Hybrid Input Research Articles

ULTRA LOW POWER HYBRID MICRO ENERGY HARVESTER USING RF, THERMAL AND VIBRATION FOR BIOMEDICAL DEVICES

<p class="lead">The objective of this research is to design ultra-low power Hybrid Micro Energy Harvester (HMEH) circuit using hybrid inputs of radio frequency (RF), thermal and vibration for biomedical devices. In the HMEH architecture, three input sources (RF, thermal and vibration) are combined in parallel to solve the limitation issue of a single source energy harvester and to improve the system performance. Energy will be scavenged from the human body for thermal and vibration sources by converting directly temperature difference and human movement to electrical energy. The inputs are set to 0.02V and 0.5V for thermal and vibration respectively with the frequency of 1 kHz. Meanwhile, RF source is absorbed from radio wave propagation in our surrounding. For this work, the frequency is set to 915MHz and the output voltages for input ranges of-20dBm to 5dBm are recorded. The performance analysis of the HMEH is divided into two; thermal and vibration harvester circuit and RF harvester circuit. These proposed HMEH circuits are modeled, designed and simulated using PSPICE software. Vibration produces AC input and will be converted to DC using a rectifier. A comparator is used to compare the two sources (thermal and vibration) and boost converter is proposed to step-up these small input sources. Meanwhile, due to RF large frequency, the voltage multiplier is practical for both rectify and step up the input instead of the boost converter. LC resonant network is used to amplify low ambient input of RF passively before it goes to 4–stages voltage multiplier. The proposed HMEH able to achieve the output ranges of 2.0 to 4.0V with 1MΩ load. The results obtained in this research work shows that the proposed design able to produce sufficient voltage for biomedical application requirement which lies between 2.0–4.0 V from the ambient input of 0.02 to 0.5V for thermal and vibration while-9dBm for RF signal.</p>

Has energy conservation been an effective policy for Thailand? An input–output structural decomposition analysis from 1995 to 2010

Thailand has depended heavily on imported fossil fuels since the 1990s, which hindered the nation's economic development because it created uncertainty in the nation's fuel supply. An energy conservation policy was implemented in 1995 to require industries to reduce their energy intensity (EI) and consumption immediately. This study investigates the effectiveness of the policy between 1995 and 2010 using the hybrid input–output approach. Surprisingly, EI improvement was observed in only a few sectors, such as transportation, non-metallic, paper, and textile. An embodied energy decomposition analysis revealed that while households were the largest energy consumer in 1995, energy consumption in exports exceeded that of households in 2000, 2005 and 2010. In addition, structural decomposition analysis revealed the final demand effect was the strongest factor in determining the efficacy of energy conservation, whereas the energy efficiency effect was not an effective factor as expected for decreasing energy consumption. Policy barriers and conflicting economic plans were factors that affected the outcome of these energy policies.

Architecture of Low Power Energy Harvester Using Hybrid Input of Solar and Thermal for Laptop or Notebook: A Review

This paper aims to develop and design the architecture of Low Power Hybrid Energy Harvester (LPHEH) using the hybrid input of solar and thermal that can be harvested for self-powered laptop or notebook. This research will focus on the development of the high performance boost power converter to power up any laptop or notebook and design power management system of the hybrid input of solar and waste heat that has been released. The main function of the boost converter is to generate a sufficient DC power supply for laptop or notebook. The second stage focuses on investigation, design and development of the architecture to convert the solar and waste heat energy to reusable energy. The solar energy harvesting elements such as solar panels and energy storage components are used and to be matched to each other with sufficient energy required to increase the energy harvesting efficiency. The proposed design performances will be described using PSPICE software simulation and experimental results. The final stage is to integrate the first stage and second stage, power management module and charge controller module. Then, the developed LPHEH will be simulated, synthesis using Mentor Graphics and coding using Verilog and then download the LPHEH modules into FPGA board for real time verification. The layout architecture of LPHEH will be tested and analyzed using CALIBRE tools from Mentor Graphics. The expected result from this LPHEH is to get 12 V to 20 V of the regulated output voltage from minimum input voltage sources range from 5 V to 12 V with efficiency more than 90%.

