Reviewerly/exHarmony huggingface dataset:
Projector Calibration Method using a Pinhole Mask Plate

In this paper, we propose a new projector calibration method. It uses only a projector, a scanner and a pinhole mask plate that can be easily prepared. In our method, pattern images are projected on the mask plate, and light rays passing through holes are captured by the scanner. By decoding scanned images, we can calibrate the projector. The mask reduces blurring of the projection even when the scanner is not in focus, so it requires only a small amount of space. Moreover, compared to conventional methods, it requires little human intervention because once the system is setup, we do not move any device after that. Therefore it guarantees an accurate calibration no matter who calibrate the projector. In the experiment, we setup the proposed system and estimated parameters.
Teacher Students’ Digital Daily Lives : Information Literacy at a Pre-school Teacher Education – A Summary

This article is a summary of the doctoral thesis “Lararstudenters digitala studievardag: informationslitteracitet vid en forskollararutbildning”, defended and published at Lund University in Februa ...
Application and evaluation of computer in Japanese teaching

With its unique charm, computers have developed rapidly in various fields of science and technology, which has led to assistant teaching in linguistics, especially human-computer interaction. Computer will implement dynamic teaching, such as online teaching, video teaching and so on, which can provide technical support for new teaching concepts. Through elaborate production of network resources and design strategies, Japanese teachers can carry out application experiments in teaching. Through continuous analysis, summary and improvement, we can draw the application strategy of computer in Japanese teaching. This paper first analyses the unique function of computer in Japanese teaching. Then, this paper puts forward some problems. Finally, some suggestions are put forward.
Detection and Recovery of Adversarial Attacks with Injected Attractors

Many machine learning adversarial attacks find adversarial samples of a victim model ${\mathcal M}$ by following the gradient of some functions, either explicitly or implicitly. To detect and recover from such attacks, we take the proactive approach that modifies those functions with the goal of misleading the attacks to some local minimals, or to some designated regions that can be easily picked up by a forensic analyzer. To achieve the goal, we propose adding a large number of artifacts, which we called $attractors$, onto the otherwise smooth function. An attractor is a point in the input space, which has a neighborhood of samples with gradients pointing toward it. We observe that decoders of watermarking schemes exhibit properties of attractors, and give a generic method that injects attractors from a watermark decoder into the victim model ${\mathcal M}$. This principled approach allows us to leverage on known watermarking schemes for scalability and robustness. Experimental studies show that our method has competitive performance. For instance, for un-targeted attacks on CIFAR-10 dataset, we can reduce the overall attack success rate of DeepFool to 1.9%, whereas known defence LID, FS and MagNet can reduce the rate to 90.8%, 98.5% and 78.5% respectively.
vi-MoCoGAN: A Variant of MoCoGAN for Video Generation of Human Hand Gestures Under Different Viewpoints

This paper presents a method for video generation under different viewpoints. The method gets inspired by MoCoGAN’s idea which modelled a video clip in two latent sub-spaces (content and motion) and achieved impressive results recently. However, MoCoGAN and most of existing methods of video generation did not take viewpoint into account so they cannot generate videos from a certain viewpoint, which is a need for data augmentation and advertisement applications. To this end, we propose to follow the idea of conditional GAN and introduce a new variable to control the generated video’s view. In addition, to keep the subject consistent during action implementation, we utilize an additional sub-network to generate the content control vector instead of using a random vector. Besides, the objective function for training the network will be modified to measure the similarity of content, action and view of the generated video with the truth one. Preliminary experiments are conducted for generating video clips of dynamic human hand gestures, showing the potential to generate videos under different viewpoints in the future.
Exploring LIS practitioner engagement with research: lessons from a UK case study

Internationally, LIS academics and professionals share a need to understand how practitioners engage withresearch. In 2013, a research team from the University of Sheffield was commissioned by the UK CILIP Library andInformation Research Group (LIRG) to conduct a Research Scan to address the question “What do LIS Practitionerswant from research?”. The team, comprising an academic and an LIS practitioner, conducted a scoping review ofcurrent literature (2010‐12), augmented by an investigation of ephemeral material.
LibGuides: ARTS 1305: Digital Studio One Foundations: Scholarly or Not?

