Search results for: inflow performance relationship

Authors: Neetu Manocha

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Image segmentation is a technique where a picture is parted into distinct parts having similar features which have a place with similar items. Various segmentation strategies have been proposed as of late by prominent analysts. But, after ultimate thorough research, the novelists have analyzed that generally, the old methods do not decrease the segmentation error rate. Then author finds the technique HIST-SI to decrease the segmentation error rates. In this technique, cluster-based and threshold-based segmentation techniques are merged together. After then, to improve the result of HIST-SI, the authors added the method of filtering and linking in this technique named Imp_HIST-SI to decrease the segmentation error rates. The goal of this research is to find a new technique to decrease the segmentation error rates and produce much better results than the HIST-SI technique. For testing the proposed technique, a dataset of Bhuvan – a National Geoportal developed and hosted by ISRO (Indian Space Research Organisation) is used. Experiments are conducted using Scikit-image & OpenCV tools of Python, and performance is evaluated and compared over various existing image segmentation techniques for several matrices, i.e., Mean Square Error (MSE) and Peak Signal Noise Ratio (PSNR).

Keywords: satellite image, image segmentation, edge detection, error rate, MSE, PSNR, HIST-SI, linking, filtering, imp_HIST-SI

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Authors: Muhammad Rizwan, Naveed Ahmad, Akhtar Naeem Khan

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Seismic behavior factors are evaluated for the performance assessment of low rise reinforced concrete RC frame structures based on experimental study of unidirectional dynamic shake table testing of two 1/3rd reduced scaled two storey frames, with a code confirming special moment resisting frame (SMRF) model and a noncompliant model of similar characteristics but built in low strength concrete .The models were subjected to a scaled accelerogram record of 1994 Northridge earthquake to deformed the test models to final collapse stage in order to obtain the structural response parameters. The fully compliant model was observed with more stable beam-sway response, experiencing beam flexure yielding and ground-storey column base yielding upon subjecting to 100% of the record. The response modification factor - R factor obtained for the code complaint and deficient prototype structures were 7.5 and 4.5 respectively, which is about 10% and 40% less than the UBC-97 specified value for special moment resisting reinforced concrete frame structures.

Keywords: Northridge 1994 earthquake, reinforced concrete frame, response modification factor, shake table testing

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Authors: Chiung-Hua Chan, Fang-Yuan Chang, Li-Chi Huang

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Stroke patients received regular rehabilitation therapy have measurable advancement in muscle strength, balance, control upper and lower physical activity, walking speed and endurance. This study aimed to investigate the relationship between increases in bedside rehabilitation time and the function of activities and daily living (ADL) in stroke patients. The study was quasi-experimental research design and randomized sampling. The researcher collected 12 stroke patients of stroke patients transferred to rehabilitation ward unit of a medical center during 1 January to 31 March 2017. All participants then were assigned to case group and control group. Data collection was through direct observation of assessment ADL of stroke patients by researchers on Day 1. Case group received regular rehabilitation, exercises in increase of bedside rehabilitation schedules exercise programs by ward nurses. Bedside rehabilitation exercise content with physical, functional and linguistic frequency and time, Control group only give routine rehabilitation schedule care. This was a randomized study performed in 12 patients who were stroke patients and transferred to rehabilitation ward unit of a medical center during 1 January to 31 March 2017. First, the researcher explained the purpose and method of the study to the patients or the family members. All participants completed a consent informed before participation. Patients were randomly assigned to a ‘bedside rehabilitation program’ (BRP) group and a control (C) group. The BRP group received bedside rehabilitation schedules exercise programs by ward nurses. while the C group did not. Both groups received routine rehabilitation schedule. The Functional Independence Measure was used to measure outcome at the first, 14th and the 28th day of rehabilitation ward admitted. Data were analyzed using SPSS 22.0. After implementation of standardized ‘‘bedside rehabilitation program’, the results were: (1) the increasing of bedside rehabilitation had significant difference (p<.05) in promotion ADL function of stroke patients (2) the extend time of the bedside rehabilitation has significant difference (p<.05) in promotion ADL function of stroke patients compared with the control group. This study demonstrated that the ‘bedside rehabilitation program’ enhanced the ADL function in stroke patients. The nurses and rehabilitation ward managers need to understand that the extend time and frequency of rehabilitation provide a chance to enhanced the ADL function of stroke patients.

Keywords: stroke, bedside rehabilitation, functional activity, ADL

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Authors: N. Sena, C. Vasconcelos

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Portugal has a lower rate of people who exercise. Fitness centers are a widely recognized context for the performance of an exercise. Thus, the objective of this study is to analyze the motivational factors for the practice of exercise in a sample of Portuguese fitness center users. The sample consists of 34 users (23 men and 11 women), aged between 16 and 60 years old (24.7 ± 11,5 years old). The instrument used for data collection was the Motivation Questionnaire for Exercise (version translated and validated into Portuguese), consisting of forty-nine items grouped into ten motivational factors. Responses to the Exercise Motivation Questionnaire are given on a 6-point Likert scale (0="not at all true for me" to 5="completely true for me"). With regard to the results, it is possible to verify that the motivational factors considered most relevant by the sample of our study were “Well-being” (4.44 ± 0.28), followed by “Health” (4.29 ± 0.57) and “Stress Management” (4.06 ± 0.54). The factors “Affiliation” (3.11 ± 0.49) “Personal Appreciation” (2.26 ± 0.59) and “Medical History” (1.71 ± 0.74) were considered by the respondents to be the least important factors for performing the exercise. The conclusion of this study is that in the sample of this study, the factors that most motivated the practice of exercise were “Well-being”, “Health” and “Stress Management”. In the opposite direction, the factors that least motivated the individuals in this sample to practice exercise were “Affiliation”, “Personal Appreciation” and “Medical History”.

