Reviewerly/exHarmony huggingface dataset:
Triple Multimodal Cyclic Fusion and Self-Adaptive Balancing for Video Q&amp;A燬ystems

Performance of Video Question and Answer (VQA) systems relies on capturing key information of both visual images and natural language in the context to generate relevant questions' answers.However, traditional linear combinations of multimodal features focus only on shallow feature interactions, fall far short of the need of deep feature fusion.Attention mechanisms were used to perform deep fusion, but most of them can only process weight assignment of single-modal information, leading to attention imbalance for different modalities.To address above problems, we propose a novel VQA model based on Triple Multimodal feature Cyclic Fusion (TMCF) and Self-Adaptive Multimodal Balancing Mechanism (SAMB).Our model is designed to enhance complex feature interactions among multimodal features with cross-modal information balancing.In addition, TMCF and SAMB can be used as an extensible plug-in for exploring new feature combinations in the visual image domain.Extensive experiments were conducted on MSVD-QA and MSRVTT-QA datasets.The results confirm the advantages of our approach in handling multimodal tasks.Besides, we also provide analyses for ablation studies to verify the effectiveness of each proposed component.
THE PECULIARITIES OF EDUCATIONAL COMMUNICATION UNDER THE DISTANCE LEARNING MODE

The article analyzes the features of educational communication in higher education institutions in the context of distance learning. It has been noted that the ultimate goal of educational communication is both the transfer of information and the formation of a certain system of students’ knowledge, skills and competencies . The objective of the article is to analyze the features of the model of educational communication as a classic element of the information and pedagogical environment in terms of distance learning on the basis of pedagogical constructivism, presented in modern domestic and foreign studies. It has been analyzed the concept of distance learning as a purposeful interactive process of higher education, based on scientific sources and the use of modern information and telecommunications technologies. The advantages of distance learning are emphasized, in particular extraterritoriality, synchronous and asynchronous modes of interaction of participants of educational process. Under the distance learning mode there is a practical mastering of information tools and communication technologies. It has been emphasized that distance learning provides access to various educational resources, gives an opportunity to receive education in a convenient, adequate and appropriate form for the student, helps to develop student abilities, provides data exchange, communicative activities based on professional and educational interests, training, retraining or change professional activity. The educational environment as a combination of offline and online structures in monocultural and multicultural space is studied. It is emphasized that with the development of information technologies the students’ communicative efficiency of increases, access to international resources is simplified. The change of the model of educational communication is substantiated, as a result of which there is an attraction of more sources of information and communication channels in the space of information flows. It has been made the conclusions about the change of information transfer technology in a modern higher education institution. The communication capabilities of the educational process in terms of distance learning depend on the means of transmitting information that meet the goals and objectives of learning. Changes in the regulation of educational communication, the modality of the learning process is to assess the information educational flow by the subject of learning in solving personal educational problems.
Enhanced financial fraud detection using cost‐sensitive cascade forest with missing value imputation

Summary Financial statement fraud is a global problem for investors, audit firms, regulators, and other stakeholders. Fraud detection can be regarded as a binary classification problem with a false negative being more expensive than a false positive. Although existing studies have made great efforts to detect fraud using various data‐mining techniques, the difference in misclassification costs is seldom considered. In this study, we propose a cost‐sensitive cascade forest (CSCF) for fraud detection, which places heavy penalty on false negative prediction and self‐adjusts the depth of a cascade forest according to the classifier’s recall (i.e. the classifier’s sensitivity). As missing values are ubiquitous in fraud research, we also explore the effect of selected missing data treatments on prediction performance, including complete case analysis, three selected classic statistical mechanisms (zero, mean, and modified mean imputation), and two machine learning (K‐nearest neighbor [KNN] and random forest [RF]) approaches. The experimental results show that the proposed CSCF significantly improves the fraud prediction in comparison with one of the latest fraud detection models using the RUSBoost algorithm. Comparing different missing value treatments, even though RUSBoost and CSCF perform well when using complete case analysis, we find that the best performance is achieved when CSCF is used with missing data imputed as zero. Such treatment further improves the performance, and results in an area under curve (AUC) score of 0.82 compared to the highest AUC (0.71) from the baseline model. Supplementary analysis further reveals that the low AUC of complete case analysis for the two examined models persists under different training sizes. Thus, our findings shed light on the potential benefits of missing value imputation for the model’s performance for fraud detection.
User perceptions about sharing exposure notification information for communicable diseases

The (GuideSafe™) Exposure Notification System (ENS) was built and deployed in (Alabama) for anonymous sending and receiving of COVID-19 exposure alerts to people who have been in close contact with someone who later reports a positive COVID-19 test. Little is known about how the demographic groups perceive recent privacy-preserving the ENS innovations, including their usability, usefulness, satisfaction, and continued interest in sharing COVID-19 exposure information. The purpose of this study was to investigate how users across the demographic groups perceive the sharing of exposure information with various types of organizations and to investigate how end-user perceptions of the ENS usability, usefulness, and satisfaction differ across the demographic groups within the context of a statewide deployment of an exposure notification system.A survey was administered to (state residents blinded for review) (N = 1,049) to assess propensity to share COVID-19 infection data and evaluate end-user perceptions about usability, usefulness, and satisfaction with the (Alabama) ENS. The ANOVA and the Tukey's Honestly Significant Difference (HSD) post-hoc tests were conducted to assess the demographic group differences.The ENS survey participants had a high awareness of contact tracing, exposure notifications, and the (GuideSafe™) ENS and reported having downloaded the app. Survey results revealed the majority of participants rated the app as useful (n = 490, 79%), easy to use (n = 490, 79%), and reported satisfaction with its use (n = 546, 88%). Other results suggest that ethnicity and age may be important factors for trust in sharing exposure information.The (GuideSafe™) system was one integrated component of comprehensive education and work re-entry strategy across (Alabama) that reached a broad user base. Users across the different demographic groups perceive the sharing of information about their communicable disease exposures differently. Furthermore, demographic factors play a role in which types of organizations individuals are willing to share their communicable disease exposure information. Public health institutions, employers, schools, healthcare providers, and technology designers may want to consider these findings as they construct technologies and perform outreach campaigns aimed at reducing infection rates with the ENS and related technologies.
Self‐improved moth flame for optimal container resource allocation in cloud

SUMMARY Resource allocation in the cloud is becoming more complicated and challenging due to the rising necessities of cloud services. Effective management of virtual resources in the cloud is of large significance since it has a great impact on both the operational cost and scalability of the cloud environment. Nowadays, containers are becoming more popular in this regard due to their characteristics like reduced overhead and portability. Conventional resource allocation schemes are usually modeled for the migration and allocation of virtual machines (VM), as a result; the question may arise on, “how these strategies can be adapted for the management of a containerized cloud”. This work evolves the solution to this issue by introducing a new fitness oriented moth flame algorithm (F‐MFA) for optimizing the allocation of containers. Further in this work, the optimal allocation relies on certain constraints like balanced cluster use, system failure, total network distance (TND), security and threshold distance, and credibility factor as well. In the end, the supremacy of the presented model is computed to the conventional models in terms of cost and convergence analysis.
About Challenges in Data Analytics and Machine Learning for Social Good

The large number of new services and applications and, in general, all our everyday activities resolve in data mass production: all these data can become a golden source of information that might be used to improve our lives, wellness and working days. (Interpretable) Machine Learning approaches, the use of which is increasingly ubiquitous in various settings, are definitely one of the most effective tools for retrieving and obtaining essential information from data. However, many challenges arise in order to effectively exploit them. In this paper, we analyze key scenarios in which large amounts of data and machine learning techniques can be used for social good: social network analytics for enhancing cultural heritage dissemination; game analytics to foster Computational Thinking in education; medical analytics to improve the quality of life of the elderly and reduce health care expenses; exploration of work datafication potential in improving the management of human resources (HRM). For the first two of the previously mentioned scenarios, we present new results related to previously published research, framing these results in a more general discussion over challenges arising when adopting machine learning techniques for social good.
PERANCANGAN WEBCOMIC “QUEEN OF BEE” MENGENAI FENOMENA SOCIAL CLIMBER UNTUK REMAJA

