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Articles 9721 - 9750 of 11148
Full-Text Articles in Computer Sciences
Investigating Dataset Distinctiveness, Andrew Ulmer, Kent W. Gauen, Yung-Hsiang Lu, Zohar R. Kapach, Daniel P. Merrick
Investigating Dataset Distinctiveness, Andrew Ulmer, Kent W. Gauen, Yung-Hsiang Lu, Zohar R. Kapach, Daniel P. Merrick
The Summer Undergraduate Research Fellowship (SURF) Symposium
Just as a human might struggle to interpret another human’s handwriting, a computer vision program might fail when asked to perform one task in two different domains. To be more specific, visualize a self-driving car as a human driver who had only ever driven on clear, sunny days, during daylight hours. This driver – the self-driving car – would inevitably face a significant challenge when asked to drive when it is violently raining or foggy during the night, putting the safety of its passengers in danger. An extensive understanding of the data we use to teach computer vision models – …
Deep Neural Network Architectures For Modulation Classification Using Principal Component Analysis, Sharan Ramjee, Shengtai Ju, Diyu Yang, Aly El Gamal
Deep Neural Network Architectures For Modulation Classification Using Principal Component Analysis, Sharan Ramjee, Shengtai Ju, Diyu Yang, Aly El Gamal
The Summer Undergraduate Research Fellowship (SURF) Symposium
In this work, we investigate the application of Principal Component Analysis to the task of wireless signal modulation recognition using deep neural network architectures. Sampling signals at the Nyquist rate, which is often very high, requires a large amount of energy and space to collect and store the samples. Moreover, the time taken to train neural networks for the task of modulation classification is large due to the large number of samples. These problems can be drastically reduced using Principal Component Analysis, which is a technique that allows us to reduce the dimensionality or number of features of the samples …
Detecting Saliency By Combining Speech And Object Detection In Indoor Environments, Kiran Thapa
Detecting Saliency By Combining Speech And Object Detection In Indoor Environments, Kiran Thapa
Boise State University Theses and Dissertations
Describing scenes such as rooms, city streets, or routes, is a very common human task that requires the ability to identify and describe the scene sufficiently for a hearer to develop a mental model of the scene. When people talk about such scenes, they mention some objects of the scene at the exclusion of others. We call the mentioned objects salient objects as people consider them noticeable or important in comparison to other non-mentioned objects. In this thesis, we look at saliency of visual scenes and how visual saliency informs what can and should be said about a scene when …
Organizational Change In The Artificial Intelligence Age – The Case Of Marketing And Sales, Yin Yang, Keng Siau
Organizational Change In The Artificial Intelligence Age – The Case Of Marketing And Sales, Yin Yang, Keng Siau
Research Collection School Of Computing and Information Systems
Artificial intelligence (AI), robotics, machine learning, and automation are revolutionizing the field of marketing and sales. Although the field of sales and marketing has been impacted by advanced technologies continuously, the impact of AI on sales and marketing field is expected to be transformational and revolutionary. The main threats pose by AI are job losses and upheaval of the society as a result (Siau, 2018; Siau and Wang, 2018). A report published in February 2016 by Citibank in partnership with the University of Oxford predicted that 47% of US jobs are at risk of automation. In UK, it is 35%. …
Trusting Artificial Intelligence In Healthcare, W. Wang, Keng Siau
Trusting Artificial Intelligence In Healthcare, W. Wang, Keng Siau
Research Collection School Of Computing and Information Systems
Artificial Intelligence (AI) is able to perform at humans and even surpass human’s performances in some tasks. Recent cases about self-driving cars, cashier-free supermarket Amazon Go, and virtual assistants such as Apple’s Siri and Google Assistant have illustrated the current and future potential of AI. AI and its applications have infiltrated human’s work and daily life. It is inevitable that humans need to build a working relationship with AI and its applications. On one hand, humans can benefit from this new technology, for instance, a home robot can release housewife from mundane and monotonous tasks (Siau 2017, Siau 2018). On …
Ethical And Moral Issues With Ai, Weiyu Wang, Keng Siau
Ethical And Moral Issues With Ai, Weiyu Wang, Keng Siau
Research Collection School Of Computing and Information Systems
AI-based technology has achieved many great things, such as facial recognition, medical diagnosis, and self-driving cars. AI promises enormous benefits for economic growth, social development, as well as human well-being and safety improvement. However, the low-level of explainability, data security, data privacy, and ethical problems of AI-based technology also pose significant risks for users, developers, and governments. As the AI advances, one critical issue is how to address the ethical and moral challenges associated with AI. This study will focus on the ethics and morality issues that may be caused by AI, andmay arise because of AI. This research uses …
Online Spatio-Temporal Matching In Stochastic And Dynamic Domains, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Online Spatio-Temporal Matching In Stochastic And Dynamic Domains, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Research Collection School Of Computing and Information Systems
Online spatio-temporal matching of servers/services to customers is a problem that arises at a large scale in many domains associated with shared transportation (e.g., taxis, ride sharing, super shuttles, etc.) and delivery services (e.g., food, equipment, clothing, home fuel, etc.). A key characteristic of these problems is that the matching of servers/services to customers in one stage has a direct impact on the matching in the next stage. For instance, it is efficient for taxis to pick up customers closer to the drop off point of the customer from the first stage of matching. Traditionally, greedy/myopic approaches have been adopted …
Sentence Compression With Reinforcement Learning, Liangguo Wang, Jing Jiang, Lejian Liao
Sentence Compression With Reinforcement Learning, Liangguo Wang, Jing Jiang, Lejian Liao
Research Collection School Of Computing and Information Systems
Deletion-based sentence compression is frequently formulated as a constrained optimization problem and solved by integer linear programming (ILP). However, ILP methods searching the best compression given the space of all possible compressions would be intractable when dealing with overly long sentences and too many constraints. Moreover, the hard constraints of ILP would restrict the available solutions. This problem could be even more severe considering parsing errors. As an alternative solution, we formulate this task in a reinforcement learning framework, where hard constraints are used as rewards in a soft manner. The experiment results show that our method achieves competitive performance …
Use Of Artificial Intelligence, Machine Learning, And Autonomous Technologies In The Mining Industry, Z. Hyder, Keng Siau, Fiona Fui-Hoon Nah
Use Of Artificial Intelligence, Machine Learning, And Autonomous Technologies In The Mining Industry, Z. Hyder, Keng Siau, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
Mining is an important industrial and economic sector that plays a major role in the economic development of a country and provides many employment opportunities. Implementation of Artificial Intelligence (AI), machine learning, and autonomous technologies in the mining industry started about a decade ago with the first application to autonomous trucks. The autonomous technologies provide many economic benefits to the mining industry through cost reduction, productivity improvement, reduction in exposure of workers to hazardous conditions, continuous production, and improved safety. However, implementation of these technologies has faced economic, financial, technological, workforce, and social challenges. This paper discusses the current status …
Cryptovisor: A Cryptocurrency Advisor Tool, Matthew Baldree, Paul Widhalm, Brandon Hill, Matteo Ortisi
Cryptovisor: A Cryptocurrency Advisor Tool, Matthew Baldree, Paul Widhalm, Brandon Hill, Matteo Ortisi
SMU Data Science Review
In this paper, we present a tool that provides trading recommendations for cryptocurrency using a stochastic gradient boost classifier trained from a model labeled by technical indicators. The cryptocurrency market is volatile due to its infancy and limited size making it difficult for investors to know when to enter, exit, or stay in the market. Therefore, a tool is needed to provide investment recommendations for investors. We developed such a tool to support one cryptocurrency, Bitcoin, based on its historical price and volume data to recommend a trading decision for today or past days. This tool is 95.50% accurate with …
Feeling Ai
SIGNED: The Magazine of The Hong Kong Design Institute
