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Research on electrocardiogram (ECG) signals has been actively undertaken to assess their value as a next generation user recognition technology, because they require no stimulation and are robust against forgery and modification. However, even within the same user, the heart rate and waveform of ECG signals will vary depending on physical activity, mental effects, and measurement time. Therefore, when data acquired across changes in the user state is used as registered data, an overfitting problem occurs due to data generalization, which degrades the recognition performance for newly acquired data. Therefore, in this paper, we propose parallel ensemble networks to solve the overfitting problem and prevent the degradation. First, ECG signals acquired in various environments are used as the input data of parallel convolutional neural networks (CNNs). Each CNN is set up with different parameters to detect different features. The ECG signals outputted from each network are classified for each subject, and then fused into one database to be used as registered data for re-training. Instead of fusing all the output signals from each network, only the ECG signals of Top-3 networks showing excellent performance are fused and composed of registered data. The reconstructed registered data are used for user recognition, by re-training with time independent comparison data in the CNN. The experimental results of comparing the proposed parallel ensemble networks with those of previous studies using the self-acquired actual ECG signals show that the proposed method achieves recognition performance higher than the previous studies, with an accuracy rate of 98.5%.

Localization plays an important role in the field of Wireless Sensor Networks (WSNs) and robotics. Currently, localization is a very vibrant scientific research field with many potential applications. Localization offers a variety of services for the customers, for example, in the field of WSN, its importance is unlimited, in the field of logistics, robotics, and IT services. Particularly localization is coupled with the case of human-machine interaction, autonomous systems, and the applications of augmented reality. Also, the collaboration of WSNs and distributed robotics has led to the creation of Mobile Sensor Networks (MSNs). Nowadays there has been an increasing interest in the creation of MSNs and they are the preferred aspect of WSNs in which mobility plays an important role while an application is going to execute. To overcome the issues regarding localization, the authors developed a framework of three algorithms named Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF) and Particle Filter (PF) Localization algorithms. In our previous study, the authors only focused on EKF-based localization. In this paper, the authors present a modified Kalman Filter (KF) for localization based on UKF and PF Localization. In the paper, all these algorithms are compared in very detail and evaluated based on their performance. The proposed localization algorithms can be applied to any type of localization approach, especially in the case of robot localization. Despite the harsh physical environment and several issues during localization, the result shows an outstanding localization performance within a limited time. The robustness of the proposed algorithms is verified through numerical simulations. The simulation results show that proposed localization algorithms can be used for various purposes such as target tracking, robot localization, and can improve the performance of localization.

In this paper, we focus on the radio resource management (RRM) issues in the two-hop Orthogonal Frequency Division Multiple Access (OFDMA) system with heterogeneous quality of service (QoS) requirements. To solve the RRM problem, we first propose a new two-hop frame structure to support the data relay operation from the base station to the relay station and cooperative transmission for the edge users. Then, a two-hop coordinated scheduling algorithm is proposed, which utilizes the proposed two-hop frame structure and considers the corresponding interference status. The proposed two-hop coordinated scheduling algorithm solves the RRM problem of the two-hop OFDMA system with heterogeneous QoS requirements in an iterative manner, and so maximizes the system utility.

Tuberculosis (TB) is one of the top 10 causes of death in the world and is a major health threat in the developing countries. There are two ways to reduce death from tuberculosis. One is rapid and accurate diagnosis and the other is DOTS (Directly observed treatment, short-course), which is the tuberculosis (TB) control strategy recommended by the World Health Organization. In this paper, we propose the AI algorithm for the effective management of the tuberculosis patient by using DOTS. For this purpose, we used the patient's real time medication data. Additionally, we divided two phased for the prediction of medication adherence, one is the screening phase and the other is the medication monitoring phase. We think that is a way to reduce the overall cost of treating tuberculosis patients.

A Voltage Sourced Converter (VSC) for High Voltage Direct Current (HVDC) operates in extremely high voltage and high-power conditions. Especially in case of Modular Multilevel Converter (MMC), hundreds of submodules are connected in series to meet the high voltage requirement. IEC 62501 suggests several tests such as the operational tests for a valve consisting of several submodules and the dielectric tests, etc. This paper proposes a new test circuit for the submodule in MMC-based HVDC system. Simulations are carried out for a system with the power rating of 2.4 [kV] and 485 [A], and both the simulation and scaled down experimental results show the validity of the proposed test circuit.

