Physical Sciences and Mathematics Commons^™

Quantum Computing And Its Applications In Healthcare, Vu Giang

OUR Journal: ODU Undergraduate Research Journal

This paper serves as a review of the state of quantum computing and its application in healthcare. The various avenues for how quantum computing can be applied to healthcare is discussed here along with the conversation about the limitations of the technology. With more and more efforts put into the development of these computers, its future is promising with the endeavors of furthering healthcare and various other industries.

A Structure-Aware Generative Adversarial Network For Bilingual Lexicon Induction, Bocheng Han, Qian Tao, Lusi Li, Zhihao Xiong

Computer Science Faculty Publications

Bilingual lexicon induction (BLI) is the task of inducing word translations with a learned mapping function that aligns monolingual word embedding spaces in two different languages. However, most previous methods treat word embeddings as isolated entities and fail to jointly consider both the intra-space and inter-space topological relations between words. This limitation makes it challenging to align words from embedding spaces with distinct topological structures, especially when the assumption of isomorphism may not hold. To this end, we propose a novel approach called the Structure-Aware Generative Adversarial Network (SA-GAN) model to explicitly capture multiple topological structure information to achieve accurate …

A Novel Hybrid Algorithm For Morphological Analysis: Artificial Neural-Net-Xmor, Ayla Kayabaş, Ahmet Ercan Topcu, Özkan Kiliç

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, we present a novel algorithm that combines a rule-based approach and an artificial neural network-based approach in morphological analysis. The usage of hybrid models including both techniques is evaluated for performance improvements. The proposed hybrid algorithm is based on the idea of the dynamic generation of an artificial neural network according to two-level phonological rules. In this study, the combination of linguistic parsing, a neural network-based error correction model, and statistical filtering is utilized to increase the coverage of pure morphological analysis. We experimented hybrid algorithm applying rule-based and long short-term memory-based (LSTM-based) techniques, and the results …

Object Manipulation With Modular Planar Tensegrity Robots, Maxine Perroni-Scharf

Dartmouth College Undergraduate Theses

This thesis explores the creation of a novel two-dimensional tensegrity-based mod- ular system. When individual planar modules are linked together, they form a larger tensegrity robot that can be used to achieve non-prehensile manipulation. The first half of this dissertation focuses on the study of preexisting types of tensegrity mod- ules and proposes different possible structures and arrangements of modules. The second half describes the construction and actuation of a modular 2D robot com- posed of planar three-bar tensegrity structures. We conclude that tensegrity modules are suitably adapted to object manipulation and propose a future extension of the modular 2D …

Lecture 08: Partial Eigen Decomposition Of Large Symmetric Matrices Via Thick-Restart Lanczos With Explicit External Deflation And Its Communication-Avoiding Variant, Zhaojun Bai

Mathematical Sciences Spring Lecture Series

There are continual and compelling needs for computing many eigenpairs of very large Hermitian matrix in physical simulations and data analysis. Though the Lanczos method is effective for computing a few eigenvalues, it can be expensive for computing a large number of eigenvalues. To improve the performance of the Lanczos method, in this talk, we will present a combination of explicit external deflation (EED) with an s-step variant of thick-restart Lanczos (s-step TRLan). The s-step Lanczos method can achieve an order of s reduction in data movement while the EED enables to compute eigenpairs in batches along with a number …

Lecture 12: Recent Advances In Time Integration Methods And How They Can Enable Exascale Simulations, Carol S. Woodward

Mathematical Sciences Spring Lecture Series

To prepare for exascale systems, scientific simulations are growing in physical realism and thus complexity. This increase often results in additional and changing time scales. Time integration methods are critical to efficient solution of these multiphysics systems. Yet, many large-scale applications have not fully embraced modern time integration methods nor efficient software implementations. Hence, achieving temporal accuracy with new and complex simulations has proved challenging. We will overview recent advances in time integration methods, including additive IMEX methods, multirate methods, and parallel-in-time approaches, expected to help realize the potential of exascale systems on multiphysics simulations. Efficient execution of these methods …

Development Of A Real Time Human Face Recognition Software System, Askar Boranbayev, Seilkhan Boranbayev, Mukhamedzhan Amirtaev, Malik Baimukhamedov, Askar Nurbekov