A hybrid input-type recurrent neural network for LVCSR language modeling

Substantial amounts of resources are usually required to robustly develop a language model for an open vocabulary speech recognition system as out-of-vocabulary (OOV) words can hurt recognition accuracy. In this work, we applied a hybrid lexicon of word and sub-word units to resolve the problem of OOV words in a resource-efficient way. As sub-lexical units can be combined to form new words, a compact set of hybrid vocabulary can be used while still maintaining a low OOV rate. For Thai, a syllable-based unit called pseudo-morpheme (PM) was chosen as a sub-word unit. To also benefit from different levels of linguistic information embedded in different input types, a hybrid recurrent neural network language model (RNNLM) framework is proposed. An RNNLM can model not only information from multiple-type input units through a hybrid input vector of words and PMs, but can also capture long context history through recurrent connections. Several hybrid input representations were also explored to optimize both recognition accuracy and computational time. The hybrid LM has shown to be both resource-efficient and well-performed on two Thai LVCSR tasks: broadcast news transcription and speech-to-speech translation. The proposed hybrid lexicon can constitute an open vocabulary for Thai LVCSR as it can greatly reduce the OOV rate to less than 1 % while using only 42 % of the vocabulary size of the word-based lexicon. In terms of recognition performance, the best proposed hybrid RNNLM, which uses a mixed word-PM input, obtained 1.54 % relative WER reduction when compared with a conventional word-based RNNLM. In terms of computational time, the best hybrid RNNLM has the lowest training and decoding time among all RNNLMs including the word-based RNNLM. The overall relative reduction on WER of the proposed hybrid RNNLM over a traditional n-gram model is 6.91 %.

A hybrid input variable selection method for building soft sensor from correlated process variables

Selection of the most relevant input variables for an inferential predictor is important for good prediction ability. A hybrid variable selection method is proposed for selecting input variables for support vector regression (SVR) model. The proposed method combines Taguchi's experimental design method with backward elimination method to select the most relevant variables from a large set of process variables. Taguchi's design of experiment (DoE) method was used to screen variables, as process variables are highly correlated this poses difficulty to fill in the design matrix of Taguchi's DoE method. The proposed method makes several modifications to Taguchi's method to deal with this problem. Subsequently backward elimination method was used to select the final set of input variables. The efficacy of the proposed methodology is demonstrated on an industrial case study.

A novel approach based on the Gauss-vSVR with a new hybrid evolutionary algorithm and input vector decision method for port throughput forecasting

The prediction of port throughput is very complicate, and its accuracy is affected by many socio-economic factors, particularly affected by their embedded distributed randomness of these factors and mixed noises produced in the processes of data collection, transformation, and calculation. Firstly, in view of the v-support vector regression hybridized with Gauss function (briefed as Gauss-vSVR model), to well solve the nonlinear and mixed noises, this paper uses this model to simulate the nonlinear evolving system of port throughput series. Then, to look for more suitable parameter combination of this model and take into account that GA still suffers from the problems of trapped into local optima and time-consuming, this study integrates the global chaotic perturbation algorithm by using Cat mapping function and local acceleration search algorithm by employing cloud theory, i.e., abbreviated as chaotic cloud genetic algorithm (CCGA), to well determine the parameter values for an Gauss-vSVR model. Additionally, based on the principal component analysis and correlation analysis method, an input vector decision method (namely IVD) is proposed to identify the final input variables for Gauss-vSVR model. Finally, hybridization of IVD and CCGA with Gauss-vSVR model, namely IGvSVR-CCGA, is proposed for port throughput forecasting. Subsequently, the port throughput data and its associate socio-economic factors of two largest Chinese ports, Shanghai Port and Tianjin Port, are employed as practical examples to test forecast performance. The numerical results indicate that the proposed hybrid forecasting model receives more satisfied forecasting performance than other classical prediction models; in the meanwhile, the CCGA algorithm also obtains higher optimal efficiency than other alternative algorithms.

Hybrid input–output table method for socioeconomic and environmental assessment of a wind power generation system

Input–output (I–O) analysis, an economic approach using an industrial commodity table, can be applied to analyze the inventories of energy and environmental burdens associated with a given product. The study thus uses I–O analysis to examine the effect of a wind power generation system on the environment, the energy sector, and the economy. New I–O table sections are developed based on actual data on wind turbine production processes. They cover wind power generation-related technology sectors such as manufacturing for system parts and construction. Both energy savings and CO2 emissions reductions are estimated under constant electricity demand, including the demand for wind power, by adding these seven sectors to a Japanese I–O table for 2005. The study also examines the resulting production and added value for all sectors related to wind power generation via lifecycle I–O analysis. The positive production and added value effects outweigh the negative effects of partially substituting electricity from wind power for conventionally generated electricity.

