Reviewerly/exHarmony huggingface dataset:
Aligning the Views of Research Quality in Empirical Software Engineering

Context: Research quality is intended to assess the design and reporting of studies. It comprises a series of concepts such as methodological rigor, practical relevance, and conformance to ethical ...
Anomaly Detection by Machine Learning Method based on the Gaussian Distribution

The article deals with the problem of using machine learning in detecting anomalies during the operation of IIoT objects, describes method of learning based on the Gaussian distribution, and implements the program that allows finding anomalies in data set.
Hardware structure of a surveillance system for strategic objectives

The paper presents the hardware structure of a system for the surveillance of strategic objectives. The proposed system consists of several mobile robots patrolling along a perimeter, identifying potential intruders. The information obtained is transmitted to both the mobile robots and a fixed control system, which may decide to get more detailed information about the event, sending a quadcopter in the area with a high-resolution infrared camera, and a radar sensor. It communicates to the control system all the information obtained, and these will lead to a decision.
Geological Survey of Queensland: Strategic Resources Exploration Program

The Queensland Government's Strategic Resources Exploration Program (SREP) has just crossed the half-way point with a variety of work underway.Data acquisition will shortly commence for the Cloncur...
Centralized embedding hypersphere feature learning for person re-identification

Deep metric learning has become a general method for person re-identification (ReID) recently. Existing methods train ReID model with various loss functions to learn feature representation and identify pedestrian. However, the interaction between person features and classification vectors in the training process is rarely concerned. Distribution of pedestrian features will greatly affect convergence of the model and the pedestrian similarity computing in the test phase. In this paper, we formulate improved softmax function to learn pedestrian features and classification vectors. Our method applies pedestrian feature representation to be scattered across the coordinate space and embedding hypersphere to solve the classification problem. Then, we propose an end-to-end convolutional neural network (CNN) framework with improved softmax function to improve the performance of pedestrian features. Finally, experiments are performed on four challenging datasets. The results demonstrate that our work is competitive compared to the state-of-the-art.
Computing Gaussian Curvature in Real-Time for 4K Video Processing

Computing Gaussian curvature is a fundamental task in image and video processing. However, this task becomes more and more time consuming when the image resolution goes higher and higher. In this paper, we tackle this issue from two aspects. First, we develop a novel discrete computing scheme for Gaussian curvature of discrete images. Our method does not require the image to be smooth. Second, we propose to perform the actual calculation by lookup tables, which significantly reduce the computation time. As a result, our method can compute the Gaussian curvature for 4K videos in real time, without requiring the image to be smooth. Moreover, our method can be implemented on mobile devices. Several experiments confirm the efficiency and effectiveness of our method. Our method can be applied on a large range of image and video processing applications that involve Gaussian curvature.
Northern Territory Geological Survey: Geophysical and remote sensing projects

The Northern Territory Government's Resourcing the Territory initiative provides $26 million over 4 years (2018–2022) to support long-term sustainability of the Territory's resource sector. The ini...
Airborne radiometric maps of Mountain Pass, California

First posted August 20, 2019 For additional information, contact: Director,Geology, Minerals, Energy, & Geophysics Science CenterMenlo Park, CaliforniaU.S. Geological Survey345 Middlefield RoadMenlo Park, CA 94025-3591 Geophysical investigations of Mountain Pass and vicinity were begun as part of an effort to study regional crustal structures as an aid to understanding the geologic framework and mineral resources of the eastern Mojave Desert. The study area encompasses Mountain Pass, host to one of the world’s largest rare earth element carbonatite deposits. The deposit is found along a north-northwest-trending, fault-bounded block that extends along the eastern parts of the Clark Mountain Range, Mescal Range, and Ivanpah Mountains. This Paleoproterozoic block is composed of a 1.7-Ga metamorphic complex of gneiss and schist that underwent widespread metamorphism and associated plutonism during the Ivanpah orogeny. The Paleoproterozoic rocks were intruded by a Mesoproterozoic (1.4 Ga) ultrapotassic alkaline intrusive suite and carbonatite body. The intrusive rocks include, from oldest to youngest, shonkinite, mesosyenite, syenite, quartz syenite, potassic granite, carbonatite, carbonatite dikes, and late shonkinite dikes.The diverse physical properties of rocks that underlie the study area are well suited to geophysical investigations. Contrasts in radiogenic signatures between Paleoproterozoic crystalline basement, rocks of the Mesoproterozoic carbonatite body and the associated alkaline intrusive suite, Paleozoic carbonate rocks, Mesozoic granitoids, Tertiary volcanic rocks, and unconsolidated alluvium, for example, produce a distinctive pattern of radiometric anomalies that can aid in understanding the geologic framework and mineral resource potential of the eastern Mojave Desert.A high-resolution radiometric survey of Mountain Pass was flown by helicopter over parts of the Clark Mountain Range, Mescal Range, and Ivanpah Mountains. Aeroradiometric surveys measure the intensity and energy spectrum of gamma-ray radiation from the three most common naturally occurring radioelements: potassium (40K), thorium (232Th), and uranium (238U). For 232Th and 238U, the source of the gamma-rays comes from their thallium (208Tl) and bismuth (214Bi) decay products, respectively, and, thus, concentrations for Th and U are referred to as “equivalent concentration,” assuming radioactive equilibrium. The concentrations of these radioelements can be used together to estimate changes in geochemistry and lithology.Carbonatite deposits typically have distinctive geophysical signatures because they are relatively dense, magnetic, and radiogenic. Specifically, the carbonatite and alkaline intrusive suite at Mountain Pass is ultrapotassic and contains relatively significant amounts of K, Th, and U, which can be delineated using airborne radiometric surveys.
Tilt Space: A Systematic Exploration of Mobile Tilt for Design Purpose

