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A large number of attacks are launched daily in the era of the internet and with a large number of users. Nowadays, effective detection of numerous attacks using the Intrusion Detection System (IDS) is an emerging research technique. Machine learning methodologies show effective results in intrusion detection system. We proposed a two-stage hybrid methodology for intrusion detection. In the first stage, the unsupervised Sparse autoencoder (SAE) with smoothed l1 regularization. We employ smoothed l1 regularization to enforce a sparsity of autoencoder. The smoothed l1 regularization is indeed able to learn sparse representations of features. In the second stage, the Deep Neural Network (DNN) was used to predict and classify attacks. The classifier classifies multi attack classification from the extracted features. Unsupervised SAE was optimized to train an efficient model. The experimental results demonstrate that proposed model better than the conventional models in terms of overall performance in detection rate and low false positive rate. The proposed model was assessed on the datasets KDDCup99, NSL-KDD and UNSW-NB15. The model attained the accuracy 99.98% , and detection rate 99.99% on UNSW-NB15 dataset.

Purpose The purpose of this paper is to print a thermolabile drug-containing tablet using the fused deposition modeling (FDM) technique and analyze its mechanical, pharmaceutical and environmental feasibility using a variety of tests. Design/methodology/approach Ascorbic acid (Vitamin C) is the thermally-sensitive drug impregnated into polyvinyl alcohol excipient using ethanol-water mixture and printed by an FDM printer by varying three parameters without using any external stabilizing agent. Afterward, Taguchi analysis has been performed on these parameters to recognize the significant factors and interactions. Besides this, a regression model has been obtained based on the dissolution data. Various thermo-mechanical and pharmaceutical tests have been carried out to confirm the feasibility. Finally, a life cycle assessment (LCA) analysis has been carried out to compare it with the existing tableting method by considering the environmental impacts. Findings The dissolution profile was found to follow the Korsmeyer-Peppas model, where the drug release occurred both by dissolution and erosion. Further, the infill percent has been found as the most significant parameter. The characterization tests and imaging outputs proved the fidelity of this attempt. Finally, the three-dimensional printed method was found to be more environmentally sustainable than the existing conventional tableting process. Originality/value LCA on a printed tablet is a one-of-a-kind attempt. Thus, this research attempt delivered another approach to print personalized tablets at a temperature lower than prescribed temperatures with required release behavior and can contribute toward the quest of sustainable personalized medication.

Age-Related Macular Degeneration (ARMD) is a medical situation resulting in blurred or no vision in the middle of the eye view. Though this disease doesn’t make the person completely blind, it makes it very difficult for the person to perform day to day activities like reading, driving, recognizing people etc. This paper aims to detect ARMD though Optical Coherence Tomography (OCT) scans where the drusen in the macula is detected and identify the infected. The images are first passed though Directional Total Variation (DTV) Denoising followed by Active contour algorithm to mark the boundaries of the layers in macula. In deep learning, a convolutional neural network is a class of deep neural networks, most commonly applied to analyzing visual imagery. Then these images categorized as healthy and infected using Convolution Neural Network. Different CNN variant algorithms like Alexnet, VggNet and GoogleNet have been compared in the experiments and the results obtained are better compared to traditional methods.

The identification of interest/disinterest over a notion is having a huge demand in the current competitive data analytical world. For example, the customer preferences in various seasons, approximate visitors to a tourist place based on scenarios like weather and special occasions in the place, and so on. While giving an opinion on any concept, natural language in form of sentences/words/symbols/ratings plays a vital role. Depends upon the context and usage of natural language, captured opinions can be interpreted as either in a positive or negative sense. The terminology used for providing the opinions is used for analysing the data in an easy way. The evaluation of the word frequencies and word cloud are identified accurately, only after a keen analysis of the collected opinions. The Term-Document Matrix is one of the techniques that identify the frequency of words in each and every document/row in the given dataset, which can be used to generate the word cloud. In this paper to identify the frequency of words from the opinions given by multi-domain personalities on Astrology, distinct Natural Language Processing (NLP) techniques are used. A word cloud can also be generated from the set of words used for the astrological dataset.

Service-oriented architecture (SOA)[1] is an incessant term to deal with various administrations dependent on solicitations of various clients in various ongoing applications. Still, now, a few people don't have total information about what SOA really has done, they get confounded how SOA identifies with distributed computing. On account of cloud administration usage in SOA need security mindful help creation with finegrained stream control to make sure about web administrations at execution time to share various administrations to various clients in dispersed condition? Routinely various models were acquainted with investigating secure web administrations at execution of various administrations. Because of access control infringement, they will take high execution time and other leader boundaries profoundly, and furthermore they don't control access assurance arrangements in composite administrations, which may deliver bothersome information spillage. To conquer these infringement issues in SOA, we present Integrated Novel Multi-Level Composite Service Model (INMLCSM)[2] to lessen infringement calculation cost dependent on customer authentic and demonstrate customer composite administrations and furthermore perform nearby/distant strategy calculation for highest customers. We acquaint idea of change factor with characterize halfway administrations. Our proposed approach portrays forceful exploratory outcomes.

