An Approach to Model Checking of Multi-agent Data Analysis

The paper presents an approach to verification of a multi-agent data analysis algorithm. We base correct simulation of the multi-agent system by a finite integer model. For verification we use model checking tool SPIN. Protocols of agents are written in Promela language and properties of the multi-agent data analysis system are expressed in logic LTL. We run several experiments with SPIN and the model.Comment: In Proceedings MOD* 2014, arXiv:1411.345

Верификация алгоритмов мультиагентного анализа данных с помощью системы проверки моделей SPIN

The paper presents an approach to formal verification of multi-agent data analysis algorithms for ontology population. The system agents correspond to information items of the input data and the rule of ontology population and data processing. They determine values of information objects obtained at the preliminary phase of the analysis. The agents working in parallel check the syntactic and semantic consistency of tuples of information items. Since the agents operate in parallel, it is necessary to verify some important properties of the system related to it, such as the property that the controller agent correctly determines the system termination. In our approach, the model checking tool SPIN is used. The protocols of agents are written in Promela language (the input language of the tool) and the properties of the multi-agent data analysis system are expressed in the liner time logic LTL. We carried out several experiments to check this model in various modes of the tool and various numbers of agents.В статье представлен подход к формальной верификации алгоритмов мультиагентного анализа данных для пополнения онтологий. Агенты системы на основе входных данных устанавливают значения элементов объектов, полученных на предварительной стадии анализа. Агенты параллельно осуществляют проверку семантической и синтаксической согласованности, используя правила пополнения онтологий и обработки данных. Поскольку агенты действуют параллельно, необходимо верифицировать некоторые важные свойства системы, связанные с этим, например, свойство корректности определения завершения работы системы. В нашем подходе используется инструмент проверки моделей SPIN. Протоколы агентов записаны на языке Promela, а свойства мультиагентной системы анализа данных выражены в логике LTL. Мы провели ряд экспериментов по проверке данной модели

CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges

Improving Cloud Governance by Increasing Observability

Rise in popularity of Cloud computing has introduced new challenges for IT-governance. The multitude of different services and possible configurations Cloud providers offer can make it hard to get a comprehensive overview of the environment. To successfully govern an organisations Cloud environment it is important to be able to easily make accurate and reliable observations of the environments state, security, and changes to the configurations. This thesis takes a look into the research literature to find out what kinds of risks have been identified in governing the Cloud environment and ways to mitigate them. One of the latest advancements in improving the Cloud governance is the introduction of automated formal reasoning tools for configuration analysis. One customer case where multiple vendors are building services on multiple cloud accounts is used as an example. Architecture for application, security, and audit log collection, indexing, and monitoring is described. Special attention is given to the identity and access management requirements. The thesis concludes with the assessment of the selected approach and tools and services used to implement it. Some alternative solutions, possible improvements, and further development to the implementation are considered

