027435   KOWSHALYA A M, VALARMATHI M L (Computer Science and Engineering Dep, Government Technology Coll, Coimbatore - 641 013, Email: meenakowshalya.gct@gmail.com) : Dynamic trust management for secure communications in social internet of things (SIoT). Sadhana 2018, 43(9), 136.

The world has faced three Information and Communication Technology (ICT) revolutions and the third ICT wave led to Internet of Things, the notion of anything, everything, anytime and everywhere. Out of the many visions of IoT, one revolutionary concept is to make IoT sociable i.e., incorporating social networking within Internet of Things. This revolution has led to the notion of Social Internet of Things (SIoT). Establishing a SIoT network or community is not so simple and requires integration of heterogeneous technology and communication solutions. This paper focuses on establishing a secure and reliable communication over nodes in SIoT by computing trust dynamically among neighboring nodes. Trust Management is an important area that has attracted numerous researchers over the past few years. The proposed DTrustInfer computes trust based on first hand observation, second hand observation, centrality and dependability factor of a node. Properties of trust such as honesty, cooperativeness, community interest and energy of a node are considered for computing trust. Also, this paper ensures secure communication among SIoT nodes through simple secret codes. Experimental results show that the proposed DTrustInfer outperforms the existing trust models significantly.

6 illus, 5 tables, 25 ref

027443   SANGEETA G P V, NAGASREE K P, JAMULLAMUDI R N, MUTHYALA M K K (Andhra Univ, Visakhapatnam - 530 003, Email: drmmkau@gmail.com) : Computer assisted drug repurposing: Anti TB activity in non antibiotics. Indian J Chem-Sect B 2018, 57B(10), 1295-303.

TB drug development is a formidable challenge at all times. As a part of our anti TB drug development program, we recently identified sertraline as a potential anti TB agent with an MIC-1.6µg/mL against MtbH37Rv. Sertraline is a popular marketed anti-depressant drug, hence we have planned to use the pharmacophoric signature of sertraline for virtual screening of drug database.We have performed shape based virtual screening of Drug Bank 5.0 database using vROCS software. Twenty chemically diverse drug molecules have been selected using Tanimoto COMBO score (TC>1.0). This gives chlormidazole, an obsolete anti-fungal drug as a Hit molecule with TC=1.67 (ranked 6^th) and shows excellent anti TB activity (MIC 1.6µg/mL). It has been subjected to lead optimization studies and various chlormidazole analogues have been synthesized (1b-9b). They have been further screened for in vitro anti TB activity studies. Our results have successfully identified chlormidazole (5b) with MIC=1.6 µg/mL which can be repurposed as anti TB drug. Compounds 1b and 4b show selective potent anti TB activity. The compound 8b shows selective antibacterial activity against Staphylococcus aureus (gram+ve) bacteria. Compounds 2b, 3b, 5b and 6b show potent anti TB activity along with antifungal activity against Aspergillus niger. In conclusion, our study has successfully identified potent anti-TB activity in Chlormidazole and its analogues.

3 illus, 3 tables, 16 ref

027437   LI Y, LAM T B V, DO T V V, CHAKKA R, ROTTER C (Budapest Technology and Economics Univ, Magyar tudósok körútja 2, Budapest, Hungary, Email: dovantien@tdt.edu.vn) : Investigation and characterization of MapReduce applications for big data analytics. J Sci Ind Res 2018, 77(9), 493-8.

Recently, many organisations have applied Hadoop MapReduce framework for big data analytics. MapReduce applications based on the MapReduce programming model can be developed to process data of large amount. Therefore, understanding a dependency among the resource usage parameters of MapReduce applications is crucially needed from the viewpoint of cloud operators. In this paper, we analyze the inter-dependency of resource usage parameters of MapReduce applications. Autocorrelation of each resource usage parameter and correlation characteristics of each pair of resource usage parameters are investigated. Based on the analysis, we identify several groups of features that can be used to classify MapReduce applications.

2 illus, 2 tables, 12 ref

027434   GANESHPURKAR A, SALUJA A (Gujarat Technological Univ, Ahmedabad, Gujarat, Email: akspharmacy@yahoo.com) : In silico interaction of catechin with some immunomodulatory targets: A docking analysis. Indian J Biotechnol 2018, 17(4), 626-31.

The use of plant products as immunomodulator has a long history. For eternal era, plant, mineral and animal products are used as drugs for the treatment of various diseases. The present-day synthetic compounds find their leads in natural products. The process of immunomodulation amends the immune system of an individual by prying with its usual functions. Research of immunomodulators from natural sources has been extensively studied for modulation of immune system along with protection and prevention of diseases. Catechin, a flavonoid has been investigated for its potential anti-inflammatory effects. Analgesic effects have been observed for catechin in experimental animals. The present study is focused on exploring the in silico interaction of catechin with some chemokines and inflammatory targets. In this study, catechin was docked with tumour necrosis factor alpha (TNF-α), interleukin (IL)-1β, IL-6, inducible nitric oxide synthase (iNOS) and cyclooxygenase 2 (COX-2). Docking studies revealed the interaction of catechin with these targets. The result of present study provides insight for the discovery of novel molecules for immunomodulation and treatment of inflammatory disorders. Findings from the present study show that catechin interact with several chemokines and inflammatory mediators. Further studies quantitative structure activity relationship and quantitative structure property relationship on catechin and associated flavonoids are necessary to develop and establish studies which may serve a stepping stone for the development of novel and safe immunomodulator. Catechin, can, therefore, can be considered as a candidate for development of an immunomodulatory agent.

4 illus, 39 ref

027438   MISHRA B, MISHRA S, SELVAM T P, CHAVAN S T, PETHE S N (Radiological Safety Div, Homi Bhabha National Institute, Mumbai - 400 094, Email: m.bibek@gmail.com) : Comparison of measured and Monte Carlo calculated dose distributions from indigenously developed 6 MV flattening filter free medical linear accelerator. J Med Phys 2018, 43(3), 162-7.

Monte Carlo simulation was carried out for a 6 MV flattening filter‑free (FFF) indigenously developed linear accelerator (linac) using the BEAMnrc user‑code of the EGSnrc code system. The model was benchmarked against the measurements. A Gaussian distributed electron beam of kinetic energy 6.2 MeV with full‑width half maximum of 1 mm was used in this study. The simulation of indigenously developed linac unit has been carried out by using the Monte Carlo‑based BEAMnrc user‑code of the EGSnrc code system. Using the simulated model, depth and lateral dose profiles were studied using the DOSXYZnrc user‑code. The calculated dose data were compared against the measurements using an RFA dosimertic system made by PTW, Germany (water tank MP3‑M and 0.125 cm³ ion chamber). The BEAMDP code was used to analyze photon fluence spectra, mean energy distribution, and electron contamination fluence spectra. Percentage depth dose (PDD) and beam profiles (along both X and Y directions) were calculated for the field sizes 5 cm × 5 cm ‑ 25 cm × 25 cm. The dose difference between the calculated and measured PDD and profile values were under 1 %, except for the penumbra region where the maximum deviation was found to be around 3 %. A Monte Carlo model of indigenous FFF linac (6 MV) has been developed and benchmarked against the measured data.

5 illus, 1 table, 29 ref

027446   SINGH G, OINAM A S, KAMAL R, HANDA B, KUMAR V, RAI B (Radiotherapy Dep, PGIMER, Chandigarh - 160 012, Email: oarunsingh@rediffmail.com) : Voxel based bed and EQD₂ evaluation of the radiotherapy treatment plan. J Med Phys 2018, 43(3), 155-61.

Three-dimensional (3D) treatment planning of patient undergoing radiotherapy uses complex and meticulous computational algorithms. These algorithms use 3D voxel data of the patient to calculate the radiation dose distribution and display it over the CT image dataset for treatment plan evaluation. The purpose of the present study is the development and implementation of radiobiological evaluation of the radiotherapy treatment plan incorporating the tissue-specific radiobiological parameters. An indigenous program was written in MATLAB® software (version 2011b of Mathworks Inc.) to extract the patient treatment plan data from DICOM-RT files which are exported from the treatment planning system. CT-, Structures- and Dose-Cube matrices are reconstructed from the exported patient plan data. BED and EQD₂ based dose volume histograms (DVHs), colorwash and iso-effective dose curves were generated from the physical Dose-Cube using the linear-quadratic (LQ) formalism and tissue-specific radiobiological parameters (α/β). BED-and EQD₂-colorwash and iso-effective curves along with BED and EQD₂ dose volume histograms provide superior radiobiological information as compared to those of physical doses. This study provides supplementary recipes of radiobiological doses along with the physical doses which are useful for the evaluation of complex radiotherapy treatment plan of the patients.

