Application Performance Research Articles

Developing an AI-based application for caries index detection on intraoral photographs.

This study evaluates the effectiveness of an Artificial Intelligence (AI)-based smartphone application designed for decay detection on intraoral photographs, comparing its performance to that of junior dentists. Conducted at The Aga Khan University Hospital, Karachi, Pakistan, this study utilized a dataset comprising 7,465 intraoral images, including both primary and secondary dentitions. These images were meticulously annotated by two experienced dentists and further verified by senior dentists. A YOLOv5s model was trained on this dataset and integrated into a smartphone application, while a Detection Transformer was also fine-tuned for comparative purposes. Explainable AI techniques were employed to assess the AI's decision-making processes. A sample of 70 photographs was used to directly compare the application's performance with that of junior dentists. Results showed that the YOLOv5s-based smartphone application achieved a precision of 90.7%, sensitivity of 85.6%, and an F1 score of 88.0% in detecting dental decay. In contrast, junior dentists achieved 83.3% precision, 64.1% sensitivity, and an F1 score of 72.4%. The study concludes that the YOLOv5s algorithm effectively detects dental decay on intraoral photographs and performs comparably to junior dentists. This application holds potential for aiding in the evaluation of the caries index within populations, thus contributing to efforts aimed at reducing the disease burden at the community level.

SimCDL: A Simple Framework for Contrastive Dictionary Learning

In this paper, we propose a novel approach to the dictionary learning (DL) initialization problem, leveraging the SimCLR framework from deep learning in a self-supervised manner. Dictionary learning seeks to represent signals as sparse combinations of dictionary atoms, but effective initialization remains challenging. By applying contrastive learning, we encourage similar representations for augmented versions of the same sample while distinguishing between different samples. This results in a more diverse and incoherent set of atoms, which enhances the performance of DL applications in classification and anomaly detection tasks. Our experiments across several benchmark datasets demonstrate the effectiveness of our method for improving dictionary learning initialization and its subsequent impact on performance in various applications.

Wavelength Stabilization of Entangled Biphotons Using Dynamic Temperature Compensation for Quantum Interference Applications

AbstractIn this paper, a dynamic temperature compensation method is presented to stabilize the wavelength of the entangled biphoton source, which is generated on spontaneous parametric down‐conversion from a magnesium oxide doped periodically poled lithium niobate waveguide. Utilizing the dispersive Fourier transformation technique, the photon wavelength variation is monitored in case of conventional static temperature control, revealing a long‐term wavelength drift up to 556.8 pm over a 14‐h measurement period. A Hong‐Ou‐Mandel (HOM) interferometer is constructed to assess the impact on quantum applications, showing a decrease in visibility from 95.5% to 69.4%. To address this issue, a digital proportional‐integral‐differential algorithm is implemented to dynamically compensate the working temperature variation of the waveguide, thereby instantly stabilizing the wavelength to a peak‐to‐peak fluctuation of +138.05 pm/‐127.61 pm with the standard deviation being 30.49 pm. The wavelength stability shows more than a hundredfold enhancement in terms of Allan deviation, reaching at an averaging time of 10000 s. With the dynamic control in operation, the HOM interference visibility turns to stable at 96.1% ± 0.6%. The method provides a simple and accessible solution for precisely controlling and stabilizing the wavelength of entangled biphotons, thus improving performance in various quantum information processing applications.

Performance Assessment of the Small and Medium-Scale Coconut Weeder Cum Fertilizer Applicator Developed by Rajarata University of Sri Lanka

