Reviewerly/exHarmony huggingface dataset:
CoLA: Weakly-Supervised Temporal Action Localization with Snippet Contrastive Learning

Weakly-supervised temporal action localization (WS-TAL) aims to localize actions in untrimmed videos with only video-level labels. Most existing models follow the "localization by classification" procedure: locate temporal regions contributing most to the video-level classification. Generally, they process each snippet (or frame) individually and thus overlook the fruitful temporal context relation. Here arises the single snippet cheating issue: "hard" snippets are too vague to be classified. In this paper, we argue that learning by comparing helps identify these hard snip-pets and we propose to utilize snippet Contrastive learning to Localize Actions, CoLA for short. Specifically, we propose a Snippet Contrast (SniCo) Loss to refine the hard snippet representation in feature space, which guides the network to perceive precise temporal boundaries and avoid the temporal interval interruption. Besides, since it is in-feasible to access frame-level annotations, we introduce a Hard Snippet Mining algorithm to locate the potential hard snippets. Substantial analyses verify that this mining strategy efficaciously captures the hard snippets and SniCo Loss leads to more informative feature representation. Extensive experiments show that CoLA achieves state-of-the-art results on THUMOS’14 and ActivityNet v1.2 datasets.
Self-supervised Learning for Large-scale Item Recommendations

Large scale recommender models find most relevant items from huge catalogs, and they play a critical role in modern search and recommendation systems. To model the input space with large-vocab categorical features, a typical recommender model learns a joint embedding space through neural networks for both queries and items from user feedback data. However, with millions to billions of items in the corpus, users tend to provide feedback for a very small set of them, causing a power-law distribution. This makes the feedback data for long-tail items extremely sparse.
Data modeling in the NoSQL world

NoSQL systems have gained their popularity for many reasons, including the flexibility they provide in organizing data, as they relax the rigidity provided by the relational model and by the other structured models. This flexibility and the heterogeneity that has emerged in the area have led to a little use of traditional modeling techniques, as opposed to what has happened with databases for decades. In this paper, we argue how traditional notions related to data modeling can be useful in this context as well. Specifically, we propose NoAM (NoSQL Abstract Model), a novel abstract data model for NoSQL databases, which exploits the commonalities of various NoSQL systems. We also propose a database design methodology for NoSQL systems based on NoAM, with initial activities that are independent of the specific target system. NoAM is used to specify a system-independent representation of the application data and, then, this intermediate representation can be implemented in target NoSQL databases, taking into account their specific features. Overall, the methodology aims at supporting scalability, performance, and consistency, as needed by next-generation web applications.
Where Do We Grow from Here? Assessing the Impact of a Digital Media Commons on Student Success [Slides]

Slides from a presentation given December 7, 2018 at the Library Assessment Conference in Houston, TX. Digital literacy skills are essential for 21st century students to succeed in their academic work and future professions. Academic libraries around the country have implemented digital media services to assist students in developing videos, 3D objects, posters and other media for course assignments and other projects. Staff in these services also work with faculty to create and assess effective assignments so that students learn these important skills. At a high-research university a Digital Media Commons (DMC) was implemented in 2012 with technology and expertise in a separate service area to focus on media production projects Services have grown to also include a green screen lab, maker space, virtual reality, drones and a gaming lab. In 2017-18 an assessment project was implemented to determine how the DMC contributes to student success. The project included three phases -- a faculty survey, customer service survey and focus groups. Results of the assessments will be used for a variety of purposes including improvement to instruction, addressing service issues and adding needed services or resources. It will be distributed to Libraries’ administration to use for planning future improvements, services and to address staffing issues. The data will also be used to inform an upcoming major library renovation and addition. The Libraries have employed a consulting firm to provide a master building plan. These assessment results will be most beneficial for planning an updated Digital Media Commons.
AN EFFECTIVE IMAGE DEBLURRING SCHEME USING CLUSTER BASED SPARSE REPRESENTATION

Sparse based representation is being used extensively for image restoration. The dictionary learningthrough patch extraction is central to the sparse based schemes. In the process of dictionary learning,a large number of patches will be extracted from high quality images and dictionary will be formed.Hence, over-complete dictionaries will be built. To overcome the complexity associated with overcompletedictionaries many schemes were proposed. Of them, the adaptive sparse domain is thepopular one. Many variations of adaptive sparse domain schemes were proposed. Selection of obviouspatches is common to all. In all these schemes, individual patches will be considered as the basic entityand will be used. This is the reason for the complexity involved in sparse representation. In this paper,to avoid the complexity, the patches are grouped according to the similarity among the patches. Inaddition to reduce the complexity the proposed cluster based scheme considers the self-similarity ofthe patches involved. Hence better performance with less complexity is possible with the proposedschemes. In the process of testing, in addition to uniform blur and Gaussian blur, a combination of thetwo blurs is also considered.
Model Pengembangan Media Pembelajaran Pendidikan Kewarganegaraan Berbasis Aplikasi Augmented Reality Sejarah Proklamasi di STT Indonesia Tanjungpinang

