Systematic Development Research Articles

Enhancing Class 6 Computer Education with Flash-Based Multimedia at Bukit Islamiah

This research focuses on developing practical and efficient media for computer systems material aimed at grade 6 students. Employing the ADDIE model, the study progresses through analysis, design, development, and implementation stages to craft a flash-based interactive multimedia. A small-scale trial involving 5 students indicates promising results, with validation scores from media and material experts at 87% and 78%, respectively. Moreover, the average student response stands at 87.2%, affirming the suitability of the developed multimedia for learning purposes. This research underscores the potential of interactive multimedia in enhancing educational experiences, particularly in computer science education for young learners. Highlights : Implementation of ADDIE model ensures systematic development. Flash-based multimedia yields high validation scores from experts. Student response supports suitability for educational use. Keywords: Interactive multimedia, Grade 6 education, Computer systems, ADDIE model, Learning efficiency

Web-based application of descriptive statistics for data dispersion analysis to support statistic learning

Statistics is a branch of science that studies ways of collecting, processing, presenting, analyzing, interpreting and drawing conclusions from data. Descriptive Statistics is a part of statistics that carries out the tasks of collecting data, classifying, processing and presenting quantitative data. Statistics has a very important and necessary role in various areas of life, so that statistics courses are taught in almost all departments, both exact and non-exact, at various educational institutions. A common problem found in studying statistics courses is that students in non-exact majors are less interested in courses involving numerical data processing, so that learning outcomes for this course are generally relatively low. With advances in information technology, several statistical applications have been developed, but these applications directly present the final results of data processing without displaying the steps to obtain the final results. This is inadequate from a learning perspective, because students do not get a clear picture of the steps for solving problems based on statistics. This research uses the method waterfall [8] [9] or linear sequential, namely a sequential and systematic software development method consist of : Analysis, Design, Coding and Testing. The result of making this application is an analysis of data dispersion measures consisting of Range, Inter Quartile Range, Quartile Deviation, Average Deviation, Standard Deviation, Variance, Coefficient Variation and Coefficient Quartile. This application will show in detail the steps to solve the problem according to theory, formulas and calculation steps to get the final result. These results will make it easier for students to understand and it is hoped that this course will be presented more interestingly and ultimately increase learning outcomes.

Integrated system for temperature-controlled fast protein liquid chromatography. IV. Continuous ‘one-column’ ‘low-salt’ hydrophobic interaction chromatography

Systematic development of a temperature-controlled isocratic process for one-column low-salt hydrophobic interaction chromatography (HIC) of proteins employing a travelling cooling zone reactor (TCZR) system, is described. Batch binding and confocal scanning microscopy were employed to define process conditions for temperature-reversible binding of bovine serum albumin (BSA) which were validated in pulse-response temperature switching HIC experiments, before transferring to TCZR-HIC. A thin-walled stainless-steel column mounted with a movable assembly of copper blocks and Peltier elements (travelling cooling zone, TCZ) was used for TCZR-HIC. In pulse-response TCZR-HIC, 12 TCZ movements along the column desorbed 86.3% of the applied BSA monomers in 95.3% purity depleted >6-fold in 2–4 mers and nearly 260-fold in higher molecular weight (HMW) species. For continuous TCZR-HIC, the TCZ was moved 49–58 times during uninterrupted loading of BSA feeds at 0.25, 0.5 or 1 mg·mL-1. Each TCZ movement generated a sharp symmetrical elution peak. In the best case, (condition 1: 0.25 mg·mL-1 BSA; >17 mg BSA applied per mL of bed) the height of TCZ elution peaks approached pseudo-steady midway through the loading phase with no rise in baseline UV280 signal between peaks. Peak composition remained constant averaging 94.4% monomer, 5.6% 2–4 mers and <0.05% HMW. Monomers were recovered in quantitative yield depleted >3.1 fold in 2–4 mers and 92-fold in HMW species cf. the feed (63.6% monomers, 21.8% 2–4 mers, 14.6% HMW). However, increasing the BSA concentration to 1 mg·mL-1 (condition 2) or employing a fouled HIC column with 0.5 mg·mL-1 BSA (condition 3) compromised monomer purification performance.

Systematic Development of an AI Chatbot for Physical Activity Habit Formation in Prehypertension Individual Integrating Needs, Theories, and Evidence.