Keywords: exercise, fitness center users, motivational factors, Portugal

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Authors: Rasha Saad, Jean Frederic Weber, Fatimah Bebe, Sadia Sultan

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The goal of study was to screen the effects of candesartan and four endophytic fungi for their potential in microbial biotransformation. In this experiment, four types of unidentified fungi with the codes of TH2L1, TH2R10, TH1P35 and TH1S46 were used in screening process by MECFUS (Microtiter plate, Elicitors, Combination, Freeze-drying, UHPLC, Statistical analysis) protocol. The experiment was carried out by using 96-well microtiter plate (MTP) with different media and elicitors. Various media with two concentrations of Potato Dextrose Broth (PDB) and elicitors used were to induce the production of secondary metabolites from the fungi as well as the biotransformation of the drug compound. After incubation, cultures were extracted by freeze drying method and finally analyzed by ultra-High performance Liquid Chromatography (uHPLC). The extracts analyzed by uHPLC followed by LC/Ms, demonstrated the presence of biotransformation products from the drug compound and elicitation of the secondary metabolism from the fungi by the occurrence of the additional peaks. From the four fungi, TH1S46 showed highly potential produced secondary metabolites as well as the biotransformation of candesartan. For other fungi, they responded when candesartan was introduced. Moreover, the additional peaks produced in uHPLC need to be further investigation by using LC-MS or NMR.

Keywords: biotransformation, candesartan, endophytes, secondary metabolites

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Authors: Shonak Bansal, Prince Jain, Arun Kumar Singh, Neena Gupta

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Recently nature–inspired algorithms have widespread use throughout the tough and time consuming multi–objective scientific and engineering design optimization problems. In this paper, we present extended forms of firefly algorithm to find optimal Golomb ruler (OGR) sequences. The OGRs have their one of the major application as unequally spaced channel–allocation algorithm in optical wavelength division multiplexing (WDM) systems in order to minimize the adverse four–wave mixing (FWM) crosstalk effect. The simulation results conclude that the proposed optimization algorithm has superior performance compared to the existing conventional computing and nature–inspired optimization algorithms to find OGRs in terms of ruler length, total optical channel bandwidth and computation time.

Keywords: channel allocation, conventional computing, four–wave mixing, nature–inspired algorithm, optimal Golomb ruler, lévy flight distribution, optimization, improved multi–objective firefly algorithms, Pareto optimal

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Authors: Ashraf Aly

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The aim of this study is to examine the impact of 5G communication technology radiation on human health and airport safety. The term 5G refers to the fifth generation of wireless mobile technology. The 5G wireless technology will increase the number of high-frequency-powered base stations and other devices and browsing and download speeds, as well as improve the network connectivity and play a big part in improving the performance of integrated applications, such as self-driving cars, medical devices, and robotics. 4G was the latest embedded version of mobile networking technology called 4G, and 5G is the new version of wireless technology. 5G networks have more features than 4G networks, such as lower latency, higher capacity, and increased bandwidth compared to 4G. 5G network improvements over 4G will have big impacts on how people live, business, and work all over the world. But neither 4G nor 5G have been tested for safety and show harmful effects from this wireless radiation. This paper presents biological factors on the effects of 5G radiation on human health. 5G services use C-band radio frequencies; these frequencies are close to those used by radio altimeters, which represent important equipment for airport and aircraft safety. The aviation industry, telecommunications companies, and their regulators have been discussing and weighing these interference concerns for years.

Keywords: wireless communication, radiofrequency, Electromagnetic field, environmental issues

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Authors: Ahmet Y. Gurkan, Cagatay S. Koksal, Cagri Aydin, U. Oral Unal

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The present paper covers the viscous flow computations for the asymmetric diffuser section of a large, high-speed cavitation tunnel which will be constructed in Istanbul Technical University. The analyses were carried out by using the incompressible Reynold-Averaged-Navier-Stokes equations. While determining the diffuser geometry, a high quality, separation-free flow field with minimum energy loses was particularly aimed. The expansion angle has a critical role on the diffuser hydrodynamic performance. In order obtain a relatively short diffuser length, due to the constructive limitations, and hydrodynamic energy effectiveness, three diffuser sections with varying expansion angles for side and bottom walls were considered. A systematic study was performed to determine the most effective diffuser configuration. The results revealed that the inlet condition of the diffuser greatly affects its flow field. The inclusion of the contraction section in the computations substantially modified the flow topology in the diffuser. The effect of the diffuser flow on the test section flow characteristics was clearly observed. The influence of the introduction of small chamfers at the corners of the diffuser geometry is also presented.

