Search

Background: Haematological parameters have an important role in the early detection of the COVID19 disease. This study is aimed to study the hematological severity markers of COVID19 infected patients in first wave versus second wave in a tertiary care centre. Methods: This is a retrospective study done in government medical college/government general hospital, Suryapet. We collected the information regarding patient’s data from hospital records who were admitted in the hospital during first wave in September 2020 and compared it with the patients admitted in the second wave in May 2021. Results: In our study, a total of 341 patients with COVID19 infection admitted in our hospital were included. 136patients were admitted in first wave and 205 patients were admitted in the second wave. Out of 136 patients in first wave, 95 were admitted in non-ICU ward and 41 were included in ICU ward. We found that there is increased Absolute Neutrophil count, decreased Absolute Lymphocyte count and Platelet counts in second wave ICU patients. Conclusion: We conclude that based on the haematological parameters disease severity was more pronounced in second wave, especially ICU patients than first wave.

Background: To evaluate the prognostic value of Neutrophil to lymphocyte ratio (NLR) in Covid -19 patients at our district area hospital/ Teritary care center. Methods: It is a prospective study from 1-8-2021 to 30-9-2021. Patients who presented with complaints of Fever, sore throat, body pains, cough, breathlessness, diarrhoea were evaluated at the triage area of the Hospital. Throat swab was taken and RT-PCR was done and only 200 confirmed cases were included in the study. Patient blood samples were collected and processed in SYSMAX 5 -part, Heamotology analyser in the Hospital Central Laboratory. The patients CBP was processed in the laboratory NLR value calculated and tabulated. Results: Out of 200 cases number of Males were 145(72.5%) more compared to the female were 55(27.5%), with NLR value 1.0-3.9 in74 cases(37%) ,4.0- 6.9 in 63 cases (33%) , 7.0 – 9.9 in 25 cases (12.5%), 10-12.9 in 17 (8.5%) cases , 13-15.9 7 cases(3.5%), 16 -18.9 3 cases(1.5%) ,19-21.9 9 cases(4.5%) ,22-24.9 0 cases, 25-27.9 0 cases , 28-30.9 2 cases ( 1%). Conclusion: NLR Value more than 3.5 found to be significant and it is correlating with the patients symptoms.

Структуры 1,4-дииод-2,5-диметилбензола (1) и 1,3,4,6-тетраиод-2,5-диметилбензола (2) установлены методом РСА. Мотив упаковки в 2 определяется преимущественно π-стекингом и системой контактов галоген⋯галоген между стопками. Структура 1 — наличие как π-стекинга, так и взаимодействия между σ-дырками атомов иода и π-системой соседних молекул. Для 1 и 2 изучена их термическая стабильность, измерены оптические спектры.

For the photocatalytic degradation of Direct Blue 15 (DB15), tin oxide/polyaniline (SnO2/PANI) nanocomposites were prepared using the co-precipitation process. SEM, FTIR, XRD, and UV–Vis analysis were used to characterize the as-prepared SnO2/PANI nanocomposites. The XRD pattern confirms the presence of SnO2 reflection planes in both bare and SnO2/PANI. The changes in planes of SnO2 are owing to the incorporation of PANI in the SnO2. The metal oxide and the hydroxyl group of SnO2 are altered slightly with the substitution of PANI. The inclusion of PANI in SnO2 reduces the crystallite size and increases surface area compared to bare SnO2 nanoparticles. The reflectance and bandgap energy (3.1–2.7 eV) of the SnO2 decreased after the substitution of PANI. The photocatalytic dye removal efficiency of the SnO2/PANI nanocomposite was significantly improved compared to bare SnO2. The photocatalytic mechanism of SnO2/PANI nanocomposites for the degradation of DB15 is systematically explained, as well as the synergetic effect of SnO2/PANI nanocomposites. Toxicity of treated DB15 prompts a lesser impact on Artemia salina than untreated DB15. This experiment clarified that SnO2/PANI nanocomposites produced non-toxic by-products and they are lesser toxic to aquatic food web components.

