• Journal of Power Electronics
• /
• v.19 no.4
• /
• pp.956-967
• /
• 2019

This paper introduces a virtual signal injected maximum torque per ampere (MTPA) control strategy for direct-torque-controlled five-phase interior permanent magnet synchronous motor (IPMSM) drives. The key of the proposed method is that a high frequency signal is injected virtually into the stator flux linkage. Then the responding stator current is calculated and regulated to compensate the amplitude of the flux linkage. This is done according to the relationship between the stator current and the stator flux linkage. Since the proposed method does not inject any real signals into the motor, it does not cause any of the problems associated with high-frequency signals, such as additional copper loss and extra torque ripple. Simulation and experimental results are offered to verify the effectiveness of the proposed method.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.4
• /
• pp.1-9
• /
• 2019

LRR(Loose Round Robin) warp scheduling policy for GPU architecture results in high warp-level parallelism and balanced loads across multiple warps. However, traditional LRR policy makes multiple warps execute long latency operations at the same time. In cases that no more warps to be issued under long latency, the throughput of GPUs may be degraded significantly. In this paper, we propose a new warp scheduling policy which utilizes latency hiding, leading to more utilized memory resources in high performance GPUs. The proposed warp scheduler prioritizes memory instruction based on GTO(Greedy Then Oldest) policy in order to provide reduced memory stalls. When no warps can execute memory instruction any more, the warp scheduler selects a warp for computation instruction by round robin manner. Furthermore, our proposed technique achieves high performance by using additional information about recently committed warps. According to our experimental results, our proposed technique improves GPU performance by 12.7% and 5.6% over LRR and GTO on average, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.12
• /
• pp.1956-1959
• /
• 2021

AIS(Automatic Identification System) provides navigational information including identification, position, a ship's course and status to ground and other vessels. To obtain AIS Marine Equipment Approval Service, various requirements are required and meet the requirements International Standards. However, most of the requirements are to identify essential functions, response time, hardware requirements, and communication protocols of AIS. The requirements for the quality of SW are not sufficient or detailed, and the weight is relatively low. As role of SW grows and types become more diverse, AIS SW quality inspection is essential. In this paper, We apply eight-quality characteristics of ISO/IEC 25023 standard to improve SW coverage quality of AIS. Suggest additional AIS SW requirements based on the eight quality characteristics of ISO/IEC 25023 standard.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.10
• /
• pp.1567-1570
• /
• 2022

This paper, we presents a RF protection technique of antenna switch by improving the power handling capability in worst case environment mode for mobile phone applications without critical payment of circuit performances such as insertion loss, isolation and ACBV (AC breakdown voltage). By applying a additional capacitive path located in front of the antenna in cell-phone, it performs the effective reduction of input power in high voltage standing wave ratio (VSWR) condition. Under the all-path off condition which causes a high VSWR, it achieved 37.7dBm power handling level as high as 5.7dB compared to that of conventional one at 2GHz. In addition, insertion loss and isolation performances were 0.31dB and 42.72dB at 2 GHz, respectively which were almost similar to that of the conventional circuit. The proposed antenna switch was fabricated in 130nm CMOS SOI technology.

• Asia Marketing Journal
• /
• v.21 no.1
• /
• pp.1-21
• /
• 2019

Online platforms often provide rating information to customers to relieve the uncertainty they encounter when purchasing experience goods. Prior research has focused mostly on the roles of rating volume and the valence of an average rating among the various possibilities. However, less frequently investigated is the effect of rating dispersion, which may be associated with uncertainty regarding how well a product fits a customer's personal preference, on new trials of experience goods. In this study, we examine the effect of rating dispersion on new trials of experience goods and identify the conditions which intensify or reduce the effect. Empirical analyses of movie box office sales data and online rating data reveal three interesting findings. First, movie sales decrease as movie ratings become increasingly dispersed. Second, the negative effect of rating dispersion on movie sales is more pronounced with more rating volume. Third, this negative effect weakens when additional information about a movie is available (i.e., higher average rating, greater star power, and time since its release). We discuss the academic and practical implications of our findings.

