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Analysis Machine Learning Based Human Health Lung Cancer Detection

Analysis Machine Learning Based Human Health Lung Cancer Det...

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international conference of Electronics, Communication and Aerospace technology (ICECA)

作者： Asha V A. Saravanan A. Anitha Nuzhat Fatima Rizvi Aarti Kalnawat G. Murugesan New Horizon College of Engineering Bangalore Karnataka India Department of Management Studies S.A.Engineering College( Autonomous) Chennai -77 ECE Department CVR College Of Engineering Telangana Symbiosis International (Deemed) University Pune India Department of Management Studies Vinayaka Mission's Kirupananda Variyar Engineering College Vinayaka Mission's Research Foundation Deemed to be University Salem India

the information shows that there were 2.2 million new belongings of lung cancer in *** quantity is still rising yearly. As a result, it has become an extremely significant issue how to identify the sickness in time. Based on the proposed VGG16 Convolutional Neural Network (CNN), research created a neural network. the trained model to divide the computed tomography (CT) scan descriptions of lung cancer into four categories. To avoid over fitting, added to the dataset using random cropping, flipping, etc. from the Kaggle database. the trained model was then combined with a chatbot and graphical user interface. More specifically, created the user interface and implemented it on a website using the Django frameworks and MySQL database. Also, included certain Natural language processing (NLP) tools in the chatbot, including decision trees and Name Entity Recognition (NER). the results of the tests show that neural network performs well. Also, user interface will make it easier for folks who are not familiar with deep learning to understand the conditions.

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Investigating the Dynamic Decision Mechanisms of Users' Relevance Judgment for information Retrieval via Log Analysis 15th

Investigating the Dynamic Decision Mechanisms of Users' Rele...

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15th Pacific Rim international conference on Artificial Intelligence (PRICAI) / 15th Pacific Rim Knowledge Acquisition Workshop (PKAW)

作者： Su, Yi Li, Jingfei Song, Dawei Zhang, Pengqing Zhang, Yazhou Tianjin Univ Sch Comp Sci & Technol 135 Yaguan Rd Tianjin 300350 Peoples R China Coordinat Ctr China Natl Comp Network Emergency Response Tech Team 3A Yumin Rd Beijing 100020 Peoples R China Beijing Inst Technol Sch Comp Sci & Technol 5 South Zhongguancun St Beijing 100081 Peoples R China Open Univ Sch Comp & Commun Walton Hall Milton Keynes MK7 6AA Bucks England

ISBN: (纸本)9783319973043;9783319973036

Measuring relevance of documents with respect to a user's query is at the heart of information retrieval ( IR), where the user's relevance judgment criteria have been recognized as multi-dimensional. A set of relevance dimensions that are considered as critical factors in document relevance judgment have been investigated, such as topicality, novelty, and reliability. However, most existing work focuses on individual relevance dimensions, yet neglecting how different dimensions would interact with each other to influence the overall relevance judgment in real-world search scenarios. this paper aims at an initial step to fill the gap. Specifically, we divide 7 relevance dimensions in an enriched Multidimensional User Relevance Model ( MURM) into three categories according to three main requirements for document relevance, i.e., document content requirement, document quality requirement and personalization requirement. We then exploit the Learning to Rank framework to conduct document ranking experiments on a query log dataset from a prominent search engine. the experimental results indicate the existence of an order effect between different dimensions, and suggest that considering different dimensions across categories in different orders for document relevance judgment could lead to distinct search results. Our findings provide valuable insights to build more intelligent and user-centric information retrieval systems, and potentially benefit other natural language processing tasks that involve decision making from multiple perspectives.

关键词： information retrieval User relevance dimensions Order effect

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Problems of introducing information technologies in practice of psychiatric service

Problems of introducing information technologies in practice...

