Electrical Engineering and Computer Science

The primary goal of this thesis is to simulate the causes of human face ageing and to detect skin illnesses. This project combines the capabilities of a Deep Learning model, notably EfficientDet, with the capabilities of a machine learning model and Advanced Computer Vision to identify and locate aging and skin disease. In an uploaded photo there are irregularities which can be detected. The appearance of age-related face changes is determined by a variety of factors. Wrinkles, dark patches, and swollen eyes are all variables to consider. The TensorFlow Objection Detection API is used to investigate the factors. TensorFlow Zoo's EfficientDet model is pre-trained. The proposed models are found to be effective based on the outcomes. Very effective in predicting the indications of ageing in people of all ages. Python was used to implement this project.

Worldwide Interoperability for Microwave Access (WiMAX) networks were expected to be the main Broadband Wireless Access (BWA) technology that provided several services such as data, voice, and video services including different classes of Quality of Services (QoS), which in turn were defined by IEEE 802.16 standard. Scheduling in WiMAX became one of the most challenging issues, since it was responsible for distributing available resources of the network among all users; this leaded to the demand of constructing and designing high efficient scheduling algorithms in order to improve the network utilization, to increase the network throughput, and to minimize the end-to-end delay. In this study, we presenedt a simulation study to measure the performance of several scheduling algorithms in WiMAX, which were Strict Priority algorithm, Round-Robin (RR), Weighted Round Robin (WRR), Weighted Fair Queuing (WFQ), Self-Clocked Fair (SCF), and Diff-Serv Algorithm.

6th International Conference on Computer Science, Engineering and Information Technology (CSITY 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Computer Science, Engineering and Information Technology. The Conference looks for significant contributions to all major fields of the Computer Science, Engineering and Information Technology in theoretical and practical aspects.

This paper presents a cluster priority ranking based approach for extractive automatic text summarization that aggregates different cluster ranks for final sentence scoring. This approach does not require any learning, feature weighting and semantic processing. Surface level features combinations are used for individual cluster scoring. Proposed approach produces quality summaries without using title feature. Experimental results on DUC 2002 dataset proves robustness of proposed approach as compared to other surface level approaches using ROUGE evaluation matrices.

Over many centuries, tools of increasing sophistication have been developed to serve the human race Digital computers are, in many respects, just another tool. They can perform the same sort of numerical and symbolic manipulations that an ordinary person can, but faster and more reliably. This paper represents review of artificial intelligence algorithms applying in computer application and software. Include knowledge-based systems; computational intelligence, which leads to Artificial intelligence, is the science of mimicking human mental faculties in a computer. That assists Physician to make dissection in medical diagnosis.

Advancements in Biomedical field provide lot of assistive devices to help deaf people and visually impaired people. When it comes to the subject of deaf-blind people (who losses both hearing and visual ability) availability of such devices are very limited. Tactile signaling and manual alphabets are the most commonly methods used to make the reciprocal communication between the impaired and the surrounding environment possible. Existing devices like MyVox, Sparsha are use braille tactile reading/writing to make communication between two deaf blind users. Assistive systems available in market are high cost and invasive. The proposed system is wearable, non-invasive, compact and low cost. It can recognize the speech and convert into Morse code vibrations. Raspberry Pi is used to convert speech into text using microphone and then each text changed to Morse code using raspberry pi. These signals will be sending to micro haptic vibrating motors through GPIO pins of raspberry pi which are attached with user's fingers.

The mobile phone environment represents one of the important environments in encryption various multimedia (audio, image, and video) , and this depends on the type of algorithm used in the encryption process, as phones have limited memory and computational resources, Therefore the selection of the algorithm must be compatible with the mobile environment in terms of speed, safety and flexibility in addition to choosing an algorithm that The simplicity and safety of the image encryption process was investigated with lightweight and efficient computing. In this paper, Hybrid Cube Encryption (HiSec) was used. When implementing this algorithm in a smart phone environment, the results showed the ease of encrypting images and retrieving the original image, in addition to that it only requires small computational resources, and the algorithm was very effective in encrypting images on mobile phones. This suggested method has been implemented in the mobile environment with android OS. The proposed method has been programmed in JAVA, and the method has been tried on different types of mobile phones (such as Huawei Nova 2, Huawei Nova 7, HTC, NOT 8, Galaxy S 20, and HONOR).

https://www.ijert.org/retail-customer-churn-analysis-using-rfm-model-and-k-means-clustering

https://www.ijert.org/research/retail-customer-churn-analysis-using-rfm-model-and-k-means-clustering-IJERTV10IS030170.pdf

