Earticle

With developments in science and technology and improvement in living standards, human life expectancy is steadily increasing worldwide. For effective healthcare, it is necessary to check health conditions according to individuals’ behavior and acquire prior knowledge on possible diseases. In this study, we classified the diseases that are major causes of death in Korea by referring to data provided by the Korea National Health and Nutrition Examination Survey. We selected indexes that could be used as indicators of major diseases and created the LCBB-SC. In the LCBB-SC, the data are systematically subdivided into related fields to provide integrated data related to each disease and to provide an infrastructure that can be used by researchers. In addition, by developing a web interface allowing for self-symptom assessments, this resource will be beneficial to people who want to check their own health condition using a list of diseases that might be caused by their behaviors.

For the information services supporting requests of data items from a great number of mobile clients, wireless data broadcasting is an effective way because it can accommodate any number of clients. In the wireless data broadcasting, various air indexing schemes and data scheduling schemes have been developed in order to enable the clients to access their desired data items efficiently. The broadcasting system needs a method to simulate newly designed air indexing and scheduling schemes of the system, and to evaluate the performance parameters of the schemes. In this paper, we design an expandable and efficient simulation framework for the wireless data broadcasting based on the partition of data ID space. The framework can adopt regular and irregular space partition and evaluate various performance parameters of the broadcasting system. We implement a testbed of the broadcasting system using the framework, that adopts IIP, GDI and EXP as its air indexing schemes. We simulate the system using the testbed and evaluate the performance parameters of the system. Thus, we show the efficiency and expandability of the designed and implemented framework.

One of the distinct features of Wireless Sensor Networks (WSNs) is duty cycling mechanism, which is used to conserve energy and extend the network lifetime. Large duty cycle interval introduces lower energy consumption, meanwhile longer end-to-end (E2E) delay. In this paper, we introduce an energy consumption minimization problem for duty-cycled WSNs. We have applied Q-learning algorithm to obtain the maximum duty cycle interval which supports various delay requirements and given Delay Success ratio (DSR) i.e. the required probability of packets arriving at the sink before given delay bound. Our approach only requires sink to compute Q-leaning which makes it practical to implement. Nodes in the different group have the different duty cycle interval in our proposed method and nodes don’t need to know the information of the neighboring node. Performance metrics show that our proposed scheme outperforms existing algorithms in terms of energy efficiency while assuring the required delay bound and DSR.

Since the global positioning system (GPS) has been included in mobile devices (e.g., for car navigation, in smartphones, and in smart watches), the impact of personal GPS log data on daily life has been unprecedented. For example, such log data have been used to solve public problems, such as mass transit traffic patterns, finding optimum travelers’ routes, and determining prospective business zones. However, a real-time analysis technique for GPS log data has been unattainable due to theoretical limitations. We introduced a machine learning model in order to resolve the limitation. In this paper presents a new, three-stage real-time prediction model for a person's daily route activity. In the first stage, a machine learning–based clustering algorithm is adopted for place detection. The training data set was a personal GPS tracking history. In the second stage, prediction of a new person's transient mode is studied. In the third stage, to represent the person's activity on those daily routes, inference rules are applied.

We propose a more stable robust recognition algorithm which detects faces reliably even in cases where there are changes in lighting and angle of view, as well it satisfies efficiency in calculation and detection performance. We propose detects the face area alone after normalization through pre-processing and obtains a feature vector using (PCA). The feature vector is applied to LDA and using Euclidean distance of intra-class variance and inter class variance in the 2nd dimension, the final analysis and matching is performed. Experimental results show that the proposed method has a wider distribution when the input image is rotated 45 ° left / right. We can improve the recognition rate by applying this feature value to a single algorithm and complex algorithm, and it is possible to recognize in real time because it does not require much calculation amount due to dimensional reduction.

