042630   EL-MANCY E M (Basic Science Dep, Jouf Univ, Sakaka, Saudi Arabia, Email: elmancy. elmancy@yahoo.com ) : Histopathological and ultrastructural changes induced in the renal cortex of male rats by gibberellic acid. Indian J Sci Technol 2020, 13(1), 70 – 84.

The present study was designed to evaluate the toxic effect of GA3 on the renal cortex of rats and to assess the possibility of recovery after GA3 withdrawal. Rats (n = 50) were classified into 5 groups: group 1 (control) received no treatment, animals belonging to group 2 and group 3 were respectively given GA3 at doses of 100 and 200part per million (ppm) daily for eight weeks in drinking water. Animals of recovery groups (group 4 and group 5) were remained for eight weeks without treatment after receiving 100 and 200 ppm of GA3 in drinking water for eight weeks respectively. Rats were dissected; kidney samples were collected and processed for histopathological and ultrastructural studies. The renal cortex of GA3-treated rats exhibited its apparent toxic effect on renal corpuscles and renal convoluted tubules associated with fibrosis. These observations confirmed by the ultrastructure examination of renal cortical tissues. The Renal cortex from animals treated with 200 ppm GA3 revealed more severe structural changes. However, eight weeks of GA3 withdrawing has resulted in some regression of the pathological changes. GA3 has dose-dependent toxic effects. While stop giving of GA3 for eight weeks revealed incomplete recovery of its harmful effects. Therefore, exposure to GA3 should be limited.

5 illus, 50 ref

042629   CALUBAQUIB J B, SUYU M C (Cagayan State Univ-Andrews Campus, Caritan, Tuguegarao City, Cagayan, 3500, Philippines, Email: jb_120771@csu.edu.ph ) : Proximate composition of fortified filipino snacks for picky eaters. Indian J Sci Technol 2020, 13(1), 61 – 9.

The study aimed to determine the nutritive values of fortified Filipino snacks and to calculate the calorie value of the energy-yielding nutrients. The Official Method of Analysis of Association of Official Analytical Chemists was used to analyze the proximate composition. The calorie content was calculated by the use of specific energy factors of 4:9:4 for proteins, fat, and carbohydrates, respectively. The majority of the food samples showed significant (P < 0.05) variations among the means concerning proximate composition. The highest protein was found in Moringa Sweet Potato Tuile, it can replace animalbased street foods. The moisture content of Saba-Potato Halaya was the highest and found lowest in Moringa Polvoron. The dry nature of Moringa Polvoron can prolong its shelf-life. It can substitute candies and gummies. The ash content was found highest in Moringa-Sweet Potato Tuile (MST). This can be associated with the mineral-dense Moringa and sweet potato. MST can be a healthier alternative for commercial pastries. The crude fiber content was again observed rich in MST. The Moringa and sweet potato are good fiber sources. MST is a healthier option than any fiber-rich junk food. Crude fat content was highest in Banana Blossom Bar. This snack can better substitute chocolate-flavored bars. The Jute-Spinach PastiYema was found richest with carbohydrates. It can be a healthier alternative for chocolate or marshmallow. All fortified snack samples are healthy calorie-containing foods suitable for picky-eating children. If sufficiently consumed, these healthy snacks may contribute to the nutritional requirement of picky-eating children. This knowledge can be used to produce greener foods for school canteens in the Northern Philippines. 

2 tables, 24 ref

042628   SOLANGI J (Media & Communication Studies Dep, Sindh Univ, Jamshoro, Sindh, Pakistan, Email: alam.solangi@ usindh.edu.pk ) : Rising tendency of journalism practised on social media sites. Indian J Sci Technol 2020, 13(1), 51 – 60.

The motive of this research study is to evaluate the influence and attractiveness of Social Networking Sites (SNSs) in the amidst the full time working journalists and the part time media practitioners, located in Hyderabad and Karachi practicing on SNSs in their professional field of work. This study examines individual approach, comfort ability, usefulness, and inclination towards the most popular SNSs. The statistics of this research work were congregated through Web-based Questionnaire Survey. That was dispended among the journalists of Hyderabad and Karachi region in Sindh Province, Pakistan. The data were collected through an online Google Docs form out of 386,309; valid questioners were selected for this research and evaluated in SPSS Software. This research work has focused on acceptance of the Technology Acceptance Model (TAM) proposed by Davis (1986) for diversified description of information system and communication technologies. This research examines individual inclination towards Social Media in a Media Profession. The pronouncement has been shown in Tables and then illustrated and interpreted to perceive the SNSs e.g. Facebook, Twitter, Instagram, Whatsapp, etc. and their acceptance and adoption by full time journalists and part time media practitioners. In this approach, it was recognized that the journalists have a great inclination towards SNSs which enables them to exchange information promptly with ease and confidently practice in the field of journalism. In the era of technology, SNSs like; facebook, Instagram, Bebo, Twitter, and Whatsapp are widely used by professional journalists as well as active citizens for journalistic purposes which highlight the untold stories. 

1 illus, 2 tables, 14 ref

042626   MANZANO JR. V J P, INES A V M (Agricultural and Biosystems Engineering Dep, Mariano Marcos State Univ, City of Batac 2906, Ilocos Norte, Philippines, Email: jemlyra@yahoo.com ) : Downscaling seasonal climate forecasts for risks management of rice production in the Philippines. Indian J Sci Technol 2020, 13(1), 23 – 39.

This study is centered on the potential use of a dynamic seasonal climate forecast for informing climate risk management in Central Luzon, Philippines to improve rice productivity and resilience. Specifically, we seek to test the downscalibility of the seasonal climate forecasts in the region using a multi-variate spatio-temporal downscaling technique, understand and assess the predictability of rice yield at selected growing areas in the Philippines, and provide guidance on how to develop agricultural risk management strategies. The coupled Global Circulation Model (GCM) CFSv2 was used to evaluate the utility of MJJA (May-June-JulyAugust) rainfall forecasts for risk management of rice production in Central Luzon, Philippines. We used a non-homogeneous hidden Markov model (NHMM) to downscale and simulate the GCM forecasts to selected weather stations in the region. On the other hand, we evaluated the skill of the climate forecasts for predicting crop yields. The simulated rainfall was used to drive the rice models set up in DSSATv4.5. Other weather variables needed by DSSAT were generated and conditioned on the occurrence of rainfall based on NHMM rainfall simulation. Simulated rice yields obtained from these models using observed (i.e., simulated by observed weather) and conditioned rainfall (i.e., NHMM downscaling) serve as a baseline for evaluating yields. We also performed a sensitivity analysis to assess appropriate planting windows for the target season for risk management. Inter-annual variability of rainfall is moderately simulated, with a skill (r) of 0.41, suggesting that NHMM was fairly successful downscaling rainfall from the regional scale given the predictive nature of the predictor, at three months lead time. The observed MJJA mean rainfall from the six stations falls at around 56 % within the interquartile ranges of simulated rainfall, which indicates reasonable skill of the NHMM downscaling CFSv2’s MJJA rainfall hindcasts. Simulated yield was found comparable with the observed at 5 % level of significance using t-test (p > 0.05). The correlations between observed and predicted yields are equal to 0.56. This indicates that the models can represent about 31.36 % of the inter-annual variability of the yields of rice, albeit of the three months lead-time of the CFSv2 hindcasts. It suggests a reasonable performance of the models in simulating rice yield using the NHMM generated climate information. Climatologically, the best planting and sowing windows for rice in the study area is on the first week of May. This can be adjusted by using seasonal climate forecasts information. Harvest period should not cross over in the month of September to avoid exposure to heavy typhoons. Sensitivity analysis showed that planting rice earlier than the usual planting windows practiced by the farmers could improve resilience to climate risks. Managing the variance of this management window, however, is of paramount importance, which can be informed by skillful climate forecasts.

