watermark is maintained very well because the watermark hidden in the stego-image is multi-encrypted. The proposed watermarking technique can be used in the applications such as military and intellectual property protection requiring high security.

Minimization of human casualties in disaster situations is of paramount importance. In particular, if a marine disaster occurs, it can be directly connected to human casualties, so prompt action is needed. In the event of a marine disaster, the route and location of movement should be identified and life tubes should be used to float on the water. This paper designs and proposes an emergency IoT notification system that can quickly rescue drowning people. The maritime emergency IoT notification system consists of four main types. First, an emergency IoT device that detects the expansion of the life tube and delivers location and situation information to the emergency IoT notification server. Second, an emergency IoT web server that manages emergency information and provides notification. Third, a database server that stores and manages emergency IoT notification information. And finally, an emergency notification app that can receive and respond to emergency notification information. The emergency IoT device consists of a TPMS(Tube Pressure Monitoring System) device that checks the pressure value of the TPMS in real time and sends it to the IoT device, and an IoT device that sends the rescuer’s voice information and emergency information to the emergency IoT server. Emergency information is delivered using the MQTT(Message Queuing Telemetry Transport) protocol, and voice information is delivered to the IoT server as HTTP FormData.

Real human digital models appear more and more frequently in VR/AR application scenarios, in which realtime markerless face capture animation of personalized virtual human faces is an important research topic. The traditional way to achieve personalized real human facial animation requires multiple mature animation staff, and in practice, the complex process and difficult technology may bring obstacles to inexperienced users. This paper proposes a new process to solve this kind of work, which has the advantages of low cost and less time than the traditional production method. For the personalized real human face model obtained by 3D reconstruction technology, first, use R3ds Wrap to topology the model, then use Avatary to make 52 Blend-Shape model files suitable for AR-Kit, and finally realize real-time markerless face capture 3D real human on the UE4 platform facial motion capture, this study makes rational use of the advantages of software and proposes a more efficient workflow for real-time markerless facial motion capture of personalized 3D real human models, The process ideas proposed in this paper can be helpful for other scholars who study this kind of work.

A very complex task in deep learning such as image classification must be solved with the help of neural networks and activation functions. The backpropagation algorithm advances backward from the output layer towards the input layer, the gradients often get smaller and smaller and approach zero which eventually leaves the weights of the initial or lower layers nearly unchanged, as a result, the gradient descent never converges to the optimum. We propose a two-factor non-saturating activation functions known as Bea-Mish for machine learning applications in deep neural networks. Our method uses two factors, beta (β) and alpha (α), to normalize the area below the boundary in the Mish activation function and we regard these elements as Bea. Bea-Mish provide a clear understanding of the behaviors and conditions governing this regularization term can lead to a more principled approach for constructing better performing activation functions. We evaluate Bea-Mish results against Mish and Swish activation functions in various models and data sets. Empirical results show that our approach (Bea-Mish) outperforms native Mish using SqueezeNet backbone with an average precision (AP50val) of 2.51% in CIFAR-10 and top-1accuracy in ResNet-50 on ImageNet-1k. shows an improvement of 1.20%.

In this paper, a model combined with explanatory artificial intelligence (xAI) models was presented to secure the reliability of machine learning-based sentiment analysis and prediction. The applicability of the proposed model was tested and described using the IMDB dataset. This approach has an advantage in that it can explain how the data affects the prediction results of the model from various perspectives. In various applications of sentiment analysis such as recommendation system, emotion analysis through facial expression recognition, and opinion analysis, it is possible to gain trust from users of the system by presenting more specific and evidence-based analysis results to users.

Recently, it is recognized as a high-cost and inefficient logistics system that increases traffic congestion and environmental problems due to an increase in traffic volume due to the activation of the online market. In order to solve inefficient problems such as unavoidable traffic congestion and environmental problems caused by the increase in traffic volume, it is necessary to develop a freight transport system technology using the existing urban railway infrastructure and freight-only urban railway. The urban subway logistics system is a logistics system that requires a combination of various technologies to solve the nationwide demand for urban logistics and road traffic problems. This paper recognized the existing traffic congestion and environmental pollution of road traffic as problems, and supplemented the contact point requirements presented above by identifying the sub-systems constituting the target system and supplementary points for each part-level contact point. In this study, as a complex system operated for one purpose by grafting various technologies, a plan is required to secure the reliability and safety of operation from various viewpoints. The results of this study can contribute to the initial configuration and basic data to solve the interface bottleneck of the urban subway logistics system to be promoted in the future.

We live in a digital age. Smartphones are used by everyone from children to the elderly. And many smart devices are pouring out and changing our daily life a lot. However, even in the development of this digital age, there are some marginalized groups. There are also those who are reluctant to expose their information in the digital age. They have difficulty making reservations on their smartphones, using payment systems, logging into the site using various authentication and verification procedures, and entering and leaving buildings. We still carry most IDs, seals, certificates, etc. in physical form. Those who use smartphones are enjoying the convenience of the times. However, among the underprivileged, the desire to pass everything with only one device is growing. In this study, the most suitable smart band model was proposed by collecting the Delphi survey and the opinions of the general public. Future research is required to improve practical usability and utility by developing cheaper and more convenient models.

