Search results for: learning physical

Authors: N. Bouhamou, F. Mostefa, A. Mebrouki, N. Belas

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Every year, millions of cube meters are dredged from dams and restraints as an entertaining and prevention procedure all over the world. These dredged sediments are considered as natural waste leading to an environmental, ecological and even an economical problem in their processing and deposing. Nevertheless, in the context of the sustainable development policy, a way of management is opened aiming to the valorization of sediments as a building material and particularly as a new binder that can be industrially exploited and that improve the physical, chemical and mechanical characteristics of the concrete. This study is a part of the research works realized in the civil engineering department at the university of Mostaganem (Algeria), on the impact of the dredged mud of Fergoug dam on the behaviour of self-consolidating concrete in fresh and hardened state, such as the mechanical performance of SCC and its impact on the differed deformations (shrinkage). The work aims to valorize this mud in SCC and to show eventual interactions between constituents. The results obtained presents a good perspectives in order to perform SCC based in calcined mud.

Keywords: sediment, calcination, reuse, self-consolidating concrete, fresh state, hard state, shrinkage

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Authors: Aliakbar Golshani, Armin Ramezanzad

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Tensile strength which is an important parameter of the rock for engineering applications is difficult to measure directly through physical experiment (i.e. uniaxial tensile test). Therefore, indirect experimental methods such as Brazilian test have been taken into consideration and some relations have been proposed in order to obtain the tensile strength for rocks indirectly. In this research, to calculate numerically the tensile strength for granitic rocks, Particle Flow Code in three-dimension (PFC3D) software were used. First, uniaxial compression tests were simulated and the tensile strength was determined for Inada granite (from a quarry in Kasama, Ibaraki, Japan). Then, by simulating Brazilian test condition for Inada granite, the tensile strength was indirectly calculated again. Results show that the tensile strength calculated numerically agrees well with the experimental results obtained from uniaxial tensile tests on Inada granite samples.

Keywords: numerical simulation, particle flow code, PFC, tensile strength, Brazilian Test

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Authors: Kyna Elliott

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The COVID-19 global pandemic has changed the shape, design, and delivery of education. As communities continue to fight the pandemic, research suggests the coronavirus is leaving an indelible mark on education which will last long after the pandemic has ended. Faculty and students bring more than their textbooks into the classroom. They bring their lived experiences into the classroom, and it is through these lived experiences that interactions and learning filter through. The COVID-19 pandemic has proved to be a traumatic experience for many. Leaders will need to have the tools and skills to mitigate trauma's impact on faculty and students. This presentation will explore research-based trauma-informed leadership practices, pedagogy, and mitigation strategies within secondary school environments.

Keywords: COVID-19, compassion fatigue, educational leadership, the science of trauma, trauma-informed leadership, trauma-informed pedagogy

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Authors: Terry Gomez

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This interpretive phenomenological qualitative study explored potential risks related to infant mental health with parental smartphone use while caring for infants. Data were collected through nine online interviews of first-time parents with infants under one-year-old. All parents reported using their smartphone during child-bonding activities such as playtime, feeding, and sleep-time. Results indicated that smartphone distractions appear to influence the synchrony of parent-child interactions. Infants displayed physical, verbal, or emotional reactions to parents’ smartphone distractions, indicating that smartphone use influences infants’ behaviors. Parents shared information on how smartphones helped them with their transition into parenthood. The findings of this study provide insights helpful to inform infant mental health professionals and parents about potential developmental consequences associated with parental technoference and absent presence.

Keywords: absent presence, infant mental health, parental distractions, smartphones, technoference

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Authors: Luís Felipe da Cunha Mendonça

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Normally, rural roads do not have any type of coating, and when they have any coating, they have a high maintenance cost due to the characteristics of natural materials. The Steel Aggregate has specific technical characteristics, which considerably reduce the maintenance costs of rural roads with the execution of the Primary Coating. For use as a primary coating, it must be mixed with clay due to the physical-chemical properties of the material. The application is mainly in the Primary Coating of rural roads due to the cementitious property in the presence of water, offering greater resistance to wear caused by traffic and consequently a longer useful life of the coating. The Steel Aggregate executed on rural roads has reduced particulate emissions and offers normal traffic in any weather condition, as well as creating sustainability. Contribute to the quality of life of communities through improvements in the conditions of rural and urban unpaved roads. Leading to substantial savings in maintenance. Because the durability, if applied correctly, is about 3 years, but if annual monitoring is carried out, it can be extended for more than 5 years.

