Reviewerly/exHarmony huggingface dataset:
Multitarget Tracking with Transformers

Multitarget Tracking (MTT) is the problem of tracking the states of anunknown number of objects using noisy measurements, with important applicationsto autonomous driving, surveillance, robotics, and others. In the model-basedBayesian setting, there are conjugate priors that enable us to express themulti-object posterior in closed form, which could theoretically provideBayes-optimal estimates. However, the posterior involves a super-exponentialgrowth of the number of hypotheses over time, forcing state-of-the-art methodsto resort to approximations for remaining tractable, which can impact theirperformance in complex scenarios. Model-free methods based on deep-learningprovide an attractive alternative, as they can in principle learn the optimalfilter from data, but to the best of our knowledge were never compared tocurrent state-of-the-art Bayesian filters, specially not in contexts whereaccurate models are available. In this paper, we propose a high-performingdeep-learning method for MTT based on the Transformer architecture and compareit to two state-of-the-art Bayesian filters, in a setting where we assume thecorrect model is provided. Although this gives an edge to the model-basedfilters, it also allows us to generate unlimited training data. We show thatthe proposed model outperforms state-of-the-art Bayesian filters in complexscenarios, while macthing their performance in simpler cases, which validatesthe applicability of deep-learning also in the model-based regime. The code forall our implementations is made available at (github link to be provided).
Computer Network Design Using PPDIOO Method With Case Study of SMA Negeri 1 Kunir

Technological developments are very beneficial for the world of education, such as the use of the internet in finding and managing information and can help in the teaching and learning process. Before using the internet, there was a computer network that played an important role in it. In building a computer network, a concept or method is needed in designing it, and here the PPDIOO method will be used and uses two types of network topologies, namely star and ring topologies. With the design of this computer network, it can help schools in the teaching and learning process and can improve the quality of teaching, the quality of knowledge and the quality of the abilities of students and teachers.&#x0D; Keywords: Education, Technology, Computer Networks, PPDIOO Method, Network Topology
Kekuatan Statement Narasumber Pada Dokumenetr Potret Dibalik Letusan Sang Kelud

The creation of the documentary film titled Behind the Eruption of the is intended to provide information about the community around Mount Kelud approached by the village of Sugihwaras with its confidence in the curse in the war film held there. In fact, up to now, according to the records of the existing Kelud volcano eruption, those approved such as Kediri, Blitar and Tulungagung are still the same as those discussed in the area, not changing the topography so that the curse on the Lembu Suro beach has not been proven true. Kelud eruption is not strong enough to change the topography of the meeting area. The creator uses a portrait documentary using narration and statement of strength so that the selection of speakers conducted by the creator as in the theory of A-B-C will present speakers with quality that can be trusted and accounted for.
SOIL EC MAPPING SYSTEM USING VERIS 3100 AT YOUNG OIL PALM AREA AT UITM JASIN MALACCA MALAYSIA

Soil electrical conductivity (EC) is a measurement that links with the soil properties that will affect crop productivity. With advances in technology for precision agriculture, Veris Technologies introduce the on-the-go sensors for measuring level of Soil EC. The combination of sensor with EC help in improving our farming system. This study was conducted at Share Farm UiTM Jasin,Melaka in Young Oil Palm area and used to measure the level of EC. This implement (Veris 3100) connected along with Auto Pilot Tractor (New Holland TD575). It works together with GPS to get accurate location before it converted to map form. The collected data contain shallow and deep. Each data shows different amount of EC. Shallow measure from 0-30cm while Deep from 0-90cm and the data measure by millisiemens. Then do an interpolation by using kriging method by used ArcGIS. Function of this software to digitize the data to get it clearer. With the development of ArcGIS software, it improves our map from simply to fully functioning system. Based on the result, it shows that there no much different of EC in that area. Besides, the fact that sands have a low conductivity, silts have a medium conductivity and clays have a high conductivity. Keyword: Deep, shallow, Soil EC, Veris 3100, GPS, ArcGIS
The Spatially-Correlative Loss for Various Image Translation Tasks

