arXiv subjects

Arshad Ali

Publications and source records attributed to Arshad Ali.

At least 19 recordsLinked to original sources

arXiv2026

A Hybrid Usability Approach for Rating Evaluation of M-Commerce Applications

The success of any mobile application relies on its usefulness and rating is considered as an important measure in this regard. This research work focuses on identifying usability factors, which contribute significantly towards the rating of M-commerce apps. This work intends to explore existing usability models consisting of different factors along with a set of criteria and evaluate in terms of rating estimation by considering 5 well-known mobile applications, namely (i) daraz, (ii) shophive, (iii) home shopping, (iv) Symbios. (v) yayvo. Then, this work provides a hybrid usability model for rating prediction of M-commerce applications. The initial hybrid usability model comprises of (i) learnability, (ii) consistency, (iii) human factors,(iv)communicativeness,(v)effectiveness, (vi) Operability, (vii) efficiency, (viii) satisfaction. Each factor consists of some criteria. Keeping in view the factors of hybrid usability model, the data was collected from 40 users for each application. Furthermore, Forward Stepwise Multiple Linear Regression based rating prediction model is suggested by analyzing each criterion of all factors of hybrid usability model. Finally, the model is assessed and validated by using PRED(x) and K-fold techniques.

cs.SE↗

arXiv2025

Gauge dependence of scalar-induced gravitational waves from isocurvature perturbations: Analytical results

We analytically study the gauge dependence of scalar-induced gravitational waves (SIGWs) sourced by primordial isocurvature perturbations during radiation domination (RD), working across nine gauges. Through analytical integrations of the kernels supported by graphical comparison we identify a clear dichotomy. We find that in some gauges viz. the uniform-density (UD), total-matter (TM), uniform-curvature (UC), comoving-orthogonal (CO) and transverse-traceless (TT) gauges the energy density grows polynomially in conformal time $\eta^n$, where $n$ varies from $2$ to $8$. While in rest of the gauges viz. the longitudinal (Long.), uniform-expansion (UE), Newtonian-motion (Nm), and N-body (Nb) gauges the late-time energy spectrum converges, and SIGWs behave as radiation. For subhorizon modes ($ k\eta \gg 1 $), the divergence becomes severe, showing that SIGWs are gauge-dependent observables in this regime. We resolve it through a kernel projection that isolates the luminal, freely propagating gravitational wave components (oscillating as $\sin(k\eta)$ and $\cos(k\eta)$), eliminating spurious contributions. The resulting kernel decays as $ (k\eta)^{-1} $ and yields a finite, gauge-independent late-time spectrum, confirming that only luminal modes represent physical SIGWs.

gr-qc↗

arXiv2024

Different effects of the Lorentz and Gaussian bump functions on the formation of primordial black holes and secondary gravitational waves

Scalar perturbations in the inflation can be amplified when the base inflation potential $V_b(\phi)$ incorporates a local bump $f(\phi)$ such as $V(\phi)=V_b(\phi)(1+f(\phi))$. This modification will lead to a peak in the curvature power spectrum, increasing a significant abundance of primordial black holes (PBHs). However, since there is no underlying physical reason for the choice of $f(\phi)$, it is essential to investigate the effects of various bump functions on PBH generation. In this paper, we choose the well-known Starobinsky potential as the base inflation potential to compare the effects produced by different bumps, specifically focusing on the Lorentz and Gaussian bumps which are widely used. To clearly illustrate the differences between these two bumps, we keep parameters in bump functions the same. We find an interesting and novel result that the Lorentz cases manifest a stronger ability to enhance the power spectrum and produce more abundance of PBHs than Gaussian cases. Moreover, we also investigate the different effects of bump functions on the scalar-induced gravitational waves (SIGWs). The results indicate that the Lorentz bump generates SIGWs with a higher energy density, which can be potentially detected in the future. Our study gives valuable insights into the choice and constraints on the bump functions, and the different effects may distinguish the two bump cases for practical purposes in future experiments.

astro-ph.CO↗

arXiv2023

On the gauge dependence of scalar induced secondary gravitational waves during radiation and matter domination eras

We revisit the vital issue of gauge dependence in the scalar-induced secondary gravitational waves (SIGWs), focusing on the radiation domination (RD) and matter domination (MD) eras. The energy density spectrum is the main physical observable in such induced gravitational waves. For various gauge choices, there has been a divergence in the energy density, $Ω_{\text{GW}}$, of SIGWs. We calculate SIGWs in different gauges to quantify this divergence to address the gauge-dependent problem. In our previous studies, we had found that the energy density diverges in the polynomial power of conformal time (e.g., $η^6$ in uniform density gauge). We try to fix this discrepancy by adding a counter-term that removes the fictitious terms in secondary tensor perturbations. We graphically compare the calculations in various gauges and also comment on the physical origin of the observed gauge dependence.

