Mohammed S. Sayed

About Mohammed S. Sayed

Mohammed S. Sayed, With an exceptional h-index of 17 and a recent h-index of 13 (since 2020), a distinguished researcher at Egypt-Japan University of Science and Technology, specializes in the field of Digital Systems Design, Image/Video Processing.

His recent articles reflect a diverse array of research interests and contributions to the field:

Performance evaluation of all intra Kvazaar and x265 HEVC encoders on embedded system Nvidia Jetson platform

TinyEmergencyNet: a hardware-friendly ultra-lightweight deep learning model for aerial scene image classification

Real-Time Tomato Quality Assessment Using Hybrid CNN-SVM Model

Identifying characterizations of BPM methodology in hotel industry: evidence from listed hotel companies in Egypt

Tomato Quality Classification based on Transfer Learning Feature Extraction and Machine Learning Algorithm Classifiers

Towards an Augmented Reality Goggles Integrated with a Mobile-Based Medication Adherence System

Virtual and augmented reality in biomedical engineering

Efficient Low Cost Automatic External Defibrillator Circuit

Mohammed S. Sayed Information

University

Egypt-Japan University of Science and Technology

Position

(E-JUST) & Zagazig University

Citations(all)

1081

Citations(since 2020)

634

Cited By

662

hIndex(all)

17

hIndex(since 2020)

13

i10Index(all)

36

i10Index(since 2020)

20

Email

University Profile Page

Egypt-Japan University of Science and Technology

Mohammed S. Sayed Skills & Research Interests

Digital Systems Design

Image/Video Processing

Top articles of Mohammed S. Sayed

Performance evaluation of all intra Kvazaar and x265 HEVC encoders on embedded system Nvidia Jetson platform

Authors

James Reech Majok,Mohammed Abo-Zahhad,Koji Inoue,Mohammed S. Sayed

Journal

Journal of Real-Time Image Processing

Published Date

2024/4

The growing demand for high-quality video requires complex coding techniques that cost resource consumption and increase encoding time which represents a challenge for real-time processing on Embedded Systems. Kvazaar and x265 encoders are two efficient implementations of the High-Efficient Video Coding (HEVC) standard. In this paper, the performance of All Intra Kvazaar and x265 encoders on the Nvidia Jetson platform was evaluated using two coding configurations; highspeed preset and high-quality preset. In our work, we used two scenarios, first, the two encoders were run on the CPU, and based on the average encoding time Kvazaar proved to be 65.44% and 69.4% faster than x265 with 1.88% and 0.6% BD-rate improvement over x265 at high-speed and high-quality preset, respectively. In the second scenario, the two encoders were run on the GPU of the Nvidia Jetson, and the results show the …

TinyEmergencyNet: a hardware-friendly ultra-lightweight deep learning model for aerial scene image classification

Authors

Obed Mogaka,Rami Zewai,Koji Inoue,Mohammed Sharaf Sayed

Journal

Journal of Real-time Image Processig

Published Date

2024/3

In the context of emergency response applications, real-time situational awareness is vital. Unmanned aerial vehicles (UAVs) with imagers have emerged as crucial tools for providing timely information in such scenarios. Convolutional neural networks (CNN) are effective in image processing. However, the deployment of CNN models in UAVs faces significant challenges. The CNN models involve large number of parameters and energy-costly floating-point computations beyond the memory and power available on-board the UAVs. To address these challenges, we propose a co-design optimization approach for deploying the EmergencyNet CNN model on resource-constrained UAVs. Our strategy includes channel-wise pruning to reduce the size and optimize the network architecture. Additionally, we apply additive powers-of-two (APoT) quantization to further compress the model and enhance computational …

Real-Time Tomato Quality Assessment Using Hybrid CNN-SVM Model

Authors

Hassan Shabani Mputu,Ahmed-Abdel Mawgood,Atsushi Shimada,Mohammed S Sayed

Journal

IEEE Embedded Systems Letters

Published Date

2024/2/27

The current quality assessment for fruits and vegetables relies on subjective human judgment and manual inspection, resulting in inconsistencies and inefficiencies. Due to that, there is a need for a real-time system that can accurately and efficiently assess the quality of fruits and vegetables by analyzing various parameters, such as color, texture, size, and blemishes, to ensure consistency and reduce waste in the food supply chain. This study presents the development of a real-time tomato classification system using a hybrid model that combines convolutional neural network (CNN) and support vector machines (SVM) deployed on the embedded single-board NVIDIA Jetson TX1. The selected CNN model EfficientNetB0 was used for feature extraction and SVM for classification. Notably, the EfficientNetB0-SVM hybrid model demonstrated impressive efficiency, achieving an average accuracy of 93.54% for …

