Developed A Hybrid Optimal Feature Vector Selection with Blockchain Technology for Smart Healthcare 4.0

The health economy has been an innovative technology since time-honored. Preserving and maintaining patient data are essential in a routine life. Patient’s medical information is very important for every individual not only for patients but also for doctors who are examining them. Advances in sensing technology, processing of data, and communication protocols have transformed the healthcare industry. Patients, physicians, hospitals, and other stakeholder may keep vital data and medical records with the use of electronic healthcare records (EHR). The goal of research should be to develop a Hybrid Optimal Feature Vector Selection with Blockchain Technology (HOFVS-BT) for smart healthcare 4.0 to improve the secure transmission of data which is supported intelligent IoT and medical detection platform possible. For Feature vector selection, proposed an Orthogonal Wolf Optimization (OWO) algorithm. Furthermore, safeguarding private patient details is taken into account by establishing an upgraded Blockchain-based IoT data security solution that not only secures the data, but also fosters trust between patients/users and healthcare service providers

Cloud based multicasting using fat tree data confidential recurrent neural network

With the progress of cloud computing, more users are attracted by its strong and cost-effective computation potentiality. Nevertheless, whether Cloud Service Providers can efficiently protect Cloud Users data confidentiality (DC) remains a demanding issue. The CU may execute several applications with multicast needs. In Cloud different techniques were used to provide DC with multicast necessities. In this work, we aim at ensuring DC in the cloud. This is achieved using a two-step technique, called Fat Tree Data Confidential Recurrent Neural Network (FT-DCRNN) in a cloud environment. The first step performs the construction of Fat Tree based on Multicast model. The aim to use Fat Tree with Multicast model is that the multicast model propagates traffic on multiple links. With the Degree Restrict Multicast Fat Tree construction algorithm using a reference function, the minimum average between two links is measured. With these measured links, multicast is said to be performed that in turn improves the throughput and efficiency of cloud service. Then, with the objective of providing DC for the multi-casted data or messages, DCRNN model is applied. With the Non-linear Recurrent Neural Network using Logistic Activation Function, by handling complex non-linear relationships, average response time is said to be reduced

Experimental Investigation of Catalytic Surface Reaction for Different Metal Surfaces

The use of a catalytic surface to enhance chemical reaction rates is a well established and common practice. However, its use in combustion devices for enhancing combustion reaction is somewhat less common and more recent. Catalytic combustors, because of their inherent ability to operate at very lean air fuel mixtures, can maintain a relatively low combustion temperature and hence reduce the formation of NOx significantly. Further the catalytic coating on the combustion chamber walls enhances the combustion process by increased rate of pre-flame reactions. This provides a basis for catalytic combustion in lean burn engine. A considerable amount of effort has been devoted in the present work to this experimental study and compares different catalyst reaction performance.A cylindrical chamber is fabricated and air-fuel mixture is passed through the chamber. A metal tube coated with the catalyst is placed inside the control volume and it is heated by an electric heater. The air-fuel mixture undergoes pre-flame combustion reaction and as a result of this, the miniature temperature increases. Various catalytic surfaces like mild steel, Nickel, Chromium and copper were tested. The activation temperatures of these catalytic surfaces were obtained from this experimental work. Keywords: catalytic reaction, LPG, activation energy, catalytic coatin

A Modified Polybius Square Based Approach for Enhancing Data Security

Digital communication is the prominent technique used by various organizations for information exchange. It replaces the traditional methods with the help of internet and its related technologies. There is a chance to retrieve the contents of the transmitted message from the unsecure communication medium. The biggest challenge is to deploy a suitable mechanism for secure communication. Cryptography plays a dominant role in the information security domain. This paper proposes a modified Polybius square based approach for efficient key generation. New key is obtained from the original key by performing three different operations on modified Polybius square namely Square ring rotation, Square reversal and Transpose. From the security analysis it can be inferred that the proposed approach generates an efficient key

Growth and Biochemical Changes of Vegetable Seedlings Induced by Arbuscular mycorrhizal Fungus

Department of Botany, Annamalai University, Annamalai Nagar – 608 002ABSTRACT: The efforts were made to study the effects of Arbuscular Mycorrhizal fungi (AM) on the morphological and biochemical changes of four different vegetable seedlings grown under nursery conditions. The symbiotic association between AM fungi and plant roots provides a significant contribution to plant nutrition and growth. Hence, an attempt has been made to examine the effect of AM fungi on the four vegetable crops such as Tomato (Lycopersicum esculentum L.), Brinjal (Solanum melongena L.), Chilli (Capsicum annuum L.) and Bhendhi (Abelmoschus esculentus Moench.). The maximum increase in four plant’s morphological parameters like root length, shoot length, fresh weight, dry weight, number of leaves, total leaf area and biochemical parameters like chlorophylls, proteins and nutrient content of nitrogen, phosphorus and potassium were observed in AM fungi treated seedlings when compared to non-mycorrhizal seedlings (controlled). The sugar and starch contents showed decrease in mycorrhizal seedlings than non-mycorrhizal one. Key words: Glumus fasciculatum, Vegetables, Morphological parameters, Biochemical content Department of Botany, Annamalai University, Annamalai Nagar – 608 002M. Lenin, G. Selvakumar, P. Thamizhiniyan, R. Rajendiran. Growth and Biochemical Changes of Vegetable Seedlings Induced by Arbuscular mycorrhizal Fungus. J. Exp. Sci. 1(4):27-31 Please Cite This Article As

