Search results for: Meshless Methods

Authors: Mohammadali Abedini Sanigy, Jiangang Fei

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In this paper, a mathematical optimization model was developed to maximize the profit in a vegetable production planning problem. It serves as a decision support system that assists farmers in land allocation to crops and harvest scheduling decisions. The developed model can handle different rotation rules in two consecutive cycles of production, which is a common practice in organic production system. Moreover, different production methods of the same crop were considered in the model formulation. The main strength of the model is that it is not restricted to predetermined production periods, which makes the planning more flexible. The model is classified as a mixed integer programming (MIP) model and formulated in PYOMO -a Python package to formulate optimization models- and solved via Gurobi and CPLEX optimizer packages. The model was tested with secondary data from 'Australian vegetable growing farms', and the results were obtained and discussed with the computational test runs. The results show that the model can successfully provide reliable solutions for real size problems.

Keywords: crop rotation, harvesting, mathematical model formulation, vegetable production

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Authors: Bin Ji, Kai Xu, Shunyu Yao, Jingjing Liu, Ye Pan

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Human pose estimation is a popular research area in computer vision for its important application in human-machine interface. In recent years, 2D human pose estimation based on convolution neural network has got great progress and development. However, in more and more practical applications, people often need to deal with tasks based on video. It’s not far-fetched for us to consider how to combine the spatial and temporal information together to achieve a balance between computing cost and accuracy. To address this issue, this study proposes a new spatiotemporal model, namely Spatiotemporal Net (STNet) to combine both temporal and spatial information more rationally. As a result, the predicted keypoints heatmap is potentially more accurate and spatially more precise. Under the condition of ensuring the recognition accuracy, the algorithm deal with spatiotemporal series in a decoupled way, which greatly reduces the computation of the model, thus reducing the resource consumption. This study demonstrate the effectiveness of our network over the Penn Action Dataset, and the results indicate superior performance of our network over the existing methods.

Keywords: convolutional long short-term memory, deep learning, human pose estimation, spatiotemporal series

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Authors: Alessandro Marano

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Aim: The author describes the aesthetic modification using orthognathic surgery and closed rhinoplasty. Methods: Series of case study. After orthognathic surgery we can observe a dramatical change of aesthetic especially in the mid-face and nose projection. The advancement of maxillary bone through Le Fort I osteotomy will change the nasal tip projection and lips roundness; combining orthognathic surgery with closed approach rhinoplasty will manage both function and aesthetic of all mid face district. Results: Combining Le Fort I osteotomy with closed approach rhinoplasty resulted in good objective results with high patient satisfaction. Le Fort I osteotomy will increase projection of mid face and the closed approach rhinoplasty will modify the nasal shape to be more harmonic with the new maxillary district. The scars are not visible because hidden inside the mouth and nose. Conclusions: The orthognathic surgery combined with closed approach rhinoplasty are very effective for changing the aesthetic of the mid face. The results illustrate the difference between the use of orthognathic surgery only and to use it in association of closed approach rhinoplasty. Using both will allow to obtain a long lasting and pleasing results.

Keywords: orthognathic, rhinoplasty, aesthetic, face

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Authors: Ahmed Elkholy

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Most power transmission cases use gearing in general, and worm gearing, in particular for energy utilization. Therefore, designing gears for minimum weight and maximum power transmission is the main target of this study. In this regard, a new approach has been developed to estimate the load share and stress distribution of worm gear sets. The approach is based upon considering the instantaneous tooth meshing stiffness where the worm gear drive was modelled as a series of spur gear slices, and each slice was analyzed separately using a well-established criteria. By combining the results obtained for all slices, the entire worm gear set loading and stressing was determined. The geometric modelling method presented, allows tooth elastic deformation and tooth root stresses of worm gear drives under different load conditions to be investigated. On the basis of the method introduced in this study, the instantaneous meshing stiffness and load share were obtained. In comparison with existing methods, this approach has both good analytical accuracy and less computing time.