Physics and Astronomy Faculty Publications and Presentations

In this study, a system for real-time face recognition was built using the Open Face tools of the Open CV library. The article describes the methodology for creating the system and the results of its testing. The Open CV library has various modules that perform many tasks. In this paper, Open CV modules were used for face recognition in images and face identification in real time. In addition, the HOG method was used to detect a person by the front of his face. After performing the HOG method, 128 face measurements were obtained using the image encoding method. A convolutional …

Research On Multi-Objective Optimization Method Based On Model, Jianjun Liu, Guangya Si, Yanzheng Wang, Dachuan He

Journal of System Simulation

Abstract: There is a model-based algorithm for the optimization of multiple objective functions by means of black-box evaluation is proposed. The algorithm iteratively generates candidate solutions from a mixture distribution over the solution space and updates the mixture distribution based on the sampled solutions’ domination count, such that the future search is biased towards the set of Pareto optimal solutions. The proposed algorithm seeks to find a mixture distribution on the solution space so that each component of the mixture distribution is a degenerate distribution centered at a Pareto optimal solution and each estimated Pareto optimal solution is uniformly spread …

Design Of Unified Algorithm For Sampling Mpdu, Ti Zhou, Miao Yi, Yang Jian

Journal of System Simulation

Abstract: The standard of CCSDS AOS is used in space exploration because of the process of the standard airspace system. The spacecraft missions have used multi-protocol data unit (MPDU) to multiplex the package channels. The range of MPDU and the data are different in different spacecrafts. This process brings some problems in the maintenance and the correctness of the algorithms of virtual channel multiplexing in simulation system. The applications of CCSDS in the world were researched, and the general definitions of MPDU in these missions were described. A circle memory was given to buffer the data of MPDU, two general …

Study Of Parallelized Graph Clustering Algorithm Based On Spark, Dongjiang Liu, Jianhui Li

Journal of System Simulation

Abstract: The parallelized graph clustering algorithm is researched. A new parallelized graph clustering algorithm is proposed based on Spark. As the top operation of Spark occupies a lot of memory space, a new algorithm which is used to substitute the top operation is proposed to reduce the memory consumption. By improving bottom up hierarchical clustering algorithm, the speed of the proposed algorithm is improved. A new data filtering method based on the feature of graph data is proposed. By the method, the running time and memory space comsuption is reduced greatly. The reason of the high efficiency of this filtering …

Telemetry Parameters Simulation Of Spacecraft Based On Computation Tree, Ti Zhou, Miao Yi

Journal of System Simulation

Abstract: Simulation system of spacecrafts' Telemetry and Command (TT&C) needs to simulate lots of telemetry parameters in every missions, whose computing algorithms are different. In the past applications, these algorithms are fixed as codes in software programs, so it is very difficult to improve the maintainability and reuse of the simulation system. By studying the computing methods of telemetry parameters described in configuration files, a design scheme was given in which the algorithms of parameters were flexibly configured, and the principle of methods were described specially in computing parameters, software models, data structure and algorithms. In this framework, the algorithms …

Towards Distributed Node Similarity Search On Graphs, Tianming Zhang, Yunjun Gao, Baihua Zheng, Lu Chen, Shiting Wen, Wei Guo

Research Collection School Of Computing and Information Systems

Node similarity search on graphs has wide applications in recommendation, link prediction, to name just a few. However, existing studies are insufficient due to two reasons: (i) the scale of the real-world graph is growing rapidly, and (ii) vertices are always associated with complex attributes. In this paper, we propose an efficiently distributed framework to support node similarity search on massive graphs, which considers both graph structure correlation and node attribute similarity in metric spaces. The framework consists of preprocessing stage and query stage. In the preprocessing stage, a parallel KD-tree construction (KDC) algorithm is developed to form a newly …

Efficient Distributed Reachability Querying Of Massive Temporal Graphs, Tianming Zhang, Yunjun Gao, Chen Lu, Wei Guo, Shiliang Pu, Baihua Zheng, Christian S. Jensen

