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The purpose of this paper is to present analysis of the feedback predictive encoder-based analog-to-digital converter (ADC).

The use of feedback predictive encoder-based ADCs presents an alternative to the traditional two-stage pipeline ADC by replacing the input estimate producing first stage of the pipeline with a predictive loop that also produces an estimate of the input signal.

The overload condition for feedback predictive encoder ADCs is dependent on input signal amplitude and frequency, system gain and filter order. The limitation on the practical usable filter order is set by limit cycle oscillation. A boundary condition is defined for determination of maximum usable filter order. In a practical implementation of the predictive encoder ADC, the time allocated to the key functions of the gain stage and loop quantizer leads to optimization of the power consumption.

A practical switched capacitor implementation of the predictive encoder-based ADC is proposed. The power consumption of key circuit blocks is investigated.

This paper presents a methodology to optimize the bandwidth of predictive encoder ADCs. The overload and stability conditions may be used to determine the maximum input signal bandwidth for a given loop quantizer. Optimization of power consumption based on the allocation of time between the gain stage and the successive approximation register ADC operation is investigated. The lower bound of power consumption for this architecture is estimated.

To explain the benefits and the regulations pertaining to Jersey as a domicile for investment funds.

Provides an overview of Jersey as an international financial center followed by a detailed description of Jersey regulations applying to private funds, expert funds, listed funds, regulated investor funds, retail and other collective investment funds (CIFs), and notification-only funds. Explains fund vehicles including unit trusts, limited partnerships, and companies. Discusses taxes and fund service providers.

Jersey is one of the world’s major international finance centers, offering location and time-zone benefits; stability and reliability; tax neutrality; a stable political, fiscal and regulatory infrastructure; and highly-skilled financial-service providers.

Expert guidance from experienced investment-funds lawyers

There exists a rich sociological literature dealing with secularisation. Such nineteenth‐century sociologists as Weber and Durkheim and twentieth‐century sociologists as Greeley, Bellah, Berger and Wilson have contributed. Berger refers to secularisation as “the process by which sectors of society and culture are removed from the domination of religious institutions and symbols”, while Wilson defines it as “the process whereby religious thinking, practices and institutions lose social significance”. These definitions represent the thrust of academic thinking about secularisation. Generally, social scientists interpret secularisation as the decline of religiosity — a movement from faith to reason. They cite numerous indicators of the change: decline in such areas as church attendance, praying, use of religious rites and rituals, recruitment to the church bureaucracy, church construction. Often they suggest a kind of inevitability relating to urbanisation and industrialisation. The focus of the process involves man becoming less concerned with the spiritual and more concerned with the mundane. Eventually, the spiritual becomes irrelevant; the Age of Enlightenment triumphs over the Age of Faith.

Massive open online courses (MOOCs) provide an innovative educational technology, which has become widely used for distance learning by independent learners. However, there has been little work so far to study the effects of using MOOCs as part of a blended classroom approach in which learning activities take place both online and in a traditional classroom setting. The purpose of this study is to investigate the aspects of blended MOOC usage in the context of a computing course for first-year undergraduates at a UK university.

The MOOC was implemented on a purpose-built platform that supports learners to make informed choices about their learning path. This research investigates students’ capacity for self-regulated learning (SRL) and understands their preparedness for independent study, profile the general areas of SRL strength and weakness, which may affect their ability to learn effectively in a self-directed environment. An existing survey instrument, based on a six-dimensional conceptualization of SRL was adapted to investigate the self-regulation in the MOOC study.

The results demonstrate that the dimensions of self-evaluation and time management represent particular areas of weakness for these students. Furthermore, profiles of SRL for individual students show considerable differences in capability within the study. However, the deficiencies in SRL dimensions contrast with the students’ of generally high levels of attainment. This leads us to question the validity of the existing SRL. Furthermore, a high level of social interaction and help-seeking was reported in relation to the MOOC study indicating the increasing importance of social learning and the importance of co-regulation for SRL.

Although this study presents findings from a small data sample, it points to a number of areas for future implementation and exploration. Firstly, in line with the action research approach, students’ SRL could, in the future, be tested early in the course with the MOOC component being ideally placed to provide personalised support for each student in aspects which they may benefit from developing further. Secondly, for students in the cohort studied in this paper, a longitudinal study will track how their SRL develops as they progress through the degree. We feel that it is important to gain further qualitative data to understand how students work in practice and the strategies they adopt when confronted with different modes of learning. Finally, it is necessary to consider the conceptualisation of SRL to understand if existing instruments could be adapted to provide a more accurate assessment of the effectiveness of learners’ self-regulation.

There has been little research on the effects of using a MOOC as the online component of a blended classroom learning approach. This study has used a theoretical perspective of SRL to investigate the approaches to self-regulation adopted by undergraduate computer science students studying in a blended MOOC environment. The MOOC used for this purpose was developed on the innovative eLDa platform, allowing students to determine, track and visualise their individual path through topics and materials offered in the MOOC.

This study explores the determinants of police officer support for pre-arrest/booking deflection programs that divert people presenting with substance use and/or mental health disorder symptoms out of the criminal justice system and connect them to supportive services.

