Search results for: deep understanding

Authors: Gorkem Algan, Ilkay Ulusoy, Saban Gonul, Banu Turgut, Berker Bakbak

Abstract:

Computer vision systems recently made a big leap thanks to deep neural networks. However, these systems require correctly labeled large datasets in order to be trained properly, which is very difficult to obtain for medical applications. Two main reasons for label noise in medical applications are the high complexity of the data and conflicting opinions of experts. Moreover, medical imaging datasets are commonly tiny, which makes each data very important in learning. As a result, if not handled properly, label noise significantly degrades the performance. Therefore, a label-noise-robust learning algorithm that makes use of the meta-learning paradigm is proposed in this article. The proposed solution is tested on retinopathy of prematurity (ROP) dataset with a very high label noise of 68%. Results show that the proposed algorithm significantly improves the classification algorithm's performance in the presence of noisy labels.

Keywords: deep learning, label noise, robust learning, meta-learning, retinopathy of prematurity

Procedia PDF Downloads 156

Authors: Kripesh Adhikari, Hamid Bouchachia, Hammadi Nait-Charif

Abstract:

Falls are one of the major causes of injury and death among elderly people aged 65 and above. A support system to identify such kind of abnormal activities have become extremely important with the increase in ageing population. Pose estimation is a challenging task and to add more to this, it is even more challenging when pose estimations are performed on challenging poses that may occur during fall. Location of the body provides a clue where the person is at the time of fall. This paper presents a vision-based tracking strategy where available joints are grouped into three different feature points depending upon the section they are located in the body. The three feature points derived from different joints combinations represents the upper region or head region, mid-region or torso and lower region or leg region. Tracking is always challenging when a motion is involved. Hence the idea is to locate the regions in the body in every frame and consider it as the tracking strategy. Grouping these joints can be beneficial to achieve a stable region for tracking. The location of the body parts provides a crucial information to distinguish normal activities from falls.

Keywords: fall detection, machine learning, deep learning, pose estimation, tracking

Procedia PDF Downloads 183

Authors: Canan Cetin

Abstract:

This essay analyses how gendered shaped views influence on our understanding of global politics. To do so, feminism used as a framework theory, thus masculinity is discussed in order to explain the male-dominated international relations (IR) discipline and the differences of reflections on our perspective considering the politics in a broader perspective. Particularly, it is highlighted that the social and cultural structures of societies have also an impact on our views about international relations and politics. From a different perspective, it is aimed that the sociological and cultural impression of the shifted gender perspectives on the political approach of different nations and societies will be examined by drawing on a range of sources. Instead of supporting one feminist theory, this essay engages with all traditions and enriches their arguments. Specifically, the main objective of the essay is hegemonic and plural masculinity on societies. The essay sets things up theoretically by looking at the nature of masculinity – the stage is set to show how this informs our understanding of IR.

Keywords: feminism, politics, international affairs, social life

Procedia PDF Downloads 201

Authors: R. G. D Jayawardena

Abstract:

The Buddha was known by great wise men from 6th century B.C up to date as a superhuman being born in the world beyond the omnipotent. The Buddha’s doctrinal descriptions reflect his deep enlightenment about imperial and metaphysical knowledge. Buddhology undertaken for this study is an unexposed subject in metaphysical points. The Buddhist wall painting in Sri Lanka depicts deep metaphysical meaning than its simple perspective of estheticism. Buddhology, in some perspectives, has been interpreted as a complete natural science discovered by the Buddha to teach the way of honorable living in perfect happiness and peace of mind till death. Such interpretations which emphasized are based on textual studies. The Buddhology conducted through literal tradition is depicted in wall paintings in Sri Lanka are in visual art with specific techniques rules. The Buddhology, which is investigated on wall paintings, portrays the Buddha in the form of a superhuman being and as an unparalleled person among the Devas, Brahmas, Yakshas, Maras, and humans. The Buddha concept is known to Sri Lankan Buddhists as a person attained to full awakening of wisdom. In personality, the Buddha is depicted as a supernormal person in the world and a rare birth. In brief, the paper will discuss and illustrate the Buddha’s transcendental position and the reality of what he experienced and its authenticity.

Keywords: Buddhology, Metaphysic, Sri Lanka, paintings

Procedia PDF Downloads 200

Authors: Jaspreet Singh, Gurvinder Singh, Prabhsimran Singh, Rajinder Singh, Prithvipal Singh, Karanjeet Singh Kahlon, Ravinder Singh Sawhney

Abstract:

Morphological evaluation of Indian languages is one of the burgeoning fields in the area of Natural Language Processing (NLP). The evaluation of a language is an eminent task in the era of information retrieval and text mining. The extraction and classification of knowledge from text can be exploited for sentiment analysis and morphological evaluation. This study coalesce morphological evaluation and sentiment analysis for the task of classification of farmer suicide cases reported in Punjab state of India. The pre-processing of Punjabi text involves morphological evaluation and normalization of Punjabi word tokens followed by the training of proposed model using deep learning classification on Punjabi language text extracted from online Punjabi news reports. The class-wise accuracies of sentiment prediction for four negatively oriented classes of farmer suicide cases are 93.85%, 88.53%, 83.3%, and 95.45% respectively. The overall accuracy of sentiment classification obtained using proposed framework on 275 Punjabi text documents is found to be 90.29%.

