Search results for: finger tracking

Authors: Sai Shruthi Sridhar, A. Madhumidha, Kreethika Guru, Priyanka Sekar, Ananthi Malayappan

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Numerous changes in technology and its recent development are structuring long withstanding effect to our world, one among them is the emergence of “Internet of Things” (IoT). Similar to Technology world, one industry stands out in everyday life–healthcare. Attention to “quality of health care” is an increasingly important issue in a global economy and for every individual. As per WHO (World Health Organization) it is estimated to be less than 50% adhere to the medication provided and only about 20% get their medicine on time. Medication adherence is one of the top problems in healthcare which is fixable by use of technology. In recent past, there were minor provisions for elderly and specially-skilled to get motivated and to adhere medicines prescribed. This paper proposes a novel solution that uses IOT based RFID Medication Reminder Solution to provide personal health care services. This employs real time tracking which offer quick counter measures. The proposed solution builds on the recent digital advances in sensor technologies, smart phones and cloud services. This novel solution is easily adoptable and can benefit millions of people with a direct impact on the nation’s health care expenditure with innovative scenarios and pervasive connectivity.

Keywords: cloud services, IoT, RFID, sensors

Procedia PDF Downloads 344

Authors: Juan Harold Sosa-Arnao, Daniel José de Oliveira Ferreira, Caice Guarato Santos, Justo Emílio Alvarez, Leonardo Paes Rangel, Song Won Park

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A comprehensive CFD model is developed to represent heterogeneous combustion and two burner designs of supply sugar-cane bagasse into a furnace. The objective of this work is to compare the insertion and burning of a Brazilian south-eastern sugar-cane bagasse using a new swirl burner design against an actual geometry under operation. The new design allows control the particles penetration and scattering inside furnace by adjustment of axial/tangential contributions of air feed without change their mass flow. The model considers turbulence using RNG k-, combustion using EDM, radiation heat transfer using DTM with 16 ray directions and bagasse particle tracking represented by Schiller-Naumann model. The obtained results are favorable to use of new design swirl burner because its axial/tangential control promotes more penetration or more scattering than actual design and allows reproduce the actual design operation without change the overall mass flow supply.

Keywords: comprehensive CFD model, sugar-cane bagasse combustion, swirl burner, contributions

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Authors: Rafael Marinho de Andrade, Elcio Hideti Shiguemori, Rafael Duarte Coelho dos Santos

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Relying on computer vision, many clever things are possible in order to make the world safer and optimized on resource management, especially considering time and attention as manageable resources, once the modern world is very abundant in cameras from inside our pockets to above our heads while crossing the streets. Thus, automated solutions based on computer vision techniques to detect, react, or even prevent relevant events such as robbery, car crashes and traffic jams can be accomplished and implemented for the sake of both logistical and surveillance improvements. In this paper, we present an approach for vehicles’ abnormal behaviors detection from highway footages, in which the vectorial data of the vehicles’ displacement are extracted directly from surveillance cameras footage through object detection and tracking with a deep convolutional neural network and inserted into a long-short term memory neural network for behavior classification. The results show that the classifications of behaviors are consistent and the same principles may be applied to other trackable objects and scenarios as well.

Keywords: artificial intelligence, behavior detection, computer vision, convolutional neural networks, LSTM, highway footage

Procedia PDF Downloads 165

Authors: Raahil Sheikh, Abhishek Maurya, Priya Gujjar, Himanshu Dwivedi, Prathamesh Minde

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UAVs have been an initial member of our environment since it's the first used by Austrian warfare in Venice. At that stage, they were just pilotless balloons equipped with bombs to be dropped on enemy territory. Over time, technological advancements allowed UAVs to be controlled remotely or autonomously. This study shall mainly focus on the intensification of pre-existing manual drones equipping them with a variety of sensors and making them autonomous, and capable, and purposing them for a variety of roles, including thermal sensing, data collection, tracking creatures, forest fires, volcano detection, hydrothermal studies, urban heat, Island measurement, and other environmental research. The system can also be used for reconnaissance, research, 3D mapping, and search and rescue missions. This study mainly focuses on automating tedious tasks and reducing human errors as much as possible, reducing deployment time, and increasing the overall efficiency, efficacy, and reliability of the UAVs. Creation of a comprehensive Ground Control System UI (GCS) enabling less trained professionals to be able to use the UAV with maximum potency. With the inclusion of such an autonomous system, artificially intelligent paths and environmental gusts and concerns can be avoided.

Keywords: UAV, drone, autonomous system, thermal imaging

Procedia PDF Downloads 73

Authors: Muhammad A. Alsubaie

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An iterative learning control framework designed in state feedback structure suffers a lack in investigating load disturbance considerations. The presented work discusses the controller previously designed, highlights the disturbance problem, finds new conditions using singular value principle to assure safe operation conditions with error convergence and reference tracking under the influence of load disturbance. It is known that periodic disturbances can be represented by a delay model in a positive feedback loop acting on the system input. This model can be manipulated by isolating the delay model and finding a controller for the overall system around the delay model to remedy the periodic disturbances using the small signal theorem. The overall system is the base for control design and load disturbance investigation. The major finding of this work is the load disturbance condition found which clearly sets safe operation condition under the influence of load disturbances such that the error tends to nearly zero as the system keeps operating trial after trial.

