Sensor Intelligence for Tackling Energy-Drain Attacks on Wireless Sensor Networks

In this paper we propose a model for intelligent agents (sensors) on a Wireless Sensor Network to guard against energy-drain attacks in an energy-efficient and autonomous manner. This is intended to be achieved via an energy-harvested Wireless Sensor Network using a novel architecture to propagate knowledge to other sensors based on automated reasoning from an attacked sensor.

Secure and Scalable Statistical Computation of Questionnaire Data in R

Collecting data via a questionnaire and analyzing them while preserving respondents’ privacy may increase the number of respondents and the truthfulness of their responses. It may also reduce the systematic differences between respondents and non-respondents. In this paper, we propose a privacy-preserving method for collecting and analyzing survey responses using secure multi-party computation (SMC). The method is secure under the semi-honest adversarial model. The proposed method computes a wide variety of statistics. Total and stratified statistical counts are computed using the secure protocols developed in this paper. Then, additional statistics, such as a contingency table, a chi-square test, an odds ratio, and logistic regression, are computed within the R statistical environment using the statistical counts as building blocks. The method was evaluated on a questionnaire dataset of 3,158 respondents sampled for a medical study and simulated questionnaire datasets of up to 50,000 respondents. The computation time for the statistical analyses linearly scales as the number of respondents increases. The results show that the method is efficient and scalable for practical use. It can also be used for other applications in which categorical data are collected.

The Communicative Dimension and Security in Asia-Pacific: A communicative-viewing proposal for reform of the Japanese Intelligence Services

The postwar development of the Intelligence Services in Japan has been based on two contrasting models: the centralized model of the USA and the collegiality of UK, neither of which has been fully developed. This has led to clashes of institutional competencies and poor anticipation of threats towards national security. This problem of opposing models has been partially overcome through two dimensions: externally through the cooperation with the US Intelligence Service under the Treaty of Mutual Cooperation and Security; and internally though the pre-eminence in the national sphere of the Department of Public Safety. However, the emergence of a new global communicative dimension requires that a communicative-viewing remodeling of this dual model is necessary due to the increasing capacity of the individual actors to determine the dynamics of international events. This article examines these challenges for the Intelligence Services of Japan and proposes a reform based on this new global communicative dimension.

A Scalable General Purpose System for Large-Scale Graph Processing

Graph analytics is an important and computationally demanding class of data analytics. It is essential to balance scalability, ease-of-use and high performance in large scale graph analytics. As such, it is necessary to hide the complexity of parallelism, data distribution and memory locality behind an abstract interface. The aim of this work is to build a scalable graph analytics framework that does not demand significant parallel programming experience based on NUMA-awareness.
The realization of such a system faces two key problems:
(i)~how to develop a scale-free parallel programming framework that scales efficiently across NUMA domains; (ii)~how to efficiently apply graph partitioning in order to create separate and largely independent work items that can be distributed among threads.

Leadership and emotional intelligence in nursing and midwifery education and practice: a discussion paper

Aim
A discussion of the concepts of leadership and emotional intelligence in nursing and midwifery education and practice.

Background
The need for emotionally intelligent leadership in the health professions is acknowledged internationally throughout the nursing and midwifery literature. The concepts of emotional intelligence and emotional-social intelligence have emerged as important factors for effective leadership in the healthcare professions and require further exploration and discussion. This paper will explore these concepts and discuss their importance in the healthcare setting with reference to current practices in the UK, Ireland and internationally.

Design
Discussion paper.

Data sources
A search of published evidence from 1990–2015 using key words (as outlined below) was undertaken from which relevant sources were selected to build an informed discussion.

Implications for nursing/midwifery
Fostering emotionally intelligent leadership in nursing and midwifery supports the provision of high quality and compassionate care. Globally, leadership has important implications for all stakeholders in the healthcare professions with responsibility for maintaining high standards of care. This includes all grades of nurses and midwives, students entering the professions, managerial staff, academics and policy makers.

Conclusion
This paper discusses the conceptual models of leadership and emotional intelligence and demonstrates an important link between the two. Further robust studies are required for ongoing evaluation of the different models of emotional intelligence and their link with effective leadership behaviour in the healthcare field internationally. This is of particular significance for professional undergraduate education to promote ongoing compassionate, safe and high quality standards of care.

Mandevillian Intelligence: From Individual Vice to Collective Virtue

Abstract Mandevillian intelligence is a specific form of collective intelligence in which individual cognitive vices (i.e., shortcomings, limitations, constraints and biases) are seen to play a positive functional role in yielding collective forms of cognitive success. In this talk, I will introduce the concept of mandevillian intelligence and review a number of strands of empirical research that help to shed light on the phenomenon. I will also attempt to highlight the value of the concept of mandevillian intelligence from a philosophical, scientific and engineering perspective. Inasmuch as we accept the notion of mandevillian intelligence, then it seems that the cognitive and epistemic value of a specific social or technological intervention will vary according to whether our attention is focused at the individual or collective level of analysis. This has a number of important implications for how we think about the cognitive impacts of a number of Web-based technologies (e.g., personalized search mechanisms). It also forces us to take seriously the idea that the exploitation (or even the accentuation!) of individual cognitive shortcomings could, in some situations, provide a productive route to collective forms of cognitive and epistemic success. Speaker Biography Dr Paul Smart Paul Smart is a senior research fellow in the Web and Internet Science research group at the University of Southampton in the UK. He is a Fellow of the British Computer Society, a professional member of the Association of Computing Machinery, and a member of the Cognitive Science Society. Paul’s research interests span a number of disciplines, including philosophy, cognitive science, social science, and computer science. His primary area of research interest relates to the social and cognitive implications of Web and Internet technologies. Paul received his bachelors degree in Psychology from the University of Nottingham. He also holds a PhD in Experimental Psychology from the University of Sussex.

Progettazione di un sistema di Location Intelligence per una multiutility

Le informazioni di tipo geografico caratterizzano più dell'80% dei dati utilizzati nei processi decisionali di ogni grande azienda e la loro pervasività è in costante aumento. La Location Intelligence è un insieme di strumenti, metodologie e processi nati con l'obiettivo di analizzare e comprendere a pieno il patrimonio informativo presente in questi dati geolocalizzati. In questo progetto di tesi si è sviluppato un sistema completo di Location Intelligence in grado di eseguire analisi aggregate dei dati georeferenziati prodotti durante l'operatività quotidiana di una grande azienda multiservizi italiana. L’immediatezza dei report grafici e le comparazioni su serie storiche di diverse sorgenti informative integrate generano un valore aggiunto derivante dalle correlazioni individuabili solo grazie a questa nuova dimensione di analisi. In questo documento si illustrano tutte le fasi caratterizzanti del progetto, dalla raccolta dei requisiti utente fino all’implementazione e al rilascio dell’applicativo, concludendo con una sintesi delle potenzialità di analisi generate da questa specifica applicazione e ai suoi successivi sviluppi.

Combinative Aspects of Leadership Style and Emotional Intelligence

Purpose – The purpose of this paper is to examine whether the leader’s emotional intelligence influences the leader’s preferences for different ways of combining leadership behaviors (i.e. combinative aspects of leadership style). Design/methodology/approach – The authors used a hybrid design to collect the data to avoid common-method biases. The authors described a high-stress workplace in a vignette and asked participants to rank four styles of combining a task-oriented leadership (i.e. Pressure) statement and a socio-emotional leadership (i.e. Support) statement. The authors then asked participants to complete a Likert-scale based questionnaire on emotional intelligence. Findings – The authors found that leaders who prefer to provide Support immediately before Pressure have higher levels of emotional intelligence than do leaders who prefer the three other combinative styles. Leaders who prefer to provide Pressure and Support separately (i.e. provide Pressure 30 minutes after Support) have the lowest levels of emotional intelligence. Research limitations/implications – A key implicit assumption in the work is that leaders do not want to evoke negative emotions in followers. The authors did not take into account factors that influence leadership style which participating managers would be likely to encounter on a daily basis such as the relationship with the follower, the follower’s level of performance and work experience, the gender of the leader and the gender of the follower, the hierarchical levels of the leader and follower, and the followers’ preferred combinative style. The nature of the sample and the use of a hypothetical scenario are other limitations of the study. Practical implications – Providing leadership behaviors that are regarded as effective is necessary but not enough because the emotional impact of leadership behaviors appears to also depend on how the behaviors are configured. Originality/value – This is the first study to show that the emotional intelligence of leaders is related to their preferences for the manner in which they combine task and social leadership statements. Furthermore, two-factor theories of leadership propose that the effects of task and social leadership are additive. However, the findings show that the effects are interactive.