Keywords: deep neural network, farmer suicides, morphological processing, punjabi text, sentiment analysis

Procedia PDF Downloads 317

Authors: E. Yazıcı, H. Sundu, E. Veli Veliev

Abstract:

In order to understand the nature of strong interactions and QCD vacuum, investigation of the meson coupling constants have an important role. The knowledge on the temperature dependence of the form factors is very important for the interpretation of heavy-ion collision experiments. Also, more accurate determination of these coupling constants plays a crucial role in understanding of the hadronic decays. With the increasing of CM energies of the experiments, researches on meson interactions have become one of the more interesting problems of hadronic physics. In this study, we analyze the temperature dependence of the strong form factor of the BcBcJ/ψ vertex using the three point QCD sum rules method. Here, we assume that with replacing the vacuum condensates and also the continuum threshold by their thermal version, the sum rules for the observables remain valid. In calculations, we take into account the additional operators, which appear in the Wilson expansion at finite temperature. We also investigated the momentum dependence of the form factor at T = 0, fit it into an analytic function, and extrapolate into the deep time-like region in order to obtain a strong coupling constant of the vertex. Our results are consistent with the results existing in the literature.

Keywords: QCD sum rules, thermal QCD, heavy mesons, strong coupling constants

Procedia PDF Downloads 188

Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

Abstract:

In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.

Keywords: data estimation, link data, machine learning, road network

Procedia PDF Downloads 508

Authors: Hushyar Azari

Abstract:

Aim and background: Deep brain stimulation (DBS) is regarded as an important therapeutic choice for Parkinson's disease (PD). The two most common targets for DBS are the subthalamic nucleus (STN) and globus pallidus (GPi). This review was conducted to compare the clinical effectiveness of these two targets. Methods: A systematic literature search in electronic databases: Embase, Cochrane Library and PubMed were restricted to English language publications 2010 to 2021. Specified MeSH terms were searched in all databases. Studies which evaluated the Unified Parkinson's Disease Rating Scale (UPDRS) III were selected by meeting the following criteria: (1) compared both GPi and STN DBS; (2) had at least three months follow-up period; (3)at least five participants in each group; (4)conducted after 2010. Study quality assessment was performed using the Modified Jadad Scale. Results: 3577 potentially relevant articles were identified, of these, 3569 were excluded based on title and abstract, duplicate and unsuitable article removal. Eight articles satisfied the inclusion criteria and were scrutinized (458 PD patients). According to Modified Jadad Scale, the majority of included studies had low evidence quality which was a limitation of this review. 5 studies reported no statistically significant between-group difference for improvements in UPDRS ш scores. At the same time, there were some results in terms of pain, action tremor, rigidity, and urinary symptoms, which indicated that STN DBS might be a better choice. Regarding the adverse effects, GPi was superior. Conclusion: It is clear that other larger randomized clinical trials with longer follow-up periods and control groups are needed to decide which target is more efficient for deep brain stimulation in Parkinson’s disease and imposes fewer adverse effects on the patients. Meanwhile, STN seems more reasonable according to the results of this systematic review.

Keywords: brain stimulation, globus pallidus, Parkinson's disease, subthalamic nucleus

Procedia PDF Downloads 176

Authors: Anjali Malik

Abstract:

This paper presents a review of the literature on behavioral addictions with a particular focus on understanding online gaming habits among adolescents. Extant researches yielded many different sets of antecedent factors for developing pathological online gaming behavior. This paper draws findings from the most-cited publications most closely associated with factors explaining why individuals develop such kind of problematic behavior. What emerges as central to understanding this phenomenon is the presence of multiple variable causes that take into account the individual, the environment and their interaction to explain the risk behavior such as pathological online gaming. In addition to that role of some mediating factors and pull factors has also been discussed, along with the consequences on personal, social and academic performance resulting from such kind of addictive behavior. The paper also makes recommendations for future research including developing a deeper understanding of the phenomena studied here by examining the relative contribution of these multiple-risk contexts.

Keywords: pathological gaming, gaming addiction, adolescents, behavior

Procedia PDF Downloads 229

Authors: Ricky Saputra, Rashmi Walvekar, Mohammad Khalid

Abstract:

Landfills, water contamination, and toxic gas emission are a few impacts faced by the environment due to the increasing number of αof waste rubber tires (WRT). In spite of such concerning issue, only minimal efforts are taken to reclaim or recycle these wastes as their products are generally not-profitable for companies. Unlike the typical reclamation process, devulcanization is a method to selectively cleave sulfidic bonds within vulcanizates to avoid polymeric scissions that compromise elastomer’s mechanical and tensile properties. The process also produces devulcanizates that are re-processable similar to virgin rubber. Often, a devulcanizing agent is needed. In the current study, novel and sustainable ammonium chloride-based ternary deep eutectic solvents (TDES), with a different number of α-hydrogens, were utilised to devulcanize ground rubber tire (GRT) as an effort to implement green chemistry to tackle such issue. 40-mesh GRT were soaked for 1 day with different TDESs and sonicated at 37-80 kHz for 60-120 mins and heated at 100-140oC for 30-90 mins. Devulcanizates were then filtered, dried, and evaluated based on the percentage of by means of Flory-Rehner calculation and swelling index. The result shows that an increasing number of α-Hs increases the degree of devulcanization, and the value achieved was around eighty-percent, thirty percent higher than the typical industrial-autoclave method. Resulting bondages of devulcanizates were also analysed by Fourier transform infrared spectrometer (FTIR), Horikx fitting, and thermogravimetric analyser (TGA). The earlier two confirms only sulfidic scissions were experienced by GRT through the treatment, while the latter proves the absence or negligibility of carbon-chains scission.

Keywords: ammonium, sustainable, deep eutectic solvent, α-hydrogen, waste rubber tire

Procedia PDF Downloads 124

Authors: Mária Csernoch, Piroska Biró

Abstract:

The legends about “user-friendly” and “easy-to-use” birotical tools (computer-related office tools) have been spreading and misleading end-users. This approach has led us to the extremely high number of incorrect documents, causing serious financial losses in the creating, modifying, and retrieving processes. Our research proved that there are at least two sources of this underachievement: (1) The lack of the definition of the correctly edited, formatted documents. Consequently, end-users do not know whether their methods and results are correct or not. They are not aware of their ignorance. They are so ignorant that their ignorance does not allow them to realize their lack of knowledge. (2) The end-users’ problem-solving methods. We have found that in non-traditional programming environments end-users apply, almost exclusively, surface approach metacognitive methods to carry out their computer related activities, which are proved less effective than deep approach methods. Based on these findings we have developed deep approach methods which are based on and adapted from traditional programming languages. In this study, we focus on the most popular type of birotical documents, the text-based documents. We have provided the definition of the correctly edited text, and based on this definition, adapted the debugging method known in programming. According to the method, before the realization of text editing, a thorough debugging of already existing texts and the categorization of errors are carried out. With this method in advance to real text editing users learn the requirements of text-based documents and also of the correctly formatted text. The method has been proved much more effective than the previously applied surface approach methods. The advantages of the method are that the real text handling requires much less human and computer sources than clicking aimlessly in the GUI (Graphical User Interface), and the data retrieval is much more effective than from error-prone documents.

Keywords: deep approach metacognitive methods, error-prone birotical documents, financial losses, human and computer resources

Procedia PDF Downloads 379

Authors: Dominic Roulx

Abstract:

Many scholars have in the past decade emphasized the relevance of Adorno’s criticism of the rationalized domination of nature (Naturbeherrschung) for thinking the environmental crisis. Beyond the intersubjective critical models of thinkers such as Habermas and Honneth, Adorno’s critical theory has the benefit, according to them, of disclosing the entwinement of social and natural domination in a critically productive way. The author will be arguing in this paper that Adorno’s model of critical theory displays a theoretical framework that is both original and relevant for thinking the ins and outs of the currentenvironmental crisis. To do so, he first construe Adorno’s understanding of the historical domination of nature and argue that Adorno’s method for its criticizing is immanent critique. He puts emphasis on how his understanding of the domination of nature implicitly implies an account of thedialectical relationship between reason and nature. In doing so, he presents a naturalistic understanding of his idea of the primacy of the object. Second, regarding Adorno’s concept of nature, he discusses what he sees as the shortcomings of many commentators’ understanding of the concept of nature in Adorno. He contends that they tend to fall short of Adorno’s concept of nature in failing to make sense of its thoroughly negative signification, thereby falling into an uncritical and fetichized comprehension of “nature. Third, he discusses the prospect for a possible “reconciliation” (Versöhnung) of nature with society. Highlighting how the domination of nature proves to produce the necessary conditions for its own overcoming, he contends that reconciliation with nature relies mainly on the subject’s capacity for critical self-reflection.

Keywords: german philosophy, adorno, nature, environmental crisis

Procedia PDF Downloads 93

Authors: Jennifer Nutton, Gayle Ployer, Ky Scott, Jenny Morgan

Abstract:

Working in a circle within higher education creates a decolonial space of mutual respect, responsibility, and reciprocity that facilitates collaborative learning and deep connections among learners and instructors. This approach is beyond simply facilitating a group in a circle but opens the door to creating a sacred space connecting each member to the land, to the Indigenous peoples who have taken care of the lands since time immemorial, to one another, and to one’s own positionality. These deep connections not only center human knowledges and relationships but also acknowledges responsibilities to land. Working in a circle as a relational pedagogical praxis also disrupts institutional power dynamics by creating a space of collaborative learning and deep connections in the classroom. Inherent within circle work is to facilitate connections not just academically but emotionally, physically, culturally, and spiritually. Recent literature supports the use of online talking circles, finding that it can offer a more relational and experiential learning environment, which is often absent in the virtual world and has been made more evident and necessary since the pandemic. These deeper experiences of learning and connection, rooted in both knowledge and the land, can then be shared with openness and vulnerability with one another, facilitating growth and change. This process of beginning with the land is critical to ensure we have the grounding to obstruct the ongoing realities of colonialism. The authors, who identify as both Indigenous and non-Indigenous, as both educators and learners, reflect on their teaching and learning experiences in circle. They share a relational pedagogical praxis framework that has been successful in educating future social workers, environmental activists, and leaders in social and human services, health, legal and political fields.

Keywords: circle work, relational pedagogies, decolonization, distance education

Procedia PDF Downloads 74

Authors: Sarojini Imran, Riza Firmansyah, Aula Ramadhan, Chudamul Furqon, Achfriyatama Oktariflandi

Abstract:

This article delves into the participatory approach in formulating a master plan for the development of pioneer village tourism in Cibubuan, Sumedang. We explore the process of participatory mapping that involves the active participation of the local community in planning and envisioning the future of village tourism. This research considers the positive impact that arises when the community takes an active role in designing a master plan that benefits the local economy while preserving culture and the environment. The results of this research reveal that the participatory approach can create a more accurate and community-responsive mapping that aligns with the aspirations of the people in Cibubuan Village. It also provides a deep insight into how community-developed mapping can guide the development of sustainable tourism. By offering a deeper understanding of the participatory role in village tourism development planning, this article provides essential insights for stakeholders and researchers in this field. We hope this article will inspire more communities to adopt a participatory approach in planning the future of their village tourism.

Keywords: participatory masterplan, pioneer village tourism, sustainable tourism, community engagement, Cibubuan Village

Procedia PDF Downloads 66

Authors: Rachid El Khoury

Abstract:

Chronic pain is perhaps the most burdensome health issue facing the planet. Our understanding of the pathophysiology of chronic pain has increased substantially over the past 25 years, including but not limited to changes in the brain. However, we still do not know why chronic pain develops in some people and not in others. Most of the recent developments in pain science, that have direct relevance to clinical management, relate to our understanding of the role of the brain, the role of the immune system, or the role of cognitive and behavioral factors. Although the Biopsychosocial model of pain management was presented decades ago, the Bio-reductionist model remains, unfortunately, at the heart of many practices across professional and geographic boundaries. A large body of evidence shows that nociception is neither sufficient nor necessary for pain. Pain is a conscious experience that can certainly be, and often is, associated with nociception, however, always modulated by countless neurobiological, environmental, and cognitive factors. This study will clarify the current misconceptions of chronic pain concepts, and their misperceptions by clinicians. It will also attempt to bridge the considerable gap between what we already know on pain but somehow disregarded, the development in pain science, and clinical practice.

Keywords: chronic pain, nociception, biopsychosocial, neuroplasticity

Procedia PDF Downloads 57

Authors: Laura Rodriguez Amaya

Abstract:

Advances in science, technology, engineering, and mathematics (STEM) are viewed as important to countries’ national economies and their capacities to be competitive in the global economy. However, many countries experience low numbers of students entering these disciplines. To strengthen the professional STEM pipelines, it is important that students are retained in these disciplines at universities. Scholars agree that to retain students in universities’ STEM degrees, it is necessary that STEM course content shows the relevance of these academic fields to their daily lives. By increasing students’ understanding on the importance of these degrees and careers, students’ motivation to remain in these academic programs can also increase. An effective way to make STEM content relevant to students’ lives is the use of geospatial technologies and geovisualization in the classroom. The Geospatial Revolution, and the science and technology associated with it, has provided scientists and engineers with an incredible amount of data about Earth and Earth systems. This data can be used in the classroom to support instruction and make content relevant to all students. The purpose of this study was to find out the prevalence use of geospatial technologies and geovisualization as teaching practices in a USA university. The Teaching Practices Inventory survey, which is a modified version of the Carl Wieman Science Education Initiative Teaching Practices Inventory, was selected for the study. Faculty in the STEM disciplines that participated in a summer learning institute at a 4-year university in the USA constituted the population selected for the study. One of the summer learning institute’s main purpose was to have an impact on the teaching of STEM courses, particularly the teaching of gateway courses taken by many STEM majors. The sample population for the study is 97.5 of the total number of summer learning institute participants. Basic descriptive statistics through the Statistical Package for the Social Sciences (SPSS) were performed to find out: 1) The percentage of faculty using geospatial technologies and geovisualization; 2) Did the faculty associated department impact their use of geospatial tools?; and 3) Did the number of years in a teaching capacity impact their use of geospatial tools? Findings indicate that only 10 percent of respondents had used geospatial technologies, and 18 percent had used geospatial visualization. In addition, the use of geovisualization among faculty of different disciplines was broader than the use of geospatial technologies. The use of geospatial technologies concentrated in the engineering departments. Data seems to indicate the lack of incorporation of geospatial tools in STEM education. The use of geospatial tools is an effective way to engage students in deep STEM learning. Future research should look at the effect on student learning and retention in science and engineering programs when geospatial tools are used.

