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HYPNOS: Highly Precise Foreground-Focused Diffusion Finetuning for Inanimate Objects 17th

HYPNOS: Highly Precise Foreground-Focused Diffusion Finetuni...

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17th Asian Conference on computer Vision, ACCV 2024

作者： Nathanael, Oliverio Theophilus Lumentut, Jonathan Samuel Muliawan, Nicholas Hans Angky, Edbert Valencio Kurniadi, Felix Indra Zakiyyah, Alfi Yusrotis Harefa, Jeklin Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Department of Computer Science Edge Hill University OrmskirkL39 4QP United Kingdom Mathematics Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Università di Pisa Pisa56126 Italy

ISBN: (纸本)9789819626434

In recent years, personalized diffusion-based text-to-image generative tasks have been a hot topic in computer vision studies. A robust diffusion model is determined by its ability to perform near-perfect reconstruction of certain product outcomes given few related input samples. Unfortunately, the current prominent diffusion-based finetuning technique falls short in maintaining the foreground object consistency while being constrained to produce diverse backgrounds in the image outcome. In the worst scenario, the overfitting issue may occur, meaning that the foreground object is less controllable due to the condition above, for example, the input prompt information is transferred ambiguously to both foreground and background regions, instead of the supposed background region only. To tackle the issues above, we proposed Hypnos, a highly precise foreground-focused diffusion finetuning technique. On the image level, this strategy works best for inanimate object generation tasks, and to do so, Hypnos implements two main approaches, namely: (i) a content-centric prompting strategy and (ii) the utilization of our additional foreground-focused discriminative module. The utilized module is connected with the diffusion model and finetuned with our proposed set of supervision mechanism. Combining the strategies above yielded to the foreground-background disentanglement capability of the diffusion model. Our experimental results showed that the proposed strategy gave a more robust performance and visually pleasing results compared to the former technique. For better elaborations, we also provided extensive studies to assess the fruitful outcomes above, which reveal how personalization behaves in regard to several training conditions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Generative adversarial networks

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Dual Word Embedding Framework for Gender-Based Writing Style Analysis Using Word2Vec and BERT

Dual Word Embedding Framework for Gender-Based Writing Style...

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2024 Beyond Technology Summit on Informatics International Conference, BTS-I2C 2024

作者： Riyanto, Aditya Zahra, Amalia Binus Graduate Program Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798331508579

Social media has evolved into a vast and multifaceted data repository, presenting valuable opportunities to investigate gender-based variations in writing styles. This study aims to enhance the precision of gender classification on Twitter text by leveraging a combined word embedding approach. The paper proposes a framework that utilizes two distinct word embedding models - a combination of GloVe and BERT, as well as GloVe and Word2Vec - to capture both global and contextual linguistic nuances within the text. The dataset comprises a comprehensive collection of tweets and user profile descriptions harvested from Twitter, which underwent meticulous preprocessing and word representation steps before being further processed using the robust Random Forest algorithm. The experimental findings indicate that the combination of GloVe and BERT outperforms the other combination of GloVe and Word2Vec, and also surpasses the performance of single embedding models, with 62.93% accuracy being the highest achieved result. This study provides valuable insights into the potential of combined word embedding techniques for enhancing the accuracy of gender classification in social media text analysis. © 2024 IEEE.

关键词： Tweets

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Efficiency of Multi-Language Data Serialization for Hybrid Cloud-Edge HRIS 9th

Efficiency of Multi-Language Data Serialization for Hybrid C...

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9th International Conference on computer science and Computational Intelligence, ICCSCI 2024

作者： Winata, Andreas Soeparno, Haryono Gaol, Ford Lumban Arifin, Yulyani Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia

In hybrid cloud-edge systems, data processing is distributed between cloud servers and edge servers, this makes data serialization critical for efficient data transfer between servers. This study evaluates the efficiency of multi-language data serialization of Human Resources Information System (HRIS) in a hybrid cloud-edge environment. Because lack of existing studies that specifically evaluate multi-language data serialization for hybrid cloud-edge HRIS, this study conducted a Systematic Literature Review (SLR) to get the list of current state of the art of data serialization methods and then used this result to evaluate the methods. By focusing on HRIS employee data from the employee management module, this study measures both data serialization and deserialization using performance metrics of time, data size, and CPU usage. The results indicate that no methods excel in all metrics, but FlatBuffers, Protocol Buffer, and Apache Avro can provide balanced effectivity across the metrics. The study gives valuable insight for selecting data serialization methods, architecture, and systems requirements in hybrid cloud-edge HRIS to ensure the performance efficiency of the system. © 2024 The Authors.

关键词： Cloud platforms

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Time Complexity Analysis of Attacking RSA Using Probabilistic Factorization Algorithm in Python 8

Time Complexity Analysis of Attacking RSA Using Probabilisti...

