Reem Almutiri^*, Sarah Alhabeeb, Sarah Alhumud, Rehan Ullah Khan

Journal on Big Data, Vol.4, No.2, pp. 97-111, 2022, DOI:10.32604/jbd.2022.028363 - 31 October 2022

Abstract Today’s world is a data-driven one, with data being produced in vast amounts as a result of the rapid growth of technology that permeates every aspect of our lives. New data processing techniques must be developed and refined over time to gain meaningful insights from this vast continuous volume of produced data in various forms. Machine learning technologies provide promising solutions and potential methods for processing large quantities of data and gaining value from it. This study conducts a literature review on the application of machine learning techniques in big data processing. It provides a More >

Belayneh Yitayew^1,*, Wondwossen Bogale²

Energy Engineering, Vol.119, No.6, pp. 2513-2532, 2022, DOI:10.32604/ee.2022.018961 - 14 September 2022

Abstract Energy is one of the most important factors in socio-economic development. The rapid increase in energy demand and air pollution has increased the number of ways to generate energy in the power sector. Currently, wind energy capacity in Ethiopia is estimated at 10,000 MW. Of these, however, only eight percent of its capacity has been used in recent years. One of the reasons for the low use of wind energy is the lack of accurate wind atlases in the country. Therefore, the purpose of this study is to develop an accurate wind atlas and review… More >

Shuna Peng¹, Xiaohong Luo¹, Shiyu Liang¹, Fengning Deng¹, Yuning Liu², Hong Zeng^1,*, Xuesong Yang^3,*

International Journal of Mental Health Promotion, Vol.24, No.5, pp. 711-724, 2022, DOI:10.32604/ijmhp.2022.020556 - 27 July 2022

Abstract Background: The coronavirus (COVID-19) outbreak in 2019 triggered psychological and emotional responses. This research investigates the psychological status and emotional problems of those who sought psychological assistance during the epidemic period by calling a mental health hotline. Methods: This study aims to combine qualitative and quantitative research. Descriptive analysis was used for undertaking qualitative research. We analyzed the data from group 1 (n = 706), in which the people used the mental health hotline from 25 January 2020 to 23 June 2020. A self-designed questionnaire was developed in accordance with the classification and summarized items… More >

Gabriela Nazar^1,2,*, Carlos-María Alcover³, Yeny Concha-Cisternas^4,5, Igor Cigarroa⁵, Ximena Díaz-Martínez⁶, Mariela Gatica-Saavedra⁷, Fabián Lanuza^8,9, Ana María Leiva-Ordónez¹⁰, María Adela Martínez-Sanguinetti¹¹, Miquel Martorell^2,12, Fanny Petermann-Rocha^13,14, Claudia Troncoso-Pantoja¹⁵, Carlos Celis-Morales¹⁶

International Journal of Mental Health Promotion, Vol.24, No.5, pp. 679-697, 2022, DOI:10.32604/ijmhp.2022.020105 - 27 July 2022

Abstract Depressive disorders are recognized as one of the most common mental health conditions across different age groups. However, the risk factors associated with depression among older people from low-and middle-income countries remains unclear. This study aims to identify socio-demographic, health and psychosocial-related factors associated with depression in Chilean older adults. A cross-sectional study was carried out in a representative sample of 1,765 adults aged ≥60 years participants from the Chilean National Health Survey 2016–2017. Depression was assessed with the Composite International Diagnostic Interview (CIDI-SF). Associations between the exposure variables and depression were investigated using Poisson… More >

Haitao Zhang^*

Journal of Information Hiding and Privacy Protection, Vol.4, No.1, pp. 41-51, 2022, DOI:10.32604/jihpp.2022.031707 - 17 June 2022

Abstract Deep learning related technologies, especially generative adversarial network, are widely used in the fields of face image tampering and forgery. Forensics researchers have proposed a variety of passive forensic and related anti-forensic methods for image tampering and forgery, especially face images, but there is still a lack of overview of anti-forensic methods at this stage. Therefore, this paper will systematically discuss the anti-forensic methods for face image tampering and forgery. Firstly, this paper expounds the relevant background, including the relevant tampering and forgery methods and forensic schemes of face images. The former mainly includes four More >