Unexpected volume changes manifested in the soil beds due to accidental release of alkalis from industrial establishments has become a major challenge. The neogenic formation that leads to volume changes due to physicochemical reactions between clay minerals and alkalis need to be addressed. The current article focusses on the possibility of using alternate by-products such as ground granulated blast furnace slag (GGBFS) and flyash (FA) for controlling the swell induced in alkali transformed kaolinitic clays, ATKC’s (i.e., red earth and kaolin). Results indicate that ATKC’s exhibited unexpected changes in swelling behavior upon inundation with water and alkali (4N NaOH) solutions. ATKC’s were later amended with FA and GGBFS to address the swelling phenomena. Marked reduction in swelling was noticed in ATKC’s with FA (10% and 20%) and GGBFS (10% and 20%). Reduction of about 40% of overall swelling was noted in alkali transformed red earth (ATR) when treated with 10% FA and 50% reduction with 10% GGBFS. Further, treatment of ATR with 20% FA and 20% GGBFS, decreased swelling to about 82% compared with ATR-4N. In case of alkali transformed kaolin (ATK), 57% and 56% reduction in swelling were observed with addition of 10% FA and 10% GGBFS, respectively. At 20% FA and GGBS content, reduction in ATK-4N swelling was 75% and 90%, respectively. Thermo Gravimetric–Differential Thermal Analysis (TG–DTA), X-ray Diffraction, and Scanning Electron Microscopy (SEM) analysis confirmed the alterations in ATKC are stabilized with FA and GGBFS.

Electrocardiogram (ECG) is widely used technique in study of heart beat irregularities such as cardiac arrhythmias, sinus rhythms and heart failure. It is a significant and popular technique to classify and detect the cardiac infraction. ECG signal analyses the electric activity of heart and outputs it in the form of waveforms which help in detection of heart irregularities. The main goal of this research work is to classify the arrhythmia with more accurate results in less computational time. The research is carried in machine learning technique- SVM classifier using Discrete Wavelet Transform (DWT). In this methodology, ECG samples of three different classes-Normal Sinus Rhythm, Congestive Heart Failure and Cardiac Arrhythmia were collected from MIT-BIH and BIDMC databanks. The collected signals were prepared into training set and testing set with a ratio of 70:30 percent respectively. Total 190 features were extracted from the prepared data using Discrete Wavelet Transform. DWT was chosen as it has the ability to vary the window size depending on the frequency. The extracted features were given to SVM classifier, which is best for classification purpose. The results were evaluated using the testing set and the final results were plotted using a confusion matrix. The performance accuracy of the model is 95.92 percent.

Image-stitching (or) mosaicing is considered an active research-topic with numerous use-cases in computer-vision, AR/VR, computer-graphics domains, but maintaining homogeneity among the input image sequences during the stitching/mosaicing process is considered as a primary-limitation & major-disadvantage. To tackle these limitations, this article has introduced a robust and reliable image stitching methodology (l,r-Stitch Unit), which considers multiple non-homogeneous image sequences as input to generate a reliable panoramically stitched wide view as the final output. The l,r-Stitch Unit further consists of a pre-processing, post-processing sub-modules & a l,r-PanoED-network, where each sub-module is a robust ensemble of several deep-learning, computer-vision & image-handling techniques. This article has also introduced a novel convolutional-encoder-decoder deep-neural-network (l,r-PanoED-network) with a unique split-encoding-network methodology, to stitch non-coherent input left, right stereo image pairs. The encoder-network of the proposed l,r-PanoED extracts semantically rich deep-feature-maps from the input to stitch/map them into a wide-panoramic domain, the feature-extraction & feature-mapping operations are performed simultaneously in the l,r-PanoED's encoder-network based on the split-encoding-network methodology. The decoder-network of l,r-PanoED adaptively reconstructs the output panoramic-view from the encoder networks' bottle-neck feature-maps. The proposed l,r-Stitch Unit has been rigorously benchmarked with alternative image-stitching methodologies on our custom-built traffic dataset and several other public-datasets. Multiple evaluation metrics (SSIM, PSNR, MSE, Lα,β,γ, FM-rate, Average-latency-time) & wild-Conditions (rotational/color/intensity variances, noise, etc) were considered during the benchmarking analysis, and based on the results, our proposed method has outperformed among other image-stitching methodologies and has proved to be effective even in wild non-homogeneous inputs.

Spinal infections can also be described as pyogenic, granulomatous (tuberculous, brucella, fungal) and parasitic. Tubercular spondylodiscitis is the commonest. Although a wide range of organisms have been associated with spondylodiscitis, it remains primarily a monomicrobial bacterial infection. A detailed evaluation of clinical features- fever, back pain (Visual Analogue score), discharging sinus, swelling, deformity, neurological status (graded as per charting by Kumar and Tuli; ASIA scale (American Spinal Injury Association). In 7.6% of NTS and 9.1% of TS, the tissue specimen was obtained by closed vertebral biopsy and in 80.7% of NTS and 90.9% of TS by open biopsy at the time of surgery. The yield of culture of the biopsy specimen was 100% in PS and 21% In BS. AFB stain was positive in 32.1% and PCR was positive in 82.8% of TS. 119 (83.3%) patients were treated by anterior decompression, biopsy posterior spinal instrumentation and global fusion.13 (8.6%) patients were treated by debridement, abscess drainage +/-antibiotic bead application.

