Reviewerly/exHarmony huggingface dataset:
Distributed compression and decompression for big image data: LZW and Huffman coding

In today’s era, digital data are being created and transmitted primarily in the form of images and videos. Storing such a huge number of images and transmitting them requires a lot of computer resources such as storage and bandwidth. So, instead of storing the image data as is, if we compress and store it, it saves a lot of resources. Image compression is the act of removing the maximum possible redundant data from an image and maintaining only the non-redundant data. To compress and decompress such big image data, a distributed environment with a map-reduce paradigm using Hadoop distributed file system and Apache Spark is used. In addition to these, Microsoft Azure cloud environment with infrastructure as a service is also used. Various setups such as a single system, 1 + 4 node cluster, 1 + 15 node cluster, and 1 + 18 node cluster cloud infrastructure are used to show the time comparisons among these setups with the self-created large image dataset. On these four self-made clusters, more than 100 million (109,670,400) images are compressed and decompressed; the execution times are compared with two of the traditional image compression methods: Lempel-Ziv-Welch (LZW) and Huffman coding. Both the LZW and Huffman coding are lossless image compression techniques. LZW removes both spatial and coding redundancies and whereas the Huffman coding removes only coding redundancy. These two compression techniques: LZW and Huffman are just placeholders, these can be replaced with any other compression technique for large image data. In our work, we have used compression ratio, average root mean square error (ARMSE), and average peak signal to noise ratios to validate that the compression and decompression process for each technique is exactly the same irrespective of the number of systems used, distributed or not.
Construction of Online Reading Corpus Based on SQL Server Database Management System

New media technology refers to the fact that new media based on Internet technology has inherent technical advantages and information service functions as media. It is the best choice for the network economy to connect with the media industry. With the advent of the new media era on the Internet and changes in media communication methods, new media can be derived from smart devices to obtain information and content, and it can also be distributed on smart devices. Users correspond to different media portals in different usage scenarios. This paper analyzes the advantages of college English online reading, and builds a cloud storage structure model consisting of a data storage layer, a basic management layer, an application interface layer and a user access layer; based on the SQL Server database management system, the data storage structure is designed; practice application strategies are proposed.
Freehand Stereotactic Image-Guidance Tailored to Neurotologic Surgery

Hypothesis: The use of freehand stereotactic image-guidance with a target registration error (TRE) of μTRE + 3σTRE < 0.5 mm for navigating surgical instruments during neurotologic surgery is safe and useful. Background: Neurotologic microsurgery requires work at the limits of human visual and tactile capabilities. Anatomy localization comes at the expense of invasiveness caused by exposing structures and using them as orientation landmarks. In the absence of more-precise and less-invasive anatomy localization alternatives, surgery poses considerable risks of iatrogenic injury and sub-optimal treatment. There exists an unmet clinical need for an accurate, precise, and minimally-invasive means for anatomy localization and instrument navigation during neurotologic surgery. Freehand stereotactic image-guidance constitutes a solution to this. While the technology is routinely used in medical fields such as neurosurgery and rhinology, to date, it is not used for neurotologic surgery due to insufficient accuracy of clinically available systems. Materials and Methods: A freehand stereotactic image-guidance system tailored to the needs of neurotologic surgery-most importantly sub-half-millimeter accuracy-was developed. Its TRE was assessed preclinically using a task-specific phantom. A pilot clinical trial targeting N = 20 study participants was conducted (ClinicalTrials.gov ID: NCT03852329) to validate the accuracy and usefulness of the developed system. Clinically, objective assessment of the TRE is impossible because establishing a sufficiently accurate ground-truth is impossible. A method was used to validate accuracy and usefulness based on intersubjectivity assessment of surgeon ratings of corresponding image-pairs from the microscope/endoscope and the image-guidance system. Results: During the preclinical accuracy assessment the TRE was measured as 0.120 ± 0.05 mm (max: 0.27 mm, μTRE + 3σTRE = 0.27 mm, N = 310). Due to the COVID-19 pandemic, the study was terminated early after N = 3 participants. During an endoscopic cholesteatoma removal, a microscopic facial nerve schwannoma removal, and a microscopic revision cochlear implantation, N = 75 accuracy and usefulness ratings were collected from five surgeons each grading 15 image-pairs. On a scale from 1 (worst rating) to 5 (best rating), the median (interquartile range) accuracy and usefulness ratings were assessed as 5 (4-5) and 4 (4-5) respectively. Conclusion: Navigating surgery in the tympanomastoid compartment and potentially in the lateral skull base with sufficiently accurate freehand stereotactic image-guidance (μTRE + 3σTRE < 0.5 mm) is feasible, safe, and useful. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT03852329.
Digital Transformation in Higher Education: A Barrier Framework