12 illus, 22 ref

042625   MAHA FR, ALI S I, JUMANI A K, KHAN M O (Computer Science Dep, ILMA Univ, Karachi, Pakistan, Email: awaisjumani@ yahoo.com) : ERP system implementation: Planning, management, and administrative issues. Indian J Sci Technol 2020, 13(01), 1 – 22.

In the modern computing and business world computerization, automation and Enterprise Resource Planning (ERP) system has become the backbone in both public and private sector organizations throughout the world. IT departments in organizations are playing major role in controlling the financial activities, procedures, business, and administrative operations. In this study, we have analyzed and examined the major issues which an organization could face while starting the ERP project. This study will also discuss the significant elements which are crucial for an organization when they move towards the ERP system. Adopting the ERP system for an organization is not only a highly difficult task, but is also an expensive process. Therefore, the organization cannot afford the failure of this implementation plan. Moreover, this study is also about the solutions regarding management and administrative plans as well as it helps to design comprehensive controls and procedures for the ERP system implementation project. The issues in the structure, functions, culture, human resource, and procedures of organizations are focused on the study and discussion is made to find out the solutions to control these issues during the implementation process. The study covers the issues regarding implementation plans, project management, and selection or designing of these systems and determines the role of different teams and workforce during the implementation process and after carrying out the process in the business environment.

4 illus, 1 table, 30 ref

044470   SHERIFF M Z, PONRAJ A P (Meenakshi Academy of Higher Education and Research, Chennai, Email: zaheer61@gmail.com) : H−hyperconnected spaces. J Comp & Math Sci 2020, 11(4), 12-7.

The aim of this Study is to analysis the ℋ −hyperconnected spaces and in ℋ − hyperconnected spaces properties of various sets are established. ℋ − hyperconnected  spaces and T_ℋ − spaces are defined. ℋ −submaximal spaces and strong $\mathrm{\beta }$− ℋ − open sets are characterized.

9 ref

040359   SINGH B, PAL S, SHRIVASTAVA A (Electrical Engineering Dep, IIT Delhi, New Delhi 110 016, Email: rewa.ashish@gmail.com) : A universal input PFC CSC converter in low power consumer lighting applications. IETE Tech Rev 2020, 37(4), 410–7.

A power factor corrected (PFC) Canonical Switching Cell (CSC) converter is proposed for low power consumer light-emitting diode (LED) lighting applications. The proposed CSC converter is intended to operate in discontinuous inductor current mode (DICM) to realize improved power quality performance. In low power consumer lighting applications, the CSC converter is more suitable due to its many benefits such as high energy storing capability, high input and low output impedance as compared to other buck-boost converters. This paper describes the different performance parameters of the proposed converter. Application of lighting load is also examined in view of achieving improved power quality over the wide input AC mains voltage. The measured converter efficiency of a laboratory prototype is found to be 93.8 % and total harmonic distortion (THD) of the input current is observed only 6.52 % at 230 V AC mains for a prototype of 50 W. Due to less switching losses, the proposed converted has shown much-improved results as compared to the conventional buck-boost converter.

8 illus, 3 tables, 22 ref

040358   PAN X, ZHANG S, GUO W, ZHAO X, CHUANG Y, CHEN Y, ZHANG H (Taizhou Univ, Taizhou 318000, People’s Republic of China, Email: tzczsq@163.com) : Video-based facial expression recognition using deep temporal–spatial networks. IETE Tech Rev 2020, 37(4), 402–9.

It’s a challenging task to recognize facial expression in video sequences due to the gap between the hand-crafted features and the subjective emotions. To bridge the gap, this paper proposes a novel method of video-based facial expression recognition using deep temporal–spatial networks. The proposed method firstly employs multimodal deep convolutional neural networks (CNN), including the spatial CNN network and the temporal CNN network, to extract high-level spatial and temporal features in video sequences, respectively. The temporal–spatial CNN networks are fine-tuned on target video facial expression data from a pre-trained CNN model. Specially, the spatial network is used to learn deep spatial features from the static expression images in a video. Likewise, the temporal network is adopted to learn deep temporal features from the produced optical flow images between multiple frames in a video. Then the extracted spatial and temporal features are combined in a fusion network to conduct video-based facial expression classification tasks. Extensive experiments on two public video-based facial expression datasets, i.e. the BAUM-1s and RML database, demonstrate the promising performance of the proposed method, outperforming the-state-of-the-arts.

7 illus, 3 tables, 26 ref

040356   GUPTA V, KAPUR S, SAURABH S, GROVER A (ECE Dep, IIIT, Delhi - 110 020, Email: sneh@iiitd.ac.in) : Resistive random access memory: A review of device challenges. IETE Tech Rev 2020, 37(4), 377–90.

With scaling, existing charge-based memory technologies exhibit limitations due to charge leaking away easily in a smaller device. Therefore, non-charge based memory technologies such as Resistive Random Access Memory (RRAM) become promising for future applications. RRAM is not only more scalable, but is typically faster and consumes less power than the existing memory technologies. However, RRAM suffers from higher impact of variations and reliability issues. In this review paper, we explain the basic aspects of RRAMs, highlight their advantages and elucidate challenges involved in replacing the existing memory technologies with RRAMs.

6 illus, 3 tables, 93 ref

040353   MISHRA S K, SAHOO S, SAHOO B, JENA S K (Computer Science & Engineering Dep, National Institute of Technology, Rourkela, Odisha - 769001, Email: skmishra.nitrkl@gmail.com) : Energy-efficient service allocation techniques in cloud: A survey. IETE Tech Rev 2020, 37(4), 339–52.

The demand for cloud computing infrastructure is increasing day by day to meet the requirement of small and medium enterprises. The data center-centric cloud technology has a high share of energy consumption from the IT-industry. The amount of energy consumption in a data center depends on the allocation of user service requests to virtual machines running on the different host. Minimization of energy consumption in the data center is a significant issue and addressed by optimal allocation of cloud resources. In this paper, we have discussed how service allocation strategies have been used to optimize the energy consumption in a cloud system. A generalized system architecture is presented based on which we define the service allocation problem and energy model. Further, we present the taxonomy of various energy-efficient resource allocation techniques found in the literature. In the end, various research challenges related to the energy-efficient service allocation in cloud are discussed.

5 illus, 8 tables, 40 ref

040352   GHOSH J (National Research Tomsk Polytechnic Univ, Tomsk, Russia, Email: joydev.ghosh.ece@gmail.com) : Energy efficiency analysis by game-theoretic approach in the next generation network. IETE Tech Rev 2020, 37(4), 329–38.

