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Communication Architecture for Autonomous Aerial Traffic Management

Communication Architecture for Autonomous Aerial Traffic Man...

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Recent advances and Innovations in Engineering (ICRAIE)

作者： Shobuj Paul Shuvrangshu Jana Onkar Chopra Ashwini Ratnoo Debasish Ghose Dept. of Mechanical Engineering National Institute of Technology Karnataka India Dept. of Aerospace Engineering Indian Institute of Science Bengaluru India

this paper presents a multi-agent communication paradigm for autonomous aerial traffic management. Multi-drone missions based on the existing ROS-based communication architecture heavily depend on the master node, and communication delay between nodes might not be sufficient for efficient inter-agent collision avoidance. In this paper, we have proposed a hybrid ROS-ROS2 communication architecture for centralised traffic management with the provision of distributed communication for collision avoidance and conflict resolution at intersections. the base station server responsible for traffic management runs on a ROS2 environment, ROS is used for communication with each onboard autopilot, and an intermediate add-on-module interfaces ROS and ROS2 messages. the content of the communication packets between the different nodes is decided based on the design requirements. Overall communication architecture is validated through simulation and hardware experiments.

关键词： Base stations Technological innovation Metals computer architecture Autopilot Servers Reliability

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Innovative advances: Crafting an Intelligent Controller for Home Energy Management Systems with Seamless Integration of Renewable Sources

Innovative Advances: Crafting an Intelligent Controller for ...

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international conference on Contemporary Computing and Informatics (IC3I)

作者： B Varasree Nv Uma Reddy Suman Avdhesh Yadav Ginni Nijhawan Monica Garg N Sirisha Department of Information Technology Institute of Aeronautical Engineering Hyderabad Telangana India Department of Artificial Intelligence & Machine Learning New Horizon College of Engineering Bangalore India Department of CSE IILM University Greater Noida Uttar Pradesh India Lovely Professional University Phagwara Lloyd Law College Greater Noida Uttar Pradesh India Department of Computer Science and Engineering MLR Institute of Technology Hyderabad Telangana India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

this research proposes an improved energy administration and optimization technique that utilizes fuzzy logic algorithms and incorporates many inputs and outputs (I/O) along with a cost-effective method. this technology is used in the administration of hybrid electric power sources, which include PV cell, turbines (wind), and grid-supportive devices. the novelty of this research lies in the precedence of solar PV, wind turbine, and storage system energy sources above the grid network. the grid network is only used in case of bad weather. this system can supply an average household with up to $\mathbf{4, 0 0 0}$ Wh of energy per day. In addition, by using an electrolyzing system, surplus unconventional energy produced during good weather conditions is used to produce hydrogen, which is well-suited for household cooking and heating purposes. Developing an intelligent economic strategy by using fuzzy technology to bolster improved energy management and optimization methods. the fuzzy logic software at the heart of this system has been written on the Arduino 2560 mega microcontroller. It is responsible for allocating events and considering all possible circumstances. this system has been developed using a flowchart that facilitates hybrid system management. In order to maintain uninterrupted housing, it is advisable to use strategies such as methodologies, a parametric search, and simulations to precisely characterize the system components that provide assistance to the power grid. the effectiveness of the recommended method is confirmed by the display of output directives generated by the electronic switches.

关键词： Fuzzy logic Wind Renewable energy sources Microcontrollers Optimization methods Software Power grids Wind turbines MATLAB Informatics

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Excavation of Time sliced and Cost based KDD for the lead generation and promotion on B2C/B2B Sales 7

Excavation of Time sliced and Cost based KDD for the lead ge...

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7th international conference on Advanced Computing and Communication Systems, ICACCS 2021

作者： Nm, Jency Rena Warrier, Gayathry S Arshey, M. Scms School of Engineering and Technology Department of Computer Science and Engineering

ISBN: (纸本)9781665405201

Fast advances in information gathering and capacity have empowered associations to collect huge measures of information and hence extracting the only relevant and useful information from large volumes of data is a challenging task. the conventional techniques for data analysis and evaluation cannot be utilized subsequently on the huge measure of the data-set and-so new methods were developed for mining data. Frequent pattern mining algorithms like Apriori, FP-Growth, etc. may sometimes miss the rare but important patterns of a database since they are dealing only with the number of times an item appears in the database. In business environments like retail shops or online markets, identifying the profit-generating items is more important than finding the items which are sold many times. the high utility item set mining with the time cube concept helps us to find the relevant, profit-generating item sets from the transactional data set by performing the calculations using the quantity that is purchased, total cost and unit gain of each item in the database. the concept of time cubes implemented here helps to efficiently deal with the temporal parts of the transactional data set. Considering total cost decides the frequent customer of particular product set. the proposed system is mainly applicable in online markets, FMCG Sectors, large retail stores, and manufacturing plants for improving the revenue by promoting the profit-generating item sets. © 2021 IEEE.

关键词： Profitability

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Mudahnya BM: A Context-Aware Mobile Cloud Learning Application Using Semantic-Based Approach

Mudahnya BM: A Context-Aware Mobile Cloud Learning Applicati...

