Reviewerly/exHarmony huggingface dataset:
Recent advances in domain-driven data mining

Abstract Data mining research has been significantly motivated by and benefited from real-world applications in novel domains. This special issue was proposed and edited to draw attention to domain-driven data mining and disseminate research in foundations, frameworks, and applications for data-driven and actionable knowledge discovery. Along with this special issue, we also organized a related workshop to continue the previous efforts on promoting advances in domain-driven data mining. This editorial report will first summarize the selected papers in the special issue, then discuss various industrial trends in the context of the selected papers, and finally document the keynote talks presented by the workshop. Although many scholars have made prominent contributions with the theme of domain-driven data mining, there are still various new research problems and challenges calling for more research investigations in the future. We hope this special issue is helpful for scholars working along this critically important line of research.
Automatic heart segmentation based on convolutional networks using attention mechanism

Heart segmentation is challenging due to the poor image contrast of heart in the CT images. Since manual segmentation of the heart is tedious and time-consuming, we propose an attention-based Convolution Neural Network (CNN) for heart segmentation. First, one-hot preprocessing is performed on the multi-tissue CT images. U-Net network with Attention-gate is then applied to obtain the heart region. We compared our method with several CNN methods in terms of dice coefficient. Results show that our method outperforms other methods for segmentation.
Reading American Historical Context with &lt;Lincoln&gt;: Focused on an Online Case Study

According as a university education has responded to the changing times, movies have been good teaching materials. In this educational environment, this study tries to explore the case study to use Lincoln (2013) directed by Steven Spielberg as a means of drawing learners’ attention to historical backdrops. Learners that have difficulty in grasping historical contexts can find out the point of contact with major historical issues from the Civil War to the early 19th century such as Indian Removal Act, New York City Draft Riots and Jim Crow Law etc. In the process of understanding various historical events based on the movie, the learners may bring out various questions and discuss them. It means that learners can enhance their critical thinking and extend the comprehensive faculty to human being and the world.
PECS: A Pareto-efficient and Envy-free Cloud Resource Scheduler

In recent years, cloud computing platforms have attracted more and more attention. A key challenge is that existing schedulers provide limited support for heterogeneous types of resources. This makes it difficult to allocate resources in a timely manner adaptively and efficiently to perform different kinds of tasks. In this paper, we develop and evaluate a scheduling system with QoS guarantees when multiple tasks are involved, in which we show a possible design driven by the use of utilities for task-based resource allocation. We call the resulting method PECS, which meets the following unique properties compared to existing systems: Pareto efficiency, i.e. no other assignment can increase the sum of utility of all tasks without harming at least one specific task; freedom of envyness, i.e. no task will find the allocation of resource for another task better for its own utility; finally, improvements based on equal distribution are guaranteed, that is, the utility of all tasks is at least as high as the equal distribution of all resources. Our evaluation results compare PECS with a state-of-the-art resource allocation method called DRF, where our results demonstrate the performance benefits of PECS applied to a rich set of task assignment scenarios.
Innovative technology of teaching M. Auezov's stories in higher education

The article provides a comprehensive analysis of traditional teaching methods, which are widely used in modern higher education, in a modern way. New conclusions were made about the history of the methodological field of modern pedagogical science, and the methodological heritage of Alash figures was analyzed. The author focuses on the complexity and problems of teaching the works of the great writer M. Auezov in higher education. New conclusions were drawn about the specificity and importance of starting the teaching of the works of the great writer in higher education with the use of new technologies from his fiction. The author speaks about the pedagogical contribution of M. Auezov to the science of literary criticism and methods of teaching literature. Considers ways to analyze the effectiveness of teaching the works of the writer in higher education. Provides a scientific study of the types of work that are effectively organized in the process of literary analysis. In the analysis of Auezov's works it is recommended to refer to the image system of the work of art, the types of analysis in revealing the characters. The search for M. Auezov's legacy and scientific works in innovative methods of teaching, the use of innovative teaching technologies is a modern requirement. Emphasizes the importance of fiction, our national values in the modern information society. Analytical work is offered in order to awaken students' ability to read and express their views on the work of art in modern society. During the study of the author's story "Karash-Karash okigasy" are analyzed the tasks that effectively lead students to cognitive work, the solution of the problem. The author offers an effective way of presenting the situation in the process of problem-based learning.&nbsp; The views, analyzes and conclusions of&nbsp; M. Auezov's artistic narrative are clearly reflected in the new methodology of autonomy in the field of modern methodology. He also concludes that the writer's legacy will last for centuries, and it is the duty of every teacher to pass it on to the younger generation. Key words: writer; innovative technology; teaching; methodology; story; literary analysis; literary text; methods.
University statute of 1884 and the organization of educational daily routine at the Kazan University at the turn of 19th and 20th centuries

