Reviewerly/exHarmony huggingface dataset:
READABILITY LEVEL OF THE ARABIC LANGUAGE TEXTBOOK OF DIPLOMA TAHFIZ AL-QURAN &amp; AL-QIRAAT DARUL QURAN JAKIM

Textbooks, or special reference books for language learning, are an important medium in language learning at IPTs in Malaysia. The level of language achievement among IPT students who are not native speakers of Arabic is still low due to various factors, including the ineffective content of textbooks. The evaluation of reading material takes into account many aspects, especially the level of readability. Readability is the level or ease of a material or reading text, while a quality textbook is a reading text that is easy to understand. This study evaluates the readability of Arabic texts among Diploma Tahfiz Al-Quran and Al-Qiraat Darul Quran students in Malaysia. A total of 300 students consists of students in semester 4 and students who have gone through semester 4. This study is to evaluate the level of readability of the textbooks they use through a level-Cloze Test, which will be the start of further study of the book. This readability study serves as a document that can help JAKIM, lecturers, syllabus drafters, textbook writers, and other parties involved. In order to achieve the objectives of this study, the Cloze Test was constructed from three Arabic texts found in Darul Quran Arabic textbooks. Through this test, students are tested to see the difference in scores obtained from the aspect of readability. The study data is analyzed quantitatively and descriptively. The results of the test conducted found that the mean score for the Cloze Test on the textbook was 88%, so this result proves that the level of readability of Darul Quran JAKIMs Arabic textbook is at frustration levelwhich means that the textbook is not suitable enoughfor the ability of students at the Diploma level in Darul Quran JAKIM, which is still at a low level that is less suitable for teaching and learning purposes. Therefore, the responsible parties, especially the drafters of the Darul Quran Arabic language curriculum, should take into account the level of readability of the text provided before it is used as student learning material in order to match the level of the students language skills.
Hold the Line – Should You Use Your Phone in the OR?

Safety Tip of the Month| August 2023 Hold the Line – Should You Use Your Phone in the OR? ASA Monitor August 2023, Vol. 87, 30. https://doi.org/10.1097/01.ASM.0000949604.30719.25 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn Email Cite Icon Cite Get Permissions Search Site Citation Hold the Line – Should You Use Your Phone in the OR?. ASA Monitor 2023; 87:30 doi: https://doi.org/10.1097/01.ASM.0000949604.30719.25 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll PublicationsASA Monitor Search Advanced Search Topics: telephone How many times have you walked into an OR and seen colleagues scrolling on their mobile phone or tablet? Nobody wants to admit they've renewed a Netflix subscription or ordered something from Amazon in the middle of a surgical procedure, but this does happen. In one study, 24% of anesthesia professionals, including attendings, residents, and nurse anesthetists, reported texting in the OR, while 11% admitted to scrolling. Interestingly, 52% of the people who responded observed other anesthesia professionals texting, 14% talking on the phone, and 34% browsing the Internet. Distractions are certainly a problem: 15% of the people responding to that survey observed someone else who was distracted by an electronic device (Int J Qual Health Care 2015;27:418-20). So, is it appropriate to use a personal electronic device in the OR? Personal electronic devices like smartphones and tablets are ubiquitous in day-to-day life, and they are indispensable in... You do not currently have access to this content.
Improving Accuracy of Recommendation Systems with Deep Learning Models

Recommendation systems have been demonstrated to be an effective strategy for preventing information overload, due to the ever-increasing amount of online information. It is impossible to overestimate the effectiveness of recommendation systems, considering their general employment in online applications and their ability to relieve a range of difficulties related to excessive options. For a variety of reasons, including its superior performance in computer vision as well as natural language processing (NLP), deep learning (DL) has gained considerable scholarly interest in recent years but also to its appealing potential to start from scratch and learn how to express features. Deep learning has recently proved its use in information retrieval along with recommendation system research, demonstrating its pervasiveness. The area of recommendation systems that combines deep learning is booming. Deep learning-based recommendation systems are the subject of much current research, which is summarized in this article. A comprehensive analysis of the current status of deep learning-based recommendation models is presented in this research paper. Last but not the least, it focuses on current developments and gives new insights on this cutting-edge new industry.
Performance Evaluation of Yoga Pose Classification Model Based on Maximum and Minimum Feature Extraction

