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Computational examination to reveal Kaempferol as the most potent active compound from Euphorbia hirta against breast cancer by targeting AKT1 and ERα

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Egyptian Journal of Basic and Applied Sciences 2023年第1期10卷 753-767页

作者： Widyananda, Muhammad Hermawan Fatchiyah, Fatchiyah Muflikhah, Lailil Ulfa, Siti Mariyah Widodo, Nashi Department of Biology Faculty of Mathematics and Natural Sciences Universitas Brawijaya Malang Indonesia Department of Informatics Engineering Faculty of computer science Universitas Brawijaya Malang Indonesia Department of Chemistry Faculty of Mathematics and Natural Sciences Universitas Brawijaya Malang Indonesia

Breast cancer belongs to diseases with the highest mortality rates. Euphorbia hirta is an herbal plant with various pharmacological properties and is predicted to have good anti-breast cancer properties. This current study analyzed a potent compound from E. hirta as an anti-breast cancer candidate and predicted its mechanism. The Bioactive compounds in E. hirta were screened for drug-likeness, toxicity, membrane permeability, and bioactivity. Protein target prediction utilized four databases, followed by functional annotation analysis. Molecular docking employed AutoDock Vina, and molecular dynamic simulation used Yet Another Scientific Artificial Reality Application with parameters reflecting human cell physiology. Kaempferol was the potent compound in E. hirta that passed the screening and was predicted to have better anti-breast cancer activity than that of other compounds. Kaempferol targets AKT1 and ERα, the proteins correlating with breast cancer progression. The molecular docking results showed that Kaempferol bound to inhibitor sites on both AKT1 and ERα. In addition, Molecular dynamic analysis showed that the interaction between Kaempferol with AKT1 and ERα was stable, as seen from the RMSD, RMSF, hydrogen bonding, and MM/PBSA binding energy values. Therefore, Kaempferol was a bioactive compound from E. hirta with promising anti-breast cancer activities by targeting the AKT1 and ERα. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： AKT1 anticancer ERα Euphorbia hirta Kaempferol

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Wrapper-Based Feature Selection to Improve The Accuracy of Intrusion Detection System (IDS) 10

Wrapper-Based Feature Selection to Improve The Accuracy of I...

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10th International Conference on Wireless and Telematics, ICWT 2024

作者： Jupriyadi Budiman, Arief Hamidi, Eki Ahmad Zaki Ahdan, Syaiful Negara, Ridha Muldina Institut Teknologi Bandung School of Electrical Engineering and Informatics Bandung Indonesia Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Bandarlampung Indonesia Universitas Gadjah Mada Department Computer Science and Electronics Yogyakarta Indonesia UIN Sunan Gunung Djati Bandung Electrical Engineering Department Bandung Indonesia Telkom University School of Electrical Engineering Bandung Indonesia

ISBN: (纸本)9798350377057

An Intrusion Detection System (IDS) is a system that can detect attacks on a network. IDS systems can be built using machine learning approaches. However, significant network traffic and many features cause machine learning algorithms to work slowly. Not all available features are essential for use as a reference in an intrusion detection system. Feature selection is important because it can reduce the dataset and speed up computing time in building models and detection systems. In this paper, feature selection using the wrapper method is proposed. Its performance is compared with filter-based feature selection, such as chi-square, information gain, gain ratio, and correlation-based feature selection (CFS). Based on the exploration, the results showed that the feature selection algorithm using the wrapper method was superior to other algorithms. The number of critical features discovered and the detection system's precision serve as proof of the wrapper approach. With only three features as a reference, the detection system produces an accuracy of 96.22%. It increases 5.84% from 90.38% to 96.22%. Computation time also increases because the number of features used is tiny compared to other algorithms and uses all features. © 2024 IEEE.

关键词： Network intrusion

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Current Trends, Challenges and Techniques in XAI Field;A Tertiary Study of XAI Research

Current Trends, Challenges and Techniques in XAI Field;A Ter...