In this current world of business, Customer Churn is one of the major concerns for various business owners or the organizations for maintaining existing and attracting new customers. Analysis of various types of customers can be conducted by researching customer relationship management which in turn provides strong support for business decisions. Customer churn occurs when certain customers are no longer loyal or a part of a particular business. Losing customers will not only result in losses but also develop threat to the organization. Because of multiple competitors in the same business, the re-engagement of customers who are less interested is essential rather than engaging a new one. It is observed that acquiring new buyers is costlier than retaining the present customer. Churn prediction is a new promising method in customer relationship management to analyze customer behavior by identifying customers with a high probability to discontinue the company based on analyzing their past data and also identify strategies for improvement. Once a customer becomes a churn, the loss incurred by the corporate isn't just the lost revenue but also the prices involved in additional marketing in order to attract new customer. Reducing customer churn is a key business goal. In this project, we've taken a dataset from UCI Machine Learning repository. This dataset contains records of transactions that happened between December 1, 2010 and December 1, 2011. This is recorded from a web retail gift store based in the United Kingdom. Here segmentation of customers has been done by using RFM technique and K-means algorithm.

The paper presents curricular and pedagogical reforms for online and digital education. It develops a platform for open online courses supported by various portals in improving the quality of education with the initiatives of NEP, 2020 policy. The recent rise in epidemics and pandemics necessitates that HEI’s are ready with alternative modes of quality education whenever and wherever traditional and in-person modes of education are not possible. In this regard, the NEP, 2020 recognizes the importance of online and digital education.

This text explains how to use mathematical models and methods to analyze problems that arise in computer science. Proofs play a central role in this work because the authors share a belief with most mathematicians that proofs are essential for genuine understanding. Proofs also play a growing role in computer science; they are used to certify that software and hardware will always behave correctly, something that no amount of testing can do.

The Internet of Things (IoT) has the power to change our world. Agriculture is the backbone of the India. Development of IoT application is a must, for solving problems that are faced by farmers in the field of agriculture. Lack of proper information and communication leads to the loss in production. In the proposed system, we have automated the drip irrigation technology with the help of IoT and optimizing the usage of water level. In this paper, we are providing most secured MQTT protocol at the database level (Mongodb) and application level with the encryption technic for data security.

Banyak penemuan Laplace yang menjadi panutan didunia matematika. Penemuannya antara lain adalah di bidang integral kalkulus, diferensial terbatas (limit), persamaan diferensial dan astronomi. Ia juga menemukan Mekanika selestial, evakuasi Laplace, operator Laplace dan transformasi Laplace.
Transformasi Laplace adalah suatu teknik untuk menyederhanakan permasalahan dalam suatu sistem yang mengandung masukan dan keluaran, dengan melakukan transformasi dari suatu domain pengamatan ke domain pengamatan yang lain.

In this paper, an all pairs optimized shortest path algorithm is presented for an unweighted and undirected graph with some additive error of at most 2.This algorithm can be extended for weighted graph also but it will not work for directed graph due to absence of commutative property. The run time of the algorithm is of order Ο(n5/2), where n is the number of vertices present in the graph. This algorithm is much simpler than the existing algorithms. A study of upper bounds on the size of a maximal independent set of such graphs has also been discussed.

Real-Time monitoring is the effective way to observe factual data. Internet of things based online monitoring is useful to access data remotely. IoT is the network of physical objects embedded with electronics, software and sensors that enable to collect and exchange data. IoT enables the flexibility and liberty to access the machine placed in a remote area access to keep a continuous track of the machine behavior in real time. Application of this technology in electrical engineering is beneficial to observe different parameters which are not easy to access. Electrical equipment performance can be monitored on a real time basis to improve the operating span. This is carried out using online monitoring system. IoT is used to observe different parameters on real time scale. This helps to measure and sense various parameters like energy, voltage, current, temperature, power factor and frequency of any given electrical equipment. This paper reviews suitability of IoT based online monitoring system for electrical equipment.

https://www.ijert.org/study-of-various-measure-to-monitor-social-distancing-using-computer-vision-a-review

https://www.ijert.org/research/study-of-various-measure-to-monitor-social-distancing-using-computer-vision-a-review-IJERTV10IS050194.pdf

