Field Of Informatics Research Articles

Application Mobile-Based Augmented Reality for Endemic Animals of Central Kalimantan

The existence of endemic animals typical of Central Kalimantan, such as orangutans and hornbills, is included in the protected species situation because the population numbers have increased slightly along with the clearing of land for the plantation sector, making orangutan and hornbill areas that should be beautiful and natural disappear. Because of this, a medium for conveying information and a unique introduction to the public is needed to know how important it is to know and know the various endangered species in Central Kalimantan to preserve animals. Therefore, this research aims to create an application for Central Kalimantan endemic animals using Mobile-based Augmented Reality to introduce Central Kalimantan's rare animals, starting from the area of residence, characteristics, leading food, and information about animal habitats. The application development process uses the Markerless Augmented Reality (AR) method, which displays 3D objects without using unique markers such as photos or images. The application development stage includes the planning, design, data collection, 3D object creation, application development and application testing using Blackbox testing with the Text Case method, which produces application testing descriptively explaining the application work process. The application for displaying 3D objects was tested in 5 trials, with an average of 5 seconds, and the marker appeared to display 3D objects. This application can have an impact on progress in the field of informatics as a medium for delivering information and learning media using Augmented Reality Markerless.

Information support of scientific research and development in medicine: The approaches and solutions

The authors discuss intellectualization of information analytics; in particular, they analyze the experience of medicine information support through the established system of databases and services of the Coсkrane Collaboration (Cockrane academic network). The authors reconstruct and explore the Cockrane method (model) of information analysis within the subject field of bibliography and informatics based on one of the authors’ personal experience of building systematic reviews of clinical trial results. The goal of the study is to reveal the potential and quality of the information analysis tools within the field of medicine, as well as to explore the feasibility and possibility of their adaptation and limitations in other fields. The study is based on the subject approach in bibliography and information analytics, informological approach, and theoretical tools of applied informatics. The structural functional and iterative methods were applied to study Cockrane through the prism of information analytics, professional user orientation, and knowledge management. The factors of user quality and performance of meta-analytical products for the purposes of evidence medicine are revealed; among them, source selection methods, data processing, procedural and organizational models, critical reviewing, and user differentiation in presenting information search findings. The analysis of meta-analytical information product building in evidence medicine enables to identify the range of methodological problems and promising vectors in the information studies.

Data Analysis of Ab initio Effective Hamiltonians in Iron-Based Superconductors — Construction of Predictors for Superconducting Critical Temperature

High-temperature superconductivity occurs in strongly correlated materials such as copper oxides and iron-based superconductors. Numerous experimental and theoretical works have been done to identify the key parameters that induce high-temperature superconductivity. However, the key parameters governing the high-temperature superconductivity remain still unclear, which hamper the prediction of superconducting critical temperatures ($T_\text{c}$s) of strongly correlated materials. Here by using data-science techniques, we clarified how the microscopic parameters in the $ab$ $initio$ effective Hamiltonians correlate with the experimental $T_\text{c}$s in iron-based superconductors. We showed that a combination of microscopic parameters can characterize the compound-dependence of $T_\text{c}$ using the principal component analysis. We also constructed a linear regression model that reproduces the experimental $T_\text{c}$ from the microscopic parameters. Based on the regression model, we showed a way for increasing $T_\text{c}$ by changing the lattice parameters. The developed methodology opens a new field of materials informatics for strongly correlated electron systems.