Keywords: steel slag, co-product, primary coating, steel aggregate

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Authors: Jaiden X. Schraut

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Medical Imaging Segmentation of Chest X-rays is used for the purpose of identification and differentiation of lung cancer, pneumonia, COVID-19, and similar respiratory diseases. Widespread application of computer-supported perception methods into the diagnostic pipeline has been demonstrated to increase prognostic accuracy and aid doctors in efficiently treating patients. Modern models attempt the task of segmentation and classification separately and improve diagnostic efficiency; however, to further enhance this process, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional CNN module for auxiliary classification output. The proposed model achieves a final Jaccard Index of .9634 for image segmentation and a final accuracy of .9600 for classification on the COVID-19 radiography database.

Keywords: chest X-ray, deep learning, image segmentation, image classification

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Authors: Amira A. Alshowkan, Aleya M. Gamal

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Background: Patient safety is a vital element in providing high quality health care. In psychiatric wards, numerous of physical and emotional factors have been found to affect patient safety. In addition, organization, healthcare provider and patients were identified to be significant factors in patient safety. Aim: This study aims to discover nurses' perception of patient safety in psychiatric wards in Saudi Arabian. Method: Date will be collected through semi-structure face to face interview with nurses who are working at psychiatric wards. Data will be analysed thought the used of thematic analysis. Results: The results of this study will help in understanding the psychiatric nurses' perception of patient safety in Saudi Arabia. Several suggestions will be recommended for formulation of policies and strategies for psychiatric wards. In addition, recommendation to nursing education and training will be tailored in order to improve patient safety culture.

Keywords: patient safety culture, psychiatric, qualitative, Saudi Arabia

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Authors: Sławomir Lasota, Tomasz Kajdanowicz

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This paper delves into adapting the Tweeting Factory paradigm to achieve universal production optimization under the Industry 5.0 framework. The proposed system creates a dynamic decision-making environment by collecting and analyzing structured telemetry data (”tweets”) from production lines. A hybrid recommendation engine combines rule-based systems with machine learning models to enhance real-time responsiveness and operator engagement. The research evaluates the system’s ability to optimize diverse industrial processes through predictive KPIs and real-time feedback loops. Results indicate significant advancements in eco-efficiency and operator productivity, showcasing the versatility of the Tweeting Factory approach in meeting the demands of human-centric and sustainable production.

Keywords: tweeting factory, production optimization, industry 5.0, recommendation

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Authors: Shaleeza Sohail

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Self, and peer evaluations are some of the main components in almost all group assignments and projects in higher education institutes. These evaluations provide students an opportunity to better understand the learning outcomes of the assignment and/or project. A number of online systems have been developed for this purpose that provides automated assessment and feedback of students’ contribution in a group environment based on self and peer evaluations. All these systems lack a progressive aspect of these assessments and feedbacks which is the most crucial factor for ongoing improvement and life-long learning. In addition, a number of assignments and projects are designed in a manner that smaller or initial assessment components lead to a final assignment or project. In such cases, the evaluation and feedback may provide students an insight into their performance as a group member for a particular component after the submission. Ideally, it should also create an opportunity to improve for next assessment component as well. Self and Peer Progressive Assessment and Feedback System encourages students to perform better in the next assessment by providing a comparative analysis of the individual’s contribution score on an ongoing basis. Hence, the student sees the change in their own contribution scores during the complete project based on smaller assessment components. Self-Assessment Factor is calculated as an indicator of how close the self-perception of the student’s own contribution is to the perceived contribution of that student by other members of the group. Peer-Assessment Factor is calculated to compare the perception of one student’s contribution as compared to the average value of the group. Our system also provides a Group Coherence Factor which shows collectively how group members contribute to the final submission. This feedback is provided for students and teachers to visualize the consistency of members’ contribution perceived by its group members. Teachers can use these factors to judge the individual contributions of the group members in the combined tasks and allocate marks/grades accordingly. This factor is shown to students for all groups undertaking same assessment, so the group members can comparatively analyze the efficiency of their group as compared to other groups. Our System provides flexibility to the instructors for generating their own customized criteria for self and peer evaluations based on the requirements of the assignment. Students evaluate their own and other group members’ contributions on the scale from significantly higher to significantly lower. The preliminary testing of the prototype system is done with a set of predefined cases to explicitly show the relation of system feedback factors to the case studies. The results show that such progressive feedback to students can be used to motivate self-improvement and enhanced team skills. The comparative group coherence can promote a better understanding of the group dynamics in order to improve team unity and fair division of team tasks.

