Majid Shaalan

Harrisburg University of Science & Technology, Computer & Information Sciences, Program Head

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My name is Majid, I am a professor of computer science and director of Computer and Information Sciences Program at Harrisburg University of Science and Technology. My teaching and research interest are in Artificial Intelligence and Computational Sciences. I believe that the field of Computer Science has developed a tradition of interdisciplinary. Numerous examples exist of such mutual interaction of computer science and mathematics or computer science and other Sciences. In the same manner when Newton’s scientific pursuit forced him to invent the mathematical tools that enabled him to solve the problem presented by physics

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Papers by Majid Shaalan

Analysis of Cloud Bursting on Openstack Infrastructure to AWS

Cloud bursting provides enterprises, especially those of small and medium scale, the ability to s... more Cloud bursting provides enterprises, especially those of small and medium scale, the ability to scale up their own infrastructure using the resource of an external cloud. However, many cloud bursting software are proprietary and strictly dependent on a specific cloud platform. Moreover, the technique remains difficult for its complexity and inconsistency in maintaining its performance especially during the production phase. In this paper, a cloud bursting technique for an Openstack environment to the AWS EC2 platform is conducted using the open-source OMNI module and the results are analyzed. We found that during the migration of many VM instances, the time to synchronize is heavily impacted in contrast to moving a small collection of VMs with larger sizes. It is also found that the utilization of adequate scheduling algorithms can be achieved to enhance the cloud bursting technique, better synchronization time, and lower delay between each separate migration.

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Comparison of the effect of cell death within each cell type

Removal of 990 (or 30%) of granule cells resulted in the least performance degradation (... more

Evolving psychosocial, emotional, functional, and support needs of women with advanced breast cancer: Results from the Count Us, Know Us, Join Us and Here & Now surveys

The Breast, 2016

Although medical advances have marginally improved survival of women with advanced breast cancer,... more Although medical advances have marginally improved survival of women with advanced breast cancer, their psychosocial, emotional, and functional needs remain unmet. Two surveys, Count Us, Know Us, Join Us (Count Us) and Here & Now (H&N), were conducted to understand the unique challenges faced by women with advanced breast cancer and to identify ways of addressing these issues. A total of 1577 women with advanced breast cancer (Count Us, N ¼ 1273; H&N, N ¼ 304) participated in the two surveys, which revealed several previously unreported challenges. Nearly half the women felt isolated and worried, and slightly more than half experienced declines in income because of change in employment; 41% of women felt that support from family and friends decreased over time, and many patients believed information about advanced breast cancer was inadequate and difficult to find. Concerted efforts by people who care for and support women with advanced breast cancer are urgently needed to address these issues.

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Performance degradation of cerebellum with basket cells removed after 25, 50, and 100 trials

Smoothness of the curve increases with the number of trials conducted (noise spikes are ... more

Performance degradation of cerebellum

Comparison of damage to individual cell types. Removal of Purkinje cells (included in th... more Comparison of damage to individual cell types. Removal of Purkinje cells (included in the inset) results in the greatest performance degradation. Random cell removal corresponds to mossy fibers, basket, Golgi, granule, and Purkinje cells, with the likelihood of a particular cell types being damaged determined by the number of cells in relation to the overall number of cells in the model of cerebellum.</p

Comparison of a performance degradation of cerebellum vis-a-vis proximal relation of individual cell types to the deep cerebellar neurons

Numbers listed in parenthesis correspond to the performance degradation of individual ce... more Numbers listed in parenthesis correspond to the performance degradation of individual cell types when maximum number of cells is removed. When the damage affects cell types the closest to cerebellar output (i.e. Purkinje cells), the performance degradation is significantly greater when the affected cells are located much further away (i.e. Golgi cells). For granule cells, the number in parenthesis represents the performance degradation when the total number of granule cells has been reduced by 90%.</p

Implementation of Prototype Environment of Virtual Reality Platform for Virtual Lab (Use case of ESL)

2021 IEEE International Conference on Big Data (Big Data)

Monitoring Artificial Neural Network Performance Degradation under Network Damage

Intelligent Engineering Systems through Artificial Neural Networks, Volume 20

ABSTRACT Recently a number of research groups presented transistor-based designs exhibiting behav... more ABSTRACT Recently a number of research groups presented transistor-based designs exhibiting behavior similar to biological synapses, facilitating creation of a tangible artificial neuron. Hardware neural networks would possess great advantages in information processing tasks that are inherently parallel, such as image processing, require learning, such as handwriting recognition, or in an environment where the processing unit might be susceptible to physical damage. A number of different possibilities for realization of hardware neural networks currently exist. This paper presents analysis of performance degradation of various architectures of artificial neural networks when subjected to neural damage. An analysis of un-optimized and optimized, feed-forward and recurrent networks, trained with uncorrelated and correlated data sets is conducted. A comparison of networks with single, dual, triple, and quadruple hidden layers is quantified. The main finding is that for damage occurring to cells in hidden layer(s) the architecture that sustains the least damage is that of a single hidden layer. However, when the damage is administered to input layer then the opposite, that is arranging cells in multiple hidden layers, offers the most resilience to the damage. Additionally, recurrent networks offer improved resilience to damage compared to feed-forward networks.

예이츠 초기 연애시에 나타난 갈망과 상실

The Yeats Journal of Korea, 2019

Monitoring Performance Degradation of Cerebellar Functions Using Computational Neuroscience Methods: Implications on Neurological Diseases

Neurodegeneration is a major cause of human disease. Within the cerebellum, neuronal degeneration... more Neurodegeneration is a major cause of human disease. Within the cerebellum, neuronal degeneration and/or dysfunction has been associated with many diseases, including several forms of cerebellar ataxia, since normal cerebellar function is paramount for proper motor coordination, balance, and motor learning. The cerebellum represents a well-established neural circuit. Determining the effects of neuronal loss is of great importance for understanding the fundamental workings of the cerebellum and disease-associated dysfunctions. This paper presents computational modeling of cerebellar function in relation to neurodegeneration either affecting a specific cerebellar cell type, such as granule cells or Purkinje cells, or more generally affecting cerebellar cells and the implications on effects in relation to performance degradation throughout the progression of cell death. The results of the models show that the overall number of cells, as a percentage of the total cell number in the mode...

On Optimization of Stock Market Prediction Methods

In the modern-day stock markets, accuracy and timeliness of price predictive methods can be key i... more In the modern-day stock markets, accuracy and timeliness of price predictive methods can be key in making a profit and edging out the competition. Stockbrokers utilize predictive systems based on these methods that rely on a plethora of data to assist in decision making. To work towards developing our own system that will eventually utilize big data, we performed research with recurrent neural networks (RNNs) and support vector machines (SVMs) to derive a backing method for the predictive system. In this paper we discuss the experimentation we have performed, and the proposed approach derived from the results of the experimentation.

Analysis of Cloud Bursting from the Openstack Infrastructure to AWS

2020 IEEE Cloud Summit

Analysis of Cloud Bursting on Openstack Infrastructure to AWS

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Comparison of the effect of cell death within each cell type

Removal of 990 (or 30%) of granule cells resulted in the least performance degradation (... more

Evolving psychosocial, emotional, functional, and support needs of women with advanced breast cancer: Results from the Count Us, Know Us, Join Us and Here & Now surveys

The Breast, 2016

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Performance degradation of cerebellum with basket cells removed after 25, 50, and 100 trials

Smoothness of the curve increases with the number of trials conducted (noise spikes are ... more

Performance degradation of cerebellum