Reviewerly/exHarmony huggingface dataset:
An Interactive Dashboard for Patient Monitoring and Management: A Support Tool to the Continuity of Care Centre

In recent years, dashboard utilization in healthcare organizations has emerged as a useful tool to monitor and improve the quality of care. In this work, we present a dashboard specifically designed to support the daily clinical activities of the Continuity of Care Centre (CCA) in Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome. CCA team, composed of multidisciplinary professional figures, plans and optimizes the treatment and discharge pathway for frail hospitalized patients. The team monitors the conditions of a large number of patients, which are spread across hospital departments, and fragmentation of patients' information on electronic health records (EHRs) is one of the greatest issues it has to deal with. The presented dashboard integrates and harmonizes data from several data sources providing physicians with a daily updated and interactive visualization of patient longitudinal history throughout hospitalization. The monitoring activity of CCA is supported through filtering options that allow to manage subgroups of patients individually. Moreover, automatic alerts promptly identify critical clinical conditions and deviations of patient processes from hospital protocols. In order to optimize patient discharge and bed occupancy, the dashboard displays also the intensity of medical care trend during hospitalization and highlights low intensity of care in patients ready to be discharged. The dashboard is currently in use by CCA team as a support tool to monitor and manage the admitted patients.
Autoencoder-Based Prediction of ICU Clinical Codes

Availability of diagnostic codes in Electronic Health Records (EHRs) is crucial for patient care as well as reimbursement purposes. However, entering them in the EHR is tedious, and some clinical codes may be overlooked. Given an incomplete list of clinical codes, we investigate the performance of ML methods on predicting the complete ones, and assess the added predictive value of including other clinical patient data in this task. We used the MIMIC-III dataset and frame the task of completing the clinical codes as a recommendation problem. We consider various autoencoder approaches plus two strong baselines; item co-occurrence and Singular Value Decomposition (SVD). Inputs are 1) a record's known clinical codes, 2) the codes plus variables. The co-occurrence-based approach performed slightly better (F1 score = 0.26, Mean Average Precision [MAP] = 0.19) than the SVD (F1 = 0.24, MAP = 0.18). However, the adversarial autoencoder achieved the best performance when using the codes plus variables (F1 = 0.32, MAP = 0.25). Adversarial autoencoders performed best in terms of F1 and were equal to vanilla and denoising autoencoders in term of MAP. Using clinical variables in addition to the incomplete codes list, improves the predictive performance of the models.
THE USE OF ELECTRONIC EDUCATIONAL RESOURCES AS A MAJOR FACTOR IN THE MODERN EDUCATIONAL PROCESS

The article deals with the issue of informatisation of higher education, reveals the importance of the use of electronic educational resources and its impact on the learning process. The most popular online services and web-tools, as well as the possibilities of their application, are given as examples. The necessary changes for the creation of the newest education system of the next generation in Russia are formulated.
Homo Sapiens Cyborg: the Cyborg Man and the Fragility of Laws

Laws are still created for civil societies that have a geographical border. The laws therefore cannot fulfil the criteria for antifragile laws. The people under a certain geographical jurisdiction belong to their online community as much as they belong to the geographical location, they are being governed in. This gives space for the laws to be compromiseable and, at times, seem unreasonable to the intended subject. Homo-Sapiens Cyborg is accelerating the fragility of laws, a citizen of the world is a citizen of nowhere.
A Three-Stage Framework to Estimate Pedestrian Path by Using Signaling Data and Surveillance Video

The estimation of pedestrian path is of great value in the study of crowd dynamics, and various data with location information can be used as the basis for path estimation. In this study, we jointly use the signal data obtained from the pedestrian interaction with the base station and the surveillance video in the study area, and estimate the pedestrian path in the network finally. This paper proposes a three-stage framework for pedestrian path estimation, in the first stage, the video is used to extract the pedestrian's trajectory in the monitoring field of view, and the road segment that the pedestrian certain to pass is determined; in the second stage, the location information contained in signaling data is used to predict the road segments that pedestrian may pass through. In the final stage, the road segments determined by surveillance videos and the road segments inferred from signaling data are integrated, then we use HMM model to determine the combination of road segments with the highest probability, so as to obtain the complete travel path of the pedestrian. To evaluate the framework proposed in this paper, we conducted simulation experiments based on CARLA. The experimental results show that the path of pedestrians in the road network can be estimated effectively through the cooperative application of signaling data and surveillance video. Compared with other methods relying on only one data source, the three-stage framework proposed has higher accuracy in path estimation.
Evaluation of Interface Design Principles' Usability in Permanent Museum Exhibition

