Reviewerly/exHarmony huggingface dataset:
MOTION GRAPHIC SEBAGAI MEDIA SOSIALISASI TENTANG PUBLIC RELATION UNTUK KARYAWAN OWNTALK.CO.ID

The development of technology in various aspects is very influential in the field of information and communication. This development can be proven by the existence of motion graphics. One company that implements motion graphics is Owntalk.co.id. Owntalk.co.id is an online news media site that was established on August 19, 2019. As a new company that is 2 years old, currently, Owntalk.co.id needs a public relations division that functions to improve the company's image and build relationships through its employees. This study aims to socialize public relations through the creation of motion graphics that are unique and easy to understand by employees of Owntalk.co.id. The benefit of public relations socialization using motion graphics is the establishment of an understanding of public relations therefore the employees can implement public relations activities according to their roles and functions. This research uses the Luther Sutopo design method, with 6 stages of concept, design, collecting, assembly, testing, and distribution materials. In this study, the results were in the form of a motion graphics video with a duration of 2 minutes 33 seconds with a percentage of 96.8%, which means that this motion graphics video is useful for Owntalk.co.id in disseminating public relations materials to its employees.
IMPROVING STUDENTS’ WRITING ABILITY IN NARRATIVE TEXT THROUGH ESTAFET WRITING METHOD AT NINTH GRADE STUDENTS OF SMP SWASTA BUKIT CAHAYA 2020/2021

This research is focused in learning writing by using Estafet writing method at SMP Swasta Bukit Cahaya 2020/2021. The design of this research is quantitative research by using the theory of Aarikunto 2010 the researcher got the teqhnique of collecting the data and analyzing the data and the researcher used Pre-test and Post-test as the way of collecting the data.the population of this research is 23 students the researcher will take all the population as the sample. The data were collected by using the Pre-test and Post-test, the Pre-test were given before the treatment and the Post-test were given after the treatment. The result of the research shows the differences between the students’ ability of writing narrative text before and after the treatment. Starting by the mean which taking all the score from the students test in total and devided by the students total and the researcher got for the Pre-test is 52 and for the Post-test is 84. For the standart deviation is 17,2. The effect size is 1,8. In the using of esstafet writting method it can be seen that it’s improving the students writing narrative text ability at SMP Swasta Bukit Cahaya 2020/2021. The researcher also used theory of Jacobs (1981) to gather the data by using the rubric scoring table which consist of Content, Organization, Vocabulary, Language Use And Mechanics
IMPROVING THE STUDENTS’ READING COMPREHENSION ON NARRATIVE TEXT BY USING BUZZ GROUP TECHNIQUE AT GRADE VII OF SMP YAYASAN PERGURUAN KELUARGA PEMATANG SIANTAR ACADEMIC YEAR 2019/2020

This research was aimed at improving the reading narrative text comprehension of the grade seven student of SMP YP.KeluargaPematangsiantar through the use of buzz group technique.This research is action research conducted in SMP YP.Keluarga. The subjects of the study were 26 students of VII-1 as a control class and 26 students as a experimental class of SMP YP.Keluarga in the 2019/2020 academic year. The data of this research were quantitative as the supporting data. The result in this research are teaching by using buzz groups technique can effectively improve students’ reading comprehension. From the observation, the reseacher found that during the action, the students have shown their improvement such as they were able to comprehend the text well, the situation of the teaching and learning process became more enjoyable and interesting, and all of the students were involved in the teaching and learning process. They can share their knowledge and help each other in understanding the lesson material. The students not only learn from the teacher explanation, but they can learn from their friends who also learn the same thing. From the reading narrative text comprehension test, the students’ pre-test in control class mean score was 16.47 , increasing to 6.8 in thepost-test. And the students’ pre-test in experimental class mean score was 6.2, increasing to 8.0 in the post-test. Therefore, it can be concluded that teaching reading by using buzz groups technique can improve the students’ reading narrative text comprehension
Energy Efficient Distributed Processing for IoT

