Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of a novel non‐volatile hybrid spintronic true random number generator

True random number generators (TRNGs) are mainly used in cryptographic applications for the generation of various keys. A standard CMOS‐based TRNG utilizes physical phenomena such as thermal noise, metastability, and oscillator jitter to generate fully non‐deterministic random outputs but has high power dissipation and a large overhead area. In this work, we develop a novel low power non‐volatile TRNG circuit that utilizes the inherent stochastic switching nature of magnetic tunnel junction (MTJ) as a randomness source. Thanks to the capabilities of MTJ and carbon nanotube field‐effect transistors (CNTFETs), the proposed TRNG circuit consumes low power when compared with conventional CMOS‐based TRNGs. The reliability of the proposed circuit is checked by running the corner case tests that considers all the process and environmental variations. The quality of the output bitstream is evaluated by running the twelve statistical randomness tests by the U.S National Institute of Standards and Technology (NIST). The circuit passes all the tests, meaning the output bit‐stream is truly random. The circuit is designed in such a way that, even if the power is turned off, the quality of the randomness is not affected. The proposed TRNG structure has a less complex design and generates truly random output.
FIRE & SMOKE DETECTION USING YOLO

A flame, whether tiny or enormous, is an unfavourable location, situation, or moment. Every location, in general, has the potential to encounter a fire. However, smoke sensors are currently the most extensively used instruments for detecting fires. Smoke sensors can only detect flames that are huge in size. As a result, a method to identify early fires is required. The basic equipment for this project is a laptop and a webcam, which will be used to design an image-based fire detection system. The approach for identifying fire using Neural Networks (YOLO).
Reinforcement Learning in the Intelligent Robot Control Task

The article describes an approach to reinforcement learning in the task of controlling an intelligent robot. The robot control system is built using the DJSM method. The DJSM method is a development of the JSM method, applicable in the case of an open world with an unknown number of examples in advance. The article deals with reinforcement learning for the movement of a wheeled robot along the black line on a limited polygon. The simulation of training in a software simulator is carried out. Examples of training results for various target functions are given. It is shown that the training work can be carried out in real time. The dependence of the learning outcomes on the initial conditions is revealed. The analysis of the obtained results is carried out.
Learner Autonomy: A Qualitative Inquiry into Indonesian Tertiary EFL Students' Voices

This study sought to explore Indonesian tertiary EFL students’ voices on learner autonomy. Specifically, it investigated the students’ conceptualization of the concept of learner autonomy, students’ perceptions of the benefits of learner autonomy, and their perceptions of the factors that hinder and support the development of learner autonomy. The study employed a qualitative design with a case study approach and involved 30 first-year students of two institutions of higher education in Jambi province, Indonesia. The data were collected using semi-structured interviews were analyzed using a thematic analysis following the steps proposed by Braun and Clarke (2006). The results revealed that the students had a limited understanding of the concept of learner autonomy. However, they believed that they would benefit from learner autonomy in terms of timing, learning effectiveness, and learning resources. The students also identified several hindering and supporting factors related to the development of learner autonomy. Practical implications for the Indonesian context are discussed.
Active Class Selection with Uncertain Class Proportions

Active class selection strategies actively choose the class proportions of the data with which a classiﬁer is trained. While this freedom of choice can improve the classiﬁcation accuracy and reduce the data acquisition cost, it has also motivated theoretical studies that quantify the limited trustworthiness of the resulting classiﬁer when the chosen class proportions diﬀer from the class proportions that need to be handled during deployment. In this work, we build on these theoretic foundations to propose an active class selection strategy that allows machine learning practitioners to express their prior beliefs about the deployment class proportions. Unlike existing approaches, our strategy is justiﬁed by PAC learning bounds and naturally supports any degree of uncertainty with respect to these prior beliefs.
Exploring the impact of silica and divalent cations on microbial iron respiration and secondary mineral products in Archean ocean simulations

