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Business Analytics Technology for Humanity

Preface點measoning from differeres skillety and strateThis book presents a deep analytics model throughistent and systematic approach and highlights itsing ten technologyandtechnology, (2) Electrical and hybrid vehicles: smart batteries, (3)RailTech: DAS, security safet(4)Emerging digital technology, (5)Solar computing Self-healing mechanism for a smart grid,ormation Security Intelligence (IsI) Analytics Adaptive sed dynamic data protection for noTCancer prediction prevention mechanism: deep learning, (8) Biomedicaastronomical hazardsty is that every stakeholder is impacted by the challestems today Thelyal whe modern global economy, The target audience ofhis book includes academic and researchity, corporate leaders, policy makers, administrators andestors,engineers,producers and directors interested in production ofideas of deep analytichope that you will find them really value adding and useful and will share with your communitiesrational and interestingto teach deep analyticsademicBent Information Systems (MIS), Strategic Management and Analytics for BBA, MBA, PGDMPGDBM) and also Electrical and Electronics Ening(eg B,Tech, MTech, BE

E, ME, Ph D)This e-book is the summary of electrAugusttains information obtained from authentic soulutilized in any form by any electronic mechanical or otheror hereafter inventedluding photocopying,ming and recording or in any information storage or retrieval systemhanks and regardsElectrical Engineering (ChakraboAnalytics Research Lab, IndiaReference of document: EBOOK/ SCHAKRABORTY/BA/V30/15082019Page 2

w is it possible to represent the structure of a system associated with a technology innovationDigital twins may be an interesting solution; it integrates thto optimize the operation andthe digital replicaliving physical entity (eg phpected to bridged support data sharing between the physical and virtual entitiestwinssuch as itself thousodes of thehema of the system and get updated continuously to represent real-time status, working conditions orThe concept of digital twins are expected to be useful for manufacturing, e(eg HVAC controlmotive industries in terms of connectivity, digital traces and productphysical objects 1cate copy of the properties and states of the objects (e

g shapeuseful for theenance of power generation equipment such as turbines, jet engines and locomotivesmonitoringnostics to optimize asset performance and utilization thrnalysis and to overcome the challenges in system development, testing, verification and validation fortomotive applications, The physical objects are virtualized and can be represented as dodelsd closely integrated in both physical and cyber spaces Digital twins should represent theoduct life-cAnother interesting technology for exploring innovative structure is Vhrough virtual (VRin a digital environment VR and AR are sophisticated, creative and powerful tools to shotstructures and offer aintegrating Al,graphics and automation in various applications such as manufacturing, retail, healthcare, entertainment,5 SECURITYLevel ILevel 4: Malicious attackdaptive securityFigure 15: Security analyReference of document: EBOOK/ SCHAKRABORTY/BA/V30/15082019Page 11

ed throughurity What do you mean by technologyrity?A systeypes of threats from both external and internal environments but it should be vigilant androtectedty policies An emerging technology demands the support of an adaptivemales vulnerabilities or malictraffic congedetected, the technology should be ablte the risks throughentive detectinctive capabilities ands Adaptive security analyzes the behethe obiectives of adcurity architecture in depth New threatan outcomand may cause new forms of disIoday, it is essential to deploy adaptive security architecture for the emergingdemand continueonitoring and remediation: traditional prevent and detect and incident respovent a set of malicious attacks It is requiredsess as-Is systemdministration strategies, investment and competencies: identify the gaps and deficiencies and adopt antextual and coordinated approacherify security intelligence of a technological innovation collectively through rationlalvtics at five levels: LlL2 Ld L5(Figurehe basic building blocks of the securitylement are an adversary model andgent threat analytics An advercol the basic objectivesThe security elementzed in terms of the assumptions, goals and capabilities of theiversary It is also crucial to analyze the adversary model in terms of environment, location, network,es, equipments, devices, actions, results, risks, reasons and motivations of attacksd probablersary attad to obtain what data)Let us consider the security of an infooff authentication authorizatiorrect identification, piauditnfidentiality, non-repudiation and data integrity

