Initial Process Research Articles

Enhancing Environmental Literacy in Aceh’s Tourism through an Ethnoecotourism Based Environmental Education Model

Trends in tourism motives include socio-cultural, customs, environment, and panorama, as well as economics and welfare. However, the implementation of tourism will undoubtedly be disrupted by management and development that are not founded on the principles of sustainability. Therefore, through the process of environmental education, preventative and awareness initiatives are required. The main objective of this research was to examine the effectiveness of an ethnoecotourism-based environmental education model for tourism actors in Aceh Province. This model was developed to increase environmental literacy in marine tourism management. Model trials were carried out in the Sabang City Marine Tourism Area. The participants of this research were tourism actors in Aceh Province. The research design uses a quasi-experimental method consisting of pretest-posttest groups and uses multiple-choice questions as a research tool. The data analysis technique applied in this research was quantitative descriptive analysis techniques, in which data were processed inductively using an interactive analysis model. It is known that this model could improve the environmental literacy skills of tourism actors at the research location. It was shown by the significant value obtained at p = 0.000 (< 0.05), where there was a difference in students’ scores after being given the learning process, with the average post-test score of 12.43, higher than the pretest score of 8.40, which means there was an increase in understanding of environmental literacy after being given a learning process using an ethnoecotourism-based environmental education model.

A Fused Deep Denoising Sound Coding Strategy for Bilateral Cochlear Implants.

Cochlear implants (CIs) provide a solution for individuals with severe sensorineural hearing loss to regain their hearing abilities. When someone experiences this form of hearing impairment in both ears, they may be equipped with two separate CI devices, which will typically further improve the CI benefits. This spatial hearing is particularly crucial when tackling the challenge of understanding speech in noisy environments, a common issue CI users face. Currently, extensive research is dedicated to developing algorithms that can autonomously filter out undesired background noises from desired speech signals. At present, some research focuses on achieving end-to-end denoising, either as an integral component of the initial CI signal processing or by fully integrating the denoising process into the CI sound coding strategy. This work is presented in the context of bilateral CI (BiCI) systems, where we propose a deep-learning-based bilateral speech enhancement model that shares information between both hearing sides. Specifically, we connect two monaural end-to-end deep denoising sound coding techniques through intermediary latent fusion layers. These layers amalgamate the latent representations generated by these techniques by multiplying them together, resulting in an enhanced ability to reduce noise and improve learning generalization. The objective instrumental results demonstrate that the proposed fused BiCI sound coding strategy achieves higher interaural coherence, superior noise reduction, and enhanced predicted speech intelligibility scores compared to the baseline methods. Furthermore, our speech-in-noise intelligibility results in BiCI users reveal that the deep denoising sound coding strategy can attain scores similar to those achieved in quiet conditions.

학습자 주도성(Student Agency)을 기반한 창의적 문제해결수업에 참여한 대학생의 학습자 주도성의 발달과정과 미래창의융합역량함양에 관한 혼합연구

Objectives The purpose of this study is to investigate the development process of learner initiative(student agen-cy) and the cultivation of future creative convergence competency in creative problem solving class based on learner initiative(student agency) and to explore implications. Methods The qualitative data was collected from 15 weeks of class reflection, class project results, teacher inter-views, peer evaluation papers, etc. The amount of collected data was 683 sheets of A4 paper and line by line anal-ysis was used. In order to support and supplement qualitative research, quantitative data collection was also conducted. Based on the operational definition of future creative convergence talent competency by Park Hyun-hee and Kwak Min-jung (2023), future creative convergence measurement was conducted before and after the 15-week class using questions suitable for this study through expert validity.The collected quantitative data were analyzed using the Spss 21 statistical program. Results As a result of qualitative data analysis, it was categorized into three core themes ⁇ understanding and demonstrating learner initiative, practicing communication and cooperation, and ⁇⁇recognizing continuous re-flection as a lifelong learner.As a result of quantitative data analysis, it was verified that the future creative con-vergence ability of college students who applied for the creative problem solving ability course based on learner initiative was cultivated. Conclusions The implications of this study are that the creativity problem solving class based on the learner ini-tiative, which is the core educational capacity for the future, has a high level of convergence ability of future crea-tivity, which is related to the core theme, and it is confirmed that the class in which the learner initiative is culti-vated through the team project activity was performed.Through this, discussions on the results, implications of limitations of the study, and future research directions were suggested.