Application Mobile-Based Augmented Reality for Endemic Animals of Central Kalimantan

The existence of endemic animals typical of Central Kalimantan, such as orangutans and hornbills, is included in the protected species situation because the population numbers have increased slightly along with the clearing of land for the plantation sector, making orangutan and hornbill areas that should be beautiful and natural disappear. Because of this, a medium for conveying information and a unique introduction to the public is needed to know how important it is to know and know the various endangered species in Central Kalimantan to preserve animals. Therefore, this research aims to create an application for Central Kalimantan endemic animals using Mobile-based Augmented Reality to introduce Central Kalimantan's rare animals, starting from the area of residence, characteristics, leading food, and information about animal habitats. The application development process uses the Markerless Augmented Reality (AR) method, which displays 3D objects without using unique markers such as photos or images. The application development stage includes the planning, design, data collection, 3D object creation, application development and application testing using Blackbox testing with the Text Case method, which produces application testing descriptively explaining the application work process. The application for displaying 3D objects was tested in 5 trials, with an average of 5 seconds, and the marker appeared to display 3D objects. This application can have an impact on progress in the field of informatics as a medium for delivering information and learning media using Augmented Reality Markerless.

Extreme Programming Method for Integrated Service System Website Development in Rejosari Village

The Rejosari Village Hall provides a manual letter submission service which is sometimes problematic, including when residents are about to submit an application letter, they have to come directly to the village hall office while the residents are still out of town. Apart from that, there was no media information which resulted when they were going to submit the requirements for the letters they brought were not in accordance, then from the data collection, and the letters were still in the books. Therefore we need a service system for the submission of letters. This integrated service system for residents of Rejosari Village is a web-based information system, the use of technology in the form of a website makes it easier to receive all forms of existing information. The Extreme Programming (XP) method is applied in developing this system, a software engineering process that refers to an object-oriented approach. The stages of this method start from the planning, design, coding and testing stages using black box testing with descriptive analysis techniques, which produce tests in the form of a proportion value of 96.42% and have a possible interpretation. In addition, this system can have an impact on progress in the field of informatics in the form of information media as well as learning materials

Bibliometric Analysis of Dental Informatics via Pubmed

Introduction: This study examines the main characteristics of dental informatics research using bibliometric analysis of articles in the online journal database PubMed, to identify the main trends of research in dental informatics. The study aims to identify trends, geographic distribution of papers and authors, rates of collaboration, and performances of journals and institutions. 
 Methods: Information on dental informatics was extracted solely from the PubMed online journal database from January 1989 to September 2019. A three-phase search approach was employed. Bibliometrics was used to examine the growth and progress of dental informatics over time.
 Results: A total of n=236 papers on dental informatics were identified, with an average of 7.9 papers per year. The trend of papers published increased over time with 41 countries represented in this study. There were only 15 countries which had 10 or more representatives, seven of which came from Europe. North America produced the most research in dental informatics, with 149 paper affiliations and ten were cross regional, in 61% of the total papers.
 Discussion: The topic of dental informatics began in the mid to late 1980s, with the most productive years in the last decade, reaching a high point in the mid 2010s. There was a low level of international collaboration, and few conducted across different continents.
 Conclusion: There is steady increase in the pace of research in dental informatics, with growing interest in exploring various implementation methods. Collaboration has become a product of a globalised world, with the potential to share data and exchange ideas using cutting-edge technologies. As these trends continue, the field of dental informatics may see further growth and development, with more technology available to provide communication and share data points and methods becoming widespread.

An analysis of the key drivers of the Japanese digital therapeutics patents: A cross-sectional study.

Digital therapeutics (DTx) are software or other tools that support or implement medical practices such as disease prevention, diagnosis, and treatment using digital technology. DTx has been approved in Japan, and it is anticipated that the number of approvals will increase in the future. DTx differs from conventional medical devices in that its primary purpose is treatment. This study aims to identify the key drivers of DTx in Japan by analyzing patents in the field of medical information, including DTx. This study visualizes the results of patent analyses for DTx and examines patent applications that feature applied technology and indications in the medical information field as the key drivers. The study will also employ patent citation analysis. It can be argued that the more citations a patent receives, the more similar research and development activities are being conducted, and the greater the competition. The number of citations per patent application will also be calculated to help identify areas where the value per patent application is high and competition intensifies. A patent citation matrix analysis will be conducted for notable Japanese companies in the DTx field. The citation matrix analysis consists of the number of citations and the company's selfcitation ratio to visualize the patent value. This study investigates the key drivers of DTx by analyzing patent technologies, focusing on patent applications with a high number of citations or a high selfcitation ratio. Key drivers of digital therapeutics were examined by analyzing patents in the fields of healthcare informatics and diagnostics. In terms of the number of patent applications and citations in Japan, numerous patents were related to "applications," "sensors," "medical imaging," "central nervous system/psychiatry," and "heart." As a result, Japanese companies are expected to conduct R&D with an eye toward overseas expansion.

