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Description
Vehicles traverse granular media through complex reactions with large numbers of small particles. Many approaches rely on empirical trends derived from wheeled vehicles in well-characterized media. However, the environments of numerous bodies such as Mars or the moon are primarily composed of fines called regolith which require different design considerations. This dissertation discusses research aimed at understanding the role and function of empirical, computational, and theoretical granular physics approaches as they apply to helical geometries, their envelope of applicability, and the development of new laws. First, a static Archimedes screw submerged in granular material (glass beads) is analyzed using two methods: Granular Resistive Force Theory (RFT), an empirically derived set of equations based on fluid dynamic superposition principles, and Discrete element method (DEM) simulations, a particle modeling software. Dynamic experiments further confirm the computational method with multi-body dynamics (MBD)-DEM co-simulations. Granular Scaling Laws (GSL), a set of physics relationships based on non-dimensional analysis, are utilized for the gravity-modified environments. A testing chamber to contain a lunar analogue, BP-1, is developed and built. An investigation of straight and helical grousered wheels in both silica sand and BP-1 is performed to examine general GSL applicability for lunar purposes. Mechanical power draw and velocity prediction by GSL show non-trivial but predictable deviation. BP-1 properties are characterized and applied to an MBD-DEM environment for the first time. MBD-DEM simulation results between Earth gravity and lunar gravity show good agreement with theoretical predictions for both power and velocity. The experimental deviation is further investigated and found to have a mass-dependant component driven by granular sinkage and engagement. Finally, a robust set of helical granular scaling laws (HGSL) are derived. The granular dynamics scaling of three-dimensional screw-driven mobility is reduced to a similar theory as wheeled scaling laws, provided the screw is radially continuous. The new laws are validated in BP-1 with results showing very close agreement to predictions. A gravity-variant version of these laws is validated with MBD-DEM simulations. The results of the dissertation suggest GSL, HGSL, and MBD-DEM give reasonable approximations for use in lunar environments to predict rover mobility given adequate granular engagement.
ContributorsThoesen, Andrew Lawrence (Author) / Marvi, Hamidreza (Thesis advisor) / Berman, Spring (Committee member) / Emady, Heather (Committee member) / Lee, Hyunglae (Committee member) / Klesh, Andrew (Committee member) / Arizona State University (Publisher)
Created2019
Description
Graphs are one of the key data structures for many real-world computing applica-
tions such as machine learning, social networks, genomics etc. The main challenges of
graph processing include diculty in parallelizing the workload that results in work-
load imbalance, poor memory locality and very large number of memory accesses.
This causes large-scale graph processing to be very expensive.
This thesis presents implementation of a select set of graph kernels on a multi-core
architecture, Transmuter. The kernels are Breadth-First Search (BFS), Page Rank
(PR), and Single Source Shortest Path (SSSP). Transmuter is a multi-tiled architec-
ture with 4 tiles and 16 general processing elements (GPE) per tile that supports a
two level cache hierarchy. All graph processing kernels have been implemented on
Transmuter using Gem5 architectural simulator.
The key pre-processing steps in improving the performance are static partition-
ing by destination and balancing the workload among the processing cores. Results
obtained by processing graphs that are partitioned against un-partitioned graphs
show almost 3x improvement in performance. Choice of data structure also plays an
important role in the amount of storage space consumed and the amount of synchro-
nization required in a parallel implementation. Here the compressed sparse column
data format was used. BFS and SSSP are frontier-based algorithms where a frontier
represents a subset of vertices that are active during the current iteration. They
were implemented using the Boolean frontier array data structure. PR is an iterative
algorithm where all vertices are active at all times.
The performance of the dierent Transmuter implementations for the 14nm node
were evaluated based on metrics such as power consumption (Watt), Giga Operations
Per Second(GOPS), GOPS/Watt and L1/L2 cache misses. GOPS/W numbers for
graphs with 10k nodes and 10k edges is 33 for BFS, 477 for PR and 10 for SSSP.
i
Frontier-based algorithms have much lower GOPS/W compared to iterative algo-
rithms such as PR. This is because all nodes in Page Rank are active at all points
in time. For all three kernel implementations, the L1 cache miss rates are quite low
while the L2 cache hit rates are high.
tions such as machine learning, social networks, genomics etc. The main challenges of
graph processing include diculty in parallelizing the workload that results in work-
load imbalance, poor memory locality and very large number of memory accesses.
