The New Science Intensive Standard of Master Preparation in Sphere of Competitive Intelligence on the Basis of Systemological Knowledge-Oriented Technologies

Methodological, theoretical and technological bases of the new branch standard of Ukraine higher education which regulates preparation process of masters - professionals in the information area and information analysts are considered. The new systemological knowledge-oriented technologies developed in KNURE which considerably surpass foreign analogues are put as the basis of training.

Actionable pattern analysis in computing and business intelligence systems

With advances in science and technology, computing and business intelligence (BI) systems are steadily becoming more complex with an increasing variety of heterogeneous software and hardware components. They are thus becoming progressively more difficult to monitor, manage and maintain. Traditional approaches to system management have largely relied on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. It is widely acknowledged as a cumbersome, labor intensive, and error prone process, besides being difficult to keep up with the rapidly changing environments. In addition, many traditional business systems deliver primarily pre-defined historic metrics for a long-term strategic or mid-term tactical analysis, and lack the necessary flexibility to support evolving metrics or data collection for real-time operational analysis. There is thus a pressing need for automatic and efficient approaches to monitor and manage complex computing and BI systems. To realize the goal of autonomic management and enable self-management capabilities, we propose to mine system historical log data generated by computing and BI systems, and automatically extract actionable patterns from this data. This dissertation focuses on the development of different data mining techniques to extract actionable patterns from various types of log data in computing and BI systems. Four key problems—Log data categorization and event summarization, Leading indicator identification , Pattern prioritization by exploring the link structures , and Tensor model for three-way log data are studied. Case studies and comprehensive experiments on real application scenarios and datasets are conducted to show the effectiveness of our proposed approaches.

Advanced Business Simulations-Incorporating business and process execution data

Key Performance Indicators (KPIs) and their predictions are widely used by the enterprises for informed decision making. Nevertheless , a very important factor, which is generally overlooked, is that the top level strategic KPIs are actually driven by the operational level business processes. These two domains are, however, mostly segregated and analysed in silos with different Business Intelligence solutions. In this paper, we are proposing an approach for advanced Business Simulations, which converges the two domains by utilising process execution & business data, and concepts from Business Dynamics (BD) and Business Ontologies, to promote better system understanding and detailed KPI predictions. Our approach incorporates the automated creation of Causal Loop Diagrams, thus empowering the analyst to critically examine the complex dependencies hidden in the massive amounts of available enterprise data. We have further evaluated our proposed approach in the context of a retail use-case that involved verification of the automatically generated causal models by a domain expert.

Technology strategies in the process of student retention and efficiency of academic management

This article discusses the application of Information and Communication Technologies and strategies for best practices in order to capture and maintain faculty students' attention. It is based on a case study of ten years, using a complete information system. This system, in addition to be considered an ERP, to support the activities of academic management, also has a strong component of SRM that provides support to academic and administrative activities. It describes the extent to which the presented system facilitates the interaction and communication between members of the academic community, using the Internet, with services available on the Web complementing them with email, SMS and CTI. Through a perception, backed by empirical analysis and results of investigations, it demonstrates how this type of practice may raise the level of satisfaction of the community. In particular, it is possible to combat failure at school, avoid that students leave their course before its completion and also that they recommend them to potential students. In addition, such a strategy also allows strong economies in the management of the institution, increasing its value. As future work, we present the new phase of the project towards implementation of Business Intelligence to optimize the management process, making it proactive. The technological vision that guides new developments to a construction based on Web services and procedural languages is also presented.

Espionage against Poland in the Documents and Analyses of the Polish Special Services (1944 - 1989) - as Illustrated by the Intelligence Activities of the USA

