Reviewerly/exHarmony huggingface dataset:
Living Lab Evaluation for Life and Social Sciences Search Platforms - LiLAS at CLEF 2021

Meta-evaluation studies of system performances in controlled offline evaluation campaigns, like TREC and CLEF, show a need for innovation in evaluating IR-systems. The field of academic search is no exception to this. This might be related to the fact that relevance in academic search is multi-layered and therefore the aspect of user-centric evaluation is becoming more and more important. The Living Labs for Academic Search (LiLAS) lab aims to strengthen the concept of user-centric living labs for the domain of academic search by allowing participants to evaluate their retrieval approaches in two real-world academic search systems from the life sciences and the social sciences. To this end, we provide participants with metadata on the systems’ content as well as candidate lists with the task to rank the most relevant candidate to the top. Using the STELLA-infrastructure, we allow participants to easily integrate their approaches into the real-world systems and provide the possibility to compare different approaches at the same time.
BUILD KNOWLEDGE GRAPH FROM HETEROGENEOUS DOCUMENTS

Knowledge Graphs are applied in many fields such as search engines, semantic analysis, and question answering in recent years. However, there are many obstacles for building knowledge graphs as methodologies, data and tools. This paper introduces a novel methodology to build knowledge graph from heterogeneous documents. We use the methodologies of Natural Language Processing and deep learning to build this graph. The knowledge graph can use in Question answering systems and Information retrieval especially in Computing domain
Functional configuration of intelligent system: serial data scaling in its paths

Problems of architectural and functional construction and a heterogeneous network structure of intelligent control system of technological and industrious assignment have been considered. Complex research of the intelligent system is based on the modern paradigm of convergence of technical, algorithmic and software solutions. The concept of convergence of system solutions in the technology of construction of intelligent systems presupposes digitizing of physical values at sensor measurements, as well as uniform depiction and successive conversion of values of each controlled parameter with a certain set of scales. For solution of this task a functionally full set of scales; natural values of measured physical parameters; results of sensor conversions of physical values; results of parameters measurement in the format of integer valued binary codes; parameter values in the format of real scaled binary numbers were proposed. Unified algorithms of digitizing results of direct measurements of continuous parameters and their representation in the format of ρ-bit integer valued binary codes, as well as conversions of measured parameters in the format of real scaled binary numbers and their depiction in the scale of natural values of physical parameters were built with this set of scales. Operations with digitized physical parameters were specified in tracts of the intelligent system: calibration of results of indirect measurements; digitizing of discrete sensor signals; digital filtration of measurement results; adjustment of measuring tracts; intellect control of executive mechanisms. The consequence of application of convergence provisions is similarity of morphological construction, as well as schematic uniformity of implementation of information processes and cycles of control in the systems. The results of analysis of the functional construction of the intelligent system may be used, for example, for construction of hybrid systems of industrial automation.
HPAI consumer shopping analysis using Apriori algorithm

Abstract PT Herba Penawar Alwahida sells a variety of herbal products. The process of buying and selling transactions occur every day, resulting in a pile of data pretty much. However, so far the transaction data has only been used as material to make monthly reports without further use of data these, even though from these data information can be extracted to support marketing. To utilize existing transaction data, the authors make a website-based data mining application. This application will be developed by method association (Association Rule) uses apriori algorithm. So that it can be seen the level of accuracy of this application. With the application of data mining, is expected to help the distributor to get information about which HPAI products are often purchased by consumers simultaneously, so as to improve the product marketing and maintaining process availability of stock of these products to remain.
Webinar as a Basis for the Development of Digital Competence of a Teachers of SVE

The article is devoted to summarize the experience of conducting webinars in the context of the coronavirus pandemic. The article considers the aspect of remote interaction with teachers and the transition to information platforms, distance learning. The goal is to determine the role of information technologies in the vocational secondary education in modern conditions. Research methods. The article presents the experience of organizing webinars for teachers of secondary vocational schools. Webinars were held for educational institutions of vocational secondary education. The following methods were used: quantitative and qualitative analysis. Discussion of the results. The analysis of the survey results showed that in the conditions of distance learning, the webinars held aroused interest. The conducted webinars on digital competence of teachers of vocational secondary education allowed to determine the impact of the digital educational space on their professional development and to identify the level of their readiness to participate in didactic communications using digital technologies. The institute sees the task in the organization and common approaches to the creation and implementation of distance learning technologies in the educational process in order to train highly qualified specialists with self-education skills that will allow them to independently develop and improve their competence and maintain professional mobility. In conclusion it is formulated about the organization and conduct of educational webinars for teachers of secondary vocational education in the region.
Two Conflicting Aspects of Digital Health Technology: Public Safety and Individual Rights*

