Reviewerly/exHarmony huggingface dataset:
Group learning: an analysis of individuals in software development teams who perform interdependent tasks

This paper aims to understand how group learning occurs within software development organisations (SDOs). The specific objectives are: 1) understand and describe the learning process in teams that perform interdependent tasks according to the addressed theoretical perspective; 2) understand and describe how developers apply the resources and infrastructures available in these organisations for their learning. Qualitative research of a multiple case study was conducted in four SDOs applying semi-structured interviews. The subjects interviewed were involved in the software development process. The analyses were performed with the qualitative data analysis software Weft_QDA. The results show that group learning does occur in SDOs through information and communication technologies, which allow developers to interact and share their knowledge. There is an asset repository that stores the knowledge acquired during the projects, equivalent to a transactive memory system (TMS).
Public Morals, Trade Secrets, and the Dilemma of Regulating Automated Driving Systems

Automated driving systems (ADSs) are growing exponentially as one of the most promising AI applications. ADSs promise to transform ways in which people commute and connect with one another, altering the conventional division of labor, social interactions, and provision of services. Regulatory issues such as testing and safety, cybersecurity, connectivity, liability, and insurance are driving governments to establish comprehensive and consistent policy frameworks. Of key importance is ADSs’ ethical challenges. How to align ADS development with fundamental ethical principles embedded in a society remains a difficult question. The “Trolley Problem” aptly demonstrates such tension. While it seems essential to have rules and standards reflecting local values and contexts, potential conflicts and duplication may have serious trade implications in terms of how ADS is designed, manufactured, distributed, serviced, and driven across borders. This chapter examines the multifaceted, complex regulatory issues related to ADS and uses the most controversial, ethical dimension to analyze the tensions between the protection of public morals and trade secrets under the WTO. It unpacks three levels of challenges that may translate into a regulatory dilemma in light of WTO members’ rights and obligations under GATT, TBT Agreement, and the TRIPS Agreement and identifies possible venues of reconfiguration.
Edgescan: Vulnerability Stats Report

Organisations are still struggling to recognise and fix web-based vulnerabilities, according to the fifth edition of Edgescan's annual report. Even when vulnerabilities are found, the time taken to remediate is leaving firms at serious risk of compromise.
Investigative linguistics

This chapter introduces the field of investigative linguistics, which is defined as the systematic application of techniques for linguistic analysis to uncover information about current events that are of concern to the general public, especially but not limited to cases of disputed authorship. A distinction is made between those forensic linguists who act as investigators, primarily working for law enforcement helping to identify suspects, and those who act as expert witnesses, primarily working for the courts providing linguistic evidence to support the prosecution or defence. In addition, this chapter innovatively extends the term investigative linguistics to include linguistic investigations into newsworthy events, i.e. linguists acting as or with investigative journalists. Two cases of disputed authorship are presented to illustrate these two forms of investigative linguistics: the investigation into the disappearance of Debbie Starbuck, which was conducted on behalf of law enforcement, and the investigation into the authorship of the paper that introduced Bitcoin, which was conducted independently and then released to the press. This chapter concludes by considering the similarities between these two forms of investigative linguistic analysis.
Blockchain-based Solution for COVID-19 Digital Medical Passports and Immunity Certificates

COVID-19 has emerged as a highly contagious disease which has caused a devastating impact across the world with a very large number of infections and deaths. Timely and accurate testing is paramount to an effective response to this pandemic as it helps identify infections and therefore mitigate (isolate/cure) them. In this paper, we investigate this challenge and contribute by presenting a blockchain-based solution that incorporates self-sovereign identity, re-encryption proxies, and decentralized storage, such as the interplanetary file systems (IPFS). Our solution implements digital medical passports (DMP) and immunity certificates for COVID-19 test-takers. We present smart contracts based on the Ethereum blockchain written and tested successfully to maintain a digital medical identity for test-takers that help in a prompt trusted response directly by the relevant medical authorities. We reduce the response time of the medical facilities, alleviate the spread of false information by using immutable trusted blockchain, and curb the spread of the disease through DMP. We present a detailed description of the system design, development, and evaluation (cost and security analysis) for the proposed solution. Since our code leverages the use of the on-chain events, the cost of our design is almost negligible. We have made our smart contract codes publicly available on Github.
Optical Multi-Imaging-Casting Accelerator for Fully Parallel Universal Convolution Computing

