Unleashing the Power of Dynamic Mode Decomposition and Deep Learning for Rainfall Prediction in North-East India

Accurate rainfall forecasting is crucial for effective disaster preparedness and mitigation in the North-East region of India, which is prone to extreme weather events such as floods and landslides. In this study, we investigated the use of two data-driven methods, Dynamic Mode Decomposition (DMD) and Long Short-Term Memory (LSTM), for rainfall forecasting using daily rainfall data collected from India Meteorological Department in northeast region over a period of 118 years. We conducted a comparative analysis of these methods to determine their relative effectiveness in predicting rainfall patterns. Using historical rainfall data from multiple weather stations, we trained and validated our models to forecast future rainfall patterns. Our results indicate that both DMD and LSTM are effective in forecasting rainfall, with LSTM outperforming DMD in terms of accuracy, revealing that LSTM has the ability to capture complex nonlinear relationships in the data, making it a powerful tool for rainfall forecasting. Our findings suggest that data-driven methods such as DMD and deep learning approaches like LSTM can significantly improve rainfall forecasting accuracy in the North-East region of India, helping to mitigate the impact of extreme weather events and enhance the region's resilience to climate change.Comment: Paper is under review at ICMC 202

A Few-Shot Approach to Dysarthric Speech Intelligibility Level Classification Using Transformers

Dysarthria is a speech disorder that hinders communication due to difficulties in articulating words. Detection of dysarthria is important for several reasons as it can be used to develop a treatment plan and help improve a person's quality of life and ability to communicate effectively. Much of the literature focused on improving ASR systems for dysarthric speech. The objective of the current work is to develop models that can accurately classify the presence of dysarthria and also give information about the intelligibility level using limited data by employing a few-shot approach using a transformer model. This work also aims to tackle the data leakage that is present in previous studies. Our whisper-large-v2 transformer model trained on a subset of the UASpeech dataset containing medium intelligibility level patients achieved an accuracy of 85%, precision of 0.92, recall of 0.8 F1-score of 0.85, and specificity of 0.91. Experimental results also demonstrate that the model trained using the 'words' dataset performed better compared to the model trained on the 'letters' and 'digits' dataset. Moreover, the multiclass model achieved an accuracy of 67%.Comment: Paper has been presented at ICCCNT 2023 and the final version will be published in IEEE Digital Library Xplor

Enhancing Knee Osteoarthritis severity level classification using diffusion augmented images

This research paper explores the classification of knee osteoarthritis (OA) severity levels using advanced computer vision models and augmentation techniques. The study investigates the effectiveness of data preprocessing, including Contrast-Limited Adaptive Histogram Equalization (CLAHE), and data augmentation using diffusion models. Three experiments were conducted: training models on the original dataset, training models on the preprocessed dataset, and training models on the augmented dataset. The results show that data preprocessing and augmentation significantly improve the accuracy of the models. The EfficientNetB3 model achieved the highest accuracy of 84\% on the augmented dataset. Additionally, attention visualization techniques, such as Grad-CAM, are utilized to provide detailed attention maps, enhancing the understanding and trustworthiness of the models. These findings highlight the potential of combining advanced models with augmented data and attention visualization for accurate knee OA severity classification.Comment: Paper has been accepted to be presented at ICACECS 2023 and the final version will be published by Atlantis Highlights in Computer Science (AHCS) , Atlantis Press(part of Springer Nature

Chemical Design Rules for Non-Fullerene Acceptors in Organic Solar Cells

Efficiencies of organic solar cells have practically doubled since the development of non-fullerene acceptors (NFAs). However, generic chemical design rules for donor-NFA combinations are still needed. Such rules are proposed by analyzing inhomogeneous electrostatic fields at the donor-acceptor interface. It is shown that an acceptor-donor-acceptor molecular architecture, and molecular alignment parallel to the interface, results in energy level bending that destabilizes the charge transfer state, thus promoting its dissociation into free charges. By analyzing a series of PCE10:NFA solar cells, with NFAs including Y6, IEICO, and ITIC, as well as their halogenated derivatives, it is suggested that the molecular quadrupole moment of ca 75 Debye A balances the losses in the open circuit voltage and gains in charge generation efficiency

Remarkable conductivity enhancement in P-doped polythiophenes via rational engineering of polymer-dopant interactions

Molecular doping is an effective approach to tune the charge density and optimize electrical performance of conjugated polymers. However, the introduction of dopants, on the other hand, may disturb the polymer microstructure and disrupt the charge transport path, often leading to a decrease of charge carrier mobility and deterioration of electrical conductivity of the doped films. Here we show that dopant-induced disorder can be overcome by rational engineering of polymer-dopant interactions, resulting in remarkable enhancement of electrical conductivity. Benchmark poly(3-hexylthiophene) (P3HT) and its analogous random polymers of 3-hexylthiophene and thiophene P[(3HT)1-x-stat-(T)x] were synthesized and doped by 2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane (F4TCNQ). Remarkably, random P[(3HT)1-x-stat-(T)x] was doped to a far superior electrical conductivity, that in the case of x ≥ 0.24, the conductivity of P[(3HT)1-x-stat-(T)x] is over 100 times higher than that of the doped P3HT, despite both P3HT and P[(3HT)1-x-stat-(T)x] exhibit comparable charge carrier mobility in their pristine state and in spite of their practically identical redox properties. This result can be traced back to the formation of π-stacked polymer-dopant-polymer co-crystals exhibiting extremely short packing distances of 3.13–3.15 \uc5. The mechanism behind these performances is based on a new role played by the dopant molecules that we name “bridging-gluing”. The results are coherently verified by the combination of optical absorption spectroscopy, X-ray diffraction, density functional theory calculations, and molecular dynamics simulations

