Temperature- and voltage-dependent trap generation model in high-k metal gate MOS device with percolation simulation

High-k metal gate stacks are being used to suppress the gate leakage due to tunneling for sub-45 nm technology nodes.The reliability of thin dielectric films becomes a limitation to device manufacturing,especially to the breakdown characteristic.In this work,a breakdown simulator based on a percolation model and the kinetic Monte Carlo method is set up,and the intrinsic relation between time to breakdown and trap generation rate R is studied by TDDB simulation.It is found that all degradation factors,such as trap generation rate time exponent m,Weibull slope β and percolation factor s,each could be expressed as a function of trap density time exponent α.Based on the percolation relation and power law lifetime projection,a temperature related trap generation model is proposed.The validity of this model is confirmed by comparing with experiment results.For other device and material conditions,the percolation relation provides a new way to study the relationship between trap generation and lifetime projection.

A Multi-Task Motion Generation Model that Fuses a Discriminator and a Generator

The human motion generation model can extract structural features from existing human motion capture data,and the generated data makes animated characters move.The 3D human motion capture sequences contain complex spatial-temporal structures,and the deep learning model can fully describe the potential semantic structure of human motion.To improve the authenticity of the generated human motion sequences,we propose a multi-task motion generation model that consists of a discriminator and a generator.The discriminator classifies motion sequences into different styles according to their similarity to the mean spatial-temporal templates from motion sequences of 17 crucial human joints in three-freedom degrees.And target motion sequences are created with these styles by the generator.Unlike traditional related works,our model can handle multiple tasks,such as identifying styles and generating data.In addition,by extracting 17 crucial joints from 29 human joints,our model avoids data redundancy and improves the accuracy of model recognition.The experimental results show that the discriminator of the model can effectively recognize diversified movements,and the generated data can correctly fit the actual data.The combination of discriminator and generator solves the problem of low reuse rate of motion data,and the generated motion sequences are more suitable for actual movement.

Kinetics and model of gas generation of source rocks in the deepwater area, Qiongdongnan Basin

In order to investigate the hydrocarbon generation process and gas potentials of source rocks in deepwater area of the Qiongdongnan Basin, kinetic parameters of gas generation （activation energy distribution and frequency factor） of the Yacheng Formation source rocks （coal and neritic mudstones） was determined by thermal simulation experiments in the closed system and the specific KINETICS Software. The results show that the activation energy （Ea） distribution of C1–C5 generation ranges from 50 to 74 kcal/mol with a frequency factor of 2.4×1015 s–1 for the neritic mudstone and the Ea distribution of C1–C5 generation ranges from 49 to 73 kcal/mol with a frequency factor of 8.92×1013 s–1 for the coal. On the basis of these kinetic parameters and combined with the data of sedimentary burial and paleothermal histories, the gas generation model of the Yacheng Formation source rocks closer to geological condition was worked out, indicating its main gas generation stage at Ro （vitrinite reflectance） of 1.25%–2.8%. Meanwhile, the gas generation process of the source rocks of different structural locations （central part, southern slope and south low uplift） in the Lingshui Sag was simulated. Among them, the gas generation of the Yacheng Formation source rocks in the central part and the southern slope of the sag entered the main gas window at 10 and 5 Ma respectively and the peak gas generation in the southern slope occurred at 3 Ma. The very late peak gas generation and the relatively large gas potential indices （GPI：20×10^8–60×10^8 m^3/km^2） would provide favorable conditions for the accumulation of large natural gas reserves in the deepwater area.

Study on End Milling Generation Surface Model and Simulation in View of Main Axle's Tolerance

In accordance with the relative movement between end-milling cutter and workpiece surface, a theoretical generation model for milled surface was established with the movement error of principal axle considered. Then the milled surfaces under various cutting condition were simulated, the results of which showed that end milled surfaces were of "vaulted profile", heights of surface irregularty at various points to be different with maximum value in the middle and smaller at both sides, the difference were determined by diameter of milling cutter, feeding speed, ratio between the diameter of milling cutter and teeth point curve radius and width of workpiece. The study results can be applied to quality prediction of milled surfaces for precision and/or super precision milling operation.

