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Building an administrative platform based on intelligent algorithms in the framework of big data

Building an administrative platform based on intelligent alg...

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Networking, Communications and Information Technology (NetCIT), international conference on

作者： Zhang Fangfang Faculty of Political Science and Law Jiangxi Normal University Nanchang China

With the continuous development of the Internet, mobile Internet, cloud computing, the Internet of Things and other information technologies, human production and lifestyle have undergone tremendous reforms, and humanity is entering a stage with a higher degree of informatization - the era of big data. data has become one of the most important values and assets of this era, and the development and application of big data has become the most prominent feature of the times. Big data has produced significant changes in the economic field, and big data and intelligent algorithms have become one of the core factors of business competition. Big data is also gradually causing profound changes in the social field, and people's way of life, way of work and way of thinking will also be engraved with the brand of Big data. The impact of big data in the field of administration is also emerging. Big data will not only provide advanced management solutions for the modernization of university governance system and governance capacity, but also promote the transformation of governance concept and governance mode. Therefore, this paper focuses on the construction of university administration platform in the era of big data and integrates the construction of big data administration platform through intelligent algorithms in order to achieve the modernization of university administration capability.

关键词： Economics Cloud computing Humanities Buildings Production Big data Information and communication technology

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Drug Recommendation System Using LDA

Drug Recommendation System Using LDA

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international conference on Futuristic technologies (INCOFT)

作者： Satwik Reddy Sripathi Nadella Venkata Sai Pradyumna Akula Dhanush Subramani R Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Amrita School of Computing Bengaluru India Department of Mathematics Amrita School of Engineering Bengaluru India

These days, people are very much concerned about their health. Many want to lead a healthy and long life. However, studies reveal that errors due to doctor’s and pharmacist’s experience resulted in many people’s death. These medical errors are costing us our lives. Technical algorithms like LDA, PCA and other machine learning algorithms can help in topic modelling that would play a major role in the industry. These technologies can aid in the investigation of medical history and, by being doctor-friendly, can help to prevent medical errors. In this paper, a medicine is proposed based on the review taken from the patient as it would be identified with our model created with LDA. Recommendation system that analyses sentiment analysis of patient review data to discover the best medication for a disease is done in our work.

关键词： Industries Drugs Sentiment analysis Machine learning algorithms Costing Medical services History

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A Unified Methodology for Early recognition of Diabetic Retinopathy

A Unified Methodology for Early recognition of Diabetic Reti...

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Smart technologies in computing, Electrical and Electronics (ICSTCEE), international conference on

作者： S. Deepa A. Umamageswari S. Shoba Department of CSE SRM Institute of Science and Technology Chennai India School of Electronics Engg Vellore Institute of Technology Chennai India

Diabetic retinopathy is the occlusion of the retinal blood vessel because of diabetic mellitus issues, which can result in visual diminution. The best way to solve this issue is to utilize a retinal screening device that can detect retinal impairment at a premature stage. This work proposes the use of morphological operations and segmentation techniques to locate blood ducts, exudates, and microaneurysms. The extracted features are then subjected to Haar wavelet transformation. After that, the principal-component analysis technique tends to improve Characteristic selection. The photos are categorized as diabetic or non-diabetic using back propagation neural network and one rule classifier approaches. Experiments were carried out on a publicly available dataset on diabetic retinopathy. Unfortunately, conventional methods are incapable of making the best use of global data, and model complexity is significant. This project proposes a method for detecting diabetic retinopathy that extracts the precise area and quantity of microaneurysms from color fundus images. Two aspects of this research have been determined, namely the number and area of MA. Green channel extraction, histogram equalization, and the morphological process will be employed as pre-processing approaches at first. Principal-component analysis (PCA), contrast limited adaptive histogram equalization (CLAHE), structural procedure, and averaging filtering are all employed to discover microaneurysms.

关键词： Wavelet transforms Histograms Visualization Retinopathy Veins Retina Feature extraction

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A Deep Learning and Optimization Method for Detecting Network Intrusion in IOT

A Deep Learning and Optimization Method for Detecting Networ...

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Advanced technologies in Intelligent Control, Environment, computing & Communication Engineering (ICATIECE), international conference on

作者： Rekha Gangula Murali Mohan Vutukuru Ranjeeth Kumar. M Department of CSE Koneru Lakshmaiah Education Foundation Guntur Andhra Pradesh Department of CSE Kakatiya Institute of Technology and Science Warangal Telangana India

ISBN: (纸本)9781665493970

The accessibility and maintenance of the internet of things depend heavily on security. Numerous investigations have looked into the use of anomalies intrusion detection in various applications. Researchers and engineers must be able to interpret the complicated structure from imprecise information, recognize the dynamic anomaly patterns, and find anomalies when there aren't enough labels to describe them. As a result, using deep learning techniques rather than conventional shallow learning methods is necessary to improve anomalous detection capability. Large computations are also necessary due to the enormous volume of data generated by the IoT's many connected devices. This article offers a survey on anomalous intrusion detection using deep learning techniques, with a focus on IoT devices utilized in real-world issues that have limited resources. The results of the research that were evaluated demonstrated that deep learning is better to traditional learning when it comes to high identification efficiency and low rate of false alarms. Therefore, it's also strongly advised to carry out additional research employing deep learning algorithms towards reliable Detection.

