Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology

EFFICIENT BIG DATA ANALYSIS ON COVID-19 MEDICAL DATA USING MACHINE LEARNING TECHNIQUES

Satya Sukumar Makkapati*, DR. N. Nagamalleswara Rao & DR. Popuri Ramesh Babu — 2022-12-08

In the present technological era, massive amounts of big data are rendered and gathered from various rich data sources. These big data can be of distinct levels of integrity because some are actual while others are vague and indecisive. Embedded in these big data are valuable data and valuable knowledge. Examples of these big data are healthcare and epidemiological data, such as data related to patients who are sorrowed from epidemic illnesses like the coronavirus disease 2019 (COVID-19). Due to the quick spread of COVID-19 to almost every part of the world, massive volumes of data and case investigations have been created, providing investigators with a special opportunity to discover tendencies and make findings like never before by leveraging such big data. This paper demonstrates the growing database of COVID-2019 has been studied from March 1, 2020, to April 11, 2020, and the next one is forecasted for the number of patients suffering from the rising COVID-2019.Various regression analysis models have been operated for data analysis of COVID-2019 in India based on data kept by Kaggle from 1 March 2020 to 11 April 2020. In this analysis, we have performed three regression analysis-based models, namely quadratic, sixth-degree, and exponential polynomial, respectively, for the COVID-2019 dataset. We have calculated these three regression analysis models’ roots mean square error (RMSE). In these three models, the RMSE of a sixth-degree polynomial is significantly less than others, like a quadratic and exponential polynomial. Thus, the sixth-degree polynomial regression model is an excellent model for predicting the next coming days for COVID-2019 data analysis in India.

THE EFFECT OF A PREDOMINANT PULSE PERIOD (Tp) HANGING WALL, AND FOOTWALL IN THE NEAR-FAULT GROUND MOTIONS ON A SINGLE DEGREE OF FREEDOM SYSTEM (SDOF)

Layla Akram* & Dr. Hussam. K. Risan — 2022-12-08

This paper aims to study the responsiveness of buildings with a single degree of freedom system in near-fault under the influence of the hanging wall and the footwall in addition to studying the influence of the predominate pulse in this type of ground motion, where it turns out when taking the readings that most of the mechanical motion of the ground in the area of the near-fault is of the reverse type and this is what calls to study the impact of the hanging wall and the footwall. Strong ground motion data were taken for different events in different places around the world and the ground motion parameters were used which are the peak acceleration of the Earth (PGA), peak velocity of the Earth (PGV), peak displacement of the earth (PGD), prevailing frequency content (TP).

COMPARISON OF SYMMETRIC AND ASYMMETRIC ENCRYPTION ALGORITHMS AND TECHNIQUES FOR IMPROVING DATA SECURITY IN A CLOUD PROVISIONED BANKING

Chandrashekhar B, Dr. Mohammed Abdul Waheed — 2022-12-08

A significant issues in cloud provisioned Banking frameworks, is the information security, which centers around the assurance of data against unapproved access. As various occupants including organizations access the framework, delicate data ought to be given distinctly to approved clients and inhabitants. In this paper, we dissect the prerequisites of information security for Banking in multi-inhabitant cloud frameworks and examine to adjust Various Encryption Algorithms and Techniques for further developing information security in Cloud Provisioned Banking.

DEVELOPING A NETWORK MODEL WITH OPPORTUNISTIC COMMUNICATION FOR TRACKING EVACUATION OF THEME PARK VISITORS IN DISASTERS

Arati Bachanna & Manoj Patil — 2022-12-08

It will consolidate the non-deterministic conduct of the human walking plan with the deterministic conduct of attractions in a subject stop. We confined the attractions into get-togethers of principal rides, medium-sized rides, live appears and cafés. We are going utilize lining theoretic models to compute times went through by visitors at different attractions. We affirmed the precision of our demonstrate through wide generations utilizing subject stop experiences, GPS takes after accumulated in a honest to goodness subject stop and the information delivered by amusements of other compactness models. The results will appear that our show gives a predominant coordinate to this display reality data contrasted with SLAW and RWP. We are going utilize honest to goodness subject stop maps to show the calamity condition. The movability of the visitors is shown utilizing the topic stop models and the social control show. Through the reenactments, our show is surveyed in relationship with the results of TP, SLAW, RWP, and the GPS takes after. Other than, the impacts of the uncommon parameters of the show, for case, perceivability and anticipated number of red-zones are inspected.

