Reviewerly/exHarmony huggingface dataset:
The Impact of Bitcoin's Search Volume on Its Price Fluctuations

From the concept of electronic currency proposed by Satoshi Nakamoto in 2008 to the official birth of Bitcoin in 2009, the virtual currency began to become a force that can not be ignored in the financial market. From the very beginning, it was not favored by the market. Now the entire virtual currency market is booming. With development, a variety of virtual currencies have sprung up like mushrooms after a rain, and the value of a Bitcoin has exceeded the 50,000 U.S. dollar mark. This volatile price also reflects the attitude of investors towards Bitcoin. Variety. Virtual currencies such as Bitcoin do not have physical or credit endorsements, and their market prices are largely determined by factors such as government supervision and policies, media influence, users' transaction behavior, and transaction needs. We can make some references for the financial investment of virtual currency by studying the influence of factors such as the search index of Bitcoin entries and media influence on Bitcoin price fluctuations.
Digitally Training Graph Viewers against Misleading Bar Charts

Author(s): Ramly, Claudia; Sen, Ayon; Kale, Ved; Rau, Martina A.; Zhu, Jerry | Abstract: Bar charts are common visual tools used to convey statistical information. Even though bar charts are effective in making abstract concepts more accessible, poorly-designed bar charts - whether designed intentionally or unintentionally - can easily mislead the viewer. For example, a poorly-designed bar chart may only present part of the effective range on the vertical axis. This exaggerates the contrast among bars, leading an unsuspecting graph viewer to wrong conclusions. More broadly, misrepresentation in data visualization is becoming an increasing societal problem contributing to daily misinformation. This paper presents a computational and cognitive solution to this problem. Our idea is to train viewers by showing them a few dozen carefully designed bar charts that are misleading, together with guidance on why these bar charts are misleading. We then test whether the viewers identify similarly misleading bar charts in the future. Importantly, we use neural networks and cognitive models to optimize the training (i.e., the design of those few dozen bar charts). Our experiment shows that perceptual trainings can help viewers not be fooled by similar misleading graphs in the future.
Design of Reed-Solomon Encoder for Error Detection in DRAM Cells

This paper investigates the design of Reed Solomon (RS) encoder. Based on the message symbols, the RS encoder generates the code-word. By carrying out a polynomial division using Galois Field algebra, the parity symbols are calculated. Reed-Solomon codes are one of the most effective and effective non-binary error codes to detect and correct burst errors. This is the focus work for my dissertation to implement RS encoder and decoder that is a complex algorithm and it is used for the reliable memory operation in a system. The RS Encoder and decoder are design in structural modeling and develop the hardware. The sift and multiplier type divider is used for Encoder and Syndrome module design.
An Improved and Optimized Practical Non-Blocking PageRank Algorithm for Massive Graphs.

PageRank is a well-known algorithm whose robustness helps set a standard benchmark when processing graphs and analytical problems. The PageRank algorithm serves as a standard for many graph analytics and a foundation for extracting graph features and predicting user ratings in recommendation systems. The PageRank algorithm iterates continuously, updating the ranks of the pages till convergence is achieved. Nevertheless, the implementation of the PageRank algorithm on large-scale graphs that on shared memory architecture utilizing fine-grained parallelism is a difficult task at hand. The experimental study and analysis of the Parallel PageRank kernel on large graphs and shared memory architectures using different programming models have been studied extensively. This paper presents the asynchronous execution of the PageRank algorithm to leverage the computations on massive graphs, especially on shared memory architectures. We evaluate the performance of our proposed non-blocking algorithms for PageRank computation on real-world and synthetic datasets using Posix Multithreaded Library on a 56 core Intel(R) Xeon processor. We observed that our asynchronous implementations achieve 10x to 30x speedup with respect to sequential runs and 5x to 10x improvements over synchronous variants.
BRITISH ACCENT THROUGH HARRY POTTER MOVIE AS A LEARNING MEDIA: IMITATING AND PRACTISING THE DIALOGUE

This research aims to identify the student's British accent ability and the motivation to learn British accents through the Harry Potter movie as a learning media by using methods of imitating and practicing the dialogue of that movie involving 8 students who sampled the research. In collecting data, tests were carried out to find out and measure the well-being of British students' accents through speaking tests, and questionnaires were given to students to get data on their responses to their motivations of learning a British accent. This research was a quantitative research, which used experimental study as a research design. Generally, the problem focus on the students who could speak English but they could not speak with good accent. The significant problems they faced are they still minus in applying the correct pronunciation and the good intonation because of influenced by their vernacular dialect that made them could not speak naturally. The result assumes that the implementation of imitating and practicing the dialogue of Harry Potter movie are very helpful to encourage students' British accent ability because there are significant readings from students after treatment is done also on the result of questionnaire, it concludes that the students’ motivation enlarge during using that method. Out of the 8 students, more than 75% chose this method can enlarge their motivation in learning English by watching Harry Potter movie in exploring British accent ability.
Quantum Meet-in-the-Middle Attack on Feistel Constructions

