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Unlocking Happiness: The Power of Spiritual Intelligence for Emerging Adults
This study investigated the relationship between spiritual intelligence (SI) and happiness among emerging adults. 163 undergraduate and postgraduate psychology students from private universities completed standardized measures of SI and subjective happiness. Results showed positive correlations between SI and happiness (r = 0.26 to 0.59, p <.01). Two SI domains - transcendental awareness and conscious state expansion - were found to be significant predictors of happiness. The findings suggest that SI plays a crucial role in promoting happiness among emerging adults, supporting the hypothesis that SI can be used as an aid in the process of achieving happiness through independent decision-making and responsibility. 2024 selection and editorial matter, Dr. Sundeep Katevarapu, Dr. Anand Pratap Singh, Dr. Priyanka Tiwari, Ms. Akriti Varshney, Ms. Priya Lanka, Ms. Aankur Pradhan, Dr. Neeraj Panwar, Dr. Kumud Sapru Wangnue; individual chapters, the contributors. -
Green synthesis of MgO nanoparticles and its antibacterial properties
Magnesium oxide nanostructured particles (NP) were prepared using a simple solution combustion technique using different leaf extracts such as Mangifera indica (Mango - Ma), Azadirachta indica (NeemNe), and Carica papaya (PapayaPa) as surfactants. The highly crystalline phase of MgO nanostructures was confirmed by PXRD and FTIR studies for 2h 500C calcined samples. To analyze the characteristics of obtained materialMaNP, NeNP, and PaNP for dosimetry applications, thermoluminescence (TL) studies were carried out for Co-60 gamma rays irradiated samples in the dose range 1050KGy; PaNP and NeNP exhibited well-defined glow curve when compared with MaNP samples. In addition, it was observed that the TL intensity decreases, with increase in gamma dose and the glow peak temperature is shifted towards the higher temperature with the increase in heating rate. The glow peak was segregated using glow curve deconvolution and thermal cleaning method. Kinetic parameters estimated using Chens method, trap depth (E), and frequency factor (s) were found to be 0.699, 7.408, 0.4929, and 38.71, 11.008, and 10.71 for PaNP, NeNP, and MaNP respectively. The well-resolved glow curve, good linear behavior in the dose range of 1050, KGy, and less fading were observed in PaNP as compared with MaNP and NeNP. Further, the antibacterial activity was checked against human pathogens such as Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa. A visible zone of clearance was observed at 200 and 100?g/mL by the PaNP and NeNP, indicating the death of colonies by the nanoparticles. Therefore, PaNP nanomaterial is a potential phosphor material for dosimetry and antibacterial application compared to NeNP and MaNP. Copyright 2023 Rotti, Sunitha, Manjunath, Roy, Mayegowda, Gnanaprakash, Alghamdi, Almehmadi, Abdulaziz, Allahyani, Aljuaid, Alsaiari, Ashgar, Babalghith, Abd El-Lateef and Khidir. -
Design and Development of Mobile Robot Manipulator for Patient Service During Pandemic Situations
Time and manpower are important constraints for completing large-scale tasks in this rapidly growing civilization. In most of the regular and often carried out works, such as welding, painting, assembly, container filling, and so on, automation is playing a vital part in reducing human effort. One of the key and most commonly performed activities is picking and placing projects from source to destination. Constant monitoring of patient bodily indicators such as temperature, pulse rate, and oxygen level and service of the patients becomes challenging in the current pandemic condition to the nurses and medical staffs. In consideration to this, a mobile robot with an integrated robotic arm has been designed and developed which can be available for service of patients continuously alongside monitoring them in general ward as well as in ICU of hospitals. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Application of fuzzy logic in multi-sensor-based health service robot for condition monitoring during pandemic situations
Purpose: The purpose of this study is to plan and develop a cost-effective health-care robot for assisting and observing the patients in an accurate and effective way during pandemic situation like COVID-19. The purposed research work can help in better management of pandemic situations in rural areas as well as developing countries where medical facility is not easily available. Design/methodology/approach: It becomes very difficult for the medical staff to have a continuous check on patients condition in terms of symptoms and critical parameters during pandemic situations. For dealing with these situations, a service mobile robot with multiple sensors for measuring patients bodily indicators has been proposed and the prototype for the same has been developed that can monitor and aid the patient using the robotic arm. The fuzzy controller has also been incorporated with the mobile robot through which decisions on patient monitoring can be taken automatically. Mamdani implication method has been utilized for formulating mathematical expression of M number of if and then condition based rules with defined input Xj (j = 1, 2, . s), and output yi. The inputs and output variables are formed by the membership functions Aij(xj) and Ci(yi) to execute the