Search results for: sensing ability

Authors: Ai Chin Wong, Wan Ahmad Jaafar Wan Yahaya, Balakrishnan Muniandy

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This study aims to explore the impact of Virtual Reality (VR) using visual signaling principles in learning about the science laboratory safety guide; this study involves students with different spatial ability. There are two types of science laboratory safety lessons, which are Virtual Reality with Signaling (VRS) and Virtual Reality Non Signaling (VRNS). This research has adopted a 2 x 2 quasi-experimental factorial design. There are two types of variables involved in this research. The two modes of courseware form the independent variables with the spatial ability as the moderator variable. The dependent variable is the students’ performance. This study sample consisted of 141 students. Descriptive and inferential statistics were conducted to analyze the collected data. The major effects and the interaction effects of the independent variables on the independent variable were explored using the Analyses of Covariance (ANCOVA). Based on the findings of this research, the results exhibited low spatial ability students in VRS outperformed their counterparts in VRNS. However, there was no significant difference in students with high spatial ability using VRS and VRNS. Effective learning in students with different spatial ability can be boosted by implementing the Virtual Reality with Signaling (VRS) in the design as well as the development of Virtual Science Laboratory (ViSLab).

Keywords: spatial ability, science laboratory safety, visual signaling principles, virtual reality

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Authors: Victor William Harris

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This research is a validation study of the Social Emotional Ability Inventory (SEAI), a multi-dimensional self-report instrument informed by positive psychology, emotional intelligence, social intelligence, and sociocultural learning theory. Designed for use in tandem with the Social Emotional Development (SEAD) theoretical model, the SEAI provides diagnostic-level guidance for professionals and individuals interested in investigating, identifying, and understanding social, emotional strengths, as well as remediating specific social competency deficiencies. The SEAI was shown to be psychometrically sound, exhibited strong internal reliability, and supported the a priori hypotheses of the SEAD. Additionally, confirmatory factor analysis provided evidence of goodness of fit, convergent and divergent validity, and supported a theoretical model that reflected SEAD expectations. The SEAI and SEAD hold potentially far-reaching and important practical implications for theoretical guidance and diagnostic-level measurement of social, emotional competency across a wide range of domains. Strategies researchers, practitioners, educators, and individuals might use to deploy SEAI in order to improve quality of life outcomes are discussed.

Keywords: emotion, emotional ability, positive psychology-social emotional ability, social emotional ability, social emotional ability instrument

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Authors: Ishrath, Tapas Kumar Chatterjee

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The present study aims developing interpretation and evaluation to integrate various data types for management of existing water resources for sustainable use. Proper study should be followed based on the geomorphology of the area. Thematic maps such as lithology, base map, land use/land cover, geomorphology, drainage and lineaments maps are prepared to study the area by using area toposheet, IRS P6 and LISIII Satellite imagery. These thematic layers are finally integrated by using Arc GIS, Arc View, and software to prepare a ground water potential zones map of the study area. In this study, an integrated approach involving remote sensing and GIS techniques has successfully been used in identifying groundwater potential zones in the study area to classify them as good, moderate and poor. It has been observed that Pediplain shallow (PPS) has good recharge, Pediplain moderate (PPM) has moderately good recharge, Pediment Inselberg complex (PIC) has poor recharge and Inselberg (I) has no recharge. The study has concluded that remote sensing and GIS techniques are very efficient and useful for identifying ground water potential zones.

Keywords: satellite remote sensing, GIS, ground water potential zones, Miyapur

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Authors: S. S. Patil, Sachidanand Kini

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Classification of land use patterns is compelling in complexity and variability of remote sensing imageries data. An imperative research in remote sensing application exploited to mine some of the significant spatially variable factors as land cover and land use from satellite images for remote arid areas in Karnataka State, India. The diverse classification techniques, unsupervised and supervised consisting of maximum likelihood, Mahalanobis distance, and minimum distance are applied in Bellary District in Karnataka State, India for the classification of the raw satellite images. The accuracy evaluations of results are compared visually with the standard maps with ground-truths. We initiated with the maximum likelihood technique that gave the finest results and both minimum distance and Mahalanobis distance methods over valued agriculture land areas. In meanness of mislaid few irrelevant features due to the low resolution of the satellite images, high-quality accord between parameters extracted automatically from the developed maps and field observations was found.

Keywords: Mahalanobis distance, minimum distance, supervised, unsupervised, user classification accuracy, producer's classification accuracy, maximum likelihood, kappa coefficient

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Authors: A. Juhász, M. Fogarasi

