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Articles 121 - 150 of 166
Full-Text Articles in Numerical Analysis and Scientific Computing
Multi-Threaded Automatic Integration Using Openmp And Cuda, Rida Assaf
Multi-Threaded Automatic Integration Using Openmp And Cuda, Rida Assaf
Masters Theses
Problems in many areas give rise to computationally expensive integrals that beg the need of efficient techniques to solve them, e.g., in computational finance for the modeling of cash flows; for the computation of Feynman loop integrals in high energy physics; and in stochastic geometry with applications to computer graphics.
We demonstrate feasible numerical approaches in the framework of the PARINT multivariate integration package. The parallel environment is provided by the cluster of the High Performance Computational Science (HPCS) laboratory, with 22 (16- or 32-core) nodes, NVIDIA GPUs, and Intel Xeon Phi coprocessors.
Monte Carlo integration is implemented in CUDA …
Computational Pain Quantification And The Effects Of Age, Gender, Culture And Cause, Colin R. Ostberg
Computational Pain Quantification And The Effects Of Age, Gender, Culture And Cause, Colin R. Ostberg
Master's Theses (2009 -)
Chronic pain affects more than 100 million Americans and more than 1.5 billion people worldwide. Pain is a multidimensional construct, expressed through a variety of means. Facial expressions are one such type of pain expression. Automatic facial expression recognition, and in particular pain expression recognition, are fields that have been studied extensively. However, nothing has explored the possibility of an automatic pain quantification algorithm, able to output pain levels based upon a facial image. Developed for a remote monitoring context, a computational pain quantification algorithm has been developed and validated by two distinct sets of data. The second set of …
Ubiquitous Data-Centric Sensor Networks, Ting Yang, Peng Yung Woo, Zhaoxia Wang, Javid Taheri, Hoong Chor Chin, Guaqiang Hu
Ubiquitous Data-Centric Sensor Networks, Ting Yang, Peng Yung Woo, Zhaoxia Wang, Javid Taheri, Hoong Chor Chin, Guaqiang Hu
Research Collection School Of Computing and Information Systems
Ubiquitous data-centric sensor networks (U-DCSN) are a new integrated science and technology, which focus on data instead of individual sensor nodes. The network, as a dynamic database system, can accurately acquire data, perform high-performance processing of big data, and effectively access data from different users/actuators. Due this characteristic, U-DCSN hold huge potentials on service improvement in a wide range of applications and have attracted significant attention in recent years, for example, mobile cloud and consumer electronics. The modern mobile cloud, comprised of mobile devices (smart phones, tablets, and embedded sensor nodes), provides unlimited information resources, putting “cloud into a pocket.” …
Recommending Investors For Crowdfunding Projects, Jisun An, Daniele Quercia, Jon Crowcroft
Recommending Investors For Crowdfunding Projects, Jisun An, Daniele Quercia, Jon Crowcroft
Research Collection School Of Computing and Information Systems
To bring their innovative ideas to market, those embarking in new ventures have to raise money, and, to do so, they have often resorted to banks and venture capitalists. Nowadays, they have an additional option: that of crowdfunding. The name refers to the idea that funds come from a network of people on the Internet who are passionate about supporting others' projects. One of the most popular crowdfunding sites is Kickstarter. In it, creators post descriptions of their projects and advertise them on social media sites (mainly Twitter), while investors look for projects to support. The most common reason for …
On Modeling Community Behaviors And Sentiments In Microblogging, Tuan Anh Hoang, William Cohen, Ee Peng Lim
On Modeling Community Behaviors And Sentiments In Microblogging, Tuan Anh Hoang, William Cohen, Ee Peng Lim
Research Collection School Of Computing and Information Systems
