Search results for: effect of collaborative learning

Authors: Irena Paramita Pramono

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Islamic bank is a financial industry with huge potential to grow in Indonesia. Profit-sharing agreement in the operations of Islamic banks distinguishes Islamic banks with conventional banks. Profit-sharing agreement allows sharing of benefits and risks between shahibul maal and mudharib in islamic bank. This study aimed to observe the patterns of influence between the risk-sharing agreement, financing risk and Profitability in Islamic banks. This research used several Islamic banks as sample and path analysis method. The empirical results of this research shows that the profit-sharing agreement in deposits structure has no direct significant effect to ROA, but it has indirect effect to ROA through profit-sharing financing. On the other hand, profit-sharing financing has direct and indirect influence to ROA through financing risk. This research shows that profit-sharing financing has a positive significant effect to the financing risk and also to the ROA. The research recommends Islamic banks to continue using and developing profit-sharing agreement in its operational activities, hence to create value.

Keywords: Islamic bank, profit-loss sharing agreement, financing risk, profitability

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Authors: Dora Vajda, Somayyeh Mohammadi, Sandor Rozsa

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Predicting the relationship satisfaction based on the personality characteristics of both partners has a long history. The association between relationship quality and personality traits has been previously demonstrated. Personality traits are most commonly assessed using the Five-Factor Model. The present study has focused on Cloninger's psychobiological model of personality that accounts for dimensions of both temperament and character. The goal of this study was to examine the actor and partner effect of couple's personality on relationship outcomes. In total, 184 heterosexual couples completed the Temperament and Character Inventory (TCI) and the Dyadic Adjustment Scale. The analysis was based on Actor-Partner Interdependence Model (APIM) using multilevel modeling (MLwiN). Results showed that character dimensions Self-Directedness and Cooperativeness had a statistically meaningful actor and partner effect on both partner's relationship quality. However, male's personality temperament dimension Reward Dependence had an only actor effect on his relationship quality. The findings contribute to the literature by highlighting the role of character dimensions of personality in romantic relationships.

Keywords: APIM (actor-partner interdependence model), MLwiN, personality, relationship quality

Procedia PDF Downloads 404

Authors: Regis Pochon, Nicolas Stefaniak, Veronique Baltazart, Pamela Gobin

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Anxiety is known to have an impact on working memory. In reasoning or memory tasks, individuals with anxiety tend to show longer response times and poorer performance. Furthermore, there is a memory bias for negative information in anxiety. Given the crucial role of working memory in lexical learning, anxious students may encounter more difficulties in learning to read and spell. Anxiety could even affect an earlier learning, that is the activation of phonological representations, which are decisive for the learning of reading and writing. The aim of this study is to compare the access to phonological representations of beginning readers and writers according to their level of anxiety, using an auditory lexical decision task. Eighty students of 6- to 9-years-old completed the French version of the Revised Children's Manifest Anxiety Scale and were then divided into four anxiety groups according to their total score (Low, Median-Low, Median-High and High). Two set of eighty-one stimuli (words and non-words) have been auditory presented to these students by means of a laptop computer. Stimuli words were selected according to their emotional valence (positive, negative, neutral). Students had to decide as quickly and accurately as possible whether the presented stimulus was a real word or not (lexical decision). Response times and accuracy were recorded automatically on each trial. It was anticipated a) longer response times for the Median-High and High anxiety groups in comparison with the two others groups, b) faster response times for negative-valence words in comparison with positive and neutral-valence words only for the Median-High and High anxiety groups, c) lower response accuracy for Median-High and High anxiety groups in comparison with the two others groups, d) better response accuracy for negative-valence words in comparison with positive and neutral-valence words only for the Median-High and High anxiety groups. Concerning the response times, our results showed no difference between the four groups. Furthermore, inside each group, the average response times was very close regardless the emotional valence. Otherwise, group differences appear when considering the error rates. Median-High and High anxiety groups made significantly more errors in lexical decision than Median-Low and Low groups. Better response accuracy, however, is not found for negative-valence words in comparison with positive and neutral-valence words in the Median-High and High anxiety groups. Thus, these results showed a lower response accuracy for above-median anxiety groups than below-median groups but without specificity for the negative-valence words. This study suggests that anxiety can negatively impact the lexical processing in young students. Although the lexical processing speed seems preserved, the accuracy of this processing may be altered in students with moderate or high level of anxiety. This finding has important implication for the prevention of reading and spelling difficulties. Indeed, during these learnings, if anxiety affects the access to phonological representations, anxious students could be disturbed when they have to match phonological representations with new orthographic representations, because of less efficient lexical representations. This study should be continued in order to precise the impact of anxiety on basic school learning.

