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Articles 37201 - 37230 of 302503

Full-Text Articles in Physical Sciences and Mathematics

Partnering For Value Perfection And Business Sustainability In The Cloud Services Brokerage Market, Richard Shang, Robert John Kauffman Jan 2022

Partnering For Value Perfection And Business Sustainability In The Cloud Services Brokerage Market, Richard Shang, Robert John Kauffman

Research Collection School Of Computing and Information Systems

The cloud computing and services market has advanced in the past ten years. They now include most IT services from fundamental computing to cutting-edge AI capabilities. With the widespread adoption of cloud services, clients are facing the fact that they are utilizing cloud resources at a sub-optimal level. Cloud services brokers (CSBs) grew from the market to fill the needs for cloud resource management and risk mitigation. Based on analysis of the cloud market and the case of cloud services brokerage and related activities in North America, we offer theoretical analysis for how value creation works, its impacts on the …

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An Exploratory Study On The Repeatedly Shared External Links On Stack Overflow, Jiakun Liu, Haoxiang Zhang, Xin Xia, David Lo, Ying Zou, Ahmed E. Hassan, Shanping Li Jan 2022

An Exploratory Study On The Repeatedly Shared External Links On Stack Overflow, Jiakun Liu, Haoxiang Zhang, Xin Xia, David Lo, Ying Zou, Ahmed E. Hassan, Shanping Li

Research Collection School Of Computing and Information Systems

On Stack Overflow, users reuse 11,926,354 external links to share the resources hosted outside the Stack Overflow website. The external links connect to the existing programming-related knowledge and extend the crowdsourced knowledge on Stack Overflow. Some of the external links, so-called as repeated external links, can be shared for multiple times. We observe that 82.5% of the link sharing activities (i.e., sharing links in any question, answer, or comment) on Stack Overflow share external resources, and 57.0% of the occurrences of the external links are sharing the repeated external links. However, it is still unclear what types of external resources …

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Authenticated Data Redaction With Accountability And Transparency, Jinhua Ma, Xinyi Huang, Yi Mu, Robert H. Deng Jan 2022

Authenticated Data Redaction With Accountability And Transparency, Jinhua Ma, Xinyi Huang, Yi Mu, Robert H. Deng

Research Collection School Of Computing and Information Systems

A common practice in data redaction is removing sensitive information prior to data publication or release. In data-driven applications, one must be convinced that the redacted data is still trustworthy. Meanwhile, the data redactor must be held accountable for (malicious) redaction, which could change/hide the meaning of the original data. Motivated by these concerns, we present a novel solution for authenticated data redaction based on a new Redactable Signature Scheme with Implicit Accountability (RSS - IA). In the event of a dispute, not only the original data signer but also the redactor can generate an evidence tag to unequivocally identify …

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Defining Smart Contract Defects On Ethereum, Jiachi Chen, Xin Xia, David Lo, John Grundy, Xiapu Luo, Ting Chen Jan 2022

Defining Smart Contract Defects On Ethereum, Jiachi Chen, Xin Xia, David Lo, John Grundy, Xiapu Luo, Ting Chen

Research Collection School Of Computing and Information Systems

Smart contracts are programs running on a blockchain. They are immutable to change, and hence can not be patched for bugs once deployed. Thus it is critical to ensure they are bug-free and well-designed before deployment. A Contract defect is an error, flaw or fault in a smart contract that causes it to produce an incorrect or unexpected result, or to behave in unintended ways. The detection of contract defects is a method to avoid potential bugs and improve the design of existing code. Since smart contracts contain numerous distinctive features, such as the gas system. decentralized, it is important …

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Perceptions And Needs Of Artificial Intelligence In Health Care To Increase Adoption: Scoping Review, Han Shi Jocelyn Chew, Palakorn Achananuparp Jan 2022

Perceptions And Needs Of Artificial Intelligence In Health Care To Increase Adoption: Scoping Review, Han Shi Jocelyn Chew, Palakorn Achananuparp