The behavior of teenagers today is very much influenced by the existence of social media. The desire to appear existent and get recognition makes teenagers like to show off a luxurious lifestyle and hits, even though sometimes that lifestyle is not in accordance with their real life. This is what causes a social climber phenomenon where an individual tries to do certain things in order to increase the degree of his social status. Social climber has many negative impacts on teenagers' lives. Because it requires a media to deliver information that can provide knowledge to adolescents about the social climber phenomenon and its negative impact on adolescents. The media for delivering information that will be used is in the form of webcomics or digital comics.Webcomic is used as the main media because it has an attractive appearance, is not boring and easy to access. By using a character approach that suits young social media users, the target audience will certainly be more interested. This webcomic will be supported by several media that can help promote products such as promotional videos, posters. X banner, T-shirt, key chain and instagram.The design methodology used is the Glassbox design method which consists of 4 stages, preparation, incubation, illumination and verification and the 5W + 2H data analysis method which is used as a basic concept for problem solving, that is what (what), who (who), when (when) , where (where), why (why), how (how) and how much (how much).Keywords: Webcomic, Digital Comic, Webtoon, Social Climber, Pansos, Panjat Sosial.
Research on the internal mechanism and path of the new growth point of marine biological economy

In order to explore how the marine economy can realize the new growth point of economic development, this study puts forward a research method based on the internal mechanism and path of the new growth point of marine economic development. This method recommends key technical problems and solutions based on the research method of the internal mechanism and path of developing new growth points, amphibious science that further integrates, ecological, and socialized theory and application and explores the internal mechanism and path of how the marine economy realizes the new growth points of economic development. The research shows that the research on the internal mechanism and path of developing new growth points has increased the marine economy by nearly 45%, deeply analyzes the internal relationship between coastal economic growth and marine pollution, the close relationship between marine resources development and marine economic growth, and briefly summarizes the marine economic growth path against the background of the adjustment and change of marine industrial structure.
Tackling Verification and Validation Techniques to Evaluate Cyber Situational Awareness Capabilities

Since cyberspace was identified as a domain of operations, defence practitioners started a race with academy, researchers, and industry and military organizations working together towards defining related lines of capability development (e.g., DOTMLPFI) and exploring the needs and opportunities they entail. An essential cornerstone of adapting to the convergence of the cyber domain with conventional theaters of operation is the need for producing tools for easing to acquire cyber situational awareness (CSA), from which human operators shall be able to perceive, reason and project situations and events observed in cyberspace that may vertically/horizontally propagate from technological to tactical, operational and strategic planes. Benefiting from the higher maturity level of civilian capabilities for cybersecurity, the military sector has embraced the challenge of creating related beyond state-of-the-art CSA enablers that comprise the existing technological background while adopting concepts such as operations, missions or courses of action (CoAs), properly aligning them with military doctrine. Beyond ongoing development efforts, there is a wide methodological gap in the lack of suitable CSA verification and validation (V&amp;V) frameworks, which are expected to analyze if related capabilities meet the requirements to operate in the military context; at the same time supporting the thorough development life-cycle of brand new cyber defence technologies. With the motivation of closing the identified gap, this research introduces a novel V&amp;V framework able to guide the evaluation of CSA-related tools, which makes converge purely military aspects with dual-use state-of-the-art V&amp;V approaches. Three core CSA evaluation concepts are discussed in-depth: software, operational and application tests. They range from the daily application of new capabilities to their ability to enable the acquisition of a joint operational picture understandable by human decision makers.
Why is my System Biased?: Rating of AI Systems through a Causal Lens

Artificial Intelligence (AI) systems like facial recognition systems and sentiment analyzers are known to exhibit model uncertainty which can be perceived as algorithmic bias in most cases. The aim of my Ph.D. is to examine and control the bias present in these AI systems by establishing causal relationships and also assigning a rating to these systems, which helps the user to make an informed selection when choosing from different systems for their application.
Digital literacy among Students and Teachers

With the advent of the internet, many sectors went into Digi-mode. During this time, a lot of work began to be done online and the convenience led it to spread. The pandemic brought about a faster spread of digital usage among people. Commercial sectors, government units, educational sectors, sales and retail, food and groceries; all these units and many more embraced the online platform. Like all other sectors, the educational sector also became dependent on digital classes and e-learning. With this, it became inevitable for the students and the teachers to educate themselves digitally. This scenario brought a need for not only students and teachers to be educated digitally but also for the parents as well, since they were now more involved in their child's education than before. The parents of the students were now responsible for making sure that the child had completed the work given, for making sure that they are available online physically and mentally during the class. It has been a huge change for everyone to be moving into a digital phase and while many have gladly embraced it and are finding it very convenient, there are others who are facing technical problems like inconsistent electricity supply, lack of necessary devices, low speed bandwidth and many more. In this paper, I am going to talk about digital literacy among students and teachers what are the challenges that they have faced and how they brought about solutions to the challenges and what more can be done to enhance digital literacy among teachers and students.
PERANCANGAN VIDEO PROMOSI OBJEK WISATA PEMANDIAN ALAM AIA BALIANG