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international conference on information, Intelligence, Systems and Applications (IISA)

作者： Nazim Y. Orudjev Olga V. Poplavskaya Lev B. Lempert Natalia A. Salnikova Marina B. Kultsova Volgograd State Medical University Volgograd Russia Volgograd Branch of the Russian Presidential Academy of National Economy and Public Administration Volgograd Russia Volgograd State Technical University Russia Volgograd Russia

ISBN: (纸本)9781509034307

Efficiency of the organization of psychiatric care increases when usage of information technologies intensifies, and interaction of various institutions providing psychiatric care improves. Development and improvement of electronic forms of medical documentation, automation of the psychiatrist's workplace, data transmission using protected information channels provide continuity in mental health care providing. However, informatization of medicine in some cases assumes a basic change of doctor's work technology, algorithms, techniques of collecting and processing information, and decision-making. For the purpose of studying doctors' readiness for work in this direction, we analyzed opinions of the practicing psychiatrists. Also integrity of using all opportunities for application of information technologies in psychiatric practice was investigated, data on integration of psychiatric community in use of information technologies at the present stage were compared, dynamics of process was estimated. Poll data of 100 psychiatrists working in out-patient and stationary facilities of Volgograd city have been used for research. Conclusions are drawn on the perspective directions of interdepartmental cooperation of medical psychiatric community and professionals of information technologies: development of high-quality Russian-language software for patients' electronic diaries, the multi-purpose automated questionnaire for a complex of organizational and methodical actions for carrying out routine inspections at the new technological level, creation and improvement of a medical information network for psychiatric service. the fastest introduction of the information technologies facilitating control and supervision of separate groups of the patients, for example, follow up the dispensary supervision (DS), carrying out the medical commissions, training, remote supervision for the areas of region and also for ensuring the principle of continuity in psychiatric practice is espec

关键词： Medical services information technology Medical diagnostic imaging Psychiatry Computers Documentation Employment

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the Design of an 8-Bit CISC CPU Based on FPGA

The Design of an 8-Bit CISC CPU Based on FPGA

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international conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Yunjie Zhang Lei Bao Electronic & Information Engineering Department Tianjin Institute of Urban Construction Tianjin China

With the development of FPGA, the design of digital electronic circuits has entered a new era, which make it possible for designers to customize their own special CPU. So it is a great significance to design an economic and applicable CPU core based on FPGA for the cost reduction and the possession of intellectual property. Based on the relevant knowledge on the principles of computer composition, the paper designed and implemented an 8-bit CISC CPU by using top-down approach, completed all of the functional modules using the hardware description language VHDL and EDA technology. It is designed, compiled and simulated under the integrated development environment of Quartus II, and after that it is downloaded to the FPGA experimental platform for units and system testing. Finally, the validity of the design was verified and the simulation result of test program for the designed CPU is presented. the experiment result shows that the functional modules are successful in performing their individual functions, and the CPU as a whole can correctly execute all of the instructions. thereby, it proves to achieve the goal as formerly designed. the research of this paper makes contributions to the design of the more complex CPU based on FPGA and readers may refer to it according to their demands.

关键词： Field programmable gate arrays Random access memory Central processing Unit Computers Timing Registers Hardware

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Semantic CIM2Matpower: Ontology-Based Network Topology Processor and Converter for CIM Node-Breaker Models

Semantic CIM2Matpower: Ontology-Based Network Topology Proce...

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IEEE international conference on Smart Energy Grid Engineering (SEGE)

作者： Artem Schumilin Hüseyin Kemal Çakmak Karl-Uwe Stucky Clemens Duepmeier Veit Hagenmeyer Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Eggenstein-Leopoldshafen Germany

Smart electricity grids are key to a successful transition towards a future sustainable energy system. Network topology processing (NTP) is an important and frequently reoccurring task in most power grid analysis and simulation applications' including power flow calculations, short circuit and contingency analysis. NTP is applied to a detailed node-break-er representation of the power grid, as provided by the IEC Common information Model (CIM). It is performed in order to obtain a reduced bus-branch representation, which serves as input to downstream analysis and simulation applications. the present paper introduces a novel approach to NTP that utilises a semantic knowledge base for network model management and exploits semantic reasoning over the formal CIM ontology and instance data. the proposed system is tested on publicly available ENTSO-E data, validated by converting the generated bus-branch model to Matpower and running power flow calculations in a power grid modelling and simulation framework.

