Search results for: community based rehabilitation

Authors: Akm Shahidullah

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This paper assessed the medicinal plants production and related entrepreneurial and management aspects with a focus to understand the present medicinal plants-based supply chain of Bangladesh. It delineated the overall supply chain and the extent of benefit that the plant-producingagrientrepreneursderive out of the existing system of the chain. The key objective was to put forward innovative supply chain strategiesthatcan leverage the benefit of the rural farmer-entrepreneur of medicinal plants. A field-based investigation was carried out in the Natore district of northwest Bangladesh, where a total of 225 farmers and households from eight villages were engaged in the production of medicinal plant species. The research had a survey with the agrientrepreneurs of two of those villages and focus group discussions at a union level to gather information about the price, buyers, seasonality, and overall supply infrastructure and trading mechanisms of the plant products. The research also gathered explanations on the overall supply chain system of the plants and plant-based processed products through key informant interviews with the local and regional selling agents, stockists, wholesalers, and secondary processors. The findings revealed that, in the existing supply chain system, the primary and wholesale secondary markets were mostly dominated by middlemen who cause market distortions and inflated prices due to a lack of coordination between the primary producers and secondary processors. The discoordination and inefficiencies in the supply chain system could be offset by the producer-processor relationship integration that could result in a multitude of benefits to both the parties in terms of price, quality, lead time, and overall control of the supply chain. Therefore, to ensure the growth of medicinal plants production, the industry users, secondary processors, and policy stakeholders should ensure that the primary producers get the fair share of the benefit; the producer-processor relationship integration in the supply chain offers to ensure that fairness with maximum producer surplus.

Keywords: medicinal-plants, agrientrepreneur, supply chain, relationship integration, Bangladesh

Procedia PDF Downloads 82

Authors: Ashish Dhamaniya, Vineet Jain, Rajesh Chouhan

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Traffic management is one of the gigantic issue in most of the urban roads in al-most all metropolitan cities in India. Speed is one of the critical traffic parameters for effective Intelligent Transportation System (ITS) implementation as it decides the arrival rate of vehicles on an intersection which are majorly the point of con-gestions. The study aimed to leverage Machine Learning (ML) models to produce precise predictions of speed on urban roadway links. The research objective was to assess how categorized traffic volume and road width, serving as variables, in-fluence speed prediction. Four tree-based regression models namely: Decision Tree (DT), Random Forest (RF), Extra Tree (ET), and Extreme Gradient Boost (XGB)are employed for this purpose. The models' performances were validated using test data, and the results demonstrate that Random Forest surpasses other machine learning techniques and a conventional utility theory-based model in speed prediction. The study is useful for managing the urban roadway network performance under mixed traffic conditions and effective implementation of ITS.

Keywords: stream speed, urban roads, machine learning, traffic flow

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Authors: Jun-ya Nagase

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There are many pipes such as a water pipe and a gas pipe in a chemical plant and house. It is possible to prevent accidents by these inspections. However, many pipes are very narrow and it is difficult for people to inspect directly. Therefore, development of a robot that can move in narrow pipe is necessary. A wheel movement type robot, a snake-like robot and a multi-leg robot are all described in the relevant literature as pipe inspection robots that are currently studied. Among them, the tracked crawler robot can travel by traversing uneven ground flexibly with a crawler belt attached firmly to the ground surface. Although conventional crawler robots have high efficiency and/or high ground-covering ability, they require a comparatively large space to move. In this study, a cylindrical crawler robot based on worm-rack mechanism, which does not need large space to move and which has high ground-covering ability, is proposed. Experiments have demonstrated smooth operation and a forward movement of the robot by application of voltage to the motor. In addition, performance tests show that it can propel itself in confined spaces. This paper reports the structure, drive mechanism, prototype, and experimental evaluation.

Keywords: tracked-crawler, pipe inspection robot, worm-rack mechanism, amoeba locomotion

Procedia PDF Downloads 423

Authors: Lin Gong, Holger Göbel

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In the present study, we have investigated the influence of UV/ozone treatment on pentacene-based organic field effect transistors (OFETs) with a bilayer gate dielectric. The OFETs for this study were fabricated on heavily n-doped Si substrates with a thermally deposited SiO2 dielectric layer (300nm). On the SiO2 dielectric a very thin (≈ 15nm) buffer layer of polystyrene (PS) was first spin-coated and then treated by UV/ozone to modify the surface prior to the deposition of pentacene. We found out that by extending the UV/ozone treatment time the threshold voltage of the OFETs was monotonically shifted towards positive values, whereas the field effect mobility first decreased but eventually reached a stable value after a treatment time of approximately thirty seconds. Since the field effect mobility of the UV/ozone treated bilayer OFETs was found to be higher than the value of a comparable transistor with a single layer dielectric, we propose that the bilayer (SiO2/PS) structure can be used to shift the threshold voltage to a desired value without sacrificing field effect mobility.

