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An Algorithm to Reduce Compression Ratio in Multimedia Applications

Computers, Materials & Continua 2023年第1期74卷 539-557页

作者： Dur-e-Jabeen Tahmina Khan Rumaisa Iftikhar Ali Akbar Siddique Samiya Asghar Department of Electronic Engineering Sir Syed University of Engineering&TechnologyKarachiPakistan Department of Information&Computer Science Sir Syed University of Engineering&TechnologyKarachiPakistan

In recent years,it has been evident that internet is the most effective means of transmitting information in the form of documents,photographs,or videos around the *** purpose of an image compression method is to encode a picture with fewer bits while retaining the decompressed image’s visual *** transmission,this massive data necessitates a lot of channel *** order to overcome this problem,an effective visual compression approach is required to resize this large amount of *** work is based on lossy image compression and is offered for static color *** quantization procedure determines the compressed data quality *** images are converted from RGB to International Commission on Illumination CIE La^(∗)b^(∗);and YCbCr color spaces before being *** the transform domain,the color planes are encoded using the proposed quantization *** improve the efficiency and quality of the compressed image,the standard quantization matrix is updated with the respective image *** used seven discrete orthogonal transforms,including five variations of the Complex Hadamard Transform,Discrete Fourier Transform and Discrete Cosine Transform,as well as thresholding,quantization,de-quantization and inverse discrete orthogonal transforms with CIE La^(∗)b^(∗);and YCbCr to RGB *** to signal noise ratio,signal to noise ratio,picture similarity index and compression ratio are all used to assess the quality of compressed *** the relevant transforms,the image size and bits per pixel are also *** the(n,n)block of transform,adaptive scanning is used to acquire the best feasible compression *** of these characteristics,multimedia systems and services have a wide range of possible applications.

关键词： Color image compression color spaces discrete orthogonal transforms(DOTs) peak-to-signal noise ratio(PSNR) similarity index

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Forecasting Karachi's Air Temperature Variation: Leveraging Mobile and Multimedia Dataset for Global Warming Insights

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Journal of Mobile Multimedia 2024年第6期20卷 1289-1320页

作者： Zaffar, Asma Ahmed, Shakil Rafique, Aysha Imran, Muhammad Amir, Muhammad Uddin, Vali Department of Mathematics and Sciences Sir Syed University of Engineering and Technology Karachi Pakistan Department of Computer Engineering Sir Syed University of Engineering and Technology Karachi Pakistan Department of Telecommunication Engineering Sir Syed University of Engineering and Technology Pakistan Department of Civil Engineering Sir Syed University of Engineering and Technology Karachi Pakistan Sir Syed University of Engineering and Technology Professor and Dean Computer and Electrical Engineering Karachi Pakistan Sir Syed University of Engineering and Technology Professor and Vice Chancellor Karachi Pakistan

In Karachi, the transport and building industries have a major impact on carbon dioxide (CO2) emissions and greenhouse gas emissions. This study is innovative in that it examines how air temperature changes over time ... 详细信息

In Karachi, the transport and building industries have a major impact on carbon dioxide (CO₂) emissions and greenhouse gas emissions. This study is innovative in that it examines how air temperature changes over time and forecasts the maximum and minimum temperatures in Karachi. Specifically, it looks at 60 years' worth of mean monthly maximum and minimum air temperatures in Karachi, spanning from (1961 to 2020) dataset classes. The monthly average air temperature in Karachi, both at its minimum and maximum, remains constant. Using dataset from the Pakistan Metrological department (PMD) and, the ARMA (p, q) model technique was used to assess forecasting and modelling the behavior of the maximum and minimum air temperatures in Karachi. The least values Akaike information criterion (AIC), the Bayesian Schwarz information criterion (SIC), and the Hannan Quinn information criterion (HIC) are used to describe how adequate the model is. Additionally, the Durbin-Watson (DW) test is used. The average monthly maximum and minimum air temperature in Karachi are strongly correlated, as indicated by DWvalues (<2). The lowest and maximum monthly average air temperatures in Karachi are predicted using diagnostic checking techniques such as Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Theil's U-Statistics. The results indicate that there is a strong correlation between the air temperature and previously measured values, with Theil's U-Statistics values for each month lying close to zero. This study is a great resource for observing how air temperature affects global warming. This study also highlights the the innovative aspect of utilizing vast datasets, possibly including those from mobile and multimedia sources, to address a critical environmental issue. It also emphasizes the predictive modelling aspect of your study, which is central to understanding and mitigating global warming effects. © 2025 River Publisher

关键词： air temperature ARMA (p kurtosis q) model root mean square error skewness

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SmogMaster- LIDAR-Enhanced Driving Assistance for Beyond Visibility in Dense Fog 4

SmogMaster- LIDAR-Enhanced Driving Assistance for Beyond Vis...

