Reviewerly/exHarmony huggingface dataset:
Review and Assessment of Performance of Genomic Inference Methods based on the Sequentially Markovian Coalescent

Many methods based on the Sequentially Markovian Coalescent (SMC) have been and are being developed. These methods make use of genome sequence data to uncover population demographic history. More recently, new methods have extended the original theoretical framework, allowing the simultaneous estimation of the demographic history and other biological variables. These methods can be applied to many different species, under different model assumptions, in hopes of unlocking the population/species evolutionary history. Although convergence proofs in particular cases have been given using simulated data, a clear outline of the performance limits of these methods is lacking. We here explore the limits of this methodology, as well as present a tool that can be used to help users quantify what information can be confidently retrieved from given datasets. In addition, we study the consequences for inference accuracy violating the hypotheses and the assumptions of SMC approaches, such as the presence of transposable elements, variable recombination and mutation rates along the sequence and SNP call errors. We also provide a new interpretation of the SMC through the use of the estimated transition matrix and offer recommendations for the most efficient use of these methods under budget constraints, notably through the building of data sets that would be better adapted for the biological question at hand.
IMPLEMENTASI FSM SEBAGAI RESPON OTONOM DAN ADAPTIF NPC PADA GAME “AWANG MENJELAJAHI KOTA TENGGARONG”

Development of the game towards a tourist promotion tool is very important. The game "Awang exploring the City of Tenggarong" is an android smartphone game that tells the story of a tourist / traveler named Awang who roams every tourist destination in the Tenggarong City. The development of this game uses multimedia development life cycle, starting from the concept, assembly, and testing. Artificial intelligence is also needed in the development of this game. Players will be accompanied by NPC (Non Player Character) in the form of a female tour guide. NPCs equipped with the Finite State Machine (FSM) model can guide players to go to each Tenggarong tourist attraction, and it can also provide information related to these tourist attractions. The final result of this research is a game that can be a media for tourism promotion in Tenggarong city
Movie Recommendation System

Recommendation systems have become an important role in today's digital world.During the last few decades, with the rise of YouTube, Amazon, Netflix and many other such web services, recommender systems have taken more and more place in our lives.From e-commerce (suggest to buyers' articles that could interest them) to online advertisement (suggest to users the right contents, matching their preferences), recommender systems are today unavoidable in our daily online journeys.Users get more data related to them using these systems.Here, we are developing a recommendation system to suggest movies to users.
Container Image Management Using Google Container Registry

In this chapter, you will get started with Google Container Registry (GCR) and learn the following:
Analisa Usability Website Akademi Komunitas Negeri Pacitan Menggunakan Metode Heuristic Evaluation

The development of information technology today provides many changes to human life, one of which is the website. The website of the university in particular can help the wider community, especially students, in obtaining information. Akademi Komunitas Negeri (AKN) Pacitan is one of the many colleges that utilize information technology in the form of websites. To find out whether the website created has made it easy for users, it is necessary to analyze the usability of the website. This study will analyze the level of usability on the AKN Pacitan website with the Heuristic Evaluation method. The variables used in this study are five usability variables of the ten variables in the Heuristic Evaluation method, including visibility of system status, the match between system and the real world, consistency and standards, flexibility and efficiency of use, and aesthetic and minimalist design. The population of this research is students, lecturers, and AKN Pacitan staff, using probability sampling, simple random sampling, and proportionate stratified random sampling as data collection techniques. The research data was taken using a questionnaire and analyzed using descriptive analysis methods. From the results of the subsequent questionnaire, the analysis will produce several recommendations for improvement and further development of the AKN Pacitan website to improve the functionality of the website itself.
Consistency-Check Edge Refinement for Deep Stereo Matching

Recent end-to-end CNN-based stereo matching algorithms obtain disparities through regression from a cost volume, which is formed by concatenating the features of stereo pairs. Some downsampling steps are often embedded in constructing cost volume for global information aggregation and computational efficiency. However, many edge details are hard to recover due to the imprudent upsampling process and ambiguous boundary predictions. To tackle this problem without training another edge prediction sub-network, we developed a novel tightly-coupled edge refinement pipeline composed of two modules. The first module implements a gentle upsampling process by a cascaded cost volume filtering method, aggregating global information without losing many details. On this basis, the second module concentrates on generating a disparity residual map for boundary pixels by sub-pixel disparity consistency check, to further recover the edge details. The experimental results on public datasets demonstrate the effectiveness of the proposed method.
MANAJEMEN E-LEARNING MAHASISWA FAKULTAS TARBIYAH DAN KEGURUAN UIN IMAM BONJOL PADANG SELAMA MASA PANDEMI COVID-19

