Search results for: hyperspectral image classification using tree search algorithm

Authors: C. Vogeler

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Change processes such as individualization and digitalization have an impact on higher education. Graduates are expected to cooperate in creative work processes in their professional life. During their studies, they need to be prepared accordingly. This includes modern learning scenarios that integrate the benefits of digital media. Therefore, design thinking and blended learning have been combined in the project-based seminar conception introduced here. The presented seminar conception has been realized and evaluated with students of information sciences since September 2017. Within the seminar, the students learn to work on a project. They apply the methods in a problem-based learning scenario. Task of the case study is to arrange a conference on the topic gaming in libraries. In order to collaborative develop creative possibilities of realization within the group of students the design thinking method has been chosen. Design thinking is a method, used to create user-centric, problem-solving and need-driven innovation through creative collaboration in multidisciplinary teams. Central characteristics are the openness of this approach to work results and the visualization of ideas. This approach is now also accepted in the field of higher education. Especially in problem-based learning scenarios, the method offers clearly defined process steps for creative ideas and their realization. The creative process can be supported by digital media, such as search engines and tools for the documentation of brainstorming, creation of mind maps, project management etc. Because the students have to do two-thirds of the workload in their private study, design thinking has been combined with a blended learning approach. This supports students’ preparation and follow-up of the joint work in workshops (flipped classroom scenario) as well as the communication and collaboration during the entire project work phase. For this purpose, learning materials are provided on a Moodle-based learning platform as well as various tools that supported the design thinking process as described above. In this paper, the seminar conception with a combination of design thinking and blended learning is described and the potentials and limitations of the chosen strategy for the development of a course with a multimedia approach in higher education are reflected.

Keywords: blended learning, design thinking, digital media tools and methods, flipped classroom

Procedia PDF Downloads 192

Authors: Igor A. Bessmertny, Bidru C. Enkomaryam

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Active involving patients and communities in health decisions can improve both people’s health and the healthcare system. Adopting artificial intelligence can lead to more accurate and complete patient record management. This review aims to identify the current state of researches conducted using artificial intelligence techniques to improve patient engagement and wellbeing, medical domains used in patient engagement context, and lastly, to assess opportunities and challenges for patient engagement in the wellness process. A search of peer-reviewed publications, reviews, conceptual analyses, white papers, author’s manuscripts and theses was undertaken. English language literature published in 2013– 2022 period and publications, report and guidelines of World Health Organization (WHO) were also assessed. About 281 papers were retrieved. Duplicate papers in the databases were removed. After application of the inclusion and exclusion criteria, 41 papers were included to the analysis. Patient counseling in preventing adverse drug events, in doctor-patient risk communication, surgical, drug development, mental healthcare, hypertension & diabetes, metabolic syndrome and non-communicable chronic diseases are implementation areas in healthcare where patient engagement can be implemented using artificial intelligence, particularly machine learning and deep learning techniques and tools. The five groups of factors that potentially affecting patient engagement in safety are related to: patient, health conditions, health care professionals, tasks and health care setting. Active involvement of patients and families can help accelerate the implementation of healthcare safety initiatives. In sub-Saharan Africa, using digital technologies like artificial intelligence in patient engagement context is low due to poor level of technological development and deployment. The opportunities and challenges available to implement patient engagement strategies vary greatly from country to country and from region to region. Thus, further investigation will be focused on methods and tools using the potential of artificial intelligence to support more simplified care that might be improve communication with patients and train health care professionals.

Keywords: artificial intelligence, patient engagement, machine learning, patient involvement

Procedia PDF Downloads 73

Authors: Irene Yi

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Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Computational linguistics is a growing field dealing with such issues of data collection for technological development. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Computational analysis on such linguistic data is used to find patterns of misogyny. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: computational analysis, gendered grammar, misogynistic language, neural networks

Procedia PDF Downloads 113

Authors: Abdulkarem Qasem Dammag, Basema Qasim Dammag, Jian Dai

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Change in Land use and Land cover (LU/LC) has a profound impact on the area's natural, economic, and ecological development, and the search for drivers of land cover change is one of the fundamental issues of LU/LC change. The study aimed to assess the temporal and Spatio-temporal dynamics of LU/LC in the past and to predict the future using Landsat images by exploring the characteristics of different LU/LC types. Spatio-temporal patterns of LU/LC change in Ibb Governorate, Yemen, were analyzed based on RS and GIS from 1990, 2005, and 2020. A socioeconomic survey and key informant interviews were used to assess potential drivers of LU/LC. The results showed that from 1990 to 2020, the total area of vegetation land decreased by 5.3%, while the area of barren land, grassland, built-up area, and waterbody increased by 2.7%, 1.6%, 1.04%, and 0.06%, respectively. Based on socio-economic surveys and key informant interviews, natural factors had a significant and long-term impact on land change. In contrast, site construction and socio-economic factors were the main driving forces affecting land change in a short time scale. The analysis results have been linked to the CA-Markov Land Use simulation and forecasting model for the years 2035 and 2050. The simulation results revealed from the period 2020 to 2050, the trend of dynamic changes in land use, where the total area of barren land decreased by 7.0% and grassland by 0.2%, while the vegetation land, built-up area, and waterbody increased by 4.6%, 2.6%, and 0.1 %, respectively. Overall, these findings provide LULC's past and future trends and identify drivers, which can play an important role in sustainable land use planning and management by balancing and coordinating urban growth and land use and can also be used at the regional level in different levels to provide as a reference. In addition, the results provide scientific guidance to government departments and local decision-makers in future land-use planning through dynamic monitoring of LU/LC change.

