Miracle-dz/UniFAR-FTUs huggingface dataset:
Reinforcement Learning agents playing Hearthstone: The influence of state description when learning in a large, partially observable state space

: Many real world problems cannot be easily formalized into compact states that fully describe the real state of the world. It is thus important to look at how di(cid:11)erent ways of representing a state would in(cid:13)uence the performance of AI agents. In this research we compare the performance of reinforcement learning agents which learn using di(cid:11)erent game state representations when playing "Hearthstone", an online collectible card game which has a state space size much larger than complex games such as Chess. Moreover, its states are only partially observable by the player and randomness governs over certain events. It is found that, when playing with very simple decks that do not require complex strategies, agents which have a simpler state description have a win rate of about 81% against a random player, whereas agents which have a larger state description only win 78% of the time regardless of the learning algorithm used. However, when playing with more complex decks that require synergistic actions in order to maximize their performance, agents with a simpler state description performed worse than before while the agents with larger state descriptions performed better with win rates of 88% against a random agent.
Frequency of diabetes, complications and vascular risk factors in male and female population of Al-Jouf, Saudi Arabia

Background: Diabetes is prevailing worldwide. This study aimed to estimate the frequency of diabetes, its complications, and relevant risk factors for the years 2014–2017 in Al Jouf, Saudi Arabia. Methodology: Three years of patient data were extracted from Diabetes Centre electronic database to deter-mine patient’s type of diabetes and complications associated with diabetes. Risk factors such as hypertension, smoking, hyperlipidemia, and body mass index (BMI) were also recorded. Results: Seven hundred eighty-five ( n = 785) patients data were included in the study, with a mean age of 52 ± 12 years and age range of 13–101 years. Among all, 58% were males and 93% were type 2 diabetics. Regardless of age and gender, there were 76% of the participants who were not having any complications. No significant association was observed between gender and diabetic complication in study population. More than one-third of the study participants were hypertensive and two-third had high blood lipids. Overall mean HbA1c and BMI were found above the normal limits (HbA1c < 6.5%; BMI < 25 kg/m 2 ) in both male and female subjects. A significant statistical difference was observed between males and females for HbA1c, BMI, serum creatinine, total cholesterol, and high-density lipoprotein. Conclusion: The majority of patient did not present with diabetic complications. However, study results suggested that elevated HbA1c and BMIs are quite prevalent among the study population and need to be addressed using patient education and awareness strategy.
Information and Legal Aspects of Economic Development in the Conditions of COVID-19

The main purpose of the study is to analyze the features of information and legal aspects of economic development in the context of COVID-19. Problems of ensuring sustainable economic development at the state, regional and local levels require immediate solutions. This is especially true of the economic and legal support of urban management and management, the effective implementation of the functions of planning, financing, investing in urban development, increasing the profitability of the city budget, efficient use of communal property, the introduction of resource-saving technologies, and support for the effective functioning of enterprises and organizations of the urban economy. whose activities directly depend on the growth of the quality of life of the territorial community. As a result of the analysis, a study was carried out of the main information and legal aspects of economic development in the context of COVID-19.
CHEMOPREVENTIVE MOLECULES OF COFFEE AND BENEFICIAL METABOLIC EFFECTS

Among all the plant species examined, together with the food products that derive from it, coffee has a reputation that over the course of history has had a rather controversial evolution: some episodes are emblematic of the mistrust that, in the first decades of its diffusion in Europe and in the World, accompanied the drink. Coffee is obtained by infusing the powder obtained by grinding the toasted seeds of some species of tropical shrubs belonging to the genus Coffea, practiced through various techniques; although there are over 100 species, those used for food consumption are very few, and almost all of the market is aimed at only two of them: Coffea arabica and Coffea canephora , better known commercially (but improperly) with the name of Robusta. Today it can be said that the antioxidant activity of coffee, intended both as a vegetable and as a drink, has been known for some time and has been evaluated through different methods; various studies have shown that the high content of polyphenols in coffee plays an important role in its strong antioxidant action. Since 1997, the year in which the first works on this activity were presented, the concern about the potential risks related to coffee intake has rapidly diminished and a line of research has originated aimed at evaluating its therapeutic effects, especially chemopreventive, antidiabetic and anticarginogenic effects. It was immediately proposed that, at the head of the wide family of active polyphenolic compounds, there were chlorogenic acids, whose remarkable ability to prevent oxidative cell damage was immediately determined.
Design and Development of an Exoskeleton Prototype Arm Utilising Electromyography

