Reviewerly/exHarmony huggingface dataset:
Legal Measures for Crimes in the Field of Cryptocurrency Billing

espanolLos casos de criptomonedas continuan aumentando. Se analiza la naturaleza legal de la criptomoneda y se concluye que hoy en dia, a pesar de algunos intentos de regular legislativamente la circulacion de la criptomoneda, existen numerosas lagunas, la mayoria de las cuales estan en el campo del derecho penal. Con base en el estudio de los puntos de vista teoricos disponibles de los nacionales, asi como el analisis de los materiales de practica de investigacion judicial de la esfera legal en consideracion, los autores consideran que es necesario llevar a cabo un trabajo para formular una serie de areas que racionalizaran relaciones de derecho penal. EnglishCryptocurrency crime cases continue to increase. The legal nature of cryptocurrency is analyzed, and it is concluded that nowadays, despite of some attempts to regulate cryptocurrency circulation legislatively, there are numerous gaps, most of which are in the field of criminal law. Based on the study of the available theoretical views of domestic, as well as the analysis of the judicial investigative practice materials of the legal sphere under consideration, the authors consider the necessity to carry out a work to formulate several areas that will streamline the criminal law relations in the field of cryptocurrency circulation.
Research Guides: Business: eBook databases

Learn about library research tools and resources specifically geared towards Business courses including citation and evaluation help, peer-reviewed articles, eBooks, and more! Find print books and eBooks related to nursing.
Visually grounded models of spoken language - A survey of datasets, architectures and evaluation techniques.

This survey provides an overview of the evolution of visually grounded models of spoken language over the last 20 years. Such models are inspired by the observation that when children pick up a language, they rely on a wide range of indirect and noisy clues, crucially including signals from the visual modality co-occurring with spoken utterances. Several fields have made important contributions to this approach to modeling or mimicking the process of learning language: Machine Learning, Natural Language and Speech Processing, Computer Vision and Cognitive Science. The current paper brings together these contributions in order to provide a useful introduction and overview for practitioners in all these areas. We discuss the central research questions addressed, the timeline of developments, and the datasets which enabled much of this work. We then summarize the main modeling architectures and offer an exhaustive overview of the evaluation metrics and analysis techniques.
Disease Diagnosis Through Blood Analysis using image processing

The department of Hematology deals in the management of blood-related disorders. In case, there is any problem in the bloodstream, it can affect the overall health of a person. The team of hematology expertise in providing an accurate diagnosis of the problem and its treatment. There are numerous blood disorders that can affect a person's well-being. Diagnosing blood disease and blood group is essential during the emergency situations. Here is a technique dependent on image processing which is exceptionally fast and it has its expansive use in biotechnological field. We put forward this precise and quick recognizable way of blood group, count and disease i.e., leukemia and malaria dependent on digital image processing.
All-optical information processing capacity of diffractive networks

We analyze the information processing capacity of diffractive optical networks to reveal that increasing the total number of diffractive features, i.e., neurons, within a network linearly increases the dimensionality of the complex-valued linear transformation space of the network, up to a limit dictated by the input and output fields-of-view. We further show that deeper diffractive neural networks formed by larger numbers of diffractive surfaces can cover a higher-dimensional subspace of the complex-valued linear transformations between a larger input field-of-view and a larger output field-of-view, increasing the learning capability and approximation power of the optical network.
Role of Superior Colliculus in Visual to Movement Spatial Transformations During Memory-Guided and Reactive Head-Unrestrained Gaze Shifts

The fundamental process in the brain which allows the generation of what is known as behavior, is the transformation of sensory or internally generated information to commands for movement. For example, shifting the line of gaze to look at and interact with our environment requires transformation of visual information into proper contraction of eye and neck muscles. In this thesis I studied the transformation of visual signals to movement commands in the primates superior colliculus, a key structure in sensory integration and gaze movement generation. In the first chapter the frames of reference and the spatial information encoded by the visual and motor activity of superior colliculus, in different neuron types, are investigated in a memory delay task, and the results provide support for visuomotor transformation process that occurs between and within neurons during the memory delay task. In the second chapter the focus of study is on reactive gaze shift task and we show that the spatial information occurs during the burst of activity of single neurons even in such a short interval and without a presence of a memory delay. In the last (third) chapter, I compared the visual and motor spatial coding and their transformation between the reactive and the memory delay tasks and found that although similarities exist, there are important differences in neural activity profiles and the spatial codes and the extent of visual to movement transformation. Together the findings in this dissertation suggest that the process of visual to movement transformation occurs between and within neurons in SC regardless of the duration of the gaze shift or the task, however task demands influence both the activity and spatial coding of neurons which are consequently translated in the differences in behavior in each task
Proof sheet of Doug Mackenzie with wine and soil from the Coonawarra region