This causes large-scale graph processing to be very expensive.
This thesis presents implementation of a select set of graph kernels on a multi-core
architecture, Transmuter. The kernels are Breadth-First Search (BFS), Page Rank
(PR), and Single Source Shortest Path (SSSP). Transmuter is a multi-tiled architec-
ture with 4 tiles and 16 general processing elements (GPE) per tile that supports a
two level cache hierarchy. All graph processing kernels have been implemented on
Transmuter using Gem5 architectural simulator.
The key pre-processing steps in improving the performance are static partition-
ing by destination and balancing the workload among the processing cores. Results
obtained by processing graphs that are partitioned against un-partitioned graphs
show almost 3x improvement in performance. Choice of data structure also plays an
important role in the amount of storage space consumed and the amount of synchro-
nization required in a parallel implementation. Here the compressed sparse column
data format was used. BFS and SSSP are frontier-based algorithms where a frontier
represents a subset of vertices that are active during the current iteration. They
were implemented using the Boolean frontier array data structure. PR is an iterative
algorithm where all vertices are active at all times.
The performance of the dierent Transmuter implementations for the 14nm node
were evaluated based on metrics such as power consumption (Watt), Giga Operations
Per Second(GOPS), GOPS/Watt and L1/L2 cache misses. GOPS/W numbers for
graphs with 10k nodes and 10k edges is 33 for BFS, 477 for PR and 10 for SSSP.
i
Frontier-based algorithms have much lower GOPS/W compared to iterative algo-
rithms such as PR. This is because all nodes in Page Rank are active at all points
in time. For all three kernel implementations, the L1 cache miss rates are quite low
while the L2 cache hit rates are high.
ContributorsRENGANATHAN, SRINIDHI (Author) / Chakrabarti, Chaitali (Thesis advisor) / Shrivastava, Aviral (Committee member) / Mudge, Trevor (Committee member) / Arizona State University (Publisher)
Created2019
Description
Power management circuits are employed in most electronic integrated systems, including applications for automotive, IoT, and smart wearables. Oftentimes, these power management circuits become a single point of system failure, and since they are present in most modern electronic devices, they become a target for hardware security attacks. Digital circuits are typically more prone to security attacks compared to analog circuits, but malfunctions in digital circuitry can affect the analog performance/parameters of power management circuits. This research studies the effect that these hacks will have on the analog performance of power circuits, specifically linear and switching power regulators/converters. Apart from security attacks, these circuits suffer from performance degradations due to temperature, aging, and load stress. Power management circuits usually consist of regulators or converters that regulate the load’s voltage supply by employing a feedback loop, and the stability of the feedback loop is a critical parameter in the system design. Oftentimes, the passive components employed in these circuits shift in value over varying conditions and may cause instability within the power converter. Therefore, variations in the passive components, as well as malicious hardware security attacks, can degrade regulator performance and affect the system’s stability. The traditional ways of detecting phase margin, which indicates system stability, employ techniques that require the converter to be in open loop, and hence can’t be used while the system is deployed in-the-field under normal operation. Aging of components and security attacks may occur after the power management systems have completed post-production test and have been deployed, and they may not cause catastrophic failure of the system, hence making them difficult to detect. These two issues of component variations and security attacks can be detected during normal operation over the product lifetime, if the frequency response of the power converter can be monitored in-situ and in-field. This work presents a method to monitor the phase margin (stability) of a power converter without affecting its normal mode of operation by injecting a white noise/ pseudo random binary sequence (PRBS). Furthermore, this work investigates the analog performance parameters, including phase margin, that are affected by various digital hacks on the control circuitry associated with power converters. A case study of potential hardware attacks is completed for a linear low-dropout regulator (LDO).
ContributorsMalakar, Pragya Priya (Author) / Kitchen, Jennifer (Thesis advisor) / Ozev, Sule (Committee member) / Brunhaver, John (Committee member) / Arizona State University (Publisher)
Created2019
Description
This research seeks to better understand the current state of US healthcare FM industry hiring practices from colleges and universities to identify potential employment barriers into healthcare FM and interventions to help overcome them. Two national surveys were distributed to healthcare facility managers and directors to collect quantifiable information on healthcare organizations, hiring practices from FM academic programs, individual demographics, and opinions of FM college graduates. Designated survey respondents were also contacted for phone interviews. Additionally, a Delphi method was used for this research to draw upon the collective knowledge and experience of 13 experts over three iterative rounds of input.
Results indicate that the healthcare FM industry is hiring very few college interns and new college graduates for entry-level management jobs. Strong homogeneousness demographics, backgrounds, and paths of entry among existing healthcare FM professionals has created an industry bias against candidates attempting to enter healthcare FM from non-traditional sources. The healthcare FM industry’s principal source for new talent comes from building trade succession within healthcare organizations. However, continuing to rely on building tradespersons as the main path of entry into the healthcare FM industry may prove problematic. Most existing healthcare facility managers and directors will be retiring within 10 years, yet it is taking more than 17 years of full-time work experience to prepare building tradespersons to assume these roles.
New college graduates from FM academic programs are a viable recruitment source for new talent into healthcare FM as younger professionals are commonly entering the healthcare FM through the path of higher education. Although few new college graduates enter the healthcare FM industry, they are experiencing similar promotion timeframes compared to other candidate with many years of full-time work experience. Unfamiliarity with FM academic programs, work experience requirements, limited entry-level jobs within small organizations, low pay, and a limited exposure to healthcare industry topics present challenges for new FM college graduates attempting to enter the healthcare FM industry. This study shows that gaps indeed exist in student learning outcomes for a comprehensive healthcare FM education; key technical topics specific to the healthcare industry are not being addressed by organizations accrediting construction and facility management academic programs. A framework is proposed for a comprehensive healthcare FM education including accreditation, regulatory and code compliance, infection control, systems in healthcare facilities, healthcare construction project management and methods, and clinical operations and medical equipment. Interestingly, academics in the field of FM generally disagree with industry professionals that these technical topics are important student learning outcomes. Consequently, FM academics prefer to teach students general FM principles with the expectation that specific technical knowledge will be gained in the workplace after graduation from college. Nevertheless, candidates attempting to enter healthcare FM without industry specific knowledge are disadvantaged due to industry perceptions and expectations. University-industry linkage must be improved to successfully attract students into the field of healthcare FM and establish colleges and universities as a sustainable recruitment source in helping address FM attrition.
This paper is valuable in establishing the current state of the US healthcare industry’s hiring practices from FM academic programs and identifying major barriers of entering the healthcare FM industry for new FM college graduates. Findings facilitate development of interventions by healthcare organizations and universities to further open FM academic programs as a sustainable source of new talent to help address healthcare FM attrition, including a healthcare FM education framework to elucidate college student learning outcomes for successful employment in healthcare FM. These student learning outcomes provide a framework for both the healthcare industry and academia in preparing future facility managers.
Results indicate that the healthcare FM industry is hiring very few college interns and new college graduates for entry-level management jobs. Strong homogeneousness demographics, backgrounds, and paths of entry among existing healthcare FM professionals has created an industry bias against candidates attempting to enter healthcare FM from non-traditional sources. The healthcare FM industry’s principal source for new talent comes from building trade succession within healthcare organizations. However, continuing to rely on building tradespersons as the main path of entry into the healthcare FM industry may prove problematic. Most existing healthcare facility managers and directors will be retiring within 10 years, yet it is taking more than 17 years of full-time work experience to prepare building tradespersons to assume these roles.
New college graduates from FM academic programs are a viable recruitment source for new talent into healthcare FM as younger professionals are commonly entering the healthcare FM through the path of higher education. Although few new college graduates enter the healthcare FM industry, they are experiencing similar promotion timeframes compared to other candidate with many years of full-time work experience. Unfamiliarity with FM academic programs, work experience requirements, limited entry-level jobs within small organizations, low pay, and a limited exposure to healthcare industry topics present challenges for new FM college graduates attempting to enter the healthcare FM industry. This study shows that gaps indeed exist in student learning outcomes for a comprehensive healthcare FM education; key technical topics specific to the healthcare industry are not being addressed by organizations accrediting construction and facility management academic programs. A framework is proposed for a comprehensive healthcare FM education including accreditation, regulatory and code compliance, infection control, systems in healthcare facilities, healthcare construction project management and methods, and clinical operations and medical equipment. Interestingly, academics in the field of FM generally disagree with industry professionals that these technical topics are important student learning outcomes. Consequently, FM academics prefer to teach students general FM principles with the expectation that specific technical knowledge will be gained in the workplace after graduation from college. Nevertheless, candidates attempting to enter healthcare FM without industry specific knowledge are disadvantaged due to industry perceptions and expectations. University-industry linkage must be improved to successfully attract students into the field of healthcare FM and establish colleges and universities as a sustainable recruitment source in helping address FM attrition.
This paper is valuable in establishing the current state of the US healthcare industry’s hiring practices from FM academic programs and identifying major barriers of entering the healthcare FM industry for new FM college graduates. Findings facilitate development of interventions by healthcare organizations and universities to further open FM academic programs as a sustainable source of new talent to help address healthcare FM attrition, including a healthcare FM education framework to elucidate college student learning outcomes for successful employment in healthcare FM. These student learning outcomes provide a framework for both the healthcare industry and academia in preparing future facility managers.
ContributorsCall, Steven Alan (Author) / Sullivan, Kenneth (Thesis advisor) / Hurtado, Kristen (Committee member) / Standage, Richard (Committee member) / Arizona State University (Publisher)
Created2019
Description
The traditional access control system suffers from the problem of separation of data ownership and management. It poses data security issues in application scenarios such as cloud computing and blockchain where the data owners either do not trust the data storage provider or even do not know who would have access to their data once they are appended to the chain. In these scenarios, the data owner actually loses control of the data once they are uploaded to the outside storage. Encryption-before-uploading is the way to solve this issue, however traditional encryption schemes such as AES, RSA, ECC, bring about great overheads in key management on the data owner end and could not provide fine-grained access control as well.
Attribute-Based Encryption (ABE) is a cryptographic way to implement attribute-based access control, which is a fine-grained access control model, thus solving all aforementioned issues. With ABE, the data owner would encrypt the data by a self-defined access control policy before uploading the data. The access control policy is an AND-OR boolean formula over attributes. Only users with attributes that satisfy the access control policy could decrypt the ciphertext. However the existing ABE schemes do not provide some important features in practical applications, e.g., user revocation and attribute expiration. Furthermore, most existing work focus on how to use ABE to protect cloud stored data, while not the blockchain applications.
The main objective of this thesis is to provide solutions to add two important features of the ABE schemes, i.e., user revocation and attribute expiration, and also provide a practical trust framework for using ABE to protect blockchain data. To add the feature of user revocation, I propose to add user's hierarchical identity into the private attribute key. In this way, only users whose identity is not revoked and attributes satisfy the access control policy could decrypt the ciphertext. To add the feature of attribute expiration, I propose to add the attribute valid time period into the private attribute key. The data would be encrypted by access control policy where all attributes have a temporal value. In this way, only users whose attributes both satisfy the access policy and at the same time these attributes do not expire,
are allowed to decrypt the ciphertext. To use ABE in the blockchain applications, I propose an ABE-enabled trust framework in a very popular blockchain platform, Hyperledger Fabric. Based on the design, I implement a light-weight attribute certificate authority for attribute distribution and validation; I implement the proposed ABE schemes and provide a toolkit which supports system setup, key generation,
data encryption and data decryption. All these modules were integrated into a demo system for protecting sensitive les in a blockchain application.
Attribute-Based Encryption (ABE) is a cryptographic way to implement attribute-based access control, which is a fine-grained access control model, thus solving all aforementioned issues. With ABE, the data owner would encrypt the data by a self-defined access control policy before uploading the data. The access control policy is an AND-OR boolean formula over attributes. Only users with attributes that satisfy the access control policy could decrypt the ciphertext. However the existing ABE schemes do not provide some important features in practical applications, e.g., user revocation and attribute expiration. Furthermore, most existing work focus on how to use ABE to protect cloud stored data, while not the blockchain applications.
