Propagation Probability Research Articles

Clustering by propagating probabilities between data points

In this paper, we propose a graph-based clustering algorithm called “probability propagation,” which is able to identify clusters having spherical shapes as well as clusters having non-spherical shapes. Given a set of objects, the proposed algorithm uses local densities calculated from a kernel function and a bandwidth to initialize the probability of one object choosing another object as its attractor and then propagates the probabilities until the set of attractors become stable. Experiments on both synthetic data and real data show that the proposed method performs very well as expected.

Propagation probability and spread rates of self-sustained smouldering fires under controlled moisture content and bulk density conditions

The consumption of large areas of peat during wildfires is due to self-sustained smouldering fronts that can remain active for weeks. We studied the effect of peat moisture content and bulk density on the horizontal propagation of smouldering fire in laboratory-scale experiments. We used milled peat with moisture contents between 25 and 250% (mass of water per mass of dry peat) and bulk densities between 50 and 150 kg m–3. An infrared camera monitored ignition, spread and extinction of each smouldering combustion front. Peats with a bulk density below 75 kg m–3 and a moisture content below 150% self-sustained smouldering propagation for more than 12 cm. Peat with a bulk density of 150 kg m–3 could self-sustain smouldering propagation up to a critical moisture content of 115%. A linear model estimated that increasing both moisture content and bulk density significantly reduced the median fire spread rate (which ranged between 1 and 5 cm h–1). Moisture content had a stronger effect size on the spread rate than bulk density. However, the effect of bulk density on spread rate depends upon the moisture content, with the largest effect of bulk density at low moisture contents.

Induction of localized synaptic plasticity in cultured neural network grown in microfluidic device

Event Abstract Back to Event Induction of localized synaptic plasticity in cultured neural network grown in microfluidic device Eugene Malishev1*, Arseniy Gladkov2, Anton Bukatin1, Yana Pigareva2, Vladimir Kolpakov2, Victor Kazantsev2, Irina Mukhina3 and Alexey Pimashkin2 1 Saint-Petersburg Academic University, Nanotechnology Research and Education Centre of the RAS, Russia 2 Lobachevsky State University of Nizhny Novgorod, Department of Neuroengineering, Center of Translational Technologies, Russia 3 Nizhny Novgorod State Medical Academy, Cell Technology Department, Russia Abstract Synaptic plasticity in neural networks remains one of the key questions in the research of fundamental mechanisms of the brain including information coding, learning and memory. In this study we investigate synaptic plasticity using microfluidic device with special shaped channels in order to guide axons and construct neural circuits with two subnetworks coupled by directed synaptic pathways. We applied high-frequency electrical stimulation to isolated neural connections which induced potentiation or depression of synaptic pathways. Motivation Cultures of dissociated neuronal cells are widely used model to study cellular and molecular mechanisms of synaptic plasticity. The model allows long term monitoring of bioelectrical functional activity and morphological changes. Many studies were done with stimulus induced plasticity in the networks of dissociated