International Journal of Innovations in Science & Technology
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Voice Spoofing Countermeasure Based on Spectral Features to Detect Synthetic Attacks Through LSTM
Get PDFWith the growing number of voice-controlled devices, it is necessary to address the potential vulnerabilities of Automatic Speaker Verification (ASV) against voice spoofing attacks such as Physical Access (PA) and Logical Access (LA) attacks. To improve the reliability of ASV systems, researchers have developed various voice spoofing countermeasures. However, it is hard for the voice anti-spoofing systems to effectively detect the synthetic speech attacks that are generated through powerful spoofing algorithms and have quite different statistical distributions. More importantly, the speedy improvement of voice spoofing structures is producing the most effective attacks that make ASV structures greater vulnerable to stumble on those voice spoofing assaults. In this paper, we proposed a unique voice spoofing countermeasure which is successful to hit upon the LA attacks (i.e., artificial speech and transformed speech) and classify the spoofing structures by the usage of Long Short-Term Reminiscence (LSTM). The novel set of spectral features i.e., Mel-Frequency Cepstral Coefficients (MFCC), Gammatone Cepstral Coefficients (GTCC), and spectral centroid are capable to seize maximum alterations present in the cloned audio. The proposed system achieved remarkable accuracy of 98.93%, precision of 100%, recall of 92.32%, F1-score of 96.01%, and an Equal Error Rate (EER) of 1.30%. Our method achieved 8.5% and 7.02% smaller EER than the baseline methods such as Constant-Q Cepstral Coefficients (CQCC) using Gaussian Mixture Model (GMM) and Linear Frequency Cepstral Coefficients (LFCC) using GMM, respectively. We evaluated the performance of the proposed system on the standard dataset i.e., ASVspoof2019 LA. Experimental results and comparative analysis with other existing state-of-the-art methods illustrate that our method is reliable and effective to be used for the detection of voice spoofing attacks.
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A Review on Transformation of Monolithic Applications towards Microservices Environment
Get PDFThe traditional monolithic approach is widely employed in centralized software development, deployment, and reusability, as the modules are tightly connected, causing several challenges in programming. The study utilized different techniques for the easy transformation of several running monolithic applications to micro services including, Angular 2, REST API, Web application and several other architectural approaches are discussed. This review paper highlights the significance of microservices and the transformation of monolithic applications towards microservices. As multiple software applications are an integral part of a traditional monolithic application, the modules cannot be extended separately, and different modules cannot use various technology stacks. So, monolithic source code must be migrated to the microservice platform in order to extend `the lifecycle of applications in today\u27s environment. However, due to structural complexity, scattered application logic, and dependency upon external framework libraries, the transformation towards a microservices platform is quite challenging. A Microservice architecture is a container of loosely coupled independent services making a flexible system. In this study, potential areas for the transformation of monolithic application source code are highlighted. Furthermore, key challenges and open research issues in this area are highlighted, requiring the research community\u27s attention. The study concludes that Microservices are not a one-size-fits-all solution for every challenging situation. Monolithic transformation requires significant amount of time and effort on the part of everyone in the business.
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Assessment and Monitoring of VIIRS-DNB and SQML-L light Pollution in Lahore-Pakistan
Get PDFThe usage of artificial light is excessive and improper. Earth\u27s night picture has changed significantly from space and studies have shown that over-exposure to artificial light in the night can influence animals, the environment and human beings. The purpose of this study was to monitor and measure skylights of Lahore City and temporary light pollution from 2012-2019. The Suite-Day/Night band of the Visible Image Radiometer was used for time changes analysis with GIS and Remote Sensing tools. Indicators were established as a table tool through zonal statistics, and a field survey was also undertaken to measure the Sky-Glow of Lahore with Sky Quality Meter-L. The results suggest that from 2012 to 2019, light pollution rose by 23.43 percent. Results suggest that around 53.99% of Lahore suffered from light pollution. The number of lights in Lahore has increased by 161.82 percent between 2012 and 2019. In the study period, the mean night light and the standard night light deviation were 127.87 and 98.22 percent, respectively. Lahore\u27s night sky was heavily polluted by light. Lahore\u27s average skylight is 17.15 meters above sea level, which means low quality skies at night. This research aims to provide people an insight into light pollution and the causes of local light pollution. Furthermore, this study aims to enhance public attention to light pollution mitigation attempts by governments and politicians.