Heterocyclic pyrene pyrazoline moieties containing similar structures but with differences in thiophene (PPT), furan (PPF) and pyridine (PPP) substitutions at the terminal molecules were synthesized. Their aggregation behaviour in THF-water mixtures was investigated and results demonstrated that PPT and PPP exhibited aggregation-induced emission (AIE), whereas PPF exhibited aggregation-induced blue-shifted emission (AIBSE). PPT and PPP provided red-shifted emission, while PPF had observed blue-shifted emission at high water fractions of 70-90%, confirming that aggregation effects played a major role in the molecular structure. Two emission peaks from locally excited and twisted intramolecular charge transfer confirmed the twisted nature from the dihedral angle values of the free reorganized molecules that were completely restricted in high water fractions due to molecular aggregation. This was further confirmed from colour Commission Internationale de l'Eclairage values as well as dynamic light scattering analysis. Third-order nonlinear optical properties were studied using a Nd:Yag laser beam Z-scan technique at 532 nm. The open aperture Z-scan revealed that PPT and PPF towards the peak point endured strong saturable absorption, whereas PPP indicated a strong reverse saturable absorption process. The AIE and AIBSE mechanisms from undergoing restricted twisting intramolecular motion in the aggregated luminogens provide great insight into new developments in AIEgen materials for these optoelectronic materials.

The influence of lattice strain on metal and metal oxide catalysts has been widely investigated by DFT calculations. However, it is still hard to prove by experimental methods. In the present investigation, we have explained how the experimentally obtained strain values are reflected in the catalytic decomposition of hydrogen peroxide by using MnO2 decorated on TiO2 and ZnO catalysts. The lattice strain parameter values have been derived from X-ray diffraction patterns using the modified Williamson–Hall (W–H) method. Uniquely, we observed that compressive strain could significantly affect the TOF of the reaction, especially on the MnO2/TiO2 catalyst. Furthermore, the equilibrium constant calculated from the Langmuir–Hinshelwood (L–H) kinetic model shows that the MnO2/TiO2 catalyst has a stronger adsorption capacity than the MnO2/ZnO material. These results directly reflect the strength of the oxophilic sites and the lattice strain of the materials. A quantitative relationship has been established between lattice strain and catalytic activity.

A new class of intermolecular hydrogen bonded liquid-crystal complex (HBLC) was designed and synthesized from non-mesogenic benzylmalonic acid (BMA) and mesogenic 4n-pentyloxybenzoic acid (5OBA). Intermolecular hydrogen bonds (H-bond) and vibrational functional groups were characterized by using Fourier transform-infrared spectroscopy (FTIR). Textural characterizations and the corresponding transition temperature along with enthalpy values were observed using polarizing optical microscopy (POM) and differential scanning calorimetry (DSC). The optical absorption and emission bandgap energies were calculated by using ultraviolet-visible (UV-vis) and photoluminescence (PL) spectra. The phase transition temperature, thermal stability factor, and thermal span width were calculated and their impact on the liquid crystal properties are discussed. An interesting feature of the BMA+5OBA HBLC complex was the observation of schlieren textures, and the induced thermoluminescence with parachromic variation in the nematic phase is an alternative tool for the manufacture of opto-electronic devices.

In this study, 8, 25 and 50 wt% Fe3O4@activated carbon (AC) catalysts were prepared by simple coprecipitation method. The efficiency of the catalysts for the advanced Fenton's oxidation process using methylene blue (MB) as a model substrate was tested. Both modified and unmodified activated carbon catalysts exhibited similar activity towards the Fenton's oxidation process. Therefore, it is difficult to identify the role of the catalyst in this dye removal process. Hence, we proposed a new methodology to remove the MB by adopting the adsorption process initially, followed by the Fenton's oxidation process. The proposed process significantly improved the methylene blue decomposition reaction over the 25 wt% Fe3O4@AC catalyst. However, this trend was not seen in pure activated carbon and Fe3O4@AC (8 and 50 wt%) catalysts due to the instability of the material in the oxidizing medium. The possible reason for the deactivation of the catalysts was evaluated from lattice strain calculations, as derived from the modified W–H models (Uniform Deformational Model (UDM), Uniform Stress Deformation Model (USDM) and Uniform Deformation Energy Density Model (UDEDM)). These results provided a quantitative relationship between the experimentally calculated lattice strain values and Fenton's catalytic activity. Furthermore, the optimized strain value and crystalite size of Fe3O4 on the activated carbon matrix are responsible for the high catalytic activity.

