Digital Communication and Soft Computing Approaches Towards Sustainable Energy Developments

Frontmatter

Robust Study on Jamming Techniques in Digital Communications

Abstract

Jamming in wireless networks has gained importance as a field of study due to the ease with which wireless communications can be disrupted. One type of denial-of-service assault is a “jamming attack,” in which an attacker node deliberately disrupts network traffic in order to impede legitimate communication. If we are going to get a grasp on this, we need to have an in-depth conversation about and analysis of jamming and anti-jamming techniques used in wireless networks. The type of jammer utilized and its location are two crucial considerations for successful jamming in ad hoc wireless networks. Many methods of jamming localization, detection, prevention, and mitigation are being researched to find the most effective way to deal with the problem.

N. Chitra Kiran, Suchira Suresh, M. N. Dhananjai Thiwari

Performance Evaluation of TAS/MRC-Assisted Communication Technique Based on Fisher-Snedecor F Fading Channels

Abstract

Multiple-input-multiple-output (MIMO) technique has turned into a salient feature in wireless communication because it can transfer information parallelly, reducing transmission power. The MIMO technique also upgrades the functioning and the capacity of the wireless communication method. But MIMO system uses an immense number of antennas, so there is an elevation in the hardware intricacy as well as its cost. To conquer these drawbacks, a MIMO system which operates with a specific transmit antenna independently, particularly, transmit antenna selection (TAS) scheme based on Fisher-Snedecor F fading channel, is considered in this paper. Maximal ratio combining (MRC) is executed at the user subject to the fading channels. Explanations considering average bit error rate (ABER) as well as outage probability are presented in the light of TAS/MRC-type MIMO structure. The obtained analytical equations are ratified by using Monte-Carlo simulation outcomes.

Hubha Saikia, Rajkishur Mudoi

Distribution Network Local Energy Market: A Comprehensive Review

Abstract

The rapid power grid transition from wholesale electricity market toward liberalized distribution market has evolved over a decade time with increasing penetration of distributed energy resources (DERs) and digitization of grid. It has facilitated two-way communication between the market players by enabling peer-to-peer (P2P) energy trading. P2P market allows flexible energy trades between peers, i.e., the local prosumers in a distribution network local energy market (D-LEM) framework. Such energy trading is challenging as it requires different market mechanism and different pricing scheme considering all the physical network constraints as well as uncertainties to be handled at the same time. This study briefs different aspects of D-LEM that have evolved in diverse market framework across different countries, their potential development and challenges.

Debasmita Panda, Altaf Q. H. Badar

Secured Audio Communication Through Light

Abstract

Invention of light-emitting diode (LED) brought a great advancement in the visible light communication. LED can be used for transmitting data for short distance in a more economical way with less interference. Present work proposes design and test of a system for communicating audio signal through light. A password-based security feature is incorporated in the system in order to authenticate exchange of information. Proposed system with password communication, password verification and audio communication modules is designed and simulated using Proteus software. Further, the hardware setup is designed and built using LED as the audio transmitter and solar panel as the receiver along with the required amplification and filtering stages. Proposed system is simulated using Proteus software and tested for successful password authentication and audio transmission. The hardware prototype is built and tested successfully for the audio transmission to a range of 90 cm using LED as the source of light. The distance of audio transmission can be extended further by using laser light as source of light.

P. Surya Kumar, P. Supraja, I. Mamatha

Optimizing the Industrial Wireless Sensor Network Connectivity Using Improved Whale Optimization Algorithm

Abstract

This paper aims to develop an improved whale optimization algorithm (IWOA) to enhance the industrial wireless sensor networks (IWSN) field device placements to achieve effective network connectivity and coverage for all the available clients in its network. The proposed IWOA is created using mathematical functions such as square, cube, and square root as the stochastic accelerator scaling coefficient parameter. As a result of using different benchmark test functions, the proposed algorithm is evaluated against the conventional whale optimization algorithm. In addition, the algorithm is further validated using the IWSN issues like the optimal placement of sensor nodes, adequate client coverage, and network overlapping. The results show that the proposed algorithm showed 64.51% increased client connectivity and network coverage. In the optimization test functions, IWOA achieved a 143.15% performance increase in finding the best global minima values in fewer iterations.

