003762   ALNASER A M A (Applied Science Dep, Al-Balqa Applied Univ, As-Salt, Jordan, Email: Asad1-99@Bau.edu.jo) : Certain contributions in traffic engineering based on software-defined networking technology. J Comput Sci 2019, 15(7), 944-53.

The paper addresses the traffic engineering in SoftwareDefined Networks (SDN). A brief analysis of the features of the SDN organization, which allows to increase the Traffic Engineering (TE) efficiency, is given. The viability of using multipath routing with TE is substantiated. Taking into account the features of the SDN technology, a modified TE method, which allows to reduce the time complexity of generating a set of paths and to reduce the rerouting time, is proposed. The procedure and an example of the routing tables’ formation are given. The results of modeling the TE process with changing communication links load are given. It is shown, that route reconfiguration does not significantly affect its traffic metric.

8 illus, 27 tables, 16 ref

003789   RODRIGUES D, SEVERINO J N, CRISTIANI A L, COSTA F T M, NAKAMURA L H V, MENEGUETTE R I (Federal Institute of São Paulo, Catanduva, Brazil, Email: meneguette@ifsp.edu.br) : A low-cost vehicular infrastructure of monitoring and communicating information for intelligent transport systems. J Comput Sci 2019, 15(7), 930-43.

Currently, vehicles have a very large range of sensors and actuators, capable of not only sensing the condition of vehicles but also the environment around them. The information from these sensors can be used for various services in which they can bring greater comfort, safety and entertainment to the passengers and conductors of the vehicle. However, the great challenge lies in the abstraction and propagation of this information to a service center or to an application in a secure and accessible way to all users. Thus, with the objective of developing low-cost information abstraction devices accessible to all, we propose the development of an architecture that will perform the capture of vehicular data through an electric circuit proposed, as well as the propagation of this information through a web service of monitoring school vans that can be accessed through an application focused on smartphones. To verify the functioning of this architecture we use our monitoring of school vans system as a case study.

11 illus, 1 table, 24 ref

003788   REKHA G, TYAGI A K, REDDY V K (Vellore Institute of Technology, Chennai- 600 127, Email: amitkrtyagi025@gmail.com) : A wide scale classification of class imbalance problem and its solutions: A systematic literature review. J Comput Sci 2019, 15(7), 886-929.

In today’s world, most of the data (real world) is present in imbalanced form by nature. This is because of not having efficient algorithms to put this data (i.e., generated data by billion of internetconnected devices (IoTs)) in respective format. Imbalanced data poses a great challenge to (both) data mining and machine learning algorithms. The imbalanced dataset consists of a majority class and a minority class, where the majority class takes the lead over the minority class. Generally, several standard learning algorithms assume the balanced class distribution or equal misclassification costs. If prediction is performed by these learning algorithms on imbalanced data, the accuracy will be high for majority classes, i.e., resulting in poor performance. To overcome this problem (or improving accuracy of deision/prediction-making process), data mining and machine learning researchers have addressed the problem of imbalanced data using datalevel, algorithmic level and ensemble or hybrid methods. This article presents a systematic literature review and analyze the results of more than 400 research papers published between 2002-2017 (till June 2017), resulting in a broader and elaborate investigation of the literature in this area of research. Note that extension of this article/work will contain till December 2018 research articles, which will be published in June 2019 (now these more papers/articles did not include due to no. of pages/space issues). The systematic analysis of the research literature has focus on the key role of Data Intrinsic Problems in classification, handling the imbalanced data and the techniques used to overcome the skewed distribution. Furthermore, this article reveals patterns, trends and gaps in the existing literature and discusses briefly the next generation research directions in this area.

8 illus, 21 tables, 211 ref

003792   SHAKAH G, ALKHASAWNEH M, KRASNOPROSHIN V, MAZOUKA D (Computer Sciences Dep, Aloun National Univ, Jordan- 26810, Email: g.shakah@anu.edu.jo) : Graphics pipeline evolution: Problems and solutions. J Comput Sci 2019, 15(7), 880-5.

Real-time computer graphics technologies such as graphics engines and graphics pipeline (software and hardware components) have improved considerably in the past decade. However, increase in efficiency and broadening of the applicability area has come at the cost of complexity of the tools. Therefore, development costs of advanced visualization systems can increase considerably. In this research we explore the possibility of addressing this problem by analyzing the software development methodology of graphics pipeline. We believe that the pipeline’s limitation regarding geometrical primitives in its operations is one of the reasons for the development efficiency bottleneck. We propose an approach that extends graphics pipeline with additional processing stages that can operate with primitives of higher order. This new method has the potential to reduce the pipeline’s application-level complexity for developers to create better software.

2 illus, 23 ref

003777   JAWAD M A, KADHIM A J (Al-Nisour Univ Coll, Baghdad, Iraq, Email: mohammed.a.medical.lab@nuc.edu.iq) : Ascorbic acid as an inhibitor for SARS-CoV-2 virus reproduction: A theoretical approach. J Commun Dis 2019, 53(3), 181-5.

In the present study, ascorbic acid’s or Vitamin C’s influence (VC) in inhibition of SARS-CoV-2 virus reproduction was investigated. Gaussian 09 with a basis set of 6-311G (d, p), MGL tools, DSV, and LigPlus software were used. According to the Total Electron Density (TED) and Millikan charges, the active sites for adsorption were determined. Further, the docking study had clearly revealed the role of VC in inhibition of the virus reproduction in accordance with binding energy (Eb) and ligand efficiency (LE). The vitamin’s interaction with the virus’s spikes may limit its replication or provide the immune system sufficient time to recognize the infection, which enhances the possibility of producing appropriate antibodies.

5 illus, 2 tables, 37 ref

003773   HUSSAIN A, VERMA C K (Bioinformatics Dep, MANIT, Bhopal, Madhya Pradesh, Email: ahussain591@gmail.com) : Ligand- and structure-based pharmacophore modeling, docking study reveals 2-[[4-[6-(isopropylamino) pyrimidin-4-yl]-1H-pyrrolo[2,3-b] pyridin-6-yl] amino] ethanol as a potential anticancer agent of CDK9/cyclin T1 kinase. J Cancer Res Ther 2019, 15(5), 1131-40.

CDK9/Cyclin T1 kinase is a protein kinase, indirectly involved in the cell cycle progression in the form of transcription elongation, CDK9 specific inhibitors may be a potential alternative treatment not only for cancer but also other life‑threatening diseases. Ligand‑based and structure‑based pharmacophore model was developed for discovering of the new anticancer agents. These models used as three‑dimensional query for virtual screening against the chemical structure databases such as Maybridge HitFinder, MDPI, and ZINC. Subsequently, the potential hit compound was filtered by the ADMET and docking score. After applying all filtration, 11 hits were found as potential hits based on good docking scores as well as good ADMET properties. Compound 2‑[[4‑[6‑(isopropylamino) pyrimidin‑4‑yl]‑1H‑pyrrolo[2,3‑b] pyridin‑6‑yl] amino] ethanol was found to be most potent among all the potential hits. These hits could be used as an anticancer agent in near future. So many advances in the treatment of death leading diseases have been made over the past few decades, However, looking for the development in this research ligand‑based and structure‑based pharmacophore modeling was done, hit1 2‑[[4‑[6‑(isopropylamino) pyrimidin‑4‑yl]‑1H‑pyrrolo[2,3 b] pyridin‑6 yl] amino] ethanol was found to be more potent and selective. It is understandable that these hits could be as selective and potent anticancer agents of cyclin‑dependent kinase complex.

9 illus, 5 tables, 44 ref

003770   DAVID T I, OKONKWO D C, ADELAKUN N S, OMOTUYI O I (Adekunle Ajasin Univ, Ondo State, Nigeria, Email: 130401064@aaua.edu.ng) : Automated QSAR and docking study of phyto-ligands of chromolaena odorata as inhibitor of bacteria beta-lactamase enzyme. J Biol Engg Res Rev 2019, 6(2), 32-42.

