Search results for: GPS bsed based Robotic library

Authors: Andrii Biloshchytskyi, Serik Omirbayev, Alexandr Neftissov, Sapar Toxanov, Svitlana Biloshchytska, Adil Faizullin

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Kazakhstan has adopted a carbon neutrality strategy until 2060. In accordance with this strategy, it is necessary to introduce various tools to maintain the environmental safety of the environment. The use of IoT, in combination with the characteristics and requirements of Kazakhstan's environmental legislation, makes it possible to develop a modern environmental monitoring system. The article proposes a solution for developing an example of an automated system for the continuous collection of data on the concentration of pollutants in the atmosphere based on an open architecture. The Audino-based device acts as a microcontroller. It should be noted that the transmission of measured values is carried out via an open wireless communication protocol. The architecture of the system, which was used to build a prototype based on sensors, an Arduino microcontroller, and a wireless data transmission module, is presented. The selection of elementary components may change depending on the requirements of the system; the introduction of new units is limited by the number of ports. The openness of solutions allows you to change the configuration depending on the conditions. The advantages of the solutions are openness, low cost, versatility and mobility. However, there is no comparison of the working processes of the proposed solution with traditional ones.

Keywords: environmental monitoring, greenhouse gases emissions, environmental pollution, Industry 4.0, IoT, microcontroller, automated monitoring system.

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Authors: Jennie Long, Marjorie Bock

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Although the professional literature related to Autism Spectrum Disorder (ASD) has focused on successful interventions and strategies, there is a lack of documentation regarding which of these methods and supports are most foundational and essential for classroom use. Specifically, literature does not define the core foundational interventions and strategies that would be elemental for educators to use with students with an ASD diagnosis. From the increase in prevalence of autism spectrum disorders, to the challenge students with ASD pose in classrooms, to the requirement to implement evidence-based practice, rises an enormous challenge in the field of education. Foundational interventions should be in place the first day the student enters the classroom. The nine interventions are foundational in nature and because of the dramatic increase in prevalence there is currently a need for classroom programs to provide the foundation of basic educational skills as well as the specialty skills specific to the area of ASD utilizing the most current research. This article presents nine evidence-based intervention categories for implementation with students on the spectrum.

Keywords: autism spectrum disorder, classroom, evidence-based, foundational

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Authors: Zhu-Qing Jia, Tao Lin, Tong Zhou

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The recognition method of Optical Character Recognition has been expensively utilized, while it is rare to be employed specifically in recognition of electronic components. This paper suggests a high-effective algorithm on appearance identification of integrated circuit components based on the existing methods of character recognition, and analyze the pros and cons.

Keywords: optical character recognition, fuzzy page identification, mutual correlation matrix, confidence self-adaptation

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Authors: Flavio O. Torres, Maria J. Castilla, Rodrigo A. Augsburger, Pedro I. Cachana, Katherine S. Reyes

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In this paper, we present a scene-based nonuniformity correction method using a modified recursive least square algorithm with a feedback system on the updates. The feedback is designed to remove impulsive noise contamination images produced by a recursive least square algorithm by measuring the output of the proposed algorithm. The key advantage of the method is based on its capacity to estimate detectors parameters and then compensate for impulsive noise contamination image in a frame by frame basics. We define the algorithm and present several experimental results to demonstrate the efficacy of the proposed method in comparison to several previously published recursive least square-based methods. We show that the proposed method removes impulsive noise contamination image.

Keywords: infrared focal plane arrays, infrared imaging, least mean square, nonuniformity correction

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Authors: Xuyang Song, Jun Yin

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The smart card has been an extremely universal tool in public transit. It collects a large amount of data on buses, urban railway transit, and ferries and provides possibilities for passenger profiling. This paper combines offline analysis of passenger profiling and real-time prediction to propose a method that can accurately predict the destination station in real-time when passengers tag on. Firstly, this article constructs a static database of user travel characteristics after identifying passenger travel patterns based on the Density-Based Spatial Clustering of Applications with Noise (DBSCAN). The dual travel passenger habits are identified: OD travel habits and D station travel habits. Then a rapid real-time prediction algorithm based on Transit Passenger Profiling is proposed, which can predict the destination of in-board passengers. This article combines offline learning with online prediction, providing a technical foundation for real-time passenger flow prediction, monitoring and simulation, and short-term passenger behavior and demand prediction. This technology facilitates the efficient and real-time acquisition of passengers' travel destinations and demand. The last, an actual case was simulated and demonstrated feasibility and efficiency.

