Popular Programming Research Articles

Logical analysis of built-in DBSCAN Functions in Popular Data Science Programming Languages

DBSCAN algorithm is a location-based clustering approach; it is used to find relationships and patterns in geographical data. Because of its widespread application, several data science-based programming languages include the DBSCAN method as a built-in function. Researchers and data scientists have been clustering and analyzing their study data using the built-in DBSCAN functions. All implementations of the DBSCAN functions require user input for radius distance (i.e., eps) and a minimum number of samples for a cluster (i.e., min_sample). As a result, the result of all built-in DBSCAN functions is believed to be the same. However, the DBSCAN Python built-in function yields different results than the other programming languages those are analyzed in this study. We propose a scientific way to assess the results of DBSCAN built-in function, as well as output inconsistencies. This study reveals various differences and advises caution when working with built-in functionality.

Analisis Semiotika Gaya Bahasa dalam Program Sie Reuboh LPP-RRi Banda Aceh

Abstract: Purpose: There are many problems that occur in the pronunciation and delivery of information both in writing and orally and visually. This happens because there is no filter in language style, therefore language style is needed with the aim that every information conveyed can be digested and consumed properly by listeners according to the age level of the listener Method: This scientific work is a descriptive study use a qualitative approach. using survey, interview, and recording methods. In collecting data the researchers used several interrelated and complementary techniques, namely, observation, interviews, recording and documentation. Results: Intern students are directly involved in the process of covering the media. In this study, while the researchers listened to several parts, namely the recorded documentation on May 14, 2022 that the entire “Sie Reuboh” programme used standard and formal language calls. The researcher concludes that the use of language style in a communication process, especially in this popular voice programme, uses several language styles to convey and explain meaning without having to use excessive word stress. Limitations: The limitation in this study lies in the search for references to previous studies because research on semiotic analysis of language style in the form of sound is still very rarely studied. and data retrieval during recording. Researchers had difficulty during interviews because of the broadcaster's schedule not every day. This research in the future will also cover other radio programs. Contribution: The result language style is more to mediate and straighten out the problems that exist between the communicator and the communicant. Keywords: 1. Semiotic analysis 2. Language style 3. Radio

A content analysis of 'junk food' content in children's TV programmes: a comparison of UK broadcast TV and video-on-demand services.

Exposure to high in fat, sugar or salt (HFSS) food imagery is associated with unhealthy consumption, and subsequently obesity, among young people. We report and compare the results of two content analyses, one of popular children's television channels in the UK and the other of a selection of children's programmes available on video-on-demand (VOD) services. Content analysis of 3days' worth of programmes on two popular children's television channels broadcast on UK television (CBeebies and Milkshake as well as a sample of children's programmes available on the VOD platforms (Netflix and Amazon Prime) using 1-min interval coding. In children's television channels, HFSS content was seen in 181 episodes (36%) and in 417 intervals (13%) on terrestrial television, 'Milkshake' had a significantly higher proportion of broadcasts, which contained HFSS content than 'CBeebies'. In VOD platforms, HFSS content was seen in 82 episodes (72% of the total number of episodes), across 459 intervals (19% of the total number of intervals), with no significant difference in the proportion of programmes containing HFSS content between Netflix and Amazon Prime. HFSS content is common in both popular UK children's television channels and children programmes on VOD services and is likely having an effect on HFSS consumption in children. Legislative opportunities to prevent this exposure are being missed.

Multiscale modeling of stochastic dynamics processes with MBN Explorer.

Stochastic dynamics describes processes in complex systems having the probabilistic nature. They can involve very different dynamical systems and occur on very different temporal and spatial scale. This paper discusses the concept of stochastic dynamics and its implementation in the popular program MBN Explorer. Stochastic dynamics in MBN Explorer relies on the Monte Carlo approach and permits simulations of physical, chemical, and biological processes. The paper presents the basic theoretical concepts underlying stochastic dynamics implementation and provides several examples highlighting its applicability to different systems, such as diffusing proteins seeking an anchor point on a cell membrane, deposition of nanoparticles on a surface leading to structures with fractal morphologies, and oscillations of compounds in an autocatalytic reaction. The chosen examples illustrate the diversity of applications that can be modeled by means of stochastic dynamics with MBN Explorer.