Fuzzy Inference System controller. Here, Aij and Ci are the developed fuzzy sets. Findings: The fuzzy-based prediction model has been tested with the output of medicines for the initial 27 runs and was validated by the correlation of predicted and actual values. The correlation coefficient has been found to be 0.989 with a mean square error value of 0.000174, signifying a strong relationship between the predicted values and the actual values. The proposed research work can handle multiple tasks like online consulting, continuous patient condition monitoring in general wards and ICUs, telemedicine services, hospital waste disposal and providing service to patients at regular time intervals. Originality/value: The novelty of the proposed research work lies in the integration of artificial intelligence techniques like fuzzy logic with the multi-sensor-based service robot for easy decision-making and continuous patient monitoring in hospitals in rural areas and to reduce the work stress on medical staff during pandemic situation. 2024, Emerald Publishing Limited. -
Automatic Weld Features Identification and Weld Quality Improvement in Laser Sensor Integrated Robotic Arc Welding
In this study, an integration of point laser sensor in robotic arc welding has been performed for achieving robotic positional accuracy automatically in every welding cycle. With the help of defined focal length of laser sensor, weld seam positions as well as weld gap have been found automatically for any newly positioned work-piece. If there is any change in robot positioning compared to the master job, the shift in every axis is sent as signal to the robot controller so that robot end effector will adjust the shift amount automatically. The welding process parameters are set at optimal values. Taguchi approach so that maximum values of weld quality in terms of depth of penetration, yield strength and ultimate strength can be achieved in every welding cycle. Overall, with the proposed approach, a smart and productive way of operating industrial welding robot has been proposed which can be implemented in any medium to large scale industries for obtaining welding joints with minimum defects. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Non-Alcoholic Fatty Liver Disease Prediction with Feature Optimized XGBoost Model
Non-alcoholic fatty liver disease (NAFLD) is an expanding health threat, posing significant risks for long-term complications. Early detection and intervention are crucial, but traditional diagnostic methods can be expensive and invasive.This study investigates the utilization of machine learning models for predicting liver diseases from various out-sourced datasets..We employed Decision Trees, Random Forests, and Support Vector Machines (SVMs) to predict NAFLD based on various clinical and demographic features. Model performance was evaluated by calculating accuracy, precision,deviation and accuracy-score.All these models achieved promising accuracy levels, ranging from 80% to 90%, showcasing their potential for NAFLD prediction. Among them, XG-Boost demonstrated the highest performance, with an accuracy of 90% and more.This study demonstrates the effectiveness of machine learning models in predicting NAFLD with high accuracy using readily available data. Further research with larger sized and more varied datasets will vindicate these models for real-world application in clinical settings. 2024 IEEE. -
Development of LIDAR-SLAM Integrated Low Cost Health Care Monitoring Robot with Sustainable Material
Beyond the global pandemic, healthcare has faced a myriad of challenges, from rising costs and accessibility issues to the need for precision in patient care and efficient medication delivery. This project embodies a visionary response to the multifaceted challenges faced by healthcare systems in health centers located in rural areas. The proposed research work focused on design and development of a health care monitoring robot with integration of 3D LIDAR Simultaneous Localization and Mapping (SLAM) based navigation approach, introduction of sustainable materials like bamboo and wood composites for development of robotic arm and robotic body frames. Also, from the initial tests it has been observed that with the developed mobile robot functions like precision medicine delivery, Open AI-Enabled continuous monitoring, hospital environment sanitization and emergency oxygen supply can be performed efficiently. 2024 IEEE. -
Influence of cryogenic treatment of cutting tool inserts on tool wear and surface roughness during milling of Inconel 718
Inconel 718 is a superalloy which is a hard to difficult machining material. It is widely used in industries such as aerospace, defence, energy production, biomechanical and marine. It is used at elevated temperatures and areas where thermal and fatigue stress is high. Due to its superior quality and hard surface, machining of this material becomes a challenge. Cutting tools have failed enormously in milling this material. However, tungsten carbide and ceramics have found some effective features in creating a better machinability. In this paper, microstructure of the inserts have been studied during machining to determine low surface roughness on the material. Cryogenic treatment of the inserts has been carried out to improve tool life and compared with the untreated inserts. 2020 Author(s). -