Keywords: travel behavior, destination prediction, public transit, passenger profiling

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Authors: Eduwin Eko Franjaya, Yesi Hendriani Supartoyo

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Integrated farming with LEISA concept as one of the systems or sustainable farming techniques in agriculture has provided opportunities to increase farmers' income. This system also has a positive impact on the environment. However, the development of integrated farming is still on a small scale/site scale. Development on a larger scale is necessary considering to the number of potential resources in the village that can be integrated each other. The aim of this research is to develop an integrated farming landscape on small scale that has been done in previous study, into the village scale. The method used in this study follows the rules of scientific planning in landscape architecture. The initial phase begins with an inventory of the existing condition of the village, by conducting a survey. The second stage is analysis of potential and constraints in the village based on the results of a survey that has been done before. The next stage is concept-making that consists of basic concept, design concept, and development concept. The basic concept is integrated farming based on LEISA. The design concept is based on commodities that are developed in the village. The development concept consists of space concept, circulation concept, the concept of vegetation and commodities, and the concept of the production system. The last stage is planning process which produces Site Plan based on LEISA on village scale. Site Plan is also the end product of this research. The results of this research are expected to increase the income and welfare of the farmers in the village, and can be develop into a tourism area of integrated farming.

Keywords: integrated farming, LEISA, site plan, sustainable agriculture

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Authors: Ansari Mohammad Reza, Hiroko Ono

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In this study, we investigated how much of the urban facilities are fairly distributing in the city of Kabul based on the factor of population. To find the answer to this question we simulated a fair model for the distribution of investigated facilities in the city which is proposed based on the consideration of two factors; the number of users for each facility and the average distance of reach of each facility. Then the model was evaluated to make sure about its efficiency. And finally, the two—the existing pattern and the simulation model—were compared to find the degree of bias in the existing pattern of distribution of facilities in the city. The result of the study clearly clarified that the facilities are not fairly distributed in Kabul city based on the factor of population. Our analysis also revealed that the education services and the parks are the most and the worst fair distributed facilities in this regard.

Keywords: Afghanistan, ArcGIS Software, Kabul City, fair distribution, urban facilities

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Authors: Cherifi Mehdi, Lahdir Mourad, Ameur Soltane

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Image compression is used to reduce the number of bits required to represent an image. The Meteosat Second Generation satellite (MSG) allows the acquisition of 12 image files every 15 minutes. Which results a large databases sizes. The transform selected in the images compression should contribute to reduce the data representing the images. The Radon transform retrieves the Radon points that represent the sum of the pixels in a given angle for each direction. Linear predictive coding (LPC) with filtering provides a good decorrelation of Radon points using a Predictor constitute by the Symmetric Nearest Neighbor filter (SNN) coefficients, which result losses during decompression. Finally, Run Length Coding (RLC) gives us a high and fixed compression ratio regardless of the input image. In this paper, a novel image compression method based on the Radon transform and linear predictive coding (LPC) for MSG images is proposed. MSG image compression based on the Radon transform and the LPC provides a good compromise between compression and quality of reconstruction. A comparison of our method with other whose two based on DCT and one on DWT bi-orthogonal filtering is evaluated to show the power of the Radon transform in its resistibility against the quantization noise and to evaluate the performance of our method. Evaluation criteria like PSNR and the compression ratio allows showing the efficiency of our method of compression.

Keywords: image compression, radon transform, linear predictive coding (LPC), run lengthcoding (RLC), meteosat second generation (MSG)

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Authors: Musa H. Arslan, Murat Ceylan, Tayfun Koyuncu

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In this study, an artificial intelligence-based (ANN based) analytical method has been developed for analyzing earthquake performances of the reinforced concrete (RC) buildings. 66 RC buildings with four to ten storeys were subjected to performance analysis according to the parameters which are the existing material, loading and geometrical characteristics of the buildings. The selected parameters have been thought to be effective on the performance of RC buildings. In the performance analyses stage of the study, level of performance possible to be shown by these buildings in case of an earthquake was determined on the basis of the 4-grade performance levels specified in Turkish Earthquake Code- 2007 (TEC-2007). After obtaining the 4-grade performance level, selected 23 parameters of each building have been matched with the performance level. In this stage, ANN-based fast evaluation algorithm mentioned above made an economic and rapid evaluation of four to ten storey RC buildings. According to the study, the prediction accuracy of ANN has been found about 74%.

