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检索条件"丛书名=Lecture Notes in Networks and Systems"

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Development of Multivariate Stock Prediction System Using N-Hits and N-Beats 1

引用

7th Computational Methods in systems and Software, CoMeSySo 2023

作者： Jeffrey, Nathanael Santoso Gunawan, Alexander Agung Kurniawan, Aditya Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9783031548208

ISBN: (纸本)9783031548192

The capital market serves as a pivotal hub within a nation’s financial ecosystem, facilitating the exchange of stocks and securities. It assumes a paramount role in propelling the country’s economic growth and development. Profitable decisions in the capital market are frequently encountered;nevertheless, the intricacy lies in the challenge of accurately forecasting unpredictable fluctuations in stock prices. The analysis and forecasting of stock price movements have emerged as a highly sought-after area of research. The forecasting of stock price movements can be effectively categorized into two primary domains: technical analysis and fundamental analysis. Time series analysis, commonly referred to as technical analysis in the realm of stock market analysis, involves the meticulous examination of a stock’s price movements over a specific period. The forecasting technique employed in this study involves the analysis of Multivariate time series data using the advanced Neural Hierarchical Interpolation for Time Series Forecasting (N-HiTS) methodology. Based on the findings of the conducted research, this methodology exhibits commendable predictive efficacy in both the short and medium time horizons. Moreover, it demonstrates a notable ability to accurately forecast long-term stock patterns. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Financial markets

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引用

5th International Conference on Data and Information Sciences, ICDIS 2023

作者： Sharma, Bhanu Prakash Purwar, Ravindra Kumar USICT Guru Gobind Singh Indraprastha University Delhi India

ISBN: (数字)9789819969067

ISBN: (纸本)9789819969050

Mammogram imaging is economical, easily available, non-invasive and preferred for breast cancer detection. This paper proposes and tests a new feature vector based on the sum of Euclidean distances of similar subsequent pixels on various well-known classifiers. The preprocessed and augmented region of interest images extracted from the Mammographic Image Analysis Society (MIAS) dataset are used for performance evaluation. The classifier’s input data is balanced by randomly selecting 2000 images from each normal, benign and malignant categories. On an Ensemble Subspace KNN classifier using a tenfold cross-validation approach, it achieved good sensitivity/recall, specificity, precision and F1-scores along with a classification accuracy of 98.4%. This technique can be used for regular breast screening for early-stage breast cancer detection and breast abnormalities identification. It can prioritize mammograms for further analysis as well as provides an opinion to the radiologists in decision-making. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Image classification

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Bridging the Physical and Virtual Worlds: A Hand Tracking Gesture Recognition System for XR Applications 1

引用

32nd International Conference on Organization and Technology of Maintenance, OTO 2023

作者： Fumić, Matija Livada, Časlav Faculty of Electrical Engineering Computer Science and Information Technology Osijek Josip Juraj Strossmayer University in Osijek Kneza Trpimira 2B Osijek31000 Croatia

ISBN: (数字)9783031514944

ISBN: (纸本)9783031514937

Extended reality (XR) is a term that encompasses augmented reality (AR), virtual reality (VR), and mixed reality (MR). These technologies allow users to interact with digital content in immersive and realistic ways. One of the challenges of XR is to provide natural and intuitive ways to control and manipulate the virtual environment. This paper presents the development of a gesture recognition system for hand tracking in extended reality technologies (XR) and its practical applications. The system uses a gesture definition language that allows the user to create custom gestures based on the hand skeleton model. The system was implemented using the Oculus Quest 2 device and the Oculus SDK in the Unity game engine and is compatible with all devices that support hand tracking. The gesture recognition system was implemented using a three-bone thumb and little finger model that is compatible with all hand models that contain four bones. The implementation of this gesture recognition system in XR has several benefits, including increased immersion, improved interaction with virtual objects, and reduced physical fatigue compared to traditional input methods such as controllers or keyboards. This system provides users with a more intuitive and natural way to interact with their virtual environment. Overall, this work demonstrates the feasibility and potential of integrating gesture recognition into XR technologies and its ability to enhance user experience and interaction. The system presented in this work can serve as a foundation for future developments in this area, with potential applications in gaming, education, healthcare, and other fields. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Augmented reality

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Directional Edge Coding for Facial Expression Recognition System 1

引用

1st International Conference on Machine Intelligence for Research and Innovations, MAiTRI 2023

作者： Sandya, Pagadala Subbareddy, K. Venkata Nirmala Devi, L. Srividya, P. ECE Department Osmania University Hyderabad India

