Reviewerly/exHarmony huggingface dataset:
DEVELOPING DIGITAL WORKSHEET BY USING WIZER.ME FOR TEACHING LISTENING SKILL TO THE TENTH GRADE STUDENTS IN SMK NEGERI 7 MEDAN

Digital worksheet, as the one of learning tools that is used to involve the students to works actively during teaching and learning process, should be developed based on students’ need. Digital worksheet in listening skill with scientific approach has not applied. A good digital worksheet must be fulfilled criteria of valid, practical and effective. The aim of this study was to develop English Listening Digital Worksheet for Grade X for Vocational school Students. This study was conducted by using Research and Development (RD need analysis, planning, designing digital worksheet, materials evaluation, revising (final product). The subject of the study was Grade X of Hospitality Major at SMK Negeri 7 Medan. The data were gathered by conducting interview to English teacher and distributing questionnaire to 1 class grade X consists of 36 students to get the students’ needs. The interview and questionnaire results prove that the students needs of English Listening Digital Worksheet appropriate with the Hospitality Major context. The product has been validated by experts. The result of the product was the digital worksheet combined with the Wizer.me platform. Keywords: english listening digital worksheet, Wizer.me, research and development (R&D)
Geospatial Intervention in Mapping of Solar PV Installations using Satellite Imagery

This paper explains the role of remote sensing and geographic information systems in mapping the solar PV installations. This part of work also explains the sources needed for mapping the solar PV installations on land. Some of the models needed for automatic extraction of the PV systems were discussed in this paper. The basic algorithms needed for effective machine learning through training samples is explained in this part of literature. The role of open source GIS is important in the mapping of the solar installations. Keywords: Google Earth Engine, LANDSAT, Mapping, Open source GIS, Solar PV
Competencies of Project Managers: the Impact of Creativity Competencies on Successful Completion of Projects

This article is devoted to the research of project managers ' competencies particularly the competence of creativity. Currently the skills approach is becoming more interesting and important. This is due to the fact that employees their knowledge and skills are the greatest value for many companies now. In conditions of instability and high speed of changes in external environment, the competencies that employees possess are the main point that determine the success of the company. This article examines the need of creativity competence in project management, depending on the final boundaries of the description of the final result. According to the results of the research, regardless of the boundaries of the final result of the project, project managers often use the competence of creativity in working on projects, and the vast majority consider that their work is creative. Based on the obtained research data and existing methods, this research presents recommendations for the development of creativity competence in project managers and ways to implement creative methods in project management.
SANDY: THE HUMAN ROBOT

The humanoid research is an approach to understand and realize the complex real world interactions between a robot, an environment, and a human. In general a human robot has a head, two arms and two legs. Our system can recognize a set of gestures. It is essential for the functional purpose, such as interacting with human tools and environments. This is human robot which closely resembles to human motion and behaviour. Human robots are meant to overcome the obstacle through the internally built sensors. In this work, we propose a vision and knowledge based gesture recognition system for human robot interaction. Our Robot mainly focuses on the gestures, with is movement in all direction, and makes its own direction to overcome the obstacle. Interaction between a robot and a human may take several forms, but these forms are largely influenced by whether the human and robot are in close proximity to each other. Hence the communication with the robot is remote controlled interaction. Simulation and experiments demonstrate that the proposed method can achieve maximum reduction in human efforts towards the work.
PERANCANGAN AUGMENTED REALITY SEBAGAI MEDIA PENGENALAN BENDA BUDAYA

Augmented reality (AR) as a technology enabler is becoming very popular in various fields such as education, design, navigation, and medicine. The aim of AR is to develop technology that allows real-time integration of digital content created by computers with the real world. Until now the development and introduction of tourism, especially sites and cultural objects in the village of Pleret is still not optimal. On the other hand, learning models in the introduction of culture and cultural objects that are commonly used today still use textbooks containing text and still images. Students tend to prefer playing gadged or mobile phones rather than learning with conventional methods because they tend to be boring and unattractive. One solution to overcome these problems is to use learning media that can display 3D objects in real-time. The application of technology using AR is expected to be able to provide motivation and enthusiasm for learning, so that the learning process becomes fun and the results of guarded learning will increase. This research will design an augmented reality technology design for the introduction of cultural objects in Pleret Village as an interesting learning media. The results of this study are in the form of AR application design which can be an interesting alternative learning media for introducing cultural objects in addition to being a means of cultural preservation as well as being a promotional media.
Artificial Intelligence Techniques for Load Balancing in Cloud Computing: A Review