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Proceedings of the International Convention MIPRO

作者： Saša Brdnik Boštjan Šumak Institute of Informatics Faculty of Electrical Engineering and Computer Science University of Maribor (Slovenia)

ISBN: (数字)9798350382501

ISBN: (纸本)9798350382518

This tertiary systematic literature review examines 29 systematic literature reviews and surveys in Explainable Artificial Intelligence (XAI) to uncover trends, limitations, and future directions. The study explores current explanation techniques, providing insights for researchers, practitioners, and policymakers interested in enhancing AI transparency. Notably, the increasing number of systematic literature reviews (SLRs) in XAI publications indicates a growing interest in the field. The review offers an annotated catalogue for human-computer interaction-focused XAI stakeholders, emphasising practitioner guidelines. Automated searches across ACM, IEEE, and Science Direct databases identified SLRs published between 2019 and May 2023, covering diverse application domains and topics. While adhering to methodological guidelines, the SLRs often lack primary study quality assessments. The review highlights ongoing challenges and future opportunities related to XAI evaluation standardisation, its impact on users, and interdisciplinary research on ethics and GDPR aspects. The 29 SLRs, analysing over two thousand papers, include five directly relevant to practitioners. Additionally, references from the SLRs were analysed to compile a list of frequently cited papers, serving as recommended foundational readings for newcomers to the field.

关键词： Surveys Ethics Systematics Explainable AI Reviews Bibliographies Market research

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Embedded Coded Relay System for Molecular Communications

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computers, Materials & Continua 2022年第8期72卷 2729-2748页

作者： Eman S.Attia Ashraf A.M.Khalaf Fathi E.Abd El-Samie Saied M.Abd El-atty Konstantinos A.Lizos Osama Alfarraj Farid Shawki Imran Khan Ki-Il Kim Department of Electrical Engineering Faculty of EngineeringMinia UniversityMiniaEgypt Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenoufiaEgypt Department of Informatics Faculty of Mathematics and Natural SciencesUniversity of Oslo(UiO)Norway Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Department of Electrical Engineering University of Engineering&TechnologyPeshawar814Pakistan Department of Computer Science and Engineering Chungnam National UniversityDaejeon34134Korea

With the emergence of the COVID-19 pandemic,the World Health Organization(WHO)has urged scientists and industrialists to exploremodern information and communication technology(ICT)as a means to reduce or even eliminate *** World Health Organization recently reported that the virus may infect the organism through any organ in the living body,such as the respiratory,the immunity,the nervous,the digestive,or the cardiovascular *** the abovementioned goal,we envision an implanted nanosystem embedded in the intra living-body *** main function of the nanosystem is either to perform diagnosis and mitigation of infectious diseases or to implement a targeted drug delivery system(i.e.,delivery of the therapeutic drug to the diseased tissue or targeted cell).The communication among the nanomachines is accomplished via communication-based molecular *** control/interconnection of the nanosystem is accomplished through the utilization of Internet of bio-nano things(IoBNT).The proposed nanosystem is designed to employ a coded relay nanomachine disciplined by the decode and forward(DF)principle to ensure reliable drug delivery to the targeted ***,both the sensitivity of the drug dose and the phenomenon of drug molecules loss before delivery to the target cell site in long-distance due to the molecules diffusion process are taken into *** this paper,a coded relay NM with conventional coding techniques such as RS and Turbo codes is selected to achieve minimum bit error rate(BER)performance and high signal-to-noise ratio(SNR),while the detection process is based on maximum likelihood(ML)probability and minimum error probability(MEP).The performance analysis of the proposed scheme is evaluated in terms of channel capacity and bit error rate by varying system parameters such as relay position,number of released molecules,relay and receiver *** results are validated through simulation and demonstrate that the proposed scheme can

关键词： Molecular communication nanonetwork internet of bio-nano things coded relay scheme coding

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Facial Palsy Image Classification Using Landmarks Extraction and Extreme Learning Machine

Facial Palsy Image Classification Using Landmarks Extraction...

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8th IEEE-EMBS Conference on Biomedical engineering and Sciences, IECBES 2024

作者： Febriyanti, Frisca P. A. Bachtiar, Fitra Abdurrachman Widodo, Agus W. University of Brawijaya Faculty of Computer Science Informatics Engineering Department Malang Indonesia

ISBN: (纸本)9798350383409

Facial palsy is a condition characterized by facial paralysis, affecting the patient's motor function. Detection is typically done through a clinical expert's direct observation of facial muscles. However, manual examinations are less effective as patients tend to go for health checks when symptoms indicate severe dysfunction. Due to these challenges, a classification system is built as early screening for facial palsy. This research aims to propose the detection of facial palsy using Extreme Learning Machine algorithm. In this research, we use three datasets: CK+, JAFFE, and Youtube Facial Palsy (YFP). The dataset is divided into training and testing data in an 80:20 ratio. Applied preprocessing techniques of landmark facial feature extraction, selection, and Euclidean distance calculation at specific face points. We employ k-fold cross-validation to find the optimal parameter during the training process. We also implemented oversampling and undersampling techniques to handle imbalanced data. The system classifies facial palsy into normal, mild, moderate, and severe dysfunction. The ELM model achieved Accuracy values of 0.9949, Precision of 0.9888, Recall of 0.9887, and F1-score of 0.9888 on balanced data using an oversampling technique. The current research indicates that the implemented techniques can handle imbalanced data, and contribute to better model performance. © 2024 IEEE.

