Dr. Kushnazarov Farruh

Dr. Kushnazarov Farruh

AI Solution Architect

Posts by Collection

portfolio

Conference IntellektTrans

Published:

Participated as an Organizing Committee member in the Intelligent Rail System Transportation Summit, contributing to the event’s organization and discussions on intelligent rail transportation systems.

Computer Network Optimizing

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Implemented a solution at L-Cube LLC to optimize the performance of their departmental network, enhancing communication efficiency and reliability.

Container Number Recognition

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Developed an intelligent system for reading and identifying ISO 6346 container codes in logistics ports, enhancing access control and efficiency.

Data-Center Network Optimizing

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Created a model for estimating the performance of communication protocols for channels with noise and simulated it using Matlab Communication Toolbox. The simulation results and implemented models on the EMC 2 data center were compared, showing deviations within 11%, confirming the research’s consistency.

Moscow City Smart City Project

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Moscow City Project involves integrating smart systems across five different office building groups with varied requirements. The project includes computer programming for central control and night light adjustment, managing over 800 square meters with 15,000 signals from different controllers.

Speech Accent Detection

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This project aims to classify the accents of English language speakers using audio recordings. By leveraging machine learning models such as FFNN, CNN, and LSTM, the system can accurately identify accents, aiding in language learning and accent improvement.

Tangren Face Recognition System

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Developed a face recognition system for smart building and parking projects in Xiamen city, China, resulting in the successful implementation of numerous projects.

publications

Decoding information flows by Viterbi

Published in ransport: Problems, ideas and perspectives. Science Week, 2013

Access paper here

Recommended citation: Farruh Kushnazarov, "Decoding information flows by Viterbi." ransport: Problems, ideas and perspectives. Science Week, 2013. https://biblioserver.usurt.ru/cgi-bin/irbis64r_13/cgiirbis_64.exe?LNG=&C21COM=S&I21DBN=TFZHT&P21DBN=TFZHT&S21FMT=fullwebr&S21ALL=%3C.%3EK%3D%D0%B4%D0%B5%D0%BA%D0%BE%D0%B4%D0%B8%D1%80%D0%BE%D0%B2%D0%B0%D0%BD%D0%B8%D0%B5%3C.%3E&FT_REQUEST=&FT_PREFIX=&Z21ID=&S21STN=1&S21REF=5&S21CNR=10

ЭФФЕКТИВНОСТЬ ЦИКЛИЧЕСКИХ КОДОВ ПРИ ПЕРЕДАЧЕ ДАННЫХ В КАНАЛАХ СВЯЗИ С ПОМЕХАМИ

Published in Сборник трудов VII научно-практической конференции молодых ученых, 2015

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Recommended citation: Фаррух Кушназаров, Одилджан Турдиев, Фирдавс Кушназаров, "ЭФФЕКТИВНОСТЬ ЦИКЛИЧЕСКИХ КОДОВ ПРИ ПЕРЕДАЧЕ ДАННЫХ В КАНАЛАХ СВЯЗИ С ПОМЕХАМИ." Сборник трудов VII научно-практической конференции молодых ученых, 2015. mr.ifmo.ru/files/Sborniki/sbornik_2016.pdf

Analysis of interference in the communication channels to the real speed of data transmission

Published in Transport: Problems, ideas and perspectives. Science Week - 2015, 2015

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Recommended citation: Farruh Kushnazarov, "Analysis of interference in the communication channels to the real speed of data transmission." Transport: Problems, ideas and perspectives. Science Week - 2015, 2015. https://biblioserver.usurt.ru/cgi-bin/irbis64r_13/cgiirbis_64.exe?LNG=en&C21COM=S&I21DBN=TFZHT&P21DBN=TFZHT&S21FMT=infow_wh&S21ALL=&Z21ID=&S21SRW=&S21SRD=&S21STN=1&S21REF=1131010&S21CNR=20&FT_REQUEST=%D0%90%D0%BD%D0%B0%D0%BB%D0%B8%D0%B7%20%D0%B2%D0%BB%D0%B8%D1%8F%D0%BD%D0%B8%D1%8F%20%D0%BF%D0%BE%D0%BC%D0%B5%D1%85%20%D0%B2%20%D0%BA%D0%B0%D0%BD%D0%B0%D0%BB%D0%B0%D1%85%20%D1%81%D0%B2%D1%8F%D0%B7%D0%B8%20%D0%BD%D0%B0%20%D1%80%D0%B5%D0%B0%D0%BB%D1%8C%D0%BD%D1%83%D1%8E%20%D1%81%D0%BA%D0%BE%D1%80%D0%BE%D1%81%D1%82%D1%8C%20%D0%BF%D0%B5%D1%80%D0%B5%D0%B4%D0%B0%D1%87%D0%B8%20%D0%B4%D0%B0%D0%BD%D0%BD%D1%8B%D1%85%20%D0%BA%D1%83%D1%88%D0%BD%D0%B0%D0%B7%D0%B0%D1%80%D0%BE%D0%B2&FT_PREFIX=K%3D