Assessment of CDM Activities by a Generation Planning Model of the Chinese Power Grids

A generation planning model of six main power grids in China is developed to evaluate the potential of advanced power generation technologies into the Chinese power system as CDM （clean development mechanism）. It is investigated how delivered coal price, on-grid power price, and environmental protection may influence the potential of advanced thermal power generation as CDM projects. One finding from the baseline analysis is that coal price, on-grid power price, and environmental protection policy have only a small significance to the grid-wide specific CO2 emissions of thermal power generation up to the year 2026, while the best thermal generation mix is influenced largely by environmental protection policy. And it is found that not only the price of CER （certified emission reduction） and the length of crediting period but also on-grid power price and the reduction of air pollutants in the baseline have a significant influence on the potential of the CDM activities.

Monetary policy rules：Forward-looking and backward-looking in an overlapping generations model

In the framework of an overlapping generations model, forward-looking monetary policy roles and backward-looking monetary policy rules were investigated. It is shown that the monetary steady state is more likely to be indeterminate under an active forwardlooking rule than under the corresponding backward-looking rule. It is also shown that backward-looking roles can render the monetary steady state unstable.

Model for Generating Scale-Free Artificial Social Networks Using Small-World Networks

The Internet of Things(IoT)has the potential to be applied to social networks due to innovative characteristics and sophisticated solutions that challenge traditional uses.Social network analysis(SNA)is a good example that has recently gained a lot of scientific attention.It has its roots in social and economic research,as well as the evaluation of network science,such as graph theory.Scientists in this area have subverted predefined theories,offering revolutionary ones regarding interconnected networks,and they have highlighted the mystery of six degrees of separation with confirmation of the small-world phenomenon.The motivation of this study is to understand and capture the clustering properties of large networks and social networks.We present a network growth model in this paper and build a scale-free artificial social network with controllable clustering coefficients.The random walk technique is paired with a triangle generating scheme in our proposed model.As a result,the clustering controlmechanism and preferential attachment(PA)have been realized.This research builds on the present random walk model.We took numerous measurements for validation,including degree behavior and the measure of clustering decay in terms of node degree,among other things.Finally,we conclude that our suggested random walk model is more efficient and accurate than previous state-of-the-art methods,and hence it could be a viable alternative for societal evolution.

Automated Service Search Model for the Social Internet of Things

The social internet of things(SIoT)is one of the emerging paradigms that was proposed to solve the problems of network service discovery,navigability,and service composition.The SIoT aims to socialize the IoT devices and shape the interconnection between them into social interaction just like human beings.In IoT,an object can offer multiple services and different objects can offer the same services with different parameters and interest factors.The proliferation of offered services led to difficulties during service customization and service filtering.This problem is known as service explosion.The selection of suitable service that fits the requirements of applications and objects is a challenging task.To address these issues,we propose an efficient automated query-based service search model based on the local network navigability concept for the SIoT.In the proposed model,objects can use information from their friends or friends of their friends while searching for the desired services,rather than exploring a global network.We employ a centrality metric that computes the degree of importance for each object in the social IoT that helps in selecting neighboring objects with high centrality scores.The distributed nature of our navigation model results in high scalability and short navigation times.We verified the efficacy of our model on a real-world SIoT-related dataset.The experimental results confirm the validity of our model in terms of scalability,navigability,and the desired objects that provide services are determined quickly via the shortest path,which in return improves the service search process in the SIoT.

