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Muhammad Shoaib

Publications and source records attributed to Muhammad Shoaib.

At least 19 recordsLinked to original sources
arXiv2026

Estimating Staged Event Tree Models via Hierarchical Clustering on the Simplex

Staged tree models enhance Bayesian networks by incorporating context-specific dependencies through a stage-based structure. In this study, we present a new framework for estimating staged trees using hierarchical clustering on the probability simplex, utilizing simplex basesd divergences. We conduct a thorough evaluation of several distance and divergence metrics including Total Variation, Hellinger, Fisher, and Kaniadakis; alongside various linkage methods such as Ward.D2, average, complete, and McQuitty. We conducted the simulation experiments that reveals Total Variation, especially when combined with Ward.D2 linkage, consistently produces staged trees with better model fit, structure recovery, and computational efficiency. We assess performance by utilizing relative Bayesian Information Criterion (BIC), and Hamming distance. Our findings indicate that although Backward Hill Climbing (BHC) delivers competitive outcomes, it incurs a significantly higher computational cost. On the other, Total Variation divergence with Ward.D2 linkage, achieves similar performance while providing significantly better computational efficiency, making it a more viable option for large-scale or time sensitive tasks.

stat.ML↗
arXiv2026

Comparison of Maximum Likelihood Classification Before and After Applying Weierstrass Transform

The aim of this paper is to use Maximum Likelihood (ML) Classification on multispectral data by means of qualitative and quantitative approaches. Maximum Likelihood is a supervised classification algorithm which is based on the Classical Bayes theorem. It makes use of a discriminant function to assign pixel to the class with the highest likelihood. Class means vector and covariance matrix are the key inputs to the function and can be estimated from training pixels of a particular class. As Maximum Likelihood need some assumptions before it has to be applied on the data. In this paper we will compare the results of Maximum Likelihood Classification (ML) before apply the Weierstrass Transform and apply Weierstrass Transform and will see the difference between the accuracy on training pixels of high resolution Quickbird satellite image. Principle Component analysis (PCA) is also used for dimension reduction and also used to check the variation in bands. The results shows that the separation between mean of the classes in the decision space is to be the main factor that leads to the high classification accuracy of Maximum Likelihood (ML) after using Weierstrass Transform than without using it.

stat.AP↗
arXiv2025

Rethinking Tamper-Evident Logging: A High-Performance, Co-Designed Auditing System

Existing tamper-evident logging systems suffer from high overhead and severe data loss in high-load settings, yet only provide coarse-grained tamper detection. Moreover, installing such systems requires recompiling kernel code. To address these challenges, we present Nitro, a high-performance, tamper-evident audit logging system that supports fine-grained detection of log tampering. Even better, our system avoids kernel recompilation by using the eBPF technology. To formally justify the security of Nitro, we provide a new definitional framework for logging systems, and give a practical cryptographic construction meeting this new goal. Unlike prior work that focus only on the cryptographic processing, we codesign the cryptographic part with the pre- and post-processing of the logs to exploit all system-level optimizations. Our evaluations demonstrate Nitro's superior performance, achieving 10X-25X improvements in high-stress conditions and 2X-10X in real-world scenarios while maintaining near-zero data loss. We also provide an advanced variant, Nitro-R that introduces in-kernel log reduction techniques to reduce runtime overhead even further.

cs.CR↗
arXiv2024

Unification of Balti and trans-border sister dialects in the essence of LLMs and AI Technology

The language called Balti belongs to the Sino-Tibetan, specifically the Tibeto-Burman language family. It is understood with variations, across populations in India, China, Pakistan, Nepal, Tibet, Burma, and Bhutan, influenced by local cultures and producing various dialects. Considering the diverse cultural, socio-political, religious, and geographical impacts, it is important to step forward unifying the dialects, the basis of common root, lexica, and phonological perspectives, is vital. In the era of globalization and the increasingly frequent developments in AI technology, understanding the diversity and the efforts of dialect unification is important to understanding commonalities and shortening the gaps impacted by unavoidable circumstances. This article analyzes and examines how artificial intelligence AI in the essence of Large Language Models LLMs, can assist in analyzing, documenting, and standardizing the endangered Balti Language, based on the efforts made in different dialects so far.

