Miracle-dz/UniFAR-FTUs huggingface dataset:
Treatment of Simulant Feces Using Microwave Plasma

It is estimated that 40% of the world's population lack adequate sanitation facilities and over 90% of feces generated by them are disposed without treatment, making lakes and rivers polluted [1] . There have been lots of studies employing plasma to the treatment of solid waste [2] . Microwave plasma carries the advantages of compact, lightweight and is suitable for household or small equipment [3] . Considering that human feces compose a median value of 75% H 2 O and of the solid fraction organic material in it makes up over 84%, we divided the treatment process into two steps: first, drying fresh feces by microwave; then, combust dry feces with microwave plasma torch [4] .
Prototype Design of IoT Water Turbidity Sensor-Based For Freshwater Fisheries

The turbidity of the water is caused by the accumulation of organic matter which causes toxic gases as well as a nesting place for vibrio which is detrimental to fish. Decree of the Minister of Fisheries and Marine Affairs No. KEP . 28/MEN/2004 sets the standard for turbidity of water for shrimp farming in ponds 50 NTU. However, pond farmers still use their instinct to purify pond water without using a valid and standard measuring instrument. Trends in measurement and monitoring that initially only focused on local areas such as conventional turbidimetry and nephelometry, can be updated with superiority through easy user access anywhere and anytime. Therefore, a prototype of an IoT -based water turbidity sensor was initiated using the Blynk server as cloud storage and the Blynk app as an interface for users. This study also compares the performance of various pairs between transmitter components in the form of UV LED and white LED-phototransistors, photoresistors, and photodiodes as receivers so that six pairs of components are produced as water turbidity sensors. The results showed that measuring the turbidity of Vannamei pond water by pairing the transmitter-receiver with UV LED-photo diode was the closest to the Lutron TU-2016 validator with an error of 2.32 NTU, repeatability 0.98, accuracy 93.63%, and precision ±0.65.
A Large Scale Content Ranking Platform as Applied to E-commerce Store Fronts

An e-commerce marketplace like Flipkart displays hundreds of millions of promotional content in a day on its home page. To display content, we predict the probabilities of various responses by a user for any given content. In this paper, we describe the various considerations and challenges in building a ranking platform for these content at Flipkart. We describe the architecture and delve into the solutions used in practice, in modelling, training, scaling, data correctness, freshness and metrics to provide a comprehensive overview of such a system.
Evaluation of E-Tax Quality Implementation Criteria: The Case of Self-Employed Taxpayers

This paper examines the significant e-tax quality implementation criteria within the emerging economy by precisely focusing on self-employed taxpayers in Nigeria. This study employs quantitative method of analysis. A total of 181 data collected through convenience sampling was used for the analysis. The psychometric properties were assessed firstly using exploratory factor analysis in identifying the component, followed by confirmatory factor analysis to check for reliability and cross validation of the items. The result shows that the six components generated from the exploratory factor analysis are important criteria to the e-tax quality implementation criteria in the sequence of Compatibility, Tangible, Complexity, Reliability, and Ease of use and Affordability in Nigeria. The limitations are that this paper uses only quantitative method of analysis and the population is limited to individual income taxpayers who are self-employed. Also a small sample size is used for the study. The practical implication is for tax authority to consider the effective use of e-tax quality implementation criteria in Nigeria. Further study could consider extending to other taxpayers, such as corporate taxpayers and also increasing the sample size.
Comparative Study of Performance of SiC SJ-MOSFETs Formed by Multi-epitaxial Growth and Trench-filling Epitaxial Growth