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Those causing fatal traffic accidents are traumatized, which negatively influences their cognitive functions and their personality. In order to clarify how much the trauma of causing a fatal accident effects their driving skills and personality traits, the results of a psychological aptitude and a personality test of drivers carelessly causing fatal accidents and of drivers not causing any accidents were compared separately. The sample (N = 354) consists of randomly selected drivers from the Transportation Aptitude and Examination Centre database who caused fatal accidents (Fatal group, n = 177) or did not cause accidents (Control group, n = 177). The aptitude tests were taken between 2014 and 2019. The comparison of the 2 groups was done according to 3 aspects: 1. Categories of aptitude (suitable, restricted, unsuited); 2. Categories of causes (ability, personality, ability and personality) within the restricted or unsuited (altogether: non-suitable subgroups); 3. Categories of ability and personality within the non-suitable subgroups regardless of the cause-category. Within ability deficiency, the two groups include those, whose ability factor is impaired or limited. This is also true in case of personality failure. Compared to the control group, the number of restricted drivers causing fatal accidents is significantly higher (p < .000) and the number of unsuited drivers is higher on a tendency-level (p = .06). Compared to the control group in the fatal non-suitable subgroup, the ratio of restricted suitability and the unsuitability due to ability factors is exclusively significantly lower (p < .000). The restricted suitability and the unsuitability due to personality factors are more significant in the fatal non-suitable subgroup (p < .000). Incapacity due to combination of ability and personality is also significantly higher in the fatal group (p = .002). Compared to the control group both ability and personality factors are also significantly higher in the fatal non-suitable subgroup (p < .000). Overall, the control group is more eligible for driving than drivers who have caused fatalities. The ability and personality factors are significantly higher in the case of fatal accident causers who are non-suitable for driving. Moreover the concomitance of ability and personality factors occur almost exclusively to drivers who caused fatal accidents. Further investigation is needed to understand the causes and how the aptitude test results for the fatal group could improve over time.

Keywords: aptitude, unsuited, fatal accident, ability, personality

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Authors: Amirhossein Hasani, Shamin Houshmand Sharifi

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In this work, we investigate humidity sensing behavior of the graphene oxide with porous silicon substrate. By evaporation method, aluminum interdigital electrodes have been deposited onto porous silicon substrate. Then, by drop-casting method graphene oxide solution was deposited onto electrodes. The porous silicon was formed by electrochemical etching. The experimental results showed that using porous silicon substrate, we obtained two times larger sensitivity and response time compared with the results obtained with silicon substrate without porosity.

Keywords: graphene oxide, porous silicon, humidity sensor, electrochemical

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Authors: Elvira Wahyuni

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This study is a classroom action research. The general objective of this study was to find out students’ speaking ability through teaching English by using video and to find out the effectiveness of using video in teaching English to improve students’ speaking ability. The subjects of this study were 34 of the first-year students of SMAN 12 Pekanbaru who were learning English as a foreign language (EFL). Students were given pre-test before the treatment and post-test after the treatment. Quantitative data was collected by using speaking test requiring the students to respond to the recorded questions. Qualitative data was collected through observation sheets and field notes. The research finding reveals that there is a significant improvement of the students’ speaking ability through the use of video in speaking class. The qualitative data gave a description and additional information about the learning process done by the students. The research findings indicate that the use of video in teaching and learning is good in increasing learning outcome.

Keywords: English teaching, fun learning, speaking ability, video

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Authors: Wichian Sriprachan, Chutikarn Sriviboon

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The objectives of this research were to study the management of local towns and to develop a better model of town management according to the Philosophy of Sufficiency Economy. This study utilized qualitative research, field research, as well as documentary research at the same time. A total of 10 local towns or Tambons of Supanburi province, Thailand were selected for an in-depth interview. The findings revealed that the model of local town management according to Philosophy of Sufficient Economy was in a level of “good” and the model of management has the five basic guidelines: 1) ability to manage budget information and keep it up-to-date, 2) ability to decision making according to democracy rules, 3) ability to use check and balance system, 4) ability to control, follow, and evaluation, and 5) ability to allow the general public to participate. In addition, the findings also revealed that the human resource management according to Philosophy of Sufficient Economy includes obeying laws, using proper knowledge, and having integrity in five areas: plan, recruit, select, train, and maintain human resources.

Keywords: management, local town (Tambon), principles of sufficiency economy, marketing management

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Authors: Hong Dinh Duong, Jong Il Rhee

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In this study, a ratiometric inorganic phosphate sensor was fabricated by a double layer of the rhodamine 6G-doped nanofibers and the CdSe/ZnS QDs-captured polymer. In which, CdSe/ZnS QDs with emission wavelengths of 595nm were synthesized and ligands on their surface were exchanged with mercaptopropionic acid (MPA). The synthesized MPA-QDs were combined with the mixture of sol-gel of 3-glycidoxypropyl trimethoxysilane (GPTMS), 3-aminopropyltrimethoxysilane (APTMS) and polyurethane (PU) to build a layer for sensing inorganic phosphate. Another sensing layer was of nanofibers doped R6G which were produced from poly(styrene-co-acrylonitrile) by electrospining. The ratio of fluorescence intensities between rhodamin 6G (R6G) and CdSe/ZnS QDs exposed at different phosphate concentrations was used for calculating a linear phosphate concentration range of 0-10mM.