Millions of people worldwide have been impacted by the latest COVID epidemic, but the number of people getting sick is on the rise. The virus is one of the few pandemics the world has not yet been able to resist; numerous countries have responded to this by taking extraordinary steps to avoid its spread. We must strive to avoid the spread of infection, which can only be done by social distancing ourselves from those who might be infected with the virus. Interactions between people are avoided to prevent the virus from spreading, such as shaking hands, helping each other, and giving each other personal items to hold. A number of examples of the application of AI and deep learning on everyday life problems have been developed in the past. This review paper would detail how we could track public locations using Python, which could include monitoring people's facial expressions, as well as identifying security threats to help identify risk of employee social recidivism using Deep Learning and Deep learning, using Computer Vision. The social distancing detection tool will monitor whether people are maintaining a safe distance from each other by analyzing real-time video streams from the camera to ensure social distancing protocol in public places and the workplace. We can incorporate this tool into their security camera systems and track whether people are maintaining a safe distance from each other at work, in warehouses, and in stores. In short various machine learning technique are studied and its application to social distancing protocols are heavily studied in our paper.

https://www.ijert.org/an-emerging-malware-analysis-techniques-and-tools-a-comparative-analysis

https://www.ijert.org/research/an-emerging-malware-analysis-techniques-and-tools-a-comparative-analysis-IJERTV10IS040071.pdf

The term Malware denotes malevolent software. This type of software is installed in the system without the awareness of its owner. This malicious software is being installed by the third party to steal, damage, corrupt the important and personal data of the user. The Malware writers have to get an upper edge in spreading their spiteful software such as-worms, trojan horses, spyware, viruses, rootkits, cookies, adware, and many more through the world of immense networking-the Internet. Antivirus vendors are receiving a thousand potentially malicious software every day which can affect the systems. Using Antivirus scanning (AVS) and firewalls to detect the malware is not enough as the malware writers are always way ahead creating numerous unsolvable and challenging threats for the computer society. This survey provides a rundown on the study of Malwares, tools, and techniques which can be useful to analyze malicious software, focusing on the online available malware analysis tools which work on cloud computing in giving results. Further, we focus on devising an Analysis Algorithm which aims and suggests various tools to execute the malware analysis procedure.

The health reports of the people including diagnostics information and medical prescriptions are provided in the form of test-based case notes due to this the previous health conditions and the medicines used by the person are not known when they visit the hospital later. But storing all the health information of a person in the cloud as the soft copy reduces this problem. To achieve every hospital, dispensary, laboratory must have an internet connection for registration of patient’s data, each patient will be identified by the unique Health ID and all the data of the patient will be stored in the cloud and the data can be accessed by only the particular patient. Accurate and on-time analysis of any health-related problem is important for the prevention and treatment of the illness. To diagnose the disease by accessing all information from linked Health ID with Machine Learning algorithm will boost the system in detection of diseases. Here the work presents review of previous researcher’s techniques used for the prediction of diseases and number of parameters used.

The Internet of Things (IoT) has the power to change our world. Agriculture is the backbone of the India. Development of IoT application is a must, for solving problems that are faced by farmers in the field of agriculture. Lack of proper information and communication leads to the loss in production. In the proposed system, we have automated the drip irrigation technology with the help of IoT and optimizing the usage of water level. In this paper, we are providing most secured MQTT protocol at the database level (Mongodb) and application level with the encryption technic for data security.

Internet of Things (IoT) consists of smart devices which can sense the environment and performs the data interaction with the users by handling the large volume of data and also provide the numerous services to the users. It also plays the significant role in Intelligent Transportation System (ITS) using the Cognition ability. One of the primary causes for the road accidents is consumption of alcohol. Driving under the influence (DUI) or Driving While Intoxicated (DWI), and involves operating a vehicle with Blood Alcohol Content (BAC) level of at least 0.08 percent is considered as the punishable offense. In order to identify and prevent the driving with alcohol consumption, the ITS system can be designed with IoT based smart helmet system. The IoT system performs the data validation using the Bayesian Algorithm which significantly detects the alcohol consumption of the rider. And the system also provides the provision to control and ride the bike if and only if the rider does not consume the alcohol.

6 th International Conference on Electrical and Electronics Engineering (EEEN 2022) aims to bring together researchers and practitioners from academia and industry to focus on recent systems and techniques in the broad field of Electrical, Electronics, Instrumentation and Communication Engineering. Original research papers, state-of-theart reviews are invited for publication in all areas of Electrical, Electronics and Instrumentation Engineering. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.

