bluuebunny/crossref_metadata_2025 huggingface dataset:
Active dendrites enable strong but sparse inputs to determine orientation selectivity
Authors: Goetz Lea , Roth Arnd , Häusser Michael
Published: July 2021

Significance

An active pyramidal cell model, constrained by physiological and anatomical data, was used to simulate dendritic integration in vivo. The model shows that small numbers of strong excitatory synapses can trigger dendritic Na
+
and NMDA spikes. Moreover, only a few dendritic spikes are sufficient to drive a single output action potential. As a consequence, as few as 1% of the synaptic inputs to a neuron can determine the tuning of somatic output in vivo. These results suggest that dendritic spikes can help to make sensory representations more efficient and flexible: they require fewer connections to sustain them, and only a small number of connections need to be changed to encode a different stimulus and alter the response properties of a neuron.
Dopaminergic brainstem disconnection is common to pharmacological and pathological consciousness perturbation
Authors: Spindler Lennart R. B. , Luppi Andrea I. , Adapa Ram M. , Craig Michael M. , Coppola Peter , Peattie Alexander R. D. , Manktelow Anne E. , Finoia Paola , Sahakian Barbara J. , Williams Guy B. , Allanson Judith , Pickard John D. , Menon David K. , Stamatakis Emmanuel A.
Published: July 2021

Significance

Understanding the neural bases of consciousness is of basic scientific and clinical importance. Human neuroimaging has established that a network of interconnected brain regions known as the default mode network disintegrates in anesthesia and after brain damage that causes disorders of consciousness. However, the neurochemical underpinnings of this network change remain largely unknown. Motivated by preclinical animal work and clinical observations, we found that across pharmacological (sedation) and pathological (disorders of consciousness) consciousness perturbation, the dopaminergic source nucleus, the ventral tegmental area, disconnects from the main nodes of the default mode network. As the severity of this dopaminergic disconnection was associated with default mode network disintegration, we propose that dopaminergic modulation may be a central mechanism for consciousness maintenance.
MYO1F regulates antifungal immunity by regulating acetylation of microtubules
Authors: Sun Wanwei , Ma Xiaojian , Wang Heping , Du Yanyun , Chen Jianwen , Hu Huijun , Gao Ru , He Ruirui , Peng Qianwen , Cui Zhihui , Zhang Huazhi , Wang Junhan , Jia Xinming , Martin Bradley N. , Zhang Cun-Jin , Li Xiaoxia , Wang Chenhui
Published: July 2021

Significance

Each year, the global mortality rates for fungal diseases now exceed those for malaria and breast cancer and are currently comparable to those for tuberculosis and HIV. The limited scope of currently available antifungal drugs is the major factor underlying the observed high mortality rate. Here, we provide evidence that Myosin IF (MYO1F) plays a critical role in the mediating of signaling molecules “trafficking from membrane to cytoplasm,” and this process is essential for the antifungal signaling pathway activation. Moreover, we provide evidence that Sirt2 deacetylase inhibitors promote antifungal immunity and protect mice from lethal
Candida albicans
infection, which indicates that the Sirt2 could be a good therapeutic target for the antifungal drug development.
Optical conductivity and superconductivity in highly overdoped La

2−
x

Ca

x

CuO
4
thin films
Authors: Kim Gideok , Rabinovich Ksenia S. , Boris Alexander V. , Yaresko Alexander N. , Suyolcu Y. Eren , Wu Yu-Mi , van Aken Peter A. , Christiani Georg , Logvenov Gennady , Keimer Bernhard
Published: July 2021

Significance

Chemical substitution is widely used to modify the charge-carrier concentration (“doping”) in complex quantum materials, but the influence of the associated structural disorder on the electronic phase behavior remains poorly understood. We synthesized thin films of the high-temperature superconductor

L
a

2
−
x

C
a

x

C
u
O

4

with minimal structural disorder and characterized their doping levels through measurements of the optical conductivity. We find that superconductivity with

T

c

= 15 to 20 K is stable up to much higher doping levels than previously found for analogous compounds with stronger disorder. The results imply that doping-induced disorder is the leading cause of the degradation of superconductivity for large carrier concentration, and they open up a previously inaccessible regime of the phase diagram of high-temperature superconductors to experimental investigation.
Beyond segments
Authors: Wang Xin
Published: July 2021

This review attempts to chart a research program that focuses on tonal bilingualism. More than 70% of the world
languages use pitch contours to disambiguate word meanings, however, limited empirical and theoretical effort was made to
understand the processing mechanisms of lexical tones in the bilingual context. This article will start with the main
characteristics of tonal languages, with a focus on Mandarin Chinese, followed by empirical findings on lexical tones in both
monolingual and bilingual populations. Finally, this article will propose a few important theoretical issues relevant to tonal
bilingualism and implications of learning a tonal language as a second/foreign language.
The development of interlanguage pragmatic markers in alignment with role relationships
Authors: Xiao Hao-Zhang , Dai Chen-Yu , Dong Li-Zheng
Published: July 2021