Artificial Intelligence techniques now a day’s cover the market due to its numerous benefits. This is because many techniques are more explore when Artificial intelligence combines with it. Cloud computing is one of the most market capture techniques and it provides numerous benefits. The load balancing mechanism in Cloud needs to consider as the most important criteria because the user and service provider both benefits are involved if the Load balancing mechanism is proper. So in this paper, we provide detailed knowledge using various proposals on how the Artificial intelligence mechanism helps to improve the load balancing mechanism in Cloud Environment.
Adversarial Knowledge Transfer from Unlabeled Data

While machine learning approaches to visual recognition offer great promise, most of the existing methods rely heavily on the availability of large quantities of labeled training data. However, in the vast majority of real-world settings, manually collecting such large labeled datasets is infeasible due to the cost of labeling data or the paucity of data in a given domain. In this paper, we present a novel Adversarial Knowledge Transfer (AKT) framework for transferring knowledge from internet-scale unlabeled data to improve the performance of a classifier on a given visual recognition task. The proposed adversarial learning framework aligns the feature space of the unlabeled source data with the labeled target data such that the target classifier can be used to predict pseudo labels on the source data. An important novel aspect of our method is that the unlabeled source data can be of different classes from those of the labeled target data, and there is no need to define a separate pretext task, unlike some existing approaches. Extensive experiments well demonstrate that models learned using our approach hold a lot of promise across a variety of visual recognition tasks on multiple standard datasets. Project page is at \texttthttps://agupt013.github.io/akt.html.
Prototype Planning and Technician Job Report System at PT Visionet Data Internasional

PT Visionet Data International is a subsidiary of PT. Multipolar tbk, based in lippo Cyber ​​Park, and is engaged in outsourcing IT service providers, serving data center operational services and a company's daily IT operational services (IT Help desk). As a company engaged in services, PT Visionet Data International always strives to run its projects optimally and always maintain the reliability and scalability of computerized infrastructure that supports the customer's main business activities. The prototype planning, control and technician report system is an information system for scheduling, monitoring and reporting the job of technicians in the customer. In this study, researchers conducted an analysis and design of a technician job report system at PT. Data International Data Tangerang. The research method used was interview, survey and literature study methods. The system design process uses UML and the application is developed using PHP. The results of this study are information systems that can improve the services provided by PT. Visionet International Data to customers.
LibGuides: Sawyer Library Services During Covid-19: Reserving Study Spaces and Computers

This guide contains the most current information on the Sawyer Library's services and building operations.
LibGuides: Popular Magazines From the Library:Full Text : POPULAR MAGAZINES

reading Reading is a gateway skill that leads supports all other learning. Leisure reading has been shown to reduce stress. SJCC student have full text access to a wide range of popular magazines, that can be read online cover-to-cover for recent issues.
Iterative Text-to-Image conversion using Recurrent Generative Adversarial Tell, Draw, Undo, Repeat

Conditional text-to-image is an active area of research. We propose a novel Recurrent GAN model architecture that can generate 2-D images from input text in an iterative manner. This is different from the one-step text-to-image generation as the model will be given continuous instructions carrying information on how to modify the most recently generated image. To generate an image in the current time step, the model would take all the previous instructions up to the current time step and will generate the image from the previous time step. We propose a novel method, which is the ability of the model to undo the modifications that it has done to the image on the previous time step. This is very essential in situations when the text instruction given to the model is incorrect (possibly unintentional human errors). The aim of the proposed model is to march towards a complete capacity of interactive text-to-image generation and to enhance the user experience from a Human-Computer Interaction (HCI) perspective.
A Uniformly Stable Algorithm For Unsupervised Feature Selection.

High-dimensional data presents challenges for data management. Feature selection, as an important dimensionality reduction technique, reduces the dimensionality of data by identifying an essential subset of input features, and it can provide interpretable, effective, and efficient insights for analysis and decision-making processes. Algorithmic stability is a key characteristic of an algorithm in its sensitivity to perturbations of input samples. In this paper, first we propose an innovative unsupervised feature selection algorithm. The architecture of our algorithm consists of a feature scorer and a feature selector. The scorer trains a neural network (NN) to score all the features globally, and the selector is in a dependence sub-NN which locally evaluates the representation abilities to select features. Further, we present algorithmic stability analysis and show our algorithm has a performance guarantee by providing a generalization error bound. Empirically, extensive experimental results on ten real-world datasets corroborate the superior generalization performance of our algorithm over contemporary algorithms. Notably, the features selected by our algorithm have comparable performance to the original features; therefore, our algorithm significantly facilitates data management.
Challenges in Teaching and Learning of English at Higher Secondary Level: The Perceptions of Teachers in Lahore