Reducing the process cost is a key issue in the manufacture of SiC superjunction-metal–oxide–semiconductor field-effect transistors (SJ-MOSFETs). In this study, we compared static and dynamic characteristics of a 1.2 kV-Class SJ-MOSFET fabricated by the multi-epitaxial growth (ME) method and the trench-filling epitaxial growth (TFE) method, which is expected to have a lower process cost. Comparably low specific on-resistance and switching losses were observed for the SJ-MOSFETs fabricated by both methods. However, the non-degraded carrier lifetime of the TFE-SJ device causes a large bipolar degradation, as compared with that of ME-SJ device. These results indicate that TFE-SJ devices have identical static and dynamic characteristics to those of ME-SJ devices, but their process cost is lower. However, the challenge of eliminating bipolar degradation by carrier lifetime control remains.
IEEE President K. J. Ray Liu, “Follow Multiple Paths,” Changing the World With Microwave Time Reversal Focusing

This is the sixth in our Microwave Pioneer series in which we are privileged to provide our readers with a very special subject: current IEEE President K. J. Ray Liu. Professor Liu's inclusion in this series is not due to his position as leader of the IEEE, but rather to his influence and leadership in the field of indoor surveillance and tracking using microwaves. His discovery, demonstration, and application, of microwave multi-path time reversal focusing for use in positioning and tracking, when coupled with recent advances in wireless communications, are primed to have worldwide impact. The imminent roll-out of commercial systems through Professor Liu's company, Origin Wireless AI, could change the very nature of our society through its many potential applications in indoor monitoring, tracking, and motion sensing using existing Wi-Fi infrastructure. The implications for both improved security and health care in the home and office – as well as the accompanying controversies over issues of privacy, are profound. It is appropriate that an individual who has already had a considerable role in shaping our local signal processing and microwave fields, as well as the broader IEEE community, should extend his influence to our society at large. With 12 books, 18 book chapters, 6 special issue journal releases, more than 800 refereed journal and conference publications, over 70 patents and dozens of editorials and magazine pieces, you will certainly appreciate Professor Liu's multi-path impact as you read about his multi-path career!
Application of the Two-layer Wrapper-Embedded Feature Selection Method to Improve Genomic Selection

Breeders and crop scientists aim to improve the genetic gain, i.e., increasing the rate of genetic improvement, within a breeding population over time. Developing an efficient Genomic Selection (GS) algorithm is primarily affected by multiple factors, such as, the performance of the genomic prediction methods, breeding parent selection strategy and the simulation platform in which the GS algorithm is deployed. This paper aims at improving the genetic gain not only by incorporating a two-layer feature selection (FS) method in the breeding process. This two-layer FS method is a pre-processing wrapper-embedded FS method that attempts to enhance the prediction performance in genomic prediction (GP) which ultimately will improve the genetic gain. It is the first time that the application of the two-layer FS method has been analyzed on multiple GS, GP, and simulation platforms. This paper proposed a comprehensive comparison approach that the performance of any GS and GP algorithms can be tested using the two-layer feature selection methods in different scenarios. The results on a real Maize data set demonstrated that incorporating the proposed FS method in GS algorithms create better-performing progeny throughout the generations compare to the case of not including it. Moreover, the results confirm the superiority of incorporating two-layer FS method GS algorithms within multiple scenarios. The scenarios are built on the combination of different GS optimizer with different prediction methods within different nature simulators.
What Can Program Repair Learn From Code Review?

Over the past fifteen years, research on automated program repair has matured, and transitions to industry have begun. However, an impediment to wider adoption is concern over automatically gen-erated patch correctness. A review of 250 program repair research papers suggests that this concern can be addressed by adapting practices from modern code review, such as multiple anonymized reviews and checklists with well-defined terminology, to better evaluate the correctness and acceptability of plausible patches. In this paper, we argue that adopting such practices from modern code review for automated program repair research can increase developer trust, paving the way for wider industrial deployments.
Topology-Aware Reliability Assessment by Graph Neural Networks