ISBN: (数字)9789819981298

ISBN: (纸本)9789819981281

Because the discriminative edges cannot currently be encoded, the local appearance-based texture descriptors used in facial expression recognition are only partially accurate. The main cause is the existence of noise-induced distortion and weak edges. We suggest a new local texture descriptor called as Weighted Directional Edge Coding for facial expression recognition system (DEC-FERS) to solve these issues instead of using the traditional local descriptors. DEC-FERS looks at neighboring pixels support for determining facial expression attributes including edges, corners, lines, and curved edges. DEC-FERS extracts weaker edge responses through edge detection masks and discards them after encoding only more robust edge responses. Robinson Compass Mask and Kirsch Compass Mask were two makes used for edge detection considered for the extraction of edge features. In addition, the DEC-FERS lessens the redundancy by removing redundant pixels those won’t have any contribution for center pixel. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Pixels

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Analyzing the Performance Variations of Naive Bayes, Linear SVM, and Random Forest for Spam Detection: A Comprehensive Study on the Spam or Ham" Dataset 1

引用

5th International Conference on Computer and Communication Technologies, IC3T 2023

作者： Ojha, Bhawna Yadav, Pradeep Arora, Rakhi Dixit, Nitin Dubey, Gaurav Shakyawar, Khemchand ITM-Institute of Technology and Management Gwalior India

ISBN: (数字)9789819997046

ISBN: (纸本)9789819997039

Spam detection is the process of identifying and filtering unsolicited or unwanted messages, often referred to as spam, from legitimate or desired messages. It is an important task in email systems, messaging platforms, and other communication channels to protect users from unwanted or potentially harmful content. The performance of Naive Bayes, Linear SVM, and Random Forest classification machine learning algorithms on the "Spam or Ham" dataset was evaluated using various metrics, including accuracy, precision, recall, and F1 score. The results indicate that all three classifiers are suitable for this dataset, but Naive Bayes outperforms Random Forest and Linear SVM in terms of precision, recall, and F1 score. This suggests that Naive Bayes can accurately classify spam messages while minimizing the number of false positives. The optimal classifier will depend on features such as dataset size, the specific business problem, and available computing resources. However, based on this specific experiment’s results, Naive Bayes appears to be a good choice for classifying spam messages. The accuracy of 0.98 is achieved by Naive Bayes algorithm. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Support vector machines

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Springback Prediction Using Gated Recurrent Unit and Data Augmentation 1

引用

International Conference on Intelligent Manufacturing and Robotics, ICIMR 2023

作者： Chen, Du Coenen, Frans Hai, Yang Oscoz, Mariluz Penalva Nguyen, Anh Department of Computer Science The University of Liverpool LiverpoolL693BX United Kingdom 9 Chengxin Avenue Nanjing21000 China Parque Cientıfico Parque Cientıfico y Tecnologico de Gipuzkoa Donostia-San Sebastian20009 Spain

ISBN: (数字)9789819984985

ISBN: (纸本)9789819984978

Artificial intelligence (AI) has been widely used in manufacturing, healthcare, sports, finance and other fields to model nonlinearities and make reliable predictions. In manufacturing, AI has been applied to improve processes, reduce costs and increase reliability. A new manufacturing process enhanced by AI is single point incremental forming (SPIF), a technique that uses a computer numerical control (CNC) machine to incrementally feed a metal sheet or polymer blank. However, achieving the geometric accuracy of the process is still of primary challenge due to the impact of springback. One of the most common solutions is toolpath correction. In this paper, we proposed a mechanism to capture local geometry using a novel point series representation, which then forms a general global geometry information. Each point series can then be associated with a predicted springback value and learns using deep learning. In particular, this article proposes the use of data augmentation to solve the problem of insufficient data and enable deep learning models to achieve better performance. Intensive experimental results show that we achieved the best R2 or "coefficient of determination" of 0.9228 compared to recent methods. We show that the proposed method provides a realistic solution to the current limitations of SPIF. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Deep learning

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Exploring the Extremes of Two-Layer Convolutional Autoencoders Architecture in Image Inpainting 6th

Exploring the Extremes of Two-Layer Convolutional Autoenco...

