The aim of this work is to develop numerical procedures for analyzing edge hardening using induction heating by turbulent currents. The section through the steel bar, whose lower edge needs to be hardened, is presente...
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From credit scoring algorithms to face recognition systems, data-driven technologies are already impacting our lives and choices. To guarantee that new technologies function for the advantage of everyone, rather than ...
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ISBN:
(纸本)9798350383881
From credit scoring algorithms to face recognition systems, data-driven technologies are already impacting our lives and choices. To guarantee that new technologies function for the advantage of everyone, rather than perpetuating prejudices and discrimination, we have to address the ability, fairness, and trustworthiness of data systems and analysis. In literature, ability of data systems and analysis is defines as the capability of data systems to capture, store, retrieve, and manipulate data in large databases. Fairness of data systems means making sure that the usage of data and analytics does not result in biased or discriminating results for individuals or organizations. Trust is an essential factor in the effectiveness and acceptability of data systems and analysis. Without trust, people may be unwilling to utilize or disclose their data with such systems, hampering their ability to give useful insights and take advantages of data systems. To analyze, the ability, fairness, and trust in data systems and analysis, researchers have used secondary, qualitative data. Researchers have used scholarly publications, research papers, and reports taken from credible and peer-reviewed research journals. Using the data, researchers came to the result that data systems analysis have enhanced decision making process and helped us to improve our productivity in daily-life activities, through its capabilities of capturing, stories, retrieving and manipulating data. Yet, there are issues regarding the fairness of data systems. While progress achieved in tackling fairness issues, trust issues concerning data systems and analysis exist owing to data breaches suffered by huge databases globally. To conclude, in order to create trust in data systems and analysis, firms need to concentrate on security, data quality, transparency and accountability of data. This requires implementing strong access limits, leveraging high-quality data sources, being transparent and honest about data
The exponential growth of multimedia content in the digital age has necessitated the development of advanced cross-lingual systems capable of understanding and interpreting visual information across different language...
The exponential growth of multimedia content in the digital age has necessitated the development of advanced cross-lingual systems capable of understanding and interpreting visual information across different languages. However, current efforts have predominantly been focused on monolingual tasks, leaving a substantial gap in cross-lingual multimedia analysis, particularly for non-English languages. To address this gap, AraTraditions10k, a comprehensive and culturally rich dataset, has been introduced to enhance cross-lingual image annotation, retrieval, and tagging, with a specific focus on Arabic and English languages. The dataset consists of 10,000 carefully curated images representing diverse aspects of Arabic culture, each annotated with five captions in Modern Standard Arabic (MSA) and professionally translated into English. To maximize the utility of the dataset, advanced machine learning models, including a Multi-Layer Perceptron (MLP) for tag recommendation and an enhanced Word2VisualVec (W2VV) model for sentence recommendation, have been developed. These models have been augmented with attention mechanisms and contrastive loss functions, resulting in measurable performance improvements. Notably, the tag recommendation system achieved an overall top-1 accuracy of 93%, while the sentence recommendation system for the English language attained BLEU-4, METEOR, ROUGE-L, CIDEr, and SPICE scores of 78.2, 68.3, 75.8, 136.7, and 52.0, respectively. By addressing the linguistic and cultural gaps in existing datasets, AraTraditions10k establishes a new benchmark for the quality and inclusivity of multilingual datasets, contributing to the broader field of cross-lingual multimedia analysis and facilitating the development of more accessible and culturally sensitive multimedia technologies.
Microblogs such as Twitter has made available a vast resource of User Generated Content (UGC) on which emotion analysis may be performed. Organizations increasingly value the opinions obtained from emotion analysis. T...
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Digital Forensics is a platform that helps in assisting investigation carried out in computer crimes through the recovery of material that is found in digital devices. Material is recovered through a method known as f...
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In this article we elaborate on reality considerations when designing and implementing application tailored TDMA-FDMA medium access protocol with guaranteed end-to-end delay. We highlight importance of considering und...
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Vehicular Ad Hoc Network VANET is emerged to improve future Intelligence Transportation Systems (ITS) and improve road safety and traffic efficiency as well as provide passenger comfort. Vehicles in VANET share their ...
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Tracking a person with an onboard camera is a very difficult and perhaps technically impossible if one camera is used. In this regard, real-life projects use a series of cameras to achieve the task. The advent of came...
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Machine to machine communication in intelligent transportation is a technology that aims to interconnect various components such as sensors, vehicles, road infrastructures and wireless networks. The significance there...
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Faba bean (Vicia faba L.) is an important cash crop for animal and human consumption in many countries, especially Ethiopia due to its high protein content and high rate of production. It also improves soil fertility ...
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