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    ์œ ๊ธฐ๋ฐœ๊ด‘ ๋‹ค์ด์˜ค๋“œ ํ‘œ์‹œ์žฅ์น˜๋ฅผ ์žฅ์ฐฉํ•œ ์ด๋™ํ˜• ์‹œ์Šคํ…œ์˜ ์ „๋ ฅ ๊ณต๊ธ‰ ์ตœ์ ํ™”

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2012. 8. ์žฅ๋ž˜ํ˜.์˜ค๋Š˜๋‚  ์Šค๋งˆํŠธํฐ, ํƒœ๋ธ”๋ฆฟ PC ์™€ ๊ฐ™์€ ํœด๋Œ€์šฉ ์ „์ž๊ธฐ๊ธฐ๋Š” ๊ณ ์„ฑ๋Šฅ์˜ ์ค‘์•™์ฒ˜๋ฆฌ์žฅ์น˜ (CPU), ๋Œ€์šฉ๋Ÿ‰ ๋ฉ”๋ชจ๋ฆฌ, ๋Œ€ํ˜• ํ™”๋ฉด, ๊ณ ์†์˜ ๋ฌด์„  ์ธํ„ฐํŽ˜์ด์Šค ๋“ฑ์„ ํƒ‘์žฌํ•จ์—๋”ฐ๋ผ ์ „ ๋ ฅ ์†Œ๋ชจ๋Ÿ‰์ด ๊ธ‰์†ํžˆ ์ฆ๊ฐ€ํ•˜์—ฌ ๊ทธ ์ „๋ ฅ ์†Œ๋ชจ๋Š” ์ด๋ฏธ ์†Œํ˜•์˜ ๋žฉํƒ‘ ์ปดํ“จํ„ฐ ์ˆ˜์ค€์— ์ด๋ฅด๊ณ  ์žˆ๋‹ค. ์„ฑ๋Šฅ๊ณผ ์ „๋ ฅ ์†Œ๋ชจ๋Ÿ‰์˜ ์ธก๋ฉด์—์„œ ํœด๋Œ€์šฉ ์ „์ž๊ธฐ๊ธฐ์™€ ๋žฉํƒ‘ ์ปดํ“จํ„ฐ ์‚ฌ ์ด์˜ ๊ตฌ๋ถ„์ด ์ ์ฐจ ์‚ฌ๋ผ์ง€๊ณ  ์žˆ์Œ์—๋„ ๋ฐฐํ„ฐ๋ฆฌ ๋ฐ ์ „๋ ฅ ๋ณ€ํ™˜ ํšŒ๋กœ๋Š” ๊ธฐ์กด์˜ ์„ค๊ณ„ ์›์น™๋“ค๋งŒ์„ ๋”ฐ๋ผ ์„ค๊ณ„๋˜๊ณ  ์žˆ๋Š” ์‹ค์ •์ด๋‹ค. ์‚ผ์„ฑ์ „์ž์˜ ๊ฐค๋Ÿญ์‹œ ํƒญ ๋ฐ Apple ์‚ฌ์˜ iPad ๋“ฑ ์Šค๋งˆํŠธํฐ ๋ฐ ํƒœ๋ธ”๋ฆฟ PC์˜ ๊ฒฝ์šฐ 1-cell ์ง๋ ฌ ๋ฆฌํŠฌ ์ด์˜จ ์ „์ง€๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ๋ฐ˜ ๋ฉด, ๋žฉํƒ‘ ์ปดํ“จํ„ฐ์˜ ๊ฒฝ์šฐ๋Š” ์ œ์กฐ์‚ฌ์— ๋”ฐ๋ผ 3-cell ์—์„œ 5-cell ์ง๋ ฌ ๋“ฑ์œผ๋กœ ์„ค๊ณ„๋˜๊ณ  ์žˆ๋‹ค. ์ด๋Š” ๋ฐฐํ„ฐ๋ฆฌ ์ถœ๋ ฅ ์ „์••์„ ๋‹ค๋ฅด๊ฒŒ ํ•จ์œผ๋กœ์จ ์ „๋ ฅ ๋ณ€ํ™˜ ํšจ์œจ์— ์˜ํ–ฅ์„ ์ค€๋‹ค. ์ „๋ ฅ ๋ณ€ํ™˜ ํšŒ๋กœ์˜ ํšจ์œจ ๋ฐ ๋ฐฐํ„ฐ๋ฆฌ์˜ ์ˆ˜๋ช…์€ ์ž…์ถœ๋ ฅ ์ „์••/์ „๋ฅ˜๋ฅผ ๋น„๋กฏํ•œ ๋™์ž‘ ํ™˜๊ฒฝ์˜ ์˜ํ–ฅ์„ ๋ฐ›๋Š”๋‹ค. ํœด๋Œ€์šฉ ์ „์ž๊ธฐ๊ธฐ์— ์‚ฌ์šฉ๋˜๋Š” ๊ฐ์ข… ์ „์ž๋ถ€ํ’ˆ์€ ์ „๋ ฅ ์†Œ๋ชจ๋ฅผ ์ค„์ด๊ธฐ ์œ„ํ•œ ๋‹ค์–‘ํ•œ ๊ธฐ๋Šฅ๋“ค์„ ๊ตฌํ˜„ํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ์ค‘์•™์ฒ˜๋ฆฌ์žฅ์น˜์˜ ๋™์  ์ „์••/์ฃผํŒŒ ์ˆ˜ ์กฐ์ ˆ ๊ธฐ๋ฒ• ๋“ฑ ๊ณต๊ธ‰์ „์••์˜ ๋ณ€ํ™”๋ฅผ ์ˆ˜๋ฐ˜ํ•˜๋Š” ๊ธฐ๋ฒ• ์—ญ์‹œ ๋‹ค์–‘ํ•˜๊ฒŒ ์ ์šฉ๋˜๊ณ  ์žˆ๋‹ค. ์ด๋Š” ๊ฐ ์žฅ์น˜์˜ ๊ณต๊ธ‰ ์ „์•• ๋ฐ ์ „๋ฅ˜์˜ ๋ณ€ํ™”๋กœ ์ธํ•œ ์ „๋ ฅ ๋ณ€ํ™˜ ํšŒ๋กœ์˜ ํšจ์œจ์˜ ๋ณ€ํ™” ๋ฅผ ์ดˆ๋ž˜ํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ์ค‘์•™์ฒ˜๋ฆฌ์žฅ์น˜, ๋””์Šคํ”Œ๋ ˆ์ด ๋“ฑ ์ฃผ์š” ์ „๋ ฅ ์†Œ๋น„ ์žฅ์น˜์˜ ์ „๋ ฅ ์ ˆ๊ฐ ๊ธฐ๋ฒ•์„ ๊ฐœ๋ฐœํ•  ๋•Œ์—๋Š” ๊ฐœ๋ณ„ ์žฅ์น˜์˜ ์ „๋ ฅ ์†Œ๋น„๋ฅผ ์ค„์ด๋Š” ๊ฒƒ๊ณผ ๋™์‹œ์— ๊ฐœ๋ณ„ ์žฅ ์น˜์˜ ๋™์ž‘ ํ–‰ํƒœ์— ๋Œ€ํ•œ ์ •ํ™•ํ•œ ๋ถ„์„์— ๊ธฐ๋ฐ˜ํ•˜์—ฌ ๋ฐฐํ„ฐ๋ฆฌ, ์ „๋ ฅ ๋ณ€ํ™˜ํšŒ๋กœ์˜ ์„ค๊ณ„๊ฐ€ ํ•จ๊ป˜์ด๋ฃจ์–ด์ ธ์•ผ ํ•œ๋‹ค. ์„ ํ–‰ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ๋ฐฐํ„ฐ๋ฆฌ์˜ ํŠน์„ฑ์„ ๊ณ ๋ คํ•œ ๋ฐฐํ„ฐ๋ฆฌ ๊ตฌ์„ฑ์˜ ์ตœ์ ํ™” ๊ธฐ๋ฒ•์ด ์ œ์•ˆ๋˜์—ˆ๋‹ค [1]. ์ค‘์•™์ฒ˜๋ฆฌ์žฅ์น˜์˜ ๋™์  ์ „์••/์ฃผํŒŒ์ˆ˜ ์ œ์–ด ๊ธฐ๋ฒ•์— ์ด์–ด ์œ ๊ธฐ๋ฐœ๊ด‘๋‹ค์ด์˜ค๋“œ(OLED) ๊ธฐ๋ฐ˜ ๋””์Šคํ”Œ๋ ˆ์ด์˜ ๋™์  ๊ตฌ๋™ํšŒ๋กœ ๊ณต๊ธ‰ ์ „์•• ๊ธฐ๋ฒ•์ด ์ œ์•ˆ๋˜์—ˆ๋‹ค [2]. ์œ ๊ธฐ๋ฐœ๊ด‘๋‹ค ์ด์˜ค๋“œ ๋””์Šคํ”Œ๋ ˆ์ด๋Š” ์ „๋ ฅ ์†Œ๋ชจ ๋ฐ ์‹œ์•ผ๊ฐ ๋“ฑ ๊ธฐ์กด ์•ก์ • ํ‘œ์‹œ์žฅ์น˜์— ๋น„ํ•ด ์—ฌ๋Ÿฌ ์šฐ์ˆ˜ํ•œ ํŠน์„ฑ์œผ๋กœ ์ธํ•ด ์ฃผ๋ชฉ๋ฐ›๊ณ  ์žˆ๋Š” ์ฐจ์„ธ๋Œ€ ๋””์Šคํ”Œ๋ ˆ์ด ์žฅ์น˜์ด๋‹ค. ์œ ๊ธฐ๋ฐœ๊ด‘๋‹ค ์ด์˜ค๋“œ ๋””์Šคํ”Œ๋ ˆ์ด์˜ ์ ์€ ์ „๋ ฅ ์†Œ๋ชจ๋Ÿ‰์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ํ™”๋ฉด์˜ ๋Œ€ํ˜•ํ™” ๋ฐ ํ•ด์ƒ๋„์˜ ๊ณ ๋ฐ€๋„ํ™”์— ๋”ฐ๋ผ ์‹œ์Šคํ…œ ์ „๋ ฅ ์†Œ๋ชจ์—์„œ ์—ฌ์ „ํžˆ ํฐ ๋น„์ค‘์„ ์ฐจ์ง€ํ•˜๊ณ  ์žˆ๋‹ค. ์œ ๊ธฐ๋ฐœ ๊ด‘๋‹ค์ด์˜ค๋“œ ๋””์Šคํ”Œ๋ ˆ์ด์˜ ๋™์  ๊ตฌ๋™ํšŒ๋กœ ๊ณต๊ธ‰ ์ „์•• ๊ธฐ๋ฒ•(OLED DVS)๋Š” ์ƒ‰์ƒ์˜ ๋ณ€ํ™”์˜ ๊ธฐ์ดˆํ•œ ๊ธฐ์กด์˜ ์œ ๊ธฐ๋ฐœ๊ด‘๋‹ค์ด์˜ค๋“œ ๋””์Šคํ”Œ๋ ˆ์ด ์ „๋ ฅ ์ ˆ๊ฐ ๊ธฐ๋ฒ•๊ณผ๋Š” ๋‹ฌ๋ฆฌ ์ตœ ์†Œํ•œ์˜ ์ด๋ฏธ์ง€ ์™œ๊ณก๋งŒ์„ ์ˆ˜๋ฐ˜ํ•˜์—ฌ ๋Œ€๋ถ€๋ถ„์˜ ์‚ฌ์ง„, ๋™์˜์ƒ ๋“ฑ์— ์ ์šฉ๊ฐ€๋Šฅํ•œ ์ „๋ ฅ ์ ˆ๊ฐ ๊ธฐ๋ฒ•์ด๋‹ค. ํ•ด๋‹น ๊ธฐ๋ฒ•์€ ๊ณต๊ธ‰ ์ „์••์˜ ๋ณ€ํ™”์‹œํ‚ฌ ํ•„์š”๊ฐ€ ์žˆ์œผ๋ฉฐ, ์ด๋ฅผ ์‹œ์Šคํ…œ์— ์˜ฌ๋ฐ”๋ฅด๊ฒŒ ํ†ตํ•ฉ์‹œํ‚ค๊ธฐ ์œ„ํ•ด์„œ๋Š” ์ „๋ ฅ ๋ณ€ํ™˜ ํšŒ๋กœ ๋ฐ ๋ฐฐํ„ฐ๋ฆฌ ๊ตฌ์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ๊ณ ๋ คํ•ด์•ผ ํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์œ ๊ธฐ๋ฐœ๊ด‘๋‹ค์ด์˜ค๋“œ ๋””์Šคํ”Œ๋ ˆ์ด์˜ ์ „๋ ฅ ์†Œ๋ชจ์™€ ํ•จ๊ป˜ ์ „์ฒด ์‹œ์Šค ํ…œ ํšจ์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ํ•จ๊ป˜ ๊ณ ๋ คํ•˜์—ฌ ์‹œ์Šคํ…œ์„ ์ตœ์ ํ™”ํ•œ๋‹ค. ๋ฐฐํ„ฐ๋ฆฌ ๊ตฌ์„ฑ ์—ญ ์‹œ ๊ธฐ์กด์˜ ์„ค๊ณ„ ํ‘œ์ค€ ๋Œ€์‹  ์ฒด๊ณ„์ ์ธ ์‹œ์Šคํ…œ ๋ถ„์„์— ๊ธฐ๋ฐ˜ํ•œ ์ตœ์ ํ™”๊ฐ€ ์‹œ๋„๋˜์—ˆ๋‹ค. ๊ณต๊ธ‰์ „์••์ด ์กฐ์ ˆ ๊ฐ€๋Šฅํ•œ ์œ ๊ธฐ๋ฐœ๊ด‘๋‹ค์ด์˜ค๋“œ ๋””์Šคํ”Œ๋ ˆ์ด ํ•˜๋“œ์›จ์–ด ๋ฐ ์ œ์–ด๊ธฐ ์‹œ์Šค ํ…œ-์˜จ-์นฉ (System-on-a-chip, SoC) ๊ฐ€ ์ œ์ž‘๋˜์—ˆ๊ณ , ๊ทธ ๋™์ž‘ ํŠน์„ฑ์ด ๋ถ„์„๋˜์—ˆ๋‹ค. ๊ธฐ์กด ์Šค๋งˆํŠธํฐ ๋ฐ ํƒœ๋ธ”๋ฆฟ PC ๊ฐœ๋ฐœ์šฉ ํ”Œ๋žซํผ์˜ ์ „๋ ฅ ๋ณ€ํ™˜ ํšจ์œจ ๋ฐ ๋™์ž‘ ํŠน์„ฑ ์—ญ์‹œ ๋ถ„์„ ๋˜์—ˆ๋‹ค. ์œ ๊ธฐ๋ฐœ๊ด‘๋‹ค์ด์˜ค๋“œ ๋””์Šคํ”Œ๋ ˆ์ด์˜ ๋™์  ๊ตฌ๋™ํšŒ๋กœ ๊ณต๊ธ‰ ์ „์•• ๊ธฐ๋ฒ•์˜ ๋™์ž‘ ํŠน์„ฑ ๋ฐ ์Šค๋งˆํŠธํฐ ํ”Œ๋žซํผ์˜ ๋™์ž‘ ํŠน์„ฑ, ๋ฐฐํ„ฐ๋ฆฌ ํŠน์„ฑ์— ๋Œ€ํ•œ ๋ถ„์„์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์‹œ์Šค ํ…œ ์ˆ˜์ค€์—์„œ์˜ ์ „๋ ฅ ๋ณ€ํ™˜ ํšจ์œจ์ด ์ตœ์ ํ™”๋˜์—ˆ๋‹ค.Modern mobile devices such as smartphone or tablet PC are typically equipped a high-performance CPU, memory, wireless interface, and display. As a result, their power consumption is as high as a small-size laptop computer. The boundary between the mobile devices and laptop computer is becoming unclear from the perspective of the performance and power. However, their battery and related power conversion architecture are only designed according to the legacy design so far. Smartphone and tablet PCs from major vendors such as iPad from Apple or Galaxy-tab from Samsung uses 1-cell Li-ion battery. The laptop PC typically has 3-cell Li-ion battery. The output voltage of the battery affect system-level power conversion efficiency. Furthermore, traditional power conversion architecture in the mobile computing system is designed only considering the fixed condition where the system-level low-power techniques such as DVFS are becoming mandatory. Such a low-power techniques applied to the major components result in not only load demand fluctuation but also supply voltage changing. It has an effect on the battery lifetime as well as the system-level power delivery efficiency. The efficiency is affected by the operating condition including input voltage, output voltage, and output current. We should consider the operating condition of the major power consumer such as a display to enhance the system-level power delivery efficiency. Therefore, we need to design the system not only from the perspective of the power consumption but also energy