The text analyses the intelligence activity against Poland in the period 1944-1989. The paper also contains a case study, i.e. an analysis of the American intelligence service activity held against Poland. While examining the research thesis, the author used the documents and analyses prepared by the Ministry of Internal Affairs. In order to best illustrate the point, the author presented a number of cases of persons who spied for the USA, which was possible thanks to the analysis of the training materials of the Ministry of Internal Affairs directed to the officers of the Security Service and the Citizens’ Militia. The text tackles the following issues: (1) to what extent did the character of the socio-political system influence the number of persons convicted for espionage against Poland in the period under examination?, (2) what was the level of interest of the foreign intelligence services in Poland before the year 1990?, (3) is it possible to indicate the specificity of the U.S. intelligence activity against Poland? 1) The analysis of data indicates that the period 1946-1956 witnessed a great number of convictions for espionage, which is often associated with the peculiar political situation in Poland of that time. Up to 1953, the countries of the Eastern bloc had reproduced the Stalin’s system, which only ceased due to the death of Stalin himself. Since then, the communist systems gradually transformed into the system of nomenklatura. Irrespective of these changes, Poland still witnessed a wave of repressions, which resulted from the threats continuously looming over the communist authorities – combating the anti-communist underground movement, fighting with the Ukrainian Insurgent Army, the Polish government-in-exile, possible revisionism of borders, social discontent related to the socio-political reforms. Hence, a great number of convictions for espionage at that time could be ascribed to purely political sentences. Moreover, equally significant was the fact that the then judicial practice was preoccupied assessing negatively any contacts and relations with foreigners. This excessive number of convictions could ensue from other criminal-law provisions, which applied with respect to the crimes against the State, including espionage. What is also important is the fact that in the Stalin’s period the judiciary personnel acquired their skills and qualifications through intensive courses in law with the predominant spirit of the theory of evidence and law by Andrey Vyshinsky. Additionally, by the decree of 1944 the Penal Code of the Polish Armed Forces was introduced; the code envisaged the increase in the number of offences classified as penalised with death penalty, whereas the high treason was subject to the military jurisdiction (the civilians were prosecuted in military courts till 1955; the espionage, however, still stood under the military jurisdiction). In 1946, there was introduced the Decree on particularly dangerous crimes in the period of the State’s recovery, which was later called a Small Penal Code. 2) The interest that foreign intelligence services expressed in relation to Poland was similar to the one they had in all countries of Eastern and Central Europe. In the case of Poland, it should be noted that foreign intelligence services recruited Polish citizens who had previously stayed abroad and after WWII returned to their home country. The services also gathered information from Poles staying in immigrant camps (e.g. in FRG). The activity of the American intelligence service on the territory of FRG and West Berlin played a key role. The documents of the Ministry of Internal Affairs pointed to the global range of this activity, e.g. through the recruitment of Polish sailors in the ports of the Netherlands, Japan, etc. In line with the development in the 1970s, espionage, which had so far concentrated on the defence and strategic sectors, became focused on science and technology of the People’s Republic of Poland. The acquisition of collaborators in academic circles was much easier, as PRL opened to academic exchange. Due to the system of visas, the process of candidate selection for intelligence services (e.g. the American) began in embassies. In the 1980s, the activity of the foreign intelligence services concentrated on the specific political situation in Poland, i.e. the growing significance of the “Solidarity” social movement. 3) The specificity of the American intelligence activity against Poland was related to the composition of the residency staff, which was the largest in comparison to other Western countries. The wide range of these activities can be proved by the quantitative data of convictions for espionage in the years 1944-1984 (however, one has to bear in mind the factors mentioned earlier in the text, which led to the misinterpretation of these data). Analysing the data and the documents prepared by the Ministry of Internal Affairs, one should treat them with caution, as, frequently, the Polish counter-intelligence service used to classify the ordinary diplomatic practice and any contacts with foreigners as espionage threats. It is clearly visible in the language of the training materials concerned with “secret service methods of the intelligence activity” as well as in the documents on operational activities of the Security Service in relation to foreigners. The level of interest the USA had in Poland was mirrored in the classification of diplomatic posts, according to which Warsaw occupied the second place (the so-called Group “B”) on the three-point scale. The CIA experienced spectacular defeats during their activity in Poland: supporting the Polish underground anti-communist organisation Freedom and Independence and the so-called Munich-Berg episode (both cases took place in the 1950s). The text focuses only on selected issues related to the espionage activities against Poland. Similarly, the analysis of the problem has been based on selected sources, which has limited the research scope - however, it was not the aim of the author to present the espionage activity against Poland in a comprehensive way. In order to assess the real threat posed by the espionage activity, one should analyse the case of persons convicted for espionage in the period 1944-1989, as the available quantitative data, mentioned in the text, cannot constitute an explicit benchmark for the scale of espionage activity. The inaccuracies in the interpretation of data and variables, which can affect the evaluation of this phenomenon, have been pointed out in the text.

