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International Conference on Emerging Trends in Networks and computer Communications (ETNCC)

作者： Inayatulloh Ahmad Fathurrozi R. Wisnu Prio Pamungkas Fried Sinlae Wowon Priatna Tyastuti Sri Lestari Muhammad Yasir Achmad Noe'man Information Systems Department School of Information system Bina Nusantara University Jakarta Indonesia Faculty of Computer Science Bhayangkara Jakarta Raya University Jakarta Indonesia

ISBN: (数字)9798350353266

ISBN: (纸本)9798350353273

Tourist travel is an activity that concern the temporary movement of tourists from their place of origin to a particular destination for recreational purposes. The many parties or agents involved in a tourist trip require coordination between parties to provide the best service for tourists. The negative impact of the lack of coordination and transparency from tourism agents has an impact on tourists. Tourists often receive services that are not as expected because there is no transparency in transactions throughout their tour. Currently, there is no mechanism that unites tourism agents and guarantees transparency and security of information for tourists and stakeholders in the tourism industry. Thus, the aim of this study is to build a blockchain prototype for travel agent partnerships in the tourism industry using blockchain technology. The research method uses a quantitative approach through a literature review by studying the mechanisms of tourist travel and the parties involved in tourist travel, as well as blockchain technology. The research result is a model for adopting blockchain technology for tourism and travel partnerships. The research outcome also show examples of data simulation using the Ganache framework.

关键词： Tourism industry Customer satisfaction Buildings Prototypes Market research Blockchains Peer-to-peer computing Security Stakeholders Business

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An Efficient Hybrid PAPR Reduction for 5G NOMA-FBMC Waveforms

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computers, Materials & Continua 2021年第12期69卷 2967-2981页

作者： Arun Kumar Sivabalan Ambigapathy Mehedi Masud Emad Sami Jaha Sumit Chakravarty Kanchan Sengar Department of Electronics and Communication Engineering JECRC UniversityJaipur303905India Center for System Design Chennai Institute of TechnologyIndia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Electrical and Computer Engineering Kennesaw State UniversityGAUSA

The article introduces Non-Orthogonal Multiple Access(NOMA)and Filter Bank Multicarrier(FBMC),known as hybrid waveform(NOMAFBMC),as two of the most deserving contenders for fifth-generation(5G)*** spectrum access and clampdown of spectrum outflow are unique characteristics of hybrid *** compare the spectral efficiency of Orthogonal Frequency Division Multiplexing(OFDM),FBMC,NOMA,and *** is seen that the hybrid waveform outperforms the existing *** to Average Power Ratio(PAPR)is regarded as a significant issue in multicarrier *** combination of Selective Mapping-Partial Transmit Sequence(SLM-PTS)is an effective way to minimize large peak power *** SLM,PTS,and SLM-PTS procedures are applied to the NOMA-FBMC *** hybrid structure is applied to the existing ***,the correlated factors like Bit Error Rate(BER)and Computational Overhead(CO)are studied and computed for these *** outcome of the work reveals that the NOMA-FBMC waveform coupled with the SLM-PTS algorithm offers superior performance as compared to the prevailing systems.

关键词： 5G NOMA-FBMC SLM-PTS PAPR BER OFDM

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Blockchain Model Adoption to Improve Transaction Transparency in Claim and Refund The General Insurance Industry

Blockchain Model Adoption to Improve Transaction Transparenc...

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International Conference on Emerging Trends in Networks and computer Communications (ETNCC)

作者： Inayatulloh Ahmad Fathurrozi Aida Fitriyani Rakhmi Khalida Dwi Budi Srisulistiowati Dian Hartanti Dwi Swasono Rachmad Information Systems Department School of Information system Bina Nusantara University Jakarta Indonesia Faculty of Computer Science Bhayangkara Jakarta Raya University Jakarta Indonesia

ISBN: (数字)9798350353266

ISBN: (纸本)9798350353273

The insurance industry is a collection of service companies that offer protection services to clients in accordance with contracts and agreements. Insurance claim procedures that utilize conventional computer networks are susceptible to data theft by hackers and carry a high risk of resulting in losses for all parties involved. Blockchain, on the other hand, is a technology that provides an immutable ledger through which insurance companies can transfer insurance claims, thereby helping to eliminate common sources of data theft and destruction in the insurance industry. This research aims to aid the insurance industry in enhancing system security using block chain technology. Using a qualitative approach, problems are identified based on observations of the mechanisms and business processes of insurance companies, particularly those pertaining to the claims process. Literature studies are used to discover alternative information technology-based solutions. This research has produced a block chain model to enhance the insurance system's security. The research results are a proposed model and simulation with a blockchain framework.