Research Collection School Of Computing and Information Systems

Reachability computation is a fundamental graph functionality with a wide range of applications. In spite of this, little work has as yet been done on efficient reachability queries over temporal graphs, which are used extensively to model time-varying networks, such as communication networks, social networks, and transportation schedule networks. Moreover, we are faced with increasingly large real-world temporal networks that may be distributed across multiple data centers. This state of affairs motivates the paper's study of efficient reachability queries on distributed temporal graphs. We propose an efficient index, called Temporal Vertex Labeling (TVL), which is a labeling scheme for distributed …

Optimization Of Q-Btgsid Based On Sensitivity Analysis, Shuwei Jia

Journal of System Simulation

Abstract: In order to make up for the defect that relative degree of incidence, absolute degree of incidence and synthetic degree of incidence are limited in the range of (0.5, 1], this paper attempts to improve the degree of grey incidence. A control factor of “λ” and the metric space are set up to adjust. A new model is established and its specific properties are studied. It is proved that the new model satisfies the grey incidence axioms and the range of degree of grey incidence can be extended to (0, 1]. We put forward four principles of …

The Moving Object Reflected Under Matlab Test-Bench (Simulation Model Through Buit-In Functions), Virtyt Lesha, Jozef Bushati, Dea Strica

UBT International Conference

Digital image processing is an area that finds many applications in three-dimensional graphics. One of the subjects considered in image processing is detection of moving objects. In this paper, we have analyzed the performance of an algorithm that detects a moving object. The performance relates to the speed of moving object during a pre-determined time interval. The methodology supports Matlab integrated with built-in functions. Specifically, as input of the simulation model is a video material containing moving objects. The model reads a video file presenting moving objects; after the model is executed in Matlab, the output emits moving objects associated …

Efficiency Of Calculating Gcd Through Computer With Help Of Modified Euclidean Algorithm, Emin Emini, Azir Jusufi, Ruhada Emini

UBT International Conference

Euclid’s algorithm remains to be the most efficient method for finding greatest common divisor of two full numbers. By using the meaning of congruences this research paper will make a modification in the note of the Euclid’s algorithm. Here are discussed both classic and modified methods, by putting appropriate codes and observe the duration of the calculation through the computer.

Multiple Attributes Decision Fusion For Wireless Sensor Networks Based On Intuitionistic Fuzzy Set, Zhenjiang Zhang, Ziqi Hao, Sherali Zeadally, Jing Zhang, Bowen Han, Han-Chieh Chao

Information Science Faculty Publications

Decision fusion is an important issue in wireless sensor networks (WSN), and intuitionistic fuzzy set (IFS) is a novel method for dealing with uncertain data. We propose a multi-attribute decision fusion model based on IFS, which includes two aspects: data distribution-based IFS construction algorithm (DDBIFCA) and the category similarity weight-based TOPSIS intuitionistic fuzzy decision algorithm (CSWBT-IFS). The DDBIFCA is an IFS construction algorithm that transforms the original attribute values into intuitionistic fuzzy measures, and the CSWBT-IFS is an intuitionistic fuzzy aggregation algorithm improved by the traditional TOPSIS algorithm, which combines intuitionistic fuzzy values of different attributes and obtains a final …

Maximum Size Of The Pareto Cost Sets For Multi-Constrained Optimal Routing, Derya Yiltaş Kaplan

Turkish Journal of Electrical Engineering and Computer Sciences

Routing under multiple independent constrains in point-to-point networks has been studied for over 10 years. Its NP-hardness keeps pushing researchers to study approximate algorithms and heuristics, and many results have been published in these years. To the best of our knowledge, the nature of its average case has been explored only for the self-adaptive multiple constraints routing algorithm (SAMCRA), which is an algorithm about multiple constraints routing. In this paper, we simplify SAMCRA into a format that is convenient for our average case analysis. This variant algorithm gives optimal solutions also for very large dimensional networks such as with more …

High Performance Text Document Clustering, Yanjun Li

Browse all Theses and Dissertations

Data mining, also known as knowledge discovery in database (KDD), is the process to discover interesting unknown knowledge from a large amount of data. Text mining is to apply data mining techniques to extract interesting and nontrivial information and knowledge from unstructured text. Text clustering is one of important techniques of text mining, which is the unsupervised classification of similar documents into different groups.

This research focuses on improving the performance of text clustering. We investigated the text clustering algorithms in four aspects: document representation, documents closeness measurement, high dimension reduction and parallelization. We propose a group of high performance …