Konstantinos Kokkinos

An Integrated Modeling Framework for Routing of Hazardous Materials

We deal with the problem of vehicle routing optimization in the case of transportation of Hazardous Materials (HazMats). This paper introduces a collaborative approach for the HazMat Vehicle Routing Problem (HVRP) by integrating the element of transportation frequencies (as a macro variable) in order to create routing schemes that minimize the overall Cost and Risk factors. This work incorporates several risk and cost models into an innovative software framework which can simulate various decision making scenarios for dynamically formed road networks and can be used by the competent authorities. We include in the objective function under optimization the variance of road usage as an additional parameter to be minimized and we argue on its importance to accommodate traffic balancing on the networks under study. Experimental results verify that our approach outperforms well known methodologies for the case of risk optimization and equally competes for the case of cost optimization.

Daily multivariate forecasting of water demand in a touristic island with the use of artificial neural network and adaptive neuro-fuzzy inference system

Water demand forecast has emerged as an imperative component of intelligent Internet and Communication Technologies based methodologies of water management. The need of increased time resolution of forecast in order to implement such methodologies is driving stakeholders to long for new more specialized forecast approaches that will take into account the special drivers of water demand in each case study. Advanced techniques have the ability to overcome the nonlinearity issues commonly met when investigating the complex relationship of water demand and weather, socioeconomic and other variables. In this article we present two approaches, an Artificial Neural Network and an Adaptive Neuro-Fuzzy Inference System, for forecasting a Mediterranean touristic resort daily water demand based on weather variables, tourism and leakage. Both models seem to have an adequate response, though ANFIS can more smoothly catch winter non-touristic water demand profile.

Soft Computing Approaches for Urban Water Demand Forecasting

This paper presents an integrated framework for water resources management at urban level which consists of a Neuro-Fuzzy and Fuzzy Cognitive Map-based, (FCM) decision support system (DSS) based on multiple objectives and multiple disciplines for planning and forecasting. The proposed DSS has as primary goals to: (a) adaptively control the water pressure of the water distribution system by forecasting the water demand at the urban level and (b) to reduce leakage of the water network by controlling the water pressure. The system follows a model-driven architecture with the inclusion of the FCM-based models and a spatio-temporal model for arranging all data. The validation of the proposed learning algorithms is made for two case studies that comprise different water supply characteristics and correspond to different locations in Europe.

Fuzzy Sets in Agriculture

Agricultural modeling and management are complex conceptual processes, where a large number of variables are taken into consideration and interact for system analysis and decision making. Most of the processes in the agricultural sector include the uncertainty, ambiguity, incomplete information and human intuition characteristics. These processes are not only constrained by their environment (e.g., market, climate, seasons, consumer choices), but they are also highly influenced by human factors (stakeholders’ perceptions). Fuzzy sets are able to manage and represent uncertainty, assure that the incomplete information is valued and provide solutions to issues which are crucial in agriculture like fertilization, land degradation, soil erosion and climate variability during planting material selection in physiological analysis. Fuzzy sets have gained constantly increasing research interest in the last twenty years and have found great applicability in the agricultural domain, helping farmers to take right decisions for their cultivated.

A Collaborative Approach to Enviromental Modeling

Integrated Environmental Modeling Systems, (IEMS) are multidisciplinary systems which focus on complex environmental problems, decisions and policies. They are characterized by formulating dynamic and interdependent environmental, hydrological, climatological and sometimes socio-economical models under a unified framework that seeks to bridge the modeling, the monitoring and the decision making processes. The main concern of such systems is how to resolve various data and computational outcome inconsistencies emanated from the high computational burden, the lack of model interoperability and the model conceptualization characteristics. In this paper, we introduce an integrated modeling system that evaluates the hydrological, environmental ecosystem and socio-economic dynamics in lakes or wetland watersheds. Apart from the architectural design paradigm and the case study for the Lake Karla in Thessaly, Greece provided here, we also illustrate a roadmap for methodological planning, implementing, monitoring and managing such systems. Finally we provide the necessary steps of an environmentally related assessment process for such systems, however future research is needed to evaluate computational performance of this loosely coupled approach.

Collaborative Migration, Coupling and Simulation of Water Resources Models through OpenMI

The present study describes the migration and coupling of a monthly conceptual rainfall runoff model named UTHBAL and a water reservoir operation model called UTHRL into the OpenMI standard. The models have been introduced by Loukas et al. [1, 2]. We have developed a collaborative decision support framework named UTH-MODELER which automates the migration of the two models into OpenMI. This framework synchronizes spatially and temporarily the two models into a collaborative simultaneous simulation. The produced software allows time series input in various formats and model extensibility. Furthermore, an optimization library for the calibration of the models has been incorporated. The experimental verification of the coupled system has been tested for the case study of the reservoir of the restored Lake Karla in Thessally Greece. The results show that the collaboration process is bounded by the time, space and optimization characteristics of the coupled models.