Prehypertension, an early stage in the development of hypertension, impacts a substantial segment of the adult population worldwide. Addressing this issue, our study introduces HabitBot, an AI-driven chatbot tailored to encourage physical activity (PA) habits among individuals with prehypertension. HabitBot combines natural language processing with multidisciplinary approaches, drawing from both theoretical frameworks and empirical studies. The chatbot development followed a systematic, five-phase process: comprehensive needs assessment, literature review on behavior change theories, analysis for selecting effective behavior change techniques (BCTs), prototype design through intervention mapping, and refining the intervention based on user feedback. The outcome includes a prototype that integrates the Health Action Process Approach and Habit Formation Theory, utilizing twelve identified BCTs effective in fostering PA habits. User feedback further refined the chatbot across multiple dimensions such as user interface, content accessibility, and privacy. HabitBot exemplifies an innovative integration of behavior change strategies with advanced language model technology, paving the way for digital health interventions in chronic disease prevention. Future studies should assess its long-term efficacy in habit formation and explore its applicability to various demographic groups.

Development of Continuous Additive-Controlled MSMPR Crystallization by DoE-Based Batch Experiments.

Additive-controlled crystallization is a promising method to improve crystal morphology and produce solid drug particles with the desired technological and pharmacological properties. However, its adaptation to continuous operation is a hardly researched area. Accordingly, in this work, we aimed to come up with a methodology that provides the systematic and fast development of a continuous three-stage MSMPR cascade crystallizer. For that, a cooling crystallization of famotidine (FMT) from water, in the presence of a formulation additive, poly(vinylpyrrolidone) (PVP-K12), was developed. Process parameters with a significant impact on product quality and quantity were examined in batch mode through a 24-1 fractional factorial design for the implementation of additive-controlled continuous crystallization. These batch experiments represented one residence time of the continuous system. Based on the statistical analysis, the residence time (RT) had the highest effect on yield, while the polymer amount was critical from the product polymorphism, crystal size, and flowability points of view. The values of critical process parameters in continuous operation were fixed according to the batch results. Two continuous cooling crystallization experiments were carried out, one with 1.25 w/wFMT% PVP-K12 and one with no additive. A mixture of FMT polymorphs (Form A and Form B) crystallized without the additive through five residence times (>6.5 h) with 70.8% overall yield. On the other hand, the additive-controlled continuous experiment resulted pure and homogeneous Form A product with excellent flowability. The system could be operated for >6.5 h without clogging with a 71.1% overall yield and a 4-fold improvement in productivity compared to its batch equivalent.

Robotic adrenalectomy-current evidence

Laparoscopic adrenalectomy is worldwide currently considered the gold standard technique for patients suffering from benign lesions. There has been an increasing number of robotic-assisted adrenalectomies in the last decade due to the systematic further development of minimally invasive surgery resulting in the implementation of robot-assisted surgery. Interestingly, the available studies show some perioperative advantages for robotic surgery but overall the current evidence is weak and there are economic aspects that are not negligible. Therefore, further high-quality studies about robotic-assisted adrenalectomy are mandatory to strengthen the current evidence.

Development and Evaluation of Docetaxel-Loaded Nanostructured Lipid Carriers for Skin Cancer Therapy.

This study focuses on the design, characterization, and optimization of nanostructured lipid carriers (NLCs) loaded with docetaxel for the treatment of skin cancer. Employing a systematic formulation development process guided by Design of Experiments (DoE) principles, key parameters such as particle size, polydispersity index (PDI), zeta potential, and entrapment efficiency were optimized to ensure the stability and drug-loading efficacy of the NLCs. Combined XRD and cryo-TEM analysis were employed for NLC nanostructure evaluation, confirming the formation of well-defined nanostructures. In vitro kinetics studies demonstrated controlled and sustained docetaxel release over 48 h, emphasizing the potential for prolonged therapeutic effects. Cytotoxicity assays on human umbilical vein endothelial cells (HUVEC) and SK-MEL-24 melanoma cell line revealed enhanced efficacy against cancer cells, with significant selective cytotoxicity and minimal impact on normal cells. This multidimensional approach, encompassing formulation optimization and comprehensive characterization, positions the docetaxel-loaded NLCs as promising candidates for advanced skin cancer therapy. The findings underscore the potential translational impact of these nanocarriers, paving the way for future preclinical investigations and clinical applications in skin cancer treatment.