Research Collection School Of Computing and Information Systems

Background: Artificial intelligence (AI) has the potential to improve the efficiency and effectiveness of health care service delivery. However, the perceptions and needs of such systems remain elusive, hindering efforts to promote AI adoption in health care. Objective: This study aims to provide an overview of the perceptions and needs of AI to increase its adoption in health care. Methods: A systematic scoping review was conducted according to the 5-stage framework by Arksey and O’Malley. Articles that described the perceptions and needs of AI in health care were searched across nine databases: ACM Library, CINAHL, Cochrane Central, Embase, IEEE Xplore, …

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Enjoy Your Observability: An Industrial Survey Of Microservice Tracing And Analysis, Bowen Li, Xin Peng, Qilin Xiang, Hanzhang Wang, Tao Xie, Jun Sun, Xuanzhe Liu Jan 2022

Enjoy Your Observability: An Industrial Survey Of Microservice Tracing And Analysis, Bowen Li, Xin Peng, Qilin Xiang, Hanzhang Wang, Tao Xie, Jun Sun, Xuanzhe Liu

Research Collection School Of Computing and Information Systems

Microservice systems are often deployed in complex cloud-based environments and may involve a large number of service instances being dynamically created and destroyed. It is thus essential to ensure observability to understand these microservice systems’ behaviors and troubleshoot their problems. As an important means to achieve the observability, distributed tracing and analysis is known to be challenging. While many companies have started implementing distributed tracing and analysis for microservice systems, it is not clear whether existing approaches fulfill the required observability. In this article, we present our industrial survey on microservice tracing and analysis through interviewing developers and operation engineers …

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A Quantum Interpretation Of Separating Conjunction For Local Reasoning Of Quantum Programs Based On Separation Logic, Xuan Bach Le, Shang-Wei Lin, Jun Sun, David Sanan Jan 2022

A Quantum Interpretation Of Separating Conjunction For Local Reasoning Of Quantum Programs Based On Separation Logic, Xuan Bach Le, Shang-Wei Lin, Jun Sun, David Sanan

Research Collection School Of Computing and Information Systems

It is well-known that quantum programs are not only complicated to design but also challenging to verify because the quantum states can have exponential size and require sophisticated mathematics to encode and manipulate. To tackle the state-space explosion problem for quantum reasoning, we propose a Hoare-style inference framework that supports local reasoning for quantum programs. By providing a quantum interpretation of the separating conjunction, we are able to infuse separation logic into our framework and apply local reasoning using a quantum frame rule that is similar to the classical frame rule. For evaluation, we apply our framework to verify various …

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Approximate K-Nn Graph Construction: A Generic Online Approach, Wan-Lei Zhao, Hui Wang, Chong-Wah Ngo Jan 2022

Approximate K-Nn Graph Construction: A Generic Online Approach, Wan-Lei Zhao, Hui Wang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Nearest neighbor search and k-nearest neighbor graph construction are two fundamental issues that arise from many disciplines such as multimedia information retrieval, data-mining, and machine learning. They become more and more imminent given the big data emerge in various fields in recent years. In this paper, a simple but effective solution both for approximate k-nearest neighbor search and approximate k-nearest neighbor graph construction is presented. These two issues are addressed jointly in our solution. On one hand, the approximate k-nearest neighbor graph construction is treated as a search task. Each sample along with its k-nearest neighbors is joined into the …

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Learning From Web Recipe-Image Pairs For Food Recognition: Problem, Baselines And Performance, Bin Zhu, Chong-Wah Ngo, Wing-Kwong Chan Jan 2022

Learning From Web Recipe-Image Pairs For Food Recognition: Problem, Baselines And Performance, Bin Zhu, Chong-Wah Ngo, Wing-Kwong Chan

Research Collection School Of Computing and Information Systems

Cross-modal recipe retrieval has recently been explored for food recognition and understanding. Text-rich recipe provides not only visual content information (e.g., ingredients, dish presentation) but also procedure of food preparation (cutting and cooking styles). The paired data is leveraged to train deep models to retrieve recipes for food images. Most recipes on the Web include sample pictures as the references. The paired multimedia data is not noise-free, due to errors such as pairing of images containing partially prepared dishes with recipes. The content of recipes and food images are not always consistent due to free-style writing and preparation of food …