8 illus, 10 ref

027441   PAULOSE R, JEGATHEESAN K, BALAKRISHNAN G S (Bharathiar Univ, Coimbatore - 641 046, Email: renpau@gmail. com) : A big data approach with artificial neural network and molecular similarity for chemical data mining and endocrine disruption prediction. Indian J Pharmacol 2018, 50(4), 169-76.

Chemical toxicity prediction at early stage drug discovery phase has been researched for years, and newest methods are always investigated. Research data comprising chemical physicochemical properties, toxicity, assay, and activity details create massive data which are becoming difficult to manage. Identifying the desired featured chemical with the desired biological activity from millions of chemicals is a challenging task. In this study, we investigate and explore big data technologies and machine learning approaches to do an efficient chemical data mining for endocrine receptor disruption prediction and virtual compound screening. The power of artificial neural network (ANN) in predicting chemicals’ activity toward androgen receptor (AR) and estrogen receptor (ER) and thereby classifying into human endocrine disruptor or nondisruptor is investigated. Molecules are collected along with their Inhibitory Concentration (IC50) values toward AR and ER. Training and test datasets are created with active and inactive classes of molecules. Molecular fingerprints of Electro Topological State (E‑State) are generated for describing every compound. ANN machine learning model is created using Apache Spark and implemented in Hadoop big data environment. Test chemical’s structural similarity toward active class of training compounds is estimated and combined with ANN model for improving prediction accuracy. AR and ER predictive models applied on corresponding test datasets gave 86.31 % and 89.57 % accuracies, respectively, in correctly classifying molecules as disruptor or nondisruptor. Molecular fragments and functional groups are ranked based on their importance in forming ANN model and influence toward the AR and ER disruption behavior. Training molecules that are specific to the test molecules’ endocrine disruption prediction are retrieved based on the structural similarity values. The current study demonstrates a new approach of chemical endocrine receptor disruption prediction combining ANN machine learning method and molecular similarity in a big data environment. This method of predictive modeling can be further tested with more receptors and hormones and predictive power can be examined.

4 illus, 1 table, 30 ref

027444   SHAH S B, BHARGAVA A K, HARIHARAN U, VISHVAKARMA G, JAIN C R, KANSAL A (Rajiv Gandhi Cancer Institute and Research Centre, New Delhi - 110 085, Email: drshagun_2010@ rediffmail.com) : Cardiac output monitoring: A comparative prospective observational study of the conventional cardiac output monitor Vigileo^™ and the new smartphone-based application Capstesia^™. Indian J Anaesth 2018, 62(8), 584-91.

Capstesia is a software designed for smartphones (AndroidTM/iOSTM) to estimate the cardiac output and other haemodynamic variables from the waveform obtained from an invasive arterial cannula. The technology has been validated by studies in simulated environmental conditions. We compared the cardiac output (CO) and stroke volume variation (SVV) obtained by conventional cardiac output monitor VigileoTM with CO and pulse pressure variation (PPV) extracted from CapstesiaTM, under clinical conditions, intraoperatively. In a Samsung smartphone in which the Capstesia software had been downloaded, the application was opened and a snapshot of the arterial waveform from the monitor screen of anaesthesia workstation was taken. The application instantaneously calculates the CO and PPV after inputting the heart rate and the systolic and diastolic blood pressure variables. These values were then compared with readings from the VigileoTM monitor. Data was collected from 53 patients and analysed. Five hundred and thirty data pairs of CO and an equal number of SVV and PPV pairs were analysed. Cardiac index by Capstesia (CIcap) was found to have a positive correlation with cardiac index by Vigileo (CIvig) using the intraclass correlation for raters, the strength of correlation being 0.757. Upper and lower 95% confidence limits were 1.43 l/min/m² and − 1.14 l/min/m² (Bland Altman’s plot). A positive correlation was found between SVV and PPV using the Pearson’s correlation (r = 0.732). CapstesiaTM is a reliable and feasible alternative to VigileoTM for intraoperative CO monitoring in oncosurgical patients.

3 illus, 3 tables, 22 ref

026200   JOSHI C, GAUTAM S (Animal Husbandry Dep, National Institute of High Security Animal Diseases, Anand Nagar- 462 022, Email: gautam.nihsad@gmail.com) : In-silico structural, functional and immunogenic characterization of Taenia solium TS14 protein. Indian J Anim Res 2018, 52(7), 1018-24.

TS14, a Cysticercosis cellulosae derived protein, has been exploited for immunodiagnosis of cysticercosis in humans and pigs. However, the information on structure, function, stability and immunogenicity of TS14 derived from different isolates is primarily lacking. The present study deals with in-silico characterization of six TS14 isolates. High thermostability and an isoelectric point of 9.41 were recorded. Based on N-terminal amino acid residues, high resistance to intracellular proteases with extended in-vivo and in-vitro half-lives was predicted. TS14 is foreseen as a secretory protein with a signal peptide and an extracellular localization. Structural analysis of TS14 exhibited the dominance of helices in the secondary structure (92 % coverage) with majority of residues showing high and medium solvent accessibility. High lysine content and presence of multiple nucleotide binding sites in TS14 suggests interaction with RNA/DNA and a role in their metabolism. Immunogenic profiling predicted presence of four distinct B-cell epitopes. Mutational analysis based on the single amino acid substitutions among six TS14 isolates demonstrated minor variations in structural stability; however, all the substitutions were well tolerated. Moreover, all the isolates revealed almost identical immunogenic profile with an equivocal potential to elicit the antibody-mediated immune response.

4 illus, 2 tables, 34 ref

026199   KUMAR A, KALRA N, GARHWAL S (Computer Science and Engineering Dep, Thapar Institute of Engineering & Technology, Patiala- 147 004, Email: ajayloura@gmail.com) : Error tolerance for the recognition of faulty strings in a regulated grammar using fuzzy sets. Sadhana 2018, 43(8), 134.

To overcome the limitations of context-free and context-sensitive grammars, regulated grammars have been proposed. In this paper, an algorithm is proposed for the recognition of faulty strings in regulated grammar. Furthermore, depending on the errors and certainty, it is decided whether the string belongs to the language or not based on string membership value. The time complexity of the proposed algorithm is O(|G²_R |·|w|), where |G_R| represents the number of production rules and |w| is the length of the input string, w. The reader is provided with numerical examples by applying the algorithm to regularly controlled and matrix grammar. Finally, the proposed algorithm is applied in the Hindi language for the recognition of faulty strings in regulated grammar as a real-life application.

8 tables, 36 ref

026198   SUNITA, GARG D (Computer Science and Engineering Dep, Thapar Univ, Patiala- 147 004, Email: sunita.tu@gmail.com) : Extended suffix array construction using Lyndon factors. Sadhana 2018, 43(8), 133.

In this paper, we are extending the novel approach of incremental suffix array construction using Lyndon factorization to the construction of extended suffix array where extended suffix array is the suffix array along with the corresponding longest common prefix (LCP) array. Main motive behind the incremental and simultaneous construction of suffix array and LCP array is that both involve in calculating the order information by considering the common prefixes of the suffixes. As local suffixes once sorted have the same sorted order when these are merged with sorted suffixes of another Lyndon factor. So, merging of Lyndon factors is simply merging of two sorted lists of suffixes of these Lyndon factors. Also, the two sorted orders coincide thus making the merging of Lyndon factors a simple merging of two sorted lists of suffixes. Incremental LCP construction simultaneously saves a lot of computation and hence time. The proposed approach has quadratic run time and the disk working space requirement is O(n). Experiments also show the performance gain of our approach in terms of time over the existing method of incremental construction.