The purpose of this study is to highlight the barriers which need to be considered when implementing digital transformation in higher education based on literature and real case. First, a systematic literature review on the barriers to digital transformation in higher education was conducted to identify the barriers. Second, to categorize the findings of the literature review, this study implemented a reference barrier model which consists of four categories (contextual barrier, social barrier, technical barrier, and cultural barrier). Finally, an exploratory case study in the specific context of digital transformation in higher education was carried out to validate the contextualized barrier framework. This study provided a contextualization barrier framework that outlines 22 barriers. Through an evaluation, the relevance level of all barriers was assessed and obtained between 2.88 and 4.00 (scale of 1-5), which means that the finding of the literature review in this study was valid and able to capture the real situations. The result of this research can give a framework for further research in the effort to minimize the effect of each barrier. In addition, the proposed framework was an initial step to standardize the description of barriers and could be used as a starting point to the effectiveness of the formulation of strategies and policies that will be applied.
Chapter 19: The Peñasquito Gold-(Silver-Lead-Zinc) Deposit, Zacatecas, Mexico

Abstract Peñasquito is an Au-Ag-Zn-Pb deposit and currently the principal Au-producing mine in Mexico. It is the most recent major discovery in the historically important Concepción del Oro mining district. Current Au reserves plus historic production at Peñasquito stand at 12.67 Moz, in addition to 527 Moz Ag, 3,600 lb Pb, and 8,000 lb Zn in remaining proven and probable reserves. Mineralization is centered on the Peñasco and Brecha Azul diatreme breccias, which cut an Upper Jurassic to Upper Cretaceous marine carbonate-dominated sedimentary sequence, which underwent folding during the Laramide orogeny. The diatreme breccias and associated mineralization are associated with early Oligocene quartz-feldspar porphyries dated at 34.4 ± 0.4 to 33.7 ± 0.4 Ma and thus 3 to 10 m.y. younger than the other skarn and polymetallic deposits known in the district. The Peñasco diatreme is about 1 km in diameter and hosts epithermal-style disseminated mineralization, whereas the contiguous Cretaceous carbonaceous and calcareous siltstone and interbedded sandstone of the Caracol Formation is the principal host for stockwork and manto-type, massive base metal sulfide mineralization. Skarn-type mineralization is Cu-Zn rich, extends to the current depth of drilling some 2 km below the premine surface, and is hosted by the Jurassic-Cretaceous sequence beneath the Caracol Formation. In addition, weakly developed stockwork Mo (±Cu) mineralization has also been intersected by drilling at depths of nearly 2 km.
Effects of Interactivity and Presentation on Review-Based Explanations for Recommendations

User reviews have become an important source for recommending and explaining products or services. Particularly, providing explanations based on user reviews may improve users’ perception of a recommender system (RS). However, little is known about how review-based explanations can be effectively and efficiently presented to users of RS. We investigate the potential of interactive explanations in review-based RS in the domain of hotels, and propose an explanation scheme inspired by dialogue models and formal argument structures. Additionally, we also address the combined effect of interactivity and different presentation styles (i.e. using only text, a bar chart or a table), as well as the influence that different user characteristics might have on users’ perception of the system and its explanations. To such effect, we implemented a review-based RS using a matrix factorization explanatory method, and conducted a user study. Our results show that providing more interactive explanations in review-based RS has a significant positive influence on the perception of explanation quality, effectiveness and trust in the system by users, and that user characteristics such as rational decision-making style and social awareness also have a significant influence on this perception.
Towards a specification theory for fuzzy modal logic

Fuzziness, as a way to express imprecision, or uncertainty, in computation is an important feature in a number of current application scenarios: from hybrid systems interfacing with sensor networks with error boundaries, to knowledge bases collecting data from often non-coincident human experts. Their abstraction in e.g. fuzzy transition systems led to a number of mathematical structures to model this sort of systems and reason about them. This paper adds two more elements to this family: two modal logics, framed as institutions, to reason about fuzzy transition systems and the corresponding processes. This paves the way to the development, in the second part of the paper, of an associated theory of structured specification for fuzzy computational systems.
Exploring Timbre Disentanglement in Non-Autoregressive Cross-Lingual Text-to-Speech

In this paper, we study the disentanglement of speaker and language representations in non-autoregressive cross-lingual TTS models from various aspects. We propose a phoneme length regulator that solves the length mismatch problem between IPA input sequence and monolingual alignment results. Using the phoneme length regulator, we present a FastPitch-based cross-lingual model with IPA symbols as input representations. Our experiments show that language-independent input representations (e.g. IPA symbols), an increasing number of training speakers, and explicit modeling of speech variance information all encourage non-autoregressive cross-lingual TTS model to disentangle speaker and language representations. The subjective evaluation shows that our proposed model can achieve decent naturalness and speaker similarity in cross-language voice cloning.
Deep-Ocean Cooling May Have Offset Global Warming Until 1990

