The Computational Theory of Intelligence: Applications to Genetic Programming and Turing Machines

In this paper, we continue the efforts of the Computational Theory of Intelligence (CTI) by extending concepts to include computational processes in terms of Genetic Algorithms (GA’s) and Turing Machines (TM’s). Active, Passive, and Hybrid Computational Intelligence processes are also introduced and discussed. We consider the ramifications of the assumptions of CTI with regard to the qualities of reproduction and virility. Applications to Biology, Computer Science and Cyber Security are also discussed.

Optimization Techniques for GPU-Based Parallel Programming Models in High-Performance Computing

This study embarks on a comprehensive examination of optimization techniques within GPU-based parallel programming models,pivotal for advancing high-performance computing(HPC).Emphasizing the transition of GPUs from graphic-centric processors to versatile computing units,it delves into the nuanced optimization of memory access,thread management,algorithmic design,and data structures.These optimizations are critical for exploiting the parallel processing capabilities of GPUs,addressingboth the theoretical frameworks and practical implementations.By integrating advanced strategies such as memory coalescing,dynamic scheduling,and parallel algorithmic transformations,this research aims to significantly elevate computational efficiency and throughput.The findings underscore the potential of optimized GPU programming to revolutionize computational tasks across various domains,highlighting a pathway towards achieving unparalleled processing power and efficiency in HPC environments.The paper not only contributes to the academic discourse on GPU optimization but also provides actionable insights for developers,fostering advancements in computational sciences and technology.

ON LINE COMPUTATION OF EMPIRICAL FORMULA BY MEANS OF ELEMENTAL ANALYSIS AND ITS PROGRAM DESIGN

On line determination of empirical formula for organic compounds with an automatic elemental analyzer and its program design method were investigated. The computational results shews that the reliability of computational results depends on the accuracy of the analytical data and the organic compound itself.

Energy-Optimal and Delay-Bounded Computation Offloading in Mobile Edge Computing with Heterogeneous Clouds

By Mobile Edge Computing(MEC), computation-intensive tasks are offloaded from mobile devices to cloud servers, and thus the energy consumption of mobile devices can be notably reduced. In this paper, we study task offloading in multi-user MEC systems with heterogeneous clouds, including edge clouds and remote clouds. Tasks are forwarded from mobile devices to edge clouds via wireless channels, and they can be further forwarded to remote clouds via the Internet. Our objective is to minimize the total energy consumption of multiple mobile devices, subject to bounded-delay requirements of tasks. Based on dynamic programming, we propose an algorithm that minimizes the energy consumption, by jointly allocating bandwidth and computational resources to mobile devices. The algorithm is of pseudo-polynomial complexity. To further reduce the complexity, we propose an approximation algorithm with energy discretization, and its total energy consumption is proved to be within a bounded gap from the optimum. Simulation results show that, nearly 82.7% energy of mobile devices can be saved by task offloading compared with mobile device execution.

Design and realization of runtime library support for irregular computation

Firstly analyzes the CHAOS and points out its shortages, and then uses the basic method—inspector/executor to deal with irregular computation, and offers the realization scheme for the CHAOS+ runtime library that supports irregular computation, and finally gives the node code program to show the example with CHAOS+ runtime library.

Programming for scientific computing on peta-scale heterogeneous parallel systems

Peta-scale high-perfomlance computing systems are increasingly built with heterogeneous CPU and GPU nodes to achieve higher power efficiency and computation throughput. While providing unprecedented capabilities to conduct computational experiments of historic significance, these systems are presently difficult to program. The users, who are domain experts rather than computer experts, prefer to use programming models closer to their domains （e.g., physics and biology） rather than MPI and OpenME This has led the development of domain-specific programming that provides domain-specific programming interfaces but abstracts away some performance-critical architecture details. Based on experience in designing large-scale computing systems, a hybrid programming framework for scientific computing on heterogeneous architectures is proposed in this work. Its design philosophy is to provide a collaborative mechanism for domain experts and computer experts so that both domain-specific knowledge and performance-critical architecture details can be adequately exploited. Two real-world scientific applications have been evaluated on TH-IA, a peta-scale CPU-GPU heterogeneous system that is currently the 5th fastest supercomputer in the world. The experimental results show that the proposed framework is well suited for developing large-scale scientific computing applications on peta-scale heterogeneous CPU/GPU systems.