Keywords: gear, load/stress distribution, worm, wheel, tooth stiffness, contact line

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Authors: Kamel Abdelaziz Mohamed

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Intoduction:Inadequate knowledge about obstetric admission and infrequent dealing with the obstetric patients in ICU results in high mortality and morbidity. Aim of the work:To evaluate the indications, course, severity of illness, and outcome of obstetric patients admitted to the intensive care unit (ICU). Patients and Methods: We collected baseline data and acute physiology and chronic health evaluation II (APACHE II) scores. ICU mortality was the primary outcome. Results: Seventy obstetric patients were admitted to the ICU over 3 years, 36 of these patients (51.4 %) were admitted during the antepartum period. The primary obstetric indication for ICU admission was pregnancy-induced hypertension (22 patients, 31.4%), followed by sepsis (8 patients, 11.4%) as the leading non-obstetric admission. The mean APACHE II score was 19.6. The predicted mortality rate based on the APACHE II score was 22%, however, only 4 maternal deaths (5.7%) were among the obstetric patients admitted to the ICU. Conclusion: Evaluation of obstetric patients by (APACHE II) scores showed higher predicted mortality rate, however the overall mortality was lower. Regular follow up, together with early detection of complications and prompt ICU admission necessitating proper management by specialized team can improve mortality.

Keywords: obstetric, complication, postpartum, sepsis

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Authors: Jonas P. Reges, Jessyca A. Bessa, Auzuir R. Alexandria

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The research came up with the need of monitoring them of temperature and relative moisture in past work that enveloped the study of a greenhouse located in the Research and Extension Unit(UEPE). This research brought several unknowns that were resolved from bibliographical research. Based on the studies performed were found some monitoring methods, including the serial communication between the arduino and matlab which showed a great option due to the low cost. The project was conducted in two stages, the first, an algorithm was developed to the Arduino and Matlab, and second, the circuits were assembled and performed the monitoring tests the following variables: moisture, temperature, and distance. During testing it was possible to momentarily observe the change in the levels of monitored variables. The project showed satisfactory results, such as: real-time verification of the change of state variables, the low cost of acquisition of the prototype, possibility of easy change of programming for the execution of monitoring of other variables. Therefore, the project showed the possibility of monitoring through software and hardware that have easy programming and can be used in several areas. However, it is observed also the possibility of improving the project from a remote monitoring via Bluetooth or web server and through the control of monitored variables.

Keywords: automation, monitoring, programming, arduino, matlab

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Authors: Andre Peres Ramos, Franklin Cesar Flores

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Colorization is the process of add colors to a monochromatic image or video. Usually, the process involves to segment the image in regions of interest and then apply colors to each one, for videos, this process is repeated for each frame, which makes it a tedious and time-consuming job. We propose a new assisted method for video colorization; the user only has to colorize one frame, and then the colors are propagated to following frames. The user can intervene at any time to correct eventual errors in color assignment. The method consists of to extract intensity and texture descriptors from the frames and then perform a feature matching to determine the best color for each segment. To reduce computation time and give a better spatial coherence we narrow the area of search and give weights for each feature to emphasize texture descriptors. To give a more natural result, we use an optimization algorithm to make the color propagation. Experimental results in several image sequences, compared to others existing methods, demonstrates that the proposed method perform a better colorization with less time and user interference.

Keywords: colorization, feature matching, texture descriptors, video segmentation

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Authors: Abuelquasim. M. Hassan, Namarig .S. Mohammed, Samah F. Mohammed, Wafaa. A. Mohammed, Wafaa M. Edriss, Amel A. Ahmed, Elfadil M. Abass

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Introduction: Cytomegalovirus (CMV), a common virus, usually causes asymptomatic infections in immunocompetent hosts; however, it may lead to serious complications especially in cancer patients. Objectives: This study was conducted to determine the seroprevalence of human cytomegalovirus (HCMV) among leukemia, breast and prostate cancer patients attending at Radiation Isotope-Center-Khartoum (RICK) from April to August 2016. Material and Methods: A total of 91 subjects were included: 30 leukemic, 22 breast cancer and 29 prostate cancer patients.10 of them were healthy and used as control group, serum samples were collected and tested for CMV IgG & IgM using enzyme-linked immune sorbent assay (ELISA). Result: Of the control group, 9/10 (9.9%) were seropositive for CMV IgG and 1/10 (1.09%) were sero positive for IgM. Also, all cancer groups demonstrated presence of IgG antibody classes as: The percentage of positive results in prostate, breast cancer and leukemia were 35.8 %, 37.2%, and 35.3% respectively. Conclusion: There was no significant correlation between leukemia, breast, prostate and HCMV.

