Examining sustainability performance in the supply chain: The case of the Greek dairy sector

This is the post-print version of the final paper published in Industrial Marketing Management. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.This paper evaluates the sustainability performance of the Greek dairy chain and the performance of its individual members by using key indicators in relation to efficiency, flexibility, responsiveness and product quality. We assessed the importance of these indicators based on the relevant perceptions of key members of this chain. A structured questionnaire was developed where nineteen sustainability-related issues were examined. Two hundred and fifty three members of the Greek dairy supply chain responded including breeders, manufacturers, wholesalers, retailers and catering companies. Our findings illustrate the immediate need for improvement in many key sustainability performance indicators. They also show the critical role of large dairy manufacturers who are the “sustainability performance champions” in this chain and are the driving force for the implementation of many sustainability initiatives.European Unio

Using A One-Class Compound Classifier To Detect In-Vehicle Network Attacks

The Controller Area Network (CAN) in vehicles provides serial communication between electronic control units that manage en- gine, transmission, steering and braking. Researchers have recently demonstrated the vulnerability of the network to cyber-attacks which can manipulate the operation of the vehicle and compromise its safety. Some proposals for CAN intrusion detection systems, that identify attacks by detecting packet anomalies, have drawn on one-class classi cation, whereby the system builds a decision surface based on a large number of normal instances. The one-class approach is discussed in this paper, together with initial results and observations from implementing a classi er new to this eld. The Compound Classier has been used in image processing and medical analysis, and holds advantages that could be relevant to CAN intrusion detection.<br/

Sport fans' roles in value co-creation

Research question The sports industry has witnessed sustained growth. The cultural, symbolic and stakeholder-embedded nature of sport provides a dynamic setting for developing service research. In this context, an evolution in the logic of value creation can be observed; fans are no longer passive receivers of value but, instead, can be active value co-creators. The sport fan exhibits distinctive characteristics and an ability and willingness to integrate resources and co-produce value propositions, which necessitates an understanding of fan value co-creation. We answer one key research question: what is the role of fans in value co-creation in sports? We do so by conceptually exploring the processes through which sport fans co-create and provide value propositions. Research methods We use case exemplars to provide a base for the theoretical consideration of the role of sport fans in value co-creation. We verify and consolidate the service-dominant logic (SDL) in the sport context. However, due to the high level of abstraction of the SDL as a general theory, we utilize consumer culture theory (CCT) as a middle range theory (MRT) to bridge the gap between contextual descriptions of the role of fans and the SDL. Results and findings Fans evaluate, redefine and reposition value propositions in different sport settings. The three roles of assimilators, adaptors and authenticators in value co-creation are identified through five case exemplars. We extend the theoretical understanding of the processes through which sport fans co-create value. Implications Knowledge of the distinctive characteristics of sport fans and their roles in value co-creation will assist managers in developing effective marketing propositions. Our theoretical contribution will generate new lines of research in the field

Optimization and prediction of dielectric behavior of small air gaps stressed by DC voltages

The present paper aims to the investigation of the methods used to optimize and predict via simulation the values of the Corona onset voltage, the Corona current and the Breakdown voltage in small rod-plate air gaps when stressed by dc voltage. The main factors which influence greatly the distribution of the electric field in the gap, and hence the above values are the geometry and the selection of grounding and charging of the electrodes, (ground effect), the polarity effect, the gap length, and the Corona effects appearing prior to breakdown. Combining theoretical, simulation and experimental work, it is resulted that: a) The electrode chosen to be ground, strongly influences the distribution of the field and the Corona effects and hence the values of the Corona onset, the Corona current and breakdown voltage. b) Minimum values of the Corona onset voltage and maximum values of the Corona current and the breakdown voltage were defined in relation to the geometry of the gap and in connection to the effects of grounding, polarity and Corona current. c) It is proven that it can be predicted by means of simulation analysis whether an air gap will lead to Corona or breakdown, and it can also be predicted which specific arrangement of a rod-plate air gap must be chosen in order to maximize the Corona current when a voltage of a certain value is applied. © 2014 IEEE

Control and optimization of the Corona effects and breakdown of small rod-plate air gaps stressed by dc and impulse voltages

In the present paper methods of controlling Corona and breakdown in small rod-plate air gaps are investigated. Combining experimental and simulation-theoretical work, it is resulted that when the rod's diameter is bigger, the gap length larger and the rod is grounded the field is less inhomogeneous. Therefore the value of the dc breakdown voltage without Corona is higher. If Corona occurs then the values of the Corona onset voltage are higher, and the corona effects are not intense. The Corona effects, lead to a rise of the value of the dc breakdown voltage especially when the rod is negatively charged. Moreover an insulated thin barrier, when positioned near the rod increases the breakdown dc voltage to a maximum value, and minimizes the Corona effects. Especially for gaps stressed by impulse voltage the Corona effects, appearing with the form of electric current pulses, are influenced by the same factors with a different way. The values of the breakdown voltage in contrast to what happens with dc voltage are higher when the Corona effects are weaker, depending on the influence of the field's inhomogenity (geometry and effect of grounding). It is also resulted that a resistor connected in series with the gap decreases its maximum charging voltage and increases the value of the breakdown voltage. © 2013 IEEE

Assessment of Machine Learning Techniques for Building an Efficient IDS

Intrusion Detection Systems (IDS) are the systems that detect and block any potential threats (e.g. DDoS attacks) in the network. In this project, we explore the performance of several machine learning techniques when used as parts of an IDS. We experiment with the CICIDS2017 dataset, one of the biggest and most complete IDS datasets in terms of having a realistic background traffic and incorporating a variety of cyber attacks. The techniques we present are applicable to any IDS dataset and can be used as a basis for deploying a real time IDS in complex environments. © 2020 IEEE

Stochastic optimization of electric vehicle charging stations

With range anxiety becoming the every day problem for Battery Electric Vehicles (BEVs) owners, even more research is being conducted in the field of BEV charging and Charging Stations (CSs) scheduling optimization. In this context our work addresses the problem of BEV charging in an urban environment with no a-priori knowledge of vehicle arrivals. Our system is modeled as a M/G/K queuing system. Two adaptive charging algorithms are proposed, both of them relying on queue stability. The first one charges BEVs up to a percentage of their maximum capacity when charging queues become unstable. The second one when detects instability charges BEVs sufficiently enough to reach their next destination. Both algorithms can be used in combination with an admission control algorithm that does not allow BEVs that do not fulfill certain criteria into the charging stations. The First-Come-First-Serve (FCFS) algorithm is directly compared to our proposed algorithms, with prominent improvement concerning congestion in charging stations and waiting time of electric vehicles. © 2019 IEEE