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Enhancing Railway Safety Through Fast and Economical Object Detection: A Grounding DINO Approach

Enhancing Railway Safety Through Fast and Economical Object ...

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Sevi, Mehmet Aydin, Ilhan Mus Alparslan Univ IT Dept Mus Turkiye Firat Univ Comp Engn Dept Elazig Turkiye

ISBN: (纸本)9783031671913;9783031671920

Nowadays, railway safety is becoming increasingly important due to increasing railway traffic and the potential hazards around it. In this context, this study presents a fast and economical method developed to detect people around the railway and increase safety. A custom dataset obtained using the Anafi4K drone was augmented using various image enhancement techniques (flip horizontal, crop 10%, and noise). This expanded data set better reflects real-world conditions, making the model more reliable and capable of generalization. The study adopts the Grounding DINO method and the Zero-Shot Object Detection method. This approach aims to detect people around the railway as foreign matter. Grounding DINO increases object detection accuracy by improving the learning process of the model. Zero-Shot Object Detection stands out with its ability to recognize classes that have not been previously trained, which strengthens the ability to have prior knowledge and rapid response in terms of railway safety. Among the strengths of the study, the fact that the developed method is both fast and economical stands out. This feature provides a practical solution for railway operators and security units, allowing them to use resources more effectively. In addition, it increases safety standards by detecting people around the railway and contributing to the early identification of potential dangers. This study evaluates the knowledge gained by examining similar studies on railway safety and object detection and offers a new approach by focusing on the deficiencies in the field. The results of the study may inspire further research in the field of railway safety.

关键词： Railway Safety Pedestrian Detection Drone Grounding DINO Zero-Shot Object Detection

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A Multi-label Few-Shot Learning with Combinations of Layers

A Multi-label Few-Shot Learning with Combinations of Layers

引用

Intelligent systems Conference (IntelliSys)

作者： Sert, Bilge Sipal Aydin, Cem Rifki Younus, Arjumand Afiniti Istanbul Turkiye

ISBN: (纸本)9783031477140;9783031477157

Multi-class and multi-label classification on noisy call transcript data generated by speech-to-text (STT) systems is challenging due to the different human accents and transcription errors. The multi-labeling task is even more complicated if the data points have only single or no labels. This study has three main contributions to solving these problems: (1) To overcome the labeling problem, we train a multi-class classification model and use a minimal set of manually annotated data to determine a threshold. We obtain a multi-label classifier by utilizing a multi-class classifier with this threshold. (2) To overcome the noise issue, we propose concatenating well-known feature extraction techniques such as word2vec, tf-idf, transformers, and fuzzy embeddings. This combined feature extraction method is more resilient to noise with proper configurations than stand-alone techniques. (3) This is an industry task;we must protect our client's data. Hence to carry out our success on French private client data to benchmark data, we propose a noising pipeline that artificially mimics the observed STT transcription errors. We combined these solutions in an NLP framework, enabling us to achieve state-of-the-art results with fewer resources, such as manually annotated data or multiple GPU utilization.

关键词： Few-shot learning Multi-labeling Noisy data

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A New E-Commerce Model Suggestion of Agricultural Products

A New E-Commerce Model Suggestion of Agricultural Products

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Computing Conference

作者： Eryilmaz, Meltem Briman, Mohammed Khalid Hilmi Yakut, Gokce OSTIM Tech Univ Software Engn Dept TR-06374 Ankara Turkiye Atilim Univ Comp Engn Dept TR-06830 Ankara Turkiye

ISBN: (纸本)9783031622830;9783031622816;9783031622809

This study aims to create an e-commerce application that enables farmers to sell their products directly to their customers without resorting to intermediaries by a smart cargo box. It presents a method by which the agricultural industry can gain momentum in e-commerce. The main contributions of the study are an e-commerce application that enables farmers to sell their products directly to the customer without the need for an intermediary and the design and implementation of a smart cargo box that is tailored to carry agricultural items throughout the delivery process that locks and unlocks only via QR code generated by the application after order. Django ***, ***, and Redux are used for the system development. The database is created with PostgreSQL using migrations, and AmazonWeb Services is used for this database. The "ESP32 Cam" is used to read the QR Code.

关键词： E-Commerce E-Farm Smart box Internet of things

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Citation Recommendation Employing Proximity-Based Heterogeneous Network Embeddings

Citation Recommendation Employing Proximity-Based Heterogene...

