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检索条件"丛书名=Lecture Notes in Networks and Systems"

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Developing a Foresight Model for Law Enforcement Organizations to Detect and Analyze Future Challenges and Threats 11th

Developing a Foresight Model for Law Enforcement Organizatio...

引用

11st World Conference on Information systems and Technologies (WorldCIST)

作者： SaadEldin, Mohamed Dubai Police Foresight & Decis Making Support Ctr Dubai U Arab Emirates

ISBN: (纸本)9783031456473;9783031456480

The Analytic Hierarchy Process (AHP) is a method for making decisions in situations where multiple criteria must be considered. It is particularly useful in crisis situations where there are a number of feasible choices and decision criteria with diverse priorities. The author has developed a new model using the Analytic Hierarchy Process (AHP) method to detect and analyze future risks and challenges in Dubai Police and provide early warning signs to decision makers. The AHP method allows decision makers to differentiate between the importance of each criterion and compare them according to their importance. This helps to avoid stimulating risks or crises by choosing the best alternative based on a systematic evaluation of the available options. A proof-of-concept has been implemented as part of the work done by the author. The model is designed to improve the future readiness of Dubai Police by identifying and analyzing potential risks and challenges. The model uses mathematical, operational research, and decision-making models and is intended to be more reliable and practical than current models used in the law-enforcement sector, which are often deterministic, simplified, or inconsistent in their application and assumptions.

关键词： Foresight Challenge Threat Priority Decision Support Criterion

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Artificial Intelligence Cyberattacks in Red Teaming: A Scoping Review 12th

Artificial Intelligence Cyberattacks in Red Teaming: A Scopi...

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12th World Conference on Information systems and Technologies (WorldCIST)

作者： Al-Azzawi, Mays Doan, Dung Sipola, Tuomo Hautamaki, Jari Kokkonen, Tero Jamk Univ Appl Sci Inst Informat Technol Jyvaskyla Finland

ISBN: (纸本)9783031602146;9783031602153

Advances in artificial intelligence are creating possibilities to use these methods in red team activities, such as cyberattacks. These AI attacks can automate the process of penetrating a target or collecting sensitive data while accelerating the pace of carrying out the attacks. This survey explores how AI is employed in cybersecurity attacks and what kind of targets are typical. We used scoping review methodology to sift through articles to find out AI methods, targets, and models that red teams can use to emulate cybercrime. Out of the 470 records screened, 11 were included in the review. Multiple cyberattack methods can be found to exploit sensitive data, systems, social media user profiles, passwords, and URLs. The use of AI in cybercrime to build versatile attack models poses a growing threat. Additionally, cybersecurity can use AI-based techniques to offer better protection tools to deal with those problems.

关键词： artificial intelligence red team red teaming cyberattack cybersecurity

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Gradient Based Grasp Pose Optimization on a NeRF that Approximates Grasp Success 18th

Gradient Based Grasp Pose Optimization on a NeRF that Approx...

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18th International Conference on Intelligent Autonomous systems (IAS)

作者： Soti, Gergely Hein, Bjoern Wurll, Christian Hsch Karlsruhe Univ Appl Sci D-76133 Karlsruhe Germany Karlsruhe Inst Technol D-76131 Karlsruhe Germany

ISBN: (纸本)9783031449802;9783031449819

Current robotic grasping methods often rely on estimating the pose of the target object, explicitly predicting grasp poses, or implicitly estimating grasp success probabilities. In this work, we propose a novel approach that directly maps gripper poses to their corresponding grasp success values, without considering objectness. Specifically, we leverage a Neural Radiance Field (NeRF) architecture to learn a scene representation and use it to train a grasp success estimator that maps each pose in the robot's task space to a grasp success value. We employ this learned estimator to tune its inputs, i.e., grasp poses, by gradient-based optimization to obtain successful grasp poses. Contrary to other NeRF-based methods which enhance existing grasp pose estimation approaches by relying on NeRF's rendering capabilities or directly estimate grasp poses in a discretized space using NeRF's scene representation capabilities, our approach uniquely sidesteps both the need for rendering and the limitation of discretization. We demonstrate the effectiveness of our approach on four simulated 3DoF (Degree of Freedom) robotic grasping tasks and show that it can generalize to novel objects. Our best model achieves an average translation error of 3mm from valid grasp poses. This work opens the door for future research to apply our approach to higher DoF grasps and real-world scenarios.

关键词： Robotic grasping Neural scene representation Transfer learning

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Toward a Readiness Assessment Model for Technology Adoption in Small and Medium Agricultural Industry 1

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

作者： Marrero, Lilianny Cruz, Pablo Solar, Mauricio Univ Tecn Federico Santa Maria Valparaiso Chile

ISBN: (数字)9789819735624

ISBN: (纸本)9789819735617;9789819735624

Information technology is increasingly seen as a key enabler for many current and future challenges in agricultural companies. We suggest that information technology adoption in agricultural settings is not as straightforward as it might seem mainly due to the particular characteristics these contexts exhibit. This paper presents a preliminary version of a readiness assessment model for information and operation technology adoption in the Small and Medium Agricultural Industry. Using Domain-Driven Design, we identified core and generic domains such as water management, agricultural process and product certification, payroll management, and supplier management that are subject to potential information and operation technology adoption. The domains were identified from key use cases elicited from nine small and medium agricultural Chilean companies. Based on the identified domains and the literature review, we have built a first version of what will be a readiness assessment model to measure the readiness of small and medium-sized agricultural industries to adopt technologies. The model considers information and operation technologies in the agricultural industry. Validation of this proposed maturity model is underway, and some of these preliminary results are presented in this paper.