For ane service, the system should ask thentity and authentication of one or more agents involved in a transaction The agents of the same trustkip authentication but it is essentia for all sensitive communicatiAfter the identification and authentication, the system should address the issue of authorization The systemThestem should ask the credentthe requester; validate the credentiaerform a specific task as per agreed protocol Each agent should be assigned an explicit sete Privacy is another important issue: an agent can view only the informaticself The agents mushetiality of data exchange asf theon system; the issue of securgital signature,The fundamental objectives of cryptography are toovide confidentiality, data integrity, authentication andpudiation Cryptographormation through encryption methods Data integrity ensures that data is protected froruthorized modifications or false data injection attack The system should provide public verifiabilityat anyone can verify the integrity of the data Redundancthrough replicateinformation security andBut thereher different types of security concerns At level L2, it is required to verify theparty computation associated with a technological innovation in termsairless robustnesstransparency, accountability, trust and cetmentes correctnessgent broadcasts correct data and each recipient receives the same correct data in time without anyand rational reasoning on payment function, trust and qualitye Fairness ensureat somethingReference of document: EBOOK/ SCHAKRABORTY/BA/V30/15082019P

rilOr wur infinitely often under certain conditions Theients expect fairness in privatcommunication according to their demand plan, objectives and constraints The sending agent expeairness from the recipients in terms of true feedback and commitment on confidentiality of data As perfairness of secure multi-party computation, either all parties learn the outputity and non-repudiatiofact, accountability is also associatedlective incation protocolation principle and automated systerechanism should clearly statedefine a policy Thereata without any provision of privacy On the other side, a fully private system providesPritbe achieved using cryptographic techniques at increased cost of computation andcommunication Is it possible to trade-off privacy vs transparency? Is it possiblecrall state without disclosing information about the state of each entity? PublicVerifiability allowo verify the correctness of the state of the sysnsistency,resiliency, liveness, deadlock freenethat some particular state or situation can be reached Safety indicatescertain conditionslectrical electronicsgineering

Liveness ensures that under certainevent will ultimatelyDead lockfreeness indicates that a systemwhichsible this indicates thecorrectness of a real-time dynamic system Another important issue is robustem The delthe output should be guaranteed and the adversary should naten atack against a protocolAt level L4, it is required to assess the risks of various types of malicious attacksk, sybil attack, shilling atlevel lrequired to assess the riskstypes of corruptions such as agents (eg sending agent,receiving agents), system administrator, communication protocol and payment function of a mechanismtechnological innovatiFor example, preverpproacof expanding threats and risks, real-time system monitorine routinees Theonly rely on trant-and-detecte strategies and rule based security but should adopt cloud based solutions andlding blockty protection which should bevelocity and variety of datAI and machine learning techniques, Intelalytics are expected to detect anomalous patterns bomparing with the normal profile and the activitiesusers, peer groups and other entities such asvices, applications and smart networks and trigger alarms by sensing single or multiple attacks on thene the barriersg security, application development andns and be integratedstem architectarchitecture Theechanism should surfacealies and adjusts individualized securityme to protect the critical datastem Adaptive Security with dynamic data protection is expectedbenefits over traditional security platforms dependze of the system and complexityamage of a threat and reduction of resolution time The emerging technology is expected to adapt to theeeds of a system irrespective of the size of network, nature of operatis the requirements of security with greatergh a setelligent policies andbetter understanding of strength, weakness, opportunities and threats of the6 STRATEGYReference of document: EBOOK/ SCHAKRABORTY/BA/V30/15082019

