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Item Automatic teaching methods analysis through classroom videos using deep learning(UMT Lahore, 2020) FAHEEM WALI MOHAMMAD KHASKHELIIn this work, an automatic teaching analytics system is developed to generate statistics related to teaching methods in classrooms using deep learning from videos. Lecture videos from different classrooms through CCTV cameras are collected. These videos are split into three seconds clips which are saved in different folders based on action performed within those clips. A teacher’s actions can be standing, student teacher talking, writing on board, pointing to board, delivering presentation or cleaning board. Several deep learning models are experimented to automatically classify these video clips into different classes. These models are developed using different layers such as 3D CNN, ConvLSTM2D and Time Distributed layer. The models are trained from scratch after which we are able to achieve 94% validation accuracy for individual clips of teachers’ actions within classrooms. Accuracy for the whole lecture video is between 70% to 72%. There are several challenges with the dataset such as the video quality is not very good, some video samples have less than one second of the action and intra-class similarity is also high among certain classes.Item 4mc-rf(UMT Lahore, 2020) FAJAR ARSHADN4-methylcytosine 4mC is an essential epigenetic modification that occurs enzymatically by DNA methyltransferase. 4mC sites exist in prokaryotes and play a vital role in regulating gene expression, DNA replication, and cell cycle. The efficient and accurate prediction of 4mC sites has a significant role in the insight of 4mC biological properties and functions. Therefore, we have proposed a sequence-based predictor, namely 4mC-RF, for identifying 4mC sites in prokaryotes by integrating statistical moments along with position and composition dependent features. Relative and absolute position based features are computed to extract the optimal features. A popular machine learning classifier Random Forest was used to training the model. Validation results were obtained under rigorous processes of Self-consistency, 10-fold crossvalidation, Independent testing, and Jackknife testing giving 95.01%, 95.02%, 97.02%, and 95.36% accuracies. Our proposed model depicts the highest prediction accuracies as compared with the literature results. Thus, the developed 4mC-RF model was constructed into a web server. A significant and more accurate predictor of 4mC Methylcytosine sites helps experimental scientists gather results moderately.Item Prediction model developed through rf, ann and svm classifier for angiogenesis &tumor angiogenesis process(UMT Lahore, 2020) RABIA KHANA crucial biological process called Angiogenesis plays a vital role in migration, growth, and wound healing of endothelial cells and other processes that are controlled by chemical signals. The balancing of these signals is necessary for the proper working of angiogenesis. Unbalancing of these signals increase blood vessel formation, which causes abnormal growth or several diseases including cancer. The proposed work focuses on developing a two-layered prediction model using different classifiers like Random Forest, Neural Network, and Support Vector Machine. The performance of the model is evaluated through various validation techniques. The first layer of the model predicts whether the given primary structure corresponds to angiogenesis proteins or not. If it is determined as an angiogenesis protein then the second layer of the model will classify whether or not the protein plays a role in tumor angiogenesis. The model was trained on RF, ANN, and SVM and it was evaluated by using k-fold crossvalidation, independent, self-consistency, and jackknife testing. The overall accuracy of RF for angiogenesis is 99.3% and tumor angiogenesis is 99.7%, ANN showed 96.23% accuracy for angiogenesis and 78.65% for tumor angiogenesis, and the accuracy of SVM for angiogenesis is 78.65% and for tumor angiogenesis is 65.19%.Item Numerical modeling and simulation of engineering problems(UMT Lahore, 2020) AHSAN RAZAThis work is presented in the study of boundary value problem for thin film flow of fourth grade fluid down a vertical cylinder. The practical usage of the exact flow is restricted as it involves very complicated integrals. The nonlinear problem that arises is solved by Galerkin’s finite element approach based on weighted-residual formulation which is used to find the approximate solutions of the fourth-grade problem. This approach utilizes a piecewise linear approximation using Linear Lagrange polynomials. Convergence of the solutions which briefly describes the flow characteristics to include the effects of the emerging parameters. The results obtained after implementation are not restrictive to small values of flow parameters. Numerical studies have shown the superior accuracy and lesser computational cost of this scheme in comparison to collocation, homotopy analysis method and homotopy perturbation method. The impact of the relevant parameters is examined