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  • Open Access

    REVIEW

    A Survey on Machine Learning in Chemical Spectral Analysis

    Dongfang Yu, Jinwei Wang*

    Journal of Information Hiding and Privacy Protection, Vol.2, No.4, pp. 165-174, 2020, DOI:10.32604/jihpp.2020.010466

    Abstract Chemical spectral analysis is contemporarily undergoing a revolution and drawing much attention of scientists owing to machine learning algorithms, in particular convolutional networks. Hence, this paper outlines the major machine learning and especially deep learning methods contributed to interpret chemical images, and overviews the current application, development and breakthrough in different spectral characterization. Brief categorization of reviewed literatures is provided for studies per application apparatus: X-Ray spectra, UV-Vis-IR spectra, Micro-scope, Raman spectra, Photoluminescence spectrum. End with the overview of existing circumstances in this research area, we provide unique insight and promising directions for the chemical imaging field to fully couple… More >

  • Open Access

    ARTICLE

    Image Denoising with GAN Based Model

    Peizhu Gong, Jin Liu*, Shiqi Lv

    Journal of Information Hiding and Privacy Protection, Vol.2, No.4, pp. 155-163, 2020, DOI:10.32604/jihpp.2020.010453

    Abstract Image denoising is often used as a preprocessing step in computer vision tasks, which can help improve the accuracy of image processing models. Due to the imperfection of imaging systems, transmission media and recording equipment, digital images are often contaminated with various noises during their formation, which troubles the visual effects and even hinders people’s normal recognition. The pollution of noise directly affects the processing of image edge detection, feature extraction, pattern recognition, etc., making it difficult for people to break through the bottleneck by modifying the model. Many traditional filtering methods have shown poor performance since they do not… More >

  • Open Access

    ARTICLE

    Image Steganography in Spatial Domain: Current Status, Techniques, and Trends

    Adeeb M. Alhomoud*

    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 69-88, 2021, DOI:10.32604/iasc.2021.014773

    Abstract This research article provides an up-to-date review of spatial-domain steganography. Maintaining the communication as secure as possible when transmitting secret data through any available communication channels is the target of steganography. Currently, image steganography is the most developed field, with several techniques are provided for different image formats. Therefore, the general image steganography including the fundamental concepts, the terminology, and the applications are highlighted in this paper. Further, the paper depicts the essential characteristics between information hiding and cryptography systems. In addition, recent well-known techniques in the spatial-domain steganography, such as LSB and pixel value differencing, are discussed in detail… More >

  • Open Access

    ARTICLE

    Hybrid Multimodal Biometric Template Protection

    Naima Bousnina1, Sanaa Ghouzali2,*, Mounia Mikram1,3, Maryam Lafkih1, Ohoud Nafea4, Muna Al-Razgan2, Wadood Abdul4

    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 35-51, 2021, DOI:10.32604/iasc.2021.014694

    Abstract Biometric template disclosure starts gaining an important concern in deploying practical biometric authentication systems, where an assailant compromises the database for illegitimate access. To protect biometric templates from disclosure attacks, biometric authentication systems should meet these four requirements: security, diversity, revocability, and performance. Different methods have been suggested in the literature such as feature transformation techniques and biometric cryptosystems. However, no single method could satisfy the four requirements, giving rise to the deployment of hybrid mechanisms. In this context, the current paper proposes a hybrid system for multimodal biometric template protection to provide robustness against template database attacks. Herein, a… More >

  • Open Access

    ARTICLE

    Building Graduate Salary Grading Prediction Model Based on Deep Learning

    Jong-Yih Kuo*, Hui-Chi Lin, Chien-Hung Liu

    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 53-68, 2021, DOI:10.32604/iasc.2021.014437

    Abstract Predicting salary trends of students after employment is vital for helping students to develop their career plans. Particularly, salary is not only considered employment information for students to pursue jobs, but also serves as an important indicator for measuring employability and competitiveness of graduates. This paper considers salary prediction as an ordinal regression problem and uses deep learning techniques to build a salary prediction model for determining the relative ordering between different salary grades. Specifically, to solve this problem, the model uses students’ personal information, grades, and family data as input features and employs a multi-output deep neural network to… More >

  • Open Access

    ARTICLE

    Investigating Crucial Factors of Agile Software Development through Composite Approach

    AbdulHafeez Muhammad1, Ansar Siddique2,*, Quadri Noorulhasan Naveed3, Usman Saleem1, Mohd Abul Hasan4, Basit Shahzad5

    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 15-34, 2021, DOI:10.32604/iasc.2021.014427

    Abstract The major emphasis of Software Engineering (SE) discipline is to produce successful software systems. The success of software projects is estimated through quadruple measures including budget, cost, scope, and quality. To meet this aim of SE, several software development processes are presented in the literature. Such processes are categorized into two different methodologies which are known as traditional and agile software development methodologies. The issue with traditional software development methodologies is that they had not shown any remarkable progress towards the fundamental goal of SE. Consequently, software development organizations have started to adopt agile methodologies in the pursuit of successful… More >

  • Open Access

    ARTICLE

    Improved Channel Allocation Scheme for Cognitive Radio Networks

    Shahzad Latif1, Suhail Akraam2, Arif Jamal Malik3, Aaqif Afzaal Abbasi3, Muhammad Habib3, Sangsoon Lim4,*

    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 103-114, 2021, DOI:10.32604/iasc.2021.014388

    Abstract

    In recent years, wireless channel optimization technologies witnessed tremendous improvements. In this regard, research for developing wireless spectrum for accommodating a wider range of wireless devices increased. This also helped in resolving spectrum scarcity issues. Cognitive Radio (CR) is a type of wireless communication in which a transceiver can intelligently detect which communication channels are being used. To avoid interference, it instantly moves traffic into vacant channels by avoiding the occupied ones. Cognitive Radio (CR) technology showed the potential to deal with the spectrum shortage problem. The spectrum assignment is often considered as a key research challenge in Cognitive Radio… More >

  • Open Access

    ARTICLE

    Parallel Equilibrium Optimizer Algorithm and Its Application in Capacitated Vehicle Routing Problem

    Zonglin Fu1, Pei Hu1, Wei Li2, Jeng-Shyang Pan1,*, Shuchuan Chu1

    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 233-247, 2021, DOI:10.32604/iasc.2021.014192

    Abstract The Equilibrium Optimizer (EO) algorithm is a novel meta-heuristic algorithm based on the strength of physics. To achieve better global search capability, a Parallel Equilibrium Optimizer algorithm, named PEO, is proposed in this paper. PEO is inspired by the idea of parallelism and adopts two different communication strategies between groups to improve EO. The first strategy is used to speed up the convergence rate and the second strategy promotes the algorithm to search for a better solution. These two kinds of communication strategies are used in the early and later iterations of PEO respectively. To check the optimization effect of… More >

  • Open Access

    ARTICLE

    A Negotiated Pricing Model for Innovation Services Based on the Multiobjective Genetic Algorithm

    Yan Zhou1,*, Yue Li1, Yunxing Zhang2

    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 191-203, 2021, DOI:10.32604/iasc.2021.014142

    Abstract Service pricing is a bottleneck in the development of innovation services, as it is the issue of most concern to the suppliers and demanders. In this paper, a negotiated pricing model that is based on the multiobjective genetic algorithm is developed for innovation services. Regarding the process of service pricing as a multiobjective problem, the objective functions which include the service price, service efficiency, and service quality for the suppliers and the demanders are constructed. Because the solution of a multiobjective problem is typically a series of alternatives, an additional negotiation process is necessary in determining the final decision. A… More >

  • Open Access

    ARTICLE

    Tyre Inspection through Multi-State Convolutional Neural Networks

    C. Sivamani1, M. Rajeswari2, E. Golden Julie3, Y. Harold Robinson4, Vimal Shanmuganathan5, Seifedine Kadry6, Yunyoung Nam7,*

    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 1-13, 2021, DOI:10.32604/iasc.2021.013705

    Abstract Road accident is a potential risk to the lives of both drivers and passers-by. Many road accidents occur due to the improper condition of the vehicle tyres after long term usage. Thus, tyres need to be inspected and analyzed while manufacturing to avoid serious road problems. However, tyre wear is a multifaceted happening. It normally needs the non-linearly on many limitations, like tyre formation and plan, vehicle category, conditions of the road. Yet, tyre wear has numerous profitable and environmental inferences particularly due to maintenance costs and traffic safety implications. Thus, the risk to calculate tyre wear is therefore of… More >

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