ITNG 2022 19th International Conference on Information Technology-New Generations
- 2022
- Book
- Editor
- Dr. Shahram Latifi
- Book Series
- Advances in Intelligent Systems and Computing
- Publisher
- Springer International Publishing
About this book
This volume represents the 19th International Conference on Information Technology - New Generations (ITNG), 2022. ITNG is an annual event focusing on state of the art technologies pertaining to digital information and communications. The applications of advanced information technology to such domains as astronomy, biology, education, geosciences, security, and health care are the among topics of relevance to ITNG. Visionary ideas, theoretical and experimental results, as well as prototypes, designs, and tools that help the information readily flow to the user are of special interest. Machine Learning, Robotics, High Performance Computing, and Innovative Methods of Computing are examples of related topics. The conference features keynote speakers, a best student award, poster award, and service award. . This publication is unique as it captures modern trends in IT with a balance of theoretical and experimental work. Most other work focus either on theoretical or experimental, but not both. Accordingly, we do not know of any competitive literature.
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Table of Contents
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Human-Computer Interaction
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Frontmatter
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Chapter 35. An Application for Interaction Comparison Between Virtual Hands and Virtual Reality Controllers
Daniel Enriquez, Christopher Lewis, Sergiu M. Dascalu, Frederick C. Harris,Jr.The chapter delves into the comparison of virtual hands and VR controllers for interaction within virtual environments. It discusses the advantages and drawbacks of each method, focusing on usability factors such as performance, presence, and ease-of-use. The application developed using Noitom Hi5 VR Gloves allows for a direct comparison of these input methods through various use cases, including menu interaction, virtualized everyday objects, and rigidbody physics object interactions. The research aims to understand how users translate real-world interactions into virtual environments and the impact of haptic feedback on user experience. The chapter also outlines future work, including user studies and the development of locomotion techniques for VR gloves.AI Generated
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AbstractThis paper presents an application for Virtual Reality (VR) interfaces for virtual hands which will allow us to compare interaction between virtual hands and VR controllers in Virtual Environments (VEs). Development for human-computer interaction in VEs needs improvement to accommodate the growth and need for applications inside VR. Virtual hands are growing more prevalent with many devices detecting the location and mimicry of the user’s own hands inside the VE. Virtual hands can also be implemented via VR Gloves to more precisely pinpoint the movements of hands. This work also implements interaction mediums that can be used by virtual hands or VR controllers to directly manipulate and control virtual objects and virtual interfaces. Unity was used to generate the VE and to render the input mediums and interactable objects. SteamVR was used to connect the input mediums to Unity. The HTC Vive Pro Eye was used to connect the user to the VE. The two input mediums that were compared are the HTC Vive Controllers and the HI5 gloves. All of these components come together to form an immersive and consistent means to compare input mediums in different kinds of interactions. -
Chapter 36. LDAT: A LIDAR Data Analysis and Visualization Tool
Andrew Muñoz, Chase Carthen, Vinh Le, Scotty D. Strachan, Sergiu M. Dascalu, Frederick C. HarrisThe chapter 'LDAT: A LiDAR Data Analysis and Visualization Tool' delves into the development and application of LDAT, a web-based tool designed to process and visualize LiDAR data. LDAT is built on the Angular and Flask web frameworks, allowing it to handle and analyze near real-time point cloud data from street-based LiDAR sensors. The tool's architecture is designed for scalability and efficiency, utilizing MQTT Broker for data transmission and Docker containers for portability. The chapter also presents a user study that evaluated the usability and effectiveness of LDAT, highlighting its potential to revolutionize real-time traffic monitoring and object detection. The detailed description of the system's design, data workflow, and user feedback makes this chapter a valuable resource for professionals interested in advanced data analysis and visualization techniques.AI Generated
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AbstractLight Detection and Ranging (LiDAR) sensors have been employed in many different ways over time and continue to be utilized today. These sensors produce point clouds which are large and complex data sets that are a collection of position points across a 3D space. As LiDAR point cloud data can be highly complex, it can often be difficult to conduct analysis and visualization of the data sets. A web tool was developed to analyze and visualize this type of data, ensuing in an interactive and readable representation of the data. The data obtained for this tool is from LiDAR sensors located on street lights directly adjacent to the University of Nevada, Reno to analyze traffic information. In order to ensure the effectiveness of the tool, a user study was conducted to test the functionality and assess possible improvements. -
Chapter 37. Social Media User Study
Autumn Cuellar, Yifan Zhang, Sergiu M. Dascalu, Frederick C. HarrisThe chapter delves into a comprehensive user study focused on evaluating the usability of four prominent social media platforms: Facebook, Twitter, Instagram, and TikTok. The study, conducted during the peak of the pandemic, involved 10 participants who were asked to perform three key tasks on each platform. The tasks included publishing images and text, publishing videos, and interacting with other users' posts. The chapter analyzes the time taken to complete these tasks and the participants' preferences, using ANOVA tests to determine significant differences. The results reveal that while Facebook was the most preferred and considered easiest to use, all four platforms showed good usability overall. The study highlights the importance of user interface design in the success of social media platforms and suggests areas for further research to confirm and expand upon these findings.AI Generated