through graphical results after implementing a number of iterations.Item Iptsw (3l)(UMT Lahore, 2020) MAHA ASHRAFThe promoter sequence in genomic data are comprising of 81-1000base pairs, exists in the upstream part of the genic transcriptional start site. It modulates the transcription mechanism of many genes in association with a variety of transcriptional factors. With the revolution in the advanced-genomic era, it is essential to statistically classify the promoters. Such classification may help in drug development. Some forecasting methods were established. Most of them were restricted to the pure recognition of a DNA query sequence. However, based on their differing levels of strength for transcriptional activation, the advertising expression can be split into three layers: promoter vs non-promoter, types of promotors, and their strengths. A modern three-layer predictor, named "iPTSW (3L)" has been established by integrating the information of nucleotide abundance and physiochemical properties into position and composition-dependent features. Its first layer decides whether the query DNA sequence is a valid promoter, the second layer classifies the type of a promoter, while its third layer determines the strength of the promoter. A model is trained by using the Random forest technique to learn the pattern and sequence of the data for prediction. An accuracy of 97.57% for 10-Fold cross-validation, 99.8% for Jackknife validation, and 89.0% for Independent Testing was achieved. These results indicate that the proposed methodology plays a vital role in prediction instead of performing all tests in the laboratory utilizing conventional ways and also cost Efficient. This research can also help in solving relevant prediction problems. The web server http://biopred.org/promotersis developed for Sequence Prediction.Item Framework for security of health monitoring applications(UMT Lahore, 2020) MUHAMMAD SAMIMobile phones have given application designers the chance of bringing actual period correspondence among doctors and patients. The proposed framework of Health monitoring apps comprises essentially of utilizations of software and work at the degree of equipment. This framework is for the most part used to sift through interminable illnesses, screen the senior and eager moms, and help the patients. iOS and the Google play stores are the two significant conveyance stages that underpin the Android and iPhone activity framework. The proposed framework of health monitoring apps helps to screen and record a patient's standard activities. The treatment includes the fundamental protection issues concerning various information of patients, specialists, and guardians. The security in the proposed framework of health monitoring apps is fundamental as their information is traded with remote systems. The proposed framework of Health monitoring apps that are likewise open in the online circulation stage which are called Android. Android stage deals with all the delicate information that is helpful for the expert (specialist, doctor, and advisor). The security framework of health monitoring apps structure configuration comprises two layers: A Monitoring Layer (ML) which is utilized to framework the modules of security-checks, an interface layer (IL) which givesinterface among (ML), and working framework Android. The approval of the proposed framework is apparent through the usage of real Android gadgets; this execution shows the system for all intents and purposes and assesses its presentation. The significance of tests indicated that they effectively secure the health care app framework against various assaults through the proposed structure.Item Cloud computing security issues and services using enhanced virtualized Platform" ”(UMT Lahore, 2020) HUSNAIN ZAHEERBy the passage of time computer technology has become more useful and of low cost . The change in computer technology has given rise to a new technology called cloud computing, computer resources have made data storage more easier using softwares and hardware tools. This new tech has been divided into two parts the inside view of system who control cloud systems and user friendly data keeping environment, customers are served in a inside database environment. This new technology has gave good attractive response to the industry .we use software to offer healthy support through internet. The cloud involves both I/o and outside software support. We openely and freely to all people we name it as public cloud; the result in response to user query in cloud is software computing. Examples of public software computing consist of all net services. We use cloud working session for inside working not open to all. The reverse order result will require a new platform for data protection. This studies will growth the service support for every layer activity and could maintain backup of all statistics offering a virtualized surroundings for every layer the statistics for every person is first being despatched to disbursed offerings introduction platform which passes it via assuarance platform which in addition transfers it to digital aid layer