Monerah M. Alawadh^*, Ahmed M. Barnawi

Journal on Big Data, Vol.4, No.1, pp. 1-25, 2022, DOI:10.32604/jbd.2022.021744 - 04 May 2022

Abstract The market trends rapidly changed over the last two decades. The primary reason is the newly created opportunities and the increased number of competitors competing to grasp market share using business analysis techniques. Market Basket Analysis has a tangible effect in facilitating current change in the market. Market Basket Analysis is one of the famous fields that deal with Big Data and Data Mining applications. MBA initially uses Association Rule Learning (ARL) as a mean for realization. ARL has a beneficial effect in providing a plenty benefit in analyzing the market data and understanding customers’ More >

Dandan Xu¹, Haijian Shao^1,*, Xing Deng^1,2, Xia Wang³

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 567-597, 2022, DOI:10.32604/cmes.2022.019245 - 14 March 2022

Abstract As wind and photovoltaic energy become more prevalent, the optimization of power systems is becoming increasingly crucial. The current state of research in renewable generation and power forecasting technology, such as wind and photovoltaic power (PV), is described in this paper, with a focus on the ensemble sequential LSTMs approach with optimized hidden-layers topology for short-term multivariable wind power forecasting. The methods for forecasting wind power and PV production. The physical model, statistical learning method, and machine learning approaches based on historical data are all evaluated for the forecasting of wind power and PV production. More >

Darshan Babu L. Arasu¹, Ahmad Sufril Azlan Mohamed^1,*, Nur Intan Raihana Ruhaiyem¹, Nagaletchimee Annamalai², Syaheerah Lebai Lutfi¹, Mustafa M. Al Qudah¹

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 633-652, 2022, DOI:10.32604/cmes.2021.016985 - 13 December 2021

Abstract Stress is a normal reaction of the human organism which triggered in situations that require a certain level of activation. This reaction has both positive and negative effects on everyone’s life. Therefore, stress management is of vital importance in maintaining the psychological balance of a person. Thermal-based imaging technique is becoming popular among researchers due to its non-contact conductive nature. Moreover, thermal-based imaging has shown promising results in detecting stress in a non-contact and non-invasive manner. Compared to other non-contact stress detection methods such as pupil dilation, keystroke behavior, social media interaction and voice modulation, More >

Xing Guo^1,#, Yu-Dong Zhang^2,#, Siyuan Lu², Zhihai Lu^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 23-71, 2022, DOI:10.32604/cmes.2021.017679 - 29 November 2021

Abstract Since Corona Virus Disease 2019 outbreak, many expert groups worldwide have studied the problem and proposed many diagnostic methods. This paper focuses on the research of Corona Virus Disease 2019 diagnosis. First, the procedure of the diagnosis based on machine learning is introduced in detail, which includes medical data collection, image preprocessing, feature extraction, and image classification. Then, we review seven methods in detail: transfer learning, ensemble learning, unsupervised learning and semi-supervised learning, convolutional neural networks, graph neural networks, explainable deep neural networks, and so on. What’s more, the advantages and limitations of different diagnosis More >

Tong Gan¹, Shi-You Wang¹, Qiang Ma¹, Yi-Dong Jia^2,*, Yun-Yun Ma³

Computer Systems Science and Engineering, Vol.41, No.1, pp. 321-337, 2022, DOI:10.32604/csse.2022.019244 - 08 October 2021

Abstract The rapid growth of mobile data traffic has caused great pressure on the limited spectrum resources, and there must be some better methods to deal with this problem. The innovative technology of Long-Term Evolution (LTE) using the unlicensed spectrum, known as LTE-Unlicensed (LTE-U), has been proposed to effectively alleviate the shortage of authorized band resources. LTE-U has explored a lot of potential capacity in mobile communication systems with limited authorized spectrum resources, and improved the spectrum utilization of unauthorized frequency bands. However, LTE-U is still facing challenges in its application. In this paper, we summarize… More >