The enhancement of coconut yield significantly hinges on proper weeding and chemical fertilizer application. In Sri Lanka, several mechanical methods have been introduced for weeding and fertilizer application of coconut, but the traditional manual approach persists most popular, despite being time, labor cost intensive. Moreover, the introduced technologies were suited for large-scale coconut cultivation and could not cope with medium or small-scale. Furthermore, most of them are designed for a single application; weeding or fertilizing. Thus, the Faculty of Agriculture, Rajarata University of Sri Lanka (RUSL), developed a coconut weeder cum fertilizer applicator for medium and small-scale coconut cultivations. However, it has not been properly evaluated and recommended for farmers. Consequently, this study sought to evaluate the performance of the above machine by conducting a comparative performance evaluation with the conventional method. A healthy, well-maintained, proper-spacing coconut plantation was selected from the faculty research unit, and each weeding and fertilizer application method was replicated ten times. In terms of performance parameters: effective field capacity, field efficiency, and weeding efficiency in mechanical and manual methods were 0.172 ha h-1, 61.86%, 66.62%, and 0.048 ha h-1, 55.34%, 60.35%, respectively. Statistical analysis indicates the mechanical method had higher field capacity and efficiency than the manual method, while weeding efficiency was not significantly different (p≤0.05). In addition, the machine had a fertilizer spreading uniformity of around 99.98% when operating at an optimum speed of 1.45 km h-1. Fertilizer application rate and performance index as a weeder were 1.7 kg/min and 1145.86, respectively. Furthermore, the fuel consumption rate of the machine was 0.733 L h-1 and its break-even point was recorded as 2.85 ha yr-1. Consequently, the coconut weeder cum fertilizer applicator proves suitable for medium and small-scale coconut cultivations in Sri Lanka.

BTIP: Branch Triggered Instruction Prefetcher Ensuring Timeliness

In CPU microarchitecture, caches store frequently accessed instructions and data by exploiting their locality, reducing memory access latency and improving application performance. However, contemporary applications with large code footprints often experience frequent Icache misses, which significantly degrade performance. Although Fetch-Directed Instruction Prefetching (FDIP) has been widely adopted in commercial processors to reduce Icache misses, our analysis reveals that FDIP still suffers from Icache misses caused by branch mispredictions and late prefetch, leaving considerable opportunity for performance optimization. Priority-Directed Instruction Prefetching (PDIP) has been proposed to reduce Icache misses caused by branch mispredictions in FDIP. However, it neglects Icache misses due to late prefetch and suffers from high storage overhead. In this paper, we proposed a branch-triggered instruction prefetcher (BTIP), which aims to prefetch Icache lines that FDIP cannot efficiently handle, including the Icache misses due to branch misprediction and late prefetch. We also introduce a novel Branch Target Buffer (BTB) organization, BTIP BTB, which stores prefetch metadata and reuses information from existing BTB entries, effectively reducing storage overhead. We implemented BTIP on the Champsim simulator and evaluated BTIP in detail using traces from the 1st Instruction Prefetching Championship (IPC-1). Our evaluation shows that BTIP outperforms both FDIP and PDIP. Specifically, BTIP reduces Icache misses by 38.0% and improves performance by 5.1% compared to FDIP. Additionally, BTIP outperforms PDIP by 1.6% while using only 41.9% of the storage space required by PDIP.

Dynamic modelling and mechanical analysis of an inertial linear piezoelectric actuator with double stators

Abstract To achieve higher output performance in precision applications, and in order to gain deeper insight into operation principle, a dynamic model is established including the transmission relationship between the stators, the driving shaft, and the mover based on a slip-slip type inertial linear piezoelectric actuator with double stators. The influence of stator material and symmetry ratio of the excitation signal on the vibration characteristics of the stator and the output performance are investigated. This study reveals the relationship between these factors through a combination of simulations and experiments. Prototypes using several materials are machined and assembled, and the vibration characteristics and output performance are rigorously tested. The results obtained from the experimental measurements are consistent with the simulation results, confirming the validity and rationality of the dynamic model. The experimental results of the stator, as well as the actuator, are analyzed. It can be concluded that the actuator is able to output a larger effective displacement in one motion period with the increased symmetry ratio of the triangular wave signal, applied with a higher operating frequency, resulting in a higher output velocity of 42 mm/s and a larger load of 300 g with the steel stator, and a higher displacement resolution of 18 nm can be achieved using the AL alloy stator. This research not only provides an effective method for enhancing and selecting the desired output performance for the researched actuator but also can be extended to other slip-slip type inertial linear piezoelectric actuators.