strategyanalysisdiflusionife-cycle analysisEmergence/ hirthpervised learningKnowledgeTranster learningThreatsness intelligenceapplicationdeep analytics is strategy IFigure 1 6 This element can be analyzed from diffsuch as R&D poSWOT analysis, techrendAn intelligent r&Dshould be defined in telpal, strategic alliance, collaborative, collective and business intelligence Top technological innovationsclosely associatedarious strategies of organizatarning and knowledge management,specifically creation, storage, transfer and intelligent application of knowledge It is essential to analyzestrength, weakness, opportunities, threats, technological trajectories, technology diffusion and dominantesign of top innovations today Diffusion is the movement of molecules from high density zone to lowtechnology diffuse in the same way globally? What is theIs the external pressure natural or artificial? Another analogy iso high density zone through a barrier? Can themerging technology spread and move from low to high density zone smoothly like osmechnological innovation is closely associated with R&d poonal le-doing and learning-before-doing [6,7] Learning by doing is effective in semi-conductor manufacturingand bio-technology sectors which demand low level of theoretical and practical knowledge On the othere through various methods such as prototype testing, computernts

It is effectivemical and metallurgicalgineerIngcommercial proof ditt plore the role of deep analytiming of technology tranroduct dngineering and R&D cost of top technological innovations It is important to compare thecost, quality and timealso criticalvation and learningn terms of dynamic cost reductioId ln casespecific production environment But, some knowledge may betransferred to commercial productintIt is also interestingpment facilities, geographic proximity between R&D lab and producdant and theduplication of cquipment betweerlopment and production facilities on practical implementationspeed and effectiveness of top technological innovations It is essential to identify the critical succesReference of document: EBOOK/ SCHAKRABORTY/BA/V30/15082019P

urce allocation, ERP and SCM strategies)that influence the rate of learning and superi61 SWOT Analysism四,9mmnmentale 17: SWOT Analyto evaluate strength, weakness, opportunities and threats of a technological7] There may be major andweaknpositive aspects,eakness indicatesns and disadvantageshat option Opportunities indicate the areas of growth of market andprofit Threats are the risks or challenges posed by an unfavorable trend causing deterioration of profit or62 Technological life-cycle analysisBirthGrowthMaturityDeclineMarket penetrationTime frFigure 18: Technology life-cycle analysIsDeep analytics evaluateinnovations in terms of technology life-cycley trajectoryand dominant design nelogy emerges, growof maturityI to evaluatestatusturity stage Emergence of new technologies follethe technology lifeth other technologies, systems, cultures, enterpriand impacts on society, All techne from thhey interact with each other to formlex technological ecologies

The parenDNA which interacts to form the new development A new technological development must be nurturedany technologies perish before they are embedded in their ents Next phase is growth; ifal changes At somt all technolint of unstableaturity ic a strategic inflection point The final stage is decline and phase out or expire; all technologiesentually decline and are phased outire at a substantial cost TLC may have other different types ofases such as acquisition, utilization, and phase-out and disposal: preparationnd operation: organization, directive, delegation, coordinate, collaborative, and dissolution; acquisition;and mReference of document: EBOOK/ SCHAKRABORTY/BA/V30/15082019Page 15

Let us consider the analysis of the performance of a new technology vs effort; it is basically an S-cuis difficult and costly to improve the performance of a new technology The perfoimprove with better understanding of the fundamental principles and system architecture Finally, thedueunties and risks Gradually, this new technology is adopted by largef thearket due to reduced cost and risks gradually the diffusithe saturaften faster than the ratarket demand over time thearket share increases with high performanTechnological change follows a cyclical pattern Theolution of a technology passes through a phase of turbulerpply chain explore different competing design options of the new technand convergence of structure Then, the producers try to improve theciency and design of products based on stable benchmark of the industry The doadvanced technological features which meet the demand of the customerply and design chain in the best possilTechnology trajectory is the path that a technology takes through its time and life-cycle from thepectives of rate of performance improvement, rate of diffusion or rate of adoption in the market

