Incredible amounts of data is being generated by various organizations like hospitals, banks, e-commerce, retail and supply chain, etc. by virtue of digital technology. Not only humans but machines ...also contribute to data in the form of closed circuit television streaming, web site logs, etc. Tons of data is generated every minute by social media and smart phones. The voluminous data generated from the various sources can be processed and analyzed to support decision making. However data analytics is prone to privacy violations. One of the applications of data analytics is recommendation systems which is widely used by ecommerce sites like Amazon, Flip kart for suggesting products to customers based on their buying habits leading to inference attacks. Although data analytics is useful in decision making, it will lead to serious privacy concerns. Hence privacy preserving data analytics became very important. This paper examines various privacy threats, privacy preservation techniques and models with their limitations, also proposes a data lake based modernistic privacy preservation technique to handle privacy preservation in unstructured data.
The present study was conducted to ascertain whether the role of kisspeptin in promoting in vitro development of preantral follicles was through the regulation of P450 aromatase gene expression and ...steroidogenesis in sheep. Accordingly, the cumulus cells and oocytes were collected from different development stages of preantral follicles grown in vivo and cultured in vitro in TCM199B (Group I), TCM199B + KP (10 μg/mL) (Group II) and Standard medium + KP (10 μg/mL). To measure the steroid (Estradiol-17β; E
and Progesterone; P
) synthesis through ELISA, spent culture medium was collected separately from the same in vitro groups. E
synthesis in the spent medium collected from all the three groups showed an increasing trend from PFs' exposed to respective culture media for 3 min to 2-day culture stage but decreased thereafter till 6-day culture stage. This is followed by a sharp increase in E
concentration in the spent medium collected after in vitro maturation. However, P
synthesis in group III followed increased pattern as the development progressed from PFs' exposed to culture medium for 3 min to in vitro maturation stage. The steroid production was observed at all stages of in vitro development in altered supplemented conditions. The steroid synthesis in the spent medium was highest in the 6 day cultured PFs' in Standard medium + KP matured in vitro for 24 h. Therefore, supplementation of kisspeptin along with other growth factors promoted steroid production in cultured preantral follicles far better than in other media.
Cryptography is a method for preventing illegitimate access to information and data. In this paper, a bio-inspired cryptographic DNA system has been proposed. The proposed method consists of three ...phases: encryption, key generation and decryption. The scheme is proposed, from reproducing the normal procedures in the genetic encoding, transcription and translation and some of the inverse procedures have been used for the encryption and decryption of the data. And also for the encryption and decryption algorithms, it concentrates on the Central Dogma of Molecular Biology (CMDB).Thus, to store in the memory storage, a Bidirectional Associative Memory Neural Network (BAMNN) is used by recognizing and restoring the set of keys in present mode, and it is used educated in the randomized important generation information. Here, Whale Optimization Algorithm (WOA) is the highest fit weight vector. The proposed bio-instrumented encrypting system consists of adequate encoding as well as the decryption times, even though when the data is correlated in larger sizes in the current systems. Different safety attacks analyze the efficiency of the cryptosystem. This paper explored efficiency of the WOA algorithm by changing the number of hidden and input neurons. The proposed method is compared with traditional cryptographic techniques results in 55 and 67% increased processing time for encryption process and decryption process respectively.
•EESNN-FSOA-LCC from CT images is proposed.•Initially, the input lung CT images are gathered through IQ-OTH/NCCD Lung Cancer Dataset.•Then the input lung CT images are pre-processed using anisotropic ...diffusion Kuwahara filtering.•These pre-processed lung CT images are fed to HFLBiC for ROI region of lung cancer.•FSOAis proposed to optimize the EESNN classifier for classifying the lung cancer.
At present, researchers have been try to enhance the CAD system performance utilizing deep learning techniques in lung cancer screening and computed tomography (CT), but none of them attain the adequate accuracy. Therefore, an Enhanced Elman Spike Neural Network optimized with flamingo search optimization algorithm espoused Lung cancer classification from CT images (EESNN-FSOA-LCC) is proposed in this article. Initially, the input lung CT images are gathered through IQ-OTH/NCCD Lung Cancer Dataset. Then the input lung CT images are pre-processed using anisotropic diffusion Kuwahara filtering. These pre-processed lung CT images are fed to Hesitant Fuzzy Linguistic Bi-objective Clustering process for ROI region of lung cancer. Then the significant features present under ROI region of lung cancer segmentation are clarified through the help of Gray level co-occurrence matrix (GLCM) window adaptive approach. The extracted features are presented to EESNN for categorizing lung CT images image as normal, Benign, and Malignant. In general, EESNN classifier not divulges any adaption of optimization methods for determining the optimum parameters and to assure exact classification of lung cancer. Hence, a flamingo search OptimizationAlgorithmis proposed to optimize the EESNN classifier, which precisely classifies the lung cancer. The proposed EESNN-FSOA-LCC approach is activated in python. The proposed EESNN-FSOA-LCC approach achieves 38.58%, 25.69% and 43.87%, high accuracy when comparing to the existing CTI-LCC-SVM, CTI-LCC-GoogleNet-DNN and CTI-LCC-CNN respectively.