We propose a novel spatially-correlative loss that is simple, efficient and yet effective for preserving scene structure consistency while supporting large appearance changes during unpaired image-to-image (I2I) translation. Previous methods attempt this by using pixel-level cycle-consistency or feature-level matching losses, but the domain-specific nature of these losses hinder translation across large domain gaps. To address this, we exploit the spatial patterns of self-similarity as a means of defining scene structure. Our spatially-correlative loss is geared towards only capturing spatial relationships within an image rather than domain appearance. We also introduce a new self-supervised learning method to explicitly learn spatially-correlative maps for each specific translation task. We show distinct improvement over baseline models in all three modes of unpaired I2I translation: single-modal, multi-modal, and even single-image translation. This new loss can easily be integrated into existing network architectures and thus allows wide applicability.
Assessment of teaching proficiency using qualimetric technology

The relevance of studying the basic psychological and pedagogical principles of the formation and improvement of teaching proficiency in the current context is due to the social and applied value of the continuing professional development of the teacher. It should be emphasized that the theory of education and teaching practice are not being transformed synchronously, which causes certain contradictions. Therefore objective monitoring of teaching proficiency is required. Nowadays, Russian education is in dire need of teachers who can improve the educational process, offer effective original methods and concepts, master teaching tools, and improve the quality of services provided. Only a teacher who continuously enhances teaching proficiency can meet the challenges of professional reality. The task of encouraging the teacher to improve professional skills seems to be difficult to achieve. The teaching proficiency assessment system, which is currently operating in secondary and higher education institutions, only allows determining the current level of professionalism, but is not able to show the dynamics of changes and determine existing prospects. In this aspect, the monitoring of teaching proficiency with the use of a complex quantitative technology based on the concept of latent variables is of particular importance. The teacher should meet the requirements of the time, demonstrate teaching proficiency and creativity, which are based on professionally important qualities and pedagogical culture. Any teacher should adhere to a humanistic philosophy, consider a person as the highest value and appreciate the uniqueness of each student’s personality, build relationships based on respect and mutual trust.
Measurement of AI3, AI4, and DS4 IT Process Maturity Using the Cobit 4.1 Framework at KOMINFO Bantul

This research discusses the condition of information technology at KOMINFO (DISKOMINFO) Bantul governance. This study aims to discover where has KOMINFO applied information technology governance properly. This research focuses only on IT processes. Only the AI3 IT process discussed how to generate and maintain the IT infrastructure. AI4 IT process discussed how to enable and use the IT infrastructure, and the last is the DS4 IT process that discussed how to ensure sustainable services. A questionnaire, an interview with employees of KOMINFO Bantul, and documentation were utilized to collect data. Data processing results were used to determine the maturity level of information technology governance at KOMINFO Bantul. After knowing the maturity level of the IT processes, then it was analyzed to measure the alignment between the TKTI current condition with the TKTI condition equipped with the COBIT framework.
Emerging Concept of Tech-Business-Analytics an Intersection of IoT & Data Analytics and its Applications on Predictive Business Decisions

This study examines the emerging fields of data analytics and decision prediction using data collected across different systems using Internet of Things technology. The Internet of Things(IoT) is a collection of inter related computing devices, mechanical and digital machines, objects,animals, or people that are provided with unique identifiers and the ability to transmit data acrossa network without needing human-to-human or human-to-computer interaction. A specified aimof predicting the future, along with the explanation of the problem using another high-tech systemand model should be used to process the enormous and continuous data produced. The possibilityof realizing (design and development) such systems for so-called Tech-Business-Analytics for different real-world applications of predictive business decisions has been addressed in this paper
중국 대학 한국어 학습자의 모바일러닝 활용 현황 및 인식에 대한 조사 연구

