Gender and Religious Dress at the European Court of Human Rights: A Comparison of \u3ci\u3eȘahin v. Turkey\u3c/i\u3e and \u3ci\u3eArslan v. Turkey\u3c/i\u3e

This paper examines the regulation of the religious dress of men and women in two decisions by the European Court of Human Rights: Şahin v. Turkey and Arslan v. Turkey. In Şahin, the Court upheld a ban on the wearing of the Islamic headscarf, an article of clothing worn exclusively by women, at a public university. In Arslan, the Court rejected a ban on the wearing of a type of religious uniform worn only by men who were members of a politically subversive Islamic group. In both cases, the Court asserted that its decision was necessary to protect the rights and freedoms of others. This Article argues that reading these two cases together reveals a gendered approach to the regulation of religious clothing, with the Court endowing the religious dress of women with a political significance it does not extend to men’s religious dress. Further, a comparative reading demonstrates that the Court is less willing to accept women’s stated reasons for adopting religious dress, thus curtailing women\u27s agency in the name of promoting gender equality

Challenging Statutory Accommodations for Religiously Affiliated Daycares: An Application of the Third-Party Harm Doctrine

Daycare facilities are subject to a host of regulations that govern matters from basic health and safety requirements, to caregiver training, to maximum caregiver-to-child ratios. In sixteen states, however, legislation exempts religiously affiliated daycares from many of these regulations, with six states extending particularly broad exemptions. Supporters of the exemptions have justified them on constitutional grounds, arguing that state oversight of religiously affiliated daycares violates the Free Exercise Clause of the First Amendment. Recent reporting has revealed that though children have been seriously injured or have died while in the care of religiously affiliated daycares exempted from regulations, challenges to the exemptions have been unsuccessful. This Note proposes an alternative strategy for challenging the statutory accommodations extended to religiously affiliated daycares. Both judicial exemptions under the Free Exercise Clause and statutory accommodations under the Establishment Clause have historically been limited by the doctrine of harm to third parties. Invoking a balancing test, this Note argues that courts ought to weigh the free exercise burden imposed on the religiously affiliated daycare against the harm to third parties caused by accommodation. As such, this Note suggests that parents of children harmed in exempt facilities invoke the balancing test to argue that the harm to third parties outweighs the free exercise burden imposed by regulations

A data cube model for analysis of high volumes of ambient data

Ambient systems generate large volumes of data for many of their application areas with XML often the format for data exchange. As a result, large scale ambient systems such as smart cities require some form of optimization before different components can merge their data streams. In data warehousing, the cube structure is often used for optimizing the analytics process with more recent structures such as dwarf, providing new orders of magnitude in terms of optimizing data extraction. However, these systems were developed for relational data and as a result, we now present the development of an XML dwarf to manage ambient systems generating XML data

Enrichment of raw sensor data to enable high-level queries

Sensor networks are increasingly used across various application domains. Their usage has the advantage of automated, often continuous, monitoring of activities and events. Ubiquitous sensor networks detect location of people and objects and their movement. In our research, we employ a ubiquitous sensor network to track the movement of players in a tennis match. By doing so, our goal is to create a detailed analysis of how the match progressed, recording points scored, games and sets, and in doing so, greatly reduce the eort of coaches and players who are required to study matches afterwards. The sensor network is highly efficient as it eliminates the need for manual recording of the match. However, it generates raw data that is unusable by domain experts as it contains no frame of reference or context and cannot be analyzed or queried. In this work, we present the UbiQuSE system of data transformers which bridges the gap between raw sensor data and the high-level requirements of domain specialists such as the tennis coach

Pattern based processing of XPath queries

As the popularity of areas including document storage and distributed systems continues to grow, the demand for high performance XML databases is increasingly evident. This has led to a number of research eorts aimed at exploiting the maturity of relational database systems in order to in- crease XML query performance. In our approach, we use an index structure based on a metamodel for XML databases combined with relational database technology to facilitate fast access to XML document elements. The query process involves transforming XPath expressions to SQL which can be executed over our optimised query engine. As there are many dierent types of XPath queries, varying processing logic may be applied to boost performance not only to indi- vidual XPath axes, but across multiple axes simultaneously. This paper describes a pattern based approach to XPath query processing, which permits the execution of a group of XPath location steps in parallel

Classification of index partitions to boost XML query performance

XML query optimization continues to occupy considerable research effort due to the increasing usage of XML data. Despite many innovations over recent years, XML databases struggle to compete with more traditional database systems. Rather than using node indexes, some efforts have begun to focus on creating partitions of nodes within indexes. The motivation is to quickly eliminate large sections of the XML tree based on the partition they occupy. In this research, we present one such partition index that is unlike current approaches in how it determines size and number of these partitions. Furthermore, we provide a process for compacting the index and reducing the number of node access operations in order to optimize XML queries

An automated ETL for online datasets

While using online datasets for machine learning is commonplace today, the quality of these datasets impacts on the performance of prediction algorithms. One method for improving the semantics of new data sources is to map these sources to a common data model or ontology. While semantic and structural heterogeneities must still be resolved, this provides a well established approach to providing clean datasets, suitable for machine learning and analysis. However, when there is a requirement for a close to real time usage of online data, a method for dynamic Extract-Transform-Load of new sources data must be developed. In this work, we present a framework for integrating online and enterprise data sources, in close to real time, to provide datasets for machine learning and predictive algorithms. An exhaustive evaluation compares a human built data transformation process with our system’s machine generated ETL process, with very favourable results, illustrating the value and impact of an automated approach

Capturing personal health data from wearable sensors

Recently, there has been a significant growth in pervasive computing and ubiquitous sensing which strives to develop and deploy sensing technology all around us. We are also seeing the emergence of applications such as environmental and personal health monitoring to leverage data from a physical world. Most of the developments in this area have been concerned with either developing the sensing technologies, or the infrastructure (middleware) to gather this data and the issues which have been addressed include power consumption on the devices, security of data transmission, networking challenges in gathering and storing the data and fault tolerance in the event of network and/or device failure. Research is focusing on harvesting and managing data and providing query capabilities

An automated ETL for online datasets

While using online datasets for machine learning is commonplace today, the quality of these datasets impacts on the performance of prediction algorithms. One method for improving the semantics of new data sources is to map these sources to a common data model or ontology. While semantic and structural heterogeneities must still be resolved, this provides a well established approach to providing clean datasets, suitable for machine learning and analysis. However, when there is a requirement for a close to real time usage of online data, a method for dynamic Extract-Transform-Load of new sources data must be developed. In this work, we present a framework for integrating online and enterprise data sources, in close to real time, to provide datasets for machine learning and predictive algorithms. An exhaustive evaluation compares a human built data transformation process with our system’s machine generated ETL process, with very favourable results, illustrating the value and impact of an automated approach

Desirable properties for XML update mechanisms

The adoption of XML as the default data interchange format and the standardisation of the XPath and XQuery languages has resulted in significant research in the development and implementation of XML databases capable of processing queries efficiently. The ever-increasing deployment of XML in industry and the real-world requirement to support efficient updates to XML documents has more recently prompted research in dynamic XML labelling schemes. In this paper, we provide an overview of the recent research in dynamic XML labelling schemes. Our motivation is to define a set of properties that represent a more holistic dynamic labelling scheme and present our findings through an evaluation matrix for most of the existing schemes that provide update functionality