Keywords: LU/LC change, CA-Markov model, driving forces, change detection, LU/LC change simulation

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Authors: Adrianna D. Hendricks

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This paper examines the factors that contribute to the re-traumatization of victims of sex trafficking within the Canadian context. Sex trafficking occurring domestically in Canada is severely under-researched, stigmatized, and under-prosecuted, leading to the re-traumatization of victims by various levels of government. This is in part due to the Canadian criminal justice system unethically utilizing prostitution laws in cases of sex trafficking and partially due to the unaddressed stigmatization victims face within the justice system itself. Utilizing evidence from a current literature review, personal correspondence, and personal life experiences, this paper will demonstrate the need for victim involvement in policy reform. The current literature review was done through an academic database search using the terms: “Sex Trafficking, Exploitation, Canada”, with the limitation of articles written within the last 5 years and written within the Canadian context. Overall, from the results, only eight articles precisely matched the criteria. The current literature argues strongly and unanimously for more research and education of professionals who have close contact with high-risk populations (doctors, police officers, social workers, etc.) to protect both minors and adults from being sexually trafficked. Additionally, for women and girls who do not have Canadian citizenship, the fear of deportation becomes a barrier to disclosing exploitation experiences to professionals. There is a desperate need for more research done in tandem with survivors and victims to inform policymaking in a meaningful way. The researcher is a survivor of sex trafficking both as a youth and as an adult, giving the researcher a unique insight into the realities of the criminal justice system for victims of sex trafficking. There is a clear need for professionals in positions of power to be re-educated about the realities of sex-trafficking, and what it means for the victims. Congruent to the current research the author calls for: standardized professional training for people in healthcare, police officers, court officials, and victim services; with the additional layers of victim involvement in creation of professional education training, and victim involvement in research. Justice for victims/survivors can only be obtained if they have been consulted and believed. Without meaningful consultation with survivors, victims who are both minors and adults will continue to fall through the cracks in policy.

Keywords: Canadian policy, re-traumatization, sex-trafficking, stigmatization

Procedia PDF Downloads 54

Authors: Tamar Khardziani, Violeta Berikashvili, Mariam Rusitashvili, Eva Kachlishvili, Vladimir Elisashvili, Mikheil Asatiani

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Last years, the search for natural sources of novel and effective antifungal substances became a scientific and technological challenge. In the present research, thirty basidiomycetes isolated from various ecological niches of Georgia and belonging to different taxonomic groups were screened for their antifungal activities against pathogenic fungi such as Aspergillus, Fusarium, and Guignardia bidwellii. Among mushroom tested, several potential producers of antifungal substances have been revealed, such as Schizophyllum commune, Lentinula edodes, Ganoderma abietinum, Fomes fomentarius, Hericium erinaceus, and Trametes versicolor. For mushroom cultivation and expression of antifungal potential, submerged and solid-state fermentations of different plant raw materials were performed and various approaches and strategies have been exploited. Sch. commune appeared as a most promising producer of antifungal compounds. It was established that among different agro-industrial wastes, the presence of mandarin juice production waste in a nutrient medium, causing the significant increase of antifungal activity Sch. commune (growth inhibition: Aspergillus – 59 %, Fusarium – 55 %, G. bidwellii – 78 %, after 3, 2 and 4 days of cultivation, respectively). Besides this, Sch. commune demonstrate similar antifungal activities in the presence of glucose, glycerol, maltose, mannitol, and xylose, and growth inhibition of Fusarium ranged in 41 % - 49 % during 6 days of cultivation. Inhibition of Aspergillus growth inhibition varied in 27 % - 36 %, and inhibition of G. bidwellii was in the range 49 % - 61 %, respectively. Sch. commune under solid-state fermentation of mandarin peels at 13 days of cultivation demonstrates powerful growth inhibition of pathogenic fungi (growth inhibition: Aspergillus – 50 %, Fusarium – 61 %, G. bidwellii – 68 %, after 3, 4, and 4 days of cultivation, respectively) as well as at 20 days old mushroom (growth inhibition: Aspergillus – 41 %, Fusarium – 54 %, G. bidwellii – 66 %, after 3 days of cultivation). It was established that Sch. commune was effective as a producer of antifungal compounds in submerged as well as in solid-state fermentation. Finally, performed study confirms that the higher basidiomycetes possess antifungal potential, which strongly depends on the physiological factors of growth. Acknowledgments: The work was implemented with the financial support of fundamental science project FR-19-3719 by the Shota Rustaveli National Science Foundation of Georgia.

Keywords: antifungal potential, higher basidiomycetes, pathogenic fungi, submerged and solid-state fermentation

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Authors: Muhammad Umer Mehmood, Muhammad Luqman, Muhammad Yaseen, Imtiaz Hussain

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Climate change is an arduous fact, which could not be unheeded easily. It is a phenomenon which has brought a collection of challenges for the mankind. Scientists have found many of its negative impacts on the life of human being and the resources on which the life of humanity is dependent. There are many issues which are associated with the factor of prime importance in this study, 'climate change'. Whenever changes happen in nature, they strike the whole globe. Effects of these changes vary from region to region. Climate of every region of this globe is different from the other. Even within a state, country or the province has different climatic conditions. So it is mandatory that the response in that specific region and the coping strategy of this specific region should be according to the prevailing risk. In the present study, the objective was to assess the coping strategies and vulnerability of small landholders. So that a professional suggestion could be made to cope with the vulnerability factor of small farmers. The cross-sectional research design was used with the intervention of quantitative approach. The study was conducted in the Khanewal district, of Punjab, Pakistan. 120 small farmers were interviewed after randomized sampling from the population of respective area. All respondents were above the age of 15 years. A questionnaire was developed after keen observation of facts in the respective area. Content and face validity of the instrument was assessed with SPSS and experts in the field. Data were analyzed through SPSS using descriptive statistics. From the sample of 120, 81.67% of the respondents claimed that the environment is getting warmer and not fit for their present agricultural practices. 84.17% of the sample expressed serious concern that they are disturbed due to change in rainfall pattern and vulnerability towards the climatic effects. On the other hand, they expressed that they are not good at tackling the effects of climate change. Adaptation of coping strategies like change in cropping pattern, use of resistant varieties, varieties with minimum water requirement, intercropping and tree planting was low by more than half of the sample. From the sample 63.33% small farmers said that the coping strategies they adopt are not effective enough. The present study showed that subsistence farming, lack of marketing and overall infrastructure, lack of access to social security networks, limited access to agriculture extension services, inappropriate access to agrometeorological system, unawareness and access to scientific development and low crop yield are the prominent factors which are responsible for the vulnerability of small farmers. A comprehensive study should be conducted at national level so that a national policy could be formulated to cope with the dilemma in future with relevance to climate change. Mainstreaming and collaboration among the researchers and academicians could prove beneficiary in this regard the interest of national leaders’ does matter. Proper policies to avoid the vulnerability factors should be the top priority. The world is taking up this issue with full responsibility as should we, keeping in view the local situation.