Keywords: iterative learning control, singular values, state feedback, load disturbance

Procedia PDF Downloads 156

Authors: Bifeng Zhu, Zhekai Wang, Chaoyang Sun, Bart Dewancker

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Under the tide of promoting sustainable development in the world, American universities that have been committed to sustainable practice and innovation, not only have its sustainable campus construction been in the forefront of the world, but also have developed STARS (The Sustainability Tracking, Assessment & Rating System), which is widely used in the world and highly recognized. At the same time, in the process of global sustainable campus construction, energy problem is often regarded as one of the most important sustainable aspects, even equivalent to the sustainability of campus. Therefore, the relationship between campus energy and sustainability is worth discussing. In this study, four American universities with the highest level evaluated by STARS are selected as examples to compare and analyze the campus energy consumption and the use of new energy, GHG emissions and the overall sustainability of the campus, in order to explore the relationship between campus energy and sustainable construction. It is found that the advantages of sustainable campus construction in the United States are mainly focused on the "software" of management, education, activities, etc. Although different energy-saving measures have been taken in campus energy, the construction results are quite different. Moreover, as an important aspect of sustainable campus, energy can not fully represent the sustainability of campus, but because of the various measures it takes, it can greatly promote the sustainable construction of the whole campus. These measures and construction experiences are worthy of summary and promotion, and have positive reference significance for other universities even communities around the world.

Keywords: sustainable campus, energy consumption, STARS assessment, GHG emissions

Procedia PDF Downloads 272

Authors: Nisa Özge Önal, Kamil Karaçuha, Göksu Hazar Erdinç, Banu Bahar Karaçuha, Ertuğrul Karaçuha

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The study aims to use a mathematical approach with the fractional calculus which is developed to have the ability to continuously analyze the factors related to the children’s height development. Until now, tracking the development of the child is getting more important and meaningful. Knowing and determining the factors related to the physical development of the child any desired time would provide better, reliable and accurate results for childcare. In this frame, 7 groups for height percentile curve (3th, 10th, 25th, 50th, 75th, 90th, and 97th) of Turkey are used. By using discrete height data of 0-18 years old children and the least squares method, a continuous curve is developed valid for any time interval. By doing so, in any desired instant, it is possible to find the percentage and location of the child in Percentage Chart. Here, with the help of the fractional calculus theory, a mathematical model is developed. The outcomes of the proposed approach are quite promising compared to the linear and the polynomial method. The approach also yields to predict the expected values of children in the sense of height.

Keywords: children growth percentile, children physical development, fractional calculus, linear and polynomial model

Procedia PDF Downloads 147

Authors: Raahil Sheikh, Prathamesh Minde, Priya Gujjar, Himanshu Dwivedi, Abhishek Maurya

Abstract:

UAVs have been an initial member of our environment since it's the first used by Austrian warfare in Venice. At that stage, they were just pilotless balloons equipped with bombs to be dropped on enemy territory. Over time, technological advancements allowed UAVs to be controlled remotely or autonomously. This study shall mainly focus on the intensification of pre-existing manual drones equipping them with a variety of sensors and making them autonomous, and capable, and purposing them for a variety of roles, including thermal sensing, data collection, tracking creatures, forest fires, volcano detection, hydrothermal studies, urban heat, Island measurement, and other environmental research. The system can also be used for reconnaissance, research, 3D mapping, and search and rescue missions. This study mainly focuses on automating tedious tasks and reducing human errors as much as possible, reducing deployment time, and increasing the overall efficiency, efficacy, and reliability of the UAVs. Creation of a comprehensive Ground Control System UI (GCS) enabling less trained professionals to be able to use the UAV with maximum potency. With the inclusion of such an autonomous system, artificially intelligent paths and environmental gusts and concerns can be avoided