This paper presents a preliminary study on bulk power system reliability assessment using graph neural networks. The proposed method is an end-to-end pipeline that can directly predict the reliability index. The Monte Carlo simulation and the end-to-end machine learning paradigm for bulk power system reliability assessment are introduced. Then, the basic principles of graph signal processing and graph neural networks are explained. Dataset generation and feature engineering for applying graph neural networks on end-to-end reliability assessment under situations of system topology-change are illustrated in detail. Experiment results on the RTS-79 system by the proposed graph neural networks pipeline demonstrate an obvious speed improvement over the regular Monte Carlo simulation method with acceptable prediction errors. Future research directions are also suggested in the final section.
System Integration of a Tour Guide Robot

In today’s world, people visit many attractive places. On such an occasion, It is of utmost importance to be accompanied by a tour guide, who is known to explain about the cultural and historical importance of places. Therefore, a human guide is necessary to provide tours for a group of visitors. However, Human tour guides might face tiredness, distraction, and the effects of repetitive tasks while providing tour service to visitors. Robots eliminate these problems and can provide tour consistently until it drains its battery. This experiment introduces a tour-guide robot that can navigate autonomously in a known map of a given place and at the same time interact with people. The environment is equipped with artificial landmarks. Each landmark provides information about that specific region. An Animated avatar is simulated on the screen. IBM Watson provides voice recognition and text-to-speech services for human-robot interaction. The experimental results show that the robot takes average time of 10000 seconds to provide a tour. TEB and DWA local planner are compared by allowing the robot to autonomously maneuver the environment for 9 trials which is tabulated in section V.
Interaction Mechanism Between CGD and CDS Based on Space Competition and Optimization Method of Dynamic Characteristic for 600V Super-Junction VDMOS

A novel view of the interaction between C<inf>GD</inf> and C<inf>DS</inf> based on space competition is proposed in this paper. For small cell pitch super-junction vertical double-diffused MOSFET (SJ VDMOS), C<inf>GD</inf> and C<inf>DS</inf> have a close interaction in the center part of the depletion region. By changing the source-end structure, the electric field lines originally contributed to the C<inf>GD</inf> can be collected by the source end, thereby realizing the indirect modulation of the C<inf>GD</inf>. C<inf>GD</inf> and C<inf>DS</inf> present an opposite trend as one falling and the other rising. By this theory, we propose a SJ VDMOS with additional P-type implantation (API) based on a multi-epitaxy/multi-implant platform. Both simulated and experimental results validate the feasibility of reducing C<inf>GD</inf> with the easy-modified C<inf>DS</inf>. SJ VDMOS with API realizes a faster switching process, and the overshoot remains low while achieving BV > 600 V and a low R<inf>ON,SP</inf> of 11.35 mΩ∙cm<sup>2</sup>.
Land use / land cover changes monitored by NDVI index in Rangamati, Bangladesh for the last four decades

The study of land use/land cover dynamics has been increasingly important in the research of earth surface natural resources. The normalized difference vegetation index (NDVI) is a widely used method for observing land use/land cover change detection. The surface land resources are easily interpreted by computing their NDVI. This study aimed at analyzing Land Use/Land Cover (LULC) changes between 1977 and 2019 in the Rangamati district, Bangladesh using reclassify the NDVI values of the Landsat satellite image and identifying the main drivers to change LULC by household survey. Five different years of Landsat images were used to extract the NDVI values January of 1977, 1989, 2000, 2011 and 2019. The NDVI values are initially computed using the user define method to reclassify the NDVI map to create land use land cover map and change detection. The highest NDVI value was found in 1977 (0.88) which indicates healthy vegetation at that time and thereafter it followed a decreasing trend (0.79 in 1989, 0.74 in 2000, 0.71 in 2011 and 0.53 in 2019) which shows a rapid vegetation cover change in the study area. Analysis of the household survey revealed that population growth, migration from plain land, rapidly urbanization, Kaptai Dam, migration policy of government, high land price, unplanned development, development of tourism industry, firewood collection and poverty have been identified as the major drivers of LULC changes in the study area. Furthermore, analysis of NDVI confirms that the forest vegetation area is being decreased and settlement area and sparseness of vegetation are being increased. The accuracy of the NDVI-based classified images is assessed, using a confusion matrix where overall classification accuracy and Kappa coefficient are computed. The overall classification accuracy was 84% - 90% with corresponding Kappa statistics of 80% - 88% for TM and OLI-TIRS images, respectively. The study serves as a basis of understanding of the LULC changes in the southeastern part of Bangladesh. Bangladesh J. Agri. 2019-2021, 44-46: 127-140
Non-verbal signs of personality: Communicative meanings of facial expressions