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8th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2024

作者： Dewi, Soraya Triutami Yolandito, Richy Vernando Faisal School of Computer Science Bina Nusantara University Mathematics Department Jakarta11480 Indonesia

ISBN: (纸本)9798350368970

This paper analyzes the time complexity of attacks on the RSA cryptosystem by focusing on the factoring of the modulus n. The RSA algorithm is widely used for secure data transmission, and its security relies on the computational difficulty of factoring large integers. This study delves into the mathematical foundations of these attacks, specifically the probabilistic algorithm for factoring n as outlined by Stein. The paper presents a mathematical model of factoring n attack, focusing on its time complexity analysis. The paper also provides a Python implementation of this cryptanalytic attack and evaluates its performance for different bit keys. The results highlight the efficiency of the algorithm to perform cryptanalytic attacks with different key sizes and the importance of using sufficiently large key lengths to maintain security against such attacks. © 2024 IEEE.

关键词： Encryption algorithms

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Exploring the Accuracy of Artificial Intelligence in Detecting Lies Through Micro-expression Analysis 6

Exploring the Accuracy of Artificial Intelligence in Detecti...

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6th International Conference on Information and Communications Technology, ICOIACT 2023

作者： Widjaja, Katriel Serafina Alamo, Carla Chika Anderies Chowanda, Andry Bina Nusantara University School of Computer Science Jakarta11480 Indonesia Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350315639

Micro-expressions are the subtle and rapid movements of human facial expressions that could reveal a person's true emotions, including emotions that people attempt to suppress, hide, or restrain. Many recent papers have researched facial expression recognition systems in video sequences using GRU models. However, they haven't found a good relevance of micro-expression (ME) in detecting deceptive behaviors. In order to improve and contribute to the development of the system, we propose a micro-expression lie detection system with GRU's hyperparameter optimization and explore its accuracy. FER-2013 is used for expression recognition learning and the dataset containing video clips of courtroom trials is used for deception detection learning. Several normalization techniques are done in the process. The CNN model with eight convolutional layers and three fully linked layers is used to train the facial expression recognition system. To improve its accuracy, multiple GRU parameter settings are employed. We used the model on the test dataset after training it. The outcome shows that it was 92.31% accurate. The confusion matrix predicts 12 out of 13 outcomes, with 100% accuracy on the deceptive class and 85% accuracy on the truthful class. © 2023 IEEE.

关键词： Artificial intelligence

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Implementation of Augmented Reality Technology on Solar System Materials in the Learning of sciences at An-Nahl Integrated Islamic Elementary school 9

Implementation of Augmented Reality Technology on Solar Syst...

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9th International Conference on Business and Industrial Research, ICBIR 2024

作者： Azzikri, Hafidz Sarwo Prabowo, Yulius Denny Gatc, Jullend Universitas Bina Nusantara BinusOnline Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350383010

The use of Augmented Reality technology in learning media provides a visualization of 3D objects to students, facilitating their understanding of the material. One of the challenges faced by SDIT AN-NAHL is ensuring that students comprehend the taught material through effective multiple communication. To address this challenge, SDIT AN-NAHL decided to implement Augmented Reality technology using the Unity 3D platform and Vuforia library. This research aims to implement Augmented Reality technology using the Unity 3D platform in Natural science learning, specifically focusing on the solar system, and to assess the improvement in students learning outcomes after the implementation of Augmented Reality media in the solar system material in IPA lessons at the Elementary school. The result of this research is the Tata Surya AR application. In all evaluations conducted on students, the questionnaire results reflect the positive adoption and effectiveness of AR technology in enhancing the experience and learning outcomes of students in the context of solar system learning. Based on the questionnaire results from the overall evaluation conducted on teachers, it can be concluded that most teachers feel that the use of Augmented Reality technology contributes positively to student learning. © 2024 IEEE.

关键词： augmented reality interactive learning learning media solar system unity 3D platform

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Recent Trends for Text Summarization in Scientific Documents 9

Recent Trends for Text Summarization in Scientific Documents

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9th IEEE International Conference on Computing, Engineering and Design, ICCED 2023

作者： Sukmandhani, Arief Agus Arifin, Yulyani Zarlis, Muhammad Budiharto, Widodo Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Information Systems Management Information Systems Management Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350370126

Text summarization is a natural language processing (NLP) technique in artificial intelligence that has been studied in recent years. Every document containing text is tested to get a good summary result. In producing a good summary, proper accuracy is required;therefore, various techniques and methods are used, and another challenge is the use of language in the documents being tested. Various types of documents have been used as research for text summarization, including scientific documents, so researchers are interested in studying them more intensely to get the state of the art in research. This research was conducted to review previous research using literature studies from various publications that published research on text summarization in scientific documents. The researcher collected data from several publishers who had published this type of research from 1988 to 2023 quarter 1 and obtained three hundred and eleven articles, then the researcher analyzed the data using the Kitchenham method to get the right literature to answer the research question. Thirty-seven articles were selected for further in-depth analysis. In addition, the researcher found some interesting findings beyond the research question, including other techniques used to solve the text summarization problem and other types of output that are not commonly produced so that it can increase knowledge in researching text summarization. © 2023 IEEE.