cs.CL↗
arXiv2024

Accurate and Scalable Detection and Investigation of Cyber Persistence Threats

In Advanced Persistent Threat (APT) attacks, achieving stealthy persistence within target systems is often crucial for an attacker's success. This persistence allows adversaries to maintain prolonged access, often evading detection mechanisms. Recognizing its pivotal role in the APT lifecycle, this paper introduces Cyber Persistence Detector (CPD), a novel system dedicated to detecting cyber persistence through provenance analytics. CPD is founded on the insight that persistent operations typically manifest in two phases: the "persistence setup" and the subsequent "persistence execution". By causally relating these phases, we enhance our ability to detect persistent threats. First, CPD discerns setups signaling an impending persistent threat and then traces processes linked to remote connections to identify persistence execution activities. A key feature of our system is the introduction of pseudo-dependency edges (pseudo-edges), which effectively connect these disjoint phases using data provenance analysis, and expert-guided edges, which enable faster tracing and reduced log size. These edges empower us to detect persistence threats accurately and efficiently. Moreover, we propose a novel alert triage algorithm that further reduces false positives associated with persistence threats. Evaluations conducted on well-known datasets demonstrate that our system reduces the average false positive rate by 93% compared to state-of-the-art methods.

cs.CR↗
arXiv2024

Probing Heavy Charged Higgs Boson Using Multivariate Technique at Gamma-Gamma Collider

The current study explores the production of charged Higgs particles through photon-photon collisions within the Two Higgs Doublet Model context, including one-loop-level scattering amplitude of Electroweak and QED radiation. The cross-section has been scanned for plane ($m_{\phi^{0}}, \sqrt{s}$) investigating the process of $\gamma\gamma \rightarrow H^{+}H^{-}$. Three particular numerical scenarios low-$m_{H}$, non-alignment, and short-cascade are employed. Hence using $h^{0}$ for low-$m_{H^{0}}$ and $H^{0}$ for non-alignment and short-cascade scenario, the new experimental and theoretical constraints are applied.The decay channels for charged Higgs particles are examined in all the scenarios along with the analysis for cross-sections revealing that at low energy it is consistently higher for all scenarios. However as $\sqrt{s}$ increases, it reaches a peak value at 1$~$TeV for all benchmark scenarios. The branching ratio of the decay channels indicates that for non-alignment, the mode of decay $W^{\pm} h^{0}$ takes control %{} when $BR(H^{\pm} \rightarrow W^{\pm} H^{0})$ decreases at larger values of $m_{H^{0}}$.} and for short cascade the prominent decay mode remains $t\bar{b}$, while in the low-$m_{H}$ the dominant decay channel is of $W^{\pm} h^{0}$. In our research, we employ contemporary machine-learning methodologies to investigate the production of high-energy Higgs Bosons within a 3$ $TeV Gamma-Gamma collider. We have used multivariate approaches such as Boosted Decision Trees (BDT), LikelihoodD, and Multilayer Perceptron (MLP) to show the observability of heavy-charged Higgs Bosons versus the most significant Standard Model backgrounds. The purity of the signal efficiency and background rejection are measured for each cut value.

