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检索条件"任意字段=2022 International Conference on Data Science and Intelligent Computing, ICDSIC 2022"

共 23138 条记录，以下是11-20 订阅

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intelligent Drone-based IoT Technology for Smart Agriculture System

Intelligent Drone-based IoT Technology for Smart Agriculture...

引用

2022 international conference on data science and intelligent computing, icdsic 2022

作者： Al-Shareeda, Mahmood A. Manickam, Selvakumar Saare, Murtaja Ali National Advanced IPv6 Center Universiti Sains Malaysia Penang Malaysia Shatt Al-Arab University College Computer Technology Engineering Basrah Iraq

ISBN: (纸本)9798350334883

Drones and the Internet of Things (IoT) are two emerging technologies used in agriculture fields, which replace traditional farming practices with a modern era of rigorous cultivation. In this paper, we propose a smart agriculture system for new farms and farms that practice crop rotation by using drones and IoT sensors. Our proposal includes farm condition monitoring, pesticide/fertilizer spraying, drone seeding, and soil sampling. Additionally, our proposal not only uses Zigbee technology for the connection among the ground sensors and the drones but also applies Long Range (LoRa) technology to enable the gateway to transmit and store farm data in the cloud for data analysis and storage. The drone in our proposed collects farm data (e.g., pH value and soil humidity) from ground sensors that the farmer has already plugged into the farm. Finally, we anticipate that our proposal will increase crop output rates and make farming tasks more automated. © 2022 IEEE.

关键词： Internet of things

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An Analytical Study of Iraqi Supermarket Materials using the RapidMiner Tools

An Analytical Study of Iraqi Supermarket Materials using the...

引用

2022 international conference on data science and intelligent computing, icdsic 2022

作者： Ali, Mustafa A. Naji, Emtiaz A. Abdulhakeem, Ali H. Alasadi, Mustafa K. Aaied, Ali Computer Center University of Kerbala Karbala Iraq College of Law University of Warith Al-Anbiyaa Karbala Iraq College of Computer Science University of Sumer Thi Qar Iraq

ISBN: (纸本)9798350334883

In our increasingly interconnected world and with the constant development of information technology and database technology. In addition to the rapid increase in the speed of internet connections and the fact that the data has shown explosive growth. However, in the countenance of huge amounts of data, individuals are often jumbled and unable to discover the hidden knowledge and the relations that govern these data, resulting in a waste of resources. This research uses the Rapid Miner tool to analyze the data of the supermarket in Iraq, analyze the products by using the Association rule algorithm, and provide instances of modeling and marketing recommendations, which have strong practical value that could even extend to the health of the customer. Likewise, could know is there a link between the food's consumers look at and what they choose. All that could be used as a basis for making decisions about marketing activities such product placements, bundling sales can be carried out, and promotional pricing to obtain more total profits. Further studies using different techniques are required to give regulation and development to this area. © 2022 IEEE.

关键词： data mining

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Intent Classification Using Machine Learning Algorithms and Augmented data

Intent Classification Using Machine Learning Algorithms and ...

引用

2022 international conference on data science and intelligent computing, icdsic 2022

作者： Al-Tuama, Alaa T. Nasrawi, Dhamyaa A. College of Computer Science and Information Technology University of Kerbala Karbala Iraq

ISBN: (纸本)9798350334883

An essential step in a conversational agent is an intent classification of user-generated text input. The purpose of building the intent classifier for a chatbot is to understand the intention of user queries to respond fast and accurately. Robust chatbots necessitate more utterances for an improved training model. Nevertheless, acquiring and annotating data is time-consuming and expensive. This paper investigates machine learning techniques and data augmentation for addressing intent classification. Experiments were conducted on office product's question answering of Amazon using Random Forest, Multinomial Naïve Bayes, Logistic Regression, and Support Vector Machine (SVM). Contextual word embedding with BERT was used for generating new synonym utterances. The main experiments are the comparison of the performance of these methods after augmenting new data. In general, SVM and random forest yield comparable results. Followed by logistic regression. However, the f1 score of the multinomial naïve base is the lowest. Additionally, we discovered that augmenting new utterances had a simple effect on the performance of models. © 2022 IEEE.

关键词： Logistic regression

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A Survey on Detecting Vandalism in Crowdsourcing Models

A Survey on Detecting Vandalism in Crowdsourcing Models

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2022 international conference on data science and intelligent computing, icdsic 2022

作者： Mohammed Ali, Azha Talal Alwan, Huda Fadhil Al-Shakarchy, Noor Dhia College of Computer Science & Information Technology University of Kerbala Computer Science Department Kerbala Iraq

ISBN: (纸本)9798350334883

Crowdsourcing is a common term for collaborative environments that include a group of workers participating in the content of these platforms to create knowledge. The most important and well-known crowdsourcing platforms are Amazon's Mechanical Turk, Kaggle, Design99, and Wikipedia. Wikipedia is one of the most vital crowdsourcing models where users are contributing in creating and editing articles. Thus, leading to significant expansion in the encyclopedia that made it one of the most visited sites for getting information or using it as a knowledge base for many applications such as Chatbots. All These characteristics have come with another aspect through which users can sabotage the content of the encyclopedia that is known as vandalism. Vandalism is any attempt to modify the article in a way that negatively affects the article's quality. Vandalism is considered as one of the five layers model that constructed for cyber threads, which is known as cyber vandalism. Instead of misusing or stealing data, cyber vandalism involves all actions for damaging or destroying it. This paper presents a comprehensive survey that deals with various aspects of the vandalism detection problem in a crowdsourcing model-Wikipedia © 2022 IEEE.

关键词： Crowdsourcing

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Comparison of Sentiment Analysis Techniques for Twitter posts classification

Comparison of Sentiment Analysis Techniques for Twitter post...

引用

2022 international conference on data science and intelligent computing, icdsic 2022

作者： Osman, Ismail Namiq Husien, Idress Mohammed University of Kirkuk Department of Computer Science Kirkuk Iraq

ISBN: (纸本)9798350334883

Social media is the most popular and fast data-generating application on the global network, boosting content research. With this kind of data readily available on the internet, sentiment analysis is a fundamental approach that serves as the foundation for many natural language applications. Sentiment analysis is the best effective technique for determining if an evaluation is positive, negative, or neutral. This article analyses seven alternative models of emotion methods. Execute sentiment analysis in this research with machine learning and deep learning techniques. The sentiment of tweets in all datasets evaluates using all available methodologies. Convolutional Neural Network attained an accuracy of 97.28 percent for 3-class classification on the vaccination dataset, while the second-highest accuracy on the same dataset was 96.85 percent. This research seeks to compare the optimal accuracy of a machine learning or deep learning model based on different dataset extraction methods. The dataset studies various issues and differentiates the file size or the number of tweets in each dataset from the smallest to the largest size. When we evaluated different algorithms in this study, our goal was to see how the number of tweets affected the accuracy of the algorithms, and we obtained a dataset about Blockchain from Twitter. © 2022 IEEE.

关键词： Sentiment analysis

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A Survey of SQL Injection Attacks, Their Methods, and Prevention Techniques

A Survey of SQL Injection Attacks, Their Methods, and Preven...

引用

2022 international conference on data science and intelligent computing, icdsic 2022

作者： Al-Shareeda, Mahmood A. Manickam, Selvakumar Sari, Sari Ali National Advanced IPv6 Center Universiti Sains Malaysia Penang Malaysia Universiti Tun Hussein Onn Malaysia Computer Science and Information Technology Johor Malaysia

ISBN: (纸本)9798350334883

The vast majority of web applications' databases are vulnerable to SQL Query Injection Attacks, which let clients directly insert sensitive data. They carry out their operations by inserting nefarious SQL Injection Query codes into the client-side web API, which allows them to retrieve all the confidential and sensitive data from the database. SQL injection is a technique where web attackers post the malicious SQL injection Query, occupying the full admin login access of the web database, for malicious Input data modifications or deletion of the existing user User's Information. The goal of this technique is to change the structure and behavior of the query that the computer programmer has proposed. The examination of SQL injections, which target a Web application's front end to get access to its back-end database, It will address the implications, categorization, and techniques of these attacks. Then, two tactics have chosen to defend the database against SQL injection assaults. As a consequence, the design and development of any new SQL injection attacks for web application may use this work as a guide and reference © 2022 IEEE.

关键词： Sensitive data

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Path Planning for an Autonomous Mobile Robot Using Red Fox Optimization Algorithm

Path Planning for an Autonomous Mobile Robot Using Red Fox O...

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2022 international conference on data science and intelligent computing, icdsic 2022

作者： Ketafa, Fetoh H. Al-Darraji, Salah College of Computer Science and Information Technology Dept. Computer Science Basrah Iraq College of Education for Pure Sciences Dept Computer Science Basrah Iraq

ISBN: (纸本)9798350334883

Path planning is a key challenge in the study of autonomous mobile robots. This paper describes a new bio-inspired optimization method known as the Red Fox Optimization algorithm, which generates a path free of collision for mobile autonomous robots in a known environment with static barriers. The actions of the red fox population in nature served as inspiration for this algorithm. Foxes have created a very successful hunting system that comprises two distinct phases. The first is carrying out a worldwide search, and the second is a local search. Global search behavior was implemented to determine the optimum collision-free route between starting position and the goal position. The algorithm was tested through a simulation in a range of static environments. The suggested algorithm demonstrates that the robot can create an ideal semi-smooth path by reducing the number of nodes and successfully navigating to its objective by avoiding obstacles. © 2022 IEEE.

