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Full-Text Articles in Computer Sciences

Orthogonal Inductive Matrix Completion, Antoine Ledent, Rrodrigo Alves, Marius Kloft Sep 2021

Orthogonal Inductive Matrix Completion, Antoine Ledent, Rrodrigo Alves, Marius Kloft

Research Collection School Of Computing and Information Systems

We propose orthogonal inductive matrix completion (OMIC), an interpretable approach to matrix completion based on a sum of multiple orthonormal side information terms, together with nuclear-norm regularization. The approach allows us to inject prior knowledge about the singular vectors of the ground-truth matrix. We optimize the approach by a provably converging algorithm, which optimizes all components of the model simultaneously. We study the generalization capabilities of our method in both the distribution-free setting and in the case where the sampling distribution admits uniform marginals, yielding learning guarantees that improve with the quality of the injected knowledge in both cases. As …

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Precision Public Health Campaign: Delivering Persuasive Messages To Relevant Segments Through Targeted Advertisements On Social Media, Jisun An, Haewoon Kwak, Hanya M. Qureshi, Ingmar Weber Sep 2021

Precision Public Health Campaign: Delivering Persuasive Messages To Relevant Segments Through Targeted Advertisements On Social Media, Jisun An, Haewoon Kwak, Hanya M. Qureshi, Ingmar Weber

Research Collection School Of Computing and Information Systems

Although established marketing techniques have been applied to design more effective health campaigns, more often than not, the same message is broadcasted to large populations, irrespective of unique characteristics. As individual digital device use has increased, so have individual digital footprints, creating potential opportunities for targeted digital health interventions. We propose a novel precision public health campaign framework to structure and standardize the process of designing and delivering tailored health messages to target particular population segments using social media–targeted advertising tools. Our framework consists of five stages: defining a campaign goal, priority audience, and evaluation metrics; splitting the target audience …

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Redesigning Patient Flow In Paediatric Eye Clinic For Pandemic Using Simulation, Kar Way Tan, Bee Keow Goh, Aldy Gunawan Sep 2021

Redesigning Patient Flow In Paediatric Eye Clinic For Pandemic Using Simulation, Kar Way Tan, Bee Keow Goh, Aldy Gunawan

Research Collection School Of Computing and Information Systems

This study proposes a systematic approach to the construction of a simulation model to support decision-making concerning the capacity limit and staffing configurations at the paediatric eye clinic in Singapore under the COVID-19 pandemic situation. During the pandemic, the clinic must ensure that the operations are aligned to the safe-distancing regulations put in place by the Ministry of Health while coping with the demand. We developed simulation models to examine the ‘asis’ process and proposed numerous ‘to-be’ processes for new clinic configurations to operate under the pandemic conditions. We combined scenario-thinking and simulation optimization to determine the additional manpower and …

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Secure And Verifiable Outsourced Data Dimension Reduction On Dynamic Data, Zhenzhu Chen, Anmin Fu, Robert H. Deng, Ximeng Liu, Yang Yang, Yinghui Zhang Sep 2021

Secure And Verifiable Outsourced Data Dimension Reduction On Dynamic Data, Zhenzhu Chen, Anmin Fu, Robert H. Deng, Ximeng Liu, Yang Yang, Yinghui Zhang

Research Collection School Of Computing and Information Systems

Dimensionality reduction aims at reducing redundant information in big data and hence making data analysis more efficient. Resource-constrained enterprises or individuals often outsource this time-consuming job to the cloud for saving storage and computing resources. However, due to inadequate supervision, the privacy and security of outsourced data have been a serious concern to data owners. In this paper, we propose a privacypreserving and verifiable outsourcing scheme for data dimension reduction, based on incremental Non-negative Matrix Factorization (NMF) method. We emphasize the importance of incremental data processing, exploiting the properties of NMF to enable data dynamics in consideration of data updating …

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Enhancing Project Based Learning With Unsupervised Learning Of Project Reflections, Hua Leong Fwa Sep 2021

Enhancing Project Based Learning With Unsupervised Learning Of Project Reflections, Hua Leong Fwa