It is widely thought that digital health technology will promote more informed decision-making and thereby improve patients’ health. Additionally, this technology is expected to enhance the quality, accessibility, and efficiency of the public healthcare system and strengthen national industrial competitiveness. However, the widespread use of digital health technology may also have certain negative effects on medical practice and raise ethical concerns. This article illuminates some of the hidden problems and concerns with this technology. First, in distinguishing between normal and abnormal conditions, this technology may end up judging and excessively controlling the characteristics and lifestyles of individuals. Second, the collection and use of big data, upon which digital health technology is based, threatens individual privacy and autonomy. During the COVID-19 pandemic, digital health technology has been used to monitor the quarantine compliance of infected individuals, trace contacts, model the spread of the virus, and provide telemedicine to COVID-19 patients. However, this ability to identify, monitor, and trace individuals has led to invasions of privacy and social discrimination.
Development of interactive CD media on processing of continental pastry

Abstract The purpose of this research was to produce an interactive CD media on the processing of continental pastry to improve the quality of learning in continental and culinary courses. The quality of media feasibility is based on the assessment of media experts who consider the criteria “good,” with the percentage criteria earned at 77.5%. The evaluation of media experts who review the rules “excellent” has a value of 90%. This media can be considered “feasible” as it can be used for learning in terms of media and technical aspects.
Second International Workshop on Algorithmic Bias in Search and Recommendation (BIAS@ECIR2021)

Providing efficient and effective search and recommendation algorithms has been traditionally the main objective for the industrial and academic research communities. However, recent studies have shown that optimizing models through these algorithms may reinforce the existing societal biases, especially under certain circumstances (e.g., when historical users’ behavioral data is used for training). Identifying and mitigating data and algorithmic biases thus becomes a crucial aspect, ensuring that these models have a positive impact on the stakeholders involved in the search and recommendation processes. The BIAS 2021 workshop aims to collect novel contributions in this emerging field, providing a common ground for researchers and practitioners.
Prediction analysis of student interest in design learning using Naïve Bayes method

Students' interest in a field is usually seen from the grades resulting from students' learning in the classroom. This is a common thing for parents and teachers to do. In the research conducted by researchers this time is in the field of design studied by students in the classroom in one semester, namely the subjects Photoshop and CorelDraw. The grades taken are grades that include the value of theory, practical grades, assignments, and quiz assignments obtained by students in the classroom. The four grades will be calculated until they get a provision on whether or not the student graduates in the subject. These values will be studied by researchers using the Naïve Bayes method, so that it can be known how much can be said to pass in this design lesson. Researchers conducted research using Rapid Miner program, where the data will be divided into 2 parts, namely by using some existing data as learning samples and the rest as test data. The results obtained from the experiment were 146 students graduated in the field of design, and 119 students failed. This suggests the experiment using the Naïve Bayes method was successful if the experiment data was entered a lot
Developing Critical Aerospace Embedded Systems with Distributed Teams Using Agile Methodologies

This work proposes a set of complementary practices to agile methodologies, aiming at adapting them to the development of critical aerospace embedded systems by distributed teams. To identify the main gaps in this context, two approaches are used. The first one confronts the main activities required by aerospace standards for the development of critical embedded systems with a set of compiled agile practices derived from a review of the most common agile methodologies. The second one confronts the same set of compiled agile practices with the main problems of distributed development. The two approaches resulted in the identification of four gaps related to software integration, software traceability, communication management, and organizational differences. One complementary practice is then proposed for each gap. Two case studies were performed to assess the gaps and evaluate the proposed practices. Both emulate the development of critical embedded systems by distributed teams using agile methodologies. The case studies were performed with and without the use of the complementary practices. The results confirmed three of the four identified gaps and pointed to a clear contribution of the complementary practices.
Experimental study of determination of earth’s gravitational acceleration using the concept of free-fall motion and conservation of mechanical energy