Keywords: anxiety, emotional valence, childhood, lexical access

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Authors: Zelalem Abebe Bekele, Kun Lei, Xiukai Lan, Xiangyu Liu, Hui Wen, Kaiyou Wang

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Spin-polarized currents offer an efficient means of manipulating the magnetization of a ferromagnetic layer for big data and neuromorphic computing. Research has shown that the orbital Hall effect (OHE) can produce orbital currents, potentially surpassing the counter spin currents induced by the spin Hall effect. However, it’s essential to note that orbital currents alone cannot exert torque directly on a ferromagnetic layer, necessitating a conversion process from orbital to spin currents. Here, we present an efficient method for achieving perpendicularly magnetized spin-orbit torque (SOT) switching by harnessing the localized orbital Hall current generated from a Mo layer within a Mo/CoGd device. Our investigation reveals a remarkable enhancement in the interface-induced planar Hall effect (PHE) within the Mo/CoGd bilayer, resulting in the generation of a z-polarized planar current for manipulating the magnetization of CoGd layer without the need for an in-plane magnetic field. Furthermore, the Mo layer induces out-of-plane orbital current, boosting the in-plane and out-of-plane spin polarization by converting the orbital current into spin current within the dual-property CoGd layer. At the optimal Mo layer thickness, a low critical magnetization switching current density of 2.51×10⁶ A cm⁻² is achieved. This breakthrough opens avenues for all-electrical control energy-efficient magnetization switching through orbital current, advancing the field of spin-orbitronics.

Keywords: spin-orbit torque, orbital hall effect, spin hall current, orbital hall current, interface-generated planar hall current, anisotropic magnetoresistance

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Authors: Omid Khandel, Azadeh Parvin

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An increase in accidental explosions in recent years has increased the interest on investigating the response and behavior of structures in more details. The present work focused on finite element analysis of multistory steel frame structures with different plan shapes subjected to blast loadings. In order to study the effect of the geometry of the building, three different shapes for the plan of the building were modeled and studied; Rectangular, Square and L shape plans. The nonlinear dynamic analysis was considered in this study. The relocation technique was also used to improve the behavior of structure. The accuracy of the multistory frame model was confirmed with those of the existing study in the literature and they were in good agreement. The effect of span length of the buildings was also considered. Finite element analysis of various scenarios for relocating the plastic hinges and improving the response of the structure was performed. The base shear versus displacement curves were compared to reveal the best possible scenarios to provide recommendations to designers and practitioners.

Keywords: nonlinear dynamic analysis, plastic hinge relocation, Retrofit, SAP2000

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Authors: Alireza Vakili, Shahab Ehtesham, Mohsen Danesh Mesgaran, Mahdi Paktinat

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The goal of this study is to determine the chemical compounds of brown Iranian propolis(BIP) extracts and to show flavonoids and phenol effects on nitrogen ammonia (NH3-N) in in vitro. Experimental samples were including two diets with different concentrate: forage ratio (80:20 and 60:40) with eight treatments (1:Control diet 60:40 without BIP,2: 60:40 diet with 25% BIP, 3:60:40 diet with 50% BIP, 4: 60:40 diet with 75% BIP,5: Control diet 80:20 without BIP,6: 80:20 diet with 25% BIP,7: 80:20 diet with 50% BIP and 8: 80:20 diet with 75% BIP) and eight repeats. The trial was analyzed considering a completely randomized design by the GLM procedure of SAS 9.1. Means among treatment were compared by Tukey test. The results of this study showed that in food with 80:20 (concentrate: forage), adding BIP 25% did not statistically change NH3-N (p > 0.05) compared to the control treatment but there was a significant difference (p < 0.05) between the effect of BIP 50% on NH3-N compared to the BIP 25% and the control. In diet with 60:40 (concentrate: forage), there was no significant difference between the effect of BIP 25% on NH3-N and the control, nor was there a significant difference between the effect of BIP 50% and 75%, while a significant difference (p < 0.05) between BIP 50% and 75% and the rest was observed. The propolis extract makes nitrogen ammonia decrease. This may help the nitrogen retain longer in ruminants.

Keywords: brown Iranian propolis, in vitro, nitrogen ammonia, ruminant

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Authors: Morolake Josephine Adeagbo

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South Africa is one of those countries that openly rejected racism, and this is entrenched in its Bill of Rights. Despite the acceptance and incorporation of racial integration into the South Africa Constitution, the implementation within some sectors, most especially the educational sector, seems difficult. Recent occurrences of racism in some higher institutions of learning in South Africa are indications that racial integration / racial transformation is still farfetched in the country’s higher educational sector. It is against this background that this study was conducted to understand how gender and residential background influence racial integration in a South African university which was predominantly a white Afrikaner institution. Using a quantitative method to test the attitude of different categories of undergraduate students at the university, this study found that the factors- residential background and gender- used in measuring student’s attitude do not necessarily have a significant relationship towards racial integration. However, this study concludes with a call for more research with a range of other factors in order to better understand how racial integration can be promoted in South African institutions of higher learning.

Keywords: racial integration, gender, residential background, transformation

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Authors: Farokh Alipour, Ali Falavand, Neda Beit Saeid

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The calculation of the effect of accidental releases of flammable materials such as LNG requires the use of a suitable consequence model. This study is due to providing a planning advice for developments in the vicinity of LNG sites and other sites handling flammable materials. In this paper, an applicable algorithm that is able to model pool fires on water is presented and applied to estimate pool fire damage zone. This procedure can be used to model pool fires on land and could be helpful in consequence modeling and domino effect zone measurements of flammable materials which is needed in site selection and plant layout.