In this paper, we propose the CBS topic model, a probabilistic graphical model, to derive the user communities in microblogging networks based on the sentiments they express on their generated content and behaviors they adopt. As a topic model, CBS can uncover hidden topics and derive user topic distribution. In addition, our model associates topic-specific sentiments and behaviors with each user community. Notably, CBS has a general framework that accommodates multiple types of behaviors simultaneously. Our experiments on two Twitter datasets show that the CBS model can effectively mine the representative behaviors and emotional topics for each community. We also …
On Finding The Point Where There Is No Return: Turning Point Mining On Game Data, Wei Gong, Ee Peng Lim, Feida Zhu, Achananuparp Palakorn, David Lo
On Finding The Point Where There Is No Return: Turning Point Mining On Game Data, Wei Gong, Ee Peng Lim, Feida Zhu, Achananuparp Palakorn, David Lo
Research Collection School Of Computing and Information Systems
Gaming expertise is usually accumulated through playing or watching many game instances, and identifying critical moments in these game instances called turning points. Turning point rules (shorten as TPRs) are game patterns that almost always lead to some irreversible outcomes. In this paper, we formulate the notion of irreversible outcome property which can be combined with pattern mining so as to automatically extract TPRs from any given game datasets. We specifically extend the well-known PrefixSpan sequence mining algorithm by incorporating the irreversible outcome property. To show the usefulness of TPRs, we apply them to Tetris, a popular game. We mine …
Modeling Contextual Agreement In Preferences, Ha Loc Do, Hady Wirawan Lauw
Modeling Contextual Agreement In Preferences, Ha Loc Do, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
Personalization, or customizing the experience of each individual user, is seen as a useful way to navigate the huge variety of choices on the Web today. A key tenet of personalization is the capacity to model user preferences. The paradigm has shifted from that of individual preferences, whereby we look at a user's past activities alone, to that of shared preferences, whereby we model the similarities in preferences between pairs of users (e.g., friends, people with similar interests). However, shared preferences are still too granular, because it assumes that a pair of users would share preferences across all items. We …
Phonon Density Of States And Anharmonicity Of Uo₂, Judy W. Pang, Aleksandr V. Chernatynskiy, Bennett C. Larson, William J. Buyers, Douglas L. Abernathy, Kenneth J. Mcclellan, Simon R. Phillpot
Phonon Density Of States And Anharmonicity Of Uo₂, Judy W. Pang, Aleksandr V. Chernatynskiy, Bennett C. Larson, William J. Buyers, Douglas L. Abernathy, Kenneth J. Mcclellan, Simon R. Phillpot
Physics Faculty Research & Creative Works
Phonon density of states (PDOS) measurements have been performed on polycrystalline UO2 at 295 and 1200 K using time-of-flight inelastic neutron scattering to investigate the impact of anharmonicity on the vibrational spectra and to benchmark ab initio PDOS simulations performed on this strongly correlated Mott insulator. Time-of-flight PDOS measurements include anharmonic linewidth broadening, inherently, and the factor of ~7 enhancement of the oxygen spectrum relative to the uranium component by the increased neutron sensitivity to the oxygen-dominated optical phonon modes. The first-principles simulations of quasiharmonic PDOS spectra were neutron weighted and anharmonicity was introduced in an approximate way by …
Computational Study Of The Rovibrational Spectrum Of Co₂-Cs₂, James Corgan Brown, Xiao-Gang Wang, Tucker Carrington Jr., Garry S. Grubbs, Richard Dawes
Computational Study Of The Rovibrational Spectrum Of Co₂-Cs₂, James Corgan Brown, Xiao-Gang Wang, Tucker Carrington Jr., Garry S. Grubbs, Richard Dawes
Chemistry Faculty Research & Creative Works