The purpose of this study is to investigate the status quo and perceptions of mobile learning of Korean language learners at Chinese universities. The subjects of this study were students who had studied Korean at Chinese universities, with a total of 151 students surveyed. The questionnaire consisted of 30 items mainly about the status quo of mobile learning use and the perception of mobile learning.The results were as follows. The Korean language learners at Chinese universities used published Korean textbooks(70.9%) the most, most of them had a smartphone(83.4%), and almost all of them had mobile learning in their dormitory(94.7%) on campus. The most used the method for mobile learning was real-time streaming content(70.2%), the most used skills in the learning field by using mobile devices was listening(61.6%) and vocabulary(61.6%), and the foremost reason for the use of mobile learning was mobility and ubiquity(78.8%). The erceptions of mobile learning were generally positive(M=5.87). The Perceptions of ‘system accessibility (M=6.05)’ and ‘ease of use(M=6.13)’ were relatively higher than ‘usefulness (M=5.50)’ and ‘intention to use(M=5.78)’. Based on the results of this study, actual data on mobile learning by Korean learners at Chinese universities were provided. (BNU-HKBU United International College)
Pengaruh Dimensi-Dimensi Dalam Gone Theory dan Religiusitas Terhadap Academic Fraud

One important sector in the development of each country is education. In the process of education sometimes the purpose of education becomes less effective. Moral fragility and the low level of personality or self-control of individual students and from outside the individual is one of the causes of fraud. This study aims to determine whether there is an influence between Gone Theory (greed, opportunity, need, disclosure), and Religiosity towards Academic Cheating on accounting students. The population in this study were accounting students at the Muhammadiyah University of Surakarta and Sebelas Maret University. The sample in this study was 90 respondents. The sampling technique in this study is Convenience Sampling. This type of research is quantitative research. The data collection method uses a questionnaire. The analytical method used is descriptive analysis, data quality testing, classical assumption test, and hypothesis testing. The data obtained in the form of answers from respondents, tabulated and processed through SPSS software version 21. The standard of significance used for this study was 5%. The results showed that the variables influencing academic fraud were opportunity and religiosity with values of 0.048 and 0,000. While the variables of greed, needs, and disclosure do not affect academic fraud.Keywords: Gone theory, Religiosity, and Academic Fraud
LINGUISTIC AMBIGUITIES IN VERBAL JOKES IN BULGARIAN AND ENGLISH

Joking and laughing are essential human traits in everyday communication. Each culture has their own humourous traditions and subjects of laughter. A common trigger of laughter is the linguistic ambiguities in verbal humour. The linguistic ambiguity is one of the mechanisms of turning a text into a humourous one. Ambiguities occur when more than one meaning of an utterance arises. This makes the Linguistic ambiguities work as a switching mechanism for shifting from one semantic script into another which can have an unexpected and/or humourous effect. Comparative linguo-cultural analysis of short humourous texts in both English and Bulgarian languages reveals which are the most common types of linguistic ambiguities used in verbal jokes and, which are the most preferred genres of jokes containing linguistic ambiguities. Comparative analysis on the jokes mechanisms can shed light on the cultural differences in verbal humour practices and linguistic traditions. The types of linguistic ambiguities in verbal jokes reveal cultural preferences encoded in linguistic features
The Limitation and Aim of Pastoral Counseling in Korean Church