gr-qc↗

arXiv2022

Effective Metaheuristic Based Classifiers for Multiclass Intrusion Detection

Network security has become the biggest concern in the area of cyber security because of the exponential growth in computer networks and applications. Intrusion detection plays an important role in the security of information systems or networks devices. The purpose of an intrusion detection system (IDS) is to detect malicious activities and then generate an alarm against these activities. Having a large amount of data is one of the key problems in detecting attacks. Most of the intrusion detection systems use all features of datasets to evaluate the models and result in is, low detection rate, high computational time and uses of many computer resources. For fast attacks detection IDS needs a lightweight data. A feature selection method plays a key role to select best features to achieve maximum accuracy. This research work conduct experiments by considering on two updated attacks datasets, UNSW-NB15 and CICDDoS2019. This work suggests a wrapper based Genetic Algorithm (GA) features selection method with ensemble classifiers. GA select the best feature subsets and achieve high accuracy, detection rate (DR) and low false alarm rate (FAR) compared to existing approaches. This research focuses on multi-class classification. Implements two ensemble methods: stacking and bagging to detect different types of attacks. The results show that GA improve the accuracy significantly with stacking ensemble classifier.

cs.CR↗

arXiv2022

A Machine Learning Based Approach to Categorize Research Journals

In this modern technological era, categorization and ranking of research journals is gaining popularity among researchers and scientists. It plays a significant role for publication of their research findings in a quality journal. Although, many research works exist on journal categorization and ranking, however, there is a lack of research works to categorize and predict the journals using suitable machine learning techniques. This work aims to categorize and predict various academic research journals. This work suggests a hybrid predictive model comprising of five steps. The first step is to prepare the dataset with twenty features. The second step is to pre-process the dataset. The third step is to apply an appropriate clustering algorithm for categorization. The fourth step is to apply appropriate feature selection techniques to get an effective subset of features. The fifth step involves some ensemble plus non ensemble methods to train the model. The model is trained on a full set of features, and a selected subset of features is obtained by applying three feature selection techniques. After model training, the prediction results are evaluated in terms of precision, recall, and accuracy. The results can help the researchers and the practitioners in predicting the journal category.

cs.DL↗

arXiv2021

Gauge transformation of scalar induced tensor perturbation during matter domination

We study the scalar induced tensor perturbations at second order during matter domination in seven different gauges. Considering the obtained solution from the Newtonian gauge, we use the gauge transformation law of the scalar induced tensor perturbation to derive the solution in six other gauges. After identifying and eliminating the residual gauge modes in the synchronous and comoving orthogonal gauges, we obtain the same analytical results of the kernel function $I_χ$ for these two gauges as those obtained from the gauge transformation. For the scalar induced gravitational waves oscillating as $\sin x$ and $\cos x$, we find that $ρ_{\text{GW}}\propto a^{-4}$, and $Ω_{\text{GW}}\propto 1/a$ in the matter dominated era, so the oscillating gravitational waves behave as radiation.

gr-qc↗

arXiv2020

Gauge transformation of scalar induced gravitational waves

The gauge dependence of the scalar induced gravitational waves (SIGWs) generated at the second order imposes a challenge to the discussion of the secondary gravitational waves generated by scalar perturbations. We provide a general formula that is valid in any gauge for the calculation of SIGWs and the relationship for SIGWs calculated in various gauges under the coordinate transformation. The formula relating SIGWs in the Newtonian gauge to other gauges is used to calculate SIGWs in six different gauges. We find that the Newtonian gauge, the uniform curvature gauge, the synchronous gauge and the uniform expansion gauge yield the same result for the energy density of SIGWs. We also identify and eliminate the pure gauge modes that exist in the synchronous gauge. In the total matter gauge and the comoving orthogonal gauge, the energy density of SIGWs increases as $η^2$. While in the uniform density gauge, the energy density of SIGWs increases as $η^6$.

gr-qc↗

arXiv2020

On the waveform of the scalar induced gravitational waves

The scalar induced gravitational waves (SIGWs) is a useful tool to probe the physics in the early universe. To study inflationary models with this tool, we need to know how the waveform of SIGWs is related to the shape of the scalar power spectrum. We propose two parameterizations to approximate the scalar power spectrum with either a sharp or a broad spike at small scales, and then use these two parameterizations to study the relation between the shapes of $Ω_{GW}$ and the scalar power spectrum. We find that the waveform of SIGWs has a similar shape to the power spectrum. Away from the peak of the spike, the frequency relation $Ω_{GW}(k)\sim \mathcal{P}_ζ^2(k)$ holds independent of the functional form of the scalar power spectrum. We also give a physical explanation for this general relationship. The general relation is useful for determining the scalar power spectrum and probing inflationary physics with the waveform of SIGWs.