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Lightweight And Expressive Fine-Grained Access Control For Healthcare Internet-Of-Things, Shengmin Xu, Yingjiu Li, Robert H. Deng, Yinghui Zhang, Xiangyang Luo, Ximeng Liu Jan 2022

Lightweight And Expressive Fine-Grained Access Control For Healthcare Internet-Of-Things, Shengmin Xu, Yingjiu Li, Robert H. Deng, Yinghui Zhang, Xiangyang Luo, Ximeng Liu

Research Collection School Of Computing and Information Systems

Healthcare Internet-of-Things (IoT) is an emerging paradigm that enables embedded devices to monitor patients vital signals and allows these data to be aggregated and outsourced to the cloud. The cloud enables authorized users to store and share data to enjoy on-demand services. Nevertheless, it also causes many security concerns because of the untrusted network environment, dishonest cloud service providers and resource-limited devices. To preserve patients' privacy, existing solutions usually apply cryptographic tools to offer access controls. However, fine-grained access control among authorized users is still a challenge, especially for lightweight and resource-limited end-devices. In this paper, we propose a novel …

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A Blockchain-Based Self-Tallying Voting Protocol In Decentralized Iot, Yannan Li, Willy Susilo, Guomin Yang, Yong Yu, Dongxi Liu, Xiaojiang Du, Mohsen Guizani Jan 2022

A Blockchain-Based Self-Tallying Voting Protocol In Decentralized Iot, Yannan Li, Willy Susilo, Guomin Yang, Yong Yu, Dongxi Liu, Xiaojiang Du, Mohsen Guizani

Research Collection School Of Computing and Information Systems

The Internet of Things (IoT) is experiencing explosive growth and has gained extensive attention from academia and industry in recent years. However, most of the existing IoT infrastructures are centralized, which may cause the issues of unscalability and single-point-of-failure. Consequently, decentralized IoT has been proposed by taking advantage of the emerging technology called blockchain. Voting systems are widely adopted in IoT, for example a leader election in wireless sensor networks. Self-tallying voting systems are alternatives to unsuitable, traditional centralized voting systems in decentralized IoT. Unfortunately, self-tallying voting systems inherently suffer from fairness issues, such as adaptive and abortive issues caused …

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Delta Debugging Microservice Systems With Parallel Optimization, Xiang Zhou, Xin Peng, Tao Xie, Jun Sun, Chao Ji, Wenha Li, Dan Ding Jan 2022

Delta Debugging Microservice Systems With Parallel Optimization, Xiang Zhou, Xin Peng, Tao Xie, Jun Sun, Chao Ji, Wenha Li, Dan Ding

Research Collection School Of Computing and Information Systems

Microservice systems are complicated due to their runtime environments and service communications. Debugging a failure involves the deployment and manipulation of microservice systems on a containerized environment and faces unique challenges due to the high complexity and dynamism of microservices. To address these challenges, we propose a debugging approach for microservice systems based on the delta debugging algorithm, which is to minimize failure-inducing deltas of circumstances (e.g., deployment, environmental configurations). Our approach includes novel techniques for defining, deploying/manipulating, and executing deltas during delta debugging. In particular, to construct a (failing) circumstance space for delta debugging to minimize, our approach defines …

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Cross-Modal Food Retrieval: Learning A Joint Embedding Of Food Images And Recipes With Semantic Consistency And Attention Mechanism, Hao Wang, Doyen Sahoo, Chenghao Liu, Ke Shu, Palakorn Achananuparp, Ee-Peng Lim, Steven C. H. Hoi Jan 2022

Cross-Modal Food Retrieval: Learning A Joint Embedding Of Food Images And Recipes With Semantic Consistency And Attention Mechanism, Hao Wang, Doyen Sahoo, Chenghao Liu, Ke Shu, Palakorn Achananuparp, Ee-Peng Lim, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Food retrieval is an important task to perform analysis of food-related information, where we are interested in retrieving relevant information about the queried food item such as ingredients, cooking instructions, etc. In this paper, we investigate cross-modal retrieval between food images and cooking recipes. The goal is to learn an embedding of images and recipes in a common feature space, such that the corresponding image-recipe embeddings lie close to one another. Two major challenges in addressing this problem are 1) large intra-variance and small inter-variance across cross-modal food data; and 2) difficulties in obtaining discriminative recipe representations. To address these …