Yoga is an ancient process that creates wired and complex poses for the human body. Yoga is the best exercise that creates a complete balance between the mind and body. It is important to create a correct body posture in yoga. The proposed approach represents the classification of various yoga poses using a deep learning algorithm. To classify correct yoga posture using a neural network, it is necessary to estimate the correct position of body joints as the keypoints. The correct position of keypoints creates the correct posture for various types of yoga. The first phase of the proposed system identifies the correct position of keypoints of body joints for various yoga poses. It records the keypoints of the body joints for individual yoga posture in form of a database. In the second phase, the Keras dense neural network is trained to classify the correct yoga pose. The proposed system can classify 10 different types of yoga postures viz. down dog pose, tree pose, plank pose, cobra pose, chair pose, warrior pose, warrior2 pose, dog pose, tree_front pose, and goddess pose. Correct pose classification is evaluated using confusion matrix parameters viz. Precision, Recall, and F1-Score. It seems that the higher the F1-Score identifies the pose is correctly classified by the model. In the proposed approach, all three mentioned parameters are measured for individual yoga pose for 17 body joints and 33 body joints respectively. The F1-Score is always maximum for 33 body joints as feature extraction then 17 body joints as feature extraction. The highest F1-Score achieved for the chair pose as 0.92 (for 33 body joints) whereas the minimum F1-Score achieved for the tree pose is 0.63 (for 33 body joints). Comparative analysis of model accuracy and model loss for 33 body joints and 17 body joints is represented as a part of the test results. The model achieves the highest accuracy as 87% for 33 body joints as feature extraction with minimum loss.
Encryption Using Binary Key Sequences in Chaotic Cryptosystem

Transmission of images on the network is considered insecure which has security-related issues. In this paper, to provide security to digital images, an encryption system that uses four chaotic maps for binary key sequence generation is proposed. The system consists of stages namely, confusion, generation of random binary chaotic key sequence, pseudo-random number generation (RN), and diffusion. Keys for encryption are chosen randomly based on a pseudo random generator from the selected chaotic maps by the linear feedback shift register (LFSR). The algorithm achieves good results in terms of NPCR, UACI, and entropy values. The developed cryptosystem resists differential attacks, is sensitive to minor alterations in the keys, and has a large key space.
IMPROVING LOGICAL THINKING COMPETENCE USING GAMES FOR HIGH SCHOOL STUDENTS

Online learning makes students bored and lazy. This condition requires teachers to think of other ways of teaching and learning activities. Gamification is a learning method using games as a teaching and learning tool. This service uses games on the code.org website application to increase high school-level students' interest in learning. In addition to gamification, several methods are applied to increase students' interest in learning, one of which is by providing personal assistance. The method applied was considered successful in increasing the interest and focus of the participants.
Dyslexia deep clustering using webcam-based eye tracking

Dyslexia is a neurodevelopmental impairment that causes difficulties in reading and can have significant academic, social, and economic impacts. In Morocco, Dyslexia accounts for 37% of children's school failures. Early detection of dyslexia is crucial to help children reach their academic potential and prevent low self-esteem. To address this issue, a dyslexia screening tool using webcam-based eye tracking was developed for the Arabic language. The tool was tested on a dataset of 61 students from three primary schools in southern Morocco, and the results showed that using Arabic dyslexic-friendly typefaces improved reading performance, particularly for those with low reading performance. Deep clustering was used to reduce the dimensionality of the dataset, and the subjects were gathered using unsupervised k-means based on AutoEncoder output. The three clusters produced showed a significant difference in many dyslexia traits, such as the number and duration of fixations, as well as the saccade period. These findings suggest that webcam-based eye-tracking techniques have the potential to be used as an initial dyslexia diagnosis tool to assess if a child exhibits some of the typical symptoms of dyslexia and whether they should seek a professional full dyslexia diagnosis.
Intelligent vehicle perpendicular parking path planning and tracking control

This paper presents a novel automatic perpendicular parking algorithm, taking into account the initial heading angle of the intelligent vehicle. The feasible parking starting point is located based on the vehicle’s minimum turning radius, the relative pose between the vehicle and the parking spot as well as the coordinates of right vertex of the parking space. The type of parking (i.e. single-step or multi-step) is determined on the basis of the collision avoidance constraint. Considering the constraint of the vehicle steering actuator, the quartic spline curve is used to smooth the single-step parking path and the last path into the parking space of multi-step parking, so as to improve the path characteristics. Then, a desired heading angle function of the vehicle is introduced, and the lateral displacement deviation in path tracking tends to zero when the actual heading angle approaches the desired heading angle. Subsequently, a nonlinear integral sliding mode controller (NISMC) with the hyperbolic tangent function based on dynamic boundary layer as the switching function is proposed to track the desired heading angle, so as to complete the path-tracking process. Co-simulations and Hardware-in-the-Loop (HIL) tests are carried out to verify the effectiveness of the designed algorithm, simulation and test results show that the desired parking path can be feasibly planned even when the vehicle has an initial heading angle; meanwhile, the tracking performance based on the proposed NISMC controller not only has small tracking error, smooth control output, but also strong response rate and robustness.
Evaluation of the softness and its impression of visual stimuli in VR space