neuronal cells but provide highly variable results. Connections between the neurons in such networks are formed randomly which obstructs application of precise plasticity induction protocols. Recently developedt microfluidic methods provide guided neuritis growth and construct cultures with predefined functional connections [1,2]. Neural network consist of two sub-cultures coupled by microchannels in which axons grow dominantly in one direction. Artificially designed morphology of the network provide easy access to the presynaptic and postsynaptic neurons in order to induce localazed synaptic plasticity. Materials and methods PDMS microfluidic chips containing an array of microchannels between two chambers A and B were fabricated by two layer lithography and PDMS molding techniques. Channel design determined axonal growth dominantly from A chamber to B (see [2] for more details). Hippocampal neural cells from mice embryos at 18-th prenatal day were plated on 60-electrode arrays (Multichannel systems, Germany) with diameter of 30 µm and 200 µm interelectrode distance. In order to investigate spike propagation inside the microchannels, each PDMS chip was positioned and mounted onto the surface of a planar microelectrode array (MEA, Multichannel systems, Germany) with 60 electrodes of 30 µm in diameter, so as to locate several electrodes in the microchannels. Before cell plating the device was covered with polyethyleneimine. Dissociated hippocampal neurons were plated into separate subcompartments (chambers). Electrical activity was recorded after by USB-MEA system (Multichannel systems, Germany). Low frequency stimulation (60 pulses per each of 7 selected electrodes (3 in A, 3 in B, 1 in channel) with 3 s interval) was implied to induce network response. High frequency stimulation (±800mV, 260µs per phase, 20 stimulus with 100ms interval repeated 150 times with 6s interval (Wagenaar, 2003) of two subpopulations with 10ms delay was implied to induce network plasticity. Scheme of the protocol is shown in figure 2. Results We growed cultures with directed archticeture of the neural network up to 30 days in vitro. To analyze spike propagation between chambers with neurons we used low-frequency electrical stimulation applied to single electrodes in various locations of the chambers. Number of stimuli that evoked a network burst response was calculated separately for two chambers. We estimated a percent of the stimuli that evoked responses in both chambers which was defined as Propagation probability (PPAB). This parameter indicated a strength between pre- and postsynaptic pathways of neuronal subpopulations. Next we induced synaptic plasticity of the connections in the microchannels by high-frequency electrical stimulation. After the stimulation the responses to low-frequency stimuli were potentiated in B chamber of the cultured network by 6.61% PPAB increase in contrast to 0.37% increase in control stimulation. Opposite effect (depression) was observed in other three cultures. Discussion and Conclusion In this study we investigated synaptic plasticity in hippocampal cultures with unidirectional architecture of the network grown in microfuidic chip. Such device composed of two chambers connected by specific microchannels which guided axon growth between chambers in one-way direction provided certain control over synaptic pathways. The results show that burst propagation probability can be modified (potentiated or depressed) by application of high-frequency stimulation applied to the synaptic pathways in the microchannels.

