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An Exploratory Analysis of Neuromarketing Techniques and Their Impact on Consumer Purchase Decisions
Neuromarketing has been playing a signification role in consumers purchase decisions. It has played a significant role in the area of business, especially in the area of marketing. Today every medium and large-scale company is using neuromarketing to promote their product and to influence the purchase decision of the consumer. The study aims to assess the impact of neuromarketing on customers and its influence on the purchase decision of the consumer. The study has employed various statistical tools and analyses to conduct the study. The study highlights the importance of using neuromarketing in business and marketing activities, by ensuring transparency to build the trust of the consumer. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
An Exploration of the Symbolic Power of Sand Play and Well-Being in Children: Analysis of Sand Play
This book chapter attempts to understand childrens inner world through the images, symbols, colors, and themes in their Sand Play. This essay covers sand play (both dry and wet sand tray) sessions of children during play therapy sessions. It provides an overview of the context of sand play, including background information, client referral, developmental age, the Play Therapy Dimension Model (PTDM), neuroscience, symbolism used, positioning, and placement of the symbols. This book chapter on SAND TRAY helps to engage effectively with children in line with PTDM, integrating theory into practice, understanding the therapists position and movement in the therapeutic process, and approaches using PTDM. Copyright 2026 by IGI Global Scientific Publishing. All rights reserved. No part of this publication may be reproduced, stored or distributed in any form or by any means, electronic or mechanical, including photocopying, without written permission from the publisher. Use of this publication to train generative artificial intelligence (AI) technologies is expressly prohibited. The publisher reserves all rights to license its use for generative AI training and machine learning model development. -
An exploration of the impact of Feature quality versus Feature quantity on the performance of a machine learning model
About 0.62 trillion bytes of data are generated every hour globally. These figures have been increasing as a result of digitalization and social networks. Some data ecosystems capture, store, and manage this big DATA. The basis is to be able to analyze their information and extract their value. This fact is a gold mine for companies researching and using this data. This leads us to follow how essential and valuable data is in this growing age. For any machine learning model, the selection of data is necessary. In this paper, several experiments have been performed to check the importance of data quality vs. data quantity on model performance. This clearly indicates comparing the data's richness regarding feature quality (e.g., features in images) and the amount of data for any machine learning model. Images are classified into two sets based on features, then removing redundant features from them, then training a machine learning model. Model getting trained with non-redundant data gives highest accuracy (>80%) in all cases versus the one with all features, proving the importance of feature variability and not just the feature count. 2023 IEEE. -
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An exploration of python libraries in machine learning models for data science
Python libraries are used in this chapter to create data science models. Data science is the construction of models that can predict and act on data, which is a subset of machine learning. Data science is an essential component of a number of fields because of the exponential growth of data. Python is a popular programming language for implementing machine learning models. The chapter discusses machine learning's role in data science, Python's role in this field, as well as how Python can be utilized. A breast cancer dataset is used as a data source for building machine learning models using Python libraries. Pandas, numpy, matplotlib, seaborn, scikitlearn, and tensorflow are some Python libraries discussed in this chapter, in addition to data preprocessing methods. A number of machine learning models for breast cancer treatment are discussed using this dataset and Python libraries. A discussion of machine learning's future in data science is provided at the conclusion of the chapter. Python libraries for machine learning are very useful for data scientists and researchers in general. 2023, IGI Global. All rights reserved. -
An exploration of attitudes toward dogs among college students in Bangalore, India
Conversations in the field of anthrozoology include treatment and distinction of food animals, animals as workers versus pests, and most recently, emerging pet trends including the practice of pet parenting. This paper explores attitudes toward pet dogs in the shared social space of urban India. The data include 375 pen-and-paper surveys from students at CHRIST (Deemed to be University) in Bangalore, India. Reflecting upon Serpells biaxial concept of dogs as a relationship of affect and utility, the paper considers the growing trend of pet dog keeping in urban spaces and the increased use of affiliative words to describe these relationships. The paper also explores potential sex differences in attitudes towards pet and stray dogs. Ultimately, these findings suggest that the presence of and affiliation with pet dogs, with reduced utility and increased affect, is symptomatic of cultural changes typical of societies encountering the second demographic transition. Despite this, sex differences as expected based upon evolutionary principles, remain present, with women more likely to emphasize health and welfare and men more likely to emphasize bravery and risk taking. 2019 by the authors. Licensee MDPI, Basel, Switzerland. -
