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arXiv 2023年

作者： Yong, Suk Yee Ong, Cheng Soon Australia Astrophysics and Space Technologies Research Centre Macquarie University SydneyNSW2109 Australia School of Mathematical and Physical Sciences Macquarie University SydneyNSW2109 Australia Faculty of Science and Engineering Macquarie University SydneyNSW2109 Australia Machine Learning and Artificial Intelligence Future Science Platform CSIRO Australia Data61 CSIRO CanberraACT2601 Australia School of Computing The Australian National University CanberraACT2601 Australia

Precise measurements of the black hole mass are essential to gain insight on the black hole and host galaxy co-evolution. A direct measure of the black hole mass is often restricted to nearest galaxies and instead, an indirect method using the single-epoch virial black hole mass estimation is used for objects at high redshifts. However, this method is subjected to biases and uncertainties as it is reliant on the scaling relation from a small sample of local active galactic nuclei. In this study, we propose the application of conformalised quantile regression (CQR) to quantify the uncertainties of the black hole predictions in a machine learning setting. We compare CQR with various prediction interval techniques and demonstrated that CQR can provide a more useful prediction interval indicator. In contrast to baseline approaches for prediction interval estimation, we show that the CQR method provides prediction intervals that adjust to the black hole mass and its related properties. That is it yields a tighter constraint on the prediction interval (hence more certain) for a larger black hole mass, and accordingly, bright and broad spectral line width source. Using a combination of neural network model and CQR framework, the recovered virial black hole mass predictions and uncertainties are comparable to those measured from the Sloan Digital Sky Survey. The code is publicly available at https://***/yongsukyee/uncertain_blackholemass. Copyright © 2023, The Authors. All rights reserved.

关键词： Forecasting

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A Logical Network Performance Improvement Design based on 6G Communication Support over WSN Framework

A Logical Network Performance Improvement Design based on 6G...

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Information Technologies and Communications (GCITC), Global Conference on

作者： L Manimegalai M Daniel Nareshkumar T Saravanan S. Rajarajeswari V. Samuthira Pandi Potharaju Yakaiah Department of Electronics and Communication Engineering R.M.K. College of Engineering and Technology Chennai Tamil Nadu India Department of Electronics and Communication Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India Department of Artificial Intelligence and Machine Learning Saveetha Engineering College Tamil Nadu India Department of Science and Humanities Prince Shri Venkateshwara Padmavathy Engineering College Chennai Tamil Nadu India Centre for Advanced Wireless Integrated Technology Chennai Institute of Technology Chennai Tamil Nadu India Department of Electronics and MLR Institute of Technology Hyderabad Telangana India

The development of wireless information and communication technologies known as 5G includes the incorporation of a number of different intelligent applications. Emerging technologies, on the other hand, have criteria that are noticeably less stringent than what the 5G specs specify. The amount of energy used per bit and the pace at which data is sent are also important aspects. Because of improvements to its frequency range, transmission speed, spectrum efficiency, connection capacity, latency, coverage area, and anti-interference power, sixth-generation (5G) wireless technology will be able to fulfill the needs of a wide variety of network configurations. The goal of 6G is to provide global coverage by connecting marine and non-terrestrial systems including communication satellites and unmanned aerial vehicle (UAV) networks for communication. To achieve this goal, terrestrial and extraterrestrial networks will be merged. Second, research into the sub-6 GHz, mm Wave, high-frequency signals in THz with laser frequency ranges will be conducted separately and in concert with one another in an attempt to increase data transmission speeds and connection densities. Thirdly, 6G networks will allow for a new class of smart applications with the help of AI and big data techniques in order to handle the enormous datasets that will be produced by the widespread deployment of these networks, the variety of interaction scenarios that will be possible, the large number of antennas that will be considered the norm, the expansive bandwidths, and the novel service requirements. In order to provide the unique service needs, such applications will be able to handle the enormous datasets produced by the usage of widely distributed networks, a wide variety of contact situations, and a huge number of antennas. In conclusion, the growth of 6G networks calls for increased network security. This article presents a discussion of the issues that have arisen as a direct result of current resea

