Reviewerly/exHarmony huggingface dataset:
Intrance: Designing an Interactive Enhancement System for the Development of QA Chatbots

User input is essential for the successful development of question-and-answer (QA) chatbots. Therefore, interactive development systems are emerging that allow developers to involve test-users in the QA chatbot development process. Although the feasibility and effectiveness of this approach have been demonstrated, there is a lack of knowledge on how to design interactive QA chatbot development systems to increase test-user engagement as well as data quality in this time-consuming and tedious task. To address this research gap, we propose an interactive system design based on the interactivity effects model. We instantiate the proposed design and introduce Intrance, an interactive enhancement system for QA chatbots. Subsequently, we show in two online experiments that the proposed design significantly increases subjective and objective engagement of test-users and has a positive effect on data quality, conceptualized as data completeness and data accuracy. We discuss design implications for an implementation of the proposed design in commercial chatbot development systems.
Referring Segmentation via Encoder-Fused Cross-Modal Attention Network

This paper focuses on referring segmentation, which aims to selectively segment the corresponding visual region in an image (or video) according to the referring expression. However, the existing methods usually consider the interaction between multi-modal features at the decoding end of the network. Specifically, they interact the visual features of each scale with language respectively, thus ignoring the correlation between multi-scale features. In this work, we present an encoder fusion network (EFN), which transfers the multi-modal feature learning process from the decoding end to the encoding end and realizes the gradual refinement of multi-modal features by the language. In EFN, we also adopt a co-attention mechanism to promote the mutual alignment of language and visual information in feature space. In the decoding stage, a boundary enhancement module (BEM) is proposed to enhance the network's attention to the details of the target. For video data, we introduce an asymmetric cross-frame attention module (ACFM) to effectively capture the temporal information from the video frames by computing the relationship between each pixel of the current frame and each pooled sub-region of the reference frames. Extensive experiments on referring image/video segmentation datasets show that our method outperforms the state-of-the-art performance.
Conditional Wasserstein Generator

The statistical distance of conditional distributions is an essential element of generating target data given some data as in video prediction. We establish how the statistical distances between two joint distributions are related to those between two conditional distributions for three popular statistical distances: f-divergence, Wasserstein distance, and integral probability metrics. Such characterization plays a crucial role in deriving a tractable form of the objective function to learn a conditional generator. For Wasserstein distance, we show that the distance between joint distributions is an upper bound of the expected distance between conditional distributions, and derive a tractable representation of the upper bound. Based on this theoretical result, we propose a new conditional generator, the conditional Wasserstein generator. Our proposed algorithm can be viewed as an extension of Wasserstein autoencoders (Tolstikhin et al. 2018) to conditional generation or as a Wasserstein counterpart of stochastic video generation (SVG) model by Denton and Fergus (Denton et al. 2018). We apply our algorithm to video prediction and video interpolation. Our experiments demonstrate that the proposed algorithm performs well on benchmark video datasets and produces sharper videos than state-of-the-art methods.
Clinical trial data-sharing policies among journals, funding agencies, foundations, and other professional organizations: a scoping review

To identify the similarities and differences in data-sharing policies for clinical trial data that are endorsed by biomedical journals, funding agencies, and other professional organizations. Additionally, to determine the beliefs, and opinions regarding data-sharing policies for clinical trials discussed in articles published in biomedical journals.Two searches were conducted, a bibliographic search for published articles that present beliefs, opinions, similarities, and differences regarding policies governing the sharing of clinical trial data. The second search analyzed the gray literature (non-peer-reviewed publications) to identify important data-sharing policies in selected biomedical journals, foundations, funding agencies, and other professional organizations.A total of 471 articles were included after database search and screening, with 45 from the bibliographic search and 426 from the gray literature search. A total of 424 data-sharing policies were included. Fourteen of the 45 published articles from the bibliographic search (31.1%) discussed only advantages specific to data-sharing policies, 27 (27/45; 60%) discussed both advantages and disadvantages, and 4 (4/45; 8.9%) discussed only disadvantages specific. A total of 216 journals (of 270; 80%) specified a data-sharing policy provided by the journal itself. One hundred industry data-sharing policies were included, and 32 (32%) referenced a data-sharing policy on their website. One hundred and thirty-six (42%) organizations (of 327) specified a data-sharing policy.We found many similarities listed as advantages to data-sharing and fewer disadvantages were discussed within the literature. Additionally, we found a wide variety of commonalities and differences-such as the lack of standardization between policies, and inadequately addressed details regarding the accessibility of research data-that exist in data-sharing policies endorsed by biomedical journals, funding agencies, and other professional organizations. Our study may not include information on all data sharing policies and our data is limited to the entities' descriptions of each policy.
Digital Cultural Heritage Twins, a Proposal and Some Examples