• International Journal of Computer Science & Network Security
• /
• v.23 no.1
• /
• pp.164-168
• /
• 2023

As our community has become increasingly dependent on technology, security has become a bigger concern, which makes it more important and challenging than ever. security can be enhanced with encryption as described in this paper by combining RC6 symmetric cryptographic algorithms with RSA asymmetric algorithms, as well as the Vigenère cipher, to help manage weaknesses of RC6 algorithms by utilizing the speed, security, and effectiveness of asymmetric algorithms with the effectiveness of symmetric algorithm items as well as introducing classical algorithms, which add additional confusion to the decryption process. An analysis of the proposed encryption speed and throughput has been conducted in comparison to a variety of well-known algorithms to demonstrate the effectiveness of each algorithm.

• International conference on construction engineering and project management
• /
• 2015.10a
• /
• pp.637-638
• /
• 2015

There has been growing interests in life-cycle project management in the construction industry. A lot of attention is given to Building Information Modeling (BIM) which stores and uses a variety of construction information for the life cycle of project management. However, due to the additional workload arising from BIM, its expected effects versus its input costs are still under discussion in practice. As an attempt to address this issue, one of previous studies suggested an automated linking process by developing Standard Classification Numbering System (SCNS) and Geometry Breakdown Structure (GBS) to enhance the efficiency of integration process of BIM objects, cost, and schedule. Though SCNS and GBS facilitates identifying all different dataset, making object sets and linking schedule activities still needs to be manually done without having an automated tool. In this context, the purpose of this paper is to develop and validate a fully automated integration system for 3D-objects, cost, and schedule. A prototype system for single family homes (Hanok) was developed and tested in order to verify its efficiency.

• The Journal of Korea Robotics Society
• /
• v.19 no.2
• /
• pp.196-202
• /
• 2024

The ability to understand given environments and plan a sequence of actions leading to goal state is crucial for personal service robots. With recent advancements in deep learning, numerous studies have proposed methods for state representation in planning. However, previous works lack explicit information about relationships between objects when the state observation is converted to a single visual embedding containing all state information. In this paper, we introduce graph-based state representation that incorporates both object and relationship features. To leverage these advantages in addressing the task planning problem, we propose a Graph Neural Network (GNN)-based subgoal prediction model. This model can extract rich information about object and their interconnected relationships from given state graph. Moreover, a search-based algorithm is integrated with pre-trained subgoal prediction model and state transition module to explore diverse states and find proper sequence of subgoals. The proposed method is trained with synthetic task dataset collected in simulation environment, demonstrating a higher success rate with fewer additional searches compared to baseline methods.

• Journal of the Chungcheong Mathematical Society
• /
• v.37 no.2
• /
• pp.57-66
• /
• 2024

In this paper, we study how the Hilbert polynomial, associated with a reduced closed subscheme X of codimension 2 in ℙ^N, reveals geometric information about X. Although it is known that the Hilbert polynomial can tell us about the scheme's degree and arithmetic genus, we find additional geometric information it can provide for smooth varieties of codimension 2. To do this, we introduce the concept of Gotzmann coefficients, which helps to extract more information from the Hilbert polynomial. These coefficients are based on the binomial expansion of values of the Hilbert function. Our method involves combining techniques from initial ideals and partial elimination ideals in a novel way. We show how these coefficients can determine the degree of certain geometric features, such as the singular locus appearing in a generic projection, for smooth varieties of codimension 2.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2024.05a
• /
• pp.692-695
• /
• 2024

With the recent advancements in artificial intelligence (AI), the performance of deep learning-based audio deepfake technology has significantly improved. This technology has been exploited for criminal activities, leading to various cases of victimization. To prevent such illicit outcomes, this paper proposes a deep learning-based audio deepfake detection model. In this study, we propose CoNSIST, an improved audio deepfake detection model, which incorporates three additional components into the graph-based end-to-end model AASIST: (i) Squeeze and Excitation, (ii) Positional Encoding, and (iii) Reformulated HS-GAL, This incorporation is expected to enable more effective feature extraction, elimination of unnecessary operations, and consideration of more diverse information, thereby improving the performance of the original AASIST. The results of multiple experiments indicate that CoNSIST has enhanced the performance of audio deepfake detection compared to existing models.