This course guide was created for ARTS 1305 Digital Studio One students. Scholarly vs. other types of articles
Distributed Ledger und Blockchain - von Bitcoin zur Token-Ökonomie

No AccessVon Augmented Reality bis KI - Die wichtigsten IT-Themen, die Sie für Ihr Unternehmen kennen müssenMar 2020Distributed Ledger und Blockchain - von Bitcoin zur Token-ÖkonomieAndreas MitscheleAndreas MitscheleSearch for more papers by this authorhttps://doi.org/10.3139/9783446464353.003SectionsAboutPDF ToolsAdd to FavoritesDownload CitationTrack CitationsCopy LTI LinkPDF key 'share (en)' returned an object instead of string.FacebookTwitterEmailLinkedIn previous chapternext chapter FiguresReferencesRelatedDetails 2020Pages: 41-68Print ISBN: 978-3-446-45915-1eISBN: 978-3-446-46435-3 Copyright & Permissions© 2020 Carl Hanser Verlag GmbH & Co. KGPDF downloadLoading ...
The spiritual power of person’s patriotism

The article is devoted to the problem of patriotism based on the unity of its cognitive and emotional components. As a consequence, patriotism as a social phenomenon has been characterized. Moreover, patriotism has the essential indicators, which are practically manifested through personality’s behavior, action and communication. The author defines patriotism as an unconditional and highly meaningful feeling-value, which characterizes the person’s attitude towards people, homeland, state and oneself. Unconditional aspect of patriotism means that the feeling of patriotism cannot be founded on external forms of encouragements. The highly semantic aspect of patriotism is not associated with the lower, existential needs, but with the highest life determinants of personality. According to a conceptual definition of patriotism, the author proposes the basic components that serve as diagnostic signals to determine its degree of development in a particular personality. A set of regulations, based on deep psychological mechanism, is practically significant for educators in order to organize the process of developing a feeling of patriotism. As a result, they are very effective in the educational process.
Makerspaces in the High School Setting

Makerspaces, also sometimes known as fab labs or hackerspaces, are locations where students and patrons can produce, craft, solve problems, collaborate, and develop new skills (Preddy, 2013). The purpose of this study is to provide a look into the perceptions, both through text and image, of public high school students who have a maker learning space in their high school library at Monticello High School in Charlottesville, Virginia. The rationale for this research was that, by obtaining a better understanding of student perceptions and perspectives, librarians and peer researchers in the field would gain a better comprehension in how students view their makerspace. Individual one-on-one interviews with student participants were used to move toward a thematic analysis of perspectives of makerspaces in a high school library setting.
A research on extraction of meter line of steel tape image based on Gabor transformation

In order to raise the robustly of the automatic verification system of steel measuring tapes, a method on extracting the meter lines on steel measuring tapes image based on Gabor transformation is proposed in this paper. This method makes full use of the frequency and direction sensitivity of Gabor filters. Through the Gabor filtering, the particular direction and frequency line structures are filtered out. Based on these line structures, positions of the meter lines in the images can be located and an ROI with the lines in it can be created automatically. Furthermore, through the RANSAC calculation to fit the double edges in the ROI, this method is able to distinguish the broken and stain lines to improve the line detect accuracy and the robustness of the image processing system. Down sampling is used to improve the efficiency of the method. An experiment has been designed to test and verify the method. By standard steel measuring tapes and dual-frequency laser interferometer, the equivalence between pixel and the physical length can be calculated. The moving distance can be calculated with the equivalence and line marker center by the method proposed in the paper. Comparing the calculated value of moving distance with reference value of moving distance measured by dual-frequency laser interferometer, the method proposed in this paper has been proof with accuracy. With the capability of solving stain, complex background, uneven illumination problems, this method can raise the degree of automation of steel measuring tapes verification system.
TS-DBSCAN: To Detect Trajectory Anomaly for Transportation Vehicles

Deep exploration of the potential characteristics from vehicle trajectory data benefits transportation safety management and improves transport efficiency. Therefore, trajectories anomaly detection plays a pivotal role in transport enterprises. In this paper, we proposed a novel density clustering model named TS-DBSCAN to detect outliers of trajectory data, which is a DBSCAN-based method for clustering time-series data. We first analyzed the time correlation of the trajectory data of transportation vehicles. Then the distance between two adjacent timestamps is considered as the training data of DBSCAN clustering algorithm, determining the $$ \upvarepsilon $$ -neighborhood radius $$ \left( {Eps} \right) $$ and the minimum neighbor number $$ \left( {MinPts} \right) $$ according to the distance density distribution. Finally, anomaly clusters are detected from the trajectory data. We conducted experiments based on real trajectory data of transportation vehicles to evaluate the effectiveness. The experimental results show that TS-DBSCAN algorithm can detect abnormal trajectory data with both efficiency and accuracy.
HAND MOTION BASED MOUSE CURSOR CONTROL USING IMAGE PROCESSING TECHNIQUE