The article considers the influence of the University Statute of 1884 on the organization of everyday learning at Kazan University in the late 19th – early 20th centuries. The Statute of 1884 and additional acts to it required university teachers to coordinate with the Ministry of Public Education all issues related to the educational process, up to the distribution of classrooms. However, complex bureaucratic approval procedures, coupled with the specific conditions for the existence of a given institution of higher education, often led to a violation of the daily routine of classes. At the beginning of the XXth century this led to the return of some norms of the organization of everyday learning during the period of the Statute of 1863, although the charter of 1884 was not officially repealed.
Location-aware IT system security using IoT in multizone

In general, GPS receivers cannot be used for indoor settings and multizone infrastructure needs to be configured to create secure zones. Since a user may have different working roles in different zones, therefore, we are proposing here a solution for fixed IT infrastructure using IoT devices, sensors, and IoT cloud services to create a technology-agnostic secure zone in home/business/industry where sensing of natural parameters like location, temperature, pressure, light, images, sound, etc. are used to create a unique hash of a zone. AWS IoT greengrass core device coordinates with all IoT devices/sensors and creates the hash of a zone. MAC address is hashed using zone hash and a unique token for the PC is generated. All PC tokens are mapped with zone ID into the IT system deployed in the cloud and AWS IoT greengrass core device deployed in home/business/industry. This token and biometric a user needs to share during login to decide allowed roles for a user in that zone.
Design and Implementation of a Virtual Machine for a Dynamic Object-Oriented Programming Language

Over the last years, dynamic, interpreted and JIT-compiled programming languages have become a primary choice for fields such as web development, data science, and artificial intelligence. The primary concept of these language interpreters is that they usually generate a set of machine code-like instructions (often called “bytecode”) instead of directly generating machine code for the targeted platform. This does not only allow programmers to follow program execution instantly but also to develop and deploy applications more efficiently, often in combination with agile practices. Their first simple functional prototypes are usually implemented in another high-level language such as Python, Java, or JavaScript due to larger flexibility for implementing algorithms and the language grammar and later converted to a low-level system language such as C or C++ with special emphasis on memory management and bytecode optimizations. This paper presents some of the common examples, approaches, and algorithms for implementing such systems with sufficient or acceptable portability and efficiency, and also describes the design and implementation of Stella, a simple, yet powerful and user-friendly dynamic programming language designed to provide an optimal infrastructure for scalable and safe object-oriented design.
PAS: Privacy Algorithms in Systems

Today we face an explosion of data generation, ranging from health monitoring to national security infrastructure systems. More and more systems are connected to the Internet that collects data at regular time intervals. These systems share data and use machine learning methods for intelligent decisions, which resulted in numerous real-world applications (e.g., autonomous vehicles, recommendation systems, and heart-rate monitoring) that have benefited from it. However, these approaches are prone to identity thief and other privacy related cyber-security attacks. So, how can data privacy be protected efficiently in these scenarios? More dedicated efforts are needed to propose the integration of privacy techniques into existing systems and develop more advanced privacy techniques to address the complex challenges of multi-system connectivity and data fusion. Therefore, we have introduced Privacy Algorithms in Systems (PAS) at CIKM which provides a venue to gather academic researchers and industry researchers/practitioners to present their research in an effort to advance the frontier of this critical direction of privacy algorithms in systems.
An Analysis of Online Research Guides for Wine, Enology, and Viticulture

This study analyzes online library research guides covering wine research, enology, and viticulture in order to determine those resources librarians promote and recommend to users. The analysis, conducted in April 2022, includes the number and specific titles of databases, periodicals, books, websites, organizations and associations, and multimedia content found in the guides. Librarians involved in collection development can use these suggested resources when acquiring new materials. In addition, reference and instruction librarians can use the data to assist library users and recommend possible resources.
A study on oettan-seongbun of North Korean grammar

