Miracle-dz/UniFAR-FTUs huggingface dataset:
Building and Querying Probabilistic Models for Open World Database Systems

EDUCATION University of Washington, Seattle, WA August 2019 ● PhD in Computer Science ● Advisors: Dan Suciu and Magdalena Balazinska ● Dissertation: Building and Querying Probabilistic Models for Open World Database Systems University of Washington, Seattle, WA June 2015 ● Masters of Science ● Advisors: Dan Suciu and Magdalena Balazinska Carleton College, Northfield, MN June 2013 ● Bachelor of Arts Degree, Computer Science ● Bachelor of Arts Degree, Mathematics
Biomimetic textiles: Design and development of moisture sensitive adaptive textile prototype for application in casual clothing systems

This project investigates the experience of physiological discomfort during travel through an urban environment such as London or New York in winter. The over and underground networks that lace a current metropolis, form vital passages that lead the traveller though a multitude of spaces each defined by unique temperature, humidity and activity level. It is impossible to predict possible eventualities and consequently accommodate in a selection of clothing to ensure physiological comfort. Modular clothing assemblies are currently employed for the management of physiological comfort to adjust the insulation and ventilation properties of a clothing system and rely on combinations of behavioural methods and textile properties. This method is compromised by factors such as limited availability of space and wearer’s ability to detect and respond to the onset of discomfort sensations. Current smart systems rely on temperature as a stimulus for actuation. Experimental work suggests that humidity is a more suitable trigger. Botanical mechanisms that employ hygroscopic expansion/contraction for seed and spore deployment were identified as paradigms for the development of a smart textile system. Biomimetic analysis of these natural mechanisms inspired the design of a textile prototype able to adapt its water vapour resistance in response to humidity changes in the microclimate of the clothing system. The resulting structure decreases its permeability to air by 20% gradually as relative humidity increases from 60% to 90%.
The Effect of Plug-in Electric Vehicles on Harmonic Analysis of Smart Grid

Abstract In this paper, the effect of plug-in electric vehicles is studied on the smart distribution system with a standard IEEE 30-bus network. At first, harmonic power flow analysis is performed by Newton-Raphson method and by considering distorted substation voltage. Afterward, proper sizes of capacitors is selected by cuckoo optimization algorithm to reduce the power losses and cost and by imposing acceptable limit for total harmonic distortion and RMS voltages. It is proposed that the impact of generated current harmonics by electric vehicle battery chargers should be factored into overall load control strategies of smart appliances. This study is generalized to the different hours of a day by using daily load curve, and then optimum time for charging of electric vehicles batteries in the parking lots are determined by cuckoo optimization algorithm. The results show that injecting harmonic currents of plug-in electric vehicles causes a drop in the voltage profile and increases power loss. Moreover, charging the vehicle batteries has more impact on increasing the power losses rather than the harmonic currents effect. Also, the findings showed that the current harmonics has a great influence on increasing of THD. Finally, optimum working times of all parking lots was obtained for the utilization cost reduction.
Development of mine detection robot COMET-II and COMET-III

The present paper proposes two types of mine detection robots which are six-legged walking robot with two manipulators based on the added stability, mobility, and functionality. The COMET-II is a medium size, electric power driven robot. The COMET-III is a full autonomous robot which is driven by hydraulic power. The COMET-III has a crawler and six legs and its weight is 900 Kg, These improved robots will soon be engaged in the mine detection job in Afghanistan.
Identification of Size and Location of Bearing Damage via Deep Learning

Rotating machine is one of the most important machines used in various sectors. The most important unit is the rotating part and the shaft held by bearings. Most of the maintenance and repair cost of these machines is related to the replacement and service of bearings. Therefore, it is very important to identify the damaged bearings and determine the location of the damage. Different methods have been developed to monitor their condition, including recording and analyzing the vibration signals of bearings. So far, vibration-based methods have often been used to analyze them. Recently, the use of machine learning and deep learning techniques have been considered. Therefore, in this paper, a convolutional neural network is developed that directly receives the raw information recorded by vibration sensors as input and after analysis, a healthy bearing is detected from a defective one, the location and size of the damage are determined. In this research, the data set of Case Western Reserve University is used to validate the model and the results show that the proposed model has very high accuracy for analysis of samples.
Morphology development of an airfoil by numerical analysis

