A Compression Algorithm for DNA Palindrome Compression Technique

Data Compression in Cryptography is one of the interesting research topic. The compression process reduces the amount of transferring data as well as storage space which in turn effects the usage of bandwidth. Further, when a plain text is converted to cipher text, the length of the cipher text becomes large. This adds up to tremendous information storing. It is extremely important to address the storage capacity issue along with the security issues of exponentially developing information. This problem can be resolved by compressing the ciphertext based on a some compression algorithm. In this proposed work used the compression technique called palindrome compression technique. The compression ratio of the proposed method is better than the standard method for both colored and gray scaled images. An experimental result for the proposed methods is better than existing methods for different types of image.

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Design, Development and Comparison of Heuristic Driven Algorithms Based on the Crossed Domain Products’ Reviews for User’s Summarization

Recent Advances in Computer Science and Communications ◽

10.2174/2213275912666190626110342 ◽

2020 ◽

Vol 13 (5) ◽

pp. 884-892

Author(s):

Sartaj Ahmad ◽

Ashutosh Gupta ◽

Neeraj Kumar Gupta

Keyword(s):

Decision Making ◽

Online Shopping ◽

Recent Time ◽

Design Development ◽

Different Types ◽

Feature Based ◽

Use Of Internet ◽

Day By Day ◽

Better Than

Background: In recent time, people love online shopping but before any shopping feedbacks or reviews always required. These feedbacks help customers in decision making for buying any product or availing any service. In the country like India this trend of online shopping is increasing very rapidly because awareness and the use of internet which is increasing day by day. As result numbers of customers and their feedbacks are also increasing. It is creating a problem that how to read all reviews manually. So there should be some computerized mechanism that provides customers a summary without spending time in reading feedbacks. Besides big number of reviews another problem is that reviews are not structured. Objective: In this paper, we try to design, implement and compare two algorithms with manual approach for the crossed domain Product’s reviews. Methods: Lexicon based model is used and different types of reviews are tested and analyzed to check the performance of these algorithms. Results: Algorithm based on opinions and feature based opinions are designed, implemented, applied and compared with the manual results and it is found that algorithm # 2 is performing better than algorithm # 1 and near to manual results. Conclusion: Algorithm # 2 is found better on the different product’s reviews and still to be applied on other product’s reviews to enhance its scope. Finally, it will be helpful to automate existing manual process.

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Identification of Essential Proteins in Yeast Using Mean Weighted Average and Recursive Feature Elimination

Recent Patents on Computer Science ◽

10.2174/2213275911666180918155521 ◽

2019 ◽

Vol 12 (1) ◽

pp. 5-10 ◽

Cited By ~ 5

Author(s):

Sivagnanam Rajamanickam Mani Sekhar ◽

Siddesh Gaddadevara Matt ◽

Sunilkumar S. Manvi ◽

Srinivasa Krishnarajanagar Gopalalyengar

Keyword(s):

Drug Design ◽

Weighted Average ◽

Living Organism ◽

Experimental Result ◽

Recursive Feature Elimination ◽

Protein Interaction Data ◽

Essential Proteins ◽

Protein Protein Interaction ◽

Result Show ◽

Better Than

Background: Essential proteins are significant for drug design, cell development, and for living organism survival. A different method has been developed to predict essential proteins by using topological feature, and biological features. Objective: Still it is a challenging task to predict essential proteins effectively and timely, as the availability of protein protein interaction data depends on network correctness. Methods: In the proposed solution, two approaches Mean Weighted Average and Recursive Feature Elimination is been used to predict essential proteins and compared to select the best one. In Mean Weighted Average consecutive slot data to be taken into aggregated count, to get the nearest value which considered as prescription for the best proteins for the slot, where as in Recursive Feature Elimination method whole data is spilt into different slots and essential protein for each slot is determined. Results: The result shows that the accuracy using Recursive Feature Elimination is at-least nine percentages superior when compared to Mean Weighted Average and Betweenness centrality. Conclusion: Essential proteins are made of genes which are essential for living being survival and drug design. Different approaches have been proposed to anticipate essential proteins using either experimental or computation methods. The experimental result show that the proposed work performs better than other approaches.

