• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.2
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• pp.128-136
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• 2002

In this paper, we developed an acoustic echo canceller in real-time using TeakLite DSP Core, which will be placed in the vocoder chip of a mobile handset. Considering the limited computational capacity given to the acoustic echo canceller in a vocoder chip, we employed a FIR-type adaptive filter using a conventional NLMS algorithm. To begin with, we designed and implemented an acoustic echo canceller with floating-point format C-source code, and then converted it into fixed-point format through integer simulation. Then we programmed and optimized it in the assembler level to make it run ill real-time. After optimization procedure, the implemented echo canceller has approximately 624 words of program memory and 811 words of data memory. With 8 KHz sampling rate and 256 filter taps in the echo canceller that corresponds to 32 msec of echo delay, it requires 14.12 MIPS of computational capacity. For coverage of 16 msec echo delay, i.e., 128 filter taps, 9 MIPS is requited.

• Journal of the Korean Geographical Society
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• v.51 no.2
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• pp.235-253
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• 2016

China has been developing a new auto industry growth plan since 2004. In line with this initiative, China actively adopted its policy favoring foreign companies' investment which had a competitive edge over their technologies and manufacturing methodologies. To meet this demand in policy and market change, many foreign auto companies and their parts' manufacturers including Korean auto companies joined this stream. Policy change favoring higher technologies applicable in China requested auto companies' swift adaptation to meet the policy requirements by higher technologies with innovation and introduction of those foreign technologies to China. The spatial (excellence) strategy was followed by the increase in its efficiency and competiveness of each region, which were materialized by or in the form of; Firstly, strategic partnership with China auto companies and encouragement of Korea auto parts manufacturing companies to set up its own factories in China. Secondly, modularization and platform sharing strategy by applying enhanced technologies. Thirdly, strategic utilization of China local government's incentive policies. As production management methodology, JIS was adopted all across the board to meet the on-demand market requirements in the manufacturing processes. Auto part manufacturers had been integrated regionally based on forward linkages and modules. As a result, regional-specific auto industry complexes have been made in the places such as Beijing-Hyundai in the north, Dongfeng-Yueda-Kia in the south, common auto parts at central area like Qingdao, and other parts and raw materials in the vicinity of Shanghai.

• 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 $9\%$.

• Asia pacific journal of information systems
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• v.21 no.1
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• pp.1-27
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• 2011

In an attempt to cope with widespread, dynamic, and accelerating changes in both internal and external business environments, companies often utilize information technologies such as SCM(Supply Chain Management). To date, SCM research has mainly focused on the effects of dynamic factors on SCM success and emphasized adoption strategies and critical success factors. Consequently, the effects of more static factors such as interdependency between SCM partners have been largely ignored. The purpose of this study, therefore, is to examine the effects of both dynamic and static factors on SCM performance by controlling for information quality and partnership quality. The five factors examined in this study include innovative ness, mutual dependency, quality of information, partnership quality, and SCM performance. All factors were examined from the perspective of part suppliers, except the mutual dependency which was examined from two aspects: supplier's dependency on customer and customer's dependency on supplier. Data was collected through five hundred survey questionnaires distributed to the part supplier companies that have implemented SCM systems for at least one year. As a result, a total of 170 valid responses were obtained. A structural equation research model was fitted using SAS 9.1.3 and SMART-PLS 2.0. The results of this study can be summarized as follows. First, innovativeness positively affected SCM information quality. SCM partnership quality, and ultimately SCM performance. The path coefficient between innovativeness and information quality was 0.387, with a t-value of 3.528. Innovativeness also had a positively direct effect on partnership quality. The path coefficient was 0.351 with a t-value of 3.366. The total effect of innovativeness on partnership quality was significant, although its indirect effect on partnership quality by altering information quality was negligible. The total indirect effect of innovativeness on SCM performance by affecting information quality and partnership quality was significant with a p-value of 0.014. Innovativeness played an important role in determining SCM performance. Second, mutual dependency showed no significant effect on SCM information quality. This result contradicts the earlier assertion that the more dependent two companies are, the more accurate and timely the information they exchange ought to be. This study showed that this may not be the case; a partner may provide information of poor quality even when it is strongly dependent on the other. Mutual dependency showed significant effect on partnership quality. However, when the mutual dependency perceived by suppliers was divided into two parts, one being a supplier's dependency on its customer company and the other being a customer's dependency on the supplier, the latter showed a significant impact on the perceived SCM partnership quality. This result indicates that a customer company can hardly improve the partnership quality perceived by suppliers by making them more dependent. It improves only when the suppliers perceive that their partners, typically having more bargaining power, are more dependent on them. The overall effect of mutual dependency of any kind on SCM performance, however, was not significant. Although mutual dependency has been mentioned as an important static factor influencing almost every aspect of cooperation on a supply chain, its influences may not be as significant as it was initially perceived to be. Third, the correlation between information quality and partnership quality was 0.448 with a p-value of less than 0.001. Information quality had a path coefficient of 0.256 to partnership quality with a t-value of 2.940. The quality of information exchanged between partners may have an impact on their partnership quality. Fourth, information quality also had a significant impact on SCM performance with a path coefficient of 0.325 with a t-value of 3.611. In this study, SCM performance was divided into four categories: product quality, cost saving, service quality, and order fulfillment. Information quality has Significant impacts on product quality, cost saving and service quality, but not on order fulfillment. Fifth, partnership quality, as expected, had a significant impact on SCM performance. The path coefficient was 0.403 with a t-value of 3.539. Partnership quality, like information quality, had positive impacts on product quality, cost saving and service quality, but showed no impact on order fulfillment. It seemed that order fulfillment is the hardest category of performance that SCM can satisfy. One major limitation of this study is that it surveyed only the suppliers. To better understand the dual aspects of SCM, it is important to survey both suppliers and the assemblers, especially in pairs. This research, to our best knowledge, was the first attempt to study the level of dependency between the two groups by measuring the dual aspects of SCM and studying mutual dependency from the categories of suppliers and assemblers each.. In the future, a more comprehensive and precise measurement of SCM characteristics needs to be achieved by examining from both the supplier's and assembler's perspectives.