Reviewerly/exHarmony huggingface dataset:
Multiple-object Tracking Based on Movement Direction Assumption and Potential Re-appearance Position with Object Flow Visualizations

This paper proposes a multiple-object tracking (MOT) approach that adopts the tracking-bydetection strategy, which is composed of two steps: detection and tracking. This study aims to improve the tracking module by integrating a kernelized correlation filter (KCF). The filter is modified to be scale-adaptive to manage the varying size of the target object. Moreover, the tracking module’s data linking is performed in two steps, i.e. data association and reidentification (ReID). Here, two novel assumptions – namely, the movement direction assumption and potential re-appearance position – are incorporated. The first assumption considers the target object’s expected movement direction, while the second assumption postulates the possible position that a missing object may re-appear in. Using selected videos in 2DMOT2015 and PNNL Parking Lot benchmarking datasets, this study demonstrates that the proposed method outperforms the baseline model. In addition to MOT, this study further introduces a simple yet effective technique called trajectory accumulation to visualize the target objects’ flow of movement using the trajectories generated by the proposed tracker.
Mobile Technology Security Concerns and NESAS as a Solution

Mobile technology has become ubiquitous in our lives. It supports worldwide connectivity to devices and the Internet of Things (IoT). The new and innovative development of 5G network technologies offers many opportunities, but it also brings security challenges. The authors present a general overview of mobile technology elements regarding security issues, including GSM and 5G. Moreover, the Network Equipment Security Assurance Scheme - a reasonable solution to handle the security issues related to these technologies, is also discussed in this paper.
LiP-Flow: Learning Inference-Time Priors for Codec Avatars via Normalizing Flows in Latent Space

Neural face avatars that are trained from multi-view data captured in camera domes can produce photo-realistic 3D reconstructions. However, at inference time, they must be driven by limited inputs such as partial views recorded by headset-mounted cameras or a front-facing camera, and sparse facial landmarks. To mitigate this asymmetry, we introduce a prior model that is conditioned on the runtime inputs and tie this prior space to the 3D face model via a normalizing flow in the latent space. Our proposed model, LiP-Flow, consists of two encoders that learn representations from the rich training-time and impoverished inference-time observations. A normalizing flow bridges the two representation spaces and transforms latent samples from one domain to another, allowing us to define a latent likelihood objective. We trained our model end-to-end to maximize the similarity of both representation spaces and the reconstruction quality, making the 3D face model aware of the limited driving signals. We conduct extensive evaluations where the latent codes are optimized to reconstruct 3D avatars from partial or sparse observations. We show that our approach leads to an expressive and effective prior, capturing facial dynamics and subtle expressions better. Check out our project page for an overview.
PERANCANGAN SISTEM INFORMASI PENJUALAN E-COMMERCE REMPEYEK ILHAMUM-TAZA BERBASIS WEB

Ilhamum-Taza is a micro, small and medium enterprise (UMKM) which is engaged in the production and sale of tempe chips and peanut brittle which have become souvenirs from Jambi. UMKM manage the sale of goods is still manual so that the sale of goods is not optimal. Sales management to be more optimal so that it must use a web based e-commerce information system. The development of this web based e-commerce information system uses the waterfall model and the data flow model uses DFD (Data Flow Diagrams) . This research and design produces an e-commerce information system that will be implemented in UMKM Ilhamum-Taza.
Arbeitsbericht: Maschinelle Übersetzung für das Gadertalische

In this report, two different machine translation approaches for the low-­resource Ladin of the Val Badia are presented and evaluated: a dictionary-based approach using Apertium and a phrase-based statistical approach using Moses. The experiments show that the statistical approach outperforms in-domain the dictionary-based one and can provide satisfactory translations. Out-of-­domain, on the other hand, both approaches deliver poor translations. Here, the dictionary-based approach offers the greater room for improvement with the available resources.
A Study on Effect of Knowledge Management on Job Satisfaction

The purpose of this study is to argue that knowledge management may be utilized to improve job satisfaction and to analyze how job satisfaction can be improved through the knowledge management for individual employees.A theoretical model is used to describe the relationships between five components of knowledge management and job satisfaction.It is then empirically tested on an 824-item survey data set obtained from members of a Finnish municipal organization using a structural equation modeling partial least squares approach.The presence of knowledge management systems in the workplace is highly associated with high levels of job satisfaction.Intraorganizational knowledge exchange appears to be a critical KM practice, boosting job satisfaction among members of an organization.Surprisingly, important knowledge-based job satisfaction boosters differ according on employment characteristics.Managers should implement Knowledge Management activities in their organizations not only to improve knowledge worker performance but also to improve employee well-being at work, as Knowledge Management has a substantial impact on employee job satisfaction.
Design and Implementation of VSTO-based Online Compilation Teaching System for C Language