A novel method has been established to mitigate the complexity of a birdcage coil design process for use in a MRI (Magnetic Resonance Imaging) system. It can reduce the time consumptions of the typical coil design process based on 3D (three-dimensional) simulations. The method combines an equivalent circuit model and a 3D electromagnetic simulation. It makes it possible to understand the coil properties intuitively and to solve the major engineering problems by using just the circuit model not by using the complex 3D simulation. The concept of the dominant resonance path length of the coil has also been introduced, which facilitates the design process by considering the skin effect of the coil. We have verified that the skin effect of the birdcage coil can be evaluated through a simple circular loop circuit instead of the whole 3D geometry. Base on the design proposed method, we also have successfully demonstrated that the birdcage coil based on a FPCB (Flexible Printed Circuit board) technique can be used in high filed (3.0 T and 4.7 T) MRI systems for small animal NMR (Nuclear Magnetic Resonance) imaging.

This paper presents a digital phase modulator for wide bandwidth polar transmitters. It adopts a digital-to-time converter (DTC) and high-speed phase calibration loop that improves sampling rate for the same phase resolution. The DTC consists of a chain delay line with different delay cells to generate a small phase. A feedback loop based on a novel time-to-digital converter (TDC) nested inside the phase modulator sets the DTC output phase accurately across the range of input digital code as well as over process, voltage, and temperature. By using the TDC-based feedback loop, the proposed phase modulator can achieve high sampling rate and small phase resolution. The phase modulator achieves 0.72 degree phase resolution and 40 MS/s sampling rate while consuming 8 mW of power. This phase modulator is implemented in a 180 nm CMOS technology and occupies 0.3 mm2.

Recently, most of context-aware services are trying to exploit the emotional contexts of the target users. The aim of this conceptual paper is to discuss affective lifelogging framework which can recognize the emotions by integrating multimodal information from multiple sources. Moreover, we will mention the open problems on affective lifelogging.

There are continuous hacking and social issues regarding APT (Advanced Persistent Threat - APT) attacks and a number of antivirus businesses and researchers are making efforts to analyze such APT attacks in order to prevent or cope with APT attacks, some host PC security technologies such as firewalls and intrusion detection systems are used. Therefore, in this study, malignant behavior patterns were extracted by using an API of PE files. Moreover, the FP-Growth Algorithm to extract behavior information generated in the host PC in order to overcome the limitation of the previous signature-based intrusion detection systems. We will utilize this study as fundamental research about a system that extracts malignant behavior patterns within networks and APIs in the future.

Smart devices have already become a dally necessity of our life since they play a pivot role to record massive amount of Information of our personal life. Current Internet of TWngs era has been seeing more and more people relying on their devices. However, most people are losing patience to set complex passwords to ensure the security for their devices. To avoid forgetting the passwords, people are more willing to choose simple alphanumeric character combinations that are easy for them to remember and convenient to enter. Therefore, their passwords are of high probability to be cracked or exposed. In tWs paper, we study the potential security problems caused by simple and weak passwords, discuss the drawbacks of some conventional works, and propose three schemes to Increase the complexity of simple passwords. Note that our proposals are based on the prediction that the textual passwords are not difficult for users to remember or enter and the proposed schemes can effldently prevent passwords from being cracked or exposed.

This paper proposes a novel architecture of time-to-digital converter (TDC) with wide input range in polar demodulators for electrical impedance spectroscopy (EIS) systems. The system combines a counter-based TDC with cascaded time interpolation stages and efficiently quantizes the phase component. The maximum phase error of 0.52 degrees from 1-kHz to 2.048-MHz frequency sweep range superior to previously reported ones. Reconfigurability of interpolation factor and cascaded architecture greatly enhances hardware efficiency of the system with average power consumption of 1.93 mW, which makes this work worth for system-on-chip (SoC) realization of EIS systems based on polar demodulators.

In recent years, both of financial technologies and its services for mobile devices have been increased sharply. However, according to the case studies of mobile security, security threats have been increased too. Thus, for sustaining their services safe, security department of companies or bank institutes continuously research and develop to upgrade their service solutions. However, recent researches of security threats reported that various new types of social engineering attack were frequently observed in mobile service. In this paper, we compare several user authentication schemes against social engineering attacks, especially shoulder surfing attack. In the experimental result, each one of existing schemes have a slightly different weaknesses. According to the result of comparative analysis, we suggest some of considerations for developing anti-shoulder surfing security solution.

The development of wireless communication technology and diverse sensors has facilitated user-centered information collection. This has also led to active research on the context-aware-based inference to provide user-tailored services. This paper proposes an approach of predicting disease outbreaks based on the fuzzy rule. There are five physiological input variables: age, blood pressure, cholesterol, obesity, and smoking. Fuzzy rule is the concept of expressing the degree of uncertain context in the membership function, which is expressed as a real number between 0 and 1. It is suitable for expression and inference of non-linear data such as physiological variables. The study performed disease outbreak risk diagnosis through the structured inference rule based on the disease outbreak element and assessed the performance of the inference system.

