The jurisprudence under international human rights treaties has had a considerable impact across countries. Known for addressing complex agendas, the work of expert bodies under the treaties has been credited and relied upon for filling the gaps in the realization of several objectives, including the peace and security agenda. -/- In 1982, the Human Rights Committee (ICCPR), in a General Comment observed that “states have the supreme duty to prevent wars, acts of genocide and other acts of mass violence ... (...) Every effort … to avert the danger of war, especially thermonuclear war, and to strengthen international peace and security would constitute the most important condition and guarantee for the safeguarding of the right to life.” Over the years, all treaty bodies have contributed in this direction, endorsing peace and security so as “to protect people against direct and structural violence … as systemic problems and not merely as isolated incidents …”. A closer look at the jurisprudence on peace and security, emanating from treaty monitoring mechanisms including state periodic reports, interpretive statements, the individual communications procedure, and others, reveals its distinctive nature. (shrink)

This chapter presents the perceptual reality monitoring theory of consciousness (PRM). PRM is a higher-order theory of consciousness. It holds that consciousness involves monitoring the reliability of one’s own sensory signals. I explain how a perceptual reality monitoring mechanism computes the higher order representations that are crucial for consciousness. While PRM accounts for the difference between conscious and unconscious states, it does not explain, on its own, why experiences feel the way they do—the phenomenal character of experience. (...) PRM is compatible with multiple theories of phenomenal character. Here, I show how to combine it with ‘Mental Quality Space’ theory. I finish by presenting empirical evidence for PRM, as well as some of its predictions. (shrink)

This article discloses topical issues of the need for constant monitoring of changes in the business activity in enterprise structures. The main purpose of the study is to monitor the business activity of industrial enterprise structures of Ukraine to predict their development under martial law. A critical analysis of the content of scientific publications to solve the problem of improving the management of business activity of business structures revealed the lack of attention of scientists to the problems under study. (...) The relevance of its solution is due to the scale of the impact of military conflicts on the business activity in enterprise structures, which requires its monitoring to further establish the state and ensure compliance of the business with the norms that are considered necessary to maintain a certain level of stability of development or to survive, to determine areas where the business can improve its activities and become more profitable. The methodological basis is the system of methods used to obtain the final results of the study: theoretical generalization – to deepen the essence of the concept of «monitoring business activity»; analysis, synthesis and logical generalization – to obtain conclusions during monitoring of business confidence and business climate in industry; prognostic – to predict the development of industrial business structures of Ukraine under martial law. The object of research in the work is the business activity of business structures. The article presents the results of monitoring business confidence and business climate in the industry of Ukraine under martial law. Analysis, synthesis and logical generalization of monitoring results became the basis for further forecasting the development of business structures. The results of the study can be useful for business structures that seek to maintain a certain level of stability of development and identify areas of improvement. (shrink)

Type 1 diabetes (T1D) is a chronic illness that requires intensive lifelong management of blood glucose concentrations by means of external insulin administration. There have been substantial developments in the ways of measuring glucose levels, which is crucial to T1D self-management. Recently, continuous glucose monitoring (CGM) has allowed people with T1D to keep track of their blood glucose levels in near real-time. These devices have alarms that warn users about potentially dangerous blood glucose trends, which can often be shared (...) with ther people. CGM is consistently associated with improved glycemic control and reduced hypoglycemia and is currently recommended by doctors. However, due to the costs of CGM, only those who qualify for hospital provision or those who can personally afford it are able to use it, which excludes many people. In this paper, I argue that unequal access to CGM results in: (1) unjust health inequalities, (2) relational injustice, (3) injustice with regard to agency and autonomy, and (4) epistemic injustice. These considerations provide prima facie moral reasons why all people with T1D should have access to CGM technology. I discuss the specific case of CGM policy in the Netherlands, which currently only provides coverage for a small group of people with T1D, and argue that, especially with additional considerations of cost-effectiveness, the Dutch government ought to include CGM in basic health care insurance for all people with T1D. (shrink)

Decision-making by a Data and Safety Monitoring Board (DSMB) regarding clinical trial conduct and termination is intricate and largely limited by cases and rules. Decision-making by legal jury is also intricate and largely constrained by cases and rules. In this paper, I argue by analogy that legal decision-making, which strives for a balance between competing demands of conservatism and innovation, supplies a good basis to the logic behind DSMB decision-making. Using the doctrine of precedents in legal reasoning as my (...) central analog will lead us to a decision-theoretic analogy for much more systematic documentation of decisions in clinical trials. My conclusion is twofold: every DSMB decision should articulate a clear general principle (a ratio decidendi) that gives reason for the decision; and all such decisions should be made public. I use Bartha’s (2010) theory of analogical arguments to both frame and assess my argument by analogy. (shrink)

