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Design, analysis and fabrication of EV with level-1 autonomous vehicle capability
The fact to this day remains true and the same for over a hundred years the Automobile industry and vehicles, in general, have become the pivoting point in our day to day lives. We might as well call it a necessary evil. Although it is very true that they have made our lives more convenient when we speak in terms of transportation; the pollution that conventional IC engine vehicles produce hasn't done much to create a cleaner environment especially with Global warming on the rise as we speak. The simplest remedy would be is to replace IC engine vehicles with Electric one, EV. A Problem common to both conventional IC engine vehicles and EV's alike is the accidents occurring due to collision caused by human error on-road. While safety measures have greatly been taken in order to reduce the damage done to the driver and passengers in the event of a collision it would be far better to avoid the collision altogether. Thus having at least, a Level-1 Autonomous Vehicles capability where the system alerts the driver in the event of a crash or collision and deploy full braking capability. Thanks to increasing urbanization and the advent of modern technology the need of the hour of the 21st century has given rise to high demands for employment in the motorized transport sectors. The authors were successfully able to design, analyze and fabricate an EV with Level-1 Autonomous Vehicles capability. The successful implementation of this project will help in reducing not only pollution and accidents occurring on-road due to vehicle collision but also pave paths in alimenting Level-1 Autonomous Vehicles capability in EV's inexpensively. 2020 Author(s). -
Design, development and characterization of polyelectrolyte multilayer membranes for potential filtration applications
The present work projects to modify the surface of commercially available microfiltration membranes using polyelectrolyte multilayer assembly. This polyelectrolytic modification changes the nature and properties of the membrane such as porosity, absorption capacity, charge etc. which can be used for potential environmental application such as herbicide removal from water. Chitosan (CHI) and polystyrene sulfonate (PSS) were incorporated into nanostructured polymeric films on polyamide membrane using layer-by-layer (LbL) technique. The developed polyelectrolyte multilayer assembly were characterized by using UV-vis spectroscopy, attenuated total reflectance fourier transform infrared (ATR-FTIR) spectroscopy, thermo gravimetric analysis (TGA) and atomic force microscopy (AFM). 2020 Elsevier Ltd. All rights reserved. -
Design, development, and analysis of segment support system for TMT primary mirror
The Thirty Meter Telescope (TMT) adopts a recently developed technology known as Stressed Mirror Polishing for the polishing of its 492 mirror segments. In this process, first the meniscus type spherical shape glass blanks are converted in to a desired aspheric shape by the application of forces around the edges using warping arms followed by spherical polishing in the stressed condition. After that, the blank edges will be cut in to its final hexagonal shape. These warping as well as the hex cutting process generate significant stress within the glass which in later stage, will cause the propagation of micro cracks and results in blank breakage. So prior and after the hex cutting process, it is essential to ensure that the glass blanks are free from stress accumulation. Hence the glass blanks need to be stress relieved before the hex cutting process. To achieve this stress relaxation, the glass blanks need to be kept over a platform or a support system which will provide a zero gravity condition for a time period of at least 48 hours. As a part of this, we designed, developed and analyzed a whiffletree based support system which will equally distribute the entire mirror blank mass into three points which are equally separated by 120 from each other and thus balance itself as if it is in a floating condition. This support system which additionally gives optimized support for the glass blank which in turn minimizes the surface deformation due to its self weight sagging. This paper also discusses the positional sensitivity, reaction force sensitivity and alignment sensitivity analyses which are essential to obtain the tolerance values in the fabrication point of view. 2020 SPIE. -
Design, Synthesis, Molecular Docking, and In Vitro Antiproliferative Evaluation of QuinolinePyranocoumarin Hybrids as Potent DNA Topoisomerase II Inhibitors
