Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring Ethnomathematics with Ethnomodeling Methodological Approach: How Does Cigugur Indigenous People Using Calculations to Determine Good Day to Build Houses

This article discusses Cigugur indigenous communities’ custom in carrying out calculation practices to determine the best time to start house construction activities. The realist ethnography approach was used in this study through exploratory research. The ethnomathematics design adopted four elements: generic questions, initial answers, critical constructs, and specific activities. Ethnomodelling was used to translate cultural mathematics ideas into academic mathematics through ethical, emic, and dialogical approaches. Based on ethnomathematics, the community practices the dimensions of necessary universal mathematical activities, such as counting, placing, and explaining. Based on ethnomodeling, mathematical ideas and practices carried out are relevant to the concepts of enumeration, integer operations, sets, relations, congruence, and modulo. The study results recommend the importance of ethnomodelling as a methodological approach to ethnomathematics to create and develop didactical situations, especially in developing a new lesson.
Core outcomes in gestational diabetes for treatment trials: The Gestational Metabolic Group treatment set

With the rising number of outcomes being reported following gestational diabetes (GDM), the outcomes in existing studies vary widely making it challenging to compare and contrast the effectiveness of different interventions for GDM. The purpose of this study was to develop a core outcome and measurement set (COS) for GDM treatment trials.
Phone based acoustic modeling for automatic speech recognition for Punjabi language

Punjabi language is a tonal language belonging to an Indo-Aryan language family and has a number of speakers all around the world. Punjabi language has gained acceptability in the media & communication and therefore deserves to have a place in the growing field of automatic speech recognition which has been explored already for a number of other Indian and foreign languages successfully. Some work has been done in the field of isolated word speech recognition for Punjabi language, but only using whole word based acoustic models. A phone based approach has yet to be applied for Punjabi language speech recognition. This paper describes an automatic speech recognizer that recognizes isolated word speech and connected word speech using a triphone based acoustic model on the HTK 3.4. 1 speech Engine and compares the performance with acoustic whole word model based ASR system. Word recognition accuracy of isolated word speech was 92.05% for acoustic whole word model based system and 97.14% for acoustic triphone model based system whereas word recognition accuracy of connected word speech was 87.75% for acoustic whole word model based system and 91.62% for acoustic triphone model based system.
Human Milk Hormone Intake in the First Month of Life and Physical Growth Outcomes in Preterm Infants.

CONTEXT Human milk contains hormones that regulate metabolism. Extrauterine growth restriction remains common among preterm infants, but the effect of ingesting milk hormones on preterm infant growth is poorly understood. OBJECTIVE To quantify associations of longitudinal exposure to leptin, adiponectin, and insulin in milk with physical growth of preterm infants. DESIGN/METHODS In 50 preterm neonates (median gestational age 29.4 weeks), we sampled maternal milk on day-of-life 7, 14, 21, and 28 and measured hormone levels in whole milk by ELISA. Milk leptin levels were available for a subset of 18 infants. We calculated milk hormone doses by multiplying the hormone level by the milk volume ingested on each day and estimated the area under the curve (AUC) to reflect longitudinal exposure. We analyzed associations of milk hormone exposure with growth outcomes in generalized estimated equations. MAIN OUTCOME MEASURES Weight gain velocity and z-scores in weight, length, head circumference, and body mass index at 36 weeks' postmenstrual age (PMA). RESULTS Higher leptin intake was associated with greater weight gain (2.17g/kg/day [95% CI, 1.31, 3.02]) and weight z-score at 36 weeks' PMA (0.30 [0.08, 0.53] higher z-score per tertile). Higher adiponectin intake was associated with greater length z-score (0.41 [0.13, 0.69]), however, this association was nullified after adjustment of protein and calorie intake. Higher adiponectin was associated with smaller head circumference z-score (-0.36 [-0.64, -0.07]). Insulin was not associated with growth outcomes. CONCLUSIONS Milk leptin and adiponectin exposures may affect growth of preterm infants. The long-term effects of milk hormones warrant further investigation.
The Simultaneous Impacts of Seasonal Weather and Solar Conditions on PV Panels Electrical Characteristics

Solar energy usage is thriving day by day. These solar panels are installed to absorb solar energy and produce electrical energy. As a result, the efficiency of solar panels depends on different environmental factors, namely, air temperature, dust (aerosols and accumulated dust), and solar incidence, and photovoltaic panel angles. The effects of real conditions factors on power and efficiency of photovoltaic panels are studied in this paper through testing the panel in real environmental tests. To study the mentioned parameters precisely, two panels with different angles are used. The case study is regarding a region of Tehran, Iran, in summer and winter seasons. The results show that panel efficiency during winter is higher than summer due to air temperature decrement. It is discovered that among air pollutants, Al and Fe have the most share in polluting the air that affect the photovoltaic efficiency. Moreover, measuring the accumulated dust on the panels shows more amount in winter in comparison with summer. The important point in studying the effect of tilt angle is that inconformity between solar incidence and photovoltaic panel angles would result in solar radiation absorption and eventually panel efficiency loss and also, photovoltaic panel installation angle would affect the amount of dust deposited on its surface.
Time-Frequency Analysis and Application of a Vibration Signal of Tunnel Excavation Blasting Based on CEEMD-MPE-HT