Understanding parent perspectives on engagement with online youth-focused mental health programs

Objective Online youth-focused health programs often include parent modules—that equip parents with skills to assist their child in improving their health—alongside youth-specific content. BRAVE Self-Help, an evidence-based program designed for children and teenagers with early signs of anxiety, is a popular Australian program that includes six parent modules. Despite its popularity and proven efficacy, BRAVE Self-Help shares the same challenge as many online self-help programs—that of low participant engagement. Using parents registered in BRAVE Self-Help as ‘information rich’ participants, we explored (a) factors that influenced parent engagement in online health programs, and (b) their recommendations for enhancing parent engagement. Design and Outcome Measure We conducted semi-structured interviews with 14 parents registered in BRAVE Self-Help. Data were analysed through reflexive thematic analysis. Results Social-, family- and program-related factors drove parents’ program engagement and recommendations. Social sub-themes related to the benefits of professional and community support in promoting more engagement. Family sub-themes included difficulties with program engagement due to competing priorities, perceptions that condition severity influenced engagement, and feelings that previously-acquired health knowledge reduced motivation to engage. Program sub-themes included perceived usefulness and ease-of-use. Conclusion Program designers could target support systems, include flexible delivery options, and use iterative design processes to enhance parent engagement.

Meaning and responsibility

In performing an act of assertion we are sometimes responsible for more than the content of the literal meaning of the words we have used, sometimes less. A recently popular research program seeks to explain certain of the commitments we make in speech in terms of responsiveness to the conversational subject matter. We raise some issues for this view with the aim of providing a more general account of linguistic commitment: one that is grounded in a more general action‐theoretic notion of responsibility.

Pradhan Mantri Jan Dhan Yojana (PMJDY) : Analyzing Performance Using Financial Inclusion Indicators

PMJDY (Pradhan Mantri Jan Dhan Yojana), one of India’s most popular financial inclusion programs, was touted as a potential game-changer that could transform decades of dreams of attaining complete financial inclusion into a reality. This article tried to verify these claims and closely examined the various financial inclusion indicators which should have changed after the introduction of this program. It was inferred that despite several flaws in its implementation, PMJDY generated a tremendous number of bank accounts for those who had none. The study found that, remarkably, females own more than half of the accounts. However, account usage among females is low due to fewer employment opportunities. Women empowerment and raising entrepreneurial spirit are some solutions to allow women to save money in the formal banking system. It has become feasible to make direct cash transfers to vulnerable people’s PMJDY accounts whenever necessary. Increased access to financial products can lift many people out of perpetual poverty. It is too early, however, to comment on the reduction of poverty and inequality in India due to PMJDY. PMJDY has not affected the C-D Ratio; an increase in profitable credit deployment is imperative for increasing bank profits. Another caveat is the low awareness and widespread financial and technological illiteracy preventing full-fledged access to the program’s benefits. Learning from the financial programs of other LMICs, the periodic assessment of PMJDY, and solving implementation problems are necessary for the program’s long-term sustainability.

Top Policy Issues: A Powerful, Passionate Journey

Top Policy Issues: A Powerful, Passionate Journey

IRS-Assisted Multicell Multiband Systems: Practical Reflection Model and Joint Beamforming Design

Intelligent reflecting surface (IRS) has been regarded as a promising and revolutionary technology for future wireless communication systems owing to its capability of tailoring signal propagation environment in an energy/spectrum/ hardware-efficient manner. However, most existing studies on IRS optimizations are based on a simple and ideal reflection model that is impractical in hardware implementation, which thus leads to severe performance loss in realistic wideband/multi-band systems. To deal with this problem, in this paper we first propose a more practical and more tractable IRS reflection model that describes the difference of reflection responses for signals at different frequencies. Then, we investigate the joint transmit beamforming and IRS reflection beamforming design for an IRS-assisted multi-cell multi-band system. Both power minimization and sum-rate maximization problems are solved by exploiting popular second-order cone programming (SOCP), Riemannian manifold, minimization-majorization (MM), weighted minimum mean square error (WMMSE), and block coordinate descent (BCD) methods. Simulation results illustrate the significant performance improvement of our proposed joint transmit beamforming and reflection design algorithms based on the practical reflection model in terms of power saving and rate enhancement.

