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Prediction of Irregular Bangladesh-EU Migration Trends Using Machine Learning Techniques

Prediction of Irregular Bangladesh-EU Migration Trends Using...

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International Conference on Advancement in Electrical and Electronic engineering (ICAEEE)

作者： Md. Shariful Islam Md Abdur Rahim Nitun Kumar Podder Md. Najmul Hossain Md Imran Hossain Dept. of Computer Science and Engineering Pabna University of Scence and Technology Pabna Bangladesh Dept. of Electrical Electronic and Communication Engineering Pabna University of Scence and Technology Pabna Bangladesh Dept. of Inormation and Communication Engineering Pabna University of Scence and Technology Pabna Bangladesh

ISBN: (数字)9798350388282

ISBN: (纸本)9798350388299

Remittances are important economic contributors to a countryâs economy. It has increased national savings, lowered foreign exchange limits, and helped balance payments and development budgets. Migrant workers are the main source of these remittance revenues. Many workers worldwide leave their homes and move to different parts of the world for overseas employment. These workers are authorized and have documentation of their country of origin and final destination. Besides, many workers have migrated illegally globally, particularly to European Union (EU) countries via marine routes. However, illegal immigration leads to a loss of national revenue due to non-payment of taxes and social security contributions and problems with living circumstances and legal issues. Therefore, this paper aims to present a time series forecast of irregular migrants in EU countries from Bangladesh over the next five years. We used five methods to analyze this forecasting: ARIMA (an autoregressive integrated moving average), XGBoost Series, Decision Tree, Feed Forward Neural Network, and CatBoost Regressor. In addition, we used data from the European Border and Coast Guard Agency to perform the time series forecast. A field intervention is carried out to assess the gender, age, education, socioeconomic level, and skill profile of migrant workers. Moreover, a few case studies of migrant workers and a survey were conducted to investigate the underlying causes of irregular migration. Finally, this study explains the underlying cause of irregular migration and its repercussions. It can provide some ideas for decreasing the loss of human life and property by reducing irregular migration to help take essential actions in the home and destination countries.

关键词： Analytical models Time series analysis Neural networks Education Europe Market research Data models

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An Artificial Intelligence based Machine Learning Approach for Automatic Blood Glucose Level Identification of Diabetes Patients

An Artificial Intelligence based Machine Learning Approach f...

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2023 International Conference on Disruptive Technologies, ICDT 2023

作者： Maguluri, Lakshmana Phaneendra Santhosh, K. Meenakshi, K. Farooqui, Muhammad Ahtesham Parveen Sultana, H. Saravanan, V. Department of Computer Science and Engineering Andhra Pradesh Guntur India Kombolcha Institute of Technology Wollo University Department of Mechatronics Ethiopia Cmr Institute of Technology Department of Mathematics Bengaluru Karnataka India Sam Global University Dept. of Computer Science & Engineering Madhya Pradesh Raisen India Vellore Institute of Technology School of Computer Science and Engineering Tamil Nadu Vellore India Dambi Dollo University Department of Computer Science Dambi Dollo Ethiopia

ISBN: (纸本)9798350323887

In general, treatments and medications for diabetics are usually prescribed based on the level of glucose-level in the human-blood. Blood glucose-level was calculated by performing two separate tests: before meals and after meals. The practical functions present in this test enable physicians to carry out appropriate treatment modalities. This paper introduces an improved method of running a machine learning system. Its main task is to accurately analyze the given input data and calculate the correct point of blood-glucose in the blood of diabetics. It was designed to do so and then list the appropriate control methods and drugs and share that data with the user in a paperless digital manner. Thus it is enough for patients to go to laboratories and do tests. Only their results will be calculated and sent to them for treatment. © 2023 IEEE.

关键词： Glucose

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Smart Modular Few-Shot Learning Framework Changes Classification of Signal Modulation

Smart Modular Few-Shot Learning Framework Changes Classifica...

