Muhammad Javid Iqbal^1,2, Ihsan Ullah^2,*, Muhammad Ali², Atiq Ahmed², Waheed Noor², Abdul Basit²

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5381-5397, 2022, DOI:10.32604/cmc.2022.024116 - 14 January 2022

Abstract Live video streaming is one of the newly emerged services over the Internet that has attracted immense interest of the service providers. Since Internet was not designed for such services during its inception, such a service poses some serious challenges including cost and scalability. Peer-to-Peer (P2P) Internet Protocol Television (IPTV) is an application-level distributed paradigm to offer live video contents. In terms of ease of deployment, it has emerged as a serious alternative to client server, Content Delivery Network (CDN) and IP multicast solutions. Nevertheless, P2P approach has struggled to provide the desired streaming quality… More >

Moath Alsafasfeh^1,*, Zaid A. Arida², Omar A. Saraereh³

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5355-5380, 2022, DOI:10.32604/cmc.2022.024093 - 14 January 2022

Abstract Deep neural networks (DNN) are widely employed in a wide range of intelligent applications, including image and video recognition. However, due to the enormous amount of computations required by DNN. Therefore, performing DNN inference tasks locally is problematic for resource-constrained Internet of Things (IoT) devices. Existing cloud approaches are sensitive to problems like erratic communication delays and unreliable remote server performance. The utilization of IoT device collaboration to create distributed and scalable DNN task inference is a very promising strategy. The existing research, on the other hand, exclusively looks at the static split method in… More >

El-Sayed M. El-kenawy^1,2, Abdelhameed Ibrahim^3,*, Seyedali Mirjalili^4,5, Yu-Dong Zhang⁶, Shaima Elnazer^7,8, Rokaia M. Zaki^9,10

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4989-5003, 2022, DOI:10.32604/cmc.2022.023884 - 14 January 2022

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… More >

Altyeb Altaher Taha^*, Sharaf Jameel Malebary

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6089-6105, 2022, DOI:10.32604/cmc.2022.023848 - 14 January 2022

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.… More >

Ghulam Ali Mallah¹, Jamil Ahmed¹, Muhammad Irshad Nazeer^2,*, Mazhar Ali Dootio³, Hidayatullah Shaikh¹, Aadil Jameel¹

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5343-5353, 2022, DOI:10.32604/cmc.2022.023581 - 14 January 2022

Abstract Detection of abnormalities in human eye is one of the well-established research areas of Machine Learning. Deep Learning techniques are widely used for the diagnosis of Retinal Diseases (RD). Fovea is one of the significant parts of retina which would be prevented before the involvement of Perforated Blood Vessels (PBV). Retinopathy Images (RI) contains sufficient information to classify structural changes incurred upon PBV but Macular Features (MF) and Fovea Features (FF) are very difficult to detect because features of MF and FF could be found with Similar Color Movements (SCM) with minor variations. This paper… More >

Muhammad Adnan Khan^1,2, Sagheer Abbas³, Ali Raza³, Faheem Khan⁴, T. Whangbo^4,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5911-5931, 2022, DOI:10.32604/cmc.2022.023557 - 14 January 2022

Abstract Progress in understanding multisensory integration in human have suggested researchers that the integration may result into the enhancement or depression of incoming signals. It is evident based on different psychological and behavioral experiments that stimuli coming from different perceptual modalities at the same time or from the same place, the signal having more strength under the influence of emotions effects the response accordingly. Current research in multisensory integration has not studied the effect of emotions despite its significance and natural influence in multisensory enhancement or depression. Therefore, there is a need to integrate the emotional 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 - 14 January 2022

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 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 - 14 January 2022

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… More >

N. B. Ghazali¹, F. C. Seman^1,*, K. Isa¹, K. N. Ramli¹, Z. Z. Abidin¹, S. M. Mustam¹, M. A. Haek², A. N. Z. Abidin², A. Asrokin²

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5427-5440, 2022, DOI:10.32604/cmc.2022.023211 - 14 January 2022

Abstract Applying the fault diagnosis techniques to twisted pair copper cable is beneficial to improve the stability and reliability of internet access in Digital Subscriber Line (DSL) Access Network System. The network performance depends on the occurrence of cable fault along the copper cable. Currently, most of the telecommunication providers monitor the network performance degradation hence troubleshoot the present of the fault by using commercial test gear on-site, which may be resolved using data analytics and machine learning algorithm. This paper presents a fault diagnosis method for twisted pair cable fault detection based on knowledge-based and… More >

Faisal Saeed^1,2,*, Mohammad Al-Sarem^1,3, Muhannad Al-Mohaimeed¹, Abdelhamid Emara^1,4, Wadii Boulila^1,5, Mohammed Alasli¹, Fahad Ghabban¹

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5639-5658, 2022, DOI:10.32604/cmc.2022.023124 - 14 January 2022

Abstract Several millions of people suffer from Parkinson's disease globally. Parkinson's affects about 1% of people over 60 and its symptoms increase with age. The voice may be affected and patients experience abnormalities in speech that might not be noticed by listeners, but which could be analyzed using recorded speech signals. With the huge advancements of technology, the medical data has increased dramatically, and therefore, there is a need to apply data mining and machine learning methods to extract new knowledge from this data. Several classification methods were used to analyze medical data sets and diagnostic… More >