Engineering Commons^™

Clustering Algorithm Of Quantum Self-Organization Network Based On Bloch Spherical Rotation, Shuyun Yang, Panchi Li

Journal of System Simulation

Abstract: To enhance the clustering ability of self-origanization network, a quantum-inspired self-organization clustering algorithm was proposed based on Bloch spherical rotation. The clustering samples were mapped to the qubits on the Bloch sphere by taking all the sample values as the phases of the qubits, and the all weight values in the competitive layer were mapped to the qubits randomly distributed on the Bloch sphere. Then, the winning node was obtained by computing the spherical distance between sample and weight value, and the weight values of the winning nodes and its neighborhood were updated by rotating them to the sample …

Decision Strategy Models Of Merge Influence Area For Outside Vehicles Based On Vehicle-Vehicle Communication, Xiaofang Yang, Guo Qian, Fu Qiang

Journal of System Simulation

Abstract: In the on-ramp merging area, appropriate driving decisions should be made by observing the running environment and estimating the driving characteristics of the surrounding vehicles, which usually led to the inordinate traffic flow. To solve this problem, the decision strategy models were built for vehicles in the on-ramp merging area, and the operating rules for the new decision strategy were updated. Furthermore, the space-time trajectory, the lane changing in merging and upstream area and the average speed in the two different circumstances were analyzed by numerical experiments. The results show that in the condition of vehicle-vehicle communication environment, …

Study On Simulation Of Turning Burr Formation Based On Finite Element Method, Yunming Zhu, Jingui Huang, Guicheng Wang, Chen Yun

Journal of System Simulation

Abstract: According to the relative motion of tool and workpiece, a new mechanical-thermal coupling finite element model of turning burr formation was established. It adopted supporting plate method to eliminate the influence of workpiece deformation which remained on the workpiece side. Operational efficiency improved greatly under this model. Based on the analysis of simulation results, it is discovered that there are both bending deflection and partly cutting occurred on cutting layer material. AISI1045 steel turning experiment was conducted, it is found that the results of simulation are close to the experimental. The model provides an effective way for analyzing the …

Research Of Marshalling Yard Dispersion Based On Simulation In Container Terminal, Yu Hang, Le Meilong

Journal of System Simulation

Abstract: As development of the precision management in the container terminal, close attention was paid to the research on the optimization of the marshalling yard template. The new concept called the yard dispersion in the container yard template was proposed and the professional simulation software Flexsim-CT was used to build a container handling simulation model which includes berth, quay crane, yard scheduling, yard crane, and trucks. The impact of the different yard dispersion on the total handling time and the efficiency of the quay crane under varying service burden was analyzed. The case study combines the simulation model with …

Optimization Design For A New Type Throttle Valve Of Managed Pressure Drilling Based On Response Surface Methodology, Guorong Wang, Chu Fei, Hongkang Fan, Siyu Tao, Zhu Hao, Jiang Long

Journal of System Simulation

Abstract: The Kriging response surface of single parameter and double parameters versus mass loss of valve spool about bonnet length, bonnet external radius and chamber inner radius of a new type throttle valve used in Managed Pressure Drilling was carried out by using CFX and ANSYS-Design Exploration. The results show that these dimensions have significant influence on erosion mass loss of valve spool. In order to improve the anti-erosion ability of the spool and enhance the service life of the whole valve, the multi-objective genetic algorithm was used for dimensional optimization design of the mentioned variables. After optimization …

Behavior Recognition Combining Regional Optical Flow Features And Temporal Templates, Manyi Wang, Yaling Song, Li Yu, Zhang Liang

Journal of System Simulation

Abstract: A method was proposed to recognize human behavior, which combined the wavelet moments of temporal templates and the speed feature by optical flow. The wavelet moments are not only rotation, translation and scale invariance, but also have the multi-scale characteristics of wavelet. The shape feature of the motion history image and motion energy image can be described. To simple motions, it's effectively, but it can't present the speed information. Regional optical flow was calculated to describe the direction and amplitude features of motion by Lucas-Kanade algorithm. It could make up shortcomings of wavelet moment without speed information. Being …