Synthesis and characterization of spark plasma sintered FeAl and in situ FeAl–Al₂O₃ composite

In the present work, nanocrystalline FeAl and FeAl–Al2O3 composite were synthesized by high energy ball milling and subsequent compaction by spark plasma sintering. Microstructural changes during all stages of processing are studied using X-ray analysis. After 20 h of milling, the disordered FeAl and some amount of Fe rich solid solution was obtained in both of these compositions. Subsequent heat treatment results in formation of ordered FeAl. However, disordering of FeAl was observed in both compositions after spark plasma sintering. Nanocrystallinity is retained in both the compositions even after sintering at high temperature of 1,000°C. Very high hardness of ∼575 HV1 and ∼600 HV1 was exhibited by FeAl and FeAl–Al2O3 composite

Lip Positional Changes Associated With Upper Incisor AP Correction

Objectives. Determination of any predictable relationship (ratio) of these changes in Caucasian patients was the Objective of this study. Methods. Pre- and post-orthodontic lateral cephalograms from de-identified records of 37 (18 male, 19 female) Caucasian private orthodontic practice “non-extraction” patients (mean age = 14 yrs, 5mos) who originally presented CL I minimal crowding or slight CL II malocclusions were traced, analyzed and compared. UL and LL positions were determined by linear measures from E line. Upper incisor (U1) incisal edge position was measured linearly perpendicularly from NP plane and from E plane. Results. Statistical analysis showed that with a mean retraction of UI-E of 3.30mm, the UL-E retracted by a mean of 1.7mm and LL-E 1.65mm (p \u3c 0.001). For every one mm retraction of U1-NP, UL-E reduced 0.68mm and LL-E 0.65mm (p \u3c 0.05). Conclusion. From this study one can conclude that in Caucasian patients of this age group, one mm upper incisor retraction will result in approximately 1/2mm reduction in lip procumbency; a ratio of 2:1

Effect of Quencher, Geometry, and Light Outcoupling on the Determination of Exciton Diffusion Length in Nonfullerene Acceptors

The correct determination of the exciton diffusion length (LD) in novel organic photovoltaics (OPV) materials is an important, albeit challenging, task required to understand these systems. Herein, a high-throughput approach to probe LD in nonfullerene acceptors (NFAs) is reported, that builds upon the conventional photoluminescence (PL) surface quenching method using NFA layers with a graded thickness variation in combination with spectroscopic PL mapping. The method is explored for two archetypal NFAs, namely, ITIC and IT-4F, using PEDOT:PSS and the donor polymer PM6 as two distinct and practically relevant quencher materials. Interestingly, conventional analysis of quenching efficiency as a function of acceptor layer thickness results in a threefold difference in LD values depending on the specific quencher. This discrepancy can be reconciled by accounting for the differences in light in- and outcoupling efficiency for different multilayer architectures. In particular, it is shown that the analysis of glass/acceptor/PM6 structures results in a major overestimation of LD, whereas glass/acceptor/PEDOT:PSS structures give no significant contribution to outcoupling, yielding LD values of 6−12 and 8−18 nm for ITIC and IT-4F, respectively. Hence, practical guidelines for quencher choice, sample geometries, and analysis approach for the accurate assessment of LD are provided.V.B., A.P., and J.G. contributed equally to this work. The authors acknowledge that this research was financially supported by the European Research Council (ERC) under grant agreement no. 648901. The authors also acknowledge financial support from the Spanish Ministry of Science and Innovation through the Severo Ochoa Program for Centers of Excellence in R&D (CEX2019-000917-S) and project PGC2018-095411-B-I00. This publication was based upon work supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under award no: OSR-2018-CARF/CCF-3079 and award no. OSR-CRG2018-3746. The authors thank Anastasia Ragulskaya (The University of Tübingen) for contributing to the development of the computational model.Peer reviewe

Efficient Hybrid Amorphous Silicon Organic Tandem Solar Cells Enabled by Near Infrared Absorbing Nonfullerene Acceptors

Monolithically stacked tandem solar cells present opportunities to absorb more of the sun s radiation while reducing the degree of energetic loss through thermalization. In these applications, the bandgap of the tandem s constituent subcells must be carefully adjusted so as to avoid competition for photons. Organic photovoltaics based on nonfullerene acceptors NFAs have recently exploded in popularity owing to the ease with which their electrical and optical properties can be tuned through chemistry. Here, highly complementary and efficient 2 terminal tandem solar cells are reported based on a wide bandgap amorphous silicon absorber, and a narrow bandgap NFA bulk heterojunction with power conversion efficiencies PCEs exceeding 15 . Interface engineering of this tandem device allows for high PCEs across a wide range of light intensities both above and below 1 sun. Furthermore, the addition of an inorganic silicon subcell enhances the operational stability of the tandem by reducing the light stress experienced by the bulk heterojunction, resolving a long standing stumbling block in organic photovoltaic researc