Algeria is one of the Maghreb countries most affected by wildfires. The economic, environmental, and societal consequences these fires can last several years after wildfire. Often, it possible to avoid such disasters if detection outbreak fire fast enough, reliable, early. lack datasets has limited methods used predict wildfires in mapping risk areas, which updated annually. This study result availability a recent dataset relating history forest cities Bejaia Sidi Bel-Abbes during year 2012....

Humanity’s quest for safe, resilient, and liveable cities has prompted research into the application of computational tools in design development sustainable smart cities. Thus, artificial intelligence (AISC) become an important field with numerous publications, citations, collaborations. However, scholarly works on publication trends landscape AISC remain lacking. Therefore, this paper examines current status future directions research. The PRISMA approach was selected to identify, screen,...

Solar energy presents a promising solution to replace fossil-based sources, mitigating global warming and climate change. However, solar faces socio-economic, environmental, technical challenges. Computational tools like machine learning offer solutions these Despite numerous studies, there's lack of comprehensive research on ML applications in Photovoltaics Energy. This study conducts critical analysis Energy using publication trends bibliometric analysis, employing the PRISMA approach...

The research landscape on the applications of advanced computational tools (ACTs) such as machine/deep learning and neural network algorithms for energy power generation (EPG) was critically examined through publication trends bibliometrics data analysis. Elsevier Scopus database PRISMA methodology were employed to identify screen published documents, whereas bibliometric analysis software VOSviewer used analyse co-authorships, citations, keyword occurrences. results showed that 152...

Logistic regression is a commonly used classification algorithm in machine learning. It allows categorizing data into discrete classes by learning the relationship from given set of labeled data. learns linear dataset and then introduces nonlinearity through an activation function to determine hyperplane that separates points two subclasses. In case logistic regression, most perform binary classification. The choice for classifications justified its ability transform any real number...

Climate change (CC) is one of the greatest threats to human health, safety, and environment. Given its current future impacts, numerous studies have employed computational tools (e.g., machine learning, ML) understand, mitigate, adapt CC. Therefore, this paper seeks comprehensively analyze research/publications landscape on MLCC research based published documents from Scopus. The high productivity impact has produced highly cited works categorized as science, technology, engineering arts,...

This research proposes a successful technique for identifying individuals using feature extraction methods and signal processing approaches. The novelty of this study is in the use conjunction with other signal-processing While working sensors, an artificial neural network (ANN) employed to identify scent patterns that are present persons. numerous gases released by human body measured ten different kinds all which metal oxide semiconductors. Before ANN generate from sensor data, it...

Object datasets used in the construction of object detectors are typically annotated with horizontal or oriented bounding rectangles for IoT-based. The optimality an annotation is obtained by fulfilling two conditions: (i) rectangle covers whole and (ii) area minimal. Building a large-scale dataset requires annotators equal manual dexterity to carry out this tedious work. When IoT-based, it easy annotator reach optimal box within reasonable time. However, if oriented, needs additional time...

The publication trends and bibliometric analysis of the research landscape on applications machine deep learning in energy storage (MDLES) were examined this study based published documents Elsevier Scopus database between 2012 2022. PRISMA technique employed to identify, screen, filter related publications MDLES recovered 969 comprising articles, conference papers, reviews English. results showed that count topic increased from 3 385 (or a 12,733.3% increase) along with citations high rate...

Twitter and Facebook are popular among college educators. The use of social media in schools higher learning has also been the subject study. opened up new avenues contact, collaboration, participation between students teachers. Accepting educators who make technological tools to do so requires insight into factors that shape their propensity so. Using Technology Acceptance Model (TAM) framework, which highlights perceived ease use, usefulness, behavioral intention technologies, this paper...

In Industry 4.0, integrating IIoT and smart manufacturing is crucial for high-quality, efficient, cost-effective production. However, the performance of systems can be hindered by unevenly distributed ESPs. To tackle this challenge, we propose an optimized embedded system edge intelligence manufacturing, leveraging digital twin technology. Our approach employs a twin-assisted alliance game resource optimization strategy to jointly optimize multi-dimensional allocation, including bandwidth,...

The aim of this paper is to compare the relative accuracies between deterministic and stochastic methods for solving bounded integrals numerically observe which tend function well converge a small amount error based on computational resources. For method, Gauss-Legendre quadrature method has been selected Monte Carlo integration selected. each case, number variables will be adjusted effect error. permutations increased with inaccuracy 9% when nodes 3 but was reduced by 90% later depicted...

This paper deals with the problem of blind separation an instantaneous mixture Gaussian autoregressive sources, without additive noise, by exact maximum likelihood approach. The maximization function is divided, using relaxation, into two suboptimization problems, solved relaxation methods as well. first one consists estimation separating matrix when structure sources fixed. second aims at estimating this We show that equivalent to determinant under nonlinear constraints. prove existence and...

Caused by a shortage of oxygen-rich blood, cardiac artery disease occurs when coronary arteries get blocked. Arterial occlusion decreases the heart's blood flow and hence its oxygen supply. Plaque buildup is leading cause arterial obstruction. Both cholesterol calcium can be found in plaque. Atherosclerosis refers to development plaque within arteries. It possible have total ischemia due an clot. As ruptures, clots form. A diet rich contribute person's Cholesterol transported bloodstream via...

Data mining methods like sentiment analysis provide useful information. This paper examines drug online user reviews. research predicts satisfaction with sentiments and applied drugs on effectiveness side effects using based classification analyzes model transfer across data sources Emzor May & Baker data. Online medication review Web crawlers was used to collect the ratings comments of forum members. Pharmaceutical Company had 463 reviews 421 split 70% for training 30% testing. We predict...

In blind source separation (BSS), many methods use positive definite symmetric pencil either to achieve the whitening procedure of data or estimate mixing matrix. All these consist in finding a linear combination (PDLC) several time delayed autocovariance matrices. Many algorithms have been developed compute coefficients such combination. However, BSS problem existence has never addressed with rigorous way. this letter, we exhibit necessary and sufficient condition for PDLC. Moreover,...

This paper presents the problem of maximizing determinant a real $K\times K$‐matrix B, subject to constraint that each row $b_k$ B satisfies $b_k^t \Gamma_kb_k \leq 1$, where $\Gamma_1, \ldots,\Gamma_K$ are K given symmetric positive definite matrices. comes from specific blind signal separation approach, but criterion differs approximate diagonalization criteria usually encountered in this area. Furthermore our corresponds following nice geometrical problem: ellipsoids ${\rm\bf R}^K,...

This correspondence presents a new algorithm to find positive definite combination of some given real symmetric matrices. When this problem has solutions, we show that it can be written as an optimization problem. An iterative using relaxation type method is proposed solve We also prove finite-step global convergence property. A comparison, by computer simulations, shows our much faster than another one generally in literature such combination.