APPLICATIONS OF THE PACK & UNPACK TECHNIQUE IN VECTOR COMPUTATION

This article describes the pack & unpack performance of the vector using YH-1 supercomputer as its platform, with its emphasis on the pack & unpack technique's unique application to vector computation, in the light of vector computer's characteristics and some practical cases. The practical numerical experiment proves that the pack & unpack techniques is a key method to the depth parallel development and vectorization research of large scale scientific computation project, and which is a highly effective method to vectorizing application programs.

Design of a Computational Heuristic to Solve the Nonlinear Liénard Differential Model

In this study,the design of a computational heuristic based on the nonlinear Liénard model is presented using the efficiency of artificial neural networks(ANNs)along with the hybridization procedures of global and local search approaches.The global search genetic algorithm(GA)and local search sequential quadratic programming scheme(SQPS)are implemented to solve the nonlinear Liénard model.An objective function using the differential model and boundary conditions is designed and optimized by the hybrid computing strength of the GA-SQPS.The motivation of the ANN procedures along with GA-SQPS comes to present reliable,feasible and precise frameworks to tackle stiff and highly nonlinear differentialmodels.The designed procedures of ANNs along with GA-SQPS are applied for three highly nonlinear differential models.The achieved numerical outcomes on multiple trials using the designed procedures are compared to authenticate the correctness,viability and efficacy.Moreover,statistical performances based on different measures are also provided to check the reliability of the ANN along with GASQPS.

Modeling and Simulation for High Energy Sub-Nuclear Interactions Using Evolutionary Computation Technique

High energy sub-nuclear interactions are a good tool to dive deeply in the core of the particles to recognize their structures and the forces governed. The current article focuses on using one of the evolutionary computation techniques, the so-called genetic programming (GP), to model the hadron nucleus (h-A) interactions through discovering functions. In this article, GP is used to simulate the rapidity distribution of total charged, positive and negative pions for p--Ar and p--Xe interactions at 200 GeV/c and charged particles for p-pb collision at 5.02 TeV. We have done so many runs to select the best runs of the GP program and finally obtained the rapidity distribution as a function of the lab momentum , mass number (A) and the number of particles per unit solid angle (Y). In all cases studied, we compared our seven discovered functions produced by GP technique with the corresponding experimental data and the excellent matching was so clear.

PARALLEL COMPUTATIONAL ALGORITHM OF SUBSTRUCTURE METHOD OF LARGE-SCALE STRUCTURE ANALYSIS

In this paper, according to the parallel environment of ELXSI computer, a parallel solving process of substructure method in static and dynamic analyses of large-scale and complex structure has been put forward, and the corresponding parallel computational program has been developed.

A New Approach of Solving Linear Fractional Programming Problem (LFP) by Using Computer Algorithm

In this paper, we study a new approach for solving linear fractional programming problem (LFP) by converting it into a single Linear Programming (LP) Problem, which can be solved by using any type of linear fractional programming technique. In the objective function of an LFP, if βis negative, the available methods are failed to solve, while our proposed method is capable of solving such problems. In the present paper, we propose a new method and develop FORTRAN programs to solve the problem. The optimal LFP solution procedure is illustrated with numerical examples and also by a computer program. We also compare our method with other available methods for solving LFP problems. Our proposed method of linear fractional programming (LFP) problem is very simple and easy to understand and apply.

An Empirical Study of the Optimum Team Size Requirement in a Collaborative Computer Programming/Learning Environment

Pair programming has been widely acclaimed the best way to go in computer programming. Recently, collaboration involving more subjects has been shown to produce better results in programming environments. However, the optimum group size needed for the collaboration has not been adequately addressed. This paper seeks to inculcate and acquaint the students involved in the study with the spirit of team work in software projects and to empirically determine the effective (optimum) team size that may be desirable in programming/learning real life environments. Two different experiments were organized and conducted. Parameters for determining the optimal team size were formulated. Volunteered participants of different genders were randomly grouped into five parallel teams of different sizes ranging from 1 to 5 in the first experiment. Each team size was replicated six times. The second experiment involved teams of same gender compositions (males or females) in different sizes. The times (efforts) for problem analysis and coding as well as compile-time errors (bugs) were recorded for each team size. The effectiveness was finally analyzed for the teams. The study shows that collaboration is highly beneficial to new learners of computer programming. They easily grasp the programming concepts when the learning is done in the company of others. The study also demonstrates that the optimum team size that may be adopted in a collaborative learning of computer programming is four.

