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Integration between Bioinformatics Algorithms and Neutrosophic Theory

Neutrosophic Sets and systems 2024年 66卷 34-54页

作者： Farag, Romany M. Shams, Mahmoud Y. Aldawody, Dalia A. Khalid, Huda E. El-Bakry, Hazem M. Salama, Ahmed A. Dept. of Math and Computer Science Faculty of Science Port Said Univ. Egypt Dept. of Machine Learning Faculty of Artificial Intelligence Kafrelsheikh University Egypt Telafer University Telafer Iraq Dept. of Information Systems Faculty of Computer and Information Sciences Mansoura University Egypt Dept. of Math and Computer Science Faculty of Science Port Said University Egypt

This paper presents a neutrosophic inference model for bioinformatics. The model is used to develop a system for accurate comparisons of human nucleic acids, where the new nucleic acid is compared to a database of old nucleic acids. The comparisons are analyzed in terms of accuracy, certainty, uncertainty, neutrality, and bias. The proposed system achieves good results and provides a reliable standard for future comparisons. It highlights the potential of neutrosophic inference models in bioinformatics applications. Data mining and bioinformatics play a crucial role in computational biology, with applications in scientific research and industrial development. Biological analysts rely on specialized tools and algorithms to collect, store, categorize, and analyze large volumes of unstructured data. Data mining techniques are used to extract valuable information from this data, aiding in the development of new therapies and understanding genetic relationships between organisms. Recent advancements in bioinformatics include gene expression tools, Bio sequencing, and Bio databases, which facilitate the extraction and analysis of vital biological information. These technologies contribute to the analysis of big data, identification of key bioinformatics insights, and generation of new biological knowledge. Data collection, analysis, and interpretation in this field involves the use of modern technologies such as cloud computing, machine learning, and artificial intelligence, enabling more efficient and accurate results. Ultimately, data mining and bioinformatics enhance our understanding of genetic relationships, aid in developing new therapies, and improve healthcare outcomes. © (2024), (Neutrosophic Sets and systems). All rights reserved.

关键词： Bioinformatics

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The Impact Of Quantum Computing In Evolutionary Algorithms

The Impact Of Quantum Computing In Evolutionary Algorithms

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2023 International Conference on Decision Aid Sciences and Applications, DASA 2023

作者： Belkebir, Djalila Lati, Abdelhai Belkebir, Malak Bp 511 Faculty of New Information and Communication Technologies Ouargla30000 Algeria University of Oum El Bouaghi Research Laboratory on Computer Science's Complex Systems Dept. Mathematics and Computer Science Oum El Bouaghi Algeria

ISBN: (纸本)9798350342055

Genetic algorithms are widely used for solving optimization problems. As the search space of the problem is augmented, the probability of falling into local minima will be augmented as well. Previous works showed that the adjusted phase (i.e. required modification per generation), may enhance badly the optimality reaching. Moreover, the search for suitable probabilities on crossover and mutation results in huge computational complexity. Recent developments in quantum technology have shown that quantum computers can provide a dramatic advantage over classical computers. This paper will be oriented toward computer scientists interested in the quantum genetic algorithm (QGA). Therefore, we will present a discussion, of the pros, and cons of classical GA. We survey the 'state of the art' of the most known techniques for evolving evolutionary algorithms and quantum computing. We intend in this work to help researchers and application developers in gaining insights into the power of quantum computing mechanisms. This science can inherently treat the balance between exploration and exploitation of the search space. This property is due to the use of Q-bits. The orientation toward the best solution is due to the use of Q-gates. © 2023 IEEE.

关键词： Genetic algorithms

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Forecasting of Monkeypox Cases Using Optimized SARIMAX Based Model 3

Forecasting of Monkeypox Cases Using Optimized SARIMAX Based...

