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Natural Convection Effect on Solidification Enhancement in a Multi-Tube Latent Heat Storage System: Effect of Tubes’ Arrangement
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The solidification process in a multi-tube latent heat energy system is affected by the natural convection and the arrangement of heat exchanger tubes, which changes the buoyancy effect as well. In the current work, the effect of the arrangement of the tubes in a multi-tube heat exchanger was examined during the solidification process with the focus on the natural convection effects inside the phase change material (PCM). The behavior of the system was numerically analyzed using liquid fraction and energy released, as well as temperature, velocity and streamline profiles for different studied cases. The arrangement of the tubes, considering seven pipes in the symmetrical condition, are assumed at different positions in the system, including uniform distribution of the tubes as well as non-uniform distribution, i.e., tubes concentrated at the bottom, middle and the top of the PCM shell. The model was first validated compared with previous experimental work from the literature. The results show that the heat rate removal from the PCM after 16 h was 52.89 W (max) and 14.85 W (min) for the cases of uniform tube distribution and tubes concentrated at the bottom, respectively, for the proposed dimensions of the heat exchanger. The heat rate removal of the system with uniform tube distribution increases when the distance between the tubes and top of the shell reduces, and increased equal to 68.75 W due to natural convection effect. The heat release rate also reduces by increasing the temperature the tubes. The heat removal rate increases by 7.5%, and 23.7% when the temperature increases from 10 °C to 15 °C and 20 °C, respectively. This paper reveals that specific consideration to the arrangement of the tubes should be made to enhance the heat recovery process attending natural convection effects in phase change heat storage systems.

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Publication Date
Fri Jul 12 2024
Journal Name
International Journal Of Advances In Scientific Research And Engineering (ijasre), Issn:2454-8006, Doi: 10.31695/ijasre
A Proposed Blockchain-Based Digital-Identity Management using ERC 725/735
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In modern technology, the ownership of electronic data is the key to securing their privacy and identity from any trace or interference. Therefore, a new identity management system called Digital Identity Management, implemented throughout recent years, acts as a holder of the identity data to maintain the holder’s privacy and prevent identity theft. Therefore, an overwhelming number of users have two major problems, users who own data and third-party applications will handle it, and users who have no ownership of their data. Maintaining these identities will be a challenge these days. This paper proposes a system that solves the problem using blockchain technology for Digital Identity Management systems. Blockchain is a powerful techniqu

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Publication Date
Fri Oct 28 2022
Journal Name
Surgical Neurology International
Extracranial carotid localized fibromuscular dysplasia: A case report and literature review
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Background:

Fibromuscular dysplasia (FMD) is a noninflammatory and nonatherosclerotic arteriopathy that is characterized by irregular cellular proliferation and deformed construction of the arterial wall that causes segmentation, constriction, or aneurysm in the intermediate-sized arteries. The incidence of FMD is 0.42–3.4%, and the unilateral occurrence is even rarer. Herein, we report a rare case of a localized extracranial carotid unilateral FMD associated with recurrent transient ischemic attacks (TIAs) treated by extracranial-intracranial bypass for indirect revascularization. The specific localization of the disease rendered our case unique.

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Publication Date
Mon Jan 01 2024
Journal Name
Fusion: Practice And Applications
A Hybrid Meta-Heuristic Approach for Test Case Prioritization and Optimization
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The application of the test case prioritization method is a key part of system testing intended to think it through and sort out the issues early in the development stage. Traditional prioritization techniques frequently fail to take into account the complexities of big-scale test suites, growing systems and time constraints, therefore cannot fully fix this problem. The proposed study here will deal with a meta-heuristic hybrid method that focuses on addressing the challenges of the modern time. The strategy utilizes genetic algorithms alongside a black hole as a means to create a smooth tradeoff between exploring numerous possibilities and exploiting the best one. The proposed hybrid algorithm of genetic black hole (HGBH) uses the

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Publication Date
Fri Mar 12 2021
Journal Name
Sensors
A Robust Handwritten Numeral Recognition Using Hybrid Orthogonal Polynomials and Moments
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Numeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential a

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Publication Date
Wed Jun 01 2022
Journal Name
Journal Of Nursing Education
Compassion Competence Among Nursing Students From Different Cultures: A Multinational Study
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Background:

Compassion competence is a nurse's ability to provide patient-centered care and communicate with patients in a sensitive and insightful manner. This descriptive cross-sectional survey study aimed to assess the compassion competence of a multinational group of nursing students.

Method:

A total of 1,158 undergraduate nursing students participated in this study, and stratified random sampling method was used to select participants from the 100 study level to the 400 or 500 level. Data were collected using the Compassion Competence Scale.

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Publication Date
Thu Dec 16 2021
Journal Name
Translational Vision Science &amp; Technology
A Hybrid Deep Learning Construct for Detecting Keratoconus From Corneal Maps
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Publication Date
Sun Dec 25 2022
Journal Name
Nurse Media Journal Of Nursing
Targeting Smoking Triggers: A Nurse-led Intervention for Tobacco Smoking Cessation
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Background: Nursing interventions tailored to the smoking triggers in patients with non-communicable chronic diseases are essential. However, these interventions are scant due to the nature of factors associated with smoking cessation and the poor understanding of the effect of nurse-led intervention in Iraq.Purpose: This study aimed to determine the dominant smoking triggers and examine the effects of a tailored nursing intervention on smoking behavior in patients with non-communicable chronic diseases.Methods: Convenience samples of 128 patients with non-communicable chronic diseases, male and female patients, who were 18-70 years old, were recruited in this quasi-experimental, randomized comparative trial in the outpatient clinic

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Publication Date
Sun Dec 25 2022
Journal Name
Nurse Media Journal Of Nursing
Targeting Smoking Triggers: A Nurse-led Intervention for Tobacco Smoking Cessation
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Background: Nursing interventions tailored to the smoking triggers in patients with non-communicable chronic diseases are essential. However, these interventions are scant due to the nature of factors associated with smoking cessation and the poor understanding of the effect of nurse-led intervention in Iraq.Purpose: This study aimed to determine the dominant smoking triggers and examine the effects of a tailored nursing intervention on smoking behavior in patients with non-communicable chronic diseases.Methods: Convenience samples of 128 patients with non-communicable chronic diseases, male and female patients, who were 18-70 years old, were recruited in this quasi-experimental, randomized comparative trial in the outpatient clinic

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach
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Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

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Publication Date
Tue Sep 16 2025
Journal Name
Construction Materials
Molasses-Modified Mortars: A Sustainable Approach to Improve Cement Mortar Performance
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The utilization of sugarcane molasses (SCM), a byproduct of sugar refining, offers a promising bio-based alternative to conventional chemical admixtures in cementitious systems. This study investigates the effects of SCM at five dosage levels, 0.25%, 0.50%, 0.75%, 1.00%, and 1.25% by weight of cement, on cement mortar performance across fresh, mechanical, thermal, durability, and density criteria. A comprehensive experimental methodology was employed, including flow table testing, compressive strength (7, 14, and 28 days) and flexural strength measurements, embedded thermal sensors for real-time hydration monitoring, water absorption and chloride ion penetration tests, as well as 28-day density determination. Results revealed clear

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