International Journal of Innovations in Science & Technology
Not a member yet
813 research outputs found
Sort by
Evaluation of Microbial Contamination in Meat and its Control Using Preservatives
Get PDFFood borne illnesses are common in both developed as well as developing countries. The majority of foodborne diseases are caused by consuming contaminated meat products. This study aimed to evaluate the microbial contamination in different meat samples. Chicken (n=20), Mutton (n=20) and beef (n=20) samples were collected from 10 towns. Total viable count (TVC) and Total coliform count (TCC) in different meat samples were checked. Microscopic, macroscopic and biochemical profiling of isolates (n=108) was done. It was observed that E. coli was the more common (34%) pathogenic bacteria found in raw chicken followed by Salmonella (28%), Staphylococcus (25%), Shigella (8%), Enterobacter (2%), and Bacillus (3%). In Beef Samples E. coli (39%) was more common followed by Salmonella (30%), Staphylococcus (18%) and Enterobacter (8%), and Shigella (5%). While in Mutton Samples E. coli (32%), Salmonella (32%), Staphylococcus (12%), Shigella (12%), Enterobacter (9%), and Bacillus (3%). Antibacterial activity of natural preservatives i.e., Ginger, Garlic, and Radish, and commonly used synthetic preservatives i.e., Sodium nitrite was also checked on isolated strains. It was observed that Ginger and Garlic showed maximum antibacterial activity at the highest concentration used up to 0.8g/ml. Radish showed no antibacterial activity at any concentration. Antibacterial activity of Sodium nitrite was also higher at the maximum concentration used (0.006mM). The renowned harmful effects of Sodium nitrite, make it necessary to devise the use of natural preservatives. It was observed that ginger and garlic may serve as natural preservatives for meat preservation without any side-effect. However, more research is required for the implementation of natural preservatives for meat storage and safety.
Full Tex
Molecular characterization of Deciphering Fungal Community structure in Zea mays L. and Triticum Aestivum L
Get PDFRhizosphere fungi are strongly associated with plant growth and health by providing nutrients and antagonizing pathogens. Commercially, fungus has multipurpose applications in several sectors including beverages, food items and in medicines. Current study aimed to reveal the core fungal community structure of the two leading cereal crops that are Zea mays L. and Triticum aestivum L. The rhizosphere fungal community was explored via morphology, biochemistry and internal transcribe spacer (ITS) metagenomics. On the basis of morphology, the retrieved fungal strains were imprecisely classified into Ascomycota and Zygomycota. The species including Yeast, Botyritis californica, Rhizopus stolonifer, Alternaria tenuissima, Aspergillus terreus, Aspergillus flavus, Aspergillus nidulans, Aspergillus niger and Microsporum canis were identified on the basis of macroscopy and microscope. Moreover, the biochemical characterization depicted the role of fungi in promotion of plant growth. Majority of the isolates depicted catalase activity, indole production, phosphate solubilization, ammonia production, nitrogenase activity and urease activity. Metagenomics using amplicon sequencing of ITS region revealed the presence of 805 Operational Taxonomic Units (OTUs) with 647 OTUs in Zea mays and 620 OTUs in Triticum aestivum. The fungal phyla found in the rhizosphere of Zea mays L. and Triticum aestivum L. were Ascomycota, Basidiomycota, Zygomycota, Chytridiomycota, Incertae sedis fungi. Ascomycota accounted for 93% and 95% of classified fungi in rhizosphere of Zea mays L. and Triticum aestivum L. respectively. The dominant species found in the rhizosphere soil of Zea mays were Gibberella intricans, Curvularia lunata, Lepidosphaeria nicotiae, Edenia gomezpompae and Myrothecium verrucaria
Machine Learning with Data Balancing Technique for IoT Attack and Anomalies Detection
Get PDFNowadays the significant concern in IoT infrastructure is anomaly and attack detection from IoT devices. Due to the advanced technology, the attack issues are increasing gradually. There are many attacks like Data Type Probing, Denial of Service, Malicious Operation, Malicious Control, Spying, Scan, and Wrong Setup that cause the failure of the IoT-based system. In this paper, several machine learning model performances have been compared to effectively predict the attack and anomaly. The performance of the models is compared with evaluation matrices (Accuracy) and confusion matrix for the final version of the effective model. Most of the recent studies performed experiments on an unbalanced dataset; that is clear that the model will be biased for such a dataset, so we completed the experiments in two forms, unbalanced and balanced data samples. For the unbalanced dataset, we have achieved the highest accuracy of 98.0% with Generalized Linear Model as well as with Random Forest; Unbalanced dataset means most of the chances are that model is biased, so we have also performed the experiments with Random Under Sampling Technique (Balancing Data) and achieved the highest accuracy of 94.3% with Generalized Linear Model. The confusion matrix in this study also supports the performance of the Generalized Linear Model.