To examine the softness and impression of visual objects in VR (Virtual Reality) space, the impression of the visual stimuli in VR space was measured using the subjective evaluation of a seven-rank scale by changing with each the value of the deformation resistance of the stimuli, of shapes, and colors. The value of the deformation resistance of the stimuli expresses the degree of deformation to return to the original of the object when touching it in VR space. The lower value indicates the larger deformation like pudding and the higher one is the smaller one like thick rubber they were used three types of values lower and higher, and no-deformation of the objects. The shapes of objects as the stimuli were three shapes (sphere, cube, pyramid). The colors of the stimuli were selected from five colors (red, green, green, gray, and white) and they have used two types of the feeling of materials (matte and metallic) in each color. Ten participants were asked to subjectively evaluate the softness and impression of the stimulus. In the results, the evaluation changes from soft to hard by increasing the values of deformation resistance in all the stimuli in VR space. It is suggested that the degree of the deformation to return to the original can express the softness of objects when touching them in VR space even though the user does not touch them physically. It also discussed the relationship between softness and its impression of the stimuli in VR space.
Quality of Experience in Internet of Things: A Systematic Literature Review

With the rapid growth of the Internet of Things paradigm, a tremendous number of applications and services that require minimal or no human involvement have been developed to enhance the quality of everyday life in various domains. In order to ensure that such services provide their functionalities with the expected quality, it is essential to measure and evaluate this quality, which can be in some cases a challenging task due to the lack of human intervention and feedback. Recently, the vast majority of the Quality of Experience QoE works mainly address the multimedia services. However, the introduction of Internet of Things IoT has brought a new level of complexity into the field of QoE evaluation. With the emerging of the new IoT technologies such as machine to machine communication and artificial intelligence, there is a crucial demand to utilize additional evaluation metrics alongside the traditional subjective and objective human factors and network quality factors. In this systematic review, a comprehensive survey of the QoE evaluation in IoT is presented. It reviews the existing quality of experience definitions, influencing factors, metrics, and models. The review is concluded by identifying the current gaps in the literature and suggested some future research directions accordingly.
ANALISIS MATERIAL SERAT ALAM TEBU SEBAGAI BAHAN PEREDAM SUARA

Abstract &#x0D; Material Sugarcane natural fiber material can be used as a sound absorber material. In measuring the value of the sound absorption coefficient of the cane natural fiber silencer using the sound level meter application on the smartphone to measure the intensity of sound (dB) and the frequency generator application connected to the speaker as a sound source (Hz). The test uses an acoustic box as a miniature room that will be tested for its sound absorption coefficient values coated with sugarcane natural fibers. The purpose of this study is to find out the influence of sugarcane fibers in reducing noise and to find out the effect of frequency variations on the value of the sound absorption coefficient. Measurement of the noise level of the sugarcane natural fiber material on the acoustic wall produces different sound absorption coefficient values based on variations in the frequency of the sound source. The greater the frequency value, the higher the absorption coefficient value. Frequency variations used include 500 Hz, 1000 Hz, 1500 Hz, 2000 Hz, 2500 Hz, and 3000 Hz. The value of the sound absorption coefficient drops at a frequency of 1000 Hz but there is a re-increase at frequencies above 1500 Hz. The smallest sound absorption coefficient is obtained at the time of frequency 1500 Hz with a value of = 0.01047 and the largest at the time of frequency 3000 Hz with a value of = 0.10139. The coefficient value is too small, so it is not effective in muffling the sound.
The Effects of Teaching Methods on Korean Academic Vocabulary Learning: Focusing on Integrated FFI and Isolated FFI

The purpose of this study is to examine the effect of integrated and isolated form-focused instruction on the learning and retention of Korean academic vocabulary. To this end, 34 foreign students were given integrated and isolated form-focused instruction, and a pre-test, an immediate post-test, and a delayed post-test were conducted together. As a result, both integrated and isolated form-focused instruction had a positive effect on the learning and retention of the target academic vocabulary, but only the isolated form-focused instruction showed a statistically significant difference. With this study as an opportunity, it is hoped that follow-up studies from various perspectives, such as learner proficiency and vocabulary types, will be continued to provide effective vocabulary teaching and learning method
Exploring Artist’s Way Program to Restore and Demonstrate Creativity in Adults