P. Arun Mozhi Devan, Rosdiazli Ibrahim, Madiah Binti Omar, Kishore Bingi, Fawnizu Azmadi Hussin, Hakim Abdulrab

Perceptual Hash Computation of Multimedia Objects Using Improved KL Transform

Abstract

This paper presents an improvement for Karhunen–Loeve (KL) transform which is a new approach for computation of perceptual hash in multimedia objects. Basically, all the cryptographic algorithms used for computation of hash function for multimedia objects suffer from avalanche effect. Perceptual hash function is a solution to the avalanche effect problem. To achieve the goal, the original image size is reduced into 8 × 8 pixels which in turn divided into sixteen 2 × 2 matrices (after grayscale conversion). The prime benefit of proposed algorithm is to improve the complexity of the 2D KL transform and also simplify the structure which can give a chance for recursive and parallel processing of images.

Stuti Pandey, Nihar Ranjan Pradhan, Akhilendra Pratap Singh, Dharmender Singh Kushwaha

Role of Artificial Intelligence (AI) in the Field of Renewables, Energy Transition, and Decarbonization

Abstract

Artificial intelligence (AI)-based intelligent solutions are increasingly used nowadays to address challenging real-world issues in a variety of industries. Because of their symbolic thinking, adaptability, and explanatory abilities, AI-based systems are being created and implemented in a wide range of applications across the globe. This thorough overview piques interest in AI and its applications to renewable energy sources, energy transition, and decarbonization. This paper also demonstrates the application of several AI techniques in large-scale systems for the integration of renewable energy, and it evaluates the performance of these strategies using a range of case studies and theoretical explanations.

N. R. Asha Rani, Sasmita Bal, M. Inayathulla

IoT-Based Solar Power Forecasting Using Deep Learning

Abstract

Due to the growing carbon footprints and the impacts of climate change, less fossil fuels are being used for transportation and energy production. The cost of creating solar photovoltaic (PV) panels has been reduced as a result of the improvements in manufacturing processes, bringing solar energy output on level with that of traditional fossil fuels. Solar power production is unpredictable, and this is influenced by the site’s capability to host. Once renewable energy sources have been installed, forecasting is essential for the grid’s effective management and functioning. The projection is helpful for choosing investments and setting up the distribution network during the initial planning phases. Three error measures were used to compare and evaluate the effectiveness of the LSTM network and variational mode decomposition (VMD).

Touseef Hasan Kazmi, Sumant Kumar Dalai, P. Ranga Babu, Gayadhar Panda

Blockchain and IoT Technologies Enabled Waste Management in Smart Cities: A Survey

Abstract

By tracking and monitoring city activities in real-time, both the Blockchain and Internet of Things (IoT) concepts are essential for developing smart city applications. Urban waste management is one of the most important concerns related to smart city applications, and it may create conflict to our society's health and environment. As a consequence, waste bins are installed throughout the city to handle municipal urban waste management, however, these bins might overflow, damaging the environment and causing public disturbances. As a result, a real-time remote monitoring system is required, which alerts the municipality community or a waste management agency regarding the level of garbage present in the waste bins. To solve the above-mentioned points, this proposed model uses Blockchain and IoT-based architecture for urban waste management in smart cities. The proposed architecture consists two types of end-user sensor nodes: UWBLMU (Urban Waste Bin Level Monitoring Unit) and RWBLMU (Residential Waste Bin Level Monitoring Unit), which are used to track waste bins in urban and residential areas respectively. This article addresses an introduction to Blockchain and IoT, as well as the interaction of wireless communication technologies of Blockchain and IoT, and Blockchain applications for IoT in urban waste management.

