Reviewerly/exHarmony huggingface dataset:
Airport Detection Based on Saliency Analysis and Geometric Feature Detection for Remote Sensing Images

Owing to the complicated background information and large data volume in remote sensing (RS) images, it's difficult to detect airport precisely and efficiently. In this paper, we propose a credible airport detection method based on saliency analysis and geometric feature detection. On the one hand, we use a novel saliency analysis model to measure both global contrast and spatial unity in RS images, by which the most salient region can be extracted accurately and the background can be suppressed preferably. On the other hand, considering the geometric features of the airport, a feature descriptor is conducted to detect proper hole structures and line segments in the saliency map. The experimental results indicate that our proposal outperforms existing saliency analysis models and shows good performance in the detection of the airport.
Reflections on Murray Aitkin's contributions to nonparametric mixture models and Bayes factors

We describe two interesting and innovative strands of Murray Aitkin's research publications, dealing with mixture models and with Bayesian inference. Of his considerable publications on mixture models, we focus on a nonparametric random effects approach in generalized linear mixed modelling, which has proven useful in a wide variety of applications. As an early proponent of ways of implementing the Bayesian paradigm, Aitkin proposed an alternative Bayes factor based on a posterior mean likelihood. We discuss these innovative approaches and some research lines motivated by them and also suggest future related methodological implementations.
Usability Testing of VLASTWA: A Vocabulary and Strategy Teaching Web App

While vocabulary learning is one of the challenging tasks of language learning, it is considered indispensable for language mastery. Vocabulary learning presents similar challenges for professionals who need to master new terminology and definitions. The use of technology has been seen to effectively support learners in the vocabulary learning challenges. In this paper, the usability and learnability of a bespoke web app, VLASTWA, is assessed in terms of usability, effectiveness and pedagogical efficacy. VLASTWA was designed and implemented utilizing effective and extensively researched vocabulary learning technique, the keyword method. In this experimental study, participants (n=160, age = 18-60) learned to use the keyword method and employed it in new vocabulary learning (Persian-English) using VLASTWA. VLASTWA experimental web app performed well in a usability study using System Usability Scale with a rating of 91.5%. Results demonstrated the web app as a usable and efficient instrument in acquiring new vocabulary and future research will investigate the inherent use of the designed web app for different population, other languages and sets of words and emerging technologies such as augment reality and virtual reality and electroencephalogram.
Fingerprint-Based Attendance Development to Support the Payroll System

Information technology that produces accounting and cashier application products in the city ofBandung, Indonesia. Development of attendance and employee payroll systems is done to help the work ofthe human resource department or HRD and the company's finance department. HRD is the part of thecompany that manages attendance, while the finance department that manages the salaries of all employees.The presence system in this company already uses fingerprints, but the presence data recorded and stored onthe fingerprint machine is still managed manually by the HRD department by connecting the fingerprintmachine to the HRD computer device using USB, and processed through Excel. This presence data will thenbe used as a consideration in providing monthly employee salaries in the company by the finance departmentwho also uses Excel, even though the number of employees in the company is many with different salaries.Therefore, a system was made to help the attendance and salary management of employees at centralized datastorage in a database and can process attendance data and employee salaries automatically. The attendanceand payroll system that was developed still uses the support of a fingerprint machine as a presence recorderand is developed on a website-based because HRD and the financial department, dominantly use computersto work, making it more appropriate and easily accessible. The system also requires the internet to be usedbecause it integrates employee attendance and payroll data.
Mapping Electric Transmission Line Infrastructure from Aerial Imagery with Deep Learning

Access to electricity positively correlates with many beneficial socioeconomic outcomes in the developing world including improvements in education, health, and poverty. Efficient planning for electricity access requires information on the location of existing electric transmission and distribution infrastructure; however, the data on existing infrastructure is often unavailable or expensive. We propose a deep learning based method to automatically detect electric transmission infrastructure from aerial imagery and quantify those results with traditional object detection performance metrics. In addition, we explore two challenges to applying these techniques at scale: (1) how models trained on particular geographies generalize to other locations and (2) how the spatial resolution of imagery impacts infrastructure detection accuracy. Our approach results in object detection performance with an F1 score of 0.53 (0.47 precision and 0.60 recall). Using training data that includes more diverse geographies improves performance across the 4 geographies that we examined. Image resolution significantly impacts object detection performance and decreases precipitously as the image resolution decreases.
How Can Head Worn Displays and Tablet Computers Affect Co-located Work: A Laboratory-Based Exploratory Study

