Welcome to the UA Campus Repository, a service of the University of Arizona Libraries. The repository shares, archives and preserves unique digital materials from faculty, staff, students and affiliated contributors. Contact us at email@example.com with any questions.
- Dissertations from the Indigenous Peoples Law and Policy Program are now available in the repository.
- The latest volume of Desert Plants, a special issue called Thirty-Seven Years on a Mountain Trail: Vascular Flora and Flowering Phenology of the Finger Rock Canyon Watershed, Santa Catalina Mountains, Arizona.
- New geologic maps and data from the Arizona Geological Survey Document Repository.
- A report on the Research Practices of Indigenous Studies Scholars at the University of Arizona.
- Honors College Theses from Fall 2018 graduates.
- Proceedings from the 2018 Critical Librarianship and Pedagogy Symposium.
Communities in the UA Campus Repository
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Assessing livelihood-ecosystem interdependencies and natural resource governance in Indian villages in the Middle Himalayas(SPRINGER HEIDELBERG, 2019-01)Mountains host high biological and cultural diversity, generating ecosystem services providing benefits over multiple scales but also suffering significant poverty and vulnerabilities. Case studies in two contrasting village communities in the Indian Middle Himalayas explore linkages between people and adjacent forest and river ecosystems. Interviews with local people and direct observations revealed low food availability and decreasing self-sufficiency, under the combined pressures of increasing foraging by wildlife (primarily pigs and monkeys) coupled with seasonal to permanent outmigration by younger men seeking more secure income and alternative livelihoods. Much of the income remitted by migrants to their villages was not retained locally but flowed back out of the Himalayan region through purchases of food produced and marketed in the plains. This threatens the economic viability of villages, also placing asymmetric pressures on resident female, elderly and young people who concentrate labour on local livestock production to the neglect of crop agriculture, further compounding land abandonment and wildlife foraging. Significant traditional knowledge remains, along with utilitarian, cultural and spiritual connections with the landscape. Many beneficiaries of locally produced ecosystem services are remote from village communities (particularly water flows downstream to the plains), but no recompense is paid to stewards of the forested Himalayan landscape. Although local people currently perceive high biodiversity as a constraint to agriculture and other economic activities, the Himalayan landscapes could potentially constitute an asset with appropriate institutional development through promotion of managed bioprospecting, guided ecotourism and payment for ecosystem services (PES) schemes for water supply and under REDD+.
Orbifolds of lattice vertex operator algebras at d = 48 and d = 72(ACADEMIC PRESS INC ELSEVIER SCIENCE, 2019-04-01)Motivated by the notion of extremal vertex operator algebras, we investigate cyclic orbifolds of vertex operator algebras coming from extremal even self-dual lattices in d = 48 and d = 72. In this way we construct about one hundred new examples of holomorphic VOAs with a small number of low weight states. (C) 2019 Elsevier Inc. All rights reserved.
Girth-Eight Reed-Solomon Based QC-LDPC Codes(IEEE, 2018)This paper presents a class of regular quasi-cyclic (QC) LDPC codes whose Tanner graphs have girth at least eight. These codes are constructed based on the conventional parity-check matrices of Reed-Solomon (RS) codes with minimum distance 5. Masking their parity-check matrices significantly reduces the numbers of short cycles in their Tanner graphs and results in codes which perform well over the AWGN channel in both waterfall and low error-rate regions.
A LiDAR Error Model for Cooperative Driving Simulations(IEEE, 2018)Cooperative driving and vehicular network simulations have done huge steps toward high realism. They have become essential tools for performance evaluation of any kind of vehicular networking application. Yet, cooperative vehicular applications will not be built on top of wireless networking alone, but rather fusing together different data sources including sensors like radars, LiDARs, or cameras. So far, these sensors have been assumed to be ideal, i.e., without any measurement error. This paper analyzes a set of estimated distance traces obtained with a LiDAR sensor and develops a stochastic error model that can be used in cooperative driving simulations. After implementing the model within the PLEXE simulation framework, we show the impact of the model on a set of cooperative driving control algorithms.
Detecting Cyber Threats in Non-English Dark Net Markets: A Cross-Lingual Transfer Learning Approach(IEEE, 2018)Recent advances in proactive cyber threat intelligence rely on early detection of cyber threats in hacker communities. Dark Net Markets (DNMs) are growing platforms in hacker community that provide hackers with highly specialized tools and products which may not be found in other platforms. While text classification techniques have been used for cyber threat detection in English DNMs, the task is hindered in non-English platforms due to the language barrier and lack of ground-truth data. Current approaches use monolingual models on machine translated data to overcome these challenges. However, the translation errors can deteriorate the classification results. The abundance of data in English DNMs can be leveraged in learning non-English threats without using machine translation. In this study, we show that a deep cross-lingual model that can jointly learn the common language representation from two languages, significantly outperforms a monolingual model learned on machine translated data for identifying cyber threats in non-English DNMs. Unlike most studies, our approach does not require any external data source such as bilingual word embeddings or bilingual lexicons. Our experiments on Russian DNMs show that this approach can achieve better performance than state-of-the-art methods for non-English cyber threat detection in malicious hacker community.