Reviewerly/exHarmony huggingface dataset:
Bi-granularity Adversarial Training for Non-factoid Answer Retrieval

Answer Retrieval is a task of automatically retrieving relevant answers towards a specific question. The recent studies, in this field, have witnessed the vast success of non-factoid QA methods which leverage the large pre-trained models. The findings in intensive experiments have shown that the existing large and deep models can be enhanced by the utilization of adversarial examples, the ones which effectively challenge encoders during training and enable them to generalize well during test. However, the majority of adversarial training methods still suffer from two limitations: 1) they separately take into consideration single-granularity adversarial examples (e.g. character, token or sentence-level examples), resulting in a monotonous mode that easily make encoders get accustomed to such examples, and 2) they fail to actively detect and apply the truly challenging adversarial examples for training. In this paper, we propose a Bi-granularity Adversarial Training (BAT) approach. It not only involves multiple perturbation into the generation of adversarial examples, but selectively utilizes them in terms of perturbation strength. A self-adaptive adversarial training method is developed for recognizing perturbative examples. We conduct experiments on the WikiPassageQA and TREC-QA benchmarks. Experimental results show that BAT substantially improve the answer retrieval performance, reaching the MAP score of about 80.05 $$\%$$ and MRR of 86.27 $$\%$$ for WikiPassageQA, MAP of 93.99 $$\%$$ and MRR of 97.55 $$\%$$ for TREC-QA.
Mobile Forensic for KeyLogger Artifact

This chapter investigates mobile forensic investigation for the KeyLogger application installed on iOS or Android; it introduces and helps the investigator to discover traces of a spy application case, determine which tools were used to investigate and search for various spy programs, and shows how to report results obtained from the iPhone spy program, which was installed and used for espionage and access to sensitive data.
Peripheral Instance Augmentation for End-to-End Anomaly Detection Using Weighted Adversarial Learning

Anomaly detection has been a lasting yet active research area for decades. However, the existing methods are generally biased towards capturing the regularities of high-density normal instances with insufficient learning of peripheral instances. This may cause a failure in finding a representative description of the normal class, leading to high false positives. Thus, we introduce a novel anomaly detection model that utilizes a small number of labelled anomalies to guide the adversarial training. In particular, a weighted generative model is applied to generate peripheral normal instances as supplements to better learn the characteristics of the normal class, while reducing false positives. Additionally, with the help of generated peripheral instances and labelled anomalies, an anomaly score learner simultaneously learns (1) latent representations of instances and (2) anomaly scores, in an end-to-end manner. The experimental results show that our model outperforms the state-of-the-art anomaly detection methods on four publicly available datasets, achieving improvements of 6.15%–44.35% in AUPRC and 2.27%–22.3% in AUROC, on average. Furthermore, we applied the proposed model to a real merchant fraud detection application, which further demonstrates its effectiveness in a real-world setting.
Electronic Serials Cataloging: Now That We're Here, What Do We Do?

Many aspects of electronic serials cataloging have not yet developed standard practice, or are still in transition. This article will explore some problematic issues in electronic serials cataloging 110first by presenting current CONSER policy in these areas and then by examining the practices of three institutions who are cataloging electronic serials. For brevity, the term “electronic serial” will be used to mean “remote access computer file serial” unless the more specific term is needed for clarity. The five topics covered in this discussion are: Access and Location Information, Multiple Versions, Definition of Electronic Serial, Bibliographic Access Points and Display of Computer File Characteristics. [Article copies available for a fee from The Haworth Document Delivery Service: 1-800-342-9678. E-mail address: getinfo@haworth.com]
Comparative Study on Hyperspectral Image Enhancement for Low Illumination Outdoor Scenes Images

Hyperspectral image is rich with information because it contains spatial and spectral properties of specific objects. However, the image quality may be affected by low lighting conditions caused by non-uniform illumination environments, uncontrollable weather, which tends to darken outdoor scenes. Difficulty arises for high order image processing modalities such as detection, classification and tracking. In this paper, a comparative study was conducted to identify the most appropriate enhancement method for outdoor scenes. Four techniques were investigated: Bio-Inspired Multi-Exposure Fusion (BIMEF), Dehazing, Illumination Estimation, and Multi-deviation Fusion (MF). Experiments revealed that BIMEF is the best approach with the lowest lightness of error.
Image Infringement Judgement with CNN-based Face Recognition

