Reviewerly/exHarmony huggingface dataset:
Age and Gender Prediction using Caffe Model and OpenCV

Automatic classification of age and gender has become crucial for a rising number of applications, especially as social platforms and social media have risen. However, there is still substantial lack of performance of present approaches in real-world photos, especially when compared to the enormous performance jumps reported lately in the associated facial recognition job. In this research we show that a considerable gain in performance may be achieved by the application of convolution neural networks (CNN). This work is primarily designed to construct an algorithm that accurately guesses a person's age and gender.Haar cascade is one of the most often utilised approaches. In this research we provide a model that can help Haar Cascade to determine a person's gender. The model trained the classifier as positive and negative pictures using diverse photos of men and women. Various face characteristics are removed. With the help of Haar Cascade, the classifier determines if the picture input is men or women. Even with insufficient data, it functions effectively. A deep education framework created with Caffe is used to do the age or sex approximation task. Our model is able to detect multiple faces in single image and predict age and gender of all faces present in the image.
Blockchain Powered Mutual Authentication and Access Control Protocol

With the advancement in the network connectivity, services can be subscribed for limited period of time. Subscribing for certain services is always an economic option rather than owning them. Implementing adequate procedures in the establishments, meeting the access control policies is challenging. Although the essential procedures are implemented using the centralized scheme where the single central server cater to the access control requests and the authorization mechanisms with the help of the stored identifiable attributes of the workstations in the web. In our article, we are proposing a blockchain powered lightweight, decentralized and secure framework for mutually authenticating the participating entities and levy the access control model among them. In our protocol, the device administrators (DA) can maintain their signed device policies for any of its services in the blockchain network which increases its visibility to more subscribers and at the same time, DAs can get rid of tedious job of authenticating each and every user/subscriber. On the other hand, users can also come to know about the wide range of services provided by different service providers and can avail appropriate service with the optimal constraints. We used elliptic curve cryptography (ECC) to transmit the secret sign parameters which makes our protocol lightweight. Secret sign parameters are used to verify the signature of any entity at the other end.
PAYMENTS AND BLOCKCHAIN/CRYPTO-ASSETS

The mainstream use of distributed ledger technology and block-chain based crypto-assets could represent the biggest change to the payments landscape within the next decade. This chapter provides a high-level background on blockchain and crypto-assets before considering the emergence of stablecoins as an influence on the payments landscape and analysing the present and potential future UK and EU regulatory approaches to the use of crypto-assets in financial services.
Categorization optimization in the construction of thematic products

One of the steps in the construction of thematic products is the categorization. This process is done by partitioning the range of values of a given feature into several subranges and associating a new value, in this case ordinal, to all instances that are in that subrange. The objective of this work is to propose an innovative pre-categorization process that applies a computational search method to maximize the accuracy of thematic products during the classification stage. The theme feature used is the Above Ground Biomass (AGB), which estimation model is built over synthetic aperture radar features. A system is developed in Java script using the Weka data mining class library. The proposed heuristic is the hill climbing greedy, with the Kappa coefficient as the objective function. The results obtained shows that the proposed Categorization Optimization algorithm demonstrated the ability to obtain new states with subintervals of categories that increased the Kappa agreement index to 1.0 with much lower computational cost than the exhaustive search. The thematic products constructed maintained the representativeness of the study area while increasing in thematic accuracy.
Audio Summary

Lead–zinc–copper (Pb–Zn–Cu) deposits in the western Kunlun Orogen of China are mostly distributed along the Keziletao–Kusilafu fault zones in the Palaeozoic clastic–carbonate rocks, which formed in a late Palaeozoic subsidence belt at the south-west margin of the Tarim platform. Geological and geochemical studies were conducted on these deposits including detailed field observation, petrographic study, and geochemical and isotopic analyses of sulfur, lead, strontium, rhenium–osmium, and argon isotopes, as well as fluid inclusion geochemistry. The characteristics of the deposits include: (1) Except for the Tiekelike Pb–Cu deposit associated with mid-Devonian rocks, all of the other deposits were developed in the lower layers of the early Carboniferous strata. These strata mostly comprise sedimentary dolomitic limestone, sandy limestone, black limestone, and calcareous shale. (2) The ore bodies are stratiform and host veins. The stratiform ores are coeval with host rocks (yielding ore-forming ages of 331–337 Ma), while the vein ore bodies are mostly massive deposits formed at 206–235 Ma. The isotopic compositions of the sulfur and lead reveal that the ore-forming elements originated from various sources. (3) The mineralization in cements of brecciated ore is a veinlet type, while in the breccias it is a disseminated type. The stratoid, disseminated, and framboidal structures of the ore reveal the synsedimentary ore-formation. However, the veins, mesh-veins, and massive structures indicate late stage hydrothermal mineralization. (4) The principal metallic minerals include sphalerite, galena, and pyrite, while the secondary oxide minerals include variable distributions of cerussite, anglesite and limonite. The gangue minerals include dolomite, calcite, quartz, sericite, and gypsum, with minor chert and barite. (5) The original host rocks likely experienced dolomitization, calcitization, and minor silicification. The ore deposits underwent hydrothermal alterations, sub-greenschist facies metamorphism, and brecciation. The ore deposits may have initially formed via syndeposition in a subsidence belt along the southwest margin of the late Paleozoic Tarim platform; these deposits were further modified during later hydrothermal alteration and orogenesis during the Triassic period.
Sistem Informasi Perpustakaan Berbasis website