Individuals who lack or have significant difficulties utilizing their arms and hands may benefit from having an exoskeletal arm to gain some independence in their daily lives. This paper outlines the design and implementation of a prototype electro-mechanical arm. The mechanisms utilised cable drawn pulleys to provide controlled angles 3degrees of freedom (DOF) for index, middle and ring and the shoulder. The elbow has a single DOF. The aim was to build a prototype, wearable prosthetic mechanism for the whole arm that could perform some basics daily tasks. Furthermore, it was intended the prosthetic mechanisms assist with some physiotherapy activities which might be helpful for individuals with muscle degenerative diseases. The arm was controlled by either utilising electromyography (EMG) signals recorded by placing sensors on the arm or by utilising a Joystick Interface. The actuation of its DC motors was programmed to reflect the user's muscle activities and to allow the user to control the modules smoothly and accurately. A Graphical 3D animation was implemented in MATLAB Simulink to demonstrate the arms’ operation while the hardware was interfaced through LabVIEW. The components were designed in Solidworks and 3D printed. The prosthetic mechanism was able to lift object up to 2 kg. The mechanism provided accurate position control for moving objects and physiotherapy. The basic daily activity of drinking was achieved however this required development.
Un algoritmo genético para sintonización de una estructura de control mpc (dmc) aplicado a una planta de presión

The development of genetic algorithm AG for tuning predictive control strategy known as Dynamic Matrix Control (DMC) to a prototype pressure plant is presented, the genetic algorithm to find the best parameters according to the minimizing performance indices. The superiority of DMC compared with conventional techniques such as PI internal model control (IMC) is also shown, the benefits are determined from performance indexes obtained with the implementation of both controllers in the system. The benefits of working with the evolutionary techniques and between the AG for tuning control systems that lack a thorough study of the influence of the tuning parameters on their responses are discussed.
Online randomised trials with children: A scoping review protocol

Abstract Introduction: This scoping review will determine how online, randomised trials with children are conducted. The objectives of the review are: (a) to determine what methods and tools have been used to create and conduct online trials with children and (b) to identify the gaps in the knowledge in this field. Over the last decade, randomised trials employing online methods have gained momentum. Decentralised methods lend themselves to certain types of trials and can offer advantages over traditional trial methods, potentially increasing participant reach and diversity and decreasing research waste. However, decentralised trials that have all aspects of the trial exclusively online are not yet common, and those involving children even less so. This scoping review will describe and evaluate the methods used in these trials to understand how they may be effectively employed. Methods: Methods are informed by guidance from the Joanna Briggs Institute and the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for scoping reviews. The search strategy was developed in consultation with an information specialist for the following databases: MEDLINE, CENTRAL, CINAHL, and Embase. Grey literature searches will be completed with the consultation of experts in decentralised trials and digital health using internet searches and suitable trial registries. Once identified, included full-text studies references will be manually searched for any trials that may have been missed. We will include randomised and quasi-randomised trials conducted exclusively online with participants under the age of 18 published in English. We will not limit by country of conduct or date of publication. Data will be collected using a data charting tool and presented in text, graphical, and tabular formats. Ethics and Dissemination: Ethical approval is not needed since all data sources used are publicly available. The review will be available as a preprint before publication in an open-access, peer-reviewed journal.
Prediction of Sound Transmission through Elastomeric Bulb Seals

Doors are the weakest parts of the buildings in ter ms of sound transmission. Examination of sound transmission loss characteristics of doors reveals two separate transmission paths to be considered. First one is transmission through door leaf and the second one is leak transmission through elastomeri c bulb seals. Seals are the important parts of the so und transmission loss characteristic of door struct ure. Hence, their insulation capability should be analyz ed and optimized to improve sound transmission loss of an acoustical door. The aim of this research is to predict sound transm ission loss of elastomeric bulb seals. This assessment includes two main steps. A static analys is is required to determine the seal shape under compression. Seals are made of elastomers which dis play nonlinear mechanical behavior. This requires hyperelastic material modeling and nonline ar finite element analysis (FEA). An acoustic analysis calculating the sound transmission is then carried on deformed geometry acquired from the first phase of the research. A sample seal geometry, which is already being used in industry, is considered as the case study. Influences of different hyper elastic material mode ls on sound insulation are also studied.
Fatigue and damage tolerance assessment of aircraft structure under uncertainty

