Reviewerly/exHarmony huggingface dataset:
Axiomatic Thinking in Neural IR: An axiomatic approach to diagnosing deep IR models

After surpassing human performance in the fields of Computer Vision, Speech Recognition and NLP, deep learning has been gaining scientific ground in IR. In spite of the sheer amount of publications that have proposed so-called neural IR approaches over the past decade, the field has not achieved the kind of progress seen in related fields. Over the past year or so, works have begun to solve the issues that complicate the progress of neural applications in IR. Among those issues we can find the lack of approaches to interpret and analyze neural IR models, which is addressed in this thesis. We propose a novel approach to diagnose retrieval models that is rooted in the axiomatic approach to IR. Axioms encapsulate search heuristics that are expressed as constraints on retrieval functions. Existing axiomatic approaches have provided fruitful analyses of traditional IR models but are no longer viable to study neural IR models. Building forth on these approaches, we propose a novel approach to empirically analyze retrieval functions, suitable for neural models. Based on inspirations from the NLP and Computer Vision communities, we use model-agnostic diagnostic datasets in order to determine what kind of search heuristics models are able to learn. Since the creation of diagnostic datasets does not require a labeled dataset, we can apply the proposed pipeline to almost any dataset containing queries and documents. We have shown for four specific axioms how to extend and relax them, in order to make them fit for obtaining diagnostic datasets. We have applied our diagnostic dataset creation pipeline to the WikiPassageQA and MSMarco corpora and evaluated three traditional baselines and six neural models. Our experiments on the WikiPassageQA dataset show that the proposed approach can indeed diagnose strengths and weaknesses of neural models. However, our experiments on the MSMarco dataset show that an axiomatic analysis based on the four axioms does not always diagnose factors that incur retrieval effectiveness. An interesting direction for future work is therefore to include more axioms in the diagnostic approach. As possible extensions of the work carried out in this thesis, several roads of future work have been proposed. Among them, we can find reproducing experiments on other neural toolkits and employing the methodology on different IR tasks, but also researching the validity of axioms and adopting a specialized metric for axiomatic performance. We furthermore identified various opportunities to use diagnostic datasets beyond diagnosing neural models. Concluding, we believe that the axiomatic approach to diagnosing neural IR models presented in this work is a step forward to gaining valuable insights into the black boxes that deep models are generally considered to be. We hope our work may prove a fruitful resource for analysis in the field of neural IR on the road towards achieving superior performance without losing sight of a better fundamental understanding of IR.
Retraction notice: Iterative noise attenuation and deconvolution with a sparse constraint

In order to reveal mining pressure in the workface using a gangue backfilling method and a caving method in Pingdingshan No. 12 coal mine, this paper establishes a numerical analysis model for different advance lengths of workface based on geological conditions.By the analysis of numerical models and field measurements, the following conclusions about mining pressure behavior in the mixed workface were drawn.(1) As the mixing face advances, its goaf is continuously compacted.Therefore, the vertical stress in the roof of the mixed workface increases gradually.(2) Because the gangue has a certain supporting effect on the roof, the peak value of abutment stress in the gangue backfilling section is less than that in the caving section, while the roof vertical stress in the goaf of the backfilling section is greater than in that of the caving section.(3) Because roof break and movement are different in the gangue backfilling section and caving section of the mixed workface, a sudden increase of vertical stress in the transition section appears.(4) Through the analysis of the working resistance of the hydraulic support and the advance stress of the coal wall in the mixed workface, the supporting role of gangue for the goaf roof and the abrupt increase of vertical stress in the transition section are verified.(5) The mining pressure of the mixed workface shows that the mining management of the caving and transition sections should be strengthened.
Mot en grönare e-handel? : En studie över hur Sveriges största e-handelsplatser applicerar CSR i sin informationsarkitektur

This bachelor study aims to investigate in what extent, and how, the biggest e-commerces in Sweden applies CSR (Corporate Social Responsibility) related content in the information architecture on t ...
Instance-based classification using prototypes generated from large noisy and streaming datasets

Nowadays, large volumes of training data are available from various data sources and streaming environments. Instance-based classifiers perform adequately when they use only a small subset of such datasets. Larger data volumes introduce high computational cost that prohibits the timely execution of the classification process. Conventional prototype selection and generation algorithms are also inappropriate for data streams and large datasets. In the past, we proposed prototype generation algorithms that maintain a dynamic set of prototypes and are appropriate for such types of data. Dynamic because existing prototypes may be updated, or new prototypes may be appended to the set of prototypes in the course of processing. Still, repetitive generation of new prototypes may result to forming unpredictably large sets of prototypes. In this paper, we propose a new variation of our algorithm that maintains the prototypes in a convenient and manageable way. This is achieved by removing the weakest prototype when a new prototype is generated. The new algorithm has been tested on several datasets. The experimental results reveal that it is as accurate as its predecessor, yet it is more efficient and noise tolerant.
Learning from Sparse and Deficient Data and its Applications