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2023 International Conference on Data Science and Network Security, ICDSNS 2023

作者： Spoorthi, T. Tabassum, Husna Devika, S.V. Rao, K. B. V. Brahma Ramachandra, A.C. Gst Gitam University Bengaluru Campus Dept. of Cse Bengaluru India Hkbk College of Engineering Dept. of Cse Bengaluru India Hyderabad Institute of Technology and Management Department of Ece Hyderabad India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Vaddeswaram India Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350301595

The purpose of this research is to categorise signal modulation using few-shot learning. The first approach is an intelligent, modular, few-shot learning framework. This system's two components are IQF and 1D-SFP, and it also has a task-driven network design. The 1D-SFP module is responsible for obtaining high-level characteristics from the raw signal, while the IQF module is in charge of retrieving low-level information. The number of 1D-SFP modules required for processing a large amount of data is calculated by studying the correlation in the hidden layer. We evaluate the suggested method using a publicly available dataset and show that it beats standard strategies in terms of accuracy. It can also learn from a small number of instances and is adaptable enough to handle innovative modulation schemes. This enables it to be used in wireless networks for data transmission and reception. The second approach uses a graph convolutional network (GCN) to calculate how many 1D-SFP modules should be integrated into a neural network architecture for a particular job. On benchmark datasets, the presented frameworks outperformed a range of state-of-the-art, conventional methodologies. Both approaches perform preprocessing, representation learning, and classification using their own distinct algorithmic frameworks. The presented strategies have the potential to increase signal modulation classification precision and efficiency in cognitive radios and other kinds of wireless communication. These gains are possible because of the potential of these techniques. © 2023 IEEE.

关键词： Learning systems

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Software Effort Estimation using ANN (Back Propagation)

Software Effort Estimation using ANN (Back Propagation)

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International Conference on Computing Methodologies and Communication (ICCMC)

作者： Ravi Kumar B N Yeresime Suresh Dept. of Computer Science and Engineering BMS Institute of Technology and Management Bangalore India Dept. of Computer Science and Engineering Ballari Institute of Technology and Management Ballari India

Project managers often use Effort Estimating strategies to manage the human resources of current or upcoming software projects. Prior to project implementation, cost, time, and personnel estimation are basically necessary. For every project of software, getting an accuracy in Effort Estimation has always been difficult. In case of this study, estimating the labor involved in developing software determined using a Back Propagation Model. This model's goal is to investigate the capabilities and potential uses of utilizing Artificial Neural Networks (ANN) as a tool for forecasting the effort required for software development. In order to estimate the software work, we are attempting to implement a machine learning technique in this research. Out of all machine learning methods, we are applying an algorithm based on Artificial Neural Networks that is Back propagation. The Desharnais dataset, a well-known publicly available dataset for estimation of software effort, is used to test the approach. The performance and accuracy of the tested model have been evaluated using three metrics: MMRE, MRE, and Pred (0.25). In the sections below that follows, I explain the algorithm and its results.

关键词： Backpropagation Computational modeling Software algorithms Estimation Artificial neural networks Machine learning Predictive models

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Simulating and Optimizing of Compact Modified Rectangular Shape Microstrip Antenna for UWB Applications 4

Simulating and Optimizing of Compact Modified Rectangular Sh...

引用

4th International Conference on Current Research in engineering and Science Applications, ICCRESA 2022

作者： Abdulkareem, Jinan Jabbar Abdulkareem, Hanan Jabbar Yousif, Lujain Nazeeh Abbood, Zainab Ali Dept. Technical Engineering College Al-Farahidi Universityn Baghdad Iraq Dept. Medical Instrumentation Al-Esraa University College Baghdad Iraq Dept. Computer Technology Engineering Al-Esraa University College Baghdad Iraq

ISBN: (纸本)9798350334944

Ultra-wideband (UWB) is a communication technology introduced for short-range communication. This technology employs radio frequency waves to enable devices to interact with each other. In this paper, an altered rectangular microstrip antenna is introduced and designed for UWB applications. The microstrip line feed technique is applied to feed the simulated antenna to ensure the optimum impedance matching. The proposed antenna is simulated using the CST software's finite integration technique. The simulated antenna covers operating frequency bands in the range of 3.66 - 21.21 GHz with a return loss of less than -10dB in the operation band, and an antenna gain variates between 2.48 to 4.85dBi in the operation band. © 2022 IEEE.