To my An-ne and Papa iv ACKNOWLEDGEMENTS Many thanks to the Gulfstream Corporation, which has supported and encouraged me throughout this endeavor. Several people from the Gulfstream Family, specifically in the Stress Department, have my utmost appreciation. Amit Chib gladly lent an ear and advice on how to proceed with the stress analysis. Casey English provided support and advice on modeling techniques for several software packages used for this thesis. Dr. Frank Simmons guided me to the best and brightest in Gulfstream, and encouraged me throughout this venture. Ernesto Lopez helped 'make things simple but no simpler', and guided me to the correct engineering assumptions needed. Mark Murphree was my first supervisor in the world of stress analysis, and helped facilitate the resources needed at Gulfstream, and engineering mentoring. I am in great debt to him for his mentoring and guidance. Finite element modeling (FEM) would not have been possible without the gracious aid of Ken Terry. Ken first exposed me to the world of FEM, which allowed me to recheck my stress and vibrations analysis. Bryes Hornish aided in natural frequency calculations, FEM modeling, conceptualization and presentation. Many correlation concepts were successful with the help of Bryes. I was fortunate to work under Kevin Jones, who guided me through risk analysis and crack growth modeling. Kevin's experience in military and commercial aviation allowed me to make sense of analyzed data and make the correct assumptions as needed. v The opportunity to produce this thesis is thanks to several important people from the Georgia Institute of Technology. Patricia Potter is a great coordinator who provided encouragement and moral support. When things may appear amiss, Pat is the glue that holds the campus and its students together. Dr. Steven Johnson provided the foundation for fatigue and damage tolerance, and provided data and ideas that I have referenced throughout this thesis, and which I constantly use at my daily job as a stress analyst. Many thanks to him. The completion of this thesis and my coursework is mainly thanks to my academic advisor, Dr. Seung-Kyum Choi, for whom no words can express my appreciation. Dr. Choi advised me on the best courses and resources at Georgia Tech needed to successfully complete my coursework and thesis. When one is under the supervision of Dr. Choi, they master the course topic beyond their initial expectations. I learned more about probability and its uses working …
Advances in Very High Frequency Power Conversion

Resonant and quasi-resonant converters operated at frequencies above 30 MHz have attracted special attention in the last two decades. Compared to conventional converters operated at ~100 kHz, they offer significant advantages: smaller volume and weight, lower cost, and faster transient performance. Excellent performance and small size of magnetic components and capacitors at very high frequencies, along with constant advances in performance of power semiconductor devices, suggests a sizable shift in consumer power supplies market into this area in the near future. To operate dc-dc converter power devices at very high frequencies, switching loss needs to reduced or eliminated, as it would become prohibitively large. In addition, as the frequency increases, hard-switched gate driving becomes less and less of an option, as it embodies the same loss mechanism. A low-loss gate drive methods may need to be applied, especially at low power levels where gating loss becomes a significant percentage of the total loss budget. Various resonant gate drive methods have been proposed to address this design challenge, with varying size, cost, and complexity. This dissertation presents a self-oscillating resonant gate drive solution, which is applicable in cases when there are at least two power stages, and with minimal additional hardware requirements. It is experimentally confirmed that the method is suitable for both parallel and serial input configurations. Compared to state-of-the-art solutions, the proposed method provides low complexity and low gate loss simultaneously. A direct design synthesis method is provided for resonant SEPIC converters employing this technique. Most experimental prototypes were developed using low cost, commercially available power semiconductors. Due to very fast transient response of VHF converters, on/off control schemes are often used for their output control. The options presented so far demonstrated excellent performance, but with very strict timing constraints on all functional blocks in the feedback loop. Therefore, an on/off control method is proposed which allows the use of conventional ICs, while still providing high control bandwidth and performance comparable to state-of-the-art solutions. Since in many applications of interest galvanic isolation is not a requirement, the thesis proposes a method for providing a DC power path from input to output of a previously galvanic isolated converter. The method requires connection rearrangement in the existing converter only, and provides higher output power and converter efficiency for the same or lower voltage and/or current stresses in the converter components.
SuperpixelGridCut, SuperpixelGridMean and SuperpixelGridMix Data Augmentation

