Search results for: Time difference of Arrival (TDOA)

Authors: Ana C. R. P. Ferreira, Adriano H. P. Pereira

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Given the frequent variation of mineral properties throughout the Araxá pyrochlore deposit, even if a good homogenization work has been carried out before feeding the processing plants, an operation with quality and performance’s high variety standard is expected. These results could be improved and standardized if the blend composition parameters that most influence the processing route are determined, and then the types of raw materials are grouped by them, finally presenting a great reference with operational settings for each group. Associating the physical and chemical parameters of a unit operation through benchmarking or even an optimal reference of metallurgical recovery and product quality reflects in the reduction of the production costs, optimization of the mineral resource, and guarantee of greater stability in the subsequent processes of the production chain that uses the mineral of interest. Conducting a comprehensive exploratory data analysis to identify which characteristics of the ore are most relevant to the process route, associated with the use of Machine Learning algorithms for grouping the raw material (ore) and associating these with reference variables in the process’ benchmark is a reasonable alternative for the standardization and improvement of mineral processing units. Clustering methods through Decision Tree and K-Means were employed, associated with algorithms based on the theory of benchmarking, with criteria defined by the process team in order to reference the best adjustments for processing the ore piles of each cluster. A clean user interface was created to obtain the outputs of the created algorithm. The results were measured through the average time of adjustment and stabilization of the process after a new pile of homogenized ore enters the plant, as well as the average time needed to achieve the best processing result. Direct gains from the metallurgical recovery of the process were also measured. The results were promising, with a reduction in the adjustment time and stabilization when starting the processing of a new ore pile, as well as reaching the benchmark. Also noteworthy are the gains in metallurgical recovery, which reflect a significant saving in ore consumption and a consequent reduction in production costs, hence a more rational use of the tailings dams and life optimization of the mineral deposit.

Keywords: mineral clustering, machine learning, process optimization, pyrochlore processing

Procedia PDF Downloads 138

Authors: Sofiene Amara, Mohamed Ali Bahri, Sabri Gaied Chortane

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The purpose of this study was to examine the effect of personal goal setting on psychological parameters (cognitive anxiety, somatic anxiety, and self-confidence) and the 50m freestyle performance. 30 young swimmers participated in this investigation, and was divided into three groups, the first group (G1, n = 10, 14 ± 0.7 years old) was prepared for the competition without a fixed target (method 1), the second group (G2, n = 10, 14 ± 0.9 years old) was oriented towards a vague goal 'Do your best' (method 2), while the third group (G3, n = 10, 14 ± 0, 5 years old) was invited to answer a goal that is difficult to reach according to a goal-setting interval (GST) (method 3). According to the statistical data of the present investigation, the cognitive and somatic anxiety scores in G1 and G3 were higher than in G2 (G1-G2, G3-G2: cognitive anxiety, P = 0.000, somatic anxiety: P = 0.000 respectively). On the other hand, the self-confidence score was lower in G1 compared with the other two groups (G1-G2, G3-G2: P = 0.02, P = 0.03 respectively). Our assessment also shows that the 50m freestyle time performance was improved better by method 3 (pre and post-Test: P = 0.006, -2.5sec, 7.83%), than by method 2 (pre and Post-Test: P = 0.03; -1sec; 3.24%), while, performance remained unchanged in G1 (P > 0.05). To conclude, the setting of a difficult goal by GST is more effective to improve the chronometric performance in the 50m freestyle, but at the same time increased the values ​​of the cognitive and somatic anxiety. For this, the mental trainers and the staff technical, invited to develop models of mental preparation associated with this method of setting a goal to help swimmers on the psychological level.

Keywords: cognitive anxiety, goal setting, performance of swimming freestyle, self-confidence, somatic anxiety

Procedia PDF Downloads 123

Authors: Farzad Jalilian, Mehdi Mirzaei Alavijeh

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Background: E-interventions as a universal approach to prevent a high-risk behavior, such as alcohol drinking. This study was conducted to evaluate web-based alcohol drinking preventative intervention efficiency among medical university students in Iran. Methods: Overall, 150 freshman and sophomore male student’s college students participated in this study as intervention and control group. This was a longitudinal randomized pre- and post-test series control group design panel study to implement a behavior modification based intervention to alcohol drinking prevention among college students. Cross-tabulation, t-test, repeated measures, and GEE by using SPSS statistical package, version 21 was used for the statistical analysis. The participants were followed up for 6 months with data collection scheduled at baseline, 3 and 6 months. The primary outcomes are attitude, self-control, and sensation seeking. Furthermore, the secondary outcome is comparing alcohol drinking among the study groups. Results: It was found significant reduce in average response for an attitude towards alcohol drinking and sensation seeking among intervention group (P < 0.05). But after intervention not significant difference between intervention and control group of improve self-control and reduce alcohol drinking (P > 0.05). Conclusion: Our intervention has been accompanied with reducing alcohol use rate. These findings indicate that e-intervention may be effectiveness approach to address the alcohol prevention among college students.

