Search results for: features comparison

Authors: Agata Twardoch

Abstract:

The processes of commodification of real estate and changes in housing markets have led to a situation where the prices of free market housing in European capitals are significantly higher than the purchasing value of average wages. This phenomenon has many negative social and spatial consequences. At the same time, the attractiveness of real estate as an asset makes these processes progress. Out of concern for sustainable social development, city authorities apply solutions to balance the burdensome effects of codification of housing. One of them is a social provision for housing investments. The article presents a comparative study of solutions applied in selected European capitals, on the example of Warsaw, Paris, London, Berlin, Copenhagen, and Vienna. The study was conducted along with works on expert report for the master plan for Warsaw. The forms of commissions applied in Local Planning Acts were compared, with particular reference to spatial solutions. The results of the analysis made it possible to determine common features of the solutions applied and to establish recommendations for further practice. Major findings of the study indicate that requirement of social provision is achievable in spatial planning documents. Study shows that application of social provision in private housing investments is a useful tool in housing policy against commodification.

Keywords: affordable housing, housing provision, spatial planning, sustainable social development

Procedia PDF Downloads 185

Authors: Hsin-Yu Lee, Ming-Zhong Li, Wen-Hsi Chiu, Su-Fen Cheng, Shwu-Wen Lin

Abstract:

Background: The use of medical terminology is essential to professional nurses on clinical practice. However, most nursing students consider traditional lecture-based teaching of medical terminology as boring and overly conceptual and lack motivation to learn. It is thus an issue to be discussed on how to enhance nursing students’ self-directed learning and improve learning outcomes of medical terminology. Digital game-based learning is a learner-centered way of learning. Past literature showed that the most common game-based learning for language education has been immersive games and teaching games. Thus, this study selected role-playing games (RPG) and digital puzzle games for observation and comparison. It is interesting to explore whether digital game-based learning has positive impact on nursing students’ learning of medical terminology and whether students can adapt well on this type of learning. Results can be used to provide references for institutes and teachers on teaching medical terminology. These instructions give you guidelines for preparing papers for the conference. Use this document as a template if you are using Microsoft Word. Otherwise, use this document as an instruction set. The electronic file of your paper will be formatted further at WASET. Define all symbols used in the abstract. Do not cite references in the abstract. Do not delete the blank line immediately above the abstract; it sets the footnote at the bottom of this column. Page margins are 1,78 cm top and down; 1,65 cm left and right. Each column width is 8,89 cm and the separation between the columns is 0,51 cm. Objective: The purpose of this research is to explore respectively the impact of RPG and puzzle game on nursing students’ self-directed learning and technology acceptance. The study further discusses whether different game types bring about different influences on students’ self-directed learning and technology acceptance. Methods: A quasi-experimental design was adopted in this study so that repeated measures between two groups could be conveniently conducted. 103 nursing students from a nursing college in Northern Taiwan participated in the study. For three weeks of experiment, the experiment group (n=52) received “traditional teaching + RPG” while the control group (n=51) received “traditional teaching + puzzle games”. Results: 1. On self-directed learning: For each game type, there were significant differences for the delayed tests of both groups as compared to the pre and post-tests of each group. However, there were no significant differences between the two game types. 2. On technology acceptance: For the experiment group, after the intervention of RPG, there were no significant differences concerning technology acceptance. For the control group, after the intervention of puzzle games, there were significant differences regarding technology acceptance. Pearson-correlation coefficient and path analysis conducted on the results of the two groups revealed that the dimension were highly correlated and reached statistical significance. Yet, the comparison of technology acceptance between the two game types did not reach statistical significance. Conclusion and Recommend: This study found that through using different digital games on learning, nursing students have effectively improved their self-directed learning. Students’ technology acceptances were also high for the two different digital game types and each dimension was significantly correlated. The results of the experimental group showed that through the scenarios of RPG, students had a deeper understanding of medical terminology, which reached the ‘Understand’ dimension of Bloom’s taxonomy. The results of the control group indicated that digital puzzle games could help students memorize and review medical terminology, which reached the ‘Remember’ dimension of Bloom’s taxonomy. The findings suggest that teachers of medical terminology could use digital games to assist their teaching according to their goals on cognitive learning. Adequate use of those games could help improve students’ self-directed learning and further enhance their learning outcome on medical terminology.

