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Multi-response Optimization of Turning Parameters for Cryogenically Treated and Tempered WC–Co Inserts
No full textThe cryo-treatment has already emerged as the sustainable manufacturing process of the future generation. It is an effective process to improve the tool life in different manufacturing processes such as turning, drilling, and milling. Thus, optimal process parameters must be determined in dry turning to attain the economic machining along with tool wear reduction and a better surface finish of the machined workpiece. The present investigation aims to optimize the machining input parameters with multi-responses in dry turning of low carbon En8 steel with deep cryo-treated (DCT) tungsten carbide cobalt bonded insert
(WC–Co) by using hybrid type multi-criteria decisionmaking methods such as Taguchi’s based Grey Relational Analysis and Technique for Order Preference by Similarity to Ideal Solution. The optimized machining conditions are suitably validated and compared in this study. Additionally, microhardness and microstructure of the DCT tools are examined. The results revealed that the DCT tool enhances the machining performances due to fine eta (g) carbides distribution and densification of Co binder after the treatment which confirms through scanning electron microscopic imag
Develop New Algorithm To Improve Safety On WMSN In Health Disease Monitoring
No full textThe WSN was already commonly used in many
applications because of the rapid growth of wireless
communication networks including semiconductor technology.
The basic elements of healthcare monitoring were Wireless
Medical Sensor Networks (WMSNs). The WMSN, as a WSN
application, has grown in importance in the current health
industry and also can enhance value. Physiological information
is retrieved by devices implanted in the body of the patient as
well as wirelessly transmitted to healthcare providers' portable
devices in the WMSN. The person's condition might then be
obtained by health experts at any time and any place. This
study identifies the much more difficult security issues in
contemporary remote patient monitoring authentication
methods as well as proposed a light general populace
authentication protocol for MSNs.The networks of MSN were
divided into the detectors, which provide measures about the
person's body, as well as actuation, which accept instructions
from health workers as well as act in a certain way.
Authenticating those instructions would be a crucial safety
concern, as any change could have severe repercussions. The
suggested method was implemented on the enhanced Rabin�Karp authentication algorithm, which has been tweaked in this
study to enhance the signatory verification procedure, making
it acceptable to delay-sensitive MSN systems. To demonstrate
the enhanced Rabin - Karp method's effectiveness, researchers
used Tmote Sky motes to construct the method with various
device configurations and also coded the method on an Field
Programmable Gate Arrays (FPGA) to examine its quality
and construction. The findings show that medical, health
doctors secure, direct, instant, and authenticated instructions
to MSN nodes. The suggested method outperforms current
protocols in terms of safety as well as systems were working.
As a result, it's better suited to WMSN-based healthcare
applications
INTELLIGENT TRACKING AND NAVIGATING MOVING OBJECTS IN A SMART ENVIRONMENT USING IOT NETWORK
No full textInternet of things (IoT) constitutes the combinations of sensors,
controllers, actuators, connectivity. Tracking and navigating moving objects are crucial tasks for security as well as a secure and smart environment. By using the sensory data, location of objects can be identified then that sensory data will be transferred to controllers for the further processes. One pivot role of the system is to identify the trajectory and location of the object using the speed, velocity, acceleration, maps etc and this can be done by machine learning programs. Analyzing service required, prediction of the trajectory and real-world knowledge of maps or locations, To avoid the loop-carrydependency, service request parameters are dynamically changed to
locate relevant virtual objects. In order to track moving items, this study provides an architecture based on IoT self-aware environment technology that facilitates the tracking and allocation of relevant virtual objects. Keywords: IoT, self-aware environment, loop-carry dependency, machine learning, object identification, sensory data
Multi-functional attributes of rare earth double doped SrBi2Nb2O9 ferroelectric system
No full textThe ferroelectric perovskite SrBi2Nb2O9 (SBN) material with a low concentration of double doping at the Bi-site of SBN was studied to understand its influence and usefulness in integrated optoelectronic, soft magnetic memory devices and wear-resistant tribomaterials. The aim of the present study is