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Data Reduction Techniques in Wireless Sensor Networks with AI

Data Reduction Techniques in Wireless Sensor Networks with A...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Gagan Deep Arora Navdeep Kumar Chopra N. Gopinath Sathish Kumar Ravichandran M. Kalyan Chakravarthi Durgaprasad Gangodkar Department of Artificial Intelligence (AI) and Machine Learning (ML) Vardhaman College of Engineering Hyderabad India Department of CSE Chandigarh Engineering College Landran Mohali Punjab Department of Computer Science and Engineering Sri Sairam Engineering College Chennai Tamil Nadu India Department of Computer Science and Engineering Christ University Bangalore Karnataka India School of Electronics Engineering VIT-AP University Amravati Andhra Pradesh India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India

Due to their numerous uses in practically every part of life and their related problems, such as energy saving, a longer life cycle, and better resource usage, the research of wireless sensor networks is ongoing. Its extensive use successfully saves and processes a considerable volume of sensor data. Since the sensor nodes are frequently placed in challenging locations where less expensive resources are required for data collection and processing, this presents a new difficulty. One method for minimizing the quantity of sensor data is data reduction. A review of data reduction methods has been provided in this publication. The different data reduction approaches that have been put forth over the years have been examined, along with their advantages and disadvantages, ways in which they can be helpful, and whether or not using them in contexts with limited resources is worthwhile.

关键词： Wireless communication Wireless sensor networks Data collection Internet Data mining Informatics artificial intelligence

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The Frontier of Geospatial AI Deep learning Applications in Data Mining and Spatial Analysis

The Frontier of Geospatial AI Deep Learning Applications in ...

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Intelligent Systems and Advanced Applications (ICISAA), International Conference on

作者： Ajit Kumar Mishra Vikash Verma R. Manivannan N. Krishna Kumar Mudunuru Srividya Sanskriti Sharma Department of Electrical & Electronics Engineering IES College of Technology Bhopal M.P India Dept of Artificial Intelligence & Machine Learning GGITS Jabalpur M.P India School of Computing Computer Science & Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai TN India Dept.of CSE Guru Nanak Institutions Technical Campus Ibrahimpatam Hyderabad Telangana India Dept. of CSE MLR Institute of Technology Hyderabad Telangana India Dept of Computer Science & Business System GGITS Jabalpur M.P India

ISBN: (数字)9798331539948

ISBN: (纸本)9798331539955

Modern artificial intelligence uses geographical data mining and regional analysis to analyze large datasets. Deep learning is a new geographic AI method. Example: Geographic Deep Mining Network (GDMN). The Spatial Feature Extractor (SFE), Temporal Geospatial Attention Mechanism (TGAM), and Geospatial Data Fusion Module (GDFM) comprise this technique. We examined six popular approaches and found GDMN performed best. It worked successfully for several reasons. GDMN always outperforms its competitors in memory, F1 score, IoU, training time, and inference time. This is always true. These findings suggest that GDMN might boost geospatial AI’s data mining and location analysis abilities. After all the effort, we have developed a solid basis for location intelligence, making it useful in various subject areas. Because it’s versatile, mapping specialists may use GDMN for better environmental monitoring or city development. Deep learning helps GDMN make better space choices and uncover insights in large, challenging data sets that no one knew about. GDMN’s cutting-edge approaches make space and time research and prediction simpler. This wide perspective offers a more full and all-encompassing picture of today’s challenges than previous techniques. This makes it impossible to overstate how significant this work is to location intelligence. Its unmatched research and insights usher in a new era.

关键词： Deep learning Training Urban areas Transforms Feature extraction Solids Spatial databases Geospatial analysis Data mining artificial intelligence

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Analysis Of A Zipline Robotic System To Assist Astronauts On Lunar And Martian Terrains 73

Analysis Of A Zipline Robotic System To Assist Astronauts On...

