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Articles 13081 - 13110 of 25753

Full-Text Articles in Computer Engineering

Can Threshold-Based Sensor Alerts Be Analysed To Detect Faults In A District Heating Network?, Liam Cantwell Jan 2018

Can Threshold-Based Sensor Alerts Be Analysed To Detect Faults In A District Heating Network?, Liam Cantwell

Dissertations

Older IoT “smart sensors” create system alerts from threshold rules on reading values. These simple thresholds are not very flexible to changes in the network. Due to the large number of false positives generated, these alerts are often ignored by network operators. Current state-of-the-art analytical models typically create alerts using raw sensor readings as the primary input. However, as greater numbers of sensors are being deployed, the growth in the number of readings that must be processed becomes problematic. The number of analytic models deployed to each of these systems is also increasing as analysis is broadened. This study aims …

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Elasticity Measurement In Caas Environments - Extending The Existing Bungee Elasticity Benchmark To Aws's Elastic Container Service, Nora Limbourg Jan 2018

Elasticity Measurement In Caas Environments - Extending The Existing Bungee Elasticity Benchmark To Aws's Elastic Container Service, Nora Limbourg

Dissertations

Rapid elasticity and automatic scaling are core concepts of most current cloud computing systems. Elasticity describes how well and how fast cloud systems adapt to increases and decreases in workload. In parallel, software architectures are moving towards employing containerised microservices running on systems managed by container orchestration platforms. Cloud users who employ such container-based systems may want to compare the elasticity of different systems or system settings to ensure rapid elasticity and maintain service level objectives while avoiding over-provisioning. Previous research has established a variety of metrics to measure elasticity. Some existing benchmark tools are designed to measure elasticity in …

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From Business Understanding To Deployment: An Application Of Machine Learning Algorithms To Forecast Customer Visits Per Hour To A Fast-Casual Restaurant In Dublin, Odunayo David Adedeji Jan 2018

From Business Understanding To Deployment: An Application Of Machine Learning Algorithms To Forecast Customer Visits Per Hour To A Fast-Casual Restaurant In Dublin, Odunayo David Adedeji

Dissertations

This research project identifies the significant factors that affects the number of customer visits to a fast-casual restaurant every hour and proceeds to develop several machine learning models to forecast customer visits. The core value proposition of fast-casual restaurants is quality food delivered at speed which means they have to prepare meals in advance of customers visit but the problem with this approach is in forecasting future demand, under estimating demand could lead to inadequate meal preparation which would leave customers unsatisfied while over estimation of demand could lead to wastage especially with restaurants having to comply with food safety …

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Can Machine Learning Beat Physics At Modeling Car Crashes?, Gavin Byrne Jan 2018

Can Machine Learning Beat Physics At Modeling Car Crashes?, Gavin Byrne

Dissertations

This study aimed to look at a traditional method used for measuring the severity and principle direction of force of a car crash and see if it could be improved on using machine learning models. The data used was publicly available from the NHTSA database and included descriptions of the vehicle, test and sensors as well as the accelerometer data over the period of the crashes. The models built were SVM classifiers and multinomial regression models. Although the SVM and Regression models were built successfully and gave higher levels of accuracy than the momentum models in terms of the severity, …

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Supervised Learning Models To Predict Stock Direction Within Different Sectors In A Bull And Bear Market, Tiffany Razy Jan 2018

Supervised Learning Models To Predict Stock Direction Within Different Sectors In A Bull And Bear Market, Tiffany Razy

Dissertations

Forecasting stock market price movement is a well researched and an alluring topic within the machine learning and financial realm. Supervised machine learning algorithms such as Random Forest (RF) and Support Vector Machines (SVM) have been used independently to gain insight on the market. With such volatility in the market the scope of this study will utilized the RF and SVM in a very volatility market to determine if these models will perform at a high level or outperform each other in both markets. This relative study is performed on 16 stocks in 4 different sectors over the bear market …

