Word spotting of Gujarati handwritten documents is a highly challenging task due to the complexity of the handwritten text in the Gujarati language. This paper presents a novel approach to word spotting, which include...
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Social networks have become essential platforms for information exchange and free expression. However, their open nature also facilitates the spread of harmful content, such as hate speech, cyberbullying, and offensiv...
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Sensors are considered as important elements of electronic *** many applications and service,Wireless Sensor Networks(WSNs)are involved in significant data sharing that are delivered to the sink node in energy efficie...
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Sensors are considered as important elements of electronic *** many applications and service,Wireless Sensor Networks(WSNs)are involved in significant data sharing that are delivered to the sink node in energy efficient man-ner using multi-hop ***,the major challenge in WSN is the nodes are having limited battery resources,it is important to monitor the consumption rate of energy is very much ***,reducing energy con-sumption can increase the network lifetime in effective *** that,clustering methods are widely used for optimizing the rate of energy consumption among the sensor *** that concern,this paper involves in deriving a novel model called Improved Load-Balanced Clustering for Energy-Aware Routing(ILBC-EAR),which mainly concentrates on optimal energy utilization with load-balanced process among cluster heads and member *** providing equal rate of energy consumption among nodes,the dimensions of framed clusters are ***,the model develops a Finest Routing Scheme based on Load-Balanced Clustering to transmit the sensed information to the sink or base *** evaluation results depict that the derived energy aware model attains higher rate of life time than other works and also achieves balanced energy rate among head ***,the model also provides higher throughput and minimal delay in delivering data packets.
As a new and potentially devastating form of cyberattack, ‘Phishing’ URLs pose a risk to users by impersonating legitimate websites in an effort to obtain sensitive information such as usernames, passwords, and fina...
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Identifying languages written in Devanagari script, including Hindi, Marathi, Nepali, Bhojpuri, and Sanskrit, is essential in multilingual contexts but challenging due to the high overlap between these languages. To a...
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Internet of Things (IoT) connects billions of devices and tiny sensors enabled with Low-Power and Lossy Networks (LLNs) to provide real time data transfer. These LLNs work as s backbone of complete IoT ecosystem which...
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Many higher education institutions adapted to the Covid-19 pandemic by switching their teaching into online mode making use of online synchronous sessions using technologies such as Zoom. It was common for lecturers t...
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A smart agricultural informatics platform integrated with Internet of Things (IoT) aims to revolutionize farming practices through a decentralized communication framework, the primary goal is to establish a knowledge-...
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The intend of this literature survey is to lessen the problems faced by dentists in the field of maxillary sinus diagnosis in image processing and to serve as a valuable reference to the literature related application...
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ISBN:
(纸本)9798350372748
The intend of this literature survey is to lessen the problems faced by dentists in the field of maxillary sinus diagnosis in image processing and to serve as a valuable reference to the literature related application. The odontogenic diseases may be diagnosed with atypical symptoms or it might mimic other conditions. This can create difficulty to disembark an accurate diagnosis. Sinusitis or temporomandibular joint disorder possibly is a symptom that resemble an odontogenic infection. Some odontogenic diseases may have overlapping symptoms, making it difficult to differentiate between them when based solely on clinical presentation. For instance, both a periapical abscess and a periodontal abscess can cause localized pain, swelling, and sensitivity. Diagnosing maxillary sinus issues through digital imaging, such as panoramic dental Xray, Cone Beam Computed Tomography (CBCT) and Computed Tomography (CT) scans, can be challenging due to the complex anatomy and the potential for overlapping structures. Radiologists utilize assorted computerized methods for maxillary sinus disease detection. CT scan analysis uses algorithms for segmentation and feature extraction, aiding machine learning algorithms in pattern recognition. CBCT provides detailed three-dimensional images, enabling comprehensive assessments of maxillary sinus anatomy and pathology. MRI utilizes signal intensity variations and texture analysis to identify potential diseases. Moreover, the integration of ultrasound, analysis of endoscopic video, and reporting of automated systems utilizing techniques of deep learning such as Convolutional Neural Networks and Recurrent Neural Networks, enhances precise detection by combining information from various imaging modalities. Interpreting dental radiographs can be complex, and certain conditions may not be clearly visible or may appear differently on different imaging modalities. It requires expertise and experience to accurately interpret radiographic findings and
Ischemic heart disease(IHD)is one of the leading causes of death ***,different geographic regions show different variations of the risk factors of this disease based on the different lifestyles of *** study examines t...
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Ischemic heart disease(IHD)is one of the leading causes of death ***,different geographic regions show different variations of the risk factors of this disease based on the different lifestyles of *** study examines the current IHD condition in southern Bangladesh,a Southeast Asian middle-income *** main approach to this research is an Al-based proposal of a reduced set of the greatest impact clinical traits that may cause *** approach attempts to reduce IHD morbidity and mortality by early detection of risk factors using the reduced set of clinical ***,diagnostic,and symptomatic features were considered for analysing this clinical *** pre-processing utilizes several machine learning techniques to select significant features and make meaningful interpretations.A proposed voting mechanism ranked the selected 138 features by their impact *** this regard,diverse patterns in correlations with variables,including age,sex,career,family history,obesity,etc.,were calculated and explained in terms of voting *** the 138 risk factors,three labels were categorized:high-risk,medium-risk,and low-risk features;19 features were regarded as high,25 were medium,and 94 were considered low impactful *** research's technological methodology and practical goals provide an innovative and resilient framework for addressing IHD,especially in less developed cities and townships of Bangladesh,where the general population's socioeconomic conditions are often *** data collection,pre-processing,and use of this study's complete and comprehensive IHD patient dataset is another innovative *** believe that other relevant research initiatives will benefit from this work.
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