Human Rights and Inclusion Policies for Transgender Women in Elite Sport: The Case of Australia ‘Rules’ Football (AFL)

ABSTRACT The discourse inside and outside of sport in Australia and abroad on the participation of transgender women in female sport focuses on the principles of fairness, equity and the safety of competitors. These concerns commonly materialise (with little evidence) labelling transgender women as ‘cheats’, dominating female sport, strategically being coached in collision sports to intentionally hurt opponents or fraudulently transitioning with the sole aim of competing in elite women’s sport. Our research examines the process by which the Australian Football League (AFL) grappled with these competing narratives in developing a policy to permit the participation of transgender and gender diverse athletes in community and ‘elite’ competitions. It will be argued that the initial AFL process lacked consideration of the human rights of transgender women and did not provide the necessary resources required to ensure a safe and inclusive process for transgender women to engage with the AFLW competition. This article will also identify lessons which other sport governing organisations should heed in developing and implementing policies for the inclusion of transgender women in sport.

Scientific Communication Initiative at a Medical Military Library

Implementation of new scholarly communication library service in the digital age is characterized by the competitive forces between the old library information services and the ambiguity of future information services. This research analyzes the development process of scientific initiative and collaborative partnership in the military medical library environment aimed to enhance the quality of scientific communication and information skills in military residents and clinicians. The hindering internal and external forces and facilitators of developing and implementing scientific initiative service in the military medical library are evaluated. The environmental analysis was conducted to determine the scholarly communication needs in the scholarly military medical environment. The ambassador-based model was used for the development of scientific communication initiative (SCI) at the military medical library. The SCI consisted of two components: library information communication and scientific communication. This implementation in the military medical environment enhanced scholarly communication, research skills development, and information education. A collaborative Scientific Hub, and liaison partnerships with military graduate medical education program directors and clinicians enhanced the scientific communication and information skills in residents. The Ambassador model, used in the development of scientific initiative in academic and military environments, was valuable for developing and implementing specialized interdisciplinary and multidisciplinary information services in the academic and military environment. Higher education hierarchy, educational needs, organizational hierarchy, academic culture, and educational environment influence the implementation of information services in academic and military environments.

Test suite optimization under multi-objective constraints for software fault detection and localization: Hybrid optimization based model

Testing and debugging have been the most significant steps of software development since it is tricky for engineers to create error-free software. Software testing takes place after coding with the goal of finding flaws. If errors are found, debugging would be done to identify the source of the errors so that they may be fixed. Detecting as well as locating defects are thus two essential stages in the creation of software. We have created a unique approach with the following two working phases to generate a minimized test suite that is capable of both detecting and localizing faults. In the initial test suite minimization process, the cases were generated and minimized based on the objectives such as D-score and coverage by the utilization of the proposed Blue Monkey Customized Black Widow (BMCBW) algorithm. After this test suite minimization, the fault validation is done which includes the process of fault detection and localization. For this fault validation, we have utilized an improved Long Short-Term Memory (LSTM). At 90% of the learning rate the accuracy of the presented work is 0.97%, 2.20%, 2.52%, 0.97% and 2.81% is better than the other extant models like AOA, COOT, BES, BMO and BWO methods. The results obtained proved that our Blue Monkey Customized Black Widow Optimization-based fault detection and localization approach can provide superior outcomes.

Monitoring and analysis of physical activity and health conditions based on smart wearable devices

The rapid growth of the Internet of Things (IoT) brings sweeping changes in various industries. Healthcare industries have become a prime example where the Internet of Healthcare Things (IoHT) is making significant progress, particularly in how we approach real-time patient care. Traditional systems for monitoring older people and people with special needs are frequently expensive, require a large workforce, and fall short of providing real-time data. This paper introduces the “3-Tier Health Care Architecture,” an integrated approach to mitigating these issues. This architecture capitalizes on IoHT technologies and is constructed around three principal tiers: Sensor, Fog, and Cloud. The Sensor Tier employs Health Metrics Acquisition Units (HMAUs) fitted with an nRF5340 Development Kit, capturing an extensive range of health-related metrics via wearable sensors. These metrics are then relayed to the Local Processing Units (LPUs) in Fog Tier, which operates on Raspberry Pi Zero 2 W microprocessors for the initial data processing before forwarding to the cloud. The Cloud Tier uses a hybrid CNN-LSTM Machine Learning (ML) model to perform Real-Time Healthcare Monitoring (RTHM) status assessments and includes an Early Warning System for immediate alert issuance. The proposed architecture is resilient, scalable, and efficient, serving as a fortified and all-encompassing solution for RTHM. This enables quick medical interventions, thus elevating healthcare quality and potentially life-saving.

Image dermoscopy skin lesion classification using deep learning method: systematic literature review

Classifying skin lesions poses a significant challenge due to the distinctive characteristics and diverse shapes they can exhibit, particularly in identifying early-stage melanoma. To address the shortcomings of the prior method, a neural network-driven strategy was introduced to differentiate between two types of skin lesions based on dermoscopic images. This new approach comprises four key stages: i) initial image processing, ii) skin lesion segmentation, iii) feature extraction, and iv) classification using deep neural networks (DNNs). Computers can also provide more accurate diagnosis results. In the review process, the articles are analyzed and summarized to contribute to developing methods or application development in skin lesion diagnosis. The stages include defining the relevant theory, input data, methods used (architecture and modules), training process, and model evaluation. This review also explores information based on trends and users, emphasizing the skin lesion segmentation process, skin lesion classification process, and minimal datasets as recommendations for future research.

Psoriasis and Bullous Pemphigoid Developing Simultaneously During Systemic Administration with Bisoprolol and Losartan

Psoriasis and bullous pemphigoid are both chronic inflammatory skin disorders, involving abnormal immune responses. Their coexistence is often observed in the literature in the context of secondary development following an initial inflammatory process. In the majority of cases, the development of psoriasis seems to occur before the onset of bullous pemphigoid. While psoriasis is associated with autoimmune bullous diseases, it’s important to note that not every individual with psoriasis will develop bullous pemphigoid. Therefore the pathogenetic mechanism behind this association remains rather a mystery. Several case reports/studies have been published describing the subsequent development of either psoriasis or bullous pemphigoid following initial monotherapy with beta blockers, sartans, or other drug class medications (which will not be mentioned in our case report as they are not relevant to the presented data). We believe that our case is the first documented example of polymedicamentous development of 2 skin diseases within the intake of 2 antihypertensive drugs heterogeneous in class and action. We present a 78-year-old female with plaque psoriasis followed shortly thereafter by bullous pemphigoid after 10-year period of antihypertensive therapy with bisoprolol and losartan. We believe that the cumulative effect of both medications may have contributed to the coexistence of these skin disorders. Following the discontinuation of the initial antihypertensive therapy with bisoprolol and losartan and substituting it verapamil and moxonidine, along with the initiation of methotrexate and folic acid, the patient showed significant improvement. Key words: psoriasis; bullous pemphigoid; drug-induced; bisoprolol; losartan

Open strategizing for developing smart city food system: Stakeholder inclusion in practice

The positive impact of stakeholder engagement (SE) in smart city development initiatives has received notable scholarly attention over the past decade. Researchers of stakeholder engagement have investigated various aspects of the engagement process from different theoretical perspectives, yet the complexity and dynamism of inclusion, especially at the societal level and in the context of smart city development, continue to inspire more research. Drawing from the intersection of open strategy (OS) and SE, we seek to enhance understanding of the open strategizing process by elucidating stakeholder inclusion practices in a smart city initiative, focusing on food systems in Da Nang, Vietnam. Our participatory action research draws on 114 semi-structured interviews and four stakeholder workshops to analyze the way stakeholder inclusion practices unfold in the strategic decision-making process of a smart city initiative. Our analysis reveals that stakeholder inclusion is complex and involves four interdependent practices at different stages of the strategizing process. These practices are trust formation, common language creation, role transformation, and expectation alignment. Together, they culminate in the creation of an interactive social space for the strategy-making process. The proposed analytical framework highlights the interdependencies among practices and their outcomes at different stages of the open strategizing process and could serve as a guideline in a context in which stakeholder inclusion at the planning phase is necessary to achieve systemic change.