A SYSTEMATIC EVALUATION ON LABOUR PRODUCTIVITY IN CONSTRUCTION SITE

Parmar Sarthak R, sst.Prof. Mamata B Rajgor — 2022-12-22

One of the biggest industries in India is Construction. But there have been delays with the majority of the construction projects. Project delays in the construction industry are frequently brought on by lower than anticipated labour productivity. Although determining labour productivity is simple and easy, doing so is sometimes more difficult. The main purpose of the study is to identify the key variables that affect labour productivity. The findings should help project managers in the construction industry to increase labour productivity at their locations. To learn more about how construction workers perceive the factors that affect their productivity at work, a study was performed with them. Also, to make effective and Systematic strategies to increase labour efficiency at the site have also been determined by surveying management engineers who work directly with construction labour to produce construction works. These findings ought to help project management teams get the most work possible out of their construction labour forces. They can employ the preventative methods suggested in this study to maintain productivity at its peak and to spot the early warning signals. The main learning from this study will help in getting the correct directions for the better management of CLP in different geographical regions.

HOMOTOPY PERTURBATION METHOD FOR THE MHD SECOND-ORDER FLUID FLOW THROUGH A CHANNEL WITH PERMEABLE SIDES

Reshu Gupta — 2022-12-22

The flow of the second-order fluid flow through the channel with permeable walls is discussed. A uniform magnetic field is imposed orthogonally on the axis. In modern time, many numerical techniques are used to solve the linear and nonlinear problems of mathematics and engineering. The obtained nonlinear partial differential equations are transformed into a nonlinear system of ordinary differential equations (ODEs) with the help of similarity transformation. In the article, the homotopy perturbation method (HPM) is applied to get the solution to the system of nonlinear ODEs. The second-order fluid behaves electrically conducting in the occurrence of the uniform magnetic field. The results obtained from this technique are discussed for the various parameters and are presented graphically. Also, the results show that the HPM can achieve virtuous output in expecting the result of such models.

COMPUTATION OF X-RAY POWDER DIFFRACTOGRAMS

Donga Sunil, Dr. N. K. Dhapekar — 2022-12-22

The importance of computed X-ray diffraction patterns of various polymorphs of alite (M3, T1, R), belite (β, γ ), aluminate (cubic, orthorhombic), aluminoferrite, gypsum and hemihydrate in the quantitative phase analysis of cement and its early stage hydration performance is highlighted in this work with three OPC samples. The analysis shows that the predominant silicate phases present in all the samples are M3 -alite phase and β-belite phase, respectively. Both cubic and orthorhombic phases of C3 A, brownmillerite, gypsum and hemihydrates are present at different levels. Quantitative phase analysis of cement by Rietveld refinement method provides more accurate and comprehensive data of the phase composition compared to Bogue method. The comparative hydration performance of these samples was studied with w/c ratio, 0·5 and the results are interpreted in the light of difference in phase compositions viz. β-C2 S/C3 S ratio, fraction of finer cement particles present in the samples and theoretical modeling of C3 S hydration.

TO MAKE SYMBIOSIS: ADAPTIVE REUSE OF PORT HERITAGE IN THE REGENERATION OF URBAN WATERFRONT. A CASE STUDY

2022-12-22

Globalization and advancement in technology have driven lots of port cities shelved their original functional territory, leaving bunches of factories and warehouses abandoned; whereas expansions from the inner cities are longing for the land and resources accumulated at the water edge to optimize the urban development, which causes the emergency of these controversial historical elements at the same time. Even knowledge and experience from icons of renewal projects with long history have inspired us what extent of significance and profitability the port heritage can be when managing waterfront regeneration strategy, yet the specific measurement to deal with those old port-related pieces rather than demolition, typically, for many small-scale inner port cities is far more than necessary. In this paper, a scheduled plan for port heritage is revealed that the vacancy and recession is just temporary, adaptive reuse of port-related constructions will contribute to the waterfront revitalization for the city through symbiosis settings as multi-functional generator, culture and recreational deliver, and landscape infrastructure in corridor. The article is motivated by the previous case studies and literature reviews, while for local case study (Yong Li Dockyard), a hypothetical design using strategy mentioned is proposed. The transformation result finally reveals that regeneration of port heritage can be a very useful bridge to connect waterfront itself and city, past and future, and fully applicable to other cases with different urban context.