Measurements of gravitational acceleration in this study use the concepts of free-fall motion and mechanical energy conservation. The purpose of this study is to compare the values of gravitational acceleration obtained from the two experiments and to determine the factors that cause deviations from the measurements of the gravitational acceleration value from free-fall motion experiments and the law of mechanical energy conservation. The research method used was a descriptive analysis of primary data in the Applied Physics Laboratory of Politeknik Negeri Bandung. The data was collected using free-fall motion equipment and the law of mechanical energy conservation. Height is the independent variable, and time is the dependent variable. The data were processed using a computer-aided device, and it is obtained the g value with the concept of free-fall and mechanical energy conservation by 9.54 m/s2 and 10.1 m/s2. The deviation of g value in the free-fall motion is caused by the presence of magnetic remanence that holds the ball from falling immediately when the time calculator was operated. The t result, which is too large, causes the value of g becomes too small. The result of g deviation in mechanical energy conservation is obtained by determining the location of the light source when the ball is in a stable condition. Meanwhile, in the real measurement, the ball moves as it passes through the light sensor, which results in a large tension force so that the sensor position moves in a higher state. The result is Δt becomes smaller than the real one so that v becomes too large. As a consequence, the value of g becomes too large.
Logical framework for hate speech detection on religion issues in Indonesia

Abstract Hate speech is a hot issue in social media era, including in Indonesia. This paper presents the concept of logical framework to analyse and detect whether the content from text in social media contains hate speech on religion issues or not. This paper use literature review to propose the logical framework for hate speech detection. We propose the text mining as a part of data mining technique that combine with sequential pattern mining to detect hate speech from social media with text data. Based on the proposed logical framework to detect hate speech from social media, it is possible and recommended to be implemented in the future research to prevent hate speech distribution which can cause disunity and commotion in the community.
Digital Support of Forensic Laboratories under Optimized Block Chain Network

It very essential that significant information is put away in a protected manner and it is measure safely. Touchy data should be sealed as more opportunities to get changed deliberately. Such, instructive information can be introduced in any configuration like picture, sound or video. For scientific confirmations, there is an incredible danger that the vindictive individuals will transform it. The criminological report created from pathology lab cross through the lab to specialist, specialist to police dept. and from that point to court by and large. To make this stream extremely straightforward and to keep up the unchanging nature of measurable report, Block chain innovation is taken into consideration. Block chain gives the medium to complete the exchange and it completely made sure about the straightforward climate. This paper proposes a protected criminological proof framework by utilizing the block chain stages. Ethereal stage is utilized to execute the framework. The utilization of block chain information structure to store the legal proof accomplishes the properties. For example, genuineness, straightforwardness and security. The proposed framework accomplishes unchanging nature and detectability in legal proof framework. The prevailing origination of measurable science as an interwoven of controls fundamentally helping the criminal equity framework (for example legal sciences) is in emergency or if nothing else shows a progression of oddities and genuine constraints. Albeit required, yet saw as the answer for these disadvantages, the nearly summed up reception of stricter plans of action in criminological science casework compounded with ever-expanding regulating and consistence measures not just spot extra weights on a control that as of now shows up in trouble, yet additionally instigate more discontinuity of the distinctive scientific science assignments, a fundamental ordinarily reviled by similar NAS report and other comparative audits.
Design of Text and Voice Machine Translation Tool for Presentations

In this paper, a machine translation tool for presentations was presented. This virtual translation tool is a novel approach for generating text or voice in other languages. The proposed system is expected to assists audiences in understanding foreign language content in the live presentations. In this study, the conventional translator was taken over by neural machine translation and human-machine interaction was improved significantly by using text to speech and speech recognition. Experimental results in Vietnamese-English pair showed the effectiveness of the proposed system design and deployment approach.
Detecting Systematic Anomalies Affecting Systems When Inputs Are Stationary Time Series

We develop an anomaly-detection method when systematic anomalies, possibly statistically very similar to genuine inputs, are affecting control systems at the input and/or output stages. The method allows anomaly-free inputs (i.e., those before contamination) to originate from a wide class of random sequences, thus opening up possibilities for diverse applications. To illustrate how the method works on data, and how to interpret its results and make decisions, we analyze several actual time series, which are originally non-stationary but in the process of analysis are converted into stationary. As a further illustration, we provide a controlled experiment with anomaly-free inputs following an ARMA time series model under various contamination scenarios.
The Use of Theory of Linear Mixed-Effects Models to Detect Fraudulent Erasures at an Aggregate Level

