A Novel Cyclic Time to Digital Converter Based on Triple-Slope Interpolation and Time Amplification

This paper investigates a novel cyclic time-to-digital converter (TDC) which employs triple-slope analog interpolation and time amplification techniques for digitizing the time interval between the rising edges of two input signals(Start and Stop). The proposed converter will be a 9-bit cyclic time-to-digital converter that does not use delay lines in its structure. Therefore, it has a low sensitivity to temperature, power supply and process (PVT) variations. The other advantages of the proposed converter are low circuit complexity, and high accuracy compared with the time-to-digital converters that have previously been proposed. Also, this converter improves the time resolution and the dynamic range. In the same resolution, linear range and dynamic range, the proposed cyclic TDC reduces the number of circuit elements compared with the converters that have a similar circuit structure. Thus, the converter reduces the chip area, the power consumption and the figure of merit (FoM). In this converter, the integral nonlinearity (INL) and differential nonlinearity (DNL) errors are reduced. In order to evaluate the idea, the proposed time-to-digital converter is designed in TSMC 45 nm CMOS technology and simulated. Comparison of the theoretical and simulation results confirms the benefits of the proposed TDC

The New Retail Experience and Its Unaddressed Privacy Concerns: How RFID and Mobile Location Analytics are Collecting Customer Information

Part I of this paper will look at the newest development of the retail experience and suggest a method to understand the privacy concerns as well as suggest a regulatory scheme to protect customers without inhibiting their shopping experience. Part II will provide a background of the three stages of shopping experiences and the evolution of privacy concerns associated with them. Part III will address the current American stance on data collection and privacy law with a particular look at privacy concerns that the eStore is facing. Finally, Part IV will provide guidance on how to deal with these data collection issues in the future and attempt to answer two questions: (i) Does the definition of data collection need to be adjusted? and (ii) Are customers ready to accept the new eStore

Impact of design on social interaction within urban residential developments in Scotland.

Over the last few decades, the emergence of various social problems within the urban neighbourhoods of cities, especially in developed countries such as the UK, has called for further research into the relationship between the built environment and the social sustainability of urban developments. Recently, the Scottish government and local authorities have started to revisit and refine their policies and guidelines in order to promote positive social interaction between residents, which is a critical factor in creating a sense of community, and preventing social problems, such as segregation, crime, and apathy. However, in the absence of any detailed information or any practical framework for designers, these policies and guidelines have ended up drawing pictures of an ideal world without helping the designers with the socially responsive solutions. Using multiple case studies, this research aims to establish if and how the design of urban residential developments can facilitate social interaction between residents in Scotland. To achieve this aim, primary data have been collected from seven urban residential developments in Scotland. Self-completion questionnaires, semi-structured interviews and a site survey, have been used to collect data in three areas: social interaction patterns, use of communal spaces and design qualities of the communal spaces within selected developments. Content analysis and GIS analytical maps have been used to analyse the data. The findings show that the access routes and service spaces of urban residential developments, such as entrances, lifts and corridors accommodate most of the interactions between residents. This calls for more attention to the design of these unintentional communal spaces as actual places of contact among neighbours. A number of physical attributes, mostly concerned with the affordance, privacy, physical proximity and visual attractiveness of communal spaces have been found to affect social interaction and the use of space patterns within selected case studies. This research contributes to the much-needed empirical evidence to inform the design of future sustainable housing developments in Scotland by creating a detailed list of design recommendations based on empirical evidence along with modifications of existing assumptions about the quality and quantity of social interaction among residents and the role of communal spaces in facilitating these interactions. It also contributes to our knowledge by introducing new methods of empirical research in the built environment, specifically for research on building scale by expanding the use of analytical GIS maps and the refinement of existing indicators and measures

Analysis of Residue Probability Density Function and Comparator Offset Error in Pipelined ADCs

This paper presents a new approach to analyze the convergence of residue probability density function (pdf) in pipelined ADCs. Compared to the previous approaches, in the proposed approach, in addition to the analysis of residue pdfs for different input densities, the analysis of the sub-ADC comparator offsets impact on output pdf is possible. Using Fourier analysis, it will be shown that the residue density converges to uniformity. In the half-bit redundant structure, residue pdf concentrates in the center half of the stage full-scale range and 6 dB of extra resolution can be gained. Also, the share of each stage in this resolution improvement is investigated. Examining the sub-ADC threshold offsets impact on residue pdfs, it is observed that with respect to the impact on converter additional resolution, the final stages offset errors are more significant than the first stages offsets

Capturing Software Architecture Knowledge for Pattern-Driven Design

Context: Software architecture is a knowledge-intensive field. One mechanism for storing architecture knowledge is the recognition and description of architectural patterns. Selecting architectural patterns is a challenging task for software architects, as knowledge about these patterns is scattered among a wide range of literature. Method: We report on a systematic literature review, with the aim of building a decision model for the architectural pattern selection problem. Moreover, twelve experienced practitioners at software-producing organizations evaluated the usability and usefulness of the extracted knowledge.\newline Results: An overview is provided of 29 patterns and their effects on 40 quality attributes. Furthermore, we report in which systems the 29 patterns are applied and in which combinations. The practitioners confirmed that architectural knowledge supports software architects with their decision-making process to select a set of patterns for a new problem. We investigate the potential trends among architects to select patterns. Conclusion: With the knowledge available, architects can more rapidly select and eliminate combinations of patterns to design solutions. Having this knowledge readily available supports software architects in making more efficient and effective design decisions that meet their quality concerns

Context-Aware Notebook Search in a Jupyter-Based Virtual Research Environment

Computational notebook environments such as the Jupyter play an increasingly important role in data-centric research for prototyping computational experiments, documenting code implementations, and sharing scientific results. Effectively discovering and reusing notebooks available on the web can reduce repetitive work and facilitate scientific innovations. However, general-purpose web search engines (e.g., Google Search) do not explicitly index the contents of notebooks, and notebook repositories (e.g., Kaggle and GitHub) require users to create domain-specific queries based on the metadata in the notebook catalogs, which fail to capture the working contexts in the notebook environment. This poster presents a Context-aware Notebook Search Framework (CANSF) to enable a researcher to seamlessly discover external notebooks based on semantic contexts of the literate programming activities in the Jupyter environment.Non