Pan Model Research Articles

Research for implementation of PANS model based on open source code

Research for implementation of PANS model based on open source code

Pulmonary Fissure Segmentation in CT Images Using Image Filtering and Machine Learning.

Both lung lobe segmentation and lung fissure segmentation are useful in the clinical diagnosis and evaluation of lung disease. It is often of clinical interest to quantify each lobe separately because many diseases are associated with specific lobes. Fissure segmentation is important for a significant proportion of lung lobe segmentation methods, as well as for assessing fissure completeness, since there is an increasing requirement for the quantification of fissure integrity. We propose a method for the fully automatic segmentation of pulmonary fissures on lung computed tomography (CT) based on U-Net and PAN models using a Derivative of Stick (DoS) filter for data preprocessing. Model ensembling is also used to improve prediction accuracy. Our method achieved an F1 score of 0.916 for right-lung fissures and 0.933 for left-lung fissures, which are significantly higher than the standalone DoS results (0.724 and 0.666, respectively). We also performed lung lobe segmentation using fissure segmentation. The lobe segmentation algorithm shows results close to those of state-of-the-art methods, with an average Dice score of 0.989. The proposed method segments pulmonary fissures efficiently and have low memory requirements, which makes it suitable for further research in this field involving rapid experimentation.

Numerical Optimization of Variable Blank Holder Force Trajectories in Stamping Process for Multi-Defect Reduction.

An intelligent optimization technology was proposed to mitigate prevalent multi-defects, particularly failure, wrinkling, and springback in sheet metal forming. This method combined deep neural networks (DNNs), genetic algorithms (GAs), and Monte Carlo simulation (MCS), collectively as DNN-GA-MCS. Our primary aim was to determine intricate process parameters while elucidating the intricate relationship between processing methodologies and material properties. To achieve this goal, variable blank holder force (VBHF) trajectories were implemented into five sub-stroke steps, facilitating adjustments to the blank holder force via numerical simulations with an oil pan model. The Forming Limit Diagram (FLD) predicted by machine learning algorithms based on the Generalized Incremental Stress State Dependent Damage (GISSMO) model provided a robust framework for evaluating sheet failure dynamics during the stamping process. Numerical results confirmed significant improvements in formed quality: compared with the average value of training sets, the improvements of 18.89%, 13.59%, and 14.26% are achieved in failure, wrinkling, and springback; in the purposed two-segmented mode VBHF case application, the average value of three defects is improved by 12.62%, and the total summation of VBHF is reduced by 14.07%. Statistical methodologies grounded in material flow analysis were applied, accompanied by the proposal of distinctive optimization strategies for the die structure aimed at enhancing material flow efficiency. In conclusion, our advanced methodology exhibits considerable potential to improve sheet metal forming processes, highlighting its significant effect on defect reduction.

Analysis of turbulent cavitation effects on water-lubricated bearing in single screw compressors

PurposeTo guide the stable radius clearance choice of water-lubricated bearings for single screw compressors, this paper aims to analyze the effects of turbulence and cavitation on bearing performance under two conditions of specified external load and radius clearance.Design/methodology/approachA modified Reynolds equation considering turbulence and cavitation is adopted, based on the Jakobsson–Floberg–Olsson boundary condition, Ng–Pan model and turbulent factors. The equation is solved using the finite difference method and successive over-relaxation method to investigate the bearing performance.FindingsThe turbulent effect can increase the hydrodynamic pressure and cavitation. In addition, the turbulent effect can lead to an increase in the equilibrium radius clearance. The turbulent region exhibits a higher load capacity and cavitation rate. However, the increased cavitation negatively impacts the frictional coefficient and end flow rate. The impact of turbulence increases as the radius clearance decreases. As the rotating speed increases, the turbulence effect has a greater impact on the bearing characteristics.Originality/valueThe research can provide theoretical support for the design of water-lubricated journal bearings used in high-speed water-lubricated single screw compressors.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2024-0029/

Investigation on cavitating turbulent flow for the twisted NACA66 hydrofoil using a PANS model with helicity modification

Investigation on cavitating turbulent flow for the twisted NACA66 hydrofoil using a PANS model with helicity modification

Research on power equipment troubleshooting based on improved AlexNet neural network

Power equipment is an important component of the whole power system, so that it is obvious that it is required to develop a correct method for accurate analysis of the infrared image features of the equipment in the field of detection and recognition. This study proposes a troubleshooting strategy for the power equipment based on the improved AlexNet neural network. Multi-scale images based on the Pan model are used to determine the equipment features, and to determine the shortcomings of AlexNet neural network, such as slower recognition speed and easy overfitting. After knowing these shortcomings, it would become possible to improve the specific recognition model performance by adding a pooling layer, modifying the activation function, replacing the LRN with BN layer, and optimizing the parameters of the improved WOA algorithm, and other measures. In the simulation experiments, this paper's algorithm was compared with AlexNet, YOLO v3, and Faster R-CNN algorithms in the lightning arrester fault detection, circuit breaker fault detection, mutual transformer fault detection, and insulator fault detection improved by an average of 5.47 %, 4.69 %, and 3.42 %, which showed that the algorithm had a better recognition effect.