Abstact. There is a lot of evidence that most people are capable of recognizing emotions by facial expressions. What information does a facial expression usually provide? Can emotions be shown without facial expressions? Can there be facial expressions without a corresponding emotional state? Are there individual facial expressions? The studies of various aspects of non-verbal communication show both similarities and differences in non-verbal behavior. It is argued that similarities are most evident at the individual level, when the focus is on the objective, formal features of behavior, while differences are more likely to be found when the analysis focuses on the relationship between individuals and interpersonal meanings of behavior. Despite the rapid expansion of research on non-verbal communication, most of it describes simple differences in the display of non-verbal signals. Although they differ in almost every other respect, most facial measurement methods focus on what is seen, on what the researcher can identify when seeing some facial movements. Most of the research methods applied are not sufficient for the study of this complex, multidimensional issue. Like all basic studies of communicative processes, proxemics is more about how than why, and more about structure than content. The article focuses on the question whether non-verbal behavior reflects cultural similarities or differences, and whether different levels of analysis allow to observe both cultural homogeneity and diversity inherent in most acts of non-verbal behavior. The authors consider the data of laboratory experiments on the relationship between emotions and adults’ facial expressions: some studies confirm the high consistency between fun and smiling, and from the low to moderate consistency between other positive emotions and smiling. The available evidence on surprise and disgust suggests that these emotions are accompanied by their ‘traditional’ facial expressions or even some components of such expressions only in a minority of cases. The American anthropologist, one of the founders of kinesics, Birdwhistell introduced this term for the complex study of facial expressions, poses, gait, and visible movements of arms and body. Birdwhistell argues that body language is determined by cultural environment rather than universal genetic programs. Birdwhistell defines kinesics as “the study of body-motion as related to the nonverbal aspects of interpersonal communication”. He argues that communication with body motion is systemic, socially learned and communicative unless proven otherwise. The article considers in detail the works and theories of Birdwhistell who often had to admit that some of his ideas were controversial. The authors conclude that Birdwhistell’s works have serious mistakes, and other researchers failed to develop his theory of kinesics. Thus, the authors consider the research in this field focusing on the so-called recognition of the communicative meanings of facial expressions.
Comparison of Albumin/Globulin (A/G) Ratio Between Pregnant and Lactation of Thin-Tail Sheep

The albumin/globulin (A/G) ratio can be an immunological indicator of sheep which can be influenced by reproductive status such as pregnant and lactation conditions. However, a study of A/G ratio during pregnant and lactation in thin-tailed sheep is still lack. This study aimed to determine the levels of A/G ratio in thin-tailed sheep during pregnancy and lactation. This study used twelve of ewes thin-tailed sheeps (seven pregnant sheeps, and five lactating sheeps) rearing in Berbah, Sleman, Yogyakarta. Blood samples were collected through the jugular vein and filled into the EDTA tube and then albumin and total protein were measured. The levels of globulin were calculated by subtracting the total protein with albumin. The mean of A/G ratio in pregnant and lactation thin-tailed sheep was 0.72±0.18, and 0.57±0.15, respectively. Statistical analysis showed that there was no significantly difference in A/G ratio between pregnant and lactation (P>0.05). In conclusion, the difference in physiological status (pregnancy versus lactation) had no significant effect on the A/G ratio in thin-tailed sheep.
Animalising and Mechanising Self-Determined Women Characters Regardless of Their Class Structure in Jasoda — A Feministic Perspective