Quantum attacks on Feistel constructions have attracted much attention from worldwide crytologists. To reduce the time complexity of quantum attacks on $r$-round ($r \ge 7$) Feistel construction, we propose a novel quantum meet-in-the-middle (QMITM) attack. For 7-round Feistel construction, we introduce quantum computing in the offline computation of the classic meet-in-the-middle (MITM) attack [Guo2016], i.e., propose a quantum claw finding algorithm based on quantum walk, which speeds up the process of finding a match in the offline computation phase. The keys in 7-round Feistel construction could be recovered by the match at last. Furthermore, to attack $r$-round ($r > 7$), we use amplitude amplification algorithm to search the last $r-7$ rounds of keys. Compared with other quantum attacks in Q2 model, our attack reduces the time complexity from $O({2^{0.25nr - n}})$ to $O({2^{2n/3 + (r - 7)n/4}})$, and is significantly better than classic attacks. Moreover, our attack only needs to make classical online queries, without quantum superposition queries in other quantum attacks, which is more practical.
Resolving data barriers

Chapter nine discusses data barriers to artificial intelligence. Artificial intelligence requires a massive amount of data to develop. The mere availability of data is not enough. Artificial intelligence needs good data. Incomplete or biased data can exacerbate problems. Good data, however, might be copyrighted or restricted, which poses a problem: where the artificial intelligence’s input infringes copyright, the output may infringe too. This chapter touches on the ways copyright and privacy laws might adapt to accommodate the expected changes. It discusses legal alternatives and exceptions such as fair dealing, sui generis legislation or a specific exemption for data mining and AI ‘training’.
Procedural Content Generation for General Video Game Level Generation

With the passage of time, video games are becoming more complex, and their development incurs greatertime and cost. The creation of video gaming content such as levels, maps, textures and so on represent a largepart of the overall cost of game development. Procedural Content Generation (PCG) is a method of generatingcontent via a pseudo-random process. Level generation has been the most signicant and oldest problem in thePCG domain. The majority of the PCG level generators are specic to a particular game, content is generatedonly for a suited single type and these generators are evaluated mostly by computational metrics, user studiesand tness functions. Considering, the grand goal of general Articial Intelligence, it would be benecial to sculptsolutions that are applicable to a general set of problems. For the level generation problem, this can be achievedby constructing a level generator that generates levels for a set of games and not explicitly for a single game. Inthis research, we have created four dierent type of generators for the GVG-LG framework. The generators followa distinct path and are able to solve multiple problems related to PCG including dynamic diculty adjustment,creation of intelligent controllers, creating aesthetically appealing levels and using patterns as objectives for levelgeneration. In addition, we evaluated all the generators using a variety of techniques. The experimental resultsshow promising results and represent our attempt at general video game level generation.
An Efficient Abnormal Head Event Detection Using Scale Invariant Feature Transform (SIFT)

Inworkplaces or homes security has been an imperative issue. Control of home security framework distantly consistently offers colossal benefits like the outfitting or incapacitating of the cautions, video observing, and energy the executives control separated from protecting the home let loose gate crashes. Considering the most seasoned straightforward techniques for reconnaissance that has a key as the validation component, at that point a move up to a general sort, and now interesting codes for the head observing. The new headway in the correspondence framework has brought the huge use of correspondence devices into our different everyday issues. This work is a constant brilliant hear checking warning framework for unusual occasions on the ongoing techniques, it is made out of the proposed interfaced with PC camera Module, The proposed framework is a framework which can be utilized for reconnaissance and observing applications. The improvement of an effective constant video head location framework is roused by their potential for arrangement in the spaces where security is the primary concern. The proposed framework presents a stage for ongoing video head location and resulting age of an alert condition when the human head is identified. The model comprisesa stage mounted with camera which gives constant criticism of the online test climate.
A study on relationship between leadership stylestowards employee performance at unifieldeducation resources / Nur Aqila Shuib

