Papers by Hassan Tarawneh
2021 22nd International Arab Conference on Information Technology (ACIT), 2021
Jordan is among the top 10 world countries in terms of producing and exporting tomatoes, which co... more Jordan is among the top 10 world countries in terms of producing and exporting tomatoes, which constitutes around 65% of the total exported agricultural produce rounding to a total of 900,000 tons exports each year. Therefore, the quality and quantity of tomato crop goes down as a result of the various kinds of diseases affecting the crop. Hence, there is a clear need to automate disease detection using deep learning-based approach. This paper presents a dynamic intelligent model based on histogram-based k-means clustering algorithm with back-propagation neural network to detect and identify various tomato plant diseases. For the disease detection and classification, a Convolution Neural Network based approach is applied. In this model, there are three dynamically convolution and pooling layers followed by fully connected layer. The overall model presented a promising experimental result based on accuracy and efficiency. The accuracy performance relied on three tested methods to detect the disease, which proves that Kalman back propagation ranked first, SVM ranked second and KNN ranked third.
Symmetry, 2022
Web service composition allows developers to create and deploy applications that take advantage o... more Web service composition allows developers to create and deploy applications that take advantage of the capabilities of service-oriented computing. Such applications provide the developers with reusability opportunities as well as seamless access to a wide range of services that provide simple and complex tasks to meet the clients’ requests in accordance with the service-level agreement (SLA) requirements. Web service composition issues have been addressed as a significant area of research to select the right web services that provide the expected quality of service (QoS) and attain the clients’ SLA. The proposed model enhances the processes of web service selection and composition by minimizing the number of integrated Web Services, using the Multistage Forward Search (MSF). In addition, the proposed model uses the Spider Monkey Optimization (SMO) algorithm, which improves the services provided with regards to fundamentals of service composition methods symmetry and variations. It a...
Simulated Annealing (SA) is a common meta-heuristic algorithm that has been widely used to solve ... more Simulated Annealing (SA) is a common meta-heuristic algorithm that has been widely used to solve complex optimization problems. This is due to its ease of implementation and capability to escape from local optimum. This research conducts an investigation on three of SA components: the initial temperature, cooling schedule and neighborhood structure. We observed that the high initial temperature leads SA to accept any solution (wasting more computational time), whilst the lower value leads SA to quickly trap in local optimum. Based on research findings from this phase, for each component we suggested a technique to overcome the limitations. The limitations are: (i) a dynamic initial temperature mechanism that dynamically chose the suitable initial temperature for each instance problem; (ii) adaptive cooling schedule that will adjust the temperature value during the search; and (iii) a new neighborhood structure that will improve the search ability by minimizing the random selection. ...
Computer Systems Science and Engineering, 2022
Social distancing during COVID-19 has become one of the most important measures in reducing the r... more Social distancing during COVID-19 has become one of the most important measures in reducing the risks of the spread of the virus. Implementing these measures at universities is crucial and directly related to the physical attendance of the populations of students, professors, employees, and other members on campus. This research proposes an automated scheduling approach that can help universities and schools comply with the social distancing regulations by providing assistance in avoiding huge assemblages of people. Furthermore, this paper proposes a novel course timetable-scheduling scheme based on four main constraints. First, a distance of two meters must be maintained between each student inside the classroom. Second, no classrooms should contain more than 20% of their regular capacity. Third, there would be no back-to-back classes. Lastly, no lectures should be held simultaneously in adjacent classrooms. The proposed approach was implemented using a variable neighborhood search (VNS) approach with an adaptive neighborhood structure (AD-NS) to resolve the problem of scheduling course timetables at Al-Ahlyyia Amman University. However, the experimental results show that the proposed techniques outperformed the standard VNS tested on university course timetabling benchmark dataset ITC2007-Track3. Meanwhile, the approach was tested using datasets collected from the faculty of information technology at Al-Ahlyyia Amman University (Jordan). Where the results showed that, the proposed technique could help educational institutes to resume their regular operations while complying with the social distancing guidelines.
Intelligent Automation & Soft Computing, 2021
Service Oriented Architecture (SOA) is a style of software design where Web Services (WS) provide... more Service Oriented Architecture (SOA) is a style of software design where Web Services (WS) provide services to the other components through a communication protocol over a network. WS components are managed, updated, and rearranged at runtime to provide the business processes as SCs, which consist of a set of WSs that can be invoked in a specific order to fulfill the clients' requests. According to the Service Level Agreement (SLA) requirements, WS selection and composition are significant perspectives of research to meet the clients' expectations. This paper presents an effective technique using SMFS that attempts to improve the WS selection as well as SC construction and ultimately optimize the WS resource utilization. The results show that the proposed SMFS technique enhances the WS resource utilization by 9.6% compared to the standard Multistage Forward Search (MFS) technique. Similarly, the number of constructed SCs using the proposed SMFS technique are increased by 36.97% compared to the number of constructed SCs with the standard MFS technique.
Modern Applied Science, 2018
Simulated Annealing (SA) is a common meta-heuristic algorithm that has been widely used to solve ... more Simulated Annealing (SA) is a common meta-heuristic algorithm that has been widely used to solve complex optimization problems. This work proposes a hybrid SA with EMC to divert the search effectively to another promising region. Moreover, a Tabu list memory applied to avoid cycling. Experimental results showed that the solution quality has enhanced using SA-EMCQ by escaping the search space from local optimum to another promising region space. In addition, the results showed that our proposed technique has outperformed the standard SA and gave comparable results to other approaches in the literature when tested on ITC2007-Track3 university course timetabling datasets.
AIP Conference Proceedings, 2017
Cryptography is the practice of transforming data to indecipherable by a third party, unless a pa... more Cryptography is the practice of transforming data to indecipherable by a third party, unless a particular piece of secret information is made available to them. Data encryption has been paid a great attention to protect data. As data sizes are growing, so does the need for efficient data search while being encrypted to protect it during transmission and storage. This research is based on our previous and continuous work to speed up and enhance global heuristic search on an encrypted data. This research is using chained hashing approach to reduce the search time and decrease the collision rate which most search techniques suffers from. The results were very encouraging and will be discussed in the experimental results section.
2011 3rd Conference on Data Mining and Optimization (DMO), 2011
ABSTRACT In this work we apply a Tabu search and multi-neighborhood structure to solve University... more ABSTRACT In this work we apply a Tabu search and multi-neighborhood structure to solve University Course Timetable at the faculty of engineering, University Kebangsan Malaysia. The aim is to introduce the neighborhood structure according to the difference between the lengths of lectures (i.e. some lectures are one hour, while others are two hours). Therefore, the new neighborhood structure is required to handle this problem. The results have demonstrate the effectiveness of the proposed neighborhood structure.
Journal of Applied Sciences, 2013
Journal of Engineering and Applied Sciences, 2013
Journal of Applied Sciences, 2013
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Papers by Hassan Tarawneh