storage design. The optimization of battery setup considering battery characteristics was presented in [1]. Beside the DVFS of microprocessor, a power saving technique based on the supply voltage scaling of the OLED driver circuit was recently introduced [2]. An organic light emitting diode (OLED) is a promising display device which has a lot of advantages compared with conventional LCD, but it still consumes significant amount of power consumption due to the size and resolution increasing. The OLED dynamic voltage scaling (OLED DVS) technique is the first OLED display power saving technique that induces only minimal color change to accommodate display of natural images where the existing OLED low-power techniques are based on the color change. The OLED DVS incurs supply voltage change. Therefore we need to consider the system-level power delivery efficiency and battery setup to properly integrate the DVS-enabled OLED display to the system. In this dissertation, we not only optimize the power consumption of the OLED display but also consider its effect on the whole system power efficiency. We perform the optimization of the battery setup by a systematic method instead of the legacy design rule. At first, we develop an algorithm for the OLED DVS for the still images and a histogram-based online method for the image sequence with a hardware board and a SoC. We characterize the behavior of the OLED DVS. Next, we analyze the characteristics of the smartphone and tablet-PC platforms by using the development platforms. We profile the power consumption of each components in the smartphone and power conversion efficiency of the boost converter which is used in the tablet-PC for the display devices. We optimize not only the power consuming components or the conversion system but also the energy storage system based on the battery model and system-level power delivery efficiency analysis.1 Introduction 1.1 Supply Voltage Scaling for OLED