Sentiment analysis examines the emotional content of a statement, such as views, assessments, feelings, or attitudes about a topic, human, or object. Emotions can be categorized as either unbiased, ...good, or bad. It determines how people feel about the company online through social media. Based on the sentiments, the problem of solving the stock price prediction model is advantageous as it involves the sentiment score evaluated from the text information. This work introduces a new stock price prediction considering sentiment scores from text info in this concern. For that, we have considered news data and stock data. Moreover, this work falls under bigdata perspective by increasing the data size. The proposed model includes two major steps: feature extraction and prediction. Feature extraction takes place under two scenarios: features from news data and features from stock data. Features like Bag of words, n-Gram, TFIDF, and Improved cosine similarity are extracted from the news data, and features like improved exponential moving average and other existing technical indicator-based features such as ATR, TR are extracted from stock data. Both the feature sets are fused to determine the final prediction results. Particularly, this final observation involves the sentiments from the given news data. For this, optimized LSTM model is used, where the optimal training process will be carried out by a new Harris Hawks Induced Sparrow Search Optimization via tuning the optimal weights. The proposed model is the combination of Harris Hawks Optimization Algorithm and Sparrow Search Algorithm, respectively. Finally, the performance of proposed work will be evaluated over the other conventional models with respect to different measures.
Background: The Village Health, Sanitation, and Nutrition Committee (VHSNC) is a participatory effort aimed to strengthen the village-level agencies and to provide better health and sanitation ...services. However, there is a lack of evidence on the functionality of VHSNCs. Objectives: The present study aimed to explore the functionality of VHSNCs in the selected localities. Materials and Methods: The study was conducted in five districts of Chhattisgarh and Madhya Pradesh states. Using a multistage sampling method, a total of 508 VHSNCs were studied. The VHSNCs were considered as the unit of study. From each VHSNC, some key functionaries and its members were interviewed using a semi-structured interview schedule to understand the nature and effectiveness of its functioning. The researchers closely observed the meetings of VHSNCs and their records. Data were analyzed using descriptive statistical methods along with the impressions from the field notes. Results: The result of the study indicates that the functionality of the majority of the VHSNCs is not promising. Inadequate participation and improper implementation of key tasks are evident. Conclusion: The functionality of the VHSNC can be improved through the active involvement of Panchayati Raj Institutions and local communities.
Data security in the cloud has become a dominant topic being discussed in recent times as the security of data in the cloud has been focused on by several researchers. However, the data security was ...enforced at the attribute level, the adversaries are capable of learning the method of data encryption even there are access restrictions are enforced at an attribute level. To challenge the adversaries with more sophisticated security measures, an efficient real-time service-centric feature sensitivity analysis (RSFSA) model is proposed in this paper. The RSFSA model analyses the sensitivity of different features being accessed by any service and at multiple levels. At each level, the method checks the set of features being accessed and the number of features the user has access grant to compute the FLAG value for the user according to the profile given. Based on the value of FLAG, the user has been granted or denied service access. On the other side, the method maintains different encryption schemes and keys for each level of features. As the features are organized in multiple levels, the method maintains a set of schemes and keys for each level dedicative. Based on the service level and data, the method selects an encryption scheme and key to perform data encryption. According to that, the service access data has been encrypted at the attribute level with a specific scheme and key. Data encrypted has been uploaded to the blockchain and the method modifies the reference part of the chain to connect only the blocks to which the user has access. The chain given to the user would do not contain any reference from a specific block to which the user has no access. The proposed method improves the performance of data security and access restriction greatly.