关键词： Semantics Data models Load modeling Unified modeling language Ontologies Switches Power grids

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Product Negotiation in E-Commerce website using Chatbot

Product Negotiation in E-Commerce Website using Chatbot

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international conference on Computing Methodologies and Communication (ICCMC)

作者： Palleti Divya Sree Manohar Raj Kokkiligadda Jagannadham Teja Yelisetti Sandeep Department of Information Technology Velagapudi Ramakrishna Siddhartha Engineering College Vijayawada India

Real-world transactions always include some amount of negotiation. the only goal of negotiations is to engage in bartering. Every important business deal, including buying food from a street vendor, requires it. this suggestion will be used for an e-commerce chatbot to assist in bargaining the cost of the merchandise. Consumer feedback and occasional reviews are the two most common techniques used to track customer satisfaction. the sellers found it difficult and practically impossible to conclude any bargaining process. A chatbot system is necessary to improve client satisfaction and negotiating effectiveness. In this research work, an intelligent chatbot system was used to generate responses based on the user's purpose. Here, the main objective is to increase the effectiveness of online shopping. therefore, to make purchasing easier, chatbots are used to communicate with sellers and negotiate prices. the chatbots will be preprogrammed with the possible questionnaire that could be possibly asked by a customer. Based on the intents that are expressed by the customer, the bot can classify them into entities. this approach includes Natural language processing (NLP) for the better understanding of chatbot framework.

关键词： Costs IEEE merchandise Customer satisfaction Chatbots Electronic commerce Standards Business

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MD16: DSP with some RISC features for embedded system

MD16: DSP with some RISC features for embedded system

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international conference on Signal processing Proceedings (ICSP)

作者： Jicheng Chen Qingdong Yao Peng Liu Ce Chi Department of Information Science and Electronic Engineering Zhejiang University Hangzhou China Zhejiang University Hangzhou Zhejiang CN Dept. of Inf. Sci. & Electron. Eng. Zhejiang Univ. Hangzhou China

To achieve the high performance/cost ratio, the idea of combining the advantages of DSP and RISC in a single architecture is a solution for the booming and versatile embedded application systems. the existent methods that appear in many literatures all focus on the construction of mixed architecture with RISC basement. Contrary to the above, a new idea of constructing architecture with DSP basement and supplementing it with some RISC features is put up in this paper. It can exert the advantages of DSP architecture by instruction level parallelization and powerful memory access capability, and obtain RISC good high-level language support by the manners of local-homogenous register set and RISC-like pipeline. To accelerate the DSP design and optimize the system, integrated design system (IDS) is presented to complete the hardware/software co-design and co-validation. Application programs can also be rapidly developed based on the integrated development environment (IDF). the behavior level simulation of the DSP system has been completed. It is given as 150 MIPS under the condition of 0.18 /spl mu/m technology library. FPGA validation is also accomplished.

关键词： Digital signal processing Reduced instruction set computing Embedded system Costs Computer architecture High level languages Registers Pipelines Acceleration Design optimization

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the Use of Distributed processing and Cloud Computing in Agricultural Decision-Making Support Systems

The Use of Distributed Processing and Cloud Computing in Agr...

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IEEE international conference on Cloud Computing, CLOUD

作者： Walter Akio Goya Marcelo Risse de Andrade Artur Carvalho Zucchi Nelson Mimura Gonzalez Rosangela de Fatima Pereira Karen Langona Tereza Cristina Melo de Brito Carvalho Jan-Erik Mangs Azimeh Sefidcon Escola Politecnica University of Sao Paulo Sao Paulo Brazil Lab. of Comput. Networks & Archit. Universidade de Sao Paulo Sao Paulo SÃ£o Paulo BR Ericsson Research Sweden Stockholm Sweden

One of the main challenges in agriculture is to sustainably meet the demand for food while preserving natural resources for future productions. information technology can assist producers to make better decisions by providing them with data and tools that enhance decision-making process, consequently allowing better management of the natural resources. Cloud-computing platforms and the extraction of data available on public weather related data sets allow the development of web applications that can assist producers with their investing and planning decisions. this paper describes the Big Weather solution, an agricultural decision-making support system that utilizes a cloud-computing platform, distributed processing technologies, and a big data framework. this paper also presents Big Weather architecture and an example of metric calculations (average temperature and humidity) and discusses the performance of the solution when tested in different virtual machine scenario configurations. the novelty is the transparency of the framework, which allows farmers to make better decisions based on data available on the cloud.