Keywords: LNG, pool fire, spill, radiation

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Authors: Mabruka S. Elashheb, Adullah Ali Bakush

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Schizophrenia is referred to as a disorder, not a disease, because there has not been any clear, reliable, and specific etiological factor. Even if schizophrenia is not a very frequent disease, it is among the most burdensome and costly illnesses worldwide. Prevention of relapse is a major goal of maintenance treatment in patients with psychotic disorders. We performed a comparison of a newer, atypical antipsychotic drug, Risperidone, and an older, conventional neuroleptic drug, Haloperidol, in terms of the effect on the usual kidney and liver functions and negative and positive symptoms in patients with schizophrenia and schizoaffective disorder after three and five weeks of their treatments. It is apparent from the comparative data of Haloperidol and Risperidone treatments in schizophrenic patients that Resperidone had superior improvement of negative and positive symptoms of patients, no harmful effect on liver and kidney functions and greater efficacy and faster recovery from schizophrenic symptoms in patients. On the basis of our findings of the present study, we concluded that treatment with Risperidone is superior to Haloperidol in reducing the risk of relapse among outpatients with schizophrenic disorders.

Keywords: schizophrenia, Haloperidol, Risperidone, positive and negative symptom

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Authors: Mohammad Javad Mollakazemi, Farhad Asadi, Aref Ghafouri

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In this paper, we considered and applied parametric modeling for some experimental data of dynamical system. In this study, we investigated the different distribution of output measurement from some dynamical systems. Also, with variance processing in experimental data we obtained the region of nonlinearity in experimental data and then identification of output section is applied in different situation and data distribution. Finally, the effect of the spanning the measurement such as variance to identification and limitation of this approach is explained.

Keywords: Gaussian process, nonlinearity distribution, particle filter, system identification

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Authors: Mohini Mohamed, Nurul Huda Mas’od

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This study was aimed at designing and developing an assistive mathematical teaching aid (courseware) in helping dyslexic students in learning multiplication. Computers and multimedia interactive courseware has benefits students in terms of increase learner’s motivation and engage them to stay on task in classroom. Most disability student has short attention span thus with the advantage offered by multimedia interactive courseware allows them to retain the learning process for longer period as compared to traditional chalk and talk method. This study was conducted in a public school at a primary level with the help of three special education teachers and six dyslexic students as participants. Qualitative methodology using interview with special education teachers and observations in classes were conducted. The development of the multimedia interactive courseware in this study was divided to three processes which were analysis and design, development and evaluation. The courseware was evaluated by using User Acceptance Survey Form and interview. Feedbacks from teachers were used to alter, correct and develop the application for a better multimedia interactive courseware.

Keywords: disability students, dyslexia, mathematics teaching aid, multimedia interactive courseware

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Authors: Mohammad Javad Mollakazemi, Farhad Asadi, Aref Ghafouri

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Performance of different filtering approaches depends on modeling of dynamical system and algorithm structure. For modeling and smoothing the data the evaluation of posterior distribution in different filtering approach should be chosen carefully. In this paper different filtering approaches like filter KALMAN, EKF, UKF, EKS and smoother RTS is simulated in some trajectory tracking of path and accuracy and limitation of these approaches are explained. Then probability of model with different filters is compered and finally the effect of the noise variance to estimation is described with simulations results.

Keywords: Gaussian approximation, Kalman smoother, parameter estimation, noise variance

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Authors: E. Kuley, M. Durmuş, E. Balikci, G. Ozyurt, Y. Uçar, F. Kuley, F. Ozogul, Y. Ozogul

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Ammonia and biogenic amine production of fish spoilage bacteria in sardine infusion decarboxylase broth and antimicrobial effect of olive by products (olive leaf extract:OL, olive cake: OC and black water:BW) was monitored using HPLC method. Fish spoilage bacteria produced all biogenic amine tested, mainly histamine and serotonin. Ammonia was accumulated more than 13.60 mg/L. Histamine production was in range 37.50 mg/L by Ser. liquefaciens and 86.71 mg/L by Ent. cloacae. The highest putrescine and cadaverine production was observed by Ent. cloacae (17.80 vs. 17.69 mg/L). The presence of OL, OC and BW in the broth significantly affected biogenic amine accumulation by bacteria. The antibacterial effect of olive by products depended on bacterial strains. OL and OC resulted in significant inhibition effect on HIS accumulation by bacteria apart from Ser. liquefaciens and Prot. mirabilis. The study result revealed that usefulness of OL and OC to prevent the accumulation of this amine which may affect human health.