Various application scenarios of a smartphone sometimes require one-handed and/or eyes-free interaction. Tilt-based interfaces have the potential to meet these requirements. Taking multiple application scenarios into account, we conducted an experiment to systematically investigate human ability in controlling tilt input of a mobile phone. Three visual feedback levels, i.e., fully visual feedback (FV), partially visual feedback (PV), and no visual feedback (NV), were investigated. Under the NV condition, the participants performed a task using an eyes-free method. The results revealed that trials were performed the fastest but were the most error-prone under the NV condition. The participants could easily distinguish 4 tilt orientation levels (TOLs) and 2 tilt magnitude levels (TMLs) or 8 TOLs and 2 TMLs under the NV condition with tolerance of an error rate 10% or 15%, respectively. We also found out that the participants’ abilities to control tilt input were related to tilt orientation directions. The results have some implications for non-visual interface designs using tilt as primitive input.
The Use of Language Aspects as Rhetorical Devices in Obama’s Inaugural Addresses

This research analyzes language aspects as rhetorical devices in inaugural addresses of the presidents of The United States, Barack H. Obama. Specifically, this research aims at describing the use of diction and language style found in the inaugural addresses. This research is descriptive qualitative using discourse analysis approach. In collecting the data, it uses listening method and note-taking technique. In analyzing the data, it uses contextual method by using socio-pragmatics theory. In presenting the result of the analysis, it uses informal method by verbal language. The result of analysis show: the use of language aspects found in inaugural addresses of Obama includes: (a) diction which includes the positive and negative connotation, (b) reference which includes inclusive and exclusive references, (c) language styles includes inclusive and exclusive references, (d) language styles includes repetition (e) the use of figurative language includes metaphor.
Application of Adaptive Fuzzy Integral Theory to Variable Structure Controllers

A new scheme is put forward, which combines fuzzy control, adaptive control and integral theory into the design of variable structure controllers. Fuzzy control and adaptive control are adopted to restrain the chattering around the sliding plane. Integral theory is introduced to eliminate static errors of the system. The results of simulation experiments indicate that the scheme is feasible and effective.
An Entity Linking Method Based on Entity Category and Word Embedding

Abstract Named entity linking is a process of linking a given reference in a document to a knowledge base. In natural language processing, entity linking can enhance the computer’s understanding of unstructured text data. Applying traditional entity linking methods, especially entity linking methods for person names and organization names, has its limitations. Similar vocabulary as an entity to be linked is difficult to make full use of its contextual semantic information for ambiguity elimination. This paper makes full use of the entity’s category attribute and the semantic information contained in the context to design an entity linking method based on entity category and semantic word embedding. First, Training text classification model based on corpus to obtain entity attributes. Then the semantic feature is extracted by the word vector template to perform entity disambiguation through the semantic classification model. Finally, the results of the entity linking are predicted by means of model ensemble. Experiments show that the accuracy of the method after fusion on the entity linking dataset has improved.
The Influence of Fernald Method to Increase Early Writing Skill of Students with Intellectual Disability in Grade II of SLB Panca Bakti Mulia Surakarta 2018-2019

This research aims to determine the influence of Fernald method to increase early writing skill of students with intellectual developmental disorder in grade II of SLB Panca Bakti Mulia Surakarta in academic year 2018/2019.This research used pre-experimental design with one group pretest-posttest design.The sample of this research is five students with intellectual developmental disorder in II grade of SLB Panca Bakti Mulia Surakarta in academic year 2018/2019, using saturation sampling technique.The research instrument uses a written test in the form of a short answer, namely a written test that thickens words, copies words, and completes words.The results of this study were analyzed using a signed ranking test (Wilcoxon Sign Rank Test).Based on the data analysis that has been done, it is known that the value of Zcount = -2,060 with Asymp.Sig.(2-tailed) of 0.039 which is below the significance level (p <0.05).These results indicate that the Fernald method has an effect on improving the writing skills of beginning class II students with intellectual developmental disorder at SLB Panca Bakti Mulia Surakarta Academic Year 2018/2019.
Study of Agile Scrum and Alikeness of Scrum Tools

