International Research Journal on Advanced Science Hub最新文献

{"title":"Medicated ointments: Methods of preparation, Mode of Action, Physico chemical characteristics- An overview","authors":"Hari Prasad P M, S. R. Manohar, Aleena Najeeb, Z. S. Pillai","doi":"10.47392/irjash.2023.056","DOIUrl":"https://doi.org/10.47392/irjash.2023.056","url":null,"abstract":"Skin protects our body against the entry of microorganisms as well as serves as a barrier to loss of salts, body fluids and maintains our body temperature. The need for efficient drug delivery system through the skin is essential to reduce systemic toxicity. This has been achieved to a certain extent by the advent of oinments/ malahara (as has been coined in Ayurveda). This review provides a detailed overview on the preparation, properties, mode of action and therapeutic use of oinments/malahara/malham in the treatment of various skin disorders. Though there are articles published on ointments and Malahara separately, a review connecting the herbal ointments to Malahara has never been done before. This article aims to fill that gap","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125443013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of Factors Affecting Sustainable Performance Using PLS-SEM Method and IPMA Chart: A Case Study in Vietnam","authors":"Minh Ly, Dang Thi Lam, Le Thi Bich Tram, Le Thi Huyen Tran Le, Minh Ly Duc","doi":"10.47392/irjash.2023.058","DOIUrl":"https://doi.org/10.47392/irjash.2023.058","url":null,"abstract":"In a dynamic world, understanding the indirect impacts of green strategies on a company’s sustainable performance through corporate social responsibility and green innovation is essential for the environmental management of the workplace. This paper proposes a conceptual SEM model for examining the mediating role of corporate social responsibility and green innovation on the relationship between green strategies and the sustainable performance of manufacturers and Importance-Performance Map Analysis (IPMA) represents the independent variables acting on the same dependent variable on the graph with one axis being performance, the other being importance. The findings indicated that corporate social responsibility and green innovation play significant mediating roles in the linkage between green strategy and sustainable performance, as well as positively influencing sustainable performance. In this study, we surveyed managers and directors of 432 publicly listed manufacturers in Vietnam; their responses were used to conduct hypotheses tests regarding the relationships among corporate social responsibility, green innovation","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133525010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Smart CCTV Detection Using Local Binary Pattern Histogram (LBPH)","authors":"Deepak Sharma, Brajesh Kumar Singh","doi":"10.47392/irjash.2023.055","DOIUrl":"https://doi.org/10.47392/irjash.2023.055","url":null,"abstract":"Smart CCTV Detection Using Local Binary Pattern Histogram (LBPH) is a computer vision technique used to improve the accuracy of object detection in video surveillance. This approach uses the LBPH algorithm with the accuracy of 97.56% to extract features from image frames captured by CCTV cameras. The LBPH algorithm is a texture-based feature extraction method that is robust to illumination changes and is capable of detecting local patterns within an image.The proposed system consists of three main stages: preprocessing, feature extraction, and classification. In the preprocessing stage, the input image is preprocessed to enhance its quality and reduce noise. In the feature extraction stage, the LBPH algorithm is applied to the preprocessed image to extract texture features. Finally, in this study, the structural similarity index and the LBPH algorithm are proposed as Smart CCTV with intrusion detection [1]. CCTV cameras record real-time video and analyses it as it is recorded, using intrusion detection to locate illegal individuals entering our monitoring area. Experimental findings demonstrate that the suggested system achieves 97.56% high accuracy in object detection compared to existing methods. This technique has potential applications in various fields such as surveillance, security, and traffic monitoring .","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126271299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing Face Mask Detection Using Convolutional Neural Networks: A Comparative Study","authors":"Shakti Punj, Lavkush Sharma, B. K. Singh","doi":"10.47392/irjash.2023.054","DOIUrl":"https://doi.org/10.47392/irjash.2023.054","url":null,"abstract":"Detecting face masks is essential for maintaining public safety and preventing the spread of contagious illnesses. In this article, we give a thorough investigation into how Convolutional Neural Networks (CNNs) may improve face mask identification. The goal of this work is to provide a reliable and robust CNN-based method for identifying people who are wearing masks in practical situations. We start by outlining the CNN architecture, which has a sequential structure made up of convolutional layers, activation