Virtual Enterprise Process Management: An Application to Industrial Maintenance

Part 2: Behaviour and Coordination

Intelligence-led policing : O papel dos sistemas de informação no planeamento e orientação do esforço de policiamento

O presente trabalho de investigação aplicada está subordinado ao tema “Intelligence-led policing: o papel dos sistemas de informação no planeamento e orientação do esforço de policiamento”. Começámos por fazer um enquadramento teórico e abordar conceitos importantes para o desenvolvimento de todo o trabalho. Assumindo um método dedutivo, desenvolvemos um estudo com base na seguinte questão de partida: “Qual o impacto dos sistemas de informação no planeamento e orientação do esforço de policiamento?”. Posto isto, este trabalho tem como objetivo perceber qual a influência que os sistemas de informação têm na tomada de decisão do comandante, neste caso de Destacamento Territorial, mais precisamente no planeamento e orientação do esforço de policiamento. Quanto à metodologia, incidiu numa análise documental sobre as variáveis em estudo e também na análise de respostas aos inquéritos por questionário efetuados aos Comandantes de Destacamento Territorial. Com este trabalho concluímos que, do ponto de vista de uma grande parte dos inquiridos, os sistemas de informação que a Guarda Nacional Republicana dispõe não são adequados às necessidades operacionais desta. Outra conclusão a que chegámos foi ao facto de, apesar da informação analisada ter reconhecidamente valor acrescentado, as ferramentas de análise que a Guarda dispõe também não são suficientes para suprir as necessidades sentidas.

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.

Fully smart cities: Analysis of the city to Smart City transformation process

Ever since the birth of the Smart City paradigm, a wide variety of initiatives have sprung up involving this phenomenon: best practices, projects, pilot projects, transformation plans, models, standards, indicators, measuring systems, etc. The question to ask, applicable to any government official, city planner or researcher, is whether this effect is being felt in how cities are transforming, or whether, in contrast, it is not very realistic to speak of cities imbued with this level of intelligence. Many cities are eager to define themselves as smart, but the variety, complexity and scope of the projects needed for this transformation indicate that the change process is longer than it seems. If our goal is to carry out a comparative analysis of this progress among cities by using the number of projects executed and their scope as a reference for the transformation, we could find such a task inconsequential due to the huge differences and characteristics that define a city. We believe that the subject needs simplification (simpler, more practical models) and a new approach. This paper presents a detailed analysis of the smart city transformation process in Spain and provides a support model that helps us understand the changes and the speed at which they are being implemented. To this end we define a set of elements of change called "transformation factors" that group a city's smartness into one of three levels (Low/Medium/Fully) and more homogeneously identify the level of advancement of this process. © 2016 IEEE.

Supporting Scientific Research Through Machine and Deep Learning: Fluorescence Microscopy and Operational Intelligence Use Cases

Although the debate of what data science is has a long history and has not reached a complete consensus yet, Data Science can be summarized as the process of learning from data. Guided by the above vision, this thesis presents two independent data science projects developed in the scope of multidisciplinary applied research. The first part analyzes fluorescence microscopy images typically produced in life science experiments, where the objective is to count how many marked neuronal cells are present in each image. Aiming to automate the task for supporting research in the area, we propose a neural network architecture tuned specifically for this use case, cell ResUnet (c-ResUnet), and discuss the impact of alternative training strategies in overcoming particular challenges of our data. The approach provides good results in terms of both detection and counting, showing performance comparable to the interpretation of human operators. As a meaningful addition, we release the pre-trained model and the Fluorescent Neuronal Cells dataset collecting pixel-level annotations of where neuronal cells are located. In this way, we hope to help future research in the area and foster innovative methodologies for tackling similar problems. The second part deals with the problem of distributed data management in the context of LHC experiments, with a focus on supporting ATLAS operations concerning data transfer failures. In particular, we analyze error messages produced by failed transfers and propose a Machine Learning pipeline that leverages the word2vec language model and K-means clustering. This provides groups of similar errors that are presented to human operators as suggestions of potential issues to investigate. The approach is demonstrated on one full day of data, showing promising ability in understanding the message content and providing meaningful groupings, in line with previously reported incidents by human operators.

Anticancer drug discovery using artificial intelligence: an application in pharmacological activity prediction

Hematological cancers are a heterogeneous family of diseases that can be divided into leukemias, lymphomas, and myelomas, often called “liquid tumors”. Since they cannot be surgically removable, chemotherapy represents the mainstay of their treatment. However, it still faces several challenges like drug resistance and low response rate, and the need for new anticancer agents is compelling. The drug discovery process is long-term, costly, and prone to high failure rates. With the rapid expansion of biological and chemical "big data", some computational techniques such as machine learning tools have been increasingly employed to speed up and economize the whole process. Machine learning algorithms can create complex models with the aim to determine the biological activity of compounds against several targets, based on their chemical properties. These models are defined as multi-target Quantitative Structure-Activity Relationship (mt-QSAR) and can be used to virtually screen small and large chemical libraries for the identification of new molecules with anticancer activity. The aim of my Ph.D. project was to employ machine learning techniques to build an mt-QSAR classification model for the prediction of cytotoxic drugs simultaneously active against 43 hematological cancer cell lines. For this purpose, first, I constructed a large and diversified dataset of molecules extracted from the ChEMBL database. Then, I compared the performance of different ML classification algorithms, until Random Forest was identified as the one returning the best predictions. Finally, I used different approaches to maximize the performance of the model, which achieved an accuracy of 88% by correctly classifying 93% of inactive molecules and 72% of active molecules in a validation set. This model was further applied to the virtual screening of a small dataset of molecules tested in our laboratory, where it showed 100% accuracy in correctly classifying all molecules. This result is confirmed by our previous in vitro experiments.

SmartForge: An event-driven architecture for simulator-based process optimization

In the metal industry, and more specifically in the forging one, scrap material is a crucial issue and reducing it would be an important goal to reach. Not only would this help the companies to be more environmentally friendly and more sustainable, but it also would reduce the use of energy and lower costs. At the same time, the techniques for Industry 4.0 and the advancements in Artificial Intelligence (AI), especially in the field of Deep Reinforcement Learning (DRL), may have an important role in helping to achieve this objective. This document presents the thesis work, a contribution to the SmartForge project, that was performed during a semester abroad at Karlstad University (Sweden). This project aims at solving the aforementioned problem with a business case of the company Bharat Forge Kilsta, located in Karlskoga (Sweden). The thesis work includes the design and later development of an event-driven architecture with microservices, to support the processing of data coming from sensors set up in the company's industrial plant, and eventually the implementation of an algorithm with DRL techniques to control the electrical power to use in it.

[meanings Of The Sickening Process For Patients With Systemic Lupus Erythematosus: A Review Of The Literature.]

Systemic lupus erythematosus is an autoimmune disease that causes many psychological repercussions that have been studied through qualitative research. These are considered relevant, since they reveal the amplitude experienced by patients. Given this importance, this study aims to map the qualitative production in this theme, derived from studies of experiences of adult patients of both genders and that had used as a tool a semi-structured interview and/or field observations, and had made use of a sampling by a saturation criterion to determine the number of participants in each study. The survey was conducted in Pubmed, Lilacs, Psycinfo e Cochrane databases, searching productions in English and Portuguese idioms published between January 2005 and June 2012. The 19 revised papers that have dealt with patients in the acute phase of the disease showed themes that were categorized into eight topics that contemplated the experienced process at various stages, from the onset of the disease, extending through the knowledge of the diagnosis and the understanding of the manifestations of the disease, drug treatment and general care, evolution and prognosis. The collected papers also point to the difficulty of understanding, of the patients, on what consists the remission phase, revealing also that this is a clinical stage underexplored by psychological studies.

[in Process Citation].

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A estimulação da inteligencia corporal cinestesica no contexto na educação fisica escolar

Universidade Estadual de Campinas. Faculdade de Educação Física