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检索条件"丛书名=Learning and Analytics in Intelligent Systems"

共 229 条记录，以下是51-60 订阅

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Auction System in Food Supply Chain Management Using Blockchain 1

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作者： Shwetha, A.N. Prabodh, C.P. Department of Computer Science and Engineering Siddaganga Institute of Technology Tumakuru India

ISBN: (数字)9789811592935

ISBN: (纸本)9789811592928;9789811592959

Blockchain has become very popular these days because of its decentralized nature. The applications of blockchain are spread out in all domains from agriculture to medical field. Food supply chain can be made transparent using blockchain. The need for transparency in food supply chain is increasing day by day because nowadays people are more cautious about the food they buy and consume. So every individual should be able to get complete details about the food they eat from farming to consumer end. In this area, blockchain is playing a vital role. Along with giving complete information of food products to end user, it is also required for a farmer to get good prices for the food products they had grown. Currently, food products are sold in centralized auction system with the involvement of a third party. Because of the biased nature of third party, farmers are not able to get valid price for food items they have even though there is a demand in market. So, this paper is discussing an auction system for food products without a third party using blockchain technology, which avoids biasing. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Supply chain management

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Transient Response Improvement of Separately Excited D.C Motor Using Fuzzy Logic Controller 1

引用

作者： Yarlagadda, Venu Ramesh Babu, V. Veeresham, K. Rajesh, Kasala Karthik Kumar, S.N.V. Department of EEE VNRVJIET Hyderabad India

ISBN: (数字)9789811592935

ISBN: (纸本)9789811592928;9789811592959

The fuzzy logic control draws the attention of Researchers to improve the system performance, when the control strategy involves ambiguity. Fuzzy means, things are not clear;hence the fuzzy logic control determines the proper control actions for non-deterministic systems. The article is aimed to determine the small signal model of a d.c shunt motor using laboratory based testing, and to design a PI controller for improving the system performance using Ziegler-Nichols tuning method. The performance of the machine can still need some improvement, which can be attained using fuzzy logic controller. The dynamic and steady state performance can be enhanced even for load disturbance. The fuzzy controller is designed with two input membership functions and one output function of triangle shape with twenty five fuzzy rules. The case study have been performed with simulation results. The machine is tested with two major cases, one is comparative analysis of ZN tuned PI controller with FLC in two cases one without load disturbance and the other is with load disturbance. The performance of the machine with fuzzy logic controller is robust and much superior to other method for both the cases. The Obtained simulation results are as follows −100% steady state error for the both without & with controller by consideration of without and with one percent load disturbance, while ZN tuned PI gives the settling time of 12 s with 3% steady state error and 12 s with 0.5% steady state error for without and with one percent load disturbance respectively FLC gives settling time of 0.82 s with zero steady state error and 0.9 s with zero steady state error for without and with one percent load disturbance respectively. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Membership functions

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Throat Microphone Speech Enhancement Using Machine learning Technique 1

引用

作者： Paul, Subrata Kumer Paul, Rakhi Rani Nishimura, Masafumi Hamid, Md. Ekramul Department of Computer Science and Engineering University of Rajshahi Rajshahi Bangladesh Faculty of Informatics Shizuoka University 3-5-1 Johoku Naka-ku Hamamatsu-shi Shizuoka432-8011 Japan

ISBN: (数字)9783030654078

ISBN: (纸本)9783030654061;9783030654092

Throat Microphone (TM) speech is a narrow bandwidth speech and it sounds unnatural, unlike acoustic microphone (AM) recording. Although the TM captured speech is not affected by the environmental noise but it suffers naturalness and intelligibility problems. In this paper, we focus on the problem of enhancing the perceptual quality of the TM speech using the machine learning technique by modifying the spectral envelope and vocal tract parameters. The Mel-frequency Cepstral Coefficients (MFCCs) feature extraction technique is carried out to extract speech features. Then mapping technique is used between the features of the TM and AM speech using Neural Network. This improves the perceptual quality of the TM speech with respect to AM speech by estimating and correcting the missing high-frequency components in between 4 and 8 kHz from the low-frequency band (0–4 kHz) of TM speech signal. Then the least-square estimation and Inverse Short-time Fourier Transform Magnitude methods are applied to measure the power spectrum is used to reconstruct the speech signal. The ATR503 dataset is used to test the proposed technique. The simulation results show a visible performance in the field of speech enhancement in adverse environments. The aim of this study is for natural human–machine interaction for vocal tract affected people. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Least squares approximations

