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Optimizing sales strategy in the Indian automobile industry: Predicting future car prices using machine learning and demographic data

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AIP Conference Proceedings 2024年第1期3123卷

作者： M. Reyasudin Basir Khan Gazi Md. Nurul Islam Poh Kiat Ng Ahmad Anwar Zainuddin Chong Peng Lean Jabbar Al-Fattah Nazhatul Hafizah Kamarudin Tun Razak Graduate School Universiti Tun Abdul Razak (UNIRAZAK) Kuala Lumpur Malaysia Faculty of Engineering and Technology Multimedia University Jalan Ayer Keroh Lama Bukit Beruang Melaka Malaysia Department of Computer Science International Islamic University Malaysia (IIUM) Kuala Lumpur Malaysia Manipal International University Putra Nilai Negeri Sembilan Malaysia Faculty of Electrical and Electronic Engineering Tun Hussein Onn University of Malaysia Parit Raja Johor Malaysia Faculty of Information Science & Technology Universiti Kebangsaan Malaysia Bangi Selangor Malaysia

Demographics play a vital role in defining the size, distribution, and structure of a population. In the context of the automobile industry, business owners can leverage demographic insights to gauge the demand for vehicles and strategically align their sales efforts. Accurate sales forecasting is essential for long-term business strategy, providing manufacturers with a competitive advantage in optimizing production planning methods. This project utilizes large-scale automobile sales data to forecast car price variations in the coming months, considering factors such as purchase patterns, car models, and other relevant data. By analyzing different attributes from a past-year dataset, three machine learning algorithms: Linear Regression, Decision Tree Regression, and Random Forest Regression were employed to predict future car prices. The performance of each algorithm is evaluated using the R-squared value. Notably, the Random Forest regression model achieves a higher accuracy of 93%, outperforming both Decision Tree regression and Linear regression. These results demonstrate the suitability of Random Forest regression in predicting big data for the industry’s future product production plan and overall strategy.

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Multimodal deep learning framework for image popularity prediction on social media

arXiv

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arXiv 2021年

作者： Abousaleh, Fatma S. Cheng, Wen-Huang Yu, Neng-Hao Tsao, Yu Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Institute of Information Science Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan Department of Computer Science National Chengchi University Taipei11605 Taiwan The Institute of Electronics Department of Electronics Engineering National Chiao Tung University Hsinchu30010 Taiwan The College of Design Department of Design National Taiwan University of Science and Technology Taipei10607 Taiwan The Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan

Billions of photos are uploaded to the web daily through various types of social networks. Some of these images receive millions of views and become popular, whereas others remain completely unnoticed. This raises the problem of predicting image popularity on social media. The popularity of an image can be affected by several factors, such as visual content, aesthetic quality, user, post metadata, and time. Thus, considering all these factors is essential for accurately predicting image popularity. In addition, the efficiency of the predictive model also plays a crucial role. In this study, motivated by multimodal learning, which uses information from various modalities, and the current success of convolutional neural networks (CNNs) in various fields, we propose a deep learning model, called visual-social convolutional neural network (VSCNN), which predicts the popularity of a posted image by incorporating various types of visual and social features into a unified network model. VSCNN first learns to extract high-level representations from the input visual and social features by utilizing two individual CNNs. The outputs of these two networks are then fused into a joint network to estimate the popularity score in the output layer. We assess the performance of the proposed method by conducting extensive experiments on a dataset of approximately 432K images posted on Flickr. The simulation results demonstrate that the proposed VSCNN model significantly outperforms state-of-the-art models, with a relative improvement of greater than 2.33%, 7.59%, and 14.16% in terms of Spearman’s Rho, mean absolute error, and mean squared error, respectively. Copyright © 2021, The Authors. All rights reserved.