Keywords: digital game-based learning, medical terminology, nursing education, self-directed learning, technology acceptance model

Procedia PDF Downloads 170

Authors: Dania Baaboud, Renad Al-zahrani, Mahnoor Khan, Riya Afroz

Abstract:

Flo is a smart period-tracking tool that uses artificial intelligence (AI) to offer individualized reproductive health predictions and insights. Flo makes very accurate predictions about menstrual cycles, ovulation, and fertility windows by evaluating user inputs, including cycle duration, symptoms, and patterns. Its machine learning algorithms are constantly evolving, providing personalized health recommendations, instructional materials, and early identification of possible health abnormalities such as reproductive problems and hormone imbalances. Flo, which was introduced in 2015 and upgraded with AI in 2017, is a revolutionary use of technology in healthcare that empowers people to make knowledgeable decisions regarding their well-being. Despite its advantages, our study included drawbacks, such as limited access to premium services and a small sample size. While highlighting unique characteristics, a comparative comparison with similar applications such as Clue and Glow confirmed Flo's outstanding AI integration for individualized healthcare. All things considered, Flo is a prime example of how AI can be used to tackle intricate biological processes, giving consumers the ability to efficiently control their reproductive health and opening the door for improvements in individualized medical technology.

Keywords: Flo, period-tracking app, period symptoms, women’s health, machinery

Procedia PDF Downloads 10

Authors: Didem Aslantaş

Abstract:

In this study, the reforms carried out by the Justice and Development Party, which came to power in 2002, and how the foreign policy understanding it transformed reflected on the relations with Syria will be analyzed from the social constructivist theory. Contrary to the increasing security concerns of the states after the September 11 attacks, the main problem of the research is how the relations between Syria and Turkey developed and how they progressed in non-security dimensions. In order to find an answer to this question, the basic assumptions of the constructivist theory will be used. Since there is a limited number of studies in the literature, a comparative analysis of the Adana Consensus and the Cooperation Agreement between the Republic of Turkey and the Syrian Arab Republic, and the Joint Cooperation Agreement Against Terrorism and Terrorist Organizations will be included. In order to answer the main problem of the research and to support the arguments, document and archive scanning methods from qualitative research methods will be used. In the first part of the study, what the social constructivist theory is and its basic assumptions are explained, while in the second part, Turkey-Syria relations between 2002-2011 are included. In the third and last part, the relations between the two countries will be tried to be read through social constructivism by referring to the foreign policy features of the Ak Party period.

Keywords: Social Constructivist Theory, foreign policy analysis, Justice and Development Party, Syria

Procedia PDF Downloads 87

Authors: Leah Wright, Trevor Townsend

Abstract:

Mode choice models are crucial instruments in the analysis of travel behaviour. These models show the relationship between an individual’s choice of transportation mode for a given O-D pair and the individual’s socioeconomic characteristics such as household size and income level, age and/or gender, and the features of the transportation system. The most popular functional forms of these models are based on Utility-Based Choice Theory, which addresses the uncertainty in the decision-making process with the use of an error term. However, with the development of artificial intelligence, many researchers have started to take a different approach to travel demand modelling. In recent times, researchers have looked at using neural networks, fuzzy logic and rough set theory to develop improved mode choice formulas. The concept of cloud theory has recently been introduced to model decision-making under uncertainty. Unlike the previously mentioned theories, cloud theory recognises a relationship between randomness and fuzziness, two of the most common types of uncertainty. This research aims to investigate the use of cloud theory in mode choice models. This paper highlights the conceptual framework of the mode choice model using cloud theory. Merging decision-making under uncertainty and mode choice models is state of the art. The cloud theory model is expected to address the issues and concerns with the nested logit and improve the design of mode choice models and their use in travel demand.

Keywords: Cloud theory, decision-making, mode choice models, travel behaviour, uncertainty

Procedia PDF Downloads 389

Authors: G. Peker, Tolga N. Aynur, E. Tinar

Abstract:

In order to determine the energy consumption level and cooling characteristics of a domestic refrigerator controlled with various cooling system algorithms, a side by side type (SBS) refrigerator was tested in temperature and humidity controlled chamber conditions. Two different control algorithms; so-called drop-in and frequency controlled variable capacity compressor algorithms, were tested on the same refrigerator. Refrigerator cooling characteristics were investigated for both cases and results were compared with each other. The most important comparison parameters between the two algorithms were taken as; temperature distribution, energy consumption, evaporation and condensation temperatures, and refrigerator run times. Standard energy consumption tests were carried out on the same appliance and resulted in almost the same energy consumption levels, with a difference of %1,5. By using these two different control algorithms, the power consumptions character/profile of the refrigerator was found to be similar. By following the associated energy measurement standard, the temperature values of the test packages were measured to be slightly higher for the frequency controlled algorithm compared to the drop-in algorithm. This paper contains the details of this experimental study conducted with different cooling control algorithms and compares the findings based on the same standard conditions.

Keywords: control algorithm, cooling, energy consumption, refrigerator

Procedia PDF Downloads 376

Authors: Kashika P. H.