Keywords: e-interventions, alcohol drinking, students, Iran

Procedia PDF Downloads 406

Authors: Salome Schulze

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The delay of students in completing their dissertations is a worldwide problem. At the University of South Africa where this research was done, only about a third of the students complete their studies within the required period of time. This study explored the reasons why the students interrupted their studies, and why they resumed their research at a later stage. If this knowledge could be utilised to improve the throughput of doctoral students, it could have significant economic benefits for institutions of higher education while at the same time enhancing their academic prestige. To inform the investigation, attention was given to key theories concerning the learning of doctoral students, namely the situated learning theory, the social capital theory and the self-regulated learning theory, based on the social cognitive theory of learning. Ten students in the faculty of Education were purposefully selected on the grounds of their poor progress, or of having been in the system for too long. The collection of the data was in accordance with a Finnish study, since the two studies had the same aims, namely to investigate student engagement and disengagement. Graphic elicitation interviews, based on visualisations were considered appropriate to collect the data. This method could stimulate the reflection and recall of the participants’ ‘stories’ with very little input from the interviewer. The interviewees were requested to visualise, on paper, their journeys as doctoral students from the time when they first registered. They were to indicate the significant events that occurred and which facilitated their engagement or disengagement. In the interviews that followed, they were requested to elaborate on these motivating or challenging events by explaining when and why they occurred, and what prompted them to resume their studies. The interviews were tape-recorded and transcribed verbatim. Information-rich data were obtained containing visual metaphors. The data indicated that when the students suffered a period of disengagement, it was sometimes related to a lack of self-regulated learning, in particular, a lack of autonomy, and the inability to manage their time effectively. When the students felt isolated from the academic community of practice disengagement also occurred. This included poor guidance by their supervisors, which accordingly deprived them of significant social capital. The study also revealed that situational factors at home or at work were often the main reasons for the students’ procrastinating behaviour. The students, however, remained in the system. They were motivated towards a renewed engagement with their studies if they were self-regulated learners, and if they felt a connectedness with the academic community of practice because of positive relationships with their supervisors and of participation in the activities of the community (e.g., in workshops or conferences). In support of their learning, networking with significant others who were sources of information provided the students with the necessary social capital. Generally, institutions of higher education cannot address the students’ personal issues directly, but they can deal with key institutional factors in order to improve the throughput of doctoral students. It is also suggested that graphic elicitation interviews be used more often in social research that investigates the learning and development of the students.

Keywords: doctoral students, engaging and disengaging experiences, graphic elicitation interviews, student procrastination

Procedia PDF Downloads 188

Authors: Gaurav Kumar Sinha

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The volatility of the oil market, influenced by geopolitical, economic, and environmental factors, presents significant challenges for stakeholders in predicting trends and demand. This article explores the application of artificial intelligence (AI) in developing robust forecasting models to anticipate changes in the oil market more accurately. We delve into various AI techniques, including machine learning, deep learning, and time series analysis, that have been adapted to analyze historical data and current market conditions to forecast future trends. The study evaluates the effectiveness of these models in capturing complex patterns and dependencies in market data, which traditional forecasting methods often miss. Additionally, the paper discusses the integration of external variables such as political events, economic policies, and technological advancements that influence oil prices and demand. By leveraging AI, stakeholders can achieve a more nuanced understanding of market dynamics, enabling better strategic planning and risk management. The article concludes with a discussion on the potential of AI-driven models in enhancing the predictive accuracy of oil market forecasts and their implications for global economic planning and strategic resource allocation.

Keywords: AI forecasting, oil market trends, machine learning, deep learning, time series analysis, predictive analytics, economic factors, geopolitical influence, technological advancements, strategic planning

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Authors: Jaydip M. Desai, Antonio Valdevit, Arthur Ritter

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Robotic surgery is used to enhance minimally invasive surgical procedure. It provides greater degree of freedom for surgical tools but lacks of haptic feedback system to provide sense of touch to the surgeon. Surgical robots work on master-slave operation, where user is a master and robotic arms are the slaves. Current, surgical robots provide precise control of the surgical tools, but heavily rely on visual feedback, which sometimes cause damage to the inner organs. The goal of this research was to design and develop a real-time simulink based robotic system to study force feedback mechanism during instrument-object interaction. Setup includes three Velmex XSlide assembly (XYZ Stage) for three dimensional movement, an end effector assembly for forceps, electronic circuit for four strain gages, two Novint Falcon 3D gaming controllers, microcontroller board with linear actuators, MATLAB and Simulink toolboxes. Strain gages were calibrated using Imada Digital Force Gauge device and tested with a hard-core wire to measure instrument-object interaction in the range of 0-35N. Designed simulink model successfully acquires 3D coordinates from two Novint Falcon controllers and transfer coordinates to the XYZ stage and forceps. Simulink model also reads strain gages signal through 10-bit analog to digital converter resolution of a microcontroller assembly in real time, converts voltage into force and feedback the output signals to the Novint Falcon controller for force feedback mechanism. Experimental setup allows user to change forward kinematics algorithms to achieve the best-desired movement of the XYZ stage and forceps. This project combines haptic technology with surgical robot to provide sense of touch to the user controlling forceps through machine-computer interface.

