Yanmei Shi¹, Wei Yu^2,*, Yanxia Zhao^3,*, Yungang Jia⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 887-906, 2024, DOI:10.32604/cmes.2024.046140

Abstract Web application fingerprint recognition is an effective security technology designed to identify and classify web applications, thereby enhancing the detection of potential threats and attacks. Traditional fingerprint recognition methods, which rely on preannotated feature matching, face inherent limitations due to the ever-evolving nature and diverse landscape of web applications. In response to these challenges, this work proposes an innovative web application fingerprint recognition method founded on clustering techniques. The method involves extensive data collection from the Tranco List, employing adjusted feature selection built upon Wappalyzer and noise reduction through truncated SVD dimensionality reduction. The core of the methodology lies in… More >

JITENDRA. S. TATE^1,2,*, HARISH KALLAGUNTA^1,2, ANDREW ALVAREZ¹

Journal of Polymer Materials, Vol.38, No.1-2, pp. 101-120, 2021, DOI:10.32381/JPM.2021.38.1-2.9

Abstract The exponential growth in composites and their increased use in military, aerospace, energy, and automotive industry is driven by their high performance and light weight. High performance thermosetting polymers such as cyanate ester have received considerable attention due to its ability of volatile-free curing. It also offers advantages such as excellent radiation shielding, high thermal stability, and hydrophobicity with lots of potential for enhanced mechanical strength. This research article discusses the results of effects of multiwalled carbon nanotubes (MWCNT) at predetermined loading levels of 0.5wt%, 1wt% and 1.5wt% on mechanical, thermal and flammability properties of cyanate ester modified carbon fiber… More >

Zhenhua Yu¹, Zhengqi Liu¹, Xuya Cong^1,*, Xiaobo Li², Li Yin³

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1-29, 2024, DOI:10.32604/cmc.2023.042361

Abstract As one of the most effective techniques for finding software vulnerabilities, fuzzing has become a hot topic in software security. It feeds potentially syntactically or semantically malformed test data to a target program to mine vulnerabilities and crash the system. In recent years, considerable efforts have been dedicated by researchers and practitioners towards improving fuzzing, so there are more and more methods and forms, which make it difficult to have a comprehensive understanding of the technique. This paper conducts a thorough survey of fuzzing, focusing on its general process, classification, common application scenarios, and some state-of-the-art techniques that have been… More >

Wei Zhou¹, Xincong Jiang^2,*, Chuan Qin²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 2069-2093, 2024, DOI:10.32604/cmes.2023.043248

Abstract Edge devices, due to their limited computational and storage resources, often require the use of compilers for program optimization. Therefore, ensuring the security and reliability of these compilers is of paramount importance in the emerging field of edge AI. One widely used testing method for this purpose is fuzz testing, which detects bugs by inputting random test cases into the target program. However, this process consumes significant time and resources. To improve the efficiency of compiler fuzz testing, it is common practice to utilize test case prioritization techniques. Some researchers use machine learning to predict the code coverage of test… More >

Casey Jones, Meghana Sudarshan, Vikas Tomar^*

Energy Engineering, Vol.120, No.12, pp. 2721-2740, 2023, DOI:10.32604/ee.2023.043219

Abstract Abuse of Lithium-ion batteries, both physical and electrochemical, can lead to significantly reduced operational capabilities. In some instances, abuse can cause catastrophic failure, including thermal runaway, combustion, and explosion. Many different test standards that include abuse conditions have been developed, but these generally consider only one condition at a time and only provide go/no-go criteria. In this work, different types of cell abuse are implemented concurrently to determine the extent to which simultaneous abuse conditions aggravate cell degradation and failure. Vibrational loading is chosen to be the consistent type of physical abuse, and the first group of cells is cycled… More >

Xiaoyu Gu¹, Linbi Chen², Seithati Mapesela³, Zheng Wang^1,*, Aijin Zhou⁴

Journal of Renewable Materials, Vol.11, No.12, pp. 4197-4210, 2023, DOI:10.32604/jrm.2023.028768

