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2022

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Articles 3421 - 3450 of 3613

Full-Text Articles in Computer Sciences

Loguad: Log Unsupervised Anomaly Detection Based On Word2vec, Jin Wang, Changqing Zhao, Shiming He, Yu Gu, Osama Alfarraj, Ahed Abugabah Jan 2022

Loguad: Log Unsupervised Anomaly Detection Based On Word2vec, Jin Wang, Changqing Zhao, Shiming He, Yu Gu, Osama Alfarraj, Ahed Abugabah

All Works

System logs record detailed information about system operation and are important for analyzing the system's operational status and performance. Rapid and accurate detection of system anomalies is of great significance to ensure system stability. However, large-scale distributed systems are becoming more and more complex, and the number of system logs gradually increases, which brings challenges to analyze system logs. Some recent studies show that logs can be unstable due to the evolution of log statements and noise introduced by log collection and parsing. Moreover, deep learning-based detection methods take a long time to train models. Therefore, to reduce the computational …

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Classification Of Parkinson Disease Based On Patient’S Voice Signal Using Machine Learning, Imran Ahmed, Sultan Aljahdali, Muhammad Shakeel Khan, Sanaa Kaddoura Jan 2022

Classification Of Parkinson Disease Based On Patient’S Voice Signal Using Machine Learning, Imran Ahmed, Sultan Aljahdali, Muhammad Shakeel Khan, Sanaa Kaddoura

All Works

Parkinson’s disease (PD) is a nervous system disorder first described as a neurological condition in 1817. It is one of the more prevalent diseases in the elderly, and Alzheimer’s is the second most common neurodegenerative illness. It impacts the patient’s movement. Symptoms start gradually with tremors, stiffness in movement, and speech and voice disorders. Researches proved that 89% of patients with Parkinson’s has speech disorder including uncertain articulation, hoarse and breathy voice and monotone pitch. The cause behind this voice change is the reduction of dopamine due to damage of neurons in the substantia nigra responsible for dopamine production. In …

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Trajectory Design For Uav-Based Data Collection Using Clustering Model In Smart Farming, Tariq Qayyum, Zouheir Trabelsi, Asad Malik, Kadhim Hayawi Jan 2022

Trajectory Design For Uav-Based Data Collection Using Clustering Model In Smart Farming, Tariq Qayyum, Zouheir Trabelsi, Asad Malik, Kadhim Hayawi

All Works

Unmanned aerial vehicles (UAVs) play an important role in facilitating data collection in remote areas due to their remote mobility. The collected data require processing close to the end-user to support delay-sensitive applications. In this paper, we proposed a data collection scheme and scheduling framework for smart farms. We categorized the proposed model into two phases: data collection and data scheduling. In the data collection phase, the IoT sensors are deployed randomly to form a cluster based on their RSSI. The UAV calculates an optimum trajectory in order to gather data from all clusters. The UAV offloads the data to …

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"What's In A Name?”: The Use Of Instructional Design In Overcoming Terminology Barriers Associated With Dark Patterns, Andrea Curley, Damian Gordon, Dympna O'Sullivan Jan 2022

"What's In A Name?”: The Use Of Instructional Design In Overcoming Terminology Barriers Associated With Dark Patterns, Andrea Curley, Damian Gordon, Dympna O'Sullivan

Conference Papers

Many users experience a phenomena when they are shopping on-line where they feel they are being pressured to either spend more money than they had intended, or to share more personal data than they wanted. In academic circles we use the term “Dark Patterns” to describe these deceptive practices, and categorize them as being within the discipline of User Experience (Narayanan, 2020). As academics it is important to name phenomena, and to categorize them, so that we can discuss and analyze these issues. However, this particular topic is one that all users should be made aware of when interacting online, …

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Towards An Active Foveated Approach To Computer Vision, Dario Dematties, Silvio Rizzi, George K. Thiruvathukal, Alejandro Javier Wainselboim Jan 2022

Towards An Active Foveated Approach To Computer Vision, Dario Dematties, Silvio Rizzi, George K. Thiruvathukal, Alejandro Javier Wainselboim

Computer Science: Faculty Publications and Other Works

In this paper, a series of experimental methods are presented explaining a new approach towards active foveated Computer Vision (CV). This is a collaborative effort between researchers at CONICET Mendoza Technological Scientific Center from Argentina, Argonne National Laboratory (ANL), and Loyola University Chicago from the US. The aim is to advance new CV approaches more in line with those found in biological agents in order to bring novel solutions to the main problems faced by current CV applications. Basically this work enhance Self-supervised (SS) learning, incorporating foveated vision plus saccadic behavior in order to improve training and computational efficiency without …

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On The Design And Implementation Of An On-Board Test Bed System For V2v Road Hazard Signaling, Fatma Outay, Faouzi Kamoun, Anouar Chemek, Hichem Bargaoui, Ansar Yasar Jan 2022

On The Design And Implementation Of An On-Board Test Bed System For V2v Road Hazard Signaling, Fatma Outay, Faouzi Kamoun, Anouar Chemek, Hichem Bargaoui, Ansar Yasar

All Works

This paper describes the design, implementation, and testing of an ITS-G5 prototype Road hazard Signaling (RHS) system that is inspired by the concept of crowdsourcing. Our approach enables drivers to interact with a touchscreen onboard interface to send ITS-G5 decentralized environmental notification messages (DENM) in order to warn nearby vehicles against the presence of a hazardous situation. These messages are analyzed, filtered for relevance, and presented to concerned drivers via the Onboard Units (OBUs) so that precautionary measures can be taken. We describe the design and implementation aspects of the proposed system and update the open source cargeo6 implementation of …

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Comparison Of Reaction Time-Based Collaborative Velocity Control And Intelligent Driver Model For Agent-Based Simulation Of Autonomous Car, Fatma Outay, Abdeljalil Abbas-Turki, Stéphane Galland, Alexandre Lombard, Nicolas Gaud Jan 2022

Comparison Of Reaction Time-Based Collaborative Velocity Control And Intelligent Driver Model For Agent-Based Simulation Of Autonomous Car, Fatma Outay, Abdeljalil Abbas-Turki, Stéphane Galland, Alexandre Lombard, Nicolas Gaud

All Works

Based on historical records, driving in hazardous weather conditions is one of the most serious causes that lead to fatal accidents on roads in general and in United Arab Emirates (UAE) highways in particular. One solution to improve road safety is to equip vehicles and infrastructure with connected and smart devices and convert them into autonomous vehicles. Before deploying a concrete solution to the field, it must be validated by simulation, and more specifically by agent-based simulation. In this paper, we propose to implement the Reaction Time-Based Collaborative Velocity Control (RT-CVC) model that was implemented in autonomous cars into an …

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Social Networking Applications: A Comparative Analysis For A Collaborative Learning Through Google Classroom And Zoom, Tariq Abu Hilal, Ala’ Abu Hilal, Hasan Abu Hilal Jan 2022

Social Networking Applications: A Comparative Analysis For A Collaborative Learning Through Google Classroom And Zoom, Tariq Abu Hilal, Ala’ Abu Hilal, Hasan Abu Hilal

All Works

Recently, social network applications were developed intensively due to the increasing compaction and user demands. These applications provide different services to their users like learning, awareness, chatting with friends, sharing global news, etc. Simply, this work introduces the advantages of these software applications, specifically in the field of education during the COVID 19 spread. Google Classroom and Zoom meetings had gained the attention of many educational institutes for using them as a learning platform for students and educators. This research used two methodologies SWOT analysis and the information system success model of DeLone and McLean's updated to evaluate the effectiveness …

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Haptic Feedback To Assist Blind People In Indoor Environment Using Vibration Patterns, Shah Khusro, Babar Shah, Inayat Khan, Sumayya Rahman Jan 2022

Haptic Feedback To Assist Blind People In Indoor Environment Using Vibration Patterns, Shah Khusro, Babar Shah, Inayat Khan, Sumayya Rahman

All Works

Feedback is one of the significant factors for the mental mapping of an environment. It is the communication of spatial information to blind people to perceive the surroundings. The assistive smartphone technologies deliver feedback for different activities using several feedback mediums, including voice, sonification and vibration. Researchers 0have proposed various solutions for conveying feedback messages to blind people using these mediums. Voice and sonification feedback are effective solutions to convey information. However, these solutions are not applicable in a noisy environment and may occupy the most important auditory sense. The privacy of a blind user can also be compromised with …

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A Novel Tunicate Swarm Algorithm With Hybrid Deep Learning Enabled Attack Detection For Secure Iot Environment, Fatma Taher, Mohamed Elhoseny, Mohammed K. Hassan, Ibrahim M. El-Hasnony Jan 2022

A Novel Tunicate Swarm Algorithm With Hybrid Deep Learning Enabled Attack Detection For Secure Iot Environment, Fatma Taher, Mohamed Elhoseny, Mohammed K. Hassan, Ibrahim M. El-Hasnony

All Works

No abstract provided.