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User-Friendly Deniable Storage For Mobile Devices, Bing Chang, Yao Cheng, Bo Chen, Fengwei Zhang, Wen-Tao Zhu, Yanju Liu, Zhan Wang Jan 2018

User-Friendly Deniable Storage For Mobile Devices, Bing Chang, Yao Cheng, Bo Chen, Fengwei Zhang, Wen-Tao Zhu, Yanju Liu, Zhan Wang

Research Collection School Of Computing and Information Systems

Mobile devices are prevalently used to process sensitive data, but traditional encryption may not work when an adversary is able to coerce the device owners to disclose the encryption keys. Plausibly Deniable Encryption (PDE) is thus designed to protect sensitive data against this powerful adversary. In this paper, we present MobiPluto, a user-friendly PDE scheme for denying the existence of sensitive data stored on mobile devices. A salient difference between MobiPluto and the existing PDE systems is that any block-based file systems can be deployed on top of it. To further improve usability and deniability of MobiPluto, we introduce a …

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Investigating The Application Of Deep Convolutional Neural Networks In Semi-Supervised Video Object Segmentation, Jayadeep Sasikumar Jan 2018

Investigating The Application Of Deep Convolutional Neural Networks In Semi-Supervised Video Object Segmentation, Jayadeep Sasikumar

Dissertations

This thesis investigates the different approaches to video object segmentation and the current state-of-the-art in the discipline, focusing on the different deep learning techniques used to solve the problem. The primary contribution of the thesis is the investigation of usefulness of Exponential Linear Units as activation functions for deep convolutional neural architectures trained to perform object semi-supervised segmentation in videos. Mask R-CNN was chosen as the base convolutional neural architecture, with the view of extending the image segmentation algorithm to videos. Two models were created, one with Rectified Linear Units and the other with Exponential Linear Units as the respective …

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Quantitative Fine-Grained Human Evaluation Of Machine Translation Systems: A Case Study On English To Croatian, Filip Klubicka, Antonio Toral, Victor Manuel Sanchez-Cartagena Jan 2018

Quantitative Fine-Grained Human Evaluation Of Machine Translation Systems: A Case Study On English To Croatian, Filip Klubicka, Antonio Toral, Victor Manuel Sanchez-Cartagena

Articles

This paper presents a quantitative fine-grained manual evaluation approach to comparing the performance of different machine translation (MT) systems. We build upon the well-established Multidimensional Quality Metrics (MQM) error taxonomy and implement a novel method that assesses whether the differences in performance for MQM error types between different MT systems are statistically significant. We conduct a case study for English-to- Croatian, a language direction that involves translating into a morphologically rich language, for which we compare three MT systems belonging to different paradigms: pure phrase-based, factored phrase-based and neural. First, we design an MQM-compliant error taxonomy tailored to the relevant …

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Applications Of Robot Operating System (Ros) To Mobile Microgrid Formation Outdoors, John Naglak Jan 2018

Applications Of Robot Operating System (Ros) To Mobile Microgrid Formation Outdoors, John Naglak

Dissertations, Master's Theses and Master's Reports

Application of mobile robots to microgrid formation has value for disaster response and service of forward operating bases. This thesis describes the development, testing and demonstration of broad effort across multiple disciplines to enable outdoor positioning and connection of mobile microgrids for the first time. This work includes an outdoor waypoint controller for a UGV agent, specifically the Clearpath Husky. It details sensor fusion of 2D LiDAR and stereo vision, and fusion of odometry sources using an Extended Kalman Filter. Development of these software tools entails integration of many of the packages available through the Robot Operating System (ROS), with …

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Matrix Effect Study And Immunoassay Detection Using Electrolyte-Gated Graphene Biosensor, Jianbo Sun, Yuxin Liu Jan 2018

Matrix Effect Study And Immunoassay Detection Using Electrolyte-Gated Graphene Biosensor, Jianbo Sun, Yuxin Liu