Keywords: adaptation, coping strategies, climate change, Pakistan, small farmers, vulnerability

Procedia PDF Downloads 135

Authors: Victoria L. Malakhova

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The research is devoted to multimodal content and its effectiveness in developing students’ linguistic and intercultural communicative competences as an indefeasible constituent of their future professional activity. Description of multimodal content both as a linguistic and didactic phenomenon makes the study relevant. The objective of the article is the analysis of creolized texts and the effect they have on fostering higher education students’ skills and their productivity. The main methods used are linguistic text analysis, qualitative and quantitative methods, deduction, generalization. The author studies texts with full and partial creolization, their features and role in composing multimodal textual space. The main verbal and non-verbal markers and paralinguistic means that enhance the linguo-pragmatic potential of creolized texts are covered. To reveal the efficiency of multimodal content application in English teaching, the author conducts an experiment among both undergraduate students and teachers. This allows specifying main functions of creolized texts in the process of language learning, detecting ways of enhancing students’ competences, and increasing their motivation. The described stages of using creolized texts can serve as an algorithm for work with multimodal content in teaching English as a foreign language. The findings contribute to improving the efficiency of the academic process.

Keywords: creolized text, English language learning, higher education, language and communication competences, multimodal content

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Authors: Samer Muthana Sarsam, Abdul Samad Shibghatullah, Chit Su Mon, Abd Aziz Alias, Hosam Al-Samarraie

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Generative Artificial Intelligence chatbots (GAI chatbots) have emerged as promising tools in various domains, including higher education. However, their specific role within the educational context and the level of legal support for their implementation remain unclear. Therefore, this study aims to investigate the role of Bard, a newly developed GAI chatbot, in higher education. To achieve this objective, English tweets were collected from Twitter's free streaming Application Programming Interface (API). The Latent Dirichlet Allocation (LDA) algorithm was applied to extract latent topics from the collected tweets. User sentiments, including disgust, surprise, sadness, anger, fear, joy, anticipation, and trust, as well as positive and negative sentiments, were extracted using the NRC Affect Intensity Lexicon and SentiStrength tools. This study explored the benefits, challenges, and future implications of integrating GAI chatbots in higher education. The findings shed light on the potential power of such tools, exemplified by Bard, in enhancing the learning process and providing support to students throughout their educational journey.

Keywords: generative artificial intelligence chatbots, bard, higher education, topic modelling, sentiment analysis

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Authors: Bo Wang

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The geometric processing of multi-source remote sensing data using control data of different scale and different accuracy is an important research direction of multi-platform system for earth observation. In the existing block bundle adjustment methods, as the controlling information in the adjustment system, the approach using single observation scale and precision is unable to screen out the control information and to give reasonable and effective corresponding weights, which reduces the convergence and adjustment reliability of the results. Referring to the relevant theory and technology of quotient space, in this project, several subjects are researched. Multi-layer quotient space of multi-geometric features is constructed to describe and filter control data. Normalized granularity merging mechanism of multi-layer control information is studied and based on the normalized scale factor, the strategy to optimize the weight selection of control data which is less relevant to the adjustment system can be realized. At the same time, geometric positioning experiment is conducted using multi-source remote sensing data, aerial images, and multiclass control data to verify the theoretical research results. This research is expected to break through the cliché of the single scale and single accuracy control data in the adjustment process and expand the theory and technology of photogrammetry. Thus the problem to process multi-source remote sensing data will be solved both theoretically and practically.

Keywords: multi-source image geometric process, high precision geometric positioning, quotient space of multi-geometric features, optimized weight selection

Procedia PDF Downloads 279

Authors: F. Hamidi, N. Amiri, H. Mishmast Nehi

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The Bilevel Programming (BP) model has been presented for a decision making process that consists of two decision makers in a hierarchical structure. In fact, BP is a model for a static two person game (the leader player in the upper level and the follower player in the lower level) wherein each player tries to optimize his/her personal objective function under dependent constraints; this game is sequential and non-cooperative. The decision making variables are divided between the two players and one’s choice affects the other’s benefit and choices. In other words, BP consists of two nested optimization problems with two objective functions (upper and lower) where the constraint region of the upper level problem is implicitly determined by the lower level problem. In real cases, the coefficients of an optimization problem may not be precise, i.e. they may be interval. In this paper we develop an algorithm for solving interval bilevel linear fractional programming problems. That is to say, bilevel problems in which both objective functions are linear fractional, the coefficients are interval and the common constraint region is a polyhedron. From the original problem, the best and the worst bilevel linear fractional problems have been derived and then, using the extended Charnes and Cooper transformation, each fractional problem can be reduced to a linear problem. Then we can find the best and the worst optimal values of the leader objective function by two algorithms.

Keywords: best and worst optimal solutions, bilevel programming, fractional, interval coefficients

Procedia PDF Downloads 439

Authors: Niklas Panten, Eberhard Abele

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

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

Procedia PDF Downloads 183

Authors: Azin Shakibabarough, Mojtaba Valinejadshoubi, Ashutosh Bagchi

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Catastrophic bridge failure happens due to the lack of inspection, lack of design and extreme events like flooding, an earthquake. Bridge Management System (BMS) is utilized to diminish such an accident with proper design and frequent inspection. Visual inspection cannot detect any subsurface defects, so using Non-Destructive Evaluation (NDE) techniques remove these barriers as far as possible. Among all NDE techniques, Ground Penetrating Radar (GPR) has been proved as a highly effective device for detecting internal defects in a reinforced concrete bridge deck. GPR is used for detecting rebar location and rebar corrosion in the reinforced concrete deck. GPR profile is composed of hyperbola series in which sound hyperbola denotes sound rebar and blur hyperbola or signal attenuation shows corroded rebar. Interpretation of GPR images is implemented by numerical analysis or visualization. Researchers recently found that interpretation through visualization is more precise than interpretation through numerical analysis, but visualization is time-consuming and a highly subjective process. Automating the interpretation of GPR image through visualization can solve these problems. After interpretation of all scans of a bridge, condition assessment is conducted based on the generated corrosion map. However, this such a condition assessment is not objective and precise. Condition assessment based on structural integrity and strength parameters can make it more objective and precise. The main purpose of this study is to present an automated interpretation method of a reinforced concrete bridge deck through a visualization technique. In the end, the combined analysis of the structural condition in a bridge is implemented.

