Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

Data Mining - Concepts and Techniques.

Data Mining Practical Machine Learning Tools and Techniques

How to Do Things With Words

Modern software systems are deployed in sociotechnical settings, combining social entities (humans and organizations) with technical entities (software and devices). In such settings, on top of technical controls that implement security features of software, regulations specify how users should behave in security-critical situations. No matter how carefully the software is designed and how well regulations are enforced, such systems are subject to breaches due to social (user misuse) and technical (vulnerabilities in software) factors. Breach reports, often legally mandated, describe what went wrong during a breach and how the breach was remedied. However, breach reports are not formally investigated in current practice, leading to valuable lessons being lost regarding past failures. Our research aim is to aid security analysts and software developers in obtaining a set of legal, security, and privacy requirements, by developing a crowdsourcing methodology to extract knowledge from regulations and breach reports. We present Corba, a methodology that leverages human intelligence via crowdsourcing, and extracts requirements from textual artifacts in the form of regulatory norms. We evaluate Corba on the US healthcare regulations from the Health Insurance Portability and Accountability Act (HIPAA) and breach reports published by the US Department of Health and Human Services (HHS). Following this methodology, we have conducted a pilot and a final study on the Amazon Mechanical Turk crowdsourcing platform. Corba yields high quality responses from crowd workers, which we analyze to identify requirements for the purpose of complementing HIPAA regulations. We publish a curated dataset of the worker responses and identified requirements. The results show that the instructions and question formats presented to the crowd workers significantly affect the response quality regarding the identification of requirements. We have observed significant improvement from the pilot to the final study by revising the instructions and question formats. Other factors, such as worker types, breach types, or length of reports, do not have notable effect on the workers’ performance. Moreover, we discuss other potential improvements such as breach report restructuring and text highlighting with automated methods.

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Çorba: crowdsourcing to obtain requirements from regulations and breaches

We are developing an approach for P2P information systems, where the peers are modelled as autonomous agents. Agents provide services or give referrals to one another to help find trustworthy services. We consider the important case of information services that can be cached. Agents request information services through high-level queries, not by describing specific objects as in caching in traditional distributed systems. Moreover, the agents autonomously decide whom to contact for a service, whom to provide a service or referral, whether to follow a referral and whether to cache a service. Thus the information system itself evolves as agents learn about each other and the contents of the caches of the agents change. We study here the effect of caching on service location and on the information system itself. Our main results are that, (1) even with a small cache, agents can locate services more easily; (2) since the agents that cache services can act like service providers, a small number of initial service providers are enough to serve the information needs of the consumers; and (3) agents benefit from being neighbours with others who have similar interests.

Trustworthy service caching: Cooperative search in P2P information systems

The Internet provides the backdrop for an important technical controversy in the domain of telecommunications. Like all good technical controversies, this one is political as well.The controversy is interesting to computer scientists because it helps focus our thinking on system design and evolution, and because it gives us an opportunity to reflect on the nature of the Internet. To highlight some differences in a brief format, I will present the controversy in the style of the Hegelian dialectic (admittedly, though, with oversimplifications).

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The Intelligence Within

We address the problem of usage license administration in federated settings. This problem arises whenever organizations, such as educational or research groups or institutions, share resources for business and scientific reasons. In such settings, each user's usage of a licensed resource is typically supported by the user's organization. License administration involves satisfying legal requirements while applying organizational strategies for effective resource usage, and carrying out suitable accounting and audit controls. We propose an approach, Licit, wherein an agent represents each resource sharing site and administers licenses in collaboration with other agents. We show how to represent a variety of usage licenses formally as executable policies and provide a simple information model using which each party can specify both the attributes involved in its licenses and how to resolve them. Our architecture naturally accommodates a variety of site-specific (i.e., custom) strategies for license administration. Licit has been implemented in a popular open source framework for virtual computing, and yields performance results indicating its practical feasibility.

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Licit: Administering Usage Licenses in Federated Environments

In the modern era of globalization, an alarming increment in energy consumption is perceived all over the world which results in the scarcity of primary energy resources in the near future. Due to expeditious economic growth and increasing population, many countries are planning to explore existing Renewable Energy (RE) sources to fulfill increasing energy demand. Selection of suitable alternative RE must be addressed in multi-criteria decision making (MCDM) problem because it involves multiple criteria which are conflicting in nature. This paper proposes an integrated method which is a combination of Additive Ratio Assessment (ARAS) method and Z-numbers. The proposed method namely ARAS-Z, Z-number is used to consider the degree of self-confidence along with the fuzzy number to handle the uncertainty involved in the human judgment used in the evaluation of criteria weights. ARAS is applied for the assessment and prioritization of feasible alternative RE sources based on utility degree. A comparative analysis of the proposed method is done with other MCDM methodologies for checking the effectiveness and capability of the proposed methodology.

Munindar P. Singh

Papers

Çorba: crowdsourcing to obtain requirements from regulations and breaches

Trustworthy service caching: Cooperative search in P2P information systems

The Intelligence Within

Licit: Administering Usage Licenses in Federated Environments

Selection of Optimal Renewable Energy Resources in Uncertain Environment Using ARAS-Z Methodology