International Journal of Innovations in Science & Technology
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Risk Factors Associated with Very Low Birth Weight: A Systematic Review and Meta-Analysis
Get PDFBackground: Very Low Birth Weight (VLBW) is due to multiple gestations and reproductive-assisted techniques. Neonatal complications mainly arise in infants with VLBW and Extremely Low Birth Weight (ELBW). The main objective was to study the risk factors associated with VLBW and to conduct a meta-analysis.
Methods: A meta-analysis was done to present the most recent risk variables for VLBW. Electronic databases were searched for information on the suggested topic. Using STATA version 14, the relevant data was extracted, and statistical analysis was conducted.
Results: A total number of 112 studies have been conducted on the topic of VLBW worldwide from 2000 to 2020. Information from many parts of the world was evaluated in which GDP or per capita income, age, and education were followed in prominent regions of the world. As GDP and education level improved, the nutritional status also improved. Fifteen studies have been identified, with five meeting the inclusion criteria for the metanalysis of VLBW <1500g in developing countries. Illiteracy, poverty, mother occupation, hypocalcemia, and hypoglycemia were the common risk factors of VLBW (<0.05).
Conclusion: It was identified that per-capita GDP is inversely proportional to VLBW throughout the world. VLBW in America was found to be significant when compared with central Europe (<0.005), similarly with Southern Europe (<0.03), Northern Europe (<0.00001), Asia (<0.0001), and Africa (<0.0001). Unlike per capita GDP, VLBW was insignificantly related to maternal age in all regions except Africa, where VLBW was significantly associated with maternal age (p<0.0001). In developing countries, illiteracy, poverty, mother occupation, hypocalcemia, and hypoglycemia are the common risk factors for VLBW (<0.05) as the complications related to VLBW are at a high-risk rate, so it is recommended that VLBW babies require special care at the time of birth, especially in poor economic countries
A Geospatial Analysis of Shishper Glacier Surge-Upper Hunza Gilgit Baltistan
Get PDFGlaciers can be an important indicator of climate change. In Pakistan, glaciers are found in the Northern Part of the country. In this study, we have discussed the occurrence of surge velocity, lake formation, and outburst of Shisper Glacier, Hunza, Gilgit, and Baltistan. To conduct this study satellite remote sensing techniques have been used. For this purpose, Sentinel-2 and Landsat 8 have been downloaded for 2015-2019. While to examine the elevation difference ASTER 2000 and SRTM 2014 Digital Elevation Model (DEM) have been downloaded, along with this other remote sensing analyses were applied including temporal change, land cover, and morphometric analysis including indices Normalized Difference Snow Index (NDSI) and Normalized Difference Water Index (NDWI). It has been analyzed that Ice-Dammed Lake formed in November 2018, which is the greatest threat to the study area as it can cause glacial lake outbursts and the volume of the lake is showing a continuous increase from 2018- to 2020. The land cover change indicated that snow area has increased about 35% from 2015 to 2018 along with an increase in debris glacier by about 20%. Whereas, a decrease in vegetation was observed up to 2% in 3 years. This study concludes that snow and clear glacier are enlarged over time. Taking into account our research, our suggestion is obligatory stride should be taken to keep away from the disastrous occurrence in the Shisper glacier.
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Knowledge Acquisition System for Sentiment Analysis
Get PDFSentiment analysis is considered an advanced technology to predict and analyze people’s opinions, attitudes, sentiments, and perceptions towards some topics, products, and services. Due to the fast evolution of Internet-based applications, opinion mining becomes a very substantial method nowadays. For this purpose, many systems have been developed so far; some use the statistical method whereas some use parsers to analyze the data. However, this article presents a complete study and uses a hybrid approach toanalyze volumetric data in the form of sentences. The hybrid approach of sentiment analysis uses both deep learning (statistical methods) and knowledge-based methods. Furthermore, this article also uses a sentence structure approach that helps to overcomethe linguistic effects in the knowledge base. In addition, this article also suggests some future directions using the sentence structure of natural language for an expert system
Quantum Key Distribution Protocols for Secure Communication
No full textData protection and information security have been the essence of communication in today\u27s digital era. Authentication and secrecy of secure communication are achieved using key-based cryptographic primitives; the security of which significantly relies upon the underlying computationally complex mathematics. Moreover, these existing cryptographic primitives are considered to be non-deterministic on the basis of the existing computational capabilities. However, the considerable advancements in the development of quantum computers have significantly enhanced parallel computations; thereby, posing a great threat to these existing encryption primitives. Thus, in the future, the physical manifestation of a large successful quantum computer is likely to break all the existing public-key encryption algorithms in no time. This has led to a remarkable surge of interest in propelling quantum mechanics into existence; subsequently, leading cryptographers to research various viable domains to offer quantum-resistant secure communications. Resultantly, quantum cryptography/quantum key distribution has emerged as a futuristic replacement for classical cryptography as it offers unconditionally secure communication along with the inherent detection of any unintended user. Thus, keeping in view the significance of this relatively newer domain of cryptography this research focuses on presenting a consolidated review of the various Quantum Key Distribution (QKD) protocols. A comparative analysis of the working mechanism of the prominent QKD protocols is presented along with an overview of the various emerging trends that have been proposed to optimize the implementational efficiency of the BB84 protocol
A Qualified review on ML and DL algorithms for Bearing Fault Diagnosis