Studies on the development of interlanguage pragmatic markers (PMs) have attracted increasing interest recently. However, little research is available on the PM dynamic development in alignment with English-as-a-foreign-language (EFL) classroom contexts. Given the lacuna, this article, based on the Complexity and the Alignment theories, investigates how PMs develop and how aligning with film-situated un/equal role relationships influences development. The study with eight data collection points tracks 28 EFL learners’ PM production over around 1.5 year. Results revealed: (1) the employed PM functions fluctuated but developed from singular to multiple, with the interpersonal function use being regressive and the structural and the cognitive, progressive; (2) the PM development manifested a significant gain in aligning with the equal role relationships; and (3) different proficiency learners had dissimilar PM development. These findings corroborate the view of context-dependent dynamic development and provide strong evidence for aligning EFL learning with various role relationships.
Erwinia ananas
. [Distribution map].
Authors: UK, CAB International
Published: July 2021

A new distribution map is provided for
Erwinia ananas
[Pantoea ananatis pv. ananatis]
Serr. Hosts: Pineapple (
Ananas comosus
). This map is discontinued because of doubt concerning the identity of the causal agent(s) involved. Various bacteria have been found associated, and have occasionally been reported to cause the disease called marbled fruit.
Human rabies: prospects for elimination
Authors: Changalucha Joel , Hampson Katie , Jaswant Gurdeep , Lankester Felix , Yoder Jonathan
Published: July 2021

Almost half of all countries in the world are effectively free of human deaths from dog-mediated rabies. But the disease still affects people in low- and middle-income countries, especially the rural poor, and children. Successful regional elimination of human rabies is attributable to advances in significant and sustained investment in dog vaccination, post-exposure vaccination and surveillance, illustrated by productive efforts to reduce human rabies in Latin America over the last 35 years. Nonetheless, countries still facing endemic rabies face significant barriers to elimination. Using the 2017 Global Strategic Plan to end human rabies deaths from dog-mediated rabies by 2030 as a reference point and an organizing framework, we assess progress toward global rabies elimination by examining the characteristics of successful regional control efforts and barriers to elimination. Although substantive barriers exist for countries where rabies remains endemic, advances in knowledge, technology, institutions, and economics provide a basis for optimism.
ADAR and hnRNPC deficiency synergize in activating endogenous dsRNA-induced type I IFN responses
Authors: Herzner Anna-Maria , Khan Zia , Van Nostrand Eric L. , Chan Sara , Cuellar Trinna , Chen Ronald , Pechuan-Jorge Ximo , Komuves Laszlo , Solon Margaret , Modrusan Zora , Haley Benjamin , Yeo Gene W. , Behrens Timothy W. , Albert Matthew L.
Published: July 2021

Cytosolic double-stranded RNA (dsRNA) initiates type I IFN responses. Endogenous retroelements, notably Alu elements, constitute a source of dsRNA. Adenosine-to-inosine (A-to-I) editing by ADAR induces mismatches in dsRNA and prevents recognition by MDA5 and autoinflammation. To identify additional endogenous dsRNA checkpoints, we conducted a candidate screen in THP-1 monocytes and found that hnRNPC and ADAR deficiency resulted in synergistic induction of MDA5-dependent IFN responses. RNA-seq analysis demonstrated dysregulation of Alu-containing introns in hnRNPC-deficient cells via utilization of unmasked cryptic splice sites, including introns containing ADAR-dependent A-to-I editing clusters. These putative MDA5 ligands showed reduced editing in the absence of ADAR, providing a plausible mechanism for the combined effects of hnRNPC and ADAR. This study contributes to our understanding of the control of repetitive element–induced autoinflammation and suggests that patients with hnRNPC-mutated tumors might maximally benefit from ADAR inhibition-based immunotherapy.
Thermally Radiative Casson Fluid Flow over a Cylinder with Newtonian Heating and Heat generation/absorption
Authors: Loganathan K , Sivakumar M , Mohanraj M , Sakthivel P
Published: July 2021

This communication explains the impact of thermally radiative flow of a Casson fluid over a cylinder with velocity slip, suction/injection, and Newtonian heating condition. The governing PDE expressions are remodeled into an ODE expressing by applying suitable variables. The homotopy analysis (HAM) technique was implemented for solving our models. The impact of velocity field, temperature distribution, skin friction coefficient, Nusselt number in terms of diverse physical parameters like Casson parameter, suction/injection parameter, Newtonian heating parameter, radiation parameters, heat generation/absorption, Hartmann number and velocity slip parameter. The Hartmann number leads to slow down the fluid velocity, skin friction coefficient and local Nusselt number. The slip parameter decreases the fluid velocity and enhance the fluid heat transfer gradient.
Pulsating flow of Casson nanofluid through a channel with thermal radiation and applied magnetic field
Authors: Thamaraikannan N , Karthikeyan S
Published: July 2021

The pulsating flow of MHD Casson nanofluid flow through a channel with the influence of thermal radiation is studied, considering the nanofluid flow in the vertically upward direction, maintaining the same velocity at the lower wall and upper wall. The perturbation technique was employed to solve the dimensionless expressions of velocity and temperature. The effect of various parameters such as Prandtl number and Casson fluid parameter on flow variables has been discussed.
Oscillatory Behavior of Solutions for Certain Fractional order Difference Equations
Authors: Shanmugapriya R , Mohammed Ali Jaffer I
Published: July 2021