A Scale Development Study on the Perceived Level of Workplace Generational Conflict

Objective: Intergenerational conflict can be defined as disagreements in values, beliefs, perspectives and behaviors of different generations. Considering today’s business environment where different generations work together, its importance emerges once again. Methods: Although intergenerational conflict has been discussed from many perspectives in the literature, studies on this type of conflict, especially in the business environment, are limited and even a scale that directly measures this conflict has not been found. Therefore, a scale was developed through a systematic scale development process based on the literature related to this study. Results: The data was collected from 1005 private sector professionals. Consequently, exploratory and confirmatory factor analysis and reliability analysis were performed and the factor structure of the scale was determined. Conclusions: As a result, the two-dimensional perceived level of workplace generational conflict scale developed and the scaleitems presented in the appendix was obtained. Originality/Value: Intergenerational conflict involves differing values, beliefs, perspectives, and behaviors among generations. In today's multi-generational workplace, its significance is clear. Consequently, a two-dimensional scale to measure workplace generational conflict has been developed, with scale items listed in the appendix.

Production and optical characterisation of blended Polyethylene Terephthalate (PET)/Polyethylene Naphthalate (PEN) scintillator samples

In Particle and Nuclear Physics research and related applications, organic scintillators provide a cost-effective technology for the detection of ionising radiation. The next generation of experiments in this field is driving fundamental research and development on these materials, demanding improved light yield, radiation hardness, and fast response. Common materials such as PEN and PET have been found to offer scintillation properties competitive to commercial alternatives without the use of dopants. Motivated by their complementarity in terms of light yield, radiation hardness, and time response, there is an increasing interest in investigating PET:PEN mixtures to ascertain whether they exhibit synergistic blending. This paper presents results from the systematic development of samples of PET, PEN, and PET:PEN blends with varied mass proportions. The manufacturing technique, involving injection moulding of granule raw material, is detailed. The effects of doping the polymer base substrate with fluorescent dopants are explored. Finally, the emission spectra of the different material compositions and their relative light output are presented.

Teaching content model for designing digital systems of power grid relay protection and automation

It was found that the effective formation of conceptual-analytical and productive-synthetic levels of formation of professional knowledge and skills regarding the design of digital systems of power grid relay protection and automation is possible with the systematic development and use of a generalized model of the teaching content. Based on the study of information models of technical systems, a feature model was adopted as a basic invariant, which includes a set of features of the purpose, construction, principle of operation and parameters of the technical system. It was found that the design process of digital systems of power grid relay protection and automation can be conventionally divided into three stages, namely, the development of the design task, the direct implementation of the design, and the determination of the parameters of operation. Causal chains of knowledge that form the basis of problem solving at these three stages are determined. It was found that the methods of step-by-step decomposition and aggregation are key in building the content of teaching the design of digital systems of power grid relay protection and automation based on causal chains of knowledge. A generalized model of the teaching content design of digital systems of power grid relay protection and automation based on causal chains of knowledge is substantiated. According to the generalized model, the teaching content design of specific microprocessor l systems of power grid relay protection and automation has been developed. With the help of experimental verification, the effectiveness of the teaching content design of digital systems of relay protection and automation based on causal chains of knowledge has been proven. The results of the research can be used in the educational process of professional training of future engineers in the specialty 141 Electric power, electrical engineering and electromechanics.

Generating synthetic building electrical load profiles using machine learning based on the CRISP-ML(Q) framework

Abstract This study presents a machine learning application for generating synthetic building electrical load profiles. The implementation followed the Cross Industry Standard Process for the development of Machine Learning Applications with Quality assurance methodology, or CRISP-ML(Q) framework, to ensure a systematic machine learning development process. The model training performance was evaluated using the mean absolute error (MAE), root mean squared error (RSME), and coefficient of determination (R2) which were observed to be 0.0739, 0.1119, and 0.5728, respectively. These metrics remained consistent during the model testing phase, suggesting robust model performance. During the initial simulation experiment, the MAE and RMSE of the generated synthetic load profile were found to be 0.014 and 0.016, respectively, underscoring high model accuracy. Additional evaluation experiments showed that the developed machine learning application can generate realistic building load profiles using high-level parameters such as building type, average daily load, and peak demand. This study can aid in the development of demand-side management strategies and building energy management systems by providing realistic building electrical load profiles especially when real-world data is limited. For future work, researchers can consider integrating additional model features, refining data processing methods, and developing an agile version of the CRISP-ML(Q) framework.

