Reviewerly/exHarmony huggingface dataset:
AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning

With the advance of text-to-image (T2I) diffusion models (e.g., Stable Diffusion) and corresponding personalization techniques such as DreamBooth and LoRA, everyone can manifest their imagination into high-quality images at an affordable cost. However, adding motion dynamics to existing high-quality personalized T2Is and enabling them to generate animations remains an open challenge. In this paper, we present AnimateDiff, a practical framework for animating personalized T2I models without requiring model-specific tuning. At the core of our framework is a plug-and-play motion module that can be trained once and seamlessly integrated into any personalized T2Is originating from the same base T2I. Through our proposed training strategy, the motion module effectively learns transferable motion priors from real-world videos. Once trained, the motion module can be inserted into a personalized T2I model to form a personalized animation generator. We further propose MotionLoRA, a lightweight fine-tuning technique for AnimateDiff that enables a pre-trained motion module to adapt to new motion patterns, such as different shot types, at a low training and data collection cost. We evaluate AnimateDiff and MotionLoRA on several public representative personalized T2I models collected from the community. The results demonstrate that our approaches help these models generate temporally smooth animation clips while preserving the visual quality and motion diversity. Codes and pre-trained weights are available at https://github.com/guoyww/AnimateDiff.
Performance Comparison of Pre-trained Models for Speech-to-Text in Turkish: Whisper-Small and Wav2Vec2-XLS-R-300M

In this study, the performances of the Whisper-Small and Wav2Vec2-XLS-R-300M models which are two pre-trained multilingual models for speech to text were examined for the Turkish language. Mozilla Common Voice version 11.0 which is prepared in Turkish language and is an open-source data set, was used in the study. The multilingual models, Whisper- Small and Wav2Vec2-XLS-R-300M were fine-tuned with this data set which contains a small amount of data. The speech to text performance of the two models was compared. WER values are calculated as 0.28 and 0.16 for the Wav2Vec2-XLS- R-300M and the Whisper-Small models respectively. In addition, the performances of the models were examined with the test data prepared with call center records that were not included in the training and validation dataset.
GPT4RoI: Instruction Tuning Large Language Model on Region-of-Interest

Visual instruction tuning large language model(LLM) on image-text pairs has achieved general-purpose vision-language abilities. However, the lack of region-text pairs limits their advancements to fine-grained multimodal understanding. In this paper, we propose spatial instruction tuning, which introduces the reference to the region-of-interest(RoI) in the instruction. Before sending to LLM, the reference is replaced by RoI features and interleaved with language embeddings as a sequence. Our model GPT4RoI, trained on 7 region-text pair datasets, brings an unprecedented interactive and conversational experience compared to previous image-level models. (1) Interaction beyond language: Users can interact with our model by both language and drawing bounding boxes to flexibly adjust the referring granularity. (2) Versatile multimodal abilities: A variety of attribute information within each RoI can be mined by GPT4RoI, e.g., color, shape, material, action, etc. Furthermore, it can reason about multiple RoIs based on common sense. On the Visual Commonsense Reasoning(VCR) dataset, GPT4RoI achieves a remarkable accuracy of 81.6%, surpassing all existing models by a significant margin (the second place is 75.6%) and almost reaching human-level performance of 85.0%. The code, dataset, and demo can be found at https://github.com/jshilong/GPT4RoI.
OmniBoost: Boosting Throughput of Heterogeneous Embedded Devices under Multi-DNN Workload

Modern Deep Neural Networks (DNNs) exhibit profound efficiency and accuracy properties. This has introduced application workloads that comprise of multiple DNN applications, raising new challenges regarding workload distribution. Equipped with a diverse set of accelerators, newer embedded system present architectural heterogeneity, which current run-time controllers are unable to fully utilize. To enable high throughput in multi-DNN workloads, such a controller is ought to explore hundreds of thousands of possible solutions to exploit the underlying heterogeneity. In this paper, we propose OmniBoost, a lightweight and extensible multi-DNN manager for heterogeneous embedded devices. We leverage stochastic space exploration and we combine it with a highly accurate performance estimator to observe a x4.6 average throughput boost compared to other state-of-the-art methods. The evaluation was performed on the HiKey970 development board.
The Impact of Distinctive Features of Blockchain Technology on the Customer's Agility: The Modified Role of the Requirements for the Implementation of Blockchain Technology-Applied Study in the Egyptian Pharmaceutical Companies

