Explainable Artificial Intelligence (XAI) from a user perspective- A synthesis of prior literature and problematizing avenues for future research

The final search query for the Systematic Literature Review (SLR) was conducted on 15th July 2022. Initially, we extracted 1707 journal and conference articles from the Scopus and Web of Science databases. Inclusion and exclusion criteria were then applied, and 58 articles were selected for the SLR. The findings show four dimensions that shape the AI explanation, which are format (explanation representation format), completeness (explanation should contain all required information, including the supplementary information), accuracy (information regarding the accuracy of the explanation), and currency (explanation should contain recent information). Moreover, along with the automatic representation of the explanation, the users can request additional information if needed. We have also found five dimensions of XAI effects: trust, transparency, understandability, usability, and fairness. In addition, we investigated current knowledge from selected articles to problematize future research agendas as research questions along with possible research paths. Consequently, a comprehensive framework of XAI and its possible effects on user behavior has been developed

The scientific payload of the Ultraviolet Transient Astronomy Satellite (ULTRASAT)

The Ultraviolet Transient Astronomy Satellite (ULTRASAT) is a space-borne near UV telescope with an unprecedented large field of view (200 sq. deg.). The mission, led by the Weizmann Institute of Science and the Israel Space Agency in collaboration with DESY (Helmholtz association, Germany) and NASA (USA), is fully funded and expected to be launched to a geostationary transfer orbit in Q2/3 of 2025. With a grasp 300 times larger than GALEX, the most sensitive UV satellite to date, ULTRASAT will revolutionize our understanding of the hot transient universe, as well as of flaring galactic sources. We describe the mission payload, the optical design and the choice of materials allowing us to achieve a point spread function of ~10arcsec across the FoV, and the detector assembly. We detail the mitigation techniques implemented to suppress out-of-band flux and reduce stray light, detector properties including measured quantum efficiency of scout (prototype) detectors, and expected performance (limiting magnitude) for various objects.Comment: Presented in the SPIE Astronomical Telescopes + Instrumentation 202

Towards a GDPR-Compliant Blockchain-Based COVID Vaccination Passport

The COVID-19 pandemic has shaken the world and limited work/personal life activities. Besides the loss of human lives and agony faced by humankind, the pandemic has badly hit different sectors economically, including the travel industry. Special arrangements, including COVID test before departure and on arrival, and voluntary quarantine, were enforced to limit the risk of transmission. However, the hope for returning to a normal (pre-COVID) routine relies on the success of the current COVID vaccination drives administered by different countries. To open for tourism and other necessary travel, a need is realized for a universally accessible proof of COVID vaccination, allowing travelers to cross the borders without any hindrance. This paper presents an architectural framework for a GDPR-compliant blockchain-based COVID vaccination passport (VacciFi), whilst considering the relevant developments, especially in the European Union region

Deep Learning Techniques for Quantification of Tumour Necrosis in Post-neoadjuvant Chemotherapy Osteosarcoma Resection Specimens for Effective Treatment Planning

Osteosarcoma is a high-grade malignant bone tumour for which neoadjuvant chemotherapy is a vital component of the treatment plan. Chemotherapy brings about the death of tumour tissues, and the rate of their death is an essential factor in deciding on further treatment. The necrosis quantification is now done manually by visualizing tissue sections through the microscope. This is a crude method that can cause significant inter-observer bias. The suggested system is an AI-based therapeutic decision-making tool that can automatically calculate the quantity of such dead tissue present in a tissue specimen. We employ U-Net++ and DeepLabv3+, pre-trained deep learning algorithms for the segmentation purpose. ResNet50 and ResNet101 are used as encoder parts of U-Net++ and DeepLabv3+, respectively. Also, we synthesize a dataset of 555 patches from 37 images captured and manually annotated by experienced pathologists. Dice loss and Intersection over Union (IoU) are used as the performance metrics. The training and testing IoU of U-Net++ are 91.78% and 82.64%, and its loss is 4.4% and 17.77%, respectively. The IoU and loss of DeepLabv3+ are 91.09%, 81.50%, 4.77%, and 17.8%, respectively. The results show that both models perform almost similarly. With the help of this tool, necrosis segmentation can be done more accurately while requiring less work and time. The percentage of segmented regions can be used as the decision-making factor in the further treatment plans

A remote and cost‐optimized voting system using blockchain and smart contract

Abstract Traditional voting procedures are non‐remote, time‐consuming, and less secure. While the voter believes their vote was submitted successfully, the authority does not provide evidence that the vote was counted and tallied. In most cases, the anonymity of a voter is also not sure, as the voter's details are included in the ballot papers. Many voters consider this voting system untrustworthy and manipulative, discouraging them from voting, and consequently, an election loses a significant number of participants. Although the inclusion of electronic voting systems (EVS) has increased efficiency; however, it has raised concerns over security, legitimacy, and transparency. To mitigate these problems, blockchain technology has been leveraged and smart contract facilities with a combination of artificial intelligence (AI) to propose a remote voting system that makes the overall voting procedure transparent, semi‐decentralized, and secure. In addition, a system that aids in boosting the number of turnouts in an election through an incentivization policy for the voters have also developed. Through the proposed virtual campaigning feature, the authority can generate a decent amount of revenue, which downsizes the overall cost of an election. To reduce the associated cost of transactions using smart contracts, this system implements a hybrid storage system where only a few cardinal data are stored in the blockchain network

A Systematic Mapping Study of Empirical Research Methods in Software Ecosystems

The field of software ecosystems is rapidly maturing and significant numbers of articles are published each year to further develop our understanding of this concept and support innovation through it. The growth of the field also brings along challenges, such as findability and reusability of research results, coordination of research initiatives, and significant review pressure on members of the community. In this mapping study of empirical research methods in the field, we show that few studies do a good job of reporting their research methods and results. Using data from the study, we provide guidelines for performing empirical research in software ecosystems

A Systematic Mapping Study of Empirical Research Methods in Software Ecosystems

The field of software ecosystems is rapidly maturing and significant numbers of articles are published each year to further develop our understanding of this concept and support innovation through it. The growth of the field also brings along challenges, such as findability and reusability of research results, coordination of research initiatives, and significant review pressure on members of the community. In this mapping study of empirical research methods in the field, we show that few studies do a good job of reporting their research methods and results. Using data from the study, we provide guidelines for performing empirical research in software ecosystems