Ittopkedly after a dominant designe improvement utilizinparticularal approach is expected to follow an S-curve pattern The evolution ofn is determinedtersecting trajectories of perfhow new technologies spread through a population ofters such Charsovei early adopters, early majority, late majority and laggardsnnovation characteristics of social enynent and7 STAFF-RESOURCESMethodce mgmtFigure 19 outlines the sixthnt of deep analytics ic staffan machinefuncmpensation, reward, incentive and performance evaluation "Machine analyzes the basic aspects of toolsand automated semi-automatedanual machines: ' material analyzes planning of raw materialReference of document: EBOOK/ SCHAKRABORTY/BA/V30/15082019Page 16

ts, semi-finished and finished gpects of process innovation,telligent mechanism and procedure, Finaley' highlights optimal fund allocation for R&Dtional investment analytics, intelligent project analytics and portfolio rationalizationfective technological evolution and diffusion such as 5Mthine, material method anddominant desictors, effects of timing and mode of entry Innds the commitment ofle Creativity is the underlying procthrough intellectual abilities, thinking style, knowledge, personalitytment andh environmentntribute through their inventive and entreve mindset Some users or customersnew products or services based on their own needs Manyfirms set up excellent R&D lab and also collaborative networks with culiers academicound research mission and vision and contribute through pubplays an active role in R&D either directly or indirectly or through collaboration networks and start-ups(e g, science parks and incubators)share the a petencies of technological innovations through efficient sharing for sms It is ta cost,antions through creation storageand applicationowledge arSearcganizations

Collaborative networks are other sources of innovation Collaboration is facilitatedeographical proximity, regional technology clusters and technology spillyorganizatioover to other firmsdevelopment of product and procsuccess factors of collaborative networks may be the right selection of innovation partners havingstrategic and resource fit, transparent and flexible monitoring and governance p

rocess so that theolution of clectronics and communication technology has been possible because of the involvement ofhe creative and efficient eeed useful andsupport of creative, skilled, experienced and knowledgeabCe talek at the problems in unconte new ideas andthrough their intellectual abilitmotivation, confidence, commitment and group dynamics The impact of knowledgdouble-edged Lack of knote is a major constraint to the original contribution in a technologicalbe biased and trapped in existing logic and paradigms It isonclude that moderate knowledge is adequate for creativity, a creative person is expectme obstacles by taking reasonable risks A cooperative and collaboratand reward creative talent in time Organizational creativity is associated wieral criticalctors suchuisition and retention policgement strategy, organization structure, corporate culturation,compensation, reward and incentive policy, social processes and71 Resource Allocation analyticsever,when the capacity is less than totalanager would have to find the combination of projects, which would fit the resource allocation model andReference of document: EBOOK/ SCHAKRABORTY/BA/V30/15082019

ContentSerialPageChaptersPartDeep Analytics-Technology for humanitySolar power electronics Nano solar cells: Dordesign and6chnoldiffusionSmart electrical hybrid vehicles: Smart batteries charging53mechanismRailTech:Driver Advice System(DAS), Security SafetyPart Ill: Emerging Digital TechnologyInformation Security Intelligence(ISI) Analytics: Adaptive Securityc Data protection foDT scadPartIV:HealthcareCancer prediction prevention: Deep learning, Genomics Precisi8Bio-medical technology for cancer care Surgical robotics, laser,89evasive wearable computinPart V: Earth Science- Water, SpaceArtificial rainfall: cloud physics, Laser collaborative resource sharingAstronomical hazards: Real-time moving target searchReference of document: EBOOK/ SCHAKRABORTY/BA/V3