Framing Media Online Terhadap Puan Maharani Sebagai Bakal Calon Presiden Dalam Pemilihan Presiden 2024

Puan Maharani is often in the media spotlight and public perception of her is influenced by positive or negative online media coverage, depending on the political interests and public perception of her policies or actions. The purpose of this study is to analyze the influence of online media in shaping public perception of Puan Maharani, especially in the context of the 2024 presidential election. The research used a descriptive qualitative approach by applying the framing analysis model of Pan and Kosicki and data collection techniques from four online media (two national and two regional) during the period of November 1st to December 31st, 2022. The results of the analysis show a tendency of positive framing towards Puan Maharani. However, there are differences in the way positive narratives are built between two regional online media and national online media. Two regional online media tend to use exaggerated narratives such as hyperbole sentences in building positive narratives about Puan Maharani, while national online media are more varied in framing and minimize excessive rhetoric in building narratives about Puan Maharani. Despite the political interests of online media in creating news, national online media appears to be more objective in providing information about Puan Maharani. Online media has a significant influence in shaping public perception of Puan Maharani, especially in the politics of the 2024 presidential election. Positive framing may provide advantages, while framing that is diverse and minimizes excessive rhetoric tends to be more objective.

Konstruksi Invasi Rusia Ukraina dalam Pemberitaan Media Nasional: Analisis Framing Media Online JawaPos.com dan Tribun Pekanbaru.com Edisi Februari-Maret 2022

The media is a means of mediation that has an important role in influencing many people, therefore media bias can occur. Indeed, the media is in between social reality with all its conflicts, interests, and diverse facts. The existence of bias in the media cannot be separated from its ideology. Framing analysis is a text analysis method used to dissect the ways or ideology of the media when constructing a fact. This research aims to analyze the framing that occurs on two news portals, namely Jawa Pos and Tribun Pekanbaru, towards the invasion case that occurred between Russia and Ukraine. Both media have different biases by showing the delivery of vocabulary, quotes, and sentences that can be constructed with different facts. This descriptive qualitative research uses the framing analysis model of Zhongdan Pan and Gerald M. Kosicki. The differences in the news raised by Jawa Pos and Tribun Pekanbaru are visible in the sources, quotes, and sentences used so as to produce different constructions. Jawa Pos has its own characteristics in informing news related to the heating up of Russian and Ukrainian news, whereas Jawa Pos seems to display the strengths and support of the Ukrainian state. In contrast to Jawa Pos, Tribun Pekanbaru displays information related to the strength and defense possessed by Russia.
 Keywords: Media, Framing, Ideology, Invasion.

Evaporation rate for covered and uncovered condition case study: UiTM Shah Alam

High development, urbanization, and industrial activity in urban areas contribute to greenhouse gases emission that increases ambient temperatures. These phenomena influence the hydrological cycle as it speeds up the rate of evaporation in water storage. Sufficient water resource is essential as it helps to grow social and economic activities in a country. The study developed three aluminium evaporation pan models with 225 mm diameter and 80 mm width to measure the evaporation in UiTM Shah Alam. Each pan was covered using ping pong balls as a floating cover with a different percentage of coverage. The percentage of coverage used in the pan models is 0% uncovered, 46.08% covered, and 92.16% covered condition. The observation lasted 12 hours, from 8.00 am to 8.00 pm. The 0% uncovered condition had the highest evaporation with 6 mm, followed by the 46.08% covered and 92.16% covered conditions with 3 mm and 2 mm, respectively. Next, the influence of temperature on the evaporation rate in the three conditions was also analysed. The provided floating cover reduces the effect of temperature on the rate of evaporation in urban area.

Proximal Alternating-Direction-Method-of-Multipliers-Incorporated Nonnegative Latent Factor Analysis

High-dimensional and incomplete (HDI) data subject to the nonnegativity constraints are commonly encountered in a big data-related application concerning the interactions among numerous nodes. A nonnegative latent factor analysis (NLFA) model can perform representation learning to HDI data efficiently. However, existing NLFA models suffer from either slow convergence rate or representation accuracy loss. To address this issue, this paper proposes a proximal alternating-direction-method-of-multipliers-based nonnegative latent factor analysis (PAN) model with two-fold ideas: 1) adopting the principle of alternating-direction-method-of-multipliers to implement an efficient learning scheme for fast convergence and high computational efficiency; and 2) incorporating the proximal regularization into the learning scheme to suppress the optimization fluctuation for high representation learning accuracy to HDI data. Theoretical studies verify that PAN converges to a Karush-Kuhn-Tucker (KKT) stationary point of its nonnegativity-constrained learning objective with its learning scheme. Experimental results on eight HDI matrices from real applications demonstrate that the proposed PAN model outperforms several state-of-the-art models in both estimation accuracy for missing data of an HDI matrix and computational efficiency.

A Novel Three-Dimensional Fractal Model for the Normal Contact Stiffness of Mechanical Interface Based on Axisymmetric Cosinusoidal Asperity

A novel three-dimensional fractal model for normal contact stiffness is proposed in this paper. First of all, a hypothetical surface based on axisymmetric cosinusoidal asperity is established. Then, based on the hypothetical surface, the analytical expressions for the contact stiffness and contact load are derived by combining the three-dimensional fractal theory with the contact mechanics theory. In addition, the simulation results of the presented model and the Pan model are compared with the experimental results. The comparison results show that the maximum relative error of the Pan model is 29.58%, while the maximum relative error of the presented model is 4.35%. Ultimately, the influence of different fractal parameters on contact stiffness is discussed. Under the same contact load, the normal contact stiffness first increases and then decreases with the increase of the fractal dimension D, while the normal contact stiffness monotonically decreases with the increase of scale coefficient G. The results are explained from the perspective of the shape of the asperity. This study provides a novel model for the calculation of normal contact stiffness, which provides a model basis for the study of contact properties for the mechanical interface.

Structural modifications, optical response, and electrical conductivity mechanism of Bi2O3 doped in P2O5–V2O5–MoO3 nanocomposite glass systems

Structural, optical and electrical conductivity mechanism of four compositional series of xBi2O3-(1-x)(0.30P2O5–0.35V2O5–0.35MoO3) [x = 0.05, 0.15, 0.25, and 0.35] have been investigated. XRD pattern affirms the existence of nanocrystallites in the glassy network, which affects the structural, optical and electrical alterations. The structural variation leads to an increase in the density of all the glassy systems. The FTIR analysis reveals the shift of different band positions suggesting structural alterations. The electrical conductivity investigation reveals the decreasing values of ac and dc activation energy, which enhances the ac and dc conductivity. The validity of Mott's VRH model has been examined and the value of hopping energy has been estimated. The obtained DC conductivity spectra of all samples have been fitted with Greaves's model. The AC conductivity scaling model of Pan and Ghosh has been used to demonstrate the electrical conduction relaxation method. In the spectroscopic investigation, by deploying the Tauc's plot, the optical band gap energies of the studied glass compositions are estimated. The calculation of Urbach energy values allows us to estimate the disorders of glassy nanocomposites. Different spectroscopic parameters like refractive index, polarizability, reflection factor, and reflectivity have been studied.

Numerical modelling of a solar salt pan for improved salt production at Lake Katwe, Uganda

The solar salt pans at Lake Katwe are set up haphazardly without any scientific guidelines which compromises the annual throughput from the solar salt works. To improve on the design of the salt pans, the heat transfer dynamics of the salt pan have been numerically and experimentally studied in this study. A representative salt pan located at the shores of the lake Katwe with a surface area of 62 m2 and a depth of 0.2 m was used in this study. The numerical model was implemented in the OpenFOAM software where a 3D heat transfer salt pan model was studied using the Finite Volume Method under Lake Katwe climatic conditions. The model was governed by continuity, salt concentration, momentum, energy equations and the Boussinesq approximation. A field experiment that determined the temperature variation with depth was carried out. The correctness of the model results was verified against experimental data. The numerical simulation model revealed a salt pan brine temperature increase with time and the salt concentration significantly remained constant with time. The salt pan brine temperature increased from 303 K to 319.5 K after 5 h of the simulation time. The model and the experimental salt concentration and temperature profiles were found to be in a good agreement. The sensitivity analysis on the effect of the salt pan depth on brine temperature was studied. It was revealed that the shallower the salt pan, the higher the rate of heat gain. This study revealed that an optimum salt pan depth to yield a higher salt quantity under Lake Katwe climatic conditions was at 0.1 m.

A Comparative Study of Deep Neural Networks for Real-Time Semantic Segmentation during the Transurethral Resection of Bladder Tumors.

Bladder cancer is a common and often fatal disease. Papillary bladder tumors are well detectable using cystoscopic imaging, but small or flat lesions are frequently overlooked by urologists. However, detection accuracy can be improved if the images from the cystoscope are segmented in real time by a deep neural network (DNN). In this paper, we compare eight state-of-the-art DNNs for the semantic segmentation of white-light cystoscopy images: U-Net, UNet++, MA-Net, LinkNet, FPN, PAN, DeepLabv3, and DeepLabv3+. The evaluation includes per-image classification accuracy, per-pixel localization accuracy, prediction speed, and model size. Results show that the best F-score for bladder cancer (91%), the best segmentation map precision (92.91%), and the lowest size (7.93 MB) are also achieved by the PAN model, while the highest speed (6.73 ms) is obtained by DeepLabv3+. These results indicate better tumor localization accuracy than reported in previous studies. It can be concluded that deep neural networks may be extremely useful in the real-time diagnosis and therapy of bladder cancer, and among the eight investigated models, PAN shows the most promising results.

Influence of local grid refinement on prediction of impinging jet heat transfer using Scale-Resolving-Simulation methods

A fine near-wall resolution plays a crucial role in simulations of unsteady heat transfer from a wall. A generation of fine structured grids for a complex domain is cumbersome and requires an enormous number of grid points and a local grid refinement is a possible technique for a grid point reduction. The present study addresses numerical simulations of impinging jet heat transfer on locally refined computational grids using the Scale-Resolving-Simulation methods (DES, LES and PANS). The study is performed at a Reynolds number Re = 23000 and two nozzle-plate distances H/D = 2 and H/D = 6. DES and the PANS model with f k = 0.25 predicted results closest to experimental data. However, DES significantly over-predicted heat transfer at the location r / D = 1 − 2 in the small nozzle-plate distance case ( H / D = 2). The decrease of physical resolution in the PANS model resulted in the over-prediction of heat transfer close to the nozzle axis. In conclusion, the influence of the local refinement in the perpendicular direction was rather low compared to the longitudinal direction. Moreover, the local grid refinement improved results predicted by LES and DES in the small nozzle-plate distance case.

External validation of cone-beam computed tomography- and panoramic radiography-featured prediction models for inferior alveolar nerve injury after lower third molar removal: proposal of a risk calculator.

We previously developed basic and extended models to predict inferior alveolar nerve injuries (IANI) after lower third molar (LM3) removal based on cone-beam computed tomography (CBCT) images. Although these models comprised predictors, including increased age and inferior alveolar canal-related CBCT factors, external validations were lacking. Therefore, this study externally validated these models and compared them with other related models based on their performance. Original and newly validated samples included patients who underwent LM3 removal following CBCT. Subsequently, 39 and 25 patients with IANI, then 457 and 295 randomly selected patients without IANI were chosen of the observed 1573 and 1052 patients, respectively. CBCT- and panoramic radiograph (PAN)-featured models were validated. Then, models' discrimination and calibration abilities were assessed using C-statistics and calibration plots, respectively. Brier scores were also quantified, after which logistic recalibration was achieved to optimize calibration, and a risk calculator was developed. During the external validation, the extended model exhibited the best C-statistic (0.822) and Brier score (0.064), whereas two CBCT- and two PAN-featured models showed lower performances with C-statistics (0.764, 0.706, 0.584, and 0.627) and Brier scores (0.069, 0.074, 0.075, and 0.072). Besides, all models showed a tendency to overpredict its high-risk range. However, recalibration of the extended model resulted in excellent calibration performance. CBCT-featured models, especially the extended model, conclusively showed a superior predictive performance to PAN models. Therefore, the risk calculator on the extended CBCTmodel is proposed to be a clinical decision-aid tool that preoperatively predicts IANI risk.

Achmad Yurianto in the frame of online journalism pioneer in Indonesia

Since the President of the Republic of Indonesia, Joko Widodo, announced the first positive case of COVID-19 in Indonesia, the government officially created the COVID-19 Handling Task Force on March 4, 2020. The government has appointed Achmad Yurianto as the Spokesperson for the COVID-19 Handling Task Force. As a spokesperson, Achmad Yurianto conveyed the development of the status issue through the media. However, information ambiguity still arises, creating discretion and negative images of the government’s communication style. This research aims to describe how Kompas.com, Republika.co.id, and Detik.com, pioneers of online journalism in Indonesia, framed the news delivered by Achmad Yurianto. In this constructivist paradigm research, the researchers analyzed 28 news samples using the framing model of Pan and Kosicki, then related them to the theory of Social Reality Construction from Berger and Luckmann. At the syntactic structure, the researcher analyzes the facts on the news scheme in the form of headlines, leads, background information, quotes, sources, statements, closings. At the script level, the researcher analyzes the completeness of the news which includes elements of 5W+1H. Furthermore, at the thematic level, the elements of pre-paragraphs and news prepositions. Finally, the researcher looks at the emphasis on facts through grammar, idioms, pictures, graphics in the news. The results disclosed that Kompas.com, Republika.co.id, and Detik.com actively reports the development of information about COVID-19 in Indonesia, including framing the COVID-19 Task Force Handling Spokesperson, Achmad Yurianto. Kompas.com could direct public opinion to see Achmad Yurianto as an arrogant and authoritarian person. Conversely, Detik.com always framed him as a competent and proportionate person in conveying information.

Numerical simulation of the flow around a circular cylinder at Reynolds number Re = 3900 by means of the PANS model

The paper presents a study of various versions of PANS approach for turbulence simulation using a flow around a cylinder at Reynolds number Re = 3900 as an example. The considered models were implemented in the in-house CFD package. The influence of the method of determining the parameter f k on the flow behind the cylinder was studied. The first method assumed a constant value of f k. In the second method, the f k value depended on the local computational mesh scale and the shear scale.

The effects of femoral metaphyseal morphology on growth plate biomechanics in juvenile chimpanzees and humans.

The distal femoral metaphyseal surface presents dramatically different morphologies in juvenile extant hominoids-humans have relatively flat metaphyseal surfaces when compared with the more complex metaphyseal surfaces of apes. It has long been speculated that these different morphologies reflect different biomechanical demands placed on the growth plate during locomotor behaviour, with the more complex metaphyseal surfaces of apes acting to protect the growth plate during flexed-knee behaviours like squatting and climbing. To test this hypothesis, we built subject-specific parametric finite-element models from the surface scans of the femora of five Pan and six Homo juveniles. We then simulated the loading conditions of either a straight-leg or flexed-knee gait and measured the resulting stresses at the growth plate. When subjected to the simulated flexed-knee loading conditions, both the maximum and mean von Mises stresses were significantly lower in the Pan models than in the Homo models. Further, during these loading conditions, von Mises stresses were strongly negatively correlated with ariaDNE, a measure of complexity of the metaphyseal surface. These results indicate that metaphyseal surface morphology has a robust effect on growth plate mechanics.

Genome-scale insights into the metabolic versatility of Limosilactobacillus reuteri

BackgroundLimosilactobacillus reuteri (earlier known as Lactobacillus reuteri) is a well-studied lactic acid bacterium, with some specific strains used as probiotics, that exists in different hosts such as human, pig, goat, mouse and rat, with multiple body sites such as the gastrointestinal tract, breast milk and mouth. Numerous studies have confirmed the beneficial effects of orally administered specific L. reuteri strains, such as preventing bone loss and promoting regulatory immune system development. L. reuteri ATCC PTA 6475 is a widely used strain that has been applied in the market as a probiotic due to its positive effects on the human host. Its health benefits may be due, in part, to the production of beneficial metabolites. Considering the strain-specific effects and genetic diversity of L. reuteri strains, we were interested to study the metabolic versatility of these strains.ResultsIn this study, we aimed to systematically investigate the metabolic features and diversities of L. reuteri strains by using genome-scale metabolic models (GEMs). The GEM of L. reuteri ATCC PTA 6475 was reconstructed with a template-based method and curated manually. The final GEM iHL622 of L. reuteri ATCC PTA 6475 contains 894 reactions and 726 metabolites linked to 622 metabolic genes, which can be used to simulate growth and amino acids utilization. Furthermore, we built GEMs for the other 35 L. reuteri strains from three types of hosts. The comparison of the L. reuteri GEMs identified potential metabolic products linked to the adaptation to the host.ConclusionsThe GEM of L. reuteri ATCC PTA 6475 can be used to simulate metabolic capabilities and growth. The core and pan model of 35 L. reuteri strains shows metabolic capacity differences both between and within the host groups. The GEMs provide a reliable basis to investigate the metabolism of L. reuteri in detail and their potential benefits on the host.