A novel red-emitting InScW3O12:Eu3+ phosphor with anti-thermal-quenching performance for high-power WLED applications

A series of red-emitting InScW3O12:Eu3+ (ISWO:Eu3+) phosphors with anti-thermal-quenching performance were successfully synthesized by conventional solid-state reaction. The phase structure and luminescent properties of ISWO:Eu3+ were systematically studied. The photoluminescence excitation (PLE) spectrum showed that ISWO:Eu3+ phosphor can be effectively matched with commercial ultraviolet (UV), violet and blue light chips. The main emission peak of the phosphor was located at 613 nm, which was attributed to the electric dipole transition 5D0 → 7F2. Under the optimal excitation, the prepared ISWO:0.08Eu3+ phosphor showed excellent anti-thermal-quenching performance, its photoluminescence (PL) intensity at 180 °C reached 157.4 % of initial intensity at room temperature. At 465 nm excitation, it also exhibited the anti-thermal-quenching property and the PL intensity remained 115.1 % at 150 °C of that at room temperature. In situ XRD analysis revealed that the lattice contraction resulting in an increase in structural rigidity as the temperature rising, which caused the change of Eu3+ local environment and improved the PL intensity. Finally, a series of warm white LED devices under varying power density conditions with stable output were prepared using the red ISWO:0.08Eu3+ phosphor, indicating that the ISWO:Eu3+ phosphor with excellent anti-thermal-quenching performance has potential application prospects in high-power white light-emitting diodes (WLEDs).

Constructing stable solid electrolyte interphases to enhance the calendar life of anode-free lithium metal batteries

Advancement of anode-free lithium metal batteries (AFLMBs) has been appreciated due to their exceptional volumetric energy density and manufacturing simplicity. However, AFLMBs suffer from poor cycle performance due to the absence of excess lithium and current research lacks an understanding of lithium corrosion and calendar aging in AFLMBs. Here, we investigate the practical effects of chemical and galvanic corrosion on battery performance (calendar life) through a modified full-cell cycling experiment. The impact of galvanic corrosion is negligible, whereas chemical corrosion during a rest period reduces the capacity retention (CR) from 47% to 32% over 100 cycles. Consequently, a corrosion control strategy is implemented, substituting 1,2-dimethoxyethane with 1,2-dimethoxypropane (DMP), which has weaker lithium ion solvation properties due to its inductive effect. This approach results in the formation of a Li2O-rich solid-electrolyte interphase (SEI) layer, which effectively prevents direct contact of lithium with the electrolyte and the formation of additional SEI layers. Consequently, the decrease in CR due to chemical corrosion is considerably mitigated in DMP-based electrolyte, with only a slight decrease from 51% to 49%. This study provides insights into lithium corrosion in practical AFLMBs and offers guidelines for designing less-corrosive electrolytes to improve AFLMB performance for diverse industrial applications as energy-storage devices.

Utilizing association rule mining for enhancing sales performance in web-based dashboard application

Utilizing association rule mining for enhancing sales performance in web-based dashboard application

Enhancement of luminescence and thermal stability in Eu3+-doped K3Y(BO2)6 with Li+ and Na+ co-doping

Eu3+-doped and Li+/Na+ co-doped K3Y(BO2)6 (KYBO) phosphors were synthesized through a microwave-assisted sol–gel method, and their structural and photoluminescent (PL) characteristics were examined. X-ray diffraction (XRD) and Rietveld refinement confirm effective dopant incorporation and preservation of the crystalline structure. Fourier Transform Infrared (FTIR) spectroscopy indicates the maintenance of the borate structure, confirming the structural integrity of the phosphors upon doping. The addition of Li+ and Na+ co-dopants notably enhances luminescent efficiency and thermal stability, making these phosphors promising candidates for solid-state lighting (SSL) applications. PL analysis reveals strong red emission peaks at 612 nm, attributed to the 5Do → 7F2 transition of Eu3+ ions. The study indicates that electric dipole-quadrupole interactions are the primary mechanism for energy migration, with a critical distance of approximately 22.68 Å. This mechanism contributes to concentration quenching at higher doping levels. High temperature PL measurements indicated an activation energy of 0.1389 eV for thermal quenching in the Li+ co-doped sample. Additionally, the Na+ co-doped sample exhibited an abnormal thermal stability behavior, with an even higher activation energy of 0.2536 eV. This suggests that Na+ co-doping significantly enhances the thermal resilience of the phosphor, making it more suitable for high-power light-emitting applications that operate under extreme conditions. CIE chromaticity diagrams highlight the potential for optimizing Eu3+ doping levels, combined with Li+ and Na+ co-doping, to improve luminescent performance and thermal stability for advanced SSL applications.