Keywords: bridge condition assessment, ground penetrating radar, GPR, NDE techniques, visualization

Procedia PDF Downloads 143

Authors: Pinel Sebastien, Bourrin François, De Madron Du Rieu Xavier, Ludwig Wolfgang, Arnau Pedro

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Heavy precipitation constitutes a major meteorological threat in the western Mediterranean. Research has investigated the relationship between the states of the Mediterranean Sea and the atmosphere with the precipitation for short temporal windows. However, at a larger temporal scale, the precursor signals of heavy rainfall in the sea and atmosphere have drawn little attention. Moreover, despite ongoing improvements in numerical weather prediction, the medium-term forecasting of rainfall events remains a difficult task. Here, we aim to investigate the influence of early-spring environmental parameters on the following autumnal heavy precipitations. Hence, we develop a machine learning model to predict extreme autumnal rainfall with a 6-month lead time over the Spanish Catalan coastal area, based on i) the sea pattern (main current-LPC and Sea Surface Temperature-SST) at the mesoscale scale, ii) 4 European weather teleconnection patterns (NAO, WeMo, SCAND, MO) at synoptic scale, and iii) the hydrological regime of the main local river (Rhône River). The accuracy of the developed model classifier is evaluated via statistical analysis based on classification accuracy, logarithmic and confusion matrix by comparing with rainfall estimates from rain gauges and satellite observations (CHIRPS-2.0). Sensitivity tests are carried out by changing the model configuration, such as sea SST, sea LPC, river regime, and synoptic atmosphere configuration. The sensitivity analysis suggests a negligible influence from the hydrological regime, unlike SST, LPC, and specific teleconnection weather patterns. At last, this study illustrates how public datasets can be integrated into a machine learning model for heavy rainfall prediction and can interest local policies for management purposes.

Keywords: extreme hazards, sensitivity analysis, heavy rainfall, machine learning, sea-atmosphere modeling, precipitation forecasting

Procedia PDF Downloads 124

Authors: Dongqi Li, Yunjia Huang, Tomo Inoue, Kohei Inoue

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With urbanization, urban cultural heritage is facing the impact and destruction of modernization and urbanization. Many historical areas are losing their historical information and regional cultural characteristics, so it is necessary to carry out systematic color planning for historical areas in conservation. As an early focus on urban color planning, Japan has a systematic approach to urban color planning. Hence, this paper selects five merchant towns from the category of important traditional building preservation areas in Japan as the subject of this study to explore the color structure and emotion of this type of historic area. First, the image semantic segmentation method identifies the buildings, roads, and landscape environments. Their color data were extracted for color composition and emotion analysis to summarize their common features. Second, the obtained Internet evaluations were extracted by natural language processing for keyword extraction. The correlation analysis of the color structure and keywords provides a valuable reference for conservation decisions for this historic area in the town. This paper also combines the color structure and Internet evaluation results with generative adversarial networks to generate predicted images of color structure improvements and color improvement schemes. The methods and conclusions of this paper can provide new ideas for the digital management of environmental colors in historic districts and provide a valuable reference for the inheritance of local traditional culture.

Keywords: historic districts, color planning, semantic segmentation, natural language processing

Procedia PDF Downloads 80

Authors: Ivonne N. Pérez-Sánchez. María L. Rascón- Gasca, Angélica Riveros-Rosas, Rebeca Robles García

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Introduction: Primary caregivers of cancer patients have health problems related to their lack of time, stress, and fiscal strain. Their health problems could affect their patients’ health and also increase the expenses in public health. Aim: To describe self-care and risk behaviors in a sample of Mexican primary caregiver and the relation of these behaviors with emotional distress (caregiver burden, anxiety and depression symptoms), coping and sociodemographic variables. Method: Participated in this study 173 caregivers of a third level reference medical facility (age: M=49.4, SD=13.5) females 78%, males 22%, 57.5% were caregivers of patients with terminal cancer (CPTC), and 40.5% were caregivers of patients on oncology treatment (CPOT). Results: The 75.7% of caregivers reported to have had health problem in last six months as well as several symptoms which were related to emotional distress, these symptoms were more frequently between CPTC and female caregivers. A half (47.3%) of sample reported have had difficulties in caring their health; these difficulties were related to emotional distress and lower coping, more affected caregivers were who attend male patients and CPTC. The 76.8% of caregivers had health problems in last six months, but 26.5% of them waited to search medical care until they were very sick, and 11% didn't do it. Also, more than a half of sample (56.1%) admitted to have risk behaviors as drink alcohol, smoke or overeating for feeling well, these caregivers showed high emotional distress and lower coping. About caregivers healthy behaviors, 80% of them had a hobby; 27.2% do exercise usually and between 12% to 60% did medical checkups (glucose tests, blood pressure and cholesterol tests, eye exams and watched their weight), these caregivers had lower emotional distress and high coping, some variables related health behaviors were: care only one patient or a female patient and be a CPOT, social support, high educational level and experience as a caregiver in past. The half of caregivers were worrying to develop cancer in the future; this idea was 2.5 times more frequent in caregiver with problems to care their health. Conclusions: The results showed a big proportion of caregivers with medical problems. High emotional distress and low coping were related to physical symptoms, risk behaviors, and low self-care; poor self-care was frequently even in caregiver who have chronic illness.