Abstract Over the last few years, optical computing has become a potential solution to computationally heavy convolution, aimed at accelerating various artificial intelligence applications. However, past schemes have never efficiently realized fully parallel optical convolution. Here, we propose a new paradigm for a universal convolution accelerator with truly massive parallelism and high precision based on optical multi-imaging-casting architecture. Specifically, a two-dimensional Dammann grating is adopted for the generation of multiple displaced images of the kernel, which is the core process for kernel sliding on the convolved matrix. Our experimental results indicate that the computing accuracy is typically close to 8-bit, and this accuracy can be improved further by using hybrid analog–digital coding method. In addition, a convolutional neural network for the standard MNIST dataset is demonstrated, and the recognition accuracy for inference is up to 97.3%. The paradigm reported here will open new opportunities for high-throughput universal convolution accelerators for real-time or quasi-real-time AI applications.
Standardisasi Resume Medis Dalam Pelaksanaan PMK 21/ 2020 Terkait Pertukaran Data Dalam Rekam Medis Elektronik

The issuance of Regulation of the Minister of Health number 21 of 2020 concerning the Strategic Plan of the Ministry of Health year 2020-2024 encourages the need for appropriate implementation measures. One of the things that was proclaimed to be realized in 2024 is the application of integrated electronic medical records (RME) reached 100%. This is intended to be able to support the exchange of medical resume data between hospitals (health information exchange / HIE). To implement this HIE requires standardization and regulation that regulates it. This research is qualitative, using a sosiolegal approach that focuses on the depth of material related to documenting standards in medical resumes enriched with literature studies. Regulations related to medical resumes / discharge summaries that exist at this time have not set about language standards, abbreviations, symbols, and units for documenting in medical resumes. The existing regulations also have not explained the dictionary related matters ...&#x0D;
PENGEMBANGAN BAHAN AJAR EVALUASI PEMBELAJARAN UNTUK PENDIDIKAN GURU SEKOLAH DASAR UNIVERSITAS KUNINGAN

Evaluation of Learning is one of the mandatory compulsory subjects that must be taken by students at PGSD FKIP Kuningan University in order to obtain assessment and evaluation skill. However, there is no teaching material for evaluating learning for PGSD that explicitly discusses the elementary school learning evaluation process. This study to develop instructional evaluation teaching materials on PGSD learning evaluation courses which are expected to equip students to be applied in primary schools when they become teachers. This research method is a research and development study by taking the object of research at the Kuningan University PGSD. The results of the validation of learning evaluation material experts obtained results with a total value of 74 of the 20 learning indicators that were assessed with a range of scores 1-5, so that a score of 3.7 from all assessment indicators in the learning evaluation instrument can be said with good category. The results of student responses to the feasibility of developing teaching materials obtained by 90.27% of students on the response Very good and good. Based on the results obtained from the response to the readability of the product development, it was obtained that the response of students was 93.65% in the Very Good and Good categories. Based on the categorization of the results of the gain score analysis in the Hake calculation table, the value of 0.59 is categorized as medium
Indicators of Sustainable Leadership for Secondary School Principals: Developing and Testing the Structural Relationship Model

The objectives of this study included to study the appropriateness of indicators for selection in the developed model, to examine the fitness of the developed model, and to verify the factor loading value of major components, sub-components, and indicators, respectively. Sample included 2,359 secondary school principals under the jurisdiction of the Office of the Basic Education Commission. Collecting data using a set of rating scale questionnaires were derived from 860 randomly selected proportional random sampling. Data were analyzed by using statistical program and AMOS program. The findings were corresponded to the following hypotheses: (a) The 62 indicators were suitable for the criteria as average equal to or higher than 3.00 and distribution coefficients equal to or less than 20% which were selected in the model, (b) The developed models were fitted with empirical data according to the value of relative Chi-square (CMIN/DF), root mean square error of approximation (RMSEA), goodness-of-fit index (GFI) adjusted goodness-fit index (AGFI), comparative fit index (CFI), and normed fit index (NFI) in accordance with the criteria from first and second order of confirmative factor analysis, and (c) the major components had factor loading ranged from 1.00 to 1.28, which were higher than the criterion at 0.70. The minor components had factor loading between 0.83 and 1.28. The indicators had factor loading ranged from 0.88 to 1.16, which are higher than the criterion as 0.30, respectively.
User Prediction in a Role for Secure Data Sharing Through Cloud