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7th international conference on advances in Visual Informatics, IVIC 2021

作者： Muhammad, Sufri Admodisastro, Novia Osman, Hafeez Mohd Ali, Norhayati Faculty of Computer Science and Information Technology Department of Software Engineering and Information System Universiti Putra Malaysia Seri Kembangan Selangor43400 Malaysia

ISBN: (纸本)9783030902346

A great potential of various learning environment in mobile learning application can clearly be seen in current pandemic situation. the accessibility of the learning resources needs to be available from anywhere anytime despite having strong or poor internet connection. It has motivated researchers to imply context-aware capability in improving the accessibility of the learning resources. this paper presents a development process of Mudahnya BM mobile application that follows a fundamental concept of Mobile Cloud Learning (MCL). Mudahnya BM is an application to learn basic Malay language for learner 7–12 years old. the injection of extrinsic and intrinsic context-aware help the application to improve the reasoning process for finding available learning resources from service providers. Semantic-based approach is applied in the reasoning process. this study involved the end users for evaluation purposes. 33 randomized scenarios have been tested using One-Sample Wilcoxon Signed Rank test. the result shows a positive impact to the population. © 2021, Springer Nature Switzerland AG.

关键词： Semantics

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TELL ME: Design of an Intelligence-Empowered Recommendation System 11th

TELL ME: Design of an Intelligence-Empowered Recommendation ...

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11th international conference on computer science and its Applications, CSA 2019 and 14th KIPS international conference on Ubiquitous Information Technologies and Applications, CUTE 2019

作者： Lai, Kuan-Hua Yen, Neil Y. Hung, Jason C. School of Computer Science and Engineering University of Aizu Aizu-Wakamatsu Japan Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taichung Taiwan

ISBN: (纸本)9789811593420

With the advances in science and technology, the life becomes smarter and more convenient. In recent years, the Artificial intelligence (AI) is a popular topic. AI can be used in many areas such as healthcare, Automotive, Finance, etc. For instance, the smart phone could be a multi-function entity such as voice connecting, data storing, information displaying, etc. these are expected to provide more significant and precise function for each user based on personal requirement. this study, with the concern on high-quality service provision, seeks for the possibility in developing location-based service(s) based on the concept of anticipatory computing. We attempt to achieve the concept of request-free and realize the scenario of ‘act before you act.’ Hence, three main portions will be discussed. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Location based services

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Simulating Measurement Attacks in a Scada System Testbed 15th

Simulating Measurement Attacks in a Scada System Testbed

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15th IFIP WG 11.10 international conference on Critical Infrastructure Protection, ICCIP 2021

作者： Reutimann, Brandt Ray, Indrakshi Computer Science Colorado State University Fort CollinsCO United States

ISBN: (纸本)9783030935108

Industrial control systems are target-rich environments for cyber criminals, terrorists and advanced persistent threats. Researchers have investigated various types of industrial control systems in smart grids, gas pipelines and manufacturing facilities to understand how they can be compromised by cyber threats. However, the manner in which industrial control systems are attacked is domain-dependent. Testbeds are a necessary tool to model specific domains and understand potential attacks. this chapter discusses the development of a virtual supervisory control and data acquisition system testbed for gas systems and how it is used to simulate the impacts of measurement attacks. the testbed provides opportunities for researchers and domain experts to model, simulate and understand the behavior of a real-world gas system and respond to cyber attacks. © 2022, IFIP international Federation for Information Processing.

关键词： SCADA systems

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7th international conference on advances in Visual Informatics, IVIC 2021

7th International Conference on Advances in Visual Informati...

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7th international conference on advances in Visual Informatics, IVIC 2021

ISBN: (纸本)9783030902346

the proceedings contain 60 papers. the special focus in this conference is on advances in Visual Informatics. the topics include: Interaction Design for Digital Saron Musical Instruments Using Call and Response System and Rhythmic Emphasis Weighting Methods;a User Experience Model for Designing Educational Mobile Application;evidence-Based of Interactive Multimedia-Based Nutrition Education Package Efficacy on Obesity Outcomes through Game and Video Intervention;evidence-Based of Improved Electron Tomogram Segmentation and Visualization through High-Pass Domain Kernel in Bilateral Filter;VR-Based Relaxation therapy for Customer Service Staff: A Pilot Study;Fusion technology and Visualisation to Share STEM Data Using PETS Robots (i-COMEL) for Open Data Readiness Amongst Primary School Children;interactive Multimedia Kolb Experiential Learning Model Using Logistic Regression Algorithm to Improve Student Cognitive;performance Analysis of Machine Learning Techniques for Sentiment Analysis;national Sport Institute Case: Automated Data Migration Using Talend Open Studio with ‘Trickle Approach’;color Aesthetic Enhancement for Categorical Data Visualization;Mudahnya BM: A Context-Aware Mobile Cloud Learning Application Using Semantic-Based Approach;software Redocumentation Using Distributed Data Processing Technique to Support Program Understanding for Legacy System: A Proposed Approach;system Design and Usability Evaluation of Ghana Music Documentation System Using the System Usability Scale;static Indoor Pathfinding with Explicit Group Two-Parameter Over Relaxation Iterative Technique;use of Faceted Search: the Effect on Researchers;Sustainable Product Innovation Using Patent Mining and TRIZ;personalised Smart Mobility Model for Smart Movement During Pandemic Covid-19;intelligent Multi-cellular Network Connectivity for Internet of things Applications;ioT-Based System for Real-Time Swimming Pool Water Quality Monitoring.

