A Smart Wellness Service Platform and Its Practical Implementation

Advances in the field of medical sciences and medical technology, and present-day challenges, such as an aging population, rising medical expenses, and lifestyle-related diseases, have collectively catalyzed a research ecosystem termed “smart wellness.” This article describes the establishment of a smart wellness service platform designed to empower individuals to create a sense of balance in their lives. Step-by-step details include service model, design, and architectural considerations. As a proof of concept, implementation details of a Health Improvement and Management Systems (HIMS) Hub, a Smart Wellness Service Platform deployed in six cities in South Korea, are presented. An on-site survey conducted in Busan Metropolitan City reveals the percentage of satisfied users to be 91.3%. Furthermore, data gathered from 27,236 physical evaluations of users from a Busan city center over the period of April 2013 to May 2018 reveal that males and females in their 50s and 60s account for the highest number of participants, while males in their 70s have a higher rate of participation than females in the same age group.     

Integrated Adsorbent Process Optimization for Minimum Cost of Electricity Including Carbon Capture by a VSA Process

Assessing vacuum swing adsorption (VSA) technology for postcombustion CO₂ capture and concentration (CCC) using energy and productivity indicators are useful, but its ultimate test must be the cost of electricity from a power plant including CCC. Here, our integrated optimization platform (Khurana and Farooq, AlChE J. 2017;63:2987–2995) developed earlier to simultaneously obtain the optimum adsorbent and process conditions is extended to include a comprehensive costing framework. The framework is complete with scale-up design and column scheduling, and compliant with National Energy Technology Laboratory costing guidelines for carbon capture. This is the ultimate tool that enables integrated optimization to minimize the cost of electricity. The Shell Cansolv CO₂ capture system is used as the benchmark for evaluating the best performance of two VSA cycles for two adsorbents. The operating conditions and isotherm shapes necessary to achieve the lowest possible cost of electricity for the two VSA cycles are also presented to facilitate designing or searching the best adsorbent for CCC. © 2018 American Institute of Chemical Engineers AIChE J, 65: 184–195, 2019     

EBSD characterization of carbide–carbide boundaries in WC–Co composites

A sample of WC‐6wt%Co was investigated for grain boundary character distribution and occurrence of coincidence site lattice (CSL) boundaries on a statistical basis. For this purpose orientation measurements of the grains were carried out using electron back‐scattered diffraction (EBSD). The dominant misorientation relationships were determined by complementary EBSD data representation tools such as orientation maps, misorientation angle distribution histograms and the sectioned three‐dimensional misorientation space. It was found that the grain boundary character distribution of the material is nearly random and the CSL boundaries are not present in statistically significant amounts. It was also found that the amount of binder phase does not play a role in the formation of special boundaries. The paper focuses on the methodology of characterizing grain boundaries in a hexagonal material using EBSD.     

Prediction of postpartum depression using machine learning techniques from social media text

Early screening of mental disorders plays a crucial role in diagnosis and treatment. This study explores how data‐driven methods can leverage the information available on social media platforms to predict postpartum depression (PPD). A generalized approach is proposed where linguistic features are extracted from user‐generated textual posts on social media and categorized as general, depressive, and PPD representative using multiple machine learning techniques. We find that techniques used in our study exhibit strong predictive capabilities for PPD content. Holdout validation showed that multilayer perceptron outperformed other techniques such as support vector machine and logistic regression used in this study with 91.7% accuracy for depressive content identification and up to 86.9% accuracy for PPD content prediction. This work adopts a hierarchical approach to predict PPD. Therefore, the reported PPD accuracy represents the performance of the model to correctly classify PPD content from non‐PPD depressive content.     

Insight into kinetics and thermodynamics properties of multicomponent lead(II), cadmium(II) and manganese(II) adsorption onto Dijah-Monkin bentonite clay

Multicomponent adsorption of lead(II), cadmium(II) and manganese(II) by Nigerian Dijah-Monkin bentonite clay was investigated. The clay samples were characterized for elemental composition, cation exchange capacity and textural properties. Natural bentonite exhibits cation exchange capacity of 47.7?meq/100?g and specific surface area of 23.5?m²/g. Manganese(II) displays higher values of rate constant than lead(II) in multimetals adsorption. However, lead(II) is favorably adsorbed onto bentonite adsorbents at different concentrations studied. The multimetals adsorption onto bentonite clay samples is site selective and site specific. The pseudo-second-order kinetics model gave a better fit to the adsorption data, suggesting ion exchange and/or complex formation. The adsorption mechanism could be described by intraparticle diffusion with some restriction of metals diffusion due to film or boundary layer. Also, the multicomponent adsorption is endothermic and becomes more spontaneous as temperature increased from 303 to 338?K. Nigerian bentonite clay in its natural form is a promising adsorbent for multimetals removal in aqueous solution.     

