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A Novel Eccentric Intrusion Detection Model Based on Recurrent Neural Networks with Leveraging LSTM

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Computers, Materials & Continua 2024年第3期78卷 3089-3127页

作者： Navaneetha krishnan Muthunambu Senthil Prabakaran Balasubramanian Prabhu kavin kishore Senthil Siruvangur kavitha Chinnadurai Jehad Ali Department of Computer Applications Karpagam College of EngineeringCoimbatore641032India Department of Computer Science and Engineering Karpagam College of EngineeringCoimbatore641032India Department of Data Science and Business Systems College of Engineering and TechnologySRM Institute of Science and TechnologyKattankulathur603203India Department of Computer Science and Engineering Sathyabama Institute of Science and TechnologyJeppiaar NagarRajiv Gandhi SalaiChennai600119India Department of AI Convergence Network Ajou UniversitySuwon16499Korea

The extensive utilization of the Internet in everyday life can be attributed to the substantial accessibility of online services and the growing significance of the data transmitted via the ***,this development has expanded the potential targets that hackers might *** adequate safeguards,data transmitted on the internet is significantly more susceptible to unauthorized access,theft,or *** identification of unauthorised access attempts is a critical component of cybersecurity as it aids in the detection and prevention of malicious *** research paper introduces a novel intrusion detection framework that utilizes Recurrent Neural Networks(RNN)integrated with Long Short-Term Memory(LSTM)*** proposed model can identify various types of cyberattacks,including conventional and distinctive *** networks,a specific kind of feedforward neural networks,possess an intrinsic memory *** Neural Networks(RNNs)incorporating Long Short-Term Memory(LSTM)mechanisms have demonstrated greater capabilities in retaining and utilizing data dependencies over extended *** such as data types,training duration,accuracy,number of false positives,and number of false negatives are among the parameters employed to assess the effectiveness of these models in identifying both common and unusual *** are utilised in conjunction with LSTM to support human analysts in identifying possible intrusion events,hence enhancing their decision-making capabilities.A potential solution to address the limitations of Shallow learning is the introduction of the Eccentric Intrusion Detection *** model utilises Recurrent Neural Networks,specifically exploiting LSTM *** proposed model achieves detection accuracy(99.5%),generalisation(99%),and false-positive rate(0.72%),the parameters findings reveal that it is superior to state-of-the-art techniques.

关键词： Cybersecurity intrusion detection machine learning leveraging long short-term memory(LLSTM) CICIDS2019 dataset innovative cyberattacks

Optimizing Enterprise Conversational AI: Accelerating Response Accuracy with Custom Dataset Fine-Tuning

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Intelligent Information Management 2024年第2期16卷 65-76页

作者： Yash kishore Independent Researcher Austin USA

As the realm of enterprise-level conversational AI continues to evolve, it becomes evident that while generalized Large Language Models (LLMs) like GPT-3.5 bring remarkable capabilities, they also bring forth formidable challenges. These models, honed on vast and diverse datasets, have undoubtedly pushed the boundaries of natural language understanding and generation. However, they often stumble when faced with the intricate demands of nuanced enterprise applications. This research advocates for a strategic paradigm shift, urging enterprises to embrace a fine-tuning approach as a means to optimize conversational AI. While generalized LLMs are linguistic marvels, their inability to cater to the specific needs of businesses across various industries poses a critical challenge. This strategic shift involves empowering enterprises to seamlessly integrate their own datasets into LLMs, a process that extends beyond linguistic enhancement. The core concept of this approach centers on customization, enabling businesses to fine-tune the AI’s functionality to fit precisely within their unique business landscapes. By immersing the LLM in industry-specific documents, customer interaction records, internal reports, and regulatory guidelines, the AI transcends its generic capabilities to become a sophisticated conversational partner aligned with the intricacies of the enterprise’s domain. The transformative potential of this fine-tuning approach cannot be overstated. It enables a transition from a universal AI solution to a highly customizable tool. The AI evolves from being a linguistic powerhouse to a contextually aware, industry-savvy assistant. As a result, it not only responds with linguistic accuracy but also with depth, relevance, and resonance, significantly elevating user experiences and operational efficiency. In the subsequent sections, this paper delves into the intricacies of fine-tuning, exploring the multifaceted challenges and abundant opportunities it presents. I