hep-ph↗
arXiv2023

Sequence-Based Nanobody-Antigen Binding Prediction

Nanobodies (Nb) are monomeric heavy-chain fragments derived from heavy-chain only antibodies naturally found in Camelids and Sharks. Their considerably small size (~3-4 nm; 13 kDa) and favorable biophysical properties make them attractive targets for recombinant production. Furthermore, their unique ability to bind selectively to specific antigens, such as toxins, chemicals, bacteria, and viruses, makes them powerful tools in cell biology, structural biology, medical diagnostics, and future therapeutic agents in treating cancer and other serious illnesses. However, a critical challenge in nanobodies production is the unavailability of nanobodies for a majority of antigens. Although some computational methods have been proposed to screen potential nanobodies for given target antigens, their practical application is highly restricted due to their reliance on 3D structures. Moreover, predicting nanobodyantigen interactions (binding) is a time-consuming and labor-intensive task. This study aims to develop a machine-learning method to predict Nanobody-Antigen binding solely based on the sequence data. We curated a comprehensive dataset of Nanobody-Antigen binding and nonbinding data and devised an embedding method based on gapped k-mers to predict binding based only on sequences of nanobody and antigen. Our approach achieves up to 90% accuracy in binding prediction and is significantly more efficient compared to the widely-used computational docking technique.

q-bio.BM↗
arXiv2021

Cable Driven Rehabilitation Robots: Comparison of Applications and Control Strategies

Significant attention has been paid to robotic rehabilitation using various types of actuator and power transmission. Amongst those, cable-driven rehabilitation robots (CDRRs) are relatively newer and their control strategies have been evolving in recent years. CDRRs offer several promising features, such as low inertia, lightweight, high payload-to-weight ratio, large work-space and configurability. In this paper, we categorize and review the cable-driven rehabilitation robots in three main groups concerning their applications for upper limb, lower limb, and waist rehabilitation. For each group, target movements are identified, and promising designs of CDRRs are analyzed in terms of types of actuators, controllers and their interactions with humans. Particular attention has been given to robots with verified clinical performance in actual rehabilitation settings. A large part of this paper is dedicated to comparing the control strategies and techniques of CDRRs under five main categories of: Impedance-based, PID-based, Admittance-based, Assist-as-needed (AAN) and Adaptive controllers. We have carefully contrasted the advantages and disadvantages of those methods with the aim of assisting the design of future CDRRs

cs.RO↗
arXiv2021

An Efficient Indexing and Searching Technique for Information Retrieval for Urdu Language

Indexing techniques are used to improve retrieval of data in response to certain search condition. Inverted files are mostly used for creating indexes. This paper proposes indexing technique for Urdu language. Language processing step in Index creation is different for a particular language. We discuss index creation steps specifically for Urdu language. We explore morphological rules for Urdu language and implement these rules to create Urdu stemmer. We implement our proposed technique with different implementations and compare results. We suggest that indexes should be created without stop words and also index file should be an order index file.

cs.IR↗
arXiv2020

Author Name Disambiguation in Bibliographic Databases: A Survey

Entity resolution is a challenging and hot research area in the field of Information Systems since last decade. Author Name Disambiguation (AND) in Bibliographic Databases (BD) like DBLP , Citeseer , and Scopus is a specialized field of entity resolution. Given many citations of underlying authors, the AND task is to find which citations belong to the same author. In this survey, we start with three basic AND problems, followed by need for solution and challenges. A generic, five-step framework is provided for handling AND issues. These steps are; (1) Preparation of dataset (2) Selection of publication attributes (3) Selection of similarity metrics (4) Selection of models and (5) Clustering Performance evaluation. Categorization and elaboration of similarity metrics and methods are also provided. Finally, future directions and recommendations are given for this dynamic area of research.

cs.SI↗
arXiv2015

Some New Generalized Results on Ostrowski Type Integral Inequalities With Application

The aim of this paper is to establish some new inequalities similar to the Ostrowski's inequalities which are more generalized than the inequalities of Dragomir and Cerone. The current article obtains bounds for the deviation of a function from a combination of integral means over the end intervals covering the entire interval. Some new purterbed results are obtained. Application for cumulative distribution function is also discussed.

math.CA↗
arXiv2015

A generalization of Ostrowski type inequality for mappings whose second derivatives belong to L$_{1}\left(a,b\right) $ and applications

In this paper, we will improve and generalize inequality of Ostrowski type for mappings whose second derivatives belong to L$_{1}\left(a,b\right) $ . Some well known inequalities can be derived as special cases. In addition, perturbed mid-point inequality and perturbed trapezoid inequality are also obtained. The obtained inequalities have immediate applications in numerical integration where new estimates are obtained for the remainder term of the trapezoid and midpoint formula. Applications to some special means are also investigated.

