Mohammed H. Alsharif¹, Md. Sanwar Hossain², Abu Jahid³, Muhammad Asghar Khan⁴, Bong Jun Choi^5,*, Samih M. Mostafa^6,7

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4803-4818, 2022, DOI:10.32604/cmc.2022.023500

Abstract Since around 1980, a new generation of wireless technology has arisen approximately every 10 years. First-generation (1G) and second-generation (2G) began with voice and eventually introduced more and more data in third-generation (3G) and became highly popular in the fourth-generation (4G). To increase the data rate along with low latency and mass connectivity the fifth-generation (5G) networks are being installed from 2020. However, the 5G technology will not be able to fulfill the data demand at the end of this decade. Therefore, it is expected that 6G communication networks will rise, providing better services through the implementation of new enabling… More >

Wan Azani Mustafa^1,2,*, Haniza Yazid³, Ahmed Alkhayyat⁴, Mohd Aminudin Jamlos³, Hasliza A. Rahim³, Midhat Nabil Salimi⁵

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5327-5342, 2022, DOI:10.32604/cmc.2022.023492

Abstract Luminosity and contrast variation problems are among the most challenging tasks in the image processing field, significantly improving image quality. Enhancement is implemented by adjusting the dark or bright intensity to improve the quality of the images and increase the segmentation performance. Recently, numerous methods had been proposed to normalise the luminosity and contrast variation. A new approach based on a direct technique using statistical data known as Hybrid Statistical Enhancement (HSE) is presented in this study. The HSE method uses the mean and standard deviation of a local and global neighbourhood and classified the pixel into three groups; the… More >

Sukanta Ghosh¹, Amar Singh¹, Kavita^2,*, N. Z. Jhanjhi³, Mehedi Masud⁴, Sultan Aljahdali⁴

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4257-4274, 2022, DOI:10.32604/cmc.2022.023414

Abstract Automatic plant classification through plant leaf is a classical problem in Computer Vision. Plants classification is challenging due to the introduction of new species with a similar pattern and look-a-like. Many efforts are made to automate plant classification using plant leaf, plant flower, bark, or stem. After much effort, it has been proven that leaf is the most reliable source for plant classification. But it is challenging to identify a plant with the help of leaf structure because plant leaf shows similarity in morphological variations, like sizes, textures, shapes, and venation. Therefore, it is required to normalize all plant leaves… More >

Labiba Gillani Fahad¹, Syed Fahad Tahir^2,*, Usama Rasheed¹, Hafsa Saqib¹, Mehdi Hassan², Hani Alquhayz³

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5083-5098, 2022, DOI:10.32604/cmc.2022.023357

Abstract The nutritional value of perishable food items, such as fruits and vegetables, depends on their freshness levels. The existing approaches solve a binary class problem by classifying a known fruit\vegetable class into fresh or rotten only. We propose an automated fruits and vegetables categorization approach that first recognizes the class of object in an image and then categorizes that fruit or vegetable into one of the three categories: pure-fresh, medium-fresh, and rotten. We gathered a dataset comprising of 60K images of 11 fruits and vegetables, each is further divided into three categories of freshness, using hand-held cameras. The recognition and… More >

Syeda Amna Rizwan¹, Yazeed Yasin Ghadi², Ahmad Jalal¹, Kibum Kim^3,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5235-5252, 2022, DOI:10.32604/cmc.2022.023328

Abstract With the advancement of computer vision techniques in surveillance systems, the need for more proficient, intelligent, and sustainable facial expressions and age recognition is necessary. The main purpose of this study is to develop accurate facial expressions and an age recognition system that is capable of error-free recognition of human expression and age in both indoor and outdoor environments. The proposed system first takes an input image pre-process it and then detects faces in the entire image. After that landmarks localization helps in the formation of synthetic face mask prediction. A novel set of features are extracted and passed to… More >

Shihao Zhou¹, Ziyuan Xu^3,4, Jin Han^1,*, Xingming Sun^1,2, Yi Cao⁵

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5995-6009, 2022, DOI:10.32604/cmc.2022.023316