The traditional empirical mode decomposition method cannot accurately extract the time-frequency characteristic parameters contained in the noisy seismic monitoring signals. In this paper, the time-frequency analysis model of CEEMD-MPE-HT is established by introducing the multiscale permutation entropy (MPE), combining with the optimized empirical mode decomposition (CEEMD) and Hilbert transform (HT). The accuracy of the model is verified by the simulation signal mixed with noise. Based on the project of Loushan two-to-four in situ expansion tunnel, a CEEMD-MPE-HT model is used to extract and analyze the time-frequency characteristic parameters of blasting seismic signals. The results show that the energy of the seismic wave signal is mainly concentrated in the frequency band above 100 Hz, while the natural vibration frequency of the adjacent existing tunnel is far less than this frequency band, and the excavation blasting of the tunnel will not cause the resonance of the adjacent existing tunnel.
Design and fabrication of MEMS lowpass filter exploiting space mapping algorithm

A high‐performance microstrip lowpass filter with coplanar waveguide as the ports is proposed and analyzed. By cascading asymmetric hairpin resonators, a compact elliptic function low‐pass filter with wide stop band was realized. The filter was optimized using aggressive space mapping algorithm, and finally a filter with a cut‐off frequency of 11.8 GHz was obtained. Stop bandwidth with attenuation level better than −27 dB extends from 15.6 to 36 GHz. Also, the maximum insertion loss in the passband is 0.9 dB and the return loss is better than −22 dB. The filter is manufactured on the silicon wafer using micro‐electromechanical systems process, and the measured results in good agreement with the simulation results.
Nanoporous copper from dual-phase alloy families and its technology application in lithium ion batteries

Abstract Nanoporous metals have recently attracted considerable interest in a wide variety of applications, including catalysis, sensors, actuators, fuel cells, microfluidic flow controllers, and so forth. Their inherent special morphology and characteristic is expected to have superior performances, such as the open porosity, high surface area, good electron conductivity, extremely clean metal surface, and high structural stability with no agglomeration in comparison with other nanostructures. Here, we mainly review our group’s systematical studies related to nanoporous copper (NPC) from dual-phase alloy families, aiming at giving a comprehensive summary about our step-by-step progress in its fabrication, microstructure evolution, dealloying behavior, and one-step strategies to special 3-D bicontinuous porous architectures in the last 5 years. Meanwhile, some encouraging test findings on the original application of NPC in lithium ion batteries have also been covered briefly in the last part of this review, which would open a window toward their other technology applications in high-performance electrochemical devices within the green, new energy industry.
“Sometimes You Reach a Point Where You Feel Burnt Out”, Job Satisfaction and Psychosocial Well Being of COVID-19 Frontline Health Workers: a Qualitative Study in Two Ugandan COVID-19 Treatment Centres.

BACKGROUND: COVID-19 has become a major global health challenge, with Uganda reporting over 25,000 cases. Frontline healthcare workers (HCWs) are the most at risk population for mental health disorders yet their well-being is key to combating the pandemic. We explored the psychosocial wellbeing and job satisfaction of COVID-19 Frontline HCWs in Uganda.METHODS: This was a qualitative study done at Entebbe regional Referral hospital (ERRH) and Mulago National Referral hospital (MNRH) in September 2020. Data collection was through 3 Focus Group Discussions (FGDs) with 5 participants for each FGD. 2 FGDs were at MNRH and 1 at ERRH. Participants included; doctors, nurses, laboratory personnels, hygienists and a security personnel. Interviews were audio-recorded, transcribed and analyzed thematically using Nvivo version 12 software.RESULTS: Despite the challenges HCWs faced, they were motivated to work when they saw patients recover and go home safely. Participants felt the Pandemic was unprecedented and as a result no person or government was fully prepared. Big unexpected patient crowds caused limited and/ or inconsistent medical supplies. Additionally, Poor Procurement lines affected sufficiency of medical supplies and equipment such as medical gowns, drugs, PPE, alcohol, beds, and COVID-19 testing kits. There was knowledge gap among the HCWs regarding COVID-19 management. This put the staff in a Panic situation hence practicing “trial and error” treatment. Poor remuneration in terms of low or delayed Salary, lack or delay of risk allowance caused dissatisfaction among staff and were affected mentally given that they were involved in risky work yet their families were suffering economically.CONCLUSION: HCWs were remarkably stressed, exhausted and burnt-out due to the heavy workload and inadequate personal protective Equipment. These findings depict a need of creating a conducive environment for these HCWs. Government and ministry should re-strategize on how well to take care of Covid 19 frontline HCWs to save lives.
Data Quality Assessment on Lecturer Primary Data: A Case Study on Higher Education Database at Ministry of Education and Culture Republic of Indonesia