Methods, progresses, and opportunities of materials informatics

AbstractAs an implementation tool of data intensive scientific research methods, machine learning (ML) can effectively shorten the research and development (R&D) cycle of new materials by half or even more. ML shows great potential in the combination with other scientific research technologies, especially in the processing and classification of large amounts of material data from theoretical calculation and experimental characterization. It is very important to systematically understand the research ideas of material informatics to accelerate the exploration of new materials. Here, we provide a comprehensive introduction to the most commonly used ML modeling methods in material informatics with classic cases. Then, we review the latest progresses of prediction models, which focus on new processing–structure–properties–performance (PSPP) relationships in some popular material systems, such as perovskites, catalysts, alloys, two‐dimensional materials, and polymers. In addition, we summarize the recent pioneering researches in innovation of material research technology, such as inverse design, ML interatomic potentials, and microtopography characterization assistance, as new research directions of material informatics. Finally, we comprehensively provide the most significant challenges and outlooks related to the future innovation and development in the field of material informatics. This review provides a critical and concise appraisal for the applications of material informatics, and a systematic and coherent guidance for material scientists to choose modeling methods based on required materials and technologies.

Recent trends in RNA informatics: a review of machine learning and deep learning for RNA secondary structure prediction and RNA drug discovery.

Computational analysis of RNA sequences constitutes a crucial step in the field of RNA biology. As in other domains of the life sciences, the incorporation of artificial intelligence and machine learning techniques into RNA sequence analysis has gained significant traction in recent years. Historically, thermodynamics-based methods were widely employed for the prediction of RNA secondary structures; however, machine learning-based approaches have demonstrated remarkable advancements in recent years, enabling more accurate predictions. Consequently, the precision of sequence analysis pertaining to RNA secondary structures, such as RNA-protein interactions, has also been enhanced, making a substantial contribution to the field of RNA biology. Additionally, artificial intelligence and machine learning are also introducing technical innovations in the analysis of RNA-small molecule interactions for RNA-targeted drug discovery and in the design of RNA aptamers, where RNA serves as its own ligand. This review will highlight recent trends in the prediction of RNA secondary structure, RNA aptamers and RNA drug discovery using machine learning, deep learning and related technologies, and will also discuss potential future avenues in the field of RNA informatics.

LINGUISTIC PROBLEMS IN THE TERMINOLOGICAL LEXICION OF INFORMATICS IN THE ALBANIAN LANGUAGE

The object of study included in this scientific work is the computer terminology, which ispenetrating from English language into the Albanian. During this penetration process, all the layers ofAlbanian language lexis are affected by several linguistic phenomena, such as synonymy, homonymy andpolysemy, which attract a special interest forscientific studies. These linguistic phenomena are non-positivefeatures in the field of terminology due to their confusion for the language. Also because of the violationof one of the most important basic principles of terminology - “only one meaning”, i.e. one term – oneconcept, which in relation to computer terms is almost impossible. Regarding the ongoing intensivepenetration of these terms into the Albanian language, it is necessary to translate them into Albanian andestablish its standardisation. This standardisation can be achieved only through a collaboration betweenlinguists and experts in the field of informatics. This scientific paper makes references to respective foreignliteratures accompanied with concrete examples extracted from vocabularies of informatics published in allthe Albanian-speaking territory.

