Reviewerly/exHarmony huggingface dataset:
Cryptocurrency adoption in e-payment: barrier of its implementation

Cryptocurrency is a type of cryptographic e-currency generated by the computational result of mathematical techniques throughout blockchain technology. It has bitcoin as the world's first decentralized anonymous digital currency which allows online transactions without relying on any third-party institutions or government. Though, its technology is considered as one of the secure online integrated payment systems in financial transactions for many different businesses, it is still struggling for its integration and people are reluctant to embrace its adoption. Therefore, to address this gap, we discussed several implications for theory within information system adoption in light with the study’s objective. the research utilized a quantitative method survey built on theories of Technological Acceptance Model (TAM), Theory of Reasoned Action (TRA), Delone and McLean Information System Success Model and Self-determination Theory Model (SDT) to examine the factors influencing its adoption in e-payment. We used a sample of 402 participants for the analysis where seven main variables and nine hypotheses got formulated and tested using PLS-SEM path modeling with SPSS. The result shows that the analysis of the data provided support for all the hypotheses and established a positive relation between variables and the findings obtained have both academic and practical worth in terms of Information Systems technology adoption for improving the understanding of factors influencing cryptocurrency adoption in e-transaction
DEVELOPMENT OF A PROMOTION SELE-EFFICACY TO PREMATURE PREGNANCY PREVENTION PROGRAME

This research is Research and Development. The purpose is to develop self-efficacy enhancement to premature pregnancy prevention by application of self - efficacy theory for evaluation and development program. The activity consists of 3 phases: 1) The development phase of the program by collecting data with people and teenage 30 sample 2) The trial phase in teenage 32 sample and 3) The evaluation phase at the end of program. Data collection is qualitative and quantitative. Percentage, mean, standard deviation, pair t-test were employed for data analysis Results reveal that self-efficacy to premature pregnancy prevention program including: Exchange of learning about premature pregnancy, modeling, refuse sexual and use of contraceptive training skills such as contraceptive pill and condom. The study reveal that after joining in program the sample had greater mean score of self-efficacy toward premature pregnancy prevention, self-efficacy in persuading and advising friend to premature pregnancy prevention and premature pregnancy prevention behavior than those before joining in program (p=.001, p<.001 and p=.002, respectively) The development of a promotion self-efficacy to premature pregnancy prevention program can enhance the self-efficacy of teenage in appropriate pregnancy prevention. Further should follow up period and use real modeling to help teenage aware of the importance of pregnancy prevention even more and might further help teenage to appropriate pregnancy prevention
Translation professions involving mental capacity to learn lexical, structural, semantic, stylistic, pragmatic

Translation is a profession which does not require much physical ability. Translation mostly involves mental capacity to learn lexical, structural, semantic, stylistic, pragmatic, and, in a word, linguistic and to some extent, extra-linguistic aspects of another language, learning to use them practically to produce target texts acceptable in that language. It can be concluded that blind and visually impaired individuals can become translators due to the non-physical nature of this work. Thus, translation is one of the professions suggested by the researcher to blind and visually impaired individuals to earn their living. It should be kept in mind that translation has specific aspects which necessitate visual ability. All texts may have non-lexical elements bearing semantic values, such as pictures, figures, tables and diagrams. Some words and sentences may be bold or italicized or may be written in a color different from the rest of the text. Different sentences might be located in different places on the page for some purposes. All these issues can be problematic for a translator poor in vision.
Non-linear Boson Sampling

Boson Sampling is a task that is conjectured to be computationally hard for a classical computer, but which can be efficiently solved by linear-optical interferometers with Fock state inputs. Significant advances have been reported in the last few years, with demonstrations of small- and medium-scale devices, as well as implementations of variants such as Gaussian Boson Sampling. Besides the relevance of this class of computational models in the quest for unambiguous experimental demonstrations of quantum advantage, recent results have also proposed first applications for hybrid quantum computing. Here, we introduce the adoption of non-linear photon-photon interactions in the Boson Sampling framework, and analyze the enhancement in complexity via an explicit linear-optical simulation scheme. By extending the computational expressivity of Boson Sampling, the introduction of non-linearities promises to disclose novel functionalities for this class of quantum devices. Hence, our results are expected to lead to new applications of near-term, restricted photonic quantum computers.
LibGuides: Tails and Tales Make Your Own Bookmark: Paper Bookmarks

