Consumer Applications Research Articles

Using Natural Language Processing With Explainable AI Approach to Construct a Human-Centric Consumer Application for Financial Climate Disclosures

Using Natural Language Processing With Explainable AI Approach to Construct a Human-Centric Consumer Application for Financial Climate Disclosures

Research on Application Authorization Control Based on Business Center Services

This article analyzes the limitations of traditional authorization in the current situation of insufficient multi-level authorization management capabilities for end consumer applications in business middleware services. Taking the authorization system of business middleware services as a reference, multi-level authorization roles are introduced, and a fine-grained authorization management and authorization management model is proposed. And based on this authorization management model, a risk authorization identification method based on authorization behavior characteristics was explored. An intelligent learning risk authorization control model was proposed, which uses authorization behavior characteristics at all levels as the analysis basis. This enables the system to identify risk authorization actions at all levels, thereby improving the authorization system of business middleware services and achieving full supervision of hierarchical authorization allocation and use. The actual operational data proves that the risk authorization control model proposed in this article can accurately evaluate the risk nature of authorization behavior, and has broad application prospects.

Investigation of Empennage Location Effect to the Unmanned Aerial Vehicle (UAV) Structure Characteristic

Over the past few decades, unmanned aerial vehicles, commonly known as UAVs, have been widely used in a number of consumer and military applications, such as surveillance, tracking, monitoring, and aerial photography. Fixed-wing and rotary UAVs are the two primary categories in UAV. Interestingly, the hybridization of fixed-wing and rotary UAV gives better performance in terms of energy consumption and the needs of runaway. Designing new hybrid fixed wing-rotary UAV or hybrid vertical take-off and landing (VTOL) is challenging especially to identify the critical location in the UAV and material selection. Therefore, the objective of this research is to study the effect of empennage location and material selection on the structural strength of a hybrid VTOL UAV. The SolidWorks software was employed to design a 3D model of the UAV with different empennage locations, as well as perform a simulation of the structural strength of fibre glass, carbon fibre and kenaf for the hybrid VTOL UAV. The simulation analysis presents stress (Von Mises). The results show that the fibre glass (4.342 N/m2) at top empennage gives the best performance as compared to other parameters. In conclusion, this study is necessary to give a better picture of structural strength of composite materials and best design location in hybrid VTOL UAV for future research.

The Open Burning of Plastic Wastes is an Urgent Global Health Issue.

The open burning of mixed wastes that contain plastics is a widespread practice across the globe, resulting in the release of gas emissions and ash residues that have toxic effects on human and environmental health. Although plastic pollution is under scrutiny as a pressing environmental concern, it is often conflated with plastic litter, and the contribution of the open burning of plastics to air, soil, and water pollution gets overlooked. Therefore, campaigns to raise awareness about plastic pollution often end up leading to increased open burning. Many countries or regions where open burning is prevalent have laws in place against the practice, but these are seldom effective. In this viewpoint, we direct attention to this critical but largely overlooked dimension of plastic pollution as an urgent global health issue. We also advocate interventions to raise awareness about the risks of open burning and emphasize the necessity of phasing out some particularly pernicious plastics in high-churn, single-use consumer applications.

CHEMISTRY IN NANOMATERIALS OF HIGHWAYS

Summary: The article presents a variety of building materials, structures and products obtained using nanotechnology, which have improved physical and mechanical characteristics compared to traditional ones: they have greater strength, wear resistance, plasticity, heat resistance, and have significantly higher flash resistance. They are lighter in weight, more rational and safer to use and more durable. The use of nanotechnologies and nanomaterials is becoming more widespread in various spheres of human life. With unique properties, they are used for industrial and consumer applications, and their various types have found their place in many sectors: agriculture, energy, aerospace, cosmetics, food, medicine, construction, transportation, electronics, etc. But at the same time, it creates new risks and increases the impact on the environment. This effect is not visible to the eye, but it is noticeable for human health and the environment. It is necessary to properly use all safety measures and take care of the state of the atmosphere, water, soils and people during production, application, processing, packaging, construction work, transportation, storage, repair or demolition. This is provided by individual means of protection, ventilation systems, and dust collection during storage, construction, demolition, and waste disposal. One of the promising areas of environmental protection and cleaning is the bioutilization of nanoparticles by microorganisms and plants due to their battery capacity. Key words: Nanomaterials, nanotechnologies, road construction, environmental protection, emissions.