Keywords: artificial intelligence, earthquake, performance, reinforced concrete

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Authors: Navaneeth Krishnan, Chandan N. Bhagwat, Aparajit P. Utpat

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Cloud Computing provides us a means to upload data and use applications over the internet. As the number of devices connecting to the cloud grows, there is undue pressure on the cloud infrastructure. Fog computing or Network Based Computing or Edge Computing allows to move a part of the processing in the cloud to the network devices present along the node to the cloud. Therefore the nodes connected to the cloud have a better response time. This paper proposes a method of moving the computation from the cloud to the network by introducing an android like appstore on the networking devices.

Keywords: cloud computing, fog computing, network devices, appstore

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Authors: Joel Ballesteros, Harriet Jane Caleja, Florian Del Mundo, Cherrie Pascual

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Diffraction-based sensing was utilized in the quantification of human ferritin in blood serum to provide an alternative to label-based immunoassays currently used in clinical diagnostics and researches. The diffraction intensity was measured by the diffractive optics technology or dotLab™ system. Two methods were evaluated in this study: direct immunoassay and direct sandwich immunoassay. In the direct immunoassay, human ferritin was captured by human ferritin antibodies immobilized on an avidin-coated sensor while the direct sandwich immunoassay had an additional step for the binding of a detector human ferritin antibody on the analyte complex. Both methods were repeatable with coefficient of variation values below 15%. The direct sandwich immunoassay had a linear response from 10 to 500 ng/mL which is wider than the 100-500 ng/mL of the direct immunoassay. The direct sandwich immunoassay also has a higher calibration sensitivity with value 0.002 Diffractive Intensity (ng mL-1)-1) compared to the 0.004 Diffractive Intensity (ng mL-1)-1 of the direct immunoassay. The limit of detection and limit of quantification values of the direct immunoassay were found to be 29 ng/mL and 98 ng/mL, respectively, while the direct sandwich immunoassay has a limit of detection (LOD) of 2.5 ng/mL and a limit of quantification (LOQ) of 8.2 ng/mL. In terms of accuracy, the direct immunoassay had a percent recovery of 88.8-93.0% in PBS while the direct sandwich immunoassay had 94.1 to 97.2%. Based on the results, the direct sandwich immunoassay is a better diffraction-based immunoassay in terms of accuracy, LOD, LOQ, linear range, and sensitivity. The direct sandwich immunoassay was utilized in the determination of human ferritin in blood serum and the results are validated by Chemiluminescent Magnetic Immunoassay (CMIA). The calculated Pearson correlation coefficient was 0.995 and the p-values of the paired-sample t-test were less than 0.5 which show that the results of the direct sandwich immunoassay was comparable to that of CMIA and could be utilized as an alternative analytical method.

Keywords: biosensor, diffraction, ferritin, immunoassay

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Authors: Andrey Khalov

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The rapid proliferation of unstructured data in IT infrastructure management demands innovative approaches for extracting actionable knowledge. This paper presents a framework for ontology-based knowledge extraction that combines relational graph neural networks (R-GNN) with large language models (LLMs). The proposed method leverages the DOLCE framework as the foundational ontology, extending it with concepts from ITSMO for domain-specific applications in IT service management and outsourcing. A key component of this research is the use of transformer-based models, such as DeBERTa-v3-large, for automatic entity and relationship extraction from unstructured texts. Furthermore, the paper explores how transfer learning techniques can be applied to fine-tune large language models (LLaMA) for using to generate synthetic datasets to improve precision in BERT-based entity recognition and ontology alignment. The resulting IT Ontology (ITO) serves as a comprehensive knowledge base that integrates domain-specific insights from ITIL processes, enabling more efficient decision-making. Experimental results demonstrate significant improvements in knowledge extraction and relationship mapping, offering a cutting-edge solution for enhancing cognitive computing in IT service environments.

