Search results for: Nikos Moustakidis

Authors: George Leventakis, George Kokkinis, Nikos Moustakidis, George Papalexandratos, Ioanna Vasiliadou

Abstract:

Enhancing the feeling of public safety and crime prevention are tasks customarily assigned to the Police. Police departments have, however, recognized that traditional ways of policing methods are becoming obsolete; Community Policing (CP) philosophy; however, when applied appropriately, leads to seamless collaboration between various stakeholders like the Police, NGOs and the general public and provides the opportunity to identify risks, assist in solving problems of crime, disorder, safety and crucially contribute to improving the quality of life for everyone in a community. Social Media, on the other hand, due to its high level of infiltration in modern life, constitutes a powerful mechanism which offers additional and direct communication channels to reach individuals or communities. These channels can be utilized to improve the citizens’ perception of the Police and to capture individual and community needs, when their feedback is taken into account by Law Enforcement Agencies (LEAs) in a structured and coordinated manner. This paper presents research conducted under INSPEC²T (Inspiring CitizeNS Participation for Enhanced Community PoliCing AcTions), a project funded by the European Commission’s research agenda to bridge the gap between CP as a philosophy and as an organizational strategy, capitalizing on the use of Social Media. The project aims to increase transparency, trust, police accountability, and the role of civil society. It aspires to build strong, trusting relationships between LEAs and the public, supporting two-way, contemporary communication while at the same time respecting anonymity of all affected parties. Results presented herein summarize the outcomes of four online multilingual surveys, focus group interviews, desktop research and interviews with experts in the field of CP practices. The above research activities were conducted in various EU countries aiming to capture requirements of end users from diverse backgrounds (social, cultural, legal and ethical) and determine public expectations regarding CP, community safety and crime prevention.

Keywords: Community partnerships, next generation community policing, public safety, social media.

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Authors: Ioannis Neokosmidis, Nikos Gkekas, Thomas Kamalakis, Thomas Sphicopoulos

Abstract:

In high powered dense wavelength division multiplexed (WDM) systems with low chromatic dispersion, four-wave mixing (FWM) can prove to be a major source of noise. The MultiCanonical Monte Carlo Method (MCMC) and the Split Step Fourier Method (SSFM) are combined to accurately evaluate the probability density function of the decision variable of a receiver, limited by FWM. The combination of the two methods leads to more accurate results, and offers the possibility of adding other optical noises such as the Amplified Spontaneous Emission (ASE) noise.

Keywords: Monte Carlo, Nonlinear optics, optical crosstalk, Wavelength-division Multiplexing (WDM).

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Authors: George D. Hatzigeorgiou, Nikos G. Pnevmatikos

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This study examines the inelastic behavior of adjacent planar reinforced concrete (R.C.) frames subjected to strong ground motions. The investigation focuses on the effects of vertical ground motion on the seismic pounding. The examined structures are modeled and analyzed by RUAUMOKO dynamic nonlinear analysis program using reliable hysteretic models for both structural members and contact elements. It is found that the vertical ground motion mildly affects the seismic response of adjacent buildings subjected to structural pounding and, for this reason, it can be ignored from the displacement and interstorey drifts assessment. However, the structural damage is moderately affected by the vertical component of earthquakes.

Keywords: Nonlinear seismic behavior, reinforced concrete structures, structural pounding, vertical ground motions.

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Authors: Nikolaos Sariannidis, Grigoris Giannarakis, Nikolaos Litinas, Nikos Kartalis

Abstract:

This study investigates the relationship between 10 year bond value, Yen/U.S dollar exchange rate, non-farm payrolls (all employs) and crude oil to U.S. Dow Jones Sustainability Index. A GARCH model is used to test these relationships for the period January 1st 1999 to January 31st 2008 using monthly data. Results show that an increase of the 10 year bond and non farm payrolls (all employs) lead to an increase of the D.J.S.I returns. On the contrary the volatility of the Yen/U.S dollar exchange rates as well as the increase of crude oil returns has negative effects on the U.S D.J.S.I returns. This study aims at assisting investors to understand the influences certain macroeconomic indicators have on the companies- stock returns as reported by the D.J.S.I.

Keywords: Bond value, Corporate Social Responsibility, Crudeoil, D.J.S.I United States, Exchange rate, GARCH, Non-farmpayrolls.