Abstract In recent years, academic misconduct has been frequently exposed by the media, with serious impacts on the academic community. Current research on academic misconduct focuses mainly on detecting plagiarism in article content through the application of character-based and non-text element detection techniques over the entirety of a manuscript. For the most part, these techniques can only detect cases of textual plagiarism, which means that potential culprits can easily avoid discovery through clever editing and alterations of text content. In this paper, we propose an academic misconduct detection method based on scholars’ submission behaviors. The model can effectively capture the atypical… More >

Uğur Ayvaz¹, Hüseyin Gürüler², Faheem Khan³, Naveed Ahmed⁴, Taegkeun Whangbo^3,*, Abdusalomov Akmalbek Bobomirzaevich³

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5511-5521, 2022, DOI:10.32604/cmc.2022.023278

Abstract Automatic speaker recognition (ASR) systems are the field of Human-machine interaction and scientists have been using feature extraction and feature matching methods to analyze and synthesize these signals. One of the most commonly used methods for feature extraction is Mel Frequency Cepstral Coefficients (MFCCs). Recent researches show that MFCCs are successful in processing the voice signal with high accuracies. MFCCs represents a sequence of voice signal-specific features. This experimental analysis is proposed to distinguish Turkish speakers by extracting the MFCCs from the speech recordings. Since the human perception of sound is not linear, after the filterbank step in the MFCC… More >

El-Sayed M. El-Kenawy^1,2, Abdelhameed Ibrahim³, Nadjem Bailek^4,*, Kada Bouchouicha⁵, Muhammed A. Hassan⁶, Basharat Jamil⁷, Nadhir Al-Ansari⁸

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5837-5854, 2022, DOI:10.32604/cmc.2022.023257

Abstract In order to achieve a highly accurate estimation of solar energy resource potential, a novel hybrid ensemble-learning approach, hybridizing Advanced Squirrel-Search Optimization Algorithm (ASSOA) and support vector regression, is utilized to estimate the hourly tilted solar irradiation for selected arid regions in Algeria. Long-term measured meteorological data, including mean-air temperature, relative humidity, wind speed, alongside global horizontal irradiation and extra-terrestrial horizontal irradiance, were obtained for the two cities of Tamanrasset-and-Adrar for two years. Five computational algorithms were considered and analyzed for the suitability of estimation. Further two new algorithms, namely Average Ensemble and Ensemble using support vector regression were developed… More >

Ganapathy Pattukandan Ganapathy¹, Kathiravan Srinivasan², Debajit Datta², Chuan-Yu Chang^3,4,*, Om Purohit⁵, Vladislav Zaalishvili⁶, Olga Burdzieva⁶

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6333-6350, 2022, DOI:10.32604/cmc.2022.023254

Abstract A substantial amount of the Indian economy depends solely on agriculture. Rainfall, on the other hand, plays a significant role in agriculture–while an adequate amount of rainfall can be considered as a blessing, if the amount is inordinate or scant, it can ruin the entire hard work of the farmers. In this work, the rainfall dataset of the Vellore region, of Tamil Nadu, India, in the years 2021 and 2022 is forecasted using several machine learning algorithms. Feature engineering has been performed in this work in order to generate new features that remove all sorts of autocorrelation present in the… More >

Muhammad Waseem Iqbal¹, Muhammad Raza Naqvi², Muhammad Adnan Khan^3,4, Faheem Khan⁵, T. Whangbo^5,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4767-4784, 2022, DOI:10.32604/cmc.2022.023239

Abstract Currently, many mobile devices provide various interaction styles and modes which create complexity in the usage of interfaces. The context offers the information base for the development of Adaptive user interface (AUI) frameworks to overcome the heterogeneity. For this purpose, the ontological modeling has been made for specific context and environment. This type of philosophy states to the relationship among elements (e.g., classes, relations, or capacities etc.) with understandable satisfied representation. The context mechanisms can be examined and understood by any machine or computational framework with these formal definitions expressed in Web ontology language (WOL)/Resource description frame work (RDF). The… More >