The Internet of Things (IoT) and Visible Light Communication (VLC) is opening up new services in lighting industry by integrating sensory network features in addition to standard illumination functionality. In this progressive developments, the next generation lighting devices for smart homes are capable to sense the environmental conditions and transfer the captured data through lights to gateway controller to access remotely. The smart home environmental sensor information’s are few kbps only so VLC systems need to built-in with low rate light connectivity to transfer data to the gateway. To provide error free communication, the quality of a received light signal is important to be considered when designing an VLC receiver. Therefore, this paper proposes the design of robust low rate IoL receiver design using NCP302 voltage detector for micro controller to adapt the IoT/IoL front end module for system integration. To evaluate the proposed system performance, the Arduino UNO based IoT/IoL controller designed with lighting, sensors and lights connectivity interfaces. The experimental result shows that the robust interference rejection is feasible on proposed VOL receiver and possible to have an error-free communication up to 10 kbps at a low SNR using OOK modulation.

Artificial neural network is inspired by the biological neural network. For simplicity, in computer science, it is represented as a set of layers. Many research has been made in evaluating the number of neurons in the hidden layer but still, none was accurate. Several methods are used until now which do not provide the exact formula for calculating the number of the hidden layer as well as the number of neurons in each hidden layer. In this paper model selection approach was presented. Proposed model is based on geographical analysis of decision boundary. Proposed model selection method is useful when we know the distribution of the training data set. To evaluate the performance of the proposed method we compare it to the traditional architecture on IRIS classification problem. According to the experimental result on Iris data proposed method is turned out to be a powerful one.

While new information technology advances have made information access and acquisition methods much more diverse and easier, there are side effects that allow illegal access using diverse and high-performance tools. In order to cope with such threats, there are access control methods in database technology, and various studies are being conducted to extend traditional access control to cope with new computing environments. In this paper, we propose an extended access control with uncertain context-awareness. It enables appropriate security policy enforcement even if the contextual constraints specified by the security policy does not match those accompanied by access request query. We extract semantic implications from context tree, and define the argument that can quantitatively measure the semantic difference between two nodes in the context tree. It is used to semantically enforce the security policy, and to prevent the excessive authorization caused by the implication.

Predictive IoT Sensor Algorithm is a technique of data science that helps computers learn from existing data to predict future behaviors, outcomes, and trends. This algorithm is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions. Sensors and computers collect and analyze data. Using the time series prediction algorithm helps to predict future temperature. The application of this IoT in industrial environments like power plants and factories will allow organizations to process much larger data sets much faster and precisely. This rich source of sensor data can be networked, gathered and analyzed by super smart software which will help to detect problems, work more productively. Using predictive IoT technology - sensors and real-time monitoring - can help organizations exactly where and when equipment needs to be adjusted, replaced or how to act in a given situation.

In this paper, we simulated three different HV systems and analyzed of each vacuum characteristics by VacCAD modelling. In each of modelled vacuum systems, selection of chamber materials, combination of rough pump with high vacuum pump and conductance of roughing line (diameter and length) were proposed as system variables. In the modelling of chamber materials, the pumping times to ultimate pressures of different chamber materials (stainless steel, aluminum) were compared by the variations of chamber volume. In this model, the effects of outgassing dependent on the chamber materials was also simulated and aluminum was estimated to optimum chamber materials. It was also obtained that modelling of vane and roots pump with diffusion pump and diameter, length of 50×250 [􀝉􀝉] roughing line were characterized as optimum variables to reach the ultimate pressure of 10E-7 [mbar] most effectively. Optimum design factors for vacuum characteristics of modelled vacuum system were achieved by VacCAD simulations. Feasibility of VacCAD as vacuum simulator was verified and applications of VacCAD expected to be increased to fields in vacuum needed.

This paper presents a link adaptation scheme for adaptive full duplex (AFD) systems. The signal modulation levels and communication link patterns are adaptively selected according to the changing channel conditions. The link pattern selection process consists of two successive steps such as a transmit-receive antenna pair selection based on maximum sum rate or minimum maximum symbol error rate, and an adaptive modulation based on maximum minimum norm. In AFD systems, the antennas of both nodes are jointly determined with modulation levels depending on the channel conditions. An adaptive algorithm with relatively low complexity is also proposed to select the link parameters. Simulation results show that the proposed AFD system offers significant bit error rate (BER) performance improvement compared with conventional full duplex systems with perfect or imperfect self-interference cancellation under the same fixed sum rate.