Abstract:

The development of computer vision systems has been greatly aided by the efficient and precise detection of images and videos. Although the ability to recognize and comprehend images is a strength of the human brain, employing technology to tackle this issue is exceedingly challenging. In the past few years, the use of Deep Learning algorithms to treat object detection has dramatically expanded. One of the key issues in the realm of image recognition is the recognition and detection of certain notable people from randomly acquired photographs. Face recognition uses a way to identify, assess, and compare faces for a variety of purposes, including user identification, user counting, and classification. With the aid of an accessible deep learning-based API, this article intends to recognize various faces of people and their facial descriptors more accurately. The purpose of this study is to locate suitable individuals and deliver accurate information about them by using the Amazon Rekognition system to identify a specific human from a vast image dataset. We have chosen the Amazon Rekognition system, which allows for more accurate face analysis, face comparison, and face search, to tackle this difficulty.

Keywords: Amazon rekognition, API, deep learning, computer vision, face detection, text detection

Procedia PDF Downloads 108

Authors: Changyong Liu, Junda Tong, Feng Xu, Ninggui Huang

Abstract:

In the injection molding process, the performance of cooling channels is crucial to the part quality. Through the application of conformal cooling channels fabricated via metal additive manufacturing, part distortion, warpage can be greatly reduced and cycle time can be greatly shortened. However, the properties of additively manufactured conformal cooling channels are quite different from conventional drilling processes such as the poorer dimensional accuracy and larger surface roughness. These features have significant influences on its cooling performance. In this study, test molds with the cooling channel diameters of φ2 mm, φ3 mm and φ4 mm were fabricated via selective laser melting and conventional drilling process respectively. A test system was designed and manufactured to measure the pressure difference between the channel inlet and outlet, the coolant flow rate and the temperature variation during the heating process. It was found that the cooling performance of SLM-fabricated channels was poorer than drilled cooling channels due to the smaller sectional area of cooling channels resulted from the low dimensional accuracy and the unmolten particles adhered to the channel surface. Theoretical models were established to determine the friction factor and heat transfer coefficient of SLM-fabricated cooling channels. These findings may provide guidance to the design of conformal cooling channels.

Keywords: conformal cooling channels, selective laser melting, cooling performance, injection molding

Procedia PDF Downloads 155

Authors: Hamid Goharnejad, Milad Sadeghpoor Moalem, Mahmood Zakeri Niri, Leili Sadeghi Khalegh Abadi

Abstract:

While there are many benefits to using reservoir dams, their break leads to destructive effects. From the viewpoint of International Committee of Large Dams (ICOLD), dam break means the collapse of whole or some parts of a dam; thereby the dam will be unable to hold water. Therefore, studying dam break phenomenon and prediction of its behavior and effects reduces losses and damages of the mentioned phenomenon. One of the most common types of reservoir dams is embankment dam. Overtopping in embankment dams occurs because of flood discharge system inability in release inflows to reservoir. One of the most important issues among managers and engineers to evaluate the performance of the reservoir dam rim when sliding into the storage, creating waves is large and long. In this study, the effects of floods which caused the overtopping of the dam have been investigated. It was assumed that spillway is unable to release the inflow. To determine outflow hydrograph resulting from dam break, numerical model using Flow-3D software and empirical equations was used. Results of numerical models and their comparison with empirical equations show that numerical model and empirical equations can be used to study the flood resulting from dam break.

Keywords: embankment dam break, empirical equations, Taleghan dam, Flow-3D numerical model

Procedia PDF Downloads 325

Authors: Mitakshara Sharma, Sonal Sharma

Abstract:

Vesiculobullous diseases are heterogeneous group of dermatological disorders with protean manifestations. The most important technique for the patients with vesiculobullous diseases is conventional histopathology and confirmatory tests like direct immunofluorescence (DIF) and indirect immunofluorescence (IIF). DIF has been used for decades to investigate pathophysiology and in the diagnosis. It detects molecules such as immunoglobulins and complement components. It is done on the perilesional skin. Diagnosis of DIF test depends on features like primary site of the immune deposits, class of immunoglobulin, number of immune deposits and deposition at other sites. The aim of the study is to correlate DIF with clinical and histopathological findings and to analyze the utility of DIF in the diagnosis of these disorders. It is a retrospective descriptive study conducted for 2 years from 2015 to 2017 in Department of Pathology, GTB Hospital on perilesional punch biopsies of vesiculobullous lesions. Biopsies were sent in Michael’s medium. The specimens were washed, frozen and incubated with fluorescein isothiocyanate (FITC) tagged antihuman antibodies IgA, IgG, IgM, C3 & F and were viewed under fluorescent microscope. Out of 401 skin biopsies submitted for DIF, 285 were vesiculobullous diseases, in which the most common was Pemphigus vulgaris (34%) followed by Bullous pemphigoid (21.5%), Dermatitis herpetiformis (16%), Pemphigus foliaceus (11.9%), Linear IgA disease (11.9%), Epidermolysisbullosa (2.39%) and Pemphigus herpetiformis (1.7%). We will be presenting the DIF findings in the all these vesiculobullous diseases. DIF in conjugation with histopathology gives the best diagnostic yield in these lesions. It also helps in the diagnosis whenever there is a clinical and histopathological overlap.