4 illus, 1 table, 41 ref

026197   SINGH G, SHRIMANKAR D (Computer Science and Engineering Dep, Visvesvaraya National Institute of Technology, Nagpur- 440 010, Email: garimasingh.mit2006@gmail.com) : A privacy-preserving authentication protocol with secure handovers for the LTE/LTE-A networks. Sadhana 2018, 43(8), 128.

Long-Term Evolution/Long-Term Evolution Advanced (LTE/LTE-A) is the latest mobile communication technology that is offering high data rates and robust performance to the subscribers. Since LTE/ LTE-A standards are established on the Internet Protocol (IP) connectivity and provide compatibility with the heterogeneous networks, these new features create availability of the new security challenges in the LTE/LTE-A networks. Taking into consideration the issues of serious signalling congestion and security loopholes in LTE/ LTE-A networks, the authors propose an Efficient Authentication and Key Agreement Protocol for Evolved Packet System (EAKA-EPS) with secure handover procedures. The proposed protocol achieves outstanding results in terms of the optimization of computation and signalling overhead. With this, the protocol guarantees the needed security requirements like protected wireless interface and strong mutual authentication between the entities, and ensures access stratum secrecy at the time of handovers. The formal verification results of the proposed scheme over the security verification and simulation tool ‘‘Automated Validation of Internet Security Protocols and Applications (AVISPA)’’ show that the suggested protocol is safe against various malicious attacks, which are still possible in LTE/LTE-A networks. To the best of the authors’ knowledge, the suggested approach is the first approach that provides perfect secrecy with less computation and communication overhead in the LTE/LTE-A networks.

12 illus, 3 tables, 51 ref

026196   DOMADIYA N, RAO U P (Sardar Vallabhbhai National Institute of Technology, Surat- 395 007, Email: domadiyanikunj002@gmail.com) : Privacy-preserving association rule mining for horizontally partitioned healthcare data: A case study on the heart diseases. Sadhana 2018, 43(8), 127.

In recent years, a trend of electronic health record (EHR) system can be seen increasingly in the hospitals, which has generated huge amount of electronically stored data of patients. Association rule mining technique is very helpful in the numerous applications of healthcare (e.g., correlation between disease and symptoms, disease and offering effective treatment and predicting risks of disease based on the historical data, etc.). The data collected by an EHR system are very important for the medical research. Currently, a patient health report is derived on the basis of a physician’s own experience and on the association rule mining results of a local EHR system maintained by a particular hospital. Association rule mining results will be more accurate if the data of all local EHR systems are integrated and association rule mining is performed. Integration of local EHR systems requires the sharing of local EHR data. Sharing of patient records violates the privacy of patients. Hence, medical research is focused on the problem of mining association rules without sharing of local private EHR data. Privacy-preserving distributed association rule mining (PPDARM) solves this issue by mining the association rules while preserving the privacy of patients. In this paper, an approach for the PPDARM is proposed for collaboratively performing association rule mining by all local EHR systems while preserving the privacy. The proposed approach is also analysed with the heart disease dataset.

6 illus, 2 tables, 40 ref

026195   MOHAN M, DEVI M K K, PRAKASH V J (Computer Science and Engineering Dep, NSS Coll of Engineering, Palakkad- 678 008, Email: mayajeevan@gmail.com) : Confidential and efficient asset proof for bitcoin exchanges. Sadhana 2018, 43(8), 126.

Technological advancements boost the business to play a crucial role in a country’s economic success. Cryptography-based currencies, called as cryptocurrencies, are now leading the world’s economy. With the increasing popularity of cryptocurrencies, cryptocurrency exchanges have emerged to support cryptocurrency-related services. Among cryptocurrencies, bitcoin takes the lead and it is widely accepted by the world community. Lots of security issues are arising day by day and the exchange should handle all of of them sensibly. It is necessary that the exchange should be solvent all the time in terms of its assets and liabilities for its survival. For this, periodic settlement of the accounts should be done using appropriate techniques. The information exchange needed for this should be concealed from the adversaries. Cryptography-based techniques with zero-knowledge protocols are suitable for this purpose. Maxwell’s proof of liabilities is the first cryptography-based method to verify the user assets. It makes use of binary Merkle hash trees for representing the proof of liabilities. The root node reveals the total assets of the exchange, which will attract the adversaries to execute an attack. Later the Dagher et al scheme, a privacy preserving proof of asset for bitcoin exchanges, was proposed. The scheme works in an interactive manner that requires the collaboration of the exchange and the user. This paper proposes an efficient non-interactive proof of assets for bitcoin exchanges.

6 illus, 1 table, 22 ref

026194   MITHRA K S, EMMANUEL W R S (Computer Science Dep, Manonmaniam Sundaranar Univ, Tirunelveli- 627 012, Email: ksmithra1@gmail.com) : FHDT: Fuzzy and Hyco-entropy-based Decision tree classifier for tuberculosis diagnosis from sputum images. Sadhana 2018, 43(8), 125.

Tuberculosis (TB) is one of the infectious diseases spread by the infectious agent Mycobacterium tuberculosis. Sputum smear microscopy is the primary tool used for the diagnosis of pulmonary TB, but has its limitations such as low sensitivity and large observation time. Hence, an automated technique is preferred for the diagnosis of TB. This paper develops a technique for TB diagnosis based on the bacilli count by proposing Fuzzy and Hyco-entropy-based Decision Tree (FHDT) classifier using sputum smear microscopic images. The proposed technique involves three steps: segmentation, feature extraction and classification. Initially, the input sputum smear microscopic image is subjected to a colour space transformation, for which a thresholding is applied to obtain the segmented result. Important features such as length, density, area and few histogram features are extracted for FHDT-based classification that classifies the segments into few-bacilli, non-bacilli and overlapping bacilli. An entropy function, called hyco-entropy, is designed for the optimal selection of feature. For further analysis of classification, that is, to count the number in the overlapping bacilli, the fuzzy classifier is adopted. FHDT classifier is evaluated in terms of Segmentation Accuracy (SA), Mean Squared Error (MSE) and Missing Count (MC) using microscopic images taken from ZNSM-iDB, where it can attain maximum mean SA of 0.954 and mean MC of 2.4.

8 illus, 1 table, 33 ref

026193   MODI C, PATEL D (National Institute of Technology, Farmagudi- 403 401, Email: cnmodi@nitgoa.ac.in) : A feasible approach to intrusion detection in virtual network layer of cloud computing. Sadhana 2018, 43(7), 114.

Intrusion detection/prevention is the greatest security challenge at virtual network layer of Cloud computing. To address this challenge, there have been several security frameworks reported. However, still there is a scope of addressing newer challenges. Here, we propose a security framework to detect network intrusions in Cloud computing. This framework uses Snort and combination of different classifiers, viz Bayesian, Associative and Decision tree. We deploy our intrusion detection system (IDS) sensors on each host machine of Cloud. These sensors correlate intrusive alerts from each region of Cloud in order to identify distributed attacks. For feasibly analysis and functional validation of this framework, we perform different experiments in real time and offline simulation.

16 illus, 8 tables, 49 ref

026192   PIKLE N K, SATHE S R, VYAVHARE A Y (Computer Science and Engineering Dep, Visvesvaraya National Institute of Technology, Nagpur, Email: nilesh.pikle@gmail.com) : GPGPU-based parallel computing applied in the FEM using the conjugate gradient algorithm: A review. Sadhana 2018, 43(7), 111.

Parallelization of the finite-element method (FEM) has been contemplated by the scientific and high-performance computing community for over a decade. Most of the computations in the FEM are related to linear algebra that includes matrix and vector computations. These operations have the single-instruction multiple-data (SIMD) computation pattern, which is beneficial for shared-memory parallel architectures. General-purpose graphics processing units (GPGPUs) have been effectively utilized for the parallelization of FEM computations ever since 2007. The solver step of the FEM is often carried out using conjugate gradient (CG)type iterative methods because of their larger convergence rates and greater opportunities for parallelization. Although the SIMD computation patterns in the FEM are intrinsic for GPU computing, there are some pitfalls, such as the underutilization of threads, uncoalesced memory access, lower arithmetic intensity, limited faster memories on GPUs and synchronizations. Nevertheless, FEM applications have been successfully deployed on GPUs over the last 10 years to achieve a significant performance improvement. This paper presents a comprehensive review of the parallel optimization strategies applied in each step of the FEM. The pitfalls and tradeoffs linked to each step in the FEM are also discussed in this paper. Furthermore, some extraordinary methods that exploit the tremendous amount of computing power of a GPU are also discussed. The proposed review is not limited to a single field of engineering. Rather, it is applicable to all fields of engineering and science in which FEM-based simulations are necessary.