Keywords: effective group work, improvement of team skills, progressive feedback, self and peer assessment system

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Authors: Aakriti Chetan Shah, Elle Sein

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Background/purpose: Group B Streptococcus(GBS) is the leading cause of severe early onset infection in newborns, with the incidence of Early Onset Group B Streptococcus (EOGBS) in the UK and Ireland rising from 0.48 to 0.57 per 1000 births from 2000 to 2015. A WHO study conducted in 2017, has shown that 38.5% of cases can result in stillbirth and infant deaths. This is an important problem to consider as 20% of women worldwide have GBS colonisation and can suffer from these detrimental effects. Current Royal College of Obstetricians and Midwives (RCOG) guidelines do not recommend bacteriological screening for pregnant women due to its low sensitivity in antenatal screening correlating with the neonate having GBS but advise a patient information leaflet be given to pregnant women. However, a Healthcare Safety Investigation Branch (HSIB) 2019 learning report found that only 50% of trusts and health boards reported giving GBS information leaflets to all pregnant mothers. Therefore, this audit aimed to assess current practices of information dissemination about GBS at Chelsea & Westminster (C&W) Hospital. Methodology: A quantitative cross-sectional study was carried out using a questionnaire based on the RCOG GBS guidelines and the HSIB Learning report. The study was conducted in antenatal clinics at Chelsea & Westminster Hospital, from 29th January 2021 to 14th February 2021, with twenty-two practicing obstetricians and midwives participating in the survey. The main outcome measure was the proportion of obstetricians and midwives who disseminate information about GBS to pregnant women, and the reasons behind why they do or do not. Results: 22 obstetricians and midwives responded with 18 complete responses. Of which 12 were obstetricians and 6 were midwives. Only 17% of clinical staff routinely inform all pregnant women about GBS, and do so at varying timeframes of the pregnancy, with an equal split in the first, second and third trimester. The primary reason for not informing women about GBS was influenced by three key factors: Deemed relevant only for patients at high risk of GBS, lack of time in clinic appointments and no routine NHS screening available. Interestingly 58% of staff in the antenatal clinic believe it is necessary to inform all women about GBS and its importance. Conclusion: It is vital for obstetricians and midwives to inform all pregnant women about GBS due to the high prevalence of incidental carriers in the population, and the harmful effects it can cause for neonates. Even though most clinicians believe it is important to inform all pregnant women about GBS, most do not. To ensure that RCOG and HSIB recommendations are followed, we recommend that women should be given this information at 28 weeks gestation in the antenatal clinic. Proposed implementations include an information leaflet to be incorporated into the Mum and Baby app, an informative video and end-to-end digital clinic documentation to include this information sharing prompt.