This research was conducted because E-learning was carried out in an impromptu manner without being planned from the principles of the faculty. Various responses from lecturers and students emerged. Therefore, research is needed to find out about online college management at the Tarbiyah and Kezuruan Faculty, Imam Bonjol University, Padang. The method used in this research is qualitative dereript. The technique used to collect data is in-depth interviews and document study. While the data source is the vice dean of the academic field, the elder/study program secretary and the designer. Haril's research shows that E-learning is carried out to replace conventional lectures to look up covid-19, carried out on a predetermined schedule using whatsapp, zoom, e-mail, google classroom, closed facebook groups. E-learning conducted in the form of faalitated E-learning The lecturer always received direction from the leadership. The obstacle is that students have difficulty in obtaining a network. For monitoring, each lecturer must report the E-learning that is carried out and there are some lecturers who report online lectures but are directly reprimanded by the leadership.
The necessity of cultural education: Current state and prospects

The article explores the reasons for the crisis of cultural studies and the possibilities of overcoming this crisis in the context of the emerging post-industrial society. In particular, it is emphasized that the so-called perestroika and the first post-perestroika decade became the “golden age” in the development of cultural studies. It is suggested that the need for worldview-based disciplines that form a person’s need for a holistic, systemic vision of phenomena and processes arises in periods characterized by irrationality and transition. When culture approves the idea of order, attempts to generalize and synthesize ideas about the world are replaced by a narrow trend which exaggerates the role of scientific and technological progress to the detriment of humanization of society and culture. This is the dangerous trend we are facing now. Therefore, the profession of a culturologist has lost its profile in public consciousness. Meanwhile, the experience of the 20th century shows that a narrow, limited, positivist consciousness of people can lead to global catastrophes. It is suggested that in the foreseeable future the attitude towards cultural science may change due to the formation of a post-industrial society, in which the breadth and heuristic of judgments, the ability to think strategically and build a dialogue between different spheres as well as developing awareness of the specifics of culture will be of value. All these abilities may now be found in people who have a cultural education. It is argued that educational, linguistic, sightseeing, hotel, museum, library and other fields may benefit from hiring a cultural expert. The hope is expressed that with the transition to the post-industrial phase, the attitude towards the humanities and cultural studies in particular will inevitably change for the better.
Genre Based Approach An Alternative in Teaching Comparison and Contrast Essay

Writing as one of the productive skills is offered as a required course in many English language program at many universities. However, research showed that teaching writing skill faced some challenges. Therefore, this article offered an approach that shed the light. The article discussed a description of what a comparison and contrast essay in general, the definition of Genre Based Approach in teaching writing and the application of GBA in teaching comparison and contrast essay. The article serve as a reference for teachers in teaching comparison and contrast essay for academic writing and other purposes.
NETWORKING OF UNIVERSITIES IN THE REGIONAL EDUCATIONAL SPACE

In accordance with the Federal law “On education in the Russian Federation” currently in force in Russia and a number of program concepts and documents, recognize an innovative form of cooperation of educational organizations as “network interaction” as promising in terms of improving the efficiency and competitiveness of the Russian national educational system in the global training space. Despite the fact that the development of network forms of interaction is actively carried out both on the basis of individual universities and in the regions, today this practice is clearly not enough for a theoretical understanding of the phenomenon of network interaction in educational practice. The purpose of this work is to consider the concept of network interaction in relation to the field of education and determine the prospects for its development in the regional framework.
Cryptography in Banking Sector

The development of cryptographic techniques has seen a lot of applications in the banking industry. In this blog we see some of the major cryptographic techniques which has been used extensively in the banking industry, for the implementation of data security norms and the fulfillment of compliance requirements.
Multi-task Batch Reinforcement Learning with Metric Learning

We tackle the Multi-task Batch Reinforcement Learning problem. Given multiple datasets collected from different tasks, we train a multi-task policy to perform well in unseen tasks sampled from the same distribution. The task identities of the unseen tasks are not provided. To perform well, the policy must infer the task identity from collected transitions by modelling its dependency on states, actions and rewards. Because the different datasets may have state-action distributions with large divergence, the task inference module can learn to ignore the rewards and spuriously correlate only state-action pairs to the task identity, leading to poor test time performance. To robustify task inference, we propose a novel application of the triplet loss. To mine hard negative examples, we relabel the transitions from the training tasks by approximating their reward functions. When we allow further training on the unseen tasks, using the trained policy as an initialization leads to significantly faster convergence compared to randomly initialized policies (up to 80% improvement and across 5 different Mujoco task distributions). We name our method MBML (Multi-task Batch RL with Metric Learning).
Language-Conditioned Feature Pyramids for Visual Selection Tasks