This paper presents a game-theoretic scheme with anti-coordinated players by incorporating adaptation of femto base station (FBS) transmit power, attenuation of interference and utility function for open access mode and closed access mode, respectively. The deployment of femtocells in the networks is to produce improved energy efficiency (EE) and optimized response of payoff function. Additionally, the operating principle of the spectrum sharing scheme has been discussed in which FBS as a player acquire knowledge from utility responses of their strategic communications and revise their strategies at each level of the game process. Here, an FBS is regarded as a player in the game to select those users who are satisfied to a greatest extent and besides an FBS plays a role of mentor. Thereafter, the equilibrium concept has been invoked to aid the anti-coordinated players for the strategies. Finally, validated the simulation results are with its rarely studied extension in cognitive-femtocell networks.

7 illus, 13 ref

040350   HOLLA K S, JIDESH P, BINI A A (Mathematical and Computational Sciences Dep, National Institute of Technology Karnataka, Srinivasanagar, Mangalore - 575 025, Email: jidesh@nitk.edu.in) : Multiple-coil magnetic resonance image denoising and deblurring with nonlocal total bounded variation. IETE Tech Rev 2020, 37(3), 309–14.

One of the complex tasks in image restoration is to restore images under data correlated noise contaminations. In real-time medical imaging scenarios, such as Magnetic Resonance (MR), Ultrasound, Computed Tomography(CT) etc, it is observed that, the data of interest is severely degraded with data dependent noise interventions. A Nonlocal Total Bounded Variation (NLTBV) approach is being proposed in this paper to denoise as well as deblur multiple-coil MR images corrupted by non-central Chi distributed noise and linear Gaussian blur. The energy functional for the restoration model is derived by applying the Maximum A Posteriori (MAP) estimator on the Probability Density Function (PDF) of the non-central Chi distribution. The numerical implementation is performed using the splitBregman iterative scheme to improve the convergence rate. The proposed model is compared with the other state of the art models in terms of both visual and statistical quantifications to demonstrate it’s performance.

4 illus, 2 tables, 24 ref

040339   MURUGAN D, MAURYA A K, GARG A, SINGH D (Electronics and Communication Engineering Dep, Indian Institute of Technology, Roorkee - 247 667, Email: dharmfec@gmail.com) : A framework for high-resolution soil moisture extraction using SCATSAT-1 scatterometer data. IETE Tech Rev 2020, 37(2), 147–56.

Retrieving soil moisture with low-resolution data is quite a challenging task. For retrieving the soil moisture, knowledge of backscattered signal from bare soil and crop-covered soil is very much important, which is difficult to obtain from the low-resolution data. This problem may be solved by using optical data. Therefore, in this paper a novel approach is proposed to classify translucent and non-transparent vegetation areas using optical sensor data, which is further used in the estimation of soil moisture. The soil moisture product is then downscaled from 25 km to $~$ 5.6 km using vegetation temperature condition index which is computed using MODIS data. Obtained results show that this approach is able to retrieve soil moisture successfully and is able to downscale soil moisture data into higher resolution product.

10 illus, 1 table, 23 ref

040330   KAR M, KUMAR A, NANDI D, MANDAL M K (Physics Dep, National Institute of Technology, Durgapur, West Bengal, Email: madhumitakar2007@gmail.com) : Image encryption using DNA coding and hyperchaotic system. IETE Tech Rev 2020, 37(1), 12–23.

The paper proposes a grey scale image encryption scheme using six-dimensional Lorenz chaotic system. The key generating system uses a 32 character (256 bits) key as input. The system uses simple modular arithmetic and bitwise XOR operations followed by coupling a series of Lorenz six-dimensional systems to generate the key-stream. This generated key stream is used in the encryption and decryption algorithm of the plain image. The basic permutation and diffusion architecture, using the fundamental properties of modular arithmetic, bitwise XOR operations and DNA encoding/decoding technique, are executed to confuse the relationship between plain image and the ciphered image. The experimental results and security tests confirm that the proposed image encryption algorithm possess high security and can be a good candidate for practical image encryption.

5 illus, 9 tables, 24 ref

040309   KUMAR P, DWARI S, UTKARSH, SINGH S, KUMAR J (Institute for Plasma Research, Gandhinagar, Gujarat, Email: jitu.kumar87@gmail.com) : Investigation and development of 3d printed biodegradable pla as compact antenna for broadband applications. IETE J Res 2020, 66(1), 53–64.

This paper presents the feasibility of biodegradable Polylactic Acid (PLA) for the creation of 3D structure as a radiator. Biodegradable PLA is a special type of polymer having a dielectric constant (ε_r) of 3.45 with loss tangent (tan δ) of 0.05 which is made from renewable resources instead of nonrenewable petroleum-based resources. Three conventional Dielectric Resonator Antennas (DRAs), i.e. Cylindrical DR Antenna (CDRA), Rectangular DR Antenna (RDRA), and Triangular DR Antenna (TDRA) with supporting pillars have been developed and investigated for broadband applications. These three different structures are used to validate the features of PLA for antenna applications. Proposed antennas cover wide impedance bandwidth of 74.54 %, 71.36 %, and 69.05 % (|S₁₁| < −10 dB) for CDRA, RDRA, and TDRA, respectively. Measured results are correlated with simulations. The average peak gain of proposed antennas is more than 4 dBi within operating band. The fabricated antenna possesses compact size with light-weight and cost-effective feature. Thus, proposed antennas can use for a variety of wireless applications such as weather monitoring, air traffic control, scanning & discrimination, mobile service, radio navigation, and many other applications of C-band, X-band, and Ku-band.

15 illus, 4 tables, 18 ref

040301   BHUNIA P, BASU I, DE M (Botany Dep, Gurudas Coll, Kolkata - 700 054, Email: mituaswb@gmail.com) : Computer mediated intervention for individuals with autism spectrum disorder (asd): A pilot study using computer games. Harvest 2020, 5(1), 21-32.

Insistence of the child on sameness is a core feature of autism spectrum disorder. Structured computer programs help autistic children to overcome their over stimulation selectiveness through practice or sufficient experience. In recent years there is an increase of High-Tech Alternative and Augmentative Communication (AAC) devices. In order to use these devices efficiently an individual with autism must develop sufficient skills like pressing space bar or enter button, visual tracking, scrolling, making choices etc. These skills maybe taught and practiced with computer games. Nowadays computer games have become a tool to communicate, teach, and influence attitudes and behaviour. In this present investigation 3 (three) computer games were used to develop basic computer skills among individuals with autism over a six (6) month study period. It was observed that by using computer games most of the participants developed considerable computer operating skills. Even though the pace of learning differed among the participants it was apparent that all they enjoyed the computer mediated intervention sessions.

6 illus, 20 ref

040272   GHOSH S, DASGUPTA R (Homi Bhabha National Institute, Khurda– 752 050, Odisha, Email: shyamasree_b@yahoo.com) : Nanoinformatics: An emerging bio-science. J Appl Zool Res 2020, 31(1), 16-23.

Nanoinformatics is an emerging science developing over the last two decades and finds utmost importance due to the ever expanding field of surface engineering of nanoparticles with desired and improved properties in drug delivery, synthesis of newer nanoparticles, green synthesis of nanoparticles and or their new applications towards human health, development and environment. The term was coined in 2007 and it has found applications in computational design of safer, biocompatible and personalised drugs, nanoparticle formulation, quantitative structure activity relationship (nanoQSAR) and nanoparticle assembly, modelling, simulation, predicting particle effects in infectious disease and malignant diseases like cancer, nanocurration, and environmental risk assessment. With the advancement of DNA and RNA based therapeutics, nanoinformatics has been applied to DNA and RNA computing in diseases. Several machine learning tools and algorithims are having application in Nanoinformatics. In this review, we highlight the importance of nanoinformatics and its application in therapeutics.