Keywords: UAV, autonomous systems, drones, geo thermal imaging

Procedia PDF Downloads 83

Authors: Maria Korman, Carmit Gal, Ella Gabitov, Avi Karni

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The main question addressed in this study was whether the time-of-day wherein training is afforded is a significant factor for motor skill ('how-to', procedural knowledge) acquisition and consolidation into long term memory in the healthy elderly population. Twenty-nine older adults (60-75 years) practiced an explicitly instructed 5-element key-press sequence by repeatedly generating the sequence ‘as fast and accurately as possible’. Contribution of three parameters to acquisition, 24h post-training consolidation, and 1-week retention gains in motor sequence speed was assessed: (a) time of training (morning vs. evening group) (b) sleep quality (actigraphy) and (c) chronotype. All study participants were moderately morning type, according to the Morningness-Eveningness Questionnaire score. All participants had sleep patterns typical of age, with average sleep efficiency of ~ 82%, and approximately 6 hours of sleep. Speed of motor sequence performance in both groups improved to a similar extent during training session. Nevertheless, evening group expressed small but significant overnight consolidation phase gains, while morning group showed only maintenance of performance level attained at the end of training. By 1-week retention test, both groups showed similar performance levels with no significant gains or losses with respect to 24h test. Changes in the tapping patterns at 24h and 1-week post-training were assessed based on normalized Pearson correlation coefficients using the Fisher’s z-transformation in reference to the tapping pattern attained at the end of the training. Significant differences between the groups were found: the evening group showed larger changes in tapping patterns across the consolidation and retention windows. Our results show that morning-oriented older adults effectively acquired, consolidated, and maintained a new sequence of finger movements, following both morning and evening practice sessions. However, time-of-training affected the time-course of skill evolution in terms of performance speed, as well as the re-organization of tapping patterns during the consolidation period. These results are in line with the notion that motor training preceding a sleep interval may be beneficial for the long-term memory in the elderly. Evening training should be considered an appropriate time window for motor skill learning in older adults, even in individuals with morning chronotype.

Keywords: time-of-day, elderly, motor learning, memory consolidation, chronotype

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Authors: Mehrnoosh Ghadimi, Golnoush Ghadimi

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Precise monitoring of glacier velocity is critical in determining glacier-related hazards. Zardkooh Mountain was studied in terms of glacial activity rate in Zagros Mountainous region in Iran. In this study, we assessed the ability of optical and radar imagery to derive glacier-surface velocities in mountainous terrain. We processed Landsat 8 for optical data and Sentinel-1a for radar data. We used methods that are commonly used to measure glacier surface movements, such as cross correlation of optical and radar satellite images, SAR tracking techniques, and multiple aperture InSAR (MAI). We also assessed time series glacier surface displacement using our modified method, Enhanced Small Baseline Subset (ESBAS). The ESBAS has been implemented in StaMPS software, with several aspects of the processing chain modified, including filtering prior to phase unwrapping, topographic correction within three-dimensional phase unwrapping, reducing atmospheric noise, and removing the ramp caused by ionosphere turbulence and/or orbit errors. Our findings indicate an average surface velocity rate of 32 mm/yr in the Zardkooh mountainous areas.

Keywords: active rock glaciers, landsat 8, sentinel-1a, zagros mountainous region

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Authors: Sharif Muddsair, Eisels Martin, Giesbrecht Eugenie

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With development of society increase the demand for the movement of people also increases gradually. The various modes of the transport in different extent which expat impacts, which depends on mainly technical-operating conditions. The up-to-date telematics systems provide the transport industry a revolutionary. Appropriate use of these systems can help to substantially improve the efficiency. Vehicle monitoring and fleet tracking are among services used for improving efficiency and effectiveness of utility vehicle. There are many telematics systems which may contribute to eco-driving. Generally, they can be grouped according to their role in driving cycle. • Before driving - eco-route selection, • While driving – Advanced driver assistance, • After driving – remote analysis. Our point of interest is regulated in third point [after driving – remote analysis]. TS [Telematics-system] make it possible to record driving patterns in real time and analysis the data later on, So that driver- classification-specific hints [fast driver, slow driver, aggressive driver…)] are given to imitate eco-friendly driving style. Together with growing number of vehicle and development of information technology, telematics become an ‘active’ research subject in IT and the car industry. Telematics has gone a long way from providing navigation solution/assisting the driver to become an integral part of the vehicle. Today’s telematics ensure safety, comfort and become convenience of the driver.

Keywords: internet of things, iot, connected vehicle, cv, ts, telematics services, ml, machine learning

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Authors: Achraf Al Faraj, Asma Sultana Shaik, Baraa Al Sayed