double doping of SBN with a set of rare earth elements Pr3+/Dy3+ (SBPDN), Pr3+/Gd3+ (SBPGN), Pr3+/Sm3+ (SBPSN), and Pr3+/Y3+ (SBPYN) at the Bi-site of SBN to establish the multifunctional ceramic nature pertaining to diverse applications. XRD with Rietveld refinement analysis acknowledged a single-phase orthorhombic structure with an increase in lattice parameters and unsystematic changes in crystallite size. SEM study indicated that the samples possessed non-uniformly distributed needle-shaped grains. The purity of the material and the detection of functional groups were received from the EDS and FTIR spectroscopy. Structural modifications in SBN have been determined based
on a diffuse reflectance spectroscopy (DRS)study and therefore the band gap values decrease from 2.98 eV(SBN) to 2.70 eV(double doping) because of the growth of distortion in the structure and pronounced increase in the density of localized states. Photoluminescence (PL)study on double doped
SBN material with an excitation wavelength of 320 nm has yielded a novel red emission at 609 nm, that may be useful for white LEDs. The ferromagnetic signature in the studied materials was confirmed from the room temperature VSM study. Noticed mild wear and a low coefficient of friction in the
studied materials of SBPDN and SBPSN compared to other studied ceramic samples from mechanical studies. The simultaneous manifestation of optical, magnetic, and mechanical properties by doubledoped SBN ceramics keeps the materials as multi-functional candidates for optoelectronic devices, soft magnetic memory devices, and wear-resistant tribomaterials
Removal of Atrizine using Rice Husk Biochar: Characteristic and Equilibrium Studies
No full textPesticides in aqua bodies resulting from drainage of industrial pollutants are the most potential environmental concerns, and their elimination is critical. Atrazine is a broad-leaf herbicide that is widely used around the world. Atrizine, on the other hand, is frequently found in water sources as a result of its long-term use. Biochar has proven potential for sorption of atrazine from solution considering the number and type of functional groups found on it. Adsorption experiments to remove atrizine from water bodies using rice husk biochar as an adsorbent are discussed in this work. Elemental analyzer, scanning electron microscopy (SEM), and the Brunauer, Emmett, and Teller (BET) analyzer were used to determine the activation and surface properties of rice husk biochar. For different pesticide concentrations, the effect of contact time on adsorption ability and percentage removal was investigated
Sustainable removal of methylene blue dye from textile effluent by using cellulose nanocrystals extracted from sugarcane bagasse
Get PDFAdsorption has proven to be a cost-effective option for treating wastewater containing dyes and other pollutants, as it is a simple and low-cost technique. In this work, cellulose nanocrystals (CNCs) were extracted from sugarcane bagasse using the acid hydrolysis technique and used as an effective adsorbent for removing methylene blue dye. The chemistry behind the segregation of cellulose nanocrystals from sugarcane bagasse and its adsorption of methylene blue dye from textile wastewater has been discussed. The obtained nanocrystals were characterized by Fourier transform infrared spectroscopy (FTIR), ultraviolet–visible spectroscopy, X-ray diffraction (XRD), and thermos gravimetric analysis (TGA). The dye solution was subjected to extracted CNC, observed the dye absorption capacity, and found that the absorbance of the dye solution after treatment was decreased compared to the stock solution. With an increase in treatment time from 30 to 90 min, there was a rapid decrease in absorbency values obtained through UV spectroscopy
Solar-Based Mosquito Trap for Household Purposes
Get PDFA practical problem in the society has been taken as a challenging problem, and efforts are devoted to provide a solution to trap mosquitoes. Mosquitoes and other insects are attracted to a light source situated on top of the trap and are pulled through a rotating fan into a collapsible cage. The trap is lightweight and issuitable for field studies where electric power is unavailable since it operates on drycell batteries. Though different methods are available to reduce the mosquito population, a mosquito trap has been designed and developed in order to trap the mosquitoes in the present study. The major components of this trap are suction fan, blue light, trap, etc. The blue light is positioned such that it can attract mosquitoesin the current research. In order to enhance the capacity of mosquitoestrapping, a suction fan is installed ahead of the blue light. Based on the above principle, the developed trap can attract and trap the mosquitoes, and the results obtained from this trap are satisfactory
Design of half adder using integrated leakage power reduction techniques
