Search results for: negative data

Authors: Marju Ben Sayed, Shigeko Haruyama

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Among all kinds of natural disaster, the flood is a common feature in rapidly urbanizing Dhaka city. In this research, assessment of flood risk of Dhaka metropolitan area has been investigated by using an integrated approach of GIS, remote sensing and socio-economic data. The purpose of the study is to measure the flooding risk concerning with the flood protection embankment in big flooding events (1988, 1998 and 2004) and urbanization of Dhaka metropolitan zone. In this research, we considered the Dhaka city into two parts; East Dhaka (outside the flood protection embankment) and West Dhaka (inside the flood protection embankment). Using statistical data, we explored the socio-economic status of the study area population by comparing the density of population, land price and income level. We have drawn the cross section profile of the flood protection embankment into three different points for realizing the flooding risk in the study area, especially in the big flooding year (1988, 1998 and 2004). According to the physical condition of the study area, the land use/land cover map has been classified into five classes. Comparing with each land cover unit, historical weather station data and the socio-economic data, the flooding risk has been evaluated. Moreover, we compared between DEM data and each land cover units to find out the relationship with flood. It is expected that, this study could contribute to effective flood forecasting, relief and emergency management for a future flood event in Dhaka city.

Keywords: land use, land cover change, socio-economic, Dhaka city, GIS, flood

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Authors: Sarah K. Hagi, Majdi Alnowaimi

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In the last decade, there were immense advancements in the medical imaging modalities. These advancements can scan a whole volume of the lung organ in high resolution images within a short time. According to this performance, the physicians can clearly identify the complicated anatomical and pathological structures of lung. Therefore, these advancements give large opportunities for more advance of all types of lung cancer treatment available and will increase the survival rate. However, lung cancer is still one of the major causes of death with around 19% of all the cancer patients. Several factors may affect survival rate. One of the serious effects is the breathing process, which can affect the accuracy of diagnosis and lung tumor treatment plan. We have therefore developed a semi automated algorithm to localize the 3D lung tumor positions across all respiratory data during respiratory motion. The algorithm can be divided into two stages. First, a lung tumor segmentation for the first phase of the 4D computed tomography (CT). Lung tumor segmentation is performed using an active contours method. Then, localize the tumor 3D position across all next phases using a 12 degrees of freedom of an affine transformation. Two data set where used in this study, a compute simulate for 4D CT using extended cardiac-torso (XCAT) phantom and 4D CT clinical data sets. The result and error calculation is presented as root mean square error (RMSE). The average error in data sets is 0.94 mm ± 0.36. Finally, evaluation and quantitative comparison of the results with a state-of-the-art registration algorithm was introduced. The results obtained from the proposed localization algorithm show a promising result to localize alung tumor in 4D CT data.

Keywords: automated algorithm , computed tomography, lung tumor, tumor localization

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Authors: Manuel Alves, Angelica Reis, Armindo Lobo, Valdemar Leiras

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In industry 4.0, it is common to have a lot of sensor data. In this deluge of data, hints of possible problems are difficult to spot. The digital twin concept aims to help answer this problem, but it is mainly used as a monitoring tool to handle the visualisation of data. Failure detection is of paramount importance in any industry, and it consumes a lot of resources. Any improvement in this regard is of tangible value to the organisation. The aim of this paper is to add the ability to forecast test failures, curtailing detection times. To achieve this, several anomaly detection algorithms were compared with a symbolic regression approach. To this end, Isolation Forest, One-Class SVM and an auto-encoder have been explored. For the symbolic regression PySR library was used. The first results show that this approach is valid and can be added to the tools available in this context as a low resource anomaly detection method since, after training, the only requirement is the calculation of a polynomial, a useful feature in the digital twin context.

Keywords: anomaly detection, digital twin, industry 4.0, symbolic regression

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Authors: Kerem Rızvanoğlu, Serhat Güney, Emre Kızılkaya, Betül Aydoğan, Ayşegül Boyalı, Onurcan Güden

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This study addresses the re-construction and implementation process of the methodological framework developed to evaluate how locative media applications accompany the urban experiences of international students coming to Istanbul with exchange programs in 2022. The research design was built on a three-stage model. The research team conducted a qualitative questionnaire in the first stage to gain exploratory data. These data were then used to form three persona groups representing the sample by applying cluster analysis. In the second phase, a semi-structured digital diary study was carried out on a gamified task list with a sample selected from the persona groups. This stage proved to be the most difficult to obtaining valid data from the participant group. The research team re-evaluated the design of this second phase to reach the participants who will perform the tasks given by the research team while sharing their momentary city experiences, to ensure the daily data flow for two weeks, and to increase the quality of the obtained data. The final stage, which follows to elaborate on the findings, is the “Walk & Talk,” which is completed with face-to-face and in-depth interviews. It has been seen that the multiple methods used in the research process contribute to the depth and data diversity of the research conducted in the context of urban experience and locative technologies. In addition, by adapting the research design to the experiences of the users included in the sample, the differences and similarities between the initial research design and the research applied are shown.

