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Modeling and Performance Analysis of Spiral Fishbone Network Using NS-2

Journal of computer and Communications 2022年第3期10卷 125-140页

作者： Pronab Biswas Md Maruf Islam Sayed Asaduzzaman Nazrul Islam M. Raihan Department of Software Engineering Daffodil International University Dhaka Bangladesh Department of Information and Communication Technology Mawlana Bhashani Science and Technology University Tangail Bangladesh Department of Computer Science and Engineering North Western University Khulna Bangladesh

In this research, we have projected and carried out a novel fishbone network that shows better performance in the term of minimizing the packet delay with respect to sink speed. Previous study implies that sector angle affects greatly on designing fishbone network. Finite Set of nodes arranges to sense the physical condition of any system is called wireless sensor. Our designed fishbone network can be potentially applied for a wireless sensing system to formulate a whole network. The network is a novel design which has been finalized by comparing sector angle. Analysis takes place by varying packet delay according to sink speed. Future analysis takes place for Quality of Service (QoS) and Quality of Experience (QoE). Latency of Packet and its size is the measurement criteria of any network or service is called Quality of Service (QoS). On the other hand the user experience of using the designed network is called Quality of Experience (QoE). Our designed network has been analyzed in TCP Tracer to find out the latency or packet delay for different users. The user data has been shorted and equated among them for latency with different no of packets. Our proposed spiral fishbone network shows better QoS and QoE. In future more nodes can be added to design extended fishbone network for wireless.

关键词： Fishbone Network Network Modelling Performance Analysis NS-2

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Clinical Significance of Measles and Its Prediction Using Data Mining Techniques: A Systematic Review

Clinical Significance of Measles and Its Prediction Using Da...

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International Conference on Artificial Intelligence and Data engineering, AIDE 2019

作者： Rao, Abhishek S. D’Mello, Demian Antony Anand, R. Nayak, Sneha Department of Information Science and Engineering NMAM Institute of Technology Nitte UdupiKarnataka574110 India Department of Computer Science and Engineering Canara Engineering College Bantwal India Department of Master of Computer Application NMAM Institute of Technology Nitte UdupiKarnataka574110 India Department of Biotechnology Engineering NMAM Institute of Technology Nitte UdupiKarnataka574110 India

ISBN: (纸本)9789811535130

Data science techniques used in the past era for data extraction are now being replaced by data mining methods due to a lot of contemporary trends and challenges. Data mining includes implicit data extraction, which is previously unknown but potentially useful information, with the help of databases to generate new information. Medical data mining is an area of challenges since the data involves in it is imprecise, inconsistent and massive. Medical diagnostics systems are evaluated by employing large information databases, but it endures many failures to extract data from the databases. There exists no tool to discover the major relationships concerning the data. In such a case, the core knowledge of healthcare data is extracted by applying the data mining methods, thus helping in turning raw data into useful information. Measles is an immunizable disease most likely seen in infants and young children. Measles (rubeola), is an RNA virus, belongs to the Morbillivirus genus, and Paramyxoviridae family. It is one among the six major killer diseases, with accounts to 90% secondary infection rate with susceptible contacts. In this paper, the authors present a systematic review of measles cases and its mortality with the help of the taxonomical tree structure. The published research which utilizes the application of data mining techniques for early prediction of measles in terms of methods used, algorithms utilized and results obtained are evaluated. The paper provides major consolidation of data with respect to motive, study and methods used in the literature. The authors present the summary of the research review findings and research gaps for further study and possible application. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Data mining

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The effects of Tx./Rx. pointing errors on the performance efficiency of local area optical wireless communication networks

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Journal of Optical Communications 2024年 45卷 s253-s259页

作者： Eid, Mahmoud M. A. Zaki Rashed, Ahmed Nabih Ahammad, Mohd. Sultan Paul, Bikash Kumar Ahmed, Kawsar Department of Electrical Engineering College of Engineering Taif University Taif Saudi Arabia Electronics and Electrical Communications Engineering Department Faculty of Electronic Engineering Menoufia University Menouf32951 Egypt Department of Computer Science and Engineering Mawlana Bhashani Science and Technology University Santosh Tangail1902 Bangladesh Department of Information and Communication Technology Mawlana Bhashani Science and Technology University Santosh Tangail1902 Bangladesh Group of Bio-photomatiχ Mawlana Bhashani Science and Technology University Santosh Tangail1902 Bangladesh Department of Software Engineering Daffodil International University Dhanmondi Sukrabad Dhaka1207 Bangladesh

