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

Challenges for the Use of Local Materials in Unbound Road Subbase in Qatar

Current practice in Qatar is to blend local limestone with dune sand for use in unbound pavement applications. Dune sand is used to improve the properties of fine aggregate and compliance with the QCS 2014 requirements of plasticity and sand equivalent. The material has been successfully used for many years but currently facing the challenge of limited dune sand supply and recent government restrictions on its use in construction. The paper presents data on the properties of limestone obtained from different sources, tested in accordance with the QCS 2014 requirements. Variation of limestone source and the presence of clay particles greatly affected its suitability for use in unbound pavement applications. Improvement could be achieved by adjusting the grading of the material. Recommendations are made to revise the QCS 2014 specifications within the context of international specifications, when the unbound material is placed in a dry environment and away from the water level to enhance the wider utilization of local materials and sustainable construction in Qatar

Machining of carbon steel under aqueous environment: Investigations into some performance measures

In this study, a new machining approach (aqueous machining) is applied for mill machining and its performance is compared with traditional wet machining. AISI 1020 steel is employed as the test material and Taguchi statistical methodology is implemented to analyze and compare the performance of the two machining approaches. The cutting speed, feed rate, and depth of cut were the machining parameters used for both types of machining, while the selected response variables were surface roughness and hardness. Temperature variations were also recorded in aqueous machining. Compared with wet machining, aqueous machining resulted in lower surface roughness (up to 13 %) for the same operating conditions and about 14 % to 16 % enhancement in hardness due to the formation of finer pearlite, as revealed by the microstructure analysis. Compared to the parent unmachined surface, the hardness of machined surfaces was 24 % to 31 % higher in wet machining and 44 % to 51% higher in aqueous machining. Another benefit of aqueous machining was the energy gain, which ranged from 718 to 8615.96 J. This amount of heat energy can be used as waste heat for preheating domestic hot water, running the organic Rankine cycle with waste heat and preheating the inlet saline water for desalination, vacuum desalination, etc. If successfully implemented in the future, this idea will provide a step towards achieving sustainable machining by saving lubricants and toxic wastes in addition to saving energy for secondary applications

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