6 illus, 1 table, 109 ref

026191   PANDEY S C (Computer Science and Engineering Dep, Birla Institute of Technology, Patna, Email: subh63@yahoo.co.in) : Can artificially intelligent agents really be conscious?. Sadhana 2018, 43(7), 110.

Mind and intelligence are closely related with the consciousness. Indeed, artificial intelligence (AI) is the most promising avenue towards artificial consciousness (AC). However, in literature, consciousness has been considered as the least amenable to being understood or replicated by AI. Further, computational theories of mind (CTMs) render the mind as a computational system and it is treated as a substantial hypothesis within the purview of AI. However, the consciousness, which is a phenomenon of mind, is partially tackled by this theory and it seems that the CTM is not corroborated considerably in this pursuit. Many valuable contributions have been incorporated by the researchers working strenuously in this domain. However, there is still scarcity of globally accepted computational models of consciousness that can be used to design conscious intelligent machines. The contributions of the researchers entail consciousness as a vague, incomplete and human-centred entity. In this paper, attempt has been made to analyse different theoretical and intricate issues pertaining to mind, intelligence and AC. Moreover, this paper discusses different computational models of the consciousness and critically analyses the possibility of generating the machine consciousness as well as identifying the characteristics of conscious machine. Further, different inquisitive questions, e.g., ‘‘Is it possible to devise, project and build a conscious machine?’’, ‘‘Will artificially conscious machines be able to surpass the functioning of artificially intelligent machines?’’ and ‘‘Does consciousness reflect a peculiar way of information processing?’’ are analysed.

5 illus, 131 ref

026190   YOUSSEF K, MESSIHA N, ABD-ELNABY M (Menoufia Univ, Egypt, Email: kyrillos.fouad@gmail.com) : Fairness and throughput enhancement based resource allocation scheme for underlay cognitive radio networks. Sadhana 2018, 43(7), 107.

Acquiring good throughput and diminishing interference to primary users (PU) are the main objectives for secondary users in a cognitive radio (CR) network. This paper proposes a centralized subcarrier and power allocation scheme for underlay multi-user orthogonal frequency division multiplexing considering the rate loss and the interference those the PU can tolerate. The main purpose of the proposed scheme is to efficiently distribute the available subcarriers among cognitive users to enhance both the fairness and the throughput performance of the cognitive network while maintaining the QoS of primary users. Simulation results show that the proposed scheme achieves a significantly higher CR network throughput than that of the conventional interference power constraint (IPC) based schemes and provides a significantly enhanced fairness performance. Also, contrary to the conventional IPC based schemes, the proposed scheme is able to significantly increase the achieved throughput as the number of CR users increases.

11 illus, 2 tables, 12 ref

026189   AZIZ N H A, IBRAHIM Z, AZIZ N A A, MOHAMAD M S, WATADA J (Multimedia Univ, Malaysia) : Single-solution simulated Kalman filter algorithm for global optimisation problems. Sadhana 2018, 43(7), 103.

This paper introduces single-solution Simulated Kalman Filter (ssSKF), a new single-agent optimisation algorithm inspired by Kalman Filter, for solving real-valued numerical optimisation problems. In comparison, the proposed ssSKF algorithm supersedes the original population-based Simulated Kalman Filter (SKF) algorithm by operating with only a single agent, and having less parameters to be tuned. In the proposed ssSKF algorithm, the initialisation parameters are not constants, but they are produced by random numbers taken from a normal distribution in the range of [0, 1], thus excluding them from tuning requirement. In order to balance between the exploration and exploitation in ssSKF, the proposed algorithm uses an adaptive neighbourhood mechanism during its prediction step. The proposed ssSKF algorithm is tested using the 30 benchmark functions of CEC 2014, and its performance is compared to that of the original SKF algorithm, Black Hole (BH) algorithm, Particle Swarm Optimisation (PSO) algorithm, Grey Wolf Optimiser (GWO) algorithm and Genetic Algorithm (GA). The results show that the proposed ssSKF algorithm is a promising approach and able to outperform GWO and GA algorithms, significantly.

10 illus, 7 tables, 40 ref

026188   GOR M M, PATHAK P M, SAMANTARAY A K, ALAM K, KUMAR P, ANAND D, VIJAY P, SARKAR R, YANG J M, KWAK S W (Indian Institute of Technology, Roorkee, Email: mehulmgor@gmail.com) : Development of a compliant legged quadruped robot. Sadhana 2018, 43(7), 102.

This paper presents the detailed steps for design and development of a compliant legged fault tolerant quadruped robot where each leg has two links and two motorized revolute joints for locomotion. The body and upper links of legs are rigid whereas the lower link of each leg is compliant. Amble gait is demonstrated on the developed robot. Safety and reliability are the most critical issues for the quadruped robot. During the failure of any joint, performance of quadruped robot is affected. In this paper, locked joint failure is also discussed. Strategies for fault tolerant control of the quadruped are developed and experimentally validated. The developed robot can be used for various hardware-in-the-loop controller prototyping such as reconfiguration, fault tolerant control, and posture control, etc. pertaining to quadruped robots.

24 illus, 4 tables, 26 ref

026187   PATOWARY A N, DUTTA B, BARMAN M P, GADDE S R (Assam Agricultural Univ, Raha - 782 103, Email: a_patowary@yahoo.com) : Accidental deaths in India: Forecasting with ARIMA model. Environ Ecol 2018, 36(3), 761-6.

Accident is one of the burning problems for pre-mature end to human lives. Road accident in India is an increasing trouble and has raised one of the country’s major problems. This paper outlines development of  a conventional  time series model viz. Autoregressive  Integrated Moving Average (ARIMA)  model for the annual total number of deaths due to accident (natural and unnatural) in India covering the period 1967 to 2015 and to forecast the number of annual accidental deaths likely to occur in future. We investigated and found that ARIMA (2, 2, 1) model is suitable for the given data set.

8 illus, 2 tables, 8 ref

026186   AL-IMAM A (Anatomy and Cellular Biology Dep, Baghdad Univ, Iraq, Email: tesla1452@gmail.com) : Digital epidemiology and geographic mapping of G6PD deficiency: Retrospective analytic of trends database existing on the surface web. Asian J Med Sci 2018, 9(5), 57-61.

Glucose-6-phosphate dehydrogenase (G6PD) deficiency is an inherited X-linked recessive condition in which the body does not synthesise a sufficient quantity of the G6PD enzyme. Hemolytic anaemic episodes occur following exposure to some medications, foods, or even infections in G6PD-deficient individuals. To assess the digital epidemiology as well as the geographic mapping of G6PD deficiency in the world including countries of the Mediterranean basin. This study is primarily based on a digital epidemiological analysis and geographic mapping based on data retrieved from Google Trends database, a very large database, existing on the surface web. A retrospective analysis was carried out for the period from the 22^nd of March 2015 to the 24^th of January 2016. Trends data will also be contrasted with a collateral data set of a cross-sectional analytic for the same period which was conducted based on the exploration of cases of G6PD deficiency admitted to Jordan University Hospital. Concerning geographic mapping, countries of the Basin of the Mediterranean Sea and the Arabian Gulf accounted for one-third of the entire geographic map at 15.66 % and 18.18 % respectively. Countries of the Mediterranean basin included Jordan, Italy, Lebanon, Israel, Egypt, Greece, Syria, Cyprus, Tunisia, Algeria, and Morocco. Contributing countries surrounding the Arabian Gulf included Kuwait, Kingdom of Saudi Arabia, Bahrain, Iran, United Arab Emirates, Qatar, and Iraq. The Hashemite Kingdom of Jordan contributed to 2.78 % of the global map which accounted for 17.74 % of the entire Mediterranean basin. Concerning digital epidemiology, the prevalence was recorded as highest during May 2015 (12.10 %), August 2015 (11.17 %), and November 2015 (11.28 %). Concerning the percentile contribution of monthly records, data were in harmony for those cases admitted to hospital and signals recorded via Google Trends. Both datasets averaged a percentile contribution of approximately 9 % per month. This study is the first inferential research on G6PD deficiency based on data from a trends database and parallel data from Jordan University Hospital. Ambitious future research should deploy the use of machine learning for real-time and predictive analytics which will provide an excellent value for public health services and epidemiological studies. 