Rancang Bangun Aplikasi Sistem Penggajian Karyawan di Yayasan Mitra Tani Mandiri Kabupaten Nagekeo Berbasis Web Menggunakan Metode Waterfall

This study aims to design and develop the application of web -based employee payroll systems at Mitra Tani Mandiri Foundation using the Waterfall method. Efficient and accurate payroll process is a crucial factor in organizational management, especially in Mitra Tani Mandiri Foundation which has employees with various responsibilities and roles. The waterfall method was chosen because of the systematic development stage, starting from the needs analysis to the maintenance stage. The needs analysis phase involves collecting data related to the existing payroll process, employee needs, and management requirements. The design stage includes planning an intuitive user interface, structured database design, and a comprehensive system implementation plan. Implementation is done by building applications according to the specifications that have been designed, involving programming, developing databases, and integration of various components. The testing phase aims to ensure the application is functioning properly, accurately, and according to purpose. The results of this study are web -based payroll systems applications that are expected to improve the efficiency of the payroll process, reduce the potential for human errors, and provide transparency of salary information to employees. The implementation of this application is expected to have a positive impact on the management of human resources and the overall operations of the foundation

Refinement of the train formation plan calculation model by considering the effect of switchyard stations' workload

The article is dedicated to improving the mathematical model for calculating the freight train formation plan (TFP) on the railway network of JSC «Ukrzaliznytsia». The system of organizing freight flows in rail transport is based on strategic planning through TFP, which allows increasing the efficiency of using cars and infrastructure, reducing delays in forming trains, and reducing their transportation time. At the same time, the existing TFP calculation models have certain shortcomings, in particular, the complexity of taking into account the numerous factors that influence the process of train formation. This study proposes a refinement of the TFP mathematical model by including the dependence of wagon-hour costs on the function of the variable utilization factor of technical stations. An automated calculation method developed by one of the authors, based on the application of the mathematical apparatus of genetic algorithms, was used for the calculations. A comparative analysis of the calculation results using the standard and improved models showed that taking into account the impact of station congestion allowed reducing costs by 405.7 wagon-hours, or 3.5% of the total costs for train accumulation and reformatting. The application of the proposed refinement of the TFP model allows the railway operator to obtain more accurate and justified planning results, which will contribute to improving the efficiency of wagon flow management. In addition, the implementation of this approach can serve as the basis for further improving the methods of strategic planning of the transportation process and minimizing the impact of uncertainty factors. The proposed refinement of the TFP calculation model has not only a practical focus, but also represents a theoretical example of the application of an approach aimed at reducing the level of epistemic uncertainty in the management system of the operational work of rail transport. The systematic development and implementation of such approaches creates the basis for mitigating the negative impact of factors that represent sources of other types of uncertainty

Analyzing the Shortcomings in Smart Healthcare for Remote Home Care-A Case Study of the Taiwan Market.

In Taiwan, remote healthcare initially focused on telemedicine, with systematic development starting in 2007 through the "Remote Care Pilot Program" and subsequent initiatives. Significant advancements came with the "Remote Health Care Services Development Plan" in 2010, which integratedArtificial intelligence and Information and communications technologies, enhancing smart healthcare in home care. This study investigated strategic gaps in smart healthcare applications for remote home care using a mixed-methods approach, particularly the Analytic Hierarchy Process (AHP). This study identified and ranked strategic gaps, including "legal regulations", "economic factors", "user behavior habits", "policy and culture", and "environment and technology". Findings, based on in-depth interviews with 6 experts and 16 AHP questionnaire samples, highlight "legal regulations" and "user behavior habits" as critical areas needing attention. Addressing these gaps can improve user acceptance and the effectiveness of smart healthcare applications, providing valuable insights for future research and practice in making remote home care more comprehensive and efficient.

