Miracle-dz/UniFAR-FTUs huggingface dataset:
Aﬀordable and Collaborative Team Formation in an Expert Network

Given an expert network, we tackle the problem of ﬁnding a team of experts that covers a set of required skills and also minimizes the communication cost as well as the personnel cost of the team. Since two costs need to be minimized, this is a bicriteria optimization problem. We show that the problem of minimizing these objectives is NP-hard. We use two approaches to solve this bicriteria optimization problem. In the ﬁrst approach, we propose several ( α, β ) -approximation algorithms that receive a budget on one objective and minimizes the other objective within the budget with guaranteed performance bounds. In the second approach, an approximation algorithm is proposed to ﬁnd a set of Pareto-optimal teams, in which each team is not dominated by other feasible teams in terms of the personnel and communication costs. The proposed approximation algorithms have provable performance bounds. Extensive experiments on real datasets demonstrate the effectiveness and scalability of the proposed algorithms.
Distributed Training of Knowledge Graph Embedding Models using Ray

Knowledge graphs are at the core of numerous consumer and enterprise applications where learned graph embeddings are used to derive insights for the users of these applications. Since knowledge graphs can be very large, the process of learning embeddings is time and resource intensive and needs to be done in a distributed manner to leverage compute resources of multiple machines. Therefore, these applications demand performance and scalability at the development and deployment stages, and require these models to be developed and deployed in frameworks that address these requirements. Ray 1 is an example of such a framework that offers both ease of development and deployment, and enables running tasks in a distributed manner using simple APIs. In this work, we use Ray to build an end-to-end system for data preprocessing and distributed training of graph neural network based knowledge graph embedding models. We apply our system to link prediction task, i.e. using knowledge graph embedding to discover links between nodes in graphs. We evaluate our system on a real-world industrial dataset and demonstrate significant speedups of both, distributed data preprocessing and distributed model training. Compared to non-distributed learning, we achieved a training speedup of 12 × with 4 Ray workers without any deterioration in the evaluation metrics.
UVC-PURGE: A Novel Cost-Effective Disinfection Robot for Combating COVID-19 Pandemic

During the COVID-19 pandemic, surface disinfection using prevailing chemical disinfection methods had several limitations. Due to cost-inefficiency and the inability to disinfect shaded places, static UVC lamps cannot address these limitations properly. Moreover, the average market price of the prevailing UVC robots is huge, approximately 55,165 USD. In this research firstly, a requirement elicitation study was conducted using a semi-structured interview approach to reveal the requirements to develop a cost-effective UVC robot. Secondly, a semi-autonomous robot named UVC-PURGE was developed based on the revealed requirements. Thirdly, a two-phased evaluation study was undertaken to validate the effectiveness of UVC-PURGE to inactivate the SARS-CoV-2 virus and the capability of semi-autonomous navigation in the first phase and to evaluate the usability of the system through a hybrid approach of SUPR-Q forms and subjective evaluation of the user feedback in the second phase. Pre-treatment swab testing revealed the presence of both Gram-positive and Gram-Negative bacteria at 17 out of 20 test surfaces in the conducted tests. After the UVC irradiation of the robot, the microbial load was detected in only 2 (1D and 1H) out of 17 test surfaces with significant reductions (95.33% in 1D and 90.9% in 1H) of microbial load. Moreover, the usability evaluation yields an above-average SUPR-Q score of 81.91% with significant scores in all the criteria (usability, trust, loyalty, and appearance) and the number of positive themes from the subjective evaluation using thematic analysis is twice the number of negative themes. Additionally, compared with the prevailing UVC disinfection robots in the market, UVC-PURGE is cost-effective with a price of less than 800 USD. Moreover, small form factor along with the real time camera feedback in the developed system helps the user to navigate in congested places easily. The developed robot can be used in any indoor environment in this prevailing pandemic situation and it can also provide cost-effective disinfection in medical facilities against the long-term residual effect of COVID-19 in the post-pandemic era.
Analysis of the strategies for managing extended-range electric vehicle powertrain in the urban driving cycle