3 illus, 1 table, 23 ref

026183   SHARMA P, KUMAR B, SINGH D (DRDO-Instrument Research and Development Establishment, Dehradun– 248 008, Email: prabhat@irde.drdo.in) : Development of adaptive threshold and data smoothening algorithm for GPR Imaging. Def Sci J 2018, 68(3), 316-25.

There are many approaches available to separate the background and foreground in image processing applications. Currently, researchers are focusing on wavelet De-noising, curvelet threshold, Edge Histogram Descriptor threshold, Otsu thresholding, recursive thresholding and adaptive progressive thresholding. In fixed and predictable background conditions, above techniques separate background and foreground efficiently. In a common scenario, background reference is blind due to soil surface moisture content and its non-linearity. There are many methodologies proposed from time to time by researchers to solve this blind reference background separation. But challenges still now remain, because there are two major problems in ground penetrating radar imaging such as targets like ground enhances the false alarm and non-metallic target detection, where the threshold decision is a critical task. In this paper, a novel real time blind adaptive threshold algorithm is proposed for ground penetrating radar image processing. The blind threshold was decided to use normal random variable variance and image data variance. Further, the image was smoothened by random variance ratio to image data variance. Experimental results showed satisfactory results for the background separation and smoothening the targeted image data with the proposed algorithm.

12 illus, 2 tables, 24 ref

026182   VERMA K, KUMAR A, GHOSH D (DRDO-Instruments Research and Development Establishment, Dehradun- 248 008, Email: kamlesh@irde.drdo.in) : Robust stabilised visual tracker for vehicle tracking. Def Sci J 2018, 68(3), 307-15.

Visual tracking is performed in a stabilised video. If the input video to the tracker algorithm is itself destabilised, incorrect motion vectors will cause a serious drift in tracking. Therefore video stabilisation is must before tracking. A novel algorithm is developed which simultaneously takes care of video stabilisation and target tracking. Target templates in just previous frame are stored in positive and negative repositories followed by Affine mapping. Then optimised affine parameters are used to stabilise the video. Target of interest in the next frame is approximated using linear combinations of previous target templates. Proposed modified L1 minimisation method is used to solve sparse representation of target in the target template subspace. Occlusion problem is minimised using the inherent energy of coefficients. Accurate tracking results have been obtained in destabilised videos.

7 illus, 3 tables, 31 ref

026185   SINGH J (Sapient Consulting, United States) : Artificial intelligence in teaching and learning scenario. Asian J Sci Technol 2018, 9(5), 8256-61.

This paper investigates the wonders of the development of the utilization of Artificial Intelligence in teaching and learning in advanced education. It explores parts and effect of AI in advanced education and ramifications of rising advances in transit under studies learn and how establishments instruct and advance. Late innovative headways and the expanding velocity of receiving new advancements in advanced education are investigated so as to fore see the future idea of advanced education in reality as we know it where Artificial Intelligence is a piece of the texture of our colleges. We pin point a few difficulties for establishments of advanced education and under study learning in the selection of these innovations for teaching, learning, under study support and investigate facilitate bearings for inquiring about.

21 ref

026184   MEDSSIA N, KHALIFA W B, GHEDIRA K (Library and Information Science Dep, Imam Abdulrahman Bin Faisal Univ, Dammam, Saudi Arabia) : Enhanced dgg algorithm1 (Problem of public transport). Asian J Sci Technol 2018, 9(5), 8058-62.

The use of personal cars presents major environmental challenges in terms of climate change, air pollution and noise pollution the government assumed to solve these objections such as pollution and energy consumption, the multi-modal transport as a solution. In fact, the multi-modal transport ten counters several problems as irritants that are related to the distribution, the condenser of researchers classifies it as a NP-hard problem. The aim of this paper is to establish an enhanced distributed as well as guided genetic algorithm in order to solve the multi-modal transport problem, particularly the problem of disturbance. For that, the solution must be accurate in the normal case and absolutely in the degraded mode too. As a consequence, this study intends to refine the quality of services provided to users. Indeed, our approach is based on evolutionary algorithms, and more specifically on the genetic algorithm. So, we apply hybridization in the selection operator and integration of a new template in the mutation operator supporting a multi-criteria method for the itineraries detection.

4 illus, 1 table, 14 ref

024974   PARNE B L, GUPTA S, CHAUDHARI N S (Computer Science and Engineering Dep, Visvesvaraya National Institute of Technology (VNIT), Nagpur - 440 010, Email: balu.parne@students.vnit.ac.in) : ESAP: Efficient and secure authentication protocol for roaming user in mobile communication networks. Sadhana 2018, 43(6), 89.

The Global System for Mobile communication (GSM) network is proposed to mitigate the security problems and vulnerabilities observed in the mobile telecommunication system. However, the GSM network is vulnerable to different kinds of attacks such as redirection attack, impersonation attack and Man in-the Middle (MiTM) attack. The possibility of these attacks makes the wireless mobile system vulnerable to fraudulent access and eavesdropping. Different authentication protocols of GSM were proposed to overcome the drawbacks but many of them lead to network signalling overload and increases the call set-up time. In this paper, an efficient and secure authentication and key agreement protocol (ESAP-AKA) is proposed to overcome the flaws of existing authentication protocol for roaming users in the GSM network. The formal verification of the proposed protocol is presented by BAN logic and the security analysis is shown using the AVISPA tool. The security analysis shows that the proposed protocol avoids the different possible attacks on the communication network. The performance analysis based on the fluid flow mobility model shows that the proposed protocol reduces the communication overhead of the network by reducing a number of messages. On an average, the protocol reduces 60 % of network signalling congestion overhead as compared with other existing GSM-AKA protocols. Moreover, the protocol not only removes the drawbacks of existing protocols but also accomplishes the needs of roaming users.

15 illus, 9 tables, 50 ref

024972   EMMANUEL W R S, MINIJA S J (Computer Science Dep, Affiliated to Manonmaniam Sundaranar Univ, Tirunelveli - 627 012, Email: minijakenson@gmail.com) : Fuzzy clustering and Whale-based neural network to food recognition and calorie estimation for daily dietary assessment. Sadhana 2018, 43(5), 78.

The calorie value of the food items taken by the person in everyday life needs to be monitored to reduce the risk of obesity, heart problems, and diabetes, etc. The calorie estimator in the existing models has reduced accuracy since the calorie value of each food varies with mass. This paper introduces a dietary assessment system based on the proposed Cauchy, Generalized T-Student, and Wavelet kernel based Wu-and-Li Index Fuzzy clustering (CSW-WLIFC) based segmentation and the proposed Whale Levenberg Marquardt Neural Network (WLM-NN) classifier. The proposed CSW-WLIFC based segmentation segments the image based on the existing WLI-FC algorithm. A novel CSW based kernel function is utilized in the segmentation process. Feature vectors such as color, shape, and texture are extracted from the segmented image. The Neural Network is trained with the Whale-Levenberg Marquardt (WLM) model to recognize each food item from the tray image. The proposed calorie estimator calculates the calorie value of each food item. From the simulation results, it is evident that the proposed model has the improved performance than the existing models with the values of 0.999, 0.9643, 0.9627, and 0.0184 for the segmentation accuracy, macro average accuracy, standard accuracy, mean square error, respectively.

12 illus, 3 tables, 39 ref

024971   KASAPBASi M C, ELMASRY W (Computer Engineering Dep, Istanbul Commerce Univ, Turkey, Email: mckasapbasi@ticaret.edu.tr) : New LSB-based colour image steganography method to enhance the eficiency in payload capacity, security and integrity check. Sadhana 2018, 43(5), 68.