Faculty & Staff Scholarship

Significant progress has been made on the development of electrolyte-gated graphene field effect transistor (EGGFET) biosensors over the last decade, yet they are still in the stage of proof-of-concept. In this work, we studied the electrolyte matrix effects, including its composition, pH and ionic strength, and demonstrate that variations in electrolyte matrices have a significant impact on the Fermi level of the graphene channel and the sensitivity of the EGGFET biosensors. This is attributed to the polarization-induced interaction between the electrolyte and the graphene at the interface which can lead to considerable modulation of the Fermi level of the graphene …

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Human Performance Modelling For Adaptive Automation, Maria Chiara Leva, M. Wilkins, F. Coster Jan 2018

Human Performance Modelling For Adaptive Automation, Maria Chiara Leva, M. Wilkins, F. Coster

Conference papers

The relentless march of technology is increasingly opening new possibilities for the application of automation and new horizons for human machine interaction. However there is insufficient scientific evidence on human factors for modern socio-technical systems supporting the guidelines currently used to design Human Machine Interfaces (HMI) (ISA 2014). This dearth of knowledge presents a particular risk in safety critical industries. The continuing 60–90% of accidents currently that are rooted in Human Factors (HF) and the rapid developments in the Internet of Things (IoT) and its novel automation archetypes means that the requirements for new interfaces are becoming more demanding, and …

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An Autonomous Intelligent Robotic Wheelchair To Assist People In Need: Standing-Up, Turning-Around And Sitting-Down, Iosif Papadakis Ktistakis Jan 2018

An Autonomous Intelligent Robotic Wheelchair To Assist People In Need: Standing-Up, Turning-Around And Sitting-Down, Iosif Papadakis Ktistakis

Browse all Theses and Dissertations

The world’s ageing population has significantly increased over the last decades, which will result in one of the most significant transformations of the twenty-first century. As people age, they become more vulnerable to diseases and their health may need constant monitoring. At the same time, the number of people who have some kind of disability is also increasing. These people with disabilities may need daily assistance and monitoring of their health condition that is provided by specialists (health providers) at a high cost. A possible solution to the aforementioned problem comes from the assistive and intelligent robotics research area. The …

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Interactive Visualization Of Search Results Of Large Document Sets, James D. Anderson Jan 2018

Interactive Visualization Of Search Results Of Large Document Sets, James D. Anderson

Browse all Theses and Dissertations

When presented with many search results, finding information or patterns within the data poses a challenge. This thesis presents the design, implementation and evaluation of a visualization enabling users to browse through voluminous information and comprehend the data. Implemented with the JavaScript library Data Driven Documents (D3), the visualization represents the search as clusters of similar documents grouped into bubbles with the contents depicted as word-clouds. Highly interactive features such as touch gestures and intuitive menu actions allow for expeditious exploration of the search results. Other features include drag-and-drop functionality for articles among bubbles, merging nodes, and refining the search …

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Overwhelming The Saa System Of Delivery Uavs By Drone Swarming, Barry Lynn Pfaff Jan 2018

Overwhelming The Saa System Of Delivery Uavs By Drone Swarming, Barry Lynn Pfaff

Browse all Theses and Dissertations

As the Internet continues to replace the brick-and-mortar store as the main place for purchasing goods, web-based companies are looking for ways to reduce the cost of delivering those goods. The use of Unmanned Aerial Vehicles, or UAVs, is one delivery method that is increasingly being used. These UAVs can be programmed with delivery routes and destinations and can complete the job while requiring limited intervention from human controllers. Sense and Avoidance (SAA) systems have recently been incorporated into these UAVs so that they can detect objects in their flight path, reroute the UAV accordingly and operate even more autonomously. …

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Fully Transparent Computer Vision Framework For Ship Detection And Tracking In Satellite Imagery, Jason T. Gottweis Jan 2018

Fully Transparent Computer Vision Framework For Ship Detection And Tracking In Satellite Imagery, Jason T. Gottweis