Experimental study of response parameters during machining of Inconel 718 with cryogenically treated ceramic round tool using cutting fluid
Highly advanced superalloys are being rapidly spreading throughout the globe. It's in need of the hour to produce similar materials which are being used in several industries similar as petrochemical, biomechanical, aerospace and marine industries. Inconel 718 is one similar superalloy which is being used due to its better characteristic features like high attrition resistance, high temperature burden conditions, thermal fatigue resistance, and cryogenic temperatures. Owing to the hardness conditions, tools indicate the low tool life and high wear characteristics. Ceramic insert is one such tool that is being used to machine Inconel 718 which is cryogenically treated to improve tool life. The use of emulsified cutting fluid reduces tool wear and improve durability of the tool, thereby improving the efficiency of the machining of Inconel 718. In this paper, experimental investigation has been carried to find the use of emulsified cutting fluid that improves the machinability of Inconel 718 based on parameters such as surface roughness and tool wear under the effect of cutting parameters which are cutting speed, feed rate and depth of cut. 2021 Elsevier Ltd. All rights reserved. -
Parametric analysis of control parameters for investigating the machinability of inconel 718 using ceramic inserts of round type
Inconel 718 is a nickel-chromium based super alloy and has high corrosion and thermal resistance, high hardness, and high thermal strength at elevated temperatures which makes it difficult to cut. Due to these mechanical properties, it is being used in toughest conditions and hence the tool life is extremely short. This hard to cut metallic alloy has a wide scope in the field of bio medical industry, aerospace industry, bearing industry, steam turbine and nuclear applications and the demand has rapidly been increased in the recent years. Ceramic insert is one such cutting tool being used in the machining of this metal and study is still being conducted to increase the machinability. This paper investigates the machinability characteristics for determining the machinability of Inconel 718 using ceramic insert based on Grey Relation Analysis (GRA) and signal to noise (S/N) ratio. The input parameters such as feed rate, cutting speed and depth of cut are taken into consideration to obtain the suitable response parameters such as minimal surface roughness and low tool wear rate to improvise the machining characteristics of this superalloy. Ceramic inserts had even been cryogenic treated to provide better machining conditions on the Inconel 718. 2023 Author(s). -
The effect of cutting fluid in improving the machinability of Inconel 718 using ceramic AS20 tool
Industries demand a vast usage of superalloys in heat resistant and high temperature applications. These include nozzle of rocket fuel engines, throttle valve of turbojet engines, turbine blade discs of aerospace industries, rivets and fittings of chemical and production industries, biomedical applications in super strength resistive steels. These superalloys such as Inconel 718 finds its vast applications in all such industries. To machine such materials a lot of wear and tear occurs at the cutting tool. Hence, cutting fluid helps in reduction of tool wear and improving surface roughness. In this paper, two cutting fluids Koolkut 40 and Hicut 590 have been used in emulsified form during the machining of Inconel 718 with Ceramic cutting tool. Hicut 590 has been seen a better heat resistive cutting fluid in reducing the tool wear and thus improving the life of the tool. 2021 Elsevier Ltd. All rights reserved. Selection and Peer-review under responsibility of the scientific committee of the Global Conference on Recent Advances in Sustainable Materials 2021. -
An Investigation to the Hardness of the Cutting Tool During Machining Inconel 718 due to the Cryogenic Effect
The machining of superalloy Inconel 718 has seen a rapid demand in industries due to the superiority factor of its composition which makes it corrosion resistant, wear resistant and abrasive resistant. Due to these advanced features of this alloy, the cutting tool to be used to machine becomes a challenging one. There have been several cutting tools being used in the machine but wear of the tool and high surface roughness has been observed. Two cutting tools Tungsten Carbide RYMX 1004-ML TT3540 and Ceramic AS20 has been identified but the hardness on it is failed due to the machining conditions. The cryogenic treatment of these tools can see a remarkable change in machining and bring low surface roughness and reduce tool wear. 2023 American Institute of Physics Inc.. All rights reserved. -
Autonomous green vegetable growth monitoring via YOLOv9 and a vine robot with tracked mobility
Urban agriculture is facing shrinking land while demand for food is increasing. The study introduces a vine-like, soft robot for non-destructive tracking of green vegetable development using a tracked mobile platform. Although an inbuilt camera and YOLOv9 object detector classify in real time and generate results in four size categories, very small, small, medium, and large, a flexible tube is everted into dense greenery through a pneumatic eversion process. Sensor fusion and hierarchical control are integrated to enable navigation through the complex canopies of crops with accurate control of pressure and direction, and steering. A field trial found 91% mAP detection accuracy at 38 FPS, accurate vine extension (1.2 m @ 4 cm/s), and stable locomotion over uneven terrain, resulting in constant coverage without harming the plants. The system provides a scalable solution for precision agriculture, enhancing crop inspection, disease diagnosis, and harvest planning through continuous data insights. 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Path Planning of KR6 R900 Vision Sensor Assisted KUKA Industrial Robot for Pick and Place Application