An exploration of 'pull' and 'push' motivational factors among transgender entrepreneurs
To date, studies have focused on the men and women entrepreneurs and the gender difference in motivations among cisgender entrepreneurs. The study aims to determine whether a transgender individual entrepreneur is motivated through a push motivational factor or a pull motivational factor. This study employs a qualitative approach uses face-to-face interviews and a semi-structured interview with a sample size of 16 transgender entrepreneurs in India. It was found that the participants in this study were motivated by both push and pull factors. The motivational factors, which add to the knowledge of already existing push and pull factors, were to forego begging and commercial sex work, to break stereotypes, to create a business opportunity for other transgender individuals, to earn respect from society, to prove entrepreneurship is non-binary, to be a role model for other transgender individuals and to the society. In contrast, the push motivational factors were the limited opportunities, support received from society, the hijra guru, media, government support, family, friends, landlords, NGOs and another push motivational factor was the exhibitions conducted exclusively for the transgender individual entrepreneurs. 2025 Inderscience Enterprises Ltd. -
An exploration of 'pull' and 'push' motivational factors among transgender entrepreneurs
To date, studies have focused on the men and women entrepreneurs and the gender difference in motivations among cisgender entrepreneurs. The study aims to determine whether a transgender individual entrepreneur is motivated through a push motivational factor or a pull motivational factor. This study employs a qualitative approach uses face-to-face interviews and a semi-structured interview with a sample size of 16 transgender entrepreneurs in India. It was found that the participants in this study were motivated by both push and pull factors. The motivational factors, which add to the knowledge of already existing push and pull factors, were to forego begging and commercial sex work, to break stereotypes, to create a business opportunity for other transgender individuals, to earn respect from society, to prove entrepreneurship is non-binary, to be a role model for other transgender individuals and to the society. In contrast, the push motivational factors were the limited opportunities, support received from society, the hijra guru, media, government support, family, friends, landlords, NGOs and another push motivational factor was the exhibitions conducted exclusively for the transgender individual entrepreneurs. 2025 Inderscience Enterprises Ltd. -
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An Explainable AI-Driven Deep Learning Algorithm for Heart Disease Detection in Healthcare
The application of preprocessed Kaggle data serves as a subject of analysis to investigate heart attack prediction capabilities through machine learning models. The research examines performance outcomes of five algorithms which consist of K-Nearest Neighbors (KNN), Random Forest, Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost) and Convolutional Neural Networks (CNN). Random Forest together with XGBoost proved as the most accurate machine learning models when used for cardiovascular risk assessment. The researchers built a hybrid structure of CNN and SVM because it improved both data classification and feature extraction processes for better prediction outcomes. The training and evaluation process of models encountered difficulties because of overfitting along with high computational expenses and problems regarding optimal hyperparameter settings. The research stresses that explainable AI (XAI) methods should integrate into systems to enhance model interpretability and achieve trust from clinical professionals. Future initiatives seek real-time patient monitoring and innovative interpretability systems for heart attack prediction to enable person-specific diagnoses and optimal clinical choices in medical fields. 2025 IEEE. -
An explainable AI-based framework for predicting and optimizing blast-induced ground vibrations in surface mining
Blast induced ground vibrations (BIGV) pose critical challenges in surface mining, threatening structural integrity, worker safety, and environmental compliance. This study proposes a novel hybrid artificial intelligence (AI) framework that integrates physics informed neural networks (PINNs) with conventional machine learning (ML) algorithms for the accurate prediction and optimization of BIGV. Unlike empirical equations that lack generalizability or black box ML models with limited transparency, the proposed approach embeds domain specific physical laws while leveraging data driven learning to improve both predictive accuracy and interpretability. A multiobjective optimization scheme is employed to balance competing goals: minimizing peak particle velocity (PPV), maximizing fragmentation efficiency, and reducing operational costs. Crucially, the framework incorporates Explainable AI (XAI) techniques such as Shapley Additive Explanations (SHAP) and Local Interpretable Model Agnostic Explanations (LIME) and uncertainty quantification (UQ) methods based on Bayesian Neural Networks to provide insight into model decisions and confidence in predictions. Validation across five operational mines in the Godavari Valley Coalfields (India) demonstrates strong generalizability, achieving up to a 20% reduction in RMSE compared to empirical baselines. The improvement is statistically significant (p<0.01) as confirmed through a paired t-test across cross-validation folds. These findings highlight that a physics informed, explainable, and uncertainty aware AI framework can substantially improve vibration prediction, ensure regulatory compliance, and support safer, more sustainable blasting operations in modern surface mining. 2025 The Author(s) -