Nowadays cloud is being used by both individuals and organizations to store and share the data without establishing their own data center. The outsourcings of these data are becoming a major security issue for businesses. Searchable encryption is one of the prominent techniques which allow the data owner to securely store the data and then share the data for their growth in business. With this technique, Cloud Service Provider can process the user request by searching on encrypted stored data without decrypting the data. In this paper we analyze different searchable encryption techniques for secure data sharing and their preventive attacks. We also proposed a method named “User Prediction in Role” to reduce the insider attack possibility in Role Based Data Sharing (RBDS), which is based on user priority levels in a role. Priorities will be decided by role manager based on the roles of a user in the organization and also predict the role assignment for new user. The proposed method can helps the organization to avoid the unauthorized data leakage.
An insight on UAV/drone autonomous navigation methods and applications: a review

In the past decade, unmanned aerial vehicles (UAVs) are gaining a lot amount of importance in the field of research and development. These UAVs have applications ranging from surveillance, the cinematography in movies, communication, transportation, agriculture, delivery of goods, and rescue operations in various scenarios. The navigation in drones is always a significant challenge as it depends on multiple aspects of technologies, which include both hardware and software. This survey paper lists the importance of UAVs and their various applications. The paper encompasses both the indoor and outdoor aspects of navigation. It describes various properties for navigating, like drone control architecture, deployed hardware-technologies, implemented algorithmic models, drone trajectory planning, and drone communications technologies requirements. Additionally, we also focus on the role of artificial intelligence paradigms for autonomous drone navigation. Vision-based navigation of UAVs using locality sensors and cameras has also discussed with the safety aspects of a drone's successful operation. This paper presents a review of the essential aspects of drone navigation methods and their applications. In the end, this survey reports the essential requirements of UAVs in civil applications from a navigation point of view.
Implementation of Quantum Gates using MATLAB

Now days we require low cost and high performance computational based applications. Quantum inspired computational device or circuit performs effective result compare to classical based devices. In the development of quantum-based devices and network needs number of quantum logic gates. Here we studied mathematical description of different types of single and multiple qubits-based quantum logic gates, the reversibility property of quantum gates also proved mathematically. We analyze the cost and effectiveness of each quantum gates has been implemented using neural network with the help of MATLAB. The cost and effectiveness of quantum gates has been analyzed with the comparison of different types of activation function.
Applying Spatial Causal Inference on Induced Seismicity

Earth and Space Science Open Archive This preprint has been submitted to and is under consideration at Journal of Geophysical Research - Solid Earth. ESSOAr is a venue for early communication or feedback before peer review. Data may be preliminary.Learn more about preprints preprintOpen AccessYou are viewing the latest version by default [v1]Applying Spatial Causal Inference on Induced SeismicityAuthorsYuchenXiaoiDCorwinZiglerPeterHenningsiDAlexandrosSavvaidisiDMichaelPyrczSee all authors Yuchen XiaoiDCorresponding Author• Submitting AuthorUniversity of Texas at AustiniDhttps://orcid.org/0000-0003-2322-9660view email addressThe email was not providedcopy email addressCorwin ZiglerUniversity of Texas at Austinview email addressThe email was not providedcopy email addressPeter HenningsiDBureau of Economic Geology, University of Texas at AustiniDhttps://orcid.org/0000-0002-1714-4997view email addressThe email was not providedcopy email addressAlexandros SavvaidisiDUniversity of Texas at AustiniDhttps://orcid.org/0000-0001-6373-5256view email addressThe email was not providedcopy email addressMichael PyrczChevron Energy Technology Companyview email addressThe email was not providedcopy email address
Facial Expression Recognition Complications with the Stages of Face Detection and Recognition

Facial expressions are the facial changes in light of a man's interior enthusiastic moods, aims, or social interchanges which are investigated by computer frameworks that endeavor to consequently examine and perceive facial movements and facial component changes from visual data. Now and again the facial expression recognition has been mistaken for feeling examination in the computer vision space prompts uncouth backings of acknowledgment process such as face detection, feature recognition and expression recognition in that way bringing about the issues of identifying impediments, enlightenments, posture varieties, acknowledgment, decrease in dimensionality, and so forth. Notwithstanding that, an appropriate computation and forecast of exact outcomes additionally enhances the execution of the facial Expression recognition. Henceforth, a detailed study was required about the strategies and systems utilized for unraveling the issues of facial expressions during the time of face detection, feature recognition and expression recognition. So thepaper displayed different current strategies and afterward basically considered the effort by the different researchers in the area of Facial Expression Recognition.
SampleSizePlanner: A Tool to Estimate and Justify Sample Size for Two-Group Studies

Planning sample size often requires researchers to identify a statistical technique and to make several choices during their calculations. Currently, there is a lack of clear guidelines for researchers to find and use the applicable procedure. In the present tutorial, we introduce a web app and R package that offer nine different procedures to determine and justify the sample size for independent two-group study designs. The application highlights the most important decision points for each procedure and suggests example justifications for them. The resulting sample size report can serve as a template for preregistrations and manuscripts.
Face Detection

Face detection is one of the challenging problems in the image processing, as a main part of automatic face recognition. Employing the color and image segmentation procedures, a simple and effective algorithm is presented to detect human faces on the input image. To evaluate the performance, the results of the proposed methodology is compared with ViolaJones face detection method.
Evaluation and Categorization of Handwriting Patterns reflecting Sentiments.