This study aims to: (1) Determine the conditions of learning and teaching activities in Citizenship Education courses prior to the implementation of the development of Android-based learning media. (2) Knowing the development of IT-based learning media in STT Indonesia. The type of research used in this research is research and development research. The data source was chosen by the head of the study program, lecturers of civic education, and 8th semester students at STT Indonesia. This research was conducted in approximately 6 months. This development research resulted in the final product of learning media based on augmented reality of the history of the proclamation. Media development is developed through five stages (analysis, design, development, implementation and evaluation). Based on the results of field trials conducted in small and large classes. The small class trial was carried out in the SI class with a random sample of 5 students, obtaining a result of 82.6%, it was concluded that this product was suitable for use. The results of the extensive trial were carried out to the IF class, SI.KA. The results obtained by 29 IF students got a response with a percentage of 78.2%, it was concluded that this product was feasible to use. Extensive trials conducted on 28 students of SI STT Indonesia Tanjungpinang received a response with a percentage of 74.7%, it was concluded that this product was quite feasible to use. Extensive trials were carried out on 29 students of the STT Indonesia Tanjungpinang KA received a response with a percentage of 87.6%, it was concluded that this product was very suitable for use. Finally, the field trial was carried out on citizenship education lecturers of STT Indonesia Tanjungpinang who received a response with a score of 92, 7%, concluded This product is very feasible to use.
Motor learning in marimba performance: Spatiotemporal control of elbow and mallet movements

Musicians coordinate the upper-limbs in both temporal and spatial domains to execute sound-producing movements. From a motor control perspective, temporospatial control mechanisms underlying sound production remain poorly understood. Four-mallet marimba performance was assessed from spatial and temporal perspectives at three timepoints spaced over twelve weeks, here representing early (S1), intermediate (S2), and late phases (S3) of motor learning. Motion tracking measured movements of nine percussionists and computed acceleration of the elbows, wrists, hands, and mallets during the individual sessions. Mallets were held proximal to the pinky (mallet 1 in the left hand, mallet 4 in the right hand) and thumb (mallet 2 in the left hand, mallet 3 in the right hand). Mallet acceleration assessed temporal aspects of learning by converting data from each mallet and session into a frequency-domain representation using the pwelch method. The relative signal amplitude was extracted (i.e., relative power) to indicate relative contributions of specific frequencies to the time-series. Spatial contributions to learning were assessed via movement variability. It was hypothesized that the magnitude of learning would be greatest between S1 and S2, as demonstrated by reductions in spatial variability in upper-limb movements and temporal variability of mallet acceleration. As hypothesized, spatial variability in right and left elbow movements reduced between S1 and S2. However, temporal acceleration of mallets 2 and 3 increased from S1 to S2. Overall, percussionists may constrain movement degrees of freedom at the elbows to focus on temporal characteristics of the mallets during intermediate phases of motor learning in marimba performance.Acknowledgments: The Canada Foundation For Innovation and the Percussion Department in the Faculty of Music at U of T
Students’ Writing Anxiety and Its Implication to Local Context

Writing anxiety has been considered a significant hindrance for most Indonesian EFL students. With a growing number of available literatures on this issue, this paper aims to grasp the trends and deliver some implications to the national and local context. The available researches are the ones that have been published from 2017 to 2021. The subjects in those researches are university students majoring in English department. This review is one of the steps in pre-research on students’ anxiety in research courses and it has been done by using scoping study method. Therefore, taken from the thirteen collected literature, the trends have been summed up into 1. Types and levels of writing anxiety; 2. Factors or causes of writing anxiety; 3. Strategies to reduce writing anxiety; 4. Implications. The findings show that cognitive anxiety, linguistic difficulties the dominant in the trends of types and factors of students writing anxiety. In respect to the level, the findings indicate that students have moderate to high anxiety levels while metacognitive and affective as the dominant strategies used by students. Thus, in general, the findings have strengthened the concept of writing anxiety as an obstacle in students’ writing skills. Overall, some other significant variables such as personality traits, teaching techniques, awareness, and affective factors should be taken in future studies, and practices in teaching writing.
Development of Listening Comprehension Learning Media for Beginners-Based Websites