A low power circuit design of BLE baseband transmission data processing module

With the quickly development of the Internet of Things technology, Bluetooth (BLE) protocol has been increasingly adopted in consumer communication applications, industry communication utilization, and even positioning requirement, due to its advantages such as low power consumption, low cost, and low complexity. Especially the outstanding low power capability compared with other short-range communication protocol, many power limited AIoT (Artificial Intelligence IoT) devices select BLE as basic component. So, the low power, high performance, and small area BLE module become the key point of successful of whole AIoT system. In BLE system, the baseband data processing is the foundation. A good hardware circuit design of BLE baseband can improve BLE module performance and decrease power simultaneously. This paper analyzes the baseband data processing function of BLE in detail, and designs the baseband transmission data processing RTL circuit IP using Verilog HDL Hardware description language based on BLE protocol. The IP includes CRC verification module, whitening module and coding mapping function module. The RTL design is simulated and evaluated in workstation server with Synopsys VCS tool. The simulation results show that this design can achieve the Low-power BLE Bluetooth baseband function.

Safety assessment of the process Reciclar, based on the EREMA Basic technology, used to recycle post-consumer PET into food contact materials.

The EFSA Panel on Food Contact Materials, Enzymes and Processing Aids (CEP) assessed the safety of the recycling process Reciclar (EU register number RECYC314), which uses the EREMA Basic technology. The input material is ■■■■■ washed and dried poly(ethylene terephthalate) (PET) flakes originating from collected post-consumer PET containers, including no more than 5% PET from non-food consumer applications. The flakes are heated in a continuous reactor under vacuum before being extruded. Having examined the challenge test provided, the Panel concluded that the continuous decontamination (step 2), for which a challenge test was provided, is critical in determining the decontamination efficiency of the process. The operating parameters to control the performance of this step are temperature, pressure and residence time. It was demonstrated that this recycling process is able to ensure a level of migration of potential unknown contaminants into food below the conservatively modelled migration of 0.1 μg/kg food, derived from the exposure scenario for infants, when such recycled PET is used at up to 95% in mixtures with virgin PET, and of 0.15 μg/kg food, derived from the exposure scenario for toddlers, when used at up to 100%. Therefore, the Panel concluded that the recycled PET obtained from this process is not of safety concern when used at up to 95% in mixtures with virgin PET for manufacturing of materials and articles for contact with all types of foodstuffs, including drinking water bottles, and at up to 100% for the manufacture of materials and articles for contact with all types of foodstuffs, except drinking water, for long-term storage at room temperature or below, with or without hotfill. Articles made of this recycled PET are not intended to be used in microwave or conventional ovens and such uses are not covered by this evaluation.

Safety assessment of the process Novatex, based on the EREMA Basic technology, used to recycle post-consumer PET into food contact materials.

The EFSA Panel on Food Contact Materials, Enzymes and Processing Aids (CEP) assessed the safety of the recycling process Novatex (EU register number RECYC313), which uses the EREMA Basic technology. The input material is ■■■■■ washed and dried poly(ethylene terephthalate) (PET) flakes originating from collected post-consumer PET containers, including no more than 5% PET from non-food consumer applications. The flakes are heated in a continuous reactor under vacuum before being extruded. Having examined the challenge test provided, the Panel concluded that the continuous decontamination (step 2), for which a challenge test was provided, is critical in determining the decontamination efficiency of the process. The operating parameters to control the performance of this step are temperature, pressure and residence time. It was demonstrated that this recycling process is able to ensure a level of migration of potential unknown contaminants into food below the conservatively modelled migration of 0.1 μg/kg food derived from the exposure scenario for infants when such recycled PET is used at up to 95% in mixtures with virgin PET, and of 0.15 μg/kg food, derived from the exposure scenario for toddlers when used at up to 100%. Therefore, the Panel concluded that the recycled PET obtained from this process is not of safety concern when used at up to 95% in mixtures with virgin PET for manufacturing of materials and articles for contact with all types of foodstuffs, including drinking water bottles, and at up to 100% for the manufacture of materials and articles for contact with all types of foodstuffs except drinking water, for long-term storage at room temperature or below, with or without hotfill. Articles made of this recycled PET are not intended to be used in microwave or conventional ovens and such uses are not covered by this evaluation.