Display 1.2 Power Conversion Efficiency in MobileSystems 1.3 Research Motivation 2 Related Work 2.1 Low-Power Techniques for Display Devices 2.1.1 Light Source Control-Based Approaches 2.1.2 User Behavior-Based Approaches 2.1.3 Low-Power Techniques for Controller and Framebuffer 2.1.4 Pre-ChargingforOLED 2.1.5 ColorRemapping 2.2 Battery discharging efficiency aware low-power techniques 2.2.1 Parallel Connection 2.2.2 Constant-Current Regulator-Based Architecture 2.3 System-level power analysis techniques 3 Preliminary 38 3.1 Organic Light Emitting Diode (OLED) Display 3.1.1 OLED Cell Architecture 3.1.2 OLED Panel Architecture 3.1.3 OLED Driver Circuits 3.2 Effect of VDD scaling on driver circuits 3.2.1 VDD scaling for AM drivers 3.2.2 VDD scaling for PWM drivers 4 Supply Voltage Scaling and Image Compensation of OLED displays 4.1 Image quality and power models of OLED panels 4.2 OLED display characterization 4.3 VDD scaling and image compensation 5 OLED DVS implementation 5.1 Hardware prototype implementation 5.2 OLED DVS System-on-Chip implementation 5.3 Optimization of OLED DVS SoC 5.4 VDD transition overhead 6 Power conversion efficiency and delivery architecture in mobile Systems 6.1 Power conversion efficiency model of switching-Mode DCโ€“DC converters 6.2 Power conversion efficiency model of linear regulator power loss model 6.3 Rate Capacity Effect of Li-ion Batteries 7 Power conversion efficiency-aware battery setup optimization with DVS- enabled OLED display 7.1 System-level power efficiency model 7.2 Power conversion efficiency analysis of smartphone platform 7.3 Power conversion efficiency for OLED power supply 7.4 Li-ion battery model 7.4.1 Battery model parameter extraction 7.5 Battery setup optimization 8 Experiments 8.1 Simulation result for OLED display with AM driver 8.2 Measurement result for OLED display with PWM driver 8.3 Design space exploration of battery setup with OLED displays 9 Conclusion 10 Future WorkDocto