Keywords: ontology mapping, R-GNN, knowledge extraction, large language models, NER, knowlege graph

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Authors: Claire Stafford, John Lewis, Ashley Stripling

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The aim of this study is to examine the relationship between both the independent effects and intersection between COVID-19 and the Black Lives Matter (BLM) movement simultaneously to investigate how the two events have coincided with impacting race-based traumatic stress in Black Americans. Four groups will be surveyed: Black Americans who participated in BLM-related activism, Black Americans who did not participate in BLM-related activism, White Americans who participated in BLM-related activism, and White Americans who did not participate in BLM-related activism. Participants are between the ages of 30 and 50. All participants will be administered a Brief Trauma Questionnaire with an additional question asking whether or not they have ever tested positive for COVID-19. Based on prior findings, it is expected that Black Americans will have significantly higher levels of COVID-19 contraction, with Black Americans who participated in BLM-related activism having the highest levels of contractions. Additionally, Black Americans who participated in BLM-related activism will likely have the highest self-reported rates of traumatic experiences due to the compounding effect of both the pandemic and the BLM movement. With the development of the COVID-19 pandemic, stark racial disparities between Black and White Americans have become more defined. Compared to White Americans, Black Americans have more COVID-19-related cases and hospitalizations. Researchers must investigate and attempt to mitigate these disparities while simultaneously critically questioning the structure of our national health care system and how it serves our marginalized communities. Further, a critical gaze must be directed at the geopolitical climate of the United States in order to holistically look at how both the COVID-19 pandemic and the Black Lives Matter (BLM) movement have interacted and impacted race-based stress and trauma in African Americans.

Keywords: COVID-19, black lives matter movement, race-based traumatic stress, activism

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Authors: S. Wietrzychowski

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The following review has identified specific programs, as well as the elements of these programs, that have been shown to be most effective in preventing suicide in schools. Suicide is an issue that affects many students each year. Although this is a prominent issue, there are few prevention programs used within schools. The primary objective of most prevention programs is to reduce risk factors such as depression and hopelessness, and increase protective factors like support systems and help-seeking behaviors. Most programs include a gatekeeper training model, education component, peer support group, and/or counseling/treatment. Research shows that some of these programs, like the Signs of Suicide and Youth Aware of Mental Health Programme, are effective in reducing suicide behaviors and increasing protective factors. These programs have been implemented in many countries across the world and have shown promising results. Since schools can provide easy access to adolescents, implement education programs, and train staff members and students how to identify and to report suicide behaviors, school-based programs seem to be the best way to prevent suicide among adolescents. Early intervention may be an effective way to prevent suicide. Although, since early intervention is not always an option, school-based programs in high schools have also been shown to decrease suicide attempts by up to 50%. As a result of this presentation, participants will be able to 1.) list at least 2 evidence-based suicide prevention programs, 2.) identify at least 3 factors which protect against suicide, and 3.) describe at least 3 risk factors for suicide.

Keywords: school, suicide, prevention, programs

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Authors: Manju Pandey, Nilay Khare, S. C. Shrivastava

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This paper is the final in a series, which has defined two new classes of aggregation operators for triangular and trapezoidal fuzzy numbers based on the geometrical characteristics of their fuzzy membership functions. In the present paper, a new aggregation operator for trapezoidal fuzzy numbers has been defined. The new operator is based on the geometric mean of the membership lines to the left and right of the maximum possibility interval. The operator is defined and the analytical relationships have been derived. Computation of the aggregate is demonstrated with a numerical example. Corresponding arithmetic and geometric aggregates as well as results from the recent work of the authors on TrFN aggregates have also been computed.

Keywords: LR fuzzy number, interval fuzzy number, triangular fuzzy number, trapezoidal fuzzy number, apex angle, left apex angle, right apex angle, aggregation operator, arithmetic and geometric mean

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Authors: S. Goel

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In the current scenario, education should be realistic and nature-friendly. The earlier definition of education was restricted to the holistic development of the child which help them to increase their capacity and helps in social upliftment. But such definition gives a more individualistic aim of education. Due to that individualistic aim, we have become disconnected from nature. So, a school should be a place which provides students with an area to explore. They should get practical learning or learning from nature which is also propounded by Rousseau in the mid-eighteenth century. Integrating Sustainable development goals in the school curriculum will make it possible to connect the nature with the lives of the children in the classroom. Then, students will be more aware and sensitive towards their social and natural surroundings. The research attempts to examine the efficiency of project-based learning in mathematics to create awareness around sustainable development goals. The major finding of the research was that students are less aware of sustainable development goals, but when given time and an appropriate learning environment, students can be made aware of these goals. In this research, project-based learning was used to make students aware of sustainable development goals. Students were given pre test and post test which helped in analyzing their performance. After the intervention, post test result showed that mathematics projects can create an awareness of sustainable development goals.