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3rd IEEE International Conference on Electronic Engineering, ICEEM 2023

作者： Elshabrawy, Mahmoud Eid, Marwa M. Abdelhamid, Abdelaziz A. El-Kenawy, El-Sayed M. Ibrahim, Abdelhameed Delta Higher Institute of Engineering and Technology Dept. of Communications & Electronics Mansoura Egypt Delta University for Science and Technology Faculty of Artificial Intelligence Mansoura35111 Egypt Ain Shams University Faculty of Computer and Information Sciences Dep. of Computer Science Cairo Egypt University Mansoura Faculty of Engineering Computer Engineering and Control Systems Dept. Egypt

ISBN: (纸本)9798350323511

This study presents a dipper-throated-based ant colony optimization (DTACO) with the Seasonal Auto-Regressive Integrated Moving Average with eXogenous factor (SARIMAX) model (DTACO+SARIMAX) to forecast monkeypox cases. The work optimizes the SARIMAX model using grid search cross-validation and fine-tunes its hyperparameters using DTACO to improve prediction accuracy. The suggested model's consistency and accuracy are considerable compared to previous studies. Comparisons with state-of-the-art models validate the proposed model's predictions. DTACO+SARIMAX can be used to control disease and monitor monkeypox. Healthcare organizations and governments can better manage and track the pandemic's course by offering accurate predictions, reducing public panic, and enabling effective pandemic planning. The Analysis of Variance (ANOVA) and Wilcoxon signed-rank tests are conducted on the proposed DTACO-SARIMAX model and compared models. © 2023 IEEE.

关键词： Ant colony optimization

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Integrating Technology and Environmental Policy for Effective Air Quality Monitoring in Indonesia

Integrating Technology and Environmental Policy for Effectiv...

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Creative Communication and Innovative Technology (ICCIT), IEEE

作者： Mohammad Ifran Sanni Reza Dani Pramudya Hery Dieng Asep Jamaludin Sondang Visiana Sihotang Ihsan Nuril Hikam Dept. of Computer Systems University of Raharja Tangerang Indonesia Dept. of Information Technology Pandawan Sejahtera Indonesia Tangerang Indonesia Dept. of Information Systems Pelita Harapan University Tangerang Indonesia Dept. of Information Technology Bina Bangsa University Serang Indonesia Dept. of Digital Business Pandawan Sejahtera Indonesia Tangerang Indonesia

ISBN: (数字)9798350367492

ISBN: (纸本)9798350367508

Air quality monitoring is crucial for protecting ecosystems and public health, especially in Indonesia, a country with unique geographical and socio-economic characteristics facing complex environmental challenges. This study examines the multifaceted interactions of various factors affecting Indonesia’s air quality monitoring system, including industrial emissions, vehicular traffic, agricultural activities, and forest fires. Geographic factors like topography, wind patterns, and regional diversity significantly influence pollutant distribution and concentrations. Social and economic dimensions, such as rapid industrialization, urbanization, and population growth, also impact energy consumption patterns and air quality. This research employs a comprehensive methodological approach, combining literature review, data analysis, and the SmartPLS analytical model to understand these complexities. Data were collected from air monitoring agencies and scientific sources, focusing on variables such as industrial activity levels, traffic density, meteorological conditions, urbanization, and health impacts. The SmartPLS model was utilized to analyze complex cause- and-effect relationships between these variables. Results highlight significant variations in air quality across different regions and times, influenced by both environmental and human factors. Advanced sensor technologies and remote monitoring systems are identified as potential solutions to enhance monitoring coverage and accuracy, especially in remote areas. Collaboration between government, academia, and the private sector is emphasized as vital for developing a sustainable and effective air quality monitoring infrastructure. The study provides actionable recommendations for improving Indonesia’s air quality monitoring system, aiming to foster a cleaner and healthier environment. Enhanced monitoring can help identify and mitigate air quality issues, ensuring better public health outcomes and environmental protec

关键词： Climate change Analytical models Urban areas Surfaces Air quality Public healthcare Protection Socioeconomics Monitoring Meteorology

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Data Security Enhancement in Cloud Computing by Proposing A DKE Encryption Protocol 23

Data Security Enhancement in Cloud Computing by Proposing A ...

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Proceedings of the 2023 International Conference on Advances in Artificial Intelligence and Applications

作者： Sahar Ebadinezhad Halmat Ayub Abdulmajed Department of Computer Information Systems Near East University North Cyprus and Computer Information Systems Research and Technology Center (CISRT) Near East University North Cyprus Dept. Engineering and Computer Systems Lebanese French University (LFU) Iraq

ISBN: (纸本)9798400708268

This study uses cryptography to tackle the important problem of data security in cloud computing. Two keys are used in the Dual Key Encryption (DKE) method for both encryption and decryption. DKE employs a public key for the first encryption round before cloud upload and a user-only private key for the second round of encryption. Decryption operates oppositely. When tested and simulated with different file sizes on a CloudAnalyst simulator, DKE operates faster and more efficiently than cryptographic methods such as Triple DES (3DES), AES, RSA, and DES. Thanks to developments in information technology, cloud computing has made several services available online. Data security assurance is still very difficult to achieve, nevertheless. In this context, cryptography is essential and has led to the creation of the novel DKE technology. This technology is not only far more efficient than well-known cryptographic techniques such as 3DES, but it also improves data security.