An Explainable AI Techniques for Advancing Diabetes Prediction Using Machine Learning
Researchers have developed an automated system to identify diabetes risk. This system combines data from two sources: a collection of female patients in Bangladesh and an expanded dataset from a local textile factory. The expanded dataset includes information from 203 additional patients. The system uses several techniques to improve its accuracy. It first identifies the most important factors for predicting diabetes, then employs a special model to estimate insulin levels. It also addresses challenges like imbalanced data (where one outcome is more common) and explains its predictions using artificial intelligence techniques. This system achieved the superlative results has an 81.0% accuracy rate, 0.812 F1 score, and 0.844 Area Under the Curve (AUC).. These metrics indicate strong performance in identifying diabetes risk. 2025 IEEE. -
An Expert System for Diabetes Diagnosis
Expert system is a computer system that emulates the decision making ability of a human expert. That is it acts in all respects like a human expert. It uses human knowledge to solve problems that would require human intelligence. The expert system represents expertise knowledge as data or rules within the computer. These rules and data can be called upon when needed to solve problems. Diabetes is a knotty disease and very common in the modern world. Diabetes is a serious disease that affects almost every organ in the body like heart, eyes, kidney, skin, nerves, blood vassals, foot etc. If left the disease unchecked it will make serious complications including death. Though the disease can not possible to cure completely, it can be well managed or control and can lead a very healthy life. Early diabetes diagnosis plays a crucial role in diabetic control, and can prevent further medical complications. This paper presents the design and development of medical expert system for Diabetes disease and it support diagnosis, give information about complications and act as diabetes trainer. It used rule based approach to collect data and forward chaining inference technique. This system provides a user interactive, menu driven environment. Symptoms and risk factors associated with diabetes are taken as the basis of this study. In case of diagnosis the system will ask a bunch of questions about the symptoms and risk factors to the expert system user and user should give yes or no answer. According to the answer the system will make judgment about the possibility of illness, how much severe it is like slight chance, moderate chance, high chance, very high chance, diabetic or not. If the user wants to know the details of diabetes complications he can select the complication option from the menu. It can also used in teaching practice. The system is drawn up with CLIPS expert system building tool version 6.3 and in Windows/Dos environment. -
An experimental study on utilisation of red mud and iron ore tailings in production of stabilised blocks
Construction of bricks using waste materials is one among the many ways to address the problems encountered in infrastructure. In the present study, various industrial and mining wastes have been used to manufacture stable bricks. These wastes include red mud (RM) from Hindalco, and iron ore tailings (IOT) from BMM Ispat, Bellary. Both RM and IOT were combined in different proportions with ground-granulated blast furnace slag (GGBS) and waste lime. In first series, IOT was replaced in the range of 45% to 60% with increments of 5%, and RM was replaced in the range of 15% to 30% with increments of 5%. In the second series, RM was replaced in the range of 45% to 60% with increments of 5%, and IOT was replaced in the range of 15% to 30% with increments of 5%. Tests were performed as per the Indian and ASTM standards on both the raw material and the developed composites. These tests include liquid, plastic limit, particle size, XRF, XRD, and SEM on raw materials, while tests performed on composites were compressive strength, water absorption, efflorescence, porosity, apparent specific gravity, and bulk density. Results of the study indicate that addition of IOT up to 55% is acceptable as brick material. Springer Nature Singapore Pte Ltd 2020. -
An Experimental Study on Improving Speaking Skills Through the Integration of Existential Intelligence for Post Graduate Learners of Business Studies
Within the field of ESP, the constrained access to discipline-specific materials has intensified the demand, emphasizing an acute necessity for refining speaking skills, particularly in conversational contexts. This reflects an evolving paradigm, emphasizing the critical need for refined and specialized speaking competencies within their scholarly domain. The dissertation examines the use of a learning module created for Postgraduate students of Business studies to improve their speaking skills. The study uses Task based Language Teaching (TBLT) approach and excerpts from Literature for pedagogical instruction, employing Dialogic Inquiry Model (DIM) as a framework and using Existential Intelligence as a guiding lens. Language and Intelligence are closely intertwined. Educational Psychologist Howard Gardner posed a challenge to the conventional notion of Intelligence which supported higher IQ based tests by introducing the Theory of Multiple