This article interprets Hegel’s hierarchical theory of race as an application of his general views about the metaphysics of classification and explanation. We begin by offering a reconstruction of Hegel’s hierarchical theory of race based on the critical edition of relevant lecture transcripts: we argue that Hegel’s position on race is appropriately classified as racist, that it postulates innate mental deficits of some races, and that it turns racism from an anthropological into a metaphysical doctrine by claiming that the division of humankind into races (at least in the Old World) is not a brute fact, but follows a ‘higher necessity’. We then summarize our interpretation of the relevant metaphysical background to this theory. On our reading, Hegel postulates an essentialist form of explanation that explains given kinds as stages in a teleological, non-temporal process through which the nature of a superordinate kind is realized. We argue that Hegel’s views about a hierarchical and necessary division of humankind into races are an application of this model to the case of human diversity, motivated by explanatory considerations and subject to confirmation bias. By way of conclusion, we address two possible attempts to ‘save’ Hegelian philosophy from its racist baggage.

Objective The goal of this retrospective study is the evaluation of risk factors for postoperative neurological deficits after petroclival meningioma (PCM) surgery with special focus on standard craniotomies. Materials and methods One-hundred-fifty-eight patients were included in the study, of which 133 patients suffered from primary and 25 from recurrent PCM. All patients were operated on and evaluated concerning age, tumor size, histology, pre- and postoperative cranial nerve (CN) deficits, morbidity, mortality, and surgical complications. Tumor-specific features—e.g., consistency, surface, arachnoid cleavage, and location—were set in a four-grade classification system that was used to evaluate the risk of CN deficits and tumor resectability. Results After primary tumor resection, new CN deficits occurred in 27.3% of patients. Preoperative ataxia improved in 25%, whereas 10% developed new ataxia. Gross total resection (GTR) was achieved in 59.4%. The morbidity rate, including hemiparesis, shunt-dependence, postop-hemorrhage, and tracheostomy was 22.6% and the mortality rate was 2.3%. In recurrent PCM surgery, CN deficits occurred in 16%. GTR could be achieved in three cases. Minor complications occurred in 20%. By applying the proposed new classification system to patients operated via standard craniotomies, the best outcome was observed in type I tumor patients (soft tumor consistency, smooth surface, plane arachnoid cleavage, and unilateral localization) with GTR in 78.7% (p < 0.001) and 11.9% new CN deficits (p = 0.006). Conclusion Standard craniotomies as the retrosigmoid or subtemporal/pterional approaches are often used for the resection of PCMs. Whether these approaches are sufficient for GTR—and avoidance of new neurological deficits—depends mainly on the localization and intrinsic tumor-specific features.

Eine angemessene Qualität der Elektroenergie ist Grundvoraussetzung für den störungsfreien Betrieb aller angeschlossenen Geräte und Anlagen und spielt in den Verteilungsnetzen moderner Industriegesellschaften wie Deutschland eine zentrale Rolle. Die Elektroenergiequalität (EEQ) wird in Strom- und Spannungsqualität unterteilt. Während die Stromqualität maßgeblich im Verantwortungsbereich der Hersteller von Geräten und Anlagen liegt, sind für die Sicherung einer angemessenen Spannungsqualität im Wesentlichen die Netzbetreiber verantwortlich. Durch die technische Weiterentwicklung bspw. neuer Gerätetechnologien und die zunehmende Integration dezentraler Erzeugungsanlagen wie Photovoltaikanlagen ist zu erwarten, dass die EEQ auch künftig weiter an Bedeutung gewinnt. Die EEQ im Niederspannungsverteilungsnetz ist abhängig von Ort und Zeit und wird durch verschiedene Qualitätskenngrößen beschrieben. Die örtliche und zeitliche Abhängigkeit resultieren aus einer Vielzahl verschiedener Einflussfaktoren, welche sich entweder der elektrischen oder der nicht-elektrischen Umgebung des betrachteten Verteilungsnetzes zuordnen lassen. Die elektrische Umgebung wird durch die Art und Anzahl angeschlossener Verbraucher bzw. Erzeuger (Abnehmer- bzw. Erzeugerstruktur) sowie Struktur und technische Parameter des Verteilungsnetzes (Netzstruktur) bestimmt. Die nicht-elektrische Umgebung umfasst u.a. Einflüsse der klimatischen Umgebung wie bspw. Temperatur oder Globalstrahlung. Ziel dieser Arbeit ist die systematische Identifikation korrelativer Zusammenhänge zwischen den genannten Umgebungseinflüssen und der EEQ sowie deren Quantifizierung auf Basis geeigneter Indizes und Kenngrößen. Die Ergebnisse der Arbeit helfen grundlegende Prinzipien der Ausprägung der Elektroenergiequalität im öffentlichen Verteilungsnetz besser zu verstehen sowie die Verteilungsnetze im Hinblick auf die Elektroenergiequalität zu charakterisieren und zu klassifizieren. Analog zu den Standard-Lastprofilen erfolgt die Definition von Standard-Qualitätsprofilen. / Power quality levels in public low voltage grids are influenced by many factors which can either be assigned to the electrical environment (connected consumers, connected genera-tion, network characteristics) or to the non-electrical environment (e.g. climatic conditions) at the measurement site. Type and amount of connected consumers (consumer topology) are expected to have a very high impact on power quality (PQ) levels. The generation topology is characterized by number and kind of equipment and generating installations like photovoltaic systems which are connected to the LV grid. The electrical parameters of the grid define the network topology. The parameters which are most suitable to describe each of the three topologies and the climatic environment will be identified. Voltage and current quality in public low voltage (LV) grids vary depending on location and time. They are quantified by a set of different parameters which either belong to events (e.g. dips) or to variations (e.g. harmonics). This thesis exclusively addresses continuous parameters describing variations. Continuous phenomena like harmonics are closely linked to an one-day-cycle which implies a more or less periodic behavior of the continuous power quality parameters. Consumer topologies such as office buildings or residential areas differ in their use of equipment. Time series analysis is used to distinguish between different consumer topologies and to identify characteristic weeks. The clustering of one-day time series is applied to identify characteristic days within the weeks of certain topologies. Based on the results, emission profiles for certain current quality parameters of different consumer topologies will be defined. Due to the characteristic harmonic current emission of certain consumer topologies which represents the typical user behaviour a classification system is developed. It is used to automatically classify the emission profiles of harmonic currents for unknown measurements and to estimate a likely consumer topology. A classification measure is introduced in order to identify unusual or false classified emission profiles. The usage behaviour of equipment by customers usually varies over the year. Subsequently, the levels of PQ parameters like harmonics may show seasonal variations which are identified by using newly defined parameters. The introduction of new device technologies on a large scale like the transition from incandescent to LED lamps might result in long-term changes to the levels of PQ parameters (e.g. harmonics). The analysis of the long-term behavior (trend) will be applied in order to quantify global trends (looking on the measurement duration as a whole) and local trends (looking on individual segments of the whole time series).

No description available.

Virtual reconstruction of historic sites, planning of restorations and attachments of new building parts, as well as forest inventory are few examples of fields that benefit from the application of 3D surveying data. Originally using 2D photo based documentation and manual distance measurements, the 3D information obtained from multi camera and laser scanning systems realizes a noticeable improvement regarding the surveying times and the amount of generated 3D information. The 3D data allows a detailed post processing and better visualization of all relevant spatial information. Yet, for the extraction of the required information from the raw scan data and for the generation of useable visual output, time-consuming, complex user-based data processing is still required, using the commercially available 3D software tools. In this context, the automatic object recognition from 3D point cloud and depth data has been discussed in many different works. The developed tools and methods however, usually only focus on a certain kind of object or the detection of learned invariant surface shapes. Although the resulting methods are applicable for certain practices of data segmentation, they are not necessarily suitable for arbitrary tasks due to the varying requirements of the different fields of research. This thesis presents a more widespread solution for automatic scene reconstruction from 3D point clouds, targeting street scenarios, specifically for the task of traffic accident scene analysis and documentation. The data, obtained by sampling the scene using a mobile scanning system is evaluated, segmented, and finally used to generate detailed 3D information of the scanned environment. To realize this aim, this work adapts and validates various existing approaches on laser scan segmentation regarding the application on accident relevant scene information, including road surfaces and markings, vehicles, walls, trees and other salient objects. The approaches are therefore evaluated regarding their suitability and limitations for the given tasks, as well as for possibilities concerning the combined application together with other procedures. The obtained knowledge is used for the development of new algorithms and procedures to allow a satisfying segmentation and reconstruction of the scene, corresponding to the available sampling densities and precisions. Besides the segmentation of the point cloud data, this thesis presents different visualization and reconstruction methods to achieve a wider range of possible applications of the developed system for data export and utilization in different third party software tools.