Image Infringement Judgment can help public figures to solve infringement of portrait rights. This paper uses Convolutional Neural Network (CNN) to predict the category of images. First, we use data scraping to get public photos to create the data set required for the training model. Secondly, this paper constructs a face prediction model through the CNN framework and extracts the feature of faces through the algorithm. Finally, we adjust parameters to optimize the model through data visualization. To verify the effectiveness of CNN, we compare it with the Multilayer Perceptron (MLP) on two different data sets, one is the data set built by reading camera pictures, and the other is the data set built by static pictures. The experimental results show that the face recognition application based on the CNN model proposed in this paper has an accuracy rate of 97%. It can classify the extracted data set well, can obtain the data content, and make accurate predictions. We applied this accurate model to the judgment of the infringement of images on the WeChat public account.
Earthquake Early Warning Systems: Methodologies, Strategies, and Future Challenges

Earthquake early warning systems are able to issue an alert just after the start of the seismic rupture on the fault plane, but before the ground shaking reaches the sites to be protected. The available lead-time for security actions is very short (seconds to several dozens of seconds), requiring fast and robust methods to make these systems operational. Here, general principles about the two paradigms of early warning systems are presented: the regional and the on-site systems. When these methods are applied to data recorded by very dense networks, such as in near-fault observatories, the blind zone can be shortened to 15–25 km. Next generation of early warning systems should reduce the epistemic variability by implementing modeling of finite-source and site effects. Finally, the combination of on-site and regional systems may lead to a real-time estimation of the ground-shaking maps, overcoming the problem of computing the event location, and magnitude.
Layout of Direct Input Interface Based on Virtual Space

Immersive virtual environment has the potential to realize natural interaction in users' close interactive space. To explore the efficient layout of direct input interface suitable for hand-eye cooperation in virtual environment, through the freehand clicking experiment, the participants were required to quickly click the random targets in three different spatial depths. The results show that in the visual field of head mounted display (HMD), the depth has a significant impact on the arm movement time and clicking accuracy. It is suggested that the low-frequency and short-term interactive content can be placed in the left and upper right areas of the visual field, and the high-frequency and long-term content can be placed in the central and lower area with low consumption endurance. The down-right area is not suitable for quick click. This paper proposes an efficient direct input interactive layout in virtual space based on spatial dimensions and arm kinematics.
PassVaRRdS - Password Generator, Encrypting and Storage using AES and Cloud

The users of computer technology and internet are increasing day by day. As the users are growing, the need for security is also felt very much. The data assets and other valuable facts are stored in the computer systems. One of the ways to safe guard the data assets is to have a proper authorization method to access the data. This is achieved by user identification and password mechanism. The selection of password is important, since the entire authorization is dependent on the password. The password needs to be strong enough to avoid brute force attack and other attacks. Also remembering complicated passwords or passwords of multiple accounts can be much hectic, thus we need a way to store or save the password securely. It should also be kept in mind that the passwords should be easily accessible to the user but cannot be breached by others. So we are using Advanced Encryption Standard algorithm to safely encrypt the passwords and store the encrypted passwords in the cloud database.
Towards Personalized Educational Resources Recommendations for Teachers

Recommender systems experience the challenging and complex process of finding educational resources recommendations for teachers which requires a careful awareness of the teacher’s context. These systems should take into consideration the contextual coexistence of teachers in multiple environments or contexts such as social, working, and sentimental contexts. The collected data for each of these contexts is assembled from different sources and systems with different data architectures. Accordingly, this paper provides a multi-step proposition towards a personalized educational resource recommendations for teachers. Furthermore, the paper discusses the data sources from which the contextual data is collected, in addition to the purposed methodology for integrating and mapping the data into the ontology. At the end, the paper illustrates the importance and the role of the teacher analytics and the sentimental data in this proposition. The proposed approach results in a complete representation of the teacher’s context and hence, the personalized recommendations.
Autonomous Off-Road Navigation Using Near-Feature-Based World Knowledge Incorporation on the Example of Forest Path Detection

