Reviewerly/exHarmony huggingface dataset:
The Future of Biometric Data Protection in Jordan in Light of the GDPR: do we Need to Comply with the GDPR?

The expansion of social media, artificial intelligence, and the Internet of Things has led to many challenges and risks for biometric data protection such as the unauthorized use or treatment of such data. The needs to protect biometric data and comply with the most important regulations have become paramount for information security, especially with the incorporation of new technologies based in biometric data into most of aspects of our daily life. Currently, data protection in Jordan is governed by several constitutional provisions and some sectoral laws, which have more recently been complemented by the new Data Privacy and Protection Bill, 2020, Draft Law. This study focuses on the future of biometrics data protection in Jordan and considers the compliance of new legislation with the General Data Protection Regulation (GDPR). This compliance is encouraged because of the universal nature of GDPR, by analyzing the ability of the new Jordanian data protection Draft Law to incorporate specific data protection principles. The novelty of this paper comes from the fact that little work has been done on best practices for biometric data privacy in Jordan, also, given the vital importance of judging and perfecting data privacy policies, especially in Jordan around this issue, this study provides insight on how Jordan might best perfect its Draft Law to protect human rights. It is certainly of interest to the fields of law and ethics. The author used content analysis to analyze relevant legislation and literature, we found that Jordan lacks a comprehensive legal framework for biometric data. Little information is available about how to best protect biometrics data, the nature of the system to which it is subject, and the extent of biometrics data protection. Accordingly, the Draft Law will require significant amendments before it can accommodate the level of legislation currently required
윌리엄 댐피어의 동아시아 지역지리

The purpose of this study is to examine the content of East Asian geography described by William Dampier who contributed to the development of Enlightenment geography. For this, I reviewed the geography contents of East Asia described by Dampier. As a result of the study, Dampier’s maps on trade winds and ocean current provide invaluable description about East Asian maritime information at the time, and he defined that typhoons and hurricanes were same phenomena as the same type of tropical storm. I have also confirmed that detailed information of politics, religion, commerce, etc. that can not be found in other navigation narrative is described. The contents dealt in his travel reports can be used as a material on the future study for the British perception of East Asia of the eighteenth century.
We see we disagree: Insights from Designing a Cooperative Requirements Prioritization System.

Information systems development is driven by a variety of stakeholders – each with specific requirements. Modern agile development methods, like Scrum, allocate the vital step of prioritizing requirements to dedicated roles like the product owner. However, this can create a bottleneck and may lead to misunderstandings and conflicts between stakeholders. Enabling stakeholders to cooperatively prioritize requirements frees up product owners while involving stakeholders more closely in a crucial development step, strengthening their ties to the final system. Therefore, stakeholders must form a mutual and shared understanding of requirements. This research in progress utilizes the design science research methodology to propose design principles for a cooperative requirements prioritization system using the MuSCoW method – which classifies requirements in four categories. By transferring the theory of shared understanding to the field of requirements prioritization, we derive design principles for cooperative requirements prioritization systems. We enable a group of heterogeneous stakeholders to identify and discuss differences and come to a mutually-agreed prioritization decision. We introduce design features that instantiate these principles and present promising results of an initial pre-test. This research in progress contribute to information systems development by introducing principles for the under-researched, but important class of requirements prioritization systems.
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Speeded-up Simple Linear Iterative Clustering Based on Region Homogeneity

For better analyzing and adopting superpixel methods in image segmentation, an improved Simple Linear Iterative Clustering (SLIC) algorithm is put forward, which sustains that homogeneous regions show high consistence during clustering. Firstly, a primary iteration of SLIC approach is employed to generate uniform superpixels. Then an update strategy is introduced to determine whether to recluster the candidate region. In homogeneous regions, a cluster center often shows relatively small deviation of last position in spatial-color feature space when local iteration occurs, which can be regarded as redundant computation and be reduced. Experimental results show that the strategy brings a remarkable increased efficiency for traditional SLIC without significant affection on segmentation results.
A Privacy Protection Method for Social Networks Based on Node Importance

The social networks record a large amount of social activities information, which contain sensitive data and private information. It makes social networks more vulnerable to be attacked. In order to resist the attacks based on structural knowledge and better protect the privacy information, this paper designs a privacy protection method for social networks based on node importance (NI-PP). This method introduces the node importance calculated by K-shell into K-symmetric anonymity to realize the purpose of protecting important nodes and provides a new restoration algorithm that can completely restore the structures of the original networks. This restoration algorithm uses labels added on the original networks to recover those nodes that are deleted mistakenly during the restoration process, so as to improve the availability of the anonymous networks and reduce the loss of information in the restoration process. Analysis and experiments results show that NI-PP can protect the privacy information of social networks very well.
Формування медіа- та інформаційної грамотності у публічних бібліотеках Австралії та Фінляндії.