关键词： Neural networks

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The Effect of Preprocessing on Skin Lesion Segmentation 8

The Effect of Preprocessing on Skin Lesion Segmentation

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8th International Conference on Information Technology, InCIT 2024

作者： Nugroho, Arief Kelik Afiahayati Wibowo, Moh Edi Soebono, Hardyanto Universitas Gadjah Mada Faculty of Mathematics and Natural Science Department of Computer Science and Electronics Yogyakarta Indonesia Universitas Jenderal Soedirman Faculty of Engineering Department of Informatics Engineering Purwokerto Indonesia Public Health and Nursing Universitas Gadjah Mada Faculty of Medicine Department of Dermatology and Venereology Yogyakarta Indonesia

ISBN: (纸本)9798350366303

Image preprocessing is a crucial step in enhancing the quality of skin lesion images before segmentation, with the primary objective of removing noise and artifacts that could interfere with the segmentation process and reduce accuracy. This process involves various techniques designed to address artifacts such as hair, black frames, skin lines, and vignettes, which may arise due to variables in image acquisition, such as lighting conditions and skin characteristics. Several preprocessing techniques used include artifact removal using Gaussian filter, bottom hat filter, and median filter, as well as hair removal methods like DullRazor and short line detector. Image augmentation techniques, such as rotation and transformation, are also employed to ensure that key features in the image are well preserved and accurately reflected in the data, helping to prevent overfitting during the classification stage. Additionally, contrast enhancement through methods like Contrast-Limited Adaptive Histogram Equalization (CLAHE) and gamma correction is used to improve lesion visibility and enhance the accuracy of lesion boundary detection. Findings from various studies indicate that appropriate preprocessing can significantly improve image quality, leading to more accurate segmentation. Descriptive statistical testing can be employed to analyze the extent to which these preprocessing steps affect segmentation outcomes, focusing on accuracy improvements and the reduction of segmentation errors caused by artifacts and noise in the images. Thus, effective preprocessing not only enhances image quality but also provides a stronger foundation for more accurate segmentation and classification in skin lesion diagnosis. © 2024 IEEE.

关键词： Median filters

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Comprehensive Analysis and Remediation of Insecure Direct Object References (IDOR) Vulnerabilities in Android APIs 1

Comprehensive Analysis and Remediation of Insecure Direct Ob...

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1st IEEE International Conference on Cryptography, informatics, and Cybersecurity, ICoCICs 2023

作者： Yulianto, Semi Abdullah, Roni Reza Soewito, Benfano Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia National Institute of Science and Technology Faculty of Informatics Engineering Jakarta12630 Indonesia Bina Nusantara University Binus Graduate Program. Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350339437

The escalating visibility of secure direct object reference (IDOR) vulnerabilities in API security, as indicated in the compilation of OWASP Top 10 API Security Risks, highlights a noteworthy peril to sensitive data. This study explores IDOR vulnerabilities found within Android APIs, intending to clarify their inception while evaluating their implications for application security. This study combined the qualitative and quantitative approaches. Insights were obtained from an actual penetration test on an Android app into the primary reasons for IDOR vulnerabilities, underscoring insufficient input validation and weak authorization methods. We stress the frequent occurrence of IDOR vulnerabilities in the OWASP Top 10 API vulnerability list, highlighting the necessity to prioritize them in security evaluations. There are mitigation recommendations available for developers, which recognize its limitations involving a possibly small and homogeneous selection of tested Android applications, the testing environment that could cause some inaccuracies, and the impact of time constraints. Additionally, the study noted insufficient threat modeling and root cause analysis, affecting its generalizability and real-world relevance. However, comprehending and controlling IDOR dangers can enhance Android API security, protect user data, and bolster application resilience. © 2023 IEEE.

关键词： Sensitive data

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A Wideband Rotary Antenna Based on Gap Wavegudie Technology for mmWave Applications 19

A Wideband Rotary Antenna Based on Gap Wavegudie Technology ...

