Computer Sciences Commons^™

Human-Computer Interaction Speech Emotion Recognition Based On Random Forest And Convolution Feature Learning, Wang Jing, Hongyan Liu, Fangfang Liu, Qingqing Wang

Journal of System Simulation

Abstract: Focus on the different speech features of different types of people in the automatic speech emotion recognition of emotional robots,a random forest for speech emotion recognition is proposed,and a preliminary simulation experiment of emotional social robot system based on convolution feature learning is carried out.The results show that the emotional robot can track in real time,the seven basic emotions of excitement,anger,sadness,happiness,surprise,fear and neutrality.By using non personalized speech emotion features,the original personalized speech emotion features are supplemented,and the general emotion and special emotion are extracted.For emotional robot,using these indicators has a certain application prospect in the simulation experiment …

Research On Fuzzy Control And Optimization For Traffic Lights At Single Intersection, Jiajia Liu, Xingquan Zuo

Journal of System Simulation

Abstract: Aiming at the traffic signal control at urban single intersection,a fuzzy control method for traffic lights is presented.The method is based on a four-phase phasing sequence to control the traffic lights at a single intersection.Inputs of the fuzzy controller are the number of vehicles in line and the arrival rate of vehicles,and the output is the green light extension time of the current green light phase.A genetic algorithm (GA) is used to optimize fuzzy rules and membership functions of the fuzzy control system to improve the performance of the fuzzy controller.The fuzzy control method is realized by using …

One Turbulent Modeling Method Based On Environmental Forecast Data, Dawei Fan, Jiahui Tong

Journal of System Simulation

Abstract: Based on the existing natural environment model of aircraft simulation test,the method of conversion and processing for environmental prediction data is studied.Based on the random wave theory,the mathematical model of turbulent wind is established,and the simulation modeling method is studied.Based on Davenport spectrum,a turbulent wind model based on environmental prediction data is established and is introduced into the mathematical simulation experiment of a type of aircraft to obtain the influence of wind turbulent on the flight state of the aircraft.The experimental results show that the gust turbulence has a greater impact on the aircraft's angle of …

Collaborative Optimization Of Production And Energy Consumption In Flexible Workshop, Ding Yu, Wang Yan, Zhicheng Ji

Journal of System Simulation

Abstract: Considering the problem of the multi-objective constrained flexible job-shop,the NSGA-Ⅱalgorithm based on hybrid mutation operator is proposed.In view of NSGA-II algorithm being prone to premature convergence,poisson average and gaussian operators are introduced to improve the global and local optimization ability of the algorithm.The optimal scheme is selected from the set of pareto solutions by adopting the strategy of FAHP-IEVM,which is the combination of subjective and objective evaluation method. The modified algorithm is tested and compared by a series of ZDT test functions.The results show that the convergence and diversity of the revised algorithm are improved obviously.The effectiveness of …

Stereo Camera Calibration Based On Multiple Fitness Full-Parameter Autonomous Mutation Particle Swarm, Guiyang Zhang, Muyao Xue, Zijian Zhu, Huo Ju

Journal of System Simulation

Abstract: The acquisition of target parameters based on visual measurement provides reliable data support for performance analysis and evaluation of simulation system.The precision of measurement results is determined by the accuracy of camera calibration.A calibration method based on full parameter autonomous mutation particle swarm optimization is proposed.Traditional calibration method is utilized to obtain the initial internal parameters.The fast and global calibration algorithm based on particle swarm optimization is achieved by inertial coefficient contraction adjustment,global factor learning adjustment strategy based on particle distance,multi-adaptation function and the independent variation law.The experimental results show that the proposed method can improve the …

A Simulation Credibility Assessment Method Based On Improved Fuzzy Comprehensive Evaluation, Peizhi Ran, Li Wei, Bao Ran, Ma Ping