Poly(styrene)-co-poly(4-vinyl pyridine) (PS-P4VP) beads were prepared by suspension polymerization technique. PPI(G2) and PPI(G3) dendrimers were grafted on the surface of PS-P4VP beads and were two types of polymer supports viz., PS-P4VP-PPI(G2) and PS-P4VP-PPI(G3). Further, these above two different matrices were used to prepare six types of heterogeneous nanoparticle catalysts viz., PS-P4VP-PPI(G2)-AgNPs, PS-P4VP-PPI(G2)-AuNPs, PS-P4VP-PPI(G2)-PdNPs, PS-P4VP-PPI(G3)-AgNPs, PS-P4VP-PPI(G3)-AuNPs and PS-P4VP-PPI(G3)-PdNPs and AgNO3, HAuCl3 and K2PdCl4 as a metal precursor. The prepared catalysts were characterized by FTIR, UV–Vis, FESEM/EDAX and HRTEM to find the functional group and surface morphology of the catalysts. The catalytic efficiency of the heterogenous nanoparticle catalysts was studied by reduction of trypan blue (TB). The obtained kobs values explain that it to increase the generation numbers/active sites have been used to enhance the metal loading. On comparing the Ag, Au and PdNPs, the AuNPs immobilized beads are an outstanding catalytic activity because of high reduction potential. Especially, the PPI(G3) dendrimer stabilized AuNPs have higher catalytic efficiency, because the PPI(G3) dendrimer contains a greater number of surface amino groups stabilized the higher amount of AuNPs and increase the dendrimer generation (PPI(G2)–PPI(G3)) the particle size also reduced. Keywords: Poly(4-vinylpyridine), Dendrimer, Heterogeneous nanoparticles, Trypan blue

Automatic hand washing effectively washes human hands where most of the bacteria are eliminated. Through using more simple and effective hand washing technologies, it can enhance people’s lives. It would also improve the grooming of the hands of individuals. Recently, the outbreak and the related spread of COVID-19 and a few well known like Ebola virus diseases across the global countries including African country like Ethiopia stimulating waves was terrifying. The countries worst affected are China, the USA, Italy, and Spain. The former incidents of 1953 and those of 2015 and 2019 were unexpectedly repeated But the medical community has so far been unable to eradicate these lethal diseases. Viral particles are released on the surface from the breathing system of affected human tissue [1]. The infection is then contaminated by the second individual and sneaks into the body through the mucous membranes. In such cases, it is most likely that some individuals are infected by these conditions, which makes it a common prevention procedure to wash their hands.The new reach must be accomplished using a Microcontroller with a solar-powered intelligent machine, as all in one can be used for handwashing cum and drying equipment will be managed and these dangerous conditions actually do not have a known antidote but can be avoided by effective preventive steps. The hand cleaners are executed to make washing of the hands and the dryers operate together with the heater, the ventilator, and other parts. The design stage is tested until the device has been assembled for its results.

In this study, 8, 25 and 50 wt% Fe

Arena of electrocardiography (ECG)has been in presence for over a span, however regardless of noteworthy progresses in grown clinical electrocardiography, information analysis methods and advanced devices, the examination of unborn ECGs is silent in bud stage. This picture is, somewhat because of an absence of accessibility of unique databases, incompletely because of the abstemiously minimal signal and noise factor of the ECG signal derived from the fetus is contrasted with the maternal ECG which is measured by the electrodes and partially due to the fewer data of the clinical information, in relation to fetal cardiac function and improvement. Motivated by this above issues, in this paper we survey a scope of various preprocessing, extraction and assessment of Heart rate for unborn ECG examination that have been produced in the recent forty eons, and confer about their deficiencies and plusses.

Detection of White Blood Cell (WBC) cancer diseases like Acute Myeloid Leukemia (AML), Acute Lymphoblastic Leukemia (ALL), and Myeloma is a complex task in medical field because they are sudden in onset. Our proposed method consists of designing and developing an automated system which will assist the medical professionals in correctly diagnosing all the types and sub-types of this disease. In this paper, we have proposed a novel method in which we have taken microscopic blood images as an input image. A dataset of 100 images in which 62 training and 38 testing images is taken. After that we have converted the image to proper format (YCbCr) for segmentation. For segmenting, we have used the combination of Gaussian Distribution, Otsu Adaptive Thresholding and for clustering we have used K-Means method. Using Gray Level Co-occurrence Matrix (GLCM), the features are extracted and were used for classification using Convolutional Neural Network (CNN). The overall accuracy of the system obtained after processing is 97.3%.

The field of computer vision is devoted to discovering algorithms, data representations and computer architectures that embody the principles underlying visual capabilities. Computer vision is an interdisciplinary field that deals with how computers can be made for gaining high level understanding from digital images or videos. While very promising result has been shown on face recognition related problems, age invariant face recognition still relics a challenge. Facial appearance of a human varies over time, which results in substantial intra-class variations. In order to address this problem, we propose Frangi2D method for normalization, Linear Binary pattern (LBP) for feature extraction and Sparse Representation Classifier (SRC). Extensive results on a well-known public domain face aging dataset: MORPH. The experimental results show the superiority of our proposed method in age invariant face recognition.

Alzheimer’s disease (AD), a devastating neurodegenerative disease, is associated with the abnormal accumulation and aggregation of β-amyloid proteins (Aβ) along with the deposition of high levels of Cu, Fe and Zn ions in the brain, causing neuronal cell deaths to lead the cognitive disabilities and even death. As there is a direct relationship between AD and Aβ aggregation, an intense research activity has been made to develop drug materials that serve as probes and inhibitors for controlling the pathways of Aβ peptide aggregation. However, their relatively instability in aqueous medium, tedious sample treatment, multistep syntheses, or low detection ability limit their potential applications. Therefore, the development of photoactive metal complexes for the selective detection and inhibition effects of Aβ aggregation is a thrust area in biomedical research. In this review, the use of non-conventional photoactive metal complexes including Ru(II), Re(I), Ir(III) and Pt(II) has the potential advantages of probes for monitoring and inhibiting the fibrillation as well as the toxicity of Aβ over conventional dyes such as Thioflavin T (ThT). The geometry, multiple electronic/spin states and redox nature of metal centres have made them tunable properties. Upon binding to the Aβ peptide aggregates, they exhibit promising potential as anti-AD agents due to their fascinating photophysical properties include red emissions, large Stokes shifts, and long lifetimes, which differentiate the competitive binding of other short-lived fluorescent molecules via photoluminescence, and time-resolved measurements. In addition, metal complexes display their remarkable selectivity and superiority over ThT. Competition study between photoactive metal complexes and ThT on fibrillation process show their effective binding of metal complex with Aβ42 fibrils by hindering the ThT binding to give higher binding constants than that of ThT. Computational studies predicted a hydrophobic domain between amino acid binding sites and the functional group of photoactive metal complexes via different noncovalent interactions. Thus, attractive characteristics of photoactive metal complexes could influence remarkable evolutions in new dimensions, which in turn address current challenges in the clinical use of the detection and inhibition of Aβ fibrils.

Heteroleptic Zn(II) 3,5-iodosalicylate (DISA) complexes of general formula [Py2ZnDISA2] (Py = 3-methyl (1), 4-methyl (2), 3,5-dimethyl (3), 3,4-dimethyl (4) and 3-bromopyridine (5), respectively) were prepared and characterized by X-ray diffractometry and thermogravimetric analysis. All complexes demonstrate luminescence in blue region with quantum yields varying in 1.45–2.6% range.

The nitrogen doped glassy carbonaceous materials were obtained on thermolysis of melamine and phenolphthalein mixtures at 500 °C. Samples in amorphous carbon with 60–100 wt% of phenolphthalein form a single-phase nitrogen solid solution in glassy carbon. IR and Raman spectroscopy prove nitrogen to chaotically substitute carbon in these solutions. Maximal concentration of 21.0 wt% N has material with brutto formula C100H52.5N25.7O6.4. The electric resistivity of that sample is 290 Ohm*m, dramatically 34,000 times lower than resistivity of undoped glassy carbon prepared from phenolphthalein (107 Ohm*m). The C3N4 has resistivity of about 1011 Ohm*m.

