International Journal of Communication Networks and Information Security (IJCNIS)
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1021 research outputs found
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Localized Modeling for Airline Price Prediction Using K-Means and Decision Tree Ensemble
No full textBoth travelers and airline companies rely on accurate prediction of flight prices, nevertheless it is difficult to train machine learning models using large-scale, current flight datasets due to computational inefficiency and risk of overfitting. This paper introduces a novel two-pronged approach that combines K-means clustering with decision trees for effective localized flight price forecasting. First, K-means clustering is employed to segment the flight data on the basis of shared characteristics into meaningful clusters thereby reducing data dimensionality and speeding up model training. Then individual Decision Tree models are built for each cluster separately. Finally, this technique emphasizes on closely related data attributes which may enhance predictive accuracy for given routes or types of flights. The proposed method solves the problem of calculation load when working with large datasets without sacrificing any details necessary for catching peculiarities in pricing in various categories of flights
Exploring Serverless Security: Identifying Security Risks and Implementing Best Practices
No full textServerless computing has emerged as atransformative paradigm in cloud computing,offering significant benefits such as reducedoperational costs, enhanced scalability, andincreased developer productivity. However,the adoption of serverless architecturesintroduces novel security challenges that differsubstantially from traditional applicationsecurity models. This comprehensive researchpaper delves into the security landscape ofserverless computing, meticulously identifyingprevalent security risks and proposing robustbest practices for mitigating these risks. Bythoroughly examining key components ofserverless platforms, analyzing commonvulnerabilities, and discussing effectivesecurity strategies, this study aims to provide adetailed understanding of serverless securityand guide organizations in implementingcomprehensive security measures for theirserverless applications. The research drawsupon the latest findings and expert insightsavailable, offering a timely and relevantanalysis of this rapidly evolving field
Zooming in with Family: The Function of Network Communication as a Social Care for Nursing Students Emotional and Academic Stress during the COVID-19 Pandemic
No full textThere were significant changes during the COVID-19 quarantine period, regardless of gender, age, culture, or even nationality; everyone followed the health precautions to avoid contracting the virus. The majority, particularly the youngsters whose daily routines and way of life had completely changed, found it difficult to accept these changes. This study aimed to determine how the COVID-19 pandemic affected nursing students' ability to manage their emotional and academic stress through network communication. A phenomenological qualitative research design was employed in this study. The participants of the study are the fifteen (15) junior high school students of the school year 2022-2023. The students are from ages 13 to 17 years old. Thus, this study has explored the live experiences of these teenagers and adolescents during the quarantine period due to the COVID-19 pandemic. This study has employed purposive sampling. The results revealed that information networks helped the nursing students cope with their emotional and academic stress. Thus, many ICTs play a role in family communication and feelings of connectedness. The concept of connected learning values relationships when the individual explores interests using technology. Parents can function as “learning heroes” and facilitate children’s learning beyond the classroom
Impact of Coiflet Wavelet Decomposition on Forecasting Accuracy: Shifts in ARIMA and Exponential Smoothing Performance
No full textAccurate forecasting of electricity demand is crucial for effectiveenergy management and resource planning. Recently, time seriesforecasting methods such as Exponential Smoothing (ES) andARIMA models have gained popularity due to their ability to detectintricate seasonal patterns in data. This study examines howvarious wavelet families, particularly the Coiflet wavelet, impact theperformance of ES and ARIMA models in forecasting electricitydemand. We observed that applying the Coiflet wavelet couldsignificantly enhance forecasting outcomes. The study evaluates theeffectiveness of different wavelets in improving the forecastingaccuracy of ES and ARIMA models, with a particular focus on thesuperior performance of Coiflet wavelets. Our findings offerinsights into the suitability of wavelet-based methods for electricitydemand forecasting. Nonetheless, the choice between ARIMA andExponential Smoothing should be guided by the specificcharacteristics of the time series data and forecasting goals. Forcomplex and noisy data, ARIMA combined with Coiflet waveletpreprocessing proves to be a robust and effective forecastingapproach, demonstrating superior performance in our analysis
Strategies to Solve People’s Poverty Sustainable with the Power House-Temple-Government of Banmai Subdistrict, Admnistrative Organization, Maharat District, Phra Nakhon Si Ayutthaya Province