1 illus, 43 ref

039736   UPLAONKAR D S S (Agricultural Sciences Univ, Karnataka - 580 005, Email: uplaonkarshilpa16@gmail.com) : Usage and awareness of OPAC by Faculty of University Library, University of Agricultural Sciences, Dharwad. Libr Prog 2020, 40(1), 87-91.

OPAC is an interactive search module of an automated library management system. Any type of reading materials is searched directly from the managed database of the library. Catalogue is the face of the libraries and the Online Public Access Catalogue (OPAC) changed the conventional card catalogue structure. This paper presents and analysis online public access catalogue services provided by university library, university of agricultural sciences, Dharwad. It also discusses the purpose, frequency, awareness on use of OPAC. The result of the study shows that the faculties of UASD are aware about use of OPAC and regularly using to trace the library holdings by Title, Author, Subject, etc.

5 tables, 9 ref

039734   DHIMAN D A K, JOSHI S (Gurukul Kangri Univ, Uttarakhand - 249 404, Email: akvishvakarma@rediffmail.com) : Use of social networking Sites/Web 2.0 tools: A study of Central Universities of Delhi. Libr Prog 2020, 40(1), 65-72.

Social networking sites (SNSs) / Web 2.0 tools are the results of advancement in information technology which are gaining their importance not only in social life but also showing their presence in educational organizations. It is seen, now a day's, everyone is connected with each other by means of various social networks like Twitter, Facebook, LinkedIn, Blogs, etc. which is an effective medium to share the knowledge and skills of the users. SNSs are also offering the opportunity to reach out to its clients. Hence, the number of universities which adopt SNSs are increasing. The present study is an investigation of five central universities of Delhi which are making use of social networking tools / web2.0 tools in one or other ways in their websites.

2 illus, 5 tables, 10 ref

039733   PRAKASH S, SHARMA D S K (Mewar Univ, Rajasthan - 312 901, Email: sanjaysharmalib@rediffmail.com) : Electronic resources (ER) for information retrieval of medicinal and aromatic plants (MAPs) research in the digital era. Libr Prog 2020, 40(1), 55-64.

With the growing worldwide in internet conservation, cultivation and use of medicinal, aromatic and other related groups of plants, there has been a four-fold increase in the volume of literature published on these crops during last two decades. This dynamic scenario demands constant updated inflow, documentation and management of accrued of knowledge, which is now-a-days largely available on electronic media and can be accessed through E-journals, scholarly databases, information gateway internet, E-Books, E-magazine and E-News letters. The current issues in MAPs research largely revolve around the production, post harvest management, value–chain alignments, profitability, efficiency and sustainability. To meet the challenges and requirements of globalization, intellectual property rights, agri-export, market intelligence and related issues adequately and successfully, developing countries like India must reorient their R&D priorities on a real time scale for which toolsfor fast retrieval of information must be developed for which refined on priority. An organized method for retrieval of nascent information is likely to play a very crucial role in this mission. But most of the information is highly scattered in various kind of information resources and their retrieval is so complex and cost intensive that it may not be affordable by every developing country. Therefore, efforts have been made in this paper to identify and list the electronic resources which are exclusive in nature is and are freely available on internet.

3 tables, 24 ref

039731   SANTOSH D, S K V, P A S (Library and Information Science Dep, Dr. Babasaheb Ambedkar Marathwada Univ, Maharashtra - 431 004, Email: khapardevaishali@gmail.com) : Mapping of world publications: Sydenham chorea disease. Libr Prog 2020, 40(1), 34-43.

The present paper focuses on Mapping of World Publications: Sydenham Chorea Disease. Which has given on PubMed database for during the year 2000 to 2018? There are total 9799 documents on Sydenham Chorea Disease. It discusses on ascertain the Sydenham chorea research of documents, ranking of most prolific authors, institution-wise distribution of publications. Concept mapping is a general method, it is particularly useful for helping social researchers and research teams develop and detail ideas for research and, it is especially valuable when researchers want to involve relevant stakeholder groups in the act of creating the research project. Although concept mapping is used for many purposes strategic planning, product development, market analysis, decision making, measurement development we concentrate here on its potential for helping researchers formulate their projects. The main objective of the study is to analyze the to ascertain the Sydenham chorea research output in world during 2000 to 2018. The specific objectives of the study are, Publication output, Share and Rank of Top 25 Most Productive countries in Sydenham chorea research during 2000-2018. etc.

4 illus, 6 tables, 9 ref

039730   SHEHU A B, SINGH K P, OYIZA H O (Library and Information Science Dep, Delhi Univ, Delhi –110 007, Email: Kpsingh330@gmail.com) : Present status of information and communication technology in Nigerian academic libraries: A review of literature. Libr Prog 2020, 40(1), 25-33.

Application of information and communication technologies to academic libraries has brought remarkable improvement to various services offered by the library, ICT has improved efficiency and influenced changes from storehouses to knowledge management centers, however application of ICT in developing economies like Nigeria is still in budding stage, application and utilization of ICT is marred with various challenges, this paper attempts to review the status of ICT in academic libraries of Nigeriakeeping in view benefits, challenges, ICT competence of library and information science professionals. itis hoped that the present studies will guide the library and information professional and management staff on effective application of ICT, understanding the need and relevance of ICT skill acquisitions by the library and information science professionals.

ref 40

039220   JOE A A F, GOPAL A, PANDIAN R (Sathyabama Institute of Science and Technology, Tamil Nadu, Email: annefrankjoe@gmail.com) : Performance evaluation of chemometric prediction models - Key components of wheat grain. J Sci Ind Res 2020, 79(02), 148-52.

The present study was aimed to evaluate the accuracy of using near-infrared spectroscopy (NIRS) for predicting protein, moisture, starch and ash content values of wheat. The physiochemical properties of wheat were predicted using twelve prediction models of preprocessing coupled with regression tools. The performance measure of SVM aided with extended multiplicative scatter correction gave confident prediction results of protein, moisture, ash and starch content with R² values of 0.989, 0.987, 0.976, 0.998 and RMSECV values of 0.263, 0.285793, 0.369 and 0.03 respectively. These results indicate the practical applicability of NIRS in wheat grain quality profiling.

2 illus, 2 tables, 16 ref

039212   MADHUBALAN S, PADMA S, ABDUL SHABEER H (EEE Dep, Sona Coll of Technology, Tamil Nadu- 636005, Chennai, Email: madhubalans@gmail.com) : Stability enhancement of power system with UPFC using hybrid TLBO algorithm. J Sci Ind Res 2020, 79(01), 112-5.

Power sector's complexity has been increasing due to rising demand—distributed generation and deregulation have greatly increased the complexity of the power system. Flexible Alternating Current Transmission System (FACTS) devices improve the quality of power by increasing the power transfer capability. This paper proposes an optimal power flow analysis using a Modified Teaching Learning Based Optimization (MTLBO) algorithm followed by an optimal placement of UPFC in the system. The proposed analysis has been validated and implemented on an IEEE 30 bus system.