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"More Than Deep Learning": Post-Processing For Api Sequence Recommendation, Chi Chen, Xin Peng, Bihuan Chen, Jun Sun, Zhenchang Xing, Xin Wang, Wenyun Zhao Jan 2022

"More Than Deep Learning": Post-Processing For Api Sequence Recommendation, Chi Chen, Xin Peng, Bihuan Chen, Jun Sun, Zhenchang Xing, Xin Wang, Wenyun Zhao

Research Collection School Of Computing and Information Systems

In the daily development process, developers often need assistance in finding a sequence of APIs to accomplish their development tasks. Existing deep learning models, which have recently been developed for recommending one single API, can be adapted by using encoder-decoder models together with beam search to generate API sequence recommendations. However, the generated API sequence recommendations heavily rely on the probabilities of API suggestions at each decoding step, which do not take into account other domain-specific factors (e.g., whether an API suggestion satisfies the program syntax and how diverse the API sequence recommendations are). Moreover, it is difficult for developers …

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Lessons Learnt Conducting Capture The Flag Cybersecurity Competition During Covid-19, Kee Hock Tan, Eng Lieh Ouh Jan 2022

Lessons Learnt Conducting Capture The Flag Cybersecurity Competition During Covid-19, Kee Hock Tan, Eng Lieh Ouh

Research Collection School Of Computing and Information Systems

This innovative practice full paper describes our experiences conducting cybersecurity capture the flag (CTF) competition for cybersecurity enthusiast participants (inclusive of both tertiary students and working professionals) local and abroad during the COVID-19 pandemic. Learning and appreciation of cybersecurity concepts for our participants with little to no technical background can be challenging. Gamification methods such as capture the flag competition style is a popular form of cybersecurity education to help participants overcome this challenge and identify talents. Participants get to apply theoretical concepts in a controlled environment, solve hands-on tasks in an informal, game-like setting and gain hands-on active learning …

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A Billion-Dollar Flight Ticket: The Race For Recreational Space Exploration And Experiences, Emma Rekate Jan 2022

A Billion-Dollar Flight Ticket: The Race For Recreational Space Exploration And Experiences, Emma Rekate

The Synapse: Intercollegiate science magazine

No abstract provided.

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The Synapse 31 Jan 2022

The Synapse 31

The Synapse: Intercollegiate science magazine

No abstract provided.

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Human-Animal Communication: Insights Into Interspecies Interactions, My Trinh Jan 2022

Human-Animal Communication: Insights Into Interspecies Interactions, My Trinh

The Synapse: Intercollegiate science magazine

No abstract provided.

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Water, Water Everywhere, But Not A Drop To Drink: A Brief Look At The Water Crisis In Flint, Michigan, Jewels Watts Jan 2022

Water, Water Everywhere, But Not A Drop To Drink: A Brief Look At The Water Crisis In Flint, Michigan, Jewels Watts

The Synapse: Intercollegiate science magazine

No abstract provided.

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Evaluating Essential Processes And Forecast Requirements For Meteotsunami-Induced Coastal Flooding, Chenfu Huang, Eric Anderson, Yi Liu, Gangfeng Ma, Greg Mann, Pengfei Xue Jan 2022

Evaluating Essential Processes And Forecast Requirements For Meteotsunami-Induced Coastal Flooding, Chenfu Huang, Eric Anderson, Yi Liu, Gangfeng Ma, Greg Mann, Pengfei Xue

Civil & Environmental Engineering Faculty Publications

Meteotsunamis pose a unique threat to coastal communities and often lead to damage of coastal infrastructure, deluge of nearby property, and loss of life and injury. The Great Lakes are a known hot-spot of meteotsunami activity and serve as an important region for investigation of essential hydrodynamic processes and model forecast requirements in meteotsunami-induced coastal flooding. For this work, we developed an advanced hydrodynamic model and evaluate key model attributes and dynamic processes, including: (1) coastal model grid resolution and wetting and drying process in low-lying zones, (2) coastal infrastructure, including breakwaters and associated submerging and overtopping processes, (3) annual/seasonal …