Keywords: digital diary study, gamification, multi-model research, persona analysis, research design for urban experience, user-centered research, “Walk & Talk”

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Authors: Igor A. Podgorny

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TurboTax AnswerXchange is a social Q/A system supporting users working on federal and state tax returns. Content quality and popularity in the AnswerXchange can be predicted with propensity models using attributes of the question and answer. Using uplift modeling, we identify features of questions and answers that can be modified during the question-asking and question-answering experience in order to optimize the AnswerXchange content quality. We demonstrate that adding details to the questions always results in increased question popularity that can be used to promote good quality content. Responding to close-ended questions assertively improve content quality in the AnswerXchange in 90% of cases. Answering knowledge questions with web links increases the likelihood of receiving a negative vote from 60% of the askers. Our findings provide a rationale for employing the uplift modeling approach for AnswerXchange operations.

Keywords: customer relationship management, human-machine interaction, text mining, uplift modeling

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Authors: Umberto Di Staso, Marco Soave, Alessio Giori, Federico Prandi, Raffaele De Amicis

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The increasing availability of information about earth surface elevation (Digital Elevation Models DEM) generated from different sources (remote sensing, Aerial Images, Lidar) poses the question about how to integrate and make available to the most than possible audience this huge amount of data. In order to exploit the potential of 3D elevation representation the quality of data management plays a fundamental role. Due to the high acquisition costs and the huge amount of generated data, highresolution terrain surveys tend to be small or medium sized and available on limited portion of earth. Here comes the need to merge large-scale height maps that typically are made available for free at worldwide level, with very specific high resolute datasets. One the other hand, the third dimension increases the user experience and the data representation quality, unlocking new possibilities in data analysis for civil protection, real estate, urban planning, environment monitoring, etc. The open-source 3D virtual globes, which are trending topics in Geovisual Analytics, aim at improving the visualization of geographical data provided by standard web services or with proprietary formats. Typically, 3D Virtual globes like do not offer an open-source tool that allows the generation of a terrain elevation data structure starting from heterogeneous-resolution terrain datasets. This paper describes a technological solution aimed to set up a so-called “Terrain Builder”. This tool is able to merge heterogeneous-resolution datasets, and to provide a multi-resolution worldwide terrain services fully compatible with CesiumJS and therefore accessible via web using traditional browser without any additional plug-in.

Keywords: Terrain Builder, WebGL, Virtual Globe, CesiumJS, Tiled Map Service, TMS, Height-Map, Regular Grid, Geovisual Analytics, DTM

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Authors: Mehdi Brahimi, Kamal Medjaher, Noureddine Zerhouni, Mohammed Leouatni

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The Prognostics and Health Management is a system engineering discipline which provides solutions and models to the implantation of a predictive maintenance. The approach is based on extracting useful information from monitoring data to assess the “health” state of an industrial equipment or an asset. In this paper, we examine multiple extracted features from Pantograph-Catenary contact force in order to select the most relevant ones to achieve a diagnostics function. The feature extraction methodology is based on simulation data generated thanks to a Pantograph-Catenary simulation software called INPAC and measurement data. The feature extraction method is based on both statistical and signal processing analyses. The feature selection method is based on statistical criteria.

Keywords: catenary/pantograph interaction, diagnostics, Prognostics and Health Management (PHM), quality of current collection

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Authors: Ariane C. Lim, Daphne Ashley L. Sze, Kenneth S. Santos

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As women are now given more freedom and choice to pursue employment, the world’s over-all fertility has been decreasing mainly due to the shift in time allocation between working and child-rearing. As such, we study the case of the Philippines, where there exists a decreasing fertility rate and increasing openness for women labor participation. We focused on the distinction between fertility and fecundity, the former being the manifestation of the latter and aim to trace and compare the effects of both fecundity and fertility to women’s employment status through the estimation of the reproduction function and multinomial logistic function. Findings suggest that the perception of women regarding employment opportunities in the Philippines links the negative relationship observed between fertility, fecundity and women’s employment status. Today, there has been a convergence in the traditional family roles of men and women, as both genders now have identical employment opportunities that continue to shape their preferences.

Keywords: multinomial logistic function, tobit, fertility, women employment status, fecundity

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Authors: Danuvasin Charoen

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The study investigates the business process and business model of GRABTAXI. The paper also discusses how the company implemented strategies to gain competitive advantages. The data is derived from the analysis of secondary data and the in-depth interviews among staffs, taxi drivers, and key customers. The findings indicated that the company’s competitive advantages come from being the first mover, emphasising on the ease of use and tangible benefits of application, and using network effect strategy.

Keywords: taxi, mobile application, innovative business model, Thailand

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Authors: Sachin Mulmi Shrestha, Xin Fang, Hui Ye, Lihua Ren, Qinghua Ji, Ruihua Shi