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4th International Conference on Innovations in Computer Science, ICONICS 2024

作者： Saleem, Falak Huzaifa, Muhammad Iqbal, Duaa Sir Syed University of Engineering & Technology Department of Software Engineering Karachi Pakistan

ISBN: (纸本)9798331504342

This paper introduces 'SmogMaster: Your Smart Driving Companion, ' the Visual Editorial Quality Assurance, an intelligent Smart Driving Assistant System (SDAS) in areas with high foggy weather affected by heavy fog. This system is installed with a RP Lidar Al sensor, camera, and the Yolov8s model for real-time feedback. By using Lidar technology, the system identifies obstacles and objects in order to create some kind of a point of cloud, which helps to avoid collisions and accidents. The Yolov8s model is equipped with a camera to identify the objects/obstacles and to calculate the distance between preprocessors using real part identification barrier to prevent accidents. SmogM aster is specially designed to be installed/implemented in the areas which are heavily affected by fog to provide accurate and timely heavy smog warnings and thus making it safer to drivers. This paper includes the development, implementation, and testing of SmogMaster, demonstrating that it has an order of magnitude lower risk acceptance potential to low-visibility accidents. The results demonstrate that The range of systems the SmogMaster helps discriminate against drivers, raising the bar for intelligent driving systems in unfavorable weather. © 2024 IEEE.

关键词： Acceptance tests

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Converting 2D Images into 3D Holograms: An Analysis of Modern Holographic technology 7

Converting 2D Images into 3D Holograms: An Analysis of Moder...

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7th Edition Global Conference on Wireless and Optical Technologies, GCWOT 2024

作者： Khalil, Nida Nawaz, Mohammad Talha Ejaz, Mahnoor Zahid, Shanzay Ahmed, Aryan Sir Syed University of Engineering & Technology Department of Software Engineering Karachi Pakistan

ISBN: (纸本)9798331534271

Several cutting-edge modern technologies, including hologram technology, have emerged due to the tremendous advancements of our era. The science of holography is used to make holograms, which are 3D images with lifelike graphics. With its vibrant 3D views and immersive experiences, holographic technology transforms into a different form of fields like education, entertainment, advertising, etc. This study outlines an easier way to modify the 2D images into 3D holograms. Blender software and a holographic fan projector are used in this process. The process begins with Blender, the 3D graphics suite, is opened and converts flat images into more detailed animated models. These are then sent to a mobile app which transfers them onto a holographic display easily. The mobile application acts as a convenient medium for users to customize or manage their pictures. Utilizing innovative holographic technology to produce lifelike 3D images, the inquiry focuses on obtaining images from the mobile app and projecting them onto the holographic display. The human hologram and building structure are the two areas covered in this study. In effect, this article essentially assists construction businesses with building structures, and educational institutions employ human holograms for lecture purposes. This research also investigates how the advantages of holographic models compare to other fast-growing platforms both now and soon. © 2024 IEEE.

关键词： Holograms

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A systematic review of machine learning and deep learning techniques for anomaly detection in data mining

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International Journal of Computers and Applications 2025年第2期47卷 169-187页

作者： Tahir, Mahjabeen Abdullah, Azizol Izura Udzir, Nur Azhar Kasmiran, Khairul Serdang Malaysia Serdang Malaysia Department of Computer Engineering Sir Syed University of Engineering & Technology Karachi Pakistan