In this paper, new oscillation criteria is obtained for solutions of fractional difference equations by using Riccati transformation technique. Some applications are also presented for the established results.
Secure efficient signature for internet of things over near-ring
Authors: Muthukumaran V , Arun M , Satheesh Kumar S , Kumta Samyukta D , Angeline Kavitha M , Vijayaraghavan R
Published: July 2021

Prediction of air quality is a topic of great interest in air quality research due to direct With rapid progression in remote innovation and inescapable computerized innovation have given in expanding prevalence and enthusiasm of Internet of Things (IoT) procedure, universally giving comfort and knowledge to our day by day exercises. In IoT based framework situation, shrewd parts are associated wherever as all inclusive things connected in an inescapable model. Guaranteeing security for intersection among brilliant items is fundamentally progressively significant, in this paper, we propose a novel signature scheme which is utilized for carrying communication amongst devices in IoT environment. Moreover we revealed different scheme that are vulnerable. The significance of the proposed scheme over other existing scheme are analyzed in terms of the summary which is illustrated using performance and security comparison.
Pythagorean Nano Alpha Interior and Alpha Closure
Authors: Joseline Charisma J , Ajay D
Published: July 2021

The main objective is to make a study on the basic properties and relation between Pythagorean nanoa-interior and Pythagorean nanoa-closure by defining them in Pythagorean nano topological spaces. Also certain Pythagorean nanoa-continuous, Pythagorean nano semi and pre continuous functions which are weak forms of Pythagorean nano continuous functions are also defined.
Fixed solutions of second order nonlinear difference equations
Authors: Raju M , Selvamani C
Published: July 2021

The paper is concerned with asymptotic and stability behaviors of fixed solutions of the second order nonlinear delay difference equation of the form ?2(xn+pnxn-k-qnxn-l)+ f(xn) = 0, n = 0,1,2, · ··,. Examples are provided to illustrate the results.
Forward and backward difference equations in digital signal processing
Authors: Parveen Banu M , Jothilakshmi R
Published: July 2021

The relationship between difference equations with constant coefficients, obtained by establishing forward and backward differences in the filter design concepts of digital signal processing is explored in this paper. Moreover, thecorrelation is established between the input-output difference equations along with definite time invariant linear systemand the state spacedifference equationsrelated to filter design andthisleads to identify the efficient adaptive filterdesign and validate its function. Finally, the state space illustration of a system is provided, that is acceptable to construct and validate a new developed system between the difference equation and the digital signal processor.
Role of recursive cubic spline interpolation method and convolution filter in image processing
Authors: Gajalakshmi N , Karunanithi S
Published: July 2021

During this article, we suggested a RCSIM through Convolution filter. This filter explores the images to enhance and improve the efficiency of both gray scale and color images. Initially we identified the noises in the images and simultaneously, the corresponding pixels are noticed to improve that particular part of that image using edge detection algorithm. The pixel values of the image is converted as the window size of the matrix. This matrix should be a (n

X n) square matrix and then we applied the convolution filtering techniques to the (« X n) matrix. The development of the (input) image through the convolution filter yields the feature map. The feature map accentuates the uniqueness of the original image. At the same time, the RCSIMis used to interrupt the mathematical data to the feature map. The proposed approach reduces the sound and protects the efficiency of the unique image.
Common fixed point theorems in complex valued extended b-metric spaces under rational contractions
Authors: Arul Xavier A , Carmel Pushpa Raj J , Maria Joseph J , Marudai M
Published: July 2021

The objective of this work is to investigate the existence and uniqueness of fixed point and common fixed point hypotheses in complex-valued extended b-metric space for a pair of mappings fulfilling some rational contraction conditions which sum up and bind together some notable outcomes in the writing.
Evaluation of Antenna Dependent Wireless Communication Based on LoRa For Clear Line of Sight (CLOS) And Non-Clear Line of Sight (NC-CLOS) Applications
Authors: Alset Utkarsh , Mehta Hrishikesh , Kulkarni Atul
Published: July 2021