gr-qc↗

arXiv2018

A Taxonomy and Survey of Grid Resource Planning and Reservation Systems for Grid Enabled Analysis Environment

The concept of coupling geographically distributed resources for solving large scale problems is becoming increasingly popular forming what is popularly called grid computing. Management of resources in the Grid environment becomes complex as the resources are geographically distributed, heterogeneous in nature and owned by different individuals and organizations each having their own resource management policies and different access and cost models. There have been many projects that have designed and implemented the resource management systems with a variety of architectures and services. In this paper we have presented the general requirements that a Resource Management system should satisfy. The taxonomy has also been defined based on which survey of resource management systems in different existing Grid projects has been conducted to identify the key areas where these systems lack the desired functionality.

cs.DC↗

arXiv2007

PhantomOS: A Next Generation Grid Operating System

Grid Computing has made substantial advances in the past decade; these are primarily due to the adoption of standardized Grid middleware. However Grid computing has not yet become pervasive because of some barriers that we believe have been caused by the adoption of middleware centric approaches. These barriers include: scant support for major types of applications such as interactive applications; lack of flexible, autonomic and scalable Grid architectures; lack of plug-and-play Grid computing and, most importantly, no straightforward way to setup and administer Grids. PhantomOS is a project which aims to address many of these barriers. Its goal is the creation of a user friendly pervasive Grid computing platform that facilitates the rapid deployment and easy maintenance of Grids whilst providing support for major types of applications on Grids of almost any topology. In this paper we present the detailed system architecture and an overview of its implementation.

cs.DC↗

arXiv2007

Scheduling in Data Intensive and Network Aware (DIANA) Grid Environments

In Grids scheduling decisions are often made on the basis of jobs being either data or computation intensive: in data intensive situations jobs may be pushed to the data and in computation intensive situations data may be pulled to the jobs. This kind of scheduling, in which there is no consideration of network characteristics, can lead to performance degradation in a Grid environment and may result in large processing queues and job execution delays due to site overloads. In this paper we describe a Data Intensive and Network Aware (DIANA) meta-scheduling approach, which takes into account data, processing power and network characteristics when making scheduling decisions across multiple sites. Through a practical implementation on a Grid testbed, we demonstrate that queue and execution times of data-intensive jobs can be significantly improved when we introduce our proposed DIANA scheduler. The basic scheduling decisions are dictated by a weighting factor for each potential target location which is a calculated function of network characteristics, processing cycles and data location and size. The job scheduler provides a global ranking of the computing resources and then selects an optimal one on the basis of this overall access and execution cost. The DIANA approach considers the Grid as a combination of active network elements and takes network characteristics as a first class criterion in the scheduling decision matrix along with computation and data. The scheduler can then make informed decisions by taking into account the changing state of the network, locality and size of the data and the pool of available processing cycles.

cs.DC↗

arXiv2006

From Grid Middleware to a Grid Operating System

Grid computing has made substantial advances during the last decade. Grid middleware such as Globus has contributed greatly in making this possible. There are, however, significant barriers to the adoption of Grid computing in other fields, most notably day-to-day user computing environments. We will demonstrate in this paper that this is primarily due to the limitations of the existing Grid middleware which does not take into account the needs of everyday scientific and business users. In this paper we will formally advocate a Grid Operating System and propose an architecture to migrate Grid computing into a Grid operating system which we believe would help remove most of the technical barriers to the adoption of Grid computing and make it relevant to the day-to-day user. We believe this proposed transition to a Grid operating system will drive more pervasive Grid computing research and application development and deployment in future.

cs.DC↗

arXiv2006

Bulk Scheduling with the DIANA Scheduler

Results from the research and development of a Data Intensive and Network Aware (DIANA) scheduling engine, to be used primarily for data intensive sciences such as physics analysis, are described. In Grid analyses, tasks can involve thousands of computing, data handling, and network resources. The central problem in the scheduling of these resources is the coordinated management of computation and data at multiple locations and not just data replication or movement. However, this can prove to be a rather costly operation and efficient sing can be a challenge if compute and data resources are mapped without considering network costs. We have implemented an adaptive algorithm within the so-called DIANA Scheduler which takes into account data location and size, network performance and computation capability in order to enable efficient global scheduling. DIANA is a performance-aware and economy-guided Meta Scheduler. It iteratively allocates each job to the site that is most likely to produce the best performance as well as optimizing the global queue for any remaining jobs. Therefore it is equally suitable whether a single job is being submitted or bulk scheduling is being performed. Results indicate that considerable performance improvements can be gained by adopting the DIANA scheduling approach.