Keywords: antibodies, direct immunofluorescence, pemphigus, vesiculobullous

Procedia PDF Downloads 368

Authors: Leah Lee

Abstract:

This paper examines the correlation between deep learning models and emotions with noises to see whether or not noises mask emotions. The deep learning models used are plain convolutional neural networks (CNN), auto-encoder, long short-term memory (LSTM), and Visual Geometry Group-16 (VGG-16). Emotion datasets used are Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS), Crowd-sourced Emotional Multimodal Actors Dataset (CREMA-D), Toronto Emotional Speech Set (TESS), and Surrey Audio-Visual Expressed Emotion (SAVEE). To make it four times bigger, audio set files, stretch, and pitch augmentations are utilized. From the augmented datasets, five different features are extracted for inputs of the models. There are eight different emotions to be classified. Noise variations are white noise, dog barking, and cough sounds. The variation in the signal-to-noise ratio (SNR) is 0, 20, and 40. In summation, per a deep learning model, nine different sets with noise and SNR variations and just augmented audio files without any noises will be used in the experiment. To compare the results of the deep learning models, the accuracy and receiver operating characteristic (ROC) are checked.

Keywords: auto-encoder, convolutional neural networks, long short-term memory, speech emotion recognition, visual geometry group-16

Procedia PDF Downloads 81

Authors: Musarrat Jabeen Khan, Uzma Azam, Kainat Umar, Jazba Amber Satti, Aiman Shehzadi, Nimo Omer

Abstract:

This study aimed to examine the comparison between substance abusers and non-abusers on anxiety, peer pressure, and risk-taking behavior among young adults. The sample consisted of 138 individuals including 64 female and 71 males, age range from 17-35 years, drawn from non-clinical population through convenient sampling. Questionnaire technique was used for the information assortment and the scales were susceptibility to peer pressure (Dieman, Pamella, Shope & Butchart, 1987), Zung self-rating anxiety scale (Zung, 1971), and risk-taking questionnaire (Gullone, Moore, Moss & Boyd, 2000) having alpha reliability of .54, .88, and .80 respectively. Results showed that anxiety negatively correlates with the risk-taking behavior. High level of anxiety stops an individual to involve himself in risk taking activities. Peer pressure have positive correlation with risk-taking behavior. Females are more susceptible to peer pressure irrespective of being abusers or non-abusers as compared to male abusers and non-abusers. Substance abusers have less anxiety as compared to non-abusers but are more susceptible to peer pressure and risk-taking behaviors.

Keywords: substance, substance abuse, anxiety, peer pressure, risk-taking behavior

Procedia PDF Downloads 167

Authors: Yang Zhou, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

Abstract:

Traffic prediction is a fundamental problem in urban environment, facilitating the smart management of various businesses, such as taxi dispatching, bike relocation, and stampede alert. Most earlier methods rely on identifying the intrinsic spatial-temporal correlation to forecast. However, the complex nature of this problem entails a more sophisticated solution that can simultaneously capture the mutual influence of both adjacent and far-flung areas, with the information of time-dimension also incorporated seamlessly. To tackle this difficulty, we propose a new multi-phase architecture, DSTDS (Dual Spatial-Temporal Data Scheme for traffic prediction), that aims to reveal the underlying relationship that determines future traffic trend. First, a graph-based neural network with an attention mechanism is devised to obtain the static features of the road network. Then, a multi-granularity recurrent neural network is built in conjunction with the knowledge from a grid-based model. Subsequently, the preceding output is fed into a spatial-temporal super-resolution module. With this 3-phase structure, we carry out extensive experiments on several real-world datasets to demonstrate the effectiveness of our approach, which surpasses several state-of-the-art methods.

Keywords: traffic prediction, spatial-temporal, recurrent neural network, dual data scheme

Procedia PDF Downloads 119

Authors: Amr AbdelAzim Ali, G. A. Elsheikh, Moutaz M. Hegazy

Abstract:

Reaction wheels (RWs) are generally used as main actuator in the attitude control system (ACS) of spacecraft (SC) for fast orientation and high pointing accuracy. In order to achieve the required accuracy for the RWs model, the main characteristics of the RWs that necessitate analysis during the ACS design phase include: technical features, sequence of operating and RW control logic are included in function (behavior) model. A mathematical model is developed including the various errors source. The errors in control torque including relative, absolute, and error due to time delay. While the errors in angular velocity due to differences between average and real speed, resolution error, loose in installation of angular sensor, and synchronization errors. The friction torque is presented in the model include the different feature of friction phenomena: steady velocity friction, static friction and break-away torque, and frictional lag. The model response is compared with the experimental torque and frequency-response characteristics of tested RWs. Based on the created RW model, some criteria of optimization based control torque allocation problem can be recommended like: avoiding the zero speed crossing, bias angular velocity, or preventing wheel from running on the same angular velocity.

