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

作者： Yongyut Ratchatawetchakul Benjamas Bansri Kamonwan Ratchatawetchakul Natarpha Satchawatee Weerayut Ratchatawetchakul Itthiphol Eampoonga Digital Business and Information System Major Mahasarakham Business School Mahasarakham University Thailand Department of Business Computer Faculty of Administrative Science Kalasin University Kalasin Thailand Business Computer Major Mahasarakham Business School Mahasarakham University Thailand Department of Management Faculty of Management Science Loei Rajabhat University Thailand

ISBN: (数字)9798350362602

ISBN: (纸本)9798350362619

This research aims to 1) apply an enterprise resource planning (ERP) system with cloud computing, 2) implement automated workflow processes (RPA) using UiPath tools within the ERP production cycle, and 3) assess the efficiency of automated workflow processes (RPA) within the ERP production cycle on cloud computing platforms. The results from applying automated workflow processes (RPA with UiPath) within the production cycle of the enterprise resource planning system (ERP with Odoo) hosted on cloud servers (Cloud with Microsoft Azure) indicate that manual processes in the production formula system take 1.05 times longer than automated processes, manual processes in the purchasing system take 1.29 times longer, manual processes in the goods receipt system take 1.22 times longer, and manual processes in the production operations take 1.15 times longer than their automated counterparts.

关键词： Intelligent automation Cloud computing Production Innovation management Enterprise resource planning Raw materials Planning

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Discoffery: A Coffee Types Detection Apps using an EfficienNet-Lite Architecture 7

Discoffery: A Coffee Types Detection Apps using an EfficienN...

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7th International Conference on Sustainable information Engineering and Technology, SIET 2022

作者： Budiman, Satrio Arif Pramono, Andi Priyambadha, Bayu Putri, Annisa Maharani Arya Purnomo, Agung Nugroho, Ilham Setyo Information System Computer Science Faculty University of Brawijaya Malang65145 Indonesia Interior Design Department School of Design Bina Nusantara University Jakarta11480 Indonesia Department of Informatics Computer Science Faculty Brawijaya University Malang65145 Indonesia Department of Mathematics Faculty of Mathematics and Natural Sciences Brawijaya University Malang65145 Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781450397117

According to data from the World Food and Agriculture Organization (FAO), Indonesia produced the fourth-most coffee in the world in 2017 and 2018. Gayo, Robusta Dampit, and Toraja coffees are only a few well-known coffee varieties Indonesian growers produce. This research aims to create an app that can identify the type of coffee and serve as a coffee-related educational tool. A single case study was the research methodology used. By employing the EfficienNet-Lite architecture for transfer learning, a model for categorizing coffee beans is created. Users can get information through the photographs they submit with the help of the type of application development that uses deep learning to do categorization based on image data of coffee bean types. The coffee bean classification feature was built using transfer learning with the EfficientNet architecture. A training accuracy of 87% and a validation accuracy of 81% were achieved using the EfficientNet-Lite 0 architecture. © 2022 ACM.

关键词： Deep learning

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Restoring Lesions in Low-Dose Computed Tomography Images of COVID-19 Using Deep Learning 6th

Restoring Lesions in Low-Dose Computed Tomography Images of ...

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6th Kuala Lumpur International Conference on Biomedical Engineering, BioMed 2021

作者： Kulathilake, K. A. Saneera Hemantha Abdullah, Nor Aniza Lachyan, Abhishek Shivanand Bandara, A. M. Randitha Ravimal Patel, Dhrumil Deveshkumar Lai, Khin Wee Faculty of Computer Science and Information Technology Department of Computer System and Technology Universiti Malaya Kuala Lumpur50603 Malaysia Faculty of Medicine Department of Social and Preventive Medicine Universiti Malaya Kuala Lumpur50603 Malaysia Faculty of Applied Sciences Department of Computer Science University of Sri Jayewardenepura Nugegoda Sri Lanka Department of Radiology Seth GS Medical College King Edward Memorial Hospital Acharya Donde Marg Parel East Maharastra Parel Mumbai400012 India Faculty of Engineering Department of Biomedical Engineering Universiti Malaya Kuala Lumpur50603 Malaysia