Keywords: cancer, primary caregiver, risk behaviors, self-care

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Authors: Ayola D. N. Jayamaha, Gihan V. Dias, Surangika Ranathunga

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Currently there are lot of educational tools designed for mathematics. Open source software such as GeoGebra and Octave are bulky in their architectural structure. In addition, there is MathLab software, which facilitates much more than what we ask for. Many of the computer aided online grading and assessment tools require integrating editors to their software. However, there are not exist suitable editors that cater for all their needs in editing equations and geometrical diagrams and graphs. Some of the existing software for editing equations is Alfred’s Equation Editor, Codecogs, DragMath, Maple, MathDox, MathJax, MathMagic, MathFlow, Math-o-mir, Microsoft Equation Editor, MiraiMath, OpenOffice, WIRIS Editor and MyScript. Some of them are commercial, open source, supports handwriting recognition, mobile apps, renders MathML/LaTeX, Flash / Web based and javascript display engines. Some of the diagram editors are GeoKone.NET, Tabulae, Cinderella 1.4, MyScript, Dia, Draw2D touch, Gliffy, GeoGebra, Flowchart, Jgraph, JointJS, J painter Online diagram editor and 2D sketcher. All these software are open source except for MyScript and can be used for editing mathematical diagrams. However, they do not fully cater the needs of a typical computer aided assessment tool or Educational Platform for Mathematics. This solution provides a Web based, lightweight, easy to implement and integrate solution of an html5 canvas that renders on all of the modern web browsers. The scope of the project is an editor that covers equations and mathematical diagrams and drawings on the O/L Mathematical Exam Papers in Sri Lanka. Using the tool the students can enter any equation to the system which can be on an online remote learning platform. The users can also create and edit geometrical drawings, graphs and do geometrical constructions that require only Compass and Ruler from the Editing Interface provided by the Software. The special feature of this software is the geometrical constructions. It allows the users to create geometrical constructions such as angle bisectors, perpendicular lines, angles of 600 and perpendicular bisectors. The tool correctly imitates the functioning of rulers and compasses to create the required geometrical construction. Therefore, the users are able to do geometrical drawings on the computer successfully and we have a digital format of the geometrical drawing for further processing. Secondly, we can create and edit Venn Diagrams, color them and label them. In addition, the students can draw probability tree diagrams and compound probability outcome grids. They can label and mark regions within the grids. Thirdly, students can draw graphs (1st order and 2nd order). They can mark points on a graph paper and the system connects the dots to draw the graph. Further students are able to draw standard shapes such as circles and rectangles by selecting points on a grid or entering the parametric values.

Keywords: geometrical drawings, html5 canvas, mathematical equations, toolbox

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Authors: Tahir Ali Akbar, Hirra Jabbar

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Land cover change analysis plays a significant role in understanding the trends of urban sprawl and land use transformation due to anthropogenic activities. In this study, the spatio-temporal dynamics of major land covers were analyzed in the last twenty years (1988-2016) for District Lahore located in the Punjab Province of Pakistan. The Landsat satellite imageries were downloaded from USGS Global Visualization Viewer of Earth Resources Observation and Science Center located in Sioux Falls, South Dakota USA. The imageries included: (i) Landsat TM-5 for 1988 and 2001; and (ii) Landsat-8 OLI for 2016. The raw digital numbers of Landsat-5 images were converted into spectral radiance and then planetary reflectance. The digital numbers of Landsat-8 image were directly converted into planetary reflectance. The normalized difference vegetation index (NDVI) was used to classify the processed images into six major classes of water, buit-up, barren land, shrub and grassland, sparse vegetation and dense vegetation. The NDVI output results were improved by visual interpretation using high-resolution satellite imageries. The results indicated that the built-up areas were increased to 21% in 2016 from 10% in 1988. The decrease in % areas was found in case of water, barren land and shrub & grassland. There were improvements in percentage of areas for the vegetation. The increasing trend of urban sprawl for Lahore requires implementation of GIS based spatial planning, monitoring and management system for its sustainable development.

Keywords: land cover changes, NDVI, remote sensing, urban sprawl

Procedia PDF Downloads 311

Authors: Vivek Mahadev, Manoj Kumar, Neelu Mathur, Brahm Dutt Pandey

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Perimeter guarding and protection of critical installations require prompt intrusion detection and assessment to take effective countermeasures. Currently, visual and electronic surveillance are the primary methods used for perimeter guarding. These methods can be costly and complicated, requiring careful planning according to the location and terrain. Moreover, these methods often struggle to detect stealthy and camouflaged insurgents. The object of the present work is to devise a surveillance technique using seismic sensors that overcomes the limitations of existing systems. The aim is to improve intrusion detection, assessment, and characterization by utilizing seismic sensors. Most of the similar systems have only two types of intrusion detection capability viz., human or vehicle. In our work we could even categorize further to identify types of intrusion activity such as walking, running, group walking, fence jumping, tunnel digging and vehicular movements. A virtual fence of 60 meters at GCNEP, Bahadurgarh, Haryana, India, was created by installing four underground geophones at a distance of 15 meters each. The signals received from these geophones are then processed to find unique seismic signatures called features. Various feature optimization and selection methodologies, such as LightGBM, Boruta, Random Forest, Logistics, Recursive Feature Elimination, Chi-2 and Pearson Ratio were used to identify the best features for training the machine learning models. The trained models were developed using algorithms such as supervised support vector machine (SVM) classifier, kNN, Decision Tree, Logistic Regression, Naïve Bayes, and Artificial Neural Networks. These models were then used to predict the category of events, employing weighted ensemble voting to analyze and combine their results. The models were trained with 1940 training events and results were evaluated with 831 test events. It was observed that using the weighted ensemble voting increased the efficiency of predictions. In this study we successfully developed and deployed the virtual fence using geophones. Since these sensors are passive, do not radiate any energy and are installed underground, it is impossible for intruders to locate and nullify them. Their flexibility, quick and easy installation, low costs, hidden deployment and unattended surveillance make such systems especially suitable for critical installations and remote facilities with difficult terrain. This work demonstrates the potential of utilizing seismic sensors for creating better perimeter guarding and protection systems using multiple machine learning models in weighted ensemble voting. In this study the virtual fence achieved an intruder detection efficiency of over 97%.