Graph Structure Learning-Based Multivariate Time Series Anomaly Detection in Internet of Things for Human-Centric Consumer Applications

Graph Structure Learning-Based Multivariate Time Series Anomaly Detection in Internet of Things for Human-Centric Consumer Applications

On the biocatalytic synthesis of silicone polymers.

Polysiloxanes, with poly(dimethyl)siloxane (PDMS) being the most common example, are widely used in various industrial and consumer applications due to the physicochemical properties imparted by their Si-O-Si backbone structure. The conventional synthesis of PDMS involves the hydrolysis of dichlorodimethylsilane, which raises environmental concerns due to the usage of chlorinated compounds. Herein, a biocatalytic approach for PDMS synthesis is demonstrated using silicatein-α (Silα), an enzyme from marine sponges that is known to catalyse the hydrolysis and condensation of Si-O bonds. Using dialkoxysilane precursors, it was found that Silα catalyses the formation of PDMS in non-aqueous media, yielding polymers with higher molecular weights (approximately 1000-2000 Da). However, on prolonged exposure, the gradual degradation of the polymers was also observed. Overall these observations indicate that Silα catalyses the formation polysiloxanes, demonstrating the potential of biocatalysis for more sustainable polysiloxane production.

Quantum Target Recognition Enhancement Algorithm for UAV Consumer Applications

Quantum Target Recognition Enhancement Algorithm for UAV Consumer Applications

Optimized resource allocation in cloud computing for enhanced performance with modified particle swarm optimization

Cloud Computing (CC) offers abundant resources and diverse services for running a wide range of consumer applications, although it faces specific issues that need attention. Cloud customers aim to choose the most suitable resource that fulfills the requirements of consumers at a fair cost and within an acceptable timeframe; however, at times, they wind up paying more for a shorter duration. Many advanced algorithms focus on optimizing a single variable individually. Hence, an Optimized Resource Allocation in Cloud Computing (ORA-CC) Model is required to achieve equilibrium between opposing aims in Cloud Computing. The ORA-CC study aims to create a task processing structure with the decision-making ability to choose the best resource in real-time for handling diverse and complicated uses on Virtual Computers (VC). It will utilize a Modified Particle Swarm Optimization (MoPSO) method to meet a deadline set by the user. The fitness value is calculated by combining a base value with the enhanced estimation of resources based on the ORA-CC algorithm to create a robust arrangement. The ORA-CC technique's effectiveness is evaluated by contrasting it with a few current multi-objective restrictions applied to machine scheduling strategies utilizing the Cloudsim simulation. The comparison demonstrates that the suggested ORA-CC strategy offers more efficient resource allocation than other techniques.

