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Model dependent analysis of ■→■ decays in beyond standard model

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Chinese Physics C 2024年第9期48卷 86-99页

作者： s.Mahata M.Mandal H.Mahapatra s.Biswas s.sahoo Department of Physics National Institute of Technology Durgapur

Motivated by the recent experimental results of branching fractions for ■→■ decays,which deviate from their sM predictions,we hve investigated these decays in W' model and scalar leptoquark model to determine potential signatures of new physics(NP) in semileptonic charm decays induced by c→■ *** recent experimental results of branching fractions for semileptonic D meson decays,new coupling parameters are predicted for the aforementioned NP *** fraction,forward-backward asymmetry,and lepton polarization asymmetry are examined by considering the predicted NP coupling *** results of branching fractions in scalar leptoquark model are found very close to the experimental results and exist around the range of 1σ *** presented a comparative study of the NP models to check their sensitivity on these *** anticipate that further research on these decays will significantly support our findings.

关键词： $ W' $ boson charm decay flavour changing charged current new physics scalar leptoquark

Model dependent analysis of D^(+)_(s)→η^(′)l+v_(l) decays in beyond standard model

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Chinese Physics C 2024年第9期48卷 82-95页

作者： s.Mahata M.Mandal H.Mahapatra s.Biswas s.sahoo Department of Physics National Institute of Technology Durgapur Durgapur 713209West BengalIndia

Motivated by the recent experimental results of branching fractions for D^(+)_(s)→η^(′)l+v_(l) decays,which deviate from their sM predictions,we hve investigated these decays in W' model and scalar leptoquark model to determine potential signatures of new physics(NP) in semileptonic charm decays induced by c→(s,d)l+v_(l) *** recent experimental results of branching fractions for semileptonic D meson decays,new coupling parameters are predicted for the aforementioned NP *** fraction,forward-backward asymmetry,and lepton polarization asymmetry are examined by considering the predicted NP coupling *** results of branching fractions in scalar leptoquark model are found very close to the experimental results and exist around the range of 1σ *** presented a comparative study of the NP models to check their sensitivity on these *** anticipate that further research on these decays will significantly support our findings.

关键词： charm decay new physics W′boson scalar leptoquark flavour changing charged current

Rotating effects on the photoionization cross-section of a 2D quantum ring

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Communications in Theoretical Physics 2024年第10期76卷 153-159页

作者： Carlos Magno O Pereira Frankbelson dos s Azevedo Luís Fernando C Pereira Edilberto O silva Departamento de Física Universidade Federal do Maranh?o

In this article, we investigate the nonrelativistic quantum motion of a charged particle within a rotating frame, taking into account the Aharonov–Bohm(AB) effect and a uniform magnetic field. Our analysis entails the derivation of the equation of motion and the corresponding radial equation to describe the system. solving the resulting radial equation enables us to determine the eigenvalues and eigenfunctions, providing a clear expression for the energy levels. Furthermore,our numerical analysis highlights the substantial influence of rotation on both energy levels and optical properties. specifically, we evaluate the photoionization cross-section with and without the effects of rotation. To elucidate the impact of rotation on the photoionization process of the system, we present graphics that offer an appealing visualization of the intrinsic nature of the physics involved.

关键词： Aharonov-Bohm effect photoionization cross-section quantum ring rotating effect

Leveraging User-Generated Comments and Fused BiLsTM Models to Detect and Predict Issues with Mobile Apps

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Computers, Materials & Continua 2024年第4期79卷 735-759页

作者： Wael M.s.Yafooz Abdullah Alsaeedi Department of Computer science College of Computer Science and EngineeringTaibah UniversityMedina42353Saudi Arabia

In the last decade, technical advancements and faster Internet speeds have also led to an increasing number ofmobile devices and users. Thus, all contributors to society, whether young or old members, can use these mobileapps. The use of these apps eases our daily lives, and all customers who need any type of service can accessit easily, comfortably, and efficiently through mobile apps. Particularly, saudi Arabia greatly depends on digitalservices to assist people and visitors. such mobile devices are used in organizing daily work schedules and services,particularly during two large occasions, Umrah and Hajj. However, pilgrims encounter mobile app issues such asslowness, conflict, unreliability, or user-unfriendliness. Pilgrims comment on these issues on mobile app platformsthrough reviews of their experiences with these digital services. scholars have made several attempts to solve suchmobile issues by reporting bugs or non-functional requirements by utilizing user ***, solving suchissues is a great challenge, and the issues still exist. Therefore, this study aims to propose a hybrid deep learningmodel to classify and predict mobile app software issues encountered by millions of pilgrims during the Hajj andUmrah periods from the user perspective. Firstly, a dataset was constructed using user-generated comments fromrelevant mobile apps using natural language processing methods, including information extraction, the annotationprocess, and pre-processing steps, considering a multi-class classification problem. Then, several experimentswere conducted using common machine learning classifiers, Artificial Neural Networks (ANN), Long short-TermMemory (LsTM), and Convolutional Neural Network Long short-Term Memory (CNN-LsTM) architectures, toexamine the performance of the proposed model. Results show 96% in F1-score and accuracy, and the proposedmodel outperformed the mentioned models.