ISBN: (纸本)9783030907235

The use of Low-dose Computed Tomography (LDCT) in clinical medicine for diagnosis and treatment planning is widespread due to the minimal exposure of patients to radiation. Also, recent studies have confirmed that LDCT is a feasible medical imaging modality for diagnosing COVID-19 cases. In general, X-ray tube current is being reduced to acquire the LDCT images. Reduction of the X-ray flux introduces the Quantum noise into the generated LDCT images and, as a result, it produces visually low-quality CT images. Therefore, it is challenging to differentiate the lesions in the diagnosis of COVID-19 patients using the LDCT images due to low contrast and failure to preserve the subtle structures. Therefore, in this study, we proposed a Deep Learning (DL) model based on the Generative Adversarial Network (GAN) for post-processing the LDCT images to enhance their visual quality. In this proposed model, the generator network is designed as a U-net to generate the restored CT images by filter out the noise. Also, the discriminator network follows a patch-GAN model to discriminate the real and generated images while preserving the texture details. The quantitative and qualitative results demonstrated the effectiveness of noise suppression and structure preservation of the proposed DL method. Hence, it provides an acceptable quality improvement for LDCT images to discriminate the lesions for diagnosing the COVID-19 positive cases. © 2022, Springer Nature Switzerland AG.

关键词： Generative adversarial networks

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Hotel information system Management Audit Using COBIT 2019 - APO12

Hotel Information System Management Audit Using COBIT 2019 -...

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Innovation in Technology (INOCON), IEEE International Conference for

作者： Joy Nashar Utamajaya Suhono Harso Supangat Ford Lumban Gaol Benny Ranti BINUS Graduate Program School of Information System BINUS University Jakarta Indonesia School of Electrical Engineering and Informatic Bandung Institute of Technology Bandung Indonesia Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Faculty of Computer Science University of Indonesia Depok Indonesia

In general, public or private organizations or companies have used information-based technology as a support to improve business performance to be more effective and efficient in order to achieve a company’s business goals. Given the large contribution of information technology in the application of hotel applications as a supporting information system, it is a vital system that must avoid risks that can hinder and cause harm to the hotel management business processes. Therefore, it is necessary to carry out risk management using the COBIT 5 framework to manage possible risks that may occur based on the APO12 (Manage Risk) domain. From the evaluation results of the data obtained through observation and interviews as well as the calculation of the results of the questionnaire based on 6 APO12 subdomains, the results of the risk management level capability assessment in hotel applications are still at level 3 or have reached the level of established process with the target to be achieved at level 4 resulting in a gap of 1 level. Based on the results obtained, it is necessary to propose recommendations that can be used by hotels in improving the application of information technology risk management so that in the future it can achieve the expected target level so that the APO12 level of capability can increase and become more optimal.

关键词： Technological innovation Companies Risk management information technology Interviews information systems

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SCALABLE LINK PREDICTION IN TWITTER USING SELF-CONFIGURED FRAMEWORK

arXiv

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arXiv 2022年

作者： Daud, Nur Nasuha Hamid, Siti Hafizah Ab Seri, Chempaka Saadoon, Muntadher Anuar, Nor Badrul Department of Software Engineering Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur50603 Malaysia Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur50603 Malaysia

Link prediction analysis becomes vital to acquire a deeper understanding of events underlying social networks interactions and connections especially in current evolving and large-scale social networks. Traditional link prediction approaches underperformed for most large-scale social networks in terms of its scalability and efficiency. Spark is a distributed open-source framework that facilitate scalable link prediction efficiency in large-scale social networks. The framework provides numerous tunable properties for users to manually configure the parameters for the applications. However, manual configurations open to performance issue when the applications start scaling tremendously, which is hard to set up and expose to human errors. This paper introduced a novel Self-Configured Framework (SCF) to provide an autonomous feature in Spark that predicts and sets the best configuration instantly before the application execution using XGBoost classifier. SCF is evaluated on the Twitter social network using three link prediction applications: Graph Clustering (GC), Overlapping Community Detection (OCD), and Redundant Graph Clustering (RGD) to assess the impact of shifting data sizes on different applications in Twitter. The result demonstrates a 40% reduction in prediction time as well as a balanced resource consumption that makes full use of resources, especially for limited number and size of clusters. © 2022, CC BY.

