Artificial Intelligence has evolved in sophistication and widespread use. This study aims to create a chatbot application in the health sector regarding the early diagnosis of pregnancy disorders. ...Based on basic health research, only 44 percent of pregnant women know the danger signs of pregnancy. The chatbot application developed is expected to facilitate and increase knowledge for pregnant women about the danger signs of pregnancy, especially early diagnosis of pregnancy disorders. The chatbot application was developed with artificial intelligence technology based on Artificial Intelligence Markup Language with the question-answer concept using the Pandorabots framework. The test is carried out in two stages: functional and pattern matching. The functional testing uses the black-box testing method, and the pattern-matching test on the chatbot uses the sentence similarity and bigram methods based on user input and keywords similarity in the bot's knowledge base. The functional testing results show that the chatbot application runs well, with the eligibility criteria reaching 81.4% and the results of the keyword similarity test (pattern matching) are zero to one, in the sense that the value of one has the same similarity between user input and pattern. Meanwhile, the zero value has no similarities, so the bot will respond to it as free input. So it can be concluded that the bot can respond to user questions when the pattern and input have the same level of similarity.
Saat ini sebagian besar universitas menggunakan sistem informasi web untuk menyampaikan informasi terkait informasi pendaftaran mahasiswa, akademik, beasiswa, biaya pendidikan dan lain-lain. Dalam ...hal pelayanan pendidikan, tentunya universitas perlu memberikan layanan yang terbaik, agar para civitas akademik kampus, masyarakat mendapatkan kepuasan terhadap layanan yang diberikan. Penelitian ini adalah mengembangkan aplikasi chatbot yang dapat digunakan sebagai layanan informasi kampus dan akademik bagi masyarakat umum maupun bagi civitas akademik kampus Universitas Lancang Kuning Adapun tahapan dalam pengembangan aplikasi chatbot ini diantaranya adalah pengumpulan kebutuhan, desain, membuat prototype, evaluasi dan perbaikan. Adapun metode yang digunakan untuk pembelajaran chatbot menggunakan Artificial Markup Language (AIML). Knowledge dari aplikasi chatbot ini adalah alamat kampus, syarat pendaftaran, langkah pendaftaran, program studi, jalur kuliah, berapa biasa kuliah dan cara daftar. Berdasarkan hasil pengujian yang telah dilakukan dengan metode whitebox dan blackbox, bahwa aplikasi chatbot dapat berjalan dengan baik sebesar 100%. Sedangkan pengujian menggunakan UAT sebesar 95%. Hal tersebut menunjukkan bahwa aplikasi chatbot mampu menjawab pertanyaan-pertanyaan yang diajukan, sesuai dengan pengetahuan yang telah diberikan sebelumnya.
.
Kata kunci: Akademik, AIML, Chatbot.
Abstract
Currently, most universities use web-based information systems to provide information on student enrollment, academics, scholarships, fees, and so on. As far as education services are concerned, of course, universities need to offer the best service to ensure that the campus learning community is happy with the services offered. The goal of this research is to build a chatbot application that can use as a campus and academic information service for the general public and the academic community of Universitas Lancang Kuning. The phases in the development of this chatbot framework include gathering needs, designing, creating prototypes, testing and improving. The tool used to learn the chatbot uses the Artificial Markup Language (AIML). Knowledge from the chatbot application is the campus address, registration requirements, registration steps, study program, course path, how many lectures are used and how to register. Based on the results of the tests carried out using the Whitebox and BlackBox methods, the chatbot framework will run 100% . While testing using UAT is 95%. The Chatbot framework can answer the questions that have been posed, based on the information that has been previously given.
Keywords: Academic, AIML, Chatbot
The reliability of fuel cells during testing is crucial for their development on test benches. For the development of fuel cells on test benches, it is essential to maintain their dependability ...during testing. It is only possible for the alarm module of the control software to identify the most serious failures because of the large operating parameter range of a fuel cell. This study presents a novel approach to monitoring fuel cell stacks during testing that relies on machine learning to ensure precise outcomes. The use of machine learning to track fuel cell operating variables can achieve improvements in performance, economy, and reliability. ML enables intelligent decision-making for efficient fuel cell operation in varied and dynamic environments through the power of data analytics and pattern recognition. Evaluating the performance of fuel cells is the first and most important step in establishing their reliability and durability. This introduces methods that track the fuel cell's performance using digital twins and clustering-based approaches to monitor the test bench's operating circumstances. The only way to detect the rate of accelerated degradation in the test scenarios is by using the digital twin LSTM-NN model that is used to evaluate fuel cell performance. The proposed methods demonstrate their ability to detect discrepancies that the state-of-the-art test bench monitoring system overlooked, using real-world test data. An automated monitoring method can be used at a testing facility to accurately track the operation of fuel cells.
INTRODUCTION: Human computer interaction (HCI) interprets the design model and the uses of computer technology which focuses on the interface between the user and the computer. HCI is a very ...important factor in the design of software-oriented decision-making ideas in health-care organizations and also it assists in accurate detection of image, disease including safety of the patients.