Keywords: asymmetric diffuser, diffuser design, cavitation tunnel, viscous flow, computational fluid dynamics (CFD), rans

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Authors: Siddharth Ojha, Varun Dua

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Classified as one of the most important reasons of aerodynamic drag in the sedan automobiles is the fluid flow separation near the vehicle’s rear end. To retard the separation of flow, bump-shaped vortex generators are being tested for its implementation to the roof end of a sedan vehicle. Frequently used in the aircrafts to prevent the separation of fluid flow, vortex generators themselves produce drag, but they also substantially reduce drag by preventing flow separation at the downstream. The net effects of vortex generators can be calculated by summing the positive and negative impacts and effects. Since this effect depends on dimensions and geometry of vortex generators, those present on the vehicle roof are optimized for maximum efficiency and performance. The model was tested through ANSYS CFD analysis and modeling. The model was tested in the wind tunnel for observing it’s properties such as aerodynamic drag and flow separation and a major time lag was gained by employing vortex generators in the scaled model. Major conclusions which were recorded during the analysis were a substantial 24% reduction in the aerodynamic drag and 14% increase in the efficiency of the sedan automobile as the flow separation from the surface is delayed. This paper presents the results of optimization, the effect of vortex generators in the flow field and the mechanism by which these effects occur and are regulated.

Keywords: aerodynamics, aerodynamic devices, body, computational fluid dynamics (CFD), flow visualization

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Authors: Xiang Shijie, Zhou Dong, Tian Dan

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Speaker recognition is a crucial task in the field of speech processing, aimed at identifying individuals based on their vocal characteristics. However, existing speaker recognition methods face numerous challenges. Traditional methods primarily rely on audio signals, which often suffer from limitations in noisy environments, variations in speaking style, and insufficient sample sizes. Additionally, relying solely on audio features can sometimes fail to capture the unique identity of the speaker comprehensively, impacting recognition accuracy. To address these issues, we propose a multi-modal network architecture that simultaneously processes both audio and text signals. By gradually integrating audio and text features, we leverage the strengths of both modalities to enhance the robustness and accuracy of speaker recognition. Our experiments demonstrate significant improvements with this multi-modal approach, particularly in complex environments, where recognition performance has been notably enhanced. Our research not only highlights the limitations of current speaker recognition methods but also showcases the effectiveness of multi-modal fusion techniques in overcoming these limitations, providing valuable insights for future research.

Keywords: feature fusion, memory network, multimodal input, speaker recognition

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Authors: Mohd Naqiuddin Bin Husri, Siti Rahmah Abd Rahman, Dalilah Abu Bakar, Dayang Izawati Abang Masli, Meilina Ong Abdullah

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A serious shortage of prime agricultural land coupled with environmental concerns inland expansion has daunted efforts to increase the national yield average. To address this issue, maximising yield per unit hectare through quality planting material is of great importance. Breeding for improved planting materials has been a continuous effort since the early days of this industry, it is time-consuming, and the likelihood of segregation within the progenies further impedes progress in this area. Incorporation of the cloning technology in oil palm breeding programmes is therefore advantageous to expedite the development of commercial elite and high-yielding planting materials. After more than 22 years of research and development through this project, reliable protocols for liquid/suspension culture systems coupled with various innovative technologies which are effective at promoting proliferation and growth of oil palm culture have been established. Subsequently, clonal palms derived from the suspension culture system were extensively studied in the field, and the results have been encouraging. Clones such as CPS1, CPS2 and a few others recorded superior performance in comparison with D x P standard crosses.

Keywords: tissue culture, suspension culture, oil palm, Elaeis guineensis

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Authors: Dessie Tibebe, Muluken Asmare, Marye Mulugeta, Yezbie Kassa, Zerubabel Moges, Dereje Yenealem, Tarekegn Fentie, Agmas Amare

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The performance of electrocoagulation (EC) using Aluminium electrodes for the treatment of effluent-containing chromium metal using a fixed bed electrochemical batch reactor was studied. In the present work, the efficiency evaluation of EC in removing physicochemical and heavy metals from real industrial tannery wastewater in the Amhara region, collected from Bahirdar, Debre Brihan, and Haik, was investigated. The treated and untreated samples were determined by AAS and ICP OES spectrophotometers. The results indicated that selected heavy metals were removed in all experiments with high removal percentages. The optimal results were obtained regarding both cost and electrocoagulation efficiency with initial pH = 3, initial concentration = 40 mg/L, electrolysis time = 30 min, current density = 40 mA/cm2, and temperature = 25oC favored metal removal. The maximum removal percentages of selected metals obtained were 84.42% for Haik, 92.64% for Bahir Dar and 94.90% for Debre Brihan. The sacrificial electrode and sludge were characterized by FT-IR, SEM and XRD. After treatment, some metals like chromium will be used again as a tanning agent in leather processing to promote a circular economy.

