Open Programming Language Research Articles

Should I Stay or Should I Code? Of Collaboration and Do-It-Yourself Programming in Investigative Journalism

For journalists, numerous digital tools such as spreadsheets or web application are readily available for easy implementation. However, using programming to build or modify scripts has been an unexplored option for many journalists. Programming requires skills from the ICT professions, so when journalists find coding to be an efficient tool, do they stick with their old methods and ask ICT specialists for help, or do they learn to code themselves? This article is a qualitative study of the methodological reports pertaining to investigative projects nominated for the Norwegian journalism award SKUP. In these reports, programming has been used as a tool in 109 projects. The study examines which problems are solved using coding and the arguments for choosing this tool over simpler methods. It also looks at who performs the coding and how the editorial teams collaborate to reap the benefits of coding. The findings show that many journalists often find it difficult to collaborate with ICT specialists. They would therefore rather learn basic coding skills themselves. They follow a “do-it-yourself” philosophy and learn simple and open programming languages such as SQL, Python just well enough to achieve their goals.

РОЗРОБКА ІНФОРМАЦІЙНОЇ МОДЕЛІ МОНІТОРИНГУ ЕКОСИСТЕМИ

Goal. Development of an information model for monitoring ecosystem data obtained from facilities to identify deviations from the standard, in real time, at a distance and make decisions to eliminate themMethodology. The development of the system was based on the Minimum viable product with minimal functionality. and the minimum cost of resources. The concept of system development is considered on the example of a reasonable dormitory, where one of the components of the system is the Internet of Things technology, in which different device connect to the Internet and interact with each other. The sensors allow the device to send data to a computer program that will collect and analyze it. This will allow you to effectively identify the problem in the event of deviations from the standard during the operation of s and will facilitate the prediction of possible accidents, malfunctions and their elimination.Results. Based on the analysis of the characteristics of microcontrollers and sensors, a wireless communication module installed in the device of the monitoring system was selected, and types of sensors were selected for collecting and further analysis of ecosystem indicators The structural elements of the subsystem and the code for the example of the board for the sensor have been developed. To implement the task, the open programming language Processing and development tools were chosen that would satisfy all the requirements and have the necessary functionality. TelegramBot was chosen as the interface for the ecosystem's automated storage database concepts. To connect hardware devices, APIs and Internet services, Node-RED was chosen as the programming tool. To write the bot, the RedBot package for NodeRED was used.Scientific novelty. An original solution is proposed for the development of an information model of ecosystem indicators in premises based on the element base of the selected monitoring module, communication protocols and an interface for interacting with the user through a chat bot.Practical significance. The system was tested on data obtained in the hostel KNUTD in may 2021. This environment is hosted on Amazon Web Services (AWS) EC2The test results showed the system's operability, the ability to receive and analyze information in real time and quickly respond to dangerous situations. All this will improve the life of students in the hostel and ensure themselves and their health from the influence of negative factors.

Dielectric Polymer Property Prediction Using Recurrent Neural Networks with Optimizations.

Despite the growing success of machine learning for predicting structure-property relationships in molecules and materials, such as predicting the dielectric properties of polymers, it is still in its infancy. We report on the effectiveness of solving structure-property relationships for a computer-generated database of dielectric polymers using recurrent neural network (RNN) models. The implementation of a series of optimization strategies was crucial to achieving high learning speeds and sufficient accuracy: (1) binary and nonbinary representations of SMILES (Simplified Molecular Input Line System) fingerprints and (2) backpropagation with affine transformation of the input sequence (ATransformedBP) and resilient backpropagation with initial weight update parameter optimizations (iRPROP- optimized). For the investigated database of polymers, the binary SMILES representation was found to be superior to the decimal representation with respect to the training and prediction performance. All developed and optimized Elman-type RNN algorithms outperformed nonoptimized RNN models in the efficient prediction of nonlinear structure-activity relationships. The average relative standard deviation (RSD) remained well below 5%, and the maximum RSD did not exceed 30%. Moreover, we provide a C++ codebase as a testbed for a new generation of open programming languages that target increasingly diverse computer architectures.