3 illus, 2 tables, 8 ref

039210   ALAMINOS D, ESTEBAN I, SALAS M B, CALLEJON A M (Mechanical Engineering and Energy Efficiency Dep, Málaga Univ, Spain, Email: jasantos@ualg.pt) : Quantum neural networks for forecasting inflation dynamics. J Sci Ind Res 2020, 79(01), 103-6.

Inflation is a key indicator in the economy that measures the average level of prices of goods and services, being an important ratio in public and private decision-making, so predicting it with precision has always been a concern of economists. This paper makes inflation predictions with different time horizons applying quantum theory through Quantum Neural Networks. The results obtained teach that Quantum Neural Networks overcome the predictive power of the existing models in the previous literature and yields a low-level of errors when predicting any change in the direction of the forecast trend.

1 illus, 1 tables, 13 ref

039109   PEREZ T A V, LOPEZ J M H, BARBOSA E M, ALONSO B D C (Faculty of Physical Sciences Mathematics Benemérita Univ, Mexico, Email: antonio_2827@hotmail.com) : Study of CT images processing with the implementation of MLEM algorithm using CUDA on NVIDIA'S GPU framework. J Nucl Phys Mat Sci Rad A 2020, 7(2), 165–71.

In medicine, the acquisition process in Computed Tomography Images (CT) is obtained by a reconstruction algorithm. The classical method for image reconstruction is the Filtered Back Projection (FBP). This method is fast and simple but does not use any statistical information about the measurements. The appearance of artifacts and its low spatial resolution in reconstructed images must be considered. Furthermore, the FBP requires of optimal conditions of the projections and complete sets of data. In this paper a methodology to accelerate acquisition process for CT based on the Maximum Likelihood Estimation Method (MLEM) algorithm is presented. This statistical iterative reconstruction algorithm uses a GPU Programming Paradigms and was compared with sequential algorithms in which the reconstruction time was reduced by up to 3 orders of magnitude while preserving image quality. Furthermore, they showed a good performance when compared with reconstruction methods provided by commercial software. The system, which would consist exclusively of a commercial laptop and GPU could be used as a fast, portable, simple and cheap image reconstruction platform in the future.

5 illus, 1 tables, 37 ref

039081   ZHU G, WANG Y, WANG Q (Northwestern Polytechnical Univ, Xi’an- 710 072, Email: flyingscott@nwpu.edu.cn) : Robust conditional probability constraint matched field processing. Indian J Geo-Mar Sci 2020, 49(2), 192-200.

In order to improve the robustness of Adaptive Matched Field Processing (AMFP), a Conditional Probability Constraint Matched Field Processing (MFP-CPC) is proposed. The algorithm derives the posterior probability density of the source locations from Bayesian Criterion, then the main lobe of AMFP is protected and the side lobe is restricted by the posterior probability density, so MFP-CPC not only has the merit of high resolution as AMFP, but also improves the robustness.To evaluate the algorithm, the simulated and experimental data in an uncertain shallow ocean environment is used.The results show that in the uncertain ocean environment MFP-CPC is robust not only to the moored source, but also to the moving source. Meanwhile, the localization and tracking is consistent with the trajectory of the moving source.

9 illus, 1 table, 17 ref

039080   ZUBIER K M (Marine Physics Dep, King Abdulaziz Univ, Jeddah- 215 89, Email: kzubier@kau.edu.sa) : Using an artificial neural network for wave height forecasting in the red sea. Indian J Geo-Mar Sci 2020, 49(2), 184-91.

Artificial Neural Networks (ANNs) are widely used in the field of wave forecasting as data-based soft-computing techniques that do not require prior knowledge regarding the nature of the relationships between the forecasted waves and the controlling physical mechanisms. Among ANN-techniques is the Nonlinear Auto-Regressive Network with eXogenous inputs (NARX), based on which two models were developed in this study to predict the significant wave heights in Eastern Central Red Sea for the next 3, 6, 12 and 24 h. The two NARX-based models differ only by the inclusion of the variance between wind and wave directions in one model and not in the other. Both models have shown the ability to efficiently predict the significant wave heights up to 12 hours in advance. However, the out performance of the model that included the difference between wind and wave directions indicated the significance of the inclusion of such an input term.

8 illus, 1 table, 47 ref

039078   KALPANA A, JAYASHREE M (Chemistry Dep, Sri Sarada Coll for Women, Salem- 636 016, Email: kalpanaanbarasu@gmail.com) : In silico analysis of the efficacy of some natural compounds as antituberculosis agents. Indian J Chem Sect- A 2020, 59A(2), 207-13.

Tuberculosis (TB) remains a disease of global importance with approximately two million deaths annually worldwide. Effective treatment of TB has been hampered by the emergence of drug resistant strains of Mycobacterium tuberculosis. Natural products have a proven global history of treating TB diseases and ailments. Available vast reservoir of chemically diverse natural products that provide new templates for drug design can be scrutinized and the most efficient may be chosen by molecular docking studies with the TB proteins. In the present study, an attempt has been made to findout a potential natural product to inhibit M. tuberculosis – proteinkinase B (PknB) protein by molecular docking method. Docking has been performed for around 40 natural products against M. tuberculosis – PknB protein target to determine their potentiality against TB diseases. The anti-TB ability has been analysed in terms of binding energy. The results indicate that 80 % of the natural products (B.E ≥ -7 kcal/mol) under study, exhibit good anti-TB activity. It is known that most of the natural product under study is found to possess greater binding activity than that of the conventional anti-TB drugs.

1 illus, 3 tables, 20 ref

006289   ISLAM B, HOSSAIN A (Computer Science and Engineering Dep, Rajshahi Univ of Engineering and Technology, Rajshahi, Bangladesh, Email: bayezid.shouvik@gmail.com) : Fusion of features and extreme learning machine for facial expression recognition. J Comput Sci 2019, 15(12), 1833-1841.

Human emotion is highly correlated to facial expressions. Due to its growing demand in different sectors, an emotion recognition method is proposed through recognizing facial expressions. The input image is preprocessed and then the resulting image is segmented into four facial expression regions following the newly proposed segmentation method. Histogram of Oriented Gradients (HOG) and Local Binary Patterns (LBP) are fused to extract the necessary features from the four segmented parts. The dimension of the feature vector is reduced using Principal Component Analysis (PCA). To classify the expressions, Extreme Learning Machine (ELM) is used. For evaluating the performance of the proposed method, three widely used and publicly available facial expression datasets (JAFFE, CK+, RaFD) are used. The proposed method achieved 95.3%, 99.84% and 98.65% accuracy while using images from JAFFE, CK+ and RaFD dataset respectively. Performance of the proposed method on these datasets is compared to other facial expression recognition methods on these datasets to indicate that the proposed method achieves state-of-the-art performance

9 illus, 6 tables, 26 ref

006287   HAJLAOUI E, KHLIFI A, DARDOURI S, ZAIER A, HAMED M B, SBITA L (Gabes Univ, Gabes, Tunisia, Email: emhajlaoui@yahoo.fr) : Performance evaluation of interference mitigation techniques in 4G networks in mobile environments. J Comput Sci 2019, 15(12), 1820-32.