본 연구에서는 ‘외딴성분’이라는 북한 문법의 독자적인 문법 부류에 대해 그 일반론과 ‘외딴성분’에 속하는 개별적인 문장성분, ‘부름말, 느낌말, 끼움말, 이음말, 보임말’에 대해 살펴보았다. 먼저 ‘외딴성분’ 일반론과 관련된 북한 문법의 쟁점 두 가지를 선정하여 그 내용을 소개하고 논평하였다. 첫째, 소위 ‘외딴성분’에 문장성분의 지위를 부여할 수 있는가? 둘째, ‘외딴성분’이 ‘맞물린성분’과 구별되는 차이점은 무엇인가? 다음으로 ‘외딴성분’에 속하는 개별적인 문장성분인 ‘부름말, 느낌말, 끼움말, 이음말, 보임말’의 기술에 대해 살펴보았다. 각 문장성분의 특징적인 설명부분만 제시하면 다음과 같다. ‘부름말’에서는 입말과 글말에서 부름말의 의미·기능, 표현, 위치가 다르게 나타남을 보였으며, ‘부름받는말’, ‘부름말부’라는 연계되는 단위를 설정하였다. ‘느낌말’에서는 감동사와 더불어 느낌말을 이루는 주된 품사로 ‘상징사’라는 새로운 개념어를 제시하였으며, 의문대명사 ‘뭐’와 요구의 의미를 갖는 일부 명사도 느낌말로 사용됨을 보였다. ‘끼움말’에서는 표현 양상이 다양하게 나타나는 끼움말의 특성이 공통적으로 언급되며, 굳어진 단어결합과 같은 끼움말의 표현 형식에 대해 자세히 설명한다. ‘이음말’의 경우, 끼움말과 이음말 구별의 모호함을 비판하면서 이음말을 별도의 문장성분으로 설정하지 않는 입장도 나타난다. ‘보임말’의 경우, 다른 외딴성분과 달리 보임받는말을 통해 다른 문장성분과 간접적으로 맞물림관계를 맺는다는 특성이 제시되었다. This study examines the general theory of the original grammatical class of North Korean grammar called oettan-seongbun (isolated constituent) as well as the individual sentence constituents belonging to the oettan-seongbun, ‘buleum-mal, neukkim-mal, kkium-mal, ieum-mal, and boim-mal’. First, two issues of North Korean grammar related to the general theory of oettan-seongbun were selected, and their contents were both introduced and commented on. First, could the oettan-seongbun be given the status of a sentence constituent? Second, what is the difference between oettan-seongbun and manmullin-seongbun(correlated constituent)? Next, the descriptions of the individual sentence constituents belonging to the oettan-seongbun, such as ‘buleum-mal, neukkim-mal, kkium-mal, ieum-mal, and boim-mal’, were examined. Characteristic explanations for each sentence constituent are as follows. In ‘buleum-mal’, it was revealed that the meaning, function, expression, and position of buleum-mal appeared differently in oral and written speech, and related units such as ‘buleum-badneun-mal’ and ‘buleum-mal-bu’ were established. In ‘neukkim-mal’, a novel concept word ‘sang-jing-sa’ was presented as the main part-of-speech constituting neukkim-mal along with interjection, and it was shown that the interrogative pronoun ‘what’ and some nouns with the meaning of the demand are also used as neukkim-mal. In ‘kkium-mal’, the characteristics of kkium-mal, which exhibit various expression forms, are commonly mentioned, and the form of expressions of kkium-mal, such as idiomatic word combinations, are explained in detail. In the case of ‘ieum-mal’, there is a position which does not set ieum-mal as another sentence constituent, criticizing the ambiguity of the distinction between kkium-mal and ieum-mal. In the case of ‘boim-mal’, unlike other oettan-seongbun, the characteristic wherein boim-mal indirectly establishes a correlated relationship with other sentence constituent through the boim-badneun-mal is suggested.
Results Comparison of Applying Object Detection and Object Segmentation Methods on Visual Surveillance Dataset

Visual surveillance aims to detect foreground objects stably under diverse variations caused by weather changes. Traditional visual surveillance algorithms are based on a statistical analysis of pixel variations along the spatio-temporal domain. Recently, deep learning-based algorithms have improved performance compared to conventional algorithms. In this paper, we investigate the performance of object detection and semantic segmentation algorithms on visual surveillance datasets. We use the CDnet dataset, which is widely used in visual surveillance. We adjust labels in the CDnet dataset to be suitable for object detection and semantic segmentation. We investigate the possibility of object detection and semantic segmentation in visual surveillance. Two types of algorithms based on CNN and transformer are used in experiments. Experimental results show that spatio-temporal processing is required to improve performance when we apply object detection and semantic segmentation in visual surveillance.
Semantic Image Segmentation-Based Safe Landing Point Determination Method for VTOL UAVs