COMPARATIVE STUDY OF MICROPOLAR FLUID FLOW BETWEEN TWO DISKS

Reshu Gupta — 2022-12-25

A comparative approach is used to analyze the steady flow of a micropolar fluid between two parallel stationary disks with permeable walls. In this study higher-order non-linear partial differential equations are transformed into a system of non-linear ordinary differential equations by using Von Karman’s similarity transformation. Analytical methods, Adomian Decomposition Method (ADM) and Homotopy Perturbation Method (HPM) are adopted to get the solution of obtained non-linear ordinary differential equations. The performance of the streamwise velocity, normal velocity components, and the microrotation for various numeric values of vortex-viscosity (m_1), spin-gradient viscosity (m_2), micro-inertia density (m_3), and suction Reynolds number (R_o) have been presented graphically. The validity of results obtained by ADM and HPM are verified by numerical results. MATLAB software is used for the calculation of velocity and the microrotation components and numerical results.

ROLE OF MUNICIPAL CORPORATIONS IN ADDRESSING ENERGY TRILEMMA THROUGH HOUSEHOLD SOLID WASTE MANAGEMENT: A CASE STUDY OF PUNE CITY, INDIA

Apurva Bhilare — 2022-12-31

The massive energy demands and solid waste generation of urban households tend to disturb the balance of sustainability. In the era of circular economy, recovering energy from waste has been considered as a viable option to address this catch-22. Further, World Energy Council’s measurable parameters like, security, access, equity sets the goals for the nations to attain energy sustainability at global level. This empirical research aims at critically evaluating the implementation of waste management mechanism and functionality of the waste to energy infrastructure in Pune City, India. On basis of this case study, the research further promotes the capacity building approach for energy recovery from waste and decentralized systems approach for household solid waste management and emphasizes need for relevant policy and legal framework by the local governments.

HYBRID RESOURCE ALLOCATION TECHNIQUE FOR CLOUD COMPUTING

Rakesh Pandit* & Dr Mona Dwivedi — 2022-12-31

The scheduling and distribution of resources are the two main factors in cloud computing that affect the overall quality of services. Since allocating resources inside a single cloud environment is such a complicated procedure, cloud computing necessitates the deployment of a resource allocation module that is both effective and efficient. While the complexity of the techniques used for allocation is further increased by the allocation of resources in a setting with many clouds. In the past, the multi-cloud environment's resources were allocated based on the demands of various workloads. It is vital to do research on the existing availability of resources and their skills before allocating resources to the activities that have been requested. As a result, the goal of this study is to offer an optimised hybrid resource allocation model that takes into account the job requirements, bandwidth needs, resource status, and distance. To distribute the resource, this model employs the particle swarm optimization technique and the bat optimization algorithm. The effectiveness of the suggested model is evaluated by simulation, and the outcomes are contrasted with those of conventional optimization techniques. With a minimal energy consumption of 168 kWh, the approach that has been provided can distribute the available resources across 400 activities in around 48 seconds. The performance of the suggested model is much superior than that of traditional methods in terms of the number of missed deadlines for assignments, the amount of resources required, the amount of energy utilized, and the amount of time provided.

OPTIMAL STATISTICAL STRATEGY FOR TEST CASE PRIORITIZATION

Bharti Bhattad* & Dr. Sachin Patel — 2022-12-31

Programming testing means to guarantee the nature of programming under test. To improve the proficiency of programming testing, particularly testing, experiment prioritization is proposed to plan the execution request of experiments in programming testing. Among different experiment prioritization methods, the straightforward extra inclusion based strategy, which is an eager technique, accomplishes shockingly serious exact outcomes. To explore how much contrast there is between the request created by the extra strategy and the ideal request regarding inclusion, we direct an investigation on different experimental properties of ideal inclusion based experiment prioritization. To empower us to accomplish the ideal request in worthy time for our article programs, we plan ideal inclusion based experiment prioritization as a whole number of direct programming issues. At that point, we lead an observational investigation for contrasting the ideal procedure with the basic extra inclusion based procedure. From this experimental investigation, the ideal strategy can just marginally beat the extra inclusion based strategy with no factually huge distinction as far as inclusion, and the last essentially outflanks the previous as far as either shortcoming location or execution time. As the ideal procedure plans the execution request of experiments dependent on their auxiliary inclusion as opposed to identified flaws, we further actualize the perfect ideal experiment prioritization method, which plans the execution request of experiments based on their identified issues. Accepting this perfect skill as the upper bound of experiment prioritization, we direct another experimental investigation for looking at the ideal method and the straightforward extra testing strategy with this perfect skill. From this experimental investigation, both the ideal method and the extra strategy essentially beat the perfect skill regarding inclusion; however, the last fundamentally outflanks the previous two procedures as far as issue identification.