关键词： Deep learning Learning systems Intrusion detection Optimization methods Maintenance engineering Pattern recognition Internet of Things

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Applications of Artificial Intelligence and Big data for Strengthening the Role of Intelligence in Human Security

Applications of Artificial Intelligence and Big Data for Str...

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international conference on computing, Engineering, and Design (ICCED)

作者： Ahmad Shahrul Mubarok Armi Susandi Teddy Mantoro Medical Intelligence Post-Graduate Program State Intelligence College Bogor Indonesia Departement of Computer Science Media-Tech Lab Sampoerna University Jakarta Indonesia

ISBN: (纸本)9781665453905

The state, through the government, should ensure national security and stability through the policies taken. For this reason, fast and accurate information and data are needed to form the basis for policymaking. Intelligence actors have an essential role in gathering information to identify and prevent threats within and outside the country. Technological advances affect changes in threats and increase the classification of these threats. Covid-19 is a real example of the threat in this era because almost all countries feel its impact. In addition to affecting health, the Covid-19 pandemic also impacts the global economic sector. The economic impact is felt by small and medium industries, goods and services products, and also the tourism sector. The method that is used in this study is a literature review from various national and international journals. AI and Big data can be used to track viruses in real time, collect adequate public health data, and integrate vaccine use. Also, AI and Big data can provide local decision and policy-makers with informed, evidence-based predictions. the threat of the Covid-19 pandemic and other infectious diseases that disrupt public health and have a broad impact must be anticipated and addressed in order to achieve the safety and existence of the nation and state. The author wants to emphasize the importance of the role of intelligence in anticipating threats from the visible to the invisible.

关键词： COVID-19 Pandemics Big data Stability analysis Vaccines Safety Security

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An Investigation of the Bibliometric Landscape of the Many Facets of Machine Learning From the Years 2000 to 2022

An Investigation of the Bibliometric Landscape of the Many F...

引用

Computational Modelling, Simulation and Optimization (ICCMSO), international conference on

作者： Neeru Sharma Raman Chadha UIE Chandigarh University Punjab

Machine Learning as an emerging and applicable learning plays a vital role in the world of Computer science. MachineLearning has attracted much attention in the last decade. With the development of Machine Learning, huge researchers and publications opted for this as the path. This paper is about the bibliometric analysis that is deployed from the year 2000 to 2022. The main three fundamental factors that guide the progress of machine learning are data, computing, and algorithmic advances. Mainly there are four different types of machine learning which accomplish Supervised ML, Unsupervised ML, Semi-Supervised ML, and Reinforcement Machine Learning which is used in different areas and applications. This paper is mainly focused on what are the major areas where machine learning has used and what are the minimal area where there is still a requirement of using Machine learning is to be used.

关键词： Computer science Machine learning algorithms Tree graphs Computational modeling Bibliometrics Closed box Machine learning

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Influence of DLT in the E-Governance Strategy

Influence of DLT in the E-Governance Strategy

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Computer, Power and Communications (ICCPC), international conference on

作者： D Kumar B.M Beena Department of Computer Science & Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Coimbatore India Department of Computer Science & Engineering Amrita Vishwa Vidyapeetham Amrita School of Computing Bengaluru India

The Distributed Ledger Technology (DLT) technology is one of the future drivers of distributed form of data handling especially with blockchain dominating with immutable and secured e-transactions. With its influence and pre-dominant implementation in various sectors like banking, DLT has different use-cases applied in the E-Governance too. Countries like Estonia have come up with various blockchain based e-services for more transparency and privacy. Smart contracts / chain code in the permissioned blockchain could provide the basic Smart Governance needs such as simplified beneficiary authentication, transparency, privacy, security, automation, cost control, faster processing time and so on. This shows the DLT as a catalyst for automation in the future of Smart Governance along with other technologies like IoT, digital twin and so on. This paper analyses the benefits and challenges of blockchain based E-Governance implementation as well as the different DLT types available such as DAG, hashgraph, etc. apart from the blockchain and their potential for an effective citizen centric E-Governance.

关键词： Privacy Automation Distributed ledger Smart contracts Process control Market research data models

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Recent advances of Patient Monitoring in Internet of Healthcare Things : A Comparative Study

Recent Advances of Patient Monitoring in Internet of Healthc...