Cr3+-doped Na2CaSn2Ge3O12 garnet showing broadband near-infrared emission at 820 nm with zero thermal quenching and near-unity quantum yield

The continually advancing near-infrared (NIR) phosphor-converted light-emitting diode (pc-LED) hold pivotal significance in optical imaging and NIR spectroscopy. Cr3+-doped garnet broadband NIR phosphors have attracted considerable attention owing to their high optical performance enabled by the rigid structure. Nonetheless, the emission wavelength is severely restricted, and longer wavelength emissions usually result in inferior quantum efficiency and poor luminescence stability. In this work, the concurrent reconstruction of dodecahedral and octahedral sites by introducing [Na+-Sn4+]C unit in the framework of Na2CaSn2Ge3O12 garnet contributes to the Cr3+ broadband NIR emission spanning 700–1200 nm, with a peak at 820 nm. Utilizing a charge compensation strategy via Ta5+ codoping largely boosts the internal quantum efficiency (IQE) of Na2CaSn2Ge3O12:Cr3+ from 93.06 % up to 95.04 %. Trap-mediated energy compensation is proposed to achieve a record-breaking zero-thermal-quenching behavior (99.39 %@423 K) of Cr3+-doped garnet with such a longer wavelength emission. The encapsulated prototype broadband NIR pc–LED gives rise to an overwhelming NIR output power of 590.9 mW@1300 mA and a photoconversion efficiency (PCE) of 32.62 % at 30 mA, rendering exceptional performance in night vision, detection, and NIR imaging applications.

Advances and challenges in UAV navigation based on visual SLAM

Abstract. In recent years, unmanned aerial vehicles (UAVs) have seen extensive use in fields such as agriculture, search and rescue, commercial, and military operations, driving the demand for autonomous navigation capabilities. Though GPS is the traditional method used for navigation, it becomes problematic in harsh environments like deserts. The Visual Simultaneous Localization and Mapping technology offers a solution to enhance UAV navigation in complex environments by constructing maps and localizing the UAV simultaneously in real time. This paper presents state-of-the-art visual SLAM technology developed for UAV navigation regarding algorithms like Oriented FAST and Rotated BRIEF SLAM (ORB-SLAM) and Large-Scale Direct Monocular SLAM (LSD-SLAM), whereby their performance is also discussed, with its positives and negatives. In this regard, the latest progress and challenges in applications are reviewed and analyzed through relevant literature from the databases of PubMed, IEEE, and Google Scholar in the past five years. The novelty of this paper lies in the comprehensive evaluation of the application performance of different visual SLAM algorithms in UAV navigation and the proposal of future research directions.

ACMamba: A State Space Model-Based Approach for Multi-Weather Degraded Image Restoration

In computer vision, eliminating the effects of adverse weather conditions such as rain, snow, and fog on images is a key research challenge. Existing studies primarily focus on image restoration for single weather types, while methods addressing image restoration under multiple combined weather conditions remain relatively scarce. Furthermore, current mainstream restoration networks, mostly based on Transformer and CNN architectures, struggle to achieve an effective balance between global receptive field and computational efficiency, limiting their performance in practical applications. This study proposes ACMamba, an end-to-end lightweight network based on selective state space models, aimed at achieving image restoration under multiple weather conditions using a unified set of parameters. Specifically, we design a novel Visual State Space Module (VSSM) and a Spatially Aware Feed-Forward Network (SAFN), which organically combine the local feature extraction capabilities of convolutions with the long-range dependency modeling capabilities of selective state space models (SSMs). This combination significantly improves computational efficiency while maintaining a global receptive field, enabling effective application of the Mamba architecture to multi-weather image restoration tasks. Comprehensive experiments demonstrate that our proposed approach significantly outperforms existing methods for both specific and multi-weather tasks across multiple benchmark datasets, showcasing its efficient long-range modeling potential in multi-weather image restoration tasks.