Keywords: electrochemical, treatment, aluminum, tannery effluent

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Authors: Jiawen Wang, Qijun Chen

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The performance of most machine-learning methods for image inpainting depends on the quantity and quality of the training samples. However, it is very expensive or even impossible to obtain a great number of training samples in many scenarios. In this paper, an image inpainting model based on a generative adversary network (GAN) is constructed for the cases when the number of training samples is small. Firstly, a feature extraction network (F-net) is incorporated into the GAN network to utilize the available information of the inpainting image. The weighted sum of the extracted feature and the random noise acts as the input to the generative network (G-net). The proposed network can be trained well even when the sample size is very small. Secondly, in the phase of the completion for each damaged image, a genetic algorithm is designed to search an optimized noise input for G-net; based on this optimized input, the parameters of the G-net and F-net are further learned (Once the completion for a certain damaged image ends, the parameters restore to its original values obtained in the training phase) to generate an image patch that not only can fill the missing part of the damaged image smoothly but also has visual semantics.

Keywords: image inpainting, generative adversary nets, genetic algorithm, small-sample size

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Authors: Philipp Ruf, Massiwa Chabbi, Christoph Reich, Djaffar Ould-Abdeslam

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In recent years, convolutional neural networks (CNN) have demonstrated high performance in image analysis, but oftentimes, there is only structured data available regarding a specific problem. By interpreting structured data as images, CNNs can effectively learn and extract valuable insights from tabular data, leading to improved predictive accuracy and uncovering hidden patterns that may not be apparent in traditional structured data analysis. In applying a single neural network for analyzing multimodal data, e.g., both structured and unstructured information, significant advantages in terms of time complexity and energy efficiency can be achieved. Converting structured data into images and merging them with existing visual material offers a promising solution for applying CNN in multimodal datasets, as they often occur in a medical context. By employing suitable preprocessing techniques, structured data is transformed into image representations, where the respective features are expressed as different formations of colors and shapes. In an additional step, these representations are fused with existing images to incorporate both types of information. This final image is finally analyzed using a CNN.

Keywords: CNN, image processing, tabular data, mixed dataset, data transformation, multimodal fusion

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Authors: Ajda Osifo, Fatma Elshafie

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Mobile-assisted language learning favors social-constructivist and connectivist theories to learning and adaptive approaches to teaching. It offers many opportunities to differentiated instruction in meaningful ways as it enables learners to become more collaborative, engaged and independent through additional dimensions such as web-based media, virtual learning environments, online publishing to an imagined audience and digitally mediated communication. MALL applications can be a tool for the teacher to personalize and adjust instruction according to the learners’ needs and give continuous feedback to improve learning and performance in the process, which support differentiated instruction practices. This paper explores the utilization of Mobile Assisted Language Learning applications as a supporting tool for effective differentiation in the language classroom. It reports overall experience in terms of implementing MALL to shape and apply differentiated instruction and expand learning options. This session is structured in three main parts: first, a review of literature and effective practice of academically responsive instruction will be discussed. Second, samples of differentiated tasks, activities, projects and learner work will be demonstrated with relevant learning outcomes and learners’ survey results. Finally, project findings and conclusions will be given.

Keywords: academically responsive instruction, differentiation, mobile learning, mobile-assisted language learning

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Authors: Amal A. Hassan, Faten H. Fahmy, Abd El-Shafy A. Nafeh, Hosam K. M. Youssef

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Due to the growing penetration of wind energy into the power grid, it is very important to study its interactions with the power system and to provide good control technique in order to deliver high quality power. In this paper, an intelligent control methodology is proposed for optimizing the controllers’ parameters of doubly fed induction generator (DFIG) based wind turbine generation system (WTGS). The genetic algorithm (GA) and particle swarm optimization (PSO) are employed and compared for the parameters adaptive tuning of the proposed proportional integral (PI) multiple controllers of the back to back converters of the DFIG based WTGS. For this purpose, the dynamic model of WTGS with DFIG and its associated controllers is presented. Furthermore, the simulation of the system is performed using MATLAB/SIMULINK and SIMPOWERSYSTEM toolbox to illustrate the performance of the optimized controllers. Finally, this work is validated to 33-bus test radial system to show the interaction between wind distributed generation (DG) systems and the distribution network.

Keywords: DFIG wind turine, intelligent control, distributed generation, particle swarm optimization, genetic algorithm

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Authors: Shruti Sakarkar, Jega Jegatheesan, Srinivasan Madapusi

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Photocatalytic membranes have shown great potential for the removal of an organic and inorganic pollutant from wastewater as it combines the degradation and antibacterial properties from photocatalysis and physical separation by the membrane in a single unit. Incorporation of the semiconductor in membrane structure results in enhancing the performance and the properties of the membrane. In this study porous ultrafiltration polyvinylidene fluoride (PVDF) membranes with entrapped TiO₂ nanoparticle were prepared by phase inversion method and further used for the degradation of reactive orange 16 (RO16). Prepared photocatalytic membranes were characterized by the scanning electron microscope (SEM), energy dispersive spectroscopy (EDS), contact angle, and atomic force microscope (AFM). The addition of TiO₂ nanopartparticles improves the strength and thermal stability of the membrane. In particular hydrophilicity and permeability increases with the increase of TiO₂ nanoparticles into the membrane. The photocatalytic membrane achieves 80-85% degrdation of RO16. The impact of different parameters such as pH, concentration of photocatalyst, dye concentration and effect of H₂O₂ were analysed. The best conditions for dye degradation were an initial dye concentration of 50 mg/L, with a membrane containing TiO₂ loading of 2wt%. It was observed that in the presence of H₂O₂, degradation increases with increasing H₂O₂ concentration and reached up to 95-98%. The high quality permeates obtained from the photocatalytic membrane can be reused.

