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Harnessing technology for mitigating water woes in the city of Bengaluru
Industrialization has caused most of the world's environmental problems like climate change, water security issues, biodiversity issues among others. Water-related issues like water scarcity, lack of water quality, water sanitation issues, lack of proper water resources management are some of them. Urbanization, population increase, pollution has led to an increase in water demand. Water being the elixir of life, is essential for the day-to-day living of an individual. The Fourth Industrial Revolution technologies like AI, IoT, Blockchain, Machine Learning have the capability of bringing solutions to these issues. The current study focuses on the water woes of Bengaluru, a fast-growing urban city, due to its migrating population. The woes are also due to the irresponsible behaviour of builders converting lakes into real estate infrastructure leading to clogged drains, excess sewage creation and flooding. A huge mismatch between demand and supply of water is created due to these issues. Before the city hits the Day Zero - no water day, it is significant to set up water infrastructure along with technology implementation which will help resolve this burning issue at the earliest. Published under licence by IOP Publishing Ltd. -
Physical layer impairment-aware routing and wavelength assignment (PLI-RWA) strategy for mixed line rate (MLR) wavelength division multiplexed (WDM) optical networks
The ever increasing global Internet traffic is resulting in a serious upgrade of the current optical networks' capacity. The legacy infrastructure can be enhanced not only by increasing the capacity, but also by adopting advance modulation formats, having increased spectral efficiency at higher data rate. In a mixed-line-rate (MLR) optical network, different line rates, on different wavelengths, can coexist on the same fiber. Further, studies have shown that migration to data rates higher than 10Gbps requires implementation of phase modulation schemes. However, the co-existing On-Off Keying (OOK) channels cause critical physical layer impairments (PLIs) to the phase modulated channels, mainly due to cross-phase modulation (XPM), which in turn limits the network's performance. In order to mitigate this effect, a more sophisticated PLI-Routing and Wavelength Assignment (PLI-RWA) scheme needs to be adopted. In this work, we investigate the critical impairment for each data rate and the way it affects the quality of transmission (QoT). We propose a novel PLI-RWA algorithm for MLR optical networks. The proposed algorithm is compared through simulations with the existing shortest path and minimum hop routing schemes. 2015 IEEE -
A novel launch power determination strategy for physical layer impairment-aware (PLI-A) lightpath provisioning in mixed-line-rate (MLR) optical networks
In mixed-line-rate (MLR) networks, various data rates, on varied wavelengths, exist on a fiber. In MLR networks, end-to-end lightpaths can be established with the desired line rate; requiring advanced modulation formats for higher data rates. However, along the route, the signals experience different physical layer impairments (PLIs), and their quality also worsens. The transmission signal quality is affected by the launch power, which must be high for lesser noise at the receiver, and must also be low, such that the PLIs do not start to distort the signal. Further, higher launch power also disrupts the existing lightpath and its neighbours. We propose a weighted strategy for provisioning PLI-aware (PLI-A) lightpaths in MLR networks. Through the simulations, we compare and demonstrate that the proposed strategy demonstrates better performances than our previously proposed algorithm (i.e. PLI-Average (PLI-A)), and existing approaches. 2016 IEEE. -
Comparative Analysis of State-of-the-Art Face Recognition Models: FaceNet, ArcFace, and OpenFace Using Image Classification Metrics
In recent years, facial recognition has emerged as a key technological advancement with numerous useful applications in numerous industries. FaceNet, ArcFace, and OpenFace are three widely used techniques for facial identification. In this study, we examined the accuracy, speed, and capacity to manage variations in face expression, illumination, and occlusion of these three approaches over a period of five years, from 2018 to 2023. According to our findings, FaceNet is more accurate than ArcFace and OpenFace, even under difficult circumstances like shifting lighting and facial occlusion. Also, during the previous five years, FaceNet has shown a significant improvement in performance. Even while ArcFace and OpenFace have made significant strides, they still lag behind FaceNet in terms of accuracy. Therefore, based on our findings, we conclude that FaceNet is the most effective method for facial recognition and is well-suited for use in high-stakes applications where accuracy is crucial. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Automated Single Responsibility Principle Enforcement: A Step Toward Reusable and Maintainable Code
In this study, we delve into the sphere of automated code scrutiny, specifically concentrating on compliance with the single responsibility principle (SRP), a key principle in software architecture. The SRP proposes that a class should have a singular reason for modification, thereby enhancing code cohesion and facilitating its maintenance and reusability. The study presents a pioneering system that utilizes a holistic strategy to ascertain SRP compliance within code. This system rigorously inspects code interfaces, the interaction points among various software components. Through this process, we extract critical insights into the codes maintainability and reusability. An optimally designed interface can significantly improve code management and foster its reuse, leading to superior software design efficiency. Beyond interface inspection, our system also explores complexity metrics such as cyclomatic complexity and hassel volume. Cyclomatic complexity offers a numerical indicator of the count of linearly independent paths traversing a programs source code, serving as a measure of code complexity. Hassel volume is an additional metric that can quantify code complexity. Moreover, our system employs code smell detection methodologies to identify instances of high interdependence between classes, often a sign of SRP breaches. High interdependence, or tight coupling, complicates code modification and maintenance. The system integrates the conclusions from these varied analyses to determine SRP compliance. The outcomes of this investigation highlight a hopeful trajectory toward automated SRP detection. This could provide developers with tools that proactively foster the development of well-organized and maintainable code, thereby enhancing software design quality. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