Keywords: nanofiber, QDs, ratiometric phosphate sensor, rhodamine 6G, sol-gel

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Authors: Kwang Chun, John Kemeny

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Light detection and ranging (LiDAR) has been a prevalent remote-sensing technology applied in the geological fields due to its high precision and ease of use. One of the major applications is to use the detailed geometrical information of underground structures as a basis for the generation of a three-dimensional numerical model that can be used in a geotechnical stability analysis such as FEM or DEM. To date, however, straightforward techniques in reconstructing the numerical model from the scanned data of the underground structures have not been well established or tested. In this paper, we propose a comprehensive approach integrating all the various processes, from LiDAR scanning to finite element numerical analysis. The study focuses on converting LiDAR 3D point clouds of geologic structures containing complex surface geometries into a finite element model. This methodology has been applied to Kartchner Caverns in Arizona, where detailed underground and surface point clouds can be used for the analysis of underground stability. Numerical simulations were performed using the finite element code Abaqus and presented by 3D computing visualization solution, ParaView. The results are useful in studying the stability of all types of underground excavations including underground mining and tunneling.

Keywords: finite element analysis, LiDAR, remote-sensing, scientific visualization, underground stability

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Authors: Bhawesh Kumar, A. P. Krishna

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There are continuous changes upon earth’s surface by a variety of natural and anthropogenic agents cut, carry away and depositing of minerals from land. Running water has higher capacity of erosion than other geomorphologic agents. This research work has been carried out on Ganga River, whose channel is continuously changing under the influence of geomorphic agents and human activities in the surrounding regions. The main focus is to study morphological characteristics and sand dynamics of Ganga River with particular emphasis on bank lines and width changes using remote sensing and GIS techniques. The advance remote sensing data and topographical data were interpreted for obtaining 52 years of changes. For this, remote sensing data of different years (LANDSAT TM 1975, 1988, 1993, ETM 2005 and ETM 2012) and toposheet of SOI for the year 1960 were used as base maps for this study. Sinuosity ratio, braiding index and migratory activity index were also established. It was found to be 1.16 in 1975 and in 1988, 1993, 2005 and 2005 it was 1.09, 1.11, 1.1, 1.09 respectively. The analysis also shows that the minimum value found in 1960 was in reach 1 and maximum value is 4.8806 in 2012 found in reach 4 which suggests creation of number of islands in reach 4 for the year 2012. Migratory activity index (MAI), which is a standardized function of both length and time, was computed for the 8 representative reaches. MAI shows that maximum migration was in 1975-1988 in reach 6 and 7 and minimum migration was in 1993-2005. From the channel change analysis, it was found that the shifting of bank line was cyclic and the river Ganges showed a trend of southward maximum values. The advanced remote sensing data and topographical data helped in obtaining 52 years changes in the river due to various natural and manmade activities like flood, water velocity and excavation, removal of vegetation cover and fertile soil excavation for the various purposes of surrounding regions.

Keywords: braided index, migratory activity index (MAI), Ganga river, river morphology

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Authors: Krzysztof Malczewski

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PET is widely applied scanning procedure in medical imaging based research. It delivers measurements of functioning in distinct areas of the human brain while the patient is comfortable, conscious and alert. This article presents the new compression sensing based super-resolution algorithm for improving the image resolution in clinical Positron Emission Tomography (PET) scanners. The issue of motion artifacts is well known in Positron Emission Tomography (PET) studies as its side effect. The PET images are being acquired over a limited period of time. As the patients cannot hold breath during the PET data gathering, spatial blurring and motion artefacts are the usual result. These may lead to wrong diagnosis. It is shown that the presented approach improves PET spatial resolution in cases when Compressed Sensing (CS) sequences are used. Compressed Sensing (CS) aims at signal and images reconstructing from significantly fewer measurements than were traditionally thought necessary. The application of CS to PET has the potential for significant scan time reductions, with visible benefits for patients and health care economics. In this study the goal is to combine super-resolution image enhancement algorithm with CS framework to achieve high resolution PET output. Both methods emphasize on maximizing image sparsity on known sparse transform domain and minimizing fidelity.

Keywords: PET, super-resolution, image reconstruction, pattern recognition

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Authors: Sunghun Jung, Wonkook Kim

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Due to the difficulty of the utilization of satellite and an aircraft, conventional ocean color remote sensing has a disadvantage in that it is difficult to obtain images of desired places at desired times. These disadvantages make it difficult to capture the anomalies such as the occurrence of the red tide which requires immediate observation. It is also difficult to understand the phenomena such as the resuspension-precipitation process of suspended solids and the spread of low-salinity water originating in the coastal areas. For the remote sensing reflectance of seawater, above-water radiometers (AWR) have been used either by carrying portable AWRs on a ship or installing those at fixed observation points on the Ieodo ocean research station, Socheongcho base, and etc. In particular, however, it requires the high cost to measure the remote reflectance in various seawater environments at various times and it is even not possible to measure it at the desired frequency in the desired sea area at the desired time. Also, in case of the stationary observation, it is advantageous that observation data is continuously obtained, but there is the disadvantage that data of various sea areas cannot be obtained. It is possible to instantly capture various marine phenomena occurring on the coast using the unmanned aerial system (UAS) including vertical takeoff and landing (VTOL) type unmanned aerial vehicles (UAV) since it could move and hover at the one location and acquire data of the desired form at a high resolution. To remotely estimate seawater constituents, it is necessary to install an ultra-spectral sensor. Also, to calculate reflected light from the surface of the sea in consideration of the sun’s incident light, a total of three sensors need to be installed on the UAV. The remote sensing reflectance of seawater is the most basic optical property for remotely estimating color components in seawater and we could remotely estimate the chlorophyll concentration, the suspended solids concentration, and the dissolved organic amount. Estimating seawater physics from the remote sensing reflectance requires the algorithm development using the accumulation data of seawater reflectivity under various seawater and atmospheric conditions. The UAS with three AWRs is developed for the remote reflection sensing on the surface of the sea. Throughout the paper, we explain the details of each UAS component, system operation scenarios, and simulation and experiment results. The UAS consists of a UAV, a solar tracker, a transmitter, a ground control station (GCS), three AWRs, and two gimbals.