K. Lova Raju, G. Ramana Murthy, Srikanth Itapu

Application of Artificial Intelligence and Machine Learning Technique for Nonlinear Flow Modelling Applicable in Petroleum Exploration and in Porous Media Flow

Abstract

Understanding and modelling nonlinear filtration through porous media is especially important in the energy sector since it directly controls the discharge in petroleum and gas wells. The efficiency of hydraulic fracturing process completely depends on our understanding of the nonlinear filtration process in porous media. However, the process is extremely complex, and therefore, theoretical and empirical understanding of the subject is very much ambiguous. This is because there are a lot of factors which are involved in the process. Efficient modelling of such process requires a clear understanding about the parameters which are important for the model. Realising the potential of machine learning and artificial intelligence in the field, we have attempted to arrange the parameters according to their importance using a random forest-based feature selection technique. Understanding the effect of these characteristics on the modelling of the porous media flow in the post-laminar regime may be of great use to academics, planners, and designers especially associated with energy sector.

Ashes Banerjee, N. R. Asha Rani

Analyzing Customers Buying Behavior Before and After COVID-19 Using Association Rule Mining and Machine Learning

Abstract

India got affected by COVID-19 in March 2020. Many super stores and online marts have seen a sudden decline in the sales of many items and increase in the demand and sales of some new items amid this. To effectively manage with such kind of changing economy, variety of products, their layout on shelves, and promoting special promotions, a quick and efficient customer purchasing pattern analysis is required which can help in increasing the revenue. In this paper, customer behavioral analysis for their buying patterns is done before and after COVID-19 using association rule mining algorithms. The 4-year dataset is collected from an online mart from January 2018 to January 2022 containing more than 5 lakhs entities for 38 countries. To validate the results of these algorithms, two machine learning algorithms are also used.

Rituraj, Shaveta Arora, Rohan Nandal, Rohit

A Hybrid INC and ANN-Based MPPT for PV System

Abstract

There has been significant change in recent years toward promoting renewable energy sources. The worldwide market has hammered on developing energy alternatives that would not only improve quality but also provide a long-term supply of power. Here, solar photovoltaic energy may be seen as an extremely promising renewable energy source. The incremental conductance (INC) method, a prominent maximum power point tracking (MPPT) technique, is the subject of this research. This method has certain advantages, but it also has some problems. An improved incremental conductance (INC) model with hybridization of artificial neural network (ANN)-based maximum power point tracking (MPPT) has been presented to reduce the oscillation around the maximum power point (MPP) and to boost the reaction time. Simulation results are provided for the hybrid maximum power point tracking (MPPT) model based on incremental conductance (INC) and artificial neural networks (ANN), developed in MATLAB/Simulink.

Franklin Burhagohain, Tilok Boruah

Profitability Allocation of UAVs and Stopping Points Empowered MEC System

Abstract

There are now many vessels in the oceans, including commercial vessels and submarines employed for military activities or scientific research. Due to the technology on board, each spacecraft generates a large quantity of data that must be sent to prospective destinations. It is proposed that the well-known Intelligent Ocean Convergence Platform, which currently supports oceanic services, assists these services using cutting-edge Internet of Things and 5G connection principles. When using edge computing, processing tasks are occasionally moved from the cloud to the network's edge. In this study, we propose merging edge computing with software-defined networking, where edge computing delivers ocean networks with ultra-reliability, scalability, and low latency, while software technology is utilized to promote interoperability across various network technologies. This will satisfy the need for speedy processing and communication capabilities as the number of maritime boats continues to grow significantly. The simulation of typical end-to-end latency is used to assess the effectiveness of the suggested edge computing architecture.