Keywords: friction torque, reaction wheels modeling, software in the loop, spacecraft attitude control

Procedia PDF Downloads 268

Authors: Ji-Wook Mauk, Yu-Suk Kim, Hyung-Joon Kim

Abstract:

This study carried out comparative seismic performance of reinforced concrete frames infilled by masonry walls with different heights. Partial and fully infilled RC frames were modeled for the research objectives and the analysis model for a bare reinforced concrete frame was established for comparison. Non-linear static analyses for the studied frames were performed to investigate their structural behavior under extreme loading conditions and to find out their collapse mechanism. It was observed from analysis results that the strengths of the partial infilled RC frames are increased and their ductility is reduced, as infilled masonry walls are higher. Especially, Reinforced concrete frames with a higher partial infilled masonry wall would experience shear failures. Non-linear dynamic analyses using 10 earthquake records show that the bare and fully infilled reinforced concrete frames present stable collapse mechanism while the reinforced concrete frames with a partially infilled masonry wall collapse in more brittle manner due to short-column effects.

Keywords: fully infilled RC frame, partially infilled RC frame, masonry wall, short-column effect

Procedia PDF Downloads 425

Authors: Ahmed Tafraoui, Gilles Escadeillas, Thierry Vidal

Abstract:

The southern Algeria is known for its huge sand dunes that cover part of its territory (Sahara). This sand has features that allow a glimpse of a recovery in the construction field in the form of Ultra High Performance Concrete (UHPC). This type of concrete using a large amount of silica fume, ultra fine addition that gives very high performance but is also relatively rare and expensive. Replacing it with another addition to equivalent properties, such as metakaolin, can also be considered. The objective of this study is to both enhance the sand dunes of Erg south west western Algeria but also reduce manufacturing costs of Ultra High Performance Concrete to incorporating metakaolin to instead of silica fume. Performances to determine mechanical performance are instantaneous, compression and bending. Initially, we characterized the Algerian sand dune. Then, we have to find a formulation of UHPC, adequate in terms of implementation and to replace silica fume by metakaolin. Finally, we studied the actual value of the sand dune. Concrete obtained have very high mechanical performance, up to a compressive strength of 250 MPa, a tensile strength of 45 MPa by bending with the method of heat treatment. This study shows that the enhancement of dune sand studied is quite possible in UHPC, and in particular UHPC bundles and the replacement of silica fume by metakaolin do not alter the properties of these concretes.

Keywords: Ultra High Performance Concrete, sand dune, formulations, silica fume, metakaolin, strength

Procedia PDF Downloads 474

Authors: Megha Gupta, Nupur Prakash

Abstract:

Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network (CNN) architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

Procedia PDF Downloads 201

Authors: Pooja Khanal, Huaming Zhang

Abstract:

Labeling of issues/bugs, also known as bug classification, plays a vital role in software engineering. Some known labels/classes of bugs are 'User Interface', 'Security', and 'API'. Most of the time, when a reporter reports a bug, they try to assign some predefined label to it. Those issues are reported for a project, and each project is a repository in GitHub/GitLab, which contains multiple issues. There are many software project repositories -ranging from individual projects to commercial projects. The labels assigned for different repositories may be dependent on various factors like human instinct, generalization of labels, label assignment policy followed by the reporter, etc. While the reporter of the issue may instinctively give that issue a label, another person reporting the same issue may label it differently. This way, it is not known mathematically if a label in one repository is similar or different to the label in another repository. Hence, the primary goal of this research is to find the semantic differences between bug labeling of different repositories via machine learning. Independent optimal classifiers for individual repositories are built first using the text features from the reported issues. The optimal classifiers may include a combination of multiple classifiers stacked together. Then, those classifiers are used to cross-test other repositories which leads the result to be deduced mathematically. The produce of this ongoing research includes a formalized open-source GitHub issues database that is used to deduce the similarity of the labels pertaining to the different repositories.