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Conceptualising The Role Of The Uae Innovation Strategy In University-Industry Knowledge Diffusion Process, Mousa Al-Kfairy, Munir Majdalawieh, Saed Alrabaee Jan 2022

Conceptualising The Role Of The Uae Innovation Strategy In University-Industry Knowledge Diffusion Process, Mousa Al-Kfairy, Munir Majdalawieh, Saed Alrabaee

All Works

Universities are considered one of the primary sources of knowledge and an essential component of the triple helix theory. They fuel the industries with the required expertise and pool of resources to operate efficiently. Moreover, entrepreneurial universities successfully contributed to regional development and employment growth by supporting entrepreneurial activities and incubation programmes. Thus, university-industry collaboration is vital for enhancing knowledge-based industries' knowledge diffusion as well as the regional innovation atmospheres. On the other hand, countries and regional authorities strive to stimulate their regional development by encouraging innovation and entrepreneurship activities. For example, the UAE announced its 2015 innovation strategy that …

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Exploring Algorithmic Literacy For College Students: An Educator’S Roadmap, Susan Gardner Archambault Jan 2022

Exploring Algorithmic Literacy For College Students: An Educator’S Roadmap, Susan Gardner Archambault

LMU Theses and Dissertations

Research shows that college students are largely unaware of the impact of algorithms on their everyday lives. Also, most university students are not being taught about algorithms as part of the regular curriculum. This exploratory, qualitative study aimed to explore subject-matter experts’ insights and perceptions of the knowledge components, coping behaviors, and pedagogical considerations to aid faculty in teaching algorithmic literacy to college students. Eleven individual, semi-structured interviews and one focus group were conducted with scholars and teachers of critical algorithm studies and related fields. Findings suggested three sets of knowledge components that would contribute to students’ algorithmic literacy: general …

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Detection Of Overlapping Passive Manipulation Techniques In Image Forensics, Gianna S. Lint, Umit Karabiyik Jan 2022

Detection Of Overlapping Passive Manipulation Techniques In Image Forensics, Gianna S. Lint, Umit Karabiyik

Annual ADFSL Conference on Digital Forensics, Security and Law

With a growing number of images uploaded daily to social media sites, it is essential to understand if an image can be used to trace its origin. Forensic investigations are focusing on analyzing images that are uploaded to social media sites resulting in an emphasis on building and validating tools. There has been a strong focus on understanding active manipulation or tampering techniques and building tools for analysis. However, research on manipulation is often studied in a vacuum, involving only one technique at a time. Additionally, less focus has been placed on passive manipulation, which can occur by simply uploading …

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Interpretable Design Of Reservoir Computing Networks Using Realization Theory, Wei Miao, Vignesh Narayanan, Jr-Shin Li Jan 2022

Interpretable Design Of Reservoir Computing Networks Using Realization Theory, Wei Miao, Vignesh Narayanan, Jr-Shin Li

Publications

The reservoir computing networks (RCNs) have been successfully employed as a tool in learning and complex decision-making tasks. Despite their efficiency and low training cost, practical applications of RCNs rely heavily on empirical design. In this article, we develop an algorithm to design RCNs using the realization theory of linear dynamical systems. In particular, we introduce the notion of α-stable realization and provide an efficient approach to prune the size of a linear RCN without deteriorating the training accuracy. Furthermore, we derive a necessary and sufficient condition on the irreducibility of the number of hidden nodes in linear RCNs based …

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Deeppose: Detecting Gps Spoofing Attack Via Deep Recurrent Neural Network, Peng Jiang, Hongyi Wu, Chunsheng Xin Jan 2022

Deeppose: Detecting Gps Spoofing Attack Via Deep Recurrent Neural Network, Peng Jiang, Hongyi Wu, Chunsheng Xin

Electrical & Computer Engineering Faculty Publications

The Global Positioning System (GPS) has become a foundation for most location-based services and navigation systems, such as autonomous vehicles, drones, ships, and wearable devices. However, it is a challenge to verify if the reported geographic locations are valid due to various GPS spoofing tools. Pervasive tools, such as Fake GPS, Lockito, and software-defined radio, enable ordinary users to hijack and report fake GPS coordinates and cheat the monitoring server without being detected. Furthermore, it is also a challenge to get accurate sensor readings on mobile devices because of the high noise level introduced by commercial motion sensors. To this …