at bottom computer community storage is used then at last transport platform is signaled and message is going to cease person.Item A survey of prediction method using feature selection in genomics(UMT Lahore, 2020) ATIF ANWAR MIRZAMicroarrays have enabled the scientists to study expression of hundreds and thousands of genes in a single experiment with very low number samples and biological replicates, most of microarray gene expression studies are used to classify human cancer using expression levels of genes in cancer cells compared with normal cells. The data scientists have huge amount of data submitted in the repositories for analysis and development of algorithms for efficient classification and selection of genes. This huge amount of data with fewer number of biological samples has huge dimensionality in the data due to a number of biological and technical reason. Feature selection in this scenario can not only reduce the dimensionality of data but it can also reduce the number of features to be analyzed without affecting the prediction capability, thus reduce the computational load and save time being used for data analysis. Two data sets having samples from three leukemia subclasses acute lymphoblastic leukemia from B and T cell and acute myeloid leukemia. While training data set comprised of 30 samples (10 acute lymphoblastic leukemia -B, 10 acute lymphoblastic leukemia –T and 10 acute myeloid leukemia). The test data set consisted of 38 samples (19 acute lymphoblastic leukemia -B, 8 acute lymphoblastic leukemia –T and 11 acute myeloid leukemia). The metagene factors were extracted and evaluated by the method described by Tamayo et al., 2007. Feature selection is a process where you automatically select those features in your data that contribute most to the prediction variable or output in which you are interested. Feature selection algorithms like Information Gain, Gain ratio, Gini Index, ReliefF, The Fast Correlation-Based Filter, Analysis of Variance (ANOVA) and Chi2 were used. For testing of hypothesis that feature selection may improve prediction efficiency of metagene classification the method proposed by Tamayo et al., 2007 was modified with hybrid approach. The feature selection was performed in python using orange 3.25 GUI and the selected data were analyzed using metagene projection model. Feature selection algorithms application was planned with for types of data selection using each algorithm i.e., 100%, 75%, 50% and 25% of total data were selected for metagene prediction using each of the seven feature selection methods. The feature selection method was applied on original data having 5571 features/genes in python using Orange 3.25 graphic user interface and 100% features were selected i.e., 5571 features were analyzed for metagene prediction SVM algorithm in R graphic user interface and the results are shown in bio plots of model and test samples, hierarchical clustering of original data and projected data and heat maps of original and projected data were developed. To evaluate the prediction ability of the model with special reference to data filtering using various feature selection categories two parameters were calculated i.e., brier score and error percentages were calculated. ReliefF was proved to be the best method for feature selection based on lowest brier score and lowest error percentage.Item Discovery of antiviral phytochemicals for the treatment of coronavirus disease 19 (covid-19)(UMT Lahore, 2020) MUHAMMAD SOHAIB ROOMICorona Virus Disease 19 (Covid-19) is an epidemic infection which is originated from Wuhan, China. Sars-Cov-2 is a virus that spreads this disease inside human body. Scientists made efforts to contain and examine the cause and severity of this Virus so that Antiviral drugs and precautionary measures could be suggested. One way to control this virus is to stop the reproduction and progression of this disease inside the human body. RNA-Dependent-RNA-Polymerase which is known as RdRp is the leading protein of coronavirus which is the main actor in the replication operation and leads the viral infection in the human body. Inhibition of RdRp can stop the replication and as result damage in the human body. To inhibit the working of RdRp, many antiviral drugs and compounds like Hesperidin, Remdesivir, Camostat Mesylate, and Famotidine have been proposed and which are in clinical trials to examine their effects on the large scale. Phytochemicals are natural and less reactive compounds and generally have very few side effects. These compounds can be found in different kinds of plants, fruits, and flavonoids. This study also focuses on phytochemicals and other natural compounds with antiviral properties so that potential compounds can be examined during interaction with the virus. A large number of natural compounds were selected from chemical and plants’ databases and most suitable compounds are selected for further evaluation. Numerous in-silico analysis tools and techniques are followed to carry out the standard procedures which are used worldwide. These techniques consist of Docking, Virtual Screening, Molecular Analysis, and