As aerial application is not quite feasible for small croplands with current aircrafts in the market, because their higher operational speed. An adequate solution is to generate morphology in the airfoil of the wing of an aircraft, that would allow to decrease the operational speed of the aircraft by increasing the lift that the wing can generate at lower speed without the issue of reach the stall speed. Different airfoils were evaluated in order to compare their characteristics of high-lift and low Reynolds number with those of the NACA 4415, which is the current airfoil of the chosen agricultural aircraft. Such evaluation was carried out by numerical analysis in two dimensions, using Computational Fluid Dynamics software (CFD) at the same air conditions. It is observed that some airfoils obtain much better lift, compare with the base airfoil, but the geometry became very complex. The GOE 449 airfoil was selected due to the minimum geometric changes to do in order to perform the morphology from the original airfoil obtaining 26% more lift. In order to obtain the minimum geometric changes as possible in the morphology from the NACA 4415 airfoil to seek the GOE 449 lift performance a new airfoil was obtained. The aerodynamics properties of this airfoil, called FUSION, are close to the GOE 449 airfoil, obtaining a 7% less lift. It is expected to substitute the use of any auxiliary mechanism like flaps, slats or airbrakes, using smart materials in order to increase the operational capacities of the aircraft and replace the weight of this by payload.
Drivers, Motivations and Barriers for Being a Socially Responsible Firm in Construction: a Critical Review

With the rapid changes in societal and environmental expectations, the concept of corporate social responsibility (CSR) has increasingly gaining its popularity among academic and practitioners within the construction industry. CSR research in construction is moving forward on a wide range of fronts but it is also fragmented as to how researchers operationalized motivators, drivers and barriers towards CSR implementation. In addressing this, this paper attempts to map out the key drivers, motivations and barriers to implementing CSR in the construction industry by undertaking a review of 69 relevant published articles. The findings have been classified into three categories of drivers, nine categories of motivations and five perspectives of barriers. The overall results reveal that the most cited drivers and motivations of construction firms are market pressure and branding, reputation and image, respectively, while the significant aspects of barriers mainly come from the business entity itself (e.g., lack of resource and capability). In conclusion, the findings offer a current state of art on the operationalization of key drivers, motivators and barriers to CSR implementation in construction and recommend some research directions. Future works should consider: (1) conduct empirical studies to test the effectiveness of the identified factors; (2) explore the relationship between key stakeholders and CSR performance; and (3) propose effective management mechanism to facilitate communication, cooperation and collaboration among stakeholders of construction firms.
Analgesic and Anti-Inflammatory Properties of Two Hydrogel Formulations Comprising Polyherbal Extract

Background Nature represents a basic source of medicinal scaffolds that can develop into potent drugs used in the treatment of many diseases. Aim The present study was planned to evaluate the combined effects of polyherbal methanolic extract of the herbs (fruit of capsicum, bark of cinnamon, rhizome of turmeric and rhizome of ginger) that were individually well known for their analgesic and anti-inflammatory activities. Furthermore, we aimed to develop hydrogel formulation of this polyherbal extract and to characterize and evaluate its analgesic and anti-inflammatory potential. Materials and Methods Zingiber officinale (R.), Capsicum annuum (L.), Curcuma longa (L.), and Cinnamomum verum (J.) polyherbal extract (GCTC) was prepared by maceration and evaluated for analgesic and anti-inflammatory potential. Then, two different types of hydrogel formulation were prepared. One is pH-based hydrogel in which carbopol-940 was used and the other is temperature-based gel in which methocel-K100 was used as gelling agent. Different concentrations of polyherbal extract (GCTC), at 1%, 3% and 5%, were used in hydrogel formulation. These prepared hydrogel formulations were characterized and evaluated for analgesic and anti-inflammatory potential. Results Results show that polyherbal extract and all the developed formulations of polyherbal extract (GCTC), at concentrations of 1%, 3% and 5%, have significant analgesic and anti-inflammatory effects with good appearance, homogeneity, spreadability, extrudability and stability. Conclusion It was concluded from this project that polyherbal extract (GCTC) and its hydrogel have significant analgesic and anti-inflammatory potential.
Designing a Model of Sports Leisure during the COVID-19 Pandemic: A Meta-Synthesis