Recently personal information due to the APT attack, the economic damage and leakage of confidential information is a serious social problem, a great deal of research has been done to solve this problem. APT attacks are threatening traditional hacking techniques as well as to increase the success rate of attacks using sophisticated attack techniques such attacks Zero-Day vulnerability in order to avoid detection techniques and state-of-the-art security because it uses a combination of intelligence. In this paper, the malicious code is designed to detect APT attack based on APT attack behavior ontology that occur during the operation on the target system, it uses intelligent APT attack than to define inference rules can be inferred about malicious attack behavior to propose a method that can be detected.

A novel birdcage type Radio Frequency (RF) receiver coil sensor with passive type detuning circuits integrated on the end-rings of the coil sensor has been implemented. A simulation model of the RF receiver coil sensor with the passive type detuning circuits has also been proposed. The simulation model completely explains the working principle of the RF receiver coil sensor with the passive type detuning circuits. The RF coil sensor was designed to perform the Nuclear Magnetic Resonance (NMR) imaging of small animal at 3T Magnetic Resonance Imaging (MRI) system. The integrated detuning circuits of the RF coil sensor eliminate the noises induced by the mutual inductance between receiving and transmitting coils. We have confirmed the performances of the RF coil sensor through experiments, which agreed well with those of the simulations.

The number of global SNS users is rapidly increasing because SNS is executed by the device called Smartphone and enables the users to overcome time and space barrier with low cost. This would be a proof that the SNS is deeply involved in the communication between many people and related data is continuously increasing. Like this, data volume for SNS continues to increase due to the increasing users and the experts are doing the research considering data reusability. In particular, even though there are many researches to provide the individually customized information using the comments which exist in the SNS, there is a limitation to get the personal information due to the number of characters (approximately 150 words) which is a characteristic of SNS. However, most data which are written by the users still exist because of the characteristic of SNS and continuously stored data are considered to be the data which could sufficiently identify the characteristics of the individual users. Therefore in this paper, interested areas of the individuals are to be identified using the comments of individual users and their friends, and the patterns are to be analyzed in each interested area and finally, the analyzed data will be used for future research.

In this paper we are demonstrating a novel method of designing and implementing a modified birdcage type Radio Frequency (RF) coil for small animal Nuclear Magnetic Resonance (NMR) imaging. This RF coil is basically a band pass type birdcage coil which is specifically designed to perform the whole body NMR imaging of small animal at 1.5T MRI systems. The designed RF coil contains the saw tooth shaped pattern as the leg conductors. The magnetic field produced at 63.85 MHz resonance frequency by this designed saw toothed shape leg pattern RF coil is significantly stronger than the magnetic field produced by a conventional straight leg band pass type birdcage coil designed with the same dimension. A full wave 3D electromagnetic simulation is carried out to optimize the RF coil dimensions, capacitor values and to study the RF coil electromagnetic characteristics.

Summary form only given. This paper presents a direct conversion Korean standard T-DMB SoC tuner using a 65nm low power CMOS technology with the best feature of size, power and BoM ever reported. A digital F/E enhanced function is implemented to reduce analog signal processing empowered by oversampled A/D converter, digital channel selection filter and lots of digital calibration blocks. And the designed LNA excludes all required inductors. Thus high voltage gain and low current consumption are achieved due to their high Q factor. A single-to-differential signaling down-conversion mixer is also announced which has well balanced output characteristic. A DC/DC converter is adopted as well for the further low power consuming. The tunable clock frequency scheme of DC/DC buck converter can prevent a degradation of sensitivity performances which is planed value to escape the channel center frequency. This reported SoC tuner consumes only 28mA at maximum gain mode. And -103.5dBm of sensitivity and 48dBc of N±1 adjacent-channel selectivity are achieved also with only 5 external LC components. This SoC occupies 2.5×2.5mm2 die and WLCSP chip size.

This paper proposed a method to classify textural documents using specified n-gram data set. Human lives in the world where web documents have a great potential and the amount of valuable information has been consistently growing over the year. There is a problem that finding relevant web documents corresponding to what users want is more difficult due to the huge amount of web size. For this reason, many approaches have been suggested to overcome this obstacle. The most important task is classifying textural documents into predefined categories. Over the years, many statistical approaches were introduced though, no one can find perfect solution yet. In this paper, we suggest a method for textural document classification using n-gram model. The n-gram data frequency has a great potential to find similarities between documents. For this reason, we construct our own n-gram data sets from research papers. If an unknown document comes to the system, the system will extract n-grams from the given unknown documents. After this step, n-grams from unknown document and n-grams in previous data sets will be compared by proposed similarity measurement. The precision rate of this method comes to 86%.