Steganography is the technique for hiding information within a carrier file so that it is imperceptible for unauthorized parties. In this study, it is intended to combine many techniques to gather a new method for colour image steganography to obtain enhanced efficiency, attain increased payload capacity, posses integrity check and security with cryptography at the same time. Proposed work supports many different formats as payload. In the proposed method, the codeword is firstly formed with secret data and its CRC-32 checksum, then the codeword is compressed by Gzip just before encrypting it by AES, and it is finally added to encrypted header information for further process and then embedded into the cover image. Embedding the encrypted data and header information process utilizes Fisher-Yates Shuffle algorithm for selecting next pixel location. To hide one byte, different LSB (least significant bits) of all colour channels of the selected pixel is exploited. In order to evaluate the proposed method, comparative performance tests are carried out against different spatial image steganographic techniques using some of the well-known image quality metrics. For security analysis, histogram, enhanced LSB and Chi-square analyses are carried out. The results indicate that with the proposed method has an improved payload capacity, security and integrity check for common problems of simple LSB method. Moreover, it has been shown that the proposed method increases the visual quality of the stego image when compared to other studied methods, and makes the secret message difficult to be discovered.

11 illus, 7 tables, 30 ref

024966   MANDAL J K, DAS S (Computer Science and Engineering Dep, Kalyani Univ, West Bengal, Email: jkm.cse@gmail.com) : An information hiding scheme in wavelet domain using chaos dynamics. J Sci Ind Res 2018, 77(5), 264-7.

In this paper an information hiding scheme in images has been proposed in transform domain using four point Daubechies Wavelet where Horizontal, Vertical and diagonal coefficients of the transformed matrix are used to embed the secret information which itself scrambled using cross coupled chaotic map with 3.5bpB payload. Transformation coefficients are prehandled through multiplying by π to overcome loss of precession. Embedded matrix is adjusted prior to reverse transformation to obtain optimal change in the embedded images which follows the inverse transformation to produce the embedded image in spatial domain. The results obtained are compared with existing techniques which shows better performance of the proposed scheme in terms of payload and quality of embedded image.

3 illus, 2 tables, 8 ref

024977   TONG L, SUN X, ZHOU Y (Heilongjiang Univ, China, Email: yzhou@aliyun.com) : Simultaneous estimation of QTL parameters for mapping multiple traits. J Genet 2018, 97(1), 267-74.

The analysis of quantitative trait loci (QTLs) aims at mapping and estimating the positions and effects of the genes that may affect the quantitative trait, and evaluating the relationship between the gene variation and the phenotype. In existing studies, most methods mainly focus on the association/linkage between multiple gene loci and one trait, in which some useful joint information of multiple traits may be ignored. In this paper, we proposed a method of simultaneously estimating all QTL parameters in the framework of multiple-trait multiple-interval mapping. Simulation results show that in accuracy aspect, the proposed method outperforms an existing method for mapping multiple traits. A real example is also provided to validate the performance of the new method.

5 tables, 22 ref

024976   SONG X D, SONG X X, LIU G B, REN C H, SUN Y B, LIU K X, LIU B, LIANG S, ZHU M (MRI Dep, Hongqi Hospital of Mudanjiang Medical Univ, China, Email: zhuminbio@126.com) : Investigating multiple dysregulated pathways in Rheumatoid arthritis based on pathway interaction network. J Genet 2018, 97(1), 173-8.

The traditional methods of identifying biomarkers in rheumatoid arthritis (RA) have focussed on the differentially expressed pathways or individual pathways, which however, neglect the interactions between pathways. To better understand the pathogenesis of RA, we aimed to identify dysregulated pathway sets using a pathway interaction network (PIN), which considered interactions among pathways. Firstly, RA-related gene expression profile data, protein–protein interactions (PPI) data and pathway data were taken up from the corresponding databases. Secondly, principal component analysis method was used to calculate the pathway activity of each of the pathway, and then a seed pathway was identified using data gleaned from the pathway activity. A PIN was then constructed based on the gene expression profile, pathway data, and PPI information. Finally, the dysregulated pathways were extracted from the PIN based on the seed pathway using the method of support vector machines and an area under the curve (AUC) index. The PIN comprised of a total of 854 pathways and 1064 pathway interactions. The greatest change in the activity score between RA and control samples was observed in the pathway of epigenetic regulation of gene expression, which was extracted and regarded as the seed pathway. Starting with this seed pathway, one maximum pathway set containing 10 dysregulated pathways was extracted from the PIN, having an AUC of 0.8249, and the result indicated that this pathway set could distinguish RA from the controls. These 10 dysregulated pathways might be potential biomarkers for RA diagnosis and treatment in the future.

2 illus, 1 table, 40 ref

024975   PATEL M, CHAKRABORTY A K, BANDYOPADHYAY M, ROTTI C (Institute for Plasma Research, Gandhinagar- 382428, Gujarat, Email: milind.patel@iter-india.org) : Performance characterization of a radiation shield baffle structure of a cryocooler based cryosorption pump for INTF. Indian J Cryog 2018, 43(1), 22-6.

To characterize Diagnostic Neutral Beam (DNB) for ITER, a test facility (INTF) is being developed at ITER-India laboratory, in Institute for Plasma Research, Gandhinagar. Operation of the beam source (BS) in INTF is based on the production of an H-- ion beam of energy 100 keV. To meet the requirement of high vacuum in INTF, twelve sets of cryocooler cooled cryosorption based cryopumps are planned of size 3.0m × 0.6m × 0.3m (L×W×D) to be installed in the INTF vacuum vessel. Each cryopump consists of Liquid Nitrogen (LN2 ) cooled 210 black TiO₂ , Al₂O₃  ceramic coated V-shaped chevron baffles arranged in staggered way precisely as radiation shield around cryocooler cooled activated charcoal coated cryopanel, with temperature around 15 – 20K. Each LN2 baffle is connected to four LN2 distribution pipes at four corners of it, maintaining precious gap to ensure sufficient gas molecule transmission through it with negligible photon transmission to cryopanel. The manufacturing of cryopumps employs two important processes which are Black coating of chevron baffles and joining process of total 210 × 4 joints with the LN2 pipes. In the past, cryopumps for SST-1 have been manufactured by utilizing (1) plasma spray technique for black coating (2) TIG brazing for joining pipe to baffles joints. In the present case, while coating is applied using the same spray technique, the joining technology selected is vacuum brazing. The advantage of vacuum brazing is it makes it possible to join large number of baffles at one go, compared to TIG brazing technique which joins the baffles one of one. Emissivity of the black coating was found to be better than 0.9 exceeding the technical specification of 0.8. Adhesion of black coating with the substrate is found to be adequate. Vacuum brazing of coupons have been qualified for the requirements of the joints. 

11 illus, 3 tables, 5 ref

024973   SAHA P, NITIN B, SANDILYA P (Indian Institute of Technology, Kharagpur- 721 302, Email: profsandilya@gmail.com) : Optimization of the performance of injection cooling system using genetic algorithm. Indian J Cryog 2018, 43(1), 16-21.

Injection cooling is a method to reduce the boil-off loss of cryogenic liquids, and has been applied in space launch vehicles. In this, subcooling due to liquid evaporation into the gas bubble causes a reduction in the liquid boil-off. Extent of evaporation depends on the gasliquid interfacial area, and heat and mass transfer rates. Hence, gas flow rate, gas injection temperature and system configuration have profound effect on liquid subcooling. Optimum values of process variables are needed to maximize the process performance. The present study involves the development of an optimization strategy to minimize the evaporative loss of cryogenic liquid in injection cooling. Genetic Algorithm (GA) has been applied for this purpose as it enables the determination of global optimum values of various process variables. An in-house code has been developed to carry out optimization studies on the injection cooling.

3 illus, 3 tables, 7 ref

024951   VAIDYA M, GARG S, SINGH C, MAHAJAN M M (Economics Dep, GGDSD Coll, Chandigarh– 160 030, Email: madhureco@gmail.com) : Changing dimensions of drug patents of Indian pharmaceutical industry. J Intellec Prop Rights 2018, 23(2-3), 111-8.

The Patents Act, 1970 which provided for process patenting led to pharmaceutical revolution in the country as India witnessed a spectacular increase in generic manufacturers. The Patent Act, 2005 however is considered to be a major game changer as it provides for both process and product patents and will set the tone to shift away from reverse engineering to forward engineering. The growth in Patent activity reflects the development in science and technology of the nation. With the passing of Patent Act, 2005 and increase in Intellectual Property (IP) awareness amongst the Indian companies, they seem to be taking IP protection more seriously on a global level. The paper aims to bring about trend, growth and prospects of patenting in Indian Pharmaceutical Sector. Relative Specialisation Index (RSI) for pharmaceutical patents in India vis-à- vis the whole world has been calculated to concur if its trend is uphill. An inter-country RSI analysis of top ten pharmaceutical markets in the world has been conducted to project India’s strength at the world level.