Vaibhav Tiwari, Chandrasen Pandey, Gayadhar Panda, Diptendu Sinha Roy

Development of SPV-Assisted E-Mobility Charging System Based on Fuzzy Logic and PI Control as Charge Controller

Abstract

The energy from solar photovoltaic systems can also be used to power hybrid vehicles. In this paper, the fuzzy logic-based maximum power point tracking (MPPT) approach is suggested for using a boost converter derived from a photovoltaic (PV) panel at constant temp. 25 °C and constant irradiance. The constant current (CC) and constant voltage (CV) are two traditional methods for charging a battery. For fast charging with low loss, it is necessary to supply a constant voltage (CV) and constant current (CC) source. In this study proportional integral (PI) control was one of the methods used to provide constants. In addition to being straight forward and well-developed PI control also delivers satisfactory outcomes. Operating the PV panel at its maximum power point (MPP) and providing the battery with the proper current and voltage will expedite charging, reduce losses, and increase the battery's life is the objective of this paper. This system was designed and examined using MATLAB/Simulink.

Manoranjan Meher, Harin M. Mohan, Santanu Kumar Dash, Gayadhar Panda

Efficient Operation of Boiler Using PLC-SCADA

Abstract

As the boiler is a very important part of the industry, it requires continuous inspection with specific time intervals. In earlier days, this inspection and monitoring were done with human workers. There are several possibilities for errors with human workers while measuring particular values in the boiler operation process. So a reliable monitoring system is required to avoid these errors and maximize profit. This paper gives the design and development of some techniques used for boiler automation. This boiler automation system includes the monitoring of oxygen concentration in the flue gases, steam pressure at the steam header and vacuum / negative draft inside the furnace using different sensors. This boiler automation system consists of an FD fan, an ID fan and two fuel feeders. Three VFDs are been used to control the speed of the FD fan, ID fan and fuel feeders. Three sensors are been used—oxygen sensor, pressure transmitter and vacuum transmitter. It is a three-loop boiler automation system, i.e., the first loop is an interlink of an oxygen sensor and FD fan, the second loop is an interlink of pressure transmitter and fuel feeders and the third loop is an interlink of ID fan and vacuum transmitter. TIA Portal software is been used which consists of Wincc advanced SCADA package and the programming of this process is written in Siemens S-7 1200 PLC which is also an inbuilt package in TIA Portal software.

Tushar Sawarn, Ritula Thakur

A Comparative Analysis of Short Term Load Forecasting Using LSTM, CNN, and Hybrid CNN-LSTM

Abstract

Short-term load forecasting (STLF) is becoming more significant and useful in the field of power systems. This manuscript proposes the best approach by comparing the results of three different deep learning models LSTM (Long-Short Term Memory), CNN (Convolutional Neural Network), and Hybrid CNN-LSTM for forecasting the short-term load, and each model is trained using sliding window algorithm and analyzed with statistical parameters like Mean Square Error (MSE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), R \(^2\), Mean Absolute Error (MAE), and training time. The models are implemented in the Tensor Flow platform and executed in Google Colab. Results show that Hybrid models give better results as compared to individual models. In this case it is shown that Hybrid CNN-LSTM gave better result as compared to CNN and LSTM individually. The RMSE, R \(^2\), MSE, MAE, and MAPE of Hybrid CNN-LSTM model are 0.024225, 0.96, 0.00058, 0.01567, and 0.051564 respectively.

Prajwal Thakre, Mohan Khedkar, B. V. Surya Vardhan

Enhancing Grid Resilience for Improved Power System Reliability

Abstract

Resilience has loomed as a crucial and acceptable quality as a result of increased worries about intrusions on the physiological and digital power grid, also the need to lessen the effects of natural disasters. A sleek transition to a more intelligent grid depends heavily on the conceptualisation, expression, and assessment of the power grid's resilience. There have been several attempts to define, gauge, and evaluate smart grid resilience. Both the obstacles and the desired characteristics of a resilience metric are discussed. The study outlined the qualitative frameworks suggested to evaluate the adaptability of the smart grid, a globally broad, organisationally complex, and technologically advanced cyber-physical system.

