Vector Based Genetic Algorithm to optimize predictive analysis in network security

A new Intrusion Detection System (IDS) for network security is proposed making use of a Vector-Based Genetic Algorithm (VBGA) inspired by evolutionary approaches. The novelty in the algorithm is to represent chromosomes as vectors and training data as matrices. This approach allows multiple pathways to calculate fitness function out of which one particular methodology is used and tested. The proposed method uses the overlap of the matrices with vector chromosomes for model building. The fitness of the chromosomes is calculated from the comparison of true and false positives in test data. The algorithm is flexible to train the chromosomes for one particular attack type or to detect the maximum number of attacks. The VBGA has been tested on two datasets (KDD Cup-99 and CTU-13). The proposed algorithm gives high detection rate and low false positives as compared to traditional Genetic Algorithm. A detailed comparative analysis is given of proposed VBGA with the traditional string-based genetic algorithm on the basis of accuracy and false positive rates. The results show that vector based genetic algorithm provides a significant improvement in detection rates keeping false positives at minimum.     

TextDNA: Visualizing Word Usage with Configurable Colorfields

Patterns of words used in different text collections can characterize interesting properties of a corpus. However, these patterns are challenging to explore as they often involve complex relationships across many words and collections in a large space of words. In this paper, we propose a configurable colorfield design to aid this exploration. Our approach uses a dense colorfield overview to present large amounts of data in ways that make patterns perceptible. It allows flexible configuration of both data mappings and aggregations to expose different kinds of patterns, and provides interactions to help connect detailed patterns to the corpus overview. TextDNA, our prototype implementation, leverages the GPU to provide interactivity in the web browser even on large corpora. We present five case studies showing how the tool supports inquiry in corpora ranging in size from single document to millions of books. Our work shows how to make a configurable colorfield approach practical for a range of analytic tasks.     

MDCBIR-MF: multimedia data for content-based image retrieval by using multiple features

Multimedia Tools and Applications - Due to recent development in technology, the complexity of multimedia is significantly increased and the retrieval of similar multimedia content is an open...     

Analyzing COVID-19 Impact on the Researchers Productivity through Their Perceptions

Context: Since the end of 2019, the COVID-19 pandemic had a worst impact on world’s economy, healthcare, and education. There are several aspects where the impact of COVID-19 could be visualized. Among these, one aspect is the productivity of researcher, which plays a significant role in the success of an organization. Problem: There are several factors that could be aligned with the researcher’s productivity of each domain and whose analysis through researcher’s feedback could be beneficial for decision makers in terms of their decision making and implementation of mitigation plans for the success of an organization. Method: We perform an empirical study to investigate the substantial impact of COVID-19 on the productivity of researchers by analyzing the relevant factors through their perceptions. Our study aims to find out the impact of COVID-19 on the researcher’s productivity that are working in different fields. In this study, we conduct a questionnaire-based analysis, which included feedback of 152 researchers of certain domains. These researchers are currently involved in different research activities. Subsequently, we perform a statistical analysis to analyze the collected responses and report the findings. Findings: The results indicate the substantial impact of COVID-19 pandemics on the researcher’s productivity in terms of mental disturbance, lack of regular meetings, and field visits for the collection of primary data. Conclusion: Finally, it is concluded that researcher’s daily or weekly meetings with their supervisors and colleagues are necessary to keep them more productive in task completion. These findings would help the decision makers of an organization in the settlement of their plan for the success of an organization.     

Multilingual Sentiment Mining System to Prognosticate Governance

In the age of the internet, social media are connecting us all at the tip of our fingers. People are linkedthrough different social media. The social network, Twitter, allows people to tweet their thoughts on any particular event or a specific political body which provides us with a diverse range of political insights. This paper serves the purpose of text processing of a multilingual dataset including Urdu, English, and Roman Urdu. Explore machine learning solutions for sentiment analysis and train models, collect the data on government from Twitter, apply sentiment analysis, and provide a python library that classifies text sentiment. Training data contained tweets in three languages: English: 200k, Urdu: 200k and Roman Urdu: 11k. Five different classification models are applied to determine sentiments, and eventually, the use of ensemble technique to move forward with the acquired results is explored. The Logistic Regression model performed best with an accuracy of 75%, followed by the Linear Support Vector classifier and Stochastic Gradient Descent model, both having 74% accuracy. Lastly, Multinomial Naïve Bayes and Complement Naïve Bayes models both achieved 73% accuracy.     