Keywords: surgical robot, haptic feedback, MATLAB, strain gage, simulink

Procedia PDF Downloads 526

Authors: Hassan Abo-Salem, Huang Xiaolin

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Background and Purpose: The effectiveness of mirror therapy (MT) has been investigated in acute hemiplegia. The present study examines whether MT, given during chronic stroke, was more effective in promoting motor recovery of the lower extremity and walking speed than standard rehabilitation alone. Methods: The study enrolled 30 patients with chronic stroke. Fifteen patients each were assigned to the treatment group and the control group. All patients received a conventional rehabilitation program for a 4-week period. In addition to this rehabilitation program, patients in the treatment group received mirror therapy for 4 weeks, 5 days a week. Main measures: Passive ankle joint dorsiflexion range of motion, gait speed, Brunnstrom stages of motor recovery, plantarflexor muscle tone by Modified Ashworth Scale. Results: Results: No significant difference was found in the outcome measures among groups before treatment. When compared with standard rehabilitation, mirror therapy improved Ankle ROM, Brunnstrom stages and waking speed (p < 0.05). However, there were no significant differences between two groups on MAS (P > 0.05). Conclusions: Mirror therapy combined with a conventional stroke rehabilitation program enhances lower-extremity motor recovery and walking speed in chronic stroke patients.

Keywords: mirror therapy, stroke, MAS, walking speed

Procedia PDF Downloads 496

Authors: Gerald Todd

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Recent advances in random epistemologies and ubiquitous theory have paved the way for web services. Given the current status of linear-time communication, cyberinformaticians compellingly desire the exploration of link-level acknowledgements. In order to realize this purpose, we concentrate our efforts on disconfirming that DHTs and model checking are mostly incompatible.

Keywords: LAN, cyberinformatics, model checking, communication

Procedia PDF Downloads 391

Authors: Bo Jin

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A variety of process equipment having flow in and out is widely used in industrial land-based cryogenic facilities. In some of this equipment, such as vapor-liquid separator, a liquid level is established during the steady operation. As the implementation of such industrial processes extends to off-shore floating facilities, it is important to investigate the effect of sea motion on the process equipment partially filled with liquid. One important aspect to consider is the occurrence of sloshing therein. The flow characteristics are different from the classical study of sloshing, where the fluid is enclosed inside a vessel (e.g., storage tank) with no flow in or out. Liquid inside process equipment continuously flows in and out of the system. To understand this key difference, a Computational Fluid Dynamics (CFD) model is developed to simulate the liquid motion inside a partially filled cylinder with and without continuous flow in and out. For a partially filled vertical cylinder without any continuous flow in and out, the CFD model is found to be able to capture the well-known sloshing behavior documented in the literature. For the cylinder with a continuous steady flow in and out, the CFD simulation results demonstrate that the continuous flow suppresses sloshing. Given typical cryogenic fluid has very low viscosity, an analysis based on potential flow theory is developed to explain why flow into and out of the cylinder changes the natural frequency of the system and thereby suppresses sloshing. This analysis further validates the CFD results.

Keywords: computational fluid dynamics, CFD, cryogenic process equipment, off-shore floating processes, sloshing

Procedia PDF Downloads 123

Authors: Ravneet Kaur

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The concept of Agile Requirements Engineering and Management is not new. However, the struggle to figure out how traditional Requirements Management Process fits within an Agile framework remains complex. This paper talks about a process that can merge the organization’s traditional Requirements Management Process nicely into the Agile Software Development Process. This process provides Traceability of the Product Backlog to the external documents on one hand and User Stories on the other hand. It also gives sufficient evidence that the system will deliver the right functionality with good quality in the form of various statistics and reports. In the nutshell, by overlaying a process on top of Agile, without disturbing the Agility, we are able to get synergic benefits in terms of productivity, profitability, its reporting, and end to end visibility to all Stakeholders. The framework can be used for just-in-time requirements definition or to build a repository of requirements for future use. The goal is to make sure that the business (specifically, the product owner) can clearly articulate what needs to be built and define what is of high quality. To accomplish this, the requirements cycle follows a Scrum-like process that mirrors the development cycle but stays two to three steps ahead. The goal is to create a process by which requirements can be thoroughly vetted, organized, and communicated in a manner that is iterative, timely, and quality-focused. Agile is quickly becoming the most popular way of developing software because it fosters continuous improvement, time-boxed development cycles, and more quickly delivering value to the end users. That value will be driven to a large extent by the quality and clarity of requirements that feed the software development process. An agile, lean, and timely approach to requirements as the starting point will help to ensure that the process is optimized.

Keywords: requirements management, Agile

Procedia PDF Downloads 362

Authors: João Madureira, Ricardo Lagido, Inês Sousa, Fraunhofer Portugal

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Surf is an increasingly popular sport and its performance evaluation is often qualitative. This work aims at using a smartphone to collect and analyze the GPS and inertial sensors data in order to obtain quantitative metrics of the surfing performance. Two approaches are compared for detection of wave rides, computing the number of waves rode in a surfing session, the starting time of each wave and its duration. The first approach is based on computing the velocity from the Global Positioning System (GPS) signal and finding the velocity thresholds that allow identifying the start and end of each wave ride. The second approach adds information from the Inertial Measurement Unit (IMU) of the smartphone, to the velocity thresholds obtained from the GPS unit, to determine the start and end of each wave ride. The two methods were evaluated using GPS and IMU data from two surfing sessions and validated with similar metrics extracted from video data collected from the beach. The second method, combining GPS and IMU data, was found to be more accurate in determining the number of waves, start time and duration. This paper shows that it is feasible to use smartphones for quantification of performance metrics during surfing. In particular, detection of the waves rode and their duration can be accurately determined using the smartphone GPS and IMU.