Keywords: photocatalytic membrane, TiO₂, PVDF, nanoparticles

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Authors: Lawrence Mzukisi Madikizela, Luke Chimuka

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Removal of organics from wastewater offers a better water quality, therefore, the purpose of this work was to investigate the use of molecularly imprinted polymer (MIP) for the elimination of selected organics from water. A multi-template MIP for the adsorption of naproxen, ibuprofen and diclofenac was synthesized using a bulk polymerization method. A MIP was synthesized at 70°C by employing 2-vinylpyridine, ethylene glycol dimethacrylate, toluene and 1,1’-azobis-(cyclohexanecarbonitrile) as functional monomer, cross-linker, porogen and initiator, respectively. Thermogravimetric characterization indicated that the polymer backbone collapses at 250°C and scanning electron microscopy revealed the porous and roughness nature of the MIP after elution of templates. The performance of the MIP in aqueous solutions was evaluated by optimizing several adsorption parameters. The optimized adsorption conditions were 50 mg of MIP, extraction time of 10 min, a sample pH of 4.6 and the initial concentration of 30 mg/L. The imprinting factors obtained for naproxen, ibuprofen and diclofenac were 1.25, 1.42, and 2.01, respectively. The order of selectivity for the MIP was; diclofenac > ibuprofen > naproxen. MIP showed great swelling in water with an initial swelling rate of 2.62 g/(g min). The synthesized MIP proved to be able to adsorb naproxen, ibuprofen and diclofenac from contaminated deionized water, wastewater influent and effluent.

Keywords: adsorption, molecularly imprinted polymer, multi template, pharmaceuticals

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Authors: Khalaf Khatatneh, Nabeel Al-Milli, Amjad Hudaib, Monther Ali Tarawneh

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Software fault prediction identify potential faults in software modules during the development process. In this paper, we present a novel approach for software fault prediction by combining a feedforward neural network with particle swarm optimization (PSO). The PSO algorithm is employed as a feature selection technique to identify the most relevant metrics as inputs to the neural network. Which enhances the quality of feature selection and subsequently improves the performance of the neural network model. Through comprehensive experiments on software fault prediction datasets, the proposed hybrid approach achieves better results, outperforming traditional classification methods. The integration of PSO-based feature selection with the neural network enables the identification of critical metrics that provide more accurate fault prediction. Results shows the effectiveness of the proposed approach and its potential for reducing development costs and effort by detecting faults early in the software development lifecycle. Further research and validation on diverse datasets will help solidify the practical applicability of the new approach in real-world software engineering scenarios.

Keywords: feature selection, neural network, particle swarm optimization, software fault prediction

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Authors: Amelyn M. Ambal, Jose Hermis Patricio

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A macro-somatic clonal propagation study was undertaken to determine the effects of method of propagation, rooting hormone, and level of rooting hormone concentration of TBOS (Calophyllum inophyllum Mer. and Pongamia pinnata L.). A factorial experiment in SSSPD with three replications was used in the study and analyzed using ANOVA and LSD. Open mist propagation is effective for rooting Calophyllum inophyllum and Pongamia pinnata cuttings as it gave statistically higher number of adventitious roots, longer length of roots, and higher rooting percentage. C. inophyllum cuttings exhibit statistically higher rooting percentage compared to P. pinnata cuttings when subjected to open mist method and treated with 600 ppm of NAA. NAA is more effective than IBA in terms of number and length of roots, and rooting percentage produced. However, levels of hormone concentration were not generally effective on the rooting performance and shoot production of both species.

Keywords: adventitious roots, Calophyllum, close-mist, macro-somatic clonal propagation, Pongamia, open-mist

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Authors: Yong Wook Kim

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The diversity of students in regular classrooms is increasing due to expand inclusive education and increase multicultural students in South Korea. In this diverse classroom environment, the universal design for learning (UDL) has been proposed as a way to meet both the educational need and social expectation of student achievement. UDL offers a variety of practical teaching methods, one of which is a differentiating instruction. The differentiating instruction has been pointed out resource limitation, organizational resistance, and lacks easy-to-implement framework. However, through the framework provided by the UDL, differentiating instruction is able to be flexible in their implementation. In practice, the UDL and differentiating instruction are complementary, but there is still a lack of research that suggests specific implementation methods that apply both concepts at the same time. This study was conducted to investigate the effects of differentiating instruction strategies according to learner characteristics (readiness, interest, learning profile), components of differentiating instruction (content, process, performance, learning environment), especially UDL principles (representation, behavior and expression, participation) existed in differentiating instruction, and implementation of UDL-based differentiating instruction through the Planning for All Learner (PAL) and UDL Lesson Plan Cycle. It is meaningful that such a series of studies can enhance the possibility of more concrete and realistic UDL-based teaching and learning strategies in the classroom, especially in inclusive settings.

