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Mobilizing Automated Vehicles: Harmonizing the Intersection of Technological Innovations and Legal Regulations
There will be significant shifts in transportation with the introduction of autonomous vehicles (AVs), which will increase efficiency, safety, and environmental friendliness. But these technologies can only be used to their full potential if technological breakthroughs are seamlessly integrated with strong legal regulations. The article delves into the ways in which technological advances and legal frameworks meet, highlighting how important regulatory measures are for ensuring the secure use of AVs. In addition, the article delves into the current legal framework around AVs, drawing attention to the difficulties caused by inconsistent regulations and the necessity for flexible rules that can stay up with the fast-paced advancements in technology. The purpose of this article is to examine current policies and case studies to shed light on how to effectively integrate technology advancements with legal requirements to create conditions that are favorable to the broad use of autonomous vehicles. The results highlight the need for manufacturers, lawmakers, and the general public to work together for the sake of society's safety and well-being during the shift to autonomous transportation. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
Modalities in data: understanding text, images, and audio
Data modalities, encompassing diverse forms such as text, audio, image, and video, play a pivotal role in shaping modern data analysis and machine learning applications. Each modality represents information in a unique format, requiring specific processing and interpretation methods. The integration of multiple modalities, known as multimodal data, enhances decision-making and predictive accuracy, particularly in complex systems like sentiment analysis, speech recognition, and medical diagnostics. Deep learning techniques have facilitated the seamless fusion of multimodal data, enabling a more comprehensive understanding across various fields, from healthcare to social media analytics. For example, combining text with images improves sentiment analysis, while integrating audio and video aids in more accurate speech recognition. However, the incorporation of multimodal data presents challenges, including data heterogeneity, synchronization issues, and dimensionality concerns. Data formats differ across modalities, and aligning them for cohesive analysis requires sophisticated algorithms and computational power. Despite these obstacles, multimodal data offers significant benefits, such as enhanced customer experience in business and increased diagnostic accuracy in health care. Furthermore, the rise of large datasets and artificial intelligence (AI) technologies has fueled innovation, enabling the development of more efficient models capable of uncovering intricate relationships within data. This chapter discusses various modalities, their applications, and the technological advancements driving their integration. It also highlights the challenges in multimodal data processing and the solutions being developed to address these complexities, offering valuable insights for businesses, researchers, and AI practitioners. 2026 Elsevier Inc. All rights reserved. -
Model and Algorithm of Multimodal Transportation in Logistics Transportation Based on Particle Swarm Optimization
With the rapid improvement of market economy and modern logistics technique, the logistics distribution link is receiving more and more attention, and the logistics distribution path question in distribution has become the core question in logistics distribution. Study the optimization of logistics distribution path. Logistics distribution path optimization needs to find an optimal distribution route with less distribution vehicles and the shortest total length of the path, and has the rapidity of distribution. The traditional algorithm takes a long time to search the optimal route, which makes it difficult to find the optimal distribution route, resulting in high logistics distribution costs. In order to quickly find the optimal distribution route and improve the quality of logistics service, a logistics model based on particle swarm optimization algorithm is proposed. The group is composed of several non-intelligent individuals or groups of individuals. Each individual's behavior follows certain simple rules and has no intelligence; Individuals or groups of individuals can cooperate to solve questions through certain principles of message exchange, thus showing the behavioral characteristics of collective intelligence. After research, the algorithm in this paper is effective and suitable for wide application in practice. 2023 IEEE. -
Model between mind share branding factors and trustworthiness /
Patent Number: 202111055024, Applicant: Dr.Vikas Singla.
The importance of Mindshare branding (MB) strategy in building long-term and sustainable psychological links with consumers had been sufficiently highlighted in literature. However, very few research attempted to provide a structured tool for its measurement. This study proposed a 13-point four-factor multidimensional scale which could be used to measure MB formally. Dimensions measuring MB were derived from literature and then examined on different brands in order to achieve a reliable and valid scale. -
Model between mind share branding factors and trustworthiness /
Patent Number: 202111055024, Applicant: Dr.Vikas Singla.
The importance of Mindshare branding (MB) strategy in building long-term and sustainable psychological links with consumers had been sufficiently highlighted in literature. However, very few research attempted to provide a structured tool for its measurement. This study proposed a 13-point four-factor multidimensional scale which could be used to measure MB formally. Dimensions measuring MB were derived from literature and then examined on different brands in order to achieve a reliable and valid scale. -
Model between mind share branding factors and trustworthiness /
Patent Number: 202111055024, Applicant: Dr.Vikas Singla.
The importance of Mindshare branding (MB) strategy in building long-term and sustainable psychological links with consumers had been sufficiently highlighted in literature. However, very few research attempted to provide a structured tool for its measurement. This study proposed a 13-point four-factor multidimensional scale which could be used to measure MB formally. Dimensions measuring MB were derived from literature and then examined on different brands in order to achieve a reliable and valid scale. -
Model between mind share branding factors and trustworthiness /
Patent Number: 202111055024, Applicant: Dr.Vikas Singla.