In der Mobilitätsforschung entstand in den vergangenen Jahrzehnten eine breite Wissensbasis für das Verständnis von Verkehrsursachen und Zusammenhängen, die das Verkehrsverhalten determinieren. Mit der Entwicklung von Verkehrsmodellen lag das Forschungsinteresse zunächst primär bei Ökonomen und Ökonometrikern sowie Verkehrsingenieuren. Bald kamen andere Wissenschaftsbereiche wie die Psychologie oder die Geowissenschaften hinzu, welche sich in der Folge zunehmend mit dem Thema Mobilität befassten und die zur Erklärung des menschlichen Verhaltens ganz unterschiedliche Methoden und Maßstäbe nutzten. Heute versuchen zumeist handlungsorientierte Ansätze, auf Individualebene, Faktoren zu bestimmen, die Aufschluss über die Verhaltensvariabilität in der Bevölkerung geben und damit einen möglichst großen Beitrag zur Varianzaufklärung leisten. Werden Einflussfaktoren in geeigneter Weise identifiziert und quantifiziert, können Defizite und Chancen erkannt und das Verhalten steuernde Maßnahmen entworfen werden. Mit deren Hilfe wird ungewollten Entwicklungen entgegengesteuert. Junge Erwachsene stellen aufgrund ihrer sehr unterschiedlichen Phasen im Lebenszyklus, z. B. gerade anstehender oder abgeschlossener Ausbildung, Umzug in eine eigene Wohnung, Familiengründung, Neuorientierung in Arbeitsroutinen oder das Einleben in ein anderes Lebensumfeld einer fremden Stadt, intuitiv eine sehr heterogene Gruppe dar. Die Modellierung des Verhaltens ist für diese Altersgruppe besonders schwierig. Aus der Komplexität dieser Problemstellung heraus ist ersichtlich, dass fundierte Analysen zur Mobilität junger Erwachsener notwendig sind, um verkehrsplanerische Defizite aufzudecken und Chancen zu erkennen. Der methodische Schwerpunkt des Beitrages liegt auf der Bildung einer Typologie des Verkehrsverhaltens junger Erwachsener. Die verwendete Datengrundlage ist das „Deutsche Mobilitätspanel – MOP“. Dabei wird der Versuch unternommen, zunächst Variablen aller relevanten Dimensionen des handlungsorientierten, aktivitätsbasierten Verkehrsverhaltens zusammenzustellen und für eine entsprechende Analyse aufzubereiten. Im Anschluss werden geeignete und in den Sozialwissenschaften erprobte Verfahren zur Ähnlichkeitsmessung eingesetzt, um möglichst verhaltensähnliche Personen zu typologisieren. Im Weiteren finden konfirmatorische Analysetechniken Anwendung, mit deren Hilfe Verhaltenshintergründe erklärt und inferenzstatistisch geprüft werden. Als Ergebnis wird eine clusteranalytische Typologisierung vorgestellt, die im Anschluss anhand soziodemografischer Indikatoren und raumstruktureller Kriterien der Lagegunst beschrieben wird. Aufgrund der gewonnenen Erkenntnisse können objektive und im Idealfall quantifizierbare, d. h. prognosefähige Merkmale zur Bildung verkehrssoziologischer und weitgehend verhaltensähnlicher Personengruppen genutzt werden. / Over the last few decades of mobility research, a wide base of knowledge for understanding travel determinants and causal relationships in mobility behavior has been established. The development of travel models was at first of interest primarily to economists and econometricians as well as transportation engineers. They were soon joined by other scientific areas such as psychology or the geosciences, which as a result increasingly addressed the theme of mobility and used quite different methodologies and criteria for explaining human behavior. Today, activity-oriented approaches generally attempt to determine individual-level factors that provide information on behavioral variability within the population, thereby contributing greatly to explaining variances. If explanatory factors can be properly identified and quantified, then deficiencies and opportunities can be recognized and measures for influencing behavior can be conceptualized. With their help, undesirable developments can be avoided. Because of their highly differing stages in life, e.g. upcoming or recently completed education, moving into their own apartment, starting a family, becoming oriented in a work routine or adapting to a new environment in a different city, young adults are intuitively a very heterogeneous group. Modeling the behavior of this age group is particularly difficult. This problem makes it clear that founded analysis of the mobility of young adults is necessary in order to recognize deficiencies and opportunities in transportation planning. The methodological focus of this work is on creating a typology of young adults’ travel behavior. The base data is from the “Deutsches Mobilitätspanel – MOP” (German Mobility Panel). An attempt is made to gather and prepare all relevant dimensions of decision-oriented, activity-based travel behavior for a corresponding analysis. Afterward, appropriate and proven methods from the social sciences are used to test for similarity in order to identify groups of persons which are as behaviorally homogeneous as possible. In addition, confirmatory data analysis is utilized which helps explain and test, through inferential statistics, determinants of behavior. The resulting typology from the cluster analysis is presented and followed by a description using sociodemographic indicators and spatial criteria of accessibility. The findings make it possible to use objective and, ideally, quantifiable and therefore forecastable characteristics for identifying sociological population groups within which similar travel behavior is displayed.

