• Proceedings of the Korean Vacuum Society Conference
• /
• 2010.02a
• /
• pp.63-63
• /
• 2010

Ability to transport extracted carriers from NQDs is essential for the development of most NQD based applications. Strategies to facilitate carrier transport while preserving NQDs' optical characteristics include: 1) Fabricating neat films of NQDs with modified surfaces either by adapting series of ligands with certain limitations or by applying physical processes such as heat annealing 2) Coupling of NQDs to one-dimensional nanostructures such as single walled carbon nanotubes (SWNTs) or various types of nanowires. NQD-nanowire hybrid nanostructures are expected to facilitate selective wavelength absorption, charge transfer to 1-D nanostructures, and efficient carrier transport. Even with the vast interests in using NQD-SWNT hybrid materials in optoelectric applications, still, no reports so far have clearly elucidated the optoelectric behavior when they were assembled on the FET mainly because the complexity involving in both components in their preparation and characterization. We have monitored the optical properties of both components (NQDs, SWNTs) from the synthesis, to the assembly, and to the device. More importantly, by using pyridine molecules as a linker to non-covalently attach NQDs to SWNTs, we were able to assemble NQDs on SWNTs with precise density control without harming their electronic structures. Furthermore, by measuring electrical signals from the fabricated aligned SWNTs-FET using dielectrophoresis (DEP), we were able to elucidate the charge transfer mechanism.

• The Korean Journal of Applied Statistics
• /
• v.34 no.3
• /
• pp.329-345
• /
• 2021

Recommender systems use data from customers to suggest personalized products. The recommender systems can be categorized into three cases; collaborative filtering, contents-based filtering, and hybrid recommender system that combines the first two filtering methods. In this work, we introduce and compare deep learning-based recommender system using autoencoder. Autoencoder is an unsupervised deep learning that can effective solve the problem of sparsity in the data matrix. Five versions of autoencoder-based deep learning models are compared via three real data sets. The first three methods are collaborative filtering and the others are hybrid methods. The data sets are composed of customers' ratings having integer values from one to five. The three data sets are sparse data matrix with many zeroes due to non-responses.

• Advances in nano research
• /
• v.13 no.2
• /
• pp.165-174
• /
• 2022

In the present study, a hybrid model of artificial neural network (ANN) and internet of things (IoT) is proposed to overcome the difficulties in deriving governing equations and numerical solutions of the dynamical behavior of the nano-systems. Nano-structures manifest size-dependent behavior in response to static and dynamic loadings. Nonlocal and length-scale parameters alongside with other geometrical, loading and material parameters are taken as input parameters of an ANN to observe the natural frequency and damping behavior of micro sensors made from nanocomposite material with piezoelectric layers. The behavior of a micro-beam is simulated using famous numerical methods in literature under base vibrations. The ANN was further trained to correlate the output vibrations to the base vibration. Afterwards, using IoT, the electrical potential conducted in the sensors are collected and converted to numerical data in an embedded mini-computer and transferred to a server for further calculations and decision by ANN. The ANN calculates the base vibration behavior with is crucial in mechanical systems. The speed and accuracy of the ANN in determining base excitation behavior are the strengths of this network which could be further employed by engineers and scientists.

• Journal of Korea Society of Industrial Information Systems
• /
• v.15 no.3
• /
• pp.1-9
• /
• 2010

In recent year, the cores of ubiquitous environment are sensor networks and RFID systems. RFID system transmits the electronic information of the tag to the reader by using RF signal. Collision happens in RFID system when there are many matched tags, and it degrades the tag identification performance. Such a system needs algorithm which is able to arbitrate tag collision. This paper suggests a hybrid method which reduces collision between the tags, and can quickly identify the tag. The proposed method operates based on certainty, which takes an advantage of tree based algorithm, and to reduce collision it selects transmission time slot by using tag ID. The simulation results show the suggested method has higher performance in the number of queries and collision compared to other tree based and hybrid algorithms.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.9 no.5
• /
• pp.299-305
• /
• 2014

In this paper, a simple version of the hybrid navigation system using Kalman filter is proposed. The implemented hybrid navigation system is composed of a GPS to measure the position and the velocity, and a IMU(inertial measurement unit) to measure the acceleration and the posture of a mobile robot. A discrete Kalman filter is applied to provide the position of the robot by fusing both of the sensor data. When GPS signal is available, the navigation system estimates the position of the robot from the Kalman filter using position and velocity from GPS, and acceleration from IMU. During the interval until next GPS signal arrives, the system calculates the position of the robot using acceleration from IMU and velocity obtained at the previous step. Performance of the navigation system is verified by comparing the real path and the estimated path of the mobile robot. From experiments, we conclude that the navigation system is acceptable for the mobile robot.