The majority of museums today provide us with an unforgettable experience through interactive digital exhibitions. Due to the failure of the interface design usability of the exhibition systems and implementation, it was discovered that several digital projects failed to achieve the results promised in previous studies, which negatively impacted the interaction and experiences of visitors. With this in mind, an empirical usability study on interface design principles was done to determine how interface design concepts may be applied to a permanent museum exhibition. The findings reveal how to implement interface design concepts in a museum exhibition effectively.
Benefits of sharing code with articles

I’m writing this blog post in preparation for a contribution to the upcoming RDA Plenary 19 session “BoF: Sharing code that supports research articles: is it time to align goals and publisher policies?” at 0030 UTC on 23 June. I want to talk about how and why software (code) is shared. Publishers When we think about different stakeholders who are trying to influence the way software is developed and shared, we can consider publishers, who are beginning to require software citation, and...
Progress on Software Management Plans in the Netherlands

I’m very pleased to see that the Netherlands group working on “Software Management Plans: Towards national guidelines” has released a draft set of guidelines for community consultation (through 20 June 2022) and is organizing a workshop on 9 June to test and discuss the guidelines with use cases from the research community: https://www.eventbrite.com/e/software-that-makes-you-proud-using-smps-tickets-341888165707. As I wrote in 2016 following my 4-year term of working as a program officer...
Is your mouse attracted by your eyes: Non-intrusive stress detection in off-the-shelf desktop environments

Increasing number of people work long hours with computers under high cognitive load. This could potentially cause mental stress in workplaces. Prolonged exposure to mental stress contributes to poor working experience and even severe health problems. Despite the growing demand, the existing intelligent stress detection methods are limited when applied to actual workplaces. They often measure physiological and physical signals, via intrusive devices, to detect stress. The intrusiveness hampers their accessibility and applicability in daily life and workplaces. To overcome that, behavior-based methods were proposed. Models that explore mouse and gaze behaviors during computer usages were demonstrated to be particularly effective. However, the current methods rely on using prior knowledge of the user interface (UI) layout to construct models. Their applicability thus is limited, especially in real workplaces where task UI is often dynamic. This paper presents a novel stress detection method to address the challenges. It attains non-intrusiveness and UI-agnostic by modeling the relative movement and coordination of mouse and gaze. The method is evaluated on a dynamic-UI task, namely, web searching. An accuracy of 78.8% is achieved using a commercial eye-tracker for gaze estimation, beating the state-of-the-art approaches by around 20%. We further use webcam to estimate gaze locations substituting for the eye-tracker, to enhance the model accessibility. The method yields 68.6% accuracy of stress detection without using any special devices. Experimental results demonstrate the effectiveness and applicability of our method. It opens up a new avenue for cognitive-aware adaptive user interface, intelligent working environment, and related applications.
Clear Sky and Real Sky Solar Radiation Modelling for Locations in India

Photovoltaic battery microgrid systems are used for improving grid reliability by functioning in grid dependent mode. To ensure supply demand match due to the intermittent nature of renewable sources, storage batteries are also used. Proper component design shall be done for a cost effective and technically viable solution for grid unreliability. Accurate solar radiation data is needed for optimum sizing of microgrid components. In case, proper radiation database is not available, empirical models are used. There are many existing models which require user inputs based on the geographical properties of the location. These models have been modified throughout the years based on changing conditions. This work presents Bird’s Clear Sky Model to model clear sky radiation for Mumbai, India. The model is validated using clear sky values from India Meteorological Department (IMD), Pune database. Angstrom Model was used to model real sky values. These values were validated using sunshine hours database from IMD. The results show that Bird’s Model is accurate to some extent in predicting solar radiation for Indian locations.
Interaction Design of ITB Library Application Using User-Centered Design

The Technical Implementation Unit is a part of a university or institute that supports the three pillars of higher education, one of which is the library. Library has a large collection of resources that can be accessed through a library catalog. ITB Library is a mobile application that allows users to search catalogs, but it currently lacks optimal appearance and user experience. The aim of this final project is to improve the ITB Library by implementing a user-centered design approach, which focuses on understanding and addressing user needs. The end goal is to create a high-fidelity prototype that meets the usability goals of effective to use, have good utility, easy to learn, and the user experience goal of being helpful. To evaluate the design, usability testing was conducted on the prototype. Testing was evaluated using several metrics, including task completion rate (100%), System Usability Scale (SUS) (93/100), Single Ease Question (SEQ) (6.7/7), and Intrinsic Motivation Inventory (IMI) (6.7/7 for the value/usefulness subscale) during the third iteration. Based on the results of the testing, the interaction design of the ITB Library meets the usability and user experience goals that were set out to be achieved.
Security Analysis of a Blockchain Based Data Collection Method for Cross Company Information Sharing