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Specific and effective targeting of drug delivery systems (DDS) to cancerous sites remains a major challenge for a better diagnostic and therapy. Recently, SWCNTs with their unique physicochemical properties and the ability to cross the cell membrane show promising in the biomedical field. The purpose of this study was first to develop a biocompatible iron oxide tagged SWCNTs as diagnostic nanoprobes to allow their noninvasive detection using MRI and their preferential targeting in a breast cancer murine model by placing an optimized flexible magnet over the tumor site. Magnetic targeting was associated to specific antibody-conjugated SWCNTs active targeting. The therapeutic efficacy of doxorubicin-conjugated SWCNTs was assessed, and the superiority of diffusion-weighted (DW-) MRI as sensitive imaging biomarker was investigated. Short Polyvinylpyrrolidone (PVP) stabilized water soluble SWCNTs were first developed, tagged with iron oxide nanoparticles and conjugated with Endoglin/CD105 monoclonal antibodies. They were then conjugated with doxorubicin drugs. SWCNTs conjugates were extensively characterized using TEM, UV-Vis spectrophotometer, dynamic light scattering (DLS) zeta potential analysis and electron spin resonance (ESR) spectroscopy. Their MR relaxivities (i.e. r1 and r2*) were measured at 4.7T and their iron content and metal impurities quantified using ICP-MS. SWCNTs biocompatibility and drug efficacy were then evaluated both in vitro and in vivo using a set of immunological assays. Luciferase enhanced bioluminescence 4T1 mouse mammary tumor cells (4T1-Luc2) were injected into the right inguinal mammary fat pad of Balb/c mice. Tumor bearing mice received either free doxorubicin (DOX) drug or SWCNTs with or without either DOX or iron oxide nanoparticles. A multi-pole 10x10mm high-energy flexible magnet was maintained over the tumor site during 2 hours post-injections and their properties and polarity were optimized to allow enhanced magnetic targeting of SWCNTs toward the primary tumor site. Tumor volume was quantified during the follow-up investigation study using a fast spin echo MRI sequence. In order to detect the homing of SWCNTs to the main tumor site, susceptibility-weighted multi-gradient echo (MGE) sequence was used to generate T2* maps. Apparent diffusion coefficient (ADC) measurements were also performed as a sensitive imaging biomarker providing early and better assessment of disease treatment. At several times post-SWCNT injection, histological analysis were performed on tumor extracts and iron-loaded SWCNT were quantified using ICP-MS in tumor sites, liver, spleen, kidneys, and lung. The optimized multi-poles magnet revealed an enhanced targeting of magnetic SWCNTs to the primary tumor site, which was found to be much higher than the active targeting achieved using antibody-conjugated SWCNTs. Iron-loading allowed their sensitive noninvasive tracking after intravenous administration using MRI. The active targeting of doxorubicin through magnetic antibody-conjugated SWCNTs nanoprobes was found to considerably decrease the primary tumor site and may have inhibited the development of metastasis in the tumor-bearing mice lung. ADC measurements in DW-MRI were found to significantly increase in a time-dependent manner after the injection of DOX-conjugated SWCNTs complexes.

Keywords: single-walled carbon nanotubes, nanomedicine, magnetic resonance imaging, cancer diagnosis and therapy

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Authors: Yahia I. Mohamed, Ahmed I. Marzouk, Mohamed A. Yacout

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Aim of this work was to study the genetic basis for oil accumulation in olive fruit via tracking DGAT2 (Diacylglycerol acyltransferase type-2) gene in three Egyptian Origen Olive cultivars namely Toffahi, Hamed and Maraki using molecular marker techniques and bioinformatics tools. Results illustrate that, firstly: specific genomic band of Maraki cultivars was identified as DGAT2 (Diacylglycerol acyltransferase type-2) and identical for this gene in Olea europaea with 100 % of similarity. Secondly, differential genomic band of Maraki cultivars which produced from RAPD fingerprinting technique reflected predicted distinguished sequence which identified as DGAT2 (Diacylglycerol acyltransferase type-2) in Fragaria vesca subsp. Vesca with 76% of sequential similarity. Third and finally, specific genomic specific band of Hamed cultivars was indentified as two fragments, 1-Olea europaea cultivar Koroneiki diacylglycerol acyltransferase type 2 mRNA, complete cds with two matches regions with 99% or 2-PREDICTED: Fragaria vesca subsp. vesca diacylglycerol O-acyltransferase 2-like (LOC101313050), mRNA with 86% of similarity.

Keywords: Olea europaea, fingerprinting, diacylglycerol acyltransferase type-2 (DGAT2), Egypt

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Authors: Abe Degale D., Cheng Jian

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When creating automated video surveillance systems, violent action recognition is crucial. In recent years, hand-crafted feature detectors have been the primary method for achieving violence detection, such as the recognition of fighting activity. Researchers have also looked into learning-based representational models. On benchmark datasets created especially for the detection of violent sequences in sports and movies, these methods produced good accuracy results. The Hockey dataset's videos with surveillance camera motion present challenges for these algorithms for learning discriminating features. Image recognition and human activity detection challenges have shown success with deep representation-based methods. For the purpose of detecting violent images and identifying aggressive human behaviours, this research suggested a deep representation-based model using the transfer learning idea. The results show that the suggested approach outperforms state-of-the-art accuracy levels by learning the most discriminating features, attaining 99.34% and 99.98% accuracy levels on the Hockey and Movies datasets, respectively.