Keywords: group B Streptococcus, early onset sepsis, Antenatal care, Neonatal morbidity, GBS

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Authors: Rapelang E. Simon, Thebeetsile A. Olebetse, Joseph R. Maritinkole, Ruth O. Moleleke

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The P and S wave seismic velocity ratios (Vp/Vs) of some aftershocks are investigated using the method ofWadati diagrams. These aftershocks occurred after the 3rdApril 2017 Botswana’s Mw 6.5 earthquake and were recorded by the Network of Autonomously Recording Seismographs (NARS)-Botswana temporary network deployed from 2013 to 2018. In this paper, P and S wave data with good signal-to-noise ratiofrom twenty events of local magnitude greater or equal to 4.0are analysed with the Seisan software and used to infer properties of the upper crust in Botswana. The Vp/Vsratiosare determined from the travel-times of body waves and then converted to Poisson’s ratio, which is useful in determining the physical state of the subsurface materials. The Vp/Vs ratios of the upper crust in Botswana show regional variations from 1.70 to 1.77, with an average of 1.73. The Poisson’s ratios range from 0.24to 0.27 with an average of 0.25 and correlate well with the geological structures in Botswana.

Keywords: Botswana, earthquake, poisson's ratio, seismic velocity, Vp/Vs ratio

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Authors: Tina Abrefa-Gyan

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Background: In Ghana and the rest of sub-Saharan Africa, HIV/AIDS is a public health threat and also causes medical crises for many who are infected with the virus. Objective: This study tested a social care intervention developed to help improve the quality of life of those living with HIV/AIDS in Ghana. Method: Adult respondents (N = 248) were assigned to receive the intervention or usual care for six weeks. Results: Results of the study revealed significant differences between the treatment and control groups in their reports of quality of life. Respondents reported better quality of life upon receiving the intervention. Implication: This study sheds light on the positive relationship between the intervention and quality of life among those living with HIV/AIDS in Ghana. Conclusion: The intervention is innovative and novel in the setting. It will, therefore, help to reduce the risks such as depression, low cognitive functioning, and low physical functioning associated with low quality of life among people living with HIV/AIDS in Ghana in specific, and in sub-Saharan Africa in general.

Keywords: social care intervention, HIV/AIDS, Ghana, quality of life

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Authors: Troels Bo Jørgensen, Preben Hagh Strunge Holm, Henrik Gordon Petersen, Norbert Kruger

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This paper presents a simulation framework for using machine learning techniques to determine robust robotic motions for handling deformable objects. The main focus is on applications in the meat sector, which mainly handle three-dimensional objects. In order to optimize the robotic handling, the robot motions have been parameterized in terms of grasp points, robot trajectory and robot speed. The motions are evaluated based on a dynamic simulation environment for robotic control of deformable objects. The evaluation indicates certain parameter setups, which produce robust motions in the simulated environment, and based on a visual analysis indicate satisfactory solutions for a real world system.

Keywords: deformable objects, robotic manipulation, simulation, real world system

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Authors: Nguyen J. M., Lucas G., Ruan S., Digonnet H., Antonioli D.

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Introduction: Deep Learning (DL) is a very powerful tool for analyzing image data. But for tabular data, it cannot compete with machine learning methods like XGBoost. The research question becomes: can tabular data be transformed into images that can be analyzed by simple CNNs (Convolutional Neuron Networks)? Will DL be the absolute tool for data classification? All current solutions consist in repositioning the variables in a 2x2 matrix using their correlation proximity. In doing so, it obtains an image whose pixels are the variables. We implement a technology, DeepNIC, that offers the possibility of obtaining an image for each variable, which can be analyzed by simple CNNs. Material and method: The 'ROP' (Regression OPtimized) model is a binary and atypical decision tree whose nodes are managed by a new artificial neuron, the Neurop. By positioning an artificial neuron in each node of the decision trees, it is possible to make an adjustment on a theoretically infinite number of variables at each node. From this new decision tree whose nodes are artificial neurons, we created the concept of a 'Random Forest of Perfect Trees' (RFPT), which disobeys Breiman's concepts by assembling very large numbers of small trees with no classification errors. From the results of the RFPT, we developed a family of 10 statistical information criteria, Nguyen Information Criterion (NICs), which evaluates in 3 dimensions the predictive quality of a variable: Performance, Complexity and Multiplicity of solution. A NIC is a probability that can be transformed into a grey level. The value of a NIC depends essentially on 2 super parameters used in Neurops. By varying these 2 super parameters, we obtain a 2x2 matrix of probabilities for each NIC. We can combine these 10 NICs with the functions AND, OR, and XOR. The total number of combinations is greater than 100,000. In total, we obtain for each variable an image of at least 1166x1167 pixels. The intensity of the pixels is proportional to the probability of the associated NIC. The color depends on the associated NIC. This image actually contains considerable information about the ability of the variable to make the prediction of Y, depending on the presence or absence of other variables. A basic CNNs model was trained for supervised classification. Results: The first results are impressive. Using the GSE22513 public data (Omic data set of markers of Taxane Sensitivity in Breast Cancer), DEEPNic outperformed other statistical methods, including XGBoost. We still need to generalize the comparison on several databases. Conclusion: The ability to transform any tabular variable into an image offers the possibility of merging image and tabular information in the same format. This opens up great perspectives in the analysis of metadata.