This research is entitled Development of Website-based Listening Comprehension Learning Media for Beginners. The purpose of this research is to produce a product, namely the learning media of the E-learning website. This study uses the ADDIE development model (Analysis, Design, Development, Implementation, and Evaluation). In the analysis phase, a preliminary study, curriculum analysis, and needs analysis are carried out. At the design stage, an outline of the contents of the website and the preparation of the website framework are made. At the Development stage, website creation, website packaging and presentation, quiz design, testing by media experts and material experts are carried out. At the implementation stage, tests were carried out on small classes and large classes. The evaluation stage includes indicators of media success which quantity evaluates each stage of development. The application used for this development is Adobe after Effects.
ABOUT MODERN EXPERIENCE, PROBLEMS AND ACHIEVEMENTS OF DISTANCE LEARNING AT THE UNIVERSITY

Distance education in a higher educational institution, taking into account its specifics and problems, can provide an opportunity for continuous learning and exchange of information without losing its relevance and novelty. The covid-19 pandemic that shook the whole world showed us how much our education system is not ready for the format of distance learning. Observing what is happening around the world, you should thoroughly prepare, since this is the format of training that will help to curb the rate of a sharp increase in infection and save many lives and health. It will take years more to teach students to assimilate and master distance learning. And you will have to teach, since education all over the world is smoothly moving to this format.
Towards secured digital business ecosystems: From threats to opportunities

This study aims at shedding more light on the values of the security landscape in the age of rapid digital businesses ecosystems development. The purpose of the paper is to enrich existing theoretical funds by providing a deeper and extended perspective on building secured digital business ecosystems, based on secondary data collection. The paper illuminates security gaps and emphasizes opportunities to effectively shift threats to sustainable value creation. Future research and management framework rely heavily on a switch from push-based to pull-based security ecosystem, protection strategies development, adoption of AI against cyber risks, and security culture development. The transformative journey towards long-term wellbeing to stakeholders included in the secured digital business ecosystems significantly lies in the multidisciplinary knowledge, simultaneous effectiveness of strategic change, and security management on one hand, and efficiency of IT and organizational capabilities, on the other. The article may contribute to academics, business owners, shareholders, strategic change, security, innovation, and IT management.
Datum: A System for TFRecord Dataset Management

Deep learning model training efficiency depends on the performance of the input pipeline. Especiallywhen training very deep neural network using GPU servers, efficient input pipeline can significantlyhelp reducing overall learning time. Tensorflow provides TFRecord format to store data in a sequence ofserialized protocol buffers as a binary record and tf.data.Dataset API for building input pipeline.TFRecord files are very read efficient and light on hard disk space usage. TFRecord files can be loadedas tf.data.Dataset for training neural network models. Creating and loading the TFRecord datasetinvolves writing a lot of complex codes and a time-consuming process. We develop Datum to automatethis complex process.
Relation Path Modeling with Entity Types for Knowledge Graph Completion

Considering that existing knowledge representation learning methods fail to make full use of various information to enhance knowledge representation, a knowledge representation learning method that incorporates entity types and relation paths is proposed. Firstly, the type-specific projection matrices is constructed by using the hierarchical type information of entities, which allows entities to have different entity representation based on type. Secondly, the representation of relationships between entities is also enhanced by rich semantic information on the path of relationships between entities. Finally, the entity vector and the relation vector are connected to obtain the final knowledge representation. The link prediction task on FB15K dataset shows that PTRL shows significant improvement in MR and Hits@10 compared to mainstream models such as TransE, TKRL and PTransE.
QUIPPER SCHOOL AND MICROSOFT TEAMS -BASED LEARNING MATERIAL IN ENGLISH CLASS: STUDENTS’ PERCEPTIONS (Study Case Taken from Saint Peter’s Junior High School)

Abstract. The aim of this study is to explore the students’ perception of the use of Quipper School And Microsoft Teams -based learning in English class which was taken at Saint Peter’s Junior High School, Jakarta. This study was researched and analyzed for the application of the online learning system applied by the teachers as the authors of this paper. Data were collected and processed from a questionnaire on student perceptions of the implementation of Likert scale-based learning. The scoring system is recommended and points are not recommended. The data were analyzed descriptively by using a table of percentage scores from 1-100 which was intended for students' points of view or opinions. The results of this study which focused on learning materials in English classes proved that students agreed that this based learning was effective to be applied and used. The average perception score is 92 as indicated by the seven product components (convenience, content, efficient use, language, clarity, collaborative use, and enjoyment of use). Keywords: Quipper School, Microsoft Teams, Students’ Perception, Jakarta, Based Learning Material
ADVANCE FACE DETECTION SYSTEM