关键词： Efficiency

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LiFi in Short-Range Wireless Communication of IoT 3

LiFi in Short-Range Wireless Communication of IoT

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3rd International Conference on Computing and information Technology, ICCIT 2023

作者： Asmak Ismail, Nurul Halimatul Awwad, Samer A. B. Hassan, Rosilah Sha'ban Kanaker, Hasan Mahmoud Bani-Awwad, Alaa Adnan Ali Applied College Princess Nourah Bint Abdulrahman University Department of Computer Science and Information System Riyadh Saudi Arabia Deanship of Information and Communication Technology Imam Abdulrahman Bin Faisal University Quality Assurance Department Dammam Saudi Arabia Fakulti Teknologi Maklumat & Sistem Maklumat Universiti Kebangsaan Malaysia Selangor Malaysia Isra University Faculty of Information Technology Cyber Security Department Jordan Ministry of Digital Economy and Entrepreneuship Jordan

ISBN: (纸本)9798350321487

In the new era, various communication systems rapidly evolve to pertain the user's needs. One of these emerging communication systems, which is crucial to providing better life aspects, is the Internet of Things (IoT). Communications between the devices in the IoT is the core part of the system. There are two types of communication between the devices in the IoT;short-range wireless communication and long-range wired or wireless communication. This paper is dedicated to discuss the short-range wireless communication in the IoT. These are not to limit but short-range wireless communication includes Bluetooth, Bluetooth Low Energy (BLE), Wireless-Fidelity (WiFi), Light-Fidelity (LiFi), Radio-frequency Identification (RFID), or ZigBee. This paper addresses the LiFi short-range wireless communication system from the operations, modulation techniques, and IEEE 802.15.7 layer architecture. Finally, a comparison of these short-range wireless communications has been made to comprehend their importance in the life of the IoT. © 2023 IEEE.

关键词： Internet of things

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headweAR: Development of Augmented Reality Based on Hat Tester to Support Product Testing

headweAR: Development of Augmented Reality Based on Hat Test...

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Advancement in Data science, E-learning and information systems (ICADEIS), International Conference on

作者： Saiful Anwar Juma’At Mohd Farhan Md Fudzee Ryan Adhitya Nugraha Dedy Syamsuar Ibrahim Umar Kontagora Faculty of Computer Science and IT Universiti Tun Hussein Onn Malaysia Parit Raja Malaysia Information System Department Telkom University Bandung Indonesia Information Systems Department School of Information Systems Bina Nusantara University Indonesia Department of Computer Science Niger State Polytechnic Zungeru Niger State Nigeria

Augmented reality technology application in variety of sectors is becoming more common in line with progress of technological advances towards the digital future. However, the experience of online shopping that lacks in virtual dressing room deter consumers to make the purchase decisions. Existing application for virtual dressing room is yet to include headwear products in software applications. Therefore, this project is proposed to develop an augmented reality mobile application that helps user to visualize virtual hat onto user’s head. The targeted users for this project are adults aged 20 to 30 years old who are the customers of The Cap City. multimedia Mobile Content Development (MMCD) model is implemented to develop the headweAR application. Based on user testing results, more than 80% of the respondents left positive feedback on the proposed application. Development with additional 3D models and multiple face tracking are some of the future works of this markerless AR-based application.

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R3−Rescale, Rotate and Randomize: A Novel Image Cryptosystem Utilizing Chaotic and Hyperchaotic systems

TechRxiv

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TechRxiv 2023年

作者： Gabr, Mohamed Korayem, Yousef Chen, Yen-Lin Por, Lip Yee Ku, Chin Soon Alexan, Wassim Cairo11835 Egypt Department of Computer Science and Information Engineering National Taipei University of Technology Taipei106344 Taiwan Department of Computer System and Technology Faculty of Computer Science and Information Technology Universiti Malaya Kuala Lumpur50603 Malaysia Department of Computer Science Universiti Tunku Abdul Rahman Kampar31900 Malaysia Cairo11835 Egypt New Administrative Capital Cairo13507 Egypt

