DeepHealthNet: Adolescent Obesity Prediction System Based on a Deep Learning Framework.

The global prevalence of childhood and adolescent obesity is a major concern due to its association with chronic diseases and long-term health risks. Artificial intelligence technology has been identified as a potential solution to accurately predict obesity rates and provide personalized feedback to adolescents. This study highlights the importance of early identification and prevention of obesity-related health issues. To develop effective algorithms for the prediction of obesity rates and provide personalized feedback, factors such as height, weight, waist circumference, calorie intake, physical activity levels, and other relevant health information must be taken into account. Therefore, by collecting health datasets from 321 adolescents who participated in Would You Do It! application, we proposed an adolescent obesity prediction system that provides personalized predictions and assists individuals in making informed health decisions. Our proposed deep learning framework, DeepHealthNet, effectively trains the model using data augmentation techniques, even when daily health data are limited, resulting in improved prediction accuracy (acc: 0.8842). Additionally, the study revealed variations in the prediction of the obesity rate between boys (acc: 0.9320) and girls (acc: 0.9163), allowing the identification of disparities and the determination of the optimal time to provide feedback. Statistical analysis revealed that the performance of the proposed deep learning framework was more statistically significant (p 0.001) compared to the other general models. The proposed system has the potential to effectively address childhood and adolescent obesity.

Grouping of unused agricultural by-product biomass for fuel conversion in South Korea through multivariate analysis.

While biomass holds significance as a resource, its abundance in South Korea is limited. Therefore, in this study analyzed the chemical characteristics of agricultural by-products produced and evaluated their fuel potentiality. To achieve this objective, multivariate analysis was utilized to create biomass clusters with diverse feature. All investigated biomass types showed heating values of at least 12.6 MJ/kg, adhering to South Korea's Bio-solid recovered fuel (SRF) standard, once the moisture content was reduced to 20 % or less. However, the biomasses only met the heating value of Level 3 of the European standard for SRF, which is at least 15 MJ/kg. Groups were formed based on a multivariate analysis using four variables: the high heating value, and carbon, nitrogen, and ash contents. The groups were centered around wood chips and hog fuel, with a cluster of lignocellulosic biomass materials surrounding them. The clusters formed around four groups. When the biomasses in each group were mixed, the combustion characteristics were compared to the ignition, maximum, and burn-out temperatures. Utilizing biomass grouping, by-products from agriculture and livestock in South Korea can be effectively employed as energy sources.

One-dimensional modeling of heterogeneous catalytic chemical looping steam methane reforming in an adiabatic packed bed reactor.

Hydrogen production via chemical looping steam methane reforming (CL-SMR) is among the most promising current technologies. This work presents the development in gPROMS Model Builder 4.1.0® of a 1D model of an adiabatic packed bed reactor used for chemical looping reforming (CLR). The catalyst used for this process was 18 wt. % NiO with the support of Al2O3. A brief thermodynamic analysis using Chemical Equilibrium Application (CEA) was carried out to identify the optimum operating conditions. The model was simulated for 10 complete CL-SMR cycles. The effects of variations in temperature, pressure, gas mass velocity, nickel oxide concentration, reactor length, and particle diameter were studied to investigate the performance of the CL-SMR process under these variations. A parametric analysis was carried out for different ranges of conditions: temperatures from 600 to 1,000 K, pressure from 1 to 5 bar, gas mass velocity between 0.5 and 0.9 kg·m-2 s-1, nickel oxide concentration values between 0.1 and 1 mol·m-3, particle diameters between 0.7 and 1 mm, and fuel reactor (FR) lengths between 0.5 and 1.5 m. At the optimum temperature (950 K), pressure (1 bar), and steam-to-carbon molar ratio (3/1), with an increase in particle diameter from 0.7 to 1 mm, an 18% decrease in methane conversion and a 9.5% increase in hydrogen yield were observed. Similarly, with an increase in FR length from 0.5 m to 1.5 m, a delay in the temperature drop was observed.

Evaluation of Organic and Inorganic Foulant Interaction Using Modified Fouling Models in Constant Flux Dead-End Operation with Microfiltration Membranes.

