Air pollution is a critical challenge for urban areas, contributing to public health crises and environmental degradation. Traditional air quality monitoring systems often lack the granularity and adaptability needed to address dynamic pollution sources and patterns. This paper explores how Artificial Intelligence (AI) and IoT technologies can enhance air quality management in smart cities by enabling real-time monitoring, pollution source identification, and adaptive mitigation strategies. By integrating data from IoT sensors, satellite imagery, and traffic systems, cities (...) can reduce pollution levels, improve public health outcomes, and promote sustainable urban environments. Experimental results demonstrate significant improvements in pollution detection accuracy, mitigation efficiency, and public awareness, offering a sustainable blueprint for urban air quality management. (shrink)

Wildfires have become an increasing global threat to public health and quality of life. Many countries employ air quality monitoring and reporting systems to mitigate health risks associated with air pollution, including wildfire smoke. This study investigates the factors influencing individuals’ sensitivity to air quality information, specifically their likelihood of reducing or ceasing outdoor activities in response to air quality ratings, with a focus on wildfire smoke exposure in the western United States. Using the Bayesian (...) Mindsponge Framework (BMF) analytics, the study analyzed data from 2,237 participants in the Boise Metropolitan Area of Idaho and Boise State University. The findings reveal that women, older individuals, and those with higher educational levels are more likely to reduce outdoor activities at lower unhealthy AQI levels (the lowest being ‘good air quality,’ while the highest being ‘hazardous air quality’), while individuals with higher incomes are less responsive. Women and older adults, in particular, are even more likely to eliminate all outdoor activities. Additionally, individuals who perceive wildfire smoke as more severe than other natural disasters are more inclined to reduce or eliminate outdoor activities at lower unhealthy air quality levels. Experiences of wildfire smoke-related illness—either personally or within their households—further amplify this effect. These findings highlight the importance of localized, context-specific approaches to AQI dissemination and wildfire smoke risk communication to build resilience and safeguard public health in the face of escalating wildfire challenges driven by climate change. (shrink)

On the basis of PM2.5 data of the national air quality monitoring sites, local population data, and baseline all-cause mortality rate, PM2.5-related health economic benefits of the Air Improvement Action Plan implemented in Wuhan in 2013–2017 were investigated using health-impact and valuation functions. Annual avoided premature deaths driven by the average concentration of PM2.5 decrease were evaluated, and the economic benefits were computed by using the value of statistical life (VSL) method. Results showed that the number of avoided (...) premature deaths in Wuhan are 21,384 (95% confidence interval (CI): 15,004 to 27,255) during 2013–2017, due to the implementation of the Air Improvement Action Plan. According to the VSL method, the obtained economic benefits of Huangpi, Wuchang, Hongshan, Xinzhou, Jiang’an, Hanyang, Jiangxia, Qiaokou, Jianghan, Qingshan, Caidian, Dongxihu, and Hannan District were 8.55, 8.19, 8.04, 7.39, 5.78, 4.84, 4.37, 4.04, 3.90, 3.30, 2.87, 2.42, and 0.66 billion RMB (1 RMB = 0.1417 USD On 14 October 2019), respectively. These economic benefits added up to 64.35 billion RMB (95% CI: 45.15 to 82.02 billion RMB), accounting for 4.80% (95% CI: 3.37% to 6.12%) of the total GDP of Wuhan in 2017. Therefore, in the process of formulating a regional air quality improvement scheme, apart from establishing hierarchical emission-reduction standards and policies, policy makers should give integrated consideration to the relationship between regional economic development, environmental protection and residents’ health benefits. Furthermore, for improving air quality, air quality compensation mechanisms can be established on the basis of the status quo and trends of air quality, population distribution, and economic development factors. (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)

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)

Urban green spaces are vital for mitigating climate change, enhancing biodiversity, and improving citizen well-being. However, traditional methods of designing and managing these spaces often lack the precision and scalability needed to address modern urban challenges. This paper explores how Artificial Intelligence (AI) and IoT technologies can optimize urban green spaces in smart cities. By integrating satellite imagery, soil sensors, and machine learning models, cities can dynamically monitor plant health, predict ecological impacts, and design green zones that maximize biodiversity and (...) sustainability. Experimental results demonstrate improvements in air quality, heat island reduction, and community engagement, offering a blueprint for AI-driven ecological urban planning. (shrink)

This study presents a neural network-based model for predicting smoke potential in a specific area using a Kaggle-derived dataset with 15 environmental features and 62,631 samples. Our five-layer neural network achieved an accuracy of 89.14% and an average error of 0.000715, demonstrating its effectiveness. Key influential features, including temperature, humidity, crude ethanol, pressure, NC1.0, NC2.5, SCNT, and PM2.5, were identified, providing insights into smoke occurrence. This research aids in proactive smoke mitigation and public health protection. The model's accuracy and feature (...) analysis empower decision-makers, with potential applications in real-time smoke event monitoring and preparedness strategies. This work contributes to the field of air quality forecasting and environmental stewardship, offering a data-driven approach to address smoke-related challenges and enhance community well-being. (shrink)

We investigate the application of Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) networks, and a hybrid CNN-LSTM model for forecasting air pollution levels based on historical data. Our experimental setup uses real-world air quality datasets from multiple regions, containing measurements of pollutants like PM2.5, PM10, CO, NO2, and SO2, alongside meteorological data such as temperature, humidity, and wind speed. The models are trained, validated, and tested using a split dataset, and their accuracy is evaluated using performance metrics like (...) Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R-squared. (shrink)

The current study is conducted to examine the following research question: 1) Who were the people who had no access to wildfire smoke notifications during the smoke event in the summer of 2018 in the Boise Metropolitan Area in Idaho? 2) Who were the people who were not familiar with the air quality rating system?