A Framework for Digital Forensics Using Blockchain to Secure Digital Data
Digital forensics (DF) requires evidence integrity and provenance across boundaries of jurisdiction, and blockchain technology is ideal for ensuring that. As part of this paper, we discussed a digital forensic framework designed to help prevent duplication of data and secure digital data. In order to accomplish such forensic capabilities, we provide a block-based forensics framework. Using it, examinations are validated, irreversible, traceable, robust, and demonstrate high levels of confidence among examiners and evidence entities. 2022 IEEE. -
Paradigm of Green Technologies in Hospitality Industry and its Sustainability Analytics
The function of the study is to investigate the customer attitude towards the sustainable or Green Technologies adopted by the hospitality industry and how this has changed the purchase intentions of the customer. This also explores the disposition of people to pay for and repeat these services and how the new green practice and techniques have changed the brand image. The data was collected through a monitored survey from 448 people across India. The conceptual framework that was formulated is tested during structural equational modelling. As a result of the study, it was found that, green purchase intentions are significantly influenced by the attitude they have towards Green Technologies/services. All stakeholders in the hospitality industry in India will find this paper useful. 2022 IEEE. -
An Efficient Underwater Image Restoration Model for Digital Image Processing
Digital image processing (DIP) is showing a massive growth intodays trending world particularly, in the field of biological research. Underwater image analysis plays a vital role, where the images are easily prone to attenuation and haziness. Capturing underwater images has always been a challenging job due to dispersion and scattering of light inside water on a high scale. Several image enhancement and restoration methodologies are currently available to address these issues, where hazing and color diffusion are viewed as a common phenomenon in it. Such procedures normally includes two basic methodologies in it, namely dehazing and contrast or color enhancement, which improves the overall output of the degraded image. However, the quality and processing time of the images can still be enhanced with additional techniques incorporated to it. This work is intended toward proposing one such channel called improvised bright channel prior for dehazing the underwater images. The technique further improves on the existing methodologies by estimating the atmospheric light and refining the transmittance of the image along with image restoration. The experimental results show that the improvised bright channel prior methodology is found to perform better in dehazing underwater images with a balanced intensity in terms of dark and white patches obtained from it. When comparing and contrasting the processing time of the proposed methodology with the existing techniques, it is found that improvised bright channel prior performs better. Also, the quality of the dehazed underwater image obtained from the proposed channel is found to be effective when compared with the existing channels. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Automated Organic Web Harvesting on Web Data for Analytics
Automated Web search and web data extraction has become an inevitable part of research in the area of web mining. The web scraping has immense influence on ecommerce, market research, web indexing and much more. Most of the web information is presented in an unstructured or free format. Web scraping helps every user to retrieve, analyze and use the data suitably according to their requirement. There exist different methodologies for web scraping. Major web scraping tools are rule based systems. In the proposed work, an automated method for web information extraction using Computer Vision is proposed and developed. The proposed automated web scraping method comprises of automated URL extraction virtual extraction of required data and storing the data in a structured format which is useful in market research. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Strength and ductility behaviour of FRC beams strengthened with externally bonded GFRP laminates