School libraries must be built and developed properly in order to provide a service to students, library admins, and leaders in finding a book reference. This information service can also be done well and can be seen in the ease of members to get accurate and fast information, so from changing the form of data processing that is still manual to computer-based data processing is one of the innovations to overcome delays in information and difficulty processing detailed data collection of existing books. The Diponegoro Majenang Middle School library is still using the manual method, there is no website or application program that can process class data, member data, loan and return transactions, loan transaction reports, returns and late returns. is due on the due date for returning to the library. The method used in making this website-based library information system is the waterfall method which consists of several stages, namely Analysis, Design, Coding, Testing and Maintenance. With the development of data communication technology, school library information systems can be built as a means of online library information systems (website-based).
Detection of Mobile Phone Usage While Driving Using Computer Vision and Deep Learning

This work proposes a computer vision-based detection of the usage of mobile phone while driving. The majority of the existing works is based on in-car camera system mounted inside the vehicles, which is more suitable to be implemented as a driver assistance system. However, there are no existing datasets that are captured based on the camera system mounted outside the vehicles. Thus, the total amount of dataset acquired is limited for this work. Since there are no datasets available for this project, the images are captured and collected using Fujifilm XT 10 with XF 35 mm f2 lens at an overhead bridge nearby Spice Arena, Penang, Malaysia. There is a total of 1351 images captured and collected. The proposed system framework is developed based on Faster R-CNN with Inception-V2 architecture. It is based on detection evaluation metrics applied by COCO. In terms of overall detection accuracy, it obtained 88.71% for the accuracy.
A Framework for Virtual Co-Urban Design

Traditionally, professionals’ urban design methods and tools do not allow users to be active in the design process. On the contrary, participatory design processes build the citizen’s capacity of traditionally omitted city building procedures. The participants act as individual actors in the participatory design process, and a social hierarchy exists among them. The visual information adheres to the design artefacts used in the process stay in assumptions and leads to an unsolved conclusion with an expense of time. The article argues that immersive virtual reality equipped with producing instantaneous design artefacts and design engagement set-up brings conclusion at the early stage of an urban design process. The design task, the perceptual understanding of the virtual environment and the feeling of affiliation are the catalysts to keep the flow of the conversation. The design experts set design tasks understanding the capacity of the virtual tools and the need for the design problem. The paper presents a conceptual framework to develop a virtual tool based on participatory mindsets and principles experimented with earlier. It discusses how virtual media leverage citizens of a neighbourhood in the design process. In the end, the article puts light on the scope of using collaborative virtual reality tools on a shared understanding of collective design discussion in regenerating and developing urban spaces.
Towards a Taxonomy of Human-Computer Interaction (HCI) Methods Based on a Survey of Recent HCI Researches

In the field of Human-Computer Interaction, there have been many studies published in journals, and these studies have adopted a variety of research methods. However, there has not been a systematic and sophisticated taxonomy of the research methods used in HCI studies. This survey reviews the research methods of thirty HCI journals published in the last six years and originally presents three dimensions concerning research methods taxonomy. These three dimensions are: qualitative or quantitative research analysis, applicable to the present or future, and the adoption of software or hardware technology. Based on these three dimensions, the survey further generates eight sub-categories and classifies the thirty HCI journals into appropriate blocks based on their research methods attributions. The results of this survey will be helpful in guiding future scholars to select appropriate research methods and avoid detours in future HCI studies.
A Reconstruction Method for Missing Data of electricity users Using Extremely Randomized Tree