In this paper, a new multi-objective functions comprising of squared values of joint jerk, acceleration, torque rate and total travel time subjected to kinematic and dynamic constraints have been formulated for achieving optimal trajectory for industrial applications. Then four different multi-objective optimization algorithmsthe multi-objective particle swarm optimization technique (MOPSO), the multi-objective genetic algorithm (MOGA), non-dominated sorting genetic algorithm-II (NSGA-II) and the proposed multi-objective enhanced teaching learning-based optimization (MOETLBO)have been utilized to obtain the optimal solution for trajectory planning. Finally, the experimental validation of the proposed technique and the summarization of simulation results have been done as a comparative study of the four different metaheuristic techniques for pick and place application of KR6 R900 KUKA industrial manipulator. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
Optimal setting of arc welding robot and laser sensor variables for getting maximal weld quality, positional accuracy, and smooth trajectory
Abstract: For seam-finding applications, a robotic welding system and laser sensor can be coupled to achieve improved repeatability and shorter cycle times. This manuscript investigates the impact of several robot variables, including robot orientation, robot travel speed, and focal length of the laser sensor, on three key factors: positioning error, associated joint jerk-torque rate, and weld quality. An Enhanced Multi-Objective NSGA-II (EMONSGA-II) is proposed, which combines NSGA-II with Nelder Mead local search to find the best values for robot and sensor variables. The goal is to acquire the lowest values for joint jerk-torque rate, positional error, and maximum weld quality metrics. The maximized weld quality is represented by maximized ultimate strength, yield strength, and penetration of weld joint, as minimized weld bead height and width. Fuzzy logic has been used to transform the multi-performance weld characteristics into one term of the weld quality. The experiments have been performed using the Arc 50 series welding system with AccuFast point laser sensor integrated MOTOMAN MA 1440 arc welding robot system. Finally, the optimal setting of the robot and sensor parameters have been validated through experimentation to observe the weld quality and positional accuracy. The Author(s), under exclusive licence to Springer-Verlag France SAS, part of Springer Nature 2025. -
Neuro-fuzzy model optimization for laser sensor-based quality control for robotic welding of AISI 1030 steel
Robotic welding demonstrates considerable potential in the automation of metal joining processes, resulting in enhanced consistency. This study proposes a methodology for evaluating weld quality by utilizing a laser sensor in conjunction with a hybrid neuro-fuzzy model. The system, designed for AISI 1030 mild steel, utilizes a Design of Experimentation (DOE) methodology to collect empirical data and train the model. A MOTOMAN MA1440 robotic arm, integrated with an AccuFast-II laser sensor, was utilized to acquire real-time weld characteristics. The proposed model integrates fuzzy logic with artificial neural networks (ANNs) for predicting weld quality and is subsequently optimized using the Class Topper Optimization (CTO) algorithm. The model exhibited a high level of prediction accuracy, as indicated by R-squared values of 1.0, 0.99677, 0.99851, and 0.97561 for the training, testing, validation, and overall WQCI datasets, respectively. The process parameters obtained from the CTO analysis yielded a WQCI of 0.824, exceeding the highest experimental value of 0.808, which reflects a 1.98% enhancement in weld quality. The system demonstrated strong performance on both straight and curved weld paths, achieving a positional error of less than 0.29 mm, which falls within the acceptable weld gap range of 11.6 mm. This study emphasizes the practical implementation of a neuro-fuzzy prediction system integrated with an innovative metaheuristic for quality control in robotic arc welding. The integration improves weld consistency, minimizes defects, and increases production efficiency, representing a notable advancement in intelligent manufacturing. The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2026. -
An investigative approach to hard machining of inconel 718 with coated carbide tool
Super alloys sustain good strength at high temperature and pressure conditions. Such
