Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of deep learning-based crack assessment technique to civil structures

In this study, a deep learning-based automated crack detection technique has been applied to real structures. The deep learning model used in this study is a Mask R-CNN model pre-trained with 200,000 COCO dataset, and a transfer learning is performed using training data collected from Internet and the other bridges. Various types of cracks are marked as ground truths on more than 1,000 images with 1000×1000 pixel resolution for the training, and they are used for the transfer learning. The trained model is developed to distinguish cracks from the concrete surface, especially against similar objects that exhibit color and contrast features similar to those of cracks. The developed model is applied to three types of civil structures, e.g., a bridge, a tunnel, and a concrete road, and the detection results are analyzed in depth using performance measures. The result shows that the carefully trained deep learning model can work as an effective alternative to the current visual inspection. 1 GENERAL INSTRUCTIONS Given that concrete is the major construction material worldwide, cracks need to be assessed during the maintenance of concrete structures for mainly two reasons: durability and aesthetics. Crack is a crucial index visually showing loading condition of a structure. Furthermore, crack can expose rebars in concrete to water and air, resulting in the corrosion and further deterioration. Wide cracks may attract the attention of people and make them uncomfortable, regardless of mechanical effects to structural safety. Despite of the importance, however, current crack assessment is mostly dependent on visual inspection that has some drawbacks, such as subjective decision according to inspector’s expertise, high labor intensity, expensive logistic time, etc. To overcome the drawback with the support of ICT techniques, civil engineers put a lot of efforts to replace visual inspection with computer vision (CV) inspection. The CV inspection is actively being implemented to steel corrosion detection (Valeti and Pakzad, 2017), concrete spalling detection (German, Brilakis and DesRoches, 2012). Furthermore, many researchers attempted to develop CV inspection methods to assess cracks that has the smallest visibility among the concrete damages (Hutchinson and Chen, 2010). But the CV inspection methods for cracks are still in the laboratory, since most of them are developed under idealized environment. Rapid development of deep learning based on convolutional neural networks (CNNs) is now solving many difficulties in the real-world CV techniques. The CNN models such as ResNet (He et al., 2016) enabled automated feature extraction to classify various kinds of objects in images. Answering the rapid development of deep learning, many attempts have been made to implement deep learning to detect cracks. Yang et al. (2018) detected crack using a FCN and measured the width of cracks on the pixel level. Kim and Cho (2018a) detected cracks using 5-
Real-time video image processing based on Kerr soliton crystal microcombs

Advanced image processing will be crucial for emerging technologies such as autonomous driving, where the requirement to quickly recognize and classify objects under rapidly changing, poor visibility environments in real time will be needed. Photonic technologies will be key for nextgeneration signal and information processing, due to their wide bandwidths of 10’s of Terahertz and versatility. Here, we demonstrate broadband real time analog image and video processing with an ultrahigh bandwidth photonic processor that is highly versatile and reconfigurable. It is capable of massively parallel processing over 10,000 video signals simultaneously in real time, performing key functions needed for object recognition, such as edge enhancement and detection. Our system, based on a soliton crystal Kerr optical micro-comb with a 49GHz spacing with >90 wavelengths in the C-band, is highly versatile, performing different functions without changing the physical hardware. These results highlight the potential for photonic processing based on Kerr microcombs for chip-scale fully programmable high-speed real time video processing for next generation technologies.
Comparison between Neural and Statistical translation after transliteration of Algerian Arabic Dialect

Research on Arabic Dialect Treatment has recently become important in the literature. Although most work on these dialects considers only the messages or the portion of text written in Arabic letters, another style of writing has emerged on social media. This style is known by Arabizi and combines between Latin letters and numbers. To address this emergent problem in the context of automatic translation, we present an Arabic dialect translation system composed by two modules: Transliteration and translation. We develop each module with a statistical and a neural model. To test our system, we used the Algerian portion of a multi-dialectal Arabic corpus named PADIC. Experimental results show that a good transliteration improves the translation results. Moreover, the neural transliteration gives better results than the statistical transliteration. However, the statistical translation still gives better results that the neural translation.
Terahertz technology: A Review on dental perspective

Significant act of spontaneities of existing methods and new explorations are going on in the improvement of fresher imaging modalities that could change the study of dental radiology. Imaging dental tissues has been a challenge due to its different physical and chemical properties. To overcome this, terahertz radiation (THz) came into use for imaging purpose. THz imaging is very encouraging in scientific and biomedical applications. Terahertz imaging doesn't cause any ionization peril on organic samples because of low energy of THz radiation. Despite the fact that it is firmly absorbed by water, which displays extremely interesting physical and chemical properties that add to solid interaction with THz radiation and teeth can still be viewed in 3-dimension. Terahertz pulsed imaging (TPI) can be utilized in the early detection of dental caries and defects in the tooth structure without using x-rays. With the development of coherent sources, terahertz technology is used widespread from biomedicine to telecommunications. In this paper we present a short review of terahertz radiation from the point of dental imaging. We discussed the development of terahertz radiation from its initial state till its recent advancement; viable terahertz sources; described its modern applications in dentistry and various fields.
Use of Gadgets in Biology Classes as a Means of Increasing Students' Motivation

