Amnart Boonloi^a, Withada Jedsadaratanachai^b,*

Frontiers in Heat and Mass Transfer, Vol.18, pp. 1-15, 2022, DOI:10.5098/hmt.18.20

Abstract Numerical analysis of fluid flow mechanism and heat transfer in a heat exchanger duct (HXD) with dual-inclined baffles (DIB) are reported. Three DIB types are examined: 1. “Type A” is located at the center of the HXD, 2. “Type B” is located on the upper-lower duct walls (as an orifice) and 3. “Type C” is a combination of the type A and B (as double orifices). The impacts of the ratio of DIB heights (b) to the square duct height (H; b/H) on increased heat transfer and friction loss are analyzed. Laminar flow (Re = 100 – 2000 based on… More >

A.C. Budiman^a,*, S. M. Hasheminejad^b, Sudirja^a, A. Mitayani^c, S. H. Winoto^d

Frontiers in Heat and Mass Transfer, Vol.19, pp. 1-6, 2022, DOI:10.5098/hmt.19.9

Abstract Streamwise development of counter-rotating vortices induced by three different types of chevron Vortex Generators (VGs) placed upstream an Electric Vehicles (EV) dummy battery module is experimentally visualized using a smoke-wire method. From the single chevron reference case, the mushroom-like vortices do not collapse until passing the module. When more chevrons are used in line, the vortices become more prominent. It can also be observed that the vortex sizes and shapes are significantly influenced by the spanwise base length of the chevron. The induced vortices from all three VGs suggest a potential heat transfer augmentation for the EV battery module application. More >

Zhiguo Chen^1,2,*, Jiabing Cao^1,2

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4445-4465, 2023, DOI:10.32604/cmc.2023.038639

Abstract The Corona Virus Disease 2019 (COVID-19) effect has made telecommuting and remote learning the norm. The growing number of Internet-connected devices provides cyber attackers with more attack vectors. The development of malware by criminals also incorporates a number of sophisticated obfuscation techniques, making it difficult to classify and detect malware using conventional approaches. Therefore, this paper proposes a novel visualization-based malware classification system using transfer and ensemble learning (VMCTE). VMCTE has a strong anti-interference ability. Even if malware uses obfuscation, fuzzing, encryption, and other techniques to evade detection, it can be accurately classified into its corresponding malware family. Unlike traditional… More >

Ahmad Moawad^*, Ahmed Ismail Ebada, Aya M. Al-Zoghby

Journal of Cyber Security, Vol.4, No.3, pp. 169-184, 2022, DOI:10.32604/jcs.2022.033537

Abstract In computer security, the number of malware threats is increasing and causing damage to systems for individuals or organizations, necessitating a new detection technique capable of detecting a new variant of malware more efficiently than traditional anti-malware methods. Traditional anti-malware software cannot detect new malware variants, and conventional techniques such as static analysis, dynamic analysis, and hybrid analysis are time-consuming and rely on domain experts. Visualization-based malware detection has recently gained popularity due to its accuracy, independence from domain experts, and faster detection time. Visualization-based malware detection uses the image representation of the malware binary and applies image processing techniques… More >

Ming Li¹, Kuntharrgyal Khysru², Haiqiang Shi^2,*, Qiang Fang^3,*, Jinrong Hu⁴, Yun Chen⁵

Computer Systems Science and Engineering, Vol.46, No.1, pp. 783-798, 2023, DOI:10.32604/csse.2023.034687

Abstract The Internet of Things (IoT) plays an essential role in the current and future generations of information, network, and communication development and applications. This research focuses on vocal tract visualization and modeling, which are critical issues in realizing inner vocal tract animation. That is applied in many fields, such as speech training, speech therapy, speech analysis and other speech production-related applications. This work constructed a geometric model by observation of Magnetic Resonance Imaging data, providing a new method to annotate and construct 3D vocal tract organs. The proposed method has two advantages compared with previous methods. Firstly it has a… More >