Keywords: geophone, seismic perimeter surveillance, machine learning, weighted ensemble method

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Authors: Nwogiji Cletus Olando, Oselebe Happiness Ogba, Enoch Achigan-Dako

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Digitaria iburua, commonly known as black fonio, is a cereal crop native to Africa and extensively cultivated by smallholder farmers in Northern Benin, Togo, and Nigeria. This crop holds immense nutritional and socio-cultural value. Unfortunately, limited knowledge about its genetic diversity exists due to a lack of scientific attention. As a result, its potential for improvement in food and agriculture remains largely untapped. To address this gap, a study was conducted using 41 accessions of D. iburua stored in the genebank of the Laboratory of Genetics, Biotechnology, and Seed Science at Abomey-Calavi University, Benin. The study employed both morphological and simple sequence repeat (SSR) markers to evaluate the genetic variability of the accessions. Agro-morphological assessments were carried out during the 2020 cropping season, utilizing an alpha lattice design with three replications. The collected data encompassed qualitative and quantitative traits. Additionally, molecular variability was assessed using eleven SSR markers. The results revealed significant phenotypic variability among the evaluated accessions, leading to their classification into three main clusters. Furthermore, the eleven SSR markers identified a total of 50 alleles, averaging 4.55 alleles per locus. The primers exhibited an average polymorphic information content value of 0.43, with the DE-ARC019 primer displaying the highest value (0.59). These findings suggest a substantial degree of genetic heterogeneity within the evaluated accessions, and the SSR markers employed in the study proved highly effective in detecting and characterizing this genetic variability. In conclusion, this study highlights the presence of significant genetic diversity in black fonio and provides valuable insights for future efforts aimed at its genetic improvement and conservation.

Keywords: genetic diversity, digitaria iburua, genetic improvement, simple sequence repeat markers, Nigeria, conservation

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Authors: Amanda Aliende da Matta

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In different fields, there are people who have something that stands out. In the educational world, for example, it is clear when some teachers have something: they are the best teachers, but this is not directly attributed to their disciplines, methodologies, etc. It is that they have something that captivates, inspires, and motivates. But we also find this something in other contexts. In this thesis, the interest is in something that some marginalized people, such as Ab (fictitious name), have. Ab was born in a rural community and saw the lifestyle of his family change drastically as a consequence of structural changes in his village. The community became impoverished, and together with a group of teenagers, he decided to migrate to Spain in search of opportunities. His best friend drowned during the crossing. After arriving, he lived in indecent conditions and felt unsafe. He now suffers from anxiety and frequently faints from it. Yet, he’s linked to Joves x la pau (a Christian project, although he is a Muslim), distributing food for people who live on the streets every Thursday afternoon. When he asked about what happens on cold and rainy days, he explained simply: "if it rains, I distribute the food, and immediately I get home, take a bath, and sleep warm under my roof. That is when we most have to go." This something he has will be called caring. And one of the general objectives of the thesis is to discover what are the meaning structures of this caring what is the lived experience of this caring. In this communication, preliminary results of an Applied Hermeneutic Phenomenology (AHP) study on the lived experience of caring as a vulnerable person are presented. The research means to answer what is the lived experience of caring as a vulnerable person. That is, to describe and explain what it is like to caregive for a vulnerable person, what it is, essentially, to caregive for a vulnerable person, what makes the lived experience of caregiving for a vulnerable person different from any other. In order to investigate the meaning of the phenomenon of caregiving as a vulnerable person, as already stated, the method used will be Applied Hermeneutic Phenomenology (AHP). We base ourselves, initially, on the proposal of Raquel Ayala-Carabajo and Max Van Manen. As Van Manen (1990) explains, AHP is a method that works essentially through fieldwork, with the collection of data on lived experience (experiential material). It is a phenomenology of practice. We here present the provisional themes we found: caregiving as a vulnerable person is seeing yourself in the other, identifying with the care-receiver; Caregiving as a vulnerable person is putting the other’s need before oneself’s; Caregiving as a vulnerable person is temporarily overcoming your weaknesses to make yourself strong for the other; Caregiving as a vulnerable person is going beyond the conventional approach; and Caregiving as a vulnerable person is taking responsibility even if it’s not yours.

Keywords: applied hermeneutic phenomenology, care ethics, hermeneutics, phenomenology

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Authors: A.Boularouk, F. Chouikh, M. Lamri, H. Moualkia, Y. Bouznit

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The principal aim of this study is to considerably reduce the resistivity of the SnO2 thin layers. In this order, we have doped tin oxide with aluminum and antimony incorporation with different atomic percentages (0 and 4%). All the pure and doped SnO2 films were grown by simple, flexible and cost-effective Automatic Spray Pyrolysis Method (ASPM) on glass substrates at a temperature of 350 °C. The microstructural, optical, morphological and electrical properties of the films have been studied. The XRD results demonstrate that all films have polycrystalline nature with a tetragonal rutile structure and exhibit the (200) preferential orientation. It has been observed that all the dopants are soluble in the SnO2 matrix without forming secondary phases. However, dopant introduction does not modify the film growth orientation. The crystallite size of the pure SnO2 film is about 36 nm. The films are highly transparent in the visible region with an average transmittance reaching up to 80% and it slightly reduces with increasing doping concentration (Al and Sb). The optical band gap value was evaluated between 3.60 eV and 3.75 eV as a function of doping. The SEM image reveals that all films are nanostructured, densely continuous, with good adhesion to the substrate. We note again that the surface morphology change with the type and concentration dopant. The minimum resistivity is 0.689*10-4, which is observed for SnO2 film doped 4% Al. This film shows better properties and is considered the best among all films. Finally, we concluded that the physical properties of the pure and doped SnO2 films grown on a glass substrate by ASPM strongly depend on the type and concentration dopant (Al and Sb) and have highly desirable optical and electrical properties and are promising materials for several applications.