Comparative Review of the Microstructural and Mechanical Properties of Ti-6Al-4V Fabricated via Wrought and Powder Metallurgy Processes

This review examines the microstructural and mechanical properties of a Ti-6Al-4V alloy produced by wrought processing and powder metallurgy (PM), specifically laser powder bed fusion (LPBF) and hot isostatic pressing. Wrought methods, such as forging and rolling, create equiaxed alpha (α) and beta (β) grain structures with balanced properties, which are ideal for fatigue resistance. In contrast, PM methods, particularly LPBF, often yield a martensitic α′ structure with high microhardness, enabling complex geometries but requiring post-processing to improve its properties and reduce stress. The study evaluated the effects of processing parameters on grain size, phase distribution, and material characteristics, guiding the choice of fabrication techniques for optimizing Ti-6Al-4V performance in aerospace, biomedical, and automotive applications. The analysis emphasizes tailored processing to meet advanced engineering demands.

Double-pulse laser peening as a surface enhancement technology

In this paper, we discuss double-pulse laser peening (DPLP) as surface enhancement technology. Although single-pulse laser peening (SPLP) has yielded excellent results across various applications, its processing performance and efficiency are limited. The DPLP technique involves two laser pulses with a controlled irradiation interval and intensity, enhancing laser absorption through the plasma plume and generating high-amplitude laser-induced shock waves. This study involved conducting DPLP experiments on stainless steel, comparing the outcomes with those of conventional SPLP to assess DPLP’s functionality. After the initial prepulse irradiation, the subsequent main pulse was timed and irradiated onto the stainless steel. We evaluated the surface hardness to ascertain the impact of laser peening. The findings indicated that the surface hardness achieved with DPLP was up to 64% greater than that with SPLP. Additionally, the surface hardness achieved through DPLP depended on the delay time between the pulses and the intensity of the initial prepulse. These findings suggest that DPLP can significantly enhance surface hardness, providing a potential pathway for improving material performance in various industrial applications. Furthermore, simulation experiments of DPLP were performed using a one-dimensional simulation code that calculates the laser-matter interaction during the peening process. The pressure profiles generated by the simulation closely matched the experimentally derived hardness profiles, confirming the simulation’s ability to predict the mechanical effects induced by DPLP on the target sample and assist in further optimization of the DPLP process.

Pore Engineering in Biomass-Derived Carbon Materials for Enhanced Energy, Catalysis, and Environmental Applications

Biomass-derived carbon materials (BDCs) are highly regarded for their renewability, environmental friendliness, and broad potential for application. A significant advantage of these materials lies in the high degree of customization of their physical and chemical properties, especially in terms of pore structure. Pore engineering is a key strategy to enhance the performance of BDCs in critical areas, such as energy storage, catalysis, and environmental remediation. This review focuses on pore engineering, exploring the definition, classification, and adjustment techniques of pore structures, as well as how these factors affect the application performance of BDCs in energy, catalysis, and environmental remediation. Our aim is to provide a solid theoretical foundation and practical guidance for the pore engineering of BDCs to facilitate the rapid transition of these materials from the laboratory to industrial applications.

Preparation, optimization, and modification of urea‐formaldehyde resin for used as a plugging agent in fractured and caved oil and gas reservoirs

AbstractBased on the requirements of resin‐based plugging agents on initial viscosity, gel time and cost, the urea‐formaldehyde resin Poly‐UF was synthesized via aqueous solution polymerization. Subsequently, the Poly‐UF was further modified by using melamine, polyvinyl alcohol (PVA), and oxidized starch to enhance its application performances, which were marked by Poly‐UF‐M, Poly‐UF‐PVA and Poly‐UF‐OS, respectively. Simultaneously, the relationship between the preparation process, structural, and performance characteristics of the different resin types was investigated using a single‐factor experimental approach, specifically, the solid content, viscosity, and free formaldehyde content were evaluated to gauge its application performance. In this study, the chemical structure, thermal stability and microscopic morphology of Poly‐UF‐M, Poly‐UF‐PVA and Poly‐UF‐OS were studied by using FTIR, TG‐DTG and SEM. As a result, it was confirmed that the Poly‐UF was successfully modified, and the thermal stability was obviously improved, and the microstructure was further enhanced by melamine, PVA and oxidized starch. The outcomes revealed a notable reduction in free formaldehyde content and a significant increase in solid content for Poly‐UF‐M, Poly‐UF‐PVA, and Poly‐UF‐OS, specifically, the free formaldehyde content decreased by 47.15%, 36.59%, and 32.52%, respectively, while the solid content increased by 3.47%, 1.62%, and 1.39%, respectively. Moreover, the acid and alkali solubility, mechanical strength of cured Poly‐UF‐M, Poly‐UF‐PVA and Poly‐UF‐OS were improved attribute to excellent membrane‐forming performance. The innovation of this study is that the systematic investigation and optimization of urea‐formaldehyde resin are presented, providing technical insights on its utilization as a plugging agent in fractured and caved oil and gas reservoirs.