This paper presents a novel approach for robust off-road navigation based on deep convolutional neural networks which are combined with OpenStreetMap data to perform a forest path-based local localization approach. Corresponding near features are used to integrate navigation relevant world knowledge into a local multi-feature map. A behavior-based controller adapts the robot’s trajectory based on available features and its detection quality. The approach was tested in the Rhineland-Palatinate forest. Different forest way detection setups were evaluated and are discussed in detail. Additionally, the autonomous mobile robot GatorX855D followed a forest trail using the resulting multi-feature map.
The Europe’s Lost Frontiers Augmented Reality Sandbox: Explaining a 2.5 Million Euro Project Using Play Sand

The subject area of the Europe's Lost Frontiers project, the submerged landscape of Doggerland, is inaccessible and the data by which we can understand it is complex and hard for the non-specialist to understand. To be able to present the project at public events, an Augmented Reality sandbox was constructed, which records the shape of sand in a box, interprets it as a landscape inhabited by humans, animals and plants, and projects this simulated land back on to the sand. Different software packages can be used to highlight the effects of climate change or provide examples of the different types of evidence available to archaeologists researching submerged landscapes. The end result is an interactive, accessible display which attracts all ages and can be used as a starting point to conversation regarding the project's archaeological, scientific and technological aspects.
A model to improve recommendation systems based on Spark platform

With the popularity of using the internet, the evolution of technology, the rapid growth of data volume, and applying recommendation systems in diverse life domains, adopting recommendation systems became indispensable. Most of the traditional recommendation systems are built un-oriented of real-time data challenges (such as item cold-start, scalability, heterogeneous data, items change, and users' opinions change), resulting in ineffective, unfulfilling recommendations. Therefore, what is needed is a real-time-based recommendation model that can make the user find what s/he needs without even searching for it; it's like building a model aware of the users' nature and behaviour. This paper aims at building a recommendation model that fulfils the user requirements and overcomes the shortcomings of the traditional recommendation systems. The proposed recommendation model is built on Apache Spark, Apache Kafka and alternative least square (ALS) algorithm, and the model is divided into two parts: recommendation system and real-time analytics dashboard. An e-commerce website is chosen as a case study to apply our model and the results are presented.
Correlation of English students’ reading habits and their writing ability

While writing is critical in education, it is a difficult skill to master. Reading is one of the many factors that affect writing. Numerous studies have established a link between reading and writing. With that assumption, this study will examine the relationship between English reading habits and writing ability among students enrolled in the Advanced Writing Course at the English Language Education Study Program of Lambung Mangkurat University. This study adopted a quantitative approach and a correlational design, with students from batch 2018 as the research population. Using a simple random sampling technique, 50 students were randomly selected to serve as samples. A questionnaire was used to ascertain the students' reading habits, whereas a test was used to ascertain their writing abilities. Pearson Product-Moment Coefficient Correlation was then used to determine the correlation between the variables. The result showed that the correlation coefficient was 0.211 and the significance value was 0.141, indicating that H0 is acceptable because of the sig. value was ? 0.05. Therefore, there is a weak and negative correlation between students' reading habits and their writing ability. This occurred because many students with strong reading habits also have weak writing abilities, implying that the correlation between the two variables is weak. It is suggested that students develop a reading habit by beginning with small steps such as selecting a short, easy-to-read book, setting small goals, making reading enjoyable, making reading friends, and remaining consistent.
A Study on the Development of Cucuk Sanggul Design in the 15th to 16th Century

Cucuk sanggul is a personal adornment accessory worn on the head.Cucuk Sanggul is one of the cultural heritages of Malays objects that are still being used as a medium during Malay community ceremony including daily activities, worship, performance and weapons as well as used in official and royal ceremonies.This cucuk sanggul is an accessory that is beautifully designed and decorated with various type of design and has different motifs.The aims of this research are to identify the development and study meaning the types of motifs and design that's found in cucuk sanggul the meanings of cucuk sanggul are different and most of them are related with the Malay philosophy.However, the modernization has transferred the design of cucuk sanggul to a very simple design and motif which are more minimal and plain.The study conclude that Malay cucuk sanggul need to be preserved in terms of the forms, function and meaning and can be sustained and valued by the future generation.Besides that, the Malay community not only follows the tradition but also the appreciation and interpretation for the cucuk sanggul.
Digital Skills and Competences in Contemporary Society