A Horse Is a Horse

A Horse Is a Horse

Präzi: from package-based to call-based dependency networks

Modern programming languages such as Java, JavaScript, and Rust encourage software reuse by hosting diverse and fast-growing repositories of highly interdependent packages (i.e., reusable libraries) for their users. The standard way to study the interdependence between software packages is to infer a package dependency network by parsing manifest data. Such networks help answer questions such as “How many packages have dependencies to packages with known security issues?” or “What are the most used packages?”. However, an overlooked aspect in existing studies is that manifest-inferred relationships do not necessarily examine the actual usage of these dependencies in source code. To better model dependencies between packages, we developed Präzi, an approach combining manifests and call graphs of packages. Präzi constructs a dependency network at the more fine-grained function-level, instead of at the manifest level. This paper discusses a prototypical Präzi implementation for the popular system programming language Rust. We use Präzi to characterize Rust’s package repository, Crates.io, at the function level and perform a comparative study with metadata-based networks. Our results show that metadata-based networks generalize how packages use their dependencies. Using Präzi, we find packages call only 40% of their resolved dependencies, and that manual analysis of 34 cases reveals that not all packages use a dependency the same way. We argue that researchers and practitioners interested in understanding how developers or programs use dependencies should account for its context—not the sum of all resolved dependencies.

ПАНДЕМІЯ COVID-19 ТА ЕЛЕКТРОННЕ НАВЧАННЯ ПРИ ВИВЧЕННІ ІНОЗЕМНОЇ МОВИ: ВИКЛИКИ ТА МОЖЛИВОСТІ ДЛЯ СТУДЕНТІВ ТА ВИКЛАДАЧІВ

The spread of COVID-19 poses a threat to humanity, as this pandemic has forced many global activities to close, including educational activities. To reduce the spread of the virus, education institutions have been forced to switch to E-learning using intelligible and free educational platforms, despite the challenges facing this sudden transformation. The focus of this study is E-learning from the perspective of students and teachers on the use and implementation of E-learning systems in higher education institutions (HEIs) in foreign language teaching during the COVID-19 pandemic. This article aims to identify issues related to the use, advantages, disadvantages and barriers of E-learning programs at the university by comparing the views of students and teachers who use this method of learning in long-term unusual circumstances. Four aspects were identified and characterized, namely: the extent of the use of E-learning during the COVID-19 pandemic, the advantages, disadvantages and obstacles of implementing E-learning in foreign language learning in in higher education institutions. In the course of our research, we have achieved some results that shed light on some of the problems, challenges and benefits of using E-learning systems instead of traditional education in higher education institutions in general and during emergencies. The most popular programs among teachers for online classes were highlighted and characterized in this article.

Top Popular Python Libraries in Research

Python is one of the most popular programming languages in research. The structure of the language and its object-oriented approach help programmers to write logical and clear code for small and large projects. Python libraries (packages) effectively simplify many important processes such as analysing and visualizing data, retrieving unstructured data from the web, image processing, building machine learning models, and textual information [1-4]. In this article, some of the most important and popular libraries and packages in Python are described.