The target of Second- Language Acquisition (SLA), emerged in the second half of the 20th century, was to be helpful in foreign- language education/ teaching. It denotes mostly the study of individuals (or sometimes groups) who are learning a language consequent to learning their first language when they are young children. At the same time, it signifies the process of learning a second language. The added language is named a second language, but it might indeed be the third, fourth or (...) more which is going to be acquired. The range of SLA comprises informal Second- Language Learning occurring in natural milieus, formal second- language learning occurring in classroom or the one that contains a combination of them both, that is, settings and conditions. The three main aspects for the study of SLA process are the linguistic, psychological and social aspects. The Monitor Theory/ Model postulated by Krashen in the 1970s is a psychological approach in nature. With its five hypotheses (The Acquisition– Learning Hypothesis, The Monitor Hypothesis, The Natural Order Hypothesis, The Input Hypothesis, and The Affective Filter Hypothesis), it tries to find answers to the problems of SLA, such as what does a second- language learner come to know, how the acquisition process takes place, and why some learners are more successful than others? The Monitor Theory (MT) received extensively many criticisms after its appearance and was rejected. Its teaching implications were also at the centre of criticisms. What place does MT occupy in SLA today? This study aims to try to find an answer. The other questions are: How important is the MT for SLA? What kind of criticisms are expressed against it? How fair is the criticism by McLaughlin (1978, 1987)? The working hypotheses of the present work are: The hypotheses developed by Krashen are not/ will not be rejected. Because science is still lying in the so- called agony phase, and cannot find any answers to all questions in psychology (e.g. how exactly is the processing of language; in particular and of mind in general). Moreover, the problems related to memory etc., the thoughts emanated from the MT can probably not be refuted. They have evolved so far and will be evolved further, perhaps with small differences. This research is completely based on the literature written since the time the theory was developed. In other words, it was carried out using a descriptive method without using a special data collection tool. The sources written on the subject were reviewed and an answer to the research questions was tried to be found. Even though the theory is expressed with different names and different meanings today, it has survived all the criticisms made, and it has been concluded that it still occupies an important place in the discipline of second- language acquisition (SLA) and foreign- language teaching. Again, the inquiries carried out since the 1970s delineate that the implications in favour of language education are not very different from those stated by Krashen (1982), which were the products of his opinions in that period. There are still basic consequences grounded on MT for language teaching today. (shrink)

Air pollutants pose a threat to biodiversity throughout the world. This study was conducted to evaluate atmospheric element accumulation in Isparta city, including Gölcük Nature Park, located in the Western Mediterranean Region of Turkey. It is aimed to determine the air quality and potential pollutant sources in the region through lichen biomonitoring. Specimens of the epiphytic foliose lichen Physcia aipolia (Erh. ex Humb.) Fürnr. were sampled from 14 sites in the study area and analyzed by ICP-MS with reference material in (...) order to detect 11 trace elements; Al, As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, V, and Zn. The spatial distribution of these airborne elements in the study area was mapped. The results showed that the elemental sequence in terms of average concentrations measured was as follows: Ni >Cr >V >Fe >As >Al >Zn >Cu> >Cd >Mn >Pb. The results of cluster analyses of the elemental data indicated that the 3 major contaminants in the urban area were Cr, Ni, and V, probably due to the extensive use of coal in heating facilities and gasoline in vehicles. P. aipolia specimens accumulated maximal concentrations of As, Cr, Fe, Ni, and V in the northern and the southeastern localities surrounding the city, while Cd, Pb were most abundant in the eastern edge of Gölcük Nature Park. The pollution in Isparta city with heavy metal is worse than expected, mostly due to the extensive use of coal as fossil fuel. In addition, it seems to be associated with the city's topographic and climatic characteristics, e.g. inversion effects. (shrink)

The data collected by these sensors are transmitted to a centralized system where optimization algorithms, such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Simulated Annealing (SA), are applied to optimize sensor placement, data transmission, and processing efficiency. This ensures accurate, real-time pollution monitoring and data analysis, providing actionable insights for policymakers, environmental agencies, and the general public. The system's performance is evaluated through simulations and real-world experiments, demonstrating its capability to deliver reliable and timely pollution data. Future (...) work will explore the integration of machine learning techniques for predictive analytics and the expansion of the sensor network for broader coverage. (shrink)

Personal Health Monitoring (PHM) uses electronic devices which monitor and record health-related data outside a hospital, usually within the home. This paper examines the ethical issues raised by PHM. Eight themes describing the ethical implications of PHM are identified through a review of 68 academic articles concerning PHM. The identified themes include privacy, autonomy, obtrusiveness and visibility, stigma and identity, medicalisation, social isolation, delivery of care, and safety and technological need. The issues around each of these are discussed. The (...) system / lifeworld perspective of Habermas is applied to develop an understanding of the role of PHMs as mediators of communication between the institutional and the domestic environment. Furthermore, links are established between the ethical issues to demonstrate that the ethics of PHM involves a complex network of ethical interactions. The paper extends the discussion of the critical effect PHMs have on the patient’s identity and concludes that a holistic understanding of the ethical issues surrounding PHMs will help both researchers and practitioners in developing effective PHM implementations. (shrink)

Do self‐monitoring accounts, a dominant account of the positive symptoms of schizophrenia, explain auditory verbal hallucination? In this essay, I argue that the account fails to answer crucial questions any explanation of auditory verbal hallucination must address. Where the account provides a plausible answer, I make the case for an alternative explanation: auditory verbal hallucination is not the result of a failed control mechanism, namely failed self‐monitoring, but, rather, of the persistent automaticity of auditory experience of a voice. (...) My argument emphasizes the importance of careful examination of phenomenology as providing substantive constraints on causal models of the positive symptoms in schizophrenia. (shrink)

The attendance is taken in every organization. Traditional approach for attendance is, professor calls student name & record attendance. For each lecture this is wastage of time. To avoid these losses, we are about to use automatic process which is based on image processing. In this project approach, we are using face detection & face recognition system. The first phase is pre-processing where the face detection is processed through the step image processing. It includes the face detection and face recognition (...) process. Second phase is feature extraction. Step by step execution of these techniques (Image Processing) helps to achieve the final output. The working of this project is to detect and recognize the face and mark the attendance for the corresponding face in the database. Input of this project is face detection and recognition and output is to mark the attendance. Our project is being presented as a solution for the Automatic Attendance Marking System. It is designed to be reliable and low power. The Automatic face detection and recognition proposed to attendance marking in database acts as the solution for the automatic attendance marking system.. (shrink)