This paper presents the research of the state of media education in Australia and Finland, considers the activities of public libraries in the sphere of media and information literacy, and provides examples of library projects and programs in demand.
KEEFEKTIFAN MODEL PEMBELAJARAN CLUSTERING DALAM KETERAMPILAN MENULIS PUISI SISWA KELAS V SD YAPIS 02 MANOKWARI

This study aims to prove the effectiveness of the clustering learning model on poetry writing skills of fifth grade students of SD Yapis 02 Manokwari. This research is an experimental research involving one class. The population of this study was the fifth grade students of SD Yapis 02 Manokwari with 95 students spread into three classes. The sample chosen was the fifth grade students with 31 students. Sampling is done using the claster random sampling technique. Assessment instruments are used with instruments related to using the clustering learning model and the initial test (pretest) and the final test (posttest). The data obtained were analyzed using descriptive statistics and inferential statistics. The results of the descriptive statistics show that the effective clustering learning model for writing poetry skills in class V a Elementary School 02 Manokwari is evidenced by the value of the test taught using a clustering learning model in a good category with an average value of 83.6. The inferential statistical results of the calculation of the significance test for the t test are 4,440 &gt; 1,690. This shows that the proposed hypothesis is accepted which means that the clustering learning model is effective against poetry writing skills carried out in class V of SD Yapis 02 Manokwari. Based on the presentation of the results of the data analysis and discussion, it can be concluded that the effectiveness of the clustering learning model for poetry writing skills of class V students of SD Yapis 02 Manokwari.
On Teaching Mathematics to Philology

The relevance of the problem stated in the article is predetermined by the fact that at present the subject Mathematics is studied practically at all university departments, including humanitarian ones, and consequently the task of motivating students to study non-core discipline arises inevitably. The aim of the research is to show the necessity of studying mathematical and historical-mathematical disciplines by students of philological directions for improving their special training and forming an ability to comprehend literary metaphors based on the facts from natural and exact sciences. The leading approach to the study of the problem is generalization of experience of the teachers of Elabuga Institute of Kazan Federal University on teaching mathematical subjects to students of humanitarian faculties. Evaluation of the effectiveness of teaching mathematical disciplines was carried out by means of questioning students of different courses and training directions whether they recognize the quotes from the poetic works of Joseph Brodsky without indicating the authorship, as well as the analysis of the content of educational curricula in these disciplines. The research allowed the authors to draw conclusions about the incorrect interpretation of the relevant fragments of literary works by the majority of students of the philological direction of training, which is a consequence of the narrowness of outlook, lack of knowledge even of the well-known facts from the history of mathematics and natural sciences. The study proves that mathematical profile students demonstrate a more exact comprehension of the author's ideas, though they do not understand the proposed citations fully. The study revealed that the training of highly qualified specialists in Philology should be more versatile in order to expand not only the students’ literary horizons, but provide them with knowledge of natural sciences. The authors developed recommendations on the content of curricula in mathematical subjects for Philology students.
Duidoku and Ultimate Duidoku

The closing chapter of the book describes to two variants of the game of Sudoku that the author developed during his game theory lectures to undergraduates at Cornell University, Ithaca, USA. These two-player games, based on similar rules as Sudoku, are called Duidoku and Ultimate Duidoku. The chapter also contains a game-theoretic analysis of Ultimate Duidoku.
Interrogative Construction in Aceh Language