The study illustrates that sexual harassment endured by women, is no way related with their class, position, hierarchy, culture, place or security. Jasoda contributes to this research by exhibiting the women characters belonging to varied societal standards undergoing abuse and oppression regardless of the hierarchal structure. The author surprises the readers by drafting women characters with self-determined characteristics and stooping to bear the patriarchal pressure exerted over them. The study throws light on the complex psychic behaviour of the independent woman protagonist, successful in sustaining herself and the family all by her own, yet subduing to her husband’s patriarchal oppression. Patriarchy steps forward in every situation where women are objectified or animalised. The paper further studies the animalisation and mechanisation of the female body by the male patriarch and also focuses on the breakage of stereotypes, built by the patriarchal power, over women society and femininity.
Functions of Breast Cancer Predisposition Genes: Implications for Clinical Management

Approximately 5–10% of all breast cancer (BC) cases are caused by germline pathogenic variants (GPVs) in various cancer predisposition genes (CPGs). The most common contributors to hereditary BC are BRCA1 and BRCA2, which are associated with hereditary breast and ovarian cancer (HBOC). ATM, BARD1, CHEK2, PALB2, RAD51C, and RAD51D have also been recognized as CPGs with a high to moderate risk of BC. Primary and secondary cancer prevention strategies have been established for HBOC patients; however, optimal preventive strategies for most hereditary BCs have not yet been established. Most BC-associated CPGs participate in DNA damage repair pathways and cell cycle checkpoint mechanisms, and function jointly in such cascades; therefore, a fundamental understanding of the disease drivers in such cascades can facilitate the accurate estimation of the genetic risk of developing BC and the selection of appropriate preventive and therapeutic strategies to manage hereditary BCs. Herein, we review the functions of key BC-associated CPGs and strategies for the clinical management in individuals harboring the GPVs of such genes.
Is terahertz emission a good probe of the spin current attenuation length?

Terahertz (THz) emission from magnetic films has recently become an important characterization tool of spintronic properties, particularly since no patterning is required. One such property of interest is the spin-current attenuation length. When separating a magnetic film from a spin-to-charge converter with a light metal, the emitted intensity reduces almost exponentially with the thickness of the spacer. However, the extracted characteristic length is more than an order of magnitude smaller than the spin diffusion length measured in equilibrium. In this work, we experimentally and theoretically demonstrate that most of the observed decay in the THz emission is of optical (THz) origin. We are able to estimate a spin current attenuation length for Cu of ∼50 nm in much closer agreement with spin diffusion length measurements. We conclude that THz emission remains a powerful characterization technique, but due to the high number of intricate conversion mechanisms, and most importantly, due to the high sensitivity to changes in the optical properties, extracting absolute numbers for spintronic phenomena remains extremely challenging.
Model Fitting and Testing for Non-Gaussian Data with Large Data Sets

1996 i Acknowledgements I would like to express my deepest gratitude to my advisor, Professor Grace Wahba, for her invaluable advice during the course of this dissertation. I would also like to thank the members of my nal exam committee, ProfessorsMadison for its nancial support and excellent computer facilities. Finally, I would like to convey my sincerest regards to my parents and sister for their love and support. ii Abstract We consider the application of the smoothing spline to the generalized linear model in large data set situations. First we derive a Generalized Approximate Cross Validation function (GACV), which is an approximate leave-out-one cross validation function used to choose smoothing parameters. In order to apply the GACV function to a large data set situation, we propose a corresponding randomized version of it. To reduce the computational intensity of calculating the smoothing spline estimate, we suggest an approximate solution and a clustering method to choose a subset of the basis functions. Combining randomized GACV with this approximate solution, we apply it to binary response data from the Wisconsin Epidemiological Study of Diabetic Retinopathy in order to establish the accuracy of the model when applied to a large data set. iii Contents Acknowledgements i Abstract ii 1 Introduction 1