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19th European Conference on Antennas and Propagation, EuCAP 2025

作者： Farahbakhsh, Ali Zarifi, Davood Mrozowski, Michal Gdansk University of Technology Faculty of Electronics Telecommunications and Informatics Department of Microwave and Antenna Engineering Gdansk 80-233 Poland Graduate University of Advanced Technology Department of Electrical and Computer Engineering Kerman Iran School of Electrical and Computer Engineering University of Kashan Kashan Iran

ISBN: (纸本)9788831299107

This study introduces the design of a gap waveguide-based rotary antenna capable of 360° mechanical beam-steering for wideband mmWave applications. This innovative design overcomes the typical limitations of electronically steerable antennas, such as narrow bandwidth, restricted steering range, gain reduction, and high cost and complexity. The designed rotary antenna achieves a gain of 13.8 dBi without any scan loss across the entire 360° steering range from 45 to 60 GHz. The proposed rotary antenna is a promising candidate for a variety of mmWave mechanical beam scanning systems. © 2025 European Association on Antennas and Propagation.

关键词： beem-steering gap waveguide technology rotary antenna

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An enhanced donkey and smuggler optimization algorithm for choosing the precise job applicant

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Iran Journal of computer Science 2023年第3期6卷 233-243页

作者： Hasan, Nazir M. Rashid, Tarik A. Alsadoon, Abeer Qosaeri, Ahmed S. Abualigah, Laith Yaseen, Zaher Mundher Computer Science and Engineering Department University of Kurdistan Hawler KR Erbil Iraq Charles Sturt University Sydney Australia Faculty of Computer Sciences and Informatics Amman Arab University Amman Jordan Civil and Environmental Engineering Department King Fahd University of Petroleum and Minerals Dhahran 31261 Saudi Arabia

Throughout the last few decades, Nature-Inspired Algorithms (NIA) have become very popular in solving real-world problems by getting inspiration from nature. This work suggests the Modified Donkey and Smuggler Optimization (MDSO) algorithm for solving the selection problem to choose suitable job applicants for a specific position. The original Donkey and Smuggler Optimization algorithm (DSO) has two modes: smuggler and donkey mode (non-adaptive and adaptive). In the smuggler mode, the algorithm tries to find the best solutions, which is the path to send the donkey to the destination;once the best path is found, the smuggler will send the donkey through the selected path. The donkey's actions will start when the smuggler mode's best solution is no longer the best one. Certain modifications have been made in the smuggler mode, including replacing the original fitness with a new fitness equation since that method can work more accurately. The Human Resource (HR) department in Korek-telecom has been used as a resource to achieve real-world data to test the original and Modified DSO. Using MDSO, not only will organizations be able to choose suitable job applicants more accurately but also will manage to do so at a faster pace as well. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023.

关键词： Donkey and smuggler algorithms Human resource management MDSO Nature-inspired algorithms Optimization algorithm Swarm intelligence

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Diesel Engine Fault Detection using Deep Learning Based on LSTM 7

Diesel Engine Fault Detection using Deep Learning Based on L...

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7th International Conference on Electrical, Telecommunication and computer engineering, ELTICOM 2023

作者： Naryanto, Rizqi Fitri Delimayanti, Mera Kartika Naryaningsih, Agustien Warsuta, Bambang Adi, Rizky Setiawan, Bima Aji Universitas Negeri Semarang Faculty of Engineering Department of Mechanical Engineering Indonesia National Research and Innovation Agency Fisheries Reseach Center Indonesia Politeknik Negeri Jakarta Department of Computer and Informatics Engineering Indonesia

ISBN: (纸本)9798350385526

This work aims to create a deep learning model utilizing Long Short-Term Memory (LSTM) as a classification model to detect and diagnose potential problems in diesel engines. The default dataset comprises 3,500 data entries and four distinct dataset types. White noise in the dataset is attributed to additive Gaussian white noise (AWGN). The main contributions of this study comprise developing a classification model aimed at identifying damage in diesel engines, as well as evaluating the performance of the Long Short-Term Memory (LSTM) method. The K-Fold cross-validation technique was utilized, where the value of k was set at 5. This study examines the damage classification in diesel engines using four datasets: default 0dB Noise, 15dB Noise, 30dB Noise, and 60dB Noise. The K-Fold Cross Validation methodology was employed, utilizing a value of k=5. The training and validation processes were conducted iteratively, employing a learning rate of 0.00005 during the training phase. The training phase utilized a mini-batch size of 128, and the maximum number of epochs was set at 10,000. The results indicate that the dataset containing 60dB noise consistently demonstrates the highest level of accuracy, with an average accuracy of 97.91% across the five folds and the efficacy of Long Short-Term Memory (LSTM) models in classification tasks is improved in the presence of white noise. © 2023 IEEE.

关键词： Long short-term memory

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