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Background: Esophageal squamous cell carcinoma (ESCC) is a tumor arising from esophageal epithelial cells and is one of the major disease subtype in Asian countries, including China. Esophageal cancer is the 7th highest incidence based on the 2020 data of GLOBOCAN. The pathogenesis of cancer is still not well understood as many molecular and genetic basis of esophageal carcinogenesis has yet to be clearly elucidated. Circular RNAs are RNA molecules that are formed by back-splicing covalently joined 3′- and 5′-endsrather than canonical splicing, and recent data suggest circular RNAs could sponge miRNAs and are enriched with functional miRNA binding sites. Hence, we studied the mechanism of circular RNA, its biological function, and the relationship between microRNA in the carcinogenesis of ESCC. Methods: 4 pairs of normal and esophageal cancer tissues were collected in Zhongda hospital, affiliated to Southeast University, and high-throughput RNA sequencing was done. The result revealed that circ_0032746 was upregulated, and thus we selected circ_0032746 for further study. The backsplice junction of circRNA was validated by sanger sequence, and stability was determined by RNASE R assay. The binding site of circRNA and microRNA was predicted by circinteractome,mirandaand RNAhybrid database. Furthermore, circRNA was silenced by siRNA and then by lentivirus. The regulatory axis of circ0032746/miR4270 was validated by shRNA, mimic, and inhibitor transfection. Then, in vitro experiments were performed to assess the role of circ0032746 on proliferation (CCK-8 assay and colon formation assay), migration and invasion (Transewell assay), and apoptosis of ESCC. Results: The upregulated circ0032746 was validated in 9 pairs of tissues and 5 types of cell lines by qPCR, which showed high expression and was statistically significant (P<0.005) ). Upregulated circ0032746 was silenced by shRNA, which showed significant knockdown in KYSE 30 and TE-1 cell lines expression compared to control. Nuclear and cytoplasmic mRNA fraction experiment displayed the cytoplasmic location of circ0032746. The sponging of miR4270 was validated by co-transfection of sh-circ0032746 and mimic or inhibitor. Transfection with mimic showed the decreased expression of circ_0032746, whereas inhibitor inhibited the result. In vitro experiments showed that silencing of circ_0032746 inhibited the proliferation, migration, and invasion compared to the negative control group. The apoptosis was seen higher in a knockdown group than in the control group. Furthermore, 11 common mircoRNA target mRNAs were predicted by Targetscan, MirTarbase, and miRanda database, which may further play role in the pathogenesis. Conclusion: Our results showed that novel circ_0032746 is upregulated in ESCC and plays role in itsoncogenicity. Silencing of circ_0032746 inhibits the proliferation and migration of ESCC whereas increases the apoptosis of cancer cells. Hence, circ0032746 acts as an oncogene in ESCC by sponging with miR4270 and could be a potential biomarker in the diagnosis of ESCC in the future.

Keywords: circRNA, esophageal squamous cell carcinoma, microRNA, upregulated

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Authors: Nazia Tarannum, M. Ayaz Ahmad

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The main goal of this article is to report some interesting features for the fabrication/design of PEDOT:PSS based humidity sensor. Here first we fabricated humidity sensor and then studied its electro-mechanical characteristics. In general the humidity plays an important role in various private and government sectors all over the world. Monitoring and controlling the humidity is a great task for the reliable operation of various systems. The PEDOT:PSS is very much promising humidity sensor and also is fabricated by performing various analyses. The interdigited electrode (IDE) has channel length 200 microns prepared by lithography. Lithography of IDE was done on PPR coated glass substrate using negative mask and exposing it with UV light for 10 secs via DSA. During the above said fabrication, we have taken account for the following steps: •Plasma ashing of IDE •Spincoating of PEDOT:PSS was done @3000 rpm on IDE substrace •Baked the substrace at 130 °C up to time limit 15 mins. •Resistance measurement using Labtracer 2.9 software via Keithley 2400source meter.

Keywords: fabrication method, PEDOT:PSS material, humidity sensor, electro-mechanical

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Authors: Hadjer Sadoune, Liza Lamini, Scherazade Krim, Amel Djouadi, Rachida Rihani

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Deep neural networks are highly regarded for their accuracy in predicting intricate fermentation processes. Their ability to learn from a large amount of datasets through artificial intelligence makes them particularly effective models. The primary obstacle in improving the performance of these models is to carefully choose the suitable hyperparameters, including the neural network architecture (number of hidden layers and hidden units), activation function, optimizer, learning rate, and other relevant factors. This study predicts biogas production from real wastewater treatment plant data using a sophisticated approach: hybrid Bayesian optimization with a tree-structured Parzen estimator (BO-TPE) for an optimised deep neural network (DNN) model. The plant utilizes an Upflow Anaerobic Sludge Blanket (UASB) digester that treats industrial wastewater from soft drinks and breweries. The digester has a working volume of 1574 m3 and a total volume of 1914 m3. Its internal diameter and height were 19 and 7.14 m, respectively. The data preprocessing was conducted with meticulous attention to preserving data quality while avoiding data reduction. Three normalization techniques were applied to the pre-processed data (MinMaxScaler, RobustScaler and StandardScaler) and compared with the Non-Normalized data. The RobustScaler approach has strong predictive ability for estimating the volume of biogas produced. The highest predicted biogas volume was 2236.105 Nm³/d, with coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) values of 0.712, 164.610, and 223.429, respectively.

Keywords: anaerobic digestion, biogas production, deep neural network, hybrid bo-tpe, hyperparameters tuning

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Authors: Ewa Bednorz, Marek Polrolniczak, Bartosz Czernecki, Arkadiusz Marek Tomczyk

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This study is meant as a contribution to the research of the upwelling phenomenon, which is one of the most pronounced examples of the sea-atmosphere coupling. The aim is to confirm the atmospheric forcing of the sea waters circulation and sea surface temperature along the variously oriented Baltic Sea coasts and to find out macroscale and regional circulation patterns triggering upwelling along different sections of this relatively small and semi-closed sea basin. The mean daily sea surface temperature data from the summer seasons (June–August) of the years 1982–2017 made the basis for the detection of upwelling cases. For the atmospheric part of the analysis, monthly indices of the Northern Hemisphere macroscale circulation patterns were used. Besides, in order to identify the local direction of airflow, the daily zonal and meridional regional circulation indices were constructed and introduced to the analysis. Finally, daily regional circulation patterns over the Baltic Sea region were distinguished by applying the principal component analysis to the gridded mean daily sea level pressure data. Within the Baltic Sea, upwelling is the most frequent along the zonally oriented northern coast of the Gulf of Finland, southern coasts of Sweden, and along the middle part of the western Gulf of Bothnia coast. Among the macroscale circulation patterns, the Scandinavian type (SCAND), with a primary circulation center located over Scandinavia, has the strongest impact on the horizontal flow of surface sea waters in the Baltic Sea, which triggers upwelling. An anticyclone center over Scandinavia in the positive phase of SCAND enhances the eastern airflow, which increases upwelling frequency along southeastern Baltic coasts. It was proved in the study that the zonal circulation has a stronger impact on upwelling occurrence than the meridional one, and it could increase/decrease a chance of upwelling formation by more than 70% in some coastal sections. Positive and negative phases of six distinguished regional daily circulation patterns made 12 different synoptic situations which were analyzed in the terms of their influence on the upwelling formation. Each of them revealed some impact on the frequency of upwelling in some coastal section of the Baltic Sea; however, two kinds of synoptic situations seemed to have the strongest influence, namely, the first kind representing pressure patterns enhancing the zonal flow and the second kind representing synoptic patterns with a cyclone/anticyclone centers over southern Scandinavia. Upwelling occurrence appeared to be particularly strongly reliant on the atmospheric conditions in some specific coastal sections, namely: the Gulf of Finland, the south eastern Baltic coasts (Polish and Latvian-Lithuanian section), and the western part of the Gulf of Bothnia. Concluding, it can be stated that atmospheric conditions strongly control the occurrence of upwelling within the Baltic Sea basin. Both local and macroscale circulation patterns expressed by the location of the pressure centers influence the frequency of this phenomenon; however, the impact strength varies, depending on the coastal region. Acknowledgment: This research was funded by the National Science Centre, Poland, grant number 2016/21/B/ST10/01440.

Keywords: Baltic Sea, circulation patterns, coastal upwelling, synoptic conditions

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Authors: Nindyo Cahyo Kresnanto, Muhamad Willdan, Wika Harisa Putri

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Gunungkidul is one of the emerging tourism industry areas in Yogyakarta Province, Indonesia. This article describes how GIS can predict the development of tourism potential in Gunungkidul. The tourism sector in Gunungkidul Regency contributes 3.34% of the total gross regional domestic product and is the economic sector with the highest growth with a percentage of 18.37% in the post-Covid-19 period. This contribution makes researchers consider that several tourist sites need to be explored more to increase regional economic development gradually. This research starts by collecting spatial data from tourist locations tourists want to visit in Gunungkidul Regency based on survey data from 571 respondents. Then the data is visualized with ArcGIS software. This research shows an overview of tourist destinations interested in travellers depicted from the lowest to the highest from the data visualization. Based on the data visualization results, specific tourist locations potentially developed to influence the surrounding economy positively. The visualization of the data displayed is also in the form of a desire line map that shows tourist travel patterns from the origin of the tourist to the destination of the tourist location of interest. From the desire line, the prediction of the path of tourist sites with a high frequency of transportation activity can figure out. Predictions regarding specific tourist location routes that high transportation activities can burden can consider which routes will be chosen. The route also needs to be improved in terms of capacity and quality. The goal is to provide a sense of security and comfort for tourists who drive and positively impact the tourist sites traversed by the route.

Keywords: tourism development, GIS and survey, transportation, potential desire line

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Authors: Atilola O. Abidemi-Iromini, Oluayo A. Bello-Olusoji, Immanuel A. Adebayo

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Ecological studies were carried out in Asejire Reservoir (AR) and Lagos Lagoon (LL), Southwest Nigeria from January 2012 to December 2013 to determine the health status of Chrysichthys nigrodigitatus (CN) and Oreochromis niloticus (ON). The fish species samples were collected every month, these were separated into sexes, and growth pattern {length, (cm); weight (g), Isometric index, condition factor} were measured. Heavy metals (lead (Pb), iron (Fe), zinc (Zn), copper (Cu), and chromium (Cr) in ppm concentrations were also determined while bacteria occurrence(s), (load and prevalence) on fish skins, gills and intestine in the two ecological zones were determined. The fish ratio collected is in range with normal aquatic (1: 1+) male: female ratio. Growth assessment determined revealed no significant difference in length and weight in O. niloticus between locations, but a significant difference in weight occurred in C. nigrodigitatus between locations, with a higher weight (196.06 ±0.16 g) from Lagos Lagoon. Highest condition factor (5.25) was recorded in Asejire Reservoir O. niloticus, (ARON); and lowest condition factor (1.64) was observed in Asejire Reservoir C. nigrodigitatus (ARCN); as this indicated a negative allometric value which is normal in Bagridae species because it increases more in Length to weight gain than for the Cichlidae growth status. Normal growth rate (K > 1) occurred between sexes, with the male species having higher K - factors than female species within locations, between locations, between species, and within species, except for female C. nigrodigitatus having higher condition factor (K = 1.75) than male C. nigrodigitatus (K = 1.54) in Asejire Reservoir. The highest isometric value (3.05) was recorded in Asejire Reservoir O. niloticus and lowest in Lagos Lagoon C. nigrodigitatus. Male O. niloticus from Asejire Reservoir had highest isometric value, and O. niloticus species had higher condition factor which ranged between isometric (b ≤ 3) and positive allometric (b > 3), hence, denoted robustness of fish to grow more in weight than in length; while C. nigrodigitatus fish has negative allometric (b < 3) indicating fish add more length than in weight on growth. The status of condition factors and isometric values obtained is species-specific, and environmental influence, food availability or reproduction factor may as well be contributing factors. The concentrations of heavy metals in fish flesh revealed that Zn (6.52 ±0.82) had the highest, while Cr (0.01±0.00) was ranked lowest; for O. niloticus in Asejire Reservoir. In Lagos Lagoon, heavy metals concentration level revealed that O. niloticus flesh had highest in Zn (4.71±0.25) and lowest in Pb (0.01±0.00). Lagos Lagoon C. nigrodigitatus heavy metal concentration level revealed Zn (9.56±0.96) had highest, while Cr (0.06±0.01) had lowest; and Asejire Reservoir C. nigrodigitatus heavy metal level revealed that Zn (8.26 ±0.74) had highest, and Cr (0.08±0.00) had lowest. In all, Zinc (Zn) was top-ranked in level among species.