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AbstractSocial media is a popular pastime in our current society. There are numerous and diverse social media applications available to use. The study presented in this paper aimed to determine which application is easiest to use and most preferred by users. The apps considered were four of the most popular existing social media applications: Facebook, Twitter, Instagram, and TikTok. The participants in the study were timed while publishing a picture, a text, and a video using each application, and were asked to comment and provide their level of linking on each post they made. Post-questionnaire answers reveal that the majority of participants found Facebook the easiest and more preferable application to use. Experiment results also show that publishing videos on Facebook is quicker than on the other three media apps. On the other hand, publishing pictures and liking/commenting take about the same time on all four apps considered in our study. -
Chapter 38. Software Interfaces for New Vehicle Operating Cost Models Used in Economic Analysis of Transportation Investments: A User Study
Arjun V. Gopinath, Hudson Lynam, Rami Chkaiban, Elie Hajj, Sergiu M. DascaluThe chapter delves into the significance of vehicle operating costs (VOCs) in transportation network performance and the need for accurate, updated estimation models. It details the development of VOC models by the University of Nevada Reno, initially implemented in Excel but later transitioned to a web-based platform due to security and scalability issues. The web interface, developed with modern web technologies, was subjected to a user study comparing it with the Excel version. The study, conducted with participants from various backgrounds, revealed that the web interface was statistically superior in terms of time taken, accuracy, and user experience. The results highlight the advantages of web-based solutions over traditional Excel-based methods, providing valuable insights for future software development in transportation economics.AI Generated
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AbstractEstimating vehicle operating costs (VOCs) allows individuals and organizations to make informed decisions about vehicle usage. As a wide variety of cars and roadway conditions exist, a relatively large amount of input must be provided to any VOC model. Developed as part of a civil engineering research project funded by the U.S. Department of Transportation, five VOC models were run initially in Microsoft Excel. While this early solution was practical and operational, to improve usability, including efficiency of data input, flexibility of running the models, and presentation of results, an alternative solution, a web-based application, was also designed and implemented. The VOC models that can be run on both Excel and the web-based application are: fuel economy, oil consumption, tire wear, mile-age-related vehicle depreciation, and repair and maintenance. This paper briefly introduces the VOC models, describes the two software interfaces created for running them, and presents the results of a user study conducted to evaluate and compare the two interfaces. The study involved 17 participants and focused on usability characteristics and the quality of the user experience. The independent variable was “user interface,” with two test conditions: Excel interface and web-based interface. The participants answered an entry questionnaire, performed tasks using both interfaces, and completed an exit questionnaire. Several dependent variables were measured and analyzed, including task completion time, number of incorrect data entries, and number of clarification questions asked to the user study facilitator. The results obtained showed that the web-based solution consistently outperformed the Excel-based solution, although the latter received some positive feedback as well. -
Chapter 39. Microservice-Based System for Environmental Science Software Applications
Vinh Le, Connor Scully Allison, Mitchell Martinez, Sergiu M. Dascalu, Frederick C. Harris,, Scotty D. Strachan, Eric FritzingerThe chapter introduces MESA, a microservice-based system designed to support environmental science software applications. It addresses the limitations of monolithic systems, such as slow querying speeds and management issues, by providing a distributed support system built with a microservice architecture. MESA was implemented to support the Nevada Research Data Center (NRDC) and its data hub, demonstrating its practical applicability in real-world environmental research projects. The paper evaluates MESA against similar systems, highlighting its advantages in functionality and flexibility. Notably, MESA does not require a complete system refactoring, making it a viable solution for small to midsize environmental research projects. The chapter also discusses MESA's software specifications, use cases, and future work, including plans to enhance machine learning and high-performance computing capabilities. Overall, MESA offers a robust and adaptable platform for environmental research projects, bridging the gap between outdated systems and expensive new ones.AI Generated
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AbstractWhen an environmental research project grows, technical concerns over system scalability, data exposure, and third-party application support are overlooked. This paper presents a system, the Microservice-based Envirosensing Support Applications (MESA), that provides a scalable environment and data infrastructure solutions for the NSF-funded Solar Energy-Water-Environment Nexus project. MESA can be broken into 4 major parts: a suite of microservices exposed over an API, an overarching service discovery, a series of tables replicated from an existing monolith, and the applications that MESA lends its support. In order to evaluate the capability of MESA, the features of this system were compared against three other existing microservice-based research systems. MESA features were more robust than two of the other systems, but was found lacking when compared to the last, as it does not lender support to advanced techniques like HPC or Machine Learning.
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Networks
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Frontmatter
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Chapter 40. Semantic Interoperability in the Internet of Things: A Systematic Literature Review
Pedro Lopes de Lopes de Souza, Wanderley Lopes de Lopes de Souza, Ricardo Rodrigues CiferriThe chapter delves into the evolution of the Internet of Things (IoT), highlighting its impact on various domains such as healthcare, transportation, and agriculture. It discusses the significant challenges posed by the heterogeneity of IoT data and platforms, emphasizing the need for semantic interoperability to ensure meaningful data exchange. The systematic literature review (SLR) methodology is employed to identify the main IoT application domains, architectures, and platforms, as well as the semantic models and approaches used to address interoperability issues. The chapter provides a detailed analysis of the most cited IoT platforms and the specific semantic models employed in primary studies. It concludes by suggesting that a generic ontology could provide an efficient solution for IoT interoperability, making it a valuable resource for researchers and practitioners in the field.AI Generated
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AbstractThe main challenges in Internet of Things (IoT) refer to the varied capabilities of things, the huge amount of data they produce, the heterogeneity of this data, and the diverse offered services. For each application domain and for each vendor, there is usually a specific and proprietary IoT platform, with no de facto standards currently being found or expected in the near future. Therefore, ensuring the semantic interoperability of things between different types of IoT platforms and applications is one of the major problems in this area. This paper aims to identify current conceptual and practical findings for the semantic interoperability problem in IoT through a Systematic Literature Review (SLR). By searching digital libraries and using the snowballing technique, 314 manuscripts were selected for data extraction from this SLR, which allowed us to come up with the current main issues and solutions related to this matter. The results obtained with this SLR and reported in this paper can help researchers and practitioners to find better solutions for this problem. -
Chapter 41. IoT Machine Learning Based Parking Management System with Anticipated Prediction of Available Parking Spots
Grzegorz Chmaj, Michael LazeroffThe chapter introduces an innovative IoT-based parking management system that uses machine learning to predict the availability of parking spots in real-time. By leveraging smartphones and user-provided data, the system optimizes traffic flow and reduces parking time in high-density areas such as university campuses. The proposed system eliminates the need for additional infrastructure like sensors, relying instead on a mobile application that interacts with a backend server. The backend server processes GPS coordinates, utilizing machine learning models to predict user movements and parking spot availability. The system also incorporates geofences to delineate virtual perimeters around parking areas, enhancing the accuracy of predictions. Additionally, the chapter discusses the potential for personalized time predictions and the integration of various parking spot categories. The detailed architecture and implementation of the system are thoroughly explored, providing a comprehensive guide for professionals seeking to implement similar solutions in smart city environments.AI Generated
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AbstractMachine Learning based designs provide an extensive means to recognize patterns and do various kinds of predictions. In this paper we apply machine learning to the Internet of Things architecture to optimize access to smart parking. We assume that the system will detect which driver parked at which spot, and also will recognize driver’s habit of returning to the car. This way we predict that the spot of the driver walking towards the parking lot or garage will soon be available for other drivers. Drivers looking for a parking spot will receive such information in advance, in a form of “Spot N will be available in X minutes”. The design operates over the features offered by smartphone devices: to determine the parking spot, determine the walking driver’s position and also serving as a base for a mobile application, so the system is convenient to use and doesn’t require additional infrastructure. -
Chapter 42. Channel State Information Spectrum Gap Filling Using Shallow Neural Networks
Avishek Mukherjee, Beata Hejno, Manish OstiThe chapter delves into the challenge of predicting Channel State Information (CSI) in Wi-Fi networks without continuous probing, leveraging existing CSI measurements from nearby channels. It introduces CSIFill, a shallow neural network-based approach, and demonstrates its high accuracy in predicting CSI coefficients, even in varying channel conditions. The study includes real-world experiments and evaluates the performance of CSIFill against actual measured CSI, showcasing its potential to improve network efficiency and speed. The chapter also discusses related work, theoretical background, and the details of the CSIFill algorithm, making it a comprehensive resource for professionals in the field.AI Generated