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Editorial: Coastal Flooding: Modeling, Monitoring, And Protection Systems, Valentina Prigiobbe, Clint Dawson, Yao Hu, Hatim O. Sharif, Navid Tahvildari Jan 2022

Editorial: Coastal Flooding: Modeling, Monitoring, And Protection Systems, Valentina Prigiobbe, Clint Dawson, Yao Hu, Hatim O. Sharif, Navid Tahvildari

Civil & Environmental Engineering Faculty Publications

Coastal flooding has received significant attention in recent years due to future sea-level rise (SLR) projections and intensification of precipitation, which will exacerbate frequent flooding, coastal erosion, and eventually create permanently inundated low-elevation land. Coastal governments will be forced to implement measures to manage risk on the population and infrastructure and build protection systems to mitigate or adapt to the negative impacts of flooding. Research in this area is required to establish holistic frameworks for timely and accurate flooding forecast and design of protection systems.

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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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Spectrum Sensing With Energy Detection In Multiple Alternating Time Slots, Călin Vlădeanu, Alexandru Marţian, Dimitrie C. Popescu Jan 2022

Spectrum Sensing With Energy Detection In Multiple Alternating Time Slots, Călin Vlădeanu, Alexandru Marţian, Dimitrie C. Popescu

Electrical & Computer Engineering Faculty Publications

Energy detection (ED) represents a low complexity approach used by secondary users (SU) to sense spectrum occupancy by primary users (PU) in cognitive radio (CR) systems. In this paper, we present a new algorithm that senses the spectrum occupancy by performing ED in K consecutive sensing time slots starting from the current slot and continuing by alternating before and after the current slot. We consider a PU traffic model specified in terms of an average duty cycle value, and derive analytical expressions for the false alarm probability (FAP) and correct detection probability (CDP) for any value of K . Our …

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Using Skeleton Correction To Improve Flash Lidar-Based Gait Recognition, Nasrin Sadeghzadehyazdi, Tamal Batabyal, Alexander Glandon, Nibir Dhar, Babajide Familoni, Khan Iftekharuddin, Scott T. Acton Jan 2022

Using Skeleton Correction To Improve Flash Lidar-Based Gait Recognition, Nasrin Sadeghzadehyazdi, Tamal Batabyal, Alexander Glandon, Nibir Dhar, Babajide Familoni, Khan Iftekharuddin, Scott T. Acton

Electrical & Computer Engineering Faculty Publications

This paper presents GlidarPoly, an efficacious pipeline of 3D gait recognition for flash lidar data based on pose estimation and robust correction of erroneous and missing joint measurements. A flash lidar can provide new opportunities for gait recognition through a fast acquisition of depth and intensity data over an extended range of distance. However, the flash lidar data are plagued by artifacts, outliers, noise, and sometimes missing measurements, which negatively affects the performance of existing analytics solutions. We present a filtering mechanism that corrects noisy and missing skeleton joint measurements to improve gait recognition. Furthermore, robust statistics are integrated with …

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Broadband Dielectric Spectroscopic Detection Of Aliphatic Alcohol Vapors With Surface-Mounted Hkust-1 Mofs As Sensing Media, Papa K. Amoah, Zeinab Mohammed Hassan, Rhonda R. Franklin, Helmut Baumgart, Engelbert Redel, Yaw S. Obeng Jan 2022

Broadband Dielectric Spectroscopic Detection Of Aliphatic Alcohol Vapors With Surface-Mounted Hkust-1 Mofs As Sensing Media, Papa K. Amoah, Zeinab Mohammed Hassan, Rhonda R. Franklin, Helmut Baumgart, Engelbert Redel, Yaw S. Obeng

Electrical & Computer Engineering Faculty Publications

We leveraged chemical-induced changes to microwave signal propagation characteristics (i.e., S-parameters) to characterize the detection of aliphatic alcohol (methanol, ethanol, and 2-propanol) vapors using TCNQ-doped HKUST-1 metal-organic-framework films as the sensing material, at temperatures under 100 °C. We show that the sensitivity of aliphatic alcohol detection depends on the oxidation potential of the analyte, and the impedance of the detection setup depends on the analyte-loading of the sensing medium. The microwaves-based detection technique can also afford new mechanistic insights into VOC detection, with surface-anchored metal-organic frameworks (SURMOFs), which is inaccessible with the traditional coulometric (i.e., resistance-based) measurements.

