Reviewerly/exHarmony huggingface dataset:
An RCCL-based GAN for Illustrative Sketch Generation from Game Scenes

We present a GAN-based framework for producing illustrative sketches from game scenes. This framework includes a relaxed cycle consistency loss (RCCL) module that estimates the difference between the edges of game scenes and resulting sketches extracted by the holistically-nested edge detection (HED) scheme. We compare the two edges using the learned perceptual image patch similarity (LPIPS) metric to focus on clear line representations. We also employ an attention map that focuses on semantic areas to identify areas that need to be intensively transformed. Our framework consists of a style extraction module, a generator module, a discriminator module, and a relaxed cycle consistency loss module. First, We extract the styles of illustrative sketch images using the style extraction module. Next, we generate illustrative sketches via style attention maps extracted from game scenes using the generator module. We then process the generated sketch images to the discriminator module to obtain the probability that the generated sketch satisfies the quality of illustrative sketch. We also apply RCCL to maintain the structure of the game scenes in the generated illustrative sketches. We demonstrate the superiority of our framework by illustrative sketches from various game scenes.
TEACHER’S CODE SWITCHING IN ENGLISH CLASSROOM AT SMAN 2 BUKITTINGGI, WEST SUMATRA

This research aimed to see the code-switching did by the English teacher at SMAN 2 Bukittinggi, West Sumatra and the purposes of doing so. The population of the research was all English teachers at the school, and the sample is one English teacher in the school, picked randomly and the teacher was non-native speaker of English. Technique of data collection was audio recording that was gathered by taking several audio recordings. Method of data analysis was done through analyzing the transcript of teaching and learning process in English subject. All the activities during 100 minutes teaching and learning were analyzed further. The result of the research showed that mostly during the lesson, the teacher used the target language, in amount of 69.54% from the total talk teacher did during the lesson. Therefore, it shows that the tendency that teacher had in her mind she should use as much English as possible in the classroom. For the function of doing code-switching, mostly because the teacher wanted to clarify the information (49.1%) and classroom management (25%). Key Words: Code-Switching, English Subject, Classroom Communication
Research on Multi-sensor Fusion Algorithm Based on Statistical Track Correlation

First, a multi-sensor sequential track association algorithm is discussed in this paper, and then modified by means of threshold adaptive technique. Due to the correlation of track estimation error among the sensors, the cross-covariance between the local tracks must be considered in the process of track fusion. However, the calculation of cross-covariance is very complicated, and the amount of calculation is very big as well, especially in the condition of existing false association probability when the tracks are being associated. Considering the above factor, a pseudo-measurements combination filtering algorithm based on statistic track association is proposed, having avoided the complexity of cross-covariance computation for distributed system and data association in dense targets and clutter environment for centralized system. It approaches the optimal solution as well. Simulation results show its effectivity.
Physical Activity Recognition from Accelerometer Data Using Multi-view Aggregation

ABSTRACTHuman physical activities play an essential role in many aspects of daily living and are inherently associated with the functional status and wellness of an individual, therefore, automatically and accurately detecting human activities with pervasive computing techniques has practical implications. Although existing accelerometer-based activity recognition models perform well in a variety of applications, most of them typically work by concatenating features of different domains and may fail to capture the multi-view relationships, resulting in degraded performance. To this end, we present a multi-view aggregation model to analyze the accelerometer data for human activity recognition. Specifically, we extract the time-domain and frequency-domain features from raw time-series sensor readings to obtain the multi-view data representations. Afterwards, we train a first-level model for each view and then unify the models with stacking ensemble into a meta-model. Finally, comparative experiments on three public datasets are conducted against other three activity recognition models. Results indicate the superiority of the proposed model over its competitors in terms of four evaluation metrics across different scenarios.
Quality Assessment Methods for Conversational Interfaces (bot)

Virtual assistants are being part of our everyday life.A computer program that simulates human conversations, by analysing and identifying their requests and giving to them the correct answer, is becoming important and a must to every business.Through Natural language processing, the bots are designed to convert text or speech from user queries into structured data.The data is used to choose a relevant answer for each request of the end user.They bring to the business cost savings by offering to the customers convenience and many services.It helps to resolve many types of user queries and issues while reducing the need for the human interaction and making the conversation friendly and useful for the users in order to accomplish their requests.Some of the main key attributes that makes chatbots very important are the reduction of the customer waiting time, the 24/7 availability to engage customers with immediate answers and easy scalability. User experience is an important aspect to take in consideration while creating a chatbot with a specific or general purpose.It should give to the user a good performance, functionality and efficiency during the conversation flow.In order to have a high user experience, before launching a specific bot is important to make a lot of tests and to make sure that all his functionalities works on time and in an efficient way. During this thesis work is presented a systematic literature review for the quality issued and attributes related to the contemporary issues of the chatbot development and is presented a methodology to evaluate the quality of the chatbots by using some attributes and their metrics during a conversation flow with an end user. Manychat, Alexa and Dialogflow skills are used to present the flow that this methodology follows for giving a result for the performance and the quality of a chatbot during the interaction with the user.
Error 5XX: A Critique on Application of Insider Trading Regulations to Cryptocurrencies in India