The article deals with the interrogative construction in Aceh language. This study used a qualitative approach. The study aims to find out; (1) kinds of interrogative words in Aceh language (2) interrogative construction in Aceh language by using X Bar Theory. The data in this study are Acehnese sentences that contain Interrogative words. The data sources in this study are (1) Acehnese dictionaries, (2) Acehnese Book, and (3) Acehnese speakers. The data collection process by an interview with the Acehnese speaker in Langsa and data analysis used X Bar Theory. The results of the study show that;1) there are eight kinds of interrogative words in Aceh language especially in East Aceh dialect in Langsa such as: a) Pue. peue, b) Soe, c) Hoe, d) pat, dipat, e) pajan, f) pakon, g) padum, h) pane, i) pakiban. There are three categories of interrogative construction;(a) Open Interrogative, (b) Close Interrogative, (c) Rhetoric Interrogative. The Structure of the sentence in Aceh language constructs by using of the specifier, complement, and Verb. Specifiers put by NP and Complement put by Auxiliary, PP, or NP and Adverb can be preposition by PP or NP.Â
Approximate Buffers for Reducing Memory Requirements in the SKA

The memory requirements of digital signal processing and multimedia applications have grown steadily over the last several decades. From embedded systems to supercomputers, the design of computing platforms involves a balance between processing elements and memory sizes to avoid the memory wall. This paper presents an algorithm based on both dataflow and approximate computing approaches in order to find a good balance between the memory requirements of an application and the quality of the result. The designer of the computing system can use these evaluations early in the design process to make hardware and software design decisions. The proposed method does not require any modification in the algorithm's computations, but optimizes how data are fetched from and written to memory. We show in this paper how the proposed algorithm saves 23.4% of memory for the full SKA SDP signal processing computing pipeline, and up to 68.75% for a wavelet transform in embedded systems.
Do it yourself or get it done? Enhancing SME CEOs’ decision-making regarding Information Security

This research addresses the determinants of CEOs’ actions regarding the information security (ISS) of small and medium enterprises (SMEs). This article aims to (a) identify factors influencing CEOs’ ISS actions, (b) examine the relevance of protection motivation theory (PMT) in explaining top management support (TMS, i.e., supportive actions), and (c) find potential differentiated effects on protective vs. supportive actions. The results of a questionnaire-based survey (N=200) show that the PMT and social influence constructs, while explaining a significant amount of variance, exert differentiated effects: in contrast with protective actions, which are influenced mainly by self-efficacy, SME CEOs’ supportive actions are strongly affected by the social influence of peers (partners and competitors) and customers. At a theoretical level, this research validates the relevance of the PMT framework for the study of TMS determinants in the context of ISS. This study is also the first to distinguish between these two types of actions and offers new insights on CEOs’ ISS-related behavior literature. For practitioners, the results imply that even when CEOs do not exert protective actions, it is important to build on their professional relations to trigger and enhance their supportive actions.
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Causal Learning via Manifold Regularization.

This paper frames causal structure estimation as a machine learning task. The idea is to treat indicators of causal relationships between variables as 'labels' and to exploit available data on the variables of interest to provide features for the labelling task. Background scientific knowledge or any available interventional data provide labels on some causal relationships and the remainder are treated as unlabelled. To illustrate the key ideas, we develop a distance-based approach (based on bivariate histograms) within a manifold regularization framework. We present empirical results on three different biological data sets (including examples where causal effects can be verified by experimental intervention), that together demonstrate the efficacy and general nature of the approach as well as its simplicity from a user's point of view.
A Study on the Impact on Management Performance of Hidden Champions Using Blue Ocean Strategy to Develop a New Product

This study is an empirical research to find out the effect on the management performance of hidden champions of food manufacturing companies when using blue ocean strategy for new product development. In order to achieve the purpose of this study, we conducted a questionnaire survey on hidden champions in the domestic food manufacturing industry and proceeded empirical analysis. When small and medium-sized enterprises in food manufacturing industries develop a new product, searching for non-customer, rebuilding the market boundary, and linking the external networks have a significant impact on their management performance. However, the fair procedure did not have a significant effect on the management performance. In terms of relative influence, rebuilding the market boundary was most affecting, followed by searching for non-customer and linking the external networks. On the other hand, this study implicated the management performance of hidden champions of food manufacturing industries when new products is developed by using the blue ocean strategy. Obtained results are as follows. If small and medium-sized enterprises of food manufacturing industries develop new products, it will be able to improve the management performance by utilizing strategies such as searching for non-customer, rebuilding the market boundary, and linking the external networks. In particular, the rebuilding the market boundary among the blue ocean strategies has a relatively high impact on management performance.
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Linguistic variability of the answers to open-ended questions of reading literacy in the computer based INVALSI tests

This paper analyzes the linguistic variability of students’ answers to the questions administered within the Invalsi tests for grade 8 in the school year 2017/2018. From a quantitative point of view, the open-ended questions were classified on the basis of the linguistic variability of the relative answers; this classification made it possible to observe different behavioral patterns and deduce general indications. From a didactic point of view, the study allows to outline focused reflections on the verbalization of answers to reading comprehension questions. From a practical point of view, the study may guide further reflection on how to formulate open-ended questions in order to reduce the variability of answers.
Customer benefits on bitcoin as a medium of exchange / Maryam Jameelah Hashim … [et al.]