Low organic matter abundance and highly efficient hydrocarbon generation of saline source rock in the Qaidam Basin,NW China

The geochemical analysis and experimental simulation are comprehensively used to systematically study the hydrocarbon generation material,organic matter enrichment and hydrocarbon generation model of Paleogene source rock in the Western Qaidam Depression,Qaidam Basin,NW China.Three main factors result in low TOC values of saline lacustrine source rock of the Qaidam Basin:relatively poor nutrient supply inhibits the algal bloom,too fast deposition rate causes the dilution of organic matter,and high organic matter conversion efficiency causes the low residual organic carbon.For this type of hydrogen-rich organic matter,due to the reduction of organic carbon during hydrocarbon generation,TOC needs to be restored based on maturity before evaluating organic matter abundance.The hydrocarbon generation of saline lacustrine source rocks of the Qaidam Basin is from two parts:soluble organic matter and insoluble organic matter.The soluble organic matter is inherited from organisms and preserved in saline lacustrine basins.It generates hydrocarbons during low-maturity stage,and the formed hydrocarbons are rich in complex compounds such as NOS,and undergo secondary cracking to form light components in the later stage;the hydrocarbon generation model of insoluble organic matter conforms to the traditional“Tissot”model,with an oil generation peak corresponding to Ro of 1.0%.

Development of a Freight Demand Model with an Application to California

This paper discusses the disaggregation of the Federal Highway Administration’s Freight Analysis Framework(FAF)database(version 3.0)on freight origin-destination data and the development of linear regression equations to describe the relationships between commodity-based freight trip productions/attractions to specific economic variables.Instead of generating a production/attraction equation for each commodity,commodities are grouped in certain ways to simplify model development and application.We consider three grouping methods and two model selection criteria(with and without intercepts),which are compared in terms of goodness of fit with two data sets(FAF versions 2.0 and 3.0).Furthermore,the freight generation models are validated using county-level economic data in California and applied to predict year 2015 commodity outputs.The results of this study can help city,county,metropolitan and state level planning agencies develop their own customized freight demand generation models without performing costly large-scale surveys.

Hydrocarbon Generation Characteristics of Source Rocks from Different Saline Environments in the Dongpu Depression,Bohai Bay Basin,China

The Dongpu Depression is a secondary salt-bearing tectonic unit in the Bohai Bay Basin,eastern China.The depositional environment of this depression regarding its Paleogene strata is clearly different in plane,including the saltwater environment(SE)in the north,the freshwater environment(FE)in the south and the brackish water environment(BE)in the middle.The result of oil and gas exploration in the Dongpu Depression shows that more than 90%of the proven oil reserves are distributed in the northern saltwater environment.Previous studies indicate that the organic geochemistry characteristics and the hydrocarbon generation capacity of the source rocks are very clearly diverse under different environments,which results in the significant differences in the proved reserves between the north and the south.In order to further explore the differences in the hydrocarbon generation capacity of the source rocks under distinct depositional environments and the mechanism of their occurrence,three samples from different depositional environments(W18-5 for SE,H7-18 for BE,CH9 for FE)were used for confined gold tube pyrolysis experiments.The results show that the CH4 yields of W18-5,H7-18 and CH9 increase with increasing temperature,the maximum yields being 405.62 mg/g TOC,388.56 mg/g TOC and 367.89 mg/g TOC,respectively.The liquid hydrocarbon yields of W18-5,H7-18 and CH9 firstly increase with increasing temperature and then decrease after the critical temperatures.The maximum yields of C6-14 are 149.54 mg/g TOC,140.18 mg/g TOC and 116.94 mg/g TOC,the maximum yields of C14+being 852.4 mg/g TOC,652.6 mg/g TOC and 596.41 mg/g TOC,respectively for W18-5,H7-18 and CH9.To summarize,the order of hydrocarbon potential from high to low is W18-5,H7-18 and CH9.On this basis,through analyzing the influencing factors of hydrocarbon differences,this paper reveals that the saltwater environment is characterized by 4 factors:higher salinity,halophilic algae,high paleo-productivity and a strongly reducing environment,which are beneficial to the enrichment of organic matter and lead to the formation of high levels of sapropelite and exinite.According to the variation of oil and gas components in the pyrolysis experiments,the hydrocarbon generation process is divided into three stages:kerogen cracking,oil cracking and C2-5 cracking.Combined with hydrocarbon generation characteristics and stages,the evolutionary model of hydrocarbon generation for source rocks under different environments is established.