Pyogenic spondylodiscitis (PS) is more common in patients aged over 50 years and it represents only 1-2% of bone infectionsin pediatric age. The incidence has been rising through the combined effect of an increase in the susceptible population (immunosuppressed and ageing population), intravenous drug use, rise in healthcare-associated infection, spinal surgery and improved ascertainment, due to better diagnosis. Of 173 patients, 15 patients with incomplete follow-up, incomplete radiographic data and 7 patients with inconclusive etiological diagnosis were also excluded. The remaining 151 patients formed the basis of the study. Mean duration of symptoms was 6 weeks in NTS and 14 weeks in TS. Back ache is the most common clinical feature seen in all patients (100%). Fever in NTS (71.1%) and deformity in TS (34.3%) were 2nd most common clinical features respectively. Neurological deficits and symptoms (radiculopathy/parasthesias) were present in 30.3% of TS and 21.1% of NTS.

High-speed vehicles and reckless driving have caused quite frequent accidents by intoxicated people. Alcoholism is one of the key causes contributing to reckless driving. We used an alcohol sensor in this work to detect the driver's condition and take the appropriate action. Because the flow of information is very critical in case of incidents, the device also integrates on board pressure and MEMS sensor to identify the effects. The camera takes the pictures, and the GPS location information is sent to registered mail via the Raspberry pi3 board's TWILIO app mounted in the car, sending the alert to the registered mobile phone. In addition, FMCW radar is used for anti-collision purposes because of its precise measurements of short range.

Solar power is free from environmental pollution and also offers economic benefits to the investors. In order to optimize at most solar power, tracking schemes are employed and traditional schemes from the family of perturbation suffer from slow response, due to specific step size disruption and oscillations around operating point. Therefore, this paper proposes an effective design and implementation of a hybrid Maximum Power Point Tracking (MPPT) scheme based on Linear Tangents - Neville Interpolation (LT-NI) techniques. Two tangents are drawn on the P-V characteristics at 75% and 90% of open circuit voltage (VOC).The chosen two tangents intersect and gives rise to a third voltage (N) point. In continuation, the three voltage points (0.75VOC, N & 0.9VOC) are computed using Neville Interpolation. The performance of the proposed LT-NI scheme is compared with Perturb & Observe (P&O) and advanced Divide and Conquer (DC) algorithms.

Background: In the process of volumetric evaluation of the damaged region in the human brain from a MR image it is very crucial to remove the non-brain tissue from the acquainted image. At times there is a chance during the process of assessing the damaged region through automated approaches might misinterpret the non-brain tissues like skull as damaged region due to their similar intensity features. So in order to address such issues all such artefacts. Objective: In order to mechanize an efficient approach that can effectively address the issue of removing the non-brain tissues with minimal computation effort and precise accuracy. It is very essential to keep the computational time to be as minimal as possible because the processes of skull removal is used in conjunction with segmentation algorithm, and if the skull scrapping approach has consumed a considerable amount of time, they it would impact the over segmentation and volume assessment time which is not advisable. Methods: In this paper a completely novel approach named Structural Augmentation has been proposed, that could efficiently remove the skull region from the MR image. The proposed approach has several phases that include applying of Hybridized Contra harmonic and Otsu AWBF filtering for noise removal and threshold approximation through Otsu based approach and constructing the bit map based on the approximated threshold. Morphological close operation followed by morphological open operation with reference to a structural element through the generated bitmap image. Results: The experiment are carry forwarded on a real time MR images of the patient at KGH hospital, Visakhapatnam and the images from open sources repositories like fmri. The experiment is conducted on the images of varied noise variance that are tabulated in the results and implementation section of the article. The accuracy of the proposed method has been evaluated through metrics like Accuracy, Sensitivity, Specificity through true positive, true negative, False Positive and False negative evaluations. And it is observed that the performance of the proposed algorithm seems to be reasonable good. Conclusion: The skull scrapping through structural Augmentation is computationally efficient when compared with other conventional approaches concerning both computational complexity and the accuracy that could be observed on experimentation. The Adaptive Weighted Bilateral Filter that acquire the weight value from the approximated contra harmonic mean will assist in efficient removal of poison noised by preserving the edge information and Otsu algorithm is used to determine the appropriate threshold value for constructing the bitmap image of the original MRI image which is efficient over the earlier mean based approach for estimating the threshold. Moreover, the efficiency of the proposed approach could be further improved by using customized structural elements and incorporating the fuzzy based assignments among the pixels that belong to brain tissue and skull effectively.