关键词： Fine-Tuning Dataset AI Conversational Enterprise LLM

Fast-to-Clinic, Fast-to-Market in Biotech Innovation: Optimizing Chemistry Manufacturing & Controls (CMC) Excellence for Clinical and Commercial Success

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Advances in Chemical Engineering and Science 2024年第3期14卷 155-171页

作者： kishore kumar Hotha Veranova Devens MA USA

In the emerging world of biotech innovation, the fast-to-clinic/market strategy has emerged as a critical “mantra” for biotech, investors, and CDMOs. This approach addresses the escalating costs and complexities of research and development by streamlining the path from concept to clinical trials and, ultimately, to market. The article delves into the intricacies of implementing a fast-to-clinic/market strategy, underlining the empowering role of strategic decision-making in preclinical and commercial stages. The plan advocates for a phase-appropriate approach, where the development decision is tailored to each phase of the product’s lifecycle. This ensures that resources are allocated efficiently, risks are managed effectively, and the product can move through the development pipeline accelerated without compromising quality or regulatory compliance. The article also discusses the role of CDMOs in facilitating rapid product development and the essential factors biotech companies must consider when selecting a partner for outsourcing. These factors include the CDMO’s expertise in navigating regulatory landscapes, technological capabilities, and ability to scale processes efficiently. Moreover, the article stresses the importance of agility and flexibility in the fast-to-clinic/market approach. Biotech companies are encouraged to adopt adaptable strategies that respond to the fast-evolving regulatory and market landscapes.

关键词： Fast to Clinic Innovation CDMO CMC Preclinical FDA IND NDA ANDA Biotech

Aldo-keto reductases:Role in cancer development and theranostics

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Oncology Research 2024年第8期32卷 1287-1308页

作者： SIDDAVARAM NAGINI PRATHAP REDDY kALLAMADI kRANTHI kIRAN kishore TANAGALA GEEREDDY BHANUPRAkASH REDDY World Neem Organization Mumbai400101India Department of Biochemistry ICMR-National Institute of NutritionHyderabad500007India Department of Pathology and Cell Biology Columbia University Irving Medical CenterNew York10032USA

Aldo-keto reductases(AkRs)are a superfamily of enzymes that play crucial roles in various cellular processes,including the metabolism of xenobiotics,steroids,and carbohydrates.A growing body of evidence has unveiled the involvement of AkRs in the development and progression of various *** are aberrantly expressed in a wide range of malignant *** expression of AkRs enables the acquisition of hallmark traits of cancer by activating oncogenic signaling pathways and contributing to *** have emerged as promising oncotherapeutic targets given their pivotal role in cancer development and *** of aldose reductase(AR),either alone or in combination with chemotherapeutic drugs,has evolved as a pragmatic therapeutic option for *** classes of synthetic aldo-keto reductase(AkR)inhibitors have been developed as potential anticancer agents,some of which have shown promise in clinical *** AkR inhibitors from natural sources also exhibit anticancer *** molecule inhibitors targeting speciﬁc AkR isoforms have shown promise in preclinical *** inhibitors disrupt the activation of oncogenic signaling by modulating transcription factors and kinases and sensitizing cancer cells to *** this review,we discuss the physiological functions of human AkRs,the aberrant expression of AkRs in malignancies,the involvement of AkRs in the acquisition of cancer hallmarks,and the role of AkRs in oncogenic signaling,and drug ***,the potential of aldose reductase inhibitors(ARIs)as anticancer drugs is summarized.