This research aim to discover the relationship between leadership typestowards employee performance among employees at the Unifield EducationResources. The leadership styles divided into two independent variables which wereautocratic and democratic and the dependent variable was employee performance.Leadership styles and employee performance were essential tools for the success ofany organization in the long terms period. The study adopted correlation researchdesign and simple random sampling were used. The target population was theemployees in the organization. The researcher instrument used was questionnaires.Besides that, finding analysis includes reliability analysis, normality analysis, surveyreturn rate, demographic analysis, correlational coefficient, multiple regression andhypothesis analysis. The researcher also used Statistical Package in the SocialScience Software (SPSS) version 23.0 to analyse the data collected. The resultsderived from the data analyse revealed that there was a relationship betweenindependent and dependent variable. Then, the researcher also made therecommendation for organization in order to improve and employee performance inthe organization. The researcher also made recommendations for future research toimprove the research study in the future.
Raman spectroscopy study of the secondary actinolite in gabbrodiorite intrusive rocks from Varan area, Urumieh-Dokhtar Magmatic Arc, Iran

Mineralogical studies play a key role in deciphering mineral’s formation and associated geochemical processes in geosciences. This paper presents the application of Raman spectroscopy to the characterization of actinolite in rock samples. The studied actinolite was formed as the pseudomorph of primary pyroxene in gabbrodiorite intrusive rock sample collected from Varan area, Urumieh-Dokhtar Magmatic Arc of Iran. The Raman spectra of micrometer-sized actinolite grains embedded in a crude rock sample are compared with the corresponding literature data for actinolite and tremolite in range of 200-1200 cm-1 and 3600-3700 cm-1 region. The results show that the quantitative estimation of Mg# = Mg/(Mg+Fe2+) can be obtained from the fractional intensities of the OH-stretching bands by applying Raman spectroscopy to micrometer-sized actinolite grains in a crude rough rock sample, which is in good agreement with the results from EMPA. The Raman spectroscopy is a fast method and low-cost for quantitative estimation of Mg# in actinolite.
The effect of applying the principle of independence on the quality of internal auditing in the Jordanian companies listed on the Amman Stock Exchange: أثر تطبيق مبدأ الاستقلالية على جودة التدقيق الداخلي في الشركات الأردنية المدرجة ببورصة عمان

This study aimed to identify the effect of applying the principle of independence on the quality of internal auditing on firms listed at the Amman Stock Exchange. To achieve the objectives of the study, the descriptive analytical approach was followed, and the study sample consist of a sample of (100) of employee in the companies that listed on the Amman Stock Exchange. The most important findings of the study are that there is a strong degree of agreement among the study participants on the extent of applying the principle of independence in the companies listed on the Amman Stock Exchange, and the general mean for its phrases was (3.86). The study also concluded that there is a good and positive degree of agreement on the quality of the internal audit found in the Jordanian firms listed on the Amman Stock Exchange from the viewpoint of workers in companies at a good level, and The general mean for its phrases was (3.35). Finally, the study found that there was a significant effect on applying the principle of independence to the quality of internal audit in the firms listed on the Amman Stock Exchange. And that the application of the principle of independence in the Jordanian companies listed on the Amman Stock Exchange is responsible for enhancing 27.5% of the quality of internal auditing, which is a good and effective percentage.
A MULTI-AGENT SYSTEM FRAMEWORK FOR CLOUD RESOURCES ALLOCATION

As cloud computing becomes increasingly attractive to entrepreneurs and resource consumers, researchers have recognized that an integrated infrastructure is needed to explore the potential of the cloud and enhance its efficiency and features. The primary people involved in cloud system operations are usually those who use the cloud, search the cloud provider's website, and make the purchase. This challenge is caused by the lack of a mechanism to provide negotiation interfaces through cloud providers to deal with them dynamically. In addition, one of the most common obstacles that consumers face is choosing resources based on their requirements at an affordable cost. Therefore, the goal of the proposed system is to simplify the process of allocating cloud computing resources to the consumer by choosing the most appropriate offer based on the cloud computing architecture and its integration with the Multi-Agent System (MAS) framework. Accordingly, the resulting system is more efficient and responsive, and negotiations can be conducted easily. In order to find mutually appropriate solutions in terms of service quality and price. The proposed system is applicable to all types of cloud deployments. It has been built using Java programming language and uses CloudSim and JADE as the two types of emulators used in the design and implementation of the system.
Qualitative, Pragmatic and Hermeneutic Inquiries in Electroacoustic Compositions

The music composers of today have to define their composition techniques anew within their every composition project. Instead of resorting to existing forms and techniques, a composer sees an empty canvas ahead of them every time they start a new project: among other things, they need to find an answer to the question how to define the overall form of the composition, as well as a working system of selecting the rhythms and pitch material? When talking about musical works based on complex forms that may also include an electronic real-time system, discussing the analytical basis preceding the actual compositional stage is inevitable. I argue that music analysis and composing go hand in hand: in order to build up a musical system that works in a coherent manner, a thorough pre-structuring phase must be conducted. This chapter highlights this issue through practice-based, qualitatively discussed case studies from the composer’s perspective.
Ground-Truth or DAER: Selective Re-Query of Secondary Information

