Search results for: critical reflective learning

Authors: Andres Bautista, Alicia Porras, Juan P. Casas, Maribel Silva

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The Colombian aeronautical industry has stimulated research in the mechanical behavior of materials under different loading conditions aircrafts are generally exposed during its operation. The Calima T-90 is the first military aircraft built in the country, used for primary flight training of Colombian Air Force Pilots, therefore, it may be exposed to adverse operating situations such as hard landings which cause impact loads on the aircraft that might produce the impact fatigue phenomenon. The Calima T-90 structure is mainly manufactured by composites materials generating assemblies and subassemblies of different components of it. The main method of bonding these components is by using adhesive joints. Each type of adhesive bond must be studied on its own since its performance depends on the conditions of the manufacturing process and operating characteristics. This study aims to characterize the typical adhesive joints of the aircraft under usual loads. To this purpose, the evaluation of the effect of adhesive thickness on the mechanical performance of the joint under quasi-static loading conditions, constant amplitude fatigue and cyclic impact fatigue using single lap-joint specimens will be performed. Additionally, using a double cantilever beam specimen, the influence of the thickness of the adhesive on the crack growth rate for mode I delamination failure, as a function of the critical energy release rate will be determined. Finally, an analysis of the fracture surface of the test specimens considering the mechanical interaction between the substrate (composite) and the adhesive, provide insights into the magnitude of the damage, the type of failure mechanism that occurs and its correlation with the way crack propagates under the proposed loading conditions.

Keywords: adhesive, composites, crack propagation, fatigue

Procedia PDF Downloads 204

Authors: M. Abbasi Layegh, S. Haghipour, K. Athari, R. Khosravi, M. Tafkikialamdari

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An approach to find the optimum mel-frequency cepstral coefficients (MFCCs) for the Radif of Mirzâ Ábdollâh, which is the principal emblem and the heart of Persian music, performed by most famous Iranian masters on two Iranian stringed instruments ‘Tar’ and ‘Setar’ is proposed. While investigating the variance of MFCC for each record in themusic database of 1500 gushe of the repertoire belonging to 12 modal systems (dastgâh and âvâz), we have applied the Fuzzy C-Mean clustering algorithm on each of the 12 coefficient and different combinations of those coefficients. We have applied the same experiment while increasing the number of coefficients but the clustering accuracy remained the same. Therefore, we can conclude that the first 7 MFCCs (V-7MFCC) are enough for classification of The Radif of Mirzâ Ábdollâh. Classical machine learning algorithms such as MLP neural networks, K-Nearest Neighbors (KNN), Gaussian Mixture Model (GMM), Hidden Markov Model (HMM) and Support Vector Machine (SVM) have been employed. Finally, it can be realized that SVM shows a better performance in this study.

Keywords: radif of Mirzâ Ábdollâh, Gushe, mel frequency cepstral coefficients, fuzzy c-mean clustering algorithm, k-nearest neighbors (KNN), gaussian mixture model (GMM), hidden markov model (HMM), support vector machine (SVM)

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Authors: Tooran Tavangar, Masoud Hosseinpoor, Jeffrey S. Marshall, Ammar Yahia, Kamal Henri Khayat

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In this study, a four-way coupled CFD-DEM methodology was used to simulate the behavior of concrete pipe flow. Fresh concrete, characterized as a biphasic suspension, features aggregates comprising the solid-suspended phase with diverse particle-size distributions (PSD) within a non-Newtonian cement paste/mortar matrix forming the liquid phase. The fluid phase was simulated using CFD, while the aggregates were modeled using DEM. Interaction forces between the fluid and solid particles were considered through CFD-DEM computations. To capture the viscoelastic characteristics of the suspending fluid, a bi-viscous approach was adopted, incorporating a critical shear rate proportional to the yield stress of the mortar. In total, three diphasic suspensions were simulated, each featuring distinct particle size distributions and a concentration of 10% for five subclasses of spherical particles ranging from 1 to 17 mm in a suspending fluid. The adopted bi-viscous approach successfully simulated both un-sheared (plug flow) and sheared zones. Furthermore, shear-induced particle migration (SIPM) was assessed by examining coefficients of variation in particle concentration across the pipe. These SIPM values were then compared with results obtained using CFD-DEM under the Newtonian assumption. The study highlighted the crucial role of yield stress in the mortar phase, revealing that lower yield stress values can lead to increased flow rates and higher SIPM across the pipe.

Keywords: computational fluid dynamics, concrete pumping, coupled CFD-DEM, discrete element method, plug flow, shear-induced particle migration.

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Authors: Raymon P. Española

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Hearing impaired students are admitted to regular high schools in the context of inclusive education. In this setting, several academic difficulties and social struggles are disregarded by many educators. The study aimed to describe the aspirations and lived experiences in mainstream classrooms of hearing impaired students. In the research process, the participants were interviewed using sign language. Thematic analysis of interview responses was done, supplemented by interviews with teachers and classroom observations. The study revealed four patterns of experiences: academic difficulties, coping mechanisms, identification with hearing peers, and impression management. This means that these learners were struggling in inclusive classrooms, where identification with and modeling the positive qualities of hearing peers were done to cope with academic difficulties and alter negative impressions about them. By implication, these learners tended to socially immerse themselves rather than resort to isolation. Along with this tendency was the aspiration for achievement as they were eager to finish post-secondary technical-vocational education. This means aspiring for continuing social immersion into the mainstream. All these findings provide insights to K-12 educators to increase the use of collaborative techniques and experiential learning strategies, as well as to adequately address the special educational needs of these students.