关键词： Cloud Services Cryptography Data Integrity Data Security Dual Key Encryption

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An Optimal Optimization of Software Development Cost Estimation Using Genetic Algorithm

An Optimal Optimization of Software Development Cost Estimat...

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Sciences and Techniques of Automatic Control and computer Engineering MI-STA, IEEE International Maghreb Meeting of the Conference on

作者： Mabroukah Amarif Salha Owaydat dept. of Information Systems Faculty of Information Technology Sebha University of Libya Sebha Libya dept. of Computer Sciences Faculty of Sciences Sebha University of Libya Sebha Libya

ISBN: (数字)9798350372632

ISBN: (纸本)9798350372649

Estimating effort allows managers and software engineers to accurately anticipate, forecast, and quote schedule, budget, and manpower requirements. Determining estimated project cost, duration, and maintenance efforts well in advance Of the development stages is the biggest defiance to be attained for software projects. Formal models for cost estimation, such as the Constructive Cost Model (COCOMO) are limited by their inability to manage uncertainty in software projects early development cycle. This research presents an optimal optimization of software development cost estimation using genetic algorithm. It provides a fine solution to set the uncertain and ambiguous properties of software factors. It adopts COCOMO II model formulas and manages fine-tuning parameters for accurate effort and scheduled time software cost estimation. An experiment has been carried out using a NASA data set in order to improve the proposed algorithm. The experimental results show a significant optimization for both software effort up to 97.27% accuracy and scheduled time up to 98.88%. This research has emphasized that applying the genetic algorithm with fine-tuning parameters of COCOMO II model definitely improve the software development cost estimation.

关键词： Costs Accuracy Uncertainty Computational modeling Software algorithms Estimation Software

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Key Factors Influencing Mobile Banking Adoption in Saudi Arabia

Key Factors Influencing Mobile Banking Adoption in Saudi Ara...

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Federated Conference on computer Science and information systems (FedCSIS)

作者： Amal Alzahrani Natalia Beloff Martin White Dept. of Computer Science & Information Systems Baha University Baha Saudi Arabia Dept. of Informatics University of Sussex Brighton United Kingdom

ISBN: (数字)9788396960160

ISBN: (纸本)9798350359718

The introduction of mobile banking has revolutionized traditional financial practices, enhancing efficiency, customer experiences, and business models globally. Despite the global advancements in mobile banking, adoption rates remain low in Saudi Arabia. This paper seeks to identify key factors affecting adoption, using a mixed-methods approach. We propose a novel model integrating factors from the DeLone and McLean (D&M) model and the Unified Theory of Acceptance and Use of Technology (UTAUT2) model, complemented by additional factors. Data was gathered through online surveys and customer interviews. Findings revealed that net benefits, compatibility, facilitating conditions, and trust positively influence adoption, while literacy levels and digital skills pose barriers. Our study offers a significant theoretical contribution by synthesizing multiple models and enriches understanding of mobile banking adoption, aiding future research and industry decisions.

关键词： Surveys Industries computer science Computational modeling Banking Interviews Business

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LIDS: Lightweight Dynamic Scheduling Technique for 6G-enabled Massive LoRa based IoT systems

LIDS: Lightweight Dynamic Scheduling Technique for 6G-enable...

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2022 IEEE GLOBECOM Workshops, GC Wkshps 2022

作者： Kumbam, Akshitha Choudhury, Nikumani Nasralla, Moustafa M. Birla Institute of Technology & Science Dept. of Computer Science & Information Systems Pilani Hyderabad India Prince Sultan University Dept. of Communications & Networks Engineering Riyadh Saudi Arabia