Fuzzy Cognitive Map-Based Modeling of Social Acceptance to Overcome Uncertainties in Establishing Waste Biorefinery Facilities

Sustainable Waste Biorefinery Facilities (WBFs) represent multifactorial systems that necessitate the organization, cooperation and the acceptance of different social stakeholders. However, these attempts have become targets of environmental, social and legal oppositions despite their obvious economic benefits. The variety of ambivalent and heterogeneous external effects of such projects result in either local support or opposition to the facility, which in turn becomes a critical factor affecting facility location decisions, and subsequent success of a WBF. Research has shown that simple surveys do not sufficiently measure social acceptance of such endeavours, and in most cases, local community factors dominate other external valuable impacts. In the current study, a novel Fuzzy Cognitive Map (FCM) modeling approach is proposed in order to analyze the socio-economic implications and to overcome multiple uncertainties occurring in sustainable WBF development and implementation. The primary investigation relates to the factors that influence the development of organic or chemical treatment of waste by the local communities and the competent authorities. The determination of concepts involved in the FCM modeling depends on a hybrid approach where both experts’ opinion and statistical results from questionnaires distributed to stakeholders participate in the concept circumscription, thus identifying the centrality of each node in the model. Several steady state and dynamic analysis scenarios show the influence of driver concepts to receiver concepts on the social aspect FCM constructed.

Efficiency in Energy Decision Support Systems Using Soft Computing Techniques

In the recent years, the advent of globalization has caused a steep rise in energy consumption especially for the most developed countries. At the same time, there is an important need for energy planning especially from the energy distributors’ point of view as, it is vital for setting energy wholesale prices and profit margins. The same argument also holds for the case of energy transition from fossil fuels to more environmentally friendly forms since, it is necessary to predict future energy demands in order to achieve sustainability by balancing energy supply and demand. Even though a lot of research has been produced towards the development of energy models that try to optimize sustainability, we claim that, there is a need for multi-criteria Decision Support Systems, (DSS) that integrate a variety of econometric and computational intelligence methodologies in order to evaluate the impacts of a mix of sometimes conflicting factors such as climatological conditions, global prices, availability etc. In this paper, we propose an integrated DSS that involves Adaptive Neuro Fuzzy Systems (ANFIS), Neural Networks, (NN) and Fuzzy Cognitive Maps, (FCM) along with Econometric Models, (EM) in a hybrid fashion to predict energy consumption and prices. Such a system defines the basic structure in building energy networks that use combined heat and power. Even though the system can be applied for the totality of energy sources, we focus only on the prediction methodologies for the natural gas consumption for the country level. We provide a comparative analysis of the aforementioned methods by obtaining the MSA, RMSE, MAE and MAPE errors, as well as R2 metric.

DEVELOPMENT AND EVALUATION OF AN ADAPTIVE NEURO FUZZY INFERENCE SYSTEM FOR THE CALCULATION OF SOIL WATER RECHARGE IN A WATERSHED