Keywords: cytomegalovirus, serodiagnostic, breast cancer, leukemia

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Authors: Soumaya Mrabet, Imen Akkari, Amira Atig, Elhem Ben Jazia

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Introduction: Autoimmune hepatitis (AIH) is a chronic inflammatory liver disease of unknown cause. Concomitant autoimmune disorders have been described in 30–50% of patients with AIH. The aim of our study is to determine the prevalence and the type of autoimmune disorders associated with AIH. Material and Methods: It is a retrospective study over a period of 16 years (2000-2015) including all patients followed for AIH. The diagnosis of AHI was based on the criteria of the revised International AIH group scoring system (IAIHG). Results: Twenty-for patients (21 women and 3 men) followed for AIH were collected. The mean age was 39 years (17-65 years). Among these patients, 11 patients(45.8%) had at least one autoimmune disease associated to AIH. These diseases were Hashimoto's thyroiditis (n = 5), Gougerot Sjogren syndrome (n=5), Primary biliary cirrhosis (n=2), Primitive sclerosant Cholangitis (n=1), Addison disease (n = 1) and systemic sclerosis (n=1). Patients were treated with corticosteroids alone or with azathioprine associated to the specific treatment of associated diseases with complete remission of AIH in 90% of cases and clinical improvement of other diseases. Conclusion: In our study, the prevalence of autoimmune diseases in AIH patients was 45.8%. These diseases were dominated by autoimmune thyroiditis and Gougerot Sjogren syndrome. The investigation of autoimmune diseases in autoimmune hepatitis must be systematic because of their frequency and the importance of adequate management.

Keywords: autoimmune diseases, autoimmune hepatitis, autoimmune thyroiditis, gougerot sjogren syndrome

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Authors: Asha Dukkipati

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Cognitive neuroscience explores neural functioning and aberrant brain activity during cognitive and perceptual tasks. Neurocinematics is a subfield of cognitive neuroscience that observes neural responses of individuals watching a film to see similarities and differences between individuals. This method is typically used for commercial use, allowing directors and filmmakers to produce better visuals and increasing their results in the box office. However, neurocinematics is increasingly becoming a common tool for neuroscientists interested in studying similar patterns of brain activity across viewers outside of the film industry. In this review, it argue that neurocinematics provides an easy, naturalistic approach for studying and diagnosing learning disorders. While the neural underpinnings of developmental learning disorders are traditionally assessed with well-established methods like EEG and fMRI that target particular cognitive domains, such as simple visual and attention tasks, there is initial evidence and theoretical background in support of neurocinematics as a biomarker for learning differences. By using ADHD, dyslexia, and autism as case studies, this literature review discusses the potential advantages of neurocinematics as a new tool for learning disorders research.

Keywords: behavioral and social sciences, neuroscience, neurocinematics, biomarkers, neurobehavioral disorders