ANU Reporter Photos - Geology, Jabal, Acatalyst Performance, etc. - Doug Mackenzie, John Richards, Mark McMillan, Kate Moore & others
Detecting Near Duplicate Images Using Hellinger Correlation Coefficient

Near duplicate images are nothing but the similar images with minute change in the original image. These similar / transformed images are available in the internet and they are displayed as a result of user search. Discovery of these near duplicate images may permit the users to abstain from encountering the presentation of a similar picture in the result set. In this work, a detection methodology is presented to identify near duplicate image from the image set for an inquiry image by the user. Initially features are extracted from the images using Pulse-Coupled Neural Network. Once the features are extracted, similarity measure is calculated. Here Hellinger coefficient is computed. In view of the relationship between the inquiry image and the images in the image set, the near duplicate images are recognized. This results in effective detection of near duplicate images. The detected near duplicate images help the users to avoid redundancy in images, detect copyright infringement, illegal copy of images detection, facilitates users’ browsing since image search engine returns multiple copies of image for a particular query.
LOCAL CONTENT CURRICULUM DEVELOPMENT BUGIS LANGUAGE IN SDI BENRONG

The purpose of this development is to (1) find out the description of the need for local content curriculum development at SD Inpres Benrong, Gattareng village, Barru Regency (2) Determine the level of validity of the Bugis language local content curriculum at SDI Benrong Gattareng Village (3) Determine the practicality of the Bugis language local content curriculum product in grade VI SD Inpres Benrong, Gattareng Village. This study uses a development method that adapts the Ken Peffers model with data collection using quantitative (instrumental curriculum experts, material experts) and qualitative (observation and interviews) methods, this research has six stages consisting of identifying problems, determining goals and solutions, The stage of designing and developing the product, the stage of demonstrating the product, the stage of evaluating the product, and the stage of communicating the results to the public. Descriptive analysis aims to provide a description of the research subject based on data obtained from the group of subjects studied. This development research uses two data analysis techniques, namely: qualitative descriptive techniques and descriptive static analysis. Based on the results of the SKL validation, content standards, syllabus, teaching materials when converted into Sudijono's score classification, are in the very good category.
Exploring dual information in distance metric learning for clustering

Distance metric learning algorithms aim to appropriately measure similarities and distances between data points. In the context of clustering, metric learning is typically applied with the assist of side-information provided by experts, most commonly expressed in the form of cannot-link and must-link constraints. In this setting, distance metric learning algorithms move closer pairs of data points involved in must-link constraints, while pairs of points involved in cannot-link constraints are moved away from each other. For these algorithms to be effective, it is important to use a distance metric that matches the expert knowledge, beliefs, and expectations, and the transformations made to stick to the side-information should preserve geometrical properties of the dataset. Also, it is interesting to filter the constraints provided by the experts to keep only the most useful and reject those that can harm the clustering process. To address these issues, we propose to exploit the dual information associated with the pairwise constraints of the semi-supervised clustering problem. Experiments clearly show that distance metric learning algorithms benefit from integrating this dual information.
Teamwork Effectiveness in Student’s Final Year Project

The goal of this paper is to deliberate issues pertaining to teamwork effectiveness among students in a university environment. Final year project is an important assessment to measure students’ teamwork skills in the university. Three main factors have been identified that contribute to teamwork effectiveness. The factors are namely interpersonal skills, interdependence and commitment to success. Interpersonal factors include social sensitivity and emotional engagement attributes. In this perspective, measures such as teamwork support, care, trust, honesty and respect towards team members are important key criteria. On the other hand, interdependence among others includes traits such as promoting each other to achieve common goals, bringing the best of each other and helping each other completing the task. Commitment to team success involves high obligation, high motivation, strong common goals and strong shared values and beliefs. In this paper, construct items for each factor are developed based on previous studies. The findings show that these factors are relevant toward the success of the student’s final year project. Lacking these skills may result in poor performance among team members and may lead to unfavorable outcome.
HIGH-PERFORMANCE COMPUTING CHALLENGES & BENEFIT

Nowadays, high-performance computing applications are gaining significant traction in the cloud computing space. The vast majority of high-performance computing (HPC) applications are utilized for scientific reasons. They need significant CPU use and data storage capacity. Historically, HPC applications needed a vast network of linked computers, such as clusters or supercomputers. Both financially and technically, these clusters are unfeasible. However, with the advent of cloud computing, the scientific community can now benefit from cloud computing’s low cost and low maintenance requirements for HPC applications.
Novel deep learning techniques for photonics