C programming is a compulsory general education course for science and technology majors in colleges and universities, and its importance is self-evident. At present, the teaching mode of C language in colleges and universities generally has the code lecture according to the text, teachers usually use PowerPoint to explain classroom knowledge, code demonstration needs to operate several software at the same time, the operation process is tedious, the performance of teaching computer is a great challenge, the classroom efficiency is affected. In order to solve the above teaching problems, it is necessary to develop a system based on VSTO's PowerPoint technology development and Spring Boot framework for C online compilation and running. The system enables PowerPoint to compile and run online in C language, which can effectively solve the problem of complicated operation of C language compiler in classroom. The system design uses Spring Boot framework to write the interaction logic, MySQL database for the data layer, Docker container for system resource virtualization and program isolation, and Nginx for front-end load balancing to improve the concurrent processing capability. The design and operation of the C online compilation system embedded in PowerPoint is studied and analyzed to achieve the goal of security and high concurrency, which will positively contribute to the progress of teaching programming courses.
A resilient voice-based speaker identification approach using deep learning

Speaker recognition technology has achieved tremendous success over the years as it has become more affordable and reliable. Much research have been conducted in the speaker recognition area, but little progress has been made by the researchers. While deep learning surpassed most machine learning techniques, it has became widely used on the topics of speech technology and its new advanced solutions. In this work, we are proposing a resilient approach for speaker identification with middle-eastern accents. experiments have been carried out in the field of speaker recognition based on deep learning methods. The long short-term memory model was used with Mel-frequency cepstral coefficients. The deep neural network model was used with statistical features and Mel-frequency cepstral coefficients. A spectrogram of each sample was generated as an input for the convolutive neural networks model.
Demonstrating CAT

Databases for OLTP are often the backbone for applications such as hotel room or cinema ticket booking applications. However, developing a conversational agent (i.e., a chatbot-like interface) to allow end-users to interact with an application using natural language requires both immense amounts of training data and NLP expertise. This motivates CAT , which can be used to easily create conversational agents for transactional databases. The main idea is that, for a given OLTP database, CAT uses weak supervision to synthesize the required training data to train a state-of-the-art conversational agent, allowing users to interact with the OLTP database. Furthermore, CAT provides an out-of-the-box integration of the resulting agent with the database. As a major difference to existing conversational agents, agents synthesized by CAT are data-aware. This means that the agent decides which information should be requested from the user based on the current data distributions in the database, which typically results in markedly more efficient dialogues compared with non-data-aware agents. We publish the code for CAT as open source.
Research on Tourists' Emotional Expression Based on Web Text Analysis

This paper uses a web crawler program to collect 2800 review texts of Duxiufeng Wangcheng Scenic Area on Ctrip.com, and after processing, 2725 review texts are retained as research samples, combined with text analysis methods, using ROSTCM6 for sentiment analysis, word cloud graph analysis and semantic network analysis to analyze user review sentiment. It is found that users have mostly positive attitudes towards Duxiufeng Wangcheng scenic spot reviews, but there are large differences between different reviewers' reviews; users are more concerned about scenic spots, guided tours, entrance fees and entertainment program costs; the scenic spot is an experience-based comprehensive scenic spot. And based on the above results, we propose countermeasures for optimizing the development of Guilin scenic spot tourism.
Shoulder surfing resistant using Cued Click Point authentication system

The main objective of this Paper is to providesecurity to the users so that they can freely access their resources without any problems. The Paper contains differentlevels and variety of authentication which verifies the user in all the three levels of the authentication. All the different typesof passwords which are available can be cracked in some wayor the other, but this Paper has aimed to achieve the highest security of the system as possible. Now a days many cyber threats are going on this digital era and attack are also high So our Proposed system to save the cyber-attack and also remove the complexity regarding remembering the numeric password of different platform, in recent digital era everyone has digital identity, but they were not able recall al the numeric password easily. We are going to proposed system who remove the complexity of all upcoming recalling password and reduce the cyber threat as well.
A Survey on Student’s Application for Using Smartphones in Learning at HCM City University of Food Industry

Nowadays, smartphone use is popular among universities both inside and outside of teaching institutions. The purpose of this research project is to investigate students' applications for using smartphones in learning. This will help students have more support in their learning. It has many positive sides. For example, most students can use many useful applications to serve their learning; it will be more effective. The percentage of students who use their phones to study is quite high, and it is also used to go on social networks, text or call in their spare time. In addition, there are also negative sides due to weak phone networks, disclosure of security information, virus intrusion systems, etc. However, it is necessary to use modern applications on the phone to support it for more learning.
Wisdom Leadership and Its Role in Enhancing the Internal Innovation Performance In the Banking Sector