Uniqueness lies in every living being that exists on the earth. It can be viewed through its behavior, walking, personality, dressing, cramming, writing and many more. Handwriting is an important aspect that reflects the uniqueness as a whole, but when it is restricted to find sentiments it does shows certain patterns. This research is dedicated to evaluate the handwriting patterns reflecting sentiments. The major challenge faced during this research is the mood of an individual while collecting the handwriting samples. The process starts, when an observer recites a joke and the audience is given a plane piece of paper and asked them to write “I LIKE IT” those who laugh or smile and “I DON’T LIKE IT” those who do not. The collected samples are then segmented at the depth of Letter ‘L’ which is either viewed as a parabola or straight line till it touches the Letter ‘I’ with image dimensions (160, 65) pixels. It is found that the value of the standard deviation of pixels goes to 14 those who laugh at their extreme and those who just smile goes to 8. Thus, it is concluded that the level of joy of an individual from smile to laugh is in between the standard deviation of pixel value ranging from 8 to 14. It can also be concluded that the handwriting changes immediately after laughing or listening a joke. Thus handwriting goes on changing when someone becomes joyful. Testing these patterns further on another blinded sample, the technique provides a result with an accuracy percentage of 97.
Satellite Imagery for Monitoring and Mapping Soil Chromium Pollution in a Mine Waste Dump

Weathering and oxidation of sulphide minerals in mine wastes release toxic elements in surrounding environments. As an alternative to traditional sampling and chemical analysis methods, the capability of proximal and remote sensing techniques was investigated in this study to predict Chromium (Cr) concentration in 120 soil samples collected from a dumpsite in Sarcheshmeh copper mine, Iran. The samples mineralogy and Cr concentration were determined and were then subjected to laboratory reflectance spectroscopy in the range of Visible--Near Infrared--Shortwave Infrared (VNIR–SWIR: 350–2500 nm). The raw spectra were pre-processed using Savitzky–Golay First-Derivative (SG-FD) and Savitzky–Golay Second-Derivative (SG-SD) algorithms. The important wavelengths were determined using correlation analysis, Partial Least Squares Regression (PLSR) and Genetic Algorithm (GA). Artificial Neural Networks (ANN), Stepwise Multiple Linear Regression (SMLR) and PLSR data mining methods were applied to the selected spectral variables to assess Cr concentration. The developed models were then applied to the selected bands of Aster, Hyperion, Sentinel-2A and Landsat 8-OLI satellite images of the area. Afterwards, rasters obtained from the best prediction model were segmented using a binary fitness function. According to the outputs of the laboratory reflectance spectroscopy, the highest prediction accuracy was obtained using ANN applied to the SD pre-processed spectra with R2 = 0.91, RMSE = 8.73 mg.kg-1 and RPD = 2.76. SD-ANN also showed an acceptable performance on mapping the spatial distribution of Cr using Ordinary Kriging (OK) technique. Using satellite images, SD-SMLR provided the best prediction models with R2 values of 0.61 and 0.53 for Hyperion and Sentinel-2A, respectively. This led to the higher visual similarity of the segmented Hyperion and Sentinel-2A images with the Cr distribution map. The findings of this study indicated that applying the best prediction models obtained by spectroscopy to the selected wavebands of Hyperion and Sentinel-2A satellite imagery could be considered as a promising technique for rapid, cost-effective and eco-friendly assessment of Cr concentration in highly heterogeneous mining areas of Sarcheshmeh in Iran.
Recommendation System: Techniques, Evaluation and Limitations

For the benefits of the user in selecting items based on their interests, the recommendation technology is developed in different domains. A recommender system is one of the major techniques, that handles information overload problem of Information Retrieval by suggesting users with appropriate and relevant items. This paper surveys recommendation technology, the challenges and its solutions. Recommendation technology is applied in many areas like movies, videos, books, research papers, libraries, music, news, tourism, etc. This survey is useful for the further implementation and analysis of how users are adapting these technologies and how helpful it is for the user. This work also helps understand the different techniques of recommendation systems and how they can be evaluated.