A Modified Polybius Square Based Approach for Enhancing Data Security

Digital communication is the prominent technique used by various organizations for information exchange. It replaces the traditional methods with the help of internet and its related technologies. There is a chance to retrieve the contents of the transmitted message from the unsecure communication medium. The biggest challenge is to deploy a suitable mechanism for secure communication. Cryptography plays a dominant role in the information security domain. This paper proposes a modified Polybius square based approach for efficient key generation. New key is obtained from the original key by performing three different operations on modified Polybius square namely Square ring rotation, Square reversal and Transpose. From the security analysis it can be inferred that the proposed approach generates an efficient key

Investigations on Electrochemical Micro Drilling of Nickel Alloy using Taguchi based Grey Approach

Inconel 600 is the nickel based super alloy which is employed in numerous engineering applications like gas turbine blades, turbochargers and heat exchangers etc. However, it is very difficult to machine due to its high strength and poor thermal diffusion. Conventional machining methods of these materials may result in decreased life time. An electrochemical machining is an advanced non-traditional technique which is suitable for machining hard material, strenuous materials and Intricate shapes. In this paper, electrochemical micro drilling (ECMD) on Inconel 600 material is investigated. The experiments are devised and analyzed using Taguchi’s L18 orthogonal array and Grey relational analysis (GRA). Analysis of variance (ANOVA) has been implemented to find out the significance of electrochemical micro drilling parameters on the performance characteristics

Investigations on Electrochemical Micro Drilling of Nickel Alloy using Taguchi based Grey Approach

424-429Inconel 600 is the nickel based super alloy which is employed in numerous engineering applications like gas turbine blades, turbochargers and heat exchangers etc. However, it is very difficult to machine due to its high strength and poor thermal diffusion. Conventional machining methods of these materials may result in decreased life time. An electrochemical machining is an advanced non-traditional technique which is suitable for machining hard material, strenuous materials and Intricate shapes. In this paper, electrochemical micro drilling (ECMD) on Inconel 600 material is investigated. The experiments are devised and analyzed using Taguchi’s L18 orthogonal array and Grey relational analysis (GRA). Analysis of variance (ANOVA) has been implemented to find out the significance of electrochemical micro drilling parameters on the performance characteristics

Accuracy of tumor segmentation from multi-parametric prostate MRI and 18F-choline PET/CT for focal prostate cancer therapy applications

Abstract Background The study aims to assess the accuracy of multi-parametric prostate MRI (mpMRI) and 18F-choline PET/CT in tumor segmentation for clinically significant prostate cancer. 18F-choline PET/CT and 3 T mpMRI were performed in 10 prospective subjects prior to prostatectomy. All subjects had a single biopsy-confirmed focus of Gleason ≥ 3+4 cancer. Two radiologists (readers 1 and 2) determined tumor boundaries based on in vivo mpMRI sequences, with clinical and pathologic data available. 18F-choline PET data were co-registered to T2-weighted 3D sequences and a semi-automatic segmentation routine was used to define tumor volumes. Registration of whole-mount surgical pathology to in vivo imaging was conducted utilizing two ex vivo prostate specimen MRIs, followed by gross sectioning of the specimens within a custom-made 3D-printed plastic mold. Overlap and similarity coefficients of manual segmentations (seg1, seg2) and 18F-choline-based segmented lesions (seg3) were compared to the pathologic reference standard. Results All segmentation methods greatly underestimated the true tumor volumes. Human readers (seg1, seg2) and the PET-based segmentation (seg3) underestimated an average of 79, 80, and 58% of the tumor volumes, respectively. Combining segmentation volumes (union of seg1, seg2, seg3 = seg4) decreased the mean underestimated tumor volume to 42% of the true tumor volume. When using the combined segmentation with 5 mm contour expansion, the mean underestimated tumor volume was significantly reduced to 0.03 ± 0.05 mL (2.04 ± 2.84%). Substantial safety margins up to 11–15 mm were needed to include all tumors when the initial segmentation boundaries were drawn by human readers or the semi-automated 18F-choline segmentation tool. Combining MR-based human segmentations with the metabolic information based on 18F-choline PET reduced the necessary safety margin to a maximum of 9 mm to cover all tumors entirely. Conclusions To improve the outcome of focal therapies for significant prostate cancer, it is imperative to recognize the full extent of the underestimation of tumor volumes by mpMRI. Combining metabolic information from 18F-choline with MRI-based segmentation can improve tumor coverage. However, this approach requires confirmation in further clinical studies.https://deepblue.lib.umich.edu/bitstream/2027.42/142871/1/13550_2018_Article_377.pd

NMR-based metabolomic profiling of urine: Evaluation for application in prostate cancer detection

Detection of prostate cancer (PCa) and distinguishing indolent versus aggressive forms of the disease is a critical clinical challenge. The current clinical test is circulating prostate-specific antigen levels, which faces particular challenges in cancer diagnosis in the range of 4 to 10 ng/mL. Thus, a concerted effort toward building a noninvasive biomarker panel has developed. In this report, the hypothesis that nuclear magnetic resonance (NMR)-derived metabolomic profiles measured in the urine of biopsy-negative versus biopsy-positive individuals would nominate a selection of potential biomarker signals was investigated. 1H NMR spectra of urine samples from 317 individuals (111 biopsy-negative, 206 biopsy-positive) were analyzed. A double cross-validation partial least squares-discriminant analysis modeling technique was utilized to nominate signals capable of distinguishing the two classes. It was observed that after variable selection protocols were applied, a subset of 29 variables produced an area under the curve (AUC) value of 0.94 after logistic regression analysis, whereas a “master list” of 18 variables produced a receiver operating characteristic ROC) AUC of 0.80. As proof of principle, this study demonstrates the utility of NMR-based metabolomic profiling of urine biospecimens in the nomination of PCa-specific biomarker signals and suggests that further investigation is certainly warranted