Development of the software tool Sample Size for Arbitrary Distributions and exemplarily applying it for calculating minimum numbers of moss samples used as accumulation indicators for atmospheric deposition

BackgroundDo we measure enough to calculate statistically valid characteristic values from random sample measurements, or do we measure too much—without any further increase in knowledge? This question is actually one of the key issues of every empirical measurement design, but is rarely investigated in environmental monitoring.ResultsIn this study, the methodology used for the design of the German Moss Survey 2015 network to determine statistically valid minimum sample numbers (MSN) for the calculation of the arithmetic mean value in compliance with certain accuracy requirements was further developed for data that are neither normally nor lognormally distributed. The core element of the procedure for estimating MSN without prerequisite to the distribution of data is an iterative Monte Carlo simulation. The methodological principle consists of using reference data (values measured in Moss Surveys preceding that in 2015) for a series of MSN candidate values to determine what accuracy would be achieved with these, and then calculating the MSN with which the specified accuracy requirement is met from a quadratic function between MSN candidates and their accuracy. The program Sample Size for Arbitrary Distributions (SSAD) was developed for the calculation of the MSN in the open programming language R.ConclusionsThe SSAD procedure closes a gap in the existing methodology for calculating statistically valid minimum sample numbers.

Application of single-board computers in experimental research on unsaturated soils

In this contribution, the application of single-board computers for the investigation of the hydro-mechanical behaviour of unsaturated granular soils is presented. Single-board computers, such as the Raspberry Pi or Arduino, have recently experienced a hype of applications in school and university teaching, in the maker scene, amongst hobbyists, but also in research. In combination with easy to learn and open programming languages, such as Python, individual experimental set-ups for research in unsaturated soil mechanics, using actuators and sensors can be easily developed with the help of different programmable hardware, such as stepper motors, analog-to-digital converters and other controller boards. For the experimental application in imaging of unsaturated granular soils by computed tomography (CT), we present a miniaturized uniaxial compression device for the measurement of unsaturated shear strength and capillary cohesion in CT-experiments. The device has already been applied for CT-imaging of the development of water distribution and capillary bridges in between different shear steps. Furthermore, a new fully programmable hydraulic experimental set-up for the automated investigation of transient hydraulic paths of the water retention curve of granular media is presented. Both devices have been developed in the framework of the Raspberry Pi single-board computer and Python programming language with simple and relatively inexpensive hardware components. In addition to the technical development of the testing devices, experimental results of the hydro-mechanical behaviour of unsaturated sand and glass beads, derived from uniaxial compression tests and water retention tests, will be presented.

Open Programming Language Interpreters

Context: This paper presents the concept of open programming language interpreters and the implementation of a framework-level metaobject protocol (MOP) to support them. Inquiry: We address the problem of dynamic interpreter adaptation to tailor the interpreter's behavior on the task to be solved and to introduce new features to fulfill unforeseen requirements. Many languages provide a MOP that to some degree supports reflection. However, MOPs are typically language-specific, their reflective functionality is often restricted, and the adaptation and application logic are often mixed which hardens the understanding and maintenance of the source code. Our system overcomes these limitations. Approach: We designed and implemented a system to support open programming language interpreters. The prototype implementation is integrated in the Neverlang framework. The system exposes the structure, behavior and the runtime state of any Neverlang-based interpreter with the ability to modify it. Knowledge: Our system provides a complete control over interpreter's structure, behavior and its runtime state. The approach is applicable to every Neverlang-based interpreter. Adaptation code can potentially be reused across different language implementations. Grounding: Having a prototype implementation we focused on feasibility evaluation. The paper shows that our approach well addresses problems commonly found in the research literature. We have a demonstrative video and examples that illustrate our approach on dynamic software adaptation, aspect-oriented programming, debugging and context-aware interpreters. Importance: To our knowledge, our paper presents the first reflective approach targeting a general framework for language development. Our system provides full reflective support for free to any Neverlang-based interpreter. We are not aware of any prior application of open implementations to programming language interpreters in the sense defined in this paper. Rather than substituting other approaches, we believe our system can be used as a complementary technique in situations where other approaches present serious limitations.