Keywords: above-water radiometers (AWR), ground control station (GCS), unmanned aerial system (UAS), unmanned aerial vehicle (UAV)

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Authors: Ade Dwi Utami

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Pedagogic competence is the basic competence of teachers to perform their tasks as educators. The ability to assess has become one of the demands in teachers pedagogic competence. Teachers ability to assess is related to curriculum instructions and applications. This research is aimed at obtaining data concerning teachers ability to assess that comprises of understanding assessment, determining assessment type, tools and procedure, conducting assessment process, and using assessment result information. It uses mixed method of explanatory technique in which qualitative data is used to verify the quantitative data obtained through a survey. The technique of quantitative data collection is by test whereas the qualitative data collection is by observation, interview and documentation. Then, the analyzed data is processed through a proportion study technique to be categorized into high, medium and low. The result of the research shows that teachers ability to assess can be grouped into 3 namely, 2% of high, 4% of medium and 94% of low. The data shows that teachers ability to assess is still relatively low. Teachers are lack of knowledge and comprehension in assessment application. The statement is verified by the qualitative data showing that teachers did not state which aspect was assessed in learning, record children’s behavior, and use the data result as a consideration to design a program. Teachers have assessment documents yet they only serve as means of completing teachers administration for the certification program. Thus, assessment documents were not used with the basis of acquired knowledge. The condition should become a consideration of the education institution of educators and the government to improve teachers pedagogic competence, including the ability to assess.

Keywords: assessment, early childhood education, pedagogic competence, teachers

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Authors: Sarono, Hamim Zaky Hadibasyir, dan Ridho Kurniawan

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Estimation of paddy production is one of the areas that can be examined using the techniques of remote sensing and geographic information systems (GIS) in the field of agriculture. The purpose of this research is to know the amount of the paddy production estimation and how remote sensing and geographic information systems (GIS) are able to perform analysis of paddy production estimation in Tegalallang and Payangan Sub district, Bali Province, Indonesia. The method used is the method of land suitability. This method associates a physical parameters which are to be embodied in the smallest unit of a mapping that represents a mapping unit in a particular field and connecting with its field productivity. Analysis of estimated production using standard land suitability from FAO using matching technique. The parameters used to create the land unit is slope (FAO), climate classification (Oldeman), landform (Prapto Suharsono), and soil type. Land use map consist of paddy and non paddy field information obtained from Geo-eye 1 imagery using visual interpretation technique. Landsat image of the Data used for the interpretation of the landform, the classification of the slopes obtained from high point identification with method of interpolation spline, whereas climate data, soil, use secondary data originating from institutions-related institutions. The results of this research indicate Tegallalang and Payangan Districts in known wetland suitability consists of S1 (very suitable) covering an area of 2884,7 ha with the productivity of 5 tons/ha and S2 (suitable) covering an area of 482,9 ha with the productivity of 3 tons/ha. The sum of paddy production estimation as a results in both districts are 31.744, 3 tons in one year.

Keywords: production estimation, paddy, remote sensing, geography information system, land suitability

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Authors: Klathea Sevilla, Marjorie Remolador, Bryan Baltazar, Imee Saladaga, Loureal Camille Inocencio, Ma. Rosario Concepcion Ang

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The underutilization of biomass resources in the Philippines, combined with its growing population and the rise in fossil fuel prices confirms demand for alternative energy sources. The goal of this paper is to provide a comparison of MODIS-based and Landsat-based agricultural land cover maps when used in the estimation of rice hull’s available energy potential. Biomass resource assessment was done using mathematical models and remote sensing techniques employed in a GIS platform.

Keywords: biomass, geographic information system (GIS), remote sensing, renewable energy

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Authors: Eman Mohamed Abdelwahab, Badreyya Alkhanbooli

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This study focuses on exploring the challenges encountered by English language teachers in same-ability English language classrooms in the United Arab Emirates public schools. This qualitative study uses open-ended questions for data collection from teacher participants. The study sample includes the participation of 60 English language teachers from 8 public schools across 4 emirates/cities in the United Arab Emirates. The study results highlight a number of challenges that are mostly encountered by English language teachers in their classrooms while teaching in same-ability classrooms, including lack of diversity in abilities, class-time limitation, difficulty in engaging all students (especially lower-achieving students), limited opportunities for peer learning and limited linguistic diversity. A set of suggestions is to be provided by participating teachers and researchers to improve the same-ability teaching and learning experience in English language classrooms.