Poly- and per-fluoroalkyl substances in water: Occurrence, analytical methodologies, and remediations strategies: A comprehensive review

Abstract Poly- and perfluoroalkyl substances (PFASs) are fluoro-organic compounds comprising thousands of anthropogenically produced chemicals with various industrial and consumer applications. This review compiles recent information on the sources, occurrence, and health effects of PFAS in aquatic environments. Secondly, as a primary requirement for assessing the PFAS concentration in water, this review systematically summarised the analytical methodologies (sample preparation and analytical detection techniques) for PFAS. Furthermore, health risks associated with PFAS in water are outlined. Finally, researchers worldwide have investigated the strategies for the remediation and elimination of PFAS from water. Previous studies have shown that PFASs are present in various water bodies with the highest concentration detected in Germany (94–4,385 ng·L−1 in river and drinking waters). The findings of this review further revealed that solid-phase extraction techniques were the most preferred for sample preparation compared to liquid–liquid extraction techniques. Solid-phase extraction technique improved the limit of detection and the limit of quantification of many analytical techniques to 0.010–1.15 and 0.030–4.00 ng·L−1, respectively. For PFAS remediation, the adsorption method and chemical oxidation using heat-activated persulfate and photochemical oxidation were the most used techniques. The most studied water matrices were drinking, river, groundwater, wastewater, and modelled ultra-pure water. The most used detection technique was found to be liquid chromatograph-tandem mass spectrometer (LC-MS/MS).

Evaluating ChatGPT Responses on Thyroid Nodules for Patient Education.

Background: ChatGPT, an artificial intelligence (AI) chatbot, is the fastest growing consumer application in history. Given recent trends identifying increasing patient use of Internet sources for self-education, we seek to evaluate the quality of ChatGPT-generated responses for patient education on thyroid nodules. Methods: ChatGPT was queried 4 times with 30 identical questions. Queries differed by initial chatbot prompting: no prompting, patient-friendly prompting, 8th-grade level prompting, and prompting for references. Answers were scored on a hierarchical score: incorrect, partially correct, correct, or correct with references. Proportions of responses at incremental score thresholds were compared by prompt type using chi-squared analysis. Flesch-Kincaid grade level was calculated for each answer. The relationship between prompt type and grade level was assessed using analysis of variance. References provided within ChatGPT answers were totaled and analyzed for veracity. Results: Across all prompts (n = 120 questions), 83 answers (69.2%) were at least correct. Proportions of responses that were at least partially correct (p = 0.795) and correct (p = 0.402) did not differ by prompt; responses that were correct with references did (p < 0.0001). Responses from 8th-grade level prompting were the lowest mean grade level (13.43 ± 2.86) and were significantly lower than no prompting (14.97 ± 2.01, p = 0.01) and prompting for references (16.43 ± 2.05, p < 0.0001). Prompting for references generated 80/80 (100%) of referenced medical publications within answers. Seventy references (87.5%) were legitimate citations, and 58/80 (72.5%) provided accurately reported information from the referenced publication. Conclusion: ChatGPT overall provides appropriate answers to most questions on thyroid nodules regardless of prompting. Despite targeted prompting strategies, ChatGPT reliably generates responses corresponding to grade levels well-above accepted recommendations for presenting medical information to patients. Significant rates of AI hallucination may preclude clinicians from recommending the current version of ChatGPT as an educational tool for patients at this time.

Synergistic Effect of Lithium (difluoromethanesulfonyl)(trifluoromethanesulfonyl)Imide (LiDFTFSI) and Vinylene Carbonate (VC) on High Performance of NMC811║Graphite Cells