The growing use of the internet has increased the threat of cyberattacks. Anomaly detection systems are vital for protecting networks by spotting irregular activities. Various studies investigated anomaly detection techniques without a systematic approach. So far, the existing reviews mainly concerned time series and data streaming methods almost neglected the growing interest in graph-based data mining techniques which are vital in social networks, finance, and IoT domains. Following PRISMA guidelines, this systematic review examines anomaly detection methods applied to time series, data streaming, and graph-based data from 2018 to 2023. A total of 34 papers were selected from four key databases ScienceDirect, Scopus, Web of Science, and IEEE. In addition, this review addressed several issues with existing techniques including low scalability, explainability, and interpretability for real-time anomaly detection systems. In modern applications where data structures are complex, and processing requirements are high these traditional techniques are insufficient for real-time data processing. Finally, our study demanded more advanced, complex methods to address these evolving challenges. © 2025 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Data streams

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The Impact of Fog computing in the IoT World 6

The Impact of Fog computing in the IoT World

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6th Global Conference on Wireless and Optical Technologies, GCWOT 2023

作者： Sohail, Fizzah Haider, Hira Ismat, Najma Sir Syed University of Engineering & Technology Software Engineering Department Karachi Pakistan

ISBN: (纸本)9798350333718

The rise in Internet of Things (IoT) devices with inadequate resources resulted in the emergence of the fog-computing, an extension of the cloud computing paradigm. In cloud computing, the network edge contains all fog cells that cause a reduction in the latency. It enables the implementation of IoT applications on the resources of computational Fog. IoT implementation aims to optimize the need for quality service (QoS) while maximizing fog resource utilization. Fog computing also enables a new generation of services and applications by extending the Cloud Computing paradigm to the network edge. Fog is defined with the help of the characteristics such as Mobility, location awareness and low latency, a significant number of nodes, major wireless access role, extensive geographical, prevalent real-Time applications, and streaming. In this study, comprehensive taxonomy is proposed, a comparison between cloud and fog computing has been highlighted, the key features of Fog Computing, also Fog-based applications is presented in detail. Moreover, it is argued that Fog is a suitable platform for various IoT applications. These characteristics include Actuators Networks, Wireless sensors, smart cities, smart Grid, and connected vehicles. At last, the paper elaborates the potential trends of Fog Computing. © 2023 IEEE.

关键词： Fog computing

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Optimizing Underwater Acoustic Sensor Networks: Insights from Energy-Efficient, Reliable, and Void Issue-Based Routing Protocols 7

Optimizing Underwater Acoustic Sensor Networks: Insights fro...

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7th Edition Global Conference on Wireless and Optical Technologies, GCWOT 2024

作者： Khan, Muhammad Umar Aamir, Muhammad Haider, Waleej Sir Syed University of Engineering and Technology Department of Telecommunication Engineering Pakistan Sir Syed University of Engineering and Technology Department of Computer Science and Information Technology Pakistan

ISBN: (纸本)9798331534271

The Underwater Acoustic Sensor Network (UASN) is based on the sensory elements that detect the environmental conditions of submerged regions and transmit the information through acoustic waves at the sink node placed on top of the water. All these sensory elements are battery-operated just like the Terrestrial Wireless Sensor Network (TWSN). However, these nodes are not stationary, unlike the nodes in TWSN. Thus, routing with limited energy and ever-changing topology decreases the reliability of the network and increases the chances of Void existence. This research paper focuses on the comparative analysis by critically reviewing some of the state-of-the-art routing protocols which are based on the effective usability of the limited energy resource, reliability of the network, and Void occurrence issues. An analytical method is employed to examine the strengths and shortcomings of existing routing protocols, with a specific emphasis on the identified difficulties. It provides a solid foundation related to UASN routing protocols which are primarily designed with a focus on resolving issues such as limited energy, low reliability, and high chances of void occurrence. The contribution of this comparative study helps the research partners from the academy and industry which are new to this field of study and would like to contribute. © 2024 IEEE.

关键词： Sensor nodes

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Expression Detection of Autistic Children Using CNN Algorithm 6

Expression Detection of Autistic Children Using CNN Algorith...