Оrganization of the initial training process for athletes in bodybuilding

The article examines generalized data on approaches to the construction of sports training during the year. The systematization of the data of special scientific and methodical literature on the construction of the training process of athletes in bodybuilding is presented. The article discusses the key components of methodical methods of building the educational and training process of athletes. The training of highly qualified athletes is characterized by a clearly expressed cycle. Unsolved issues of building the training process of highly qualified bodybuilders in the annual macrocycle have been identified. The purpose of the study is to systematize the data of special scientific and methodological literature on the issues of building an education. To achieve this goal, modern methods were developed: theoretical analysis and data processing, descriptive method, classification, systematization and referenced scientific and methodological literature, sociological research methods. The expansion of the number of competitions, periodic changes in the programs and rules of competitions significantly affect the training system, including its periodization. However, the analysis of numerous innovations in the field of building sports training during the year only shows that they do not in any way contradict the main provisions of the periodization system, but only complement and develop its individual parts, taking into account the features of the modern stage of bodybuilding development.
 Summing up, it should be noted that in the scientific and methodological literature, the specifics of the training process of athletes engaged in bodybuilding have been studied in depth, but the issue of developing training programs taking into account the body structure of athletes remains unresolved. Therefore, research in this direction is relevant for the theory and practice of bodybuilding.

Application of Na2CO3 as a Sacrificial Electrode Additive in Na‐ion Batteries to Compensate for the Sodium Deficiency in Na2/3[Fe1/2Mn1/2]O2

AbstractOwing to their high discharge capacities, P2‐type transition metal layered oxides have attracted attention for use as positive electrode materials in Na‐ion batteries. However, owing to the Na‐deficient compositions of these oxides, additional Na+ must be supplied using a Na‐metal negative electrode to attain a high capacity in a half‐cell configuration. In this study, solid Na2CO3 powder was introduced into the P2−Na2/3Fe1/2Mn1/2O2 composite positive electrode as a sacrificial salt to compensate for the Na deficiency. Na+ was supplied through the electrochemical oxidative decomposition of Na2CO3 during the initial charging process; the decomposition mechanism responsible for this process was investigated in detail. Online electrochemical mass spectrometry confirmed that Na2CO3 was oxidatively decomposed in combination with the decomposition of the ethylene carbonate electrolyte. This reaction produced CO2, wherein the carbon source was derived from both Na2CO3 and the electrolyte. Consequently, Na+ supplementation improved the reversible capacity of the Na‐ion full cell. This study offers practical insights and a mechanistic understanding of the pre‐doping technique for Na‐free negative electrodes. This approach also compensates for the irreversible reductive capacity in a process that can be easily applied to practical sodium‐ and lithium‐ion batteries and capacitors.

A Proposed Model for Variation Order Management in Construction Projects

This study aims to identify the causes of excessive change orders and their impact on public construction projects in Saudi Arabia. This should support the organizations working in the construction industry to improve variation order management (VOM) as a preventive action by dealing proactively with variation order causes. Therefore, a new methodology was proposed to minimize change orders and their impact on the successful completion of projects as well as cost during the project lifecycle. The methodology involved ten selected turnkey building projects at King Faisal University (KFU) campus, Saudi Arabia. Statistical analyses were conducted to predict the cost overrun in project size and contract value. The findings showed the most significant causes leading to variation order in public construction projects. These include the combined effect of the designer and owner technical committee, designer document, and owner stakeholder committee. Hence, a new model for VOM was developed as a best practice approach, including three stages. The first stage is the initiation process, which includes seven procedures, seven tools, and key responsibilities. The second stage deals with the course of change orders based on a certain number of procedures and weight for each parameter assigned to this phase. It supports decision processes based on a certain average ratio of weights calculation. The third stage is the decision to support decision makers in proceeding or not proceeding with the variation order. Although the present study was conducted in Saudi Arabia’s public building construction project, it is envisaged that these research results are widely applicable to other developing countries. The paper presents a direction for further research to enhance the impact of cost overrun in public sector construction projects in developing countries, i.e., Saudi Arabia.