Technological change and energy consumption in India: a decomposition analysis

Increasing demand for energy from its fast growing economy notwithstanding, India is committed to reduce energy consumption on account of the concerns for climate change. It is often held that growth in energy demand could be moderated through autonomous changes in production technology. This paper analyses the sector-wise changes in production technology and its effect on the demand for direct and embodied energy by using structural decomposition analysis in a constant price hybrid Input–Output framework. Results support the hypothesis that changes in production technology contribute significantly to reduce additional energy requirements of the economy. The differences in magnitude, direction and rate of change in production technology between energy and non-energy inputs highlight their varying contributions to energy savings. The significant efficiency impact of embodied consumption in non-energy sectors highlights the scope of technological changes in these sectors, which has a cascading effect in the production chain. Therefore, the focus of policies shall be on lowering the consumption of embodied energy.

Quantitative X-ray phase contrast waveguide imaging of bacterial endospores.

Quantitative waveguide-based X-ray phase contrast imaging has been carried out on the level of single, unstained, unsliced and freeze-dried bacterial cells of Bacillus thuringiensis and Bacillus subtilis using hard X-rays of 7.9 keV photon energy. The cells have been prepared in the metabolically dormant state of an endospore. The quantitative phase maps obtained by iterative phase retrieval using a modified hybrid input-output algorithm allow for mass and mass density determinations on the level of single individual endospores but include also large field of view investigations. Additionally, a direct reconstruction based on the contrast transfer function is investigated, and the two approaches are compared. Depending on the field of view and method, a resolution down to 65 nm was achieved at a maximum applied dose of below 5 × 105 Gy. Masses in the range of about ∼110-190 (20) fg for isolated endospores have been obtained.

Architecture of Ultra-Low-Power Micro Energy Harvester Using Hybrid Input for Biomedical Devices

Architecture of Ultra-Low-Power Micro Energy Harvester Using Hybrid Input for Biomedical Devices

Combination of equilibrium models and hybrid life cycle - input–output analysis to predict the environmental impacts of energy policy scenarios

Abstract Nowadays, many countries adopt an active agenda to mitigate the impact of greenhouse gas emissions by moving towards less polluting energy generation technologies. The environmental costs, directly or indirectly generated to achieve such a challenging objective, remain however largely underexplored. Until now, research has focused either on pure economic approaches such as Computable General Equilibrium (CGE) and partial equilibrium (PE) models, or on (physical) energy supply scenarios. These latter could be used to evaluate the environmental impacts of various energy saving or cleaner technologies via Life Cycle Assessment (LCA) methodology. These modelling efforts have, however, been pursued in isolation, without exploring the possible complementarities and synergies. In this study, we have undertaken a practical combination of these approaches into a common framework: on the one hand, by coupling a CGE with a PE model, and, on the other hand, by linking the outcomes from the coupling with a hybrid input–output−process based life cycle inventory. The methodological framework aimed at assessing the environmental consequences of two energy policy scenarios in Luxembourg between 2010 and 2025. The study highlights the potential of coupling CGE and PE models but also the related methodological difficulties (e.g. small number of available technologies in Luxembourg, intrinsic limitations of the two approaches, etc.). The assessment shows both environmental synergies and trade-offs due to the implementation of energy policies. For example, despite the changes in technologies towards the reduction of greenhouse gas emissions, only marginal improvements are observed in the climate change mitigation scenario as compared to the Business-As-Usual. The energy related production and imports are indeed expected to increase over time and represent a large contribution to the country’s impacts. Interestingly, side effects on other impacts than climate change or fossil resource depletion (e.g. ionising radiation and water depletion) may also occur mainly due to the use of nuclear energy in neighbouring countries.

