Добірка наукової літератури з теми "MONITORABLE FEATURES"

NGOs are an integral part of present day organizational landscape. They are perceived to be much better than government and for-profit businesses in delivering the social welfare goods and services needed by society. Policy makers in India and the world over are showing an increasing preference for NGOs to implement various social welfare programmes. The present essay examines the rationale underlying such a preference and the relevance of the advantages attributed to NGOs. The NGO organizational form differs from public bureaucracies and for-profit businesses based on the two criteria of non-governmentness and non-profitness. Various advantages like ability to attract altruistic resources, to provide for unmet and heterogenous demand for public goods, protection against contract failure, and freerider problem are attributed to these two defining features of NGOs. They are also seen as sites that facilitate socialization in democratic participation, social innovation, and responsiveness. When examined in the socio-historical backdrop of Indian NGO sector, each of these advantages while having relevance historically is being severely compromised in recent times. The shift in voluntarism from a calling to a paid employment, institutionalization of funding sources, deployment of hard contracting and other developments in the NGO sector have dampened the perceived advantages. Altruism is more likely an involuntary subsidization and NGOs are more and more becoming mass producers of welfare goods. The focus on clear, wellplanned project proposals and documents and clearly specified procedures and budgets have reduced the elbow room available to NGOs to innovate. This loss of relevance is primarily because the organic features of the organizational form which bestowed some of the advantages on NGOs are now being traded off in favour of a more standardized, formalized form that is scalable and monitorable. Yet, because of the preferences of the institutionalized funders, non-profitness continues to remain a defining feature of NGOs even though it may not be giving the organization a competitive advantage over public bureaucracies or for-profit businesses. On the contrary, the constraint on profits, has resulted in NGOs adopting practices which expose them to criticism. These practices, while being perfectly rational for other kinds of organizations, become contortions in the case of NGOs. It is therefore necessary for us to re-examine the nature of NGOs and assess the role played by the non-profit constraint and come up with appropriate mechanisms that facilitate the provision of welfare goods/services to society by these organizations.

Abstract Background Despite their shared origins, medicine and dentistry are not always two sides of the same coin. There is a long history in medical philosophy of defining disease and various medical models have come into existence. Hitherto, little philosophical and phenomenological work has been done considering dental caries and periodontitis as examples of disease and illness. Methods A philosophical methodology is employed to explore how we might define dental caries and periodontitis using classical medical models of disease – the naturalistic and normativist. We identify shared threads and highlight how the features of these highly prevalent dental diseases prevent them fitting in either definition. The article describes phenomenology and the current thought around the phenomenology of illness, exploring how and why these dental illnesses might integrate into a phenomenological model. Results We discover that there are some features particular to dental caries and periodontitis: ubiquity, preventability and hyper-monitorablility. Understanding the differences that these dental diseases have compared to many other classically studied diseases leads us to ethical questions concerning how we might manage those who have symptoms and seek treatment. As dental caries and periodontitis are common, preventable and hyper-monitorable, it is suggested that these features affect the phenomenology of these illnesses. For example, if we experience dental illness when we have consciously made decisions that have led to it, do we experience them differently to those rarer illnesses that we cannot expect? Other diseases share these features are discussed. Conclusions This paper highlights the central differences between the classical philosophical notion of disease in medicine and the dental examples of caries and periodontitis. It suggests that a philosophical method of conceptualising medical illness - phenomenology - should not be applied to these dental illnesses without thought. A phenomenological analysis of any dental illness is yet to be done and this paper highlights why a separate strand of phenomenology should be explored, instead of employing those that are extant. The article concludes with suggestions for further research into the nascent field of the phenomenology of dental illness and aims to act as a springboard to expose the dental sphere to this philosophical method of analysis.

AbstractStream acoustics has been proposed as a means of monitoring discharge and wave hazards from outside the stream channel. To better understand the dependence of sound on discharge and wave characteristics, this study analyzes discharge and infrasound data from an artificial wave feature which is adjusted to accommodate daily changes in recreational use and seasonal changes in irrigation demand. Monitorable sound is only observed when discharge exceeds ∼35 m3/s, and even above that threshold the sound‐discharge relationship is non‐linear and inconsistent. When sound is observed, it shows consistent dependence on wave type within a given year, but the direction of this dependence varies among the three years studied (2016, 2021, and 2022). These findings support previous research that establishes discharge and stream morphology as relevant controls on stream acoustics and highlights the complex, combined effects of these variables.

The Android platform became one of the most vulnerable targets for cyberattacks in recent times due to a rapid surge in malware embedded apps. Researchers have inves- tigated various machine learning techniques for Android malware detection but most of these techniques are inefficient against the novel malware. The various problems like code obfuscation, the requirement of device root privileges, simulated and small size datasets pose serious flaws to the existing solutions. This work evaluates several machine learning models for mitigating these issues using low-privileged monitorable features sampled in the SherLock dataset. The findings of this research conclude that the XGBoost clas- sifier is the most accurate in detecting the malware compared to other classifiers with 93% overall values of precision, recall, and accuracy. In terms of FNR values, which sig- nify the undetected malware, the XGBoost classifier also performs better than the other algorithms with values of 7.0%.

Diabetes is a disease with high prevalence worldwide, however, about 44% of patients are asymptomatic, which leads to a later diagnosis of the disease and, consequently, increases the risk of developing complications. The development of new approaches for early diagnosis is imperative to allow proper adoption of preventive measures. From a motivational point of view, it is easier for patients to adopt healthy eating habits and lifestyles when there is an altered marker that indicates subclinical disease, particularly in a pathology that remains asymptomatic until advanced stages. Thus, timely diagnosis based on a measurable and monitorable indicator is extremely important so that such behaviors are implemented as early as possible, increasing effective health gains and reducing the costs related to this pathology. Pre-clinical studies in animal models have shown that the etiology of type 2 diabetes mellitus (T2DM) is related to alterations in the carotid bodies (CB), chemosensory organs located in the bifurcation of the carotid arteries. In animals with T2DM it has been observed that the CBs are overactivated causing an increased heart rate, respiratory rate, and blood glucose levels. In humans, this mechanism has been confirmed but is not yet well-characterized. This paper highlights the importance of developing a device that allows early detection of changes in CB activity correlating it with emerging diabetes. The design strategies to prototype the CBmeter were to model and characterize the features of interest for the diagnosis- respiratory rate, heart rate, peripheral oxygen saturation and glucose - in healthy people and people with diabetes using a combination of set commercial sensors pre-existent in the market that were integrated to collect real-time data. After determining health and disease patterns, the CBmeter development pipeline includes a co-design approach in which physiologists, endocrinologists, nurses, computer and electrical engineers, designers and patients are collaborating to develop an easy-to-use, portable, and minimally invasive medical device that associates CB function with endocrine dysregulation, with very small discomfort and risk for users. The definition and specification of the most appropriate architecture for the CBmeter, in order to allow its modularity, signal acquisition and consequently the communication between the sensor/device and the receiver/backend in the most efficient way is being allied to the selection of materials, tools and steps to create an innovative product, that will fill a technical gap in the market, designed for the early diagnosis of metabolic diseases, in a subclinical phase, with the potential to contribute with significant gains for public health in the medium/long term.