Browse Items (2150 total)
Sort by:
-
Mechanical Properties of FSW Joints Magnesium Alloy at Different Rotational Speeds
Magnesium (Mg) has become a focus in the transportation industry due to its potential in reducing fuel consumption and gas emissions while improving recyclability. Mg alloys are also known for their low neutron absorption, good resistant of carbon dioxide as well as thermal conductivity which makes them suitable for use in industrial equipment for nuclear energy. there has been an increasing interest in the research and development of Mg alloys. These are the lightest of all metallic structural materials and are approximately 33% lighter than aluminium (Al) and 75% lighter than ferrous (Fe) alloys and have excellent specific mechanical properties. In this work, FSW of AZ31B Alloy was examined at the various rotational speeds of 900 -1440 rpm, with fixed welding speed of 40mm/min and 2 tool tilt angle using an HSS tool. The mechanical properties were compared for the different rotational speeds. The quality of FSW joints is dependent on input value of heat and material flow rate, which are prejudiced by process parameters., higher rotation speeds may cause abnormal stirring, resulting in a tunnel defect at the weld nugget due to increased strain rate and turbulence. 2024 E3S Web of Conferences -
Mechanical strength and impact resistance of hybrid fiber reinforced concrete with coconut and polypropylene fibers
This experimental study investigates the mechanical properties and resistance to impact of concrete reinforced with coconut fibers (CF) and polypropylene fibers (PPF). The fiber proportions were decided based on the results obtained from the tests on coconut fiber reinforced concrete (CFRC) and polypropylene fiber reinforced concrete (PPFRC), tested individually. PP fibers of 12 mm and 24 mm of 0.1%, 0.2%, and 0.3% of the volume of concrete were used in PPFRC. Coconut fibers having 50 mm and 75 mm of 0.2%, 0.3%, and 0.4% of the volume of concrete were used in CFRC. Based on test results, PPF (12 mm) and CF (50 mm) were selected for hybrid fiber reinforced concrete (HyFRC). By varying both PPF and CF content, three different proportions with a total fiber content of 0.2% and 0.3% of the volume of concrete were selected. The improvement in strength was observed to be maximum when the total fiber content in the hybrid fiber reinforced concrete was 0.3%. The increase in impact resistance of HyFRC was almost double that of individual FRC and three times that of plain concrete. 2022 -
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 -
Media and Urban Governance: The Quest for Sustainable Cities and Communities
Connectivity becomes the hallmark of network society facilitated by digital technologies. Cities are fundamentally well-connected, fast-growing, communicative, and global in outlook. Cities are also known for media concentration, as the structures and people there extensively create and exchange messages - social, political, economic, and cultural. The urban communication landscape is very complex, and therefore, a robust media and communication infrastructure is required to form, reform, and transform urban communities from a sustainable development perspective. Media not only perform the responsibilities of information dissemination and community building but also facilitate urban governance and public discourses on policies. The policy-making process that consists of policy inputs, policy processes, and policy outputs - is heavily influenced by the public discourses triggered by the media. Media can establish a policy issue at the center of the public sphere, set the policy agenda, and create public opinion. It inevitably leads to the mediatization of public policy. Media can effectively place SDGs at the center of the policy discourse and serve as a tool for urban governance by enhancing citizens' participation and helping to solve complex urban problems. This research paper explores various aspects of the governance-media interface in an urban landscape to create sustainable cities and communities. The Electrochemical Society -
Medical Ultrasound Image Segmentation Using U-Net Architecture
This research article discusses the implementation aspects of a Deep Learning architecture based on U-Net for medical image segmentation. A base model of the U-Net architecture is extended and experimented. Unlike the existing model, the input images are enhanced by applying a Non-Local Means filter optimized using a metaheuristic Grey wolf optimization method. Further, the model parameters are modified to achieve better performance. Tests were performed using two benchmark B-mode Ultrasound image datasets of 200 Breast lesion images and 504 Skeletal images. Experimental results demonstrate that the modifications resulted in more accurate segmentation. The performance of the modified implementation is compared with the base model and a Bidirectional Convolutional LSTM architecture. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
MediCrypt: A Model with Symmetric Encryption for Blockchain Enabled Healthcare Data Protection
