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A Critical Analysis Toward Sustainable Farming: The Role of AI in Weed Identification and Management 5th

A Critical Analysis Toward Sustainable Farming: The Role of ...

引用

5th International Conference on Communication and Intelligent systems (ICCIS)

作者： Singh, Shweta Yadav, Pritaj Rabindranath Tagore Univ Bhopal India

ISBN: (纸本)9789819720521;9789819720538

An artificial intelligence-based weed detection system is a computerized system designed to automatically identify and classify different types of weeds in agricultural fields. The system utilizes advanced computer vision techniques and machine learning algorithms to accurately detect and differentiate weeds from crops or other elements in the field. The weed detection system typically consists of hardware components such as cameras or drones which capture high-resolution images or videos of the agricultural area. These images are then analyzed by the artificial intelligence algorithms which have been trained on large datasets of weed images to recognize and distinguish various weed species. This paper examines the pivotal role of AI in weed detection, a critical aspect of farming that determines crop yield and health. Through a comprehensive review, we shed light on the diverse AI-driven techniques including image recognition using Deep Learning, real-time automation, data augmentation, multispectral imaging, and predictive analysis, among others. The ability of AI to distinguish between crops and weeds, often in real-time and under varied environmental conditions, underscores its transformative potential. As weed management represents a significant challenge in agriculture, the precise and proactive capabilities offered by AI can lead to optimized herbicide usage, reduced costs, and enhanced crop productivity.

关键词： Image processing Image enhancement Weed detection Machine learning

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Effects of Work Digitalization and Hybridization Within the Tax System of Bosnia and Herzegovina 10th

Effects of Work Digitalization and Hybridization Within the ...

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International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Cizmic, Elvir Karajbic, Elvir Sasic, Devad Dogic, Rifet Univ Sarajevo Sch Business & Econ Trgoslobodenja 1 Sarajevo 71000 Bosnia & Herceg Parliament Federat Bosnia & Herzegovina Ent Sarajevo 71000 Bosnia & Herceg Univ Sarajevo Fac Adm Sarajevo 71000 Bosnia & Herceg Univ Zenica Fac Econ Zenica 72000 Bosnia & Herceg

ISBN: (纸本)9783031662706;9783031662713

Hybridization of work is a phenomenon that is more intensively applied with the emergence of digitization and computerization of processes in different types of organizations. Hybridization is a possibility of performing work by managers and employees through temporal, spatial, technological, administrative and innovation differentiation, all in the function of simultaneously improving the satisfaction and performance of all participants in this process. The conceptual framework of the research is modelled in a way that the phenomenon of hybridization is observed in the context of the key components of job design, which includes the working task, the technical system, the task executors, the quality of the work environment and the performance of the executors. The research was carried out in the period May-September 2023 and is aimed to executors in the tax system of Bosnia and Herzegovina. The sample includes 153 respondents, while the questionnaire is made up of six segments, five of which measure attitudes related to the hybridization and digitization of work through five model components, with a special sixth segment that includes demographic characteristics of the respondents. This paper goal is to recognize the intensity of hybridization and digitalization of this type of work, while measuring their impact on the performances of the executors through their engagement and satisfaction, along with the projection of future guidelines for application of the hybrid work format.

关键词： Digitization of work Hybridization of work Components of workplace Performance of executors

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Perception of Users of the Video Streaming Platform Netflix About the Transmedia Narrative of the Series Stranger Things Season 4 9th

Perception of Users of the Video Streaming Platform Netflix ...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Lopez Orosco, Lizeth Aracelly Solano Guevara, Valeria Alexandra Caldas Gayoso, Norma Ines Margarita Turriate-Guzman, Adriana Univ Privada Norte Lima Peru

ISBN: (纸本)9789819733040;9789819733057

Over the years, the way we watch series has been changing due to new technologies such as the internet and especially video streaming platforms in relation to transmedia storytelling. Make sure that the audience is not content to end a series. Nowadays, many users choose to look for more content related to their favorite series on other entertainment platforms. Because of this, this research answers the question: What is the perception of users of the video streaming platform Netflix about the transmedia narrative of the series Stranger Things Season 4? This research is qualitative in nature, because it allows us to explain clearly and objectively the facts and experiences of the world. Specifically, the study carried out a qualitative sample of 25 people with the following inclusion and exclusion criteria, which are: that people are subscribed to the Netflix platform with their own accounts. Millennials between the ages of 24 and 32 who have watched the Stranger Things Season 4 series, which is our focus of study.