A new intermolecular potential energy surface, rovibrational transition frequencies, and line strengths are computed for CO2-CS2. the potential is made by fitting energies obtained from explicitly correlated coupled-cluster calculations using an interpolating moving least squares method. the rovibrational Schrödinger equation is solved with a symmetry-adapted Lanczos algorithm and an uncoupled product basis set. All four intermolecular coordinates are included in the calculation. in agreement with previous experiments, the global minimum of the potential energy surface (PES) is cross shaped. the PES also has slipped-parallel minima. Rovibrational wavefunctions are localized in the cross minima and the slipped-parallel …
Receiver Function Constraints On Crustal Seismic Velocities And Partial Melting Beneath The Red Sea Rift And Adjacent Regions, Afar Depression, Cory A. Reed, Sattam Almadani, Stephen S. Gao, Ahmed A. Elsheikh, Solomon Cherie, Mohamed G. Abdel Salam, Allison K. Thurmond, Kelly H. Liu
Receiver Function Constraints On Crustal Seismic Velocities And Partial Melting Beneath The Red Sea Rift And Adjacent Regions, Afar Depression, Cory A. Reed, Sattam Almadani, Stephen S. Gao, Ahmed A. Elsheikh, Solomon Cherie, Mohamed G. Abdel Salam, Allison K. Thurmond, Kelly H. Liu
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
The Afar Depression is an ideal locale for the investigation of crustal processes involved in the transition from continental rifting to oceanic spreading. To provide relatively high resolution images of the crust beneath the Red Sea rift (RSR) represented by the Tendaho graben in the Afar Depression, we deployed an array of 18 broadband seismic stations in 2010 and 2011. Stacking of about 2300 receiver functions from the 18 and several nearby stations along the ~200 km long array reveals an average crustal thickness of 22 ± 4 km, ranging from ~17 km near the RSR axis to 30 km …
Seismic Anisotropy And Mantle Flow Beneath The Northern Great Plains Of North America, Bin B. Yang, Stephen S. Gao, Kelly H. Liu, Ahmed A. Elsheikh, Awad A. Lemnifi, Hesham A. Refayee, Youqiang Yu
Seismic Anisotropy And Mantle Flow Beneath The Northern Great Plains Of North America, Bin B. Yang, Stephen S. Gao, Kelly H. Liu, Ahmed A. Elsheikh, Awad A. Lemnifi, Hesham A. Refayee, Youqiang Yu
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
A diverse set of tectonic features and the recent availability of high-quality broadband seismic data from the USArray and other stations on the northern Great Plains of North America provide a distinct opportunity to test different anisotropy-forming mechanisms. A total of 4138 pairs of well-defined splitting parameters observed at 445 stations show systematic spatial variations of anisotropic characteristics. Azimuthally invariant fast orientations subparallel to the absolute plate motion (APM) direction are observed at most of the stations on the Superior Craton and the southern Yavapai province, indicating that a single layer of anisotropy with a horizontal axis of symmetry is …
Proton Computed Tomography: Matrix Data Generation Through General Purpose Graphics Processing Unit Reconstruction, Micah Witt
Electronic Theses, Projects, and Dissertations
Proton computed tomography (pCT) is an image modality that will improve treatment planning for patients receiving proton radiation therapy compared with the current techniques, which are based on X-ray CT. Images are reconstructed in pCT by solving a large and sparse system of linear equations. The size of the system necessitates matrix-partitioning and parallel reconstruction algorithms to be implemented across some sort of cluster computing architecture. The prototypical algorithm to solve the pCT system is the algebraic reconstruction technique (ART) that has been modified into parallel versions called block-iterative-projection (BIP) methods and string-averaging-projection (SAP) methods. General purpose graphics processing units …
On Predicting User Affiliations Using Social Features In Online Social Networks, Minh Thap Nguyen
On Predicting User Affiliations Using Social Features In Online Social Networks, Minh Thap Nguyen
Dissertations and Theses Collection (Open Access)
User profiling such as user affiliation prediction in online social network is a challenging task, with many important applications in targeted marketing and personalized recommendation. The research task here is to predict some user affiliation attributes that suggest user participation in different social groups.