A revised version of the program VEC (visual computing in electron crystallography)

The program package VEC （Visual computing in Electron Crystallography） has been revised such that （i） a program converting one-line symbols to two-line symbols of （3＋1）-dimensional superspace groups has been incorporated into VEC so that the latter can interpret both kinds of symbols; （ii） a bug in calculating structure factors of onedimensionally incommensurate modulated crystals has been fixed. The correction has been verified by successfully matching the experimental electron microscopy image of an incommensurate crystal with a series of simulated images. The precompiled revised version of VEC and relevant materials are available on the Web at http：//cryst.iphy.ac.cn.

CALCULATION OF ADIABATIC TEMPERATURE THROUGH COMPUTER PROGRAM IN PROCESS OF COMBUSTION SYNTHESIS

The adiabatic temperature in the process of self-propagating high temperature synthesis iscalculated through FOXBASE language program on the base of establishing thermodynamic datapool concerned.The adiabatic temperature of some common self-propagating high temperaturesynthesis has been calculated,and the computed results are compared with the adiabatic tempera-ture reported.At the same time,the curve about the influence of preheating temperature andadding diluent on Tadis drawn as an example.

A Computer Program for Dynamic Load Simulation of Spur Gears with Asymmetric and Symmetric Teeth

An important concern in gear design is to reduce the dynamic load and noise of gear systems. It has been found that the noise generated from gearing is basically due to gearbox vibration excited by the dynamic load. Since one of the situations that demand high performance is the high rotational speeds, there is a need to understand the dynamic behavior of the gears at such speeds. Such knowledge would shed light on detrimental characteristics like dynamic loads and vibrations. An efficient way in performing studies on the dynamic behavior of gears is using computer aided analysis on numerical models. In this paper, a developed computer program is introduced to analyze dynamic behavior of spur gears with asymmetric teeth that have a potential use for higher performance in wind turbine gearboxes. This program can be used to compare conventional spur gears with symmetric teeth and spur gears with asymmetric teeth. By using this program, gear designers can design a gear pair and obtain results, e.g dynamic Load, transmitted torque, static transmission error, and frequency spectra of static transmission error etc., just by pressing a command button.

Computer Program Calculation for Distortion of Wide-Band Track and Hold Amplifier

Tow different computer calculation methods for distortion of the wide-band diode bridge track and hold amplifier (THA) are presented based on a high frequency Schottky diode model. One of the computer programs calculates the distortion of weekly nonlinear THA based on the KCL and the nonlinear-current method. The other calculates the weekly nonlinear distortion by using a Volterra series method and a nodal formulation. Comparative calculation results for the diode bridge THA have shown good agreement with these two computer program calculation methods, whereas the overall computational efficiency of the nonlinear-current method is better than that of the nodal formulation method in a special evaluation.

Computer program of nonlinear, curved regression for ‘probacent’-probability equation in biomedicine

On the basis of experimental observations on animals, applications to clinical data on patients and theoretical statistical reasoning, the author developed a com-puter-assisted general mathematical model of the ‘probacent’-probability equation, Equation (1) and death rate (mortality probability) equation, Equation (2) derivable from Equation (1) that may be applica-ble as a general approximation method to make use-ful predictions of probable outcomes in a variety of biomedical phenomena [1-4]. Equations (1) and (2) contain a constant, γ and c, respectively. In the pre-vious studies, the author used the least maximum- difference principle to determine these constants that were expected to best fit reported data, minimizing the deviation. In this study, the author uses the method of computer-assisted least sum of squares to determine the constants, γ and c in constructing the ‘probacent’-related formulas best fitting the NCHS- reported data on survival probabilities and death rates in the US total adult population for 2001. The results of this study reveal that the method of com-puter-assisted mathematical analysis with the least sum of squares seems to be simple, more accurate, convenient and preferable than the previously used least maximum-difference principle, and better fit-ting the NCHS-reported data on survival probabili-ties and death rates in the US total adult population. The computer program of curved regression for the ‘probacent’-probability and death rate equations may be helpful in research in biomedicine.

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.

UAV flight strategy algorithm based on dynamic programming

Unmanned aerial vehicles(UAVs) may play an important role in data collection and offloading in vast areas deploying wireless sensor networks, and the UAV’s action strategy has a vital influence on achieving applicability and computational complexity. Dynamic programming(DP) has a good application in the path planning of UAV, but there are problems in the applicability of special terrain environment and the complexity of the algorithm.Based on the analysis of DP, this paper proposes a hierarchical directional DP(DDP) algorithm based on direction determination and hierarchical model. We compare our methods with Q-learning and DP algorithm by experiments, and the results show that our method can improve the terrain applicability, meanwhile greatly reduce the computational complexity.