Keywords: English language teaching, same ability grouping, ESL, English language learners

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Authors: Jiraporn Lao-Un, Dararat Khampusaen

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Lack of exposure to English language in the authentic English setting naturally leads to a lack of fluency in the language. As a result, Thai EFL learners are struggling in meeting with the communication 'can do' descriptors of the Common European Framework of References (CEFR) required by the Ministry of Education. This initial phase of the ongoing study, employing the e-portfolio to promote the English speaking ability, probed into the effects of the use of e-portfolio on Thai EFL nursing students' speaking ability. Also, their opinions towards the use of e-portfolio to enhance their speaking ability were investigated. The participants were 44 undergraduate nursing students at a Thai College of Nursing. The participants undertook four lessons to promote their communication skills according to the CEFR criteria. Throughout the semester, the participants videotaped themselves while completing the four speaking tasks. The videos were then uploaded onto the e-portfolio website where the researcher provided them with the feedbacks. The video records were analyzed by the speaking rubric designed according to the CEFR 'can do' descriptors. Also, students were required to record self-reflections in video format and upload onto the same URL Students' oral self-reflections were coded to find out the perceptions towards the use of the e-portfolio in promoting their speaking ability. The results from the two research instruments suggested the effectiveness of the tool on improving speaking ability, learner autonomy and media literacy skills. In addition, the oral reflection videos revealed positive opinion towards the tool. The discussion offers the current status of English speaking ability among Thai EFL students. This reveals the gaps between the EFL speaking ability and the CEFR ‘can do’ descriptors. In addition, the author raises the light on integration of the 21st century IT tool to enhance these students’ speaking ability. Lastly, the theoretical implications and recommendation for further study in integrating electronic tools to promote language skills in the EFL context are offered for further research.

Keywords: EFL communication, EFL speaking, English communication, E-learning, E-portfolio, speaking ability, Thai EFL learners

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Authors: Jin Koo

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The main purpose of this study is to investigate the comparability of student scores obtained from Test Center (TC) vs. Online-Proctored (OP) Delivery in the three subject areas of Verbal, Reading, and Mathematics for each level (Middle and Upper). Also, this study examines whether there is an interaction effect between test deliveries (TC vs. OP) and gender/ethnicity/ability level in each subject area. The test used in this study is a multiple-choice standardized test for students in grades 5-11. For this study, data were collected during the 2022-23 test administration. This research used a one-factor between-subjects ANOVA and Cohen’s d to compare the TC and OP groups’ test means for each level and each subject area. Also, 2-factor between-subjects ANOVAs were conducted to investigate examinee characteristics: gender (male and female), ethnicity (African-American, Asian, Hispanic, Multi-racial, and White), and ability level (low, average, and high-ability groups). The author found that students’ test scores in some subject areas varied between TC and OP test deliveries by gender, ethnicity, and ability level, meaning that gender, ethnicity, and ability level were related to the score difference. These results will be discussed according to the current testing systems.

Keywords: ability level, ethnicity, gender, online-proctored delivery, standardized test, test center

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Authors: K. Berhanu

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Improper land use results in land degradation and decline in agricultural productivity. Hence, in order to get maximum benefits out of land, proper utilization of its resources is inevitable. The present study was aimed at identifying the landcover changes in the study area in the last 25 years and determines the extent and direction of change that has occurred. The study made use of Landsat TM 1986 and 2011 Remote Sensing Satellite Image for analysis to determine the extent and pattern of rangeland change. The results of the landuse/landcover change detection showed that in the last 25 years, 3 major changes were observed, grassland and open shrub-land resource significantly decreased at a rate of 17.1km2/year and 12 km2/year/, respectively. On the other hand in 25 years dense bushland, open bush land, dense shrubland and cultivated land has shown increment in size at a rate of 0.23km2/year,13.5 km2/year, 6.3 km2/year and 0.2 km2/year, respectively within 25 years. The expansion of unpalatable woody species significantly reduced the rangeland size and availability of grasses. The consequence of the decrease in herbaceous biomass production might result in high risk of food insecurity in the area unless proper interventions are made in time.

Keywords: GIS and remote sensing, Dire District, land use/land cover, land sat TM