Introduction. An Extended-Range Electric Vehicle (EREV) is a type of electric vehicle that uses an additional internal combustion engine (ICE) to charge the battery in order to provide the vehicle with a greater range than in electric only mode. Purpose. Analysis and comparison of the performance of EREV powertrain managed according to three control strategies: pure electric mode, hybrid mode with ICE constantly working, and hybrid mode with ICE working only at high power demand. Methods. The tests were carried out using a laboratory test stand that represented the structure of EREV powertrain. Liquefied petroleum gas was used as a fuel to supply the ICE. The test conditions were defined by a special driving cycle simulating urban driving. Results. Time series plots of selected parameters of electric motor, electrochemical battery pack, range extender generator and active load system. Practical value. Among the considered control strategies of EREV powertrain, the energy balance of the electrochemical battery is negative for a purely electric mode, significantly positive for continuous range extenders (REXs) operation mode and moderately positive for the mode with REX activation only in dynamic states.
The Combined Effect of IgG and Fe Supply and Feeding Management on Growth Rates of Calves on Eight Commercial Dairy Farms in Germany

Simple Summary Well-thought-out calf rearing is essential to produce long-lived and productive cows for future dairy herds. The first days of a calf’s life are a very important period. It is known that calves that are adequately supplied with colostrum during this period have sufficient antibodies. They gain weight faster and fall ill less frequently. Identifying other management factors that have positive effects on calf growth is the subject of this study. To investigate this, 123 Holstein calves on eight conventional dairy farms were followed from birth to 50 days of life in spring 2017, and the influence on the animals’ weight gain due to management factors such as timing and supply of colostrum, iron supplementation, feeding regime and microbial load at first feeding was analyzed. The results show that, in addition to an adequate level of antibodies in the colostrum fed to the calves, the iron concentration in the calves’ blood and the feeding regimen play an important role in the calves’ weight gains and thus in calf rearing. Abstract During the first days of a calf’s life, the foundations are laid for successful growth and thus also for the later performance of the cows. The aim of the present study was to analyze the impact on the weight gain of newborn calves due to important management factors related to colostrum supply, iron supply, feeding regime and microbial load at first feeding. In spring 2017, information of 123 Holstein calves were analyzed with regard to the colostrum supply and management factors on eight commercial dairy farms located in Germany. Additionally, blood samples of newborn calves were analyzed for total immunoglobulin G (IgG) and serum iron content. Furthermore, Brix analysis and analysis of contamination by E. coli were performed on first colostrum samples from teats or buckets. Average daily weight gain of calves at days 14 and 50 was calculated. The colostrum IgG was estimated by Brix refractometer. The volume of initial colostrum supply and the time between birth and colostrum intake significantly (p < 0.05) influenced the serum IgG concentration. The serum IgG concentration, the serum iron concentration and the feeding regimen (restrictive or not restrictive feeding) had a significant effect (p < 0.05) on daily weight gains. In conclusion, this study shows that, in addition to a sufficient supply of immunoglobulins, other aspects, such as an adequate colostrum, iron and milk supply, play an essential role in calf growth rates.
Crown Position and Rootstock Genotype Influence Leaf Stomatal Density in Macadamia sp.

: We investigated the effects of three rootstocks (Beaumont, Daddow, and WJMAS-29) and two crown positions (north and south) on abaxial leaf stomatal density (SD) of a common macadamia scion ‘HAES741’. Manual counting and artiﬁcial intelligence (AI) image processing methods were used to measure SD from the leaves of the scion grafted onto each rootstock. In both methods, rootstock and crown position showed signiﬁcant effects on scion SD (352 stomata mm − 2 in WJMAS-29,310 stomata mm − 2 in Beaumont, and 332 stomata mm − 2 in Daddow; 358 stomata mm − 2 in north and 305 stomata mm − 2 in south). We discussed that variability in SD due to genotype (rootstock) and environment (differential solar irradiance due to crown position) can be used to improve productivity of future orchard systems.
Wing Connected Network Dual Voltage Source Inverter with the Ability to Improve the Quality Characteristics