In the dynamic field of medicine, combining blockchain technology and data security becomes a vital strategy to solve the problem of protecting sensitive medical data. This study presents a new way to improve the security and privacy of medical data, using MediCrypt as an example of two- way encryption. Doctors initially used algorithms like AES or Blowfish to retrieve medical data. Smart contracts on the Ethereum-based blockchain introduce a layer of protection, combining SHA-256 with symmetric encryption technology. The multi-level transmission model includes encryption time, encryption time, elapsed time, and encryption size. Functionality in this model involves managing patient records (EHR), counterfeit drugs, drug reviews, clinical outcomes, and consent for all care areas. As shown in the methodology, the user ecosystem facilitates the exchange of information by defining the roles and responsibilities of doctors/pharmacists, administrators, and patients. The study shows the deployment of the MediCrypt model in three distinct stages. Distinct comparison of encryption time is done for different encryption algorithms. Also, parameters of MediCrypt model is compared with existing healthcare based blockchain models. 2024 IEEE. -
Melanoma Skin Cancer Detection using a CNN-Regularized Extreme Learning Machine (RELM) based Model
Recent years have brought a heightened awareness of skin cancer as a potentially fatal type of human disease. While all three forms of skin cancer - Melanoma, Basal, and Squamous are terrifying, Melanoma is the most erratic. Melanoma cancer is curable if caught at an early stage. Multiple current systems have demonstrated that computer vision can play a significant role in medical image diagnosis. This study suggests a new approach to picture categorization that can help convolutional neural networks train more quickly (CNN). CNN has seen widespread use in multiclass image classification datasets, but its poor learning performance for huge volumes of data has limited its usefulness. On the other hand, whereas Regularized Extreme Learning Machine (RELM) are capable of rapid learning and have strong generalizability to improve their recognized accuracy quickly. This study introduces a novel CNN-RELM, a novel classifier that integrates convolutional neural networks with regularized extreme learning machines. CNN-RELM begins by training a Convolutional Neural Network (CNN) through the gradient descent technique until the desired learning and target accuracy is achieved. This approach outperforms the CNN and RELM model with an accuracy of around 98.6%. 2023 IEEE. -
Mental Health Data Analysis Using Cloud
In health care related research studies, there exists a need for retrieving patient's health record from multiple sites. So here comes the digitization of health records, which leads to a wide range of access to various users such as doctors, patients, psychiatrists and pharmacists. The sensitive nature of individual health care data pose a threat to security. Moreover, the increased access of health information by the users threatens the privacy and confidentiality of the stored data. Notwithstanding the existing privacy protection approaches used for mental health records, we suggest a privacy preserving data analysis methodology enabling protection of health records, once user access to records are granted. This paper mainly focuses on utilizing the data analysis approach in preserving privacy of personal health records to overcome the drawbacks of existing approaches. 2020 IEEE. -
Mental Health Stigma: Strategies for Destigmatization in Healthcare Settings
Mental illness is one of the most common disabilities in the world. The term "mental illness stigma"describes harmful practices and misconceptions that lead to a detrimental effect on the mental health, motivation, and self-worth of those who suffer from mental illnesses. Health care services are important for treating and reducing the negative stigma of mental health, as they are areas where patients seek relief and support. The study aims to investigate the causes and how to reduce them. Explores ways to disrupt the health care environment, specifically the RESHAPE program, which focuses on the concept of "critical". This review paper looks at 8-10 papers on mental health and stigma and how stigma will be reduced. The results show that a large number of doctors and students are stigmatized, negatively affecting the lives of people affected by mental illness. RESHAPE, KAP, and IBH therapies are also effective ways to minimize mental health stigma. This intervention aims to educate public health workers, promote social cohesion, and integrate treatment into primary health care, improving treatment into primary health care, improving treatment quality and patient outcomes. The study draws attention to the importance of stigma reduction efforts in the long term in health education and practice emphasis. 2024 IEEE. -
Mental Workload Estimation Using EEG
Mental workload contributes considerably to the outcome or the performance of any task. The concern of human workload increases during a human-machine collaboration task or in a multitasking environment. This paper presents a comparative study of machine learning algorithms used to estimate workload using Electroencephalography (EEG) data. An open-access EEG dataset acquired during a 'simultaneous capacity (SIMKAP) experiment' and 'no task' is used to create and validate models for binary classification of workload as present and absent respectively. The paper presents an implementation of various classification models that use EEG data to predict the workload. In this paper, implementation for KNN classifier (57.3%), Random Forest classifier (57.19%), MLP network classifier (58.2%), CNN+ LSTM network classifier (58.68%), and LSTM network classifier (61.08%) has been reported. The paper can be further extended to study operator workload in real-time using a brain-computer interface paradigm for any kind of task in a real-world application. The workload classification can be further used in human-machine tasks to decide task allocation between the system to achieve optimal performance in a complex critical system. 2020 IEEE. -
Mesoporous iron aluminophosphate: An efficient catalyst for one pot synthesis of amides by ester-amide exchange reaction