We propose here to consider the digitalized image of a CH entity as the association of two components, the first describing the physical properties of the entity, and the second its immaterial/symbolic aspects under the form of a “Digital Cultural Heritage Twin”. NKRL, the Narrative Knowledge Representation Language, has been chosen for the implementation of the Digital CH Twins components; some detailed examples of its use are given in the paper.
Beyond the Pandemic and Privacy Concerns: Perceived Benefit and Expected Use of Pandemic-Tracking Apps in India

Pandemic-tracking apps could be a viable pandemic-mitigation technique, although their efficacy has been weakened by limited adoption in many places. Therefore, it is important to investigate how the perceptions of such apps are formed in different regions, which may help explain the differences in adoption. We replicated prior work on the adoption of pandemic-tracking apps in the United States with participants from India (n = 236). We identified that the perceptions of pandemic-tracking apps are connected to social orientation, familiarity with health-related technology, and demographics. We found that the perceptions and expected use were uncorrelated with privacy concerns, suggesting that privacy may not necessarily be the most suitable lens for studying the adoption of pandemic-tracking apps in India. Based on the findings, we make several recommendations for future pandemic-preparedness campaigns and identify the need to continue the trend toward contextualizing privacy-centered research with privacy-adjacent individual factors across multiple regions.
Implementation of Text Association Rules about Terrorism on Twitter in Indonesia

Along with globalization's positive effects, there are many negative consequences. Cybercrime, cyber-war, and cyberterrorism have entered social media platforms like Twitter. Therefore, identifying opinion patterns in social media is an important research task to understand what types of conversations about terrorism case patterns occur. This study will add to the knowledge of terrorism concerns in Indonesian social media. Then we might be willing to seek guidance way earlier and avoid any conflict. We attempt to analyze Twitter data with the keyword “terrorism” based on the existing problems. We want to prove that using the FP-Growth algorithm can generate rules from terrorism-related tweets. The FP-Growth algorithm generates 75 association rules from Tweet data which was collected on November 20, 2021, with minimum support of 0.05 and minimum confidence of 0.9.
Research on foreign object detection method in track area based on Mask-RCNN

Abstract As the train speeds up, the damage caused by the collisions between trains and foreign objects are becoming more and more severe. Therefore, it is of great significance to monitor the intrusion of foreign objects in the track environment. In this paper, transfer learning is introduced into Mask-RCNN deep learning model. And the data set of rail image is used to train the model, which improves the effect of rail segmentation. The trained model is used to segment the rail in the picture, and the rail vulnerable area is divided based on the segmentation results. The sliding window ORB feature matching algorithm is used to calculate the similarity of vulnerable area. The detection of foreign objects in the area where is easy to invade is realized, and the detection reliability is improved. Experiments represent that this method has high accuracy, strong practicability, good robustness and universality.
Supporting conservation and restoration through digital media modeling and exploitation - the example of the Acropolis of Ancient Tiryns

Open laboratories (OpenLabs) in Cultural Heritage (CH) institutions constitute an effective practice for providing visibility of all the processes that take place “behind the scenes”, as well as for the promotion of documentation data, which the specialists of the domain collect and produce. However, a simple “presentation” of processes, or the absence of necessary further explanation and communication with the specialists, may be problematic in terms of what visitors eventually see and understand. The exploitation of digital media and their efficient management and interlinking to meaningful data and knowledge may contribute significantly to the dissemination of publicly available information and the support of OpenLabs. Considering all the above, the CAnTi (Conservation of Ancient Tiryns) research project aims to design and implement virtual and augmented reality interactive applications that will visualize the conservation and restoration (CnR) data of the Acropolis of Ancient Tiryns. The digital content of the applications will be modeled using Semantic Web (SW) technologies, providing cultural visitors with access to insight documentation data and media produced by CnR scientists. The applications will constitute a part of the OpenLab activities that will be carried out on the archaeological site, enhancing the visitors’ experience regarding the CnR of the site’s current practices and past.
Infological modeling of the space for software engineering education

