Lahore Garrison University Research Journal of Computer Science and Information Technology
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A Comparative Analysis of COVID Forecasting by Using Various Machine Learning Methods
Full text linkCovid-19 emerged as one of the most infectious diseases in the history of mankind, affecting nearly 250 million people all over the world in just a short period. The pandemic which started in China, has now spread all over the world, taking about 5 million lives globally. This has also severely affected the economies of countries and has proved to be a burden on health care systems. Due to these reasons, forecasting the spread of the disease has become critical so that concerned government authorities in countries can have the chance to mitigate the spread and plan health care resources efficiently and properly. This makes it more important to have a reliable forecast so that resources can be planned ahead of time. In the present work, linear regression is used for time forecasting the spread of Covid-19 in Pakistan. Statistical parameters and metrics have been used to evaluate and validate the model. The results show that linear regression results are highly reliable, time efficient and accurate.  
Urdu News Content Classification Using Machine Learning Algorithms
Full text linkAs the world has become a global village, the flow of news in terms of volume and speed increases. It is necessary to engage computing machines for assisting people in dealing with this massive data. The availability of different types of news and such material on the Internet serves as a source of information for billions of users. Millions of people in our subcontinent speak and understand Urdu. There are several classification techniques that are available and are applied to classify English news like political, Education, Medical, etc. Plenty of research work has been done in multiple languages but Urdu is still to be worked on due to a lack of resources. This research evaluates the performance of twelve (12) different Machine learning classifiers for the Urdu News text Classification problem. The analysis was performed on a relatively big and recent collection of Urdu text that contains over 0.15 million (153,050) labeled instances of eight different classes. In addition, after applying pre-processing techniques, the TF-IDF weighting technique was adopted for feature selection and data extraction. After evaluating various machine learning methods, the SVM outperforms the other eleven algorithms with an accuracy of 91.37 %. We also compare its results with other classifiers like linear SVM, Logistic regression, SGD, Naïve bays, ridge regression, and a few others
Analysis of Advantages and Problems in Teaching and Assessment with Online System during Covid-19
No full textDuring Covid-19 spread over, throughout the world, online classes were arranged at school and University level. In certain institutions, the experiments of online systems were successful while in certain cases difficulties were observed and reported. In this paper, we are interested to highlight and analyze the problems occurring in assessment and evaluation. The delivery of lectures and grades assessment, comparison of time spent on in-class lectures and online, the provided infrastructure and technology to faculty and its synchronization with that arranged by students. The objective type questions are automatically marked by the system for example Moodle, whereas the essay type (subjective type) questions are normally preferred to be marked by faculty on the system. This is indeed a facility that all students are provided with different question papers. The online system is more economical, time-saving and easily usable. The most serious issues have been unfair means and cheating used by students during examinations. A detailed analysis of the state-of-the-art is presented in this paper. We also present a comparison of online and in-class teaching and assessment, but irresistibly the benefits of online system are more advantageous. For example, a lot of stationary is saved. The online system causes breaks and pauses during delivery of lessons due to instability of internet and concavity issues. The most important is the choice concerning system subject to available facility with leaner and the faculty and its compatibility with emphasis on technology. The use of anti-cheating software makes the examination secure
Intelligent Digital Twin to make Robot Learn the Assembly process through Deep Learning
Full text linkThe objective of this paper is to utilize deep learning technology to develop an intelligent digital twin for the operational support of a human-robot assembly station. Digital twin, as a virtual portrayal, is used to design, simulate, and optimize the complexity of the assembly system. For testing purposes, a convolutional neural network (CNN) is integrated with a digital twin. It is used for the application of a collaborative robot for an assembly application. Collaborative robots are a new form of industrial robots that are safe for humans and can work alongside humans and have received ample attraction in recent years for automation of simple to complex tasks
Information Security for Cloud using Image Steganography
No full textCloud computing is getting involved in almost every technological field to serve customers in a more efficient way. The shared resources (pool) with different configurations according to the user’s needs are provided by cloud vendors. Users stores their data on the cloud, data can be personal, or organizational, and data of every type must be secure on clouds. Making the data secure and reducing the integrity of data during transfer through public channels. In this paper, we will try to make data secure using image steganography. Using the steganography technique, we use encryption-decryption of data into images and make data invisible
Traffic Intensity Based Energy Efficiency Architecture for Data-Centers