Automatic classification of complaints from public administration

Complaint management is a problem faced by many organizations that is both vital to customer satisfaction and retention, while being highly dependent on human resources. This work attempts to tackle a part of the problem, by classifying summaries of complaints using machine learning models in order to better redirect these to the appropriate responders. To solve the aforementioned problem text mining, and more specifically natural language processing, were used alongside machine learning algorithms for automatic classification. The main challenge of this task is related with the diverse set of characteristics real world datasets have, in this case being small and highly imbalanced. This can have a big impact on the performance of the classification models. The dataset analyzed in this work suffers from both of these problems, being relatively small and having labels in different proportions the three most common labels account for around 95% the dataset. In this work, two different techniques are analyzed: multistage classification with for classifying the more common labels first and the remaining on a second step; and, generating new artificial examples for some classes via translation into other languages. The classification models explored were the following: k-NN, SVM, Naïve Bayes, boosting, and Deep Learning approaches, including transformers. Although, in general using summaries leads to better results, we also experimented with the full documents. Using the models trained with the summarized documents the classification of the full documents. Even though the results were not on par with the summarized dataset the experimented presented good results for signaling the most common label of the documents. We conclude that although, as expected, the classes with little representation are hard to classify, the techniques explored helped to boost the performance, especially in the classes with a low number of elements. SVM and Transformer-based models outperformed their peers.A classificação de texto é uma área de estudo em aberto, dependendo do problema dos dados disponíveis e estudo em questão, o melhor método nem sempre é mesmo. Dentro da área da inteligência artificial No caso das empresas a classificação de queixas (como neste trabalho) ou mesmo de incidentes é uma tarefa que ainda requer muito trabalho manual. Neste trabalho vai ser abordada a classificação automática de queixas recebidas por uma instituição pública. No processo de tratamento das queixas a classificação é parte do grande panorama e a sua automatização permite acelerar muito os processos manuais que são actualmente usados. Neste contexto, foram trabalhados os sumários das queixas e as técnicas usadas para aplicar modelos de classificação automática. O conjunto de dados é consideravelmente pequeno e apresenta um grande desequilíbrio na distribuição das classes, sendo que as três maiores têm perto de 95% dos dados. Para colmatar este problema foram analisadas duas abordagens: classificação em duas etapas e aumento do conjunto de treino com base em traduções dos sumários. Neste contexto foram usados alguns modelos de classificação como k-NN, SVM, Naïve Bayes, boosting e BERT. Usando modelos treinados com os sumários foi também realizada uma experiência de classificação dos textos completos das queixas. Apesar dos resultados serem piores do que os obtidos usando o dados resumidos, estes apresentam alguma taxa de sucesso, especialmente para classificação da classe mais frequente. Com base neste trabalho foi possível concluir que a classificação das classes com menos representação é um desafio, mas através de técnicas de aumento do conjunto de treino é possível melhorar substancialmente o resultado obtido. Também utilizar uma estratégia de classificação multietapa permite melhorar os resultados obtidos. Os melhores modelos para a classificação foram SVM e BERT

Сучасні виміри лінгвістики та комунікації: моделі розвитку мови у цифровому середовищі: навчальний посібник

The manual presents theoretical and practical explanations for preparation students on the actualization of modeling of the innovative logosphere of modern digital environment Complex modeling of the field of digital technologies with a view to innovative language, as well as phenomenological parameters, contributes to a more complete the study of the nature of the linguistic environment of the tsifir environment. A similar approach allows consider ontological (time-space) aspects of reality in their lexical-semantic coverage, to investigate in detail the human phenomenon, its complex linguo-categorical positioning within the existential digital linguosphere, determine the basics logocentricity of the modern digital environment and predict directions development of language models in digital communication. The guide is addressed to philology students studying the module "Modern aspects of linguistics and language communication: General models of language development in digital environment".У посібнику представлено теоретико-практичні викладки для підготовки студентів з актуалізації моделювання інноваційної логосфери сучасного цифрового середовища. Комплексне моделювання сфери цифрових технологій з огляду як на інноваційні мовні, так і на феноменологічні параметри, сприяє більш повному вивченню природи лінгвосфери цфирового середовища. Подібний підхід дозволяє розглянути онтологічні (часо-просторові) аспекти дійсності в їх лексико-семантичному висвітленні, детально дослідити феномен людини, її комплексне лінгвокатегоріальне позиціонування в межах екзистенційної цифрової лінгвосфери, визначити засади логоцентричності сучасного цифрового середовища та спрогнозувати напрямки розвитку мовних моделей у цифровій комунікації. Посібник адресовано студентам-філологам, які вивчають модуль «Сучасні аспекти лінгвістики та мовної комунікації: Загальні моделі розвитку мови у цифровому середовищі»

A framework for active software engineering ontology

The passive structure of ontologies results in the ineffectiveness to access and manage the knowledge captured in them. This research has developed a framework for active Software Engineering Ontology based on a multi-agent system. It assists software development teams to effectively access, manage and share software engineering knowledge as well as project information to enable effective and efficient communication and coordination among teams. The framework has been evaluated through the prototype system as proof-of-concept experiments

Unfolding plant desiccation tolerance : evolution, structure, and function of LEA proteins

When plants colonized land they developed a wide range of adaptations to cope with life in a drier environment. One key adaptation was desiccation tolerance (DT) which is the ability to survive the removal of almost all cellular water without irreparable damage. DT is recurrent in orthodox seeds and in the vegetative body of species commonly known as ‘resurrection plants’. In this thesis a multilevel approach, combining genomics, transcriptomics, gene family evolution, protein structural and functional analysis, and seed physiology was employed in order to tackle curiosity-driven fundamental questions about the major mechanisms governing DT. Several mechanisms were found to be important for DT, including the coordinated activation of cell protection through Late Embryogenesis Abundant (LEA) proteins, which were shown to be common amongst resurrection plants and orthodox seeds. These findings aid to the comprehension of the complexity of DT in plants, and may provide transferrable knowledge to design more water-stress tolerant crops.</p

New Fundamental Technologies in Data Mining

The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining

Developing Constrained p27 Peptides to Target the Oncogenic E3 Ubiquitin Ligase SCF-Skp2

The ubiquitin-proteasome system (UPS) maintains homeostatic levels of proteins in normal cells and controls the levels of oncogenes and tumour suppressors by tagging proteins with ubiquitin for proteasomal degradation. The UPS is regulated by sequential action of three enzymes: E1 – ubiquitin activating enzyme, E2 - ubiquitin conjugating enzyme, and E3 - ubiquitin ligase. The SCF-Skp2 complex is one of 600 E3s in the human genome, and Skp2 serves as a substrate recognition subunit. Skp2 is an oncoprotein that exerts its oncogenic functions through degradation of specific substrates. A major target of SCF-Skp2 is the cyclin-dependent kinase inhibitor p27 which positively regulates cell cycle progression. Elevated levels of Skp2 and reduced levels of p27 are common in a variety of cancers, including lymphomas and breast and prostate carcinomas. A lack of suitable binding pockets in Skp2 and the intrinsically disordered nature of p27 make this protein-protein interaction (PPI) challenging for conventional small molecule approaches. We aim to develop instead a macrocyclic peptide inhibitor for this PPI. We have designed and synthesised p27 peptides containing unnatural amino acids and successfully constrained them using ‘click’ chemistry. The dissociation constants show that the constrained peptides (CPs) have dramatically higher affinities for the Cks1-Skp2- Skp1 complex compared with the linear (unconstrained) p27 peptide. The 30 nM affinity of the tightest binding peptide is almost two orders of magnitude higher than that of the linear peptide (3 μM). We suggest that this large enhancement of affinity arises because the binding-competent form of the peptide has a tight turn-like conformation, which is very effectively constrained by the macrocyclic linker. The CPs were also shown to inhibit p27 ubiquitination in vitro. Interestingly, the CPs also inhibited the ubiquitination of two other Skp2 substrates, p21 and N-myc, to varying degrees. A number of different approaches were taken to deliver the CPs into cells and investigate their effect on p27 protein levels and on cellular proliferation. CPs were able to restore p27 levels associated with Skp2 over-expression as well as reduce proliferation of breast cancer cell line MCF-7. We additionally investigated a different route to constrain the p27 sequence by grafting it onto a loop of a small, stable protein scaffold. These grafted proteins were also able to inhibit p27 ubiquitination. Lastly, we constructed novel proteolysis-targeting proteins (polyproxins) that hijack SCF-Skp2 and direct it to drive the destruction of disease-causing proteins. We generated a library of polyproxins, combining a module that binds a cancer-associated protein, β-catenin, with a module that binds Skp2. β-catenin ubiquitination and degradation in cells was successfully demonstrated using these polyproxins