Intelligences. Gardner's Intelligence framework initially comprised of seven types. In 1999, he introduced Existential Intelligence (EI), expanding the model to include EI as a half intelligence, but due to its abstract nature and lack of clear brain localization, it has posed challenges for precise quantification. Furthermore, Howard Gardners Intelligence Reframed (1999) was used as the primary text for the study. By contextualizing the study within Higher Education's Business studies domain, it examines how existential principles influence the development of speaking skills. Additionally, it explores how these principles contribute in shaping aspiring business entrepreneurs, providing added motivation to instill a sense of purpose which will enhance their managerial attributes. The research argues that infusing unexplored existential elements into the curriculum can stimulate critical thinking among Business Studies students, resulting in notable improvements in specific speaking dimensions like Fluency, Turn-Taking, Presentation and Negotiation skills (FTPN). Moreover, it highlights the pivotal role of this integration in reshaping ESP curricula to better cater to the unique needs of learners in this discipline. The research comprised of two cohorts of students. The first cohort consisted of first- year postgraduate students pursuing Business Studies at Sinhagad Institute of Management (SIOM), Pune while the second cohort included students from CHRIST Deemed to be University) Pune Lavasa Campus, resulting in a cumulative total of approximately 68 participants. The study extended over a 15-day duration to facilitate the completion of a comprehensive 30-hour module for both the phases separately. The study employs a mixed-method approach by combining qualitative and quantitative analysis. For the qualitative study, the analysis involved researchers observations and an examination of Achievement tests questionnaires employing the Likert scale. For quantitative analysis, a series of six Task-Based Language Teaching (TBLT) activities were conducted, encompassing pre and post achievement tests, each of which was assessed based on the study's objectives. The assessment tool utilized is the Communicative Skills Rating Scale (CSRS) by Spitzberg and Cupach (2002), featuring a four-tier evaluation system: self, partner, observer, and external evaluations. Data was collected via Audio-Visual methods for documentation purposes and to cross-reference any overlooked data during the concurrent evaluation process. The collected data underwent a systematic analysis to investigate how applying EI principles can improve conversational speaking skills. The efficacy of the learning module was evaluated based on the proficiency demonstrated in TBLT activities concerning FTPN skills. TBLT activities were administered both prior to and subsequent to the completion of each unit. The assessment of the effectiveness of classroom pedagogy (independent variable) was gauged through the researcher's observations and achievement test questionnaires. Simultaneously, the evaluation of participants' specific conversational skills (dependent variable) was evaluated and analyzed through the course of experimental study using CSRS evaluation scale. Data was analysed using Descriptive statistics through Excel and it was verified using R programming. The research delineates apparent improvements in FTPN within the DIM framework upon the integration of this intervention. Noteworthy enhancements also included a heightened motivation levels across the sample population. Both fast and slow learners exhibited advancements, with a more pronounced improvement observed among the latter group. Additionally, significant strides were observed in non-verbal proficiencies, notably in body posture, and refined listening and responsive non-verbal skills, which was a byproduct of the intervention. Also, a Gender-based analysis revealed an overall positive trend in both male and female students, yet a comparatively greater enhancement was evident among male students in assimilating and applying these interventions. The analysis of data obtained from the CSRS tool shows statistically significant influence on overall English anguage production of the participants in terms of FTPN variables. Moreover. progress tests provided statistically significant evidence for the efficacy of the researcher- developed learning module based on TBLT and DIM approach integrated using EI subsets. Each phase of participants underwent separate experimentation and assessment of their proficiency both before and after the intervention. The pre-achievement test revealed inadequate speaking skills and a lack of basic conversational understanding in both cohorts. Phase 1 (SIOM) showcased noticeable improvement, with a growth in Fluency (39.7%), Presentation (32.1%), Negotiation (37.3%), and Turn-Taking (38.5%) using the CSRS tool. Fast learners improved by an average of 24.1%, while slow learners showed a significant average increase of 51% from their pretest scores. Moreover, there was a 15.7% increase in motivation levels during the intervention. Group 2 (CUL) exhibited improvements in Fluency (36.35%), Presentation (35.8%), Negotiation (43.7%), and Turn-taking (40.5%). Fast learners increased by an average of 26.9%, and slow learners saw an average increase of 49.6% from their pretest scores. Additionally, there was an 18.2% spike in motivation levels during the intervention. Overall, the analysis of CSRS data and progress tests strongly supports the effectiveness of the researcher-developed learning module based on existential principles. It significantly enhanced oral participation and achievement of learning outcomes across both groups. The results through the post-achievement test showed that the researcher-developed