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The continuous rising trend shown by greenhouse emissions has led to a global situation in which the promotion of clean alternative technologies is crucial. In this context, small green power self-consumption installations represent an effective ...

This article compares various classification techniques in their ability to predict risk levels and recurrence in patients with thyroid disorders. Focusing on a detailed dataset incorporating clinical and pathological features, four prominent ...

In countries like India which have historically been reliant on rainfed agriculture, the increasing need of water for irrigation to support greater cropping intensity and shifts towards horticulture, has largely been supported through groundwater based ...

Arising popularity for resource-efficient machine learning models makes random forests and decision trees famous models in recent years. Naturally, these models are tuned, optimized, and transformed to feature maximally low-resource consumption. A subset ...

This study investigates the impact of machine learning models on the generation of counterfactual explanations by conducting a benchmark evaluation over three different types of models: a decision tree (fully transparent, interpretable, white-box model), ...

Abstract: In response to the low efficiency and resolution of traditional agricultural data collection methods, which are difficult to support precise real-time monitoring and feedback, this article focused on wheat crops and combined Unmanned Aerial ...

Spatially explicit information on land cover (LC) is commonly derived using remote sensing, but the lack of training data still remains a major challenge for producing accurate LC products. Here, we develop a computer vision methodology to ...

• The lack of training data remains a major challenge to produce accurate land cover maps.
• Landscape photos represent a rich source for data on land cover.
• Computer vision and machine learning can help to extract land cover ...

In the digital age, the use of data-driven approaches to streamline processing and improve assessment has gained popularity. This paper introduces a data-driven method for assessing water resources carrying capacity (WRCC), aiming to overcome challenges ...

The Software-Defined Networking (SDN) paradigm empowers network operators to manage and coordinate network activities, allowing for greater flexibility and dynamic updating of switching tables. Over time, more and more service providers are integrating ...

People have been increasingly interested in sleep, and the number of services that provide simple sleep status monitoring is increasing. In order for users to continue to use these services, it is necessary to ensure that both users and services ...

Measuring software functional size via standard Function Points Analysis (FPA) requires the availability of fully specified requirements and specific competencies. Most of the time, the need to measure software functional size occurs well in advance with ...

Heating, ventilation, and air conditioning (HVAC) systems are essential for maintaining a comfortable indoor environment in modern buildings. However, HVAC systems are known to consume a lot of energy, which can account for up to $50\%$ of a building’...

Cancer patients may undergo lengthy and painful chemotherapy treatments, comprising several successive regimens or plans. Treatment inefficacy and other adverse events can lead to discontinuation (or failure) of these plans, or prematurely ...

Uplift modeling aims to estimate the incremental impact of a treatment, such as a marketing campaign or a drug, on an individual’s behavior. These approaches are very useful in several applications such as personalized medicine and advertising, as ...

The importance of studying double-diffusive fluid flows along with the significance of non-Newtonian fluids have been well recognized in the fluid dynamics field for scientific and practical purposes. However, and given the ever-rising ...

Smart Tourism for the Industry 4.0 and post Covid-19 challenge needs explainable AI Algorithms adapted for the Volatility, Uncertainty, Complexity and Ambiguity (VUCA) World with smart (physical components, algorithms, and IoT/mobile connectivity) ...

Optimizing compilers rely on many hand-crafted heuristics to guide the optimization process. However, the interactions between different optimizations makes their design a difficult task. We propose using machine learning models to either replace such ...

This document presents a forecaster based on statistical features to implement the electricity load forecasting for the Mexican National Interconnected System. A particularity of this work is that the data used in the forecaster implementation are ...

Livestock producer’s profits are generally linked to the weight of their animals. This will allow them to better plan their supply of the worldwide increasing demand on meat An interesting approach to address the issue of final performance ...

We consider a multivariate data matrix of size $n\times d=2183\times 15$, where $n=2183$ is the number of time segments recorded from vibration signals of two gearboxes, and $d=15$ is the number of variables (traits) characterizing these segments. To learn about ...