Identifying characterizations of BPM methodology in hotel industry: evidence from listed hotel companies in Egypt

Authors

Mohamed Hany B Moussa,MS Sayed,Batta R Allam

Journal

Business Process Management Journal

Published Date

2024/2/5

PurposeThe purpose of this study is to identify the characterizations of business process management (BPM) methodology in hotel industry through an aggregate processing of the core cyclesteps (CCCs) of the highly-cited BPM life-cycle models in the literature aiming to highlight the major issues of the current methodological approach of BPM in hotels when to put the notion of service process into practice.Design/methodology/approachThe paper identifies and examines the most popular BPM life-cycles models in the literature and locates 15 life-cycles that are highly cited. The paper then focuses on applying the theory on nine listed hotel companies in Egypt using a questionnaire in the form of a semi-structured interview technique.FindingsThe CCSs of BPM life-cycle model applied in hotels revealed a gap between BPM theory and practice in this sector. Utilizing this model of BPM life-cycle, the paper focuses on …

Tomato Quality Classification based on Transfer Learning Feature Extraction and Machine Learning Algorithm Classifiers

Authors

Hassan Shabani Mputu,Ahmed Abdel-Mawgood,Atsushi Shimada,Mohammed S Sayed

Journal

IEEE Access

Published Date

2024/1/11

The demand for high-quality tomatoes to meet consumer and market standards, combined with large-scale production, has necessitated the development of an inline quality grading. Since manual grading is time-consuming, costly, and requires a substantial amount of labor. This study introduces a novel approach for tomato quality sorting and grading. The method leverages pre-trained convolutional neural networks (CNNs) for feature extraction and traditional machine-learning algorithms for classification (hybrid model). The single-board computer NVIDIA Jetson TX1 was used to create a tomato image dataset. Image preprocessing and fine-tuning techniques were applied to enable deep layers to learn and concentrate on complex and significant features. The extracted features were then classified using traditional machine learning algorithms namely: support vector machines (SVM), random forest (RF), and k …

Towards an Augmented Reality Goggles Integrated with a Mobile-Based Medication Adherence System

Authors

Aya Taghian,Ahmed H Abd El-Malek,Mohammed S Sayed,Mohammed Abo-Zahhad

Published Date

2023/12/18

Medication management is administered by medical therapists with the goal of improving patients' therapeutic results. Medical issues might result from missed medications or improper dosage administration. In this article, a smart mobile health (m-Health) medication reminder system is introduced. The augmented reality (AR) goggles that come with the smartphone application can help patients with common issues in managing their medications. The hardware (HW) and software (SW) of the system were planned and implemented concurrently while making sure that the non-functional requirements were satisfied using the HW/SW co-design technique. Our proposed system is smart m-Health software that was created and developed as a medicine reminder backed by AR goggles. It has a great deal of potential for use in practical contexts, according to the outcomes.

Virtual and augmented reality in biomedical engineering

Authors

Aya Taghian,Mohammed Abo-Zahhad,Mohammed S Sayed,Ahmed H Abd El-Malek

Published Date

2023/7/31

BackgroundIn the future, extended reality technology will be widely used. People will be led to utilize virtual reality (VR) and augmented reality (AR) technologies in their daily lives, hobbies, numerous types of entertainment, and employment. Medical augmented reality has evolved with applications ranging from medical education to picture-guided surgery. Moreover, a bulk of research is focused on clinical applications, with the majority of research devoted to surgery or intervention, followed by rehabilitation and treatment applications. Numerous studies have also looked into the use of augmented reality in medical education and training.MethodsUsing the databases Semantic Scholar, Web of Science, Scopus, IEEE Xplore, and ScienceDirect, a scoping review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. To find other articles, a …