Keywords: engineering education, geospatial technology, geovisualization, STEM

Procedia PDF Downloads 249

Authors: A. Pedro, T. Goldschmidt

Abstract:

Dyspraxia affects approximately 5-6% of school aged children. Utilising an ecological framework, this study aimed to (1) explore the awareness and understanding of dyspraxia or similar disorders among preschool parents and (2) to explore what skills are required or sought after by parents of children presenting with dyspraxia. A qualitative methodological approach with an exploratory design was employed in this study. A total of 15 parents were purposively selected from urban mainstream preschools in the Cape Town metropole region. Data were collected by means of semi-structured interviews and analysed thematically according to Braun and Clarke (2006). Participants were knowledgeable of their rights throughout the research process. The findings reveal that parents understanding of dyspraxia hinges on observable characteristics of their children’s abilities in comparison to typically developing children. Although parents are aware of ways to explore various avenues to better assist their child, they desire more social support and skills in terms of resources to inform them about their child’s difficulties as well as different techniques to better manage their child’s condition. Findings indicate that regular contact between preschool teachers and parents of children presenting with dyspraxia is an important factor in children’s academic success. The implications of the findings are related to the awareness of dyspraxia and similar learning disorders among both parents and teachers.

Keywords: awareness and understanding, dyspraxia, parents, preschool

Procedia PDF Downloads 150

Authors: Godwin Ojochogu Adejo, Evelyn UnekwuOjo Adejo, Sunday UnenwOjo Adejo

Abstract:

The mainstream contemporary approach to controlling the impact of diseases among poultry birds rely largely on curative measures through the administration of drugs to infected birds. Most times as observed in the deep liter poultry farming system, entire flocks including uninfected birds receive the treatment they do not need. As such, unguarded use of chemical drugs and antibiotics has led to wastage and accumulation of chemical residues in poultry products with associated health hazards to humans. However, wanton and frequent drug usage in poultry is avoidable if feeding and drinking equipment are designed to curb infection transmission among birds. Using toxicological assays as guide and with efficiency and simplicity in view, two newly field-tested and recently patented equipments called 'healthy liquid drinking trough (HDT)' and 'healthy feeding trough (HFT)' that systematically eliminate contamination of the feeding and drinking channels, thereby, curbing wide-spread infection and transmission of diseases in the (intensive) deep litter poultry farming system were designed. Upon combined usage, they automatically and drastically reduced both the amount and frequency of antibiotics use in poultry by over > 50%. Additionally, they conferred optimization of feed and water utilization/elimination of wastage by > 80%, reduced labour by > 70%, reduced production cost by about 15%, and reduced chemical residues in poultry meat or eggs by > 85%. These new and cheap technologies which require no energy input are likely to elevate safety of poultry products for consumers' health, increase marketability locally and for export, and increase output and profit especially among poultry farmers and poor people who keep poultry or inevitably utilize poultry products in developing countries.

Keywords: healthy, trough, toxicological, assay-guided, poultry

Procedia PDF Downloads 154

Authors: Sudheer Kumar J., Sudhanshu Sharma

Abstract:

Stone columns are extensively used as constructive and environmentally sustainable improvement methods for improving stiffness, modulus of subgrade reaction, and maximum lateral displacement in the multilayer soil system. The advantage of using stone columns in improving the single-layer soft soil as a ground reinforcement element for supporting various structures up to shallow depth is well researched, but the understanding of strengthening the multiplayer soil system for a deeper level requires further studies. In this paper, a series of cases have been conducted to study the behaviour of ordinary stone columns (OSC), geosynthetic encased stone columns (GESC) over various objectives for strengthening multilayer soil system up to deep level. A finite element analyses were carried out using the software package PLAXIS to study further correlate the results. The study aims to find the stiffness of composite soil, modulus of subgrade reaction, which is generally required for designing of various foundations, and also discusses the maximum horizontal displacement location, which is the major failure criteria seen after the installation of stone columns.

Keywords: stone columns, geotextile, finite element method, stiffness, modulus of subgrade reaction, maximum lateral displacement point

Procedia PDF Downloads 133

Authors: Mustafa Alhamdi

Abstract:

Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

Procedia PDF Downloads 148

Authors: Deybith Venegas-Rojas, Sercan Keskin, Svenja Riekeberg, Sana Azim, Stephanie Manz, R. J. Dwayne Miller, Hoc Khiem Trieu

Abstract:

