Browsing by Author "Liu, Chia-Hung"

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A Sustainable Soil Energy Harvesting System With Wide-Range Power-Tracking Architecture
(2019-10-01)
Ou, I-Che
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Yang, Jia-Ping
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Liu, Chia-Hung
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Huang, Kai-Jie
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Tsai, Kun-Ju
For wide-range deployment of wireless sensing nodes in power- and size-constrained Internet of Things applications, self-sustaining wireless sensors without batteries are needed. The energy supply for these ubiquitous sensing devices should harness environmental energy sources to avoid frequent battery replacement and pollution. This paper presents a new soil energy harvesting system with a power management integrated circuit (IC) for wide-range maximum power point tracking (MPPT). The output power of a soil energy cell varies widely according to the soil moisture and soil contents. To extract the maximum amount of energy from the soil, high-efficiency power management with adaptive dc-dc conversion ratios and an MPPT mechanism is essential. The proposed system is implemented with a high-efficiency dc-dc converter IC in a 0.18-mu m CMOS process. The design achieves a peak tracking efficiency of 90.5% in the throughput power range from 56 mu W to 1 mW at an output voltage of 3 V and system efficiency exceeding 65% over an input resistance range of the soil energy source; the peak system efficiency is 73.9%. A demonstration was undertaken of the soil energy harvesting system lighting an LED array without any chemical batteries.
A Wide-Range Capacitive DC-DC Converter with 2D-MPPT for Soil/Solar Energy Extraction
(2018-01-01)
Ou, I-Che
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Yang, Jia-Ping
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Liu, Chia-Hung
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Huang, Kai-Jie
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Tsai, Kun-Ju
This paper presents a capacitive DC-DC converter with adaptive DC-DC conversion ratios and maximum power point tracking (MPPT) for soil and solar energy extraction. To overcome the varying input power ranges of the soil/solar energy sources, a two-dimension power tracking loop with time-based current slope detection was employed. The design was fabricated in a 0.18 mu m CMOS process, achieving >80% efficiency in a throughput power range of 360 mu W to 25mW in the soil mode and from 400 mu W to 10mW in the solar mode while the peak system efficiency is 89.5%.
An Interdigitated Non-Contact ECG Electrode for Impedance Compensation and Signal Restoration
(2015-01-01)
Lin, Jeng-Hau
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Liu, Hao
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Liu, Chia-Hung
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Lam, Phillip
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Pan, Gung-Yu
This paper presents a non-contact electrocardiogram (ECG) measurement platform that compensates for motion-induced impedance changes via interdigitated electrode channels in concert with software reconstruction algorithms. Specifically, the impedance of the non-contact electrode is non-invasively acquired in real-time by exploiting a custom electrode designed with two independent channels featuring independent transfer functions that are used to reconstruct motion-compensated ECG waveforms. The developed platform is validated on human subjects, illustrating up to a 76.3% improvement over conventional approaches, paving the path towards comfortable, convenient, and robust non-contact electrophysiological sensing.
Essential factors that affect bioelectricity generation byRhodopseudomonas palustrisstrainPS3in paddy soil microbial fuel cells
(1970-01-01)
Liu, Chia-Hung
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Lee, Sook-Kuan
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Ou, I-Che
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Tsai, Kun-Ju
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Lee, Yu
A plant-associated phototrophic bacterium,R. palustrisstrain PS3, was inoculated into a soil-based MFC to generate electricity. We evaluated the performance of this soil-based microbial fuel cell (MFC) and elucidated the essential factors that contributed to power generation. PS3 showed the potential to enhance power generation, especially when the apparatus was operated in a sealed chamber with illumination.We deduced that the improved power performance was due to the enhanced electron transport through the living electrode that was grown as a PS3 biofilm via photoheterotrophic metabolism. In addition, we suggested that the interplay between phototrophic fixation of ambient CO(2)and anaerobic oxidation of ferrous iron in soil was also involved in the increased power output. We implemented CMOS (complementary metal-oxide-semiconductor) technology with the soil-based MFC to harvest energy in a more efficient and stable manner. The above system is expected to provide a potentially low-cost and low-energy system with a high power conversion efficiency for practical applications in the future.
