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Keyword: IAA Survey of Text Mining in Social Media: Facebook and Twitter Perspectives
Text mining has become one of the trendy fields that has been incorporated in several research fields such as computational linguistics, Information Retrieval (IR) and data mining. Natural Language Processing (NLP) techniques were used to extract knowledge from the textual text that is written by human beings. Text mining reads an unstructured form of data…
Read MoreCross layers security approach via an implementation of data privacy and by authentication mechanism for mobile WSNs
To implement a new secure network with high mobility and low energy consumption, we use smart sensors. These sensors are powered by micro batteries generally non rechargeable. So, to extend their lifetime, it is necessary to implement new energy conservation techniques. Existing works separate the two features (security, energy conservation) and are interested specifically in…
Read MoreThe Class Imbalance Problem in the Machine Learning Based Detection of Vandalism in Wikipedia across Languages
This paper analyses the impact of current trend in applying machine learning in detection of vandalism, with the specific aim of analyzing the impact of the class imbalance in Wikipedia articles. The class imbalance problem has the effect that almost all the examples are labelled as one class (legitimate editing); while far fewer examples are…
Read MoreStudents’ Perception of Library Services in Academia: A Case Study of Universiti Teknologi Brunei
This paper is an outcome of a case study conducted at the Universiti Teknologi Brunei in order to measure students’ perceptions of the library services offered in the university library. The main objectives were to identify the purpose of the library visit and to find out the service quality of university library, to determine whether…
Read MoreAn Application of ANN Model with Bayesian Regularization Learning Algorithm for Computing the Operating Frequency of C-Shaped Patch Antennas
In this paper, an application of artificial neural network (ANN) using bayesian regularization (BR) learning algorithm based on multilayer perceptron (MLP) model is presented for computing the operating frequency of C-shaped patch antennas (CPAs) in UHF band. Firstly, the operating frequencies of 144 CPAs having varied dimensions and electrical parameters were simulated by the XFDTD…
Read MoreSolar Irradiance & On Grid Solar Power Systems with Net Metering in Pakistan
This paper presents a case study of solar irradiance and scope of on-grid solar power systems with net-metering in Pakistan. Detailed analysis of solar irradiance in Pakistan is being carried out by developing the dedicated solar excel sheets. The need of on grid solar power systems for the present energy crisis in developing countries like…
Read MoreEffect of Foliar Application of Zinc on Growth and Yield of Guava (Psidium Guajava L.)
In depth study focusing to ascertain the effect of different rates of Zinc (Zn) fertilization in improving the quality and yield of Guava fruit was carried out at Gharo, Sindh – Pakistan during year 2014-15. The outcome of the research revealed that there was no significant effect on the yield as well as quality, without…
Read MoreCoal Seam Methane Abatement and Utilization Techniques with Availability and Feasibility Criteria
Methane found in coal seams is about 17% of total methane emissions by human activities and 8% of world’s greenhouse gases emissions. Mine methane can be generated through different streams of coal mines like degasification of underground coal mines, ventilation of air in coal seams, post mining processes and surface mining. Methane from ventilation air…
Read MoreDevelopment of a Learning System for Robot Modular Manipulators
This paper presents a modular robot learning system for robotics education, comprising a reconfigurable physical manipulator and an automatically configuring 3D simulation framework. Unlike prior modular manipulator systems that require manual software re-parameterization after hardware reconfiguration, the proposed system detects the assembled topology in real time through Dynamixel motor ID sequencing and renders a synchronized…
Read MorePayload and Watermarking Trade-Offs in Online Handwriting: A Structured Comparative Study
Online handwriting is a dynamic signal that can support digital watermarking, but existing studies have mainly evaluated individual embedding methods, leaving limited structured evidence on the joint relationship between payload, distortion, robustness, and host-signal characteristics. This paper addresses this gap through a comparative framework that combines cross-dataset host-signal characterization with a controlled evaluation of representative…
Read MoreMany-objective Placement Optimization in Virtual Network Functions
Network Functions Virtualization (NFV) poses the VNF placement problem under multiple, potentially conflicting objectives, such as Quality of Service (QoS), costs, and resource efficiency. This work treats VNF placement as a many-objective optimization problem (MaOP) and presents two primary contributions: (i) a correlation analysis of state-of-the-art objectives to reduce dimensionality while maintaining representativeness, resulting in…
Read MoreThe Impact of Antenna Design on Breast Microwave Imaging
Breast microwave sensing (BMS) systems offer a low-cost and efficient alternative to current breast cancer screening methods. However, reported performance varies widely due to differences in system configuration, antenna design, measurement protocols, and image reconstruction techniques. This study evaluates the impact of antenna design on key image quality metrics using a controlled experimental platform. Spatial…
Read MoreTL-SOC: A Hybrid Decision-Centric Intrusion Detection Framework for Security Operations Centers
Security Operations Centers (SOCs) require intrusion detection systems that achieve high detection accuracy while maintaining a low false-positive rate and robustness to evolving attack patterns. However, most existing machine learning-based approaches primarily focus on detecting known threats and often overlook distribution shifts and the reliability of generated alerts. In this paper, we propose TL-SOC, a…