In this paper, the entire IoT-fog-cloud architecture is modelled, the service placement problem is optimized through Mixed Integer Linear Programming (MILP) and the total power consumption is jointly minimized for processing and networking. Four aspects of IoT service placements are examined: 1) non-splittable services, 2) splittable services, 3) inter-service processing overhead for sub-service synchronization and 4) deployment of special-purpose cloud data centers (SP-DCs). The results showed that for a capacitated problem, service splitting introduces power consumption savings of up to 86% compared to 46% with non-splittable services in relation to processing in general-purpose data centers (GP-DCs). Moreover, it is observed that the inter sub-service processing overhead has a great influence on the total number of service splits. However much insignificant the ratio of the processing overhead, the results showed that this is not a trivial matter and hence much attention needs to paid to this area in order to make the best use of the resources that are available in the edge of the network. Moreover, the optimization results showed that, for very high demands, power savings of up to 50% could be achieved with SP-DCs compared to 30% with GP-DCs.
Fault Matters: Sensor Data Fusion for Detection of Faults using Dempster-Shafer Theory of Evidence in IoT-Based Applications

Fault detection in sensor nodes is a pertinent issue that has been an important area of research for a very long time. But it is not explored much as yet in the context of Internet of Things. Internet of Things work with a massive amount of data so the responsibility for guaranteeing the accuracy of the data also lies with it. Moreover, a lot of important and critical decisions are made based on these data, so ensuring its correctness and accuracy is also very important. Also, the detection needs to be as precise as possible to avoid negative alerts. For this purpose, this work has adopted Dempster-Shafer Theory of Evidence which is a popular learning method to collate the information from sensors to come up with a decision regarding the faulty status of a sensor node. To verify the validity of the proposed method, simulations have been performed on a benchmark data set and data collected through a test bed in a laboratory set-up. For the different types of faults, the proposed method shows very competent accuracy for both the benchmark (99.8%) and laboratory data sets (99.9%) when compared to the other state-of-the-art machine learning techniques.
Learning Generalisable Coupling Terms for Obstacle Avoidance via Low-dimensional Geometric Descriptors

Unforeseen events are frequent in the real-world environments where robots are expected to assist, raising the need for fast replanning of the policy in execution to guarantee the system and environment safety. Inspired by human behavioural studies of obstacle avoidance and route selection, this paper presents a hierarchical framework which generates reactive yet bounded obstacle avoidance behaviours through a multi-layered analysis. The framework leverages the strengths of learning techniques and the versatility of dynamic movement primitives to efficiently unify perception, decision, and action levels via low-dimensional geometric descriptors of the environment. Experimental evaluation on synthetic environments and a real anthropomorphic manipulator proves that the robustness and generalisation capabilities of the proposed approach regardless of the obstacle avoidance scenario makes it suitable for robotic systems in real-world environments.
SeGMA: Semi-Supervised Gaussian Mixture Auto-Encoder

We propose a semi-supervised generative model, SeGMA, which learns a joint probability distribution of data and their classes and which is implemented in a typical Wasserstein auto-encoder framework. We choose a mixture of Gaussians as a target distribution in latent space, which provides a natural splitting of data into clusters. To connect Gaussian components with correct classes, we use a small amount of labeled data and a Gaussian classifier induced by the target distribution. SeGMA is optimized efficiently due to the use of Cramer-Wold distance as a maximum mean discrepancy penalty, which yields a closed-form expression for a mixture of spherical Gaussian components and thus obviates the need of sampling. While SeGMA preserves all properties of its semi-supervised predecessors and achieves at least as good generative performance on standard benchmark data sets, it presents additional features: (a) interpolation between any pair of points in the latent space produces realistically-looking samples; (b) combining the interpolation property with disentangled class and style variables, SeGMA is able to perform a continuous style transfer from one class to another; (c) it is possible to change the intensity of class characteristics in a data point by moving the latent representation of the data point away from specific Gaussian components.
Adversarial Examples to Fool Iris Recognition Systems