This study aims to investigate to what extent the sample recognizes the distinctive features of blockchain technology, the requirements of the implementation of this technology and customer agility (sensing and responsing), as well as how this effect varies with the presence of a modifying variable (the requirements of the implementation of this technology), as the study aims to identify the significant differences between the views of the sample on the distinctive features of blockchain technology, the requirements of the implementation of this technology and customer agility according to the nature of the ownership of the company (foreign or private). The study was applied to 388 managers (top and IT managers of foreign and private pharmaceutical companies). Using SEM available in SmartPLS 2.0.M3, the study found that top and IT managers of foreign and private pharmaceutical companies recognize the presence of the distinctive features of blockchain technology, the requirements for its implementation and customer agility, as the results proved a positive significant effect of the distinctive features of blockchain technology on customer agility and a positive significant effect of the requirements of the implementation of blockchains on the relationship between them as a modifying variable. The study proved that there are statistically significant differences between the sample of mangers about distinctive features of blockchain technology and the requirements of the implementation of this technology in favor of foreign companies, while there have been no significant differences in relation to the customer agility. The study presents several recommendations, including supporting the availability of the requirements for the implementation of blockchain technology to significantly and effectively support customer agility in pharmaceutical companies operating in Egypt.
The Characteristics of Trademark Management and Its Role in Achieving Competitive Advantage: Applied Study- Qatar Telecommunication Company

This study aims to examine the characteristics of trademark management and its role in achieving competitive advantage at Qatar Telecommunication Company "Ooredoo". To meet this objective, a quantitative descriptive approach was adopted through using a questionnaire as the main tool for data collection. A random sample of (340) participants was randomly recruited from the company's employees. The questionnaires were electronically distributed via the Google Form program. About (311) questionnaires were completed which represented (91%) of all questionnaires. The data was statistically analyzed. The results revealed that there is a significant impact of the characteristics of trademark management on achieving competitive advantage in the company. Furthermore, the impact of every dimension of the competitive advantage represented in product quality, response to customers, creativity, innovation and efficiency was statistically significant. The findings also showed that the characteristics of the company's brand management and competitive advantage are applied at a high level. The study recommends that the company proceeds in studying the changes in the market and tools to achieve competitive advantage, identifying future opportunities to utilize them to achieve this advantage, besides developing technology to improve services. The study also suggests conducting future research that shows the relationship of the brand with variables, such as customer satisfaction, the degree of trust in the brand, the phenomenon of brand imitation and its impact on the reputation of the original brand and ways to combat this phenomenon.
An Efficient and Secure Blockchain Based Homomorphic Encryption for Intelligent Transport System

Abstract The volume of automobiles on roadways keeps growing and crashes increase in frequency, managing traffic routes gets increasingly crucial. Real-time messages are delivered through wireless connections in Intelligent Transport Systems(ITS), although this might raise safety and confidentiality issues. Safety flaws, hefty data processing and transmission costs, and safety vulnerabilities plague current traffic route management ideas. With fog-based ITS's, a simple congestion routing management system was developed to overcome these problems. In this system, automobiles encrypted their travel courses using homomorphic encryption and transfer the secured data onto a fog node. Despite being aware of what specific path was taken by every automobile, Traffic Control Centre (TMC) decodes the received ciphertexts which have been collected by the fog node and manages congestion based on the decoded data. Additionally, the plan makes utilization of the blockchain system to maintain the vehicle's public key. This makes it possible to manage individual vehicle's public key securely and impenetrably, guaranteeing that only authorized cars may join the ITS. The idea was put into operation via the Rinkeby test network based on Ethereum to show that it is feasible. According to the results of the study, this aforementioned approach outperforms other pertinent representative schemes. This lightweight traffic route management system offers a safe and effective method for controlling travel routes in ITSs by utilizing homomorphic encryption and blockchain technology. By addressing the safety and confidentiality concerns raised by sending real-time communications via wireless methods, also lowers the computation and transmission costs of previous ideas. This approach has the potential to improve traffic safety and ease congestion in ITS's.
Retracted: Realization of English Instructional Resources Clusters Reconstruction System Using the Machine Learning Model

[This retracts the article DOI: 10.1155/2022/2838935.].
Retracted: Construction of Teaching Mode of Film and TV Art in Institution of Higher Learning Using Virtual Simulation Technology

[This retracts the article DOI: 10.1155/2022/6216232.].
Retracted: Sports Feedback System Based on Video Digital Processing

[This retracts the article DOI: 10.1155/2022/2859567.].
Retracted: Contrast-Enhanced Ultrasound and Magnetic Resonance Enhancement Based on Machine Learning in Cancer Diagnosis in the Context of the Internet of Things Medical System

[This retracts the article DOI: 10.1155/2022/4378173.].
Retracted: Effect Analysis of Nursing Method Based on Stratified Emergency Knowledge in Emergency Myocardial Infarction

[This retracts the article DOI: 10.1155/2022/3505228.].
Retracted: Prediction Model of Piano Collective Class Teaching and Learning Effect Based on Deep Learning

[This retracts the article DOI: 10.1155/2022/2572372.].
Retracted: Ensemble Learning-Based Multi-Cues Fusion Object Tracking in Complex Surveillance Environment

[This retracts the article DOI: 10.1155/2022/9165744.].
Retracted: Application of Sandwich Teaching Method Based on Network Platform in Rehabilitation Nursing Teaching in Postepidemic Era

[This retracts the article DOI: 10.1155/2022/7489023.].
Retracted: Development of Wireless Network Indoor Coverage System Based on Optical Fiber Distribution System

[This retracts the article DOI: 10.1155/2022/9728536.].
Retracted: The Method of Pose Judgment of Potential Motion Damage in 3D Image Analysis

[This retracts the article DOI: 10.1155/2021/4743231.].
Imaging static Fourier transform spectrometry: impact of trajectory perturbations on the hyperspectral images

Imaging static Fourier transform spectrometry (isFTS) may be used for pushbroom air-or spaceborne hyperspectral remote sensing.In isFTS, the spectral information is multiplexed over several instantaneous images, and numerical reconstruction is needed to recover the full spectrum for each pixel.The registration of instantaneous images is a crucial step.Unsufficient precision leads to artefacts on the images and degradation of the estimated spectra.We developed a simulation program of the entire processing chain of an isFTS system that can reproduce the degradations of actual isFTS images.Using this program we studied spatial and spectral effects of temporally correlated and uncorrelated trajectory perturbations.We also performed a theoretical study to quantify these degradations.We demonstrated that the most significant degradations occur in the regions of high radiance gradient.
Retracted: Nursing of Gastrointestinal Peristalsis Function Recovery after Abdominal Mirror Surgery for Rectal Cancer Patients Based on Intelligent Electronic Medicine

[This retracts the article DOI: 10.1155/2021/6668885.].
Tingkat Pengetahuan tentang Anemia dan Hubungannya dengan Kepatuhan Konsumsi Tablet Fe pada Remaja Putri di MTS Raudhatul Muta’allimin Tahun 2021

Introduction: Adolescence is a period that is passed in every individual development, adolescent development is a period of individual development which is a period of achieving mental, emotional, social, physical and escape patterns from childhood to adulthood Objectives: To find out the relationship between the level of knowledge about anemia and the compliance with consumption of Fe tablets in young women at MTs Raudhatul Muta'allimin in 2021 Methods: The research design used is correlation analytic with a cross-sectional correlation or cross-sectional approach. Cross-sectional approach. The population in this study were female students at Mts Raudhatul Muta’allimin 75 people. The sample calculation in this study was total sampling. The sample inclusion criteria in this study were young women who attended school at Mts Raudhatul Muta’allimin in 2021. The instrument used a questionnaire. In this study, the Chi-square test was used to see the dependence between the independent variables and the dependent variable on a nominal or ordinal scale. Results: The results of the bivariate analysis of the level of knowledge of anemia showed p = 0.000, and the bivariate analysis of adherence to Fe tablet consumption showed p = 0.000. Conclusion: Based on the results of research on the relationship between the level of knowledge about anemia and adherence to Fe tablets consumption in adolescent girls at MTs Raudhatul Muta'allimin in 2021
APLIKASI CHATBOT UNTUK PENERIMAAN MAHASISWA BARU UNIVERSITAS INDO GLOBAL MANDIRI MENGGUNAKAN DEEP LEARNING

Most prospective new students want to get fast and accurate information. Prospective new students certainly want to get a lot of information about the procedure for registering new students at each tertiary institution, especially Indo Global Mandiri University. Information on new student admissions at Indo Global Mandiri University only uses websites and social pages as general information. To overcome this problem, a new student acceptance chatbot application was created at Indo Global Mandiri University to provide information that can summarize well and display the information to users. To create this chatbot using the Python programming language using Deep learning. The deep learning algorithm model that is applied in making chatbots uses the Artificial Neural Network model. The application of the Artificial Neural Network model can recognize question patterns quickly and accurately so as to get an appropriate response. The model was then tested with 15 different conversations and successfully answered with a chatbot accuracy value of 86% and 13% error
Sistem Informasi Manajemen Aset Bendung Serdang BWS Sumatera II Menggunakan Metode Straight Line dan Simple Additive Weighting