Multilayer cluster designing algorithm for lifetime improvement of wireless sensor networks

Cluster-based network is a proven architecture for energy-aware routing, but more attention is required to ameliorate the energy consumption aspect of its cluster designing process. In this research work, we introduce a novel design of clustered network architecture. The proposed design technique is innovative in its idea. The general trend in this scene is either centralized decision at base station for cluster head selection and its members or distributed decision by exchanging information between neighboring nodes until the cluster head and its members are selected. Both the techniques drastically create mess in energy consumption due to too much broadcasting, especially in large networks as well as message exchange until some final decision is made. Our novel layer-based hybrid algorithm for cluster head and cluster member selection comes up to novel communication architecture. Since its substantial constituent is cluster designing, we named it Multilayer Cluster Designing Algorithm (MCDA). The proposed design not only has effect on lessening blind broadcasting, but also on decreasing the message exchange in a passionate way. It also encapsulates the beauty of efficient centralized decision making for cluster designing and energy-aware distributed cluster head selection and cluster member allocation process. Comprehensive experimentations have been performed on the comparative analysis of MCDA with state-of-the-art centralized and distributed cluster designing approaches present in published literature. Calculation of energy consumption in various operational parametric values, number of clusters designed and the number of packets broadcasted during cluster designing are the main performance evaluation parameters. It has been found that MCDA outperforms compared to its three competing algorithms with respect to the aforementioned parameters due to its multilayered synergistic mating approach.     

Radiative flow of MHD non-Newtonian fluid by utilizing the updated version of heat flux model under Joule heating

This exploration reports the analysis of thermal and species transportation to yields manifesting non-Newtonian material flowing over the linear stretching sheet. Phenomena of heat transport are presented via Cattaneo–Christov heat flux definition. Mass transportation is modeled by engaging the traditional Fick's second law with updated model of mass flux including the species relaxation time. Moreover, Joule heating and radiation contribution to thermal transmission are also considered. The significant contribution of diffusion-thermo and thermos-diffusion is engaged in thermal and species transmission. Physical depiction of the considered scenario is modeled via boundary layer approximation. Similarity analysis has been made to transfigure the system of modeled partial differential equations into respective ordinary differential equations. Afterwards, transformed physical expressions are computed for the momentum, thermal, and species transportation inside the boundary layer.     

Gatifloxacin–Ionic Surfactant Interactions: Volumetric,Acoustic, Voltammetric,and Spectroscopic Studies

Surfactant systems have been frequently used as pseudomodels for investigating interactions of drugs with biological membranes because of their structural similarities with the latter. This helps to understand complicated yet very important biological processes like diffusion of bioactive moieties through biomembranes. The current study deals with voltammetric and spectroscopic studies to evaluate the interaction of a potential antibacterial drug, gatifloxacin (GTF), with a cationic surfactant, dodecyltrimethylammonium bromide (DTAB), and an anionic surfactant, sodium dodecyl sulfate (SDS), under physiological conditions (phosphate buffer, pH 7.4). For more detailed insight into the GTF–ionic surfactant interactions, density and acoustic data were also recorded and used to calculate several important parameters, namely, apparent molar volume (ɸ_V ), isentropic compressibility (K_s ), and apparent molar isentropic compressibility (ɸ_K ) at T = 298.15, 303.15, 308.15, and 313.15 K. Values for partial molar volume (, partial molar expansivity , specific acoustic impedance (Z), relative association (RA), intermolecular free length (L_f), and sound velocity number (U) were also obtained. The interpretation of the concentration dependence of the above-mentioned quantities using a cosphere overlap model led to a better apprehension of solute–solute and solute–solvent intermolecular interactions present in the investigated system, whereas cyclic voltammetry and ultra violet (UV)–visible spectroscopic studies assisted in predicting the location of adsorbed GTF molecules within the DTAB and SDS micelles.     

On the contact of an inflated spherical membrane-fluid structure with a rigid conical indenter

The large deformations of a spherical membrane inflated by an incompressible fluid in contact with a frictionless rigid conical indenter are analyzed. The objective is to study the stress distribution and the fluid pressure in this membrane-fluid structure in response to contact with the conical indenter. The membrane is assumed to be homogeneous, elastic, and isotropic while the enclosed fluid is taken to be incompressible. The equilibrium equations of the membrane-fluid structure are expressed as a set of two first-order ordinary differential equations for the part of the membrane in contact with an indenter and four first-order ordinary differential equations for the part not in contact. A neo-Hookean material model is used to describe the material property of the membrane. The nonlinear system of ordinary differential equations is solved numerically using the shooting method.