Keywords: descriptive, experiences and aspirations of hearing impaired learners, inclusive classrooms, Surigao City Philippines

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Authors: Justin Tang

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Balance tests are frequently used to diagnose concussions on the sidelines of sporting events. Manual scoring, however, is labor intensive and subjective, and many concussions go undetected. This study institutes a novel approach to conducting the Balance Error Scoring System (BESS) more quantitatively using Microsoft’s gaming system Kinect, which uses a contactless sensor and several cameras to receive data and estimate body limb positions. Using a machine learning approach, Visual Gesture Builder, and a deterministic approach, MATLAB, we tested whether the Kinect can differentiate between “correct” and erroneous stances of the BESS. We created the two separate solutions by recording test videos to teach the Kinect correct stances and by developing a code using Java. Twenty-two subjects were asked to perform a series of BESS tests while the Kinect was collecting data. The Kinect recorded the subjects and mapped key joints onto their bodies to obtain angles and measurements that are interpreted by the software. Through VGB and MATLAB, the videos are analyzed to enumerate the number of errors committed during testing. The resulting statistics demonstrate a high correlation between manual scoring and the Kinect approaches, indicating the viability of the use of remote tracking devices in conducting concussion tests.

Keywords: automated, concussion detection, contactless sensors, microsoft kinect

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Authors: Satpal Yadav, Ashish Phulkar, Krishna K. Sahu

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Aim: The research aims at doing a 3 Dimension biomechanical analysis in the shot put techniques of International throwers to evaluate the performance. Research Method: The researcher adopted the descriptive method and the data was subjected to calculate by using Pearson’s product moment correlation for the correlation of the biomechanical parameters with the performance of shot put throw. In all the analyses, the 5% critical level (p ≤ 0.05) was considered to indicate statistical significance. Research Sample: Eight (N=08) international shot putters using rotational/glide technique in male category was selected as subjects for the study. The researcher used the following methods and tools to obtain reliable measurements the instrument which was used for the purpose of present study namely the tesscorn slow-motion camera, specialized motion analyzer software, 7.260 kg Shot Put (for a male shot-putter) and steel tape. All measurement pertaining to the biomechanical variables was taken by the principal investigator so that data collected for the present study was considered reliable. Results: The finding of the study showed that negative significant relationship between the angular velocity right shoulder, acceleration distance at pre flight (-0.70), (-0.72) respectively were obtained, the angular displacement of knee, angular velocity right shoulder and acceleration distance at flight (0.81), (0.75) and (0.71) respectively were obtained, the angular velocity right shoulder and acceleration distance at transition phase (0.77), (0.79) respectively were obtained and angular displacement of knee, angular velocity right shoulder, release velocity shot, angle of release, height of release, projected distance and measured distance as the values (0.76), (0.77), (-0.83), (-0.79), (-0.77), (0.99) and (1.00) were found higher than the tabulated value at 0.05 level of significance. On the other hand, there exists an insignificant relationship between the performance of shot put and acceleration distance [m], angular displacement shot, C.G at release and horizontal release distance on the technique of shot put.

Keywords: biomechanics, analysis, shot put, international throwers

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Authors: Soodabeh Dehghan, Siavash Hamidzadeh, Naqshbandi Seyyed Salahedin, Ali Mohammad Safania

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The present research with the aim of the relationship between organizational silence and organizational voice with quality of work-life among employees of the sport and youth departments of Tehran Province was done. The statistical population of this research includes all employees of the sport and youth departments of Tehran province, and considering the not very large number of society, the sample and society were considered to be the same, and the sample was considered as the whole number. To measure each of these variables, a questionnaire was used. The research questionnaire was presented in four sections. The results showed that, since the extension of the process of organizational silence is usually done by managers, their attitude and attitudes toward this phenomenon are prioritized and also because silence reduces learning due to lack of knowledge sharing, makes it less effective and makes changes more difficult, it is necessary to take steps to break the silence and to further urge the staff (employees) to express their beliefs (organizational voices) and to share them in the organization's fate individuals, whose beliefs are respected and so called taken into account in the organization, would be dependent on the organization and feel obliged to remain with the organization during the hardships. This affects employees' quality of work life and their satisfaction too much.

Keywords: organizational silence, organizational voice, quality of work life, the sports and youth departments of Tehran province

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Authors: Aimite Jorge, Leenekela Usebiu

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In recent years the International Community has seen a rise of what can be termed as ‘actio popularis”;that is to say lawsuits brought by third parties in the interest of the public or the world community as a whole, such as in cases of genocide and terrorism prosecutions under international law. It is equally clear that under current globalized world the effect of multinational activities on the environment is often felt beyond the borders of the territories where they operate. Equally true is the fact that the correspondence of citizens self-determination with national government is increasingly upset by the increasing willingness of states to share some ‘sovereign powers’ in order to address new economic, environmental and security interdependencies. The ‘unbundling’ of functional governance from fixed territories sees continuously citizens give up their formal approval of key decisions in exchange for a more remote, indirect say in supra-national or international decision-making bodies. The efforts to address a growing transnational flow of ecological harm are at the forefront of such indirect transformations, as evidenced by a proliferation of multilateral environmental agreements (MEAs) over the past three decades. However, unlike the defence of the global commons in cases of terrorism and genocide, there is still to be a clear application of action popularis in the case of environment, despite acknowledgement that the effect of the activities of several multinationals on the environment is as destructive to the global commons as genocide or terrorism are. Thus, this paper looking at specific cases of harmful degradation of the environment by certain multinationals transcending national boundaries, argues that it is high-time for a serious consideration of the application of the actio-popularis to environmental concerns. Although it is acknowledged that in international environmental law the challenge to reach a “critical mass” of recognition and support for an ‘actio-popularis’ for environment damage is particularly demanding, it is worth the try.