Progress in passive spent fuel pool cooling system R&D based on heat pipe technology

Following the Fukushima Daiichi Nuclear Power Plant accident, particularly the hydrogen explosion at Unit 4, the safety of spent fuel pools garnered heightened attention, and the global nuclear industry extensively studied post-accident cooling of spent fuel pools consequently. During this period, the distinguished passive capabilities of heat pipes led to their superior adoption as primary heat exchangers, gradually becoming a technical consensus in the whole field. Starting in 2016, based on the series of PEX (Passive Experimental Facility), the group led by China Nuclear Power Engineering Co., Ltd. (CNPE) commenced continuous research on heat pipe mechanisms, the design of separate plate heat exchangers, and the overall characteristics of the Passive Spent Fuel Pool Cooling System (PSFS). And in 2023, CNPE proposed the conceptual design for the Linglong One PSFS system finally. The PEX series experiments were completed in two phases using four sets of experimental apparatus: the feasibility study phase with PEX00 and PEX00+, smaller-scale experimental setups with heat power 2–10 kW, primarily addressing issues related to heat pipe mechanisms, working fluid selection, optimal filling rate, vacuum maintenance, system startup characteristics, and the engineering feasibility of separate heat pipe heat exchanger; and the prototype testing phase with PEX50K and PEX100K. PEX50K, a medium-scale conceptual prototype test facility with heat power 50–100 kW employing a novel separated plate heat pipe (SPHP), focusing on research on innovative heat pipe devices. PEX100K, a large-scale engineering prototype test facility with heat power 100–200 kW employing traditional separated tube heat pipes (STHP), aimed at performance verification of engineering prototype units. After five years of research, the SPHP-based approach was ultimately selected, while the initial one with STHP was discarded. This paper provides a comprehensive overview of CNPE's pioneering, exhaustive, and systematic research and development process on SPHP and PSFS. details the PEX series experimental apparatus, and presents the main conclusions. More detailed experimental data, discussions on specific phenomena in certain experiments, detailed descriptions of equipment's processes, and ongoing actual system-level tests will be discussed in subsequent papers.

Seasonal variations in city color preferences incorporating sex and age factors

ABSTRACT City color, serving as a pivotal element within the urban landscape, has garnered significant scholarly attention. Numerous cities have diligently instituted city color planning initiatives to enhance urban landscapes and cultivate city images. The color preference of citizens serves as a crucial foundation for the systematic development of city color planning. Nevertheless, the dynamic aspect of city color preferences is frequently neglected in previous research. Therefore, this article examined seasonal variations in city color preferences using Busan Metropolitan City, South Korea, as an illustrative case. Data collected through a questionnaire survey underwent statistical analyses, including the chi-square test, Wilcoxon rank sum test, and multiple logistic regression, to investigate the influence of seasons on city color preference. The findings revealed that seasons primarily impact the hue preferences in city colors, rather than brightness and chroma preferences. Furthermore, sex and age factors were introduced, and the Cochran–Mantel–Haenszel (CMH) test was employed to identify demographic groups exhibiting seasonal variations in city color preferences. The analysis disclosed noteworthy seasonal disparities in city color preference, particularly among middle-aged and elderly males, who exhibited a significant decrease in preference for yellow and a notable increase in preference for green during winter compared to summer. The outcomes of this study provide valuable insights for informing city color planning. Additionally, the distinctive city color preferences observed among different demographic groups can be effectively applied in urban regeneration initiatives, thereby contributing to human well-being.

The Development of Islamic Banking in the UK – A Comparison of Islamic and Conventional Banking

The purpose of the article is to compare the development of several Islamic banks and conventional banks operating in the UK in 2014–2021. A statistical method of linear ordering of objects characterized by several variables, which is simple in interpretation, was used. The main difficulty was to take into account the time-varying quotation of the values of the considered variables. A novel method was proposed to take into account both the value of several variable and their variability over time. In this method, the emphasis can be placed on the final reslut, that is, consider only the values of the variables at the beginning and end of the period under study but the smoothness of the systematic development of the bank can be taken into account by placing emphasis on the analysis of the variable-stimulants from year to year. In the obtained ordering, Islamic banks grew more dynamically than conventional banks in all considered configurations of variables.

Design and Implementation of an Ontology for Measurement Terminology in Digital Calibration Certificates.