Keywords: Antimicrobials, biogenic amine, fish spoilage bacteria, olive-by products

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Authors: Pradeep Singh, Shrish Verma

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Software fault prediction models are created by using the source code, processed metrics from the same or previous version of code and related fault data. Some company do not store and keep track of all artifacts which are required for software fault prediction. To construct fault prediction model for such company, the training data from the other projects can be one potential solution. The earlier we predict the fault the less cost it requires to correct. The training data consists of metrics data and related fault data at function/module level. This paper investigates fault predictions at early stage using the cross-project data focusing on the design metrics. In this study, empirical analysis is carried out to validate design metrics for cross project fault prediction. The machine learning techniques used for evaluation is Naïve Bayes. The design phase metrics of other projects can be used as initial guideline for the projects where no previous fault data is available. We analyze seven data sets from NASA Metrics Data Program which offer design as well as code metrics. Overall, the results of cross project is comparable to the within company data learning.

Keywords: software metrics, fault prediction, cross project, within project.

Procedia PDF Downloads 328

Authors: Nikolaos Konstantopoulos, Aristeidis Samitas, Vasileiou Evangelos

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The purpose of this study is to examine if the financial trends influence not only the stock markets’ returns, but also their anomalies. We choose to study the day of the week effect (DOW) for the Greek stock market during the Euro period (2002-12), because during the specific period there are not significant structural changes and there are long term financial trends. Moreover, in order to avoid possible methodological counterarguments that usually arise in the literature, we apply several linear (OLS) and nonlinear (GARCH family) models to our sample until we reach to the conclusion that the TGARCH model fits better to our sample than any other. Our results suggest that in the Greek stock market there is a long term predisposition for positive/negative returns depending on the weekday. However, the statistical significance is influenced from the financial trend. This influence may be the reason why there are conflict findings in the literature through the time. Finally, we combine the DOW’s empirical findings from 1985-2012 and we may assume that in the Greek case there is a tendency for long lived turn of the week effect.

Keywords: day of the week effect, GARCH family models, Athens stock exchange, economic growth, crisis

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Authors: Elnaz Lashgari, Emel Demircan

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Electromyography (EMG) is one of the most important interfaces between humans and robots for rehabilitation. Decoding this signal helps to recognize muscle activation and converts it into smooth motion for the robots. Detecting each muscle’s pattern during walking and running is vital for improving the quality of a patient’s life. In this study, EMG data from 10 muscles in 10 subjects at 4 different speeds were analyzed. EMG signals are nonlinear with high dimensionality. To deal with this challenge, we extracted some features in time-frequency domain and used manifold learning and Laplacian Eigenmaps algorithm to find the intrinsic features that represent data in low-dimensional space. We then used the Bayesian classifier to identify various patterns of EMG signals for different muscles across a range of running speeds. The best result for vastus medialis muscle corresponds to 97.87±0.69 for sensitivity and 88.37±0.79 for specificity with 97.07±0.29 accuracy using Bayesian classifier. The results of this study provide important insight into human movement and its application for robotics research.

Keywords: electromyography, manifold learning, ISOMAP, Laplacian Eigenmaps, locally linear embedding

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Authors: Kunto Nurcahyoko

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The fundamental perception used in this study is that teaching and learning activities in Indonesian classroom have potentially generated individual’s sensitivity on cross-cultural understanding. This study aims at investigating Indonesian university students’ perception on cross-cultural understanding after doing Cultural Snapshot Project. The data was critically analyzed through multicultural ideology and diversity theories. The subjects were 30 EFL college students in one of colleges in Indonesia. Each student was assigned to capture a photo which depicted the existence of any cultural manifestation in their surrounding such as discrimination, prejudice and stereotype. Students were then requested asked to reflect on the picture by writing a short description on the picture and make an exhibition using their pictures. In the end of the project, students were instructed to fill in questionnaires to show their perception before and after the project. The result reveals that Cultural Snapshot Project has given the opportunity for the students to better realize cross-cultural understanding in their environment. In conclusion, the study shows that Cultural Snapshot Project has specifically enhanced students’ perception of multiculturalism in three major areas: cultural sensitivity and empathy, social tolerance, and understanding of diversity.

Keywords: cultural snapshot, cross-cultural understanding, students’ perception, multiculturalism

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Authors: Lazic Marina, Sugden Scott, Sharma Kanta Hem, Sauvageau Dominic, Stein Lisa

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Methane is a highly potent greenhouse gas mostly released through anthropogenic activities. Methane represents a low-cost and sustainable feedstock used for the biological production of value-added compounds by bacteria known as methanotrophs. In addition to methane, these organisms can utilize methanol, another cheap carbon source that is a common industrial by-product. Alphaproteobacteria methanotrophs can utilize both methane and methanol to produce the biopolymer polyhydroxybutyrate. The goal of this study was to examine the effect of methanol on polyhydroxybutyrate production in Methylocystis sp. Rockwell and to identify the optimal methane: methanol ratio that will improve PHB without reducing biomass production. Three methane: methanol ratios (4, 2.5., and 0.5) and three nitrogen source (ammonium or nitrate) concentrations (10 mM, 1 mM, and 0.1 mM) were combined to generate 18 growing conditions (9 per carbon source). The production of polyhydroxybutyrate and biomass was analyzed at the end of growth. Overall, the methane: methanol ratios that promoted polyhydroxybutyrate synthesis without reducing biomass were 4 and 2.5 and the optimal nitrogen concentration was 1 mM for both ammonium and nitrate. The physiological mechanism behind the beneficial effect of combining methane and methanol as carbon sources remain to be discovered. One possibility is that methanol has a dual role as a carbon source at lower concentrations and as a stringent response trigger at higher concentrations. Nevertheless, the beneficial effect of methanol and optimal nitrogen concentration for PHB production was confirmed, providing a basis for future physiological analysis and conditions for process scale-up.