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Intelligent systems Conference (IntelliSys)

作者： Ali, Zafar Ullah, Irfan Kefalas, Pavlos Thierry, Nimbeshaho Haq, Kalim Ul Sarkar, Anupam Southeast Univ Sch Comp Sci & Engn Nanjing Peoples R China Shaheed Benazir Bhutto Univ Dept Comp Sci Sheringal Pakistan Nanjing Univ Posts & Telecommun Coll Informat & Commun Engn Nanjing Peoples R China Aristotle Univ Thessaloniki Dept Informat Thessaloniki Greece Southeast Univ Sch Informat Sci & Engn Nanjing Peoples R China

ISBN: (纸本)9783031477201;9783031477218

The number of research papers is growing exponentially on the Web and digital libraries, which makes it a cumbersome chore to determine relevant research works. To address this problem, citation recommendation (CR) models have been proposed. Nevertheless, these CR models are limited in considering the semantic relations among network objects, e.g., authors, papers, tags, venues, and topics in the heterogeneous paper's network. Moreover, existing models do not consider the significance of proximity information between network nodes. Additionally, the current CR models face cold-start paper problems. To alleviate such problems, this work proposes a proximity-based heterogeneous network embedding (CR-PHNE) model that exploits semantic information of a network from node sequences using a probability-sensitive meta-structure-guided random walk method. Next, this information is given as input to deep neural networks to learn the latent representations of contributing nodes. Compared to its counterparts, the results produced by CR-PHNE over publicly available datasets bring 5% and 4% improvement regarding MAP and nDCG metrics, respectively. Further, the model demonstrates 7% and 3% improvements in terms of MAP and Recall@100 scores, respectively, to mitigate the cold-start paper problem compared to its counterparts.

关键词： Deep Learning Citation Recommendation Cold-Start Problem Heterogeneous Network Embedding

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Statistical Optimisation of the Static Aperture Synthesis Method

Statistical Optimisation of the Static Aperture Synthesis Me...

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International Scientific and Technical Conference on Integrated Computer Technologies in Mechanical Engineering - Synergetic Engineering (ICTM)

作者： Kolesnikov, Denys Pavlikov, Volodymyr Zhyla, Semen Vlasenko, Dmytro Kovalchuk, Danyil Shcherbina, Kseniia Natl Aerosp Univ Kharkiv Aviat Inst Kharkiv Ukraine

ISBN: (纸本)9783031614149;9783031614156

Using the statistical theory of optimisation of radio systems for remote sensing and radiolocation, a method of static synthesis of the antenna aperture for a radiovision system of static surface area is synthesized. The models of signals, noise and their correlation characteristics are determined. The likelihood functional is developed and its maximum is found. The optimal algorithm is analyzed and a block diagram for radio images formation of surfaces using the method of static synthesis of aperture is developed.

关键词： Algorithms Optimisation Stochastic Signals Aperture Synthesis Block Diagrams

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Predictive Analysis of Bank Marketing for Financial Decision Support and Smart Economy

Predictive Analysis of Bank Marketing for Financial Decision...

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Intelligent systems Conference (IntelliSys)

作者： Vashi, Hiral Yadav, Jyoti Varde, Aparna S. Stryker Corp IT Delivery Lead Kalamazoo MI USA Montclair State Univ Data Sci Program Montclair NJ USA Montclair State Univ Dept Comp Sci Montclair NJ 07043 USA

ISBN: (纸本)9783031477140;9783031477157

An active purpose of financial organizations is to preserve existing customers and accomplish imminent long-term ones. Bank marketing campaigns often depend on huge electronic data from a plethora of customers. Given the enormous and ever-growing data, it is not feasible for human analysts to procure interesting information and derive inferences for financial decision support. This motivates us to build a software tool for predictive analysis of bank marketing based on data mining from customer profiles. The success of telemarketing depends on various factors such the customers' age, job, loan status etc. Hence, these factors constitute various features analyzed by data mining to predict customer tendencies with respect to marketing campaigns. We deploy classical methods of association rules and decision trees because they fall in the category of explainable AI and hence provide good interpretability for decision-making. The resulting software tool helps to predict the types of clients that will subscribe to a given term deposit. Hence, it aims to improve bank marketing by targeting more customers, hitting the right audience. It assists telemarketing campaigns and offers financial decision support, in line with e-commerce. This work fits the theme of smart economy, an important characteristic of smart cities.

关键词： Banking Customer profiles Data mining e-Commerce Explainable AI Financial decision support Machine Learning Predictive analysis Smart cities Smart economy Telemarketing White-box models

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Evaluating Mean Squared Error as a Fitness Function in SOMA for Software Effort Estimation: Insights from the NASA Dataset 13th

Evaluating Mean Squared Error as a Fitness Function in SOMA ...

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13th Computer Science Online Conference

作者： Bajusova, Darina Silhavy, Radek Silhavy, Petr Tomas Bata Univ Zlin Fac Appl Informat Zlin 76001 Czech Republic

ISBN: (纸本)9783031702990;9783031703003

Software effort estimation plays a pivotal role in software development. The Constructive Cost Model (COCOMO) is one of the most well-known algorithmic models for estimating software effort. However, the precision of these estimates is susceptible to input constants, potentially resulting in inaccuracies. To address this challenge, this research employs the Self-Organizing Migration Algorithm (SOMA), a metaheuristic algorithm, to optimize input constants of the basic COCOMO. This study uses the NASA18 dataset to evaluate the proposed experiment's performance against the original COCOMO. Evaluation criteria such as MMRE, PRED(0.25), MAE, and MSE, with MSE serving as a fitness function, were employed to validate results. Comparative analysis indicates that optimized COCOMO estimates exhibit improved prediction accuracy. Building on these promising findings, future research will extend testing more deeply with other datasets and involve investigation of the intermediate COCOMO and COCOMO II.