The current study is conducted to examine the following research question: What are the factors associated with the sensitivity towards the air quality rating index to reduce outdoor activities?

In recent years, the prediction of air quality has become a critical task due to its significant impact on human health and the environment. With urbanization and industrial growth, the need for accurate air quality forecasting has become more urgent. Traditional methods for air quality prediction are often based on statistical models or physical simulations, which, while valuable, can struggle to capture the complexity of air pollution dynamics. This study explores the use of deep learning techniques to (...) predict air quality, providing a comparative analysis of different neural network models and their performance. (shrink)

We investigate the application of Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) networks, and a hybrid CNN-LSTM model for forecasting air pollution levels based on historical data. Our experimental setup uses real-world air quality datasets from multiple regions, containing measurements of pollutants like PM2.5, PM10, CO, NO2, and SO2, alongside meteorological data such as temperature, humidity, and wind speed. The models are trained, validated, and tested using a split dataset, and their accuracy is evaluated using performance metrics like (...) Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R-squared. (shrink)

The results show that the hybrid CNN-LSTM model outperforms the individual models in terms of prediction accuracy and robustness, suggesting that combining convolutional layers with recurrent units is beneficial for capturing both spatial and temporal patterns in air quality data. This study demonstrates the potential of deep learning methods to offer real-time, accurate air quality forecasting systems, which can aid policymakers and urban planners in managing air pollution more effectively.

In recent years, the prediction of air quality has become a critical task due to its significant impact on human health and the environment. With urbanization and industrial growth, the need for accurate air quality forecasting has become more urgent. Traditional methods for air quality prediction are often based on statistical models or physical simulations, which, while valuable, can struggle to capture the complexity of air pollution dynamics. This study explores the use of deep learning techniques to (...) predict air quality, providing a comparative analysis of different neural network models and their performance. (shrink)

The Importance of Urban Planning and Strict Laws on Informal Settlements -/- Introduction -/- Urbanization is a global phenomenon, bringing both opportunities and challenges. Rapid population growth, especially in developing nations, has led to the rise of informal settlements or “squatter areas.” These settlements often lack proper infrastructure, sanitation, and legal recognition, creating social, economic, and environmental issues. Effective urban planning, combined with strict enforcement of land-use laws and inclusive housing policies, is essential to ensuring sustainable and livable cities. This (...) essay explores the importance of urban planning and strict laws against illegal settlements, using successful case studies from Singapore, Brazil, South Korea, the Philippines, and Ethiopia. -/- The Role of Urban Planning in Sustainable Cities -/- Urban planning is the process of designing and regulating the use of land to ensure the orderly development of cities. Proper urban planning provides essential services such as housing, transportation, sanitation, and green spaces, preventing the formation of illegal settlements. -/- Key Aspects of Effective Urban Planning -/- 1. Zoning Regulations – Defining areas for residential, commercial, and industrial use helps prevent uncontrolled development. -/- 2. Infrastructure Development – Roads, drainage, sewage systems, and utilities must be planned in advance to accommodate future growth. -/- 3. Disaster Risk Management – Cities must prevent settlements in flood-prone or hazardous areas to minimize risks to human life. -/- 4. Affordable Housing Programs – Governments should provide legal, affordable alternatives to illegal settlements. -/- Without proper urban planning, cities face overcrowding, pollution, poor sanitation, and increased crime rates. Case studies from different countries demonstrate the effectiveness of strong urban policies in addressing informal settlements. -/- Case Studies: Successful Urban Planning and Settlement Control -/- 1. Singapore: A Model for Integrated Public Housing -/- Singapore transformed from a city with severe housing shortages in the 1960s into one of the most well-planned urban environments in the world. The government’s Housing and Development Board (HDB) played a crucial role in developing affordable, high-quality public housing with integrated amenities such as schools, parks, and public transportation. -/- Key Strategies: ✔ Strict zoning laws prevented unregulated settlements. ✔ Homeownership was promoted through subsidized housing loans. ✔ Government-planned townships provided complete services. -/- Results: ✔ Over 80% of Singaporeans now live in well-planned public housing. ✔ Illegal settlements have been completely eliminated. -/- Singapore’s success demonstrates how strict land-use policies combined with affordable housing programs can prevent informal settlements. -/- 2. Brazil: Upgrading Informal Settlements Instead of Evictions -/- Rio de Janeiro faced a severe problem with favelas—informal settlements that grew due to rapid urban migration. Instead of mass evictions, the government launched the Favela-Bairro program (1994-2008), improving living conditions rather than displacing people. -/- Key Strategies: ✔ Infrastructure improvements (roads, sanitation, electricity). ✔ Community engagement ensured residents’ needs were met. ✔ Legal property rights were granted to residents. -/- Results: ✔ Over 250,000 residents benefited from improved housing conditions. ✔ Crime and poverty rates declined as favelas were integrated into the formal city. -/- Brazil’s approach shows that slum upgrading can be a viable alternative to forced eviction, improving both human welfare and urban order. -/- 3. South Korea: Urban Renewal in Seoul (Cheonggyecheon Project) -/- Seoul’s Cheonggyecheon River was once covered by illegal settlements and highways. The government removed the informal settlements, revitalizing the area into a public green space. -/- Key Strategies: ✔ Slum clearance and restoration of natural spaces. ✔ Improved public transport (bus rapid transit) reduced congestion. ✔ Business relocation incentives prevented economic disruption. -/- Results: ✔ 35% reduction in air pollution, making Seoul more livable. ✔ Increased property values and economic growth. -/- This case highlights how urban renewal projects can enhance sustainability, public health, and economic opportunities while addressing informal settlements. -/- 4. The Philippines: Housing and Resettlement Programs -/- Metro Manila faces a long-standing issue of informal settlers occupying flood-prone and government-owned areas. The Philippine government introduced various strategies, including in-city relocation, socialized housing, and land clearing operations. -/- Key Strategies: ✔ Balik Probinsya, Bagong Pag-asa (BP2) Program: Encouraged migration from overcrowded cities with financial aid. ✔ Vertical housing solutions: High-rise social housing projects maximized limited land. ✔ Land clearing operations: Removed settlements from hazardous areas. -/- Results: ✔ Some success in decongesting Metro Manila, but rapid urban migration remains a challenge. ✔ Affordable housing remains a priority for sustainable urban development. -/- The Philippines’ experience shows that a combination of enforcement and social programs is necessary to manage informal settlements effectively. -/- 5. Ethiopia: Large-Scale Public Housing (Addis Ababa’s Condominium Program) -/- Ethiopia faced a housing crisis, with 70% of Addis Ababa’s population living in informal settlements. The government launched a large-scale condominium housing program to address the issue. -/- Key Strategies: ✔ Government-built high-rise condominiums replaced slums. ✔ Low-interest loans made homeownership possible for low-income families. ✔ Priority was given to families displaced by urban renewal projects. -/- Results: ✔ Significant reduction in slums as many moved into formal housing. ✔ Homeownership increased, improving living conditions. -/- Ethiopia’s approach highlights how government-led mass housing projects can transform urban development. -/- Lessons from Successful Urban Planning -/- 1. Strict Land-Use Laws Prevent Slums from Forming ✔ Clearly defining residential, commercial, and public spaces prevents illegal occupation. -/- 2. Affordable Housing is Essential ✔ Governments must provide low-cost housing as a legal alternative to informal settlements. -/- 3. Upgrading Slums Can Be More Effective Than Evictions ✔ Programs like Favela-Bairro (Brazil) and Ethiopia’s condominium projects show that improving existing settlements works better than forced displacement. -/- 4. Technology Can Help Monitor and Prevent Illegal Settlements ✔ GIS mapping and AI tracking can detect unauthorized land occupation. ✔ E-governance systems can simplify property registration and land-use approvals. -/- 5. Community Engagement is Critical ✔ Urban planning must involve local residents to ensure sustainability and social acceptance. -/- 6. Economic and Livelihood Programs Reduce Informal Settlements ✔ Job creation, microfinance, and small business support help low-income families transition into formal housing. -/- Conclusion -/- Urban planning and strict laws against informal settlements are crucial for creating sustainable, safe, and prosperous cities. Case studies from Singapore, Brazil, South Korea, the Philippines, and Ethiopia demonstrate that a balanced approach—combining strict enforcement, affordable housing, and community-driven solutions—leads to long-term success. Governments worldwide must prioritize sustainable housing, infrastructure development, and urban regulations to ensure that growing populations are accommodated in a way that promotes both human dignity and urban order. -/- By learning from successful models and implementing proactive urban policies, cities can prevent slums, improve living conditions, and build a more sustainable future for all. -/- . (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)