Keywords: Oreochromis niloticus, growth status, Chrysichthys nigrodigitatus, environments, heavy metals

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Authors: Tulasi Acharya

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The paper is a qualitative analysis of status of women and women in politics and administration in Nepal Himalaya. The paper reviews data of women in civil service and in administrative levels. Looking at the Nepali politics and administration from the social constructivist perspective, the paper highlights some social and cultural issues that have othered women as “second sex.” As the country is heading towards modernity, gender friendly approaches are being instituted. Although the data reflects on the progress on women’s status and on women’s political and administrative participation, the data is not enough to predict the democratic gender practices in political and administrative levels. The political and administrative culture of Nepal Himalaya should be changed by promoting gender practices and deconstructing gender images in administrative culture through representative bureaucracy and by introducing democratic policies.

Keywords: politics, policy, administration, culture, women, Nepal, democracy

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Authors: Yong Hwang, Kang Yeol Suh, Yundeok Jang, Tae Hoon Kim

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Introduction: Rhabdomyolysis is a syndrome characterized by muscle necrosis and the release of intracellular muscle constituents into the circulation. Acute kidney injury is a potential complication of severe rhabdomyolysis and the prognosis is substantially worse if renal failure develops. We try to identify the factors that were predictive of AKI in severe trauma patients with rhabdomyolysis. Methods: This retrospective study was conducted at the emergency department of a level Ⅰ trauma center. Patients enrolled that initial creatine phosphokinase (CPK) levels were higher than 1000 IU with acute multiple trauma, and more than 18 years older from Oct. 2012 to June 2016. We collected demographic data (age, gender, length of hospital day, and patients’ outcome), laboratory data (ABGA, lactate, hemoglobin. hematocrit, platelet, LDH, myoglobin, liver enzyme, and BUN/Cr), and clinical data (Injury Mechanism, RTS, ISS, AIS, and TRISS). The data were compared and analyzed between AKI and Non-AKI group. Statistical analyses were performed using IMB SPSS 20.0 statistics for Window. Results: Three hundred sixty-four patients were enrolled that AKI group were ninety-six and non-AKI group were two hundred sixty-eight. The base excess (HCO3), AST/ALT, LDH, and myoglobin in AKI group were significantly higher than non-AKI group from laboratory data (p ≤ 0.05). The injury severity score (ISS), revised Trauma Score (RTS), Abbreviated Injury Scale 3 and 4 (AIS 3 and 4) were showed significant results in clinical data. The patterns of CPK level were increased from first and second day, but slightly decreased from third day in both group. Seven patients had received hemodialysis treatment despite the bleeding risk and were survived in AKI group. Conclusion: We recommend that HCO3, CPK, LDH, and myoglobin should be checked and be concerned about ISS, RTS, AIS with injury mechanism at the early stage of treatment in the emergency department.

Keywords: acute kidney injury, emergencies, multiple trauma, rhabdomyolysis

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Authors: Estevan B. Costa, Armando M. Toda, Marcell A. A. Mesquita, Jacques D. Brancher

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The advances in technology in the last five years allowed an improvement in the educational area, as the increasing in the development of educational software. One of the techniques that emerged in this lapse is called Gamification, which is the utilization of video game mechanics outside its bounds. Recent studies involving this technique provided positive results in the application of these concepts in many areas as marketing, health and education. In the last area there are studies that cover from elementary to higher education, with many variations to adequate to the educators methodologies. Among higher education, focusing on IT courses, data structures are an important subject taught in many of these courses, as they are base for many systems. Based on the exposed this paper exposes the development of an interactive web learning environment, called DSLEP (Data Structure Learning Platform), to aid students in higher education IT courses. The system includes basic concepts seen on this subject such as stacks, queues, lists, arrays, trees and was implemented to ease the insertion of new structures. It was also implemented with gamification concepts, such as points, levels, and leader boards, to engage students in the search for knowledge and stimulate self-learning.