The goal of this study was to elucidate the interaction of complex feed solutions under modified membrane fouling models for constant flux operation. The polyvinylidene fluoride membrane (PVDF) was tested for three types of solutions containing inorganic foulants (Al, Mn, and Fe), organic foulants, and suspended solids at 0.5 mM Ca2+ ionic strength. The membrane's performance was evaluated by measuring the increase in transmembrane pressure (TMP) during two different filtration scenarios: continuous filtration lasting 1 h and cyclic filtration lasting 12 min, with 3 min backwashing cycles included. Statistical analysis (linear regression results (R2), p-value) was used to verify the fouling model propagation along with the determination of the contributing constant of each fouling model. An increasing TMP percentage of 164-302%, 155-300%, and 208-378% for S1 (HA + Ca2+), S2 (inorganics + kaolin + Ca2+), and S3 (HA + inorganics + kaolin + Ca2+) was recorded for 1 h filtration, respectively. Furthermore, a five percent increase in irreversible resistance was noted for the S3 solution due to the strong adsorption potential of foulants for the PVDF membrane caused by the electrostatic and hydration forces of foulants. In addition to that, the participation equation elucidated the contribution of the fouling model and confirmed that complete blocking and cake layer contribution were dominant for the S1 and S3 solutions, while standard blocking was dominant for the S2 solution with a high significance ratio. Moreover, R2 and cyclic filtration analysis also confirmed the propagation of these fouling models. The statistical confirmation and regression results analysis of the modified model gave comparative results and satisfied the filtration mechanism and can be used for the constant flux dead filtration analysis of water treatment.

Effects of air blower and pump failures on the performance of A2O processes for wastewater treatment.

The unexpected failure of equipment such as pumps and fans in wastewater treatment plants can reduce wastewater treatment efficiency, leading to direct leakage of untreated wastewater into the environment. It is hence important to predict the possible consequences of equipment failure to minimize the leakage of harmful substances. This study examines the impacts of equipment shutdown on the performance and recovery time of a laboratory-scale anaerobic/anoxic/aerobic system with regard to reactor conditions and water quality. Two days after the air blowers are stopped, the concentrations of the soluble chemical oxygen demand, NH4-N, and PO4-P in the effluent of the settling tank increase to 122 mg/L, 23.8 mg/L, and 46.6 mg/L, respectively. These concentrations return to their initial values after 12, 24, and 48 h of restarting the air blowers. The concentrations of PO4-P and NO3-N in the effluent increase to 58 mg/L and 20 mg/L, respectively, about 24 h after stopping the return activated sludge and mixed liquor recirculation pumps, owing to the release of phosphates in the settling tank and inhibition of denitrification.

A deep learning-based framework for predicting pork preference.

Meat consumption per capita in South Korea has steadily increased over the last several years and is predicted to continue increasing. Up to 69.5% of Koreans eat pork at least once a week. Considering pork-related products produced and imported in Korea, Korean consumers have a high preference for high-fat parts, such as pork belly. Managing the high-fat portions of domestically produced and imported meat according to consumer needs has become a competitive factor. Therefore, this study presents a deep learning-based framework for predicting the flavor and appearance preference scores of the customers based on the characteristic information of pork using ultrasound equipment. The characteristic information is collected using ultrasound equipment (AutoFom III). Subsequently, according to the measured information, consumers' preferences for flavor and appearance were directly investigated for a long period and predicted using a deep learning methodology. For the first time, we have applied a deep neural network-based ensemble technique to predict consumer preference scores according to the measured pork carcasses. To demonstrate the efficiency of the proposed framework, an empirical evaluation was conducted using a survey and data on pork belly preference. Experimental results indicate a strong relationship between the predicted preference scores and characteristics of pork belly.

A Comprehensive Survey on Security and Privacy for Electronic Health Data.

Recently, the integration of state-of-the-art technologies, such as modern sensors, networks, and cloud computing, has revolutionized the conventional healthcare system. However, security concerns have increasingly been emerging due to the integration of technologies. Therefore, the security and privacy issues associated with e-health data must be properly explored. In this paper, to investigate the security and privacy of e-health systems, we identified major components of the modern e-health systems (i.e., e-health data, medical devices, medical networks and edge/fog/cloud). Then, we reviewed recent security and privacy studies that focus on each component of the e-health systems. Based on the review, we obtained research taxonomy, security concerns, requirements, solutions, research trends, and open challenges for the components with strengths and weaknesses of the analyzed studies. In particular, edge and fog computing studies for e-health security and privacy were reviewed since the studies had mostly not been analyzed in other survey papers.