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Deep Learning Based Superconducting Radio-Frequency Cavity Fault Classification At Jefferson Laboratory, Lasitha Vidyaratne, Adam Carpenter, Tom Powers, Chris Tennant, Khan M. Iftekharuddin, Md. Monibor Rahman, Anna S. Shabalina Jan 2022

Deep Learning Based Superconducting Radio-Frequency Cavity Fault Classification At Jefferson Laboratory, Lasitha Vidyaratne, Adam Carpenter, Tom Powers, Chris Tennant, Khan M. Iftekharuddin, Md. Monibor Rahman, Anna S. Shabalina

Electrical & Computer Engineering Faculty Publications

This work investigates the efficacy of deep learning (DL) for classifying C100 superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. CEBAF is a large, high-power continuous wave recirculating linac that utilizes 418 SRF cavities to accelerate electrons up to 12 GeV. Recent upgrades to CEBAF include installation of 11 new cryomodules (88 cavities) equipped with a low-level RF system that records RF time-series data from each cavity at the onset of an RF failure. Typically, subject matter experts (SME) analyze this data to determine the fault type and identify the cavity of …

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Bitcoin Selfish Mining Modeling And Dependability Analysis, Chencheng Zhou, Liudong Xing, Jun Guo, Qisi Liu Jan 2022

Bitcoin Selfish Mining Modeling And Dependability Analysis, Chencheng Zhou, Liudong Xing, Jun Guo, Qisi Liu

Electrical & Computer Engineering Faculty Publications

Blockchain technology has gained prominence over the last decade. Numerous achievements have been made regarding how this technology can be utilized in different aspects of the industry, market, and governmental departments. Due to the safety-critical and security-critical nature of their uses, it is pivotal to model the dependability of blockchain-based systems. In this study, we focus on Bitcoin, a blockchain-based peer-to-peer cryptocurrency system. A continuous-time Markov chain-based analytical method is put forward to model and quantify the dependability of the Bitcoin system under selfish mining attacks. Numerical results are provided to examine the influences of several key parameters related to …

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Artificial Intelligence And Machine Learning In Optical Information Processing: Introduction To The Feature Issue, Khan Iftekharuddin, Chrysanthe Preza, Abdul Ahad S. Awwal, Michael E. Zelinski Jan 2022

Artificial Intelligence And Machine Learning In Optical Information Processing: Introduction To The Feature Issue, Khan Iftekharuddin, Chrysanthe Preza, Abdul Ahad S. Awwal, Michael E. Zelinski

Electrical & Computer Engineering Faculty Publications

This special feature issue covers the intersection of topical areas in artificial intelligence (AI)/machine learning (ML) and optics. The papers broadly span the current state-of-the-art advances in areas including image recognition, signal and image processing, machine inspection/vision and automotive as well as areas of traditional optical sensing, interferometry and imaging.

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"Mystify": A Proactive Moving-Target Defense For A Resilient Sdn Controller In Software Defined Cps, Mohamed Azab, Mohamed Samir, Effat Samir Jan 2022

"Mystify": A Proactive Moving-Target Defense For A Resilient Sdn Controller In Software Defined Cps, Mohamed Azab, Mohamed Samir, Effat Samir

Electrical & Computer Engineering Faculty Publications

The recent devastating mission Cyber–Physical System (CPS) attacks, failures, and the desperate need to scale and to dynamically adapt to changes, revolutionized traditional CPS to what we name as Software Defined CPS (SD-CPS). SD-CPS embraces the concept of Software Defined (SD) everything where CPS infrastructure is more elastic, dynamically adaptable and online-programmable. However, in SD-CPS, the threat became more immanent, as the long-been physically-protected assets are now programmatically accessible to cyber attackers. In SD-CPSs, a network failure hinders the entire functionality of the system. In this paper, we present MystifY, a spatiotemporal runtime diversification for Moving-Target Defense (MTD) to secure …

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A Channel State Information Based Virtual Mac Spoofing Detector, Peng Jiang, Hongyi Wu, Chunsheng Xin Jan 2022

A Channel State Information Based Virtual Mac Spoofing Detector, Peng Jiang, Hongyi Wu, Chunsheng Xin