Protein-Ligand Visualization. After following all these steps, combinations of most suitable natural substances were selected via in-silico analysis. A comparative analysis has been carried out between the proposed compounds and compounds which are already under trial. A study has shown that the proposed compounds have strong potential to be considered in place of already under trial compoundsItem Nested bee hive(UMT Lahore, 2020) RANA MUHAMMAD NADIRSeveral smart city ideas are introduced to manage various problems caused by overpopulation but, the futuristic smart cities is a concept of dense and artificial intelligence (AI) centric cities. Thus, a massive device connectivity with huge data traffic is expected in the future, that can make the situation more complicated for the existing networks. 6G is considered as the problem-solving network of futuristic cities with huge bandwidth and low latency. The expected sixth generation of the Radio Access Network (RAN) is on terahertz (THz) waves with the capability of carrying up-to one terabit per second (Tbps). THz waves have the capability of carrying a large number of data but these waves have some drawbacks like short-range and atmospheric attenuation. Hence, these problems with THz waves can create complications for 6G network. In this article, we have envisioned the futuristic smart cities using 6G and proposed a conceptual Terrestrial Network (TN) architecture for 6G. Moreover, we have designed the multilayer network infrastructure while considering the expectations from network of futuristic smart city and complications of THz waves. Furthermore we have performed simulations of different path finding algorithms in 3D multilayer domain to evaluate and set the dynamics of futuristic communication of 6G.Item A novel s-box design technique based on modular inverse and square transformation(UMT Lahore, 2020) MUHAMMAD AZFAR TARIQ BAIGCryptography is an important field for making data confidential. Modern block ciphers in cryptography are the crucial and worthwhile techniques employed to provide secure communication. Permutation and substitution enhance the effectiveness and efficacy of block ciphers. For the purpose of substitution, block ciphers utilize substitution boxes. An S-Box plays an essential role to produce chaos between plaintext as well as cipher text. Many techniques are applied to construct cryptographically robust S-Boxes. The proposed method is based on modular inverse and square transformation for designing more efficient and solid S-Box. S-Box is passed through various criteria such as Nonlinearity, Strict Avalanche Criterion (SAC), Bit Independence Criterion (BIC), Linear Probability (LP), as well as Differential Probability (DP) to analyze the durability of S-Box. Comparison between proposed S-Box and previously designed S-Boxes demonstrates that the proposed S-Box is more viable than compared S-boxes. Consequences collected from criteria suggest that the proposed S-Box can be employed in modern ciphers.Item Itransaminase- pseaac(UMT Lahore, 2020) Mahreen ZainabThe major focus of this thesis is to identification of transaminase and non-transaminase through dataset of 3077 positive and 2500 negative sequences which was collected from uniport. We review new spectrophotometric determination methods to determine the transaminase activity. The main diseases which were diagnosis through transaminase levels in bloodstream are liver and heart it is very important to diagnose them in preliminary stage for better treatment. In present scenario to detect infection of liver devise like sensors were used or blood sampling in laboratory. In this context, this research utilizes neural network approaches for classification of the diseases due to transaminase in patients. We majorly discuss algorithm (SVM) and their results for the identification of transaminase and non-transaminase. Further to improve the accuracy of identification a new model was developed i-transaminase using Random forest Algorithm. This model was tested for its performance using feature extraction components like Statistical Moments Calculation, PRIM, RPRIM, AAPIV and RAAPIV. The new model resulted in prediction accuracy of 99.9% using testing like self-consistency, jackknife, cross validation. The accuracies for above mention testing is 99.9%, 99.93% and 99.87. The results ensure that development of this model improved the accuracy of identification. To serve the medicine community for identification of transaminase in liver and heart patients, a user interface also developed using Python. This GUI is deployed as a package in local repository or also on webserver.Item A novel method to design the substitution box by an affine transformation matrix and aes block cipher(UMT Lahore, 2020) MIAN MUHAMMAD UMAR SHABANNowadays, data security and privacy have become a major challenge. To secure the information, most of the organizations use data encryption and decryption methods known as ciphers. Modern day ciphers use key-dependent dynamic substitution boxes (S-Boxes) to encrypt and decrypt data. An S-Box is generated from the key to make it dynamic. In this thesis, a novel method of S-Box design is presented. To prove the strength of the proposed S-Box, a critical evaluation is done with standard properties that include Bit Independence Criterion, Nonlinearity, Linear Probability, Differential Uniformity, and Strict Avalanche Criterion. The results are compared with other well-known S-Boxes. The results of the proposed S-Box are quite encouraging and hence can be used in future ciphers.Item Prediction of rna-binding proteins with respect to their domains.