Hawksbill presence and habitat suitability of a marine reserve in Honduras

Marine protected areas (MPAs) have been established to decrease the negative impacts of human activities on important marine habitats. Several sea turtle species reside within MPAs; however, analyses of habitat suitability for sea turtles within many MPAs is typically lacking. Habitat modeling and species mapping have become essential tools in determining areas suitable for species inhabitance. MaxEnt is a popular machine-learning program that uses presence-only occurrence data and is considered the best modeling method in discriminating between suitable and unsuitable habitats. Using MaxEnt, we created species distribution models (SDMs) from presence-only occurrence points for juvenile hawksbills and three environmental variables: boat traffic intensities, prey item distributions, and benthic characterizations, within the Sandy Bay West End Marine Reserve (SBWEMR) in Roatán, Honduras. Area under the receiving operator curve (AUC) values were greater than 0.75, indicating high model accuracy. Jackknife evaluations indicated algal prey item Dictyota spp., boat traffic intensity, and Geodia neptuni sponge abundance had the greatest influence on species distribution. Areas of suitability shifted based on time of day and ranged from a low probability of hawksbill presence (0.0) to a high probability of hawksbill presence (0.8). Regardless of time of day, the SBWEMR is classified as at least moderately suitable (>0.2–0.4), with least suitable habitat (0–0.2) prevalent in the most northeastern region of the reserve. The greatest suitability (>0.6–1) was evident within the mid-region and southern most regions of the reserve. Probability of hawksbill presence increased in accordance with increasing boat traffic, although there was no clear causative relationship between the two. Although the reserve overall is mostly moderately suitable, the SBWEMR remains an important local recruitment and foraging ground for juvenile hawksbills. Hawksbills have been considered resilient, continually functioning beneath their operational limits. However, with continued global depletion of essential habitats over time and lack of effective MPA management, areas of habitat suitable for hawksbill inhabitance may decrease below levels sufficient for hawksbill presence in protected areas of the Western Caribbean.

Graphical user interface for SDTrimSP to simulate sputtering, ion implantation and the dynamic effects of ion irradiation

SDTrimSP is a popular simulation program to compute several effects of the interaction between an impinging ion and a solid, such as ion implantation ranges, damage formation or sputtering of surface atoms. We now introduce a graphical user interface for SDTrimSP to make its operation more accessible for a broad group of users. It is written as a separate Python program and is not restricted to any specific operating system. The interface allows a quick and easy start as well as the direct evaluation of SDTrimSP simulations. Its capabilities are demonstrated here in the form of several example cases, including the dynamic simulations with SDTrimSP, where ion-induced target changes are taken into account. The presented graphical user interface is made freely available to support a large number of users in performing simulations of ion–solid interaction.

Evaluation of an electrochemical membrane reactor for the removal of β-blocker compound from water

As part of the Brazilian Popular Pharmacy Program, the β-blocker Atenolol (ATN) is widely used, and its presence in the environmental ecosystems is a reality. Aiming the ATN removal, the use of an electrochemical membrane reactor was evaluated and compared to a membraneless one. The results show that the generation of SO4•− in the membrane reactor occurs by the reaction of HSO4−/H2SO4 scavenging HO•, whereas, in the membraneless reactor, the SO4•− generation occurs mainly by the direct oxidation mechanism. Operating both reactors in the same hydrodynamic conditions, it was found that the concentrations of SO4•− and S2O82− are higher in the membrane reactor, leading to a greater concentration of these species being transported to the bulk solution, changing the kinetics, and presenting better results in electrochemical combustion (ϕ), mineralization current efficiency (MCE) and specific energy consumption (Es). Since the mass transport limitations were overcome in membrane reactor, the processes may find their good applications in water and wastewater treatment.

Fotografías de Juan Maino para el Programa Padres e Hijos: Una huella material del pasado reciente.

This article synthesize the main results of the research on the transit to the archive of a series of images on photographic slides. Created around the popular education program called "Parents and Children Program" of the Center for Research and Development of Education and whose authorship corresponds to Juan Maino Canales, photographer by trade and Detained Disappeared in the 70s in Chile, these images offer a singular vision of the world, due to the materiality of the support and also due to the historical moment they capture.