This natural bathing attraction is located on the Padang-Solok causeway precisely at kilometer 14, if from Padang to Solok the location is right on a bend before the Lubuk Paraku bath to Sitinjau Lauik. The atmosphere in Aia Baliang is very natural, the water flowing cold and fresh, plus quite shady trees and a waterfall with a height of about 6 meters adds to the natural impression on this one tourist attraction.The creative purpose of Aia Baliang natural bathing tourism video to be achieved is to design an information media that aims to convey information to the target audience completely, communicatively, attractively and reflect the image of professionalism as expected. The approach used rationally but still packaged attractively, so that the information to be conveyed is achieved effectively.The main media used in designing the promotional video of Aia Baliang natural bathing attraction is Video. In addition to the main media, this promotional video is complemented by supporting media such as X-Banners, t-shirts, posters, hats, drinking bottles, pamphlets and stickers which aim to strengthen the application of the main media.Keywords: Design of Promotion Videos for Nature Baths Aia Baliang, Media
CoRec: An Efficient Internet Behavior-based Recommendation Framework with Edge-cloud Collaboration on Deep Convolution Neural Networks

Both accurate and fast mobile recommendation systems based on click behaviors analysis are crucial in e-business. Deep learning has achieved state-of-the-art accuracy and the traditional wisdom often hosts these computation-intensive models in powerful cloud centers. However, the cloud-only approaches put significant computational pressure on cloud servers and increase the latency in heavy-load scenarios. Moreover, existing work often adopts RNN structures to model behaviors that suffer from low processing speed for under-utilization of parallel devices such as GPUs. In this work, we propose an efficient internet behavior-based recommendation framework with edge-cloud collaboration on deep CNNs (CoRec) to improve both the accuracy and speed for mobile recommendation. A novel convolutional interest network (CIN) improves the accuracy by modeling the long- and short-term interests and accelerates the prediction through parallel-friendly convolutions. To further improve the serving throughput and latency, a novel device-cloud collaboration strategy reduces workloads by pre-computing and caching long-term interests in the cloud offline and real-time computation of short-term interests in devices. Extensive experiments on real-world datasets show that CoRec significantly outperforms the state-of-the-art methods in accuracy and has achieved at least an order of magnitude improvement in latency and throughput compared to cloud-only RNN-based approaches for long behaviors.
Analysis of the Teaching Design Process Mode of College English Application Oriented Curriculum with NLP Voice Data Authentication

The purpose is to introduce game-based learning into college English communication courses, improve the competence of college students’ oral English expression and reduce their anxieties in speaking English. Four games are designed and an experiment of 20 sophomores’ performances in college oral communication classes is conducted for a semester. According to the classroom activities of oral English, the content of the games is reciting and delivering the sentences in order, guessing and understanding the characteristics of the single word, guessing the word by asking questions, and describing the pictures in English. This can be implemented with the Natural language Processing Assistance on Digital Library Management which presents the requirements for handling the documents in digital libraries.The research tools include an oral English test, FLCAS (Foreign Language Classroom Anxiety Scale), classroom observation and a game-based learning recordwith the efficientresults are as follows: 1. The introduction of the four games into the oral English communication courses is found feasible. But the student's basic knowledge of English affects their enthusiasm for the games. 2.The skill of students' oral English expression is improved significantly after the introduction of the games, and they can speak complete English sentences to answer questions and describe pictures. 3. The students’ test anxiety decreases significantly, but they still feel anxious about the negative comments on their oral English performances. 4. According to the reflection and revision of the whole research process, the teaching mode design of the college English application course is developed in three aspects, including game design, game-course matching, and game integration into teaching.
Big Data Distributed Storage and Processing Case Studies

This research paper summarizes the evolution of big data concept and the techniques that are closely connected to big data concept, including CAP theorem, which happens to be one of the most important rules in modern distributed computing. Moreover, this paper focuses on the open-source software built from the Apache big data platform. It looks under the domain of NoSQL database Cassandra, which is the primary software considered in this study, and real use cases of Cassandra and related technologies in real-world scenarios. The proposed study also describes the development of certain use cases.