New machine learning techniques have estimated ocean temperatures below 2,000 meters, leading to a new model of warming trends.
Collaborative Efforts and Success Story of an <scp>Open‐Learning</scp> Program: Partnership Growth of the Research Data Management Librarian Academy (<scp>RDMLA</scp>)

Abstract Launched in October 2019, the Research Data Management Librarian Academy (RDMLA) addresses the learning gaps in RDM training. Through a unique partnership among practicing librarians, LIS faculty, and industry, the RDMLA has produced a dynamic open learning experience, highlighting the benefits of collaboration and skill‐sharing. This collaboration's success lies in how the project leveraged each partner's strengths and experience while centering on the shared purpose, dedication to equitable learning, and mutual respect among the team members. This panel focuses on the collaborative efforts undertaken by the RDMLA leadership and instructors to develop an open‐access professional development education program. Five panelists will share their experience working on this large collaborative project from varying perspectives, the lessons learned while developing their content, the challenges they encountered, and their understanding of the benefits of such a collaborative endeavor in producing free, open‐access learning to foster a community of practice in RDM.
The Influence of Message Direction on Attribute Benefit and Purchase Intention Applied to the Logical Design of an AI Chatbot

This study aims to explore the influence of various possible combinations of consumer attribute benefits and the message direction provided by merchants on the final purchase intention of consumers. A two-factor experimental design was used to collect data from Generation Z consumers. Four experimental combination scenarios were designed based on consumer attribute benefits (hedonic or utilitarian) and message direction (positive or negative messages). A total of 160 valid samples were obtained, and the influence of variable-final purchase intention was analyzed. The results showed that the combination of product attributes and message direction has a significant impact on purchase intention and that hedonic products should be recommended to process-benefit consumers through positive messages. However, chatbots should choose utilitarian products and negative messages to effectively improve consumers’ purchase intention and willingness. In practical application, by finding out the best correspondence method of message transmission and providing the AI chatbot with a reference for the logical construction of content transmission, the communication efficiency between merchants and consumers can be enhanced, and the scientific and technological service capability of merchants can be improved.
A Novel Harmony Search Based Method for Noise Minimization on EEG Signals

Big data is a topic that is increasing in popularity day by day, and new techniques are being developed for the optimization processes performed on it. Harmony Search (HS) algorithm, inspired by music and harmonies, is an intuitive algorithm and has been used for the optimization of many problems. In this study, a new technique called source-linked HS algorithm (slinkHSA) focusing on big data optimization problems is presented. Experimental results were obtained with the slinkHS algorithm, results were compared with other popular metaheuristic algorithms and unmodified HS algorithm. The obtained results showed that the technique applied in the slinkHS algorithm adapted to the problem better, in this way better results could be obtained than other algorithms compared.
pygrank: A Python package for graph node ranking

We introduce pygrank, an open source Python package to define, run and evaluate node ranking algorithms. We provide object-oriented and extensively unit-tested algorithmic components, such as graph filters, post-processors, measures, benchmarks, and online tuning. Computations can be delegated to numpy, tensorflow, or pytorch backends and fit in back-propagation pipelines. Classes can be combined to define interoperable complex algorithms. Within the context of this paper, we compare the package with related alternatives, describe its architecture, demonstrate its flexibility and ease of use with code examples, and discuss its impact.
SECURITY AND PRIVACY ISSUES RELATED TO QUICK RESPONSE CODES

Quick response codes are widely used for tagging products, sharing information and making digital payments due to their robustness against distortion, error correction features and small size. As the adoption and popularity of quick response codes have grown, so have the associated security and privacy concerns. This chapter discusses advancements in quick response codes and the major security and privacy issues related to quick response codes.
New techniques for bounding stabilizer rank

In this work, we present number-theoretic and algebraic-geometric techniques for bounding the stabilizer rank of quantum states. First, we refine a number-theoretic theorem of Moulton to exhibit an explicit sequence of product states with exponential stabilizer rank but constant approximate stabilizer rank, and to provide alternate (and simplified) proofs of the best-known asymptotic lower bounds on stabilizer rank and approximate stabilizer rank, up to a log factor. Second, we find the first non-trivial examples of quantum states with multiplicative stabilizer rank under the tensor product. Third, we introduce and study the generic stabilizer rank using algebraic-geometric techniques.
Prototype of a Small, Agile, Drone-Based SAR System and Preliminary Focusing Results