Wireless Data communication is fastest growing technology era in which the research society has recently embarked. Today, Computer data can include financial transactions such as electronic payments, M- wallets and sensitive multimedia contents. The explosive volumes of computer devices personal data, bring-up more attention to securely data storage rather than consideration on data privacy and confidentiality levels. In this scenario Air Gap Data Communication, Machine Leaning (ML) and image processing brings an important role in the electronic data management. It is always expensive and hard to manage the data manually without adopting machine learning and image processing techniques using metadata. The contribution of this research article is to demonstrate a securing computer data storage secrecy and privacy in cloud communication framework in terms of automatic data classification using computer training datasets with help of Training dataset which classifies the data based on the confidentiality level of the record with higher accuracy and powerful timelines as compared to the traditional KNN algorithms and RSA algorithm securing such confidential data category afterwards by applying various existing cryptographic solutions to assuring data privacy, confidentiality levels and alerting the use of abusive contents and simulation results demonstrates that reducing the overall cost. Training dataset which classifies the data based on the confidentiality level of the record with higher accuracy and powerful timelines as compared to the traditional KNN algorithms and RSA algorithm securing such confidential data category.

There are two major ways to treat wastewater; it is either through chemical or non-chemical treatment. Both improve water quality, but do not make water safe for domestic use. Most firms or companies use coagulation treatment or chemical treatment. But the problem for this treatment is the selection of the best chemical to be used; it is expensive and frequent dosage adjustments are required to ensure good water treatment results. All coagulation chemical add specific elements to the water, improper doses and application generally pose problems (health risks). Hence, it requires extra preventive measures. A more cost-effective method to clean a wide range of polluted water on-site, and with minimal additives, is required for sustainable water management. Electrocoagulation treatment of water may fit this description [1]. Electrocoagulation is most widely used in other countries but not in the Philippines. Hence, the device readily available in the market is very expensive. The paper focuses on the automation of the Electrocoagulation process by using microcontroller, sensor, relays, and sacrificial anodes.

The mobile phones are becoming now an irreplaceable utility of every household. It serves as wall clock, alarm clock, calculator, calendar, timer and many more, but have this multi-functionality overloaded the interface of the new generation of the mobile phones. The youth have adapted well to these multiple functionalities graphical user interface, but the interface has now haunting effects for usage by the two age groups i.e. elderly and kids. The interface may end up leading the new generation mobiles in the market useless or of very little use to the elderly and kids. This leads towards the need of age based user interface in the mobile operating system which will consist of interface selection home screen which further directs to age oriented interfaces.

Image segmentation is commonly applied technique in different domains such as automatic pattern recognition, image retrieval based content, machine vision, face detection, medical imaging, and object detection. Image segmentation involves classifying or identifying sub patterns in a given image. Many of algorithms and techniques for image segmentation have been proposed to optimize segmentation problems in a specific application area. In this work, different image segmentation techniques had been applied (threshold based, region based segmentation and edge based preserving methods. This Experiment have been done using MATLAB R2018b. Different edge detection methods such as Sobel, Prewitt, Roberts, Laplacian, Kiresh and Canny methods are performed on the benchmark image and the performance is analyzed with respect to the standard measure peak signal-to-noise ratio (PSNR), and mean square error. The results present that the Laplacian method is more effective than the other methods.

The multicore processor architectures have been gaining increasing popularity in the recent years. However, many available applications cannot take full advantage of these architectures. Therefore, many researchers have developed several characterization techniques to help programmers understand the behavior of these applications on multicore platforms and to tune them for better efficiency. This paper proposes an on-the-fly, configuration-independent characterization approach for characterizing the inherent characteristics of multicore applications. This approach is fast, because it does not depend on the details of any specific machine configuration and does not require repeating the characterization for every target configuration. It just keeps track of memory accesses and the cores that perform these accesses through piping memory traces, on-the-fly, to the analysis tool. We applied this approach to characterize eight applications drawn from SPLASH-2 and PARSEC benchmark suites. This paper presents the inherent characteristics of these applications, including memory access instructions, communication characteristics patterns, sharing degree, invalidation degree, communication slack and communication locality. The results show that two of the studied applications have high parallelization overhead, which are Cholesky and Fluidanimate. The results also indicate that the studied applications of SPLASH-2 have higher communication rates than the studied applications of PARSEC and these rates generally increase as the number of used threads increases. Most of the sharing and invalidation occurs in small degrees. However, two of SPLASH-2 applications have significant fraction of communication with high sharing degrees involving four or more threads. Most of the applications have some uniform communication component and the initial thread is generally involved in more communication compared to the other threads.