Efficient Low Cost Automatic External Defibrillator Circuit

Authors

Mohammed S Sayed,Samir A Elsagheer,Mohsen A Hassan

Published Date

2023/12/18

Cardiac arrest happens when the heart stops beating suddenly, hence, blood stops flowing to the brain and other vital organs. The lack of blood flow to the brain and other organs can cause a person to lose consciousness, become disabled or die if not treated immediately. Restoring heart rhythm can happen by delivering an electrical shock to the patient through the chest wall. With the increase of out-of-hospital cardiac arrest (OHCA) the need for Automatic External Defibrillator (AED) increases. AED is a portable device used to restore normal heart rhythm to patients by delivering an electric shock through the chest to the heart when it detects an abnormal rhythm. It is easy-to-use medical device that can be used by normal person. It analyzes the heart's rhythm and, if necessary, deliver an electrical shock, or defibrillation, to help the heart regain its normal rhythm. In this paper we present a low cost and light weight …

Design of smart wearable system for sleep tracking using SVM and multi-sensor approach

Authors

Mohammed M Abo-Zahhad,Moaaz Elsayed,Mohammed Sayed,Ahmed Abdel Malek,AbdelRahman Fawaz,Ahmed Sharshar,Mohamed Abo Zahhad

Journal

JES. Journal of Engineering Sciences

Published Date

2023/7/1

Healthcare has been considered one of the main issues to be spotted and improved in a high manner. Thus, many technology trends are customized to be used in the development of the field of healthcare. One of the fields that highly affects health is sleeping, therefore, the importance of developing a portable and cost-affordable sleep-tracking system has arisen. Getting enough good-quality sleep is essential for living a healthy life. This could be done by monitoring vital signals that affect sleep quality such as heart rate, blood oxygen saturation, and positioning. Furthermore, these parameters could be used to detect sleep stages. Detecting sleep stages provides the ability to specify sleep quality and how to get better sleep hygiene. In this paper, a sleep quality monitoring system using commercial off-the-shelf sensors has been developed. The main aims are to make the system cheap, besides being portable, lightweight, and easy to use with better sleep quality and sleep stages accuracies compared to recently published systems. Based on the personalized data collected, the system could identify the sleep onset latency, the wake after sleep onset, the total sleep time, and the pattern based on the step before. Then, users would know about their quality of sleep and sleeping habits, which will be directly reflected in their health and well-being. The obtained results indicate that sleep quality accuracy is 97.5% and sleep stages accuracy is 67.5% which are better than similar systems used with commercial off-the-shelf sensors.

M-PPM Fast Delay Unit Based on Silicon-on-Insulator Coupled Resonator Optical Waveguides

Authors

Basma E Abu-Elmaaty,Mohammed S Sayed,Hossam MH Shalaby

Published Date

2023/10/21

A discrete delay system, that consists of N cascaded stages of coupled resonator optical waveguides (CROWs), is proposed to be implemented in M-ary pulse-position modulation (M-PPM) techniques. The cascaded stages allocate delay times of an emerging optical pulse to be one of 2 N possibilities. The number of ring resonators in a CROW intermediate stage is a multiple of that in the preceding stage and provides two different time delays, which are multiples of that in previous stage. The system design is developed analytically and time delay simulation is performed to validate our theoretical analysis. Both 4- and 8-PPM schemes with one pulse transmitted in each frame are used in our simulation to ensure allocating the propagating optical pulse in the convenient position. Both theoretical and simulation results are in good agreement in characterizing the device parameters and performance.

Fall Detection Algorithm Using a Smart Wearable System for Remote Health Monitoring

Authors

Abdelrahman Fawaz,Moaz Elsayed,Ahmed Sharshar,M Sayed,A Abd El-Malek,M Zahhad

Published Date

2023

Nowadays more people prefer to live independently, especially the elderly, leaving them prone to incidents that they might not be able to report. Falls, for instance, are responsible for over 3 million emergency hospitalizations for head injuries and hip fractures each year in the US In addition, other cases often go unreported, leading to further complications including chronic disabilities and even fatality. Therefore, the detection of such incidents has become of urgent necessity. The purpose of this paper is to develop and propose a machine learning support vector classification (SVC) algorithm for fall detection using accelerometer, gyroscope, and magnetometer sensors embedded in a smart wearable system for remote health monitoring. The device is placed on the subject’s wrist to collect data on various motion activities in real-time, such as walking, running, jogging, waving, and stair-climbing in addition to other static postures like standing, lying, and sitting. The constructed dataset comprises 30 subjects with over 1200 data frames. The model achieved an overall accuracy of 98.3% and a specificity of 98.2% in separating falls from other daily-life activities.