    Energy-Aware Mobile Learning:Opportunities and Challenges

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    As mobile devices are becoming more powerful and affordable they are increasingly used for mobile learning activities. By enabling learners' access to educational content anywhere and anytime, mobile learning has both the potential to provide online learners with new opportunities, and to reach less privileged categories of learners that lack access to traditional e-learning services. Among the many challenges with mobile learning, the battery-powered nature of mobile devices and in particular their limited battery life, stands out as one issue that can significantly limit learners' access to educational content while on the move. Adaptation and personalisation solutions have widely been considered for overcoming the differences between learners and between the characteristics of their mobile devices. However, while various energy saving solutions have been proposed in order to provide mobile users with extended device usage time, the areas of adaptive mobile learning and energy conservation in wireless communications failed to meet under the same umbrella. This paper bridges the two areas by presenting an overview of adaptive mobile learning systems as well as how these can be extended to make them energy-aware. Furthermore, the paper surveys various approaches for energy measurement, modelling and adaptation, three major aspects that have to be considered in order to deploy energy-aware mobile learning systems. Discussions on the applicability and limitations of these approaches for mobile learning are also provided

    Dynamic power management: from portable devices to high performance computing

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    Electronic applications are nowadays converging under the umbrella of the cloud computing vision. The future ecosystem of information and communication technology is going to integrate clouds of portable clients and embedded devices exchanging information, through the internet layer, with processing clusters of servers, data-centers and high performance computing systems. Even thus the whole society is waiting to embrace this revolution, there is a backside of the story. Portable devices require battery to work far from the power plugs and their storage capacity does not scale as the increasing power requirement does. At the other end processing clusters, such as data-centers and server farms, are build upon the integration of thousands multiprocessors. For each of them during the last decade the technology scaling has produced a dramatic increase in power density with significant spatial and temporal variability. This leads to power and temperature hot-spots, which may cause non-uniform ageing and accelerated chip failure. Nonetheless all the heat removed from the silicon translates in high cooling costs. Moreover trend in ICT carbon footprint shows that run-time power consumption of the all spectrum of devices accounts for a significant slice of entire world carbon emissions. This thesis work embrace the full ICT ecosystem and dynamic power consumption concerns by describing a set of new and promising system levels resource management techniques to reduce the power consumption and related issues for two corner cases: Mobile Devices and High Performance Computing

    A versatile data acquisition system for capturing electromagnetic emissions in VHF band