This study analyzes the significant determinants of a bank choice by a customer in the banking industry. Given the significance of customers as the most important resources of associations, customer maintenance is by all accounts a fundamental, essential necessity for any association. Banks are no special case for this standard. The competitive environment within which electronic banking administrations are given by various banks increases the need of customer maintenance. Text classification is a significant errand in natural language processing with wide applications. Conventional text classification strategies manually separate the highlights which are subsequently taken care of into the classifier for training. Conventional text portrayal strategies have been effectively applied to independent records of medium size. Be that as it may, information in short texts is regularly insufficient, due, for instance, to the utilization of memory helpers, which makes them difficult to classify. Subsequently, the particularities of explicit domains should be abused.

https://www.ijert.org/dynamic-load-balancing-algorithm-in-sdn-based-data-center-networks

https://www.ijert.org/research/dynamic-load-balancing-algorithm-in-sdn-based-data-center-networks-IJERTV10IS030200.pdf

Current networking architectures have many drawbacks that must be overcome to meet modern IT requirements. To overcome these limitations; Software Defined Networking (SDN) is taking place as the new networking approach. One of the major issues is that they use static switches that cause poor utilization of the network resources. Another issue is the slow response and delays are the main problems in current networking trend. This research proposes an implementation of a dynamic load balancing algorithm for SDN based three tier Data Center network to overcome these issues. A test has been implemented using Floodlight controller as SDN controller and Mininet software to emulate the network. Python programming language is used to define a network topology and to write the load balancing algorithm program. Finally, iPerf is used to test network performance. The network was tested before and after running the load balancing algorithm. The testing focused on Quality of Service (QoS) parameters such as throughput, bandwidth, and response time. The algorithm increased throughput with at least 50% at distribution level and with 33% at core level which also result in faster response time as well.

With the increase in the number of electric vehicles, requirement of the electric vehicle battery chargers (EV) are increased too. The EV battery chargers have many features which should be examined for optimization operation. The charging time and bad impacts of EV battery chargers to grid are two of that features. The EV chargers should optimized in terms of different aspects for optimal results on grid and vehicle sides. This article aims to minimizing the EV battery charging time and minimizing the bad impacts of EV chargers to grid. Solution advices were presented for optimal results in this article. Also benefits and barriers of optimization of the EV battery chargers were explained.

Dynamic increase in the amount of waste and despicable dumping of waste has become a matter of concern because of the threat it causes to the environment. There comes the pivotal role of an automated waste segregate which avoid this plight and also reduces the difficulty of recycling. The importance and the economic value of waste is realized only when it is segregated. Currently there is no such system for segregation of dry and wet wastes. This system proposes a spot automatic waste segregation unit that effectively gives a solution to this problem. . For the separation of wet and dry waste capacitive sensors are used. The benefits of this work are, the waste has a higher potential for recovery and the occupational hazards of waste separating workers is also reduced. IOT Based Smart Trash consists of sensors, microcontroller and SMS module. The sensors detect the garbage level if the level reaches its average or maximum. The waste segregator as the name suggests, segregates the waste into three major classes: dry, wet. Waste is pushed through a flap into the proposed system. The inlet section is provided with open and close mechanism to regulate the flow of waste on to the bin. Wet detecting sensor is used to detect or identify the waste. The signal from the sensor initiates the push mechanism to discard the waste.

The introduction of Transport Layer Security has been one of the most important contributors to the privacy and security of internet communications during the last decade. Malware authors have followed suit, using TLS to hide potentially dangerous network connections. Because of the growing use of encryption and other evasion measures, traditional content-based network traffic categorization is becoming more challenging. In this paper, we provide a malware classification technique that uses packet information and machine learning algorithms to detect malware. We employ the use of classification algorithms such as support vector machine and random forest. We start by eliminating characteristics that are highly correlated. We utilized the Random Forest method to choose only the 10 best characteristics from all the remaining features after eliminating the unnecessary ones. Following the feature selection phase, we employ several classification algorithms and evaluate their performance. Random forest algorithm performed exceptionally well in our experiments resulting in an accuracy score of over 0.99.

https://www.ijert.org/augmented-reality-navigation

https://www.ijert.org/research/augmented-reality-navigation-IJERTV9IS060441.pdf

With the introduction of the Android system, smart phones are growing faster and more easily with internet access to smart phones, user location information can be quoted anywhere at any time with ease. With this growth, many new technologies are introduced and to be very beneficial to the Users as they can be used with the existing technologies/applications in various fields. One of the major technologies introduced is Augmented Reality, this can be used to interact with the real world using virtual objects and videos. Augmented Reality based Technology enables the provision of a variety of information such as photos and placement of buildings in the travel field. This field can also be used in the Navigation as discussed in this paper. Most of the unconventional virtual programming used for the Visual Trace Way (Marker and Marker less method). For visual tracking, digital tagging and digital information should be provided while the Non-visual Trace Way requires the use of Hardware (G.P.S, sensors etc.). Most navigation requests can only show the path from the user's current location to its destination. In this paper, the design and implementation of augmented reality system are discussed. It will use a well-designed smart phone camera and GPS to display user-centric information in real time on a smart phone. The proposed app will combine G.P.S location technology with tracking technology to provide the user with basic information about the building they want or one they are close to.