A simple transmission power control technique has been proposed and demonstrated to realize an energy efficient sensor network over existing CATV infrastructures. The sensor network has been implemented by using the wasted bandwidth of the coaxial cables of a conventional CATV network and supports automatic transmission power control to enhance the network lifetime. The transmission power control technique can enhance the lifetime of sensor network by a factor of 1.7 times with a 42% improved power saving efficiency.

As the use of the internet increases, the distribution of web based malicious code has also vastly increased. By inputting malicious code that can attack vulnerabilities, it enables one to perform various illegal acts, such as SQL Injection and Cross Site Scripting (XSS). Furthermore, an extensive amount of computer, network and human resources are consumed to prevent it. As a result much research is being done to prevent and detecting malicious code. Currently, research is being done on readable sentences which do not use proper grammar. This type of malicious code cannot be classified by previous vocabulary analysis or document classification methods. This paper proposes an approach that results in an effective n-gram feature extraction from malicious code for classifying executable as malicious or benign with the use of Support Vector Machines (SVM) as the machine learning classifier.

The CATV infrastructure has been deployed in most houses and buildings and the coaxial cables of the CATV infrastructure usually can provide sufficient bandwidth to accommodate other services as well as CATV service. We have proposed and demonstrated a novel remotely powered sensor network over the existing CATV infrastructure composed of coaxial cables, splitters and so on. The proposed sensor network has been implemented by using the wasted bandwidth of the coaxial cable (VHF and UHF bands) of the conventional CATV network without any change of the existing infrastructure. Furthermore, it supports a convenient remote power feeding from a central node to end nodes (sensor nodes) by using coaxial cable. We have developed transceiver for the wired sensor network matched the characteristics impedance of the coaxial cable of the CATV network. We also have developed protocol stack of the transceiver to interface with wired cable instead of air and to support the remote power feeding to the end nodes. We have confirmed the performance of the proposed sensor network by measuring the packet error rate (PER) for various data rates when the end nodes were remotely powered. The maximum transmission distance between the central node and the end node of the wired CATV network was about 265 m when the 128 sensor nodes were joined the network at the operating data rate of 250 kb/s.

A novel sensor network by using the coaxial cable infrastructure of the CATV network has been demonstrated. The sensor network has been implemented by using the wasted bandwidth of the coaxial cable (900-MHz band) of the CATV network without any change of the existing infrastructure. We have confirmed the performance of the sensor network by measuring the packet error rate (PER) for various data rates and verified that there was no sensitivity degradation due to the transmission over the CATV in frastructure. The maximum transmission distance between the coordinate node and the sensor node of the network was about 364 m w hen 128 sensor nodes were joined the sensor network at the operating data rate of 256 kb/s. The sensor network over the CATV infrastructure inherently guarantees a reliable networking between the nodes with excellent securities. Furthermore it is free from the interferences from other wireless services, which is especially useful in massive wireless environments such as in house or building.

ZigBee technology is being embedded in a range of applications up to smart energy, healthcare, and telecommunication services. In this paper, we present a voice transmission system, one of telecommunication value-added services, based on the low-rate ZigBee networks. We design a model to perform a sensor role as a member of ZigBee networks in addition to providing the cost-effective voice transmission function.

Digital polar transmitter is suitable for high integrated and power efficient implementation. In order to support high data rate communication systems, the digital polar transmitter need a high performance phase modulator with high resolution and sub-nanoseconds settling time. In this paper, as a phase modulator, a digital-to-time converter (DTC) with high resolution and short settling time is proposed. The DTC adopts serial delay architecture, and can be used in high data-rate and gigahertz wireless communication system. It exploits inverters with different delays to generate small phase differences while maintaining the sub-nanoseconds settling time. The DTC implemented in the TSMC 0.18 um CMOS process achieves the phase resolution of 0.78 ps and relative settling time of 0.7 ns with 2.5 GHz clock while consuming 0.8 mW of power.

In this paper, the structure of a trellis-coded 3-dimensional orthogonal frequency division multiplexing (3-D OFDM) is proposed and its error performance in additive white Gaussian channel is analyzed. We present the set-partitioning of a 3-D 8-ary constellation for trellis coding. As a result, the trellis-coded 3-D OFDM system has around 6 dB coding gain over an uncoded one when an 8-ary constellation is exploited. And it also has around 3 dB better symbol error probability as compared to the uncoded system when a 4-ary constellation is employed. Thus, the proposed trellis-coded 3-D OFDM may be appropriate for an application in the high-quality wireless communication system for the next generation.