The repair and rehabilitation of structural members are perhaps one of the most crucial problems in civil engineering applications. One of the advanced techniques of strengthening the reinforced concrete members is done by fiber-reinforced polymer composites. FRP is very effective to repair and strengthen the structural members that have become structurally weak over their life span. FRP repair system provides an economically viable alternative to traditional repair systems and materials. This experimental study focuses on the flexural strengthening of fiber reinforced concrete beams externally bonded with FRP laminates of different thicknesses. Six beams were cast for the study and tested under a four-point bending system. Out of which two beams were served as a control beam, one beam was considered as a reinforced concrete beam and the other was fiber reinforced concrete beam. The fibers used in this investigation were steel fiber. The beams were strengthened with GFRP of 3 mm and 5 mm of woven roving type. The study parameters of this investigation included yield load, ultimate load, deflection, yield load deflection, ultimate load deflection, deflection ductility, energy ductility, and the beam was found to be very effective in the load-carrying capacity, deflection, and ductility when compared to the control specimen. The fiber-reinforced concrete beam exhibit an increase in ultimate deflection by 79.3% when compared to the control specimen. GFRP strengthened beams showed an increase in ultimate deflection by 18.75% to 94.06%. GFRP strengthened fiber reinforced concrete beams showed an increase in ultimate deflection by 7.8 to 13.125%. GFRP strengthened beams showed an increase in ultimate deflection by 54.7% to 81.88%. GFRP strengthened fiber reinforced concrete beams showed an increase in ultimate load-carrying capacity by 36.9% to 48.7%. The ductility for the specimens increases by 1.27% to 1.34%, compared to the controlled specimen. 2020 Elsevier Ltd. All rights reserved. -
Weather Forecasting Accuracy Enhancement Using Random Forests Algorithm
In today's world, weather forecasting is essential for decision-making in a variety of fields, including agriculture, transportation, and disaster preparedness. It's not simple to make weather predictions. Today, both in business and academia, data analytics is growing in importance as a tool for decision-making. The adoption of data-driven concepts is for our graduates, enhancing their marketability. Data Analytics us a study belonging to science that analyses gathered raw data, which makes conclusions about the particular information. Data analytics has been used by many sectors recently, such as hospitality, where this industry can collect data, find out where the problem is, and manage to fix the problem. Nominal, ordinal, interval, and ratio data levels are the four types of data measurement. Applications of data analytics can be found in many industries, including shipping and logistics, manufacturing, security, education, healthcare, and web development. Any business that wants to succeed in the modern digital economy should make analytics a core focus. To make such data meaningful, a transformation engine was used with types from several sources. Ironically, this has made analytics harder for businesses. As businesses employ more platforms and applications, the amount of data available has grown tremendously. This article focuses on different applications of data analytics in the modern world. Weather forecasting is a highly intricate and multifaceted process that draws upon data from various sources. It relies on a combination of scientific studies and sophisticated weather models to decipher the vast amount of information available. 2023 IEEE. -
Artificial Intelligence and Machine Learning-Based Systems for Controlling Medical Robot Beds for Preventing Bedsores
Artificial Intelligence is one of the most important technologies of the modern world which is continuously changing the dimensions of almost every sector. AI and IoT have together resulted in multiple outstanding technological innovations which have also impacted the healthcare sector massively. This study has critically focused on the role of AI and robotics in the treatment outcomes for patients. This study has done deep research regarding the role of automated beds in reducing pressure ulcers or bed sores among patients who are recovering from any chronic disease. This entire study has secondary qualitative data collection for analyzing the design and microcontroller systems in automated beds. This has provided a detailed data analysis with relevant equations and tables for reaching its proposed outcomes. 2022 IEEE. -
Creation of Bookshelf Using Autodesk 3ds Max: 3D Modelling and Rendering
The step-by-step process of creating a bookshelf design is specified, including the ProBoolean compound primitive, applying edit poly modifier, using detach option, making use of lattice modifier, using bend modifier, using twist modifier. The manner in which materials are added to the model, together with environment lighting and renderer configuration, is defined. Procedures and methods for rendering are also defined. What we aim to achieve through our research is to create a Bookshelf design that uses materials to enhance the models. The shapes used in the model were Box, Teapot, sphere, chamfercyl, Oiltank, ProBoolean compound. The modifiers used were edit poly, bend, twist, lattice. Afterwards we used the Arnold light and material editor to enhance and glorify the model. 2023 IEEE. -
A Non-Linear Approach to Predict the Salary of NBA Athletes using Machine Learning Technique
Every sportsman traded/drafted receives monetary compensation in accordance with their contract. In this study, we propose a nonlinear approach based on performance and other aspects to determine the salary of a basketball player. We estimate the salary based on four regressive models. Whilst predicting we also Figure out the important features impacting the salary. Comparatively speaking, random forest outperformed other algorithms. Furthermore, we consider that our findings might benefit discussions between basketball teams and players. This model can also help set a benchmark for salary expectations by the players in accordance. 2022 IEEE. -
Alkali-Activated Materials - A Review for Sustainable Construction
