Iram Arshad^1,*, Saeed Hamood Alsamhi¹, Wasif Afzal²

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2739-2770, 2023, DOI:10.32604/cmc.2023.030266

Abstract Big Data is reforming many industrial domains by providing decision support through analyzing large data volumes. Big Data testing aims to ensure that Big Data systems run smoothly and error-free while maintaining the performance and quality of data. However, because of the diversity and complexity of data, testing Big Data is challenging. Though numerous research efforts deal with Big Data testing, a comprehensive review to address testing techniques and challenges of Big Data is not available as yet. Therefore, we have systematically reviewed the Big Data testing techniques’ evidence occurring in the period 2010–2021. This paper discusses testing data processing… More >

Sneha Basak¹, Himanshi Agrawal¹, Shreya Jena¹, Shilpa Gite^2,*, Mrinal Bachute², Biswajeet Pradhan^3,4,5,*, Mazen Assiri⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1053-1089, 2023, DOI:10.32604/cmes.2022.021755

Abstract Speech recognition systems have become a unique human-computer interaction (HCI) family. Speech is one of the most naturally developed human abilities; speech signal processing opens up a transparent and hand-free computation experience. This paper aims to present a retrospective yet modern approach to the world of speech recognition systems. The development journey of ASR (Automatic Speech Recognition) has seen quite a few milestones and breakthrough technologies that have been highlighted in this paper. A step-by-step rundown of the fundamental stages in developing speech recognition systems has been presented, along with a brief discussion of various modern-day developments and applications in… More >

Kamal A. ElDahshan, AbdAllah A. AlHabshy, Luay Thamer Mohammed^*

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 817-839, 2023, DOI:10.32604/cmc.2023.032287

Abstract This study focuses on meeting the challenges of big data visualization by using of data reduction methods based the feature selection methods. To reduce the volume of big data and minimize model training time (Tt) while maintaining data quality. We contributed to meeting the challenges of big data visualization using the embedded method based “Select from model (SFM)” method by using “Random forest Importance algorithm (RFI)” and comparing it with the filter method by using “Select percentile (SP)” method based chi square “Chi2” tool for selecting the most important features, which are then fed into a classification process using the… More >

Xiaoting Liang¹, Fang Liu^1,*, Linqi Wang¹, Baoying Zheng¹, Yiyuan Sun²

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 469-488, 2023, DOI:10.32604/cmc.2023.029641

Abstract Driven by the visions of the Internet of Things (IoT), Artificial Intelligence (AI), and 5G communications, the Internet of Cultural Things (IoCT) realize the comprehensive interconnection among cultural products, cultural services, cultural resources, and cultural platforms, bringing individuals with richer humanistic experience, increasing economic benefits for the cultural sector, and promoting the development of cultural heritage protection and education. At present, IoCT has received widespread attention in both industry and academia. To explore new research opportunities and assist users in constructing suitable IoCT systems for specific applications, this survey provides a comprehensive overview of the IoCT components and key technologies.… More >

Wenjun Zhang¹, Wenfeng Wang^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1597-1619, 2023, DOI:10.32604/cmes.2022.020517

Abstract Face recognition has been rapidly developed and widely used. However, there is still considerable uncertainty in the computational intelligence based on human-centric visual understanding. Emerging challenges for face recognition are resulted from information loss. This study aims to tackle these challenges with a broad learning system (BLS). We integrated two models, IR³C with BLS and IR³C with a triplet loss, to control the learning process. In our experiments, we used different strategies to generate more challenging datasets and analyzed the competitiveness, sensitivity, and practicability of the proposed two models. In the model of IR3C with BLS, the recognition rates for… More >

Liang Luo¹, Xingmei Li¹, Kaijiang Yang¹, Mengyang Wei¹, Jiong Chen¹, Junqian Yang¹, Liang Yao^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1565-1595, 2023, DOI:10.32604/cmes.2022.021198

Abstract The emergence of power dispatching automation systems has greatly improved the efficiency of power industry operations and promoted the rapid development of the power industry. However, with the convergence and increase in power data flow, the data dispatching network and the main station dispatching automation system have encountered substantial pressure. Therefore, the method of online data resolution and rapid problem identification of dispatching automation systems has been widely investigated. In this paper, we perform a comprehensive review of automated dispatching of massive dispatching data from the perspective of intelligent identification, discuss unresolved research issues and outline future directions in this… More >

Gulshan Kumar^1,*, Hamed Alqahtani²

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 89-119, 2023, DOI:10.32604/cmes.2022.020724

Abstract Software-Defined Networking (SDN) enables flexibility in developing security tools that can effectively and efficiently analyze and detect malicious network traffic for detecting intrusions. Recently Machine Learning (ML) techniques have attracted lots of attention from researchers and industry for developing intrusion detection systems (IDSs) considering logically centralized control and global view of the network provided by SDN. Many IDSs have developed using advances in machine learning and deep learning. This study presents a comprehensive review of recent work of ML-based IDS in context to SDN. It presents a comprehensive study of the existing review papers in the field. It is followed… More >

Jamie Penno^*, Sarah Hetrick, Grant Christie

International Journal of Mental Health Promotion, Vol.24, No.5, pp. 771-781, 2022, DOI:10.32604/ijmhp.2022.020090

Abstract The mental health of New Zealand’s adolescents is, by global standards, remarkably poor. Addressing such mental health needs is not only pertinent with regards to the quality of life of our young people, but also the health of our society as a whole, with current unmet youth mental health needs becoming future adult population health deficits. While an array of evidence-based psychotherapies are available as treatment, our knowledge of the mechanism of actions underlying each of these is lacking. We propose that the practice of goal setting as a therapeutic technique may represent not only a common element across these… More >

Basit Shahzad¹, Wardah Naeem Awan^1,*, Fazal-e-Amin², Ahsanullah Abro³, Muhammad Shoaib⁴, Sultan Alyahya⁴

Computer Systems Science and Engineering, Vol.44, No.1, pp. 407-422, 2023, DOI:10.32604/csse.2023.022601

Abstract There is an emerging interest in using agile methodologies in Global Software Development (GSD) to get the mutual benefits of both methods. Scrum is currently admired by many development teams as an agile most known methodology and considered adequate for collocated teams. At the same time, stakeholders in GSD are dispersed by geographical, temporal, and socio-cultural distances. Due to the controversial nature of Scrum and GSD, many significant challenges arise that might restrict the use of Scrum in GSD. We conducted a Systematic Literature Review (SLR) by following Kitchenham guidelines to identify the challenges that limit the use of Scrum… More >

Indra Mamad Gandidi^1,*, Apri Wiyono¹, Nugroho Agung Pambudi^2,*, Rahmat Romadhon³, Alfan Sarifudin²

Energy Engineering, Vol.119, No.4, pp. 1403-1418, 2022, DOI:10.32604/ee.2022.019200

Abstract The rapid spread of COVID-19 pandemic has forced several countries in the world to store vaccines in cold storage towards ensuring their protection from being damaged and to maintain their stability. However, most remote clinics, especially those in the equator and islands, are faced with the challenges of hot climates and the inability to afford electricity resources needed to power the cold storage facility. Meanwhile, the hot equatorial region has abundant solar energy to power the vaccine cold storage but previous studies showed that several field workers do not have the ability to maintain the vaccine storage temperature as indicated… More >