Keywords: tin oxide, automatic spray, Al and Sb doped, transmittance, MEB, XRD and UV-VIS

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Authors: Bonguen Onouck Rolande Carole, Ndongo Barthelemy

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The climate change effects on the Lake Chad, coupled with population growth, have pushed large masses of people of various origins towards the lower part of the lower Logonewatershed in search of the benefits of environmental services, causing pressure on the environment and its resources. Economic services are therefore threatened, and the decrease in resources contributes to the deterioration of the social wellbeing resulting to conflicts among/between local communities, immigrants, displaced people, and foreigners. This paper is an information contribution on ethnical conflicts drivers in the area and the provided local management mechanisms such can help mitigate present or future conflicts in similar areas. It also prints out the necessity to alleviate water access deficit and encourage good practices for the population wellbeing. In order to meet the objective, in 2018, through the interface of the World Bank-Cameroon project-PULCI, data were collected on the field directly by discussing with the population and visiting infrastructures, indirectly by a questionnaire survey. Two administrative divisions were chosen (Logoneet Chari, Mayo-Danay) in which targeted localities were Zina, Mazera, Lahai, Andirni near the Waza Park and Yagoua, Tekele, Pouss, respectively. Due to some sociocultural and religious reasons, some information were acquired through the traditional chiefs. A desk study analysis based on resources access and availability conflicts history, and management mechanism was done. As results, roots drivers of ethnical conflicts are struggles over natural resources access, and the possibility of conflicts increases as the scarcity and vulnerabilities persist, creating more sociocultural gaps and tensions. The mitigation mechanisms though fruitful, are limited. There is poor documentation on the topic, the resources management policies of this basin are unsuitable and ineffective for some. Therefore, the restoration of environmental and ecosystems, the mitigation of climate change effects, and food insecurity are the challenges that must be met to alleviate conflicts in these localities.

Keywords: ethnic, communities, conflicts, mitigation mechanisms, natural resources, logone basin

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Authors: Qiang Zhang, Xiaojian Hu

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In multi-vehicle tracking, based on feature selection, the tracking system efficiently tracks vehicles in a video with minimal error in combination with color attribution, which focuses on presenting a simple and fast, yet accurate and robust solution to the problem such as inaccurately and untimely responses of statistics-based adaptive traffic control system in the intersection scenario. In this study, a real-time tracking system is proposed for multi-vehicle tracking in the intersection scene. Considering the complexity and application feasibility of the algorithm, in the object detection step, the detection result provided by virtual loops were post-processed and then used as the input for the tracker. For the tracker, lightweight methods were designed to extract and select features and incorporate them into the adaptive color tracking (ACT) framework. And the approbatory online feature selection algorithms are integrated on the mature ACT system with good compatibility. The proposed feature selection methods and multi-vehicle tracking method are evaluated on KITTI datasets and show efficient vehicle tracking performance when compared to the other state-of-the-art approaches in the same category. And the system performs excellently on the video sequences recorded at the intersection. Furthermore, the presented vehicle tracking system is suitable for surveillance applications.

Keywords: real-time, multi-vehicle tracking, feature selection, color attribution

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Authors: Nyamela M. ‘Masekhohola, Khanare P. Fumane

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The Lesotho downward trend in mathematics attainment at all levels is compounded by the absence of innovative approaches to teaching and learning in Early Childhood. However, studies have shown that play pedagogy can be used to mitigate the challenges of mathematics education. Despite the benefits of play pedagogy to rural learners, its full potential has not been realized in early childhood care and education classrooms to improve children’s performance in mathematics because the adoption of play pedagogy depends on a strength-based approach. The study explores the potential of play pedagogy to improve mathematics education in early childhood care and education in Lesotho. Strength-based approach is known for its advocacy of recognizing and utilizing children’s strengths, capacities and interests. However, this approach and its promisingattributes is not well-known in Lesotho. In particular, little is known about the attributes of play pedagogy that are essential to improve mathematic education in ECCE programs in Lesotho. To identify such attributes and strengthen mathematics education, this systematic review examines evidence published on the strengths of play pedagogy that supports the teaching and learning of mathematics education in ECCE. The purpose of this review is, therefore, to identify and define the strengths of play pedagogy that supports mathematics education. Moreover, the study intends to understand the rural teachers’ perceived intention of using play in ECCE math classrooms through a strength-based approach. Eight key strengths were found (cues for reflection, edutainment, mathematics language development, creativity and imagination, cognitive promotion, exploration, classification, and skills development). This study is the first to identify and define the strength-based attributes of play pedagogy to improve the teaching and learning of mathematics in ECCE centers in Lesotho. The findings reveal which opportunities teachers find important for improving the teaching of mathematics as early as in ECCE programs. We conclude by discussing the implications of the literature for stimulating dialogues towards formulating strength-based approaches to teaching mathematics, as well as reflecting on the broader contributions of play pedagogy as an asset to improve mathematics in Lesotho and beyond.

Keywords: early childhood education, mathematics education, lesotho, play pedagogy, strength-based approach.

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Authors: J. K. Adedeji, S. T. Ijatuyi

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The application of neural network using pattern recognition to study the fluid dynamics and predict the groundwater reservoirs properties has been used in this research. The essential of geophysical survey using the manual methods has failed in basement environment, hence the need for an intelligent computing such as predicted from neural network is inevitable. A non-linear neural network with an XOR (exclusive OR) output of 8-bits configuration has been used in this research to predict the nature of groundwater reservoirs and fluid dynamics of a typical basement crystalline rock. The control variables are the apparent resistivity of weathered layer (p₁), fractured layer (p₂), and the depth (h), while the dependent variable is the flow parameter (F=λ). The algorithm that was used in training the neural network is the back-propagation coded in C++ language with 300 epoch runs. The neural network was very intelligent to map out the flow channels and detect how they behave to form viable storage within the strata. The neural network model showed that an important variable g_r (gravitational resistance) can be deduced from the elevation and apparent resistivity p_a. The model results from SPSS showed that the coefficients, a, b and c are statistically significant with reduced standard error at 5%.