This study analyzes responses from 254 surveys fielded to police officers in Delaware. Questionnaires asked about views on leadership, approaches toward crime, training, occupational experience and officer’s personal characteristics. The study applies a new machine learning method called kernel-based regularized least squares (KRLS) for non-linearities and interactions among independent variables. Estimates from a KRLS model are compared with those from an ordinary least square regression (OLS) model.

Support for diversion is positively associated with leadership endorsing diversion and thinking of new ways to solve problems. Tough-on-crime attitudes diminish programmatic support. Tenure becomes less predictive of police attitudes in the KRLS model, suggesting interactions with other factors. The KRLS model explains a larger proportion of the variance in officer attitudes than the traditional OLS model.

The study demonstrates the usefulness of the KRLS method for practitioners and scholars seeking to illuminate patterns in police attitudes. It further underscores the importance of agency leadership in legitimizing deflection as a pathway to addressing behavioral health challenges in communities.

Tropical wetland ecosystems are threatened by climate change but also play a key role in its mitigation and adaptation through management of land use and other drivers. Local-level assessments are needed to support evidence-based wetland management in the face of climate change. This study aims to examine the local communities’ knowledge and perception of climate change in Yala wetland, Kenya, and compare them with observed data on climate trends. Such comparisons are useful to inform context-specific climate change adaptation actions.

The study used a mixed methods approach that combined analysis of climate data with perceptions from the local community. Gridded data on temperature and rainfall for the period from 1981 to 2018 were compared with data on climate change perceptions from semi-structured questionnaires with 286 key informants and community members.

Majority of the respondents had observed changes in climate parameters – severe drought (88.5%), increased frequency of floods (86.0%) and irregular onset and termination of rains (90.9%) in the past 20 years. The perceptions corresponded with climate trends that showed a significant increasing trend in the short rains and the average maximum temperature, high incidence of very wet years and variability in onset and termination of rainfall between 1981 and 2018. Gender, age and education had little influence on knowledge and awareness of climate change, except for frequency of floods and self-reported understanding of climate change. The community perceived the wetland to be important for climate change adaptation, particularly the provision of resources such as grazing grounds during drought.

The study faced challenges of low sample size, use of gridded climate data and reproducibility in other contexts. The results of this study apply to local communities in a tropical wetland in Western Kenya, which has a bi-modal pattern of rainfall. The sample of the study was regional and may therefore not be representative of the whole of Kenya, which has diverse socioeconomic and ecological contexts. Potential problems have been identified with the use of gridded data (for example, regional biases in models), although their usefulness in data scarce contexts is well established. Moreover, the sample size has been found to be a less important factor in research of highly complex socio-ecological systems where there is an attempt to bridge natural and social sciences.

This study addresses the paucity of studies on climate change trends in papyrus wetlands of sub-Saharan Africa and the role of local knowledge and perceptions in influencing the management of such wetlands. Perceptions largely influence local stakeholders’ decisions, and a study that compares perceptions vs “reality” provides evidence for engagement with the stakeholders in managing these highly vulnerable ecosystems. The study showed that the local community’s perceptions corresponded with the climate record and that adaptation measures are already ongoing in the area.

This study presents a case for the understanding of community perceptions and knowledge of climate change in a tropical wetland under threat from climate change and land use change, to inform management under a changing climate.

In the quest for better construction workforce management, this chapter explored the background of workforce management and related theories, models, and practices. Through a review, the chapter provided meaning to the concept of construction and workforce management. The chapter concluded that while the construction industry worldwide is important to the economic growth of the countries where it operates, the industry’s management of its workforce is challenged by several problems. These problems include the nature of the industry, skill shortage, unhealthy working environment, and poor image of the industry, among others. Also, while the construction industry is rich in diversity, this has been a major source of problems for workforce management. The chapter further revealed that to improve workforce management and attain better-performing construction organisations, careful recruitment, effective training, providing a safe working environment, putting policies to promote diversity, and ensuring innovativeness, among others, are essential.

Many librarians have hypothesized that psychological and sociological variables can be used to explain library use. This article examines the possibility of utilizing biological variables to explain library use.

A flexible model which is based on a Triangular intuitionistic flexibility ranking and aggregating (TIFRA) operator is proposed for failure detection and reliability management in a Wind Turbine system. The model which is employed when there are limited research data and valid source of information, uses expert-based knowledge/opinion for failure detection and reliability management. The results from the study concludes that, the most important area affected by failure with respect to the failure criteria used, includes; oil level sensor tilt sensors for tower installation and accelerometers for tower sway (A₂), Pressure sensor for blade monitoring (A₃), and the Pitch actuator (A₄). The main advantage of the proposed method is that it provides advanced information about faults that identifies the intensity of the system behavior also; the method provides a more complete view of the reliability management and root cause of failure in the Wind Turbine (WT) system using the flexibility parameter in the model.

At the Multimedia University, Malaysia, a first‐year undergraduate course in electronic commerce was given the task of evaluating commercial Web sites. The existence of the host was verified when it was added to the sample, and again six months later. The sample was then analysed for correlation between domain names and regional allocation of IP addresses. Three characteristics of the sample stand out. First, in many cases the top‐level domain name does not correspond to the location of the host; there is a noticeable bias toward hosting sites with regional domain names in North America. Second, dot COM and certain regional domains seem to dominate the Internet commercial landscape. Finally, there is a measurable rate of attrition over time, which may or may not be truly significant.