关键词： Agriculture Technology adoption Readiness assessment Maturity model

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Finding Potential On-street Parking Spots: An Object Detection and Segmentation Approach 8th

Finding Potential On-street Parking Spots: An Object Detecti...

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Shivaprasad, Spoorthi Anand, Meghana Chilkunda, Surabhi A. Kamalesh, Akash Oruganti, Rishabh Radhakrishna, Sriram Venugopal, N. Peoples Educ Soc Univ PESU Bengaluru India

ISBN: (纸本)9789819713288;9789819713295

The scarcity of on-street parking spaces in metropolitan areas has led to traffic congestion, frustration among drivers and resource wastage. Conventional parking management systems fall short in addressing these challenges, particularly as manual searches for parking spots contribute to an increase in traffic congestion. This research contributes to intelligent parking management by proposing a novel approach to identify potential parking spots along roads using image processing and deep learning techniques. Our method includes three models and proposes a solution for identifying parking spaces in urban environments. You Only Look Once (Yolov8), a Convolutional Neural Network (CNN)-based image processing model serves as the base for three models. The three models are sequential and are used to perform different set of tasks like detect parking signs, lane lines, road edges, footpath and differentiate between parked and moving vehicles. The models' outputs also act as an elimination criterion at each step thereby focusing on predicting a potential parking spot. The experimental analysis is performed in terms of F1-scores that provide 0.96 at 0.96 IoU, 0.39 at 0.186 IoU, 0.53 at 0.315 IoU for the first, second and third models, respectively.

关键词： YOLOv8 Segmentation Object detection

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Facial Recognition Model Using Custom Designed Deep Learning Architecture 5th

Facial Recognition Model Using Custom Designed Deep Learning...

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

作者： Kesarwani, Tanish Mittal, Rohit Panwar, Deepak Saini, G. L. Kumar, Sandeep Manipal Univ Jaipur Jaipur Rajasthan India CHRIST Deemed Univ Sch Engn & Technol Dept Comp Sci & Engn Kengeri Campus Bangalore 560074 Karnataka India

ISBN: (纸本)9789819720811;9789819720828

Facial Recognition is widely used in some applications such as attendance tracking, phone unlocking, and security systems. An extensive study of methodologies and techniques used in face recognition systems has already been suggested, but it doesn't remain easy in the real-world domain. Preprocessing steps are mentioned in this, including data collection, normalization, and feature extraction. Different classification algorithms such as Support Vector Machines (SVM), Naive Bayes, and Convolutional Neural networks (CNN) are examined deeply, along with their implementation in different research studies. Moreover, encryption schemes and custom-designed deep learning architecture, particularly designed for face recognition, are also covered. A methodology involving training data preprocessing, dimensionality reduction using Principal Component Analysis, and training multiple classifiers is further proposed in this paper. It has been analyzed that a recognition accuracy of 91% is achieved after thorough experimentation. The performance of the trained models on the test dataset is evaluated using metrics such as accuracy and confusion matrix.

关键词： Facial recognition Deep learning Artificial intelligence

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AI Based Commercial Decisions: The Cryptocurrency Market Case

AI Based Commercial Decisions: The Cryptocurrency Market Cas...

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Computing Conference

作者： Joshi, Sujata Satya, Mohit Domb, Menachem Symbiosis Int Deemed Univ Symbiosis Inst Digital & Telecom Management Pune Maharashtra India Ashkelon Acad Coll Comp Sci Dept Ashqelon Israel

ISBN: (纸本)9783031622717;9783031622694;9783031622687

The cryptocurrency market is a fast-growing and highly volatile market that poses significant challenges for investors seeking to make informed decisions. As the market continues to evolve and become more mainstream, there is a growing need for accurate forecasting methods to help investors navigate this unpredictable terrain. This study examines the potential of machine learning techniques, specifically Long Short-Term Memory (LSTM), for predicting future trends in the cryptocurrency market. The study evaluates the effectiveness of various machine learning algorithms in predicting the price movements of different cryptocurrency assets. The research employs historical data analysis and machine learning techniques, focusing on LSTM. LSTM is a neural network that can capture long-term dependencies in time-series data suited for predicting trends in the cryptocurrency market. The study uses performance criteria such as recall precision, measuring how well an algorithm can identify true-positive and negative cases in a dataset, required for assessing its accuracy and effectiveness. This study has the potential to provide valuable insights into the effectiveness of machine learning techniques, specifically LSTM, for predicting trends in the cryptocurrency market. Investors can make better decisions in this highly volatile and unpredictable market by identifying the most effective and efficient algorithm expanding the use of machine learning in the financial forecasting domain.

