• Journal of Korean Institute of Industrial Engineers
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• v.11 no.2
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• pp.101-111
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• 1985

This study deals with problems of estimating the availability of the multi-module software systems. The result presented in this paper is an extension of our previous paper (2) entitled "A modified Markov model for the estimation of computer software performance". The extension is made by assuming that (1) the software system consists of R statistically independent software modules; (2) no failure occurrence while the process is in transition between software modules.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.9
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• pp.5652-5659
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• 2014

The purpose of this study was to introduce a software task processing evaluation model that considers the following situations: i) a software system is integratedly composed of several number of modules, ii) each modules has its corresponding module task, iii) all module tasks are tested simultaneously, and iv) the processing times of the module tasks are mutually dependent. The software task completion probability with the module dependency was derived using the joint distribution function of Farlie [11]. The results showed that the task completion probability of software increases with increasing module dependency parameter.

• Communications for Statistical Applications and Methods
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• v.19 no.4
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• pp.571-577
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• 2012

Modules that consist of software are respectively coded in the early development phase and the modules are unified as a software. After unification, the software is repeatedly tested with a given taskset (the set of module tasks that are tested simultaneously) until a required performance level is satisfied. In this paper, we expand the one-module software debugging model of Jang and Lee (2011) to a multi-module debugging model and derive the taskset completion probability and the mean of the completed tasksets under the assumption that the processing times of module tasks given in a taskset are mutually dependent.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2458-2482
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• 2023

Medical image segmentation techniques based on convolution neural networks indulge in feature extraction triggering redundancy of parameters and unsatisfactory target localization, which outcomes in less accurate segmentation results to assist doctors in diagnosis. In this paper, we propose a multi-level semantic-rich encoding-decoding network, which consists of a Pooling-Conv-Former (PCFormer) module and a Cbam-Dilated-Transformer (CDT) module. In the PCFormer module, it is used to tackle the issue of parameter explosion in the conservative transformer and to compensate for the feature loss in the down-sampling process. In the CDT module, the Cbam attention module is adopted to highlight the feature regions by blending the intersection of attention mechanisms implicitly, and the Dilated convolution-Concat (DCC) module is designed as a parallel concatenation of multiple atrous convolution blocks to display the expanded perceptual field explicitly. In addition, MultiHead Attention-DwConv-Transformer (MDTransformer) module is utilized to evidently distinguish the target region from the background region. Extensive experiments on medical image segmentation from Glas, SIIM-ACR, ISIC and LGG demonstrated that our proposed network outperforms existing advanced methods in terms of both objective evaluation and subjective visual performance.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.4
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• pp.622-629
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• 2011

In this paper, you can see the structure of data slaving software module that is in use on flight test and result of the test with the slaving. The data slaving software module has many functions, data slaving for various instrumentation systems(instrumentation radars, telemetry systems for missile, aircraft and so on), setting some slaving group for multi-target, communicating with the instrumentation systems in a far away site and sending a specific value as slaving data. This fits the requests for flight test that is being performed and improves performance of the instrumentation systems.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.1
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• pp.1-12
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• 2021

Due to the Global Navigation Satellite System (GNSS) modernization, the recently launched GNSS satellites transmit signals at various frequency bands of L1, L2 and L5. Considering the Korea Positioning System (KPS) signal and other GNSS augmentation signals in the future, there is a high probability of applying more complex communication techniques to the new GNSS signals. For the reason, GNSS receivers based on flexible Software Defined Radio (SDR) concept needs to be developed to evaluate various experimental communication techniques by accessing each signal processing module in detail. In this paper, we introduce a multi-constellation (GPS/Galileo/BeiDou) multi-band (L1/L2/L5) SDR by utilizing Ettus USRP N210. The signal reception module of the developed SDR includes down-conversion, analog-to-digital conversion, signal acquisition, and tracking. The down-conversion module is designed based on the super-heterodyne method fitted for MHz sampling. The signal acquisition module performs PRN code generation and FFT operation and the signal tracking module implements delay/phase/frequency locked loops only by software. In general, it is difficult to sample entire main lobe components of L5 band signals due to their higher chipping rate compared with L1 and L2 band signals. Experiment result shows that it is possible to acquire and track the under-sampled signals by the developed SDR.

• Journal of Information Processing Systems
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• v.8 no.1
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• pp.21-54
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• 2012

As we know every software development process is pretty large and consists of different modules. This raises the idea of prioritizing different software modules so that important modules can be tested by preference. In the software testing process, it is not possible to test each and every module regressively, which is due to time and cost constraints. To deal with these constraints, this paper proposes an approach that is based on the fuzzy multi-criteria approach for prioritizing several software modules and calculates optimal time and cost for software testing by using fuzzy logic and the fault tolerance approach.

• The KIPS Transactions:PartA
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• v.9A no.4
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• pp.451-458
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• 2002

In this article, we present, design, and implement a software and hardware for an embedded RAID system. The merits and drawbacks of our system are presented by performance evaluation. The proposed hardware system consists of three fibre channel controllers for the interface with fibre channel disks and hosts. Embedded Linux in which a RAID software is implemented is ported to the hardware. A SCSI target mode device driver and a target mode SCSI module are designed for that our RAID system is considered as a block device to a host computer. Linux Multi-device is used as RAID functions of this system. A data cache module is implemented for high performance and the interconnection between Linux Multi-device and the target mode SCSI module. The RAID 5 module of Multi-device is modified for improvement of read performance. The benchmark shows that the new RAID 5 module is superior to the original one in overall performance.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.11
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• pp.949-958
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• 2016

This paper presents the new development result of the multi-band, the multi-mode SDR(Software Defined Radar) platform. The SDR hardware platform is implemented by using the reconfigurable multi-band RF transceiver and antenna modules of S, X, and K-bands, and a programmable signal processing module. The SDR software platform is implemented by using the multi-mode waveform generation of CW, Pulse, FMCW, and LFM Chirp as well as the adaptable algorithm library of signal processing and open API software modules. Through the integrated test of the SDR platform, the operational performance was verified in real-time. Also, through the field-application test, the ground target and air-vehicle drone target were successfully detected and their test results were presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3976-3990
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• 2022

Currently, cross-attention is widely used in Siamese trackers to replace traditional correlation operations for feature fusion between template and search region. The former can establish a similar relationship between the target and the search region better than the latter for robust visual object tracking. But existing trackers using cross-attention only focus on rich semantic information of high-level features, while ignoring the appearance information contained in low-level features, which makes trackers vulnerable to interference from similar objects. In this paper, we propose a Multi-level Cross-attention Siamese network(MCSiam) to aggregate the semantic information and appearance information at the same time. Specifically, a multi-level cross-attention module is designed to fuse the multi-layer features extracted from the backbone, which integrate different levels of the template and search region features, so that the rich appearance information and semantic information can be used to carry out the tracking task simultaneously. In addition, before cross-attention, a target-aware module is introduced to enhance the target feature and alleviate interference, which makes the multi-level cross-attention module more efficient to fuse the information of the target and the search region. We test the MCSiam on four tracking benchmarks and the result show that the proposed tracker achieves comparable performance to the state-of-the-art trackers.