Querying Recurrent Convoys Over Trajectory Data, Munkh-Erdene Yadamjav, Zhifeng Bao, Baihua Zheng, Farhana M. Choudhury, Hanan Samet

Research Collection School Of Computing and Information Systems

Moving objects equipped with location-positioning devices continuously generate a large amount of spatio-temporal trajectory data. An interesting finding over a trajectory stream is a group of objects that are travelling together for a certain period of time. Existing studies on mining co-moving objects do not consider an important correlation between co-moving objects, which is the reoccurrence of the movement pattern. In this study, we define a problem of finding recurrent pattern of co-moving objects from streaming trajectories and propose an efficient solution that enables us to discover recent co-moving object patterns repeated within a given time period. Experimental results on …

The Entanglement Of Influential Technology Channels In Practice And Design, Ciarán O'Leary

Doctoral

Design for academic practice is an important phenomenon in Higher Education. This is the practice through which informal, non-professional designers operating in a variety of roles in academic institutions carry out the design of systems, resources, activities and processes that are intended to enhance academic practice. Despite its importance, the area has not received sufficient attention in studies of academic practice, quality enhancement and digital transformation. This thesis argues that the absence of insight into how designers for academic practice engage with digital technology in their design practice contributes to the mismatch between the ambitions for digital transformation in higher …

Detection Of Software Vulnerability Communication In Expert Social Media Channels: A Data-Driven Approach, Andrei Lima Queiroz

Doctoral

Conceptually, a vulnerability is: "A flaw or weakness in a system’s design, implementation,or operation and management that could be exploited to violate the system’s security policy".Some of these flaws can go undetected and exploited for long periods of time after soft-ware release. Although some software providers are making efforts to avoid this situ-ation, inevitability, users are still exposed to vulnerabilities that allow criminal hackersto take advantage. These vulnerabilities are constantly discussed in specialised forumson social media. Therefore, from a cyber security standpoint, the information found inthese places can be used for countermeasures actions against malicious exploitation ofsoftware. However, manual inspection …

Hybrid Deep Neural Networks For Mining Heterogeneous Data, Xiurui Hou

Dissertations

In the era of big data, the rapidly growing flood of data represents an immense opportunity. New computational methods are desired to fully leverage the potential that exists within massive structured and unstructured data. However, decision-makers are often confronted with multiple diverse heterogeneous data sources. The heterogeneity includes different data types, different granularities, and different dimensions, posing a fundamental challenge in many applications. This dissertation focuses on designing hybrid deep neural networks for modeling various kinds of data heterogeneity.

The first part of this dissertation concerns modeling diverse data types, the first kind of data heterogeneity. Specifically, image data and …

Live Media Production: Multicast Optimization And Visibility For Clos Fabric In Media Data Centers, Ammar Latif

Dissertations

Media production data centers are undergoing a major architectural shift to introduce digitization concepts to media creation and media processing workflows. Content companies such as NBC Universal, CBS/Viacom and Disney are modernizing their workflows to take advantage of the flexibility of IP and virtualization.

In these new environments, multicast is utilized to provide point-to-multi-point communications. In order to build point-to-multi-point trees, Multicast has an established set of control protocols such as IGMP and PIM. The existing multicast protocols do not optimize multicast tree formation for maximizing network throughput which lead to decreased fabric utilization and decreased total number of admitted …

Energy And Performance-Optimized Scheduling Of Tasks In Distributed Cloud And Edge Computing Systems, Haitao Yuan