Keywords: violence detection, faster RCNN, transfer learning and, surveillance video

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Authors: Kasra Afsahi, Maryam Soheilifar, S. Hossein Hosseini

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Background: There is growing evidence that Cerebral Vascular Accident (CVA) can be a consequence of Covid-19 infection. Understanding novel treatment approaches are important in optimizing patient outcomes. Case: This case explores the use of Virtual Reality (VR) in the treatment of a 23-year-old COVID-positive female presenting with left hemiparesis in August 2020. Imaging showed right globus pallidus, thalamus, and internal capsule ischemic stroke. Conventional rehabilitation was started two weeks later, with virtual reality (VR) included. This game-based virtual reality (VR) technology developed for stroke patients was based on upper extremity exercises and functions for stroke. Physical examination showed left hemiparesis with muscle strength 3/5 in the upper extremity and 4/5 in the lower extremity. The range of motion of the shoulder was 90-100 degrees. The speech exam showed a mild decrease in fluency. Mild lower lip dynamic asymmetry was seen. Babinski was positive on the left. Gait speed was decreased (75 steps per minute). Intervention: Our game-based VR system was developed based on upper extremity physiotherapy exercises for post-stroke patients to increase the active, voluntary movement of the upper extremity joints and improve the function. The conventional program was initiated with active exercises, shoulder sanding for joint ROMs, walking shoulder, shoulder wheel, and combination movements of the shoulder, elbow, and wrist joints, alternative flexion-extension, pronation-supination movements, Pegboard and Purdo pegboard exercises. Also, fine movements included smart gloves, biofeedback, finger ladder, and writing. The difficulty of the game increased at each stage of the practice with progress in patient performances. Outcome: After 6 weeks of treatment, gait and speech were normal and upper extremity strength was improved to near normal status. No adverse effects were noted. Conclusion: This case suggests that VR is a useful tool in the treatment of a patient with covid-19 related CVA. The safety of newly developed instruments for such cases provides new approaches to improve the therapeutic outcomes and prognosis as well as increased satisfaction rate among patients.

Keywords: covid-19, stroke, virtual reality, rehabilitation

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Authors: B. Gopal, Pannala Krishna Murthy, G. N. Sreenivas

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The increasing demand of electric power is giving an emphasis on the need for the maximum utilization of renewable energy sources. On the other hand maintaining power quality to satisfaction of utility is an essential requirement. In this paper the design aspects of a Unified Power Quality Conditioner integrated with photovoltaic system in a distributed generation is presented. The proposed system consist of series inverter, shunt inverter are connected back to back on the dc side and share a common dc-link capacitor with Distributed Generation through a boost converter. The primary task of UPQC is to minimize grid voltage and load current disturbances along with reactive and harmonic power compensation. In addition to primary tasks of UPQC, other functionalities such as compensation of voltage interruption and active power transfer to the load and grid in both islanding and interconnected mode have been addressed. The simulation model is design in MATLAB/ Simulation environment and the results are in good agreement with the published work.

Keywords: distributed generation (DG), interconnected mode, islanding mode, maximum power point tracking (mppt), power quality (PQ), unified power quality conditioner (UPQC), photovoltaic array (PV)

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Authors: Larissa Negris de Souza, Ana Regina Mizrahy Cuperschmid, Daniel de Carvalho Moreira

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Augmented Reality (AR) alters the elaboration of the architectural project, which relates to project cognition: representation, visualization, and perception of information. Understanding these features from the earliest stages of the design can facilitate the study of relationships, zoning, and overall dimensions of the forms. This paper’s goal was to explore a new approach for information visualization during the early stages of architectural design using Augmented Reality (AR). A three-dimensional marker inspired by the Rubik’s Cube was developed, and its performance, evaluated. This investigation interwovens the acquired knowledge of traditional briefing methods and contemporary technology. We considered the concept of patterns (Alexander et al. 1977) to outline geometric forms and associations using visual programming. The Design Science Research was applied to develop the study. An SDK was used in a game engine to generate the AR app. The tool's functionality was assessed by verifying the readability and precision of the reconfigurable 3D marker. The results indicated an inconsistent response. To use AR in the early stages of architectural design the system must provide consistent information and appropriate feedback. Nevertheless, we conclude that our framework sets the ground for looking deep into AR tools for briefing design.

Keywords: augmented reality, cuboid marker, early design stages, graphic representation, patterns

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Authors: Sonia Perez-Gamboa, Qingquan Sun, Yan Zhang

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Non-intrusive sensor-based human activity recognition (HAR) is utilized in a spectrum of applications, including fitness tracking devices, gaming, health care monitoring, and smartphone applications. Deep learning models such as convolutional neural networks (CNNs) and long short term memory (LSTM) recurrent neural networks (RNNs) provide a way to achieve HAR accurately and effectively. In this paper, we design a multi-layer hybrid architecture with CNN and LSTM and explore a variety of multi-layer combinations. Based on the exploration, we present a lightweight, hybrid, and multi-layer model, which can improve the recognition performance by integrating local features and scale-invariant with dependencies of activities. The experimental results demonstrate the efficacy of the proposed model, which can achieve a 94.7% activity recognition rate on a benchmark human activity dataset. This model outperforms traditional machine learning and other deep learning methods. Additionally, our implementation achieves a balance between recognition rate and training time consumption.