Abstract Digitization within medium-sized enterprises advanced in the last years. Collecting and analyzing data for optimizing internal production processes therefor is the current state of many companies. The next step of digitization is using this collected data not only for internal processes but for cross company business models along the value network. This step brings new requirements for how data is collected, stored and shared. In this paper those requirements are listed and explained. Afterwards, an implemented solution for data collection fulfilling the requirements is analyzed. The focus of the analysis lies on security issues within the data flow between data creation and cross-company usage. Therefore, the timespan between data creation on a sensor, processing the data within local IT-systems and reliably storing data within a blockchain is considered. A threat modeling approach considering attack vectors along the described data flow is used to quantitatively compare the proposed solution to regular industrial solutions. The analysis will highlight the differences of the compared solutions on different topics like data integrity and immutability. Lastly, an outlook on industrial usage of the analyzed solution is given.
ELECTRONIC MODULE (E-MODULE) AS INNOVATIVE LEARNING MEDIA TO INCREASE KNOWLEDGE AMONG NURSING STUDENTS

Electronic modules (e-modules) as innovative learning media that can be accessed anytime and anywhere are promised to increase nursing students' knowledge. However, there are still limited studies that examine the effectiveness of E-modules and the effect of E-modules on increasing student knowledge. This study aims to evaluate the effectiveness of the e-module on undergraduate nursing students' knowledge level. One group pre-posttest research design was conducted on 46 students recruited through purposive sampling. Respondents filled out the pretest, followed by studying the E-module material on spontaneous delivery compiled by maternity nursing experts for three reading periods in a week and working on a posttest questionnaire compiled by the researcher. Then the data were analyzed using the Wilcoxon test with a significance level of 0.05. Students' knowledge before giving the intervention was seen in the pretest results , with an average value of 72 and an increase in the average value in the posttest after the intervention was given to 97. So there was a significant effect of e-module as a learning medium on increasing student knowledge (p =0.00). The E Module has been proven to be effective in increasing knowledge. Still, nursing education and science continue to develop, so regular updating of the content of the e-module is needed and combining it with nursing moral values is essential because good moral attitudes are also the focus of nursing education.
AMST2: aggregated multi-level spatial and temporal context-based transformer for robust aerial tracking

Recently, many existing visual trackers have made significant progress by incorporating either spatial information from multi-level convolution layers or temporal information for tracking. However, the complementary advantages of both spatial and temporal information cannot be leveraged when these two types of information are used separately. In this paper, we present a new approach for robust visual tracking using a transformer-based model that incorporates both spatial and temporal context information at multiple levels. To integrate the refined similarity maps through multi-level spatial and temporal encoders, we propose an aggregation encoder. Consequently, the output of the proposed aggregation encoder contains useful features that integrate the global contexts of multi-level spatial and the temporal contexts. The feature we propose offers a contrasting yet complementary representation of multi-level spatial and temporal contexts. This characteristic is particularly beneficial in complex aerial scenarios, where tracking failures can occur due to occlusion, motion blur, small objects, and scale variations. Also, our tracker utilizes a light-weight network backbone, ensuring fast and effective object tracking in aerial datasets. Additionally, the proposed architecture can achieve more robust object tracking against significant variations by updating the features of the latest object while retaining the initial template information. Extensive experiments on seven challenging short-term and long-term aerial tracking benchmarks have demonstrated that the proposed tracker outperforms state-of-the-art tracking methods in terms of both real-time processing speed and performance.
Resolving Context Contradictions in the Neural Dialogue System based on Sentiment Information

Chatbots trained on large corpus generate fluent responses, but often suffer from the problem of generating responses that contradict past utterances. Recent research treats dialogue contradiction detection as a task of natural language inference (NLI), and a method to remove contradiction from responses has been proposed and has shown high performance. However, these datasets do not provide explicit information about emotions, and these models cannot capture changes in emotions. In this work, we create a new dataset by explicitly labeling emotional information on an existing contradiction detection dataset and use this dataset to train an NLI model. Furthermore, we train the NLI model on the original dataset as well and compare the accuracy of both in dialogue contradiction detection.
IMPLEMENTATION OF DIGITAL TECHNOLOGIES IN THE EDUCATIONAL PROCESS IN UKRAINE

