Adaptive Applications Research Articles

Cross-cultural adaptation and clinical application of Meniere's disease outcomes questionnaire

Objective:To cross-culturally adapt the Meniere's Disease Outcomes Questionnaire（MDOQ） into Chinese language, to evaluate its reliability and validity, and to apply in clinical. Methods:The MDOQ was translated according to the Brislin model. Cross-cultural adaption was done by expert discussion and pilot study. The MDOQ was applied to 101 patients to test its reliability and validity. The quality of life（QOL） of 272 patients was measured by MDOQ-C, analyzing the influence factors of QOL of patients with Meniere's disease. Results:The CR value of each item of MDOQ-C exceeded 3.00, the Cronbach's α coefficient was 0.88, and the Spearman Brown coefficient was 0.90. The Pearson correlation coefficient of MDOQ-C and the DHI was 0.803（P<0.01）. Three factors were extracted by factor analysis, which could explain 60.503% of the total variance. The dimension composition was different from the original scale. The average QOL score of Meniere's disease patients was 52.94±13.87. The main influence factors were age, marital status, work status, with tinnitus and the number of vertigo attacks. Conclusion:The MDOQ-C is reliable and valid. After dimension reconstruction, MDOQ-C can be used to evaluate the QOL of patients with Meniere's disease. Through the preliminary clinical application, the influence factors of quality of life of patients with Meniere's disease were identified, thus providing reference for optimizing clinical management strategies.

Patient self-assessment of urine dipsticks to estimate sodium intake in patients with hypertension.

Dietary sodium restriction is recommended by current guidelines to reduce blood pressure and decrease the risk of cardiovascular disease. Current methods to assess sodium intake such as dietary questionnaires and 24-h urine collection are cumbersome, and the results are not readily available to patients. In this analysis, we evaluated using chloride and creatinine dipsticks as a convenient method to monitor sodium intake, in addition to patients' ability to practice this method independently. This is a post-hoc analysis of a previously published trial, LowSalt4Life, that measured change in sodium consumption over 8 weeks to evaluate the effect of a just-in-time adaptive mobile application intervention. Participants were instructed on how to complete and interpret Quantab® chloride and Multistix® PRO 10 LS creatinine dipstick measurements at home and upload a picture of their results. A pharmacy student interpreted the chloride dipsticks, and intraclass correlation coefficients (ICC) were calculated to assess interrater reliability between the participant and pharmacy student. Predicted 24-h sodium values were calculated by the Kawasaki and Mann methods and compared to actual 24-h sodium excretion. There was a strong interobserver correlation between interpretations of the chloride dipsticks, with the ICC values 0.90, 0.97, 0.99, and 0.98atweeks 2, 4, 6, and 8, respectively. There was a moderate correlation between the dipstick predicted 24-h sodium excretion and actual 24-h sodium excretion at baseline (r=0.506; P<0.001), and a weak correlation at week 8 (r=0.187; P=0.217). When corrected creatinine values were used, the dipstick predicted 24-h sodium excretion correlated with the actual 24-h sodium excretion at baseline and week 8 (r=0.512; P<0.001 and r=0.451; P=0.002). Our analysis suggests that chloride and creatinine dipsticks have the potential to predict total daily excretion of sodium. This method provides patients with an easy, convenient, and accurate method to assess sodium excretion at home. Further research is needed to identify the optimal timing of performing the dipstick analysis as well as ways to improve the creatinine measurement of the urine samples. ClinicalTrials.gov NCT03099343; https://clinicaltrials.gov/ct2/show/NCT03099343.

Sistem Informasi Raport Online Pada Mts Minhajut Tholibin Jakarta Barat

Schools have not fully utilized technological developments in processing data such as student data, teacher data, student attendance, and student report cards, and have not been integrated with the school system due to the lack of an academically adaptable application system. The use of media or dissemination of information is still done by pasting pamphlets on the walls of magazines, as well as storing academic data in archives in a form that is difficult to find. This is considered less effective in school management, given the rapid development of technology today. With the problems that the authors found, an online report card information system application will be designed using the Waterfall method, to make it easier to manage administrative and academic data to be more organized in decision-making in the school environment.