关键词： Cryptocurrency Predictive analysis Machine learning LSTM Forecasting Historical data analysis Neural network Bitcoin Price movements Volatility modelling

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Measuring the Angular Orientation of Objects in Radio Navigation in the Absence of One of the Antennas 13th

Measuring the Angular Orientation of Objects in Radio Naviga...

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13th Computer Science Online Conference

作者： Tryapitsyn, Valery Dubinko, Tatyana Farwater 3 Zaitseva Str St Petersburg 198096 Russia

ISBN: (纸本)9783031702990;9783031703003

This article presents a method for measuring the angular orientation of objects in radio navigation systems, based on an iterative approach. The method is intended for satellite systems installed on a ship that determine the orientation angles of the ship. An approach has been developed to calculate orientation angles by introducing corrections in real time. The mechanism that is used is based on the Euler angle matrix. It allows you to calculate all three orientation angles: heading, roll, trim. In this matrix, its elements are the direction cosines of the base vector of the three-antenna system (three-antenna compass). Using the antenna system, the heading, roll and trim angles are calculated. In this work, the problem of implementing a single-base compass is solved, that is, only two antennas are used for the situation of loss of radio navigation data from one of the antennas. The accuracy of calculating orientation angles in an antenna compass when one antenna is lost was checked, and errors were determined that show how accurate it is compared to a three-antenna compass. This experiment was modeled mathematically. A solution was compared that determined orientation angles from three antennas, then one antenna was turned off in the program. The results obtained showed that the method is applicable for use in real navigation systems. #CSOC1120.

关键词： Radio Navigation Orientation Angles Three-Antenna Compass Coordinate systems Antenna Base

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State-of-the-Art fNIRS for Clinical Scenarios: A Brief Review 2nd

State-of-the-Art fNIRS for Clinical Scenarios: A Brief Revie...

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2nd International Conference on Forthcoming networks and Sustainability in the AIoT Era (FoNeS-AIoT)

作者： Mirdan, Samandari Ali Nikolaevich, Afonin Andrey Belgorod State Natl Res Univ Belgorod Russia

ISBN: (纸本)9783031628801;9783031628818

Technologies that monitor human health, diagnose health problems, or contribute to the study of brain functions and translate them into commands in the pursuit of finding replacements for those who have lost limbs to improve their lives are techniquesworth studying. Today, the Neuroimaging technique functional near-infrared spectroscopy (fNIRS) has become one of the pioneering technologies in various applications, especially in the medical field, and this technology has gone through major events and attracted the attention of researchers for numerous and diverse studies. Considering recent indications for this method, a brief review highlights the state-of-the-art of this method and offers various recent uses of its directions toward clinical application scenarios, in particular in the field of artificial limbs and neurological rehabilitation. In addition, this review provides insight into the expected uses of this method shortly. The research methodology included the theory of fNIRS, its basic principles, systems, and its relationship with other neuroimaging methods considering contemporary scientific modernity. Among hundreds of scientific publications, the selection of popular and fruitful research and articles related to the subject of review and their analysis led to beneficial results. Monitoring, diagnosing, and finding solutions to physical problems may fall a great deal on the responsibility of this technique, which is still in the circle of modern scientific research that has yielded discoveries even at the expense of the challenges it faces by combining it with another technology to fill its inherent flaw, which means encouraging the expansion of future studies of this technology, which may be the most promising technology for several clinical applications shortly.

关键词： Functional near-infrared spectroscopy (fNIRS) Functional magnetic resonance imaging (fMRI) Hemodynamic response Electroencephalography (EEG) Electromyography (EMG) Brain-computer interface (BCI)

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Emotional Analysis Based on Text Using X MBTI Data

Emotional Analysis Based on Text Using X MBTI Data

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Intelligent systems Conference

作者： Lee, Irene Songyeon St Paul Preparatory 50-11 Banpo Dong Seoul South Korea

ISBN: (纸本)9783031664304;9783031664311

Recently, since various forms of text, photos, and videos are getting uploaded on the internet, the importance of utilizing data has increased. Among the online platforms with lots of users, X (Twitter) allows users to post their lifestyle based on text and images and provide the latest news and information. Since the users create and share text about their individual lives, the data of X contains their language habitats and personalities. Moreover, as the importance of personal emotion is increasing, self-objectification based on the Myers-Briggs Type Indicator (MBTI) is now trending. MBTI divides personality into 16 detailed categories through the various selections, emphasizes the strength and weakness of each personality, and shares the result to the individuals. However, MBTI is not perfectly accurate, which can be changed based on the emotional states or feelings. This study trains a MBTI prediction model based on text data created from X. The trained model allows one to determine the difference between numerous feelings and psychological state immediately, and display the linguistic characteristics of each MBTI through data-driven statistics by data analysis.

关键词： Data-driven MBTI (Myers-Briggs Type Indicator) Natural language processing Sentiment analysis Word2Vec

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