Dissertations

Infrastructure resources in distributed cloud data centers (CDCs) are shared by heterogeneous applications in a high-performance and cost-effective way. Edge computing has emerged as a new paradigm to provide access to computing capacities in end devices. Yet it suffers from such problems as load imbalance, long scheduling time, and limited power of its edge nodes. Therefore, intelligent task scheduling in CDCs and edge nodes is critically important to construct energy-efficient cloud and edge computing systems. Current approaches cannot smartly minimize the total cost of CDCs, maximize their profit and improve quality of service (QoS) of tasks because of aperiodic arrival …

Changing The Focus: Worker-Centric Optimization In Human-In-The-Loop Computations, Mohammadreza Esfandiari

Dissertations

A myriad of emerging applications from simple to complex ones involve human cognizance in the computation loop. Using the wisdom of human workers, researchers have solved a variety of problems, termed as “micro-tasks” such as, captcha recognition, sentiment analysis, image categorization, query processing, as well as “complex tasks” that are often collaborative, such as, classifying craters on planetary surfaces, discovering new galaxies (Galaxyzoo), performing text translation. The current view of “humans-in-the-loop” tends to see humans as machines, robots, or low-level agents used or exploited in the service of broader computation goals. This dissertation is developed to shift the focus back …

Towards Practical Homomorphic Encryption And Efficient Implementation, Gyana R. Sahu

Dissertations

Cloud computing has gained significant traction over the past few years and its application continues to soar as evident from its rapid adoption in various industries. One of the major challenges involved in cloud computing services is the security of sensitive information as cloud servers have been often found to be vulnerable to snooping by malicious adversaries. Such data privacy concerns can be addressed to a greater extent by enforcing cryptographic measures. Fully homomorphic encryption (FHE), a special form of public key encryption has emerged as a primary tool in deploying such cryptographic security assurances without sacrificing many of the …

Analyzing And Assisting Patient Decision-Making In Online Health Communities, Mingda Li

Dissertations

In recent years, many users have joined online health communities (OHC) to seek information, suggestions and social support. However, little has been studied about the roles of OHCs in patients' decision-making processes. The aim of this research is to analyze OHC data to better understand patient decision-making processes, and to provide assistance to OHC users in their decision-making.

In order to analyze or assist patients in their decision-making, a novel classification model is designed to identify discussion threads in OHC that are related to decision making. This is achieved by building a two-step combined deep learning model. Empirical evaluation shows …

Cyber Social Threats 2020 Workshop Meta-Report: Covid-19, Challenges, Methodological And Ethical Considerations, Ugur Kursuncu, Yelena Mejova, Jeremy Blackburn, Amit Sheth

Publications

Online platforms have been increasingly misused by ill-intentioned actors, affecting our society, often leading to real-world events of social significance. On the other hand, recog-nizing the narratives related to harmful behaviors is challeng-ing due to its complex and sensitive nature. The Cyber SocialThreats Workshop 2020 aimed to stimulate research for thechallenges on methodological and ethical considerations indeveloping novel approaches to analyze online harmful con-versations, concerning social, cultural, emotional, commu-nicative, and linguistic aspects. It provided a forum to bringtogether researchers and practitioners from both academiaand industry in the areas of computational social sciences, so-cial network analysis and mining, natural language process-ing, …

Toward A Network Controlled Delivery Of Energy, Zhengqi Jiang

Dissertations

The next-generation power grid aims to integrate the recent technological advancements in the information and communications technology into energy distribution and management. Prior research works propose the concept of the digital grid (DG) as means to fulfill the requirements of the next-generation power grid. While there are several approaches to the DG, they all share the use of internet protocol (IP) addresses to identify lines and grid devices but lack of a full integration of core concepts of digital communications into the management on the delivery of energy.