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Comparison of Machine Learning Algorithms for Sepsis Detection
Get PDFSepsis is a very fatal disease, causing a lot of causalities all over the world, about 2, 70,000 die of Sepsis annually, thus early detection of Sepsis disease would be a remedy to prevent this disease and it would be a big relief to the family of sepsis patients. Different researchers have worked on sepsis disease detection and its prediction but still the need to have an improved model for Sepsis detection remains. We compared various machine learning algorithms for Sepsis detection and used the dataset publicly available for all the researchers at Physionet.org, the dataset contains many empty or Null values, we applied backward filling and forward filling techniques, and we calculated missing values of MAP using equation (1) which gives more precise results, we divided the 40,336 files of datasets A and B into 80% training set and 20% testing set. We applied the algorithms twice one time using vital signs and clinical values of patients and the second time using only vital signs of the patients; using vital signs only the training accuracy of KNN, Logistic Regression, Random Forest, MLP, and Decision Trees was 0.992, 0.999, 0.981, 0.981, and 0.981 respectively, while the testing accuracy of KNN, Logistic Regression, Random Forest, MLP, and Decision Trees was 0.987, 0.980, 0.983, 0.981, and 0.981 respectively, for Sepsis Label 0, the value of precision for KNN, Random Forest, Decision Trees, Logistic Regression, and MLP was 0.99, 0.98, 0.98, 0.98, and 0.98 respectively, while the value of recall for KNN, Random Forest, Decision Trees, Logistic Regression, and MLP was 1.00, 1.00, 1.00, 1.00, and 1.00 respectively; the comparison of all the above-mentioned algorithms showed that KNN leads over all the competitors regarding the accuracy, precision, and recall.
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Dual-Band 10-Element MIMO Antenna for Sub-6 GHz MIMO Applications in 5G Smartphones
Get PDFThe dramatic growth of mobile users, IoT-based applications, and astounding channel capacity requirements to connect trillions of devices are some huge challenges of the previous mobile generations, 5G turned up the key solution. Although the 5G MIMO can boost channel capacity and spectrum efficiency, it is very challenging to integrate multiple antennas into a mobile phone with limited space. Therefore, we presented a multi-band 10-elements array antenna operating at the LTE (long term evolution) 42, 43, and 46 frequency spectrum (sub-6 GHz band) for MIMO applications in fourth/fifth generation (4G/5G) modern mobile phones in this paper. A simple T-shaped slot antenna is designed to acquire 10-element MIMO antenna implementation in LTE 42/43 and 46 bands. The presented antenna array is integrated using a low-priced FR-4 substrate which is typically used for 5.7- 6-inch smartphones and possesses dimensions of 150mm × 80mm × 0.8mm. The simulated results show superb impedance matching and isolation between ports (> -12 dB), radiation efficiency (>70 %), and Envelope Correlation Coefficient (ECC< 0.05) over the operational frequency. Consequently, the designed MIMO antenna array is effectively favorable for the 5G MIMO smartphone to enhance data output and the spectrum efficiency.
