Data mining is the field containing procedures for finding designs or patterns in a huge dataset, it includes strategies at the convergence of machine learning and database framework. It can be ...applied to various fields like future healthcare, market basket analysis, education, manufacturing engineering, crime investigation etc. Among these, crime investigation is an interesting application to process crime characteristics to help the society for a better living. This paper survey various data mining techniques used in this domain. This study may be helpful in designing new strategies for crime prediction and analysis.
Human papillomavirus type 16 (HPV16) plays a major role in the development of cervical cancer. The oncogenic potential of HPV16 is attributed to E6 and E7 oncoproteins. Here, we investigated the ...relationship between fused toes homolog (FTS) and HPV16 E6 and E7 in cervical cancer cells. HPV16-positive CaSki and SiHa cell lines were used for in vitro studies. FTS silencing was performed using a small interfering RNA (siRNA)-based approach, and western blotting was performed to determine the protein expression of tumor suppressors and cell survival markers. Immunoprecipitation, immunofluorescence, in silico analysis, and immunohistochemistry were performed to determine the interaction between, and intracellular co-localization of, FTS and both the E6 and E7 proteins. Silencing of FTS reduced the expression of the E6 and E7 proteins in cervical cancer cell lines and conversely increased the expression of the tumor suppressor proteins p53 and retinoblastoma protein. However, the primary transcripts of HPV16 E6 and E7 were unaffected by FTS silencing; furthermore, FTS transcription was unaffected by silencing of either E6 or E7, suggesting their interaction occurs post-translationally. Immunofluorescence and immunohistochemistry analysis demonstrated co-localization of FTS with the HPV16 E6 and E7 proteins, while immunoprecipitation results suggested that FTS interacts with both E6 and E7. Furthermore, in silico structural analysis identified putative residues involved in the binding of FTS with E6 and E7. Taken together, these results show that FTS affects both HPV16 E6 and E7 oncogenes in cervical cancer. We propose FTS as a target for the prevention of cervical cancer development and progression.
Summary
As Network traffic rises and attacks become more widespread and complicated, we must come across Innovative ways to enrich Intrusion Detection Systems in Cloud Computing. This paper proposes ...the Ensemble approaches for Network Intrusion Detection and Classification in Cloud. The major aids of the Ensemble Learning to improve the outcome of each Machine Learning Algorithms and to get a robust Classifier. Real Time Malicious Network Streams Samples were collected using Honeynet, which is deployed on cloud environment. We use supervised learning and Unsupervised learning algorithms for classifying the known malicious network streams and unknown malicious streams. Network related attacks can be segregated into four classes, namely, Denial of service (DOS), User to root (U2 R), Remote to local (R2L), and probe, and the vital constraints that must be overcome with the end goal to build efficient Intelligent Intrusion Detection. The motivation behind the proposed work is to enhance the accuracy rate with response time. The outcome obtained from the Ensemble method has better accuracy rate compared to the SVM, Naive Bayes, and Logistic regression method.
Cloud computing is a preferred option for organizations around the globe, it offers scalable and internet-based computing resources as a flexible service. Security is a key concern factor in any ...cloud solution due to its distributed nature. Security and privacy are huge obstacles faced in its success of the on-demand service as it is easily vulnerable to intruders for any kind of attack. A huge upsurge in network traffic has paved the way to security breaches which are more complicated and widespread. Tackling these attacks has become an inefficient application of traditional intrusion detection systems (IDS) environment. In this research, we developed an efficient Intrusion Detection System (IDS) for the cloud environment using ensemble feature selection and classification techniques. This proposed method was relying on the univariate ensemble feature selection technique, which is used for the selection of valuable reduced feature sets from the given intrusion datasets. While the ensemble classifiers that can competently fuse the single classifiers to produce a robust classifier using the voting technique. An ensemble based proposed method effectively classifies whether the network traffic behavior is normal or attack. The implementation of the proposed method was measured by applying various performance evaluation metrics and ROC-AUC (“area under the receiver operating characteristic curves”) across various classifiers. The results of the proposed methodology achieved a strong considerable amount of performance enhancement compared with other existing methods. Moreover, we performed a pairwise
t
test and proved that the performance of the proposed method was statistically significantly different from other existing approaches. Finally, the outcome of this investigation was obtained with the best accuracy and lowest false alarm rate (FAR).