The emerging field of the internet of things (IoT) requires a low-power-low-range solution in remote and inaccessible places where connectivity in any form is not possible. There are many IoT devices like Zigbee, LoRa WAN, Sigfox, which operate within 5m to 5kms, with a change in bandwidth and power consumption. The difficulties in installing these types of IoT devices are critical because of connectivity issues and external hindrances like a non-clear line of sight (NC-LOS), frequency, bandwidth, time on Air (ToA), and power availability. The long-range (LoRa) is a portable, low-power wireless communication device that works on the principle of chirp spread spectrum (CSS) modulation. Its performance concerning frequency, power consumption, ToA, clear line of sight (CLOS), and NC-LOS depends on the type of antenna used for unknown distances. Therefore, in this paper, the 868MHz frequency is used to communicate between LoRa - end-transmitter node to LoRa-end receiver node with a fixed bandwidth of 125 kHz in the premises of Symbiosis. The constant data size, also known as the data-packet of 11-bytes, is sent wirelessly through transmitter-node receiver-node at different locations and altitudes. The contribution of this paper is to investigate the distance required to transmit the data-packet and give a choice of the antenna in CLOS & NC-LOS. A practical demonstration of different low-cost available antennas with variation in the distance with different LoRa devices like SX1276/SX1278 is proposed. It shows that the low-cost helical type antenna is more-favorable horizontally and vertically up to a certain range in CLOS and NC-LOS conditions.
Detection of Hexavalent Chromium Concentration in Aqueous Solution Using Lab Developed Colorimeter
Authors: Deshpande Pooja , Alset Utkarsh , Mehta Hrishikesh , Kulkarni Atul , Patil Yogesh
Published: July 2021

The detection of hazardous carcinogenic heavy metals in aqueous solutions is important for biological health and environmental protection. There are various techniques to ascertain these oncogenic chemicals in an aqueous solution, like a potentiometric electrochemical sensor, spectrophotometer sensor, colorimeter sensor, and chemical sensors. As compared to other available methods, the colorimeter sensor has advantages such as low-cost instrument, qualitative sample detection, and higher precision. In this paper, the colorimeter is developed in the lab to detect hexavalent chromium [Cr (VI)] in the aqueous solution. Moreover, the absorbance principle is used to calibrate and measure the known sample concentration using amplified optical power light-emitting diodes (OP-LED). The estimation of Cr (VI) concentration in an aqueous solution is evaluated and programmed in a low-cost Arduino UNO development board. The concentration value is displayed on the touch screen. The readings displayed on the lab developed instrument annotates that the concentration percentage of the known sample can be used to determine the unknown concentration. The concentration of the known solution is determined and compared with commercially available colorimeters concerning the lab-developed colorimeter.
RETRACTED: Classification Techniques for Behaviour study of Autism spectrum Disorder
Authors: Vignesh U , Suma K G , Elakya R , Vinothini C , Senthil Kumar A M
Published: July 2021

Autism spectrum Disorder is a mental imbalance disorder. Research has distinguished that youngsters with Autism Spectrum Disorders (ASD) as a rule show challenges in language securing, proficiency improvement, and social association. Albeit broad examinations have been led to portray shortages in language and social attitudes among youngsters with Autism range issue, inquire about on the proficiency advancement of this gathering is as yet meagre. This is the most valuable data for neurons to take care of a specific issue in light of the fact that the weight typically energizes or hinders the sign that is being conveyed. They will include the provision of information and advocacy, assessment, early intervention therapies, help at school, behavioral support, individual support, supported accommodation and respite. The National Autistic Society’s Pledges initiative, which offers neuro-typical people 18 ways to alter their behaviour in order to help friends and colleagues on the spectrum, they seemed really obvious. Every neuron has an inner state, which is called an actuation signal. Mental imbalance conduct expectation technique helps in dealing with the Autism lack utilizing a few grouping calculations and Neural Networks.
A Comparative Study on the Feasibility of Graphene Based Avidin Conjugate for Potential Curcumin Detection
Authors: Dey Nibedita , Raj Deena S , Devasena T
Published: July 2021

In the area of interdisciplinary research, modern and creative methods of interpreting substances are still of considerable importance. Curcuma longa’ active component commonly known as diferuloylmethane is the most sorts after food preservative, medicinal spice, additive and coloring agent, which harbors a wide range of the biological spectrum. The major problem observed with this wonder drug is the low bioavailability of the drug in the gut, hence leading to further lower concentrations of the therapeutic reaching the tissues and plasma. Constituting only a minor part of its parent rhizome, curcumin is not the only compound to be offered by turmeric, but for certain ailments, the amount of curcumin required is more than others, and this higher concentration of curcumin cannot be met with a daily consumption of curcumin from the normal food diet. This very fact has led to the introduction of commercialization of supplements of curcumin as tablets and capsules. This artificial rise in curcumin levels by supplementation could have an opposite impact on the human body, as some reports have indicated. Therefore, a potential alternative, quick, economical way of sensing curcumin was proposed in the present research. The effect of protein decorated electrode in the same was studied. Before experimental implantation, the experimental feasibility of the same through docking was checked. In silico study on the possible interaction of the protein with curcumin, a protein with GO and rGO respectively using discovery studio 4 software was conducted. Experimental feasibility deals with the sensing of curcumin using electrochemical work station using avidin conjugated GO (Av-GO) and rGO (Av- rGO). The Av-GO modified electrode showed a lowest detection of 3.9nM while the Av-rGO modified electrode showed a lower detection limit of 4.9nM. These values have been the lowest using avidin that has been reported for curcumin. The concentration detected correlates to the quantity that is present in the gut physiology, hence substantiating the potential use in real time sensing of curcumin.
ZHLS Security Enhancement by integrating SHA256, AES, DH in MANETS
Authors: Barani Sundaram B , Mishra Manish Kumar , Thirumoorthy Dhanabal , Rastogi Umang , Pattanaik Balachandra
Published: July 2021