Lithium-ion batteries (LIBs) have gained increasing importance in energy storage systems, driven by the growing demands of grid storage, automotive, and portable consumer applications. To meet the need for high energy density batteries, one promising approach involves the utilization of high capacity layered transition metal oxide cathodes, such as nickel-rich LiNi0.8Mn0.1Co0.1O2 (NMC811), which can deliver a high reversible specific capacity of over 180 mAh·g-1 [1,2]. However, due to the structural and interfacial instability[3], nickel-rich NMC cathode still faces challenges in long-term galvanostatic cycling. For these reasons, design of novel electrolyte formulations, which enable formation of an effective cathode electrolyte interphase (CEI), is highly desirable. Recent studies have highlighted the cross-talk between the cathode and anode, indicating that the evolution of the solid electrolyte interphase (SEI) can impact the formation of the CEI[4]. Thus, establishing an effective SEI/CEI pair is essential for achieving long-term cycling of nickel-rich NMC cathode-based cells. Electrolyte optimization plays a crucial role in facilitating the formation of a desirable SEI/CEI pair, leading to an improved cell performance and longevity. Lithium (difluoromethanesulfonyl)(trifluoro-methanesulfonyl)imide (LiDFTFSI) has proven to be promising in solid-polymer-electrolyte batteries due to the good SEI/CEI formation ability and suppressed Al-dissolution[5]. Additionally, LiDFTFSI exhibits also good compatibility with Li-metal batteries[6], heralding promising applications in Li-ion batteries. However, there is lack of systematic research investigating the potential impact of LiDFTFSI on the cathode as well as on resulting CEI formation and dynamics.In this work, we demonstrated enhanced galvanostatic cycling performance of NMC811||graphite cells achieved by utilizing LiDFTFSI and lithium hexafluorophosphate (LiPF6) in a blended salt organic carbonate-based electrolyte formulation. Comprehensive electrochemical and post mortem analysis revealed that the LiDFTFSI alone can effectively mitigate the structural changes in the NMC811 electrode by facilitating the formation of modified CEI. However, the continued growth of an inhomogeneous CEI, caused by the cross-talk effect between electrodes, adversely affected long-term cycling stability. To address this, vinylene carbonate (VC) was introduced to the electrolyte. Synergistic effect with LiDFTFSI leads to the formation of effective and uniform SEI and CEI. As a result, 720 charge/discharge cycles were achieved in NMC811||graphite cells with LiDFTFSI and VC containing electrolytes at 1C while maintaining 80% state-of-health (SOH80%).

Recyclability of Post-Consumer Polystyrene at Pilot Scale: Comparison of Mechanical and Solvent-Based Recycling Approaches.

Solvent-based and mechanical recycling technology approaches were compared with respect to each process's decontamination efficiency. Herein, post-consumer polystyrene (PS) feedstock was recycled by both technologies, yielding recycled PS resins (rPS). The process feedstock was subjected to four recycling cycles in succession to assess the technology perennity. The physico-chemical and mechanical properties of the rPS were then evaluated to discern the advantages and drawbacks of each recycling approach. The molecular weight of the mechanically recycled resin was found to decrease by 30% over the reprocessing cycles. In contrast, the solvent-base recycling technology yielded a similar molecular weight regarding the feedstock. This consistency in the rPS product is critical for consumer applications. Further qualitative and quantitative analyses on residual organic compounds and inorganic and particulate contaminants were investigated. It was found that the solvent-based technology is very efficient for purifying deeply contaminated feedstock in comparison to mechanical recycling, which is limited to well-cleaned and niche feedstocks.

Enhancing thermal management in channels with sinusoidal elastic obstacles and pulsating nano-jet impingement: A new model

This study presents a new model for effective thermal management of a channel with elastic sinusoidal obstacles and pulsating multiple nano-jet impingements. The channel was cooled by alumina Al2O3 in various forms (platelets, blades, cylinders, and bricks) and water as a basic fluid. A hybrid nanofluid (multi-wall carbon nanotube-Fe3O4) was also used. The governing equations were solved using the finite volume method. Results were recorded for Reynolds numbers (Re = 350), Strouhal numbers (St = 0.01–1), pulse amplitude (A = 0.25–1), and the number of slots (Nj = 1–13). The results showed that the cooling efficiency was improved by using pulsating flow by 24.383%. It was also noted that using sinusoidal elastic obstacles improved the heat transfer rate by 8.344%. In addition, the number of slots affected the heat transfer rate, increasing it to 259.983%. The results obtained from this study demonstrate the effectiveness of the proposed design, which incorporates elastic sinusoidal obstacles and pulsating multiple nano-jet impingements, in significantly improving thermal management performance and reliability. These advancements hold great importance in various industrial and consumer applications.

