2023 International Conference for Advancement in Technology (ICONAT)最新文献_第3页

Object Tracking Based on Background Subtraction and Kalman Filtering 基于背景减法和卡尔曼滤波的目标跟踪

2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080170

Debabrata Roy, Mohammad Hossam-E-Haider

引用次数: 0

Real-Time Retrieving Vedic Sanskrit Text into Multi-Lingual Text and Audio for Cultural Tourism Motivation 为文化旅游动机实时检索吠陀梵文文本为多语言文本和音频

2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080862

Anchal Chand, Piyush Agarwal, Sachin Sharma

{"title":"Real-Time Retrieving Vedic Sanskrit Text into Multi-Lingual Text and Audio for Cultural Tourism Motivation","authors":"Anchal Chand, Piyush Agarwal, Sachin Sharma","doi":"10.1109/ICONAT57137.2023.10080862","DOIUrl":"https://doi.org/10.1109/ICONAT57137.2023.10080862","url":null,"abstract":"There are many uses for handwritten writing that has been digitally transformed. helping both those working in the field of education and visitors better understand the local culture. The Vedas are the best informational source for understanding Indian culture; the only drawback is that it exists in physical form. The ability to access cultural knowledge and historic heritage is facilitated by the real-time retrieval and translation of Vedic Sanskrit text. The tourist will benefit from this in understanding Indian culture and traditions and its significance. The manual Sanskrit text is translated into an easily editable format using the suggested methods in this study. The language translation and the audio generation in a specific selected language are the features of the methodology used. The proposed method has a four-step process i) image processing, ii) text extraction, iii) text-to-speech conversion, and iv) multi language translation. The OTSUs threshold method is employed in the suggested method to differentiate between the image’s foreground and background. Tesseract OCR is used for image processing. The LSTM is utilised in the real-time text extraction process. The outcome demonstrates that the suggested technique was effective in rendering the Sanskrit text into a variety of languages for the purpose of promoting cultural tourism.","PeriodicalId":250587,"journal":{"name":"2023 International Conference for Advancement in Technology (ICONAT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121782390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Resolving Attached USBs: Analysis of Windows 11 Artifacts 解析附加usb: Windows 11工件分析

2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080101

Akash Budhrani, Upasna Singh, Bhupendra Singh

引用次数: 0

Layered Division Multiplexing in 5G NR 5G NR中的分层分复用

2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080542

Jayaram Shanbhag, S. Malarvizhi, S. Krithiga, Supragya Vikram Singh, Ritisha Pushilal, Suvodeep Saibal Sinha, Satyaki Mukherjee

引用次数: 0

Deep Learning based Target detection and Recognition using YOLO V5 algorithms from UAVs surveillance feeds 基于深度学习的目标检测和识别，使用来自无人机监视馈送的YOLO V5算法

2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080677

Sushil Kumar, Crs Kumar

引用次数: 2

Comparative Analysis of ST, ECRL and Static Logic Style at Different Process Technologies ST、ECRL和静态逻辑风格在不同工艺条件下的比较分析

2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080818

Nidhi Arora, Akshay Sanadhya, Abhijit R. Asati

引用次数: 0

Performance Evaluation of FFT through Adaptive Hold Logic (AHL) Booth Multiplier 基于自适应保持逻辑(AHL)展台乘法器的FFT性能评估

2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080290

Banisetti Venkata Mahesh, Talla Srivasarao

{"title":"Performance Evaluation of FFT through Adaptive Hold Logic (AHL) Booth Multiplier","authors":"Banisetti Venkata Mahesh, Talla Srivasarao","doi":"10.1109/ICONAT57137.2023.10080290","DOIUrl":"https://doi.org/10.1109/ICONAT57137.2023.10080290","url":null,"abstract":"Multiplication is such a key operator in any kind of signal processing modules. Processor’s performance is potential, if the processing elements like multipliers or adders are efficient. One of the stringent multiplier is through Booth’s multiplication algorithm which takes 2’s complement notation of two signed binary numbers. It reduces the number of steps while doing addition when compared with normal multiplication. About radix-8 Booth multipliers’ fundamental design, this is tested on ASIC-based platforms. FPGA-based hardware accelerators cannot give the required performance gain. This can be achieved by using FPGAs and ASICs. For approximation 6-input Look Up Table (LUT) and carry chains of the FPGAs are used. In the existing method, it is possible to have data with 40% of error probability reduction and is not acceptable in logic design for signal processing or for data communications. To overcome this error in end product, instead of Booth multiplier, AHL (Adaptive Hold Logic) Booth multiplier is recommended. With the AHL booth multiplier, the error Probability is expected to reduce to a great extent. Means that100% of accurate data reception is possible at the output compared to existing approximate Booth multiplier. AHL Booth multiplier improves the operation speed and reduces the delay. To test its impact, FFT will be designed with and without AHL Booth multiplier and is simulated using Xilinx ISE. Area, delay and power dissipation parameters of FFT are compared for an effective logic realization.","PeriodicalId":250587,"journal":{"name":"2023 International Conference for Advancement in Technology (ICONAT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128081489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Performance Evaluation of Automatic Suspicious Activity Detection Method 可疑活动自动检测方法的性能评价

2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080627

S. Gurav, V. Khandare

引用次数: 0

Bankruptcy Prediction Using Machine Learning: A New Technological Approach to Prevent Corporate Bankruptcy Through Well Deployed Streamlit Based Application 利用机器学习进行破产预测:一种通过部署良好的基于流光的应用程序来防止企业破产的新技术方法

2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080089

Manisha More, Rajasmita Panda, B. Bandgar, Mayuri More

{"title":"Bankruptcy Prediction Using Machine Learning: A New Technological Approach to Prevent Corporate Bankruptcy Through Well Deployed Streamlit Based Application","authors":"Manisha More, Rajasmita Panda, B. Bandgar, Mayuri More","doi":"10.1109/ICONAT57137.2023.10080089","DOIUrl":"https://doi.org/10.1109/ICONAT57137.2023.10080089","url":null,"abstract":"Corporate bankruptcy prevention and prediction is the most significant problem in the finance domain. The successful machine learning based predictive model allows the corporate stakeholders to check the status of their business. It claims that the person or the organization is the debtor. The proposed research study focused on building a machine learning model to predict the bankruptcy and deploy ML model by using Streamlit, the open-source Python library. The ML framework helps to accept all the values of independent parameters and predict the corporate bankruptcy which leads to early actions to avoid economic losses. Bankruptcy prediction is a classification problem (Bankrupt / Non-Bankrupt). Since the variable to predict is binary. The predictive models are built by applying several machine learning algorithms such as SVM, KNN, Naive Bayes and CART. We find that SVM model with Polynomial Kernel which achieves a high degree of accuracy in all applied ML models. The SVM model with 96.00% model accuracy and 4% error rate is selected for prediction purposes. The SVM model then deployed with the help of Streamlit library to check bankruptcy classification. This application helps stakeholders to prevent their business from bankruptcy by checking through it in early stages. User has to just input the values and our model immediately displays the prediction of bankruptcy either bankrupt(0) or non-bankrupt (1).","PeriodicalId":250587,"journal":{"name":"2023 International Conference for Advancement in Technology (ICONAT)","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127968560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

State of Charge Estimation of Lithium-ion Batteries for Electric Vehicle. 电动汽车用锂离子电池的充电状态估计。

2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080458

Manavi M Naik, Shweta Koraddi, A. B. Raju

引用次数: 1