RETROFITTING OF DILAPIDATE STRUCTURAL MEMBERS OF RESIDENTIAL BUILDING DUE TO CARBONATION AND ITS EFFECT ON REINFORCEMENT

Miss. Deepali Sunil Barad*, Raju Narwade & Dr. Karthik Nagarajan — 2022-12-30

Corrosion of reinforcement is one of the devastating form of deterioration that any concrete structure has to withstand. One of the leading causes of corrosion often overlooked is the process of carbonation in the concrete. Carbonation is the reaction between calcium hydroxide and atmospheric carbon dioxide. This reaction reduces the pH concrete which causes the corrosion of the reinforcement in RCC structural elements. This paper deals with a case study of repair of columns damaged by carbonation induced corrosion. This paper incorporates use of Indian Standard 15988-2013for retrofitting of these damaged column. The case study has been taken from one of the building in Navi Mumbai, India which was undergoing distress due to cracks in two external columns. Servers cracks were found of the columns and after evaluation of strength of concrete, it has been decided to carryout retrofitting of these two columns using IS 15988-2013. After strengthening the columns using jacketing method, the building appears to have stabilized and no further crack propagation has been observed in the building.

DETECTION AND ANALYSIS OF NETWORK TRAFFIC IN NETWORK FORENSICS USING MACHINE LEARNING

2022-12-25

In this study, an automated system that can gather and process network packets is built. Machine learning techniques are used to create a traffic classifier that divides packets into hazardous and non-malicious categories. In the past, several conventional strategies were used to classify the network utilising tools; however, this method combines machine learning, a study area that is currently active and has produced good results so far. The main goals of this article are to analyse and control intrusions while also monitoring traffic. The traffic data collection KDD is used to develop a traffic classification system based on features of observed network packets. This category will assist the IT administrators in identifying the undefined assault that is becoming more common in the IT environment. The proposed methodologies detailed in this research, which help in gathering network packets and detecting which attack was carried out in a certain network, apply the machine learning algorithm to differentiate between dangerous and normal packets. The main objective of this project is to provide a proactive network attack detection system using machine learning based classifiers that identified incoming packets and discriminated between harmful and non-malicious network packets using rules from the KDD dataset. The system is trained using the attributes of the NSL-KDD dataset.

DDOS ATTACK DETECTION IN SOFTWARE DEFINED INTERNET OF THINGS USING UNSUPERVISED LEARNING APPROACH

Pinkey Chauhan, Mithilesh Atulkar — 2022-12-25

Both the area of software-defined networking (SDN) and that of the Internet of Things (IoT) are on the rise because of the convenience they provide to device management via simplified data access. In the same way that software-defined networking (SDN) makes it possible to employ a wide variety of devices for network management, the Internet of Things (IoT) makes it possible to collect data in a wide variety of real-time settings. When users put the two together, they have a setup where a number of devices may be utilised remotely and controlled from one location. Consequently, several attacks on the SD-IoT controller have arisen since its introduction. One such attack is a distributed denial-of-service (DDoS) attack, which prevents the server from responding to valid requests. To counteract DDoS attacks, this study provides a comprehensive strategy for creating datasets, training models, and deploying them to the controller of SD-IoT. Several popular unsupervised classifiers have been trained on the newly created dataset. These include KMeans, MeanShift, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), AgglomerativeClustering, Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH), MiniBatchKMeans, Ordering Points To Identify Cluster Structure (OPTICS), and SpectralClustering. Silhouette Score (SS), Calinski Harabasz Index (CHI), and Davies Bouldin Index (DBI) have been used to assess their effectiveness. The OPTICS classifier has been implemented in the SD-IoT controller because of its superior performance. It is found that OPTICS classifier is outperforming other classifiers, so it has been deployed in the controller of the SD-IoT