The importance of Mindshare branding (MB) strategy in building long-term and sustainable psychological links with consumers had been sufficiently highlighted in literature. However, very few research attempted to provide a structured tool for its measurement. This study proposed a 13-point four-factor multidimensional scale which could be used to measure MB formally. Dimensions measuring MB were derived from literature and then examined on different brands in order to achieve a reliable and valid scale. -
Model between mind share branding factors and trustworthiness /
Patent Number: 202111055024, Applicant: Dr.Vikas Singla.
The importance of Mindshare branding (MB) strategy in building long-term and sustainable psychological links with consumers had been sufficiently highlighted in literature. However, very few research attempted to provide a structured tool for its measurement. This study proposed a 13-point four-factor multidimensional scale which could be used to measure MB formally. Dimensions measuring MB were derived from literature and then examined on different brands in order to achieve a reliable and valid scale. -
Model between viral branding factors and trustworthiness /
Patent Number: 202211039578, Applicant: Dr. Vikas Singla.
The importance of Viral branding (VB) strategy in building long-term and sustainable psychological links with consumers had been sufficiently highlighted in literature. However, very few research attempted to provide a structured tool for its measurement. This study proposed a 13- point four-factor multidimensional scale which could be used to measure VB formally. Dimensions measuring VB were derived from literature and then examined on different brands in order to achieve a reliable and valid scale. -
Model independent analysis in (?, n) reactions using deuterium targets
Photonuclear reactions play an important role in nuclear physics, astrophysics and in various applications such as non-destructive measurement of nuclear materials (NDT). The study of (?, n) reactions using deuterium targets i.e., photodisintegration of deuterons in addition to all the other (?, n) reactions, is of considerable interest to these fields. In this contribution, we have studied the photodisintegration of deuterons with unpolarized photons. The angular dependence of the differential cross section is studied by expressing it in terms of Legendre polynomials. The analysis of differential cross-section is presented using the model-independent irreducible tensor formalism. 2021 -
Model independent approach to photodisintegration of 7Li at the range of energies of interest to BBN
One of the elements that was synthesized primordially in the standard Big Bang Nucleosynthesis is lithium. Lithium, being fragile gets easily destroyed at relatively low temperatures in the mixing process between stellar surface and hot internal layers. So that, at the end of the stellar lifetime the lithium content is believed to be depleted. Series of experimental measurements on lithium isotopes were carried out at High Intensity Gamma Ray Source (HIGS) at Duke Free Electron Laser Laboratory. More recently experiments [1]-[2] were performed, to measure the differential cross section of the photo-neutron reaction channel in photodisintegration of 7Li, where the progeny nuclei is in the ground state as well as in excited states. The purpose of present contribution is to study the reaction channel 7Li + ? ? 6Li + n using linearly polarized photons.The model independent irreducible tensor formalism [3]-[5] will be used to study the differential cross section of the reaction. We study the angular dependence of differential cross section by expressing differential cross section in terms of legendre polynomials. In view of the several theoretical and ongoing experimental studies, a detailed theoretical study of the spin structure of the amplitudes in 7Li+ ? ? 6Li+ n and their expansion in terms of'electric' and 'magnetic' amplitudes is needed to analyze the measurements of spin observables as well as differential cross section, which leads to a better understanding of the problem at astrophysical energies. 2022 Institute of Physics Publishing. All rights reserved. -
Model independent approach to proton polarization in photodisintegration of deuteron
In addition to other photonuclear reactions, the study of photonuclear reactions on deuterium targets is important for laser physics, nuclear physics, astrophysics, and a number of applications, including nondestructive testing of nuclear materials. In this paper, we have carried out a model independent analysis of proton polarization in photodisintegration of deuterons with initially unpolarized beam and unpolarized target. The angular dependence of the polarization is studied by expressing it in terms of multipole amplitudes. 2023 Elsevier Ltd. All rights reserved. -
Model of cross-cultural adjustment and view of life-career among Japanese expatriate spouses in India
In the globalized economy, it is necessary to consider expatriates cross-cultural adjustment, which is affected by their spouses, whose cross-cultural adjustment should not be neglected. We examined a model of cross-cultural adjustment among Japanese spouses in India. We hypothesized that demands (e.g., cultural differences, language immaturity) and resources (e.g., spouses personality/agreeableness, perceived social support) negatively and positively affect cross-cultural adjustment, respectively. In turn, cross-cultural adjustment positively affects subjective happiness and intent to stay. In addition, cross-cultural adjustment consists a part of life-career perspective for expatriate spouses who quit their job when go to abroad. To examine the hypotheses, we use a mixed methods approach (QUAN?QUAL) that uses multiple variables and sampling to collect quantitative and qualitative data over two phases sequentially. First, from August to October 2018, a survey using a web-based questionnaire was conducted in four areas in India: New Delhi, Mumbai, Chennai, and Bengaluru. Responses from 105 participants, who are parents of Japanese school children or members of a parenting support group were received. Second, from October to December 2018, the interview data for 17 participants were collected at Bengaluru. To confirm the hypothesized model, we tested a structural equations modeling (SEM) analysis. Additionally, the interview transcript data were analyzed with a modified version of the Grounded Theory approach (M-GTA). The Results demonstrated that Japanese expatriate spouses who had difficulties in communicating in English and felt large cultural differences, decreased their adjustment, their subjective happiness was lowered, and they wanted to return to their home country early. However, the more the personality was cooperative and compassionate, and the more they worked to adjust to their international life; their subjective happiness increased. Additionally, expatriate spouses obtained the concept of view of life-career. The view of life-career included cross-cultural adjustment. Cross-cultural adjustment affects positive view of life-career that will lead to smooth re-employment after returning to Japan. 2020, Springer Science+Business Media, LLC, part of Springer Nature. -