Adversarial examples have recently proven to be able to fool deep learning methods by adding carefully crafted small perturbation to the input space image. In this paper, we study the possibility of generating adversarial examples for code-based iris recognition systems. Since generating adversarial examples requires back-propagation of the adversarial loss, conventional filter bank-based iris-code generation frameworks cannot be employed in such a setup. Therefore, to compensate for this shortcoming, we propose to train a deep auto-encoder surrogate network to mimic the conventional iris code generation procedure. This trained surrogate network is then deployed to generate the adversarial examples using the iterative gradient sign method algorithm. We consider non-targeted and targeted attacks through three attack scenarios. Considering these attacks, we study the possibility of fooling an iris recognition system in white-box and black-box frameworks.
Quantitative Mitigation of Timing Side Channels

Timing side channels pose a significant threat to the security and privacy of software applications. We propose an approach for mitigating this problem by decreasing the strength of the side channels as measured by entropy-based objectives, such as min-guess entropy. Our goal is to minimize the information leaks while guaranteeing a user-specified maximal acceptable performance overhead. We dub the decision version of this problem Shannon mitigation, and consider two variants, deterministic and stochastic. First, we show the deterministic variant is NP-hard. However, we give a polynomial algorithm that finds an optimal solution from a restricted set. Second, for the stochastic variant, we develop an algorithm that uses optimization techniques specific to the entropy-based objective used. For instance, for min-guess entropy, we used mixed integer-linear programming. We apply the algorithm to a threat model where the attacker gets to make functional observations, that is, where she observes the running time of the program for the same secret value combined with different public input values. Existing mitigation approaches do not give confidentiality or performance guarantees for this threat model. We evaluate our tool SCHMIT on a number of micro-benchmarks and real-world applications with different entropy-based objectives. In contrast to the existing mitigation approaches, we show that in the functional-observation threat model, SCHMIT is scalable and able to maximize confidentiality under the performance overhead bound.
Field Recordings: A Manifesto

The article focuses on the political implications of field recording (FR) in relation to sound ecology, education, art, and technology. On the one hand, it discusses how FR can protect us as a social tool in a paradoxical relationship between FR as an artistic practice and social networks that motivate alienation. On the other hand, it addresses the difference between what we perceive as sonic properties used for aesthetic purposes and what neural networks compute to create their internal structures in the process of artificial intelligence. This article adopts a preliminary approach to the above-mentioned topics while it seeks to raise questions and awareness. Drawing upon such theorists as Voegelin, Steingo and Sykes, LaBelle, and Agostinho, it adopts a pragmatic perspective on everyday life and its political implications.
Quantifying Differences Between Machine Learning Classification Models Applied to Cancer Microscopy Data

Journal Article Quantifying Differences Between Machine Learning Classification Models Applied to Cancer Microscopy Data Get access William Franz Lamberti, William Franz Lamberti Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA Search for other works by this author on: Oxford Academic Google Scholar Chongzhi Zang Chongzhi Zang Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA Corresponding author: zang@virginia.edu Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 28, Issue S1, 1 August 2022, Pages 3006–3008, https://doi.org/10.1017/S1431927622011266 Published: 01 August 2022
Influence of Knowledge Management Capability on Internationalization Status of Public Universities in Kenya

Purpose: The purpose of the study was to analyze the influence of knowledge management capability on internationalization status of public universities in Kenya.&#x0D; Methodology: The study was conducted in 31 public chartered universities in Kenya and employed a descriptive research design. A cross-sectional survey involving both analytical and descriptive methods to address the objectives of the study was used. To analyze quantitative data, descriptive factor analysis and inferential statistics (correlation and regression) were used. To analyze quantitative data, descriptive factor analysis and inferential statistics (correlation and regression) were used.&#x0D; Results: Regression results showed that knowledge management capability had a significant and positive influence on internationalization status.&#x0D; Recommendations: The study further recommends that universities should utilize knowledge to enhance internationalization status through development of knowledge management policies and to encourage employees to utilize the knowledge gained on internationalization to develop new innovations and come up with new products and services. It is important for policy makers in public universities to develop robust and dedicated knowledge management capabilities. This is because knowledge management lead to growth and expansion of organizations internationally and subsequently improve the firm’s performance.
AN ANALYSIS OF ENGLISH TEACHERS’ STRATEGIES ONE -LEARNING CLASSES DURING COVID-19 AT SMK NEGERI 1 PEMATANGSIANTAR