cs.DC↗

arXiv2006

Bulk Scheduling with DIANA Scheduler

Results from and progress on the development of a Data Intensive and Network Aware (DIANA) Scheduling engine, primarily for data intensive sciences such as physics analysis, are described. Scientific analysis tasks can involve thousands of computing, data handling, and network resources and the size of the input and output files and the amount of overall storage space allocated to a user necessarily can have significant bearing on the scheduling of data intensive applications. If the input or output files must be retrieved from a remote location, then the time required transferring the files must also be taken into consideration when scheduling compute resources for the given application. The central problem in this study is the coordinated management of computation and data at multiple locations and not simply data movement. However, this can be a very costly operation and efficient scheduling can be a challenge if compute and data resources are mapped without network cost. We have implemented an adaptive algorithm within the DIANA Scheduler which takes into account data location and size, network performance and computation capability to make efficient global scheduling decisions. DIANA is a performance-aware as well as an economy-guided Meta Scheduler. It iteratively allocates each job to the site that is likely to produce the best performance as well as optimizing the global queue for any remaining pending jobs. Therefore it is equally suitable whether a single job is being submitted or bulk scheduling is being performed. Results suggest that considerable performance improvements are to be gained by adopting the DIANA scheduling approach.

cs.DC↗

arXiv2005

JClarens: A Java Framework for Developing and Deploying Web Services for Grid Computing

High Energy Physics (HEP) and other scientific communities have adopted Service Oriented Architectures (SOA) as part of a larger Grid computing effort. This effort involves the integration of many legacy applications and programming libraries into a SOA framework. The Grid Analysis Environment (GAE) is such a service oriented architecture based on the Clarens Grid Services Framework and is being developed as part of the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) at European Laboratory for Particle Physics (CERN). Clarens provides a set of authorization, access control, and discovery services, as well as XMLRPC and SOAP access to all deployed services. Two implementations of the Clarens Web Services Framework (Python and Java) offer integration possibilities for a wide range of programming languages. This paper describes the Java implementation of the Clarens Web Services Framework called JClarens. and several web services of interest to the scientific and Grid community that have been deployed using JClarens.

cs.DC↗

arXiv2005

Resource Management Services for a Grid Analysis Environment

Selecting optimal resources for submitting jobs on a computational Grid or accessing data from a data grid is one of the most important tasks of any Grid middleware. Most modern Grid software today satisfies this responsibility and gives a best-effort performance to solve this problem. Almost all decisions regarding scheduling and data access are made by the software automatically, giving users little or no control over the entire process. To solve this problem, a more interactive set of services and middleware is desired that provides users more information about Grid weather, and gives them more control over the decision making process. This paper presents a set of services that have been developed to provide more interactive resource management capabilities within the Grid Analysis Environment (GAE) being developed collaboratively by Caltech, NUST and several other institutes. These include a steering service, a job monitoring service and an estimator service that have been designed and written using a common Grid-enabled Web Services framework named Clarens. The paper also presents a performance analysis of the developed services to show that they have indeed resulted in a more interactive and powerful system for user-centric Grid-enabled physics analysis.

cs.DC↗

arXiv2005

Heterogeneous Relational Databases for a Grid-enabled Analysis Environment

Grid based systems require a database access mechanism that can provide seamless homogeneous access to the requested data through a virtual data access system, i.e. a system which can take care of tracking the data that is stored in geographically distributed heterogeneous databases. This system should provide an integrated view of the data that is stored in the different repositories by using a virtual data access mechanism, i.e. a mechanism which can hide the heterogeneity of the backend databases from the client applications. This paper focuses on accessing data stored in disparate relational databases through a web service interface, and exploits the features of a Data Warehouse and Data Marts. We present a middleware that enables applications to access data stored in geographically distributed relational databases without being aware of their physical locations and underlying schema. A web service interface is provided to enable applications to access this middleware in a language and platform independent way. A prototype implementation was created based on Clarens [4], Unity [7] and POOL [8]. This ability to access the data stored in the distributed relational databases transparently is likely to be a very powerful one for Grid users, especially the scientific community wishing to collate and analyze data distributed over the Grid.

cs.DC↗