: The worldwide coronavirus pandemic has led to the emergence of different patterns of behavior in different contexts; one of the most important of these contexts is leisure. The aim of this study was to identify the concepts and categories of leisure during the coronavirus pandemic (emphasis on sports-related studies) and using a qualitative meta-synthesis method. For this purpose, after searching for resources related to the field of leisure (emphasis on sports-related studies) during the coronavirus pandemic, 169 primary sources were found and among them 36 sources were selected and analyzed. The results of a meta-synthesis of leisure studies during the coronavirus pandemic (emphasis on sports-related research) was classified into 7 main categories physical, cognitive (mental), emotional, sociocultural, economic, technology, and environmental conditions and a sports leisure model was presented during the coronavirus pandemic. According to the results of this study, if proper planning and monitoring by sports-related organizations and the media is considered, sports leisure time during the coronavirus pandemic can bring physical, cognitive (mental), emotional and sociocultural benefits for individuals and reduce the negative effects of coronavirus disease in communities. On the other the coronavirus pandemic has revolutionized leisure conditions, and in particular sports leisure, by revolutionizing technology, economics, and conditions environment.
Exploring tangible interaction: Alternative interfaces for assisting elderly users

The use of tangible user interfaces in assisting elderly users is still a fairly unexplored domain. While the current research provides some solutions to this domain, the research are still limited. The elderly population is growing, as a result of increased living standard and better health services. This causes a high demand of nursing homes, which will cause more elderly people to be living in their own homes. This thesis investigates how tangible user interfaces (TUI) can make things easier compared to the elderly people’s current living situation. Domain-knowledge of common age impairments and details of TUIs have been collected through literature review, to propose a framework for designing TUIs for elderly people, based on previous frameworks on TUIs and common age impairments discovered. Further domain-knowledge has been collected through focus groups, interviews, workshops and observations. Four prototypes featuring TUIs and designed to compensate for some challenges of aging have been developed. This includes T-Radio; a radio controlled by tangible blocks, Payless; an alternative way to pay for food and beverages in a canteen using only a RFID key card, Natural Charge; seven different wireless chargers to investigate the best configuration, and LightUp; a light bulb that changes the color intensity depending on environmental temperature. The prototypes were taken through a formative usability test with experts from the HCI community, revealing some problems of the prototypes before a few modifications were done. Then summative usability tests with elderly participants were conducted at two different research sites; a local care home and a senior center. The results were analyzed using the proposed framework and led to three problem areas that were investigated, before the implications for design were presented. The results show that there are great potential in TUIs to compensate for age impairments and make things easier than today.
Compressive Sensing for Electromagnetic Imaging Using a Nesterov-Based Algorithm