Keywords: bug classification, bug labels, GitHub issues, semantic differences

Procedia PDF Downloads 206

Authors: Ali Babajanzade, Hossein Bozorgian

Abstract:

Cognitive load plays an important role in learning in general and L2 listening comprehension in particular. This study is an attempt to investigate the effect of metacognitive strategy intervention through dialogic interaction (MSIDI) on L2 listeners’ cognitive load. A mixed-method design with 50 participants of male and female Iranian lower-intermediate learners between 20 to 25 years of age was used. An experimental group (n=25) received weekly interventions based on metacognitive strategy intervention through dialogic interaction for ten sessions. The second group, which was control (n=25), had the same listening samples with the regular procedure without a metacognitive intervention program in each session. The study used three different instruments: a) a modified version of the cognitive load questionnaire, b) digit span tests, and c) focused group interviews to investigate listeners’ level of cognitive load throughout the process. Results testified not only improvements in listening comprehension in MSIDI but a radical shift of cognitive load rate within this group. In other words, listeners experienced a lower level of cognitive load in MSIDI in comparison with their peers in the control group.

Keywords: cognitive load theory, human mental functioning, metacognitive theory, listening comprehension, sociocultural theory

Procedia PDF Downloads 151

Authors: Romisaa Ali

Abstract:

This paper presents a comparison between twin-delayed Deep Deterministic Policy Gradient (TD3) and Soft Actor-Critic (SAC) reinforcement learning algorithms in the context of training robust navigation policies for Jackal robots. By leveraging an open-source framework and custom motion control environments, the study evaluates the performance, robustness, and transferability of the trained policies across a range of scenarios. The primary focus of the experiments is to assess the training process, the adaptability of the algorithms, and the robot’s ability to navigate in previously unseen environments. Moreover, the paper examines the influence of varying environmental complexities on the learning process and the generalization capabilities of the resulting policies. The results of this study aim to inform and guide the development of more efficient and practical reinforcement learning-based navigation policies for Jackal robots in real-world scenarios.

Keywords: Jackal robot environments, reinforcement learning, TD3, SAC, robust navigation, transferability, custom environment

Procedia PDF Downloads 109

Authors: Luc Conti, Dimitry Dumont-Fillon, Harald van Lintel, Eric Chappel

Abstract:

Flow control valves comprise a silicon flexible membrane that deflects against a substrate, usually made of glass, containing pillars, an outlet hole, and anti-stiction features. However, there is a strong interest in using silicon instead of glass as substrate material, as it would simplify the process flow by allowing the use of well controlled anisotropic etching. Moreover, specific devices demanding a bending of the substrate would also benefit from the inherent outstanding mechanical strength of monocrystalline silicon. Unfortunately, direct Si-Si bonding is not easily achieved with highly structured wafers since residual stress may prevent the good adhesion between wafers. Using a thermoplastic polymer, such as parylene, as intermediate layer is not well adapted to this design as the wafer-to-wafer alignment is critical. An alternative anodic bonding method using an intermediate borosilicate layer has been successfully tested. This layer has been deposited onto the silicon substrate. The bonding recipe has been adapted to account for the presence of the SOI buried oxide and intermediate glass layer in order not to exceed the breakdown voltage. Flow control valves dedicated to infusion of viscous fluids at very high pressure have been made and characterized. The results are compared to previous data obtained using the standard anodic bonding method.

Keywords: anodic bonding, evaporated glass, flow control valve, drug delivery

Procedia PDF Downloads 204

Authors: Roslina Che Soh

Abstract:

Best interest of the child has been the prevailing principle of the custody legislations of most nations in the world. The tremendous shift from parental rights to parental responsibilities throughout the centuries had made the principle of best interests of the child as the utmost matter which parents must uphold in child upbringing. Despite the commitment to this principle is significantly enshrined in the United Nation Convention on Rights of the Child, the content and application of the principle differs across borders. Differences persist notwithstanding many countries have experienced a substantial shift over the last several decades in the types of custodial arrangements that are thought to best serve children’s interests. The laws in Malaysia similarly uphold this principle but do not provide further deliberation on the principle itself. The principle is entirely developed by the courts through decided cases. Thus, this paper seeks to discuss the extent of the application of best interest of the child principle in custody disputes. In doing so, it attempts to provide an overview of the current laws and the approach of the Civil and the Shariah courts in Malaysia in applying the principle in determining custody disputes. For purposes of comparison, it briefly examines the legislations and the courts practices in Australia and England on this matter. The purpose is to determine the best standard to be adopted by Malaysia and to propose improvement to the laws whenever appropriate.