No full textThe purposes of this study were to study 1) To study the factorsaffecting the poverty problem of people in the area of BanmaiSubdistrict Administrative Organization, Maharat District, PhraNakhon Si Ayutthaya Province.2) To create Strategies to SolvePeople's Poverty Sustainable with the Power House -Temple –Government of the Banmai Subdistrict AdministrativeOrganization, Maharat District, Phra Nakhon Si AyutthayaProvince. 3) To evaluate the implementation ofStrategies to SolvePeople's Poverty Sustainable with the Power House -Temple –Government of the Banmai Subdistrict AdministrativeOrganization, Maharat District, Phra Nakhon Si AyutthayaProvince. This research methodologies were quantitativeresearch and qualitative research. The sample group used in thequantitative research consisted of 400 people.The sample groupsused in the qualitative researchhave three groups. 1)representative from home 17 populations. 2) representative fromtemple5 populations. 3) representative from government 5populations, by cluster sampling. The tool used in quantitativeresearch was a questionnaire. Tools used in qualitative researchwas an interview. The quantitative data were analyzed bysoftware package. Statistics used for data analysis werepercentage, mean, standard deviation, andt-test.The results of research found that 1. The results of thequantitative research found that the factors affecting the povertyproblem of people in the area of the Banmai SubdistrictAdministrative Organization, Maharat District, Phra Nakhon SiAyutthaya Province as a whole were at a moderate level.Whenconsidering each aspect, it was found to be at a moderate level inall 5 areas, arranged in order of average from highest tolowest.First are economic factors, followed by personal factors.Psychological factors Social factors and the least is a factor of government policy.2.Strategies to Solve People'sPoverty Sustainable with thePower House -Temple –Government of the BanmaiSubdistrict AdministrativeOrganization, MaharatDistrict, Phra Nakhon SiAyutthaya Province were 1)Philosophy of sufficiencyeconomy.2) Exploring indepthinformation in everydimension.3) Defining thetarget group clearly.4)Adding knowledge by goingon study tours.5) Promotingadditional careers toincrease income.6) Productmarketing promotion.7)Creating community kitchenlogistics for the welfare ofthe elderly.8) Creating aFDA Standard Central Kitchen,1 subdistrict, 1 central kitchen. 9)Development of local food toglobal food.10) Development of OneSubdistrict, One Team, OTOP Community.3. Evaluation of theimplementation of the strategy for solving people's poverty issuessustainably with the power House-Temple–Government by theBanmai Subdistrict Administrative Organization, MaharatDistrict, Phra Nakhon Si Ayutthaya Province. They were 1) Thestrength or advantage is that it stimulates the community to gainexperience in analyzing the poverty problem in the communityitself, making them more aware of themselves. 2) Theweaknesses or disadvantages are that people still have opposingattitudes and lack of continuity in leadership. Strategies forsolving people's poverty problems sustainably with the power ofimplementation. 3) The opportunity: This strategy has apossibility of being developed further. 4) The obstacleis the factthat some people do not understand the process of solvingpeople's poverty problems sustainably with the power ofBuddhism
MFHO-An Approach for Vehicle Image Enhancement
No full textThe role of image enhancement is crucial for the processing of images to enhance their quality. Image pre-processing is essential in gathering precise data when detecting any vehicle using its license plate. It requires a method to improve the images to help the persons detect any vehicle and reach the vehicle's owner easily. However most state-of-the-art methods induce different types of distortion such as intensity shift, wash-out, noise and intensity saturation. For this purpose, in this paper, a meta heuristic Modified Fire Hawks optimizer technique has been introduced, which is used to optimize the parameter of Bi-Histogram Equalization with the Adaptive Sigmoid Function method. The pixel and graphic quality of the images are improved with this new technique. Mean square error (MSE), Peak Signal-to-Noise Ratio (PSNR), Mean Absolute Error(MAE), Structural Similarity Index Metric(SSIM), and Absolute Mean Brightness Error(AMBE) are the metrics applied in this paper to check the quality of the processed images. In this paper, main objective of work is to improve the image quality of vehicles and enhancing the image without distortion. This paper is organized in different sections. Section 1 is the introduction section. In section 2, Literature review is presented in which all recent works related to the topic are studied thoroughly. Section 3 describes the methodologies used for the purpose so far and proposed methodology. In section 4, results are shown and compared with the previous results The results of the proposed method are comparatively better than the other state-of-the-art methods for detecting any number of vehicle images. Section 5 is the discussion section in which quantative and qualitative assessments is being done. Section 6 briefs the paper and focus on future scope and section 7 describes the various references used for the paper
Harnessing Deep Learning for Precision Tree Extraction in ArcGIS Pro
