A CLUSTERING OF DJA STOCKS - THE APPLICATION IN FINANCE OF A METHOD FIRST USED IN GENE TRAJECTORY STUDY

Previously we employed the Gene Trajectory Clustering methodology to search for different associations of the stocks composing the DJA index, with the aim of finding different, logic clusters, supported by economic reasons, preferably different than theclustering model, data trajectory, cluster analysis

A FUNCTIONAL SKETCH FOR RESOURCES MANAGEMENT IN COLLABORATIVE SYSTEMS FOR BUSINESS

This paper presents a functional design sketch for the resource management module of a highly scalable collaborative system. Small and medium enterprises require such tools in order to benefit from and develop innovative business ideas and technologies. As computing power is a modern increasing demand and no easy and cheap solutions are defined, especially small companies or emerging business projects abide a more accessible alternative. Our work targets to settle a model for how P2P architecture can be used as infrastructure for a collaborative system that delivers resource access services. We are focused on finding a workable collaborative strategy between peers so that the system offers a cheap, trustable and quality service. Thus, in this phase we are not concerned about solutions for a specific type of task to be executed by peers, but only considering CPU power as resource. This work concerns the resource management module as a part of a larger project in which we aim to build a collaborative system for businesses with important resource demandsresource management, p2p, open-systems, service oriented computing, collaborative systems

Full Paper: Ontology-Based Dialogue System for Domain-Specific Knowledge Acquisition

Building task-oriented dialogue systems for solving specific tasks within companies represents a challenging research objective especially when the specific expertise of the company is not yet machine-readable formalized. Aiming to collect the specific knowledge in a company-scope knowledge graph, we design the architecture of a dialog system integrating the natural language processing modules with the specific concepts described in the domain ontology and the com- pany’s graph of instances. The described system helps growing the knowledge graph with the specific company data, while also providing the NLP building blocks for a future dialog system specifically tuned for the requirements of the target company processes

Implementing and Running a Workflow Application on Cloud Resources

Scientist need to run applications that are time and resource consuming, but, not all of them, have the requires knowledge to run this applications in a parallel manner, by using grid, cluster or cloud resources. In the past few years many workflow building frameworks were developed in order to help scientist take a better advantage of computing resources, by designing workflows based on their applications and executing them on heterogeneous resources. This paper presents a case study of implementing and running a workflow for an E-bay data retrieval application. The workflow was designed using Askalon framework and executed on the cloud resources. The purpose of this paper is to demonstrate how workflows and cloud resources can be used by scientists in order to achieve speedup for their application without the need of spending large amounts of money on computational resources.Workflow, Cloud Resource

The citizens’ perspective : awareness, feelings and acceptance of surveillance and surveillance systems for fighting crime in Romania. A quantitative study

This document presents the results for Romania within the framework of a larger study undertaken as part of the RESPECT project – “Rules, Expectations and Security through Privacy-enhanced Convenient Technologies” (RESPECT; G.A. 285582) – which was co-financed by the European Commission within the Seventh Framework Programme (2007-2013). Analyses are based on a survey regarding the perceptions, feelings, attitudes and behaviours of citizens towards surveillance for the purpose of fighting crime, carried out amongst a quota sample that is representative of the population in Romania for age and gender. Responses were gathered, predominantly, through an online survey supplemented by a number of questionnaires administered in face to face interviews, in order to fulfil the quota and also reach those citizens who do not use the internet. The questionnaire consisted of 50 questions and was available online in all languages of the European Union between November 2013 and March 2014. The face to face interviews were carried out between December 2013 and March 2014. The sample is based on the responses from 200 individuals who indicated Romania as their country of residence in the online survey or were administered the questionnaire face to face. As a result, the Romanian respondents indicated a strongly felt lack of trust in the protection of, and control over, personal information gathered via surveillance. Further, the majority of respondents feel more happy than unhappy with the different types of surveillance (except surveillance using databases containing personal information), but they feel more unhappy than happy about surveillance taking place without them knowing about it. Additionally, there is no link between feeling happy, or unhappy, about surveillance and feeling secure or insecure through the presence of surveillance. Romanian respondents appear to have two distinct, and very different, reactions to surveillance. Some people feel secure in the presence of surveillance, but in others surveillance produces feelings of insecurity. However, analyses also indicate that increasing citizens’ belief in the effectiveness of laws regarding the protection of personal data gathered via surveillance may make reduce citizens’ feelings of insecurity more than only increasing the effectiveness of surveillance measures. More research is needed to disentangle the relationships and effects between surveillance measures, feelings of security or insecurity, and citizens’ general quality of life feelings.This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no 285582.peer-reviewe