Some Considerations about the Influence of the Stress Intensity Factors KImin, KIImax and Keq in Fatigue Crack Propagation in the Substrate of the Gear Teeth

The values of the stress intensity factor (SIF) KI are almost always negative in the substrate of the gear teeth, due to the compressive stresses field. The more negative values are higher, respectively, the positive values are lower, the crack faces are more compressed, so the probability of crack propagation after the mode I is lower. Thus, the analysis of the factors leading to the minimum KI values may reveal the conditions that favor the fatigue crack propagation by opening mode. Instead, SIF KII is determinant in the growth rate of the fatigue crack by mode II, in terms of compressive stresses field. Thus, the more KII is higher, the propagation speed is higher, so an analysis of the factors that lead to its maximum value is very useful. The equivalent stress intensity factor Keq corresponds to a mixed-mode of loading and take into account the simultaneous influence of both stress intensity factors KI and KII. The variation of this factor can be used as a parameter of the modified Paris law, in order to study the propagation of the fatigue cracks in the case of mixed-mode loading of contact area between teeth flanks. SIFs variations were analyzed according to the state of stresses, position on the pitch line between the gear teeth flanks, position and angle of an initial crack in the gear tooth substrate, residual tensions etc.

A Method about the Propagation of Faults in Network

The study of network has been developed for several years. The research usually focuses on the attributes of the network, including the heterogeneity [1], the topology [2] [3] and the communities [4][5] of the network. About the propagation dynamics, reference [6][7] laid emphasis on the mathematical analysis of the propagation of networks. Although these researches are important, with the developing of computer, how to simulate the propagation weighs more and more. Abstraction of ways to propagate is limited to virus model. There are two virus propagation models. One is about bio-virus model. Although these 2 respects have been developed very well and there are lots of different attributes within, the faults propagation varies a lot from these two. For example, other forms of network like SOA and supply chain vary a lot in ways to propagate. This paper focuses on another useful way to simulate the propagation of faults within scale-free directed networks. Based on the fundamental analysis of propagation and the different situations of simulating complexity and amount of information, this paper gives different methods to simulate the propagation of faults in the whole network. This paper invents an ingenious way with pseudo-nodes to deal with nodes of small in-degree. This methods balance the performance of the simulation with the complexity of the simulation. Then this paper simply analyzes an example with two different methods to test their validation. Of course, there are several questions remaining in this method, like how to give the probability of propagation based on different exclusiveness. These are shown at the end of this paper.

Norm Characterization for Body-Centric Networks

Body-centric wireless communication (BCWC) is affected by many uncertain factors. Available propagation models aim to characterize the radio propagation behavior for a specific scenario; model selection is based on the a posteriori knowledge from previous experience. To generalize existing parametric propagation models, the $\ell _{1} $ -norm probability propagation model, which is independent of a posteriori knowledge, was developed in this paper. To validate the $\ell _{1} $ -based model, Duke phantom was used as the carrier in the finite-difference time-domain calculation. Simulation and experimental results demonstrated that the generalized $\ell _{1} $ -norm propagation model is very appropriate for BCWC, which always undergoes various changes in practice.

K-Center: An Approach on the Multi-Source Identification of Information Diffusion

The global diffusion of epidemics, computer viruses, and rumors causes great damage to our society. It is critical to identify the diffusion sources and timely quarantine them. However, most methods proposed so far are unsuitable for diffusion with multiple sources because of the high computational cost and the complex spatiotemporal diffusion processes. In this paper, based on the knowledge of infected nodes and their connections, we propose a novel method to identify multiple diffusion sources, which can address three main issues in this area: 1) how many sources are there? 2) where did the diffusion emerge? and 3) when did the diffusion break out? We first derive an optimization formulation for multi-source identification problem. This is based on altering the original network into a new network concerning two key elements: 1) propagation probability and 2) the number of hops between nodes. Experiments demonstrate that the altered network can accurately reflect the complex diffusion processes with multiple sources. Second, we derive a fast method to optimize the formulation. It has been proved that the proposed method is convergent and the computational complexity is $O(mn~\textrm {log}\alpha)$ , where $\alpha = \alpha (m,n)$ is the slowly growing inverse-Ackermann function, $n$ is the number of infected nodes, and $m$ is the number of edges connecting them. Finally, we introduce an efficient algorithm to estimate the spreading time and the number of diffusion sources. To evaluate the proposed method, we compare the proposed method with many competing methods in various real-world network topologies. Our method shows significant advantages in the estimation of multiple sources and the prediction of spreading time.

A Pagerank-Inspired Heuristic Scheme for Influence Maximization in Social Networks

This article focused on seeking a new heuristic algorithm for the influence maximization problem in complex social networks, in which a small subset of individuals are intentionally selected as seeds to trigger a large cascade of further adoptions of a new behavior under certain influence cascade models. In literature, degree and other centrality-based heuristics are commonly used to estimate the influential power of individuals in social networks. The major issues with degree-based heuristics are twofold. First, those results are only derived for the uniform IC model, in which propagation probabilities on all social links are set as same, which is rarely the case in reality; Second, intuitively, an individual's influence power depends not only on the number of direct friends, but also relates to kinds of those friends, that is, the neighbors' influence should also be taken into account when measuring one's influential power. Based on the general weighted cascade model (WC), this article proposes Pagerank-inspired heuristic scheme, PRDiscount, which explicitly discounts the influence power of those individuals who have social relationships with chosen seeds, to alleviate the “overlapping effect” occurred in behavior diffusion. Then, the authors use both the artificially constructed social network graphs (with the features of power-law degree distribution and small-world characteristics) and the real-data traces of social networks to verify the performance of their proposal. Simulations illustrate that PRDiscount can advantage over the existing degree-based discount algorithm, DegreeDiscount, and achieve the comparable performance as greedy algorithm.

