In-house & Collaborative Research

Ninu Preetha N S, Brammya G, Ramya R, Praveena S, Binu D, Rajakumar B R

The channels used to convey the human emotions consider actions, behaviors, poses, facial expressions, and speech. In fact, the facial expressions take prominent role in our daily life to communicate to other people. An immense research has been carried out to analyze the relationship between the facial emotions and these channels. The goal of this paper is to develop a system for Facial Emotion Recognition (FER) that can analyze the elemental facial expressions of human, such as normal, smile, sad, surprise, anger, fear and disgust. The recognition process of the proposed FER system is categorized into four processes, such as pre-processing, feature extraction, feature selection, and classification. After preprocessing, SIFT-based feature extraction method is used to extract the features from the facial point. Further, a metaheuristic algorithm called Grey Wolf Optimization (GWO) is used to select the optimal features. Subsequently, GWO-based Neural Network (NN) is used to classify the emotions from the selected features. To the next of the implementation, an effective performance analysis of the proposed as well as the conventional methods like Convolutional Neural Network (CNN), NN- Levenberg–Marquardt (NN-LM), NN- Gradient descent (NN-GD), NN- Evolutionary Algorithm (NN-EA), NNFirefly (NN-FF), and NN-Particle Swarm Optimization (NN-PSO), is provided by evaluating few performance measures and thereby, the effectiveness of the proposed strategy over the conventional methods is validated.

Manuscript EditingE

Distributed Parallel Medical data clustering based on the proposed BatDol-Sparse FCM-based Map Reduce Framework

Suki Antely A, Jegatheeswari P, Bibin Prasad M, Vinolin V,Vinusha S, Rajakumar B R and BinuD

Parallel clustering serves as a platform for handling the big data that updates asseveral millions of medical data with time. The literature displays a number of clusteringalgorithms using map-reduce framework, but they did not assure the effective clusters such thatknowledge extraction becomes tough. With the aim to render a better and effective dataclustering method to analyze the big medical data arriving from distributed systems, this paperuses a new clustering method. The proposed method named as BatDolphin-based Sparse FuzzyC-Means (BatDol-Sparse FCM) clustering algorithm is proposed that paves way for the optimalselection of the cluster centroids. The distributed medical big data is managed using the Map-Reduce framework that is inbuilt with the BatDolphin-based Sparse Fuzzy C-Means algorithmsuch that the local and global clustering is executed. Implementation of proposed BatDol-SparseFCM algorithm is done by taking six different medical datasets and evaluated based on metricssuch as clustering accuracy (CA) and dice coefficient (DC). From the simulation results it isevident that, the proposed parallel clustering scheme provided better results than the existingalgorithms with the values of 0.96 and 0.9667 for CA and DC respectively.


Deer Hunting Optimization Algorithm: A new nature inspired meta-heuristic paradigm

Brammya G, Praveena S, NinuPreetha N S, Ramya R,Rajakumar B R and Binu D

This paper proposes a novel meta-heuristic algorithm, named DHOA, inspired from the hunting procedure of humans toward deer. Even though the activities of the huntersdiffer, the way of attacking the buck/deer is based on the hunting strategy they develop. The hunting strategy depends on the movement of two hunters in their best positions, termed asleader and successor. Accordingly, each hunter updates his position until they reach the buck. The experimental results reveal that the proposed DHOA provides competitive results whencompared with the state-of- the-art optimization algorithms, such as GWO, WOA, FF, PSO, and so on. The experimentation is carried out with 39 benchmark functions and threeengineering applications. Moreover, a specific application is exploited by integrating NN in DHOA (DHOA-NN), to show the efficiency of the proposed algorithm in the classification.The proposed algorithm experimented in real-time engineering applications, and the performance comparison with the existing optimization algorithms proves the superiority ofthe DHOA algorithm..


Optimization using Lion Algorithm: A Biological Inspiration from Lion’sSocial Behavior