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AbstractWe propose CSIFill, a novel system to predict the Channel State Information (CSI) in indoor wireless networks. CSIFill can estimate the CSI on different frequency subcarriers by using the CSI measurements from neighboring frequencies. CSIFill is different from traditional estimation techniques which attempt to recreate the wireless channel and instead relies on already collected CSI data, to predict the CSI on different wireless frequencies. This is especially useful in indoor wireless networks where an Access Point (AP) needs to periodically measure the CSI on other frequency channels to find better data rates. CSIFill can be used to automatically determine when to switch to another channel to obtain better service without any additional probing or overhead. Our initial results with CSIFill have been very encouraging. CSIFill was evaluated using real world experimental CSI data and was found to accurately estimate CSI data for up to 7.5 MHz channel bandwidth using a shallow neural network.
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Potpourri
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Frontmatter
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Chapter 43. Unveiling a Novel Corporate Structure in World-Class Business, Merging Digital-Physical Environment in Hyper Famili Incorporation
Mohammad Khakzadeh, Fatemeh Saghafi, Seyed Milad Seyed Javadein, Mohammad Hossein Asmaie, Masoud Matbou SalehThis chapter delves into the innovative corporate structure of Hyper Famili Incorporation, focusing on the creation of a world-class business ecosystem. It begins by highlighting the importance of organizational structure and business elements in the prosperity of successful businesses. The chapter then explores the concept of business ecosystems, drawing on the theories of James Moore and the success stories of corporations like Walmart and Carrefour. The text emphasizes the integration of digital technologies to enhance business operations, creating an 'Intelligent Seamless Ecosystem.' It also discusses the role of immersive learning technologies, such as virtual reality, in training and skill development within the new ecosystem. The chapter concludes by proposing a new organizational structure for Hyper Famili, inspired by international best practices and future studies, aimed at ensuring the survival and growth of the corporation. The detailed analysis and comparative study make this chapter a must-read for professionals interested in the future of retail and digital transformation.AI Generated
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AbstractIn this paper we aim to design a brand new corporate structure which merges Physical and Digital Technology in World-Class Business, whilst utilizing new technologies based on digitalization drivers. We propose a method in which we have introduced a state of the art Organizational structure that surveys our world-class Business Model case studies and all of the mandatory technologies which shape the fundamental framework of such innovative business ecosystems that end up as the most important input for the decision making process in management levels. In the upcoming research we will be comparing this model with other models in different aspects like comparability in utilizing brand new technologies to building up the dominant share of global market. -
Chapter 44. Developing an Affective Audio Toolbox for Audio Post-production
Harrison Ridley, Stuart Cunningham, Richard PickingThe chapter 'Developing an Affective Audio Toolbox for Audio Post-production' delves into the intricate world of film sound design, focusing on how sound professionals use audio to evoke emotions and shape perceptions in audiences. Through qualitative research and interviews with seasoned professionals, the authors uncover techniques and considerations that go into creating impactful soundtracks. The study reveals that sound designers are well-aware of the affective qualities of sound and use them strategically to enhance narrative and emotional depth. The chapter also introduces a hierarchical workflow for affective audio implementation, providing a practical guide for professionals in the field. By highlighting real-world examples and expert insights, this chapter offers a compelling look into the creative process behind film sound design, making it a valuable read for anyone interested in the intersection of sound and emotion in cinema.AI Generated
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AbstractThis research aims to understand how soundtrack elements can stimulate an emotional response in viewers whilst watching film and how sound professionals utilise sound for this purpose. The article reviews research on affective audio in film and informs ten semi-structured interviews with film sound professionals. These interviews cover a variety of topics, all with a focus on sound design. The interview transcripts were thematically analysed, and six themes were drawn from them and are discussed in detail and explored through case-study examples. A workflow for sound design is synthesised using each theme as a step in the post-production process, intended as a way of visualising how this research can aid the film-sound profession and inform future research in the field. It is concluded that sound is currently used to bring about affective responses in specific instances, when other emotional devices are not already in use. The use of sound as a narrative aid is found to be more prevalent, and indeed currently seen as more important within the industry than for specific affective use. Further research is suggested to enhance understanding of affective audio and to develop a framework for its widespread effective implementation in film. -