Keywords: buffer layer, organic field effect transistors, threshold voltage, UV/ozone treatment

Procedia PDF Downloads 325

Authors: Seema Sant

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In the 21st century were four generation workforces are working, it’s crucial for organizations to build talent management strategy, as tech-savvy Gen Y has entered the work force. They are more connected to each other than ever – through the internet enabled Social media networks Social media has become important in today’s world. The users of such Social media sites have increased in multiple. From sharing their opinion for a brand/product to researching a company before going for an interview, making a conception about a company’s culture or following a Company’s updates due to sheer interest or for job vacancy, Work force today is constantly in touch with social networks. Thus corporate world has rightly realized its potential uses for business purpose. Companies now use social media for marketing, advertising, consumer survey, etc. For HR professionals, it is used for networking and connecting to the Talent pool- through Talent Community. Social recruiting is the process of sourcing or hiring candidates through the use of social sites such as LinkedIn, Facebook Twitter which provide them with an array of information about potential employee; this study represents an exploratory investigation on the role of social networking sites in recruitment. The primarily aim is to analyze the factors that can enhance the channel of recruitment used by of the recruiter with specific reference to the IT organizations in Mumbai, India. Particularly, the aim is to identify how and why companies use social media to attract and screen applicants during their recruitment processes. It also examines the advantages and limitations of recruitment through social media for employers. This is done by literature review. Further, the papers examine the recruiter impact and understand the various opportunities which have created due to technology, thus, to analyze and examine these factors, both primary, as well as secondary data, are collected for the study. The primary data are gathered from five HR manager working in five top IT organizations in Mumbai and 100 HR consultants’ i.e., recruiter. The data was collected by conducting a survey and supplying a closed-ended questionnaire. A comprehension analysis of the study is depicted through graphs and figures. From the analysis, it was observed that there exists a positive relationship between the level of employee recruited through social media and their organizational commitment. Finally the findings show that company’s i.e. recruiters are currently using social media in recruitment, but perhaps not as effective as they could be. The paper gives recommendations and conditions for success that can help employers to make the most out of social media in recruitment.

Keywords: recruitment, social media, social sites, workforce

Procedia PDF Downloads 167

Authors: Samaneh Abolli, Mahdi Ahmadi Nasab, Kamyar Yaghmaeian, Mahmood Alimohammadi

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The quality of drinking water, in addition to the presence of physicochemical parameters, depends on the type and geographical location of water sources. In this study, groundwater quality was investigated by sampling total dissolved solids (TDS), electrical conductivity (EC), total hardness (TH), Cl, Ca²⁺, and Mg²⁺ parameters in 13 sites, and 40 water samples were sent to the laboratory. Electrometric, titration, and spectrophotometer methods were used. In the next step, the water quality index (WQI) was used to investigate the impact and weight of each parameter in the groundwater. The results showed that only the mean of magnesium ion (40.88 mg/l) was lower than the guidelines of World Health Organization (WHO). Interpreting the WQI based on the WHO guidelines showed that the statuses of 21, 11, and 7 samples were very poor, poor, and average quality, respectively, and one sample had excellent quality. Among the studied parameters, the means of EC (2,087.49 mS/cm) and Cl (1,015.87 mg/l) exceeded the global and national limits. Classifying water quality of TH was very hard (87.5%), hard (7.5%), and moderate (5%), respectively. Based on the geographical distribution, the drinking water index in sites 4 and 11 did not have acceptable quality. Chloride ion was identified as the responsible pollutant and the most important ion for raising the index. The outputs of statistical tests and Spearman correlation had significant and direct correlation (p < 0.05, r > 0.7) between TDS, EC, and chloride, EC and chloride, as well as TH, Ca²⁺, and Mg²⁺.

Keywords: water quality index, groundwater, chloride, GIS, Garmsar

Procedia PDF Downloads 86

Authors: Maryam Khazaei Pool, Lori Lewis

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This is a summary of articles based on higher order B-splines methods and the variation of B-spline methods such as Quadratic B-spline Finite Elements Method, Exponential Cubic B-Spline Method, Septic B-spline Technique, Quintic B-spline Galerkin Method, and B-spline Galerkin Method based on the Quadratic B-spline Galerkin method (QBGM) and Cubic B-spline Galerkin method (CBGM). In this paper, we study the B-spline methods and variations of B-spline techniques to find a numerical solution to the Burgers’ equation. A set of fundamental definitions, including Burgers equation, spline functions, and B-spline functions, are provided. For each method, the main technique is discussed as well as the discretization and stability analysis. A summary of the numerical results is provided, and the efficiency of each method presented is discussed. A general conclusion is provided where we look at a comparison between the computational results of all the presented schemes. We describe the effectiveness and advantages of these methods.