This research is significant because it aims to determine the challenges faced by English languageteachers at higher secondary level. It is important because it will help devise different strategieswhich are helpful for English language teachers in coping up with these challenges. This studyhighlights different important issues such as weak backgrounds of the teachers, syllabus relatyedproblems, and lack of teachers training. A sample of 100 teachers was chosen from 10 collegeslocated in Lahore. The research utilized two research instruments which are; the first instrumentwas a survey to explore the difficulties of the English educators at higher secondary level whilethe second instrument was open ended interview from the respondents. The study was a mixedmethod study with both qualitative and quantitative data methods converging to present betterunderstanding. The findings suggest that English educators are confronting numerous problemsand issues which ascribe to their teaching this language. The findings of this research revealed thatthere were certain problems faced by the English educators which hampered the learning of thestudents. There was lack of teachers training and big size of classes which created negative impacton teaching and learning process. The burdensome syllabus and the tensed environment of theschools and colleges was also credited to hamper the expected outcomes. The study suggestedimportant recommendation which can be very helpful in better performance of the teachers athigher secondary level.
Client-Side Web and APIs

The web is the infinite source of information, and it’s right there for you to tap. Lots of services can be used straight away, in other cases you have to do some massaging, and in yet other cases you need to be properly authorized. In all these cases, Raku is there to help you.
A Study on the Acceptance Attitude of HealthㆍMedical Information Program Viewers

In proportion to the growing interest in healthy living, various media provide health and medical information to the public. In response to the craze for well-being and the growing interest in health, it is meaningful at this point to analyze how viewers think about the health and medical information programs produced by broadcasters. The purpose of this study is to examine the types of subjective perceptions and characteristics of domestic health and medical information programs and to consider the considerations and improvement plans for future domestic health and medical information programs. A total of 22 P and 33 Q samples were collected for this purpose, and the collected data were analyzed using the PC-QUANL program. As a result of the analysis, three types were found: the first type was ‘negative suspect’, the second type was ‘positive trust’, and the third type was ‘selective acceptance’. Looking at the results of the analysis, it seems urgent to establish an institutional device that can prevent excessive commercialization of health and medical information programs.
EFSG: Evolutionary Fooling Sentences Generator

Large pre-trained language representation models (LMs) have recently collected a huge number of successes in many NLP tasks. In 2018 BERT, and later its successors (e.g. RoBERTa), obtained state-of-the-art results in classical benchmark tasks, such as GLUE benchmark. After that, works about adversarial attacks have been published to test their generalization proprieties and robustness. In this work, we design Evolutionary Fooling Sentences Generator (EFSG), a model- and task-agnostic adversarial attack algorithm built using an evolutionary approach to generate false-positive sentences for binary classification tasks. We successfully apply EFSG to CoLA and MRPC tasks, on BERT and RoBERTa, comparing performances. Results prove the presence of weak spots in state-of-the-art LMs. We finally test adversarial training as a data augmentation defence approach against EFSG, obtaining stronger improved models with no loss of accuracy when tested on the original datasets.
Hubungan Antara Ketersediaan Fasilitas Belajar di Rumah Dengan Motivasi Belajar Siswa

The purpose of this study is (1) To determine the availability of learning facilities in the homes of eighth grade students of Blitar 7 MTs. (2) To determine the level of learning motivation of class VIII students of Blitar 7 MTs. (3) To find out the relationship between the availability of learning facilities at home with student motivation. This research is a quantitative study, the number of samples is 93 students selected by the correlational product moment research technique from person, the research instrument uses questionnaires or questionnaires, the data are analyzed by statistical techniques using the SPSS version 16.00 program. The results of this study are (1) 82.8% of grade VIII students of MTs 7 Blitar have the availability of learning facilities at home in a very good category. (2) 63.4% of class VIII students of MTs Negeri 7 Blitar have motivation to learn in a very good category. (3) There is a positive and significant relationship between the availability of learning facilities at home with learning motivation, which is indicated by the correlation coefficient of 0.651> 0.374 with a strong level of relationship, and the significance is 0,000 <0.05.
Determining the Idiosyncrasy of Blockchain: An Affordances Perspective

IS researchers' assessment of blockchain’s business value varies considerably, resulting in diverging recommendations on how companies should apply the technology. To develop a more uniform understanding of the potential of blockchain, we propose an affordances perspective to identify action potentials of blockchain. We apply a critical realist perspective to analyze blockchain applications of the thirty largest financial institutions globally, resulting in a three-layered affordances model. While the model comprises technical, design, and business affordances, we assert that business affordances determine the idiosyncrasy of blockchain technology. By shifting the focus on business affordance, we contribute to a shared understanding and thereby bridge the chasm between different assessments of the blockchain’s impact on companies and pushing full-fledged applications of the technology forward.
LibGuides: Bibliotherapy: Using Books for Therapy: Recommendations