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6th Global Conference on Wireless and Optical Technologies, GCWOT 2023

作者： syed, Abeer Javed Durrani, Deenar Jawaid Shahid, Neha Khan, Wajahat Muhammad, Ali Sir Syed University of Engineering & Technology Software Engineering Department Karachi Pakistan

ISBN: (纸本)9798350333718

Facial emotion detection is a technique for identifying human emotions from facial expressions. Autism Spectrum Disorder is an advanced neurobehavioral disorder, autism is a vast field with many problems, including hyperactivity, sensory, speech, etc. Children with autism who have behavioral problems are the focus of this research. This research is on an automatic detection system that will detect the expressions of autistic children and generate a report explaining their behaviors during their therapy sessions. This automatic system is primarily focusing on three main behavioral issues: happy, neutral, and irritated. This research is done to provide facilities to the parents, therapists, and Autistic Rehabilitation Centers to keep records of their children's and patients' progress in the form of reports. This is carried out using machine learning and image processing methods. The autistic children's faces are used to extract the features using local binary patterns. The proposed system uses CNN, Haar Cascade object detection Algorithm, and TensorFlow. The classification of emotions and face detection is done using the CNN algorithm and Haar Cascade object detection algorithm. Helping Hands Rehabilitation Center, a Pakistan-based autism rehabilitation center has provided its utmost assistance to make this research possible. © 2023 IEEE.

关键词： Patient rehabilitation

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Cache Algorithms for software Defined Network Efficiency: An Analytical Approach 7

Cache Algorithms for Software Defined Network Efficiency: An...

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7th Edition Global Conference on Wireless and Optical Technologies, GCWOT 2024

作者： Haider, Warda Zardari, Shehnila Memon, Shiza Riaz Aamir, Muhammad Ned University of Engineering & Technology Department of Software Engineering Karachi Pakistan Sir Syed University of Engineering & Technology Department of Telecommunication Engineering Karachi Pakistan

ISBN: (纸本)9798331534271

In today's networking environments caching algorithms plays a very important role to get the best use of resources and maximizing performance of networks. In this paper, we conduct a comparative analysis of the three caching algorithms: Dependent set, Cover set and Mixed set. Every algorithm is intended to solve one problem of rule dependency management and cache optimization in the network switches. Each has its strengths and trade-offs, and a detailed comparison across dozens of dimensions, throughput, adaptability, memory usage, cache-hit rate, execution time, resource efficiency, scalability (both operational- and system-level), flexibility in supporting different workloads, robustness to system behavior changes independent of user behavior (like the slow generation asymptote), and operational stability just to name a few popular ones, are relevant for many high-scale web services products. There are many other dependencies in the region, so pay a lot of memory which is not acceptable for the very first versions. The Dependent Set algorithm is designed to be an optimized memory, easy to adapt and resource-efficient rule dependency manager. This further enforces the emphasis on rule coverage policies of the Cover Set algorithm, improving cache performance and scalability. The Mixed Set algorithm combines the strengths of both methods providing a rounded approach, with throughput, adaptability and resource allocation. The study examines the benefits of each algorithm in real-world situations. It shows how they improve network efficiency and adaptability. This research expands our understanding of caching algorithms. It explains how they optimize networks. This paves the way for better network management and performance. By comparing these algorithms, the paper provides useful information. It helps network administrators and researchers enhance caching mechanisms in networks. © 2024 IEEE.

关键词： Caching Cover Set Dependent Set Mixed Set Rules software Defined Networking

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Enhancing Contextualized GNNs for Multimodal Emotion Recognition: Improving Accuracy and Robustness 7

Enhancing Contextualized GNNs for Multimodal Emotion Recogni...

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7th International Multi-Topic ICT Conference: IMTIC 2023

作者： Shahbaz, Muhammad Huzaifa Zain-Ul-Abidin Mahboob, Khalid Ali, Fayyaz Sir Syed University of Engineering & Technology Software Engineering Department Karachi Pakistan

ISBN: (纸本)9798350338461

Emotion recognition from facial expressions is an important research area in the field of artificial intelligence. In this study, a novel deep-learning model is proposed for emotion recognition from facial expressions. The model uses a combination of modifications in COGMEN (Contextualized GNN-based Multimodal Emotion Recognition) to extract features from facial images and other modalities and capture temporal dependencies between frames. The model was evaluated on the IEMOCAP dataset, achieving an accuracy of 87.8%, outperforming (mostly) existing state-of-the-art methods. Furthermore, the model has a lower computational complexity compared to other methods, making it more practical for real-time applications. A high F1 score was reported for each emotion category, indicating good performance across all classes. The results demonstrate the potential method for improving emotion recognition from multiple modalities (i.e.: Audio, Visual & Text) and have implications for a wide range of applications such as affective computing, human-computer interaction, and mental health monitoring. © 2023 IEEE.

关键词： Emotion Recognition

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