ISBN: (纸本)9781665459754

The sixth-generation (6G) wireless communication networks are envisioned to deliver improved Quality of Services (QoS) such as data-rate, latency, localization, etc., compared to 5G services. This demand will mainly arise due to the massive Internet of Things (IoT) connections among billions of embedded devices. It is worth noting that these IoT devices are constrained in nature in terms of memory, computation and most importantly power. Low-power wireless computing necessitates a link-layer technology that considers the aforementioned IoT device requirements such as low-power, low data-rate, long-range and energy efficient reliable communications. Long Range Radio (LoRa) technology has recently become widely popular to facilitate low-power, long-range communication, while other similar technologies struggle to achieve long-range transmissions. The LoRA standard defines several PHY and MAC sub-layer specifications for Low-Power Wide Area Networks (LPWAN) that can be used to build several IoT applications. With 6G communications, an IoT application is expected to consist of hundreds of devices connected at a time, and this will need a proper scheduling mechanism among these devices for optimal performance. The LoRa standard does not define any scheduling mechanism and leaves it to the research community to explore. In this paper, we propose a distributed scheduling mechanism under the supervision of a common LoRa gateway. The proposed mechanism focuses on a Lightweight DynamicScheduling (LIDS) scheme to minimize loss in data transmissions through collisions. The proposed mechanism optimizes the power consumption to achieve the desired level of QoS requirements such as throughput and latency. © 2022 IEEE.

关键词： Internet of things

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A Variable Step-Size Hybrid Adaptive Nonlinear Filter for Solar Radiation Prediction

A Variable Step-Size Hybrid Adaptive Nonlinear Filter for So...

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International Conference on systems and Informatics (ICSAI)

作者： Y. Xiao L. Ma K. Khorasani Dept. of Management & Information Systems Prefectural University of Hiroshima Hiroshima Japan Dept. of Electrical & Computer Engineering Concordia University Montreal Canada

ISBN: (数字)9798331510138

ISBN: (纸本)9798331510145

In this paper, a new hybrid adaptive nonlinear filter (HANF) scheme with variable step sizes (VSS) is proposed for solar radiation prediction. Our methodology consists of a Volterra filter and a functional link artificial neural network (FLANN) filter. The Volterra filter with the first- and second-order kernels is included, that is capable of expressing both linearity and nonlinearity. The FLANN filter can handle the nonlinearity that may be expressed by higher-order exponential terms that the Volterra filter with a limited number of kernels is unable to deal with. The VSSs are introduced in the two filters to allow the HANF to enjoy desirable tracking capability such that the time-varying nonlinearity underlying the nonlinear phenomena can be detected and tracked. The proposed VSS-HANF is applied to a real hourly solar radiation time sequence to confirm its improved prediction performance as compared to its counterpart with fixed step sizes.

关键词： Accuracy Finite impulse response filters Adaptive filters Weather forecasting Linearity Nonlinear filters Artificial neural networks Solar radiation Kernel Informatics

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Improving Fake News Detection with a Mixture of Experts: Leveraging Sentiment Analysis and Sarcasm Detection as Core Expert Models

Improving Fake News Detection with a Mixture of Experts: Lev...

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Advancements in Computing (ICAC), International Conference on

作者： Tharindu Gunasekara Disira Thihan Sansika Kodithuwakku Dinuka Dissanayake Harinda Fernando Samitha Vidhanaarachchi Archchana Sindhujan dept. of Software Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka dept. of Computer Computer Systems Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka dept. of Computer Science and Electronic Engineering University of Surrey United Kingdom

ISBN: (数字)9798331517878

ISBN: (纸本)9798331517885

Fake news continues to proliferate, posing an increasing threat to public discourse. The paper proposes a framework of a Mixture of Experts, Sentiment Analysis, and Sarcasm Detection experts for improved fake news detection. This approach captures the emotional cues in the text through a Sentiment Analysis expert, which is based on bidirectional encoder representations from Transformers (BERT) models with sentiment vectors generated using SentiWordNet and Integrated Gradients. It combines a sarcasm detection expert based on BERT, recognizing sarcasm and its type to help classify fake news. By fusing these experts through a Mixture of Experts gateway, subtle linguistic cues often found in fake news are more effectively analyzed, leading to improved accuracy in detecting misinformation. Experimental results are presented as 96% for the Sarcasm expert with the BERT base model and 83% for the Sentiment Analysis expert with the distilled version of the BERT (DistilBERT) base model, proving the effectiveness of the proposed approach in beating traditional methods.

关键词： Sentiment analysis Analytical models Accuracy Bidirectional control Logic gates Linguistics Transformers Encoding Vectors Fake news

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