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Authors: Mapule Maema

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The paper aims to highlight the role that community activism has played in promoting social justice around housing issues in the Western Cape. The Western Cape is one of the largest spatially segregated provinces in South Africa which continues to exhibit grave inequalities between cities, townships and farms. These inequalities cut across intersectional issues such as, race, class, gender, and politics. The main challenges facing marginalized communities in the Western Cape include access to housing, land and basic services. This is not peculiar to only the Western Cape, the entire country is facing similar challenges however the Western Cape is seen as a fasted urbanizing province in the country due to tourism. Various social movements have been formed across the country to counter these challenges, however, this paper focuses on the resilience communities have fostered despite the myriad housing and spatial crisis they are faced with. The paper focuses on the Legal Resource’s Centre’s clients from an informal settlement called Imizamo Yethu based in Hout Bay Valley area. The 18 hectare settlement houses approximately 33600 people. On the 21st July 2017, Hout Bay experienced violent protests following an eviction order passed by the City of Cape Town. The protest was characterized by tensions within the community regarding the super-blocking initiative which aims to establish roads in informal settlements to ensure basic services. Residents against the process argued that there were no proper consultations done to educate them on what this process entailed. Public participation is one of the objectives the municipalities aim to promote however it remains a great challenge. In order to highlight the experiences of the LRC clients in relation to what motivated their involvement in the movement, how it felt their participation, and aspirations, the paper will employ qualitative research methods. Qualitative research methods enable the researcher to get a deeper and nuanced understanding of the social world in the eyes of those who experienced it. It is a flexible methodology that enables one to also understand social processes and the significance they generate. Data will be collected through the use of the World Cafe as a focus group method. The World Café is a simple, effective and flexible format for hosting group dialogue. The steps taken when setting up a World Café includes the following: setting the context (why you are bringing people together and what you want to achieve), create hospitality space (make participants feel at home and free to discuss issues), explore questions that matter, connect diverse perspectives (the opportunity to actively contribute your thinking), listen together for patterns and insights, share collective discoveries and learnings. Secondary data will be used to augment the data collected. Stories of impact will be drawn from the exercises. This paper will contribute to the discourse of sustainable housing and urban development and the research outputs will be disseminated to the public for learning.

Keywords: community activism, influence, social justice, development

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Authors: A. Fogliata, L. Martiniello, A. Ambretti

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Introduction: The significance of balance and stability in physical education among adolescents is well-established. This study aims to assess the efficacy of Centering (CENT), which employs intra-abdominal pressure (IAP) in line with the Synchrony Method, in optimizing balance and reducing perceived stress. Materials and Methods: A 6-week intervention was conducted on a sample of adolescents, divided into a control group and an experimental group that incorporated CENT into their physical education program. The Stork Balance Test and the Perceived Stress Scale (PSS) were used to measure changes. Results: Findings revealed a significant enhancement in the balance of both the dominant and non-dominant limbs in the experimental group compared to the control group. Moreover, the PSS test indicated a reduction in perceived stress within the experimental group. Conclusion: Integrating the centering technique into physical education programs can lead to substantial improvements in adolescents' balance and stability, in addition to a reduction in perceived stress levels. These findings suggest the need for further research on broader populations to solidify these pivotal outcomes.

Keywords: adolescents, physical education, balance, centering, intra-abdominal pressure

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Authors: Besma Abdeltif, Chebabhi Imen

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Introduction: it is important to define the genital pathologies encountered in Algeria in postpartum dairy cows. The objective was to identify the different pathologies of reproduction in cows found at the communal abattoir of Souk Ahras. Materials and Methods: Our study was carried at the communal slaughterhouse of Souk-Ahras on 63 genital tracts were examined macroscopically after slaughter. Results: The results obtained reveal a high frequency of pregnant females (14.28%), most of the gestations were at their beginning. Uterine anomalies ranked first in the genital lesions of the cow (20.37%). The frequencies of these abnormalities are in ascending order: aplasia of the horns = 1.85%, traumatic cervical = 1.85%, cervical tumors = 1.85%, chronic endometritis = 3.70% and Acute endometritis = 11.11%. The ovarian cyst is the most common lesion, with a frequency of 3.70%, followed by smooth ovaries (1.85%). These are single, thin-walled cysts more present on the right ovary than the left ovary. Salpingitis is the only tubal lesion found on 5.55% of the non-pregnant genital tract. Neoformation is the only vaginal lesion identified in this work (1.85%). Conclusion: Our result, in general, conforms to the data of the literature.

Keywords: genital tract, cow, slaughterhouse, pathology

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Authors: Manar Amayri, Hussain Kazimi, Quoc-Dung Ngo, Stephane Ploix

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A general approach is proposed to determine occupant behavior (occupancy and activity) in residential buildings and to use these estimates for improved energy management. Occupant behaviour is modelled with a Bayesian Network in an unsupervised manner. This algorithm makes use of domain knowledge gathered via questionnaires and recorded sensor data for motion detection, power, and hot water consumption as well as indoor CO₂ concentration. Two case studies are presented which show the real world applicability of estimating occupant behaviour in this way. Furthermore, experiments integrating occupancy estimation and hot water production control show that energy efficiency can be increased by roughly 5% over known optimal control techniques and more than 25% over rule-based control while maintaining the same occupant comfort standards. The efficiency gains are strongly correlated with occupant behaviour and accuracy of the occupancy estimates.