Keywords: Burgers’ equation, Septic B-spline, modified cubic B-spline differential quadrature method, exponential cubic B-spline technique, B-spline Galerkin method, quintic B-spline Galerkin method

Procedia PDF Downloads 107

Authors: D. Suman, B. Nikitha, J. Sarvani, V. Archana

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Histological slides provide clinical diagnostic information about the subjects from the ancient times. Even with the advent of high resolution imaging cameras the image tend to have some background noise which makes the analysis complex. A study of the histological slides is done by using a nonlinear transfer function based image enhancement method. The method processes the raw, color images acquired from the biological microscope, which, in general, is associated with background noise. The images usually appearing blurred does not convey the intended information. In this regard, an enhancement method is proposed and implemented on 50 histological slides of human tissue by using nonlinear transfer function method. The histological image is converted into HSV color image. The luminance value of the image is enhanced (V component) because change in the H and S components could change the color balance between HSV components. The HSV image is divided into smaller blocks for carrying out the dynamic range compression by using a linear transformation function. Each pixel in the block is enhanced based on the contrast of the center pixel and its neighborhood. After the processing the V component, the HSV image is transformed into a colour image. The study has shown improvement of the characteristics of the image so that the significant details of the histological images were improved.

Keywords: HSV space, histology, enhancement, image

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Authors: Andrzej Kesiak

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Contemporary theology is often accused of answering questions that nobody is asking, and of employing hermetic language that has lost its communication capacity. There is also a question that theology is asking itself: how theological discourse can still be influential on other disciplines and, how to overcome the separation of theology and belief. Undoubtedly, in the wider spectrum, the theological discourse has been and will be needed. The difficulty is how to find the right model of it, the model that would help theology to enter in dialogue with culture, art, science, and politics. Presumably, there is no only one such model, theology constantly needs to seek such models, and this is probably a never-ending journey; in other words, theology should adopt a profile of ‘a restless being’ if it wants to remain influential. Music, on the other hand, has always been very close to theology; in fact, a huge part of classical music is either sacred or religious. Many composers sought inspiration in religion, liturgy, religious painting and sacred texts. This paper will argue that despite all that it seems that a proper and factual dialogue is still in a starting phase. Such a thing as a reciprocal relationship between theology and music definitely exists, but it has not yet been theoretically developed enough. Correlation between musical and theological disciplines constitutes a very broad and complex discourse. Therefore this study would rather narrow the subject and put it in a specific context: Theology and Music in the XXI. Century. This paper is a text-based study; therefore it will be based on textual-analysis with elements of the text hermeneutics.

Keywords: music, theology, reciprocal relationship between theology and music, XXI Century

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Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu

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Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies.

Keywords: runoff, roughness coefficient, PAR, WRM model

Procedia PDF Downloads 361

Authors: M. M. Qasaymeh, M. A. Khodeir

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Subspace channel estimation methods have been studied widely. It depends on subspace decomposition of the covariance matrix to separate signal subspace from noise subspace. The decomposition normally is done by either Eigenvalue Decomposition (EVD) or Singular Value Decomposition (SVD) of the Auto-Correlation matrix (ACM). However, the subspace decomposition process is computationally expensive. In this paper, the multipath channel estimation problem for a Slow Frequency Hopping (SFH) system using noise space based method is considered. An efficient method to estimate multipath the time delays basically is proposed, by applying MUltiple Signal Classification (MUSIC) algorithm which used the null space extracted by the Rank Revealing LU factorization (RRLU). The RRLU provides accurate information about the rank and the numerical null space which make it a valuable tool in numerical linear algebra. The proposed novel method decreases the computational complexity approximately to the half compared with RRQR methods keeping the same performance. Computer simulations are also included to demonstrate the effectiveness of the proposed scheme.

Keywords: frequency hopping, channel model, time delay estimation, RRLU, RRQR, MUSIC, LS-ESPRIT

Procedia PDF Downloads 399

Authors: Abebe Mulugojam Negash, Yongbin Yu, Ekong Favour, Bekalu Nigus Dawit, Molla Woretaw Teshome, Aynalem Birtukan Yirga

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Breast cancer remains a significant health concern, necessitating advancements in diagnostic methodologies. Addressing this, our paper confronts the notable challenges in breast cancer classification, particularly the imbalance in datasets and the constraints in the accuracy and interpretability of prevailing deep learning approaches. We proposed an attention-based residual neural network (ResNet), which effectively combines the robust features of ResNet with an advanced attention mechanism. Enhanced through strategic data augmentation and positive weight adjustments, this approach specifically targets the issue of data imbalance. The proposed model is tested on the BreakHis dataset and achieved accuracies of 99.00%, 99.04%, 98.67%, and 98.08% in different magnifications (40X, 100X, 200X, and 400X), respectively. We evaluated the performance by using different evaluation metrics such as precision, recall, and F1-Score and made comparisons with other state-of-the-art methods. Our experiments demonstrate that the proposed model outperforms existing approaches, achieving higher accuracy in breast cancer classification.