This paper presents a safe landing point determination method for vertical take-off and landing (VTOL) unmanned aerial vehicles (UAVs) with a downward-looking camera. The semantic image segmentation method was applied to determine whether the VTOL UAV could land safely at the designated landing site during the final stage of landing. A deep neural network with a U-Net structure was constructed for the semantic image segmentation, and a deep neural network was trained to recognize the landing site and any obstacles. The dataset used for training the deep neural network was collected through efficient labeling rules. The deep neural network of the U-Net structure outputs the area of the landing field and the area of the obstacle in units of pixels. Based on this output data, the area occupied by the obstacle in the area of the landing site is calculated to determine whether to land. Finally, the performance of the safe landing point determination method was verified using a landing pad image taken from the downward-looking camera.
Research on the Teaching Reform of "Analog Electronic Technology"

Analog electronic technology is a professional compulsory course of electronic information, automation, electrical engineering and automation in our school, and it is also one of the core courses, with its own system and strong practice. A large number of engineering cases are introduced into the teaching content, an innovative practical training mode is adopted, the integration of theory and practice is emphasized, and the practical characteristics of the teaching content are fully reflected through the teaching mode of "learning by doing" and "learning to do".
On the inverse identification of wood elastic properties using a DIC-based FEMU approach

Purpose This work aims to identify the linear elastic orthotropic material paramters of Pinus pinaster Ait. wood, using full-field measurements and an inverse identification strategy based on the finite element (FE) method updating technique. Design/methodology/approach Compression tests are carried out under uniaxial and quasi-static loading conditions on wood specimens oriented on the radial-tangential (RT) plane, with different grain orientations. Full-field displacements and strains are measured using digital image correlation (DIC), which are then used as a reference in the identification procedure. A FE model is implemented assuming plane stress conditions, where wood is modelled as an orthotropic homogeneous material. Based on the numerical results, a synthetic image reconstruction scheme is implemented to synthetically deform the reference experimental image, which is then processed by DIC and further compared to the experimental results. Findings The results for both approaches were similar when both specimen configurations were used in a single run. However, when using the DIC-based FEMU approach with the on-axis configuration, the identified modulus of elasticity in the tangential direction and shear modulus are closer to the reference values. Originality/value This approach ensures a fair comparison between both sets of data since the full-field strain maps are obtained through the same filter and therefore have the same strain formulation, spatial resolution and data filtering. Firstly, the identification is performed using a single configuration, either the on-axis or the off-axis specimen. Secondly, the identification is carried out by merging data from both on-axis and off-axis configurations.
Enabling Reproducibility in Group Recommender Systems

Reproducibility is a challenging aspect that considerably affects the quality of most scientific papers. To deal with this, many open frameworks allow to build, test, and benchmark recommender systems for single users. Group recommender systems involve additional tasks w.r.t. those for single users, such as the identification of the groups, or their modeling. While this clearly amplifies the possible reproducibility issues, to date, no framework to benchmark group recommender systems exists. In this work, we enable reproducibility in group recommender systems by extending the LibRec library, which stands out as one of the richest, with more than 70 different recommender algorithms, good performance and several evaluation metrics. Specifically, we include several approaches for all the stages of group recommender systems: group formation, group modeling strategies, and evaluation. To validate our framework, we consider a use-case that compares several group building, recommendation, and group modeling approaches.
Drake or Hen? Machine Learning for Gender Identification on Twitter

Social media offers an invaluable wealth of data to understand what is taking place in our society. However, the use of social media data to understand phenomena occurring in populations is difficult because the data we obtain is not representative and the tools which we use to analyze this data introduce hidden biases on characteristics such as gender or age. For instance, in France in 2021 women represent 51.6% of the population [1] whereas on Twitter they represent only 33.5% of the french users [2]. With such a difference between social networks user demographics and real population, detecting the gender or the age before going into a deeper analysis becomes a priority. In this paper we provide the results of an ongoing work on a comparative study between three different methods to estimate gender. Based on the results of the comparative study, we evaluate future work avenues.
Contextual TV Show Recommendation

Recommender systems are a form of artificial intelligence that is used to suggest items to users of digital platforms. They use large data sets to infer models of users’ behavior and preferences in order to recommend items that the user may be interested in. Following the trend imposed by digital media companies and willing to adapt to the media consumption habits of their customers, TV broadcasters are starting to realize the potential of recommender systems to personalize the access to their online catalog. By understanding what viewers are watching and what they might like, TV broadcasters can improve the quality of their programming, increase viewership, and attract new viewers. In this work, we analyze one specific group of users that TV broadcasters must take into account when creating a recommender system: non-logged users. In this scenario the challenge is to use contextual information about the interaction in order to predict recommendations, as it is not feasible to use any kind of information about the user. We propose a method to leverage data from other type of users (logged users and identified devices) by using Graph Convolutional Networks in order to come up with a more accurate recommender system for unidentified users.