Browse all Theses and Dissertations

Tracking of ships in satellite imagery is a challenging problem in remote sensing since it requires both object detection and object recognition. Most of the resources available only cover one of these problems and are often filled with machine learning techniques which are costly to train. Additionally, the techniques covered in these resources are often difficult to replicate or may be hard to combine with other solutions to get a full tracking algorithm. The proposed framework offers a transparent and efficient alternative to machine learning approaches and includes preprocessing, detection, and recognition needed for tracking. All components of the framework …

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Augment The Multi-Modal Interaction Capabilities Of Hololens Through Networked Sensory Devices, Subhadra Tummalapally Jan 2018

Augment The Multi-Modal Interaction Capabilities Of Hololens Through Networked Sensory Devices, Subhadra Tummalapally

Browse all Theses and Dissertations

Augmented Reality (AR) places virtual contents along with real objects to enhance user perception in the physical environment. It is a technology that has shown great potential in many industries such as medicine, education and transportation. AR devices, such as Microsoft HoloLens, come with multi-modal interaction capabilities, such as voice, gesture and gaze, to support intuitive and reliable human-computer interactions. However, HoloLens gesture support is limited to simple gestures like tap, bloom and hold, it stops short to support meaningful interaction through full hand gesture and motion tracking, which may be critical in field operations of various industry practices in …

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G-Code Modeling For 3d Printer Quality Assessment, Tyler Welander, Ronald Marsh, Md Nurul Amin Jan 2018

G-Code Modeling For 3d Printer Quality Assessment, Tyler Welander, Ronald Marsh, Md Nurul Amin

Computer Science Faculty Publications

The Department of Computer Science at the University of North Dakota (UND) has been evaluating optical/imaging methods for measuring the quality of 3D printed parts. In particular, we are interested in optical/imaging methods that can detect and measure such quality issues as layer shifting, layer separation and splitting, overheating, dimensional accuracy, and infill errors. This paper describes our work towards the analysis of infill errors as the quality of the infill does impact the structural integrity of the part being made. Externally, a part may look acceptable, but if the infill is faulty the part may be structurally unsound. Furthermore, …

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Pedagogical Benefits From An Exercise In Reverse Engineering For An Aviation Software Systems, Emanuel S. Grant, Pann Ajjimaporn Jan 2018

Pedagogical Benefits From An Exercise In Reverse Engineering For An Aviation Software Systems, Emanuel S. Grant, Pann Ajjimaporn

Computer Science Faculty Publications

Since the Y2K crisis, reverse engineering has become a major area of work in industrial software application development, but lacks emphasis in US academia. This issue is exemplified by the high demand for software systems in new and expanding software application areas, which has resulted in systems being implemented before the requirements and design phases have been completed. Towards the maintenance of such systems, it is necessary to conducted reverse engineering for the derivation of software documentation for requirements and high-level and low-level design. When this scenario exists in the domain of safety-critical system, particularly in the aviation industry, reverse …

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Administrative Cost Reimbursement Online, Luciano Mogorovic Jan 2018

Administrative Cost Reimbursement Online, Luciano Mogorovic

Williams Honors College, Honors Research Projects

Administrative Cost Reimbursement (ACR) is a program funded by the state of Ohio that reimburses non-public elementary and high schools for having employees perform a series of mandated activities. ACR Consultants is a company that collects data from schools that contains the amount of time each teacher spent on any of the mandated activities. The president of ACR Consultants is a neighbor and longtime family friend. Currently, to collect the time data, the company goes to each school it services and gives each teacher a large paper spreadsheet for them to fill in with the amount of time they spend …

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A Twitter-Based Study For Understanding Public Reaction On Zika Virus, Roopteja Muppalla Jan 2018

A Twitter-Based Study For Understanding Public Reaction On Zika Virus, Roopteja Muppalla