It is determined that the quality of software engineering education is influenced by modern industrial trends and IT trends, software technology tendencies, as well as the dynamics of software development teams. Given the wide range of technologies faced by groups of developers, it is determined that teaching should be based not only on the characteristics of technologies and projects, but also on the personal characteristics of programmers in accordance with the methodology of group dynamics and communications. In general, this leads to the fact that learning tasks are usually multifactorial and information overloaded. This produces educational problems related to expansion the fundamental (traditional) sets of competencies and skills and requires methodological delineation for the prospect of their wider application in pedagogical systems of software engineering. To support this area, the target audience should include industry employers and other actors. It was revealed that current issues also include problems of quality and completeness of information collected and submitted to support educational problems, questions to acquaint students with information support of decision-making processes. The approach to software engineering education is improved by modelling the integration of the requirements of current industry and IT industry trends, international recommendations, and the potential of soft skills. An ontological model of the subject area of software engineering as a basis of knowledge base of intelligent information system for application within pedagogical systems of higher education is offered. The following researches are planned, focused on the further development of the ontological model, filling it with content, creating an appropriate knowledge base and improvement of methodical materials.
An ISVM Algorithm Based on High-Dimensional Distance and Forgetting Characteristics

In the face of the batch, dynamic access data, or the flow of data that continuous changes over time, the traditional support vector machine algorithm cannot dynamically adjust the previous classification model. To overcome this shortcoming, the incremental support vector machine (ISVM) algorithm is proposed. However, many incremental support vector algorithms still have shortcomings such as low efficiency, memory limitation, and poor generalization. This paper puts forward the new ISVM algorithm, HDFC-ISVM <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <msup> <mrow /> <mi>∗</mi> </msup> </math> algorithm, based on the high-dimensional distance and forgetting characteristics. This paper firstly proposes the original HDFC-ISVM algorithm that first learns the distribution characteristics of the samples according to the distance between the samples and the normative hyperplane. Then, it introduces the forgetting factor. In the incremental learning process, the classifier gradually accumulates the spatial distribution knowledge of samples, eliminates the samples that have no contributions to the classifier, and selectively forgets some useless samples according to the forgetting factor, which overcomes the shortcomings such as low efficiency and poor accuracy of some algorithms. But, the original HDFC-ISVM algorithm is sensitive to parameters, and different settings of the parameters have a great impact on the final classification accuracy of the algorithm. Therefore, on the basis of the original algorithm, an improved algorithm HDFC-ISVM <math xmlns="http://www.w3.org/1998/Math/MathML" id="M2"> <msup> <mrow /> <mi>∗</mi> </msup> </math> based on the adjustments to the initialization strategy and updating rules of the forgetting factor is proposed. The initialization strategy and updating rules of the forgetting factor are adjusted to adapt datasets with different distributions in this improved algorithm. The rationality of the improved strategy about the forgetting factor is discussed theoretically. At the same time, the proposed algorithm has better classification accuracy, classification efficiency, and better generalization ability than other algorithms, which is verified by experiments.
Security Risk Management Analysis using Failure Mode and Effects Analysis (FMEA) Method and Mitigation Using ISO 27002:2013 for Agency in District Government

The Personnel Management Information System is managed by the Personnel and Human Resources Development Agency on local government office to provide personnel services. The existence of a system and information technology can help ongoing business processes but can have an impact or risk if the proper mitigation is not carried out. It is known that the problems are damage to databases, servers, and computer equipment due to bad weather, network connections being lost due to power outages, data loss due to not having backup data, and human error. This resulted in PMIS being inaccessible for some time, thus hampering ongoing business processes and causing financial losses. This study aims to identify risks, conduct a risk assessment using the failure mode and effects analysis (FMEA) method, and provide mitigation recommendations based on the ISO/IEC 27002:2013 standard. The analysis results obtained 50 failure modes categorized into five asset categories, and six failure modes have a high level. Then provide mitigation recommendations based on the ISO/IEC 27002:2013 Standard, which has been adapted to the needs of Human Resources Development Agency. Thus, the results of this study are expected to assist and serve as material for local office government's consideration in making improvements and security controls to avoid emerging threats to information assets.
Webqual Method on Online Course in Suburban Area: Post-Pandemic Study