Keywords: actio popularis in environment law, global commons, transnational environmental damage, law and environment

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Authors: Hana Porkertová, Pavel Doboš

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Based on a research project studying the experience of visually disabled people with urban space in the Czech Republic, the conference contribution discusses the limits of social-science methodologies used in sociology and human geography. It draws on actor-network theory, assuming that science does not describe reality but produces it. Methodology connects theory, research questions, ways to answer them (methods), and results. A research design utilizing ableist methodologies can produce ableist realities. Therefore, it was necessary to adjust the methods so that they could mediate blind experience to the scientific community without reproducing ableism. The researchers faced multiple challenges, ranging from questionable validity to how to research experience that differs from that of the researchers who are able-bodied. Finding a suitable theory that could be used as an analytical tool that would demonstrate space and blind experience as multiple, dynamic, and mutually constructed was the first step that could offer a range of potentially productive methods and research questions, as well as bring critically reflected results. Poststructural theory, mainly Deleuze-Guattarian philosophy, was chosen, and two methods were used: interviews and go-along interviews that had to be adjusted to be able to explore blind experience. In spite of a thorough preparation of these methods, new difficulties kept emerging, which exposed the ableist character of scientific knowledge. From the beginning of data collecting, there was an agreement to work in teams with slightly different roles of each of the researchers, which was significant especially during go-along interviews. In some cases, the anticipations of the researchers and participants differed, which led to unexpected and potentially dangerous situations. These were not caused only by the differences between scientific and lay communities but also between able-bodied and disabled people. Researchers were sometimes assigned to the assistants’ roles, and this new position – doing research together – required further negotiations, which also opened various ethical questions.

Keywords: ableist methodology, blind experience, go-along interviews, research ethics, scientific knowledge

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Authors: Xuyang Song, Jun Yin

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The smart card has been an extremely universal tool in public transit. It collects a large amount of data on buses, urban railway transit, and ferries and provides possibilities for passenger profiling. This paper combines offline analysis of passenger profiling and real-time prediction to propose a method that can accurately predict the destination station in real-time when passengers tag on. Firstly, this article constructs a static database of user travel characteristics after identifying passenger travel patterns based on the Density-Based Spatial Clustering of Applications with Noise (DBSCAN). The dual travel passenger habits are identified: OD travel habits and D station travel habits. Then a rapid real-time prediction algorithm based on Transit Passenger Profiling is proposed, which can predict the destination of in-board passengers. This article combines offline learning with online prediction, providing a technical foundation for real-time passenger flow prediction, monitoring and simulation, and short-term passenger behavior and demand prediction. This technology facilitates the efficient and real-time acquisition of passengers' travel destinations and demand. The last, an actual case was simulated and demonstrated feasibility and efficiency.

Keywords: travel behavior, destination prediction, public transit, passenger profiling

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Authors: R. R. Billones, N. Lukkahatai, L. N. Saligan

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Mindfulness based interventions (MBIs) have been used in medically unexplained symptoms (MUS). This systematic review describes the literature investigating the general effect of MBIs on MUS and identifies the effects of specific MBIs on specific MUS conditions. The preferred reporting items for systematic reviews and meta-analysis guidelines (PRISMA) and the modified Oxford quality scoring system (JADAD) were applied to the review, yielding an initial 1,556 articles. The search engines included PubMed, ScienceDirect, Web of Science, Scopus, EMBASE, and PsychINFO using the search terms: mindfulness, or mediations, or mindful or MBCT or MBSR and medically unexplained symptoms or MUS or fibromyalgia or FMS. A total of 24 articles were included in the final systematic review. MBIs showed large effects on socialization skills for chronic fatigue syndrome (d=0.65), anger in fibromyalgia (d=0.61), improvement of somatic symptoms (d=1.6) and sleep (d=1.12) for painful conditions, physical health for chronic back pain (d=0.51), and disease intensity for irritable bowel disease/syndrome (d=1.13). A manualized MBI that applies the four fundamental elements present in all types of interventions were critical to efficacy. These elements were psycho-education sessions specific to better understand the medical symptoms, the practice of awareness, the non-judgmental observance of the experience at the moment, and the compassion to ones’ self. The effectiveness of different mindfulness interventions necessitates giving attention to improve the gaps that were identified related to home-based practice monitoring, competency training of mindfulness teachers, and sound psychometric properties to measure the mindfulness practice.

Keywords: mindfulness-based interventions, medically unexplained symptoms, mindfulness-based cognitive therapy, mindfulness-based stress reduction, fibromyalgia, irritable bowel syndrome

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Authors: Junaid Ahmed, Nandita Shenoy

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Maintaining lifelong knowledge and skills is essential for safe clinical practice. Continuing Professional Development (CPD) is an established method that can facilitate lifelong learning. It focuses on maintaining or developing knowledge, skills and relationships to ensure competent practice.To date, relatively little has been done to comprehensively and systematically synthesize evidence to identify subjects of interest among practising dentist. Hence the aim of our study was to identify areas in clinical practice that would be favourable for continuing professional dental education amongst practicing dentists. Participants of this study consisted of the practicing dental surgeons of Mangalore, a city in Dakshina Kannada, Karnataka. 95% of our practitioners felt that regular updating as a one day program once in 3-6 months is required, to keep them abreast in clinical practice. 60% of subjects feel that CPD programs enrich their theoretical knowledge and helps in patient care. 27% of them felt that CPD programs should be related to general dentistry. Most of them felt that CPD programs should not be charged nominally between one to two thousand rupees. The acronym ‘CPD’ should be seen in a broader view in which professionals continuously enhance not only their knowledge and skills, but also their thinking,understanding and maturity; they grow not only as professionals, but also as persons; their development is not restricted to their work roles, but may also extend to new roles and responsibilities.