Head-worn displays (HWDs) have shown promise for supporting workers in a range of contexts due to their ability to provide live ‘heads up and hands free’ information. However, in many work environments co-located workers may need to collaborate and communicate about the tasks that they are engaged with, and this may be difficult when information is presented privately on a HWD. The current study explored a laboratory-based dual-task game for evaluating how presenting task-relevant information HWDs versus tablet computers can affect the process of collaborative and mobile work. We found no effects of display type on performance, perhaps because ten of the twelve participating dyads allocated tasks in a way that minimised the need to communicate about the displayed information. We suggest that future research focusses on specific features of HWDs, and/or how representative teams adapt to the constraints of HWDs.
Comic Strip Project in the M-Comic Application for Mandarin Vocabulary Learning

Abstract How to arrange sentences and reading texts often come from textbooks. The example sentences and text provided only display the meaning and position in the sentence. The procedures for using it grammatically in sentences are often unclear. The context of the conversation used as an example sentence often does not relate directly to the daily lives of students. So that students have difficulty in composing sentences with the vocabulary learned. This study aims to overcome difficulties in learning Mandarin vocabulary through the comic strip project in the M-Comic application. Through a survey method of 48 students, first-year Chinese literature, there are three difficulties for students in learning vocabulary, namely, the meaning of words, how to use, and the context of use in conversation. Therefore, the author sparked the idea of M-Comic as a new learning media. M-Comic requires a story update in each period. The author involved 24 students who were divided into 8 groups to create comic content following the instructor’s direction. The survey results show students can apply learning by doing, by collaborating with fellow group members, together creating their conversation context that is closely related to daily life, to help mastering Mandarin vocabulary in more exciting way.
A Multipath Fusion Strategy Based Single Shot Detector

Object detection has wide applications in intelligent systems and sensor applications. Compared with two stage detectors, recent one stage counterparts are capable of running more efficiently with comparable accuracy, which satisfy the requirement of real-time processing. To further improve the accuracy of one stage single shot detector (SSD), we propose a novel Multi-Path fusion Single Shot Detector (MPSSD). Different from other feature fusion methods, we exploit the connection among different scale representations in a pyramid manner. We propose feature fusion module to generate new feature pyramids based on multiscale features in SSD, and these pyramids are sent to our pyramid aggregation module for generating final features. These enhanced features have both localization and semantics information, thus improving the detection performance with little computation cost. A series of experiments on three benchmark datasets PASCAL VOC2007, VOC2012, and MS COCO demonstrate that our approach outperforms many state-of-the-art detectors both qualitatively and quantitatively. In particular, for input images with size 512 × 512, our method attains mean Average Precision (mAP) of 81.8% on VOC2007 test, 80.3% on VOC2012 test, and 33.1% mAP on COCO test-dev 2015.
The Principle of Blurring. Conscious, Artistically Produced Blurrings

Filtering' is the differentiation of the essential and the secondary – depending on context and goal. With music it is the basal stage of sharpening. Thus natural material is processed, transformed into tones, sounds, noises, and systematized. This then serves as material for the second stage, the 'crystallization' (see chap. 6). These filtering processes repeat themselves, now already in the field of music, when chords are filtered out of heterophonic lines, and when in electroacoustic musical tones are worked out of noises or sine tones. The automated filtering by soft computing and FL-oriented methods is analysis of similarities. Our 'leitmotif' BACH serves as a test for internet research, which shows the productivity of Fuzzy Logic. Filtering as highlighting essential information via the Phonographic Form supports the re-sharpening of the memory. The compositional use of the partial-tone-spectrum as in Wagner's Prelude to Rheingold is already a transition to crystallization.
Cognitive Images for the Visual Analysis of the States of Complex Objects in Relation to the Space Industry

The work is aimed at supporting the decision-making of ground station operators who monitor and diagnose spacecraft subsystems. The problem of automatic construction of color-bright cognitive symbols that contribute to an operational understanding of the current situation is solved. For the first time, a comprehensive formal assessment of the quality of cognitive symbols designed to observe the state of a complex real-time dynamic system was given.
Automatic Brain Tumor Segmentation Using Multi-OTSU Thresholding and Morphological Reconstruction