INTELLIGENCE PULMONARY TUBERCULOSIS DIAGNOSIS USING A HYBRID CLUSTERING AND RANDOM FOREST ALGORITHM

Sıraj Sebhatu, Parma Nand , Pooja — 2022-12-30

Tuberculosis (TB), according to the World Health Organization (WHO), tuberculosis (TB) is a disease that has been described as a major global health concern. In 2019, approximately 10 million cases were registered, along with 1.2 million deaths. A country-wide survey conducted in India between 1997 to 2021 WHO report a case of TB established that the issue was precise, with 188 cases of Positive Pulmonary Tuberculosis Bacteriologically testing being found at the national level for every 100,000 people (PTB) and the incidence of the approximate report at 2,590,000 million cases [1]. Tuberculosis has clinical symptoms that determine whether a patient has the disease complex without adequate testing. It is essential that the diagnostic process is enhanced and that patients be encouraged to continue with their medical treatment adherence. This study introduces a model for diagnosing early pulmonary tuberculosis disease. According to the current study, it successfully improved diagnostic accuracy and introduced a new hybrid model that could provide a framework for similar medical disciplines in this domain. The Random Forest model achieves a high-performance testing score of AUC 98.90%. Clustering-enhanced data-tuned disease diagnosis with tuned parameters and a cluster test score of 99.8.

IOT-BASED INTIMATION OF POISONOUS GASES USING SPANNING TREE ALGORITHM

Karishma Mandal, Shilpa Gaikwad — 2022-12-25

Each new industrial accident contributes to an overall increase in the risk to human life. Reduces the risk of industrial disasters by developing a single device with a radiation and dangerous gas detection monitoring system that is connected to the internet of things. The purpose of this study was to ensure that industrial accidents are avoided and to monitor the activities of the pollution control board. The primary purpose of this project is to investigate Internet of Things (IoT) methods for the early warning of toxic gas emissions utilising the spanning tree algorithm. A sensor to collect data from the surrounding environment at the time of the leak. This instrument is utilised for the detection of as many different gases and types of radiation as it can. The programme was tested with single or multiple dangerous gases and radiation leaking, and the results showed that the response time was high and was quite quick. An alarm is a sound signal that is produced and utilised to alert industries that are in the vicinity of living people. After the gas has been identified, the pin will transition from 0 to 1, at which point the microcontroller will show the warning message and subsequently notify the GSM. If the levels of the gases and radiation were to rise over the typical level, an alert would be sent out via the internet to a certain website and also to an Android app. At first, the system was built so that it could build a single webpage and an android app. This information is also visible to a large number of users, and it mostly focuses on the radiation and gas leaks key advantages. It will be a solid start for sectors concerned with keeping people safe in their daily lives if sensors collecting all data store it on internet corresponding websites, which can then be used for further processing.

RECENT TECHNIQUES IN HIGHWAY CONSTRUCTION

Pratik Kumar Kathale, Dr.N.K.Dhapekar — 2022-12-30

The maintenance of of flexible and rigid pavement is very important for the life cycle of the road strength of the road and smooth traffic moment in the highways .The major budget is spent on the maintenance of the road .The need of the cost deduction in the maintenance and construction of flexible pavement is helpful ,using of new materials ,change in the fine sieve size of the aggregates and increasing the bituminous binding percentage help in enhancing the binding property on the old rough surface of the patch which have to be repaired ,various machines are discovered for the instant maintenance,The Ministry of road transport & highways gives specific rule book name specifications for road and bridge works Indian road congress ,the methodology has been described in the volume. The steps should be strictly followed by the for rapid repairing work of the flexible pavement and enhancing is strength again.

ENHANCING IOT SECURITY USING 5G AND TECHNOLOGIES FOR 5G NETWORKS

*Pratik Shah, *Dr. Deepika Pathak — 2022-12-30

5G is still in its infancy, and no consensus has been reached on what it will include. As hard as the standardising process is, others opt to concentrate only on it. This research considers a wide range of breakthrough technologies that will shape wireless in the years to come as we migrate from 4G to 5G. Next-generation wireless networks, even if there is no one image of what they will look like at their most expansive, will deliver almost everything to everyone. IoT (Internet of Things) growth will be aided by 5G, which ITIF believes will provide massive capacity increases, lower costs, and higher levels of reliability for critical communications and large-scale industrial automation. 5G is expected to allow for ultra-high-definition streaming of augmented reality, as well as a greater number of low-cost connections.

