Combining reinforcement learning with mathematical programming:An approach for optimal design of heat exchanger networks

Heat integration is important for energy-saving in the process industry.It is linked to the persistently challenging task of optimal design of heat exchanger networks(HEN).Due to the inherent highly nonconvex nonlinear and combinatorial nature of the HEN problem,it is not easy to find solutions of high quality for large-scale problems.The reinforcement learning(RL)method,which learns strategies through ongoing exploration and exploitation,reveals advantages in such area.However,due to the complexity of the HEN design problem,the RL method for HEN should be dedicated and designed.A hybrid strategy combining RL with mathematical programming is proposed to take better advantage of both methods.An insightful state representation of the HEN structure as well as a customized reward function is introduced.A Q-learning algorithm is applied to update the HEN structure using theε-greedy strategy.Better results are obtained from three literature cases of different scales.

An Approach to Detect Structural Development Defects in Object-Oriented Programs

Structural development defects essentially refer to code structure that violates object-oriented design principles. They make program maintenance challenging and deteriorate software quality over time. Various detection approaches, ranging from traditional heuristic algorithms to machine learning methods, are used to identify these defects. Ensemble learning methods have strengthened the detection of these defects. However, existing approaches do not simultaneously exploit the capabilities of extracting relevant features from pre-trained models and the performance of neural networks for the classification task. Therefore, our goal has been to design a model that combines a pre-trained model to extract relevant features from code excerpts through transfer learning and a bagging method with a base estimator, a dense neural network, for defect classification. To achieve this, we composed multiple samples of the same size with replacements from the imbalanced dataset MLCQ1. For all the samples, we used the CodeT5-small variant to extract features and trained a bagging method with the neural network Roberta Classification Head to classify defects based on these features. We then compared this model to RandomForest, one of the ensemble methods that yields good results. Our experiments showed that the number of base estimators to use for bagging depends on the defect to be detected. Next, we observed that it was not necessary to use a data balancing technique with our model when the imbalance rate was 23%. Finally, for blob detection, RandomForest had a median MCC value of 0.36 compared to 0.12 for our method. However, our method was predominant in Long Method detection with a median MCC value of 0.53 compared to 0.42 for RandomForest. These results suggest that the performance of ensemble methods in detecting structural development defects is dependent on specific defects.

Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

Shrek:a dynamic object-oriented programming language

From a perspective of theoretical study, there are some faults in the models of the existing object-oriented programming languages. For example, C# does not support metaclasses, the primitive types of Java and C# are not objects, etc. So, this paper designs a programming language, Shrek, which integrates many language features and constructions in a compact and consistent model. The Shrek language is a class-based purely object-oriented language. It has a dynamical strong type system, and adopts a single-inheritance mechanism with Mixin as its complement. It has a consistent class instantiation and inheritance structure, and the ability of intercessive structural computational reflection, which enables it to support safe metaclass programming. It also supports multi-thread programming and automatic garbage collection, and enforces its expressive power by adopting a native method mechanism. The prototype system of the Shrek language is implemented and anticipated design goals are achieved.

Decomposition of Mathematical Programming Models for Aircraft Wing Design Facilitating the Use of Dynamic Programming Approach

Aircraft designers strive to achieve optimal weight-reliability tradeoffs while designing an aircraft. Since aircraft wing skins account for more than fifty percent of their structural weight, aircraft wings must be designed with utmost care and attention in terms of material types and thickness configurations. In particular, the selection of thickness at each location of the aircraft wing skin is the most consequential task for aircraft designers. To accomplish this, we present discrete mathematical programming models to obtain optimal thicknesses either to minimize weight or to maximize reliability. We present theoretical results for the decomposition of these discrete mathematical programming models to reduce computer memory requirements and facilitate the use of dynamic programming for design purposes. In particular, a decomposed version of the weight minimization problem is solved for an aircraft wing with thirty locations (or panels) and fourteen thickness choices for each location to yield an optimal minimum weight design.