Diabetic retinopathy (DR) is also called diabetic eye disease, which causes damage to the retina due to diabetes mellitus and that leads to blindness when the disease reaches an extreme stage. The ...medical tests take a lot of procedure, time, and money to test for the proliferative stage of diabetic retinopathy (PDR). Hence to resolve this problem, this model is proposed to detect and identify the proliferative stages of diabetic retinopathy which is also identified by its hallmark feature that is neovascularization. In the proposed system, the paper aims to correctly identify the presence of neovascularization using color fundus images. The presence of neovascularization in an eye is an indication that the eye is affected with proliferative PDR. Neovascularization is the development of new abnormal blood vessels in the retina. Since the occurrence of neovascularization may lead to partial or complete vision loss, timely and accurate prediction is important. The aim of the paper is to propose a method to detect the presence of neovascularization which involves image processing methods such as resizing, green channel filtering, Gaussian filter, and morphology techniques such as erosion and dilation. For classification, the different layers of CNN have been used and modeled together in a VGG-16 net architecture. The model was trained and tested on 2200 images all together from the Kaggle database. The proposed model was tested using DRIVE and STARE data sets, and the accuracy, specificity, sensitivity, precision, F1 score achieved are 0.96, 0.99, 0.95, 0.99, and 0.97, respectively, on DRIVE and 0.95, 0.99, 0.9375, 0.96, and 0.95, respectively, on STARE.
This study concentrated on utilizing a novel heterogeneous dolomite catalyst in transesterification of Azolla pinnata algae oil with methanol to convert Azolla pinnata methyl ester (AME). The ...thermophysical properties of the catalyst were characterized by XRF, XRD, FTIR, and BET analysis. The optimized AME yield of 88.7% was obtained for the methanol to oil molar ratio (30:1), catalyst weight% (4 wt%), and operating temperature of (70 °C) through central composite design (CCD) in response surface methodology (RSM) technique. Five different proportions of Azolla pinnata methyl ester (AME) viz., 10%, 20%, 30%, 40% and 100% by volume were blended with 90%, 80%, 70%, 60% and 0% by volume of diesel. These AME test fuel blends were named AME10, AME20, AME30, AME40, and AME100. American Society for Testing and Materials (ASTM D6751) standards followed to testing the thermophysical properties of prepared biodiesel. AME fuel blends were tested in the single-cylinder variable compression ratio (VCR) engine with varied compression ratios (CR) of 16:1, 17:1, and 18:1 for different loadings at a constant speed of 1500 rpm. The performance, in-cylinder combustion, and exhaust emission results were concluded among five different diesel-AME blends at varied compression ratios. The obtained results for AME blends were compared with the diesel fuel under the same working conditions. At peak load condition, AME30 test fuel with CR18:1 gives a reduction of CO (14.0%), HC (12.06%) and smoke opacity (5.88%) and slight increment in NOx (2.46%) emissions as well as reduced BTE (10.20%) and increased BSEC (17.33%) were obtained related to diesel fuel. Better diffusion phase combustion was recorded for AME blends due to their higher cetane value than neat diesel.
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In this study, Al
2
O
3
nanoparticles were included in the
Azolla pinnata
methyl ester blend (AME30) in different concentrations (25 ppm, 50 ppm and 75 ppm) to analyze the effects on single-cylinder ...diesel engine. Box-Behnken design (BBD) based on RSM was used for production process optimization. The maximum biodiesel yield of 90.77 % attained at methanol-oil molar ratio (20:1), catalyst (3 wt%) and temperature (75 °C). The experiments were performed in a 3.75 kW Kirloskar diesel engine at a constant speed of 1500 rpm with Al
2
O
3
dosed biodiesel blends (AME30+Al25, AME30+Al50 and AME30+Al75), and outcomes were compared with pure diesel and AME30 blend. The corresponding test fuel properties were examined with ASTM standards. As a result, the AME30+Al50 test fuel has improved BTE and reduced BSEC compared to other test fuels. Subsequently, the highest reduction of HC (24.4 %), CO (21.24 %) and smoke opacity (15.25 %) was observed for AME30+Al50 at full load condition compared to diesel results.
•Joint approaches of Y3+ ions integrated with rGO in TiO2 resulted in enhanced optical and electrical properties.•Induced oxygen defects improved the electron concentration in the doped TiO2 ...lattice.•Improved average carrier lifetime of YTO/rGO leads to efficient charge separation and electrical properties.