Research Collection School Of Computing and Information Systems

Natural Language Processing (NLP) is an area of research and application that uses computers to analyze human text. It has seen wide adoption within several industries but few studies have investigated it for use in evaluating the effectiveness of educational interventions and pedagogies. Pedagogies such as Project based learning (PBL) centers on learners solving an authentic problem or challenge which leads to knowledge creation and higher engagement. PBL also lends itself well in plugging the gap between what is taught in classrooms and applying the knowledge gained to the real working environment. In this study, we seek to investigate how …

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Dynamic Heterogeneous Graph Embedding Via Heterogeneous Hawkes Process, Yugang Ji, Tianrui Jia, Yuan Fang, Chuan Shi Sep 2021

Dynamic Heterogeneous Graph Embedding Via Heterogeneous Hawkes Process, Yugang Ji, Tianrui Jia, Yuan Fang, Chuan Shi

Research Collection School Of Computing and Information Systems

Graph embedding, aiming to learn low-dimensional representations of nodes while preserving valuable structure information, has played a key role in graph analysis and inference. However, most existing methods deal with static homogeneous topologies, while graphs in real-world scenarios are gradually generated with different-typed temporal events, containing abundant semantics and dynamics. Limited work has been done for embedding dynamic heterogeneous graphs since it is very challenging to model the complete formation process of heterogeneous events. In this paper, we propose a novel Heterogeneous Hawkes Process based dynamic Graph Embedding (HPGE) to handle this problem. HPGE effectively integrates the Hawkes process into …

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Quantum Computing For Supply Chain Finance, Paul R. Griffin, Ritesh Sampat Sep 2021

Quantum Computing For Supply Chain Finance, Paul R. Griffin, Ritesh Sampat

Research Collection School Of Computing and Information Systems

Applying quantum computing to real world applications to assess the potential efficacy is a daunting task for non-quantum specialists. This paper shows an implementation of two quantum optimization algorithms applied to portfolios of trade finance portfolios and compares the selections to those chosen by experienced underwriters and a classical optimizer. The method used is to map the financial risk and returns for a trade finance portfolio to an optimization function of a quantum algorithm developed in a Qiskit tutorial. The results show that whilst there is no advantage seen by using the quantum algorithms, the performance of the quantum algorithms …

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Which Variables Should I Log?, Zhongxin Liu, Xin Xia, David Lo, Zhenchang Xing, Ahmed E. Hassan, Shanping Li Sep 2021

Which Variables Should I Log?, Zhongxin Liu, Xin Xia, David Lo, Zhenchang Xing, Ahmed E. Hassan, Shanping Li

Research Collection School Of Computing and Information Systems

Developers usually depend on inserting logging statements into the source code to collect system runtime information. Such logged information is valuable for software maintenance. A logging statement usually prints one or more variables to record vital system status. However, due to the lack of rigorous logging guidance and the requirement of domain-specific knowledge, it is not easy for developers to make proper decisions about which variables to log. To address this need, in this work, we propose an approach to recommend logging variables for developers during development by learning from existing logging statements. Different from other prediction tasks in software …

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Semi-Supervised Semantic Visualization For Networked Documents, Delvin Ce Zhang, Hady W. Lauw Sep 2021

Semi-Supervised Semantic Visualization For Networked Documents, Delvin Ce Zhang, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Semantic interpretability and visual expressivity are important objectives in exploratory analysis of text. On the one hand, while some documents may have explicit categories, we could develop a better understanding of a corpus by studying its finer-grained structures, which may be latent. By inferring latent topics and discovering keywords associated with each topic, one obtains a semantic interpretation of the corpus. One the other hand, by visualizing documents, latent topics, and category labels on the same plot, one gains a bird’s eye view of the relationships among documents, topics, and various categories. Semantic visualization is a class of methods that …

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Does Bert Understand Idioms? A Probing-Based Empirical Study Of Bert Encodings Of Idioms, Minghuan Tan, Jing Jiang Sep 2021

Does Bert Understand Idioms? A Probing-Based Empirical Study Of Bert Encodings Of Idioms, Minghuan Tan, Jing Jiang

Research Collection School Of Computing and Information Systems

Understanding idioms is important in NLP. In this paper, we study to what extent pre-trained BERT model can encode the meaning of a potentially idiomatic expression (PIE) in a certain context. We make use of a few existing datasets and perform two probing tasks: PIE usage classification and idiom paraphrase identification. Our experiment results suggest that BERT indeed can separate the literal and idiomatic usages of a PIE with high accuracy. It is also able to encode the idiomatic meaning of a PIE to some extent.