Serdang Dam is one of the water resource dams managed by the Regional Office of the Sumatra II River Basin, which is a technical implementing unit of the Ministry of Public Works and Public Housing located in North Sumatra Province. Asset management at Serdang Dam has been done manually through recording and bookkeeping, which are then inputted into a document file. This system has several shortcomings, including difficulties in tracing asset information in each activity and the lack of a basis for asset depreciation and acquisition calculations, resulting in suboptimal asset management processes. To overcome these issues, research will be conducted to facilitate the management of Serdang Dam assets by developing an asset management information system using the Straight Line and Simple Additive Weighting methods. The findings of this research will provide a solution to the existing problems by creating a system that can assist in managing Serdang Dam assets in all its activities.
Penerapan Model Kesuksesan Sistem Informasi HOT-Fit terhadap Penggunaan e-Belajar sebagai Media Pembelajaran Daring Berbasis Website (Studi Kasus: STIKI)

This research aims to gather the necessary information to build a conceptual model that will be used to measure the success of online learning implemented in higher education institutions. The methodology used in this study is a literature review conducted by comparing various sources such as scientific journals, books, and expert opinions to support the findings. This research employs a quantitative method, where data can be interpreted using statistical analysis, making the quantitative approach more objective, scientific, and rational. The conclusion of this research is a conceptual model that implements the relationship between system quality, service quality, system usage, and user satisfaction with the benefits of e-learning. Furthermore, future related studies can refer to this conceptual model in their implementation.
DEVELOPMENT OF A WEB-BASED DIGITAL MATHEMATICS BOOK FOR CLASS VII ODD SEMESTER OF SMPN 5 WATANSOPPENG

This type of research and development aims to identify the need for digital math books, design digital math books, and measure the level of validity, practicality, and effectiveness of digital math books. The digital book development process refers to the ADDIE model, which includes five stages: analysis, design, development, implementation, and evaluation. This research was conducted at SMPN 5 Watansoppeng with the whole research subject to see the effectiveness of digital math books, 2 experts to get the validity of the digital math books developed, learning achievement tests in large group trials to see the effectiveness of digital books, and teacher response questionnaires to see the practicality of digital books. The results of the study show that the validation of material experts is in a good category and that media experts are in a very good category so that digital math books can be used in the learning process. The results of individual and small group trials by distributing questionnaires to each student's responses were in a good category, while in the large group trials by giving pretests and posttests, scores were in a significant category so that scores were obtained in the effective category. Then an analysis of the level of practicality was carried out by giving the value of the teacher's response to the mathematics subject teacher in the very good category so that a value was obtained in the practical category.
DEVELOPMENT OF PDF FLIP-BASED E-MODULE FOR MATHEMATICS LEARNING

This research of development aims to develop an e-module based on Flip PDF with valid, practical, and effective integer and fraction material. This research conducted in R&amp;D (Research and Development) design with ADDIE’s development model which included 5 stages, those are analysis, design, development, implementation, and evaluation. Respondents of the product development trial were grade VII students of SMP Negeri 25 Bulukumba with 64 students. The research instrument was a media assessment sheet by media experts and material experts to measure the validity and then questionnaires for teacher and student responses to measure the practicality of the mathematics e-module. The results showed that the mathematics e-module fulfilled the validity and practical criteria. The product meets the criteria of validity based on the assessment by the material expert with an average score of 3.88 and the assessment by the media expert with an average score of 3.33. The product meets the practicality criteria based on student responses with an average score of response at 3.72, categorized as practical, and teacher responses with an average score of response at 3.7, categorized as very practical. Based on the data criteria above, it can be concluded that the mathematics e-module can be used in learning activities. Further research can be done by developing learning media on specific abilities.
IMPLEMENTATION OF DIRECT INSTRUCTION IN MATHEMATICS CLASSROOMS DURING THE NEW NORMAL

The development of the covid-19 vaccine and the impact of online learning enable the government in Indonesia to remove some restrictions caused by the pandemic and our situation now is called the new normal. In the sector of education, some schools already implemented PTMT (Pembelajaran Tatap Muka Terbatas) by fully implementing face-to-face learning with some restrictions recommended by the government. One of the learnings that most teachers used was direct instruction. This study employed a sequential explanatory design to investigate the implementation of direct instruction in mathematics classrooms during the new normal. Firstly, we measured the effectiveness of direct instruction. Secondly, we investigated the factors affecting the results of our measurement of learning effectiveness. Two classes of the eleventh grade in one of the high schools in Makassar were chosen as the sample of our study. The findings of our study imply that the implementation of direct instruction in the mathematics classroom is not effective during the new normal based on the mathematics test results of the students. However, students and teachers respond positively to the implementation of direct instruction in mathematics lessons during the new normal. Our interview results reveal several factors causing the ineffectiveness, which were lesson duration, the number of tasks, and the short deadline of tasks from other subjects. Thus, the students cannot focus and overlook mathematics because they shift their focus to other subjects.