math.CA↗
arXiv2015

Central Configurations in the Trapezoidal Four-Body Problems

In this paper we discuss the central configurations of the Trapezoidal four-body Problem. We consider four point masses on the vertices of an isosceles trapezoid with two equal masses $m_1=m_4$ at positions $(\mp 0.5, r_B)$ and $m_2=m_3$ at positions $(\mp \alpha/2, r_A)$. We derive, both analytically and numerically, regions of central configurations in the phase space where it is possible to choose positive masses. It is also shown that in the compliment of these regions no central configurations are possible.

math.DS↗
arXiv2014

Attitude dynamics and control of spacecraft using geomagnetic Lorentz force

The attitude stabilization of a charged rigid spacecraft in Low Earth Orbit (LEO) using torques due to Lorentz force in pitch and roll directions is considered. A spacecraft that generates an electrostatic charge on its surface in the Earth magnetic field will be subject to perturbations from Lorentz force. The Lorentz force acting on an electrostatically charged spacecraft may provide a useful thrust for controlling a spacecraft's orientation. We assume that the spacecraft is moving in the Earth's magnetic field in an elliptical orbit under the effects of the gravitational, geomagnetic and Lorentz torques. The magnetic field of the Earth is modeled as a non-tilted dipole. A model incorporating all Lorentz torques as a function of orbital elements has been developed on the basis of electric and magnetic fields. The stability of the spacecraft orientation is investigated both analytically and numerically. The existence and stability of equilibrium positions is investigated for different values of the charge to mass ratio ($\alpha^*$). Stable orbits are identified for various values of $\alpha^*$. The main parameters for stabilization of the spacecraft are $\alpha^*$ and the difference between the components of the moment of inertia of spacecraft.

astro-ph.IM↗
arXiv2014

Equilibria of a charged artificial satellite subject to gravitational and Lorentz torques

Attitude Dynamics of a rigid artificial satellite subject to gravity gradient and Lorentz torques in a circular orbit is considered. Lorentz torque is developed on the basis of the electrodynamic effects of the Lorentz force acting on the charged satellite's surface. We assume that the satellite is moving in Low Earth Orbit (LEO) in the geomagnetic field which is considered as a dipole model. Our model of the torque due to the Lorentz force is developed for a general shape of artificial satellite, and the nonlinear differential equations of Euler are used to describe its attitude orientation. All equilibrium positions are determined and {their} existence conditions are obtained. The numerical results show that the charge $q$ and radius $\rho_0$ of the charged center of satellite provide a certain type of semi passive control for the attitude of satellite. The technique for such kind of control would be to increase or decrease the electrostatic radiation screening of the satellite. The results {obtained} confirm that the change in charge can effect the magnitude of the Lorentz torque, which may affect the satellite's control. Moreover, the relation between the magnitude of the Lorentz torque and inclination of the orbits is investigated.

physics.space-ph↗
arXiv2014

A Weighted Ostrowski Type inequality for L$_{1}\left[ a,b\right] $ and applications

The aim of this paper is to obtain some generalized weighted Ostrowski inequalities for differentiable mappings. Some well known inequalities can be derived as special cases of the inequalities obtained here. In addition, perturbed mid-point inequality and perturbed trapezoid inequality are also obtained. The inequalities obtained here have direct applications in Numerical Integration, Probability Theory, Information Theory and Integral Operator Theory. Some of these applications are discussed.

math.CA↗
arXiv2014

Weighted Ostrowski Type inequality Involving Integral Means

The ostrowski inequality expresses bounds on the deviation of a function from its integral mean. The aim of this paper is to establish a new inequality using weight function which generalizes the inequalities of Dragomir, Wang and Cerone .The current article obtains bounds for the deviation of a function from a combination of integral means over the end intervals covering the entire interval. A variety of earlier results are recaptured as particular instances of the current development. Applications for cumulative distribution function are also discussed.

math.CA↗