Search results for: k-means clustering based feature weighting

Authors: Mariam Shalaby, Kayla Krause, Raisha Ismail, Daniel George

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Introduction: The Pennsylvania State College of Medicine Refugee Initiative is a student-run organization that works with eleven Syrian and Congolese refugee families. Since 2016, it has used grant funding to make weekly produce purchases at a local market, provide tutoring services, and develop trusting relationships. This case study explains how the Refugee Initiative shifted focus to face new challenges due to the COVID-19 pandemic in 2020. Methodology: When refugees who had previously attained stability found themselves unable to pay the bills, the organization shifted focus from food security to direct assistance such as applying for unemployment compensation since many had recently lost jobs. When refugee families additionally struggled to access hygiene supplies, funding was redirected to purchase them. Funds were also raised from the community to provide financial relief from unpaid rent and bills. Findings: Systemic challenges were encountered in navigating federal/state unemployment and social welfare systems, and there was a conspicuous absence of affordable, language-accessible assistance that could help refugees. Finally, as struggling public schools failed to maintain adequate English as a Second Language (ESL) education, the group’s tutoring services were hindered by social distancing and inconsistent access to distance-learning platforms. Conclusion: Ultimately, the pandemic highlighted that a charity-based arrangement is helpful but not sustainable, and challenges persist for refugee families. Based on the Refugee Initiative's experiences over the past year of the COVID-19 pandemic, several needs must be addressed to aid refugee families at this time, including: increased access to affordable and language-accessible social services, educational resources, and simpler options for grant-based financial assistance. Interventions to increase these resources will aid refugee families in need in Central Pennsylvania and internationally

Keywords: COVID-19, health, pandemic, refugees

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Authors: Hui Fang Huang Su, Jia Borror

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This study compared two interventions for teaching math to preschool-aged students with autism spectrum disorder (ASD). The first is considered the business as usual (BAU) intervention, which uses the Strategies for Teaching Based on Autism Research (STAR) curriculum and discrete trial teaching as the instructional methodology. The second is the Math is Not Difficult (Project MIND) activity-embedded, naturalistic intervention. These interventions were randomly assigned to four preschool students with ASD classrooms and implemented over three months for Project Mind. We used measurement gained during the same three months for the STAR intervention. In addition, we used A quasi-experimental, pre-test/post-test design to compare the effectiveness of these two interventions in building mathematical knowledge and skills. The pre-post measures include three standardized instruments: the Test of Early Math Ability-3, the Problem Solving and Calculation subtests of the Woodcock-Johnson Test of Achievement IV, and the Bracken Test of Basic Concepts-3 Receptive. The STAR curriculum-based assessment is administered to all Baudhuin students three times per year, and we used the results in this study. We anticipated that implementing these two approaches would improve the mathematical knowledge and skills of children with ASD. Still, it is crucial to see whether a behavioral or naturalistic teaching approach leads to more significant results.

Keywords: early learning, autism, math for pre-schoolers, special education, teaching strategies

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Authors: Endalamaw Ewnu Kassa, Ade Kurniawan, Ya-Fen Wu, Sajal Biring

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Perovskite-based gas sensors represent a highly promising materials within the realm of gas sensing technology, with a particular focus on detecting ammonia (NH3) due to its potential hazards. Our work conducted thorough comparison of various solvents, including dimethylformamide (DMF), DMF-dimethyl sulfoxide (DMSO), dimethylacetamide (DMAC), and DMAC-DMSO, for the preparation of our perovskite solution (MAPbI3). Significantly, we achieved an exceptional response at 10 ppm of ammonia gas by employing a binary solvent mixture of DMAC-DMSO. In contrast to prior reports that relied on single solvents for MAPbI3 precursor preparation, our approach using mixed solvents demonstrated a marked improvement in gas sensing performance. We attained enhanced surface coverage, a reduction in pinhole occurrences, and precise control over grain size in our perovskite films through the careful selection and mixtures of appropriate solvents. This study shows a promising potential of employing binary and multi-solvent mixture strategies as a means to propel advancements in gas sensor technology, opening up new opportunities for practical applications in environmental monitoring and industrial safety.

Keywords: sensors, binary solvents, ammonia, sensitivity, grain size, pinholes, surface coverage

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Authors: Gabriella Vermeulen

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This paper applies a Bourdieusian lens to a Limpopo Citrus farm referred to as Malapeng in order to understand how conflict and authority are reproduced in Malapeng in the larger context of the South African agricultural industry. The South African citrus industry is an export industry, with South Africa being the second largest exporter of citrus in the world. Agriculture in South Africa has undergone extensive liberalisation since 1994, and many historical patterns, such as the racial divide in agriculture and the exploitation of black workers, are still continuously reproduced on farms in South Africa. This chapter looks at the institution of the ‘farm bank’ on Malapeng, which provides loans to workers whose livelihood strategies have been otherwise limited both by the larger agricultural context they are a part of and by the owner of Malapeng. By discussing the role of farm banks in a conflict between two permanent workers, the chapter illustrates how various oppositional discourses are strategically emphasised or de-emphasised at different times by the actors on Malapeng depending on their immediate goals. Farm bank proves to be a nexus of various discourses on Malapeng as the actors on Malapeng all construct farm bank in different (and often contradictory) terms in order to explain their influence and responsibility on Malapeng. The findings of the paper are based on data collected during fieldwork for an MA dissertation and are based on observation and semi-structured interviews conducted in 2021.

