Code Optimization Method Research Articles

Optimizing the productivity of solutions built with the help of ReactJS and D3 libraries

Problem. Recently, the problem of the performance of web applications has become particularly acute. This is due to the complexity of the software and the simultaneous deterioration of the code quality. The work considers important aspects of performance of the client part of the web application, built using the ReactJS and D3 libraries. React is known to deliver a faster user interface than most competitors, thanks to its in-house, performance-oriented development approach. However, when your React application starts to scale, you may notice some performance issues or lag. Internal optimization methods may not be sufficient to support the growing traffic and complexity of a fast-paced, enterprise-level application. This is where the question arises: "How to improve performance in ReactJS?". Next, the article will consider important aspects of the performance of the client part of the web application, built using the ReactJS and D3 libraries. Goal. The purpose of the article is to develop a React component (optimized by a new method) in the form of a graph, whose data changes in real time. Methodology. Analytical research methods and functional programming methodology were used. Results. The paper considers the problem of optimizing a component built using ReactJS and D3. Its feature is the change of state in real time. A new code optimization method is proposed, which allows to minimize the number of renders. The proposed solutions will enable to more effectively use all the capabilities of the D3 functionality when designing a wide range of monitoring and billing systems and automated process management systems. Originality. A method is proposed that will help improve the performance of the React application and reduce the number of re-renders. The method is developed using additional React hooks and using a reference to the current graphic component from the parent. The method is based on the fundamental property of the D3 library - saving its own state this allows you to get rid of unnecessary renders. Practical value. The proposed solutions will allow you to use all the functionality of D3 when designing a wide range of monitoring and billing systems and automated process management systems. D3 has the flexibility to display a large layer of diverse data and allows data visualization using HTML, SVG and CSS.

A Novel Hybrid Code-Domain Index Modulation Scheme

In this letter, a novel hybrid code-domain index modulation (CDIM) scheme is proposed for future multi-domain communications, where the indices of the interleaving and spreading codes are exploited for information transmission. Specifically, we first provide a general design framework for CDIM, including the bit-to-symbol mapping rule and the detector. Then, we propose a code optimization method to select the utilized interleaver sequence and spreading code, with the objective of significantly improving the bit error ratio (BER) performance. Moreover, an intelligent detector is also proposed for CDIM in complicated wireless communication scenarios, e.g., non-Gaussian wireless channels. Simulation results show that the proposed CDIM is capable of substantially improving the system error performance compared with the conventional coded wireless communication systems.

Code Optimization for Fast Chirp FMCW Automotive MIMO Radar

Fast chirp FMCW MIMO radar with inter-chirp coding provides high emission power by utilizing simultaneous antennas transmissions. However, the coding produces high side-lobes in the Doppler and angle dimensions of the radar's ambiguity function. The high side-lobes may cause miss-detection due to masking between targets that are at similar range and have large received power difference, as is often the case in automotive scenarios. In this paper, we develop a novel code optimization method that attenuates the side-lobes of the radar's ambiguity function and hence improves the probability of detection in the case of multiple targets. We formulate an analytical expression for the ambiguity function side-lobes, which takes into account that the targets range difference migrates during the detection interval, and that the migration is proportional to the targets Doppler frequency difference. We then develop an optimization algorithm that finds the code that minimizes the ambiguity function side-lobes average energy. The optimized code attenuates the ambiguity function side-lobes at the Doppler frequencies that are near the main lobe frequency. These frequencies correspond to targets with small speed difference, for which the range difference between the targets does not change significantly during the detection interval, and hence overlapping in range can cause severe interference. We demonstrate by simulation that the optimized code achieves an improvement in the ambiguity function side-lobes attenuation and an improvement in the probability of detection compared to reference codes.

Ultra-broadband transmissive gradient metasurface based on the topologically coding optimization method.

