• 전기학회논문지
• /
• 제66권1호
• /
• pp.40-47
• /
• 2017

In this paper, a small signal model for grid-connected inverter with unipolar pulse width modulation method is presented. Small-signal analysis allows to predict the stability and dynamics of the inverter. To regulate output voltage and to achieve power factor correction, inverter has two control loops. Loop gains are useful to identify the stability for multi-loop controlled system. Based on small-signal model, controllers are designed to improve audio susceptibility and output impedance characteristics. Proposed small-signal model and controllers are verified by PSIM simulation and experiments.

• Journal of Information Processing Systems
• /
• 제14권1호
• /
• pp.218-227
• /
• 2018

Vocal effort detection is important for both robust speech recognition and speaker recognition. In this paper, the spectral information entropy feature which contains more salient information regarding the vocal effort level is firstly proposed. Then, the model fusion method based on complementary model is presented to recognize vocal effort level. Experiments are conducted on isolated words test set, and the results show the spectral information entropy has the best performance among the three kinds of features. Meanwhile, the recognition accuracy of all vocal effort levels reaches 81.6%. Thus, potential of the proposed method is demonstrated.

• Journal of Power Electronics
• /
• 제13권6호
• /
• pp.1000-1007
• /
• 2013

This paper proposes a sliding-mode-based direct power control (DPC) method in a three-phase boost rectifier without the use of a voltage sensor. This sliding-mode-based DPC is used to improve transient-state response characteristics. This DPC can eliminate voltage sensors by calculating a voltage using a sensorless method, thus considerably reducing cost. This DPC first presents an effective algorithm that does not significantly affect the previous performance and does not need a voltage sensor. Thereafter, the effectiveness of the algorithm is verified by simulations and experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제6권12호
• /
• pp.3197-3218
• /
• 2012

Compared with traditional itinerary planning, intention-oriented itinerary recommendations can provide more flexible activity planning without requiring the user's predetermined destinations and is especially helpful for those in unfamiliar environments. The rank and classification of points of interest (POI) from location-based social networks (LBSN) are used to indicate different user intentions. The mining of vehicles' physical trajectories can provide exact civil traffic information for path planning. This paper proposes a POI category-based itinerary recommendation framework combining physical trajectories with LBSN. Specifically, a Voronoi graph-based GPS trajectory analysis method is utilized to build traffic information networks, and an ant colony algorithm for multi-object optimization is implemented to locate the most appropriate itineraries. We conduct experiments on datasets from the Foursquare and GeoLife projects. A test of users' satisfaction with the recommended items is also performed. Our results show that the satisfaction level reaches an average of 80%.

• Journal of Information Processing Systems
• /
• 제13권6호
• /
• pp.1467-1486
• /
• 2017

Fuzzy co-clustering is sensitive to noise data. To overcome this noise sensitivity defect, possibilistic clustering relaxes the constraints in FCM-type fuzzy (co-)clustering. In this paper, we introduce a new possibilistic fuzzy co-clustering algorithm based on information bottleneck (ibPFCC). This algorithm combines fuzzy co-clustering and possibilistic clustering, and formulates an objective function which includes a distance function that employs information bottleneck theory to measure the distance between feature data point and feature cluster centroid. Many experiments were conducted on three datasets and one artificial dataset. Experimental results show that ibPFCC is better than such prominent fuzzy (co-)clustering algorithms as FCM, FCCM, RFCC and FCCI, in terms of accuracy and robustness.

• Journal of Power Electronics
• /
• 제19권6호
• /
• pp.1449-1457
• /
• 2019

This paper presents two voltage domain stacking topologies for powering integrated digital loads such as multiprocessors or 3D integrated circuits. Pairs of loads and capacitors are connected in series to form a stack of voltage domains. The voltage is balanced by switching the position of the capacitors in one case and the position of the loads in the other case. This method makes the voltage regulation robust to large differential load power consumption. The first configuration can be named the load stacking topology. The second configuration can be named the capacitor stacking topology. This paper aims at proposing and comparing these two topologies. Models of both topologies and a switching scheme are presented. The behavior, control scheme, losses and overall performance are analyzed and compared theoretically in simulation and experiments. Experimental results show that the capacitor stacking topology has better performance with a 30% voltage ripple reduction.

• Quantitative Bio-Science
• /
• 제37권2호
• /
• pp.81-89
• /
• 2018

It is commonplace that high false detection rates interfere with immediate vision-based fire monitoring system. To circumvent this challenge, we propose a fire detection algorithm that can accommodate color variations of RGB in temporal domain, aiming at reducing false detection rates. Despite interrupting images (e.g., background noise and sudden intervention), the proposed method is proved robust in capturing distinguishable features of fire in temporal domain. In numerical studies, we carried out extensive real data experiments related to fire detection using 24 video sequences, implicating that the propose algorithm is found outstanding as an effective decision rule for fire detection (e.g., false detection rate <10%).

• 한국컴퓨터정보학회:학술대회논문집
• /
• 한국컴퓨터정보학회 2019년도 제60차 하계학술대회논문집 27권2호
• /
• pp.385-386
• /
• 2019

This paper proposes a fusion model based on Long-Short Term Memory networks (LSTM) and CNN deep learning methods, and applied to multi-category news datasets, and achieved good results. Experiments show that the fusion model based on deep learning has greatly improved the precision and accuracy of text sentiment classification.

• Journal of Information Processing Systems
• /
• 제15권1호
• /
• pp.91-99
• /
• 2019

An innovative tone modeling framework based on deep neural networks in tone recognition was proposed in this paper. In the framework, both the prosodic features and the articulatory features were firstly extracted as the raw input data. Then, a 5-layer-deep deep belief network was presented to obtain high-level tone features. Finally, support vector machine was trained to recognize tones. The 863-data corpus had been applied in experiments, and the results show that the proposed method helped improve the recognition accuracy significantly for all tone patterns. Meanwhile, the average tone recognition rate reached 83.03%, which is 8.61% higher than that of the original method.

• International Journal of Computer Science & Network Security
• /
• 제22권6호
• /
• pp.139-144
• /
• 2022

Technological advancements taken the health care industry by a storm by embedding sensors in human body to measure their vitals. These smart solutions provide better and flexible health care to patients, and also easy monitoring for the medical practitioners. However, these innovative solutions provide their own set of challenges. The major challenge faced by embedding sensors in body is the issue of lack of infinite energy source. This work presents a meta-heuristic based routing model using modified PSO, and adopts an energy harvesting scheme to improve the network lifetime. The routing process is governed by modifying the fitness function of PSO to include charge, temperature and other vital factors required for node selection. A reactive routing model is adopted to ensure reliable packet delivery. Experiments have been performed and comparisons indicate that the proposed Energy Harvesting and Modified PSO (EHMP) model demonstrates low overhead, higher network lifetime and better network stability.