In the year 2020, the Supreme Court of India struck down the Reserve Bank of India’s circular that banned virtual currencies since 2018. This judgement changed India’s economic scene forever by attracting millions of investors and organizations all from around the world to herald its arrival into the mainstream. Its popularity re-established the Indian cryptocurrency exchanges that were once beaten down in a gory battle with the RBI. However, these entirely unregulated exchange platforms have fostered insider trading and qua market manipulation that has no apparent recourse and Indian policymakers have done little to stop it. This article explores the concept of blockchain technology and cryptocurrency, the trend of insider trading, and the difficulties that Indian officials face as they attempt to reconcile cryptocurrency's novelty with its requirement for stability. Further, this article classifies cryptocurrencies as a class unto itself to reconcile their models with the traditional financial instruments and finally concludes this discourse by delineating and suggesting various solutions to the cryptocurrency insider trading quandary.
Pengaruh Model Pembelajaran Savi dan Tingkat Kepercayaan Diri terhadap Prestasi Belajar Siswa

This study was conducted to determine the effect of the SAVI (Somatic, Auditory, Visual, and Intellectual) learning model on the science learning achievement of fourth-grade students. student of SDN 1 Setiamulya District Tamansari. This type of research is the same experiment with a research design using Factorial Experimental design. The population in this research is grade IV SDN 1 Setiamulya District of Tamansari. The sample of this research is all grade IV SDN 1 Setiamulya amounting to 41 students. Data collection techniques are conducted with pretest and posttest test dan data analyzed using SPSS version 21. Data obtained are analyzed using descriptive statistics and inferential statistics. Based on the result of data analysis, obtained significance of 0,793 &lt; 0,05, it can be concluded that Ho in reject and H1 is acceptable. This means that students’ confidence can influence the SAVI (Somatic, Auditory, Visual and Intellectual) model towards students’ learning performance in the Grade IV SDN 1 Setiamulya.
Treatment and rehabilitation of drug addicts A field study for inmates in the Rusafa second parking lot and Ibn Rushd Psychiatric Hospital

The study aimed to identify the treatment and rehabilitation of drug addicts for a sample of inmates in the Al-Rusafa second parking lot and in Ibn Rushd Psychiatric Hospital, in order to identify the causes of addiction and the rehabilitation programs provided to drug users. To achieve this, the researcher followed the descriptive and analytical approach by applying a questionnaire to a sample of 60 Addict The results showed that the most popular groups for addiction are young people, and crystal is the most popular drug among them, and among the most important factors driving their addiction are bad friends and unemployment as well as leisure time, and the results showed that there are differences between age and the desire of addicts to take treatment Also, the company of friends restricts the addict and hinders him from applying for treatment, and the results show that the demand for drug treatment decreases the lower the educational level. Key words: drugs, addiction, rehabilitation, treatment of addicts
DETERMINATION OF AN OPTIMAL PIPELINE FOR IMBALANCED CLASSIFICATION: PREDICTING POTENTIAL CUSTOMER COMPLAINTS TO A TEXTILE MANUFACTURER

There is an urgent need to reduce customer complaints because they damage reputations and incur losses. This study predicts the likelihood of complaint about a new production order using its intrinsic features. Customer complaints, however, are relatively rare, creating a serious class-imbalanced problem when training a classifier. To overcome this problem, we use a pipeline including the upsampling, the hyper-parameter generation, the classifier, and the evaluation metric. As each strategy involves different tricks in the pipeline, we use the design of experiments (DOE) concept to find, automatically, a suitable combination. A multi-response DOE is used to maximize balanced accuracy and minimize overfitting during training. The experimental results showed that the balanced accuracy of the proposed method for the testing dataset was about 23.6% better than those of the base classifiers and about 7% better than those of the current state-of-the-art methods.
Translating Import Documents from English into Indonesian at PT. Binabusana Internusa Semarang

ABSTRACTI wrote the Internship report after conducting an internship program at Exim Department of PT. Binabusana Internusa Semarang from January 6 to February 28, 2020. The objective of the internship report is to explain the translation process during translating the legal import documents from English to Indonesian. Thus, I described problems and solutions that I faced in translating the documents.I went through analyzing, transferring, and restructuring as the stages in the translation process. To produce good translations, I applied some translation techniques and made use of translation tools as well as references. I discovered problems while translating the documents. The problems were technical import terms, dictions, and target text document layouts. I overcame the problems by searching the terms on online glossaries, dictionaries as well as other references and having consultations with my internship supervisor. As a result, I fruitfully translated fourteen legal import documents.Keywords: Translation, Legal Documents, Import Document
Semi-automated fault extraction and structural analysis from DEM data of the Magadi and Natron basins, East African Rift System

