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Following the commodification reform of residential properties in China, multi-unit residential buildings (MURBs) have emerged as the most prevalent housing type owing to their high economic value and convenient infrastructure. In recent years, there has been an increasing concern regarding the potential negative impacts of MURBs on residents. To address this issue, in this study, a survey was conducted among 552 purchasers, and methods such as expert questionnaires, factor analysis, Kano two-dimensional quality, and analytic hierarchy process (AHP) were employed to evaluate the significance of 19 factors related to the quality of MURBs’ unit spatial layouts. An index model summarizing their utility was developed. The research findings indicated that spatial function held the greatest influence, followed by indoor environment, with spatial organization ranking last. Moreover, we analyzed the influence of preferences on satisfaction and the variations in preferences based on sociodemographic factors. The results aim to assist real estate developers and purchasers in evaluating the quality of housing spatial layouts, ultimately enhancing the overall quality and comfort of MURBs.

In contemporary times, science-based technologies are needed for launching innovative products and services in the market. As technology-based management strategies are gaining importance, associated patents need to be comprehensively studied. Previous studies have proposed predictive models based on patent factors. However, technology-based management strategies can influence the growth and decline of firms. Thus, this study aims to estimate uncertainties of the factors that are frequently used in technology-based studies. Furthermore, the importance of the factors may fluctuate over time. Therefore, we propose a Bayesian neural network model based on Flipout and four research hypotheses to evaluate the validity of our method. The proposed method not only estimates the uncertainties of the factors, but also predicts the future value of technologies. Our contribution is to (i) provide a tractable Bayesian neural network applicable to big data, (ii) discover factors that affect the value of technology, and (iii) present empirical evidence for the timeliness and objectivity of technology evaluation. In our experiments, 3781 healthcare-related cases of patents were used, and we found that the proposed hypotheses were all statistically significant. Therefore, we believe that reliable and stable technology-based management strategies can be established through our method.

A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

Creation of the national innovation system and development of innovative strategies and programs have become the key tasks for the Republic of Kazakhstan in the context of establishment of the knowledge-based economy. With the purpose of defining the state and priority areas of development of the innovative infrastructure of the republic, it was analyzed based on the data collected through a questionnaire survey, study of the scientific literature and policy documents, as well as analysis of statistical data. The situational SWOT analysis was the methodical research tool.

The Kuandian County (Northeast China) has suffered frequent rockfall disasters because of its topography, geological setting, and anthropogenic activities. This research work conducts rockfall susceptibility assessment in Kuandian County by comprehensively combining the Information Content Method (ICM) with the Analytic Hierarchy Process (AHP). Firstly, information contents of the evaluation factors are calculated via statistical analysis on the existing rockfall sites. Then, weights of the evaluation factors are determined by adopting AHP. In the final step, the susceptibility value of each evaluation unit is obtained by weighted summation of the information content of each evaluation factor. The combination of ICM and AHP is able to promote the objectiveness of the evaluation process and accuracy of the evaluation results. Furthermore, in order to analyze the influence of evaluation factor setting on susceptibility, assessments using reduced number of evaluation factors are also conducted for comparative analysis. Additionally, to analyze the influence of evaluation units on susceptibility, comparative analysis on the assessment results from both slope units and grid units in a small area is performed. The susceptibility assessment results presented in this study are generally consistent with the current situation of rockfall disasters in Kuandian County, providing reliable data support for disaster prevention and mitigation. Furthermore, the outcome of this study serves as a methodological reference for rockfall risk assessment in Northeast China and other mountainous regions.