The article highlights the current problem of motivating students to learn. The use of gadgets in the educational process can positively affect the motivation of students to learn, involve them in creative activities, as well as interest in better and more honest performance of tasks. Since most students are bored at school, it is difficult to involve them in active work in the classroom. The problem of increasing student activity in the classroom is a fairly common and urgent today. It is difficult to imagine a world without modern technology. Laptops, mobile phones, tablets, computers and other gadgets have become good friends for people. They are real colleagues: they help perform many tasks, which normally take a long time to solve. As with any adult, gadgets play a significant role in children's lives. Teenagers and mobile phones are the same inseparable things as teachers and well-prepared notes. Children are increasingly choosing entertainment in front of a monitor, instead of playing outside or walking with family. Social networks, wellthought-out computer games, take the first place among youth hobbies. That is why the important task facing teachers is to arouse interest in learning, to motivate students. And here ICT are simply irreplaceable: they are the chain that connects the interests of teachers and students. You just need to learn to creatively use children's hobbies with gadgets. Our research has shown how students' attitudes towards biology lessons and their motivation to learn have changed after using the online lab on the Go-Lab platform, the Kahoot application, and QR-codes.
The Relationship between Social Health and Work Conscience of Tehran Councilors

Work conscience can be considered as a situation in which people in the society in various jobs, attempt to do their job accurately and completely. Considering the significance of discussing work conscience, the present study aimed to investigate the relationship between social health and work conscience of councilors by using field method, survey technique, questionnaire tool and using SPSS and Smart PLS software. The statistical population of the present study included 3500 councilors of neighborhoods in Tehran according to the latest statistics. The results indicated a significant positive and direct relationship between social health (0.34) and its dimensions i.e. social correlation (P = 0.32), social participation (P = 0.40), social cohesion (P = 0.30), social acceptance (p=0.35), social self-actualization (p=0.33) and the work conscience of Tehran councilors. Therefore, all research hypotheses were confirmed. The results of the Smart PLS structural equation model showed that the effect of the independent variable of social health on the work conscience of Tehran councilors was 0.58.
The Relative Abundance Analysis of Microbial Community in the Baltic Sea

The microbial community is important to control the sustainability of water ecosystems. The microbial community also has a negative impact on the environment. In particular, the toxin of Algae Bloom in the Baltic Sea which is harmful to the environment and humans. Several previous studies have tried various machine learning methods to analyze algae growth, but with limited achievement. The 167 samples were collected from 2012 to 2013 by the Linnaeus Marine Observatory at 11 km off the shore of Kårehamn in the Baltic Sea. Here we analyze the abundance of the microbial community using the Operational Taxonomic Units (OTUs) based on the normalization method after filtering samples. The aim to analyze the composition of the microbial community based on the past measurement of microbial composition. It is the pre-processing of data which is the step toward the prediction in the future. The result shows large different variations in each of OTUs in the fractions from the same sample. Many OTUs that are very abundant in one fraction but very rare in the other fraction. The Large difference abundance of OTU composition make a major challenge when predicting OTU composition in the future. Further quantification of normalization method is required in the pre-processing of data to get the proper data for prediction. Keywords—Microbial community; Normalization data; Relative abundance, OTUs
A Typified Greedy Dynamic Programming Model for the MetaTrader Platform

Users of the MetaTrader platform and forex investors are usually perplexed and puzzled on the choice of the best values for take profit, stop loss, and pending order distance for trade orders and positions for profit optimization. By design, the MetaTrader platform contains so many constraints with diverse effects that mystify the traders and investors. For example, increasing the pending order distance automatically reduces the take profit while the effect of such a decision on the stop loss is uncertain. Furthermore, trading with a very high stop loss combined with low or moderate take profit values usually produces very nice looking profits for a period but results in great losses in the long run because of the swooping losses that accompany high stop losses when hit by the forex market price. I propose a typified greedy dynamic programming model for the MetaTrader platform for the optimization of the take profit, stop loss, and pending order distance values to guide investors’ decisions for optimal profitability. The model is a hybrid of a proposed typified greedy algorithm and dynamic programming algorithm. The proposed model makes a distinction between take profit, stop loss and pending order distance for the long orders, short orders and positions to clarify the effects of changes in the values of these data on an expert adviser’s profit. Research results show that my proposed model out-performed the conventional dynamic programming algorithm for profit optimization.
Experimental Evaluation of Power Consumption in Virtualized Base Stations