A framework for materials informatics education through workshops.

The burgeoning field of materials informatics necessitates a focus on educating the next generation of materials scientists in the concepts of data science, artificial intelligence (AI), and machine learning (ML). In addition to incorporating these topics in undergraduate and graduate curricula, regular hands-on workshops present the most effective medium to initiate researchers to informatics and have them start applying the best AI/ML tools to their own research. With the help of the Materials Research Society (MRS), members of the MRS AI Staging Committee, and a dedicated team of instructors, we successfully conducted workshops covering the essential concepts of AI/ML as applied to materials data, at both the Spring and Fall Meetings in 2022, with plans to make this a regular feature in future meetings. In this article, we discuss the importance of materials informatics education via the lens of these workshops, including details such as learning and implementing specific algorithms, the crucial nuts and bolts of ML, and using competitions to increase interest and participation.

PROPERTIES OF DISCRETE-TIME CONDITIONAL LINEAR CYCLOSTATIONARY RANDOM PROCESSES IN THE PROBLEMS OF ENERGY INFORMATICS

Modern challenges in the energy industry require comprehensive research in the field of energy informatics, which combines computer science, control systems, and energy management systems within a single methodology. An important area of energy informatics is the study of problems of systems and processes modeling in energy, including energy loads and consumption. Linear and conditional linear random processes (CLRP) are mathematical models of signals represented as the sum of a large number of random impulses occurring at random times. The energy consumption, vibration signals of energy objects, etc. can be modeled using this approach. A variant of the CLRP model with discrete time, taking into account the cyclic properties of energy consumption, has been investigated in the paper. The goal is to justify the conditions for the discrete-time CLRP to be a periodically correlated random process, as well as a cyclostationary process. It has been shown that the corresponding conditions depend on the periodicity of the probability distributions of the kernel and the generating white noise of the CLRP representation. To achieve the goal, the properties of mathematical expectation and covariance function of CLRP, as well as the method of characteristic functions, have been used. The paper proves that the discrete-time CLRP is a periodically correlated random sequence if the generating white noise has periodic mathematical expectation and variance, and the kernel is a periodically correlated random field. Based on the analysis of the multivariate characteristic function, it has been proven that the discrete-time CLRP is cyclostationary if the generating white noise is a cyclostationary process and the kernel is a cyclostationary random field. The properties of discrete-time conditional linear cyclostationary random processes are important for mathematical modeling, simulation, statistical analysis, and forecasting of energy consumption. Keywords: mathematical model, energy informatics, conditional linear random process, cyclostationary process, white noise, characteristic function.

COMPUTATIONAL THINKING

Technology is present in the world so that its use becomes intuitive. The purpose of the study originated from the perception of people, especially young people who use technology practically all the time, but many of them do not use it to develop. In this case, the need to implement computing teaching in schools increases. The introduction of computing concepts from the early years of basic education gains a lot of importance. Computational thinking instructs people how to think about solving problems through concepts in the field of informatics. The unplugged activity presents great computing concepts, even without the need to use electronic devices, being an effective alternative in teaching. The method used is based on bibliographical reading on the subject and use of resources such as data show, cardboard, markers, cardboard, paper, glue, bond sheets and notebook. The general objective is to present the computer language and its importance by experiencing it in practice through the suggested games. As specific objectives, instigate students to learn by playing, increase interest in subjects such as mathematics, physical education, science, art and the Portuguese language, practice the programming language in known games in an interactive and unplugged way. As expected results are to contribute to computational thinking to become present and worked in schools in order to reframe the school teaching and learning process.