Wollack et al. (2015) suggested the erasure detection index (EDI) for detecting fraudulent erasures for individual examinees. Wollack and Eckerly (2017) and Sinharay (2018) extended the index of Wollack et al. (2015) to suggest three EDIs for detecting fraudulent erasures at the aggregate or group level. This article follows up on the research of Wollack and Eckerly (2017) and Sinharay (2018) and suggests a new aggregate-level EDI by incorporating the empirical best linear unbiased predictor from the literature of linear mixed-effects models (e.g., McCulloch et al., 2008). A simulation study shows that the new EDI has larger power than the indices of Wollack and Eckerly (2017) and Sinharay (2018). In addition, the new index has satisfactory Type I error rates. A real data example is also included.
Application of Artifi cial Intelligence Systems in Education in China and Japan

In the era of development of information technology and computing technology, the development and application of artificial intelligence (AI) technologies, computer technology, which is designed to perform specialized tasks and expand human capabilities in the field of machine learning, are relevant and debatable. This article provides an overview of the development of AI in Asian countries such as China and Japan. The countries under consideration are among the leading countries and their experience in AI can serve as a basis for other AI developers to develop new technologies based on existing developments. A number of approaches of the Japanese and Chinese communities to the development of artificial intelligence, including startups, are considered. Ideas and requirements for the development of educational systems using AI from corporations, regulatory bodies and their government programs, associations and AI developers are given. The article provides a comparative analysis of two Asian countries based on their priorities and approaches that affect the speed of development of new technologies in the field of AI.
Analysis of Markov Jump Processes under Terminal Constraints

Abstract Many probabilistic inference problems such as stochastic filtering or the computation of rare event probabilities require model analysis under initial and terminal constraints. We propose a solution to this bridging problem for the widely used class of population-structured Markov jump processes. The method is based on a state-space lumping scheme that aggregates states in a grid structure. The resulting approximate bridging distribution is used to iteratively refine relevant and truncate irrelevant parts of the state-space. This way, the algorithm learns a well-justified finite-state projection yielding guaranteed lower bounds for the system behavior under endpoint constraints. We demonstrate the method’s applicability to a wide range of problems such as Bayesian inference and the analysis of rare events.
RAPID: An Algorithm for Quick Replanning Under Changed Dynamical Constraints

There are many scenarios where the dynamical constraints of a vehicle may change mid-mission either due to added payload, vehicle damage or changes to the environment. The vehicle may need to come back to the base safely without undergoing collisions with obstacles. We present RAPID (RApid Planning for Interchanged Dynamics), a sampling based motion planning algorithm for quick replanning when the dynamical constraints associated with a vehicle change. RAPID uses the planning information associated with the original dynamics as a heuristic for quick replanning. RAPID is useful when a vehicle must replan to account for changes to its dynamics but does not have enough time or resources to run a whole planning algorithm (like RRT or SST) from scratch. We compare RAPID with brute-force replan using RRT and SST using a combination of hardware and software experiments. The hardware experiments are performed using a modified Parrot Bebop 2 quadrotor fitted with an Intel UP board traversing an obstacle course. Our experimental results demonstrate RAPID provides considerable improvements over planning from scratch (RRT, SST) in solution completion time, path length, and flight time performance metrics.
시뮬레이션을 활용한 LGBT 간호 교육의 효과

Purpose: As health care needs for Lesbian, Gay, Bisexual and Transgender (LGBT) are becoming increasingly important, it has become imperative for the nurses to be attentive towards their health problems and provide nursing care with an open-minded attitude. Due to limited opportunity to provide direct nursing care to LGBT patients, it is hypothesized that simulation would provide good opportunity for students to experience LGBT nursing care in a safe environment. This study was conducted to develop and apply simulation of LGBT nursing care to ultimately provide unbiased nursing care for LGBT population and prepare basic data for LGBT nursing education.Methods: This study was a single-group pre-post experimental design study for 57 senior nursing students based on the comparison of existing LGBT knowledge, general attitude towards LGBT, and nursing attitude towards LGBT before and after simulation. The scenario content included discussion of coming out issue, providing sexual health information, and supportive nursing care for LGBT population. Data were analyzed with descriptive statistics and Wilcoxon signed rank.Results: Simulation education-led to a significant increase in LGBT knowledge and nursing attitude. However, there was no change in the general attitude towards LGBT.Conclusion: The results of this study suggest that LGBT education using simulation may be effective for nursing students and nurses from the point of concern for LGBT population. It is hypothesized that future LGBT educational programs might need more detailed information from both care recipients and nurses. Finally, LGBT education needs to be included in the nursing education curriculum.