This dissertation is about the relationship between Epistemology and other domains. In it I want to show that in an important sense, Epistemology is an autonomous domain. That is, epistemic vocabulary (e.g., “knowledge”, “justification”, “rationality”, “epistemic reason”, etc.) cannot be analyzed without remainder into non-epistemic vocabulary. Epistemic phenomena must be explained in terms of epistemic reasons and the form of assessment proprietary to them. Although epistemic vocabulary cannot be reduced to the vocabulary of other domains, Epistemology is nonetheless connected with (...) other domains in an important way. In this dissertation I focus on the connection between Epistemology and the Philosophy of Mind. I distinguish different forms cognitive self-monitoring can take and corresponding forms of cognitive autonomy. The kind of self-monitoring that receives the most attention involves simulating interpersonal argumentation. I argue that the capacity to self-monitor in this way grounds familiar epistemic standards (e.g., knowledge and justification) and explains how reasons get their grip on us. On the picture that emerges, Epistemology and Philosophy of Mind need to be done in tandem. Epistemology gives us the normative framework that is modeled by the self-monitoring system. The self-monitoring system, conversely, explains the kind of activity we engage in that makes that normative framework applicable to us. Epistemic reasons themselves are just episodes of this kind of activity. In Chapter 1 I argue that epistemic luck cannot be analyzed in non-epistemic terms. Here I generalize Jennifer Lackey’s criticism of Duncan Pritchard’s safety-based account of epistemic luck to all reductive theories. I argue that they will either be extensionally inadequate, or they will illicitly presuppose the vocabulary they are trying to reduce. The upshot is that epistemic luck can only be understood in terms of the epistemic assessment of reasons. By extension, we can’t give a reductive analysis of knowledge. This is not to say we cannot analyze knowledge, just that we can’t analyze away the epistemic vocabulary without remainder. In chapter 2 I explain the relation between epistemic luck, epistemic justification, and knowledge. I argue that previous work in the defeasible reasoning tradition, despite being on the right track, fell short of realizing its full potential. This is because the account of how these three things relate given by its proponents was insufficiently unified, which encouraged many epistemologists to abandon the defeasible reasoning tradition entirely. I argue that a unified and principled account of their relation is possible, and it allows for an elegant analysis of knowledge. In slogan form: good reasons are apparent to the knowing subject. In chapter 3 I extend the defeasible reasoning tradition to explain how knowledge is gradable. I show that this enables us to bring the debates about fake barns and knowledge from falsehoods to ecumenical resolutions, while also shedding light on a new kind of case. Furthermore, I explain how background assumptions are themselves defeasible and some of the epistemic significance of this fact. In chapter 4 I make the connection between Epistemology and Philosophy of Mind. I argue that the self-monitoring system of cognitively mature humans uses a model of the normative framework described in the previous chapters to regulate its own cognition. Here I build on that claim to develop an account of the role played by knowledge and justification in doxastic social coordination. I build on the claim that background assumptions are themselves defeasible to develop an account of the foundations of knowledge according to which they are social but not brutely sociological. In chapter 5 I discuss the relation between the epistemic states of cognitively mature humans, children, and non-human animals. I do this in a way meant to integrate an insight from virtue epistemology into the reasons-first picture developed here: positive epistemic standing is a state attributable to the subject. In chapter 6 I discuss the metaphysics of epistemic reasons. I claim that they are episodes of the activity of reasoning. In the preceding chapters, we get a sense of what that activity involves. Here I argue that the materials developed there put us in a position to understand what epistemic reasons are. This account incorporates the insights of rival positions while sidestepping familiar objections to them. The resulting picture is in line with the non-reductive approach to the epistemic developed so far. In fact, it goes further than other “reasons-first” approaches to Epistemology by claiming that reasons are not only basic within Epistemology, but they are also basic full-stop. One key consideration for my argument here is that reasons are, by their very nature, competitors. Although this point is generally acknowledged in the literature on reasons, its consequences for the metaphysics of reasons hasn’t been. Participants in the debate about the metaphysics of reasons typically try to identify reasons with something (e.g., facts or mental states) that are either not competitors, or only competitors insofar as they constitute, or bear on the epistemic assessment of, episodes of reasoning. (shrink)

Many philosophers and psychologists have sought to explain experiences of auditory verbal hallucinations and “inserted thoughts” in schizophrenia in terms of a failure on the part of patients to appropriately monitor their own inner speech. These self-monitoring accounts have recently been challenged by some who argue that AVHs are better explained in terms of the spontaneous activation of auditory-verbal representations. This paper defends two kinds of self-monitoring approach against the spontaneous activation account. The defense requires first making some (...) important clarifications concerning what is at issue in the dispute between the two forms of theory. A popular but problematic self-monitoring theory is then contrasted with two more plausible conceptions of what the relevant self-monitoring deficits involve. The first appeals to deficits in the neural mechanisms that normally filter or attenuate sensory signals that are the result of one’s own actions. The second, less familiar, form of self-monitoring approach draws an important analogy between Wernicke’s aphasia and AVHs in schizophrenia. This style of self-monitoring theory pursues possible connections among AVHs, inserted thoughts, and the disorganized speech characteristic formal thought disorder. (shrink)

An invited commentary on Ara Norenzayan's Big Gods: How Religion Transformed Cooperation and Conflict, focusing on whether early China constitutes an exception to his general theory.