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Learning And Evaluating Chinese Idiom Embeddings, Minghuan Tan, Jing Jiang Sep 2021

Learning And Evaluating Chinese Idiom Embeddings, Minghuan Tan, Jing Jiang

Research Collection School Of Computing and Information Systems

We study the task of learning and evaluating Chinese idiom embeddings. We first construct a new evaluation dataset that contains idiom synonyms and antonyms. Observing that existing Chinese word embedding methods may not be suitable for learning idiom embeddings, we further present a BERT-based method that directly learns embedding vectors for individual idioms. We empirically compare representative existing methods and our method. We find that our method substantially outperforms existing methods on the evaluation dataset we have constructed.

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Artificial Intelligence And Work: Two Perspectives, Steven Miller, Thomas H. Davenport Sep 2021

Artificial Intelligence And Work: Two Perspectives, Steven Miller, Thomas H. Davenport

Research Collection School Of Computing and Information Systems

One of the most important issues in contemporary societies is the impact of intelligent technologies on human work. For an empirical perspective on the issue, we recently completed 30 case studies of people collaborating with AI-enabled smart machines. Twenty-four were from North America, mostly in the US. Six were from Southeast Asia, mostly in Singapore. We compare some of our observations to one of the broadest academic examinations of the issue. In particular, we focus on our case study observations with regard to key findings from the MIT Task Force on the Work of the Future report.

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The Empathetic Car: Exploring Emotion Inference Via Driver Behaviour And Traffic Context, Shu Liu, Kevin Koch, Zimu Zhou, Simon Foll, Xiaoxi He, Tina Menke, Elgar Fleisch, Felix Wortmann Sep 2021

The Empathetic Car: Exploring Emotion Inference Via Driver Behaviour And Traffic Context, Shu Liu, Kevin Koch, Zimu Zhou, Simon Foll, Xiaoxi He, Tina Menke, Elgar Fleisch, Felix Wortmann

Research Collection School Of Computing and Information Systems

An empathetic car that is capable of reading the driver’s emotions has been envisioned by many car manufacturers. Emotion inference enables in-vehicle applications to improve driver comfort, well-being, and safety. Available emotion inference approaches use physiological, facial, and speech-related data to infer emotions during driving trips. However, existing solutions have two major limitations: Relying on sensors that are not built into the vehicle restricts emotion inference to those people leveraging corresponding devices (e.g., smartwatches). Relying on modalities such as facial expressions and speech raises privacy concerns. By contrast, researchers in mobile health have been able to infer affective states (e.g., …

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Feeder Vessel Routing And Transshipment Coordination At A Congested Hub Port, Jiangang Jin, Qiang Meng, Hai Wang Sep 2021

Feeder Vessel Routing And Transshipment Coordination At A Congested Hub Port, Jiangang Jin, Qiang Meng, Hai Wang

Research Collection School Of Computing and Information Systems

With increasing container-shipping traffic, congestion at transshipment hub ports happens from time to time incurring longer-than-expected waiting time for vessels and loss of transshipment connections. This situation is even worse for feeder companies, due to their relatively lower berthing priority. It is essential to design the feeder vessel routes and schedules in response to hub port congestion while ensuring efficient transshipment connection with their connecting long-haul services. In this paper, we study the vessel routing and transshipment coordination problem for a feeder liner company where only limited choices of berthing time slots are available at the hub port. We proposed …

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Holistic Prediction For Public Transport Crowd Flows: A Spatio Dynamic Graph Network Approach, Bingjie He, Shukai Li, Chen Zhang, Baihua Zheng, Fugee Tsung Sep 2021

Holistic Prediction For Public Transport Crowd Flows: A Spatio Dynamic Graph Network Approach, Bingjie He, Shukai Li, Chen Zhang, Baihua Zheng, Fugee Tsung

Research Collection School Of Computing and Information Systems

This paper targets at predicting public transport in-out crowd flows of different regions together with transit flows between them in a city. The main challenge is the complex dynamic spatial correlation of crowd flows of different regions and origin-destination (OD) paths. Different from road traffic flows whose spatial correlations mainly depend on geographical distance, public transport crowd flows significantly relate to the region’s functionality and connectivity in the public transport network. Furthermore, influenced by commuters’ time-varying travel patterns, the spatial correlations change over time. Though there exist many works focusing on either predicting in-out flows or OD transit flows of …