IDENTIFYING AND ANALYZING TIME SERIES DATA PREDICTION USING DEEP LEARNING

Vivek Uprit, Dr Pritej Yadav, Dr Sanjeev Gupta — 2022-12-30

In the present scenario, Time Series data analysis is crucial for Decision Makers. In various fields varying from medicine to finance. These diversified and critical utility Time-series data analysis motivates researchers to perform it in a more precise and accurate manner, especially the future value prediction. As the data involved are usually huge in the volume. Therefore, the implementation of Deep learning will provide more meaningful insides. For doing this the identification of impacting Hyper parameters and related algorithms is to be done. So, the value predicted from former specified hyper parameters and an algorithm should be effective and efficient.

DEVELOPMENT OF PROJECT MANAGEMENT MATURITY MODEL FOR CONSTRUCTION FIRM IN VADODARA

Rushi V. Patel, Asst. Prof. Mamata Rajgor — 2022-12-30

Identifying the methods followed on building sites in emerging nations is becoming increasingly difficult due to rising competition in the construction industry. An organisation can only increase its Project Management competence via the usage of maturity models. The goal of this study is to provide a structure for evaluating the "Maturity Level of Construction Projects" in the leading smart city of Gujarat. Eleven factors were considered while developing the questionnaire; ten were gleaned from the literature, one was contributed by an expert, and two were derived from actual building site procedures. We used the Rank Sum Method, the Probability Method, and Statistical Tools to compile the feedback of key stakeholders with a focus on quality, including the Project Owner, Project Management Consultants, the Project Manager, and the Contractors. Vadodara, a city in Gujarat, has its own Maturity Assessment methodology with 5 stages (Initial, Controlled, Managed, Defined, and Optimized). The Maturity Framework was conceived using a survey questionnaire. Applying the proposed model to a building site would reveal how developed the site is, and the practises involved would be clearly outlined in a questionnaire, allowing for further refinement via implementation.

IMPROVISING CONSTRUCTION INVENTORY MANAGEMENT USING IOT

Anurag Pandita*, Nimita Gujar — 2022-12-30

The Internet of Things (IoT) has been implemented as a component of cyber physical systems across many different sectors in this cutting-edge age of Industrial Revolution 4.0, but its adoption in the construction sector is still limited to a few applications. This study looks at, analyses, and assesses the obstacles to using IOT in construction projects. In this work, we describe an effective inventory management system for a variety of applications dealing with solid or liquid assets. By integrating IOT-based inventory management, we minimize needless manpower and automate the measurement and order placing processes, hence enhancing inventory management efficiency. Recent advancements in the IT sector, such as smart phones and communication technologies, have led in the fast rise of Internet of Things (IoT) technology and related markets.

LIFE CYCLE COST AND ENVIRONMENTAL IMPACT ASSESSMENT OF HIGH-RISE RESIDENTIAL BUILDING

Dharmesh Kakreja, Nimita Gujar — 2022-12-30

Potential costs may be estimated with the use of Life Cycle Cost Analysis (LCCA), a valuable tool for projecting costs into the future. Using a tried-and-true method for systematic literature review, publications published between 2015 and 2020 are culled from databases including Scopus, Web of Science, Springer, Elsevier, Science Direct, Emerald, and the Proceedings of the American Society of Civil Engineers. Life Cycle Environmental Assessments (LCEAs) and Life Cycle Cost Assessments (LCCAs) were utilised in the majority of the studies we reviewed to isolate the environmental and financial aspects that affect a building's sustainability. Many studies have tried to figure out the most economical and ecologically responsible structural design for buildings while also offering a conceptual framework for assessing sustainability by choosing the most economical and environmentally friendly product designs.

LEAN CONSTRUCTION TECHNIQUES APPLIED IN THE INDIAN CONSTRUCTION OF ROW HOUSE

Pankaj R Sharma, Asst. Prof. Mamata Rajgor — 2022-12-30

To increase efficiency in the construction industry, lean construction is a powerful management tool. To apply lean ideas from the manufacturing sector to the construction industry, significant research has been conducted recently and is still being done. Lean construction is a modern management technique that aims to increase productivity and reduce waste. The Indian construction sector is facing several difficulties in applying the lean approach. The adoption of the lean management approach for a construction project is still in progress because of a lack of interest in and ignorance of the concept among stakeholders including builders, contractors, engineers and project management organisations, etc. With the use of a questionnaire survey, attempts are made in this article to identify the primary obstacles to the application of lean principles in the Indian construction sector. Additionally, practical site implementations are made to create a process map for active projects. The survey's results indicated that in order to improve the lean building process, several lean practises should get greater attention. The findings indicate that the non-value-added and essential non-value-added activities have the greatest influence on the project's length. Because of this, by using the suggested lean strategies, the NVA and ENVA operations are enhanced, and their durations may be significantly decreased.