Keywords: residual neural network, attention mechanism, positive weight, data augmentation

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Authors: Abdul Mufid

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This study aims to integrate hadith, astronomy, and sociology studies in studying the accelerated implementation of the unification of the Hijri calendar through a multidisciplinary approach. The Hijri calendar is compiled based on the astronomical phenomena of regular movements of the earth, moon, and sun. Meanwhile, for the implementation of worship, the Hijri calendar must refer to the provisions of Islamic law or fiqh. To set the Hijri calendar, agreement on the criteria for the visibility of the new moon (first crescent), date limits, and absolute authority is required. Agreement on visibility criteria requires a valid basis for astronomical studies. Agreement on territorial boundaries is necessary because our earth is round, and the new moon cannot be observed simultaneously. And the agreement of the authorities is also needed to resolve unavoidable differences, especially differences in the appearance of the new moon and differences in schools of thought. The research is based on astronomical data, the experiences of Indonesia and Islamic countries regarding the Hijri calendar, in-depth and focused interviews with various sources, as well as a review of hadith literature. The results of the study show that the implementation of the unification of the Hijri calendar through the three approaches above can be carried out and can be accelerated.

Keywords: calendar unification, new moon (hilal) visibility, multidisciplinary approach, the unity of the Muslims

Procedia PDF Downloads 68

Authors: Heng Yang, Tao Luo, Yakun Zhang, Kai Wang, Wei Qin, Liang Xie, Ye Yan, Erwei Yin

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Recent years have seen that audio-visual recognition has shown great potential in a strong noise environment. The existing method of audio-visual recognition has explored methods with ResNet and feature fusion. However, on the one hand, ResNet always occupies a large amount of memory resources, restricting the application in engineering. On the other hand, the feature merging also brings some interferences in a high noise environment. In order to solve the problems, we proposed an effective framework with bidirectional distillation. At first, in consideration of the good performance in extracting of features, we chose the light model, Efficientnet as our extractor of spatial features. Secondly, self-distillation was applied to learn more information from raw data. Finally, we proposed a bidirectional distillation in decision-level fusion. In more detail, our experimental results are based on a multi-model dataset from 24 volunteers. Eventually, the lipreading accuracy of our framework was increased by 2.3% compared with existing systems, and our framework made progress in audio-visual fusion in a high noise environment compared with the system of audio recognition without visual.

Keywords: lipreading, audio-visual, Efficientnet, distillation

Procedia PDF Downloads 118

Authors: Chitra Rajagopal, Indra Deo Kumar, Ila Chauhan, Ruchi Joshi, Binoy Bhargavan

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Reliability and safety are essential for the success of mission-critical and safety-critical defense systems. Humans are part of the entire life cycle of defense systems development and deployment. The majority of industrial accidents or disasters are attributed to human errors. Therefore, considerations of human performance and human reliability are critical in all complex systems, including defense systems. Defense systems are operating from the ground, naval and aerial platforms in diverse conditions impose unique physical and psychological challenges to the human operators. Some of the safety and mission-critical defense systems with human-machine interactions are fighter planes, submarines, warships, combat vehicles, aerial and naval platforms based missiles, etc. Human roles and responsibilities are also going through a transition due to the infusion of artificial intelligence and cyber technologies. Human operators, not accustomed to such challenges, are more likely to commit errors, which may lead to accidents or loss events. In such a scenario, it is imperative to understand the human factors in defense systems for better systems performance, safety, and cost-effectiveness. A case study using Task Analysis (TA) based methodology for assessment and reduction of human errors in the Air and Missile Defense System in the context of emerging technologies were presented. Action-oriented task analysis techniques such as Hierarchical Task Analysis (HTA) and Operator Action Event Tree (OAET) along with Critical Action and Decision Event Tree (CADET) for cognitive task analysis was used. Human factors assessment based on the task analysis helps in realizing safe and reliable defense systems. These techniques helped in the identification of human errors during different phases of Air and Missile Defence operations, leading to meet the requirement of a safe, reliable and cost-effective mission.

Keywords: defence systems, reliability, risk, safety

Procedia PDF Downloads 121

Authors: Hiba Hamdi, Thomas Corpetti, Laure Roupioz, Xavier Briottet

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Air temperatures are generally higher in cities than in their rural surroundings. The overheating of cities is a direct consequence of increasing urbanization, characterized by the artificial filling of soils, the release of anthropogenic heat, and the complexity of urban geometry. This phenomenon, referred to as urban heat island (UHI), is more prevalent during heat waves, which have increased in frequency and intensity in recent years. In the context of global warming and urban population growth, helping urban planners implement UHI mitigation and adaptation strategies is critical. In practice, the study of UHI requires air temperature information at the street canyon level, which is difficult to obtain. Many urban air temperature simulation models have been proposed (mostly based on physics or statistics), all of which require a variety of input parameters related to urban morphology, land use, material properties, or meteorological conditions. In this paper, we build and evaluate a neural network model based on Urban Weather Generator (UWG) model simulations and data from meteorological stations that simulate air temperature over Toulouse, France, on days favourable to UHI.

