Miracle-dz/UniFAR-FTUs huggingface dataset:
MODELING OF CELESTIAL ULTRAVIOLET SOURCES

Abstract : We have constructed models of the diffuse ultraviolet background radiation (zodiacal light; direct starlight; and starlight scattered from interstellar dust) for comparison with observations that were carried out with the UVISI instruments aboard the MSX spacecraft. We have written and implemented software for the reduction of the data from the four ultraviolet and visible imagers, and the five imaging spectrometers, collectively called UVISI, aboard the MSX spacecraft. We have examined the ultraviolet celestial backgrounds data that were produced during a partial survey of the sky, and we provide examples of the data, a guide to the software, and a map and listing of the sky survey, showing what portions of the sky survey were completed. We also provide a discussion of the science goals of the sky survey in the ultraviolet.
Understanding the Collaboration Difficulties Between UX Designers and Developers in Agile Environments

Author: Huang, Yun-Han. M.S. Institution: Purdue University Degree Received: August 2018 Title: Understanding the Collaboration Difficulties Between UX Designers and Developers in Agile Environments Major Professor: Mihaela Vorvoreanu With the growing number of UX designers in tech companies in the U.S., the collaboration between UX designers and developers in Agile environments has become a new challenge in the industry. This research study aims to understand the collaboration difficulties between UX designers and developers in Agile environments and further provides insights from the results. The research method was semi-structured interview. A total of five professional UX designers and five professional developers in the industry were interviewed about topics surrounding their collaboration difficulties. The results indicated that UX designers integrating in Agile environments and factors related of organizational context are the collaboration difficulties, and different mindsets between UX designers and developers and misunderstanding and ignorance of UX and UX designers are the causes of the collaboration difficulties. In the end, the author discussed some suggestions on achieving better collaboration and implications for developer education, UX, and Agile communities.
A Coordinating Control for Hybrid HVdc Systems in Weak Grid

A coordinating control strategy is proposed for a hybrid high voltage dc (HVdc) system comprising a capacitor commutated converter connected in series with a two-stage voltage source converter called “Vernier. ” This approach ensures that 1) the tap changers and switched capacitor banks are eliminated by Vernier controls that maintain constant firing angle and margin angle at the rectifier and inverter, respectively, and provide volt-VAr control at the commutation bus, and 2) improves the power flow recovery and risk of commutation failure following sever faults. To that end, a detailed switched model of hybrid-HVdc is built in EMTDC/PSCAD platform. For the frequency-domain analysis, a new nonlinear state-space averaged model is also developed and benchmarked against the detailed model. The steady-state operating characteristics of the proposed hybrid HVdc system are established. Finally, the effectiveness of the proposed approach is demonstrated for weak ac systems interfacing the rectifier and inverter sides. Improvement in commutation failure and power flow recovery following severe disturbances are also shown through case studies.
An Extended Delay Motivated On-Demand Routing Protocol for Cognitive Radio Based Wireless Mesh Networks

: In a mesh network topology, each node is connected to every other node in the network. A wireless mesh network (WMN) is a collection of radio nodes that are organized in a mesh topology. The wireless mesh network consists of – mesh clients, mesh routers, mesh gateway and mesh cloud. The mesh clients are the wireless devices connected via the mesh routers that forward traffic to and from the mesh gateway with an area of coverage called the mesh cloud. Wireless mesh networks can self-form and self-heal. Since all the clients are connected to one another, there is traffic congestion as only limited bandwidth is available for the large number of users. This can be solved by cognitive radio paradigm that enables spectrum sensing and management techniques there by effectively utilizing the available bandwidth. Delay motivated On-Demand Routing protocol (DORP) is a delay based protocol that combines several delay metrics to minimize the end-to-end delay. In this paper, an Extended Delay motivated On-Demand Routing Protocol (E-DORP) is proposed and implemented on wireless sensor networks like random and mesh networks. The tool used here to implement E-DORP is Network Simulator (NS2).
A Teaching Method for Software Measurement Process based on Gamification