Education in schools and universities suffers from different problems like the lack of interaction between the lecturer and the students as well as the fear of asking irrelevant questions or providing wrong answers in front of a large audience. A lot of systems exist that try to solve these issues by means of technical tools; e.g., audience response systems. Each of these individual systems supports different functional scopes with different didactic purposes in order to support specific use cases. For the lecturer, it is very hard to choose an appropriate system. Besides the functional scope, there are a lot of predefined limitations, such as a given room with technical restrictions or a favorite operating system and presentation software to present the slides. This paper gives an overview of fifty existing systems (with varying degree of detail) and proposes a filter mechanism based on the index card metaphor to select appropriate systems depending on their individual limitations. In order to simplify this selection process for the lecturer, the filter mechanism is implemented in a web-based selection tool.

Virtual reconstruction of historic sites, planning of restorations and attachments of new building parts, as well as forest inventory are few examples of fields that benefit from the application of 3D surveying data. Originally using 2D photo based documentation and manual distance measurements, the 3D information obtained from multi camera and laser scanning systems realizes a noticeable improvement regarding the surveying times and the amount of generated 3D information. The 3D data allows a detailed post processing and better visualization of all relevant spatial information. Yet, for the extraction of the required information from the raw scan data and for the generation of useable visual output, time-consuming, complex user-based data processing is still required, using the commercially available 3D software tools. In this context, the automatic object recognition from 3D point cloud and depth data has been discussed in many different works. The developed tools and methods however, usually only focus on a certain kind of object or the detection of learned invariant surface shapes. Although the resulting methods are applicable for certain practices of data segmentation, they are not necessarily suitable for arbitrary tasks due to the varying requirements of the different fields of research. This thesis presents a more widespread solution for automatic scene reconstruction from 3D point clouds, targeting street scenarios, specifically for the task of traffic accident scene analysis and documentation. The data, obtained by sampling the scene using a mobile scanning system is evaluated, segmented, and finally used to generate detailed 3D information of the scanned environment. To realize this aim, this work adapts and validates various existing approaches on laser scan segmentation regarding the application on accident relevant scene information, including road surfaces and markings, vehicles, walls, trees and other salient objects. The approaches are therefore evaluated regarding their suitability and limitations for the given tasks, as well as for possibilities concerning the combined application together with other procedures. The obtained knowledge is used for the development of new algorithms and procedures to allow a satisfying segmentation and reconstruction of the scene, corresponding to the available sampling densities and precisions. Besides the segmentation of the point cloud data, this thesis presents different visualization and reconstruction methods to achieve a wider range of possible applications of the developed system for data export and utilization in different third party software tools.