Keywords: holistic development, natural learning, project based learning, sustainable development goals

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Authors: Qihang Zeng, Wei Xu, Ying Shen, Changyuan Yu

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In this paper, a highly sensitive fiber-optic curvature sensor based on four mode fiber (FMF) is presented and investigated. The proposed sensing structure is constructed by fusing a section of FMF into two standard single mode fibers (SMFs) concatenated with two no core fiber (NCF), i.e., SMF-NCF-FMF-NCF-SMF structure is fabricated. The length of the NCF is very short about 1 millimeter acting as exciting/recoupling the light from/into the core of the SMF, while the FMF is with 3 centimeters long supporting four eigenmodes including LP₀₁, LP₁₁, LP₂₁ and LP₀₂. High core modes in FMF can be effectively stimulated owing to mismatched mode field distribution and the mainly sensing principle is based on modal interferometer spectrum analysis. Different curvatures induce different strains on the FMF such that affecting the modal excitation, resulting spectrum shifts. One can get the curvature value by tracking the wavelength shifting. Experiments have been done to address the sensing performance, which is about 7.8 nm/m⁻¹ within a range of 1.90 m⁻¹~3.18 m⁻¹.

Keywords: curvature, four mode fiber, highly sensitive, modal interferometer

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Authors: Restituto I. Rodelas

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The higher education has adopted the outcomes-based education from K-12. In this approach, the teacher uses any teaching and learning strategies that enable the students to achieve the learning outcomes. The students may be required to exert more effort and figure things out on their own. Hence, outcomes-based students are assumed to be more responsible and more capable of applying the knowledge learned. Another approach that the higher education in the Philippines is starting to adopt from other countries is blended learning. This combination of classroom and fully online instruction and learning is expected to be more effective. Participating in the online sessions, however, is entirely up to the students. Thus, the effect of blended learning on the performance of students in Statistics may be mediated by outcomes-based education. If there is a significant positive mediating effect, then blended learning can be optimized by integrating outcomes-based education. In this study, the sample will consist of four blended learning Statistics classes at Jose Rizal University in the second semester of AY 2015–2016. Two of these classes will be assigned randomly to the experimental group that will be handled using outcomes-based education. The two classes in the control group will be handled using the traditional lecture approach. Prior to the discussion of the first topic, a pre-test will be administered. The same test will be given as posttest after the last topic is covered. In order to establish equality of the groups’ initial knowledge, single factor ANOVA of the pretest scores will be performed. Single factor ANOVA of the posttest-pretest score differences will also be conducted to compare the performance of the experimental and control groups. When a significant difference is obtained in any of these ANOVAs, post hoc analysis will be done using Tukey's honestly significant difference test (HSD). Mediating effect will be evaluated using correlation and regression analyses. The groups’ initial knowledge are equal when the result of pretest scores ANOVA is not significant. If the result of score differences ANOVA is significant and the post hoc test indicates that the classes in the experimental group have significantly different scores from those in the control group, then outcomes-based education has a positive effect. Let blended learning be the independent variable (IV), outcomes-based education be the mediating variable (MV), and score difference be the dependent variable (DV). There is mediating effect when the following requirements are satisfied: significant correlation of IV to DV, significant correlation of IV to MV, significant relationship of MV to DV when both IV and MV are predictors in a regression model, and the absolute value of the coefficient of IV as sole predictor is larger than that when both IV and MV are predictors. With a positive mediating effect of outcomes-base education on the effect of blended learning on student performance, it will be recommended to integrate outcomes-based education into blended learning. This will yield the best learning results.