Background/AimsThe current study evaluates the efficacy and safety of the stand-alone implantation of the MINIject (iSTAR Medical, Wavre, Belgium) supraciliary, microinvasive glaucoma drainage device in patients with medically uncontrolled open-angle glaucoma.MethodsThis prospective, multicentre, first-in-human, single-arm interventional study evaluated stand-alone, ab interno implantation in 25 patients of a 5 mm long uveoscleral device made of STAR biocompatible material, which is a soft, microporous, flexible silicone. The primary outcome was the reduction of intraocular pressure (IOP) at 6 months compared with baseline, and follow-up continued until 2 years for 21 patients. Secondary outcomes included success defined as diurnal IOP of ≤21 mmHg and >5 mmHg with an IOP reduction of 20% without (complete) or with/without (qualified) glaucoma medication.ResultsMean baseline IOP was 23.2±2.9 mmHg on 2.0±1.1 glaucoma medication ingredients and decreased to 13.8±3.5 mmHg (−40.7% reduction) on 1.0±1.3 medications 2 years after implantation. Complete success was achieved in 47.6% of patients (10/21) and qualified success in 100% of patients (21/21) at the 2-year follow-up. All patients achieved a 20% IOP reduction with 48% of patients medication-free. No serious ocular adverse events or additional glaucoma surgery were reported. Mean central endothelial cell density (ECD) mildly decreased from 2411 cells/mm2 (n=26) to 2341 cells/mm2 (n=21) at 24 months, which represents a 5% decrease for matched eyes. No patient had a ≥30% decrease in central ECD.ConclusionThis first-in-human study on the stand-alone implantation of the MINIject supraciliary drainage system shows promising IOP-lowering results and medication reduction over 24 months with few adverse events.Trial registration numberNCT03193736.

Purpose Earlier imaging techniques for coronary artery disease (CAD) focused primarily on either morphological or functional assessment of CAD. However, dual-energy computed tomography (DECT) can be used to assess myocardial blood supply both morphologically and functionally. We aimed to evaluate the diagnostic accuracy of DECT in detecting morphological and functional components of CAD, using invasive coronary angiography (ICA) and single photon emission computed tomography (SPECT) as reference standards. Methods Twenty-five patients with known or suspicious CAD and scheduled for ICA were investigated by DECT and SPECT. DECT was performed during the resting state using retrospective electrocardiography (ECG) gating. CT coronary angiography and perfusion images were generated from the same raw data. All patients were evaluated for significant stenosis (≥50%) on both ICA and DECT coronary angiography, and for myocardial perfusion defects on SPECT and DECT perfusion. Comparison was done between ICA and DECT coronary angiography for detection of significant stenosis and between SPECT and DECT perfusion for detecting myocardial perfusion defects. Results Using ICA as reference standard, sensitivity, specificity, and accuracy of DECT coronary angiography in detecting ≥50% stenosis of coronary artery lumen were 81.6%, 97.8%, and 95.0%, respectively, by segment-based analysis and 92.1%, 96.1%, and 93.7%, respectively, by vessel-based analysis. Using SPECT as the reference standard, the sensitivity, specificity, and accuracy of DECT perfusion in detecting myocardial perfusion defects were 70.4%, 86.4%, and 80.6%, respectively, on per-segment analysis and 90.7%, 66.6%, and 84.7%, respectively, on per-territorial basis. Conclusion DECT accurately detected coronary artery stenosis and myocardial ischemia using ICA and SPECT as reference standards. In the same scan, DECT can accurately provide integrative imaging of coronary artery morphology and myocardial perfusion.

Burnout remains an emerging challenge in healthcare. Burnout in these settings has been associated with compromised personal wellbeing, decreased work productivity, higher healthcare costs, decreased patient satisfaction, and deteriorating quality of patient care. As pharmacist roles on healthcare teams expand, health-system pharmacy leaders should be cognizant of burnout, including risk factors and identification. Coordinated efforts should foster pharmacist wellbeing and resilience, individualized work-related responsibilities to ensure professional ambitions are met, promotion of upper leadership expectation transparency, and cultivation of relationships within the pharmacy department.

Retinal image blood vessels are having significant role in different eye related diseases such as diabetic retinopathy, glaucoma, cataract, age-related macular degeneration and many more. Vasculature retinal feature extraction is an important factor to different doctors for treatment and diagnosis of different diseases. For automatic extraction of retinal blood vessels, different types of clustering related approaches (i.e. k-means/fuzzy c-means) are introduced to explore blood vessels from real time retinal images. Novel blood vessel extraction approach is introduced to explore retinal blood vessels with unsupervised clustering procedures like fuzzy c-means followed with Gabor filter. In this paper, we propose Enhanced blood vessel exploration approach (EBVEA) to improve the segmentation and visualization of vasculature retinal images or fundus images in blood vessel extraction with a combination of hessian based center-to boundary (BB) filters. These filters are used to indicate elongated boundary structures by enhancing the functions based on hessian Eigen values represented in (nxn) matrix. Performance of proposed enhanced approach with traditional approaches in terms of true positive rate (tpr), accuracy etc. are tested. Experimental results carried out and tested on bench mark data sets like DRIVE and STARE datasets produced better results.

The usage of transportation systems is inevitable; any assistance module which can catalyze the flow involved in transportation systems, parallelly improving the reliability of processes involved is a boon for day-to-day human lives. This paper introduces a novel, cost-effective, and highly responsive Post-active Driving Assistance System, which is "Adaptive-Mask-Modelling Driving Assistance System" with intuitive wide field-of-view modeling architecture. The proposed system is a vision-based approach, which processes a panoramic-front view (stitched from temporal synchronous left, right stereo camera feed) & simple monocular-rear view to generate robust & reliable proximity triggers along with co-relative navigation suggestions. The proposed system generates robust objects, adaptive field-of-view masks using FRCNN+Resnet-101_FPN, DSED neural-networks, and are later processed and mutually analyzed at respective stages to trigger proximity alerts and frame reliable navigation suggestions. The proposed DSED network is an Encoder-Decoder-Convolutional-Neural-Network to estimate lane-offset parameters which are responsible for adaptive modeling of field-of-view range (157o-210o) during live inference. Proposed stages, deep-neural-networks, and implemented algorithms, modules are state-of-the-art and achieved outstanding performance with minimal loss(L{p, t}, Lδ, LTotal) values during benchmarking analysis on our custombuilt, KITTI, MS-COCO, Pascal-VOC, Make-3D datasets. The proposed assistance-system is tested on our custom-built, multiple public datasets to generalize its reliability and robustness under multiple wild conditions, input traffic scenarios & locations.