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CHAPTER 1: DEEP ANALYTICS- TECHNOLOGYfor hUmanity1 INTRODUCTION: DEEP ANALYTICSStructureSkill-Style-SupportSystemecuritStaff-ResourcStratintelligencenalytics discovery fromdata (KDD)achineelligencegureDeep analytiintelligephased and-dimensional data analysisThe basic steps ofdata filtering/praput variables, features and dimensions(eg scope, system, structure, security, strategy, stalfressetdata analysis and knowledge discovery from data The authorized data analskill-style-support) correctly being free from malicious attacks(eg

false data injection, shilling): inpidata is sourced through authenticated channels accordingly The sourced data is filtered, preprocessed (egagging, boosting, cross validation) and ensembled It is rational to adopt an optimal mix of quantitative(eg regression, prediction, sequence, association, classification and clustering algorithms) and qualitatiReference of document: EBOOK/ SCHAKRABORTY/BA/V30/15082019Page 4

e g case baseding, perception, process mapping, SWOT, CSF and value chain analysis) methodsmulti-dimensional analysis The analysts define intelligent training and testing strategies in termslection of correct soft computing tools, network architecture -no, of layers and nodes; training algorithm,validation and stoppinganalysts audit fairness and correcalso reliabi(eg petabytes) data setsg is an advanced machine learning technique where artificial neural networks (e g CNN) can learntively from large amount of data like human braing a taskpeatedly and gradually improves the outcome of learning Deep analytics follotreamlined and structured process that can extract, organize andbeing acceptable, useful and beneficial(eg

individual human agent, organizationBIIformation system) It is basically a specific type of distributed computing across a numbernodes to speed up the analysis process Generally, shallow analytics use the conceptprobability, proportions, pie charts, bar charts and tabs to analyze small data set Deelalytics analyze large data sets based on the concepts of data visualization, descriptive and prescriptivetistics, predictive modeling, machine learning, multilevel modeling, data reduction, multivariatecoupled with bitelligence applications which perform query based search on large data,extract information from data sets hosted on aand distributed architectuation outcome such as reports, charts and graphs In this book,cs has been applied for technology management system(TMsechnological innovations are practical implementation of creative novel ideas into new products orns may be initiated in manys from various sources such as firmsarch laboratories, government and privatreats and demands from the prodervice providersand regulatorInnovation funnel is a critical issue in technology management;process is often perceived like apotential ideas passing through the wide end of a funnel but very few become successful,profitable, economically and technically feasible products or services through the development processnd consulting tool that is essential for effectiveof top technological innovations today [Figure 11] It is basically an integrated framework which iserfedimensiny technologicalects fail due to theability of the project managers to recognize the importance of the fit and their tendency tonly on a few of these factors and ignore the others These seven factorsbe inteoordinatedand synchronized for the diffusion of top technological innovations globally [1653Agents: Single or a group of data analySystem: Technology Management System/Technology for humanitysMovesAdopt a hybrid approach: quantitative e qualitativeo Collaborative analytics /agents: multiple data analysts"Constraints: Availability of authenticated and correct data, time, effort, costInput: Technical data(D,), Business data(D ); /*Entity An emerging technology for humanity/ProcedureSource data(D, DhEnsemble dataReference of document: EBOOK/ SCHAKRABORTY/BA/V30/15082019Page 5

qualiSWOT TLCChoice 2: quantitative analysis(Prediction, SimulationChoice 3: Hybrid (quantitative e qualitative)Multi-dimensionalysis KDD(SI S2, S3, S4, Ss, SoS7);/'SI: Technology scopS2, Structure sc hnology security, Ss: Strategy, S: Staff-DD: Knowledge discovery from dataRevelation principle:Audit fairness, correctness, reliability, consistencyayment function: Compare a set of technologies based on cost benefit analyOutput: Technologynce(collective, collaborativeUsiness)threeRequts engineering schema: scope [S11;(b)Techneema: systS, structure Sty [S4 and (c) Technology management schema: strategySaI and skill-style-support [S,l Figure 1 1