Keywords: methane, methanol, methanotrophs, polyhydroxybutyrate, methylocystis sp. rockwell, single carbon bioconversions

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Authors: Busra Ekinci

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Urban heat island term becomes one of the most important problem in urban areas as a reflection of global warming in local scale last years. Many communities and governments are taking action to reduce heat island effects on urban areas where the half of the world's population live today. At this point, urban design turned out to be an important practice and research area for providing an environmentally sensitive urban development. In this study, mitigating strategies of urban heat island effects by urban design are investigated in Aksaray Square and surroundings in Istanbul. Aksaray is an important historical and commercial center of Istanbul, which has an increasing density due to be the node of urban transportation. Also, Istanbul Metropolitan Municipality prepared an urban design project to respond the needs of growing population in the area for 2018. The purpose of the study is emphasizing the importance of urban design objectives and strategies that are developed to reduce the heat island effects on urban areas. Depending on this, the urban heat island effect of the area was examined based on the albedo (reflectivity) parameter which is the most effective parameter in the formation of the heat island effect in urban areas. Albedo values were calculated by Albedo Viewer web application model that was developed by Energy and Environmental Engineering Department of Kyushu University in Japan. Albedo parameter had examined for the present situation and the planned situation with urban design project. The results show that, the current area has urban heat island potential. With the Aksaray Square Project, the heat island effect on the area can be reduced, but would not be completely prevented. Therefore, urban design strategies had been developed to reduce the island effect in addition to the urban design project of the area. This study proves that urban design objectives and strategies are quite effective to reduce the heat island effects, which negatively affect the social environment and quality of life in urban areas.

Keywords: Albedo, urban design, urban heat island, sustainable design

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Authors: M. Imran Hossen Khan, M. Mahiuddin, M. A. Karim

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Drying is a food processing technique where simultaneous heat and mass transfer take place from surface to the center of the sample. Deformation of food materials during drying is a common physical phenomenon which affects the textural quality and taste of the dried product. Most of the plant-based food materials are porous and hygroscopic in nature that contains about 80-90% water in different cellular environments: intercellular environment and intracellular environment. Transport of this cellular water has a significant effect on material deformation during drying. However, understanding of the scale of deformation is very complex due to diverse nature and structural heterogeneity of food material. Knowledge about the effect of transport of cellular water on deformation of material during drying is crucial for increasing the energy efficiency and obtaining better quality dried foods. Therefore, the primary aim of this work is to investigate the effect of intracellular water transport on material deformation during drying. In this study, apple tissue was taken for the investigation. The experiment was carried out using 1H-NMR T2 relaxometry with a conventional dryer. The experimental results are consistent with the understanding that transport of intracellular water causes cellular shrinkage associated with the anisotropic deformation of whole apple tissue. Interestingly, it is found that the deformation of apple tissue takes place at different stages of drying rather than deforming at one time. Moreover, it is found that the penetration rate of heat energy together with the pressure gradient between intracellular and intercellular environments is the responsible force to rupture the cell membrane.

Keywords: heat and mass transfer, food material, intracellular water, cell rupture, deformation

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Authors: Yangzhi Li

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Network transfer of information and performance customization is now a viable method of digital industrial production in the era of Industry 4.0. Robot platforms and network platforms have grown more important in digital design and construction. The pressing need for novel building techniques is driven by the growing labor scarcity problem and increased awareness of construction safety. Robotic approaches in construction research are regarded as an extension of operational and production tools. Several technological theories related to robot autonomous recognition, which include high-performance computing, physical system modeling, extensive sensor coordination, and dataset deep learning, have not been explored using intelligent construction. Relevant transdisciplinary theory and practice research still has specific gaps. Optimizing high-performance computing and autonomous recognition visual guidance technologies improves the robot's grasp of the scene and capacity for autonomous operation. Intelligent vision guidance technology for industrial robots has a serious issue with camera calibration, and the use of intelligent visual guiding and identification technologies for industrial robots in industrial production has strict accuracy requirements. It can be considered that visual recognition systems have challenges with precision issues. In such a situation, it will directly impact the effectiveness and standard of industrial production, necessitating a strengthening of the visual guiding study on positioning precision in recognition technology. To best facilitate the handling of complicated components, an approach for the visual recognition of parts utilizing machine learning algorithms is proposed. This study will identify the position of target components by detecting the information at the boundary and corner of a dense point cloud and determining the aspect ratio in accordance with the guidelines for the modularization of building components. To collect and use components, operational processing systems assign them to the same coordinate system based on their locations and postures. The RGB image's inclination detection and the depth image's verification will be used to determine the component's present posture. Finally, a virtual environment model for the robot's obstacle-avoidance route will be constructed using the point cloud information.