Throughput of communication protocols for distributed systems transferring a group of frames under noise

Published in 2018 IEEE 3rd International Conference on Cloud Computing and Big Data Analysis (ICCCBDA), 2018

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Recommended citation: Farruh Kushnazarov, "Throughput of communication protocols for distributed systems transferring a group of frames under noise." 2018 IEEE 3rd International Conference on Cloud Computing and Big Data Analysis (ICCCBDA), 2018. https://ieeexplore.ieee.org/document/8386554

Anomaly Detection of Unitary Air Conditioners Based on Isolation Forest Method/基于孤立森林方法的单元式空调器异常检测

Published in Chinese Journal of Refrigeration Technology/制冷技术, 2021

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Recommended citation: Dan ZHAO, Bo FAN, FARRUH Kushnazarov, "Anomaly Detection of Unitary Air Conditioners Based on Isolation Forest Method/基于孤立森林方法的单元式空调器异常检测." Chinese Journal of Refrigeration Technology/制冷技术, 2021. https://scjg.cnki.net/kcms/detail/detail.aspx?filename=ZLJS202103007&dbcode=CJFQ&dbname=CJFD2021&v=

talks

Using the big data and deep learning algorithms for Unmanned Vehicle

Published:

The human brain is a biologically inspired class of algorithms that process the information network of primitive computational elements. Deep learning is a useful technology to build a multilayer neural network architectures and their applications in a broad class of problems. Deep learning is used for speech recognition, image analysis, video analysis, and behavior prediction text processing machine translation. Used static data processing has several disadvantages, like high labor costs, for developing specialized data processing systems. The deep learning achieves low labor costs due to the algorithms’ versatility, the ease of adaptation when you change the structure of the data, more data volume, and reliable data.

Unmanned vehicles with AI

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In particular, the seminar discussed the technical parameters and trends in the production of cars driven without human intervention, the introduction of information and communication technologies in the automotive industry, in the ongoing scientific research and changes in the automotive industry. This event was organized interactively and aroused great interest among students.

Artificial Intelligence/Machine Learning - New Level of Business Intelligence

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Nowadays, we can see the implementation of high-speed machine learning in all areas of society, such as trading, factoring, security, services, and others. We can see different examples of AI/ML’s implementation in journal publications, on TV shows, and on the Internet every day. We will analyze the pitfalls and possible obstacles in the implementation of AI/ML in BL through different examples.

Big Data

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The volume of information is increasing every day. Despite this, Big Data functioning all over the world is only an insignificant part of it. According to IDC forecasts, the volume of information may reach 40 Zettabytes by 2020. From the beginning of 2010 to the present, the amount of data has increased 50-55 times. According to research, 2.8 Zettabytes of information currently exist and are processed. In his talk on Big Data, he will highlight fundamental issues in this area.

The World of Artificial Intelligence

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Speech about what DL and ML are and how to use these technologies in the interests of contemporary life. And also about artificial neural networks based on CNN (Convolutional NN) and RNN (Recurrent NN) technologies, etc.

Involvement of AI to Customer Lifetime Value

Published:

Customer lifetime value is the metric that indicates the total revenue a business can reasonably expect from a single customer account. It considers a customer’s revenue value and compares that number to the company’s predicted customer lifespan. Businesses use this metric to identify significant customer segments that are the most valuable to the company.

teaching

Assistant of Professor September 2014 to July 2015

Workshop, Emperor Alexander I St.Petersburg State Transport University, Information and computing systems, 2014

During the Ph.D. study had amazing experience of assist professor and conduct below subjects:

Associate Professor

Undergraduate course, Tashkent University of Information Technologies, Multimedia technologies, 2020

To conduct laboratory and practical classes for below subjects: