Online data processing consent under EU law: a theoretical framework and empirical evidence from the UK

This article analyses the results of an empirical study on the 200 most popular UK-based websites in various sectors of e-commerce services. The study provides empirical evidence on unlawful processing of personal data. It comprises a survey on the methods used to seek and obtain consent to process personal data for direct marketing and advertisement, and a test on the frequency of unsolicited commercial emails (UCE) received by customers as a consequence of their registration and submission of personal information to a website. Part One of the article presents a conceptual and normative account of data protection, with a discussion of the ethical values on which EU data protection law is grounded and an outline of the elements that must be in place to seek and obtain valid consent to process personal data. Part Two discusses the outcomes of the empirical study, which unveils a significant departure between EU legal theory and practice in data protection. Although a wide majority of the websites in the sample (69%) has in place a system to ask separate consent for engaging in marketing activities, it is only 16.2% of them that obtain a consent which is valid under the standards set by EU law. The test with UCE shows that only one out of three websites (30.5%) respects the will of the data subject not to receive commercial communications. It also shows that, when submitting personal data in online transactions, there is a high probability (50%) of incurring in a website that will ignore the refusal of consent and will send UCE. The article concludes that there is severe lack of compliance of UK online service providers with essential requirements of data protection law. In this respect, it suggests that there is inappropriate standard of implementation, information and supervision by the UK authorities, especially in light of the clarifications provided at EU level.

Design of a unified data with business rules storage model for OLTP and OLAP systems

This paper reviews the literature concerning the practice of using Online Analytical Processing (OLAP) systems to recall information stored by Online Transactional Processing (OLTP) systems. Such a review provides a basis for discussion on the need for the information that are recalled through OLAP systems to maintain the contexts of transactions with the data captured by the respective OLTP system. The paper observes an industry trend involving the use of OLTP systems to process information into data, which are then stored in databases without the business rules that were used to process information and data stored in OLTP databases without associated business rules. This includes the necessitation of a practice, whereby, sets of business rules are used to extract, cleanse, transform and load data from disparate OLTP systems into OLAP databases to support the requirements for complex reporting and analytics. These sets of business rules are usually not the same as business rules used to capture data in particular OLTP systems. The paper argues that, differences between the business rules used to interpret these same data sets, risk gaps in semantics between information captured by OLTP systems and information recalled through OLAP systems. Literature concerning the modeling of business transaction information as facts with context as part of the modelling of information systems were reviewed to identify design trends that are contributing to the design quality of OLTP and OLAP systems. The paper then argues that; the quality of OLTP and OLAP systems design has a critical dependency on the capture of facts with associated context, encoding facts with contexts into data with business rules, storage and sourcing of data with business rules, decoding data with business rules into the facts with the context and recall of facts with associated contexts. The paper proposes UBIRQ, a design model to aid the co-design of data with business rules storage for OLTP and OLAP purposes. The proposed design model provides the opportunity for the implementation and use of multi-purpose databases, and business rules stores for OLTP and OLAP systems. Such implementations would enable the use of OLTP systems to record and store data with executions of business rules, which will allow for the use of OLTP and OLAP systems to query data with business rules used to capture the data. Thereby ensuring information recalled via OLAP systems preserves the contexts of transactions as per the data captured by the respective OLTP system.

Towards the design of a unified semantics model for OLTP and OLAP systems

The concepts of on-line transactional processing (OLTP) and on-line analytical processing (OLAP) are often confused with the technologies or models that are used to design transactional and analytics based information systems. This in some way has contributed to existence of gaps between the semantics in information captured during transactional processing and information stored for analytical use. In this paper, we propose the use of a unified semantics design model, as a solution to help bridge the semantic gaps between data captured by OLTP systems and the information provided by OLAP systems. The central focus of this design approach is on enabling business intelligence using not just data, but data with context.

Cloud-assisted body area networks: state-of-the-art and future challenges

Body area networks (BANs) are emerging as enabling technology for many human-centered application domains such as health-care, sport, fitness, wellness, ergonomics, emergency, safety, security, and sociality. A BAN, which basically consists of wireless wearable sensor nodes usually coordinated by a static or mobile device, is mainly exploited to monitor single assisted livings. Data generated by a BAN can be processed in real-time by the BAN coordinator and/or transmitted to a server-side for online/offline processing and long-term storing. A network of BANs worn by a community of people produces large amount of contextual data that require a scalable and efficient approach for elaboration and storage. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of body sensor data streams. In this paper, we motivate the introduction of Cloud-assisted BANs along with the main challenges that need to be addressed for their development and management. The current state-of-the-art is overviewed and framed according to the main requirements for effective Cloud-assisted BAN architectures. Finally, relevant open research issues in terms of efficiency, scalability, security, interoperability, prototyping, dynamic deployment and management, are discussed.

Is children's reading “good enough”? Links between online processing and comprehension as children read syntactically ambiguous sentences

We monitored 8- and 10-year-old children’s eye movements as they read sentences containing a temporary syntactic ambiguity to obtain a detailed record of their online processing. Children showed the classic garden-path effect in online processing. Their reading was disrupted following disambiguation, relative to control sentences containing a comma to block the ambiguity, although the disruption occurred somewhat later than would be expected for mature readers. We also asked children questions to probe their comprehension of the syntactic ambiguity offline. They made more errors following ambiguous sentences than following control sentences, demonstrating that the initial incorrect parse of the garden-path sentence influenced offline comprehension. These findings are consistent with “good enough” processing effects seen in adults. While faster reading times and more regressions were generally associated with better comprehension, spending longer reading the question predicted comprehension success specifically in the ambiguous condition. This suggests that reading the question prompted children to reconstruct the sentence and engage in some form of processing, which in turn increased the likelihood of comprehension success. Older children were more sensitive to the syntactic function of commas, and, overall, they were faster and more accurate than younger children.

Incremental processing in head-final child language: online comprehension of relative clauses in Turkish-speaking children and adults

The present study investigates the parsing of pre-nominal relative clauses (RCs) in children for the first time with a realtime methodology that reveals moment-to-moment processing patterns as the sentence unfolds. A self-paced listening experiment with Turkish-speaking children (aged 5–8) and adults showed that both groups display a sign of processing cost both in subject and object RCs at different points through the flow of the utterance when integrating the cues that are uninformative (i.e., ambiguous in function) and that are structurally and probabilistically unexpected. Both groups show a processing facilitation as soon as the morphosyntactic dependencies are completed and parse the unbounded dependencies rapidly using the morphosyntactic cues rather than waiting for the clause-final filler. These findings show that five-year-old children show similar patterns to adults in processing the morphosyntactic cues incrementally and in forming expectations about the rest of the utterance on the basis of the probabilistic model of their language.

Multi-modal fingerprinting for multimedia assets: optimisation of media security protection in online distribution environments

Since the advent of the internet in every day life in the 1990s, the barriers to producing, distributing and consuming multimedia data such as videos, music, ebooks, etc. have steadily been lowered for most computer users so that almost everyone with internet access can join the online communities who both produce, consume and of course also share media artefacts. Along with this trend, the violation of personal data privacy and copyright has increased with illegal file sharing being rampant across many online communities particularly for certain music genres and amongst the younger age groups. This has had a devastating effect on the traditional media distribution market; in most cases leaving the distribution companies and the content owner with huge financial losses. To prove that a copyright violation has occurred one can deploy fingerprinting mechanisms to uniquely identify the property. However this is currently based on only uni-modal approaches. In this paper we describe some of the design challenges and architectural approaches to multi-modal fingerprinting currently being examined for evaluation studies within a PhD research programme on optimisation of multi-modal fingerprinting architectures. Accordingly we outline the available modalities that are being integrated through this research programme which aims to establish the optimal architecture for multi-modal media security protection over the internet as the online distribution environment for both legal and illegal distribution of media products.

Analytical and compositional aspects of isoflavones in food and their biological effects

This paper provides an overview of analytical techniques used to determine isoflavones (IFs) in foods and biological fluids with main emphasis on sample preparation methods. Factors influencing the content of IFs in food including processing and natural variability are summarized and an insight into IF databases is given. Comparisons of dietary intake of IFs in Asian and Western populations, in special subgroups like vegetarians, vegans, and infants are made and our knowledge on their absorption, distribution, metabolism, and excretion by the human body is presented. The influences of the gut microflora, age, gender, background diet, food matrix, and the chemical nature of the IFs on the metabolism of IFs are described. Potential mechanisms by which IFs may exert their actions are reviewed, and genetic polymorphism as determinants of biological response to soy IFs is discussed. The effects of IFs on a range of health outcomes including atherosclerosis, breast, intestinal, and prostate cancers, menopausal symptoms, bone health, and cognition are reviewed on the basis of the available in vitro, in vivo animal and human data.

Gaps in second language sentence processing

Four groups of second language (L2) learners of English from different language backgrounds (Chinese, Japanese, German, and Greek) and a group of native speaker controls participated in an online reading time experiment with sentences involving long-distance whdependencies. Although the native speakers showed evidence of making use of intermediate syntactic gaps during processing, the L2 learners appeared to associate the fronted wh-phrase directly with its lexical subcategorizer, regardless of whether the subjacency constraint was operative in their native language. This finding is argued to support the hypothesis that nonnative comprehenders underuse syntactic information in L2 processing.

Eyes, amygdala, and other models of face processing: Questions for the SIMS model

This commentary raises general questions about the parsimony and generalizability of the SIMS model, before interrogating the specific roles that the amygdala and eye contact play in it. Additionally, this situates the SIMS model alongside another model of facial expression processing, with a view to incorporating individual differences in emotion perception.

Scaling up classification rule induction through parallel processing

The fast increase in the size and number of databases demands data mining approaches that are scalable to large amounts of data. This has led to the exploration of parallel computing technologies in order to perform data mining tasks concurrently using several processors. Parallelization seems to be a natural and cost-effective way to scale up data mining technologies. One of the most important of these data mining technologies is the classification of newly recorded data. This paper surveys advances in parallelization in the field of classification rule induction.

Online bayesian inference in some time-frequency representations of non-stationary processes

The use of Bayesian inference in the inference of time-frequency representations has, thus far, been limited to offline analysis of signals, using a smoothing spline based model of the time-frequency plane. In this paper we introduce a new framework that allows the routine use of Bayesian inference for online estimation of the time-varying spectral density of a locally stationary Gaussian process. The core of our approach is the use of a likelihood inspired by a local Whittle approximation. This choice, along with the use of a recursive algorithm for non-parametric estimation of the local spectral density, permits the use of a particle filter for estimating the time-varying spectral density online. We provide demonstrations of the algorithm through tracking chirps and the analysis of musical data.

Pronoun processing in Broca's aphasia: discourse-syntax effects in ambiguous anaphora resolution

Background: The interpretation of ambiguous subject pronouns in a null subject language, like Greek, requires that one possesses grammatical knowledge of the two subject pronominal forms, i.e., null and overt, and that discourse constraints regulating the distribution of the two pronouns in context are respected. Aims: We investigated whether the topic-shift feature encoded in overt subject pronouns would exert similar interpretive effects in a group of seven participants with Broca’s aphasia and a group of language-unimpaired adults during online processing of null and overt subject pronouns in referentially ambiguous contexts. Method & Procedures: An offline picture–sentence matching task was initially administered to investigate whether the participants with Broca’s aphasia had access to the gender and number features of clitic pronouns. An online self-paced listening picture-verification task was subsequently administered to examine how the aphasic individuals resolve pronoun ambiguities in contexts with either null or overt subject pronouns and how their performance compares to that of language-unimpaired adults. Outcomes & Results: Results demonstrate that the Broca group, along with controls, had intact access to the morphosyntactic features of clitic pronouns. However, the aphasic individuals showed decreased preference for non-salient antecedents in object position during the online resolution of ambiguous overt subject pronouns and preferred to pick the subject antecedent instead. Conclusions: Broca’s aphasic participants’ parsing decisions in the online task reflect their difficulty with establishing topic-shifted interpretations of the ambiguous overt subject pronouns. The presence of a local topic-shift effect in the immediate temporal vicinity of the overt pronoun suggests that sensitivity to the marked informational status of overt pronouns is preserved in the aphasic individuals, yet, it is blocked under conditions of global sentential processing.