Expeditious increase in population and industrialization has led to alarming rates of air pollution in all countries. However, developing economies have had to face a more adverse and severe impact. This had led to many changes in the day to day living of citizens. In this paper we have focused on the psychological process and predictors of migration intention of the people living in Hanoi, Vietnam. Two stratified random datasets of 475 people were used, and Bayesian analysis was performed on (...) this dataset. We found out that the intent to move was negatively associated to the individual’s satisfaction with air quality. We also found that people who have family members that have fallen victim to a disease caused by air pollution are more likely to migrate. This paper discusses an important topic: immigration of the younger demographic, i.e. the Hanoi workforce, which may cause restrictions and hurdles in the city's urbanisation and development. The findings suggest that, if measures against air pollution are not taken, economic forces may be disrupted, posing a threat to urban growth. As a result, collaborative activities and steps need to be taken by the government to curb this unfortunate consequence. (shrink)

Purpose: This article aims to highlight key indicators of residents' quality of life in a specific contemporary building in Kruja, Albania. -/- Design/Method/Approach: A questionnaire with 30 questions was prepared for the inhabitance, and the Binary or Tobit probabilistic models were taken into consideration as part of the methodology, to conclude. The study will further analyze the implications of the inhabitants and their behavior in a specific contemporary building in the city of Kruja. It was examined the statistical significance (...) of each variable (questions) in the models elaborated with EViews 8 software. The stable models that are associated with the “Log-likelihood” statistics were statistically significant at a significance level of p < 5%, or with 95% confidence, based on the model tests. -/- Findings: The study concluded that the most statistically significant quality of life indicators part of the questionnaire is related to the typology of the apartments, methods of cooling during summer, present living conditions, apartment improvement, apartment orientation, and time spent in the living room. Furthermore, the study reveals that most of the quality-of-life indicators (part of the questionnaire) are not statistically important, so they will not be considered part of the models created in the article. The study reveals that increasing the living space and improving orientation is crucial to enhance the satisfaction of apartment inhabitants. When apartment sizes increase and orientation is improved, residents are more likely to opt for fans over air conditioners to reduce electricity costs and avoid installing additional cooling facilities during summer. They believe that better living conditions require larger apartments, additional water supply, increased electrical costs, and more time spent in the living room. The inhabitants also emphasize the importance of reducing moisture levels, decreasing window opening frequency, and increasing time spent with family. Interestingly, a one-degree improvement in summer cooling methods (e.g., switching from air blowers to air conditioning) corresponds to a one-degree improvement in winter heating methods (e.g., switching from gas to electricity), leading to a heightened need for clean electric heating. Overall, the study emphasizes the importance of meeting the physical and spatial needs of the residents to enhance their overall satisfaction and quality of life. Urban policies significantly impact housing affordability, quality, transport systems, environmental sustainability, and social equity, affecting overall living standards and economic growth. Cities must create well-designed policies that consider residents' needs and study findings to ensure sustainable development and citizen welfare. -/- Theoretical Implications: Gujarati’s (Basic Economics) theory was developed in the article. -/- Practical Implications: This study will serve as an indicator to analyze the further improvements that might occur in the specific building (not just in the city of Kruja), considering the main quality of life indicators. -/- Originality/Value: The article will serve as a base for further analysis of resident’s behavior and their social impact in the community in order to be aware of their needs for further developments in the construction field. -/- Research Limitations/Future Research: The findings depend profoundly on the type of building the residents are living in. The research stream that can be inspired by the research is strongly related to mathematical regression models, statistics, and probability. -/- Paper Type: Empirical . (shrink)