关键词： COCOMO model MSE optimization Self-Organizing Migrating Algorithm software effort estimation

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Novel Adaptive Model-Free Speed Control for Uncertain Permanent Magnet Synchronous Motor 7th

Novel Adaptive Model-Free Speed Control for Uncertain Perman...

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7th International Conference on Green Technology and Sustainable Development

作者： Nguyen Tien Dat Ho Pham Huy Anh Ho Chi Minh City Univ Technol HCMUT 268 Ly Thuong Kiet StDist 10 Ho Chi Minh City Vietnam Vietnam Natl Univ Ho Chi Minh City VNU HCM Linh Trung Ward Ho Chi Minh City Vietnam

ISBN: (纸本)9783031761966;9783031761973

The problem is that permanent magnet synchronous motor model parameters are difficult to determine accurately or may be distorted during operation. This results in a significant reduction in controller performance. Therefore, it is necessary to use algorithms to compensate for parameter deviations, such as observers and parameter adaptation. This paper aims to build a current controller of a permanent magnet synchronous motor that does not require any motor model information. At the same time, to ensure the Maximum torque per ampere (MTPA) condition, the d-axis current must also be controlled stably at zero. Based on the above reasons, a novel Adaptive Back-Stepping Current Controller (ABS-CC) - based field-oriented control scheme for a permanent magnet synchronous motor is investigated in this paper. Specifically, ABS-CC control law is utilized to generate the control signal based on the mathematical model and neuron network, which guides the motor toward the given current reference. Finally, a simulation experiment is carried out to validate the theoretical conclusions, which show the high performance of the designed current control scheme.

关键词： Permanent magnet synchronous motor (PMSM) Adaptive Back-Stepping Current Controller (ABS-CC) Maximum torque per ampere (MTPA) Lyapunov's direct method Backstepping technique

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Toward Complete Digitalisation of Postal Items Clearance in the Republic of Croatia 10th

Toward Complete Digitalisation of Postal Items Clearance in ...

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International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Tomislav, Kljak Marijan, Binicki Pero, Skorput Domagoj, Vrkic Univ Zagreb Fac Transport & Traff Sci Zagreb 10000 Croatia Croatian Post Zagreb 10000 Croatia

ISBN: (纸本)9783031662706;9783031662713

The initial idea of this paper is determining the need and possibilities of the complete digitalisation of postalitems clearance (collection, acceptance, receiving, reception phase). Although many postal service providers have already digitalised a significant portion of their technological processes, including the clearance of postal items, it hasn't been completed yet. There are certain situations that require traditional manual completion of requests/data for sending postal items. This unnecessarily burdens collection capacities, increases the time needed for providing postal service (although it is being measured only after the collection of the postal item), what proportionally affects the quality of service and customer satisfaction, regardless objectively the measured or "only" the subjectively experienced. Significant differences exist among postal service providers, depending on the type of users and the type of postal items/services. The paper analyses relevant examples for the situation in the Republic of Croatia. The achieved level of digitalisation, not only in the society as a whole but among almost all postal service providers as well, represents a solid foundation for extending this approach to the remaining part of the postal items collection. In addition to reducing the negative effects, such efforts would enable potentials for further automation of postal processes, standardisation of procedures, and sharing of certain network resources by multiple postal operators, bringing various benefits to both users and postal service providers as well.

关键词： Postal traffic digitalisation quality of service

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DAP: A Framework for Driver Attention Prediction 1

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Intelligent systems Conference (IntelliSys)

作者： Kamel, Ahmed Sobh, Ibrahim Al-Atabany, Walid Nile Univ Giza Egypt Valeo Giza Egypt

ISBN: (数字)9783031477157

ISBN: (纸本)9783031477140;9783031477157

Human drivers employ their attentional systems during driving to focus on critical items and make judgments. Because gaze data can indicate human attention, collecting and analyzing gaze data has emerged in recent years to improve autonomous driving technologies. In safety-critical situations, it is important to predict not only where the driver focuses his attention but also on which objects. In this work, we propose DAP, a novel framework for driver attention prediction that bridges the attention prediction gap between pixels and objects. The DAP Framework is evaluated on the Berkeley DeepDrive Attention (BDD-A) dataset. DAP achieves state-of-the-art performance in both pixel-level and object-level attention prediction, especially improving object detection accuracy from 78 to 90%.

关键词： Attention prediction Transformer Deep learning Driver attention

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