One method for preventing the spread of the coronavirus and other contagious diseases is through social distancing. Therefore, creating a tool to measure and quickly discover the precise distance is necessary. In order to prevent physical contact between individuals, this study aimed to detects individuals’ physical distance, through an inaugurated battery-powered device that monitors physical distance through wireless technology. Specifically, in public or crowded areas, to lessen the spread of the virus. This study focuses on detecting people’s physical distance in (...) the region of interest utilizing an Ultrasonic and VL53L0X sensors and determining the significant difference between the two sensors in monitoring physical distance. This study employs an applied experimental research design. The efficiency of both sensors in measuring physical distance was evaluated through analysis. The Ultrasonic and VL53L0X sensors underwent 15 tests. Furthermore, the researchers effectuated a t-test to determine the significant difference between the two sensors. Data gathered revealed that the sensors’ combined mean in terms of measuring physical distance indicates that the ultrasonic sensor performed better than VL53L0X, measuring 134.7 cm, notwithstanding 99.8 cm for the VL53L0X sensor. Complementary to this, the results of the t-test show that the VL53L0X sensor and Ultrasonic sensor have a significant difference in terms of distance precision. (shrink)

In addition to existing practices and norms within the institutions to which they belong, scientists form an epistemic community. The flow of information, the processes of belief formation, and the assumptions scientists are making determine the structure of an epistemic community. Members of such communities can be categorized as epistemic experts or epistemic agents. In exceptional circumstances, such as the crisis caused by the global coronavirus pandemic, the existing organization, conventions, and rules within the epistemic community are disrupted. In times (...) of crisis, epistemic agents’ trust in experts becomes as crucial as scientific knowledge. Trust epistemic agents have in experts may decrease in crisis situations and affect experts’ roles within the epistemic community. This puts epistemic experts in the position of needing to reestablish their trustworthiness through various rhetorical attempts. Here, we examine some of those attempts from the existing framework of rhetorical strategies used to reestablish or defend one’s own expert role, but on novel data. To that end, we use examples of epistemic experts’ justifications when confronted with public questioning about their behavior amidst the coronavirus crisis. We analyze experts’ rhetorical approaches via qualitative content analysis and replicate four rhetorical strategies experts use when defending their epistemic positions that are previously established in analyses of similar cases in other crisis situations. (shrink)

The current increase of air pollution rates and its consequences of global warming, health problems and threats to human lives necessitate the continuous search for more efficient and cost effective gas monitoring devices. Devices that is easily available and implementable worldwide. In developing countries the cost and the availability of the equipment is one of the obstacles that contribute to not having an efficient monitoring system. Hence, modifying cheap and easily available devices to work as pollution monitoring (...) system will be an asset in this direction. In this work I am presenting the design of a computer based pollution detection and measuring system using cheap CO (Carbon Monoxide) alarms used in homes. The outcome is a cost-effective computer based CO monitoring system that is easily available and could be easily modified to work as a network based CO nose. A C# based program is also designed to show and log the sensor readings in an easy to use and read Window. (shrink)

Open-content communities that focus on co-creation without requirements for entry have to face the issue of institutional trust in contributors. This research investigates the various ways in which these communities manage this issue. It is shown that communities of open-source software—continue to—rely mainly on hierarchy (reserving write-access for higher echelons), which substitutes (the need for) trust. Encyclopedic communities, though, largely avoid this solution. In the particular case of Wikipedia, which is confronted with persistent vandalism, another arrangement has been pioneered instead. (...) Trust (i.e. full write-access) is ‘backgrounded’ by means of a permanent mobilization of Wikipedians to monitor incoming edits. Computational approaches have been developed for the purpose, yielding both sophisticated monitoring tools that are used by human patrollers, and bots that operate autonomously. Measures of reputation are also under investigation within Wikipedia; their incorporation in monitoring efforts, as an indicator of the trustworthiness of editors, is envisaged. These collective monitoring efforts are interpreted as focusing on avoiding possible damage being inflicted on Wikipedian spaces, thereby being allowed to keep the discretionary powers of editing intact for all users. Further, the essential differences between backgrounding and substituting trust are elaborated. Finally it is argued that the Wikipedian monitoring of new edits, especially by its heavy reliance on computational tools, raises a number of moral questions that need to be answered urgently. (shrink)

The continuous growth of healthcare data has made it essential to develop efficient systems that not only alert healthcare providers but also visualize patient data in a comprehensible way. This study introduces a Health Alert System integrated with Report Visualization powered by Data Analytics to improve patient monitoring and alerting mechanisms. By leveraging real-time data from wearable sensors and hospital records, the system generates health alerts based on deviations from normal parameters. The proposed system combines predictive analytics and historical (...) data to flag potential emergencies before they occur. The visual analytics platform provides comprehensive reports to healthcare providers, enabling them to monitor trends, identify risk factors, and make informed decisions. This approach significantly enhances patient care by minimizing delays in response and improving overall health outcomes. The system's architecture, based on big data frameworks, supports scalable and efficient data processing. The study demonstrates how the integration of predictive models and data visualization tools can revolutionize health alert systems, making them more responsive and adaptive to individual patient needs. Future enhancements will focus on incorporating machine learning models for more personalized predictions and extending the system's capabilities to remote patient care. (shrink)

The continuous growth of healthcare data has made it essential to develop efficient systems that not only alert healthcare providers but also visualize patient data in a comprehensible way. This study introduces a Health Alert System integrated with Report Visualization powered by Data Analytics to improve patient monitoring and alerting mechanisms. By leveraging real-time data from wearable sensors and hospital records, the system generates health alerts based on deviations from normal parameters. The proposed system combines predictive analytics and historical (...) data to flag potential emergencies before they occur. The visual analytics platform provides comprehensive reports to healthcare providers, enabling them to monitor trends, identify risk factors, and make informed decisions. This approach significantly enhances patient care by minimizing delays in response and improving overall health outcomes. The system's architecture, based on big data frameworks, supports scalable and efficient data processing. The study demonstrates how the integration of predictive models and data visualization tools can revolutionize health alert systems, making them more responsive and adaptive to individual patient needs. Future enhancements will focus on incorporating machine learning models for more personalized predictions and extending the system's capabilities to remote patient care. (shrink)