The Influence of Transparency and Control on the Willingness of Data Sharing in Adaptive Mobile Apps

Today, adaptive mobile applications use mobile sensing and user tracking, allowing for adaptation to the users' context and needs. This raises several privacy concerns. Privacy dashboards provide transparency and sharing control; however, their impact on the users' behavior is unclear. To shed light on the effects of (a) transparency and (b) control features, we developed a mobile sensing privacy dashboard and evaluated it in the wild (N=227). We found that the pure presentation of raw logging data is rather deterring, and users tend to use the app less, but offering the user control over the data collection can compensate for that. Users used the control features rarely and, as such, did not affect the data collocation. Our work informs the design of future privacy-enhancing interfaces in applications relying on passively collected mobile sensing data. Moreover, our results encourage the adoption of privacy dashboards in the applications and relieve developers from concerns about the negative influences of transparency information on the quality of collected data.

Single iron atoms embedded in MOF-derived nitrogen-doped carbon as an efficient heterogeneous electro-Fenton catalyst for degradation of carbamazepine over a wide pH

Developing efficient, stable heterogeneous catalysts with wide adaptability to pH is of great significance for the degradation of organic pollutants by electro-Fenton (EF). In this work, a novel heterogeneous EF (Hetero-EF) catalyst, single atomic Fe sites embedded into N-doped porous carbon (Fe-N/C) was prepared using Fe-doped zeolitic imidazolate frameworks as a precursor. Single Fe atoms anchored on N/C were clearly observed by high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM). Due to the single-atom dispersion and the highest content of FeNx, the optimized 0.3Fe-N/C exhibited excellent catalytic activity for the removal of carbamazepine (CBZ) over a wide pH between 3∼11 with very low iron leaching (<0.3 mg/L even at pH 3). The turnover frequency in the Hetero-EF process was 1.6–19 times higher than that of most catalysts in literature. Besides, 0.3Fe-N/C showed superior durability in seven cycling tests and wide suitability to various pollutants. The quenching experiments and electron paramagnetic resonance demonstrated that both OH and 1O2 were responsible for the CBZ degradation, which made 0.3Fe-N/C had a strong tolerance to pH. This work provides a new perspective for the application of atomic Fe-based catalysts, improving stability and pH adaptability in Hetero-EF for wastewater treatment.

Improving Students' Critical Thinking Ability with Enhanced-Open Learning Approach Using Adaptive Hypermedia

The Critical thinking is important in education because it encourages students to gain an understanding of more complex information. High critical thinking skills will lead students to find and conclude their understanding. The prolonged COVID-19 pandemic has made global changes in the implementation of learning. Until now, the learning process is still directed at the online learning model with the help of various Learning Management System (LMS) platforms. Conditions like this have implications for the decline in students' critical thinking skills in various aspects, such as inference, interpretation, explanation, analysis, evaluation, and self-regulation. This study aims at proposing an alternative learning approach, namely the enhanced-open learning model which is used to empower and improve students' critical thinking skills. This learning model was developed using the Research and Development (R&amp;D) method and implemented with an adaptive hypermedia learning application media designed with the Luther development model. The sampling technique used was cluster random sampling on 98 students of informatics education in Surakarta City. The data were analyzed with the prerequisites for normality and homogeneity of the data before the Wilcoxon Signed Rank Test and Mann Whitney U test was carried out to determine the effectiveness of the model. The results of the increase in the gain score obtained from the experiment are in the aspect of interpretation of 93.18%, inference 76.74%, explanation 96.33%, analysis 97, 87%, evaluation 63.01%, and self-regulation 98.13%. Based on the experiments conducted, it is proven that the adaptive open learning approach has a very significant impact on improving students' critical thinking aspects so that it can be concluded that the model is effective in improving students' critical thinking skills.