No full textThe world is moving towards cost-effective and time-constrained solutions. The uses of applications and automated devices have been growing day by day. In computing, resources available in personal computers are limited due to less storage capacity and lower computation speeds. Using all applications on personal systems may not be cost-effective. Therefore, the trends of online storage and computing have become popular. On the other hand, there must be some serving end for these users. One of the major issues, due to the growth of data centers is the increase in power usage of a larger number of servers and network devices. These devices are power-hungry and consume energy even during idle hours even if there are no network traffic loads. The cost of energy used and dissipated is increased in this situation. In this paper, we have given a solution for efficient usage of energy efficiency in data center networks based on traffic loads. We have proposed a model to use traffic intensity to decide the number of machines inactive conditions so that we can save the energy consumption in data center networks. We have implemented this proposed model and simulated it to validate it
Rapid Digital Transformation Using Agile Methodologies for Software Development Projects
Full text linkNow a day’s all organizations are moving towards digitalization. These consequences of the use of digital technologies made organizations seek for best and fast digital solutions. All software developer companies are also trying to draw consumer's attention by offering prompt services. In this regard, the critical issue in information technology and other areas of computation is how software can be created easily and rapidly for complex businesses. In this context, the main aim of the research is to show the agile methodology role in the rapid digital transformation. In this paper, we have surveyed different agile methodologies and tools for rapid software development and introduced an agile management tool having a backlog. We identified the key practices of agile methods and after a survey, it is suggested that the agile approach can help to achieve a balance between the applications generated by developers on customer demand. This paper illuminates and translates agile methodologies into agile project management tools for simple and rapid application development. Empirical research based on a case study is provided for better understanding and showing the importance of agility in software developmen
Configuration-Free Systems for WiFi Sensing based Smart Home using the Smart Remote Controller
No full textThe Smart Home invention offers us extreme supervision over our home by automating the lighting structure, the dimming, the screens, electric machines, the sound and safety frames. Main technologies that provide connectivity to smart home facilities, WiFi is one of them. In traditional households, where the household appliances will increase, the remote controls to manage them and the interference between them will also increase. This makes the system configuration dependent and troublesome for users to manage them that increases their burden. Recently, some systems were developed to manage multiple household appliances through one interface. However, the matter is once the dataset will increases the interface gets sophisticated and every home appliance or controller wants a special device to connect with it. In this paper, we introduced FreeGesture in the DeepRemote controller, which is a gesture recognition scheme without a device that uses preferred computer vision algorithms, particularly deep learning, to recognize numerous devices and manage them via IR or network. It simplifies deployment and makes systems without configuration. We are going to consider it as “Smart Remote” in this article. Smart Remote consists of four buttons, a camera, an Inertial Measurement Unit (IMU), a WiFi component, an Infrared (IR) transceiver, and a speaker. The popularity accuracy of smart Remote for 5 varieties of home appliances from completely different places is hyperbolic from 81.07% to 95.8%
An Expert System for Weapon Identification and Categorization Using Machine Learning Technique to Retrieve Appropriate Response
Full text linkIn response to any terrorist attack on hospitals, airports, shopping malls, schools, universities, colleges, railway stations, passport offices, bus stands, dry ports and the other important private and public places, a proper plan will need to be developed effective response. In normal moments, security guards are deployed to prevent criminals from doing anything wrong. For example, someone is moving around with a weapon, and security guards are watching its movement through closed circuit television (CCTV). Meanwhile, they are trying to identify his weapon in order to plan an appropriate response to the weapon he has. The process of manually identifying weapons is man-made and slow, while the security situation is critical and needs to be accelerated. Therefore, an automated system is needed to detect and classify the weapon so that appropriate response can be planned quickly to ensure minimal damage. Subject to previous concerns, this study is based on the Convoluted Neural Network (CNN) model using datasets that are assembled on the YOLO and you only see once. Focusing on real-time weapons identification, we created a data collection of images of multiple local weapons from surveillance camera systems and YouTube videos. The solution uses parameters that describe the rules for data generation and problem interpretation. Then, using deep convolutional neural network models, an accuracy of 97.01% is achieved
A Comparative Analysis on Handling Big Data Using Cloud Services
Full text linkIn this era of technology, a lot of advancements have been done in almost every field such as medical, science, aerospace and other fields. With the increasing advancements in technology, a lot of data is being produced at the same time. For instances in the field of medicine there is a huge amount of data that is being generated as there are hundreds and thousands of patients who came for their checkup. So now the question arises where this huge amount of data is being stored. This huge amount of data is called as Big Data. And the major problem faced is how to manage and organize this huge amount of data along with its security and not being lost. Big data is used for extracting a lot of useful information but it is not easy to organize it. If the data is being lost than there are a lot of problems that can occur on a huge level as a lot of data being stored in big data is very confidential. This data can be stored on cloud which is the new advancement in the field of technology as it is highly reliable for huge amount of information. So, in this survey paper we will discuss about the solutions of organizing and handling big data proposed by different authors