This study analyzed the monitoring and evaluation of HIV/AIDS prevention programs in Southern Senatorial District of Cross River State, Nigeria. The study considered different levels of care/support and tested for locational variations in the monitoring/evaluation of HIV/AIDs prevention programs. A descriptive survey research design was utilized. This study covered 596 public health employees (doctors, nurses, pharmacists, and laboratory employees) in the study area. A sample of 239 respondents was chosen using the proportional stratified random sampling procedure. Data was (...) collected using a questionnaire constructed by the researchers and validated by specialists. Data gathered were analyzed using descriptive and inferential statistics. Results indicated that HIV/AIDs programs have been successfully monitored/evaluated to a high extent. High rates of success in the monitoring/evaluation of HIV/AIDs prevention programs are attributable to high rates of care/support provided to people living with HIV/AIDs. There was a significant variation in the monitoring/evaluation of HIV/AIDs prevention programs based on the location of health facilities, with higher rates recorded for urban areas. Based on the findings, it was concluded that the monitoring/evaluation of HIV/AIDs prevention programs in the Southern Senatorial District of Cross River State had recorded a significant level of success. The study recommended, among others, that there should be even distribution of medical facilities, resources and personnel to both urban and rural areas to promote equity and access to materials needed to contain or mitigate the spread of the pandemic across all locations. (shrink)

Complex systems are difficult to manage, operate and maintain. This is why we see teams of highly specialised engineers in industries such as aerospace, nuclear and subsurface. Condition based monitoring is also employed to maximise the efficiency of extensive maintenance programmes instead of using periodic maintenance. A level of automation is often required in such complex engineering platforms in order to effectively and safely manage them. Advances in Artificial Intelligence related technologies have offered greater levels of automation but this (...) potentially pivots the weight of decision making away from the operator to the machine. Implementing AI or complex algorithms into a platform can mean that the Operators’ control over the system is diminished or removed altogether. For example, in the Boeing 737 Air Max Disaster, AI had been added to a platform and removed the operators’ control of the system. This meant that the operator could not then move outside the extremely reserved, algorithm defined, “envelope” of operation. This paper analyses the challenges of AI driven condition based monitoring where there is a potential to see similar consequences to those seen in control engineering. As the future of society becomes more about algorithm driven technology, it is prudent to ask, not only whether we should implement AI into complex systems, but how this can be achieved ethically and safely in order to reduce risk to life. (shrink)

Prescription Drug Monitoring Programs (PDMPs) contain detailed information about which controlled medications physicians prescribe individuals, including where, when, how much, by whom, and more. The programs allow physicians to glimpse into the life of each patient that visits them — sometimes before a single word is exchanged between them. Every state has a PDMP, and almost all states share the data they collect through it. In this paper, I argue that informed consent should be required for recording of prescriptions (...) related to addiction management into the PDMP. (shrink)

Wireless Sensors Network is a novel field shows tremendous application potential. To monitor the environmental parameters of high-tech polyhouse the Wireless Sensors Network (WSN) is developed. The heart of this ubiquitous field is the Wireless Sensor Node. Moreover, the field of microcontroller based embedded technology is innovative and more reliable. Therefore, based on an embedded technology and the RF module Zigbee a wireless senor node is designed about highly promising AVR ATmega8L microcontroller and implemented for WSN development. Recently, the modern (...) agriculturists are demanding sophisticated instrumentation for measurement and control of environmental parameters of the polyhouse. To enhance crop yield one has to provide controlled environment to the crop. The humidity is important parameter, which plays vital role on the crop yield. Therefore, a Wireless Sensors Network (WSN) is designed and implemented for monitoring of humidity of polyhouse and the results of implementation are interpreted in this paper. (shrink)

This approach significantly enhances patient care by minimizing delays in response and improving overall health outcomes. The system's architecture, based on big data frameworks, supports scalable and efficient data processing. The study demonstrates how the integration of predictive models and data visualization tools can revolutionize health alert systems, making them more responsive and adaptive to individual patient needs. Future enhancements will focus on incorporating machine learning models for more personalized predictions and extending the system's capabilities to remote patient care.

The growth and development of children are closely related to the role of a mother, not a few mothers, and having the task of caring for children and working women, which will lead to suboptimal childcare. At this time, many android-based information system facilities that can be used to streamline child care for a mother who is a working woman. This study aimed to provide an overview and ideas of using android-based digital media in childcare to maximize children's growth and (...) development for working mothers with a literature review method. From the study results and review of 10 selected journals, it was concluded that for parents of workers who cannot maximize childcare time or parenting time, many applications could facilitate parents to monitor the child's growth and development safely. The development of a child health nursing management information system can include healthy children, sick children, education, environment, and parenting patterns. The implication of developing a child health nursing management information system during parenting is very useful ad preventive and promotive action in children’s health. Child nurses can effectively, efficiently, quickly, and accurately identify problems that arise in the preventive process so that they are expected to make nursing interventions that are also right on target. (shrink)

Abstract—Generator set (genset) is a backup power supply which is used when the PLN supply is off. With such an important function, the generator set maintenance must be taken care of for long life durability. Monitoring activity is usually conducted on a regular basis, but still run manually by relying on operators who go directly to the plant. This research goes over the making of HMI remote control system for generator set in order to produce effective and continuous reporting. (...) HMI is designed by Microsoft Visual Studio 2012 software with C # programming language. The data communication used is serial asynchronous wireless communication using 3DR Telemetry 433MHz. The prototype generator set uses an Atmega16 microcontroller which is programmed by CodeVision AVR 2.05.3. Daily data storage and reports use Microsoft Excel. Based on the tests performed, it can be concluded that the HMI system works well. The HMI monitoring system can accurately monitor the plant on fuel percentage and data difference of 1 celcius degree at temperature. The alarm test works well. The farthest test resulted was 84.6 meters. In testing data storage and daily reports all the required information can be stored properly. (shrink)