This chapter analyzes each dimensionp technology innovations today in chapters [2-10 applying the tool of deep anabasic building blocks of our research methodology include critical reviews of existing works on technologye have reviewed van,53 We have collected the datac cases from various technicala RESEARCH METHODOLOGY AND OPEN AGENDAThe basic objective of this book is to explore a set of fundamental questions on technologyc hema and dominant design of a system associated withtechnology innovationStructure: what are the basic elements of thearchitecture associated with achnology inon? How to represent the structure correctly and transparently throughecurity: What doan by technology security? Hoerify the security intelligenof a svstem associated with a technology innovationStrategyWhat are the strategic moves of technology innovation, adoption and diffusionWhat is the outcomechnology with the existing old technologies throughwhat are the technology spillover effectsise eRP and sCM in a technology innovationct? whatnould be the talent management strategySkill-style-supportat arestyle andechnology=ojects efficientlyWhat should be the shared vision, common goals and communication protocolsReference of document: EBOOK/ SCHAKRABORTY/BA/V30/15082019Page 6

How toe a perfect fit among "7-s elementsWhat type of organization structure istial for various types of technologyWe have adopted two approaches to develop 7-s model of deep analytics for technologicagement The first approach is learning-before-doing, We have reviewed relevant literaturery management and have deframework of theop emerging technologies today from the technical reportser ieee mit and other sources weand sustainabilities of the humanity globally There is too much focus on information and communicatitechnology; butal domains such as biomedical and electricalur society globally The most of these technologies arenrough growth phase As a part of learning-by-doing approach; we have analyzed these-s model and have backtracked to redefine the initial framework of deep analytics

We have foundents for the proposed deepanalytics whichtramline thelution and diffusiotechnFor instancedeep analytics may be 10-S model instead of 7-s in figure 11(b)Isnsider too many elements simultancously? Should we consider resourcesnstead of staff -resources? Should we decompose sixth element into skill,Should we position the element centrally or 'strategy'in figure 1 1?(c) There are 'C2 links(suchSl-S7, S2-S7,S3-S7, S4-S7, S5-S7, S6-S7) among 7-s elements of the deep analytics: what are theThere may be other various typesnsiderin5-S6-Shnologicalechnology(e)hefoster creatiity, learning rate, generalizabilityional learning?constraints and barriers against nine cases of technological innovations? There areseveral open issues of debate on the concept of deep analytics It is an interesting observation from thisbook thatin 21 century today: but we couldextensive R&D efforts are still pending for the sustainability of ht2 SCOPEScope analytics of technologicaTop-bottom approacIdentification of gapsSecondary value chaReference of document: EBOOK/ SCHAKRABORTY/BA/V30/15082019Page 7

echnoovation act and initiativesunching new devices methods or materialsmmercial and pracplications, It is one of the most critical competitive driversy industries such as informationnication technologies, high technology manufacturing and lifetion process; the impactbalization of markets and advancedcomputer sided design, computer aidedscale and short productiondiffumic effects, negative effects of technologicalges:R&D fund allocation strategy: pace, advantages and disadvantages of innovation, criticalctors, causes of failure; cost optimization and differentiation Technoessential tocreate new business models But, many innovation projects fail to make profit due tous reasons suchThe first element of deep analype [Figure 12] The scope of a technologyon projectnould be explored through various scientific and systematic methoccess factors(CSF) analysis, value chain analysis, analysis of business objectives, constraidwn 4aches, Process mapping analyzes a set of critical issueshat is as-is process? How to identify gaps of as-is process? How to innovate to-be process? What are theconstrainta setmodeation,application domain and industry analThe scope of a technologyn project is explored based on CSFs The basic objectives of valuers: what is value: ittionost leadershOw tOvation? what arthe activities associated with primary and secondary value chain? Primary activities add value to a produdirectly such as manufacturing and supply chain management; secondaryhain activitieschain activities Top bottom approach analyzes businessogyation projects On the other side, bottom up approach analyze asem, identifies gapsplores the basic needs or scope of a projectThe scope of a technological inexored through indysis and alsoexternal environment and various stakeholders associated with the value chain

