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Cauliflower Leaf Disease Detection Using Computerized Techniques 6

Cauliflower Leaf Disease Detection Using Computerized Techni...

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6th IEEE international conference on computing, Communication and Automation, ICCCA 2021

作者： Orin, Taslima Yesmin Mojumdar, Mayen Uddin Siddiquee, Shah Md. Tanvir Chakraborty, Narayan Ranjan Daffodil International University Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9781665414739

Crop cultivation is an important role in the agriculture industry. Presently, food loss is primarily caused by sick crops, which affects growth rate and increase. High yield depends a lot on its growth. However, now crop leaf disease has become a significant problem in agriculture as a result of which the quality and growth rate of yield in agriculture is declining day by day. through this paper, we have tried to diagnose the leaf disease of a particular crop (cauliflower). In this study, we collected data from each cauliflower leaf and created a dataset, and we divided our study was split into two sections: leaf disease detection and machine learning techniques. To detect leaf disease, we have used Matlab and various algorithms of classic machine learning such as Nav Bayes (NB), Decision Tree (TT), Random Forest (RF), Support Vector Machine (SVM), Secular Minimal Optimization (SMO). For each, we determined the accuracy, retraction, F-measurement, accuracy, and ROC values classification. this paper describes a simple but effective technique for reviewing leaf disease detection evidence and applying it to image processing and computer vision. © 2021 IEEE.

关键词： Support vector machines

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A Machine Learning Approach for Prediction of Sedentary Behavior Based on Daily Step Counts 43

A Machine Learning Approach for Prediction of Sedentary Beha...

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43rd Annual international conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (IEEE EMBC)

作者： Papathomas, Evangelos Triantafyllidis, Andreas Mastoras, Rafail-Evangelos Giakoumis, Dimitrios Votis, Konstantinos Tzovaras, Dimitrios Ctr Res & Technol Hellas Informat Technol Inst 6th Klm Charilaou Thermi RdPOB 60361 GR-57001 Thessaloniki Greece

ISBN: (纸本)9781728111797

Sedentary behavior is considered as a major public health challenge, linked with many chronic diseases and premature mortality. In this paper, we propose a steps counting -based machine learning approach for the prediction of sedentary behavior. Our work focuses on analyzing historical data from multiple users of wearable physical activity trackers and exploring the performance of four machine learning algorithms, i.e., Logistic Regression, Random Forest, XGBoost, Convolutional Neural Networks, as well as a Majority Vote Ensemble of the algorithms. To train and test our models we employed a crowd sourced dataset containing a month's data of 33 users. For further evaluation, we employed a dataset containing 6 months of data of an additional user. the results revealed that while all models succeed in predicting next-day sedentary behavior, the ensemble model outperforms all baselines, as it manages to predict sedentary behavior and reduce false positives more effectively. On the multi-subjects test dataset, our ensemble model achieved an accuracy of 82.12% with a sensitivity of 74.53% and a specificity of 85.71% On the additional unseen dataset, we achieved 76.88% in accuracy, 63.27% in sensitivity and 81.75% in specificity. these outcomes provide the ground towards the development of real-life artificially intelligent systems for sedentary behavior prediction.

关键词： healthcare sedentary behavior wearable devices machine learning

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A Real-time Approach System for Vineyards Intra-row Weed Detection 10

A Real-time Approach System for Vineyards Intra-row Weed Det...

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10th international conference on Information and Communication Technologies in Agriculture, Food and Environment, HAICTA 2022

作者： Moysiadis, Vasileios Kateris, Dimitrios Katikaridis, Dimitrios Vasileiadis, Giorgos Kolorizos, Vasileios Tagarakis, Aristotelis C. Bochtis, Dionysis 6th km Charilaou-Thermi Rd Thessaloniki57001 Greece Department of Computer Science & Telecommunications University of Thessaly Lamia35131 Greece Laboratory of Agricultural Engineering School of Agriculture Aristotle University of Thessaloniki Thessaloniki54124 Greece Department of Energy Systems University of Thessaly Gaiopolis Campus Larisa41500 Greece