Electrical & Computer Engineering Faculty Publications

Physical layer security has attracted lots of attention with the expansion of wireless devices to the edge networks in recent years. Due to limited authentication mechanisms, MAC spoofing attack, also known as the identity attack, threatens wireless systems. In this paper, we study a new type of MAC spoofing attack, the virtual MAC spoofing attack, in a tight environment with strong spatial similarities, which can create multiple counterfeits entities powered by the virtualization technologies to interrupt regular services. We develop a system to effectively detect such virtual MAC spoofing attacks via the deep learning method as a countermeasure. …

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Runtime Power Allocation Based On Multi-Gpu Utilization In Gamess, Masha Sosonkina, Vaibhav Sundriyal, Jorge Luis Galvez Vallejo Jan 2022

Runtime Power Allocation Based On Multi-Gpu Utilization In Gamess, Masha Sosonkina, Vaibhav Sundriyal, Jorge Luis Galvez Vallejo

Electrical & Computer Engineering Faculty Publications

To improve the power consumption of parallel applications at the runtime, modern processors provide frequency scaling and power limiting capabilities. In this work, a runtime strategy is proposed to maximize performance under a given power budget by distributing the available power according to the relative GPU utilization. Time series forecasting methods were used to develop workload prediction models that provide accurate prediction of GPU utilization during application execution. Experiments were performed on a multi-GPU computing platform DGX-1 equipped with eight NVIDIA V100 GPUs used for quantum chemistry calculations in the GAMESS package. For a limited power budget, the proposed strategy …

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Arithfusion: An Arithmetic Deep Model For Temporal Remote Sensing Image Fusion, Md Reshad Ul Hoque, Jian Wu, Chiman Kwan, Krzysztof Koperski, Jiang Li Jan 2022

Arithfusion: An Arithmetic Deep Model For Temporal Remote Sensing Image Fusion, Md Reshad Ul Hoque, Jian Wu, Chiman Kwan, Krzysztof Koperski, Jiang Li

Electrical & Computer Engineering Faculty Publications

Different satellite images may consist of variable numbers of channels which have different resolutions, and each satellite has a unique revisit period. For example, the Landsat-8 satellite images have 30 m resolution in their multispectral channels, the Sentinel-2 satellite images have 10 m resolution in the pan-sharp channel, and the National Agriculture Imagery Program (NAIP) aerial images have 1 m resolution. In this study, we propose a simple yet effective arithmetic deep model for multimodal temporal remote sensing image fusion. The proposed model takes both low- and high-resolution remote sensing images at t1 together with low-resolution images at a …

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Facial Landmark Feature Fusion In Transfer Learning Of Child Facial Expressions, Megan A. Witherow, Manar D. Samad, Norou Diawara, Khan M. Iftekharuddin Jan 2022

Facial Landmark Feature Fusion In Transfer Learning Of Child Facial Expressions, Megan A. Witherow, Manar D. Samad, Norou Diawara, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Automatic classification of child facial expressions is challenging due to the scarcity of image samples with annotations. Transfer learning of deep convolutional neural networks (CNNs), pretrained on adult facial expressions, can be effectively finetuned for child facial expression classification using limited facial images of children. Recent work inspired by facial age estimation and age-invariant face recognition proposes a fusion of facial landmark features with deep representation learning to augment facial expression classification performance. We hypothesize that deep transfer learning of child facial expressions may also benefit from fusing facial landmark features. Our proposed model architecture integrates two input branches: a …

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Srf Cavity Fault Classification And Prediction At Jefferson Lab, Chris Tennant, Adam Carpenter, Lasitha Vidyaratne, Md. Monibor Rahman, Khan Iftekharuddin Jan 2022

Srf Cavity Fault Classification And Prediction At Jefferson Lab, Chris Tennant, Adam Carpenter, Lasitha Vidyaratne, Md. Monibor Rahman, Khan Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Over the last few years several machine learning projects at Jefferson Lab have had a common focus to optimize operation of superconducting RF (SRF) cavities in the Continuous Electron Beam Accelerator Facility (CEBAF). In this talk we highlight work to identify and classify types of faults from C100-type cavities and then to extend those capabilities to provide real-time fault prediction. Early prediction may enable mitigation strategies to prevent some types of faults. In our approach we apply a two-step fault prediction pipeline. In the first step, a model distinguishes between faulty and normal signals. In the second step, signals flagged …

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Performance Evaluation Of Different Raspberry Pi Models For A Broad Spectrum Of Interests, Eric Gamess, Sergio Hernandez Jan 2022

