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Prefabricated Houses - A Model to Sustainable Housing Market
Effective spatial planning in an urban center is the need of the hour especially for offering affordable and sustainable houses. separate sheet. Spatial planning may help in achieving Sustainable Development goals (SDG) (09) Industry, Innovation and Infrastructure, (11) Sustainable cities and communities, and (15) Life on Land. The prefabricated house model can be used as a strategy in achieving above mentioned SDGs. It is important to study the prefabricated housing market for a country like India, considering its growing population and the necessity of access to affordable and sustainable houses. The main objective of this study is to identify the determinant factors of prefabricated houses and its impact on preference among urban consumers. The study is quantitative in nature and adopts a survey method. SEM model is used to analyze the data. A structured questionnaire is developed based on the objectives of the study. The questionnaire majorly focused on the perception of Sustainability, Affordability, Durability, Barriers, Opportunities, and Quality. The Electrochemical Society -
Single-use Plastic Packaging and Food and Beverage industry's take on it
Micro-plastics created by the gradual breakdown of SUP in oceans have recently been consumed by marine organisms, including fish, shellfish, etc. It is causing significant disturbance to marine life. The environment is littered with food packing. Snack food packaging is a great example of a long-standing, aesthetically obnoxious form of pollution. The majority of SUPs, especially perishable products, wind up in landfills within months of purchase.This is due to a rise in on-the-go food and beverage consumption, fueling the proliferation of single-use plastic packaging. The lack of dumpsters in some areas might contribute to an increase in littering. While the majority of food packaging plastics end up in the trash, municipal waste, landfills, and even the seas, a tiny fraction can be recycled. The reason for this is that poor countries have a prevalent culture of human waste. The Electrochemical Society -
Green Orientation and Customer-Based Brand Equity in FMCG Industry in India
In the recent years, the idea of green-oriented approach gained traction in both academic research as well as corporate research. Companies are now able to identify the long-term benefits of being responsible towards the environment. This paper attempted to understand the relationship between green-orientation of a brand, antecedents of customer based brand equity namely of Aaker's Model with respect to the FMCG Industry in India. Data was collected from 207 FMCG product consumers from India above the age of 18. Person's correlation coefficient and Multiple Linear Regression were calculated to ascertain the relationship between green orientation and the antecedents of CBBE. It was found that Brand Loyalty was the most significant on CBBE whereas Brand Association was the least. The results of this research would be helpful for the brands to take decisions accordingly as it may act as an incentive to be more innovative towards sustainable ways of operating. The Electrochemical Society -
Detection and Classification of Thoracic Diseases in Medical Images using Artificial Intelligence Techniques: A Systematic Review
Artificial Intelligence is at the leading edge of innovation and is developing very fast. In recent studies, it has played a progressive and vital role in Computer-Aided Diagnosis. The chest is one of the large body parts of human anatomy and contains several vital organs inside the thoracic cavity. Furthermore, chest radiographs are the most commonly ordered and globally used by physicians for diagnosis. An automated, fast, and reliable detection of diseases based on chest radiography can be a critical step in radiology workflow. This study presents the conduction and results of a systematic review investigating Artificial Intelligence Techniques to identify Thoracic Diseases in Medical Images. The systematic review was performed according to PRISMA guidelines. The research articles published in English were filtered based on defined inclusion and exclusion criteria. The Electrochemical Society -
Ear Recognition Using ResNet50
Deep learning techniques have become increasingly common in biometrics over the last decade. However, due to a lack of large ear datasets, deep learning models in ear biometrics are limited. To address this drawback, researchers use transfer learning based on various pre-trained models. Conventional machine learning algorithms using traditional feature extraction techniques produce low recognition results for the unconstrained ear dataset AWE. In this paper, an ear recognition model based on the ResNet-50 pretrained architecture outperforms traditional methods in terms of recognition accuracy in AWE dataset. A new feature level fusion of ResNet50 and GLBP feature is also experimented to improve the recognition accuracy compared to traditional features. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Does Packaging Elements Affects Consumers Preference During The Purchase Of Chocolate?