Network virtualization is intended to be a key element of new generation networks. However, it is no clear how the implantation of this new paradigm will affect the power consumption of the network. To shed light on this relatively unexplored topic, we evaluate and analyze the power consumption of virtualized Base Station (vBS) experimentally. In particular, we measure the power consumption associated with uplink transmissions as a function of different variables such as traffic load, channel quality, modulation selection, and bandwidth. We find interesting tradeoffs between power savings and performance and propose two linear mixed-effect models to approximate the experimental data. These models allow us to understand the power behavior of the vBS and select power-efficient configurations. We release our experimental dataset hoping to foster further efforts in this research area.
SELECTIVE LASER MELTING PROCESS

The quality and strength of a product fabricated by selective laser melting (SLM) process depend upon the physical behaviors of materials occur at the time of fabrication. Hence, it is necessary for the researchers to know the physical behaviours and the processing parameters which influence those behaviors to fabricate a highquality product. Numerous thermal and physical behaviours occur in the SLM process where thermal behaviors affect the physical behaviours of materials during fabrication. The notable physical behaviours are melting of powder, molten pool formation, solidification, amalgamation, separation, vaporization, spattering of powder and liquid material, Marangoni effect, capillary effect, vortex, gaseous bubble entrapment, keyhole formation, metallic vapor entrapment, explosion of the molten pool, instability of the pool, presence of powder particles without melting, partially melting powder particles, re-melting, excess heating, reheating and cooling, microstructural phase transformation, bending and shrinking. The physical behaviors are highly influenced by the manufacturing parameters namely energy density, laser power, scanning speed, hatch spacing, layer thickness, and scanning strategy. The behaviours can be regulated by controlling the mentioned processing parameters. This chapter has emphasized the physical behaviours of materials as well as the processing parameters which influence those behaviours and their effects on the product quality.
Floristic Survey: The Treatment of Gastrointestinal Disorders

The present study showed the diversity and importance of plants used to treat gastrointestinal disorders in Shivamogga district of Karnataka. We documented a total of 36 species belonging to 25 families and 33 genera used to treat gastrointestinal disorders in Shivamogga area. Among the plant parts used for gastrointestinal disorder leaf used the highest number (12), followed by fruit (7), rhizome (4), whole plant (4), root (3), seed (2), bark (1), vegetative bud (1), stem/bark (1) and fruit/twigs (1). Further, the existing information on traditional uses of medicinal plants are declining rapidly because of the lack of interest of young people to learn the traditional knowledge from the old medical practitioner. So the documentation and conservation of the information is essential.
COMPARATIVE GROWTH PERFORMANCE AND ECONOMIC EFFICIENCY OF INDIGENOUS ASEEL VARIETIES FED ON DIFFERENT DIETARY LYSINE REGIMENS

This study was planned to investigate the growth performance and economic efficiency of Lakha, Mianwali, Mushki and Peshawari varieties of Indigenous Aseel Chicken. For this purpose, 240 day old Aseel chicks 60 from each variety were selected and kept under randomized complete block design having factorial arrangement of 20 replicates with one bird in each [4(varieties)×3(lysine regimens)×20(replicates)=240]. Each of the 20 birds from four varieties were fed on lysine regimens containing 1.3 % lysine (L1) for 6 weeks, 1.4% and 1.2 % (L2) each for 3 weeks and 1.5%, 1.3%, 1.1% lysine (L3) each for subsequent 2 weeks. Data regarding different growth parameters were collected and analyzed by ANOVA technique while Duncan’s Multiple Range (DMR) Test was applied to compare the treatment means. The economic efficiency was also calculated. Significant (P<0.05) differences were observed in body weight, weight gain, FCR and feed efficiency (FE) of birds fed with L3 lysine regimen while the overall growth performance was better in Mushki variety of Aseel. The current study revealed that Mushki Aseel should be preferred in terms of its better growth performance while Lysine is better to be fed in L3 regimen.
The Use of an Online Tennis Learning Platform for Sedentary Adults

The purpose of this research was to analyse the impact of a web platform as a result of its use to support a leisure-time physical activity program based on the organized practice oftennis. The hypothesis of this research is based on the assumption that the use of a web platform for a recreational physical activity program, in particular a tennis one, will havebeneficial effects on the effectiveness of learning the game technique. The research was carried out on a sample of 47 volunteer subjects, all of them working in a sedentaryenvironment. The subjects of the study were divided into 3 groups, the intervention program consisted of 90-minute tennis training sessions, twice a week, for 4 months. Thestatistical analysis of the data was accomplished by using the IBM SPSS Statistics 20 program. At the end of the study, could be observed in total technical score, staticforehand, dynamic forehand, static backhand, dynamic backhand and serve score.
University of Birmingham A comprehensive review of techniques for natural fibers as reinforcement in composites:

Designing environmentally friendly materials from natural resources represents a great challenge in the last decade. However, the lack of fundamental knowledge in the processing of the raw materials to fabricate the composites structure is still a major challenge for potential applications. Natural fibers extracted from plants are receiving more attention from researchers, scientists and academics due to their use in polymer composites and also their environmentally friendly nature and sustainability. The natural fiber features depend on the preparation and processing of the fibers. AC CE PT ED M AN US CR IP T
Siting and Sizing of Charging Infrastructure for Shared Autonomous Electric Fleets

Business models rooted in shared economy, electrification, and automation are transforming urban mobility. Accounting for how these transformations interact is crucial if synergies are to be exploited. In this paper, we focus on how a cost-effective charging infrastructure for e-mobility can support the emergence of shared, autonomous mobility. This study addresses the problem of siting and sizing of charging stations for a fleet of shared autonomous electric vehicles (SAEVs). We develop a hybrid simulation-optimization model to find locations and numbers of chargers needed to serve charging demands. Our agent-based model provides an enhanced representation of SAEV operations allowing for smart charging and vehicle cruising when parking/charging is not available. Also, we model charging station placement as full covering optimization and solve the location-allocation problem simultaneously. Finally, we employ real-world trip data from ShareNow in Berlin to evaluate our approach for realistic demand patterns under different charging strategies and fleet sizes. The results show that charging station locations depend mostly on the spatial distribution of installation costs and charging demands. Moreover, charging strategies and fleet size affect the charging patterns and the required number of chargers as well as fleet performance.
The relationship between Gender Mainstreaming approaches and the Performance of Rice growers’ cooperative in Bugesera District, Rwanda

To assess the correlation between Gender mainstreaming approaches (gender incorporate prospectus, sex-disaggregated data, and gender budgeting) and the performance of Rice growers’ cooperative in Bugesera District, Rwanda. This study is an important tool for government, society, and the researcher by formulating Gender mainstreaming strategies to improve the state of development projects in the country. The descriptive and analytical research was adopted. The sample size of the study is 83 respondents drawn from the selected registered cooperative’s members in Bugesera District, Rwanda, and was determined by using Sloven’s formula. Data collection instruments were both primary and secondary which include questionnaires; interview guide and documentary review and a purposive sampling technique was used. Data was analyzed using computer software called Statistical Package for Social Scientists (SPSS) version 22. Quantitative data was analyzed using descriptive statistics, Chi-square, and multivariate analysis using SPSS v22 while qualitative data was analyzed thematically. Concerning the major findings related to the research question one, the study revealed that there is a positive relationship between Gender Mainstreaming approaches and Success factors of Rice growers' Cooperative as it was confirmed by the Pearson correlation(r) =0.787 ** . This means that there is a high positive correlation between the two variables.
Application of the integrated AE and HFCT sensors for online Dry-type Transformer Partial Discharge Monitoring. Case study

This study proposes a measurement technique to identify and determine the occurrence of partial discharge in the insulation of Dry-type transformers, as well as their criteria level. Concerning IEC 62478, the four AE (acoustic emission) sensors were used to determine the PD sources and one HFCT (High-Frequency Current Transducer) technique was to identify the PD source and the criteria level. This process accurately identified the PD source location occurring at any position in a transformer. The gap time was 3.2 ms. The level of partial discharge for this case study is Major PD that means soon monitoring every 3 months. The results of this technique could prevent insulation failure of a transformer in time. Streszczenie. Zaprezentowano technikę wykrywania wyładowań niezupełnych w izolacji suchego transformatora. Zgodnie z IEC 62478 użyto czterech czujników emisji akustycznej AE oraz jednego czujnika prądów wysokiej częstotliwości HFCT. Umożliwia to lokalizację źródła wyładowania. (Wykorzystanie scalonego czujnika AE I HFCT do online monitoringu wyładowań niezupełnych w suchym transformatorze)
Syncytiotrophoblast extracellular microvesicles in preeclampsia

Preeclampsia is a major cause of mortality and morbidity in expecting mothers and is one of the most common causes of pregnancy complications and premature birth [2]. Along with eclampsia, it is directly associated with 10-15% of maternal deaths [2]. Currently, it is diagnosed during the second or third trimester after clinical symptoms are displayed, but studies have attempted to understand the pathophysiologic mechanism underlying preeclampsia, noting its beginnings in the first trimester. Although there is no defined cause nor is there a cure for the disease, it is widely agreed that preeclampsia stems from the placenta and is related to a decrease in uteroplacental blood flow and hypoxia [3].