Widespread chemical sedimentary deposits known as Banded Iron Formations (BIFs) archive Archean ocean chemistry and, potentially, traces of ancient microbial life. Microbial Fe(III) respiration likely influenced the mineralization of early BIF sediments. One hypothesis suggests that the early diagenetic bioreduction of primary iron oxides in BIFs resulted in the formation of other iron phases, including iron-rich silicates, carbonates, and magnetite common in BIF assemblages. Here, we simulated this proposed pathway in experimental/laboratory incubations of Shewanella putrefaciens CN32, a model iron-reducing bacterium, grown under conditions mimicking the predicted Archean seawater geochemistry. We examined the variability in the secondary mineral precipitates that formed in the presence or absence of calcium, magnesium, and dissolved silica to assess the impact of silica and divalent cations on the resultant mineral product. We analyzed the reduced mineral phases harvested from these experiments using Raman spectroscopy, electron microscopy, powder x-ray diffraction, and spectrophotometric techniques to identify mineral precipitates and track the distributions of Fe/Fe. We detected a diverse range of calcium carbonate morphologies and polymorphism in incubations with calcium. We also identified aggregates of wavy, ironand silica-rich, amorphous precipitates in all DIR incubations amended with silica. Our observations indicate that microbial iron reduction of ferrihydrite is a viable pathway for precursor iron silicate phases. This finding allows us to draw parallels between our experimental proto-silicates and the iron silicate nano-inclusions in BIF chert deposits, suggesting that early iron silicates could be signatures of iron-reducing metabolisms on early Earth.
Biasly: a machine learning based platform for automatic racial discrimination detection in online texts

Warning : this paper contains content that may 001 be offensive or upsetting. 002 Detecting hateful, toxic, and otherwise racist 003 or sexist language in user-generated online con-004 tents has become an increasingly important task 005 in recent years. Indeed, the anonymity, the 006 transience, the size of messages, and the dif-007 ficulty of management, facilitate the diffusion 008 of racist or hateful messages across the Inter-009 net. The critical influence of this cyber-racism 010 is no longer limited to social media, but also 011 has a significant effect on our society : corpo-012 rate business operation, users’ health, crimes, 013 etc. Traditional racist speech reporting chan-014 nels have proven inadequate due to the enor-015 mous explosion of information, so there is an 016 urgent need for a method to automatically and 017 promptly detect texts with racial discrimination. 018 We propose in this work, a machine learning-019 based approach to enable automatic detection 020 of racist text content over the internet. State-of-021 the-art machine learning models that are able 022 to grasp language structures are adapted in this 023 study. Our main contribution include 1) a large 024 scale racial discrimination data set collected 025 from three distinct sources and annotated ac-026 cording to a guideline developed by specialists, 027 2) a set of machine learning models with vari-028 ous architectures for racial discrimination de-029 tection, and 3) a web-browser-based software 030 that assist users to debias their texts when us-031 ing the internet. All these resources are made 032 publicly available.
Scalability of Encointer-a Proof-Of-Personhood Cryptocurrency

Encointer is a cryptocurrency using a novel consensus mechanism called ProofOf-Personhood which is based on people meeting physically at regular intervals in order to attest each other’s personhood. After having a digital identity which is provably linked to a real human being, each user receives a universal basic income in one of Encointer’s local community currencies. The protocol requires complex logic to be calculated on the blockchain like verifying geolocations or assigning users to meetups in order to guarantee the security of the system. To ensure Encointer’s scalability to a large number of users it is crucial that those computations are as efficient as possible which is not yet the case. In this thesis we present solutions to three major scalability problems of Encointer, evaluate them in terms of runtime and security and provide implementations that are ready to be merged into Encointer’s production system.
Exploring a Larger Search Space for Automatic Program Repair

Software engineering is an expensive economic activity, summing to over two percent of the US GDP annually. Software Maintenance accounts for over two-thirds of its life cycle cost, and a key aspect is bug-fixing. The process of fixing bugs is still a painful and time consuming task, as it requires a developer to understand the context of the bug, implement fixes and ensure that the fixed program works correctly, without introducing any new side effects. Automatic Program Repair (APR) techniques have been used to automatically fix bugs, helping developers save time in this process. These techniques are usually applied in three steps. The localization step identifies the locations of the program where a fix could be applied to (note that the faulty locations are not always the only good locations for fixes). The fix step generates fixes that modify the code (patch) in the locations returned by the previous step, and the validation step which checks if the modified program has repaired the program. In this work, we propose to improve the fix step through a search-based automated program repair technique that reuses code from the program under repair, as well as code that does not exist in the program but might useful in solving some classes of bugs. We implement this technique in a tool, Figra, that works by simply replacing code at the expression level, neither adding or deleting code. We evaluate Figra on three different benchmarks and compare it with the state-of-theart program repair techniques. Our evaluation shows that Figra outperforms and complements existing techniques on two of those benchmarks. Furthermore, Figra finds a patch to at least four unique buggy programs that have never been successfully automatically fixed in prior work.
Trophic Niche Dynamics and Diet Partitioning of King Crab Lithodes santolla in Chile’s Sub-Antarctic Water