A series of metal aluminophosphates (MAlP: M = V, Fe, Co, Ni & Cu) were prepared by co-precipitation method. All the materials were characterized by various physico-chemical techniques. The materials were found to be mesoporous and moderately acidic. The catalytic activity of the materials was investigated in the synthesis of benzamides in a single pot reaction under solvent free refluxing conditions from methyl benzoate and different amines. Iron aluminophosphate was found to be the most effective catalyst for the synthesis of benzamides with 100% selectivity. The isolated yield of benzamide varied from 46% to 100% depending on the nature of amine. A possible reaction mechanism has been proposed which correlates the surface acidity and catalytic activity of the catalyst. The catalyst could be recycled for about three times without any appreciable loss in activity, thus making the method ecofriendly and economical. -
Message efficient ring leader election in distributed systems
Leader Election Algorithm, not only in distributed systems but in any communication network, is an essential matter for discussion. Tremendous amount of work are happening in the research community on election as network protocols are in need of co-ordinator process for the smooth running of the system. These so called Coordinator processes are responsible for the synchronization of the system otherwise, the system loses its reliability. Furthermore, if the leader process crashes, the new leader process should take the charge as early as possible. New leader is one among the currently running processes with the highest process id. In this paper we have presented a modified version of ring algorithm. Our work involves substantial modifications of the existing ring election algorithm and the comparison of message complexity with the original algorithm. Simulation results show that our algorithm minimizes the number of messages even in worst case scenario. 2013 Springer Science+Business Media. -
Metaheuristicsbased Task Offloading Framework in Fog Computing for Latency-sensitive Internet of Things Applications
The Internet of Things (IoT) applications have tremendously increased its popularity within a short span of time due to the wide range of services it offers. In the present scenario, IoT applications rely on cloud computing platforms for data storage and task offloading. Since the IoT applications are latency-sensitive, depending on a remote cloud datacenter further increases the delay and response time. Most of the IoT applications shift from cloud to fog computing for improved performance and to lower the latency. Fog enhances the Quality of service (QoS) of the connected applications by providing low latency. Different task offloading schemes in fog computing are proposed in literature to enhance the performance of IoT-fog-cloud integration. The proposed methodology focuses on constructing a metaheuristic based task offloading framework in the three-tiered IoT-fog-cloud network to enable efficient execution of latency-sensitive IoT applications. The proposed work utilizes two effective optimization algorithms such as Flamingo search algorithm (FSA) and Honey badger algorithm (HBA). Initially, the FSA algorithm is executed in an iterative manner where the objective function is optimized in every iteration. The best solutions are taken in this algorithm and fine tuning is performed using the HBA algorithm to refine the solution. The output obtained from the HBA algorithm is termed as the optimized outcome of the proposed framework. Finally, evaluations are carried out separately based on different scenarios to prove the performance efficacy of the proposed framework. The proposed framework obtains the task offloading time of 71s and also obtains less degree of imbalance and lesser latency when compared over existing techniques. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Micro grid Communication Technologies: An Overview
Micro grid is a small-scale power supply network designed to provide electricity to small community with integrated renewable energy sources. A micro grid can be integrated to the utility grid. Due to lack of computerized analysis, mechanical switches causing slow response time, poor visibility and situational awareness blackouts are caused due to cascading of faults. This paper presents a brief survey on communication technologies used in smart grid and its extension to micro grid. By integration of communication network, device control, information collection and remote management an intelligent power management system can be achieved 2022 IEEE. -
Microhardness studies of vapour grown tin (II) sulfide single crystals
Earth abundant tin sulfide (SnS) has attracted considerable attention as a possible absorber material for low-cost solar cells due to its favourable optoelectronic properties. Single crystals of SnS were grown by physical vapour deposition (PVD) technique. Microindentation studies were carried out on the cleaved surfaces of the crystals to understand their mechanical behaviour. Microhardness increased initially with the load, giving sharp maximum at 15 g. Quenching effect has increased the microhardness, while annealing reduced the microhardness of grown crystals. The hardness values of as-grown, annealed and quenched samples at 15 g load are computed to be 99.69, 44.52 and 106.29 kg/mm 2 respectively. The microhardness of PVD grown crystals are high compared to CdTe, a leading low-cost PV material. The as-grown faces are found to be fracture resistant. 2015 AIP Publishing LLC. -
Micromachining process-current situation and challenges