Performance Evaluation Of Different Raspberry Pi Models For A Broad Spectrum Of Interests, Eric Gamess, Sergio Hernandez

Research, Publications & Creative Work

Now-a-days, Single Board Computers (SBCs), especially Raspberry Pi (RPi) devices, are extensively used due to their low cost, efficient use of energy, and successful implementation in a wide range of applications; therefore, evaluating their performance is critical to better understand the applicability of RPis to solve problems in different areas of knowledge. This paper describes a comparative and experimental study regarding the performance of five different models of the RPi family (RPi Zero W, RPi Zero 2 W, RPi 3B, RPi 3B+, and RPi 4B) in several scenarios and with different configurations. To conduct our multiple experiments on RPis, we …

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Effect Of Connection State & Transport/Application Protocol On The Machine Learning Outlier Detection Of Network Intrusions, George Yuchi, Torrey J. Wagner, Paul Auclair, Brent T. Langhals Jan 2022

Effect Of Connection State & Transport/Application Protocol On The Machine Learning Outlier Detection Of Network Intrusions, George Yuchi, Torrey J. Wagner, Paul Auclair, Brent T. Langhals

Faculty Publications

The majority of cyber infiltration & exfiltration intrusions leave a network footprint, and due to the multi-faceted nature of detecting network intrusions, it is often difficult to detect. In this work a Zeek-processed PCAP dataset containing the metadata of 36,667 network packets was modeled with several machine learning algorithms to classify normal vs. anomalous network activity. Principal component analysis with a 10% contamination factor was used to identify anomalous behavior. Models were created using recursive feature elimination on logistic regression and XGBClassifier algorithms, and also using Bayesian and bandit optimization of neural network hyperparameters. These models were trained on a …

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Application Of Artificial Intelligence To Plasma Metabolomics Profiles To Predict Response To Neoadjuvant Chemotherapy In Triple-Negative Breast Cancer, Ehsan Irajizad, Ranran Wu, Jody Vykoukal, Eunice Murage, Rachelle Spencer, Jennifer B Dennison, Stacy Moulder, Elizabeth Ravenberg, Bora Lim, Jennifer Litton, Debu Tripathym, Vicente Valero, Senthil Damodaran, Gaiane M Rauch, Beatriz Adrada, Rosalind Candelaria, Jason B White, Abenaa Brewster, Banu Arun, James P Long, Kim Anh Do, Sam Hanash, Johannes F Fahrmann Jan 2022

Application Of Artificial Intelligence To Plasma Metabolomics Profiles To Predict Response To Neoadjuvant Chemotherapy In Triple-Negative Breast Cancer, Ehsan Irajizad, Ranran Wu, Jody Vykoukal, Eunice Murage, Rachelle Spencer, Jennifer B Dennison, Stacy Moulder, Elizabeth Ravenberg, Bora Lim, Jennifer Litton, Debu Tripathym, Vicente Valero, Senthil Damodaran, Gaiane M Rauch, Beatriz Adrada, Rosalind Candelaria, Jason B White, Abenaa Brewster, Banu Arun, James P Long, Kim Anh Do, Sam Hanash, Johannes F Fahrmann

Faculty, Staff and Student Publications

There is a need to identify biomarkers predictive of response to neoadjuvant chemotherapy (NACT) in triple-negative breast cancer (TNBC). We previously obtained evidence that a polyamine signature in the blood is associated with TNBC development and progression. In this study, we evaluated whether plasma polyamines and other metabolites may identify TNBC patients who are less likely to respond to NACT. Pre-treatment plasma levels of acetylated polyamines were elevated in TNBC patients that had moderate to extensive tumor burden (RCB-II/III) following NACT compared to those that achieved a complete pathological response (pCR/RCB-0) or had minimal residual disease (RCB-I). We further applied …

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คลังข้อมูลและระบบสนับสนุนการตัดสินใจของผู้พัฒนาอสังหาริมทรัพย์รายย่อยในพื้นที่กรุงเทพมหานคร, เศรษฐ์พสุ จงพสุภิญโญ Jan 2022

คลังข้อมูลและระบบสนับสนุนการตัดสินใจของผู้พัฒนาอสังหาริมทรัพย์รายย่อยในพื้นที่กรุงเทพมหานคร, เศรษฐ์พสุ จงพสุภิญโญ

Chulalongkorn University Theses and Dissertations (Chula ETD)