of the Dissertation Compressive Sensing for Electromagnetic Imaging Using a Nesterov-Based Algorithm by Yolanda Rodriguez Vaqueiro Doctor of Philosophy in Electrical Engineering Northeastern University, March 2015 Dr. Jose Angel Martinez-Lorenzo, Adviser Compressive Sensing (CS) is a relatively novel signal processing theory; it states that sparse signals can be recovered using far fewer samples or measurements than the required by the Nyquist sampling criterion. This technique, applied to Electromagnetic Imaging and implemented using the Nesterov’s algorithm, has been used in this work to reduce the number of sensors and improve the robustness of several security and biomedical imaging systems. Nesterov’s algorithm is a first order method that provides a framework for minimizing nonsmooth convex functions on any given convex set. The algorithm recasts the original problem as finding a saddle point in the primal-dual feasibility set when the original function is smoothed by using weighted prox-function. The solution to this minimization problem is given by iteratively estimating three sequences: the first sequence is computed using a gradient-descent pathway, the second sequence is computed from an averaged gradientdescent pathway, and the third sequence is computed as a weighted average of the first two
Metaphorical Representation of Coronavirus in Medical Myths 1

This paper focuses on metaphorical representation of coronavirus in medical myths on the example of the British media. To attain this goal, the descriptive metaphor theory is used for the analysis of metaphorical models for the conceptualization of coronavirus. The information about the virus transmitted by the media correlates with background knowledge of the recipient, acquires new conceptual characteristics. Our hypothesis is that metaphorical actualization of coronavirus in medical myths is represented by the descriptive metaphor, the content of which changes depending on the specifics of the spread of the virus over the country as well as the political situation in the country. The research is based on the assumption that metaphorical implications in medical myths influence the representation of the disease, which reflects not only general beliefs about this disease, but also molds the public opinion on political situation in the linguocultural society. The objective of this research is to analyze the titles and leads of the British press about coronavirus and interpret the metaphorical models for the conceptualization of coronavirus, used in medical myths. and leads that contain metaphorical models for the conceptualization of coronavirus in medical myths; sampling analysis aimed at identifying and describing the functions of metaphorical models in the representation of the disease in medical myths. The notions of metalanguage such as the signification descriptor and the denotation descriptor are used to describe the functioning of metaphors. The research findings reveal that for the conceptualization of coronavirus in medical myths the following metaphorical models are used: ‘Coronavirus-military rival’, ‘Coronavirus-natural disaster’ and ‘Coronavirus-silver lining’.
Power Factor Improvement of The Glenmore Sugar Industry Electrical System

AbstractThis study discusses the improvement of the power factor in the Glenmore Sugar Industry electrical system. Low power factor can be caused by variations in inductive loads. This has an impact on large currents and high reactive power so that a black out can occur in the Glenmore Sugar Industry electrical system. Low power factor is corrected with the most effective Costum Power Devices, namely Static Var Compensator (SVC) and Static Synchronous Compensator (STATCOM). The evaluated and corrected load buses are those with low power factor.The simulation results show in the application of SVC for the lowest results, power factor increased from 0.76 to 0.78 with reactive power values in the range from + 1.6 to – 0.64 MVAR. The power factor increased from 0.76 to 0.85 with reactive power values in the range from +4.9 to –1.9 MVAR. And for the highest results, the power factor increased from 0.82 to 0.92 with reactive power values in the range from +3.9 to –1.5 MVAR.The application of STATCOM can increase the power factor with reactive power values in the range from +4.9 to – 0.994 MVAR, +1.6 to -0.32 MVAR and +3.9 to -0.7875 MVAR. Keywords – Power factor, SVC, STATCOM, Reactive power, Industry.
THE MICROBIAL GROWTH INHIBITION PROFILE OF SELECTED INDONESIAN SPICES ESSENTIAL OILS ON TOFU DURING 8-DAY STORAGE

This study evaluated the profile of microbial growth inhibition on tofu treated by the essential oil of the selected spices. The microbial growth on the tofu was visually observed by the pour plate method, while their number was enumerated by the indirect optical density (OD) method. All the tested essential oils were visually reduced the microbial growth on tofu during storage. Each spices oil showed a different inhibition pattern, with bay leaf, galangal, and ginger oils exerting favorable effects for the most prolonged period. The day-bay-day comparison demonstrated that the best inhibition effect was on day-6 and -8, with bay leaf and galangal oils showing the most promising activity. The best profile of both essential oils might play a vital role in the tofu preservation process by natural products.
Chemical Composition, Bioactive and Phenolic Compounds in three Varieties of Annona Fruit Grown in Egypt