Chocolate is one of the highest consumed products and the packaging of such a product is important. The primary goal of the study is to understand if the packaging of chocolate has an impact on the consumer's preference during the purchase of chocolate. The researcher concentrates on the elements of packaging which are the color of the packaging, shape, and size of the packaging, labeling information on the packaging, and the material of packaging. The study helps the producer to understand what factors on the packaging impacts the customer during the purchase of chocolate. The researcher concentrates on how these elements of packaging play a role in affecting the consumer at the point of purchase of chocolate. Through this study one will be able to deliver the product i.e., chocolate more efficiently and effectively way to the consumers or the buyers. The Electrochemical Society -
Carbon Dioxide Neutralization across the Global Supply Chain
The increased impacts of climatic changes and global warming has led many organizations to adopt green initiatives in several areas of their business processes. Many multinational companies are moving towards reduction of carbon emission across its various operations. Carbon neutrality is the process where steps are taken to achieve net zero carbon dioxide emissions. This article proposes measures to achieve carbon neutrality across the supply chain globally. As part of its sustainability initiative, organizations have decided to reduce carbon consumption across their plants. This calls for estimation of carbon dioxide emissions and reducing the carbon footprint in the entire supply chain process. It also involves gauging Green House CO2 emissions during the transportation process for all TMC regions and Transportation models used by various companies. The main calculations include total CO2 emissions, CO2 Emissions per Ton. Of Goods Transported, CO2 Emissions per Transport Km. These calculations are done based on factors such as Full Truck Load, Less Truck Load, Sea mode of transportation and Air mode of transportation. An analysis is performed on the resulting calculation figures for different modes of transportation such as road, air and sea. The analysis shows that there is an increase in overall CO2e for Air mode of transportation. The least increase in overall Co2 is Sea mode of transportation. Through this analysis, it helps the company to take better decisions regarding the mode of transportation that they need to adopt to achieve carbon neutrality. The Electrochemical Society -
Retention of a Community Healthcare Worker for Three Decades in a Rural and Remote CHC of Bolba in Jharkhand: A Case Study
The dearth of healthcare personnel in rural areas is a global problem. Even developed countries are struggling to meet demand. In such circumstances, identifying a health worker who worked for a single CHC for three decades necessitates deeper exploration. Individual case studies were employed to investigate the phenomenon, then thematically evaluated using QAD Miner Lite following a lengthy telephonic interview. The study's findings revealed that a rural upbringing, social class, economic factors, and behaviourism influenced the altruism of Community Healthcare Workers (CHWs). As a result, external and internal factors influenced CHW to service rural areas. But extrinsic factors worked in tandem with intrinsic factors to influence CHW's willingness to serve the rural areas. Rural healthcare shortages exist despite the National Rural Health Mission (NRHM) execution. A substantial amount of the population's health is entrusted to 20 percent of health workers, who account for disproportionately 75.05 percent of rural health outcomes. The Electrochemical Society -
Design of Computationally Efficient IFIR based Filter Structure for Digital Channelizer'
A low computational complexity digital channelizer is essential for a wide band system. FRM is a widely used method to generate a sharp transition width sub-bands or channels in a digital channelizer. The aim of this work is to design a uniform and non-uniform sharp transition width FIR filter bank with low computational complexity compared to FRM based digital channelizer. The design parameters of the proposed structure are evaluated in an efficient way. The proposed structure is designed based on IFIR filter and complex exponential modulation technique (CEMT). The performance of the proposed structure is demonstrated with the help of an example. Results show that the number of multipliers of the proposed structure is less compared to other existing methods. 2022 IEEE. -
Bioprospecting of Fungal Endophytes in Hulimavu Lake for Their Repertoire of Bioactive Compounds
Fungal endophytes hold a prominent position in the research world, in part due to the rich repertoire of bioactive compounds useful for industrial and environmental applications. The present study aims at bioprospecting few endophytic fungi isolated from Hulimavu lake flora (Bengaluru) for characterization of biological applications of their bioactive compounds. Among the lake plants screened, Alternanthera philoxeroides, Ricinus communis and Persicaria glabra were taken forward for isolation of fungal endophytes. Subsequent biochemical analyses were performed to quantify few fungal enzymes and bioactive compounds, followed by antimicrobial and cytotoxic assays. In conclusion, this pilot study aims to probe the plethora of bioactive compounds present in fungal endophytes that possess wide ranging biological properties. Due to the species richness and diversity of fungal endophytes across different host plants and habitats, bioprospecting fungal endophytes remains a very extensive yet promising topic for research, representing broad ranging environmental and industrial applications. The Electrochemical Society -
Mechanical strength and water penetration depth of palmyra fibre reinforced concrete
Natural fibre reinforced composites are replacing the conventional fibre reinforced composites for several applications due to natural fibre availability, variety and lesser raw material cost. Using natural fibres in composites also reduces the issue of agricultural residue disposals, which are in abundance. Different natural fibres exhibit unique properties when it is used in composites and hence there is a need to study the behaviour of scarcely used natural fibres. Indian palmyra trees (Borassus flabellifer) are fast growing commonly found trees in Southern India. From the base of these palm tree leaves, palmyra fibres are taken out. Though these fibres are locally available in huge quantities, these are very rarely used as reinforcing material in concrete compared to other natural fibres like coir, sisal, jute etc. Palmyra fibre reinforced cement composite specimens were prepared by varying the fibre content (0.5%, 1% and 2% by weight of cement) and length of fibre (25 mm and 50 mm). Plain concrete and palmyra fibre reinforced concrete specimens of identical size were tested for mechanical strength and also for its depth of water penetration. The work carried out revealed that the water penetration of palmyra fibre reinforced concrete increased with fibre content increase. The compressive strength of palmyra fibre reinforced concrete improved up to 1% of fibre content and further increase in fibre content upto 2% resulted in compressive strength reduction for both the fibre lengths. However, split tensile strength, flexure strength and shear strength increased with fibre content increase in the mix. Based on the mechanical strength properties investigated, increase in shear strength was found to be more significant with the inclusion of palmyra fibres in concrete. 2022 -
LGBT inclusion in UNSDGs - Has the Situation Improved for Sexual Minorities at Indian Workplaces?