Effects of steam pretreatment on fouled membrane in chemical cleaning for flux recovery in drinking water treatment.

This paper shows the possibility of using steam pretreatment to improve the efficiency of membrane recovery chemical cleaning. Before applying chemicals to clean a fouled membrane, steam pretreatment was employed to loosen the structure of the foulant layer and weaken the attachment of those foulants on the membrane. Although longer steam contact times would lead to even better cleaning efficiency, the steam pretreatment duration was limited to less than 2 min to maintain membrane integrity. When cleaning fouled membranes with 1 mol/L HCl, the cleaning efficiency without steam pretreatment went from 83.3 to 90.2% as cleaning time increased from 30 to 180 min. As for 90-s steam pretreatment, the cleaning efficiency showed high values of more than 93% regardless of cleaning time. When the concentration of HCl was decreased to 0.2 mol/L, the cleaning efficiencies with a 90-s steam pretreatment was 78.6% and 92.6% for relatively short cleaning times of 30 and 60 min, respectively; this is much higher than the 62.2% and 76.7% achieved when cleaning without steam pretreatment. In addition, when using alkaline solution as the cleaning chemical, similar results were obtained. This implies that the application of steam before chemical cleaning is effective in improving cleaning efficiency, and so, this technique has the potential to reduce the amount of cleaning chemical required for membrane recovery cleaning.

Self-Adaptive Framework Based on MAPE Loop for Internet of Things.

The Internet of Things (IoT) connects a wide range of objects and the types of environments in which IoT can be deployed dynamically change. Therefore, these environments can be modified dynamically at runtime considering the emergence of other requirements. Self-adaptive software alters its behavior to satisfy the requirements in a dynamic environment. In this context, the concept of self-adaptive software is suitable for some dynamic IoT environments (e.g., smart greenhouses, smart homes, and reality applications). In this study, we propose a self-adaptive framework for decision-making in an IoT environment at runtime. The framework comprises a finite-state machine model design and a game theoretic decision-making method for extracting efficient strategies. The framework was implemented as a prototype and experiments were conducted to evaluate its runtime performance. The results demonstrate that the proposed framework can be applied to IoT environments at runtime. In addition, a smart greenhouse-based use case is included to illustrate the usability of the proposed framework.

Electrospun Nanofiber Membranes Incorporating PDMS-Aerogel Superhydrophobic Coating with Enhanced Flux and Improved Antiwettability in Membrane Distillation.

Electrospun nanofiber membranes (ENMs) have garnered increasing interest due to their controllable nanofiber structure and high void volume fraction properties in membrane distillation (MD). However, MD technology still faces limitations mainly due to low permeate flux and membrane wetting for feeds containing low surface tension compounds. Perfluorinated superhydrophobic membranes could be an alternative, but it has negative environmental impacts. Therefore, other low surface energy materials such as silica aerogel and polydimethylsiloxane (PDMS) have great relevancy in ENMs fabrication. Herein, we have reported the high flux and nonwettability of ENMs fabricated by electrospraying aerogel/polydimethylsiloxane (PDMS)/polyvinylidene fluoride (PVDF) over electrospinning polyvinylidene fluoride- co-hexafluoropropylene (PVDF-HFP) membrane (E-PH). Among various concentrations of aerogel, the 30% aerogel (E-M3-A30) dual layer membrane achieved highest superhydrophobicity (∼170° water contact angle), liquid entry pressure (LEP) of 129.5 ± 3.4 kPa, short water droplet bouncing performance (11.6 ms), low surface energy (4.18 ± 0.27 mN m-1) and high surface roughness ( Ra: 5.04 µm) with re-entrant structure. It also demonstrated nonwetting MD performance over a continuous 7 days operation of saline water (3.5% of NaCl), high antiwetting with harsh saline water containing 0.5 mM sodium dodecyl sulfate (SDS, 28.9 mN m-1), synthetic algal organic matter (AOM).

Engineering the Re-Entrant Hierarchy and Surface Energy of PDMS-PVDF Membrane for Membrane Distillation Using a Facile and Benign Microsphere Coating.