Expected Utility and Risk Management in Complex Projects

Much research has been conducted to the study of methods for managing ISD projects. This resulted in a large amount of literature on a variety of often normative ISD methods. The increasing projects\u27 complexity provide new challenges regarding management and development. In complex projects scenarios where the outcome is composed of several deployed components, guaranteeing specific contract requirements for the prime contractor of the project is a real challenge. The focus of this paper is to find appropriate methods to facilitate end-to-end contract parameters in complex projects environments by automated supply chain formation and to establish and enforce contract parameters between each pair of component consumer/provider. Communication between agents along the supply chain is done by message exchange and provides propagation of constraints between subcontractors in the supply chain. Our findings reveal that the proposed method is able to address the emerging issues arising in complex projects

Marrying Big Data with Smart Data in Sensor Stream Processing

Widespread deployments of spatially distributed sensors are continuously generating data that require advanced analytical processing and interpretation by machines. Devising machine-interpretable descriptions of sensor data is a key issue in building a semantic stream processing engine. This paper proposes a semantic sensor stream processing pipeline using Apache Kafka to publish and subscribe semantic data streams in a scalable way. We use the Kafka Consumer API to annotate the sensor data using the Semantic Sensor Network ontology, then store the annotated output in an RDF triplestore for further reasoning or semantic integration with legacy information systems. We follow a Design Science approach addressing a Smart Airport scenario with geolocated audio sensors to evaluate the viability of the proposed pipeline under various Kafka-based configurations. Our experimental evaluations show that the multi-broker Kafka cluster setup supports read scalability thus facilitating the parallelization of the semantic enrichment of the sensor data

Risks and Assets: A Qualitative Study of a Software Ecosystem in the Mining Industry

Digitalization and servitization are impacting many domains, including the mining industry. As the equipment becomes connected and technical infrastructure evolves, business models and risk management need to adapt. In this paper, we present a study on how changes in asset and risk distribution are evolving for the actors in a software ecosystem (SECO) and system-of-systems (SoS) around a mining operation. We have performed a survey to understand how Service Level Agreements (SLAs) -- a common mechanism for managing risk -- are used in other domains. Furthermore, we have performed a focus group study with companies. There is an overall trend in the mining industry to move the investment cost (CAPEX) from the mining operator to the vendors. Hence, the mining operator instead leases the equipment (as operational expense, OPEX) or even acquires a service. This change in business model impacts operation, as knowledge is moved from the mining operator to the suppliers. Furthermore, as the infrastructure becomes more complex, this implies that the mining operator is more and more reliant on the suppliers for the operation and maintenance. As this change is still in an early stage, there is no formalized risk management, e.g. through SLAs, in place. Rather, at present, the companies in the ecosystem rely more on trust and the incentives created by the promise of mutual future benefits of innovation activities. We believe there is a need to better understand how to manage risk in SECO as it is established and evolves. At the same time, in a SECO, the focus is on cooperation and innovation, the companies do not have incentives to address this unless there is an incident. Therefore, industry need, we believe, help in systematically understanding risk and defining quality aspects such as reliability and performance in the new business environment

Topic Classification for Short Texts

In the context of TV and social media surveillance, constructing models to automate topic identification of short texts is key task. This paper formalizes the topic classification as a top-K multinomial classification problem and constructs worth-to-consider models for practical usage. We describe the full data processing pipeline, discussing about dataset selection, text preprocessing, feature extraction, model selection and learning, including hyperparameter optimization. When computing time and resources are limited, we show that a classical model like SVM performs as well as an advanced deep neural network, but with shorter model training time

Risk assessment in service provider communities

On-line service delivery undertaken between clients and service providers often incurs risks for both the client and the provider, especially when such an exchange takes place in the context of an electronic service market. For the client, the risk involves determining whether the requested service will be delivered on time and based on the previously agreed Service Level Agreement (SLA). Often risk to the client can be mitigated through the use of a penalty clause in an SLA. For the provider, the risk revolves around ensuring that the client will pay the advertised price and more importantly whether the provider will be able to deliver the advertised service to not incur the penalty identified in the SLA. This becomes more significant when the service providers outsource the actual enactment/execution to a data centre–a trend that has become dominant in recent years, with the emergence of infrastructure providers such as Amazon. In this work we investigate the notion of “risk” from a variety of different perspectives and demonstrate how risk to a service owner (who uses an external, third party data centre for service hosting) can be managed more effectively. A simulation based approach is used to validate our findings