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73rd International Astronautical Congress, IAC 2022

作者： Kadagadakai, Vishnurat Thuluva, Sushmith Kodukula, Ananya Bharadwaj, Vyoma Jain, Alankriti Rao, Bhavana B. Pulicallu, Greeshmanth Rai, Riddhi Shukla, Aayush Mitra, Ruhi Nanditha Prabhu, M. Kamath, Satwik Preetham, M.P. Department of Electronics & Telecommunication Engineering Ramaiah Institute of Technology MSRIT Post M S Ramaiah Nagar MSR Nagar Karnataka Bengaluru560054 India Department of Electrical and Computer Engineering Carnegie Mellon University 5000 Forbes Ave PittsburghPA15213 United States Department of Computer Science & Engineering Ramaiah Institute of Technology MSRIT Post M S Ramaiah Nagar MSR Nagar Karnataka Bengaluru560054 India Department of Mechanical Engineering Ramaiah Institute of Technology MSRIT Post M S Ramaiah Nagar MSR Nagar Karnataka Bengaluru560054 India Department of Artificial Intelligence & Data Science Ramaiah Institute of Technology MSRIT Post M S Ramaiah Nagar MSR Nagar Karnataka Bengaluru560054 India Department of Artificial Intelligence & Machine Learning Ramaiah Institute of Technology MSRIT Post M S Ramaiah Nagar MSR Nagar Karnataka Bengaluru560054 India Department of Information Science & Engineering Ramaiah Institute of Technology MSRIT Post M S Ramaiah Nagar MSR Nagar Karnataka Bengaluru560054 India Department of Electronics & Communication Engineering Ramaiah Institute of Technology MSRIT Post M S Ramaiah Nagar MSR Nagar Karnataka Bengaluru560054 India

In the realm of drones and probes, this paper proposes a subsequent derivative idea of ziplining automated mobile systems to assist astronauts on Lunar and Martian surfaces. Although the conventional human-like robotic systems alleviate many challenges to astronauts on the moon and the mars, one particular challenge of reaching farther on land is left to the technology of drones. Drones however are more efficient in overviewing the area and are less effective in transporting samples or astronauts to the target. This paper discusses an idea of a ziplining robotic system that can reach farther places from the base camp in a secure and safe way. The system comprises multiple support poles, a subsystem of ziplining and a mobility subsystem to traverse the contents from point to point. This paper describes the overall design of the robotic system, its operations and possible advancements for the future scope. The future applications of such an idea involves the support for constructing a settlement for our Martian outposts. The paper explores these domains of applications and the effectiveness of such a mobility system in various situations. The paper investigates the proposed design on Lunar and Martian surfaces but can be optimised for other planetary bodies as well. © 2022 International Astronautical Federation, IAF. All rights reserved.

关键词： Drones

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A Strategic Approach To Tackle Interplanetary Communication Delay: Exploiting artificial intelligence Solutions For Future Space Exploration 73

A Strategic Approach To Tackle Interplanetary Communication ...

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73rd International Astronautical Congress, IAC 2022

作者： Rai, Riddhi Thuluva, Sushmith Kodukula, Ananya Bharadwaj, Vyoma Jain, Alankriti Shadaksharaiah, Anushree Maligehalli Pulicallu, Greeshmanth Kadagadakai, Vishnurat Shukla, Aayush Mitra, Ruhi Nanditha Prabhu, M. Preetham, M.P. Department of Artificial Intelligence & Data Science Ramaiah Institute of Technology MSRIT Post M S Ramaiah Nagar MSR Nagar Karnataka Bengaluru560054 India Department of Electrical and Computer Engineering Carnegie Mellon University 5000 Forbes Ave PittsburghPA15213 United States Department of Computer Science & Engineering Ramaiah Institute of Technology MSRIT Post M S Ramaiah Nagar MSR Nagar Karnataka Bengaluru560054 India Department of Electronics & Telecommunication Engineering Ramaiah Institute of Technology MSRIT Post M S Ramaiah Nagar MSR Nagar Karnataka Bengaluru560054 India Department of Electronics & Instrumentation Engineering Ramaiah Institute of Technology MSRIT Post M S Ramaiah Nagar MSR Nagar Karnataka Bengaluru560054 India Department of Mechanical Engineering Ramaiah Institute of Technology MSRIT Post M S Ramaiah Nagar MSR Nagar Karnataka Bengaluru560054 India Department of Artificial Intelligence & Machine Learning Ramaiah Institute of Technology MSRIT Post M S Ramaiah Nagar MSR Nagar Karnataka Bengaluru560054 India Department of Information Science & Engineering Ramaiah Institute of Technology MSRIT Post M S Ramaiah Nagar MSR Nagar Karnataka Bengaluru560054 India

Despite the extreme measures in any interplanetary mission, a probe is inevitably prone to a handful of unexpected errors. Concerning this, an exceptional challenge in every interplanetary endeavour is the inescapable communication gap (delay) resulting from the various factors. Although the gap is in the range of few minutes to seconds, the actions performed by the probe during critical events creates the necessary to establish a continuous and real time communication with the mission control. Thinking long term on manned missions to Mars and beyond, escalates the concern *** currently tackling such communication issues faced when a satellite communicates with earth is of high *** current paper proposes an alternate strategy to tackle this subject. With recent advancements in the development of artificial intelligence (AI), state-of-the art algorithms,neural networks, and reinforcement based models, it can be so optimized for applications suitable to meet the needs of satellite communication issues. In the light of which, the paper investigates the design of a monitoring satellite. This monitoring satellite is trained with the data and a developed deep learning algorithm/machine learning model is employed by the satellite to make future decisions. Hence using the current knowledge and data we have regarding the communication issues faced while establishing a link with earth, we can train the data models present in the satellite to make the communication with earth more *** the results we gain from this can be later transferred to tackle interplanetary communication *** in the future,we can transfer this knowledge to a a probe that can help tackle interplanetary communication. Copyright © 2022 by the International Astronautical Federation (IAF). All rights reserved.

关键词： Satellites

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Analysing Blockchain-Based Cryptography: Enhancing Security, Transparency, and Practical Implementations

Analysing Blockchain-Based Cryptography: Enhancing Security,...

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Technological engineering and its Applications in Sustainable Development (ICTEASD), International Conference for

作者： Laith H. Jasim Anshoo Mishra Sanjeev Kumar Joshi I. B. Sapaev Primmia D R Suseela D Aadi Nagender Babu The Islamic University Najaf Iraq Department of Computer Science & Engineering IES Insititute of Technology and Management IES University Bhopal Madhya Pradesh India Department of Mechanical Engineering Uttaranchal Institute of Technology Uttaranchal University Dehradun India Tashkent Institute of Irrigation and Agricultural Mechanization Engineers National Research University Tashkent Uzbekistan the Department Physics and Chemistry Western Caspian University Scientific Researcher Baku Azerbaijan CSE Prince Shri Venkateshwara Padmavathy Engineering College Chennai Department of Artificial Intelligence and Machine Learning Bannari Amman Institute of Technology GRIET Hyderabad Telangana India