Abstrac t—The value of an effective measurement program lies in the ability to control and predict what can be measured. Thus, the measurement program has the capacity to provide a basis in decision-making to support the interests of an organization. This means it is only possible to run an effective measurement program with a team of software engineers who are well trained in this area. However, as the literature shows, there are few computer science courses that include the teaching of software process measurement in their program. Even these, generally only discuss the basic theoretical concepts of this process with little or no measurement in practice, which discourages the students from’s learning the measurement process. In this context, according to some experts in software process improvement, one of the most widely used approaches to maintaining the motivation and commitment to improving the program, is the use of gamification. In light of this, the aim of this paper is to set out a proposal for teaching the gamification measurement process. This seeks to improve student motivation and performance in carrying out tasks related to software measurement, by incorporating elements from games into the measurement process, and thus making it more attractive for learning.
Prediction of Winning Team using Machine Learning

—Machine learning (ML) is one of the intelligent techniques. It has shown optimistic results in the field of classification and prediction accuracy. Sports Prediction is one of the expanding areas in good predictive accuracy as it involves huge money in betting. Since football is an interesting area of research, it is regarded as complex and dynamic when compared to other sports. It is the most widely played sport and currently being played in more than 190 countries. In this paper, prediction of winning team in English Premier League (EPL) is implemented using Machine Learning techniques. The objective is to predict the full time result (FTR) of the football match, which decides the winning team. We implement algorithms viz. Support Vector Machines, Random Forest and Naïve Bayes for training the data and the one that gives the maximum and best accuracy will be used for predicting the winning team. The dataset used were gathered from [6] for the past seasons.
Improving visibility of test results for continuous integration and delivery pipeline : case: Liaison ALLOY platform development

Tampereen ammattikorkeakoulu Tampere University of Applied Sciences Master’s Degree In Information Technology Riku Halonen Improving Visibility of Test Results for Continuous Integration and Delivery Pipeline CASE: Liaison ALLOY Platform Development Master's thesis 43 pages, appendices 2 pages November 2017 In the modern software development cycle; testing, releasing and deploying software continuously has become an important factor of the process. Equally important is to be able to see the test reports from any given phase of the process, proving that the functionality and the over quality requirements of software product are met. Feedback in the form of test reports generated from automated tests part of the continuous integration and delivery pipeline help to react on possible defect immediately. Test reports are also an important part of the release documentation. To be able track the quality of software continuously and the deviation between software builds, releases and deploy environments; results and other artifacts captured from automated tests has to be persisted in a centralized database or repository. This enables to create different views to data, such as reports and dashboards. This thesis addresses the need of capturing test results, possibly different formats, from continuous delivery pipeline to enable fast feedback for the project teams as well as reporting to different project stakeholders and to supplement release documentation. The work is carried out for Liaison Technology Oy as part of the ALLOY integration and data management platform project. The goal is to improve the visibility of test result captured from continuous integration pipeline, so that it is easy to see status of projects’ quality. The output and result from thesis is a design of a web service that provides upload and persisting of test results from deployment pipelines as well as queries over data the stored result.
Survey on a Keyword-Based Retrieval of Data on DHT Networks

— Many Peer-to-Peer systems nowadays support the subscription function for past offering the amply used keyword search function. For example, Vuze allows peers to create subscription filters based on the keyword search. New documents or related data will be delivered to the peers whenever new episodes are available for given the subscription. Unsuccessfully, these applications suffer from the downsides, for example, high network traffic in the hubs keeping putative terms. In this paper, we propose the MTAF mechanism to outrival the issues. The key of MTAF is to incautiously select a subgroup of terms sans incurring false negatives and to send the data item sheepish the home hubs of such picked terms for low data forwarding cost. Experimental outputs based on real datasets indicate that the proposed solutions are operational compared to current approaches.
COABRA: collaborative secured auditing with privacy preservation policy on group shared data in cloud based digital repositories