With the incorporation of autonomous robotic platforms in various areas (industry, agriculture, etc.), numerous mundane operations have become fully automated. the highly demanding working environment of Agriculture let the development of techniques and machineries that could cope with each case. New technologies (from high performance motors to optimization algorithms) have been implemented and tested in this field. Every cultivation season, there are several operations that contribute to crop development and have to take place at least once. One of these operations is the weeding. In every crop, there are plants that are not part of it. these plants, in most cases have a negative impact on the crop and had to be removed. In the past the weeding was taken place either by hand (smaller fields) or by the use of herbicides (larger fields). In the second case, the dosage and the time are pre-defined, and they are not taking into consideration the growth percentage and the weed allocation within the field. In this work, a novel approach for intra-row weed detection in vineyards is developed and presented. All the experiments both for data collection and algorithm testing took place in a high value vineyard which produce numerous wine varieties. the aim of this work is to implement an accurate real-time robotic system for weed detection and segmentation using a deep learning algorithm in order to optimize the weeding procedure. this approach consists of two essential sub-systems. the first one is the robotic platform that embeds all the necessary sensors and the required computational power for the detection algorithm. the second one is the developed algorithm. From all the developed models, the selected one performed accurately in the training procedure and in the unknown datasets. In order to properly validate the algorithm, the unknown datasets were acquired in different time periods with variations in both camera angle and wine varieties. © 2022 Copyright for this pa

关键词： Learning algorithms

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6th conference on Machine Translation, WMT 2021

作者： Mujadia, Vandan Sharma, Dipti Misra Machine Translation - Natural Language Processing Lab Language Technologies Research Centre Kohli Center on Intelligent Systems International Institute of Information Technology Hyderabad India

ISBN: (纸本)9781954085947

this paper describes the participation of team oneNLP (LTRC, IIIT-Hyderabad) for the WMT 2021 task, similar language translation. We experimented with transformer based Neural Machine Translation and explored the use of language similarity for Tamil-Telugu and Telugu-Tamil. We incorporated use of different subword configurations, script conversion and single model training for both directions as exploratory experiments. © 2021 Association for Computational Linguistics

关键词： Neural machine translation

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proceedings - 2019 6th international conference on Control, Instrumentation and Automation, ICCIA 2019

Proceedings - 2019 6th International Conference on Control, ...

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6th international conference on Control, Instrumentation and Automation, ICCIA 2019

ISBN: (纸本)9781728158150

the proceedings contain 60 papers. the topics discussed include: output voltage control of inverters using SDRE tracking and LQT controllers;metro traffic regulation by considering the effect of transfer stations;observer-based sensor fault detection in islanded AC microgrids using online recursive estimation;unscented kalman filter in gas pipeline leakage magnitude estimation and localization;accuracy improvement of GPS/INS navigation system using extended kalman filter;neural networks adaptive DSC design of nonlinear systems in the presence of input saturation and external disturbance;design of a nonlinear model-based predictive controller for a wind turbine based on PMSG using an augmented extended kalman filter;robust fault tolerant position tracking control for a quadrotor UAV in presence of actuator faults;and high-performance robust grid-connected power systems.

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Overcoming brittleness in pareto-optimal learning-augmented algorithms 24

Overcoming brittleness in pareto-optimal learning-augmented ...

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proceedings of the 38th international conference on Neural Information Processing systems

作者： Alex Elenter Spyros Angelopoulos Christoph Dürr Yanni Lefki Sorbonne University CNRS LIP6 Paris France International Laboratory on Learning Systems Montreal Canada and Sorbonne University CNRS LIP6 Paris France Institut Polytechnique de Paris Palaiseau France

ISBN: (纸本)9798331314385

the study of online algorithms with machine-learned predictions has gained considerable prominence in recent years. One of the common objectives in the design and analysis of such algorithms is to attain (Pareto) optimal tradeoffs between the consistency of the algorithm, i.e., its performance assuming perfect predictions, and its robustness, i.e., the performance of the algorithm under adversarial predictions. In this work, we demonstrate that this optimization criterion can be extremely brittle, in that the performance of Pareto-optimal algorithms may degrade dramatically even in the presence of imperceptive prediction error. To remedy this drawback, we propose a new framework in which the smoothness in the performance of the algorithm is enforced by means of a user-specified profile. this allows us to regulate the performance of the algorithm as a function of the prediction error, while simultaneously maintaining the analytical notion of consistency/robustness tradeoffs, adapted to the profile setting. We apply this new approach to a well-studied online problem, namely the one-way trading problem. For this problem, we further address another limitation of the state-of-the-art Pareto-optimal algorithms, namely the fact that they are tailored to worst-case, and extremely pessimistic inputs. We propose a new Pareto-optimal algorithm that leverages any deviation from the worst-case input to its benefit, and introduce a new metric that allows us to compare any two Pareto-optimal algorithms via a dominance relation.

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5G/6G Technology Capabilities Designed for Secure Edge Network: Smart City Use Cases of Turkcell

5G/6G Technology Capabilities Designed for Secure Edge Netwo...