&amp;lt;p&amp;gt;Continental rifts show surface expressions of deep crustal processes, such as faulting and volcanism. The East African Rift System (EARS) is one of the most prominent examples of an active continental rift driven by tectonics and magmatism. Nonetheless, we still struggle to quantify the amount of extension due to these processes on a kyr- to Myr-time-scale. In particular, the distribution of extension within low-offset normal fault networks within rift basin interiors is challenging to determine.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;To address these issues, we develop a semi-automated workflow to extract normal faults from the TanDEM-X science DEM data (12 m horizontal resolution, 0.4 m average height error) of the Magadi-Natron Region of the Eastern branch of the EARS, limited to the north by the Suswa caldera (1.15&amp;amp;#176;S) and to the south by Gelai and Oldoinyo Lengai volcanoes (2.75&amp;amp;#176;S). This data allows us to quantify brittle surface deformation that occurred since the last deposition of widespread volcanic lavas in&amp;amp;#160; these basins. Our workflow consists of five steps: (1) gradient calculation, (2) thresholding, (3) skeletonization, (4) Hough transformation, and (5) clustering. Because the surface faults appear as topographic discontinuities, we first calculate the gradient of the DEM to detect them. Then we use an adaptive threshold (Otsu) to distinguish faults from unfaulted areas. Next, we skeletonize the threshold to extract line segments and perform a Hough transformation to determine the orientation of these segments. Finally, we use a density-based clustering algorithm (DBSCAN) to group these segments into faults. This algorithm is considering proximity between the segment, similarity in dip and strike direction.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;A strike analysis applied on the fault data of the whole basin shows four main directions from distinct fault populations. Each direction cluster corresponds to a geological layer and a time interval. For example, the azimuth N20&amp;amp;#176;, corresponds to present and recent rift direction, mostly on the ~1Myr old Magadi trachyte. A direction of N170&amp;amp;#176; is mostly represented in earlier,&amp;amp;#160; Mio-Pliocene volcanic units of the rift. Moreover, we derive the fault displacement distribution throughout the basin.This allows us to calculate the total extension of each geological unit and to compute the overall amount of extension of the region during geologically recent times.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;We provide a new high-resolution fault map that depicts strike direction and throw even of small-offset normal faults. This characterization helps us increase our understanding of recent brittle deformation within the Magadi-Natron region and thus the propagation of rifting in the eastern branch of the East African Rift System.&amp;lt;/p&amp;gt;
Lower Bounds on Cross-Entropy Loss in the Presence of Test-time Adversaries

Understanding the fundamental limits of robust supervised learning has emerged as a problem of immense interest, from both practical and theoretical standpoints. In particular, it is critical to determine classifier-agnostic bounds on the training loss to establish when learning is possible. In this paper, we determine optimal lower bounds on the cross-entropy loss in the presence of test-time adversaries, along with the corresponding optimal classification outputs. Our formulation of the bound as a solution to an optimization problem is general enough to encompass any loss function depending on soft classifier outputs. We also propose and provide a proof of correctness for a bespoke algorithm to compute this lower bound efficiently, allowing us to determine lower bounds for multiple practical datasets of interest. We use our lower bounds as a diagnostic tool to determine the effectiveness of current robust training methods and find a gap from optimality at larger budgets. Finally, we investigate the possibility of using of optimal classification outputs as soft labels to empirically improve robust training.
E-Learning During Covid-19 Pandemic

The traditional learning method has been interrupted by the Covid-19 Pandemic, but a strategy is required to solve these questions.Online learning is a viable option for resolving this problem.The aim of this study was to get a summary of how online learning was implemented in the English Education Study Program at Faculty of Teacher Training and Education University of Muhammadiyah Enrekang in order to combat the spread of covid-19 in tertiary institutions.The test participants were members of the English Education Study Program.Data was collected by interview via zoom cloud meeting.The interactive analysis technique of Miles and Huberman was used to analyze the data.The findings revealed that: students also have the basic facilities required to participate in online learning; online learning is flexible in its implementation and may encourage independent learning and motivation to be more involved in learning; and distance learning encourages the emergence of social distancing behavior and minimizes the appearance of student crowds, making it a more effective method of learning.Weak monitoring of students, lack of signal power in distant regions, and heavy quota fees are obstacles to online learning.Other benefits of online learning include increased independence, curiosity and inspiration, and the courage to propose ideas and concerns.
Research Guides: IDT 4170 and 7170: Mobile Learning: Module 3