No full textThe fields of environmental management and geographic analysis have been completely transformed by the incorporation of deep learning techniques with Geographic Information Systems (GIS). In this thesis, ArcGIS Pro is used to investigate the use of deep learning techniques, specifically the Single Shot MultiBox Detector (SSD), for tree extraction in urban settings. The focus of the assessment of the SSD model's accuracy and dependability in tree identification from aerial photography is the study region of Pekan, Malaysia. cc Analyses conducted in comparison with alternative object identification algorithms, such as FCN and R-CNN, demonstrate how much faster, more accurate, and more efficient SSD is. The findings show that the SSD model can effectively identify trees while reducing false positives and false negatives, with high precision and recall rates reaching over 90%. The model's efficacy is further supported by the IoU metric, which shows a noteworthy degree of spatial alignment and precision between predicted and ground truth bounding boxes. Visual interpretations give specific instances of how accurately SSD can identify trees; these include bounding box visualisations and confusion matrices. Enhancing dataset augmentation and diversity, connecting SSD with GIS platforms for smooth data analysis, and offering user training and capacity-building activities are among the recommendations for future research and development. Sustainable urban development methods and automated tree recognition systems require cooperation and knowledge exchange among researchers, practitioners, and policymakers. Together deep learning and ArcGIS Pro integration provides a strong toolkit for environmental monitoring and tree extraction in urban settings like Pekan, Malaysia. With its exceptional precision, efficacy, and adaptability, the SSD model is a mainstay of automated tree recognition systems, opening the door to well-informed choices and environmentally sound practices
The Advances in the Security of Cloud Services using Customer Master Encryption Keys (CMEK)
No full textThis research paper examines the role of Customer-Managed Encryption Keys (CMEK) in enhancing security for cloud services. As organizations increasingly migrate their data and operations to the cloud, concerns about data privacy and security have become paramount. CMEK offers a solution by allowing customers to retain control over their encryption keys while leveraging cloud infrastructure. This study explores the architecture, implementation, and implications of CMEK across various cloud service models. It analyzes cryptographic techniques, performance considerations, security challenges, and compliance requirements associated with CMEK. The research also delves into advanced concepts and future directions, including homomorphic encryption and blockchain-based key management. By synthesizing current literature and industry practices, this paper provides a comprehensive overview of CMEK and its potential to revolutionize cloud security
FORECASTING INDIA’S GDP USING ARIMA: FACTORS CONTRIBUTING TO INDIA’S GROWTH
No full textIndia is poised to reach the ambitious target of becoming a USD 5 trillion economy by 2027 and become the third largest economy of the world by 2032. This trajectory is fuelled by a youthful population, a burgeoning middle class, and robust digital infrastructure. Indian Prime Minister, Narendra Modi, has built his global image with political astuteness, emphasising multilateralism and the rule of law. However, in a world, where nationalism, egotism and authoritarianism are on the rise, India faces a challenging task as a global leader in maintaining world peace, contain global wars and coax others countries to play by the book. India may need to recalibrate its foreign policy in order to align its global political ambitions with its growing economic targets. This paper looks at the factors that have contributed to India’s economic growth and its growing international stature. ARIMA (Auto-Regressive Integrated Moving Average) technique has been applied to forecast the GDP growth rates of India until 2035. India is projected to reach a GDP of USD 7 trillion during this period. The paper concludes that with economic growth, India is also likely to increase its influence as a global leader
Detection Protocol for the Five Variants of Selective Forwarding Attack in the Internet of Things
No full textRPL (Routing Protocol for Low power and lossy networks), the most widely used routing protocol in the Internet of Things, has numerous security vulnerabilities. These make it particularly susceptible to selective forwarding attacks. This work aims to add a scalable, fast, and accurate detection process to RPL for the five variants of this attack, regardless of the type of data collected. To this end, each node is constantly evaluated by its neighbors. Packets routing is modeled as a maximum flow problem, which allows for the prediction of maximum throughput and average delivery delay. By comparing these indicators to the node’s actual performance, each neighbor estimates a trust level. The node's final status is determined through feedback from the neighbors, following an approach inspired by Dempster-Shafer theory. Simulation showed thattheproposed scheme is precise, energy-efficient, and outperforms similar recent state-of-the-art contributions