Bacteria resistance to antibacterial antibiotics is made possible by the production of beta-lactamase. Beta-lactamase enzyme confers resistance by breaking open the Beta-lactam structure of antibiotics, thereby deactivating their antibacterial properties. As a result of this, attention shifted into identifying potential lead inhibitor of beta-lactamase, with ability to reduce resistance encountered in bacteria antibiotics. The computational approach was employed in the generation of QSAR model using Automated QSAR, and in the docking of ligands from Chromolaena odorata with Betalactamase. The best model obtained was KPLS_Dendritic_43 (R² = 0.8564 and Q²=0.7819), and was used in predicting the bioactivity of the lead compounds. Docking study revealed that the ligands bind with a higher binding score than co-crystallized ligand and other standard drug employed in this study. Tianshic acid and chromomorate recorded binding energy of -9.305 and -7.989 respectively. The drug-like properties of the ligands were evaluated using the Lipinski rule of Five, which revealed that C. odorata ligands do not only inhibit the activity of beta-lactamase, but the ligands are also druglike. Therefore, further studies are needed to adequately justify the mechanism of action of these ligands as a beta-lactamase inhibitor.

4 illus, 5 tables, 54 ref

003771   DAVID T I, OMOTUYI O I, AGBOOLA O D, OKONKWO D C, ADELAKUN N S (Adekunle Ajasin Univ, Ondo State, Nigeria, Email: 130401064@aaua.edu.ng) : Identification of Gly/NMDA receptor antagonist from Chromolaena odorata’s derived compounds using induced fit docking and ADME study. J Biol Engg Res Rev 2019, 6(2), 19-26.

The ionotropic activation of N-methyl-D-aspartic acid (NMDA) plays a significant role in different type of neurodegenerative disease, as it is a tetramer with two Glycine binding subunit and two glutamate subunits. NMDA receptor can be inhibited by either blocking of the glycine site or glutamate site. Previously reported inhibitors of NMDA receptor focus on the inhibition of the glutamate subunit, which was reported to be associated with side effects such as ataxia, memory deficits, and neurotoxicity. Therefore, different compounds with antagonistic effect are been explored on Gly/NMDA site. Glide XP docking was employed in screening phytoconstituent of Chromolaena odorata against Gly/NMDA receptor for hit compounds with antagonistic properties. The hit compounds were further subjected to Induced fit docking (IFD) and Lipinski rule of five. The final selection was based on Rigid XP docking score using co-crystallized ligand as threshold docking score, interaction with receptor site residues, and IFD score. Ferulic acid, caffeic acid and scutellarein recorded binding affinity of -8.752 Kcal/mol, 10.004 Kcal/mol and -9.096 Kcal/mol respectively, which is higher than the binding affinity of co-crystallized ligand. Induced fit score obtained were -614.38, -614.03 and -616.31 for ferulic acid, caffeic acid and scutellarein respectively. The result obtained in this study shows the potency of phytochemical from C. odorata to inhibit NMDA receptor. ADME study showed that the drug-like nature of these compounds.

2 illus, 1 table, 44 ref

003783   PADHY S K, TAKKAR B, CHAWLA R, KUMAR A (All India Institute of Medical Sciences, Ansari Nagar, New Delhi - 110 029, Email: atul56kumar@yahoo.com) : Artificial intelligence in diabetic retinopathy: A natural step to the future. Indian J Ophthalmol 2019, 67(7), 1004-9.

Use of artificial intelligence in medicine in an evolving technology which holds promise for mass screening and perhaps may even help in establishing an accurate diagnosis. The ability of complex computing is to perform pattern recognition by creating complex relationships based on input data and then comparing it with performance standards is a big step. Diabetic retinopathy is an ever‑increasing problem. Early screening and timely treatment of the same can reduce the burden of sight threatening retinopathy. Any tool which can aid in quick screening of this disorder and minimize requirement of trained human resource for the same would probably be a boon for patients and ophthalmologists. In this review we discuss the current status of use of artificial intelligence in diabetic retinopathy and few other common retinal disorders.

1 table, 46 ref

003785   PANDEY S K, SHARMA V (SuVi Eye Institute and Lasik Laser Center, Kota, Rajasthan, Email: suresh.pandey@gmail.com) : Robotics and ophthalmology: Are we there yet?. Indian J Ophthalmol 2019, 67(7), 988-94.

Ophthalmology is a field that is now seeing the integration of robotics in its surgical procedures and interventions. Assistance facilitated by robots offers substantial improvements in terms of movement control, tremor cancellation, enhanced visualization, and distance sensing. Robotic technology has only recently been integrated into ophthalmology; hence, the progression is only in its initial stages. Robotic technologies such as da Vinci Surgical System are integrated into the field of ophthalmology and are assisting surgeons in complex eye surgeries. Ophthalmic surgeries require high accuracy and precision to execute tissue manipulation, and some complex ocular surgery may take few hours to complete the procedures that may predispose high‑volume ophthalmic surgeons to work‑related musculoskeletal disorders. A complete paradigm shift has been achieved in this particular field through the integration of advanced robotic technology, resulting in easier and more efficient procedures. Where robotic technology assists the surgeons and improves the overall quality of care, it also projects several challenges including limited availability, training, and the high cost of the robotic system. Although considerable studies and trials have been conducted for various robotic systems, only a few of them have made it to the commercial stage and ophthalmology, on its own, has a long way to go in robotics technology.

3 illus, 2 tables, 31 ref

002514   PATHAK U, SHRIVASTAVA A K, NAIK R K (Farm Machinery and Power Engineering Dep, JNKVV, Jabalpur, Madhya Pradesh) : Computer programme for selecting farm machinery for tomato crop in central region of Madhya Pradesh. Pharma Innov 2019, 8(6), 35-40.

As a major sector, agriculture continues to be the life line for millions of farmers in Madhya Pradesh, India. A computer programme has been developed in order to aid decision making in tractor and implement selection for the small farm in Central region. The application of decision support system was demonstrated in the paper to select tractor power. The selection of tractor power in the study area. Through model a linear relationship was found between the optimum PTO power of tractor selected and the farm size. The unit power requirement followed an inverse relationship with the farm size. Initially it decreased rapidly from 1 to 5 ha of farm size and thereafter it tended to be asymptotic with the farm size. The programme able to handle a wide range of tractor and working condition because of its datafiles structure.

6 illus, 1 table, 5 ref

002519   ZUO Y-Q, YI Z-S, XU J, RUI Y-F, WEI Y-C, LIU H-Y (Guilin Univ of Technology, Guangxi Guilin- 541 004, China, Email: yzs@glut.edu.cn) : Molecular simulation and spectroscopic studies on the interaction between perfluorohexadecanoic acid and human serum albumin. Indian J Biochem Biophys 2019, 56(3), 185-92.

In the present study, the interaction between Perfluorohexadecanoic acid (PFHxDA) and human serum albumin (HAS) was studied by fluorescence spectroscopy, molecular docking, dynamic simulation and circular dichroism (CD). The interaction character and the effect on human serum albumin conformation were measured by simulating the physiological condition (pH= 7.4). Experiments and simulation results revealed that PFHxDA molecules and HSA have regular fluorescence quenching, and the quenching mechanism is static quenching and non-radiative energy transfer. Thermodynamic analysis revealed the binding behavior was mainly governed by hydrophobic forces. Specific binding site experiments showed that the binding site of PFHxDA was a site I of HSA. The results from the CD spectrum demonstrated that PFHxDA changed the molecular conformation of HSA, which is consistent with the results obtained by molecular docking and dynamic simulation.

5 illus, 4 tables, 30 ref

002517   SARANYADEVI S, MURUGESWARI R, BATHRINATH S (Computer Science and Engineering Dep, Kalasalingam Academy of Research and Education, Krishnankoil - 626 126, Email: saranyadevism@gmail.com) : Road risk assessment using fuzzy context-free grammar based association rule miner. Sadhana 2019, 44(6), 151.

Road traffic accidents are a major social concern as well as a crucial issue for the public in recent days due to the risk factors involved. Analysing and identifying the major risk factors of road accident is still a challenging task. In this paper, a fuzzy Context-free Grammar (FCFG)-based association rule mining (ARM) technique is proposed to categorize a heterogeneous road accident dataset into two categories based on the critical factors such as total number of accidents (TA), persons killed (PK) and persons injured (PI). The role of the fuzzy grammar in this paper is to govern the entire algorithm using the prescribed grammar rules to proceed further. The considered road accident dataset does not have class labels; hence there is a need to assign class labels for the available data instance. The accident data with assigned class labels are given as input to K-nearest neighbour (KNN) machine learning algorithm in order to train the classifier for testing purpose. Further, the collected test data from the user are utilized by the KNN classifier for carrying out the performance analysis of the proposed algorithm. The case study is conducted on the National Highway roads, India, to examine the proposed approach. The experimentations are executed for road accident records using MATLAB software and the analysis is made using the following performance measures: accuracy, recall or sensitivity, precision or specificity and F1 score. A comparative study is accomplished with existing algorithms in order to show that the proposed algorithm works with improved accuracy of more than 83 %. The results suggested that the road users are responsible for the acceptance or rejection of safe or un-safe roads, respectively.