Probability-based particle detection that enables threshold-free and robust in vivo single-molecule tracking.

Single-molecule detection in fluorescence nanoscopy has become a powerful tool in cell biology but can present vexing issues in image analysis, such as limited signal, unspecific background, empirically set thresholds, image filtering, and false-positive detection limiting overall detection efficiency. Here we present a framework in which expert knowledge and parameter tweaking are replaced with a probability-based hypothesis test. Our method delivers robust and threshold-free signal detection with a defined error estimate and improved detection of weaker signals. The probability value has consequences for downstream data analysis, such as weighing a series of detections and corresponding probabilities, Bayesian propagation of probability, or defining metrics in tracking applications. We show that the method outperforms all current approaches, yielding a detection efficiency of >70% and a false-positive detection rate of <5% under conditions down to 17 photons/pixel background and 180 photons/molecule signal, which is beneficial for any kind of photon-limited application. Examples include limited brightness and photostability, phototoxicity in live-cell single-molecule imaging, and use of new labels for nanoscopy. We present simulations, experimental data, and tracking of low-signal mRNAs in yeast cells.

Transitivity in coherence-based probability logic

We study probabilistically informative (weak) versions of transitivity by using suitable definitions of defaults and negated defaults in the setting of coherence and imprecise probabilities. We represent p-consistent sequences of defaults and/or negated defaults by g-coherent imprecise probability assessments on the respective sequences of conditional events. Moreover, we prove the coherent probability propagation rules for Weak Transitivity and the validity of selected inference patterns by proving p-entailment of the associated knowledge bases. Finally, we apply our results to study selected probabilistic versions of classical categorical syllogisms and construct a new version of the square of opposition in terms of defaults and negated defaults.

Production of Fischer–Tropsch hydrocarbons via oxygen-blown gasification of charred pinewood pellets

Thermochemical conversion of biomass to petroleum-equivalent liquid fuels is of particular practical interest since this approach would require practically no changes in existing engine technology and transportation infrastructure. This paper presents results of experimental studies aimed at the producing liquid hydrocarbons (C7+) via a two-step process: gasification of charred pinewood pellets (CPP) followed by Fischer–Tropsch (FT) synthesis. The gasifier was operated in a semi-continuous updraft mode using a steam-oxygen mixture (in the range of [H2O]/[O2]=2.2–4.4mol/mol) as an input oxidizing gas. The effect of gasification parameters, including the rate of oxygen flow and steam/oxygen molar ratio on the syngas yield and composition was determined. It was found that increasing oxygen flow rate into the gasifier (by a factor of 2.3) resulted in higher (by 32%) H2/CO ratio while it had a minor effect on the CO/CO2 ratio in the syngas. Increasing the steam/oxygen ratio led to higher H2/CO ratio in the syngas (up to 2.1mol/mol) with slight decrease in the gasification rate of CPP. The water consumption rate was significantly reduced at higher steam/oxygen ratios (by almost half at [H2O]/[O2] ratio of 4.4mol/mol). The syngas from the gasifier was scrubbed of particulate matter and traces of oxygen and dried before it was directed to a FT synthesis reactor. FT synthesis reactor packed with cobalt-based catalyst featuring novel radial-flow design with improved heat-transfer characteristics was employed in this work. The integrated operation of the gasifier and FT reactor yielded mainly C7–C28 straight-chain hydrocarbons. The chain propagation probability (α) of the FT-hydrocarbon products estimated according to Anderson–Schulz–Flory (ASF) distribution model was about 0.8.