REVIEW OF HIGH LEVEL FAULT MODELING APPROACHES FOR MIXED-SIGNAL SYSTEMS

In the modern analogue design, Transistor Level Fault Simulation (TLFS) plays the im-portant part since every fault in the whole circuit has to be simulated at that level. Unfortunately, it is a very CPU intensive task even though it maintains the high accuracy. Therefore, High Level Fault Modeling (HLFM) and High Level Fault Simulation (HLFS) are required in order to alleviate the efforts of simulation. In this paper, different HLFM approaches are reviewed at the device level during last two decades. We clarify their domains of application and evaluate their strengths and current limitations. We also analyze causes of faults and introduce various test approaches.

A novel framework of ecological risk management for urban development in ecologically fragile regions: A case study of Turpan City, China

Assessing and managing ecological risks in ecologically fragile areas remain challenging at present.To get to know the ecological risk situation in Turpan City,China,this study constructed an ecological risk evaluation system to obtain the ecological risk level(ERL)and ecological risk index(ERI)based on the multi-objective linear programming-patch generation land use simulation(MOP-PLUS)model,analyzed the changes in land use and ecological risk in Turpan City from 2000 to 2020,and predicted the land use and ecological risk in 2030 under four different scenarios(business as usual(BAU),rapid economic development(RED),ecological protection priority(EPP),and eco-economic equilibrium,(EEB)).The results showed that the conversion of land use from 2000 to 2030 was mainly between unused land and the other land use types.The ERL of unused land was the highest among all the land use types.The ecological risk increased sharply from 2000 to 2010 and then decreased from 2010 to 2020.According to the value of ERI,we divided the ecological risk into seven levels by natural breakpoint method;the higher the level,the higher the ecological risk.For the four scenarios in 2030,under the EPP scenario,the area at VII level was zero,while the area at VII level reached the largest under the RED scenario.Comparing with 2020,the areas at I and II levels increased under the BAU,EPP,and EEB scenarios,while decreased under the RED scenario.The spatial distributions of ecological risk of BAU and EEB scenarios were similar,but the areas at I and II levels were larger and the areas at V and VI levels were smaller under the EEB scenario than under the BAU scenario.Therefore,the EEB scenario was the optimal development route for Turpan City.In addition,the results of spatial autocorrelation showed that the large area of unused land was the main reason affecting the spatial pattern of ecological risk under different scenarios.According to Geodetector,the dominant driving factors of ecological risk were gross domestic product rating(GDPR),soil type,population,temperature,and distance from riverbed(DFRD).The interaction between driving factor pairs amplified their influence on ecological risk.This research would help explore the low ecological risk development path for urban construction in the future.

Rules of variation in hydrogen during reignition of underground fire zones of spontaneous coal combustion

In light of the possibility of reignition when unsealing the closed fire zones, the occurrence of reignition was simulated by a home-made experimental device, hydrogen variety rule from combustion to unsealing was analyzed, the three-stage generation model of hydrogen during reignition in fire zone was put forward and the probability that hydrogen was taken as an indicator gas was discussed. The results show that: when fire zone is ready to unseal, which is filled with hydrogen at a high concentration, it is more prone to reignite.

Short-term photovoltaic power forecasting based on a new hybrid deep learning model incorporating transfer learning strategy

The accurate prediction of photovoltaic(PV)power generation is an important basis for hybrid grid scheduling.With the expansion of the scale of PV power plants and the popularization of distributed PV,this study proposes a multilayer PV power generation prediction model based on transfer learning to solve the problems of the lack of data on new PV bases and the low accuracy of PV power generation prediction.The proposed model,called DRAM,concatenates a dilated convolutional neural network(DCNN)module with a bidirectional long short-term memory(BiLSTM)module,and integrates an attention mechanism.First,the processed data are input into the DCNN layer,and the dilation convolution mechanism captures the spatial features of the wide sensory field of the input data.Subsequently,the temporal characteristics between the features are extracted in the BiLSTM layer.Finally,an attention mechanism is used to strengthen the key features by assigning weights to efficiently construct the relationship between the features and output variables.In addition,the power prediction accuracy of the new PV sites was improved by transferring the pre-trained model parameters to the new PV site prediction model.In this study,the pre-training of models using data from different source domains and the correlations between these pre-trained models and the target domain were analyzed.