Keywords: energy, management, control, optimization, Bayesian methods, learning theory, sensor networks, knowledge modelling and knowledge based systems, artificial intelligence, buildings

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Authors: Neda Rezvanisanijouybari

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Cities are living and dynamic organisms that can play an essential role in meeting people's psychological and mental needs. The green and blue spaces, including parks, play an important role in meeting those needs, and therefore they should be prioritised in urban planning and designing. Sari city had several city designs and planning projects to expand the green spaces. These included adding more parks and open spaces with new urban furniture in the city and were an important step forward in creating a pleasant urban landscape in the north of Iran. This research used quantitative and qualitative methods to examine whether the citizens of Sari were satisfied with green and blue spaces and new urban furniture in the city or not. From a questionnaire of 120 Sari citizens, it was found that the citizens were generally satisfied with the green and blue spaces and new urban furniture in Sari. It was also found that the favourite park was Mellal park, and the least favourite was Azadegan park. Accessibility, safety, design, facilities, and water source were the most important reason to visit the parks.

Keywords: satisfaction, green, blue, urban furniture

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Authors: Alexandre Rabaseda, Emelie Seguin, Marc Doumit

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Human mobility exoskeletons have been in development for several years and are becoming increasingly efficient. Unfortunately, user comfort was not always a priority design criterion throughout their development. To further improve this technology, exoskeletons should operate and deliver assistance without causing discomfort to the user. For this, improvements are necessary from an ergonomic point of view. The device’s control method is important when endeavoring to enhance user comfort. Exoskeleton or rehabilitation device controllers use methods of control called interaction controls (admittance and impedance controls). This paper proposes an extended version of an admittance controller to enhance user comfort. The control method used consists of adding an inner loop that is controlled by a proportional-integral-derivative (PID) controller. This allows the interaction force to be kept as close as possible to the desired force trajectory. The force-tracking admittance controller modifies the actuation force of the system in order to follow both the desired motion trajectory and the desired relative force between the user and the exoskeleton.

Keywords: mobility assistive device, exoskeleton, force-tracking admittance controller, user comfort

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Authors: Kang-Mo Jung

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The use of regularization for statistical methods has become popular. The least absolute shrinkage and selection operator (LASSO) framework has become the standard tool for sparse regression. However, it is well known that the LASSO is sensitive to outliers or leverage points. We consider a new robust estimation which is composed of the weighted loss function of the pairwise difference of residuals and the adaptive penalty function regulating the tuning parameter for each variable. Rank regression is resistant to regression outliers, but not to leverage points. By adopting a weighted loss function, the proposed method is robust to leverage points of the predictor variable. Furthermore, the adaptive penalty function gives us good statistical properties in variable selection such as oracle property and consistency. We develop an efficient algorithm to compute the proposed estimator using basic functions in program R. We used an optimal tuning parameter based on the Bayesian information criterion (BIC). Numerical simulation shows that the proposed estimator is effective for analyzing real data set and contaminated data.

Keywords: adaptive penalty function, robust penalized regression, variable selection, weighted rank regression

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Authors: Pogula Rakesh, T. Kishore Kumar

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Speech enhancement is a long standing problem with numerous applications like teleconferencing, VoIP, hearing aids, and speech recognition. The motivation behind this research work is to obtain a clean speech signal of higher quality by applying the optimal noise cancellation technique. Real-time adaptive filtering algorithms seem to be the best candidate among all categories of the speech enhancement methods. In this paper, we propose a speech enhancement method based on Recursive Least Squares (RLS) adaptive filter of speech signals. Experiments were performed on noisy data which was prepared by adding AWGN, Babble and Pink noise to clean speech samples at -5dB, 0dB, 5dB, and 10dB SNR levels. We then compare the noise cancellation performance of proposed RLS algorithm with existing NLMS algorithm in terms of Mean Squared Error (MSE), Signal to Noise ratio (SNR), and SNR loss. Based on the performance evaluation, the proposed RLS algorithm was found to be a better optimal noise cancellation technique for speech signals.