The Indian Recruitment market has grown substantially over the last half-decade as the need for cheap labor grows and the number of job openings is increasing. And as the job market increases so does the recruitment industry which is a new way of hiring people by outsourcing the hiring process itself to other companies whose sole purpose is to give the correct talent required for the company. This is done because these companies are hiring in bulk and doing such a thing in-house will require a lot of company resources which will hamper productivity. As such companies emerge even for them manually going through all of the Resume of candidates is very time-consuming and tedious so these Talent Acquisition Companies use various Machine Learning models to filter out top resumes according to the job roles, which reduces the efforts for the Human Resource team

India being an agricultural country, its economy predominantly depends on agriculture yield growth and allied agro industry products. In India, agriculture is largely influenced by rainwater which is highly unpredictable. Agriculture growth also depends on diverse soil parameters, namely Nitrogen, Phosphorus, Potassium, Crop rotation, Soil moisture, and Surface temperature and also on weather aspects which include temperature, rainfall, etc. India now is rapidly progressing towards technical development. Thus, technology will prove to be beneficial to agriculture which will increase crop productivity resulting in better yields to the farmer. The proposed project provides a solution for Smart Agriculture by monitoring the agricultural field which can assist the farmers in increasing productivity to a great extent. Weather forecast data obtained from IMD (Indian Metrological Department) such as temperature and rainfall and soil parameters repository gives insight into which crops are suitable to be cultivated in a particular area.

Alumni are graduates of a school, college, or university. As at Private University in Jakarta, every year there are new alumni. After graduating from college, Alumni are usually busy working or continuing to higher education, they will be separated by distance. Based on these problems, a media is needed to interact with other alumni and this media can also be used by Alumni in helping the campus in collecting data on other alumni. The media is a social network that connects people to one another. Our research is aimed at the alumni of Private University in Jakarta. Even though nowadays there are many social media, not all alumni use usernames according to their real names, not even all alumni use these social media, this of course makes it difficult for alumni to communicate again with other alumni. With the website-based application, namely the Ruang Alumni, it will make it easier for Alumni to connect with each other, and can help the campus to complete alumni data even though not all of them are complete because it is only based on other Alumni who have registered in the application. This application was developed using the Waterfall method. With this Ruang Alumni website-based application, Alumni can connect with each other by sharing data and information in this application, such as posting personal photos, posting job vacancies and posting lots of information in this application, alumni can also update personal data like on other social media. Alumni can also find information on campus such as events or competitions held by faculties, study programs, or student organizations at University.

The current era of an emerging technology is cloud computing. It is internet based computing, works as pay-per-use model and process large data. The cloud Service provider goal is to manage resources efficiently, So, in cloud computing the mechanism of Scheduling has an important function. The revised scheduling technique is meant to improve the server performance and decrease the switching time to increase the use of resources. Different sorts of scheduling algorithms have been studied and analysed in this research to deliver efficient cloud services. The improved Scheduling algorithm prioritises the task, which improves computer performance and does my best possible efforts to limit the duration and duration of waiting. A CloudSim tool is used to simulate the suggested approach.

The sudden increase in COVID-19 patients is a major shock to our global health care systems. With limited availability of test kits, it is not possible for all patients with respiratory infections to be tested using RT-PCR. Testing also takes a long time, with limited sensitivity. The detection of COVID-19 infections on Chest X-Ray can help isolate patients at high risk while awaiting test results. X-Ray machines are already available in many health care systems, and with many modern X-Ray systems already installed on the computer, there is no travel time involved in the samples. In this work we propose the use of chest X-Ray to prioritize the selection of patients for further RT-PCR testing. This can be useful in a hospital setting where current systems have difficulty deciding whether to keep the patient in the ward with other patients or isolate them from COVID-19 areas. It may also be helpful in identifying patients with high risk of COVID with false positive RT-PCR that will require repeated testing. In addition, we recommend the use of modern AI techniques to detect COVID-19 patients who use X-Ray imaging in an automated manner, especially in areas where radiologists are not available, and help make the proposed diagnostic technology easier. Introducing the CovidAID: COVID-19 AI Detector, a model based on a deep neural network of screening patients for proper diagnosis. In a publicly available covid-chest x-ray-dataset [2], our model provides 90.5% accuracy with 100% sensitivity (remember) to COVID-19 infection. We are greatly improving the results of Covid-Net [10] on the same database.