Browse all Theses and Dissertations

In recent times, social media platforms like Twitter have become more popular and people have become more interactive and responsive than before. People often react to every news in real-time and within no-time, the information spreads rapidly. Even with viral diseases like Zika, people tend to share their opinions and concerns on social media. This can be leveraged by the health officials to track the disease in real-time thereby reducing the time lag due to traditional surveys. A faster and accurate detection of the disease can allow health officials to understand people's opinion of the disease and take necessary precautions …

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A Model For Seasonal Dynamic Networks, Jace D. Robinson Jan 2018

A Model For Seasonal Dynamic Networks, Jace D. Robinson

Browse all Theses and Dissertations

Sociotechnological and geospatial processes exhibit time varying structure that make insight discovery challenging. This paper presents statistical model of systems with seasonal dynamics, modeled as a dynamic network, to address this challenge. It assumes the probability of edge formations depend on a type assigned to incident nodes and the current time. Time dependencies are modeled by unique seasonal processes. The model is studied on several synthetic and real datasets. Superior fidelity of this model on seasonal datasets compared to existing network models, while being able to remain equally accurate for networks with randomly changing structure, is shown. The model is …

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Virtual Doctor: An Intelligent Human-Computer Dialogue System For Quick Response To People In Need, Stavros Mallios Jan 2018

Virtual Doctor: An Intelligent Human-Computer Dialogue System For Quick Response To People In Need, Stavros Mallios

Browse all Theses and Dissertations

One of the challenges of our society is the existence of chronic-related conditions and diseases among the elderly and people at risk. Apart from the welfare of people, a significant impact of this phenomenon is the accumulation of high financial costs for both individuals and health care systems. In order to address this issue and to reduce its effects, many efforts have been made towards preventing, identifying in early stages and, generally, managing chronic-related medical conditions and diseases. As a result, there has been a keen research and market interest in health monitoring devices during the past few decades. Nevertheless, …

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A Multi-Formal Languages Collaborative Scheme For Complex Human Activity Recognition And Behavioral Patterns Extraction, Anargyros Angeleas Jan 2018

A Multi-Formal Languages Collaborative Scheme For Complex Human Activity Recognition And Behavioral Patterns Extraction, Anargyros Angeleas

Browse all Theses and Dissertations

Human Activity Recognition is an actively researched domain for the past few decades, and is one of the most eminent applications of today. It is already part of our life, but due to high level of uncertainty and challenges of human detection, we have only application specific solutions. Thus, the problem being very demanding and still remains unsolved. Within this PhD we delve into the problem, and approach it from a variety of viewpoints. At start, we present and evaluate different architectures and frameworks for activity recognition. Henceforward, the focal point of our attention is automatic human activity recognition. We …

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Use Of Adaptive Mobile Applications To Improve Mindfulness, Wiehan Boshoff Jan 2018

Use Of Adaptive Mobile Applications To Improve Mindfulness, Wiehan Boshoff

Browse all Theses and Dissertations

Mindfulness is the state of retaining awareness of what is happening at the current point in time. It has been used in multiple forms to reduce stress, anxiety, and even depression. Promoting Mindfulness can be done in various ways, but current research shows a trend towards preferential usage of breathing exercises over other methods to reach a mindful state. Studies have showcased that breathing can be used as a tool to promote brain control, specifically in the auditory cortex region. Research pertaining to disorders such as Tinnitus, the phantom awareness of sound, could potentially benefit from using these brain control …

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Domain-Specific Knowledge Extraction From The Web Of Data, Sarasi Lalithsena Jan 2018

Domain-Specific Knowledge Extraction From The Web Of Data, Sarasi Lalithsena

Browse all Theses and Dissertations

Domain knowledge plays a significant role in powering a number of intelligent applications such as entity recommendation, question answering, data analytics, and knowledge discovery. Recent advances in Artificial Intelligence and Semantic Web communities have contributed to the representation and creation of this domain knowledge in a machine-readable form. This has resulted in a large collection of structured datasets on the Web which is commonly referred to as the Web of data. The Web of data continues to grow rapidly since its inception, which poses a number of challenges in developing intelligent applications that can benefit from its use. Majority of …