The various devices are used for communications between the human and the machine. These devices are keyboard, mouse, etc. for performing tasks. While the workstation technologies are developing up, the roll of Person Workstation Interaction (HCI) is also increasing rapidly. Most of the devices uses touch screen technology which cannot be affordable to all the applications. For the traditional touch screen, virtual mouse can be used as substitute way in virtual person interactive module. Motion based interaction systems are very popular at workplace and at home. This paper proposes to develop a method and model that identifies hand motions which can be used as an input command to work together with the workstation system. The motion is recognized and the action specific is performed. While developing the system using image processing, one key area is looking for the system. The method is created to recognize the motions and built in task for every motion. PyAutoGUI is providing coding system in Python and uses the OpenCV library. The purpose of real-time hand motion recognition in the real world are numerous, since it can be used almost anywhere. The technique is focused on the use of a webcam. Then it is used to develop a virtual Person Workstation Interaction Device in a cost-effective manner.
A Study on the Service Marketing Promotion Plans of Hotel Bakery and Perception on Hotel Bakery by Analyzing Unstructured Big Data

The purpose of this study to examine the promotion plans of hotel bakery and perception of hotel bakery consumer’s by unstructured big data analysis. The study used major portal sites and social networking sites Naver, Google, Daum
Digital Entrepreneurship Competencies among Students: Methodological Aspects of the Maturity Level and Development Program Making

The article highlights the methodological aspects of determining the maturity level of digital entrepreneurship competencies among students. The authors offer an approach to developing digital entrepreneurship competencies model in the form of an ordered list of four groups: entrepreneurial competencies; digital competencies; communication, interpersonal and intercultural interaction; self-development and security competencies. The authors have tested the method on a focus group of students of Nur-Sultan universities. The authors have developed a matrix of digital entrepreneurship competencies ranking, which allows the prioritization of the competencies to develop according to the criteria of importance and problematicity. The authors have determined criteria for the selection of student training methods (number of students, practice orientation, the level of expertise of trainees, the level of learning motivation and cognitive activity, the pace of academic work, material difficulty level), and has summed up the most common methods on highlighted criteria. The authors have formed the scheme of development for the student development program as a set of training methods focused on overcoming the revealed gaps of competencies. The authors have offered an algorithm of a training method selection on the basis of delivering desired results with the maximum possible coverage of trainees and the training material difficulty level.
Cryptographically Enforced Access Control in Blockchain-Based Platforms

In this paper, we took a two-stage approach to address privacy issues in blockchain-based applications. Using smart contracts, our approach automatically enforces access policies through encryption and is in contrast to most access control models that solely rely on smart contract policies. These contracts are prone to many security vulnerabilities and in some cases written by developers whose trustworthiness is dubious. A cryptically enforced access control, on the other hand, gives more of the sovereignty promised by the blockchain technology, back to users as showcased in our medical data management framework.
Coarse-to-Fine Document Ranking for Multi-Document Reading Comprehension with Answer-Completion

Multi-document machine reading comprehension (MRC) has two characteristics compared with traditional MRC: 1) many documents are irrelevant to the question; 2) the length of the answer is relatively longer. However, in existing models, not only key ranking metrics at different granularity are ignored, but also few current methods can predict the complete answer as they mainly deal with the start and end token of each answer equally. To address these issues, we propose a model that can fuse coarse-to-fine ranking processes based on document chunks to distinguish various documents more effectively. Furthermore, we incorporate an answer-completion strategy to predict complete answers by modifying loss function. The experimental results show that our model for multi-document MRC makes a significant improvement with 7.4% and 13% respectively on Rouge-L and BLEU-4 score, in contrast with the current models on a public Chinese dataset, DuReader.
Alignment Recovery for General Integer Scoring

Alignment recovery is the process of recovering optimal alignment results based on weighted computational scores. Alignment recovery in classical dynamic programming (DP) is obtained by backtracking a trace created in the computational scoring phase. Bit parallelism is a parallel computing technique done by increasing the size of the word processing unit. The actual value of the score in the DP matrix is replaced by the difference of the adjacent matrix cell values. This requires adjustment of the scoring computation and its alignment recovery mechanism, especially for integer weights. General integer scoring involves a set of integers as its weights in bit-parallelism score computation that are not yet accompanied by alignment recovery. This paper presents an algorithm to recover the final alignment results from interpreting the horizontal and vertical adjacent-cell bit parallelism score values. The results show that the algorithm produces the same match pair result as the classical backtracking DP algorithm with less gap insertion. The algorithm requires O(m) space and time.
Digital Multimeter Automatic Verification Device Design

This unit is used for the automatic verification operation of the digital multimeter. The computer is used as the core to complete the verification of the digital multimeter, and the digital image processing technology is used for the digital universal representation number reading. The verification data and verification results in the multimeter verification process are stored in the computer. The device realizes the automatic operation of the digital multimeter from instrument plug-in, range adjustment, reading recognition, data storage, data processing, and result determination. The utility model relates to a digital multimeter verification device, belonging to the field of automatic verification of power meters.
The mapping of information landscapes as a tool to develop IL