关键词： Streaming Netflix Stranger Things Perception Transmedia storytelling

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Terraria AI: YOLO Interface for Decision-Making Algorithms 9th

Terraria AI: YOLO Interface for Decision-Making Algorithms

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9th International Congress on Information and Communication Technology (ICICT)

作者： Barrantes Chaves, Emmanuel Rivera Alvarado, Ernesto Tecnol Costa Rica Sj Costa Rica

ISBN: (纸本)9789819735556;9789819735563

This paper presents a method to enable agents for the Terraria game to evaluate algorithms commonly used in general video game artificial intelligence competitions. The usage of the "You Only Look Once" model in the first layer of the process obtains information from the screen, translating this information into a Video Game Description Language known as "Video Game Description Language";the agents take that as input to make decisions. For this, the state-of-the-art algorithms were tested and compared, Monte Carlo Tree Search and Rolling Horizon Evolutionary;in this case, Rolling Horizon Evolutionary shows a better performance. This approach's main advantage is that a VGDL beforehand is unnecessary. It will be built on the fly and opens the road for using more games as a framework for AI.

关键词： AI MCTS RHEA Terraria VGDL Yolov5

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Superiority of Deep Learning in Ambient Intelligence, a Myth or an Ubiquitous Truth? 1

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16th International Conference on Ubiquitous Computing and Ambient Intelligence

作者： Styve, Tchamba Kuinze Brondon Bouchard, Kevin Univ Quebec Chicoutimi Lab Intelligence Ambiante Reconnaissance Activite Chicoutimi PQ G7H 2B1 Canada

ISBN: (数字)9783031775710

ISBN: (纸本)9783031775703;9783031775710

This research examines the effectiveness of Deep Learning (DL) and classical Machine Learning (ML) in human activity recognition within smart environments, showing that the performance difference between the two is often minimal. By critically analyzing documented DL performances and comparing them with our own ML models, we provide an empirical perspective on DL's real usefulness in ambient intelligence. We reviewed papers in the field and selected common datasets for smart homes to compare classical ML methodologies with DL counterparts, focusing on hyperparameter tuning to optimize model performance. The hypothesis was that DL benefits are often overstated, and well-tuned classical ML methods can achieve competitive results more efficiently and simply. Our findings reveal the strengths and weaknesses of each approach, offering a critical perspective on their applicability in smart environments. For instance, a well-tuned SVM outperformed all approaches in the literature on the UCI-HAR dataset. Our findings can be perceived as quite surprising, suggesting to ambient intelligence practitioners to be critical in their technology choices.

关键词： Human activity recognition smart environments machine learning deep learning

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A Real-Time Scheduling Method for Emergency Tasks in Satellite-Ground System 9th

A Real-Time Scheduling Method for Emergency Tasks in Satelli...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Wu, Yan Yu, Tingyi Chen, Kunhao Yu, Qingyun Li, Li Tongji Univ Shanghai 201804 Peoples R China

ISBN: (纸本)9789819735587;9789819735594

The rapid progress in satellite technology has led to an escalating demand for a wide range of diverse and complex satellite tasks. The increasing number of satellites and the complexity of tasks have made the efficient utilization of ground station resources indispensable. Hence, this study presents a novel dynamic scheduling method that holistically considers both routine tasks and emergency tasks, with the objective of optimizing the utilization of ground station resources. In the case of emergency tasks, the real-time scheduling approach employs a direct insertion preemptive scheduling strategy. Regarding routine tasks, the scheduling methods encompass indirect insertion scheduling and rescheduling techniques. Simulation experiments have substantiated that the proposed real-time scheduling algorithm effectively solves the scheduling challenges associated with emergency tasks. The results demonstrate a high task completion rate while minimizing the impact on routine tasks. Experimental findings substantiate the algorithm's effectiveness in optimizing ground station resource allocation, leading to improved overall operational efficiency.

关键词： Real-time scheduling Emergency tasks Routine tasks Rescheduling

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An MCDM on Complex Pentapartitioned Neutrosophic Einstein Aggregation Operators in Oil-Centric Agriculture

An MCDM on Complex Pentapartitioned Neutrosophic Einstein Ag...