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Authors: Yun-Hsiang Lee

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Cancer is the main cause of death worldwide. With advances in medical technology, immunotherapy, which is a newly developed advanced treatment, is currently a crucial cancer treatment option. For better quality cancer care, the ability to communicate and critical thinking plays a central role in clinical oncology settings. However, few studies have explored the impact of communication skills on immunotherapy-related issues and their related factors. This study was to (i) explore the current status of communication skill ability for immunotherapy-related issues, self-efficacy for immunotherapy-related care, and critical thinking ability; and (ii) identify factors related to communication skill ability. This is a cross-sectional study. Oncology nurses were recruited from the Taiwan Oncology Nursing Society, in which nurses came from different hospitals distributed across four major geographic regions (North, Center, South, East) of Taiwan. A total of 123 oncology nurses participated in this study. A set of questionnaires were used for collecting data. Communication skill ability for immunotherapy issues, self-efficacy for immunotherapy-related care, critical thinking ability, and background information were assessed in this survey. Independent T-test and one-way ANOVA were used to examine different levels of communication skill ability based on nurses having done oncology courses (yes vs. no) and education years (< 1 year, 1-3 years, and > 3 years), respectively. Spearman correlation was conducted to understand the relationships between communication skill ability and other variables. Among the 123 oncology nurses in the current study, the majority of them were female (98.4%), and most of them were employed at a hospital in the North (46.8%) of Taiwan. Most of them possessed a university degree (78.9%) and had at least 3 years of prior work experience (71.7%). Forty-three of the oncology nurses indicated in the survey that they had not received oncology nurses-related training. Those oncology nurses reported moderate to high levels of communication skill ability for immunotherapy issues (mean=4.24, SD=0.7, range 1-5). Nurses reported moderate levels of self-efficacy for immunotherapy-related care (mean=5.20, SD=1.98, range 0-10) and also had high levels of critical thinking ability (mean=4.76, SD=0.60, range 1-6). Oncology nurses who had received oncology training courses had significantly better communication skill ability than those who had not received oncology training. Oncology nurses who had higher work experience (1-3 years, or > 3 years) had significantly higher levels of communication skill ability for immunotherapy-related issues than those with lower work experience (<1 year). When those nurses reported better communication skill ability, they also had significantly better self-efficacy (r=.42, p<.01) and better critical thinking ability (r=.47, p<.01). Taken altogether, courses designed to improve communication skill ability for immunotherapy-related issues can make a significant impact in clinical settings. Communication skill ability for oncology nurses is the major factor associated with self-efficacy and critical thinking, especially for those with lower work experience (< 1 year).

Keywords: communication skills, critical thinking, immunotherapy, oncology nurses, self-efficacy

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Authors: Sofiane Bendoukha, Daniel Moldt, Hayat Bendoukha

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Workflow concepts are essential for the development of remote sensing applications. They can help users to manage and process satellite data and execute scientific experiments on distributed resources. The objective of this paper is to introduce an approach for the specification and the execution of complex scientific workflows in Cloud-like environments. The approach strives to support scientists during the modeling, the deployment and the monitoring of their workflows. This work takes advantage from Petri nets and more pointedly the so-called reference nets formalism, which provides a robust modeling/implementation technique. RENEWGRASS is a tool that we implemented and integrated into the Petri nets editor and simulator RENEW. It provides an easy way to support not experienced scientists during the specification of their workflows. It allows both modeling and enactment of image processing workflows from the remote sensing domain. Our case study is related to the implementation of vegetation indecies. We have implemented the Normalized Differences Vegetation Index (NDVI) workflow. Additionally, we explore the integration possibilities of the Cloud technology as a supplementary layer for the deployment of the current implementation. For this purpose, we discuss migration patterns of data and applications and propose an architecture.

Keywords: cloud computing, scientific workflows, petri nets, RENEWGRASS

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Authors: Ionel D. Craiu, Mihai Nedelcu

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Thin-walled cylinders are often used by the offshore industry as columns of floating installations. Based on observed strains, the inverse Finite Element Method (iFEM) may rebuild the deformation of structures. Structural Health Monitoring uses this approach extensively. However, the number of in-situ strain gauges is what determines how accurate it is, and for shell structures with complicated deformation, this number can easily become too high for practical use. Any thin-walled beam member's complicated deformation can be modeled by the Generalized Beam Theory (GBT) as a linear combination of pre-specified cross-section deformation modes. GBT uses bar finite elements as opposed to shell finite elements. This paper proposes an iFEM/GBT formulation for the shape sensing of thin-walled cylinders based on these benefits. This method significantly reduces the number of strain gauges compared to using the traditional inverse-shell finite elements. Using numerical simulations, dent damage detection is achieved by comparing the strain distributions of the undamaged and damaged members. The effect of noise on strain measurements is also investigated.

Keywords: damage detection, generalized beam theory, inverse finite element method, shape sensing

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Authors: Mohammed Al Sulaimani, Hamad Al Manhi

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With the development of Remote Sensing technology, the resolution of optical Remote Sensing images has greatly improved, and images have become largely available. Numerous detectors have been developed for detecting different types of objects. In the past few years, Remote Sensing has benefited a lot from deep learning, particularly Deep Convolution Neural Networks (CNNs). Deep learning holds great promise to fulfill the challenging needs of Remote Sensing and solving various problems within different fields and applications. The use of Unmanned Aerial Systems in acquiring Aerial Photos has become highly used and preferred by most organizations to support their activities because of their high resolution and accuracy, which make the identification and detection of very small features much easier than Satellite Images. And this has opened an extreme era of Deep Learning in different applications not only in feature extraction and prediction but also in analysis. This work addresses the capacity of Machine Learning and Deep Learning in detecting and extracting Oil Leaks from Flowlines (Onshore) using High-Resolution Aerial Photos which have been acquired by UAS fixed with RGB Sensor to support early detection of these leaks and prevent the company from the leak’s losses and the most important thing environmental damage. Here, there are two different approaches and different methods of DL have been demonstrated. The first approach focuses on detecting the Oil Leaks from the RAW Aerial Photos (not processed) using a Deep Learning called Single Shoot Detector (SSD). The model draws bounding boxes around the leaks, and the results were extremely good. The second approach focuses on detecting the Oil Leaks from the Ortho-mosaiced Images (Georeferenced Images) by developing three Deep Learning Models using (MaskRCNN, U-Net and PSP-Net Classifier). Then, post-processing is performed to combine the results of these three Deep Learning Models to achieve a better detection result and improved accuracy. Although there is a relatively small amount of datasets available for training purposes, the Trained DL Models have shown good results in extracting the extent of the Oil Leaks and obtaining excellent and accurate detection.