https://www.ijert.org/electronic-voting-system-blockchain-vs-hashgraph

https://www.ijert.org/research/electronic-voting-system-blockchain-vs-hashgraph-IJERTV10IS030305.pdf

Voting is one of the most important civil right for the people of a democratic country by which the citizens can ensure that the state is being governed lawfully. For centuries, citizens have voted in elections to express their opinions in governance of the country, but the electronic voting system is a relatively new concept. Many countries in the world are currently experimenting with blockchain based voting systems, however, there are significant drawbacks of this method. The hashgraph encryption method is a superior version of the blockchain encryption and eradicates a few of the drawbacks of blockchain. This paper compares the two methods and highlights the advantages of the hashgraph encryption method over the blockchain encryption method.

The purpose of this paper is to present fuzzy TOPSIS in an entropic fuzzy environment. Due to the ambiguous concepts often represented in decision data, exact values are insufficient to model real-life situations. In this paper, the rating of each alternative is defined in fuzzy linguistic terms, which can be expressed with triangular fuzzy numbers. The weight of each criterion is then derived from the decision matrix using the entropy weighting method. Next, a vertex method is proposed to calculate the distance between two triangular fuzzy numbers. According to the TOPSIS concept, a closeness coefficient is defined to determine the ranking order of all alternatives by simultaneously calculating the distances to both the fuzzy positive-ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS). Finally, an illustrative example of selecting stealth fighter aircraft is shown at the end of this article to highlight the procedure of the proposed method. Correlation analysis and validation analysis using TOPSIS, WSM, and WPM methods were performed to compare the ranking order of the alternatives.

https://www.ijert.org/iot-based-smart-shopping-cart-using-rfid

https://www.ijert.org/research/iot-based-smart-shopping-cart-using-rfid-IJERTV10IS040179.pdf

These days, when a client needs to purchase an item, the client needs to put the item in the shopping basket, and afterward place it in the RFID truck peruser to peruse the RFID labels appended to every item. The pertinent insights regarding the item will be shown in the portable application, before the client associated with the shopping basket. Clients can without much of a stretch speak with the interface and utilize the different assets of the proposed framework. By utilizing the proposed administration, clients can choose the best items that place the item in the shopping basket, and the expense will be remembered for the aggregate sum. After the buy is finished, the bill will be concluded by the client and itemized data will be shipped off the focal worker. The guide gave in the proposed framework will discover items in the shopping center dependent on disruptive data to support clients. By utilizing this program, clients can buy huge amounts of items in a brief timeframe with negligible force. The savvy shopping basket contains 4 nuts and bolts: equipment coordination, programming interface, remote association and organization information store. In such manner, a brilliant Internet-based (IoT) shrewd shopping basket, highlighting a radio recurrence sensor (RFID) sensor, Arduino microcontroller, Bluetooth module and a versatile framework, is proposed. RFID sensors depend on remote correspondence. One section is the RFID label connected to every item, the other part is a RFID peruser who can effectively peruse item subtleties. From that point onward, the subtleties of every item will be shown in the "versatile" application. Clients can without much of a stretch deal with the shopping list in the versatile application as indicated by their inclinations. From that point forward, the buy subtleties are shipped off the remote worker, and the bill is naturally executed. This testing model means to kill tedious acquisition cycles and administration quality issues. The proposed framework can be effortlessly executed and tried at a business level under genuine conditions later on. That is the reason the proposed model is more serious than different models.

https://www.ijert.org/design-of-a-pipeline-for-a-fixed-point-multiplication-using-single-electron-tunneling-technology

https://www.ijert.org/research/design-of-a-pipeline-for-a-fixed-point-multiplication-using-single-electron-tunneling-technology-IJERTV10IS040029.pdf