Keywords: continuing professional development, competent practice, dental education, practising dentist

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Authors: Hosein Maghsoudi

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Rheumatois arthritis (RA) is progressive inflammatory autoimmune diseases that primarily affect the joints, characterized by synovial hyperplasia and inflammatory cell infiltration, deformed and painful joints, which can lead tissue destruction, functional disability systemic complications, and early dead and socioeconomic costs. The cause of rheumatoid arthritis is unknown, but genetic and environmental factors are contributory and the prognosis is guarded. However, advances in understanding the pathogenesis of the disease have fostered the development of new therapeutics, with improved outcomes. The current treatment strategy, which reflects this progress, is to initiate aggressive therapy soon after diagnosis and to escalate the therapy, guided by an assessment of disease activity, in pursuit of clinical remission. The pathobiology of RA is multifaceted and involves T cells, B cells, fibroblast-like synoviocyte (FLSc) and the complex interaction of many pro-inflammatory cytokine. Novel biologic agents that target tumor necrosis or interlukin (IL)-1 and Il-6, in addition T- and B-cells inhibitors, have resulted in favorable clinical outcomes in patients with RA. Despite this, at least 30% of RA patients are résistance to available therapies, suggesting novel mediators should be identified that can target other disease-specific pathway or cell lineage. Among the inflammatory cell population that might participated in RA pathogenesis, FLSc are crucial in initiaing and driving RA in concert of cartilage and bone by secreting metalloproteinase (MMPs) into the synovial fluid and by direct invasion into extracellular matrix (ECM), further exacerbating joint damage. Invasion of fibroblast-like synoviocytes (FLSc) is critical in the pathogenesis of rheumatoid-arthritis. The metalloproteinase (MMPs) and activator of Toll-like receptor 4 (TLR4)/nuclear factor- κB pthway play a critical role in RA-FLS invasion induced by lipopolysaccharide (LPS). The present study aimed to explore the anti-invasion activity of Glycyrrhizic Acid as a pharmacologically safe phytochemical agent with potent anti-inflammatory properties on IL-1beta and TNF-alpha signalling pathways in Bovine fibroblast-like synoviocyte ex- vitro, on LPS-stimulated bovine FLS migration and invasion as well as MMP expression and explored the upstream signal transduction. Results showed that Glycyrrhizic Acid suppressed LPS-stimulated bovine FLS migration and invasion by inhibition MMP-9 expression and activity. In addition our results revealed that Glycyrrhizic Acid inhibited the transcriptional activity of MMP-9 by suppression the nbinding activity of NF- κB in the MMP-9 promoter pathway. The extract of licorice (Glycyrrhiza glabra L.) has been widely used for many centuries in the traditional Chinese medicine as native anti-allergic agent. Glycyrrhizin (GL), a triterpenoidsaponin, extracted from the roots of licorice is the most effective compound for inflammation and allergic diseases in human body. The biological and pharmacological studies revealed that GL possesses many pharmacological effects, such as anti-inflammatory, anti-viral and liver protective effects, and the biological effects, such as induction of cytokines (interferon-γ and IL-12), chemokines as well as extrathymic T and anti-type 2 T cells. GL is known in the traditional Chinese medicine for its anti-inflammatory effect, which is originally described by Finney in 1959. The mechanism of the GL-induced anti-inflammatory effect is based on different pathways of the GL-induced selective inhibition of the prostaglandin E2 production, the CK-II- mediated activation of both GL-binding lipoxygenas (gbLOX; 17) and PLA2, an anti-thrombin action of GL and production of the reactive oxygen species (ROS; GL exerts liver protection properties by inhibiting PLA2 or by the hydroxyl radical trapping action, leading to the lowering of serum alanine and aspartate transaminase levels. The present study was undertaken to examine the possible mechanism of anti-inflammatory properties GL on IL-1beta and TNF-alpha signalling pathways in bovine fibroblast-like synoviocyte ex-vivo, on LPS-stimulated bovine FLS migration and invasion as well as MMP expression and explored the upstream signal transduction. Our results clearly showed that treatment of bovine fibroblast-like synoviocyte with GL suppressed LPS-induced cell migration and invasion. Furthermore, it revealed that GL inhibited the transcription activity of MMP-9 by suppressing the binding activity of NF-κB in the MM-9 promoter. MMP-9 is an important ECM-degrading enzyme and overexpression of MMPs in important of RA-FLSs. LPS can stimulate bovine FLS to secret MMPs, and this induction is regulated at the transcription and translational levels. In this study, LPS treatment of bovine FLS caused an increase in MMP-2 and MMP-9 levels. The increase in MMP-9 expression and secretion was inhibited by ex- vitro. Furthermore, these effects were mimicked by MMP-9 siRNA. These result therefore indicate the the inhibition of LPS-induced bovine FLS invasion by GL occurs primarily by inhibiting MMP-9 expression and activity. Next we analyzed the functional significance of NF-κB transcription of MMP-9 activation in Bovine FLSs. Results from EMSA showed that GL suppressed LPS-induced NF-κB binding to the MMP-9 promotor, as NF-κB regulates transcriptional activation of multiple inflammatory cytokines, we predicted that GL might target NF-κB to suppress MMP-9 transcription by LPS. Myeloid differentiation-factor 88 (MyD88) and TIR-domain containing adaptor protein (TIRAP) are critical proteins in the LPS-induced NF-κB and apoptotic signaling pathways, GL inhibited the expression of TLR4 and MYD88. These results demonstrated that GL suppress LPS-induced MMP-9 expression through the inhibition of the induced TLR4/NFκB signaling pathway. Taken together, our results provide evidence that GL exerts anti-inflammatory effects by inhibition LPS-induced bovine FLSs migration and invasion, and the mechanisms may involve the suppression of TLR4/NFκB –mediated MMP-9 expression. Although further work is needed to clarify the complicated mechanism of GL-induced anti-invasion of bovine FLSs, GL might be used as a further anti-invasion drug with therapeutic efficacy in the treatment of immune-mediated inflammatory disease such as RA.