This guide is intended to introduce adult patrons to different resources on bibliotherapy, it's uses and effects.
Unseen Activity Recognition in Space and Time

Progress in video understanding has been astonishing in the past decade. Classifying, localizing, tracking and even segmenting actor instances at the pixel level is now common place, thanks to label-supervised machine learning. Yet, it is becoming increasingly clear that label-supervised knowledge transfer is expensive to obtain and scale, especially as the need for spatiotemporal detail and compositional semantic specification in long video sequences increases. In this talk we will discuss alternatives to label-supervision, using semantics [1], language [2], ontologies [3], similarity [4] and time [5] as the primary knowledge sources for various video understanding challenges. Despite being less example-dependent, the proposed algorithmic solutions are naturally embedded in modern (self-)-learned representations and lead to state-of-the-art unseen activity recognition in space and time.
Research on Implementation Approaches to Online-offline Blended Teaching Mode in Business English Teaching

In business English classroom teaching practice, the cultivation of students’ language competence and the impartation of business knowledge cannot be both covered within limited class time. In order to solve this problem, this paper proposed an online-offline blended teaching mode which is suitable for business English courses. Rich and high-quality online resources can meet different learning needs of students at different levels, facilitating students’ autonomic learning of business knowledge, thus fully mobilizing the autonomy of students’ learning. Offline classroom teaching facilitates teachers to carry out various forms of language skill training and fully play teachers’ leading role in class. The online-offline blended teaching mode combines the offline classroom teaching with online teaching, which takes the advantages of both teaching forms, therefore, effectively improves the quality of business English teaching.
Top-Down Fusing Multi-level Contextual Features for Salient Object Detection

Recently, benefiting from the fast development of deep convolutional neural networks, salient object detection (SOD) has achieved gratifying performance in a variety of challenging scenarios. Among them, how to learn more discriminative features plays a key role. In this paper, we propose a novel network architecture that progressively fuses the rich multi-level contextual features from top to bottom to learn a more effective feature presentation for robust SOD. Concretely, we first design a multi-receptive field block (MRFB) to capture multi-scale contextual information. Then, we develop a feature fusion block that progressively fuses different outputs of MRFBs from top to bottom, which can effectively filter out the non-complementary parts of the high-level and low-level features. Afterwards, we leverage a refinement residual block to refine the results further. Finally, we leverage an edge-aware loss as an aid to guide the network to learn more sharpen details of the salient objects. The whole network is trained end-to-end without any pre-processing and post-processing. Exhaustive evaluations on six benchmark datasets demonstrate superiority of the proposed method against state-of-the-arts in terms of all metrics.
KEMAMPUAN BERBICARA BAHASA INGGRIS MAHASISWA DENGAN MENGGUNAKAN METODE FOLKTALE BASED STORYTELLING DI INSTITUT PENDIDIKAN TAPANULI SELATAN

ABSTRACT The aim of this research are to know : 1) students’ speaking ability before using folktare based storytelling method;2) students’ speaking ability after using folktare based storytelling method; 3) whether there is a significant effect of using folktare based storytelling method in Institut Pendidikan Tapanuli Selatan. This research is used qualitative research. This researched is used total sampling. The instrument of the research is speaking test to measure the ability of students’ speaking. Then the results after using the folktale based storytelling method, the students' speaking ability was 72,37, mode 72, and median 70. The result of the t test was 17 and the result of the t table score was 2.04, it means that there is a significant effect of folktale based storytelling method on students’ speaking ability inInstitut Pendidikan Tapanuli Selatan. Keywords : Folktale Based Storytelling Method, Students’ Speaking Ability.
Deep Image Features for Instance-level Recognition and Matching

In this talk, I will discuss recent work from our team at Google Research, covering novel methods and datasets. Instance-level recognition, retrieval and matching are key computer vision problems which generally depend on effective image representations, both global and local. Our team has proposed a suite of state-of-the-art models to address these tasks: DELF (ICCV'17), one of the first deep learning methods for joint detection & description of local image features; Detect-to-Retrieve (CVPR'19), where deep local features can be efficiently aggregated guided by a trained object detector; DELG (ECCV'20), the first end-to-end trained deep model for joint local and global feature extraction. I will also present our team's efforts on pushing for larger scale and more realistic benchmarks in this area, with the Google Landmarks Dataset (CVPR'20), and three workshops at computer vision conferences (CVPR'18, CVPR'19, ECCV'20).