Author(s): Li, Ruirui | Advisor(s): Wang, Wei | Abstract: Deep learning models have been attracting substantial attention in the last few years as they successfully demonstrated remarkable performance on different tasks (e.g., classification and ranking) in various fields. The success of most deep learning models significantly depends on massive training data as these models inherently work by memorizing or distinguishing massive training instances in the data. However, such a huge amount of training data may not be available or accessible all the time due to privacy issues, user experience concerns, or corporation constraints, etc. This leads to the data deficiency issue, which corresponds to the scenarios where we have just a few training instances to accomplish a task. Even though sufficient training data could be acquired, sometimes the data could be very sparse due to the large base of elements (e.g. users and items) in the dataset. This results in the data sparsity issue, which corresponds to the scenarios where we have very limited training instances to pinpoint the characteristics of each element in the data. Both the data deficiency and data sparsity issues limit the expressiveness of strong model capacities of the deep learning models and generally lead to inferior performances on a variety of tasks.In this dissertation, we propose several deep learning frameworks to compensate for the data deficiency and data sparsity in the context of three concrete applications, i.e., customer recommendation in location-based social networks, query recommendation in search engines, and automatic speaker recognition. The methodologies presented in these frameworks span different research areas, including geographical influence modeling on location data, automatic data augmentation via adversarial training, comprehensive instance utilization through metric-learning-based few-shot learning, and knowledge transfer via gradient-based meta-learning. As a result, these methodologies not only tackle specific challenges in the applications mentioned above but also shed light on other relevant applications.
A Delphi Study On Online Qurâ€™Änic Themes

Thematic interpretations of al-Qurâ€™Än (TIaQ) has a sensitivity due to the interrelation of Qurâ€™Änic verses/ verse with each other. The purpose of this research was to extract the online Qurâ€™Änic search engines (OQSE) and investigate the existing thematic interpretations of al-Qurâ€™Än (TIaQ) based on the alignment with their relevant verses. The OQSEs provide the list of themes and the aligned verses theme and the aligned rhyme in their websites. The ambiguous thematic search engines have the possibility to mislead the user by retrieving nonaligned verses against a certain subject/theme (query) or the user may not fully understand the interpretations due to the incomplete results. The extracting of themes/topic and the aligned verses have been conducted using Cranfieldâ€™s Index Device method. Then a two-round Delphi method has been applied to justify the existing themes and the aligned verses by 20 experts of Qurâ€™Änic discipline. There are 240 themes and 400 verses have been extracted and categorized into 40 thematic groups (TG). The expertsâ€™ justification through Delphi method has revealed that the accuracy of ordinated thematic groups in OQSE is 40% (16/40) only and the accuracy of the ordination of the themes and the verses achieved 35.41% (85/240). Despite the significant outcome of this research, the limitation recommends that further research should be conducted extracting more themes and aligned verses from OQSEs. Instead of 20 experts in Delphi, future research can concentrate on a big number of experts to investigate all the thematic verses of entire Qurâ€™Än.&#x0D; Keywordsâ€”Delphi; Thematic interpretation; Tafseer; Qurâ€™Änic search, Qurâ€™anic theme
PROBLEMS OF ENSURING THE SAFETY OF THE DOCUMENTS OF DEPARTMENTAL ARCHIVES IN THE ARKHANGELSK PROVINCE IN 1917–1922

The article attempts to examine the history of the archival service in the Arkhangelsk province from the point of view of the approach of the Soviet authorities to ensure the safety of documents of the departments and organizations that existed on the territory of the province before the revolution of 1917. The events described in the article have not previously received their coverage on the pages of scientific and popular publications, as related documents have not yet been introduced into scientific circulation. The period of study was characterized by the great social upheaval, the consequences of which could not but affect the safety of the old archives. For the representatives of the new local administration, as well as for the majority of the population, such archives did not represent any practical or cultural and historical significance, and that fact left an imprint on the way the SNK decrees on archives administration were executed. In fact, it was only in 1920 that the issue started being resolved, when the Soviet power was re-established in the provincial center. In the conditions of the post-war devastation, the questions of the administration of the provincial archival fund were accomplished on the residual principle, there were neither personnel, nor the rooms suitable in size for archival storage. V. Ivanovsky, the only person, who was entrusted with the duties of preserving the documentary heritage of the region, became the ancestor of the archival service of the Arkhangelsk province.
IMPLEMENTASI ALGORITMA SPRITZ DAN SPREAD SPECTRUM UNTUK MENYEMBUYIKAN PESAN ENKRIPSI KEDALAM FILE AUDIO MP3