MECHANICAL, RHEOLOGICAL & DURABILITY PROPERTIES OF CRUMB RUBBER BASED FIBRE REINFORCED SELF-COMPACTING CONCRETE : A REVIEW

Parul Mangal and Lalit Thakur — 2022-12-30

Concrete is one of the versatile material used in construction worldwide. Self-compacting concrete is an innovative concrete which is highly flow able concrete, can flow under its own weight by completely filling the formwork and achieving full compacting without using any external vibration. Due to its advantages like faster construction, less manpower, super-workable concrete, improved durability etc SCC becomes popular in civil engineering projects. For improving the various engineering properties of self-compacting concrete, several attempts have been done by using rubber in various forms in self-compacting concrete as a replacement to aggregates. But limited information is available on the use of crumb rubber as a replacement to fine aggregate. Hence a review is presented for using crumb rubber as a replacement to fine aggregate, also with the addition of various fibers and admixtures. From the various papers reviewed, it has been observed that fresh concrete properties increases but hardened concrete properties decreases of rubberized self-compacting concrete, also addition of fibers decreases packing density and increases surface area causing detrimental effect on the rheological properties of concrete. Steel fibres effect the flowability of SCRC more than PP fibers, the flowability & workability decreases if more steel fibres are added. Certain research gaps has been observed i.e. Study of additional mechanical (dynamic and impact loading) and fresh properties of rubberized SCC with the addition of steel and PP fibers as reinforcement. Durability tests (i.e. corrosive resistance, sulphate attack) and long term experimental studies can be evaluated for rubberized SCC with the addition of mineral admixtures like fly ash and blast slag. Feasibility of combining rheology and particle packing models for proportioning SCC mixture (long term goal). Evaluating the role of fines, superplasticizers and viscosity modifying agents (VMA) in SCC mixtures with respect to cement. Preparation of a set of design tables for mixture proportioning of SCC on the lines of ACI Committee 211. Study of sieve stability & penetration of SCC containing Crumb Rubber (CR) as a replacement to fine aggregate. This study mainly focused on the rheological, mechanical and durability properties of Rubberized self-compacting concrete which is prepared by replacing fine aggregate by crumb rubber with the addition of fibers.

SIX-SIGMA AS QUALITY IMPROVING TOOL FOR THE CONSTRUCTION INDUSTRY

Chani Anmol Singh, Nimita Gujar — 2022-12-30

Six Sigma is a quality-improvement methodology used in the manufacturing and other sectors of the economy & new to the construction sector. The construction industry is notoriously difficult to navigate due to the intricacy of its many processes, production flows, building types, quality standards, and long construction cycles. Additionally, the final construction quality must completely satisfy consumer demands. A high-quality product may be produced by validating circumstances and satisfying customers using the qualitative and quantitative technique known as Six Sigma. These organisations are examining the efficacy of measuring and monitoring technologies like six-sigma in other areas, including manufacturing, in order to accomplish these audacious goals. DMAIC and DMADV are the two main approaches to achieving six sigma quality. DMAIC is used to enhance an already effective process. In order to achieve a performance that is more consistent, mature, and error-free, DMADV develops a new product or process design. Some of the top companies in the construction industry just started using the six-sigma technique recently. Hence Six sigma, which is utilised successfully in the manufacturing sector, may be used to the building sector. Managing a profitable and efficient facility requires excellent material management. The researchers note that Six sigma will play a vital role in the construction industry.

ASSESSMENT OF CRUMB RUBBER BASED SELF COMPACTING CONCRETE: A REVIEW

Meghraj Sinh, Parul Bansal — 2022-12-30

A significant environmental and financial issue is the absence of facilities to dispose of used tyres from various vehicles. Self-compacted concrete (SCC) can use tyre waste-derived crumb rubber (CR) can partially replace fine natural aggregates, saving resources and lowering sand use. This study's primary goal is to provide an overview of how CR functions as a partial substitute for sand in SCC behavior. Out of 89 papers that were pertinent to the goal of this study, 42 were chosen for this purpose. The addition of CR to SCC mixtures decreased all of the mechanical parameters, including the compressive strength, flexural strength, splitting tensile strength, elastic modulus, and bond strength, as well as the ultrasonic pulse velocity (UPV). Self- compacting concrete (SCC) is described in this review study along with its benefits, applications, and uses. This paper aids in the comprehension of self-compacting concrete.