Water inrush from confined aquifers in coal seam floor poses a great threat to the safety production of coal mines, while the aquiclude in coal seam floor is a key factor to avoid water inrush disasters. Therefore, an objective and accurate evaluation on the water-resisting ability of the aquiclude can effectively identify potential risk areas of water inrush and plays an important role in preventing such disasters. In this study, Longfeng coal mine was taken as an example. And based on the availability of data and the representativeness of factors, thickness of effective aquiclude, brittle rock thickness of aquiclude, rock quality designation of aquiclude, consumption of drilling fluid, mudstone ratio of aquiclude and fault fracture zone were selected as evaluation factors for water-resisting ability. Besides, the non-linear mathematical method—entropy weight method was combined to construct a comprehensive evaluation model of the water-resisting ability of aquiclude in coal seam floor. On this basis, the information processing and spatial display functions of GIS technology were used to make a thematic map of influencing factors and the thematic map was compositely superimposed. Finally, the evaluation on the water-resisting ability of aquiclude in coal seam floor in Longfeng coal mine was realized. The multi-source information fusion evaluation method based on GIS and entropy weight can comprehensively and objectively reflect the feature that the water-resisting ability of aquiclude in coal seam floor was controlled by multiple factors and had complex formation mechanisms. Also, the evaluation results were displayed intuitively and visually and can provide a scientific basis for the prevention and control of water inrush disasters from coal seam floor.

The rapid evolution of digital health technologies, particularly within the Web 3.0 framework, has underscored eHealth literacy (eHL) as a critical competency for patients engaging with digital health care platforms. Patients in sustained hospital stays, often in vulnerable conditions, face unique challenges in using eHealth tools effectively. However, existing eHL assessment tools are insufficient to address the intricate and dynamic demands of contemporary health care systems, especially for individuals under continuous hospital care. This study aimed to develop the Adult Inpatient eHealth Literacy Scale (AIPeHLS), a comprehensive, multidimensional tool grounded in the Lily Model, to evaluate eHL among adult inpatients within the context of digital health care innovations. The development of the AIPeHLS followed a systematic, multiphase process. Initial item pool generation was informed by a literature review and then refined using the Delphi method, resulting in a preliminary set of 53 items spanning 6 dimensions of the Lily Model. The scale was refined through a pilot survey among 100 individuals requiring inpatient care, followed by item analysis and exploratory factor analysis (EFA). Validation was achieved via a cross-sectional study with 532 participants, using confirmatory factor analysis (CFA) to verify the scale structure, alongside evaluations of convergent, discriminant, criterion-related, and content validity. Reliability was assessed using Cronbach α, Omega, and split-half reliability. The finalized AIPeHLS comprised 44 items across 6 dimensions: traditional literacy, information literacy, media literacy, health literacy, computer literacy, and scientific literacy, reflecting the skills necessary in the Web 3.0 context. Both EFA and CFA confirmed the 6-factor structure, demonstrating acceptable model fit indices (χ²=1974.654 (df=887), root mean square error of approximation=0.048, comparative fit index=0.957, normed fit index=0.925, and incremental fit index=0.957). The scale exhibited robust content validity, convergent and discriminant validity, criterion-related validity, and high internal consistency, with a Cronbach α of .965, Omega coefficient of 0.962, and a split-half reliability of 0.791 for the entire scale. The 44-item AIPeHLS was found to be a reliable and valid instrument for assessing eHL in adult inpatients in the evolving Web 3.0 context. Its comprehensive framework and strong psychometric properties make it an effective tool for health care providers to understand patients' digital health competencies and tailor interventions accordingly. For researchers, our findings provided opportunities to explore the relationship between eHL and health outcomes, while offering valuable insights into the development of more effective eHealth interventions and policies.

The relevance of the study is confirmed by the rapid development of automation in agriculture, in particular, horticulture; the lack of methodological developments to assess the effectiveness of the introduction of robotic technologies; and the need to expand the functionality of mobile robots. The purpose of the study was to increase the level of autonomy of a robotic platform for picking apple fruits based on a new method, develop a system of factors to determine the effectiveness of the introduction of robots in horticulture, and develop a control system using integrated processing of onboard data. The article discussed the efficiency factors for the introduction of robotic systems and technologies in agricultural enterprises specializing in horticulture within the framework of projects with different budgets. The study sample consisted of 30 experts—enterprises that have implemented robotic platforms and scientists specializing in this field. Based on an expert survey of enterprise specialists, a ranked list of 18 efficiency factors was obtained. To select an evaluation factor that determines the effectiveness of robotization and the developed control system, a method for calculating the concordance coefficient (method of expert analysis) was applied as a measure of the consistency of a group of experts for each group of factors. An analysis of the results of the expert evaluation showed that three factors are the most significant: the degree of autonomy of work; positioning accuracy; and recognition accuracy. The generalized indicator of local autonomy of task performance was estimated based on the analysis of a set of single indicators. A system for controlling the movement of an autonomous robotic wheeled platform based on inertial and satellite navigation and calculation of the path to be overcome was developed. The developed software allows for the design of a route for the robotic platform in apple horticulture to automatically perform various technological operations, such as fertilization, growth and disease control, and fruit harvesting. With the help of the software module, the X, Y coordinates, speed and azimuth of movement were given, and the movement of the platform along the given typical turn trajectories in an intensive horticulture environment was visualized.