5 illus, 4 tables, 43 ref

024970   LIU J, WANG W, LI X, WANG T, WANG T (System Engineering Coll, National Univ of Defence Technology, China, Email: l.jiajie@yahoo.com) : A motif-based mission planning method for UAV swarms considering dynamic reconfiguration. Def Sci J 2018, 68(2), 159-66.

Influenced by complex terrain conditions of combat environments and constrained by the level of communication technology, communication among unmanned aerial vehicles (UAV) is greatly restricted. In light of this situation, mission planning for UAV swarms under limited communication has become a difficult problem. This paper introduces motifs as the basic unit of configuration and proposes a motif-based mission planning method considering dynamic reconfiguration. This method uses multidimensional dynamic list scheduling algorithm to generate a mission planning scheme based on the motif-based swarm configuration solution. Then it incorporates order preserved operators with NSGA-III algorithm to find Pareto front solutions of all possible mission planning schemes. The feasibility of this mission planning method is validated through a case study.

13 illus, 1 table, 17 ref

024969   SUDARSAN N V, SARSAR R B, DAS S K, NAIK S D (DRDO-Armament Research and Development Establishment, Pune - 411 021, Email: nvshemrl@gmail.com) : Prediction of shot start pressure for rifled gun system. Def Sci J 2018, 68(2), 144-9.

Determination of short start pressure (SSP) for gun system has always been of paramount interest for gun designers. In this paper, a generalised model has been developed for theoretical prediction of SSP for rifled gun system using dimensional analysis approach. For this, parameters affecting the SSP of the gun like rifling dimensions, driving band dimensions, material properties of driving band, projectile mass and diameter are taken into consideration. For a particular case of large caliber rifled gun system, the model is established using linear relations among dimensionless groups of parameters. The model has been validated by data available from the open literature.

2 illus, 7 tables, 23 ref

024968   ANBARASU B, ANITHA G (Madras Institute of Technology, Anna Univ, Chennai - 600 044, Email: avianbu@gmail.com) : Indoor scene recognition for micro aerial vehicles navigation using enhanced-GIST descriptors. Def Sci J 2018, 68(2), 129-37.

An indoor scene recognition algorithm combining histogram of horizontal and vertical directional morphological gradient features and GIST features is proposed in this paper. New visual descriptor is called enhanced-GIST. Three different classifiers, k-nearest neighbour classifier, Naïve Bayes classifier and support vector machine, are employed for the classification of indoor scenes into corridor, staircase or room. The evaluation was performed on two indoor scene datasets. The scene recognition algorithm consists of training phase and a testing phase. In the training phase, GIST, CENTRIST, LBP, HODMG and enhanced-GIST feature vectors are extracted for all the training images in the datasets and classifiers are trained for these image feature vectors and image labels (corridor-1, staircase-2 and room-3). In the test phase, GIST, CENTRIST, LBP, HODMG and enhanced-GIST feature vectors are extracted for each unknown test image sample and classification is performed using a trained scene recognition model. The experimental results show that indoor scene recognition algorithm employing SVM with enhanced GIST descriptors produces very high recognition rates of 97.22 per cent and 99.33 per cent for dataset-1 and dataset-2, compared to kNN and Naïve Bayes classifiers. In addition to its accuracy and robustness, the algorithm is suitable for real-time operations.

9 illus, 5 tables, 20 ref

024967   SHIM J-Y, KIM H-Y, CHO B-K, YANG S H, MO C, KWON K D, KIM J, LEE W-H (Biosystems Machinery Engineering Dep, Chungnam National Univ, Korea, Email: wanghee@cnu.ac.kr) : Multivariate analysis of deboning data for classifying Hanwoo (Korean native cattle) by gender. Curr Sci 2018, 114(5), 1075-82.

Gender is an important factor in determining the market price of Hanwoo, but its discrimination is impossible after deboning. This study aims at identifying the variables in Hanwoo deboning data that could be used for gender identification and classification. Deboning data of Hanwoo were analysed by discriminant function analysis. Seven pre-deboning and 24 post-deboning variables were identified and showed 91.3 % and 98.9 % accuracy in gender identification respectively. Discriminant power was 98.9 % on using all 31 deboning variables. This result suggests that physical characteristics of meat parts are suitable factors for classification of beef by gender.

2 illis, 6 tables, 34 ref

024965   ARORA A A, AGRAWAL S S (Centre for Development of Advanced Computing, Noida, Email: karunesharora@cdac.in) : Comparative analysis of phrase based, hierarchical and syntax based statistical machine translation. J Sci Ind Res 2018, 77(3), 172-5.

Languages have inherent property of tree-based recursive arrangement of phrases and follow a syntactic grammar. Phrase Based Translation is considered state-of-the-art in the field of statistical machine translation, but does not take into account the above mentioned properties of languages. Hierarchical and Syntax based machine translations are aimed to model these properties of languages. English-Hindi language pair, belonging to two different language families needs conversion of Subject-Verb-Object (SVO) structure of English to Subject-Object-Verb (SOV) structure of Hindi. This paper is aimed to perform comparative analysis of these models for this language pair which demands long distance movement of words or phrases.

1 illus, 3 tables, 8 ref

024964   ABIRAMI K R, SUMITHRA M G (Computer Science and Engineering Dep, PSNA Coll of Engineering and Technology, Dindigul- 624 308, Email: ramaabirami1988@gmail.com) : Preventing the impact of selfish behavior under MANET using Neighbor Credit Value based AODV routing algorithm. Sadhana 2018, 43(3), 60.

Mobile Ad hoc Network (MANET) nodes exchange information using the multi-hop wireless communications without the need for any pre-existing infrastructure. Routing protocols of MANET are designed with an assumption that the nodes will cooperate in routing process. To achieve high throughput and reliable communication, the nodes are expected to cooperate with each other. Routing protocol plays a crucial role in an effective communication between nodes and operates on the assumption that the nodes are fully cooperative. Due to the open structure and limited battery-based energy in MANET, some nodes may not cooperate correctly or behave maliciously and such kind of misbehavior impacts the fairness, reliability and efficiency in MANET. Previous work addressed the ways to overcome these kinds of node misbehaviors and attacks. Most of the existing works need time to analyse the neighbor traffic and decide whether a neighbor is behaving maliciously or not. Further, the existing credit-based detection mechanisms may mark a genuine idle node as a malicious node. This work addresses a simple Neighbor Credit Value based AODV (NCV-AODV) routing algorithm for the detection of selfish behavior which avoids such false detection. The proposed idea is implemented in Ad hoc On Demand Distance Vector (AODV) routing protocol and an extensive analysis on the performance of the proposed detection mechanism against the selfish behavior of some MANET nodes are conducted.

6 illus, 1 table, 19 ref

024963   AARTI B, KOPPARAPU S K (Electronics and Communication Dep, SNDT Univ, Mumbai- 400 020, Email: artigauri@yahoo.com) : Spoken Indian language identification: A review of features and databases. Sadhana 2018, 43(3), 53.

Spoken language is one of the distinctive characteristics of the human race. Spoken language processing is a branch of computer science that plays an important role in human–computer interaction (HCI), which has made remarkable advancement in the last two decades. This paper reviews and summarizes the acoustic, phonetic and prosody features that have been used for spoken language identification specifically for Indian languages. In addition, we also review the speech databases, which are already available for Indian languages and can be used for the purposes of spoken language identification.

1 illus, 5 tables, 85 ref

024962   BHUVANESHWARI M, PARAMASIVAN B, KANDASAMY A (Computer Science and Engineering Dep, National Engineering Coll, Kovilpatti- 628 503, Email: itsbhuvana@gmail.com) : Stochastic dynamic programming model for optimal resource allocation in vehicular ad hoc networks. Sadhana 2018, 43(3), 52.