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Comprehensive Analysis of State-of-the-Art Techniques for VQA 1

引用

作者： Chirgaiya, Sachin Rajavat, Anand SVVV Indore India

ISBN: (数字)9789811592935

ISBN: (纸本)9789811592928;9789811592959

The visual question answering is an upcoming field in the domain of computer vision and NLP, i.e., natural language processing community. In this domain, a person will be giving any image and can answer certain questions using common sense about the given image, this combines various visual and linguistic processing using the understanding of the user by analyzing the image. This discussion concerned the various datasets that are used in these studies and using the various question and the answer format and which increases the robustness and efficiency of different machine learning models. Also, here, various methods are discussed, which are classified using the machine learning mechanism taking the help of popular textual and visual modalities. The latest convolutional and neural networks of recurring nature are used to map several questions and images in the feature space, which is very common in deep learning. Also, numerous question answers are examined from the diverse depth and the project of visual modalities to understand the relevance of the annotations of structured images and photographs using a visual question answering method in this study. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Natural language processing systems

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An Approach for Optimizing Algorithms Which Find k1-Most Demanding Products 1

引用

作者： Chittepu, Sireesha Reddy, P. Yeshwanth Reddy, M. Nikhil Vasavi College Of Engineering Hyderabad India NIIT University Jaipur India VNR VJIET Hyderabad India

ISBN: (数字)9789811592935

ISBN: (纸本)9789811592928;9789811592959

The primary goal of this paper is on optimizing the process of finding k1-most demanding products using traditional algorithms and clustering. We have used four clustering algorithms over two traditional algorithms to optimize the time for finding k1-most demanding products. A synthetic data set was used for demonstration and the results are plotted in a graph for comparison. This approach can be used in various fields for optimization purposes. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Self organizing maps

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Malware Detection Kit for Malware Analysis of Big Data 1

引用

作者： Sree Lakshmi, T. Govindarajan, M. Sreenivasulu, Asadi Department of CSE Annamalai University Tamil Nadu Chidambaram India Department of CSE Annamalai University Tamil Nadu Chidambaram India Department of CSE Sreevidyanikethan Engineering College Andra Pradesh Tirupati India

ISBN: (数字)9789811592935

ISBN: (纸本)9789811592928;9789811592959

Contemporaneously, Security is a major mission in technological world, irrespective of domains, fields and technologies. Like other areas, Big Data and IOT too experiencing security issues, threats and attacks in every single minute. These attacks can be on different components of Big Data and IOT, like data stored on various nodes, clusters, propagated through networks, and via various components of the system or sensors. Big data security deals with the measures, techniques and tools used to protect both the data and analytics methods from attacks, threats, or other unauthorized activities. In this paper, To apply Security measures to overcome vulnerability of infrastructure, proposed a method called Malware Detection Kit (MDK). MDK comprises of static and dynamic analysis. Malware detection kit identifies attacks and threats. To detect attacks analysis is performed in two iterations. Whenever a new data enters into system, data undergoes first iteration of MDK, by static analysis it identifies threats if any. In the second iteration, file is submitted to automated dynamic analysis tools. The tool reports whether the file is malware on benign. Static Analysis is done by using Random Forest classifier, it produced high accuracy and low error rate for Malgenome dataset. Dynamic analysis is done by using automated sandboxes. Finally, this method recognises whether the file is benign or malware. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Malware

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Machine learning Techniques and analytics for Cloud Security

引用

丛书名： Advances in learning analytics for intelligent cloud-IoT systems

2022年

作者： edited by Rajdeep Chakraborty Anupam Ghosh and Jyotsna Kumar Mandal.

ISBN: (数字)9781119764090;9781119764106

ISBN: (纸本)9781119762256

MACHINE learning TECHNIQUES AND analytics FOR CLOUD SECURITY This book covers new methods, surveys, case studies, and policy with almost all machine learning techniques and analytics for cloud security solutions The aim of Machine learning Techniques and analytics for Cloud Security is to integrate machine learning approaches to meet various analytical issues in cloud security. Cloud security with ML has long-standing challenges that require methodological and theoretical handling. The conventional cryptography approach is less applied in resource-constrained devices. To solve these issues, the machine learning approach may be effectively used in providing security to the vast growing cloud environment. Machine learning algorithms can also be used to meet various cloud security issues, such as effective intrusion detection systems, zero-knowledge authentication systems, measures for passive attacks, protocols design, privacy system designs, applications, and many more. The book also contains case studies/projects outlining how to implement various security features using machine learning algorithms and analytics on existing cloud-based products in public, private and hybrid cloud respectively. Audience Research scholars and industry engineers in computer sciences, electrical and electronics engineering, machine learning, computer security, information technology, and cryptography.