Project management is a methodology used to achieve objectives of a project in cost effective and timely manner.There are different project management methodologies depending upon nature of project and nature of organization.Broadly the approach of project management can be divided into categories of traditional waterfall and agile.Traditional waterfall approach recommends executing the project in sequential manner.In recent time the industry product lifecycle has become shorten which require faster implementation and iterative approach of product development.This approach is well suited for agile.Due to its iterative nature, Agile enjoys wide popularity in sectors where the requirements from the customer are continuously changing.Agile project management uses various frameworks like Scrum, Kanban, XP (Extreme Programming) etc.To implements the principles of agile framework, different tools can be used like Jira, Trello, Wrike etc.The primary objective of this paper is two-fold.First, it provides the detailed overview of agile scrum methodology.After that, the paper goes on the comparative analysis of the industry tools of scrum.The targeted audience is professionals who are involved in project management and execution.This paper aims to enable the users with enough information to compare and choose tools of agile scrum.
Generate Secure Image based Password to Access the Cloud Data

In modern day technology, the Information Society is at risk.Passwords are a multi-user computer systems usual first line of defense against intrusion.A password may be textual with any combination of alphanumeric characters.But no authentication protocol is fully secured against todays hackers as all of them are Static in type.Dynamic authentication protocol is still a theoretical concept.In this paper, proposed system doing introduce a secure data scheme with cryptographic primitives for data access from the database server.In a proposed methodology using the data encryption and steganography technique to secure the image password generation to secure access on the data server's files, for more security splitting technique used to the stegno image for verification server side and client side user data.This system provides strong data security to storage on local cloud server and also provide the strong security to registered users during data uploads and downloads user data.In this paper covered the idea of generating an algorithm for generates secure image based password authentication system.
Separable reverse connected network for efficient multi-scale vehicle detection

Vehicle detection is involved in a wide range of intelligent transportation and smart city applications, and the demand of fast and accurate detection of vehicles is increasing. In this article, we propose a convolutional neural network-based framework, called separable reverse connected network, for multi-scale vehicles detection. In this network, reverse connected structure enriches the semantic context information of previous layers, while separable convolution is introduced for sparse representation of heavy feature maps generated from subnetworks. Further, we use multi-scale training scheme, online hard example mining, and model compression technique to accelerate the training process as well as reduce the parameters. Experimental results on Pascal Visual Object Classes (VOC) 2007 + 2012 and MicroSoft Common Objects in COntext (MS COCO) 2014 demonstrate the proposed method yields state-of-the-art performance. Moreover, by separable convolution and model compression, the network of two-stage detector is accelerated by about two times with little loss of detection accuracy.
Application of Time-Weighted User Behavior Analysis Collaborative Filtering Algorithm in Short Video

In the big data environment, the information overload is serious. The traditional search engine does not satisfy the user's demand for information. The user wants to obtain the user's acquired information conveniently and quickly, and the information producer wants to transmit the information to the target user. The intermediary that acts as both is the recommendation system. Recommendation system is an important way to deal with massive information. This technology brings great convenience to viewers in the field of short video. It is very difficult to extract features from missing short video data and from content information of short video. About this question. This paper proposes a time-weighted user behavior analysis collaborative filtering algorithm. This paper starts with the behavior of short video users. In order to compensate for date sparseness, the explicit and implicit behaviors of users are deeply analyzed and a user-video scoring model is established. The user's interest in video will change with time, so we use time weighting to adjust the time variable. Finally, the K most similar neighbors are extracted and recommended to the user in order from high to low. Experiments show that the proposed algorithm alleviates sparsity of date and improves the accuracy of recommendation.
Improving Students’ Grammar Competences in Writing Descriptive Text Through Community Language Learning (Cll) Method

This research aims at identifying: (1) whether and to what extent Community Language Learning (CLL) method can improve students’ grammar competences in writing descriptive text, and explain (2) the class situation when Community Language Learning (CLL) method is used in teaching grammar in writing descriptive text. The students in the first year of junior high school have difficulty in their grammar competences that causes many errors in writing descriptive text. The classroom action research was conducted in two cycles. The research findings show that: (1) Community Language Learning (CLL) method can improve the students’ grammar competences in writing descriptive text, and (2) Community Language Learning (CLL) method provides enjoyment to support the effective classroom situation when used to teach grammar in writing descriptive text. This method can be an alternative method for the teacher or the future researchers who will conduct the similar research.
Revealing Student’s Reading Interest through creative WhatsApp Status