functions, pooling layers, and fully linked layers, and is utilized for facemask identification. The architecture is made to recognize masked and unmasked faces with accuracy and learn hierarchical representations of input photos. Layers are pooled for downsampling, fully linked layers are used for high-level representations, and activation functions are used to induce non-linearities. We use a number of measures, including accuracy, precision, recall, and F1-score, to assess the performance of our CNN model. The accuracy of our experimental findings is encouraging, with a 95% overall accuracy in identifying people wearing masks. The accuracy in accurately detecting both positive and negative cases is balanced, as seen by the precision and recall values, which are determined to be 92% and 96%, respectively. We also assess the model’s effectiveness in other scenarios, such as those involving several people spread out across a wide area. Our findings show that even when people are at different distances from one another, there is constant performance with a high accuracy rate of above 90%. This demonstrates the model’s capacity to identify masks regardless of the distance that people are from the camera. We compare the performance of our CNN-based approach to current mask recognition algorithms and show how it outperforms them, outperforming more conventional approaches that generally had accuracy levels of 70–80%.","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"163 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125927018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IEEE 802.15.4 Cluster Analysis With Different DRA & TDMA Wireless Models","authors":"Sukhvinder Singh Bamber","doi":"10.47392/irjash.2023.053","DOIUrl":"https://doi.org/10.47392/irjash.2023.053","url":null,"abstract":"This paper presents the IEEE 802.15.4 clustered Wireless Personal Area Network (WPAN) Sensor Network for different DRA (Dielectric Resonator Anten-nae) and TDMA (Time Division Multiple Access) wireless T x / R x models. Implementing Non-beacon enabled mode in mobile and static Zigbee nodes in the WPAN network and then analyzing: throughput, delay, load, packets sent, packets received, packets dropped etc. proved that DRA model produces enhanced performance in IEEE 802.15.4 WPAN as compared to TDMA model both for mobile and static nodes in the WPAN sensor network. The major reason is less load generated and high PDR (Packet Drop Ratio) of TDMA which leads to a smaller number of packets received and low throughput whereas DRA T x /R x models provides very less PDR and high load and throughput in comparison. Also, it has been simulatively proved that TDMA models do works better for static Zigbee network then mobile Zigbee network but still not equivalent or close alternative of DRA models.","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117298363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Consumer Awareness for Ayurvedic Skin Care Products","authors":"Nalina K B, Aruna Adarsh, Abhilash Puttabuddhi","doi":"10.47392/irjash.2023.052","DOIUrl":"https://doi.org/10.47392/irjash.2023.052","url":null,"abstract":"This research paper delves into the awareness and perceived effectiveness of Ayurvedic medicines among the Indian diaspora. Additionally, it explores the underlying factors that shape the mentality of Indian consumers and influence their buying behavior in the context of Ayurvedic products, with a specific focus on skincare products. The study adopts a holistic approach to examine the level of awareness and attitude of consumers toward Ayurvedic skincare products. Employing a descriptive research design, the paper aims to identify the demographic characteristics of consumers of Ayurvedic skincare products in Karnataka, India. Data collection is carried out using stratified sampling, ensuring representative insights from diverse consumer segments. A 5-point Likert scale is utilized for data gathering, allowing for nuanced assessments of consumer perceptions. Both primary and secondary data sources are lever-aged for comprehensive analysis. Findings from the data analysis revealed that consumers’ purchase behavior is influenced by various factors, including family preferences, pricing considerations, product ingredients, and the influence of advertisements. Interestingly, the study uncovers that consumers display limited knowledge about Ayurvedic skincare products, leading them to rely heavily on the aforementioned factors while making purchase decisions. An intriguing suggestion emerges from the younger cohort of consumers who advocate for the establishment of a regulatory body to study the effectiveness of Ayurvedic skincare products. This proposal aims to verify the claims made by manufacturers regarding the efficacy of their products, even though Ayurveda is deeply rooted in India’s traditional healthcare system. Overall, this research paper offers valuable insights into the awareness, attitude, and buying behavior of Indian consumers towards Ayurvedic skincare products, shedding light on the dynamic factors that shape their preferences and decisions. The study’s implications hold significance for