Adaptive co-simulation method and platform application of drive mechanism based on Fruit Fly Optimization Algorithm

The simulation of the control rod drive mechanism is a co-simulation process of multi-physics coupling. It has the problem of conflict between simulation accuracy and efficiency in the simulation process based on the centralized simulation idea. Therefore, a multidisciplinary co-simulation method and simulation platform with adaptive step size are proposed in this paper. According to the characteristics of the simulation nodes, the fruit fly optimization method is used to determine the adaptive step size of different simulation stages. A multi-disciplinary co-simulation platform is constructed based on the Isight which can integrate co-simulation tool. The co-simulation process of the control rod drive mechanism is completed with the method and platform. The results show that the simulation accuracy of the platform built in this paper is increased by 23%, and the simulation efficiency is increased by 64%, which verifies that the proposed method has good compatibility in terms of simulation accuracy and efficiency.

Mobile information technology's impacts on service innovation performance of manufacturing enterprises

PurposeGiven the rapid adoption of intelligent and digital manufacturing among the current business environment, emerging mobile information technology (MIT) becomes an ever more important factor, driving innovations in manufacturing sectors. This paper analyzes the impact of MIT on innovation service performance in manufacturing firms and builds a model structuring the mechanisms of this information technology. Design/methodology/approachThis paper proposes a theoretical model and derives a set of hypotheses based on the dynamic capability theory and innovation diffusion theory. Data used in this paper is collected via surveying 462 manufacturing firms in China using valid questionnaires. Statistical analysis, such as the AMOS method, is then carried out using the data collected to investigate and identify influencing factors upon which to build the model and test the hypotheses. FindingsThis paper presents findings that indicate MIT having a direct impact on a firm's service innovation capabilities (SIC) and service innovation performance (SIP). In particular, SIC continuously drives the growth of SIP in a firm, and hence acts as a mediating factor. Moreover, results indicate that both SIC and SIP varies with the strength of innovation network in each firm, while the moderated mediating effect of SIC remains constant. In other words, the performance of service innovation was not to be impacted by certain basic conditions of firms. Originality/valueThis paper is the first attempt to investigate the relationship between the manufacturing industry and advanced technology adoption of enterprise innovation networks and service innovation capabilities. Results are application for adaptation in firms within the manufacturing industry regarding adoption of such advanced technology, such as MIT, and are supportive of these firms constructing enterprise innovation networks and investing in efforts to shape service innovation capabilities. Findings suggests that initiatives associated with adoption of advanced technology are likely to improve service transformation abilities and service innovation performance.

Mechano-Regulable and Healable Silk-Based Materials for Adaptive Applications.

Mechanically adaptive materials responsive to environmental stimuli through changing mechanical properties are highly attractive in intelligent devices. However, it is hard to regulate the mechanical properties of most mechanically adaptive materials in a facile way. Moreover, it remains a challenge to achieve mechano-regulable materials with mechanical properties ranging from high strength to extreme toughness. Here, inspired by the reversible nanofibril network structure of skeletal muscle to achieve muscle strength regulation, we present a mechano-regulable biopolymeric silk fibroin (SF) composite through regulating dynamic metal-ligand coordination bonds by using water molecules as competitive regulators. Efficient interfacial hydrogen bonds between tannic acid-tungsten disulfide nanohybrids and the SF matrix endow the composite with high mechanical strength and self-healing ability. The resulting composite exhibits 837-fold change in Young's modulus (5.77 ± 0.61 GPa to 6.89 ± 0.64 MPa) after water vapor triggering, high mechanical properties (72.5 ± 6.3 MPa), and excellent self-healing efficiency (nearly 100%). The proof-of-concept ultraconformable iontronic skin and smart actuators are demonstrated, thereby providing a direction for future self-adaptive smart device applications.

Testing Self-Adaptive Software With Probabilistic Guarantees on Performance Metrics: Extended and Comparative Results

This paper discusses methods to test the performance of the adaptation layer in a self-adaptive system. The problem is notoriously hard, due to the high degree of uncertainty and variability inherent in an adaptive software application. In particular, providing any type of formal guarantee for this problem is extremely difficult. In this paper we propose the use of a rigorous probabilistic approach to overcome the mentioned difficulties and provide probabilistic guarantees on the software performance. We describe the set up needed for the application of a probabilistic approach. We then discuss the traditional tools from statistics that could be applied to analyse the results, highlighting their limitations and motivating why they are unsuitable for the given problem. We propose the use of a novel tool – <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">the Scenario Theory</i> – to overcome said limitations. We conclude the paper with a thorough empirical evaluation of the proposed approach, using three adaptive software applications: the Tele-Assistance Service, the Self-Adaptive Video Encoder, and the Traffic Reconfiguration via Adaptive Participatory Planning. With the first, we empirically expose the trade-off between data collection and confidence in the testing campaign. With the second, we demonstrate how to compare different adaptation strategies. With the third, we discuss the role of the randomisation in the selection of test inputs. In the evaluation, we apply the scenario theory and also classical statistical tools: Monte Carlo and Extreme Value Theory. We provide a complete evaluation and a thorough comparison of the confidence and guarantees that can be given with all the approaches.

Adaptive Control and Application for Nonlinear Systems With Input Nonlinearities and Unknown Virtual Control Coefficients.

This article is devoted to an adaptive tracking control problem for nonlinear systems with input deadzone and saturation, whose virtual control coefficients include the known and unknown terms. A novel smooth function is first introduced to approximate the input nonlinearities. By utilizing an auxiliary variable and the Nussbaum gain technique, an improved real control signal is constructed to handle the uncertainties of the virtual control coefficients and input nonlinearities. Furthermore, an adaptive tracking controller is constructed and applied to the attitude control of a quadrotor, which guarantees the boundedness of all the signals in the resulting closed-loop system. Finally, both stability analysis and simulation results validate the effectiveness of the developed control strategy.

Adaptive weight grey wolf algorithm application on path planning in unknown environments

Autonomous mobile robots developed using metaheuristic algorithms are increasingly becoming a hot topic in control and computer sciences. Specifically, finding the shortest route to the goal and avoiding hurdles are current subjects of autonomous mobile robots. The Modified Grey Wolf Optimization (MGWO) is demonstrated in this work using two approaches: first, the Adaptive Adjustment Approach of the Control Parameters, and second, the Adaptive Variable Weights method. Those two methods are utilized for updating the wolf position, accelerate convergence, and cut down on time. The proposed online optimization approach is used in three different environments including an environment with unknown static obstacles, dynamic obstacles, and an environment with a dynamic target. The online optimization method is performed using two phases which are the sensors reading phase and the path calculation phase. The proposed approach can solve a local minima problem in the static obstacles. A comparison study result between the proposed method and two other algorithms revealed that the proposed algorithm performed better in avoiding obstacles, which include the situation with the local minima. Finally, when put to comparison with Hybrid Fuzzy-Wind Driven Optimization and Adaptive Particle Swarm Optimization the average improvement rates in route length are 2.86% and 4.70391%, respectively.

Adaptation: A Twin Concept in Literature and Translation

While volumes of works have been published on adaptation as a concept, little has been done on the issue of adaptation in literature and translation. Adaptation can, therefore, be defined generally as an action or a process of changing something or of being changed to suit a new situation. It is the act of changing something or changing an act to make it suitable for a new purpose or situation. The idea of adaptation is not limited to both literature and translation only but it can be extended to films and their contemporary features. In literature, adaptation serves as a technique of narration and it is applicable in all genres of literature. The concept is equally applicable in translation studies; it serves as a technique of translation which may be applied to isolated parts of the text in order to deal with specific differences between the language and culture of the source text and that of the target text. Adaptation ameliorates cultural narrative, by considering the cultural links between the source language and the target language in translation studies. This is going to show us that adaptation elucidates more on the cultures and how these can be adapted into a real sense of newness of ideas in another cultural cycle. It is further explicated that the concept can be employed as an interdisciplinary one which can be applied in anthropology, philosophy, cultural studies, history, sciences and in all fields of arts. Diverse examples of adaptation are explored in series of African literature, western literature and translation studies. The major objective of this is to examine how adaptation can be described as a twin concept in literature and translation. This study also attempts to explicate the areas of convergence and divergence in the concept and application of adaptation in literature and translation studies. In this study, we adopt descriptive, narrative and expository methods where we describe, narrate and reveal the necessary issues on adaptation as a technique in both literature and translation. In this study, we adopt Skopos theory, which is formulated by the German translator, Hans Vermeer in 1970’s. The theory suggests that the mission and the purpose of translation are of paramount importance. The process of translation is determined by the function of the product. This function is specified by the addressee. This theory is one of the functionalist approaches whose aim is to dethrone the source text (ST). The word “Skopos” was from Greek, meaning purpose or aim. It is used as a technical term for the purpose of translation. The Skopos theory principally suggests that translations should focus on the target culture and language illustrating the source text, their effects on the reader, and the original author’s purpose as decisive factors, rather than the effects and purposes of the source language. The study concludes that Adaptation makes the old literary work popular and marketable because it is a trend to the original work. Literary adaptation that is done rightly has more advantages than disadvantages. One of the common reasons a book or story is adapted is because the characters in that story are already well-known and this help the adapted one. Adaptation will remain relevant in all fields of arts as long as the concept of masterpiece is adapted into the current trends in literary and translation studies. The concept will continue to be significant all over the world because it exposes literary ideas to different audience. Adaptation is as old as the world and it cannot cease because of its pertinence in a changing world.

EXPLORING THE USE OF ADAPTIVE LEARNING TECHNOLOGY IN HIGHER EDUCATION WRITING CLASSES: STUDENTS’ PERSPECTIVES

This study investigates students' perspectives on using Adaptive Learning Technology (ALT) in writing classes in higher education. The ALTs used include Grammarly as an Automated Writing Evaluation (AWE), Quizizz as an Adaptive Content Application (ACA), and Google Docs and Miro as Digital Writing Platforms (DWP). Underpinning Bloom’s Taxonomy, this mixed-methods research design combining a questionnaire adapted from Nguyen and Nguyen (2022), Gohar and El-Ghool (2016) as well as an observation checklist were employed to collect both quantitative and qualitative data on students' overall attitudes toward ALT, perceptions of its utility, satisfaction with its implementation, challenges, and recommendations. The findings indicate that students generally had a positive attitude towards ALT, particularly its capacity to provide personalized feedback and support for specific learning requirements. However, obstacles such as technical difficulties and the need for both students and teachers to receive adequate training and support must be addressed. The study additionally suggests several recommendations for the implementation of ALT in writing classes.

Cloud Computing Database and Travel Smart Platform Design Based on LSTM Algorithm

Information technology has played a key role in the development of the tourism planning service industry and has now become an important foundation for the survival and rapid development of the industry. In this context, due to the fast updating and popularization of information technology, it has greatly promoted the development of the tourism industry. In order to meet the current public demand for tourism information, this paper integrates cloud computing, VR technology, and big data analysis technology to build a smart platform for intelligent perception tourism information services. The system can obtain tourism information through mobile Internet terminals. Among them, the database of the smart tourism planning platform is the most important module. Aiming at the many difficulties in adapting data encryption in cloud storage applications, this article designs an adaptive CloudCrypt data encryption system based on cloud computing technology and proposes dynamic JavaScript dynamic analysis and automatic identification of data technology, through adaptive different cloud applications to obtain data encryption protection. CloudCrypt is suitable for typical cloud applications, such as mail and storage. The entry cost of the system is extremely low; it can fully guarantee the security of the tourism information platform database and can integrate wireless sensor networks into the tourism information platform. The network system composed of sensor nodes activates detection, calculation, and communication modules through wireless communication and has the advantages of low cost, low power consumption, and fast networking speed. In this paper, through the construction of integrated wireless sensor technology and cloud computing database, it is applied to the construction of a tourism smart platform, thereby promoting the development of smart travel technology.

Mechanically mutable polymer enabled by light.

Human skin is a remarkable example of a biological material that displays unique mechanical characters of both soft elasticity and stretchability. However, mimicking these features has been absent in photoresponsive soft matters. Here, we present one synthetic ABA-type triblock copolymer consisting of polystyrene as end blocks and one photoresponsive azopolymer as the middle block, which is stiffness at room temperature and shows a phototunable transition to soft elastics athermally. We have synthesized an elastics we term “photoinduced soft elastomer,” where the photo-evocable soft midblock of azopolymer and the glassy polystyrene domains act as elastic matrix and physical cross-linking junctions, respectively. On the basis of the photoswitchable transformation between stiffness and elasticity at room temperature, we demonstrated precise control over nanopatterns on nonplanar substrates especially adaptable in the human skin and fabrication of packaged perovskite solar cells, enabling the simple, human-friendly, and controllable approach to be promising for mechanically adaptable soft photonic and electronic packaging applications.

Student Perceptions and Engagement in Video-based Learning for Microbiology Education

Online learning increases the physical distance between instructors and students and depending on the mode of delivery, it can be challenging to close this gap. To ameliorate this potential for student isolation, instructors need to communicate to students in a variety of ways, blending original online resources with synchronous interactive learning activities. During 2020, 34 lecture videos were created for a large undergraduate microbiology and immunology course offered at The University of Queensland. The teaching team applied a subset of Mayer’s multimedia learning design principles – embodiment, mixed perspectives, segmenting, signalling – to create videos featuring instructor presence, multiple presentation styles, and dynamic pacing. When compared to voice-over presentations created by automated lecture capture software, the outcomes of this design process increased student engagement in video-based learning across the 2020 and 2021 course offerings. Analysis of student perception data collected by online questionnaires and interviews revealed broad agreement with the design principles used for video-based learning. However, their value of on-screen instructor visibility, graphics, and text was variable as a result of individual preferences. Together these findings present a case study in which instructional videos were developed iteratively through the selective application of multimedia design principles and strategic adaptation of existing learning resources.

Adaptive parallel applications: from shared memory architectures to fog computing (2002–2022)

Adaptive parallel applications: from shared memory architectures to fog computing (2002–2022)

Multithreaded runtime framework for parallel and adaptive applications

Multithreaded runtime framework for parallel and adaptive applications

Fast VMAT planning for prostate radiotherapy: dosimetric validation of a deep learning-based initial segment generation method

Objective. To develop and evaluate a deep learning based fast volumetric modulated arc therapy (VMAT) plan generation method for prostate radiotherapy. Approach. A customized 3D U-Net was trained and validated to predict initial segments at 90 evenly distributed control points of an arc, linked to our research treatment planning system (TPS) for segment shape optimization (SSO) and segment weight optimization (SWO). For 27 test patients, the VMAT plans generated based on the deep learning prediction (VMATDL) were compared with VMAT plans generated with a previously validated automated treatment planning method (VMATref). For all test cases, the deep learning prediction accuracy, plan dosimetric quality, and the planning efficiency were quantified and analyzed. Main results. For all 27 test cases, the resulting plans were clinically acceptable. The V 95% for the PTV2 was greater than 99%, and the V 107% was below 0.2%. Statistically significant difference in target coverage was not observed between the VMATref and VMATDL plans (P = 0.3243 > 0.05). The dose sparing effect to the OARs between the two groups of plans was similar. Small differences were only observed for the Dmean of rectum and anus. Compared to the VMATref, the VMATDL reduced 29.3% of the optimization time on average. Significance. A fully automated VMAT plan generation method may result in significant improvement in prostate treatment planning efficiency. Due to the clinically acceptable dosimetric quality and high efficiency, it could potentially be used for clinical planning application and real-time adaptive therapy application after further validation.