Suburban areas become an object of research that attracts researchers in terms of assessing the quality of the Online Course Website. The findings at the beginning of the research regarding the poor quality of information on the Online Course make users feel confused. The purpose of this study is to establish the quality of the Online Course Website using the Webqual Method and to determine what factors affect the quality of the Online Course Website in the Suburban Area during the Post-Pandemic. The researcher reports on the results of the research, that the quality of the Online Course website in the Suburban Area using the Webqual Method is categorized as good, as shown from the results of the analysis on the Usability Quality and Service Interaction Quality variables. While the factors that affect the Quality of the Online Course Website are obtained from proving 3 hypotheses which state that everything is acceptable. The contribution of this research is that it can be used as a reference by further researchers regarding alternative problem solving in making an Online Course website with the Webqual Method. Some of the things that the researcher reports can also be used as material for the Online Course Website Developer. Of course with a different object of research will be very interesting to do.
Fingerprint-based Security System in Smart Portable Display at Brawijaya Museum

The placement of artefacts on display at the museum can be placed on the floor, walls, showcases, or in portable displays. Problems that arise in museums related to artefacts are damage due to lighting factors, Indoor Air Quality (IAQ) factors, and acts of looting that irresponsible people often carry out. This research aims to create a portable museum display by implementing a fingerprint-based security system to protect the artefacts. This research used a single case study in manufacturing furniture as a portable display and implemented NodeMCU ESP8266 as a security system. In this research, the author uses a fingerprint reader as a trigger in the system. This study uses the right thumbnail to open the door of the portable display. On the other hand, when the operator is forced to open the door, the operator uses the left thumbnail. The display door will open, and no alarm will sound, but it will send an SOS SMS to the registered number informing that the door is forced to open. The microprocessor will also buzz the alarm and send an SMS if objects fall or are picked up by irresponsible people by breaking glass.
Analysis of the Use of Information Technology in Distance Learning During a Pandemic Using the IS Success Model in Islamic Boarding School

Islamic boarding schools which are identical to face-to-face learning must be changed to online learning. The perceived problems are the lack of readiness of the teacher in preparing the material, the difficulty of changing the habits of the students, and the difficulty of networking during learning. This study aims to determine the success and the factors that influence the use of information technology during distance learning in Islamic boarding schools. The research object chosen is the Insan Pratama Islamic boarding school. The researcher used the Delone & Mclean (2003) model as the main model by adding the user characteristics variable. The results of this study indicate that 9 out of 11 hypotheses are accepted. Most of the variables used have an influence on the success of using technology in distance learning, except for the relationship between system quality and user satisfaction with a t-test value of -0.004 and the relationship between information quality and system use with a t-test value of 1.812.
Analysis of E-Government Service Quality using E-GovQual and Importance Performance Analysis (IPA)

Government instructions in implementing E-government in Indonesia have been regulated in presidential instructions No. 3 of 2013. The West Sumatra Province is the province that has implemented the instruction by providing various kinds of online-based public services. This can be seen on the West Sumatra Provincial Government website with the domain www.sumbarprov.go.id. However, the site visitors tend to decrease about 58.7% as shown in the period of December 2021 to February 2022, in the meantime the system has never been evaluated and assessed in terms of quality of its services based on user perceptions, so it is not yet known what factors affect service quality and what improvements need to be made to improve the website quality. This study uses the E-GovQual method combined with Importance Performance Analysis (IPA). This study uses 5 E-GovQual variables, namely efficiency, trust, reliability, citizen support and user satisfaction variables to measure user satisfaction with E-GovQual. Respondents used in this study amounted to 230 people. The data obtained from the distribution of previous questionnaires have been tested for validity and reliability. The results of this study indicate that the overall level of conformity is 71.7% while the gap value is −1.28%. The results of this study indicate that the overall service quality of the E-Government website in West Sumatra Province has not met user expectations. The recommendations for improvement are carrying out periodic maintenance, updating the website domain, changing the appearance of the website to a minimalist, disseminating information about the security of user data, and increasing service interaction with users.
P4AI: E-Application for Researching Student Interests based on Artificial Intelligence

The disruptive era has led to various adaptation efforts so that it has an impact on a shift from the old profession being replaced with a variety of new professions. Therefore, it is necessary to have an instrument that is able to measure the interest and profession of students in accordance with current needs. This study aims to build an e-application based on artificial intelligence to measure Profiling for Aptitude Indicators (P4AI).. The development of e-application is carried out using the waterfall method. The application development model that will be used is Agile with the Scrum model. Scrum is used to develop innovative products or services. The design of this application development will use UML and ERD based on the analyzed features. Algorithm, code, logic, and validation testing of application programs using integration testing This test method will test all modules if combined into one group to see if the program runs well or not. The results of the research are in the form of an e-application that users can use to conduct self-assessment about their interests and professions. Thus, this e-application can help the self-development needed related to the specialization and profession they have.