We present a few novel deep learning techniques for applications inphotonics. Of particular interest are few-shot techniques which minimize the amount of needed training data.
Pelayanan Pelanggan Tambah Daya Dan Migrasi Serta Proses Melakukan Pasang Baru Pada PT PLN Unit Induk Wilayah Kalsel-Kalteng

Along with the times, the need for electricity is increasing for lighting or others. To improve electricity services at UP3 PLN (Persero) provides prepaid electricity services. Prepaid electricity services are used for customers who have made it possible to use postpaid electricity services and the entire renewal for new installations of electrical services. At UP3 PLN (Persero) there is an AP2T (Centralized Customer Service Application) application that can be used to provide services for customers who will add electric power, new installations of electricity, migrate electricity from postpaid to prepaid, and other customer complaints. This is done by checking the Customer ID of each electricity user.Keywords: Customer ID, AP2T, Postpaid, Prepaid
Blueprint : Burger Sauce Spreader / Hazman Abu Yazid

The sauce spreader is a device that spread the sauce onto the food. This device is also available for any other products that has its function to be spread sauce on the food. The user or the worker will only have to refill the sauce into the device and close the lid tightly. Next, the user also need to push the pressure stick to ensure that the air is in pressure form and the user need pump device to ensure the air in the device out to ensure the sauce can be spread. It is a save cost device as it uses no power or electricity. This device also suitable for the small businesses such as burger stall, restaurant and many more. Any household that are interested in spreading sauce onto large quantity food can use it as it is affordable.This device said affordable because it does not use electricity but it use man power to generate it. Thus, it uses man power as the pump is provided to make easier for user to spread sauce onto the food. The hand pump is the unique features as it contributes a lot of benefit of this device and the base of the device is made of copper base which is a good conductor to put on the hot pan to ensure the sauce in a hot condition. This sauce spreader is a universal device which can put any types of sauce such as mayonnaise, black pepper sauce and many more. The body of this device is made of stainless steel that can make high durability of the sauce spreader and non-stick that makes user easy to wash the device. It can also easy to wash the body of the spreader. The stick is made of heavy duty plastic that can withstand high temperature and can be the best heat insulator to ensure the safety of the users
Blockchain Capabilities in Defending Advanced Persistent Threats Using Correlation Technique and Hidden Markov Models (HMM)

In December 2019, the world witnessed the start of a pandemic outbreak (Coronavirus or COVID-19) in Wuhan the capital of China’s Hubei province and from there quickly spread globally. The uncertainty and fear change represented a golden opportunity for threat actors. Early 2020 research discovered widespread evidence that threat actors embraced the COVID-19 fear event to mount Advanced Persistent Threats (APT) attacks and exploit the opportunity exposed by the disruption. Tactics ranging from phishing emails and social engineering to malware distribution have been identified with many malicious domains with medical information that delivered sophisticated malware to the victims’ systems. APTs are incredibly sophisticated, stealthy and remain undetected for potentially long periods. They use zero-day or unknown vulnerabilities and are carried out by adversaries possessing a very high level of expertise and deploying significant resources for the primary purpose of data exfiltration or positioning for long term attack strategies. The current defence security solutions are a combination of Intrusion Detection and Prevention Systems (IDPS), Security Operations Centre (SOC), anomaly and heuristic-based endpoint protection systems, etc. However, IDPS face several problems in mitigating APT attacks, such as a lack of historical correlation of attack data, knowledge of defence against known APT attacks stages only. This chapter explores Blockchain distributed technology and its applicability towards cybersecurity defence and explores a new system in defence against APT attacks called Blockchain Advanced Persistent Threat Correlation Detection System (Orion System), implemented as chaincode micro-smart contracts.
Blueprint : Easy Sdn Bhd “Space-Saving Plastic Bag Storage Box” / Nurul Anies Suraya Young Rockie

Space-Saving Plastic Bag Storage Box is a storage box that can help consumers in storing their used plastic bags. The consumers can place the box either on the wall or cabinet door or even on the floor. When plastic bags are inserted, the consumer will have to pull down the compressor handle for compessor to compress the plastic bags and thus will save more space. There is also a hole at the bottom of the box for the purpose of practical bag taking
Identifying Severe Malnutrition in Children with an Expert System

