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The High Economic Value for Videos in a YouTube Channel by Communication using Digital social media (Case Study: Successful Videos about A Particular Motorcycle Group in a YouTube Channel) 23

The High Economic Value for Videos in a YouTube Channel by C...

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6th International Conference on computers in Management and Business, ICCMB 2023

作者： Pane, Murty Magda Siregar, Christian Sriyanto, Hari Character Building Development Center School of Computer Science Computer Science Department Bina Nusantara University Jakarta Indonesia Character Building Development Center Mass Communication Program Communication Department Faculty of Digital Communication and Hotel and Tourism Bina Nusantara University Jakarta Indonesia Character Building Development Center Information System Department School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781450398046

This research's objective is to describe the sustainable activities of a particular motorcycle club (TP) by delivering reciprocal humor and showing nice friendship on social media from a business perspective, especially from a business psychology perspective. The research used a qualitative method by observations in seven periods for seven tour opportunities. Their high amount of interactive communication has led them into the most popular motorcycle group (recognized by the high number of views, like expressions, and positive comments on the YouTube channel and Instagram) which has also led it to a higher economic value. Their particular cohesiveness and engagement were transmitted and deployed in their internal communications in the videos that influence the netizens and the business world positively through their reciprocal humor and nice friendship. © 2023 ACM.

关键词： Motorcycles

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Rice Commodity Supply Chain Issues in Indonesia: Exploring Blockchain technology as an Alternative Solution

Rice Commodity Supply Chain Issues in Indonesia: Exploring B...

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technology Innovation Management and Engineering science International Conference (TIMES-iCON)

作者： Rohmat Taufiq Harco Leslie Hendric Spits Warnars Haryono Soeparno Tanty Oktavia Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Information System Management Department BINUS Graduate Program Master of IS Management Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350362602

ISBN: (纸本)9798350362619

Agriculture has long been recognized as pivotal to economic development, offering avenues to alleviate poverty, foster prosperity, and sustainably meet the food demands of a burgeoning global population projected to reach 9.7 billion by 2050. However, persistent inefficiencies within agricultural supply chains, particularly in sectors like rice production, pose formidable challenges. Addressing these inefficiencies is imperative to avert a surge in hunger and malnutrition. Failure to do so could condemn 815 million people to hunger and leave 3 out of 10 individuals malnourished. Thus, investigating solutions to enhance the resilience of rice supply chains is paramount. This research endeavors to identify and analyze challenges inherent in tracing the rice supply chain, offering a conceptual model proposal as a potential remedy. Employing a methodology centered on scholarly discourse and extensive literature review, our study reveals various impediments facing rice commodity supply chains in Indonesia. Furthermore, this study leverages blockchain technology, specifically the Sawtooth Hyperledger platform, to streamline the tracing process for rice commodities and rationalize the supply chain by reducing intermediary actors. From the proposed model, there is great hope that it can provide implications for the rice supply chain to run more efficiently.

关键词： Economics Supply chains Sociology Production Innovation management Blockchains Proposals

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Generation of target speech with speaker individuality based on accent conversion for English pronunciation learning

Generation of target speech with speaker individuality based...

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Asia-Pacific Signal and information Processing Association Annual Summit and Conference (APSIPA)

作者： Rei Hamakawa Michiharu Niimi Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Japan Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Japan

ISBN: (数字)9798350367331

ISBN: (纸本)9798350367348

This paper first provides an overview of the English pronunciation learning support tool. The tool aims to use "accent-modified speech that retains the learner’s voice quality" as the "target speech." We propose a new conversion model based on conventional methods for this accent conversion. Specifically, we improve the conventional LSTM-based DNN model for accent conversion by adopting a transformer-based model. Our experiments investigated the model’s ability to handle the unique katakana pronunciation characteristic of Japanese speakers. The results confirmed the effectiveness of the proposed conversion method, although challenges remain, such as the scarcity of Japanese speech data and the need to improve the accuracy of speaker identity retention.

关键词： Accuracy Synthesizers Training data Symbols Switches information processing Phonetics Transformers Data models Speech processing

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Creation and Testing of Synthetic Datasets for Training Road Scenes Algorithms

Creation and Testing of Synthetic Datasets for Training Road...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Khulan Khalzaa Stephen Karungaru Kenji Terada Computer Science and Mathematical Science Program at Graduate school of Sciences and Technology for Innovation Tokushima University Japan Computer Science and Mathematical Science Program Tokushima University Japan

Deep learning models require large amounts of data to be trained to fulfill their potential. To solve this problem, we propose a novel method for creating high-quality photorealistic synthetic training data and compare its performance to real data for object detection. We introduce the RealStreet and SynthStreet datasets, which were designed to enhance a safety analysis for road object detection. The objective of the project is to provide a useful synthetic environment for learning and building a road traffic experience by imitating the real environment as nearly as possible. This will improve the safety of road users and enable testing and planning before actual, dangerous events arise. The RealStreet data-set was collected in real-world scenarios of an urban city, while the SynthStreet closely recreates the RealStreet scenes: field of view, road objects, such as pedestrians, cyclists, vehicles, and background information buildings are matched. We study the performance and behavior of a network model trained on real and synthetic data-sets and both with various ratio mixes. Our approach is to evaluate data-set performances using a state-of-the-art method for object detection tasks in learning from synthetic data. We also compare the performance of each dataset, which is evaluated on real-world data, to determine the possibility of synthetic data-set benefits and analyze the effect of limited real-world data. However, it is important to note that synthetic data-sets may not always accurately represent the variability and complexity of real-world environments and may not generalize well to real-world scenarios. Therefore, it is important to carefully evaluate the performance of deep learning models trained on synthetic data and validate their results using real-world data.