Keywords: inertial measurement unit (IMU), global positioning system (GPS), smartphone, surfing performance

Procedia PDF Downloads 394

Authors: Niklas Panten, Eberhard Abele

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This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.

Keywords: industrial smart grids, energy efficiency, deep reinforcement learning, optimal control

Procedia PDF Downloads 183

Authors: Daodu Joshua Rotimi

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This study investigated the Efficacy of Self-Assessment Metacognitive Strategy on Academic performance in Energy Concepts among Upper Basic Science Students in Ankpa, Kogi State, Nigeria. The research design adopted for the study was a Quasi-experimental control group design which employed a pretest, posttest of the experimental and control groups. The population of the study consisted of one hundred and twenty-four (124) JSSII Students; sixty-five (65) for the experimental group and (59) for the control group. The instrument used for the study was the Energy Concept Performance Test (ECPT), with a reliability coefficient of 0.80. Two research questions were answered using descriptive statistics of mean and standard deviation, while two hypotheses were tested using a t-test at P≤0.05 level of significance. The findings of the study revealed that the use of the Self-Assessment Metacognitive Strategy has a positive effect on students’ performance in energy concepts among upper Basic Science Students leading to high academic performance; also, there is no significant difference in the mean Academic Performance scores between Male and Female students taught Energy Concept using Self-Assessment Metacognitive Strategy. Based on the research findings, recommendations were made, which include that Secondary school teachers should be encouraged the use Self-Assessment Metacognitive strategy so as to make the learning process attractive, interactive and enriching to the learners.

Keywords: metacognition, self-assessment, performance, efficacy

Procedia PDF Downloads 113

Authors: Aderonke A. Okoya, Oluwaseun A. Somoye, Omotayo S. Amuda, Ifeanyi E. Ofoezie

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This study assessed the efficiency of Hydroxyapatite Powder (HAP) in the removal of dyes in wastewater in comparison with Commercial Activated Carbon (CAC). This was with a view to developing cost effective method that could be more environment friendly. The HAP and CAC were used as adsorbent while Indigo dye was used as the adsorbate. The batch adsorption experiment was carried out by varying initial concentrations of the indigo dye, contact time and adsorbent dosage. Adsorption efficiency was classified by adsorption Isotherms using Langmuir, Freundlich and D-R isotherm models. Physicochemical parameters of a textile industry wastewater were determined before and after treatment with the adsorbents. The results from the batch experiments showed that at initial concentration of 125 mg/L of adsorbate in simulated wastewater, 0.9276 ± 0.004618 mg/g and 3.121 ± 0.006928 mg/g of indigo adsorbed per unit time (qt) of HAP and CAC respectively. The ratio of HAP to CAC required for the removal of indigo dye in simulated wastewater was 2:1. The isotherm model of the simulated wastewater fitted well to Freundlich model, the adsorption intensity (1/n) presented 1.399 and 0.564 for HAP and CAC, respectively. This revealed that the HAP had weaker bond than the electrostatic interactions which were present in CAC. The values of some physicochemical parameters (acidity, COD, Cr, Cd) of textile wastewater when treated with HAP decreased. The study concluded that HAP, an environment-friendly adsorbent, could be effectively used to remove dye from textile industrial wastewater with added advantage of being regenerated.

Keywords: adsorption isotherm, commercial activated carbon, hydroxyapatite powder, indigo dye, textile wastewater

Procedia PDF Downloads 233

Authors: Anmol Patel

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Cardiopulmonary resuscitation is medical intervention which should be considered for all inpatients; with a patient centred approach, open communication and accurate documentation of clinical decisions. National enquiries have shown that in a significant number of cases CPR was attempted when it was considered inappropriate. In these circumstances attempting to prevent a natural death and subjecting a patient to trauma at the end of life would deprive them of a dignified death. Anticipatory “do not attempt CPR (DNACPR)” decisions aim to prevent this for those considered appropriate. As a legal document, these forms are required to be completed accurately and thoroughly. The aim of this study was to evaluate the difference in quality of DNACPR forms completed using electronic versus paper formats. A retrospective review of DNACPR forms and related documentation was completed in two District General Hospitals in South-East England, one of which uses electronic forms, while the other uses paper red forms. 50 completed forms from each hospital were analysed to assess for legibility, and quality of completion of all subsections of the form, including communications with family, relatives and the Multidisciplinary team. The hospital using paper forms showed a 40-44% rate of completion of sections relating to communication with patients and family, compared to 70% with the hospital using electronic forms. Similar trends were observed with other sections of the form. Conclusion: This study suggests that the implementation of electronic DNACPR forms significantly improves clinical practice and promotes better open communication with patients, family and the MDT.