The rapid progress in the scientific innovations and the hunt for the renewable energy increases the urge for producing the bio electronic products, solar cells, bio batteries, nano robots, MEMS, blood less surgical tools which can be possible with the aid of the micromachining. This article helps us to understand the evolution and the challenges faced by the micromachining process. Micro machining is an enabling technology that facilitates component miniaturization and improved performance characteristics. Growing demand for less weight, high accuracy, high precision, meagre lead time, reduced batch size, less human interference are the key drivers for the micromachining than the conventional machining process. Owned by the authors, published by EDP Sciences, 2015. -
Microstructure and Mechanical Behaviour of Al6061-ZrB2 In-situ Metal Matrix Composites
Aluminium matrix composites processed through in-situ molten reaction has emerged as an alternative for eliminating defects existing in ex-situ reinforced metal matrix composites. Development of composites through in-situ method using inorganic salts via liquid metallurgy route is the most widely accepted technique. In the present work, Al6061-ZrB2 in-situ composites have been developed through in-situ reaction of Al-10%Zr and Al-3%B master alloys in Al6061 alloy. Study of microstructure and mechanical properties of in-situ reinforced ZrB2 in Al6061 alloy have been carried out. Composite exhibited grain refinement and improved the mechanical properties of Al6061 alloy. Ductility of composite is reduced with increase in content of ZrB2. Published under licence by IOP Publishing Ltd. -
Miniaturization of Microstrip Antenna with Enhanced Gain Using Defected Ground Structures
The rapid advancement and growth in the wireless technology demands miniaturized communication equipment's. Microstrip antennas attracted many researchers over the past decades because of its various features like small in size, light weight, low cost and conformability. These antennas can operate at high frequencies and multiple bands with high gain and larger bandwidths if suitably designed. This work presents a Rectangular Microstrip Antenna (RMSA)performance improvement using defected Ground Structures (DGS). The simulation results revealed that the creation of Complementary Split Ring Resonator (CSRR)and Phi as a defect in the ground of proposed antenna has improved its gain. Introduction of DGS improved the gain by 27% and reduced the size by approximately 3.35%. Proposed Rectangular Microstrip Antenna with Defected Ground (RMSA-DGS)exhibits gain of 3 dB at 2.4 GHz with S11 response of -30.44 dB. In addition to this the antenna also shows one more resonance at 4.66 GHz with S11 of -14.29 dB and gain of -1.24 dB. RMSA-DGS has an overall dimension of 37.2 47.23 mm2. 2019 IEEE. -
Miniaturized Band Stop Frequency Selective Surface for Stable Resonance Characteristics
In this paper, miniaturized 7.45 GHz resonant frequency band stop frequency selective surface (FSS) is designed. The unit cell dimensions of designed FSS is only about 0.1?0 at the 7.45 GHz. Proposed design involves a crossed dipole metallic element together with meander shape on the substrate. Simulation results provide about 800 MHz bandwidth (7.1 GHz-7.9 GHz) with-20 dB insertion loss. The FSS properties are studied on a unit cell using electromagnetic (EM) solver to observe the characteristics. Proposed FSS demonstrates a stable resonance frequency behavior for the arbitrary angle of incidences in both the polarizations such as TM and TE modes. Thus, the design holds a polarization independent characteristic for all incident angles and polarizations. Finally, the FSS properties are validated by a fabricated array of 311 mm2. 2018 IEEE. -
MIST-based Tuning of Cyber-Physical Systems Towards Holistic Healthcare Informatics
The entire world seems shaken and disrupted since the strike of Covid-19 ever since its outbreak towards the end of 2019 and its continued perils. During this unprecedented event of the century, people's health emerged as the most vulnerable and affected area either directly or indirectly by the coronavirus and its new variants. Disrupting almost all spheres of life, patients' health and care systems required timely support from healthcare professionals to provide the needed medical advice on one hand and a prescriptive mechanism to avoid another impending casualty. Similarly, a proactive approach became desirable from the health ministry, pharmaceutical firms, medical insurance companies, and other stakeholders in fine-tuning their offerings to the patients as per the recommender systems. The devices to measure the vitals of a person, became more efficient and ergonomically sound with the advent of wearable gadgets. These devices monitored the physical activities of the user and transferred the vital signals wirelessly to any base computing device and cloud-based repositories. This mechanism, however, was reported to fail in addressing the issues with non-communicating or stand-alone devices that were used by the masses in developing countries including India. If the real-time data could be used from these devices, the healthcare diagnosis and analysis of a patient's medical condition could have taken a progressive dimension with the addition of missing data points. This research thus aims to fill the information gap and proposes a transforming approach towards existing non-communicating devices used to measure the vitals like blood pressure, oxygen level, blood sugar, etc. The proposed MIST-based Cyber-Physical System shall create extensive scalability towards the retrieval of the vital details from the devices which were otherwise captured offline previously and were unused at multiple critical points of healthcare processes. 2022 IEEE.