Keywords: tabular data, CNNs, NICs, DeepNICs, random forest of perfect trees, classification

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Authors: Belkacem Benadda, Adil Benabdellah, Boutheyna Souna

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The Internet of Things (IoT) is an unprecedented creation. Electronics objects are now able to interact, share, respond and adapt to their environment on a much larger basis. Actual spread of these modern means of connectivity and solutions with high data volume exchange are affecting our ways of life. Accommodation is becoming an intelligent living space, not only suited to the people circumstances and desires, but also to systems constraints to make daily life simpler, cheaper, increase possibilities and achieve a higher level of services and luxury. In this paper we are as Internet access, teleworking, consumption monitoring, information search, etc.). This paper addresses the design and integration of a smart home, it also purposes an IoT solution that allows smart power consumption based on measurements from power-grid and deep learning analysis.

Keywords: array sensors, IoT, power grid, FPGA, embedded

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Authors: Xiaohui Wang, Zhichuan Guan, Roman Shor, Chuanbin Xu

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Early monitoring and real-time quantitative description of gas intrusion under the premise of ensuring the integrity of the drilling fluid circulation system will greatly improve the accuracy and effectiveness of deepwater gas-kick monitoring. Therefore, in order to study the propagation characteristics of ultrasonic waves in the gas-liquid two-phase flow within the marine riser, in this paper, a numerical simulation method of ultrasonic propagation in the annulus of the riser was established, and the credibility of the numerical analysis was verified by the experimental results of the established gas intrusion monitoring simulation experimental device. The numerical simulation can solve the sound field in the gas-liquid two-phase flow according to different physical models, and it is easier to realize the single factor control. The influence of each parameter on the received signal can be quantitatively investigated, and the law with practical guiding significance can be obtained.

Keywords: gas-kick detection, ultrasonic, void fraction, coda wave velocity

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Authors: Soha Saad, Jean Bigeon, Florence Ossart, Etienne Sourdille

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Developing better solutions for train rescheduling problems has been drawing the attention of researchers for decades. Most researches in this field deal with minor incidents that affect a large number of trains due to cascading effects. They focus on timetables, rolling stock and crew duties, but do not take into account infrastructure limits. The present work addresses electric infrastructure incidents that limit the power available for train traction, and hence the transportation capacity of the railway system. Rescheduling is needed in order to optimally share the available power among the different trains. We propose a rescheduling process based on dynamic multiphysics railway simulations that include the mechanical and electrical properties of all the system components and calculate physical quantities such as the train speed profiles, voltage along the catenary lines, temperatures, etc. The optimization problem to solve has a large number of continuous and discrete variables, several output constraints due to physical limitations of the system, and a high computation cost. Our approach includes a phase of sensitivity analysis in order to analyze the behavior of the system and help the decision making process and/or more precise optimization. This approach is a quantitative method based on simulation statistics of the dynamic railway system, considering a predefined range of variation of the input parameters. Three important settings are defined. Factor prioritization detects the input variables that contribute the most to the outputs variation. Then, factor fixing allows calibrating the input variables which do not influence the outputs. Lastly, factor mapping is used to study which ranges of input values lead to model realizations that correspond to feasible solutions according to defined criteria or objectives. Generalized Sobol indexes are used for factor prioritization and factor fixing. The approach is tested in the case of a simple railway system, with a nominal traffic running on a single track line. The considered incident is the loss of a feeding power substation, which limits the power available and the train speed. Rescheduling is needed and the variables to be adjusted are the trains departure times, train speed reduction at a given position and the number of trains (cancellation of some trains if needed). The results show that the spacing between train departure times is the most critical variable, contributing to more than 50% of the variation of the model outputs. In addition, we identify the reduced range of variation of this variable which guarantees that the output constraints are respected. Optimal solutions are extracted, according to different potential objectives: minimizing the traveling time, the train delays, the traction energy, etc. Pareto front is also built.