In this century fast growing and progressive change of technology, Mobile Ad hoc Network (MANET) which is a no centralized structure plays great role. The routing protocol in this network is objective to deliver efficient route since sender to receiver. One of the hybrid routing protocols example is Zone Based Hierarchical Link State Routing Protocol (ZHLS) that is can’t allowable huge amount of inside attacks which arise from malevolent nodes. The third party in the routing system may drop the data, as well as disturbs the progression of the routing. To resolve this difficult, ZHLS Security is enhanced by integrating SHA256, AES, DH in MANETS. Security to routing protocols in MANETS is incorporated with different traditional Security mechanisms. My idea behind this thesis is to use integrated security ZHLS protocol by integrating Advanced Encryption Standard (AES) as well as secure hash algorithms to provide the data security. Also, it is, Deffi-Hellman to preserve privacy among the data transmission nodes. In the proposed method, AES is applied to symbol, also authentication to provide the confidentiality of the message in the routing system. This work will be simulated on NS2 environment and it may highly improve the security of data transmission among wireless mobile nodes.
Study of Detection Analysis of Cardiac Amyloidosis Heart Disease Using Image Segmentation Technique
Authors: Jebakumari Gladys , Raaza Arun
Published: July 2021

Cardiac amyloidosis is a collection of mayhem, which increases the less important disposition of abnormal proteins in the heart. It may happen either in segregation or like a fraction of systemic disease and can be hereditary or attained. The major forms of amyloid proteins, namely Amyloid Light Chain also Amyloid Transthyretin (ATTR), can penetrate the heart. With the enhanced utilization of advanced image techniques and procedures, the identification and diagnosis of cardiac amyloidosis, especially ATTR, has become very easier. In general, congestive heart failure disease has been diagnosed through an electrocardiogram. In this survey, the ultrasound heart image is gathered as an input image to diagnose whether the heart’s functioning is normal or abnormal. Based on input ultrasound heart image or picture, the ultrasound high-frequency sound waves afford the heart’s image and valves, which allows us to observe the heart-pumping action. The image segmentation technique was well performed in segmenting the specified heart image into high-intensity range, and low-intensity level deliberated to enhance patients’ lives with cardiac amyloidosis. The disorders or variations or any abnormalities happening in the heart can be done via a segmentation approach through that intensity level.
Sliding Mode Control and Fuzzy With MPPT Control Based PV Integrated Grid System
Authors: MadhusudhanaRao G , Jayaprakash S , Murugesan R , Soundara Bala S
Published: July 2021

In this paper, the photovoltaic (PV) system based energy generation with grid integration of inverter and DC-DC boost converter. To enhance the system transient response and track the PV voltage in the load perturbations, the sliding mode controller (SMC) is implemented. The power conversion of DC-DC is accomplished using the converter controlled using the fuzzy logic controller with the MPPT control system. The proposed system increases the grid system stability, and it is achieving the quick settling time in power converter output, which means DC link voltage improvement. The results are achieved using the MATLAB/Simulink, and the obtained results are verified successfully.
A Shared Blockchain Intelligent Public Protection Service Framework
Authors: Reddy Gangireddy Prabhakar , Kalaiselvi Geetha M , SureshAnand M , Jaanaa Rubavathy S
Published: July 2021

With accelerated technical advancements in the IoT network, an intelligent scheme of public security is possible with the incorporation of heterogeneous data processing systems, with which public security services will collaboratively be provided. While this system design has always been pursued by IoT and Cyber internal environments, the provision of scalable and flexible IoT-based PLC frames in a legacy system is challenging. Traditional security techniques are sometimes founded on a tall structure which can be an in efficiency or a point let-down. Enthused through micro services also blockchain technologies, this article offers the Smart Public Security Architecture of Blockchain-Enabled Decentralized Micro services. A micro service-based authentication framework is implemented within a licence blockchain network for safe monitoring of data access in a PLC environment. Such functionality is divided into a single, intelligently organised package micro service which is dispersed at fog and edge node computing. A comprehensive experimental study found that the Blend MAS proposed would provide decentralised, scalable and secure intelligence gathering and access controls to the purchaser of IoT based PLC systems.
Community-Friendly and Cost-Effective Monitoring Device for Environmental Pollution Using IoT
Authors: Balarengadurai C , Akilandeswari A , Raja A , Kalimuthu K
Published: July 2021

Air contamination is today the world’s toughest problem for the environment and public health. Air contamination has a detrimental effect on the wellbeing of humans, the atmosphere and the biodiversity. Factory air pollution continues caused by leaked toxic gases, vehicle waste and increasing accumulation of unhealthy gases and particulate matter. Particular materials are among the principal parameters of elevated air emissions, including real-time air quality monitoring to be monitored and analysed to determine correctly in a prompt manner. A standalone air quality control system with many parameters in operation in real-time is introduced in this article: CO2, temperature, humidity, air quality PM 2.5 and carbon monoxide. In reality, in every sector, the Internet of Things is commonly used and is also a key factor in air quality management. The Internet of Things Cloud Computing is a new way of improving the data processing of multiple sensors obtained and transmitted by the low-cost Raspberry pi ARM minicomputer.
Connectivity and Mobility Awake Efficient Routing In MWSN
Authors: Lenin J. , Asha Shiny X. S. , Vanisree K. , Sivakumar P.
Published: July 2021