Keywords: adaptive filter, adaptive noise canceller, mean squared error, noise reduction, NLMS, RLS, SNR, SNR loss

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Authors: Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

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Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

Keywords: fake news detection, natural language processing, machine learning, classification techniques.

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Authors: Sanja Peter

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Transformation of urban environments can be compared to evolutionary processes. Systematic digital mapping of historical data can enable capturing some of these processes and their outcomes. For example, it may help reveal the structure of a city’s historical DNA. Gathering historical data for automatic processing may be giving a basis for cultural algorithms. Gothenburg City museum is trying to make city’s heritage information accessible through GIS-platforms and is now partnering with academic institutions to find appropriate methods to make accessible the knowledge on the city’s historical fabric. Hopefully, this will be carried out through a project called Digital Twin Cities. One part of this large project, concerning matters of Cultural Heritage, will be in collaboration with Chalmers University of Technology. The aim is to create a layered map showing historical developments of the city and extracting quantitative data about its built heritage, above and below the earth. It will allow interpreting the information from historic maps through, for example, names of the streets/places, geography, structural changes in urban fabric and information gathered by archaeologists’ excavations. Through the study of these geographical, historical and local metamorphoses, urban environment will reveal its metaphorical DNA or its MEM (Dawkins).

Keywords: Gothenburg, mapping, cultural heritage, city history

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Authors: Issam M Hajjaji, Adel Tajoury, Salah R Benhamid

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The MENA region has the highest prevalence of diabetes in the world. Various risk scores were developed, not all appropriate locally. The objective of this study is to apply the FINDRISC Score to adult Libyan males to determine its significance, sensitivity, specificity and Positive Predictive Values as an initial screening tool for type 2 diabetes, and suggest a cut-off point. Methods: 600 subjects answered the questionnaire at their place of work, and their waist, weight, height & BP were measured. Thereafter, after excluding those with known diabetes, an Oral Glucose Tolerance Test was done. Results: 414 subjects aged 19-78 completed the questionnaire and tests. 35 (8.4%) had impaired glucose tolerance (IGT) and 13 (3.1%) had diabetes (DM). The AUC-ROC for IGT was 0.614 (95% CI: 0.527-0.701), for DM 0.810 (95% CI: 0.709-0.911) and for both 0.689 (95% CI: 0.609-0.769). The Positive Predictive Value for a cut-off score of 5 were 15.5%, 11.7% & 5.7% for both conditions combined, prediabetes & diabetes respectively. The equivalent values for a cut-off score of 8 were 16.1%, 9.0% & 7.7%. The Negative Predictive Values were uniformly above 90%. Conclusions & Recommendations: The FINDRISC Score had a low predictive value for dysglycaemia in this sample and performed at a level of significance for IGT that is similar to other MENA countries, but did better for DM. A larger sample that included women is suggested, with a view of adjusting the Score to suit the local population.

Keywords: diabetes, FINDRISK, Libya, prediabetes

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Authors: Avantika Vats, Kushal Thakur

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This paper displays the point at issue, improvement, and utilization of a Monarch Butterfly Optimization (MBO) rather than a Genetic Algorithm (GA) in cognitive radio for the channel portion. This approach offers a satisfactory approach to get the accessible range of both the users, i.e., primary users (PUs) and secondary users (SUs). The proposed enhancement procedure depends on a nature-inspired metaheuristic algorithm. In MBO, all the monarch butterfly individuals are located in two distinct lands, viz. Southern Canada and the northern USA (land 1), and Mexico (Land 2). The positions of the monarch butterflies are modernizing in two ways. At first, the offsprings are generated (position updating) by the migration operator and can be adjusted by the migration ratio. It is trailed by tuning the positions for different butterflies by the methods for the butterfly adjusting operator. To keep the population unaltered and minimize fitness evaluations, the aggregate of the recently produced butterflies in these two ways stays equivalent to the first population. The outcomes obviously display the capacity of the MBO technique towards finding the upgraded work values on issues regarding the genetic algorithm.