ปัจจุบันการแข่งขันในธุรกิจอสังหาริมทรัพย์มีแนวโน้มที่สูงขึ้นอันเป็นผลมาจากวิกฤตการแพร่ระบาดของโควิด 19 ที่ทำให้ความต้องการซื้อลดลงไม่ว่าจะเป็นผลกระทบจากการปิดเมือง การปิดประเทศรวมทั้งยังส่งผลให้ผู้บริโภคบางกลุ่มมีพฤติกรรมการบริโภคและความต้องการที่เปลี่ยนแปลงไปอย่างรวดเร็วจากผลกระทบในครั้งนี้ ส่งผลให้ผู้ประกอบการจำเป็นต้องปรับตัวตามให้ทันไม่ว่าจะเป็นในเรื่องของการออกแบบโครงการให้ตอบโจทย์มากยิ่งขึ้น การหาจุดขายใหม่ ๆ เพื่อให้ตอบสนองต่อความต้องการของผู้บริโภคให้ได้มากที่สุดรวมไปถึงการกำหนดกลยุทธ์และแนวทางการพัฒนาโครงการให้มีประสิทธิภาพและทำให้บริษัทสามารถเติบโตต่อไปได้อย่างยั่งยืน โครงการ “คลังข้อมูลและระบบสนับสนุนการตัดสินใจของผู้พัฒนาอสังหาริมทรัพย์รายย่อยในพื้นที่กรุงเทพมหานคร” นี้ประกอบด้วย 5 ระบบหลัก ได้แก่ ระบบวิเคราะห์ภาพรวมของธุรกิจอสังหาริมทรัพย์ ระบบวิเคราะห์คู่แข่ง ระบบวิเคราะห์ตัวเลขและอัตราส่วนทางการเงินย้อนหลังของบริษัท ระบบวิเคราะห์ภาพรวมในแต่ละโครงการของบริษัท และระบบวิเคราะห์ลูกค้า ระบบได้พัฒนาขึ้นบนระบบจัดการฐานข้อมูล Microsoft SQL Server for Mac และใช้เครื่องมือต่าง ๆ ของชุดโปรแกรม Tableau Desktop ระบบที่พัฒนาขึ้นนี้จะช่วยให้ผู้บริหารสามารถวิเคราะห์ข้อมูลในมุมมองต่าง ๆ ได้อย่างถูกต้องและรวดเร็ว เพื่อนำไปใช้ประกอบการตัดสินใจที่ก่อให้เกิดประโยชน์กับการดำเนินธุรกิจ และสร้างความได้เปรียบทางการแข่งขันในธุรกิจ

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การใช้การคิดเชิงออกแบบเพื่อพัฒนาเว็บแอปพลิเคชันของธุรกิจสั่งพิมพ์ตามความต้องการ, เกวลี วุฒิอุดม Jan 2022

การใช้การคิดเชิงออกแบบเพื่อพัฒนาเว็บแอปพลิเคชันของธุรกิจสั่งพิมพ์ตามความต้องการ, เกวลี วุฒิอุดม

Chulalongkorn University Theses and Dissertations (Chula ETD)