Cloud storage services like digital repositories, allow users to store and share data across multiple users within a group. However it is always a big time challenge to conserve the integrity of the data stored, due to the high probability of inevitable hardware and software failures. The Third Party Auditor (TPA) is allowed to verify the integrity of the data ie checking correctness of the data. There are many challenges during auditing process, mainly privacy issue. Another prevailing challenge is to achieve high degree of access control and traceability along with extensive abstraction to preserve privacy.This proposal provides solution for this privacy preserving issue by Hol-omorphic Circle Sign (HCS) method without revealing the identity of signer where the signer is one of the group members. Also provides Random Combination Block (RCB) method to audit random combination of encoded data rather than actual data. RCB method provides reduced data transmission and avoids decoding/recalculation process.The proposal also support public auditing on regenerated data which is used for providing reliability on shared data and prompt traceability mechanism that tracks.
Comparative Evaluation of Background Subtraction Algorithms for High Performance Embedded Systems

— Background Subtraction technique is widely used in surveillance systems to identify moving objects. Although color features have been extensively used in several background subtraction algorithms, demonstrating high efficiency and performances, in actual real-time applications the background subtraction performance is still a challenge due to high computational requirements. In this paper, two approaches and their optimized versions are evaluated to implement high-performance background subtraction algorithms for real-time applications. Gaussian Mixture Model and the Multimodal Background Subtraction are characterized by two different color descriptors: Gray scale and H color invariant combined with Gray scale information respectively. Different experimental analysis allows evaluating the efficiency in terms of computational complexity and accuracy for outdoor and indoor environments. Experimental tests demonstrated that the Multimodal Background Subtraction approach with its variants is established as affordable for real-time applications and particularly suitable on hardware platforms with on-board memory and limited computational resources.
Association of Interleukin-10 Cytokine Expression Status with HLA Non-DRB1*02 and Mycobacterium bovis BCG Scar-Negative Status in South Indian Pulmonary Tuberculosis Patients

HLA DRB1*02 and its subtypes predispose individuals for a far-advanced sputum-positive pulmonary tuberculosis transcending ethnic boundaries. Mycobacterium bovis BCG does not afford the desired protection against adult pulmonary tuberculosis, and a spectrum of immune reactivity exists in controls and hospital contacts. All of these ﬁndings have been identiﬁed and demonstrated in areas of endemicity. Skewing of immunity from protective to pathogenic may involve a shift in the Th1-Th2 paradigm. To elaborate these ideas, we studied gamma interferon (IFN- g ), interleukin-4 (IL-4), and IL-10 cytokine expression in 71 adult pulmonary tuberculosis patients and 74 controls from areas of endemicity in south India by 48-h microculture and reverse transcription-PCR. Most of the patients and controls expressed IFN- g de novo, and in the presence of puriﬁed protein derivative (PPD), all of them expressed signiﬁcantly higher levels of IFN- g , suggesting a PPD-speciﬁc recall memory. HLA DRB1* allele-dependent IFN- g expression was identiﬁed only in controls, suggesting a skewing of the immune response in patients. In contrast to the case for IFN- g , only some patients and controls expressed IL-4 or IL-10 (Th2 proﬁle); thus, the Th1 proﬁle was identiﬁable only by a nonexpres- sion of IL-4 or IL-10 in this area of endemicity. The Th2 proﬁle was associated with HLA non-DRB1*02 and BCG scar-negative status in patients, attributing a signiﬁcant risk (odds ratio 5 2.074; 95% conﬁdence interval 5 0.612 to 7.07). It is possible that Mycobacterium tuberculosis (PPD)-speciﬁc IL-10 is expressed preemptively in unvaccinated (BCG scar-negative) individuals with a non-DR2 genetic background by chronic exposure in this area of endemicity and leads to pulmonary tuberculosis of adults.
Grazing of Reed Canarygrass (Phalaris arundinacea) in Restored Wet Meadows