Detecting Design Patterns in Object-Oriented Program Source Code by Using Metrics and Machine Learning

Detecting well-known design patterns in object-oriented program source code can help maintainers understand the design of a program. Through the detection, the understandability, maintainability, and reusability of object-oriented programs can be improved. There are automated detection techniques;however, many existing techniques are based on static analysis and use strict conditions composed on class structure data. Hence, it is difficult for them to detect and distinguish design patterns in which the class structures are similar. Moreover, it is difficult for them to deal with diversity in design pattern applications. To solve these problems in existing techniques, we propose a design pattern detection technique using source code metrics and machine learning. Our technique judges candidates for the roles that compose design patterns by using machine learning and measurements of several metrics, and it detects design patterns by analyzing the relations between candidates. It suppresses false negatives and distinguishes patterns in which the class structures are similar. As a result of experimental evaluations with a set of programs, we confirmed that our technique is more accurate than two conventional techniques.

OBJECT-ORIENTED FINITE ELEMENT ANALYSIS AND PROGRAMMING IN VC++

The design of finite element analysis program using object-oriented programming (OOP) techniques is presented. The objects, classes and the subclasses used in the programming are explained. The system of classes library of finite element analysis program and Windows-type Graphical User Interfaces by VC + + and its MFC are developed. The reliability, reusability and extensibility of program are enhanced. It is a reference to develop the large-scale, versatile and powerful systems of object-oriented finite element software.

Automatic Generation of UML Class Diagrams for Object-oriented Design and Programing Course

UML Class diagram generation from textual requirements is an important task in object-oriented design and programing course.This study proposes a method for automatically generating class diagrams from Chinese textual requirements on the basis of Natural Language Processing(NLP)and mapping rules for sentence pattern matching.First,classes are identified through entity recognition rules and candidate class pruning rules using NLP from requirements.Second,class attributes and relationships between classes are extracted using mapping rules for sentence pattern matching on the basis of NLP.Third,we developed an assistant tool integrated into a precision micro classroom system for automatic generation of class diagram,to effectively assist the teaching of object-oriented design and programing course.Results are evaluated with precision,accuracy and recall from eight requirements of object-oriented design and programing course using truth values created by teachers.Our research should benefit beginners of object-oriented design and programing course,who may be students or software developers.It helps them to create correct domain models represented in the UML class diagram.

An Object-Oriented Robot Programming and Simulation System

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The Design and Implementation of an Object-Oriented Hypermedia System

Presents an object-oriented NBO(node-block-object)data model for hypermedia system.It takes advantage of object-oriented method,encapsulates all multimedia information as well as link functions in one unit,It has successfully achieved cross link to offer much better flexibility and two-way link to realize forward and backward searching in hypermedia system navigation.A conditional relation on links has also been realized,that is very helpful for time sensitive multimedia information processing and multimedia object cooperation.

THE OBJECT-ORIENTED INTELLIGENT PROGRAMMING IN CAD/CAM

Design and manufacture organizations currently suffer from a number of problems that aignificantly affect their productivity.Despite their fragmented efforts to automate portioas of operations,they still suffer from 'islands' of designing and manufacturing automation,long lead time for semi-custom proposals and engineering work, lengthy cycles of product development and introduction into the market,and low morale due to boring,repetitive engineering and industrial design activities.Thereby,the integration of design and manufacturing poses to the CAD/CAM researchere a series of challenges.The paper introduces a methodology that allows for the integration of product design with manufacturing process planning and the application of a new software technology known as 'Object-Oriented Intelligent Programming' .The task is achieved through an object-oriented intelligent CAD/CAM environment where a design model from the CAD system can be analysed, and manufacturing process plans with specifications of machining can be automatically determined.The manufacturing information of a part is extracted from the 3D geometric model and the 2D engineering drawing,thus,both geometric and non-geometric attributes of a part can be obtained.