The main objective of this thesis is to provide solutions to add two important features of the ABE schemes, i.e., user revocation and attribute expiration, and also provide a practical trust framework for using ABE to protect blockchain data. To add the feature of user revocation, I propose to add user's hierarchical identity into the private attribute key. In this way, only users whose identity is not revoked and attributes satisfy the access control policy could decrypt the ciphertext. To add the feature of attribute expiration, I propose to add the attribute valid time period into the private attribute key. The data would be encrypted by access control policy where all attributes have a temporal value. In this way, only users whose attributes both satisfy the access policy and at the same time these attributes do not expire,
are allowed to decrypt the ciphertext. To use ABE in the blockchain applications, I propose an ABE-enabled trust framework in a very popular blockchain platform, Hyperledger Fabric. Based on the design, I implement a light-weight attribute certificate authority for attribute distribution and validation; I implement the proposed ABE schemes and provide a toolkit which supports system setup, key generation,
data encryption and data decryption. All these modules were integrated into a demo system for protecting sensitive les in a blockchain application.
ContributorsDong, Qiuxiang (Author) / Huang, Dijiang (Thesis advisor) / Sen, Arunabha (Committee member) / Doupe, Adam (Committee member) / Arizona State University (Publisher)
Created2020
Description
The goal of any solar photovoltaic (PV) system is to generate maximum energy throughout its lifetime. The parameters that can affect PV module power output include: solar irradiance, temperature, soil accumulation, shading, encapsulant browning, encapsulant delamination, series resistance increase due to solder bond degradation and corrosion and shunt resistance decrease due to potential induced degradation, etc. Several PV modules together in series makes up a string, and in a power plant there are a number of these strings in parallel which can be referred to as an array. Ideally, PV modules in a string should be identically matched to attain maximum power output from the entire string. Any underperforming module or mismatch among modules within a string can reduce the power output. The goal of this project is to quickly identify and quantitatively determine the underperforming module(s) in an operating string without the use of an I-V curve tracer, irradiance sensor or temperature sensor. This goal was achieved by utilizing Radiovoltmeters (RVM). In this project, it is demonstrated that the voltages at maximum power point (Vmax) of all the individual modules in a string can be simultaneously and quantitatively obtained using RVMs at a single irradiance, single module operating temperature, single spectrum and single angle of incidence. By combining these individual module voltages (Vmax) with the string current (Imax) using a Hall sensor, the power output of individual modules can be obtained, quickly and quantitatively.
ContributorsTahghighi, Arash (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Rogers, Bradley (Committee member) / Srinivasan, Devarajan (Committee member) / Arizona State University (Publisher)
Created2019
Description
Research findings have shown that many computerized maintenance management systems (CMMS) are largely underutilized, often leading to the loss of efficiencies in the organization’s maintenance program. A literature review is presented of the available research in CMMS and of operations and management roles in a maintenance program. In addition, research was conducted around CMMS users to identify if any misalignments exist between management and operations. The articles selected for review offer a variety of perspectives, considerations, instructions, and noted failures involved with implementation, day to day use and reporting expectations. Through conducting a survey of both management and operations this paper will show how management and operations conceptions of CMMS vary, even greatly in some areas. The objective of this research is to gain an in-depth perspective from CMMS in all roles and analyze where utilizations vary. This information will then be utilized to understand possible misconceptions between roles, leading to inaccuracies and sub-par outcomes of proposed CMMS implementations.
ContributorsRennert, Andrew William (Author) / Sullivan, Kenneth (Thesis advisor) / Stone, Brian (Committee member) / Smithwick, Jake (Committee member) / Arizona State University (Publisher)
Created2019
Description
This work introduces self-organizing techniques to reduce the complexity and burden of coordinating distributed energy resources (DERs) and microgrids that are rapidly increasing in scale globally. Technical and financial evaluations completed for power customers and for utilities identify how disruptions are occurring in conventional energy business models. Analyses completed for Chicago, Seattle, and Phoenix demonstrate site-specific and generalizable findings. Results indicate that net metering had a significant effect on the optimal amount of solar photovoltaics (PV) for households to install and how utilities could recover lost revenue through increasing energy rates or monthly fees. System-wide ramp rate requirements also increased as solar PV penetration increased. These issues are resolved using a generalizable, scalable transactive energy framework for microgrids to enable coordination and automation of DERs and microgrids to ensure cost effective use of energy for all stakeholders. This technique is demonstrated on a 3-node and 9-node network of microgrid nodes with various amounts of load, solar, and storage. Results found that enabling trading could achieve cost savings for all individual nodes and for the network up to 5.4%. Trading behaviors are expressed using an exponential valuation curve that quantifies the reputation of trading partners using historical interactions between nodes for compatibility, familiarity, and acceptance of trades. The same 9-node network configuration is used with varying levels of connectivity, resulting in up to 71% cost savings for individual nodes and up to 13% cost savings for the network as a whole. The effect of a trading fee is also explored to understand how electricity utilities may gain revenue from electricity traded directly between customers. If a utility imposed a trading fee to recoup lost revenue then trading is financially infeasible for agents, but could be feasible if only trying to recoup cost of distribution charges. These scientific findings conclude with a brief discussion of physical deployment opportunities.