learning module had a statistically significant influence on overall English language production in the participants. In educational psychology, Multiple Intelligence has garnered substantial research attention for its application in ESL/EFL and broader school curricula, particularly in teaching English and various subjects. However, the integration of Existential Intelligence within the context of ESP remains unexplored. Its potential significance and applicability within higher education for business students could be substantial. This intelligence category, rooted in philosophy, mysticism, aesthetics, and related domains, aligns closely with the fundamental realms of interest for MBA students. Its introduction could offer profound implications for their learning experience and academic endeavors. The research attempts to contribute to the growing field of English for Specific Field ix for Business students by situating the study within the Pune district of Maharashtra by analysing only FTPN which further offers scope for exploration. -
An experimental study on improving speaking skills through the integration of existential intelligence for post graduate learners of business studies
"Within the field of ESP, the constrained access to discipline-specific materials has intensified the demand, emphasizing an acute necessity for refining speaking skills,
particularly in conversational contexts. This reflects an evolving paradigm, emphasizing the critical need for refined and specialized speaking competencies within their
scholarly domain. The dissertation examines the use of a learning module created for Postgraduate students of Business studies to improve their speaking skills. The study
uses Task based Language Teaching (TBLT) approach and excerpts from Literature for pedagogical instruction, employing Dialogic Inquiry Model (DIM) as a framework and
using Existential Intelligence as a guiding lens. Language and Intelligence are closely intertwined. Educational Psychologist Howard Gardner posed a challenge to the conventional notion of Intelligence which supported higher IQ based tests by introducing the Theory of Multiple Intelligences. Gardner's Intelligence framework initially comprised of seven types. In 1999, he introduced Existential Intelligence (EI), expanding the model to include EI as a half intelligence, but due to its abstract nature and lack of clear brain localization, it has posed challenges for precise quantification. Furthermore, Howard Gardner’s Intelligence Reframed (1999) was used as the primary text for the study. By contextualizing the study within Higher Education's Business studies domain, it examines how existential principles influence the development of speaking skills. Additionally, it explores how these principles contribute in shaping aspiring business entrepreneurs, providing added motivation to instill a sense of purpose which will enhance their managerial attributes. The research argues that infusing unexplored existential elements into the curriculum can stimulate critical thinking among Business Studies students, resulting in notable improvements in specific speaking dimensions like Fluency, Turn-Taking, Presentation and Negotiation skills (FTPN). Moreover, it highlights the pivotal role of this integration in reshaping ESP curricula to better cater to the unique needs of learners in this discipline. The research comprised of two cohorts of students. The first cohort consisted of first- year postgraduate students pursuing Business Studies at Sinhagad Institute of Management (SIOM), Pune while the second cohort included students from CHRIST Deemed to be University) Pune Lavasa Campus, resulting in a cumulative total of approximately 68 participants. The study extended over a 15-day duration to facilitate the completion of a comprehensive 30-hour module for both the phases separately. The study employs a mixed-method approach by combining qualitative and quantitative analysis. For the qualitative study, the analysis involved researcher’s observations and an examination of Achievement tests questionnaires employing the Likert scale. For quantitative analysis, a series of six Task-Based Language Teaching (TBLT) activities
were conducted, encompassing pre and post achievement tests, each of which was assessed based on the study's objectives. The assessment tool utilized is the Communicative Skills Rating Scale (CSRS) by Spitzberg and Cupach (2002), featuring a four-tier evaluation system: self, partner, observer, and external evaluations. Data was collected via Audio-Visual methods for documentation purposes and to cross-reference any overlooked data during the concurrent evaluation process. The collected data underwent a systematic analysis to investigate how applying EI principles can improve conversational speaking skills. The efficacy of the learning module was evaluated based on the proficiency demonstrated in TBLT activities concerning FTPN skills. TBLT activities were administered both prior to and subsequent to the completion of each unit. The assessment of the effectiveness of classroom pedagogy (independent variable) was gauged through the researcher's observations and achievement test questionnaires. Simultaneously, the evaluation of participants' specific conversational skills (dependent variable) was evaluated and analyzed through the course of experimental study using CSRS evaluation scale. Data was analysed using Descriptive statistics through Excel and it was verified using R programming. The research delineates apparent improvements in FTPN within the DIM framework upon the integration of this intervention. Noteworthy enhancements also included a heightened motivation levels across the sample population. Both fast and slow learners exhibited advancements, with a more