ISBN: (数字)9798350336474

ISBN: (纸本)9798350336481

This paper explores the many uses of blockchain-based cryptography for building trust, improving transparency, and providing security in a variety of contexts. The article begins with a thorough Introduction that lays the groundwork for a thorough analysis of the cryptographic underpinnings of blockchain technology. In "Cryptographic Foundations," the fundamental components of blockchain security are thoroughly dissected. This includes a detailed examination of Digital Signatures (2.1.2), Cryptographic Keys (2.1.3), Data Encryption (2.1.4), Cryptographic Hashes (2.1.1), and Merkle Trees (2.1.5), explaining their vital functions in guaranteeing the validity and integrity of data on the blockchain. After that, the study goes into great length to analyse symmetric encryption in blockchain (3), highlighting how important it is to protecting the privacy of transaction data. Safe Communication (3.2), Privacy Protection (3.1), Next, Asymmetric Encryption in Blockchain (4) takes front stage, explaining how to improve security and trust in decentralised networks using Public and Private Keys (4.1), Secure Communication (4.2), Digital Signatures (4.3), Access Control (4.4), and Transaction Integrity (4.5). After that, the study delves into the specifics of Local Peer Network Components (5.1), illuminating the design and function of local peers in supporting blockchain transactions. Expanding on this basis, the section Cryptographic Foundations in Blockchain (6) goes over the essential cryptographic components, namely Cryptographic Hashing (6.1), Digital Signatures (6.2), and Cryptographic Keys (6.3), emphasising their critical role in the data integrity and immutability of blockchains. The actions that Internet of Things devices need to take in order to register with the Transaction Processing and Device Registration (7) process are described. A fascinating examination of Blockchain Success Stories (8) completes the article. Three noteworthy case studies are covered: Food Tra

关键词： Access control Data privacy Blockchains Encryption Registers Reliability Internet of Things

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An Innovative Design Of A Reusable Constellation Of CubeSats For Space Debris Removal 73

An Innovative Design Of A Reusable Constellation Of CubeSats...

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73rd International Astronautical Congress, IAC 2022

作者： Shukla, Aayush Thuluva, Sushmith Kodukula, Ananya Bharadwaj, Vyoma Jain, Alankriti Shadaksharaiah, Anushree Maligehalli Pulicallu, Greeshmanth Kadagadakai, Vishnurat Rai, Riddhi Mitra, Ruhi Prabhu, M. Nanditha Department of Artificial Intelligence & Machine Learning Ramaiah Institute of Technology MSRIT Post M S Ramaiah Nagar MSR Nagar Karnataka Bengaluru560054 India Department of Electrical and Computer Engineering Carnegie Mellon University 5000 Forbes Ave PittsburghPA15213 United States Department of Computer Science & Engineering Ramaiah Institute of Technology MSRIT Post M S Ramaiah Nagar MSR Nagar Karnataka Bengaluru560054 India Department of Electronics & Telecommunication Engineering Ramaiah Institute of Technology MSRIT Post M S Ramaiah Nagar MSR Nagar Karnataka Bengaluru560054 India Department of Electronics & Instrumentation Engineering Ramaiah Institute of Technology MSRIT Post M S Ramaiah Nagar MSR Nagar Karnataka Bengaluru560054 India Department of Mechanical Engineering Ramaiah Institute of Technology MSRIT Post M S Ramaiah Nagar MSR Nagar Karnataka Bengaluru560054 India Department of Artificial Intelligence & Data Science Ramaiah Institute of Technology MSRIT Post M S Ramaiah Nagar MSR Nagar Karnataka Bengaluru560054 India Department of Information Science & Engineering Ramaiah Institute of Technology MSRIT Post M S Ramaiah Nagar MSR Nagar Karnataka Bengaluru560054 India

Space debris is one significant setback in our attempt to explore space and enhance satellite technology. Eradicating this upshot is eminent to our future missions and a safe environment for our planet. The scale of the space junk in the low earth orbit is around few hundreds of thousands and more, sizing from 10s of centimeters in diameter and lower. Although it is inevitable for the space debris to reenter the atmosphere naturally, it is a matter of years and hence the rate is too slow. With advances in the CubeSat technology, a variety of designs are possible for CubeSat systems to function as per the mission requirements. The current paper hence nominates an idea to remove some of the inoperative satellites and it's corresponding components with the help of a constellation of CubeSats that are equipped with distributed actuators for propulsion. The CubeSats are so designed to function as a propulsive device alone with minimal subsystem requirements. The constellation is contained in a cuboidal station with CubeSats docked on all the lateral sides. Once a target body is locked and intended to be removed, the constellation releases one or more CubeSats en route to the target body. Once at site, the CubeSats attach themselves to the target and propel the body to reenter the atmosphere. This constellation station is so designed to be compatible for reusability and the maintenance of such a design is discussed in the paper. The entire approach is thoroughly analyzed investigating multiple designs for the CubeSats. An additional benefit of the proposed idea is to ensure an immediate solution for deorbiting any critically unstable debris in the future in an event of emergency. Copyright © 2022 by the International Astronautical Federation (IAF). All rights reserved.

