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Auto-ejection of liquid from a nozzle

Physical Review E 2024年第4期109卷 045302-045302页

作者： Fang Shan Zhenhua Chai Baochang Shi School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan 430074 China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Wuhan 430074 China Institute of Interdisciplinary Research for Mathematics and Applied Science Huazhong University of Science and Technology Wuhan 430074 China

Auto-ejection of liquid is an important process in engineering applications, and is also very complicated since it involves interface moving, deforming, and jet breaking up. In this work, a theoretical velocity of meniscus at nozzle exit is first derived, which can be used to analyze the critical condition for auto-ejection of liquid. Then a consistent and conservative axisymmetric lattice Boltzmann (LB) method is proposed to study the auto-ejection process of liquid jet from a nozzle. We test the LB model by conducting some simulations, and find that the numerical results agree well with the theoretical and experimental data. We further consider the effects of contraction ratio, length ratio, contact angle, and nozzle structure on the auto-ejection, and observe some distinct phenomena during the ejection process, including the deformation of meniscus, capillary necking, and droplet pinch off. Finally, the results reported in the present work may play an instructive role on the design of droplet ejectors and the understanding of jetting dynamics in microgravity environment.

关键词： Lattice-Boltzmann methods

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Reseed Skipping of Linear Congruential Generator for Multi-level Image Steganography Security of Financial Data

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SN Computer Science 2023年第2期4卷 124页

作者： Danso, Juliana Mantebea Missah, Yaw Marfo Gyamfi, Enoch Opanin Dankwa, Stephen Kwabena, Sarpong Department of Computer Science Kwame Nkrumah University of Science and Technology (KNUST) Kumasi Ghana School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China Department of Cyber Security and Computer Engineering Technology School of Computing and Information Sciences C.K. Tedam University of Technology and Applied Sciences Upper East Region Navrongo Ghana School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

This paper proposed a multi-level image steganography model that integrates with image and plaintext encryption schemes. The model starts by partitioning the cover-image pixel positions into two regions of respective purposes, one is reserved to hold the data, and through the implementation of the dynamic difference expansion principle, the other sloughs some parts to the reserved region in responsive to the size of the data to embed. Continuously reseeding and initializing the parameter values of a Linear Congruential Generator (LCG), generate a set of random pixel positions as members of the reserved region. Before data embedding, the region reserved to hold the data as well as the data bits to embed, are then encrypted using AES with respective keys. Encryption keys are randomly generated using a Cryptographically Secure Pseudo-Random Number Generator (CSPRNG), the Fortuna algorithm. Multiplex security nature of using a randomization generator to reserve image region for encryption and encrypting plaintext data before performing steganography still ensures stability in computational complexities better than a logarithmic O(n log n). A visual inspection by evaluators who made 3000 choices to correctly differentiate stego images from its cover-images shows that only 47 choices were correct, 1884 choices were wrong, while 1069 choices were uncertain. An experiment shows an average Embedding Rates (ERs) of 0.00109 bpp and an average PSNR of 72. This concludes, as our integrated steganography and image encryption which implements the dynamic difference expansion principle, outputs encrypted stego mages that can deceive the naked human eyes into identifying them as rather cover-images, its embedding rate is faster (i.e. ER < 0.1), suitably good, and ensures better imperceptibility of cover-image alterations. When comparing these experimental results with existing methods, our proposed model shows significant competitiveness. We even show real-life scenarios on how this

关键词： AES encryption scheme Dynamic difference expansion principle Linear congruential generator Pseudo-random number generator Reserving room before encryption Steganography

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A New Sentiment Analysis-based Approach for the Prediction of Users Beliefs

A New Sentiment Analysis-based Approach for the Prediction o...

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Sadia Abdulhalim Rakif Pathan Belkacem Chikhaoui Department of Data Science and Artificial Intelligence College of Computing and Information Technology University of Doha for Science and Technology Doha Qatar Department of Science and Technology Institute of Applied Artificial Intelligence TELUQ University Montreal Canada

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

This paper proposes a new approach based on sentiment analysis for predicting the relevance of religious beliefs in contemporary relationships within the context of online dating. The motivation for this research lies in understanding how shared values, common missions, and rituals in various religions might influence decision-making in relationships, the study aims to predict users’ religious beliefs based on OkCupid profiles. Our approach starts first by 1) extracting relevant features using sentiment analysis from text data, and 2) developing machine learning models based on state-of-the-art algorithms such as random forests, logistic regression, and decision trees. The results obtained demonstrated the effectiveness of our proposed approach in accurately predicting religious beliefs and its superiority compared to the state-of-the-art methods. Through this investigation, the paper seeks insights into the interplay between religious beliefs and romantic choices.