Keywords: robotic construction, robotic assembly, visual guidance, machine learning

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Authors: Kemal Polat

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In this paper, three feature weighting methods have been used to improve the classification performance of diabetic retinopathy (DR). To classify the diabetic retinopathy, features extracted from the output of several retinal image processing algorithms, such as image-level, lesion-specific and anatomical components, have been used and fed them into the classifier algorithms. The dataset used in this study has been taken from University of California, Irvine (UCI) machine learning repository. Feature weighting methods including the fuzzy c-means clustering based feature weighting, subtractive clustering based feature weighting, and Gaussian mixture clustering based feature weighting, have been used and compered with each other in the classification of DR. After feature weighting, five different classifier algorithms comprising multi-layer perceptron (MLP), k- nearest neighbor (k-NN), decision tree, support vector machine (SVM), and Naïve Bayes have been used. The hybrid method based on combination of subtractive clustering based feature weighting and decision tree classifier has been obtained the classification accuracy of 100% in the screening of DR. These results have demonstrated that the proposed hybrid scheme is very promising in the medical data set classification.

Keywords: machine learning, data weighting, classification, data mining

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Authors: Staniek Halina

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The inappropriate trace elements supply such as iron(III) and chromium(III) may be risk factors of many metabolic disorders (e.g., anemia, diabetes, as well cause toxic effect). However, little is known about their mutual interactions and their impact on these disturbances. The effects of Cr(III) supplementation with a deficit or excess supply of Fe(III) in vivo conditions are not known yet. The objective of the study was to investigate the combined effect of different Fe(III) levels in the diet and simultaneous Cr(III) supplementation on the Ca distribution in organs in healthy rats. The assessment was based on a two-factor (2x3) experiment carried out on 54 female Wistar rats (Rattus norvegicus). The animals were randomly divided into 9 groups and for 6 weeks, they were fed semi-purified diets AIN-93 with three different Fe(III) levels in the diet as a factor A [control (C) 45 mg/kg (100% Recommended Daily Allowance for rodents), deficient (D) 5 mg/kg (10% RDA), and oversupply (H) 180 mg/kg (400% RDA)]. The second factor (B) was the simultaneous dietary supplementation with Cr(III) at doses of 1, 50 and 500 mg/kg of the diet. Iron(III) citrate was the source of Fe(III). The complex of Cr(III) with propionic acid, also called Cr₃ or chromium(III) propionate (CrProp), was used as a source of Cr(III) in the diet. The Ca content of analysed samples (liver, kidneys, spleen, heart, and femur) was determined with the Atomic Absorption Spectrometry (AAS) method. It was found that different dietary Fe(III) supply as well as Cr(III) supplementation independently and in combination influenced Ca metabolism in healthy rats. Regardless of the supplementation of Cr(III), the oversupply of Fe(III) (180 mg/kg) decreased the Ca content in the liver and kidneys, while it increased the Ca saturation of bone tissue. High Cr(III) doses lowered the hepatic Ca content. Moreover, it tended to decrease the Ca content in the kidneys and heart, but this effect was not statistically significant. The combined effect of the experimental factors on the Ca content in the liver and the femur was observed. With the increase in the Fe(III) content in the diet, there was a decrease in the Ca level in the liver and an increase in bone saturation, and the additional Cr(III) supplementation intensified those effects. The study proved that the different Fe(III) content in the diet, independently and in combination with Cr(III) supplementation, affected the Ca distribution in organisms of healthy rats.

Keywords: calcium, chromium(III), iron(III), rats, supplementation

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Authors: Jason Maffia, Maria D’urso, Robert Crupi, Margaret Cartmell

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The emotional aspects of traumatic events such as workplace violence are often ignored, causing low productivity, disillusionment, and resentment within an organization. As a result, if workplace violence, particularly in healthcare settings, is not adequately addressed, it will become a phenomenon, undermining the peace and stability among the active communities while also posing a risk to the population's health and well-being. This review intends to identify the risk factors and the implications of workplace violence in healthcare settings and highlight the collaborative efforts needed in sustaining control and prevention measures against workplace violence. It is essential that health care organizations are prepared physically and emotionally for traumatic situations. This study explores the theoretical nature of addressing work-related violence in healthcare settings as well as traumatic stress reactivity and the context within which reactions occur and recovery takes place. Cognitive, social, and organizational influences on response are identified and used to tentatively offer explanations for identifying security risks, development, and implementation of de-escalation teams, CISM programs and training staff in violence prevention are among strategies hospitals are employing to keep workers and patients safe. General conclusion regarding the implications for intervention effectiveness and design are discussed.

