18 research outputs found
Type of Tomato Classification Using Deep Learning
Abstract: Tomatoes are part of the major crops in food security. Tomatoes are plants grown in temperate and hot regions of South
American origin from Peru, and then spread to most countries of the world. Tomatoes contain a lot of vitamin C and mineral salts,
and are recommended for people with constipation, diabetes and patients with heart and body diseases. Studies and scientific
studies have proven the importance of eating tomato juice in reducing the activity of platelets in diabetics, which helps in
protecting them from developing deadly blood clots. A tomato classification approach is presented with a data set containing
approximately 5,266 images with 7 species belonging to tomatoes. The Neural Network Algorithms (CNN), a deep learning
technique applied widely in image recognition, is used for this task
Software Development in the Post-PC Era: Towards Software Development as a Service
Abstract. Software systems affect all aspects of our modern life andare revolutionizing the way we live. Over the years, software developmenthas evolved to meet the needs of new types of applications and toembrace new technological disruptions. Today, we witness the rise of mobilitywhere the role of the conventional high-specification PC is declining.Some refer to this era as the Post-PC era. This technological shift,powered by a key enabling technology - cloud computing, has opened new opportunities for human advancement (e.g. the Internet of Things).Consequently, the evolving landscape of software systems drives the need for new methods for conceiving them. Such methods need to a) address the challenges and requirements of this era and b) embrace the benefitsof new technological breakthroughs. In this paper, we list the characteristics of the Post-PC era from the software development perspective. In addition, we describe three motivating trends of software development processes. Then, we derive a list of requirements for the future software development approach from the characteristics of the Post-PC era and from the motivating trends. Finally, we propose a reference architecturefor cloud-based software process enactment as an enabler for Software Development as a Service (SDaaS). The architecture is thefirst step to address the needs that we have identified
Handwritten Signature Verification using Deep Learning
Every person has his/her own unique signature that is used mainly for the purposes of personal
identification and verification of important documents or legal transactions. There are two kinds of signature
verification: static and dynamic. Static(off-line) verification is the process of verifying an electronic or document
signature after it has been made, while dynamic(on-line) verification takes place as a person creates his/her
signature on a digital tablet or a similar device. Offline signature verification is not efficient and slow for a large
number of documents. To overcome the drawbacks of offline signature verification, we have seen a growth in
online biometric personal verification such as fingerprints, eye scan etc. In this paper we created CNN model
using python for offline signature and after training and validating, the accuracy of testing was 99.70%
Knowledge Management Processes and Their Role in Enhancing the Strategic Decision-Making Process - An Applied Study at Al-Azhar University - Gaza
This study aimed to highlight the nature of the relationship between knowledge management and the strategic decision-making process, considering that strategic decisions are formulated and made based on a specific knowledge perspective. The study targeted the university management, deans of faculties, and college directors at Al-Azhar University - Gaza. The study followed a descriptive-analytical approach, and data was collected through a questionnaire designed to cover six dimensions related to knowledge management processes and an axis related to strategic decision-making. The data was analyzed using various statistical methods. The study results showed a statistically significant positive relationship between the role of knowledge management processes and activating the strategic decision-making process at Al-Azhar University - Gaza. The study recommended that the university pay more attention to the processes of knowledge awareness and application as they serve as the link between existing knowledge and the creation of good knowledge. Furthermore, these processes are considered the essential means through which the university improves the effectiveness of strategic decisions and enhances its position
The Reality of Spreading the Culture of Entrepreneurship and Proposals for Activating It (An Applied Study on the University of Al-Azhar in Gaza)
The study aimed to investigate the reality of spreading the culture of entrepreneurship at Al-Azhar University from the point of view of students of the Faculty of Engineering and Information Technology and diagnose the most important obstacles that limit its activation. The researchers used the descriptive approach (survey) to achieve the objectives of the study, and relied on the questionnaire as a tool for applied study. The study concluded that: The reality of spreading the culture of entrepreneurship at Al-Azhar University from the point of view of the students participating in the study came with an average degree of approval, while the most important obstacles and possible proposals for activating it came with a high degree of approval, which indicates the existence of strengths of Al-Azhar University in spreading the culture of entrepreneurship among students. Deficiencies must be corrected through proposals. In light of the results of the study, it was possible to develop a number of recommendations that can contribute to activating the culture of entrepreneurship at Al-Azhar University. Including the establishment of a specialized center for entrepreneurship within the university, develop a declared strategic plan to spread and develop the culture of entrepreneurship, allocate a sufficient budget to sponsor and support entrepreneurial ideas and projects for students and provide specialized cadres and certified trainers in the field of entrepreneurship
Automated mitral inflow Doppler peak velocity measurement using deep learning
Doppler echocardiography is a widely utilised non-invasive imaging modality for assessing the functionality
of heart valves, including the mitral valve. Manual assessments of Doppler traces by clinicians introduce
variability, prompting the need for automated solutions. This study introduces an innovative deep learning
model for automated detection of peak velocity measurements from mitral inflow Doppler images, independent
from Electrocardiogram information. A dataset of Doppler images annotated by multiple expert cardiologists
was established, serving as a robust benchmark. The model leverages heatmap regression networks, achieving
96% detection accuracy. The model discrepancy with the expert consensus falls comfortably within the range
of inter- and intra-observer variability in measuring Doppler peak velocities. The dataset and models are
open-source, fostering further research and clinical application
Enabling GSD task allocation via cloud-based software processes
Allocating tasks to distributed sites in Global Software Development (GSD) projects is often done unsystematically and based on the personal experience of project managers. Wrong allocation decisions increase the projectrs risks as tasks have dependencies that are inherited by the distributed sites. Decision support can help make the task allocation a more informed and systematic process. The challenges in allocating tasks to distributed sites exist because of three distance dimensions between sites (geographical, temporal and cultural). An informed task allocation decision needs to consider these distances. Therefore, in this paper, we propose to integrate and semi-automate the calculation of an existing Global Distance Metric (GDM) into an architecture that supports executing cloud-based software processes. We analyze the potential of integrating the GDM into this architecture and identify the needed extensions to the architecture