International Journal on Recent and Innovation Trends in Computing and Communication
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Exploring Cloud Computing Challenges: A Thorough Examination of Issues in the Cloud Environment
Full text linkCloud computing has evolved into a critical component of contemporary enterprises, providing various advantages including scalability, adaptability, and cost efficiency. However, Cloud Computing also introduces a number of security vulnerabilities that can be exploited by cybercriminals. This article provides an overview of the most common cloud vulnerabilities and their impact on cyber security threats. Among various issues, DDoS issue is very serious, so we identify the causes and issues that address these issues
Visual Eureka Navigating Images Through Textual Queries
Full text linkWithin the domain of text extraction technologies, progress has been somewhat constrained, notwithstanding notable instances such as Google Lens, which proficiently extracts text from images. A conspicuous gap persists, however, in the availability of software tailored for the reciprocal task of searching images based on their textual content. Our pioneering conceptual framework introduces a transformative paradigm shift—a software solution engineered for image retrieval through text search. The crux of our technical innovation lies in the systematic incorporation of metadata as a repository for textual data linked to images. Through advanced text extraction algorithms, including robust optical character recognition methods, we decipher and store relevant textual information in this metadata. This meticulous indexing facilitates a highly efficient search mechanism, allowing users to query images based on specific text-related parameters. The user interface seamlessly integrates these functionalities, providing an intuitive platform for users to input text queries and retrieve images with unprecedented precision. Scalability and performance optimization measures ensure the system's adaptability to growing datasets, promising not only a redefined utility of image search but also a significant advancement in user convenience and operational efficiency within the visual data retrieval landscape
Analysis on Agile Software Development Using Cloud Computing based on Agile Methodology and Scrum Framework
Full text linkThe advent of agile software development processes was a response to the problems with more traditional approaches. Popular agile approaches utilized in software development include Scrum, Extreme Programming, and Kanban.A key component of an Agile methodology is the emphasis on customer-developer cooperation and the promotion of self-organization within development teams. Teams accomplish this by implementing various Agile techniques into their projects. There are teams that stick to a single practice and others that mix it up. Scrum, user stories, pair programming, burndown charts, and stand-ups are the most popular methods. The use of cloud computing has several benefits, including the potential to scale, improve communication, and lower overall costs. Here we take a look at the ADCC framework, which was suggested in a previous study, and see how well it mixes Agile Development with Cloud Computing. In order to put the design into action, the Malaysia Research and Education Network, or MyRen cloud, is used. One way to check the notion is using a case study. Before diving into the case study, participants get a rundown of the ADCC framework. Case study results demonstrate that ADCC framework usage improves agile method performance. Results from both centralized and decentralized agile development environments are used to evaluate the evolution
Design of a Fully Reconfigurable Multifunctional Non-Reciprocal Quise Reflection-Less Interdigital BPF
Full text linkThis paper presents the design, simulation, and measurement of a multifunctional nonreciprocal quasi-reflectionless bandpass filter. Initially, we designed a conventional 5-pole interdigital bandpass filter (BPF). Subsequently, a suitable absorptive component is attached to the conventional interdigital BPF in order to absorb any reflected signals, resulting in the formation of a quasi-reflectionless BPF. One can turn a normal bandpass filter (BPF) into a nonreciprocal BPF by employing the Spatial Temporal Modulation (STM) . In order to obtain a multifunctional bandpass filter, all of these features must be combined into a single filter. Therefore, pin diodes can operate as switches to control the response of multifunctional bandpass filters. The proposed filter can provide multiple response states, including reflective bandpass filters, quasi-reflectionless bandpass filters (with one port and two ports), non-reciprocal bandpass filters, and non-reciprocal quasi-reflectionless bandpass filters. The filter was designed using a Fr4 substrate and a CNC machine. The measured results demonstrate a high level of agreement with the simulated results
The Impact of the Preparation Procedure on the Structural, Optical, And Magnetic Characteristics of Nickel Ferrite Nanoparticles.
