Federated Learning Framework for Real-Time Activity and Context Monitoring Using Edge Devices.

With the increasing need for effective elderly care solutions, this paper presents a novel federated learning-based system that uses smartphones as edge devices to monitor and enhance elderly care in real-time. In this system, elderly individuals carry smartphones equipped with Inertial Measurement Unit (IMU) sensors, including an accelerometer for activity recognition, a barometer for altitude detection, and a combination of the accelerometer, gyrometer, and magnetometer for location tracking. The smartphones continuously collect real-time data as the elderly individuals go about their daily routines.

Comparative study on efficiency of surface enhanced coal fly ash and raw coal fly ash for the removal of hazardous dyes in wastewater: optimization through response surface methodology.

Crystal violet (CV) dye, because of its non-biodegradability and harmful effects, poses a significant challenge for wastewater treatment. This study addresses the efficiency of easily accessible coal fly ash (CFA)-based adsorbents such as raw coal fly ash (RCFA) and surface enhanced coal fly ash (SECFA), in removing CV dye from waste effluents. Various analytical techniques such as FTIR, XRD, SEM, TEM, BET, zeta sizer and zeta potential were employed for the characterization of the adsorbents and dye-loaded samples.

Advances in organocatalyzed synthesis of organic compounds.

The recent advancements in utilizing organocatalysts for the synthesis of organic compounds have been described in this review by focusing on their simplicity, effectiveness, reproducibility, and high selectivity which lead to excellent product yields. The organocatalytic methods for various derivatives, such as indoles, pyrazolones, anthrone-functionalized benzylic amines, maleimide, polyester, phthalimides, dihydropyrimidin, heteroaryls, -aryl benzimidazoles, stilbenoids, quinazolines, quinolines, and oxazolidinones have been specifically focused. The review provides more understanding by delving into potential reaction mechanisms.

Characterization of three different benzimidazolium ligands and their organo-selenium complexes by using density functional theory and Raman spectroscopy.

In the present study, Raman spectroscopy (RS) along with density functional theory (DFT) calculations have been performed for the successful characterization and confirmation of the formation of three different selenium-based N-heterocyclic carbene (NHC) complexes from their respective salts. For this purpose, mean RS features and DFT calculations of different ligands and their respective selenium NHC complexes are compared. The identified characteristic RS and DFT features, of each of these ligands and their selenium complexes, show that the polarizability of benzimidazolium rings increases after complex formation with selenium.

Synthesis, Characterization, and Evaluation of Antifungal Activity of 1-Butyl-3-hexyl-1-imidazol-2(3)-selenone by Surface-Enhanced Raman Spectroscopy.

In the present research work, a selenium N-heterocyclic carbene (Se-NHC) complex/adduct was synthesized and characterized by using different analytical methods including FT-IR, HNMR, and CNMR. The antifungal activity of the Se-NHC complex against () fungus was investigated with disc diffusion assay. Moreover, the biochemical changes occurring in this fungus due to exposure of different concentrations of the in-house synthesized compound are characterized by surface-enhanced Raman spectroscopy (SERS) and are illustrated in the form of SERS spectral peaks.

Assessing Household's Municipal Waste Segregation Intentions in Metropolitan Cities of Pakistan: A Structural Equation Modeling Approach.

There is a growing concern about inappropriate waste disposal and its negative impact on human health and the environment. The objective of this study is to understand household waste segregation intention considering psychological, institutional, and situational factors simultaneously. Insights into the motivations of household waste segregation drivers may assist in a better knowledge of how to pursue the most efficient and effective initiatives.

Automated Uterine Fibroids Detection in Ultrasound Images Using Deep Convolutional Neural Networks.

Fibroids of the uterus are a common benign tumor affecting women of childbearing age. Uterine fibroids (UF) can be effectively treated with earlier identification and diagnosis. Its automated diagnosis from medical images is an area where deep learning (DL)-based algorithms have demonstrated promising results.

An Adaptive Real-Time Malicious Node Detection Framework Using Machine Learning in Vehicular Ad-Hoc Networks (VANETs).

Modern vehicle communication development is a continuous process in which cutting-edge security systems are required. Security is a main problem in the Vehicular Ad Hoc Network (VANET). Malicious node detection is one of the critical issues found in the VANET environment, with the ability to communicate and enhance the mechanism to enlarge the field.

Towards Intelligent Zone-Based Content Pre-Caching Approach in VANET for Congestion Control.

In vehicular ad hoc networks (VANETs), content pre-caching is a significant technology that improves network performance and lowers network response delay. VANET faces network congestion when multiple requests for the same content are generated. Location-based dependency requirements make the system more congested.

