Introduction Geographic information system (GIS) is a strong tool in flood hazard mapping, mitigation, and management. GIS-based approach provides the capability to measure the flood inundation. Integration of web technologies with GIS (Web-GIS) is quite significant to accomplish the aim. Methodology In this research, HEC-RAS 1D was used to map the flooded area around River Ravi at Lahore. The output of HEC-RAS with Web-GIS stack were used to build the interactive flood measuring tool. The Web-GIS stack used for this study was Geo Server, PHP, HTML, CSS, and JavaScript. Geo Server provides the OGC implemented standards with vendor specific capabilities like WMS Animator in Geo Server animate the flood inundation on the User-Interface (UI) and extent animation to make visual interpretations. CQL filter is vendor specific capability in Geo Server used to measure the flood inundation. Results The Output maps of HEC-RAS are capable enough to understand flood inundation and other damage assessments not only to analyst but also the layman. The working and animated layers are shown in Result section of this research. Conclusion This web-based flood inundation is robust, user-friendly, and expandable for more features, scenarios, and conditions. This research concludes that visual and web-based data is near to mind understanding for common person intellectuals.

In computer vision image detection and quantification play an important role. Image Detection and quantification is the process of identifying nodule position and the amount of covered area. The dataset which we have used for this research contains 3D CT lung images. In our proposed work we have taken 3D images and those are high-resolution images. We have compared the accuracy of the existing mask and our segmented images. The segmentation method that we have applied to these images is Sparse Field Method localized region-based segmentation and for Nodule detection, I have used ray projection. The ray projection method is efficient for making the point more visible by its x, y, and z components. like a parametric equation where the line crossing through a targeted point by that nodule is more dominated. The Frangi filter was to give a geometric shape to the nodule and we got 90% accurate detection. The high mortality rate associated with lung cancer makes it imperative that it be detected at an early stage. The application of computerized image processing methods has the potential to improve both the efficiency and reliability of lung cancer screening. Computerized tomography (CT) pictures are frequently used in medical image processing because of their excellent resolution and low noise. Computer-aided detection systems, including preprocessing and segmentation methods, as well as data analysis approaches, have been investigated in this research for their potential use in the detection and diagnosis of lung cancer. The primary objective was to research cutting-edge methods for creating computational diagnostic tools to aid in the collection, processing, and interpretation of medical imaging data. Nonetheless, there are still areas that need more work, such as improving sensitivity, decreasing false positives, and optimizing the identification of each type of nodule, even those of varying size and form.

Pakistan, which is positioned in the South Asian sub-continent, occupies a significant climatological location. It is included among the world's few countries which experience a comprehensive transformation from summer all the way to winter season. The variation in precipitation has direct and significant consequences on society. In this ongoing research, the latitudinal variation in the track of the frontal system and trends in Pakistan during the monsoon period have been examined. Meteorological data (monthly rainfall, maximum temperature, satellite images, upstream data for Tarbela, Mangla, Rasool, and Marala) has been taken to conduct the ongoing research. Consequently, the focus of the study is the frontal weather system that moves North of Pakistan and energizes the monsoon rainfall over the Indus Basin which makes it a source of flooding. The rainfall is the cause of flooding downstream of rivers in the plains of Punjab and Sindh. Varying trends in rainfall were observed across the selected stations in Pakistan. The ongoing research is conducted across Pakistan with Gilgit and Skardu being the cities in Northern Pakistan. Among all the water reservoirs, Tarbela exhibited an increased upstream flow due to the snow melt factor over glaciers in Gilgit and Skardu because of an increase in maximum temperature.

Alarge number of studies including research articles and surveys on android malware detection and analysis techniques have been presented during the last one and a half decades. The authors proposed different systems and frameworks to identify malware from software applications. However, there is no recent and comprehensive systematic literature review on the detection and analysis of android malware methods, systems, and frameworks. We present a systematic review of literature on android malware detection and analysis techniques and tools by following standard guidelines for Systematic Literature Review methodology from 2010 to 2021. We selected 75 most relevant studies out of 3343 published studies. We found that the prominent malicious datasets are Genome (39%) and Drebin (36%) used by different researchers for the detection of malware. The static, dynamic, and hybrid source code analysis methods are applied by android malware detection techniques. We also identified the limitations and future research directions of existing techniques as research gaps for the community. Based on the pragmatic evidence of this research, we have proposed a hybrid analysis-based multiple feature analysis framework. This framework will not only address the limitations of static and dynamic-based approaches, but it also analyzes evolving android malware datasets using deep neural network and machine learning techniques and improve the accuracy of evolving malware samples.