With the ever-changing needs of consumers and technology, innovation is seen as an essential element of business to ensure the success and competitiveness of companies in the marketplace. The aim of this article is to identify and evaluate the factors determining the implementation of innovations in Lithuanian industrial enterprises. The article examines the concept of innovation, classification models and theoretical factors of innovation implementation. According to the developed research methodology, a questionnaire survey of companies in the engineering and technology industry sector was conducted. The analysis of the research data, which allowed to identify the most important factors for the implementation of innovations, identified problem areas. At the end of the study, a model of factors determining innovation implementation was created, based on the innovation implementation process, empirical research data and the disturbance management process. The model depicts the factors determining and hindering the implementation of innovations identified in the empirical research, integrated into the process of innovation implementation, and the process of eliminating disturbances proposed for the hindering factors. At the end of the article, the research conclusions and suggestions are presented. Article in Lithuanian. Inovacijų diegimą lemiančių veiksnių vertinimas Lietuvos pramonės įmonėse Santrauka Vis sparčiau besikeičiant vartotojų poreikiams ir technologijoms, inovacijos yra laikomos būtinu verslo elementu, užtikrinančiu įmonių verslo sėkmę ir konkurencingumą rinkoje. Šio straipsnio tikslas yra identifikuoti ir įvertinti inovacijų diegimą Lietuvos pramonės įmonėse lemiančius veiksnius. Straipsnyje nagrinėjama inovacijų samprata, klasifikavimo modeliai ir teoriniai inovacijų diegimo veiksniai. Pagal sukurtą tyrimo metodologiją atlikta inžinerijos ir technologijų pramonės sektoriaus įmonių anketinė apklausa. Atlikta tyrimo duomenų analizė, kuri leido identifikuoti svarbiausius veiksnius inovacijų diegimui, nustatytos probleminės sritys. Tyrimo pabaigoje sukurtas inovacijų diegimą lemiančių veiksnių modelis, paremtas inovacijų diegimo procesu, empirinio tyrimo duomenimis bei trikdžių valdymo procesu. Modelyje vaizduojami empiriniame tyrime nustatyti inovacijų diegimą lemiantys ir stabdantys veiksniai, integruoti į inovacijų diegimo procesą, trukdantiems veiksniams pasiūlytas trikdžių eliminavimo procesas. Straipsnio pabaigoje pateiktos tyrimo išvados ir pasiūlymai. Reikšminiai žodžiai: inovacijų diegimas, inovacijų veiksniai, Lietuvos pramonė, veiksnių vertinimas.

In recent decades, necessity to protect environment has been a serious concern for all people and international communities. In appropriate development of human economic activities, subsistence dependence of the growing world population on nature decreases the natural diversity of ecosystems and habitats day by day and provides additional constraints for life and survival of wildlife. As a result, implementation of programs to protect species and ecosystems is of great importance. The current study was carried out to implement a comprehensive strategic environmental management plan in the Mond protected area in southern Iran. Accordingly, the protected area was zoned using multi criteria decision method. According to the numerical models, fifteen data layer were obtained on a scale of 1:50,000. The results revealed that 28.35% out of the entire study area belongs to nature conservation zone. In the following step, in order to offer the strategic planning using strength, weaknesses, opportunities and threats method, a total number of 154 questionnaires were prepared and filled by the relevant experts. For this purpose, after identifying the internal and external factors, they were weighted in the form of matrices as; internal factor evaluation and external factor evaluation. Analytical hierarchy process and expert choice software were applied to weight the factors. At the end, by considering the socioeconomic and environmental issues, the strategy of using protective strategies in line with international standards as well as a strong support of governmental national execution with a score of 6.05 was chosen as the final approach.