Keywords: glycyrrhizic acid, bovine fibroblast-like synoviocyte, tlr4/nf-κb, metalloproteinase-9

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Authors: Thaveesha Dheerasekera, Dileeka Sandamali Alwis

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The escalating prevalence of mental health issues, such as depression and suicidal ideation, is a matter of significant global concern. It is plausible that a variety of factors, such as life events, social isolation, and preexisting physiological or psychological health conditions, could instigate or exacerbate these conditions. Traditional approaches to diagnosing depression entail a considerable amount of time and necessitate the involvement of adept practitioners. This underscores the necessity for automated systems capable of promptly detecting and diagnosing symptoms of depression. The PsyVBot system employs sophisticated natural language processing and machine learning methodologies, including the use of the NLTK toolkit for dataset preprocessing and the utilization of a Long Short-Term Memory (LSTM) model. The PsyVBot exhibits a remarkable ability to diagnose depression with a 94% accuracy rate through the analysis of user input. Consequently, this resource proves to be efficacious for individuals, particularly those enrolled in academic institutions, who may encounter challenges pertaining to their psychological well-being. The PsyVBot employs a Long Short-Term Memory (LSTM) model that comprises a total of three layers, namely an embedding layer, an LSTM layer, and a dense layer. The stratification of these layers facilitates a precise examination of linguistic patterns that are associated with the condition of depression. The PsyVBot has the capability to accurately assess an individual's level of depression through the identification of linguistic and contextual cues. The task is achieved via a rigorous training regimen, which is executed by utilizing a dataset comprising information sourced from the subreddit r/SuicideWatch. The diverse data present in the dataset ensures precise and delicate identification of symptoms linked with depression, thereby guaranteeing accuracy. PsyVBot not only possesses diagnostic capabilities but also enhances the user experience through the utilization of audio outputs. This feature enables users to engage in more captivating and interactive interactions. The PsyVBot platform offers individuals the opportunity to conveniently diagnose mental health challenges through a confidential and user-friendly interface. Regarding the advancement of PsyVBot, maintaining user confidentiality and upholding ethical principles are of paramount significance. It is imperative to note that diligent efforts are undertaken to adhere to ethical standards, thereby safeguarding the confidentiality of user information and ensuring its security. Moreover, the chatbot fosters a conducive atmosphere that is supportive and compassionate, thereby promoting psychological welfare. In brief, PsyVBot is an automated conversational agent that utilizes an LSTM model to assess the level of depression in accordance with the input provided by the user. The demonstrated accuracy rate of 94% serves as a promising indication of the potential efficacy of employing natural language processing and machine learning techniques in tackling challenges associated with mental health. The reliability of PsyVBot is further improved by the fact that it makes use of the Reddit dataset and incorporates Natural Language Toolkit (NLTK) for preprocessing. PsyVBot represents a pioneering and user-centric solution that furnishes an easily accessible and confidential medium for seeking assistance. The present platform is offered as a modality to tackle the pervasive issue of depression and the contemplation of suicide.

Keywords: chatbot, depression diagnosis, LSTM model, natural language process

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Authors: kaveh Jalilzadeh, Maryam Rastgari

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Motivation for learning a foreign language is needed for learners of any foreign language to effectively learn language skills. However, there are some factors that lead to the learners’ demotivation. Therefore, teachers of foreign languages, most notably English language which turned out to be an international language for academic and business purposes, need to be well aware of the demotivation sources and know how to reduce learners’ demotivation. This study is an attempt to explore demotivation-reducing strategies employed by Turkish EFL learners in L2 writing. The researchers used a qualitative case study and employed semi-structured interviews to collect data. The informants recruited in this study were 20 English writing lecturers who were selected through purposive sampling among university lecturers/instructors at the state and non-state universities in Istanbul and Ankara. Interviews were transcribed verbatim, and MAXQDA software (version 2022) was used for performing coding and thematic analysis of the data. Findings revealed that Turkish EFL teachers use 18 strategies to reduce language learners’ demotivation. The most frequently reported strategies were: writing in a group, writing about interesting topics, writing about new topics, writing about familiar topics, writing about simple topics, and writing about relevant topics. The findings have practical implications for writing teachers and learners of the English language.

Keywords: phenomenological study, emotional vulnerability, motivation, digital Settings

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Authors: Cuneyt Yucelbas, Seral Ozsen, Sule Yucelbas, Gulay Tezel

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Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.

Keywords: artificial immune system, breast cancer diagnosis, Euclidean function, Gaussian function

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Authors: Andrey Khalov

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The rapid proliferation of unstructured data in IT infrastructure management demands innovative approaches for extracting actionable knowledge. This paper presents a framework for ontology-based knowledge extraction that combines relational graph neural networks (R-GNN) with large language models (LLMs). The proposed method leverages the DOLCE framework as the foundational ontology, extending it with concepts from ITSMO for domain-specific applications in IT service management and outsourcing. A key component of this research is the use of transformer-based models, such as DeBERTa-v3-large, for automatic entity and relationship extraction from unstructured texts. Furthermore, the paper explores how transfer learning techniques can be applied to fine-tune large language models (LLaMA) for using to generate synthetic datasets to improve precision in BERT-based entity recognition and ontology alignment. The resulting IT Ontology (ITO) serves as a comprehensive knowledge base that integrates domain-specific insights from ITIL processes, enabling more efficient decision-making. Experimental results demonstrate significant improvements in knowledge extraction and relationship mapping, offering a cutting-edge solution for enhancing cognitive computing in IT service environments.