The efficient tuning of defects in the host lattice to obtain the desired electrical and optical properties is the recent trend in the research arena. Here we aim to tune to oxygen vacancies in TiO2 lattice by dopant incorporation and also investigated the influence of rGO on the electrical properties of doped TiO2 lattice. In this paper, Yttrium incorporated TiO2 (YTO) and YTO/rGO nanocomposites are synthesized. YTO and YTO/rGO nanocomposites are characterized by X-Ray Diffraction (XRD), UV-Differential reflectance spectroscopy (UV-DRS), Raman, X-ray photoelectron spectroscopy (XPS), Hall measurement studies, electrical impedance spectroscopic studies and TRPL measurements. Yttrium (6 mol%) in the TiO2 lattice introduces more oxygen defect sites, modifying the charge carrier dynamics of the lattice (improved electron concentration, enhanced electrical properties, lowered the charge transfer resistance). To improve the average lifetime of the charge carrier, YTO was composited with rGO. YTO/rGO nanocomposite formation was confirmed by XPS and Raman analysis. Nyquist plot of YTO/rGO nanocomposites exhibited reduced charge transfer resistance and lesser relaxation time. TRPL measurements of YTO/rGO nanocomposites showed a significant improvement in the average lifetime of the charge carriers from 19.7 ns for YTO to 30.7 ± 0.5 ns. This improved lifetime of electrons in the nanocomposite system signifies efficient charge separation and reduced charge recombination at the YTO and rGO interface, thus proving YTO/rGO nanocomposite as a better electron extraction layer.
Edge-based privacy preserving cryptosystem is identified as the upcoming amenities of cloud-based secure remote healthcare monitoring systems. Usually, the cloud-based healthcare system will directly ...collect the remote patient data through a sensor layer and provide the continuous monitoring and diagnosis through various prediction processes made by the decision support system. These sensing and processing of real-time patient's medical data without compromising its privacy and security become daunting issues in the traditional healthcare services. Therefore, the proposed research incorporates the security mechanism in the patient-centric edge-cloud-based healthcare system architecture. More precisely, an edge level privacy preserving additive homomorphic encryption is proposed for secure data processing and filtering non-sensitive data in the edge layer. In addition, response time and network capacity usage are minimized in the proposed healthcare system due to effective filtering and offloading mechanisms adapted in the edge level. Next, an adaptive weighted probabilistic classifier model is proposed in the cloud layer for onboard disease prediction and rehabilitation of remote patients. It will improve the disease prediction time and prediction accuracy while comparing to traditional classifier models. Finally, security and performance analysis of the proposed Secure Edge-Cloud-based Healthcare System (SECHS) was demonstrated with respect to empirical evaluation of Parkinson disease dataset.
Cellulose pulp (CP), hydroxyethyl cellulose (HEC), and turmeric-powder-based ecofriendly, transparent, and flexible composite films were prepared. The above-mentioned materials dissolved well with an ...environmentally friendly process using N-methyl morpholine N-oxide (NMMO) ionic liquids. The Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), and scanning electron microscopy (SEM) analysis studied their structure, microstructure, and morphology properties. Thermal properties of the CP/HEC/turmeric powder composites were thoroughly studied by thermogravimetric analysis (TGA) and differential scanning calorimetry analysis (DSC) and dynamic mechanical analysis (DMA) instruments. The initial thermal stability of the composites was significantly improved by the addition of HEC. All the composite films exhibited a single glass transition temperature (T g), and it was confirmed by both DSC and DMA analysis. The tensile strength (TS) of CP was 94.5 MPa, which decreased to 19 MPa for CP/HEC-1:0.5 composites, and then, it steadily increased to 24.7 MPa with an increment of HEC. Similarly, HEC increased the elongation at break (EB) of CP from 9.4 to 67.2%. The addition of HEC into the CP composite improved its flexibility, and it is more transparent in the visible light spectrum. The water vapor permeability (WVP) and swelling ratio of CP/HEC/turmeric powder composites were in the range of 1.35–1.61 × 10–9 g/m2 Pa and 185–209%, respectively. Furthermore, the composites have no cytotoxicity to the HaCat cell line. However, they exhibited excellent antioxidant properties. These merits of CP/HEC/turmeric powder composite establish them as a potential candidate for packaging and biomedical applications.
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