ContributorsJanko, Samantha Ariel (Author) / Johnson, Nathan (Thesis advisor) / Zhang, Wenlong (Committee member) / Herche, Wesley (Committee member) / Arizona State University (Publisher)
Created2019
Description
This research summarizes the characterization of the constituent materials of a unidirectional composite for use in a finite element model. Specifically the T800s-F3900 composite from Toray Composites, Seattle, WA. Testing was carried out on cured polymer matrix provided by the manufacturer and single fiber specimen. The material model chosen for the polymer matrix was MAT 187 (Semi-Analytical Model for Polymers) which allowed for input of the tension, compression, and shear load responses.
The matrix was tested in tension, compression, and shear and was assumed to be isotropic. Ultimate strengths of the matrix were found to be 10 580 psi in tension, 25 900 psi in compression, and 5 940 in shear. The material properties calculated suggest the resin as being an isotropic material with the moduli in tension and compression being approximately equal (3% difference between the experimental values) and the shear modulus following typical isotropic relations. Single fiber properties were obtained for the T800s fiber in tension only with the modulus being approximately 40 500 ksi and the peak stress value being approximately 309 ksi.
The material model predicts the behavior of the multi-element testing simulations in both deformation and failure in the direction of loading.
The matrix was tested in tension, compression, and shear and was assumed to be isotropic. Ultimate strengths of the matrix were found to be 10 580 psi in tension, 25 900 psi in compression, and 5 940 in shear. The material properties calculated suggest the resin as being an isotropic material with the moduli in tension and compression being approximately equal (3% difference between the experimental values) and the shear modulus following typical isotropic relations. Single fiber properties were obtained for the T800s fiber in tension only with the modulus being approximately 40 500 ksi and the peak stress value being approximately 309 ksi.
The material model predicts the behavior of the multi-element testing simulations in both deformation and failure in the direction of loading.
ContributorsRobbins, Joshua (Author) / Rajan, Subramaniam D. (Thesis advisor) / Mobasher, Barzin (Committee member) / Hoover, Christian (Committee member) / Arizona State University (Publisher)
Created2019
Description
As the microelectronics industry continues to decrease the size of solder joints, each joint will have to carry a greater current density, making atom diffusion due to current flow, electromigration (EM), a problem of ever-increasing severity. The rate of EM damage depends on current density, operating temperature, and the original microstructure of the solder joint, including void volume, grain orientation, and grain size. While numerous studies have investigated the post-mortem effects of EM and have tested a range of current densities and temperatures, none have been able to analyze how the same joint evolves from its initial to final microstructure. This thesis focuses on the study of EM, thermal aging, and thermal cycling in Sn-rich solder joints. Solder joints were either of controlled microstructure and orientation or had trace alloying element additions. Sn grain orientation has been linked to a solder joints’ susceptibility to EM damage, but the precise relationship between orientation and intermetallic (IMC) and void growth has not been deduced. In this research x-ray microtomography was used to nondestructively scan samples and generate 3D reconstructions of both surface and internal features such as interfaces, IMC particles, and voids within a solder joint. Combined with controlled fabrication techniques to create comparable samples and electron backscatter diffraction (EBSD) and energy-dispersive spectroscopy (EDS) analysis for grain orientation and composition analysis, this work shows how grain structure plays a critical role in EM damage and how it differs from damage accrued from thermal effects that occur simultaneously. Unique IMC growth and voiding behaviors are characterized and explained in relation to the solder microstructures that cause their formation and the possible IMC-suppression effects of trace alloying element addition are discussed.
ContributorsBranch Kelly, Marion (Author) / Chawla, Nikhilesh (Thesis advisor) / Ankit, Kumar (Committee member) / Antoniswamy, Aravindha (Committee member) / Arizona State University (Publisher)
Created2019