Developing an integrated medication adherence system: Exploring the potential of i‐Ware's augmented reality goggles and mobile application

Authors

Aya Taghian,Ahmed H Abd El‐Malek,Mohammed S Sayed,Mohammed Abo‐Zahhad

Journal

IET Smart Cities

Published Date

2023/9

Medical therapists often manage medications to improve therapeutic outcomes for their patients. For senior patients who take multiple drugs to manage various conditions, medication adherence is critical. To provide an immersive and engaging medication reminder experience, the authors propose i‐Ware, a smart wearable m‐Health (mobile health) device. The system's hardware and software were co‐designed to meet non‐functional requirements. The model reminds patients to take their medication, and the augmented reality goggles aid those who struggle to manage their medicine. The navigation features help users find their way home, and the audio feature reads out the date and time, useful for patients with low vision. The i‐Ware system has the potential for real‐world application and can significantly improve medication adherence. As an AR‐enabled medicine reminder, i‐Ware is an innovative solution for …

Internet of medical things and healthcare 4.0: Trends, requirements, challenges, and research directions

Authors

Manar Osama,Abdelhamied A Ateya,Mohammed S Sayed,Mohamed Hammad,Paweł Pławiak,Ahmed A Abd El-Latif,Rania A Elsayed

Published Date

2023/8/25

Healthcare 4.0 is a recent e-health paradigm associated with the concept of Industry 4.0. It provides approaches to achieving precision medicine that delivers healthcare services based on the patient’s characteristics. Moreover, Healthcare 4.0 enables telemedicine, including telesurgery, early predictions, and diagnosis of diseases. This represents an important paradigm for modern societies, especially with the current situation of pandemics. The release of the fifth-generation cellular system (5G), the current advances in wearable device manufacturing, and the recent technologies, e.g., artificial intelligence (AI), edge computing, and the Internet of Things (IoT), are the main drivers of evolutions of Healthcare 4.0 systems. To this end, this work considers introducing recent advances, trends, and requirements of the Internet of Medical Things (IoMT) and Healthcare 4.0 systems. The ultimate requirements of such networks in the era of 5G and next-generation networks are discussed. Moreover, the design challenges and current research directions of these networks. The key enabling technologies of such systems, including AI and distributed edge computing, are discussed.

detecting the differential item function of gender on the emotional balance scale using Mantel Hansel Method According to the assumptions of the item response theory

Authors

M Sayed,R Bakhoum,M Moussa,M Mohamed

Journal

Journal of Research in Education and Psychology

Published Date

2022

The aim of this research is to be to detecting the differential item function of gender on the emotional balance scale using Mantel Hansel Method According to the assumptions of the item response theory, the researcher assumes a several questions that express the research problem, which are: To what extent are the assumptions of the item response theory fulfilled in the data taken from the performance of the grading sample on the emotional balance scale?, What is the possibility of detecting the differential item function of gender on the emotional balance scale using Mantel Hansel Method? To answer the previous questions, the researcher applied his research on a sample of (639) male and female students of the scientific and literary specialization in the first and fourth year, at Faculty of Education, Minya University. The data were analyzed according to the program (Winsteps 3.73). The results showed that: the assumptions of the item response theory in the data taken from the performance of the grading sample on the emotional balance scale in the current research were fulfilled, the possibility of detecting the differential item function on the scales of the emotional balance scale using Mantel Hansel Method.

