• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.1
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• pp.138-145
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• 2007

Wireless transmission system using the multipath channel is affected ISI due to the delay spread. So we use a decision feedback equalizer which consist of decision part and feedback filter for remove the ISI effectively. In this paper, we propose a improved adaptive decision feedback equalizer to mitigate ISI effectively. The proposed adaptive decision feedback equalizer is construct by using soft decision device and hierarchical feedback filter based on MMSE sub-optimal equalizer using the LMS algorithm. Soft decision device mitigate the error propagation in feedback filter by incorrectly detected decision symbol and feedback filter which is divided two step independently mitigate the ISI by using a adaptive algorithm. As a result this structure shows better performance than conventional decision feedback equalizer by mitigating the error propagation in filter cause incorrectly detecting symbol. and we get the MSE more rapidly by using larger step-size due to reduce the number of feedback filter tap. In computer simulation, we compare the bit error rate performance of proposed decision feedback equalizer with conventional one on the S-V channel model for UWB system.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.10
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• pp.69-77
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• 1998

This paper presents a new efficient and stable multilevel partitioning algorithm for VLSI circuit design. The performance of multilevel partitioning algorithms that are proposed to enhance the performance of previous iterative-improvement partitioning algorithms for large scale circuits, depend on choice of construction methods for partition hierarchy. As the most of previous multilevel partitioning algorithms forces experimental constraints on the process of hierarchy construction, the stability of their performances goes down. The lack of stability causes the large variation of partition results during multiple runs. In this paper, we minimize the use of experimental constraints and propose a new method for constructing partition hierarchy. The proposed method clusters the cells with the connection status of the circuit. After constructing the partition hierarchy, a partition improvement algorithm, HYIP$^{[11]}$ using hybrid bucket structure, unclusters the hierachy to get partition results. The experimental results on ACM/SIGDA benchmark circuits show improvement up to 10-40% in minimum outsize over the previous algorithm $^{[3] [4] [5] [8] [10]}$. Also our technique outperforms ML$^{[10]}$ represented multilevel partition method by about 5% and 20% for minimum and average custsize, respectively. In addition, the results of our algorithm with 10 runs are better than ML algorithm with 100 runs.

• Journal of IKEEE
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• v.21 no.4
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• pp.388-396
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• 2017

Since there are many variables such as various poses, illuminations and occlusions in a face detection problem, a high performance detection system is required. Although CNN is excellent in image classification, CNN operatioin requires high-performance hardware resources. But low cost low power environments are essential for small and mobile systems. So in this paper, the CPU-FPGA integrated system is designed based on 3-stage cascade CNN architecture using small size FPGA. Adaptive Region of Interest (ROI) is applied to reduce the number of CNN operations using face information of the previous frame. We use a Field Programmable Gate Array(FPGA) to accelerate the CNN computations. The accelerator reads multiple featuremap at once on the FPGA and performs a Multiply-Accumulate (MAC) operation in parallel for convolution operation. The system is implemented on Altera Cyclone V FPGA in which ARM Cortex A-9 and on-chip SRAM are embedded. The system runs at 30FPS with HD resolution input images. The CPU-FPGA integrated system showed 8.5 times of the power efficiency compared to systems using CPU only.

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.357-372
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• 2001

In this paper, we present the concept of generalization in constructing windows for subsequence matching and propose a new subsequence matching method. GeneralMatch, based on the generalization. The earlier work of Faloutsos et al.(FRM in short) causes a lot of false alarms due to lack of the point-filtering effect. DualMatch, which has been proposed by the authors, improves performance significantly over FRM by exploiting the point filtering effect, but it has the problem of having a smaller maximum window size (half that FRM) given the minimum query length. GeneralMatch, an improvement of DualMatch, offers advantages of both methods: it can use large windows like FRM and, at the same time, can exploit the point-filtering effect like DualMatch. GeneralMatch divides data sequences into J-sliding windows (generalized sliding windows) and the query sequence into J-disjoint windows (generalized disjoint windows). We formally prove that our GeneralMatch is correct, i.e., it incurs no false dismissal. We also prove that, given the minimum query length, there is a maximum bound of the window size to guarantee correctness of GeneralMatch. We then propose a method of determining the value of J that minimizes the number of page accesses, Experimental results for real stock data show that, for low selectivities ($10^{-6}~10^{-4}$), GeneralMatch improves performance by 114% over DualMatch and by 998% iver FRM on the average; for high selectivities ($10^{-6}~10^{-4}$), by 46% over DualMatch and by 65% over FRM on the average.

• The KIPS Transactions:PartA
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• v.12A no.6 s.96
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• pp.523-530
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• 2005

When a PCI 2.2 bus master requests data using Memory Read command, a target device may hold PCI bus without data to be transferred for long time because a target device needs time to prepare data infernally. Because the usage efficiency of the PCI bus and the data transfer efficiency are decreased due to this situation, the PCI specification recommends to use the Delayed Transaction mechanism to improve the system performance. But the mechanism cann't fully improve performance because a target device doesn't know the exact size of prefetched data. In the previous work, we propose a new method called Prefetch Request when a bus master intends to read data from the target device. In this paper, we design PCI 2.2 controller and local device that support the proposed method. The designed PCI 2.2 controller has simple local interface and it is used to convert the PCI protocol into the local protocol. So the typical users, who don't know the PCI protocol, can easily design the PCI target device using the proposed PCI controller. We propose the basic behavioral verification, hardware design verification, and random test verification to verify the designed hardware. We also build the test bench and define assembler instructions. And we propose random testing environment, which consist of reference model, random generator ,and compare engine, to efficiently verify corner case. This verification environment is excellent to find error which is not detected by general test vector. Also, the simulation under the proposed test environment shows that the proposed method has the higher data transfer efficiency than the Delayed Transaction about $9\%$.