Keywords: deep learning, LSTM, CNN, human activity recognition, inertial sensor

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Authors: Vivek Krishna, Nikhil Jain, A. Mary Posonia A., Albert Mayan J

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Terrorism and insurgency are significant global issues that require constant attention and effort from governments and scientists worldwide. To combat these threats, nations invest billions of dollars in developing new defensive technologies to protect civilians. Breakthroughs in vehicle automation have led to the use of sophisticated machines for many dangerous and critical anti-terrorist activities. Our concept of an "Unmanned Ground Vehicle" can carry out tasks such as border security, surveillance, mine detection, and active combat independently or in tandem with human control. The robot's movement can be wirelessly controlled by a person in a distant location or can travel to a pre-programmed destination autonomously in situations where personal control is not feasible. Our defence system comprises two units: the control unit that regulates mobility and the motion tracking unit. The remote operator robot uses the camera's live visual feed to manually operate both units, and the rover can automatically detect movement. The rover is operated by manpower who controls it using a joystick or mouse, and a wireless modem enables a soldier in a combat zone to control the rover via an additional controller feature.

Keywords: robotics, computer vision, Machine learning, Artificial intelligence, future of AI

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Authors: Homyr L. Garcia, Jr., Anne Margaret A. Rendon, Carla Michaela B. Taguinod

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Nothing is constant in this world but change. This is the reality wherein a lot of people fail to recognize and maybe, it is because of the fact that some see things that are happening with little value or no value at all until it’s gone. For the past years, Egypt was known for its stable government. It was able to withstand a lot of problems and crisis which challenged their country in ways which can never be imagined. In the present time, it seems like in just a snap of a finger, the said stability vanished and it was immediately replaced by a crisis which resulted to a failure in some parts of their government. In addition, this problem continued to worsen and the current situation of Egypt is just a reflection or a result of it. On the other hand, as the researchers continued to study the reasons why the government of Egypt is unstable, they concluded that there might be a possibility that they will be able to produce ways in which their country could be helped or improved. The instability of the government of Egypt is the product of combining all the problems which affects the lives of the people. Some of the reasons that the researchers found are the following: 1) unending doubts of the people regarding the ruling capacity of elected presidents, 2) removal of President Mohamed Morsi in position, 3) economic crisis, 4) a lot of protests and revolution happened, 5) resignation of the long term President Hosni Mubarak and 6) the office of the President is most likely available only to the chosen successor. Also, according to previous researches, there are two plausible scenarios for the instability of Egypt: 1) a military intervention specifically the Supreme Council of the Armed Forces or SCAF, resulting from a contested succession and 2) an Islamist push for political power which highlights the claim that religion is a hindrance towards the development of their country and government. From the eight possible reasons, the researchers decided that they will be focusing on economic crisis since the instability is more clearly seen in the country’s economy which directly affects the people and the government itself. In addition, they made a hypothesis which states that stable economy is a prerequisite towards a stable government. If they will be able to show how this claim is true by using the Social Autopsy Research Design for the qualitative method and Pearson’s correlation coefficient for the quantitative method, the researchers might be able to produce a proposal on how Egypt can stabilize their government and avoid such problems. Also, the hypothesis will be based from the Rational Action Theory which is a theory for understanding and modeling social and economy as well as individual behavior.

Keywords: Pearson’s correlation coefficient, rational action theory, social autopsy research design, supreme council of the armed forces (SCAF)

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Authors: Ayad Al-Mahturi, Herman Wahid

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This paper presents an optimal state feedback controller based on Linear Quadratic Regulator (LQR) for a two-rotor aero-dynamical system (TRAS). TRAS is a highly nonlinear multi-input multi-output (MIMO) system with two degrees of freedom and cross coupling. There are two parameters that define the behavior of LQR controller: state weighting matrix and control weighting matrix. The two parameters influence the performance of LQR. Particle Swarm Optimization (PSO) is proposed to optimally tune weighting matrices of LQR. The major concern of using LQR controller is to stabilize the TRAS by making the beam move quickly and accurately for tracking a trajectory or to reach a desired altitude. The simulation results were carried out in MATLAB/Simulink. The system is decoupled into two single-input single-output (SISO) systems. Comparing the performance of the optimized proportional, integral and derivative (PID) controller provided by INTECO, results depict that LQR controller gives a better performance in terms of both transient and steady state responses when PSO is performed.