Online Feature Selection And Its Applications, Jialei Wang, Peilin Zhao, Steven C. H. Hoi, Rong Jin
Online Feature Selection And Its Applications, Jialei Wang, Peilin Zhao, Steven C. H. Hoi, Rong Jin
Research Collection School Of Computing and Information Systems
Feature selection is an important technique for data mining. Despite its importance, most studies of feature selection are restricted to batch learning. Unlike traditional batch learning methods, online learning represents a promising family of efficient and scalable machine learning algorithms for large-scale applications. Most existing studies of online learning require accessing all the attributes/features of training instances. Such a classical setting is not always appropriate for real-world applications when data instances are of high dimensionality or it is expensive to acquire the full set of attributes/features. To address this limitation, we investigate the problem of online feature selection (OFS) in …
Retrieval-Based Face Annotation By Weak Label Regularized Local Coordinate Coding, Dayong Wang, Steven C. H. Hoi, Ying He, Jianke Zhu, Mei Tao, Jiebo Luo
Retrieval-Based Face Annotation By Weak Label Regularized Local Coordinate Coding, Dayong Wang, Steven C. H. Hoi, Ying He, Jianke Zhu, Mei Tao, Jiebo Luo
Research Collection School Of Computing and Information Systems
Auto face annotation, which aims to detect human faces from a facial image and assign them proper human names, is a fundamental research problem and beneficial to many real-world applications. In this work, we address this problem by investigating a retrieval-based annotation scheme of mining massive web facial images that are freely available over the Internet. In particular, given a facial image, we first retrieve the top n similar instances from a large-scale web facial image database using content-based image retrieval techniques, and then use their labels for auto annotation. Such a scheme has two major challenges: 1) how to …
Social Correlation In Latent Spaces For Complex Networks, Freddy Chong Tat Chua
Social Correlation In Latent Spaces For Complex Networks, Freddy Chong Tat Chua
Dissertations and Theses Collection (Open Access)
This dissertation addresses the subject of measuring social correlation among users within a complex social network. Social correlation is closely related to the measurement of social influence in social sciences. While social influence focuses on the existence of causal influence among users, we take a computational approach to measure correlation strength among users based on their shared interactions. We call this social correlation. To formally model social correlation, we propose a framework which contains two major parts. The first part is that of representing users behavior in a computationally efficient and accurate manner. For example, social media users perform many …
Criticality And Quenched Disorder: Harris Criterion Versus Rare Regions, Thomas Vojta, José A. Hoyos
Criticality And Quenched Disorder: Harris Criterion Versus Rare Regions, Thomas Vojta, José A. Hoyos
Physics Faculty Research & Creative Works
We employ scaling arguments and optimal fluctuation theory to establish a general relation between quantum Griffiths singularities and the Harris criterion for quantum phase transitions in disordered systems. If a clean critical point violates the Harris criterion, it is destabilized by weak disorder. At the same time, the Griffiths dynamical exponent z' diverges upon approaching the transition, suggesting unconventional critical behavior. In contrast, if the Harris criterion is fulfilled, power-law Griffiths singularities can coexist with clean critical behavior, but z' saturates at a finite value. We present applications of our theory to a variety of systems including quantum spin chains, …
Role Of Electron Saddle Swaps In The Photon Spectra Following Li³⁺ Charge-Exchange Collisions With H*(N = 2), Na(3s), Na*(3p), And Li(2s) Targets, Sebastian Otranto, R. Hoekstra, Ronald E. Olson
Role Of Electron Saddle Swaps In The Photon Spectra Following Li³⁺ Charge-Exchange Collisions With H*(N = 2), Na(3s), Na*(3p), And Li(2s) Targets, Sebastian Otranto, R. Hoekstra, Ronald E. Olson
Physics Faculty Research & Creative Works
The role of electron saddle swaps in collisions of bare Li with metastable hydrogen and alkali-metal atoms is investigated by means of the classical trajectory Monte Carlo method. In particular, we show that oscillations as a function of collision energy in the photon spectra resulting from charge exchange are directly related to the number of potential-saddle crossings that a receding electron can achieve during a given reaction. The range of impact energies spanned is 0.01-50 keV/amu, an area of interest for diagnostic purposes in tokamak nuclear fusion power reactors.
Predicting Response In Mobile Advertising With Hierarchical Importance-Aware Factorization Machine, Richard Jayadi Oentaryo, Ee Peng Lim, Jia Wei Low, David Lo, Michael Finegold
Predicting Response In Mobile Advertising With Hierarchical Importance-Aware Factorization Machine, Richard Jayadi Oentaryo, Ee Peng Lim, Jia Wei Low, David Lo, Michael Finegold
Research Collection School Of Computing and Information Systems
Mobile advertising has recently seen dramatic growth, fueled by the global proliferation of mobile phones and devices. The task of predicting ad response is thus crucial for maximizing business revenue. However, ad response data change dynamically over time, and are subject to cold-start situations in which limited history hinders reliable prediction. There is also a need for a robust regression estimation for high prediction accuracy, and good ranking to distinguish the impacts of different ads. To this end, we develop a Hierarchical Importance-aware Factorization Machine (HIFM), which provides an effective generic latent factor framework that incorporates importance weights and hierarchical …
A Fast Algorithm For The Inversion Of Quasiseparable Vandermonde-Like Matrices, Sirani M. Perera, Grigory Bonik, Vadim Olshevsky
A Fast Algorithm For The Inversion Of Quasiseparable Vandermonde-Like Matrices, Sirani M. Perera, Grigory Bonik, Vadim Olshevsky
Publications
The results on Vandermonde-like matrices were introduced as a generalization of polynomial Vandermonde matrices, and the displacement structure of these matrices was used to derive an inversion formula. In this paper we first present a fast Gaussian elimination algorithm for the polynomial Vandermonde-like matrices. Later we use the said algorithm to derive fast inversion algorithms for quasiseparable, semiseparable and well-free Vandermonde-like matrices having O(n2) complexity. To do so we identify structures of displacement operators in terms of generators and the recurrence relations(2-term and 3-term) between the columns of the basis transformation matrices for quasiseparable, semiseparable and well-free polynomials. Finally we …
Designs Of Fullerene-Based Frameworks For Hydrogen Storage, Yi Gao, Xiaojun Wu, Xiao Cheng Zeng
Designs Of Fullerene-Based Frameworks For Hydrogen Storage, Yi Gao, Xiaojun Wu, Xiao Cheng Zeng
Holland Computing Center: Faculty Publications
No abstract provided.