Intercell Interference (ICI) is one of the major factors that limit the performance and Quality of Service (QoS) of 4G wireless networks (Long Term Evolution/LTE-Advanced). For this reason, heterogeneous networks present an attractive solution for the improvement of mobile network’s services to provide better data rates and coverage. So, a key scheme in 4G traffic processing is the interference mitigation techniques. In the present work, we propose a model while optimizing the simulation parameters of three well-known ICI mitigation algorithms, namely Soft Frequency Reuse (SFR), Distributed Fractional Frequency Reuse (DFFR) and Strict Frequency Reuse (Strict FR). Here, mobile users are considered to be moving at high speed (300 Km/h: speed allowed by the LTE/LTE-A standards). We provide a simulation framework that is suitable for the parameters of the 4G system in terms of cells number and inter-eNodeB distance for an LTE/LTE-A network deployed in an urban area. Subsequently, we compare our proposed model with the aforementioned algorithms in terms of throughput, Signal-toInterference-plus-Noise-Ratio (SINR) and Spectral efficiency by using the NS3 open source simulator. Results prove the efficiency of the proposed model in condensed area of mobile users compared to previous works that evaluated and tested immobile scenarios.

14 illus, 2 tables, 20 ref

006279   ABOUHOGAIL R A, ALI A H (Electrical Quantities Metrology Dep, National Institute of Standards, Giza, Egypt, Email: rehlatif@yahoo.com) : Design and development of an advanced authentication protocol for mobile applications using NFC technology. J Comput Sci 2019, 15(12), 1809-19.

In this paper, we proposed a new Authentication Protocol for Mobile Applications using NFC technology (AP for MAN). The proposed protocol minimizes the required time to complete the authentication process between the shared entities with a high level of privacy. According to the main security measures, the proposed protocol is evaluated. The current paper presents a new idea for preventing denial of service attack and preserves the limited mobile device capability. The proposed protocol is checked using BAN logic and established that it has no redundancy, the mutual authentication property between the shared parties is verified. The implementation of the proposed protocol shows that it works as designed and it is practical.

4 illus, 4 tables, 21 ref

006292   NABI R M, SAEED S A M, HARRON H B, FUJITA H (Sulaimani Polytechnic Univ, Sulaimani, Iraq, Email: rebwar.nabi@spu.edu.iq) : Ultimate prediction of stock market price movement. J Comput Sci 2019, 15(12), 1795-1808.

Investment in the stock market is currently very popular due to its economic gain. Numerous researchers’ and academicians’ work is focused on financial time series prediction due to its data availability and profitability. Therefore, this study presents the design and implementation of a novel binary classification framework to predict stock market trends. The framework is composed of data preprocessing, feature engineering, feature selection and classification algorithms. The model is built on multiple sector stock market companies’ data collected from NASDAQ over a period of ten years. Various feature selection algorithms are applied in combination with several machine learning algorithms. Furthermore, as the new contribution, we have constructed two new features which have been found to be promising in terms of improving overall performance. Ultimately, a collaboration of feature selection and classification techniques is employed. The application of Principal Component Analysis (PCA) with Multilayer Perceptron and Support Vector Machine (SVM) to added featured datasets shows 100% accuracy on the majority of datasets. In summary, an intensive comparison is presented among the various feature selection and classification algorithms.

10 illus, 6 tables, 24 ref

006285   CHIWAMBA S H, PHIRI J, NKUNIKA P O Y, SIKASOTE C, KABEMBA M M, MOONGA M N (Computer Science Dep, Zambia Univ, Lusaka, Zambia, Email: shchiwamba@yahoo.com) : Automated fall armyworm (Spodoptera frugiperda, J.E. Smith) pheromone trap based on machine learning. J Comput Sci 2019, 15(12), 1759-79.

Maize is the main food crop that meets the nutritional needs of both humans and livestock in the sub-Saharan African region. Maize crop has in the recent past been threatened by the fall armyworm (Spodoptera frugiperda, J.E Smith) which has caused considerable maize yield losses in the region. Controlling this pest requires knowledge on the time, location and extent of infestation. In addition, the insect pest’s abundance and environmental conditions should be predicted as early as possible for integrated pest management to be effective. Consequently, a fall armyworm pheromone trap was deployed as a monitoring tool in the present study. The trap inspection is currently carried out manually every week. The purpose of this paper is to bring automation to the trap. We modify the trap and integrate Internet of Things technologies which include a Raspberry Pi 3 Model B+ micro-computer, Atmel 8-bit AVR microcontroller, 3G cellular modem and various sensors powered with an off-grid solar photovoltaic system to capture real-time fall armyworm moth images, environmental conditions and provide real-time indications of the pest occurrences. The environmental conditions include Geographical Positioning System coordinates, temperature, humidity, wind speed and direction. The captured images together with environmental conditions are uploaded to the cloud server where the image is classified instantly using Google’s pre-trained InceptionV3 Machine Learning model. Intended users view captured data including prediction accuracy via a web application. Once this smart technology is adopted, the labour-intensive task of monitoring will reduce while stakeholders shall be provided with a near real-time insight into the FAW situation in the field therefore

17 illus, 12 tables, 77 ref

006295   PRABOWO S A, ADIWIJAYA, MUBAROK M S, FARABY S A, NAF M Z, BAKAR M Y A (Telkom Univ, Bandung, Indonesia, Email: adiwijaya@telkomuniversity.ac.id) : An implementation of support vector machine on the multi-label classification of english-translated quranic verses. J Comput Sci 2019, 15(12), 1752-8.

One of the attempts to understand the meaning and content of the Quran, the central religious text of Islam, is the topic classification of Quranic verses. Verse topic classification aims to help the reader, so he can easily and quickly find information or knowledge contained in the Quran. In this paper, we build a classification model for the topics of English- translated Quranic verses using Support Vector Machine (SVM). The problem of classification of topics of Quranic verses is categorized as a multi-label classification problem. Hence, we design an SVM-based classifier to solve the multi-label classification of topics of Quranic verses. We also implement several techniques such as preprocessing, feature extraction, and dimensionality reduction to solve this problem. Then, we use Hamming Loss as a performance measure to evaluate our proposed classifier model. We find that our proposed model yields outstanding results.

6 illus, 21 ref

006290   MASUM A K M, KARIM A N M R, ABID F B A, ISLAM S, ANAS M (Computer Science and Engineering Dep, International Islamic Univ, Chittagong, Bangladesh, Email: zakianaser@yahoo.com) : A new hybrid AHP-TOPSIS method for ranking human capital indicators by normalized decision matrix. J Comput Sci 2019, 15(12), 1746-51.

Human Capital or HC plays a significant role in the field of economic growth. Advancement on human capital and knowledge-based economy are of core importance for developing countries. Active representatives of capital accumulation are the people and utilizing natural resources for contributing to the socio-economic growth of the country. Evaluation of HC helps organizations to concern about their present position taking Human Capital Management into account. The core goal of this work is to measure performance of each organization individually based on criteria and rating the individual depending on the measurements. The technique used in this paper is based on the integration of “AHP” and “TOPSIS” as “AHPTOPSIS” Hybrid method. The Analytic Hierarchy Process determines criteria’s weight and significance of the indicators or alternatives. The final ranking of HC is done by TOPSIS method considering the importance of the indicators. The proposed MCDM approach is effective, compatible and reliable considering the goal of the study.