In the past few years frequency-modulated continuous-wave synthetic aperture radar enabled the miniaturizing of carrier systems. Small aircraft as well as UAV/drones are nowadays capable of producing electro-magnetic radar images of the earth surface. In this paper, we present our drone hardware setup, its operational mode including a quasi real-time downlink and produced images via time domain back projection. Furthermore, using the airborne system MIRANDA-35 we present preliminary results of a new autofocusing technique targeting modern UAV SAR applications. The algorithm is constructed as an optimal path problem.
Comparison of Satisfaction and Academic Achievement between Field and Online Practice of Nursing Students

Purpose: This study aimed to compare the level of satisfaction and academic achievement of nursing students'' clinical practice achievement between field and online practice. Methods: In this descriptive research, we recruited junior and senior nursing students who experienced both field and online practice from nursing college in Daegu and Gyeongbuk, Korea. Data were collected using the online survey and analyzed via a t-test, ANOVA, and paired t-test using SPSS V 25.0. Results: There was no statistically significant difference in the satisfaction of practice between field and online practice types. However, academic achievement was higher in the field group than in the online group. Out of five points, the scores of field practice and online practice were 3.66 points and 3.39 points, respectively, which indicated that academic performance was higher in field practice than online practice (t=6.21, p<.001). Conclusion: Field practice has been shown to achieve higher academic performance than online practice. Hence, research is needed in order to develop suitable field practice models for the New Normal era in preparation for situations that practice is limited, such as COVID-19 and future outbreaks.
Generating correct initial page tables from formal hardware descriptions

Modern hardware platforms are increasingly complex and heterogeneous. System software uses a hodgepodge of different mechanisms and representations to express the memory topology of the target platform. Considerable maintenance effort is required to keep them in sync while often sharing is impossible due to hard-coded values. Incorrect platform-specific values in the hardware initialization sequence can lead to security critical and hard-to-find bugs because of misconfigured translation hardware, inaccessible devices, or the use of bad pointers.
Low-latency Serverless Computing: Characterization, Optimization and Outlooking: JCC 2021 Invited Keynote

Summary form only given, as follows. The complete presentation was not made available for publication as part of the conference proceedings. Serverless computing promises cost-efficiency and elasticity for high-productive software development. To achieve this, the serverless computing platform must address two challenges: strong isolation between function instances, and low startup latency to ensure user experience. In this talk, I will first present a characterization of state-of-the-art serverless platform and derive several key metrics, which collectly forms a systematic methodology and a benchmark called severlessbench. Then, I will show how severless platform can be optimized for (sub-)millisecond startup latency for both normal and condential severless computing. Finally, I will present an outlook on challenges and opportunities of serverless comptuting, including how to make it secure and efficient for joint cloud computing.
Features of ore-metasomatic zonation of ore area Freedom of Malmyzh gold-copper porphyry deposit

Present the ore-metasomatic zonation of the Freedom area, one of the ore centers of the Malmyzh Au-Cu porphyry deposit. The central part of ore-mineralization zones composes of quartz-sericite and biotite-K-feldspar metasomatites which carry relatively rich gold-copper. Flank zones are composed mainly of phyllic and propylites. These zones are characterized by increase content of lead, manganese and zinc. A positive correlation was found in two groups of elements: Mo–Cu–Au and Pb–Zn–Mn. Based on the analysis of the vertical change in the contents of ore components and their relationships, presumably, modern erosional level takes upper-ore position.
Real-time Robot Path Planning using Rapid Visible Tree

This paper proposes a new path planning strategy - the Rapid Visible Tree (RVT) algorithm to guide a robot to its goal in a complex environment without dangerous collisions. By fusing the visibility information with the classic tree-based searching method, RVT only takes the noisy points locally acquired from the environment as input and computes the visible region at each location to decide the growing direction of the path tree. Compared with traditional methods, RVT is more efficient, lightweight, and robust. We demonstrate that the RVT algorithm can not only complete the path planning task in real-time but also explore the unknown environment in simulated or real scenes.
Joint CD and DGD estimation enabled by FrFT based time-frequency reconstruction

We developed a joint CD and DGD estimation algorithm using Fractional Fourier Transform (FrFT) based time-frequency reconstruction and multi-task deep neural network (MT-DNN). The estimation error for CD and DGD is 217ps/nm and 0.46ps, respectively.
Programming - What is Next?

The paper provides an introduction to the track: “Programming - What is Next?”, organized by the authors as part of ISoLA 2021: the 9th International Symposium On Leveraging Applications of Formal Methods, Verification and Validation. A total of 14 papers were presented in the track, with responses to the question: what are the trends in current more recent programming languages, and what can be expected of future languages?. The track covers such topics as general-purpose programming languages, domain-specific languages, formal methods and modeling languages, textual versus graphical languages, and application programming versus embedded programming.