To consolidate the position of membrane distillation (MD) as an emerging membrane technology that meets global water challenges, it is crucial to develop membranes with ideal material properties. This study reports a facile approach for a polyvinylidene fluoride (PVDF) membrane surface modification that is achieved through the coating of the surface with poly(dimethylsiloxane) (PDMS) polymeric microspheres to lower the membrane surface energy. The hierarchical surface of the microspheres was built without any assistance of a nano/microcomposite by combining the rapid evaporation of tetrahydrofuran (THF) and the phase separation from condensed water vapor. The fabricated membrane exhibited superhydrophobicity-a high contact angle of 156.9° and a low contact-angle hysteresis of 11.3°-and a high wetting resistance to seawater containing sodium dodecyl sulfate (SDS). Compared with the control PVDF-hexafluoropropylene (HFP) single-layer nanofiber membrane, the proposed fabricated membrane with the polymeric microsphere layer showed a smaller pore size and higher liquid entry pressure (LEP). When it was tested for the direct-contact MD (DCMD) in terms of the desalination of seawater (3.5% of NaCl) containing SDS of a progressively increased concentration, the fabricated membrane showed stable desalination and partial wetting for the 0.1 and 0.2 mM SDS, respectively.

Enhanced vapor transport in membrane distillation via functionalized carbon nanotubes anchored into electrospun nanofibres.

To ascertain membrane distillation (MD) as an emerging desalination technology to meet the global water challenge, development of membranes with ideal material properties is crucial. Functionalized carbon nanotubes (CNTs) were anchored to nanofibres of electrospun membranes. Covalent modification and fluorination of CNTs improved their dispersibility and interfacial interaction with the polymer membrane, resulting in well-aligned CNTs inside crystalline fibres with superhydrophobicity. Consideration for the chemical/physical properties of the CNT composite membranes and calculation of their theoretical fluxes revealed the mechanism of MD: CNTs facilitated the repulsive force for Knudsen and molecular diffusions, reduced the boundary-layer effect in viscous flow, and assisted surface diffusion, allowing for fast vapor transport with anti-wetting. This study shows that the role of CNTs and an optimal composite ratio can be used to reduce the gap between theoretical and experimental approaches to desalination.

High flux and antifouling properties of negatively charged membrane for dyeing wastewater treatment by membrane distillation.

This study investigated the applicability of membrane distillation (MD) to treat dyeing wastewater discharged by the textile industry. Four different dyes containing methylene blue (MB), crystal violet (CV), acid red 18 (AR18), and acid yellow 36 (AY36) were tested. Two types of hydrophobic membranes made of polytetrafluoroethylene (PTFE) and polyvinylidene fluoride (PVDF) were used. The membranes were characterized by testing against each dye (foulant-foulant) and the membrane-dye (membrane-foulant) interfacial interactions and their mechanisms were identified. The MD membranes possessed negative charges, which facilitated the treatment of acid and azo dyes of the same charge and showed higher fluxes. In addition, PTFE membrane reduced the wettability with higher hydrophobicity of the membrane surface. The PTFE membrane evidenced especially its resistant to dye absorption, as its strong negative charge and chemical structure caused a flake-like (loose) dye-dye structure to form on the membrane surface rather than in the membrane pores. This also enabled the recovery of flux and membrane properties by water flushing (WF), thereby direct-contact MD with PTFE membrane treating 100 mg/L of dye mixtures showed stable flux and superior color removal during five days operation. Thus, MD shows a potential for stable long-term operation in conjunction with a simple membrane cleaning process, and its suitability in dyeing wastewater treatment.

A mechanistic study of in situ chemical cleaning-in-place for a PTFE flat sheet membrane: fouling mitigation and membrane characterization.

This study aimed at unfolding the role and mechanisms of chemically enhanced cleaning-in-place (CIP) regimes in fouling control of polytetrafluoroethylene (PTFE) made flat sheet (FS) membrane bio-reactors (MBRs). The trans-membrane pressure (TMP) was successfully maintained below 10 kPa using a daily CIP regime consisting of 100 to 600 mg l(-1) of NaOCl and cake layer resistance control was shown to be critical for effective high-flux MBR operation. In contrast, in the control unit without the CIP, the TMP exceeded 35 kPa at a flux of 40 LMH. The extracellular polymeric substances associated with proteins (EPSprotein) were also controlled effectively with a daily application of the CIP to the fouled membrane. Moreover, the CIP prompted a thinner and looser bio-cake layer on the membrane surface, suggesting that in situ CIP can be a favorable method to control FS membrane fouling at high-flux MBR operation.