Keywords: outcome-based teaching, blended learning, face-to-face, student-centered

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Authors: Aylin Sahin, Yasemin Kilic, Abdulkadir Sari, Burcu Duymaz, Mustafa Kara

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Foam glass is an innovative material which composed of glass and carbon/carbonate based minerals; and has incomparable properties like light weight, high thermal insulation and cellular structure with sufficient rigidity. In the present study, the effects of the glass type and mineral addition on the foam glass properties were investigated. Nano sized SiC was fixed as foaming agent at the whole of the samples, mixed glass waste and sheet glass were selectively used as glass sources; finally Al₂O₃ was optionally used as mineral additive. These raw material powders were mixed homogenously, pressed at same pressure and sintered at same schedule. Finally, obtained samples were characterized based on the required properties of foam glass material, and optimum results were determined. At the end of the study, 0.049 W/mK thermal conductivity, 72 % porosity, and 0.21 kg/cm² apparent density with 2.41 MPa compressive strength values were achieved with using nano sized SiC, sheet glass and Al₂O₃ mineral additive. It can be said that the foam glass materials can be preferred as an alternative insulation material rather than polymeric based conventional insulation materials because of supplying high thermal insulation properties without containing unhealthy chemicals and burn risks.

Keywords: foam glass, foaming, silicon carbide, waste glass

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Authors: Syed Makhdoom Hussain, Muhammad Afzal, Farhat Jabeen, Arshad Javid, Tasneem Hameed

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A feeding trial was conducted with Cirrhinus mrigala fingerlings to study the effects of microbial phytase with graded levels (0, 500, 1000, 1500, and 2000 FTUkg-1) by sunflower meal based diet on growth performance and nutrient digestibility. The chromic oxide was added as an indigestible marker in the diets. Three replicate groups of 15 fish (Average wt 5.98 g fish-1) were fed once a day and feces were collected twice daily. The results of present study showed improved growth and feed performance of Cirrhinus mrigala fingerlings in response to phytase supplementation. Maximum growth performance was obtained by the fish fed on test diet-III having 1000 FTU kg-1 phytase level. Similarly, nutrient digestibility was also significantly increased (p<0.05) by phytase supplementation. Digestibility coefficients for sunflower meal based diet increased 15.76%, 17.70%, and 12.70% for crude protein, crude fat and apparent gross energy as compared to the reference diet, respectively at 1000 FTU kg-1 level. Again, maximum response of nutrient digestibility was recorded at the phytase level of 1000 FTU kg-1 diet. It was concluded that the phytase supplementation to sunflower meal based diet at 1000 FTU kg-1 level is optimum to release adequate chelated nutrients for maximum growth performance of C. mrigala fingerlings. Our results also suggested that phytase supplementation to sunflower meal based diet can help in the development of sustainable aquaculture by reducing the feed cost and nutrient discharge through feces in the aquatic ecosystem.

Keywords: sunflower meal, Cirrhinus mrigala, growth, nutrient digestibility, phytase

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Authors: Keunho Park, Sunghwan Jeong

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The 4th Industrial Revolution, the next-generation industrial revolution, which is made up of convergence of information and communication technology (ICT), is no exception to the livestock industry, and various studies are being conducted to apply the livestock smart farm. In order to monitor livestock using sensors, it is necessary to drill holes in the organs such as the nose, ears, and even the stomach of the livestock to wear or insert the sensor into the livestock. This increases the stress of livestock, which in turn lowers the quality of livestock products or raises the issue of animal ethics, which has become a major issue in recent years. In this paper, we conducted a study to monitor livestock activity based on vision technology, effectively monitoring livestock activity without increasing animal stress and violating animal ethics. The movement rate was calculated based on the difference images between the frames, and the livestock activity was evaluated. As a result, the average F1-score was 96.67.

Keywords: barn monitoring, livestock, machine vision, smart farm

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Authors: Wang Lin, Li Zhiqiang

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The purpose of this paper is to analyze the cooperative learning behavior pattern based on the data of students' movement. The study firstly reviewed the cooperative learning theory and its research status, and briefly introduced the k-means clustering algorithm. Then, it used clustering algorithm and mathematical statistics theory to analyze the activity rhythm of individual student and groups in different functional areas, according to the movement data provided by 10 first-year graduate students. It also focused on the analysis of students' behavior in the learning area and explored the law of cooperative learning behavior. The research result showed that the cooperative learning behavior analysis method based on movement data proposed in this paper is feasible. From the results of data analysis, the characteristics of behavior of students and their cooperative learning behavior patterns could be found.