Scenari applicativi per Smart Home su piattaforma Home Manager: verso il livello intelligence

Analisi degli scenari applicativi in ambiente Home Manager e progettazione, implementazione e collaudo di alcune delle funzionalità proposte.

La Business Intelligence per il monitoraggio delle vendite: il caso Ducati Motor Holding

“La Business Intelligence per il monitoraggio delle vendite: il caso Ducati Motor Holding”. L’obiettivo di questa tesi è quello di illustrare cos’è la Business Intelligence e di mostrare i cambiamenti verificatisi in Ducati Motor Holding, in seguito alla sua adozione, in termini di realizzazione di report e dashboard per il monitoraggio delle vendite. L’elaborato inizia con una panoramica generale sulla storia e gli utilizzi della Business Intelligence nella quale vengono toccati i principali fondamenti teorici: Data Warehouse, data mining, analisi what-if, rappresentazione multidimensionale dei dati, costruzione del team di BI eccetera. Si proseguirà mediante un focus sui Big Data convogliando l’attenzione sul loro utilizzo e utilità nel settore dell’automotive (inteso nella sua accezione più generica e cioè non solo come mercato delle auto, ma anche delle moto), portando in questo modo ad un naturale collegamento con la realtà Ducati. Si apre così una breve overview sull’azienda descrivendone la storia, la struttura commerciale attraverso la quale vengono gestite le vendite e la gamma dei prodotti. Dal quarto capitolo si entra nel vivo dell’argomento: la Business Intelligence in Ducati. Si inizia descrivendo le fasi che hanno fino ad ora caratterizzato il progetto di Business Analytics (il cui obiettivo è per l'appunto introdurre la BI i azienda) per poi concentrarsi, a livello prima teorico e poi pratico, sul reporting sales e cioè sulla reportistica basata sul monitoraggio delle vendite.

A Scalable Design Framework for Variability Management in Large-Scale Software Product Lines

Variability management is one of the major challenges in software product line adoption, since it needs to be efficiently managed at various levels of the software product line development process (e.g., requirement analysis, design, implementation, etc.). One of the main challenges within variability management is the handling and effective visualization of large-scale (industry-size) models, which in many projects, can reach the order of thousands, along with the dependency relationships that exist among them. These have raised many concerns regarding the scalability of current variability management tools and techniques and their lack of industrial adoption. To address the scalability issues, this work employed a combination of quantitative and qualitative research methods to identify the reasons behind the limited scalability of existing variability management tools and techniques. In addition to producing a comprehensive catalogue of existing tools, the outcome form this stage helped understand the major limitations of existing tools. Based on the findings, a novel approach was created for managing variability that employed two main principles for supporting scalability. First, the separation-of-concerns principle was employed by creating multiple views of variability models to alleviate information overload. Second, hyperbolic trees were used to visualise models (compared to Euclidian space trees traditionally used). The result was an approach that can represent models encompassing hundreds of variability points and complex relationships. These concepts were demonstrated by implementing them in an existing variability management tool and using it to model a real-life product line with over a thousand variability points. Finally, in order to assess the work, an evaluation framework was designed based on various established usability assessment best practices and standards. The framework was then used with several case studies to benchmark the performance of this work against other existing tools.

Does Emotional Intelligence have a “Dark” Side? A Review of the Literature

Emotional intelligence (EI) was once touted as the ‘panacea’ for a satisfying and successful life. Consequently, there has been much emphasis on developing interventions to promote this personal resource in applied settings. Despite this, a growing body of research has begun to identify particular contexts when EI does not appear helpful and may even be deleterious to a person, or those they have contact with, suggesting a ‘dark’ side to the construct. This paper provides a review of emergent literature to examine when, why and how trait and ability EI may contribute to negative intrapersonal (psychological ill-health; stress reactivity) and interpersonal outcomes (emotional manipulation; antisocial behaviour). Negative effects were found to operate across multiple contexts (health, academic, occupational) however these were often indirect, suggesting that outcomes depend on pre-existing qualities of the person. Literature also points to the possibility of ‘optimal’ levels of EI – both within and across EI constructs. Uneven profiles of self-perceptions (trait facets) or actual emotional skills contribute to poorer outcomes, particularly emotional awareness and management. Moreover, individuals who possess high levels of skill but have lower self-perceptions of their abilities fare worse that those with more balanced profiles. Future research must now improve methodological and statistical practices to better capture EI in context and the negative corollary associated with high levels.