This article is aimed to study the thermal energy transport phenomenon caused by heating the porous cavity at left vertical wall as well as an internal heating by a strip of varying length near the cooling surface. The internal heating strip that varies in length is kept at x = 3L/4 of the cavity where L is the overall cavity length. Finite element method is at the core of solution techniques which is employed along with triangular shaped elements. The solution is arrived by following an iterative method that depends on satisfying the equations to a predetermined error level. It is ensured that the results are accurate enough to predict the phenomenon under study. The main aim of the study is to understand what happens when the heating element is placed towards the right vertical surface. The results are described for physical and geometrical parameters of the problem being considered.

Objectives: The purpose of this study is to assess the effectiveness of mineralized plasmatic matrix in the soft tissue closure of naso-alveolar fistula, to estimate the postoperative bone fill and volume of the graft placed in the alveolar cleft defect using cone-beam computed tomography (CBCT) at 3rd- month and 6th- month. Material and methods: 10 patients, in the age group of 15‑30 years were included in this study. They were diagnosed with unilateral cleft lip and alveolus defects with or without a cleft palate requiring late secondary alveolar bone grafting. Alveolar cleft defects were closed with mineralized plasmatic matrix (MPM), a combination of autogenous iliac bone graft and platelet rich plasma (PRP) and platelet rich fibrin (PRF). Results: The mean defect volume pre-operatively is 0.75 cm3 and at the end of 3rd-month postoperatively is 0.51 cm3 and at 6th-month postoperatively is 0.27 cm3. The average percentage of bone fill between preoperative (A) & 3th- month postoperatively (B) is 33.4% and between 3rd-month (B) and 6th-month post operatively (C) is 49.5%. Conclusions: Utilization of this new matrix (MPM), has shown to be effective in the closure of the cleft defect, oro-nasal fistula and also reduction in the volume of the residual cleft defect seen with sequential cone-beam computed tomography (CBCT) radiographs.

Convex probe-endobronchial ultrasound (CP-EBUS) has been proven to be safe and accurate for identifying malignancy and granulomatous disease affecting the mediastinum and hilum. CP-EBUS can be used for intraparenchymal lesions also and has been shown to be efficacious. A subset of lesions particularly suited for CP-EBUS are those completely surrounded by lung parenchyma, centrally located, and typically close to but without an airway leading directly to them. We report a case of transbronchial needle aspiration (TBNA) done from a nodule of size 11 mm in the superior segment of the right lower lobe. EBUS-TBNA was done from this lesion, which was 5 mm away from the bronchus in the lung parenchyma with intervening normal lung tissue in between. TBNA was performed by compressing the abutting normal lung tissue, thus causing compression collapse of the intervening normal lung. We labeled this Zealous Unique Trans Arterial Maneuver as the “ZUTAM” technique.

To describe the safety and efficacy of a novel, supraciliary, microinvasive glaucoma surgery drainage system, MINIject (iSTAR Medical, Wavre, Belgium), in the study.Prospective, multicenter, interventional, single-arm trial.Twenty-six patients with primary open-angle glaucoma uncontrolled with 1 or more intraocular pressure (IOP)-lowering medications.Using an ab interno approach, 25 eyes were implanted successfully in a stand-alone procedure with a 5-mm long device made of biocompatible STAR material, which is soft and flexible silicone in a microporous, network design. Intraocular pressure, medication use, and other ocular parameters were evaluated before surgery, 1 day, 1 and 2 weeks, and 1, 3, and 6 months after surgery.Intraocular pressure reduction at 6 months compared with baseline analyzed using a paired t test. Safety evaluation entailed tabulation of the nature and frequency of adverse events.Mean baseline diurnal IOP was 23.2 mmHg (standard error, 0.6 mmHg) using a mean ± standard deviation of 2.0±1.1 IOP-lowering medication classes. During the 6-month follow-up period, mean IOP ranged from 10.0-16.3 mmHg (mean reductions, 6.9-13.2 mmHg or 31.0%-56.8%). Six months after surgery, mean diurnal IOP was 14.2 mmHg (standard error, 0.9 mmHg), equivalent to a reduction of 9.0 mmHg or 39.1% (P0.0001). The mean ± standard deviation number of IOP-lowering medications was 0.3±0.7. Of 24 patients seen at 6-month follow-up, 21 (87.5%) were medication-free and 23 (95.8%) achieved a minimum 20% IOP reduction from baseline. There were no serious adverse events related to the device or procedure, and no additional glaucoma surgery was required. Frequently reported events included anterior chamber inflammation (n = 8), IOP elevation (n = 6), of which 1 event was an IOP spike per protocol, visual acuity reduction (n = 3), and hyphema (n = 3), all of which resolved. There was no change to mean central or peripheral corneal endothelial cell density. No device-related adverse events were reported.The MINIject glaucoma drainage system significantly lowered IOP and eliminated the need for medication in most patients 6 months after surgery when implanted in a standalone procedure. There were no serious ocular adverse events.