In this connectionPorters six force model is useful to assess the bargaining power of the customers and suppliers, rolecompliments, threats of new entrants and substitutes and competition The internal environmetnould be accessed through swot annd rigiditiespotential strength and opportunities ofcope should be also explorerms of strategIcrspectives such as procen, organizationsatisfactionThe scope of technological innovations may be analyzed from the perprodir incremental architecturad competence enhancingvation productproducts or services Processor manufacturing process such asdecrease of rejection rate Componenoduct architectunnovation changes the overall desiscnts of ath each other radicalw and differesolutions incrementalWe havelored a sctputing, large scale cheap solarelgy for humanity, cachndata analytics, adayand dynamic data protection, smart transformers, applied AI and machinestedratio(oT), cloud computingreaming, Internet of bodies, Blockchain and distributed ledger tecash-proof code, social indexing, gestural interfaces, social credit algorithms, advanced smartdevices, activity security protection, virtual reality, chatbots, automated voice spam prevention, serverlessReference of document: EBOOK/ SCHAKRABORTY/BA/V30/15082019Page 8

uting, edge computing, real-time ray tracing, digital twins, tablets and mobile devices invative mobile applications and interfaces for a multichannel future, humalterface, context aware computing and social media, enterprise app stores and marketplaces, inn:-memory3 SYSTEMguremachines and agentsbe decomposed intteracting sub-systems Agleobjectivdesigned to achieveossible way It is possible to analyze a system from the perspectives of system state, complexity, modelcause effect analysis feedback loop, physicaly decisions [35-41] A system may be open or closed loop A hard system has clearly definedtitativeIt is hard to define theobjectives and qualitativetimemberting elements, number of linear and nonlinear dynamic relationshiptheents, number of goals or objectives and numbement

a model is an abf real system a model is isolated from its environment throtodel boundaries A model may be static or dynamic, linear or non-linear based on functional relationshipariables in a modeltechnological innovationsInformationpointsMiscellaneousTechnologyLifescienceelectronicsEarth ScienceComputingPolicy denformation fcholoch as information and communicgy,electricalelectronics, mechanicalemical, metallurgical, biotechnology, genetic engineering, pharmacy and others IT system can benalyzed in terms of computing, communication or networking, data, application and security schema andso application integration (EAI) An clectrical system may havech as powemrenewable cwer clectronics maasurementReference of document: EBOOK/ SCHAKRABORTY/BA/V30/15082019Page 9

instrumentation, illumination and high voltage engineering Aex system may be associated witharious domains of earth science such aswater wind and solarThe basic objectives of system analytics are to analyze complex, dynamic, non-linear and lineartypes of systems and design new structures and policies to improve the behavior of adynamics are cause effects analysisve feedbackd physical and informThe basic functions of systerblem and model boundary, buildinodel, testing and validation oflicy alternatives andcommendation of most viable R&d policy related to technolvations [424 STRUCTUREThe third element of deep analytics is structure ie the backbone of aassociated with a specifictechnological innovation [Figure 14]

What are the basic elements of the systervation? It has two critical viewpoints: system architecture andstructure The first oneders technological aspects of the system architecture in terms of topologus components of industrial control system such as SCADA, Expert system, DeThe topology of a system should be analyzedyers, interfaces bete OSI model is ak for the designphysical, data link, network, transport, sessionnd application layers a danication system hamessage, sender, receiver,n medium and protocol On the basis of nodes and links, the physipology of a communication network can be classified into four categories such as mesh, ring, star andwhat type of structure is suitabbetween technology andIt depends on the characteristics of business modeshould be explored in terms of organization structure, size of a firm,scale in R&D, access to complementaryces such as capital and market, goveand organizational learning There are various types of organization structure such as divisional andmodels, The effiepes of structural dimensions such as formalization, standardization, centralization, decentralization andlyhin and between firms, global firms should consider several critical factorsh as knowledge, resources and technological diffusion to conduct R&D activitiestheologicaarchitectureSmart gridStandalone systemFigure 1 4: Structure analyticsReference of document: EBOOK/ SCHAKRABORTY/BA/V30/15082019P