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Authors: Ioannis Andrianakis, Vasileios Gkatas, Nikos Eleftheriadis, Alexios Ellinidis, Ermioni Avramidou

Abstract:

The paper discusses the main aspects involved in the development of a supply chain management system using the developed PredictionSCMS software as a basis for the discussion. The discussion is focused on three topics: the first is demand forecasting, where we present the predictive algorithms implemented and discuss related concepts such as the calculation of the safety stock, the effect of out-of-stock days etc. The second topic concerns the design of a supply chain, where the core parameters involved in the process are given, together with a methodology of incorporating these parameters in a meaningful order creation strategy. Finally, the paper discusses some critical events that can happen during the operation of a supply chain management system and how the developed software notifies the end user about their occurrence.

Keywords: Demand forecasting, machine learning, risk management, supply chain design.

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Authors: Hazem M. El-Bakry, Nikos Mastorakis

Abstract:

Fast forecasting of stock market prices is very important for strategic planning. In this paper, a new approach for fast forecasting of stock market prices is presented. Such algorithm uses new high speed time delay neural networks (HSTDNNs). The operation of these networks relies on performing cross correlation in the frequency domain between the input data and the input weights of neural networks. It is proved mathematically and practically that the number of computation steps required for the presented HSTDNNs is less than that needed by traditional time delay neural networks (TTDNNs). Simulation results using MATLAB confirm the theoretical computations.

Keywords: Fast Forecasting, Stock Market Prices, Time Delay NeuralNetworks, Cross Correlation, Frequency Domain.

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Authors: Aikaterini Fountoulaki, Nikos Karacapilidis, Manolis Manatakis

Abstract:

This paper proposes an innovative methodology for Acceptance Sampling by Variables, which is a particular category of Statistical Quality Control dealing with the assurance of products quality. Our contribution lies in the exploitation of machine learning techniques to address the complexity and remedy the drawbacks of existing approaches. More specifically, the proposed methodology exploits Artificial Neural Networks (ANNs) to aid decision making about the acceptance or rejection of an inspected sample. For any type of inspection, ANNs are trained by data from corresponding tables of a standard-s sampling plan schemes. Once trained, ANNs can give closed-form solutions for any acceptance quality level and sample size, thus leading to an automation of the reading of the sampling plan tables, without any need of compromise with the values of the specific standard chosen each time. The proposed methodology provides enough flexibility to quality control engineers during the inspection of their samples, allowing the consideration of specific needs, while it also reduces the time and the cost required for these inspections. Its applicability and advantages are demonstrated through two numerical examples.

Keywords: Acceptance Sampling, Neural Networks, Statistical Quality Control.

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Authors: Panagiotis Lemonakis, Theodoros Αlimonakis, George Kaliabetsos, Nikos Eliou

Abstract:

It is very well known that certain vertical and longitudinal slopes have to be assured in order to achieve adequate rainwater runoff from the pavement. The selection of longitudinal slopes, between the turning points of the vertical curves that meet the afore-mentioned requirement does not ensure adequate drainage because the same condition must also be applied at the transition curves. In this way none of the pavement edges’ slopes (as well as any other spot that lie on the pavement) will be opposite to the longitudinal slope of the rotation axis. Horizontal and vertical alignment must be properly combined in order to form a road which resultant slope does not take small values and hence, checks must be performed in every cross section and every chainage of the road. The present research investigates the rain water runoff from the road surface in order to identify the conditions under which, areas of inadequate drainage are being created, to analyze the rainwater behavior in such areas, to provide design examples of good and bad drainage zones and to track down certain motorcycle types which might encounter hazardous situations due to the presence of water film between the pavement and both of their tires resulting loss of traction. Moreover, it investigates the combination of longitudinal and cross slope values in critical pavement areas. It should be pointed out that the drainage gradient is analytically calculated for the whole road width and not just for an oblique slope per chainage (combination of longitudinal grade and cross slope). Lastly, various combinations of horizontal and vertical design are presented, indicating the crucial zones of bad pavement drainage. The key conclusion of the study is that any type of motorcycle will travel for some time inside the area of improper runoff for a certain time frame which depends on the speed and the trajectory that the rider chooses along the transition curve. Taking into account that on this section the rider will have to lean his motorcycle and hence reduce the contact area of his tire with the pavement it is apparent that any variations on the friction value due to the presence of a water film may lead to serious problems regarding his safety. The water runoff from the road pavement is improved when between reverse longitudinal slopes, crest instead of sag curve is chosen and particularly when its edges coincide with the edges of the horizontal curve. Lastly, the results of the investigation have shown that the variation of the longitudinal slope involves the vertical shift of the center of the poor water runoff area. The magnitude of this area increases as the length of the transition curve increases.

Keywords: Drainage, motorcycle safety, superelevation, transition curves, vertical grade.

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