Keywords: agriculture, South Africa, capital, labour

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Authors: M. Ghanbari, S. Hossainpour, G. Rezazadeh

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In this paper, longitudinal vibration of a micro-beam in micro-scale fluid media has been investigated. The proposed mathematical model for this study is made up of a micro-beam and a micro-plate at its free end. An AC voltage is applied to the pair of piezoelectric layers on the upper and lower surfaces of the micro-beam in order to actuate it longitudinally. The whole structure is bounded between two fixed plates on its upper and lower surfaces. The micro-gap between the structure and the fixed plates is filled with fluid. Fluids behave differently in micro-scale than macro, so the fluid field in the gap has been modeled based on micro-polar theory. The coupled governing equations of motion of the micro-beam and the micro-scale fluid field have been derived. Due to having non-homogenous boundary conditions, derived equations have been transformed to an enhanced form with homogenous boundary conditions. Using Galerkin-based reduced order model, the enhanced equations have been discretized over the beam and fluid domains and solve simultaneously in order to obtain force response of the micro-beam. Effects of micro-polar parameters of the fluid as characteristic length scale, coupling parameter and surface parameter on the response of the micro-beam have been studied.

Keywords: micro-polar theory, Galerkin method, MEMS, micro-fluid

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Authors: Ayesha Sanjana Kawser Parsha

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S-acylation is an irreversible bond in which cysteine residues are linked to fatty acids palmitate (74%) or stearate (22%), either at the COOH or NH2 terminal, via a thioester linkage. There are several experimental methods that can be used to identify the S-palmitoylation site; however, since they require a lot of time, computational methods are becoming increasingly necessary. There aren't many predictors, however, that can locate S- palmitoylation sites in Arabidopsis Thaliana with sufficient accuracy. This research is based on the importance of building a better prediction tool. To identify the type of machine learning algorithm that predicts this site more accurately for the experimental dataset, several prediction tools were examined in this research, including the GPS PALM 6.0, pCysMod, GPS LIPID 1.0, CSS PALM 4.0, and NBA PALM. These analyses were conducted by constructing the receiver operating characteristics plot and the area under the curve score. An AI-driven deep learning-based prediction tool has been developed utilizing the analysis and three sequence-based input data, such as the amino acid composition, binary encoding profile, and autocorrelation features. The model was developed using five layers, two activation functions, associated parameters, and hyperparameters. The model was built using various combinations of features, and after training and validation, it performed better when all the features were present while using the experimental dataset for 8 and 10-fold cross-validations. While testing the model with unseen and new data, such as the GPS PALM 6.0 plant and pCysMod mouse, the model performed better, and the area under the curve score was near 1. It can be demonstrated that this model outperforms the prior tools in predicting the S- palmitoylation site in the experimental data set by comparing the area under curve score of 10-fold cross-validation of the new model with the established tools' area under curve score with their respective training sets. The objective of this study is to develop a prediction tool for Arabidopsis Thaliana that is more accurate than current tools, as measured by the area under the curve score. Plant food production and immunological treatment targets can both be managed by utilizing this method to forecast S- palmitoylation sites.

Keywords: S- palmitoylation, ROC PLOT, area under the curve, cross- validation score

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Authors: Constantinos S. Mammas, Andreas Lazaris, Adamantia S. Mamma-Graham, Georgia Kostopanagiotou, Chryssa Lemonidou, John Mantas, Eustratios Patsouris

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The process to build a better safety culture, methods of error analysis, and preventive measures, starts with an understanding of the effects when human factors engineering refer to remote microscopic diagnosis in surgery and specially in organ transplantation for the evaluation of the grafts. Α high percentage of solid organs arrive at the recipient hospitals and are considered as injured or improper for transplantation in the UK. Digital microscopy adds information on a microscopic level about the grafts (G) in Organ Transplant (OT), and may lead to a change in their management. Such a method will reduce the possibility that a diseased G will arrive at the recipient hospital for implantation. Aim: The aim of this study is to analyze the ergonomics of digital microscopy (DM) based on virtual slides, on telemedicine systems (TS) for tele-pathological evaluation (TPE) of the grafts (G) in organ transplantation (OT). Material and Methods: By experimental simulation, the ergonomics of DM for microscopic TPE of renal graft (RG), liver graft (LG) and pancreatic graft (PG) tissues is analyzed. In fact, this corresponded to the ergonomics of digital microscopy for TPE in OT by applying virtual slide (VS) system for graft tissue image capture, for remote diagnoses of possible microscopic inflammatory and/or neoplastic lesions. Experimentation included the development of an OTE-TS similar experimental telemedicine system (Exp.-TS) for simulating the integrated VS based microscopic TPE of RG, LG and PG Simulation of DM on TS based TPE performed by 2 specialists on a total of 238 human renal graft (RG), 172 liver graft (LG) and 108 pancreatic graft (PG) tissues digital microscopic images for inflammatory and neoplastic lesions on four electronic spaces of the four used TS. Results: Statistical analysis of specialist‘s answers about the ability to accurately diagnose the diseased RG, LG and PG tissues on the electronic space among four TS (A,B,C,D) showed that DM on TS for TPE in OT is elaborated perfectly on the ES of a desktop, followed by the ES of the applied Exp.-TS. Tablet and mobile-phone ES seem significantly risky for the application of DM in OT (p<.001). Conclusion: To make the largest reduction in errors and adverse events referring to the quality of the grafts, it will take application of human factors engineering to procurement, design, audit, and awareness-raising activities. Consequently, it will take an investment in new training, people, and other changes to management activities for DM in OT. The simulating VS based TPE with DM of RG, LG and PG tissues after retrieval, seem feasible and reliable and dependable on the size of the electronic space of the applied TS, for remote prevention of diseased grafts from being retrieved and/or sent to the recipient hospital and for post-grafting and pre-transplant planning.

Keywords: digital microscopy, organ transplantation, tele-pathology, virtual slides

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Authors: Bashir Ahmad Aasim, Abdul Khaliq Karimi, Jun Tomiyama

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Material aging is one of the vital issues among all the civil, mechanical, and aerospace engineering societies. Sustenance and reliability of concrete, which is the widely used material in the world, is the focal point in civil engineering societies. For few decades, researchers have been able to present some form algorithms that could lead to evaluate a structure globally rather than locally without harming its serviceability and traffic interference. The algorithms could help presenting different methods for evaluating structures non-destructively. In this paper, a non-destructive vibration-based damage detection method is adopted to evaluate two concrete beams, one being in a healthy state while the second one contains a crack on its bottom vicinity. The study discusses that damage in a structure affects modal parameters (natural frequency, mode shape, and damping ratio), which are the function of physical properties (mass, stiffness, and damping). The assessment is carried out to acquire the natural frequency of the sound beam. Next, the vibration response is recorded from the cracked beam. Eventually, both results are compared to know the variation in the natural frequencies of both beams. The study concludes that damage can be detected using vibration characteristics of a structural member considering the decline occurred in the natural frequency of the cracked beam.