Expert system is a computer program which is designed for modelling the ability of problem solving as it is an expert (human expert). The expert system method used is the forward chaining method which is the inference method that is doing logical reasoning from the problem to its solution. The aim of this research is to design and develop an expert system that is able to identify the severe malnutrition on children from the age of 0 - 5 years old. The knowledge is derived from the question askedto a nutrition expert. The data are taken from the questions asked to the user and when all of the questions has been answered, then the goal will be appeared which shows the nutrition status. This system application will enable the user to diagnose the nutrition/disease that affects children and get the solution. This system can be used by any kind of user due to the easy access. This system is also put the important information about the severe malnutrition and the recent news of children’s health so it will add more knowledge for the parents about the importance of severe malnutrition’s prevention.
PLUS CURRICULUM IN THE MADRASAH ALIYAH SCHOOL BANDA ACEH DARUL ULUM (TEACHING METHOD MATERIAL USED IN EFL)

This study is to interpret the teaching materials, approaches and methods used in the plus curriculum in the teaching English as a compulsory subject in the Madrasah Aliyah Darul Ulum Banda Aceh. An ethnography method was purposefully used where four participants were involved for an in-depth interview and classroom observation. The result revealed that the approaches were the employed namely scientific and communicative approach. The method instantly becomes priority were lecture method, demonstration, discussion, simulation, grammar-translation method, direct method, debate, and role play. Whereas the teaching material was sourced from the technical school guiding book, relevant technical books, magazines, visual-based teaching, audio-visual based and  multimedia-based learning sources. Therefore, this is one of the evidence that the successful using of teaching material, approaches, and method under the plus curriculum can mediate the Madrasah Aliyah students‘ English learning outcomes. This may put into account due to the specific educational and cultural issue and practices in those private Madrasah Aliyah. Moreover, it can be typically recommended to other schools in Banda Aceh to apply such an  innovative and combination curriculum contents; local school and national curriculum instruction. Further ethnographic research is needed to investigate how teachers and principals prepare or determine teaching materials and learning model prior to the learning process conducted. Keywords: learning method, teaching material, plus curriculum, learning English, approaches
A novel implementation for brain MRI noise reduction

In this paper proposed algorithm is based on Dual Tree-CWT and Nonlocal Mean filtering processes is used to eliminate Rician noise from the brain magnetic resonance images. The noise reduction is done using two stage processes, first sparse DT-CWT is applied, which allows for distinction of data directionality in the transform space and then Rotational invariant version of Non-Local Mean filter is applied. The proposed algorithm is tested with different Rician noise levels of brain MR Images. Even the Image is degraded by 15% Rician noise the PSNR and SSIM obtained are 23dB and 0.93 which is a better performance as compared to Anisotropic Diffusion Filter (ADF), Non local Maximum Likelihood (NLML), Nutrosophic Set Median Filter (NS median).
The Space Between The Stars - Parts 1, 2 and 3

A music composition output using prepared audio recordings played back using extreme audio rate settings. The process manipulations for this work exploit a process that I define as Multiphasic or, as a looser definition, a 'Smear Symphony'. The smearing is a process that obscures the original source of sonic materials and to blend them in ways that create a slow but continuously shifting soundscape, whilst repeated melodic motifs can be heard at varying levels of foreground/background. This process and its outputs must be understood as not being procedural, as many compositions can be. There is no function or computation taking place.This smearing and elongating then, whilst not performable in human terms, acts as a mediation between original source, modifications and the listener. Therefore the point is not to hear the original material but to consider the processed audio as original material rather than as a process or remixing of prepared recordings.This piece presents a time based exposition of small artefacts whose value is exchanged into a more significant and profound work. Whilst listeners might well project onto the piece and suggest that parts sound like a collection of voices, nothing of human origin has been used to compose this piece. It is, in effect, a piece that can only exist in a computer environment but is not computationally derived.
QR CODE BASED MULTI FACTOR AUTHENTICATION PROTOCOL FOR IoT NETWORKS

In recent years, with rapid growth and development in Internet of Things (IoT) Technology using wireless communication networks. There are major applications like smart home, smart health care and smart transportation etc. Generally the IoT devices access the user private data, the security and privacy become a challenge. As we are having various authentication systems implemented for authorizing the user to get the access of device or to get the controls of device. Multi-factor authentication (MFA) provides great security to the device. QR code is a 2D matrix code provides high data store capacity than bar code. Now a days, QR code is applied in many applications like payment systems, security etc. The proposed architecture implements the security enabled IoT device, in order to get the access or controls it requires MFA which is encrypted QR code.Keywords: Encrypted QR Code (EQR Code), IoT, Key Pair, Multifactor authentication.