A collection of directions, craft templates, and pictures for making your own creative bookmarks at home.
Gradient Descent on Two-layer Nets: Margin Maximization and Simplicity Bias

The generalization mystery of overparametrized deep nets has motivated efforts to understand how gradient descent (GD) converges to low-loss solutions that generalize well. Real-life neural networks are initialized from small random values and trained with cross-entropy loss for classification (unlike the lazy or NTK regime of training where analysis was more successful), and a recent sequence of results (Lyu and Li, 2020; Chizat and Bach, 2020; Ji and Telgarsky, 2020) provide theoretical evidence that GD may converge to the max-margin solution with zero loss, which presumably generalizes well. However, the global optimality of margin is proved only in some settings where neural nets are infinitely or exponentially wide. The current paper is able to establish this global optimality for two-layer Leaky ReLU nets trained with gradient flow on linearly separable and symmetric data, regardless of the width. The analysis also gives some theoretical justification for recent empirical findings (Kalimeris et al., 2019) on the so-called simplicity bias of GD towards linear or other classes of solutions, especially early in training. On the pessimistic side, the paper suggests that such results are fragile. A simple data manipulation can make gradient flow converge to a linear classifier with suboptimal margin.
Remarks on two approaches to NPI licensing

In relation to the notion of informativity, two types of approaches to DPs headed by any (any-DPs) have been distinguished. At a ﬁrst approximation, one approach takes an any-DP to be accompanied by a requirement that a clause containing it be more informative than all its relevant alternatives (cf. Kadmon & Landman 1993), while the other approach requires a clause containing it to be more informative than all its relevant alternatives that are true (cf. Chierchia 2013). The goal of this paper is to compare these approaches with respect to their predictions about the distribution of plural any-DPs in modal environments.
Developing Noun Words Domino Card (NWDC) Learning Media to Improve English Vocabulary Mastery of Junior High School Students

For junior high school pupils, research on the development of learning media is badly needed. Students' understanding and mastery of specific materials should improve as a result of the availability of learning media. The goals of this study are to (1) create a product in the form of a learning media called Noun Words Domino Card (NWDC) that is appropriate for seventh-graders at Satap Woja State Junior High School; and (2) develop a product in the form of a learning media called Noun Words Domino Card (NWDC) that is appropriate for eighth-graders at Satap Woja State Junior High School. (2) understand the use of NWDC learning media for students, and (3) understand the efficacy of NWDC learning media in improving student vocabulary knowledge. The ADDIE paradigm, which consists of five steps: Analyze, Design, Develop, Implement, and Evaluate, was used to conduct this research. The findings revealed: (1) The noun words domino card (NWDC) is a viable learning material for students to use and assess. The practicality is determined by material experts, who gave it a score of 3.7, and media experts, who gave it a score of 3.5. (2) The noun words domino card (NWDC) is a useful tool for pupils to improve their vocabulary mastery. (3) Learning media noun words domino card (NWDC) is helpful in developing student vocabulary knowledge, according to the student's reaction as a user of learning media with a total average score of 3.6. It was calculated using the average oral test score of students who met the English subject's minimal completion criteria.
The Mediating Role of Motivation between Organizational Climate and Organizational Citizenship behaviour in the Jordanian Telecommunication Companies

The study's goal was to determine the computerized organizational climate (OC) and their relationship to improving the organizational citizenship behaviour with motivation as mediating of the employees of the Jordanian telecommunication companies. A questionnaire was prepared and produced to gather data and measure the study variables in order to meet the study's objectives. SmartPLS (3.3.2) was used. 350 randomly selected respondents from three major telecommunication companies in Jordan were given the self-administered questionnaire. The study found the following direct effects are positive and significant namely, OC on OCB (β=0.484; P = 0.000), OC on motivation (β=0.852; P = 0.000), and motivation on OCB (β=0.383; P = 0.013). The study also found motivation mediates the relationship between OC and OCB. Overall, the findings support OC and its link to motivation as a means for businesses to assist employees in improving their OCB.
Monetary policy transmission and income inequality in Sub-Saharan Africa