Water quality assessment is critical for environmental sustainability and public health. This research employs neural networks to predict water quality, utilizing a dataset of 21 diverse features, including metals, chemicals, and biological indicators. With 8000 samples, our neural network model, consisting of four layers, achieved an impressive 94.22% accuracy with an average error of 0.031. Feature importance analysis revealed arsenic, perchlorate, cadmium, and others as pivotal factors in water quality prediction. This study offers a valuable contribution to (...) enhancing water quality monitoring and decision-making for stakeholders and policymakers. (shrink)

The odds of encountering a senior citizen selling on the street have increased. The claim that they have no choice but to work and sell on the street, despite the dangers, illnesses, and psychological issues they may face, to provide for their family’s needs is very evident. Therefore, this study explores the quality of life, lived experiences, challenges, and coping mechanisms of senior citizen street vendors in Bulacan, Philippines. The study employed Heideggerian Phenomenology and Interpretative Phenomenological Analysis (IPA). Moreover, (...) the following themes arise (1) Golden years, (2) Socially connected, and (3) Unknown journey. These themes highlighted the experiences and challenges faced by the participants. Moreover, it is highly suggested that local government agencies enhance and strictly monitor the existing program that alleviates mental and physical health concerns and senior citizens' safety and financial assistance. (shrink)

Noise pollution is a growing concern in urban areas, contributing to public health issues such as stress, sleep disturbances, and hearing loss. Traditional noise monitoring systems often lack the granularity and adaptability needed to address dynamic noise sources and patterns. This paper explores how Artificial Intelligence (AI) and IoT technologies can enhance noise pollution management in smart cities by enabling real-time monitoring, source identification, and adaptive mitigation strategies. By integrating data from IoT sensors, traffic systems, and urban infrastructure, (...) cities can reduce noise levels, improve public health outcomes, and enhance the quality of life for residents. Experimental results demonstrate significant improvements in noise detection accuracy, mitigation efficiency, and public awareness, offering a sustainable blueprint for urban noise pollution management. (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)

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)

During the production process, production companies need to monitor the finished products and ensure their quality, which imposes on them the appointment of inspectors for auditing, and this appointment costs the company amounts that affect the general profit, so it strives to make this cost as low as possible and that the audit process is carried out with high accuracy because in case that the finished products do not conform to the basic specifications of the product, the company is (...) required to pay a fine. In this research, we will formulate the text of the problem appropriately for such a case and then we will build the appropriate mathematical model through which we can obtain the lowest possible cost of inspection, and we will present the study using classical values and neutrosophic values, and we will demonstrate them through an example that shows us the difference between them. (shrink)

Wearable devices are increasingly present in the health context, as tools for biomedical research and clinical care. In this context, wearables are considered key tools for a more digital, personalised, preventive medicine. At the same time, wearables have also been associated with issues and risks, such as those connected to privacy and data sharing. Yet, discussions in the literature have mostly focused on either technical or ethical considerations, framing these as largely separate areas of discussion, and the contribution of wearables (...) to the collection, development, application of biomedical knowledge has only partially been discussed. To fill in these gaps, in this article we provide an epistemic (knowledgerelated) overview of the main functions of wearable technology for health: monitoring, screening, detection, and prediction. On this basis, we identify 4 areas of concern in the application of wearables for these functions: data quality, balanced estimations, health equity, and fairness. To move the field forward in an effective and beneficial direction, we present recommendations for the 4 areas: local standards of quality, interoperability, access, and representativity. (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)

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)

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)

This IoT-based water quality monitoring system ensures good water quality in distribution lines by monitoring pH value, flow rate, and conductivity level in real-time. Utilizing Arduino, pH, flow, and conductivity sensors, and ESP8266 WiFi module, the system analyses data and sends automated alerts to authorized personnel's Android devices. This automated monitoring enhances public health, provides real-time data analysis, and enables remote monitoring, making it an efficient solution for water distribution plants to maintain optimal water (...) quality. (shrink)

Urban wastewater management is a critical component of sustainable water cycles, but traditional systems often struggle with inefficiencies such as high operational costs, resource wastage, and environmental pollution. This paper explores how Artificial Intelligence (AI) and IoT technologies can optimize urban wastewater management by enabling real-time monitoring, predictive maintenance, and resource recovery. By integrating data from IoT sensors, water quality monitors, and treatment plants, cities can improve water quality, reduce operational costs, and recover valuable resources such as (...) energy and nutrients. Experimental results demonstrate significant improvements in treatment efficiency, resource recovery rates, and environmental impact, offering a sustainable blueprint for smart urban wastewater systems. (shrink)

