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1. Improved Geometric Optics with Topography (IGOT) Model for GNSS-R Delay-Doppler Maps Using Three-Scale Surface Roughness

   https://doi.org/10.3390/rs15071880  

   Melebari, Amer; Campbell, James D.; Hodges, Erik; Moghaddam, Mahta (April 2023, Remote Sensing)

   Although multiple efforts have been made to model global navigation satellite system (GNSS)-reflectometry (GNSS-R) delay-Doppler maps (DDMs) over land, there is still a need for models that better represent the signals over land and can enable reliable retrievals of the geophysical variables. Our paper presents improvements to an existing GNSS-R DDM model by accounting for short-wave diffraction due to small-scale ground surface roughness and signal attenuation due to vegetation. This is a step forward in increasing the model fidelity. Our model, called the improved geometric optics with topography (IGOT), predicts GNSS-R DDM over land for the purpose of retrieving geophysical parameters, including soil moisture. Validation of the model is carried out using DDMs from the Cyclone GNSS (CYGNSS) mission over two validation sites with in situ soil moisture sensors: Walnut Gulch, AZ, USA, and the Jornada Experimental Range, NM, USA. Both the peak reflectivity and the DDM shape are studied. The results of the study show that the IGOT model is able to accurately predict CYGNSS DDMs at these two validation sites. 

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2. Key Factors Affecting User Adoption of Open-Access Data Repositories in Intelligence and Security Informatics: An Affordance Perspective

   https://doi.org/10.1145/3460823  

   Wen, Bo; Hu, Paul Jen-Hwa; Ebrahimi, Mohammadreza; Chen, Hsinchun (March 2022, ACM Transactions on Management Information Systems)

   Rich, diverse cybersecurity data are critical for efforts by the intelligence and security informatics (ISI) community. Although open-access data repositories (OADRs) provide tremendous benefits for ISI researchers and practitioners, determinants of their adoption remain understudied. Drawing on affordance theory and extant ISI literature, this study proposes a factor model to explain how the essential and unique affordances of an OADR (i.e., relevance, accessibility, and integration) affect individual professionals' intentions to use and collaborate with AZSecure, a major OADR. A survey study designed to test the model and hypotheses reveals that the effects of affordances on ISI professionals' intentions to use and collaborate are mediated by perceived usefulness and ease of use, which then jointly determine their perceived value. This study advances ISI research by specifying three important affordances of OADRs; it also contributes to extant technology adoption literature by scrutinizing and affirming the interplay of essential user acceptance and value perceptions to explain ISI professionals' adoptions of OADRs. 

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3. Data sharing and ontology use among agricultural genetics, genomics, and breeding databases and resources of the Agbiodata Consortium

   https://doi.org/10.1093/database/baad076  

   Clarke, Jennifer L; Cooper, Laurel D; Poelchau, Monica F; Berardini, Tanya Z; Elser, Justin; Farmer, Andrew D; Ficklin, Stephen; Kumari, Sunita; Laporte, Marie-Angélique; Nelson, Rex T; et al (January 2023, Database)

   Abstract Over the last couple of decades, there has been a rapid growth in the number and scope of agricultural genetics, genomics and breeding databases and resources. The AgBioData Consortium (https://www.agbiodata.org/) currently represents 44 databases and resources (https://www.agbiodata.org/databases) covering model or crop plant and animal GGB data, ontologies, pathways, genetic variation and breeding platforms (referred to as ‘databases’ throughout). One of the goals of the Consortium is to facilitate FAIR (Findable, Accessible, Interoperable, and Reusable) data management and the integration of datasets which requires data sharing, along with structured vocabularies and/or ontologies. Two AgBioData working groups, focused on Data Sharing and Ontologies, respectively, conducted a Consortium-wide survey to assess the current status and future needs of the members in those areas. A total of 33 researchers responded to the survey, representing 37 databases. Results suggest that data-sharing practices by AgBioData databases are in a fairly healthy state, but it is not clear whether this is true for all metadata and data types across all databases; and that, ontology use has not substantially changed since a similar survey was conducted in 2017. Based on our evaluation of the survey results, we recommend (i) providing training for database personnel in a specific data-sharing techniques, as well as in ontology use; (ii) further study on what metadata is shared, and how well it is shared among databases; (iii) promoting an understanding of data sharing and ontologies in the stakeholder community; (iv) improving data sharing and ontologies for specific phenotypic data types and formats; and (v) lowering specific barriers to data sharing and ontology use, by identifying sustainability solutions, and the identification, promotion, or development of data standards. Combined, these improvements are likely to help AgBioData databases increase development efforts towards improved ontology use, and data sharing via programmatic means. Database URL https://www.agbiodata.org/databases 

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4. An empirical study of task infections in Ansible scripts

   https://doi.org/10.1007/s10664-023-10432-6  

   Rahman, Akond; Bose, Dibyendu Brinto; Zhang, Yue; Pandita, Rahul (January 2024, Empirical Software Engineering)

   Feldt, Robert; Zimmermann, Thomas (Ed.)

   Context Despite being beneficial for managing computing infrastructure at scale, Ansible scripts include security weaknesses, such as hard-coded passwords. Security weaknesses can propagate into tasks, i.e., code constructs used for managing computing infrastructure with Ansible. Propagation of security weaknesses into tasks makes the provisioned infrastructure susceptible to security attacks. A systematic characterization of task infection, i.e., the propagation of security weaknesses into tasks, can aid practitioners and researchers in understanding how security weaknesses propagate into tasks and derive insights for practitioners to develop Ansible scripts securely. Objective The goal of the paper is to help practitioners and researchers understand how Ansible-managed computing infrastructure is impacted by security weaknesses by conducting an empirical study of task infections in Ansible scripts. Method We conduct an empirical study where we quantify the frequency of task infections in Ansible scripts. Upon detection of task infections, we apply qualitative analysis to determine task infection categories. We also conduct a survey with 23 practitioners to determine the prevalence and severity of identified task infection categories. With logistic regression analysis, we identify development factors that correlate with presence of task infections. Results In all, we identify 1,805 task infections in 27,213 scripts. We identify six task infection categories: anti-virus, continuous integration, data storage, message broker, networking, and virtualization. From our survey, we observe tasks used to manage data storage infrastructure perceived to have the most severe consequences. We also find three development factors, namely age, minor contributors, and scatteredness to correlate with the presence of task infections. Conclusion Our empirical study shows computing infrastructure managed by Ansible scripts to be impacted by security weaknesses. We conclude the paper by discussing the implications of our findings for practitioners and researchers. 

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5. Direct Digital Subtractive Manufacturing of Functional Assemblies Using Voxel-Based Models

   144. Lynn, R. (November 2017, Journal of manufacturing science and engineering)

   Direct digital manufacturing (DDM) is the creation of a physical part directly from a computer-aided design (CAD) model with minimal process planning and is typically applied to additive manufacturing (AM) processes to fabricate complex geometry. AM is preferred for DDM because of its minimal user input requirements; as a result, users can focus on exploiting other advantages of AM, such as the creation of intricate mechanisms that require no assembly after fabrication. Such assembly free mechanisms can be created using DDM during a single build process. In contrast, subtractive manufacturing (SM) enables the creation of higher strength parts that do not suffer from the material anisotropy inherent in AM. However, process planning for SM is more difficult than it is for AM due to geometric constraints imposed by the machining process; thus, the application of SM to the fabrication of assembly free mechanisms is challenging. This research describes a voxel-based computer-aided manufacturing (CAM) system that enables direct digital subtractive manufacturing (DDSM) of an assembly free mechanism. Process planning for SM involves voxel-by-voxel removal of material in the same way that an AM process consists of layer-by-layer addition of material. The voxelized CAM system minimizes user input by automatically generating toolpaths based on an analysis of accessible material to remove for a certain clearance in the mechanism's assembled state. The DDSM process is validated and compared to AM using case studies of the manufacture of two assembly free ball-in-socket mechanisms. 

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