G. Swetha Shekarappa, Sheila Mahapatra, Saurav Raj

An Optimal Design of PV—PHS Hybrid System Using HOMER: A Case Study—Khallikote, Ganjam

Abstract

Among the potential sources for the various renewable energy options, solar energy and wind energy are very easily and economically available options, which are clean, inexhaustible, and eco-friendly. Adopting such renewable energy sources is a more practical and simple way to meet the country's energy needs as solar power becomes more affordable and other competing technologies gain credibility. But during specific hours of the day, renewable energy sources produce the majority of their energy. The peak demand hours are not coincided with its electrical generation. The sporadic nature of sunlight makes it impossible to have a constant supply of power and thus it is unpredictable. Thus, the hunt for storage alternatives is ongoing. In that situation, the simpler and superior option for energy storage is the pumped hydro storage system (PHS). The PHS is a concept that involves pumping water up a hill using excess energy, holding it there until it's needed, and releasing the water when it's time to generate energy. This helps rotate the turbine and produce energy to satisfy demand. PHS has existed for a very long time. Around the world, it already makes up 97% of energy storage. In this context, the study further discusses a case study of Odisha (Khallikote, Ganjam) to show the usefulness of proposed methodology and techno-economic feasibility for adopting PHS to meet the energy needs of Berhampur city. The paper considered applying a different methodology for evaluation of feasibility of PHS by using HOMER software for its validation.

Parameswar Panigrahi, Swapnasis Satpathy, Pratyush Parida, Samarjit Patnaik, Manas Ranjan Nayak

Preventing Photovoltaic Curtailment in India: A Brief Analysis

Abstract

This paper examines the curtailment of power generated by solar projects which is a big problem in many prominent nations of the world like the USA, China, and Germany. Curtailment means the activity under which the flow of power generated by photovoltaic (PV) is restricted which, therefore, results in the reduced output of the plant and thus the energy wasted which could have been used otherwise. The main reason for curtailment is when the supply of power exceeds its demand and thus power has to be curtailed to stabilize the system. Economic reasons and the inefficiency of transmission infrastructure are among the other reasons for PV curtailment. Some solutions to avoid PV curtailment include load shifting and the use of energy storage devices but both of them are not the perfect solutions to avoid curtailment due to technical and economic reasons. The situations causing increasing levels of PV penetration could give rise to PV curtailment in India soon. The policies could be framed by analysing the PV growth in India by comparing it with those nations where PV energy is already getting curtailed at present time and by analysing the existing policies regarding solar projects and PV curtailment in the nations like China and Germany.

Akash Midha, Parth Rai, Gaurav Lamba, Shashank, Anuradha Tomar

A Bibliometric Analysis on ‘Role of Electric Vehicles in the Smart Grids’

Abstract

As the Green House Gas (GHG) emission is the buzz word nowadays. Electric vehicles play an important role to reduce GHG emissions. By the deployment of electric vehicles, we are moving forward towards the net zero emission. To meet the sustainable development goals SDG, electric vehicles are need of the hour. As the sale of electric vehicles increases in last 5 years. Even during COVID-19, customers prefer to buy electric vehicles on subsidies as provided by respective governments. As the enhancement of plug-in electric vehicles, various challenges and opportunities are faced by power grid. To overcome these challenges and adopting the opportunities, smart grid plays an important role. Electric vehicles can used in number of ways like peak shaving, load shedding and “valley filling” by use of “V2G” “vehicle-to-grid” technology in addition with smart grid. The paper tells about the bibliometric analysis of “role of electric vehicles in the smart grid” has been presented. The objective behind this paper is to assess various research patterns in the field of smart grid and electric vehicles. Based on Scopus database the study focused on analysis of co-authorship between various authors and countries. The analysis of co-occurrences of keywords related to the title has been analysed. A total of 612 articles related to ‘Role of Electric Vehicles in smart grid’ published by different journals from 2010 to 2022.