The main aim of project is to improve the power quality by using fuzzy based grid connected dual voltage source inverter. The proposed scheme is comprised of two inverters, which enables the microgrid to exchange power generated by the distributed energy resources (DERs) and also to compensate the local unbalanced and nonlinear load. The control algorithms are developed based on instantaneous symmetrical component theory (ISCT) to operate DVSI in grid sharing and grid injecting modes. The proposed scheme has increased reliability, lower bandwidth requirement of the main inverter, lower cost due to reduction in filter size, and better utilization of microgrid power while using reduced dc-link voltage rating for the main inverter. These features make the DVSI scheme a promising option for microgrid supplying sensitive loads. the proposed topology validated through simulation results.
The effect of wheat flour extraction rate on blood glucose response and glycemic index in healthy individuals

The aim of this work is to study the effect of flour extraction ratio on the Glucose index (Glycemic Index (GI) of Iraqi bread made from some kinds of wheat with different extraction ratios, which were 72 % ,90 % and 100 % for each kind and with participation of 70 healthy volunteers, their ages ranging from 22-40 years old and Body Mass Index between 22-30 kg/m2 . The volunteers were in good health Body Mass Index, BMI and they do not have any chronic diseases, including diabetes at the start of measurement, each participant underwent a gluocose Tolerance Test (GTT ), each participant took 50 gm from carbohydrates after fasting 10-12 hours , then blood samples were drawn from a finger after the time 0 ,30 ,60 ,90, 120 minutes. The results of calculating GI values showed a significant differences at the level (p < 0.01) between the prepared bread from the white wheat 72% and the bread prepared from flour extract 90% and the whole extracted bread 100%.
Methods for Non-invasive Trustworthy Estimation of Arterial Blood Pressure

ii Acknowledgements iii List of Tables vi List of Figures vii List of Abbreviations ix Chapter 1 Introduction 1 1.1 Background 5 1.2 Motivation 7 1.3 Contributions 9 1.4 Scholarly Outputs 11 1.5 Thesis Organization 12 Chapter 2 Literature Review 13 2.1 Oscillometry 14 2.1.1 Maximum Amplitude Algorithm (MAA) 17 2.1.2 Linear Approximation Algorithm (LAA) 18 2.1.3 Maximum/Minimum Slope Algorithm (MMSA) 18 2.1.4 Pulse Morphology 20 2.1.5 Pulse Transit Time Analysis 22 2.2 Standards for Automated BP Monitors 23 Chapter3 Dynamic Threshold Algorithm (DTA) and Trustworthiness of the BP Readings 25 3.1 Dynamic Threshold Algorithm (DTA) 28 3.1.1 Trustworthiness Evaluation of the BP Measurements 32 3.2 Experimental Results 33 3.3 Results and Discussion 37 3.4 Conclusion 39 Chapter 4 Modeling approach for BP Estimation 42 4.1 BP Estimation method from Arterial Lumen Area Oscillations Model (ALA-based) 43 4.1.1 Evaluation of the Compliance Parameter (Procedure 1) 47
Augmented Reality Games and Presence: A Systematic Review

