Load profiling and data mining techniques in electricity deregulated market

This paper presents load profiles of electricity customers, using the knowledge discovery in databases (KDD) procedure, a data mining technique, to determine the load profiles for different types of customers. In this paper, the current load profiling methods are compared using data mining techniques, by analysing and evaluating these classification techniques. The objective of this study is to determine the best load profiling methods and data mining techniques to classify, detect and predict non-technical losses in the distribution sector, due to faulty metering and billing errors, as well as to gather knowledge on customer behaviour and preferences so as to gain a competitive advantage in the deregulated market. This paper focuses mainly on the comparative analysis of the classification techniques selected; a forthcoming paper will focus on the detection and prediction methods.

Consequences of customer loyalty to the loyalty program and to the company

Gaining customer loyalty is an important goal of marketing, and loyalty programs are intended to help in reaching it. Research on loyalty programs suggests that customers differentiate between loyalty to a company and loyalty to a loyalty program, yet little is known about the consequences of these two types of loyalty. Therefore, our study intends to make two main contributions: (1) improving our understanding of the constructs "program loyalty" and "company loyalty", (2) investigating the relative impact of the two types of loyalty on preference, intention, and purchase behavior for the case of a multi-firm loyalty program. Results indicate that company loyalty influences a customer's choice to visit a particular provider and to prefer it over competitors, but it is not a strong predictor of purchase behavior. Conversely, program loyalty is a far more important driver of purchase behavior. This implies that company loyalty primarily attracts customers to a particular provider and program loyalty ensures that once inside the store, more money is spent. © 2011 Academy of Marketing Science.

Applications of Nonclassical Logic Methods for Purposes of Knowledge Discovery and Data Mining

* The work is partially supported by Grant no. NIP917 of the Ministry of Science and Education – Republic of Bulgaria.

Analysis and Data Mining of Lead-Zinc Ore Data

This paper presents the results of our data mining study of Pb-Zn (lead-zinc) ore assay records from a mine enterprise in Bulgaria. We examined the dataset, cleaned outliers, visualized the data, and created dataset statistics. A Pb-Zn cluster data mining model was created for segmentation and prediction of Pb-Zn ore assay data. The Pb-Zn cluster data model consists of five clusters and DMX queries. We analyzed the Pb-Zn cluster content, size, structure, and characteristics. The set of the DMX queries allows for browsing and managing the clusters, as well as predicting ore assay records. A testing and validation of the Pb-Zn cluster data mining model was developed in order to show its reasonable accuracy before beingused in a production environment. The Pb-Zn cluster data mining model can be used for changes of the mine grinding and floatation processing parameters in almost real-time, which is important for the efficiency of the Pb-Zn ore beneficiation process. ACM Computing Classification System (1998): H.2.8, H.3.3.

A Taxonomy of Big Data for Optimal Predictive Machine Learning and Data Mining

Big data comes in various ways, types, shapes, forms and sizes. Indeed, almost all areas of science, technology, medicine, public health, economics, business, linguistics and social science are bombarded by ever increasing flows of data begging to be analyzed efficiently and effectively. In this paper, we propose a rough idea of a possible taxonomy of big data, along with some of the most commonly used tools for handling each particular category of bigness. The dimensionality p of the input space and the sample size n are usually the main ingredients in the characterization of data bigness. The specific statistical machine learning technique used to handle a particular big data set will depend on which category it falls in within the bigness taxonomy. Large p small n data sets for instance require a different set of tools from the large n small p variety. Among other tools, we discuss Preprocessing, Standardization, Imputation, Projection, Regularization, Penalization, Compression, Reduction, Selection, Kernelization, Hybridization, Parallelization, Aggregation, Randomization, Replication, Sequentialization. Indeed, it is important to emphasize right away that the so-called no free lunch theorem applies here, in the sense that there is no universally superior method that outperforms all other methods on all categories of bigness. It is also important to stress the fact that simplicity in the sense of Ockham’s razor non-plurality principle of parsimony tends to reign supreme when it comes to massive data. We conclude with a comparison of the predictive performance of some of the most commonly used methods on a few data sets.

Business Process Management and Process Mining within a Real Business Environment: An Empirical Analysis of Event Logs Data in a Consulting Project

Il presente elaborato esplora l’attitudine delle organizzazioni nei confronti dei processi di business che le sostengono: dalla semi-assenza di struttura, all’organizzazione funzionale, fino all’avvento del Business Process Reengineering e del Business Process Management, nato come superamento dei limiti e delle problematiche del modello precedente. All’interno del ciclo di vita del BPM, trova spazio la metodologia del process mining, che permette un livello di analisi dei processi a partire dagli event data log, ossia dai dati di registrazione degli eventi, che fanno riferimento a tutte quelle attività supportate da un sistema informativo aziendale. Il process mining può essere visto come naturale ponte che collega le discipline del management basate sui processi (ma non data-driven) e i nuovi sviluppi della business intelligence, capaci di gestire e manipolare l’enorme mole di dati a disposizione delle aziende (ma che non sono process-driven). Nella tesi, i requisiti e le tecnologie che abilitano l’utilizzo della disciplina sono descritti, cosi come le tre tecniche che questa abilita: process discovery, conformance checking e process enhancement. Il process mining è stato utilizzato come strumento principale in un progetto di consulenza da HSPI S.p.A. per conto di un importante cliente italiano, fornitore di piattaforme e di soluzioni IT. Il progetto a cui ho preso parte, descritto all’interno dell’elaborato, ha come scopo quello di sostenere l’organizzazione nel suo piano di improvement delle prestazioni interne e ha permesso di verificare l’applicabilità e i limiti delle tecniche di process mining. Infine, nell’appendice finale, è presente un paper da me realizzato, che raccoglie tutte le applicazioni della disciplina in un contesto di business reale, traendo dati e informazioni da working papers, casi aziendali e da canali diretti. Per la sua validità e completezza, questo documento è stata pubblicato nel sito dell'IEEE Task Force on Process Mining.