关键词： Social networking (online)

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Revolutionising engineering pedagogy: The role of 3D printing in modern engineering education

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PLET: programmed Learning & Educational Technology 2025年第2期62卷

作者： Muhammad Tajammal Munir Prashant K. Jamwal Bing Li Susan Carter Shahid Hussain a College of Engineering and Technology American University of the Middle East Egaila Kuwait b Department of Electrical and Computer Engineering School of Engineering and Digital Sciences Nazarbayev University Astana Kazakhstan c Water Research Center Shenzhen International Graduate School Tsinghua University Shenzhen China d School of Critical Studies in Higher Education The University of Auckland Auckland New Zealand e Human-Centred Technology Research Center Faculty of Science and Technology University of Canberra Canberra Australia

ABSTRACTThis paper presents a comprehensive study on the integration of 3D printing technology in biomedical robotics education with undergraduate students learning about the design of robotic systems. The research investigated the effectiveness of this new teaching strategy in enhancing students’ understanding of complex engineering principles by comparing their learning experiences, and academic performance with results from traditional teaching methods. The students’ learning and performance were evaluated through a survey and grade analysis. The Mann – Whitney U test was used to analyse the data, revealing statistically significant improvements in both student satisfaction and grades. The Mann-Whitney U test results show a clear preference for the 2017 3D printing and project-based learning strategy over the 2016 traditional method. With a U-value of 0 and a critical U-value atp< 0.05 being 23, coupled with a z-score of −3.742, the data significantly indicates enhanced student outcomes with the newer teaching approach compared to conventional methods. The study also found that 3D printing technology fostered creativity, critical thinking, and enhanced spatial visualisation skills among students. However, we also identify potential challenges, including equipment maintenance, safety concerns, and the need for faculty expertise. The study concludes by providing potential strategies to overcome these challenges. This research offers valuable insights for educators and policy-makers in leveraging technology for improved learning outcomes in engineering education.

关键词： 3D printing engineering education pedagogical theories curriculum integration

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Development of a Selective Wet-Chemical Etchant for 3D Structuring of Silicon via Nonlinear Laser Lithography

arXiv

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arXiv 2023年

作者： Borra, Mona Zolfaghari Radfar, Behrad Nasser, Hisham Çolakoğlu, Tahir Tokel, Onur Turnalı, Ahmet Demirtaş, Merve Ustunel, Hande Toffoli, Daniele Ömer İlday, F. Turan, Raşit Pavlov, Ihor Bek, Alpan ODTÜ-GÜNAM Middle East Technical University Ankara06800 Turkey Ankara06800 Turkey Department of Electronics and Nanoengineering Aalto University Tietotie 3 EspooFI-02150 Finland Department of Physics Engineering Ankara University Ankara06100 Turkey Department of Physics Bilkent University Ankara06800 Turkey UNAM National Nanotechnology Research Center Institute of Materials Science and Nanotechnology Bilkent University Ankara06800 Turkey Department of Electrical and Electronics Engineering Bilkent University Ankara06800 Turkey Department of Electrical and Computer Engineering Boston University 8 Saint Mary’s Street BostonMA02215 United States Ankara06800 Turkey Network Technologies Department TUBITAK ULAKBIM Ankara06800 Turkey Department of Chemical and Pharmaceutical Sciences Trieste University Trieste Italy IOM-CNR Istituto Officina dei Materiali Trieste34149 Italy Micro and Nanotechnology Graduate Program of Natural and Applied Sciences Middle East Technical Turkey

Recently-demonstrated high-quality three-dimensional (3D) subsurface laser processing inside crystalline silicon (c-Si) wafers opens a door to a wide range of novel applications in multidisciplinary research areas. Using this technique, a novel maskless micro-pillars with precise control on the surface reflection and coverage are successfully fabricated by etching the laser processed region of c-Si wafer. To achieve this, a particular selective wet chemical etching is developed to follow subsurface laser processing of c-Si to reveal the desired 3D structures with smooth surfaces. Here, we report the development of a novel chromium-free chemical etching recipe based on copper nitrate, which yields substantially smooth surfaces at high etch rate and selectivity on the both laser-processed Si surface and subsurface, i.e., without significant etching of the unmodified Si. Our results show that the etch rate and surface morphology are interrelated and strongly influenced by the composition of the adopted etching solution. After an extensive compositional study performed at room temperature, we identify an etchant with a selectivity of over 1600 times for laser-modified Si with respect to unmodified Si. We also support our findings using density functional theory calculations of HF and Cu adsorption energies, indicating significant diversity on the c-Si and laser-modified surfaces. Copyright © 2023, The Authors. All rights reserved.