Keywords: DNACPR, resuscitation, DNAR, patient communication

Procedia PDF Downloads 71

Authors: Krishang Surapaneni

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The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%

Keywords: finance, linear regression model, machine learning model, neural network, stock price

Procedia PDF Downloads 68

Authors: Benniche Omar

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We are concerned with abstract fully nonlinear differential equations having the form y’(t)=Ay(t)+f(t,y(t)) where A is an m—dissipative operator (possibly multi—valued) defined on a subset D(A) of a Banach space X with values in X and f is a given function defined on I×X with values in X. We consider a graph K in I×X. We recall that K is said to be viable with respect to the above abstract differential equation if for each initial data in K there exists at least one trajectory starting from that initial data and remaining in K at least for a short time. The viability problem has been studied by many authors by using various techniques and frames. If K is closed, it is shown that a tangency condition, which is mainly linked to the dynamic, is crucial for viability. In the case when X is infinite dimensional, compactness and convexity assumptions are needed. In this paper, we are concerned with the notion of near viability for a given graph K with respect to y’(t)=Ay(t)+f(t,y(t)). Roughly speaking, the graph K is said to be near viable with respect to y’(t)=Ay(t)+f(t,y(t)), if for each initial data in K there exists at least one trajectory remaining arbitrary close to K at least for short time. It is interesting to note that the near viability is equivalent to an appropriate tangency condition under mild assumptions on the dynamic. Adding natural convexity and compactness assumptions on the dynamic, we may recover the (exact) viability. Here we investigate near viability for a graph K in I×X with respect to y’(t)=Ay(t)+f(t,y(t)) where A and f are as above. We emphasis that the t—dependence on the perturbation f leads us to introduce a new tangency concept. In the base of a tangency conditions expressed in terms of that tangency concept, we formulate criteria for K to be near viable with respect to y’(t)=Ay(t)+f(t,y(t)). As application, an abstract null—controllability theorem is given.

Keywords: abstract differential equation, graph, tangency condition, viability

Procedia PDF Downloads 134

Authors: Laurie Dempsey

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Relationships are considered to be beneficial for emotional wellbeing, happiness and physical health. However, they are also complicated: individuals engage in a multitude of complex and volatile relationships during their lifetime, where the change to or ending of these dynamics can be deeply disruptive. As the internet is further integrated into everyday life and relationships are increasingly mediated, Media Studies’ and Sociology’s research interests intersect and converge. This study longitudinally explores how relationship change over time corresponds with the developing UK technological landscape between 2005-2018. Since the early 2000s, the use of computer-mediated communication (CMC) in the UK has dramatically reshaped interaction. Its use has compelled individuals to renegotiate how they consider their relationships: some argue it has allowed for vast networks to be accumulated and strengthened; others contend that it has eradicated the core values and norms associated with communication, damaging relationships. This research collaborated with UK media regulator Ofcom, utilising the longitudinal dataset from their Adult Media Lives study to explore how relationships and CMC use developed over time. This is a unique qualitative dataset covering 2005-2018, where the same 18 participants partook in annual in-home filmed depth interviews. The interviews’ raw video footage was examined year-on-year to consider how the same people changed their reported behaviour and outlooks towards their relationships, and how this coincided with CMC featuring more prominently in their everyday lives. Each interview was transcribed, thematically analysed and coded using NVivo 11 software. This study allowed for a comprehensive exploration into these individuals’ changing relationships over time, as participants grew older, experienced marriages or divorces, conceived and raised children, or lost loved ones. It found that as technology developed between 2005-2018, everyday CMC use was increasingly normalised and incorporated into relationship maintenance. It played a crucial role in altering relationship dynamics, even factoring in the breakdown of several ties. Three key relationships were identified as being shaped by CMC use: parent-child; extended family; and friendships. Over the years there were substantial instances of relationship conflict: for parents renegotiating their dynamic with their child as they tried to both restrict and encourage their child’s technology use; for estranged family members ‘forced’ together in the online sphere; and for friendships compelled to publicly display their relationship on social media, for fear of social exclusion. However, it was also evident that CMC acted as a crucial lifeline for these participants, providing opportunities to strengthen and maintain their bonds via previously unachievable means, both over time and distance. A longitudinal study of this length and nature utilising the same participants does not currently exist, thus provides crucial insight into how and why relationship dynamics alter over time. This unique and topical piece of research draws together Sociology and Media Studies, illustrating how the UK’s changing technological landscape can reshape one of the most basic human compulsions. This collaboration with Ofcom allows for insight that can be utilised in both academia and policymaking alike, making this research relevant and impactful across a range of academic fields and industries.

Keywords: computer mediated communication, longitudinal research, personal relationships, qualitative data

Procedia PDF Downloads 114

Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

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We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: situation-awareness, smart home, IoT, machine learning, classifier

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Authors: N. Guru Prasath, Sangjin Ma, Chang-Wan Kim

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A butterfly valve is a quarter turn valve which is used to control the flow of a fluid through a section of pipe. Generally, butterfly valve is used in wide range of applications such as water distribution, sewage, oil and gas plants. In particular, butterfly valve with larger diameter finds its immense applications in hydro power plants to control the fluid flow. In-lieu with the constraints in cost and size to run laboratory setup, analysis of large diameter values will be mostly studied by computational method which is the best and inexpensive solution. For fluid and structural analysis, CFD and FEM software is used to perform large scale valve analyses, respectively. In order to perform above analysis in butterfly valve, the CAD model has to recreate and perform mesh in conventional software’s for various dimensions of valve. Therefore, its limitation is time consuming process. In-order to overcome that issue, python code was created to outcome complete pre-processing setup automatically in Salome software. Applying dimensions of the model clearly in the python code makes the running time comparatively lower and easier way to perform analysis of the valve. Hence, in this paper, an attempt was made to study the fluid-structure interaction (FSI) of butterfly valves by varying the valve angles and dimensions using python code in pre-processing software, and results are produced.