Read MoreAn Ensemble Learning Approach for Student Performance Analysis of a Higher Educational Institute using a SHAP-Based Feature Selection and Optuna Optimization
Forecasting and assessing student performance are crucial for allowing educators to pinpoint deficiencies and promote grade improvement. A thorough comprehension of feature contributions is crucial for improving model interpretability and facilitating informed decision-making in academic institutions. Explainable artificial intelligence encompasses methodologies and strategies designed to deliver transparent and accessible rationales for the decisions rendered by…
Read MoreGC4miRNA - a Pipeline for Examining Impact of GC Content in miRNA Seed Sequences on Expression in Tumor Samples
MicroRNAs (miRNAs) are small RNA molecules that play a crucial role in regulating gene expression by binding to and degrading targeted mRNAs. miRNAs targeting a specific mRNA have a region known as the “seed sequence”, which typically has a high affinity for its complementary sequence in the targeted mRNA. Single Nucleotide Polymorphisms (SNPs) are mutations…
Read MoreInvestigating the Influence Biomass Additive on the Thermal Performance of a Fired-Clay for Producing the Inner Liner of a Biomass Cook-Stove
This study investigated the influence of a biomass additive on the thermal performance of the inner liner of fired-clay cook-stoves. Fired-clay cook-stoves are essential cooking devices, particularly in areas with limited access to modern energy resources. The study aimed to enhance the thermal efficiency of the cook-stoves by incorporating rice husk into the inner liner…
Read MoreMulti Attribute Stratified Sampling: An Automated Framework for Privacy-Preserving Healthcare Data Publishing with Multiple Sensitive Attributes
The accumulation and analysis of large-scale patient data have led to breakthrough discoveries in potential flags for diseases based on pattern recognition, highlight medication efficacy, and local population health trends that would be impossible with traditional paper-based records. However, these benefits come with unique challenges posed by the application of data sharing for research and…
Read MoreEfficient Pattern Recognition Resource Utilization Neural Network
Neural Networks derives intelligent systems and modern autonomous applications. With the complexity introduced in today’s systems, designing architectures remains open research problem in all fields. Despite many efforts to generalize, the resources required by neural architectures remain challenge. Robots design, Smart cities, IoTs …etc. become the leading industry and driving the fourth industrial revolutions. All…
Read MoreBeyond Fitness: Revolutionary Exercise Tracker Combining Pose Recognition with Heart Rate Monitoring using Remote Photoplethysmography (rPPG)
Heart rate (HR) is a critical indicator in fitness monitoring, athletic performance evaluation, and injury prevention. However, traditional motion-sensitive wearable devices are highly susceptible to movement artifacts, which degrade measurement accuracy during physical activity. Remote photoplethysmography (rPPG) offers a non-contact alternative for HR measurement, though it too remains sensitive to motion. This study proposes a…
Read MoreDetection Method and Mitigation of Server-Spoofing Attacks on SOME/IP at the Service Discovery Phase
Service-oriented architecture has attracted attention in automotive development. The Automotive Open System Architecture (AUTOSAR) specifies Scalable Service-Oriented Middleware over IP (SOME/IP) as a key middleware for service-oriented communication in-vehicles. However, SOME/IP-based networks are vulnerable to server spoofing during the service discovery phase, enabling attackers to cause man-in-the-middle attacks by impersonating legitimate services. This paper proposes…
Read MoreComputationally Efficient Explainable AI Framework for Skin Cancer Detection
Skin cancer stands among some of the fastest growing and fatal malignancies of the world as a result early and accurate diagnosis of skin cancer is essential in order to enhance patient survival and treatment prognosis. Conventional methods of diagnosis including dermoscopy and histopathological examinations are expensive and time consuming also subject to inter-observer error.…
Read MoreDesign and Electronic Interfacing of FR4 and Polyimide PCB-based Electromagnetic Resonating Micro-mirrors
This paper presents the design and fabrication of an electromagnetically actuated PCB-based resonating scanning micro-mirror for LiDAR applications, with optimization targeted towards low-cost fabrication and a high scanning angle. Traditional silicon MEMS-based micro-mirrors, while offering high precision and compatibility with CMOS processing, are limited by fragility at low scanning frequencies and costly fabrication processes. To…
Read MoreA Multi-class Acoustic Dataset and Interactive Tool for Analyzing Drone Signatures in Real-World Environments
The rapid proliferation of drones across various industries has introduced significant challenges related to privacy, security, and noise pollution. Current drone detection systems, primarily based on visual and radar technologies, face limitations under certain conditions, highlighting the need for effective acoustic-based detection methods. This paper presents a unique and comprehensive dataset of drone acoustic signatures,…
Read MorePerfVis+: From Timestamps to Insight through Integration of Visual and Statistical Analysis
Complex networked systems provide a cornucopia of network statistics, many of which relate to the temporal behaviour of subsystems, devices, or even individual protocol layers. Different and flexible visualizations can play a crucial role in discovering and making patterns, relations, and trends tangible. We developed PerfVis, a tool that visualizes timestamp data to aid in…
Read MoreIdentifying Comprehension Faults Through Word Embedding and Multimodal Analysis
This study establishes a method for determining whether learners have an understanding of data science. Data science requires knowledge in various fields, which makes many learners give up. To prevent learners from being discouraged, it is necessary to judge the comprehension of the principles in each specified skill. It is important to assess not only…
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