Metasurfaces have provided a novel way on modulating the wavefront of electromagnetic (EM) waves, where phase modulating is an important method to control EM waves. Normally, phase can be continuously modulated by changing the size of a meta-atom. For a broadband device, it is essential that phase changes linearly varying against frequency within a wide frequency interval, which is quite difficult to design, especially for the transmissive scheme. In this paper, we propose a 0-1 coding method by using genetic algorithm (GA) to realize broadband linear transmission phase and high transmission amplitude against frequency. To verify the method, a beam bending metasurface is designed based on array of six meta-atoms with step gap of 60°. Simulation and experimental results show that the metasurface deflector achieves perfect beam refraction from 8 to 12 GHz, which is consistent with theoretical calculations. Moreover, the working efficiency is kept at about 75%, with the variation of the frequency, which demonstrates the good stability of the metasurface. This method offers a new insight into the designing of broadband devices.

High-efficiency and ultra-broadband asymmetric transmission metasurface based on topologically coding optimization method.

Achieving asymmetric transmission effects, especially in an ultra-broadband frequency region, is of particular importance in communication systems. Currently available asymmetric transmission metasurfaces are limited to narrow bands and low efficiencies because of the inherently dispersion effects and large transmission fluctuations. In this paper, we propose a new strategy to realize high efficiency and ultra-broadband asymmetric transmission in an ultra-thin profile by using the topologically coding optimization method. The meta-atom consists of two outer orthogonal gratings and a central lattice particle optimized by genetic algorithm. The optimized central lattice suppresses the transmission fluctuations by tuning the coupling among different metallic layers, resulting in very broad band and high transmissions. Experimental results show that our metasurface achieved perfect reflection over 95% and high cross-polarization transmission over 80% for y- and x-polarized incidence from 5.3 GHz to 16.7 GHz, respectively. Our findings pave a way to high-performance and broadband polarization transformers and polarization-controlled devices working in different frequency domains.

Dynamic Translation Optimization Method Based on Static Pre-Translation

Binary translation technology is an effective method to solve the problem of software cross-platform transplantation, especially for software porting without source code. Static binary translation has a good translation effect in general, but it faces the problem of code discovery. Dynamic binary translation can completely reproduce the execution process of the source program according to the execution order of the binary code. But it is severely limited by its low efficiency, as the time of translation is part of the whole runtime and it is no time for better code optimization in dynamic binary translation. This paper aims to optimize the execution process of dynamic binary translation by taking full advantage of the strengths of static binary translation. An optimization method of dynamic binary translation with static pre-translation was proposed in this paper. By pre-translating the source program and using more in-depth code optimization method to optimize the translated code, most of the code translation time can be cut down and the translated code will be more efficient. A new dynamic translation framework with the static pre-translation module, based on the dynamic translator named QEMU (a quick emulator), was designed to translate the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> 86 program to the Sunway platform. As the experimental results show, the framework and optimization method are valid to improve the efficiency of the general dynamic translator.

Design of testing framework for code smell detection (OOPS) using BFO algorithm

Detection of bad smells refers to any indication in the program code of a execution that perhaps designate a issue, maintain the software and software evolution. Code Smell detection is a main challenging for software developers and their informal classification direct to the designing of various smell detection methods and software tools. It appraises 4 code smell detection tool in software like as a in Fusion, JDeodorant, PMD and Jspirit. In this research proposes a method for detection the bad code smells in software is called as code smell. Bad smell detection in software, OOSMs are used to identify the Source Code whereby Plug-in were implemented for code detection in which position of program initial code the bad smell appeared so that software refactoring can then acquire position. Classified the code smell, as a type of codes: long method, PIH, LPL, LC, SS and GOD class etc. Detection of the code smell and as a result applying the correct detection phases when require is significant to enhance the Quality of the code or program. The various tool has been proposed for detection of the code smell each one featured by particular properties. The main objective of this research work described our proposed method on using various tools for code smell detection. We find the major differences between them and dissimilar consequences we attained. The major drawback of current research work is that it focuses on one particular language which makes them restricted to one kind of programs only. These tools fail to detect the smelly code if any kind of change in environment is encountered. The base paper compares the most popular code smell detection tools on basis of various factors like accuracy, False Positive Rate etc. which gives a clear picture of functionality these tools possess. In this paper, a unique technique is designed to identify CSs. For this purpose, various object-oriented programming (OOPs)-based-metrics with their maintainability index are used. Further, code refactoring and optimization technique are applied to obtain low maintainability Index. Finally, the proposed scheme is evaluated to achieve satisfactory results. The results of the BFOA test defined that the lazy class caused framework defects in DLS, DR, and SE. However, the LPL caused no framework defects what so ever. The consequences of the connection rules test searched that the LCCS (Lazy Class Code Smell) caused structured defects in DE and DLS, which corresponded to the consequences of the BFOA test. In this research work, a proposed method is designed to verify the code smell. For this purpose, different OOPs based Software Metrics with their MI (Maintainability Index) are utilized. Further Code refactoring and optimization method id applied to attained the less maintainability index and evaluated to achieved satisfactory results.