Chapter 45. Boundary Approximation and External Visibility
Laxmi Gewali, Samridhi JhaThe chapter delves into the complexities of polygonal boundary approximation and its effects on visibility properties. It reviews key algorithms such as the Douglas-Peucker and Imai-Iri methods, highlighting their limitations in preserving visibility. The novel C-Chain Approximation algorithm is introduced, which successfully retains external visibility properties during simplification. This algorithm has practical applications in areas such as covert path planning and efficient data transmission in geospatial contexts. The chapter concludes with discussions on potential future research directions and practical implementations.AI Generated
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AbstractAlgorithms for covering and simplifying a 1.5D terrain have been extensively investigated. Minimally covering a 1.5D terrain is an intractable problem. We present a critical review of existing approximation algorithms for simplifying a 1.5 D terrain by a fewer number of vertices. We introduce the problem of simplifying a 1.5D chain with a fewer number of vertices subject to visibility requirement. We then present the development of an efficient algorithm for chain approximation with minimal effect on external visibility. -
Chapter 46. Detection of Strictly L3-Live Structures by Structural Analysis of General Petri Net Using SAT-Solver
Yuta Yoshizawa , Katsumi WasakiThe chapter delves into the critical issue of ensuring the reliability of parallel systems, such as asynchronous circuits and communication protocols, by modeling them with Petri nets. It introduces the concept of strictly L3-live structures and explains how structural analysis and SAT-solver can be employed to detect these structures efficiently. The chapter also discusses the structural properties required for the existence of these structures and provides examples to illustrate the analysis process. By understanding and applying the methods described in this chapter, professionals can significantly improve the reliability and performance of complex systems.AI Generated
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AbstractOne of the dynamic properties of Petri nets is liveness, which ranges from L0 to L4 depending on the severity of the condition. The structure required for the existence of strictly L3-live transitions is referred to as the strictly L3-live structure. The strictly L3-live structure consists of three elements: a repeating closed circuit (L3-circuit), a transition that cancels the liveness of the L3-circuit (CircuitBreaker), and a place that receives a token supplied by the L3-circuit (k-place). To detect these elements, we use the partially-conservative, partially-repetitive, and bounded structurally properties of general Petri nets, as well as solving the matrix inequalities, which are necessary and sufficient conditions for the three structural properties, using the SAT solver to detect the three elements that constitute the strictly L3-live structure. -
Chapter 47. Space Abstraction and of PetriNets Using the Submarking Method Quasi-home States
Tomoki Miura , Katsumi WasakiThis chapter delves into the application of Petri nets for modeling and verifying the reliability of parallel systems, highlighting the challenges in handling large and complex models. It introduces the Hierarchical Petri net Simulator (HiPS) as a tool to facilitate the descriptiveness and analysis of Petri nets. The main focus is on the submarking method, which compresses the state space by abstracting markings without altering the system's essence. The study defines four submarking methods and demonstrates how to determine quasi-home states, which are crucial for understanding the system's stable states. By abstracting unnecessary information, the submarking method enhances the efficiency of dynamic analysis, offering a significant advancement in the field of Petri net modeling and verification.AI Generated
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AbstractThe home state is a property of Petri nets. The home state is a state that can be returned to from all markings, and is the stable state in the system. In this study, we define a quasi-home state as a state in which the conditions of the home state are relaxed. The quasi-home state is the home state in submarkings, which are abstracted markings. The submarking method can compress the state space while giving meaning to the marking. In this study, we defined four submarking methods. The user specifies the place to be abstracted and the submarking method, and submarking is obtained. The home state is obtained through the submarking’s dynamic analysis. This study aims to improve the net analysis’ efficiency using the submarking method to determine the quasi-home state.
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Backmatter
- Title
- ITNG 2022 19th International Conference on Information Technology-New Generations
- Editor
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Dr. Shahram Latifi
- Copyright Year
- 2022
- Publisher
- Springer International Publishing
- Electronic ISBN
- 978-3-030-97652-1
- Print ISBN
- 978-3-030-97651-4
- DOI
- https://doi.org/10.1007/978-3-030-97652-1
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