The purpose of the study is to analyze the strategies of the English teacher on E-learning classes during covid-19 at SMK Negeri 1 Pematangsiantar. This type of research was field research with qualitative approach. This study aimed at answering the following research questions: (1) what are the strategies on English e-learning classes during the COVID-19 pandemic at SMK Negeri 1 Pematangsiantar? Data collection techniques in this study are observation, interview, and documentation. The results of the study show that (1) The teachers use different strategies because the expected skill output are different, for writing skills the teacher uses 3 strategies namely planning, drafting, and editing. As for listening skills, the teacher applies several strategies such as listening to songs, writing song lyrics, matching lyrics, and finally sing a songs. For reading the researcher find 2 strategies, like that reading of textbook, and observed, and make a sentence. For the, speaking the researcher find the strategies such as using video on you tube, conversation, and make poetry. But all of them use the video-based learning model and also virtual education through WhatsApp. (2) Strategies in teaching through e-learning classes during the COVID-19 pandemic greatly assisted teachers in the teaching and learning process to achieve learning goals
IMPROVING THE STUDENTS’ READING COMPREHENSION BY USING COMIC STRIPS AT SMAMUHAMMADIYAH-7 SERBELAWAN GRADE XI

This Research entitled improving the students’ reading comprehension by using comic strips at SMA MUHAMMADIYAH-7 Serbelawan. It concerned with the problem: Does comic strips effective to improve students’ reading comprehension through narrative text at the eleventh grade of SMA MUHAMMADIYAH-7 Serbelawan?. To answer the research problem, some theories are used: Kligner, Vaughn &amp; Boardman (2007), to Patel and Jain (2008), Snow (2002), Arikunto(2009,2010). Reading is basic skills which should be studied are speaking, listening, reading and writing and a process of looking at series of written symbols and getting meaning from them. Comic strips is some series of drawing that tell a story and drawings interrelated panels to display brief humor or form a narrative often serialized with text in balloons and captions and with the comic strips can improve reading comprehension of students in English. This research is designed into quantitative research by following experimental design of control class and experimental class. The population is 216 students and the sample is taken by using cluster sampling technique so that the sample is 72 students. The research subject is XI IPA1 as experimental class and XI IPA2 as control class of SMA MUHAMMADIYAH-7 Serbelawan. Research instrument is multiple choices. The data analysis is started from scoring the students’ answer sheet, tabulating students’ pre-test and post-test scores, calculating the standard deviation pre-test and post-test scores. Based on the data analysis, it was found before the treatment of using comic stripsvalue pre-test was 1904 and mean (average) was 52,88 in post-test get value was 2132 and mean (average) was 59,22 and the standard deviation pre-test was 10,20 and post-test was 10,01. get value pre-test was 1972 and mean (average) was 54,78 in post-test value was 3004 and mean (average) was 83,45 and the standard deviation pre-test was 6,91 and post-test was 6,93. Using comic strips effective in improvingstudents’ reading comprehension through narrative text at the eleventh grade of SMA MUHAMMADIYAH-7 Serbelawan. The t-table value is on the amount sample (n) 72 subtracted 2 then the number of sample will be 70 which the value of t-table was 1,99. Then, result was df(degree of freedom) =70. So, the t-test result was than 5,73&gt; 4,22 &gt;1,99. It can be concluded that result of experimental class more of control class result that the researcher was accepted
THE CODE - MIXING AND CODE - SWITCHING IN TEACHING ENGLISH AT SEVENTH GRADE OF SMP N 1 RAYA