Keywords: optimization, rescheduling, railway system, sensitivity analysis, train timetable

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Authors: Violeta Juanico

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While there was a statement made by the RVM Education Ministry Commission that its strength is its Ignacian identity, shaped by the Ignacian spirituality that permeates the school community leading to a more defined RVM school culture, there has been no empirical study made in terms of a clear and convincing conceptual framework on how the RVM Educational mission is lived in the Religious of the Virgin Mary (RVM) learning institutions to the best of author’s knowledge. This dissertation is an attempt to come up with a substantive theory that supports and explains the stakeholders’ experiences with the RVM educational mission in the Philippines. Participants that represent the different stakeholders ranging from students to administrators were interviewed. The expressions and thoughts of the participants were initially coded and analyzed using the Barney Glaser’s original grounded theory methodology to find out how the RVM mission is lived in the field of education.

Keywords: catholic education, grounded theory, lived experience, RVM educational mission

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Authors: Nada Souissi, Mourad Mroua

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The main purpose of this study is to examine the interaction between financial asset volatility, economic factors and investor's behavioral indicators related to both the company's and the markets stocks for the period from January 2000 to January2020. Using multiple linear regression and Bayesian Networks modeling, results show a positive and negative relationship between investor's psychology index, economic factors and predicted stock market return. We reveal that the application of the Bayesian Discrete Network contributes to identify the different cause and effect relationships between all economic, financial variables and psychology index.

Keywords: Financial asset return predictability, Economic factors, Investor's psychology index, Bayesian approach, Probabilistic networks, Parametric learning

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Authors: Hikmet Cicek

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Transition metal nitrides are widely used as protective coatings on machine parts and cutting tools to protect the surfaces from abrasion and corrosion for decades. In this study, the ternary TiNbVN thin coatings were produced with closed field unbalanced magnetron sputtering system and their structural, mechanical and fatigue-like (multi-pass scratch test) properties were investigated. Two different substrates (M2 and H13 steels) were used to explore substrates effects. X-Ray diffractometer, scanning electron microscope, and energy dispersive spectroscopy were used for the structural and chemical analysis of the coatings. Nanohardness tests were proceed for mechanical properties. The fatigue-like properties of the coatings obtained from the multi-scratch test under three different cycle passes. The results showed that TiNbVN films have excellent fatigue resistance and the coatings deposited on M2 steel substrate have higher hardness and better fatigue resistance.

Keywords: physical vapor deposition, fatigue, metal nitride, multipass scratch test

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Authors: Shah Muhammad Butt, Ahmed Masaud Ansari

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Present Financial crisis in Higher Educational Institutes (HEIs) facing lots of problems considerable budget cuts, make difficult to meet the ever growing IT-based research and learning needs, institutions are rapidly planning and promoting cloud-based approaches for their academic and research needs. A cost effective Hybrid Cloud framework for HEI’s will provide educational services for campus or intercampus communication. Hybrid Cloud Framework comprises Private and Public Cloud approaches. This paper will propose the framework based on the Open Source Cloud (OpenNebula for Virtualization, Eucalyptus for Infrastructure, and Aneka for programming development environment) combined with CSP’s services which are delivered to the end-user via the Internet from public clouds.