Keywords: concrete beam, natural frequency, non-destructive testing, vibration characteristics

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Authors: B. R. Campomanes-Alvarez, P. Quiros, B. Fernandez

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Automatic Speech Recognition (ASR) is a machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speaker or an audio file, analyzes it using algorithms, and produces an output in the form of a text. Some speech recognition systems use Hidden Markov Models (HMMs) to deal with the temporal variability of speech and Gaussian Mixture Models (GMMs) to determine how well each state of each HMM fits a short window of frames of coefficients that represents the acoustic input. Another way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden layers and are trained using new methods have been shown to outperform GMMs on a variety of speech recognition systems. Acoustic models for state-of-the-art ASR systems are usually training on massive amounts of data. However, audio files with their corresponding transcriptions can be difficult to obtain, especially in the Spanish language. Hence, in the case of these low-resource scenarios, building an ASR model is considered as a complex task due to the lack of labeled data, resulting in an under-trained system. Semi-supervised learning approaches arise as necessary tasks given the high cost of transcribing audio data. The main goal of this proposal is to develop a procedure based on acoustic semi-supervised learning for Spanish ASR systems by using DNNs. This semi-supervised learning approach consists of: (a) Training a seed ASR model with a DNN using a set of audios and their respective transcriptions. A DNN with a one-hidden-layer network was initialized; increasing the number of hidden layers in training, to a five. A refinement, which consisted of the weight matrix plus bias term and a Stochastic Gradient Descent (SGD) training were also performed. The objective function was the cross-entropy criterion. (b) Decoding/testing a set of unlabeled data with the obtained seed model. (c) Selecting a suitable subset of the validated data to retrain the seed model, thereby improving its performance on the target test set. To choose the most precise transcriptions, three confidence scores or metrics, regarding the lattice concept (based on the graph cost, the acoustic cost and a combination of both), was performed as selection technique. The performance of the ASR system will be calculated by means of the Word Error Rate (WER). The test dataset was renewed in order to extract the new transcriptions added to the training dataset. Some experiments were carried out in order to select the best ASR results. A comparison between a GMM-based model without retraining and the DNN proposed system was also made under the same conditions. Results showed that the semi-supervised ASR-model based on DNNs outperformed the GMM-model, in terms of WER, in all tested cases. The best result obtained an improvement of 6% relative WER. Hence, these promising results suggest that the proposed technique could be suitable for building ASR models in low-resource environments.

Keywords: automatic speech recognition, deep neural networks, machine learning, semi-supervised learning

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Authors: Tony Ngoy Mbodi, Christophe Muanda

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Textile industry is considered as one of the most polluting sectors in terms of effluent volume of discharge and wastewater composition, such as dye, which represents an environmental hazard when discharged without any proper treatment. A study was conducted to investigate the capability of the use of recycled alum sludge (RAS) as an alternative treatment for the reduction of colour, chemical oxygen demand (COD), total dissolved solids (TDS) and pH adjustment from dye based synthetic textile industry wastewater. The coagulation/flocculation process was studied for coagulants of Alum:RAS ratio of, 1:1, 2:1, 1:2 and 0:1. Experiments on treating the synthetic wastewater using membrane filtration and adsorption with corn cobs were also conducted. Results from the coagulation experiment were compared to those from adsorption with corn cobs and membrane filtration experiments conducted on the same synthetic wastewater. The results of the RAS experiments were also evaluated against standard guidelines for industrial effluents treated for discharge purposes in order to establish its level of compliance. Based on current results, it can be concluded that reusing the alum sludge as a low-cost material pretreatment method into the coagulation/flocculation process can offer some advantages such as high removal efficiency for disperse dye and economic savings on overall treatment of the industry wastewater.

Keywords: alum, coagulation/flocculation, dye, recycled alum sludge, textile wastewater

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Authors: Anar Koli

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After the Paris agreement in 2015, a comprehensive initiative both from the developed and developing countries towards the adaptation to climate change is emerging. The Global Environmental Facility (GEF), which is financing a global portfolio of adaptation projects and programs in over 124 countries is playing a significant role to a new financing framework that included the concept of “climate-resilient development”. However, both the adaptation and sustainable development paradigms remain continuously contested, especially the role of the multilateral institutions with their technical and financial assistance to the developing world. Focusing on the adaptation initiatives of the GEF, this study aims to understand to what extent the global multilateral institutions, particularly the GEF is contributing to the climate-resilient development. From the political ecology perspective, the argument of this study is that the global financial framework is highly politicized, and understanding the contribution of the global institutions of the global climate change needs to be related both from the response and causal perspectives. A holistic perspective, which includes the contribution of the GEF as a response to the climate change and as well the cause of global climate change, are needed to understand the broader environment- political economic relation. The study intends to make a critical analysis of the way in which the political economy structure and the environment are related along with the social and ecological implications. It does not provide a narrow description of institutional responses to climate change, rather it looks at how the global institutions are influencing the relationship of the global ecologies and economies. This study thus developed a framework combining the global governance and the political economy perspective. This framework includes environment-society relation, environment-political economy linkage, global institutions as the orchestra, and division between the North and the South. Through the analysis of the GEF as the orchestra of the global governance, this study helps to understand how GEF is coordinating the interactions between the North and the South and responding the global climate resilient development. Through the other components of the framework, the study explains how the role of the global institutions is related to the cause of the human induced global climate change. The study employs a case study based on both the quantitative and qualitative data. Along with the GEF reports and data sets, this study draws from an eclectic range of literature from a range of disciplines to explain the broader relation of the environment and political economy. Based on a case study on GEF, the study found that the GEF has positive contributions in bringing developing countries’ capacity in terms of sustainable development goal, local institutional development. However, through a critical holistic analysis, this study found that this contribution to the resilient development helps the developing countries to conform the fossil fuel based capitalist political economy. The global governance institution is contributing both to the pro market based environment society relation and, to the consequences of this relation.

Keywords: climate change adaptation, global environmental facility (GEF), political economy, the north -south relation

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Authors: Mohammad Izadkhah, Mojtaba Hoseini, Alireza Khalili Tehrani

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In this paper we presented a new method for tracking flying targets in color video sequences based on contour and kernel. The aim of this work is to overcome the problem of losing target in changing light, large displacement, changing speed, and occlusion. The proposed method is made in three steps, estimate the target location by particle filter, segmentation target region using neural network and find the exact contours by greedy snake algorithm. In the proposed method we have used both region and contour information to create target candidate model and this model is dynamically updated during tracking. To avoid the accumulation of errors when updating, target region given to a perceptron neural network to separate the target from background. Then its output used for exact calculation of size and center of the target. Also it is used as the initial contour for the greedy snake algorithm to find the exact target's edge. The proposed algorithm has been tested on a database which contains a lot of challenges such as high speed and agility of aircrafts, background clutter, occlusions, camera movement, and so on. The experimental results show that the use of neural network increases the accuracy of tracking and segmentation.

Keywords: video tracking, particle filter, greedy snake, neural network

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Authors: Heba Kamal, Ghada Saudi

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Due to The rapid expansion of energy and growing number of wind turbines construction in earthquake areas, a design method for simple and accurate evaluation of seismic load to ensure structural integrity is required. In Egypt, there are some appropriate places to build wind turbine towers lie in active seismically regions, so accurate analysis is necessary for prediction of seismic loads with consideration of intensity of the earthquake, soil and structural characteristics. In this research, seismic behavior of wind turbine towers Gamesa Type G52 in Zafarana Wind Farm Egypt is investigated using experimental work by ambient vibration test, and fully dynamic analysis based on time history from El Aqaba Earthquake 1995 using 3D by PLAXIS 3D software, including the soil structure interaction effect. The results obtained from dynamic analyses are discussed. From this study, it is concluded that, the fully dynamic seismic analysis based on used PLAXIS 3D with the aid of the full scale ambient vibration test gives almost good simulation for the seismic loads that can be applied to wind turbine tower design in Egypt.

Keywords: Wind turbine towers, Zafarana Wind Farm, Gamesa Type G52, ambient vibration test

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Authors: Heri Suryoatmojo, Adi Kurniawan, Feby A. Pamuji, Nursalim, Syaffaruddin, Herbert Innah

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Photovoltaic (PV) system hybrid with diesel system is utilized widely for electrification in remote area. PV output power fluctuates due to uncertainty condition of temperature and sun irradiance. When the penetration of PV power is large, the reliability of the power utility will be disturbed and seriously impact the unstable frequency of system. Therefore, designing a robust frequency controller in PV-diesel hybrid power system is very important. This paper proposes new method of frequency control application in hybrid PV-diesel system based on artificial neural network (ANN). This method can minimize the frequency deviation without smoothing PV output power that controlled by maximum power point tracking (MPPT) method. The neural network algorithm controller considers average irradiance, change of irradiance and frequency deviation. In order the show the effectiveness of proposed algorithm, the addition of battery as energy storage system is also presented. To validate the proposed method, the results of proposed system are compared with the results of similar system using MPPT only. The simulation results show that the proposed method able to suppress frequency deviation smaller compared to the results of system using MPPT only.

Keywords: energy storage system, frequency deviation, hybrid power generation, neural network algorithm

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Authors: Mark Opmeer

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The fruitful relationship between cultural heritage and digital technology is evident. Due to the development of user-friendly software, an increasing amount of heritage scholars use ict for their research activities. As a result, the implementation of information technology for heritage planning has become a research objective in itself. During the last decades, we have witnessed a growing debate and literature about the importance of computer technologies for the field of cultural heritage and ecotourism. Indeed, implementing digital technology in support of these domains can be very fruitful for one’s research practice. However, due to the rapid development of new software scholars may find it challenging to use these innovations in an appropriate way. As such, this contribution seeks to explore the interplay between geospatial technologies (geo-ict), civic engagement and cultural heritage and tourism. In this article, we discuss our findings on the use of geo-ict in support of civic participation, cultural heritage and sustainable tourism development in the southern Italian district of Brindisi. In the city of Latiano, three workshops were organized that involved local members of the community to distinguish and discuss interesting points of interests (POI’s) which represent the cultural significance and identity of the area. During the first workshop, a so called mappa della comunità was created on a touch table with collaborative mapping software, that allowed the participators to highlight potential destinations for tourist purposes. Furthermore, two heritage-based itineraries along a selection of identified POI’s was created to make the region attractive for recreants and tourists. These heritage-based itineraries reflect the communities’ ideas about the cultural identity of the region. Both trails were subsequently implemented in a dedicated mobile application (app) and was evaluated using a mixed-method approach with the members of the community during the second workshop. In the final workshop, the findings of the collaboration, the heritage trails and the app was evaluated with all participants. Based on our conclusions, we argue that geospatial technologies have a significant potential for involving local communities in heritage planning and tourism development. The participants of the workshops found it increasingly engaging to share their ideas and knowledge using the digital map of the touch table. Secondly, the use of a mobile application as instrument to test the heritage-based itineraries in the field was broadly considered as fun and beneficial for enhancing community awareness and participation in local heritage. The app furthermore stimulated the communities’ awareness of the added value of geospatial technologies for sustainable tourism development in the area. We conclude this article with a number of recommendations in order to provide a best practice for organizing heritage workshops with similar objectives.

Keywords: civic engagement, geospatial technologies, tourism development, cultural heritage

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Authors: Prakash Singh

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The focus of this exploratory study is on whether teachers demonstrate emphatic concern for their learners in planning, implementing and assessing learning outcomes in their regular classrooms. Empathy must be shown to all learners equally and not only for high-risk learners at the expense of other ability learners. Empathy demonstrated by teachers allows them to build a stronger bond with all their learners. This bond based on trust leads to positive outcomes for learners to be able to excel in their work. Empathic teachers must make every effort to simplify the subject matter for high risk learners so that these learners not only enjoy their learning activities but are also successful like their more able peers. A total of 87.5% of the participants agreed that empathy allows teachers to demonstrate humanistic values in their choice of learning materials for learners of different abilities. It is therefore important for teachers to select content and instructional materials that will contribute to the learners’ success in the mainstream of education. It is also imperative for teachers to demonstrate empathic skills and consequently, to be attuned to the emotions and emotional needs of their learners. Schools need to be reformed, not by simply lengthening the school day or by simply adding more content in the curriculum, but by making school more satisfying to learners. This must be consistent with their diverse learning needs and interests so that they gain a sense of power, fulfillment, and importance in their regular classrooms. Hence, teacher - pupil relationships based on empathic concern for the latter’s educational needs lays the foundation for quality education to be offered.

Keywords: emotional intelligence, empathy, learners’ emotional needs, teachers’ empathic skills

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Authors: Athanasia Petropoulou

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While there is a common understanding that a person’s sex, gender, gender identity, and sexual orientation shape every stage of the migration experience, theories of international migration had until recently not been focused on exploring and incorporating a gender perspective in their analysis. In a similar vein, refugee law has long been the object of criticisms for failing to recognize and respond appropriately to women’s and sexual minorities’ experiences of persecution. The present analysis attempts to depict the challenges faced by the European Court of Human Rights (ECtHR) and U.S. courts when adjudicating in cases involving asylum claims with a gendered perspective. By providing a comparison between adjudicating strategies of international and national jurisdictions, the article aims to identify common or distinctive approaches in addressing gendered based claims. The paper argues that, despite the different nature of the judicial bodies and the different legal instruments applied respectively, judges face similar challenges in this context and often fail to qualify and address the gendered dimensions of asylum claims properly. The ECtHR plays a fundamental role in safeguarding human rights protection in Europe not only for European citizens but also for people fleeing violence, war, and dire living conditions. However, this role becomes more difficult to fulfill, not only because of the obvious institutional constraints but also because cases related to claims of asylum seekers concern a domain closely linked to State sovereignty. Amid the current “refugee crisis,” risk assessment performed by national authorities, like in the process of asylum determination, is shaped by wider geopolitical and economic considerations. The failure to recognize and duly address the gendered dimension of non - refoulement claims, one of the many shortcomings of these processes, is reflected in the decisions of the ECtHR. As regards U.S. case law, the study argues that U.S. courts either fail to apply any connection between asylum claims and their gendered dimension or tend to approach gendered based claims through the lens of the “political opinion” or “membership of a particular social group” reasons of fear of persecution. This exercise becomes even more difficult, taking into account that the U.S. asylum law inappropriately qualifies gendered-based claims. The paper calls for more sociologically informed decision-making practices and for a more contextualized and relational approach in the assessment of the risk of ill-treatment and persecution. Such an approach is essential for unearthing the gendered patterns of persecution and addressing effectively related claims, thus securing the human rights of asylum seekers.

Keywords: asylum, European court of human rights, gender, human rights, U.S. courts

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Authors: Covadonga Rodrigo, Felipe Alvarez Arrieta, Ana Garcia Serrano

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Mobile augmented reality technologies have become very popular in the last years in the educational field. Researchers have studied how these technologies improve the engagement of the student and better understanding of the process of learning. But few studies have been made regarding the accessibility of these new technologies applied to digital humanities. The goal of our research is to develop an accessible mobile application with embedded augmented reality main characters of the art work and gamification events accompanied by multi-sensorial activities. The mobile app conducts a learning itinerary around the artistic work, driving the user experience in and out the museum. The learning design follows the inquiry-based methodology and social learning conducted through interaction with social networks. As for the software application, it’s being user-centered designed, following the universal design for learning (UDL) principles to assure the best level of accessibility for all. The mobile augmented reality application starts recognizing a marker from a masterpiece of a museum using the camera of the mobile device. The augmented reality information (history, author, 3D images, audio, quizzes) is shown through virtual main characters that come out from the art work. To comply with the UDL principles, we use a version of the technology acceptance model (TAM) to study the easiness of use and perception of usefulness, extended by the authors with specific indicators for measuring accessibility issues. Following a rapid prototype method for development, the first app has been recently produced, fulfilling the EN 301549 standard and W3C accessibility guidelines for mobile development. A TAM-based web questionnaire with 214 participants with different kinds of disabilities was previously conducted to gather information and feedback on user preferences from the artistic work on the Museo del Prado, the level of acceptance of technology innovations and the easiness of use of mobile elements. Preliminary results show that people with disabilities felt very comfortable while using mobile apps and internet connection. The augmented reality elements seem to offer an added value highly engaging and motivating for the students.

Keywords: H.5.1 (multimedia information systems), artificial, augmented and virtual realities, evaluation/methodology

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Authors: Amir Hossein Hejazi, Nima Amjady

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In recent years, due to environmental issues traditional energy sources had been replaced by renewable ones. Wind energy as the fastest growing renewable energy shares a considerable percent of energy in power electricity markets. With this fast growth of wind energy worldwide, owners and operators of wind farms, transmission system operators, and energy traders need reliable and secure forecasts of wind energy production. In this paper, a new forecasting strategy is proposed for short-term wind power prediction based on Echo State Networks (ESN). The forecast engine utilizes state-of-the-art training process including dynamical reservoir with high capability to learn complex dynamics of wind power or wind vector signals. The study becomes more interesting by incorporating prediction of wind direction into forecast strategy. The Big Bang-Big Crunch (BB-BC) evolutionary optimization algorithm is adopted for adjusting free parameters of ESN-based forecaster. The proposed method is tested by real-world hourly data to show the efficiency of the forecasting engine for prediction of both wind vector and wind power output of aggregated wind power production.

Keywords: wind power forecasting, echo state network, big bang-big crunch, evolutionary optimization algorithm

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Authors: Nasser A. Al-Shabib

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Food allergens are most common non-native form when exposed to the immune system. Most food proteins undergo various treatments (e.g. thermal or proteolytic processing) during food manufacturing. Such treatments have the potential to impact the chemical structure of food allergens so as to convert them to more denatured or unfolded forms. The conformational changes in the proteins may affect the allergenicity of treated-allergens. However, most allergenic proteins possess high resistance against thermal modification or digestive enzymes. In the present study, ovomucoid (a major allergenic protein of egg white) was heated in phosphate-buffered saline (pH 7.4) at different temperatures, aqueous solutions and on different surfaces for various times. The results indicated that different antibody-based methods had different sensitivities in detecting the heated ovomucoid. When using one particular immunoassay‚ the immunoreactivity of ovomucoid increased rapidly after heating in water whereas immunoreactivity declined after heating in alkaline buffer (pH 10). Ovomucoid appeared more immunoreactive when dissolved in PBS (pH 7.4) and heated on a stainless steel surface. To the best of our knowledge‚ this is the first time that antibody-based methods have been applied for the detection of ovomucoid adsorbed onto different surfaces under various conditions. The results obtained suggest that use of antibodies to detect ovomucoid after food processing may be problematic. False assurance will be given with the use of inappropriate‚ non-validated immunoassays such as those available commercially as ‘Swab’ tests. A greater understanding of antibody-protein interaction after processing of a protein is required.

Keywords: ovomucoid, thermal treatment, solutions, surfaces

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Authors: Nur Mohammad Ali, Md. Shafiqul Alam, Jayanta Bhusan Deb, Nowrin Sharmin

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The past ten years have seen significant expansion in the aviation sector, which during the previous five years has steadily pushed emerging countries closer to economic independence. It is crucial to accurately forecast the potential demand for air travel to make long-term financial plans. To forecast market demand for low-cost passenger carriers, this study suggests working with low-cost airlines, airports, consultancies, and governmental institutions' strategic planning divisions. The study aims to develop an artificial intelligence-based methods, notably fuzzy inference systems (FIS), to determine the most accurate forecasting technique for domestic low-cost carrier demand in Bangladesh. To give end users real-world applications, the study includes nine variables, two sub-FIS, and one final Mamdani Fuzzy Inference System utilizing a graphical user interface (GUI) made with the app designer tool. The evaluation criteria used in this inquiry included mean square error (MSE), accuracy, precision, sensitivity, and specificity. The effectiveness of the developed air passenger demand prediction FIS is assessed using 240 data sets, and the accuracy, precision, sensitivity, specificity, and MSE values are 90.83%, 91.09%, 90.77%, and 2.09%, respectively.

Keywords: aviation industry, fuzzy inference system, membership function, graphical user interference

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Authors: N. Mahmoudnia, M. Khormali

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This experiment was conducted to determine the apparent protein digestibility of poultry byproduct meal (PBPM) from two industrial poultry slaughter-houses on Ross 308 male broiler chickens in independent comparisons. The experiment consisted of seven dietary treatments and three replicates per treatment with three broiler chickens per replicate in a completely randomized design. Dietary treatments consisted of a control corn- soybean diet, and levels 3, 6, and 9% PBPM produced by slaughter-house 1 and levels 3, 6, and 9% PBPM produced by slaughter house 2. Chromic oxide was added to the experimental diets as an indigestible marker. The apparent protein digestibility of each diet were determined with two methods of sample collection of ileum and excreta in 21-28 d of age. The results this experiment showed that use of PBPM had no significant effect on the performance of broiler chicks during period of experiments. The apparent protein digestibility of PBPM groups was significantly higher than control group by excreta sampling procedure (P<0.05). Using of PBPM 2 significantly (P<0.05) decreased the apparent protein digestibility values based on ileum sampling procedure vs control (85.21 vs. 90.14).Based results of this experiment,it is possible to use of PBPM 1 in broiler chicken.

Keywords: poultry by-product meal, apparent protein digestibility, independed comparison, broiler chicken

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Authors: Glemarie C. Hermosa, Sheng-Jie You, Chien Chih Hu

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Efficient separation technologies are required for the removal of carbon dioxide from natural gas streams. Membrane-based natural gas separation has emerged as one of the fastest growing technologies, due to the compactness, higher energy efficiency and economic advantages which can be reaped. The removal of Carbon dioxide from gas streams using membrane technology will also give the advantage like environmental friendly process compared to the other technologies used in gas separation. In this study, Polyimide membranes, which are mostly used in the separation of gases, are blended with a new kind of solvent: Deep Eutectic Solvents or simply DES. The three types of DES are used are choline chloride based mixed with three different hydrogen bond donors: Lactic acid, N-methylurea and Urea. The blending of the DESs to Polyimide gave out high permeability performance. The Gas Separation performance for all the membranes involving CO2/CH4 showed low performance while for CO2/N2 surpassed the performance of some studies. Among the three types of DES used the solvent Choline Chloride/Lactic acid exhibited the highest performance for both Gas Separation applications. The values are 10.5 for CO2/CH4 selectivity and 60.5 for CO2/N2. The separation results for CO2/CH4 may be due to the viscosity of the DESs affecting the morphology of the fabricated membrane thus also impacts the performance. DES/blended Polyimide membranes fabricated are novel and have the potential of a low-cost and environmental friendly application for gas separation.

Keywords: deep eutectic solvents, gas separation, polyimide blends, polyimide membranes

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Authors: Bin Liu

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MicroRNAs (miRNAs) are small non-coding RNA molecules, functioning in transcriptional and post-transcriptional regulation of gene expression. The discrimination of the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops) is necessary for the understanding of miRNAs’ role in the control of cell life and death. Since both their small size and sequence specificity, it cannot be based on sequence information alone but requires structure information about the miRNA precursor to get satisfactory performance. Kmers are convenient and widely used features for modeling the properties of miRNAs and other biological sequences. However, Kmers suffer from the inherent limitation that if the parameter K is increased to incorporate long range effects, some certain Kmer will appear rarely or even not appear, as a consequence, most Kmers absent and a few present once. Thus, the statistical learning approaches using Kmers as features become susceptible to noisy data once K becomes large. In this study, we proposed a Gapped k-mer approach to overcome the disadvantages of Kmers, and applied this method to the field of miRNA prediction. Combined with the structure status composition, a classifier called imiRNA-GSSC was proposed. We show that compared to the original imiRNA-kmer and alternative approaches. Trained on human miRNA precursors, this predictor can achieve an accuracy of 82.34 for predicting 4022 pre-miRNA precursors from eleven species.

Keywords: gapped k-mer, imiRNA-GSSC, microRNA precursor, support vector machine

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Authors: Deden Misbahudin Muayyad, Lavlimatria Esya

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Up to the month of June 2015, Indonesia has 12 Islamic Commercial Banks, 22 Islamic Business Unit, 327 offices in 33 provinces. The initial purpose of the establishment of Islamic financial institutions is to achieve and the welfare of the people in this world and in the hereafter. To realize these goals, the Islamic financial institutions in every kind of aspect of product development and in terms of operations should be based on maqashid sharia, namely keeping the faith, keep the soul, keep the sense, maintain the property, keeping the offspring. To see whether Islamic banking grounded in maqasid sharia, the Islamic banking performance measurements based on the principles of maqasid sharia. Banking performance measurement is not only focusing on profit and other financial measures, but put other values of banks reflects the size of the benefit of non-profit in accordance with the bank's objectives. The measurement using the measurement of financial performance called maqasid sharia index. Maqasid syariah index is a model of Islamic banking performance measurement in accordance with the objectives and characteristics of Islamic banking. Maqasid syariah index was developed based on three main factors, namely the education of individuals, the creation of justice, the achievement of well-being, where the three factors were in accordance with the common goal of maqasid sharia is achieving prosperity and avoid evil. Maqasid syariah index shows that maqasid sharia approach can be a strategic alternative approach to describe how good the performance of the banking system and it can be implemented in the comprehensive policy strategy. This study uses a model of performance measurement framework based on maqasid syariah, in addition to financial performance measures that already exist. Methods to develop the idea of a performance measurement framework of Islamic banking by maqasid sharia is the Sekaran method. Operationally, the methods have now able to describe the elements that will be measured by this study. This is done by observing the behavior of the dimensions illustrated through a concept that has been set. These dimensions translate into derivative elements that can be observed and more scalable, so it can establish measurement indices. This research is descriptive quantitative. Techniques are being made to collect data in this paper is by using purposive sampling method, with 12 Islamic Commercial Banks that qualify as research samples. The financial data taken at 12 banks was sourced from the annual financial statements the period 2008 to 2012 with consideration of the database and ease of access to data. The ratio measured in this study only 7 ratio used in determining the performance of Islamic banking, namely: four ratio refers to the sharia objectives related to education. three ratio while again referring to sharia objectives related to the achievement of welfare. While other ratios associated with justice can not be used in this study because of the limited data used. Total overall calculation of performance indicators and performance ratios on each goal for each bank describes the maqasid syariah index.

Keywords: Islamic banking, Maslahah, maqashid syariah, maqashid syariah index

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Authors: Preetham Shankapal, Jill King, Kori Murray, Corby Martin, Paula Giselman, Jason Hicks, Owen Carmicheal

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Activation of reward and satiety networks in the brain while processing palatable food cues, as well as functional connectivity during rest has been studied using functional Magnetic Resonance Imaging of the brain in various obesity phenotypes. However, functional connectivity within the reward and satiety network during food cue processing is understudied. 14 obese individuals underwent two fMRI scans during viewing of Macronutrient Picture System images. Each scan included two blocks of images of High Sugar/High Fat (HSHF), High Carbohydrate/High Fat (HCHF), Low Sugar/Low Fat (LSLF) and also non-food images. Seed voxels within seven food reward relevant ROIs: Insula, putamen and cingulate, precentral, parahippocampal, medial frontal and superior temporal gyri were isolated based on a prior meta-analysis. Beta series correlation for task-related functional connectivity between these seed voxels and the rest of the brain was computed. Voxel-level differences in functional connectivity were calculated between: first and the second scan; individuals who saw novel (N=7) vs. Repeated (N=7) images in the second scan; and between the HC/HF, HSHF blocks vs LSLF and non-food blocks. Computations and analysis showed that during food image viewing, reward network ROIs showed significant functional connectivity with each other and with other regions responsible for attentional and motor control, including inferior parietal lobe and precentral gyrus. These functional connectivity values were heightened among individuals who viewed novel HS/HF images in the second scan. In the second scan session, functional connectivity was reduced within the reward network but increased within attention, memory and recognition regions, suggesting habituation to reward properties and increased recollection of previously viewed images. In conclusion it can be inferred that Functional Connectivity within reward network and between reward and other brain regions, varies by important experimental conditions during food photography viewing, including habituation to shown foods.

Keywords: fMRI, functional connectivity, task-based, beta series correlation

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Authors: Rajat Mittal, Harshal Raut, Jung Hee Seo

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Wave-assisted propulsion (WAP) systems convert wave energy into thrust using elastically mounted hydrofoils. We employ sharp-interface immersed boundary simulations to examine the effect of two key parameters on the flow physics, the fluid-structure interaction, as well as thrust performance of these systems - the stiffness of the torsional spring and the location of the rotational center. The variation in spring stiffness leads to different amplitude of pitch motion, phase difference with respect to heaving motion and thrust coefficient and we show the utility of ‘maps’ of energy exchange between the flow and the hydrofoil system, as a way to understand and predict this behavior. The Force Partitioning Method (FPM) is used to decompose the pressure forces into individual components and understand the mechanism behind increase in thrust. Next, a scaling law is presented for the thrust coefficient generated by heaving and pitching foil. The parameters within the scaling law are calculated based on direct-numerical simulations based parametric study utilized to generate the energy maps. The predictions of the proposed scaling law are then compared with those of a similar model from the literature, showing a noticeable improvement in the prediction of the thrust coefficient.