Mobile Wireless Sensor Networks (MWSNs) have established their applications in various streams, particularly in agriculture, forest fire detection, and military applications. However, insufficient bandwidth, communication faults, energetic topography, energy restraints, and stability of connection variations guide to node movement. However, the major problem is to link failures between sensor nodes. As s result, make the rerouting process create an additional delay. To solve the connectivity and Mobility Awake Efficient Routing in MWSNis introduced. We design this paper is mainly for monitoring crop agriculture also produce the supervise information to base stations. In this strategy, the dynamic connectivity is used to measure the node connectivity among nodes. Average encounter rate and the route encounter rate is applied to evaluate the node mobility. These three parameters are used to choose the best forwarder node in MWSN. Simulation results illustrate that improve the network performance equate to the baseline approach.
Cryptochain approach to Cloud Computing Security: Case study, Challenges, and Solutions
Authors: Mukherjee Subham , Sandane Raghav
Published: July 2021

Cryptochain has attracted the new generation of FinTech technologies because of its disruptive security that adapts to teaching time. In particular, it provides security with peer-to-peer authentication, encryption, and hash generation. According to the FinTech sector, the security market’s technology sector is predicted to grow to $ 20 billion at the end of 2021. With this, the cryptochain can operate across the whole Internet of Things (Cloud) ecosystem; its programs are predicted to expand. Cloud technology has been widely welcomed in all tech fields for its efficiency and reliability. This paper will discuss the theory of cryptochain technology and elated thermal research methods. We will learn how to sync cryptochain security on a cloud with its secure data solutions.
Segmentation of Services Provided by E-Commerce Platforms Using PAM Clustering
Authors: Gaikwad Divya , Lamkuche Hemraj
Published: July 2021

Today, data analytics have helped in solving many critical issues in various domains. From credit card fraud detection, detecting cancer to sentiment analysis, data analytics has come a long way. One of the important domains is e-commerce. With everything going digital, shopping has made its significant place in the digital world. A Partition around Medoids (PAM) clustering algorithm is discussed for grouping the services provided by e-commerce websites to their customers. The PAM clustering method helps to work upon real-time data with mixed data types. The clusters formed will provide better insights and patterns for the businesses to make better decisions in order to improve their customers’ engagement and multiply their profits using the historical data. With limited time and resources to invest, this method helps the company to proceed further by understanding the focus points of each service and their scope of development. Implementation of the proposed PAM clustering is done on the artificial dataset and is found to be effective.
Fusion of ACO and PSO Technique Based Optimized Routing for Intellectual Routing in Wireless Ad hoc Networks
Authors: Velmurugan A K , Madhan E S , Padmanaban K , Senthil Kumar A M
Published: July 2021

Wireless Ad hoc network (WANET) is an assortment of mobile nodes, which energetically custom a provisional network lacking the dependence of any infrastructure. In Dijkstra-Ant Colony Optimization Algorithm (ACO) forStraightas well asHarmlessEmigrationis applied to finding the shortest and safest path. However, this method cannot work perform when nodes are movable. In addition, ACO algorithm increases the power consumption and execution time. To solve the above problem in this work, Fusion of ACO and PSO technique based Optimized Routing (FAPO) for Intellectual Routing in WANET. This approachACOand Particle Swarm Optimization (PSO) technique is proposed to provide optimized routing and reduces link failures. The ACO and PSO techniquesinitiates with creating a greatquantity of mobile nodes in the search space and selects the route with high quality link. The function of the introducedtechnique is measured using the network simulator tool NS-2.
Analysis for Lossless Data Compression Algorithms for Low Bandwidth Networks
Authors: Semunigus Wogderes , Pattanaik Balachandra
Published: July 2021

Analysis for loss less data compression delivers the relevant data about variations of them as well as to describe the possible causes for each algorithm and best performing data types. It describes the basic lossless techniques of data compression Huffman encodes, Arithmetic Encoding, and Lempel Ziv Encodings then briefly with their effectiveness under varying data types of Latin text, audio and video. These properties give the solution of which lossless compression algorithm more suitable compared to other from the Saving Percentage, compression ratio, time of compression and time of decompression with Low Bandwidth Network. Moreover here Lossless Data Compression Algorithms (LDCA) being implemented and tested Huffman compression, Arithmetic compression, and Lempel Ziv algorithms, the implemented result shows that LZW algorithm saves more size than that of the others two with text file, Huffman compression algorithm saves more file sizes and the time takes to compressed decompress is higher than that of other two for audio file type and finally Huffman performs greater on very huge data compressions that is due to much compressing capability.
Understanding and Analysing Resource Utilization, Costing Strategies and Pricing Models in Cloud Computing
Authors: Ramesh Aishwarya , Pradhan Vishal , Lamkuche Hemraj
Published: July 2021