Discipline of urban planning only developed around a century back with the first academic school at the University of Liverpool in 1909. However, the theory of this discipline is relatively older and might date to varying timelines around various parts of the world. However, modern urban planning discipline has got birth in the US and Western Europe. Early development in the theory of urban planning develops challenges for the cities. In response to such challenges, the planning approaches seem to adapt to the needs of emerging regimes evident from the high-scale urban renovation of Paris by Haussmann. This is called the Progressive Model of Planning wherein planners of the time struggled to deal with the challenges imparted by the Industrial Revolution through scientific and engineering-based knowledge. Early urban planning efforts were mostly anarchist movements that reacted to the social issues of the time and include Garden City, Radiant City, Broadacre, etc. This study sought to present these theoretical considerations with respect to certain development classifications in urban planning. Accordingly, the methodology of the research study comprises the following sections/segments for a better understanding of urban planning at different times: i. Pre-History of Urban Planning ii. Foundational Years iii. Modernism (Rational Planning) iv. Post Modernism (Post war suburbia) v. Current Era In short, it is concluded that cities have emerged as a result of conscious decisions. Accordingly, looking into the planning theory requires due consideration of the planning approaches utilized over time. This perceives that planning theory is essentially the study of the decisions made from intuition and that is equally right because planning theory and practice development are in parallel.

Human action recognition recognizes an action performed by human beings in order to witness the type of action being performed. A lot of technologies have been developed in order to perform this task like GRN, KNN, SVM, depth maps, and two-stream maps. We have used 3 different methods in our research first method is a 2D CNN model, the second method uses an LSTM model and the third method is a combination of CNN+LSTM. With the help of ReLu as an activation function for hidden and input layers. Softmax is an activation function for output training of a neural network. After performing some epochs the results of the recognition of activity are declared. Our dataset is WISDM which recognizes 6 activities e.g., Running, Walking, Sitting, Standing, Downstairs, and Upstairs. After the model is done training the accuracy and loss of recognition of action are described. We achieved to increase in the accuracy of our LSTM model by tuning the hyperparameter by 1.5%. The accuracy of recognition of action is now 98.5% with a decrease in a loss that is 0.09% on the LSTM model, the accuracy of 0.92% and loss of 0.24% is achieved on our 2D CNN model while the CNN+LSTM model gave us an accuracy of 0.90% with the loss of 0.46% that is a stupendous achievement in the path of recognizing actions of a human. Then we introduced autocorrelation for our models. After that, the features of our models and their correlations with each other are also introduced in our research.

Introduction/Importance of Study: Social networking websites have become the main medium for communication, information sharing, entertainment, buying/selling, and various other purposes. People of every age use social networking websites, and their usage is increasing daily, especially in current circumstances. People with different abilities also used social networking websites, but each set of users had their requirements forusing these websites. Visually impaired people use computers and the web with the help of screen reading tools e. g.; jaws, NVDA. Screen reading tools read a web page sequentially, which wastime-consuming. The major problem with screen reading tools came while reading visual content. Screen reading tools only read the alternate texts of non-visual contents behind their tag. This research focuses on the usability Usability of social networking websitesfor visually impaired people. Two of the most commonly used social networking websites, Facebook and Instagram, were selected for the usability evaluation. Accessibility, efficiency, and effectiveness were the metrics of Usability, which were evaluated in this study. Novelty statement: A consolidated set of guidelines specific to social networking websites were presented in which some new guidelines were also proposed for Facebook. A mock interface was developed based on the proposed guidelines for Facebook. Material and Method: For the evaluation of Usability, a controlled experiment was conducted with 28 visually impaired people in which 16 participants evaluated Facebook and 12 evaluated Instagram to find the usability problems faced by visually impaired people. Result and Discussion: Results show that Instagram was as easy to use asFacebook when used by visually impaired people with the help of screen reading tools. Concluding Remarks: This research evaluated the Usability of social networking websites Facebook and Instagram by visually impaired people. A controlled experiment was conducted for their evaluation. Results showed that Facebook was difficult to use as Instagram. Thus, new guidelines were proposed for Facebook and based on the guidelines, a prototype was proposed.

With the passage of time networking field has become much more advanced. Because of this advancement, the communicating parties don't want to rely on the third party for communication because a third party may misuse or share their personal information with someone else. That’s why there is a need for such a method at which we can rely on secure communication. In recent years a lot of cryptographic techniques based on ASCII values have been proposed, but selecting an efficient and effective technique from them is a big task. In this paper, we have made a comparison among several techniques based on certain parameters to find out the best one for the ease of the users.

Background: The primary purpose of this study is to find out the Significance of Cognitive Distortions and Risk Factors due to Android Game Addiction for Adults. Methods: The research population includes three main parameters Physical Effects, Mental Effects, and, Cognitive Effects each part contains 10 questions. The sample comprises 200 school students (male=150, females=50) between the ages of 8 to 20 years recruited from schools in Lahore, Pakistan. A total of 200 copies of the Questionnaire are distributed among the students. Only 180 copies are received and filled so the total response rate of the data collection was 90%. The SPSS tool was used to analyze the results of the Questionnaire. It aims to investigate the impacts that Android Games have on adults. As most of the researchers have done Quantitative research in this area, so I decided to conduct both Quantitative and Qualitative research designs which can help us get a deeper understanding of Android Game Addiction. Findings: By going through the results, it is revealed that the all above-mentioned three main parameters are found positive in adults. According to the range of the frequency, it is concluded that all three factors are in the medium range not more harmful. There was a strong positive association between the addictions of students to Android mobile games and their physical and mental well-being in terms of physical, mental, and cognitive health.