—One of the promising applications of wireless sensor networks (WSNs) is monitoring of the human body for health concerns. For this purpose, a large number of small sensors are implanted in the human body. These sensors altogether provide a network of wireless sensors (WBANs) and monitor the vital signs and signals of the human body; these sensors will then send this information to the doctor. The most important application of the WBAN is the implementation of the monitoring network (...) for patient safety in the hospital environment. In this case, supporting patients’ mobility is one of the basic needs, which has been underestimated in recent studies. The problem that involves providing the required energy for the units used in this type of network is challenging; for this reason, sent/ received units with very low power consumption and with a very small radius are used in order to save energy. The resulting small sending range, leads to the lack of support for patients' mobility. In this paper, the AD HOC mode is suggested for use to establish a network and a multi-path routing algorithm, for the purpose of importing patients’ mobility in hospital setting. The results of the simulation show that in addition to supporting patients' mobility, the use of the proposed idea instead of previously presented protocols, reduces delays in data transmission and energy consumption; and it also increases the delivery rate depending on the destination and the lifetime of the network, while on the other hand, it increases routing overhead. (shrink)

The continuous growth of healthcare data has made it essential to develop efficient systems that not only alert healthcare providers but also visualize patient data in a comprehensible way. This study introduces a Health Alert System integrated with Report Visualization powered by Data Analytics to improve patient monitoring and alerting mechanisms. By leveraging real-time data from wearable sensors and hospital records, the system generates health alerts based on deviations from normal parameters. The proposed system combines predictive analytics and historical (...) data to flag potential emergencies before they occur. The visual analytics platform provides comprehensive reports to healthcare providers, enabling them to monitor trends, identify risk factors, and make informed decisions. (shrink)

The EdTech revolution in India has emerged as a transformative force, particularly during and after the COVID-19 pandemic, when traditional education systems faced unprecedented disruptions. While digital technologies have unlocked new opportunities for teaching and learning, they have also exposed systemic inequities and deepened the existing digital divide. This paper examines how EdTech is reshaping India's education landscape by addressing these challenges, with a focus on both the opportunities it presents and the barriers it creates.

The proposed system combines predictive analytics and historical data to flag potential emergencies before they occur. The visual analytics platform provides comprehensive reports to healthcare providers, enabling them to monitor trends, identify risk factors, and make informed decisions. This approach significantly enhances patient care by minimizing delays in response and improving overall health outcomes. The system's architecture, based on big data frameworks, supports scalable and efficient data processing. The study demonstrates how the integration of predictive models and data visualization tools (...) can revolutionize health alert systems, making them more responsive and adaptive to individual patient needs. Future enhancements will focus on incorporating machine learning models for more personalized predictions and extending the system's capabilities to remote patient care. (shrink)

In the paper, I argue there is a whole political logistics to deportation. This is made visible by bringing the concept of microphysics to bear on the topic. Taking the case of enforced and escorted removals from the UK, I show that this logistics is vividly and graphically documented in the inspection reports. Hitherto largely ignored, inspection reports offer researchers a trove of information regarding the mechanisms and procedures of deportation. As I finally draw out, this focus can speak to (...) questions about the relationship of ethics to deportation: the inspection reports show how a certain form of ethical calculation, based on a risk-based approach to the use of force has been inscribed into the practices of deportation. DOI 10.17879/95189425134. (shrink)

Cloud computing has become an essential component of enterprises and organizations globally in the current era of digital technology. The cloud has a multitude of advantages, including scalability, flexibility, and cost-effectiveness, rendering it an appealing choice for data storage and processing. The increasing storage of sensitive information in cloud environments has raised significant concerns over the security of such systems. The frequency of cyber threats and attacks specifically aimed at cloud infrastructure has been increasing, presenting substantial dangers to the data, (...) reputation, and financial stability of enterprises. Conventional security methods can become inadequate when confronted with ever intricate and dynamic threats. Artificial Intelligence (AI) technologies possess the capacity to significantly transform cloud security through their ability to promptly identify and thwart assaults, adjust to emerging risks, and offer intelligent perspectives for proactive security actions. The objective of this research study is to investigate the utilization of AI technologies in augmenting the security measures within cloud computing systems. This paper aims to offer significant insights and recommendations for businesses seeking to protect their cloud-based assets by analyzing the present state of cloud security, the capabilities of AI, and the possible advantages and obstacles associated with using AI into cloud security policies. (shrink)

The rapid advancement of urbanization has necessitated the creation of "smart cities," where information and communication technologies (ICT) are used to improve the quality of urban life. Central to the smart city paradigm is data integration—connecting disparate data sources from various urban systems, such as transportation, healthcare, utilities, and public safety. This paper explores the role of Artificial Intelligence (AI) in facilitating data integration within smart cities, focusing on how AI technologies can enable effective urban governance. By examining the current (...) landscape of data integration and AI in smart cities, we highlight key challenges, solutions, and future trends. We conclude that AI-driven data integration is essential for optimizing city operations, fostering sustainability, and enhancing decision-making for urban governance. This paper explores the role of Artificial Intelligence (AI) in facilitating data integration within smart cities, focusing on how AI technologies can enable effective urban governance. By examining the current landscape of data integration and AI in smart cities, we highlight key challenges, solutions, and future trends. We conclude that AI-driven data integration is essential for optimizing city operations, fostering sustainability, and enhancing decision-making for urban governance. (shrink)

