Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (22,095)
  • Open Access

    ARTICLE

    Fuzzy Control Based Resource Scheduling in IoT Edge Computing

    Samah Alhazmi, Kailash Kumar*, Soha Alhelaly

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4855-4870, 2022, DOI:10.32604/cmc.2022.024012

    Abstract Edge Computing is a new technology in Internet of Things (IoT) paradigm that allows sensitive data to be sent to disperse devices quickly and without delay. Edge is identical to Fog, except its positioning in the end devices is much nearer to end-users, making it process and respond to clients in less time. Further, it aids sensor networks, real-time streaming apps, and the IoT, all of which require high-speed and dependable internet access. For such an IoT system, Resource Scheduling Process (RSP) seems to be one of the most important tasks. This paper presents a RSP for Edge Computing (EC).… More >

  • Open Access

    ARTICLE

    Data Hiding in AMBTC Images Using Selective XOR Hiding Scheme

    Yung-Yao Chen1,*, Yu-Chen Hu2, Ting-Kai Yang3, You-An Wang3

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5167-5182, 2022, DOI:10.32604/cmc.2022.023993

    Abstract Nowadays since the Internet is ubiquitous, the frequency of data transfer through the public network is increasing. Hiding secure data in these transmitted data has emerged broad security issue, such as authentication and copyright protection. On the other hand, considering the transmission efficiency issue, image transmission usually involves image compression in Internet-based applications. To address both issues, this paper presents a data hiding scheme for the image compression method called absolute moment block truncation coding (AMBTC). First, an image is divided into non-overlapping blocks through AMBTC compression, the blocks are classified four types, namely smooth, semi-smooth, semi-complex, and complex. The… More >

  • Open Access

    ARTICLE

    Robust Watermarking of Screen-Photography Based on JND

    Siyu Gu1, Jin Han1,*, Xingming Sun1,2, Yi Cao1,3

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4819-4833, 2022, DOI:10.32604/cmc.2022.023955

    Abstract With the popularity of smartphones, it is often easy to maliciously leak important information by taking pictures of the phone. Robust watermarking that can resist screen photography can achieve the protection of information. Since the screen photo process can cause some irreversible distortion, the currently available screen photo watermarks do not consider the image content well and the visual quality is not very high. Therefore, this paper proposes a new screen-photography robust watermark. In terms of embedding region selection, the intensity-based Scale-invariant feature transform (SIFT) algorithm used for the construction of feature regions based on the density of feature points,… More >

  • Open Access

    ARTICLE

    Hydrodynamics and Heat Transfer Analysis of Airflow in a Sinusoidally Curved Channel

    Abid. A. Memon1, M. Asif Memon1, Kaleemullah Bhatti1, Thanin Sitthiwirattham2,*, Nichaphat Patanarapeelert3

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4835-4853, 2022, DOI:10.32604/cmc.2022.023912

    Abstract For heat transfer enhancement in heat exchangers, different types of channels are often tested. The performance of heat exchangers can be made better by considering geometry composed of sinusoidally curved walls. This research studies the modeling and simulation of airflow through a units long sinusoidally curved wavy channel. For the purpose, two-dimensional Navier Stokes equations along with heat equations are under consideration. To simulate the fluid flow problem, the finite element-based software COMSOL Multiphysics is used. The parametric study for Reynolds number from to and the period of vibration P from to are observed. The surface plots, streamline patterns, contours,… More >

  • Open Access

    ARTICLE

    Optimized Ensemble Algorithm for Predicting Metamaterial Antenna Parameters

    El-Sayed M. El-kenawy1,2, Abdelhameed Ibrahim3,*, Seyedali Mirjalili4,5, Yu-Dong Zhang6, Shaima Elnazer7,8, Rokaia M. Zaki9,10

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4989-5003, 2022, DOI:10.32604/cmc.2022.023884

    Abstract Metamaterial Antenna is a subclass of antennas that makes use of metamaterial to improve performance. Metamaterial antennas can overcome the bandwidth constraint associated with tiny antennas. Machine learning is receiving a lot of interest in optimizing solutions in a variety of areas. Machine learning methods are already a significant component of ongoing research and are anticipated to play a critical role in today's technology. The accuracy of the forecast is mostly determined by the model used. The purpose of this article is to provide an optimal ensemble model for predicting the bandwidth and gain of the Metamaterial Antenna. Support Vector… More >

  • Open Access

    ARTICLE

    Optimization Model in Manufacturing Scheduling for the Garment Industry

    Chia-Nan Wang1, Yu-Chen Wei2, Po-Yuk So3,*, Viet Tinh Nguyen4, Phan Nguyen Ky Phuc5

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5875-5889, 2022, DOI:10.32604/cmc.2022.023880

    Abstract The garment industry in Vietnam is one of the country's strongest industries in the world. However, the production process still encounters problems regarding scheduling that does not equate to an optimal process. The paper introduces a production scheduling solution that resolves the potential delays and lateness that hinders the production process using integer programming and order allocation with a make-to-order manufacturing viewpoint. A number of constraints were considered in the model and is applied to a real case study of a factory in order to view how the tardiness and lateness would be affected which resulted in optimizing the scheduling… More >

  • Open Access

    ARTICLE

    A Hybrid Meta-Classifier of Fuzzy Clustering and Logistic Regression for Diabetes Prediction

    Altyeb Altaher Taha*, Sharaf Jameel Malebary

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6089-6105, 2022, DOI:10.32604/cmc.2022.023848

    Abstract Diabetes is a chronic health condition that impairs the body's ability to convert food to energy, recognized by persistently high levels of blood glucose. Undiagnosed diabetes can cause many complications, including retinopathy, nephropathy, neuropathy, and other vascular disorders. Machine learning methods can be very useful for disease identification, prediction, and treatment. This paper proposes a new ensemble learning approach for type 2 diabetes prediction based on a hybrid meta-classifier of fuzzy clustering and logistic regression. The proposed approach consists of two levels. First, a base-learner comprising six machine learning algorithms is utilized for predicting diabetes. Second, a hybrid meta-learner that… More >

  • Open Access

    ARTICLE

    Smart Bubble Sort: A Novel and Dynamic Variant of Bubble Sort Algorithm

    Mohammad Khalid Imam Rahmani*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4895-4913, 2022, DOI:10.32604/cmc.2022.023837

    Abstract In the present era, a very huge volume of data is being stored in online and offline databases. Enterprise houses, research, medical as well as healthcare organizations, and academic institutions store data in databases and their subsequent retrievals are performed for further processing. Finding the required data from a given database within the minimum possible time is one of the key factors in achieving the best possible performance of any computer-based application. If the data is already sorted, finding or searching is comparatively faster. In real-life scenarios, the data collected from different sources may not be in sorted order. Sorting… More >

  • Open Access

    ARTICLE

    An EFSM-Based Test Data Generation Approach in Model-Based Testing

    Muhammad Luqman Mohd-Shafie1,*, Wan Mohd Nasir Wan Kadir1, Muhammad Khatibsyarbini1, Mohd Adham Isa1, Israr Ghani1, Husni Ruslai2

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4337-4354, 2022, DOI:10.32604/cmc.2022.023803

    Abstract Testing is an integral part of software development. Current fast-paced system developments have rendered traditional testing techniques obsolete. Therefore, automated testing techniques are needed to adapt to such system developments speed. Model-based testing (MBT) is a technique that uses system models to generate and execute test cases automatically. It was identified that the test data generation (TDG) in many existing model-based test case generation (MB-TCG) approaches were still manual. An automatic and effective TDG can further reduce testing cost while detecting more faults. This study proposes an automated TDG approach in MB-TCG using the extended finite state machine model (EFSM).… More >

  • Open Access

    ARTICLE

    Sentiment Analysis in Social Media for Competitive Environment Using Content Analysis

    Shahid Mehmood1, Imran Ahmad1, Muhammad Adnan Khan1,2, Faheem Khan3, T. Whangbo3,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5603-5618, 2022, DOI:10.32604/cmc.2022.023785

    Abstract Education sector has witnessed several changes in the recent past. These changes have forced private universities into fierce competition with each other to get more students enrolled. This competition has resulted in the adoption of marketing practices by private universities similar to commercial brands. To get competitive gain, universities must observe and examine the students’ feedback on their own social media sites along with the social media sites of their competitors. This study presents a novel framework which integrates numerous analytical approaches including statistical analysis, sentiment analysis, and text mining to accomplish a competitive analysis of social media sites of… More >

Displaying 9181-9190 on page 919 of 22095. Per Page