Cryptocurrency is a digital currency that is powered by blockchain technology. One of it is bitcoin, a system that is digitally created and traded tokens to which value is assigned. The level of adoption of bitcoin has accelerated due to several fiscal crises that leads to financial crashes that have affected the lives of millions of people. This has created a demand for new kinds of niche money. Issues need to be closely discussed before it is fully accepted by customers as a medium of exchange. Even though bitcoin is used as a medium of exchange, there is still no specific guidance and benefits to the users. The issues concernedare whether the customers will get the benefits of privacy, lower transaction costs and freedom in payment. Therefore, the aims of this paper are to identify the relationship between transaction cost, privacy and digital payment as a benefit of bitcoin as a medium of exchange. This research will be conducted in Klang Valley area and the questionnaires will be disseminated directly to respondents. These respondents will be identified using probability simple random sampling. A regression analysis will be conducted comprising 200 observations in Klang Valley, Malaysia. Partial least square-structural equation (PLS-SEM) will be used. In the measurement model, reliability will be assessed by examining the Composite Reliability (CR), while validity will be assessed by convergent validity and discriminant validity. Subsequently, structural model testing with 500 re-samples was applied to test the hypothesized relationships between exogenous variables and endogenous variable. Digital payment and privacy are statistically significant towards the benefit of using bitcoin as a medium of exchange. It was found that the digital payment contributes the highest benefit to the customers followed by privacy. The results provide interesting insight into the determinants for the customers benefit using bitcoin. Although the findings show significant results customers should always decide the good and bad thoroughly before finalizing their decisions on the usage of bitcoin. Therefore, it is hoped that this study will enrich the growing literature on the subject and future research needs to explore on the benefits of using bitcoin among the real users. This study is expected to give guidelines to the policymakers on the implementation of bitcoin as a medium of exchange. It is also expected that the results may provide interesting insight into the determinants of customer benefits using bitcoin. Simultaneously, it will contribute to the elements of industry, innovation and infrastructure.
남북 정상에 대한 언론 보도문의 호칭어와 경어법 : 2018년 남북정상회담을 중심으로

The purpose of this paper is to compare how the South and North Korean press used the terms of address and honorifics for the leaders of the two Koreas. We analyze the press reports related to the three inter-Korean summits in 2018 and the Panmunjeom meeting among the leaders of two Koreas and USA in 2019. We focused on the data of address terms and honorifics for President Moon Jae-in and Kim Jong-un used by the South Korean and North Korean newspapers. Specifically, we looked at the difference in usages between the South Korean newspapers and North Korea's newspaper Rodong Sinmun, the difference in usages between the Hankyoreh and Chosun Ilbo in South Korea, and the difference in usages between the 2000 and 2018 inter-Korean summits. Through this analysis and discussion, we can clearly see that many factors affect the use of language in the media, such as the political system of the two Koreas, the political attitude of the two South Korean media toward North Korea, and the age of the top leaders of North Korea.
CLRCNet: Cascaded Low-rank Convolutions for Semantic Segmentation in Real-time

Recent work has shown that deep convolutional neural networks have made immensely successful in many computer vision tasks such as semantic image segmentation, which can be thought as a complexed localization and classification problem. However, due to the limitation of computing cost and memory, most existing models are difficult to deploy on mobile devices. It is also an arduous task to get more semantic information from the feature map of downsampling. In this paper, we introduce cascaded low-rank convolutions network (CLRCNet) which is an efficient neural network by using multiple low-rank layers. The cascaded low-rank layers are used to reduce computational complexity. A pooling operation in network units is introduced to learn more contextual information during training. A large number of experiments show that the method has better performance than other network structures. Our network struct attains mean intersection over union (mIOU) of 63.3% on Cityscapes dataset at 76.9 frames per second on $512 \times 1024$ resolution.
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