Keywords: gamification, Interactive learning environment, data structures, e-learning

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Authors: Victoria Goodall, Paul Fatti, Norman Owen-Smith

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Hidden Markov Models have become popular for the analysis of animal tracking data. These models are being used to model the movements of a variety of species in many areas around the world. A common assumption of the model is that the observations need to have regular time steps. In many ecological studies, this will not be the case. The objective of the research is to modify the movement model to allow for irregularly spaced locations and investigate the effect on the inferences which can be made about the latent states. A modification of the likelihood function to allow for these irregular spaced locations is investigated, without using interpolation or averaging the movement rate. The suitability of the modification is investigated using GPS tracking data for lion (Panthera leo) in South Africa, with many observations obtained during the night, and few observations during the day. Many nocturnal predator tracking studies are set up in this way, to obtain many locations at night when the animal is most active and is difficult to observe. Few observations are obtained during the day, when the animal is expected to rest and is potentially easier to observe. Modifying the likelihood function allows the popular Hidden Markov Model framework to be used to model these irregular spaced locations, making use of all the observed data.

Keywords: hidden Markov Models, irregular observations, animal movement modelling, nocturnal predator

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Authors: Tsai-Hsiu Lin

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Dan C. Lortie’s Schoolteacher: A sociological study is one of the best works on the sociology of teaching since W. Waller’s classic study. It is a book worthy of review. Following the tradition of symbolic interactionists, Lortie demonstrated the qualities who studied the occupation of teaching. Using several methods to gather effective data, Lortie has portrayed the ethos of the teaching profession. Therefore, the work is an important book on the teaching profession and teacher culture. Though outstanding, Lortie’s work is also flawed in that his perspectives and methodology were adopted largely from symbolic interactionism. First, Lortie in his work analyzed many points regarding teacher culture; for example, he was interested in exploring “sentiment,” “cathexis,” and “ethos.” Thus, he was more a psychologist than a sociologist. Second, symbolic interactionism led him to discern the teacher culture from a micro view, thereby missing the structural aspects. For example, he did not fully discuss the issue of gender and he ignored the issue of race. Finally, following the qualitative sociological tradition, Lortie employed many qualitative methods to gather data but only foucused on obtaining and presenting interview data. Moreover, he used measurement methods that were too simplistic for analyzing quantitative data fully.

Keywords: education reform, teacher culture, teaching profession, Lortie’s Schoolteacher

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Authors: Omar Hamdy, Schichen Zhao, Hussein Abd El-Atty, Ayman Ragab, Muhammad Salem

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One of the most risky areas in Aswan is Abouelreesh, which is suffering from flood disasters, as heavy deluge inundates urban areas causing considerable damage to buildings and infrastructure. Moreover, the main problem was the urban sprawl towards this risky area. This paper aims to identify the urban areas located in the risk areas prone to flash floods. Analyzing this phenomenon needs a lot of data to ensure satisfactory results; however, in this case the official data and field data were limited, and therefore, free sources of satellite data were used. This paper used ArcGIS tools to obtain the storm water drains network by analyzing DEM files. Additionally, historical imagery in Google Earth was studied to determine the age of each building. The last step was to overlay the urban area layer and the storm water drains layer to identify the vulnerable areas. The results of this study would be helpful to urban planners and government officials to make the disasters risk estimation and develop primary plans to recover the risky area, especially urban areas located in torrents.

Keywords: risk area, DEM, storm water drains, GIS

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Authors: Liz Jackson

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Fear is usually considered as a basic emotion. In society, it is normally cast as undesirable, but also as partly unavoidable. Fear can be said to underlie courage or be required for courage, or it can be understood as its foil. Fear is not normally promoted (intentionally) in education, or treated as something that should be cultivated in schools or in society. However, fear is a basic, to some extent unavoidable emotion, related to truly fearsome things in the world. Fear is also understood to underlie anxiety. Fear is seen as basically disruptive to education, while from a psychological view it is an ordinary state. that cannot be avoided altogether. Despite calls to diminish this negative and mixed feeling in education and society, it can be regarded as socially and personally valuable, and psychologically functional in some situations. One should not take for granted the goodness of fear. However, it can be productive to explore its moral worth, and uses and abuses. Such uncomfortable feelings and experiences can be cultivated and explored via educational and other societal influences, in ways that can benefit a person and their relations with others in the world, while they can also be detrimental.

Keywords: virtue ethics, philosophy of education, moral philosophy, fear

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Authors: Sakir Tasdemir, Mustafa Altin, Gamze Fahriye Pehlivan, Sadiye Didem Boztepe Erkis, Ismail Saritas, Selma Tasdemir

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Artificial intelligence applications are commonly used in industry in many fields in parallel with the developments in the computer technology. In this study, a fire room was prepared for the resistance of wooden construction elements and with the mechanism here, the experiments of polished materials were carried out. By utilizing from the experimental data, an artificial neural network (ANN) was modeled in order to evaluate the final cross sections of the wooden samples remaining from the fire. In modelling, experimental data obtained from the fire room were used. In the system developed, the first weight of samples (ws-gr), preliminary cross-section (pcs-mm2), fire time (ft-minute), fire temperature (t-oC) as input parameters and final cross-section (fcs-mm2) as output parameter were taken. When the results obtained from ANN and experimental data are compared after making statistical analyses, the data of two groups are determined to be coherent and seen to have no meaning difference between them. As a result, it is seen that ANN can be safely used in determining cross sections of wooden materials after fire and it prevents many disadvantages.

Keywords: artificial neural network, final cross-section, fire retardant polishes, fire safety, wood resistance.