This study aims to study non-rechargeable wrist-type smart bands for those vulnerable to the digital environment. The transition to the digital age means improving the efficiency of human life and the convenience of management. In the digital age, it can be a very convenient infrastructure for the digital generation, but otherwise, it can cause inconvenience. COVID-19 is spreading non-face-to-face culture. The reality is that the vulnerable are complaining of discomfort in non-face-to-face culture. The core of the digital environment is smartphones. Digital life is spreading around smartphones. Technology that drives the digital environment is the core technology of the Fourth Industrial Revolution. The technologies are lot, big data, Blockchain, Smart Mobility, and AI. Related technologies based on these technologies include digital ID cards, digital keys, and nfc technologies. Non-rechargeable wrist-type smart bands based on related technologies can be conceptualized. Through these technologies, blind people can easily access books and manage their ID cards conveniently and efficiently. In particular, access authentication is required wherever you go due to COVID-19, which can be used as a useful tool for the elderly who feel uncomfortable using smartphones. It can also eliminate the inconvenience of the elderly finding or losing their keys.

The energy efficiency of memory systems is an important task in designing future computer systems as memory capacity continues to increase to accommodate the growing big data. In this article, we present an energy-efficient last-level cache management policy for future mobile systems. The proposed policy makes use of low-power PCM (phase-change memory) as the main memory medium, and reduces the amount of data written to PCM, thereby saving memory energy consumptions. To do so, the policy keeps track of the modified cache lines within each cache block, and replaces the last-level cache block that incurs the smallest PCM writing upon cache replacement requests. Also, the policy considers the access bit of cache blocks along with the cache line modifications in order not to degrade the cache hit ratio. Simulation experiments using SPEC benchmarks show that the proposed policy reduces the power consumption of PCM memory by 22.7% on average without degrading performances.

As of 2020, the cumulative number of electric vehicles worldwide increased 43% from 2019, exceeding 10 million. We surveyed and analyzed important factors when purchasing electric vehicles for consumers who own electric vehicles. Through this, we tried to find an effective way to supply electric vehicles in the future. The purpose of this study is to present customized marketing proposals for companies by empirically analyzing the factors affecting consumers' electric vehicle purchases and deriving market demands for electric vehicles .We identified the market status of electric vehicles through literature research and reviewed previous studies on the factors affecting the purchase intention of electric vehicles. Through empirical studies, differences in electric vehicle purchase factors according to gender, age, and the degree of importance of performance were analyzed. To this end, the SPSS statistics package was used.Factors influencing the purchase of electric vehicles were set to mileage, charging time, new technology, degree of driving autonomous development, design, price, infrastructure for charging, the phase of maintenance and repair, by the government and local governments. In addition, the most important factors were derived, and the average difference analysis was conducted according to gender, age, and performance importance.

As around the world, ground and underground transportation capacity is reaching its limit, centering on urban areas. As urban traffic becomes congested, time and cost are astronomical, and environmental destruction caused by urban pollution is becoming increasingly serious. As a way to solve this problem, the means of flying over the air are in the spotlight as the next generation of future transportation, and the concept of urban air mobility (UAM, Urban Air Mobility) is defined as systematic planning. The development of an electric-powered vertical take-off (eVTOL) aircraft that obtains electric power through a battery using a personal aerial vehicle (PAV) as a means of transportation has accelerated. As the aircraft development of new technology aircraft in the evtol method is actively carried out, the need to prepare systems such as aircraft certification standards, pilot qualification systems, and qualification management is emerging. The Federal Aviation Administration (FAA) and the European Union Aviation Safety Agency (EASA), which lead international standards, announced new special technical conditions and temporary regulations SCVTOL- 01, respectively.However, the pilot qualification system for operating the uam aircraft has not yet been clearly announced. Therefore, this paper analyzes the recently announced FAA regulations and EASA regulations to identify differences and directions in perspectives on UAMs and study the existing vertical take-off and landing aircraft (VTOL) pilot qualification system to present directions for qualification classification.

Today, with the development of the Internet and mobile technology, consumers' purchasing patterns have shifted from offline to online. In addition, due to the recent COVID-19, online purchases have significantly increased, and accordingly, the courier industry for logistics delivery has also grown significantly. Various logistics robots are being operated in many industrial and can reduce the labor intensity and physical and mental fatigue of workers. However, if the logistics robot does not properly recognize the people or environment around it, it can lead to a serious accident. We conducted that how logistics robots can perform safe work in a working environment such as a logistics warehouse through the application of ISO/DIS 21448 (SOTIF) to autonomous logistics transport robots. This result is expected to contribute to the operation of unmanned logistics warehouses using AGV.

The Internet can deliver various information and services at the lowest cost without time and space constraints while targeting the world among all existing means of communication. Unlike traditional media such as TV, newspapers, and radio in the past, promotions through mobile environments allow target customers to use two-way low-cost, high-efficiency promotional strategies regardless of time and place. With the development of the Internet, social media has developed into a place to acquire information about favorite companies and their products. Social media greatly contributes to the production of text, photos, videos, and various networks, and has expanded global communication and communication media through the interaction and sharing of various information. In addition, through social media, users can communicate in various ways, reveal themselves, and share and exchange information such as knowledge and personal thoughts. In line with these changes, corporate marketers and sellers are striving to provide consumers with appropriate information more quickly. We aims to find out about social media marketing strategies useful for companies.

The purpose of this study was to investigate the pre- and post-exercise performance, edema, and pain of plyometrics in water and land environments. Twelve males in their 20s were selected as subjects and performed 10 sets of squat jumps 10 times in 2 environmental conditions (water and ground). There was no significant difference in iEMG of vastus medilais according to exercise conditions and time. In MPV of CMJ, there was no significant difference according to exercise conditions and time. The thigh circumference showed a significant difference according to the exercise condition and time, and was higher in the ground condition after exercise. There was a significant difference in pain according to the exercise condition and time, and it was found to be high after exercise, 48 hours, and 72 hours in the ground condition. We believe that plyometric training in an aquatic environment will have less swelling and pain compared to plyometric training conducted in a land environment, and the pain will improve quickly, so we think that training can be conducted in a relatively shorter period than in the land environment.