A novel approach of data augmentation based on irregular superpixel decomposition is proposed. This approach called SuperpixelGridMasks permits to extend original image datasets that are required by training stages of machine learning-related analysis architectures towards increasing their performances. Three variants named SuperpixelGridCut, SuperpixelGridMean and SuperpixelGridMix are presented. These grid-based methods produce a new style of image transformations using the dropping and fusing of information. Extensive experiments using various image classification models and datasets show that baseline performances can be significantly outperformed using our methods. The comparative study also shows that our methods can overpass the performances of other data augmentations. Experimental results obtained over image recognition datasets of varied natures show the efficiency of these new methods. SuperpixelGridCut, SuperpixelGridMean and SuperpixelGridMix codes are publicly available at https://github.com/hammoudiproject/SuperpixelGridMasks
Audio-Visual Wake Word Spotting System for MISP Challenge 2021

This paper presents the details of our system designed for the Task 1 of Multimodal Information Based Speech Processing (MISP) Challenge 2021. The purpose of Task 1 is to leverage both audio and video information to improve the environmental robustness of far-field wake word spotting. In the proposed system, firstly, we take advantage of speech enhancement algorithms such as beamforming and weighted prediction error (WPE) to address the multi-microphone conversational audio. Secondly, several data augmentation techniques are applied to simulate a more realistic far-field scenario. For the video information, the provided region of interest (ROI) is used to obtain visual representation. Then the multi-layer CNN is proposed to learn audio and visual representations, and these representations are fed into our two-branch attention-based net-work which can be employed for fusion, such as transformer and conformer. The focal loss is used to fine-tune the model and improve the performance significantly. Finally, multiple trained models are integrated by casting vote to achieve our final 0.091 score.
System Analysis for Responsible Design of Modern AI/ML Systems

The irresponsible use of ML algorithms in practical settings has received a lot of deserved attention in the recent years. We posit that the traditional system analysis perspective is needed when designing and implementing ML algorithms and systems. Such perspective can provide a formal way for evaluating and enabling responsible ML practices. In this paper, we review components of the System Analysis methodology and highlight how they connect and enable responsible practices of ML design.
Context-Auditor: Context-sensitive Content Injection Mitigation

Cross-site scripting (XSS) is the most common vulnerability class in web applications over the last decade. Much research attention has focused on building exploit mitigation defenses for this problem, but no technique provides adequate protection in the face of advanced attacks. One technique that bypasses XSS mitigations is the scriptless attack: a content injection technique that uses (among other options) CSS and HTML injection to infiltrate data. In studying this technique and others, we realized that the common property among the exploitation of all content injection vulnerabilities, including not just XSS and scriptless attacks, but also command injections and several others, is an unintended context switch in the victim program’s parsing engine that is caused by untrusted user input. In this paper, we propose Context-Auditor, a novel technique that leverages this insight to identify content injection vulnerabilities ranging from XSS to scriptless attacks and command injections. We implemented Context-Auditor as a general solution to content injection exploit detection problem in the form of a flexible, stand-alone detection module. We deployed instances of Context-Auditor as (1) a browser plugin, (2) a web proxy (3) a web server plugin, and (4) as a wrapper around potentially-injectable system endpoints. Because Context-Auditor targets the root cause of content injection exploitation (and, more specifically for the purpose of our prototype, XSS exploitation, scriptless exploitation, and command injection), our evaluation results demonstrate that Context-Auditor can identify and block content injection exploits that modern defenses cannot while maintaining low throughput overhead and avoiding false positives.
Protostellar and Protoplanetary Disk Masses in the Serpens Region

We present the results from an Atacama Large Millimeter/submillimeter Array (ALMA) 1.3 mm continuum and 12CO (J = 2 − 1) line survey spread over 10 deg2 in the Serpens star-forming region of 320 young stellar objects, 302 of which are likely members of Serpens (16 Class I, 35 flat-spectrum, 235 Class II, and 16 Class III). From the continuum data, we derive disk dust masses and show that they systematically decline from Class I to flat-spectrum to Class II sources. Grouped by stellar evolutionary state, the disk mass distributions are similar to other young (<3 Myr) regions, indicating that the large-scale environment of a star-forming region does not strongly affect its overall disk dust mass properties. These comparisons between populations reinforce previous conclusions that disks in the Ophiuchus star-forming region have anomalously low masses at all evolutionary stages. Additionally, we find a single deeply embedded protostar that has not been documented elsewhere in the literature and, from the CO line data, 15 protostellar outflows, which we catalog here.