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international Wireless Communications and Mobile computing conference, IWCMC

作者： Ghina Saad Hassan Harb Abdelhafid Abouaissa Nour Charara Lhassane Idoumghar Computer Science Department University of Haute Alsace Colmar Colmar France ICCS-Lab American University of Culture and Education (AUCE) Beirut Lebanon Computer Science Department Faculty of Sciences Lebanese University Beirut Lebanon

Healthcare requires the cooperation of many administrative units and medical specialties. The Internet of Things (IoT) is involved into healthcare field and plays an extremely important role by providing healthcare services. In the Internet of Healthcare Things (IoHT) several challenges appeared in terms of limited battery life, long processing time, large amounts of collected data, paquets overhead on sink,…etc. A lot of research studies have been done in order to improve the healthcare IoT based applications. However, these proposed systems have been focused on some specific purpose without ensuring an effective solution for all problems. This paper presents a comparative study for the recent advances in Internet of healthcare monitoring. In addition, an optimized intra WBSN communication (OIC) an is proposed in order to overcome the over-mentioned challenges. OIC is based on merging an energy efficient routing protocol with the data transmission process. This approach also reduces the data acquisition redundancy, and finds the optimum path for data transmission, according to the patient situation. Our approach is implemented and tested on real biosensor data while the obtained results prove the efficiency on extending the network lifetime (up to 84%), removing the data transmission redundancy (up to 60%), minimizing the overhead on sink (up to 83%), and optimizing the transmission time. Based on a comparative study with four state-of-the-art methods, the superiority of our approach is validated.

关键词： Wireless communication Patient monitoring Medical specialties Redundancy Merging Medical services Routing protocols

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Proof of Game (PoG): A Proof of Work (PoW)’s Extended Consensus Algorithm for Healthcare Application 3rd

Proof of Game (PoG): A Proof of Work (PoW)’s Extended Conse...

引用

3rd international conference on Innovative computing and Communication, ICICC 2020

作者： Kumar, Adarsh Jain, Saurabh School of Computer Science University of Petroleum and Energy Studies BidholiDehradun India

ISBN: (纸本)9789811551123

Advancement in blockchain technologies during the past decade has attracted tremendous interests from academia, research community and the industry. A blockchain network is a peer-to-peer, decentralized and immutable distributed ledger system for transactional records. With an increase in the number of blockchain-based applications, it becomes a powerful technology for decentralized data processing and consensus mechanisms based blockchain networks. In this work, a single- and multiplayer bit challenging and incentivized consensus mechanisms for blockchain networks are used in proposing a "proof-of-game (PoG)" protocol for resource variant blockchain networks. Bit verifier PoG is designed to be memory dependent and CPU independent mechanism for time efficiency and resource independence. In results, it is observed that the number of blocks mined using this protocol is proportional to the number of participants associated with blocks. Further, it is observed that the priority of a blockchain increases exponentially with an increase in the number of blocks mined, and the number of blocks mined decreases exponentially with an increase in computational challenge. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Blockchain

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Blockchain based Security Solution for Internet of Drones

Blockchain based Security Solution for Internet of Drones

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international conference on Innovative Sustainable Computational technologies (CISCT)

作者： Sudhanshu Maurya V. R. Niveditha B Anandapriya Rohan Verma Kashish Mirza Mohit Tiwari Bhimtal Campus School of Computing Graphic Era Hill University Nainital India Department of Computer Science & Engineering Sathyabama Institute of Science and Technology Chennai India Department of Computer Application Patrician College of Arts and Science Chennai India Department of Computer Science & Engineering Hemvati Nandan Bahuguna Garhwal University Srinagar Uttarakhand India Department of Computer Science & Engineering Bhimtal Campus Graphic Era Hill University Nainital India Department of Computer Science & Engineering Bharati Vidyapeeth’s College of Engineering Delhi India

ISBN: (纸本)9781665474177

Nowadays, Drone usage is increasing faster than before. They have frequently been employed in civil services. In a number of sectors, including transportation, agriculture, building, and emergency response, drones have grown in significance. Drones can operate in places that are inaccessible to humans, collect data more effectively than conventional techniques, and carry out tasks more quickly. With the development of technology and laws, their use is anticipated to increase in the future. Therefore, it is imperative that drones must become smarter, more private, and more secure as they offer data transfer secrecy and reliability. In this paper, we have proposed a blockchain-based security solution model for the Internet of Drone environment. The proposed method is evaluated on a limited number of pretend drones. Here we may easily authenticate the administrator, add new drones, authenticate a drone, delete drones, get data from drones, save it to a blockchain-based secure system, and securely retrieve that information.

关键词： Wireless sensor networks Privacy Transportation Emergency services Information and communication technology Internet of Things Reliability

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