Keywords: child custody, best interest, Malaysian law, bioinformatics, biomedicine

Procedia PDF Downloads 279

Authors: Nebiat Lemenih Lenger

Abstract:

Today, the digital economy is evolving faster than ever in Ethiopia. Platforms that provide a ride-hailing service are growing fast in the country. The market welcomed them as they disrupt it with quality services and lower prices. This revolution is, however, not without challenges. These include cybersecurity breaches, facilitating illegal economic activities, and challenging concepts of privacy. To mitigate the risks and utilize the benefits, appropriate regulation should be introduced in the economy. By identifying legal and institutional gaps in Ethiopia`s digital economy, this research work assists the government`s effort to create a better digital economy. Moreover, this study, being a pioneer study in the area, will be an input for further studies in academia. The research employs a qualitative legal research method and analyzes various legal and policy instruments in Ethiopia in comparison with best international experiences. As this research applies a qualitative research method, a grounded theory method of data analysis is used. The research concluded that Ethiopia is far from designing appropriate legal and regulatory infrastructures. Due to the government monopoly of the sector, there is poor digital infrastructure in the country. The existing labor laws have no specific provisions on the rights and obligations of gig workers.

Keywords: Ethiopia, gig economy, digital, ride-hailing, regulation

Procedia PDF Downloads 99

Authors: Khaled Ayfi

Abstract:

In industrial oxygen systems at high temperature and high pressure, contamination by solid particles is one of the principal causes of ignition hazards. Indeed, gas can sweep away particles, generated by corrosion inside the pipes or during maintenance operations (welding residues, careless disassembly, etc.) and produce accumulations at places where the gas velocity decrease. Moreover, in such an environment rich in oxygen (oxidant), particles are highly reactive and can ignite system walls more actively and at higher temperatures. Oxidation based thermal effects are responsible for mechanical properties lost, leading to the destruction of the pressure equipment wall. To deal with this problem, a numerical analysis is done regarding a sample representative of a wall subjected to pressure and temperature. The validation and analysis are done comparing the numerical simulations results to experimental measurements. More precisely, in this work, we propose a numerical model that describes the thermomechanical behavior of thin metal disks under pressure and subjected to laser heating. This model takes into account the geometric and material nonlinearity and has been validated by the comparison of simulation results with experimental measurements.

Keywords: ignition, oxygen, numerical simulation, thermomechanical behavior

Procedia PDF Downloads 109

Authors: Aleksandra Zysk, Pawel Badura

Abstract:

Recognizing and controlling vocal registers during singing is a difficult task for beginner vocalist. It requires among others identifying which part of natural resonators is being used when a sound propagates through the body. Thus, an application has been designed allowing for sound recording, automatic vocal register recognition (VRR), and a graphical user interface providing real-time visualization of the signal and recognition results. Six spectral features are determined for each time frame and passed to the support vector machine classifier yielding a binary decision on the head or chest register assignment of the segment. The classification training and testing data have been recorded by ten professional female singers (soprano, aged 19-29) performing sounds for both chest and head register. The classification accuracy exceeded 93% in each of various validation schemes. Apart from a hard two-class clustering, the support vector classifier returns also information on the distance between particular feature vector and the discrimination hyperplane in a feature space. Such an information reflects the level of certainty of the vocal register classification in a fuzzy way. Thus, the designed recognition and training application is able to assess and visualize the continuous trend in singing in a user-friendly graphical mode providing an easy way to control the vocal emission.

Keywords: classification, singing, spectral analysis, vocal emission, vocal register

Procedia PDF Downloads 308

Authors: Fares Laouacheria, Said Kechida, Moncef Chabi

Abstract:

The objective of the study was based on the hydrological routing modelling for the continuous monitoring of the hydrological situation in the Moudjar river catchment, especially during floods with Hydrologic Engineering Center–Hydrologic Modelling Systems (HEC-HMS). The HEC-GeoHMS was used to transform data from geographic information system (GIS) to HEC-HMS for delineating and modelling the catchment river in order to estimate the runoff volume, which is used as inputs to the hydrological routing model. Two hydrological routing models were used, namely Muskingum and Muskingum routing models, for conducting this study. In this study, a comparison between the parameters of the Muskingum and Muskingum-Cunge routing models in HEC-HMS was used for modelling flood routing in the Moudjar river catchment and determining the relationship between these parameters and the physical characteristics of the river. The results indicate that the effects of input parameters such as the weighting factor "X" and travel time "K" on the output results are more significant, where the Muskingum routing model was more sensitive to input parameters than the Muskingum-Cunge routing model. This study can contribute to understand and improve the knowledge of the mechanisms of river floods, especially in ungauged river catchments.

Keywords: HEC-HMS, hydrological modelling, Muskingum routing model, Muskingum-Cunge routing model

Procedia PDF Downloads 279

Authors: Moataz Medhat, Essam Khalil, Hatem Haridy

Abstract:

The present study investigates the flame structure of turbulent diffusion flame of synthesis fuel in a 300 KW swirl-stabilized burner. The three-dimensional model adopts a realizable k-ε turbulent scheme interacting with two-dimensional PDF combustion scheme by applying flamelet concept. The study reveals more characteristics on turbulent diffusion flame of synthesis fuel when changing the inlet air swirl number and the burner quarl angle. Moreover, it concerns with studying the effect of flue gas recirculation and staging with taking radiation effect into consideration. The comparison with natural gas was investigated. The study showed two zones of recirculation, the primary one is at the center of the furnace, and the location of the secondary one varies by changing the quarl angle of the burner. The results revealed an increase in temperature in the external recirculation zone as a result of increasing the swirl number of the inlet air stream. Also, it was found that recirculating part of the combustion products decreases pollutants formation especially nitrogen monoxide. The predicted results showed a great agreement when compared with the experiments.

