The rapid advancement in artificial intelligence and machine learning techniques, availability of large-scale data, increased computational capabilities the opens door to develop sophisticated methods predicting stock price. In meantime, easy access investment opportunities has made market more complex volatile than ever. world is looking for an accurate reliable predictive model which can capture market's highly nonlinear behavior a holistic framework. This study uses long short-term memory...

The accelerated progress in artificial intelligence encourages sophisticated deep learning methods predicting stock prices. In the meantime, easy accessibility of market palm one's hand has made its behavior more fuzzy, volatile, and complex than ever. world is looking at an accurate reliable model that uses text numerical data which better represents market's highly volatile non-linear a broader spectrum. A research gap exists accurately target stock's closing price utilizing combined data....

Stock price prediction is a prevalent research field in both industry and academia. There pressing demand to develop model that captures the pattern of financial activities with high precision make an informed decision. challenging due complex, incomplete, fuzzy, nonlinear, volatile nature data. However, developing robust possible advancements artificial intelligence, availability large-scale data, increased access computational capability. This study performs comparative analysis three deep...

Deep-SDM is a unified layer framework built on TensorFlow/Keras and written in Python 3.12. The aligns with the modular engineering principles for design development strategy. Transparency, reproducibility, recombinability are framework’s primary criteria. platform can extract valuable insights from numerical text data utilize them to predict future values by implementing long short-term memory (LSTM), gated recurrent unit (GRU), convolution neural network (CNN). Its end-to-end machine...

Teak [Tectona grandis L.f.] has a wide distribution range in tropical countries and is Nepal’s second most planted commercial tree species. This study aimed to develop robust reliable taper equation for species Nepal. To achieve this, 15 parametric equations were fitted evaluated using the diameter height data of 100 trees sampled from two stands Sagarnath Plantation projects, The set was split into training (90%) testing (10%) sets based on trees’ ID, model fitting conducted phases. In...

The Himalayan region has already witnessed profound climate changes detectable in the cryosphere and hydrological cycle, resulting drastic socio-economic impacts. We developed a 619-yea-long tree-ring-width chronology from central Nepal Himalaya, spanning period 1399–2017 CE. However, due to low replication of early part chronology, only section after 1600 CE was used for reconstruction. Proxy relationships indicate that temperature conditions during spring (March–May) are main forcing...

Vulnerability forecasting models help us to predict the number of vulnerabilities that may occur in future for a given Operating System (OS). There exist few focus on quantifying without consideration trend, level, seasonality and non linear components vulnerabilities. Unlike traditional ones, we propose vulnerability analytic prediction model based non-linear approaches via time series analysis. We have developed Auto Regressive Moving Average (ARIMA), Artificial Neural Network (ANN),...

Stock price prediction is a prevalent research field in both industry and academia. There pressing demand to develop model that captures the pattern of financial activities with high precision make an informed decision. challenging due complex, incomplete, fuzzy, nonlinear, volatile nature data. However, developing robust possible advancements artificial intelligence, availability large-scale data, increased access computational capability.

There are several security metrics developed to protect the computer networks. In general, common focus on qualitative and subjective aspects of networks lacking formal statistical models. present study, we propose a stochastic model quantify risk associated with overall network using Markovian process in conjunction Common Vulnerability Scoring System (CVSS) framework. The uses host access graph represent environment. Utilizing model, one can filter large amount information available by...

Abstract Wood stiffness (modulus of elasticity, MOE) is an important property for conifer wood, with the variability in MOE largely being a function both specific gravity (SG) (wood density) and angle microfibrils within S2 layer longitudinal tracheids. Rapid analysis techniques can be used together to quantify MOE; while SG determined relative ease, this not case microfibril angle, requiring expensive X-ray diffraction equipment. An alternative measure acoustic velocity. The objective study...

Predicting stock market movement direction is a challenging task due to its fuzzy, chaotic, volatile, nonlinear, and complex nature. However, with advancements in artificial intelligence, abundant data availability, improved computational capabilities, creating robust models capable of accurately predicting now feasible. This study aims construct predictive model using news headlines predict direction. It conducts comparative analysis five supervised classification machine learning...

Abstract The consideration of environmental, social, and governance (ESG) aspects has become an integral part investment decisions for individual institutional investors. Most recently, corporate leaders recognized the core value ESG framework in fulfilling their environmental social responsibility efforts. While stock market prediction is a complex challenging task, several factors associated with developing further increase complexity volatility portfolios compared broad indices. To...

Creatine is a popular and widely used ergogenic dietary supplement among athletes, for which studies have consistently shown increased lean muscle mass exercise capacity when with short-duration, high-intensity exercise. This article provides an overview of creatine supplementation, particularly in the context focusing on its safety, benefits, dosage, considerations young individuals. Research has that supplementation may provide additional benefits including enhanced post-exercise recovery,...

Developing a predictive model for detecting Coronary Artery Disease (CAD) is crucial due to its high global fatality rate of approximately 17.9 million people annually. With the advancements in artificial intelligence, availability large-scale data, and increased access computational capability, it feasible create robust models that can detect CAD with precision. This study aims build assist health workers timely detection ultimately reduce mortality. performs comparative analysis four...

Summary Resin canals produce and transport oleoresins that are important for tree defenses within the Pinaceae family. Rapid measurement techniques needed to better understand how resin canal characteristics vary due genetic environmental effects. Here we describe a semi-automated microscopy imaging system was built quantifying longitudinal canals. Tree increment cores from 210 loblolly pine ( Pinus taeda L.) trees were prepared into radial strips transverse surface of samples polished with...

A software vulnerability is defined as a flaw that exists in computer resources or control can be exploited by one more threats. Vulnerabilities are discovered throughout the entire life cycle of software. In this paper, we examine existing models on subject area and propose new time-based differential equation model. Our proposed model based assumption saturation local phenomenon, possesses an increasing cyclic behaviour within cycle. Daily data extracted from National Vulnerability...