We all develop emotional connections to the devices we use; the smartphone that is a constant companion or the office printer that is a constant source of frustration. Soon, these machines might be able to respond in kind
Mining Temporal Activity Patterns On Social Media, Nikan Chavoshi
Mining Temporal Activity Patterns On Social Media, Nikan Chavoshi
Computer Science ETDs
Social media provide communication networks for their users to easily create and share content. Automated accounts, called bots, abuse these platforms by engaging in suspicious and/or illegal activities. Bots push spam content and participate in sponsored activities to expand their audience. The prevalence of bot accounts in social media can harm the usability of these platforms, and decrease the level of trustworthiness in them. The main goal of this dissertation is to show that temporal analysis facilitates detecting bots in social media. I introduce new bot detection techniques which exploit temporal information. Since automated accounts are controlled by computer programs, …
The Price Of Usability: Designing Operationalizable Strategies For Security Games, Sara Marie Mccarthy, Corine M. Laan, Kai Wang, Phebe Vayanos, Arunesh Sinha, Milind Tambe
The Price Of Usability: Designing Operationalizable Strategies For Security Games, Sara Marie Mccarthy, Corine M. Laan, Kai Wang, Phebe Vayanos, Arunesh Sinha, Milind Tambe
Research Collection School Of Computing and Information Systems
We consider the problem of allocating scarce security resources among heterogeneous targets to thwart a possible attack. It is well known that deterministic solutions to this problem being highly predictable are severely suboptimal. To mitigate this predictability, the game-theoretic security game model was proposed which randomizes over pure (deterministic) strategies, causing confusion in the adversary. Unfortunately, such mixed strategies typically involve randomizing over a large number of strategies, requiring security personnel to be familiar with numerous protocols, making them hard to operationalize. Motivated by these practical considerations, we propose an easy to use approach for computing strategies that are easy …
Non-Destructive Evaluation For Composite Material, Desalegn Temesgen Delelegn
Non-Destructive Evaluation For Composite Material, Desalegn Temesgen Delelegn
Electrical & Computer Engineering Theses & Dissertations
The Nondestructive Evaluation Sciences Branch (NESB) at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) has conducted impact damage experiments over the past few years with the goal of understanding structural defects in composite materials. The Data Science Team within the NASA LaRC Office of the Chief Information Officer (OCIO) has been working with the Non-Destructive Evaluation (NDE) subject matter experts (SMEs), Dr. Cheryl Rose, from the Structural Mechanics & Concepts Branch and Dr. William Winfree, from the Research Directorate, to develop computer vision solutions using digital image processing and machine learning techniques that can help identify …
Modeling Contemporaneous Basket Sequences With Twin Networks For Next-Item Recommendation, Duc Trong Le, Hady W. Lauw, Yuan Fang
Modeling Contemporaneous Basket Sequences With Twin Networks For Next-Item Recommendation, Duc Trong Le, Hady W. Lauw, Yuan Fang
Research Collection School Of Computing and Information Systems
Our interactions with an application frequently leave a heterogeneous and contemporaneous trail of actions and adoptions (e.g., clicks, bookmarks, purchases). Given a sequence of a particular type (e.g., purchases)-- referred to as the target sequence, we seek to predict the next item expected to appear beyond this sequence. This task is known as next-item recommendation. We hypothesize two means for improvement. First, within each time step, a user may interact with multiple items (a basket), with potential latent associations among them. Second, predicting the next item in the target sequence may be helped by also learning from another supporting sequence …
Taxis Strike Back: A Field Trial Of The Driver Guidance System, Shih-Fen Cheng, Shashi Shekhar Jha, Rishikeshan Rajendram
Taxis Strike Back: A Field Trial Of The Driver Guidance System, Shih-Fen Cheng, Shashi Shekhar Jha, Rishikeshan Rajendram
Research Collection School Of Computing and Information Systems