Keywords: gas turbine, syngas, analysis, recirculation

Procedia PDF Downloads 274

Authors: M. Abou Al-alaa, H. A. Elsadek, E. A. Abdallah, E. A. Hashish

Abstract:

A square patch antenna with both frequency and polarization reconfigurability is presented. The antenna consists of a square patch with coplanar feed on the ground plane. On the patch side, there is a parasitic square ring that is responsible for changing the antenna polarization. On the ground plane, there is a rectangular slot. By changing of length of this slot, the antenna resonance frequency can be changed. The antenna operates at 1.57 and 2.45 GHz that used in GPS and Bluetooth applications, respectively. The length of the slot in the proposed antenna is 40 mm, and the antenna operates at the lower frequency (1.57 GHz). By using switches in the ground plane the slot length can be adjust to 24 mm, so the antenna operates at upper frequency (2.45 GHz). Two switches are mounted on the parasitic ring at optimized positions. By switching between the different states of these two switches, the proposed antenna operates with linear polarization (LP) and circular polarization (CP) at each operating frequency. The antenna gain at 1.57 and 2.45 GHz are 5.9 and 7.64 dBi, respectively. The antenna is analyzed using the CST Microwave Studio. The proposed antenna was fabricated and measured. Results comparison shows good agreement. The antenna has applications in several wireless communication systems.

Keywords: microstrip patch antenna, reconfigurable antenna, frequency reconfigurability, polarization reconfigurability, parasitic square ring, linear polarization, circular polarization

Procedia PDF Downloads 538

Authors: Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević, Lidija R. Jevrić, Stela Jokić

Abstract:

The complexes of transition metals with various organic ligands have been extensively studied as models of some important pharmaceutical molecules. It was found that biological properties of different substituted organic molecules are improved when they are complexed by different metals. Therefore, it is of great importance for the development of coordination chemistry to explore the assembly of functional organic ligands with metal ion and to investigate the relationship between the structure and property. In the present work, we have bioassayed the antibacterial potency of benzimidazoles and their metal salts (Cu or Zn) against yeast Sarcina lutea. In order to validate our in vitro study, we performed in silico studies using molecular docking software. The investigated compounds and their metal complexes (Cu, Zn) showed good to moderate inhibitory activity against Sarcina lutea. In silico docking studies of the synthesized compounds suggested that complexed benzimidazoles have a greater binding affinity and improved antibacterial activity in comparison with non-complexed ligands. These results are part of the CMST COST Action No. 1105 "Functional metal complexes that bind to biomolecules".

Keywords: organometallic complexes, benzimidazoles, chemometric design, Sarcina lutea

Procedia PDF Downloads 345

Authors: Azam Tabatabaee, Fereshteh Dastgoshadeh, Akram Tabatabaee

Abstract:

This paper describes the use of by-products as adsorbents for removing heavy metals from aqueous effluent solutions. Products of almond skin, walnut shell, saw dust, rice bran and egg shell were evaluated as metal ion adsorbents in aqueous solutions. A comparative study was done with commercial adsorbents like ion exchange resins and activated carbon too. Batch experiments were investigated to determine the affinity of all of biomasses for, Cd(ΙΙ), Cr(ΙΙΙ), Ni(ΙΙ), and Pb(ΙΙ) metal ions at pH 5. The rate of metal ion removal in the synthetic wastewater by the biomass was evaluated by measuring final concentration of synthetic wastewater. At a concentration of metal ion (50 mg/L), egg shell adsorbed high levels (98.6 – 99.7%) of Pb(ΙΙ) and Cr(ΙΙΙ) and walnut shell adsorbed high levels (35.3 – 65.4%) of Ni(ΙΙ) and Cd(ΙΙ). In this study, it has been shown that by-products were excellent adsorbents for removal of toxic ions from wastewater with efficiency comparable to commercially available adsorbents, but at a reduced cost. Also statistical studies using Independent Sample t Test and ANOVA Oneway for statistical comparison between various elements adsorption showed that there isn’t a significant difference in some elements adsorption percentage by by-products and commercial adsorbents.

Keywords: adsorbents, heavy metals, commercial adsorbents, wastewater, by-products

Procedia PDF Downloads 416