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Estimating Efforts For Various Activities In Agile Software Development: An Empirical Study, Lan Cao Jan 2022

Estimating Efforts For Various Activities In Agile Software Development: An Empirical Study, Lan Cao

Information Technology & Decision Sciences Faculty Publications

Effort estimation is an important practice in agile software development. The agile community believes that developers’ estimates get more accurate over time due to the cumulative effect of learning from short and frequent feedback. However, there is no empirical evidence of an improvement in estimation accuracy over time, nor have prior studies examined effort estimation in different development activities, which are associated with substantial costs. This study fills the knowledge gap in the field of software estimation in agile software development by investigating estimations across time and different development activities based on data collected from a large agile project. This …

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Why Do Family Members Reject Ai In Health Care? Competing Effects Of Emotions, Eun Hee Park, Karl Werder, Lan Cao, Balasubramaniam Ramesh Jan 2022

Why Do Family Members Reject Ai In Health Care? Competing Effects Of Emotions, Eun Hee Park, Karl Werder, Lan Cao, Balasubramaniam Ramesh

Information Technology & Decision Sciences Faculty Publications

Artificial intelligence (AI) enables continuous monitoring of patients’ health, thus improving the quality of their health care. However, prior studies suggest that individuals resist such innovative technology. In contrast to prior studies that investigate individuals’ decisions for themselves, we focus on family members’ rejection of AI monitoring, as family members play a significant role in health care decisions. Our research investigates competing effects of emotions toward the rejection of AI monitoring for health care. Based on two scenario-based experiments, our study reveals that emotions play a decisive role in family members’ decision making on behalf of their parents. We find …

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A Unified Health Information System Framework For Connecting Data, People, Devices, And Systems, Wu He, Justin Zuopeng Zhang, Huanmei Wu, Wenzhuo Li, Sachin Shetty Jan 2022

A Unified Health Information System Framework For Connecting Data, People, Devices, And Systems, Wu He, Justin Zuopeng Zhang, Huanmei Wu, Wenzhuo Li, Sachin Shetty

Information Technology & Decision Sciences Faculty Publications

The COVID-19 pandemic has heightened the necessity for pervasive data and system interoperability to manage healthcare information and knowledge. There is an urgent need to better understand the role of interoperability in improving the societal responses to the pandemic. This paper explores data and system interoperability, a very specific area that could contribute to fighting COVID-19. Specifically, the authors propose a unified health information system framework to connect data, systems, and devices to increase interoperability and manage healthcare information and knowledge. A blockchain-based solution is also provided as a recommendation for improving the data and system interoperability in healthcare.

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Visible Opacity Of M Dwarfs And Hot Jupiters: The Tio B³Π-X³Δ Band System, W. Doug Cameron, Peter Bernath Jan 2022

Visible Opacity Of M Dwarfs And Hot Jupiters: The Tio B³Π-X³Δ Band System, W. Doug Cameron, Peter Bernath

Chemistry & Biochemistry Faculty Publications

The TiO B3Π−X3Δ electronic transition (𝛾' system) is an important opacity source in the atmospheres of M dwarfs and hot Jupiter exoplanets. The 0–0, 1–0, and 2–1 bands of the B3Π−X3Δ band system have been analyzed using a TiO emission spectrum recorded at the McMath-Pierce Solar Telescope, operated by the National Solar Observatory at Kitt Peak, Arizona. Improved spectroscopic and equilibrium constants were determined. Line strengths were calculated from an ab initio transition-dipole moment function scaled using an experimental lifetime. A new line list for v' = 0–2 and v′′ = 0–4 …

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