关键词： Sentiment analysis Logistic regression Machine learning algorithms Shape Predictive models Feature extraction Prediction algorithms Decision trees Information technology Random forests

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Network Malaria Model on Account of Wide Communication

Network Malaria Model on Account of Wide Communication

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IoT, Communication and Automation technology (ICICAT), International Conference on

作者： Padmaja Tripathi Harish Chandra Ramkeval Department of Mathematics and Scientific Computing Madan Mohan Malviya University of Technology Gorakhpur India Department of Applied Mathematics MJP Rohilkhand University Bareilly India

ISBN: (数字)9798350368109

ISBN: (纸本)9798350368116

Diseases caused by parasites proliferate quickly over the globe. As a result, their control intervention needs to be swift and comprehensive. Preventing chronic diseases can be accomplished by using multi-modal communication to attract attention and enhance awareness. This study presents a nonlinear dynamical model to evaluate the impact of media knowledge on the dissemination of illnesses carried by vectors. In this research, we propose a network model for wide-area multi-media communication. Positiveness, simple reproduction number equilibria, numerical simulation, and a fitted model using Delhi malaria data are used to analyze the mathematical model. An informed community makes it more difficult for disease to spread. Constant multi-media efforts combined with quick communication can effectively eradicate the illness.

关键词： Network topology Social networking (online) Malaria Media Numerical simulation Mathematical models Stability analysis Vectors Numerical models Numerical stability

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Rear-End Collision Avoidance Using Multi-Agent Deep Reinforcement Learning

Rear-End Collision Avoidance Using Multi-Agent Deep Reinforc...

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Advancements in computing (ICAC), International Conference on

作者： Ranuja Perera Surith Arawwala Shalika Harshamali Yohan Perera Samadhi Rathnayake Nelum Chathuranga Amarasena Sasadara Adikari Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Faculty of Applied Sciences University of Sri Jayawardenapura Nugegoda Sri Lanka

ISBN: (数字)9798331517878

ISBN: (纸本)9798331517885

This research paper offers a novel approach to detect rear-end collisions and increase the acceleration of the victim car to possibly avoid or minimize the impact of the collision. A Deep Q-Learning model is utilized to predict the collision, the optimum acceleration of the victim car and the optimum braking of the committer car. The study uses a multi-agent reinforcement learning framework in a simulated environment, focusing on synchronized responses between lead and following vehicles. A comprehensive reward function encourages safe driving behaviors, optimized braking, and successful obstacle detection and avoidance. The continuous action space allows for subtle vehicle control, enhancing the system's adaptability to various collision scenarios. Experimental results demonstrate an overall improvement in collision avoidance and impact reduction over 5000 training episodes. This approach addresses a critical gap in existing safety systems by specifically targeting rear-end collisions, offering the potential for a significant reduction in accident rates and severity. Future work includes real-world testing and expansion to more complex traffic scenarios.

关键词： Training Predictive models Lead Deep reinforcement learning Control systems Safety Automobiles Synchronization Collision avoidance Testing

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Assessment Process in the Light of GenAI: Prohibiting Vs Endorsing

Assessment Process in the Light of GenAI: Prohibiting Vs End...

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IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE)

作者： Bashar Barmada Abha Chitalia Eltahir Kabbar School of Computing Electrical and Applied Technology Unitec Auckland New Zealand Department of Teaching and Learning (Te Puna Ako) Unitec Auckland New Zealand

ISBN: (数字)9798350376234

ISBN: (纸本)9798350376241

Generative AI has become inevitable technology in the current era. Many businesses have started to rely on it in their daily activities. On the other hand, others are sceptical of allowing a full use of GenAI, especially in the academic sector, as it may jeopardise students achieving the learning outcomes. Many academic providers including ones in New Zealand give their staff the choice of either allow or deny the usage of GenAI in assessment work by their students. This paper analyses these two approaches (allowing or denying), their benefits, and drawbacks. It discusses the redesign of assessment requirements and the evaluation process of students’ work to guarantee the academic integrity of the submitted work and the achievement of learning outcomes. Two examples of assessment types that are commonly used in computing discipline are discussed in detail regarding both approaches: the report, which is considered to be prone to GenAI, and the practical project, which is considered to be more resilient to GenAI. The paper will help academic staff in their decision regarding the use of GenAI in assessment work and provide guidance through each approach to achieve the learning outcomes by students with the emphasis on academic integrity.

关键词： Hands Law enforcement Generative AI Education Learning (artificial intelligence) Reflection Disruptive technologies Business

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Virtual Trust on Driverless Cars Using Fuzzy Logic Design

Virtual Trust on Driverless Cars Using Fuzzy Logic Design

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2022 International Conference on Business Analytics for technology and Security, ICBATS 2022

作者： Alroshan, Ayat Asgher, Tayba Hussain, Munawar Shahzad, Muhammad Rasool, Faiz Abu-Khadrah, Ahmed School of Information Technology Skyline University College P.O. Box 1797 Sharjah United Arab Emirates Riphah International University Department of Computing and Applied Sciences Lahore Pakistan Saudi Electronic University College of Computing and Informatics Riyadh Saudi Arabia