Keywords: universal design for learning, differentiating instruction, UDL lesson plan, PAL

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Authors: Tuna Şahsuvaroğlu

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The concept of disability is a concept that has been the subject of many studies in national and international literature with its social, sociological, political, anthropological, economic and social dimensions as well as with individual and social consequences. A disabled person is defined as a person who has difficulties in adapting to social life and meeting daily needs due to loss of physical, mental, spiritual, sensory and social abilities to various degrees, either from birth or for any reason later, and they are in need of protection, care, rehabilitation, counseling and support services. The industrial revolution and the rapid industrialization it brought with it led to an increase in the rate of disabilities resulting from work accidents, in addition to congenital disabilities. This increase has resulted in disabled people included in the employment policies of nations as a disadvantaged group. Although the participation of disabled individuals in the workforce is of great importance in terms of both increasing their quality of life and their integration with society and although disabled individuals are willing to participate in the workforce, they encounter with many problems. One of these problems is the negative attitudes and prejudices that develop in society towards the employment of disabled individuals. One of the most powerful ways to turn these negative attitudes and prejudices into positive ones is education. Education is a way of guiding societies and transferring existing social characteristics to future generations. This can be maintained thanks to teachers, who are one of the most dynamic parts of society and act as the locomotive of education driven by the need to give direction and transfer and basically to help and teach. For this reason, there is a strong relationship between the teaching profession and the attitudes formed in society towards the employment of disabled individuals, as they can influence each other. Therefore, the purpose of this study is to examine teacher candidates' attitudes towards the employment of disabled individuals in terms of various variables. The participants of the study consist of 665 teacher candidates studying at various departments at Marmara University Faculty of Education in the 2022-2023 academic year. The descriptive survey model of the general survey model was used in this study as it intends to determine the attitudes of teacher candidates towards the employment of disabled individuals in terms of different variables. The Attitude Scale Towards Employment of Disabled People was used to collect data. The data were analyzed according to the variables of age, gender, marital status, the department, and whether there is a disabled relative in the family, and the findings were discussed in the context of further research.

Keywords: teacher candidates, disabled, attitudes towards the employment of disabled people, attitude scale towards the employment of disabled people

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Authors: Young Ik Suh, Taewook Chung, Glaucio Scremin, Tywan Martin

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In May of 2016, the Philadelphia 76ers announced that StubHub, the ticket resale company, will have advertising on the team’s jerseys beginning in the 2017-18 season. The 76ers and National Basketball Association (NBA) became the first team and league which embraced jersey sponsorships in the four major U.S. professional sports. Even though many professional teams and leagues in Europe, Asia, Africa, and South America have adopted jersey sponsorship actively, this phenomenon is relatively new in America. While the jersey sponsorship provides economic gains for the professional leagues and franchises, sport fans can have different points of view for the phenomenon of jersey sponsorship. For instance, since many sport fans in U.S. are not familiar with ads on jerseys, this movement can possibly cause negative reaction such as the decrease in ticket and merchandise sales. They also concern the small size of ads on jersey become bigger ads, like in the English Premier League (EPL). However, some sport fans seem they do not mind too much about jersey sponsorship because the ads on jersey will not affect their loyalty and fanship. Therefore, the assumption of this study was that the sport fans’ reaction about jersey sponsorship can be possibly different, especially based on different levels of the sport fans’ team identification and various sizes of ads on jersey. Unlike general sponsorship in sport industry, jersey sponsorship has received little attention regarding its potential impact on sport fans attitudes and buying intentions. Thus, the current study sought to identify how the various levels of team identification influence brand attitude and buying intention in terms of jersey sponsorship. In particular, this study examined the effect of team identification on brand attitude and buying intention when there are no ads, small size ads, and large size ads on jersey. 3 (large, small, and no ads) X 3 (Team Identification: high, moderate, low) between subject factorial design was conducted on attitude toward the brand and buying intention of jersey sponsorship. The ads on Philadelphia 76ers jersey were used. The sample of this study was selected from message board users provided by different sports websites (i.e., forums.realgm.com and phillysportscentral.com). A total of 275 respondents participated in this study by responding to an online survey questionnaire. The results showed that there were significant differences between fans with high identification and fans with low identification. The findings of this study are expected to have many theoretical and practical contributions and implications by extending the research and literature pertaining to the relationship between team identification and brand strategy based upon different levels of team identification.

Keywords: brand attitude, buying intention, Jersey sponsorship, team identification

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Authors: Carly Cummings, Maria Soledad Peresin

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Alabama has a long history of racial injustice and unsatisfactory educational performance. In the 1870s Jim Crow laws segregated public schools and disproportionally allocated funding and resources to white institutions across the South. Despite the Supreme Court ruling to integrate schools following Brown vs. the Board of Education in 1954, Alabama’s school system continued to exhibit signs of segregation, compounded by “white flight” and the establishment of exclusive private schools, which still exist today. This discriminatory history has had a lasting impact of the state’s education system, reflected in modern school demographics and achievement data. It is well known that Alabama struggles with education performance, especially in science education. On average, minority groups scored the lowest in science proficiency. In Alabama, minority populations are concentrated in a region known as the Black Belt, which was once home to countless slave plantations and was the epicenter of the Civil Rights Movement. Today the Black Belt is characterized by a high density of woodlands and plays a significant role in Alabama’s leading economic industry-forest products. Given the economic importance of forestry and agriculture to the state, environmental science proficiency is essential to its stability; however, it is neglected in areas where it is needed most. To better understand the inequity of science education within Alabama, our study first investigates how geographic location, demographics and school funding relate to science achievement scores using ArcGIS and Pearson’s correlation coefficient. Additionally, our study explores the implementation of a relevant, problem-based, active learning lesson in schools. Relevant learning engages students by connecting material to their personal experiences. Problem-based active learning involves real-world problem-solving through hands-on experiences. Given Alabama’s significant woodland coverage, educational materials on forest products were developed with consideration of its relevance to students, especially those located in the Black Belt. Furthermore, to incorporate problem solving and active learning, the lesson centered around students using forest products to solve environmental challenges, such as water pollution- an increasing challenge within the state due to climate change. Pre and post assessment surveys were provided to teachers to measure the effectiveness of the lesson. In addition to pedagogical practices, community and mentorship programs are known to positively impact educational achievements. To this end, our work examines the results of surveys measuring educational professionals’ attitudes toward a local mentorship group within the Black Belt and its potential to address environmental and science literacy. Additionally, our study presents survey results from participants who attended an educational community event, gauging its effectiveness in increasing environmental and science proficiency. Our results demonstrate positive improvements in environmental awareness and science literacy with relevant pedagogy, mentorship, and community involvement. Implementing these practices can help provide equitable and inclusive learning environments and can better equip students with the skills and knowledge needed to bridge this historic educational gap within Alabama.

Keywords: equitable education, environmental science, environmental education, science education, racial injustice, sustainability, rural education

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Authors: Dana Cassandra Winkler, Delia Leiding, Rene Bergs, Franziska Kaiser, Ramona Kirchhart, Ute Habel

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Background: Violence is a multidimensional phenomenon, affecting people of every age, socio-economic status and gender. Nevertheless, most studies primarily focus on men perpetrating women. Aim of the present study is to identify the likelihood of mental and somatic disorders and risk-taking behavior in male violence affected. In addition, the relationship between age of violence experience and the risk for health-related problems was analyzed. Method: On the basis of current evidence, a questionnaire was developed focusing on demographic background, health status, risk-taking behavior, and active and passive violence exposure. In total, 5221 males (Mean: 56,1 years, SD: 17,6) were consulted. To account for the time of violence experience in an efficient way, age clusters ‘0-12 years’, ‘13-20 years’, ‘21-35 years’, ‘36-65 years’ and ‘over 65 years’ were defined. A binary logistic regression was calculated to reveal differences in violence-affected and non-violence affected males regarding health and risk-taking factors. Males who experienced violence on a daily/ almost daily basis vs. males who reported violence occurrence once/ several times a month/ year were compared with respect to health factors and risk-taking behavior. Data of males, who indicated active and passive violence exposure, were analyzed by a chi²-analysis, to investigate a possible relation between the age of victimization and violence perpetration. Findings: Results imply that general violence experience, independent of active and passive violence exposure increases the likelihood in favor of somatic-, psychosomatic- and mental disorders as well as risk-taking behavior in males. Experiencing violence on a daily or almost daily basis in childhood and adolescence may serve as a predictor for increased health problems and risk-taking behavior. Furthermore, the violence experience and perpetration occur significantly within the same age cluster. This underlines the importance of a near-term intervention to minimize the risk, that victims become perpetrators later. Conclusion: The present study reveals predictors concerning health risk factors as well as risk-taking behavior in males with violence exposure. The results of this study may underscore the benefit of intervention and regular health care approaches in violence-affected males and underline the importance of acknowledging the overlap of violence experience and perpetration for further research.

Keywords: health disease, male, mental health, prevalence, risk-taking behavior, violence

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Authors: Apoorva Vinod, Archana Mathur, Snehanshu Saha

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Though there exists a plethora of Activation Functions (AFs) used in single and multiple hidden layer Neural Networks (NN), their behavior always raised curiosity, whether used in combination or singly. The popular AFs –Sigmoid, ReLU, and Tanh–have performed prominently well for shallow and deep architectures. Most of the time, AFs are used singly in multi-layered NN, and, to the best of our knowledge, their performance is never studied and analyzed deeply when used in combination. In this manuscript, we experiment with multi-layered NN architecture (both on shallow and deep architectures; Convolutional NN and VGG16) and investigate how well the network responds to using two different AFs (Sigmoid-Tanh, Tanh-ReLU, ReLU-Sigmoid) used alternately against a traditional, single (Sigmoid-Sigmoid, Tanh-Tanh, ReLUReLU) combination. Our results show that using two different AFs, the network achieves better accuracy, substantially lower loss, and faster convergence on 4 computer vision (CV) and 15 Non-CV (NCV) datasets. When using different AFs, not only was the accuracy greater by 6-7%, but we also accomplished convergence twice as fast. We present a case study to investigate the probability of networks suffering vanishing and exploding gradients when using two different AFs. Additionally, we theoretically showed that a composition of two or more AFs satisfies Universal Approximation Theorem (UAT).