(UMT Lahore, 2020) ARJMAND MAJEEDDue to innumerability and diversity in biological processes, many cellular physiological processes depend on the decisive factors of interaction between RNA and protein. RNA-binding proteins (RBPs) habitually changes the functionality of RNA by making abound with one or more globular domains of RNA-binding with incredibly diverse structure and mechanisms. High productiveness of biological experiments come up with enough essential information, to initially identify the RNAprotein interaction, however, RPI networks complexities are so time-consuming and expensive. Hence, a reliable and high-speed prediction method becomes necessary. In this proposed work, we put forward a computation method that uses sequential information for the prediction of RNAprotein interactions and their domains like K- homology, RNA Recognition Motif, Ribosomal protein S! -like, THUMP domain, C2h2 Zinc Finger/CCCH zinc finger and PUA through which they interact. Position relative statistical moments were calculated for the training of neural networks. With the use of 10-fold cross-validation and jackknife testing accuracies of 94.97% and 96% have been achieved respectively whereas the accuracy of the overall system is 94.4% with a sensitivity value of 94%. The obtained result shows a high potential to play an important role among the existing method.Item Sequence-based prediction model developed through xg-boost, rf, knn, ann and svm classifier for phage promoter prediction(UMT Lahore, 2020) KANWAL MAJEEDAs numerous potential applications of phages in modern biotechnology industry are wellknown. Knowing that they have been proposed as a vehicle for the DNA and protein vaccines, as a vehicle for gene therapy; an alternative to antibiotics; for detection of the pathogenic bacteria. The challenging task in the phage genomes annotation is to identify the regulatory elements, which are primarily the promoters, the specific DNA sections which are accountable for transcription initiation. Considering this prediction present research is creating a model to identify the phage promoter. The proposed work emphases on the development of a prediction model by using different classifiers ANN, SVM, Random Forest, KNN, and XG-Boost. The performance of models is evaluated using independent testing, cross-validation, and jackknife testing. The accuracies of ANN, KNN, XG-Boost, and Random Forest are 99.8% whereas the accuracy of SVM for phage promoters is 100%.Item Blockchain technology and its association with artificial intelligence(UMT Lahore, 2020) MUHAMMAD RASHID ILYASThis work gives a precise review of blockchain and its relationship with artificial intelligence alongside the security difficulties of Blockchain. It is additionally an investigation of a few speculations on the union of Blockchain and Artificial Intelligence. A status of blockchain revolution along applications, momentum challenges in blockchain and investigation the future patterns of blockchain is presented. The synthesis of BC, and AI will give adaptable, secure elevated level scholarly working that will be the new worldview of advanced data. This paper presents an extensive investigation of the tradeoffs of blockchain and furthermore clarifies the scientific categorization and engineering of block chain, gives diverse agreement instruments, and talks about difficulties including, adaptability, administrative issues, and protection, interoperability, and energy utilization. Various papers from highly reputable journals are added in the study which was published during last five years. Considering an organized and orderly survey, an extensive grouping of applications of block chain across different areas, such as information the board, protection, medical care, business, store network, IoT is made in this survey along we highlight the deficiencies present currently especially limits the block chain revolution presents and how these constraints bring forth across various areas and enterprises.Item Evaluation of customer behavior using social media (a statistical analysis)(UMT Lahore, 2020) MUHAMMAD AFAQNow a days for the growth of any business we know that customer engagement is very important. So, social media marketing plays very important role for that purpose.it is very important to know that which company growth graph is in positive direction for customer engagement and which company graph is in down direction for customer engagement. The main purpose of this study to analyze that which and how many customers like and dislike the pizza brands on Facebook that is used for social media platform. So, in