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Evaluation Of Wind Data Reliability By Using Logarithmic And Power Laws: A Case Study In Southern Iraq, Ahmed B. Khamees, Saif F. Yaseen, Khalid S. Heni, Mudar Ahmed Abdulsattar Aug 2021

Evaluation Of Wind Data Reliability By Using Logarithmic And Power Laws: A Case Study In Southern Iraq, Ahmed B. Khamees, Saif F. Yaseen, Khalid S. Heni, Mudar Ahmed Abdulsattar

Karbala International Journal of Modern Science

In this study, two sites were investigated in the southern region of Iraq: Ali AL-Gharbi and AL-Salman in Mesan and AL-Muthana provinces, respectively. A theoretical extrapolation between wind speed and height was carried out for both locations each month using the Logarithmic Law. Power Law was also applied to achieve calculations of wind shear coefficient (α) by using the actual data collected from the meteorological mast installed in each site at three levels of 10 m, 30 m, and 50 m, at an interval of ten minutes. To compare the effects of each law, two laws are employed.

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Polystyrene Molecular Weight Determination Of Submicron Particles Shell, Airat Z. Sakhabutdinov, Safaa.M.R.H. Hussein, Alsu R. Ibragimova Ph.D., Vladimir Kuklin Ph.D., Maxim Petrovich Danilaev, L.Y. Zaharova Aug 2021

Polystyrene Molecular Weight Determination Of Submicron Particles Shell, Airat Z. Sakhabutdinov, Safaa.M.R.H. Hussein, Alsu R. Ibragimova Ph.D., Vladimir Kuklin Ph.D., Maxim Petrovich Danilaev, L.Y. Zaharova

Karbala International Journal of Modern Science

The method of determination of the molecular weight of the polystyrene, which is formed as the shell on the surfaces of submicron aluminum oxide particles is considered in the paper. This method is based on the sedimentation of submicron particles, covered by polymer molecules, in a solvent for polystyrene. It is shown that the average polystyrene molecular weight is 39500±11250 amu, when the polymer shells on the surfaces of submicron particles (Al2O3) are formed by the vapor-phase method.

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Adaptive Reconstruction Of The Heterogeneous Scan Line Etm+ Correction Technique, Heba Kh. Abbas, Salema S. Salman, Rash Awad Abtan, Anwar H. Al-Saleh, Ali A. Al-Zuky Aug 2021

Adaptive Reconstruction Of The Heterogeneous Scan Line Etm+ Correction Technique, Heba Kh. Abbas, Salema S. Salman, Rash Awad Abtan, Anwar H. Al-Saleh, Ali A. Al-Zuky

Karbala International Journal of Modern Science

ETM+ is a land-imaging sensor with great and wide use in many fields, however, after May 2003, because of a technical defect in the sensor´s system scan line corrector SLC, it started giving images of earth containing black gap lines at a 22% rate. These gaps made the process of analyzing and extracting accurate information from these images difficult and complicated. Therefore, scientists have developed many techniques to remove the gap lines from all ETM+ band-images and complete the missing data. In this study, three different ETM+ time images with a 16-day interval between them were used to fill gap …

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Two-Dimensional Quantitative Profiling Of Cell Morphology With Serous Effusion By Unsupervised Machine Learning Analysis, Safaa Al-Qaysi Ph.D., Ding Dai Md Ph.D., Heng Hong Md Ph.D., Yuhua Wen Ph.D., X.H. Hu Ph.D. Aug 2021

Two-Dimensional Quantitative Profiling Of Cell Morphology With Serous Effusion By Unsupervised Machine Learning Analysis, Safaa Al-Qaysi Ph.D., Ding Dai Md Ph.D., Heng Hong Md Ph.D., Yuhua Wen Ph.D., X.H. Hu Ph.D.

Karbala International Journal of Modern Science

Cytological evaluation of serous effusion specimens is an important part of cancer diagnosis. In this study we performed two-dimensional (2D) morphometric features and clustering analysis for development of useful techniques for identification and differentiation of malignant and begin cells in serous effusion specimens extracted from ten patients with clinical symptoms of pleural and peritoneal effusion. Our findings show that the two-dimensional (2D) morphometric features and clustering analysis are useful techniques for identification and differentiation of malignant and begin cells in serous effusion specimens, which can lead to development of new methods for rapid cells profiling in clinical application.