关键词： Morphology

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Macroscopically Self-Aligned and Chiralized Carbon Nanotubes: From Filtration to Innovation

arXiv

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arXiv 2023年

作者： Doumani, Jacques Zahn, Keshav Yu, Shengjie Barrios, Gustavo Rodriguez Sasmal, Somesh Kikuchi, Rikuta Kritzell, T. Elijah Xu, Hongjing Baydin, Andrey Kono, Junichiro Department of Electrical and Computer Engineering Rice University 6100 Main Street HoustonTX77005 United States Applied Physics Graduate Program Smalley–Curl Institute Rice University 6100 Main Street HoustonTX77005 United States Carbon Hub Rice University 6100 Main Street HoustonTX77005 United States Smalley–Curl Institute Rice University 6100 Main Street HoustonTX77005 United States Department of Physics and Astronomy Rice University 6100 Main Street HoustonTX77005 United States Department of Materials Science and NanoEngineering Rice University 6100 Main Street HoustonTX77005 United States

Because of their natural one-dimensional (1D) structure combined with intricate chiral variations, carbon nanotubes (CNTs) exhibit various exceptional physical properties, such as ultrahigh electrical and thermal conductivity, exceptional mechanical strength, and chirality-dependent metallicity. These properties make CNTs highly promising for diverse applications, including field-effect transistors, sensors, photodetectors, and thermoelectric devices. While CNTs excel individually at the nanoscale, their 1D and chiral nature can be lost on a macroscopic scale when they are randomly assembled. Therefore, the alignment and organization of CNTs in macroscopic structures is crucial for harnessing their full potential. In this review, we explore recent advancements in understanding CNT alignment mechanisms, improving CNT aligning methods, and demonstrating macroscopically 1D properties of ordered CNT assemblies. We also focus on a newly discovered class of CNT architectures, combining CNT alignment and twisting mechanisms to create artificial radial and chiral CNT films at wafer scales. Finally, we summarize recent developments related to aligned and chiral CNT films in optoelectronics, highlighting their unique roles in solar cells, thermal emitters, and optical modulators. Copyright © 2023, The Authors. All rights reserved.

关键词： Carbon nanotubes

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Angle-resolved photoemission spectroscopy with an in situ tunable magnetic field

arXiv

引用

arXiv 2023年

作者： Huang, Jianwei Yue, Ziqin Baydin, Andrey Zhu, Hanyu Nojiri, Hiroyuki Kono, Junichiro He, Yu Yi, Ming Department of Physics and Astronomy Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Smalley–Curl Institute Rice University HoustonTX77005 United States Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States Institute for Materials Research Tohoku University Katahira 2-1-1 Sendai980-8577 Japan Department of Applied Physics Yale University New HavenCT06511 United States

Angle-resolved photoemission spectroscopy (ARPES) is a powerful tool for probing the momentum-resolved single-particle spectral function of materials. Historically, in situ magnetic fields have been carefully avoided as they are detrimental to the control of photoelectron trajectory during the photoelectron detection process. However, magnetic field is an important experimental knob for both probing and tuning symmetry-breaking phases and electronic topology in quantum materials. In this paper, we introduce an easily implementable method for realizing an in situ tunable magnetic field at the sample position in an ARPES experiment and analyze magnetic field induced artifacts in ARPES data. Specifically, we identified and quantified three distinct extrinsic effects of a magnetic field: Constant energy contour rotation, emission angle contraction, and momentum broadening. We examined these effects in three prototypical quantum materials, i.e., a topological insulator (Bi2Se3), an iron-based superconductor (LiFeAs), and a cuprate superconductor (Pb-Bi2Sr2CuO6+x), and demonstrate the feasibility of ARPES measurements in the presence of a controllable magnetic field. Our studies lay the foundation for the future development of the technique and interpretation of ARPES measurements of field-tunable quantum phases. Copyright © 2023, The Authors. All rights reserved.