ABSTRACT Reed canarygrass (Phalaris arundinacea) is a grass species that can dominate wet meadow plant communities. This study investigated if grazing by cattle on restored wet meadows suppresses reed canarygrass, thereby promoting the restored plant community. This study was conducted at two locations in northwest Minnesota, one managed by The Nature Conservancy (TNC) and the other a Minnesota Board of Water and Soil Resources (BWSR) wetland bank site. Management practices used were a patch-burn grazing treatment on the TNC site and a high-density, short-duration grazing rotation system on the BWSR site. A pretreatment survey of total species canopy coverage was conducted before grazing followed by periodic surveys up to 7 y after grazing started. Both the patch-burn grazing and the grazing rotation system reduced reed canarygrass canopy cover by 49% compared to non-grazed control sites 5–7 y after grazing. With a reduction in reed canary grass canopy coverage due to grazing, the plant community moved toward a community with higher canopy coverage of Carex pellita that met restoration goals. Some of the species change was to grasses like Kentucky bluegrass (Poa pratensis), which is an exotic, invasive grass in prairies. The changed plant community held steady in native plant species richness or had an increase in native plant species richness. This study demonstrates grazing reduces the cover of reed canarygrass, while meeting restoration goals for wet meadows.
Emojis and conditionals: exploring the super linguistic interplay of pictorial modifiers and conditional meaning

Abstract In recent years, formal linguistic analysis has expanded its scope to include objects of study beyond natural language, under the umbrella of Super Linguistics (where the intended meaning of super is its Latinate meaning ‘beyond’); see (Patel-Grosz et al. 2022. Super linguistics: An introduction. Unpublished manuscript, April 2022 version. Available at: https://ling.auf.net/lingbuzz/005242). One super linguistic object of study is emojis, which can be analyzed as digital counterparts of gestures and facial expressions, but which also share properties with natural language expressions such as alas and unfortunately (Grosz, Patrick Georg, Gabriel Greenberg, Christian De Leon & Elsi Kaiser. 2021b. A semantics of face emoji in discourse. Manuscript, December 2021 version. https://ling.auf.net/lingbuzz/005981 (Accepted with minor revisions for publication in Linguistics and Philosophy)). In this paper, I use conditionals as a case study to argue that natural language semantics can benefit from investigating the semantics of emojis. I start by arguing that face emojis (disk-shaped pictographs with stylized facial expressions) operate on contextually salient propositions. I show that they can comment on the presuppositions of wh-questions and definite descriptions, but not on conversational implicatures. I then show that face emojis can also comment on the counterfactual inferences of subjunctive conditionals (or, more broadly, subjunctive if-clauses). This suggests that these counterfactual inferences may be presupposition-like and not, as widely assumed, an instance of implicature (see Zakkou, Julia. 2019. Presupposing counterfactuality. Semantics and Pragmatics 12(21). 1–20, for recent discussion). The study of emojis, a nonstandard object for linguistic inquiry, can thus directly inform more traditional linguistic exploration.
Antimicrobial and antioxidant activity of methanol extract of Echinophora spinosa L. from Jijel, Algeria

In this study, the antioxidant and antimicrobial activities of Echinophora spinosa were investigated. Antimicrobial activity of methanol extracts obtained from Echinophora spinosa was examined using the disc diffusion method. Antioxidant activity of the methanol extracts was examined using the stable 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging test. Methanol extract of ripe fruits of E. spinosa showed highest total phenolic content (69.17 ± 1.2 µg GAE/mg extract) and the major flavonoid contents (12.122 ± 0.44 µg QE/mg extract) was found in leaves of the plant. In disk diffusion antimicrobial assay, E. spinosa manifested broad spectrum of activity. The largest capacity to neutralize DPPH radicals was found for ripe fruits methanol extract of E. spinosa plant. The results shows that the various parts of E. spinosa extracts promising antioxidant and antimicrobial activities have potential bioactivities due to high content of phenolic and flavonoid compounds.
Deflection of Wide Hidden Beams in One-Way Slab Systems: A Nonlinear Finite Element Study