Traditional taxi fleet operators world-over have been facing intense competitions from various ride-hailing services such as Uber and Grab (specific to the Southeast Asia region). Based on our studies on the taxi industry in Singapore, we see that the emergence of Uber and Grab in the ride-hailing market has greatly impacted the taxi industry: the average daily taxi ridership for the past two years has been falling continuously, by close to 20% in total. In this work, we discuss how efficient real-time data analytics and large-scale multi-agent optimization technology could potentially help taxi drivers compete against more technologically advanced service …
Identification And Optimal Linear Tracking Control Of Odu Autonomous Surface Vehicle, Nadeem Khan
Identification And Optimal Linear Tracking Control Of Odu Autonomous Surface Vehicle, Nadeem Khan
Mechanical & Aerospace Engineering Theses & Dissertations
Autonomous surface vehicles (ASVs) are being used for diverse applications of civilian and military importance such as: military reconnaissance, sea patrol, bathymetry, environmental monitoring, and oceanographic research. Currently, these unmanned tasks can accurately be accomplished by ASVs due to recent advancements in computing, sensing, and actuating systems. For this reason, researchers around the world have been taking interest in ASVs for the last decade. Due to the ever-changing surface of water and stochastic disturbances such as wind and tidal currents that greatly affect the path-following ability of ASVs, identification of an accurate model of inherently nonlinear and stochastic ASV system …
Using Eeg-Validated Music Emotion Recognition Techniques To Classify Multi-Genre Popular Music For Therapeutic Purposes, Dejoy Shastikk Kumaran
Using Eeg-Validated Music Emotion Recognition Techniques To Classify Multi-Genre Popular Music For Therapeutic Purposes, Dejoy Shastikk Kumaran
The International Student Science Fair 2018
Music is observed to possess significant beneficial effects to human mental health, especially for patients undergoing therapy and older adults. Prior research focusing on machine recognition of the emotion music induces by classifying low-level music features has utilized subjective annotation to label data for classification. We validate this approach by using an electroencephalography-based approach to cross-check the predictions of music emotion made with the predictions from low-level music feature data as well as collected subjective annotation data. Collecting 8-channel EEG data from 10 participants listening to segments of 40 songs from 5 different genres, we obtain a subject-independent classification accuracy …
Perception & Perspective: An Analysis Of Discourse And Situational Factors In Reference Frame Selection, Robert J. Ross, Kavita E. Thomas
Perception & Perspective: An Analysis Of Discourse And Situational Factors In Reference Frame Selection, Robert J. Ross, Kavita E. Thomas
Conference papers
To integrate perception into dialogue, it is necessary to bind spatial language descriptions to reference frame use. To this end, we present an analysis of discourse and situational factors that may influence reference frame choice in dialogues. We show that factors including spatial orientation, task, self and other alignment, and dyad have an influence on reference frame use. We further show that a computational model to estimate reference frame based on these features provides results greater than both random and greedy reference frame selection strategies.
Using Eeg-Validated Music Emotion Recognition Techniques To Classify Multi-Genre Popular Music For Therapeutic Purposes, Dejoy Shastikk Kumaran
Using Eeg-Validated Music Emotion Recognition Techniques To Classify Multi-Genre Popular Music For Therapeutic Purposes, Dejoy Shastikk Kumaran
The International Student Science Fair 2018
Music is observed to possess significant beneficial effects to human mental health, especially for patients undergoing therapy and older adults. Prior research focusing on machine recognition of the emotion music induces by classifying low-level music features has utilized subjective annotation to label data for classification. We validate this approach by using an electroencephalography-based approach to cross-check the predictions of music emotion made with the predictions from low-level music feature data as well as collected subjective annotation data. Collecting 8-channel EEG data from 10 participants listening to segments of 40 songs from 5 different genres, we obtain a subject-independent classification accuracy …
Mind The Gap: Situated Spatial Language A Case-Study In Connecting Perception And Language, John D. Kelleher
Mind The Gap: Situated Spatial Language A Case-Study In Connecting Perception And Language, John D. Kelleher
Other
This abstract reviews the literature on computational models of spatial semantics and the potential of deep learning models as an useful approach to this challenge.