The rapid advancement of urbanization has necessitated the creation of "smart cities," where information and communication technologies (ICT) are used to improve the quality of urban life. Central to the smart city paradigm is data integration—connecting disparate data sources from various urban systems, such as transportation, healthcare, utilities, and public safety. This paper explores the role of Artificial Intelligence (AI) in facilitating data integration within smart cities, focusing on how AI technologies can enable effective urban governance. By examining the current (...) landscape of data integration and AI in smart cities, we highlight key challenges, solutions, and future trends. We conclude that AI-driven data integration is essential for optimizing city operations, fostering sustainability, and enhancing decision-making for urban governance. This paper explores the role of Artificial Intelligence (AI) in facilitating data integration within smart cities, focusing on how AI technologies can enable effective urban governance. By examining the current landscape of data integration and AI in smart cities, we highlight key challenges, solutions, and future trends. We conclude that AI-driven data integration is essential for optimizing city operations, fostering sustainability, and enhancing decision-making for urban governance. (shrink)

By leveraging convolutional neural networks (CNNs), the model identifies various plant diseases with high accuracy. The experimental setup includes a dataset consisting of healthy and diseased leaf images of different plant species. The dataset is preprocessed to remove noise and augmented to address the issue of class imbalance. The CNN model is then trained, validated, and tested on this dataset. The results indicate that the deep learning model achieves a classification accuracy of over 95% for most plant diseases. Additionally, the (...) system is designed to provide real-time feedback to farmers, helping them take immediate corrective action. This automated approach eliminates the need for expert human intervention and can be deployed on mobile devices for ease of use in rural areas. The potential future applications of this system include integration with precision agriculture techniques and expansion to a wider range of crops. (shrink)

The research material proposes the use of decision support information-analytical technology in discharge military personnel employment, which, in contrast to the usual processing of survey results, makes it possible to obtain more information for decision-making. Adherence to such an approach in the development of public administration mechanisms increases the likelihood that in the case of their implementation in the country there will be positive changes, as they will indirectly take into account the availability of necessary resources. Information and analytical technology (...) to support decisions in the field of labor economics substantiates the development of the example of discharged military personnel social welfare. According to the content, the developed decision support information-analytical technology in the field of labor economics provides for the following components: formation of social protection mechanisms; development of a questionnaire on the use of the appropriate mechanism; statistical analysis of survey results (generation of empirical distributions of answers to questions relative frequencies; comparison of answers medians; correspondences analysis; factor analysis; analysis of hierarchies); meaningful interpretation; decision making. (shrink)

How does the monitoring of a testifier's credibility by recipients of testimony bear upon the epistemic licence accruing to a recipient's belief in the testifier's communications? According to an intuitive and philosophically influential conception, licensed acceptance of testimony requires that recipients of testimony monitor testifiers with respect to their credibility. I argue that this conception, however, proves to be untenable when confronted with the wealth of empirical evidence bearing on the ways in which testifiers and their interlocutors actually interact.

Research in the psychology of deception detection implies that Fricker, in making her case for reductionism in the epistemology of testimony, overestimates both the epistemic demerits of the antireductionist policy of trusting speakers blindly and the epistemic merits of the reductionist policy of monitoring speakers for trustworthiness: folk psychological prejudices to the contrary notwithstanding, it turns out that monitoring is on a par (in terms both of the reliability of the process and of the sensitivity of the beliefs (...) that it produces) with blind trust. The consequence is that while (a version of) Fricker’s argument for the necessity of a reduction succeeds, her argument for the availability of reductions fails. This does not, however, condemn us to endorse standard pessimistic reductionism, according to which there is no testimonial knowledge, for recent research concerning the methods used by subjects to discover deception in non-laboratory settings suggests that only a more moderate form of pessimism is in order. (shrink)

According to phenomenal conservatism or dogmatism, perceptual experiences can give us immediate justification for beliefs about the external world in virtue of having a distinctive kind of phenomenal character—namely phenomenal force. I present three cases to show that phenomenal force is neither pervasive among nor exclusive to perceptual experiences. The plausibility of such cases calls out for explanation. I argue that contrary to a long-held assumption, phenomenal force is a separate, non-perceptual state generated by some metacognitive mechanisms that monitor one’s (...) first-order mental processes and states. This new account advances our understanding of the nature of phenomenal force. (shrink)

Artificially Intelligent (AI) systems have ushered in a transformative era across various domains, yet their inherent traits of unpredictability, unexplainability, and uncontrollability have given rise to concerns surrounding AI safety. This paper aims to demonstrate the infeasibility of accurately monitoring advanced AI systems to predict the emergence of certain capabilities prior to their manifestation. Through an analysis of the intricacies of AI systems, the boundaries of human comprehension, and the elusive nature of emergent behaviors, we argue for the impossibility (...) of reliably foreseeing some capabilities. By investigating these impossibility results, we shed light on their potential implications for AI safety research and propose potential strategies to overcome these limitations. (shrink)

What entitles you to rely on information received from others? What entitles you to rely on information retrieved from your own memory? Intuitively, you are entitled simply to trust yourself, while you should monitor others for signs of untrustworthiness. This article makes a case for inverting the intuitive view, arguing that metacognitive monitoring of oneself is fundamental to the reliability of memory, while monitoring of others does not play a significant role in ensuring the reliability of testimony.