关键词： Photoelectrons

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Blackhole-Inspired Thermal Trapping with Graded Heat-Conduction Metadevices

arXiv

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arXiv 2022年

作者： Xu, Liujun Liu, Jinrong Jin, Peng Xu, Guoqiang Li, Jiaxin Ouyang, Xiaoping Li, Ying Qiu, Cheng-Wei Huang, Jiping Fudan University Shanghai200438 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Graduate School of China Academy of Engineering Physics Beijing100193 China School of Mechatronics Engineering Harbin Institute of Technology Harbin150001 China School of Materials Science and Engineering Xiangtan University Xiangtan411105 China Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang University Hangzhou310027 China International Joint Innovation Center Key Laboratory of Advanced Micro/Nano Electronic Devices and Smart Systems of Zhejiang The Electromagnetics Academy of Zhejiang University Zhejiang University Haining314400 China

Black holes are one of the most intriguing predictions of general relativity. So far, metadevices have enabled analogous black holes to trap light or sound in laboratory spacetime. However, trapping heat in a conductive ambient is still challenging because diffusive behaviors are directionless. Inspired by black holes, we construct graded heat-conduction metadevices to achieve thermal trapping, resorting to the imitated advection produced by graded thermal conductivities rather than the trivial solution of using insulation materials to confine thermal diffusion. We experimentally demonstrate thermal trapping for guiding hot spots to diffuse towards the center. Graded heat-conduction metadevices have advantages in energy-efficient thermal regulation because the imitated advection has a similar temperature field effect to the realistic advection that is usually driven by external energy sources. These results also provide insights into correlating transformation thermotics with other disciplines such as cosmology for emerging heat control schemes. Copyright © 2022, The Authors. All rights reserved.

关键词： Advection

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Ubiquitous Flat Bands in a Cr-based Kagome Superconductor

arXiv

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arXiv 2024年

作者： Guo, Yucheng Wang, Zehao Xie, Fang Huang, Yuefei Gao, Bin Oh, Ji Seop Wu, Han Liu, Zhaoyu Ren, Zheng Fang, Yuan Biswas, Ananya Zhang, Yichen Yue, Ziqin Hu, Cheng Jozwiak, Chris Bostwick, Aaron Rotenberg, Eli Hashimoto, Makoto Lu, Donghui Kono, Junichiro Chu, Jiun-Haw Yakobson, Boris I. Birgeneau, Robert J. Si, Qimiao Dai, Pengcheng Yi, Ming Department of Physics and Astronomy Rice University HoustonTX77005 United States Advanced Light Source Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States Department of Physics University of California BerkeleyCA94720 United States Department of Physics University of Washington Washington98105 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Stanford Synchrotron Radiation Lightsource SLAC National Accelerator Laboratory Menlo ParkCA94025 United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States

In the quest for novel quantum states driven by topology and correlation, kagome lattice materials have garnered significant interest due to their distinctive electronic band structures, featuring flat bands (FBs) arising from the quantum destructive interference of the electronic wave function. The tuning of the FBs to the chemical potential would lead to the possibility of liberating electronic instabilities that lead to emergent electronic orders. Despite extensive studies, direct evidence of FBs tuned to the chemical potential and their participation in emergent electronic orders have been lacking in bulk quantum materials. Here using a combination of Angle-Resolved Photoemission Spectroscopy (ARPES) and Density Functional Theory (DFT), we reveal that the low-energy electronic structure of the recently discovered Cr-based kagome metal superconductor CsCr3Sb5 is dominated by a pervasive FB in close proximity to, and below the Fermi level. A comparative analysis with orbital-projected DFT and polarization dependence measurement uncovers that an orbital-selective renormalization mechanism is needed to reconcile the discrepancy with the DFT calculations, which predict the FB to appear 200 meV above the Fermi level. Furthermore, we observe the FB to shift away from the Fermi level by 20 meV in the low-temperature density wave-ordered phase, highlighting the role of the FB in the emergent electronic order. Our results reveal CsCr3Sb5 to stand out as a promising platform for further exploration into the effects of FBs near the Fermi level on kagome lattices, and their role in emergent orders in bulk quantum materials. © 2024, CC BY.