Keywords: butterfly valve, flow coefficient, automatic CFD analysis, FSI analysis

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Authors: J. Fenianos, C. Khater, D. Brouillet

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Ecological projects are often faced with reluctance from local communities hosting the project, especially when this project involves variation from preset ideas or classical practices. This paper aims at appreciating the contribution of environmental psychology through cognitive flexibility exercises to improve the acceptability of local communities in adopting more ecological rehabilitation scenarios. The study is based on a quarry site located in Bekaa- Lebanon. Four groups were considered with different levels of involvement, as follows: Group 1 is Training (T) – 50 hours of on-site training over 8 months, Group 2 is Awareness (A) – 2 hours of awareness raising session, Group 3 is Flexibility (F) – 2 hours of flexibility exercises and Group 4 is the Control (C). The results show that individuals in Group 3 (F) who followed flexibility sessions accept comparably the ecological rehabilitation option over the more classical one. This is also the case for the people in Group 1 (T) who followed a more time-demanding “on-site training”. Another experience was conducted on a second quarry site combining flexibility with awareness-raising. This research confirms that it is possible to reduce resistance to change thanks to a limited in-time intervention using cognitive flexibility. This methodological approach could be transferable to other environmental problems involving local communities and changes in preset perceptions.

Keywords: acceptability, ecological restoration, environmental psychology, Lebanon, local communities, resistance to change

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Authors: Gökhan Polat, Dicle Kocaoğlu Yılmazer, Muhlis Nezihi Sarıdede

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Iron oxides are the main input to produce iron in integrated iron and steel plants. During production of iron from iron oxides, some wastes with high iron content occur. These main wastes can be classified as basic oxygen furnace (BOF) sludge, flue dust and rolling scale. Recycling of these wastes has a great importance for both environmental effects and reduction of production costs. In this study, recycling experiments were performed on basic oxygen furnace sludge, flue dust and rolling scale which contain 53.8%, 54.3% and 70.2% iron respectively. These wastes were mixed together with coke as reducer and these mixtures are pressed to obtain cylindrical briquettes. These briquettes were pressed under various compacting forces from 1 ton to 6 tons. Also, both stoichiometric and twice the stoichiometric cokes were added to investigate effect of coke amount on reduction properties of the waste mixtures. Then, these briquettes were reduced at 1000°C and 1100°C during 30, 60, 90, 120 and 150 min in a muffle furnace. According to the results of reduction experiments, the effect of compacting force, temperature and time on reduction ratio of the wastes were determined. It is found that 1 ton compacting force, 150 min reduction time and 1100°C are the optimum conditions to obtain reduction ratio higher than 75%.

Keywords: Coke, iron oxide wastes, recycling, reduction

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Authors: Mohammad Tawhid Kawser, Ishrak Kabir, Sadia Sultana, Tanjim Ahmad

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A promising service category of 5G, popularly known as Ultra-Reliable Low-Latency Communications (URLLC), is devoted to providing users with the staunchest fail-safe connections in the splits of a second. The reliability of data transfer, as offered by Hybrid ARQ (HARQ), should be employed as URLLC applications are highly error-sensitive. However, the delay added by HARQ ACK/NACK and retransmissions can degrade performance as URLLC applications are highly delay-sensitive too. To improve latency while maintaining reliability, this paper proposes the use of blind transmissions of redundancy versions exploiting the frequency diversity of wide bandwidth of 5G. The blind HARQ retransmissions proposed so far consider narrow bandwidth cases, for example, dedicated short range communication (DSRC), shared channels for device-to-device (D2D) communication, etc., and thus, do not gain much from the frequency diversity. The proposal also combines blind and ACK/NACK based retransmissions for different multiplexing options between time and frequency depending on the current radio channel quality and stringency of latency requirements. The wide bandwidth of 5G justifies that the proposed blind retransmission, without waiting for ACK/NACK, is not palpably extravagant. A simulation is performed to demonstrate the improvement in latency of the proposed scheme.