关键词： Industries Computational modeling Insurance information security Companies Propagation losses Market research computer networks Blockchains Protection

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Applied Linguistics with Mixed Leader Optimizer Based English Text Summarization Model

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Intelligent Automation & Soft Computing 2023年第6期36卷 3203-3219页

作者： Hala J.Alshahrani Khaled Tarmissi Ayman Yafoz Abdullah Mohamed Manar Ahmed Hamza Ishfaq Yaseen Abu Sarwar Zamani Mohammad Mahzari Department of Applied Linguistics College of LanguagesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of English College of Science&HumanitiesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The term‘executed linguistics’corresponds to an interdisciplinary domain in which the solutions are identified and provided for real-time language-related *** exponential generation of text data on the Internet must be leveraged to gain knowledgeable *** extraction of meaningful insights from text data is crucial since it can provide value-added solutions for business organizations and *** Automatic Text Summarization(ATS)process reduces the primary size of the text without losing any basic components of the *** current study introduces an Applied Linguistics-based English Text Summarization using a Mixed Leader-Based Optimizer with Deep Learning(ALTS-MLODL)*** presented ALTS-MLODL technique aims to summarize the text documents in the English *** accomplish this objective,the proposed ALTS-MLODL technique pre-processes the input documents and primarily extracts a set of ***,the MLO algorithm is used for the effectual selection of the extracted *** the text summarization process,the Cascaded Recurrent Neural Network(CRNN)model is exploited whereas the Whale Optimization Algorithm(WOA)is used as a hyperparameter *** exploitation of the MLO-based feature selection and the WOA-based hyper-parameter tuning enhanced the summarization *** validate the perfor-mance of the ALTS-MLODL technique,numerous simulation analyses were *** experimental results signify the superiority of the proposed ALTS-MLODL technique over other approaches.

关键词： Text summarization deep learning hyperparameter tuning applied linguistics multi-leader optimizer

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Deer Hunting Optimization with Deep Learning Enabled Emotion Classification on English Twitter Data

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computer systems science & Engineering 2023年第12期47卷 2741-2757页

作者： Abdelwahed Motwakel Hala J.Alshahrani Jaber S.Alzahrani Ayman Yafoz Heba Mohsen Ishfaq Yaseen Amgad Atta Abdelmageed Mohamed I.Eldesouki Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Applied Linguistics College of LanguagesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityMakkahSaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Currently,individuals use online social media,namely Facebook or Twitter,for sharing their thoughts and *** of emotions on social networking sites’finds useful in several applications in social welfare,commerce,public health,and so *** is expressed in several means,like facial and speech expressions,gestures,and written *** recognition in a text document is a content-based classification problem that includes notions from deep learning(DL)and natural language processing(NLP)*** article proposes a Deer HuntingOptimizationwithDeep Belief Network Enabled Emotion Classification(DHODBN-EC)on English Twitter Data in this *** presented DHODBN-EC model aims to examine the existence of distinct emotion classes in *** the introductory level,the DHODBN-EC technique pre-processes the tweets at different ***,the word2vec feature extraction process is applied to generate the word embedding *** emotion classification,the DHODBN-EC model utilizes the DBN model,which helps to determine distinct emotion class ***,the DHO algorithm is leveraged for optimal hyperparameter adjustment of the DBN *** extensive range of experimental analyses can be executed to demonstrate the enhanced performance of the DHODBN-EC approach.A comprehensive comparison study exhibited the improvements of the DHODBN-EC model over other approaches with increased accuracy of 96.67%.