ISBN: (纸本)9781665409209

People's interest in self-driving cars is increasing day by day. How they affect our daily lives and how they benefit us in different ways. These cars are also called robotic cars. These vehicles work with the latest technology to meet the needs of human transportation without any interference. This is a major development in the car manufacturing industry using the latest technology features. These cars communicate with each other over a wireless network. These cars take note of their surroundings with cameras and sensors. Their positions are tracked by navigation paths, GPS radar, etc. If the current path changes, the cars change their position through the modern control system. These cars reduce traffic accidents, increase confidence, and increase road capacity. The main advantage is to reduce the traffic police and no car insurance policy is required, self-drive cars use less fuel than other cars. But on the other hand, issues related to software such as cybersecurity, reliability need to be overcome. The most important thing is related to driver jobs which are most dangerous for human beings. This paper deals with the calculation of virtual trust on driverless cars using fuzzy logic design. Verified results and analysis obtained through the Mamdani Fuzzy Inference System to test virtual trust in driverless cars. Results have been verified using MATLAB simulation. © 2022 IEEE.

关键词： Insurance

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Toxic Comment Classification Using S-BERT Vectorization and Random Forest Algorithm 1

Toxic Comment Classification Using S-BERT Vectorization and ...

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1st IEEE International Conference on Contemporary computing and Communications, InC4 2023

作者： Kumar, Aparna Ashok Pati, Peeta Basa Deepa, K. Sangeetha, S.Tresa Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Karnataka India Amrita Vishwa Vidyapeetham Amrita School of Engineering Department of Electrical and Electronics Engineering Karnataka India University of Technology and Applied Sciences Department of Engineering AlMusannah Oman

ISBN: (纸本)9798350335774

The growing popularity of social media platforms and microblogging websites has led to an increase in the expression of views and opinions. However, conversations and debates on these platforms often lead to the use of toxic comments, which consists of insulting and hateful remarks. To address this issue, it is important for social media systems to be able to recognize harmful comments. With the rising incidence of cyberbullying, it is crucial to study the classification of toxic comments using various algorithms. This study compares the effectiveness of different word and sentence embedding methods, including TF-IDF, InferSent, Bert, and T5 for toxic comments classification. A comparative study is also conducted on the impact of using SMOTE to balance the highly imbalanced dataset. The results of these models are compared and analysed. It is observed that T5 embedding with Random Forest Classifier works best at 0.91 F1-Score. © 2023 IEEE.

关键词： Social networking (online)

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Generalized autocorrelation function in the family of deterministic and stochastic anomalous diffusion processes

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Physical Review Research 2024年第3期6卷 033169-033169页

作者： Muhammad Tayyab School of Computing Sciences Pak-Austria Fachhochschule Institute of Applied Sciences and Technology Mang Haripur 22621 Pakistan Faculty of Engineering Sciences Ghulam Ishaq Khan Institute of Engineering Sciences and Technology Swabi Topi 23640 Pakistan

We investigate the observables of the one-dimensional model for anomalous transport in semiconductor devices where diffusion arises from scattering at dislocations at fixed random positions, known as the Lévy-Lorentz gas. To gain insight into the microscopic properties of such a stochastically complex system, deterministic dynamics known as the slicer map and fly-and-die dynamics are used. We analytically derive the generalized position autocorrelation function of these dynamics and study the special case, the 3-point position correlation function. For this, we derive single-parameter-dependent scaling and compare it with the numerically estimated 3-point position autocorrelation of the Lévy-Lorentz gas, for which the analytical expression is still an open question. Here we obtained a remarkable agreement between them, irrespective of any functional relationship with time. Moreover, we demonstrate that the position moments and the position autocorrelations of these systems scale in the same fashion, provided the times are large enough and far enough apart. Other observables, such as velocity moments and correlations, are reported to distinguish the systems.

关键词： Ballistic transport Classical transport Diffusion Random walks Stochastic processes 1-dimensional systems

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Intelligent Traffic Light Solution for Green and Sustainable Smart City

Intelligent Traffic Light Solution for Green and Sustainable...

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Mediterranean Conference on Embedded computing (MECO)

作者： Omid Jafari Stanislav Kolosov Nhan Vo Asmita Thapa Magar Jukka Heikkonen Rajeev Kanth School of Engineering and Technology Savonia University of Applied Sciences Kuopio Finland Department of Computing University of Turku Turku Finland

This research aims to develop a smart traffic light system that can improve traffic flow in urban areas. The proposed system uses sensors, cameras, and software to adjust the timing of traffic signals based on real-time traffic conditions. In this study, a Raspberry Pi 4 and MATLAB software was used to build the smart traffic controller. The detection part of the system involves several steps, including removing noise and retrieving information to calculate the number of cars detected. The system then switches traffic lights based on the detected car count. The MATLAB Image Acquisition and Computer Vision toolboxes were used to obtain and analyze the video frames received from the connected cameras. The detector uses the Gaussian Mixture Model to suppress frequently occurring features and to detect abnormal features, which are then used to detect changes caused by moving objects. Morphological operations are used to remove noise from the output. Finally, the system counts the cars detected by the Foreground Detector and switches the traffic lights accordingly. The proposed approach can help reduce traffic congestion and improve the overall flow of traffic in urban areas.

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