Graph-Based Optimal Reactant Minimization for Sample Preparation on Digital Microfluidic Biochips
(2013-01-01)
Chiang, Ting-Wei
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Liu, Chia-Hung
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Huang, Juinn-Dar
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電機資訊學士班
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Undergraduate Honors Program of Electrical Engineering and Computer Science
Sample preparation is an essential step in biochemical reactions. Reactants must be diluted to achieve given target concentrations in sample preparation. Since some reactants like costly reagents and infant's blood are valuable, their usage should be minimized during dilution. In this paper, we propose an optimal reactant minimization algorithm, GORMA, for sample preparation on digital microfluidic biochips. GORMA adopts a systematic method to exhaustively check all possible dilution solutions and then identifies the one with minimal reactant usage and waste through maximal droplet sharing. Experimental results show that GORMA outperforms all the existing methods in reactant usage. Meanwhile, the waste amount is reduced up to 30% as compared with existing waste minimization methods. Moreover, GORMA requires only 0.6% more operations on average when compared with an operation-minimal dilution method.
Graph-Based Optimal Reactant Minimization for Sample Preparation on Digital Microfluidic Biochips
(2013-01-01)
Chiang, Ting-Wei
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Liu, Chia-Hung
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Huang, Juinn-Dar
;
電機資訊學士班
;
電子工程學系及電子研究所
Sample preparation is an essential step in biochemical reactions. Reactants must be diluted to achieve given target concentrations in sample preparation. Since some reactants like costly reagents and infant's blood are valuable, their usage should be minimized during dilution. In this paper, we propose an optimal reactant minimization algorithm, GORMA, for sample preparation on digital microfluidic biochips. GORMA adopts a systematic method to exhaustively check all possible dilution solutions and then identifies the one with minimal reactant usage and waste through maximal droplet sharing. Experimental results show that GORMA outperforms all the existing methods in reactant usage. Meanwhile, the waste amount is reduced up to 30% as compared with existing waste minimization methods. Moreover, GORMA requires only 0.6% more operations on average when compared with an operation-minimal dilution method.
Latency-Optimization Synthesis with Module Selection for Digital Microfluidic Biochips
(2013-01-01)
Liu, Chia-Hung
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Liu, Kuang-Cheng
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Huang, Juinn-Dar
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電子工程學系及電子研究所
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Department of Electronics Engineering and Institute of Electronics
Digital microfluidic biochip (DMFB) is one of the latest developments in bioelectronics. It can replace traditional bulky equipment to facilitate biochemical assays and save the labor cost. Latency optimization is a common optimization objective of synthesis on DMFBs for assay time reduction. It is helpful for latency minimization if an operation can freely select one from a set of functional modules with various area-latency tradeoffs. In this paper, we propose an efficient latency-optimization synthesis algorithm with module selection capability, LOSMOS, for DMFBs. Experimental results show that LOSMOS outperforms several existing state-of-the-art synthesis algorithms and an ILP-based method without module selection.
Reactant and Waste Minimization in Multitarget Sample Preparation on Digital Microfluidic Biochips
(2013-10-01)
Huang, Juinn-Dar
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Liu, Chia-Hung
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Lin, Huei-Shan
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電子工程學系及電子研究所
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Department of Electronics Engineering and Institute of Electronics
Sample preparation is one of essential processes in biochemical reactions. Raw reactants are diluted in this process to achieve given target concentrations. A bioassay may require several different target concentrations of a reactant. Both the dilution operation count and the reactant usage can be minimized if multiple target concentrations are considered simultaneously during sample preparation. Hence, in this paper, we propose a multitarget sample preparation algorithm that extensively exploits the ideas of waste recycling and intermediate droplet sharing to reduce both reactant usage and waste amount for digital microfluidic biochips. Experimental results show that our waste recycling algorithm can reduce the waste and operation count by 48% and 37%, respectively, as compared to an existing state-of-the-art multitarget sample preparation method if the number of target concentrations is ten. The reduction can be up to 97% and 73% when the number of target concentrations goes even higher.
Reactant Minimization during Sample Preparation on Digital Microfluidic Biochips using Skewed Mixing Trees
(2012)
Huang, Juinn-Dar
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Liu, Chia-Hung
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Chiang, Ting-Wei
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電子工程學系及電子研究所
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Department of Electronics Engineering and Institute of Electronics
Sample preparation is an indispensable process to biochemical reactions. Original reactants are usually diluted to the solutions with desirable concentrations. Since the reactants, like infant's blood, DNA evidence collected from a crime scene, or costly reagents, are extremely valuable, the usage of reactant must be minimized in the sample preparation process. In this paper, we propose the first reactant minimization approach, REMIA, during sample preparation on digital microfluidic biochips (DMFBs). Given a target concentration, REMIA constructs a skewed mixing tree to guide the sample preparation process for reactant minimization. Experimental results demonstrate that REMIA can save about 31%similar to 52% of reactant usage on average compared with three existing sample preparation methods. Besides, REMIA can be extended to tackle the sample preparation problem with multiple target concentrations, and the extended version also successfully decreases the reactant usage further.
Reactant Minimization for Sample Preparation on Microfluidic Biochips With Various Mixing Models
(2015-12-01)
Liu, Chia-Hung
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Shen, Kuo-Cheng
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Huang, Juinn-Dar
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電子工程學系及電子研究所
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Department of Electronics Engineering and Institute of Electronics
Sample preparation is one of the essential processes for most on-chip biochemical applications. During this process, raw reactants are diluted to specific concentration values. Current sample preparation algorithms are generally created for digital microfluidic biochips with the (1:1) mixing model. For other biochip architectures supporting multiple mixing models, such as flow-based microfluidic biochips, there is still no dedicated solution yet. Hence, in this paper, we propose the first sample preparation method dedicated to microfluidic biochips with various mixing models, named tree pruning and grafting (TPG) algorithm. It starts with a dilution tree created by regarding the (1: 1) mixing model only, and then applies TPG through a bottom-up dynamic programming strategy to obtain a solution with minimal reactant consumption. Experimental results show that our algorithm can save reactant amount by up to 69% against the well-known bit-scanning method on a biochip with a four-segment mixer. Even compared with the state-of-the-art reactant minimization algorithm, it still achieves a reactant reduction of 37%. Therefore, it is convincing that the TPG algorithm is a promising sample preparation solution for biochip architectures that support various mixing models.
Reactant Minimization in Sample Preparation on Digital Microfluidic Biochips
(2015-09-01)
Liu, Chia-Hung
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Chiang, Ting-Wei
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Huang, Juinn-Dar
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電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
Sample preparation plays an essential role in most biochemical reactions. Raw reactants are diluted to solutions with desirable concentration values in this process. Since the reactants, like infant\'s blood, DNA evidence collected from crime scenes, or costly reagents, are extremely valuable, their usage should be minimized whenever possible. In this paper, we propose a two-phased reactant minimization algorithm (REMIA), for sample preparation on digital microfluidic biochips. In the former phase, REMIA builds a reactant-minimized interpolated dilution tree with specific leaf nodes for a target concentration. Two approaches are developed for tree construction; one is based on integer linear programming (ILP) and the other is heuristic. The ILP one guarantees to produce an optimal dilution tree with minimal reactant consumption, whereas the heuristic one ensures runtime efficiency. Then, REMIA constructs a forest consisting of exponential dilution trees to produce those aforementioned specific leaf nodes with minimal reactant consumption in the latter phase. Experimental results show that REMIA achieves a reduction of reactant usage by 32%-52% as compared with three existing state-of-the-art sample preparation approaches. Besides, REMIA can be easily extended to solve the sample preparation problem with multiple target concentrations, and the extended version also effectively lowers the reactant consumption further.