Fast-food restaurant employees’ demographics variances regarding counterproductive work behaviours in Cairo

Authors

Alyaa Essam Lotfy,Tamer Mohamed Abbas,Mohammed Sayed

Journal

International Journal of Tourism, Archaeology and Hospitality

Published Date

2022/7/1

Today, restaurants are becoming increasingly concerned about the issue of Counterproductive Work Behaviours (CWBs). As a result, every restaurant strives to lessen the effects of these negative actions (Wallace & Coughlan, 2022). Employees' CWB propagation rates vary according to demographic characteristics (Uche et al., 2017). Therefore, this study examines the variances between fast-food restaurant employees’ demographics, including gender, age, and marital status, regarding CWBs. This study's target population was employees working at fast-food restaurants in Cairo that serve fried chicken, burgers, and pizza. Because the questionnaire questions condemn the self, this study used an online questionnaire as the data collection instrument. This is because the participants' identity is hidden, ensuring their responses' credibility. The questionnaire was sent between July and August 2022 to about twenty fast-food restaurants in Cairo. About 12–15 employees from each restaurant responded. All told, 255 employees from all the restaurants responded to the survey. The questionnaire included eighteen items of CWBs (i.e., counterproductive work behaviours against individuals and counterproductive work behaviours against the organization). The results indicated that in fast-food restaurants, older employees are less likely to engage in both dimensions of CWBs than younger employees. Female employees are also less likely to engage in both dimensions of CWBs than male employees. Moreover, marital status showed no difference in CWB dimensions between fast-food restaurant employees. This research will give fast-food restaurant …

The Impact of Electronic Word-of-Mouth (eWOM) on the Tourists’ Purchasing Intentions in Tourism and Hotel Sectors

Authors

Haidy Elsaid,Mohammed Sayed

Journal

International Academic Journal Faculty of Tourism and Hotel Management

Published Date

2022/6/1

Purpose Word of Mouth (WOM) is an important information source for consumers when making purchase decisions, especially in the tourism and hospitality industries, where it is difficult to evaluate intangible products before consumption. Consumers increasingly use online resources to share their experiences on goods and services, and to compare them to their substitutes. The growth of digital communication across social networks, webpages, and other platforms has generated a new approach of WOM, which is: Electronic Word of Mouth (eWOM). Objective This paper aims to explore the impact of eWOM on the purchasing intentions of tourists in tourism and hotel sectors, utilizing the Information Acceptance Model (IACM).Method Data is collected through a web-based survey from customers who have experience with tourism and hotel organizations in Egypt via travel applications and websites. The questionnaire designed based on (IACM) Model. A total of 233 valid forms were received electronically and were statistically analyzed. Structural equation modelling was used to investigate the hypothesized correlations.Findings This study highlights the importance of consumers' behaviors towards information as well as the characteristics of information. These findings will provide marketers with a framework to understand the impact of eWOM in travel apps and websites on tourists' purchasing intentions. There was a significant impact on management by explaining the limitations of eWOM information for travel applications and websites. Therefore, the results of this study would enable marketers to understand the dynamics of eWOM on …

Efficient coding unit classifier for HEVC screen content coding based on machine learning

Authors

Nabila Elsawy,Mohammed S Sayed,Fathi Farag

Journal

Journal of Real-Time Image Processing

Published Date

2022/4/1

The Video Coding Joint Collaboration team (JCT-VC) has been working on an emerging standard for screen content coding (SCC) as an extension of high efficiency video coding (HEVC) standard known as HEVC-SCC. The two powerful coding mechanisms used in HEVC-SCC are intra block copy (IBC) and palette coding (PLT). These techniques achieve the best coding efficiency at the expense of extremely high computational complexity. Therefore, we propose a new technique to minimize computational complexity by skipping undesired modes and retaining coding efficiency. A fast intra mode decision approach is suggested based on efficient CU classification. Our proposed solution depends on categorizing a CU as a natural content block (NCB) or a screen content block (SCB). Two classifiers are used for the classification process. The first one is a neural network (NN) classifier, and the other is an …

Long-term reverse remodeling and clinical improvement by MultiPoint Pacing in a randomized, international, Middle Eastern heart failure study

Authors

Abdulmohsen Almusaad,Raed Sweidan,Haitham Alanazi,Abdelrahman Jamiel,Fayez Bokhari,Yahya Al Hebaishi,Ahmed Al Fagih,Najib Alrawahi,Amjad Al-Mandalawi,Mohamed Hashim,Bandar Al Ghamdi,Mohammad Amin,Mohamed Elmaghawry,Naeem Al Shoaibi,Antonio Sorgente,Maria Loricchio,Ghaliah AlMohani,Ismail Al Abri,Edmon Benjamin,Nazar Sudan,Alexandre Chami,Nima Badie,Mohammed Sayed,Ahmad Hersi