One of the most important aspects of postsurgical care is finding an efficient way for the management of pain. Third molar extractions/surgical impaction is one of the most frequent surgical procedures in dental hospitals, and it is most often associated with postoperative complications like severe pain, oedema and reduced mouth opening. This study was aimed to evaluate the efficacy of 2 g intravenous (IV) vitamin C compared to 100 mg aceclofenac on postsurgical pain, swelling and trismus after the surgical removal of third molars. A total of 101 patients were recruited for the study, and theywere divided into two treatment groups; group A (n = 51) received 2 g IV vitamin C and group B (n = 50) received 100 mg aceclofenac. Pain intensity, facial swelling and mouth opening were assessed till day 3 post-surgically. Statistical analysis of pain intensity revealed that IV vitamin C performed slightly better but not significantly different (p>0.05) from aceclofenac group at the end of day 3. No significant difference for facial swelling and mouth opening between the two treatment protocols was seen (p>0.05). Our results concluded that both treatment groups were overall similar in analgesic efficacy, postoperative oedema and reduction in mouth opening. It was also determined that the method devised administering 2 g IV vitamin C intravenously was well suited to the treatment of postoperative pain, swelling and trismus following the surgical extraction of impacted third molars.

Background: Fibrin glue is an alternative to conventional suturing and stapling of skin grafts and has several advantages. It acts as a sealant and a hemostatic agent with an added adhesive property that has been reportedly used in many specialties with better outcomes. Objective: The objective was to study the effectiveness of fibrin glue in anchoring the split skin graft to the wound bed and to analyze the advantages, disadvantages, and outcome of using fibrin glue compared to suturing and stapling. Methodology: A total of 60 patients undergoing split skin grafting for various indications were studied. Each patient was used as both case and control, where fibrin glue was applied on one half and sutures and/or staples were applied on the other half of the same ulcer. Examination of the wound was conducted by two observers independently from the 3rd postoperative day at regular intervals onward and included inspection for the graft uptake, soakage, and infection and graded accordingly based on the three parameters. Results: Overall, graft uptake was better in fibrin glue study group. Furthermore, soakage and infection were less in fibrin glue study group when compared to the conventional suturing/stapling. No difference in infections rate was found among burns and postsurgical raw area patients. Conclusion: The use of fibrin glue is a simple, safe, and cost-effective method, with a rapid technique to fix the skin graft, avoid peroperative bleeding and postoperative collection, better uptake of graft, and better overall results.

Image segmentation is a method of segregating the image into required segments/regions. Image thresholding being a simple and effective technique, mostly used for image segmentation, these thresholds are optimized by optimization techniques by maximizing the Tsallis entropy. However, as the two level thresholding extends to multi-level thresholding, the computational complexity of the algorithm is further increased. So there is need of evolutionary and swarm optimization techniques. In this article, first time optimal thresholds are obtained by maximizing the Tsallis entropy by using novel hybrid bacteria foraging optimization technique and particle swam optimization (hBFOA-PSO). The proposed hBFOA-PSO algorithm performance in segmenting the image is tested using natural and standard images. Experiments show that the proposed hBFOA-PSO is better than particle swarm optimization (PSO), the cuckoo search (CS) and the adaptive Cuckoo Search (ACS).

Aim: The present study aims to study causes, modes of presentation, investigations of choice and management of right iliac fossa masses. Materials and Methods: A prospective study was undertaken on 50 patients presenting with mass in right iliac fossa to surgery outpatient department during the period august 2015 to October 2017. All cases were investigated and managed as per protocol and their data recorded. All the demographic variables were tabulated as per percentage among total cases. Results: In this series out of 50 patients, 23 patients (46%) diagnosed to have Appendicular mass followed by Ileocaecal TB (20%), Appendicular abscess (16%), CA Caecum (12%) and psoas abscess (6%). Appendicular pathology is more common in 3rd decade, Ileocaecal TB in 4thdecade, CA Caecum and Psoas abscess in 6th decade.In total of 50 patients, 28 (56%) were males and 22 (44%) were females. In the present study pain was the commonest symptom of presentation seen in all cases, fever was present in 78% cases, vomiting was present in 42% cases, loss of weight and appetite was present in 24% cases, constipation was present in 16% cases, diarrhea was present in 8% cases, mass per abdomen was present in 26% cases. Conclusion: The common cause of right iliac fossa mass is of appendicular pathology followed by lleocaecal TB, Carcinoma caecum and psoas abscess in that order, with male preponderance and most of cases falling in 3rd decade.

