Finds documents with both search terms in any word order, permitting "n" words as a maximum distance between them. Best choose between 15 and 30 (e.g. NEAR(recruit, professionals, 20)).
Finds documents with the search term in word versions or composites. The asterisk * marks whether you wish them BEFORE, BEHIND, or BEFORE and BEHIND the search term (e.g. lightweight*, *lightweight, *lightweight*).
Following the establishment of Indonesia’s sovereign wealth fund, a move poised to reshape the nation’s investment environment, there has been an increasing need to interpret market sentiment and its influence on stock performance. This study …
Trading decision-making is significantly influenced by psychological resistance that emerges under dynamic market conditions. Fear and greed states provide a quantifiable representation of these behavioral dynamics, serving as the basis for …
Biometric authentication systems, which use unique biological traits for identification, have gained popularity in various fields as a replacement for traditional password- or token-based systems. While offering enhanced security, these systems …
The business world is concentric around the imperative of information extraction and analysis. The information extraction processes are blended with different data mining techniques like clustering, classification, etc. Clustering is an …
In multivariate time series (MTS) anomaly detection, existing graph neural network (GNN) methods often neglect multi-level feature representations, relying solely on the final layer output and fixed thresholds, which leads to information loss and …
High-entropy alloys (HEAs) represent a state-of-the-art material system, exhibiting exceptional physical and chemical properties that hold great potential for engineering applications. Nevertheless, accurately identifying their complex phase …
The connection between stock market prices and trading volume has long been a subject of extensive research interest among scholars. This study examines whether the effective utilization of exogenous information from market participants …
The rapid integration of Internet of Things (IoT) devices in healthcare demands a robust framework to ensure secure patient monitoring and timely attack detection. This study proposes a Secure Healthcare Monitoring and Attack Detection Framework …
Functional data analysis (FDA) continues to gain prominence in modern statistical research. Building on the concept of statistical depth, originally developed for multivariate data, this paper extends its application to functional settings and …
Accurate inflation forecasting is critical for effective economic planning and monetary policy formulation, especially in emerging economies such as Nigeria. Persistent inflation volatility driven by structural inefficiencies, external shocks, and …
Autism Spectrum Disorder (ASD) are neurodevelopmental disorders that severely impact daily life and social interactions. According to research, early diagnosis and intervention of autism is crucial to improve the overall quality of life of …
Automatic music generation plays a crucial role in generating creative compositions autonomously, facilitating applications in various fields, including entertainment and education. The challenges faced by existing approaches include capturing …
To address the seasonal energy imbalance resulting from the high penetration of renewable energy sources in power systems, this study leverages smart grid technologies to innovatively design a hybrid electric-hydrogen energy storage system. The …
Internet of Things (IoT) is playing a vital role in healthcare by automating the real time monitoring of patients seamlessly with the help of a variety of sensors. In the current scenario of smart healthcare, IoT with the integration of machine …
Stock return predictability has been one of the most studied fields in finance. This research examines SPDR S&P500 ETF Trust—SPY’s—daily data from December 3, 2007, to May 20, 2025, employing machine learning (including Logistic Regression, Ridge …
This paper introduces a novel one-parameter bounded distribution, called the Unit Rayleigh Half-Normal (URHN) distribution, designed for modeling data on the unit interval (0,1), which frequently arises in many fields such as economics, actuarial …
In the presence of imbalanced data problem, existing feature selection methods focus on retaining features that are useful for majority class sample recognition, which leads to poor performance of recognizing minority class samples. However, in …
Smoothing is a foundational operation in time series analysis, often used to mitigate the effects of noise and outliers prior to visualization, modeling, or classification. However, traditional filters such as Gaussian smoothing, exponential …