Get PDFThe necessity for the development of compact, portable, and reliable electronic devices of enhanced speed and efficiency has prompted the scaling of CMOS devices to be indispensable. However, the benefit of scaling CMOS devices comes at the cost of increased leakage current in circuits. The variance in power consumption by these circuits incites detrimental impacts on the operational characteristics of the entire device. So, in this work, a novel leakage power reduction technique obtained by combining the Leakage Control Transistor (LECTOR) approach and drain gating approach is proposed. Both these subthreshold leakage minimization approaches are prominently used in Complementary Metal Oxide Semiconductor (CMOS) devices for curtailing the leakage power. The effectiveness ofthe proposed Integrated Drain Gating Lector (IDGL) technique in mitigating the leakage power is ascertained by designing a half adder circuit. Hence the overall leakage power is of 3.16nW & delay 69.12µs in 180nm technology, and in low scale technology of 90nm the same leakage power decline to 2.19nW & delay is 65.45µs
An Automated Word Embedding with Parameter Tuned Model for Web Crawling
No full textIn recent years, web crawling has gained a significant attention due to
the drastic advancements in the World Wide Web. Web Search Engines have the issue of retrieving massive quantity of web documents. One among the web crawlers is the focused crawler, that intends to selectively gather web pages from the
Internet. But the efficiency of the focused crawling can easily be affected by the environment of web pages. In this view, this paper presents an Automated Word Embedding with Parameter Tuned Deep Learning (AWE-PTDL) model for focused web crawling. The proposed model involves different processes namely pre-processing, Incremental Skip-gram Model with Negative Sampling (ISGNS) based word embedding, bidirectional long short-term memory-based classification
and bird swarm optimization based hyperparameter tuning. The SGNS training desires to go over the complete training data to pre-compute the noise distribution before performing Stochastic Gradient Descent (SGD) and the ISGNS technique
is derived for the word embedding process. Besides, the cosine similarity is computed from the word embedding matrix to generate a feature vector which is fed as input into the Bidirectional Long Short-Term Memory (BiLSTM) for the prediction of website relevance. Finally, the Birds Swarm Optimization-Bidirectional Long Short-Term Memory (BSO-BiLSTM) based classification model is used to classify the webpages and the BSO algorithm is employed to determine the hyperparameters of the BiLSTM model so that the overall crawling performance can be considerably enhanced. For validating the enhanced outcome of the presented
model, a comprehensive set of simulations are carried out and the results are examined in terms of different measures. The Automated Word Embedding with Parameter Tuned Deep Learning (AWE-PTDL) technique has attained a higher
harvest rate of 85% when compared with the other techniques. The experimental results highlight the enhanced web crawling performance of the proposed model over the recent state of art web crawlers
Investigation of recent progress in metal-based materials as catalysts toward electrochemical water splitting
No full textIn the present study, the mechanical behavior of Pt-graphene nanocomposites has been investigated using molecular dynamics simulation (MDS). Preparation of Pt-graphene nanocomposite was performed by powder metallurgy method. Adding porosity to these structures reduces the weight of the manufactured specimens and ultimately increases the usability of this specimen in various industrial and medical
applications. Therefore, in this study, factors such as the number of graphene nanosheets, graphene atomic ratio, and porosity on the mechanical behavior of platinum-graphene (Pt-graphene) nanocomposites have been investigated. The results show that the mechanical strength of the sample is improved by
increasing the number of nanosheets in the Pt structure. By increasing the number of graphene nanosheets from 10 to 20, YM and final structure strength increase from 1099 MPa and 116 MPa to 1231 MPa and 130 MPa, respectively. By adding 4% of graphene nanosheets to nanocomposites, the amount of Young’s modulus (YM) and ultimate strength (US) is reduced from the maximum value (1396 MPa and 143 MPa) to 1044 MPa and 110 MPa, due to the effects of aggregation. Also, increasing
the atomic ratio of graphene from 1 to 5 % leads to an increase in YM from 1099 to 1396 MPa and an increase in US from 116 to 147 MPa. On the other hand, increasing the porosity (from 1 to 5 %) leads to a decrease in YM to 969 MPa and the nanocomposite US to 102 MPa, respectively. Finally, by performing this simulation and studying the mechanical behavior of this nanocomposite, it is expected that optimal mechanical systems can be designed for use in medical purpos