Liquid Transmission Electron Microscopy (TEM) is a growing area with a broad range of applications from physics and chemistry to material engineering and biology, in which it is possible to image in-situ unseen phenomena. For this, a nanofluidic device is used to insert the nanoflow with the sample inside the microscope in order to keep the liquid encapsulated because of the high vacuum. In the last years, Si3N4 windows have been widely used because of its mechanical stability and low imaging contrast. Nevertheless, the pressure difference between the inside fluid and the outside vacuum in the TEM generates bulging in the windows. This increases the imaged fluid volume, which decreases the signal to noise ratio (SNR), limiting the achievable spatial resolution. With the proposed device, the membrane is fortified with a microstructure capable of stand higher pressure differences, and almost removing completely the bulging. A theoretical study is presented with Finite Element Method (FEM) simulations which provide a deep understanding of the membrane mechanical conditions and proves the effectiveness of this novel concept. Bulging and von Mises Stress were studied for different membrane dimensions, geometries, materials, and thicknesses. The microfabrication of the device was made with a thin wafer coated with thin layers of SiO2 and Si3N4. After the lithography process, these layers were etched (reactive ion etching and buffered oxide etch (BOE) respectively). After that, the microstructure was etched (deep reactive ion etching). Then the back side SiO2 was etched (BOE) and the array of free-standing micro-windows was obtained. Additionally, a Pyrex wafer was patterned with windows, and inlets/outlets, and bonded (anodic bonding) to the Si side to facilitate the thin wafer handling. Later, a thin spacer is sputtered and patterned with microchannels and trenches to guide the nanoflow with the samples. This approach reduces considerably the common bulging problem of the window, improving the SNR, contrast and spatial resolution, increasing substantially the mechanical stability of the windows, allowing a larger viewing area. These developments lead to a wider range of applications of liquid TEM, expanding the spectrum of possible experiments in the field.

Keywords: liquid cell, liquid transmission electron microscopy, nanofluidics, nanofluidic cell, thin films

Procedia PDF Downloads 251

Authors: Tatjana Jurić, Bojana Blagojević, Denis Uka, Ružica Ždero Pavlović, Boris M. Popović

Abstract:

Natural deep eutectic solvents (NADES) represent a class of modern systems that have been developed as a green alternative to toxic organic solvents, which are commonly used as extraction media. It has been considered that hydrogen bonding is the main interaction leading to the formation of NADES. The aim of this study was phytochemical characterization and determination of the antioxidant and antibacterial activity of Mentha piperita leaf extracts obtained by six choline chloride-based NADES. NADES were prepared by mixing choline chloride with different hydrogen bond donors in 1:1 molar ratio following the addition of 30% (w/w) water. The mixtures were then heated (60 °C) and stirred (650 rpm) until the clear homogenous liquids were obtained. The Mentha piperita extracts were prepared by mixing 75 mg of peppermint leaves with 1 mL of NADES following by the heating and stirring (60 °C, 650 rpm) within 30 min. The content of six phenolics in extracts was determined using HPLC-PDA. The dominant compounds presented in peppermint leaves - rosmarinic acid and luteolin 7-O-glucoside, were extracted by NADES at a similar level as 70% ethanol. The microdilution method was applied to test the antibacterial activity of extracts. Compared with 70% ethanol, all NADES systems showed higher antibacterial activity towards Pseudomonas aeruginosa (Gram -), Staphylococcus aureus (Gram +), Escherichia coli (Gram -), and Salmonella enterica (Gram -), especially NADES containing organic acids. The majority of NADES extracts showed a better ability to neutralize DPPH radical than conventional solvent and similar ability to reduce Fe3+ to Fe2+ ions in FRAP assay. The obtained results introduce NADES systems as the novel, sustainable, and low-cost solvents with a variety of applications.

Keywords: antibacterial activity, antioxidant activity, green extraction, natural deep eutectic solvents, polyphenols

Procedia PDF Downloads 183

Authors: Selim M. Khan, Aaron A. Goodarzi, Joshua M. Taron, Tryggve Rönnqvist

Abstract:

Indoor air quality, a prime determinant of health, is strongly influenced by the presence of hazardous radon gas within the built environment. As a health issue, dangerously high indoor radon arose within the 20th century to become the 2nd leading cause of lung cancer. While the 21st century building metrics and human behaviors have captured, contained, and concentrated radon to yet higher and more hazardous levels, the issue is rapidly worsening in Canada. It is established that Canadians in the Prairies are the 2nd highest radon-exposed population in the world, with 1 in 6 residences experiencing 0.2-6.5 millisieverts (mSv) radiation per week, whereas the Canadian Nuclear Safety Commission sets maximum 5-year occupational limits for atomic workplace exposure at only 20 mSv. This situation is also deteriorating over time within newer housing stocks containing higher levels of radon. Deep machine learning (LSTM) algorithms were applied to analyze multiple quantitative and qualitative features, determine the most important contributory factors, and predicted radon levels in the known past (1990-2020) and projected future (2021-2050). The findings showed gradual downwards patterns in Sweden, whereas it would continue to go from high to higher levels in Canada over time. The contributory factors found to be the basement porosity, roof insulation depthness, R-factor, and air dynamics of the indoor environment related to human window opening behaviour. Building codes must consider including these factors to ensure adequate indoor ventilation and healthy living that can prevent lung cancer in non-smokers.