REVIEW AND ANALYSIS OF CODING SCHEMES FOR TEST DATA COMPRESSION

Dr. V. Suresh Kumar, Dr. N. Subhashini, Mr. C. Saravanakumar, Mr. S. Marirajan — 2022-12-30

Testing of Integrated Chips (ICs) becomes more and more difficult due to functional complexity and its size, caused by increase in integration levels of Very Large Scale Integrated (VLSI) chips. Testing of chips accounts for dominant cost factor in VLSI industry and reducing the cost of testing is the major challenge, VLSI designers and IC manufacturers are given to accomplish vivaciously. Test data volume and Test power are the two most important sources of test cost. By and large, much power is needed for a circuit when it undergoes test mode than in normal mode. This powerful utilization amid testing influences the circuit dependability [1]. Test force relies upon the quantity of sweep components present in the circuit. Productive test volume reduction procedures can reduce the test time, test power, and Automatic Test Equipment (ATE) memory requirement.

APPLICATION OF VALUE ENGINEERING TECHNIQUES IN BUILDING CONSTRUCTION PROJECTS - A CASE STUDY

Tanishq Bhatnagar, Asst. Prof. Mamata Rajgor — 2022-12-30

Value Engineering may be a creative, organized effort, that analyzes the necessities of a project for the aim of achieving the essential functions at rock bottom total prices over the lifetime of the project. Through a bunch investigation, mistreatment experienced, multidisciplinary teams, value and economy are improved through the study of alternate style concepts, materials, and ways while not compromising the useful and value objectives of the client. price engineering is that the method of relating the functions, the standard and also the costs of the project within the determination of optimum answers for the project. a cheap solution is achieved by an application of VE principle for completely different parts of the structures relating its quality and quantity. This study in the main focuses on new techniques, ways and materials which will be adopted in construction industry, in that, its cost, quality, method time and practicableness are considered. price Engineering focuses on accomplishing the desired functions at rock bottom overall cost. It helps in eliminating or minimizing wastage of material, time, and reserve cost, which improves value to the customer.

DEVELOPMENT OF FIBER RICH COOKIES INCORPORATED WITH OATS AND QUINOA

Adesh R. Kale, Ms. Kinjal P.Rana — 2022-12-30

This study intends to develop a fiber rich and gluten free cookie by incorporating oats and quinoa. Quinoa and oats are a rich source of carbohydrates, protein, dietary fiber, vitamins and minerals. Incorporating them in cookies by replacing refined wheat flour (maida) can enrich the nutritional quality. Quinoa and oats are gluten free products which can be consumed by celiac disease patients. These cookies were studied with respect to Physio-chemical parameters, Microbiological analysis and sensory analysis. Four formulations were used: T0, T1, T2, T3. Among them T3 was mostly preferred by the panelist. Sensory evaluation was done using a 9 point hedonic scale. The designed cookies have the following composition : 68.53 % carbohydrates, 5.71% protein, 20.86 % fat, 8.79% dietary fiber, 2.44 % ash, 2.46% moisture and delivers up to 484.7 Kcal of energy. The finding demonstrates that oats and quinoa cookies are excellent sources of dietary fiber and can replace the ordinary refined wheat flour cookies.

A REVIEW OF MACHINE LEARNING METHODS FOR DETECTING SEVERAL DISEASES

Dongari Rohith Varma, A. Harsha, Krithi Majjigapu, V.Mallaiah — 2022-12-30

Early illness detection may help reduce the number of fatalities. In recent years, several researchers have applied different machine learning-based methodologies to construct autonomous disease detection systems. The goal of the illness detection models is to combine the fields of medicine and artificial intelligence (AI) so that people can see how well they can work together. We want to conduct extensive research on AI applications for the healthcare industry better to grasp the function of AI in the medical profession. We'll start by reviewing the highlights and reasons why AI should be used in healthcare. Then, we thoroughly discuss machine-learning-based integration methods for the healthcare industry. After discussing the technical issues with AI in the medical sector, we next demonstrate how machine learning might be helpful. We also investigate how machine learning is affecting the medical industry. We also discuss a few exciting projects showing how vital machine learning is in healthcare applications and services. Finally, talk about current problems with diagnosing diseases and recommend future research and development directions that will result in the use of machine learning in the healthcare industry.