Data assets of electricity users are very important to the production, operation and maintenance of power grid, but data loss may occur during the collection, communication, and storage of power data. Therefore, this paper proposes a cyclic regression reconstruction method based on extremely randomized tree for missing data of electricity users. This method transforms the problem of missing data reconstruction into a regression problem, and introduces a regression reconstruction model based on extremely randomized tree, which overcomes the shortcomings of slow training and poor generalization ability of the deep forest method. Moreover, missing samples are sequentially reconstructed in a specific order, and the error stacking problem of sequential regression is solved through cyclic regression reconstruction. Finally, simulation verification is carried out by taking the actual measurement data set of a certain electricity users in China as an example. The results show that the proposed method has higher reconstruction accuracy and shorter simulation time than existing reconstruction methods, meaning that it is easy to popularize in engineering applications.
Passively stabilized single-photon interferometer

A single-photon interferometer is a fundamental element in quantum information science. In most previously reported works, single-photon interferometers use an active feedback locking system to stabilize the relative phase between two arms of the interferometer. Here, we use a pair of beam displacers to construct a passively stable single-photon interferometer. The relative phase stabilization between the two arms is achieved by stabilizing the temperature of the beam displacers. A purely polarized single-photon-level pulse is directed into the interferometer input port. By analyzing and measuring the polarization states of the single-photon pulse at the output port, the achieved polarization fidelity of the interferometer is about 99.1±0.1%. Our passively stabilized single-photon interferometer provides a key element for generating high-fidelity entanglement between a photon and atomic memory.
Best Practices to Secure API Implementations in Core Banking System (CBS) in Banks

The use of application programming interfacing (APIs) is showing a world of plausible outcomes for different industries especially financial institutions. APIs are an easy way to integrate applications within and across enterprises. To enable the flow of information between applications, to access customer data, to create innovative products tailored to consumer, market and regulatory needs, our banks are using APIs with Core Banking Solutions (CBS). While they are quick and easy to implement, they can be dangerous if not secured properly, putting the entire bank at risk of exposure to hackers. Therefore, API security should be well-architected, designed and managed, prior to actually starting the development of APIs. There is no proven technique to ensure foolproof APIs, but a well-designed and rightly implemented API can greatly mitigate the security risks and banks can secure the benefits of APIs. The purpose of this study was to investigate and analyze the APIs implementation risks in Core Banking System and recommend the best practices to secure APIs implementation in Core Banking System in Banks.
Secondary Roles

Secondary Roles are a newer addition to the RBAC system in Snowflake. In the past few chapters, we’ve run into some limitations with how primary roles work, specifically for users that work cross-functionally and need to assume multiple roles. One of the solutions I mentioned was role inheritance, which we will cover in the next chapter. The other solution I mentioned is secondary roles.
Large-Scale Machine Learning

Written by leading authorities in database and Web technologies, this book is essential reading for students and practitioners alike. The popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. This book focuses on practical algorithms that have been used to solve key problems in data mining and can be applied successfully to even the largest datasets. It begins with a discussion of the MapReduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream-processing algorithms for mining data that arrives too fast for exhaustive processing. Other chapters cover the PageRank idea and related tricks for organizing the Web, the problems of finding frequent itemsets, and clustering. This third edition includes new and extended coverage on decision trees, deep learning, and mining social-network graphs.
Memory Effects in High-Dimensional Systems Faithfully Identified by Hilbert–Schmidt Speed-Based Witness

A witness of non-Markovianity based on the Hilbert-Schmidt speed (HSS), a special type of quantum statistical speed, has been recently introduced for low-dimensional quantum systems. Such a non-Markovianity witness is particularly useful, being easily computable since no diagonalization of the system density matrix is required. We investigate the sensitivity of this HSS-based witness to detect non-Markovianity in various high-dimensional and multipartite open quantum systems with finite Hilbert spaces. We find that the time behaviors of the HSS-based witness are always in agreement with those of quantum negativity or quantum correlation measure. These results show that the HSS-based witness is a faithful identifier of the memory effects appearing in the quantum evolution of a high-dimensional system with a finite Hilbert space.
Breaking the barriers to interdisciplinarity: Contributions from the Environmental Research Infrastructures