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Recently there has been immense interest in the exploration of richly available two-dimensional non-toxic layered material such as tin disulfide (SnS2) for potential employment in ...energy and environmental needs. In this regard, we report on the synthesis of few-layered Sn1−xMgxS2 nanosheets through a facile one-step hydrothermal route to address all such functions concerning photocatalysis and photoelectrochemical conversion. The crystalline order and structure of processed layered Sn1−xMgxS2 were initially found to exhibit a strong influence on their physicochemical properties. Their optical properties attest the Mg doping in SnS2 to benefit us with enhanced visible-light absorption via red-shift in their absorption edge. In the photoluminescence spectrum the emissions observed along visible and red region signifies the association of Mg related trap states in Sn1−xMgxS2. Next, the photocurrent and electrochemical impedance spectroscopic results revealed the Mg doping to promote the effective charge transfer process (which was beneficial to enhance their photocatalytic activity). Consequently, the layered Sn0.98Mg0.02S2 made photoanodes displayed 1.7 fold higher photocurrent density under simulated solar radiation with respect to their undoped counterpart. Furthermore, the layered Sn0.98Mg0.02S2 nanosheets exhibits enhanced visible light decomposition of organic dye while compared with pristine SnS2 nanosheets. The value of rate constants obtained for the Sn0.98Mg0.02S2 nanosheets was found to be 1.4 times higher than that of pristine SnS2. Finally, the results obtained through the present study projects the huge potential of layered Sn0.98Mg0.02S2 nanosheets for future multifunctional applications.
Diabetic peripheral neuropathy is the most common complication of diabetes producing metabolic disruptions in the peripheral nervous system. Alteration in the predictable nature of tendon reflexes is ...the most common indicator suggesting the possibility of diabetic neuropathy. Evaluation of tendon reflexes is a part of various clinical scoring systems that assess neuropathy. The conventional reflex grading scales are subjective, lack temporal data, and have high inter-rater variability. Hence, an indigenous quantification tool was developed to evaluate the tendon reflexes in order to assess diabetic peripheral neuropathy.
A cross-sectional study was carried out in 140 healthy volunteers and 140 patients with type 2 diabetes. The mean age of controls and diabetics (49.1 ± 8.9, 50.7 ± 7.5) years, weight (66.9 ± 9.4, 69.8 ± 11.5) kilograms and BMI (24.5 ± 3.8, 26.1 ± 4.7), respectively. All of them are subjected to evaluation of tendon reflexes using the reflex quantification tool comprised of surface mechanomyography and electrogoniometry that can provide various static and dynamic variables of tendon reflex.
The dynamic variables such as reflex amplitude, muscle velocity and angular velocity were significantly low in diabetic patients (p: <0.001) whereas latency and duration (p: <0.001) were prolonged. Furthermore, no significant difference was observed in the application of tendon striking force (p: 0.934) among the participants.
The current study demonstrates that the proposed reflex quantification tool provides several dynamic variables of patellar tendon reflex, which are significantly affected and altered in diabetic patients suggesting the involvement of peripheral neurons.
•The neuropathic and myopathic complications of diabetes alter the predictive nature of the phasic muscle stretch reflexes.•An objective method was developed to assess the muscle activity and movement patterns associated with the reflex response.•Surface mechanomyography and electrogoniometry were implemented to evaluate the reflexes in patients with diabetes.•The muscle velocities, reflex amplitude and angular displacements were significantly affected in people with diabetes.
Quantitative patterns of expression of the growth differentiation factor 9 (GDF9) and bone morphogenic protein 15 (BMP15) genes in different development stages of in vivo and in vitro grown ovarian ...follicles in sheep were studied for the first time. Both GDF9 and BMP15 were expressed in the cumulus cells and oocytes at all the development stages of in vivo and in vitro grown ovarian follicles. Growth differentiation factor 9 and bone morphogenic protein 15 exhibited stage-specific undulations in the expression in the cumulus cells and oocytes isolated from in vivo grown ovarian follicles. These undulations could be related to discrete development events during the ovarian follicle development. The expression of GDF9 and BMP15 was highest (3.38 ± 0.02 and 2.69 ± 0.06, respectively; P ≤ 0.05) in the primordial follicles compared with preantral, early antral, antral, and large antral stages. Similarly, GDF9 and BMP15 expression in the cumulus cells (0 ± 0.16 and 0 ± 0.07) and oocytes (1.47 ± 0.07 and 1.32 ± 0.03) was lowest (P ≤ 0.05) in the in vivo grown antral follicles. In the cultured follicles, the stage-specific undulations observed in the expression of GDF9 and BMP15 in the in vivo grown follicles were either different or abolished. For example, in the oocytes from in vitro grown follicles, the expression of BMP15 did not change as the development progressed all the way from preantral to large antral follicle stage although in the oocytes from in vivo grown follicles BMP15 expression exhibited stage-specific variations. It is concluded that GDF9 and BMP15 follow a stage-specific pattern of expression during the in vivo development of ovarian follicles in sheep, and in vitro culture altered the stage-specific changes in the expression of these two genes.
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