6 illus, 5 tables, 27 ref

002513   NARANG S, JINDAL M K, KUMAR M (Computational Sciences Dep, Maharaja Ranjit Singh Punjab Technical Univ, Bathinda, Punjab, Email: munishcse@gmail.com) : Devanagari ancient documents recognition using statistical feature extraction techniques. Sadhana 2019, 44(6), 141.

Devanagari ancient document recognition process is drawing a lot of consideration from researchers nowadays. These ancient documents contain a wealth of knowledge. However, these documents are not available to all because of their fragile condition. A Devanagari ancient manuscript recognition system is designed for digital archiving. This system includes image binarization, character segmentation and recognition phases. It incorporates automatic recognition of scanned and segmented characters. Segmented characters may include basic characters (vowels and consonants), modifiers (matras) and various compound characters (characters formed by joining more than one basic characters). In this paper, handwritten Devanagari ancient manuscripts recognition system has been presented using statistical features extraction techniques. In feature extraction phase, intersection points, open endpoints, centroid, horizontal peak extent and vertical peak extent features are extracted. For classification, Convolutional Neural Network, Neural Network, Multilayer Perceptron, RBF-SVM and random forest techniques are considered in this work. Various feature extraction and classification techniques are considered and compared to the recognition of basic characters segmented from Devanagari ancient manuscripts. A data set, of 6152 pre-segmented samples of Devanagari ancient documents, is considered for experimental work. Authors have achieved 88.95 % recognition accuracy using a combination of all features and a combination of all classifiers considered in this work by a simple majority voting scheme.

5 illus, 4 tables, 24 ref

002516   SAHANA S C, DAS M L, BHUYAN B (Information Technology Dep, North Eastern Hill Univ, Shillong - 793022, Email: subhas.sahana@gmail.com) : A provable secure key-escrow-free identity-based signature scheme without using secure channel at the phase of private key issuance. Sadhana 2019, 44(6), 132.

The identity-based cryptosystems furnish us with simplest key management procedures. Yet, they have a very slow adoption in cryptography due to the key escrow problem and the necessity of a secure channel between the user and the Private Key Generator (PKG) to transmit the created private key to the user. In this paper, we propose an identity-based signature scheme that not only solves the key escrow problem but also eliminates the requirement of the secure channel. The proposed scheme is secure against existential forgery under adaptively chosen message and ID attacks in the random oracle model assuming the hardness of the Computational Diffie–Hellmann Problem (CDHP). Furthermore, we compare the efficiency of our scheme to that of a similar established scheme.

3 illus, 3 tables, 26 ref

002518   SHANTHAKUMARI R, MALLIGA S (Information Technology Dep, Kongu Engineering Coll, Erode - 638 060, Email: shanabiraki@gmail.com) : Dual-layer security of image steganography based on IDEA and LSBG algorithm in the cloud environment. Sadhana 2019, 44(5), 119.

The architecture development of cloud computing technology is growing tremendously in recent times, which leads to improvement of scalability, accessibility and cost reduction measures in the IT sectors of all enterprises. In this service, the data storage without reviewing security policies and procedures is a challenging task and probabilities of extracting secret information by an unauthorized intervention are more. However, to prevent the breaches of security in the cloud service, the steganography art plays an essential role in the data communication medium to improve the security measures, and it is an indispensable technique for hiding the secret information into a cover object. This paper describes the implementation of new steganography method with International Data Encryption Standard Algorithm (IDEA) and Least Significant Bit Grouping (LSBG) algorithm for embedding the secret information into an original image and extracting the same. The result shows the improvement of data embedding capacity and reduces the issues related to data security by effective utilization of this new approach, which reveals the remarkable achievement of the combinational execution of steganography and cryptography technique. The IDEA and LSBG have some vital qualities such as data confidentiality, integrity verification, capacity and robustness, which are crucial factors to achieve successful implementation of steganography process in data security system. The effectiveness and properties of the stego image can be evaluated by some specific measures like mean squared error, root mean squared error, peak signal to noise ratio and structural similarity index matrix to analyse the image quality. The results show that the proposed technique outperforms the existing methodologies and resolves the data security problem in data transmission and storage system of cloud computing services.

5 illus, 2 tables, 28 ref

001267   NAGPAL A, PALIWAL S (Pharmacy Dep, Banasthali Vidyapith, Banasthali - 304 022, Email: ashima_nagpal@yahoo.com) : Design of novel JNK1 inhibitors using molecular modeling technique: An in silico approach. Indian J Chem Sec B 2019, 58B(03), 403-15.

To address the issue of unavailability of selective JNK1 inhibitors resulting in off-target effects, leading to multiple diseases, an endeavour to discover novel and specific JNK1 inhibitors is taken up in the present study. To achieve this goal, computer-aided drug design approach has been used and a validated 2D QSAR model, of excellent statistical quality, has been developed through MLR (Multiple Linear Regression) and PLS (Partial Lest Square) method. The r² value obtained through PLS method (0.97) corroborated the r² value that has been obtained through MLR approach (0.97). The insights obtained through in-depth study of the developed model has capacitated us to design optimized molecules (compound A1OOP and compound A2SSR) with better selectivity profile than the most active compound of the selected set of compounds that have been employed to build the QSAR model. Additionally, molecular docking and structure based pharmacophore design have been performed to ensure that the affinity of the designed molecules towards JNK1 receptor and evaluation of their ADME properties have been done to ensure their lead likeness. Further, extremely small values for Tanimoto similarity index are obtained that clearly suggest that the designed molecules are novel.

9 illus, 6 tables, 33 ref

001269   ROHANE S H, MAKWANA A G (Chemistry Dep, K. B. Institute of Pharmaceutical Education and Research, Gandhinagar - 382 023, Email: sachinrohane29@gmail.com) : In silico study for the prediction of multiple pharmacological activities of novel hydrazone derivatives. Indian J Chem Sec B 2019, 58B(03), 387-402.

The present studies are aimed to predict multiple pharmacological activities of novel hydrazone derivatives. Molecular docking of compounds 1 to 51 have been performed in Small-Molecule Drug Discovery Suite of Schrödinger. Fifty one compounds have been targeted on seven enzymes viz. 2NSD and 2X22 involved in tuberculosis activity, 4COX and 3LN1 involved in inflammation, 4GCP and 4HL2 involved in bacterial infection and 4WMZ involved in fungal infection. The generated lower energy conformers of all ligands have been docked into generated grid of active site of enzymes by XP precision of docking inside Glide-v7.4. Molecular docking results suggest that the compounds 4, 5, 11, 18, 30, 34, 35, 37, 38, 42, 43, 44, 45, 46 and 47 have good docking score and are predicted to interact with all enzymes. In all fifteen novel hydrazone derivatives have been predicted for multiple pharmacological activities.

14 illus, 3 tables, 13 ref

001271   SHARAVANAN V J, SIVARAMAKRISHNAN M, KOTHANDAN R, MUTHUSAMY S, KANDASWAMY K (Biotechnology Dep, Kumaraguru Coll of Technology, Coimbatore, Tamil Nadu, Email: kumaravel.k.bt@kct.ac.in) : Molecular docking studies of phytochemicals from Leucas aspera targeting Escherichia coli and Bacillus subtilis subcellular proteins. Pharmacogn J 2019, 11(2), 278-85.

Bacterial subcellular proteins play a vital role in cell division, pilus assembly and virulence. In addition, such proteins were perceived as potential antimicrobial targets. Therefore, in this article we attempt to screen for potential phytochemicals that can target those subcellular proteins. A computational screening for phytochemicals from Leucas aspera with better bioavailability followed by molecular docking studies for better understanding of interaction between phytochemical and target proteins. erythro-2-(4-allyl-2,6- dimethoxyphenoxy)-1-(4-hydroxy-3-methoxyphenyl) propan-1-ol and Leucasperone B from Leucas aspera possess great binding affinity (> -100 kcal/mol) towards one or more bacterial subcellular protein targets and possess bioavailability. Based on the docking result we claim that erythro-2-(4-allyl-2,6-dimethoxyphenoxy)-1-(4-hydroxy-3-methoxyphenyl) propan-1-ol and Leucasperone B could serve as an effective antimicrobial compounds to treat bacterial infections.