Combination Forecasting Of Stock Index Time Series Based On Cooperative Game Theory, Luo Wei
Combination Forecasting Of Stock Index Time Series Based On Cooperative Game Theory, Luo Wei
Journal of System Simulation
Abstract: In view of the characteristics of nonlinear, large amplitude, frequent fluctuations in China's stock market, a prediction method of intelligent composite stock index time series based on the cooperative game is presented. The prediction model of stock index time series is established by using neural network method based on the correlations among the various economic indicators, and the development trend and laws of stock index time series are established by using the improved ARIMA method. The two methods are combined by importing cooperative game method. Simulation results show that the prediction accuracy of the presented method is controlled …
Real-Time Simulator For Spatial Information Networks Based On Analog If Signal Processing, Zeguo Yang, Ma Shang, Diaopeng Huang, Jianhao Hu, Lixiang Liu
Real-Time Simulator For Spatial Information Networks Based On Analog If Signal Processing, Zeguo Yang, Ma Shang, Diaopeng Huang, Jianhao Hu, Lixiang Liu
Journal of System Simulation
Abstract: To solve the problem of real-time simulation of spatial information network with high dynamic network topology, a real-time simulator based on the IF signal processing is proposed. Compared with traditional channel simulator, it supports both the channel transmission characteristics like channel fading, Doppler shift, noise, and path delay, and the real-time simulation of dynamic network topology changes. The simulator supports 8~128 70 MHz IF (0~20 MHz signal bandwidth) emulated nodes with flexible link type configuration. The maximal fading depth is 100 dB, the maximal Doppler shift is 2 MHz, and the maximal path delay can reach up …
A Lightweight Modeling And Simulation Technical Framework For Complex Systems, Ji Hang, Junhua Zhou, Guoqiang Shi, Tingyu Lin, Junjie Xue
A Lightweight Modeling And Simulation Technical Framework For Complex Systems, Ji Hang, Junhua Zhou, Guoqiang Shi, Tingyu Lin, Junjie Xue
Journal of System Simulation
Abstract: Aiming at the modeling and simulation verification of complex systems, the paper established a lightweight simulation technical framework and a system building method. The simulation technical framework is built based on distributed network communication middleware and has graphic user interface, simulation management and run control modules, it packages effective and lightweight network middleware, object management, event management and time management and it is capable of interoperability and its members have abilities of reusable and combinable. The results show that the framework can supports flexible construction and effective simulation on complex systems.