The objective of this research was to find types of code-mixing and code-switching used in teaching English Raya and to find the factors of using code-mixing and code-switching in teaching English. This research was conducted at SMP N 1 Raya with method of this research used qualitative content analysis method. Population and sample of this research was all of English teachers’ statement which contain code-mixing and code-switching in teaching English at seventh grade of SMP N 1 Raya. The technique of collecting data was recording and interview. The result of this research showed that there were 31 utterances three types of code-mixing and 56 utterances types of code-switching that used by English teachers in teaching learning process. Code-mixing namely intra-sentential code-mixing, intra-lexical code-mixing and involving change of pronunciation. Intra-sentential code mixing was the dominant type that used by English teachers in teaching learning process, which is 24 utterances included intra-sentential code-mixing, 3 utterances included intra-lexical and 4 utterances included Involving change of pronunciation. Code-switching namely tag code-switching, inter-sentential code-switching and intra-sentential code-switching. Inter-sentential code-switching was the dominant type that used by English teachers in teaching learning process, which is 52 utterances included inter-sentential code-switching and 4 utterances included tag code-switching.While the factors of English teachers used code mixing in teaching learning process were social factor whereas topic, participant and situation become aspects which influenced they mixed and switched their language
IMPROVING THE STUDENTS WRITING DESCRIPTIVE TEXT BY USING PICTURES MEDIA IN SENIOR HIGH SCHOOL AT THE TENTH GRADE OF MA SWASTA IKHLASIYAH GUPPI MUSLIMIN

The research focused of Improving Students Writing Descriptive Text by Using Picture Media in senior high school of MA Swasta Ikhlasiyah Guppi Muslimin Academic year 2020/2021. The research design was quantitative method. The population was 29 students and the sample was taken by Sugiyono 2017: 81 at class X with 29 students. The instrument was easy test. The data analysis started from scoring composition and finding different mean of the score. Based on the data analysis the researcher finding also proved that in the pre-test students mean score was only 1475 and the mean was 50,86 and after the treatment, it had been improved since the post-test data was 2168 and the mean was 74,75. After analyzing the data, it was concluded that the use of picture media gives significant contribution in improving student’s competence in writing descriptive text at grade X MAS Ikhlasiyah Guppi Muslimin in academic year 2020/2021
THE GRAMMATICAL ERRORS IN WRITING RECOUNT TEXT AT TENTH GRADE SMA NEGERI 4 PEMATANGSIANTAR

This research intended to find out the grammatical errors made by the students at tenth grade SMA Negeri 4 Pematangsiantar in writing recount text. The method of research was qualitative content analysis. The instrument of the research was the writer herself. The sample constituted 36 students or 15% of the total 249 population. The result of this research can be showed as follow: the grammatical errors in writing recount text at tenth grade SMA Negeri 4 Pematangsiantar the error of omission was 46 (35.5%), error of addition was 5 (3.8%), error of mis-formation was 77 (59.2%), and error of disordering was 2 (1.5%). The dominant errors that the students made were error of mis-formation, 77 (59.2%). It could happen because the lack of using simple past tense, misplacement of adjective words, incorrect usage of singular and plural verb, the wrongness of using personal pronoun, limited knowledge of vocabulary, the mistake of using the article, the wrong form of to infinitive verb, and carelessness
THE USE OF MODELED WRITING STRATEGY ON STUDENTS’ NARRATIVE TEXT ABILITY AT GRADE VIII SMP SWASTA PTPN IV BAH JAMBI IN ACADEMIC YEAR 2019/2020

This study aims to find out whether the writing modeling strategy improves the ability to write narrative texts for seventh grade students of PTPN IV Bah Jambi T.P. Private Junior High School. 2019/2020. There are several reference sources used in writing this research journal as well as conducting direct research on seventh grade students of PTPN IV Bah Jambi Private Junior High School T.P. 2019/2020. Based on the results of data analysis, it was found that the writing modeling strategy significantly improved the ability to write narrative texts for the seventh grade students of PTPN IV Bah Jambi T.P. Private Junior High School. 2019/2020