The quality of an organization’s data is an important component that can influence various policies taken in technical and strategic terms. This study aims to analyze the quality of basic data for lecturers on resource information systems whose data is integrated with the Higher Education Database (PDDikti). Measurement of data quality based on the rules that have been set in the main unit of higher education data management which is then determined in this study includes 4 dimensions of data quality, namely completeness, validity, accuracy, and currency. The application of quantitative methods by processing data and then analyzing the quality of the data using qualitative methods based on the dimensions that have been determined for the basic data quality assessment for lecturer in every tertiary institution in Indonesia. The results showed that the quality of the data had been resolved by 91.94% so that it can be used as a basis for decision making according to predetermined standards. The results of this data quality research can be used as supporting information in policy making in terms of developing and improving data quality in the scope of higher education, especially those related to the quality of basic data for lecturers.
SKNet: Detecting Rotated Ships as Keypoints in Optical Remote Sensing Images

Detecting rotated ships is difficult in optical remote sensing images due to the challenges of complex scenes. Existing advanced rotated ship detectors are typically anchor-based algorithms that require plenty of predefined anchors. However, the use of anchors brings three critical problems: 1) a large number of anchors bring a huge amount of calculation; 2) the attributes (e.g., size and aspect ratios) of anchors are designed via ad hoc heuristics; and 3) only a tiny fraction of anchors that overlap with ground-truth bounding boxes of ships tightly can be considered as positive samples, which causes an extreme imbalance between positive and negative samples. As a result, the detection accuracy will be influenced seriously when the design of anchors is not suitable. To address the above problems, this article proposes a novel anchor-free rotated ship detection framework, called SKNet, which detects rotated ships as keypoints in optical remote sensing images. In SKNet, a ship target is modeled as its center keypoint and morphological sizes, including the width, height, and rotation angle. Accordingly, we design two customized modules: orthogonal pooling and soft-rotate-nonmaximum suppression (NMS), where the former is to improve the prediction accuracy of the center keypoint and the morphological size, and the latter is to effectively remove redundant rotated ship detection results. Extensive experiments are conducted to demonstrate the effectiveness of SKNet on three optical remote sensing image data sets: HRSC2016, DOTA-ship, and HPDM-OSOD, which is collected by ourselves and published in this article. Empirical studies show that SKNet achieves state-of-the-art detection performance while being time-efficient. Overall, SKNet achieves the best speed–accuracy tradeoff.
Studying QGP transport properties in a concurrent minijet+hydro framework

Minijets are ubiquitous in heavy-ion collision experiments. However, they are often excluded from the hydrodynamic simulations of QGP as they do not thermalize at short time scales and are not treated as part of the collective medium. Using a concurrent jet+hydro framework, we show that the minijets could account for a significant portion of particle multiplicity. Therefore, the energy deposition from minijet-medium interactions can substantially modify the QGP transport properties inferred from model-to-data comparisons.
Implementation of ICAP Principles through Technology Tools: Exploring the Alignment between Pedagogy and Technology

Higher education institutions around the world have encountered unprecedented times in the year 2020 due to the impact of the COVID19 pandemic All academic institutions were forced to an online mode of learning due to the sudden lockdown imposed across different countries to curb the growth of the pandemic Faculty who were teaching courses had to radically change their pedagogy and adopt technology tools that could support virtual synchronous learning In this paper, we explore one such effort where faculty at a private undergraduate engineering institution reimagined how they could apply and teach innovative teaching methodologies through technology tools Faculty teaching engineering courses have to often utilize active and collaborative pedagogical techniques to help students achieve higher level cognitive outcomes and we describe how the same techniques could be implemented through online mode of teaching All the faculty prior to the start of the semester has undergone a 3-week faculty development program on technology-enhanced learning During the program, the faculties were encouraged to identify technology tools that can be used to implement pedagogic techniques that are aligned to the Interactive Constructive Active and Passive (ICAP) framework We describe in the paper the process followed by the faculty to align technology tools with the various pedagogies identified for the courses We provide a list of various pedagogies by mapping them to the ICAP framework and discuss how the technology tools were used to implement them The discussion in this paper will provide engineering educators with much needed insights on how to implement innovative pedagogies through technology tools The results can be used by faculty as they transition to a blended mode of learning post COVID19 © 2021, Rajarambapu Institute Of Technology All rights reserved
A Model-Based Sensor Fault Diagnosis Scheme for Batteries in Electric Vehicles