This study presents the effects of Tx./Rx. pointing errors on the performance efficiency of local area optical wireless communication networks. The received signal power and max Q factor are measured in the presence of vertical-cavity surface-emitting lasers (VCSELs) bias current and modulation current at maximum propagation distance for the wireless network. The signal is enhanced with increasing of bias and modulation peak currents of the VCSEL device. The optimum received power and max. Q factor is also examined at Tx./Rx. the pointing error of 0.1 mrad and propagation reach of 5 km at available bit rates transmission of 10 Gb/s. © 2021 Walter de Gruyter GmbH, Berlin/Boston.

关键词： Surface emitting lasers

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A deep learning-based approach for predicting ubiquitination sites using word embedding techniques

A deep learning-based approach for predicting ubiquitination...

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International Conference on computer and Information Technology (ICCIT)

作者： Md. Faruk Hosen Md. Abul Basar Md. Samim Hossain Sakib Sarker Md. Suhag Ali Monir Morshed Muhammad Shahin Uddin Department of Information and Communication Technology Mawlana Bhashani Science and Technology University Tangail Bangladesh Department of Computing and Information System Daffodil International University (DIU) Ashulia Dhaka Bangladesh Department of Computer Science and Engineering Uttara University Dhaka Department of Software Engineering Daffodil International University (DIU) Ashulia Dhaka Bangladesh

ISBN: (数字)9798331519094

ISBN: (纸本)9798331519100

Ubiquitination is a prevalent and reversible post-translational modification (PTM) that controls apoptosis and plays a crucial role in protein breakdown and cell disorders. Ubiquitination also involved in the control of a number of physiological mechanisms such as cellular proliferation, gene transcription, intracellular signaling, DNA correction, and synthesis. However, experimental identification of ubiquitination sites prediction is time-consuming and costly, so it is an urgent need to construct effective predictors. In this paper, a novel predictor called UbiSite-DeepWET has been developed to accurately predict ubiquitination sites from sequences using a convolutional neural network (CNN) model. First, we perform nine feature extraction method, namely Amino Acid Composition (AAC), Dipeptide Compostion (DPC), Composition of k-spaced Amino Acid Pairs (CKSAAP), Pseudo-Amino Acid Composition (PAAC), Amino Acid index (AAindex) database, Word2Vec, GloVe and fastText, to represent protein sequence patterns. Secondly, SHapley Additive exPlanations (SHAP) are used to remove unnecessary and irrelevant features for predicting ubiquitination sites. Finally, the best features are fed into the CNN classifier to build the UbiSite-DeepWET model for identifying the protein ubiquitination sites. Five-fold cross validation shows that the AUC values of Set1-Set6 datasets are 0.8846, 0.7764, 0.7881, 0.7740, 0.6870 and 0.7238, respectively. The Adaptive synthetic sampling approach (ADASYN) is applied in Set4 to Set6 unbalanced datasets, and the AUC values are 0.9929, 0.9975 and 0.9971, respectively. Additionally, we have created three independent test (IT) datasets which the AUC values are 0.8529, 0.6215 and 0.6001, respectively. The results demonstrate that the proposed technique UbiSite-DeepWET outperforms conventional ubiquitination prediction methods and offers new guidance for the identification of ubiquitination sites.

关键词： Protein engineering Additives Predictive models Amino acids Feature extraction Physiology Robustness Protein sequence Convolutional neural networks Bioinformatics

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Delay-optimized Topology Management of a Wirelessly Networked Disaster Area

Delay-optimized Topology Management of a Wirelessly Networke...