A series of novel quinolinepyranocoumarin hybrids incorporating quinoline and coumarin moieties were designed, synthesized, and evaluated as DNA topoisomerase II inhibitors. The key scaffold, 2-amino-5-oxo-4-(quinolin-4-yl)-4,5-dihydropyrano[3,2-c]chromene-3-carbonitrile, was obtained via a one-pot reaction in 92% yield at room temperature. Ten derivatives (4a4j) were characterized by 1H/13C NMR and mass spectrometry. Docking studies against TOPO II? (PDB ID: 5GWK) revealed compound 4b with the best binding affinity (?8.02kcal/mol), outperforming doxorubicin. In vitro cytotoxicity on MCF-7 and K562 cells showed lower IC50 values for MCF-7, and cell cycle analysis indicated G2/M arrest consistent with TOPO II inhibition. 2026 Wiley-VCH GmbH. -
Design, synthesis, single-crystal X-ray and docking studies of imidazopyridine analogues as potent anti-TB agents
With the intent to discover new anti-TB compounds, new imidazopyridine analogues were synthesized through Schiff-base reaction. The newly developed imidazopyridines (I1-I8) were characterized using spectroscopic and elemental analysis. In addition the structure of compound I3 was elucidated by the single crystal X-ray diffraction technique. The global chemical reactivity descriptor parameter was calculated using theoretically DFT-B3LYP-631G(d) basis set which estimated HOMO-LUMO value and results are discussed. All the newly synthesized compounds were screened for their in vitro anti-tubercular activity, while the most active compounds were subjected to a cytotoxicity assay on Vero cell lines. Most of the tested compounds exhibited significant anti-TB activity with MIC in the range 3.12 12.5 ?g/mL. Among the synthesized, compound I2 and I7 were found to be more active than the standard anti-TB drug streptomycin and comparable activity to pyrazinamide. A cytotoxicity study on Vero-cell lines confirmed the nontoxic nature of compound I2 and I7 indicating good safety profile. The molecular docking studies on PDB IB: 4ED4 enzyme of Mycobacterium tuberculosis was conducted to investigate mechanisms of anti-TB activity. The compounds displayed excellent hydrogen binding interactions and docking scores against MTB, which were in accordance with the results and further supported its credibility. 2023 -
Designer Crops for Biotic Stress Tolerance: Technologies and Applications
The interplay of population growth and climate change makes the creation of specialized crops in a context teeming with both biotic and abiotic hazards exceptionally challenging. Despite the optimism surrounding integrated pest and disease control based on host plant tolerance, the ongoing appearance of novel races and biotypes of major plant diseases and parasites poses a significant and growing threat to global agricultural output. Crop plants sustain severe harm from biotic stressors like diseases and pests. Managing these pressures has an influence on ecosystems and the environment in addition to raising production costs. Growers, exporters, and the health of both people and animals are concerned about the growing usage of chemical agents to combat biotic stressors. To address this, the most efficient approach is to employ resistant cultivars, as they offer cost-effectiveness, health benefits, and environmental friendliness. For enhancing global food security, the utilization of genome-editing tools requires close collaboration and dialogue among scientists, policymakers, regulators, and journalists. This concerted endeavor aims to simultaneously tackle public apprehensions about genetically modified crops. This chapter offers a comprehensive examination of the impact of biotic stress on crop plants and underscores the significance of developing crops with the ability to withstand such stresses. Additionally, it delves into diverse technologies created for crop enhancement and explores the economic significance of currently available engineered crops in the market. 2026 by John Wiley & Sons, Inc. -
Designer Crops for Biotic Stress Tolerance: Technologies and Applications
The interplay of population growth and climate change makes the creation of specialized crops in a context teeming with both biotic and abiotic hazards exceptionally challenging. Despite the optimism surrounding integrated pest and disease control based on host plant tolerance, the ongoing appearance of novel races and biotypes of major plant diseases and parasites poses a significant and growing threat to global agricultural output. Crop plants sustain severe harm from biotic stressors like diseases and pests. Managing these pressures has an influence on ecosystems and the environment in addition to raising production costs. Growers, exporters, and the health of both people and animals are concerned about the growing usage of chemical agents to combat biotic stressors. To address this, the most efficient approach is to employ resistant cultivars, as they offer cost-effectiveness, health benefits, and environmental friendliness. For enhancing global food security, the utilization of genome-editing tools requires close collaboration and dialogue among scientists, policymakers, regulators, and journalists. This concerted endeavor aims to simultaneously tackle public apprehensions about genetically modified crops. This chapter offers a comprehensive examination of the impact of biotic stress on crop plants and underscores the significance of developing crops with the ability to withstand such stresses. Additionally, it delves into diverse technologies created for crop enhancement and explores the economic significance of currently available engineered crops in the market. 