关键词： Cloud computing Computer networks Machine learning. Security measures. Security measures.

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An Improved Web Information System Through Identification of Faculty Browsing Patterns in Affiliated Engineering Institutions 1

引用

作者： Swathi, M. Sreedhar, K.C. Shaik, Meeravali Prabhakar, V. Department of CSE VMTW Hyderabad India Department of CSE Sreenidhi Institute of Science and Technology Hyderabad India

ISBN: (数字)9789811592935

ISBN: (纸本)9789811592928;9789811592959

Now a days, the teaching methodology in engineering stream is extensively making use of internet resources. The concepts being taught in engineering institutions are very well presented in online resources, such as Wikipedia, Tutorialspoint etc. The faculty working in engineering institutions frequently visits the pages in the previously mentioned websites. As the syllabus the faculty has to teach is predetermined by the university to which they had been affiliated to. As a result, the pages those faculty browses are ordered by the topics in syllabus which is streamlined in a semester through the timetable of a particular year and branch of engineering. So we can know in advance the pages that can be browsed for all subjects, all branches, and all years of engineering courses. As a result, the web server efficiency can be improved by prefetching these pages into random access memory. We have implemented this idea with various well known page replacement algorithms like FIFO, LRU, LFU, OPT and analyzed the performance with proposed idea and without proposed idea in all four algorithms. Results suggest that there is a significant improvement in hit ratio and thus in access latency. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Websites

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Prediction of Rice Plant Diseases Based on Soil and Weather Conditions 1

引用

作者： Maneesha, Akula Suresh, Chalumuru Kiranmayee, B.V. Department of CSE VNRVJIET Hyderabad India

ISBN: (数字)9789811592935

ISBN: (纸本)9789811592928;9789811592959

India is an agriculture-dependent country as most of its inhabitants pivot on the cultivation of crops for their livelihood. The growth of crop mainly relies upon climatic conditions, water quality and water content in the soil. In recent years, the crop yield has been decreased due to the occurrence of diseases, variations in the climatic conditions and changes in the soil properties. The main challenge is to reduce the loss of crop due to diseases and increase the productivity of the crop. For this, it is very important to predict the disease in advance so that the necessary precautions will be taken. In order to achieve this, a system is proposed to detect the rice plant diseases based on Internet of Things and machine learning techniques where IOT is used to collect the sensor data and prediction of disease is done by Naïve Bayes machine learning algorithm. Climate and water data is obtained with the help of sensors and is sent to the ThingSpeak cloud and this data is extracted and utilized for predicting the plant disease and the accuracy obtained is nearly 92%. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Crops

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Preventing Crime Using Advanced Artificial Intelligence Techniques 1

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作者： Gogineni, Saikiran Pimpalshende, Anjusha Arumugham, Poongodai Dhanrajnath, Porika CSE CMR College of Engineering & Technology Hyderabad India

ISBN: (数字)9789811592935

ISBN: (纸本)9789811592928;9789811592959

Crime is increasing significantly from day to day. Every crime is associated with a certain pattern. The modern AI techniques can be implemented in crime scenarios to obtain valuable insights. In contrast to the existing works on crime analysis, we used the latest and much more efficient algorithms to handle crime. Our research work is segregated into three independent modules—prevention, detection and investigation. Prevention phase uses AI strategies to predict regions with high probability of crime occurrence in specified time and preventing crime from happening. Detection phase uses Faster RCNN to detect the kind of crime happening in an area through a security camera and alerting the police for instant response. If crime happens, AI Investigation can predict criminals through clues left in the crime spot. Our work also classifies police complaints. Criminal complaints registered by victims are automatically classified as an appropriate type such as robbery or murder. Our work achieved significant performance compared with earlier works. For prevention stage, SAN FRANCISCO crime dataset is considered. Fordetection stage, crime images dataset is constructed and annotated by extractingframes from UCF crime dataset (1900 videos, 128 hours of videos). Textcomplaints are manually constructed. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Crime

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