—The effectiveness of compression reinforcement in controlling the deflection of a wide-hidden continuous reinforced concrete beam is studied using nonlinear finite element (FE) simulations. Concrete Damaged-Plasticity and reinforcing steel Elasto-Plasticity are used in the nonlinear FE simulations of ABAQUS. Results are compared to Elastic FE simulations as well as to conventional code procedures.
Topological order in Gutzwiller-projected wave functions for quantum antiferromagnets

We study the topological order in RVB state derived from Gutzwiller projection of BCS-like mean field state. We propose to construct the topological excitation on the projected RVB state through Gutzwiller projection of mean field state with inserted $Z_{2}$ flux tube. We prove that all projected RVB states derived from bipartite effective theories, no matter the gauge structure in the mean field ansatz, are positive definite in the sense of the Marshall sign rule, which provides a universal origin for the absence of topological order in such RVB state.
A Hybrid of Copula Prediction and Time Series Computation to Estimate Stream Discharge Based on Precipitation Data

Stream discharge is a key hydrological factor for water supply planning, wetland loss investigation, ecological service assessment, and climate change impact estimation. Conceptually, stream discharge is expected to be highly and positively related to precipitation. In reality, however, such a relationship may be weaker because precipitation characteristics are affected by local climate of watersheds. For many watersheds around the world, a vast amount of precipitation data are readily available but the stream discharge data are very limited or unavailable. It would be time‐saving and cost‐effective to predict stream discharge based on precipitation data. Unfortunately, this task is very difficult to achieve using the traditional methods. Although the copula method is able to establish a good relationship (or a good dependence structure) between discharges and precipitations, this relationship does not include the time series process, and thus is impractical for applications. Therefore, a hybrid of copula prediciton and time series computation was developed (with detailed procedures) here to estimate stream discharge based on precipitation data. The method was validated using the measured daily discharges with the good statistical measures, that is, the Kandell’s τ (0.42–0.44), normalized root mean square error (2.19–2.28 m3/s), and R2 (0.66–0.84). This study suggests that the hybrid method is a useful tool to predict stream discharges based on precipitation data.
Diffeomorphic Neural Surface Parameterization for 3D and Reflectance Acquisition

This paper proposes a simple method which solves the problem of multi-view 3D reconstruction for objects with unknown and generic surface materials, imaged by a freely moving camera and lit by a freely moving point light source. The object can have arbitrary (diffuse or specular) and spatially-varying surface reflectances. Our solution consists of two small-sized neural networks (dubbed the ‘Shape-Net’ and ‘BRDF-Net’), used to parameterize the unknown shape and material map as functions on a canonical surface (e.g. unit sphere). Key to our method is a velocity field shape representation that drives the canonical surface to target shape through time. We show this parameterization can be implemented as a recurrent residual network that is guaranteed to be diffeomorphic and orientation-preserving. Our method yields an exceptionally clean formulation that can be optimized by standard gradient descent without initialization, and works with both near-field and distant light source. Synthetic and real experiments demonstrate the reliability and accuracy of our reconstructions, with extensions including novel-view-synthesis, relighting and material retouching done with ease. Our source codes are available at https://github.com/za-cheng/DNS.
On quasi-Einstein almost hyperbolic Hermitian manifold with quasi-constant curvature

In 1954 almost hyperbolic Hermitian manifold introduced by P. Libermann were classified for the first time in 1988 by C. L. Bejan. Recently in 1998 C. L. Bejan and L. Ornea constructed an example of an almost hyperbolic Hermitian manifold. Object of present paper is to study properties of quasi-Einstein almost hyperbolic Hermitian manifold with quasi-constant curvature.