A hybrid input–output multi-objective model to assess economic–energy–environment trade-offs in Brazil

A multi-objective linear programming (MOLP) model based on a hybrid Input–Output (IO) framework is presented. This model aims at assessing the trade-offs between economic, energy, environmental (E3) and social objectives in the Brazilian economic system. This combination of multi-objective models with Input–Output Analysis (IOA) plays a supplementary role in understanding the interactions between the economic and energy systems, and the corresponding impacts on the environment, offering a consistent framework for assessing the effects of distinct policies on these systems. Firstly, the System of National Accounts (SNA) is reorganized to include the National Energy Balance, creating a hybrid IO framework that is extended to assess Greenhouse Gas (GHG) emissions and the employment level. The objective functions considered are the maximization of GDP (gross domestic product) and employment levels, as well as the minimization of energy consumption and GHG emissions. An interactive method enabling a progressive and selective search of non-dominated solutions with distinct characteristics and underlying trade-offs is utilized. Illustrative results indicate that the maximization of GDP and the employment levels lead to an increase of both energy consumption and GHG emissions, while the minimization of either GHG emissions or energy consumption cause negative impacts on GDP and employment.

Direct phasing of protein crystals with high solvent content.

An iterative transform method is proposed for solving the phase problem in protein crystallography. In each iteration, a weighted average electron-density map is constructed to define an estimated protein mask. Solvent flattening is then imposed through the hybrid input-output algorithm [Fienup (1982). Appl. Opt. 21, 2758-2769]. Starting from random initial phases, after thousands of iterations the mask evolves into the correct shape and the phases converge to the correct values with an average error of 30-40° for high-resolution data for several protein crystals with high solvent content. With the use of non-crystallographic symmetry, the method could potentially be extended to phase protein crystals with less than 50% solvent fraction. The new phasing algorithm can supplement and enhance the traditional refinement tools.

A New SVPWM Modulated Input Switched Multilevel Converter for Grid-Connected PV Energy Generation Systems

This paper proposes a new space vector pulsewidth modulation (SVPWM) strategy for a hybrid input switched multilevel converter for photovoltaic energy generation systems. The converter topology is a cascaded connection of input switched and H-bridge converters, which can provide 2N + 1 voltage levels for each phase. The proposed SVPWM strategy treats the multilevel converter as a two-level converter by introducing an offset vector. With a generated switching pattern, it is possible to obtain minimum number of switching-state transitions and switch the H-bridge close to line frequency; thus, the switching losses can be significantly reduced. The proposed SVPWM strategy has been realized on a seven-level converter to demonstrate the principle of operation. The advantages of the proposed scheme and architecture are verified by both simulation and experimental results.

Atomic resolution tomography reconstruction of tilt series based on a GPU accelerated hybrid input-output algorithm using polar Fourier transform.

Advances in diffraction and transmission electron microscopy (TEM) have greatly improved the prospect of three-dimensional (3D) structure reconstruction from two-dimensional (2D) images or diffraction patterns recorded in a tilt series at atomic resolution. Here, we report a new graphics processing unit (GPU) accelerated iterative transformation algorithm (ITA) based on polar fast Fourier transform for reconstructing 3D structure from 2D diffraction patterns. The algorithm also applies to image tilt series by calculating diffraction patterns from the recorded images using the projection-slice theorem. A gold icosahedral nanoparticle of 309 atoms is used as the model to test the feasibility, performance and robustness of the developed algorithm using simulations. Atomic resolution in 3D is achieved for the 309 atoms Au nanoparticle using 75 diffraction patterns covering 150° rotation. The capability demonstrated here provides an opportunity to uncover the 3D structure of small objects of nanometers in size by electron diffraction.

Development of LED Street Lighting Controller for Wind-Solar Hybrid Power System

This paper presents the design and implementation of a wind-solar hybrid power system for LED street lighting and an isolated power system. The proposed system consists of photovoltaic modules, a wind generator, a storage system (battery), LED lighting, and the controller, which can manage the power and system operation. This controller has the functions of maximum power point tracking (MPPT) for the wind and solar power, effective charging/discharging for the storage system, LED dimming control for saving energy, and remote data logging for monitoring the performance and maintenance. The proposed system was analyzed in regard to the operation status of the hybrid input power and the battery voltage using a PSIM simulation. In addition, the characteristics of the proposed system's output were analyzed through experimental verification. A prototype was also developed which uses 300(W) of wind power, 200(W) of solar power, 60(W) LED lighting, and a 24(V)/80(Ah) battery. The control system principles and design scheme of the hardware and software are presented.