Visitors to a Web site leave access logs documenting their activity in the site. These access logs provide a valuable source of information about the visitors’ access patterns in the Web site. In addition to the pages that the user visited, it is generally possible to discover the geographical locations of the visitors. Web servers also records other information such as the entry into the site, the URL, the used operating system and the browser, etc. There are several Web mining techniques to extract useful information from such information and visualization of a Web log is one of those techniques. This paper presents a technique as well as a case a study of visualizing a Web log.

In this study, we introduce a new image gradient computation based on understanding of image generation. Most images consist of groups of pixels with similar color information because the images are generally obtained by taking a picture of the real world. The general gradient operator for an image compares only the neighboring pixels and cannot obtain information about a wide area, and there is a risk of falling into a local minimum problem. Therefore, it is necessary to attempt to introduce the gradient operator of the interval concept. We present a bow-tie gradient by color values of pixels on bow-tie region of a given pixel. To confirm the superiority of our study, we applied our bow-tie gradient to image segmentation algorithms for various images.

The purpose of this paper is to develop simulations that can be used for virtual education in dentistry. This development goal is to allow dental students to learn the necessary surgical techniques at the point of their choice, not going into the operating room, away from time, space, and physical limits. In this paper configuration, the optimization method is applied convergent, and when the operation of the VR contents is performed, the content data is extracted from the interaction analysis formed in the VR engine, and the data is processed by the content algorithm. It also computes events and dental operations generated within the 3D engine programming and generates corresponding events through data processing according to the input signal. The visualization information is output to the HMD using the rendering information. In addition, the operating room environment was constructed by studying lighting and material for actual operating room environment. We applied the ratio of actual space to virtual space and the ratio between character and actual person to create a spatial composition at a similar rate to actual space.

This paper develops and builds an Integrated Assessment System for National Competency Standard Professional Basic. The integrated evaluation system for basic job competency in the National Competency Standards is developed to conduct examination by means of computers, smartphones and tablet PCs. The system can be used for the basic job competency test, examination for online cyber universities, job competency examination for enterprises, and the listening, reading, and speaking test in the foreign language proficiency examination and is even better in terms of facility investment and saved operating costs as well as efficient use of spaces in comparison with conventional evaluation schemes. Even greater synergy effects can be achieved by providing support for the integrated evaluation system for basic job competency in connection with the NCS qualification system. The evaluation system has been tested and practiced at a specialized high school and can be applied to the NCS education evaluation of the college and four-year college and to the selection examination of new employees of the company.

In the programming education, there is a great need of a teaching support system that can support the learner in the programming process regardless of the computer language due to instructor’s difficulty of checking the progress of learners in real-time. Its importance is especially important in lower grade coding classes such as in K-12 education because they are not used to coding and so simple problems can be regarded as complex problems. For this, a pilot coding education support system based on Levenshtein distance algorithm which shows learners’ progress to given solution in real-time was developed in order to help learners to solve complex problems easily, and the learners’ motivation and self-efficacy was measured for estimating the usefulness of developed system targeting elementary school students. When the learners use the developed system, it was found that a statistically significant difference appears in the sub-factors of learning motivation compared with traditional class teaching environments. Among the sub-factors of self-efficacy, the efficacy dimension showed statistically significant difference too.

Generally, the animation and image production process consists of three stages: Pre-Production, Main-Production, and Post-Production. Real-time video production is also made based on this configuration. On the premise of the increase of productivity by reducing the production time effectively in the main production stage that takes the most time, this study aims to summarize the process of producing videos, focusing on the concrete main production stage. To do this, we propose a method for creating a real-time image from the point of view of the general user using Unity 3D, one of the game engines. Also, this study utilizes the Cinemachine feature provided by Unity 3D, which is suitable for the implementation of the proposed module structure.

This study is about the interactive self-portrait which provides the experience of self-consciousness reflection of the viewer to modern people who are easily alienated in rapid social change. We proposed interactive self-portrait is implemented by an interactive mirror that reproduces the appearance of the viewer acquired using a webcam. The interactive mirror, which can directly project its own image, is drawn by searching news articles in real time and using the extracted characters as pixel information in real time. The viewer has the opportunity to experience a new style of active self-expression while watching his/herself composed of news characters that are issues of modern society. The virtual self-portrait designed with news characters can attract viewers' attention by visually expressing the interests of modern people and can act as an incentive to generate positive interaction.