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Porchudar, T. Ajay, D. Sacred Heart Coll Autonomous Dept Math Tirupattur 635601 Tamil Nadu India

ISBN: (纸本)9783031671913;9783031671920

This paper aims to advance the theory of Pentapartitioned Neutrosophic sets(PNSs) by introducing Complex Pentapartitioned Neutrosophic(C-PNSs) with Einstein aggregation operator. We propose Complex Pentapartitioned Neutrosophic Einstein Weighted Average(C-PNEWA) operator and Complex Pentapartitioned Neutrosophic Einstein Weighted Geometric (C-PNEWG) operator. Further using the proposed complex pentapartitioned neutrosophic einstein aggregation operators, a real life application in the field of agriculture validates the utility of the proposed research work.

关键词： Complex Pentapartitioned Neutrosophic Sets Einstein operator Oil-Centric Agriculture MCDM

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Modular Smart City Digital Twins: A Survey of Key Technologies 20th

Modular Smart City Digital Twins: A Survey of Key Technologi...

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20th International Workshop on Combinatorial Image Analysis (IWCIA)

作者： Immonen, Eero Villman, Tero Lindholm, Michael Kaivo-oja, Jari Turku Univ Appl Sci Computat Engn & Anal Res Grp Turku Finland Univ Turku Finland Futures Res Ctr FFRC Turku Finland Turku Sci Pk Ltd Turku Finland

ISBN: (纸本)9783031665936;9783031665943

Smart City Digital Twins (SCDT) are virtual replicas of cities (or parts thereof) that integrate real-time data from various sources to enable simulation, monitoring, and optimization of urban systems for more efficient and sustainable urban management. In this article, we provide a survey of modular SCDTs, covering standardization and key enabling technologies. Modular hardware and software architectures pave way for standardization, which is crucial for efficient maintenance as well as scalability and portability to new application domains.

关键词： Sustainable city

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Multi-mode Simultaneous Tactile Feedback Using Soft Pneumatic Fingertip Actuator with Dual Air Chamber 1

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18th International Conference on Intelligent Autonomous systems (IAS)

作者： Hashem, Mohammad Shadman Joolee, Joolekha Bibi Hassan, Waseem Jeon, Seokhee Kyung Hee Univ Dept Comp Engn Yongin 446701 South Korea

ISBN: (数字)9783031448515

ISBN: (纸本)9783031448508;9783031448515

The paper suggests a new fingertip actuator made of silicone that can simultaneously produce pressure and vibrotactile feedback in order to offer a more realistic and immersive haptic experience in virtual environments. The actuator has a dual-layer air chamber design, with the top layer providing vibration feedback and the bottom layer providing pressure feedback. Pneumatic valves with pressurized air tanks can regulate the actuator. The actuator was tested in a simulated environment to render three different kinds of haptic textures. It is made to be worn conveniently at the fingertips. To compare the effectiveness of the suggested actuator to an actuator with a single vibrotactile feedback, performance assessments and user studies were done.

关键词： Feedback

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Prompt-Based Learning for Thread Structure Prediction in Cybersecurity Forums

Prompt-Based Learning for Thread Structure Prediction in Cyb...

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Intelligent systems Conference (IntelliSys)

作者： Kashihara, Kazuaki Pal, Kuntal Kumar Baral, Chitta Trevino, Robert P. Arizona State Univ Sch Comp & Augmented Intelligence Tempe AZ 85287 USA Design Pickle Tempe AZ USA

ISBN: (纸本)9783031477140;9783031477157

With recent trends indicating cyber crimes increasing in both frequency and cost, it is imperative to develop new methods that leverage data-rich hacker forums to assist in combating ever evolving cyber threats. Defining interactions within these forums is critical as it facilitates identifying highly skilled users, which can improve prediction of novel threats and future cyber attacks. We propose a method called Next Paragraph Prediction with Instructional Prompting (NPP-IP) to predict thread structures while grounded on the context around posts. This is the first time to apply an instructional prompting approach to the cybersecurity domain. We evaluate our NPP-IP with the Reddit dataset and Hacker Forums dataset that has posts and thread structures of real hacker forums' threads, and compare our method's performance with existing methods. The experimental evaluation shows that our proposed method can predict the thread structure on average 14% better than existing best methods allowing for better social network prediction based on forum interactions.

关键词： Instructional prompts Thread structure prediction Thread structure Social network Unstructured forums Next paragraph prediction Cybersecurity

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