Journal of System Simulation

Abstract: Aiming at the problems of inaccurate evaluation results caused by experts in the process of simulation credibility evaluation based on traditional fuzzy comprehensive evaluation according to personal preferences or expectations,and unreasonable selection of fuzzy synthetic calculations,a simulation credibility evaluation method based on improved fuzzy comprehensive evaluation is proposed.For the tree-like assessment index system,the fuzzy comprehensive evaluation matrix is used to determine the weight of each index in the assessment index system based on the minimum membership weighted average deviation;in the fuzzy synthesis operation,the membership evaluation weighted average deviation is used to obtain the comprehensive evaluation vector,and then the …

Reliability Evaluation Method For Reuse Model Of Complex Simulation System, Ziheng Ye, Fuzhen Zhang, Yaoqin Zhu, Weiqing Li

Journal of System Simulation

Abstract: Model reuse can enhance the flexibility and scalability of simulation applications,and is necessary in the construction of complex simulation systems.Assessing credibility in multi-model combination simulation is the basic question of whether the model can be effectively reused.Aiming at the two simulation model reuse,in different application environments of physical model-oriented and numerical settlement-oriented,the credibility evaluation method for simulation reuse models based on bias propagation is proposed,and the respective modeling methods and evaluation methods are introduced in detail. Taking UAV as an example,the comparison result with the classic credibility evaluation method shows that the method can reduce the difficulty of …

Establishment And Development Of Simulation-Based Aero Engine Acquisition On, Caiyun Liang, Hongxin Li, Yanfeng Sui, Luan Xu, Shi Feng

Journal of System Simulation

Abstract: Follow the increasing demand of aircraft for aero engine‘s capabilities and because of the increase of engine‘s own technical difficulty,the risks,cycles and costs of the engine development is rising,and the high demand of traditional acquisition model is urgently needed.The idea of digitalized aero engine acquisition is presented,which starts from joint analysis,applies multi-dimensional scaling technology,carries out integrated simulation based on the models of each dimension of virtual prototype,and realizes the evaluation of technical scheme.The mapping relationship among technical solutions,schedules and costs etc.are established,and a basic framework for simulation based acquisition of engines is constructed by using the work …

Automatic Discovery Method Of Dynamic Job Shop Dispatching Rules Based On Hyper-Heuristic Genetic Programming, Suyu Zhang, Wang Yan, Zhicheng Ji

Journal of System Simulation

Abstract: The dynamic job shop has the uncertainty of resource state and the randomness of tasks,so it is difficult to find the common dispatching rules applicable to a variety of complex production scenarios.A method for automatic discovery of dynamic shop dispatching rules based on Hyper-Heuristic genetic programming is proposed,with makespan and average weighted tardiness as the optimization goals,is improved by using the automatic discovery of machine sequencing rules and the dynamic adaptability of workshop scheduling under different production scenarios.Through the semantic analysis of dispatching rules,the function of terminators on different optimization objectives is analyzed.The experiment result shows that …

Hardness Of Reconfiguring Robot Swarms With Uniform External Control In Limited Directions, David Caballero, Angel A. Cantu, Timothy Gomez, Austin Luchsinger, Robert Schweller, Tim Wylie

Computer Science Faculty Publications

Motivated by advances is nanoscale applications and simplistic robot agents, we look at problems based on using a global signal to move all agents when given a limited number of directional signals and immovable geometry. We study a model where unit square particles move within a 2D grid based on uniform external forces. Movement is based on a sequence of uniform commands which cause all particles to move 1 step in a specific direction. The 2D grid board additionally contains \blocked" spaces which prevent particles from entry. Within this model, we investigate the complexity of deciding 1) whether a target …

Extending Import Detection Algorithms For Concept Import From Two To Three Biomedical Terminologies, Vipina K. Keloth, James Geller, Yan Chen, Julia Xu

Publications and Research

Background: While enrichment of terminologies can be achieved in different ways, filling gaps in the IS-A hierarchy backbone of a terminology appears especially promising. To avoid difficult manual inspection, we started a research program in 2014, investigating terminology densities, where the comparison of terminologies leads to the algorithmic discovery of potentially missing concepts in a target terminology. While candidate concepts have to be approved for import by an expert, the human effort is greatly reduced by algorithmic generation of candidates. In previous studies, a single source terminology was used with one target terminology.