Keywords: gravitational resistance, neural network, non-linear, pattern recognition

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Authors: Shveta Bathla, Preeti Rawat, Sudarshan Kumar, Rubina Baithalu, Jogender Singh Rana, Tushar Kumar Mohanty, Ashok Kumar Mohanty

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Pregnancy is a complex process which includes series of events such as fertilization, formation of blastocyst, implantation of embryo, placental formation and development of fetus. The success of these events depends on various interactions which are synchronized by endocrine interaction between a receptive dam and competent embryo. These interactions lead to change in expression of hormones and proteins. But till date no protein biomarker is available which can be used to detect successful completion of these events. We employed quantitative proteomics approach to develop putative serological biomarker which has diagnostic applicability for early detection of pregnancy in cows. For this study, sera were collected from control (non-pregnant, n=6) and pregnant animals on successive days of pregnancy (7, 19, 45, n=6). The sera were subjected to depletion for removal of albumin using Norgen depletion kit. The tryptic peptides were labeled with iTRAQ. The peptides were pooled and fractionated using bRPLC over 80 min gradient. Then 12 fractions were injected to nLC for identification and quantitation in DDA mode using ESI. Identification using Mascot search revealed 2056 proteins out of which 352 proteins were differentially expressed. Twenty proteins were upregulated and twelve proteins were down-regulated with fold change > 1.5 and < 0.6 respectively (p < 0.05). The gene ontology studies of DEPs using Panther software revealed that majority of proteins are actively involved in catalytic activities, binding and enzyme regulatory activities. The DEP'S such as NF2, MAPK, GRIPI, UGT1A1, PARP, CD68 were further subjected to pathway analysis using KEGG and Cytoscape plugin Cluego that showed involvement of proteins in successful implantation, maintenance of pluripotency, regulation of luteal function, differentiation of endometrial macrophages, protection from oxidative stress and developmental pathways such as Hippo. Further efforts are continuing for targeted proteomics, western blot to validate potential biomarkers and development of diagnostic kit for early pregnancy diagnosis in cows.

Keywords: bRPLC, Cluego, ESI, iTRAQ, KEGG, Panther

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Authors: T. Sattarpour, D. Nazarpour

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This paper investigates the effect of simultaneous placement of DGs and smart meters (SMs), on voltage profile improvement in active distribution networks (ADNs). A substantial center of attention has recently been on responsive loads initiated in power system problem studies such as distributed generations (DGs). Existence of responsive loads in active distribution networks (ADNs) would have undeniable effect on sizing and siting of DGs. For this reason, an optimal framework is proposed for sizing and siting of DGs and SMs in ADNs. SMs are taken into consideration for the sake of successful implementing of demand response programs (DRPs) such as direct load control (DLC) with end-side consumers. Looking for voltage profile improvement, the optimization procedure is solved by genetic algorithm (GA) and tested on IEEE 33-bus distribution test system. Different scenarios with variations in the number of DG units, individual or simultaneous placing of DGs and SMs, and adaptive power factor (APF) mode for DGs to support reactive power have been established. The obtained results confirm the significant effect of DRPs and APF mode in determining the optimal size and site of DGs to be connected in ADN resulting to the improvement of voltage profile as well.

Keywords: active distribution network (ADN), distributed generations (DGs), smart meters (SMs), demand response programs (DRPs), adaptive power factor (APF)

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Authors: Almutazballlah Qablan, Jihan M. Muhaidat, Bana Abu Rajab

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Background: Acne vulgaris is the most common skin condition that general practitioners and dermatologists encounter. It represents a chronic inflammatory disease affecting the pilosebaceous unit. Although acne vulgaris is not a life-threatening condition, it has a considerable psychological impact on the affected person. Acne patients have poor body image, low self-esteem, social isolation, and restricted activities. As part of the emotional impact, increased levels of anxiety, anger, depression, and frustration have also been observed in acne patients. (1) In this study, we want to assess the association between two modifiable risk factors; BMI and smoking, regarding acne vulgaris. Methods: A case-control study was conducted at King Abdullah University Hospital in Irbid, north Jordan in 2019/2020. A total number of 163 Acne cases were collected and interviewed by the author; on the other hand, there were 162 control cases. Anthropometric measures for Acne patients and control individuals were taken, and BMI was calculated. Both groups were asked about smoking habits. Data on subjects between 14 and 33 years of age were extracted. The characteristics of people who reported acne were compared with those with no acne using univariate and multivariate analysis. The Statistical Package for Social Sciences (SPSS) was relied on to analyze the collected data. The crosstabs methods (chi-square) and odd ratios were relied on to test the study hypothesis. Results: Cigarette smoking was highly associated with no-acne, with an odds ratio of 0.4 (95% CI: 0.2–0.9), P-value = 0.018. BMI and waterpipe smoking were not significantly associated with acne in the multivariate analysis. Conclusion: Cigarette smoking was found to be protective from Acne. No significant relation between BMI nor waterpipe smoking and the development of Acne Vulgaris.

Keywords: acne, BMI, smoking, case-control

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Authors: Isabel Moscol, Carlos J. Díaz, Ciro Rodríguez

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Hip replacement becomes necessary when a person suffers severe pain or considerable functional limitations and the best option to enhance their quality of life is through the replacement of the damaged joint. One of the main components in femoral prostheses is the stem which distributes the loads from the joint to the proximal femur. To preserve more bone stock and avoid weakening of the diaphysis, a short starting stem was selected, generated from the intramedullary morphology of the patient's femur. It ensures the implantability of the design and leads to geometric delimitation for personalized optimization with machine learning (ML) and metaheuristic algorithms. The present study attempts to design a cementless short stem to make the strain deviation before and after implantation close to zero, promoting its fixation and durability. Regression models developed to estimate the percentage change of maximum principal stresses were used as objective optimization functions by the metaheuristic algorithm. The latter evaluated different geometries of the short stem with the modification of certain parameters in oblique sections from the osteotomy plane. The optimized geometry reached a global stress shielding (SS) of 18.37% with a determination factor (R²) of 0.667. The predicted results favour implantability integration in the short stem optimization to effectively reduce SS in the proximal femur.

Keywords: machine learning techniques, metaheuristic algorithms, short-stem design, stress shielding, hip replacement

Procedia PDF Downloads 192