Sometimes, literature therapy is done by literature question. Participants naturally get the effect of literature therapy depending on when and what questions we ask. This study aims to lead the discussion of Gosijo's literature physiology ignited by the question. Gosijo, the subject of the study, described the depressed present state of the poetic narrator in the first and second line. By the way, poetic narrator asked a question in the first phrase of the last line and led the action potential. And in the second phrase of the last line, the poetic narrator called the code of sadness and the sadness code came. We have plotted this as Emotion Codon. The result of Emotion Codon at this time was that the narrative of Gosijo ignites the literature therapy mechanism through sadness.

Recently, the bio-sensing information systems for collecting and analysing human body information of a patient in real time in the field of medical information and healthcare information service are continuously increasing. Specially, various wearable devices such as a wrist, a garment, and a skin attachment type for supporting health information of a mobile user are rapidly increasing. Until now, there is no patch-type biometric information service model. Therefore, this paper presents a biometric information system model and the application examples to support biometric information sensing and health information service of mobile user with digital patch system as a new biometric information system. As a result, through this research, research issues based on digital patch system are searched to suggest the direction of continuous research.

Iris diagnosis based on the color and texture information is one of a novel approach which can represent the current state of a certain organ inside body or the health condition of a person. In analysis of the iris images, there are critical image artifacts which can prevent of use interpretation of the iris textures on images. Here, we developed the iris diagnosis system based on a hand-held typed imaging probe which consists of a single camera sensor module with 8M pixels, two pairs of 400~700 nm LED, and a guide beam. Two original images with different light noise pattern were successively acquired in turns, and the light noise-free image was finally reconstructed and demonstrated by the proposed artifact removal approach.

The efficiency and safety of social-overhead capital (SOC) public infrastructures have become an eminent social concern. In this regard, a continuous structural health monitoring has been widely implemented to oversee the robustness of such public infrastructures for the safety of the public. This paper deals with the analysis of a distributed mobility management (DMM) support for wireless sensor network (WSN) based information transmission system. The partial DMM support separates the data and control plane infrastructures, wherein, the control plane is managed by a particular mobility management network entity, while the data plane is distributed by the mobility anchors. The system will be able to optimize the information transmission for a wireless structural health monitoring of SOC public infrastructures specifically designed for bridges, and thus, guarantees the safety of public commuters.

Based on World Health Organization (WHO) children and adults have a problem with their oral health, such as Dental cavities and periodontal disease. It is not easy to obtain the high convince level of result of the dental and periodontal diseases. Because each of them have different degrees of uncertainty and there have several discounting factors (error rates) in different of survey. To solve this problem we propose the Dezert-Smarandache Theory (DSmT) for efficient combination of uncertain, imprecise and highly conflicting sources of information. Moreover, we apply the SEFP as a context reasoning. Finally, we make the simulation by using 12 surveys and compare Propotional Conflict Redistribution 5 (PCR5) and Dempster-Shafer Theory (DST) to show the belief or probability for the low, a heavy, high and ultra-high risk situation.

Nowadays, wireless sensor networks (WSNs) have been widely adopted in structural health monitoring (SHM) systems for social overhead capital (SOC) public infrastructures. Structural health information, environmental disturbances and sudden changes of weather conditions, damage detections, and external load quantizing are among the capabilities required of SHM systems. These information requires an efficient transmission with which an efficient mobility management support for wireless networks can provide. This paper deals with the analysis of mobility management schemes in order to address the real-time requirement of data traffic delivery for critical SHM information. The host-based and network-based mobility management protocols have been identified and the advantages of network mobility (NEMO) enabled Proxy Mobile Internet Protocol version 6 (PMIPv6) have been leveraged in order to address the SHM information transmission needs. The scheme allows an efficient information transmission as it improves the handover performance due to shortened handover latency as well as reduced signaling overhead.