A comparative study on per capita waste generation according to a waste collecting system in Korea.

As cities are becoming increasingly aware of problems related to conventional mobile collection systems, automated pipeline-based vacuum collection (AVAC) systems have been introduced in some densely populated urban areas. The reasons are that in addition to cost savings, AVAC systems can be efficient, hygienic, and environmentally friendly. Despite difficulties in making direct comparisons of municipal waste between a conventional mobile collection system and an AVAC system, it is meaningful to measure the quantities in each of these collection methods either in total or on a per capita generation of waste (PCGW, g/(day*capita)) basis. Thus, the aim of this study was to assess the difference in per capita generation of household waste according to the different waste collection methods in Korea. Observations on household waste show that there were considerable differences according to waste collection methods. The value of per capita generation of food waste (PCGF) indicates that a person in a city using AVAC produces 60 % of PCGF (109.58 g/(day*capita)), on average, compared with that of a truck system (173.10 g/(day*capita)) as well as 23 %p less moisture component than that with trucks. The value of per capita generation of general waste (PCGG) in a city with an AVAC system showed 147.73 g/(day*capita), which is 20 % less than that with trucks delivered (185 g/(day*capita)). However, general waste sampled from AVAC showed a 35 %p increased moisture content versus truck delivery.

Influence of microbubble in physical cleaning of MF membrane process for wastewater reuse.

Currently, there is a growing emphasis on wastewater reclamation and reuse all over the world due to restricted water resources. Among a variety of wastewater reuse technologies, the use of microfiltration membranes (MF) is one of the popular processes because it has the ability to successfully eliminate particulates and colloidal matters. However, successful fouling control is not easy because effluents from the activated sludge process still contain small particulates and colloidal matters such as extracellular polymeric substance (EPS) and soluble microbial products (SMP). On the other hand, microbubbles have advantageous properties compared to common bubbles, but there hasn't been reporting of the use of microbubbles in physical cleaning instead of aeration. Encouraging results were obtained herein through the application of microbubbles for physical cleaning. In evaluation of the cleaning efficiency, the efficiency of microbubbles was observed to be twice as high as that of aeration, except during the course of the initial 30 min. Total organic carbon (TOC) concentration of the membrane tank after treatment with microbubbles was more than twice as high as that after aeration for physical cleaning. The membrane cleaned with microbubbles also had the smoothest surface, with a roughness of 42.5 nm. In addition, microbubbles were found to effectively remove EPS and make the structure of the gel layer loose. In particular, the microbubbles had the ability to remove proteins through the effect of pyrolytic decomposition. Therefore, in FT-IR spectra of the membrane surfaces taken before and after physical cleaning, while each treatment showed similar peak positions, the peak values of the membrane treated with microbubbles were the lowest. Through various analyses, it was confirmed that microbubbles can remove foulants on the gel layer in spite of their very low shear force. This means that microbubble cleaning has full potential for use as a physical cleaning method in the wastewater reclamation process.

An analysis of the effects of osmotic backwashing on the seawater reverse osmosis process.

Fouling control is an important consideration in the design and operation of membrane-based water treatment processes. It has been generally known that chemical cleaning is still the most common method to remove foultants and maintain the performance of reverse osmosis (RO) desalination. Regardless of the chemical membrane cleaning methods applied effectively, however, frequent chemical cleaning can shorten the membrane life. In addition, it also increases operating and maintenance costs due to the waste chemical disposal. As an alternative, osmotic backwashing can be applied to RO membranes by diluting the concentration polarization (CP) layer. In this study, the effects of osmotic backwashing were analysed under different total dissolved salts (TDSs) and backwashing conditions, and the parameters of the osmotic backwashing were evaluated. The results of the analysis based on the properties of the organic matters found in raw water showed that the cleaning efficiency in respect to the fouling by hydrophilic organic matters was the greatest. Osmotic backwashing was carried out by changing the TDS of the permeate. As a result, the backwashing volume decreased with time due to the CP of the permeate and the backwashing volume. The difference in the osmotic pressure between the raw water and the permeate (Delta pi) also decreased as time passed. It was confirmed that when the temperature of the effluent was high, both the cleaning efficiency and the backwashing volume, which inpours at the same time, increased. When the circulation flow of the effluent was high, both the cleaning efficiency and the backwashing volume increased.