关键词： Deer hunting optimization deep belief network emotion classification Twitter data sentiment analysis english corpus

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Image Captioning with Reinforcement Learning 2

Image Captioning with Reinforcement Learning

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2nd IEEE International Conference on computer Vision and Machine Intelligence, CVMI 2023

作者： Verma, Anand Agarwal, Saurabh Arya, K.V. Petrlik, Ivan Esparza, Roberto Rodriguez, Ciro ABV-IIITM Gwalior Department of Information Technology Madhya Pradesh 474015 India ABV-Indian Institute of Information Technology and Management Multimedia and Information Security Research Group Department of Computer Science and Engineering Gwalior474015 India National University Federico Villarreal Faculty of Industrial and Systems Engineering Lima Peru National University Mayor de San Marcos Faculty of Systems Engineering and Informatics Peru

ISBN: (纸本)9798350305142

Image captioning involves generating a natural language description that accurately represents the content and context of an image. To achieve this, image captioning utilises various machine learning techniques and fields, such as computer vision and natural language processing. In the field of image captioning, a lot of advances have been made with encoder-decoder models and reinforcement learning algorithms. However, there are still problems of imbalance between testing and training, as reinforcement learning only handles single comparator metrics such as CIDEr, SPICE, and BLEU and could not perform better in multiple metrics at once. Which is why a lack of diversity can be seen in generated captions. This idea proposes a general technique for collaborative updating that can bridge the gap between evaluation measures and test metrics to produce captions that are more human-like. To increase the precision of image captions, the approach involves using a compiled reward system that considers multiple evaluation metrics to compare the generated sentence with the provided sentences. We will evaluate the model's performance and the reward updating process on standard datasets like MS COCO. © 2023 IEEE.

关键词： Reinforcement learning

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New In-Air Signature Datasets

New In-Air Signature Datasets

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2023 International Symposium on Networks, computers and Communications, ISNCC 2023

作者： Alobaidi, Abdulazeez R. Dhieb, Thameur Nuimi, Zeina N. Hamdani, Tarek M. Wali, Ali Alimi, Adel M. University of Sfax REGIM-Lab.: REsearch Groups in Intelligent Machines Enis Tunisia Imam ja'Afar Al-Sadiq University Faculty of Information Technology Department of Computer Techniques Engineering Iraq Higher Institute of Business Administration University of Gafsa Tunisia College of Engineering Department of Electrical Engineering University of Misan Iraq Higher Institute of Computer Science Mahdia University of Monastir Tunisia Higher Institute of Computer Science and Multimedia of Sfax University of Sfax Tunisia University of Johannesburg Faculty of Engineering and the Built Environment Department of Electrical and Electronic Engineering Science South Africa

ISBN: (纸本)9798350335590

Compared to traditional biometric systems, in-air signatures are considered more robust and secure than classical pen paper. A few datasets capturing in-air signatures have been introduced, utilizing various devices such as the Leap Motion and the Microsoft Kinect sensor camera. However, these devices are not exempt from shortcomings and exhibit certain limitations. The expenses associated with their implementation and the requirement for technical proficiency in operating them present notable challenges for in-air signature analysis. Additionally, users may encounter difficulties in adapting their finger movements to fit within the device's limited field of view, particularly if they lack familiarity with these devices. To address these concerns, this paper proposes the creation of three in-air signature datasets using solely the camera of a laptop or a smartphone, eliminating the need for any additional specialized equipment. Our datasets were collected in three ways. The first is the In-Air Signature dataset (IAS dataset) and the second is the In-Air Signature dataset using a transparent Glass Plate (IASGP dataset) while the third is the In-Air Signature dataset using Smart Phone (IASSP dataset). Forty volunteers participated in the construction of these datasets. Their ages ranged from 21 to 40 years. Each volunteer signs in the air five signatures and imitates five signatures of five other volunteers. Our in-air signatures datasets are publicly available and can be used for various research tasks like in-air signature verification and identification. © 2023 IEEE.

关键词： Cameras

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systematic Literature Review on Organizational Cyber Security Deficiency in Mitigating Mobile Device Risk 2

Systematic Literature Review on Organizational Cyber Securit...

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2nd International Conference on computer science and Engineering, IC2SE 2021

作者： Abu Othman, Noor Ashitah Norman, Azah Anir Kiah, Laiha Mat Mutlaq Alnajrani, Hussain Universiti Malaya Faculty of Computer Science and Information Technology Kuala Lumpur Malaysia Universiti Teknologi MARA Faculty of Computer and Mathematical Sciences Melaka Malaysia Universiti Malaya Faculty of Computer Science and Information Technology Department of Information Systems Kuala Lumpur Malaysia Universiti Malaya Faculty of Computer Science and Information Technology Department of Computer System and Technology Kuala Lumpur Malaysia Albaha University Faculty of Computer Science and Information Technology Albaha Saudi Arabia