Application of the GUM approach to estimate uncertainty in measurements of sustainability systems

This work incorporates measurement uncertainty estimation into the model framework proposed by dos Santos and Brandi (Clean Technol Environ Policy, doi: 10.1007/s10098-015-0919-8 , 2015). It brings the metrology science procedures to sustainability situations by incorporating the use of the GUM framework (GUF) together with the Monte Carlo method (MCM) (BIPM, Evaluation of measurement data—guide to the expression of uncertainty in measurement 2008a; Evaluation of measurement data—Supplement 1 to the “Guide to the expression of uncertainty in measurement”—propagation of distributions using a Monte Carlo method 2008b). The GUF uses the law of propagation of uncertainties and the MCM the propagation probability distributions. This scheme is applied to analyze the Integration and Logistic Infrastructure sustainability dimension of a biofuel supply chain in six countries (Santos et al. 2014). An initial set of specific indicators (input quantities) satisfying well-established criteria is used to aggregate indicators in a methodological manner into a single aggregate indicator. The Canberra and the normalized Euclidean distances are assumed as model functions. As recommended by the GUM approach, Supplement 1 (BIPM, Evaluation of measurement data—Supplement 1 to the “Guide to the expression of uncertainty in measurement”—propagation of distributions using a Monte Carlo method 2008b) is used to compare the GUF and the MCM results, adopting the GUM recommendation to perform the MCM with 106 random trials. This allows the determination of the numerical statistical results with the precision level required for comparing the sustainability level of the six countries. It was shown that the use of the GUF is not validated to treat the adopted model functions. The two fundamental reasons are the limitation of the GUF concerning the truncation of the Taylor’s expansion and the deviation of the probability density function from the normal distribution (BIPM, Evaluation of measurement data—Supplement 1 to the “Guide to the expression of uncertainty in measurement”—propagation of distributions using a Monte Carlo method 2008b; Couto et al., Theory and applications of Monte Carlo simulations 2013). This result was predictable because of the nonlinear dependence on the indicators of the Canberra and the normalized Euclidean distances. The MCM calculations have shown that the uncertainties depend on the choice of the aggregate metrics, consequently affecting the countries sustainability ranking. The results demonstrate that Canberra and the Euclidean metrics separate the developed from the developing countries in clusters. The calculations for the single sustainability indicator and its uncertainty suggest that the Euclidean distance separates the countries better than the Canberra distance and, thus, it may be considered more adequate to represent the sustainability metrics Integration and Logistic Infrastructure sustainability dimension of a biofuel supply chain.

Indentation for evaluating cracking and delamination of thin coatings using finite element analysis

The mechanics of indentation induced coating cracking and interfacial delamination in a typical weakly bonded brittle thin coating-substrate system (diamond-like carbon coating with low adhesion on steel substrate) is investigated by using finite element method. A bilinear cohesive zone model with prescribed cohesive strength and energy is applied to simulate evolutions of the crack and delamination. The effects of the cohesive zones, coating elastic modulus, and coating thickness on the indentation response are evaluated. It is found that increasing the cohesive strength/energy of coating reduces the probabilities of crack generation and propagation, whereas increases the susceptibility to interfacial delamination. At a critical value of the cohesive strength of the bonding layer, the resistance to interfacial delamination reaches its minimum. Nevertheless, the coating cracking is not sensitive to the interface adhesive properties. Moreover, a coating can receive better protection with lower coating elastic modulus. Additionally, increasing the coating thickness generally increases the critical load for coating/interface failures, but opposite effect occurs when the coating is thinner than a critical thickness. Numerical results have also been compared with other emulational or experimental works, and can establish a theoretical basis for improving the durability of brittle thin coatings.

