Modeling and simulation with augmented reality

In applications such as airport operations, military simulations, and medical simulations, conducting simulations in accurate and realistic settings that are represented by real video imaging sequences becomes essential. This paper surveys recent work that enables visually realistic model constructions and the simulation of synthetic objects which are inserted in video sequences, and illustrates how synthetic objects can conduct intelligent behavior within a visual augmented reality

Efficient Poisson Image Editing

Image composition refers to the process of composing two or more images to create a natural output image. It is one of the important techniques in image processing. In this paper, two efficient methods for composing color images are proposed. In the proposed methods, the Poisson equation is solved using image pyramid and divide-and-conquer methods. The proposed methods are more efficient than other existing image composition methods. They reduce the time taken in the composition process while achieving almost identical results using the previous image composition methods. In the proposed methods, the Poisson equation is solved after converting it to a linear system using different methods. The results show that the time for composing color images is decreased using the proposed methods

Using High Dimensional Computing on Arabic Language Speech to Text Classification

High-Dimensional Processing is the idea that mind register illustrations of neural activities which are not immediately related with numbers. The objective of the article is hyper- dimensional computation of data for categorization of text from two distinct speech datasets, namely the Arabic Corpus dataset and the MediaSpeech dataset with four languages (Arabic, Spanish, French, and Turkish). Through the use of an n-gram encoding scheme, hyper dimensional computing is used to conduct the analysis from the prior set of data. Using hyper dimensional computing, the MediaSpeech dataset accomplishes 100% accuracy for all 4-gram to 14-gram encoding schemes, while the Arabic Corpus dataset accomplishes 100% accuracy for 4-gram to 7-gram encoding schemes

Water-Cooling-Based Approach for PV System Performance Enhancement towards UAE Future Energy Efficiency Policies

United Arab Emirates (UAE) has implemented the UAE Energy Strategy 2050, targeting a 50% increase in renewable energy's contribution by 2050. Steps to achieve this strategy include accelerating efficient consumption of energy and focusing on research and development for sustainable energy solutions. This research aims to investigate the potential improvement in the performance of PV systems as a result of panel’s water-cooling under the UAE climatic conditions. In this work, a PV system consists of two identical 100-W PV panels and an automated water cooling arrangement was built. To assess the effectiveness of the cooling method used, one PV panel was subjected to water cooling, while the other remained uncooled in order to be taken as a benchmark. The experiments took place over a typical summer day during the period between 8:00 am and 5:00 pm. The proposed cooling strategy was repeatedly applied every half an hour to investigate the temperature reduction behavior at different times of the day. The experimental results demonstrated that the adopted water approach was able to achieve a temperature drop of up to 14.6 K. The corresponding power output was improved by up to 12% as a result of the PV panel cooling

Enhancing image captioning with depth information using a Transformer-based framework

Captioning images is a challenging scene-understanding task that connects computer vision and natural language processing. While image captioning models have been successful in producing excellent descriptions, the field has primarily focused on generating a single sentence for 2D images. This paper investigates whether integrating depth information with RGB images can enhance the captioning task and generate better descriptions. For this purpose, we propose a Transformer-based encoder-decoder framework for generating a multi-sentence description of a 3D scene. The RGB image and its corresponding depth map are provided as inputs to our framework, which combines them to produce a better understanding of the input scene. Depth maps could be ground truth or estimated, which makes our framework widely applicable to any RGB captioning dataset. We explored different fusion approaches to fuse RGB and depth images. The experiments are performed on the NYU-v2 dataset and the Stanford image paragraph captioning dataset. During our work with the NYU-v2 dataset, we found inconsistent labeling that prevents the benefit of using depth information to enhance the captioning task. The results were even worse than using RGB images only. As a result, we propose a cleaned version of the NYU-v2 dataset that is more consistent and informative. Our results on both datasets demonstrate that the proposed framework effectively benefits from depth information, whether it is ground truth or estimated, and generates better captions. Code, pre-trained models, and the cleaned version of the NYU-v2 dataset will be made publically available.Comment: 19 pages, 5 figures, 13 table