关键词： Space debris

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A Super-Wideband Multiband MIMO Antenna for Microwave and Millimeter Wave Wireless Applications

A Super-Wideband Multiband MIMO Antenna for Microwave and Mi...

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Wireless Antenna and Microwave Symposium (WAMS), IEEE

作者： Manish Sharma Kanhaiya Sharma Rana Gill Ganga Prasad Pandey Shailaja Salagrama Om Mishra Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of Commuter Science & Engineering Symbiosis Institute of Technology Symbiosis International (Deemed) University Pune Department of Electronics & Communication Engineering University Centre for Research & Development Chandigarh University Gharuan Mohali Punjab India Information & Communication Technology School of Technology Pandit Deendayal Energy University Gandhinagar India Department of Information Technology University of Cumberland’s Williamsburg Kentucky USA Department of Artificial Intelligence & Machine Learning Symbiosis Institute of Technology Symbiosis International (Deemed) University Pune

This communication reports a multi-super-wideband microwave-access antenna that achieves a bandwidth of 8.56GHz-39.02GHz and finds applications for X-band, Ku-band in Microwave and 28.0GHz & 38.0GHz for millimeter-Wave band 5G infrastructure. The patch which radiates electromagnetic energy consists of a hexagon shape with partial rectangular ground printed on Rogers-Substrate with a thin thickness of 0.254mm. The proposed work with a single element occupies a very compact space of 120 mm 2 and the MIMO SWB counterpart occupies a space of 240 mm 2 . The proposed antenna releasing EM wave offers an average peak realized gain of 4.74dBi and directivity of 4.09dB. The proposed antenna also offers desirable 2-D radiation patterns at 10.60GHz, 16.0GHz, 28.0GHz, and 38.0GHz respectively. The MIMO SWB configuration with an edge-to-edge spacing of 2.50mm achieves isolation of more than 12.50dB with diversity parameters ECC SWB <0.12, DG SWB >9.995dB, TARC SWB SWB<0.30b/s/Hz. The antenna radiating technology achieving several useable bands is useful in mobile networks for achieving information and communication system.

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Age Detection based on Facial Features Using Support Vector machine

Age Detection based on Facial Features Using Support Vector ...

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Knowledge engineering and Communication Systems (ICKECS), International Conference on

作者： Jayaprada S. Hiremath Shantala S. Hiremath Sujith Kumar Elukoti Hebbare Shantakumar B. Patil Mrutyunjaya S. Hiremath Computer Science and Engineering Research Scholar at VTU Belgaum India Specialist in Image Processing Tata Elxsi Limited Bangalore India Principal Engineer (Artificial intelligence / Machine learning) VVDN Technologies Pvt. Ltd. Bangalore India Department of Image Processing eMath Technology Pvt. Ltd. Bangalore India Computer Science and Engineering Sai Vidya Institute of Technology Bengaluru India

Face aging has been studied for decades. Determining age from a facial shot is key to our technique for diagnosing abnormal behavior. Security monitoring, forensics, biometrics, and Human-Computer Interface (HCI) use facial age estimates. We only look at adults 1–75 in the UTK Face database, which covers 0 to 116 years. The database contains 23,708 face photos with age, gender, and ethnicity annotations. In work, preprocessing, feature extraction, feature selection, and age categorization are involved. Preprocessing adjusts images. Computer vision uses Local Binary Pattern (LBP) and Histogram of Oriented Gradient (HOG) as visual descriptors, whereas fscmrmr is utilized for classification. Support Vector machines (SVM) improve classification accuracy in highdimensional areas. The chosen characteristics are concatenated and passed to a multiclass SVM classifier to classify the images with 95.69% success.

关键词： Support vector machines Training Human computer interaction Visualization Databases Transfer learning Feature extraction

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