Research ArticleOpen accessIn the author namesStock Market Development and Economic GrowthAthanasios Vazakidis, Antonios AdamopoulosProblem statement: This study investigated the causal relationship between stock market development and economic growth for France for the period 1965-2007 using a Vector Error Correction Model (VECM). Questions were raised whether stock market development causes economic growth or reversely taking into account the negative effect of interest rate. Stock market development is estimated by the general stock market index. … …American Journal of Applied Sciences, Vol. 6, Issue 11 · 30 Nov 2009 · 8,361 accessesView PDFCite
Research ArticleOpen accessIn the author namesFinancial Development and Economic Growth An Empirical Analysis for GreeceAthanasios Vazakidis, Antonios AdamopoulosProblem statement: This study investigated the causal relationship between financial development and economic growth for Greece for the period 1978-2007 using a Vector Error Correction Model (VECM). Questions were raised whether financial development causes economic growth or reversely taking into account the positive effect of industrial production index. Financial market development is estimated by the effect of credit market development … …American Journal of Applied Sciences, Vol. 6, Issue 7 · 31 Jul 2009 · 7,749 accessesView PDFCite
Research ArticleOpen accessIn the author namesCredit Market Development and Economic GrowthAthanasios Vazakidis, Antonios AdamopoulosProblem statement: This study investigated the relationship between credit market development and economic growth for Italy for the period 1965-2007 using a Vector Error Correction Model (VECM). Questions were raised whether economic growth spurs credit market development taking into account the negative effect of inflation rate on credit market development. This study aimed to investigate the short-run and the long-run … …American Journal of Economics and Business Administration, Vol. 1, Issue 1 · 31 Mar 2009 · 8,402 accessesView PDFCite
Research ArticleOpen accessIn the author namesConstruction of an Integrated Object Oriented System for Temporal GISSouheil Khaddaj, Abdul Adamu, Munir MoradThe development of temporal GIS systems capable of dealing with the evolution of geographical objects is still a challenging task. Although many successful GIS systems have been implemented, comparatively little has been done on how to determine and analyze the patterns of continuous changes of geographical objects. The aim of this paper is to construct a GIS system using an … …American Journal of Applied Sciences, Vol. 2, Issue 12 · 31 Dec 2005 · 6,727 accessesView PDFCite
Research ArticleOpen accessIn the author namesA Causal Relationship and Macroeconomic Activity: Empirical Results From European UnionChaido Dritsaki, Antonios AdamopoulosThis study investigates the relationship among macroeconomic variables using quarterly data for European Union covering the period from 1970 I to 2000 IV. The purpose of this study is to estimate the dynamic interrelation among macroeconomic variables such as money, gross domestic product, interest rates, level of price and exchange rates. For the empirical analysis of this investigation, we employ … …American Journal of Applied Sciences, Vol. 2, Issue 2 · 28 Feb 2005 · 7,854 accessesView PDFCite
Research ArticleOpen accessIn the author namesA Causal Relationship between Trade, Foreign Direct Investment and Economic Growth in GreeceMelina Dritsaki, Chaido Dritsaki, Antonios AdamopoulosThis study investigates the relationship between Trade, Foreign Direct Investment (FDI) and economic growth in Greece over the period 1960-2002. The cointegration analysis suggested that there is a long-run equilibrium relationship. The results of the Granger causality test showed that there is a causal relationship between the examined variables. Economic growth, trade and FDI appear to be mutually reinforcing under … …American Journal of Applied Sciences, Vol. 1, Issue 3 · 30 Sep 2004 · 9,630 accessesView PDFCite
Research ArticleOpen accessIn the abstractMorphological Database and Quantification of Liberica Coffee Beans Using a Hybrid CNN ModelDioneces O. Alimoren, Francis G. Balazon, Jonnah R. Melo et al.Traditional evaluation of Liberica coffee (Kapeng Barako) in Batangas is commonly performed through manual visual inspection and sensory judgment, which are slow, subjective, and difficult to reproduce across farms, buyers, and grading personnel. These limitations can lead to inconsistent quality classification, weak traceability, and reduced bargaining power for local producers. This study develops and validates a web-based morphological analysis system … …Journal of Computer Science, Vol. 22, Issue 8 · 24 Aug 2026 · 1,337 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnimal Health Prediction Using Hybrid CNN Based BiLSTM Classification Model: A Deep Learning ApproachJ. Rathi, A. SumathiAccurate prediction of animal diseases is vital in veterinary medicine, as it can substantially enhance animal health outcomes and mitigate economic losses, making it a critical task that warrants attention and innovative solutions. This paper proposes a novel approach to animal condition classification, leveraging an Auto-encoder-based feature selection process and an Improved Hybrid Convolutional Neural Networks (CNN) with Bidirectional (Bi-LSTM) … …Journal of Computer Science, Vol. 22, Issue 5 · 20 May 2026 · 1,481 accessesView PDFCite
Research ArticleOpen accessIn the abstractIoT-Integrated CNN Deep Learning for Automated Breast Cancer Detection and DiagnosisYamini Kalva, R. Ganesh Babu, Sindhu V. et al.Breast cancer continues to be a primary cause of death in women, requiring prompt and accurate diagnosis to enhance treatment results. Traditional diagnostic techniques depend on manual assessment, which leads to possible misclassification, significant inter-observer variability, and delays in decision-making. Current deep learning models, including CNNs, frequently experience feature loss, gradient declining and restricted adaptability to real-time data. To overcome … …Journal of Computer Science, Vol. 22, Issue 4 · 30 Mar 2026 · 1,753 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Dam Safety and Management: Long Short-Term Memory Based Predictive Models for Accurate Alert ForecastingNisha C. M, N. ThangarasuDam management and early alert systems are critical for effective water resource management. Accurate prediction of dam alert signals facilitates proactive decision-making, thereby aiding in the effective management and reduction of potential risks linked to dam operations. Within this research, Long Short-Term Memory (LSTM) networks are utilized to forecast dam alert signals issued from the dam by leveraging daily parameters, … …Journal of Computer Science, Vol. 22, Issue 1 · 6 Feb 2026 · 1,626 accessesView PDFCite