Reviewerly/exHarmony huggingface dataset:
Evaluasi Kinerja Sistem Informasi Kepegawaian pada Dinas Kependudukan dan Catatan Sipil Salatiga Menggunakan COBIT 5

The information system used must be balanced with the correct processing to support business processes and become an operational supporter of the organization. In caryyng out business process there are several factors that must be considered by the company, not only focusing on the use of information technology that supports business processes, but the company must be able to focus on maintenance, monitoring and management. Therefore, researchers use the Monitor, Evaluate and Assess domains. The purpose of this study is to measure the level of information technology maturity at Dinas Kependudukan dan Catatan Sipil Kota Salatiga. The research methodology is a qualitative method, by collecting data and interviews with informants. The results of this study are to determine the level of maturity of Dinas Kependudukan dan Catatan Sipil Kota Salatiga and provide recommendations, so that the application of information technology can be better.
Abnormally detection based on feature similarity measure of image time series in zinc flotation

Aiming at the problem that the anomaly detection process of the flotation process is repeated and the abnormal trend can be captured and the number of abnormal samples is inferior, an anomaly detection method based on the similarity measure between the time series features of the foam image is proposed. The time-series bubble image is collected by the real- time acquisition system in the industrial field, and the size feature of the bubble image is extracted. The log-norm function is used to fit the bubble size distribution method to eliminate the left tilt and large peak difference of the bubble histogram shape, the method of time series piecewise linear representation is then used to generate the trend characteristics of the bubble time series. The probability of abnormal conditions is evaluated by the degree of difference from the trend characteristics of the typical anomalous process foam image, and the Markov distance method is used to measure the similarity to eliminate the influence between different dimensions. Anomaly detection is implemented by using similarity matching with features of time series anomaly feature library. The results of industrial operation data test show that the method can effectively perform online anomaly detection, and successfully divide the abnormal trend data mixed in the experimental process. The effectiveness of the method is verified by the foam image test data set in the industrial field.
Integration of Cloud Technologies in Teaching Foreign Languages in Higher Education Institutions

This study was aimed at summarizing theoretical knowledge of students studying Economics, enhancing the educational process and training skills of independent long-term professional upgrade of students (sustainability training) through the use of an English-taught training program implemented through the use of MS Office 365 cloud services. The variational traits studied were identified: educational motivation, self-confidence, cognitive and creative skills. The study used methods that are recommended for quantitative research, namely: Raschâ€™s models for measuring academic motivation, methods for determining the level of academic confidence; methods of diagnosis of cognitive reflection and decision making, and a questionnaire to determine the level of creativity of thinking. The results of the diagnostic tests on academic motivation were processed using the Rasch Unidimensional Measurement Model (RUMM-2010) software, and the results of other tests were processed using SPSS 10.0.5., Statistica v. 5.5 A., MathCAD 2000 Pro. It has been found that the problem of integrating cloud technologies into the teaching foreign languages has been of interest of scholars, as the former are gradually becoming a full-fledged educational tool, allowing all institutions to create their own online spaces. In terms of language teaching methods, the used in this study teaching approach proved to create the learning environment helping to deal with the studentsâ€™ communication and interaction barriers, reluctance to being engaged resulted in the enhanced studentsâ€™ learning activity, their motivation for learning. This approach addressed the studentsâ€™ needs in developed logical (critical) thinking and creative tactic to problem-solving, student memory (cognitive component). The integration of cloud (education) services in general proved to increase the efficiency of the learning process. https://doi.org/10.26803/ijlter.19.2.4
White-Box Traitor-Tracing from Tardos Probabilistic Codes

In this paper, we address the problem of tracing traitors in the white-box model. A traitor tracing system generally comes with a broadcast encryption scheme where each user is equipped with a secret that allows him to decrypt broadcast data. When a broadcast encryption scheme is provided with a tracing procedure, the user’s key is used to uniquely identify him. A white-box model refers to a context where an attacker shares the host with a software implementation of a cryptographic algorithm and controls the execution environment. Thus, a traditional broadcast encryption scheme will fail in this context since an adversary may steal the user’s decryption key and illegally decrypts broadcast contents. In this work, we describe a traitor tracing system where each user is provided with a distinct key generation function instead of a secret key. The key generator is made user-specific and enables to generate a content key which is used to decrypt the encrypted content. We use techniques of White-Box Cryptography to build the key generation function and use a collusion-secure code to derive the user-specific key generators. Finally, we prove that the system is collusion-resilient.
SATUA BALI SEBAGAI MEDIA LITERASI MASYARAKAT BALI

The low reading interest and the contribution of behavioral deviations as a manifestation of the poor character of the students. Moral degradation, there are many behavioral deviations that reflect not yet maximal character education among children and adolescents. Satua is part of the Purwa Bali Literature which is a prose. Satua or dogeng also presents all forms of stories that have always been there and are told with generations. In fostering a culture of literacy or reading culture, it is necessary to have help or support from the environment, it is also very important to provide interesting reading so students are interested in reading. One form or type of reading that is interesting for students is Satua. Many Balinese contain moral values so that it is very effective as a medium for handling character. After students can understand the one reading text, the teacher then discusses the characters available in this story to be given so that students are able to implement it in their daily lives
Gimme That Model!: A Trusted ML Model Trading Protocol.