Amritjot Kaur

Frequency Control of Hybrid Power System with Electric Vehicle SoC Estimation

Abstract

In our work, the Load Frequency Control (LFC) of Hybrid Power System (HPS) is accomplished using a Fuzzy PIDF-based controller. The HPS comprises one unit of each of the following: solar, wind, fuel cell, diesel generator, battery energy storage, fly-wheel energy storage system, and Electric Vehicle (EV). To fine-tune the settings of a Fuzzy PIDF-based controller, a recently published approach called Pelican Optimization Algorithm (POA) is used. For frequency stabilisation of the HPS, a Fuzzy PIDF controller with the State-of-Charge (SoC) control of battery of EV is proposed in our work. When the HPS’s Frequency Deviation Response (FDR) is compared to the previous one, the effect of the SoC control is shown. The frequency response is substantially improved with the suggested control strategy, according to simulation findings. Additionally, this is supported by sensitivity tests on the modelled system and stability tests using bode plots.

Truptimayee Nayak, Debidasi Mohanty

Scenario-Based Visualization for Traffic Congestion Mitigation

Abstract

Traffic congestion is a major problem in most sustainable smart cities in current days, causing delays, increased emissions, and decreased quality of life. This research proposes a new approach for visualizing traffic congestion using scenario-based visualization. This method uses real-time traffic data to create interactive visualizations of different traffic scenarios, allowing decision-makers and stakeholders to explore the potential impact of different congestion mitigation strategies. It demonstrates the effectiveness of this approach by applying it to a real-world case study of traffic congestion in a major city. The results show that scenario-based visualization can provide valuable insights into the causes and potential solutions for traffic congestion and support evidence-based decision-making in traffic management. When analysing several causes of traffic congestion, it becomes easier to get the solution to mitigate such problems. Here by taking the help of urban mobility tools like SUMO, it is possible to create a scenario for any futuristic event by taking past real-time information. And based on the scenario, it can be possible to define alternate routes for transportation for that particular event so that the overall traffic congestion can be reduced with proper visualization to understand the whole process.

Timothy Dkhar, Prasant Kumar Mohanty, Soumen Moulik, Diptendu Sinha Roy

Comparative Study of Vehicle Detection with Different YOLOv5 Algorithms

Abstract

Vehicle sensing is key to implementing AI-based driving and monitoring systems. Vehicles on the road have increased dramatically. For that, managing the transportation system becomes difficult. To solve this problem, this article proposes a vision-based vehicle detection system. In this study, we developed real-time multi-object media detection based on “You only look once” algorithm (YOLOv5). We analyzed the accuracy of vehicle detection using YOLOv5s (small), YOLOv5n (nano), YOLOv5l (large), YOLOv5m (medium), and the largest of the five YOLOv5x. The test results confirm that the YOLOv5x model can provide higher detection accuracy than other algorithms. The main indicators of accuracy are Precision, Recall, and mAP (0.5).The determined accuracy of the YOLO5s, YOLOv5 m, YOLOv5n, YOLOv5l, and YOLOv5x algorithms on the dataset were 62.4, 64.2, 62.9, 68.7, and 69.7%. Our analysis shows that YOLOv5x is better and more efficient at detecting vehicles and can be implemented in real-time traffic control in traffic systems.

Md. Milon Rana, Md. Dulal Haque, Md. Mahabub Hossain

Hospital Energy Management System for Enhancing Sustainability and Reliability of Power Supply

Abstract

Hospitals are adopting new technologies to provide modern healthcare facilities to enhance the sense of security and hope among the citizens. However, uninterrupted power supply is highly required in hospitals to run the modern life-supporting equipments. Further, it is observed that the distribution grid outage is quite frequent in many countries. During the grid outage, usually hospitals used diesel generator to meet the critical load demand. However, diesel generator sometime may fail to start in emergency conditions, and it is also not eco-friendly. Hence, this paper developed a grid tied micro grid using Homer Grid, NREL, USA considering actual load profile of cancer hospital Imphal, Manipur, India. Further, Hospital Energy Management System (HEMS) has been developed to enhance sustainability and reliability of power supply to the hospital. Simulation results reveal that the developed grid tied micro grid, which is comprised of solar photovoltaic, battery storage and diesel generator, can meet the critical load of the hospital during occurrence of both.