Images segmentation aims to divide an image into several segments. They can be selected according to the composition of the region of interest, the types of tissues, and the functional zones []. In this paper, we present a new segmentation method, based on the multi-thresholding method and morphological reconstruction for brain tumor separation from Magnetic Resonance Imaging (MRI). Firstly, we use a pre-processing to enhance image contrast and quality by intensity adjustment. Secondly, the improved image is segmented using the multi-Otsu method and finally, a morphological reconstruction was performed with the appropriate structuring element parameter on the segmented image to determine the tumor. A comparison with some state-of-the-art algorithms demonstrated the efficiency of the proposed method with regard to accuracy.
Application of Gamma Algorithm in Ink Drop Forming Process

Droplet forming plays an important role in inkjet control system, especially in substrate imaging. To this end, we used the principle of Gamma algorithm to correct the ink droplet image taken by CCD camera to analyze the forming state of the ink droplet and analyze the shape change of the formation and spreading process of the ink droplet under the fluid with different viscosity and surface tension. By analyzing the contrast of the image formed by the droplet in different Gamma values, the droplet forming state was simulated and analyzed by MATLAB/Simulink simulation tool. The analysis results show that the analysis of the droplet image at Gamma=0.5 can get the best effect. Through the analysis of the droplet image, we detected that the droplet formed the best state when the viscosity was 10Pa·s and the surface tension was 40mN/m. In this way, we could also print the best picture on the substrate. Finally, we were able to design the best ink-jet printing system.
PENGARUH PENERAPAN MODEL PEMBELAJARAN CARD SORT TERHADAP KETERAMPILAN MENULIS SYAIR SISWA KELAS VII C SMP NEGERI 5 KOTA JAMBI TAHUN AJARAN 2017/2018

The purpose of this research is to describe the card sort learning model towards students class VII C writing skill at SMP Negeri 5 Kota Jambi. This research is Quasi eksperiment by using quantitative approach. This research used 1 experimental class which consists of 36 students by using Liliefors test. The requirement test used in this research is normality and homogeinity test. The result of normality pre-test is -92,48 and post-tes is -432 and the homogeinity score is 0,57 which is higher than significant = 0,05. It means that the data is normal and homogen so that hypothesis test can be tested. Hypothesis test is done by using t test formula. The result shows that the score of is 1,859 which is higher that the score of 1,000 with significant = 0,05 with dk 36. It can be concluded that there is a significant correlation between the use of Card sort learning model towards students class VII C writing skill at SMP Negeri 5 Kota Jambi in which the mean category is 93,33 more higher than the mean of pre-test 76,80 Keywords: The Effect, Card Sort, Poetry Writing
Dystrophy of the Sense of Incomprehension and its Consequences

The problem under investigation directly relates to a radically new social situation – the possibility to immediately get any information, which has drastically changed the process of education. This situation has superimposed some previous tendencies, particularly the simplification of tasks and diminishing of challenging conditions of education from the very beginning, which leads to diminishing the joy of learning and efforts to overcome difficulties. The trend towards early specialization plays the same role, because in reality it usually only leads to the exclusion of some subjects. Special attention is given to the distinction between information and knowledge. The crucial difference is between “obtaining knowledge” and “being informed”. Generally speaking, in the first case, a person has to construct an integrated picture of the fragment of reality with different links and relationships between parts of this picture. In the second case, the bits of information are added to something already known without endeavor to continue any further work to understand the subject on a deeper level. In relation to the process of comprehension, this means that in the first case we move from the surface level to the deeper one, while in the second case we are left on the surface level. Short-term memory is used instead of long-term memory. Also, the changed ratio between oral and written communication is analyzed. Due to the habitual practice of communication using electronic devices, the predominantly oral verbal dialogues are replaced with written ones. Therefore, the connection between actors of communication becomes 1) stretched and more muddled due to the mediation of written text, and 2) much narrower, because it lacks additional hints usual for oral communication. The integral result of such education expresses itself in a certain quality of personality that can be described as “the acquired dystrophy of the sense of incomprehension.” It has extremely significant negative consequences related to the formation of a free personality, for social life, and for genuine professional education.
Augmented Reality Applications in Support of Electrical Utility Operations

The electric utilities industry is facing a potential crisis. As experienced workers are preparing to retire, new employees are being hired to take their place. These new workers lack the training and experience of the retiring workforce. This paper describes the potential use of Augmented Reality (AR) to address the challenges posed by this loss of expertise. The research effort investigated opportunities to use AR to improve knowledge transfer in the electric utilities industry.
Web-Based 3D and 360° VR Materials for IoT Security Education Supporting Learning Analytics