ISBN: (纸本)9781665400459

The use of mobile devices by employees to access organizational information systems (IS) is common nowadays, and it can be seen from the trend to the formalization of Bring Your Own Device (BYOD) and remote working settings. However, allowing IS resources to be accessed by mobile devices that enable work flexibility across time, location, and network also increased the cybersecurity risk and vulnerabilities towards organizational resources, including network, system, and data. Therefore, this paper presents a systematic literature review on this context to explore the cybersecurity deficiency and mitigating techniques proposed for mobile device risk mitigation in organizational IS. Following the systematic Literature Review protocol, 31 research articles are selected and reviewed using Thematic Analysis. Three themes were set to classify the output presented by the selected articles according to the context of Security Control, Cybersecurity Pillars, and information system Management (ISM). This thematic analysis has successfully integrated various terms and narratives. Through analysis, nine security controls have been identified, with the most frequent concern being on Cybersecurity systems and Mobile Device profiling. The authors also discovered that deficiency in the Process factor is mostly discussed compared to the People and Technology factor, which also called for improvement in the ISM Planning phase. This study is beneficial in understanding the organizational cybersecurity deficiency in mitigating the risk of mobile devices and providing a reference for the significant security control in the context of the discussed environment. © 2021 IEEE.

关键词： Cybersecurity

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Hybrid Discrete Wavelet Transform and Histogram of Oriented Gradients for Feature Extraction and Classification of Breast Dynamic Thermogram Sequences 5

Hybrid Discrete Wavelet Transform and Histogram of Oriented ...

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5th International Conference on information Retrieval and Knowledge Management, CAMP 2021

作者： Al-Rababah, Khaleel Mustaffa, Mas Rina Doraisamy, Shyamala C. Khalid, Fatimah Universiti Putra Malaysia Upm Serdang Faculty of Computer Science and Information Technology Multimedia Department Selangor Malaysia

ISBN: (纸本)9781665412377

Breast cancer is responsible for the death of thousands of women around the world. A cancerous tumour increases temperature in the region near to the tumour, such heating is then transferred to the skin surface. Early breast cancer detection can save many lives and reduce the cost of treatment. There are many imaging techniques to do the screening such as thermography. To achieve an early detection, computer-Aided Detection (CAD) systems are needed to classify masses in thermogram images. In this research, we propose a hybrid methodology based on Histogram of Oriented Gradients (HOG) and Discrete Wavelet Transform (DWT) to classify temporal-based thermogram images into either normal or cancerous. In this study we propose a technique to reduce the HOG coefficient vector and extract features from this vector. Two-dimensional Discrete Wavelet Transform (DWT) is applied on the original images to obtain HH (high-high) sub band. Then, HOG is applied using the HH sub band. Support Vector Machine (SVM) binary classifier is used to classify images to either normal or abnormal using the extracted features. The obtained results showed comparable results with state-of-the-art related research. © 2021 IEEE.

关键词： Discrete wavelet transforms

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Acquiring Automation and Control Data in The Manufacturing Industry: A systematic Review

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Procedia computer science 2023年 227卷 214-222页

作者： Andi Sama Harco Leslie Hendric Spits Warnars Harjanto Prabowo Meyliana Achmad Nizar Hidayanto Computer Science Department Binus Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Management Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia 11480 Information System Department School of Information System Bina Nusantara University Jakarta Indonesia 11480 Faculty of Computer Science Universitas Indonesia Depok Indonesia 16424

Industry 4.0 has driven the need for information Technology (IT) & Operational Technology (OT) convergence to modernize OT by leveraging IT. The challenges for manufacturing operations are utilizing and converting years of scattered data into valuable information integrated into the company's digital transformation strategy. This paper aims to provide a systematic literature review of current evidence in digital transformation for acquiring automation & control technologies data in manufacturing operations, such as Programmable Logic Controller (PLC), Supervisory Control and Data Acquisition (SCADA), Distributed Control system (DCS), and Manufacturing Execution system (MES), for analytics purposes and identify the current trends and best practices in this area. The findings cover current information on influential researchers, published journals, research trends, industries, industry types, types of analytics applications, methods, and frameworks for acquiring automation & control technologies data from the legacy OT infrastructure.

关键词： Industry 4.0 Operational Technology PLC SCADA MES Data Acquisition IT/OT convergence Manufacturing

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