A novel double hydrogen bonded ferroelectric liquid crystal (HBFLC) complex was isolated from (R)-(+)-Methylsuccinic acid (RMSA) and 4-Nonyloxybenzoic acid (9OBA). The presence of hydrogen bond between proton donor (RMSA) and proton acceptor (9OBA) molecules were characterized by FT-IR spectroscopy. Mesomorphic behavior and its phase transition temperature of the HBFLC complex (1:1 and 1:2 ratio) were studied by differential scanning calorimeter (DSC), polarized optical microscope (POM) and identified smectic A*, smectic C* and smectic G* phases by quenching of nematic. MSA + 9OBA HBFLC complex has strong dipole moment which is vertical to the lengthy molecular axis provide a pathway to the insight of smectic mesophases. Sm C* phase revealed paramorphic effect due to refractive index changes in the H-bond layers and leads violet to red color textures. Stabilization of the smectic phase by dipole-dipole interaction in the HBFLC complex was reported using density functional theory (DFT) analysis. Stability of the phase increase while increasing the mesogenic ratio in the present HBFLC complex was also discussed. The structure of the MSA + 9OBA HBFLC complex was optimized by B3LYP theory with the basis set of 6311-G (d, p). In natural bond orbital analysis, it was found that the high stabilization energy specified the intermolecular interaction among the molecules.

We are considering the website network http://www.pantechsolutions.net/ of the web navigation of the customers. This website network can be representing as an intuitionistic fuzzy directed graph by means of considering the navigation of the customers. In this intuitionistic fuzzy directed graph, the links are considering as vertices and the path between the links are considering as edges. The weightage of each edge are considering as number of visitors getting the link from one link to another link (membership value), number of visitors not getting the link, i.e. under traffic from one link to another link (non-membership value) and drop off case (intuitionistic fuzzy index). For this graph we are determining the maximum, minimum energies and its upper, lower bounds.

The reliability analysis of a component or a system is an important concept in almost all engineering disciplines. In general, fuzzy sets are used to analyze the system reliability. The system reliability may be formed as linear or nonlinear programming with cost function in fuzzy environment. To analyze the fuzzy system reliability, the reliability of each component of the system is represented as fuzzy number in nature. In this paper, we have presented the parallel system model with fuzzy cost function to evaluate the maximum reliability subject to minimum cost using trapezoidal fuzzy number and to find out the Co-efficient of Variance for each membership function. A numerical example is given to illustrate the model for nonlinear programming and to evaluate the system reliability.

The performance of the wavelets within the field of image process is standard. Multiwavelets is the next step in riffle theory and it takes the performance of wavelets to the next level. In this work the performance of the Integer Multiwavelet transform (IMWT) for lossy compression has been studied. The Proposed IMWT shows sensible performance in lossy reconstruction of the images than that of Existing lossy reconstruction. This work utilizes the performance of the Proposed IMWT for lossy compression of images with encoding techniques like Magnitude set coding and Run Length Encoding. The transform coefficients are unit coded by means of Magnitude set coding and run length coding techniques which in turn results with low bits. The transform coefficient matrix is coded on not taking under consideration of the sign values using the Magnitude Set--Variable Length Integer illustration. The sign data of the coefficients is coded as bit plane with zero thresholds. This Bit plane may be used as it is or coded to scale back the bits per pixels. The Simulation was exhausted using Matlab.

A new series of novel mesoporous silica filled polybenzoxazine (SBA-15/PBZ) nanocomposites were designed and developed. Mesoporous SBA-15 was first functionalized using 3-mercaptopropyltrimethoxysilane (MPTMS). The thiol functionalized mesoporous SH-SBA-15 was then characterized by FT-IR, TGA and TEM analyses. Three different types of maleimido terminal triaryl pyridine core benzoxazines were prepared and confirmed by NMR and FT-IR techniques. Varying weight percentages (1, 3, 7, 5 and 10 wt %) of thiol functionalized mesoporous silica (SH-SBA-15) were then reinforced into maleimido terminal benzoxazine matrices to prepare SBA-15/PBZ nanocomposites. The successive increments in the weight percentages of SH-SBA-15 into the polybenzoxazine matrices exhibited lower values of the dielectric constant, superior thermal stability and higher glass transition temperature than those of neat PBZs. The developed nanocomposites were also found to have better flame retardancy and low water uptake percentage. The optical properties were ascertained by the UV–vis absorption bands in the region of 200–400 nm and strong fluorescence emissions were also observed in the wavelength range of 300–550 nm through photoluminescence analysis. The mesoporous nature of the SBA-15 after incorporating in the PBZ matrices was retained and which was evidenced by SEM and TEM images.

