1,725,405 research outputs found
Ahmed Ali Iyaye
No full textCredit management is one of the most important activities in any company and cannot be overlooked by any economic enterprise engaged in credit irrespective of its business nature. Sound credit management is a prerequisite for a financial institution’s stability and continuing profitability, while deteriorating credit quality is the most frequent cause of poor financial performance and condition. As with any financial institution, the biggest risk in microfinance is lending money and not getting it back
Recommended from our members
Photograph of Nasima Ali, Sadaf Munshi and Ahmed Ali Shah
No full textPhotograph of Nasima Ali (left), Sadaf Munshi (center) and Ahmed Ali Shah, a Nagar Burushaski speaker (right)
Les implications juridiques du principe de l'avantage comparatif dynamique
No full textKhavand Ahmed Ali. Les implications juridiques du principe de l'avantage comparatif dynamique. In: Tiers-Monde, tome 27, n°105, 1986. pp. 61-75
PROCESO DE PINTADO DE VEHICULOS.
No full textJalloul Ahmed, Ali; director de proyecto: Monedero Buso, Germán2022-2023Curso de Formación Pedagógica y Didáctica para Profesorado de Formación Profesional y DeportivaFacultad de Ciencias de la Educació
Il Self Help nel campo dell'abitazione : teorie e opposizioni interpretative : con uno studio di caso sul settore abitativo informale ad Erbil-Kurdistan iracheno
No full textPredicting epileptic seizures from Electroencephalography
No full textEpilepsy is a neurological disorder that is characterised by repeated seizures. The sudden onset of a seizure affects a patient’s quality of life. Therefore, predicting an epileptic seizure in advance can improve their life by giving them warning and thus avoiding serious accidents. In this work, two general prediction models are formulated using the electroencephalography (EEG) signals of patients with Temporal Lobe Epilepsy (TLE) and Absence seizures. EEG is the most common technique to map brain functions. Studying brain functions and how the brain regions interact is essential to understand the basis of several neurodegenerative diseases. Functional brain connectivity, as derived from multichannel EEG, is currently used as a tool to understand how the various brain regions interact with each other during a cognitive task. Researchers started to study the functional brain network by analysing the EEG data captured. Because of the high level of synchronization observed during a seizure, synchronization measures are logically the best way to assess the dynamic change in functional brain connectivity. In the current work, Phase Locking Value (PLV), Phase Lag Index (PLI) and Synchronization likelihood (SL) were used to create functional brain connectivity networks. The networks were characterized by nine graph-theoretic parameters (assortativity coefficient, transitivity, clustering coefficient, strength of node, modularity, betweenness centrality, characteristic path length, global efficiency and radius). A machine-learning framework was used to extract the patterns that the patients’ data had in common to build the prediction models. Both general prediction models were formulated using PLI and SL connectivity networks. They achieved sensitivity (both 100%) and a false prediction rate of 0.00001/h and 0.01/h, with a maximum prediction time of 19 and 40 minutes, respectively
Bird's-eye Perspective of the Historic Core of Hyderabad Viewed from the North
No full textfull view, including Gulzar Haus in the central square and the Mecca Masjid on the far left
- …