Peculiarities of the Woody Plants Re-Bloom

The data of literary sources concerning the bloom of angiosperm plants and deviation in the development of a flower and inflorescence, in particular untimely flowering, was generalized; our observation results of some peculiarities of re-bloom of woody plants in the National Dendrological Park Sofiyivka of NAS of Ukraine (NDP Sofiyivka) were discussed. The flowering process was formed during a long-term evolution of a propagation system of angiosperm plants as a basis of fertilization and further fruit and seed development. As a result of vernalization and photoperiodism reactions, flowering (under regular conditions) occurs in the most favorable period for pollination and fertilization of every plant. However, various deviations, in particular, the untimely (most frequently double, sometimes threeand four-fold) flowering occurs in this perfect process of generative organ formation of angiosperm plants. An increased number of reports about re-bloom (at the end of summer at the beginning of fall) of the representatives of various woody plant species whose flowers usually blossom in May-June prompts the analysis of the available information concerning the mechanisms of flowering and the causes which lead to deviation of flowering processes. Flowering of the woody plant representatives of the collection fund of the NDP Sofiyivka was studied; statistics about re-bloom in different cities of Ukraine were monitored. The classification of re-bloom facts was carried out according to V.L. Vitkovskiy (1984). Although this classification has mostly a stated nature, it was good enough when being formulated and, with certain conditions, it can be applied nowadays. Accordingly, using this classification, abnormal cases can include facts of early summer-fall flowering and early winter flowering. A late spring flowering can be adaptive response of damaged plants to exogenous stresses, due to which the probability of sexual propagation remains. Early spring-early summer flowering is a dual-natured category which, under certain conditions, may have adaptive meaning and facilitate seminal propagation. Most cases of untimely flowering registered in NDP Sofiyivka represent a group of early summer-fall flowering, in some cases late spring flowering occurred though. Secondary flowering is usually connected with meteorological peculiarities of the year. Most frequently it is seen in very dry years, first of all, after hot and dry spring. The rebloom can have an adaptive nature in case of development seeds with full germination, moreover the immature germs of underdeveloped seeds formed from the flowers of early summer-fall flowering can be used in breeding programs.

New Methodology for Predicting Vertical Atmospheric Profile and Propagation Parameters in Subtropical Arabian Gulf Region

A new simplified approach is proposed to evaluate the vertical refractivity profile within the lowest 1 km of atmosphere from the analysis of surface refractivity $\bm{N}_{\bm{s}}$ in areas where upper-air data are not available. Upper-air measurements from the nearest available radiosonde location with similar surface profile to these sites are utilized. The profiles of $\bm{N}_{\bm{s}}$ and refractivity extrapolated to sea level $N_o$ obtained from surface meteorological data using both fixed stations and radiosonde are investigated and compared. Vertical refractivity gradient $\boldsymbol{\Delta} {\bm{N}}$ is evaluated at three atmospheric layer heights within the first kilometer above the ground in addition to propagation parameters relevant to each atmospheric layer. At six sites, different approaches are compared for the analysis of three important parameters; namely effective earth radius factor $k$ anomalous propagation probability parameter ${\boldsymbol{\upbeta}_0}$ and point refractivity gradient at 65 m not exceeded for 1% of time $dN_1$ . The ${\bm{k}}$ -factor parameter is investigated using a new weighted average approach of $\boldsymbol{\Delta} {\bm{N}}$ at 65-m, 100-m, and 1-km layers above the ground. The results are compared with the latest ITU maps and tables for the same area.

Probabilistic infrasound propagation using realistic atmospheric perturbations

AbstractThis study demonstrates probabilistic infrasound propagation modeling using realistic perturbations. The ensembles of perturbed analyses, provided by the European Centre for Medium‐Range Weather Forecasts (ECMWF), include error variances of both model and assimilated observations. Ensemble spread profiles indicate a yearly mean effective sound speed variation of up to 8 ms−1 in the stratosphere, exceeding occasionally 25 ms−1 for a single ensemble set. It is shown that errors in point estimates of effective sound speed are dominated by variations in wind strength and direction. One year of large mining explosions in the Aitik mine, northern Sweden, observed at infrasound array IS37 in northern Norway are simulated using 3‐D ray tracing. Probabilistic propagation modeling using the ensembles demonstrates that small‐scale fluctuations are not always necessary to improve the match between predictions and observations.