Many vision tasks use secondary information at inference time -- a seed -- to assist a computer vision model in solving a problem. For example, an initial bounding box is needed to initialize visual object tracking. To date, all such work makes the assumption that the seed is a good one. However, in practice, from crowdsourcing to noisy automated seeds, this is often not the case. We hence propose the problem of seed rejection -- determining whether to reject a seed based on the expected performance degradation when it is provided in place of a gold-standard seed. We provide a formal definition to this problem, and focus on two meaningful subgoals: understanding causes of error and understanding the model's response to noisy seeds conditioned on the primary input. With these goals in mind, we propose a novel training method and evaluation metrics for the seed rejection problem. We then use seeded versions of the viewpoint estimation and fine-grained classification tasks to evaluate these contributions. In these experiments, we show our method can reduce the number of seeds that need to be reviewed for a target performance by over 23% compared to strong baselines.
Telling the What While Pointing to the Where: Multimodal Queries for Image Retrieval

Most existing image retrieval systems use text queries as a way for the user to express what they are looking for. However, fine-grained image retrieval often requires the ability to also express where in the image the content they are looking for is. The text modality can only cumbersomely express such localization preferences, whereas pointing is a more natural fit. In this paper, we propose an image retrieval setup with a new form of multimodal queries, where the user simultaneously uses both spoken natural language (the what) and mouse traces over an empty canvas (the where) to express the characteristics of the desired target image. We then describe simple modifications to an existing image retrieval model, enabling it to operate in this setup. Qualitative and quantitative experiments show that our model effectively takes this spatial guidance into account, and provides significantly more accurate retrieval results compared to text-only equivalent systems.
Autonomía y autorregulación: aplicación de competencias en tecnología e informática

The present investigation was aimed at ascertaining the autonomy and self-regulation skills in a group of Grade 11 students Technical College District Julio Florez in the subjects of technology and information. In order to identify the competencies was an experience in which students design on paper made robot prototype and subsequently digitized into a computer software; subsequently materialized in the technology workshop. Significant changes were noted in the attitudes of students and it was evident as between students stood and demanded performance goals according to the tasks imposed are obvious changes in the levels of regulation by students, these results are part of research in application of information technology researchers institutional educational knowledge allows modification in the teaching-learning methodologies.
Giving up Privacy for Security: A Survey on Privacy Trade-off During Pandemic Emergency

While the COVID-19 pandemic continues to be as complex as ever, the collection and exchange of data in the light of fighting coronavirus poses a major challenge for privacy systems around the globe. The disease’s size and magnitude are not uncommon but it appears to be at the point of hysteria surrounding it. Consequently, in a very short time, extreme measures for dealing with the situation appear to have become the norm. Any such actions affect the privacy of individuals in particular. In some cases, there is intensive monitoring of the whole population while the medical data of those diagnosed with the virus is commonly circulated through institutions and nations. This may well be in the interest of saving the world from a deadly disease, but is it appropriate and right? Although creative solutions have been implemented in many countries to address the issue, proponents of privacy are concerned that technologies will eventually erode privacy, while regulators and privacy supporters are worried about what kind of impact this could bring.While that tension has always been present, privacy has been thrown into sharp relief by the sheer urgency of containing an exponentially spreading virus. The essence of this dilemma indicates that establishing the right equilibrium will be the best solution. The jurisprudence concerning cases regarding the willingness of public officials to interfere with the constitutional right to privacy in the interests of national security or public health has repeatedly proven that a reasonable balance can be reached.
Smart contracts, blockchain and intellectual property: challenges and reality

The present chapter will look at the possible application of smart contracts in the intellectual property arena in general, but it will specifically discuss mostly copyright solutions, although a few uses apply to different areas of protection. This presents a few challenges, at the time of writing many of the proposals that will be discussed have not yet been implemented, or are in a prototype level, and as such we may have to assume their viability based on nothing other than a few examples that have not been fully tested. Similarly, legal discussions about the blockchain and smart contracts tend to be surrounded by considerable hype, often fuelled by commercial interests, and it is often difficult to separate facts from sales pitches. This is why this work will try to take a more sceptical approach to the phenomenon.
SELM: Software Engineering of Machine Learning Models

One of the pillars of any machine learning model is its concepts. Using software engineering, we can engineer these concepts and then develop and expand them. In this article, we present a SELM framework for Software Engineering of machine Learning Models. We then evaluate this framework through a case study. Using the SELM framework, we can improve a machine learning process efficiency and provide more accuracy in learning with less processing hardware resources and a smaller training dataset. This issue highlights the importance of an interdisciplinary approach to machine learning. Therefore, in this article, we have provided interdisciplinary teams’ proposals for machine learning.