General Approach to Hydrolysis Resistive Aluminum Nitride and Its High-Performance Thermal Interface Materials.

Aluminum nitride (AlN), noted for its excellent thermal conductivity and exceptional electrical insulation, presents a promising alternative to traditional ceramic particles in thermal interface materials (TIMs). However, its broader adoption in practical applications is limited by performance degradation due to the vulnerability of its crystal structure to ubiquitous moisture. This study introduces a dual solution, utilizing a mechanochemical method to design a dense outer layer of Galinstan liquid metal (LM) that simultaneously enhances AlN's resistance to hydrolysis and improves its thermal performance in TIM applications. The high surface free energy of the LM layer imparts hydrophobic properties to the AlN surface and, combined with outer metal oxides, forms a dual-layer protective barrier that prevents water penetration, significantly enhancing the TIM's long-term stability in high-humidity conditions. Additionally, the LM layer at the interface improves the thixotropic properties of the TIM and enhances interfacial heat transport through the bridging effect of the LM, resulting in improved rheological mobility and thermal conductivity of the composite material. This win-win surface modification strategy opens opportunities for the practical and durable application of AlN in widespread electronic thermal management.

Ytopt: Autotuning Scientific Applications for Energy Efficiency at Large Scales

ABSTRACTAs we enter the exascale computing era, efficiently utilizing power and optimizing the performance of scientific applications under power and energy constraints has become critical and challenging. We propose a low‐overhead autotuning framework to autotune performance and energy for various hybrid MPI/OpenMP scientific applications at large scales and to explore the tradeoffs between application runtime and power/energy for energy efficient application execution, then use this framework to autotune four ECP proxy applications—XSBench, AMG, SWFFT, and SW4lite. Our approach uses Bayesian optimization with a Random Forest surrogate model to effectively search parameter spaces with up to 6 million different configurations on two large‐scale HPC production systems, Theta at Argonne National Laboratory and Summit at Oak Ridge National Laboratory. The experimental results show that our autotuning framework at large scales has low overhead and achieves good scalability. Using the proposed autotuning framework to identify the best configurations, we achieve up to 91.59% performance improvement, up to 21.2% energy savings, and up to 37.84% EDP (energy delay product) improvement on up to 4096 nodes.

Preparation of Tectona grandis Leaves derived Activated Carbon for High-Performance Supercapacitor Application

In energy-based applications, biomass porous micro/nanostructures activated carbon materials are the significant candidates, because of their high specific surface area, superior electrical conductivity, affordability and environmental friendliness. In this work, the activated carbon was prepared from Tectona grandis leaves as a biomass, and thus activated by 25% K2CO3 solution. The prepared carbon was designated as TGLAC. Second carbon was prepared from TGLAC was doped with urea and named as N-doped TGLAC. The physico-chemical analytical methods were employed to access the phase structure, bonding nature and morphological properties of the freshly prepared activated carbon material. Three electrode systems were utilized to estimate the supercapacitor features in 1 M Na2SO4 electrolyte. The prepared activated carbon electrode provides a specific capacitance of 371 F g–1 at 1 A g–1 and a 62% rate capability at 5 A g–1. It retains 94% of its initial capacitance during the cyclic stability analysis at 5 A g–1 over 5,000 cycles. This study demonstrates that carbon based materials obtained from sustainable waste biomass can exhibit favourable electrochemical performance in energy applications, providing a clear and feasible synthetic approach and strategy for their utilization.