1 illus, 4 tables, 16 ref

006288   HASHIM A N, AL-HASHIMI B M (Computer Science Dep, Kufa Univ, Kufa, Iraq, Email: Asaad.alshareefi@uokufa.edu.iq) : Human iris recognition based on hybrid technique. J Comput Sci 2019, 15(12), 1734-45.

Iris recognition is a biometric technique that uses iris pattern information to detect person identification. Initially, the system find out the boundary of the pupil and iris. Then, Circular Hough transform used to find out the center of both pupil and iris in order to crop iris part from the eye image. After that, Daugman’s Rubber Sheet model utilized for performing the normalizing step. Then, features extracted based on Legendre moment and Local Quantized. Several orders value with many region of iris have been used to get best value, which satisfied the highest recognition rate. Matching was performed by City Block Distance. The simulation was carried out using samples from CASIA.v4-Interval database, the main tool for programming is MATLAB.

12 illus, 13 tables, 15 ref

006281   ALAEDDINE H, SERRHINI K, MAIZIA M, NÉRON E (François-Rabelais Univ, Tours, France, Email: : houssein.alaeddine@hotmail.fr) : Establishing an evacuation network: A path ranking approach. J Comput Sci 2019, 15(12), 1710-20.

The evacuation of population exposed to flood hazard requires the establishment of a specific transportation network. This is to compute escape routes to be taken by affected population. At evacuation time, inhabitants of affected area must be evacuated through transportation network to safety area. The main objective of this work is to provide assistance to rescue forces in terms of accessibility by providing itinieraries between buildings at risk of flooding and safety points equipped for this purpose. Technically, the problem of k-shortest paths between two nodes in network has been extensively studied in the literature offering several efficient algorithms for different applications. Those algorithms so-called ranking methods aim to compute the first shortest path then the second one and so on. It’s well known that the computation in ranking methods is based only on one criterion which is generally distance or time. Often a single criterion is not sufficient in some real-world problems (road network, internet, etc.,) where one or several supplementary criteria (such as cost, capacity, security, etc.,) must also be taken into consideration. This multi-criteria optimization so-called labeling method aims to compute a Pareto front that represents a set of non-dominated paths. However it is very difficult to take a decision on which k-paths to select among this set and especially when selected paths are served as a data input for a sensitive problem such as the evacuation. We contribute in this paper to establish an evacuation network dedicated to the evacuation of population exposed to natural hazards and more particularly to flood hazard. Two ranking methods to compute paths between each origin (building) - destination (shelter) pair are presented. The criteria free-flow travel time, capacity and number of lanes of road are considered in computing paths. Thus we aim in the proposed ranking approach to simulate a multi-criteria aspect by combining travel time and number of lanes as weight function. The establishment of network (determination of k-paths between each building and shelter associated) is then performed according to several measures we introduce in this paper.

10 illus, 26 ref

006298   SILVA A F D, SOUZA L D D (Informatic Dep, Maringa Univ, Parana, Brazil, Email: anderson@din.uem.br) : Understanding the code transformation algorithms’ impact. J Comput Sci 2019, 15(11), 1678-93.

Modern compilers provide several code transformations, which are automatic program transformations applied with the goal of improving the program performance. In this article, we investigate how standard compiler code transformations, performed at the compiler intermediate representation, affect such representation and consequently the performance. Our research targets clang/LLVM, a popular compiler infrastructure. Our experimental evaluation demonstrates how several code transformations change the intermediate representation and consequently improve the target code’s performance in terms of runtime.

4 illus, 8 tables, 24 ref

006280   ABU-ARQOUB M, ISSA G, BANNA A E, SAADEH H (Petra Univ, Amman, Jordan, Email: abu-rqoup@uop.edu.jo) : Interactive multimedia-based educational system for children using interactive book with augmented reality. J Comput Sci 2019, 15(11), 1648-58.

This paper describes a system's model for Augmented Reality Learning in which a traditional book is converted to an interactive book using Glyphs (TAGs) and multimedia. The interactive book can be used by a child, parent, or by a teacher to make learning an enjoyable experience. As the child goes through the contents of the book, illustrations and images come to live, thus enforcing the learning and comprehension of concepts in an interactive and fun way. To make a printed book interactive, special TAGs (Glyphs) are inserted in the required places within the book, ready to be read by the webcam and then converted to video, 2-D or 3-D images, audio and explanation text. An actual example (Sandy Starfish) is presented to illustrate the architecture and the implementation of the Augmented Reality learning system and to explain the steps and procedure used to transform a textbook to an interactive one.

10 illus, 41 ref

006291   MUMIN M A A, SEDDIQUI M H, IQBAL M Z, ISLAM M J (Computer Science and Engineering Dep, Shahjalal Univ of Science and Technology, Sylhet, Bangladesh, Email: mumin-cse@sust.edu) : Neural machine translation for low-resource English-Bangla. J Comput Sci 2019, 15(11), 1627-37.

Neural machine translation has recently been able to gain stateof-the-art translation quality for many language pairs. However, neural machine translation has been less tested for English-Bangla language pair, two linguistically distant and widely spoken languages. In this paper, we apply neural machine translation to the task of English-Bangla translation in both directions and compare it against a standard phrase-based statistical machine translation system. We obtain up to +0.30 and +4.95 BLEU improvement over phrase-based statistical machine translation for Englishto-Bangla and Bangla-to-English respectively. Due to low-resource and morphological richness of Bangla, English-Bangla translation task produces a large number of rare words. We apply subword segmentation with byte pair encoding to handle this rare words issue. We obtain up to +0.69 and +0.30 BLEU improvement over baseline neural machine translation for English-to-Bangla and Bangla-to-English respectively. We further investigate our system output for several challenging linguistic properties like subject-verb agreement, noun inflection, long distance reordering and rare words translation. We observe that neural machine translation with and without subword segmentation significantly outperform the phrase-based statistical machine translation system, thus establishing itself as the stateof-the-art technology for low-resource English-Bangla machine translation.

2 illus, 4 tables, 61 ref

006286   FATEMA K, SYEED M M M (Association for Computing Machinery, New York, United States, Email: mahbubul.syeed@gmail.com) : A privacy protected platform to aggrandize micro-business. J Comput Sci 2019, 15(11), 1595-1606.

This paper presents a platform, which will provide both the microbusinesses and its consumers a common ground to maximize their interests and benefits and in turn better contribute to the economy. This research work offers a comprehensive study on the micro businesses to portray their contributions and needs for expansion. The research then designs a conceptual platform to host, promote and manage businesses and their consumers. The platform is integrated with the MyGeoTrust privacy service for better protecting associated information. Finally, the research presents a prototype implementation of the platform in android to demonstrate its applicability.

10 illus, 1 table, 20 ref

006293   PATEL H, THAKUR G S (Computer Applications Dep, Maulana Azad National Institute of Technology, Bhopal- 462 003) : An improved fuzzy K-nearest neighbor algorithm for imbalanced data using adaptive approach. IETE J Res 2019, 65(6), 780-9.

Fuzzy classification is a widely explored research solution of objects in data sciences and engineering. With the span of time, it got new heights with significant improvements according to the needs. Still there are some issues to be discussed and solved in a fuzzy manner; fuzzy classification of imbalanced data is one of them. Consequently, the importance of fuzzy nearest neighbor came into the scenario and deployed in many applications. Various improved crisp nearest neighbor approaches are performing well on imbalanced data-sets, but not much work has done on the fuzzy nearest neighbor for imbalanced data. In this paper, we propose to find out correct memberships of test instances from imbalanced data by merging an adaptive K-nearest neighbor approach to deal with the imbalanced issue and then join it with fuzzy K-nearest neighbor.