The southern king crab Lithodes santolla is one of the most economically important fishery species in the southern waters of the Atlantic and Pacific Oceans. A combination of stomach content and stable isotope analyses was used to reveal the potential dietary characteristics, isotopic niche, overlap among maturity stages and sexes, and trophic relationships of an L. santolla population in the Nassau Bay, Cape Horn region. Stable isotope analyses indicated that L. santolla assimilated energy from a basal carbon source, the giant kelp Macrocystis pyrifera, forming the trophic baseline of the benthic food web. Moreover, the trophic position of L. santolla varied among late juveniles and adults, suggesting that the southern king crab does undergo an ontogenetic diet shift. L. santolla exhibited intraspecific isotopic niche variation, reflecting niche differentiation which allows the species to partition resources. The trophic relationships of L. santolla with the associated fauna suggested some potential interactions for food resources/habitat use when they are limited. This study is the first attempt to characterize the trophic dynamics of the southern king crab in the Cape Horn area and, by generating more data, contributes to the conservation of the king crab population and the long-term management of local fisheries that rely on this resource.
Evaluating a smoking cessation app by involving end-users and health insurance companies: a mixed method approach

Background mHealth has seen an increase in use in the past years. However, most mHealth applications are not widely implemented. The problem is two-fold: most mHealth evaluations only focus on effective outcomes and not on usability, as well as limited focus on financial incentives for potential investor stakeholders. The smoking cessation application Stopmaatje has been released in 2018 to the public and has not been met with wide implementation. Both user experience and stakeholder involvement have to be evaluated for positive implementation. A mixed-methods approach was used to gain insights into the user experience and the requirements for eHealth set by health insurance companies. Methods This thesis consisted of two studies: user experience and a stakeholder analysis. The user experience part consisted of a log data analysis, usage pattern analysis, and a questionnaire. Log data of 1336 participants were collected within the Stopmaatje application and 12 responses were gathered on the questionnaire. Descriptive analyses were used on the log data and questionnaire responses. The stakeholder analysis consisted of three semi-structured interviews with four participants. A qualitative analysis was done on the interviews based on the NASSS framework. Five codes were gathered. Data triangulation was executed to combine the results of both studies. Results The log data (n = 1336) showed that more than half of the users did not return to Stopmaatje after two sessions. Only 6.3% of the users were deemed as adherent. Adherent users mostly returned to the app to monitor their progress on their current cessation attempt. User experience scores on the questionnaire (n = 12) were overall positive. Respondents showed a positive behavioral intention to continue using the app, but this was not reflected in the log data analysis. The stakeholder analysis (n = 4) resulted in five themes: the condition, the technology, the value proposition, the organization, and the wider system. Health insurance companies showed interest in telemonitoring applications, reduction in current healthcare costs, and were more likely to implement eHealth if it had been endorsed by their overarching association. Conclusion Significant attrition was found, but no clear reasons for this attrition were found in the questionnaire. While there is a positive behavioral intention, this has not been translated into actual behavior yet. This points to an intention-behavior gap. Usage patterns can be used to support the uptake of Stopmaatje. The stakeholder analysis revealed different factors of interest for health insurance companies in eHealth. However, applications like Stopmaatje are not their top priority. Stopmaatje can create an interesting business case by adding efficiency to current smoking cessation treatments.
Camera-IMU Extrinsic Calibration Quality Monitoring for Autonomous Ground Vehicles

Highly accurate sensor extrinsic calibration is critical for data fusion from multiple sensors, such as camera and Inertial Measurement Unit (IMU) sensor suit. A pre-calibrated extrinsics, however, may no longer be accurate due to external disturbances, e.g., vehicle vibration, which will lead to significant performance deterioration of autonomous vehicles. Existing approaches rely on online recalibration at a fixed frequency regardless of whether the extrinsics have actually been changed or recalibration is needed, which is computationally inefficient. In this letter, we present an approach to monitor extrinsic calibration quality for camera-IMU sensor suite to determine when recalibration is actually necessary. We propose an efficient algorithm to detect robust road image features, utilize IMU data to capture the mismatches of those features, and quantify extrinsic calibration error through three commonly-used error metrics. Our algorithm is demonstrated to be effective using both simulated and real-world data.
Hybrid sabotage modal logic