This dissertation discusses the incorporation of the concept of controllable delivery of …

Numerical Study Of Paraffin Wax Melting In A Cavity With A Gradient Of Hot Wall Inclination, Agus Dwi Korawan

Makara Journal of Technology

The melting of a phase change material (PCM) in a cavity with a gradient of hot wall inclination was simulated numerically using five models, namely, Model-A, Model-B, Model-C, Model-D, and Model-E with gradients of −2, −4, ∞, 4, and 2, respectively. The PCM was paraffin wax, which was melted using an enthalpy porosity technique with a pressure-based method. Model-A was found to be the best model. For the completion of the melting process, the models were assigned with the liquid fraction of 1. Model-A required the shortest time, followed by Model-B, Model-C, Model-E, and Model-D, respectively. Compared with Model-C, Model-A …

Synchrony: Music Of Sarah Weaver And Collaborations (2006–2019), Sarah Weaver

Journal of Network Music and Arts

Synchrony is a prominent lens in works by composer Sarah Weaver and collaborations from the years 2006 to 2019 for solo, chamber, large ensemble, and network music pieces. “Synchrony,” defined as perceptual alignment of distributed time and space components, has a practical motivation for transcending both latency and technology mediation in the network music medium. Synchrony also functions as a deep realm of artistic expression for both network and localized music. This essay outlines the technological context of performances, artistic strategies for synchrony, examples from the pieces, and new directions for the work going forward.

Low-Latency Networked Music Collaborations: Does “Good Enough” Do Enough Good?, Gareth Dylan Smith, Zack Moir, Paul Ferguson, Gill Davies

Journal of Network Music and Arts

LoLa is a cutting-edge technology that enables low latency, real-time collaborations across vast distances using high-bandwidth, low-jitter networks. It has the capacity to transform how music is made and experienced. It has been utilized on a relatively small scale to date, primarily for teaching and performances associated with music colleges and concert halls. In this article we discuss various ways in which LoLa technology is “good enough” by describing examples of recent networked music performances “anchored” at Edinburgh Napier University, Scotland. We discuss the ways in which processes and outcomes were “good enough” for the sound engineer, participating musicians, and …

A Quantum-Classical Network For Beat-Making Performance, Scott Oshiro, Omar Costa Hamido

Journal of Network Music and Arts

In recent years, quantum computing has emerged as the next frontier in computational and information technologies. Even though it has found potential applications in solving complex problems in fields such as chemistry, machine learning, and cryptography, among other fields, there has been little research conducted on its applications for music and acoustic technologies. This paper will discuss the use of a quantum internet protocol in the context of networked music performance in which quantum computing could play a role in processing musical data via a cloud-based music software application. We also propose an example model for a beat-making performance network …

Purpose And Well-Being Through Administering Network Performances, Andrew Mcmillan, Fabio Morreale

Journal of Network Music and Arts

Due to the COVID-19 crisis, music communities who found themselves in social and physical isolation have been trying to find alternative solutions to keep some form of connection. Network performance is one of these solutions, one that is specifically aimed at enhancing communities’ connectivity beyond one’s intimate surroundings. In order for network performances to properly work, there are numerous roles that need to be filled; these include performers, administrators, technicians, and event organizers. This paper presents new discussions aimed at understanding these evolving roles and the way in which they are intertwined. These discussions are based on the autobiographical reflections …

Networked Music Performance In Virtual Reality: Current Perspectives, Ben Loveridge

Journal of Network Music and Arts

The ability for musicians to interact face-to-face has been highly impacted by the COVID-19 pandemic. Physical distancing and travel restrictions have forced teaching, rehearsals, and performances to be moved online. The use of videoconference platforms designed for conversation has also meant accepting their limitations when used in musical contexts. For example, in networked music performance (NMP), low-latency audio is usually transmitted alongside a separate video image. Since videoconference systems usually have a higher degree of in-built delay, the result is that performers often ignore the video image of each other in order to maintain a steady rhythm. If musicians usually …

Editorial, Sarah Weaver

Journal of Network Music and Arts

No abstract provided.