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Comparative Study of Cryptography for Cloud Computing for Data Security

Recent Advances in Computer Science and Communications ◽

10.2174/2666255813666190911114909 ◽

2019 ◽

Vol 13 ◽

Author(s):

Priya Mathur ◽

Amit Kumar Gupta ◽

Prateek Vashishtha

Keyword(s):

Cloud Computing ◽

Data Security ◽

Elliptic Curve Cryptography ◽

Plain Text ◽

Hybrid Encryption ◽

Cipher Text ◽

Business Applications ◽

Computing Grid ◽

Cloud Servers ◽

Client Side

Cloud computing is an emerging technique by which anyone can access the applications as utilities over the internet. Cloud computing is the technology which comprises of all the characteristics of the technologies like distributed computing, grid computing, and ubiquitous computing. Cloud computing allows everyone to create, to configure as well as to customize the business applications online. Cryptography is the technique which is use to convert the plain text into cipher text using various encryption techniques. The art and science used to introduce the secrecy in the information security in order to secure the messages is defined as cryptography. In this paper we are going to review few latest Cryptographic algorithms which are used to enhance the security of the data on the cloud servers. We are comparing Short Range Natural Number Modified RSA (SRNN), Elliptic Curve Cryptography Algorithm, Client Side Encryption Technique and Hybrid Encryption Technique to secure the data in cloud.

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Fighting Together against the Pandemic: Learning Multiple Models on Tomography Images for COVID-19 Diagnosis

AI ◽

10.3390/ai2020016 ◽

2021 ◽

Vol 2 (2) ◽

pp. 261-273

Author(s):

Mario Manzo ◽

Simone Pellino

Keyword(s):

Network Architecture ◽

State Of The Art ◽

Ensemble Classification ◽

Effective Vaccine ◽

Rt Pcr ◽

Neural Network Architecture ◽

Experimental Phase ◽

Different Types ◽

Polymerase Chain ◽

Better Than

COVID-19 has been a great challenge for humanity since the year 2020. The whole world has made a huge effort to find an effective vaccine in order to save those not yet infected. The alternative solution is early diagnosis, carried out through real-time polymerase chain reaction (RT-PCR) tests or thorax Computer Tomography (CT) scan images. Deep learning algorithms, specifically convolutional neural networks, represent a methodology for image analysis. They optimize the classification design task, which is essential for an automatic approach with different types of images, including medical. In this paper, we adopt a pretrained deep convolutional neural network architecture in order to diagnose COVID-19 disease from CT images. Our idea is inspired by what the whole of humanity is achieving, as the set of multiple contributions is better than any single one for the fight against the pandemic. First, we adapt, and subsequently retrain for our assumption, some neural architectures that have been adopted in other application domains. Secondly, we combine the knowledge extracted from images by the neural architectures in an ensemble classification context. Our experimental phase is performed on a CT image dataset, and the results obtained show the effectiveness of the proposed approach with respect to the state-of-the-art competitors.

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Deep Learning Methods for Classification of Certain Abnormalities in Echocardiography

Electronics ◽

10.3390/electronics10040495 ◽

2021 ◽

Vol 10 (4) ◽

pp. 495

Author(s):

Imayanmosha Wahlang ◽

Arnab Kumar Maji ◽

Goutam Saha ◽

Prasun Chakrabarti ◽

Michal Jasinski ◽

...

Keyword(s):

Deep Learning ◽

Short Term Memory ◽

Support Vector ◽

Variational Autoencoder ◽

Different Types ◽

Static Images ◽

Long Short Term Memory ◽

2D And 3D ◽

Better Than

This article experiments with deep learning methodologies in echocardiogram (echo), a promising and vigorously researched technique in the preponderance field. This paper involves two different kinds of classification in the echo. Firstly, classification into normal (absence of abnormalities) or abnormal (presence of abnormalities) has been done, using 2D echo images, 3D Doppler images, and videographic images. Secondly, based on different types of regurgitation, namely, Mitral Regurgitation (MR), Aortic Regurgitation (AR), Tricuspid Regurgitation (TR), and a combination of the three types of regurgitation are classified using videographic echo images. Two deep-learning methodologies are used for these purposes, a Recurrent Neural Network (RNN) based methodology (Long Short Term Memory (LSTM)) and an Autoencoder based methodology (Variational AutoEncoder (VAE)). The use of videographic images distinguished this work from the existing work using SVM (Support Vector Machine) and also application of deep-learning methodologies is the first of many in this particular field. It was found that deep-learning methodologies perform better than SVM methodology in normal or abnormal classification. Overall, VAE performs better in 2D and 3D Doppler images (static images) while LSTM performs better in the case of videographic images.

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Numerical Study of Pressure Attenuation Effect on Tunnel Structures Subjected to Blast Loads

Applied Sciences ◽

10.3390/app11125646 ◽

2021 ◽

Vol 11 (12) ◽

pp. 5646

Author(s):

Cheng-Wei Hung ◽

Ying-Kuan Tsai ◽

Tai-An Chen ◽

Hsin-Hung Lai ◽

Pin-Wen Wu

Keyword(s):

Numerical Simulation ◽

Orifice Plate ◽

Experimental Result ◽

Scale Model ◽

Pressure Reduction ◽

Expansion Chamber ◽

Pressure Relief ◽

Attenuation Effect ◽

The One ◽

Better Than

This study used experimental and numerical simulation methods to discuss the attenuation mechanism of a blast inside a tunnel for different forms of a tunnel pressure reduction module under the condition of a tunnel near-field explosion. In terms of the experiment, a small-scale model was used for the explosion experiments of a tunnel pressure reduction module (expansion chamber, one-pressure relief orifice plate, double-pressure relief orifice plate). In the numerical simulation, the pressure transfer effect was evaluated using the ALE fluid–solid coupling and mapping technique. The findings showed that the pressure attenuation model changed the tunnel section to diffuse, reduce, or detour the pressure transfer, indicating the blast attenuation effect. In terms of the effect of blast attenuation, the double-pressure relief orifice plate was better than the one-pressure relief orifice plate, and the single-pressure relief orifice plate was better than the expansion chamber. The expansion chamber attenuated the blast by 30%, the one-pressure relief orifice plate attenuated the blast by 51%, and the double-pressure relief orifice plate attenuated the blast by 82%. The blast attenuation trend of the numerical simulation result generally matched that of the experimental result. The results of this study can provide a reference for future protective designs and reinforce the U.S. Force regulations.

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Etude par spectrométrie infrarouge de l'action de solvants aprotiques sur l'association ester–eau et ester–Ba2+. Discussion du rôle catalytique du solvant et de l'ion Ba2+ dans l'hydrolyse alcaline du propionate de methyle

Canadian Journal of Chemistry ◽

10.1139/v79-067 ◽

1979 ◽

Vol 57 (4) ◽

pp. 400-403 ◽

Cited By ~ 1

Author(s):

Anne Le Narvor ◽

Pierre Saumagne

Keyword(s):

Ir Spectra ◽

Charge Density ◽

Carbonyl Group ◽

Alkaline Hydrolysis ◽

Experimental Results ◽

Methyl Propionate ◽

Orbital Control ◽

Different Types ◽

Kinetics Of ◽

Better Than

The ir spectra of mixtures of methyl propionate/water and methyl propionate/Ba2+ in dimethylsulfoxide and in acetonitrile have been recorded in the region of the νCO mode of the ester. Evidence is presented to indicate the presence of different types of complexes; their concentration was determined as a function of the composition of the medium. The spectroscopic results are compared to those from the kinetics of the alkaline hydrolysis in the same conditions. It is demonstrated that the orbital control explains the experimental results better than does the charge density on the carbon of the carbonyl group. [Journal translation]

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DISSOLUTION ENHANCEMENT OF ATOVAQUONE USING CYCLODEXTRINS AND FORMULATING TO ORODISPERSIBLE TABLETS

INDIAN DRUGS ◽

10.53879/id.53.06.10427 ◽

2016 ◽

Vol 53 (06) ◽

pp. 32-39

Author(s):

A. K Mahapatra ◽

◽

P. N. Murthy

Keyword(s):