2026 by John Wiley & Sons, Inc. -
Designing a Dynamic Topology (DHT) for Cluster Head Selection in Mobile Adhoc Network
The mobile ad hoc networks (MANETs) are a collection of dynamic nodes facilitating communication from source to destination either using single or multi hop forwarding mechanism. The nodes within the network possess energy constraints for which an effective clustering mechanism is used for facilitating communication between the nodes within and outside the clusters by designing a dynamic hybrid topology (DHT). The paper concentrates on clustering mechanism (EBCH) for reducing the energy consumption during communication from source to destination and number of parameters where analyzed in order to determine the selection of cluster head based on the energy consumption because this is directly related to the lifetime of the network. The implementation was carried out using MATLAB which offered an environment for performing simulation. The obtained results on comparison with conventional ENB and CPN algorithm improved the operations of cluster computation in ad hoc environments effectively in relation to the cluster head selection and reduced energy consumption. 2019, Springer Science+Business Media, LLC, part of Springer Nature. -
Designing a One-Pot Ternary Fe-Mn-Zn Oxide Positive Electrode with Enhanced Energy-Storage Properties for Hybrid Supercapacitors
In recent years, ternary metal-oxide nanocomposite-based active electrodes have been investigated more effectively for supercapacitor applications due to the existence of a greater number of electroactive sites and the synergistic effect of three different transition-metal ions. Herein, Fe-Mn-Zn oxide ternary nanocomposites are synthesized using a simple and cost-effective one-pot hydrothermal approach. The characterizations of XRD, FTIR, FESEM, EDX, HRTEM, and XPS are analyzed for the synthesized Fe-Mn-Zn oxide nanocomposites to study their phases, functional groups, morphologies, purity, and binding energies. The electrochemical characteristics for the developed electrodes are studied in a three-electrode technique using CV, GCD, EIS, and a cyclic stability test. As expected, the ternary nanocomposite electrode of Fe-Mn-Zn oxide reveals a maximum specific capacitance (Cspc1) of 1673.4 F/g in comparison to other developed electrodes of ZnFe2O4 (271.7 F/g) and ZnMn2O4 (412.7 F/g) at the appropriate scan rate of 10 mV/s. In addition, the Fe-Mn-Zn oxide ternary nanocomposite active electrode exhibits 2616.25 F/g of total capacitance (qT**), 686.94 F/g of outer capacitance (qO**), and 1929.30 F/g of inner capacitance (qI**) which are determined by Trasatti analysis. Moreover, the fabricated hybrid supercapacitor device provides a good specific capacitance of 320.8 F/g, a high energy density of 75.3 Wh/kg at the power density of 649.9 W/kg at 1 A/g of current density range, and 88.75% of superior capacitive retention over 10,000 cycles at 10 A/g. Therefore, a ternary metal-oxide nanocomposite electrode is proposed to be a promising material for energy-storage devices. 2024 American Chemical Society. -
Designing a One-Pot Ternary Fe-Mn-Zn Oxide Positive Electrode with Enhanced Energy-Storage Properties for Hybrid Supercapacitors
In recent years, ternary metal-oxide nanocomposite-based active electrodes have been investigated more effectively for supercapacitor applications due to the existence of a greater number of electroactive sites and the synergistic effect of three different transition-metal ions. Herein, Fe-Mn-Zn oxide ternary nanocomposites are synthesized using a simple and cost-effective one-pot hydrothermal approach. The characterizations of XRD, FTIR, FESEM, EDX, HRTEM, and XPS are analyzed for the synthesized Fe-Mn-Zn oxide nanocomposites to study their phases, functional groups, morphologies, purity, and binding energies. The electrochemical characteristics for the developed electrodes are studied in a three-electrode technique using CV, GCD, EIS, and a cyclic stability test. As expected, the ternary nanocomposite electrode of Fe-Mn-Zn oxide reveals a maximum specific