This research explores the identity of pastoral counseling. The main concern of pastoral counseling has been related with counselors who have psychological backgrounds and have trained as specialists although many of them are pastors. This study asks a question of how pastoral counseling goes along in church. It points out that pastoral counseling seriously has to concern church and pastors.<BR> This article divides into four sections. Firstly, it deals with the identity of pastoral counseling. Scholars discern pastoral counseling from pastoral care. It is said that pastoral counseling is a more professional area while pastoral care is regarded as the ordinary caring of pastors. Whatever the classification is, pastoral counseling should differ from ordinary counseling and recover its identity. Furthermore, it argues that pastoral counseling should develop theories and skills for ordinary pastors.<BR> In the second section, it points out the limitation of theological education and pastoral counseling in contemporary Korean church. Contemporary pastoral counseling and ordinary counseling are alike. The counseling of pastors in church has not developed theoretical backgrounds and skills. Pastoral counseling includes religious elements and spiritual areas.<BR> In the next part, it claims that pastoral counseling includes Christian spirituality. Pastoral counseling should include the recovery of spiritual aspects, which is different from the purpose of the ordinary counseling. It also compares pastoral counseling with spiritual direction. In a sense, pastoral counseling must partly be the spiritual direction in that pastors should take care of the spiritual life of lay christians.<BR> Lastly, it will delineate the religious resources of church and the necessity of manual, which can be used for pastoral counseling. Pastoral counseling can use religious resources such as the Bible, prayer, church community, pastoral visiting and so on. It argues that pastoral counseling needs to make manuals for pastors in church. This research contributes to showing the developmental possibility of pastoral counseling that can be used in church.
GrammarTagger: A Multilingual, Minimally-Supervised Grammar Profiler for Language Education

We present GrammarTagger, an open-source grammar profiler which, given an input text, identifies grammatical features useful for language education. The model architecture enables it to learn from a small amount of texts annotated with spans and their labels, which 1) enables easier and more intuitive annotation, 2) supports overlapping spans, and 3) is less prone to error propagation, compared to complex hand-crafted rules defined on constituency/dependency parses. We show that we can bootstrap a grammar profiler model with $F_1 \approx 0.6$ from only a couple hundred sentences both in English and Chinese, which can be further boosted via learning a multilingual model. With GrammarTagger, we also build Octanove Learn, a search engine of language learning materials indexed by their reading difficulty and grammatical features. The code and pretrained models are publicly available at \url{https://github.com/octanove/grammartagger}.
Quantum sensing to suppress systematic errors with measurements in the Zeno regime

Quantum magnetic field sensing is an important technology for material science and biology. Although experimental imperfections affect the sensitivity, repetitions of the measurements decrease the estimation uncertainty by a square root of the total number of the measurements if there are only statistical errors. However, it is difficult to precisely characterize the coherence time of the system because it fluctuates in time in realistic conditions, which induces systematic errors. In this case, due to residual bias of the measured values, estimation uncertainty cannot be lowered than a finite value even in the limit of the infinite number of measurements. On the basis of the fact that the decoherence dynamics in the so-called Zeno regime are not significant compared to other regimes, we propose a novel but very simple protocol to use measurements in the Zeno regime for reducing systematic errors. Our scheme allows the estimation uncertainty $\delta ^2 \omega$ to scale as $L^{1/4}$ where $L$ denotes the number of the measurements even when we cannot precisely characterize the coherence time.
Malaria around large dams in Africa: effect of environmental and transmission endemicity factors

Background: The impact of large dams on malaria has received widespread attention. However, understanding how dam topography and transmission endemicity influence malaria incidences is limited. > Methods: Data from the European Commissionâ€™s Joint Research Center and Shuttle Radar Topography Mission were used to determine reservoir perimeters and shoreline slope of African dams. Georeferenced data from the Malaria Atlas Project (MAP) were used to estimate malaria incidence rates in communities near reservoir shorelines. Population data from the WorldPop database were used to estimate the population at risk of malaria around dams in stable and unstable areas. > Results: The data showed that people living near ( Conclusion: Gentler, more gradual shoreline slopes were associated with much greater malaria risk. Dam-related environmental variables such as dam topography and shoreline slopes are an important factor that should be considered in efforts to predict and control malaria around dams.
Birth and Death Processes with Emigration Related to First Order Gaussian Autoregressive Sequences