This work proposes a novel image encryption algorithm that combines unique image transformation techniques with the principles of chaotic and hyperchaotic systems. The proposed algorithm performs rescaling, rotation, and randomization on the target image by exploiting the unpredictable behavior of the Chua system and the hyperchaotic nature of the Chen system. These chaotic systems’ unpredictability and sensitivity to initial conditions are utilized to create an encryption algorithm that provides an extensive key space of 25208, contributing to its robustness against brute-force attacks and amplifying its overall security. The efficiency of the algorithm is demonstrated in its computational speed and minimal resource consumption, making it practical for real-time applications. A series of rigorous tests and analyses were conducted to evaluate the algorithm’s performance, substantiating its capability to withstand a wide array of attacks, including differential attacks, statistical attacks, and brute-force attacks. With its vast key space, high efficiency, and robust resistance to attacks, the proposed algorithm shows potential as a vital tool for securing digital images in various applications, such as secure communication, data storage, and multimedia transmission. This research contributes to the ongoing development and evolution of high-security image encryption methodologies, meeting the escalating demand for advanced security in the digital information era. © 2023, CC BY.

关键词： Cryptography

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Development of User Management in Ihya Digital Ecosystem Using Iterative Incremental Method 4

Development of User Management in Ihya Digital Ecosystem Usi...

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4th International Conference Advancement in Data science, E-Learning and information systems, ICADEIS 2022

作者： Priandhika Izzulhaq, Afif Fauzi, Rahmat Suakanto, Sinung Kadir Hassan Disina, Abdul Mahdin, Hairulnizam Anka Salihu, Ibrahim Information System Telkom University Bandung Indonesia Nigeria Army University Biu Borno State Department of Cyber Security Nigeria Universiti Tun Hussein Onn Malaysia Faculty of Computer Science and Information Technology Johor Malaysia Nile University of Nigeria Abuja Nigeria

ISBN: (纸本)9781665463874

information systems have an essential role in the development of technology and information in Indonesia. information systems are employed and utilized in many facets of society and organizations. Digitizing and utilizing this information system will often form an integrated relationship between several digital sectors into an ecosystem or what is commonly called a digital ecosystem. Digital ecosystem provides benefits for users by exchanging data between systems within it since only one user account could access several systems or services in the ecosystem. The development of user management in the digital ecosystem will serve as a solution to accommodate the increasing number of users of the digital ecosystem. Iterative incremental development methods are used in the development of user management in Ihya digital ecosystem. The system was also tested using scenario tests, user acceptance tests, and load tests. Based on the results of the tests, the Ihya digital ecosystem user management module has met user needs with a User Acceptance Test value of 82.5%. Further development can be done in this research, including using APIs in the data exchange process and adding a two-factor authentication feature to improve data security. © 2022 IEEE.

关键词： information systems

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Alignment of Chan's Supply Value chain Waste Management Using Artificial Intelligence

Alignment of Chan's Supply Value chain Waste Management Usin...

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International Seminar on Application for Technology of information and Communication (ISemantic)

作者： Agus Winarno Oky Dwi Nurhayati Rahmad Gernowo Zainal Arifin Hasibuan Doctoral of Information System Departement Diponegoro University Semarang Indonesia Information System Department Universitas Dian Nuswantoro Semarang Indonesia Information System School of Postgraduate Universitas Diponegoro Semarang Indonesia Faculty of Computer Science Universitas Dian Nuswantoro Semarang Indonesia

Economy circulation can extend product cycle life, efficiency in using (extracting) natural resources, reduce waste generated from the production process and use recycled products as an increase in state revenue. The amount of waste does not show that the pattern of supply chain management in waste management is still not optimal, and the management of organic, inorganic waste (plastic, glass, wood, etc.) to hazardous and toxic waste (B3) which causes pollution, increases emissions impact on human health and the environment. Prevention to reduce excessive consumption patterns, waste management with the 3R pattern (reduce, reuse, and recycle), bio-physical-chemical processes for turning waste into new products, and waste incineration processes. Implementation of the Integrated Circular Economy system of waste in Indonesia with several stages of separating the waste into several waste groups, waste collection, waste transportation, waste treatment, and final waste treatment. Data collection in the form of data sets in the process of artificial intelligence or data mining for descriptive analysis, diagnostic analysis to find out the root of the problem and the background that occurs, predictive analysis to predict what will happen in the future, predictive analysis which is carried out at the latest and requires 4.0 technology supported by Artificial Intelligence (AI), Internet of Things (IoT) which is integrated with information systems in waste management to be able to improve people's welfare, reduce waste from upstream / households and provide government input to make policy technical, budgeting, operational efficiency, optimization of TPA and garbage transportation system.

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