materials have high demand in Aerospace industry, Marine industry, and Nuclear power plants. They have a great demand in Nuclear and Aerospace applications because of it retain its properties at temperature over 700 °C. Machinability of nickel based super - alloys is extremely poor, mainly due to their low thermal conductivity, build up edge and self-hardening, which leads to high dynamic cutting forces. They are difficult to machine because of its high shear strength, work hardening and precipitation hardening. High abrasive particles in its microstructure and tendency forming chip to weld to tool and form Built Up Edge (BUE) make it more difficult to machine. Friction between tool and material and its low thermal conductivity results in high temperature generation. They have Nickel (Ni), Chromium (Cr), Ferrous (Fe) or Cobalt (Co) as base contains. Small amount of Al, Ti, Nb, Ta, W, Mo added to these alloys to sustain at high temperature. Chromium is important alloying element in order to obtain the hot corrosion resistance property. Due to these factors the tool wear is extremely high and increasing the tool life by minutes is an enormous success. To overcome this situation, various materials have been developed for Inconel 718 machining. Though Ceramic tools, Silicon Carbide whiskers, reinforced alumina tools, carbide tools have been used to machine Inconel 718 but they have failed to produce good surface, better accuracy and minimum tool wear. -
Semantic segmentation for data validation in unmanned robotic vehicles
Semantic segmentation is a vital aspect of computer vision, widely used in fields such as autonomous driving, medical imaging, and industrial automation. Maintaining high-quality datasets is crucial for enhancing model accuracy and minimizing real-world errors. This paper focuses on developing a comprehensive data validation pipeline for semantic segmentation using OpenCV. The proposed framework integrates automated integrity checks, preprocessing techniques, and consistency verification to manage large-scale datasets effectively. Key validation processes include image quality assessment (detection of blurriness and noise), verification of annotation accuracy, class distribution analysis, and identification of anomalies. Additionally, OpenCV-powered preprocessing steps, such as image resizing, normalization, contrast optimization, and data augmentation, are applied to refine dataset quality for segmentation models. This paper also addresses scalability concerns associated with processing extensive datasets, introducing optimized batch handling and parallel validation techniques. By implementing a structured validation workflow, this research enhances the reliability, robustness, and overall effectiveness of semantic segmentation models, ensuring high-quality training data for deep learning applications. 2026, Intelektual Pustaka Media Utama. All rights reserved. -
Thermomechanical Analysis of Cutting Tool Used for Minimizing Tool Wear During Machining of Inconel 718
During the CNC machining process, high stresses and temperatures are created at the cutting edge during machining of Inconel 718 due to severe tool wear. Inconel 718, one of the most often used Ni alloys, has a low machinability. Hence, determination of proper cutting tool to minimize tool wear and reduce surface roughness becomes an important aspect. Considering the scenario, the model-ling of dry turning of Inconel 718, a 3-Dimensional (3D) numerical model based on Finite Element (FE) is used. Turning tests were used to validate the model. The main wear modes that were dis-covered experimentally (chipping, notching, and built up edge BUE) were linked to variables predicted by the computational model, such as temperature and plastic strain at the chip. In this study, response surface methodology is used to design four features, matrix for a flexible composite design consisting of 5 repetitive levels; planning, implementation, implementation and development of mathematical models. Medium cutting strength is determined by the different feed values in the tangential, radial, and axial directions during the tooth by maintaining immersion and axial depth of the cut as constant. A comparison is shown between modeling and experimentation. In this paper, the principal stress and displacement strain has been seen at the tool-work interface region of three cutting tools during machining Inconel 718. Three directions i.e tangential, radial, and axial directions these stress and displacement has been applied to observe the changes and determine the selection of the suitable cutting tool for optimal machining conditions and parameter selection. It is observed that titanium cutting tool can prove to be a better tool to be used for machining Inconel 718 for longer tool life and improve productivity. Major Findings: The principal stress and Von-Mises stress in the thermomechanical analysis during Machining of Inconel 718 is found to be less in titanium cutting tool. This is the most suitable tool that can be used for machining hard to cut material Inconel 718. 2025, Informatics Publishing Limited. All rights reserved. -
Fully automatic commercial line vehicle assembly line system /
Patent Number: 202241007000, Applicant: Dr. M. Srinivasnaik.
An assembly line control system, and more specifically, an automotive assembly line storage and lot control system, is shown off in this paper. A communications network is put on top of a manufacturing line. The assembly line has a lot of readers and processing stations that help workers figure out and confirm the identities of the cars that pass by. They also check the cars' build instructions, status, position, condition, defect and repair history, and more. It's in a computer database, and it's easy to find.