Accessibility for Everyone in Health Communication Mobile Application Usage

With the development of new communication technologies and the change and transformation of mobile applications, communication styles also acquire a different dimension. Currently, individuals can access information about many health-related issues easily and quickly. Mobile applications also provide support to individuals in this area anywhere at any time. However, awareness about mobile applications and their availability is important at this point. While the transformation in the technological field makes life easier for users, not everyone (young, old, disabled, etc.) enjoys the advantages equally. In this study, user-based usability testing will be carried out on the axis of E-nabız application with female users above 65 years selected according to certain criteria. The E-nabız application is a platform for all citizens registered to the E-devlet system to access health information. In this context, besides pointing out the accessibility problems of the application, possible solutions will also be offered.

A Survey on Different Approaches to Automating the Design Phase in the Software Development Life Cycle

Software design is a basic plan of all elements in the software, how they relate to each other in such a way that they meet the user requirements. In software development process, software design phase is an important phase as it gives a plan of what to do and how to do it during the implementation phase. As the technology is evolving and people's needs in the technological field are increasing, the development of software is becoming more complex. To make the development process somewhat easy, it is always better to have a plan which is followed throughout the process. In this way, many problems can be solved in the design phase, for which a number of tools and techniques are present. One is known as Design Patterns. In software engineering, a design pattern is a general solution to commonly occurring problems in software design. A design pattern isn't a finished design that can be transformed directly into code.

Att-BiL-SL: Attention-Based Bi-LSTM and Sequential LSTM for Describing Video in the Textual Formation

With the advancement of the technological field, day by day, people from around the world are having easier access to internet abled devices, and as a result, video data is growing rapidly. The increase of portable devices such as various action cameras, mobile cameras, motion cameras, etc., can also be considered for the faster growth of video data. Data from these multiple sources need more maintenance to process for various usages according to the needs. By considering these enormous amounts of video data, it cannot be navigated fully by the end-users. Throughout recent times, many research works have been done to generate descriptions from the images or visual scene recordings to address the mentioned issue. This description generation, also known as video captioning, is more complex than single image captioning. Various advanced neural networks have been used in various studies to perform video captioning. In this paper, we propose an attention-based Bi-LSTM and sequential LSTM (Att-BiL-SL) encoder-decoder model for describing the video in textual format. The model consists of two-layer attention-based bi-LSTM and one-layer sequential LSTM for video captioning. The model also extracts the universal and native temporal features from the video frames for smooth sentence generation from optical frames. This paper includes the word embedding with a soft attention mechanism and a beam search optimization algorithm to generate qualitative results. It is found that the architecture proposed in this paper performs better than various existing state of the art models.

Machine Learning in Assessing the Performance of Hydrological Models

Machine learning has been employed successfully as a tool virtually in every scientific and technological field. In hydrology, machine learning models first appeared as simple feed-forward networks that were used for short-term forecasting, and have evolved into complex models that can take into account even the static features of catchments, imitating the hydrological experience. Recent studies have found machine learning models to be robust and efficient, frequently outperforming the standard hydrological models (both conceptual and physically based). However, and despite some recent efforts, the results of the machine learning models require significant effort to interpret and derive inferences. Furthermore, all successful applications of machine learning in hydrology are based on networks of fairly complex topology that require significant computational power and CPU time to train. For these reasons, the value of the standard hydrological models remains indisputable. In this study, we suggest employing machine learning models not as a substitute for hydrological models, but as an independent tool to assess their performance. We argue that this approach can help to unveil the anomalies in catchment data that do not fit in the employed hydrological model structure or configuration, and to deal with them without compromising the understanding of the underlying physical processes.

Assessing Economic Security of the Russian Federation in Technological Field

The article studies elements of technological sphere, such as science, technology and innovation. Appraisal of economic security of Russia was conducted by using methodology of utmost crucial indicators. The most important indicators and their crucial values based on the principle ‘resources – results’ were selected, which gave an opportunity to estimate the efficiency of resource investment and their use. The author substantiated the threshold values for each indicator The method of utmost crucial values together with zoning by the degree of risk can allow us to identify the possibility of threat arising and understand their degree for spheres being investigated. During the analysis the standing of values in accordance with zone distribution was estimated and general trends were found out. On the basis of estimation the general dynamics of indicators was plotted in the form of indexes of economic security and on their foundation the integral appraisal of the condition of economic security in technological field was built. In conclusion the author stated the overall level of technological sphere and described threats to economic security of Russia.

Development of Decision Support System Based on the Bayes ARD Algorithm for Irrigation of Cotton

Cotton is a plant, which is mainly cultivated in regions where the irrigation is necessary as rainwater is not adequate. Researches in the recent years have showed that the irrigation water used could be declined. Improvements in the technological field has made Decision Support Systems combined with Neural Networks and data analysis, an important tool of sustainable agriculture. Cotton producers need to reduce irrigation water needs and that can be achieved by using new technologies. The development Decision Support System was conducted, having 3 different types of input. Data derived from a variety of IoT sensors, weather stations, and on-site measurements (yield and ΕΜ38) derived from 3 fields in Greece, creating a dataset of 9 different inputs. A total of 13 different algorithms were tested and evaluated in order to determine which one is the ideal for our dataset. The adoption of this technology in real data predicted the reduction of the irrigation times, ensuring that there will be no losses in the final yield.

Opportunities to Develop Lifelong Learning Tendencies in Practice-Based Teacher Education: Getting Ready for Education 4.0

Education 4.0 prepares new generations to develop the skills required to perform in a technological, dynamic, and unpredictable world. The main barrier to implementing Education 4.0 in schools is that teachers have not been trained for it. Given the advances and new resources of the technological field, teacher preparation will be insufficient if it focuses on technological skills but does not incorporate the necessary dispositions for lifelong learning. Universities have the ethical imperative to update teacher education so teachers can become lifelong learners. The objective of this study was to understand whether practice-based curricula offer opportunities to promote lifelong learning tendencies. We used a sequential explanatory method. Quantitative and qualitative instruments were applied to pre-service teachers (survey: n = 231, semi-structured interviews: n = 8), and causal and descriptive approaches were supported by a structural equation model and constant comparative method, respectively. Data triangulation confirmed and added depth to the relationship found. Practice opportunities provided by teacher educators in learning activities and assessment tasks promote curiosity, motivation, perseverance, and self-learning regulation, when they are (i) systematic; (ii) relevant to the classroom work; (iii) presented with clear instructions and effective rubrics; (iv) accompanied with feedback focused on the task, soliciting reflection, and performed by peers and teacher educators in a trustworthy environment. This research may be of value to universities looking to renew their Education 4.0 programs because it shows that practice-based curricula not only transform pre-service teachers into teaching experts but also into lifelong learners.

A Methodology for Evaluation and Distribution of Patent Applications to INPI-BR Patent Examiners: A Case Study in the Electricity Field

This paper presents the development of a new methodology for evaluation and distribution of patent applications to the examiners at the Brazilian Patent Office considering a specific technological field, represented by classification of the application according to the International Patent Classification (IPC), and the variables corresponding to the volume of data of the application and its complexity for the examination process. After identifying the most relevant variables, such as the Specific Areas of Expertise (ZAE) of the examiners, a mathematical model was developed, including: (a) application of the principal component analysis (PCA) method; (b) calculation of a General Complexity Ratio (IGC); (c) classification into five classes (very light, light, moderate, heavy and very heavy) according to IGC average ranges and standard deviations; (d) implementation of a logic of distribution, compensating very heavy applications with very light ones, and light applications with heavy ones; and (e) calculation of a Distribution Balancing Ratio (IBD), considering the differences between the samples’ medians. The model was validated using a sample of patent applications including, in addition to the identified variables, the time for substantive examination by the examiner. Then, a correlation analysis of the variables with time and a comparison of the classifications according to the time and the IGC generated by the model were carried out. The results obtained showed a high correlation of the IGC with time, above 80%, as well as correct IGC classes in more than 80% of applications. The model proposed herein suggests that the three main relevant variables are: total number of pages, total number of claims, and total number of claim pages.

Research of trends in the development of laser additive manufacturing in the Russian Federation on the basis of patent information

The article presents the results of the analysis of patent documentation on laser additive manufacturing registered in the territory of the Russian Federation. As a result of the research, the dynamics of patent activity is determined, the top patent holders, the leading countries in the considered technological field are identified, the top of inventors is compiled, the main technological segments for application of patented solutions from the field of laser additive manufacturing are identified.