Service innovation is critical to organizations' success in a competitive marketplace, where customers increasingly demand better services.This study aims to investigate if and how wisdom leadership helps organizations increase service innovation performance.The study questionaries were conducted with 191 participants in the 30 different private bank sectors in Erbil, KRI.The conceptual framework of this study led to three main hypotheses and subhypothesizes; our analysis showed positive correlations between wisdom leadership and, service innovation performance and significant impacts on each one.According to this thesis's data analyses, Banks will get the highest point of service innovation performance through cultivating wisdom leadership in the workplace in which enhances well-being among employees.
Digitalisation of education and specificity of collecting the digital footprint of students in creative disci-plines

In this article, implementing digitalisation in the educational process of students of creative disciplines is discussed. The research is based on the final paper completed within the framework of the profes-sional retraining programme entitled “Project Management in Digital Educational Environment of a Uni-versity” (NRNU MEPhI). The importance of collecting the digital footprint of students during the learn-ing process as valuable information content was revealed, which allows feedback in the teaching pro-cess to be established in order to adjust the educational path. The challenges of implementing the digi-tal footprint acquisition of students attending Art and Design were formulated, and the existing oppor-tunities for implementing this process were assessed. The principles of digitalisation in the educational process based on the performance (”to know”, “to be able to”, “to master”) were defined, which allows the methods of digital footprint acquisition to be identified. The study showed that forming a working model of “student–young professional–production” is based on the digitalisation of education, which implies a well-functioning system of “teacher–content–student–information technology”.
Guidelines for the creation of digital educational resources in the field of technosphere safety at NSTU

The key challenges for the flagship technical university of NSTU are new formats of open online learning, open mass online courses on external learning platforms (MOOCs), as well as campus private courses hosted on the DiSpace 2.0 platform in the light of digital changes and transformations in education. Various types of digital educational resources are presented, including online courses and courses based on electronic educational and methodological complexes at NSTU. Guidelines for creating online courses on the NSTU LMS “DiSpacе” have been developed. The components of the online course are described according to the quality criteria of Quality Matters (QM), an organization that provides a scalable online course quality assurance process. Conclusions are drawn about the use of online courses hosted on the NSTU software platform as mass open courses when placed on learning platforms, as well as when organizing blended learning at NSTU.
Accurate Acquisition of Minimum Gap of Non-Concentric Stator and Rotor during Rotation

In the production process of compression pump, the minimum gap measurement of non-concentric stator and rotor rotation is the key to ensure the quality of finished products. At present, it is mainly manual detection, which has the problems of high labor intensity and low detection efficiency. Aiming at the problem, a detection method based on image processing is proposed in this paper. Firstly, the image obtained by the high-power camera is filtered, and different filter sizes are used to obtain the stator and rotor contour. Then, the ordinary least squares method based on threshold filtering is used to obtain the fitting circle of the stator and rotor contour, and then the maximum distance between the fitting circle and the stator and rotor contour is calculated. Through this distance, the largest repulsion circle of the stator contour and the minimum circumscribed circle of the rotor contour are obtained. The minimum distance between the two circles is the minimum gap value, Finally, by building an platform for experiments, and comparing the experimental results with the manual detection results, it is concluded that the detection method can fully meet the actual production needs and can replace the manual detection.
Object-Oriented Programming

Python is an object-oriented programming language. This means that the program design is based around objects, rather than functions and logic.
Development of Microsoft Power Point Based Educational Game in Vocabulary Learning in Elementary School

This article aims to determine the development of Microsoft Power Point-based educational games in vocabulary learning at SD Muhammadiyah 2 Sidoarjo and to determine student responses to this educational game. The research approach used by researchers is development research because it makes a product that can help learning. The results showed that, 1) It is known how to develop this educational game, namely by finding problems in the field, collecting data, designing products, design validation, design revisions, product trials, limited trials, product revisions, and game distribution for all class students. 5. 2) From the experimental results of distributing games to 5 respondents, it is known that games are interesting and able to overcome the needs of learning Arabic vocabulary by obtaining 4.97 results on the Linkert Scale interval which means that they agree with Microsoft Power Point-based games. And when it was distributed to class 5, it was found that the respondent's results scored 4.94, which means that they strongly agree with the existence of educational games based on Microsoft Power Point. As for the results of the quizzioner distributed to grade 5 students, it is also known that the answers strongly agree with the existence of educational games based on Microsoft Power Point by 83%, agree 17%, and the answers disagree 0%. From these results, the researcher was able to draw the conclusion that educational games are a new tool for learning Arabic vocabulary for grade 5 at SD Muhammadiyah 2 Sidoarjo, have an attractive appearance, and are able to increase students' enthusiasm when learning Arabic vocabulary, and overcome the needs of students. Arabic vocabulary learning, and easy to use.
A highly efficient FPGA implementation of AES for high throughput IoT applications

