International Journal of Innovations in Science & Technology
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Integration of Probability Based Ridge Variation Information with Local Ridge Orientation for Fingerprint Liveness Detection
Get PDFFingerprints are commonly used in biometric systems. However, the authentication of these systems became an open challenge because fingerprints can easily be fabricated. In this paper, a hybrid feature extraction approach named Integration of Probability Weighted Spatial Gradient with Ridge Orientation (IPWSGRo) has been proposed for fingerprint liveness detection. IPWSGRo integrates intensity variation and local ridge orientation information. Intensity variation is computed by using probability-weighted moments (PWM) and second order directional derivative filter. Moreover, the ridge orientation is estimated using rotation invariant Local Phase Quantization (LPQri) by retaining only the significant frequency components. These two feature vectors are quantized into predefined intervals to plot a 2-D histogram. The support vector machine classifier (SVM) is then used to determine the validity of fingerprints as either live or spoof. Results are obtained by applying the proposed technique on three standard databases of LivDet competition 2011, 2013, and 2015. Experimental results indicate that the proposed method is able to reduce the average classification error rates (ACER) to 5.7, 2.1, and 5.17% on LivDet2011, 2013, and 2015, respectively.
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Power Spectrum of Brain for Complex Task using Electroencephalogram
Get PDFCognitive processes are constantly under critical relevance in the field of neuroscience. In the examination of Electroencephalogram (EEG) data, frequency bands are always significant because they determine how the brain responds to various activities and circumstances in different situations. However, it is usually accepted that each brain region is associated with a certain activity, such as auditory, visual, or cognitive tasks. Moreover, to retrieve additional information from the brain, it is often required to establish new neural connections. In this study, the researchers established a functional relationship between different EEG frequencies and the cognitive task under investigation. The frequencies of alpha, beta, and theta waves are often discussed in connection to cognitive tasks, but the frequency of the delta wave is seldom referenced throughout the cognitive process. We then focused on the frequency of delta waves in different parts of the brain, such as the occipital and front alregions
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Meme Detection of Journalists from Social Media by Using Data Mining Techniques
Get PDFWith regard to today\u27s social media networks, memes have become central character where millions of memes are shared per second on different social media networks. The detection of memes is a very concentrated and demanding subject in the current era. Today\u27s social media (What\u27s App, Twitter, and Facebook) is widespread around the world. People in all countries use these networks and spend their plentiful time on daily basis. As social media has an enormous amount of data overall in the world. Meme detection from media networks can be done by using their authenticated APIs. For this analysis we used some opinion mining techniques and sentiment analysis like statistical descriptive and content analysis. In our society, it is the better way to analyze about any journalist because social media can provide very huge amounts of data about any journalist however the authenticity is compromised, what is true or false, no one bother to check. Anyone can make approximate correct perceptions by using sentiment analysis and text mining techniques. It will provide highly wanted and hidden characteristics and perceptions for searchers and demanding people about journalists. Finally use for sentiment analysis by using Python
Determination and Mitigation of Urban Heat Island (UHI) In Lahore (A comparative Study of Landsat 8&9)
Get PDFThe term "Urban Heat Island" (UHI) refers to a city or metropolitan area that is significantly warmer than its surroundings. Heatwaves are one of the most visible hazards associated with UHI, that intensified exponentially over the last two decades. The overall approach of the study is initially based on a review of the literature and qualitative studies. The findings were applied to the case study to obtain empirical shreds of evidence. The study investigated the spatiotemporal urbanization trends and their impacts on UHI in Lahore, Pakistan, using multiple datasets. By identifying thermal drivers and simulating the spatial pattern, the direct relationship between development patterns and thermal properties can be visualized. To identify hot spots multi-temporal Landsat TM/OLI satellite images were processed using GIS and remote sensing techniques. It also investigates urban green spaces using spectral indices like the Normalized Difference Vegetation Index (NDVI). The findings indicate that Lahore\u27s urbanization trend is intensifying in both existing and newly proposed zones which increases the pressure on land use planning. The negative correlation between Land Surface Temperature (LST) and NDVI confirms urban sprawl at the expense of green spaces, reshaping and aggregating the UHI profile of Lahore. These methodologies were combined to create UHI mitigation strategies that may aid communication among various stakeholders, including those in academia, development authorities, planners, and practitioners of the built environment. LST calculation by Landsat 9 proved efficient in comparison to Landsat 8 whch may be due to improvement in spatial and spectral domain in architectural design Landsat series.