Efficient Poisson Image Editing

Image composition refers to the process of composing two or more images to create an acceptable output image. It is one of the important techniques of image processing. In this paper, two efficient methods for composing color images are proposed. In the proposed methods, the Poisson equation is solved using image pyramid, and divide-and-conquer methods. The proposed methods are more efficient than other existing image composition methods. They reduce the time taken in the composition process while achieving almost identical results using the previous image composition methods. In the proposed methods, the Poisson equation is solved after converting it to a linear system using different methods. The results show that the time for composing color images is decreased using the proposed methods

Assessment of hole quality, thermal analysis, and chip formation during dry drilling process of gray cast iron ASTM A48

The cutting parameters in drilling operations are important for high-quality holes and productivity improvement in any manufacturing industry. This study investigates the effects of spindle speed and feed rate on temperature, surface roughness, hole size, circularity, and chip formation during dry drilling of gray cast iron ASTM A48. The results showed that the temperature increased as spindle speed and feed rate increased. The surface roughness had an inverse relationship with the spindle speed and direct relation with the feed rate. Furthermore, hole size increased with increased spindle speed and decreased as the feed rate increased, while hole circularity decreased with increasing both the spindle speed and feed rate. The analysis of variance (ANOVA) indicated that the spindle speed had the highest percentage contribution of 56.24 % on temperature, followed by the feed rate with 42.35 %. The surface roughness was highly influenced by the feed rate and the spindle speed with 55 % and 44.12 %, respectively. While the hole size was highly influenced by the feed rate with a 74.18 % percentage contribution, and the contribution of spindle speed was 21.36 %. In addition, the feed rate has a percentage contribution of 70.82 % on circularity, which is higher than the spindle speed of 24.26 % percentage contribution. The results also showed that thick and discontinuous chips were generated at higher feed rates, while long continuous chips were produced at high spindle speeds

Development and Performance of Cement Bound Materials in Road Pavements

The use of cement bound materials (CBMs) for road construction in Qatar is relatively new. CBM improves the structural capacity and durability of pavement, but considerations should be made to the setting time and strength development in hot arid environment, such as in Qatar. The paper presents a laboratory development and performance characteristics of CBM mixtures, with environmental and economic benefits through the use of local and recycled materials. The developed mixtures showed full compliance with the grading, strength and durability requirements of the Qatar Construction Specifications (QCS, 2014). Site data from Ashghal projects indicated the difficulty of producing consistent strength in practice, with the potential of increased strength and associated risk of reflection cracking in the asphalt overlaying. Recommendations are made to improve the construction practice and specification of cement and other hydraulically bound materials to enhance the service life of pavement and support the government strategy of sustainable construction

Blockchain-based Digital Twins:Research Trends, Issues, and Future Challenges

Industrial processes rely on sensory data for decision-making processes, risk assessment, and performance evaluation. Extracting actionable insights from the collected data calls for an infrastructure that can ensure the dissemination of trustworthy data. For the physical data to be trustworthy, it needs to be cross validated through multiple sensor sources with overlapping fields of view. Cross-validated data can then be stored on the blockchain, to maintain its integrity and trustworthiness. Once trustworthy data is recorded on the blockchain, product lifecycle events can be fed into data-driven systems for process monitoring, diagnostics, and optimized control. In this regard, digital twins (DTs) can be leveraged to draw intelligent conclusions from data by identifying the faults and recommending precautionary measures ahead of critical events. Empowering DTs with blockchain in industrial use cases targets key challenges of disparate data repositories, untrustworthy data dissemination, and the need for predictive maintenance. In this survey, while highlighting the key benefits of using blockchain-based DTs, we present a comprehensive review of the state-of-the-art research results for blockchain-based DTs. Based on the current research trends, we discuss a trustworthy blockchain-based DTs framework. We also highlight the role of artificial intelligence in blockchain-based DTs. Furthermore, we discuss the current and future research and deployment challenges of blockchain-supported DTs that require further investigation.</p