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Hydrological Assessment Under Climatic and Socioeconomic Scenarios Using Remote Sensing, QGIS, and Climate Models : A Case Study of the Tuban Delta, Yemen

(1) Background: Water scarcity is a pressing global issue, impacting food security, health, and economic stability in many regions. In Yemen, the challenges related to water resources are particularly acute, exacerbated by climate change, overuse, and a lack of sustainable management strategies. (2) Objective: this paper assesses water resources and demands under two shared socioeconomic pathways,

Prototyping for Internet of Things with Web Technologies: A Case on Project-Based Learning using Scrum

The traditional way of teaching may no longer be sufficient to cope with current requirements specifically in the Internet of Things (IoT) domain. The case for this paper is related to an introductory programming course on JavaScript for the period of 2016-2018. In this study a multi-method approach for data collection is utilized. Project-Based Learning (PBL), Scrum and rapid prototyping are util

EzSkiROS : enhancing robot skill composition with embedded DSL for early error detection

When developing general-purpose robot software components, we often lack complete knowledge of the specific contexts in which they will be executed. This limits our ability to make predictions, including our ability to detect program bugs statically. Since running a robot is an expensive task, finding errors at runtime can prolong the debugging loop or even cause safety hazards. This paper propose

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The purpose of this study is to look into patronage effects of extended supply outside peak hours on regional public transport services. Previous studies have shown that the service frequency is an attribute of great importance for regional passengers, but little is known about the details regarding peak and off-peak frequencies or service hours. The present study addresses this knowledge gap, dep

Discrimination Based on Immigration Status under the ECHR: Navigating between the Factual versus the Normative and the Comparison-based versus the Minimum-based Treatment

Immigration status as a ground of making distinctions that might be in violation of the right to non-discrimination, is conceptually underdeveloped. This gap is addressed by explaining how the European Court of Human Rights has chosen to use arguments shaped by factual and legal/normative elements to reason under Article 14 of the European Convention on Human Rights. One such argument concerns the

Taking an Extra Moment to Consider Treatment Effects on Distributions

This paper introduces Parameter Estimation by Raw Moments (PERM), a flexible method for evaluating a policy’s impact on the parameters of an outcome distribution. Such parameters include the variance (E[Y2]−E[Y]2), skewness and covariance of two outcomes. PERM simplifies distributional analysis by first separately estimating higher-order moment treatment effects (e.g., E[Y2]), then combining these

EVALUATION OF HEAVY METALS (Cu, Zn, Pb) UPTAKE IN CARROT AND ASSOCIATED HEALTH RISK

The escalating levels of heavy metals in soil, attributed to diverse sources, pose a pressing concern for human and animal health through their entry into the food chain. This study aimed to evaluate the uptake behavior of Cu, Zn, and Pb in carrots grown in different levels of contaminated soil (control, 30, 60, 90, 120 ppm) and to assess the associated health risks to mitigate the enrichment of h

pyISC: A Bayesian Anomaly Detection Framework for Python

The pyISC is a Python API and extension to the C++ based Incremental Stream Clustering (ISC) anomaly detection and classification framework. The framework is based on parametric Bayesian statistical inference using the Bayesian Principal Anomaly (BPA), which enables to combine the output from several probability distributions. pyISC is designed to be easy to use and integrated with other Python li

Using machine learning hardware to solve linear partial differential equations with finite difference methods

This study explores the potential of utilizing hardware built for Machine Learning (ML) tasks as a platform for solving linear Partial Differential Equations via numerical methods. We examine the feasibility, benefits, and obstacles associated with this approach. Given an Initial Boundary Value Problem (IBVP) and a finite difference method, we directly compute stencil coefficients and assign them

Gamifying user feedback collection on static program analysis tools

Use of static program analysis tools can be highly beneficial in software development, but usage is hindered by usability issues. One method to better understand these issues is to gather user feedback, but it is challenging to get developers to invest effort in giving user feedback.In this paper, we investigate whether gamification can increase user engagement in feedback collection on static ana