Immature Oils in China and Their Genetic Mechanisms

Immature crude oils are a kind of unconventional petroleum resources. They are generated through early low-temperature biochemical/chemical reactions of some specific organic matter. Their geological reserves explored are as high as several hundred million tons in China. Based on a detailed organic geochemical study, five genetic mechanisms of immature oils have been proposed in this paper for early hydrocarbon generation from suberinite, resinite, bacteria-reworked terrestrial organic matter, biolipids and sulphur-rich macromolecules respectively.

Wash Waves Generated by High Speed Displacement Ships

It is difficult to compute far-field waves in a relative large area by using one wave generation model when a large calculation domain is needed because of large dimensions of the waterway and long distance of the required computing points. Variation of waterway bathymetry and nonlinearity in the far field cannot be included in a ship fixed process either. A coupled method combining a wave generation model and wave propagation model is then used in this paper to simulate the wash waves generated by the passing ship. A NURBS-based higher order panel method is adopted as the stationary wave generation model; a wave spectrum method and Boussinesq-type equation wave model are used as the wave propagation model for the constant water depth condition and variable water depth condition, respectively. The waves calculated by the NURBS-based higher order panel method in the near field are used as the input for the wave spectrum method and the Boussinesq-type equation wave model to obtain the far-field waves. With this approach it is possible to simulate the ship wash waves including the effects of water depth and waterway bathymetry. Parts of the calculated results are validated experimentally, and the agreement is demonstrated. The effects of ship wash waves on the moored ship are discussed by using a diffraction theory method. The results indicate that the prediction of the ship induced waves by coupling models is feasible.

Parity Violation in Weak Nuclear Interactions

The treatment of parity violations in the weak nuclear interactions is discussed within the frameworks of both the Standard Model (SM) and the Generation Model (GM) of particle physics. It will be demonstrated that several important differences between these two models lead to the SM merely describing the parity violations, while the GM provides an understanding of the cause of the parity violations in weak nuclear interactions. The significant differences arising from several dubious assumptions made during the development of the SM, lead to very different conclusions concerning the nature of the parity violations in the two models. While the SM is able to describe the observed parity violations in terms of a “V-A” theory of the weak nuclear interactions, the GM is also able to demonstrate the cause of the observed parity violations: in the GM, the observed parity violations arise as a consequence of the negative intrinsic parity of both the W massive bosons, which mediate these so-called charge-changing (CC) weak nuclear interactions.

A Low Spectral Bias Generative Adversarial Model for Image Generation

We propose a systematic analysis of the neglected spectral bias in the frequency domain in this paper.Traditional generative adversarial networks(GANs)try to fulfill the details of images by designing specific network architectures or losses,focusing on generating visually qualitative images.The convolution theorem shows that image processing in the frequency domain is parallelizable and performs better and faster than that in the spatial domain.However,there is little work about discussing the bias of frequency features between the generated images and the real ones.In this paper,we first empirically demonstrate the general distribution bias across datasets and GANs with different sampling methods.Then,we explain the causes of the spectral bias through the deduction that reconsiders the sampling process of the GAN generator.Based on these studies,we provide a low-spectral-bias hybrid generative model to reduce the spectral bias and improve the quality of the generated images.

Integration system research and development for three-dimensional laser scanning information visualization in goaf

An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, cloud data de-noising optimization, construction, display and operation of three-dimensional model, model editing, profile generation, calculation of goaf volume and roof area, Boolean calculation among models and interaction with the third party soft ware. Concerning this system with a concise interface, plentiful data input/output interfaces, it is featured with high integration, simple and convenient operations of applications. According to practice, in addition to being well-adapted, this system is favorably reliable and stable.