The sense of presence in augmented reality (AR) has been studied by multiple researchers through diverse applications and strategies. In addition to the valuable information provided to the scientific community, new questions keep being raised. These approaches vary from following the standards from virtual reality to ascertaining the presence of users’ experiences and new proposals for evaluating presence that specifically target AR environments. It is undeniable that the idea of evaluating presence across AR may be overwhelming due to the different scenarios that may be possible, whether this regards technological devices—from immersive AR headsets to the small screens of smartphones—or the amount of virtual information that is being added to the real scenario. Taking into account the recent literature that has addressed the sense of presence in AR as a true challenge given the diversity of ways that AR can be experienced, this study proposes a specific scope to address presence and other related forms of dimensions such as immersion, engagement, embodiment, or telepresence, when AR is used in games. This systematic review was conducted following the PRISMA methodology, carefully analysing all studies that reported visual games that include AR activities and somehow included presence data—or related dimensions that may be referred to as immersion-related feelings, analysis or results. This study clarifies what dimensions of presence are being considered and evaluated in AR games, how presence-related variables have been evaluated, and what the major research findings are. For a better understanding of these approaches, this study takes note of what devices are being used for the AR experience when immersion-related feelings are one of the behaviours that are considered in their evaluations, and discusses to what extent these feelings in AR games affect the player’s other behaviours.
Harmonics Filtering Capability of Doubly Fed Induction Generator for Wind Energy Conversion Systems

This paper manages the operation of Doubly Fed Induction Generator (DFIG) with an incorporated dynamic channel capacities utilizing Grid Side Converter (GSC). The principle commitment of this work lies in the control of GSC for providing music notwithstanding its slip control exchange. The Rotor Side Converter (RSC) is utilized for accomplishing most extreme power extraction and to supply required responsive energy to DFIG. This Wind Energy Conversion System (WECS) functions as a Static Compensator (STATCOM) for providing music notwithstanding when the wind turbine is in closed down condition. Control calculations of both GSC and RSC are exhibited in detail. Proposed DFIG based WECS is recreated utilizing MATLAB/Simulink. A model of a proposed DFIG based WECS is created utilizing a DSP (Digital Signal Processor). Reenacted results are approved with test consequences of the created DFIG for various useful conditions, for example, factor wind speed and lopsided/single stage burdens.
Comparison of two synchronous motors with interior magnets

The paper presents two prototypes of Interior Permanent Magnet Synchronous Motor (IPMSM) and their experimental and simulation results comparison. After the optimization, two different rotors have been constructed and tested. Particularly self and mutual winding inductances as well as dand q-axis inductances were evaluated. The torque values for different currents and power angles, as well as induced voltage, were measured and compared with calculated values. Finally self and mutual waveforms of inductances of a phase windings were measured and simulated. Streszczenie. W pracy przedstawiono porównanie wyników symulacji i pomiarów dwóch prototypów maszyn synchronicznych z zagnieżdżonymi magnesami trwałymi (IPMSM). Wykorzystując wyniki wcześniejszych optymalizacji zbudowano i następnie przebadano dwa różne wirniki. Wyznaczono wartości indukcyjności własnych i wzajemnych, a także indukcyjności w osiach di g-. Dokonano obliczeń i pomiarów wartości momentu elektromagnetycznego dla różnych prądów, a także indukowanego napięcia, momentu zaczepowego i funkcji sprawności. Ostatecznie zmierzono i zasymulowano przebiegi indukcyjności własnych i wzajemnych uzwojeń fazowych. (Porównanie dwóch wariantów maszyny synchronicznej z zagnieżdżonymi magnesami trwałymi).
Bamboo-Fiber-Reinforced Thermoset and Thermoplastic Polymer Composites: A Review of Properties, Fabrication, and Potential Applications

Natural-fiber-reinforced composites, especially bamboo, are an alternative material to compete with conventional materials. Their environmentally friendly, renewable, low-cost, low-density, non-toxic, and fully biodegradable properties are concerning for researchers because of their advantages over synthetic polymers. This comprehensive review presents the results of work on bamboo fiber composites with special reference to bamboo types, thermoplastic and thermoset polymers matrices, hybrid composites, and their applications. In addition, several studies prove that these properties are very good and efficient in various applications. However, in the development of composite technology, bamboo fiber has certain constraints, especially in moisture conditions. Moisture is one of the factors that reduces the potential of bamboo fiber and makes it a critical issue in the manufacturing industry. Therefore, various efforts have been made to ensure that these properties are not affected by moisture by treating the surface fibers using chemical treatments.
Acid Mine Drainage Treatment Using a Process Train with Laterite Mine Waste, Concrete Waste, and Limestone as Treatment Media