FULL TEX
Optimal Selection of Reactive Power For Single Tuned Passive Filter Based on Curve Fitting Technique
Get PDFThis research presents the Optimal Reactive Power (Qc) selection for a single-tuned passive filter. DC drives are very popular in the industrial zone due to their high performance, flexibility, easy control, and low cost. DC drives operate by giving supply from an AC utility and AC to DC can be converted using the AC-DC converter. But this conversion introduces harmonics in the input supply current that affect the performance of the DC drive and also cause serious problems for the overall power quality of the system. Many researchers are searching for the appropriate solutions to mitigate this cause. A passive filter is one solution to minimize or avoid harmonics from entering the electrical system. The key aspect of the passive filter design has been a difficult task. The parameters of the passive filter largely depends upon selecting the suitable value of reactive power (Qc). In this paper, the Simulink model of an AC-DC converter based on a separately excited dc motor is used as an industrial load, and a curve fitting technique has been used to select the optimal value of reactive power (Qc) for the passive filter. The simulation results and analysis show that optimal selection of reactive power for single tuned passive filter using the proposed technique is very effective by taking international standards limits for harmonic distortion
BCAS: A Blockchain Model for Collision Avoidance to Prevent Overtaking Accidents on Roads
Get PDFOvertaking at high speeds, especially on non-divided roadways, is a leading cause of traffic accidents. During overtaking maneuvers, humans are more likely to make mistakes due to factors that cannot be predicted. For overtaking operations in autonomous vehicles, prior research focused on image processing and distant sensing of the driving environment, which didn\u27t consider the speed of the surrounding traffic, the size of the approaching vehicles, or the fact that they could not see beyond impediments in the road. The past researches didn\u27t focus on the speed of the surrounding traffic or the size of the approaching vehicles. Moreover, most of the techniques were based on single agent systems where one agent manages the source vehicle\u27s (autonomous) mobility within its surroundings. This research conducts a feasibility study on a remote Vehicle-to-Vehicle (V2V) communication framework based on Dedicated Short-Range Communication (DSRC) to improve overtaking safety. This work also tries to improve safety by introducing a blockchain-based safety model called BCAS (Blockchain-based Collision Avoidance System). The proposed multi-agent technique strengthens the ability of real-time, high-speed vehicles to make decisions by allocating the total computation of processing responsibilities to each agent. From the experimental results, it is concluded that the proposed approach performs better than existing techniques and efficiently covers the limitations of existing studies
Usability Evaluation of Facebook and Instagram by Visually Impaired People
Get PDFIntroduction/Importance of Study:
Social networking websites have become the main medium for communication, information sharing, entertainment, buying/selling, and various other purposes. People of every age use social networking websites, and their usage is increasing daily, especially in current circumstances. People with different abilities also used social networking websites, but each set of users had their requirements for using these websites. Visually impaired people use computers and the web with the help of screen reading tools e. g.; jaws, and NVDA. Screen reading tools read a web page sequentially, which was a time-consuming process. The major problem with screen reading tools came while reading visual content. Screen reading tools only read the alternate texts of non-visual content behind their tag. This research focuses on the usability of social networking websites for visually impaired people. Two of the most commonly used social networking websites, Facebook and Instagram, were selected for the usability evaluation. Accessibility, efficiency, and effectiveness were the metrics of usability, which were evaluated in this study.
Novelty statement:
A consolidated set of guidelines specific to social networking websites were presented in which some new guidelines were also proposed for Facebook. A mock interface was developed based on the proposed guidelines for Facebook.
Material and Method:
`For the evaluation of usability, a controlled experiment was conducted with 28 visually impaired people in which 16 participants evaluated Facebook and 12 evaluated Instagram to find the usability problems faced by visually impaired people.
Result and Discussion:
Results show that Instagram was as easy to use as compared to Facebook when used by visually impaired people with the help of screen reading tools.
Concluding Remarks:
Results showed that Facebook was difficult to use in comparison to Instagram. Thus, new guidelines were proposed for Facebook, and based on the guidelines, a prototype was proposed
An Automated Framework for Corona Virus Severity Detection using Combination of AlexNet and Faster RCNN
Get PDFCoronavirus has affected daily lives of people all around the globe. Lungs being the respiratory organ are the most affected by such a virus. Alternative techniques for diagnosing the coronavirus involving X-rays and CT scans of the chest have been proposed. The severity of the disease, on the other hand, is a crucial component in the patient\u27s treatment. As a consequence, an automated approach to ascertain the severity of the coronavirus on the lungs is designed to decrease the impacts of the coronavirus on the lungs and practice the right treatment. In this manuscript, we proposed a deep learning-based model for identifying the severity level of coronavirus on the lungs which is further categorized in high, moderate, and low. We employed AlexNet for the disease detection and Faster RCNN for the severity level prediction based on the affected area of the lungs. The evaluation is assessed using X-rays and CT scans of the lungs. Total 1400 images have been employed for the training and performance evaluation of the proposed system. The metrics that we considered for the performance evaluation are accuracy, precision, recall, error rate, and time. The results showed that our proposed model attained about 98.4% accuracy and 98.15% precision.
Full Tex
MODIS-Observed Spatiotemporal Changes in Surface Albedo of Karakoram Glaciers During 2000-2018
Get PDFThe role of albedo is very important in modulating the surface energy balance of glaciers. The main objective of this study is to assess the spatiotemporal variability in surface albedo of the Karakoram glaciers in Pakistan during the summer seasons (June, July and August) for the period from 2000-2018. We used Moderate Resolution Imaging Spectroradiometer (MODIS) data to estimate the amount of glacier surface albedo. We combined the MODIS Terra- and Aqua-derived albedo products to reduce the amount of cloud influence and to improve the estimation of glacier surface albedo. Our results indicate that the average annual decrease in albedo is ~0.041% during the summer. The decrease in albedo was relatively high during recent years, with an annual rate of decrease of ~0.45%. The decreasing trend in albedo is towards the north-western part of the Karakoram mountain range. Climate change is the potential cause of albedo variations in the study area. Albedo has a strong negative correlation with temperature (r = -0.811) and a strong positive correlation with precipitation (r = 0.809). The present study concludes that trend in decreasing albedo is higher during the recent years than the last decade and climate change is playing a vital role in it.
Text Ful
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.
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