Keywords: educational services, hybrid campus cloud, open source, electrical and systems sciences

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Authors: B. Siva Kumar Reddy, B. Lakshmi

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Cognitive Radio is a turning out technology that empowers viable usage of the spectrum. Energy Detector-based Sensing is the most broadly utilized spectrum sensing strategy. Besides, it is a lot of generic as receivers does not like any information on the primary user's signals, channel data, of even the sort of modulation. This paper puts forth the execution of energy detection sensing for AM (Amplitude Modulated) signal at 710 KHz, FM (Frequency Modulated) signal at 103.45 MHz (local station frequency), Wi-Fi signal at 2.4 GHz and WiMAX signals at 6 GHz. The OFDM/OFDMA based WiMAX physical layer with convolutional channel coding is actualized utilizing USRP N210 (Universal Software Radio Peripheral) and GNU Radio based Software Defined Radio (SDR). Test outcomes demonstrated the BER (Bit Error Rate) augmentation with channel noise and BER execution is dissected for different Eb/N0 (the energy per bit to noise power spectral density ratio) values.

Keywords: BER, Cognitive Radio, GNU Radio, OFDM, SDR, WiMAX

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Authors: C. Gebauer, C. Henke, R. Vossen

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Within the Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2020, a team of unmanned aerial vehicles (UAV) is used to capture intruder drones by physical interaction. The challenge is motivated by UAV safety. The purpose of this work is to investigate the agility of a quadcopter being controlled visually. The aim is to track and follow a highly dynamic target, e.g., an intruder quadcopter. The following is realized in close range and the opponent has a velocity of up to 10 m/s. Additional limitations are given by the hardware itself, where only monocular vision is present, and no additional knowledge about the targets state is available. An image based visual servoing (IBVS) approach is applied in combination with a Linear Quadratic Regulator (LQR). The IBVS is integrated into the LQR and an optimal trajectory is computed within the projected three-dimensional image-space. The approach has been evaluated on real quadcopter systems in different flight scenarios to demonstrate the system's stability.

Keywords: image based visual servoing, quadcopter, dynamic object tracking, linear-quadratic regulator

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Authors: Pengchao Wei, Xiangzhong Fang

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Noise is ubiquitous in this world. Denoising is an essential technology, especially in image semantic segmentation, where noises are generally categorized into two main types i.e. feature noise and label noise. The main focus of this paper is aiming at modeling label noise, investigating the behaviors of different types of label noise on image semantic segmentation tasks using K-Nearest-Neighbor and Convolutional Neural Network classifier. The performance without label noise and with is evaluated and illustrated in this paper. In addition to that, the influence of feature noise on the image semantic segmentation task is researched as well and a feature noise reduction method is applied to mitigate its influence in the learning procedure.

Keywords: convolutional neural network, denoising, feature noise, image semantic segmentation, k-nearest-neighbor, label noise

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Authors: George Clifford Yamson

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As institutions across the world become more focused on sustainability, academic libraries are considering ways to reduce their environmental impact. One strategy is the use of sustainable online services, which can reduce the need for physical materials and transportation. This study aims to analyze the effectiveness of sustainable online services in reducing the environmental impact of academic libraries. Using a mixed-methods approach, the survey will be used to solicit information from library staff and users to gather data on their attitudes towards sustainable online services and their usage patterns. A comparative analysis will be conducted on the costs of traditional library services versus sustainable online services. The findings of this study will contribute to the growing body of literature on green academic libraries and provide insights into the potential of sustainable online services to reduce the environmental impact of academic libraries.

Keywords: sustainability, environmental sustainability, academic libraries, green printing, green copying, online services

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Authors: Qiuyu Dai, Haochong Zhang, Xiangrong Liu

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Diagonal sparse matrix-vector multiplication is a well-studied topic in the fields of scientific computing and big data processing. However, when diagonal sparse matrices are stored in DIA format, there can be a significant number of padded zero elements and scattered points, which can lead to a degradation in the performance of the current DIA kernel. This can also lead to excessive consumption of computational and memory resources. In order to address these issues, the authors propose the DIA-Adaptive scheme and its kernel, which leverages the parallel instruction sets on MLU. The researchers analyze the effect of allocating a varying number of threads, clusters, and hardware architectures on the performance of SpMV using different formats. The experimental results indicate that the proposed DIA-Adaptive scheme performs well and offers excellent parallelism.