Methods: In this paper, we are extending …

Twitter Fake Account Detection And Classification Using Ontological Engineering And Semantic Web Rule Language, Mohammed Jabardi, Asaad Sabah Hadi

Karbala International Journal of Modern Science

Nowadays, Twitter has become one of the fastest-growing Online Social Networks (OSNs) for data sharing frameworks and microblogging. It attracts millions of users worldwide where subscribers communicate with each through posts and messages known as "tweets". The open structure and behaviour of Twitter cause it to be vulnerable to attacks from fake accounts and a large number of automated software, known as 'bots'. Bots are regarded to be malicious as they send spam to users of social networks over the internet. Data security and privacy are among the most critical issues of social network users, as the protection and fulfilment …

Editorial Board

Karbala International Journal of Modern Science

No abstract provided.

Fractal And Edge-Based Techniques For Kidney Enhancement And Segmentation On Magnetic Resonance Images (Mri), Alaá Rateb Mahmoud Al-Shamasneh

Student Works (2020-2029)

Recently, many rapid developments in digital medical imaging have made further contributions to healthcare systems. However, the segmentation of regions of interest in medical images plays a vital role in assisting doctors in their medical diagnoses and for the early detection of disease. Since health issues related to the kidneys are increasing exponentially, this thesis focused on developing methods for the segmentation of MRI images of the kidney. Kidney images frequently suffer from low contrast, low resolution and noise, and are blur. Hence, it is necessary to enhance the images in order to improve the segmentation. Therefore, the current thesis …

Sybil Defense Using Efficient Resource Burning, Diksha Gupta

Computer Science ETDs

In 1993, Dwork and Naor proposed using computational puzzles, a resource burning mechanism, to combat spam email. In the ensuing three decades, resource burning has broadened to include communication capacity, computer memory, and human effort. It has become a well-established tool in distributed security. Due to the cost attached to utilizing resource burning mechanism, these have not been popularized in domains apart from cryptocurrency.

In this dissertation, we design efficient resource burning based Sybil defense techniques for permissionless systems. As a first step, we identify existing resource burning mechanisms in literature in Chapter 2. Additionally, we enumerate numerous open problems …

A Logical Method For Finding Maximum Compatible Subsystems Of Systems Of Boolean Equations, Anvar Kabulov, Erkin Urunbaev, Mansur Berdimurodov

Scientific Journal of Samarkand University

The problem of finding the maximum joint subsystem of Boolean equation systems is solved. An algorithm for finding the maximum upper zero of a monotone Boolean function is proposed. An efficient procedure for calculating the values of monotone functions on sets of a - dimensional cube is investigated and developed. An algorithm for solving systems of Boolean equations based on the search for the maximum upper zero of monotone functions of the logic algebra is developed.

Finding All ∈-Good Arms In Stochastic Bandits, Blake Mason, Lalit Jain, Ardhendu S. Tripathy, Robert Nowak

Computer Science Faculty Research & Creative Works

The pure-exploration problem in stochastic multi-armed bandits aims to find one or more arms with the largest (or near largest) means. Examples include finding an ∈-good arm, best-arm identification, top-k arm identification, and finding all arms with means above a specified threshold. However, the problem of finding all ∈-good arms has been overlooked in past work, although arguably this may be the most natural objective in many applications. For example, a virologist may conduct preliminary laboratory experiments on a large candidate set of treatments and move all ∈-good treatments into more expensive clinical trials. Since the ultimate clinical efficacy is …

Using Eye-Gaze To Evaluate Neural Attention, Shahansha Salim

Master’s Dissertations

The ability to selectively concentrate on areas of interest while ignoring the rest is termed as attention in human beings. This ability has played a key role in survival as well as information processing. Neural Attention is said to be an effort to bring similar action of selectively concentrating areas of relevance in deep neural networks. This simple yet powerful concept has attracted a lot of research in recent years, yielding breakthrough results in Natural Language Processing (NLP) problems and main stream Computer Vision problems such as Image Caption Generation, Neural Machine Translation (NMT), Visual Question Answering (VQA), Action Recognition, …