Journal

Journal of Interventional Cardiac Electrophysiology

Published Date

2022/3

PurposeCardiac resynchronization therapy (CRT) with multipoint left ventricular (LV) pacing (MultiPoint™ Pacing, MPP) has been shown to improve CRT response, although MPP response using automated pacing vector programming has not been demonstrated in the Middle East. The purpose of this study was to compare the impact of MPP to conventional biventricular pacing (BiV) using echocardiographic and clinical changes at 6-month post-implant.MethodsThis prospective, randomized study was conducted at 13 Middle Eastern centers. After de novo CRT-D implant (Abbott Unify Quadra MP™ or Quadra Assura MP™) with quadripolar LV lead (Abbott Quartet™), patients were randomized to either BiV or MPP therapy. In BiV patients, the LV pacing vector was selected per standard practice; in MPP patients, the two LV pacing vectors were selected automatically using VectSelect. CRT response was defined at 6 …

Intelligent IoT-Based Tracking System for Constant Supervision of Health Status and Daily Activities of Children

Authors

Mohammed Abo-Zahhad,Mohammed S Sayed,Ahmed H Abd El-Malek,Mayar Hossam,Nora Atef,Sarah Reda

Published Date

2022/12/19

At some point, kids start to grow and acquire more independence to explore the world independently. And while it is a natural stage of kids’ growth, parents usually feel restless during this stage, fearing that their children might face dangers in the absence of their supervision. This problem is the main motivation behind the system introduced in this paper. It is aimed to assist parents in maintaining the safety of their children by tracking the child’s relative location and monitoring the health status to ensure his/her wellbeing. It also follows up and supervises the daily activities and prevents any potential danger that can befall the child. The system consists of two main units. The first unit is implemented in form of a bracelet worn by the child, while a mobile application acts as the second unit on the parents’ side. In comparison to the prior introduced systems, this system is designed to be a comprehensive system that …

Complex pattern Jacquard fabrics defect detection using convolutional neural networks and multispectral imaging

Authors

Mahmoud M Khodier,Sabah M Ahmed,Mohammed Sharaf Sayed

Journal

IEEE Access

Published Date

2022/1/19

Manual inspection of textiles is a long, tedious, and costly method. Technology has solved this problem by developing automatic systems for textile inspection. However, Jacquard fabrics present a challenge because patterns can be complex and seemingly random to systems. Only a few in-depth studies have been conducted on jacquard fabrics despite their important and intriguing nature. Previous studies on jacquard fabrics are of simple patterns. This paper introduces a new and novel field in fabrics defect detection. Complex-patterned jacquard fabrics are much more challenging. In this paper, novel defect detection models for jacquard-patterned fabrics are presented. Owing to the lack of available databases for jacquard fabrics, we compiled and experimented on our own novel dataset. Our dataset was collected from plain, undyed jacquard fabrics with different complex patterns. In this study, we used and …

See List of Professors in Mohammed S. Sayed University(Egypt-Japan University of Science and Technology)

Mohammed S. Sayed FAQs

What is Mohammed S. Sayed's h-index at Egypt-Japan University of Science and Technology?

The h-index of Mohammed S. Sayed has been 13 since 2020 and 17 in total.

What are Mohammed S. Sayed's top articles?

The articles with the titles of

Performance evaluation of all intra Kvazaar and x265 HEVC encoders on embedded system Nvidia Jetson platform

TinyEmergencyNet: a hardware-friendly ultra-lightweight deep learning model for aerial scene image classification

Real-Time Tomato Quality Assessment Using Hybrid CNN-SVM Model

Identifying characterizations of BPM methodology in hotel industry: evidence from listed hotel companies in Egypt

Tomato Quality Classification based on Transfer Learning Feature Extraction and Machine Learning Algorithm Classifiers

Towards an Augmented Reality Goggles Integrated with a Mobile-Based Medication Adherence System

Virtual and augmented reality in biomedical engineering

Efficient Low Cost Automatic External Defibrillator Circuit

...

are the top articles of Mohammed S. Sayed at Egypt-Japan University of Science and Technology.

What are Mohammed S. Sayed's research interests?

The research interests of Mohammed S. Sayed are: Digital Systems Design, Image/Video Processing

What is Mohammed S. Sayed's total number of citations?

Mohammed S. Sayed has 1,081 citations in total.

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