Temperature Characteristics Of Contact Wire Under Different Driving Intervals, Hongwei Wang, Zhang Kai, Zhiyong Wang, Fengyi Guo, Liu Shuai, Zhang Qiong
Temperature Characteristics Of Contact Wire Under Different Driving Intervals, Hongwei Wang, Zhang Kai, Zhiyong Wang, Fengyi Guo, Liu Shuai, Zhang Qiong
Journal of System Simulation
Abstract: To reduce the wear of pantograph and catenary system while decreasing the headway, the temperature field of the contact wire is studied. A simulation model is established by using the COMSOL Multiphysics software. The effectiveness of the model is verified with temperature experiments. Temperature field of the contact wire of freight locomotive and passenger locomotive in different intervals is studied by simulation. The smaller the headway of trains, the higher the temperature value, and the shorter the balance process. Under the constraint of temperature field, the headway of freight locomotive couldn't be less than 180s under long term operation. …
Analysis And Simulation Of Temperature Control For Battery Pole Piece Electromagnetic Heating Roller, Jing Ran, Feng Hua, Yonggeng Wang, Haiping Song, Yanjun Xiao
Analysis And Simulation Of Temperature Control For Battery Pole Piece Electromagnetic Heating Roller, Jing Ran, Feng Hua, Yonggeng Wang, Haiping Song, Yanjun Xiao
Journal of System Simulation
Abstract: With the application of electromagnetic heating roller on battery pole piece rolling,the processing technology, quality and efficiency of the battery pole piece are improved. The special heating technology of electromagnetic heating roller which involves multi-physics coupling in the process of conversion makes it difficult to control the heating process and determine the control index. By studying the electromagnetic heating theory, the mathematical model of electromagnetic heating roller is established and the simulation and analysis of the electromagnetic heating roller using MATLAB software and the finite difference method are carried out. The distribution, change rule and influence factors of the …
Modeling & Simulation Technology In Manufacturing, Zhang Lin, Longfei Zhou
Modeling & Simulation Technology In Manufacturing, Zhang Lin, Longfei Zhou
Journal of System Simulation
Abstract: With the continuous deepening of the application of information technology in the manufacturing field, the informatization of manufacturing systems is developing from unit digital manufacturing to integration networked manufacturing, and then to the comprehensive digital, networked and intelligent manufacturing. As a comprehensive information technology integrating computer, model theory, and scientific computing, modeling & simulation technology plays an irreplaceable role during the development of manufacturing informatization and is widely applied in all phases of the whole product lifecycle, such as design, manufacturing, testing, maintenance, purchase, sales and other phase. This paper reviews and summarizes the research and application of modeling …
Research On Maturity Evaluation Technology Of Complex Digital Industrial System, Geng Chao, Shiyou Qu, Tingyu Lin, Guoqiang Shi, Yingying Xiao, Wang Mei, Qiudan Ma, Ji Hang
Research On Maturity Evaluation Technology Of Complex Digital Industrial System, Geng Chao, Shiyou Qu, Tingyu Lin, Guoqiang Shi, Yingying Xiao, Wang Mei, Qiudan Ma, Ji Hang
Journal of System Simulation
Abstract: Under the background of a new round of the innovation of science and technology and the revolution of industry, the complex digital industrial system is constantly innovating and shaping. Firstly, the paper established maturity evaluation model of the complex digital industrial system based on system engineering. Then, the paper proposed multi - index maturity analysis method and multi - enterprise maturity synthesis method of the complex digital industrial system. Combined with the digital industrial system of aerospace complex product, an evaluation example is presented. The results show that the maturity evaluation method can be used to standardize and guide …
Identification Of Closed Loop Projection Subspace For Motor Based On Hankel Correlation Function, Minghong She
Identification Of Closed Loop Projection Subspace For Motor Based On Hankel Correlation Function, Minghong She
Journal of System Simulation
Abstract: To solve estimation deviation problem of model parameter in the closed-loop system identification, the subspace identification model and state space model based on the estimation of the correlation function are presented, and through the correlation function estimation and zero space followed by projection, the block Hankel matrix of identification framework was filled so as to obtain the scope of the extended observability matrix; on the basis of the same projection on the time offset set of related data, the RQ decomposition of the projection is calculated by numerical calculation, and the dynamic estimation of the system model is obtained. …
High Frequency Blend Clips Matching Based Fire Sound Synthesis, Yin Qiang, Shiguang Liu
High Frequency Blend Clips Matching Based Fire Sound Synthesis, Yin Qiang, Shiguang Liu
Journal of System Simulation
Abstract: Aimed at the problem which generated by fire sound simulation in virtual reality field, a new fire sound synthesis method was proposed. Most of the sound synthesis methods currently separate the fire sound into low and high frequencies for synthesizing. The influence of low frequency fire sound models was considered and the low frequency signal was synthesized based on the physical visual fire model data. The high frequency sound signal was synthesized based on high frequency blend clips matching method. According to the characteristics of the fire's high frequency, the different frequency bands of high noise signal …