In der Mobilitätsforschung entstand in den vergangenen Jahrzehnten eine breite Wissensbasis für das Verständnis von Verkehrsursachen und Zusammenhängen, die das Verkehrsverhalten determinieren. Mit der Entwicklung von Verkehrsmodellen lag das Forschungsinteresse zunächst primär bei Ökonomen und Ökonometrikern sowie Verkehrsingenieuren. Bald kamen andere Wissenschaftsbereiche wie die Psychologie oder die Geowissenschaften hinzu, welche sich in der Folge zunehmend mit dem Thema Mobilität befassten und die zur Erklärung des menschlichen Verhaltens ganz unterschiedliche Methoden und Maßstäbe nutzten. Heute versuchen zumeist handlungsorientierte Ansätze, auf Individualebene, Faktoren zu bestimmen, die Aufschluss über die Verhaltensvariabilität in der Bevölkerung geben und damit einen möglichst großen Beitrag zur Varianzaufklärung leisten. Werden Einflussfaktoren in geeigneter Weise identifiziert und quantifiziert, können Defizite und Chancen erkannt und das Verhalten steuernde Maßnahmen entworfen werden. Mit deren Hilfe wird ungewollten Entwicklungen entgegengesteuert. Junge Erwachsene stellen aufgrund ihrer sehr unterschiedlichen Phasen im Lebenszyklus, z. B. gerade anstehender oder abgeschlossener Ausbildung, Umzug in eine eigene Wohnung, Familiengründung, Neuorientierung in Arbeitsroutinen oder das Einleben in ein anderes Lebensumfeld einer fremden Stadt, intuitiv eine sehr heterogene Gruppe dar. Die Modellierung des Verhaltens ist für diese Altersgruppe besonders schwierig. Aus der Komplexität dieser Problemstellung heraus ist ersichtlich, dass fundierte Analysen zur Mobilität junger Erwachsener notwendig sind, um verkehrsplanerische Defizite aufzudecken und Chancen zu erkennen. Der methodische Schwerpunkt des Beitrages liegt auf der Bildung einer Typologie des Verkehrsverhaltens junger Erwachsener. Die verwendete Datengrundlage ist das „Deutsche Mobilitätspanel – MOP“. Dabei wird der Versuch unternommen, zunächst Variablen aller relevanten Dimensionen des handlungsorientierten, aktivitätsbasierten Verkehrsverhaltens zusammenzustellen und für eine entsprechende Analyse aufzubereiten. Im Anschluss werden geeignete und in den Sozialwissenschaften erprobte Verfahren zur Ähnlichkeitsmessung eingesetzt, um möglichst verhaltensähnliche Personen zu typologisieren. Im Weiteren finden konfirmatorische Analysetechniken Anwendung, mit deren Hilfe Verhaltenshintergründe erklärt und inferenzstatistisch geprüft werden. Als Ergebnis wird eine clusteranalytische Typologisierung vorgestellt, die im Anschluss anhand soziodemografischer Indikatoren und raumstruktureller Kriterien der Lagegunst beschrieben wird. Aufgrund der gewonnenen Erkenntnisse können objektive und im Idealfall quantifizierbare, d. h. prognosefähige Merkmale zur Bildung verkehrssoziologischer und weitgehend verhaltensähnlicher Personengruppen genutzt werden. / Over the last few decades of mobility research, a wide base of knowledge for understanding travel determinants and causal relationships in mobility behavior has been established. The development of travel models was at first of interest primarily to economists and econometricians as well as transportation engineers. They were soon joined by other scientific areas such as psychology or the geosciences, which as a result increasingly addressed the theme of mobility and used quite different methodologies and criteria for explaining human behavior. Today, activity-oriented approaches generally attempt to determine individual-level factors that provide information on behavioral variability within the population, thereby contributing greatly to explaining variances. If explanatory factors can be properly identified and quantified, then deficiencies and opportunities can be recognized and measures for influencing behavior can be conceptualized. With their help, undesirable developments can be avoided. Because of their highly differing stages in life, e.g. upcoming or recently completed education, moving into their own apartment, starting a family, becoming oriented in a work routine or adapting to a new environment in a different city, young adults are intuitively a very heterogeneous group. Modeling the behavior of this age group is particularly difficult. This problem makes it clear that founded analysis of the mobility of young adults is necessary in order to recognize deficiencies and opportunities in transportation planning. The methodological focus of this work is on creating a typology of young adults’ travel behavior. The base data is from the “Deutsches Mobilitätspanel – MOP” (German Mobility Panel). An attempt is made to gather and prepare all relevant dimensions of decision-oriented, activity-based travel behavior for a corresponding analysis. Afterward, appropriate and proven methods from the social sciences are used to test for similarity in order to identify groups of persons which are as behaviorally homogeneous as possible. In addition, confirmatory data analysis is utilized which helps explain and test, through inferential statistics, determinants of behavior. The resulting typology from the cluster analysis is presented and followed by a description using sociodemographic indicators and spatial criteria of accessibility. The findings make it possible to use objective and, ideally, quantifiable and therefore forecastable characteristics for identifying sociological population groups within which similar travel behavior is displayed.

Eine angemessene Qualität der Elektroenergie ist Grundvoraussetzung für den störungsfreien Betrieb aller angeschlossenen Geräte und Anlagen und spielt in den Verteilungsnetzen moderner Industriegesellschaften wie Deutschland eine zentrale Rolle. Die Elektroenergiequalität (EEQ) wird in Strom- und Spannungsqualität unterteilt. Während die Stromqualität maßgeblich im Verantwortungsbereich der Hersteller von Geräten und Anlagen liegt, sind für die Sicherung einer angemessenen Spannungsqualität im Wesentlichen die Netzbetreiber verantwortlich. Durch die technische Weiterentwicklung bspw. neuer Gerätetechnologien und die zunehmende Integration dezentraler Erzeugungsanlagen wie Photovoltaikanlagen ist zu erwarten, dass die EEQ auch künftig weiter an Bedeutung gewinnt. Die EEQ im Niederspannungsverteilungsnetz ist abhängig von Ort und Zeit und wird durch verschiedene Qualitätskenngrößen beschrieben. Die örtliche und zeitliche Abhängigkeit resultieren aus einer Vielzahl verschiedener Einflussfaktoren, welche sich entweder der elektrischen oder der nicht-elektrischen Umgebung des betrachteten Verteilungsnetzes zuordnen lassen. Die elektrische Umgebung wird durch die Art und Anzahl angeschlossener Verbraucher bzw. Erzeuger (Abnehmer- bzw. Erzeugerstruktur) sowie Struktur und technische Parameter des Verteilungsnetzes (Netzstruktur) bestimmt. Die nicht-elektrische Umgebung umfasst u.a. Einflüsse der klimatischen Umgebung wie bspw. Temperatur oder Globalstrahlung. Ziel dieser Arbeit ist die systematische Identifikation korrelativer Zusammenhänge zwischen den genannten Umgebungseinflüssen und der EEQ sowie deren Quantifizierung auf Basis geeigneter Indizes und Kenngrößen. Die Ergebnisse der Arbeit helfen grundlegende Prinzipien der Ausprägung der Elektroenergiequalität im öffentlichen Verteilungsnetz besser zu verstehen sowie die Verteilungsnetze im Hinblick auf die Elektroenergiequalität zu charakterisieren und zu klassifizieren. Analog zu den Standard-Lastprofilen erfolgt die Definition von Standard-Qualitätsprofilen. / Power quality levels in public low voltage grids are influenced by many factors which can either be assigned to the electrical environment (connected consumers, connected genera-tion, network characteristics) or to the non-electrical environment (e.g. climatic conditions) at the measurement site. Type and amount of connected consumers (consumer topology) are expected to have a very high impact on power quality (PQ) levels. The generation topology is characterized by number and kind of equipment and generating installations like photovoltaic systems which are connected to the LV grid. The electrical parameters of the grid define the network topology. The parameters which are most suitable to describe each of the three topologies and the climatic environment will be identified. Voltage and current quality in public low voltage (LV) grids vary depending on location and time. They are quantified by a set of different parameters which either belong to events (e.g. dips) or to variations (e.g. harmonics). This thesis exclusively addresses continuous parameters describing variations. Continuous phenomena like harmonics are closely linked to an one-day-cycle which implies a more or less periodic behavior of the continuous power quality parameters. Consumer topologies such as office buildings or residential areas differ in their use of equipment. Time series analysis is used to distinguish between different consumer topologies and to identify characteristic weeks. The clustering of one-day time series is applied to identify characteristic days within the weeks of certain topologies. Based on the results, emission profiles for certain current quality parameters of different consumer topologies will be defined. Due to the characteristic harmonic current emission of certain consumer topologies which represents the typical user behaviour a classification system is developed. It is used to automatically classify the emission profiles of harmonic currents for unknown measurements and to estimate a likely consumer topology. A classification measure is introduced in order to identify unusual or false classified emission profiles. The usage behaviour of equipment by customers usually varies over the year. Subsequently, the levels of PQ parameters like harmonics may show seasonal variations which are identified by using newly defined parameters. The introduction of new device technologies on a large scale like the transition from incandescent to LED lamps might result in long-term changes to the levels of PQ parameters (e.g. harmonics). The analysis of the long-term behavior (trend) will be applied in order to quantify global trends (looking on the measurement duration as a whole) and local trends (looking on individual segments of the whole time series).