capacitance (Cspc1) of 1673.4 F/g in comparison to other developed electrodes of ZnFe2O4 (271.7 F/g) and ZnMn2O4 (412.7 F/g) at the appropriate scan rate of 10 mV/s. In addition, the Fe-Mn-Zn oxide ternary nanocomposite active electrode exhibits 2616.25 F/g of total capacitance (qT**), 686.94 F/g of outer capacitance (qO**), and 1929.30 F/g of inner capacitance (qI**) which are determined by Trasatti analysis. Moreover, the fabricated hybrid supercapacitor device provides a good specific capacitance of 320.8 F/g, a high energy density of 75.3 Wh/kg at the power density of 649.9 W/kg at 1 A/g of current density range, and 88.75% of superior capacitive retention over 10,000 cycles at 10 A/g. Therefore, a ternary metal-oxide nanocomposite electrode is proposed to be a promising material for energy-storage devices. 2024 American Chemical Society. -
Designing a Precision Seed Sowing Machine for Enhanced Crop Productivity
A seed sowing machine is a valuable agricultural device that facilitates the precise and efficient sowing of seeds in fields. When designing and optimizing such a machine, several crucial factors need consideration including seed size, seed rate, soil type, and field conditions. The primary objective is to achieve uniform seed distribution and optimal seed-to-soil contact, which can be accomplished by incorporating a seed metering mechanism to control the seed rate accurately. Versatility is another important aspect of the machine's design, as it should be able to handle different seed sizes, types, soil conditions, and field variations. To achieve this, utilizing advanced technologies such as sensors, automation, and precision farming techniques can significantly enhance the machine's performance and efficiency while also reducing costs and minimizing environmental impact. The optimization of a seed sowing machine plays a crucial role in ensuring successful crop production. By implementing cutting-edge technologies and precision farming techniques, farmers can increase their yields and decrease the amount of seed and fertilizer needed for a specific area. Ultimately, this leads to improved productivity, increased profitability, and a more sustainable approach to agriculture. 2024 E3S Web of Conferences -
Designing an artificial intelligence-enabled large language model for financial decisions
Purpose: Artificial intelligence (AI) has profoundly reshaped financial decision-making, introducing a paradigm shift in how institutions and individuals navigate the complex finance landscape. The study evaluates the significant impact of integrating advanced AI and large language models (LLMs) in financial decision analytics. Design/methodology/approach: The study offers FinSageNet, a novel framework designed and tested to harness the potential of LLMs in financial decisions. The framework excels in handling and analyzing large volumes of numerical and textual data through advanced data mining techniques. Findings: FinSageNet demonstrates exceptional text summarization capabilities, outperforming models like FLAN and GPT-3.5 in Rouge score metrics. The proposed model has shown more accuracy than generic models. Originality/value: The study emphasizes the significance of consistently updating models and adopting a comprehensive approach to integrating AI into financial decisions. This study improves our understanding of how artificial intelligence transforms financial analytics and decision-making processes. 2025, Emerald Publishing Limited. -
Designing an artificial intelligence-enabled large language model for financial decisions
Purpose Artificial intelligence (AI) has profoundly reshaped financial decision-making, introducing a paradigm shift in how institutions and individuals navigate the complex finance landscape. The study evaluates the significant impact of integrating advanced AI and large language models (LLMs) in financial decision analytics. Design/methodology/approach The study offers FinSageNet, a novel framework designed and tested to harness the potential of LLMs in financial decisions. The framework excels in handling and analyzing large volumes of numerical and textual data through advanced data mining techniques. Findings FinSageNet demonstrates exceptional text summarization capabilities, outperforming models like FLAN and GPT-3.5 in Rouge score metrics. The proposed model has shown more accuracy than generic models. Originality/value The study emphasizes the significance of consistently updating models and adopting a comprehensive approach to integrating AI into financial decisions. This study improves our understanding of how artificial intelligence transforms financial analytics and decision-making processes. 2025 Emerald Publishing Limited -
Designing an efficient and scalable relational database schema: Principles of design for data modeling