Abstract The bamboo scrimber is an anisotropic material. The elastic constant values of the bamboo scrimber specimens measured by the dynamic and static methods are consistent, and the dynamic test method has the advantages of rapidity, simplicity, good repeatability, and high precision. Bamboo scrimber has strong potential as a building material, and its elastic constant is an important index to measure its mechanical properties. To quickly, simply, non-destructively, and accurately detect the elastic constant of the bamboo scrimber, they were dynamically tested by the free plate transient excitation method and cantilever plate torsional vibration method. The static four-point bending method was… More >

Fulai Cao^1,*, Yanpu Chao^1,*, Hao Yi^2,3, Shuai Lu¹, Chengshui Guo⁴

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.11, pp. 2891-2905, 2023, DOI:10.32604/fdmp.2023.029243

Abstract The properties of droplets produced by existing on-demand injection systems are typically determined by the nozzle diameter, i.e., only droplets with size larger than this diameter can be obtained. To solve this problem, a system for electric field-driven droplet injection and deposition was developed, and the related performances were compared with those of a standard pneumatic system. The results show that the diameter of droplets generated accordingly can be significantly smaller than the nozzle diameter. In particular, the effects of frequency and duty ratio on the number of droplets were studied by assuming microcrystalline wax as work material. A deposition… More > Graphic Abstract

Zhongguo Tang¹, Haijin Zhuo¹, Beian Li¹, Xiaotao Ma², Siyu Zhao², Kai Tong^2,*

Structural Durability & Health Monitoring, Vol.17, No.5, pp. 407-431, 2023, DOI:10.32604/sdhm.2023.026033

Abstract Corrosion can be very harmful to the service life and several properties of reinforced concrete structures. The metal magnetic memory (MMM) method, as a newly developed spontaneous magnetic flux leakage (SMFL) non-destructive testing (NDT) technique, is considered a potentially viable method for detecting corrosion damage in reinforced concrete members. To this end, in this paper, the indoor electrochemical method was employed to accelerate the corrosion of outsourced concrete specimens with different steel bar diameters, and the normal components BB_z and its gradient of the SMFL fields on the specimen surfaces were investigated based on the metal magnetic memory (MMM) method.… More >

Guo Li¹, Shaochen Bao², Shuiting Ding³, Zhenlei Li^2,*, Liangliang Zuo¹, Shuyang Xia¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09927

Abstract Advanced air-cooling turbine blades are capable of operating above the melting temperature of Nickel-based superalloy, which accordingly withstand complex thermomechanical fatigue loads during service life. This paper considers the problem of realizing gas turbine representative thermal gradients in the elevated temperature fatigue test, while ensuring the thermal gradient induced stress inside the specimens. For this purpose, a novel temperature control device utilizing impingement cooling, which supplies cooling air inside the gauge section and releases toward the inner wall, was constructed in tubular fatigue specimens. A single induction coil was arranged outside the gauge section, providing heat sources to establish thermal… More >

Bilal Khan¹, Muhammad Arshad², Sarwar Shah Khan^3,4,*

Journal of Cyber Security, Vol.5, pp. 1-11, 2023, DOI:10.32604/jcs.2023.042501

Abstract The proliferation of maliciously coded documents as file transfers increase has led to a rise in sophisticated attacks. Portable Document Format (PDF) files have emerged as a major attack vector for malware due to their adaptability and wide usage. Detecting malware in PDF files is challenging due to its ability to include various harmful elements such as embedded scripts, exploits, and malicious URLs. This paper presents a comparative analysis of machine learning (ML) techniques, including Naive Bayes (NB), K-Nearest Neighbor (KNN), Average One Dependency Estimator (A1DE), Random Forest (RF), and Support Vector Machine (SVM) for PDF malware detection. The study… More >