This paper evaluates the monetary policy transmission and income inequality in Sub-Saharan Africa (SSA) countries. We find procyclical response of income inequality to unanticipated monetary easing in the last two decades. Countercyclical monetary measures may have been efficient, but they have been dis-equalising as well. Taking cognisance of the explanations of the earnings heterogeneity channel, this evidence signals high concentration of assets and resources, limited employment of labour and limited distributive capacity of the state in SSA countries. Economic outturns may have favoured chiefly, the top of the distribution - entrepreneurs and their profit margin. Three main channels distinguish the transmission of standard and non-standard monetary measures: the reaction in the stock market, the response of the exchange rate and the fiscal response. Unconventional monetary policies appear to rely more on wealth effects than conventional policy measures. Unexpected non-standard monetary easing depreciates the exchange rate while unanticipated conventional accommodative monetary action appreciates the currency. Fiscal transfers increase in reaction to expansionary unconventional monetary policy shock. In contrast, a surprised standard monetary expansion decreases fiscal distributions, an effect that appears to underscore the limited fiscal space and tax revenues in most developing and emerging economies. The evidence demonstrates that the fiscal reaction to monetary policy action is important to the overall transmission of monetary policy to macroeconomic aggregates. Instructively, we find that the inflation cost of countercyclical monetary measures is comparatively less severe for standard monetary measures than non-standard monetary actions.
Texture Filtering With Filtering Scale Map

In this paper, we propose a novel texture filtering method. Starting with a texture boundaries extraction, we obtain the possibility of texture boundary by the statistics of the proportion of the pixels in different colors. The possibility of texture boundary can be obtained by calculating the Bhattacharyya distance of the color proportion on each side of each pixel. Further, we build a filtering scale map to guide the parameters of the filter. This filtering scale map is based on the texture boundary. Finally, to obtain the texture filtering result, we design an adaptive shape edge-preserving filter which is simple and effective. By counting the color information of all pixel neighborhoods the filter can select the pixels in a similar color to filter. Experiments are performed on different color-texture images, and the results show that our proposed method performs much better compared with state-of-the-art methods on texture filtering.
Examining the Impact of Social Media on the Academic Performances of Saudi Students - Case Study: Prince Sattam Bin Abdul Aziz University

undergraduate students’ academic performances and their social interpersonal skills in the Prince Sattam bin Abdulaziz University.Design/methodology/approach: 64 samples were collected from full-time undergraduate students studying in Prince Sattam bin Abdulaziz University from different colleges including Community college, College of Business Administration, College of Education, College of Engineering and College of Pharmacy. The descriptive statistics analysis was used to analyze the demographic data while inferential statistics were used in testing the research hypotheses. The results obtained from the analyses were used to interpret the outcomes.Findings: The empirical results reveal that the students enjoy meeting new friends online using social media rather than meeting in person and for this reason they spend a lot of time – addicted. It is also confirmed that the bad comments are passed easily through social media affecting other's sentiments and most of them strongly believe that all the information in social media is true and reliable and the rumors were spread easily in social media. Further, it is also confirmed that social media does not support the Learning of the students.Practical Implications: The study confirms that the students exchange learning materials through social media and it helps them to update the developments in their college/university. The students believe that through Social media they have improved their communication skills and they can communicate with anyone at any time. It is also found that some of their teachers communicate with them and encourage them to use social media but for studying only.   Originality/value: The research work is of its first kind as it focuses on the impact of social media on the academic performances of the students studying in Prince Sattam bin Abdulaziz University, Saudi Arabia, which has suggested effective means for effective implementation of social media strategy.
Library Research Guides: Image Resources: University-Wide Databases with Images

This guide contains image resources available through IU Libraries (both campus specific and university-wide) as well as information about open access images. The databases listed on this page are available to all Indiana University communities.
On the Limitations of Cryptocurrencies

The threat of double-spending attacks on proof-of-work based cryptocurrencies is typically analysed without endogenising the incentive of attackers or allowing for multiple attackers. To overcome this limitation, I adopt the general equilibrium model of Chiu and Koeppl (2017) and allow for coalitions pursuing collective doublespending attacks. I show that in their current form cryptocurrencies are unfit to settle large transaction volumes safely. Thus, cryptocurrencies do not pose a valid alternative to established payment systems.
Internet Cafe Billing System Data Security Using RC4 Stream Cipher