Design and Analysis of In-Pipe Hydro-Turbine for an Optimized Nearly Zero Energy Building.

Pakistan receives Direct Normal Irradiation (DNI) exceeding 2000 kWh/m²/annum on approximately 83% of its land, which is very suitable for photovoltaic production. This energy can be easily utilized in conjunction with other renewable energy resources to meet the energy demands and reduce the carbon footprint of the country. In this research, a hybrid renewable energy solution based on a nearly Zero Energy Building (nZEB) model is proposed for a university facility.

Enhanced PDR-BLE Compensation Mechanism Based on HMM and AWCLA for Improving Indoor Localization.

This paper presents an enhanced PDR-BLE compensation mechanism for improving indoor localization, which is considerably resilient against variant uncertainties. The proposed method of ePDR-BLE compensation mechanism (EPBCM) takes advantage of the non-requirement of linearization of the system around its current state in an unscented Kalman filter (UKF) and Kalman filter (KF) in smoothing of received signal strength indicator (RSSI) values. In this paper, a fusion of conflicting information and the activity detection approach of an object in an indoor environment contemplates varying magnitude of accelerometer values based on the hidden Markov model (HMM).

Investigating correlations between illness and defensive behaviour approach: A case of twin cities of Pakistan.

Municipal solid waste (MSW) management has emerged as a major problem for modern societies in recent decades. An optimal waste management system is essential to prevent the pollution burden and associated health related issues. This study carries out an empirical evaluation of the illness caused by inadequate solid waste management in the metropolitan of Rawalpindi-Islamabad.

An Efficient Dynamic-Decision Based Task Scheduler for Task Offloading Optimization and Energy Management in Mobile Cloud Computing.

Restricted abilities of mobile devices in terms of storage, computation, time, energy supply, and transmission causes issues related to energy optimization and time management while processing tasks on mobile phones. This issue pertains to multifarious mobile device-related dimensions, including mobile cloud computing, fog computing, and edge computing. On the contrary, mobile devices' dearth of storage and processing power originates several issues for optimal energy and time management.

Testing the Role of Waste Management and Environmental Quality on Health Indicators Using Structural Equation Modeling in Pakistan.

Improper management of municipal waste has become a growing concern globally due to its impact on the environment, health, and overall living conditions of households in cities. Waste production has increased because households do not adopt waste management practices that ensure sustainability. Previous studies on household waste management often considered socio-economic aspects and overlooked the environmental and behavioral factors influencing the disposal practices and health status.

An integrated assessment model for food security under climate change for South Asia.

The present study develops an integrated assessment model (IAM) for food security under climate change for South Asia. For IAM, initially, an econometric model is estimated that identifies the impact of climate change on crop yields, using the historical relationships between temperature, precipitation, and the production of cereals. Subsequently, future projections have been collected for temperature and precipitation from climate models of the Coupled Model Inter-comparison Project Phase 5 (CMIP5), and the previous econometric model is applied to obtain the implied future cereal yields changes.

Towards Secure Fitness Framework Based on IoT-Enabled Blockchain Network Integrated with Machine Learning Algorithms.

Blockchain technology has recently inspired remarkable attention due to its unique features, such as privacy, accountability, immutability, and anonymity, to name of the few. In contrast, core functionalities of most Internet of Things (IoT) resources make them vulnerable to security threats. The IoT devices, such as smartphones and tablets, have limited capacity in terms of network, computing, and storage, which make them easier for vulnerable threats.

Toward Accurate Position Estimation Using Learning to Prediction Algorithm in Indoor Navigation.

Internet of Things is advancing, and the augmented role of smart navigation in automating processes is at its vanguard. Smart navigation and location tracking systems are finding increasing use in the area of the mission-critical indoor scenario, logistics, medicine, and security. A demanding emerging area is an Indoor Localization due to the increased fascination towards location-based services.

Towards a Remote Monitoring of Patient Vital Signs Based on IoT-Based Blockchain Integrity Management Platforms in Smart Hospitals.

Over the past several years, many healthcare applications have been developed to enhancethe healthcare industry. Recent advancements in information technology and blockchain technologyhave revolutionized electronic healthcare research and industry. The innovation of miniaturizedhealthcare sensors for monitoring patient vital signs has improved and secured the human healthcaresystem.

Improving Accuracy of the Alpha-Beta Filter Algorithm Using an ANN-Based Learning Mechanism in Indoor Navigation System.

The navigation system has been around for the last several years. Recently, the emergence of miniaturized sensors has made it easy to navigate the object in an indoor environment. These sensors give away a great deal of information about the user (location, posture, communication patterns, etc.