Referring expression comprehension, which is the ability to locate language to an object in an image, plays an important role in creating common ground.Many models that fuse visual and linguistic features have been proposed.However, few models consider the fusion of linguistic features with multiple visual features with different sizes of receptive fields, though the proper size of the receptive field of visual features intuitively varies depending on expressions.In this paper, we introduce a neural network architecture that modulates visual features with varying sizes of receptive field by linguistic features.We evaluate our architecture on tasks related to referring expression comprehension in two visual dialogue games.The results show the advantages and broad applicability of our architecture.
Complete Analysis of Doctor Signature in Medical Recording Form Siti Rahmah Hospital in 2018 Using C4.5 Algorithm

The development of science and technology and the medical world today is very rapid, especially in the field of Information Technology and health, in the health sector by using the Knime application program and C 4.5 algorithm to provide accurate and precise information to decision makers in determining the completeness of the doctor's signature, because the sign the doctor's hand is very important especially for the patient in taking responsibility for the work the doctor has done to the patient and to the hospital where the doctor is devoting his knowledge. Because in carrying out a doctor's actions towards his patient if there is no doctor's signature in his handler, and the patient has a disability due to a doctor's mistake, then the doctor cannot be prosecuted legally because of the completeness of information on the health care data. Knime Program is able to provide answers and solutions in the process of data access, data transformation, initial investigation, visualization to report making to the hospital and can provide fast and accurate information to decision makers, both patients, hospitals and other party. From the results obtained in this study of 110 patients treated after screening and cleaning data obtained 69 patient data, where doctors who did not sign the patient data were 35 people or 50.7% were being signed as many as 34 people or 49 , 3%
Who is to Blame? Runtime Verification of Distributed Objects with Active Monitors

Since distributed software systems are ubiquitous, their correct functioning is crucially important.Static verification is possible in principle, but requires high expertise and effort which is not feasible in many eco-systems.Runtime verification can serve as a lean alternative, where monitoring mechanisms are automatically generated from property specifications, to check compliance at runtime.This paper contributes a practical solution for powerful and flexible runtime verification of distributed, object-oriented applications, via a combination of the runtime verification tool LARVA and the active object framework PROACTIVE.Even if LARVA supports in itself only the generation of local, sequential monitors, we empower LARVA for distributed monitoring by connecting monitors with active objects, turning them into active, communicating monitors.We discuss how this allows for a variety of monitoring architectures.Further, we show how property specifications, and thereby the generated monitors, provide a model that splits the blame between the local object and its environment.While LARVA itself focuses on monitoring of control-oriented properties, we use the LARVA front-end STARVOORS to also capture data-oriented (pre/post) properties in the distributed monitoring.We demonstrate this approach to distributed runtime verification with a case study, a distributed key/value store.
GNSS Data Processing through the Wavelet Transform

The present work shows an approach to signal processing through the wavelet transform received by positioning equipment, which are transmitted by GNNS constellation satellites.In these techniques of GNSS geopositioning, there are no applications of the wavelet transform, due to the absence of experts in the field or in its absence by complication, for this reason we undertake the task of carrying out this processing with this transform on gps satellite reception data.Situation that allows to establish an approximation to the calculation of speed of displacement in a particular zone.Having as main input a series of data very robust in time over 24 months.
IMPROVEMENT OF STUDENT LEARNING RESULTS USING MACROMEDIA FLASH APPLICATION IN THE THEME OF MY COUNTRY CLASS IV SD SWASTA RK BINTANG TIMUR RANTAUPRAPAT

This research aims to improve learning outcomes by using the Macromedia flash application on the theme of my country kayanta in Sd Swasta Rk Bintang Timur Rantau Prapat in the academic year 2019/2020. This type of research is Classroom Action Research. The subjects of this research were grade IV students, totaly 30 students consisting of 17 male students and 13 female students. This research was conducted in two cycles, each cycle having two meetings. Data on the results of this study were obtained from student learning outcomes tests and observations. Based on the research results obtained indicate an increase in student learning outcomes on the theme of the richness of my country by using the Macromedia flash application. This can be seen from the improvement in student learning outcomes each cycle. In the initial test (pre-test) student learning outcomes conducted before the application of learning there are 7 students (23%) completed learning while 23 students (77%) have not been completed with an average grade of 57.33 In cycle 1 completeness student learning outcomes are 13 students (43%) completed in 17 students (57%) not yet finished with an average grade of 73.00. In the second cycle of student learning outcomes completeness there are 24 students (80%) complete while 6 students (20%) have not finished with an average grade of 83.00. The results of the observation of the first cycle teachers amounted to 64% with enough categories while student observations by 62% with enough categories. The observation results of the second cycle teachers experienced an increase of 82% with a very good category while student observation by 84% with a good category. By looking at the percentage of learning outcomes and observations it can be concluded that using the macromedia flash application can improve student learning outcomes.Keywords: Learning Outcomes, macromedia flash application, observation.
How mobile safety apps can streamline <scp>COVID</scp>‐19 response and management