Full text linkNanocrystalline NiFe2O4 particles were synthesized using traditional sol-gel, citrate-nitrate sol-gel combustion, and coprecipitation techniques. The synthesized samples underwent annealing at a temperature of 1000 °C for two hours. Subsequently, an investigation was conducted to analyze the structural, chemical, morphological, optical, and magnetic properties of nickel ferrite. The X-ray diffraction (XRD) technique was used to analyze the structural properties, which validated the creation of single-phase NiFe2O4 particles using all three methods. The chemical characteristics were assessed using Fourier transform infrared (FT-IR) spectroscopy, which verified the presence of the correct vibration modes in the samples. The UV-Vis spectroscopy technique was used to investigate the optical characteristics. The as-synthesized materials were analyzed using scanning electron microscopy (SEM) to determine their morphology. The scanning electron microscopy (SEM) scans revealed the presence of clustered nanoparticles of NiFe2O4. The magnetic characteristics were examined using a vibrating sample magnetometer (VSM), which revealed that the calcined samples had characteristic magnetic behavior
An Approach for Reducing the Emergency Vehicle’s Travel Time by Routing
Full text linkIn order to improve the effectiveness of the routing of an emergency vehicle, it is recommended to combine traffic signal preemption with dynamic path planning processes. We construct a graph version of the D*Lite informed search algorithm in order to design ideal routes for the emergency vehicle in a manner that is both efficient and dynamic. This is accomplished by taking into account real-time updates of congestion levels and other delays to travel time. The findings demonstrate that dynamic path planning has the ability to enhance travel time in situations of unpredictable congestion. Furthermore, the incorporation of an appropriate traffic signal preemption mechanism has the potential to further enhance travel time for emergency vehicles, which might possibly save lives
Automated Leukemia Disease Classification using Machine Learning on Microscopic Blood Images
Full text linkLeukemia is a pathology that affects teenagers and adults, which leads to several other symptoms and premature death. Computer-aided system (CAD) is used to assist specialists in the diagnosis of this disease and lower the risk of prescribing improper treatment. Microscopic analysis is an efficient strategy for performing the initial screening of patients with leukemia. This kind of test can be manually done, generating fatigue in operators. Consequently, an economical method that is robust and automatic is needed to prevent the influence of operators. Several CAD systems were designed by using computational intelligence and image processing methods. In this paper, we present an Automated Leukemia Disease Classification utilizing Machine Learning on Microscopic Blood Images (ALDC-MLMBI) method. The ALDC-MLMBI technique aims to employ ML approaches for the identification of leukemia. As a primary step, the ALDC-MLMBI technique follows median filtering (MF) based noise elimination and adaptive histogram equalization (AHE) based contrast enhancement. Besides, the segmentation process can be performed by watershed segmentation. Meanwhile, the ALDC-MLMBI technique involves a set of feature extractors namely local binary pattern (LBP), histogram of gradients (HOG), scale-invariant feature transform (SIFT), and gray level co-occurrence matrix (GLCM). Furthermore, the classification of leukemia can be made by the use random forest (RF) method. The simulation analysis of the ALDC-MLMBI system can be performed using the Kaggle image dataset. The experimental outcomes highlighted the superior performance of the ALDC-MLMBI system compared to existing classifiers
Lattice Boltzmann Simulation of Fluid Flow and Heat Transfer Through Porous Media – A Pore-Scale Approach
Full text linkThe size and arrangement of the obstacles that form in the porous media have an influence on fluid flow and heat transfer., even in the same porosity. To address this issue, the present study simulated three obstacles in both regular and different staggered arrangements through a channel to compare the effect of staggered and regular arrangements, as well as different obstacle positions in the same porosity, on fluid flow and heat transfer. In the present study, the Single Relaxation Time Lattice Boltzmann Method, with Bhatnagar-Gross-Krook (BGK) approximation and D2Q9 model, is implemented for the numerical simulation. The temperature field is modeled using a Double Distribution Function (DDF) approach. Results are presented in terms of velocity and temperature fields, streamlines, percentage of pressure drop and Nusselt number of the obstacles walls. Also, the correlation between tortuosity and Nusselt number of the walls of the obstacles, has been proposed. The results show that by changing the arrangement of the obstacles from regular to staggered, with the same porosity, the Nusselt number of the obstacles increased by up 167%
A Review on Various Sensors Employed for Detecting Adulterants (Urea and Melamine) in Milk and Milk Products
Full text linkFood safety is a critical concern globally, with increasing incidents of adulteration posing a significant threat to public health. Adulteration involves the addition of unauthorized substances to food products, compromising their quality and safety. The use of advanced sensor technologies for the detection of adulterants has gained prominence in recent years. There are various methods for detecting the urea and melamine used as an adulterant in milk but the use of sensor based technology has made it easy, fast, and accurate detection of food adulterants. A wide variety of biosensing approaches for the detection of urea adulteration in milk have been developed in recent years. This review article presents a comprehensive case study on various sensors used for spotting adulterants - Urea and Melamine, in milk and milk products, emphasizing their principles, applications, and effectivenes
Automated Test Case Generation Model from UML Diagrams based on Monotonic Genetic Algorithm
Full text linkThe procedure of developing package includes software testing as an imperative phase. The three components of the testing process are test execution, test evaluation and test case generation. The creation of test cases remains at the heart of challenging automation. It decreases the amount of mistakes and flaws while saving time and effort. A new way to automate the testing process has been developed to reduce the high tot test evaluation al of software testing and to improve the dependability of the testing procedures. In this paper, a innovative technique for creating and refining test cases using UML Activity Chart diagrams is proposed. The Genetic Algorithm's crossover method was used to create the new test sequence, and the test sequences' effectiveness was assessed by Mutation Analysis. As a result, they are unable to effectively combat multilayer perceptrons when faced with incorrect properties. Monotonic genetic algorithm is a Concept that is easy to understand and Supports multi-objective. The radial basis function (RBF) neural network algorithm currently in use has challenges counting the amount of neurons in the hidden layer and has poor weight learning ability from the hidden layer to the output layer. RBF networks have the drawback of giving respectively attribute a comparable weight since all factors are taken into account equally while calculating distance unless the attribute weight parameters are included in the entire optimization procedure