关键词： Aldo-keto reductases(AkRs) Aldo-keto reductase(AkR)inhibitors Cancer Drug-resistance Xenobiotics

FPGA Implementation of 5G NR Primary and Secondary Synchronization

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Computers, Materials & Continua 2022年第10期73卷 1585-1600页

作者： Aytha Ramesh kumar k.Lal kishore Department of ECE VNR Vignana Jyothi Institute of Engineering&TechnologyHyderabad500090India JNTUA Former Vice ChancellorIndia

The 5G communication systems are widely established for highspeed data processing to meet users *** 5G New Radio(NR)communications comprise a network of ultra-low latency,high processing speeds,high throughput and rapid synchronization with a time frame of 10 *** between User Equipment(UE)and 5G base station known as gNB is a fundamental procedure in a cellular system and it is performed by a synchronization *** 5G NR system,Primary Synchronization Signal(PSS)and Secondary Synchronization Signal(SSS)are used to detect the best serving base station with the help of a cell search *** paper aims to determine the Physical Cell Identity(PCI)by using primary synchronization and secondary synchronization *** PSS and SSS detection for finding PCI is implemented on Zynq-7000 series Field Programmable Gate Arrays(FPGA)*** are reconfigurable devices and easy to design complex circuits at high *** proposed architecture employs Primary Synchronization Signal(PSS)and Secondary Synchronization Signal(SSS)detection aims with high speed and low power *** synchronization blocks have been designed and the synthesized design block is implemented on the Zynq-7000 series Zed board with a maximum operating clock frequency of 1 GHz.

关键词： 5G new radio FPGA physical cell identity primary and secondary synchronization

Human and Machine Vision Based Indian Race Classification Using Modified-Convolutional Neural Network

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Computer Systems Science & Engineering 2023年第3期44卷 2603-2618页

作者： Vani A.Hiremani kishore kumar Senapati Department of Computer Science&Engineering Birla Institute of TechnologyMesraRanchi835215JharkhandIndia

The inter-class face classification problem is more reasonable than the intra-class classification *** address this issue,we have carried out empirical research on classifying Indian people to their geographical *** work aimed to construct a computational classification model for classifying Indian regional face images acquired from south and east regions of India,referring to human *** have created an Automated Human Intelligence System(AHIS)to evaluate human visual *** of AHIS response showed that face shape is a discriminative feature among the other facial *** have developed a modified convolutional neural network to characterize the human vision response to improve face classification *** proposed model achieved mean F1 and Matthew Correlation Coefficient(MCC)of 0.92 and 0.84,respectively,on the validation set,outperforming the traditional Convolutional Neural Network(CNN).The CNN-Contoured Face(CNN-FC)model is developed to train contoured face images to investigate the influence of face ***,to cross-validate the accuracy of these models,the traditional CNN model is trained on the same *** an accuracy of 92.98%,the Modified-CNN(M-CNN)model has demonstrated that the proposed method could facilitate the tangible impact in intra-classification problems.A novel Indian regional face dataset is created for supporting this supervised classification work,and it will be available to the research community.

关键词： Data collection and preparation human vision analysis machine vision canny edge approximation method color local binary patterns convolutional neural network

A new protection scheme for PV-wind based DC-ring microgrid by using modified multifractal detrended fluctuation analysis

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Protection and Control of Modern Power Systems 2022年第1期7卷 100-123页

作者： kanche Anjaiah Pradipta kishore Dash Mrutyunjaya Sahani Department of Electrical Engineering Siksha‘O’Anusandhan Deemed to be UniversityBhubaneswarOdishaIndia Multidisciplinary Research Cell Siksha‘O’Anusandhan Deemed to be UniversityBhubaneswarOdishaIndia Department of Electrical and Electronics Engineering Siksha‘O’Anusandhan Deemed to be UniversityBhubaneswarOdishaIndia