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Prospects of Biosynthetically produced Nanoparticles in Biocontrol of Pests and Phytopathogens: A review: Prospects of Biosynthetically produced Nanoparticles in Biocontrol of Pests and Phytopathogens
No full textModern nanotechnology is playing a vital role in our daily life by contributing in different domains such as usage of nanoparticles for target-specific drug delivery system, as these nanoparticle are being used as scratch proof coating on glass for tracking of biomolecules. Some emerging applications of nanoparticles include usage of nanoparticles for diagnostic purposes such as biomedical imaging and as green technology producing nano pesticides. The use of endophytic or plant beneficial bacteria for the production of metallic nanoparticles have shown promising results in not only controlling the pest but also contributing in enhanced developmental growth due to their small size, target specificity, and enhanced interaction with the plant in controlled environment. As for increasing environmental crisis, use of biological methods to remediate the environment is becoming a necessity. Green technology based nano-materials being used now a days in multiple fields, especially in bio-control of pests. This review is based on the microbial synthesized metallic nanoparticles, which are being used as nano pesticides (nanoparticles are pesticides)
The Impact of Language Syntax on the Complexity of Programs: A Case Study of Java and Python
Get PDFProgramming is the cornerstone of computer science, yet it is difficult to learn and program. The syntax of a programming language is particularly challenging to comprehend, which makes learning arduous and affects the program\u27s testability. There is currently no literature that definitively gives quantitative evidence about the effect of programming language complex syntax. The main purpose of this article was to examine the effects of programming syntax on the complexity of their source programs. During the study, 298 algorithms were selected and their implementations in Java and Python were analyzed with the cyclomatic complexity matrix. The results of the study show that Python\u27s syntax is less complex than Java\u27s, and thus coding in Python is more comprehensive and less difficult than Java coding. The Mann-Whitney U test was performed on the results of a statistical analysis that showed a significant difference between Java and Python, indicating that the syntax of a programming language has a major impact on program complexity. The novelty of this article lies in the formulation of new knowledge and study patterns that can be used primarily to compare and analyze other programming languages
Development and Psychometric Properties of Harassment Tendency Scale
Get PDFThe aim of this research was to construct a native scale for harassment tendency and psychometric properties for the assessment of the Harassment tendency scale according to the cultural perspective of the Urdu language used. This indigenous scale can be used by psychologists, psychiatrists and even researchers for the general population to measure the tendency of harassment among males and females as well. Utilizing existent content and information from the literature research, the initial item pool of 150 items were created. Following the pilot research, 12 of the 138 expert-evaluated items were kept, including the eight aspects of harassment. Additionally, data from the sample of (N=340) people who completed this scale\u27s final administration were gathered. Participants from educational institutions and local communities from different areas of Pakistan by using a self-reported questionnaire through convenient sampling. Rotated component matrix analysis shows, factors loading ranges from 0.402 to 0.641 of 97 items. The sample adequacy showed KMO=0.866 on 27 items (N=340) and factor loading loaded 8 factors. CFI value 0.909 with the significant model fit p<0.05 with appropriate model fit indices. HTS also conformed to good test-retest reliability (r=0.954, p=.000) at a 0.01 alpha level which is indicated the scale is a reliable measure for harassment tendency. A scale to measure Harassment tendency in the Urdu language is competently established with 27 questions and eight factors. Statistical Package for the Social Science volume 24 used for EFA (Exploratory Factor Analysis). AMOS (Analysis of a Moment structure) version 24 was used for CFA (Confirmatory Factor Analysis)
Personality Construct Among Patients With Substance Use Disorder: An Explanatory Study In Pakistan
Get PDFObjective: Many researches defined the critical predictors and significant risk factors associated with various substance use behaviors, revealing the personality traits as important determinants. Thus, the present study aimed to explore the personality constructs of individuals with a history of substance use disorder in Pakistan.
Method: The Qualitative Study was conducted through purposive sampling by selecting the professionals (psychiatrists=9, clinical psychologists=4, patients with SUD = 5) with having a minimum of 5 years to a maximum of 29 years of experience working with substance use disorder patients and participants with the history of at least three years of diagnosis. A total of 18 semi-structured interviews were conducted with nine (N=13) mental health professionals and five (N=05) patients with substance use disorder. The interviews were audio-recorded and transcribed by independent researchers. The transcripts were analyzed using a systematic approach that incorporates inductive thematic analysis.
Results: The themes that emerged after analyses were combined under the main three headings: Social, Cultural and Psychological/individual factors. The main results indicated that authoritative parenting style, family lifestyles, pleasure-seeking, enhanced energy, dependent personality traits, emotional instability and conflicting interpersonal relationship lead to substance use which can be addressed through early intervention
Performance Evaluation of Classification Algorithms for Intrusion Detection on NSL-KDD Using Rapid Miner
Get PDFThe rapid advancement of the internet and its exponentially increasing usage has also exposed it to several vulnerabilities. Consequently, it has become an extremely important that can prevent network security issues. One of the most commonly implemented solutions is Intrusion Detection System (IDS) that can detect unusual attacks and unauthorized access to a secured network. In the past, several machine learning algorithms have been evaluated on the KDD intrusion dataset. However, this paper focuses on the implementation of the four machine learning algorithms: KNN, Random Forest, gradient boosted tree and decision tree. The models are also implemented through the Auto Model feature to determine its convenience. The results show that Gradient Boosted trees have achieved the highest accuracy (99.42%) in comparison to random forest algorithm that achieved the lowest accuracy (93.63%).
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