Relational databases are a critical component of modern software applications, providing a reliable and scalable method for storing and managing data. A well-designed database schema can enhance the performance and flexibility of applications, making them more efficient and easier to maintain. Data modeling is an essential process in designing a database schema, and it involves identifying and organizing data entities, attributes, and relationships. In this chapter, the authors discuss the principles of designing an efficient and scalable relational database schema, with a focus on data modeling techniques. They explore the critical aspects of normalization, data types, relationships, indexes, and denormalization, as well as techniques for optimizing database queries and managing scalability challenges. The principles discussed in this chapter can be applied to various database management systems and can be useful for designing a schema that meets the demands of modern data-intensive applications. 2023, IGI Global. All rights reserved. -
Designing Artificial Intelligence-Enabled Training Approaches and Models for Physical Disabilities Individuals
The focus of this research is on investigating AI-based strategies and models that can be used to develop workforce training systems specifically for individuals with physical disabilities. The goal is to leverage the advancements in artificial intelligence (AI) and its potential impact on workplace learning and development. There is an increasing demand for utilizing AI capabilities to design comprehensive training programs that are both inclusive and effective for people who face physical challenges. The research will examine effective strategies, real-life examples, and current AI-based training platforms for people with physical disabilities. Additionally, it aims to tackle the obstacles and ethical matters linked to incorporating AI in workforce training. These concerns include mitigating biases, ensuring accessibility, and safeguarding privacy. The outcomes of this study will assist in creating progressive approaches and frameworks driven by AI that can empower individuals with physical disabilities by improving their employability prospects while simultaneously fostering inclusivity within workforce training. The chapter will also explore the integration of AI-powered solutions in training programs for physically challenged individuals. By utilizing AI technologies like personalized learning algorithms, predictive analytics, and adaptive content delivery systems, training can be customized to cater to the unique requirements and learning needs of everyone. The implementation of AI has the potential to automate processes, analyze data effectively, and generate personalized learning pathways for improved accessibility. 2024 selection and editorial matter, Alex Khang; individual chapters, the contributors. -
Designing Bifunctional Electrocatalysts Based on Complex Cobalt-Sulfo-Boride Compound for High-Current-Density Alkaline Water Electrolysis
In the quest to harness renewable energy sources for green hydrogen production, alkaline water electrolysis has emerged as a pivotal technology. Enhancing the reaction rates of overall water electrolysis and streamlining electrode manufacturing necessitate the development of bifunctional and cost-effective electrocatalysts. With this aim, a complex compound electrocatalyst in the form of cobalt-sulfo-boride (Co-S-B) was fabricated using a simple chemical reduction method and tested for overall alkaline water electrolysis. A nanocrystalline form of Co-S-B displayed a combination of porous and nanoflake-like morphology with a high surface area. In comparison to Co-B and Co-S, the Co-S-B electrocatalyst exhibits better bifunctional characteristics requiring lower overpotentials of 144 mV for hydrogen evolution reaction and 280 mV for oxygen evolution reaction to achieve 10 mA/cm2 in an alkaline electrolyte. The improved Co-S-B performance is attributed to the synergistic effect of sulfur and boron on cobalt, which was experimentally confirmed through various material characterization tools. Tafel slope, electrochemical surface area, turnover frequency, and charge transfer resistance further endorse the active nature of the Co-S-B electrocatalyst. The robustness of the developed electrocatalyst was validated through a 50 h chronoamperometric stability test, along with a recyclability test involving 10,000 cycles of linear sweep voltammetry. Furthermore, Co-S-B was tested in an alkaline zero-gap water electrolyzer, reaching 1 A/cm2 at 2.06 V and 60 C. The significant activity and stability demonstrated by the cobalt-sulfo-boride compound render it as a promising and cost-effective electrode material for commercial alkaline water electrolyzers. 2024 The Authors. Published by American Chemical Society. -