关键词： Motion planning

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intelligent Control for Obstacle Avoidance in the Self-Driving Car

Intelligent Control for Obstacle Avoidance in the Self-Drivi...

引用

2022 international conference on data science and intelligent computing, icdsic 2022

作者： Abd-Alrasool, Fatima M. Al-Moadhen, Ahmed A. Kamil, Haider G. University of Kerbala Department of Electrical and Electronic Engineering Karbala Iraq Alsafwa University College Department of Computer Engineering Techniques Karbala Iraq

ISBN: (纸本)9798350334883

The keys to autonomous car accident avoidance in crucial traffic settings are motion planning and tracker control. It necessitates not just system operation but also reliable real-time. We merged an autonomous vehicle's motion planning and tracking control system in this paper to provide path planning and tracking for avoiding obstacles. The motion planning is based on a combination of A∗ and potential function algorithms. The Tracking Control Module is designed based on model predictive control (MPC) using a vehicle kinematics model and neural network to set the steering angle value. The simulation shows that the scheme can generate smooth paths that can be chosen as references to the console. In addition, it is shown by the results that the car in this method can track the reference path even at sharp angles. The maximum vehicle stopping error at the target is less than 0.1 m when the vehicle's desired speed is 40 km/h, and the maximum vehicle stopping error at the target is about 0.3 m when the desired speed of the vehicle is 120 km/h. © 2022 IEEE.

关键词： Model predictive control

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A Review Paper of Model Based Collaborative Filtering Techniques

A Review Paper of Model Based Collaborative Filtering Techni...

引用

2022 international conference on data science and intelligent computing, icdsic 2022

作者： Al-Mani, Inas Amjed Al-Sabaawi, Ali M. Ahmed Hussien, Mohsin Hasan Alhadbaa University Faculty of Law Mosul Iraq Nineveh University Ministry of Education Gifted Student School Nineveh Faculty of Information Technology Mosul Iraq University of Kerbala Faculty of Computer Science and It Kerbala Iraq

ISBN: (纸本)9798350334883

The development of Web 2.0 has seen a growth in rapid data and has caused an information overload problem. Recently, collaborative filtering of Recommendation System (CFRS) has attracted many researchers to handle this problem. Several survey papers have been proposed on CFRS, which concentrate on specific aspects of RSs, such as explanations of various challenges, methods or supported sources of RSs, none of them includes all of these aspects in one paper. Thus, this study aims to overcome the aforementioned limitation and collect the most significant aspects of CFRS in one paper to facilitate the researchers' tasks. First, the most dominant approaches involving the data mining methods are presented. Second, seven different challenges that are affect the prediction performance negatively are illustrated, including data sparsity, cold-start, scalability, synonymy, privacy-preserving, gray sheep users, and shilling attacks. Eventually, recent research directions such as social-based, session-based, multi-criteria and mobile-based were highlighted. © 2022 IEEE.

关键词： Recommender systems

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Secure Wireless Sensor Network Authentication by Utilized Modified SHA3 Hash Algorithm

Secure Wireless Sensor Network Authentication by Utilized Mo...

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2022 international conference on data science and intelligent computing, icdsic 2022

作者： Jafer, Azhar Sadiq Hussein, Khalid A. Naif, Jolan Rokan College of Education Mustanisiryah University Department of Computer Science Baghdad Iraq Iraqi Commission for Computers & Informatics Informatics Institute for Postgraduate Studies Baghdad Iraq

ISBN: (纸本)9798350334883

Wireless Sensor Network is an integration between software and hardware network that makes use a number of sensors to identify physical phenomena. However, WSN is easily attacked by attackers because WSNs uses wireless communications together with their insufficient tamper resistance. Commonly, sensor nodes are more concerned regarding two major security problems which are node authentication and the privacy preserving. A well-structured authentication method is able to be sure that not any unauthorized node can fraudulently participate and obtain important information from WSNs. Hence, many schemes have been proposed to protect communications in WSNs by improving security of authentication. In this work we intended to improve password protection through authentication process by using Modified SHA3 that combined Chaotic maps and SHA-3 hash algorithm to create a hybrid method that have advantage of these techniques. The proposed model is also have been implemented on hardware to simulate real operation © 2022 IEEE.

关键词： Authentication

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