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UAV-Aided Data Acquisition Using Gaining-Sharing Knowledge Optimization Algorithm

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computers, Materials & Continua 2022年第9期72卷 5999-6013页

作者： Rania M Tawfik Hazem A.A.Nomer M.Saeed Darweesh Ali Wagdy Mohamed Hassan Mostafa Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGiza12677Egypt School of Information Technology and Computer Science(ITCS) Nile UniversityGiza12677Egypt Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Department of Mathematics and Actuarial Science School of Science and EngineeringThe American University in CairoEgypt Electronics and Communications Engineering Department Cairo UniversityEgypt University of Science and Technology Nanotechnology and Nanoelectronics ProgramZewal City of Science and TechnologyOctober Gardens6th of OctoberGiza12578Egypt

Unmanned Aerial Vehicles(UAVs)provide a reliable and energyefficient solution for data collection from the Narrowband Internet of Things(NB-IoT)***,the UAV’s deployment optimization,including locations of the UAV’s stop points,is a necessity to minimize the energy consumption of the UAV and the NB-IoT devices and also to conduct the data collection *** this regard,this paper proposes GainingSharing Knowledge(GSK)algorithm for optimizing the UAV’s *** GSK,the number of UAV’s stop points in the three-dimensional space is encapsulated into a single individual with a fixed length representing an entire *** superiority of using GSK in the tackled problem is verified by simulation in seven *** provides significant results in all seven scenarios compared with other four optimization algorithms used before with the same ***,the NB-IoT is proposed as the wireless communication technology between the UAV and IoT devices.

关键词： NB-IoT UAV GSK stop points optimization

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Generation of Photo Slideshow with Song based on Closeness between Concept of Lyrics and That of Images

Generation of Photo Slideshow with Song based on Closeness b...

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Asia-Pacific Signal and information Processing Association Annual Summit and Conference (APSIPA)

作者： Mei Hashimoto Michiharu Niimi Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Japan Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Japan

ISBN: (数字)9798350367331

ISBN: (纸本)9798350367348

This paper proposes a method that allows users to easily convert a large number of still images into movies by displaying photos in sync with memories or favorite songs, which offers a new media viewing method for users to look back at the vast number of photos in their photo folders. We assume here that users select a song and have images stored in local PC. One method of synchronization involves selecting images based on elapsed time of song. However, since lyrics convey meaning, it can be better to display the images that align with both lyrics’ meaning and images’ meaning matched. In order to do this, we need the space which shares the concept of both lyrics and images, and select colors as the concept. Displayed images are determined based on the distance between points that are mapped from words and images to color space. Specifically, the color concepts from words are extracted using the Color Image Scale, and that from images are determined as the most frequent colors by cluster analysis. Experimental results show that it is possible to easily create movies where images with colors that match the mood of the lyrics are displayed.

关键词： Image color analysis Mood Refining Asia information processing Color Media Motion pictures Synchronization

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Enhanced Intrusion Detection System for an EH IoT Architecture Using a Cooperative UAV Relay and Friendly UAV Jammer

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IEEE/CAA Journal of Automatica Sinica 2021年第11期8卷 1786-1799页

作者： Van Nhan Vo Hung Tran Chakchai So-In Institute of Research and Development Duy Tan UniversityDa Nang 550000Vietnam Faculty of Information Technology Duy Tan UniversityDa Nang 550000Vietnam Applied Network Technology Laboratory Department of Computer ScienceFaculty of ScienceKhon Kaen UniversityKhon Kaen 40002Thailand Faculty of Computer Science Phenikaa UniversityHanoi 100000Vietnam

In this paper,the detection capabilities and system performance of an energy harvesting(EH)Internet of Things(Io T)architecture in the presence of an unmanned aerial vehicle(UAV)eavesdropper(UE)are *** communication protocol is divided into two *** the first phase,a UAV relay(UR)cooperates with a friendly UAV jammer(UJ)to detect the UE,and the UR and UJ harvest energy from a power beacon(PB).In the second phase,a ground base station(GBS)sends a confidential signal to the UR using non-orthogonal multiple access(NOMA);the UR then uses its harvested energy to forward this confidential signal to IoT destinations(IDs)using the decode-and-forward(DF)***,the UJ uses its harvested energy to emit an artificial signal to combat the detected UE.A closed-form expression for the probability of detecting the UE(the detection probability,DP)is derived to analyze the detection ***,the intercept probability(IP)and throughput of the considered IoT architecture are ***,we identify the optimal altitudes for the UR and UJ to enhance the system and secrecy *** Carlo simulations are employed to verify our approach.