This paper presents fault detection,classification,and location for a PV-Wind-based DC ring microgrid in the MATLAB/SIMULINk ***,DC fault signals are collected from local measurements to examine the outcomes of the proposed *** detection is carried out for all faults,(i.e.,cable and arc faults)under two cases of fault resistance and distance variation,with the assistance of primary and secondary detection techniques,***-order differential current derivatived2I3 dt2and sliding mode window-based Pearson’s correlation *** fault classification a novel approach using modified multifractal detrended fluctuation analysis(M-MFDFA)is *** advantage of this method is its ability to estimate the local trends of any order polynomial function with the help of polynomial and trigonometric *** also doesn’t require any signal processing algorithm for decomposition resulting and this results in a reduction of computational *** detected fault signals are directly passed through the M-MFDFA classifier for fault type *** enhance the performance of the proposed classifier,statistical data is obtained from the M-MFDFA feature vectors,and the obtained data is plotted in 2-D and 3-D scatter plots for better *** fault distance estimation is carried out for all types of faults in the DC ring bus microgrid with the assistance of recursive least squares with a forgetting factor(FF-RLS).To verify the performance and superiority of the proposed classifier,it is compared with existing classifiers in terms of features,classification accuracy(CA),and relative computational time(RCT).

关键词： DC ring microgrid Differential current Fault resistance Detection Classification Fault location estimation Multifractal detrended fluctuation analysis

FBG Based High Sensitive Pressure Sensor and Its Low-Cost Interrogation System With Enhanced Resolution

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Photonic Sensors 2015年第4期5卷 321-329页

作者： Vengal Rao PACHAVA Srimannarayana kAMINENI Sai Shankar MADHUVARASU kishore PUTHA venkata Reddy MAMIDI Department of Physics National Institute of Technology Warangal 506004 lndia

A fiber Bragg grating （FBG） pressure sensor with high sensitivity and resolution has been designed and demonstrated. The sensor is configured by firmly fixing the FBG with a metal bellows structure. The sensor works by means of measuring the Bragg wavelength shift of the FBG with respect to pressure change. From the experimental results, the pressure sensitivity of the sensor is found to be 90.6proJpsi, which is approximately 4000 times as that of a bare fiber Bragg grating. A very good linearity of 99.86% is observed between the Bragg wavelength of the FBG and applied pressure. The designed sensor shows good repeatability with a negligible hysteresis error of 4-0.29 psi. A low-cost interrogation system that includes a long period grating （LPG） and a photodiode （PD） accompanied with simple electronic circuitry is demonstrated for the FBG sensor, which enables the sensor to attain high resolution of up to 0.025 psi. Thermal-strain cross sensitivity of the FBG pressure sensor is compensated using a reference FBG temperature sensor. The designed sensor can be used for liquid level, specific gravity, and static/dynamic low pressure measurement applications.

关键词： Fiber Bragg grating metal bellows pressure long period grating

搅拌针形状对Al-Mg-Si合金搅拌摩擦焊过程中材料流动和力学性能的影响（英文）

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Transactions of Nonferrous Metals Society of China 2019年第11期29卷 2281-2289页

作者： krishna kishore MUGADA kumar ADEPU Department of Mechanical Engineering Gayatri Vidya Parishad College of EngineeringMadhuwarada-530041VishakhapatnamIndia Energy System Materials Lab Department of Advanced Materials EngineeringDong-Eui UniversityBusan 614-714Korea Department of Mechanical Engineering National Institute of TechnologyWarangal-506004TelanganaIndia

了解搅拌摩擦焊中搅拌头几何形状对材料流动的影响对工业应用中的高质量焊接产品具有挑战性。讨论在材料流动中起重要作用的搅拌轴肩和搅拌针的最佳设计组合。采用标记插入技术对塑化材料的流动情况进行分析。结果表明,正方形和六边形... 详细信息

了解搅拌摩擦焊中搅拌头几何形状对材料流动的影响对工业应用中的高质量焊接产品具有挑战性。讨论在材料流动中起重要作用的搅拌轴肩和搅拌针的最佳设计组合。采用标记插入技术对塑化材料的流动情况进行分析。结果表明,正方形和六边形的搅拌针滚花设计有利于与焊缝长度/时间相关的恒稳定力。正方形搅拌针(粘连长度最小)的轴肩滚花设计(Tk)S有利于塑化材料均匀混合和分布,在搅拌针底部观察到了铜碎片。采用(Tk)S搅拌头的焊缝具有较高的力学性能,材料的搅拌区强度可达182 MPa,硬度可达HV 78。

关键词：轴肩末端特征多边形搅拌针材料流动轴向力力学性能