New, sustainable low-Carbon Dioxide (CO2) construction materials must be developed for the global building sector to decrease its environmental impact. During the last several decades, Alkali-activated Materials (AAMs) is a Portland cement-free form, have been intensively researched as a potential alternative for ordinary Portland cement concrete (OPCC), with the objective of lowering CO2 emissions while repurposing a large volume of industrial waste by-products. The suitability of using AAMs made up of industrial waste by-products such as blast furnace slag (BFS), calcined clay (metakaolin), and fly ash (FA) was investigated in this study utilizing a performance-based approach that was unaffected by binder chemistry, history, or environmental effect, Binder paste microstructural assessment and influence on engineering effectiveness, including fresh and hardened characteristics of these materials, In the Viewpoints area, we analyze specific premature phase and long-phase performance of AAMs, as well as Upcoming scientific breakthroughs are also discussed in the Viewpoints section. 2022 American Institute of Physics Inc.. All rights reserved. -
Performance Evaluation of Time-based Recommendation System in Collaborative Filtering Technique
The Collaborative Filtering (CF) technique is the most common neighbourhood-based recommendation strategy, that provides personalized recommendation to a user for the items using a similarity measure. Hence, the selection of the appropriate similarity measure becomes crucial in the CF based recommendation system. The traditional similarity measures merely focus only on the historical ratings provided by the users to compute the similarity, completely ignoring the fact that preferences change over a period of time. Considering this, the paper aims to develop an effective Recommendation System that uses temporal information to capture the changes in the preferences over a period of time. For this, the existing exponential and power time decay functions are integrated with Cosine, Pearson Correlation, and Gower's similarity measures to compute similarity. The similarity is computed at the similarity computation and prediction levels of recommendation processes. Experimental findings in terms of MAE and RMSE on the MovieLens-100k demonstrate that performance of Gower's coefficient is better when applied with the exponential function at the similarity computation level of the recommendation process. 2022 Elsevier B.V.. All rights reserved. -
Wideband Compact Two-Element Millimeter Wave MIMO Antenna for Communication Systems
This article presents the wide band two-element MIMO antenna with an I-shaped decoupling structure in the ground plane. It is to enhance the isolation on the MIMO antenna. The dimension is 7.5 17.5 mm2. The measured bandwidth is 2 GHz (22.25-24.25 GHz) with a maximum gain of 4.5 dBi and bidirectional radiation. MIMO antenna satisfies three diversity metrics. 2024 IEEE. -
Emotional Landscape of Social Media: Exploring Sentiment Patterns
Sentiment analysis, a pivotal research area, involves exploring emotions, attitudes, and evaluations prevalent in diverse public spheres. In the contemporary era, individuals extensively share their perspectives on various subjects through social media platforms. Twitter has emerged as a prominent microblogging site, facilitating users to express opinions and insights globally. However, disrespectful or unfair comments have prompted specific platforms to restrict user comments, highlighting the need to foster productive discourse on social media. This study addresses this imperative by analyzing sentiments using data from Twitter. This work employed various deep learning algorithms and methods to classify elements as negative or positive. The Sentiment140 dataset, sourced from Twitter, serves as the training data for the models to identify the most accurate classification approach. By delving into sentiment analysis on Twitter, the study contributes to a better understanding of the nuances of online expressions. It aims to enhance the overall quality of discourse in social media. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Predictive Analytics for Network Traffic Management
It examines how this can be applied to monitoring network traffic and carrying out predictive analysis to improve the functionality and effectiveness of network management. The study uses historical data of the network traffics and uses machine learning techniques such as the Long Short Term Memory based models and the Ensemble Methods to predict the traffic patterns in the future. It includes data gathering, data pre-processing, feature selection, model choice, model training, model validation, and the architectural setup of the machine learning solution in a real-time stream processing pipeline using Apache Kafka and Apache Flink. It is evident from the results that the proposed models yield a high level of accuracy in terms of prediction and that the Ensemble method alone gives a slightly higher accuracy than LSTM in the specific metrics. Real-time values closely followed actual traffic level, thus allowing real-time adjustments in network usage. In light of this, there is a clear understanding of the significance of having reliable data preprocessing, feature engineering, and model optimization process. The study also notes the need in prediction concerning data quality and scalability issues taking into account that current and future networks are characterized as dynamic and highly complex to offer more effective solutions for intelligent and proactive networking. 2024 IEEE. -
User Sentiment Analysis of Blockchain-Enabled Peer-to-Peer Energy Trading
A new way for the general public to consume and trade green energy has emerged with the introduction of peer-to-peer (P2P) energy trading platforms. Thus, how the peer-to-peer energy trading platform is designed is crucial to facilitating the trading experience for users. The data mining method will be used in this study to assess the elements affecting the P2P energy trading experience. The Natural Language Processing (NLP) approach will also be used in this study to evaluate the variables that affect the P2P energy trading experience and look at the role of topic modeling in the topic extraction using LDA. The findings show that the general public was more interested in the new technology and how the energy coin payment system operated during the trade process. This explanation of energy as a CC is an outlier that fits well with the conventional literature. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.