Keywords: healthcare settings, stress reactions, traumatic events, workplace violence

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Authors: Ayman M. Othman, Hassan Y. Ahmed

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This paper discusses the effect of using blast furnace iron slag as a part of fine aggregate on the mechanical performance of hot mix asphalt (HMA). The mechanical performance was evaluated based on various mechanical properties that include; Marshall/stiffness, indirect tensile strength and unconfined compressive strength. The effect of iron slag content on the mechanical properties of the mixtures was also investigated. Four HMA with various iron slag contents, namely; 0%, 5%, 10% and 15% by weight of total mixture were studied. Laboratory testing has revealed an enhancement in the compressive strength of HMA when iron slag was used. Within the tested range of iron slag content, a considerable increase in the compressive strength of the mixtures was observed with the increase of slag content. No significant improvement on Marshall/stiffness and indirect tensile strength of the mixtures was observed when slag was used. Even so, blast furnace iron slag can still be used in asphalt paving for environmental advantages.

Keywords: blast furnace iron slag, compressive strength, HMA, indirect tensile strength, marshall/stiffness, mechanical performance, mechanical properties

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Authors: Dawood Al Chanti, Alice Caplier

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Sparse representations of signals have received a great deal of attention in recent years. In this paper, the interest of using sparse representation as a mean for performing sparse discriminative analysis between spontaneous facial expressions is demonstrated. An automatic facial expressions recognition system is presented. It uses a KSVD-SVM approach which is made of three main stages: A pre-processing and feature extraction stage, which solves the problem of shared subspace distribution based on the random projection theory, to obtain low dimensional discriminative and reconstructive features; A dictionary learning and sparse coding stage, which uses the KSVD model to learn discriminative under or over dictionaries for sparse coding; Finally a classification stage, which uses a SVM classifier for facial expressions recognition. Our main concern is to be able to recognize non-basic affective states and non-acted expressions. Extensive experiments on the JAFFE static acted facial expressions database but also on the DynEmo dynamic spontaneous facial expressions database exhibit very good recognition rates.

Keywords: dictionary learning, random projection, pose and spontaneous facial expression, sparse representation

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Authors: Alexandru Gridan, Georgeta Ionescu, Ovidiu Ionescu, Ramon Jurj, George Sirbu, Mihai Fedorca

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The Brown Bear population size in Romania is approximately 7300-7600 individuals, which is projected to be 3000 individuals over the ecological carrying capacity. The Habitats Directive imposed certain protection rules on European Union (EU) Member States with Brown Bear populations. These however allow countries like Sweden, Croatia, Slovakia, Estonia to hunting as management tool, harvesting up to 10% of the surplus bear population annually. From the point Romania joined the EU to 2016, active conservation management has contributed to maintaining the highest and most genetically diverse Brown Bear population in Europe. Importantly, there has been good coexistence between people and bears and low levels of human-bear conflict. After social pressure and campaigning by some non-governmental organisations citing issues over monitoring, the environment minister decided in September 2016 to stop the use of hunting as a management tool for bears. Against this background, this paper provides a set of recommendations to resolve the current conflict in Romania. These include the need for collaborative decision-making to reduce conflicts between stakeholders and mechanisms to reduce current human-bear conflicts, which have increased by 50 percent in the past year.

Keywords: bear, bear population, bear management, wildlife conflict

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Authors: Pei Yi Lin

Abstract:

Objective: The objective of this study is to use machine learning methods to build an early prediction classifier model for acute delirium to improve the quality of medical care for intensive care patients. Background: Delirium is a common acute and sudden disturbance of consciousness in critically ill patients. After the occurrence, it is easy to prolong the length of hospital stay and increase medical costs and mortality. In 2021, the incidence of delirium in the intensive care unit of internal medicine was as high as 59.78%, which indirectly prolonged the average length of hospital stay by 8.28 days, and the mortality rate is about 2.22% in the past three years. Therefore, it is expected to build a delirium prediction classifier through big data analysis and machine learning methods to detect delirium early. Method: This study is a retrospective study, using the artificial intelligence big data database to extract the characteristic factors related to delirium in intensive care unit patients and let the machine learn. The study included patients aged over 20 years old who were admitted to the intensive care unit between May 1, 2022, and December 31, 2022, excluding GCS assessment <4 points, admission to ICU for less than 24 hours, and CAM-ICU evaluation. The CAMICU delirium assessment results every 8 hours within 30 days of hospitalization are regarded as an event, and the cumulative data from ICU admission to the prediction time point are extracted to predict the possibility of delirium occurring in the next 8 hours, and collect a total of 63,754 research case data, extract 12 feature selections to train the model, including age, sex, average ICU stay hours, visual and auditory abnormalities, RASS assessment score, APACHE-II Score score, number of invasive catheters indwelling, restraint and sedative and hypnotic drugs. Through feature data cleaning, processing and KNN interpolation method supplementation, a total of 54595 research case events were extracted to provide machine learning model analysis, using the research events from May 01 to November 30, 2022, as the model training data, 80% of which is the training set for model training, and 20% for the internal verification of the verification set, and then from December 01 to December 2022 The CU research event on the 31st is an external verification set data, and finally the model inference and performance evaluation are performed, and then the model has trained again by adjusting the model parameters. Results: In this study, XG Boost, Random Forest, Logistic Regression, and Decision Tree were used to analyze and compare four machine learning models. The average accuracy rate of internal verification was highest in Random Forest (AUC=0.86), and the average accuracy rate of external verification was in Random Forest and XG Boost was the highest, AUC was 0.86, and the average accuracy of cross-validation was the highest in Random Forest (ACC=0.77). Conclusion: Clinically, medical staff usually conduct CAM-ICU assessments at the bedside of critically ill patients in clinical practice, but there is a lack of machine learning classification methods to assist ICU patients in real-time assessment, resulting in the inability to provide more objective and continuous monitoring data to assist Clinical staff can more accurately identify and predict the occurrence of delirium in patients. It is hoped that the development and construction of predictive models through machine learning can predict delirium early and immediately, make clinical decisions at the best time, and cooperate with PADIS delirium care measures to provide individualized non-drug interventional care measures to maintain patient safety, and then Improve the quality of care.