6 illus, 4 tables, 61 ref

001259   GANDHI S A, BAROT V M, PATEL M C, MALEK T J, PATEL U H (J. M. Shah Commerce Coll, Dakor - 388 225, Email: sahajg7@gmail.com) : Molecular docking, pharmacophore modelling and 3D QSAR analysis of novel chalcone derivatives. Int J Pharm Sci Res 2019, 10(4), 1725-33.

Chalcone based structures have many interesting biological properties like anti-malarial, anticancer, antiviral, antibacterial, antifungal, anti-hyperglycaemic and photo-cytotoxicity activities. In this study, the novel chalcone derivatives (1a-1l) have been synthesized and investigated for antimicrobial activities. The MIC results of antimicrobial activities reveal that one of the chalcone derivative (2-Br- and 4- OCH₃- group) against specific bacteria are quite significant. 3D QSAR, three dimensional quantitative structure activity is one of the most powerful technique which involves the quantitative relationship between the biological activity of a set of compounds and their three dimensional structural properties, using statistical correlation methods. Pharmacophore modelling and molecular docking play an important role in drug design. To elucidate the relationship between structures and its activity, field-based 3D QSAR analysis has been carried out of novel chalcone derivatives. Structural properties such as electrostatic, hydrophobic, aromatic, and hydrogen-bond donor and acceptor have been worked out for novel chalcone derivatives. To investigate the influence of drugstore, chalcone derivatives (1a-1l) have docked with receptor 2IOK and results displayed the highest Gscore of ligand 1f (3-OCH₂C₆H₅-4-OCH₃- group).

7 illus, 4 tables, 18 ref

001255   BHUVAD M A, SAMANT L R (B. J. Wadia Hospital for Children, Mumbai - 400 012, Email: samantlalit@gmail.com) : In-silico docking analysis of phytochemicals from Verbascum phlomoides L. as an antiviral agents against herpes simplex virus type I and type II. Int J Pharm Sci Res 2019, 10(3), 1241-5.

Almost 85 % of the world population is infected with the Herpes Simplex Virus (HSV). Herpes simplex virus infections have been described in the medical literature for centuries, yet the drugs available nowadays for therapy are largely ineffective and low oral bioavailability plays an important role on the inefficacy of the treatments. Additionally, the details of the inhibition of Herpes virus type 1 are still not fully understood. The present study was undertaken to evaluate the antiviral property of selected phytochemicals from Verbascum phlomoides L. through their interaction with the Herpes simplex virus. Depending on the non-covalent interaction and best docking score it was concluded that these phytochemicals may be useful for treatment against Herpes infection and can act as inhibitors to Herpesviral protein receptor. Also using phytochemicals as a medium of medication may reduce the cost dependent factor and can be widely used as medicinal purposes to treat several chronic and dreadful diseases.

2 tables, 17 ref

001257   DHAKE N, RAUT S, RAHANGDALE A (Computer Science and Engineering Dep, Visvesvaraya National Institute of Technology, Nagpur - 440 010, Email: dhakenikhil511@gmail.com) : Identification of efficient algorithms for web search through implementation of learning-to-rank algorithms. Sadhana 2019, 44(4), 97.

Today, amount of information on the web such as number of publicly accessible web pages, hosts and web data is increasing rapidly and exhibiting an enormous growth at an exponential rate. Thus, information retrieval on web is becoming more difficult. Conventional methods of information retrieval are not very effective in ranking since they rank the results without automatically learning the model. Machine learning domain called learning-to-rank comes to the aid to rank the obtained results. Different state-of-the-art methodologies have been developed for learning-to-rank to date. This paper focuses on finding out the best algorithm for web search by implementation of different state-of-the-art algorithms for learning-to-rank. Our work in this paper marks the implementation of learning-to-rank algorithms and analyses effect of topmost performing algorithms on respective datasets. It presents an overall review on the approaches designed under learning-to-rank and their evaluation strategies.

3 illus, 7 tables, 39 ref

001253   AHMAD S W, BAMNOTE G R (Computer Science and Engineering Dep, Prof. Ram Meghe Institute of Technology and Research, Badnera, Amravati - 444 701, Email: sumeraahmad2003@gmail.com) : Whale–crow optimization (WCO)-based optimal regression model for software cost estimation. Sadhana 2019, 44(4), 94.

Software Cost Estimation (SCE) is the emerging concern of the software companies during the development phase of the software, as it requires effort and cost factors for modelling the software. These factors are modelled using the Artificial Intelligence models, which seem to be less accurate and non-reliable by increasing the risk factor of the software projects. Thus, for estimating the software cost, meta-heuristics are employed. This paper proposes an algorithm, termed as whale–crow optimization (WCO) algorithm, which is the integration of the whale optimization algorithm (WOA) and the crow search algorithm (CSA). The main function of the WCO algorithm is to determine the Optimal Regression coefficients for the regression models, such as the Linear Regression model and the Kernel Logistic Regression model, to develop an Optimal Regression model to estimate the software cost. The experimentation is carried out using four datasets taken from the Promise software engineering repository to perform effective performance analysis. Analysis is carried out regarding the mean magnitude of relative error (MMRE) that proves that the proposed method of SCE is effective, attaining the average MMRE at a rate of 0.2442 for the proposed Linear Regression model and 0.2692 for the proposed Kernel Regression model.

10 illus, 4 tables, 37 ref

001254   ASHOKKUMAR C, VENKATESH M B S, GIRI R P, ROY B, MENEZES B (Computer Science and Engineering Dep, Indian Institute of Technology Bombay, Mumbai, Maharashtra, Email: ashokkumar@cse.iitb.ac.in) : An error-tolerant approach for efficient AES key retrieval in the presence of cacheprefetching – experiments, results, analysis. Sadhana 2019, 44(4), 88.

The challenge in cache-based attacks on cryptographic algorithms is not merely to capture the cache footprints during their execution but to process the obtained information to deduce the secret key. Our principal contribution is to develop a theoretical framework based upon which our AES key retrieval algorithms are not only more efficient in terms of execution time but also require up to 75 % fewer blocks of ciphertext compared with previous work. Aggressive hardware prefetching greatly complicates access-driven attacks since they are unable to distinguish between a cache line fetched on demand versus one prefetched and not subsequently used during a run of a victim executing AES. We implement a multi-threaded spy code that reports accesses to the AES tables at the granularity level of a cache block. Since prefetching greatly increases side-channel noise, we develop sophisticated heuristics to ‘‘clean up’’ the input received from the spy threads. Our key retrieval algorithms process the sanitized input to recover the AES key using only about 25 blocks of ciphertext in the presence of prefetching and, stunningly, a mere 2–3 blocks with prefetching disabled. We also derive analytical models that capture the effect of varying false positive and false negative rates on the number of blocks of ciphertext required for key retrieval.

5 illus, 3 tables, 52 ref

001265   MAITY G, MARDANYA D, ROY S K, WEBER G-W (Applied Mathematics with Oceanology and Computer Programming Dep, Vidyasagar Univ, Midnapore - 721 102, Email: sankroy2006@gmail.com) : A new approach for solving dual-hesitant fuzzy transportation problem with restrictions. Sadhana 2019, 44(4), 75.

This paper addresses a study on the transportation problem based on dual-hesitant fuzzy environment. The dual-hesitant fuzzy set accommodates imprecise, uncertain or incomplete information and knowledge situations in real-life operational research problems that are not possible or difficult to tackle by existing fuzzy uncertainties. Here, we present the concept of uncertainty in a transportation problem using dual-hesitant fuzzy numbers. In most of the research works, fuzzy uncertainty has been considered in transportation parameters. However, we consider the dual-hesitant fuzzy numbers to formulate a mathematical model by considering the capacity of delivering the goods by a decision maker. A special emphasis of this paper is to derive an optimal solution of transportation problem with some restrictions under uncertainty by the traditional approach (cf. Vogel’s approximation method—VAM) without using any mathematical aids. In this regard, an algorithm is developed to find the optimal solution for the dual-hesitant fuzzy transportation problem including some restrictions. Thereafter, the proposed method is illustrated by giving a numerical example for showing the effectiveness. Finally, conclusions are given with the lines of future studies based on this paper.