Keywords: air temperature, neural network model, urban heat island, urban weather generator

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Authors: Nathenal Thomas Lambamo

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Based on the fact that more than 85% of the labor force and 90% of the export earnings are taken by agriculture in Ethiopia and it can be said that it is the backbone of the overall socio-economic activities in the country. Among the cereal crops that the agriculture sector provides for the country, wheat is the third-ranking one preceding teff and maize. In the present day, wheat is in higher demand related to the expansion of industries that use them as the main ingredient for their products. The local supply of wheat for these companies covers only 35 to 40% and the rest 60 to 65% percent is imported on behalf of potential customers that exhaust the country’s foreign currency reserves. The above facts show that the need for this crop in the country is too high and in reverse, the productivity of the crop is very less because of these reasons. Wheat disease is the most devastating disease that contributes a lot to this unbalance in the demand and supply status of the crop. It reduces both the yield and quality of the crop by 27% on average and up to 37% when it is severe. This study aims to detect the most frequent and degrading wheat diseases, Septoria and Leaf rust, using the most efficiently used subset of machine learning technology, deep learning. As a state of the art, a deep learning class classification technique called Convolutional Neural Network (CNN) has been used to detect diseases and has an accuracy of 99.01% is achieved.

Keywords: septoria, leaf rust, deep learning, CNN

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Authors: María José Núñez-Ruiz, Luis Álvarez-González, Cristian Olivares-Rodriguez, Benjamin Lazo-Letelier

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This paper begins with some concept of formative assessment and the relationship with learning objective: contents objectives, processes objectives, and metacognitive objectives. Two methodologies are describes Evidence-Based teaching and Question Drive Instruction. To do formative assessments in larges classes a Classroom Response System (CRS) is needed. But most of CRS use only Multiple Choice Questions (MCQ), True/False question, or text entry; however, this is insufficient to formative assessment. To do that a new CRS, call FAMA was developed. FAMA support six types of questions: Choice, Order, Inline choice, Text entry, Associated, and Slider. An experiment participated in 149 students from four engineering careers. For results, Kendall's Range Correlation Analysis and descriptive analysis was done. In conclusion, there is a strong relation between contents question, process questions (ask in formative assessment without a score) and metacognitive questions, asked in summative assessment. As future work, the lecturer can do personalized teaching, because knows the behavior of all students in each formative assessment

Keywords: Python language, formative assessment, classroom response systems, evidence-Based teaching, question drive instruction

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Authors: Eva Laryea, Clement Yeboah Authors

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A pretest-posttest within subjects, experimental design was employed to examine the effects of a computerized basic statistics learning game on achievement and statistics-related anxiety of students enrolled in introductory graduate statistics course. Participants (N = 34) were graduate students in a variety of programs at state-funded research university in the Southeast United States. We analyzed pre-test posttest differences using paired samples t-tests for achievement and for statistics anxiety. The results of the t-test for knowledge in statistics were found to be statistically significant indicating significant mean gains for statistical knowledge as a function of the game-based intervention. Likewise, the results of the t-test for statistics-related anxiety were also statistically significant indicating a decrease in anxiety from pretest to posttest. The implications of the present study are significant for both teachers and students. For teachers, using computer games developed by the researchers can help to create a more dynamic and engaging classroom environment, as well as improve student learning outcomes. For students, playing these educational games can help to develop important skills such as problem solving, critical thinking, and collaboration. Students can develop interest in the subject matter and spend quality time to learn the course as they play the game without knowing that they are even learning the presupposed hard course. The future directions of the present study are promising, as technology continues to advance and become more widely available. Some potential future developments include the integration of virtual and augmented reality into educational games, the use of machine learning and artificial intelligence to create personalized learning experiences, and the development of new and innovative game-based assessment tools. It is also important to consider the ethical implications of computer game-based pedagogy, such as the potential for games to perpetuate harmful stereotypes and biases. As the field continues to evolve, it will be crucial to address these issues and work towards creating inclusive and equitable learning experiences for all students. This study has the potential to revolutionize the way basic statistics graduate students learn and offers exciting opportunities for future development and research. It is an important area of inquiry for educators, researchers, and policymakers, and will continue to be a dynamic and rapidly evolving field for years to come.