Keywords: cognitive radio, channel allocation, monarch butterfly optimization, evolutionary, computation

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Authors: Ajay Wadhwa

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A Laboratory course on computational physics is different from the conventional lab course on other topics of physics like Mechanics, Heat, Optics, etc. because it involves active participation of the teacher as well as one-to-one interaction between teacher and the student. The course content requires the teacher to teach programming language as well as numerical methods along with their applications in physics. The task becomes more daunting when about 90% of the students in the class have no previous experience of any programming language. In the presented work, we have described a methodology for conducting the computational physics course by using the Google Drive and Dropitto.me cloud storage services. We have evaluated the performance in a class of sixty students by dividing them equally into four groups. One of the groups was made the peer group on whom the presented methodology was tested. The other groups were taught by using conventional method of classroom lectures. In order to assess our methodology, we analyzed the performance of students in four class tests. A study of certain statistical parameters like the mean, standard deviation, and Z-test hypothesis revealed that the cyber methodology based on cloud storage is more efficient than the conventional method of teaching.

Keywords: computational Physics, Z-test hypothesis, cloud storage, Google drive

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Authors: Hsien-Wei Kuo

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The thoughts of the military citizens, pragmatism, naturalism and nationalism related to physical education were developed during the warring period of the Republic of China. Moreover, the development of martial art formed by nationalism and political party was to utilize to save the nation, the people and the world. The martial art was also promoted in the system of school physical education gradually at the same time. The aim of this study is to explore the role, duty and position of the martial art education with the political color and advocacy in the system of school physical education. This study focuses on the practice, course hours, selective materials and competitive rules of physical education in the school system in modern China. Therefore, the methods of the historical research and content analysis were used to collect the historical materials and documents for going into them. The results will give a detailed account of the developed model of institutionalization, unification and regularization of martial art, and its growing, golden and stagnant periods in the school physical education system under the impact of western sport and physical education. It may sum up the meaning relationships among the politics, education practice and sport for all.

Keywords: martial art education, national martial arts institution, sick man of East Asia, the may 4th movement

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Authors: Christina A. van Hal, Xiaoqian Jiang, Luyao Chen, Yan Chu, Robert D. Jolly, Yaobin Lin, Jitian Zhao, Kang Lin Hsieh

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The COVID-19 Literature Summary App was created for the primary purpose of enabling academicians and clinicians to quickly sort through the vast array of recent coronavirus publications by topics of interest. Multiple methods of summarizing and sorting the manuscripts were created. A summary page introduces the application function and capabilities, while an interactive map provides daily updates on infection, death, and recovery rates. A page with a pivot table allows publication sorting by topic, with an interactive data table that allows sorting topics by columns, as wells as the capability to view abstracts. Additionally, publications may be sorted by the medical topics they cover. We used the CORD-19 database to compile lists of publications. The data table can sort binary variables, allowing the user to pick desired publication topics, such as papers that describe COVID-19 symptoms. The application is primarily designed for use by researchers but can be used by anybody who wants a faster and more efficient means of locating papers of interest.

Keywords: COVID-19, literature summary, information retrieval, Snorkel

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Authors: Heba M. Mohamed

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Owing to scientific and public concern about health and environment and seeking for a better quality of life; “Green”, “Environmentally” and “Eco” friendly practices have been presented and implemented in different research areas. Subsequently, researchers’ attention is drawn in the direction of greening the analytical methodologies and taking the Green Analytical Chemistry principles (GAC) into consideration. It is of high importance to appraise the environmental impact of each of the implemented green approaches. Compared to the other traditional green metrics (E-factor, Atom economy and the process profile), the eco scale is the optimum choice to assess the environmental impact of the analytical procedures used for pharmaceuticals analysis. For analytical methodologies, Eco-Scale is calculated by allotting penalty points to any factor of the used analytical procedure which disagree and not match with the model green analysis, where the perfect green analysis has its Eco-Scale value of 100. In this work, calculation and comparison of the Eco-Scale for some of the reported green analytical methods was done, to accentuate their greening potentials. Where the different scores can reveal how green the method is, compared to the ideal value. The study emphasizes that greenness measurement is not only about the waste quantity determination but also dictates a holistic scheme, considering all factors.