Mapping past,current and future energy research trend in Pakistan: a scientometric assessment

This work describes the contribution of researchers in the field of the energy from Pakistan in the period 1990–2016. A scientometric approach was applied to analyze the scientific publications in the field using the Scopus Elsevier database. Different aspects of the publications were analyzed, such as publication type, major research areas, journals, citations, authorship pattern, affiliations as well as the keyword occurrence frequency. The present research trends are analyzed and future research directions are outlined. The impact factor, h-index and number of citations were used to investigate the strength of active institutes, authors, and journals in the field of the energy in Pakistan. From 1990 to 2016, 991 articles have been published by 2139 authors from 213 research institutes. The total number of citations and impact factor are 10,287 and 2301 respectively, corresponding to 10 citations per paper and an impact factor of 2.32 per publication. The research articles originate primarily from COMSATS, NUST, PIEAS, and PINSTECH. Pakistan has published 60% of publication with the collaboration of the foreign institutes, mainly from the United States, the United Kingdom, China and Malaysia. The core research activities in the field are mainly focused on resource assessment, energy policy, energy efficiency, feasibility study, energy economics, and performance assessment. The most productive journal, author, institution, are renewable & sustainable energy review, Shahbaz M., and COMSATS, respectively.     

Novel Analytical Thermal Performance Rate Analysis in ZnO-SAE50 Nanolubricant: Nonlinear Mathematical Model

The investigation of local thermal transport rate in the nanolubricants is significant. These lubricants are broadly used in environmental pollution, mechanical engineering and in the paint industry due to high thermal performance rate. Therefore, thermal transport in ZnO-SAE50 nanolubricant under the impacts of heat generation/absorption is conducted. The colloidal suspension is flowing between parallel stretching disks in which the lower disk is positioned at z = 0 and upper disk apart from distance d. The problem is transformed in dimensionless version via described similarity transforms. In the next stage, an analytical technique (VPM) is implemented for the solution purpose. The graphical results against multiple flow parameters were furnished over the region of interest and explained comprehensively. It is imperative to mention that the results are plotted for ZnO-SAE50 and conventional liquid as well. Further, rapid motion of the fluid is perceived against high Reynolds and γ parameters. The wall shear stresses at the upper end rises for multiple Reynolds and γ while; decrement is detected at the lower end. The significant contribution of an internal heat source is noted for thermal performance rate at the upper end. Foremost, the local heat transport rate declines at the lower disk. By altering Reynolds number, prompt heat transfer rate is gained at the upper disk and increasing behavior of the local heat transport rate is slow at the lower disk. From the study, it is concluded that the nanolubricants have high thermal characteristics. Therefore, such fluids are reliable to use in above stated areas.     

Al₂O₃ and γAl₂O₃ Nanomaterials Based Nanofluid Models with Surface Diffusion: Applications for Thermal Performance in Multiple Engineering Systems and Industries

Thermal transport investigation in colloidal suspensions is taking a significant research direction. The applications of these fluids are found in various industries, engineering, aerodynamics, mechanical engineering and medical sciences etc. A huge amount of thermal transport is essential in the operation of various industrial production processes. It is a fact that conventional liquids have lower thermal transport characteristics as compared to colloidal suspensions. The colloidal suspensions have high thermal performance due to the thermophysical attributes of the nanoparticles and the host liquid. Therefore, researchers focused on the analysis of the heat transport in nanofluids under diverse circumstances. As such, the colloidal analysis of H₂O composed by γAl₂O₃ and Al₂O₃ is conducted over an elastic cylinder. The governing flow models of γAl₂O₃/H₂O and Al₂O₃/H₂O is reduced in the dimensionless form by adopting the described similarity transforms. The colloidal models are handled by implementing the suitable numerical technique and provided the results for the velocity, temperature and local thermal performance rate against the multiple flow parameters. From the presented results, it is shown that the velocity of Al₂O₃–H₂O increases promptly against a high Reynolds number and it decreases for high-volume fraction. The significant contribution of the volumetric fraction is examined for thermal enhancement of nanofluids. The temperature of Al₂O₃–H₂O and γAl₂O₃–H₂O significantly increases against a higher ϕ. Most importantly, the analysis shows that γAl₂O₃–H₂O has a high local thermal performance rate compared to Al₂O₃–H₂O. Therefore, it is concluded that γAl₂O₃–H₂O is a better heat transfer fluid and is suitable for industrial and technological uses.     

Traffic Queuing Management in the Internet of Things: An Optimized RED Algorithm Based Approach

Congestion control is one of the main obstacles in cyberspace traffic. Overcrowding in internet traffic may cause several problems; such as high packet hold-up, high packet dropping, and low packet output. In the course of data transmission for various applications in the Internet of things, such problems are usually generated relative to the input. To tackle such problems, this paper presents an analytical model using an optimized Random Early Detection (RED) algorithm-based approach for internet traffic management. The validity of the proposed model is checked through extensive simulation-based experiments. An analysis is observed for different functions on internet traffic. Four performance metrics are taken into consideration, namely, the possibility of packet loss, throughput, mean queue length and mean queue delay. Three sets of experiments are observed with varying simulation results. The experiments are thoroughly analyzed and the best packet dropping operation with minimum packet loss is identified using the proposed model.