Keywords: ontology mapping, R-GNN, knowledge extraction, large language models, NER, knowlege graph

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Authors: Zhanna Dedovets

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Fostering a mathematical style of thinking is crucial for cultivating intellectual personalities capable of thriving in modern society. Intuitive thinking stands as a cornerstone among the components of mathematical cognition, playing a pivotal role in grasping mathematical truths across various disciplines. This article delves into the exploration of leveraging search activities rooted in students' intuitive thinking, particularly when tackling geometric problems. Emphasizing both student engagement with the task and their active involvement in the search process, the study underscores the importance of heuristic procedures and the freedom for students to chart their own problem-solving paths. Spanning several years (2019-2023) at the Physics and Mathematics Lyceum of Dushanbe, the research engaged 17 teachers and 78 high school students. After assessing the initial levels of intuitive thinking in both control and experimental groups, the experimental group underwent training following the authors' methodology. Subsequent analysis revealed a significant advancement in thinking levels among the experimental group students. The methodological approaches and teaching materials developed through this process offer valuable resources for mathematics educators seeking to enhance their students' learning experiences effectively.

Keywords: teaching of mathematics, intuitive thinking, heuristic procedures, geometric problem, students.

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Authors: Georgii Emelianov, Mikhail Polikarpov, Fabian Hübner, Jochen Deuse, Jochen Schiemann

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Recycling refrigerating appliances plays a major role in protecting the Earth's atmosphere from ozone depletion and emissions of greenhouse gases. The performance of refrigerator recycling plants in terms of material retention is the subject of strict environmental certifications and is reviewed periodically through specialized audits. The continuous collection of Refrigerator data required for the input-output analysis is still mostly manual, error-prone, and not digitalized. In this paper, we propose an automated data collection system for recycling plants in order to deduce expected material contents in individual end-of-life refrigerating appliances. The system utilizes laser scanner measurements and optical data to extract attributes of individual refrigerators by applying transfer learning with pre-trained vision models and optical character recognition. Based on Recognized features, the system automatically provides material categories and target values of contained material masses, especially foaming and cooling agents. The presented data collection system paves the way for continuous performance monitoring and efficient control of refrigerator recycling plants.

Keywords: automation, data collection, performance monitoring, recycling, refrigerators

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Authors: Hajra Hussain

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Positive education, the inclusion of social, emotional and intellectual skills across a curriculum, is fundamental to the optimal functioning of young people in any society because it combines the best teaching practices with the principles of positive psychology. While learning institutions foster academic skills, little attention is being paid to the identification and development of character strengths and their integration into teaching. There is an increasing recognition of the important role education plays in equipping today’s youth with 21st century social skills. For youth to succeed in this highly competitive environment, there is a need for positive education that is focused on character strengths such as the growth of social, emotional and intellectual skills that promote the flourishing of well-rounded individuals. Character strength programs and awareness are a necessity if the human capital within a region is to be competitive, productive and happy. The Counselling & Wellbeing Centre at Amity University Dubai has consistently implemented Character Strength awareness workshops and has found that such workshops have increased student life satisfaction due to individual awareness of signature strengths. A positive education/positive psychology framework with its key focus on the development of character strengths can be fundamental to individual's confidence and self-awareness; thus allowing both optimum flourishing and functioning.

Keywords: positive psychology, positive education, strengths, youth, happiness

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Authors: Young Kwon Yang, Bo Rang Park, Hyo Eun Lee, Tea Won Kim, Eun Ji Choi, Jin Chul Park

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To develop an artificial intelligence based automatic ventilation system, recent research trends were analyzed and analyzed. This research method is as follows. In the field of architecture and window technology, the use of artificial intelligence, the existing study of machine learning model and the theoretical review of the literature were carried out. This paper collected journals such as Journal of Energy and Buildings, Journal of Renewable and Sustainable Energy Reviews, and articles published on Web-sites. The following keywords were searched for articles from 2000 to 2016. We searched for the above keywords mainly in the title, keyword, and abstract. As a result, the global artificial intelligence market is expected to grow at a CAGR of 14.0% from USD127bn in 2015 to USD165bn in 2017. Start-up investments in artificial intelligence increased from the US $ 45 million in 2010 to the US $ 310 million in 2015, and the number of investments increased from 6 to 54. Although AI is making efforts to advance to advanced countries, the level of technology is still in its infant stage. Especially in the field of architecture, artificial intelligence (AI) is very rare. Based on the data of this study, it is expected that the application of artificial intelligence and the application of architectural field will be revitalized through the activation of artificial intelligence in the field of architecture and window.

Keywords: artificial intelligence, window, fine dust, thermal comfort, ventilation system

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Authors: Somayeh Abedian, Pirhossein Kolivand, Hamid Reza Lornejad, Amin Karampour, Ebrahim Keshavarz Safari

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For emergency and relief service providers such as pre-hospital emergencies, quick arrival at the scene of an accident or any EMS mission is one of the most important requirements of effective service delivery. Response time (the interval between the time of the call and the time of arrival on scene) is a critical factor in determining the quality of pre-hospital Emergency Medical Services (EMS). This is especially important for heart attack, stroke, or accident patients. Location-based e-services can be broadly defined as any service that provides information pertinent to the current location of an active mobile handset or precise address of landline phone call at a specific time window, regardless of the underlying delivery technology used to convey the information. According to research, one of the effective methods of meeting this goal is determining the location of the caller via the cooperation of landline and mobile phone operators in the country. The follow-up of the Communications Regulatory Authority (CRA) organization has resulted in the receipt of two separate secured electronic web services. Thus, to ensure human privacy, a secure technical architecture was required for launching the services in the pre-hospital EMS information management system. In addition, to quicken medics’ arrival at the patient's bedside, rescue vehicles should make use of an intelligent transportation system to estimate road traffic using a GPS-based mobile navigation system independent of the Internet. This paper seeks to illustrate the architecture of the practical national model used by the Iranian EMS organization.