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Blockchain computing and Applications (BCCA), international conference on

作者： Gokhan Kalem Semiha Kosu Mehmet Basaran Network Technologies Turkcell Technology Next-Generation R&D Istanbul Turkiye Information and Communications Research Group Istanbul Technical University Istanbul Turkiye 6GEN Lab. Next-Generation R&D Network Technologies Istanbul Turkiye

ISBN: (数字)9798350351538

ISBN: (纸本)9798350351545

there is no doubt that 5G and 6G technologies coupled with secure edge network capabilities play crucial roles in the evolution of Industry 4.0 and emerging Industry 5.0. In Industry 4.0, 5G enhances smart manufacturing by enabling ultra-reliable low-latency communication (URLLC), massive machine-type communication (mMTC), and enhanced mobile broadband (eMBB). these features support real-time monitoring, automation, edge computing, and data exchange across interconnected devices and systems to improve industrial efficiency and productivity. With Industry 5.0, which focuses on human-machine collaboration, 5G continues to be vital, but the advent of 6G will bring even greater capabilities. 6G is expected to offer a higher level of autonomy and advanced artificial intelligence integration by facilitating seamless interaction between humans, machines as well as intelligent systems via edge networking. this will enable more sophisticated applications, such as advanced robotics, virtual and augmented reality experiences, further connected driving innovations, and also the symbiosis between humans and technology, built on ubiquitous connectivity. From a leading mobile network operator perspective, in this paper, we delve into how 5G technology, empowered with secure edge networks, can transform XR communication, vehicular communication, and also UAV-based aerial communication while enabling safer, more reliable, and more efficient systems in the smart city applications on the road to 6G.

关键词： 6G mobile communication Productivity Technological innovation 5G mobile communication Smart cities Collaboration Ultra reliable low latency communication Fourth Industrial Revolution Reliability Fifth Industrial Revolution

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Analyzing Adaptive Spectrum Sharing Techniques in 6G Cellular Networks

Analyzing Adaptive Spectrum Sharing Techniques in 6G Cellula...

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international conference on computing and Networking Technology (ICCNT)

作者： Pallavi Sumanta Sen Deeplata Sharma Department of Psychology School of Sciences JAIN (Deemed to be University) Bangalore Karnataka India Department of Pharmacy ARKA JAIN University Jamshedpur Jharkhand India Department of Chemistry Vivekananda Global University Jaipur India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

the C. Precision of studying Adaptive Spectrum Sharing techniques in 6G mobile Networks refers to the potential to properly expect the anticipated performance of such networks based totally on the assessment of the records collected from actual-world networks. the suitable statistics evaluation is made possible through the usage of superior algorithms together with AI-based spectrum-sharing strategies to provide particular insight into the to-be-had spectrum property in networks. those technically superior algorithms permit operators to choose spectrum bands in the manner to offers the most cost-powerful coverage for their network boom goals. Moreover, the AI-based spectrum sharing techniques are used to properly decide the c aggregate of spectrum bands to advantage top-of-the-line overall performance. It additionally the interference amongst networks and makes certain community balance. Similarly, C. Precision of reading Adaptive Spectrum Sharing techniques in 6G cell Networks additionally facilitates operators to determine the community configuration that gives the nice man or woman enjoy and most reliable network utilization.

关键词： 6G mobile communication Cellular networks Adaptive systems 5G mobile communication Aggregates Interference throughput Reliability engineering User experience Time factors

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2019 6th international conference on systems and Informatics, ICSAI 2019

2019 6th International Conference on Systems and Informatics...

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6th international conference on systems and Informatics, ICSAI 2019

ISBN: (纸本)9781728152561

the proceedings contain 292 papers. the topics discussed include: application of improved multi-threshold birch clustering in reservoir prediction;prediction of house price based on the back propagation neural network in the keras deep learning framework;intelligent fan system based on big data and artificial intelligence;the application of a new approach of fuzzy soft sets based decision-making in website rank and similarity;mission policy and optimization objectives in cognitive emergency communication networks;an electromagnetic and piezoelectric coupled energy harvester using cantilever beam for low frequency vibration;investigation and analysis on lightning protection maintenance schemes of high-speed rail catenary abroad and their reference significance for china;and very robust direct solver of the P3P problem.

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2019 6th international conference on Software Defined systems, SDS 2019

2019 6th International Conference on Software Defined System...

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6th international conference on Software Defined systems, SDS 2019

ISBN: (纸本)9781728107226

the proceedings contain 46 papers. the topics discussed include: intelligent intrusion detection using radial basis function neural network;hybrid SDN-ICN architecture design for the Internet of things;enabling scalability, adaptivity, and resilience in cloud applications by software-defined M-task-based programming;trust-aware service chain embedding;enhancing multipath TCP security through software defined networking;using blockchain technology to manage membership and legal contracts in a distributed data market;towards optimized verification and validation of 5G services;VNF placement strategy for availability and reliability of network services in NFV;and SDN-based slice orchestration and MAC management for QoS delivery in IEEE 802.11 networks.

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