On Computational Complexity Reduction Methods for Kalman Filter Extensions

The Kalman filter and its extensions are used in a vast number of aerospace and navigation applications for nonlinear state estimation of time series. In the literature, different approaches have been proposed to exploit the structure of the state and measurement models to reduce the computational demand of the algorithms. In this tutorial, we survey existing code optimization methods and present them using unified notation that allows them to be used with various Kalman filter extensions. We develop the optimization methods to cover a wider range of models, show how different structural optimizations can be combined, and present new applications for the existing optimizations. Furthermore, we present an example that shows that the exploitation of the structure of the problem can lead to improved estimation accuracy while reducing the computational load. This tutorial is intended for persons who are familiar with Kalman filtering and want to get insights for reducing the computational demand of different Kalman filter extensions.

A Fast Optimization Method for General Binary Code Learning.

Hashing or binary code learning has been recognized to accomplish efficient near neighbor search, and has thus attracted broad interests in recent retrieval, vision, and learning studies. One main challenge of learning to hash arises from the involvement of discrete variables in binary code optimization. While the widely used continuous relaxation may achieve high learning efficiency, the pursued codes are typically less effective due to accumulated quantization error. In this paper, we propose a novel binary code optimization method, dubbed discrete proximal linearized minimization (DPLM), which directly handles the discrete constraints during the learning process. Specifically, the discrete (thus nonsmooth nonconvex) problem is reformulated as minimizing the sum of a smooth loss term with a nonsmooth indicator function. The obtained problem is then efficiently solved by an iterative procedure with each iteration admitting an analytical discrete solution, which is thus shown to converge very fast. In addition, the proposed method supports a large family of empirical loss functions, which is particularly instantiated in this paper by both a supervised and an unsupervised hashing losses, together with the bits uncorrelation and balance constraints. In particular, the proposed DPLM with a supervised ℓ2 loss encodes the whole NUS-WIDE database into 64-b binary codes within 10 s on a standard desktop computer. The proposed approach is extensively evaluated on several large-scale data sets and the generated binary codes are shown to achieve very promising results on both retrieval and classification tasks.

Evolution of Angiosperm Pollen. 1. Introduction1

This paper is the first in a series that documents the diversity, distribution, and evolution of palynological characters across angiosperms in a contemporary phylogenetic context, using modern optimization methods. The objectives of the series are: (1) to describe the diversity of pollen morphologies across the angiosperms; (2) to estimate ancestral palynological character states, diagnostic characters, and synapomorphies for monophyletic groups; (3) to highlight and interpret inferred patterns and processes of evolution in palynological characters; and (4) to provide a framework for the placement of enigmatic taxa (including fossil taxa) based on pollen morphology. This first paper examines the methods available for such a study and presents an overview of palynological characters across angiosperms as a whole. Using a well-supported, recent, molecular phylogeny, we consider the effects of coding strategy, method of optimization, and starting tree topology upon inference of trait evolution. Coding strategy and optimization method had significant effects upon inferred ancestral character states, the latter probably due to the different evolutionary models applied. Phylogenetic topology had little effect upon inferred ancestral character states, because the uncertainty in topology at this level involved only nodes where few character state changes occurred. Several palynological characters showed consistent, structured patterns in the context of phylogeny: angiosperms are distinguished from other seed plants by character states including supratectal elements echinate and less than 1 mu m in size, and infratectum structure columellate; eudicots, as recognized in previous studies, may be defined by globose, isopolar, radially symmetrical grains with three equatorial apertures. We present a framework for the remainder of the series, in which the angiosperms are divided into nine monophyletic and paraphyletic groups each having a similar level of pollen variability, and a set of recommendations for the analysis of these groups. The series will provide a reference for future palynological and systematic studies and an approach that may be replicated for other character sets.