marketers and policymakers seeking to better understand and cater to the needs of the Indian skincare market","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129061259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Review - Smoke-Fire Detection and YOLO (You Only Look Once)","authors":"Sirajudeen S, S. S","doi":"10.47392/irjash.2023.051","DOIUrl":"https://doi.org/10.47392/irjash.2023.051","url":null,"abstract":"","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128765714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SBK: A Framework for Performance Benchmarking for a Variety of Storage Systems","authors":"Sanjay Kumar N V, Keshava Munegowda","doi":"10.47392/irjash.2023.047","DOIUrl":"https://doi.org/10.47392/irjash.2023.047","url":null,"abstract":"Benchmarking storage systems at scale can be challenging, Within the realm of big data, performance stands out as a significant challenge. Proper storage and maintenance of big data are crucial in order to guarantee accessibility, achieve cost savings, enhance risk management, and gain a deeper comprehension of customer needs. This paper addresses the challenges faced in managing extensive and rapidly growing data volumes and to place importance on maintaining optimal storage performance. The SBK framework is containerized and vendor-neutral, making it easy to use and deploy. A software benchmarking framework designed to evaluate the performance of any storage system inclusive of all types data/payload. This paper demonstrates the use of SBK in benchmarking and to highlight the relevance of benchmark testing in evaluating the storage performance. SBK aims to provide transparency and ease of use for benchmarking purposes. This framework functions correctly with different hardware configurations, operating systems, and software environments.","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115148533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Feature Extraction from Brain MR Images for Detecting Brain Tumor using Deep Learning Techniques","authors":"Hanumanthappa S, Guruprakash C D","doi":"10.47392/irjash.2023.049","DOIUrl":"https://doi.org/10.47392/irjash.2023.049","url":null,"abstract":"Detection of a brain tumor due to their intricacy, the irregularity of their tumor formations, and the variety of their tissue textures and forms, gliomas provide a difficult problem for medical image interpretation. Machine learning-based approaches to semantic segmentation have consistently surpassed earlier techniques in this difficult challenge. However some of the Machine learning techniques are unable to deliver the necessary local information associated to changes in tissue texture brought on by tumor development. In this study, we used Hybrid technique that combines supervised learning features and hand-crafted features. The texture features based on the grey level co-occurrence matrix (GLCM) are used to build the hand-crafted features. The recommended technique also lowers the intensity of nearby unimportant areas and only the region of interest (ROI) method is used, which precisely represents the input size of the entire tumor structure. ROI MRI scan pixels are divided into several tumor components using a decision tree (DT).","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127345289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Improved Data Aggregation Method to Minimize The Energy Consumption and Increase Life Time In WSN","authors":"R. M, Lochanambal K P","doi":"10.47392/irjash.2023.048","DOIUrl":"https://doi.org/10.47392/irjash.2023.048","url":null,"abstract":"Many applications exist for WSN, including but not limited to environmental monitoring, exploration, and military surveillance. When data relevant to several applications is gathered by the WSN’s nodes and sent to the sink, it may be analysed and repurposed. Sensing data is often sent from the sensor to the sink via multi-hop routing. To identify the network event, the sink stores the data in a database, processes it using control instructions, and then assesses the results. (Wu, Lee, and Chung) Data aggregation reduces the amount of data that must be sent by processing data locally inside the network.This paper suggested clustering method called ”Improved Data Accumulation Clustering (IDAC)” emphasises the formation of clusters with the goals of load balancing and lifespan extension for the network. First, the cluster heads are selected depending on their distance from the hub. The base station is located outside the sensing area. At initially, we feed each sensor the same amount of energy. All sensors can simultaneously gather data and it has been send to hub. The BS is aware of the positions of every sensor node, also nodes at top level of cluster have communication capabilities. cluster head probability is denoted by the symbol p. Once a node has served as cluster leader for 1/p rounds, it may serve in that capacity again. Initial node energy levels are represented by the symbol Emax.","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"246 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123010806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}