Without treatment, the harmful effects of acid mine drainage (AMD) lead to the destruction of surrounding ecosystems, including serious health impacts to affected communities. Active methods, like chemical neutralization, are the most widely used approach to AMD management. However, these techniques require constant inputs of energy, chemicals, and manpower, which become unsustainable in the long-term. One promising and sustainable alternative for AMD management is to use passive treatment systems with locally available and waste-derived alkalinity-generating materials. In this study, the treatment of synthetic AMD with laterite mine waste (LMW), concrete waste, and limestone in a successive process train was elucidated, and the optimal process train configuration was determined. Six full factorial analyses were performed following a constant ratio of 0.75 mL AMD/g media with a 15-min retention time. The evolution of the pH, redox potential (Eh), total dissolved solids (TDS), heavy metals concentration, and sulfates concentrations were monitored as the basis for evaluating the treatment performance of each run. LMW had the highest metal and sulfates removal, while concrete waste caused the largest pH increase. A ranking system was utilized in which each parameter was normalized based on the Philippine effluent standards (DENR Administrative Order (DAO) 2016–08 and 2021–19). Run 4 (Limestone-LMW-Concrete waste) showed the best performance, that is, the pH increased from 1.35 to 8.08 and removed 39% Fe, 94% Ni, 72% Al, and 52% sulfate. With this, the process train is more effective to treat AMD, and the order of the media in treatment is significant.
Ultracapacitor/Battery Hybrid Energy Storage Systems for Electric Vehicles

Ultracapacitor/Battery Hybrid Energy Storage Systems for Electric Vehicles Mazhar Moshirvaziri Master of Applied Science Graduate Department of Electrical and Computer Engineering University of Toronto 2012 This thesis deals with the design of Hybrid Energy Storage System (HESS) for Light Electric Vehicles (LEV) and EVs. More specifically, a tri-mode high-efficiency nonisolated half-bridge converter is developed for the LEV based HESS applications. A 2 kW, 100 V interleaved two-phase converter prototype was implemented. The peak efficiency of 97.5% and a minimum efficiency of 88% over the full load range are achieved. Furthermore, a power-mix optimizer utilizing the real-time Global Positioning System (GPS) data for the EV based HESS is proposed. For a specific design, it is shown that at the cost of less than 1.5% of the overall energy savings, the proposed scheme reduces the peak battery charge and discharge rates by 76% and 47%, respectively. A 30 kW bi-directional dc-dc converter is also designed and implemented for future deployment of the designed HESS into a prototype EV, known as A2B.
Optimal process integration architectures in off-site construction: Theorizing the use of multi-skilled resources

ABSTRACT The architecture, engineering and construction industry has long dealt with problems such as schedule and budget overruns, quality and safety issues, and low productivity. Off-site construction, which is a hybrid of manufacturing and construction, has significant potential to address industry’s endemic problems. However, off-site construction has been criticized for replicating the traditional subcontracting approach and therefore fragmented practice in the construction industry. The current research focuses on process integration and cross-training of multi-skilled resources as a solution to the aforementioned problem. To identify optimal process integration architectures for off-site construction, production data of three off-site manufacturers were analyzed by using a hybrid of fuzzy theory and the technique for order of preference by similarity to ideal solution. Findings reveal that process integration architectures transferring excess capacity from under-utilized to over-utilized resources in direct or indirect pathways are preferable in terms of satisfying decision criteria such as time and cost of cross-training, skill transferability, compliance with network logic, and safety considerations. The study contributes to the off-site construction literature by providing insight into dynamics of using multi-skilled resources. It also contributes to practice by developing a customizable and user-friendly framework for off-site production managers in order to identify the optimal process integration architecture in their own production scenarios.