Developing countries have seen rapid economic growth, but they have also faced unprecedented environmental challenges, including air pollution, water pollution, land pollution, waste pollution, etc. Take air pollution as an example. It is alarming that 99 percent of the world’s population breathes polluted air. Air pollution is deemed a “quiet killer”, giving rise to numerous consequences ranging from health and psychological impacts to economic and social costs. For example, air pollution annually causes roughly 7 million premature deaths and an economic (...) loss of USD 8.1 trillion, accounting for 6.1% of the global GDP. Furthermore, it is worth noting that the urban population is projected to exceed two-thirds of the total global population by 2050, as urbanization exacerbates the air pollution problem, creating even more air pollution challenges for humankind in the long run. Every new piece of information matters for scientific progress in air pollution assessment, policymaking, and public health protection. From this viewpoint, the goal/objective of this Special Issue (SI) of Urban Science is to keep communities, scholars, and policymakers informed on the research progress on air quality and human health. Specifically, this SI serves as a forum for advancing scientific understanding of environmental changes associated with air pollution and air quality, strategies and/or different measures that the public, particularly urban residents, can employ to lessen and/or mitigate unexpected impacts. I hope that the useful information and insightful findings presented by scholars in this SI can support or facilitate desirable urban environment policies that help, ultimately, increase human and societal wellbeing. (shrink)

Coronavirus disease-19 (COVID-19), produced by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global pandemic, giving rise to a serious health threat globally. The global Covid-19 pandemic is a setback for sustainable development and compromise the world commitment to the 2030 Agenda for Sustainable Development. The measures taken to control the spread of the virus and the slowdown of economic activities during lockdown have significant effects on the environment. Therefore, this review discuss the indirect positive and negative (...) impacts of Covid-19 pandemic towards sustainable environment. This study indicates that, the pandemic situation significantly improves air quality in different cities across the world, reduces the emission of greenhouse gases, and decreases water and noise pollution, which may help in the restoration of the ecosystem. In addition, there are also some negative impact of Covid-19, such as increase of medical waste, haphazard use and disposal of disinfectants, mask, and gloves; and burden of untreated wastes continuously endangering the environment. It points to the fact that the net effect has been positive; in terms of reduction in greenhouse emissions, oil exploration activities, and pollution. It is expected that the proper implementation of the proposed suggestion might be helpful for the global environmental sustainability. (shrink)

Monitoring soil pH levels forms the backbone of precision agriculture with regard to maximizing crop health and yield. The paper discusses an IoT-based solution, specifically designed for continuous soil pH testing in digital farming. It has pH sensors placed strategically around the agricultural fields such that the information regarding the acidity or alkalinity of the soil is available in real-time. The pH information will be transmitted to the central IoT gateway. Here, the information is processed, and via communication of (...) cloud-based platforms, it is further stored and analyzed. So, by checking variations in soil pH, the system provides actionable information to farmers. Thus, by adjusting soil treatments like lime or fertilizers better, it enhances crop performance. The response uses mobile and web interfaces that support automated pH testing with automatically designed data visualization. This allows farmers the chance to decide from remote sites about imminent and proper fluctuations in soil pH by the use of historical data analysis and models from machine learning. One part of the effectuality of this proactive approach would be that soil quality is improved while unnecessary chemical use is avoided, therefore reducing the resulting costs of farming with sustainability considerations. By limiting itself to pH value testing, this solution increases the farmland's productivity with less wastage of resources. (shrink)

Coronavirus disease-19 (COVID-19), produced by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global pandemic, giving rise to a serious health threat globally. The global Covid-19 pandemic is a setback for sustainable development and compromise the world commitment to the 2030 Agenda for Sustainable Development. The measures taken to control the spread of the virus and the slowdown of economic activities during lockdown have significant effects on the environment. Therefore, this review discuss the indirect positive and negative (...) impacts of Covid-19 pandemic towards sustainable environment. This study indicates that, the pandemic situation significantly improves air quality in different cities across the world, reduces the emission of greenhouse gases, and decreases water and noise pollution, which may help in the restoration of the ecosystem. In addition, there are also some negative impact of Covid-19, such as increase of medical waste, haphazard use and disposal of disinfectants, mask, and gloves; and burden of untreated wastes continuously endangering the environment. It points to the fact that the net effect has been positive; in terms of reduction in greenhouse emissions, oil exploration activities, and pollution. It is expected that the proper implementation of the proposed suggestion might be helpful for the global environmental sustainability. (shrink)

Cities and towns are expanding and thriving as a result of urbanization, which also significantly changes the local climate. One of the most significant phenomena associated with urbanization is the Urban Heat Island (UHI) effect. This phenomenon is increasingly being studied worldwide. The paper aims to investigate the UHI phenomenon in the metropolitan area of Tirana, Albania. It analyses the impact of the UHI on four specific locations in Tirana, its causes and mitigation measures, as well as variations in surface (...) temperature, CO2 emissions, and relative humidity. The regions are measured and observed using a specific instrument such as the Testo 435. Considering the mean surface temperature variations between urban and rural regions ranging from 28.4°C to 33.7 °C, CO2 emissions from 302.9 ppm to 416.2 ppm, and relative humidity from 34.1% to 41.2%, it is found that the UHI impact in Tirana is significant. The lack of green spaces, high building density, urban patterns, building materials used, transport, and energy use are the main contributors to the UHI in central Tirana. Increasing green spaces, using reflective materials, and promoting sustainable urban design are some of the mitigation techniques suggested to reduce the UHI effect in Tirana. (shrink)

There is widespread consensus that the volatility, uncertainty, complexity, and ambiguity (VUCA) environment has contributed to the subpar quality of public sector service delivery in South Africa. Hence, the aim of this paper is to ascertain how the South African government can enhance service delivery in a VUCA world. This article presents a comprehensive study of a number of secondary literature sources. The author makes an effort to draw attention to knowledge gaps that might serve as the foundation for (...) more research in the future. The main finding is that for the South African government to provide good service in a VUCA environment, its employees must be proficient in Results-Based Monitoring and Evaluation, Strategic Planning, Programme and Project Management Methodology, and Change Management Methodology. There is a severe lack of empirical study on the delivery of public sector services in an environment characterized by VUCA. As a result, there is a need for more research on this topic. Specifically, in order to establish the effect that the VUCA environment has on the governments of emerging nations. The research will be beneficial to the governments of developing countries, notably South Africa, as well as to those who work in the field of public administration. (shrink)

This study delved into the Senior High School Technical-Vocational-Livelihood (TVL) track in Bohol Province for the 2022-2023 school year, aiming to evaluate policy implementation, recognize barriers, and propose interventions. Employing a mixed-method approach, integrating quantitative-descriptive surveys and qualitative-descriptive research methods as recommended by Creswell and Plano Clark (2017), the findings unveiled a predominantly positive perception of policy implementation across various dimensions of the TVL track. These encompass curriculum development, teacher training, resource allocation, industry partnerships, assessment and evaluation, student support services, (...) monitoring and quality assurance, policy adaptation and improvement, stakeholder engagement, legal framework and compliance, data collection and analysis, and inclusivity and equity. Despite variations among teachers and administrators, a general commitment to policy implementation emerged. The study identified barriers in curriculum and instruction, readiness and preparedness, resource limitations, and teaching and learning, emphasizing evidence-based strategies and interdisciplinary approaches to surmount challenges. It underscores the crucial role of research and policy development in elevating the quality and efficacy of TVL education. (shrink)

Seeking to expand on previous theories, this paper explores the AIR (Applying Intelligence to the Reflexes) approach to expert performance previously outlined by Geeves, Christensen, Sutton and McIlwain (2008). Data gathered from a semi-structured interview investigating the performance experience of Jeremy Kelshaw (JK), a professional musician, is explored. Although JK’s experience of music performance contains inherently uncertain elements, his phenomenological description of an ideal performance is tied to notions of vibe, connection and environment. The dynamic nature of music performance advocated (...) by the AIR approach is illustrated by the strategies that JK implements during performance. Through executing these strategies, JK attempts to increase the likelihood of vibe and connection by selectively exercising agency over performance variables within his control. In order to achieve this, JK must engage in ongoing monitoring of his performance, whereby the spotlight of his attention pans across a vast array of disparate performance processes (and levels within these processes) in order to ascertain how he can most effectively meet the specific demands of a given performance situation. It is hoped that future research compiling data from numerous interviews and sources as well as using different research methodologies will further unlock the potential that the AIR approach holds for understanding expert performance. (shrink)

The Western Philippines University – College of Education’s Project MATHEMATICS (Mathematics Enhanced Mentoring, Assistance, and Training to In-need and Challenged Students) was implemented as part of the Adopt-a-School Program to address the mathematical needs of Laura Vicuña Center – Palawan youths. To evaluate the extent of the project implementation, the study assessed its impact through the feedback gathered from the clients served. It specifically described the quality of project implementation, determined the attainment of project objectives, and enumerated client feedback. (...) A concurrent triangulation mixed-method research design was used with 32 clientele samples selected purposively. The study utilized a survey, problem set test, and focus-grouped interview to obtain data pertinent to the study’s objectives. The findings revealed an aspirational quality of the implemented project, improved mathematical performance, and the client’s desire for ongoing mentoring. The implications and limitations of the study are discussed, along with recommendations for future extension projects, monitoring and evaluation, and re-planning activities. (shrink)

Being sure of each other is the blossoming of Kimberley Brownlee’s earlier work on the intrinsic value and qualities of human connection (2013, 2016c, 2016b), opening with a scene from A. A. Milne’s House at Pooh Corner: lost in the woods together, Piglet takes Pooh’s paw ‘just to be sure’ of his friend. The importance of social connection is often overlooked because it is central to our lives, like breathable air. Brownlee’s work highlights the need for social connection, as deserving (...) of more philosophical attention and practical protection through rights. But her key insight is that receiving relational goods isn’t all that matters: being able and permitted to provide relational goods to others, as Piglet and Pooh receive and offer each other reassurance, is just as essential for our wellbeing. Brownlee argues these interests are strong enough to ground rights (2016c: 28). (shrink)

Metacognition is associated with planning, monitoring, evaluating and repairing performance Designers of elearning systems can improve the quality of their environments by explicitly structuring the visual and interactive display of learning contexts to facilitate metacognition. Typically page layout, navigational appearance, visual and interactivity design are not viewed as major factors in metacognition. This is because metacognition tends to be interpreted as a process in the head, rather than an interactive one. It is argued here, that cognition and metacognition (...) are part of a continuum and that both are highly interactive. The tenets of this view are explained by reviewing some of the core assumptions of the situated and distribute approach to cognition and then further elaborated by exploring the notions of active vision, visual complexity, affordance landscape and cue structure. The way visual cues are structured and the way interaction is designed can make an important difference in the ease and effectiveness of cognition and metacognition. Documents that make effective use of markers such as headings, callouts, italics can improve students’ ability to comprehend documents and ‘plan’ the way they review and process content. Interaction can be designed to improve ‘the proximal zone of planning’ – the look ahead and apprehension of what is nearby in activity space that facilitates decisions. This final concept is elaborated in a discussion of how e-newspapers combine effective visual and interactive design to enhance user control over their reading experience. (shrink)

