Development and Application of Intelligent Prediction Software for Broken Rock Zone Thickness of Drifts

In order to seek the economical, practical and effective method of obtaining the thickness of broken rock zone, an emerging intelligent prediction method with adaptive neuro-fuzzy inference system (ANFIS) was introduced into the thickness prediction. And the software with functions of creating and applying prediction systems was devel- oped on the platform of MATLAB6.5. The software was used to predict the broken rock zone thickness of drifts at Li- angbei coal mine, Xinlong Company of Coal Industry in Xuchang city of Henan province. The results show that the predicted values accord well with the in situ measured ones. Thereby the validity of the software is validated and it provides a new approach to obtaining the broken zone thickness.

An Uneven Impact of Emerging Technologies on Taxpayers With Various Income Levels Audited by the IRS: Empirical Evidence From an AI Technology Application and Regression Models

This study aims to investigate the influence of emerging technology adoption on tax compliance, encompassing both the Internal Revenue Service’s (IRS) compliance audits and taxpayers’ compliance performance (collectively, tax compliance). We employed the Gradient Descent optimization algorithm, an artificial intelligence (AI) technology application, to scrutinize the connection between the quality of US tax filings and the development of emerging technology, among other contributing factors. Additionally, we utilized multiple linear regression to evaluate the relationships between dependent variables, specifically IRS audit rates and the no-change rate at different income levels,1 and several independent variables, including a proxy for emerging technology in the form of tax software. Our findings reveal that while emerging technology significantly impacts tax compliance within the IRS and taxpayers’ performance, its effects vary across income groups. Notably, emerging technology seems to confer greater advantages to higher-income individuals compared to their lower-income counterparts. These study results hold considerable policy implications for government decision-makers in promoting the adoption of emerging technology among lower-income taxpayers.

Development of the entire roller inlayed block intelligence cold strip shape meter and its industrial application

The entire roller inlayed block intelligence cold strip shape meter is developed successfully in this paper,which can stably work chronically in the cold rolling workshop,the independent innovation of the key technology of cold strip shape measuring,the foreign technical monopoly and blockade are broken through.The structural form which is different from the international popular segmented detection roller is put forward,the entire detection roller inlayed block is developed,a group of elastic blocks in that the sense organs are installed are inlayed in the radial symmetry rectangular grooves of the detection roller body,the entire roller structure is composed of elastic pieces and the roller body,the scratch of the strip surface due to different thermal expansion of the traditional detection roller measuring unit is avoided effectively.The signal transmission form which is different form the international popular dry slip ring is put forward,the spray wet slip ring is developed,slip ring and detection roller can be taken down and installed as possibly as fast,so the maintain is convenient,while through the section auto-spray cleaning,lubrication and cooling, the service life is remarkable improved and the outside interference signal is reduced.The signal processing form which is different form the international popular gathering card is put forward,the embedded DSP shape signal processing hardware system is developed,the electromagnet,temperature,humidity and vibration's interference of industry practice to shape transmission signal can be effectively avoided,which can guarantee the instantaneity and measured precision of shape measured signal.The shape signal processing software system whose function contains error compensation,pattern recognition,establishment of the target shape and the closed-loop control calculation is built,the shape meter' computer human interaction is friendly,and function of shape meter is strong,at the same time the intellectualized level of the shape meter is improved.Now,this shape meter has been successfully applied on the 1 250 mm cold strip mill of Angang Steel Company Limited,the long-term operating testing is done,every guide line achieves the anticipative effect,the measuring precision is high and the measuring signal is stable and reliable,the shape meter is tested on high speed,big tension,changed wrap angle and big depressed complicated working conditions,any scratch of the detection roller surface and the strip surface is not appearing,it can completely adapt well to the industrial production environment,reaching the international advanced level.

Research on reconfigurable collaborative remote diagnosis system

The function-layer model and working model of collaborative remote fault diagnosis system （FDS）, which includes three layers： task layer, collaboration layer and diagnosing layer, are proposed. The running mechanism of the system is discussed. A collaborative FDS may consist of several subsystems running at different places and the subsystem consists of several fimction modules. A structure centered on data-bus is adopted in subsystem. All the function modules in subsystem are encapsulated into software intelligent chips （SICs） and SIC can but connect with data-bus. So, it is feasible to reuse these diagnosis fimction modules and the structure of subsystem in different diagnosis applications. With the reconfigurable SICs, several different function modules can reconstruct quickly some different diagnosis subsystems in different combinations, and some subsystems can also reconfigure a specified collaborative FDS.

Code Smell Detection Using Whale Optimization Algorithm

Software systems have been employed in many fields as a means to reduce human efforts;consequently,stakeholders are interested in more updates of their capabilities.Code smells arise as one of the obstacles in the software industry.They are characteristics of software source code that indicate a deeper problem in design.These smells appear not only in the design but also in software implementation.Code smells introduce bugs,affect software maintainability,and lead to higher maintenance costs.Uncovering code smells can be formulated as an optimization problem of finding the best detection rules.Although researchers have recommended different techniques to improve the accuracy of code smell detection,these methods are still unstable and need to be improved.Previous research has sought only to discover a few at a time(three or five types)and did not set rules for detecting their types.Our research improves code smell detection by applying a search-based technique;we use the Whale Optimization Algorithm as a classifier to find ideal detection rules.Applying this algorithm,the Fisher criterion is utilized as a fitness function to maximize the between-class distance over the withinclass variance.The proposed framework adopts if-then detection rules during the software development life cycle.Those rules identify the types for both medium and large projects.Experiments are conducted on five open-source software projects to discover nine smell types that mostly appear in codes.The proposed detection framework has an average of 94.24%precision and 93.4%recall.These accurate values are better than other search-based algorithms of the same field.The proposed framework improves code smell detection,which increases software quality while minimizing maintenance effort,time,and cost.Additionally,the resulting classification rules are analyzed to find the software metrics that differentiate the nine code smells.

A REVIEW AND PROSPECT OF READABLE MACHINE PROOFS FOR GEOMETRY THEOREMS

After half a century research, the mechanical theorem proving in geometries has become an active research topic in the automated reasoning field. This review involves three approaches on automated generating readable machine proofs for geometry theorems which include search methods, coordinate-free methods, and formal logic methods. Some critical issues about these approaches are also discussed. Furthermore, the authors propose three further research directions for the readable machine proofs for geometry theorems, including geometry inequalities, intelligent geometry softwares and machine learning.