Model of ICT based blended education system: Productive implementation for sector skills development /
Patent Number: 202141055854, Applicant: Suplab Podder. -
Model of ICT based blended education system: Productive implementation for sector skills development /
Patent Number: 202141055854, Applicant: Suplab Podder. -
Model Selection Procedure in Alleviating Drawbacks of the Electronic Whiteboard
Deep learning has paved the way for critical and revolutionary applications in almost every field of life in general. Ranging from engineering to healthcare, machine learning and deep learning has left its mark as the state-of-the-art technology application which holds the epitome of a reasonable high benchmarked solution. Incorporating neural network architectures into applications has become a common part of any software development process. In this paper, we perform a comparative analysis on the different transfer learning approaches in the domain of hand-written digit recognition. We use two performance measures, loss and accuracy. We later visualize the different results for the training and validation datasets and reach to a unison conclusion. This paper aims to target the drawbacks of the electronic whiteboard with simultaneous focus on the suitable model selection procedure for the digit recognition problem. 2021 IEEE. -
Model Selection Strategies for Identifying Effective Energy Storage Systems
Energy is present in various forms in and around us. Capturing and storing energy from various sources have diverse challenges. Designing and developing energy storage systems are challenging, as various techniques are used to distribute energy from sources and to store for diverse use cases. Identifying the optimal and effective energy storage system requires the application of various model selection strategies. The success and adoption of effective energy storage systems can be identified with numerous factors, which include the systems efficiency, reliability, cost-effectiveness, and scalability. Various model selection strategies are available to compute and determine the effective energy storage mechanisms. Various researchers are planning and designing energy storage systems based on the insights from the data with the support of optimisation algorithms, mathematical models, and Artificial Intelligence (AI) and Machine Learning (ML) technologies. The chapter discusses the various model selection strategies for identifying effective models for energy storage systems. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Model Selection Strategies for Identifying Effective Energy Storage Systems
Energy is present in various forms in and around us. Capturing and storing energy from various sources have diverse challenges. Designing and developing energy storage systems are challenging, as various techniques are used to distribute energy from sources and to store for diverse use cases. Identifying the optimal and effective energy storage system requires the application of various model selection strategies. The success and adoption of effective energy storage systems can be identified with numerous factors, which include the systems efficiency, reliability, cost-effectiveness, and scalability. Various model selection strategies are available to compute and determine the effective energy storage mechanisms. Various researchers are planning and designing energy storage systems based on the insights from the data with the support of optimisation algorithms, mathematical models, and Artificial Intelligence (AI) and Machine Learning (ML) technologies. The chapter discusses the various model selection strategies for identifying effective models for energy storage systems. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Model-Independent Cosmography with Logarithmic Polynomial using Recent Observational Data
The accelerated expansion of the Universe remains a fundamental challenge in cosmology, motivating model-independent methods to reconstruct its expansion history without relying on specific dark energy models. Cosmography, which employs series expansions of cosmological observables around the present epoch, provides a powerful kinematic framework rooted in the cosmological principle. However, standard Taylor expansions suffer from limited convergence at high redshift, prompting the exploration of alternative expansions. In this work, logarithmic polynomial cosmography is investigated, which expands observables in powers of the logarithm of redshift, thereby enhancing convergence over a broad redshift range while maintaining physical insight. The logarithmic polynomial parameters are constrained using recent datasets, including gravitational-wave standard sirens, DESI DR2, cosmic chronometers, and multiple Type Ia supernova compilations (DES-SN5YR, Union3, Pantheon+SH0ES). The analysis demonstrates the efficacy of the logarithmic approach in accurately modeling the cosmic expansion history, providing an interpretable alternative to traditional cosmographic techniques. 2026 Wiley-VCH GmbH. -
Modeling a Logistic Regression based Sustained Approach for Cancer Detection
This assessment and treatment of cancer may be done using logistic regression. To properly forecast whether a tumour is malignant or benign, the likelihood of binary outcomes may be simulated based on input variables and taken into account for factors like volume, topology and texture. It aids in risk assessment by estimating an individual's likelihood of developing cancer using factors like age-group, relatives past data, life choices and gene based markers. Logistic regression plays an important role in early cancer detection and creating screening tools that identify high-risk individuals through patent characteristics, biomarkers, and medical imaging data. Prediction of the probability of survival based on age, tumor characteristics, treatment options and comorbidities is useful for survival analysis. In a comparative study, logistic regression achieved a high accuracy of 97.4%, along with random forest, in cancer detection and diagnosis. 2023 IEEE.