Keywords: radon, building metrics, deep learning, LSTM prediction model, lung cancer, canada, sweden

Procedia PDF Downloads 108

Authors: Joy Chadwick

Abstract:

There is no doubt that classrooms of today are more complex and diverse than ever before. Preparing teacher candidates to meet these challenges is essential to ensure the retention of teachers within the profession and to ensure that graduates begin their teaching careers with the knowledge and understanding of how to effectively meet the diversity of students they will encounter. Creating inclusive classrooms requires teachers to have a repertoire of effective instructional skills and strategies. Teachers must also have the mindset to embrace diversity and value the uniqueness of individual students in their care. This qualitative study analyzed teacher candidates' experiences as they completed a fourteen-week teaching practicum while simultaneously completing a university course focused on inclusive pedagogy. The research investigated the challenges and successes teacher candidates had in navigating the translation of theory related to inclusive pedagogy into their teaching practice. Applying threshold concept theory as a framework, the research explored the troublesome concepts, liminal spaces, and transformative experiences as connected to inclusive practices. Threshold concept theory suggests that within all disciplinary fields, there exists particular threshold concepts that serve as gateways or portals into previously inaccessible ways of thinking and practicing. It is in these liminal spaces that conceptual shifts in thinking and understanding and deep learning can occur. The threshold concept framework provided a lens to examine teacher candidate struggles and successes with the inclusive education course content and the application of this content to their practicum experiences. A qualitative research approach was used, which included analyzing twenty-nine course reflective journals and six follow up one-to-one semi structured interviews. The journals and interview transcripts were coded and themed using NVivo software. Threshold concept theory was then applied to the data to uncover the liminal or stuck spaces of learning and the ways in which the teacher candidates navigated those challenging places of teaching. The research also sought to uncover potential transformative shifts in teacher candidate understanding as connected to teaching in an inclusive classroom. The findings suggested that teacher candidates experienced difficulties when they did not feel they had the knowledge, skill, or time to meet the needs of the students in the way they envisioned they should. To navigate the frustration of this thwarted vision, they relied on present and previous course content and experiences, collaborative work with other teacher candidates and their mentor teachers, and a proactive approach to planning for students. Transformational shifts were most evident in their ability to reframe their perceptions of children from a deficit or disability lens to a strength-based belief in the potential of students. It was evident that through their course work and practicum experiences, their beliefs regarding struggling students shifted as they saw the value of embracing neurodiversity, the importance of relationships, and planning for and teaching through a strength-based approach. Research findings have implications for teacher education programs and for understanding threshold concepts theory as connected to practice-based learning experiences.

Keywords: inclusion, inclusive education, liminal space, teacher education, threshold concepts, troublesome knowledge

Procedia PDF Downloads 71

Authors: S. Alansary, M. Nagi

Abstract:

This paper presents an approach of conducting semantic annotation of Arabic corpus using the Universal Networking Language (UNL) framework. UNL is intended to be a promising strategy for providing a large collection of semantically annotated texts with formal, deep semantics rather than shallow. The result would constitute a semantic resource (semantic graphs) that is editable and that integrates various phenomena, including predicate-argument structure, scope, tense, thematic roles and rhetorical relations, into a single semantic formalism for knowledge representation. The paper will also present the Interactive Analysis​ tool for automatic semantic annotation (IAN). In addition, the cornerstone of the proposed methodology which are the disambiguation and transformation rules, will be presented. Semantic annotation using UNL has been applied to a corpus of 20,000 Arabic sentences representing the most frequent structures in the Arabic Wikipedia. The representation, at different linguistic levels was illustrated starting from the morphological level passing through the syntactic level till the semantic representation is reached. The output has been evaluated using the F-measure. It is 90% accurate. This demonstrates how powerful the formal environment is, as it enables intelligent text processing and search.

Keywords: semantic analysis, semantic annotation, Arabic, universal networking language

Procedia PDF Downloads 579

Authors: Mehrnaz Mostafavi, Mahtab Shabani, Alireza Azani, Fatemeh Ghafari

Abstract:

Artificial intelligence (AI) can transform breast cancer diagnosis and therapy by providing sophisticated solutions for screening, imaging interpretation, histopathological analysis, and treatment planning. This literature review digs into the many uses of AI in breast cancer treatment, highlighting the need for collaboration between AI scientists and healthcare practitioners. It emphasizes advances in AI-driven breast imaging interpretation, such as computer-aided detection and diagnosis (CADe/CADx) systems and deep learning algorithms. These have shown significant potential for improving diagnostic accuracy and lowering radiologists' workloads. Furthermore, AI approaches such as deep learning have been used in histopathological research to accurately predict hormone receptor status and categorize tumor-associated stroma from regular H&E stains. These AI-powered approaches simplify diagnostic procedures while providing insights into tumor biology and prognosis. As AI becomes more embedded in breast cancer care, it is crucial to ensure its ethical, efficient, and patient-focused implementation to improve outcomes for breast cancer patients ultimately.