12 tables, 33 ref

001270   SAXENA R, DEY S (Computer Science and Engineering Dep, Indian Institute of Technology Indore, Indore, Madhya Pradesh - 453 552, Email: rajat.saxena@iiti.ac.in) : Data integrity verification: A novel approach for cloud computing. Sadhana 2019, 44(3), 74.

Data integrity verification (DIV) is one of the primary security checks for data stored on cloud servers. Cloud users have assured the safety of their data with frequent checking of data integrity. In this paper, we provide an efficient and effective DIV approach that offers effective and privacy-preserving audit structure. The main building components of our approach are a multi-power variant of the Paillier cryptography system with homomorphic tag. The Paillier cryptography system along with homomorphic tag assigns a unique and verifiable value to each data block, which helps performing dynamic data operations in cloud environment. To demonstrate our approach, we have implemented an application on Hadoop and MapReduce framework. We have tested this application with respect to the different parameters. The efficiency of the proposed method has been shown through the experimental results. Our method has shown a good improvement over those of the other modern systems.

7 illus, 3 tables, 30 ref

001266   MALEKI S, MATIN R K (Mathematics Dep, Islamic Azad Univ, Karaj, Iran, Email: rkmatin@kiau.ac.ir) : A Russell-based model for estimating overall and divisional efficiency in two-stage production systems with sets of convex hulls in intermediate products. Sadhana 2019, 44(3), 69.

Data Envelopment Analysis (DEA) research works have been recently examining production systems with a two-stage network structure. These studies consider system operations that are performed in two stages where intermediate products play dual roles: they are the outputs of the previous stage and inputs to the next stage. This dual role is incompatible with Pareto–Koopmans dominance in activity analysis. Also, disregarding intermediate products in assessing performance of two-stage systems compromises the models. The present work introduces a new production possibility set for two-stage network production systems by considering a convex hull for intermediate products. In addition, new models are introduced for evaluating overall efficiency and divisional efficiency of production units from the Pareto–Koopmans efficiency perspective. The proposed models are developed based on an enhanced Russell graph model for efficiency evaluation of twostage network production structures with convex hulls for intermediate products. Numerical examples are further provided for illustration purposes.

4 illus, 5 tables, 43 ref

001262   KARPAGAM K, SARADHA S (Computer Applications Dep, Dr Mahalingam Coll of Engineering and Technology, Pollachi - 642 003, Email: karpagam80@gmail.com) : A framework for intelligent question answering system using semantic context-specific document clustering and Wordnet. Sadhana 2019, 44(3), 62.

The question answering system plays an important role in information retrieval field, where the user is in need of getting a precise answer instead of large collections of documents. The aim of this paper is to investigate techniques for improving sentence-based question answering system. To achieve this, a POS-Taggerbased question pattern analysis model is proposed to identify question type based on pattern template for the user-submitted query. Next, the knowledge base is created from a large corpus by clustering the documents by grouping on domain context. The proposed semantic-word-based answer generator model deals with the user query mapping with an appropriate sentence in the knowledge base. By the proposed models, the system reduces the search gap among user queries and answer sentences using Wordnet. It considers word order, overlap, sentence similarity, string distance, unambiguous words and semantic similarity of words. The proposed algorithm evaluates with benchmark datasets such as 20Newsgroup and TREC-9 QA, and proves its efficiency by statistical test for significance.

6 illus, 10 tables, 19 ref

001264   KUMAR A, MUSTIKOVILA K N, SINGH G K, LEE S, LEE H-N (PDPM Indian Institute of Information Technology, Jabalpur - 482 005, Email: anilkdee@gmail.com) : A new design method for FIR notch filter using fractional derivative and swarm intelligence. Sadhana 2019, 44(3), 61.

In this paper, a new design method for the finite impulse response (FIR) notch filters using fractional derivative (FD) and swarm intelligence technique is presented. The design problem is constructed as a minimization of the magnitude response error w.r.t. filter coefficients. To acquire high accuracy of notch filter, fractional derivative (FD) is evaluated, and the required solution is computed using the Lagrange multiplier method. The fidelity parameters like passband error, notch bandwidth, and maximum passband ripple vary nonlinearly with respect to FD values. Moreover, the tuning of appropriate FD value is computationally expensive. Therefore, modern heuristic methods, known as the constraint factor particle swarm optimization (CFI-PSO), which is inspired by swarm intelligence, is exploited to search the best values of FDs and number of FD required for the optimal solution. After an exhaustive analysis, it is affirmed that the use of two FDs results in 21 % reduction in passband error, while notch bandwidth is slightly increased by 2 % only. Also, it has been observed that, in the proposed methodology, at the most 66 iterations are required for convergence to optimum solution. To examine the performance of designed notch filter using the proposed method, it has been applied for removal of power line interference from an electrocardiography (ECG) signal, and the improvement in performance is affirmed.

8 illus, 4 tables, 32 ref

001258   EYDI A, NASIRI R (Kurdistan Univ, Sanandaj, Iran, Email: Alireza.eydi@uok.ac.ir) : A P-hub median network design problem with preventive reliability approach for before and after hub failure. Sadhana 2019, 44(3), 57.

Hubs are vital elements of communication and transportation networks and play an important role in interchanging the flows of information/passenger/goods. For this purpose, designing a highly reliable hub network is very critical, because inefficiency of even a single hub across the network tends to reduce the efficiency of the whole network in transferring the flow appropriately. In this research, a bi-objective mathematical model was designed to study the situations before and after hub failure. Considering reliability, the first objective was to maximize the flow through the network, and the second objective was to prevent wasting the flow due to a possible hub failure. The lexicographic method was used to solve this multi-objective problem with dependent objectives. This method represents an appropriate solution for problems whose objective functions are of different priorities or depend on one another. Various cases of different sizes were used to evaluate the model in terms of reliability. Since the hub location problem is an NP-Hard problem of commonly large dimensions, a hybrid meta-heuristic algorithm called ‘‘memetic algorithm’’ was used to have it solved. The algorithm was a combination of genetic algorithm with simulated annealing algorithm, where simulated annealing algorithm was used for local neighborhood search. Findings indicated that, consideration of the backup hub tends to enhance route reliability, thereby increasing the flow through the network, as compared to the case with no backup hub.

7 illus, 15 tables, 41 ref

001268   PRADEEP A, SHARMA A K (Indira Gandhi Centre for Atomic Research, Kalpakkam - 603 102, Email: arjun@igcar.gov.in) : Numerical investigation of single bubble dynamics in liquid sodium pool. Sadhana 2019, 44(3), 56.

The single gas bubble rise dynamics in liquid sodium/sodium-potassium alloy (NaK) pool due to entrainment of argon cover gas/non-condensable fission gas (xenon) have received considerable attention in the safe operation of Sodium-cooled Fast Reactor (SFR). Numerical simulation of single bubble dynamics in liquid sodium/NaK pool is an essential intermediate step for the evaluation of rise velocity and shape changes, which are of utmost importance in areas of reactor safety concerned with source term evaluation and cover gas purification. The interFoam solver of OpenFOAM package is used to evaluate inert gas bubble rise dynamics in stagnant liquid metal pool of sodium and NaK. The governing equations are discretized and solved using the Volume of Fluid (VOF) based solver available in OpenFOAM with appropriate initial and boundary conditions. The VOF module of the solver is validated against numerical benchmark data and experimental results available in literature. The bubble dynamics in liquid sodium/NaK pool are studied in terms of trajectory, shape and rise velocity for diameters ranging from 10 to 20 mm, domain aspect ratios and for different gas-liquid systems. The study shows that the bubble rise velocity increases with diameter for liquid sodium systems. The rise behavior of single inert gas bubble in liquid water and sodium pool are compared. The study supports the use of air-water system as a simulant for studying bubble dynamics in liquid sodium systems as suggested by other researchers. The study is very useful and forms an intermediate step towards the development of an OpenFOAM based computational framework to analyze heat and mass transfer from single bubble rising in liquid sodium pool for reactor safety studies.

23 illus, 9 tables, 30 ref

001256   BISWAS M, KUPPILI V, EDLA D R (Computer Science and Engineering Dep, National Institute of Technology Goa, Ponda - 403 401, Email: mainakmani@gmail.com) : ALDL: A novel method for label distribution learning. Sadhana 2019, 44(3), 53.

Data complexity has increased manifold in the age of data-driven societies. The data has become huge and inherently complex. The single-label classification algorithms that were discrete in their operation are losing prominence since the nature of data is not monolithic anymore. There are now cases in machine learning where data may belong to more than one class or multiple classes. This nature of data has created the need for new algorithms or methods that are multi-label in nature. Label distribution learning (LDL) is a new way to view multi-labelled algorithms. It tries to quantify the degree to which a label defines an instance. Therefore, for every instance there is a label distribution. In this paper, we introduce a new learning method, namely, angular label distribution learning (ALDL). It is based on the angular distribution function, which is derived from the computation of the length of the arc connecting two points in a circle. Comparative performance evaluation in terms of mean-square error (MSE) of the proposed ALDL has been made with algorithm adaptation of k-NN (AA-kNN), multilayer perceptron, Levenberg–Marquardt neural network and layer-recurrent neural network LDL datasets. MSE is observed to decrease for the proposed ALDL. ALDL is also highly statistically significant for the real world datasets when compared with the standard algorithms for LDL.

5 illus, 18 tables, 28 ref

001260   HATAI B, BANERJEE S K (Techno India Univ, Kolkata, West Bengal) : Molecular docking interaction between superoxide dismutase (receptor) and phytochemicals (ligand) from Heliotropium indicum Linn for detection of potential phytoconstituents: New drug design for releasing oxidative stress condition/inflammation of osteoarthritis patients. J Pharmacogn Phytochem 2019, 8(2), 1700-6.

Antioxidant properties of medicinal plants play a very important role in different inflammatory, pain and oxidative stress related diseases. Osteoarthritis is most common musculoskeletal joint disease among middle aged and older people. The present study was attempted to detect potential Phyto-constituents in Heliotropium indicum against inflammation and pain. Superoxide dismutase (SOD) is an anti-oxidative enzyme and it was increased due to free radical generation or oxidative stress condition. This present study was focused at assessing the target level analysis of antioxidant activity of these (Lupeol and β amyrin) Phyto-constituents through molecular docking studies. The interaction between SOD and phytochemicals from H. indicum was carried out by using PyRx software to compare energy value and binding site of phytochemicals in reference to established synthetic non-steroidal anti-inflammatory drugs (NSAIDs). This result show that both phytoconstituents (lupeol and β amyrin) possessed potent capacity and is capable of activating SOD and showed better affinity towards SOD. Based on molecular docking we found few phytochemicals of H. indicum that can be used as lead compounds in future drug development as anti-inflammatory agent at low cost. It is also suggested to carry out functional assay of predicted compounds to validate suitability of this lead.

3 illus, 2 tables, 45 ref

001273   WANG Y, WANG S, DENG Y (Electronic Science and Technology of China Univ, Chengdu, China, Email: dengentropy@uestc.edu.cn) : A modified efficiency centrality to identify influential nodes in weighted networks. Pramana – J Phys 2019, 92(4), 68.

It is still a crucial issue to identify influential nodes effectively in the study of complex networks. As for the existing efficiency centrality (EffC), it cannot be applied to a weighted network. In this paper, a modified efficiency centrality (EffC^m) is proposed by extending EffC into weighted networks. The proposed measure trades off the node degree and global structure in a weighted network. The influence of both the sum of the average degree of nodes in the whole network and the average distance of the network is taken into account. Numerical examples are used to illustrate the efficiency of the proposed method.

10 illus, 3 tables, 60 ref

001261   JU Z, MA J, XIE J, WANG Y, CUI H, DUAN C (Hebei Univ of Science and Technology, Shijiazhuang 050018, China, Email: mzjinlong@163.com) : Cascading failure model for the mitigating edge failure of scale-free networks. Pramana – J Phys 2019, 92(4), 62.

By studying the classical betweenness and the universal degree methods, we put forward a new model to control the spread of cascading failure on scale-free networks. The new model is based on defining the load of an edge with respect to the betweenness centrality of the two connected nodes. The iterative process of a cascading failure on scale-free networks is analysed by removing one edge. We find that the proposed new model can control the spread of cascading failure more significantly. To make our conclusions more convincing, we have explored the performance of new models in real network by the power grid of the western United States. We further give the following reasonable explanations: First, the reason why the new model shows a more stable performance than the others has been explained. Secondly, we have explored the reason why the new model shows different advantages depending on the load for different networks and lastly, we have studied the exact difference between these two methods and the network structure. This paper might be useful for preventing and mitigating the cascading failure in real life.

10 illus, 54 ref

001263   KHANAL P, MANDAR B K, MAGADUM P, PATIL B M, HULLATTI K K (Pharmacology and Toxicology Dep, KLE Coll of Pharmacy, Belagavi - 590 010, Email: pukarkhanal58@gmail.com) : In silico docking study of limonoids from Azadirachta indica with pfpk5: A novel target for Plasmodium falciparum. Indian J Pharm Sci 2019, 81(2), 326-32.

The present investigation dealt with determination of the binding affinities in silico of six limonoids from Neem, 7-deacetoxy-7-oxogedunin, 17-hydroxyazadiradione, nimolicinol, 6-acetynimbadiol, andirobin and gedunin to bind the protein kinase, pfpk5 from Plasmodium falciparum, compared to staurosporine, a wellknown protein kinase inhibitor. Further, the molecules’ pharmacokinetics and toxicity was also evaluated. Among the six compounds, 7-deacetoxy-7-oxogedunin and nimolicinol showed the best binding affinity for pfpk5 via interactions of hydrogen and pi bond and were also predicted to be potent molecules. The current in silico study suggested that limonoids could be potential pfpk5 inhibitors, which could further be developed as antimalarial drugs. Going forward the in vitro and in vivo studies are needed to confirm the efficacy of limonoids as pfpk5 inhibitors.

2 illus, 5 tables, 19 ref

000033   SUBBURAYALU S, GOLDA P B, ASHA K R T, PALAVESAM A (Animal Science Dep, Manonmanium Sundaranar Univ, Tirunelveli, Tamil Nadu, Email: krplacement97@yahoo.in) : Molecular docking studies of Indigofera tirunelvelica Sanjappa against Hepatocarcinomo receptors. Int J Pharm Biol Sci 2019, 9(1), 94-102.

Hepatocarcinomo keeps on being an overall executioner, in spite of the huge measure of research and quick advancements seen amid the previous decade. Since it is normally trusted that many are preventable, there is dire need to recognize regular meds as viable hepatoprotective specialists. Normal items recognized and disengaged from plants have assumed an imperative job in disclosure of medications against liver infections. In silico docking systems are being utilized to explore the correlatively at the sub-atomic dimension of a ligand and a protein target. In the present investigation, four ligands which have been disengaged and distinguished from the ethanolic concentrate of the entire plant of Indigofera tirunelvelica Sanjappa are docked with two novel hepatocacrcinomo receptors, Hepatitis B X and Heme Oxygenase I. Out of the four phytochemical constituents separated and distinguished from the ethanolic concentrate of the entire plant of Indigofera tirunelvelica, phytol ligand uncovered the best wellness score contrasted and the other three ligands. This present examination induced that phytol could be a viable potential inhibitor against Hepatitis B X and Heme Oxygenase I receptor and could be assessed as hepatoprotective medication particle.

3 illus, 3 tables, 14 ref

000023   MISHRA G J, PRAJAPATI C, PATEL M, REDDY M N (Biosciences Dep, Veer Narmad South Gujarat Univ, Surat - 395 007, Email: gaurav.j.mishra@gmail.com) : Comparative molecular docking analysis of flavonoid component from Launaea procumbens (Roxb.) against tyrosine-protein kinase Fyn. Int J Pharm Sci Res 2019, 10(2), 537-45.

Plants have been studied since ages for their therapeutic uses. In the earlier time, not much was known about the phytocompounds, but today the constituents of the different plants have been extracted and isolated for the use in the name of medicines or drugs. Flavonoid is one of the most characteristic classes’ of compounds in higher plants known to play several important roles including therapeutic uses in cancer treatment. The activation of oncogenes in the cancer cells can be regulated by the selective tyrosine kinases inhibitors, and therefore it can be considered as a promising approach for the targeted therapeutic development. Hence, in the present study, the authors tried to combine the knowledge of using plant Launaea procumbens in traditional medicine by analyzing and identifying the specific phytocompounds, especially flavonoids, and evaluating its anticancer potential. The scope of the present study is based on the aim to determine the possible use of plant Launaea procumbens in the field of therapeutics for cancer studies by performing in-silico docking analysis of isolated flavonoid compound on Tyrosine-protein kinase Fyn in comparison to Methotrexate, Imatinib, Clofarabine, and Daunorubicin. Based on the molecular drugs docking and binding affinities of the target proteins with an isolated flavonoid constituent from the plant, and its physicochemical detailing, it was found that the isolated flavonoid constituent has high possibilities to be an anticancer drug if utilized further with systematic approaches.

5 illus, 5 tables, 47 ref

000006   ANBARASU K, MAHENDRAN R, KUMAR R M S (Bioinformatics Dep, VISTAS, Chennai - 600 117, Email: anbarasuk.sls@velsuniv.ac.in) : Computational insights on antiviral resistance mechanism of HIV-1 protease with GS-8374. Int J Pharm Sci Res 2019, 10(1), 363-66.

Human immunodeficiency virus type 1 (HIV-1), is an etiologic agent of the most life-threatening disease AIDS. HIV-1 protease (HIVP) is a key enzyme that performs an essential step in the life cycle of the virus. HIV-1 protease assembled as a dimer in the functional form and involved in cutting “polyprotein" into the proper protein-sized pieces. The two chains assemble to form a long tunnel covered by two flexible protein forms a "flaps." The flaps open up, and the enzyme wraps around a protein chain, closing and holding it tightly in the tunnel. Highly active antiretroviral therapy (HAART) is the current successful treatment approach for AIDS and protease inhibitors plays a crucial role in HAART. The drugs that target against protease consider as one of the major approaches in modern medicine. Till date, 26 anti-HIV compounds have been approved by the Food and Drug Administration (FDA), and 10 are HIV protease inhibitors. The antiviral resistance occurs due to a point mutation in the viral protein which has been a big hurdle in the treatment of AIDS. To decipher the resistance mechanism of HIV-1 protease against current drug GS-8374, the computational studies have been carried out. The molecular docking analysis of protease mutants confirms the loss of crucial H-bonds with the drug that in-turn leads to antiviral resistance. In a nutshell, our studies can provide crucial structural insights on the resistance mechanism of HIV-1 protease against GS-8374.

6 illus, 1 table, 20 ref

000024   NWOBI-OKOYE C C (Anambra State Univ (Chukwuemeka Odumegwu Ojukwu Univ), Uli, Nigeria, Email: chidozien@yahoo.com) : Notes on procedure for the development of fuzzy rules in SCOP methodology. Sadhana 2019, 44(2), 52.

The lack of statistical foundations among other shortcomings of existing methods of measuring efficiency necessitated the development of a new method called, Systems Coefficient of Performance Methodology (SCOPM). One key feature of SCOP methodology is the use of fuzzy logic to express complex efficiency measurement parameters into linguistic variables understandable by non experts and the general public. In this research note, the procedure for development of membership functions for the fuzzy logic aspect of SCOPM modeling was standardized and presented. A thorough analysis of fuzzy logic modeling which is at the heart of SCOPM was done. Real life examples and case studies are used to highlight the practical applications and utility of the methodology. The study gives a deep insight into the strengths of SCOP as an efficiency measurement method and its superiority over other efficiency measurement methods like, Data Envelopment Analysis (DEA), Stochastic Frontier Analysis (SFA), etc. Finally, a guide to practitioners on implementation of SCOPM as well as future research direction for academics and researchers is presented.

15 illus, 14 tables, 29 ref

000007   APARNA K (Computer Applications Dep, BMS Institute of Technology and Management, Bengaluru, Karnataka, Email: aparnak@bmsit.in) : Evolutionary computing based hybrid bisecting clustering algorithm for multidimensional data. Sadhana 2019, 44(2), 45.

The emerging technologies and data centric applications have been becoming an integral part of business intelligence, decision process and numerous daily activities. To enable efficient pattern classification and data analysis, clustering has emerged as a potential mechanism that classifies data elements based on respective feature homogeneity. Although K-Means clustering has exhibited appreciable performance for data clustering, it suffers to enable optimal classification with high dimensional data sets. Numerous optimization efforts including genetic algorithm (GA) based clustering also require further optimization to avoid local minima issues. In this paper, an improved Canonical GA based Bisecting K-Means algorithm (CGABC) has been developed. The proposed model incorporates min-max normalization based feature normalization of the high dimensional data sets, which is followed by T-Test analysis that significantly reduces data dimensions based on feature similarity of the data elements. The fitness value has been assigned based on inter-cluster (heterogeneous distance) and within-cluster (homogeneous distance) distances. To enable optimal features and process parameter selection, particularly cluster centers information, the conventional GA has been modified by applying multistage reproduction process, enhanced crossover and mutation. By incorporating the optimized cluster center information the Bisecting K-Means clustering has been performed, which has exhibited optimal solution for highly accurate and efficient clustering with high dimensional data sets.

6 illus, 3 tables, 30 ref

000020   MADANKUMAR S, RAJENDRAN C (Management Studies Dep, Indian Institute of Technology, Chennai - 600 036, Email: craj@iitm.ac.in) : A mixed integer linear programming model for the vehicle routing problem with simultaneous delivery and pickup by heterogeneous vehicles, and constrained by time windows. Sadhana 2019, 44(2), 39.

In this work, we consider the Vehicle Routing Problem with Simultaneous Delivery and Pickup, and constrained by time windows, to improve the performance and responsiveness of the supply chain by transporting goods from one location to another location in an efficient manner. In this class of problem, each customer demands a quantity to be delivered as a part of the forward supply service and another quantity to be picked up as a part of the reverse recycling service, and the complete service has to be done simultaneously in a single visit of a vehicle, and the objective is to minimize the total cost, which includes the traveling cost and dispatching cost for operating vehicles. We propose a Mixed Integer Linear Programming (MILP) model for solving this class of problem. In order to evaluate the performance of the proposed MILP model, a comparison study is made between the proposed MILP model and an existing MILP model available in the literature, with the consideration of heterogeneous vehicles. Our study indicates that the proposed MILP model gives tighter lower bound and also performs better in terms of the execution time to solve each of the randomly generated problem instances, in comparison with the existing MILP model. In addition, we also compare the proposed MILP model (assuming homogeneous vehicles) with the existing MILP model that also considers homogeneous vehicles. The results of the computational evaluation indicate that the proposed MILP model gives much tighter lower bound, and it is competitive to the existing MILP model in terms of the execution time to solve each of the randomly generated problem instances.

1 illus, 9 tables, 14 ref

000009   BORISANIYA B, PATEL D (Computer Engineering Dep, Sardar Vallabhbhai National Institute of Technology, Surat- 395 007, Email: borisaniyabhavesh@gmail.com) : Towards virtual machine introspection based security framework for cloud. Sadhana 2019, 44(2), 34.

Virtualization enables provision of resources to users according to their requirement through Infrastructure as a Service (IaaS) delivery model in cloud computing environment. Malicious users could lease cloud resources and use them as platforms to launch attacks. In this paper, we propose a Virtual Machine Introspection (VMI)-based security framework to monitor cloud users’ in-VM activities and detect malicious one if any. We justify our selection of VMI method based on hardware knowledge for proposed framework by discussing its key advantages over other VMI methods. We propose design of multi-threaded analysis component that can introspect number of virtual machines hosted on cloud servers in real time. Experimental results demonstrate that our framework performs well with a set of metrics appropriate for cloud IaaS environment.

11 illus, 6 tables, 41 ref

000021   MAJUMDER A, EKBAL A, NASKAR S K (Techno India Univ, Kolkata - 700 091, Email: jobamit48@yahoo.co.in) : Bio-molecular event extraction by integrating multiple event extraction systems. Sadhana 2019, 44(1), 12.

Event extraction from biomedical text is a very important task in text mining and natural language processing. The overall task involves finding event-related expressions, classifying these into predefined categories and attaching arguments to these events. We perform event detection and event classification in one step using an ensemble of classifiers. For event argument extraction, we also use an ensemble of classification models. Our base models are developed using supervised machine learning that makes use of statistical, contextual and syntactic features. Our experimental result on the benchmark datasets of BioNLP-2011 shared task shows the recall, precision and F-measure values of 51.20 %, 65.78 % and 57.58 %, respectively.