Linguistic intuitions are a central source of evidence across a variety of linguistic domains. They have also long been a source of controversy. This chapter aims to illuminate the etiology and evidential status of at least some linguistic intuitions by relating them to error signals of the sort posited by accounts of on-line monitoring of speech production and comprehension. The suggestion is framed as a novel reply to Michael Devitt’s claim that linguistic intuitions are theory-laden “central systems” responses, rather (...) than endorsed outputs of a modularized language faculty (the “Voice of Competence”). Along the way, it is argued that linguistic intuitions may not constitute a natural kind with a common etiology; and that, for a range of cases, the process by which intuitions used in linguistics are generated amounts to little more than comprehension. (shrink)

The visual analytics platform provides comprehensive reports to healthcare providers, enabling them to monitor trends, identify risk factors, and make informed decisions. This approach significantly enhances patient care by minimizing delays in response and improving overall health outcomes. The system's architecture, based on big data frameworks, supports scalable and efficient data processing. The study demonstrates how the integration of predictive models and data visualization tools can revolutionize health alert systems, making them more responsive and adaptive to individual patient needs. Future (...) enhancements will focus on incorporating machine learning models for more personalized predictions and extending the system's capabilities to remote patient care. (shrink)

The data collected by these sensors are transmitted to a centralized system where optimization algorithms, such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Simulated Annealing (SA), are applied to optimize sensor placement, data transmission, and processing efficiency. This ensures accurate, real-time pollution monitoring and data analysis, providing actionable insights for policymakers, environmental agencies, and the general public. The system's performance is evaluated through simulations and real-world experiments, demonstrating its capability to deliver reliable and timely pollution data. Future (...) work will explore the integration of machine learning techniques for predictive analytics and the expansion of the sensor network for broader coverage. (shrink)

Air pollution is a significant environmental concern that affects human health, ecosystems, and climate change. Effective monitoring and management of outdoor air quality are crucial for mitigating its adverse effects. This paper presents an advanced approach to outdoor pollution measurement utilizing Internet of Things (IoT) technology, combined with optimization techniques to enhance system efficiency and data accuracy. The proposed framework integrates a network of IoT sensors that continuously monitor various air pollutants, such as particulate matter (PM), carbon monoxide (CO), (...) sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and ozone (O₃), across different geographic locations. The data collected by these sensors are transmitted to a centralized system where optimization algorithms, such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Simulated Annealing (SA), are applied to optimize sensor placement, data transmission, and processing efficiency. This ensures accurate, real-time pollution monitoring and data analysis, providing actionable insights for policymakers, environmental agencies, and the general public. (shrink)

Ancient Egyptians precisely direct their temples and tombs to specific astronomical points, as attested in the designs of the Old kingdom pyramids and related temples. Likewise, the same approach was used in many religious and funerary buildings across the sequential historical epochs of ancient Egypt. This research introduces what can be called "astronomical design improvements" conducted by ancient Egyptians to secure a precise orientation for a specific direction of religious and funerary monuments. Moreover, this precise orientation requires observatories used for (...) the orientation and monitoring of geographical directions. Therefore, this paper discusses the inquiring; are there any Astronomical Observatories evidences in ancient Egypt? (shrink)

Inner speech is commonly understood as the conscious experience of a voice within the mind. One recurrent theme in the scientific literature is that the phenomenon involves a representation of overt speech, for example, a representation of phonetic properties that result from a copy of speech instructions that were ultimately suppressed. I propose a larger picture that involves some embodied objects and their misperception. I call it “the Body Error Theory,” or BET for short. BET is a form of illusionism, (...) but the particular version I favor is a cross-modal illusion. Newly described here, my hypothesis is that the experience of inner speech arises from a mix of interoception and audition. Specifically, there is the detection of slight but well-confirmed activities in the speech musculature that occur during inner speech, which helps to transform representations of normal but quiet nonverbal sounds that inevitably occur during inner speech, from breathing to background noise, into a mistaken perception of inner speech. Simply put, activities in the speech musculature mix with sounds to create the appearance of speech sounds, which thus explains the “voice within the mind.” I also show how BET’s cross-modal system fits with standard information processing accounts for speech monitoring and how it accommodates the central insights of leading theories of inner speech. In addition, I show how BET is supported by data from experience-sampling surveys and how it can be empirically tested against its rivals. (shrink)

The results are interpreted in terms of a deficit in initial rule learning and subsequent generalization of these rules to new stimuli. Negative feedback is adequately processed at a neural level but this information is not used to improve behaviour on subsequent trials. As learning is degraded, the process of error detection at the moment of the actual response is diminished. Therefore, the current study demonstrates that disturbed error-monitoring processes play a central role in the often reported learning deficits (...) in individuals with PP. (shrink)

In recent years there has been an explosion of interest in Artificial Intelligence (AI) both in health care and academic philosophy. This has been due mainly to the rise of effective machine learning and deep learning algorithms, together with increases in data collection and processing power, which have made rapid progress in many areas. However, use of this technology has brought with it philosophical issues and practical problems, in particular, epistemic and ethical. In this paper the authors, with backgrounds in (...) philosophy, maternity care practice and clinical research, draw upon and extend a recent framework for shared decision-making (SDM) that identified a duty of care to the client's knowledge as a necessary condition for SDM. This duty entails the responsibility to acknowledge and overcome epistemic defeaters. This framework is applied to the use of AI in maternity care, in particular, the use of machine learning and deep learning technology to attempt to enhance electronic fetal monitoring (EFM). In doing so, various sub-kinds of epistemic defeater, namely, transparent, opaque, underdetermined, and inherited defeaters are taxonomized and discussed. The authors argue that, although effective current or future AI-enhanced EFM may impose an epistemic obligation on the part of clinicians to rely on such systems' predictions or diagnoses as input to SDM, such obligations may be overridden by inherited defeaters, caused by a form of algorithmic bias. The existence of inherited defeaters implies that the duty of care to the client's knowledge extends to any situation in which a clinician (or anyone else) is involved in producing training data for a system that will be used in SDM. Any future AI must be capable of assessing women individually, taking into account a wide range of factors including women's preferences, to provide a holistic range of evidence for clinical decision-making. (shrink)