关键词： Microstrip antennas

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SpecWav-Attack: Leveraging Spectrogram Resizing and Wav2Vec 2.0 for Attacking Anonymized Speech

SpecWav-Attack: Leveraging Spectrogram Resizing and Wav2Vec ...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yuqi Li Yuanzhong Zheng Zhongtian Guo Yaoxuan Wang Jianjun Yin Haojun Fei Dept. of Large Language Model Qifu Technology Shanghai China Dept. of Computer Science Fudan University Shanghai China School Of Information Science And Technology Fudan University Shanghai China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

This paper presents SpecWav-Attack, an adversarial model for detecting speakers in anonymized speech. It leverages Wav2Vec2 for feature extraction [1] and incorporates spectrogram resizing and incremental training for improved performance. Evaluated on librispeech-dev and librispeech-test, SpecWav-Attack outperforms conventional attacks, revealing vulnerabilities in anonymized speech systems and emphasizing the need for stronger defenses, benchmarked against the ICASSP 2025 Attacker Challenge [2].

关键词： Training Error analysis Benchmark testing Feature extraction Acoustics Speech processing Spectrogram

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Paths Planning for Agricultural Robots: Recent Development, Taxonomy, Challenges, and Opportunities for Future Research 20

Paths Planning for Agricultural Robots: Recent Development, ...

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20th IEEE Student Conference on Research and Development, SCOReD 2022

作者： Yahaya, Zimit Aminu Buyamin, Salinda Chiroma, Haruna Azimi Mahmud, Mohd Saiful Hassan, Fazilah H Badi, Abubaker Ahmed Universiti Teknologi Dept. of Control and Mechatronics Engineering Malaysia University of Hafr Albatin Dept. of Computer Science Technology Saudi Arabia Universiti Teknologi Malaysia Malaysia

ISBN: (数字)9781665474887

ISBN: (纸本)9781665474887

The world is currently experiencing population explosion, and it has been forecast that the population would reach nine billion by the year 2050. This rapid population growth is accompanied with new challenges, including high demand for food supply, which may lead to food crises. Contemporary agricultural methods and resources cannot meet the forecast food demand. Precision agriculture is one of the best ways to meet this demand, and using agricultural robots is an important aspect of it. Many researchers have been conducting studies on the application of robots in agricultural tasks such as farm clearance, seeding, seedling, spraying, fertilization, and harvesting. This paper presents a comprehensive review on path planning techniques for agricultural robots. it focuses on different types of agricultural robots and path plans in use. It also provides taxonomy of agricultural robot path plans, metadata analysis, and deep insights into the recent developments in the research area, while pointing out the challenges being faced and possible future solutions. This article may serve as a guide to early career researchers with interest in agricultural robots to easily understand the current developments and the future research focus in this field. © 2022 IEEE.

关键词： Agricultural robots

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IoT-based Smart Water Consumption Monitoring System for Residential Complex

IoT-based Smart Water Consumption Monitoring System for Resi...

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information and Communication technology (ICICT), International Conference on

作者： Imtiaz Ahamed Md Liakot Ali Nazmus Salehin Institute of Information and Communication Technology Bangladesh University of Engineering and Technology Dhaka Bangladesh Dept. of Electrical and Electronic Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh

ISBN: (数字)9798331508227

ISBN: (纸本)9798331508234

Freshwater scarcity is a pressing global matter right now and the importance of putting more focus on monitoring and conserving water resources is growing. This research presents the development of a cost-effective, scalable, easy to maintain IoT-based water consumption monitoring system for residential buildings using Long Range Communication technology (LoRa). The key components of the system include IoT-enabled smart water meters installed in each residential unit with LoRa communication modules for long-range, low-power communication which enables data transmission over considerable distances with minimal energy consumption, and an open-source IoT analytics platform called ThingSpeak. The water sensors capture real-time data on water usage, which is then transmitted to ThingSpeak through a microcontroller and WiFi module using LoRa communication. Sample tests demonstrate the system's effectiveness in measuring water usage and flow rate at a given time, offering real-time visualization and user engagement, making it an essential tool for promoting sustainable water management practices.