In data communication, against a data security method known as cryptography (Cryptography). Cryptography is a data security method that can be used to maintain data confidentiality, data authenticity or integrity, and the authenticity of the sender. This method is intended so that important information of a limited or confidential nature sent through public telecommunications facilities cannot be known or utilized by unauthorized parties. In this case, data security is also needed at the internet cafe (internet cafe). Warnet which is a place that provides Interconnection Networking that connects computers to form a network system that covers the whole world (global). Each cafe requires a billing system that is used to determine the state of the user in using the facilities at the cafe, starting from how long it takes to use and how much it costs each user. For this reason, so that the data on the billing system cannot be manipulated or modified by unauthorized persons, it is necessary to secure data. The data security method that will be used is cryptography, especially by using the RC4 stream cipher.
Snapshot Based Disaster Recovery on Cloud

Nowadays, data has been produced in a larger amount. So, it is important to have some recovery issues also related to it. Cloud computing refers to the interconnection of various systems for the purpose of sharing resources. Cloud is one of the largest platforms that is growing rapidly in the IT sector. There are many private data that are related to cloud. Therefor the need for data recovery in the cloud is gaining more importance day by day. For this an efficient and effective data recovery techniques are to be developed. Recovery of data helps the users to collect information on any backup servers whenever the server is down. Many solutions have been developed for the disaster recovery. This research paper mainly discusses about some of the techniques and solutions that are needed to recover the data in cloud architectures. This work proposed snapshot based backup technique for the databases and implemented successfully.
Remote Sensing Image Retrieval Based on Multi-scale Pooling and Norm Attention Mechanism

Remote sensing images have rich content, and then the features extracted by the general depth model are easily interfered by the complex background. The key features cannot be extracted well, and it is difficult to express the spatial information of the image. A deep convolutional neural network based on multi-scale pooling and norm attention mechanism is proposed, which adaptively weights salient features at the channel level and the spatial level. First, in the multi-scale pooling channel attention module, the max pooling of different scales is performed on the feature map of each channel based on spatial pyramid pooling. Next, the feature maps of different sizes are transformed to a uniform size by adaptive average pooling. Thus the salient features of different scales can be paid attention by element-wise addition. Then, in the norm spatial attention module, the pixels corresponding to the same spatial position of each channel are formed into vectors, and the feature map with spatial information is obtained by calculating the L1 norm and L2 norm of the vector group. Finally, the cascaded pooling method is adopted to optimize the high-level features, and the high-level features are used for remote sensing image retrieval. Experiment are conducted on UC Merced data set, AID data set and NWPU-RESISC45 data set. The results show that the proposed attention model improves the retrieval performance by concerning the salient features of different scales and combining the spatial information.
Bitcoin buyers punished by surging bond yields

Investors' love affair with bitcoin has become a double-edged sword as surging bond yields sparked a sell-off in risk assets, including bitcoin, and punished shares of companies that recently bought the cryptocurrency.
Traffic Patterns Detection in Video Surveillance Using Optical Flow and Topic Model

Research in the field of video surveillance systems has been improving because of the increasing need for intelligent monitoring, control and management. Given the large amount of data on these intelligent transportation systems, extracting patterns and automatically labeling them is a challenging task. In this paper, a topic model was used to detect and extract traffic patterns at intersections so that visual patterns are transformed into visual words. The input video is first split into clips. Then, the flow characteristics of the clips, which are based on abundant local motion vector information, are computed using optical flow algorithms and converted to visual words. After that, with a non-probabilistic topic model, the traffic patterns are extracted to the designed system by a group sparse topical coding method. These patterns represent visible motion that can be used to describe a scene by answering a behavioral question such as: Where does a vehicle go? The results of the implementation of the proposed method on the QMUL video database show that the proposed method can correctly detect and display meaningful traffic patterns such as turn left, turn right and crossing a roundabout.
AN ANALYSIS OF STUDENTS’ ANXIETY IN SPEAKING

This article aims to define the factors of students’ speaking anxiety and how the students’ strategies to overcome speaking anxiety in the class room. The problem in this research is anxiety of tenth grade students SMK to speak in classroom. Based on the issues above, the purpose of this researcher is to define the factor causing of speaking anxiety and how the students' strategies to overcome speaking anxiety. This research is qualitative descriptive. The subject in this study is tenth grade of SMK in Academic year 2020/2021. The totally number is 22 students. The data collected by Interview and questionnaire. The results showed that the factor causing of the students' speaking anxiety to speak in the language classroom are: lack of familiarity of task, fear of making mistakes, low motivation, incomprehensible inputs, lack of confidence and then low English proficiency. And the student’s strategies to overcome speaking anxiety were peer seeking, preparation, relaxation, positive thinking and resignation.