Along with the rapid development of technology and digital era, this research investigated and reveal millennial students about their reading habit and interest. Specifically, this paper investigates about students’ reading interest through creative WhatsApp&lt;em&gt; &lt;/em&gt;status. This study was carried out by 18 students taking “Basic Reading” class and “Cultural Based Reading” class. It was conducted with descriptive qualitative method by using interview and observation of the students’ WhatsApp &lt;em&gt;status&lt;/em&gt; screenshot. It is found that 89% students of English Department Universitas Muhammadiyah Semarang are more interested in reading fiction than the factual text. Besides, students also find that learning using experiment with social media is fun and challenging.
TECHNOLOGY-CONFIDENT TEACHERS ENABLING DEEP E-LEARNING PEDAGOGIES

There are various types of successful teachers in the use of e-learning pedagogies when delivering curriculum in primary school context.That is, novice users, intermediate users and confident/expert users.But little is known about how confident teachers successfully integrate technologies in a dynamic and rapidly changing classroom context to enable quality pedagogies.This study conducted a baseline survey of 42 teachers to select three confident/expert teachers to undergo nine interviews and six classroom observations.An interpretivist and qualitative approach enabled deeper understandings from these teachers, while expansive learning framework facilitated capturing the various interactivities between m-devices, learners, teachers and curriculum content.A case study method using two levels of analysis, thematic and theoretical, helped unfold the key factors that constitute quality e-learning pedagogies.This paper presents two of its five findings, explorative learning and device affordances, that were critical to confident/expert teachers to enable deep learning with technologies using multiple pedagogic strategies.
VOTING DAPP IN EMBEDDED DEVICES USING BLOCKCHAIN TECHNOLOGY AND SECURITY CHALLENGES

The paper presents the implementation challenges of a proof of concept development for a voting distributed application in an embedded device using the block-chain technology.First section is dedicated for the existing D-App voting solutions in the market and types of block-chains used for such applications.The second section shows the Ethereum (ETH) blockchain technical details that are used by the proof of the concept.In the third section, there are highlighted the implementation details for the voting D-App deployed into an embedded device.The last section shows the conclusions and the security challenges.
Let’s stop reinventing the wheel: How existing segmentation strategies can be overlaid on to new consumer data

Segmentation is well regarded as an effective strategy to optimise resources for program delivery by governments, private companies, and NGOs. With segmentation methodologies becoming easier to implement, measure and test, their usage has increased drastically since Smith's (1956) seminal work. However, new versions are being created with such frequency that instead of testing and comparing competing models, new versions of very similar segmentation strategies are being created. Instead of constantly reinventing the wheel, researchers and practitioners should be able to take what already exists and test it through the lens of their data. As such, this work examines an existing segmentation model and applies it to new data. Using mixture modelling the process is demonstrated and some mechanisms for assessing alignment are discussed.
VIOLATION ON MAXIM OF COOPERATIVE PRINCIPLE IN THE SLOGAN

This study argued that violation on maxim of cooperative principle occurs in various type of communication such as in the slogan. This study uses theory from Grice about cooperative principle as main theory and theory about pragmatic context from Cipollone as supporting theory to analyze the data. Based on Grice, violation on maxim of cooperative principle divides into four; violation one maxim, two, three, and four. Cipollone divides pragmatics context into physical context, linguistic, social, and epistemic. In this study, descriptive analysis method is used in analyzing the data. This study is expected can help to understand the strategy of creating slogan that uses violation on maxim of cooperative principle. The result of this study shows that each violation causes other violation as occurs in the violation on maxim of relevance, which is triggered by violation on maxim of quantity.
A Robust Sandwich Technique with DWT with DB1 and DCT for Image Watermarking with MATLAB

Over the last few years, growth of internet and technology of media, the protection of copyright have become very vital.To look after multimedia data against illegal copying and transferring, the inclusion of a signal (digital signature, watermark) has become a duty without alter the quality of the original image, the objective of this operation is to identify the holder and care for his intellectual property.Digital watermarking has been projected as a solution to solving the copyright difficulty by introducing indistinguishable data (watermark) into original image.In this paper, we propose a study of digital images watermarking.This study is accomplish by put in watermark in different coefficients of DWT (LH, HL, HH) using dct with db1 wavelets family transform by searching the optimal block that have the maximum entropy which can be used to insert the watermark in original image.The experimental results show the different results of PSNR, NCC and IF for each coefficient of DWT and the robustness against most attacks.