Optimizing the security of confidential text messages is very important to protect the contents of messages from those who want to use or damage the message. The use of cryptographic techniques in securing data can still raise suspicion of the message that has been secured. This study explores how to use steganography techniques to coat encrypted message security based on steganography techniques. The spritz algorithm is a cryptographic algorithm that is used to obtain the cipher from the original message, while the spread spectrum method is a method used to hide the original data password into an image. Based on testing done by combining these two techniques, it is quite reliable to optimize the security of secret messages because others cannot see the existence of the cipher of the original data in plain sight.Keywords: Cryptography, Steganography, Spritz, Spread Spectrum, mp3
THE CONDITIONS OF INNOVATIVE CLIMATE FORMATION IN HIGHER EDUCATION

The article is devoted to the theoretical and methodological analysis of the formation of innovative climate in higher education. Internal and external factors influencing this process are analyzed. The article considers the hierarchy of the components of IHE (“education” – “science” – “production of innovations”) as its innovative potential.
Standby Redundancy Optimization of Multi-Level Systems

This paper deals with an redundancy allocation problem to improve the system reliability in the multi-level systems with serial structures. We consider cold-standby structure for redundancy and assume that the switching devices are imperfect. Under the design cost constraints, the optimal redundant units and numbers are selected to maximize the system reliability. We use the standard genetic algorithm to obtain the optimal redundant units and numbers. In numerical studies, the effects of model parameters under some cost constraints are investigated. Additionally, we compare the standby redundancy problem with the existing parallel redundancy problems numerically.
Chaotic Map based Privacy Preservation User Authentication Scheme for WBANs

The rapid development of wireless communication technologies provides convenient and efficient online services to make life easier. Wireless body area network (WBAN) such type of service which provides a simple and low-cost strategy for health monitoring without going to the hospital. WBAN consists of a number of sensors, which embedded into the patient's body and send the collected information to the server. However, the privacy of the patient is an essential feature as the leakage of patient's sensitive data cause threats to tampering of health. This study proposes a privacy preservation user authentication scheme (PUASW) for WBAN based on the chaotic map. The formal security analysis of the scheme has been done using ROR model. In addition, PUASW can achieve several security features and can withstand several well-known attacks. AVISPA tool is used for the formal verification of our scheme. The communicational and computational cost of the proposed scheme is less compared to other related schemes.
PENGARUH METODE PROJECT BASED LEARNING DALAM PEMBELAJARAN MENULIS TEKS EKSPOSISI

From the results of observations made by the author, one of the problems with the current Indonesian language material is that students have difficulty when recording exposition text skills due to a lack of student interest in learning as well as an understanding of the material being studied and a lack of student understanding. Therefore, this problem gets the author's special attention to conduct research with innovative learning methods. The formulation of the problem of this study is knowing the effect of the Project Based Learning method on recording exposition text? The purpose of this study is to determine the effect of the Project Based Learning method on the skills to record exposition texts, increase student creativity, and practice critical thinking. The research method used was quasi experiment with the type of nonequivalent control group design supported by descriptive qualitative. The pretest stage of pretest scores got the highest points of 70 medium 65, and the lowest points 55. After the treatment was given showed an increase in the students' Posttest score the highest score was 90, the medium value was 85, and the lowest score was 75. From the scores obtained the material noted that the text of the exposition felt more effective. That way, students can determine the structure of the exposition text and be able to overcome the problems found to be rich in understanding gained by emphasizing training themselves through complex activities, conducive classroom structuring, and the creative role of the teacher making the learning process better and feel efficient.
CURRENT RELATIONSHIP OF CZECH MATHEMATIC TEACHERS TO USE DIGITAL TECHNOLOGIES IN TEACHING

Appears in: ICERI2019 Proceedings Publication year: 2019Pages: 1334-1339ISBN: 978-84-09-14755-7ISSN: 2340-1095doi: 10.21125/iceri.2019.0401Conference name: 12th annual International Conference of Education, Research and InnovationDates: 11-13 November, 2019Location: Seville, Spain
Peningkatan Hasil Belajar Muatan Ipa Pada Tema Peduli Terhadap Makhluk Hidup Dengan Media Permainan Ular Tangga Di Kelas Iv SD Negeri Ngawu Tahun Ajaran 2018/2019