XPS study on passivation behavior of naturally formed oxide on AlFeCuCrMg1.5 high-entropy alloy

High-entropy alloys have exceptional oxidation resistance due to their passive oxide film. In this study, photoelectron spectroscopy was used in a modern atomic-scale in situ initial oxidation analysis process to determine the oxidation behavior and elemental variation on its breakdown. Furthermore, the behavior of natural oxide formed on the AlFeCuCrMg1.5 HEA after the exposure of the alloy to the atmosphere for one hour, one day, and seven days was investigated in detail. Through a survey scan, the elements present on the oxidized surface were determined and quantified. Additionally, the seven-day-exposed HEA was depth-profiled and discovered drastic modifications in the alloy.

Experimental study on the influence of the wall cavity on stability of kerosene two-phase rotating detonation combustion

The combustion characteristics in annular rotating detonation combustors are experimentally investigated using 40% oxygen-enriched air and liquid aviation kerosene (RP-3) as reactants. Two types of wall cavity structures, embedded in the outer and the inner wall of the annular combustors, respectively, are employed to study their effects on detonation stability. The characteristics of typical combustion modes observed in the annular combustors are firstly analyzed. The regime of typical combustion modes is then examined in the phase diagram of mass flow rate and equivalence ratio. Results show that the single-wave mode regime can be affected by wall cavities. In comparison to the combustor without a wall cavity, the regime is expanded for the cavity in the inner wall but significantly reduced for the cavity in the outer wall. When the single-wave mode forms, the cavities embedded in the inner wall result in a significant increase of the apparent detonation wave velocity but a decrease in the velocity fluctuation rate, and the effects are changed with the axial location of the cavities. The axial location of the cavity can also influence the stable propagation location of the detonation wave. Additionally, the analysis of the high-frequency pressure signals indicates that the cavities do not affect the initiation process of the formation of the combustion modes. However, the variation of oxidizer mass flow rate and equivalence ratio can evidently influence the evolution time of different combustion modes after ignition. The study indicates that the wall cavity structure has a significant influence on the propagation behavior of rotating detonation waves in the combustors, and it can be utilized to enhance the stability of kerosene two-phase rotating detonation combustion.

Numerical study on dynamic cracking characteristic and mechanism of quasi-brittle materials under impulsive loading

This study focuses on investigating the dynamic cracking behaviors of quasi-brittle materials under impulsive loading using the extended non-ordinary state-based peridynamic (NOSB-PD) model. This extended model incorporates two stress-based failure criteria: Mohr-Coulomb and maximum tensile stress criteria, to represent shear and tensile fractures of quasi-brittle materials, respectively. By analyzing the evolution characteristics of the maximum principal stress obtained from the NOSB-PD model, the fracture mechanisms of quasi-brittle materials subjected to impulsive loading are explored. The research reveals that tensile failure predominantly governs the initiation and propagation processes of quasi-brittle materials under impulsive loading. The stress concentration effect, transfer effect, and dissipation effect observed in the maximum principal stress fields provide insights into the cracking mechanism during the failure processes of such materials. To validate the findings, the crack initiation modes and crack propagation paths obtained from the NOSB-PD model are compared with those obtained from the existing experimental and numerical approaches. The results demonstrate that the extended NOSB-PD model is effective in addressing fracture problems associated with quasi-brittle materials under impulsive loading conditions.

COVID-19 detection in lung CT slices using Brownian-butterfly-algorithm optimized lightweight deep features

Several deep-learning assisted disease assessment schemes (DAS) have been proposed to enhance accurate detection of COVID-19, a critical medical emergency, through the analysis of clinical data. Lung imaging, particularly from CT scans, plays a pivotal role in identifying and assessing the severity of COVID-19 infections. Existing automated methods leveraging deep learning contribute significantly to reducing the diagnostic burden associated with this process. This research aims in developing a simple DAS for COVID-19 detection using the pre-trained lightweight deep learning methods (LDMs) applied to lung CT slices. The use of LDMs contributes to a less complex yet highly accurate detection system. The key stages of the developed DAS include image collection and initial processing using Shannon's thresholding, deep-feature mining supported by LDMs, feature optimization utilizing the Brownian Butterfly Algorithm (BBA), and binary classification through three-fold cross-validation. The performance evaluation of the proposed scheme involves assessing individual, fused, and ensemble features. The investigation reveals that the developed DAS achieves a detection accuracy of 93.80% with individual features, 96% accuracy with fused features, and an impressive 99.10% accuracy with ensemble features. These outcomes affirm the effectiveness of the proposed scheme in significantly enhancing COVID-19 detection accuracy in the chosen lung CT database.