关键词： Buildings LoRa Pressing Water conservation Real-time systems Time measurement Internet of Things Monitoring Water resources Wireless fidelity

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A Comprehensive Study on Accident Detection Approaches

A Comprehensive Study on Accident Detection Approaches

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2022 IEEE Delhi Section Conference, DELCON 2022

作者： Donepudi, Harshini S Saxena, Mayank Yun, Yeo Xiong Jansirani, Preethaa Sethi, Simardeep Singh Banik, Barnali Gupta Andhra University Dept. of Computer Science Sys Engineering Andhra Pradesh Visakhapatnam India University of Allahabad Dept. of Computer Science and Engineering Uttar Pradesh Allahabad India National University of Singapore Dept. of Engineering Science Singapore Singapore College of Engineering Guindy Anna University Dept. of Electronics and Comm. Engineering Chennai India Guru Tegh Bahadur Institute of Technology Dept. of Computer Science and Engineering New Delhi India C. R. Rao Advanced Institute of Mathematics Statistics Computer Science University of Hyderabad Telangana India

ISBN: (纸本)9781665458832

Accident-prone detection predicts the likelihood of a vehicle getting into an accident. Major contributing factors to road accidents include distracted driving, unsafe road infrastructures, and social sensitivity features, but not only these factors. The data collected by monitoring the traffic is used to model and test the detection systems. This behaviour is usually identified utilising exploratory data analysis of historical data based on previous accidents, traffic patterns, the infrastructure of the roads and other miscellaneous factors. In this paper, existing techniques are studied in detail to weigh the benefits and costs of implementing different detection models. This study aims to determine how various model(s) can be implemented to ensure a safe commute that can eventually lead to real-time alerts to prevent fatal accidents. The notion of lane-less and lane-based traffic is also considered. Specifically, a Long Short-Term Memory (LSTM) network has been reviewed, and notable enhancements have been suggested. After arriving at the conclusions, the future scope has also been discussed. © 2022 IEEE.

关键词： Data mining

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Image Denoising and Enhancement for Planktonic Foraminifera Fossil

Image Denoising and Enhancement for Planktonic Foraminifera ...

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International Conference on Electrical engineering and computer Science (ICECOS)

作者： Muhammad Farid Ghazali Silmi Fauziati Igi Ardiyanto Akmaluddin R.M. Benediktus Suryo W Putu Desyanndana Dept. of Electrical Engineering and Information Technology Faculty of Engineering University of Gajah Mada Yogyakarta Indonesia Dept. of Geological Engineering Faculty of Engineering University of Gajah Mada Yogyakarta Indonesia

ISBN: (数字)9798350368253

ISBN: (纸本)9798350368260

Foraminifera are marine microfossils encased in multi-layered shells and serve as crucial indicators in geological, paleontological, and environmental studies. They are sensitive to environmental factors and provide valuable insights into past conditions such as sea temperature, dept., and oxygen levels. However, microscopic images of foraminifera often exhibit imperfections like blur, noise, and insufficient detail, which complicate accurate analysis. This study addresses these challenges through advanced image processing techniques to enhance image quality. The research evaluates and compares various image enhancement methods including Unsharp Masking (USM), Local Laplacian Filter (LLF), Histogram Equalization (HE), Adaptive Histogram Equalization (AHE), Single-Scale Retinex (SSR), and Multi-Scale Retinex (MSR). Quantitative metrics such as MSE, RMSE, PSNR, and SSIM are used to assess the effectiveness of each technique, while qualitative parameters include image quality, noise, color contrast, and texture detail. The USM method yields the highest SSIM value of 0.3868 and the lowest MSE (5517.34) and RMSE (74.28), indicating a minimal difference from the ground truth. However, qualitative evaluations support the combination of LLF with AHE, yielding the highest SSIM (0.3559) among LLF methods. LLF combined with AHE enhances image clarity, brightness, and structural fidelity, essential for accurate analysis and identification.

关键词： Image quality Temperature sensors Histograms Laplace equations Accuracy Temperature Microscopy Adaptive equalizers Image enhancement Ocean temperature

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