The Amplifier - v. 2, no. 8(b)

In this issue...Engineer's Valentine, Butte Chamber of Commerce, Jaycee Club, Main Hall, Wilmington Oil Field, Hecla Mining Company, Petroleum Engineers, Finlen Hotel

Analysis of corporate social responsibility (CSR) performance and financial performance of selected mining companies

The global concern about sustainability has been growing and the mining industry is questioned about its environmental and social performance. Corporate social responsibility (CSR) is an important issue for the extractive industries. The main objective of this study was to investigate the relationship between CSR performance and financial performance of selected mining companies. The study was conducted by identifying and comparing a selection of available CSR performance indicators with financial performance indicators. Based on the result of the study, the relationship between CSR performance and financial performance is unclear for the selected group of companies. The result is mixed and no industry specific realistic way to measure CSR performance uniformly is available. The result as a whole is contradictory and varies at company level as well as based on the selected indicators. The result of this study confirms that the relationship between CSR performance and financial performance is complicated and difficult to determine. As an outcome, evaluation of benefits of CSR in the mining sector could better be analyzed based on different attributes.

The Gandarela Mountain Range and the “resistance space” against iron ore mining threat: a focus on the contrapositions

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Nationalised large-scale mining, trade unions and community representation: perspectives from Northern Madagascar

This article critically explores the nature and purpose of relationships and inter-dependencies between stakeholders in the context of a parastatal chromite mining company in the Betsiboka Region of Northern Madagascar. An examination of the institutional arrangements at the interface between the mining company and local communities identified power hierarchies and dependencies in the context of a dominant paternalistic environment. The interactions, inter alia, limited social cohesion and intensified the fragility and weakness of community representation, which was further influenced by ethnic hierarchies between the varied community groups; namely, indigenous communities and migrants to the area from different ethnic groups. Moreover, dependencies and nepotism, which may exist at all institutional levels, can create civil society stakeholder representatives who are unrepresentative of the society they are intended to represent. Similarly, a lack of horizontal and vertical trust and reciprocity inherent in Malagasy society engenders a culture of low expectations regarding transparency and accountability, which further catalyses a cycle of nepotism and elite rent-seeking behaviour. On the other hand, leaders retain power with minimal vertical delegation or decentralisation of authority among levels of government and limit opportunities to benefit the elite, perpetuating rent-seeking behaviour within the privileged minority. Within the union movement, pluralism and the associated politicisation of individual unions restricts solidarity, which impacts on the movement’s capacity to act as a cohesive body of opinion and opposition. Nevertheless, the unions’ drive to improve their social capital has increased expectations of transparency and accountability, resulting in demands for greater engagement in decision-making processes.

The Role of Fraternal Organisation in Migration and Informal Labour Organisations in Mining Communities: Cornwall, the Keweenaw, and California Compared

During the second half of the nineteenth century fraternal and benevolent associations of numerous descriptions grew and prospered in mining communities everywhere. They played an important, but neglected role, in assisting transatlantic migration and movement between mining districts as well as building social capital within emerging mining communities. They helped to build bridges between different ethnic communities, provided conduits between labour and management, and networked miners into the non-mining community. Their influence spread beyond the adult males that made up most of their membership to their wives and families and provided levels of social and economic support otherwise unobtainable at that time. Of course, the influence of these organisations could also be divisive where certain groups or religions were excluded and they may have worked to exacerbate, as much as ameliorate, the problems of community development. This paper will examine some of these issues by looking particularly at the role of Freemasonry and Oddfellowry in Cornwall, Calumet, and Nevada City between 1860 and 1900. Work on fraternity in the Keweenaw was undertaken in Houghton some years ago with a grant from the Copper Country Archive and has since been continued by privately funded research in California and other Western mining states. Some British aspects of this research can be found in my article on mining industrial relations in Labour History Review April 2006

A Balance Shifted: The Unionization of Michigan’s Lake Copper District, 1935-1955

Three decades after the unsuccessful 1913-1914 strike at the Lake District copper mines of Michigan, workers organized as Local 584 of the International Union of Mine, Mill, and Smelter Workers (Mine Mill) signed a union contract with Calumet & Hecla Consolidated Copper Company. C & H was the last and most significant of the region’s three major copper mining companies to unionize during the three-year period from 1939 to 1942. This paper tells the untold history of the successful union drives in the Lake District’s copper mines, starting with Copper Range Company in 1939 and encompassing the subsequent unionizations of Quincy Mining Company and finally C & H. The paper develops thematic connections between the 1913-1914, including Mine Mill’s lineage to the Western Federation of Miners, parallel ethnic dimensions, and, most significantly, the contrasting role of state authority between the two time periods. The paper carries the Lake District’s labor history forward to 1955 to include United Steelworkers’ successful challenge to Mine Mill in 1950 and the strike of 1955. This history also incorporates source material from the papers of highly influential union organizer and representative Eugene Saari, material which to date has not been integrated into the labor history of the region. This paper has not yet been submitted.

Building clusters for CRM strategies by mining airlines customer data

Trabalho de Projeto apresentado como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação