Search results for "MAC"
showing 10 items of 24950 documents
Analysis of MAC-level throughput in LTE systems with link rate adaptation and HARQ protocols
2015
LTE is rapidly gaining momentum for building future 4G cellular systems, and real operational networks are under deployment worldwide. To achieve high throughput performance, in addition to an advanced physical layer design LTE exploits a combination of sophisticated mechanisms at the radio resource management layer. Clearly, this makes difficult to develop analytical tools to accurately assess and optimise the user perceived throughput under realistic channel assumptions. Thus, most existing studies focus only on link-layer throughput or consider individual mechanisms in isolation. The main contribution of this paper is a unified modelling framework of the MAC-level downlink throughput of …
IAEA Contribution to Nanosized Targeted Radiopharmaceuticals for Drug Delivery.
2022
The rapidly growing interest in the application of nanoscience in the future design of radiopharmaceuticals and the development of nanosized radiopharmaceuticals in the late 2000′s, resulted in the creation of a Coordinated Research Project (CRP) by the International Atomic Energy Agency (IAEA) in 2014. This CRP entitled ‘Nanosized delivery systems for radiopharmaceuticals’ involved a team of expert scientist from various member states. This team of scientists worked on a number of cutting-edge areas of nanoscience with a focus on developing well-defined, highly effective and site-specific delivery systems of radiopharmaceuticals. Specifically, focus areas of various teams of scientists com…
Radiolabeling of Nanoparticles and Polymers for PET Imaging
2014
Nanomedicine has become an emerging field in imaging and therapy of malignancies. Nanodimensional drug delivery systems have already been used in the clinic, as carriers for sensitive chemotherapeutics or highly toxic substances. In addition, those nanodimensional structures are further able to carry and deliver radionuclides. In the development process, non-invasive imaging by means of positron emission tomography (PET) represents an ideal tool for investigations of pharmacological profiles and to find the optimal nanodimensional architecture of the aimed-at drug delivery system. Furthermore, in a personalized therapy approach, molecular imaging modalities are essential for patient screeni…
Radiomics Analysis of Brain [18F]FDG PET/CT to Predict Alzheimer’s Disease in Patients with Amyloid PET Positivity: A Preliminary Report on the Appli…
2022
Background: Early in-vivo diagnosis of Alzheimer’s disease (AD) is crucial for accurate management of patients, in particular, to select subjects with mild cognitive impairment (MCI) that may evolve into AD, and to define other types of MCI non-AD patients. The application of artificial intelligence to functional brain [18F]fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography(CT) aiming to increase diagnostic accuracy in the diagnosis of AD is still undetermined. In this field, we propose a radiomics analysis on advanced imaging segmentation method Statistical Parametric Mapping (SPM)-based completed with a Machine-Learning (ML) application to predict the diagnosi…
Economic policy uncertainty effects for forecasting future real economic activity
2018
Recently introduced measures for Economic Policy Uncertainty (EPU) included in the data from 1997 - 2016 have a role in forecasting out-of-sample values for the future real economic activity for both the euro area and the UK economies. The inclusion of EPU measures, either for the US, the UK or for overall European economies, improves the forecasting ability of models based on standard financial market information, especially for the period before the 2008 global crisis. However, during and after the crisis period, the slope of the yield curve and excess stock market returns improves the out-of-sample forecast performance the most compared to an AR-benchmark model. Hence, the EPU informatio…
Finland’s great depression of the 1990s: Lessons about financial reform based on econometric macro evidence
2020
The paper re‐examines the Finnish Great Depression of the 1990s, based on an open macro model, with specific dummy variables to identify the initial effects of liberalized financial markets and capital mobility, and of the Russian trade collapse. It is shown that the explosive credit expansion resulting from the simultaneous liberalization of the financial markets and international capital movements in 1986 has played the most important role in explaining the uncontrolled growth and the subsequent depression in 1989 in real economic activity in Finland. Their effects were strengthened by a vicious circle between the financial and asset markets. The Russian trade collapse in 1991 had a small…
Biological and Mechanical Characterization of the Random Positioning Machine (RPM) for Microgravity Simulations
2021
The rapid improvement of space technologies is leading to the continuous increase of space missions that will soon bring humans back to the Moon and, in the coming future, toward longer interplanetary missions such as the one to Mars. The idea of living in space is charming and fascinating; however, the space environment is a harsh place to host human life and exposes the crew to many physical challenges. The absence of gravity experienced in space affects many aspects of human biology and can be reproduced in vitro with the help of microgravity simulators. Simulated microgravity (s-μg) is applied in many fields of research, ranging from cell biology to physics, including cancer biology. In…
Improvements and applications of the elements of prototype-based clustering
2018
Clustering or cluster analysis is an essential part of data mining, machine learning, and pattern recognition. The most popularly applied clustering methods are partitioning-based or prototype-based methods. Prototype-based clustering methods usually have easy implementability and good scalability. These methods, such as K-means clustering, have been used for different applications in various fields. On the other hand, prototype-based clustering methods are typically sensitive to initialization, and the selection of the number of clusters for knowledge discovery purposes is not straightforward. In the era of big data, in high-velocity, ever-growing datasets, which can also be erroneous, outl…
The manipulation of Euribor: An analysis with machine learning classification techniques
2022
The manipulation of the Euro Interbank Offered Rate (Euribor) was an affair which had a great impact on in ternational financial markets. This study tests whether advanced data processing techniques are capable of classifying Euribor panel banks as either manipulating or non-manipulating on the basis of patterns found in quotes submissions. For this purpose, panel banks’ daily contributions have been studied and monthly variables obtained that denote different contribution patterns for Euribor panel banks. Thus, in accordance with the court verdict, banks are categorized as manipulating and non-manipulating and Machine Learning classification techniques such as Supervised Learning, Anomaly …
Organizational Change - A Remedly Prescribed in Over-dose?
2006
People in general want improvements, but rarely radical changes. To overcome this conservatism among employees, managers are often overselling change. During a long time there has been a frenetic enthusiasm for managers to become leaders with ‘transformational’ and charismatic capabilities. To do things right has been less important than doing the right thing. This article questions this prophetic capability of managers and also the value of change. As a phenomenon in modern society, and in modern companies change is often overestimated and overvalued. What happened to the new economy? Maybe time has come to question the leader and appreciate the manager?