Keywords: pretest-posttest within subjects, experimental design, achievement, statistics-related anxiety

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Authors: Shubham Gogri, Lucia Florescu

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Medical diagnosis and radiotherapy treatment planning using Computed Tomography (CT) rely on the quantitative accuracy and quality of the CT images. At the same time, requirements for CT imaging include reducing the radiation dose exposure to patients and minimizing scanning time. A solution to this is the sparse-view CT technique, based on a reduced number of projection views. This, however, introduces a new problem— the incomplete projection data results in lower quality of the reconstructed images. To tackle this issue, deep learning methods have been applied to enhance the quality of the sparse-view CT images. A first approach involved employing Mir-Net, a dedicated deep neural network designed for image enhancement. This showed promise, utilizing an intricate architecture comprising encoder and decoder networks, along with the incorporation of the Charbonnier Loss. However, this approach was computationally demanding. Subsequently, a specialized Generative Adversarial Network (GAN) architecture, rooted in the Pix2Pix framework, was implemented. This GAN framework involves a U-Net-based Generator and a Discriminator based on Convolutional Neural Networks. To bolster the GAN's performance, both Charbonnier and Wasserstein loss functions were introduced, collectively focusing on capturing minute details while ensuring training stability. The integration of the perceptual loss, calculated based on feature vectors extracted from the VGG16 network pretrained on the ImageNet dataset, further enhanced the network's ability to synthesize relevant images. A series of comprehensive experiments with clinical CT data were conducted, exploring various GAN loss functions, including Wasserstein, Charbonnier, and perceptual loss. The outcomes demonstrated significant image quality improvements, confirmed through pertinent metrics such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) between the corrected images and the ground truth. Furthermore, learning curves and qualitative comparisons added evidence of the enhanced image quality and the network's increased stability, while preserving pixel value intensity. The experiments underscored the potential of deep learning frameworks in enhancing the visual interpretation of CT scans, achieving outcomes with SSIM values close to one and PSNR values reaching up to 76.

Keywords: generative adversarial networks, sparse view computed tomography, CT image correction, Mir-Net

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Authors: Ibrahim Khan, Waqas Khalid

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The Healthcare sector is known to consume a higher proportion of total energy consumption in the HVAC market owing to an excessive cooling and heating requirement in maintaining human thermal comfort in indoor conditions, catering to patients undergoing treatment in hospital wards, rooms, and intensive care units. The indoor thermal comfort conditions in selected hospitals of Islamabad, Pakistan, were measured on a real-time basis with the collection of first-hand experimental data using calibrated sensors measuring Ambient Temperature, Wet Bulb Globe Temperature, Relative Humidity, Air Velocity, Light Intensity and CO2 levels. The Experimental data recorded was analyzed in conjunction with the Thermal Comfort Questionnaire Surveys, where the participants, including patients, doctors, nurses, and hospital staff, were assessed based on their thermal sensation, acceptability, preference, and comfort responses. The Recorded Dataset, including experimental and survey-based responses, was further analyzed in the development of a correlation between operative temperature, operative relative humidity, and other measured operative parameters with the predicted mean vote and adaptive predicted mean vote, with the adaptive temperature and adaptive relative humidity estimated using the seasonal data set gathered for both summer – hot and dry, and hot and humid as well as winter – cold and dry, and cold and humid climate conditions. The Machine Learning Logistic Regression Algorithm was incorporated to train the operative experimental data parameters and develop a correlation between patient sensations and the thermal environmental parameters for which a new ML-based adaptive thermal comfort model was proposed and developed in our study. Finally, the accuracy of our model was determined using the K-fold cross-validation.

Keywords: predicted mean vote, thermal comfort, energy management, logistic regression, machine learning

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Authors: Shyamlal Kumawat

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Cloud computing is shifting the approach IT capital are utilized. Cloud computing dynamically delivers convenient, on-demand access to shared pools of software resources, platform and hardware as a service through internet. The cloud computing model—made promising by sophisticated automation, provisioning and virtualization technologies. Users want the ability to access these services including infrastructure resources, how and when they choose. To accommodate this shift in the consumption model technology has to deal with the security, compatibility and trust issues associated with delivering that convenience to application business owners, developers and users. Absent of these issues, trust has attracted extensive attention in Cloud computing as a solution to enhance the security. This paper proposes a trusted computing technology through Standard Resource parameter Based Trust Model in Cloud Computing to select the appropriate cloud service providers. The direct trust of cloud entities is computed on basis of the interaction evidences in past and sustained on its present performances. Various SLA parameters between consumer and provider are considered in trust computation and compliance process. The simulations are performed using CloudSim framework and experimental results show that the proposed model is effective and extensible.

Keywords: cloud, Iaas, Saas, Paas

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Authors: Fernanda Miranda da Cruz

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This paper aims to systematize, descriptively and analytically, the relations between language, body and material world explored in a specific empirical context: everyday co-presence interactions between children diagnosed with Autistic Spectrum Disease ASD and various interlocutors. We will work based on 20 hours of an audiovisual corpus in Brazilian Portuguese language. This analysis focuses on 1) the analysis of daily interactions that have the presence/participation of subjects with a diagnosis of ASD based on an embodied interaction perspective; 2) the study of the status and role of gestures, body and material world in the construction and constitution of human interaction and its relation with linguistic-cognitive processes and Autistic Spectrum Disorders; 3) to highlight questions related to the field of videoanalysis, such as: procedures for recording interactions in complex environments (involving many participants, use of objects and body movement); the construction of audiovisual corpora for linguistic-interaction research; the invitation to a visual analytical mentality of human social interactions involving not only the verbal aspects that constitute it, but also the physical space, the body and the material world.