5 illus, 10 tables, 21 ref

000034   THAKUR R K, DESHPANDE M V (Narsee Monjee Institute of Management Studies, Mumbai - 400 056, Email: thakurrashmik@gmail.com) : Kernel optimized-support vector machine and MapReduce framework for sentiment classification of train reviews. Sadhana 2019, 44(1), 6.

Sentiment analysis is one of the popular techniques gaining attention in recent times. Nowadays, people gain information on reviews of users regarding public transportation, movies, hotel reservation, etc., by utilizing the resources available, as they meet their needs. Hence, sentiment classification is an essential process employed to determine the positive and negative responses. This paper presents an approach for sentiment classification of train reviews using MapReduce model with the proposed Kernel Optimized-Support Vector Machine (KO-SVM) classifier. The MapReduce framework handles big data using a mapper, which performs feature extraction and reducer that classifies the review based on KO-SVM classification. The feature extraction process utilizes features that are classification-specific and SentiWordNet-based. KO-SVM adopts SVM for the classification, where the exponential kernel is replaced by an optimized kernel, finding the weights using a novel optimizer, self-adaptive lion algorithm. In a comparative analysis, the performance of KO-SVM classifier is compared with SentiWordNet, Naive Bayes, neural network, and LSVM, using the evaluation metrics, specificity, sensitivity, and accuracy, with train review and movie review database. The proposed KO-SVM classifier could attain maximum sensitivity of 93.46 % and 91.249 %, specificity of 74.485 % and 70.018 %; and accuracy of 84.341 % and 79.611 %, respectively, for train review and movie review databases.

8 illus, 3 tables, 28 ref

000017   KORPAL R (Computer Science Dep, Savitribai Phule Pune Univ, Pune, Maharashtra, Email: ritambhra.korpal@unipune.ac.in) : Content-based indexing of sequential data using bitmaps for efficient retrieval. Int J Info Computing Sci 2019, 6(2), 169-79.

While applying machine learning to unearth the underlying abstractions in the data can lead to overwhelmingly large number of detected patterns. Selecting the patterns as they are being generated, which may point to significant trends in the underlying data becomes an arduous task. In order to ensure that relevant patterns can be put to use, they can be stored in a persistent store and can be retrieved later for reference. With huge number of such patterns, the content-based retrieval can be very slow. In this paper, a novel method of indexing is presented for efficient retrieval of selected patterns. The new index structure, proposed in this paper, called Sequence Bitmap, does not require any preprocessing and retains the sequence of states while indexing, which is essential for indexing sequential patterns. Sequence bitmap performed very efficiently as compared to non-indexed content-based retrieval and significant improvements were observed as the database size increased. Variation of index creation time and index size with the increase in database size was also studied.

13 illus, 1 table, 22 ref

000012   KALMEGH S R (Computer Science Dep, Sant Gadge Baba Amravati Univ, Amravati, Maharashtra, Email: sushil.kalmegh@gmail.com) : Effective classification of Indian news using lazy classifier IB1 and IBk from weka. Int J Info Computing Sci 2019, 6(2), 160-8.

The amount of data in the world and in our lives increasing day by day with rapid speed. It seems ever-increasing and there’s no end to it. We are overwhelmed with data. The WWW overwhelms us with information. The Weka workbench is an organized collection of state-of-the-art machine learning algorithms and data pre-processing tools. The basic way of interacting with these methods is by invoking them from the command line. However, convenient interactive graphical user interfaces are provided for data exploration, for setting up large-scale experiments on distributed computing platforms, and for designing configurations for streamed data processing. Classification may refer to categorization, the process in which ideas and objects are recognized, differentiated and understood. It classifies data of various kinds. There are many classification problems that occurs in different application areas and need to be solved. Different types of classification algorithms like lazy, tree-based, rule-based, etc are widely used. This paper has been carried out to make a performance evaluation of Lazy Classifier algorithms IB1 and IBk by using different Test Mode. The paper sets out to make a comparative evaluation of classifiers IB1 & IBk in test mode (i) evaluate on training data, (ii) 5-fold cross-validation, and (iii) 10-fold cross-validation in the context of a dataset of Indian news to maximize true positive rate and minimize false-positive rate.

4 illus, 14 tables, 11 ref

000015   KHEDIKAR K A, YEVALE V V, MEHTA P M, BADNORE S S (Computer Science & Engineering Dep, Walchand Institute of Technology, Solapur, Maharashtra, Email: kanchan.khedikar@gmail.com) : Automation system for textile industry using BI. Int J Info Computing Sci 2019, 6(2), 155-9.

Business intelligence is a technology and an application which can be used when it comes to automate the industry. Now a days industries need to process large amount of data. This data needs to be processed to give the proper information for making the business decisions. But often these data have so many challenges such as, many industries generate huge chunk of data in any format and in many unstructured files. These data must be combined, compared to work as a whole to get the proper decision. So to overcome these problems the solution is to use the concept of Data Integration which would allow data from different databases and formats to communicate with each other. Among the various available ETL tools in the market, Informatica is the market’s leading integration platform. This paper presents the proposed idea of implementing the system that will be capable of analyzing its environment and presenting business data to support better business decision making. The system consists of a website for an industry which will be used for data integration and will also keep their information secure and make their management flexible. It will integrate different modules such as designing database, data processing using ETL tool Informatica and at the end final reporting using the Pentaho reporting tool. This paper explains the system architecture of proposed idea, various technologies used for this system and methodology used in the project.

5 illus, 10 ref

000026   PREMRAJ H, GOVINDASAMY P (Vels Institute of Science, Technology & Advanced Studies (VISTAS), Chennai – 117, Email: premraj1960@gmail.com) : Reconnaissance beyond integrated marketing communication – A panacea for advertisers’ qualms. Int J Info Computing Sci 2019, 6(2), 122-31.

With the advent of computers, internet, mobile phones, iPods, portable DVRs, video game systems, et al., consumers are empowered as never before. Effective communication impact created through Mass Media advertising seem to fade into oblivion. The recent explosion in the new communication technology, ever-changing consumers, and the impelling need to seek out more productive, effective and result-oriented medium to convey the message, have made marketers seek venues beyond the horizon of mass media. Marketers across the globe have attempted to integrate multiple communication tools in such a way as to offset the weakness of one with the strength of the other, thus leading to emergence of Integrated Marketing Communication. But a stage as come where even IMC is being considered to be a mix of communication strategies lacking unified approach in delivering the required impetus at the right time and in an environment where it would be acted upon. To tide over this, marketers may resort to the novice concepts of “Below the Line (BTL) Marketing” and “Permission Marketing”, whose underlying tenet is that communication taking place with the permission of the customer is bound to be more effective and result oriented. The study focuses on the fading age of mass communication and scouts beyond IMC and explores venues for generating cost-effective, customer-centric and result-oriented communication in tandem with the contemporary business realm.

6 tables, 7 ref

000031   SINGH N, VERMA P (Computer Science & Engineering Dep, BBD Univ, Lucknow, Uttar Pradesh, Email: erpoojarec89@bbdu.ac.in) : A review on cloud computing securities and algorithms. Int J Info Computing Sci 2019, 6(2), 98-104.

In the cloud, the information is exchanged among the server and customer. Cloud security is the present exchange in the IT world. This review paper helps in anchoring the information without influencing the system layers and shielding the information from unapproved sections into the server, the information is anchored in server dependent on clients' decision of security strategy so information is given high secure need. Usually cloud computing services are delivered by a third party provider who owns the infrastructure. It advantages to mention but a few include scalability, resilience, flexibility, efficiency and outsourcing non-core activities. Cloud computing offers an innovative business model for organizations to adopt IT services without upfront investment. Despite the potential gains achieved from the cloud computing, the organizations are slow in accepting it due to security issues and challenges associated with it. Security is one of the major issues which hamper the growth of cloud. In this Cloud processing innovation there are a gathering of critical strategy issues, which incorporate a few issues of protection, security, namelessness, media communications limit, government observation, unwavering quality, and risk, look at among others. So the most imperative between them is security insurance and how cloud supplier guarantees it.

2 illus, 1 table, 34 ref