Granular computing as a tool of human data interaction - a cognitive cities use case

The article proposes granular computing as a theoretical, formal and methodological basis for the newly emerging research field of human–data interaction (HDI). We argue that the ability to represent and reason with information granules is a prerequisite for data legibility. As such, it allows for extending the research agenda of HDI to encompass the topic of collective intelligence amplification, which is seen as an opportunity of today’s increasingly pervasive computing environments. As an example of collective intelligence amplification in HDI, we introduce a collaborative urban planning use case in a cognitive city environment and show how an iterative process of user input and human-oriented automated data processing can support collective decision making. As a basis for automated human-oriented data processing, we use the spatial granular calculus of granular geometry.

BitWorker, a Decentralized Distributed Computing System based on BitTorrent

In this paper we present BitWorker, a platform for community distributed computing based on BitTorrent. Any splittable task can be easily specified by a user in a meta-information task file, such that it can be downloaded and performed by other volunteers. Peers find each other using Distributed Hash Tables, download existing results, and compute missing ones. Unlike existing distributed computing schemes relying on centralized coordination point(s), our scheme is totally distributed, therefore, highly robust. We evaluate the performance of BitWorker using mathematical models and real tests, showing processing and robustness gains. BitWorker is available for download and use by the community.

Facilitating Emotional Processing: An Experimental Induction of Psychotherapeutically Relevant Affective States

Psychotherapy research has shown that cognitive-affective meaning making is related to beneficial therapy outcomes. This study explores the underlying micro-processes by inducing specific cognitive-affective states and studying their immediate effects on emotional activation, the resolution of interpersonal grievances, and factors related to therapeutic progress, e.g., mastery experiences, clarification of meaning. Participants suffering from interpersonal grievances were randomly assigned to two conditions. A sentence completion task was employed to induce either the expression of emotional distress or cognitive-affective meaning making. Expressive writing was used to deepen processing. Findings of those participants adhering to the induction procedure (n = 85) showed no differences between conditions at baseline. During writing, participants in both conditions were equally emotionally activated. Directly after the writing task, participants in the meaning making condition (n = 50) reported less unresolved interpersonal grievances, and more mastery experiences, but, e.g., not more clarification, compared to those in the emotional expression condition (n = 35). Results suggest that engagement in specific states that promote meaning making of emotional experience facilitates emotional processing and is related to therapeutic benefit.

Service level agreements-driven management of distributed applications in cloud computing environments

Advancements in cloud computing have enabled the proliferation of distributed applications, which require management and control of multiple services. However, without an efficient mechanism for scaling services in response to changing workload conditions, such as number of connected users, application performance might suffer, leading to violations of Service Level Agreements (SLA) and possible inefficient use of hardware resources. Combining dynamic application requirements with the increased use of virtualised computing resources creates a challenging resource Management context for application and cloud-infrastructure owners. In such complex environments, business entities use SLAs as a means for specifying quantitative and qualitative requirements of services. There are several challenges in running distributed enterprise applications in cloud environments, ranging from the instantiation of service VMs in the correct order using an adequate quantity of computing resources, to adapting the number of running services in response to varying external loads, such as number of users. The application owner is interested in finding the optimum amount of computing and network resources to use for ensuring that the performance requirements of all her/his applications are met. She/he is also interested in appropriately scaling the distributed services so that application performance guarantees are maintained even under dynamic workload conditions. Similarly, the infrastructure Providers are interested in optimally provisioning the virtual resources onto the available physical infrastructure so that her/his operational costs are minimized, while maximizing the performance of tenants’ applications. Motivated by the complexities associated with the management and scaling of distributed applications, while satisfying multiple objectives (related to both consumers and providers of cloud resources), this thesis proposes a cloud resource management platform able to dynamically provision and coordinate the various lifecycle actions on both virtual and physical cloud resources using semantically enriched SLAs. The system focuses on dynamic sizing (scaling) of virtual infrastructures composed of virtual machines (VM) bounded application services. We describe several algorithms for adapting the number of VMs allocated to the distributed application in response to changing workload conditions, based on SLA-defined performance guarantees. We also present a framework for dynamic composition of scaling rules for distributed service, which used benchmark-generated application Monitoring traces. We show how these scaling rules can be combined and included into semantic SLAs for controlling allocation of services. We also provide a detailed description of the multi-objective infrastructure resource allocation problem and various approaches to satisfying this problem. We present a resource management system based on a genetic algorithm, which performs allocation of virtual resources, while considering the optimization of multiple criteria. We prove that our approach significantly outperforms reactive VM-scaling algorithms as well as heuristic-based VM-allocation approaches.

Medical image computing in diagnosis and intervention of spinal diseases

Spinal image analysis and computer assisted intervention have emerged as new and independent research areas, due to the importance of treatment of spinal diseases, increasing availability of spinal imaging, and advances in analytics and navigation tools. Among others, multiple modality spinal image analysis and spinal navigation tools have emerged as two keys in this new area. We believe that further focused research in these two areas will lead to a much more efficient and accelerated research path, avoiding detours that exist in other applications, such as in brain and heart.

A new Stata command for computing and graphing percentile shares

Percentile shares provide an intuitive and easy-to-understand way for analyzing income or wealth distributions. A celebrated example are the top income shares sported by the works of Thomas Piketty and colleagues. Moreover, series of percentile shares, defined as differences between Lorenz ordinates, can be used to visualize whole distributions or changes in distributions. In this talk, I present a new command called pshare that computes and graphs percentile shares (or changes in percentile shares) from individual level data. The command also provides confidence intervals and supports survey estimation.

A new Stata command for computing and graphing percentile shares

Percentile shares provide an intuitive and easy-to-understand way for analyzing income or wealth distributions. A celebrated example is the top income shares sported by the works of Thomas Piketty and colleagues. Moreover, series of percentile shares, defined as differences between Lorenz ordinates, can be used to visualize whole distributions or changes in distributions. In this talk, I present a new command called pshare that computes and graphs percentile shares (or changes in percentile shares) from individual level data. The command also provides confidence intervals and supports survey estimation.

Effect of Cage-Induced Stereotypies on Measures of Affective State and Recurrent Perseveration in CD-1 and C57BL/6 Mice.

Stereotypies are abnormal repetitive behaviour patterns that are highly prevalent in laboratory mice and are thought to reflect impaired welfare. Thus, they are associated with impaired behavioural inhibition and may also reflect negative affective states. However, in mice the relationship between stereotypies and behavioural inhibition is inconclusive, and reliable measures of affective valence are lacking. Here we used an exploration based task to assess cognitive bias as a measure of affective valence and a two-choice guessing task to assess recurrent perseveration as a measure of impaired behavioural inhibition to test mice with different forms and expression levels of stereotypic behaviour. We trained 44 CD- 1 and 40 C57BL/6 female mice to discriminate between positively and negatively cued arms in a radial maze and tested their responses to previously inaccessible ambiguous arms. In CD-1 mice (i) mice with higher stereotypy levels displayed a negative cognitive bias and this was influenced by the form of stereotypy performed, (ii) negative cognitive bias was evident in back-flipping mice, and (iii) no such effect was found in mice displaying bar-mouthing or cage-top twirling. In C57BL/6 mice neither route-tracing nor bar-mouthing was associated with cognitive bias, indicating that in this strain these stereotypies may not reflect negative affective states. Conversely, while we found no relation of stereotypy to recurrent perseveration in CD-1 mice, C57BL/6 mice with higher levels of route-tracing, but not bar-mouthing made more repetitive responses in the guessing task. Our findings confirm previous research indicating that the implications of stereotypies for animal welfare may strongly depend on the species and strain of animal as well as on the form and expression level of the stereotypy. Furthermore, they indicate that variation in stereotypic behaviour may represent an important source of variation in many animal experiments.

Granular computing as a basis of human–data interaction: a cognitive cities use case

The article proposes granular computing as a theoretical, formal and methodological basis for the newly emerging research field of human–data interaction (HDI). We argue that the ability to represent and reason with information granules is a prerequisite for data legibility. As such, it allows for extending the research agenda of HDI to encompass the topic of collective intelligence amplification, which is seen as an opportunity of today’s increasingly pervasive computing environments. As an example of collective intelligence amplification in HDI, we introduce a collaborative urban planning use case in a cognitive city environment and show how an iterative process of user input and human-oriented automated data processing can support collective decision making. As a basis for automated human-oriented data processing, we use the spatial granular calculus of granular geometry.

Mapping Emotion Terms into Affective Space: Further Evidence for a Four-Dimensional Structure

Recent empirical work on the semantics of emotion terms across many different cultures and languages, using a theoretical componential approach, suggested that four dimensions are needed to parsimoniously describe the semantic space of the emotion domain as reflected in emotion terms (Fontaine, Scherer, Roesch, & Ellsworth, 2007; Fontaine, Scherer, & Soriano, 2013). In addition to valence, power, and arousal, a novelty dimension was discovered that mostly differentiated surprise from other emotions. Here, we further explore the existence and nature of the fourth dimension in semantic emotion space using a much larger and much more representative set of emotion terms. A group of 156 participants each rated 10 out of a set of 80 French emotion terms with respect to semantic meaning. The meaning of an emotion term was evaluated with respect to 68 emotion features representing the appraisal, action tendency, bodily reaction, expression, and feeling components of the emotion process. A principal component analysis confirmed the four-dimensional valence, power, arousal, and novelty structure. Moreover, this larger and much more representative set of emotion terms revealed that the novelty dimension not only differentiates surprise terms from other emotion terms, but also identifies substantial variation within the fear and joy emotion families.

Affective Commitment and Job Satisfaction among Non-family Employees: Investigating the Roles of Justice Perceptions and Psychological Ownership

Due to numerous characteristics often attributed to family firms, they constitute a unique context for non-family employees’ justice perceptions. These are linked to non-family employees’ pro-organizational attitudes and behaviors, which are essential for family firms’ success. Even though scholarly interest in non-family employees’ justice perceptions has increased, more research is still needed, also because the mechanism connecting justice perceptions and favorable outcomes is not fully understood yet. We address this gap by explicitly investigating non-family employees’ justice perceptions and by introducing psychological ownership as a mediator in the relationships between justice perceptions (distributive and procedural) and common work attitudes (affective commitment and job satisfaction). Our analysis of a sample of 310 non-family employees from Germany and German-speaking Switzerland reveals that psychological ownership mediates the relationships between distributive justice and affective commitment as well as job satisfaction. This represents valuable contributions to family business research, organizational justice and psychological ownership literature, and to practice.

Psychological Ownership of Employees as a Mediator in the Justice - Affective Commitment Relationship

Numerous scholars have accumulated evidence on the positive effects that employees’ organizational justice perceptions exert on work-related outcomes such as affective commitment. However, research still lacks understanding of the underlying mechanisms connecting the two constructs. In this article we aim to narrow this gap by examining the concept of psychological ownership as a possible mediator between organizational justice perceptions and affective commitment. Investigating a sample of 619 employees, we find distributive justice to be positively related to psychological ownership, and observe psychological ownership as a full mediator of the distributive justice and affective commitment relationship. These insights offer a new explanation in understanding the justice-commitment connection, contributing to both organizational justice and psychological ownership literature and opening up ways for promising future research.