Solving Typhoon Turbulence Using the Universal Formula -/- By Angelito Malicse -/- Introduction -/- Typhoons are among the most destructive natural phenomena, bringing extreme winds, heavy rainfall, and turbulent ocean currents. The chaotic turbulence within a typhoon makes it difficult to predict and control, causing widespread devastation to coastal regions, infrastructure, and human lives. Despite advancements in meteorology and fluid dynamics, the turbulence inside typhoons remains a challenge for accurate forecasting and disaster mitigation. -/- By applying my universal formula, based (...) on three fundamental laws of nature, we can develop a structured and effective approach to understanding and controlling typhoon turbulence. This essay explores how the Law of Karma (causality and system integrity), the Law of Balance in Nature, and the Law of Feedback Regulation provide the ultimate solution to typhoon turbulence. -/- Understanding Typhoon Turbulence Using the Universal Formula -/- Typhoons form due to energy imbalances in the atmosphere and ocean, driven by heat, pressure differences, and moisture content. The chaotic turbulence inside a typhoon is the result of: -/- 1. Unstable air currents caused by pressure and temperature gradients. -/- 2. Vortex formation driven by Earth’s rotation and wind shear. -/- 3. Excess energy accumulation in warm ocean waters. -/- By examining typhoon turbulence through the three universal laws, we can develop a scientific strategy to predict, weaken, and potentially neutralize typhoons before they cause destruction. -/- 1. The Law of Karma: Cause, Effect, and Systemic Integrity -/- The Law of Karma states that every effect has a cause, and for a system to function properly, it must be free of defects. A typhoon is an effect caused by imbalances in atmospheric and oceanic conditions. If these imbalances are corrected, typhoon turbulence can be weakened or prevented. -/- Applying the Law of Karma to Typhoon Control -/- ✅ Eliminate the root cause: Typhoons are fueled by warm ocean waters. Artificial cooling methods, such as cloud seeding or deep-sea upwelling (bringing cold water to the surface), could reduce the heat energy supply and prevent typhoon formation. -/- ✅ Detect turbulence before it intensifies: AI-driven weather models can predict early-stage typhoon turbulence and allow preemptive interventions. AI can identify defective atmospheric conditions (such as extreme heat buildup in ocean currents) and trigger mitigation efforts. -/- ✅ Disrupt vortex formation: Since typhoons rely on rotational forces, deploying strategically placed atmospheric pressure disturbances (via drones or cloud-seeding techniques) could disrupt the vortex before it gains full strength. -/- By identifying and neutralizing the causes of typhoon turbulence, we ensure that the system remains balanced, preventing large-scale destruction. -/- 2. The Law of Balance in Nature -/- The Law of Balance states that all systems naturally seek equilibrium. When a typhoon forms, it represents an extreme imbalance in the Earth’s energy system—excess heat and moisture create an unstable feedback loop of wind and turbulence. -/- Restoring Balance to Weaken Typhoon Turbulence -/- ✅ Regulating ocean surface temperature: Large-scale ocean-based temperature regulation systems (such as reflective films or artificial cooling platforms) can prevent typhoon formation by reducing the excess heat energy that fuels storms. -/- ✅ Breaking the pressure imbalance: Typhoons depend on a low-pressure core that intensifies wind speeds. By artificially increasing local air pressure using ionization or controlled cloud seeding, the extreme wind turbulence can be diffused before it reaches destructive levels. -/- ✅ Balancing atmospheric moisture: AI-assisted weather control could help regulate humidity levels through strategic rainfall induction in high-risk areas, ensuring that water vapor does not accumulate excessively to fuel a typhoon. -/- Since all systems follow natural equilibrium, strategically rebalancing temperature, pressure, and humidity will neutralize extreme typhoon turbulence. -/- 3. The Law of Feedback Regulation -/- The Law of Feedback Regulation states that all systems operate through feedback loops, where continuous monitoring and adjustment are necessary for stability. Typhoon turbulence follows feedback patterns, which means it can be tracked, analyzed, and counteracted using real-time data. -/- Developing an AI-Driven Typhoon Suppression System -/- ✅ AI-powered real-time monitoring: Advanced satellites, ocean buoys, and drones can provide instant feedback on typhoon development, allowing for proactive interventions rather than reactive disaster response. -/- ✅ Adaptive wind and pressure control: Deploying AI-controlled drones or weather balloons to release cooling agents, modify air pressure, or disperse cloud formations could interrupt the storm's feedback loop, reducing its intensity. -/- ✅ AI-driven weather forecasting for early response: Using deep learning algorithms, AI can accurately predict turbulence patterns weeks in advance, allowing governments to take preventive action instead of just preparing for disaster relief. -/- By implementing real-time monitoring and intervention, we can use feedback regulation to weaken or redirect typhoons before they cause catastrophic damage. -/- The Future of Typhoon Control with the Universal Formula -/- By integrating my universal formula into meteorology and disaster prevention, we can develop a comprehensive AI-driven typhoon suppression system that follows the three fundamental laws of nature: -/- 1. Law of Karma (Causality and Systemic Integrity): Address the root causes of typhoon formation by eliminating atmospheric and oceanic imbalances. -/- 2. Law of Balance in Nature: Restore equilibrium by regulating ocean temperatures, air pressure, and humidity. -/- 3. Law of Feedback Regulation: Use AI-driven real-time monitoring and intervention to weaken or prevent typhoons. -/- Through advanced AI, environmental engineering, and a deep understanding of nature’s laws, we can move beyond simply predicting typhoons and start actively controlling their development. -/- Conclusion -/- Typhoon turbulence, long considered an unpredictable force of nature, is fundamentally a problem of imbalance, energy accumulation, and feedback-driven intensification. By applying my universal formula, we can shift from passive disaster response to active typhoon control, using AI, environmental intervention, and natural equilibrium principles to prevent devastation. -/- This solution is not just theoretical—it aligns with the fundamental laws governing all natural systems. Once implemented, it will mark the beginning of a new era where humanity can harness nature’s own principles to create balance, stability, and protection from extreme weather. -/- . (shrink)