Sample Preparation for Droplet-Based Microfluidics
(2014)
Huang, Juinn-Dar
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Liu, Chia-Hung
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電子工程學系及電子研究所
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Department of Electronics Engineering and Institute of Electronics
Sample preparation plays an essential role in most biochemical reactions. Raw reactants are diluted to solutions with desirable concentration values in this process. In this paper, a survey of existing techniques addressing sample preparation on digital microfluidic biochips (DMFBs) is given. The fundamentals of DMFBs are introduced first. Next, we explain how dilution operations are performed on DMFBs and how the constraint on mixing models comes due to the DMFB architecture limit. Then, we divide the existing techniques into four groups according to the count of target concentration values as well as the number of different reactant types, and briefly introduce selected major research works in each category.
Sample Preparation for Many-Reactant Bioassay on DMFBs using Common Dilution Operation Sharing
(2013)
Liu, Chia-Hung
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Chang, Hao-Han
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Liang, Tung-Che
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Huang, Juinn-Dar
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電子工程學系及電子研究所
Sample preparation is an essential processing step in most biochemical applications. Various reactants are mixed together to produce a solution with the target concentration. Since reactants generally take a notable part of the cost in a bioassay, their usage should be minimized whenever possible. In this paper, we propose an algorithm, CoDOS, to prepare the target solution with many reactants using common dilution operation sharing on digital microfluidic biochips (DMFBs). CoDOS first represents the given target concentration as a recipe matrix, and then identifies rectangles in the matrix, where each rectangle indicates an opportunity of dilution operation sharing for reactant minimization. Experimental results demonstrate that CoDOS can achieve up to 27% of reactant saving as compared with the bit-scanning method in single-target sample preparation. Moreover, even if CoDOS is not developed for multi-target sample preparation, it still outperforms the recent state-of-the-art algorithm, RSMA. Hence, it is convincing that CoDOS is a better alternative for many-reactant sample preparation.
Versatile Ring-Based Architecture and Synthesis Flow for General-Purpose Digital Microfluidic Biochips
(2018-01-01)
Huang, Juinn-Dar
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Liu, Chia-Hung
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Yang, Wei-Hao
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電子工程學系及電子研究所
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Department of Electronics Engineering and Institute of Electronics
Digital microfluidic biochip (DMFB) is a tiny device that can carry out a rich set of bioassays without the need of bulky equipment. However, designing a good general-purpose DMFB architecture is still considered a big challenge today. NP-hard synthesis problems make on-line synthesis virtually impossible on exiting array-based architectures. In this paper, we first elaborate on the major concerns in a DMFB design flow, from the aspects of both synthesis and physical design. We then propose a versatile ring-based architecture VERBA and its corresponding fast one-pass synthesis flow. Experimental results show that VERBA incorporated with the proposed synthesis flow is a better solution than existing architectures and synthesis algorithms especially for real-time cyber-physical systems.
Volume-Oriented Sample Preparation for Reactant Minimization on Flow-Based Microfluidic Biochips with Multi-Segment Mixers
(2015)
Huang, Chi-Mei
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Liu, Chia-Hung
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Huang, Juinn-Dar
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電子工程學系及電子研究所
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Department of Electronics Engineering and Institute of Electronics
Sample preparation is one of essential processes in most biochemical reactions. In this process, raw reactants are diluted to achieve given target concentrations. So far, most of existing sample preparation techniques only consider mixing of two source solutions under the (1:1) mixing model. In this paper, we propose the first sample preparation algorithm VOSPA that not only blends several (>= 2) solutions in a dilution operation but also allows various mixing models on flow-based microfluidic biochips with multi-segment mixers. VOSPA is a volume-oriented sample preparation algorithm that enables segment-based intermediate solution reuse for better reactant minimization. Experimental results show that VOSPA can lower the reactant consumption and operation count by 72% and 59% as compared to the baseline bit-scanning method if an 8-segment mixer is used. Moreover, VOSPA outperforms an optimal algorithm, which merely allows the use of (1:1) mixing model; the reactant usage and operation count can be further reduced by 37% and 76%.