Critical success factors of smart card technology in South African public hospitals

Background: Even though the government has set several admirable targets for raising the standard of healthcare, as highlighted by communities and media reports, public health institutions’ services continue to fall short of patients’ expectations and basic standards of care. For this reason, the general public has lost faith in the healthcare system. The public healthcare system in South Africa is completely dysfunctional and urgently needs to be transformed to serve the majority of those who use public hospitals.Objectives: The study aimed to improve healthcare for the majority of South Africans by investigating the critical success factors (CSFs) that influence the adoption of smart card technology (SCT) in South African public hospitals.Methods: A thorough review of peer-reviewed literature was conducted to determine potential barriers to adopting SCT. Furthermore, a hybrid model that combines the Health Unified Technology of Acceptance Theory (HUTAUT) model, DeLone and McLean IS success model (DM) and the diffusion of innovation (DOI) theory will be developed, validated and tested to identify the CSFs adoption of SCT in public hospitals in South Africa.Results: The validated research model has been developed to be adopted by nurses at public hospitals.Conclusion: This research will contribute to the development of a new framework that identifies the CSFs for SCT adoption in South African public hospitals.Contribution: The study’s results will make a special contribution to the body of knowledge in the fields of health informatics, particularly e-health.

Disease Prediction and Treatment Recommendation Using Machine Learning

Abstract: Despite the availability of advanced technology and easy access to information, many people still rely on traditional methods of seeking medical treatment, such as visiting hospitals and consulting doctors for even minor symptoms. However, this approach can be time-consuming and inefficient, as patients with minor illnesses can take up valuable resources that could be better used to treat more serious cases. As a result, this research proposes a new approach to disease prediction using machine learning and symptom-based analysis. The goal is to develop a predictive model that can accurately identify potential diseases based on a patient's symptoms. This model utilizes machine learning techniques to analyze and process symptom data, allowing for quick and precise disease prediction. The study uses a large dataset of patient symptoms and medical records to train and test the model, which demonstrated high accuracy in predicting diseases. The results of this study suggest that the proposed model could be a useful tool for early diagnosis and treatment of diseases, with the potential to improve healthcare outcomes. Overall, this research represents an important contribution to the field of healthcare informatics, with possible applications in disease prevention, treatment, and management.

Forms of Community Informatics in Rural Communities (A Case of Kaliro District)

The field of community informatics (CI) is broadly concerned with the study, design and application of Information and Communication Technologies (ICTs) in communities. It is about identifying community needs and figuring out how technology can be leveraged to help meet those needs. It recognizes the importance of ICTs in shaping the lives of people in communities and communities shaping the future of ICTs. This study identified the forms of community informatics in Kaliro district using participative case study design with mixed methods research approach. To that end, data from questionnaires issued to 173 CI users across the district and interviews held with 33 district workers were analysed and the results presented in form of tables and themes for interpretation and discussion. Data obtained from the study revealed that Kaliro district had various forms of CI in the education sector, health sector, DLG (District Local Government) administration, and general community of the district. The study recommended; implementation of more forms of CI in the deeper areas of the district to suitably address common concerns of uneven CI distribution and contribute towards closing the information gap between the information “haves” and “have nots”, sensitisation of masses in communities on matters pertaining to CI and formulation of inclusive CI policies to regulate the implementation, management, maintenance and sustainability of CI in communities.

Defining and Scoping Participatory Health Informatics: An eDelphi Study.

Health care has evolved to support the involvement of individuals in decision making by, for example, using mobile apps and wearables that may help empower people to actively participate in their treatment and health monitoring. While the term "participatory health informatics" (PHI) has emerged in literature to describe these activities, along with the use of social media for health purposes, the scope of the research field of PHI is not yet well defined. This article proposes a preliminary definition of PHI and defines the scope of the field. We used an adapted Delphi study design to gain consensus from participants on a definition developed from a previous review of literature. From the literature we derived a set of attributes describing PHI as comprising 18 characteristics, 14 aims, and 4 relations. We invited researchers, health professionals, and health informaticians to score these characteristics and aims of PHI and their relations to other fields over three survey rounds. In the first round participants were able to offer additional attributes for voting. The first round had 44 participants, with 28 participants participating in all three rounds. These 28 participants were gender-balanced and comprised participants from industry, academia, and health sectors from all continents. Consensus was reached on 16 characteristics, 9 aims, and 6 related fields. The consensus reached on attributes of PHI describe PHI as a multidisciplinary field that uses information technology and delivers tools with a focus on individual-centered care. It studies various effects of the use of such tools and technology. Its aims address the individuals in the role of patients, but also the health of a society as a whole. There are relationships to the fields of health informatics, digital health, medical informatics, and consumer health informatics. We have proposed a preliminary definition, aims, and relationships of PHI based on literature and expert consensus. These can begin to be used to support development of research priorities and outcomes measurements.