Keywords: critically ill patients, machine learning methods, delirium prediction, classifier model

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Authors: Eden G. Mariquit, Winarto Kurniawan, Masahiro Miyauchi, Hirofumi Hinode

Abstract:

This research studied the effect of adding surfactant to the titanium dioxide (TiO2) sol-gel solution that was used to immobilize TiO2 on glass substrates by dip coating technique using TiO2 sol-gel solution mixed with different types of surfactants. After dipping into the TiO2 sol, the films were calcined and produced pure anatase crystal phase. The thickness of the thin film was varied by repeating the dip and calcine cycle. The prepared films were characterized using FE-SEM, TG-DTA, and XRD, and its photocatalytic performances were tested on degradation of an organic dye, methylene blue. Aside from its phocatalytic performance, the photo-induced hydrophilicity of thin TiO2 films surface was also studied. Characterization results showed that the addition of surfactant gave rise to characteristic patterns on the surface of the TiO2 thin film which also affects the photocatalytic activity. The addition of CTAB to the TiO2 dipping solution had a negative effect because the calcination temperature was not high enough to burn all the surfactants off. As for the surface wettability, the addition of surfactant also affected the induced surface hydrophilicity of the TiO2 films when irradiated under UV light.

Keywords: photocatalysis, surface hydrophilicity, TiO2 thin films, surfactant

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Authors: Ahmad Abu-Akel, Emilie De Montpellier, Sophie Von Bentivegni, Lyn Luechinger, Alessandro Ishii, Christine Mohr

Abstract:

Convergent and divergent thinking are two main components of creativity that have been viewed as complementary. While divergent thinking refers to the fluency and flexibility of generating new ideas, convergent thinking refers to the ability to systematically apply rules and knowledge to arrive at the optimal solution or idea. These creativity components have been shown to be susceptible to variation in subclinical expressions of autistic and schizotypal traits within the general population. Research, albeit inconclusively, mainly linked positive schizotypal traits with divergent thinking and autistic traits with convergent thinking. However, cumulative evidence suggests that these trait dimensions can co-occur in the same individual more than would be expected by chance and that their concurrent effect can be diametric and even interactive. The current study aimed at investigating the concurrent effect of these trait dimensions on tasks assessing convergent and divergent thinking abilities. We predicted that individuals with high positive schizotypal traits alone would perform particularly well on the divergent thinking task, whilst those with high autistic traits alone would perform particularly well on the convergent thinking task. Crucially, we also predicted that individuals who are high on both autistic and positive schizotypal traits would perform particularly well on both the divergent and convergent thinking tasks. This was investigated in a non-clinical sample of 142 individuals (Males = 45%; Mean age = 21.45, SD = 2.30), sufficient to minimally observe an effect size f² ≥ .10. Divergent thinking was evaluated using the Alternative Uses Task, and convergent thinking with the Anagrams Task. Autistic and schizotypal traits were respectively assessed with the Autism Quotient Questionnaire (AQ) and the Oxford-Liverpool Inventory of Feelings and Experiences (O-LIFE). Regression analyses revealed that the positive association of autistic traits with convergent thinking scores was qualified with an interaction with positive schizotypal traits. Specifically, positive schizotypal traits were negatively associated with convergent thinking scores when AQ scores were relatively low, but this trend was reversed when AQ scores were high. Conversely, the positive effect of AQ scores on convergent thinking progressively increased with increasing positive schizotypal traits. The results of divergent thinking task are currently being analyzed and will be reported at the conference. The association of elevated autistic and positive schizotypal traits with convergent thinking may represent a unique profile of creative thinkers who are able to simultaneously draw on trait-specific advantages conferred by autistic and positively schizotypal traits such as local and global processing. This suggests that main-effect models can tell an incomplete story regarding the effect of autistic and positive schizotypal traits on creativity-related processes. Future creativity research should consider their interaction and the benefits conferred by their co-presence.

Keywords: autism, schizotypy, convergent thinking, divergent thinking, comorbidity

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