Keywords: autism spectrum disease, multimodality, social interaction, non-verbal interactions

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Authors: L. Wei Sheng, M. T. Noor Syazwanee, C. J. Carolyna, M. Amiruddin, M. Pauziah

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This paper exhibits the alternatives towards active suspension systems revised based on the classical passive suspension system to improve comfort and handling performance. An active Magneto rheological (MR) suspension system is proposed as to explore the active based suspension system to enhance performance given its freedom to independently specify the characteristics of load carrying, handling, and ride quality. Malaysian quarter car with two degrees of freedom (2DOF) system is designed and constructed to simulate the actions of an active vehicle suspension system. The structure of a conventional twin-tube shock absorber is modified both internally and externally to comprehend with the active suspension system. The shock absorber peripheral structure is altered to enable the assembling and disassembling of the damper through a non-permanent joint whereby the stress analysis of the designed joint is simulated using Finite Element Analysis. Simulation on the internal part where an electrified copper coil of 24AWG is winded is done using Finite Element Method Magnetics to measure the magnetic flux density inside the MR damper. The primary purpose of this approach is to reduce the vibration transmitted from the effects of road surface irregularities while maintaining solid manoeuvrability. The aim of this research is to develop an intelligent control system of a consecutive damping automotive suspension system. The ride quality is improved by means of the reduction of the vertical body acceleration caused by the car body when it experiences disturbances from speed bump and random road roughness. Findings from this research are expected to enhance the quality of ride which in return can prevent the deteriorating effect of vibration on the vehicle condition as well as the passengers’ well-being.

Keywords: active suspension, FEA, magneto rheological damper, Malaysian quarter car model, vibration control

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Authors: Ismail Seçer

Abstract:

The purpose of this study is to investigate the effects of anxiety sensitivity in adolescents on anxiety disorder and childhood depression. Mood disorders and anxiety disorders in children and adolescents can be given examples of important research topics in recent years. The participants of the study consist of 670 students in Erzurum and Erzincan city centers. The participants of the study were 670 secondary and high school students studying in city centers of Erzurum and Erzincan. The participants were chosen based on convenience sampling. The participants were between the ages of 13 and 18 (M=15.7, Ss= 1.35) and 355 were male and 315 were female. The data were collected through Anxiety Sensitivity Index and Anxiety and Depression Index for Children and Adolescents. For data analysis, Correlation analysis and Structural Equation Model were used. In this study, correlational descriptive survey was used. This model enables the researcher to make predictions related to different variables based on the information obtained from one or more variables. Therefore, the purpose is to make predictions considering anxiety disorder and childhood depression based on anxiety sensitivity. For this purpose, latent variable and structural equation model was used. Structural equation model is an analysis method which enables the identification of direct and indirect effects by determining the relationship between observable and latent variables and testing their effects on a single model. CFI, RMR, RMSEA and SRMR, which are commonly accepted fit indices in structural equation model, were used. The results revealed that anxiety sensitivity impacts anxiety disorder and childhood depression through direct and indirect effects in a positive way. The results are discussed in line with the relevant literature. This finding can be considered that anxiety sensitivity can be a significant risk source in terms of children's and adolescents’ anxiety disorder experience. This finding is consistent with relevant research highlighting that in case the anxiety sensitivity increases then the obsessive compulsive disorder and panic attack increase too. The adolescents’ experience of anxiety can be attributed to anxiety sensitivity.

Keywords: anxiety sensitivity, anxiety, depression, structural equation

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Authors: Mohamed Elhakeem, A. N. Thanos Papanicolaou, Christopher Wilson, Yi-Jia Chang

Abstract:

In this study, a physically-based, modelling framework was developed to predict saturated hydraulic conductivity (KSAT) dynamics in the Clear Creek Watershed (CCW), Iowa. The modelling framework integrated selected pedotransfer functions and watershed models with geospatial tools. A number of pedotransfer functions and agricultural watershed models were examined to select the appropriate models that represent the study site conditions. Models selection was based on statistical measures of the models’ errors compared to the KSAT field measurements conducted in the CCW under different soil, climate and land use conditions. The study has shown that the predictions of the combined pedotransfer function of Rosetta and the Water Erosion Prediction Project (WEPP) provided the best agreement to the measured KSAT values in the CCW compared to the other tested models. Therefore, Rosetta and WEPP were integrated with the Geographic Information System (GIS) tools for visualization of the data in forms of geospatial maps and prediction of KSAT variability in CCW due to the seasonal changes in climate and land use activities.