Keywords: breast cancer, artificial intelligence, cancer diagnosis, clinical practice

Procedia PDF Downloads 56

Authors: Bubaker F. Shareia, Almuetaz R. Boubakr

Abstract:

The aim of this paper is to show how Libya’s legal, economic, political, social, and cultural systems have shaped Libyan development. This will provide a background to develop an understanding of the current role of the accounting information system in Libya and the challenges facing the design of the aeronautical information system to meet the development needs of Libya. Our knowledge of the unified economic operating systems of the world paves the way for the economic development of every developing country. In order to achieve this understanding, every developing country should be provided with a high-efficiency communications system in order to be able to interact globally. From the point of view of the theory of globalization, Libya's understanding of its socio-economic and political systems is vital in order to be able to adopt and apply accounting techniques that will assist in the economic development of Libya.

Keywords: accounting, economic development, globalisation theory, information system

Procedia PDF Downloads 268

Authors: Alexey Mustafin

Abstract:

This paper explores the complex interplay between materialism, spiritualism, dualism, and non-dualism in the context of both Western and Eastern philosophical traditions. The research question is centered around understanding the implications of these perspectives on our comprehension of reality. The study employs a comparative analysis of worldviews, scientific perspectives, and case studies to achieve its objectives. The theoretical framework examines the critiques of materialism, spiritualism, dualism, and non-dualism, synthesizing different perspectives. A comparative analysis of Western (Greek, Christian, and Enlightenment) and Eastern (Hinduism, Buddhism, and Taoism) philosophical traditions provides a holistic understanding of diverse worldviews. The study further investigates scientific perspectives, including classical physics, quantum physics, biology, neuroscience, and their implications on the understanding of reality. Case studies on near-death experiences, meditation, healing, and parapsychology serve as practical examples of the interplay between these perspectives. The synthesis of findings offers insights into the implications for our understanding of reality and highlights future directions for research in this interdisciplinary field.

Keywords: biocentrism, quantum physics, neurosciense and consciousness, meditation and brain, religion experiences and scientific research, buddhism and science

Procedia PDF Downloads 72

Authors: Haytham Yassine

Abstract:

This research seeks to identify how money laundering activities are executed through the real estate sector. This article provides academics with literature on the topic and provides scholars, and practitioners with a better understanding of the risks and challenges involved. Data are gathered through survey in the Middle East and North Africa region and review of the available research. The results of the analysis will help identifying the factors attracting criminals to the real estate sector and develop an understanding of the methods used to launder illicit funds through this sector and the indicators of suspicion for reporting entities. Further analysis reveals the risks posed by money laundering and terrorist financing on the real estate sector and challenges facing states in this regard.

Keywords: money laundering, terrorism financing, real estate sector, Middle East and North Africa

Procedia PDF Downloads 153

Authors: Daniela Velichová

Abstract:

Plenty of ideas on how to adopt active learning methods in education are available nowadays. Mathematics is a subject where the active involvement of students is required in particular in order to achieve desirable results regarding sustainable knowledge and deep understanding. The present article is based on the outcomes of an Erasmus+ project DrIVE-MATH, that was aimed at developing a novel and integrated framework to teach maths classes in engineering courses at the university level. It is fundamental for students from the early years of their academic life to have agile minds. They must be prepared to adapt to their future working environments, where enterprises’ views are always evolving, where all collaborate in teams, and relations between peers are thought for the well-being of the whole - workers and company profit. This reality imposes new requirements on higher education in terms of adaptation of different pedagogical methods, such as project-based and active-learning methods used within the course curricula. Active learning methodologies are regarded as an effective way to prepare students to meet the challenges posed by enterprises and to help them in building critical thinking, analytic reasoning, and insight to the solved complex problems from different perspectives. Fostering learning-by-doing activities in the pedagogical process can help students to achieve learning independence, as they could acquire deeper conceptual understanding by experimenting with the abstract concept in a more interesting, useful, and meaningful way. Clear information about learning outcomes and goals might help students to take more responsibility for their learning results. Active learning methods implemented by the project team members in their teaching practice, eduScrum and Jigsaw in particular, proved to provide better scientific and soft skills support to students than classical teaching methods. EduScrum method enables teachers to generate a working environment that stimulates students' working habits and self-initiative as they become aware of their responsibilities within the team, their own acquired knowledge, and their abilities to solve problems independently, though in collaboration with other team members. This method enhances collaborative learning, as students are working in teams towards a common goal - knowledge acquisition, while they are interacting with each other and evaluated individually. Teams consisting of 4-5 students work together on a list of problems - sprint; each member is responsible for solving one of them, while the group leader – a master, is responsible for the whole team. A similar principle is behind the Jigsaw technique, where the classroom activity makes students dependent on each other to succeed. Students are divided into groups, and assignments are split into pieces, which need to be assembled by the whole group to complete the (Jigsaw) puzzle. In this paper, analysis of students’ perceptions concerning the achievement of deeper conceptual understanding in mathematics and the development of soft skills, such as self-motivation, critical thinking, flexibility, leadership, responsibility, teamwork, negotiation, and conflict management, is presented. Some new challenges are discussed as brought by introducing active learning methods in the basic mathematics courses. A few examples of sprints developed and used in teaching basic maths courses at technical universities are presented in addition.

Keywords: active learning methods, collaborative learning, conceptual understanding, eduScrum, Jigsaw, soft skills

Procedia PDF Downloads 47