• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2160-2179
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• 2015

In many Radio Frequency Identification (RFID) applications, the reader recognizes the tags within its scope repeatedly. For these applications, some algorithms such as the adaptive query splitting algorithm (AQS) and the novel semi-blocking AQS (SBA) were proposed. In these algorithms, a staying tag retransmits its ID to the reader to be identified, even though the ID of the tag is stored in the reader's memory. When the length of tag ID is long, the reader consumes a long time to identify the staying tags. To overcome this deficiency, we propose a slot allocated blocking anti-collision algorithm (SABA). In SABA, the reader assigns a unique slot to each tag in its range by using a slot allocation mechanism. Based on the allocated slot, each staying tag only replies a short data to the reader in the identification process. As a result, the amount of data transmitted by the staying tags is reduced greatly and the identification rate of the reader is improved effectively. The identification rate and the data amount transmitted by tags of SABA are analyzed theoretically and verified by various simulations. The simulation and analysis results show that the performance of SABA is superior to the existing algorithms significantly.

• Korean Journal of Materials Research
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• v.31 no.2
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• pp.75-83
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• 2021

To cope with automobile exhaust gas regulations, ISG (Idling Stop & Go) and charging control systems are applied to HEVs (Hybrid Electric Vehicle) for the purpose of improving fuel economy. These systems require quick charge/discharge performance at high current. To satisfy this characteristic, improvement of the positive electrode plate is studied to improve the charge/discharge process and performance of AGM(Absorbent Glass Mat) lead-acid batteries applied to ISG automotive systems. The bonding between grid and A.M (Active Material) can be improved by applying the Sand-Blasting method to provide roughness to the surface of the positive grid. When the Sand-Blasting method is applied with conditions of ball speed 1,000 rpm and conveyor speed 5 M/min, ideal bonding is achieved between grid and A.M. The positive plate of each condition is applied to the AGM LAB (Absorbent Glass Mat Lead Acid Battery); then, the performance and ISG life characteristics are tested by the vehicle battery test method. In CCA, which evaluates the starting performance at -18 ℃ and 30 ℃ with high current, the advanced AGM LAB improves about 25 %. At 0 ℃ CA (Charge Acceptance), the initial charging current of the advanced AGM LAB increases about 25 %. Improving the bonding between the grid and A.M. by roughening the grid surface improves the flow of current and lowers the resistance, which is considered to have a significant effect on the high current charging/discharging area. In a Standard of Battery Association of Japan (SBA) S0101 test, after 300 A discharge, the voltage of the advanced AGM LAB with the Sand-Blasting method grid was 0.059 V higher than that of untreated grid. As the cycle progresses, the gap widens to 0.13 V at the point of 10,800 cycles. As the bonding between grid and A.M. increases through the Sand Blasting method, the slope of the discharge voltage declines gradually as the cycle progresses, showing excellent battery life characteristics. It is believed that system will exhibit excellent characteristics in the vehicle environment of the ISG system, in which charge/discharge occurs over a short time.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.215-235
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• 2024

As artificial intelligence (AI) technology is recognized as a key technology that will determine future national competitiveness, competition for AI technology and industry promotion policies in major countries is intensifying. This study aims to present implications for domestic policy making by analyzing the policies of major countries on the start-up of AI companies, which are the basis of the AI industry ecosystem. The top four countries and the EU for the number of new investment attraction companies in the 2023 AI Index announced by the HAI Research Institute at Stanford University in the United States were selected, The United States enacted the National AI Initiative Act (NAIIA) in 2021. Through this law, The US Government is promoting continued leadership in the United States in AI R&D, developing reliable AI systems in the public and private sectors, building an AI system ecosystem across society, and strengthening DB management and access to AI policies conducted by all federal agencies. In the 14th Five-Year (2021-2025) Plan and 2035 Long-term Goals held in 2021, China has specified AI as the first of the seven strategic high-tech technologies, and is developing policies aimed at becoming the No. 1 AI global powerhouse by 2030. The UK is investing in innovative R&D companies through the 'Future Fund Breakthrough' in 2021, and is expanding related investments by preparing national strategies to leap forward as AI leaders, such as the implementation plan of the national AI strategy in 2022. Israel is supporting technology investment in start-up companies centered on the Innovation Agency, and the Innovation Agency is leading mid- to long-term investments of 2 to 15 years and regulatory reforms for new technologies. The EU is strengthening its digital innovation hub network and creating the InvestEU (European Strategic Investment Fund) and AI investment fund to support the use of AI by SMEs. This study aims to contribute to analyzing the policies of major foreign countries in making AI company start-up policies and providing a basis for Korea's strategy search. The limitations of the study are the limitations of the countries to be analyzed and the failure to attempt comparative analysis of the policy environments of the countries under the same conditions.