Keywords: saturated hydraulic conductivity, pedotransfer functions, watershed models, geospatial tools

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Authors: Ofuan James Ilaboya, Okhae J. Ibhadode

Abstract:

The objective of this paper is to theoretically examine the truism of the “true and fair view” in the context of financial reporting. The paper examines the concepts such as true, fair, true and fair view, problems of true and fair view, the origin/history of true and fair view, review of attributes and key issues relating to true and fair view. The methodological approach adopted in this paper is library-based research, focusing on the review of relevant and related extant literature. The findings based on the review of relevant and related literature is suggestive of the fact that the true and fair concept in financial reporting environment is contentious. The study concludes that given the circumstances as chronicled on this paper, it is evident that the truism of the true and fair view of the auditor’s opinion is under serious threat. The way forward may be for the auditor to certify the accuracy and the correctness of the financial statement. While this position being canvassed here may help to substantially bridge the age-long expectation gap, it may as well require an upward review of the current audit fee structure in order to be able to operationalize the onerous task of certifying the accuracy and correctness of the financial statement. This position is contentious and will require a robust consideration which is not within the purview of the present review.

Keywords: fiduciary duty, financial statement, true and correct, true and fair

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Authors: B. Safi, B. Amrane, M. Saidi

Abstract:

The main purpose of this study is to evaluate the reuse of refractory brick wastes (RBW) as a supplementary cementitious materials (by a total replacement of silica fume) to produce a high performance fiber-reinforced concrete (HPFRC). This work presents an experimental study on the formulation and physico-mechanical characterization of ultra high performance fiber reinforced concretes based on three types of refractory brick wastes. These have been retrieved from the manufacturing unit of float glass MFG (Mediterranean Float Glass) after their use in the oven basin (ie d. they are considered waste unit). Three compositions of concrete (HPFRC) were established based on three types of refractory brick wastes (finely crushed), with the dosage of each type of bricks is kept constant, similar the dosage of silica fume used for the control concrete. While all the other components and the water/binder ratio are maintained constant with the same quantity of the superplasticizer. The performance of HPFRC, were evaluated by determining the essential characteristics of fresh and hardened concrete.

Keywords: refractory bricks, concrete, fiber, fluidity, compressive strength, tensile strength

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Authors: Salim H. Al Salmani, Kevin Tansey, Mohammed S. Ozigis

Abstract:

The study of the growth of built-up areas and settlement expansion is a major exercise that city managers seek to undertake to establish previous and current developmental trends. This is to ensure that there is an equal match of settlement expansion needs to the appropriate levels of services and infrastructure required. This research aims at demonstrating the potential of satellite image processing technique, harnessing the utility of single feature probability-object based image analysis technique in assessing the urban growth dynamics of the Muscat Governorate in Oman for the period 1990, 2002 and 2013. This need is fueled by the continuous expansion of the Muscat Governorate beyond predicted levels of infrastructural provision. Landsat Images of the years 1990, 2002 and 2013 were downloaded and preprocessed to forestall appropriate radiometric and geometric standards. A novel approach of probability filtering of the target feature segment was implemented to derive the spatial extent of the final Built-Up Area of the Muscat governorate for the three years period. This however proved to be a useful technique as high accuracy assessment results of 55%, 70%, and 71% were recorded for the Urban Landcover of 1990, 2002 and 2013 respectively. Furthermore, the Normalized Differential Built – Up Index for the various images were derived and used to consolidate the results of the SFP-OBIA through a linear regression model and visual comparison. The result obtained showed various hotspots where urbanization have sporadically taken place. Specifically, settlement in the districts (Wilayat) of AL-Amarat, Muscat, and Qurayyat experienced tremendous change between 1990 and 2002, while the districts (Wilayat) of AL-Seeb, Bawshar, and Muttrah experienced more sporadic changes between 2002 and 2013.

Keywords: urban growth, single feature probability, object based image analysis, landcover change

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Authors: Ghulam Mustafa Peerzada, Shagufta Rashid, Nadeem Bashir

Abstract:

These the influence of initial reagent concentrations on the Belousov-Zhabotinsky (BZ) system with Mn2+/Mn3+ as redox catalyst, inorganic bromate as oxidant and pyrogallol as organic substrate was studied. The reactions were monitored by potentiometery in oxidation reduction potential (ORP) mode. The aforesaid reagents were mixed with varying concentrations to evolve the optimal concentrations at which the reaction system exhibited better oscillations. The various oscillatory parameters such as induction period (tin), time period (tp), frequency (v), amplitude (A) and number of oscillations (n) were derived and the dependence of concentration of the reacting species on these oscillatory parameters was interpreted on the basis of the Field-Koros-Noyes mechanism. Ferroin based BZ system with pyrogallol as organic substrate was optimized under CSTR condition at temperature of 30±0.1oC Effect of molecules like monomer and polymer as additives to the system was checked and their interaction with the system was also studied. It has been observed that the monomer affects the time period, while the polymer has its effect on the amplitude of oscillations because of monomer’s interaction with the bromine and polymer’s with that of the Ferroin.

Keywords: Belousov Zhabotinsky reaction, oscillatory parameters, polymer, pyrogallol

Procedia PDF Downloads 297