This paper is primarily focused on understanding the basics of cloud computing economics – specific pricing models and general cost structure and compares between basic cost structures. It also examines 15 pricing models dependent on various bases and attempts to consolidate the different pricing methods used to guarantee maximum profitability to both the service provider and consumer. To avail the services of cloud computing from the cloud service provider, the organization has to incur individual costs. There are three types of costs: fixed, variable, and semi-variable costs. Each type is computed and analyzed. There are more than 30 pricing models though the pay-as-you-go model, subscription model, and pay-for-resources models are in demand. To consider and discuss the basics of cloud computing, emphasizing its economics and pricing models considering various aspects and costing components, using and estimating plans from various cloud Registering suppliers. The paper also considers identifying gaps, if any, present in the current pricing models that are highly preferred with other pricing models that are designed but not implemented due to practical conditions and fear of higher percentage of risk and error and to compare the basic prices provided by the cloud service providers.
Power efficient in WSN supported clustering and tree technique
Authors: Nasurulla I , Kaniezhil R
Published: July 2021

WSN (Wireless Sensor Network), an outsized quantity of sensor nodes are establish and that they for the most part devour power in communicating information over significant distances. Sensor nodes are power unit managed and their power is compact. Compact power unit face the problem of limited power unit lifetime that has become the main issue in these networks and which represents to a test to their plan and the board. There are several forward (routing) protocols are implemented on WSN to transfer the info supported the top user need. The main goal (target) of the forward protocols is to compress the consumption of nodes power and develop the nodes life time. Between many forward protocols, In PEGASIS, there are so many used protocols; each protocol overcomes their drawbacks on further improvements. In this paper proposed a novel procedure by establishes a crossover calculation for clustering and cluster follower choice inside the WSN. After the decision of cluster leader and follower nodes, the proposed Tree method is set up for apportioning and preparing the information. The proposed plot productively reduces the unseeing transmission messages yet additionally diminishes the sign overhead in light of the fact that the aftereffects of cluster arrangement. Inevitably, the forward strategy is given upheld the layered design. The proposed Tree engineering productively limits the forward ways toward the base station. Complete investigation is performed on the proposed plot with cutting edge unified bunching and circulated clustering procedures. From the outcomes, it is indicated that the proposed plot performs better than LEACH.
IoT based Emergency Handling Communication System for Medical and Traffic Rescue Teams
Authors: Lenin J. , Divya Jyothi M. G. , Alzadjali Najiba Said Hamed , Azeem Sheik Abdul
Published: July 2021

Cloud Computing is a thriving technology, capable of revolutionizing the planet. On the Internet of Things (IoT), all objects across the universe have the potential to connect, which in turn provides the citizens with an understanding of everything. Many programs hire IoT to help people make their everyday life better, faster and healthier. In this article, we are suggesting an IoT-controlled emergency response system for Medical and Traffic emergency handling teams, which could be very useful when a vehicle is experiencing a catastrophic accident. A quick and accurate assessment of the extent of the incident is critical to improve the overall recovery method and enable emergency responders to properly determine the resources needed. The proposed device immediately starts to work when an emergency condition is observed. The program would initiate communication with the authority involved and sends critical and relevant details, such as the position of the incident, monitored health condition and photographs taken while the accident happened, using the camera. The device implementation uses Raspberry Pi 3 and required specific sensors.
A Surveillance System Focused On Approved Blockchains and Computation of Edges
Authors: Victor Benevent Raj A. , Srikanth B. , Thilagavathy A. , Mathivanan B.
Published: July 2021

Video surveillance systems have become a critical tool for urban management in recent decades. Without visiting the scene, managers may grasp the scene information. The monitoring system can improve management and supervision effects and reduce the likelihood of major accidents. With both the invention of the Internet of Things (IoT) era, however, sensor networks face difficulties, like massive access to equipment, massive data, inadequate bandwidth, attack vulnerability and real-time surveillance problems. We provide an overview of the implementations situation of the visual supervision system accordance with the project blockchain and border computers. The framework uses BCs, edge processors, developments from the IPFS and transformed neural networks. Edge computing is used for huge wireless communication collection and analysis. The IPFS storage service can be used and CNN infrastructure is used in legitimate surveillance to do a large video collection.
Prediction of the Speed and Wind Direction Using Machine Learning
Authors: Pattanaik Balachandra , Manikandan S. , Peniel Pauldoss S. , Gobinath S.
Published: July 2021

The wind is a free energy source; however, its high unpredictability is a significant integration problem of large wind power plant into an energy system. In a wind conversion system, the wind speeds are a vital power-generated tracking, regulation, schedules and dispatch and satisfy consumer requirements. This paper proposes using the machine learning (ML) based ant colony optimization (ACO) method for the wind speed prediction. A correlation among predicted and real data from climate models showed strong consensus. The significance of the current research depends on its ability to forecast wind speeds, a crucial precursor to performing successful incorporation of wind power.
Review for the Solar Radiation Forecasting Methods Based on Machine Learning Approaches
Authors: Hemavathi U , Medona Ann C V , Dhilip Kumar V , Raja Sekar R
Published: July 2021