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IEEE International Symposium on Embedded Multicore Socs (MCSoC)

作者： Michael Conrad Meyer Yu Wang Department of Computer Science and Electrical Engineering Eastern Washington University Spokane WA USA Software Research and Development Division TriOrb Inc Kitakyushu Japan

Major disasters can often destroy communication networks. To address this issue, companies such as NTT have developed movable base stations (MBSs), which can be easily deployed to construct an emergency communication network. A sample of how MBSs can be connected to form a network can be seen in Fig. 1. However, these networks have performance drawbacks. In order to improve their performance, we propose an algorithm that determines the best way for the MBSs to be connected. The proposed model and algorithm resulted in a reduction in the overall delay and average delay of the system compared to the greedy algorithm. For the realistic constraints, the genetic algorithm (GA) was so successful that its worst-case delay almost matched the average delay of the greedy algorithm. The simulations did show that for extremely high communication rates or extremely slow processing rates, the impact of the topology on the system delay was minimal, and thus both algorithms had similar results. This is because the system bottleneck in these cases is the processing times. However, for the realistic network constraints, the GA outperforms the greedy algorithm by approximately 40% in the fog system and 90% in the cloud system.

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Machine Learning Algorithms for Intrusion Detection Performance Evaluation and Comparative Analysis

Machine Learning Algorithms for Intrusion Detection Performa...

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Smart Electronics and Communication (ICOSEC), International Conference on

作者： B. Md. Irfan V. Poornima S Mohana Kumar Upendra Singh Aswal N. Krishnamoorthy Ramya Maranan Department of Information Technology Nalsar University of Law Hyderabad Telengana India Department of Computer Science VISTASPallavaram Chennai Department of Computer Science and Engineering Ramaiah Institute of Technology Bengaluru Karnataka India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India Department of Software Systems and Engineering Vellore Institute of Technology Vellore Campus Vellore Tamilnadu Department of Research and Innovation Saveetha School of Engineering SIMATS Chennai Tamil Nadu India

The security of computer networks is increasingly difficult to maintain due to the rising complexity and frequency of cyber-attacks. Important tools for finding and neutralizing these dangers are intrusion detection systems. This study sets out to do a thorough examination and comparison of the efficacy of several machine learning algorithms for use in intrusion detection. This research study evaluates the efficacy of several machine learning algorithms in correctly categorizing instances of network traffic as normal or invasive via extensive experiments performed on representative datasets. Algorithms like random forests, decision trees, SVMs, DL models and NNs are all being tested and rated. Effectiveness is measured and compared using a variety of performance indicators including accuracy, recall, precision, false positive rate, and F1-score. The results of this study emphasize the potential of deep learning models and Random Forests for use in intrusion detection and add to the body of knowledge around machine learning methods for this task. Professionals in the field of network security might use the results to their advantage when building intrusion detection systems. Future research areas are also mentioned, which will hopefully lead to even greater improvements in the field and safer, more reliable intrusion detection systems.

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An Advanced Full Stack Decentralized Approach for Secure Election Voting Process

An Advanced Full Stack Decentralized Approach for Secure Ele...

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International Conference on Innovative Sustainable Computational Technologies (CISCT)

作者： Neelam Singh Prashant Rohila Kashif Anwar Tanweer Alam Vandana Rawat Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun India Department of Computer Application Graphic Era Deemed to be University Dehradun India Department of Computer Science Islamic University of Madinah Saudi Arabia

ISBN: (纸本)9781665474177

Designing a safe electronic voting system offering secrecy with impartial approach while being transparent and flexible is a challenging task. Full Stack decentralized applications are smart contract decentralized application that runs on a Decentralized Blockhain Network. Problems constructing a vote casting software at the Central Web Server are: the votes at the database will be modified and will be counted extra or eliminated entirely, also the supply code at the net server can also be modified at any time. Rather than having a separate central server database we can deploy Blockchain. Blockchain is a network and database which handles all the transaction. Blocks on the network are added if the transaction is valid and the Blocks also ensure that the data distributed across the Blockchain network are valid. In this paper, we will elaborate the design and development of a Decentralized Approach for Election Voting System using Solidity language to make our smart contract. This Decentralized Approach will have the option for the voter to cast a vote in an election by their Ethereum account address which has public and private key address. This approach aims to provide a secure and trusted voting transaction.

关键词： Costs Voting Smart contracts Full stack Decentralized applications Real-time systems Web servers

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Optimizing Drug Dosage and Medication Management for Geriatric Patients with Artificial Neural Networks

Optimizing Drug Dosage and Medication Management for Geriatr...