Let $$g_{1}, g_{2}, \ldots $$ be a sequence of independent identically distributed standard normal random variables and $$\{x_{n}\}$$ a sequence of positive numbers.
Pemodelan Dan Prediksi Conducted Pemodelan Dan Prediksi Conducted Emission Menggunakan Machine Learning Dengan Algoritma Support Vector Machine (SVM): Pemodelan Dan Prediksi Conducted Emission Menggunakan Machine Learning Dengan Algoritma Support Vector Machine (SVM)

Electronic devices used can produce unwanted emissions, both radiated and conducted. Some techniques that have been used to reduce emissions include filters, shielding, switching modification, and converter design. One way to find out these emissions is to predict emissions that have excess can reduce development costs and time. In this study the prediction of EMI conducted emission power level generated by the LED driver uses several periodic modulating signals (sine signals, triangular signals, and box signals) and non periodic modulating signals (noise signals) with frequencies from 150 KHz - 30MHz and amplitude 0 - 1.2 V. Characteristics and EMI conducted emission obtained is used as training data in machine learning. Using machine learning can find out how accurately the EMI conducted emission power level is predicted by the SVM algorithm (Support Vector Machine). Machine learning will display the results of a comparison between training data and testing data to determine theaccuracy of the EMI power level conducted emission generated by the LED driver. From the data the prediction results are obtained, where the SVM (Support Vector Machine) algorithm results in accuracy obtained on periodic signals (sine signals have an average of 97.257%, triangle signals have an average of 95.262%, and box signals have an average of 92,02%) and non periodic signals (signal noise has an average of 91.022%).
Half-Real Half-Fake Distillation for Class-Incremental Semantic Segmentation

Despite their success for semantic segmentation, convolutional neural networks are ill-equipped for incremental learning, \ie, adapting the original segmentation model as new classes are available but the initial training data is not retained. Actually, they are vulnerable to catastrophic forgetting problem. We try to address this issue by "inverting" the trained segmentation network to synthesize input images starting from random noise. To avoid setting detailed pixel-wise segmentation maps as the supervision manually, we propose the SegInversion to synthesize images using the image-level labels. To increase the diversity of synthetic images, the Scale-Aware Aggregation module is integrated into SegInversion for controlling the scale (the number of pixels) of synthetic objects. Along with real images of new classes, the synthesized images will be fed into the distillation-based framework to train the new segmentation model which retains the information about previously learned classes, whilst updating the current model to learn the new ones. The proposed method significantly outperforms other incremental learning methods and obtains state-of-the-art performance on the PASCAL VOC 2012 and ADE20K datasets. The code and models will be made publicly available.
PLANNING AND BEGINNING A UNIVERSITY COURSE IN A GLOBAL PANDEMIC: THE CASE OF AGRICULTURAL ENGINEERING AT THE UNIVERSITY OF LA LAGUNA (CANARY ISLANDS, SPAIN)

Information about the paper titled "PLANNING AND BEGINNING A UNIVERSITY COURSE IN A GLOBAL PANDEMIC: THE CASE OF AGRICULTURAL ENGINEERING AT THE UNIVERSITY OF LA LAGUNA (CANARY ISLANDS, SPAIN)" at IATED Digital Library
Multilingual Cyberbullying Detection System

As the use of social media has evolved in recent times, so has the ability to cyberbully victims using it. The last decade has witnessed a surge of cyberbullying-this bullying is not only limited to English but also happens in other languages. A large number of mobile device users are in Asian countries such as India. Such a large audience is a fertile ground for cyberbullies -hence, it is very important to detect cyberbullying in multiple languages. Most of the current approaches to identify cyberbullying are focused on English text, and a very few approaches are venturing into other languages. This paper proposes a Multilingual Cyberbullying Detection System for detection of cyberbullying in two Indian languages- Hindi and Marathi. We have developed a prototype that operates across data sets created for these two languages. Using this prototype, we have carried out experiments to detect cyberbullying in these two languages. The results of our experiments show an accuracy up-to 97% and Fl-score up-to 96% on many datasets for both the languages.