Keywords: eco scale, green analysis, environmentally friendly, pharmaceuticals analysis

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Authors: Olalekan Bamidele Aruleba

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This research assessed the impact of manpower training and development in the construction industry. The aim is to determine the effect of training and development on employees for effective organizational growth in the construction industry to identify the training method for each category of employee in the construction industry, challenges to training and development of workers in the construction industry and impact of manpower training and development on employees and employers. Data for the study were obtained through a well-structured questionnaire administered to building professionals in Nigeria construction firm. Eighty (80) questionnaires were distributed among building professionals in three selected local governments within Ondo State and sixty-four (64) were returned. Data collected were analysed using descriptive statistics and ranking. Findings of the study revealed that in house training and in-service training methods were preferred by most construction industry. It concluded that the attitude of top management and lack of fund was seen as the significant challenges militating against training of employees. The study recommended that manpower training and development must be sustained by all stakeholders in the industry in order to improve workers' productivity; the organization should adopt the right method in training each category of employees and carry out the need assessment for training to avoid training wrong employees.

Keywords: construction, development, manpower, training

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Authors: Mikhail Sandzhiev

Abstract:

The monitoring of metal pollution in environmental waters is crucial for the protection of ecosystems, human health and agricultural activities. Traditional laboratory-based metal analysis methods are time-consuming and expensive, which often leads to delays in the availability of information. This study presents an approach to real-time water quality monitoring using portable X-ray fluorescence (p-XRF) technology coupled with geographic information systems (GIS). Using a custom Python script, p-XRF data is processed and formatted into a GIS-compatible format, facilitating spatial visualization of metal concentrations in ǪGIS. Field-usable filters, especially bisphosphonate-functionalized thermally carbonized porous silicon (BP-TCPSi), preformed metals such as Mn, Ni, Cu, Zn, and Pb allow direct detection in the field by using p-XRF. Key objectives include robust data collection, spatial visualization and validation processes to ensure accuracy and efficiency. This provides quick and efficient insights into metal contamination trends and allows proactive decision-making.

Keywords: metal concentrations, predictive mapping, environmental monitoring, environmental waters

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Authors: Eyup Dogan

Abstract:

This empirical aims to analyze the impacts of real income and biomass energy consumption on the level of emissions in the EKC model for the panel of biomass-consuming countries over the period 1980-2011. Because we detect the presence of cross-sectional dependence and heterogeneity across countries for the analyzed data, we use panel estimation methods robust to cross-sectional dependence and heterogeneity. The CADF and the CIPS panel unit root tests indicate that carbon emissions, real income and biomass energy consumption are stationary at the first-differences. The LM bootstrap panel cointegration test shows that the analyzed variables are cointegrated. Results from the panel group-mean DOLS and the panel group-mean FMOLS estimators show that increase in biomass energy consumption decreases CO2 emissions and the EKC hypothesis is validated. Therefore, countries are advised to boost their production and increase the use of biomass energy for lower level of emissions.

Keywords: biomass energy, CO2 emissions, EKC model, heterogeneity, cross-sectional dependence

Procedia PDF Downloads 298

Authors: Tahany W. Sadak, Fouly, A. Anwer, M. Rizk

Abstract:

The current investigation presents a study on the hydraulic performance of an electro-hydraulic servo solenoid valve controlled linear piston used in hydraulic systems. Advanced methods have been used to measure and record laboratory experiments, to ensure accurate analysis and evaluation. Experiments have been conducted under different values of temperature (28, 40 and 50 °C), supply pressure (10, 20, 30, 40 and 50 bar), system stiffness (32 N/mm), and load (0.0 & 5560 N). It is concluded that increasing temperature of hydraulic oil increases the quantity of flow rate, so it achieves an increase of the quantity of flow by 5.75 % up to 48.8 % depending on operating conditions. The values of pressure decay at low temperature are less than the values at high temperature. The frequency increases with the increase of the temperature. When we connect the springs to the system, it decreases system frequency. These results are very useful in the process of packing and manufacturing of fluid products, where the properties are not affected by 50 °C, so energy and time are saved.

Keywords: electro-hydraulic servo valve, fluid power control system, system stiffness, static and dynamic performance

Procedia PDF Downloads 157