In cloud storage systems, users must be able to shut down the application when not in use and restart it from the last consistent state when required. BlobSeer is a data storage application, specially designed for distributed systems, that was built as an alternative solution for the existing popular open-source storage system-Hadoop Distributed File System (HDFS). In a cloud model, all the components need to stop and restart from a consistent state when the user requires it. One of the limitations of BlobSeer DFS is the possibility of data loss when the system restarts. As such, it is important to provide a consistent start and stop state to BlobSeer components when used in a Cloud environment to prevent any data loss. In this paper, we investigate the possibility of BlobSeer providing a consistent state distributed data storage system with the integration of checkpointing restart functionality. To demonstrate the availability of a consistent state, we set up a cluster with multiple machines and deploy BlobSeer entities with checkpointing functionality on various machines. We consider uncoordinated checkpoint algorithms for their associated benefits over other alternatives while integrating the functionality to various BlobSeer components such as the Version Manager (VM) and the Data Provider. The experimental results show that with the integration of the checkpointing functionality, a consistent state can be ensured for a distributed storage system even when the system restarts, preventing any possible data loss after the system has encountered various system errors and failures.

The Quality-of-Service-Network-on-Chip (QNoC) architecture is used in complex System-on-Chip (Soc) for intercommunication. For high efficiency and throughput, Buffer Virtual-Channel (VC) input port NoC is utilized. In order to provide a good Quality-of-Service (QoS), input port buffer area optimization is important. Compared to traditional VC approaches, the current efficient dynamic VC (EDVC) organizes the buffers in an effective way to minimize area overhead for enhanced performance. In this paper, we propose an Isochronous Efficient Dynamic Virtual Channel (IEDVC) router architecture that aims to effectively organize the VC input port, prioritise packets, and provide good communication. To enhance the QoS, techniques such as frequency boosting and error termination have been introduced. Thus, with all modifications, the results of IEDVC showed that it utilizes the 14.19 % less hardware, with a 3.7% and 3.8% increase in frequency and throughput respectively.

Human life is the most valuable thing, and many lives are lost in battles. Robot uses in battles to give detailed information and live feed will help in saving lives. To perform this intelligent navigation, the Microcontroller is loaded with an efficient program written using embedded “C” language. Since all the operations of this robot can be controlled by an operator, real time situations can be analyzed and actions can be taken accordingly. System reduces fuel requirements as it can also run on solar power. It can be used for public security, monitoring.

Sentiment Classification is a continuing area of research in text mining. Sentiment Analysis the automatic representation of the ideas, emotions and subjectivity of text, whose purpose is to define the polarity of the content of text, and opinion of the expresses in the form of binary ratings such as likes or dislikes, or a more granular set of choices, such as a 1 to 5 rating. This paper focuses primarily on high-level, end-to-end workflow to solve text classification problems using machine learning algorithm such as Naive-Bayes classifier for text classification issues to mining opinions and Amazon User Reviews.

Non-negative matrix factorization (NMF) has been one of the substantial progresses in the use of various clustering tasks in the recent times. NMF solves challenging data mining and machine learning problems. Our proposed technique solves this precarious problem of mining mathematical keywords from textual documents using NMF clustering based on a training set of mathematical keyword and formulae pairs. The recital of the proposed method is calculated using the metrics such as retrieval time, sensitivity, efficiency, and FNR are used for appraisal of the proposed technique.

Hydrothermal carbonization (HTC) of yard waste (YW) and food waste (FW) was performed in landfill leachate (LL) to overcome the unnecessary exploitation of our limited natural resources. The physicochemical properties and combustion behavior of the resulting hydrochars were compared with those obtained using distilled water (DW) as reaction medium. Although performing HTC in LL led to lower hydrochar mass yields (43% YWH and 36% FWH) than DW (47.1% YWH and 41.5% FWH), it had minimal impact on the fuel characteristics of the hydrochars. Notably, the higher heating value of the hydrochars prepared in LL (22.8 MJ kg−1 for YWH and 30.2 MJ kg−1 for FWH) is comparable to that of conventional solid fuels, and may, therefore, be considered as inexpensive alternatives to fossil fuels. Overall, the results of this study conclusively suggest that the use of LL as an alternative moisture source can significantly improve the sustainability of HTC technology.

The electromagnetic(EM) waves are used for long distance communication by using air as a medium but when EM waves are used for communication through soil it cannot penetrate through soil due to various compositions of soil like red, black cotton soil etc. When these waves are used for data transmission in soil there will be loss in data because of high difraction. When there is increase in transmission distance there will be high path loss and high attenuation because of interior distance. In this present day to day communication underground communication system needs to play a key role for the effective data transmission. To establish this effective wireless connection wireless underground sensor networks(WUSN) has been introduced. To overcome problems in the electromagnetic waves, Magnetic induction(MI) has been proposed as it consists of magnetic induction coils which are used as transceivers for the effective data transmission.

The traditional healthcare method follows 'one-size-fits-all' criteria, which shows some limitations in rendering proper results due to varied pharmacokinetic traits of different patients. Each patient shows a different result to a set of prescribed medicines with respect to other patient. In addition, this empirical criterion is also vulnerable to develop unfavourable side-effects due to overdose or under-dose. The advancements in the field of pharmacogenetic testing has paved the way for searching solutions to achieve the goal of 'personalized medicine'. This concept has the potential to provide more effective results as compared to the traditional technique. The technology of additive manufacturing or 3D printing can cater the need of the patient-centric principle. A wide range of 3D printing techniques provide the independence to work with a number of bio-materials. This paper carries out a systematic review methodology based on the application of this novel technology in the field of drug delivery. The materials, methods of drug administration, techniques used for printing have been elaborated along with the manufacturing of polypills with varied release profiles and geometries. Certain in vivo studies has also been reported to assess the feasibility of this technology. The concept of 4D printing in this direction has also been discussed. Finally, some excerpts on estimated future scope have also been illustrated.