• The KIPS Transactions:PartC
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• v.9C no.1
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• pp.97-106
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• 2002

In 3GPP2 standard, MIP is used and a PDSN performs the function of FA to support macro mobility. When a MS is roaming from a PDSN area to another, the mobility supported is called macro mobility, while it is called micro mobility when a MS is roaming from a RN area to another in a PDSN area. Since a PDSN performs the function of FA in 3GPP2 standard, it is possible to support mobility but its mechanism is actually for supporting macro mobility, not for micro mobility, thus it is weak in processing fast and seamless handoff to support micro mobility. In this paper, we suggest the seamless handoff algorithm barred on multicast group mechanism to support micro mobility. Depending on the moving direction and velocity of a MS, the suggested algorithm constructs a multicast group of RNs on the forecasted MS's moving path, and maximally delays RNs'joining to a multicast group to increase the network efficiency. Moreover, to resolve the buffer overhead problem of the existent multicast scheme, the algorithm suggests that each RN buffers data only after the forecasted handoff time. To prove deadlock freeness and liveness of the algorithm. we use state transition diagrams, a Petri-net modeling and its reachability tree. Then, we evaluate the performance by simulation.

• KIISE Transactions on Computing Practices
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• v.21 no.7
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• pp.506-511
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• 2015

IOV is a technology that supports one or more virtual desktops, and can share a single physical device. In general, the virtual desktop uses the virtual IO devices which are provided by virtualization SW, using SW emulation technology. Virtual desktops that use the IO devices based on SW emulation have a problem in which service quality and performance are declining. Also, they cannot support the high-end application operations such as 3D-based CAD and game applications. In this paper, we propose a physical network separation system using Virtual Desktop Service based on HW direct assignments to overcome these problems. The proposed system provides independent desktops that are used to access the intranet or internet using server virtualization technology in a physical desktop computer for the user. In addition, this system can also support a network separation without network performance degradation caused by inspection of the network packet for logical network separations and additional installations of the desktop for physical network separations.

• Journal of KIISE
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• v.42 no.1
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• pp.54-67
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• 2015

Nowadays, studies on the fusion of Semantic Web technologies are being carried out to promote the interoperability and value of sensor data in an IoT environment. To accomplish this, the semantic translation of sensor data is essential for convergence with service domain knowledge. The existing semantic translation technique, however, involves translating from static metadata into semantic data(RDF), and cannot properly process real-time and large-scale features in an IoT environment. Therefore, in this paper, we propose a technique for translating large-scale streaming sensor data generated in an IoT environment into semantic data, using real-time and parallel processing. In this technique, we define rules for semantic translation and store them in the semantic repository. The sensor data is translated in real-time with parallel processing using these pre-defined rules and an ontology-based semantic model. To improve the performance, we use the Apache Storm, a real-time big data analysis framework for parallel processing. The proposed technique was subjected to performance testing with the AWS observation data of the Meteorological Administration, which are large-scale streaming sensor data for demonstration purposes.

• The KIPS Transactions:PartD
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• v.13D no.5 s.108
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• pp.633-640
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• 2006

Spatial clustering, which groups similar objects based on their distance, connectivity, or their relative density in space, is an important component of spatial data mining. Density-based and grid-based clustering are two main clustering approaches. The former is famous for its capability of discovering clusters of various shapes and eliminating noises, while the latter is well known for its high speed. Clustering large data sets has always been a serious challenge for clustering algorithms, because huge data set would make the clustering process extremely costly. In this paper, we propose an enhanced Density-Grid based Clustering algorithm for Large spatial database by setting a default number of intervals and removing the outliers effectively with the help of a proper measurement to identify areas of high density in the input data space. We use a density threshold DT to recognize dense cells before neighbor dense cells are combined to form clusters. When proposed algorithm is performed on large dataset, a proper granularity of each dimension in data space and a density threshold for recognizing dense areas can improve the performance of this algorithm. We combine grid-based and density-based methods together to not only increase the efficiency but also find clusters with arbitrary shape. Synthetic datasets are used for experimental evaluation which shows that proposed method has high performance and accuracy in the experiments.

• Journal of Internet Computing and Services
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• v.13 no.4
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• pp.83-93
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• 2012

HTML5 has developed not to have browser dependancy considering interoperability as same as maintaining compatability with lower versions of HTML. HTML5, the newest web standardization is on going of being structured. Along with the smart phone boom, HTML5 is spotlighted because it can be applied to cross platforms in mobile web environments. Specially the local Storage that has been listed in new features in HTML5 supports offline function for web application that enables web application to be run even when the mobile is not connected to 3G or wifi. With Local storage, development of server-independent web application can be possible. However Local storage stores plaintext data in it without applying any security measure and this makes the plaintext data dangerous to security threats that are already exist in other client side storages like Cookie. In the paper we propose secure Local storage methods to offer a safe way to store and retrieve data in Local storage guaranteeing its performance. Suggested functions in this paper follow localStorage standard API and use a module that provide cryptographic function. We also prove the efficiency of suggested secure Local storage based on its performance evaluation with implementation.