Get PDFMoving machinery is the backbone of socio-economic development. The use of machines help in increasing the production of everyday used items, and tools, that generate electricity and mechanical energy, and provides easy and fast transportation and help by saving human efforts, energy, and time. The mechanical industry is totally dependent on the bearing and it is considered as bread and butter of the system. Bearing failure is about 40% of the total failures of induction motors which is why it is a crucial challenge to predict the failure and helps prevent future downtime events through maintenance schedules with the latest techniques and tools of. This paper presents a review of how DL techniques and algorithms outsmarted ML for bearing fault detection and diagnosis and summarizes the accuracy results generated by most common DL algorithms over classical ML algorithms.Additionally this paper reasons different criteria for which DL algorithms have been proved efficient for building productive model in the field of bearing fault detection. Furthermore, some of the most famous datasets by different universities have been discussed and accuracy results are provided by reviewing algorithms on the CWRU dataset by different researchers and comparison chart is listed in the results section
Compact Frequency Selective Surface (FSS) for X-Band Shielding
Get PDFWith the increase in the usage of electromagnetic devices, electromagnetic interference increased many folds. Frequency Selective Surface (FSS) provide effective shielding from unwanted frequency ranges. A thin, conformal band-stop FSS is presented in this research that provides effective electromagnetic shielding properties in X-band. The FSS acts as a band stop filter at 10 GHz. The proposed FSS has 54.7% fractional bandwidth. The design is of the dimensions 6.79 x 6.79 x 0.127 milimeter cube, employing Rogers RT 5880 substrate with 0.0009 dielectric constant. It has an attenuation of at least -57.97 dB. The proposed FSS shows oblique incidence angle independence for both TE and TM modes, up to 60o scan angle. The incidence angle independence makes the FSS response stable for both normal and varying angles of the incident waves. The design has a copper cladding of 0.018 mm, making the overall FSS thickness of 0.145 mm. The thin substrate makes the design flexible and easily bendable for curved surfaces. Its thin structure makes it easily applicable on buildings, vehicles and military aircrafts for electromagnetic shielding purposes. The conformability and shielding properties make the design suitable for various other applications.
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Comparative Analysis of Machine Learning Algorithms for Classification of Environmental Sounds and Fall Detection
Get PDFIn recent years, number of elderly people in population has been increased because of the rapid advancements in the medical field, which make it necessary to take care of old people. Accidental fall incidents are life-threatening and can lead to the death of a person if first aid is not given to the injured person. Immediate response and medical assistance are necessary in case of accidental fall incidents to elderly people. The research community explored various fall detection systems to early detect fall incidents, however, still there exist numerous limitations of the systems such as using expensive sensors, wearable sensors that are hard to wear all the time, camera violates the privacy of person, and computational complexity. In order to address the above-mentioned limitations of the existing systems, we proposed a novel set of integrated features that consist of melcepstral coefficients, gammatone cepstral coefficients, and spectral skewness. We employed a decision tree for the classification performance of both binary problems and multi-class problems. We obtained an accuracy of 91.39%, precision of 96.19%, recall of 91.81%, and F1-score of 93.95%. Moreover, we compared our method with existing state-of-the-art methods and the results of our method are higher than other methods. Experimental results demonstrate that our method is reliable for use in medical centers, nursing houses, old houses, and health care provisions.
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Detection of Coronary Artery Using Novel Optimized Grid Search-based MLP
Get PDFIn recent years, we have witnessed a rapid rise in the mortality rate of people of every age due to cardiac diseases. The diagnosis of heart disease has become a challenging task in present medical research, and it depends upon the history of patients. Rapid advancements in the field of deep learning. Therefore, it is a need to develop an automated system that assists medical experts in their decision-making process. In this work, we proposed a novel optimized grid search-based multi-layer perceptron method to effectively detect heart disease patients earlier and accurately. We evaluated the performance of our method on a dataset named Public Health dataset for heart diseases. More specifically, our method obtained an accuracy of 95.12%, precision of 95.32%, recall of 95.32%, and F1-score of 95.32%. We made a comparison of our method with existing methods to check superiority and robustness of our system to detect heart disease patients. Experimental results along with comprehensive comparison with other methods illustrate that our technique has superior performance and is robust to detect heart disease patients. From the results, we can conclude that our method is reliable to be used in hospitals for the early detection of heart disease patients.
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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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Health Consultant Bot: Primary Health Care Monitoring Chatbot for Disease Prediction
Get PDFThis research paper presents a disease prediction chatbot that is intelligent enough to communicate with patients to predict their disease by detecting their symptoms through natural language processing. This system allows the user to describe their medical health condition in natural language, and by processing their natural language-based statement, our system detects the symptoms, predicts the disease, and provides basic precautions as well as a brief introduction about the disease. We have used IBM Watson Assistant to build this system. Watson assistant provides several machine learning algorithms to process user statements and symptoms extraction. In our system, symptoms were mapped by considering the community data which resulted in a predicted disease. Our system provides the relevant information about the predicted disease from the system\u27s database. In an experimental evaluation, we carried out a study having 156 subjects, who interact with the system in a daily use scenario. Results show the effectiveness and accuracy of our system to support the patient in taking good care of their health.
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