Keywords: LQR controller, optimal control, particle swarm optimization (PSO), two rotor aero-dynamical system (TRAS)

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Authors: Sifan Guo, Xuesen Zheng

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Visitors as the vital research group have been mentioned in high frequency in the field of museum studies. With the rise of the New Museology Movement, new challenges in the museum appeared, ranging from how to eliminate the cliché class prejudices in museums to how to make visitor-oriented museums more welcome. In line with this new situation, to create a successful visiting experience is the focus of museums in today. National museums as tourist attractions always attract flooded attention, however the local museums may have the different situations. The residents could be one of the main visitors to the local museums how to attract them returned should be considered here. There are various people with different cultural, education and religion backgrounds, it is necessary to keep the balance of the education and entertainment to reach visitors’ expectations. Regarding these questions, a mixed methods research approach has been adopted: observations, tracking and questionnaires. Based on analysing some museums’ cases in the UK, it can be argued that: 1) Audiences’ accessibility support their options and judgments during the visiting. 2) Highly inclusive architecture and narrative expressions could encourage the visitors to proceed deeply understanding and alleviate conflicts. In addition, the main characteristics of the local museums and the interlinks between museums and urban renaissance will be clarified. The conclusion informs not only practical suggestions for reachable characteristic design, but also potential future research subjects.

Keywords: accessibility, challenging visitors, new museology movement, visiting experience

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Authors: Chandra Prayaga, Lakshmi Prayaga, Aaron Wade, Kyle Rank, Gopi Shankar Mallu, Sri Satya, Harsha Pola

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In today's tech-driven world, where connectivity shapes our daily lives, maintaining physical and emotional health is crucial. Athletic trainers play a vital role in optimizing athletes' performance and preventing injuries. However, a shortage of trainers impacts the quality of care. This study introduces a vision-based exercise monitoring system leveraging Google's MediaPipe library for precise tracking of bicep curl exercises and simultaneous posture monitoring. We propose a three-stage methodology: landmark detection, side detection, and angle computation. Our system calculates angles at the elbow, wrist, neck, and torso to assess exercise form. Experimental results demonstrate the system's effectiveness in distinguishing between good and partial repetitions and evaluating body posture during exercises, providing real-time feedback for precise fitness monitoring.

Keywords: physical health, athletic trainers, fitness monitoring, technology driven solutions, Google’s MediaPipe, landmark detection, angle computation, real-time feedback

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Authors: Fatemeh Aghamohammadzadeh, Mahdi Asghari Ozma

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SARS-CoV-2 was transmitted from animals to humans in China and through air transport to almost all world countries, including Iran, creating the first pandemic of the 21st century. The virus was spread through droplets from sneezing, coughing, loud talking, and exhalation of sick and asymptomatic people, even during incubation. It was transmitted from human to human directly by inhalation of viruses in droplets or indirectly through contact with infected surfaces, resulting in the death of a significant number of patients, especially the elderly and those with underlying diseases. The virus is more likely to be transmitted in places with high population densities. The chain of transmission of infection can be broken by observing the following: risk perception, reduced travel, complete quarantine in a particular area, home quarantine, social distancing, use of personal protective equipment (PPE), prevention of gatherings, cleaning and disinfection of public utilities and busy places, identifying, isolating and treating infected people, tracking calls, continuing health education, following health principles by people, especially in poor areas, and washing their hands frequently with soap and water or disinfecting them with 70% ethanol.

Keywords: COVID-19, transmission, population density, home quarantine, social distancing

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Authors: Yuyun Wabula, B. J. Dewancker

Abstract:

In the past decade, the social networking app has been growing very rapidly. Geolocation data is one of the important features of social media that can attach the user's location coordinate in the real world. This paper proposes the use of geolocation data from the Twitter social media application to gain knowledge about urban dynamics, especially on human mobility behavior. This paper aims to explore the relation between geolocation Twitter with the existence of people in the urban area. Firstly, the study will analyze the spread of people in the particular area, within the city using Twitter social media data. Secondly, we then match and categorize the existing place based on the same individuals visiting. Then, we combine the Twitter data from the tracking result and the questionnaire data to catch the Twitter user profile. To do that, we used the distribution frequency analysis to learn the visitors’ percentage. To validate the hypothesis, we compare it with the local population statistic data and land use mapping released by the city planning department of Makassar local government. The results show that there is the correlation between Twitter geolocation and questionnaire data. Thus, integration the Twitter data and survey data can reveal the profile of the social media users.

Keywords: geolocation, Twitter, distribution analysis, human mobility

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Authors: K. Parandhama Gowd

Abstract:

The aim of this research paper is to conceptualize, discuss, analyze and propose alternate design methodologies for futuristic Black Box for flight safety. The proposal also includes global networking concepts for real time surveillance and monitoring of flight performance parameters including GPS parameters. It is expected that this proposal will serve as a failsafe real time diagnostic tool for accident investigation and location of debris in real time. In this paper, an attempt is made to improve the existing methods of flight data recording techniques and improve upon design considerations for futuristic FDR to overcome the trauma of not able to locate the block box. Since modern day communications and information technologies with large bandwidth are available coupled with faster computer processing techniques, the attempt made in this paper to develop a failsafe recording technique is feasible. Further data fusion/data warehousing technologies are available for exploitation.

