Information driven evaluation of data hiding algorithms

Abstract. Privacy is one of the most important properties an information system must satisfy. A relatively new trend shows that classical access control techniques are not sufficient to guarantee privacy when datamining techniques are used. Privacy Preserving Data Mining (PPDM) algorithms have been recently introduced with the aim of modifying the database in such a way to prevent the discovery of sensible information. Due to the large amount of possible techniques that can be used to achieve this goal, it is necessary to provide some standard evaluation metrics to determine the best algorithms for a specific application or context. Currently, however, there is no common set of parameters that can be used for this purpose. This paper explores the problem of PPDM algorithm evaluation, starting from the key goal of preserving of data quality. To achieve such goal, we propose a formal definition of data quality specifically tailored for use in the context of PPDM algorithms, a set of evaluation parameters and an evaluation algorithm. The resulting evaluation core process is then presented as a part of a more general three step evaluation framework, taking also into account other aspects of the algorithm evaluation such as efficiency, scalability and level of privacy.

Hydra: A mixture modeling framework for subtyping pediatric cancer cohorts using multimodal gene expression signatures.

Precision oncology has primarily relied on coding mutations as biomarkers of response to therapies. While transcriptome analysis can provide valuable information, incorporation into workflows has been difficult. For example, the relative rather than absolute gene expression level needs to be considered, requiring differential expression analysis across samples. However, expression programs related to the cell-of-origin and tumor microenvironment effects confound the search for cancer-specific expression changes. To address these challenges, we developed an unsupervised clustering approach for discovering differential pathway expression within cancer cohorts using gene expression measurements. The hydra approach uses a Dirichlet process mixture model to automatically detect multimodally distributed genes and expression signatures without the need for matched normal tissue. We demonstrate that the hydra approach is more sensitive than widely-used gene set enrichment approaches for detecting multimodal expression signatures. Application of the hydra analysis framework to small blue round cell tumors (including rhabdomyosarcoma, synovial sarcoma, neuroblastoma, Ewing sarcoma, and osteosarcoma) identified expression signatures associated with changes in the tumor microenvironment. The hydra approach also identified an association between ATRX deletions and elevated immune marker expression in high-risk neuroblastoma. Notably, hydra analysis of all small blue round cell tumors revealed similar subtypes, characterized by changes to infiltrating immune and stromal expression signatures

Zeolite-like liquid crystals

Zeolites represent inorganic solid-state materials with porous structures of fascinating complexity. Recently, significant progress was made by reticular synthesis of related organic solid-state materials, such as metal-organic or covalent organic frameworks. Herein we go a step further and report the first example of a fluid honeycomb mimicking a zeolitic framework. In this unique self-assembled liquid crystalline structure, transverse-lying π-conjugated rod-like molecules form pentagonal channels, encircling larger octagonal channels, a structural motif also found in some zeolites. Additional bundles of coaxial molecules penetrate the centres of the larger channels, unreachable by chains attached to the honeycomb framework. This creates a unique fluid hybrid structure combining positive and negative anisotropies, providing the potential for tuning the directionality of anisotropic optical, electrical and magnetic properties. This work also demonstrates a new approach to complex soft-matter self-assembly, by using frustration between space filling and the entropic penalty of chain extension

A synthesizing framework for technology and content choices for information exchange

In this paper, we develop a synthesizing framework for information exchange. In particular, we identify the drivers of both the content of information exchange as well as the choice of the technology used to facilitate information exchange across multiple organizations. Our first driver is the inter-organizational architecture. Unlike the general architectures developed by Williamson [11] and Adler [1], we focus specifically on the effect of architectures on information exchange. We classify the existing architectures in three dimensions, namely, customization, information sharing or trading and closed or open networks. Such a classification enables us to identify particular architectural characteristics that affect content and technology choices. Our second driver refers to the characteristics of the information, the system, the network and the regulatory environment that affect the credibility and usefulness of information exchange for the participants. Our third driver is the incentive structure in the architecture. Only the information that is deemed to be mutually beneficial by all participants will get exchanged. The incentive structure highlights the cost-benefit trade-offs of individual participants. We also place all the five papers accepted for this special issue within this synthesizing framework. Such positioning allows us to identify potential areas for future research and exploration. © Springer Science + Business Media, LLC 2006

Just in time or just in case? An explanatory model with informational and incentive effects

There is extensive literature on the benefits of manufacturing control arising from minimal inventory policies of just in time (JIT). Operations management literature has focused on controlling set-up, lead and changeover times to streamline the operations and achieve low optimal inventory levels. Our paper first expands these models to include information and incentive effects. We then develop a model in which JIT focuses attention on process imbalances and derive the compensation contract that induces managers to be more creative in managing the process. We show that the loss of controllability decreases the benefits of JIT and increase the benefits of traditional buffer inventory. If, as on 11 September 2001, the loss or gain of controllability occurs quickly and unexpectedly, organizations need to develop the agility to switch between minimal inventory and buffer inventory systems

Conflicting evidence for ferroelectricity

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