Rajakumar B R

During the past decade, solving complex optimization problems with bio-inspiredoptimization algorithms, especially evolutionary computation-based and swarm intelligence-based algorithms has received substantial attention among practitioners and researchers. Inthis paper, a novel optimization algorithm on the basis of the lion’s unique social behaviour isdeveloped. Here, unique lifestyle of the lion has been the fundamental motivation for thedevelopment of this optimization algorithm. The two most popular lion’s social behavioursare Territorial defense and Territorial takeover. Moreover, the algorithm is experimented onunimodal and multimodal benchmark minimization functions and compared with leadingswarm intelligence such as Artificial Bee colony (ABC), Bacterial Foraging OptimizationAlgorithm (BFO), Cuckoo Search (CS), FireFly (FF), Group Search Optimization (GSO), Moth-flame Optimization (MFO), Particle Swarm Optimization, Simulated Annealing, andDragon Fly algorithm and other algorithms Biogeography-based optimization (BBO),Differential Evolution (DE), Genetic Algorithm (GA), Gravitational Search Algorithm(GSA), Grey Wolf Optimization (GWO), Harmony Search Algorithm (HSA), SimulatedAnnealing (SA), Whale Optimization Algorithm (WOA), Crow Search Algorithm (CrS). Theobtained results show that lion algorithm is competent over majority of the evolutionaryalgorithms and equivalent to few other algorithms.


Lion Algorithm on Standard and Large Scale Engineering Problems

Rajakumar B R

Engineering optimization problems have become complex owing to their nonlinear objectivefunctions, where a number of linear and/or nonlinear constraints have to be satisfied. Hence,conventional optimization methods such as gradient-based algorithms are often unable tooffer satisfactory solutions. During the last two decades, evolutionary algorithms haveattained increasing consideration as optimization techniques for complex engineeringproblems. However, solving these problems remains as challenging yet. Hence, this proposedwork intends to exploit a new algorithm known as Lion Optimization Algorithm (LA), whichis based on lion’s unique social behaviour. The algorithm mimics the two most popular lion’ssocial behaviours, called as Territorial defense and territorial takeover. Here, lions follow aunique defined process to drive weak lions and to keep the species strong enough over others.These entire processes are also modelled here and hence named as lion algorithm. Moreover,the performance of this algorithm on engineering problems like pressure vessel design, Geartrain design, spring tension design, three-bar truss design, tension/compression spring andwelded beam are rigorously analyzed and compared both in standard as well as large scales.


C-GWO: Trust included Cluster Head SelectionModel in WSN using Crossover influenced Grey WolfOptimization

R. Ramya, T. Angelin Deepa, G. Brammya, N.S. NinuPreetha, S. Praveena,B.R. Raja Kumar, D. Binu

In wireless sensor networks (WSNs), energy efficiency is considered as the vitalaspect since the deployed sensor nodes are battery-operated devices. In order to fulfil theneed of energy efficient data transmission, clustering based approaches are implemented viadata aggregation so that the balancing of energy consumption among the sensor nodes innetwork may be more satisfactory. Clustering is the most important approach or strategy forprolonging the lifetime of network in WSNs. It engages in sensor nodes grouping to formclusters and in each cluster a sensor node should behave as head of the cluster, which istechnically termed as ‘Cluster Head’. The role of this cluster head is: It collects the data orinformation from respective nodes in cluster and forwards the aggregated data to Base Station(BS). However, the selection of cluster head is a serious problem in WSN and yet that is notup to the mark. This paper intends to propose a new cluster head selection approach thatincorporates many criteria including Energy, Delay, Distance and Trust. Moreover, the paperalso highly concentrates on secure data transmission, and this is adorably satisfied throughthe concern of Trust measure. The proposed Crossover influenced Grey Wolf Optimization(C-GWO) compares its performance over other conventional methods in terms of normalizedenergy and number of alive nodes.


The academicians are in need and in fact, eligible for conducting research. However, they experience many difficulties in availing appropriate guidance, facilities and even exploiting them. Exploration for right expertise is nothing but associating with right firms or experts, who are dominating in the field. A good research practice is actually not conducting the research in an unwarranted pressure. It exactly means to enjoy the research doings and observing the outcomes hopefully. The primary intent is not in fact blue sky research, rather it should be outcome and implication based research. So in order to crack this entire dilemma it is very decisive to encompass an external guidance, networking with experts and sitting together with in-house laboratory of any premiere research institute. It is exactly refers to collaborate with researchers and experts of other institutes.

Resbee Info Technologies is a premier research oriented organization that emphasizes viable research prospects. It has multiple wings to promote the research of diverse fields. It shows great interest in interdisciplinary research, bridging experts of multiple domains into a signal platform and disseminates the outcomes geographically. Yes, we are RESearch BEEs (Resbee). The Resbee wings include editing services, publishing services and in-house research. We are associated with a unique, sophisticated and controlled platform on which our research team can identify and resolve the technical and operational risks of integrating emerging technologies. Our highly flexible facilities allow enabling to work independently.

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Our computing laboratory is the key structure for conducting all our in-house research activities, client’s projects and collaborative research. Exceedingly refined computing machineries with expandable memory storage and communication lines have constructed the layout of our lab. All the machineries are sporadically promoted with latest software, tools and applications. The lab is well structured, and monitored to pledge elevated productivity and well-timed research outcomes. One can glimpse the passion, inquisitiveness and interestingness far and wide within our lab. The key research areas in the lab include, machine learning, soft computing, artificial intelligence and their applications areas such as image processing, data mining, networking, etc. Both researching and developing team share the lab resources in a most prolific manner. The resource outcomes, annotations and motivating assert from the lab are sporadically accessible and published in referred journals and conferences. The lab shares its resources to our team, clients as well as our collaborating researchers and hence it timely meets the crucial and momentous spot in accomplishing our organizational aspirations.

Software tools

Software tools for research and related measures are a key aspect to protract the conception and enlistment to explore the research facts. Tools are considered to be as the medium that mainly help out for the research and allied actions to let researchers to collect, systematize, implement, investigate, visualize, mobilize and store quantitative and qualitative data and creative outputs. Resbee Info Technologies is well-equipped with the top engineering design tools and software in the hopes of making the jobs of our teams to work little easier. Our wide range of software support research and coursework in several engineering disciplines. A researcher can perform hassle-free simulation and analysis in our laboratory using MATLAB and JAVA and also with other research tools given below.

ImageJ Xilinx itK-SNAP (MRI imaging) XSG tool OpenCV SimElectronics OTB Tool (Satellite imaging) SimPower Systems JNS SimMechanics JADE SimHydraulics CloudSim Bioinformatics tool NS2 SimBiology NS3 Chemometrics tools Weka Computational physics tools MapReduce and Hadoop MATLink

We are always open to collaboration with academia and we often host visiting researchers. Our interns are typically researchers with interests in programming languages, distributed systems, information retrieval, or empirical software engineering. All our clients are made highly benefited by each and every tool with we are collaborating. Appropriate software has been used to demonstrate the project status and completion to our clients. Further, we provide accurate acquaintance shift to the clients in the course of online networking applications. Our SEO technology elevated the impact of research we conduct in our labs.

Resbee Info Technologies not fit with a single or a group of domain expertise, because of its broad network of experts, associations and virtual meeting premises. We have a robust set of domain capabilities that anchor our functional and engineering expertise. Until recently, we have depended on the availability of teams of willing domain experts and technical experts working together to extract the required semantics and to encode them in some usable form. This rigorous set of engineering courses provides researchers with comprehensive coverage of engineering challenges and solution approaches in several areas associated with the domains. Researchers choose a focus area and work with our domain experts to identify a set of focus areas appropriate to their research and professional interests. Here are some of the following domains in which we expertise, but not limited to the following research areas,

Artificial Intelligence Audio and Speech Processing Knowledge Engineering Life Science and Health Care Big Data and Data mining Logistics and Supply Chain Management Biometrics Machine Learning Cloud Computing Mobile Computing Communication Engineering and Systems Natural Language Processing Data warehousing Networked and Control Systems Digital Image Processing Numerical Methods Digital Signal Processing Power and Energy Systems Electrical Systems Power Electronics Industrial Informatics Scheduling and Optimization Soft Computing Software Engineering

Our research environment is based on the key qualities of honesty, openness, care, integrity and accountability. Our companionship is committed for developing and nurturing a culture of research integrity. This is achieved through actively supporting experts and defining clearly how they can comply with ethical guidelines and good research practice. Our aim is to create a framework for understanding how to design, manage, conduct, and disseminate research in a conscientious and responsible manner. This includes supporting experts to understand and act according to the expected standards of the researchers, making guidelines and having procedures in place to ensure that research is conducted in compliance with the universities to support research integrity. Our companionship continuously works toward providing comprehensive training and development on good research practice. As well as having appropriate arrangements in place through which researchers can access advice and bestow nonstop guidance on ethical, legal and professional obligations and standards.

With incomparable facilities, we are uniquely positioned to do research that cannot be done anywhere else. Our companionship comprises a team of world-class academics and experts who are contributing to the development of new knowledge, tools and technologies that positively impact on the environment. The core of our philosophy is for our research to enlighten the ideas and professional practice for the researchers. Thus, your research can take you much further afield though. You may find yourself visiting archives or facilities to examine the data or even can take a look at rare source materials. Moreover, you can even have the opportunity to spend an extended period in research with our company.

1. Apply for collaborative research

2. Confirm the schedule, fees, topic and research tenureh

3. Join as an external researcher

4. Conduct research with our advisory panel

5. Complete and get publication in top class refereed journals