A Study Of Static And Dynamic Characteristics Of Multifunctional Signal Converters, Akmal Abdumalikov

Chemical Technology, Control and Management

The issues of continuity, accuracy, speed and reliability of signal conversion, which are the main problems of quality control and management of production processes, remain relevant. Research shows that in practice there are different signal variables, the study of which is highly formalized in a number of modeling tasks and basic classification studies, in particular transients in converters, its sources and elements requires a unified mathematical approach, that is, visual, highly formalized modeling and research based on it. The paper presents a graph model of multifunctional signal converters that provide microprocessor and electronic devices with signals in the form of …

Navigating In Numerous Video Data: User Interface Design For An On-Camera Video Analytics Engine, Sabriya Maryam Alam

The Journal of Purdue Undergraduate Research

Video analytics powered by artificial intelligence shows high promise in making our society smarter. Harnessing large amounts of video data, however, requires the development of processing systems demonstrating high performance and high efficiency. To this end, this work has contributed to a video analytics system powered by artificial intelligence for object detection and recognition. Rather than streaming all the video frames to the cloud, the system analyzes images on-camera and only returns those of interest to the cloud. This edge analytics research-grade software is available, but it lacks a simple web interface for general use by scientists, engineers, and other …

A Fortran-Keras Deep Learning Bridge For Scientific Computing, Jordan Ott, Mike Pritchard, Natalie Best, Erik Linstead, Milan Curcic, Pierre Baldi

Engineering Faculty Articles and Research

Implementing artificial neural networks is commonly achieved via high-level programming languages such as Python and easy-to-use deep learning libraries such as Keras. These software libraries come preloaded with a variety of network architectures, provide autodifferentiation, and support GPUs for fast and efficient computation. As a result, a deep learning practitioner will favor training a neural network model in Python, where these tools are readily available. However, many large-scale scientific computation projects are written in Fortran, making it difficult to integrate with modern deep learning methods. To alleviate this problem, we introduce a software library, the Fortran-Keras Bridge (FKB). This two-way …

Zero-Bias Deep Learning For Accurate Identification Of Internet Of Things (Iot) Devices, Yongxin Liu, Houbing Song, Thomas Yang, Jian Wang, Jianqiang Li, Shuteng Niu, Zhong Ming

Publications

The Internet of Things (IoT) provides applications and services that would otherwise not be possible. However, the open nature of IoT makes it vulnerable to cybersecurity threats. Especially, identity spoofing attacks, where an adversary passively listens to the existing radio communications and then mimic the identity of legitimate devices to conduct malicious activities. Existing solutions employ cryptographic signatures to verify the trustworthiness of received information. In prevalent IoT, secret keys for cryptography can potentially be disclosed and disable the verification mechanism. Noncryptographic device verification is needed to ensure trustworthy IoT. In this article, we propose an enhanced deep learning framework …

Paralleling Simulation Of Operation Plan Based On Decision Point Controlling, Zhanguang Cao, Pinggang Yu, Kuo Wang

Journal of System Simulation

Abstract: Operation plan simulation traditionally uses serial and static method. It can't be fulfilled for the military need of swift simulation and real-time decision in the modern complicated and dynamically battle field. So, the higher complexity and dynamical decision according to situation of the operation plan bring new challenge to the simulation. Operation Plan Paralleling Simulation Based on Decision Point Controlling (P2SDPC) can realize the operation plan's dynamic adjusting and cutting impossible branch based on decision point controlling technology. From then on, the efficiency of operation plan's simulation could be improved by the way of paralleling simulation. Thus the problem …

Model And Simulation Of Virtual Character Based On Real-Time Sensor Data-Driven, Lufeng Luo, Xiangjun Zou, Zhang Cong, Xie Lei

Journal of System Simulation

Abstract: The real-time control of virtual character behavior is a challenge in simulating virtual exercise. A kind of virtual character running behavior control method based on real-time data-driven was proposed, the real-time data acquisition with the help of sensor was expounded, the time-series law of human body running was analyzed, the human body posture mathematics expression was modeled, and a limb movement parts and rotation degrees of freedom computing model was proposed. By use of rotation angle method, the space and time relationship of each part of human movement chains was established and the movement process frame when moving was …