pronounced improvement observed among the latter group. Additionally, significant strides were observed in non-verbal proficiencies, notably in body posture, and refined listening and responsive non-verbal skills, which was a byproduct of the intervention. Also, a Gender-based analysis revealed an overall positive trend in both male and female students, yet a comparatively greater enhancement was evident among male students in assimilating and applying these interventions. The analysis of data obtained from the CSRS tool shows statistically significant influence on overall English anguage production of the participants in terms of FTPN variables. Moreover. progress tests provided statistically significant evidence for the efficacy of the researcher- developed learning module based on TBLT and DIM approach integrated using EI subsets. Each phase of participants underwent separate experimentation and assessment of their proficiency both before and after the intervention. The pre-achievement test revealed inadequate speaking skills and a lack of basic conversational understanding in both cohorts. Phase 1 (SIOM) showcased noticeable improvement, with a growth in Fluency (39.7%), Presentation (32.1%), Negotiation (37.3%), and Turn-Taking (38.5%) using the CSRS tool. Fast learners improved by an average of 24.1%, while slow learners showed a significant average increase of 51% from their pretest scores. Moreover, there was a 15.7% increase in motivation levels during the intervention. Group 2 (CUL) exhibited improvements in Fluency (36.35%), Presentation (35.8%), Negotiation
(43.7%), and Turn-taking (40.5%). Fast learners increased by an average of 26.9%, and slow learners saw an average increase of 49.6% from their pretest scores. Additionally,
there was an 18.2% spike in motivation levels during the intervention. Overall, the analysis of CSRS data and progress tests strongly supports the effectiveness of the
researcher-developed learning module based on existential principles. It significantly enhanced oral participation and achievement of learning outcomes across both groups.
The results through the post-achievement test showed that the researcher-developed learning module had a statistically significant influence on overall English language
production in the participants. In educational psychology, Multiple Intelligence has garnered substantial research attention for its application in ESL/EFL and broader school curricula, particularly in teaching English and various subjects. However, the integration of Existential Intelligence within the context of ESP remains unexplored. Its potential significance and
applicability within higher education for business students could be substantial. This intelligence category, rooted in philosophy, mysticism, aesthetics, and related domains,
aligns closely with the fundamental realms of interest for MBA students. Its introduction could offer profound implications for their learning experience and academic endeavors.
The research attempts to contribute to the growing field of English for Specific Field ix for Business students by situating the study within the Pune district of Maharashtra by
analysing only FTPN which further offers scope for exploration. "
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An experimental investigation to study the performance and emission characteristics of n-butanol-gasoline blends in a twin spark ignition engine
The need of a substitute for the fossil fuels has gained maximum importance in the recent days with the depletion of fossil fuels, increasing vehicle population, enforcement of strict pollution norms to ensure a better environment for the present and future generations. Researchers around the world have investigated many fuels for IC engines and have found that alcohols exhibit properties that closely resemble the properties of gasoline. Alcohols form a stable mixture with gasoline in almost all proportions. This property of alcohol has increased its popularity as a fuel blend with gasoline. This paper aims at presenting the performance characteristics of a twin spark ignition engine fuelled with the blends of n-butanol-gasoline. In this investigation, pure gasoline (B00) and blends of gasoline with n-Butanol forms the fuel for twin spark ignition engine. The use of B35 blend, lower carbon monoxide emissions, lower unburnt hydrocarbon and lower nitrogen oxide emissions are observed as compared to pure gasoline. With these investigational results, one can arrive at the conclusions that with the use of higher blends of n-butanol-gasoline, the emission of the regulated emissions are reduced and are seen to be optimal with B35 in a twin spark ignition engine. TJPRC Pvt. Ltd. -
An Experimental Investigation on Flexural Strength of Ferrocement Slab Made of Slag Sand Partially Replaced with Iron Ore Tailings
Effective use of slag sand and Iron Ore Tailings and other waste obtained from the manufacturing industry and mining industry like waste foundry sand, will reduce the negative impact on the environment and also will provide opportunities for effective use of natural resources and contribute to sustainability. The aim of this research project is to study the flexural strength of ferrocement slab made of slag sand partially replaced with iron ore tailings with sustainability point of view. Investigation of 48 slab panels of 700mm 300 mm size with thickness 25 mm and 30 mm was conducted using 1 and 2 layers of weld mesh reinforcement casted with different percentage of iron ore tailings. Slabs were tested in Universal Testing Machine, which showed good results with 15% of iron ore tailings. Published under licence by IOP Publishing Ltd. -
An Expected Model of Management Program in India
Pravara Management Review, Vol 15, Issue 2, pp. 17-23, ISSN No. 0975-7201