Domestic violence in itself is one of the most difficult, specific and wide-spread social-legal problems containing the number of signs of violation. Conflict directly concerns people connected with coexistence; it has the local, exclusive character and the fight against it is less effective in accordance with common practice of fight against the crime. Specificity of the fight against the crime of this category is expressed in both complexity of its revealing and in effective and lawful choice of coercive measures against it. The issue of domestic violence has been tabooed in many countries for a long time, because the disclosure of such issues was considered as interference in people’s private life. Although the society has gradually realized that the problem of domestic violence must not be ignored as violence endangers people’s health and life. Domestic violence is not only the problem of separate individuals, it has negative effect on the other members of the family, especially on minors and leads to distortion of their psyche and consciousness which, in its turn, leads to the formation of an unhealthy situation in the society.The author analyzes the results of the four stages of victimization surveys and Unified Crime Reports prepared by the Ministry of Internal Affairs of Georgia in 2010-2013. The results of victimization surveys and statistics reports related to indexes and structure of crime became important after the parliamentary elections held in October 1, 2012, resulted by defeating of the ruling political party “National Movement” which was in power for the last 9 years. The new coalition “Georgian Dream”, headed by the billionaire B. Ivanishvili, radically changed political climate and announced the acceleration of democratization of the country and adopted the legislation decriminalization policy. According the new policy, the government of the country carried out the general amnesty, and released more than 60% of all prisoners from the custody. Such policy became the object of serious criticism from the part of the oppositions and some experts. They have expressed concerns about the criminal situation and decreasing level of security in the country predicted anarchy and disorganizations. This article is an attempt to assess the real situation in Georgia and the level of real threat to stability posed by criminality.Everything has his pros and cons. Debtor’s rights and obligations during court order enforcement, causes of problems that may arise. This problem is in the whole country, not just in one city or in one social class. A very large number of families from everywhere around Georgia have been affected. How and where it started will be discussed below in the text. Rights of creditors and debtors overlap in many aspects. We need to be very careful when sorting out this issue. We cannot under any circumstances make a decision with a benefit of one party while the other party will suffer losses. Georgian law on “Law Enforcement” does not support in any ways rights of debtors and all the procedures highlighted are towards forcing the debtor to pay off the debt. At this stage based on the current law, current socio-economic problems, statistics, ways on sorting out the problem, this object of studies is very important and has a very high intrinsic value in its theoretical part as well as in its practical part. If the right approach is taken it is possible to minimise the need to protect rights of creditors or debtors in the futures, because every party will be fully aware of their abilities and punishments for failures to fulfil their obligations, before signing the contractThe article includes detailed employment and uniploymant analysis in each municipality. In the analysis we use results from household survey conducted by the National Statistics Service. More specific information about the labour market at the municipal level was collected through cooperation with local municipalities. For the analysis we used information from municipalities’ web pages, telephone conversations with stakeholders, personal meetings with experts and so on. It should also be noted that a certain part of the data obtained from municipalities and from administrative territorial units have an approximate nature, but based on these information it is possible to gain some valuable conclusions and make assumptions. Terms and reality of employment analysis is carried out not only at the level of the municipality but on the country and regional ones as well.This project aims to apply learning of operations research and optimizing resources to practical cases. The aim of this problem is to maximize the the fairness of the schedule , while respecting all the constraints . In regards with the results obtained after some tests ILP has found a very good solution to our problem . Better values of the penalties associated to the shifts could be defined in order to represent the reality more accurately especially by taking into account the length of the shifts. The models can also be solved by means of optimization software. As shown in this paper, the current schedules can benefit from this work. My problem is NP-hard that it means unsolvable.My objective is to do the objective values ( diff =0.1) . The ideal must be 0 but it is impossible.there is shown in the table in 5 shifts , 20 nurses 10 weeks. We see that when we increase the number of shift the objective value is decreasing. It is fact that when we add a shift the software must do more iterations but the penalty is decreasing. We see that with the same number of iterations the penalty is smaller when we add a shift.For the welfare of modern society and any state`s correct function it is very important to have straightened working court system and to ensure every person`s court accessibility. Each step of court case management is detailed in civil procedure code. The legislation of civil procedure of Georgia foresees some mechanisms and opportunities of the restriction of court accessibility, which must be studied. The meaning of this study is stipulated by huge importance of court accessibility itself and by need of due caution during its restricting. The access to the court right is reserved not only by national, but also by international law, as evidenced by Article 42 of the Constitution [1], ``The UN Convention for Protection of Human Rights and Fundamental Freedoms`` Article 6 [3]. As any study issue, this one also needs scientific, systemic approach. For fully demonstrating the issue it is advised to classify and define court accessibility restriction mechanisms. Here presented work is about this matter.The Administrative Law is a part of public law, as it is depended on the subordinate principle. It aims to realize public interest. On the other hand, Enforcement Law is part of administrative space, which regulates the rules and procedures of the enforcement process for different court’s decisions as well as other acts. As administrating effects our everyday lives, it is a public interest that this process should be kept in the legal borders. This is exactly what the Administrative Law is all about. It regulates the social relations in which were government and other administrative bodies play a major role. It is true that Enforcement Law provides us with the norms, rules and procedures of the legal administration, but it is still court’s responsibility to assess the legal quality of it. This is why we need effective justice, to have the competent court ruling practice and to enforce them properly.Collision issues are discussed in family law such as conditions of marriage, results of marriage, annulment of marriage, duty of maintenance, relations between parents and children, relations related to child’s origin, conditions of adopting, guardianship and tuition. I discuss issues of guardianship and tuition in mentioned work, which I think is very interesting and actual.

On intrusion detection in opportunistic networks

Opportunistic networks (oppnets) can be deployed in an ad hoc manner in order to cover large geographical areas. The main challenges in oppnets are interoperability, security and privacy issues. In this paper we concentrate on security issues and especially on intrusion detection. Specifically, this paper includes a survey of different attacks and existing intrusion detection techniques. Moreover, it presents a Multi-Layer Anomaly Intrusion Detection technique that is based on an existing approach used in sensornets. Anomaly-based intrusion detection method was used because it can automatically infer attacks which are yet unknown without prior knowledge. In addition, the multilayer nature of the proposed technique, offers increased situational awareness and understanding of system security events as it uses corroborating evidence/information from different layers. The proposed technique is protocol independent since it uses the available system information produced by the various existing protocols of network layers. Consequently, it poses a low overhead which makes it energy efficient for the resource constrained oppnets. Finally, simulation results demonstrate that using such a Multi-Layer intrusion detection approach in oppnets is valuable.