In this paper, a three-dimensional (3-D) orthogonal frequency division multiplexing (OFDM) is introduced. In the new OFDM, a 3-D signal mapper and 2-D inverse discrete Fourier transform are used to allocate 3-D signals to OFDM subchannels and to modulate the signals, respectively. The minimum Euclidean distance of the 3-D signal mapper is much farther than that of the 2-D mapper if both mappers are normalized to have the same average power. As a result, the proposed OFDM has much improved error performance as compared with the conventional scheme.

Nowadays, travel information is increasing to appeal the tourists on the web. Although there are numerous information provided on the web, the user gets puzzled in finding accurate information. In order to solve these web problems, the concept of semantic web comes into existence to have communication between human and computer.In this paper, we propose intelligent recommendation system based on Jeju travel ontology. The proposed system can recommend the tourist more intelligent information using properties, relationships of travel ontology. Next, the system is responsible for finding personalized attractions and plotting location of traveler on the AlMap.

A 13.56MHz RFID transceiver SoC supporting ISO/IEC 14443 type A/B, 15693, 18000-3 is proposed in this paper. Before designing the circuit, standard analysis is processed. And also, we did a board level measurement for implementation to a chip level. That is, A RFID transceiver test board using commercial components was configured and tested. Using this test board, we can confirm some considerations for implementing designed transceiver. Based on the test results and considerations, the multi standard 13.56MHz RFID transceiver SoC was designed and fabricated using Chartered 0.18um CMOS technology. Through the chip measurement, designed transceiver system can be operated in multiple standard conditions.

Zigbee standard includes no technical references for voice communication. Since the Zigbee standard has very limited size of data payload, high compression with good waveform recovery capability is essential to realize voice communication. This paper presents a voice coding scheme based on discrete wavelet transform (DWT) for Zigbee. Theoretical analysis and simulation verify that 2-stage DWT-based scheme is considered as a feasible method for voice communication over Zigbee networks.

A HF (13.56 MHz) RFID receiver architecture SoC (System on Chip) is proposed. The receiver can be used in the standards of ISO/IEC 14443 type A/B, 15693, and 18000-3. Before designing the circuit, standard analysis is processed. And also, we did a previous measurement for preparing implementation as a chip level. That is, a RFID transceiver test board using commercial components was configured and tested. Through the board experiments, we checked the possibilities of operation of designed receiver. Based on the experiment results, the multi-standard 13.56 MHz RFID receiver SoC was designed and fabricated using TSMC 0.18 um CMOS technology. The test results show that designed receiver system as a chip level can be operated properly in multiple standard conditions.

We analyzed 13.56 MHz RFID standards and obtained specifications of transmitting section and receiving section of the RFID reader. With these analyses, we proposed a multistandard 13.56 MHz RFID reader system. For supporting multistandard in 13.56 MHz RFID system, circuits for controlling modulation index and power emitted to the tag are added in transmitter. In order to accept to various response signal levels from the tag, a certain voltage is applied to the receiver after eliminating DC voltage at VGA input and internal reference voltage is set in comparator. From measurement using commercial tags and additional FPGA board, we can conclude that this transceiver chip is compatible with mentioned standards.

The ultimate aim of this paper is for semantic information retrieval. Especially, we concentrate on measure of concept similarity. There are 9 kinds of relation (arc) in WordNet to define concepts and we have a motive from that a value of each arc is different up to kind of relation. So, this paper first makes a fundamental for the value of relation between concepts. And we measure the arc-value based on the fundamental and calculate concept similarity using the value.

It is expected that the intelligent management system will be able to provide intelligent building services based on context-awareness mechanism, which consists of a sensor platform, a context-aware framework and an intelligent agent. The sensor platform collects raw data and sends them to a context-aware framework which perceives the residents and a building's context. The intelligent agent triggers an automatic services according to the information based on the sensed situation of the context-aware framework. We designed and implemented the intelligent visitor care system based on this context-awareness technology, which minimizes residents' interventions and maximizes functionality autonomy of systems. Also we suggested system architecture and the flows for the proposed system. In this article we discuss interaction issue about conflict and interference between various context information and service in the building environment. Context information conflict arises when deciding service through various sensing information. Service interaction generated when a service is applied to different controls at the same time, for same device. Also we proposed a model to implement the sensing information management (SIM) module which can gather and optimized information through interaction within sensed information and adapts it's to the context-aware services.