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Authors: Ayliana Dharmawan, Heng Yong Sheng, Zhang Xiaojin, Tan Thai Lian

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To facilitate discharge planning, doctors are presently required to assign an Estimated Discharge Date (EDD) for each patient admitted to the hospital. This assignment of the EDD is largely based on the doctor’s judgment. This can be difficult for cases which are complex or relatively new to the doctor. It is hypothesized that a data-driven approach would be able to facilitate the doctors to make accurate estimations of the discharge date. Making use of routinely collected data on inpatient discharges between January 2013 and May 2016, a predictive model was developed using machine learning techniques to predict the Length of Stay (and hence the EDD) of inpatients, at the point of admission. The predictive performance of the model was compared to that of the clinicians using accuracy measures. Overall, the best performing model was found to be able to predict EDD with an accuracy improvement in Average Squared Error (ASE) by -38% as compared to the first EDD determined by the present method. It was found that important predictors of the EDD include the provisional diagnosis code, patient’s age, attending doctor at admission, medical specialty at admission, accommodation type, and the mean length of stay of the patient in the past year. The predictive model can be used as a tool to accurately predict the EDD.

Keywords: inpatient, estimated discharge date, EDD, prediction, data-driven

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Authors: Zama Mahmood

Abstract:

The increasing demand of food management, monitoring of the crop growth and forecasting its yield well before harvest is very important. These days, yield assessment together with monitoring of crop development and its growth are being identified with the help of satellite and remote sensing images. Studies using remote sensing data along with field survey validation reported high correlation between vegetation indices and yield. With the development of remote sensing technique, the detection of crop and its mechanism using remote sensing data on regional or global scales have become popular topics in remote sensing applications. Punjab, specially the southern Punjab region is extremely favourable for wheat production. But measuring the exact amount of wheat production is a tedious job for the farmers and workers using traditional ground based measurements. However, remote sensing can provide the most real time information. In this study, using the Normalized Differentiate Vegetation Index (NDVI) indicator developed from Landsat satellite images, the yield of wheat has been estimated during the season of 2013-2014 for the agricultural area around Bahawalpur. The average yield of the wheat was found 35 kg/acre by analysing field survey data. The field survey data is in fair agreement with the NDVI values extracted from Landsat images. A correlation between wheat production (ton) and number of wheat pixels has also been calculated which is in proportional pattern with each other. Also a strong correlation between the NDVI and wheat area was found (R2=0.71) which represents the effectiveness of the remote sensing tools for crop monitoring and production estimation.

Keywords: landsat, NDVI, remote sensing, satellite images, yield

Procedia PDF Downloads 326

Authors: Swati Srivastava, Mattia Lauriola, Yuval Gilad, Adi Kimchi, Yosef Yarden

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The glucocorticoid receptor (GR) has been proposed to play important, but incompletely understood roles in cancer. Glucocorticoids (GCs) are widely used as co-medication of various carcinomas, due to their ability to reduce the toxicity of chemotherapy. Furthermore, GR antagonism has proven to be a strategy to treat triple negative breast cancer and castration-resistant prostate cancer. These observations suggest differential GR involvement in cancer subtypes. The goal of our study has been to elaborate the current understanding of GR signaling in tumor progression and metastasis. Our study involves two cellular models, non-tumorigenic breast epithelial cells (MCF10A) and Ewing sarcoma cells (CHLA9). In our breast cell model, the results indicated that the GR agonist dexamethasone inhibits EGF-induced mammary cell migration, and this effect was blocked when cells were stimulated with a GR antagonist, namely RU486. Microarray analysis for gene expression revealed that the mechanism underlying inhibition involves dexamenthasone-mediated repression of well-known activators of EGFR signaling, alongside with enhancement of several EGFR’s negative feedback loops. Because GR mainly acts primarily through composite response elements (GREs), or via a tethering mechanism, our next aim has been to find the transcription factors (TFs) which can interact with GR in MCF10A cells.The TF-binding motif overrepresented at the promoter of dexamethasone-regulated genes was predicted by using bioinformatics. To validate the prediction, we performed high-throughput Protein Complementation Assays (PCA). For this, we utilized the Gaussia Luciferase PCA strategy, which enabled analysis of protein-protein interactions between GR and predicted TFs of mammary cells. A library comprising both nuclear receptors (estrogen receptor, mineralocorticoid receptor, GR) and TFs was fused to fragments of GLuc, namely GLuc(1)-X, X-GLuc(1), and X-GLuc(2), where GLuc(1) and GLuc(2) correspond to the N-terminal and C-terminal fragments of the luciferase gene.The resulting library was screened, in human embryonic kidney 293T (HEK293T) cells, for all possible interactions between nuclear receptors and TFs. By screening all of the combinations between TFs and nuclear receptors, we identified several positive interactions, which were strengthened in response to dexamethasone and abolished in response to RU486. Furthermore, the interactions between GR and the candidate TFs were validated by co-immunoprecipitation in MCF10A and in CHLA9 cells. Currently, the roles played by the uncovered interactions are being evaluated in various cellular processes, such as cellular proliferation, migration, and invasion. In conclusion, our assay provides an unbiased network analysis between nuclear receptors and other TFs, which can lead to important insights into transcriptional regulation by nuclear receptors in various diseases, in this case of cancer.