Containerization in a multi-cloud environment facilitates workload portability and optimized resource uti-lization. Containerization in multi-cloud environments has received significant attention in recent years both from academic research and industrial development perspectives. However, there exists no effort to systematically investigate the state of research on this topic. The aim of this research is to systematically identify and categorize the multiple aspects of containerization in multi-cloud environment. We conducted the Systematic Mapping Study (SMS) on the literature published between January 2013 and March (...) 2023. Eighty-six studies were finally selected and the key results are: (1) Four leading themes on cloud computing and network systems research were identified: ‘Scalability and High Availability’, ‘Performance and Optimization’, ‘Security and Privacy’, and ‘Multi-Cloud Container Monitoring and Adaptation’. (2) Seventy-four patterns and strategies for containerization in multi-cloud environment were classified across 10 subcategories and 4 categories. (3) Ten quality attributes considered were identified with 47 associated tactics. (4) Four frameworks were introduced from the analysis of identified challenges and solutions: security, automation, deployment, and monitoring challenge-solution frameworks. The results of this SMS will assist researchers and practitioners in pursuing further studies on containerization in multi-cloud environment and developing specialized solutions for containerization applications in multi-cloud environment. (shrink)

Abstract: This study introduces a machine learning-based model for predicting student performance using a comprehensive dataset derived from educational sources, encompassing 15 key features and comprising 62,631 student samples. Our five-layer neural network demonstrated remarkable performance, achieving an accuracy of 89.14% and an average error of 0.000715, underscoring its effectiveness in predicting student outcomes. Crucially, this research identifies pivotal determinants of student success, including factors such as socio-economic background, prior academic history, study habits, and attendance patterns, shedding light on the (...) nuanced dynamics of student performance. The key influential features identified in this study offer valuable insights into the complex factors shaping student achievement. These insights are vital for educators, policymakers, and institutions seeking to enhance educational outcomes and promote equitable access to quality education. This research provides a data-driven foundation for proactive interventions, personalized learning strategies, and support systems, ultimately contributing to improved student performance and academic success. The high accuracy of the predictive model and the feature analysis it provides empower decision-makers in the education sector. This model holds significant potential for applications in student performance monitoring, early intervention, and tailored educational strategies. By adopting a data-driven approach, this work advances the field of educational analytics and contributes to the goal of fostering student success and educational equity. (shrink)

Stress has become a significant concern in today’s fast-paced world, affecting individuals’ physical and mental well-being. This project, titled Human Stress Detection Based on Sleeping Habits Using Machine Learning Algorithms, aims to address this issue by leveraging data-driven insights to identify stress levels. The proposed system analyzes sleeping patterns, including sleep duration, interruptions, and quality, to classify stress levels effectively. By utilizing advanced machine learning algorithms such as Decision Tree, Random Forest, Logistic Regression, and Support Vector Machine, the model (...) processes data from wearable devices or sleep-monitoring apps to extract relevant features. Key parameters such as sleep latency, efficiency, and disturbances are analyzed alongside other influencing factors like age, lifestyle, and physical activity. The project employs a robust dataset for training and testing, ensuring high accuracy and reliability in predicting stress levels. The system not only identifies stress levels but also provides actionable insights and recommendations to improve sleep quality and overall well-being. Evaluation metrics such as accuracy, precision, recall, and F1 score are employed to measure the model's performance. The outcome of this project demonstrates the potential of machine learning in enhancing healthcare applications. It provides a scalable and efficient tool for stress detection, promoting early intervention and better management of stress-related disorders. (shrink)

The study aimed to look into the organizational performance of Higher Education Institutions in the Philippines particularly in Zamboanga del Norte. The descriptive method of research was used. There were 95 respondents to the survey. Frequency count, percentage, and Mean were used as a statistical tool. The investigation revealed that organizational performance of the Higher Education Institutions involved was found to be very good along the areas of VMGO, faculty, curriculum and instruction, support to students, research, extension, library, physical plant (...) and facilities, laboratories and administration. The Higher Education Institutions met the standards of quality over and above the minimum requirement of government under Article XIV Accreditation, Section 60. There were areas need to focus such as congruent to the needs of the people in the community, monitoring of faculty adequacy and loading, sourcing out funds and other resources, and maintaining safety and security inside the campuses, even though all areas in organizational performance found very good, Further, the administration continuously requires planning, implementation, monitoring, and evaluation. (shrink)

The ear is one of our sensory organs that allow us to perceive our surroundings. We perceive with it the voices that the objects possess by means of the waves within the mass of air surrounding us. In this sense, the ear has an important value for being. In the Qur'an, besides being an ear or a sensory organ, it reveals a person who reflects his level of consciousness and perception, revealing his awareness. It is not just the voices heard; (...) the ear is special importance in understanding what is being said and what is said. Other sense organs and mold are mentioned together because of the feature. Of course, the word "voice" is also on the agenda when the ear is concerned. The verses found at the base of the basic qualities that man should possess present important dynamics about sound. Beyond being a symptom of voice being an inherent symptom, the latest discovery is pointing to the dimension of telling the apocalypse. This study tries to show in what context the hearing aid ear is expressed in the verses and its distinctive features, and its associated value, as well as its inherent value. (shrink)

Abstract: The convergence of nanotechnology and artificial intelligence (AI) represents a transformative frontier in modern science, with the potential to revolutionize multiple industries, particularly healthcare. Nanotechnology enables the manipulation of matter at the atomic and molecular scale, while AI offers sophisticated data analysis, pattern recognition, and decision-making capabilities. This paper explores the synergies between these two fields, focusing on their impact on medical diagnostics, targeted drug delivery, and personalized treatments. By leveraging AI's predictive power and nanotechnology's precision, healthcare can achieve (...) unprecedented levels of accuracy in disease detection and treatment, leading to improved patient outcomes. Beyond healthcare, this convergence extends to environmental monitoring, smart materials, and manufacturing, offering solutions to some of the world’s most pressing challenges. The paper also discusses the ethical considerations and potential risks of integrating AI with nanotechnology, emphasizing the need for responsible innovation. Together, AI and nanotechnology hold the promise of reshaping industries and improving quality of life on a global . (shrink)