关键词： Density functional theory

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Layer-dependent optically-induced spin polarization in InSe

arXiv

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arXiv 2022年

作者： Nelson, Jovan Stanev, Teodor K. Lebedev, Dmitry LaMountain, Trevor Tyler Gish, J. Zeng, Hongfei Shin, Hyeondeok Heinonen, Olle Watanabe, Kenji Taniguchi, Takashi Hersam, Mark C. Stern, Nathaniel P. Applied Physics Program Northwestern University EvanstonIL60208 United States Department of Physics and Astronomy Northwestern University EvanstonIL60208 United States Department of Material Science & Engineering Northwestern University EvanstonIL60208 United States Computational Science Division Argonne National Laboratory LemontIL60439 United States Material Science Division Argonne National Laboratory LemontIL60439 United States Research Center for Functional Materials National Institute for Materials Science 1-1 Namiki Tsukuba305-0044 Japan International Center for Materials Nanoarchitectonics National Institute for Materials Science 1-1 Namiki Tsukuba305-0044 Japan Department of Chemistry Northwestern University EvanstonIL60208 United States Department of Electrical Engineering and Computer Science Northwestern University EvanstonIL60208 United States

Optical control of spin in semiconductors has been pioneered using nanostructures of III-V and II-VI semiconductors, but the emergence of two-dimensional van der Waals materials offers an alternative low-dimensional platform for spintronic phenomena. Indium selenide (InSe), a group-III monochalcogenide van der Waals material, has shown promise for opto-electronics due to its high electron mobility, tunable direct bandgap, and quantum transport. In addition to these confirmed properties, there are predictions of spin-dependent optical selection rules suggesting potential for all-optical excitation and control of spin in a two-dimensional layered material. Despite these predictions, layer-dependent optical spin phenomena in InSe have yet to be explored. Here, we present measurements of layer-dependent optical spin dynamics in few-layer and bulk InSe. Polarized photo-luminescence reveals layer-dependent optical orientation of spin, thereby demonstrating the optical selection rules in few-layer InSe. Spin dynamics are also studied in many-layer InSe using time-resolved Kerr rotation spectroscopy. By applying out-of-plane and in-plane static magnetic fields for polarized emission measurements and Kerr measurements, respectively, the g-factor for InSe was extracted. Further investigations are done by calculating precession values using a k·p model, which is supported by ab-initio density functional theory. Comparison of predicted precession rates with experimental measurements highlights the importance of excitonic effects in InSe for understanding spin dynamics. Optical orientation of spin is an important prerequisite for opto-spintronic phenomena and devices, and these first demonstrations of layer-dependent optical excitation of spins in InSe lay the foundation for combining layer-dependent spin properties with advantageous electronic properties found in this material. Copyright © 2022, The Authors. All rights reserved.

关键词： Spin dynamics

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Terahertz chiral photonic-crystal cavities with broken time-reversal symmetry

arXiv

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arXiv 2024年

作者： Tay, Fuyang Sanders, Stephen Baydin, Andrey Song, Zhigang Welakuh, Davis M. Alabastri, Alessandro Rokaj, Vasil Dag, Ceren B. Kono, Junichiro Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley–Curl Institute Rice University HoustonTX77005 United States Smalley–Curl Institute Rice University HoustonTX77005 United States John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA02139 United States Max Planck Institute for The Structure and Dynamics of Matter Luruper Chaussee 149 Hamburg22761 Germany ITAMP Harvard-Smithsonian Center for Astrophysics CambridgeMA02138 United States Department of Physics Harvard University CambridgeMA02138 United States Department of Physics Villanova University VillanovaPA19085 United States Department of Physics and Astronomy Rice University HoustonTX77005 United States Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States

Strong coupling between matter and vacuum electromagnetic fields in a cavity can induce novel quantum phases in thermal equilibrium via symmetry breaking. Particularly, coupling with circularly polarized fields can break time-reversal symmetry, leading to topological modifications in the band structure. Therefore, chiral optical cavities that host chiral vacuum fields are being sought, especially in the terahertz (THz) frequency range, where various large-oscillator-strength resonances exist. Here, we present a novel approach to achieving THz chiral photonic-crystal cavities (PCCs) with high-quality factors (>400) using a magnetoplasma in a lightly doped semiconductor. Numerical simulations of an optimized structure based on InSb in a small perpendicular magnetic field (∼0.2 T) show chiral cavity resonances with near-perfect ellipticity at the surfaces of the central dielectric layer, where one can place atomically thin materials like monolayer graphene. We theoretically estimate an energy gap on the order of 1 meV in graphene when coupled to our proposed chiral cavity, which is potentially measurable in experiments. These THz chiral PCCs offer a promising platform for exploring new phases in cavity-dressed condensed matter with broken time-reversal symmetry. Copyright © 2024, The Authors. All rights reserved.

关键词： Crystal symmetry

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