Vehicular ad hoc network (VANET) is an emerging trend where vehicles communicate with each other and possibly with a roadside unit to assist various applications like monitoring, managing and optimizing the transportation system. Collaboration among vehicles is significant in VANET. Resource constraint is one of the great challenges of VANETs. Because of the absence of centralized management, there is pitfall in optimal resource allocation, which leads to ineffective routing. Effective reliable routing is quite essential to achieve intelligent transportation. Stochastic dynamic programming is currently employed as a tool to analyse, develop and solve network resource constraint and allocation issues of resources in VANET. We have considered this work as a geographical-angular-zone-based two-phase dynamic resource allocation problem with a homogeneous resource class. This work uses a stochastic dynamic programming algorithm based on relaxed approximation to generate optimal resource allocation strategies over time in response to past task completion status history. The second phase resource allocation uses the observed outcome of the first phase task completion to provide optimal viability in resulting decisions. The proposed work will be further extended for the scenario that deals with heterogeneous resource class. Simulation results show that the proposed scheme works significantly well for the problems with identical resources.

7 illus, 3 tables, 19 ref

024961   RANI P I, MUNEESWARAN K (Computer Science and Engineering Dep, Mepco Schlenk Engineering Coll, Sivakasi- 626 005, Email: muhilrani@gmail.com) : Emotion recognition based on facial components. Sadhana 2018, 43(3), 48.

Machine analysis of facial emotion recognition is a challenging and an innovative research topic in human–computer interaction. Though a face displays different facial expressions, which can be immediately recognized by human eyes, it is very hard for a computer to extract and use the information content from these expressions. This paper proposes an approach for emotion recognition based on facial components. The local features are extracted in each frame using Gabor wavelets with selected scales and orientations. These features are passed on to an ensemble classifier for detecting the location of face region. From the signature of each pixel on the face, the eye and the mouth regions are detected using the ensemble classifier. The eye and the mouth features are extracted using normalized semi-local binary patterns. The multiclass Adaboost algorithm is used to select and classify these discriminative features for recognizing the emotion of the face. The developed methods are deployed on the RML, CK and CMU-MIT databases, and they exhibit significant performance improvement owing to their novel features when compared with the existing techniques.

8 illus, 11 tables, 27 ref

024960   KHAN M N A, MAHMOOD A (Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Pakistan, Email: dr.naeem@szabist-isb.edu.pk) : A distinctive approach to obtain higher page rank through search engine optimization. Sadhana 2018, 43(3), 43.

Search engine optimization (SEO) pertains to the activity of optimizing individual websites and webpages to get higher page rank in the search results. Websites are ordinarily optimized through back links, while individual webpages are optimized through specific keywords. In this paper, we propose a framework based on set of guidelines for keyword research analysis and back links generation. The proposed framework suggests that webpage content should be based on keywords and the site traffic should be monitored through referrals. We argue that if a website has some prevalent and pertinent keywords in its content and title along with a reasonable amount of back links that help watch the website traffic, then we can get better rank for the website in the search results. The framework also emphasizes that proper keyword selection and link building should be taken into account when developers and designers work on a software development project. The results of the study are reported here.

6 illus, 2 tables, 28 ref

024959   ABRAHAM A, PAPPA N, HONC D, SHARMA R (Applied Electronics & Instrumentation Dep, APJ Abdul Kalam Technological Univ, Kerala, Email: anuj1986aei@gmail.com) : Reduced order modelling and predictive control of multivariable nonlinear process. Sadhana 2018, 43(3), 41.

In this paper, an efficient model-predictive control strategy that can be applied to complex multivariable process is presented. A reduced order generalized predictive algorithm is proposed for online applications with reduction in complexity and time elapsed. The complex multivariable process considered in this work is a binary distillation column. The reduced order model is developed with a recently proposed hybrid algorithm known as Clustering Dominant Pole Algorithm and is able to compute the full set of dominant poles and their cluster centre efficiently. The controller calculates the optimal control action based on the future reference signals, current state and constraints on manipulated and controlled variables for a high-order dynamic simulated model of nonlinear multivariable binary distillation column process. The predictive control algorithm uses controlled auto-regressive integrated moving average model. The performance of constraint generalized predictive control scheme is found to be superior to that of the conventional PID controller in terms of overshoot, settling time and performance indices, mainly ISE, IAE and MSE.

9 illus, 10 tables, 31 ref

024958   DAISY V R, NIRMALA S (Electrical and Electronics Engineering Dep, Paavai Engineering Coll, Namakkal- 637 018, Email: roynadaisy@gmail.com) : Stability-integrated Fuzzy C means segmentation for spatial incorporated automation of number of clusters. Sadhana 2018, 43(3), 40.

Fuzzy C Means clustering, one of the predominant segmentation algorithms, requires prior knowledge of number of clusters in the image and is sensitive to noise and outliers. Determining the number of clusters and including spatial information to basic Fuzzy C Means clustering are done in numerous ways. Literature reveals that either number of clusters is defined or spatial information is incorporated. In the proposed work, spatial information and cluster determination are integrated based on the concept of stability. Implementation of split and merge algorithm to find the number of clusters is done based on the modified Sylvester’s theorem in the context of positive definite functions. Experiments are performed on synthetic and real images and the number of clusters determined is validated using validation indices. Results show that correct clusters are classified with robustness to noise.

8 illus, 3 tables, 31 ref

024957   SINGH B, KAUR M (Computer Science and Engineering Dep, Sant Longowal Institute of Engineering and Technology, Longowal- 148 106, Email: birmohans@gmail.com) : An approach for classification of malignant and benign microcalcification clusters. Sadhana 2018, 43(3), 39.

The only reliable and successful treatment of breast cancer is its detection through mammography at initial stage. Clusters of microcalcifications are important signs of breast cancer. Manual interpretation of mammographic images, in which the suspicious regions are indicated as areas of varying intensities, is not error free due to a number of reasons. These errors can be reduced by using computer-aided diagnosis systems that result in reduction of either false positives or true negatives. The purpose of the study in this paper is to develop a methodology for distinguishing malignant microcalcification clusters from benign microcalcification clusters. The proposed approach first enhances the region of interest by using morphological operations. Then, two types of features, cluster shape features and cluster texture features, are extracted. A Support Vector Machine is used for classification. A new set of shape features based on the recursive subsampling method is added to the feature set, which improves the classification accuracy of the system. It has been found that these features are capable of differentiating malignant and benign tissue regions. To investigate the performance of the proposed approach, mammogram images are taken from Digital Database for Screening Mammography database and an accuracy of 94.25 % has been achieved. The experiments have shown that the proposed classification system minimizes the classification errors and is more efficient in correct diagnosis.

8 illus, 13 tables, 56 ref

024956   PATIL H V, SHIRBAHADURKAR S D (Electronics and Telecommunication Dep, NDMVPS’s KBT COE, Nashik- 422 013, Email: hemant.devkrupa@gmail.com) : FWFusion: Fuzzy Whale Fusion model for MRI multimodal image fusion. Sadhana 2018, 43(3), 38.

Medical treatment and diagnosis require information that is taken from several modalities of images like Magnetic Resonance Imaging (MRI), Computerized Tomography and so on. The information obtained for certain ailments is often incomplete, invisible and lacking in consistent scanner performance. Hence, to overcome these issues in the image modalities, image fusion schemes are developed in the literature. This paper proposes a hybrid algorithm using fuzzy concept and a novel P-Whale algorithm, called Fuzzy Whale Fusion (FWFusion), for the fusion of MRI multimodal images. Two multimodal images from MRI (T1, T1C, T2 and FLAIR) are considered as the source images, which are fed as inputs to a wavelet transform. The transform utilized converts the images into four different bands, which are fused using two newly derived fusion factors, fuzzy fusion and whale fusion, in a weighted function. The proposed P-Whale approach combines Whale Optimization Algorithm (WOA) and Particle Swarm Optimization (PSO) for the effective selection of whale fusion factors. The performance of FWFusion model is compared to those of the existing strategies using Mutual Information (MI), Peak Signal-to-Noise Ratio (PSNR) and Root Mean Squared Error (RMSE), as the evaluation metrics. From the mean performance evaluation, it is observed that the proposed approach can achieve MI of 1.714, RMSE of 1.9 and PSNR of 27.9472.

8 illus, 1 table, 31 ref