OBJECTIVES: There are some pitfalls arises over some previous works on cloud based HCI applications. For that reason, to masafety, patient’s safety we wanted to work on explainable artificial intelligence (x-AI) and human intelligence in conjunction with HCI in various fields and algorithms to pro-vide transparency to the user. This may also use some web-based technologies and digital platforms with HCI for development of quality, safety and usability of the patients.
METHODS: The purpose of this study about the communication between the HCI design and healthcare system through client and apply that method to the information system of Healthcare department to analyse the functions, effects and outcomes.
RESULTS: The integration of explainable artificial intelligence (x-AI) and human intelligence with Human-Computer Interaction (HCI) demonstrated promising potential in enhancing patient safety and optimizing healthcare processes.
CONCLUSION: By leveraging web-based technologies and digital platforms, this study established a framework for improving the quality, safety, and usability of healthcare services through effective communication between HCI design and healthcare systems.
Display omitted
•We propose an interactive chatbot for chronic patients support based on three pillars.•Multiple actors are supported to build an effective care environment.•The chatbot design ...ensures data privacy and security being compliant with GDPR.•The chatbot offers scalability and modularity using microservices.
Chatbots are able to provide support to patients suffering from very different conditions. Patients with chronic diseases or comorbidities could benefit the most from chatbots which can keep track of their condition, provide specific information, encourage adherence to medication, etc. To perform these functions, chatbots need a suitable underlying software architecture. In this paper, we introduce a chatbot architecture for chronic patient support grounded on three pillars: scalability by means of microservices, standard data sharing models through HL7 FHIR and standard conversation modeling using AIML. We also propose an innovative automation mechanism to convert FHIR resources into AIML files, thus facilitating the interaction and data gathering of medical and personal information that ends up in patient health records. To align the way people interact with each other using messaging platforms with the chatbot architecture, we propose these very same channels for the chatbot-patient interaction, paying special attention to security and privacy issues. Finally, we present a monitored-data study performed in different chronic diseases, and we present a prototype implementation tailored for one specific chronic disease, psoriasis, showing how this new architecture allows the change, the addition or the improvement of different parts of the chatbot in a dynamic and flexible way, providing a substantial improvement in the development of chatbots used as virtual assistants for chronic patients.
In this research article, authors have engineered the model to control soft material robotic car with single and multi-hand gestures based on Artificial Intelligence and Machine Learning approach. A ...user centric representation of this features is obtained by using hand detection and hand gesture recognition mechanism. Authors have assigned the desire hand gestures to move the soft material robotic car in 360 degrees. In this research work, different gestures of human hands are simulated in terms of landmarks using Mediapipe. Each combination of hand landmark performs different actions to control the robotic car in multiple directions. In this research work, the soft material robotic car has been controlled using single hand as well as multi hands gesture-based approach. Our motive of this research work is to reduce human efforts by controlling the soft material robotic car through hand gestures based on AIML techniques. The proposed CNN model has yielded high accuracy as compared to baseline ML algorithms such as KNN, Decision Tree, SVM etc. It is also observed that CNN model remains ahead of other ML algorithms for both single hand and multi-hand gesture based robotic car control. The performance of proposed CNN model for controlling robotic car has been represented in term of ROC curve using validation and test data set. The average performances of single hand gesture and multi hand gestures using proposed CNN are found as 97% and 98% respectively.
This study is intended to create an innovative contextual English learning environment making use of the widely used communication software, LINE ChatBot, based on the Artificial Intelligence Markup ...Language (AIML), in order to improve speaking and listening ability among learners. A total of 73 students were invited to participate in learning activities involving a 4-week English conversation exercise including both speaking and listening. Additionally, in order to explore the influence of competition on language acquisition, we added competition characteristics to the learning activities in the experimental group to enhance learning motivation and learning outcomes. The results showed that with the help of the LINE ChatBot contextual learning environment, the performance of both groups of students was slightly enhanced, but no significant differences were found. Meanwhile, extrinsic motivation in both the experimental and control group was improved if they spoke anonymously. That is, the contextual learning environment based on the LINE ChatBot significantly improved the learners' English speaking and listening ability. In addition, the results showed that the addition of a competition element effectively enhanced the learners' intrinsic motivation to learn English on the LINE ChatBot.
Since the discovery of the Coronavirus (nCOV-19), it has become a global pandemic. At the same time, it has been a great challenge to hospitals or healthcare staff to manage the flow of the high ...number of cases. Especially in remote areas, it is becoming more difficult to consult a medical specialist when the immediate hit of the epidemic has occurred. Thus, it becomes obvious that if effectively designed and deployed chatbot can help patients living in remote areas by promoting preventive measures, virus updates, and reducing psychological damage caused by isolation and fear. This study presents the design of a sophisticated artificial intelligence (AI) chatbot for the purpose of diagnostic evaluation and recommending immediate measures when patients are exposed to nCOV-19. In addition, presenting a virtual assistant can also measure the infection severity and connects with registered doctors when symptoms become serious.
PDF
