Search results for: Finite element Method (FEM)

Authors: Diane M. Bender

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In architecture and design education, students learn and understand their discipline through lecture courses and within studios. A studio is where the instructor works closely with students to help them understand design by doing design work. The final jury is the culmination of the studio learning experience. It’s value and significance are rarely questioned. Students present their work before their peers, instructors, and invited reviewers, known as jurors. These jurors are recognized experts who add a breadth of feedback to students mostly in the form of a verbal critique of the work. Since the design review or jury has been a common element of studio education for centuries, jurors themselves have been instructed in this format. Therefore, they understand its value from both a student and a juror perspective. To better understand how these reviewers see the value of a studio review, a survey was distributed to reviewers at a multi-disciplinary design school within the United States. Five design disciplines were involved in this case study: architecture, graphic design, industrial design, interior design, and landscape architecture. Respondents (n=108) provided written comments about their perceived value of the studio review system. The average respondent was male (64%), between 40-49 years of age, and has attained a master’s degree. Qualitative analysis with thematic coding revealed several themes. Reviewers view the final jury as important because it provides a variety of perspectives from unbiased external practitioners and prepares students for similar presentation challenges they will experience in professional practice. They also see it as a way to validate the assessment and evaluation of students by faculty. In addition, they see a personal benefit for themselves and their firm – the ability to network with fellow jurors, professors, and students (i.e., future colleagues). Respondents also provided additional feedback about the jury system and studio education in general. Typical responses included a desire for earlier engagement with students; a better explanation from the instructor about the project parameters, rubrics/grading, and guidelines for juror involvement; a way to balance giving encouraging feedback versus overly critical comments; and providing training for jurors prior to reviews. While this study focused on the studio review, the findings are equally applicable to other disciplines. Suggestions will be provided on how to improve the preparation of guests in the learning process and how their interaction can positively influence student engagement.

Keywords: assessment, design, jury, studio

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Authors: Khadijat Olabisi Abdulwahab, Mohammad Azad Malik, Paul O'Brien, Grigore Timco, Floriana Tuna

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The synthesis of spinel ferrite nanoparticles with a narrow size distribution is very crucial in their numerous applications including information storage, hyperthermia treatment, drug delivery, contrast agent in magnetic resonance imaging, catalysis, sensors, and environmental remediation. Ferrites have the general formula MFe₂O₄ (M = Fe, Co, Mn, Ni, Zn e.t.c) and possess remarkable electrical and magnetic properties which depend on the cations, method of preparation, size and their site occupancies. To the best of our knowledge, there are no reports on the use of a single source precursor to synthesise quaternary ferrite nanoparticles. Here in, we demonstrated the use of trimetallic iron pivalate cluster [CrCoFeO(O₂CᵗBu)₆(HO₂CᵗBu)₃] as a single source precursor to synthesise monodisperse cobalt chromium ferrite (FeCoCrO₄) nanoparticles by the hot injection thermolysis method. The precursor was thermolysed in oleylamine, oleic acid, with diphenyl ether as solvent at 260 °C. The effect of reaction time on the stoichiometry, phases or morphology of the nanoparticles was studied. The p-XRD patterns of the nanoparticles obtained after one hour was pure phase of cubic iron cobalt chromium ferrite (FeCoCrO₄). TEM showed that a more monodispersed spherical ferrite nanoparticles were obtained after one hour. Magnetic measurements revealed that the ferrite particles are superparamagnetic at room temperature. The nanoparticles were characterised by Powder X-ray Diffraction (p-XRD), Transmission Electron Microscopy (TEM), Energy Dispersive Spectroscopy (EDS) and Super Conducting Quantum Interference Device (SQUID).

Keywords: cobalt chromium ferrite, colloidal, hot injection thermolysis, monodisperse, reaction time, single source precursor, quaternary ferrite nanoparticles

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Authors: Nursigit Bintoro, Abadi Barus, Catur Setyo Dedi Pamungkas

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Indonesia is an agrarian country have almost population work as farmers. One of the popular agriculture commodity in Indonesia is paddy and corn. Production of paddy and corn are increased, but not balanced to the development of appropriate technology to farmers. Methods of drying applied with farmers still using sunshine. Drying by this method has some drawbacks, such as differences moisture content of corn grains, time used to dry around 3 days, and less quality of the products obtained. Beside it, the method of drying by using sunshine can’t do when the rainy season arrives. On this season the product obtained has less quality. One solution to the above problems is to create a dryer with simple technology. That technology is made silo dryer from webbing bamboo and wood. This technology is applicable to be applied to farmers' groups as well as the creation technology is quite cheap. The experiment material used in this research will be obtained from the corn grains. The equipment used are woven bamboo with a height of 3 meters and have capacity of up to 900 kgs as a silo, gas, burner, blower, bucket elevators, thermocouple, Arduino microcontroller 2560. This tools automatically records all the data of temperature and relative humidity. During on drying, each 30 minutes take 9 sample for measuring moisture content with moisture meter. By using this technology, farmers can save time, energy, and cost to the drying their agriculture product. In addition, by using this technology have good quality moisture content of grains and have a longer shelf life because the temperature when the heating process is controlled. Therefore, this technology is applicable to be applied to the public because the materials used to make the dryer easier to find, cheaper, and manufacture of the dryer made simple with good quality.

Keywords: grains, dryer, moisture content, appropriate technology

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Authors: Basanti Ekka, Talis Juhna

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Dairy industrial effluents originated by the typical processing activities are composed of various organic and inorganic constituents, and these include proteins, fats, inorganic salts, antibiotics, detergents, sanitizers, pathogenic viruses, bacteria, etc. These contaminants are harmful to not only human beings but also aquatic flora and fauna. Because consisting of large classes of contaminants, the specific targeted removal methods available in the literature are not viable solutions on the industrial scale. Therefore, in this on-going research, a series of coagulation, electrochemical, and catalytic methods will be employed. The bulk coagulation and electrochemical methods can wash off most of the contaminants, but some of the harmful chemicals may slip in; therefore, specific catalysts designed and synthesized will be employed for the removal of targeted chemicals. In the context of Latvian dairy industries, presently, work is under progress on the characterization of dairy effluents by total organic carbon (TOC), Inductively Coupled Plasma Mass Spectrometry (ICP-MS)/ Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES), High-Performance Liquid Chromatography (HPLC), Gas Chromatography-Mass Spectrometry (GC-MS), and Mass Spectrometry. After careful evaluation of the dairy effluents, a cost-effective natural coagulant will be employed prior to advanced electrochemical technology such as electrocoagulation and electro-oxidation as a secondary treatment process. Finally, graphene oxide (GO) based hybrid materials will be used for post-treatment of dairy wastewater as graphene oxide has been widely applied in various fields such as environmental remediation and energy production due to the presence of various oxygen-containing groups. Modified GO will be used as a catalyst for the removal of remaining contaminants after the electrochemical process.

Keywords: catalysis, dairy wastewater, electrochemical method, graphene oxide

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Authors: Chahrazed Zouaoui

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In recent years, the volume of geospatial information is increasing due to the evolution of communication technologies and information, this information is presented often by geographic information systems (GIS) and stored on of spatial databases (BDS). The classical data mining revealed a weakness in knowledge extraction at these enormous amounts of data due to the particularity of these spatial entities, which are characterized by the interdependence between them (1st law of geography). This gave rise to spatial data mining. Spatial data mining is a process of analyzing geographic data, which allows the extraction of knowledge and spatial relationships from geospatial data, including methods of this process we distinguish the monothematic and thematic, geo- Clustering is one of the main tasks of spatial data mining, which is registered in the part of the monothematic method. It includes geo-spatial entities similar in the same class and it affects more dissimilar to the different classes. In other words, maximize intra-class similarity and minimize inter similarity classes. Taking account of the particularity of geo-spatial data. Two approaches to geo-clustering exist, the dynamic processing of data involves applying algorithms designed for the direct treatment of spatial data, and the approach based on the spatial data pre-processing, which consists of applying clustering algorithms classic pre-processed data (by integration of spatial relationships). This approach (based on pre-treatment) is quite complex in different cases, so the search for approximate solutions involves the use of approximation algorithms, including the algorithms we are interested in dedicated approaches (clustering methods for partitioning and methods for density) and approaching bees (biomimetic approach), our study is proposed to design very significant to this problem, using different algorithms for automatically detecting geo-spatial neighborhood in order to implement the method of geo- clustering by pre-treatment, and the application of the bees algorithm to this problem for the first time in the field of geo-spatial.

Keywords: mining, GIS, geo-clustering, neighborhood

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Authors: Assamen Ayalew Ejigu, Liang-Chiun Chao

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In recent semiconductor and nanotechnology, quality material synthesis, proper characterizations, and productions are the big challenges. As cuprous oxide (Cu2O) is a promising semiconductor material for photovoltaic (PV) and other optoelectronic applications, this study was aimed at to grow and characterize high quality Cu2O nanorods for the improvement of the efficiencies of thin film solar cells and other potential applications. In this study, well-structured cuprous oxide (Cu2O) nanorods were successfully fabricated using IBSD method in which the Cu2O samples were grown on silicon substrates with a substrate temperature of 400°C in an IBSD chamber of pressure of 4.5 x 10-5 torr using copper as a target material. Argon, and oxygen gases were used as a sputter and reactive gases, respectively. The characterization of the Cu2O nanorods (NRs) were done in comparison with Cu2O thin film (TF) deposited with the same method but with different Ar:O2 flow rates. With Ar:O2 ratio of 9:1 single phase pure polycrystalline Cu2O NRs with diameter of ~500 nm and length of ~4.5 µm were grow. Increasing the oxygen flow rates, pure single phase polycrystalline Cu2O thin film (TF) was found at Ar:O2 ratio of 6:1. The field emission electron microscope (FE-SEM) measurements showed that both samples have smooth morphologies. X-ray diffraction and Rama scattering measurements reveals the presence of single phase Cu2O in both samples. The differences in Raman scattering and photoluminescence (PL) bands of the two samples were also investigated and the results showed us there are differences in intensities, in number of bands and in band positions. Raman characterization shows that the Cu2O NRs sample has pronounced Raman band intensities, higher numbers of Raman bands than the Cu2O TF which has only one second overtone Raman signal at 2 (217 cm-1). The temperature dependent photoluminescence (PL) spectra measurements, showed that the defect luminescent band centered at 720 nm (1.72 eV) is the dominant one for the Cu2O NRs and the 640 nm (1.937 eV) band was the only PL band observed from the Cu2O TF. The difference in optical and structural properties of the samples comes from the oxygen flow rate change in the process window of the samples deposition. This gave us a roadmap for further investigation of the electrical and other optical properties for the tunable fabrication of the Cu2O nano/micro structured sample for the improvement of the efficiencies of thin film solar cells in addition to other potential applications. Finally, the novel morphologies, excellent structural and optical properties seen exhibits the grown Cu2O NRs sample has enough quality to be used in further research of the nano/micro structured semiconductor materials.

Keywords: defect levels, nanorods, photoluminescence, Raman modes

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Authors: Kunihisa Kakumoto

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“Purpose”: Global environmental issues are now being raised in a global dimension. By predicting sprawl phenomena beyond the limits of nature with algorithms, we can expect to protect our social life within the limits of nature. It turns out that the sustainable state of the planet now consists in maintaining a balance between the capabilities of nature and the possibilities of our social life. The amount of water on earth is finite. Sustainability is therefore highly dependent on water capacity. A certain amount of water is stored in the forest by planting and green space, and the amount of water can be considered in relation to the green space. CO2 is also absorbed by green plants. "Possible measurements and methods": The concept of the solar community has been introduced in technical papers on the occasion of many international conferences. The solar community concept is based on data collected from one solar model house. This algorithmic study simulates the amount of water stored by lush green vegetation. In addition, we calculated and compared the amount of CO2 emissions from the Taiyo Community and the amount of CO2 reduction from greening. Based on the trial calculation results of these solar communities, we are simulating the sustainable state of the earth as an algorithm trial calculation result. We believe that we should also consider the composition of this solar community group using digital technology as control technology. "Conclusion": We consider the solar community as a prototype for finding sustainable conditions for the planet. The role of water is very important as the supply capacity of water is limited. However, the circulation of social life is not constructed according to the mechanism of nature. This simulation trial calculation is explained using the total water supply volume as an example. According to this process, algorithmic calculations consider the total capacity of the water supply and the population and habitable numbers of the area. Green vegetated land is very important to keep enough water. Green vegetation is also very important to maintain CO2 balance. A simulation trial calculation is possible from the relationship between the CO2 emissions of the solar community and the amount of CO2 reduction due to greening. In order to find this total balance and sustainable conditions, the algorithmic simulation calculation takes into account lush vegetation and total water supply. Research to find sustainable conditions is done by simulating an algorithmic model of the solar community as a prototype. In this one prototype example, it's balanced. The activities of our social life must take place within the permissive limits of natural mechanisms. Of course, we aim for a more ideal balance by utilizing auxiliary digital control technology such as AI.

Keywords: solar community, sustainability, prototype, algorithmic simulation

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Authors: Bhavani Veasuvalingam

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Case-based learning (CBL) is a popular instructional method aimed to bridge theory to clinical practice. This study aims to explore CBL mixed modality curriculum in influencing students’ learning styles and strategies that support learning. An explanatory sequential mixed method study was employed with initial phase, 44-itemed Felderman’s Index of Learning Style (ILS) questionnaire employed across year one medical students (n=142) using convenience sampling to describe the preferred learning styles. The qualitative phase utilised three focus group discussions (FGD) to explore in depth on the multimodal learning style exhibited by the students. Most students preferred combination of learning stylesthat is reflective, sensing, visual and sequential i.e.: RSVISeq style (24.64%) from the ILS analysis. The frequency of learning preference from processing to understanding were well balanced, with sequential-global domain (66.2%); sensing-intuitive (59.86%), active- reflective (57%), and visual-verbal (51.41%). The qualitative data reported three major themes, namely Theme 1: CBL mixed modalities navigates learners’ learning style; Theme 2: Multimodal learners active learning strategies supports learning. Theme 3: CBL modalities facilitating theory into clinical knowledge. Both quantitative and qualitative study strongly reports the multimodal learning style of the year one medical students. Medical students utilise multimodal learning styles to attain the clinical knowledge when learning with CBL mixed modalities. Educators’ awareness of the multimodal learning style is crucial in delivering the CBL mixed modalities effectively, considering strategic pedagogical support students to engage and learn CBL in bridging the theoretical knowledge into clinical practice.

Keywords: case-based learning, learnign style, medical students, learning

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Authors: Katya E. Manalastas

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This thesis is a dialogue with Freud about vulnerability and any forms of transience we encounter in life. This study argues that Freud’s Ethics of Finitude, which is framed within the psychoanalytic context, is a critical theory about how human beings fail to become what they are because of their attachment to their illusions—to their visions of perfection and immortality. Freud’s Ethics of Finitude positions itself between our detachment to ideals and recognition of our own death through our loved one. His texts portray the predicament of the finite individual who suffers from feelings of guilt and anxiety because of his failure to live up to the demands of his idealistic civilized society. The civilized society has overestimated men’s susceptibility to culture. It imposes excessive sublimation, conformity to rigid moral ideals, and instinctive repression to manage human aggression. However, by doing this, civilization becomes a main source of men’s suffering. The lack of instinctive freedom will result in a community of tamed but unhappy people. Civilization has also constructed theories and measures to rule out death and pain from the realities of life. Therefore, a man lives his life repressing his instincts and ignorant of his own mortality. For Freud, war and neurosis are just few of the consequences of a civilization that imprisons the individual from cultural hypocrisy instead of giving more play to truthfulness. The occurrence of Great War destroyed our pride in the attainments of civilization and let loose the hostile impulses within us which we thought had been totally eradicated by means of instinctive repression and sublimation. War destroyed most of the things that we had loved and showed us the impermanence of all the things that we had deemed perfect and everlasting. This chaotic event also revealed the damaging impact of our attachment to past values that no longer bind us; our futile attempts to escape suffering; and our refusal to confront the painfulness of loss and mourning. With this given backdrop, this study launches Freud’s Ethics of Finitude—which culminates not in the submission of an individual to the unquestioned authority nor in the blind optimism and love for illusory happiness but in the pedagogy of mourning which brings forth the authentic education of man towards the truth about himself. His Ethics of Finitude is a form of labor in and through which the individual steps out of the realm of illusions and ideals that hinder him to confront his imperfections and accept the difficulties of existence. Through his analysis of the Great War, Freud seeks to awaken in us our ability to evaluate the way we see ourselves and to live our lives with death in mind. His Ethics of Finitude leads us to the fulfillment of our first duty as a living being, which is to endure life. We can only endure life if we are prepared to die and let go.

Keywords: critical theory, ethics of finitude, psychoanalysis, Sigmund Freud

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Authors: Christina Klippel, Lucia Pezzi, Silvio Neto, Rafael Bertani, Priscila Mendes, Flavio Machado, Aline Szeliga, Maria Cosendey, Adilson Mariz, Raquel Santos, Lys Bendett, Pedro Velasco, Thalita Rolleigh, Bruna Bellote, Daria Coelho, Bruna Martins, Julia Almeida, Juliana Cerqueira

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This project presents a framework for teaching intracranial pressure monitoring (ICP) concepts using a low-cost experimental model in a neurointensive care education program. Data concerning ICP monitoring contribute to the patient's clinical assessment and may dictate the course of action of a health team (nursing, medical staff) and influence decisions to determine the appropriate intervention. This study aims to present a safe method for teaching ICP monitoring to medical students in a Simulation Center. Methodology: Medical school teachers, along with students from the 4th year, built an experimental model for teaching ICP measurement. The model consists of a mannequin's head with a plastic bag inside simulating the cerebral ventricle and an inserted ventricular catheter connected to the ICP monitoring system. The bag simulating the ventricle can also be changed for others containing bloody or infected simulated cerebrospinal fluid. On the mannequin's ear, there is a blue point indicating the right place to set the "zero point" for accurate pressure reading. The educational program includes four steps: 1st - Students receive a script on ICP measurement for reading before training; 2nd - Students watch a video about the subject created in the Simulation Center demonstrating each step of the ICP monitoring and the proper care, such as: correct positioning of the patient, anatomical structures to establish the zero point for ICP measurement and a secure range of ICP; 3rd - Students train the procedure in the model. Teachers help students during training; 4th - Student assessment based on a checklist form. Feedback and correction of wrong actions. Results: Students expressed interest in learning ICP monitoring. Tests concerning the hit rate are still being performed. ICP's final results and video will be shown at the event. Conclusion: The study of intracranial pressure measurement based on an experimental model consists of an effective and controlled method of learning and research, more appropriate for teaching neurointensive care practices. Assessment based on a checklist form helps teachers keep track of student learning progress. This project offers medical students a safe method to develop intensive neurological monitoring skills for clinical assessment of patients with neurological disorders.

Keywords: neurology, intracranial pressure, medical education, simulation

Procedia PDF Downloads 151

Authors: Fariba Jafari, Samaneh Heydarian

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Al2(HPO4)3 was easily prepared and used as a solid acid in acetalization of carbonyl compounds at room temperature and under solvent-free conditions. The protection was done in short reaction times and in good to high isolated yields. The cheapness and availability of this reagent with easy procedure and work-up make this method attractive for the organic synthesis.

Keywords: acetalization, acid catalysis, carbonylcompounds, green condition, protection

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Authors: Setareh Yousife

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Introduction: Studies suggest that Extramarital Infidelity (EMI) variants, such as sexual and emotional infidelities are increasing in marriage relationships. To our knowledge, less is known about what therapies and mental-hygiene factors can prevent more effective this behavior and address it. Spiritual and cognitive-behavioural health have proven to reduce marital conflict, Increase marital satisfaction and commitment. Objective: This study aims to discuss the effectiveness of spiritual counseling combined with Cognitive-behavioural techniques in addressing Extramarital Infidelity. Method: Descriptive, analytical, and intervention articles indexed in SID, Noormags, Scopus, Iranmedex, Web of Science and PubMed databases, and Google Scholar were searched. We focused on Studies in which Women with extramarital relationships, including heterosexual married couples-only studies and spirituality/religion and CBT as coping techniques used as EMI therapy. Finally, the full text of all eligible articles was prepared and discussed in this review. Results: 25 publications were identified, and their textual analysis facilitated through four thematic approaches: The nature of EMI in Women, the meaning of spirituality in the context of mental health and human behavior as well as psychotherapy; Spirituality integrated into Cognitive-Behavioral approach, The role of Spirituality as a deterrent to EMI. Conclusions: The integration of the findings discussed herein suggests that the application of cognitive and behavioral skills in addressing these kinds of destructive family-based relationships is inevitable. As treatments based on religion/spirituality or cognition/behavior do not seem adequately effective in dealing with EMI, the combination of these approaches may lead to higher efficacy in fewer sessions and a shorter time.

Keywords: spirituality, religion, cognitive behavioral therapy, extramarital relation, infidelity

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Authors: Shang-Yu Chiang, Yu-Shan Tsai, Shih-Hsien Sung, Chung-Ming Lo

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Mitral regurgitation (MR) is a heart disorder which the mitral valve does not close properly when the heart pumps out blood. MR is the most common form of valvular heart disease in the adult population. The diagnostic echocardiographic finding of MR is straightforward due to the well-known clinical evidence. In the determination of MR severity, quantification of sonographic findings would be useful for clinical decision making. Clinically, the vena contracta is a standard for MR evaluation. Vena contracta is the point in a blood stream where the diameter of the stream is the least, and the velocity is the maximum. The quantification of vena contracta, i.e. the vena contracta width (VCW) at mitral valve, can be a numeric measurement for severity assessment. However, manually delineating the VCW may not accurate enough. The result highly depends on the operator experience. Therefore, this study proposed an automatic method to quantify VCW to evaluate MR severity. Based on color Doppler ultrasound, VCW can be observed from the blood flows to the probe as the appearance of red or yellow area. The corresponding brightness represents the value of the flow rate. In the experiment, colors were firstly transformed into HSV (hue, saturation and value) to be closely align with the way human vision perceives red and yellow. Using ellipse to fit the high flow rate area in left atrium, the angle between the mitral valve and the ultrasound probe was calculated to get the vertical shortest diameter as the VCW. Taking the manual measurement as the standard, the method achieved only 0.02 (0.38 vs. 0.36) to 0.03 (0.42 vs. 0.45) cm differences. The result showed that the proposed automatic VCW extraction can be efficient and accurate for clinical use. The process also has the potential to reduce intra- or inter-observer variability at measuring subtle distances.

Keywords: mitral regurgitation, vena contracta, color doppler, image processing

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Authors: Choukri Lekbir, Mira Mokhtari

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Hydrogen-Materials interaction and mechanisms can be modeled at nano scale by quantum methods. In this work, the effect of hydrogen on the electronic properties of a cluster material model «nickel» has been studied by using of density functional theoretical (DFT) method. Two types of clusters are optimized: Nickel and hydrogen-nickel system. In the case of nickel clusters (n = 1-6) without presence of hydrogen, three types of electronic structures (neutral, cationic and anionic), have been optimized according to three basis sets calculations (B3LYP/LANL2DZ, PW91PW91/DGDZVP2, PBE/DGDZVP2). The comparison of binding energies and bond lengths of the three structures of nickel clusters (neutral, cationic and anionic) obtained by those basis sets, shows that the results of neutral and anionic nickel clusters are in good agreement with the experimental results. In the case of neutral and anionic nickel clusters, comparing energies and bond lengths obtained by the three bases, shows that the basis set PBE/DGDZVP2 is most suitable to experimental results. In the case of anionic nickel clusters (n = 1-6) with presence of hydrogen, the optimization of the hydrogen-nickel (anionic) structures by using of the basis set PBE/DGDZVP2, shows that the binding energies and bond lengths increase compared to those obtained in the case of anionic nickel clusters without the presence of hydrogen, that reveals the armor effect exerted by hydrogen on the electronic structure of nickel, which due to the storing of hydrogen energy within nickel clusters structures. The comparison between the bond lengths for both clusters shows the expansion effect of clusters geometry which due to hydrogen presence.

Keywords: binding energies, bond lengths, density functional theoretical, geometry optimization, hydrogen energy, nickel cluster

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Authors: Daira Radouane, Naim Boudmagh, Hamada Adel

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The but of this handling is to use the technique of the shearing with a mechanism lapping machine of image: a prism of Wollaston. We want to characterize this prism in order to be able to employ it later on in an analysis by shearing. A prism of Wollaston is a prism produced in a birefringent material i.e. having two indexes of refraction. This prism is cleaved so as to present the directions associated with these indices in its face with entry. It should be noted that these directions are perpendicular between them.

Keywords: non destructive control, aluminium, interferometry, treatment of image

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Authors: Sweeti, Anoop Kant Godiyal, Neha Singh, Sneh Anand, B. K. Panigrahi, Jayasree Santhosh

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This work is about developing a tool for visualization and segmentation of Electroencephalograph (EEG) signals based on frequency domain features. Change in the frequency domain characteristics are correlated with change in mental state of the subject under study. Proposed algorithm provides a way to represent the change in the mental states using the different frequency band powers in form of segmented EEG signal. Many segmentation algorithms have been suggested in literature having application in brain computer interface, epilepsy and cognition studies that have been used for data classification. But the proposed method focusses mainly on the better presentation of signal and that’s why it could be a good utilization tool for clinician. Algorithm performs the basic filtering using band pass and notch filters in the range of 0.1-45 Hz. Advanced filtering is then performed by principal component analysis and wavelet transform based de-noising method. Frequency domain features are used for segmentation; considering the fact that the spectrum power of different frequency bands describes the mental state of the subject. Two sliding windows are further used for segmentation; one provides the time scale and other assigns the segmentation rule. The segmented data is displayed second by second successively with different color codes. Segment’s length can be selected as per need of the objective. Proposed algorithm has been tested on the EEG data set obtained from University of California in San Diego’s online data repository. Proposed tool gives a better visualization of the signal in form of segmented epochs of desired length representing the power spectrum variation in data. The algorithm is designed in such a way that it takes the data points with respect to the sampling frequency for each time frame and so it can be improved to use in real time visualization with desired epoch length.

Keywords: de-noising, multi-channel data, PCA, power spectra, segmentation

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Authors: Iman Shabanzadeh

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Over the last three decades, the main demands of the Iranian workforce have been focused on three areas: "The right to a decent wage", "The right to organize" and "The right to job security". In order to investigate and analyze this situation, the present study focuses on the component of job security. The purpose of the study is to figure out what mechanisms in Iran's Labor Law have led to the destabilization and undermining of workers' job security. The research method is descriptive-analytical. To collect information, library and document sources in the field of laws related to labor rights in Iran and, semi-structured interviews with experts have been used. In the data analysis stage, the qualitative content analysis method was also used. The trend analysis of the statistics related to the labor force situation in Iran in the last three decades shows that the employment structure has been facing an increase in the active population, but in the last decade, a large part of this population has been mainly active in the service sector, and contract-free enterprises, so a smaller share of this employment has insurance coverage and a larger share has underemployment. In this regard, the results of this study show that four contexts have been proposed as the main legal and executive mechanisms of labor instability in Iran, which are: 1) temporaryization of the labor force by providing different interpretations of labor law, 2) adjustment labor in the public sector and the emergence of manpower contracting companies, 3) the cessation of labor law protection of workers in small workshops and 4) the existence of numerous restrictions on the effective organization of workers. The theoretical conclusion of this article is that the main root of the challenges of the labor society and the destabilized workforce in Iran is the existence of structural inequalities in the field of labor security, whose traces can be seen in the legal provisions and executive regulations of this field.

Keywords: inequality, precariat, temporaryization, labor force, labor law

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Authors: Lanchi Xie, Zhihui Li, Zhigang Li, Guiqiang Wang, Lei Xu, Yuwen Yan

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Image-based facial features can be classified into category recognition features and individual recognition features. Current automated face recognition systems extract a specific feature vector of different dimensions from a facial image according to their pre-trained neural network. However, to improve the efficiency of parameter calculation, an algorithm generally reduces the image details by pooling. The operation will overlook the details concerned much by forensic experts. In our experiment, we adopted a variety of face recognition algorithms based on deep learning, compared a large number of naturally collected face images with the known data of the same person's frontal ID photos. Downscaling and manual handling were performed on the testing images. The results supported that the facial recognition algorithms based on deep learning detected structural and morphological information and rarely focused on specific markers such as stains and moles. Overall performance, distribution of genuine scores and impostor scores, and likelihood ratios were tested to evaluate the accuracy of biometric systems and forensic experts. Experiments showed that the biometric systems were skilled in distinguishing category features, and forensic experts were better at discovering the individual features of human faces. In the proposed approach, a fusion was performed at the score level. At the specified false accept rate, the framework achieved a lower false reject rate. This paper contributes to improving the interpretability of the objective method of facial comparison and provides a novel method for human-machine collaboration in this field.

Keywords: likelihood ratio, automated facial recognition, facial comparison, biometrics

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Authors: Gesti Prastiti, Maylina Adani, Yuyun darma A. N., M. Khilmi F., Yunita Wahyu Pratiwi

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Combination therapy may allow interaction on two drugs or more that can give adverse effects on patients. Simvastatin is a drug of antihyperlipidemia it can interact with drugs which work on cytochrome P450 CYP3A4 because it can interfere the performance of simvastatin. Flavonoid found in plants can inhibit the cytochrome P450 CYP3A4 if taken with simvastatin and can increase simvastatin levels in the body and increases the potential side effects of simvastatin such as myopati and rhabdomyolysis. Green tea leaves and mint are herbal medicine which has the effect of antihiperlipidemia. This study aims to determine the potential interaction of simvastatin with herbal drinks (green tea leaves and mint). This research method are experimental post-test only control design. Test subjects were divided into 5 groups: normal group, negative control group, simvastatin group, a combination of green tea group and the combination group mint leaves. The study was conducted over 32 days and total cholesterol levels were analyzed by enzymatic colorimetric test method. Results of this study is the obtainment of average value of total cholesterol in each group, the normal group (65.92 mg/dL), the negative control group the average total cholesterol test in the normal group was (69.86 mg/dL), simvastatin group (58.96 mg/dL), the combination of green tea group (58.96 mg/dL), and the combination of mint leaves (63.68 mg/dL). The conclusion is between simvastatin combination therapy with herbal drinks have the potential for pharmacodynamic interactions with a synergistic effect, antagonist, and a powerful additive, so the combination therapy are no more effective than a single administration of simvastatin therapy.

Keywords: hyperlipidemia, simvastatin, herbal drinks, green tea leaves, mint leaves, drug interactions

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Authors: Mohammed Panthakkal Abdul Muthalif, Shanmugasundaram Kanagaraj, Jumi Park, Hangyu Park, Youngson Choe

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The present study reports the incorporation of calcium ions into the CuS counter electrodes (CEs) in order to modify the photovoltaic performance of quantum dot-sensitized solar cells (QDSSCs). Metal ion-doped CuS thin film was prepared by the chemical bath deposition (CBD) method on FTO substrate and used directly as counter electrodes for TiO₂/CdS/CdSe/ZnS photoanodes based QDSSCs. For the Ca-doped CuS thin films, copper nitrate and thioacetamide were used as anionic and cationic precursors. Calcium nitrate tetrahydrate was used as doping material. The surface morphology of Ca-doped CuS CEs indicates that the fragments are uniformly distributed, and the structure is densely packed with high crystallinity. The changes observed in the diffraction patterns suggest that Ca dopant can introduce increased disorder into CuS material structure. EDX analysis was employed to determine the elemental identification, and the results confirmed the presence of Cu, S, and Ca on the FTO glass substrate. The photovoltaic current density – voltage characteristics of Ca-doped CuS CEs shows the specific improvements in open circuit voltage decay (Voc) and short-circuit current density (Jsc). Electrochemical impedance spectroscopy results display that Ca-doped CuS CEs have greater electrocatalytic activity and charge transport capacity than bare CuS. All the experimental results indicate that 20% Ca-doped CuS CE based QDSSCs exhibit high power conversion efficiency (η) of 4.92%, short circuit current density of 15.47 mA cm⁻², open circuit photovoltage of 0.611 V, and fill factor (FF) of 0.521 under illumination of one sun.

Keywords: Ca-doped CuS counter electrodes, surface morphology, chemical bath deposition method, electrocatalytic activity

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Authors: Pil Seong Park

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Homemade HPC clusters are widely used in many small labs, because they are easy to build and cost-effective. Even though incremental growth is an advantage of clusters, it results in heterogeneous systems anyhow. Instead of adding new nodes to the cluster, we can extend clusters to include some other Internet servers working independently on the same LAN, so that we can make use of their idle times, especially during the night. However extension across a firewall raises some security problems with NFS. In this paper, we propose a method to solve such a problem using SSH tunneling, and suggest a modified structure of the cluster that implements it.

Keywords: extension of HPC clusters, security, NFS, SSH tunneling

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Authors: Ahmed Ismail, Mustafa Baysal

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Although the energy source in the world is mainly based on fossil fuels today, there is a need for alternative energy generation systems, which are more economic and environmentally friendly, due to continuously increasing demand of electric energy and lacking power resources and networks. Distributed Energy Resources (DERs) such as fuel cells, wind and solar power have recently become widespread as alternative generation. In order to solve several problems that might be encountered when integrating DERs to power system, the microgrid concept has been proposed. A microgrid can operate both grid connected and island mode to benefit both utility and customers. For most distributed energy resources (DER) which are connected in parallel in LV-grid like micro-turbines, wind plants, fuel cells and PV cells electrical power is generated as a direct current (DC) and converted to an alternative currents (AC) by inverters. So the inverters are assumed to be primary components in a microgrid. There are many control techniques of parallel inverters to manage active and reactive sharing of the loads. Some of them are based on droop method. In literature, the studies are usually focused on improving the transient performance of inverters. In this study, the performance of two different controllers based on droop control method is compared for the inverters operated in parallel without any communication feedback. For this aim, a microgrid in which inverters are controlled by conventional droop controller and modified droop controller is designed. Modified controller is obtained by adding PID into conventional droop control. Active and reactive power sharing performance, voltage and frequency responses of those control methods are measured in several operational cases. Study cases have been simulated by MATLAB-SIMULINK.

Keywords: active and reactive power sharing, distributed generation, droop control, microgrid

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Authors: M. Gulam Kibria, Shourav Ahmed, Kais Zaman

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In system analysis, the information on the uncertain input variables cause uncertainty in the system responses. Different probabilistic approaches for uncertainty representation and propagation in such cases exist in the literature. Different uncertainty representation approaches result in different outputs. Some of the approaches might result in a better estimation of system response than the other approaches. The NASA Langley Multidisciplinary Uncertainty Quantification Challenge (MUQC) has posed challenges about uncertainty quantification. Subproblem A, the uncertainty characterization subproblem, of the challenge posed is addressed in this study. In this subproblem, the challenge is to gather knowledge about unknown model inputs which have inherent aleatory and epistemic uncertainties in them with responses (output) of the given computational model. We use two different methodologies to approach the problem. In the first methodology we use sampling-based uncertainty propagation with first order error analysis. In the other approach we place emphasis on the use of Percentile-Based Optimization (PBO). The NASA Langley MUQC’s subproblem A is developed in such a way that both aleatory and epistemic uncertainties need to be managed. The challenge problem classifies each uncertain parameter as belonging to one the following three types: (i) An aleatory uncertainty modeled as a random variable. It has a fixed functional form and known coefficients. This uncertainty cannot be reduced. (ii) An epistemic uncertainty modeled as a fixed but poorly known physical quantity that lies within a given interval. This uncertainty is reducible. (iii) A parameter might be aleatory but sufficient data might not be available to adequately model it as a single random variable. For example, the parameters of a normal variable, e.g., the mean and standard deviation, might not be precisely known but could be assumed to lie within some intervals. It results in a distributional p-box having the physical parameter with an aleatory uncertainty, but the parameters prescribing its mathematical model are subjected to epistemic uncertainties. Each of the parameters of the random variable is an unknown element of a known interval. This uncertainty is reducible. From the study, it is observed that due to practical limitations or computational expense, the sampling is not exhaustive in sampling-based methodology. That is why the sampling-based methodology has high probability of underestimating the output bounds. Therefore, an optimization-based strategy to convert uncertainty described by interval data into a probabilistic framework is necessary. This is achieved in this study by using PBO.

Keywords: aleatory uncertainty, epistemic uncertainty, first order error analysis, uncertainty quantification, percentile-based optimization

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Authors: M. Alsharqawi, T. Zayed, S. Abu Dabous

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To ensure safety and serviceability of bridge infrastructure, accurate condition assessment and rating methods are needed to provide basis for bridge Maintenance, Repair and Replacement (MRR) decisions. In North America, the common practices to assess condition of bridges are through visual inspection. These practices are limited to detect surface defects and external flaws. Further, the thresholds that define the severity of bridge deterioration are selected arbitrarily. The current research discusses the main deteriorations and defects identified during visual inspection and Non-Destructive Evaluation (NDE). NDE techniques are becoming popular in augmenting the visual examination during inspection to detect subsurface defects. Quality inspection data and accurate condition assessment and rating are the basis for determining appropriate MRR decisions. Thus, in this paper, a novel method for bridge condition assessment using the Quality Function Deployment (QFD) theory is utilized. The QFD model is designed to provide an integrated condition by evaluating both the surface and subsurface defects for concrete bridges. Moreover, an integrated condition rating index with four thresholds is developed based on the QFD condition assessment model and using K-means clustering technique. Twenty case studies are analyzed by applying the QFD model and implementing the developed rating index. The results from the analyzed case studies show that the proposed threshold model produces robust MRR recommendations consistent with decisions and recommendations made by bridge managers on these projects. The proposed method is expected to advance the state of the art of bridges condition assessment and rating.

Keywords: concrete bridge decks, condition assessment and rating, quality function deployment, k-means clustering technique

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Authors: Adeyinka Adeniran, Omowunmi Bakare, Esther Oluwole, Florence Chieme, Temitope Durojaiye, Modupe Akinyinka, Omobola Ojo, Babatunde Olujobi, Marcus Ilesanmi, Akintunde Ogunsakin

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Introduction: Globally, COVID-19 has greatly impacted the human race physically, socially, mentally, and economically. However, healthcare workers seemed to bear the greatest impact. The study, therefore, sought to assess the impact of COVID-19 on the primary healthcare workers in Ekiti, South-west Nigeria. Methods: The study was a cross-sectional descriptive study using a quantitative data collection method of 716 primary healthcare workers in Ekiti state. Respondents were selected using an online convenience sampling method via their social media platforms. Data was collected, collated, and analyzed using SPSS version 25 software and presented as frequency tables, mean and standard deviation. Bivariate and multivariate analyses were conducted using a t-test, and the level of statistical significance was set at p<0.05. Results: Less than half (47.1%) of respondents were between 41-50 age group and a mean age of 44.4+6.4SD. A majority (89.4%) were female, and almost all (96.2%) were married. More than (90%) had ever heard of Coronavirus, and (85.8%) had to spend more money on activities of daily living such as transportation (90.1%), groceries (80.6%), assisting relations (95.8%) and sanitary measures (disinfection) at home (95.0%). COVID-19 had a huge negative impact on about (89.7%) of healthcare workers, with a mean score of 22+4.8. Conclusion: COVID-19 negatively impacted the daily living and professional duties of primary healthcare workers, which reflected their psychological, physical, social, and economic well-being. Disease outbreaks are unlikely to disappear in the near future. Hence, global proactive interventions and homegrown measures should be adopted to protect healthcare workers and save lives.

Keywords: Covid-19, health workforce, primary health care, health systems, depression

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Authors: Gabrielle Peck, Ryan Hayes

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Polyurethane (PU) foam is typically sold as acoustic foam that is often used as sound insulation in settings such as night clubs and bars. As a construction product, PU is tested by being glued to the walls and ceiling of the ISO 9705 room corner test room. However, when heat is applied to PU foam, it melts and burns as a pool fire due to it being a thermoplastic. The current test layout is unable to accurately measure mass loss and doesn’t allow for the material to burn as a pool fire without seeping out of the test room floor. The lack of mass loss measurement means gas yields pertaining to smoke toxicity analysis can’t be calculated, which makes data comparisons from any other material or test method difficult. Additionally, the heat release measurements are not representative of the actual measurements taken as a lot of the material seeps through the floor (when a tray to catch the melted material is not used). This research aimed to modify the ISO 9705 test to provide the ability to measure mass loss to allow for better calculation of gas yields and understanding of decomposition. It also aimed to accurately measure smoke toxicity in both the doorway and duct and enable dilution factors to be calculated. Finally, the study aimed to examine if doubling the fuel loading would force under-ventilated flaming. The test layout was modified to be a combination of the SBI (single burning item) test set up inside oof the ISO 9705 test room. Polyurethane was tested in two different ways with the aim of altering the ventilation condition of the tests. Test one was conducted using 1 x SBI test rig aiming for well-ventilated flaming. Test two was conducted using 2 x SBI rigs (facing each other inside the test room) (doubling the fuel loading) aiming for under-ventilated flaming. The two different configurations used were successful in achieving both well-ventilated flaming and under-ventilated flaming, shown by the measured equivalence ratios (measured using a phi meter designed and created for these experiments). The findings show that doubling the fuel loading will successfully force under-ventilated flaming conditions to be achieved. This method can therefore be used when trying to replicate post-flashover conditions in future ISO 9705 room corner tests. The radiative heat generated by the two SBI rigs facing each other facilitated a much higher overall heat release resulting in a more severe fire. The method successfully allowed for accurate measurement of smoke toxicity produced from the PU foam in terms of simple gases such as oxygen depletion, CO and CO2. Overall, the proposed test modifications improve the ability to measure the smoke toxicity of materials in different fire conditions on a large-scale.

Keywords: flammability, ISO9705, large-scale testing, polyurethane, smoke toxicity

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Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

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Authors: Michael Lognoul

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In April 2021, the European Commission released its AI Act Proposal, which is the first policy proposal at the European Union level to target AI systems comprehensively, in a horizontal manner. This Proposal notably aims to achieve an ecosystem of trust in the European Union, based on the respect of fundamental rights, regarding AI. Among many other requirements, the AI Act Proposal aims to impose several generic transparency obligationson all AI systems to the benefit of natural persons facing those systems (e.g. information on the AI nature of systems, in case of an interaction with a human). The Proposal also provides for more stringent transparency obligations, specific to AI systems that qualify as high-risk, to the benefit of their users, notably on the characteristics, capabilities, and limitations of the AI systems they use. Against that background, this research firstly presents all such transparency requirements in turn, as well as related obligations, such asthe proposed obligations on record keeping. Secondly, it focuses on a legal analysis of their scope of application, of the content of the obligations, and on their practical implications. On the scope of transparency obligations tailored for high-risk AI systems, the research notably notes that it seems relatively narrow, given the proposed legal definition of the notion of users of AI systems. Hence, where end-users do not qualify as users, they may only receive very limited information. This element might potentially raise concern regarding the objective of the Proposal. On the content of the transparency obligations, the research highlights that the information that should benefit users of high-risk AI systems is both very broad and specific, from a technical perspective. Therefore, the information required under those obligations seems to create, prima facie, an adequate framework to ensure trust for users of high-risk AI systems. However, on the practical implications of these transparency obligations, the research notes that concern arises due to potential illiteracy of high-risk AI systems users. They might not benefit from sufficient technical expertise to fully understand the information provided to them, despite the wording of the Proposal, which requires that information should be comprehensible to its recipients (i.e. users).On this matter, the research points that there could be, more broadly, an important divergence between the level of detail of the information required by the Proposal and the level of expertise of users of high-risk AI systems. As a conclusion, the research provides policy recommendations to tackle (part of) the issues highlighted. It notably recommends to broaden the scope of transparency requirements for high-risk AI systems to encompass end-users. It also suggests that principles of explanation, as they were put forward in the Guidelines for Trustworthy AI of the High Level Expert Group, should be included in the Proposal in addition to transparency obligations.

Keywords: aI act proposal, explainability of aI, high-risk aI systems, transparency requirements

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Authors: Fatemeh Daneshvartarigh

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New technologies and applications have radically altered construction techniques in recent years. In order to anticipate how the building will act, perform, and appear, these technologies encompass a wide range of visualization, simulation, and analytic tools. These new technologies and applications have a considerable impact on completing construction projects in today's (architecture, engineering and construction)AEC industries. The rate of changes in BIM-related topics is different worldwide, and it depends on many factors, e.g., the national policies of each country. Therefore, there is a need for comprehensive research focused on a specific area with common characteristics. Therefore, one of the necessary measures to increase the use of this new approach is to examine the challenges and obstacles facing it. In this research, based on the Delphi method, at first, the background and related literature are reviewed. Then, using the knowledge obtained from the literature, a primary questionnaire is generated and filled by experts who are selected using snowball sampling. It covered the experts' attitudes towards implementing BIM in renovation projects and their view of the benefits and obstacles in this regard. By analyzing the primary questionnaire, the second group of experts is selected among the participants to be interviewed. The results are analyzed using Theme analysis. Six themes, including Management support, staff resistance, client willingness, Cost of software and implementation, the difficulty of implementation, and other reasons, are obtained. Then a final questionnaire is generated from the themes and filled by the same group of experts. The result is analyzed by the Fuzzy Delphi method, showing the exact ranking of the obtained themes. The final results show that management support, staff resistance, and client willingness are the most critical barrier to BIM usage in renovation projects.

Keywords: building information modeling, BIM, BIM implementation, BIM barriers, BIM in renovation

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Authors: Jaehong Yu, Seoung Bum Kim

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Clustering analysis can facilitate the extraction of intrinsic patterns in a dataset and reveal its natural groupings without requiring class information. For effective clustering analysis in high dimensional datasets, unsupervised dimensionality reduction is an important task. Unsupervised dimensionality reduction can generally be achieved by feature extraction or feature selection. In many situations, feature selection methods are more appropriate than feature extraction methods because of their clear interpretation with respect to the original features. The unsupervised feature selection can be categorized as feature subset selection and feature ranking method, and we focused on unsupervised feature ranking methods which evaluate the features based on their importance scores. Recently, several unsupervised feature ranking methods were developed based on ensemble approaches to achieve their higher accuracy and stability. However, most of the ensemble-based feature ranking methods require the true number of clusters. Furthermore, these algorithms evaluate the feature importance depending on the ensemble clustering solution, and they produce undesirable evaluation results if the clustering solutions are inaccurate. To address these limitations, we proposed an ensemble-based feature ranking method with random subspace and multiple-k ensemble (FRRM). The proposed FRRM algorithm evaluates the importance of each feature with the random subspace ensemble, and all evaluation results are combined with the ensemble importance scores. Moreover, FRRM does not require the determination of the true number of clusters in advance through the use of the multiple-k ensemble idea. Experiments on various benchmark datasets were conducted to examine the properties of the proposed FRRM algorithm and to compare its performance with that of existing feature ranking methods. The experimental results demonstrated that the proposed FRRM outperformed the competitors.

Keywords: clustering analysis, multiple-k ensemble, random subspace-based feature evaluation, unsupervised feature ranking

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