Ukraine, like most developed countries in the world, is considering its future connected with the development of the digital economy. The digital economy determines the trajectory of development not only of industry, agriculture, construction, and services, but also of the fourth sector of the economy – information technology, education, research, and banking. In the budget of Ukraine for 2021, UAH 1.8 billion was allocated for the digitalization of the country, of which 602 million were allocated. it will be spent on a national program that will implement digital transformation projects in various fields, including education. Since 2014, the country's information society development policy has been implemented by the State Agency for E-Government of Ukraine, which since 2019 has been transformed into the Ministry of Digital Transformation. During this period, a number of documents regulating the transformation of Ukraine into a digital space were adopted: Digital agenda of Ukraine-2020, Strategies for the development of higher education in Ukraine for 2021-2031, projects launched « Diya» («The state and I), «є- Baby », «BroadBand», «е- Residence », «Diya.Csty», «е- Business », « European integration », « Protecting children in the Internet », « Digital education», digitized documents have been introduced – a driver's license and a certificate of ownership of a vehicle. The Digital Education project intends to teach digital literacy to at least 6 million citizens within 3 years, and at the age of 30 to 60+ years. For this purpose, a number of courses in five different categories for teaching digital literacy to the population were launched on the website of the Ministry of Digital Transformation. However, the most rational way, as the author sees it, for the implementation of this project is the introduction of appropriate disciplines for the training of the younger generation, primarily in the pedagogical universities of the country; the formation of digital competencies among students of pedagogical specialties and the training of digital skills for the use of their acquired knowledge in future practical activities. The computer science course, which is taught at the faculties of humanities in pedagogical universities, and which is usually called ICT (information and communication technologies), involves only 3 credits, this is 90 academic hours, which is not enough time to familiarize students with digital technologies in sufficient volume.
Joint Action Representation and Prioritized Experience Replay for Reinforcement Learning in Large Discrete Action Spaces

In dealing with the large discrete action spaces, a joint action representation and prioritized experience replay method is proposed in this paper, which consists of three modules. In the first module, we use the k-nearest neighbor method to reduce the dimensionality of the original action space, generating a compact action space, and then the critic network is introduced to further evaluate and filter this compact space to obtain the optimal action. Note that the optimal action may have inconsistency with the actual desired action. Then in the second module, we introduce a multi-step update technique to reduce the training variance when storing data in the replay buffer. In the third module, considering the existence of correlation between samples when sampling data, we assign the corresponding weight to the sample experience by calculating the absolute value of temporal difference error and use such a non-uniform sampling method to prioritize the samples for sampling. Experimental results on four benchmark environments demonstrate the effectiveness and efficiency of the proposed method in dealing with the large discrete action spaces.
Aplikasi Penentuan Rute Terpendek Pengambilan Sampah Berbasis Internet of Things Terintegrasi Dengan Google Maps API

Solid waste is a sensitive issue involving serious environmental problems in the world today. The situation of direct disposal of waste without proper inspection and segregation has left a serious impact on environmental pollution which has led to a tremendous growth in health problems. This study aims to monitor the level of fullness of waste in trash cans, send the results to a Google map using the Google Maps API and determine the shortest route for waste collection based on the level of fullness of waste. The android application was developed to make it easier for users to find out which trash cans are full and need to be taken immediately and to determine the shortest route using google maps.
Security-Aware and Privacy-Preserving Blockchain Chameleon Hash Functions for Education System

The most crucial properties of decentralized, immutable blockchain technologies are being transparent, tamper-proof, and have total traceability. With an increase in overseas students globally, the problem of diploma forgery, and the sale of forged credentials, the management and dissemination of student educational information continue to encounter several problems. Privacy violation issues like security, privacy, trustworthiness, consistency challenges, and traceability issues are considered when managing student academic records in educational sectors. The proposed work is a novel decentralized Chameleon Hash Function and it is applied to overcome these privacy violation issues. Security-aware and privacy-preserving blockchain Chameleon hash functions for Education System are suggested because every redaction needs to be approved by numerous blockchain nodes. A Proof of Continuous Work (PoCW) consensus algorithm entirely based on Blockchain is proposed for data storage and sharing, which minimizes processing power wastage to enhance the accessibility and transparency of the procedure for students receiving educational degree certificates. By consistently giving proof of storage, miners can gain an edge in the mining procedure. Without any outside help, Blockchain has created a reliable blockchain-based storage system that does not depend on a third party. The simulation and theoretical study's findings demonstrate that the proposed scheme has enhanced security, trustworthiness, and traceability.