Pembuatan Sistem Kebakaran Ruang Server Berbasis Web pada DISKOMINFO Kota Makassar

Development of Web-Based Fire Alarm System in Server Room at Diskominfo Makassar City. Diskominfo Makassar City is an institution that carries out some of the regional government affairs of Makassar City in the field of communication and informatics. Makassar City Diskominfo has a server room to handle services in the communications and informatics sector for sub-districts and villages in Makassar City. Making a web-based fire alarm is intended as a form of meeting server room security standards in terms of fire threats that can occur at any time and helping to supervise or monitor the server room. The working method or procedure for making this tool goes through the stages of analysis, design, implementation, and testing. The main components needed consist of a KY026 fire sensor, MQ2 sensor, ESP8266 microcontroller, and Laravel 7. This fire alarm tool utilizes Internet of Things (IoT) technology so that the tool can be connected to web applications. This tool detects indications of fire based on the flame wave indicator and carbon monoxide gas through the KY026 flame sensor and MQ2 sensor. Users of this tool will receive email notifications if there is a fire in the server room. It is easy for users to monitor server rooms by accessing web applications built using Laravel 7. This website is still local and can be accessed via a search engine with the address 192.168.43.244. This tool is expected to minimize damage and accelerate the handling of fire incidents in the server room. Testing of this tool was carried out on two components, namely the KY026 fire sensor and the MQ2 sensor. Based on the results of the tests that have been carried out, both components are able to detect fire indicators at certain distances. This is proven by the user receiving a fire notification when the component detects a wave of fire or carbon monoxide gas and the user can monitor the condition of the server room in real time.

Guest Editorial: Special issue on machine learning and deep learning algorithms for complex networks

Guest Editorial: Special issue on machine learning and deep learning algorithms for complex networks

Identifying a Clinical Informatics or Electronic Health Record Expert Witness for Medical Professional Liability Cases.

The health care field is experiencing widespread electronic health record (EHR) adoption. New medical professional liability (i.e., malpractice) cases will likely involve the review of data extracted from EHRs as well as EHR workflows, audit logs, and even the potential role of the EHR in causing harm. Reviewing printed versions of a patient's EHRs can be difficult due to differences in printed versus on-screen presentations, redundancies, and the way printouts are often grouped by document or information type rather than chronologically. Simply recreating an accurate timeline often requires experts with training and experience in designing, developing, using, and reviewing EHRs and audit logs. Additional expertise is required if questions arise about data's meaning, completeness, accuracy, and timeliness or ways that the EHR's user interface or automated clinical decision support tools may have contributed to alleged events. Such experts often come from the sociotechnical field of clinical informatics that studies the design, development, implementation, use, and evaluation of information and communications technology, specifically, EHRs. Identifying well-qualified EHR experts to aid a legal team is challenging. Based on literature review and experience reviewing cases, we identified seven criteria to help in this assessment. The criteria are education in clinical informatics; clinical informatics knowledge; experience with EHR design, development, implementation, and use; communication skills; academic publications on clinical informatics; clinical informatics certification; and membership in informatics-related professional organizations. While none of these criteria are essential, understanding the breadth and depth of an individual's qualifications in each of these areas can help identify a high-quality, clinical informatics expert witness.