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International Conference on ICT in Business Industry & Government (ICTBIG)

作者： Beemkumar N Daljeet Pal Singh Zahid Ahmed Department of Mechanical Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bagalore Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science & Application Vivekananda Global University Jaipur India

In this paper, we utilize ANNs to investigate how medicine dosing and management might be improved for the elderly population. The suggested strategy calls for the use of patient-specific data as inputs for the ANNs, such as age, renal and hepatic function, body mass index, and preexisting prescription profiles. The neural network model dynamically changes drug doses using the combination of the Multilayer Perceptron (MLP) algorithm, Backpropagation, and the Stochastic Gradient Descent (SGD) algorithm to maximize therapeutic benefits and reduce the likelihood of adverse drug events. The research highlights the improved accuracy, sensitivity, specificity, precision, and F1 score of the suggested technique compared to numerous conventional methods. As a result, the suggested system has great potential to revolutionize medication management for the elderly population since it is more personalized, flexible, patient-safe, effective, and efficient in its use of resources.

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Evaluating the Impact of Pair Documentation on Requirements Quality and Team Productivity

arXiv

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arXiv 2023年

作者： Qamar, Nosheen Sabahat, Nosheen Mashmool, Amir Mosavi, Amir Department of Software Engineering University of Management and Technology Lahore54000 Pakistan Department of Computer Science Forman Christian College University Lahore54000 Pakistan Department of Computer Science Bioengineering Robotics and System Engineering University of Genova Genova16126 Italy Obuda University Budapest1034 Hungary

The most important deliverable of the requirements engineering process is the software/system requirements specification (SRS) document. Requirements documentation is important during the complete software development lifecycle to share the vision and effective communication between major stakeholders. The Standish Group reported that the top factors behind project failures are related to requirements. By giving the right level of attention to key requirements good quality software can be produced. Therefore, more research is needed in this area and this study is trying to fill this gap. This empirical study aims to examine the importance of pair documentation. Unconventional documentation refers to the approach when two persons work on the same document’s requirements collaboratively just like pair programming on the requirements quality and team productivity. Twenty pairs of documentation writers worked into two groups – one group using pair documentation, i.e., the experimental group, and the other one using conventional documentation i.e., the control group. The resultant requirements’ documents for the same project, produced by both groups were then compared. It is observed that there is a significant improvement in the quality and productivity of the experimental group using pair documentation. The findings of this study may assist requirement engineers in forming efficient teams that can create high-quality SRS documents. Copyright © 2023, The Authors. All rights reserved.

关键词： Requirements engineering

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Implementation and Visualization of Path Finding Algorithms

Implementation and Visualization of Path Finding Algorithms

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International Conference on Inventive Research in Computing applications (ICIRCA)

作者： Chandradeep Bhatt Ritabh Sharma Rahul Chauhan Ashish Vishvakarma Mahesh Manchanda Sanjay Sharma CSE Department Graphic Era Hill University Dehradun India Computer Science and Engineering Graphic Era Hill University Dehradun India Department of Information technology Institute of Technology & Management Uttarakhand India Computer Application Department SGRRITS Dehradun India

Learning computer science is tough for many students, especially the ones who don't have any knowledge about it previously. Just like other subjects, there are a lot of things that needs to be learned in computer science. It is often to seen that students find it difficult to cope up with the extreme change in their learning environment. There are many reasons why students struggle in this field. ‘Algorithms’ is one such topic that students find the most confusing. Lecturers on the other hand, also face problems in describing the algorithms to students. Based on several researches, Algorithm Visualization has been to have a positive impact on learning abilities of student. It is already known that a person can learn much more efficiently if it sees what is going on and how is it done. Pathfinding refers to the exploration of an optimal and shortest route, commencing from a designated initial point and concluding at a specified destination. Within the realm of artificial intelligence, pathfinding algorithms are specifically crafted to navigate through graph structures. These algorithms find utility in diverse domains like navigation systems, computer gaming, network architectures, and beyond. Their performance can be degraded by numerous factors such as the length of the path, size of the problem, obstacles and its distribution, data structures used and much more. Whenever a new path-finding algorithm is suggested, its performance is often investigated on the basis of the observations made when that algorithm is used. Proper design and analysis play an important role in giving an explanatory and precise evaluation. By conducting analysis of multiple research works, this study systematically categorized them based on their provisional designs, methodologies, and logical approaches. Throughout this process, this work discovered minor imperfections in these algorithms, which were frequently observed as well.

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