&amp;lt;p&amp;gt;As science and technology evolve, interdisciplinary targets are anything but static, introducing additional levels of complexity and challenging further the initiatives to break the barriers to interdisciplinary research. For over a decade the community of the Environmental Research Infrastructures, forming the ENVRI cluster, has been building strong foundations to overcome these challenges and benefit the environmental sciences. One of the overarching goals of the ENVRI cluster is to provide more FAIR (Findable, Accessible, Interoperable and Reusable) data and services which will be open to everyone who wishes to get access to environmental observations, from scientists and research communities of scientifically diverse clusters to curious citizens, data scientists and policy makers.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Starting with domain-specific use cases we further explore potential cross-domain cases, e.g. in the form of environmental science stories crossing disciplinary boundaries. A set of Jupyter Notebooks developed by the contributing Research Infrastructures (and accessible from a hub of services called the ENVRI-Hub) are promising tools to demonstrate and validate the capabilities of service provision among ENVRIs and across Science Clusters, and act as examples of what a user can achieve through the ENVRI-Hub. In one of the examples we investigate, a user-friendly well-structured Jupyter Notebook that makes use of research infrastructures&amp;amp;#8217; application programming interfaces (APIs) jointly plots in a map the geographical locations of several Marine and Atmospheric stations (where the stations in this example are defined as measurement points actively collecting data). The FAIR principles provide a firm foundation defining the layer that supports the ENVRI-Hub structure and the preliminary results are promising. Considering that the APIs can become discoverable via a common ENVRI catalogue, the ENVRI-Hub aims to make full use of the machine-actionability of such a catalogue in the future to facilitate this kind of use case execution in the Hub itself.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;strong&amp;gt;Acknowledgement&amp;lt;/strong&amp;gt;: ENVRI-FAIR has received funding from the European Union&amp;amp;#8217;s Horizon 2020 research and innovation programme under grant agreement No 824068. This work is only possible with the collaboration of the ENVRI-FAIR partners and thanks to the joint efforts of the whole ENVRI team.&amp;lt;/p&amp;gt;
Literature Review: Penggunaan Komik dalam Pembelajaran Bahasa Asing untuk Pengembangan Media Ajar Bahasa Jepang Berfokus pada Bentuk dan Tampilan Komik

The study was aimed to discover the form of comics used in language learning and the development process, as well as the style of the Comic suitable with the interest of Japanese language students used in the previous study, which is expected to elaborate types of necessary research in the future for Japanese language teaching material development. There were 20 articles reviewed related to comics development for language learning. Based on the review result, it was found that 1) There are two types of comics, namely 1-Panel Comic used to explain one specific material and 4-Panel Comic used for conversation materials. However, there has yet any research related to comics development in the form of comic books; 2) In terms of process, both types of comics are formulated and developed by referring to a curriculum and learning plan so that the comics may assist students in understanding learning material; 3) Comic styles discussed in previous researches refer to American comic style, and thus less suitable to be used as Japanese language learning materials. The style used in Japanese comics is predicted to be more attractive for Japanese language students. However, there has yet any scientific study on the development of Japanese style comics in Japanese language learning.
An analysis of research trends on machine translation in the linguistic and Japanese language society in Korea

In this study, I reviewed the current research trend of machine translation by overviewing the development of computer science and the overall previous research in linguistics. To this end, the research trend of Japanese, an individual language was identified, and the research direction was suggested by finding areas where research is insufficient or nonexistent.<BR> First, focusing on the translation method, I investigated the development process of computer engineering for the development of machine translation.<BR> Next, I analyzed the overall research trends in the humanities community in Korea since 2016. Based on its analysis results, I divided the machine translation-related researches into three phases:
Detecting Microseismicity in Jammu and Kashmir Himalaya Using Template Matching Technique

&amp;lt;p&amp;gt;We study microseismicity in the Kashmir seismic gap from broadband data of the Jammu and Kashmir Seismological NETwork (JAKSNET) using the template-matching technique. Template-matching is done by the Python routine &amp;amp;#8216;PyMPA&amp;amp;#8217; (Vuan et al. 2018) to detect new events. For templates, we use 189 earthquakes, taken from the ISC reviewed catalogue, which occurred between 2013 and 2018. We use 5 second long waveform templates by taking 2.5 s before and after the S-wave arrival. Normalized cross-correlations are calculated for each template earthquake, recorded at different channels, with continuous data from their respective recording channels. The individual cross-correlation traces are shifted according to the travel times of the template earthquake, calculated using a local 1D velocity model, and stacked to get a Network Stack Function (NSF). A detection is declared if the NSF crosses a threshold value eight times the Median Absolute Deviation. We assign the location of the template, corresponding to the detection, as the location of the newly detected event. If multiple templates detect one event, we consider the one with the maximum NSF value. After running the process, we obtain a catalog of 935 events, an immediate 5-fold increase in the number of events. We also observe two clear sequences of events in the middle of 2013 and in the start of 2016. We intend to perform a probabilistic and relative relocation of all the events to get a detailed seismotectonics of the region.&amp;lt;/p&amp;gt;