In India, the acceptance of the sexual minorities has been considerably poor and challenging owing to societal biases and traditional misinformation. Speaking of workplaces in India, sexual minorities find it relatively difficult to have a complete breakthrough in these existing waves of biases as the policies are not that effective to help them survive in such competitive environment. The authors through this article have presented a qualitative account depicting an in-depth analysis of experiences that the sexual minorities have had in their workplaces. The paper examines the current situation of sexual minority employees at Indian workplaces after inclusion of the Universal value in UNSDGs. The authors in this paper have studied the existing issues that the sexual minorities are still facing in their respective workplaces further comparing it with the sustainable development goals on the grounds of the implicated hindrances that the practice imposes on the aim of United Nations. The Electrochemical Society -
A Systematic Review on Features Extraction Techniques for Aspect Based Text Classification using Artificial Intelligence
Aspect Extraction is an important, challenging, and meaningful task in aspect-based text classification analysis. To apply variants of topic models on task, while reasonably successful, these methods usually do not produce highly coherent aspects. This review presents a novel neural/cognitive approach to discover coherent methods. They exploited the distribution of word co-occurrences through neural/cognitive word embeddings. Unlike topics that typically assume independently generated words, word embedding models encourage words that appear in similar factors close to each other in the embedding space. Also, use an attention mechanism to de-emphasize irrelevant words during training, improving aspects coherence. Methods results on datasets demonstrate that the approach discovers more meaningful and coherent aspects and substantially outperforms baseline. Aspect-based text analysis aims to determine people's attitudes towards different aspects in a review. The Electrochemical Society -
A Study of Investment Behavior Of Economically Weaker Section (EWS) Investors
While investing, it is most important for an investor that he/she understand and follows the basic principles of investing to gain maximum advantages out of it. The present study analyzes the investment behavior of 190 economically weaker section (EWS) investors and rank their preferences and reasons using Garret ranking. The study observes that investors prefer to invest in traditional investment avenue over modern avenue due to lack of awareness and ease of investing across demographics. Results of ANOVA inform a small shift to mutual funds and change in perceived risk and return behavior in selected age, income and education category. The study recommends for opening of dedicated small financial planning centers/branches/kiosks etc to increase their awareness level and participation so that they can gain maximum advantages from their investment. The Electrochemical Society -
Sustainable Development- Adopting a Balanced Approach between Development and Development Induced Changes
The emergence of globalization has raised serious concerns and promoted ever increasing dichotomy between development and climate change issues that are borne out of such trade development plans and strategies. The sustainable development goals embark on 17 broad categories that calls upon the nations to achieve them by 2030. In order to achieve these goals the need of the hour is to make a paradigm shift from traditional trade agreements and policies to such agreements that aim to prioritize the attainment of these goals. There has to be uniform environment laws to promote intergeneration and intra-generational equity among the nations and leaving no lacuna for geographical disparity. The Artificial Intelligence can play a pivotal role in achieving sustainability by cross fertilization of technology and sustainable development leading to smart states, effective utilization of resources, green investment policies, use of eff icacious renewable energy resources, analyzing agricultural needs and prior analyses of prospective disasters. The Electrochemical Society -
Ethnic Food: A Solution With Sustainable Food Resources A Study On Consumer Awareness Of Ethnic Food And Its Impact On Consumption Attitude
Food has seen numerous transformations over the centuries and has been a focus of study pertaining to culture and evolution. Besides being a celebration of diversity and a marker of human adaptations, food is also a broad knowledge domain that represents various geographic, cultural and lifestyle outlooks. Ethnic food relates to a heritage or the culture of an ethnic group with them incorporating the local produce and animal sources into their diet. Ethnic food also has a sustainability aspect to it in terms of food miles and carbon emissions since more transportation involved means higher level of GHG released, economic aspect such as with composition changes and food security, and community relationship. This paper finds that when consumer awareness of ethnic food increases, the consumption attitude towards it does, too. This could be of importance in policy implementation and identifying sustainability systems. A connection with the land and a community relationship involving food could help represent more ethnic food, to increase awareness on a global level and also allow more people to experience these vast cultural diversities. If understood well and implemented, ethnic food could be of use as a tourism brochure, sustainability driver, economical promoter and community supporter. The Electrochemical Society -