关键词： Detection probability(DP) energy harvesting(EH) friendly UAV jammer Internet of Things(IoT) system performance UAV detection

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A Self-Supervised Transformer-Based Model for Early Recurrence Prediction of HCC with Multimodal MRI 12

A Self-Supervised Transformer-Based Model for Early Recurren...

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12th IEEE Global Conference on Consumer Electronics, GCCE 2023

作者： Zhang, Xianru Zhan, Gan Wang, Fang Li, Yinhao Lin, Lanfen Hu, Hongjie Chen, Yen-Wei Ritsumeikan University Graduate School of Information Science and Engineering Shiga Japan Zhejiang University Sir Run Run Shaw Hospital Department of Radiology Hangzhou China Zhejiang University College of Computer Science and Technology Hangzhou China

ISBN: (纸本)9798350340181

Hepatocellular carcinoma (HCC) is a representative primary liver cancer with high incidence and mortality. Surgical resection is the first option of treatment, but patients are usually at a high risk of tumor recurrence within the first 2 years, resulting in poor overall outcomes. Thus, it is of great clinical significance to predict HCC early recurrence to improve the survival rate. Existing transformer-based methods typically rely on models pretrained on ImageNet, which may not effectively extract features from medical images. Thus, we propose a self-supervised transformer-based method for HCC early recurrence prediction. We first leverage a vision transformer trained through self-supervised learning to capture more informative semantic features from multimodal MRI. These enhanced features are subsequently fused with a transformer architecture to predict the early recurrence of HCC. Experiments show that our method achieved better results than other methods. © 2023 IEEE.

关键词： Forecasting

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Imitation Game for Adversarial Disillusion with Chain-of-Thought Role-Play in Generative AI

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IEEE Access 2025年 13卷 95085-95093页

作者： Chang, Ching-Chun Chen, Fan-Yun Gu, Shih-Hong Gao, Kai Wang, Hanrui Echizen, Isao Feng Chia University Department of Information Engineering and Computer Science Taichung Taiwan National Institute of Informatics Information and Society Research Division Tokyo Japan University of Tokyo Graduate School of Information Science and Technology Tokyo Japan

As the cornerstone of artificial intelligence, machine perception confronts a fundamental threat posed by adversarial illusions. These adversarial attacks manifest in two primary forms: deductive illusion, where specific stimuli are crafted based on the victim model's general decision logic, and inductive illusion, where the victim model's general decision logic is shaped by specific stimuli. The former exploits the model's decision boundaries to create a stimulus that, when applied, interferes with its decision-making process. The latter reinforces a conditioned reflex in the model, embedding a backdoor during its learning phase that, when triggered by a stimulus, causes aberrant behaviours. The multifaceted nature of adversarial illusions calls for a unified defence framework, addressing vulnerabilities across various forms of attack. In this study, we propose a disillusion paradigm based on the concept of an imitation game. At the heart of the imitation game lies a multimodal generative agent, steered by chain-of-thought reasoning, which observes, internalises and reconstructs the semantic essence of a sample, liberated from the classic pursuit of reversing the sample to its original state. As a proof of concept, we conduct experimental simulations using a multimodal generative dialogue agent and evaluates the methodology under a variety of attack scenarios. Experimental results demonstrate that the proposed framework consistently neutralises both deductive and inductive adversarial illusions. Across a range of white-box and black-box attack scenarios, the imitation-based method achieved classification accuracies between 94% and 97% on a subset of the ImageNet dataset, significantly outperforming benchmark defences such as JPEG compression and DiffPure. © 2013 IEEE.

关键词： Intelligent systems

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Trace Semantics and Algebraic Laws for Total Store Order Memory Model

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Journal of computer science & technology 2021年第6期36卷 1269-1290页

作者： Li-Li Xiao Hui-Biao Zhu Qi-Wen Xu Shanghai Key Laboratory of Trustworthy Computing East China Normal UniversityShanghai 200062China Department of Computer and Information Science Faculty of Science and TechnologyUniversity of Macao MacaoChina

Modern multiprocessors deploy a variety of weak memory models(WMMs).Total Store Order(TSO)is a widely-used weak memory model in SPARC implementations and x86 *** omits the store-load constraint by allowing each core to employ a write *** this paper,we apply Unifying Theories of programming(abbreviated as UTP)in investigating the trace semantics for TSO,acting in the denotational semantics style.A trace is expressed as a sequence of snapshots,which records the changes in registers,write buffers and the shared *** the valid execution results containing reorderings can be described after kicking out those that do not satisfy program order and modification *** paper also presents a set of algebraic laws for *** study the concept of head normal form,and every program can be expressed in the head normal form of the guarded choice which is able to model the execution of a program with *** the linearizability of the TSO model is ***,we consider the linking between trace semantics and algebraic *** linking is achieved through deriving trace semantics from algebraic semantics,and the derivation strategy under the TSO model is provided.

关键词： weak memory model Total Store Order(TSO) trace semantics algebraic law Unifying Theories of programming(UTP)

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