We propose a HE-based protocol for trading ML models and describe possible improvements to the protocol to make the overall transaction more efficient and secure.
Determination of Malaria Parasite Concentration using Image Processing

Malaria may be a severe communicable disease caused by feminine genus Anopheles mosquito.In 2016 alone 216 million cases of protozoal infection occurred worldwide and 445000 died.Thus treatment ought to be initiated as shortly as attainable.Except species of infecting parasite, concentration of protozoal infection decides the course of correct treatment.Patients with severe protozoal infection want intensive parental care till the parasite density falls below 1% and that they will tolerate oral medical care.If blood disorder exceeds 10% then transfusion is also necessary.A general structure of image process is employed to search out the concentration of malaria parasite.The skinny blood smear pictures of Giesma stained square measure processed.The system uses intensity as a feature to search out the malaria parasite.The image is pre-processed and binarized and metameric to search out the circles of interest wherever infected erythrocytes square measure found.This investigates the employment and application of Digital Image process for detecting malaria parasite and deciding its concentration exploitation microscopic color pictures.
THE EFFECT OF GENRE BASED APPROACH ON STUDENTS’ WRITING ABILITY OF RECOUNT TEXT

The objective of this research was to investigate the effect of genre based approach on students’ writing ability of recount text. This study was conducted through quasi experimental design. The population were the total of 52 second year students of SMAN 05 Bengkulu Tengah (IPS1 as experimental class dan IPS2 as control class). Theexperimental class was taught by using genre based approach and the control class was taught by using the conventional approach.The instrument was a written test of a recount text. Before analyzing the data by using t-test, a normality and homogenity test were conducted, then scored by using assessment rubric of Heaton (1988). The result showed that there was significant effect of genre based approach on students’ writing ability of recount text. The effects were on the content, organization, vocabulary, language use, and mechanics.
Healy, Robert Gartley - Biographical entry - Index to the AMA archive

Healy, Robert Gartley - Biographical entry - Index to the AMA archive - NAME is a biographical, bibliographical and archival database of SUBJECT with links to related articles and images. ADD MORE DESCRIPTION AS REQUIRED
Robust Estimator based Adaptive Multi-Task Learning

Multi-Task Learning(MTL) algorithm leverages valuable information across similar tasks to improve regression accuracy. However, applications in practice often encounter scenes that cannot give an accurate relationship between the large-scale number of multiple tasks. When task clustering based method is employed in those cases, excessive connections between dissimilar tasks and meaningless dimensions would cause a poorly predictive performance, which cannot be perfectly interpreted by existing MTL methods. In this paper, a novel MTL method is proposed to make more accurate use of valuable shared information between multiple tasks, where a redescending robust estimator is utilized to adaptively unify the continuous clustering of a large-scale number of tasks and dynamically selecting valuable features of few-shot tasks. To enable a better description of relationships between multiple tasks, we formulate a multi-convex objective function that can be optimized alternatively. After analyzing the complexity and convexity of the problem, we provide a scalable solving approach which can converge to the optimum with approximately linear time complexity. Compared with state-of-the-art models, the proposed approach performs better RMSE score and time efficiency both in synthetic and realistic datasets. Meanwhile, with similar computational overhead, the experiment demonstrates that our method has better regression accuracy than clustering tasks alone or selecting valuable features individually.
ASAN: Self-Attending and Semantic Activating Network towards Better Object Detection

Recent top-performing object detectors usually depend on a two-stage approach, which benefits from its region proposal and refining practice but suffers low detection speed. By contrast, one-stage approaches have the advantage of high efficiency while sacrifice their accuracies to some extent. In this paper, we propose a novel single-shot object detection network which inherits the merits of both. Motivated by the idea of semantic enrichment to the convolutional features within a typical deep detector, we propose two novel modules: 1) by modeling the semantic interactions between channels and the long-range dependencies between spatial positions, the self-attending module generates both channel and position attention, and enhance the original convolutional features in a self-guided manner; 2) leveraging the class-discriminative localization ability of classification-trained CNN, the semantic activating module learns a semantic meaningful convolutional response which augments low-level convolutional features with strong class-specific semantic information. The so called self-attending and semantic activating network (ASAN) achieves better accuracy than two-stage methods and is able to fulfil real-time processing. Comprehensive experiments on PASCAL VOC indicates that ASAN achieves state-of-the-art detection performance with high efficiency.
Blind Feature-Based Steganalysis with and Without Cross Validation on Calibrated JPEG Images Using Support Vector Machine