The Understanding of Household Livelihood Diversity on Production Forest Areas: A Preliminary Survey on Social Studies

Forest resources play an essential role in supporting the livelihoods of forest farming households. Households in this area depend heavily on forest-related activities as a source of income and livelihood. However, forest farming households are often faced with various challenges and uncertainties due to climate change, market fluctuations, limited access to land ownership, lack of infrastructure and technological support, and developments in socio-economic conditions that change the values and structure of people's lives. This study is a preliminary survey as an initial process of collecting information and data before carrying out the primary research. This preliminary survey aims to gain an initial understanding of the diversity of forest farmer household livelihoods. Data was collected through a rapid study of 30 households in Gandu Village. Then, data was identified according to information needs and planning the next steps. The results of this study show that forest farming households in Gandu Village diversify their livelihoods in both the agricultural and non-agricultural sectors. The diversity value in the non-agricultural sector shows an average figure of 2.1, which means that each household does not only depend on one source of income. However, they will diversify the number of livelihoods in the amount of 2.1 to meet their household's living needs. The findings of this preliminary survey can become initial data and contribute to further research.

PREDICTIVE DISTRIBUTION TO DETERMINE LEARNING MODEL AT THE STRATEGIC COMPETENCE LEVEL OF STUDENTS IN STATISTICS GROUP COURSE

The problem of this research comes from a situation or condition that is not static. The description of these problems is the condition of the learning system, which tends to change due to the Covid-19 pandemic, causing learning conditions to be dynamic. From a statistical perspective, the dynamic situation can be modeled using a predictive distribution approach, so its characteristics can be studied. The purpose is to provide policy recommendations on appropriate learning models for lecturers in improving students' strategic competence, which is an ability that students need to master in solving various mathematical problems. The main discussion of this paper consists of three parts: clustering, predictive distribution, and statistical inference. The purpose of clustering is to group students based on test results to determine the level of strategic competence. In addition, clustering is also used as an initial process to predict students' strategic competence level if the learning used is still the same. The benefits of statistical inference in the distribution procedure in this study are used to determine the type of data distribution from each arrival of new information or data. The results of the statistical inference determine whether or not it is necessary to update the learning model of the lecturer. This research produce a new alternative statistical inference needed to make decisions. Based on the simulation results and discussion, the use of a predictive distribution approach to predict dynamic data is very appropriate. Distribution approach can use for detecting changes in new data distribution with historical data for the dynamic condition. If the changes are insignificant, direct instruction can still be used for the learning model in statistics course. A new learning model is recommended for the statistics group course at a higher level when the changes are significant.

The Effect of Adding Propolis to Formula Milk on The Streptococcus Sobrinus Inhibition Zone (In Vitro)

Background: Caries is one of the dental and oral health problems that are often suffered by children. One of the main causes is the habit of children consuming formula milk as it contains sucrose. Streptococcus sobrinus is an oral pathogenic bacteria that has a role in the initial process of dental caries. One of the natural ingredients that function as anti-caries is propolis. Objective: Therefore, this study aims to determine the effect of adding propolis to formula milk on the inhibition zone of Streptococcus sobrinus bacteria. Methods: This type of research is a Laboratory Experiment with a Post-Test control Group Design. It consists of 4 groups, namely the formula milk group without propolis as a negative control, the formula milk treatment group with propolis concentrations of 5%, 10%, and 20% carried out with 7 replications of each group. The sample is a pure isolate of Streptococcus sobrinus bacteria. Results: The results showed the average inhibition zone was the formula milk group without propolis was 0.00±0.00 mm, the formula milk group with propolis concentration of 5% was 12.87±1.18 mm, the formula milk group with propolis concentration of 10% was 16.65±1.51 mm, and the formula milk group with propolis concentration of 20% was 24.87±0.39 mm. Conclusion: It means the addition of propolis to formula milk has been proven to be effective in inhibiting the growth of Streptococcus sobrinus bacteria.