Inclusion Complexes ◽

Dissolution Enhancement ◽

Phase Solubility ◽

Scanning Calorimetry ◽

Compression Technique ◽

Sodium Starch Glycolate ◽

Orodispersible Tablets ◽

Kneading Method ◽

Gibb’S Free Energy ◽

Better Than

The aim of the study was to enhance the dissolution rate of atovaquone by preparing inclusion complexes with cyclodextrins (β-CD/ HP β-CD) and formulating their orodispersible tablets. Phase solubility studies were conducted by adding 0.5, 1, 2 and 4% of cyclodextrins in water. The values of Gibb’s free energy were found increased. Inclusion complexes of atovaquone were prepared using β -CD/ HP β -CD by kneading method. Tablets were formulated using superdisintegrants i.e., sodium starch glycolate, crospovidone and Ac-Di sol at concentrations of 4, 8 and 12% of tablet weight by direct compression technique. The interaction studies were made by Fourier transform infrared spectroscopy and differential scanning calorimetry, and no significant interaction was observed. Inclusion complexes showed better dissolution than pure atovaquone and HP-β-CD established better than β-CD. Inclusion complexes of atovaquone at 1:0.25 w/w (drug: HP β -CD) in the tablets with 12% of crospovidone showed satisfactory results.

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The structures of benzimidazole derivatives and their potential as tuberculostatics

Acta Crystallographica Section C Structural Chemistry ◽

10.1107/s2053229618014675 ◽

2018 ◽

Vol 74 (12) ◽

pp. 1684-1691

Author(s):

Marek L. Główka ◽

Sylwia Kałużyńska ◽

Malwina Krause ◽

Katarzyna Gobis ◽

Henryk Foks ◽

...

Keyword(s):

Multidrug Resistant ◽

Benzimidazole Derivatives ◽

X Ray Diffraction ◽

Intermolecular Hydrogen Bonds ◽

X Ray ◽

Resistant Varieties ◽

Different Types ◽

Mdr Tb ◽

Aromatic Systems ◽

Better Than

Tuberculosis still remains a very important problem, especially its multidrug resistant varieties (MDR-TB). Among the potential tuberculostatics, there are two benzimidazole derivatives, namely 5,6-dimethyl-2-phenylethylbenzo[d]imidazole (1) and (E)-5,6-dimethyl-2-styryl-1H-benzo[d]imidazole (2) which showed significant tuberculostatic activities, better than those of Pyrazinamide and Isoniazyd. Also, the cytotoxicity of 1 appeared promising. The compounds were studied (with the use of X-ray diffraction) in the form of the hemihydrate of 1, C17H18N2·0.5H2O (1a), the methanol hemisolvate of 2, C17H16N2·0.5CH3OH (2a), and the acid oxalate salt of 2, namely (E)-5,6-dimethyl-2-styryl-1H-benzo[d]imidazolium hydrogen oxalate, C17H17N2 +·C2HO4 − (2b). All three structures reveal a similar extended conformation, despite the flexible linker between the two aromatic systems and the different types of strong intermolecular hydrogen bonds. The molecules of 2a are practically planar due to the double bond in the linker, which enables conjugation along the whole molecule, while the molecules of 1a exhibit the possibility of parallel orientations of their aromatic systems, despite the aliphatic (ethyl) linker.

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Free-Choice, Final Performance and Attitudes toward Different Types of Programmed Instruction

Journal of Education ◽

10.1177/002205747315500307 ◽

1973 ◽

Vol 155 (3) ◽

pp. 56-63

Author(s):

Avraham Scherman ◽

Marion Scherman

Keyword(s):

Free Choice ◽

Programmed Instruction ◽

Traditional Lecture ◽

Fourth Class ◽

Choice Group ◽

Different Types ◽

Mode Of Instruction ◽

Experimental Subjects ◽

Better Than ◽

Instruction Approach

One-hundred thirty-six students enrolled in four classes of a counseling theories course served as the experimental subjects. In three classes students were randomly assigned to one of three modes of instruction: prose-text, linear programmed instruction, and branching programmed instruction. Subjects from the fourth class were given free choice to select the mode of instruction preferred. It was found that the free-choice group performed better than the linear and branching programmed instruction groups, although not significantly better than the prose-text group. In response to a questionnaire, males stated that when compared to traditional lecture-type courses, the programmed instruction approach helped them concentrate and resulted in a more efficient use of their time. Females did not think that the use of programmed instruction offered an interesting and stimulating approach.

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