The paper presents the comparative result analysis of calibrated JPEG images with and without cross-validation technique. Pixel-value differencing, LSB replacement, F5 and LSB Matching are used as steganographic algorithms. 25% of embedding is considered for the analysis. The images are calibrated before they are considered for analysis and relevant features are extracted. The classifier used is SVM with six various kernels and four types of sampling methods. The sampling methods are linear, shuffle, stratified and automatic. Radial, dot, Epanechnikov, multiquadratic, polynomial and ANOVA kernels are taken into consideration in this paper.
Bogdanov&amp;apos;s Organizational Theory: Work, Communication, Culture

The article analyzes Bogdanov's approach to the socio-historical process. The use of monistic, systematic methodology by the thinker allows us to consider his view of man and society in the variety of meanings and relationships in which he is included. The application of natural-scientific, in particular, evolutionary models allowed to present the socio-historical process as an adaptation to the development of comprehensive social relations in the unity of labor—communication—culture. It is shown that for the equilibrium development and the state of society, it is necessary to strengthen and harmonize all components of its parts and relations.
Tokenizer for Icelandic text

Tokenizer is a compact pure-Python (2.7 and 3) executable program and module for tokenizing Icelandic text. It converts input text to streams of tokens, where each token is a separate word, punctuation sign, number/amount, date, e-mail, URL/URI, etc. It also segments the token stream into sentences, considering corner cases such as abbreviations and dates in the middle of sentences. More information at: https://github.com/mideind/TokenizerTokenizer er pakki fyrir Python 2.7 og 3, asamt skipanalinutoli, sem ser um tilreiðslu islensks texta. Pakkinn umbreytir inntakstexta i tokastraum. Hver toki er stakt orð, greinarmerki, tala/upphaeð, dags-/timasetning, netfang, vefsloð o.s.frv. Tolið skiptir tokastraumnum einnig i setningar og tekur tillit til jaðartilvika eins og skammstafana og dagsetninga i miðjum setningum. Frekari upplýsingar a: https://github.com/mideind/Tokenizer
STC: Improving the Performance of Virtual Machines Based on Task Classification

Virtualization technology provides crucial support for cloud computing, and the virtual CPU (vCPU) scheduling in a virtualization system is one of the key factors to determine the system’s performance. However, due to the semantic gap in the virtualization system, the mainstream current scheduling policy does not take the tasks’ characteristics and spin lock into account, which leads to performance degradation in a virtual machine. This paper proposes a vCPU scheduling system STC (Virtual CPU Scheduling Based on Task Classification) in KVM to bridge the semantic gap. In STC, every virtual machine is configured with two types of vCPUs, among which the one with a shorter scheduling period is called the short vCPU (svCPU) and the ones with the default period are called the long vCPU (lvCPU). STC utilizes the Naïve Bayes classifier to classify the tasks, and the I/O-bound tasks are allocated to the svCPU, while the CPU-bound tasks are processed by lvCPUs. Correspondingly, in a host, two types of physical CPUs, the sCPU and lCPUs, are set to process the thread svCPU and lvCPUs. Moreover, lvCPUs adopt dispersive scheduling to alleviate Lock-Holder Preemption (LHP). STC improves the I/O response speed and saves the resources. Compared with the default algorithm, STC has achieved an 18% time delay decrease, a 17%–25% bandwidth improvement, and a 21% overhead decrease and ensured the fairness of the whole system.
Þátttaka nemenda í kennslustundum í framhaldsskólum á Íslandi