We introduce a new hybrid modal logic HSML for reasoning about sabotage-style graph games with edge deletions, and provide a complete Hilbert-style axiomatization. We extend the completeness analysis to protocol models with restrictions on available edge deletions, and clarify the connections between HSML-style logics of edge deletions and recent modal logics for stepwise point deletion from graphs.
Three-dimensional Numerical Simulation of the Flow Characteristics at a Large Incidence of the Variable-geometry Power Turbine of a Marine Gas Turbine

By employing three-dimensional numerical simulation techniques a study was conducted of the flow field mechanism of the aerodynamic performance variation of a variable-geometry power turbine caused by the rotation of adjustable guide vanes. The results of the study indicate that within a range of relatively small turning angles the adjustable guide vanes designed by using a large turning angle will enable the turbine to operate at a large incidence.The three-dimensional separation flow field structure and its generation mechanism in the rotating cascade flow channel of an adjustable guide vane stage at a large positive incidence are very different from those of the same vane stage at a large negative incidence.Moreover,the suction-surface separation flow caused by a large positive incidence will significantly reduce the efficiency of the turbine as a whole.Through a systematic mechanismic analysis the authors have proposed the use of a rear loaded blade profile for the adjustable guide vanes using a relatively small turning angle and the adoption of an aerodynamic design principle under which a relatively large negative incidence is employed for the rotating cascade of the adjustable guide vane stage of the variable-geometry power turbine.
The measurement of productive efficiency : techniques and applications

This work focuses on measuring and explaining producer performance. The contributors to this volume view performance as a function of the state of technology and economic efficiency. They show that insights can be gained by allowing for the possibility of a divergence between the economic objective and actual performance, and by associating this inefficiency with causal variables subject to managerial or policy influence. The book is derived from a series of lectures held on techniques and applications of the three approaches to the construction of production frontiers and measures of efficiency. Available in OSO:
EVALUATION AND IMPROVEMENT OF PRE-PROCESSING TECHNIQUES FOR MULTIPLE-GAZE GEOMETRY RESEARCH

Multiple-gaze geometry, a research project from the Interdisciplinary Visual Intelligence Lab (IVI-LAB) at the University of Arizona, aims to gain an understanding of a 3D scene using a view from a single camera. The locations of points of interest in the scene are inferred by utilizing the intersection of the gazes of the people within it. This task requires several smaller pre-processing tasks to be run on the video data; in particular, people must be detected, along with their faces and key facial features. Currently, these pre-processing steps are performed with older code. Since new detection programs have been developed since the start of this project, there is value in examining how these programs can improve tracking results by providing better face and body detections. In this paper, I show the performance of these detectors on datasets that are being used with the multiple-gaze geometry tracker, and then compare the results visually and quantitatively to those from the currently used detection code. Through this research, I found that the program OpenPose can be used to obtain better body detections, but also that none of the software I tested for face detections outperform the one currently in use.
A Moderated Mediation Model of Empowering Leadership and Employees’ Innovative Work Behavior

This study examined the moderated mediation model of empowering leadership and employees’ innovative work behavior (IWB) by analyzing the mediating role of employees’ psychological empowerment and high-performance work system (HPWS). Using the convenience sampling technique, time-lagged data was collected from 433 software engineers working in different software companies operating in Pakistan. Hierarchical regression analysis and PROCESS macro were used to perform the analysis. The findings revealed that empowering leadership impacts employees’ IWB directly as well as through their psychological empowerment, while HPWS moderates the relationship between empowering leadership and employees’ psychological empowerment. The findings further articulated that the moderated mediation effects of HPWS also arbitrate between empowering leadership and employees’ IWB. The results of this study implied that when employees work in the context of a high HPWS, they reciprocate positively to the support and resources received from their leaders. Similarly, in the context of a high HPWS, empowering leadership greatly enhances employees’ psychological empowerment and creativity. In the context of a low HPWS, employees’ IWB depends upon their leaders’ behavior and also on their own psychological empowerment. Hence, the study analyzed when (contextual boundary conditions) and how (the underlying mechanism) empowering leadership enhances employees’ IWB by utilizing the moderated mediation model.
MARKETING INFORMATION SYSTEM AS A FACTOR OF MARKETING INFORMATION SYSTEM AS A FACTOR OF IMPROVMENT OF BUSINESS IMPROVMENT OF BUSINESS

It is no secret that the importance of information resources in the activities of enterprises is increasing today. At the first stage of the marketing information system, information from the external environment comes separately, and then is gradually systematized on the basis of the process of collecting and processing marketing information, which helps to solve the problems associated with the analysis and use of data in the enterprise. The main goal of the marketing information system in enterprises is to make available to the manager information about the state of the object under study and the processes taking place in the marketing environment.