With nearly 500 billion connected devices in 2025, information security will be the main concern of the researchers. It is the driving force in developing resource efficient cryptographic solutions. In this paper, we present a high throughput AES design with 32-bit data path that achieves the high efficiency via FPGA implementation. With the help of data path compression and effective utilization of FPGA architecture, the resource consumption is minimized. Galois field arithmetic is utilized for s-box implementation. Separate S-box for key generation has been employed to achieve higher throughput and low latency. The proposed design has been synthesized by PlanAhead software and implemented on different Xilinx FPGAs. It is compared with AES implementations. With a throughput of 2.34 Gbps and efficiency of 5.10 Mbps/slice, the design outperforms different lightweight ciphers. High throughput and low latency make it suitable for surveillance applications in IoT and smart grid.
A Survey of Recent Advances on Two-Step 3D Human Pose Estimation

Human pose estimation in images is an important and challenging problem in Computer Vision. Currently, methods that employ deep learning techniques excel in the task of 2D human pose estimation. 2D human poses can be used in a diverse and broad set of applications, of great relevance to society. However, the use of 3D poses can lead to even more accurate and robust results. Since joint coordinates for 3D poses are difficult to estimate, fully convolutional methods tend to perform poorly. One possible solution is to estimate 3D poses based on 2D poses, which offer improved performance by delegating the exploration of image features to more mature 2D pose estimation techniques. The goal of this paper is to present a survey of recent advances on two-step techniques for 3D human pose estimation based on 2D human poses.
GENDER CLASSIFICATION USING SINGLE IMAGE PER PERSON

This paper presents a framework based on object appearance and shape based features to address gender classification problem through face image.Histogram of Oriented Gradients (HOG) based scheme is presented for gender classification having one frame/object for training.In presented scheme nearest neighbor based classifier Euclidean distance method is used for classification.Presented scheme's results have been compared in cross dataset environment with state-of-the-art various algebraic (PCA, LDA), geometric (Gabor Wavelets) and texture (LBP) based features.Experiments have been performed in two folds using FEI face dataset consisting of 99 objects each (Male and Female) having one frame/object.Experiment's results based on fold-2 are promising, indicating that HOG and the proposed ensemble framework have sufficient discriminative power for the gender classification problem with the accuracy of 91.41%.Current research findings include a claim that forehead, hair style, chin, ears and outer boundary of face having information about face shapes has significant importance in gender classification task.
Blockchain based Energy IoT Data Trusted Collection and Transmission

With continuous upgrading of energy types and information technologies, the energy Internet of Things (IoT) presents a trend of distribution, intelligence and integration, which inevitably generates massive and diverse energy data. These data are dispatched by different parties in the process of generation, transmission, storage and usage. The data also cause a large number of security risks such as data loss, theft, and tampering easily. In this paper, we propose a blockchain-based energy IoT data trusted collection and transmission technology to improve the security and reliability of the energy IoT. We use consortium blockchain technology to achieve energy data management monitoring. To reduce block storage pressure, only energy collection process are recorded in the block, meanwhile the original data are stored off the block. Finally, we build a simulation platform in Python environment to verify the feasibility of our proposed algorithm.
Measurement and modeling of an electromechanical spring reverb device

A spring reverb is an electromechanical device used to artificially reverberate an audio signal, i.e. to impart a sense of spaciousness to the audio signal, as if the sound were being emitted into a reverberant acoustic space. The device consists of a number of helical springs set into motion by electrically driven magnetized beads, with the elastic wave motion along the springs being analogous to acoustic waves propagating along the various dimensions of a room. While originally invented by the Hammond organ company to add a sense of spaciousness to the sound of their electric organs, spring reverbs have been used in a number of electronic instruments and audio devices over the years, with probably the most iconic and enduring use being in classic electric guitar amplifiers. In this talk, a general overview of the history and technical aspects of spring reverb devices will be given, with particular emphasis placed on the highly dispersive nature of elastic wave propagation along helical springs, which it will be argued is primarily responsible for the distinctive sound of the device. Finally, a simplified computation model will be presented that captures the salient features of a spring reverb device.