The emerging rapid increase in the connectivity of computer networks and their usage has drawn the attention of organizations and data science researchers towards a secure data storage architecture, where it can be protected from unauthorized entities. In this paper a novel methodology "Image Encryption with Modified Diffie Hellman" (IEMDH) is designed and developed to address the suitability of encryption algorithms for low powered de vices and to offer a better security than existing approaches to contribute towards the Intelligent Enterprise security and sustainability. Here, the symmetric AES algorithm and Modified Diffie Hellman (MDH) algorithms are combined to enhance the overall security and it also eliminates the key exchange drawback in symmetric key techniques. Later, a performance evaluation is carried out between the proposed IEMDH approach and IERSA (Image Encryption with RSA algorithm) to check the suitability on low power devices.

The multilevel inverters (MLI) are having more features to usage. In existing methods like diode clamped MLI and H-Bridge MLI, more number of switches are using compared to proposed MLI. So, a new method of 35-level MLI topology is a combination of diode clamped and cascaded multilevel inverters. In this method using the less number of switches and their pulse generating circuit. So, thereby ensuring the switching loss, reducing size and installation cost also less. So, the new proposed technology is well designed for renewable applications (RA) like PV cell and wind energy systems. Comparing to the other existing inverters, the switch count is very less. The results are validating by using MATLAB/Simulink design.

The two different thermoplastic materials such as poly lactic acid (PLA) and carbon fiber poly lactic acid (CF-PLA) are selected for printed specimen preparation by the fused deposition modeling (FDM) technique. The FDM technique is also named as 3D printing technique. The experimental investigation is made to get the said materials specimen tensile and flexural strength and hardness properties to make a comparison between the two chosen printing materials with respect to the change in working limits of process parameters. The literature and trial experiments are performed to propose various and most effective process parameters of 3D printing technique like fill density (60, 80 and 100%), print speed (0.06, 0.08 and 0.1 m/s) and layer thickness (0.1, 0.2 and 0.3 microns). The influence of these process parameters is understood by analyzing the obtained testing results. The fill density and print speed are most accountable for getting maximum hardness, flexural and tensile strength of 3D printed PLA and carbon fiber material specimen. The most suitable material among CF-PLA, and PLA can be assessed and the working range of 3D printing process parameters can be assumed through this experimental investigation.

Distributed generator (DG) resources are the emerging micro-generating technologies such as fuel cells, micro turbines, IC engines. They also make use of renewable energy sources such as PV arrays and wind turbines. DG units have low emission rates and are environment friendly and economical. Power loss reductions, voltage profile improvement and increasing reliability are some advantages of DG units. The above benefits can be achieved by optimal placement of DGs. Optimal DG locations are obtained from power loss index method. A novel meta heuristic algorithm called whale optimization algorithm (WOA) is used to determine the optimal DG-unit's size in this paper. WOA modeled based on the unique hunting behavior of humpback whales. The WOA algorithm is tested on IEEE 15-bus, 33-bus, 69-bus, 85-bus and 118-bus test systems. The results obtained by the proposed WOA algorithm was compared with different types of DGs and other evolutionary algorithms. When compared with other algorithms the WOA algorithm gives better results. From the analysis best results have been achieved from type III DG operating at 0.9 pf. Keywords: Whale optimization algorithm, Power loss index method, Distributed generation placement, Radial distribution system, Loss reduction

As a new lingo-cellulosic natural fiber sources, agricultural processing wastes of onion and garlic, stalks and skins, were investigated by determining their chemical composition and characterizati...

Although both pulmonary and extrapulmonary tuberculosis (TB) are commonly encountered in developing countries, tenosynovitis is an uncommon presentation of musculoskeletal TB. TB mimics a lot of other conditions and causes diagnostic dilemma in day-to-day practice. We present the case of a 30-year-old male who presented with the complaints of swelling of right index finger which was initially suspected to be giant cell tumour of the flexor tendon sheath but on histological examination turned out to be tuberculous tenosynovitis.

Purpose To describe a case report of the beauty parlor stroke syndrome in a 32 year old patient Summary: Beauty parlor stroke syndrome, otherwise known as a Hairdresser-related ischemic cerebrovascular event (HICE) or vertebral-basilar ischemia (VBI), is a rare phenomenon caused by either cerebral artery dissection or vertebral artery compression due to neck positioning and manipulation at the hair salon sink bowl. Majority of the cases previously reported occurred in elderly women, rather than younger patients. We describe a case of beauty stroke syndrome in a 32 year-old patient with no prior medical history or risk factors such as atherosclerotic disease, diabetes, hypertension and hyperlipidemia. Conclusion: The 2014 Stroke guidelines issued a warning to healthcare professionals regarding the risk of cervical artery dissections following cervical manipulative therapy in young and middle-aged adults. However, the risk of cervical artery dissection following manipulation at the shampoo bowl was not specifically mentioned. Practitioners must be cognizant of the various symptoms of beauty salon syndrome, and intervene in a timely manner to prevent potential ongoing issues.