关键词： Mobile apps issues play store user comments deep learning LsTM bidirectional LsTM

Internet of Things Enabled DDos Attack Detection Using Pigeon Inspired Optimization Algorithm with Deep Learning Approach

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Computers, Materials & Continua 2024年第9期80卷 4047-4064页

作者： Turki Ali Alghamdi saud s.Alotaibi Department of Computer science and Artificial Intelligence College of ComputingUmm Al-Qura UniversityMakkah21955Saudi Arabia

Internet of Things(IoTs)provides better solutions in various fields,namely healthcare,smart transportation,home,*** Denial of service(Dos)outbreaks in IoT platforms is significant in certifying the accessibility and integrity of IoT *** learning(DL)models outperform in detecting complex,non-linear relationships,allowing them to effectually severe slight deviations fromnormal IoT activities that may designate a Dos *** uninterrupted observation and real-time detection actions of DL participate in accurate and rapid detection,permitting proactive reduction events to be executed,hence securing the IoT network’s safety and ***,this study presents pigeon-inspired optimization with a DL-based attack detection and classification(PIODL-ADC)approach in an IoT *** PIODL-ADC approach implements a hyperparameter-tuned DL method for Distributed Denial-of-service(DDos)attack detection in an IoT ***,the PIODL-ADC model utilizes Z-score normalization to scale input data into a *** handling the convolutional and adaptive behaviors of IoT,the PIODL-ADCmodel employs the pigeon-inspired optimization(PIO)method for feature selection to detect the related features,considerably enhancing the recognition’s ***,the Elman Recurrent Neural Network(ERNN)model is utilized to recognize and classify DDos ***,reptile search algorithm(RsA)based hyperparameter tuning is employed to improve the precision and robustness of the ERNN method.A series of investigational validations is made to ensure the accomplishment of the PIODL-ADC *** experimental outcome exhibited that the PIODL-ADC method shows greater accomplishment when related to existing models,with a maximum accuracy of 99.81%.

关键词： Internet of things denial of service deep learning reptile search algorithm feature selection

Prediction of Bandwidth of Metamaterial Antenna Using Pearson Kernel-Based Techniques

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Computers, Materials & Continua 2024年第3期78卷 3449-3467页

作者： sherly Alphonse s.Abinaya sourabh Paul school of Computer science and Engineering Vellore Institute of TechnologyChennai600127India school of Electronics Engineering Vellore Institute of TechnologyChennai600127India

The use of metamaterial enhances the performance of a specific class of antennas known as metamaterial *** radiation cost and quality factor of the antenna are influenced by the size of the *** antennas allow for the circumvention of the bandwidth restriction for small *** parameters have recently been predicted using machine learning algorithms in existing *** learning can take the place of the manual process of experimenting to find the ideal simulated antenna *** accuracy of the prediction will be primarily dependent on the model that is *** this paper,a novel method for forecasting the bandwidth of the metamaterial antenna is proposed,based on using the Pearson Kernel as a standard *** with these new approaches,this paper suggests a unique hypersphere-based normalization to normalize the values of the dataset attributes and a dimensionality reduction method based on the Pearson kernel to reduce the dimension.A novel algorithm for optimizing the parameters of Convolutional Neural Network(CNN)based on improved Bat Algorithm-based Optimization with Pearson Mutation(BAO-PM)is also presented in this *** prediction results of the proposed work are better when compared to the existing models in the literature.