Keywords: propulsion, flapping foils, hydrodynamics, wave power

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Authors: Mohamed Sadok Bensalem, Soulef Amamria, Khaled Lazzez, Mohamed Ghanmi

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The southern-central Tunisian Atlas presents a typical example of an external zone. It occupies a particular position in the North African chains: firstly, it is the eastern limit of atlassic structures; secondly, it is the edges between the belts structures to the north and the stable Saharan platform in the south. The evolution of deformation study is based on several methods, such as classical or numerical methods. The principals parameters controlling the genesis of folds in the southern central Tunisian Atlas are; the reactivation of pre-existing faults during the later compressive phase, the evolution of decollement level, and the relation between thin and thick-skinned. One of the more principal characters of the southern-central Tunisian Atlas is the variation of belts structures directions determined by: NE-SW direction, named the attlassic direction in Tunisia, the NW-SE direction carried along the Gafsa fault (the oriental limit of southern atlassic accident), and the E-W direction defined in the southern Tunisian Atlas. This variation of direction is the result of important variation of deformation during different tectonics phases. A classical modelling of the Jebel ElKebar anticline, based on faults throw of the pre-existing faults and its reactivation during compressive phases, shows the importance of extensional deformation, particular during Aptian-Albian period, comparing with that of later compression (Alpine phases). A numerical modelling, based on the software Rampe E.M. 1.5.0, applied on the anticline of Jebel Orbata confirms the interpretation of “fault related fold” with decollement level within the Triassic successions. The other important parameter of evolution of deformation is the vertical migration of decollement level; indeed, more than the decollement level is in the recent series, most that the deformation is accentuated. The evolution of deformation is marked the development of duplex structure in Jebel At Taghli (eastern limit of Jebel Orbata). Consequently, the evolution of deformation is proportional to the depth of the decollement level, the most important deformation is in the higher successions; thus, is associated to the thin-skinned deformation; the decollement level permit the passive transfer of deformation in the cover.

Keywords: evolution of deformation, pre-existing faults, decollement level, thin-skinned

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Authors: Mohamad Amin Amini, Mehdi Poursha

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Nonlinear response history analysis (NL-RHA) is a robust analytical tool for estimating the seismic demands of structures responding in the inelastic range. However, because of its conceptual and numerical complications, the nonlinear static procedure (NSP) is being increasingly used as a suitable tool for seismic performance evaluation of structures. The conventional pushover analysis methods presented in various codes (FEMA 356; Eurocode-8; ATC-40), are limited to the first-mode-dominated structures, and cannot take higher modes effect into consideration. Therefore, since more than a decade ago, researchers developed enhanced pushover analysis procedures to take higher modes effect into account. The main objective of this study is to propose an enhanced invariant lateral displacement distribution to take higher modes effect into consideration in performing a displacement-based pushover analysis, whereby a set of laterally applied displacements, rather than forces, is monotonically applied to the structure. For this purpose, the effect of different parameters such as the spectral displacement of ground motion, the modal participation factor, and the effective modal participating mass ratio on the lateral displacement distribution is investigated to find the best distribution. The major simplification of this procedure is that the effect of higher modes is concentrated into a single invariant lateral load distribution. Therefore, only one pushover analysis is sufficient without any need to utilize a modal combination rule for combining the responses. The invariant lateral displacement distribution for pushover analysis is then calculated by combining the modal story displacements using the modal combination rules. The seismic demands resulting from the different procedures are compared to those from the more accurate nonlinear response history analysis (NL-RHA) as a benchmark solution. Two structures of different heights including 10 and 20-story special steel moment resisting frames (MRFs) were selected and evaluated. Twenty ground motion records were used to conduct the NL-RHA. The results show that more accurate responses can be obtained in comparison with the conventional lateral loads when the enhanced modal lateral displacement distributions are used.

Keywords: displacement-based pushover, enhanced lateral load distribution, higher modes effect, nonlinear response history analysis (NL-RHA)

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Authors: Raymon Maac, Michael Arthus Muega, Joyce Ann Calingasan, Elva Maureen Gorospe

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Critical pedagogy is known for its advocacy of humanistic and liberating education. Its far-reaching approach helps students to understand and analyze their own situations and the realities happening in their society. However, this pedagogy together with its promising features is not well-known in the Philippines. This paper determines the place of critical pedagogy in the new values education curriculum and analyzes its features in the K-12 Values Education curriculum and textbook. The study examines the position of critical pedagogy in the Philippine K-12 Values Education curriculum by closely studying and comparing their features; and scrutinizes the Grade 8 Values Education textbook specifically modules 4, 8, 10 and 13 which comprises 25% of the total 16 modules. The said modules are concerned with the role of the family in the preservation of social justice, which is one of the objectives of critical pedagogy. The findings in this research were based on the pieces of evidence gathered from the curriculum and textbook itself. Based on the evaluation done, the study found out that the ideas of critical pedagogy were the same with that of the objectives of K-12 Values Education Curriculum. Due to this, values education teachers can utilize critical pedagogy in their subject. In addition, the K-12 Values Education curriculum exhibits some of the features of critical pedagogy such as authentic student empowerment and critical thinking. Lastly, some features of critical pedagogy are also evident in some of the general parts and recommended activities in the K-12 Values Education textbook while other activities need to be fully developed by both teacher and students to reflect the genuine critical pedagogy.

Keywords: authentic student empowerment, critical pedagogy, critical thinking, liberating education

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