Nowadays face detection is attracting much attention in the digital era to access the information for the security purpose. The face detection system is used for the information processing technology in different areas. The present research paper is used to detect the face of predefined images with the help of an application which detect the face using camera and detailed attendance is recorded in the excel file using the name of the student and time. The present application shows the accuracy reliability and robust for the face recognition system that can be practically implemented in the real life as an automatic attendance management system
Model Business Canvas to Reduce Desertion in Massive Online Courses

The full boom of digital transformation, e-learning through LMS systems (Learning Management System), has impacted on the development of the globalized world, and competes directly with face-to-face education; One of the main problems of those who start a virtual course is desertion, that is, many abandon the courses before concluding them, therefore, the objective of this research is the implementation of a business model that guarantees the success of a e-learning project, taking into account fundamental factors such as: the quality of the LMS design, tutoring strategies and digital marketing, generating in the participant an innovative digital experience that achieves specific learning. E-learning provider companies seek that their clients can start and conclude a virtual course, with guaranteed learning using an LMS, which will impact the positioning of the company, for this the content of the LMS must be interactive, motivating and designed for a high level of learning with innovative educational resources. As a result of the research, it has been shown that the perception of users of online courses regarding that the processes that prevent dropouts are good has gone from 25% without the application of the model to 56% with the application of the implemented model Canvas
IMPROVING THE SPEAKING ABILITY OF STUDENTS IN CLASS IVA SD NEGERI 0411 UJUNG BATU THROUGH VOCABULARY CARD MEDIA

The purpose of this study is (1) to find out how to improve speaking skills using vocabulary card media in fourth grade students of SD Negeri 0411 Ujung Batu in the academic year 2020/2021; (2) to determine the form of planning and implementation of learning to speak using vocabulary card media: (3) to find out the obstacles and results obtained from learning to speak using vocabulary card media, consisting of 20 students. This study also uses 2 (two) cycles starting from February to May 2021. From the results of the learning activities, it can be concluded as follows: (1) learning using vocabulary card media has a positive impact on improving speaking skills marked by an increase in students' speaking in each cycle, namely the first cycle obtained an average of 66.25 and in the second cycle obtained an average of 80; (2) the application of vocabulary card media in speaking skills has a positive influence, namely students are able to express and express ideas, and the results of students' scores meet the minimum completeness criteria
LibGuides: Alcohol & Drugs Studies Focused Library Resources for Faculty: Home

See how specific library resources can be made easily accessible within Canvas Supports SJCC's Alcohol & Drug Studies Program.
Rancang Bangun Sistem Pemantauan Staf Dan Manajemen Proyek Berbasis Web Menggunakan Codeigniter

The spread of the Covid-19 virus causes society behavior change, due to the very rapid spread of the Covid-19 virus through interactions with people or objects that have previously been infected or affected by the virus. This requires everyone to reduce activities outside the home and work from home. Work From Home is a working concept where workers do not need to come to the office. This concept is new for several companies including XYZ company. The Covid-19 pandemic has forced XYZ company staff to work from home. To ensure that the staff of XYZ company work productively, XYZ company have to monitors each of its staff. The implementation of the working from home can hinder project completion because staff productivity is decreasing. We propose an application to monitor staff based on working hours. This application also monitors project progress with features adding staff involved in each project, designing work plans, and target setting. To monitor project progress, each staff have to uploads their progress each day. This website is built using CodeIgniter and MySql as databases. Based on the functional testing result, the application can meet the functional requirement set by the company.
Critical Infrastructure Security in the Healthcare Sector.pdf

All critical infrastructures around the globe have become an increasing target of cyberattacks day by day. These cyberattacks are significantly concerning the healthcare sector as their primary target [1,2]. The last few years have seen the healthcare sector is undergoing an extraordinary transformation. There is a substantial shift from traditional system procedures towards modern, automated, and complex systems [2]. The outdated IT infrastructure, insecure database approaches, vulnerability systems still exist in most early level healthcare firms. They are not efficient to manage the high amount of data processing, new types of equipment and storage needs. When examining the adoption of Healthcare Information Systems (HIS) in the healthcare industry, the security of patient's data, data of hospital employees and hospital informational data is the most overbearing restrictions to access for the cyber attackers [3]. The study will discuss the critical infrastructure security of the healthcare industry, and threats to healthcare infrastructure and various techniques that can use to prevent happening cyberattacks and how to apply them to the IoT [Internet of Things] based health care sector. The study also focuses on Encryption standards used in the health care sector to defend its infrastructure from cyber threats.