引用

6th conference on Computing systems and Applications, CSA 2024

作者： Azri, Youcef Amamra, Abdenour Amara, Yacine Ourghi, Fethi Ecole Militaire Polytechnique Bordj El-Bahri BP 17 Algiers Algeria

ISBN: (纸本)9783031718472

Inpainting, the process of filling in missing or damaged regions of an image, has witnessed significant progress with the advent of deep learning, particularly neural networks. This investigation delves into the outermost capabilities of two-layer Convolutional Autoencoders (2L-CAEs) architectures applied to image inpainting. The study scrutinizes the boundaries of performance and feasibility within this specific neural network configuration. The overarching objective is to provide an intricate understanding of the potential and limitations inherent in pushing a 2L-CAE architecture to its extremes, particularly when tasked with the intricate process of mending missing or impaired regions within an image. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Convolution

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Machine Learning Models for Human Activity Recognition: A Comparative Study 1

引用

2nd International Conference on Advances in Data-driven Computing and Intelligent systems, ADCIS 2023

作者： Sheoran, Anshul Boora, Ritu Jangra, Manisha Guru Jambheshwar University of Science and Technology Hisar India

ISBN: (数字)9789819995219

ISBN: (纸本)9789819995202

With the advancements in machine learning, human activity recognition has found its applications in several emerging areas such as robotics healthcare, surveillance, smart environment etc. This paper aims to study and evaluate the performance of some popularly used machine learning algorithms in classifying human activities. We have selected K-NN, SVM and XGBoost methods in this study and the performance of the methods has been evaluated for 19 different activities which were performed by eight random persons. The required data was recorded using 5 MTx 3-DOF orientation trackers. The raw data was processed before feature extraction and then fed as input to the machine learning models. On performance comparison of these methods, it has been found that the SVM method when implemented with a polynomial kernel, outperforms the other state-of-the-art methods. It classified the different activities with an accuracy of 96.9%. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Support vector machines

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Optimal Allocation of Mobile Finance Company Agents Using Convex Hull Optimization 1

引用

World Conference on Information systems for Business Management, ISBM 2023

作者： Haque, Farah Binta Rafi, Md. Shoaib Akhter Sadeque, Farig BRAC University Dhaka Bangladesh Bangladesh University of Engineering and Technology Dhaka Bangladesh

ISBN: (数字)9789819983469

ISBN: (纸本)9789819983452

Efficient distribution of agents in mobile finance systems is crucial for optimizing service delivery and enhancing the user experience. Proper agent distribution not only maintains the popularity of the service but also helps it stand out in competition with others. It also increases the probability of an agent getting a customer without affecting others nearby. This paper explores the application of employing the Convex Hull algorithm as a key tool in facilitating agent distribution in such systems. Bkash is one of the most popular mobile finance organizations in Bangladesh. Unfortunately, the distribution of Bkash agents throughout the country is not optimal, especially in remote areas. Finding and allocating the optimal number of agents so that more people can be brought under the service while maintaining maximum distance from one agent to another is the main goal of this paper. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Finance

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Littoral Morpho-Dynamic Evolution: The Case of Al-Hoceima (Mediterranean Sea, North Morocco) 1

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International Conference on Advanced Intelligent systems for Sustainable Development, AI2SD 2023

作者： Damnati, Brahim Lemqeddem, Khadija Ait Ed-daoudy, Lhoussaine Lahmam, Nouh Rghif, Yousra Abdelmalek Essaadi University FSTT EMRN Tangier Morocco

ISBN: (数字)9783031542886

ISBN: (纸本)9783031542879

Climate change will majorly influence our lives in the next few decades through its impact on the severity of coastal erosion and marine submersion, which are associated with an increasing frequency and intensity of extreme events. This study employs three complementary approaches: the interpretation of vertical satellite imagery, seasonal measurements of beach width in the field, and a sedimentological study. The main objectives are to evaluate the risk of erosion on the Moroccan Mediterranean coastline, particularly the impact of climate change, in order to prevent disasters, minimize risks, and manage the consequences. The study reveals that approximately 54% of beaches in Al-Hoceima have experienced erosion, while around 14% have remained relatively stable. The erosion speed at Sfiha Beach in the western zone varies between 2.68 m/year and 2.25 m/year, while in the eastern part, the evolution is relatively low at around 1.34 m/year. The high erosion rates recorded on some transects pose significant problems, accompanied by reduced beach width, particularly during winter. Additionally, a study estimating the areas likely lost by submersion allows for identifying flood zones based on different seawater rise scenarios. Approximately 47% of the entire coastline of Al-Hoceima presents a risk of submersion with a maximum flood level of 10m, compared to 64% in Tangier, for example. These impacts affect populations, socio-economic activities, land use, and transitional waters, particularly along the coastline. The study highlights significant implications for coastal management, emphasizing the need for proactive measures to mitigate climate change's impacts on coastlines. Practical strategies like beach nourishment, dune restoration, and coastal defenses can prevent erosion and protect vulnerable areas. Land use planning and resilient infrastructure development are crucial for sustainable management. © The Author(s), under exclusive license to Springer Nature Switzerla

关键词： Climate change

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