The purpose of this study is to examine the main contents and application cases of Artist’s Way program, which was created by Julia Cameron and used worldwide for the recovery and display of creativity of adults, and to have an educational discussion. In this regard, It will be possible to consider the direction of reflection and composition as subjects or extracurricular programs at the university liberal arts level in the future. For this study, literature data such as Julia Cameron’s Artist’s Way books and articles were comprehensively investigated. Based on this, the basic concept, purpose, tools, main contents, and use cases of Artist’s Way were presented. Through this study, specific ideas and help for understanding and implementing a self-growth program that promotes creativity for adults will be obtained.
P‐2.32: Six‐degree‐of‐freedom Platform Motion Anomaly Prediction Technology Based on Binocular Vision

Binocular stereo vision is based on the principle of parallax and uses imaging equipment to obtain two images of the measured object from different positions, and obtains the three-dimensional geometric information of the object by calculating the position deviation between the corresponding points of the image. As an important execution component of the six-degree-of-freedom platform in the flight simulator, the electric cylinder can undertake the important task of dynamic simulation, and its abnormal working state directly affects the training effect and life safety of the flight simulator users. In this paper, the electric cylinder position pose is obtained by the three-dimensional point cloud method, and the improved active learning anomaly detection algorithm is proposed to predict the electric cylinder position posture, so as to determine whether the platform electric cylinder fails.
Non-Interactive Multi-Client Searchable Symmetric Encryption With Small Client Storage

Considerable attention has been paid to dynamic searchable symmetric encryption (DSSE) which allows users to search on dynamically updated encrypted databases. To improve the performance of real-world applications, recent non-interactive multi-client DSSE schemes are targeted at avoiding per-query interaction between data owners and data users. However, existing non-interactive multi-client DSSE schemes do not consider forward privacy or backward privacy, making them exposed to leakage abuse attacks. Besides, most existing DSSE schemes with forward and backward privacy rely on keeping a keyword operation counter or an inverted index, resulting in a heavy storage burden on the data owner side. To address these issues, we propose a non-interactive multi-client DSSE scheme with small client storage, and our proposed scheme can provide both forward privacy and backward privacy. Specifically, we first design a lightweight storage chain structure that binds all keywords to a single state to reduce the storage cost. Then, we present a Hidden Key technique, which preserves non-interactive forward privacy through time range queries, ensuring that data with newer timestamps cannot match earlier time ranges. We conduct extensive experiments to validate our methods, which demonstrate computational efficiency. Moreover, security analysis proves the privacy-preserving property of our methods.
Explaining Anomalous Events in Flight Data of UAV With Deep Attention-Based Multi-Instance Learning

Ensuring the safety and reliability of unmanned aerial vehicles (UAVs) has become a critical issue as they continue to advance. Analyzing anomalous events using event-based explanations is an effective approach to identifying key anomalous behaviors and mitigating potential risks. However, this task is challenging because anomalous events in flight data lack time-step labels in real-world UAV flight scenarios. To address this challenge, we propose a dual attention-based multi-instance learning (DA-DI-MIL) for pinpointing anomaly instances and automatically explaining anomalous events. Our MIL-based framework, from a weakly supervised learning perspective, treats a segment of flight data as a ‘bag’ with an available label, and its time steps as ‘instances’ without labels. The dual attention mechanism in DA-DI-MIL combines a temporal pseudo-label, predicted by temporal attention, and sensor variable importance obtained from delta feature attention to better pinpoint anomalies from instance-level labels. We use these labels in our proposed MIL-based framework to establish the relationships between anomalous events and anomalous behaviors. We conducted extensive experiments on real UAV flight data with engine failures to demonstrate the effectiveness and robustness of our proposed method compared to existing state-of-the-art methods. DA-DI-MIL achieves near 90% in evaluation metrics with less than 5 time steps' delay of anomalous event detection and around 85% in temporal anomaly detection. Additionally, we present an illustration of both global and local interpretations in the time domain and feature space, providing comprehensive insights into anomalous events. Our proposed method has efficiently and automatically explained anomalous events in UAV flight data, contributing to high-level aviation safety and reliability.
P‐2.18: Overview and Prospect of the Application of Digital Human in Medical Field

This article briefly describes the concept of digital human and the difference between it and virtual human and digital virtual human, summarizes the application status of digital human in the medical field, by analyzing the advantages and characteristics of digital human and applying it in the medical field, such as the construction of digital virtual human model, discusses the advantages and disadvantages of digital human in the medical field and its application prospects. It is of great significance to study the medical research mode, clinical teaching mode and clinical medical work mode in the digital age.