Digitalization is an integral part of society. Every process, phenomenon, community and relationship is related to digitalization and information technology. The life of a modern person is a long series of active penetration of digital devices in our way of life, in our professional responsibilities and activities, in our free time and personal contacts. This strong digital saturation today is constantly recognized and modern man is clearly aware of his dependence on information technology, without which it would be difficult to do his job, to contact people and institutions that reflect different levels of social interaction, and to organize free your time and entertainment. From this point of view, it is necessary to show the different forms of symbiosis between society and digitalization, as well as to emphasize the possible manifestations of this symbiosis.The objectives of this paper are to show specific dimensions of the advent of digitization and the various technologies in the Bulgarian society and in particular:-What digital devices do individuals have and how do they use them;-How they get involved in the Internet and what is their participation in the various social networks;-What is the quality of online learning as one of the examples of digital activity in social terms;-What is the technological level of the online environment;-What are the challenges of online education?The main research questions are related to the performance of high-tech level of Bulgarian online environment and focus on the main features of online learning, which is a new educational activity for Bulgarian schools and universities and its basic actors who gradually become active users of its.The Methodology is based on results obtained from an online survey conducted in March 2021 with people of different ages, occupations and education. The survey questionnaire included topics that directly relate to the digitalization of society, the use of various digital devices and the Internet, participation in online education and attitudes towards it. The results obtained show that digitalization has undisputable a place in the Bulgarian educational system. It is assessed relatively positively, it is perceived as a good step and solution and gradually people perceive it as a main element of the educational space. One of the advantages of online learning is its flexibility. Instead of training taking place in a fixed place and time, with the help of high technology it can take place anywhere and at any time. An important conclusion of this article is that various improvements need to be made to make the online education activity more effective. The most important thing to think about is how to overcome the shortcomings of online learning and how to deal with them people of different ages and statuses.
Underwater Magnetic Target Detection Method Based on Lightweight YOLOv3

In order to enable intelligent underwater robots to quickly and accurately detect underwater magnetic targets in complex underwater environments, a lightweight YOLOv3 algorithm-YOLOv3-Metal is proposed. By improving the structure of the network YOLOv3 and reducing the residual structure to compress the network, the detection speed of the improved algorithm can be increased; the spatial pyramid pooling (SPP) module is introduced by improving the feature fusion network, which can enrich the deep features; by improving the loss function of the basic YOLOv3 algorithm, the detection accuracy of small targets can be improved. Secondly, a crawler program is developed, training data is obtained from the internet and annotated, and data enhancement technology is used to expand the training data. Finally, the underwater magnetic target detection experiment was carried out on the computer workstation and the embedded development board. From the experimental results, it can be concluded that the YOLOv3-Metal algorithm has higher detection accuracy and faster detection speed than the original YOLOv3 algorithm.
Introduction to the Minitrack on Data Analytics, Data Mining and Machine Learning for Social Media

Social media continues to reflect our daily lives.Ubiquitous mobile devices allow for immersion into social media on a nearly universal basis.As such, the blurring of the line between our online and offline worlds and personas only continues to increase.Traditional text-based platforms are increasingly turning to image and video content, with video-intensive platforms appealing more to younger generations.We are also starting to see longer threads, stories, and conversations emerging, meaning there is significance in looking at social media messages as part of a larger discussion.These shifts result in both additional challenges and opportunities for researchers to understand the role social media is playing in society.The papers in our minitrack represent the diversity of our field.We see data gathered from multiple platforms as well as new techniques to analyze these data.
Leadership

Leadership and the different associated styles have an immense impact on how employee perform and grow to lead positive organizational out comes. The purpose of this study would be to investigate the impact of leadership styles on motivation and commitment as on predictor of group of organizational performance. Leadership and management must go hard in hand. They are not the same thing. Through they are different. they are necessarily linked, and complementary. Leadership is an important aspect of managing. As leaders, they are not only the responsible for directing their followers but also responsible for the attainment of goals of the organizations. It is believe that leaders are born not made. At the same time, a few people also believe that leaders are not born but made. But generally leaders are born and also made. Leadership is the process of influencing the activities of an individual or a group towards the achievement of a goal in a given situation. Leadership process is a function of the leader, the follower and other situational variable. Coming to the business organizations, people working there need leaders-individuals who could be instrumental in guiding the efforts of groups of workers to the achievement of goals and objectives both the individuals and the organizations. The objectives may not be very far reaching and the actions of the leader may not be so dramatic. but the successful performance of the leadership role is essential to the survival of the business enterprise.