Digital Calibration Certificates (DCCs) are a key focus in metrology digitalization, necessitating that they satisfy the criteria for machine readability and understandability. Current DCCs are machine-readable, but they are still missing the essential semantic information required for machine understandability. This shortfall is particularly notable in the lack of a dedicated semantic ontology for measurement terminologies. This paper proposes a domain ontology for measurement terminologies named the OMT (Ontology for Measurement Terminology), using a foundation of metrological terms from standards like the International Vocabulary of Metrology (VIM), the Guide to the Expression of Uncertainty in Measurement (GUM), and JJF1001. It also incorporates insights from models such as the SI Reference Point, the Simple Knowledge Organization System (SKOS), and the DCC Schema. The methodology was guided by Stanford's Seven-Step Method, ensuring a systematic development process tailored to the needs of metrological semantics. Through semantic expression capability verification and SPARQL query validations, the OMT has been confirmed to possess essential machine readability and understandability features. It has been successfully integrated into version 3.2.1 of DCCs across ten representative domains. This integration demonstrates an effective method for ensuring that DCCs are machine-readable and capable of interoperating within digital environments, thereby advancing the research in metrology digitization.

MDB-66. HIGH-THROUGHPUT SMALL MOLECULE DRUG SCREENING, TRANSCRIPTOMICS AND INTEGRATIVE AI IDENTIFY TARGETABLE MYC-DEPENDENT THERAPEUTIC VULNERABILITIES IN HIGH-RISK MEDULLOBLASTOMA

Abstract INTRODUCTION MYC-amplified Group 3 medulloblastomas (MBGroup3-MYC) do not respond to conventional up-front therapies and are almost universally fatal (&amp;lt;5% survival). MYC is not directly targetable. Thus, the systematic development of therapies which target complementary MYC-dependencies offers clear potential to rationally re-design effective therapeutic strategies. METHODS Isogenic cell-based models with regulable shRNA MYC-knockdown were developed in three independent MYC-amplified backgrounds (D283Med; D425Med; HD-MB03). These were utilised to i) define the MYC-dependent transcriptome/proteome in MBGroup3, through analysis in conjunction with our primary tumour cohort, and ii) as the basis of an automated MYC-dependent high-throughput drug screen (HTS; &amp;gt;500 clinically-actionable compounds). Bespoke integrative AI tools and bioinformatic analysis, and subsequent siRNA/pharmacodynamic validation, identified and validated candidate MYC-dependent therapeutic vulnerabilities. Prioritised drugs were advanced to pre-clinical trials across two in vivo MBGroup3 models (GTML/Trp53KI/KI (GEMM; MYCN-driven) and GMYC (GEMM-derived allografts; MYC-driven)) to evaluate candidate efficacy and toxicity. RESULTS shRNA-mediated MYC knockdown could be maintained for 28 days without escape in all models and, as anticipated, was associated with cell cycle abrogation and elevated caspase-3/-7 activity. HTS across all models revealed that MYC expression confers differential dependencies to small molecule inhibitors, with 82 compounds spanning 11 major drug classes demonstrating MYC-dependent activity. AI-based integration of HTS data with model and primary patient MYC-dependent transcriptome data shortlisted multiple druggable molecular targets which, in turn, were independently validated. To date, we have progressed alisertib (AURKAi), volasertib (PLK1i) and prexasertib (CHK1i) to in vivo pre-clinical trials. Promisingly, both alisertib and prexasertib demonstrated efficacy within MBGroup3-MYC models. CONCLUSIONS Integrated human tumour and model-based screening approaches have enabled identification and validation of critical MYC co-dependencies, targetable using established small-molecules, to inhibit MBGroup3 tumour growth. Their further evaluation, including integration into established and/or rationally-designed combinations, will be essential next steps in their (pre-)clinical development.

Development and Usability Evaluation of Transitional Cross-Reality Interfaces

The concept of Transitional Cross-Reality Interfaces where a user can seamlessly transition across the Reality-Virtuality-Continuum dates back to the introduction of the Magic Book in 2001 but recently gained new research momentum since head-mounted displays advanced by combining the former distinctive concepts of augmented reality and virtual reality into a single device. New technological capabilities require new ways of developing applications to satisfy user requirements. Especially in the context of operating in multiple realities, developing AR/VR applications is not a trivial task. In this context, the development of Transitional Cross-Reality Interfaces remains a complex engineering problem that requires specific methods, concepts, and tools. To address this problem and provide a systematic development approach, we propose a conceptual framework for both developing and evaluating Transitional Cross-Reality Interfaces. To evaluate our solution, we implemented a Transitional Cross-Reality Interface based on our framework and evaluated it with both the measurements provided by the framework and additional questionnaires. We found high usability and interesting transitional behavior of users indicating the usefulness of the proposed framework as an underlying software architecture for Transitional Cross-Reality Interfaces.