Keywords: response time, geographic location inquiry service (GLIS), location-based service (LBS), emergency medical services information system (EMSIS)

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Authors: Mawloud Mosbah, Bachir Boucheham

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We present here the results for a comparative study of some techniques, available in the literature, related to the relevance feedback mechanism in the case of a short-term learning. Only one method among those considered here is belonging to the data mining field which is the K-Nearest Neighbours Algorithm (KNN) while the rest of the methods is related purely to the information retrieval field and they fall under the purview of the following three major axes: Shifting query, Feature Weighting and the optimization of the parameters of similarity metric. As a contribution, and in addition to the comparative purpose, we propose a new version of the KNN algorithm referred to as an incremental KNN which is distinct from the original version in the sense that besides the influence of the seeds, the rate of the actual target image is influenced also by the images already rated. The results presented here have been obtained after experiments conducted on the Wang database for one iteration and utilizing colour moments on the RGB space. This compact descriptor, Colour Moments, is adequate for the efficiency purposes needed in the case of interactive systems. The results obtained allow us to claim that the proposed algorithm proves good results; it even outperforms a wide range of techniques available in the literature.

Keywords: CBIR, category search, relevance feedback, query point movement, standard Rocchio’s formula, adaptive shifting query, feature weighting, original KNN, incremental KNN

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Authors: Irene Carter, Roy Hanes, Judy MacDonald

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Considering that disability is universal and people with disabilities are part of all societies; that there is a connection between the disabled individual and the societal; and that it is society and social arrangements that disable people with impairments, contemporary disability discourse emphasizes the social model of disability to counter medical and rehabilitative models of disability. However, the social model does not go far enough in addressing the issues of oppression and inclusion. The authors indicate that the social model does not specifically or adequately denote the oppression of persons with disabilities, which is a central component of progressive social work practice with people with disabilities. The social model of disability does not go far enough in deconstructing disability and offering social workers, as well as people with disabilities a way of moving forward in terms of practice anchored in individual, familial and societal change. The social model of disability is expanded by incorporating principles of anti-oppression social work practice. Although the contextual analysis of the social model of disability is an important component there remains a need for social workers to provide service to individuals and their families, which will be illustrated through anti-oppressive practice (AOP). By applying an anti-oppressive model of practice to the above definitions, the authors not only deconstruct disability paradigms but illustrate how AOP offers a framework for social workers to engage with people with disabilities at the individual, familial and community levels of practice, promoting an emancipatory focus in working with people with disabilities. An anti- social- oppression social work model of disability connects the day-to-day hardships of people with disabilities to the direct consequence of oppression in the form of ableism. AOP theory finds many of its basic concepts within social-oppression theory and the social model of disability. It is often the case that practitioners, including social workers and psychologists, define people with disabilities’ as having or being a problem with the focus placed upon adjustment and coping. A case example will be used to illustrate how an AOP paradigm offers social work a more comprehensive and critical analysis and practice model for social work practice with and for people with disabilities than the traditional medical model, rehabilitative and social model approaches.

Keywords: anti-oppressive practice, disability, people with disabilities, social model of disability

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Authors: Dhurgham Al-Karawi, Nisreen Polus, Shakir Al-Zaidi, Sabah Jassim

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The management of COVID-19 patients based on chest imaging is emerging as an essential tool for evaluating the spread of the pandemic which has gripped the global community. It has already been used to monitor the situation of COVID-19 patients who have issues in respiratory status. There has been increase to use chest imaging for medical triage of patients who are showing moderate-severe clinical COVID-19 features, this is due to the fast dispersal of the pandemic to all continents and communities. This article demonstrates the development of machine learning techniques for the test of COVID-19 patients using Chest X-Ray (CXR) images in nearly real-time, to distinguish the COVID-19 infection with a significantly high level of accuracy. The testing performance has covered a combination of different datasets of CXR images of positive COVID-19 patients, patients with viral and bacterial infections, also, people with a clear chest. The proposed AI scheme successfully distinguishes CXR scans of COVID-19 infected patients from CXR scans of viral and bacterial based pneumonia as well as normal cases with an average accuracy of 94.43%, sensitivity 95%, and specificity 93.86%. Predicted decisions would be supported by visual evidence to help clinicians speed up the initial assessment process of new suspected cases, especially in a resource-constrained environment.

Keywords: COVID-19, chest x-ray scan, artificial intelligence, texture analysis, local binary pattern transform, Gabor filter

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Authors: Sonia Arradaza-Pajaron

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English as a second language is widely spoken in the Philippines. In fact, it is used as a medium of instruction in school. However, Filipino students, in general, are still not proficient in the use of the language. Since it plays a very crucial role in the learning and comprehension of some subjects in the school where important key concepts and in English, it is imperative to look into other factors that may affect such concern. This study may post an answer to the said concern because it aimed to investigate the association between a psychological construct, known as emotional intelligence, and the English language performance of the 55 senior high school students. The study utilized a descriptive correlational method to determine the significant relationship of variables with preliminary data, like GPA in English subject as baseline information of their performance. Results revealed that the respondents had an average GPA in the English subject; however, improving from their first-year high school level to the fourth year. Their English performance resulted to an above average level with a notable higher performance in the speaking test than in the written. Further, a strong correlation between English performance and emotional intelligence was manifested. Based on the findings, it can be concluded that students with higher emotional intelligence their English language performance is expected to be the same. It can be said further that when students’ emotional intelligence (EI components) is facilitated well through various classroom activities, a better English performance would just be spontaneous among them.