Keywords: 5G, URLLC, HARQ, latency, frequency diversity

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Authors: Jemma Porrett

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Background: We present a literature review examining the research surrounding tick paralysis resulting in facial nerve palsy. A case of an intra-aural paralysis tick bite resulting in unilateral facial nerve palsy is also discussed. Methods: A novel case of otoacariasis with associated ipsilateral facial nerve involvement is presented. Additionally, we conducted a review of the literature, and we searched the MEDLINE and EMBASE databases for relevant literature published between 1915 and 2020. Utilising the following keywords; 'Ixodes', 'Facial paralysis', 'Tick bite', and 'Australia', 18 articles were deemed relevant to this study. Results: Eighteen articles included in the review comprised a total of 48 patients. Patients' ages ranged from one year to 84 years of age. Ten studies estimated the possible duration between a tick bite and facial nerve palsy, averaging 8.9 days. Forty-one patients presented with a single tick within the external auditory canal, three had a single tick located on the temple or forehead region, three had post-auricular ticks, and one patient had a remarkable 44 ticks removed from the face, scalp, neck, back, and limbs. A complete ipsilateral facial nerve palsy was present in 45 patients, notably, in 16 patients, this occurred following tick removal. House-Brackmann classification was utilised in 7 patients; four patients with grade 4, one patient with grade three, and two patients with grade 2 facial nerve palsy. Thirty-eight patients had complete recovery of facial palsy. Thirteen studies were analysed for time to recovery, with an average time of 19 days. Six patients had partial recovery at the time of follow-up. One article reported improvement in facial nerve palsy at 24 hours, but no further follow-up was reported. One patient was lost to follow up, and one article failed to mention any resolution of facial nerve palsy. One patient died from respiratory arrest following generalized paralysis. Conclusions: Tick paralysis is a severe but preventable disease. Careful examination of the face, scalp, and external auditory canal should be conducted in patients presenting with otalgia and facial nerve palsy, particularly in tropical areas, to exclude the possibility of tick infestation.

Keywords: facial nerve palsy, tick bite, intra-aural, Australia

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Authors: Sanjeev Kumar Shukla, Govind Singh, Prabhat Pant Shahzad Ahmad

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Background: Graves’ disease is an autoimmune disorder with a genetic predisposition, and CD40 plays a pathogenic role in various autoimmune diseases. A single nucleotide polymorphism at position –1 of the Kozak sequence of the 5 untranslated regions of the CD40 gene of exon 1 has been reported to be associated with the development of Graves’ Disease. Objective: The aim of the present study was to investigate whether CD40 gene polymorphism confers susceptibility to Graves’ disease in the Kumaon region. CD40 gene polymorphisms were studied in Graves’ Disease patients (n=50) and healthy control subjects without anti-thyroid autoantibodies or a family history of autoimmune disorders (n=50). Material and Method: CD40 gene polymorphisms were studied in fifty Graves’ Disease patients and fifty healthy control subjects. All samples were collected from STG Hospital, Haldwani, Nainital. A C/T polymorphism at position –1 of the CD40 gene was measured using the polymerase chain reaction-restriction fragment length polymorphism. Results: There was no significant difference in allele or genotype frequency of the CD40 SNP between Graves’ Disease and control subjects. There was a significant decrease in the TT genotype frequency in the Graves’ Disease patients who developed Graves’ Disease after 40 years old than those under 40 years of age. These data suggest that the SNP of the CD40 gene is associated with susceptibility to the later onset of Graves’ Disease. Conclusion: The CD40 gene was a different susceptibility gene for Graves’ Disease within certain families because it was both linked and associated with Graves’ Disease.

Keywords: autoimmune diseases, pathogenesis, diagnosis, therapy

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Authors: Valentin Père, Mathieu Milhé, Fabien Baillon, Jean-Louis Dirion

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Microgrids offer potential solutions to meet the need for local grid stability and increase isolated networks autonomy with the integration of intermittent renewable energy production and storage facilities. In such a context, sizing production and storage for a given network is a complex task, highly depending on input data such as power load profile and renewable resource availability. This work aims at developing an operating cost computation methodology for different microgrid designs based on the use of deep reinforcement learning (RL) algorithms to tackle the optimal operation problem in stochastic environments. RL is a data-based sequential decision control method based on Markov decision processes that enable the consideration of random variables for control at a chosen time scale. Agents trained via RL constitute a promising class of Energy Management Systems (EMS) for the operation of microgrids with energy storage. Microgrid sizing (or design) is generally performed by minimizing investment costs and operational costs arising from the EMS behavior. The latter might include economic aspects (power purchase, facilities aging), social aspects (load curtailment), and ecological aspects (carbon emissions). Sizing variables are related to major constraints on the optimal operation of the network by the EMS. In this work, an islanded mode microgrid is considered. Renewable generation is done with photovoltaic panels; an electrochemical battery ensures short-term electricity storage. The controllable unit is a hydrogen tank that is used as a long-term storage unit. The proposed approach focus on the transfer of agent learning for the near-optimal operating cost approximation with deep RL for each microgrid size. Like most data-based algorithms, the training step in RL leads to important computer time. The objective of this work is thus to study the potential of Batch-Constrained Q-learning (BCQ) for the optimal sizing of microgrids and especially to reduce the computation time of operating cost estimation in several microgrid configurations. BCQ is an off-line RL algorithm that is known to be data efficient and can learn better policies than on-line RL algorithms on the same buffer. The general idea is to use the learned policy of agents trained in similar environments to constitute a buffer. The latter is used to train BCQ, and thus the agent learning can be performed without update during interaction sampling. A comparison between online RL and the presented method is performed based on the score by environment and on the computation time.