Improving smart deals system to secure human-centric consumer applications: Internet of things and Markov logic network approaches

Considering the increasing inclination of modern consumers to frequent large retail chains capable of promptly fulfilling their diverse needs, there is a noticeable surge in the prevalence of contemporary shopping complexes. Subscription services, customer-focused strategies, and efficient supply management are driving the progression of intelligent commerce within these expansive retail platforms. The Internet of Things (IoT) presents the foundation for “smart” retailers that can monitor inventory levels, diminish equipment failures, and provide better customer experience. Many models, as one of the widely used methods in this domain, Markov Logic Network (MLN), can simultaneously use activity knowledge and data by unifying probability and logic. In this research, we determine a smart deals system (SDS), consider the improved machine learning algorithms to meet performance, and develop secure human-centric consumer applications to render the system workable. From the results, and based on the percentage of efficiency, around 10% of clients are connected randomly, which has a minor impact on the outcomes from LR (logistic regression). Similar outcomes are delivered when the number of customers in the scope of 30–40% is connected for NB (Naive Bayes). Hence, prospective shopping sales will increase along with the efficiency and speed at which it operates.

Machine Learning Based Foreign Object Detection in Wireless Power Transfer Systems

As power electronics continue to drive advancement in electronic devices by managing the system's energy flow, it is advantageous to examine all areas of energy transfer. Wireless power transfer is one section seeing increased adoption in consumer, industrial, and healthcare applications. This consequently increases the concern for safety, reliability, and efficiency. Power transmission to any unintended load is a primary safety issue in high-power wireless power transfer applications, such as unmanned aircraft systems. Foreign object detection is utilized to selectively transmit power to only the intended target to mitigate this issue. This paper seeks to demonstrate a novel alternative method of using machine learning and artificial intelligence techniques for performing foreign object detection solely on the transmitter portion of the system by only monitoring the TX coil current. This method is first evaluated in SPICE simulation software. Then by transitioning to a closed-loop hardware-based testbed designed to be deployed in unmanned aircraft systems. During the test process for the novel FOD method, the aggregate detection accuracy achieved was 83%, including worst-case misalignment conditions with the RX coil. When the outlying worst-case conditions are excluded, the detection accuracy improves to 97%. To measure the FOD effectiveness in preventing temperature rise in a metallic object, the metallic object was placed at the peak power draw location on the transmitter coil. When the metallic object is left at this location for extended periods, the novel FOD method lowers the maximum temperature reached by 86.8°C when compared to no FOD being active. The primary advantage to this novel method is the simplistic hardware additions, which only require minimal alterations to a WPTS without any FOD implemented. Along with this, implementing this foreign object detection method in the transmitter would mitigate the need for a direct communication link between the receiver and transmitter. As a result, the entire system complexity would decrease, thus increasing the UAS power density while maintaining a safe, effective, and reliable wireless power transmission method.

Current applications and future trends of artificial senses in fish freshness determination: A review.

Fish is a highly demanding food product and the determination of fish freshness is crucial as it is a fundamental factor in fish quality. Therefore, the fishery industry has been working on developing rapid fish freshness determination methods to monitor freshness levels. Artificial senses that mimic human senses are developed as convenient emerging technologies for fish freshness determination. Computer vision, electronic nose (e-nose), and electronic tongue (e-tongue) are the emerging artificial senses for fish freshness determination. This review article is uniquely worked upon to investigate the current applications of the artificial senses in fish freshness determination while describing the steps, and fundamental principles behind each artificial sense, comparing them with their advantages and limitations, and future trends related to fish freshness determination. Among the artificial senses, computer vision determines the freshness of fish in a completely nondestructive way while the e-tongue determines the freshness of fish in a completely destructive way. There are developed e-noses for fish freshness determination in both destructive and nondestructive ways. By analyzing visual cues such as color, computer vision systems can assess fish quality without the need for physical contact and it makes computer vision suitable for large-scale industrial fish quality assessing applications. Overall, this review study reveals artificial senses as a proven replacement for traditional sensory panels in determining fish freshness precisely and conveniently. As future trends, there is a demand for developing applications for consumers to determine fish freshness based on artificial senses.