A Study of Reasons behind Unproductivity and Indecisiveness in public Institutions of Urban Planning in Pakistan
Get PDFUrban Planning plays a crucial role in managing the systematic growth of the cities. Over time, it has been observed that institutions dealing with the planning, development & regulations are suffering from unproductivity because of numerous reasons. The objective of the study is to find the social, psychological, administrative, structural & academic factors affecting the most in the non-performance and unproductivity of the institutions dealing with the Urban Planning & Development and their respective severity so that the causes of those factors could be evaluated & so as remedial measures & reforms could be suggested. The performance evaluation is needed for the organizations working in the Urban Planning field. Otherwise, the Master plan/strategic plan/ development plan will remain merely an academic concept. It’s about giving a chance to look deep inside your organization to enhance its efficiency and effectiveness
Analyzing ML-Based IDS over Real-Traffic
Get PDFThe rapid growth of computer networks has caused a significant increase in malicious traffic, promoting the use of Intrusion Detection Systems (IDSs) to protect against this ever-growing attack traffic. A great number of IDS have been developed with some sort of weaknesses and strengths. Most of the development and research of IDS is purely based on simulated and non-updated datasets due to the unavailability of real datasets, for instance, KDD \u2799, and CIC-IDS-18 which are widely used datasets by researchers are not sufficient to represent real-traffic scenarios. Moreover, these one-time generated static datasets cannot survive the rapid changes in network patterns. To overcome these problems, we have proposed a framework to generate a full feature, unbiased, real-traffic-based, updated custom dataset to deal with the limitations of existing datasets. In this paper, the complete methodology of network testbed, data acquisition and attack scenarios are discussed. The generated dataset contains more than 70 features and covers different types of attacks, namely DoS, DDoS, Portscan, Brute-Force and Web attacks. Later, the custom-generated dataset is compared to various available datasets based on seven different factors, such as updates, practical-to-generate, realness, attack diversity, flexibility, availability, and interoperability. Additionally, we have trained different ML-based classifiers on our custom-generated dataset and then tested/analyzed it based on performance metrics. The generated dataset is publicly available and accessible by all users. Moreover, the following research is anticipated to allow researchers to develop effective IDSs and real traffic-based updated datasets
Critical Review of Blockchain Consensus Algorithms: challenges and opportunities
Get PDFBlockchain is a distributed ledger in which transactions are grouped in blocks linked by hash pointers. Blockchain-based solutions provide trust and privacy because of the resistance to the inconsistency of data and advanced cryptographic features. In various fields, blockchain technology has been implemented to ensure transparency, verifiability, interoperability, governance, and management of information systems. Processing large volumes of data being generated through emerging technologies is a big issue. Many researchers have used Blockchain in various fields integrated with IoT, i.e., industry 4.0, biomedical, health, genomics, etc. Blockchain has the attributes of decentralization, solidness, security, and immutability with a possibility to secure the system design for transmission and storage of data. The purpose of the consensus protocols is to keep up the security and effectiveness of the blockchain network. Utilizing the correct protocol enhances the performance of the blockchain applications. This article presents essential principles and attributes of consensus algorithms to show the applications, challenges, and opportunities of blockchain technology. Moreover, future research directions are also presented to choose an appropriate consensus algorithm to enhance the performance of Blockchain based application
Analysis of the Historical Temperature of Different Cities of Pakistan to Determine the Trends and Shift in Temperature