Keywords: flight data recorder (FDR), black box, diagnostic tool, global networking, cockpit voice and data recorder (CVDR), air traffic control (ATC), air traffic, telemetry, tracking and control centers ATTTCC)

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Authors: Seong Jun Yoon, Jasurbek Doliev, Sang Min Oh, Rodi Hartono, Kyoojae Shin

Abstract:

Electric power steering (EPS), which is commonly used in electric vehicles recently, is an electric-driven steering device for vehicles. Compared to hydraulic systems, EPS offers advantages such as simple system components, easy maintenance, and improved steering performance. However, because the EPS system is a nonlinear model, difficult problems arise in controller design. To address these, various machine learning and artificial intelligence approaches, notably artificial neural networks (ANN), have been applied. ANN can effectively determine relationships between inputs and outputs in a data-driven manner. This research explores two main areas: designing an EPS identifier using an ANN-based backpropagation (BP) algorithm and enhancing the EPS system controller with an ANN-based Levenberg-Marquardt (LM) algorithm. The proposed ANN-based BP algorithm shows superior performance and accuracy compared to linear transfer function estimators, while the LM algorithm offers better input angle reference tracking and faster response times than traditional PID controllers. Overall, the proposed ANN methods demonstrate significant promise in improving EPS system performance.

Keywords: ANN backpropagation modelling, electric power steering, transfer function estimator, electrical vehicle driving system

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Authors: Ben-Caleb Egbide, Egharevba Mathew, Achugamonu Uzoma, Faboyede Samuel

Abstract:

The importance of budgeting in government and corporate entities as medium for the efficient management of scarce resources is self-evident. But when it comes to home or personal budgeting, there seem to be lingering misconceptions as regards its relevance. While most people view personal budgeting merely as a tool for tracking expenses and schedule for paying bills and indebtedness, very few consider it as one of the most important device for sound financial planning, money management instrument and/or wealth-creation mechanism. This paper is conceptualised to investigate the association between personal budgeting and financial well-being among staffers of tertiary institution in the South West Nigeria. Underpinned by the individualistic/cultural theory of well-being and the adoption of a survey research design, a structured questionnaire was used to gather data from a cross section of staff of tertiary Institutions in Ogun State. A Spearman Rank Correlation was utilised for analysis of data. The result indicates a high positive relationship between personal budgeting and tendencies for enhanced financial well-being among staff. The paper established that a change of value and behavioural pattern by individuals and household, especially in the areas of personal spending and budgeting could drastically reduce the incidence of the severity of financial stress, hence, enhanced wellness among staff.

Keywords: personal budgeting, financial well-being, tertiary institutions staffers, Nigeria

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Authors: Junkyeong Kim, Jooyoung Park, Aoqi Zhang, Seunghee Park

Abstract:

The tensile force of Pre-Stressed Concrete (PSC) girder is the most important factor for evaluating the performance of PSC girder bridges. To measure the tensile force of PSC girder, several NDT methods were studied. However, conventional NDT method cannot be applied to the real-size PSC girder because the PS tendons could not be approached. To measure the tensile force of real-size PSC girder, this study proposed embedded EM sensor based tensile force estimation method. The embedded EM sensor could be installed inside of PSC girder as a sheath joint before the concrete casting. After curing process, the PS tendons were installed, and the tensile force was induced step by step using hydraulic jacking machine. The B-H loop was measured using embedded EM sensor at each tensile force steps and to compare with actual tensile force, the load cell was installed at each end of girder. The magnetization energy loss, that is the closed area of B-H loop, was decreased according to the increase of tensile force with regular pattern. Thus, the tensile force could be estimated by the tracking the change of magnetization energy loss of PS tendons. Through the experimental result, the proposed method can be used to estimate the tensile force of the in-situ real-size PSC girder bridge.

Keywords: tensile force estimation, embedded EM sensor, magnetization energy loss, PSC girder

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Authors: Mohammad Lemar Zalmai, Osman Hurol Turkakin, Cemil Akcay, Ekrem Manisali

Abstract:

Most of the construction projects are exposed to time and cost overruns due to various factors and this is a major problem. As a solution to this, the Earned Value Management (EVM) method is considered. EVM is a powerful and well-known method used in monitoring and controlling the project. EVM is a technique that project managers use to track the performance of their project against project baselines. EVM gives an early indication that either project is delayed or not, and the project is either over budget or under budget at any particular day by tracking it. Thus, it helps to improve the management control system of a construction project, to detect and control the problems in potential risk areas and to suggest the importance and purpose of monitoring the construction work. This paper explains the main parameters of the EVM system involved in the calculation of time and cost for construction projects. In this study, the project management software Primavera P6 is used to deals with the project monitoring process of a seven-storeyed (G+6) faculty building whose construction is in progress at Istanbul, Turkey. A comparison between the planned progress of construction activities and actual progress is performed, and the analysis results are interpreted. This case study justifies the benefits of using EVM for project cash flow analysis and forecasting.

Keywords: earned value management (EVM), construction cost management, construction planning, primavera P6, project management, project scheduling

Procedia PDF Downloads 238