A new series of nanosized silica-reinforced polybenzoxazine (nSiO2/PBZ) hybrid nanocomposites were prepared from three types of maleimido terminal benzoxazine monomers and nSiO2. The successive increment of nSiO2 into the PBZ matrices exhibited lower dielectric constant, superior thermal stability and higher glass transition temperature. The hydrophobic nature due to the presence of a less polar Si-O-Si linkage in the composites reduced water uptake properties. The incorporation of nSiO2 particles also retains their luminescence properties. The homogeneous morphology of the nanocomposites caused from the good interfacial interaction between the embedded nSiO2 and PBZ matrix as evidenced by SEM and AFM images.

A new technique Multiple-feature-based adaptive sparse representation (MFASR) has been demonstrated for Hyperspectral Images (HSI’s) classification. This method involves mainly in four steps at the various stages. The spectral and spatial information reflected from the original Hyperspectral Images with four various features. A shape adaptive (SA) spatial region is obtained in each pixel region at the second step. The algorithm namely sparse representation has applied to get the coefficients of sparse for each shape adaptive region in the form of matrix with multiple features. For each test pixel, the class label is determined with the help of obtained coefficients. The performances of MFASR have much better classification results than other classifiers in the terms of quantitative and qualitative percentage of results. This MFASR will make benefit of strong correlations that are obtained from different extracted features and this make use of effective features and effective adaptive sparse representation. Thus, the very high classification performance was achieved through this MFASR technique.

Nowadays, the traditional database paradigm does not have enough storage for the data produced by Internet of Things (IoT) devices leads to the need of cloud storage. These data's are analyzed with the help of Big Data mining techniques. Cloud based big data analytics and the IoT technology performs an important role in the feasibility study of smart agriculture. Smart or precision agricultural systems are estimated to play an essential role in improving agriculture activities. Mobile device usage is very common by everyone, including the farmers. In that, in the daily life of farmers the Information and Communication Technologies (ICT) play a vital role to get the agricultural Information. The IoT has various applications in Digital Agriculture domain like monitoring the crop growth, selection of the fertilizer, irrigation decision support system, etc. In this paper, IoT device is used to sense the agricultural data and it is stored into the Cloud database. Cloud based Big data analysis is used to analyze the data viz. fertilizer requirements, analysis the crops, market and stock requirements for the crop. Then the prediction is performed based on data mining technique which information reaches the farmer via mobile app. Our ultimate aim is to increase the crop production and control the agricultural cost of the products using this predicted information.

Now a day's more number of vehicles are growing due topopulations are growing day by day. All type of vehicles like bus, car, two wheeler, plane, cycle making collision with othervehicles or with other objects like wall, trees, down position, curve position etc. Every year almost 1.25 million people arekilled on the road due to vehicle accident. At present one of thebiggest problems in the world is vehicle accident. The vehicle tovehicle accident is very high compared than other type ofaccident. There are many research solutions already existing forpreventing collision then also accident not possible to control it. According to the vehicle to vehicle accident in this paper theproposed solution for controlling the vehicle to vehicle collisionprevention. Not only that the information about the vehicle likeGPS location, traffic information, vehicle information and driverinformation also send to fog computing and then stored in cloud. The cloud agent is stored incoming data into Hadoop database. The sensor will be attached to all type of vehicle in all side basedon the vehicle to vehicle distance will be measured throughsensor and the data will be transmit to the Fog Computing andthen send to cloud agent. After that the cloud agents store all theinformation to the Hadoop database. The cloud agent playingmajor role between mobile app and Hadoop database. The cloudagent analysis incoming data from the sensor and it will send themessage to driver mobile app. It is based on distance betweentwo vehicles the mobile app produce the alarm. After the alarmdriver can reduce the speed after that the vehicle will becontrolled by the driver. The security is also very important fordata and protection of data based on elliptic curve cryptographyencryption and decryption with shorter key and also the dataprocessing can be very fast. Through mobile app all driver, trafficpolice, transport in charge and pedestrian can get informationabout the all type of vehicle information from the database. Separate login is provided for all type of user.

Data is getting accumulated fast in various domains all over the world and the data size varies from terabytes to yottabytes. Such huge size data are known as Big Data. Extraction of meaningful information from raw data using special patterns are called Data Mining and sophisticated algorithms have been designed for this purpose. In this paper, the time complexity for MapReduce-based data mining algorithm is presented.