The present study is an attempt to measure the morphological parameters of the three famous Annona varieties grown in Egypt, and study the nutritional value, bioactive compounds and phenolic compounds of the Annona fruits. Concerning the morphological parameters Abdel Razek variety had the highest fruit weight (621.43 g) and fruit peel weight (121.94 g), while Balady variety fruits have the highest ratio of fruit peel to the total fruit weight (0.289) and the number of seeds in one fruit (55). Hindi variety recorded the highest weight values of 100 seed (11.74 g). It was found that the highest levels of fats, fiber, carbohydrates, most quantitative sugar and TSS were recorded in the Abd El-Razik variety. The highest contents of moisture, ash and protein were recorded in the Hindy variety. While the acidity content was nearly the same in the three varieties. Abdel Razek variety was the highest compared with the other varieties in all the estimated mineral elements (P, K, Fe, Ca, Zn and Mg). Abde Razik verity was high in bioactive compounds as ascorbic acid, flavonoid, and antioxidant activity, while Hindy variety was the highest in phenolics and DPPH.
A CRITICAL DISCOURSE ANALYSIS OF PRESIDENT OBAMA’S 9/11 MEMORIAL ADDRESS

Gần đây, thế giới đã và đang chứng kiến cuộc giao tranh giữa Nga và Ukraine. Vì bất cứ lý do gì, mọi cuộc tấn công luôn gây ra tổn thất lớn cho những người dân vô tội. Nhìn lại quá khứ xa hơn, chắc chắn chúng ta không thể quên được ngày mà ngay cả một cường quốc lớn nhất thế giới cũng bị tấn công vào ngày 11 tháng 9 năm 2001, và Hợp chủng quốc Hoa Kỳ từ đó vẫn mang những ký ức đau thương. Để kỷ niệm ngày thảm kịch này, Barack Obama – tổng thống thứ 44 của Hoa Kỳ đã có bài phát biểu tưởng niệm vô cùng xúc động và truyền cảm hứng. Để hiểu sâu hơn về bài phát biểu này, nghiên cứu đã được thực hiện với phương pháp phân tích diễn ngôn phê phán (CDA). Trong quá trình phân tích về bài phát biểu chính trị này, tác giả chủ yếu tập trung nghiên cứu sức mạnh của ngôn ngữ bằng cách phân tích đặc điểm từ vựng và ngữ pháp. Sau đó, cấu trúc vĩ mô của văn bản được tìm hiểu sâu hơn để nhằm thể hiện hàm ý và hệ tư tưởng được truyền tải qua các yếu tố ngôn ngữ. Bài diễn văn này có thể được coi là thông điệp gửi đến tất cả người dân Mỹ nói riêng và toàn thế giới nói chung về vấn đề giao tranh quân sự và hòa bình.
A ResNet-LSTM Based Credit Scoring Approach for Imbalanced Data

Detecting potential defaults or bad debt with limited information has become a huge challenge. The main difficulties faced by the credit scoring are sample imbalance and poor classification performance. For this reason, we first proposed the auxiliary conditional tabular generative adversarial network (ACTGAN) to generate sufficient default transaction samples from the original data, then we designed a model based on ResNet-LSTM used for feature extraction, which includes two submodels of ResNet and LSTM to extract static local features and dynamic temporal features from the original data, respectively. After that, a spatiotemporal attention module is added to calculate the importance of the two submodel’s output in order to extract more critical information. Finally, we applied the focus loss function into the XGBoost classifier to improve the probability output of the credit default risk. We verified the designed credit scoring model in two real-world datasets. The experimental results showed that ACTGAN can effectively solve the problem of data imbalance. The ResNet-LSTM+XGBoost model for classification is better than other traditional algorithms in F1 value, AUC, and KS value, which proves the effectiveness and portability of this model in the field of credit scoring.