关键词： Meteorology Agriculture Big data Clouds Distributed processing Virtual machining Computer architecture

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the Power of Context: A Comparative Analysis of Text Embeddings in Radiology Report Generation

The Power of Context: A Comparative Analysis of Text Embeddi...

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international conference on information and Communications technology (ICOIACT)

作者： Tsaniya Hilya Fatichah Chastine Suciati Nanik Informatics Department Institut Teknologi Sepuluh Nopember Indonesia

ISBN: (数字)9798331536206

ISBN: (纸本)9798331536213

In radiology report generation, the representation of medical language is crucial for producing accurate and meaningful descriptions of imaging findings. However, accurately capturing and representing complex medical language and imaging findings remains a significant challenge. the variability in radiology report structures, specialized medical terminology, and the need for precise contextual understanding complicate the automated generation of high-quality reports. While recent advancements in natural language processing (NLP) have introduced powerful text embeddings, it remains unclear which of these methods best addresses the unique demands of radiological language. this study aims to address this gap by conducting a comparative analysis of several prominent text embedding techniques, including BERT, BioBERT, clinicalBERT, and BioGPT, to understand their effectiveness in generating radiology reports. We employ a framework that integrates image features extracted from Vision Transformer (ViT) with contextualized text embeddings, followed by Long Short Term Memory Network (LSTM) decoder and Generative Pre-Trained Transformer 2 (GPT -2) decoder for report generation. Our experiments reveal that BioGPT outperforms other embeddings, demonstrating a superior ability to capture complex medical concepts and provide coherent description up to 20% better than other embedding models in both LSTM and GPT-2 decoder. these findings highlight the importance of selecting appropriate text embeddings for optimizing the quality and clinical relevance of automated radiology report generation.

关键词： Training Accuracy Generative Pre-trainer transformer Radiology Transformers Feature extraction Natural language processing Decoding Medical diagnostic imaging Long short term memory

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Machine Learning for Accurate and Efficient Pomegranate Fruit Disease Detection: A Novel Approach to Improve Crop Yield and Quality

Machine Learning for Accurate and Efficient Pomegranate Frui...

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international conference on Computing Communication Control and Automation (ICCUBEA)

作者： Prashant Wakhare S. Neduncheliyan Pradeep B. Mane Bharath Institute of Higher Education and Research Tamil Nadu India AISSMS Institute of Information Technology Pune Maharashtra

this paper presents a web-based tool for identifying diseases in fruit crops to address the negative impact of climate change on agriculture. With the increase in population, there is a growing demand for more food production, which puts pressure on farmers to increase crop yields. However, climate change is causing uneven weather conditions, leading to decreased crop yields. this paper proposes a solution that allows farmers to upload an image of a fruit to a system that has a trained dataset of fruit images. the system uses several image processing steps, including feature extraction based on parameters such as color, morphology, and CCV, followed by clustering using CNN Algorithm and classification using SVM to determine if the fruit is infected or not. An intent search technique is used to find the user intention from the features extracted. the experimental evaluation of the approach shows that it is effective, with a 98.38% accuracy rate in identifying diseases in fruit crops. the proposed tool can be used to identify the diseases that affect fruit crops and provide farmers with timely and accurate information, enabling them to take preventive measures to protect their crops, improve crop yields, and contribute to the overall agricultural economy. the recommendations for the application of the developed machine learning model for pomegranate fruit disease detection include using high-quality data, regularly updating the model, integrating with other detection methods, providing an easy-to-use interface, and providing technical support to growers.

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