Scaling Law for Hysteresis Losses in Round Superconductors Magnetized by Alternating, Rotating or Elliptical Magnetic Fields

AC losses in an isolated superconducting round wire with a power-law electrical behavior produced by the combined effect of transverse alternating and rotating fields, i.e., an elliptical field, are investigated. The goal is to provide semianalytical expressions of the magnetization losses with a high enough reliability to be used in sizing code development or optimization methods. The fit expressions are based on data generated by means of a 2-D numerical model using the well-known and proved H-formulation. In the meantime, data processing allows for revealing a universal variable cn of utmost importance in magnetization loss calculation. This variable depends on the n-value of the power-law resistivity, and both the dimensionless magnetic field b* and frequency f*.

Early exit from a function as method of code optimization in the component environments

This paper presents the use of code optimization method in the component environments (Java VM, MS .NET, Mono). In the proposed solution implemented for component environments there are occurrences when manual code optimization can accelerate run time of programs. In components environments, due to the JIT (Just In Time) optimization, the code cannot be fully optimized because of the short time available. JIT optimization takes place during execution of the currently used part of the code. That is why the time spent on searching the best optimization must be balanced between the user waiting time and the choice of optimal optimization. This article presents optimization method ending with conclusion on when, why and in which component environment is recommended to use a given method. The presented methods is called early exit from function (authorial method).

Network Coding Optimization Method Research Based on Genetic Algorithm

Network coding optimization method research based on genetic algorithm applies network coding technology in monophyletic multicast network. After reaching network multicast rate, find link coding scheme which makes the minimum of the total number of network coding. Moreover, it makes the analysis and improvement for general genetic algorithm’s defects in network coding link optimization such as rare individual successful decoded by randomly generated initial population strategies, reduced algorithm search ability, premature convergence of genetic algorithm and long algorithm running time.

Energy Efficient Security Algorithm for Power Grid Wide Area Monitoring System

Modern power grid is the most complex human-made system, which is monitored by wide-area monitoring system (WAMS). Providing time-synchronized data of power system operating states, WAMS will play a crucial role in next generation smart grid protection and control. WAMS helps secure efficient energy transmission as well as reliable and optimal grid management. As the key enabler of a smart grid, numerous sensors such as PMU and current sensors transmit real-time dynamic data, which is usually protected by encryption algorithm from malicious attacks, over wide-area-network (WAN) to power system control centers so that monitoring and control of the whole system is possible. Security algorithms for power grid need to consider both performance and energy efficiency through code optimization techniques on encryption and decryption. In this paper, we take power nodes (sites) as platforms to experimentally study ways of energy consumptions in different security algorithms. First, we measure energy consumptions of various security algorithms on CrossBow and Ember sensor nodes. Second, we propose an array of novel code optimization methods to increase energy consumption efficiency of different security algorithms. Finally, based on careful analysis of measurement results, we propose a set of principles on using security algorithms in WAMS nodes, such as cryptography selections, parameter configuration, and the like. Such principles can be used widely in other computing systems with energy constraints.