• International journal of advanced smart convergence
• /
• v.8 no.4
• /
• pp.34-39
• /
• 2019

Millimeter-wave (mmWave) and Non-orthogonal multiple access (NOMA) are expected to be the major techniques that lead to the next generation wireless communication. NOMA provides a high spectrum efficiency by sharing of spatial resources among users in the same frequency band. Meanwhile, millimeter-wave gives a huge underutilized bandwidth at extremely high frequency band (EHF) which covers 30GHz to 300GHz. These techniques have been proven in several recent literatures to achieve high data rates. The combination of NOMA and millimeter-wave techniques further improves average sum capacities, as well as reduces the interference compared to conventional wireless communication systems. In this paper, we focus on hybrid NOMA system working in millimeter-wave frequency. We propose a clustering algorithm used for a hybrid NOMA scheme to optimize the usage of wireless resources. The proposed clustering algorithm adds several conditions in grouping users and defining clusters to increase the probability of the successful superposition decoding process. The performance of the proposed clustering algorithm is investigated in hybrid NOMA system and compared with the conventional orthogonal multiple access (OMA) scheme.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.20 no.1
• /
• pp.149-153
• /
• 2020

This paper presents a new page placement policy for DRAM/NVRAM hybrid main memory in smartphones. Unlike previous studies on hybrid memory systems, this paper performs the placement of pages based on the offline analysis of memory access behaviors as smartphone's memory accesses are skewed to a certain address ranges, which is consistent regardless of smartphone applications, specially for write operations. Thus, we aim at reducing the write traffic to NVRAM by the offline analysis results. Experimental results show that the proposed policy reduces the write traffic to NVRAM by 61% on average without performance degradations.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.1
• /
• pp.21-27
• /
• 2020

In this paper, a hybrid scheduling algorithm is proposed for CMS(Combat Management System) to improve QoS(Quality of Service) based on DWDRR(Dynamic Weighted Deficit Round Robin) and priority-based scheduling method. The main proposed scheme, DWDRR is method of packet transmission through giving weight by traffic of queue and priority. To demonstrate an usefulness of proposed algorithm through simulation, efficiency in special section of the proposed algorithm is proved. Therefore, We propose hybrid algorithm between existing algorithm and proposed algorithm. Also, to prevent frequent scheme conversion, a hysteresis method is applied. The proposed algorithm shows lower packet loss rate and delay in the same traffic than existing algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.3
• /
• pp.1035-1056
• /
• 2015

The efficiency of live Peer-to-Peer (P2P) streaming protocols depends on the appropriateness and the management abilities of their underlying overlay multicast. While a tree overlay structure confines transmission delays efficiently by maintaining deterministic delivery paths, an overlay mesh structure provides adequate resiliency to peers dynamics and easy maintenance. On the other hand, content freshness, playback fluidity and streaming continuity are still challenging issues that require viable solutions. In this paper, we propose a Hybrid Live P2P Streaming Protocol (HLPSP) based on a hybrid overlay multicast that integrates the efficiency of both the tree and mesh structures. Extensive simulations using OMNET++ are conducted to investigate the efficiency of HLPSP in terms of relevant performance metrics, and position HLPSP with respect to DenaCast the enhanced version of the well-known CoolStreaming protocol. Simulation results show that HLPSP outperforms DenaCast in terms of startup delay, end-to-end delay, play-back delay and data loss.

• Smart Structures and Systems
• /
• v.14 no.6
• /
• pp.1081-1103
• /
• 2014

Real-time hybrid simulation (RTHS) has emerged as an important tool for testing large and complex structures with a focus on rate-dependent specimen behavior. Due to the real-time constraints, accurate dynamic control of servo-hydraulic actuators is required. These actuators are necessary to realize the desired displacements of the specimen, however they introduce unwanted dynamics into the RTHS loop. Model-based actuator control strategies are based on linearized models of the servo-hydraulic system, where the controller is taken as the model inverse to effectively cancel out the servo-hydraulic dynamics (i.e., model-based feedforward control). An accurate model of a servo-hydraulic system generally contains more poles than zeros, leading to an improper inverse (i.e., more zeros than poles). Rather than introduce additional poles to create a proper inverse controller, the higher order derivatives necessary for implementing the improper inverse can be calculated from available information. The backward-difference method is proposed as an alternative to discretize an improper continuous time model for use as a feedforward controller in RTHS. This method is flexible in that derivatives of any order can be explicitly calculated such that controllers can be developed for models of any order. Using model-based feedforward control with the backward-difference method, accurate actuator control and stable RTHS are demonstrated using a nine-story steel building model implemented with an MR damper.