Designing Biomass Rice Husk Silica as an Efficient Catalyst for the Synthesis of Biofuel Additive n-Butyl Levulinate
The conversion of lignocellulosic biomass levulinic acid to biorefinery platform organic component n-butyl levulinate is done by an eco-friendly process. The catalyst used for this reaction was prepared by an innovative strategy of impregnating CeO2 and Sm2O3 on silica derived from rice husk, biomass of low economic value, using different methods. The impregnation of ceria and samaria into the silica framework led to a change in the textural properties which was confirmed by various spectroscopic methods. A comprehensive study of the influence of reaction parameters on the esterification of levulinic acid with n-butanol revealed the optimum conditions for maximum yield and selectivity. In the solvent-free condition, the reaction achieved 94.9% conversion of levulinic acid and 97.2% selectivity of n-butyl levulinate within a duration of 1.5h. The regenerated catalysts were stable and efficient up to four cycles. [Figure not available: see fulltext.]. 2020, Springer Science+Business Media, LLC, part of Springer Nature. -
Designing coordinatively unsaturated metal sites in bimetallic organic frameworks for oxygen evolution reaction
Metal organic frameworks (MOFs) are developing as promising catalysts for oxygen evolution reactions. A bimetallic electrocatalyst MOF using Ni and Cu as metal sources and 1,4-benzene dicarboxylic acid as a linker has been synthesized and evaluated for oxygen evolution reaction. Compared to monometallic MOFs, bimetallic MOFs participate more actively in electrocatalysis due to the higher abundance of active sites, local crystallinity, and lower long-range disorder. When utilized as oxygen evolution catalysts, NiCu MOFs have a low overpotential of 340 mV at 10 mA/cm2 and a low Tafel slope of 65 mV/dec. The study paves the way for the development of highly efficient catalysts for water splitting applications. 2023 Elsevier Ltd -
Designing culture through the human resource functions
Human resource management now plays an active strategic partner role instead of being a passive observer. Today, the HR department of an organization is expected to drive organization performance through the biggest strength of the firm; its people. It is expected that all HR functions will contribute to the company's strategic goals and foster an inclusive and productive work environment. The current study is based on data gathered from the hotel industry and aims to comprehend how HR functions impact various aspects of organisational culture. The findings point to important connections between specific HR procedures and cultural elements. The results offer insight into how HR specialists can use their roles to establish the ideal atmosphere within the company. 2025, IGI Global Scientific Publishing. -
Designing Emotionally Adaptive Chatbots for Diverse Users: A User-Centered Human-AI Interface Framework
Recent advancements in conversational AI have improved task efficiency but often neglect the emotional and cognitive diversity of users. This research introduces a novel, user-centered framework for emotionally adaptive chatbots that integrates ML-based emotion recognition with personalized responses that are ethically filtered meaning they are designed to respect user privacy, fairness, and transparency principles. The Berlin Emotional Speech Database (EmoDB) was used to train and evaluate three machine learning models using MFCC features. Among them, the XGBoost model achieved the highest classification accuracy of 77.6%, outperforming Random Forest (75.0%) and SVM (68.2%). To evaluate user experience, a dataset of 385 participants was generated using a 15-item Likert-scale questionnaire adapted from the UTAUT model and extended with trust and emotional alignment measures. Statistical tests, including a t-test (p = 0.711) between neurodiverse and non-neurodiverse users and an ANOVA (p = 0.337) across domains, confirmed the consistency and inclusivity of perceived satisfaction. Visual analytics, including correlation heatmaps and radar charts, revealed that users with predicted emotions such as happiness and neutral reported the highest satisfaction scores (mean = 4.49, SD = 0.29 and mean = 4.26, SD = 0.31, respectively). A seven-layered modular architecture was proposed, supporting real-time emotional adaptivity, personalization, and ethical compliance. The framework is integration-ready with NLP engines like GPT and Dialogflow, offering a scalable solution for affective AI deployment across healthcare, education, and public service domains. Author(s) 2026. This work is distributed under https://creativecommons.org/licenses/by-sa/4.0/.