Thaw Publications, Carl Landwehr, David Kotz

Computer Science Technical Reports

In 2013, the National Science Foundation's Secure and Trustworthy Cyberspace program awarded a Frontier grant to a consortium of four institutions, led by Dartmouth College, to enable trustworthy cybersystems for health and wellness. As of this writing, the Trustworthy Health and Wellness (THaW) project's bibliography includes more than 130 significant publications produced with support from the THaW grant; these publications document the progress made on many fronts by the THaW research team. The collection includes dissertations, theses, journal papers, conference papers, workshop contributions and more. The bibliography is organized as a Zotero library, which provides ready access to citation materials …

Applying Web Technologies For Data Mining Of Models Of Advancement Over Time In Space Exploration Technology, Peng-Hung Tsai

Theses and Dissertations

The development of web technologies has progressed rapidly in the past few decades. As a result, these technologies have increasingly gained popularity among researchers as an instrument for data analysis and visualization to aid their work. The purpose of this project is to pursue a new method for mining time-based data to perform curve fitting, using web client technology. This requires comparing the advantages and disadvantages of different JavaScript software designs to determine which is best. Based on the results, we emphasize developing a client-side web application and demonstrate its use through fitting a curve for a new metric to …

How Live Streaming And Twitch Have Changed The Gaming Industry, Krystal Ruiz

ART 108: Introduction to Games Studies

Live streaming in itself has become a booming industry in which its content consists of “streamers” who live broadcast numerous events and real-time interactions while simultaneously chatting with viewers drawing huge and increasing numbers (Adamovich). Twitch has especially excelled at garnering attention as one of the most popular live streaming platforms that focuses on broadcasting and viewing video game content (Adamovich). Twitch has grown rapidly within the last few years asserting its dominance as one of the major forces in the games industry and becoming a multi-billion-dollar industry (Adamovich). For example, according to Descrier, in 2016 there were approximately 292 …

Distributed De Novo Assembler For Large-Scale Long-Read Datasets, Sayan Goswami, Kisung Lee, Seung Jong Park

Computer Science Faculty Research & Creative Works

Third-generation DNA sequencing technologies such as single-molecule real-time sequencing (SMRT) and nanopore sequencing have the potential to fill the gaps in the existing genome databases since the raw sequences produced by these machines are much longer than those of previous generations and therefore result in more contiguous assemblies. However, these long reads have a high error rate, which makes the assembly process computationally challenging. Moreover, since existing long-read assemblers are designed to run on a single machine, they either take days to complete or run out of memory on even moderate-sized datasets. In this paper, we present a distributed long-read …

Lsomp: Large Scale Ordinance Mining Portal, Xu Du, Matthew Kowalski, Aparna S. Varde, Boxiang Dong

Department of Computer Science Faculty Scholarship and Creative Works

We propose a novel scalable Web portal called LSOMP (Large Scale Ordinance Mining Portal) to analyze ordinances and their tweets (of the order of thousands and millions). It entails commonsense knowledge (CSK) and natural language processing (NLP), disseminating ordinance-tweet mining results via interactive graphics and Question Answering (QA).

2d-Att: Causal Inference For Mobile Game Organic Installs With 2-Dimensional Attentional Neural Network, Boxiang Dong, Hui Bill Li, Yang Ryan Wang, Rami Safadi

Department of Computer Science Faculty Scholarship and Creative Works

In the mobile gaming industry, organic installs refer to downloads that cannot be attributed to any advertising channel and thus do not introduce upfront user acquisition (UA) cost. Understanding the causal factors on organic installs is of vital importance for a game's ecosystem, as such knowledge can help bring in more organic users, who tend to be more loyal and active. A major challenge in discovering the causal effects is the potential temporal lag between an UA operation and the growth in organic installs. In this paper, we solve the problem by using a deep attentional neural network to analyze …

Item-Based Collaborative Filtering And Association Rules For A Baseline Recommender In E-Commerce, Jessica Lourenco, Aparna S. Varde