Performance analysis of Clustering algorithms for dyslexia detection
Clustering algorithms plays vital role in analysing and evaluating vast number of high dimensional health care data ranging from medical data repositories, clinical data, electronic health records, body sensor networks, IoT devices, and so on. Dyslexia, a learning disorder is a common problem that is found in children during the initial stages of formal education, which is detected as mild to severe. It can also be one of the reasons of failure in the school. According to the literature this difficulty is commonly seen among Special Education Need children. There are few studies focussed on the application of classification algorithms for detecting the presence of dyslexia. This paper focusses one of SDG, goal 4:Quality Education, as dyslexic students can be given equal and quality education. Analyses of an online gamified test-based dataset is done by applying various clustering techniques such as K-means, Fuzzy c-means, and Bat K-means to assess their effectiveness in detecting the problem dyslexia. As the dataset is large, it is observed that usage of clustering methods gives us gain insight into the distribution of data to observe characteristics of each cluster. The clustering results are evaluated using root mean squared error (RMSE), mean absolute error (MAE), Xie-Beni index and it is found K Means outperforms FCM, Bat K Means algorithm for analysing different levels of the learning disorder. The Electrochemical Society -
The Empirical Analysis of Machine Learning Approaches for Enhancing the Cyber security for better Quality
In recent years, there have been significant advances in both technologies tactics so in area of cyber security, with (ML) machine learning at the forefront of the transformation. It is the ability to obtain security event characteristics or findings from cyber security information and then develop a matching information model that will allow a security system to become autonomous and smart. The widespread proliferation and the usage of Web and Smartphone applications has increased the size of cyber world as a consequence. When a computerized assault takes too long to complete, the internet becomes vulnerable. Security measures may be improved by recognizing and reacting to cyber-attacks, thanks to cyber security techniques. Security measures that were previously used aren't any longer appropriate because scammers have learned how to evade them. It is getting more difficult to detect formerly unknown and unpredictable security breaches, which are growing more widespread. Cyber security is becoming more dependent on machine learning (ML) techniques. Machine learning algorithms' dependability remains a major challenge, given its continual advancement. It is possible to find malicious hackers in internet that are ready to exploit ML defects that have been made public. A thorough review of machine learning techniques safeguarding cyberspace against attacks is provided in this paper, which presents a literature review on Cyber security using machine learning methods, such as vulnerability scanning, spam filtering, or threat detection on desktop networks as well as smart phone networks. Among other things, this paper provides brief descriptions of each machine-learning technique and security info, essential machine-learning technology, and evaluation parameters for a classification method. 2022 IEEE. -
Real-Time Traffic Sign Detection Under Foggy Condition
Traffic congestion becomes high in urban areas and using public and private transportation services. The image of traffic signs gets affected by fog, and the detection of traffic signs has become difficult. To solve this issue, the machine learning technique has been used. Convolution neural network helps to solve real-time problems; hence, it can be used in the study for detecting traffic signs under foggy condition. The study results revealed that the model network has accuracy of 99.8%, and the proposed algorithm detects a traffic sign under foggy conditions in 2s per frame. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Upper Bounds of Zagreb Radio Indices
Let G= (V, E) be a simple connected graph with vertex set V and edge set E. This chapter consists of several bounds of the Zagreb radio indices of graphs such as the Primary Zagreb Radio Index, the First Zagreb Radio Index, the Second Zagreb Radio Index and the Third Zagreb Radio Index. The indices are defined for graphs after administering a radio labelling. In radio labelling, vertices are labelled with the positive integers such that the absolute difference of two vertex labels added to their distance should be at least one more than the diameter of the graph. In radio labelling, every vertex gets distinct labels. The least possible labels given to the vertices are used to create the radio indices. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.