The aim of this paper is to consider whether critical rationalism has any ideas which could usefully be applied to the INTERNET.  Today we tend to take the INTERNET for granted and it is easy to forget that it was only about two decades ago that it began to be used to any significant extent. Accordingly in section 1 of the paper, there is a brief consideration of the history of the INTERNET.  At first sight this makes it looks implausible that any of Popper’s ideas could be applicable to the INTERNET, since Popper died before the INTERNET came into general use.  However, section 2 argues that Popper’s theory of World 3 does apply very well to the INTERNET.  This application is significant because, as shown in section 3, it leads to the problem of misinformation, which is one of the most significant problems generated by the INTERNET.  In section 4 there is an attempt to solve this problem using ideas taken from Popper’s epistemology. It is argued that there should be changes in education designed to prepare students for the INTERNET age. Teaching in the INTERNET age should focus on presenting to the students not just the accepted theories but also the evidence on which they are based. An illustration of how this might be done is given by considering an example from science teaching, namely the teaching of Newtonian mechanics in the last years of school or first years of university.

In traditional speech processing, feature extraction and classification were conducted as separate steps. The advent of deep neural networks has enabled methods that simultaneously model the relationship between acoustic and phonetic characteristics of speech while classifying it directly from the raw waveform. The first convolutional layer in these networks acts as a filter bank. To enhance interpretability and reduce the number of parameters, researchers have explored the use of parametric filters, with the SincNet architecture being a notable advancement. In SincNet's initial convolutional layer, rectangular bandpass filters are learned instead of fully trainable filters. This approach allows for modeling with fewer parameters, thereby improving the network's convergence speed and accuracy. Analyzing the learned filter bank also provides valuable insights into the model's performance. The reduction in parameters, along with increased accuracy and interpretability, has led to the adoption of various parametric filters and deep architectures across diverse speech processing APPLICATIONS. This paper introduces different types of parametric filters and discusses their integration into various deep architectures. Additionally, it examines the specific APPLICATIONS in speech processing where these filters have proven effective.

Quality of service and trustworthiness of data is of high importance for decision making in INTERNET-of-Things (IoT) APPLICATIONS. Malicious nodes and devices may compromise the quality of service and experience for other nodes through providing invalid data and evaluations. Hence, a trust management system to assess the trust level of users and gathered data is deemed to be essential to every IoT system. The current approach in the literature for computing the trust level is entity-centric trust in which the trust level of end users are estimated. However, the trustworthiness of data is equally important in many APPLICATIONS. In this paper, we propose, Trusty, a hybrid trust computation approach, aiming at trust assessment for both entities as well as data. In our proposed approach, a Bayesian learning method is used for computing the entity trust, while Dempster-Shafer theory is exploited to data fusion and data trustworthiness assessment. We implement Trusty in a smart parking system scenario to investigate the performance of our model in the different settings for misbehavior nodes and faulty sensors. As shown by the extensive simulation experiments, Trusty outperforms the competing approaches in terms of convergence for both data trustworthiness and entity trust.

Context: The INTERNET of things (IoT) is a system of wireless, interconnected and digital devices that can collect and store data in a network without needing to establish human-to-human or human-to-computer interactions. Objectives: Due to the importance of adopting up-to-date technologies in hospitals and health centers, this systematic review aimed to explore all aspects of the IoT applicable in hospitals. Methods: The present study was a systematic review conducted in 4 August 2021 according to PRISMA guidelines. The INTERNET searches were performed to access three scientific databases of PubMed, Scopus, and ISI Web of Science using a combination of keywords, such as the IoT and hospital. Finally, the required data were extracted from original research articles investigating the IoT application in hospitals and were entered into EndNote X8 software. Quality assessment of the studies was carried out by two researchers independently. Results: A total of 18 articles were included in the study. The application of IoT had been introduced by 13 articles as an effective method in reducing and controlling dust levels as well as improving the quality of health in wards. Moreover, the possibility of using and installing IoT systems on mobile phones as well as their application for monitoring health improvement had been investigated by two articles. The advantages of using the IoT to save time and keep users’ information confidential had also been discussed by some other reviewed articles. Conclusions: It was concluded that the application of IoT system in hospitals increased the quality of healthcare and improved the patient satisfaction. It was also found that adopting IoT technology may have been extremely effective in controlling various hospital infections. Moreover, this technology was detected to have the true potential for improving the security of devices and databases in the hospital. Overall, the application of IoT was confirmed to increase the efficiency of hospitals and health centers.

In today's world, the INTERNET of Things (IoT), which is a fairly new technology, has become a popular topic for discussion. Meanwhile, the increasing demand for personalized healthcare with the assistance of new technologies has created new APPLICATIONS called e-health IoT APPLICATIONS; however, researchers are still attempting to find its APPLICATIONS, therefore they have not been able to focus on comparing these APPLICATIONS. We have aimed at understanding the benefits of ehealth IoT APPLICATIONS in comparison to one another. Therefore, this study is an attempt to provide a list of e-health IoT APPLICATIONS for individuals and to prioritize them. The Fuzzy Analytical Hierarchy Process (FAHP) method has been used, which is a method for MultiCriteria Decision Making (MCDM) and a useful tool for prioritizing multiple alternatives based on criteria. Eight important criteria, based on a comprehensive literature review and experts’ opinions, were determined. Then, by using the FAHP method, the weight of each criterion was calculated. As a result, seven APPLICATIONS identified for individuals were prioritized based on the weight of each criterion and the score of each application in each criterion. Health Effectiveness, Empowerment, Safety, Privacy, and Peace of Mind are the most important criteria in e-health IoT APPLICATIONS for individuals; Cost Saving, round-the-clock Access, and Time-Saving are in the next levels of importance. The results also show that Chronic disease management, Medication reminders, Health monitoring, Air quality, Fall detection, Sleep control and Fitness were respectively ranked as first, second, third, fourth, fifth, sixth and seventh among the IoT APPLICATIONS.