Designs Of Fullerene-Based Frameworks For Hydrogen Storage, Yi Gao, Xiaojun Wu, Xiao Cheng Zeng
Designs Of Fullerene-Based Frameworks For Hydrogen Storage, Yi Gao, Xiaojun Wu, Xiao Cheng Zeng
Holland Computing Center: Faculty Publications
No abstract provided.
Functional Evolution Of Plp-Dependent Enzymes Based On Active-Site Structural Similarities, Jonathan Catazaro, Adam Caprez, Ashu Guru, David Swanson, Robert Powers
Functional Evolution Of Plp-Dependent Enzymes Based On Active-Site Structural Similarities, Jonathan Catazaro, Adam Caprez, Ashu Guru, David Swanson, Robert Powers
Holland Computing Center: Faculty Publications
Families of distantly related proteins typically have very low sequence identity, which hinders evolutionary analysis and functional annotation. Slowly evolving features of proteins, such as an active site, are therefore valuable for annotating putative and distantly related proteins. To date, a complete evolutionary analysis of the functional relationship of an entire enzyme family based on active-site structural similarities has not yet been undertaken. Pyridoxal-5’-phosphate (PLP) dependent enzymes are primordial enzymes that diversified in the last universal ancestor. Using the Comparison of Protein Active Site Structures (CPASS) software and database, we show that the active site structures of PLP-dependent enzymes can …
A Comparative Study Of Reservoir Computing For Temporal Signal Processing, Alireza Goudarzi, Peter Banda, Matthew R. Lakin, Christof Teuscher, Darko Stefanovic
A Comparative Study Of Reservoir Computing For Temporal Signal Processing, Alireza Goudarzi, Peter Banda, Matthew R. Lakin, Christof Teuscher, Darko Stefanovic
Computer Science Faculty Publications and Presentations
Reservoir computing (RC) is a novel approach to time series prediction using recurrent neural networks. In RC, an input signal perturbs the intrinsic dynamics of a medium called a reservoir. A readout layer is then trained to reconstruct a target output from the reservoir's state. The multitude of RC architectures and evaluation metrics poses a challenge to both practitioners and theorists who study the task-solving performance and computational power of RC. In addition, in contrast to traditional computation models, the reservoir is a dynamical system in which computation and memory are inseparable, and therefore hard to analyze. Here, we compare …
Hidden Markov Model With Information Criteria Clustering And Extreme Learning Machine Regression For Wind Forecasting, Dao Lam, Shuhui Li, Donald C. Wunsch
Hidden Markov Model With Information Criteria Clustering And Extreme Learning Machine Regression For Wind Forecasting, Dao Lam, Shuhui Li, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
This paper proposes a procedural pipeline for wind forecasting based on clustering and regression. First, the data are clustered into groups sharing similar dynamic properties. Then, data in the same cluster are used to train the neural network that predicts wind speed. For clustering, a hidden Markov model (HMM) and the modified Bayesian information criteria (BIC) are incorporated in a new method of clustering time series data. to forecast wind, a new method for wind time series data forecasting is developed based on the extreme learning machine (ELM). the clustering results improve the accuracy of the proposed method of wind …
Epistasis In Predator-Prey Relationships, Iuliia Inozemtseva
Epistasis In Predator-Prey Relationships, Iuliia Inozemtseva
College of Graduate Studies: Theses & Dissertations
Epistasis is the interaction between two or more genes to control a single phenotype. We model epistasis of the prey in a two-locus two-allele problem in a basic predator- prey relationship. The resulting model allows us to examine both population sizes as well as genotypic and phenotypic frequencies. In the context of several numerical examples, we show that if epistasis results in an undesirable or desirable phenotype in the prey by making the particular genotype more or less susceptible to the predator or dangerous to the predator, elimination of undesirable phenotypes and then genotypes occurs.