Fire danger assessment in Iran based on geospatial information

Fire danger assessment is a vital issue to alleviate the impacts of wildland fires. In this study, a fire danger assessment system is proposed, which extensively uses geographical databases to characterize the spatial variations of fire danger conditions in Iran. This assessment requires three steps: (i) generation of the required input variables, (ii) methods to integrate those variables for creating synthetic indices and (iii) validation of those indices versus fire occurrence data. This fire danger model is based on previous works but adapted to Iranian conditions. It includes an estimation of the fire ignition potential (both considering human and climatic factors) and fire propagation potential. The former was generated from a logistic regression approach based on a wide range of input variables. The fire propagation probability was estimated from the Flammap fire behavior model. A first stage for validation of our fire danger system was based on comparing the estimated danger values to actual fire occurrence, based on satellite detected active fires and burned areas. The logistic regression model for fire ignition probability estimated 72.7% of true ignitions. Detected hotspots occurred more frequently in areas with higher fire ignition probability (average value: 0.65) than non hotspots (average value: 0.4). Propagation probability showed higher values for areas with higher proportion of burned area (r=0.68, p<0.001).

위험 전파 모형을 고려한 공급사슬의 구조적 취약성 평가 지표 설계

It is general that the impact of supply chain risk spread out to the whole network along the connected structure. Due to the risk propagation the probability to exposure a certain risk is affected by not only the characteristics of each risk factor but also network structure. It means that the structural connectivity among vertices should be considered while designing supply chain network in order to minimize disruption cost. In this research, the betweenness centrality has been utilized to quantitatively assess the structural vulnerability. The betweenness centrality is interpreted as the index which can express both the probability of risk occurrence and propagation of risk impact. With the structural vulnerability index, it is possible to compare the stability of each alternative supply chain structure and choose the better one.

충돌벽면이 직분식 LPG의 분무 및 연소 특성에 미치는 영향에 관한 실험 연구

As an alternative fuel that can be used in SI engine, LPG is one of clean fuels with larger H/C ratio compared to gasoline, low <TEX>$CO_2$</TEX> emission, and small amount of pollutants such as sulfur compounds. When LPG is used in spark ignition engine, volumetric efficiency of the engine can be improved and pumping loss can be reduced by performing direct injection into the combustion chamber instead of port fuel injection. LPG-DI engine allows for lean combustion and stratified combustion under low load. In case of stratified combustion, air fuel ratio can be greatly increased compared to theoretic mixture ratio combustion. Improved thermal efficiency of the engine and reduced pumping loss can be expected from stratified combustion. Accordingly in this study, an experimental apparatus for visualization was designed and manufactured to study the combustion process of LPG after injection and ignition, intended to examine ignition probability and combustion characteristics of spark ignition direct injection(SIDI) LPG fuel. Ambient pressure, ambient temperature and fuel injection pressure were found as important variables that affect ignition probability and flame propagation characteristics of LPG-air mixture. Also, it was verified that the injected LPG fuel can be directly ignited by spark plug under appropriate ambient conditions.

Soft Error Susceptibility Analysis for Sequential Circuit Elements Based on EPPM

Due to the reduction in device feature size, transient faults (soft errors) in logic circuits induced by radiations increase dramatically. Many researches have been done in modeling and analyzing the susceptibility of sequential circuit elements caused by soft errors. However, to the best knowledge of the authors, there is no work which has well considerated the feedback characteristics and the multiple clock cycles of sequential circuits. In this paper, we present a new method for evaluating the susceptibility of sequential circuit elements to soft errors. The proposed method uses four Error Propagation Probability Matrixs (EPPMs) to represent the error propagation probability of logic gates and flip-flops in current clock cycle. Based on the predefined matrix union operations, the susceptibility of circuit elements in multiple clock cycles can be evaluated. Experimental results on ISCAS’89 benchmark circuits show that our method is more accurate and efficient than previous methods.