关键词： Antenna pearson optimization bandwidth metamaterial

Efficiency-Driven Custom Chatbot Development: Unleashing LangChain, RAG, and Performance-Optimized LLM Fusion

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Computers, Materials & Continua 2024年第8期80卷 2423-2442页

作者： s.Vidivelli Manikandan Ramachandran A.Dharunbalaji school of Computing SASTRA Deemed UniversityThanjavurTamilnadu613401India

This exploration acquaints a momentous methodology with custom chatbot improvement that focuses on pro-ficiency close by *** accomplish this by joining three key innovations:LangChain,Retrieval Augmented Generation(RAG),and enormous language models(LLMs)tweaked with execution proficient strategies like LoRA and *** takes into consideration fastidious fitting of chatbots to explicit purposes,guaranteeing engaged and important collaborations with ***’s web scratching capacities engage these chatbots to get to a tremendous store of data,empowering them to give exhaustive and enlightening reactions to *** recovered data is then decisively woven into reaction age utilizing LLMs that have been calibrated with an emphasis on execution *** combination approach offers a triple advantage:further developed viability,upgraded client experience,and extended admittance to *** become proficient at taking care of client questions precisely and productively,while instructive and logically pertinent reactions make a more regular and drawing in cooperation for *** last,web scratching enables chatbots to address a more extensive assortment of requests by conceding them admittance to a more extensive information *** digging into the complexities of execution proficient LLM calibrating and underlining the basic job of web-scratched information,this examination offers a critical commitment to propelling custom chatbot plan and *** subsequent chatbots feature the monstrous capability of these advancements in making enlightening,easy to understand,and effective conversational specialists,eventually changing the manner in which clients cooperate with chatbots.

关键词： LangChain retrieval augumental generation(RAG) fine tuning

Twinning aspects and their efficient roles in wrought Mg alloys:A comprehensive review

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Journal of Magnesium and Alloys 2024年第6期12卷 2201-2230页

作者： s.s.A.shah Manping Liu Azim Khan Farooq Ahmad M.R.Abdullah Xingquan Zhang shiwei Xu Zhen Peng school of Materials science and Engineering Jiangsu UniversityZhenjiang 212013China school of Mechanical Engineering Anhui University of TechnologyMáanshan 243002China College of Mechanical and Vehicle Engineering Hunan UniversityChangsha 410082China

Twinning is widely recognized as an effective and cost-efficient method for controlling the microstructure and properties of wrought magnesium(Mg)***,twins play a crucial role in initiating dynamic recrystallization(DRX),while twin regions experience rapid recrystallization during static recrystallization(sRX).The activation of twinning can lead to changes in lattice orientation,significantly impacting the final texture in Mg *** active roles of twinning are influenced by various factors during the activation process,and the mobility of twin boundaries(TB)can be amplified by stress effects,dislocation interactions,and thermal ***,annealing treatments that involve proper segregation or precipitation on TBs serve to stabilize them,restraining their *** such as segregation may also alter the twinning propensity in Magnesium-rare earth(Mg-RE)***{10–11}contraction twins(CT)and{10–11}-{10–12}double twins(DT)can promote dynamic recrystallization(DRX),they also pose a risk as potential sources of voids and ***,understanding the nucleation and growth mechanisms of twinning is crucial,and these aspects are briefly reviewed in this *** the factors mentioned above,this article summarizes the recent research progress in this field,shedding light on advancements in recent eras.

关键词： Mg alloys Twinning Recrystallization Texture Mechanical properties

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Enhancing Multicriteria-Based Recommendations by Alleviating scalability and sparsity Issues Using Collaborative Denoising Autoencoder

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Computers, Materials & Continua 2024年第2期78卷 2269-2286页

作者： s.Abinaya K.Uttej Kumar school of Computer science&Engineering Vellore Institute of TechnologyChennaiTamilnadu600127India

A Recommender system(Rs)is a crucial part of several firms,particularly those involved in *** conventional Rs,a user may only offer a single rating for an item-that is insufficient to perceive consumer ***,businesses in industries like e-learning and tourism enable customers to rate a product using a variety of factors to comprehend customers’*** the other hand,the collaborative filtering(CF)algorithm utilizing AutoEncoder(AE)is seen to be effective in identifying user-interested ***,the cost of these computations increases nonlinearly as the number of items and users *** triumph over the issues,a novel expanded stacked autoencoder(EsAE)with Kernel Fuzzy C-Means Clustering(KFCM)technique is proposed with two *** the first phase of offline,the sparse multicriteria rating matrix is smoothened to a complete matrix by predicting the users’intact rating by the EsAE approach and users are clustered using the KFCM *** the next phase of online,the top-N recommendation prediction is made by the EsAE approach involving only the most similar user from multiple *** the EsAE_KFCM model upgrades the prediction accuracy of 98.2%in Top-N recommendation with a minimized recommendation generation *** experimental check on the Yahoo!Movies(YM)movie dataset and TripAdvisor(TA)travel dataset confirmed that the EsAE_KFCM model constantly outperforms conventional Rs algorithms on a variety of assessment measures.

关键词： Recommender systems multicriteria rating collaborative filtering sparsity issue scalability issue stacked-autoencoder Kernel Fuzzy C-Means Clustering