this study we collected one year data of selected five pizza brands. Using these pizza brand’s customer generated data we can analyze the customer behavior about any pizza brand that how much customers are engaged with any pizza brand. This engagement is analyze base on the customer generated comments and like and dislike action performed by the customer for any pizza brand pages on Facebook. So by this analyses we find that images and videos type content are more attractive than any other written content and.so it is analyze that videos or images type content provide help to engage more customer on Facebook pages. So in this study we analyze how we can measured Facebook usage for any pizza brand and we find that how pizza industry can grow their business using social media (Facebook). So with the help of this study pizza brands can plan their strategies for the marketing purpose.Item Emotion recognition from speech using deep neural networks(UMT Lahore, 2020) KAMRAN UL HAQEmotions play an important role in the social interactions of humans and it is often said that emotions separate us from machines. Spoken words may have different interpretations depending on how they are uttered. The same sentences can have different meanings under different types of emotional states. The human brain understands different meanings by perceiving underlying emotions in speech. Finding the emotional content from speech signals is desirable because this enables us to teach emotional intelligence to computers. Speech emotion recognition is an important field of study with applications ranging from emotionally intelligent robot creation, audio surveillance, web-based E-learning, computer games, etc. The objective of this dissertation is to identify emotions in an audio speech by using deep learning algorithms including Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) to identify different emotional states of a person. In this regard, the RADVEES dataset, Ryerson Audio-Visual Database of Emotional Speech and Song, is used to study speech emotion recognition. For experiments, we used approximately 1247 audio and song files containing eight different emotions for the classification of audio data. The experimental results show that the best performing model was CNN based model with an accuracy of 74.57% while the RNN model only showed 60.00% accuracy, which is far less in comparison. This work will be extended in the future using different variants of RNNs and other DNNs like autoencoders. Audio is a complex signal with linguistic and paralinguistic features and our future goal is to combine these features with different neural network architectures for developing improved SER systems.Item Desksolutions(UMT Lahore, 2020) Muhammad Kaleem Shahid; Dawood Meer; Muhammad Badar Maqsood; Rukhsar Iqbal; Fahad SajjadDeskSolutions elaborates on the premise of developing an application as well as a web portal that would support multiple inter-related functionalities of an HR Management System. The document discusses how various components of HR are to be brought into an integrated system to provide companies with an effective solution to their daily tasks that were previously relied heavily on manual work. The document further encompasses the explanation and detailed working of how each module works on its own and would be embedded with other components.Item A security and privacy evaluation of fintech mobile applications(UMT Lahore, 2020) ZUNAIRA MUNAWARFinTech is an emerging technology comprises of two words i.e. financial and technology. FinTech is proving to be a disruptive technology and is meant to help users in managing their day-to-day financial activities. The FinTech industry is growing up enormously in Pakistan for the last few years, due to the continuous development in information technology; user expectations are continuously increasing in financial services owing to transparency, convenience, privacy, and security, moreover, it has a simple and effective interface. Security is the key feature in mobile apps as Security is an important any time money is involved so security should be among the most important consideration when building FinTech mobile applications. This research objectives is to produce a survey of FinTech security by assembling and studying existing accomplishments in security issues of the financial business. Afterward, our research analysis exclusively focused on identifying the security issues in FinTech mobile applications and evaluate how many people have faced security issues using FinTech apps in Pakistan. Therefore, a quantitative analysis has been applied to the collected data to figure out the issues of FinTech in detail, which currently has an impact on the quality of FinTech mobile apps directly and indirectly. It also provides comprehensive statistical analysis by analyzing and applying on respondents’ profiles, frequencies, and descriptive studies through SPSS. Using the finance-related Information apps on cell phones in a superior manner will improve the user’s satisfaction. It proves that the security mechanism guarantees the success of any mobile app.