Internet of Things (IoT) technology is developing rapidly in recent years. With the maturity of this technology, many device companies have already start to provide various IoT devices to consumers, such as smart speaker and smart meter. Then, the security problems of IoT devices become more and more important. Except that device companies ensure the security of IoT devices in technology level, users and IoT professors should have enough security knowledge as well. In this paper, we introduce a novel framework for generating web-based 3D and 360-degree VR materials for IoT security education. In order to enhance the educational effort of these materials, we important visual analyzing tools, Time Tunnel and Cubic Gantt Chart, into this framework. By using these two tools, we can easily obtain the common week points of the education target, and such results can help us improve the development of IoT security education materials.
Introduction of traditional lebak musical instruments through aplikasi android for early childhood

Abstract Traditional musical instruments are cultural heritage that must be preserved. This is done so that the existence of this instrument is not extinct and can continue to be known until the next generation. Lebak is one area that has several diverse traditional musical instruments, traditional musical instruments such as lojor dogs, angklungbuhun, and lisung which play various ways and produce different sounds. The introduction of musical instruments early is needed to preserve culture in childhood requires methods and ways for the introduction of this instrument can be done with fun. One method that can be used is to present the knowledge of this musical instrument by utilizing animation media based on Android applications. This application not only presents the visual form of musical instruments, but also displays the sounds of each ethnic musical instrument. The purpose of this research is to increase children’s knowledge about traditional musical instruments. This research produces an Android-based application animation media that will present information about a typical Lebak musical instrument that is presented to be understood by early childhood. So that their understanding of traditional musical instruments increased.
Robust RGB-T tracking via Bimodal Constrained Correlation Filtering

With the rapid development of Internet of Things, thermal camera has been widely applied in the intelligence surveillance. Thus, RGB-T tracker has become a hot topic, because it can effectively use the complement of RGB and thermal target information to achieve full-time visual tracking. To effectively enhance the RGB-T tracking speed, we propose a bimodal constrained correlation filter based method. The key point of our method is to integrate bimodal regularization into the traditional correlation filter tracking framework. In addition, to enhance the robustness of tracking performance, we mine the multi-source oriented correlation filter coefficients to make the regression parameters of RGB and thermal images avoid negative effect when obtaining complementary advantages. The experiment results demonstrate that the proposed method can improve the tracking speed without decreasing the tracking accuracy.
Exploration Strategy based on Validity of Actions in Deep Reinforcement Learning

How to explore environments is one of the most critical factors for the performance of an agent in reinforcement learning. Conventional exploration strategies such as ε-greedy algorithm and Gaussian exploration noise simply depend on pure randomness. However, it is required for an agent to consider its training progress and long-term usefulness of actions to efficiently explore complex environments, which remains a major challenge in reinforcement learning. To address this challenge, we propose a novel exploration method that selects actions based on their validity. The key idea behind our method is to estimate the validity of actions by leveraging zero avoiding property of kullback-leibler divergence to comprehensively evaluate actions in terms of both exploration and exploitation. We also introduce a framework that allows an agent to explore efficiently in environments where reward is sparse or cannot be defined intuitively. The framework uses expert demonstrations to guide an agent to visit task-relevant state space by combining our exploration strategy with imitation learning. We demonstrate our exploration strategy on several tasks ranging from classical control tasks to high-dimensional urban autonomous driving scenarios at roundabout. The results show that our exploration strategy encourages an agent to visit task-relevant state space to enhance validity of actions, outperforming several previous methods.
An Efficient Methodology for the Cross-Comparison of Text Documents

Cross comparison of documents is important to school assignments, but it is rarely implemented because of the heavy cost of text-similarity evaluation algorithms. The paper presents an efficient algorithm based on a hybrid of LCS and hashing, and extends the framework of cross comparison that visualizes the suspected plagiarism within massive submissions.
It's All About Creating Customer Value

In a digitally (em)powered age, customers expect a service and product experience in line with continuously evolving expectations. This induces great potential for organisations that shape engagement before, during, or after the main customer touch points. Powered by insights coming from the CRM driven 360° view, they entail even more value when enabling a company to quickly and continuously learn from its experiences. This chapter will illustrate that project managers need to master a dual dynamic to attain through activated customer engagement. On the one hand, new types of projects, changing expectations, and shifting habits offer humbling challenges. On the other hand, governance, change, and delivery continue to be the foundational baseline. By integrating theoretical insights and real-life cases, the author wants to stimulate project managers. Rather than seeing the digital era as a transformational tsunami for customer engagement, they should see it as an opportunity to go beyond things in a reality where rapidly changing demand entails growth, learning, and great value.