Keywords: GIS, remote sensing, oil leak detection, machine learning, aerial photos, unmanned aerial systems

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Authors: Pola Goldberg Oppenheimer, Stephan Hofmann, Sumeet Mahajan

Abstract:

Owing to its fingerprint molecular specificity and high sensitivity, surface-enhanced Raman scattering (SERS) is an established analytical tool for chemical and biological sensing capable of single-molecule detection. A strong Raman signal can be generated from SERS-active platforms given the analyte is within the enhanced plasmon field generated near a noble-metal nanostructured substrate. The key requirement for generating strong plasmon resonances to provide this electromagnetic enhancement is an appropriate metal surface roughness. Controlling nanoscale features for generating these regions of high electromagnetic enhancement, the so-called SERS ‘hot-spots’, is still a challenge. Significant advances have been made in SERS research, with wide-ranging techniques to generate substrates with tunable size and shape of the nanoscale roughness features. Nevertheless, the development and application of SERS has been inhibited by the irreproducibility and complexity of fabrication routes. The ability to generate straightforward, cost-effective, multiplex-able and addressable SERS substrates with high enhancements is of profound interest for miniaturised sensing devices. Carbon nanotubes (CNTs) have been concurrently, a topic of extensive research however, their applications for plasmonics has been only recently beginning to gain interest. CNTs can provide low-cost, large-active-area patternable substrates which, coupled with appropriate functionalization capable to provide advanced SERS-platforms. Herein, advanced methods to generate CNT-based SERS active detection platforms will be discussed. First, a novel electrohydrodynamic (EHD) lithographic technique will be introduced for patterning CNT-polymer composites, providing a straightforward, single-step approach for generating high-fidelity sub-micron-sized nanocomposite structures within which anisotropic CNTs are vertically aligned. The created structures are readily fine-tuned, which is an important requirement for optimizing SERS to obtain the highest enhancements with each of the EHD-CNTs individual structural units functioning as an isolated sensor. Further, gold-functionalized VACNTFs are fabricated as SERS micro-platforms. The dependence on the VACNTs’ diameters and density play an important role in the Raman signal strength, thus highlighting the importance of structural parameters, previously overlooked in designing and fabricating optimized CNTs-based SERS nanoprobes. VACNTs forests patterned into predesigned pillar structures are further utilized for multiplex detection of bio-analytes. Since CNTs exhibit electrical conductivity and unique adsorption properties, these are further harnessed in the development of novel chemical and bio-sensing platforms.

Keywords: carbon nanotubes (CNTs), EHD patterning, SERS, vertically aligned carbon nanotube forests (VACNTF)

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Authors: Aliaa M. S. Salem, Soliman I. El-Hout, Amira Gaber, Hassan Nageh

Abstract:

Nowadays, the development of poisonous gas detectors is considered to be an urgent matter to secure human health and the environment from poisonous gases, in view of the fact that even a minimal amount of poisonous gas can be fatal. Of these concerns, various inorganic or organic sensing materials have been used. Among these are conducting polymers, have been used as the active material in the gassensorsdue to their low-cost,easy-controllable molding, good electrochemical properties including facile fabrication process, inherent physical properties, biocompatibility, and optical properties. Moreover, conducting polymer-based chemical sensors have an amazing advantage compared to the conventional one as structural diversity, facile functionalization, room temperature operation, and easy fabrication. However, the low selectivity and conductivity of conducting polymers motivated the doping of it with varied materials, especially graphene, to enhance the gas-sensing performance under ambient conditions. There were a number of approaches proposed for producing polymer/ graphene nanocomposites, including template-free self-assembly, hard physical template-guided synthesis, chemical, electrochemical, and electrospinning...etc. In this work, we aim to prepare a novel gas sensordepending on Electrospun nanofibers of conducting polymer/RGO composite that is the effective and efficient expectation of poisonous gases like ammonia, in different application areas such as environmental gas analysis, chemical-,automotive- and medical industries. Moreover, our ultimate objective is to maximize the sensing performance of the prepared sensor and to check its recovery properties.