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Crime Forecasting : A theoretical Approach

Crime Forecasting : A Theoretical Approach

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Recent advances and Innovations in Engineering (ICRAIE)

作者： Anuvarshini S R Deeksha Nidhi Deeksha Sree C Krishna Sowjanya K Department of Computer Science and Engineering CMR Institute of Technology Bengaluru India

Crime and its increase are detrimental to any society. High crime rates can affect the functioning of a city and its economy. the prediction and future forecasting of crime can help law enforcement officers curb crime in a city. there is a need for a better prediction system which intimates law enforcement regarding hot spots of crime in the city. Previous research shows a lower accuracy in crime prediction and forecasting using machine learning. therefore, this study includes the application of different Machine Learning models like, Decision Tree, Extra Tree Classifier, K- Nearest Neighbor, AdaBoost, Random Forest, Light Gradient Boosting and Gradient Boosting algorithms and time series analysis by Long Short Term Memory and Convolutional Neural Network, Auto Regressive Integrated Moving Average and Seasonal ARIMA to suit our *** performance of a fully convolutional neural network showed the most promising results. Moreover, identification of districts which have the most contribution to the total crime is also determined. this study is useful in assisting law enforcement in identification of districts with higher crime and future patterns of crime in the city of Boston.

关键词： Training Law enforcement Urban areas Time series analysis Boosting Safety Convolutional neural networks

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Zero-Shot Learning in Cybersecurity: A Paradigm Shift in Attack and Defense Strategies 8th

Zero-Shot Learning in Cybersecurity: A Paradigm Shift in Att...

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8th international conference on advances in Computing and Data sciences, ICACDS 2024

作者： Srivastava, Aviral Sanghavi, Priyansh Parmar, Viral Rani, Seema College of IST Pennsylvania State University University Park16803 United States School of Technology Pandit Deendayal Energy University Gujarat Gandhinagar382007 India Computer Science and Engineering Guru Jambheshwar University of Science and Technology Haryana Hisar India

ISBN: (纸本)9783031709050

this paper explores the application of zero-shot learning, a novel machine learning approach, in predicting and mitigating cybersecurity threats and defenses. Our research bridges the gap between the theory and practice of using zero-shot learning, a technique that allows models to adapt to unseen scenarios, in anticipating and managing cybersecurity threats. We propose new attack methodologies based on zero-shot learning and discuss the development of robust defense mechanisms. An interdisciplinary approach, combining social engineering, behavioral psychology, and AI governance, underpins our work. Our research also introduces a quantitative model to assess the impact of these emerging threats and a proof-of-concept prototype. In closing, we discuss ethical considerations and advocate for responsible AI practices and robust regulations to prevent misuse. this paper underscores the potential of zero-shot learning to revolutionize cybersecurity practices and preparations for future threats. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Zero-shot learning

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Content-Based Spam Classification of Academic E-mails: A Machine Learning Approach 1

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4th international conference on advances in Information Communication technology and Computing, AICTC 2022

作者： Iddrisu, Wahab Abdul Adjei-Gyabaa, Sylvester Kwasi Akoto, Isaac Department of Mathematics and Statistics Ghana Communication Technology University Accra Ghana Department of Computer Science Sunyani Technical University Sunyani Ghana Department of Mathematics and Statistics University of Energy and Natural Resources Sunyani Ghana

ISBN: (数字)9789811998881

ISBN: (纸本)9789811998874

In the academic environment, players have overstretched University faculty with less available time. the task of reading and deleting electronic mail (e-mail) spam tends to consume or steal the little available time they have at their disposal. Due to the spam issue, automated processes or methods for separating spam from valid emails are becoming important. Due to the unstructured nature of the material, additional features, and a vast number of documents, the process of automatically classifying spam email presents significant difficulties. Increasing usage of the e-mail spam directly affects the performance of these spam classifications with regards to the quality and speed based on the challenges stated above. Most of the recent algorithms consider only relevant features or characteristics for the classification of the e-mails as spam or legitimate. the main objective of this work was to use a machine-learning algorithm to detect and categorize e-mail messages of university faculty into spam and non-spam with the identification of the most occurring attributes that are contained in the messages. these attributes helped in the generation of a classification model based on the Random Forest algorithm. Exploratory analysis of the academic e-mails revealed that the most occurring attributes that are easily associated with spam messages included "your", "open access" and "remove". Five hundred decision trees were generated in the Random Forest Model, which had an excellent classification accuracy of 0.942 (94.2%). the performance of the model was compared with similar models based on the random forest algorithm. the comparative analysis revealed that classification accuracy differs depending on the type of e-mails used. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Machine learning

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