In her discussion of information literacy, Annemaree Lloyd (2010) developed the notion of the information landscape as a way of conceptualising the informational and technological resources arrayed around individuals and groups, and which they must learn to navigate. She alludes (p. 2) to the idea of mapping this landscape as a way by which actors learn these navigational skills and, thus, develop information literacy. But she offers no detail in this work or others regarding what mapping might actually mean as an educational practice, and how it might be employed in the teaching and learning of information literacy.&#x0D; This paper will report on research conducted on data generated in different ways from a course in which mapping is integrated, as both a graphical and discursive practice. At the start of this course, students are asked to collaborate on drawing mind maps that depict their information landscape as they see it at this point, and these maps can be analysed as depictions of their information horizons, in ways similar to the study of Sonnenwald, Wildemuth and Harmon (2001). In addition, data have been generated from online discussions undertaken throughout the course, which record how within small groups, students negotiate and build the information landscape that they use to complete the course assessment. By suggesting and/or validating the judgments of members, the group develops an agreed-upon representation of their landscape that can be the basis for further judgments. Thus, from the dialogue emerges a discursive map of this landscape.&#x0D; It will be argued that the process of negotiating this map is a productive one when considering how information literacy sklills can be developed in ways that will transfer effectively outside the university.
Differential Learning Particle Swarm Optimization with Full Dimensional Information

The particle swarm optimization (PSO) algorithm has been abroad applied in many tasks due to its merits, such as simple structure and easy to implement. However, PSO tends to converge prematurely, and the results are usually not satisfactory when addressing complex problems. This paper proposes a novel hybrid optimization technique called differential learning particle swarm optimization with full dimensional information (FDLPSO). In FDLPSO, the differential search method is adopted to enhance diversity and avoid getting trapped in a local optimal solution. Unlike the traditional PSO algorithm, in order to improve the comprehensive search capabilities of the algorithm, a full dimensional information learning strategy is proposed to construct learning exemplars to guide the learning of the particles and the convergence and adaptability of FDLPSO. The comparison results show that FDLPSO has a superior performance than seven well-known PSO variants and can quickly find a more competitive solution.
DIFFERENCES IN FORENSIC SCIENCE TRAINING AMONG THE INVESTIGATING POLICE OFFICERS IN NIGERIA

Training remains an important activity which organisations should embrace to ensure achievement of organizational goals. With modernization and development in science and technology, police organisations should train their personnel in the area of forensic investigation, because it is a fair and reliable means of understanding how crimes and related issues occurred. Sociodemographic factors play an important role in determining who goes for training among workers in an organisations; this could apply to the Nigeria Police (NP) agency. The aim of this study was to understand whether there were differences in the attendance of forensic science training among the Investigating Police Officers (IPOs) in the NP, based on their sociodemographic characteristics, namely, gender, age, marital status, highest educational qualification, rank and years spent in service. Using sample survey method, information related to the frequency of forensic science training attendance and sociodemographic profiles of 401 IPOs was collected. SPSS was used to analyze the data. Although forensic training was generally infrequent among the IPOs, the results showed that the frequency of training attendance was not similar among the categories of age, marital status, highest educational qualification and years spent in service, but was the same in the categories of gender and rank of the IPOs. It is recommended that sociodemographic profiles of IPOs need to be properly considered in selecting who should attend forensic training among the IPOs. Article visualizations:
Beyond takedown

The current preoccupation with ‘fake news’ has spurred a renewed emphasis in popular discourse on the potential harms of speech. In the world of international law, however, ‘fake news’ is far from new. Propaganda of various sorts is a well-worn tactic of governments, and in its most insidious form, it has played an instrumental role in inciting and enabling some of the worst atrocities of our time. Yet as familiar as propaganda might be in theory, it is raising new issues as it has migrated to the digital realm. Technological developments have largely outpaced existing legal and political tools for responding to the use of mass communications devices to instigate or perpetrate human rights violations. This chapter evaluates the current practices of social media companies for responding to online hate, arguing that they are inevitably both overbroad and under-inclusive. Using the example of the role played by Facebook in the recent genocide against the minority Muslim Rohingya population in Myanmar, the chapter illustrates the failure of platform hate speech policies to address pervasive and coordinated online speech, often state-sponsored or state-aligned, denigrating a particular group that is used to justify or foster impunity for violence against that group. Addressing this “conditioning speech” requires a more tailored response that includes remedies other than content removal and account suspensions. The chapter concludes by surveying a range of innovative responses to harmful online content that would give social media platforms the flexibly to intervene earlier, but with a much lighter touch.