Keywords: electro spinning process, conducting polymer, polyaniline, polypyrrole, polythiophene, graphene oxide, reduced graphene oxide, functionalized reduced graphene oxide, spin coating technique, gas sensors

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Authors: Ming-Jong Tsai, T. M. Wu, R. C. Chu

Abstract:

The purpose of this study is to develop an Advanced linear calibration Technique for air flow sensing by using CTA-based Hot wire Anemometry. It contains a host PC with Human Machine Interface, a wind tunnel, a wind speed controller, an automatic data acquisition module, and nonlinear calibration model. To improve the fitting error by using single fitting polynomial, this study proposes a Multiple three-order Polynomial Fitting Method (MPFM) for fitting the non-linear output of a CTA-based Hot wire Anemometry. The CTA-based anemometer with built-in fitting parameters is installed in the wind tunnel, and the wind speed is controlled by the PC-based controller. The Hot-Wire anemometer's thermistor resistance change is converted into a voltage signal or temperature differences, and then sent to the PC through a DAQ card. After completion measurements of original signal, the Multiple polynomial mathematical coefficients can be automatically calculated, and then sent into the micro-processor in the Hot-Wire anemometer. Finally, the corrected Hot-Wire anemometer is verified for the linearity, the repeatability, error percentage, and the system outputs quality control reports.

Keywords: flow rate sensing, hot wire, constant temperature anemometry (CTA), linear calibration, multiple three-order polynomial fitting method (MPFM), temperature compensation

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Authors: Hestika D. Waraningrum, Indriani N. Khairunnisa, Nabila Isnandini, Nadine Yasminah, Sekar A. Winesa

Abstract:

Each individual’s ability to recall, whether they are male or female, is allegedly influenced by the environmental circumstances during the recalling process. The presence of a distraction is one of the environmental variables that affect recall ability in its capacity in the Short Term Memory. This study was made to see the difference in number of words that was successfully recalled by male participants and female participants with the presence of music as a distraction and also without music as a distraction. Data was taken using an experimental procedure from 75 female and male undergraduate students of Universitas Indonesia. The study design used was a 2x2 Factorial ANOVA, which aimed to see the difference between two variables, which were gender (male vs female) and the presence of a distraction (music serving as a distraction vs absence of music). The results indicated that there were no significant mean differences in the ability to recall between male and female participants. There are no significant mean differences between the presence and the absence of music as a distraction, but a significant interaction was found between gender and distraction with the ability to recall.

Keywords: college, gender, music, recall

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Authors: Tingwei Shu, Dong Zhou, Chengjun Guo

Abstract:

Semantic communication is an emerging form of communication that realize intelligent communication by extracting semantic information of data at the source and transmitting it, and recovering the data at the receiving end. It can effectively solve the problem of data transmission under the situation of large data volume, low SNR and restricted bandwidth. With the development of Deep Learning, semantic communication further matures and is gradually applied in the fields of the Internet of Things, Uumanned Air Vehicle cluster communication, remote sensing scenarios, etc. We propose an improved semantic communication system for the situation where the data volume is huge and the spectrum resources are limited during the transmission of remote sensing images. At the transmitting, we need to extract the semantic information of remote sensing images, but there are some problems. The traditional semantic communication system based on Convolutional Neural Network cannot take into account the global semantic information and local semantic information of the image, which results in less-than-ideal image recovery at the receiving end. Therefore, we adopt the improved vision-Transformer-based structure as the semantic encoder instead of the mainstream one using CNN to extract the image semantic features. In this paper, we first perform pre-processing operations on remote sensing images to improve the resolution of the images in order to obtain images with more semantic information. We use wavelet transform to decompose the image into high-frequency and low-frequency components, perform bilinear interpolation on the high-frequency components and bicubic interpolation on the low-frequency components, and finally perform wavelet inverse transform to obtain the preprocessed image. We adopt the improved Vision-Transformer structure as the semantic coder to extract and transmit the semantic information of remote sensing images. The Vision-Transformer structure can better train the huge data volume and extract better image semantic features, and adopt the multi-layer self-attention mechanism to better capture the correlation between semantic features and reduce redundant features. Secondly, to improve the coding efficiency, we reduce the quadratic complexity of the self-attentive mechanism itself to linear so as to improve the image data processing speed of the model. We conducted experimental simulations on the RSOD dataset and compared the designed system with a semantic communication system based on CNN and image coding methods such as BGP and JPEG to verify that the method can effectively alleviate the problem of excessive data volume and improve the performance of image data communication.

Keywords: semantic communication, transformer, wavelet transform, data processing

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Authors: Fikre Belay Tekulu

Abstract:

The Adigrat town lies in the Tigray region of Ethiopia. This region is mountainous and experiences a semiarid type of climate. Most of the rainfall occurs in four months of the year, which are June to September. During this season, flood is a common natural disaster, especially in urban areas. In this paper, an attempt is made to identify flood-prone areas in Adigrat town using Boolean logic with GIS and remote sensing techniques. Three parameters were incorporated as land use type, elevation, and slope. Boolean logic was used as land use equal to buildup land, elevation less than 2430 m, and slope less than 5 degrees. As a result, 0.575 km² was identified severely affected by floods during the rainy season.

Keywords: flood, GIS, hydrology, Adigrat

Procedia PDF Downloads 121