Rannsökuð var þátttaka nemenda í kennslustundum í níu íslenskum framhaldsskólum og var markmið þríþætt. Í fyrsta lagi að greina hvernig þátttaka nemenda birtist í kennslustundum. Í öðru lagi að skoða hvort kennsluaðferðirnar í þeim kennslustundum þar sem þátttaka nemenda var til staðar væru kennarastýrðar eða nemendamiðaðar. Í þriðja lagi að skoða viðmót og athafnir kennara í kennslustundum þar sem nemendur tóku þátt. Unnið var úr 130 vettvangslýsingum á kennslustundum í níu framhaldsskólum sem safnað var á skólaárinu 2013–2014 og haustið 2014 í rannsóknarverkefninu Starfshættir í framhaldsskólum. Kennslustundir voru flokkaðar eftir því hvort þær náðu viðmiðum um þátttöku. Viðmiðið var að 75% af nemendunum tækju þátt í því sem kennarinn ætlaðist til af þeim í 75% af tímanum og náðu 83 kennslustundir þessu viðmiði. Algengustu birtingarmyndir þátttöku nemenda í kennslustundum voru að þeir unnu verkefni og spurðu kennara um námsefnið og komu þessar athafnir fram í meirihluta kennslustundanna. Í um helmingi stundanna kom einnig fram að nemendur sýndu athygli (fylgdust með) og ræddu um viðfangsefnið. Niðurstöður benda til þess að þátttaka nemenda í kennslustundum tengist ekki hvaða kennsluaðferðir eru notaðar, þar sem þátttökustundirnar skiptust frekar jafnt í nemendamiðaðar og kennarastýrðar kennslustundir. Flestar birtingarmyndir þátttöku nemenda komu tiltölulega jafnt fyrir í bæði kennarastýrðum og nemendamiðuðum kennslustundum en athöfnin að sýna athygli var algengari í kennarastýrðum kennslustundum og athafnirnar að leita og nota efnivið og hjálpast að við að leysa verkefni komu oftar fram í nemendamiðuðum kennslustundum. Flestar þátttökustundanna einkenndust af því að kennari sýndi jákvætt viðmót, hafði skapað hlýlegt andrúmsloft, hafði gefið skýr fyrirmæli um vinnu nemenda eða verið hvetjandi. Þannig virðast viðmót og athafnir kennara hafa haft jákvæð áhrif á þátttöku nemenda í kennslustundunum. Niðurstöðurnar undirstrika að mikilvægt er að gefa viðmóti og athöfnum kennara sérstakan gaum í samhengi við námslega skuldbindingu nemenda.
MODELING OF THE MONITORING SYSTEM OF LEARNING OUTCOMES IN ADULT EDUCATION

In recent years, the need has arisen for a change in conceptual approaches to the phenomena of “monitoring” and “assessment” of learning outcomes in adult education. The ultimate goal of monitoring should be to strengthen and achieve a high level of responsibility of the learners for the process and outcomes of their education. The purpose of the research is to create a model of the monitoring system of learning outcomes in adult education and to describe a methodology for implementing alternative methods of monitoring. Research methods: a theoretical analysis of the concept of “monitoring”, generalization and systematization of approaches to monitoring, analysis of the characteristics of adult education, modeling of the monitoring system of learning outcomes in adult education, ranging monitoring types by teachers, analysis of the results of the empirical research. The main results of the research: a model of the monitoring system oflearning outcomes in adult education includes preparatory, practical and analytical stages and it is built taking into account the purpose, content, methods of pedagogical communication, means, timing and duration of control. It also includes traditional and alternative ways of monitoring learning outcomes with guidelines for their use in adult education.
Characteristics of a good language learnerin relation to her language learning strategies

The purpose of this research is to know the characteristics possessed by Meta, a single subject in this study, as a good language learner in relation to her language learning strategies. It is a case study design. The result of the research shows that Meta possesses all of the kinds of language learning strategies (memory, cognitive, compensation, metacognitive, affective and social strategies). In terms of memory strategy she visualizes new languages. She remembers new words by writing the words for many times. In terms of metacognitive strategy she creates opportunities to practice English language skills. She identifies errors in understanding or producing the new language. She tracks the source of important errors and tries to eliminate them. She also evaluates her own progress. In terms of cognitive strategy she makes summary of English text, she highlights certain words and does scanning and skimming in reading English text. In terms of affective strategy she pushes herself to take risk in language learning situation, she discovers and controls motivation that influences language learning, she gives reward to herself for doing good performance in her language learning. In terms of social strategy she works with other language learners to improve her language skills. In terms of compensation strategy she uses guessing technique in reading and uses synonym technique in speaking.
An Easy-to-implement Construction for $(k,n)$-threshold Progressive Visual Secret Sharing Schemes

Visual cryptography encrypts the secret image into $n$ shares (transparency) so that only stacking a qualified number of shares can recover the secret image by the human visual system while no information can be revealed without a large enough number of shares. This paper investigates the $(k,n)$-threshold Visual Secret Sharing (VSS) model, where one can decrypt the original image by stacking at least $k$ shares and get nothing with less than $k$ shares. There are two main approaches in the literature: codebook-based schemes and random-grid-based schemes; the former is the case of this paper. In general, given any positive integers $k$ and $n$, it is not easy to design a valid scheme for the $(k,n)$-threshold VSS model. In this paper, we propose a simple strategy to construct an efficient scheme for the $(k,n)$-threshold VSS model for any positive integers $2\leq k\leq n$. The crucial idea is to establish a seemingly unrelated connection between the $(k,n)$-threshold VSS scheme and a mathematical structure -- the generalized Pascal's triangle. This paper improves and extends previous results in four aspects: Our construction offers a unified viewpoint and covers several known results; The resulting scheme has a progressive-viewing property that means the more shares being stacked together the clearer the secret image would be revealed. The proposed scheme can be constructed explicitly and efficiently based on the generalized Pascal's triangle without a computer. Performance of the proposed scheme is comparable with known results.