Phonon Thermal Transport Through Tilt Grain Boundaries In Strontium Titanate, Zexi Zheng, Xiang Chen, Bowen Deng, Aleksandr V. Chernatynskiy, Shengfeng Yang, Jinjun Xiong, Youping Chen
Phonon Thermal Transport Through Tilt Grain Boundaries In Strontium Titanate, Zexi Zheng, Xiang Chen, Bowen Deng, Aleksandr V. Chernatynskiy, Shengfeng Yang, Jinjun Xiong, Youping Chen
Physics Faculty Research & Creative Works
In this work, we perform nonequilibrium molecular dynamics simulations to study phonon scattering at two tilt grain boundaries (GBs) in SrTiO3. Mode-wise energy transmission coefficients are obtained based on phonon wave-packet dynamics simulations. The Kapitza conductance is then quantified using a lattice dynamics approach. The obtained results of the Kapitza conductance of both GBs compare well with those obtained by the direct method, except for the temperature dependence. Contrary to common belief, the results of this work show that the optical modes in SrTiO3 contribute significantly to phonon thermal transport, accounting for over 50% of the Kapitza …
Introduction To Parallel Computation, Clinton Mckay
Introduction To Parallel Computation, Clinton Mckay
Graduate Student Theses, Dissertations, & Professional Papers
Introduction to Parallel Computing is a course designed to educate students on how to use the parallel libraries and tools provided by modern operating systems and massively parallel computer graphics hardware.
Using a series of lectures and hands-on exercises. Students will learn about parallel algorithms and concepts that will aid them in analyzing a problem and constructing a parallel solution, if possible, using the tools available to their disposal.
The course consists of lectures, projects, quizzes, and homework. The combination of these components will deliver the necessary domain knowledge to students, test them, and in the process train them to …
Mobile Indoor Positioning For Augmented Reality Systems, Robert B. Glass
Mobile Indoor Positioning For Augmented Reality Systems, Robert B. Glass
Theses and Dissertations
This thesis explores the creation and setup of a prototype that allows users of the device to interact within an indoor real world environment and a virtual environment simultaneously using high-tech common technology. The prototype is comprised of a small mobile device such as a cellular mobile phone, Raspberry Pi computer, a battery powered handheld Pico projector, and software developed for the Android OS. The software can easily be ported to other mobile and non-mobile operating systems. The mobile device must contain accelerometer, magnetometer, and gyroscope embedded sensors as well as 802.11 wireless network chip. The prototype software implements an …
Triply Differential (E,2e) Studies Of Phenol, Silva G. Da, R. F. Neves, L. Chiari, D. B. Jones, E. Ali, Don H. Madison, C. G. Ning, K. L. Nixon, M. C. Lopes, M. J. Brunger
Triply Differential (E,2e) Studies Of Phenol, Silva G. Da, R. F. Neves, L. Chiari, D. B. Jones, E. Ali, Don H. Madison, C. G. Ning, K. L. Nixon, M. C. Lopes, M. J. Brunger
Physics Faculty Research & Creative Works
We have measured (e,2e) triple differential cross sections (TDCS) for the electron-impact ionisation of phenol with coplanar asymmetrical kinematics for an incident electron energy of 250 eV. Experimental measurements of the angular distribution of the slow outgoing electrons at 20 eV are obtained when the incident electron scatters through angles of -5°, -10°, and -15°, respectively. The TDCS data are compared with calculations performed within the molecular 3-body distorted wave model. In this case, a mixed level of agreement, that was dependent on the kinematical condition being probed, was observed between the theoretical and experimental results in the binary peak …