Keywords: English language performance, emotional intelligence, EI components, emotional literacy, emotional quotient competence, emotional quotient outcomes, values and beliefs

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Authors: Jeremy Schultz, Kelly Bricker

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Ecotourism has proven itself to be a forerunner in the advancement of environmental conservation all the while supporting cultural tradition, uniqueness, and pride among indigenous communities. Successful private-community partnerships associated with ecotourism operations are vital to the overall prosperity of both the businesses and the local communities. Such accomplishments can be seen through numerous livelihood goals including income, food security, health, reduced vulnerability, governance, and empowerment. Private-community partnerships also support global initiatives such as the sustainable development goals and sustainable development frameworks including those proposed by the United Nations World Tourism Organization (WTO). Understanding such partnerships assists not only large organizations such as the WTO, but it also benefits smaller ecotourism operators and entrepreneurs who are trying to achieve their sustainable tourism development goals. This study examined the partnership between an ecotourism company (Rivers Fiji) and two rural villages located in Fiji’s Upper Navua Conservation Area. Focus groups were conducted in each village. Observation journals were also used to record conversations outside of the focus groups. Data were thematically organized and analyzed to offer researcher interpretations and understandings. This research supported the notion that respectful and emboldening partnerships between communities and private enterprise are vital to the composition of successful ecotourism operations that support sustainable development protocol. Understanding these partnerships can assist in shaping future ecotourism development and re-molding existing businesses. This study has offered an example of a thriving partnership through community input and critical researcher analysis. Research has identified six contributing factors to successful ecotourism partnerships, and this study provides additional support to that framework.

Keywords: community partnerships, conservation areas, ecotourism, Fiji, sustainability

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Authors: Veronica Kah Jo Wong, Yoke Mui Lim, Nurul Sakina Mokhtar Azizi

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The impact on the construction industry in Malaysia is unprecedented, as the government implemented a lockdown to restrict human movement in an effort to stop COVID-19 from spreading. Quantity surveyor (QS), as one of the key construction professionals, found that the working practices and environments for quantity surveyors today have changed due to the current pandemic. The QS profession must deal not only with changes in project issues but also with a different working environment in which most people are required to work from home and follow the standard operating procedures. Therefore, QS should be flexible, agile, and have the capability to adapt to the current working practices by strengthening their competencies. Adapting to the current and recovering environment of COVID-19 may result in the emergence of a new competence such as skill and knowledge for QS in order to maintain the quality of performance in the delivery of their professional services. Thus, this paper's objective is to investigate the changes in knowledge and skills in quantity surveyors. The data will be collected through interviews with registered professional QS to gain better insights that are specific in this industry, and the findings will be verified using the Delphi method. It is hoped that new knowledge and skill will be found from the study and will not only contribute to the betterment of the professional QS but also in guiding higher learning institutions to incorporate the new competencies into their curriculum.

Keywords: competency, COVID-19 pandemic, Malaysia, quantity surveying

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Authors: Kuixi Du, Thomas J. Lipscomb

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The proficiency in Mathematics skills is fundamental to success in the STEM disciplines. In the US, beginning college students who are placed in remedial/developmental Mathematics courses frequently struggle to achieve academic success. Therefore, Mathematics remediation in college has become an important concern, and providing Mathematics remediation is a prevalent way to help the students who may not be fully prepared for college-level courses. Programs vary, however, and the effectiveness of a particular remedial Mathematics program must be empirically demonstrated. The purpose of this study was to apply the sharp regression discontinuity (RD) technique to determine the effectiveness of the Jack Leaps Summer (JLS) Mathematic remediation program in supporting improved Mathematics learning outcomes among newly admitted Mathematics students in the South Dakota State University. The researchers studied the newly admitted Fall 2019 cohort of Mathematics majors (n=423). The results indicated that students whose pretest score was lower than the cut-off point and who were assigned to the JLS program experienced significantly higher scores on the post-test (Math 101 final score). Based on these results, there is evidence that the JLS program is effective in meeting its primary objective.

Keywords: causal inference, mathematisc remedial program evaluation, quasi-experimental research design, regression discontinuity design, cohort studies

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Authors: Zahra Hamedani

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Many wonderful technological developments in recent years has opened up the possibility of using intelligent buildings for a number of important applications, ranging from minimizing resource usage as well as increasing building efficiency to maximizing comfort, adaption to inhabitants and responsiveness to environmental changes. The concept of an intelligent building refers to the highly embedded, interactive environment within which by exploiting the use of artificial intelligence provides the ability to know its configuration, anticipate the optimum dynamic response to prevailing environmental stimuli, and actuate the appropriate physical reaction to provide comfort and efficiency. This paper contains a general identification of the intelligence paradigm and its impacts on the architecture arena, that with examining the performance of artificial intelligence, a mechanism to analyze and finally for decision-making to control the environment will be described. This mechanism would be a hierarchy of the rational agents which includes decision-making, information, communication and physical layers. This multi-agent system relies upon machine learning techniques for automated discovery, prediction and decision-making. Then, the application of this mechanism regarding adaptation and responsiveness of intelligent building will be provided in two scales of environmental and user. Finally, we review the identifications of sustainability and evaluate the potentials of intelligent building systems in the creation of sustainable architecture and environment.

Keywords: artificial intelligence, intelligent building, responsiveness, adaption, sustainability

Procedia PDF Downloads 410