SHUBHRA CHANDRA^1,2, JENNIFER C. WILSON^1,2, DAVID GOOD³, MING Q. WEI^1,2,*

Oncology Research, Vol.32, No.10, pp. 1543-1564, 2024, DOI:10.32604/or.2024.043987

Abstract The advent of RNA therapy, particularly through the development of mRNA cancer vaccines, has ushered in a new era in the field of oncology. This article provides a concise overview of the key principles, recent advancements, and potential implications of mRNA cancer vaccines as a groundbreaking modality in cancer treatment. mRNA cancer vaccines represent a revolutionary approach to combatting cancer by leveraging the body’s innate immune system. These vaccines are designed to deliver specific mRNA sequences encoding cancer-associated antigens, prompting the immune system to recognize and mount a targeted response against malignant cells. This personalized… More > Graphic Abstract

Mohammad Ababneh^*, Ayat Al-Droos, Ammar El-Hassan

Computer Systems Science and Engineering, Vol.48, No.5, pp. 1171-1191, 2024, DOI:10.32604/csse.2024.052875

Abstract With the high level of proliferation of connected mobile devices, the risk of intrusion becomes higher. Artificial Intelligence (AI) and Machine Learning (ML) algorithms started to feature in protection software and showed effective results. These algorithms are nonetheless hindered by the lack of rich datasets and compounded by the appearance of new categories of malware such that the race between attackers’ malware, especially with the assistance of Artificial Intelligence tools and protection solutions makes these systems and frameworks lose effectiveness quickly. In this article, we present a framework for mobile malware detection based on a… More >

Abdullah Alabdulatif¹, Navod Neranjan Thilakarathne^2,*, Mohamed Aashiq^3,*

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3655-3683, 2024, DOI:10.32604/cmc.2024.054610

Abstract The increasing prevalence of Internet of Things (IoT) devices has introduced a new phase of connectivity in recent years and, concurrently, has opened the floodgates for growing cyber threats. Among the myriad of potential attacks, Denial of Service (DoS) attacks and Distributed Denial of Service (DDoS) attacks remain a dominant concern due to their capability to render services inoperable by overwhelming systems with an influx of traffic. As IoT devices often lack the inherent security measures found in more mature computing platforms, the need for robust DoS/DDoS detection systems tailored to IoT is paramount for… More >

MEIR DJALDETTI^*

Oncology Research, Vol.32, No.9, pp. 1389-1399, 2024, DOI:10.32604/or.2024.049745

Abstract Resveratrol (RSV), the primary polyphenol found in grapes, has been revealed to have anti-inflammatory properties by reducing the capacity of the peripheral blood mononuclear cells to produce pro-inflammatory cytokines, including IL-1β, IL-6, IL-1ra and TNFα. Considering the close association between chronic inflammation and cancer development, RSV’s immunomodulatory properties are one way by which the polyphenol may inhibit cancer initiation, proliferation, neovascularization, and migration. Resveratrol influences the generation of microtumor environment which is one of the key factors in cancer progress. In addition to immunomodulation, RSV inhibits cancer development by expressing anti-oxidant effects, causing cell cycle… More > Graphic Abstract

Brij B. Gupta^1,2,3,*, Akshat Gaurav⁴, Razaz Waheeb Attar⁵, Varsha Arya^6,7, Ahmed Alhomoud⁸, Kwok Tai Chui⁹

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2689-2706, 2024, DOI:10.32604/cmes.2024.050825

Abstract This study introduces a long-short-term memory (LSTM)-based neural network model developed for detecting anomaly events in care-independent smart homes, focusing on the critical application of elderly fall detection. It balances the dataset using the Synthetic Minority Over-sampling Technique (SMOTE), effectively neutralizing bias to address the challenge of unbalanced datasets prevalent in time-series classification tasks. The proposed LSTM model is trained on the enriched dataset, capturing the temporal dependencies essential for anomaly recognition. The model demonstrated a significant improvement in anomaly detection, with an accuracy of 84%. The results, detailed in the comprehensive classification and confusion More >

Ibraheem Al-Hejri¹, Farag Azzedin^1,*, Sultan Almuhammadi¹, Naeem Firdous Syed²

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4197-4218, 2024, DOI:10.32604/cmc.2024.047117

Abstract The use of the Internet of Things (IoT) is expanding at an unprecedented scale in many critical applications due to the ability to interconnect and utilize a plethora of wide range of devices. In critical infrastructure domains like oil and gas supply, intelligent transportation, power grids, and autonomous agriculture, it is essential to guarantee the confidentiality, integrity, and authenticity of data collected and exchanged. However, the limited resources coupled with the heterogeneity of IoT devices make it inefficient or sometimes infeasible to achieve secure data transmission using traditional cryptographic techniques. Consequently, designing a lightweight secure More >

Yuping Bian^*, Xiu Wan, Xiaoyu Zhou

Energy Engineering, Vol.121, No.6, pp. 1637-1656, 2024, DOI:10.32604/ee.2024.047678

Abstract To address uncertainty as well as transient stability constraints simultaneously in the preventive control of wind farm systems, a novel three-stage optimization strategy is established in this paper. In the first stage, the probabilistic multi-objective particle swarm optimization based on the point estimate method is employed to cope with the stochastic factors. The transient security region of the system is accurately ensured by the interior point method in the second stage. Finally, the verification of the final optimal objectives and satisfied constraints are enforced in the last stage. Furthermore, the proposed strategy is a general More >

Xiaoyan Zhu¹, Ruchun Jia², Tingrui Zhang³, Song Yao^4,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4363-4377, 2024, DOI:10.32604/cmc.2023.045615

Abstract The traditional air traffic control information sharing data has weak security characteristics of personal privacy data and poor effect, which is easy to leads to the problem that the data is usurped. Starting from the application of the ATC (automatic train control) network, this paper focuses on the zero trust and zero trust access strategy and the tamper-proof method of information-sharing network data. Through the improvement of ATC’s zero trust physical layer authentication and network data distributed feature differentiation calculation, this paper reconstructs the personal privacy scope authentication structure and designs a tamper-proof method of… More >

Hongsheng Su, Lixia Dong^*, Xiaoying Yu, Kai Liu

Energy Engineering, Vol.121, No.4, pp. 973-986, 2024, DOI:10.32604/ee.2023.043497

Abstract Time based maintenance (TBM) and condition based maintenance (CBM) are widely applied in many large wind farms to optimize the maintenance issues of wind turbine gearboxes, however, these maintenance strategies do not take into account environmental benefits during full life cycle such as carbon emissions issues. Hence, this article proposes a carbon emissions computing model for preventive maintenance activities of wind turbine gearboxes to solve the issue. Based on the change of the gearbox state during operation and the influence of external random factors on the gearbox state, a stochastic differential equation model (SDE) and More > Graphic Abstract

Ali Hamid Farea^1,*, Omar H. Alhazmi¹, Kerem Kucuk²

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1525-1545, 2024, DOI:10.32604/cmc.2023.045794

Abstract While emerging technologies such as the Internet of Things (IoT) have many benefits, they also pose considerable security challenges that require innovative solutions, including those based on artificial intelligence (AI), given that these techniques are increasingly being used by malicious actors to compromise IoT systems. Although an ample body of research focusing on conventional AI methods exists, there is a paucity of studies related to advanced statistical and optimization approaches aimed at enhancing security measures. To contribute to this nascent research stream, a novel AI-driven security system denoted as “AI2AI” is presented in this work.… More >