For high operating speed, low power consumption, and high integration density-based equipment(s) are financially indispensable in engineering, science and technology in the present era. Single Electron tunneling Device (SED) is one such equipment by which all Boolean logic gates can be implemented. SEDs and Linear Tunnel Gates (TLG) are capable of controlling the transport of only an electron through the tunneling junction. It is a single electron that is sufficient to store information in the SED in the atmosphere of 0K. Power consumed in the single electron tunneling circuits is very low in comparison with (CMOS) circuits. The processing speed of TLG based device will be nearly close to electronic speed. The single-electron transistor (SET) and LTG attracts the researchers, scientists or technologists to design and implement large scale circuits for the sake of the consumption of ultra-low power and its small size. All the tunneling events for the case of a LTG-based circuit happen when only a single electron tunnels through the tunnel junction under the proper applied bias voltage and multiple input voltages. For implementing a fixed-point Multiplication circuit, LTG would be a best candidate to fulfil the requirements of it. Ultra-low noise is generated during tunneling through the LTG based circuit. Different logic gates, a D-Flip-flop, a full adder are implemented, and based on them, a "Pipeline for a fixed-point Multiplication" is presented at last.

Online media are becoming extra attention those days. Public and personal evaluation on a extensive collection of topics are communicated and unfold always by diverse on line media. Twitter is one of the on line media this is obtaining prominence. Twitter gives association’s short and compelling method to research clients' viewpoints closer to the primary to accomplishment within side the industrial Centre. Building up a software for belief research is a manner to cope with be applied to computationally degree clients' insights. This paper investigates the plan of a end examination, setting apart a massive degree of tweets. Prototyping is applied on this flip of events. Results set up clients' factor of view thru tweets into fantastic and negative, that is addressed in a pie define and html page. Nonetheless, this system has desired to create on an internet utility framework, but due to restrict of Django which may be bartered with a Linux employee or LAMP, for added thi...

The system proposed can be used to regular checkup of the COVID patients while maintaining the social distancing. Also, the data sensed by the sensors is directly sent to doctor, reducing the cost of paying regular visits to doctor. The Iot platform used in the system helps to transfer the real time patient’s data remotely to host device. Daily health record can be maintained and can be viewed in oxygen level or rise in temperature. To track the patient health micro-controller is in turn interfaced to an LCD display and wi-fi connection to send the data to the web-server (wireless sensing node). In case of any abrupt changes in patient heart-rate or body temperature alert is sent about the patient using IoT. This system also shows patients temperature and heartbeat tracked live data with timestamps over the Internetwork.

This review paper discuss about recent techniques and methods used for grain classification and grading. Grains are important source of nutrients and they play important role in healthy diet. The production of grains across worldwide each year is in terms of hundreds of millions. The common method to classify these hugely produced grains is manual which is mind-numbing and not accurate. So the automated system is required which can classify the verities and predict the quality (i.e. grade A, grade B) of grain fast and accurate. As machine learning had done most of the difficult things easy, many machine learning algorithms can be used which can easily classify and predict the quality of grains. The system uses colour and geometrical features like size and area of grains as attributes for classification and quality prediction. Here, several image procession methods and machine learning algorithms are reviewed.

This paper presents a techno-economic investigation of an integrated rooftop solar PV system for typical home applications in Oman that reduces the power consumption from the grid and export excess PV generated power back to the gird. Since renewable energy systems design technically depends on the site, this study selects a typical two-story villa in Al-Hamra, Oman as the site. Temperature is one of the critical parameters in this design as it varies widely over the day and has a considerable variation from one season to another in Oman. With the effect of temperature variation, the PV system has designed using system models for the required load of the home. The available rooftop space and the grid-connection availability are two main design constraints have realized in this study. This research also evaluates the economic feasibility of the design system considering the energy export tariff as per the Bulk Supply Tariff (BST) scheme in Oman. The design outcome reveals that the de...

https://www.ijert.org/a-survey-of-peer-to-peer-ride-sharing-services-using-blockchain

https://www.ijert.org/research/a-survey-of-peer-to-peer-ride-sharing-services-using-blockchain-IJERTV10IS080172.pdf

Ride Sharing has seen a steep rise in popularity in metropolitan cities to avoid wastage of resources, traffic jams and congestions. This gave birth to a whole new trend which ride aggregator services went on to capitalize by providing the option of sharing cabs to its users at a lower price. Although conventional ride sharing methods have proven to be quite effective, there is always scope for improvement in certain fields. This idea of vehicle sharing can be revolutionized by implementing blockchain technologies. Blockchain is a decentralized record where all the information is stored on systems everywhere which can be retrieved and traced freely. There is a mechanism that allows peer to peer transactions and brings the need for third parties to an absolute minimum. The system is no longer trust-based but simply based on concrete proof that exists which is built into the ledger.