We consider the problem of expected cost analysis over nondeterministic probabilistic programs, which aims at automated methods for analyzing resource-usage such programs. Previous approaches this could only handle nonnegative bounded costs. However, in many scenarios, as queuing networks or cryptocurrency protocols, both positive and negative costs are necessary unbounded well.

Tool state monitoring is a key technology in intelligent manufacturing. But it still research stage and lacks general adaptability for different machining conditions. To overcome this limitation, work systematically investigates an intelligent, real-time, visible tool through adopting integrated theories technologies, i.e., (a) distinctively designed experimental technique with comprehensive consideration of cutting parameters wear values as variables, (b) bisensor fusion simultaneous...

The notion of program sensitivity (aka Lipschitz continuity) specifies that changes in the input result proportional to output. For probabilistic programs is naturally extended expected sensitivity. A previous approach develops a relational logic framework for proving while loops, where number iterations fixed and bounded. In this work, we consider loops not fixed, but randomized depends on initial values. We present sound such programs. Our martingale-based can be automated through existing...

In Bayesian probabilistic programming, a central problem is to estimate the normalised posterior distribution (NPD) of program with conditioning via score (a.k.a. observe) statements. Most previous approaches address this by Markov Chain Monte Carlo and variational inference, therefore could not generate guaranteed outcomes within finite time limit. Moreover, existing methods for exact inference either impose syntactic restrictions or cannot guarantee successful in general. work, we propose...

In order to build the post‐peak strain softening model of rock, evolution laws rock parameters ( m , s ) were obtained by using evolutionary mode piecewise linear function regarding maximum principle stress. Based on nonlinear Hoek–Brown criterion, analytical relationship strength ), cohesion c and friction angle φ has been developed theoretical derivation. According analysis four different types it is found that, within range from 0 σ 3min peak hardness becomes smaller as confining pressure...

Geomagnetic navigation is a new method, which can make up for the shortcomings of traditional methods. The geomagnetic matching algorithm an important algorithm, obtain relatively high precision position information. However, location data measured by sensor not be uniquely corresponding to database, and it easy produce mismatch rate so that accurate positioning realized. Based on related theory graph theory, method based full-connected constraints proposed in this paper. only correspondence...

We consider the problem of expected cost analysis over nondeterministic probabilistic programs, which aims at automated methods for analyzing resource-usage such programs. Previous approaches this could only handle nonnegative bounded costs. However, in many scenarios, as queuing networks or cryptocurrency protocols, both positive and negative costs are necessary unbounded well. In work, we present a sound efficient approach to obtain polynomial bounds on accumulated Our can (a) general with...

Deep Reinforcement Learning (DRL) has gained prominence as an effective approach for control systems. However, its practical deployment is impeded by state perturbations that can severely impact system performance. Addressing this critical challenge requires robustness verification about performance, which involves tackling two quantitative questions: (i) how to establish guaranteed bounds expected cumulative rewards, and (ii) determine tail rewards. In work, we present the first of...

The rapid advancement of social media has enabled people from all around the world to create, express and share their feelings easily freely. It also generates voluminous data in various fields including health, education, finance security etc. huge amount is beneficial for research analysis. In this study, a model based on algorithm Random Forest SVM developed classify sentiment comments. Nearly 100 thousand posts Chinese Language are taken comments, then trained tested using emotion...

With the implementing of national polices to prevent property bubble, it is difficult for real estate company get sufficient funds from loan. As a result, trust financing has gradually become priority, especially when small or medium-sized enterprise choosing their plans in growth period. Although many advantages on flexibility, application scope, and financial expense, also some risks that could bring negative influence project, like capital operation risk, payment credit etc. This paper...

The social contradiction is becoming complex, and the workload of police officers also growing while there no significant increase in number officers. efficient optimization on allocation resources has become an urgent issue for public security organs. Big data technology provides a new method resources. This paper designed potential criminal prediction resource system based existing jurisdiction. Based analysis work, case information, organs, will predict key locations where criminals...

Valuation methods used by the listed company vary with type of industry and profit model. Real estate business is capital intensive, which characterized occupation large funds a long period turnover. The significance this study to select appropriate evaluation method reflect value real company. Considering characteristics company, paper selects valuation companies. Based on analysis factors having an impact profitability financial risk, explores relationship between price, trading volume,...

In Bayesian probabilistic programming, a central problem is to estimate the normalised posterior distribution (NPD) of program with conditioning via score (a.k.a. observe) statements. Most previous approaches address this by Markov Chain Monte Carlo and variational inference, therefore could not generate guaranteed outcomes within finite time limit. Moreover, existing methods for exact inference either impose syntactic restrictions or cannot guarantee successful in general. work, we propose...

RISC-V, as an emerging open source instruction set architecture, has the advantages of simplicity and modularity. With increasing maturity perfection related tool chain, construction software ecology is being paid more attention. As video encoder, many scholars have proposed different optimized implementations based on characteristics architectural instructions, but there are few efficient optimizations x264 algorithm library vector instructions for RISC-V platform., this paper rewrites...

Deep Reinforcement Learning (DRL) has gained prominence as an effective approach for control systems. However, its practical deployment is impeded by state perturbations that can severely impact system performance. Addressing this critical challenge requires robustness verification about performance, which involves tackling two quantitative questions: (i) how to establish guaranteed bounds expected cumulative rewards, and (ii) determine tail rewards. In work, we present the first of...