การสกรีนถือเป็นการพิมพ์รูปแบบหนึ่งที่มีประวัติความเป็นมาที่ยาวนาน ซึ่งในปัจจุบันได้รับความนิยมเพิ่มขึ้นอย่างแพร่หลาย นอกจากนี้เทคนิคการพิมพ์ยังพัฒนาขึ้นอย่างมาก มีการพิมพ์หลากหลายวิธีและไม่เพียงแค่พิมพ์ลงบนวัสดุที่เป็นเนื้อผ้าอย่างเดียว แต่ยังสามารถพิมพ์ลงบนวัสดุประเภทอื่น ๆ เช่น แก้ว โลหะ และเซรามิก เป็นต้น ทำให้ธุรกิจการสกรีนเติบโตขึ้น ไม่ได้จำกัดแค่การสกรีนเสื้อเพียงอย่างเดียว และในยุคดิจิทัล เทคโนโลยีได้พัฒนาอย่างก้าวกระโดด เกือบทุกธุรกิจต้องเข้าสู่การค้าขายออนไลน์ ธุรกิจการพิมพ์ก็ต้องปรับตัวโดยเพิ่มช่องทางการขายออนไลน์เช่นกัน ท่ามกลางการแข่งขันอย่างดุเดือดของธุรกิจการพิมพ์ การสร้างความแตกต่างให้กับธุรกิจเป็นสิ่งที่สำคัญยิ่ง ในขณะเดียวกันวัยรุ่นในสมัยนี้มักนิยมแต่งกายและใช้ข้าวของเครื่องใช้ที่บ่งบอกถึงไลฟ์สไตล์และเอกลักษณ์ของตนเอง ทำให้มีศิลปินที่ผลิตสินค้าลวดลายศิลปะต่าง ๆ ออกมาขายเพิ่มมากขึ้น ดังนั้นจึงเกิดการนำแนวทางการคิดเชิงออกแบบมาประยุกต์ใช้กับธุรกิจสั่งพิมพ์ตามความต้องการร่วมกับศิลปินที่สร้างสรรค์งานศิลปะดิจิทัล เพื่อสร้างความแตกต่างให้กับธุรกิจ ระบบต้นแบบที่ได้จากโครงการนี้จะช่วยให้การดำเนินการของธุรกิจสั่งพิมพ์ตามความต้องการสามารถดำเนินการได้อย่างมีประสิทธิภาพมากยิ่งขึ้น ผ่านการออกแบบที่ช่วยแก้ไขปัญหาเดิมในอดีตและสามารถตอบโจทย์ผู้ใช้งานได้จริง

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การพัฒนาระบบแชตบอตสำหรับธุรกิจจำหน่ายบรรจุภัณฑ์ไปรษณีย์, เสริมศิริ นวลิขิต Jan 2022

การพัฒนาระบบแชตบอตสำหรับธุรกิจจำหน่ายบรรจุภัณฑ์ไปรษณีย์, เสริมศิริ นวลิขิต

Chulalongkorn University Theses and Dissertations (Chula ETD)

ในปัจจุบัน เทคโนโลยีสารสนเทศได้เข้ามามีบทบาทในชีวิตประจำวันของผู้บริโภคเป็นอย่างมาก ผู้บริโภคสามารถเข้าถึงข้อมูลและทำธุรกรรมออนไลน์สะดวกรวดเร็ว ทำให้ธุรกิจประเภทพาณิชย์อิเล็กทรอนิกส์ (Electronic Commerce หรือ e-Commerce) มีอัตราการเติบโตที่สูงขึ้น ส่งผลให้ความต้องการบรรจุภัณฑ์ไปรษณีย์เติบโตตามไปด้วย ในช่วงเวลาที่ผ่านมา เทคโนโลยีแชตบอตเข้ามามีบทบาทสำคัญให้กับธุรกิจในด้านการให้บริการอัตโนมัติด้วยภาษาที่ใกล้เคียงกับภาษาธรรมชาติภายใต้แพลตฟอร์มที่ใช้กันทั่วไปและไม่ถูกจำกัดด้วยสถานที่หรือเวลาบริการ โครงการ “การพัฒนาระบบแชตบอตสำหรับธุรกิจจำหน่ายบรรจุภัณฑ์ไปรษณีย์” ที่พัฒนาขึ้นนี้ประกอบด้วย 5 ระบบ ได้แก่ (1) ระบบแชตบอตสำหรับแนะนำสินค้า (2) ระบบแชตบอตสำหรับประมวลผลคำสั่งซื้อ (3) ระบบแชตบอตสำหรับการสนับสนุนลูกค้า (4) ระบบแชตบอตสำหรับตอบคำถามที่พบบ่อย และ (5) ระบบวิเคราะห์การใช้งานแชตบอต โดยระบบแชตบอตถูกพัฒนาขึ้นด้วยโปรแกรม Dialogflow และ LINE Messaging API ส่วนระบบวิเคราะห์ข้อมูลถูกพัฒนาขึ้นด้วยโปรแกรม Microsoft Power BI 2.110 ร่วมกับระบบจัดการฐานข้อมูล Microsoft SQL Server 2019 ระบบสารสนเทศจากโครงการพิเศษนี้จะช่วยเพิ่มศักยภาพการให้บริการของธุรกิจ และสร้างประสบการณ์การรับบริการในรูปแบบใหม่ให้กับลูกค้า รวมถึงสามารถนำข้อมูลที่ได้จากการให้บริการมาวิเคราะห์เพื่อนำไปปรับปรุงและเพิ่มประสิทธิภาพให้กับระบบเพื่อสร้างความได้เปรียบในการแข่งขันให้กับธุรกิจ

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