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Stability-Delay Efficient Cluster-Based Routing Protocol For Vanet, Ahmed Jawad Kadhim Al-Shaibany Ph.D Aug 2021

Stability-Delay Efficient Cluster-Based Routing Protocol For Vanet, Ahmed Jawad Kadhim Al-Shaibany Ph.D

Karbala International Journal of Modern Science

Vehicular Ad hoc Network (VANET) can be used in safety applications to transfer information about some events (e.g. accidents) with minimum time. Sending this information is achieved by using a routing algorithm. A large number of cluster-based routing schemes were presented for VANET. Unfortunately, the mobility of vehicles in unexpected directions negatively affects the performance of these schemes, destroys the network links, and decreases the routes' stability. This problem leads to repeat route discovery and maintenance operations and, as a result increases the overhead and delay. Thus, they are not an optimal selection for safety applications. Moreover, the cluster-based policies …

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A New Chaotic Image Cryptosystem Based On Plaintext-Associated Mechanism And Integrated Confusion-Diffusion Operation, Ahmed Kareem Shibeeb, Mohammed Hussein Ahmed, Ahmed Hashim Mohammed Aug 2021

A New Chaotic Image Cryptosystem Based On Plaintext-Associated Mechanism And Integrated Confusion-Diffusion Operation, Ahmed Kareem Shibeeb, Mohammed Hussein Ahmed, Ahmed Hashim Mohammed

Karbala International Journal of Modern Science

In modern chaotic image cryptosystems, the initial values generated for the chaotic system are carried out based on the hash function or summation result of the image pixels. Also, the confusion-diffusion structure is often typically split into two different components. However, it decreases the cryptosystem security because the independent structure can be cryptanalysis separately. A practical chaotic image cryptosystem based on plaintext-associated mechanism and integrated confusion-diffusion operation has been developed in this research paper to enhance the encryption reliability. The initial values of the four-dimensional chaotic system are updated by using the pixel values and locations to increase the sensitivity …

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Editorial Board Aug 2021

Editorial Board

Karbala International Journal of Modern Science

No abstract provided.

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An Empirical Study Of Thermal Attacks On Edge Platforms, Tyler Holmes Aug 2021

An Empirical Study Of Thermal Attacks On Edge Platforms, Tyler Holmes

Symposium of Student Scholars

Cloud-edge systems are vulnerable to thermal attacks as the increased energy consumption may remain undetected, while occurring alongside normal, CPU-intensive applications. The purpose of our research is to study thermal effects on modern edge systems. We also analyze how performance is affected from the increased heat and identify preventative measures. We speculate that due to the technology being a recent innovation, research on cloud-edge devices and thermal attacks is scarce. Other research focuses on server systems rather than edge platforms. In our paper, we use a Raspberry Pi 4 and a CPU-intensive application to represent thermal attacks on cloud-edge systems. …

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Molecular Vibrations Of Symmetric Molecules: Raman Scattering Driven Molecular Dynamics Method, Martina Kaledin, Dominick Pierre-Jacques, Ciara Tyler, Jason Dyke Aug 2021

Molecular Vibrations Of Symmetric Molecules: Raman Scattering Driven Molecular Dynamics Method, Martina Kaledin, Dominick Pierre-Jacques, Ciara Tyler, Jason Dyke

Symposium of Student Scholars

This project focuses on developing a novel computational technique to study molecular vibrations through infrared (IR) and Raman scattering Driven Molecular Dynamics (DMD) method. While the main criterion for IR absorption is a net change in the dipole moment in a molecule as it vibrates, presently we wish to predict and analyze vibrational spectra to study symmetric vibrational modes that are IR inactive or weakly active while strongly Raman active. A newly developed method was tested on CO2, H2O, CH4, and C20 molecules. Students optimized the molecular structures, obtained vibrational frequencies, and IR …

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Learning Environment Containerization Of Machine Learning For Cybersecurity, Hao Zhang Aug 2021

Learning Environment Containerization Of Machine Learning For Cybersecurity, Hao Zhang