关键词： Text processing

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Development of Controller for Electric Wheelchair using Pressure in Front of Mouth and Cheek Sensors 1

Development of Controller for Electric Wheelchair using Pres...

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1st International Conference on Innovations in Communications, Electrical and computer Engineering, ICICEC 2024

作者： Sondhi, Savita Jowkins, Davrell Mylka Birmani, Sukrit Santoso, Kenneth William Salhan, Ashok Susanti, Maria Ngarianto, Heri Budiharto, Widodo Bina Nusantara Group Binus School Simprug Jakarta12220 Indonesia New Delhi110054 India Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350376517

Advancement of assistive technology has played an instrumental role in developing varied wheelchair controllers for people with severe disabilities. The principal objective of this study is to provide greater independence to people whose bodies are paralyzed below the neck as they cannot use the traditional joystick. A non-invasive and non-intrusive wheelchair controller designed using one pressure sensor (MPS20N0040D-S), two touch sensors (TTP223), and an Arduino controller, is presented here. The pressure sensor is connected to a pipe and is placed inside the mouth of the user. By varying the air pressure from the user's mouth, it can control the forward and backward movement of the wheelchair. Two touch sensors are integrated into the head gear and placed adjacent to the cheeks of the user to move the wheelchair in the left and right direction. Ten healthy and 5 paraplegic subjects, both genders, volunteered to test the accuracy and robustness of the developed wheelchair controller. It was observed that all users successfully navigated the path with no collision or difficulty. Pressure and touch sensors responded efficiently and correctly to the forward, backward, left, and right commands respectively with 98% accuracy. As an extension to this work, authors plan to develop a wheelchair to assist visually impaired individuals. © 2024 IEEE.

关键词： DC motors

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Object-Driven Fuzzy Decision Model for Assessing the Employees' Work from Home Eligibility 4

Object-Driven Fuzzy Decision Model for Assessing the Employe...

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4th International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2024

作者： Utama, Ditdit Nugeraha Immanuel, Christiawan Bina Nusantara University Binus Graduate Program Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798331506490

Work from Home (WFH), especially in the post-pandemic era, has emerged as an alternative work system adopted by many companies. Efficiency and effectiveness are the two main reasons why WFH is favored. In addition, the implementation of the WFH system in conducting business processes within the company allows for greater flexibility in work methods. For certain types of jobs or specific industry domains, this WFH system can be quite reliable. Workers can perform their tasks from anywhere and at any time. Also, monitoring systems enable employees to be remotely tracked by the company. However, the question remains: is an employee's work environment suitable enough to ensure the successful implementation of WFH? To answer this, a standardized model is needed to assess the level of eligibility for WFH implementation. This study aims to develop a fuzzy-based decision model to evaluate the eligibility of an employee's work environment for implementing WFH. An object-oriented approach is used to describe the design of the decision model, while fuzzy logic serves as the primary method for building the model. The model successfully simulated 24 raw employee data points, yielding a highest eligibility score of 88.61 with a similarity index of 0.78 when compared to the model proposed in previous research. © 2024 IEEE.

关键词： Personnel

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Comparison of Decision Tree and Support Vector Machine for Predicting Jakarta Air Quality Index

Comparison of Decision Tree and Support Vector Machine for P...

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2023 International Conference on computer science, Information Technology and Engineering, ICCoSITE 2023

作者： Rafif, Musyaffa Ayman Sanjaya Indrajaya, Gede Al-Ghazi, Muhammad Kent Johnny, Johnny Sagala, Noviyanti T M Bina Nusantara University School of Computer Sciences Data Science Program Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Statistics Department Jakarta11480 Indonesia

ISBN: (纸本)9798350320954

The people in the capital city of the Republic of Indonesia, Jakarta, have been living for years with air pollution. Air quality has been a concern for a long time due to the health risks it has on people, especially those at risk. Using classification algorithms, we would like to implement data mining for the air quality index and make predictions from our capital city, DKI Jakarta. This research aims to compare Decision Tree and Support Vector Machine in predicting Air Quality Index in DKI Jakarta in 2020. The dataset was collected from the Jakarta Open Data Web, and the results of this research highlight the effectiveness of data mining techniques in predicting air quality index levels in Jakarta and emphasize the importance of selecting the appropriate classification algorithm for data mining applications. This research shows that SVM, compared to the Decision tree, has a better result with an accuracy score of 87.86%. On the other hand, Decision Tree has a score of 90.56%. © 2023 IEEE.

关键词： Decision trees

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