Your CECH Library course guide for IDT 4170 and 7170. This guide links to course readings by module. For research support, see the Technology and Instructional Design research guide linked from the home section of this course guide.
PENERAPAN METODE INKUIRI TERHADAP KEMAMPUAN MENGANALISIS UNSUR INTRINSIK DALAM NOVEL “9 SUMMERS 10 AUTUMNS” KARYA IWAN SETYAWAN OLEH SISWA KELAS IX-3 SMP NEGERI 7 MEDAN TAHUN PEMBELAJARAN 2017/2018

The purpose of this study was to describe the students' ability to analyze the intrinsic elements in Iwan Setyawan's novel 9 Summers 10 Autumns before using the inquiry method. This type of research is one group pretest posttest design. The population in the study of students of class IX-3 SMP Negeri 7 Medan. The sample in this study were 32 students of class IX-3 SMP Negeri 7 Medan. The inquiry method is in the sufficient category, this can be seen at an average value of 62.96. Hypothesis testing is tcount> ttable (9.14> 1.67). It can be concluded that there is a significant influence in the application of the inquiry method on the ability to analyze the intrinsic elements of the novel by students of class IX-3 SMP Negeri 7 Medan in the 2017–2018 academic year
Scribe-Free Way for the Specially Abled to Write Exams

The specially-abled face a lot of issues when it comes to taking up exams. They require specific assistance for taking up their exams known as a scribe. However in today’s world finding a scribe is of great difficulty. Even if the scribe is found there are a lot of other practical difficulties while using a scribe to write exams. One such practical difficulty in using a scribe to write exams is that the scribe may not be aware of the technical terms used by the candidate. This causes loss of marks for the candidate if the scribe makes an error. The scribe should also have a legible handwriting which again is a problem. Our project aims at eliminating the need for a scribe and allowing the candidate itself to take up their exams by leveraging the latest technologies such as speech recognition and synthesis. This is achieved with the help of an android application, using which the questions can be stored in a database using administrator login. A separate candidate login is given. The question will be read out to the candidate and the answer will be taken as a voice response.
UPAYA GURU BK DALAM MENINGKATKAN KEMAMPUAN PERENCANAAN KARIR SISWA KELAS XI MELALUI LAYANAN INFORMASI DI SMK SURYA DHARMA BANDAR LAMPUNG TAHUN PELAJARAN 2018/2019

Abstract: This research aims to improve the student’s career plan ability to determine the steps to achieve the goals based on their ability and the requirements. Career plan ability of students grades XI SMK Surya Dharma is in the low categories based on the result of observation. This research aims to prove the effectiveness of public career information service for students grades XI SMK Surya Dharma Bandar Lampung.The subject of career plan ability is 15 student of Accounting Major grade XI to get the statistic data of observation. The techniques of data submit is using source triangulation by comparing the result of observation, interview with the students and the result of documentation. Triangulation techniques focus on the effectiveness process and achieve the goals.The result of the research is public career information service can improve the career plan ability of the student with the percentage 61% at the beginning of the observation and increase to 77.56% in the final of the observation. The conclusion is public career information service can improve the career plan competence of the students grade XI SMK Surya Dharma Bandar Lampung.
The effect of electronic banking services usage on clients electronic loyalty

BACKGROUND AND OBJECTIVES This research targets at investigating and identifying the factors affecting electronic loyalty (E-loyalty) of electronic banking services (E-banking services) in Jordanian bank sector from clients' point of view. The scale of eTailQ was appointed to accomplish the research objectives. The procedures of current research were conducted under COVID-19 pandemic conditions such data collection, access the sample and different aspects. The model of current research was adopted based on three stages which are aiming at measuring the level of influence of  independent determinants; that are subject norms, value perception, web design, reliability, customer support security; through mediation determinants; that are Electronic-satisfaction (E-satisfaction) and Electronic-trust (E-trust); on the E-loyalty of E-banking services usage.METHODSThe population of the current research was the Jordanian clients who use the E-banking services, the sample size was 403 client. Structural Equation Model was declared to be a methodology of research to acquire the research outcomes.FINDINGDepending on the obtained outcomes, Reliability, Customer support, Value Perception, and Subject Norms have a positive effect on E-satisfaction with the .484, -.166, .281, and .249 scores respectively. Moreover, Web design, Reliability, Customer support, and Security/privacy a positive effect on E-trust with 199, .719, -.017, and .463scores, respectively. The results also indicated that E-satisfaction and E-trust have a positive effect on E-loyalty with the .441 and .515 scores, respectively.CONCLUSIONThe focal result of present study is that scale of eTailQ is an optimal measurement for determining the factors that impact the clients E-loyalty of E-banking services usage in Jordanian banks. The present study is encouraged the related specialists to conduct many investigations attached to E-banking services and the development process of E-loyalty.