Symposium of Student Scholars

Machine learning plays a critical role in detecting and preventing in the field of cybersecurity. However, many students have difficulties on configuring the appropriate coding environment and retrieving datasets on their own computers, which, to some extent, wastes valuable time for learning core contents of machine learning and cybersecurity. In this paper, we propose an approach with learning environment containerization of machine learning algorithm and dataset. This will help students focus more on learning contents and have valuable hand-on experience through Docker container and get rid of the trouble of configuration coding environment and retrieve dataset. This paper provides an …

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Spam Email Detection: Comparison Between Naïve Bayes And Neural Network, Zhuolin Li Aug 2021

Spam Email Detection: Comparison Between Naïve Bayes And Neural Network, Zhuolin Li

Symposium of Student Scholars

Classification is an important technique to deal with cybersecurity threats. In this paper, we detect spam emails from publicly available dataset using Naive Bayes and Neural Network (NN). The results from experiments show that for data sets with more balanced for classification, the accuracy of Naive Bayes is better than NN

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Finding Similar Stocks By Detecting Cliques In Market Graphs, Sudhashree Sayenju Aug 2021

Finding Similar Stocks By Detecting Cliques In Market Graphs, Sudhashree Sayenju

Symposium of Student Scholars

The stock market provides an abundant source of data. However, when the amount of raw data becomes overwhelming it grows increasingly difficult to know how the stocks interact with each other. Stock data visualization as a market graph serves as one of the most popular way of summarizing important information. When modelling the data as a graph, vertices correspond to stocks and edges correspond to strong correlation in their pricing in a certain period of time. This project presents a technique to find stocks that behave very similarly. Such information helps investors make decisions on which stocks to purchase next. …

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Probing Structure And Energetics Of Proton-Bound Complexes N2…Hco+ And N2h+…Oc Using Computational Chemistry Methods, Antonio Barrios, Dalton Boutwell, Onyi Okere, Monique Olocha, Oluwaseun Omodemi, Alexander Toledo, Antonio Barrios Aug 2021

Probing Structure And Energetics Of Proton-Bound Complexes N2…Hco+ And N2h+…Oc Using Computational Chemistry Methods, Antonio Barrios, Dalton Boutwell, Onyi Okere, Monique Olocha, Oluwaseun Omodemi, Alexander Toledo, Antonio Barrios

Symposium of Student Scholars

N2…HCO+ and N2H+…OC are predicted to exist in interstellar clouds. These complexes involve HCO+ and N2H+ fragments that are bound to N2 and CO, respectively using hydrogen-bonded interaction. The reason these molecules are important is that the existence of nitrogen can be measured indirectly through ion-molecular complexes studied in this work. The measured vibrational spectra of molecules is an excellent way to characterize and detect molecules. We used B3LYP, MP2, and CCSD(T) computational methods to predict the structure and vibrational frequencies of N2…HCO+ and N …

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Theoretical Study On The Isomerization And Detection Of N2h+…Oc Complex In Interstellar Clouds, Dalton Boutwell, Martina Kaledin Aug 2021

Theoretical Study On The Isomerization And Detection Of N2h+…Oc Complex In Interstellar Clouds, Dalton Boutwell, Martina Kaledin

Symposium of Student Scholars

In this study, we characterize N2H+…OC linear complex using Driven Molecular Dynamics (DMD) and Vibrational Self-Consistent Field Theory (VSCF) methods due to its relevance in astrochemistry. A central challenge is the detection of the molecular complex in interstellar media (ISM). Computational chemistry approaches can predict vibrational spectra, hence facilitate prediction of its existence and stability in the ISM. N2H+…OC involves the proton transfer process via hydrogen bonding interaction. Proton motion is highly anharmonic, therefore facing a significant challenge to characterize it accurately. Quantum mechanical variational methods are popular among many theoretical chemists …

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Energy Saving On Edges: State-Of-The-Art And Future Directions, Kousalya Banka Aug 2021

Energy Saving On Edges: State-Of-The-Art And Future Directions, Kousalya Banka

Symposium of Student Scholars

Internet of Things (IoT) comprises a set of devices that are interconnected ranging from our daily used objects to advanced networked devices. It is a constantly evolving phenomenon as the number of devices owned by the regular user is increasing at a rapid rate. These devices are used for various reasons such as social networking, monitoring, performing complex operations and with the increase of advanced technologies, they demand more energy to perform such tasks. Cloud computing enables these communications to seamlessly perform complex tasks in a cloud environment but utilizing these resources properly to perform at the best is the …

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