Keywords: adaptive method, DIA, diagonal sparse matrices, MLU, sparse matrix-vector multiplication

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Authors: Fabrizio Logiurato

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Light Polarization has many technological applications, and its discovery was crucial to reveal the transverse nature of the electromagnetic waves. However, despite its fundamental and practical importance, in high school, this property of light is often neglected. This is a pity not only for its conceptual relevance, but also because polarization gives the possibility to perform many brilliant experiments with low cost materials. Moreover, the treatment of this matter lends very well to an interdisciplinary approach between art, biology and technology, which usually makes things more interesting to students. For these reasons, we have developed, and in this work, we introduce a laboratory on light polarization for high school and undergraduate students. They can see beautiful pictures when birefringent materials are set between two crossed polarizing filters. Pupils are very fascinated and drawn into by what they observe. The colourful images remind them of those ones of abstract painting or alien landscapes. With this multidisciplinary teaching method, students are more engaged and participative, and also, the learning process of the respective physics concepts is more effective.

Keywords: light polarization, optical activity, multidisciplinary education, science and art

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Authors: Ashenafi Sileshi Etefa, Bezawit Worku Yenealem

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Micro-insurance is a relatively new concept that is just being introduced in Ethiopia. For an agrarian economy dominated by small holder farming and vulnerable to natural disasters, mainly drought, the need for an Index-Based Micro Insurance (IBMI) is crucial. Since IBMI solves moral hazard, adverse selection, and access issues to poor clients, it is preferable over traditional insurance products. IBMI is being piloted in drought prone areas of Ethiopia with the aim of learning and expanding the service across the country. This article analyses the demand of IBMI and the barriers to demand and finds that the demand for IBMI has so far been constrained by lack of awareness, trust issues, costliness, and the level of basis risk; and recommends reducing the basis risk and increasing the role of government and farmer cooperatives.

Keywords: agriculture, index based micro-insurance (IBMI), drought, micro-finance institution (MFI)

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Authors: Aadya Kaktikar

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The role of a traditional dance teacher in India revolves around teaching movements and postures that have been a part of the movement vocabulary of dancers from before the 2nd century BC. These movements inscribe on the mind and body of the dancer a complex web of philosophy, culture history, and religion. However, this repository of tradition sits in a fast globalizing India creating a cultural space which is in a constant flux, where identities and meanings are being constantly challenged. The guru-shishya parampara, the traditional way of learning dance, sits uneasily with a modern education space in India. The traditional dance teacher is caught in the cross-currents of tradition and modernity, of preservation and exploration. This paper explores conflicting views on what dance ought to mean and how it should be taught. The paper explores the tensions of the social, economic and cultural spaces that the traditional dance teacher navigates.

Keywords: pedagogy, dance education, dance curriculum, teacher training

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Authors: Geetishree Mishra, S. Akhila

Abstract:

Embedded System Design, the most challenging course of electronics engineering has always been appreciated and well acclaimed by the students of electronics and its related branches of engineering. Embedded system, being a product of multiple application domains, necessitates skilled man power to be well designed and tested in every important aspect of both hardware and software. In the current industrial scenario, the requirements are even more rigorous and highly demanding and needs to be to be on par with the advanced technologies. Fresh engineers are expected to be thoroughly groomed by the academic system and the teaching community. Graduates with the ability to understand both complex technological processes and technical skills are increasingly sought after in today's embedded industry. So, the need of the day is to restructure the under-graduate course- both theory and lab practice along with the teaching methodologies to meet the industrial requirements. This paper focuses on the importance of such a need in the present education system.

Keywords: embedded system design, industry requirement, syllabus restructuring, project-based learning, teaching methodology

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