Get PDFAntrhopogenic activities are responsible for exponential increase in temperature in recent dacades. To examine this variation, data from 30 meteorological stations in Pakistan\u27s largest cities were examined to determine the annual average and highest temperatures between 1981 and 2020. A combination of parametric and non-parametric tests, including Sen\u27s slope estimator, the Mann-Kendall trend test, and linear regression, were utilized for the analysis. NASA Power Data Access Viewer provides historical climatic datasets which are reliable and provide promising results. We extracted historical footprints of climatic data from NASA website and mapped the trends. About 90% of the meterological stations had rising annual temperature trends, whereas 10% had declining trends. The average annual temperature increased by 0.49 °C per decade in Gilgit, Hyderabad, Quetta, and Lasbela, which was the largest rate of change. Chitral, Gilgit, Nawabshah, and Quetta experienced the biggest increase in annual temperature that was 0.34 °C per decade. Various indicators e.g., simple linear regression and the Mann-Kendall test, respectively, revealed that the yearly average temperature was rising at a 0.001 % (at the 0.06 level). Annual temperatures were increasing at 27 stations and 23 stations were experiencing 0.002 level of significance (at the 0.06 level). Overall, the findings indicated that all climatic parameters were increasing, but during the study period, the annual average temperature was increasing more quickly than the annual maximum temperature
Arsenic (v) Adsorption by Using Synthesized Iron Oxide Nanoparticles (Fe2O3-NPs) and Aluminum Oxide Nanoparticles (Al2O3-NPs)
Get PDFArsenic, is one of the most harmful elements to human health that continuously causes a threat to the world. Arsenic is found in combined form in rocks under the earth\u27s surface and when it dissolves, it contaminates groundwater. The current research synthesized iron oxide nanoparticles (Fe2O3-NPs) and aluminum oxide nanoparticles (Al2O3-NPs) for removal of arsenic (As) (˅) from an aqueous medium and characterized the synthesized material by different analytical techniques such as FT-IR spectroscopy and XRD spectroscopy. The results show successful synthesis of Fe2O3-NPs and Al2O3-NPs. Furthermore, the synthesized material was used as an adsorbent for extraction of as (V) from water. The effect of different parameters such as pH, temperature, contact time, and adsorbent dose on the adsorption process was investigated. The adsorption efficiency was determined by Fe2O3-NPs at about 20 mg/g and Al2O3-NPs at 19.5 mg/g. The quantitative removal of as (V) from industrial water required a minimum amount (0.2 g) of Fe2O3-NPs and Al2O3-NPs. various kinetic and isotherms were investigated in the current study. The result showed that the obtained data for Fe2O3-NPs was more fitted to Pseudo second order kinetic and Freundlich equation, while for Al2O3-NPs the data was more fitted to Pseudo second order kinetic and Elovich model equation, which confirms the interaction among as (V) and adsorbents. Thermodynamic parameters were also investigated which shows the process is spontaneous and endothermic. This model was used to estimate the site energy distribution for each adsorbent. Thermodynamic parameters were also investigated which shows the non-spontaneous and endothermic nature of the adsorbent. According to the results of the analysis of the approximate site energy distribution, adding Fe2O3 and Al2O3-NPs to arsenic decreased the area under the frequency distribution curve of the sorption site energies, which in turn decreased the number of sorption sites that were open to arsenic. This might be explained by the hydrophobic interaction between synthesized materials and arsenic being reduced due to the blocking of the Fe2O3 and Al2O3-NPs hydrophobic surface
Impact of Land-use Change on Agricultural Production & Accuracy Assessment through Confusion Matrix
Get PDFLand modification and its allied resources have progressively become a severe problem presently pulling the worldwide attention and now it rests at the central point of the conservation of the environment and sustainability. The present research aimed to examine the land-use changes and their impact on agricultural production using remote sensing and GIS techniques over the study area that comprised of Tehsil Shorkot, District Jhang, Punjab, Pakistan. Images were pre-processed by using the Arc GIS and ERDAS Imagine 15 software for stacking of the layers, sub-setting, and mosaicking of the satellite bands. After the pre-processing of the images, supervised image classification scheme was applied by employing a maximum likelihood algorithm to recognize the land-use changes which have been observed in the area under study. The area under water was occupied 9.6 km2 in 2010 that increased to 21.04 km2 in 2015 and decreased to 19.4 km2in 2020. Built-up land was 16.6 km2 in 2010 that increased to 19.4 km2 in 2015 and 26.8 km2 in 2020. The total area under vegetation was computed as 513.2 km2 in 2010 that increased to 601.6km2 in 2015 and further increased to 717.7 km2in 2020. Forest land use showed decreasing trend as the covered area in 2010 was occupied 90.8 km2 that decreased to 86.7 km2 in 2015 and further decreased to 61.84 km2 in 2020. In 2010, barren land use was occupied 528.54 km2 that considerably decreased to 429.64 km2 in 2015 further decreased to 333.1 km2 in 2020. Barren land drastically decreased into watered, built-up, and vegetation land uses. The findings of this study will be helpful for the future conservation of various land-use types, urban and regional planning, and an increase in agricultural production of various crops in the study area.
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