Keywords: epidermal growth factor, glucocorticoid receptor, protein complementation assay, transcription factor

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Authors: Shan Zhang, Peter Suechting

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Predicting trade patterns is critical to decision-making in public and private domains, especially in the current context of trade disputes among major economies. In the past, U.S. recycling has relied heavily on strong demand for recyclable materials overseas. However, starting in 2017, a series of new recycling policies (bans and higher inspection standards) was enacted by multiple countries that were the primary importers of recyclables from the U.S. prior to that point. As the global trade flow of recycling shifts, some new importers, mostly developing countries in South and Southeast Asia, have been overwhelmed by the sheer quantities of scrap materials they have received. As the leading exporter of recyclable materials, the U.S. now has a pressing need to build its recycling industry domestically. With respect to the global trade in scrap materials used for recycling, the interest in this paper is (1) predicting how the export of recyclable materials from the U.S. might vary over time, and (2) predicting how international trade flows for recyclables might change in the future. Focusing on three major recyclable materials with a history of trade, this study uses data-driven and machine learning (ML) algorithms---supervised (shrinkage and tree methods) and unsupervised (neural network method)---to decipher the international trade pattern of recycling. Forecasting the potential trade values of recyclables in the future could help importing countries, to which those materials will shift next, to prepare related trade policies. Such policies can assist policymakers in minimizing negative environmental externalities and in finding the optimal amount of recyclables needed by each country. Such forecasts can also help exporting countries, like the U.S understand the importance of healthy domestic recycling industry. The preliminary result suggests that gravity models---in addition to particular selection macroeconomic predictor variables--are appropriate predictors of the total export value of recyclables. With the inclusion of variables measuring aspects of the political conditions (trade tariffs and bans), predictions show that recyclable materials are shifting from more policy-restricted countries to less policy-restricted countries in international recycling trade. Those countries also tend to have high manufacturing activities as a percentage of their GDP.

Keywords: environmental economics, machine learning, recycling, international trade

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Authors: José Alberto García Fernández, Zhimin Du, Xinqiao Jin

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Nowadays, data center industry faces strong challenges for increasing the speed and data processing capacities while at the same time is trying to keep their devices a suitable working temperature without penalizing that capacity. Consequently, the cooling systems of this kind of facilities use a large amount of energy to dissipate the heat generated inside the servers, and developing new cooling techniques or perfecting those already existing would be a great advance in this type of industry. The installation of a temperature sensor matrix distributed in the structure of each server would provide the necessary information for collecting the required data for obtaining a temperature profile instantly inside them. However, the number of temperature probes required to obtain the temperature profiles with sufficient accuracy is very high and expensive. Therefore, other less intrusive techniques are employed where each point that characterizes the server temperature profile is obtained by solving differential equations through simulation methods, simplifying data collection techniques but increasing the time to obtain results. In order to reduce these calculation times, complicated and slow computational fluid dynamics simulations are replaced by simpler and faster finite element method simulations which solve the Burgers‘ equations by backward, forward and central discretization techniques after simplifying the energy and enthalpy conservation differential equations. The discretization methods employed for solving the first and second order derivatives of the obtained Burgers‘ equation after these simplifications are the key for obtaining results with greater or lesser accuracy regardless of the characteristic truncation error.

Keywords: Burgers' equations, CFD simulation, data center, discretization methods, FEM simulation, temperature profile

Procedia PDF Downloads 163

Authors: Ziwei Qi

Abstract:

This paper focuses on issues on Urbanization, Rural Migration and Neighborhood Collective Efficacy in urban China. The urbanization and migration trend and policies in China will be discussed and the various mechanisms through which social structures affect economic action and the consequent of social disequilibrium due to urbanization will be discussed. The positive and negative propositions on urbanization will also be highlighted. The primary methodologies applied in the paper will be the theoretical application and empirical implication on urbanization in developing countries. Western sociological theories, including theories in urban criminology /sociology including social disorganization, theories of social capital and collective efficacy will be applied and analyzed to test the market society in Chinese economic and cultural setting.

Keywords: collective efficacy, civic engagement, rural migration, urbanization

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Authors: Živa Ravnikar, Alfonso Bahillo Martinez, Barbara Goličnik Marušić

Abstract:

Climate change mitigation has been formally adopted and announced by countries over the globe, where cities are targeting carbon neutrality through various more or less successful, systematic, and fragmentary actions. The article is based on the fact that environmental conditions affect human comfort and the usage of space. Urban planning can, with its sustainable solutions, not only support climate mitigation in terms of a planet reduction of global warming but as well enabling natural processes that in the immediate vicinity produce environmental conditions that encourage people to walk or cycle. However, the article draws attention to the importance of integrating climate consideration into urban planning, where detailed environmental data play a key role, enabling urban planners to improve or monitor environmental conditions on cycle paths. In a practical aspect, this paper tests a particular ICT tool, a prototype used for environmental data. Data gathering was performed along the cycling lanes in Ljubljana (Slovenia), where the main objective was to assess the tool's data applicable value within the planning of comfortable cycling lanes. The results suggest that such transportable devices for in-situ measurements can help a researcher interpret detailed environmental information, characterized by fine granularity and precise data spatial and temporal resolution. Data can be interpreted within human comfort zones, where graphical representation is in the form of a map, enabling the link of the environmental conditions with a spatial context. The paper also provides preliminary results in terms of the potential of such tools for identifying the correlations between environmental conditions and different spatial settings, which can help urban planners to prioritize interventions in places. The paper contributes to multidisciplinary approaches as it demonstrates the usefulness of such fine-grained data for better consideration of microclimatology in urban planning, which is a prerequisite for creating climate-comfortable cycling lanes promoting active mobility.

Keywords: information and communication technology tools, urban planning, human comfort, microclimate, cycling lanes

Procedia PDF Downloads 130