Improved design of reconfigurable frequency response masking filters based on second-order cone programming

In order to improve the design results for the reconfigurable frequency response masking FRM filters an improved design method based on second-order cone programming SOCP is proposed.Unlike traditional methods that separately design the proposed method takes all the desired designing modes into consideration when designing all the subfilters. First an initial solution is obtained by separately designing the subfilters and then the initial solution is updated by iteratively solving a SOCP problem. The proposed method is evaluated on a design example and simulation results demonstrate that jointly designing all the subfilters can obtain significantly lower minimax approximation errors compared to the conventional design method.

Exploration on 5E Teaching Principle-based Education for the Object-oriented Software Construction Course

Most current object-oriented programming courses offered by domestic colleges and universities generally focus on the object-oriented programming language itself,i.e.,the programming grammar of the language,but ignore the design pattern.However,design patterns are essential to software engineering because they can solve common problems in software design and improve code reuse,readability,extensibility,and reliability.Our Object-oriented Software Construction Course is creative since it aims at cultivating students’object-oriented thinking as well as basic abilities required to construct high-quality,object-oriented software.Specifically,we exploit the 5E teaching principle during the education of this course,and present the whole pipeline in the paper.We also provide one case of the factory pattern to further demonstrate the implementation of the 5E teaching principle in the course.The effect of the 5E teaching principle has also been demonstrated.

Accelerating Factor Xa inhibitor discovery with a de novo drug design pipeline

Small-molecule drugs are essential for maintaining human health. The objective of this study is to identify a molecule that can inhibit the Factor Xa protein and be easily procured. An optimization-based de novo drug design framework, Drug CAMD, that integrates a deep learning model with a mixed-integer nonlinear programming model is used for designing drug candidates. Within this framework, a virtual chemical library is specifically tailored to inhibit Factor Xa. To further filter and narrow down the lead compounds from the designed compounds, comprehensive approaches involving molecular docking,binding pose metadynamics(BPMD), binding free energy calculations, and enzyme activity inhibition analysis are utilized. To maximize efficiency in terms of time and resources, molecules for in vitro activity testing are initially selected from commercially available portions of customized virtual chemical libraries. In vitro studies assessing inhibitor activities have confirmed that the compound EN300-331859shows potential Factor Xa inhibition, with an IC_(50)value of 34.57 μmol·L^(-1). Through in silico molecular docking and BPMD, the most plausible binding pose for the EN300-331859-Factor Xa complex are identified. The estimated binding free energy values correlate well with the results obtained from biological assays. Consequently, EN300-331859 is identified as a novel and effective sub-micromolar inhibitor of Factor Xa.

Multi-gene genetic programming extension of AASHTO M-E for design oflow-volume concrete pavements

The American Association of State Highway and Transportation Officials Mechanistic-Empirical Pavement DesignGuide (AASHTO M-E) offers an opportunity to design more economical and sustainable high-volume rigid pavementscompared to conventional design guidelines. It is achieved through optimizing pavement structural andthickness design under specified climate and traffic conditions using advanced M-E principles, thereby minimizingeconomic costs and environmental impact. However, the implementation of AASHTO M-E design for low-volumeconcrete pavements using AASHTOWare Pavement ME Design (Pavement ME) software is often overly conservative.This is because Pavement ME specifies the minimum design thickness of concrete slab as 152.4 mm (6 in.). Thispaper introduces a novel extension of the AASHTO M-E framework for the design of low-volume joint plain concretepavements (JPCPs) without modification of Pavement ME. It utilizes multi-gene genetic programming (MGGP)-based computational models to obtain rapid solutions for JPCP damage accumulation and long-term performanceanalyses. The developed MGGP models simulate the fatigue damage and differential energy accumulations. Thispermits the prediction of transverse cracking and joint faulting for a wide range of design input parameters and axlespectrum. The developed MGGP-based models match Pavement ME-predicted cracking and faulting for rigidpavements with conventional concrete slab thicknesses and enable rational extrapolation of performance predictionfor thinner JPCPs. This paper demonstrates how the developed computational model enables sustainable lowvolumepavement design using optimized ME solutions for Pittsburgh, PA, conditions.