The implementation of each function of a battery management system (BMS) depends on sensor data. Efficient sensor fault diagnosis is essential to the durability and safety of battery systems. In this paper, a model-based sensor fault diagnosis scheme and fault-tolerant control strategy for a voltage sensor and a current sensor are proposed with recursive least-square (RLS) and unscented Kalman filter (UKF) algorithms. The fault diagnosis scheme uses an open-circuit voltage residual generator and a capacity residual generator to generate multiple residuals. In view of the different applicable state of charge (SOC) intervals of each residual, different residuals need to be selected according to the different SOC intervals to evaluate whether a sensor fault occurs during residual evaluation. The fault values of the voltage and current sensors are derived in detail based on the open-circuit voltage residual and the capacity residual, respectively, and applied to the fault-tolerant control of battery parameters and state estimations. The performance of the proposed approaches is demonstrated and evaluated by simulations with MATLAB and experimental studies with a commercial lithium-ion battery cell.
Profiles in understanding operations with rational numbers

ABSTRACT Students often show difficulties in understanding rational numbers. Often, these are related to the natural number bias, that is, the tendency to apply the properties of natural numbers to rational number tasks. Although this phenomenon has received a lot of research interest over the last two decades, research on the existence of qualitatively different profiles regarding students’ understanding is scarce. The current study investigated the different ways students reasoned in arithmetic operation items with fractions and decimals. A cross-sectional study with 1,262 participants from 5th to 10th grade was performed. A TwoStep Cluster Analysis revealed eight different student reasoning profiles. We found that the natural number bias is first overcome in addition and subtraction, and later in multiplication and division. Moreover, differences regarding representation were only found in addition and subtraction items, indicating that natural numbers interfered more strongly in fractions than in decimal numbers. Finally, results showed that some students’ difficulties with rational number multiplications and divisions had other explanations than the natural number bias.
Exploring Risks in the Adoption of Business Intelligence in SMEs Using the TOE Framework

The business success of small- and medium-sized enterprises (SMEs) increasingly relies on the adoption of various technological innovations. For today’s unpredictable business operations, business intelligence systems (BISs) represent one of the most prominent tools with a significant impact on business performance. However, different internal and external risks may influence BIS adoption. The goal of this paper is to investigate the risks that impact BIS adoption in SMEs, using the Technology, Organization, and Environment (TOE) framework. For that purpose, we develop the logistic regression model, using data collected by a questionnaire survey using a sample of 100 Croatian SMEs. The results indicate the applicability of the TOE theoretical framework for examining BIS adoption in SMEs. Given the results obtained, the sampled SMEs should take into account the internal risks related to the organizational dimension and external risks related to the environmental dimension. Our research did not reveal the significant impact of technological risks that encompass characteristics of considered technological innovation related to the technology dimension.
Numerical Simulation Analysis of Ag Crystallite Effects on Interface of Front Metal and Silicon in the PERC Solar Cell

In the fabrication of crystalline silicon solar cells, the contact properties between the front metal electrode and silicon are one of the most important parameters for achieving high-efficiency, as it is an integral element in the formation of solar cell electrodes. This entails an increase in the surface recombination velocity and a drop in the open-circuit voltage of the solar cell; hence, controlling the recombination velocity at the metal-silicon interface becomes a critical factor in the process. In this study, the distribution of Ag crystallites formed on the silicon-metal interface, the surface recombination velocity in the silicon-metal interface and the resulting changes in the performance of the Passivated Emitter and Rear Contact (PERC) solar cells were analyzed by controlling the firing temperature. The Ag crystallite distribution gradually increased corresponding to a firing temperature increase from 850 ∘C to 950 ∘C. The surface recombination velocity at the silicon-metal interface increased from 353 to 599 cm/s and the open-circuit voltage of the PERC solar cell decreased from 659.7 to 647 mV. Technology Computer-Aided Design (TCAD) simulation was used for detailed analysis on the effect of the surface recombination velocity at the silicon-metal interface on the PERC solar cell performance. Simulations showed that the increase in the distribution of Ag crystallites and surface recombination velocity at the silicon-metal interface played an important role in the decrease of open-circuit voltage of the PERC solar cell at temperatures of 850–900 ∘C, whereas the damage caused by the emitter over fire was determined as the main cause of the voltage drop at 950 ∘C. These results are expected to serve as a steppingstone for further research on improvement in the silicon-metal interface properties of silicon-based solar cells and investigation on high-efficiency solar cells.