This research is motivated by the low ability of students to master material forms outsideanimals and plants as well as its function on the theme of Care for Living Creatures in class IVSDN Ngawu in 2018. Prior to the research the students' ability to master the materialespecially in the material was classically only 30% of students declared complete with anaverage of 61. Classroom action research (CAR) in this study aims to improve the ability tomaster the material so that students can be declared complete. Efforts are made to overcomethe problem is through learning by using a snake ladder game media. The research was carriedout in 2 cycles each cycle I 2x meetings and cycle II 3x meetings. The steps of implementinglearning begin with the teacher's explanation, group games, and competition. Methods of datacollection through observation, test sheets, assessment sheets and documentation. From theobservations of the results of the evaluation of learning in the research activities showed thatthe use of snakes and ladders game media can improve the ability to master the materialoutward forms of animals and plants on the theme of Caring for Living Beings of Grade IVstudents of SDN Ngawu in 2018. These results are evidenced by the increase in studentlearning outcomes in each cycle, both cycle I and cycle II. After completing the first cycle, thecompleteness level becomes 60% with an average of 73. After the improvement and reflectionin the second cycle, the completeness of learning outcomes increases to 100% with an averageof 87.Keywords: PTK, Natural Sciences, Ladder Snake
Improving the Quality of Higher Education with the Project Based Learning

The article deals with the issues of ensuring the quality of the educational process using the project based learning. The features of project based learning are determined in the article. Project based learning develops professional skills that are necessary both for the students themselves and for the employers who formulate the requests. Project based learning encourages the teacher to be aware of current industry problems and ways to solve them. Participation in project based learning programs allows students to fill their portfolios and be competitive in the labor market immediately after getting higher education.
Analytic Approach to Determine Algorithm Parameters of HS Optimization

Harmony search (HS) is a relatively recently developed meta-heuristic optimization method imitating the music improvisation process. The algorithm parameter, HMCR, play a very important role in HS. The value of HMCR must be determined differently depending on the dimensions of a problem and the number of optimum values. But there is no analytic approach to determine the parameter value and the rule of thump is applied.BRTo solve the problem, the relation between HMCR and new harmony generation is studied. As a result, new harmonies are classified into two parts of ‘diversification’ and ‘intensification’ and the generation probabilities of the two group harmonies are analysed. In this paper, HMCR, unlike the conventional method, is determined based on the DIVR which is the probability of diversification harmony.BRBy applying new method, the value of HMCR can be customized for a given optimization problem. The proposed method is applied to the test optimization functions and the results shows that the proposed method works very well.
An improved algorithm for corner extraction of checkerboard in camera calibration

In automatic camera calibration with traditional chessboard patterns, the corner sorting results are usually influenced by the rotation angle of the calibration pattern. Therefore, this paper designs an improved chessboard pattern and corresponding corner extraction algorithm. In the new pattern, five nested rings are added near the four corners to determine the sorting origin.After completing the checkerboard positioning process, the improved algorithm first identifies the nested contours by five concentric circles on the four corners of the calibration plate. Then it identifies the center of each contour and determines the order of four centers. After that it uses a perspective projection to correct part of the image on the calibration plate and reorder the calibration points in order to obtain a sequence of calibration points. Experiment results show that the corner detection results are correct and the new method has a lower mean reprojection error per image.
THE APPLICATION OF RECOMMENDER SYSTEMS TO DATA-DRIVEN DIGITAL MEMORY

Data-driven digital memory applications lack predefined navigation paths and strict hierarchical structures.They are based on large collections of memory items that can become overwhelming to users.Recommender systems can improve user experience through the proposal of personalized relevant items.However, very little academic literature has been dedicated to discussing this type of filtering of digital memory resources and the provision of customized contents to active users.In this paper, an architecture of a hybrid enhanced recommender (HER) system, which integrates collaborative filtering and content based filtering techniques and resolves most of the weaknesses of the individual approaches.This architecture also proposes an ontology to build semantic user profiles and represent memory items to mitigate the lack of semantics of traditional content-based method.Through combining those techniques, this architecture has the potential to cope with data sparsity problems, avoid overspecialization issues and partially resolve cold start problems.
GEOGRAPHY TEACHING IN PRE-PRIMARY EDUCATION

1 Constantine the Philosopher University in Nitra (SLOVAKIA)2 Matej Bel University in Banská Bystrica (SLOVAKIA)
Digital subjection Art in the Technology Trap

Artistic practices have now been dominated by an aesthetic regime that has revolutionarily transformed them, making works the result of free play - free from ethical meaning and the requirement to comply with rules - suspend the logic of perception. All norms and principles governing the production of performances, including the hierarchy of topics, have also been abolished. The images, which are subject to constant redistribution, have become part of this modified space of experience. We live in a world filled with images and understand this world through images. That is why defining the status of an image in contemporary culture, together with the dominant aesthetic strategies, may be the basis for understanding the processes taking place within it. The dynamics of technological development made visuality a prerequisite for the redefinition of the social world. Visibility is thus a political criterion, and thanks to new media the authorities can control and subjugate individuals more effectively.