Keywords: activation function, universal approximation function, neural networks, convergence

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Authors: Aleksandr Kalinenko, Igor Vysotskiy, Sergey Malopheyev, Sergey Mironov, Rustam Kaibyshev

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From a thermo-mechanical standpoint, friction-stir welding (FSW) represents a unique combination of very large strains, high temperature and relatively high strain rate. The material behavior under such extreme deformation conditions is not studied well and thus, the microstructural examinations of the friction-stir welded materials represent an essential academic interest. Moreover, a clear understanding of the microstructural mechanisms operating during FSW should improve our understanding of the microstructure-properties relationship in the FSWed materials and thus enables us to optimize their service characteristics. Despite extensive research in this field, the microstructural behavior of some important structural materials remains not completely clear. In order to contribute to this important work, the present study was undertaken to examine the grain structure evolution during the FSW of 6061-T6 aluminum alloy. To provide an in-depth insight into this process, the electron backscatter diffraction (EBSD) technique was employed for this purpose. Microstructural observations were conducted by using an FEI Quanta 450 Nova field-emission-gun scanning electron microscope equipped with TSL OIMTM software. A suitable surface finish for EBSD was obtained by electro-polishing in a solution of 25% nitric acid in methanol. A 15° criterion was employed to differentiate low-angle boundaries (LABs) from high-angle boundaries (HABs). In the entire range of the studied FSW regimes, the grain structure evolved in the stir zone was found to be dominated by nearly-equiaxed grains with a relatively high fraction of low-angle boundaries and the moderate-strength B/-B {112}<110> simple-shear texture. In all cases, the grain-structure development was found to be dictated by an extensive formation of deformation-induced boundaries, their gradual transformation to the high-angle grain boundaries. Accordingly, the grain subdivision was concluded to the key microstructural mechanism. Remarkably, a gradual suppression of this mechanism has been observed at relatively high welding temperatures. This surprising result has been attributed to the reduction of dislocation density due to the annihilation phenomena.

Keywords: electron backscatter diffraction, friction-stir welding, heat-treatable aluminum alloys, microstructure

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Authors: Ramin Vafadary, Maryam Khanbaghi

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Forecasting electricity load is important for various purposes like planning, operation, and control. Forecasts can save operating and maintenance costs, increase the reliability of power supply and delivery systems, and correct decisions for future development. This paper compares various time series methods to forecast 24 hours ahead of electricity load. The methods considered are the Holt-Winters smoothing, SARIMA Modeling, LSTM Network, Fbprophet, and Tensorflow probability. The performance of each method is evaluated by using the forecasting accuracy criteria, namely, the mean absolute error and root mean square error. The National Renewable Energy Laboratory (NREL) residential energy consumption data is used to train the models. The results of this study show that the SARIMA model is superior to the others for 24 hours ahead forecasts. Furthermore, a Bagging technique is used to make the predictions more robust. The obtained results show that by Bagging multiple time-series forecasts, we can improve the robustness of the models for 24 hours ahead of electricity load forecasting.

Keywords: bagging, Fbprophet, Holt-Winters, LSTM, load forecast, SARIMA, TensorFlow probability, time series

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Authors: Mia Wimala, Emma Akmalah, Ira Irawati, M. Rangga Sururi

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One way that has been aggressively implemented in creating a sustainable environment nowadays is through the implementation of green building concept. In order to ensure the success of its implementation, the support and initiation from educational institutions, especially higher education institutions are indispensable. This research was conducted to figure out the obstacles restraining the success of green campus implementation in Indonesia, as well as to propose strategies to overcome those obstacles. The data presented in this paper are mainly derived from interview and questionnaire distributed randomly to the staffs and students in 10 (ten) major institutions around Jakarta and West Java area. The data were further analyzed using ANOVA and SWOT analysis. According to 182 respondents, it is found that resistance to change, inadequate knowledge, information and understanding, no penalty for any environmental violation, lack of reward for green campus practices, lack of stringent regulations/laws, lack of management commitment, insufficient funds are the obstacles to the green campus movement in Indonesia. In addition, out of 6 criteria considered in UI GreenMetric World Ranking, education was the only criteria that had no significant difference between public and private universities in generating the green campus performance. The work concludes with recommendation of strategies to improve the implementation of green campus in the future.

Keywords: green campus, obstacles, sustainable, higher education institutions

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Authors: Shane D. Inder, Mehrdad Khamooshi

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Efficient energy storage is a crucial factor in facilitating the uptake of renewable energy resources. Among the many options available for energy storage systems required to balance imbalanced supply and demand cycles, compressed air energy storage (CAES) is a proven technology in grid-scale applications. This paper reviews the current state of micro scale CAES technology and describes a micro-scale advanced adiabatic CAES (A-CAES) system, where heat generated during compression is stored for use in the discharge phase. It will also describe a thermodynamic model, developed in EES (Engineering Equation Solver) to evaluate the performance and critical parameters of the discharge phase of the proposed system. Three configurations are explained including: single turbine without preheater, two turbines with preheaters, and three turbines with preheaters. It is shown that the micro-scale A-CAES is highly dependent upon key parameters including; regulator pressure, air pressure and volume, thermal energy storage temperature and flow rate and the number of turbines. It was found that a micro-scale AA-CAES, when optimized with an appropriate configuration, could deliver energy input to output efficiency of up to 70%.

Keywords: CAES, adiabatic compressed air energy storage, expansion phase, micro generation, thermodynamic

Procedia PDF Downloads 311