Yu Su^1,2,3, Lingjuan Hou^2,3,*, Sinan Li¹, Zhaochang Jiang¹, Haoran Peng⁴

Computer Systems Science and Engineering, Vol.46, No.1, pp. 521-536, 2023, DOI:10.32604/csse.2022.028606

Abstract Mobile location-based services (MLBS) refer to services around geographic location data. Mobile terminals use wireless communication networks (or satellite positioning systems) to obtain users’ geographic location coordinate information based on spatial databases and integrate with other information to provide users with required location-related services. The development of systems based on MLBS has significance and practical value. In this paper a visualization management information system for personnel in major events based on microservices, namely MEPMIS, is designed and implemented by using MLBS. The system consists of a server and a client app, and it has some functions including map search and… More >

Jingwei Hao^*, Senlin Luo, Limin Pan

Computer Systems Science and Engineering, Vol.46, No.1, pp. 719-734, 2023, DOI:10.32604/csse.2023.033923

Abstract The byte stream is widely used in malware detection due to its independence of reverse engineering. However, existing methods based on the byte stream implement an indiscriminate feature extraction strategy, which ignores the byte function difference in different segments and fails to achieve targeted feature extraction for various byte semantic representation modes, resulting in byte semantic confusion. To address this issue, an enhanced adversarial byte function associated method for malware backdoor attack is proposed in this paper by categorizing various function bytes into three functions involving structure, code, and data. The Minhash algorithm, grayscale mapping, and state transition probability statistics… More >

Ziwen Yu¹, Jianjun Zhang^1,*, Wenwu Tan¹, Ziyi Xiong¹, Peilun Li¹, Liangqing Meng², Haijun Lin¹, Guang Sun³, Peng Guo⁴

Journal on Big Data, Vol.4, No.2, pp. 135-143, 2022, DOI:10.32604/jbd.2022.031024

Abstract Many countries are paying more and more attention to the protection of water resources at present, and how to protect water resources has received extensive attention from society. Water quality monitoring is the key work to water resources protection. How to efficiently collect and analyze water quality monitoring data is an important aspect of water resources protection. In this paper, python programming tools and regular expressions were used to design a web crawler for the acquisition of water quality monitoring data from Global Freshwater Quality Database (GEMStat) sites, and the multi-thread parallelism was added to improve the efficiency in the… More >

Umair Yousaf¹, Muhammad Asif¹, Shahbaz Ahmed¹, Noman Tahir¹, Azeem Irshad², Akber Abid Gardezi³, Muhammad Shafiq^4,*, Jin-Ghoo Choi⁴, Habib Hamam^5,6,7,8

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4165-4181, 2023, DOI:10.32604/cmc.2023.026607

Abstract The research volume increases at the study rate, causing massive text corpora. Due to these enormous text corpora, we are drowning in data and starving for information. Therefore, recent research employed different text mining approaches to extract information from this text corpus. These proposed approaches extract meaningful and precise phrases that effectively describe the text's information. These extracted phrases are commonly termed keyphrases. Further, these key phrases are employed to determine the different fields of study trends. Moreover, these key phrases can also be used to determine the spatiotemporal trends in the various research fields. In this research, the progress… More >

Jun Liu¹, Geng Yuan², Changdi Yang², Houbing Song³, Liang Luo^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1571-1587, 2023, DOI:10.32604/cmes.2022.023195

Abstract The interpretability of deep learning models has emerged as a compelling area in artificial intelligence research. The safety criteria for medical imaging are highly stringent, and models are required for an explanation. However, existing convolutional neural network solutions for left ventricular segmentation are viewed in terms of inputs and outputs. Thus, the interpretability of CNNs has come into the spotlight. Since medical imaging data are limited, many methods to fine-tune medical imaging models that are popular in transfer models have been built using massive public ImageNet datasets by the transfer learning method. Unfortunately, this generates many unreliable parameters and makes… More >