Arvind Kumar Jain, Tapomay Debnath, Arup Ratan Bhowmik

Challenges in Peer-to-Peer Energy Trading Considering Indian Scenario

Abstract

Energy trading among peers has become the new standard for power systems operating, allowing local energy exchange between individuals. It predicts lowering peak demand, decreasing network loss, and minimizing energy costs while assisting the grid. The concept appears to be promising for the future given that electricity consumption is continuously increasing in a nation like India. This paper described the current status of P2P energy sharing in India. It mainly focused on the challenges such as market establishment, security, cyberattacks, cost, while implementing trading mechanisms. Also, it emphasized the physical and virtual layers challenges in the P2P energy trading network. Further, this article highlighted consumers’ costs and producers’ revenue while participating in P2P energy trading.

Chaitali D. Morey, Ashwini D. Manchalwar, Nita R. Patne

An Implementation of Hyperchaotic Encryption Though Direct Sequence Spread-Spectrum Image Steganography (DSSSIS)

Abstract

Due to its high robustness attribute, spread-spectrum steganography for multimedia signals is appealing and is used widely for a variety of applications. In recent years, one similar application of spread-spectrum image steganography (SSIS) has shown promise in that it can assess the QoS (quality of services) of multimedia services without any prior knowledge. This study offers an outstanding and secure algorithm for stegno pictures and a Direct Sequence Spread-Spectrum (DSSS) methodology. This mechanism is based on Code Division Multiple Access (CDMA) for the encryption and decryption-based approach. Through a 127 bit Barker code sequence, data pulses are produced by utilizing the high-speed BPSK modulation method. The Xilinx ISE simulator is used to complete the design and simulate it using VHDL. The hardware model is put into practice in CoolRunner II complex programmable logic device (CPLD). The system for four users to transmit eight bits of parallel data is designed in the simulation portion. Dynamic CDMA and code hopping increase the system’s capacity and security.

M. Sivaranjani, N. Nithya, Srikanth Itapu

Severity Analysis Automation for Detection of Non-Proliferative Diabetic Retinopathy

Abstract

The most significant eye condition that results in blindness, according to the World Health Organization (WHO), claim is 135 million people with diabetes may increase by the number 300 million by 2025. This results in the same incremental rate of diabetic retinopathy (DR) of non-proliferation. Regular retinal examinations help in the early diagnosis of DR, which enables prompt treatment that can successfully stop permanent vision loss. The early detection and monitoring of DR can be aided by automatic lesion recognition in Fundal retinal imagery. One of the major symptoms of DR is microaneurysms. Expertise in microaneurysms can be detected and investigated with hemorrhages. Therefore, the primary prerequisite for diagnosing the progression of DR is the identification of these microaneurysms. In this study, an automated system for evaluating and classifying the severity of non-proliferative diabetic retinopathy (NPDR) is proposed with hemorrhage count. The proposed study is an analysis carried out automatically using a variety of imaging processing approaches based on the count of microaneurysms found in the fundus samples. The work's accuracy performance has been demonstrated to be 96%. Compared to the outcome of region-based image processing techniques, appears to be the most successful.

Anil Kumar Neelapala, Gnane Swarnadh Satapathi, Satya Anuradha Mosa

Design of Energy-Efficient High-Speed 1-Bit Hybrid Full Adder for Fast Computation

Abstract

Hybrid logic style is widely used to implement full adder (FA) circuits. Performance of hybrid FA in terms of delay, power, and driving capability is largely dependent on the performance of XOR–XNOR circuit. In this article, a high-speed, low-power 8-T XOR–XNOR circuit is proposed, which provides full-swing outputs simultaneously with improved delay performance. The performance of the proposed circuit is measured by simulating it in cadence virtuoso environment using 45-nm CMOS technology with a supply voltage of 1.0 V. The power delay product (PDP) is reduced by proposed circuit.

Vesapaga Grace Nissi, Satyajeet Sahoo