An Empirical Study on the Impact of Python Dynamic Typing on the Project Maintenance

Python is a popular typical dynamic programming language. In Python, dynamic typing is one of the most critical dynamic features. The lack of type information is likely to hinder the maintenance of Python projects. However, existing work has seldom focused on studying the impact of Python dynamic typing on project maintenance. This paper focuses on the two most common practices of Python dynamic typing, i.e. inconsistent-type assignments (ITA) and inconsistent variable types (IVT). Two approaches are proposed to identify ITA and IVT, i.e. identifying ITA by analyzing Abstract Syntax Trees and comparing identifiers types and identifying IVT by constructing a type dependency graph. In empirical experiments, we first locate the usage of ITA and IVT in 10 open-source Python projects. Then, we investigate the relations between the occurrence of ITA and IVT and the results of maintenance tasks. The study results show that projects are more prone to change as the number of dynamic typing identifiers increases. There is a weak connection between change-proneness and variable dynamic typing. There is a high probability that maintenance time and the acceptance of commits decrease as dynamic typing identifiers increase in projects. These results implicate that dynamic and static variables should be divided while developing new programming languages. Dynamic typing identifiers may not be the direct root causes for most software bugs. The categories of these bugs are worth exploring.

Objective crystallographic symmetry classifications of a noisy crystal pattern with strong Fedorov-type pseudosymmetries and its optimal image-quality enhancement.

Statistically sound crystallographic symmetry classifications are obtained with information-theory-based methods in the presence of approximately Gaussian distributed noise. A set of three synthetic patterns with strong Fedorov-type pseudosymmetries and varying amounts of noise serve as examples. Contrary to traditional crystallographic symmetry classifications with an image processing program such as CRISP, the classification process does not need to be supervised by a human being and is free of any subjectively set thresholds in the geometric model selection process. This enables crystallographic symmetry classification of digital images that are more or less periodic in two dimensions (2D), also known as crystal patterns, as recorded with sufficient structural resolution from a wide range of crystalline samples with different types of scanning probe and transmission electron microscopes. Correct symmetry classifications enable the optimal crystallographic processing of such images. That processing consists of the averaging over all asymmetric units in all unit cells in the selected image area and significantly enhances both the signal-to-noise ratio and the structural resolution of a microscopic study of a crystal. For sufficiently complex crystal patterns, the information-theoretic symmetry classification methods are more accurate than both visual classifications by human experts and the recommendations of one of the popular crystallographic image processing programs of electron crystallography.

Potential for the use of large unstructured data resources by public innovation support institutions

Effective programming of research and development (R&D) support, adjusted to the actual potential of beneficiaries, requires the use of modern analytical tools. An efficient R&D support system requires up-to-date data on technological trends, ongoing (and planning) research, market needs and developing innovation. The most popular programming methods were based on the analysis of data with a 4 to 5-year time delay until recently. Having described the method of refining information from unstructured data, we explore how to make it possible not only to solve the issue of up-to-date data but to identify of the latest trends in R&D activities.The analytical tools we describe were already fully functional in 2018 and are constantly being improved. The article presents the potential of one tool that can be applied in public support institutions. Methods of identifying and diagnosing technology trends are presented within the case study of the electric car technology trend. The presented case study shows the effectiveness of the method we developed for identifying and diagnosing areas requiring support from public funds. Public institutions, including public institutions supporting R&D and innovation processes, can apply tools that allow an increase in the quality of public support programmes offered, but also beneficial for the quality of strategic resources management within the institution itself. The comparison of the predictions made by the described tools with the classifications made by experts, the former are more accurate and precise. Moreover, the results of the analyses performed by the presented model are not influenced by distorting factors—fads, trends, political pressures, or processes with an unidentified, non-substantive background. It should be emphasized that the accuracy of the whole model is 0.84. The described tools and methods are already directly applicable in many areas related to the support of R&D activity worldwide. The article presents a solution that effectively enables the management of more precise programmes supporting innovative activities used for the first time in Poland. It is also one of the first uses of these methods by public administration in the world. Our approach not only strengthens improved adjustment of the support offered for R&D activity, but also makes it possible to apply and improve management methods in public institutions.