Keywords: batch-constrained reinforcement learning, control, design, optimal

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Authors: Disaphon Boobpachat, Nuttaset Manimmanakorn, Apiwan Manimmanakorn, Worrawut Thuwakum, Michael J. Hamlin

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Objectives: To evaluate effect of kinesio tape compared to placebo tape and static stretching on recovery of anaerobic power and maximal oxygen uptake (Vo₂max) after intensive exercise. Methods: Thirty nine untrained healthy volunteers were randomized to 3 groups for each intervention: elastic tape, placebo tape and stretching. The participants performed intensive exercise on the dominant quadriceps by using isokinetic dynamometry machine. The recovery process was evaluated by creatine kinase (CK), pressure pain threshold (PPT), muscle soreness scale (MSS), maximum voluntary contraction (MVC), jump height, anaerobic power and Vo₂max at baseline, immediately post-exercise and post-exercise day 1, 2, 3 and 7. Results: The kinesio tape, placebo tape and stretching groups had significant changes of PPT, MVC, jump height at immediately post-exercise compared to baseline (p < 0.05), and changes of MSS, CK, anaerobic power and Vo₂max at day 1 post-exercise compared to baseline (p < 0.05). There was no significant difference of those outcomes among three groups. Additionally, all experimental groups had little effects on anaerobic power and Vo₂max compared to baseline and compared among three groups (p > 0.05). Conclusion: Kinesio tape and stretching did not improve recovery of anaerobic power and Vo₂max after eccentric exercise compared to placebo tape.

Keywords: stretching, eccentric exercise, Wingate test, muscle soreness

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Authors: Mamadou Sileye Niang

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The study is a contribution to the development of a feed for juvenile tilapia Oreochromis niloticus, from local raw materials in order to reduce the cost of feeding farmed tilapia in Senegal. Three feeds were formulated from local raw materials. The basic composition of the tested feeds is as follows: A1 (peanut meal, rice bran, millet bran, maize meal and no fish meal); A2 (peanut meal, rice bran, millet bran, maize meal and 10% fish meal) and A3 (peanut meal, rice bran, millet bran, maize meal and 25% fish meal). All feeds contain 31% protein. The trial compared three batches, in 2 replicates, with different diets. The initial weight of the juveniles was 0.37± 0.5g. The daily ration was distributed at 9 am and 4 pm. After 90 days of the experiment, the final mean weights were 2.45 ± 0.5g; 2.75±0.5g; and 4.67 ± 0.5g for A1, A2, and A3, respectively. A performance test, of which the objective was to compare growth parameters, was conducted. The results of the growth parameters of juveniles fed A3 were significantly higher (p < 0.05) than those fed A1 and A2. The weight growth study shows similar growth during the first month. However, from this date onwards, juveniles fed A3 show a faster growth, which is maintained throughout the experiment. On the other hand, the Protein Efficiency Coefficient and the Survival Rate showed no significant difference. The zootechnical parameters are not significantly different (p > 0.05) between the two tanks for the same feed treatment.

Keywords: nutrition, feed, fingerlings, Oreochromis, local raw materials, feed cost

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Authors: Remy Jonkam Oben

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Using a time series approach, this study investigates how natural resources impact financial development from a global perspective over the 1980-2019 period. Some important determinants of financial development (economic growth, trade openness, population growth, and investment) have been added to the model as control variables. Unit root tests have revealed that all the variables are integrated into order one. Johansen's cointegration test has shown that the variables are in a long-run equilibrium relationship. The vector error correction model (VECM) has estimated the coefficient of the error correction term (ECT), which suggests that the short-run values of natural resources, economic growth, trade openness, population growth, and investment contribute to financial development converging to its long-run equilibrium level by a 23.63% annual speed of adjustment. The estimated coefficients suggest that global natural resource rent has a statistically-significant negative impact on global financial development in the long-run (thereby validating the financial resource curse) but not in the short-run. Causality test results imply that neither global natural resource rent nor global financial development Granger-causes each other.

Keywords: financial development, natural resources, resource curse hypothesis, time series analysis, Granger causality, global perspective

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Authors: Qiangqiang Xu, Xu Ji, Jingyang Han, Changchun Yang, Ming Li

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Replacing of complex solar concentrating unit, this paper designs a solar heat-concentrating medium-temperature steam-generating system. Solar radiation is collected by using a large solar collecting and heat concentrating plate and is converged to the metal evaporating pipe with high efficient heat transfer. In the meantime, the heat loss is reduced by employing a double-glazed cover and other heat insulating structures. Thus, a high temperature is reached in the metal evaporating pipe. The influences of the system's structure parameters on system performance are analyzed. The steam production rate and the steam production under different solar irradiance, solar collecting and heat concentrating plate area, solar collecting and heat concentrating plate temperature and heat loss are obtained. The results show that when solar irradiance is higher than 600 W/m², the effective heat collecting area is 7.6 m² and the double-glazing cover is adopted, the system heat loss amount is lower than the solar irradiance value. The stable steam is produced in the metal evaporating pipe at 100 ℃, 110 ℃, and 120 ℃, respectively. When the average solar irradiance is about 896 W/m², and the steaming cumulative time is about 5 hours, the daily steam production of the system is about 6.174 kg. In a single day, the solar irradiance is larger at noon, thus the steam production rate is large at that time. Before 9:00 and after 16:00, the solar irradiance is smaller, and the steam production rate is almost 0.

Keywords: heat concentrating, heat loss, medium temperature, solar steam production

Procedia PDF Downloads 172