3 illus, 8 tables, 44 ref

006297   SHARMA S M, DASGUPTA S, KARTIKEYAN M V (Electronics and Communication Engineering Dep, Indian Institute of Technology, Roorkee- 247 667) : A hybridized fuzzy-neural predictive intelligent (HFNPI) modelling approach based underlap FinFET model. IETE J Res 2019, 65(6), 771-9.

This paper presents the hybridized fuzzy-neural predictive intelligent (HFNPI) based approach for predicting FinFET model. The proposed model is an improved approach over artificial neural network (ANN) model and adaptive neuro fuzzy inference system (ANFIS) model that provides optimum model parameters. In this paper, the challenge of optimization of large number of parameters is reduced. It assesses the performance of resultant structure on the basis of selected RF figure-of-merit. Based on the application requirements, RF figure-of-merit such as f_T and f_max are used as appropriate performance parameters to analyse the device performance. The framework for the HFNPI model is underlapped FinFET structural/process parameters. The mean prediction error was found 2.8 X 10^-4 GHz. The comparative analysis of HFNPI with ANN and ANFIS model is done. It is found that combination of fuzzy and neural logic shows better result rather than individual ANFIS and ANN model to redevelop the model and increase the number of inputs.

17 illus, 3 tables, 24 ref

006296   SARKAR M (Computer Science and Technology Dep, Kingston Polytechnic Coll, Barasat, West Bengal, Email: moumita.kishalay@gmail.com) : Deep learning- An advancement of artificial neural network. Everyman's Sci 2019, 54(4), 223-7.

Deep learning algorithm has rapidly become a methodology of choice for the analysis of huge unstructured data using unsupervised learning. In this paper, Deep learning as a successor of Artificial neural network, types of Deep learning network, its application in different areas, its strengths and challenges have been discussed.

1 illus, 2 tables, 4 ref

006294   POLA M, DURTHI C P, RAJULAPATI S B (Biotechnology Dep, National Institute of Technology Warangal, Hanamkonda, Telangana, Email: satishbabu@nitw.ac.in) : Modeling and optimization of L-asparaginase production from novel Bacillus stratosphericus by soft computing techniques. Curr Trends Biotechnol Pharm 2019, 13(4), 438-47.

Feed forward Artificial Neural Network (ANN) model and global optimization by Genetic Algorithm (GA) were employed on significant variables to enhance the production of L-Asparaginase from Bacillus stratosphericus.Using the experimental data, network was built with 4 inputs and 2 outputs along with 10 hidden neurons. Levenberg-Marquardt back propagation algorithm was employed to study the interactions between variables and their influence on L-Asparaginase and L-Glutaminase activity. The predicted enzyme activities were compared with the experimental data. The R² value was found to be 0.99419 from ANN and it was higher compared to Response Surface Methodology (RSM). GA optimization was employed on the quadratice quation obtained from RSM studies to find optimal solution. The optimal concentrations of L-Asparaginase and L-Glutaminase obtained from GA were 29.68 IU/ml and 0.12 IU/ml respectively. The optimal process variables were found to be incubation time-55h, pH- 6.0 and Temperature-24 °C and L-Asparagine-2.5 g/L.

2 illus, 4 tables, 55 ref

006284   CHITHRA P L, HENILA M (Computer Science Dep, Madras Univ, Chennai, Tamil Nadu, Email: chitrasp2001@yahoo.com) : A novel thresholding technique for digital image segmentation. Bull Pure Appl Sci Sect E Math Stat 2019, 38E(2), 40-7.

Segmentation of region of interest is one among the main image processing step that has been carried on for any image analysis. A novel thresholding technique for segmenting an input image is proposed in this paper. As the first step RGB image is acquired. Taking into account only the green component image, we convert the image into a logical image and obtain the rank of the resultant image. Using this value as a threshold value we segment the given RGB image. A black and white segmented image is the output image that is generated using this proposed thresholding methodology. 112 sample images of apples, oranges, bananas and leaves are used for testing the accuracy rate of segmentation. A comparison between the famous Otsus thresholding technique and the proposed technique is done and it is found that the accuracy rate of segmentation of the test images using the proposed method is greater than or equal to the output images obtained using Otsus histogram thresholding technique.

6 illus, 2 tables, 8 ref

006299   SINGH N K, MUJWAR S, GARABADU D (Pharmacology Div, GLA Univ, Mathura- 281 406, Email: debapriya.garabadu@gla.ac.in) : In silico anti-cholinestarase activity of flavonoids: A computational approach. Asian J Chem 2019, 31(12), 2859-64.

In the present study, a computational approach has been designed to evaluate the potential anti-cholinesterase activity of derivatives of flavonoids. Molecular docking studies is performed for the 9 flavonoids against the human acetylcholine (ACh) enzyme to evaluate their binding affinity for having anti-alzheimer activity. All the 9 flavonoid compounds exhibited strong binding affinity that promises potent inhibition of human acetylcholine enzyme. Potential binding affinity of all the flavonoids against human acetylcholine enzyme confirms their possible mechanism of action by using AutoDock based molecular docking simulation technique. Thus, these flavonoid compounds could be presumed to be potential anti-cholinesterase drugs.

4 illus, 3 tables, 46 ref

006283   BRINDHA J, REJI T F A F (Manonmaniam Sundaranar Univ, Tirunelveli- 627 012, Email: abbsfen@gmail.com) : Synthesis and molecular docking studies of coumarinyl thiazole as cell division protein kinase 2 inhibitor. Asian J Chem 2019, 31(11), 2453-6.

A series of 2-alkylamino-4-(3-coumarinyl)thiazoles were synthesized, characterized and evaluated their anticancer activity through molecular docking studies. Cell division protein kinase 2 (PDB code: 1KE9) is selected as a target and the compounds which obeys Lipinski rule of five is selected as a ligand. Molecular docking study is carried out using AutoDock Vina in PyRx virtual screening tool. This study revealed that all the compounds are active against the molecular target and compounds 5a and 5c have the highest docking score.

1 illus, 2 tables, 19 ref

006282   BHADRACHAR S, VIJAYAKUMAR G R, MAHADEVAN K M, BASAVARAJA T (Chemistry Dep, Tumkur Univ, Tumkur- 572 103, Email: vijaykumargr18@gmail.com) : Synthesis, molecular docking and radical scavenging activity of 1,2,4,5-Tetrasubstituted imidazole derivatives. Asian J Chem 2019, 31(11), 2448-52.

A series of 1,2,4,5-tetrasubstituted imidazoles (2a-g) were synthesized using 1,2-diketone, 1-naphthaldehyde, substituted aromatic amine and ammonium acetate in the presence of ceric ammonium nitrate as a catalyst. The synthesized compounds were characterized by FT-IR, 1 H NMR, Mass spectra and explored for their antioxidant activity by DPPH free radical scavenging assay method. Among the synthesized compounds 2a, 2e and 2f exhibit good antioxidant activities. Molecular docking study was also been performed to know the possible interactions between the synthesized compound and antioxidant receptor 3MNG.

1 illus, 2 tables, 30 ref