Evolutionary Design of Fault-Tolerant Digital Circuit Based on Cartesian Genetic Programming

In many areas, reliability of the digital circuits has become the key factor to restrict circuit development. Fault-tolerant design is the commonly used method to improve the reliability of digital circuits. The current fault-tolerant design methods are based on triple modular redundancy( TMR) or multiple modular redundancy( MMR). These redundancy designs rely on the experience of the designers,and the designed circuits have poor adaptabilities to a complex environment. However, evolutionary design of digital circuits does not rely on prior knowledge. During the evolution, some novel and optimal circuit topologies can be found, and the evolved circuits can feature strong adaptive capacities. Based on Cartesian genetic programming( CGP), a novel method for designing fault-tolerant digital circuits by evolution is proposed,key steps of the evolution are introduced,influences of function sets on evolution are investigated,and as a preliminary result,an evolved full adder with high fault-tolerance is shown.

Semi-definite programming based pulse waveform design and its further analysis

In order to provide a judicious pulse waveform design required for ultra-wideband(UWB)communication to enable the UWB spectral mask compatible and coexistent with other existing wireless communication systems,a semi-definite programming(SDP)based pulse waveform design method for UWB radios is introduced and a further analysis is given in this paper.By using Sedumi and Yalmip toolboxes of Matlab,the procedure of solving the SDP problem is simplified.Simulation results show that this SDP based pulse waveform design method can be used to design pulses that fulfill the Federal Communications Commission(FCC)spectral mask strictly and optimize the power efficiency at the same time.This paper also analyzes the influences of the power efficiency duing to the changes of sampling interval and the number of combined pulses,and then the optimal sampling interval that maximizes the transmission power can be found.

Joint Beamforming Design for Dual-Functional Radar-Communication Systems Under Beampattern Gain Constraints

The joint beamforming design challenge for dual-functional radar-communication systems is addressed in this paper.The base station in these systems is tasked with simultaneously sending shared signals for both multi-user communication and target sensing.The primary objective is to maximize the sum rate of multi-user communication,while also ensuring sufficient beampattern gain at particular angles that are of interest for sensing,all within the constraints of the transmit power budget.To tackle this complex non-convex problem,an effective algorithm that iteratively optimizes the joint beamformers is developed.This algorithm leverages the techniques of fractional programming and semidefinite relaxation to achieve its goals.The numerical results confirm the effectiveness of the proposed algorithm.

Object-Oriented Design for FDTD Visual Scientific Computing

A scheme for general purposed FDTD visual scientific computing software is introduced in this paper using object-oriented design (OOD) method. By abstracting the parameters of FDTD grids to an individual class and separating from the iteration procedure, the visual software can be adapted to more comprehensive computing problems. Real-time gray degree graphic and wave curve of the results can be achieved using DirectX technique. The special difference equation and data structure in dispersive medium are considered, and the peculiarity of parameters in perfectly matched layer are also discussed.

Research on object-oriented SOC design methodology

The growing complexity of System on Chip （SOC） requres a system level specicanon and design approach. High-level languages such as C＋＋/SystemC can play multiple roles in system design as target languages. There are many practical problems in the application of object-oriented methods for this goal. Based on the analysis of traditional and system-level design methodology, a new object-oriented SOC design methodology with object-oriented design patterns is proposed, which emphasizes high-level design and verification. Aiming at the final goal of developing design patterns specific to SOC design, the reuse of design patterns in SOC systems and the capability of new SOC design patterns are discussed. With the illustration of some concrete examples of SOC design patterns, the application of object-oriented design methodology in the SOC design process is presented.