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Sensor Data Streams Correlation Platform For Asthma Management, Vaikunth Sridharan Jan 2018

Sensor Data Streams Correlation Platform For Asthma Management, Vaikunth Sridharan

Browse all Theses and Dissertations

Asthma is a high-burden chronic inflammatory disease with prevalence in children with twice the rate compared to adults. It can be improved by continuously monitoring patients and their environment using the Internet of Things (IoT) based devices. These sensor data streams so obtained are essential to comprehend multiple factors triggering asthma symptoms. In order to support physicians in exploring causal associations and finding actionable insights, a visualization system with a scalable cloud infrastructure that can process multimodal sensor data and Patient Generated Health Data (PGHD) is necessary. In this thesis, we describe a cloud-based asthma management and visualization platform that …

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Measuring Goal Similarity Using Concept, Context And Task Features, Vahid Eyorokon Jan 2018

Measuring Goal Similarity Using Concept, Context And Task Features, Vahid Eyorokon

Browse all Theses and Dissertations

Goals can be described as the user's desired state of the agent and the world and are satisfied when the agent and the world are altered in such a way that the present state matches the desired state. For physical agents, they must act in the world to alter it in a series of individual atomic actions. Traditionally, agents use planning to create a chain of actions each of which altering the current world state and yielding a new one until the final action yields the desired goal state. Once this goal state has been achieved, the goal is said …

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Image Stitching And Matching Tool In The Automated Iterative Reverse Engineer (Aire) Integrated Circuit Analysis Suite, David C. Bowman Jan 2018

Image Stitching And Matching Tool In The Automated Iterative Reverse Engineer (Aire) Integrated Circuit Analysis Suite, David C. Bowman

Browse all Theses and Dissertations

Due to current market forces, leading-edge semiconductor fabrication plants have moved outside of the US. While this is not a problem at first glance, when it comes to security-sensitive applications, over-production, device cloning, or design alteration becomes a possibility. Since these vulnerabilities exist during the fabrication phase, a Reverse Engineering (RE) step must be introduced to help ensure secure device operation. This thesis proposes several unique methods and a collection of tools to ensure trust assurance in integrated circuit design by detecting fabrication flaws and possible hardware Trojans using several image processing techniques; fused into a singular view of the …

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The Feasibility Of Dementia Caregiver Task Performance Measurement Using Smart Gaming Technology, Garrett G. Goodman Jan 2018

The Feasibility Of Dementia Caregiver Task Performance Measurement Using Smart Gaming Technology, Garrett G. Goodman

Browse all Theses and Dissertations

Dementia caregiver burnout is detrimental to both the familial caregiver and their loved ones with dementia. As the population of older adults increases, both the number of individuals with dementia and their corresponding caregivers increase as well. Thus, we are interested in developing a potential tool to non-invasively detect signs of caregiver burnout using a mobile application combined with machine learning. Hence, the mobile application "Caregiver Assessment using Smart Technology" (CAST) was developed which personalizes a word scramble game. The CAST application utilizes a heuristically constructed Fuzzy Inference System (FIS) optimized via a Genetic Algorithm (GA) to provide an individualized …

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Development Of A Human-Ai Teaming Based Mobile Language Learning Solution For Dual Language Learners In Early And Special Educations, Saurabh Shukla Jan 2018

Development Of A Human-Ai Teaming Based Mobile Language Learning Solution For Dual Language Learners In Early And Special Educations, Saurabh Shukla

Browse all Theses and Dissertations

Learning English as a secondary language is often an overwhelming challenge for dual language learners (DLLs), whose first language (L1) is not English, especially for children in early education (PreK-3 age group). These early DLLs need to devote a considerable amount of time learning to speak and read the language, in order to gain the language proficiency to function and compete in the classroom. Fear of embarrassment when mispronouncing words in front of others may drive them to remain silent; effectively hampering their participation in the class and overall curricular growth. The process of learning a new language can benefit …

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