Predictions of solar potential for these systems’ production are important, whether they ensure sound activity or the perfect control of an energy discharge heading to the solar system. It is important to base the prediction on solar irradiance before predicting solar systems performance. The measurement of solar radiation elements is a very significant criterion for applications of solar energy. Several globalized solar radiation prediction modes can be done in the two major categories: cloud imagery with physical models and machine learning techniques are correlated. In this paper, the methods used to predict solar radiation are explained with machine learning algorithms.
Machine Learning-Based Solution Predicting Hardware Faults
Authors: Ganesan R , Prabahar Godwin James T , Perumal P , Kumar Pardeep
Published: July 2021

Constant exploration of better performance and energy consumption has led to several hardware-based generators being used in interdependent SoC. Such generators abuse the intrinsic contrast of activities, and they also forgive inconsistencies in their outputs, such as image and optical machine learning applications. At about the same time owing to process growing and control constraints, irreversible faults are escalating, leading to incorrect outputs. Strategy to resolve this issue, which uses machine learning training tools to improve the impact of permanent fix in hardware accelerators that can withstand incorrect outputs. The suggested financial benefits do not need any accelerator details and are highly flexible with low capital areas. Furthermore, earlier work is very time intensive as it involves the introduction of fault pairs into the gate netlists to test their effect on the outputs. To solve these problems, this paper proposed to improve representation first by increasing the degree of complexity from the degree of both the gate to a stage of actions. The power to make segments and sub of the same contextual definition with specific features by establishing numerous propagation commands in the supply chain context involves. Test data demonstrate that our proposed approach is a simple and reliable way of generating different designs to secure the device.
Glaucoma Image Classification Using Entropy Feature and Maximum Likelihood Classifier
Authors: Rebinth Anisha , Mohan Kumar S , Kumanan T , Varaprasad G
Published: July 2021

In general, the nerve that links the eye to the brain is affected because of high eye pressure. The most common kind of glaucoma sometimes has no other symptoms than a gradual loss of vision. In this study, the Glaucoma Image Classification (GIC) is made by using different entropy features and Maximum Likelihood Classifier (MLC). Initially, the input fundus images are decomposed by using rankles transform, then the entropy features like sample entropy, Shannon entropy and approximate entropy are used to extract features. Finally, MLC is applied for classification. The GIC scheme’s function produces the classification accuracy of 96 % by using Shannon entropy feature and MLC.
A Distributed Fewer Environment for the Use of Blockchain IoT Device Sharing
Authors: Sundaramoorthy K , Thenmozhi E , Josphineleela R , Suma Christal Mary S , Shanmugapriya T.
Published: July 2021

Due to the fact that the data markets become ubiquitous, it also becomes apparent that Internet of Things (IoT) applications produce data sources that are of benefit for future third party users. We are creating a marketplace for IoT data sources, allowing any pair of data providers and customers to participate in data transactions without any previous dependence on the shared trusts, to unlock those possible utility. We have a marketplace and architecture for the exchanging of streaming data, ranging from data publicity to legally binding exchange deals and payments. We prove that we can give participants an interchange of costs between the transactional data exchange and the possibility of loss of data when trading through unreliable third parties, through the use of blockchained technologies and smart contracts, in particular. On a test platform using Crypto currency Smart Contracts, we analyze these agreements experimentally.
Analysis on Sports Data Match Result Prediction Using Machine Learning Libraries
Authors: Kevin Andrews S , Lakshmi Narayanan K , Balasubadra K , Josephine M S
Published: July 2021

Sports research and betting have been powered by quick exposure to the Internet and machine learning popularity. Football is considered the most popular game in 200 countries and contrasts to other sports. It is considered much more diverse and complicated, making soccer an enticing area to do research. A variety of methodologies and methods are used for the production of prediction systems. We expect the outcome of a match between the Premier League and a home side. The projections are based on numerous significant evidences from the Premier League’s previous seasons. These essential characteristics would possibly decide the result of a match. We use three different algorithms to predict the machine learning techniques and then choose from those three the best algorithm for predicting the label.
Enhancement and Development of Next Generation Data Mining Photolithographic Mechanism
Authors: Geetha D , Kavitha V , Manikandan G , Karunkuzhali D
Published: July 2021

The analytical data of project management was established. In a stereolithography method, the APC system was already implemented in essential dimensions and overlays. Productivity and system efficiency have been enhanced. The new APC, however, is created on the inspection information where the method anomalies are blended with the fluctuation of the system and which have to evaluate very small quantities, and it has the impact cap. The inspection data for the CD, overlay and log information of the acquaintance tool in ainteractive data base have been compiled and processed. We have also investigated how the earlier in this thread problem can be paid and resolved. First of all, in the enormous tool log data we have extracted ties between inspection informationbesides several parameters, particularly factor loadings. We then discussed problems with big relationships and have, thus, gathered valuable knowledge which did not come out of the traditional system. In order to show the stabilising machine fluctuation effect, we developed, along with APC, a second-generationinformation mining system.