A NoSQL-Based Framework for Managing Home Services

Individuals and companies have an increasing need for services by specialized suppliers in their homes or premises. These services can be quite different and can require different amounts of resources. Service suppliers have to specify the activities to be performed, plan those activities, allocate resources, follow up after their completion and must be able to react to any unexpected situation. Various proposals were formulated to model and implement these functions; however, there is no unified approach that can improve the efficiency of software solutions to enable economy of scale. In this paper, we propose a framework that a service supplier can use to manage geo-localized activities. The proposed framework is based on a NoSQL data model and implemented using the MongoDB system. We also discuss the advantages and drawbacks of a NoSQL approach

Human Activity Behavioural Pattern Recognition in Smarthome with Long-hour Data Collection

The research on human activity recognition has provided novel solutions to many applications like healthcare, sports, and user profiling. Considering the complex nature of human activities, it is still challenging even after effective and efficient sensors are available. The existing works on human activity recognition using smartphone sensors focus on recognizing basic human activities like sitting, sleeping, standing, stair up and down and running. However, more than these basic activities is needed to analyze human behavioural pattern. The proposed framework recognizes basic human activities using deep learning models. Also, ambient sensors like PIR, pressure sensors, and smartphone-based sensors like accelerometers and gyroscopes are combined to make it hybrid-sensor-based human activity recognition. The hybrid approach helped derive more activities than the basic ones, which also helped derive human activity patterns or user profiling. User profiling provides sufficient information to identify daily living activity patterns and predict whether any anomaly exists. The framework provides the base for applications such as elderly monitoring when they are alone at home. The GRU model's accuracy of 95\% is observed to recognize the basic activities. Finally, Human activity patterns over time are recognized based on the duration and frequency of the activities. It is observed that human activity pattern, like, morning walking duration, varies depending on the day of the week

Community-based social services: practical advice based upon lessons from outside the World Bank

The purpose of this paper is to gather information in both developed and developing countries, on design and delivery of community based social service initiatives. While the field is sufficiently new that best practice may not yet be fully identifiable, there are many initiatives funded by other governments, NGOs, and donor agencies, which taken along with acknowledged good practice from the industrialized world, can help task managers with the design of community-based social service projects.Street Children,Adolescent Health,Health Monitoring&Evaluation,Banks&BankingReform,Civil Society

Financial Management: Social Agency, Social Enterprise and Social Economy

There has been a quiet revolution in financial management practice in social agencies in recent decades, symbolized by the transition from fund to enterprise accounting and increasing recognition of the ‘third sector’ of the social economy. The traditional voluntary agency model of donations has been joined by grants, performance contracts, ‘managed care’ and an array of other options, and traditional voluntary agency based and public agency practice now exist alongside corporate for profit service delivery and various forms of private practice. Social enterprise and entrepreneurship are a common theme in all this diversity, as social agencies must aggressively seek out financial support. In this environment, two models of budgeting, termed ‘common-pool’ and social enterprise budgeting have emerged

Joint Analysis of Zero-heavy Longitudinal Outcomes: Models and Comparison of Study Designs

Understanding the patterns and mechanisms of the process of desistance from criminal activity is imperative for the development of effective sanctions and legal policy. Methodological challenges in the analysis of longitudinal criminal behaviour data include the need to develop methods for multivariate longitudinal discrete data, incorporating modulating exposure variables and several possible sources of zero-inflation. We develop new tools for zero-heavy joint outcome analysis which address these challenges and provide novel insights on processes related to offending patterns. Comparisons with existing approaches demonstrate the benefits of utilizing modeling frameworks which incorporate distinct sources of zeros. An additional concern in this context is heaping of self-reported counts where recorded counts are rounded to different levels of precision. Alternatively, more accurate data that is less burdensome on participants to record may be obtained by collecting information on presence/absence of events at periodic assessments. We compare these two study designs in the context of self-reported data related to criminal behaviour and provide insights on choice of design when heaping is expected. The contributions of this research work include the following: (i) Developing a general framework for joint modeling of multiple longitudinal zero-inflated count outcomes which incorporates a variety of probabilistic structures on the zero counts. (ii) Accommodating a subgroup of subjects who are not at-risk to engage in a particular outcome (iii) Incorporating the effect of a time-dependent exposure variable in settings where some outcomes are prohibited during exposure to a treatment. (iv) Illustrating the extent to which heaping of zero-inflated counts, arising from a variety of heaping mechanisms, can introduce bias, impeding the identification of important risk factors (v) Identifying situations where there is very little loss of efficiency in the analysis of presence/absence data, depending on the partition of the time for the presence/absence records and the underlying rate of events. (vi) Providing recommendations on the design of studies when heaping is a concern. (vii) Modeling of multiple longitudinal binary outcomes where a mixture model approach allows differential rates of recurrence of events, and where the underlying process generating events may resolve

Financing local government in Hungary

Hungary has undertaken a bold and far-ranging reform of its system of subnational finances. This paper outlines the changes introduced in the system of local finance as a result of the 1990 Local Self-Government Act, and the 1990 Act on Local Taxes and provides a preliminary assessment of their implications as well as the need for further reform. These Acts, together with the annual Act on the Budget, define the overall scope and authorities of Hungary's approximately 3100 new local self-governments. These Acts: (i) define the new assignment of expenditures between central and local government; (ii) define the new local revenue sources; and (iii) establish the economic foundation, property rights and entrepreneurial functions of the localities. The paper outlines the historical evolution of the system, provides international comparisons, and describes its present-day form. Drawing on this background, it suggests some revised policies that should not only both help avert the potentially undesirable outcomes of the current system but, more positively, help Hungary to achieve its goal of a smaller, more efficient government sector without unduly exacerbating social inequalities. In turn, issues and recommendations are discussed in the following areas: local finance; assignment of expenditures; assignment of taxes; design of the transfer system; role of the localities in property management; capital investment; and other requisites for sound local finance.Banks&Banking Reform,Municipal Financial Management,National Governance,Urban Economics,Public Sector Economics&Finance