Keywords: behavior pattern, cooperative learning, data analyze, k-means clustering algorithm

Procedia PDF Downloads 187

Authors: Abigail Ekeigwe, Bethany McGowan, Loran C. Parker, Stephen Byrn, Kari L. Clase

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There are growing calls in the literature to develop and implement competency-based regulatory sciences education (CBRSE) in sub-Saharan Africa to expand and create a pipeline of a competent workforce of regulatory scientists. A defined competence framework is an essential component in developing competency-based education. However, such a competence framework is not available for regulatory scientists in sub-Saharan Africa. The purpose of this research is to identify entry-level competencies for inclusion in a competency framework for regulatory scientists in sub-Saharan Africa as a first step in developing CBRSE. The team systematically reviewed the literature following the PRISMA guidelines for systematic reviews and based on a pre-registered protocol on Open Science Framework (OSF). The protocol has the search strategy and the inclusion and exclusion criteria for publications. All included publications were coded to identify entry-level competencies for regulatory scientists. The team deductively coded the publications included in the study using the 'framework synthesis' model for systematic literature review. The World Health Organization’s conceptualization of competence guided the review and thematic synthesis. Topic and thematic codings were done using NVivo 12™ software. Based on the search strategy in the protocol, 2345 publications were retrieved. Twenty-two (n=22) of the retrieved publications met all the inclusion criteria for the research. Topic and thematic coding of the publications yielded three main domains of competence: knowledge, skills, and enabling behaviors. The knowledge domain has three sub-domains: administrative, regulatory governance/framework, and scientific knowledge. The skills domain has two sub-domains: functional and technical skills. Identification of competencies is the primal step that serves as a bedrock for curriculum development and competency-based education. The competencies identified in this research will help policymakers, educators, institutions, and international development partners design and implement competence-based regulatory science education in sub-Saharan Africa, ultimately leading to access to safe, quality, and effective medical products.

Keywords: competence-based regulatory science education, competencies, systematic review, sub-Saharan Africa

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Authors: Gherbi Nabil

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Detection of ground targets in SAR radar images is an important area for radar information processing. In the literature, various algorithms have been discussed in this context. However, most of them are of low robustness and accuracy. To this end, we discuss target detection in SAR images based on compressive sensing. Firstly, traditional SAR image target detection algorithms are discussed, and their limitations are highlighted. Secondly, a compressive sensing method is proposed based on the sparsity of SAR images. Next, the detection problem is solved using Multiple Measurements Vector configuration. Furthermore, a robust Alternating Direction Method of Multipliers (ADMM) is developed to solve the optimization problem. Finally, the detection results obtained using raw complex data are presented. Experimental results on real SAR images have verified the effectiveness of the proposed algorithm.

Keywords: compressive sensing, raw complex data, synthetic aperture radar, ADMM

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Authors: Ming Lun Wang, Yan Wang, Ning Ruo Sun

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With the development of cloud computing, more and more users start to utilize the cloud storage service. However, there exist some issues: 1) cloud server steals the shared data, 2) sharers collude with the cloud server to steal the shared data, 3) cloud server tampers the shared data, 4) sharers and key generation center (KGC) conspire to steal the shared data. In this paper, we use advanced encryption standard (AES), hash algorithms, and accountable key-policy attribute-based encryption without key escrow (WOKE-AKP-ABE) to build a security cloud storage scheme. Moreover, the data are encrypted to protect the privacy. We use hash algorithms to prevent the cloud server from tampering the data uploaded to the cloud. Analysis results show that this scheme can resist conspired attacks.

Keywords: cloud storage security, sharing storage, attributes, Hash algorithm

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Authors: Alluru Gopala Krishna, Thella Babu Rao

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In machining, there is always a problem with heat generation and friction produced during the process as they consequently affect tool wear and surface finish. An instant heat transfer mechanism could protect the cutting tool edge and enhance the tool life by cooling the cutting edge of the tool. In the present work, carbon nanotube (CNT) based nano-cutting fluid is proposed for machining a hard-to-cut material. Tool wear and surface roughness are considered for the evaluation of the nano-cutting fluid in turning process. The performance of nanocoolant is assessed against the conventional coolant and dry machining conditions and it is observed that the proposed nanocoolant has produced better performance than the conventional coolant.

Keywords: CNT based nano cutting fluid, tool wear, turning, surface roughness

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Authors: Ivan Stanev, Maria Koleva

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Described are challenges to the Bulgarian e-Customs (BeC) related to low level of interoperability and standardization, inefficient use of available infrastructure, lack of centralized identification and authorization, extremely low level of software process automation, and insufficient quality of data stored in official registers. The technical requirements for BeC are prepared with a focus on domain independent common platform, specialized customs and excise components, high scalability, flexibility, and reusability. The Knowledge Based Automated Software Engineering (KBASE) Common Platform for Automated Programming (CPAP) is selected as an instrument covering BeC requirements for standardization, programming automation, knowledge interpretation and cloud computing. BeC stage 3 results are presented and analyzed. BeC.S3 development trends are identified.

Keywords: service oriented architecture, cloud computing, knowledge based automated software engineering, common platform for automated programming, e-customs

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Authors: Syamala Krishnannair

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A multivariate statistical process monitoring methodology using dissimilarity scale-based singular spectrum analysis (SSA) is proposed for the detection and diagnosis of process faults in the base metal flotation plant. Process faults are detected based on the multi-level decomposition of process signals by SSA using the dissimilarity structure of the process data and the subsequent monitoring of the multiscale signals using the unified monitoring index which combines T² with SPE. Contribution plots are used to identify the root causes of the process faults. The overall results indicated that the proposed technique outperformed the conventional multivariate techniques in the detection and diagnosis of the process faults in the flotation plant.

Keywords: fault detection, fault diagnosis, process monitoring, dissimilarity scale

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Authors: Brenda Margaret Behan

Abstract:

Kenya is a water-stressed country with highly varied socio-ecological environments in its devolved county system, and is currently implementing a polycentric water governance system; this paper examines the importance of social capital in community-based natural resource management and its role in supporting good water governance systems in the Kenya context. Through a robust literature review of theory and case studies, specific aspects of social capital are examined to determine their importance in the implementation of local community-based water management arrangements which support and complement the more formal institutions outlined in the 2002 and 2016 Water Acts of Kenya. Water is an increasingly important and scarce resource not only for Kenya, but for many communities across the globe, and lessons learned in the Kenya context can be useful for other countries and communities faced with similar challenges. Changing climates, increasing populations, and increased per capita consumption of water is contributing to a situation in which the management of water resources will be vital to community resilience. Community-based natural resource management is widely recognized as a building block and component of wider water resource management systems, and when properly conducted can provide a way to enable sustainable use of resources and empower communities. Greater attention to the social and cultural norms and traditional institutions associated with a community’s social capital can lead to better results for Kenya’s polycentric governance of water. The key findings and recommendations from this research show that in Kenya, traditional institutions need to be understood and integrated into governance systems; social values and cultural norms have a significant impact on the implementation of community-based water management efforts; and social capital is a dynamic concept which influences and is influenced by policies and practices. The community-based water management approach will continue to be a key cornerstone for Kenya’s polycentric water governance structure, especially in the more remote arid and semi-arid lands; thus, the successful integration of social capital aspects into planning and implementation will contribute to a strengthened, sustainable, and more equitable national water governance system. Specific observations and recommendations from this study will help practitioners and policymakers to better craft community-based interventions.

Keywords: community-based natural resource management, social capital, traditional institutions, water governance

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Authors: Donatello Cardone

Abstract:

Shape memory alloys (SMAs) have great potential for use in the field of civil engineering. The author of this manuscript has been involved, since 1996, in several experimental and theoretical studies on the application of SMAs in structural engineering, within national and international research projects. This paper provides an overview of the main results achieved, including the conceptual design, implementation, and testing of different SMA-based devices, namely: (i) energy-dissipating braces for RC buildings, (ii) seismic isolation devices for buildings and bridges, (iii) smart tie-rods for arches and vaults and (iv) seismic restrainers for bridges. The main advantages of using SMA-based devices in the seismic protection of structures derive from the double-flag shape of their hysteresis loops, which implies three favourable features, i.e., self-centering capability, good energy dissipation capability, and high stiffness for small displacements. The main advantages of SMA-based units for steel tie-rods are associated with the thermal behaviour of superelastic SMAs, which is antagonistic compared to that of steel. This implies a strong reduction of force changes due to air temperature variations. Finally, SMA-based seismic restrainers proved to be effective in preventing bridge deck unseating and pounding.

Keywords: seismic protection of structures, shape memory alloys, structural engineering, steel tie-rods, seismic restrainers for bridges

Procedia PDF Downloads 98