The COVID‐19 pandemic has forced campus safety administrators and first responders to adapt existing tools to a continually changing public health reality. Mobile technology is proving to be especially useful in keeping campus communities safe and informed. Today, few leave home without their mobile device, making mobile applications a powerfully effective way to quickly share information.
A Study on The Efficiency of Using 5e Learning Model in Social Studies Teaching

Learning models can be effective in enabling learners to be active throughout the educational process and in achieving meaningful learning.Within these models, the 5E learning model, which was developed based on constructivist learning approach, offers a variety of possibilities for both learners and tutorials.This study aims to determine the effect of using 5E learning model in Social Studies on academic achievement of students and the opinions of students regarding this model.The study has conducted in a secondary school in Adıyaman city center in 2019-2020 school year.In determination of academic achievement grades of the students, achievement test formed by the researcher has been used.On the other hand, in determination of the students' opinions regarding 5E learning model, open-ended questionnaire formed by the researcher has been used.Parallel mixed-methods study design has been used in the study in which the data collected by means of qualitative and quantitative methods are evaluated together.In the quantitative aspect of the study, out of the experimental models "pretest-posttest control group" model has been used.In the qualitative aspect of the study, however, opinions of the students in regard to 5E learning model are collected with open-ended questionnaire.Quantitative data are collected with descriptive statistics and repeated measures ANOVA while qualitative data with content analysis.The findings obtained at the end of the study indicate that 5E learning model affects the academic achievement of the students positively and the students have positive opinions regarding this model.
Automatic detection of rare observations during production tests using statistical models

Engines are verified through production tests before delivering them to customers. During those tests, lot of measures are taken on different parts of the engine, considering multiple physical parameters. Unexpected measures can be observed. For this very reason, it is important to assess if these unusual observations are statistically significant.&#x0D; However, anomaly detection is a difficult problem in unsupervised learning. The obvious reason is that, unlike supervised classification, there is no ground truth against which we could evaluate results. Therefore, we propose a methodology based on two independent statistical algorithms to double check our results. One approach is the Isolation Forest (IF) model which is specific to anomaly detection and able to handle a large number of variables. The goal of the algorithm is to find rare items, events or observations which raise suspicions by differing significantly from the majority of the data and, at the same time, it discriminates non-informative variables to improve. One main issue of IF is its lack of interpretability. Within this scope, we extend the shapley values, interpretation indicators, to the unsupervised context to interpret the model outputs.&#x0D; The second approach is the Self-Organizing Map (SOM) model which has nice properties for data mining by providing both clustering and visual representation. The performance of the method and its interpretability depends on the chosen subset of variables. In this respect, we first implement a sparse-weighted K-means to reduce the input space, allowing the SOM to give an interpretable discretized representation.&#x0D; We apply the two methodologies on data on aircraft engines measurements. Both approaches show similar results which are easily interpretable and exploitable by the experts.
MQT-TZ: Secure MQTT Broker for Biomedical Signal Processing on the Edge.

Physical health records belong to healthcare providers, but the information contained within belongs to each patient. In an increasing manner, more health-related data is being acquired by wearables and other IoT devices following the ever-increasing trend of the Quantified Self. Even though data protection regulations (e.g., GDPR) encourage the usage of privacy-preserving processing techniques, most of the current IoT infrastructure was not originally conceived for such purposes. One of the most used communication protocols, MQTT, is a lightweight publish-subscribe protocol commonly used in the Edge and IoT applications. In MQTT, the broker must process data on clear text, hence exposing a large attack surface for a malicious agent to steal/tamper with this health-related data. In this paper, we introduce MQT-TZ, a secure MQTT broker leveraging Arm TRUSTZONE, a popular Trusted Execution Environment (TEE). We define a mutual TLS-based handshake and a two-layer encryption for end-to-end security using the TEE as a trusted proxy. We provide quantitative evaluation of our open-source PoC on streaming ECGs in real time and highlight the trade-offs.