The driving forces of China׳s energy use from 1992 to 2010: An empirical study of input–output and structural decomposition analysis

The energy consumption in China has accelerated since the early 2000s, and China became the largest energy consumer in the world by 2010. To examine the driving forces of China׳s energy use, this paper conducts a structural decomposition analysis based on hybrid input–output tables. In addition, we describe the framework of China׳s energy system by using two energy flow charts. The results show that China׳s current energy use is investment-led demand. Between 1992 and 2007, the three main final-demand categories – gross fixed capital formation, household consumption and exports – contributed approximately one-third each to the changes of total energy use in China. Between 2007 and 2010, however, three-quarters of energy consumption changes came from investment activity only. Technological improvement saved approximately five percent of the total energy use annually during the periods of 1992–1997, 1997–2002 and 2007–2010. In the period of 2002–2007, however, its contribution dropped to only three percent p.a. due to the rise of the indirect energy requirement coefficient in the construction sector. These results suggest that adjusting the final demand structure and improving energy efficiency further will meet China׳s energy challenges in the future.

A guiding framework for ecosystem services monetization in ecological–economic modeling

Monetary valuation techniques are often used for evaluating the effect of a change in ecosystem services on components of human wellbeing, even though they face several drawbacks. This paper seeks to reconcile monetary valuation techniques with methods that address ecosystem–economy interactions by developing a guiding framework that limits the use of monetary valuation to various market simulations. Simulations of scenarios of environmental measures are carried out with a semi-dynamic hybrid input–output model. The guiding framework ensures that monetary valuation techniques contribute to the understanding of the impact of economic activities on changes in ecosystems services and the feedback impact of these changes on economic activities. The framework operates according to three criteria: (i) the category of ecosystem components (intermediate products, ecosystem services, benefits obtained from the ecosystem), (ii) existence of a market, intention to exchange or possibility for restoration or preservation, and (iii) direct/indirect monetary valuation techniques. The methodology is then tested with a case-study.

Quantitative verification of implantable cardiac pacemakers over hybrid heart models

We develop a model-based framework which supports approximate quantitative verification of implantable cardiac pacemaker models over hybrid heart models. The framework is based on hybrid input–output automata and can be instantiated with user-specified pacemaker and heart models. For the specifications, we identify two property patterns which are tailored to the verification of pacemakers: “can the pacemaker maintain a normal heart behaviour?” and “what is the energy level of the battery after t time units?”. We implement the framework in Simulink based on the discrete-time simulation semantics and endow it with a range of basic and advanced quantitative property checks. The advanced property checks include the correction of pacemaker mediated Tachycardia and how the noise on sensor leads influences the pacing level. We demonstrate the usefulness of the framework for safety assurance of pacemaker software by instantiating it with two hybrid heart models and verifying a number of correctness properties with encouraging experimental results.

The carbon payback of micro-generation: An integrated hybrid input–output approach

Feed-in Tariffs (FiTs) in the UK have been introduced to stimulate growth in small-scale renewables such as photovoltaics and micro-wind. They form one of the UK’s key policies to decarbonise electricity by 2030. However, the evidence used to inform the policy was predominantly related to costs, capacity and deployment; not contribution to meeting decarbonisation targets. This paper employs an integrated hybrid lifecycle assessment method, which overcomes boundary limitations of traditional process-based assessments, to measure the full lifecycle emissions of solar PV and micro-wind technologies eligible under FiTs. Environmental assessments of policies often do not take account of the lifecycle emissions of technologies, therefore underestimating their emissions contribution and overestimating the success of policies towards decarbonisation targets. Considering the full lifecycle emissions, the paper assesses the effectiveness of FiTs for driving the UK’s low carbon transition. The results demonstrate that, while there is still significant variation and uncertainty with such estimates, even with the most conservative figures, both the technologies can offer substantial emission savings compared to fossil fuel alternatives when installed in suitable locations. However, the renewable resource of installation sites is critical to the carbon intensity that the technologies can offer. Under a poor renewable resource their impacts can be as high as fossil fuels alternatives. As FiTs makes no distinction between installation sites this should form part of the assessment of funding. Finally, despite their potential for carbon reduction, with the full lifecycle of the considered technologies taken into account, a target of 50gCO2e/kWh is not possible with the current technology generation efficiencies. The paper concludes that a complete re-assessment of the role of technologies in the decarbonisation of electricity is required to take into account the full lifecycle impacts to gain a more realistic picture of the mitigation potential.