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    This research investigates the occurrence of EM emissions from compressed rock and assesses their value as precursors to earthquakes. It is understood that electromagnetic emissions are accompanied by crack generation in the Earth's crust, and effort has been targeted on the analysis of electromagnetic signals preceding seismic events. There is a need for a robust Data Acquisition System for the reliable collection of such signals. The design and deployment of a novel system form part of this research. The EM data collected by the Data Acquisition System is subsequently analysed and correlations are made with natural phenomena. The design of the Data Acquisition System is presented and meets a specification which includes accuracy, robustness, power consumption, remote configurability achieved by the development of a novel architecture for flash memories which significantly increases the live span of these devices. The measuring of electromagnetic emissions should be performed by reliable systems, using devices that fully correspond to the specifications set by the needs of this research. This type of systems is not fully covered by existing commercial devices. These prototype VHF field stations (ground base - electromagnetic variation monitors in VHF band) are located around the Hellenic Are. This region is one of the most seismically active regions in western Eurasia due to subduction of the oceanic African lithosphere beneath the Eurasian plate. After approximately two years of electromagnetic VHF data collection, the final stage of this project took place. In this stage, possible correlation between naturally occurring electromagnetic emissions in VHF band and seismic events within a predefined radius around the observation location is investigated. Supplementary, effects of alternative electromagnetic sources, such as solar activity, is considered. Whilst EM emissions from compressed rocks can be demonstrated in the laboratory, it was found from a two-year evaluation that no reliable correlation with earthquake events could be established. However, significant patterns of activity were detected in EM spectrum and it was shown that these correlate strongly with other naturally occurring phenomena such as solar flares. The Data Acquisition System as developed in this thesis has related applications in long term and remote sensing operations including meteorology, environmental analysis and surveillance.EThOS - Electronic Theses Online ServiceNational Foundation of Scholarships (I.K.Y.)European Social Fund and National Resources - (EPEAEK II) ARXIMIDISGBUnited Kingdo

    A versatile data acquisition system for capturing electromagnetic emissions in VHF band

    Get PDF
    This research investigates the occurrence of EM emissions from compressed rock and assesses their value as precursors to earthquakes. It is understood that electromagnetic emissions are accompanied by crack generation in the Earth's crust, and effort has been targeted on the analysis of electromagnetic signals preceding seismic events. There is a need for a robust Data Acquisition System for the reliable collection of such signals. The design and deployment of a novel system form part of this research. The EM data collected by the Data Acquisition System is subsequently analysed and correlations are made with natural phenomena. The design of the Data Acquisition System is presented and meets a specification which includes accuracy, robustness, power consumption, remote configurability achieved by the development of a novel architecture for flash memories which significantly increases the live span of these devices. The measuring of electromagnetic emissions should be performed by reliable systems, using devices that fully correspond to the specifications set by the needs of this research. This type of systems is not fully covered by existing commercial devices. These prototype VHF field stations (ground base - electromagnetic variation monitors in VHF band) are located around the Hellenic Are. This region is one of the most seismically active regions in western Eurasia due to subduction of the oceanic African lithosphere beneath the Eurasian plate. After approximately two years of electromagnetic VHF data collection, the final stage of this project took place. In this stage, possible correlation between naturally occurring electromagnetic emissions in VHF band and seismic events within a predefined radius around the observation location is investigated. Supplementary, effects of alternative electromagnetic sources, such as solar activity, is considered. Whilst EM emissions from compressed rocks can be demonstrated in the laboratory, it was found from a two-year evaluation that no reliable correlation with earthquake events could be established. However, significant patterns of activity were detected in EM spectrum and it was shown that these correlate strongly with other naturally occurring phenomena such as solar flares. The Data Acquisition System as developed in this thesis has related applications in long term and remote sensing operations including meteorology, environmental analysis and surveillance.EThOS - Electronic Theses Online ServiceNational Foundation of Scholarships (I.K.Y.)European Social Fund and National Resources - (EPEAEK II) ARXIMIDISGBUnited Kingdo

    Virtualisation and Thin Client : A Survey of Virtual Desktop environments

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    This survey examines some of the leading commercial Virtualisation and Thin Client technologies. Reference is made to a number of academic research sources and to prominent industry specialists and commentators. A basic virtualisation Laboratory model is assembled to demonstrate fundamental Thin Client operations and to clarify potential problem areas

    Workload model for video decoding and its applications

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