An Efficient Framework for Configurable Video Encoder

The implementation of real-time video coding systems with limited resources such as memory volume and CPU speed is a challenging task. In this paper, an efficient embedded multi-modal MPEG-4 video encoder (EMVC) is proposed and implemented to meet the requirement of encoding different modals (colors, resolutions, and bandwidths) video in size and power-restricted scenario. The hardware framework of EMVC is based on FPGA and DSP, which takes full advantage of the strongpoint of DSP and FPGA—powerful digital signal processing ability of DSP is utilized to complete most of the complex video coding, and flexible configuration, the parallelism and high speed of FPGA cooperates to accomplish logical control and auxiliary functions in video coding. The hardware framework is designed with strong processing ability, flexible configuration, and extensive coverage. In software design, we first improve some key algorithms in MPEG-4 standard that have great impact on coding efficiency, a fast motion estimation algorithm—smooth motion vector field adaptive search technique (SMVFAST) and a DSP-based efficient quantization computation method—EQ4DSP are put forward respectively; second, according to the characters of DSP's hardware resource, the encoder software is optimized at system and code levels. At the system level, EDMA (Enhanced Direct Memory Access) channels in DSP are used to parallel the data transfer, and the software structure of the video encoders is changed from frame-based to GMB-based (Group of Macro-Block) to make use of the parallel processing capacity of DSP. At code level, the codes of the frequently called modules in the encoder are the critical optimized part, and the main code optimization methods used in EMVC include: using an intrinsic function to replace the complicated C/C++ code, using packed data processing to maximize the data throughput, unrolling the loop to increase software pipelines, translating C code to Linear Assembly, and so on. By making use of the reserved user-data field in the MPEG-4 standard syntax, a multi-modal function of EMVC is realized, namely, the system can switch among 720 × 576 and 352 × 288 resolutions, grey and color video, 2 M and 256 K bandwidth. Moreover, the mode switch can be achieved in real time according to the input control command. Experimental results show that EMVC not only runs efficiently but also has good flexibility and generality. Furthermore, by realizing diverse video or image coding algorithms, it can also satisfy the requirements of various embedded video applications, especially those with strict restriction in size, power consumption, and control flexibility.

Transmission code optimization method for incoherent scatter radar

Abstract. When statistical inversion of a lag profile is used to determine an incoherent scatter target, the posterior variance of the estimated target can be used to determine how well a set of transmission codes perform. In this work we present an incoherent scatter radar transmission code optimization search method suitable for different modulation types, including binary phase, polyphase and amplitude modulation. We found that the combination of amplitude and phase modulation provides better performance than traditional binary phase coding, in some cases giving better accuracy than alternating codes.

Code Optimization of Polynomial Approximation Functions on Clustered Instruction-Level Parallelism Processors

The authors propose a general code optimization method for implementing polynomial approximation functions on clustered instruction-level parallelism (ILP) processors. In the proposed method, we first introduce the parallel algorithm with minimized data dependency. We then schedule and map the data dependency graph (DDG) constructed based on the parallel algorithm to appropriate clusters and functional units of a specific clustered ILP processor using the proposed parallel scheduling and mapping (PSAM) algorithm. The PSAM algorithm prioritizes those nodes on the critical path to minimize the total schedule length and ensures that the resulting schedule satisfies the resource constraints imposed by a specific cluster ILP processor. As a result, our method produces schedule lengths close to the lower bounds determined by the critical path lengths of the DDGs. Experimental results of typical polynomial mathematical functions on TI 'C67x DSP show that the proposed method achieves significant performance improvement over the traditional computation method.

CODE OPTIMIZATION OF POLYNOMIAL APPROXIMATION FUNCTIONS ON CLUSTERED INSTRUCTION-LEVEL PARALLELISM PROCESSORS

The authors propose a general code optimization method for implementing polynomial approximation functions on clustered instruction-level parallelism (ILP) processors. In the proposed method, we fi...

Unified Phase Compiler by Use of 3-D Representation Space

A novel unified phase compiler framework for embedded VLIWs and DSPs is shown. In this compiler, a given program is represented in 3-D representation space, which enables quantitatively estimating required resources and elapsed time. Transformation of a 3-D representation graph that corresponds to a code optimization method for a specific processor architecture is also proposed. The proposal compiler and the code optimization methods are compared with an ordinary compiler in terms of their generated codes. The results demonstrate their effectiveness.

Memory Allocation and Code Optimization Methods for DSPs with Indexed Auto-Modification

A memory address allocation method for digital signal processors of indirect addressing with indexed auto-modification is proposed. At first, address auto-modification amounts for a given program are analyzed. And then, address allocation of program variables are moved and shifted so that both indexed and simple auto-modifications are effectively exploited. For further reduction in overhead codes, a memory address allocation method coupled with computational reordering is proposed. The proposed methods are applied to the existing compiler, and generated codes prove their effectiveness.