Department of Computer Science Faculty Scholarship and Creative Works

In the ever-growing data-driven world today, data increases in many forms, e.g. e-commerce sites uploading new products, streaming services adding TV shows and movies, and music platforms uploading new songs. It would be highly infeasible for end users to quickly browse all this data. Hence recommender systems can benefit end users (individuals as well as companies) in efficiently finding suitable products. Rather than making end users search through a vast array of items, recommender systems can suggest suitable items to users based on popularity of the items and the respective users' buying behavior. Accordingly, in this paper we explore two …

Transfer Learning For Decision Support In Covid-19 Detection From A Few Images In Big Data, Divydharshini Karthikeyan, Aparna S. Varde, Weitian Wang

Department of Computer Science Faculty Scholarship and Creative Works

The novel coronavirus (Covid-19) has spread rapidly amongst countries all around the globe. Compared to the rise in cases, there are few Covid-19 testing kits available. Due to the lack of testing kits for the public, it is useful to implement an automated AI-based E-health decision support system as a potential alternative method for Covid-19 detection. As per medical examinations, the symptoms of Covid-19 could be somewhat analogous to those of pneumonia, though certainly not identical. Considering the enormous number of cases of Covid-19 and pneumonia, and the complexity of the related images stored, the data pertaining to this problem …

On Improving The Memorability Of System-Assigned Recognition-Based Passwords, Mahdi Nasrullah Al-Ameen, Sonali T. Marne, Kanis Fatema, Matthew Wright, Shannon Scielzo

Computer Science Faculty and Staff Publications

User-chosen passwords reflecting common strategies and patterns ease memorization but offer uncertain and often weak security, while system-assigned passwords provide higher security guarantee but suffer from poor memorability. We thus examine the technique to enhance password memorability that incorporates a scientific understanding of long-term memory. In particular, we examine the efficacy of providing users with verbal cues—real-life facts corresponding to system-assigned keywords. We also explore the usability gain of including images related to the keywords along with verbal cues. In our multi-session lab study with 52 participants, textual recognition-based scheme offering verbal cues had a significantly higher login success …

Walking The Walk

In The Loop

DePaul's College of Computing and Digital Media has several programs that engage students in enjoyable and educational endeavors that build their skill sets, confidence, and connections. The School of Cinematic Arts has partnered for several years with the Chicago Housing Authority (CHA) on a program that pays youth residents of CHA housing to participate in documentary filmmaking, screenwriting and design. DeSports involves students at two Chicago Public Schools (CPS) in e-sports to develop collaboration, communication and critical-thinking skills. Middle-school girls in CPS participate STEM-oriented pursuits as part of Digital Youth Divas.

The Impact Of Shigeru Miyamoto On The Game Design Industry, Luan Tran

ART 108: Introduction to Games Studies

Nintendo started as a small company in the 1970s that sold playing cards. Having seen the exemplary gift in his son, Miyamoto's father arranged for an interview with the president of Nintendo Hiroshi Yamauchi. Consequently, Miyamoto got a position in 1977 as an apprentice in the planning department after showing his toy creations to the president. He became the first Nintendo artist as he helped create the art for the first original coin-operated arcade game. The approach demonstrated his innate abilities that would help him become the ultimate guru in the industry. Through individual discovery, Miyamoto has managed to produce …

Metalearning By Exploiting Granular Machine Learning Pipeline Metadata, Brandon J. Schoenfeld

Theses and Dissertations

Automatic machine learning (AutoML) systems have been shown to perform better when they use metamodels trained offline. Existing offline metalearning approaches treat ML models as black boxes. However, modern ML models often compose multiple ML algorithms into ML pipelines. We expand previous metalearning work on estimating the performance and ranking of ML models by exploiting the metadata about which ML algorithms are used in a given pipeline. We propose a dynamically assembled neural network with the potential to model arbitrary DAG structures. We compare our proposed metamodel against reasonable baselines that exploit varying amounts of pipeline metadata, including metamodels used …